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Feng X, Tao J, Wang Y, Long AY, He LJ, Zhang N. [Clinicopathological and molecular characteristics of angiomatoid fibrous histiocytoma in children]. Zhonghua Bing Li Xue Za Zhi 2024; 53:483-485. [PMID: 38678331 DOI: 10.3760/cma.j.cn112151-20231026-00316] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 04/29/2024]
MESH Headings
- Humans
- Female
- Child
- Male
- Child, Preschool
- Histiocytoma, Malignant Fibrous/pathology
- Histiocytoma, Malignant Fibrous/metabolism
- Histiocytoma, Malignant Fibrous/genetics
- Histiocytoma, Malignant Fibrous/diagnosis
- Histiocytoma, Malignant Fibrous/surgery
- Actins/metabolism
- RNA-Binding Protein EWS/genetics
- RNA-Binding Protein EWS/metabolism
- 12E7 Antigen/metabolism
- In Situ Hybridization, Fluorescence
- Anaplastic Lymphoma Kinase/genetics
- Anaplastic Lymphoma Kinase/metabolism
- Soft Tissue Neoplasms/pathology
- Soft Tissue Neoplasms/genetics
- Soft Tissue Neoplasms/metabolism
- Soft Tissue Neoplasms/surgery
- Antigens, CD/metabolism
- Oncogene Proteins, Fusion/genetics
- Oncogene Proteins, Fusion/metabolism
- Cell Adhesion Molecules/metabolism
- Cell Adhesion Molecules/genetics
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Affiliation(s)
- X Feng
- Department of Pathology, Children's Hospital Affiliated to Zhengzhou University, Henan Children's Hospital Zhengzhou Children's Hospital, Zhengzhou 450018, China
| | - J Tao
- Department of Pathology, Children's Hospital Affiliated to Zhengzhou University, Henan Children's Hospital Zhengzhou Children's Hospital, Zhengzhou 450018, China
| | - Y Wang
- Department of Pathology, Children's Hospital Affiliated to Zhengzhou University, Henan Children's Hospital Zhengzhou Children's Hospital, Zhengzhou 450018, China
| | - A Y Long
- Department of Pathology, Children's Hospital Affiliated to Zhengzhou University, Henan Children's Hospital Zhengzhou Children's Hospital, Zhengzhou 450018, China
| | - L J He
- Department of Pathology, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health, Beijing 100045, China
| | - N Zhang
- Department of Pathology, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health, Beijing 100045, China
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Zhang M, Liu SB, Zhang N, Xiao LY, Li WJ, Wang WF, Xu MZ, Hu JG, Li J, Zuo LG, Zhang XF, Geng ZJ, Wang L, Wang YY, Song X. [Application of improved "Swiss roll" method in mouse intestinal tissue section]. Zhonghua Bing Li Xue Za Zhi 2024; 53:393-397. [PMID: 38556826 DOI: 10.3760/cma.j.cn112151-20231016-00270] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 04/02/2024]
Affiliation(s)
- M Zhang
- Department of Central Laboratory, the First Affiliated Hospital of Bengbu Medical University, Bengbu 233004, China School of Laboratory Medicine, Bengbu Medical University, Bengbu 233000, China
| | - S B Liu
- School of Laboratory Medicine, Bengbu Medical University, Bengbu 233000, China
| | - N Zhang
- School of Laboratory Medicine, Bengbu Medical University, Bengbu 233000, China
| | - L Y Xiao
- School of Laboratory Medicine, Bengbu Medical University, Bengbu 233000, China
| | - W J Li
- Anhui Province Key Laboratory of Basic and Translational Research of Inflammation-Related Diseases, the First Affiliated Hospital of Bengbu Medical University, Bengbu 233004, China
| | - W F Wang
- Anhui Province Key Laboratory of Basic and Translational Research of Inflammation-Related Diseases, the First Affiliated Hospital of Bengbu Medical University, Bengbu 233004, China
| | - M Z Xu
- Anhui Province Key Laboratory of Basic and Translational Research of Inflammation-Related Diseases, the First Affiliated Hospital of Bengbu Medical University, Bengbu 233004, China
| | - J G Hu
- Anhui Province Key Laboratory of Basic and Translational Research of Inflammation-Related Diseases, the First Affiliated Hospital of Bengbu Medical University, Bengbu 233004, China Department of Clinical Laboratory, the First Affiliated Hospital of Bengbu Medical University, Bengbu 233004, China
| | - J Li
- Anhui Province Key Laboratory of Basic and Translational Research of Inflammation-Related Diseases, the First Affiliated Hospital of Bengbu Medical University, Bengbu 233004, China Department of Clinical Laboratory, the First Affiliated Hospital of Bengbu Medical University, Bengbu 233004, China
| | - L G Zuo
- Anhui Province Key Laboratory of Basic and Translational Research of Inflammation-Related Diseases, the First Affiliated Hospital of Bengbu Medical University, Bengbu 233004, China Department of Gastrointestinal Surgery, the First Affiliated Hospital of Bengbu Medical University, Bengbu 233004, China
| | - X F Zhang
- Department of Central Laboratory, the First Affiliated Hospital of Bengbu Medical University, Bengbu 233004, China Anhui Province Key Laboratory of Basic and Translational Research of Inflammation-Related Diseases, the First Affiliated Hospital of Bengbu Medical University, Bengbu 233004, China
| | - Z J Geng
- Department of Central Laboratory, the First Affiliated Hospital of Bengbu Medical University, Bengbu 233004, China Anhui Province Key Laboratory of Basic and Translational Research of Inflammation-Related Diseases, the First Affiliated Hospital of Bengbu Medical University, Bengbu 233004, China
| | - L Wang
- Anhui Province Key Laboratory of Basic and Translational Research of Inflammation-Related Diseases, the First Affiliated Hospital of Bengbu Medical University, Bengbu 233004, China Department of Gastrointestinal Surgery, the First Affiliated Hospital of Bengbu Medical University, Bengbu 233004, China
| | - Y Y Wang
- Anhui Province Key Laboratory of Basic and Translational Research of Inflammation-Related Diseases, the First Affiliated Hospital of Bengbu Medical University, Bengbu 233004, China Department of Clinical Laboratory, the First Affiliated Hospital of Bengbu Medical University, Bengbu 233004, China
| | - X Song
- Department of Central Laboratory, the First Affiliated Hospital of Bengbu Medical University, Bengbu 233004, China Anhui Province Key Laboratory of Basic and Translational Research of Inflammation-Related Diseases, the First Affiliated Hospital of Bengbu Medical University, Bengbu 233004, China
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Chan DC, Kim C, Kang RY, Kuhn MK, Beidler LM, Zhang N, Proctor EA. Cytokine expression patterns predict suppression of vulnerable neural circuits in a mouse model of Alzheimer's disease. bioRxiv 2024:2024.03.17.585383. [PMID: 38559177 PMCID: PMC10979954 DOI: 10.1101/2024.03.17.585383] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 04/04/2024]
Abstract
Alzheimer's disease is a neurodegenerative disorder characterized by progressive amyloid plaque accumulation, tau tangle formation, neuroimmune dysregulation, synapse an neuron loss, and changes in neural circuit activation that lead to cognitive decline and dementia. Early molecular and cellular disease-instigating events occur 20 or more years prior to presentation of symptoms, making them difficult to study, and for many years amyloid-β, the aggregating peptide seeding amyloid plaques, was thought to be the toxic factor responsible for cognitive deficit. However, strategies targeting amyloid-β aggregation and deposition have largely failed to produce safe and effective therapies, and amyloid plaque levels poorly correlate with cognitive outcomes. However, a role still exists for amyloid-β in the variation in an individual's immune response to early, soluble forms of aggregates, and the downstream consequences of this immune response for aberrant cellular behaviors and creation of a detrimental tissue environment that harms neuron health and causes changes in neural circuit activation. Here, we perform functional magnetic resonance imaging of awake, unanesthetized Alzheimer's disease mice to map changes in functional connectivity over the course of disease progression, in comparison to wild-type littermates. In these same individual animals, we spatiotemporally profile the immune milieu by measuring cytokines, chemokines, and growth factors across various brain regions and over the course of disease progression from pre-pathology through established cognitive deficit. We identify specific signatures of immune activation predicting hyperactivity followed by suppression of intra- and then inter-regional functional connectivity in multiple disease-relevant brain regions, following the pattern of spread of amyloid pathology.
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Affiliation(s)
- Dennis C Chan
- Department of Neurosurgery, Penn State College of Medicine, Hershey, PA, USA
- Department of Pharmacology, Penn State College of Medicine, Hershey, PA, USA
- Department of Biomedical Engineering, Pennsylvania State University, University Park, PA, USA
- Center for Neural Engineering, Pennsylvania State University, University Park, PA, USA
- Center for Neurotechnology in Mental Health Research, Pennsylvania State University, University Park, PA, USA
| | - ChaeMin Kim
- Department of Neurosurgery, Penn State College of Medicine, Hershey, PA, USA
- Department of Pharmacology, Penn State College of Medicine, Hershey, PA, USA
| | - Rachel Y Kang
- Department of Neurosurgery, Penn State College of Medicine, Hershey, PA, USA
- Department of Pharmacology, Penn State College of Medicine, Hershey, PA, USA
| | - Madison K Kuhn
- Department of Neurosurgery, Penn State College of Medicine, Hershey, PA, USA
- Department of Pharmacology, Penn State College of Medicine, Hershey, PA, USA
- Department of Biomedical Engineering, Pennsylvania State University, University Park, PA, USA
- Center for Neural Engineering, Pennsylvania State University, University Park, PA, USA
| | - Lynne M Beidler
- Department of Neurosurgery, Penn State College of Medicine, Hershey, PA, USA
- Department of Pharmacology, Penn State College of Medicine, Hershey, PA, USA
| | - Nanyin Zhang
- Department of Biomedical Engineering, Pennsylvania State University, University Park, PA, USA
- Center for Neural Engineering, Pennsylvania State University, University Park, PA, USA
- Center for Neurotechnology in Mental Health Research, Pennsylvania State University, University Park, PA, USA
| | - Elizabeth A Proctor
- Department of Neurosurgery, Penn State College of Medicine, Hershey, PA, USA
- Department of Pharmacology, Penn State College of Medicine, Hershey, PA, USA
- Department of Biomedical Engineering, Pennsylvania State University, University Park, PA, USA
- Center for Neural Engineering, Pennsylvania State University, University Park, PA, USA
- Department of Engineering Science & Mechanics, Pennsylvania State University, University Park, PA, USA
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Li GB, Shi WK, Zhang N, Lin GL. [Anal adenocarcinoma combined with perianal Paget disease involving vulva: a case report]. Zhonghua Wei Chang Wai Ke Za Zhi 2024; 27:75-76. [PMID: 38262904 DOI: 10.3760/cma.j.cn441530-20230505-00145] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 01/25/2024]
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Tu W, Cramer SR, Zhang N. Disparity in temporal and spatial relationships between resting-state electrophysiological and fMRI signals. Res Sq 2024:rs.3.rs-3251741. [PMID: 37645880 PMCID: PMC10462190 DOI: 10.21203/rs.3.rs-3251741/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/31/2023]
Abstract
Resting-state brain networks (RSNs) have been widely applied in health and disease, but their interpretation in terms of the underlying neural activity is unclear. To systematically investigate this cornerstone issue, here we simultaneously recorded whole-brain resting-state functional magnetic resonance imaging (rsfMRI) and electrophysiology signals in two separate brain regions in rats. Our data show that for both recording sites, band-specific local field potential (LFP) power-derived spatial maps can explain up to 90% of the spatial variance of RSNs obtained by the rsfMRI signal. Paradoxically, the time series of LFP band power can only explain up to 35% of the temporal variance of the local rsfMRI time course from the same site. In addition, regressing out time series of LFP power from rsfMRI signals has limited impact on the spatial patterns of rsfMRI-based RSNs. This disparity in the spatial and temporal relationships between resting-state electrophysiology and rsfMRI signals suggest that the electrophysiological activity alone does not account for all effects in the rsfMRI signal. To further interpret this disparity, we propose a model hypothesizing that a significant component in the rsfMRI signal is driven by electrophysiology-invisible neural activities that are active in neurovascular coupling. Temporally, this electrophysiology-invisible signal is weakly correlated to electrophysiology data. However, as signaling of these two types of neural activities are both constrained by the same anatomical backbone, they can generate similar RSN spatial patterns. These data and the model provide a new perspective of our interpretation of RSNs.
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Affiliation(s)
- Wenyu Tu
- The Neuroscience Graduate Program, The Huck Institutes of the Life Sciences, Pennsylvania State University, University Park, USA
| | - Samuel R. Cramer
- The Neuroscience Graduate Program, The Huck Institutes of the Life Sciences, Pennsylvania State University, University Park, USA
| | - Nanyin Zhang
- The Neuroscience Graduate Program, The Huck Institutes of the Life Sciences, Pennsylvania State University, University Park, USA
- Department of Biomedical Engineering, Pennsylvania State University, University Park, USA
- Center for Neural Engineering, Pennsylvania State University, University Park, USA
- Center for Neurotechnology in Mental Health Research, Pennsylvania State University, University Park, USA
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Hou X, Tian F, Guo L, Yu Y, Hu Y, Chen S, Wang M, Yang Z, Wang J, Fan X, Xing L, Wu S, Zhang N. Remnant cholesterol is associated with hip BMD and low bone mass in young and middle-aged men: a cross-sectional study. J Endocrinol Invest 2024:10.1007/s40618-023-02279-x. [PMID: 38183565 DOI: 10.1007/s40618-023-02279-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/02/2023] [Accepted: 12/08/2023] [Indexed: 01/08/2024]
Abstract
PURPOSE Remnant cholesterol (RC) is a contributor to cardiovascular diseases, obesity, diabetes, and metabolic syndrome. However, the specific relationship between RC and bone metabolism remains unexplored. Therefore, we aimed to investigate the relationships of RC with hip bone mineral density (BMD) and the risk of low bone mass. METHODS Physical examination data was collected from men aged < 60 years as part of the Kailuan Study between 2014 and 2018. The characteristics of the participants were compared between RC quartile groups. A generalized linear regression model was used to evaluate the relationship between RC and hip BMD and a logistic regression model was used to calculate odds ratios (ORs) and 95% confidence intervals (CIs) for low bone mass. Additional analyses were performed after stratification by body mass index (BMI) (≥ or < 24 kg/m2). Sensitivity analyses were performed by excluding individuals who were taking lipid-lowering therapy or had cancer, cardiovascular diseases, or diabetes. RESULTS Data from a total of 7,053 participants were included in the analysis. After adjustment for confounding factors, RC negatively correlated with hip BMD (β = - 0.0079, 95% CI: - 0.0133, - 0.0025). The risk of low bone mass increased from the lowest to the highest RC quartile, with ORs of 1 (reference), 1.09 (95% CI: (0.82, 1.44), 1.35 (95%CI: 1.02, 1.77), and 1.43 (95% CI: 1.09, 1.89) for Q1, Q2, Q3, and Q4, respectively (P for trend = 0.004) in the fully adjusted model. Compared to RC < 0.80 mmol/l group, the risk of low bone mass increased 39% in RC ≥ 0.80 mmol/l group (P < 0.001). The correlation between RC and hip BMD was stronger in participants with BMI ≥ 24 kg/m2 group (β = - 0.0159, 95% CI: - 0.0289, - 0.0029). The results of sensitivity analyses were consistent with the main results. CONCLUSION We have identified a negative correlation between serum RC and hip BMD, and a higher RC concentration was found to be associated with a greater risk of low bone mass in young and middle-aged men.
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Affiliation(s)
- X Hou
- School of Public Health, North China University of Science and Technology, Tangshan, People's Republic of China
| | - F Tian
- School of Public Health, North China University of Science and Technology, Tangshan, People's Republic of China
| | - L Guo
- School of Public Health, North China University of Science and Technology, Tangshan, People's Republic of China
| | - Y Yu
- School of Public Health, North China University of Science and Technology, Tangshan, People's Republic of China
| | - Y Hu
- School of Public Health, North China University of Science and Technology, Tangshan, People's Republic of China
| | - S Chen
- Kailuan General Hospital, Tangshan, People's Republic of China
| | - M Wang
- Beijing Jishuitan Hospital, Capital Medical University, Beijing, People's Republic of China
| | - Z Yang
- School of Public Health, North China University of Science and Technology, Tangshan, People's Republic of China
| | - J Wang
- School of Public Health, North China University of Science and Technology, Tangshan, People's Republic of China
| | - X Fan
- Kailuan General Hospital, Tangshan, People's Republic of China
| | - L Xing
- School of Public Health, North China University of Science and Technology, Tangshan, People's Republic of China
- Affiliated Hospital of North China University of Science and Technology, Tangshan, People's Republic of China
| | - S Wu
- Kailuan General Hospital, Tangshan, People's Republic of China.
| | - N Zhang
- Kailuan General Hospital, Tangshan, People's Republic of China.
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Zhang N, Fard M, Xu J, Davy JL, Robinson SR. Road safety: The influence of vibration frequency on driver drowsiness, reaction time, and driving performance. Appl Ergon 2024; 114:104148. [PMID: 37813019 DOI: 10.1016/j.apergo.2023.104148] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/04/2023] [Revised: 09/05/2023] [Accepted: 10/04/2023] [Indexed: 10/11/2023]
Abstract
Driver drowsiness is a factor in at least 20% of serious motor vehicle accidents. Although research has shown that Whole-Body Vibration (WBV) can induce drowsiness in drivers, it is unknown whether particular frequencies are more problematic. The present study systematically investigated the influence of WBV frequency on driver drowsiness. Fifteen participants each undertook six 1-h sessions of simulated driving while being subjected to WBV of either 0 Hz (no vibration), 1-4 Hz, 4-8 Hz, 8-16 Hz, 16-32 Hz or 32-64 Hz. Subjective sleepiness, as measured by the Karolinska Sleepiness Scale (KSS), confirmed that drivers felt drowsier when exposed to the two lowest frequency ranges (1-4 Hz and 4-8 Hz). Reaction time, which measures attention and alertness, was significantly impaired by the two lowest frequency ranges. Objective driving performance measures (Standard Deviation of Lane Position (SDLP), Standard Deviation of (SD) Steering Angle, Time in Unsafe Zone) also showed significant degradation due to exposure to the two lowest frequency ranges. Exposure to 1-4 Hz or 4-8 Hz vibration caused attention to become significantly impaired within 15-20 min and driving performance to be significantly impaired by 30-35 min. The other frequency ranges had little or no effect. These findings point to a need to develop equivalent vibration-induced drowsiness contours that can be adopted as transportation safety standards.
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Affiliation(s)
- N Zhang
- School of Engineering, RMIT University, Australia.
| | - M Fard
- School of Engineering, RMIT University, Australia
| | - J Xu
- School of Engineering, RMIT University, Australia
| | - J L Davy
- School of Science, RMIT University, Australia; Infrastructure Technologies, CSIRO, Australia
| | - S R Robinson
- School of Health and Biomedical Sciences. RMIT University, Australia; Institute for Breathing and Sleep, Austin Health, Heidelberg, Australia
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Staplin N, Haynes R, Judge PK, Wanner C, Green JB, Emberson J, Preiss D, Mayne KJ, Ng SYA, Sammons E, Zhu D, Hill M, Stevens W, Wallendszus K, Brenner S, Cheung AK, Liu ZH, Li J, Hooi LS, Liu WJ, Kadowaki T, Nangaku M, Levin A, Cherney D, Maggioni AP, Pontremoli R, Deo R, Goto S, Rossello X, Tuttle KR, Steubl D, Petrini M, Seidi S, Landray MJ, Baigent C, Herrington WG, Abat S, Abd Rahman R, Abdul Cader R, Abdul Hafidz MI, Abdul Wahab MZ, Abdullah NK, Abdul-Samad T, Abe M, Abraham N, Acheampong S, Achiri P, Acosta JA, Adeleke A, Adell V, Adewuyi-Dalton R, Adnan N, Africano A, Agharazii M, Aguilar F, Aguilera A, Ahmad M, Ahmad MK, Ahmad NA, Ahmad NH, Ahmad NI, Ahmad Miswan N, Ahmad Rosdi H, Ahmed I, Ahmed S, Ahmed S, Aiello J, Aitken A, AitSadi R, Aker S, Akimoto S, Akinfolarin A, Akram S, Alberici F, Albert C, Aldrich L, Alegata M, Alexander L, Alfaress S, Alhadj Ali M, Ali A, Ali A, Alicic R, Aliu A, Almaraz R, Almasarwah R, Almeida J, Aloisi A, Al-Rabadi L, Alscher D, Alvarez P, Al-Zeer B, Amat M, Ambrose C, Ammar H, An Y, Andriaccio L, Ansu K, Apostolidi A, Arai N, Araki H, Araki S, Arbi A, Arechiga O, Armstrong S, Arnold T, Aronoff S, Arriaga W, Arroyo J, Arteaga D, Asahara S, Asai A, Asai N, Asano S, Asawa M, Asmee MF, Aucella F, Augustin M, Avery A, Awad A, Awang IY, Awazawa M, Axler A, Ayub W, Azhari Z, Baccaro R, Badin C, Bagwell B, Bahlmann-Kroll E, Bahtar AZ, Baigent C, Bains D, Bajaj H, Baker R, Baldini E, Banas B, Banerjee D, Banno S, Bansal S, Barberi S, Barnes S, Barnini C, Barot C, Barrett K, Barrios R, Bartolomei Mecatti B, Barton I, Barton J, Basily W, Bavanandan S, Baxter A, Becker L, Beddhu S, Beige J, Beigh S, Bell S, Benck U, Beneat A, Bennett A, Bennett D, Benyon S, Berdeprado J, Bergler T, Bergner A, Berry M, Bevilacqua M, Bhairoo J, Bhandari S, Bhandary N, Bhatt A, Bhattarai M, Bhavsar M, Bian W, Bianchini F, Bianco S, Bilous R, Bilton J, Bilucaglia D, Bird C, Birudaraju D, Biscoveanu M, Blake C, Bleakley N, Bocchicchia K, Bodine S, Bodington R, Boedecker S, Bolduc M, Bolton S, Bond C, Boreky F, Boren K, Bouchi R, Bough L, Bovan D, Bowler C, Bowman L, Brar N, Braun C, Breach A, Breitenfeldt M, Brenner S, Brettschneider B, Brewer A, Brewer G, Brindle V, Brioni E, Brown C, Brown H, Brown L, Brown R, Brown S, Browne D, Bruce K, Brueckmann M, Brunskill N, Bryant M, Brzoska M, Bu Y, Buckman C, Budoff M, Bullen M, Burke A, Burnette S, Burston C, Busch M, Bushnell J, Butler S, Büttner C, Byrne C, Caamano A, Cadorna J, Cafiero C, Cagle M, Cai J, Calabrese K, Calvi C, Camilleri B, Camp S, Campbell D, Campbell R, Cao H, Capelli I, Caple M, Caplin B, Cardone A, Carle J, Carnall V, Caroppo M, Carr S, Carraro G, Carson M, Casares P, Castillo C, Castro C, Caudill B, Cejka V, Ceseri M, Cham L, Chamberlain A, Chambers J, Chan CBT, Chan JYM, Chan YC, Chang E, Chang E, Chant T, Chavagnon T, Chellamuthu P, Chen F, Chen J, Chen P, Chen TM, Chen Y, Chen Y, Cheng C, Cheng H, Cheng MC, Cherney D, Cheung AK, Ching CH, Chitalia N, Choksi R, Chukwu C, Chung K, Cianciolo G, Cipressa L, Clark S, Clarke H, Clarke R, Clarke S, Cleveland B, Cole E, Coles H, Condurache L, Connor A, Convery K, Cooper A, Cooper N, Cooper Z, Cooperman L, Cosgrove L, Coutts P, Cowley A, Craik R, Cui G, Cummins T, Dahl N, Dai H, Dajani L, D'Amelio A, Damian E, Damianik K, Danel L, Daniels C, Daniels T, Darbeau S, Darius H, Dasgupta T, Davies J, Davies L, Davis A, Davis J, Davis L, Dayanandan R, Dayi S, Dayrell R, De Nicola L, Debnath S, Deeb W, Degenhardt S, DeGoursey K, Delaney M, Deo R, DeRaad R, Derebail V, Dev D, Devaux M, Dhall P, Dhillon G, Dienes J, Dobre M, Doctolero E, Dodds V, Domingo D, Donaldson D, Donaldson P, Donhauser C, Donley V, Dorestin S, Dorey S, Doulton T, Draganova D, Draxlbauer K, Driver F, Du H, Dube F, Duck T, Dugal T, Dugas J, Dukka H, Dumann H, Durham W, Dursch M, Dykas R, Easow R, Eckrich E, Eden G, Edmerson E, Edwards H, Ee LW, Eguchi J, Ehrl Y, Eichstadt K, Eid W, Eilerman B, Ejima Y, Eldon H, Ellam T, Elliott L, Ellison R, Emberson J, Epp R, Er A, Espino-Obrero M, Estcourt S, Estienne L, Evans G, Evans J, Evans S, Fabbri G, Fajardo-Moser M, Falcone C, Fani F, Faria-Shayler P, Farnia F, Farrugia D, Fechter M, Fellowes D, Feng F, Fernandez J, Ferraro P, Field A, Fikry S, Finch J, Finn H, Fioretto P, Fish R, Fleischer A, Fleming-Brown D, Fletcher L, Flora R, Foellinger C, Foligno N, Forest S, Forghani Z, Forsyth K, Fottrell-Gould D, Fox P, Frankel A, Fraser D, Frazier R, Frederick K, Freking N, French H, Froment A, Fuchs B, Fuessl L, Fujii H, Fujimoto A, Fujita A, Fujita K, Fujita Y, Fukagawa M, Fukao Y, Fukasawa A, Fuller T, Funayama T, Fung E, Furukawa M, Furukawa Y, Furusho M, Gabel S, Gaidu J, Gaiser S, Gallo K, Galloway C, Gambaro G, Gan CC, Gangemi C, Gao M, Garcia K, Garcia M, Garofalo C, Garrity M, Garza A, Gasko S, Gavrila M, Gebeyehu B, Geddes A, Gentile G, George A, George J, Gesualdo L, Ghalli F, Ghanem A, Ghate T, Ghavampour S, Ghazi A, Gherman A, Giebeln-Hudnell U, Gill B, Gillham S, Girakossyan I, Girndt M, Giuffrida A, Glenwright M, Glider T, Gloria R, Glowski D, Goh BL, Goh CB, Gohda T, Goldenberg R, Goldfaden R, Goldsmith C, Golson B, Gonce V, Gong Q, Goodenough B, Goodwin N, Goonasekera M, Gordon A, Gordon J, Gore A, Goto H, Goto S, Goto S, Gowen D, Grace A, Graham J, Grandaliano G, Gray M, Green JB, Greene T, Greenwood G, Grewal B, Grifa R, Griffin D, Griffin S, Grimmer P, Grobovaite E, Grotjahn S, Guerini A, Guest C, Gunda S, Guo B, Guo Q, Haack S, Haase M, Haaser K, Habuki K, Hadley A, Hagan S, Hagge S, Haller H, Ham S, Hamal S, Hamamoto Y, Hamano N, Hamm M, Hanburry A, Haneda M, Hanf C, Hanif W, Hansen J, Hanson L, Hantel S, Haraguchi T, Harding E, Harding T, Hardy C, Hartner C, Harun Z, Harvill L, Hasan A, Hase H, Hasegawa F, Hasegawa T, Hashimoto A, Hashimoto C, Hashimoto M, Hashimoto S, Haskett S, Hauske SJ, Hawfield A, Hayami T, Hayashi M, Hayashi S, Haynes R, Hazara A, Healy C, Hecktman J, Heine G, Henderson H, Henschel R, Hepditch A, Herfurth K, 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Yamagata K, Yamaguchi M, Yamaji Y, Yamamoto A, Yamamoto S, Yamamoto S, Yamamoto T, Yamanaka A, Yamano T, Yamanouchi Y, Yamasaki N, Yamasaki Y, Yamasaki Y, Yamashita C, Yamauchi T, Yan Q, Yanagisawa E, Yang F, Yang L, Yano S, Yao S, Yao Y, Yarlagadda S, Yasuda Y, Yiu V, Yokoyama T, Yoshida S, Yoshidome E, Yoshikawa H, Young A, Young T, Yousif V, Yu H, Yu Y, Yuasa K, Yusof N, Zalunardo N, Zander B, Zani R, Zappulo F, Zayed M, Zemann B, Zettergren P, Zhang H, Zhang L, Zhang L, Zhang N, Zhang X, Zhao J, Zhao L, Zhao S, Zhao Z, Zhong H, Zhou N, Zhou S, Zhu D, Zhu L, Zhu S, Zietz M, Zippo M, Zirino F, Zulkipli FH. Effects of empagliflozin on progression of chronic kidney disease: a prespecified secondary analysis from the empa-kidney trial. Lancet Diabetes Endocrinol 2024; 12:39-50. [PMID: 38061371 PMCID: PMC7615591 DOI: 10.1016/s2213-8587(23)00321-2] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/05/2023] [Revised: 10/24/2023] [Accepted: 10/25/2023] [Indexed: 12/23/2023]
Abstract
BACKGROUND Sodium-glucose co-transporter-2 (SGLT2) inhibitors reduce progression of chronic kidney disease and the risk of cardiovascular morbidity and mortality in a wide range of patients. However, their effects on kidney disease progression in some patients with chronic kidney disease are unclear because few clinical kidney outcomes occurred among such patients in the completed trials. In particular, some guidelines stratify their level of recommendation about who should be treated with SGLT2 inhibitors based on diabetes status and albuminuria. We aimed to assess the effects of empagliflozin on progression of chronic kidney disease both overall and among specific types of participants in the EMPA-KIDNEY trial. METHODS EMPA-KIDNEY, a randomised, controlled, phase 3 trial, was conducted at 241 centres in eight countries (Canada, China, Germany, Italy, Japan, Malaysia, the UK, and the USA), and included individuals aged 18 years or older with an estimated glomerular filtration rate (eGFR) of 20 to less than 45 mL/min per 1·73 m2, or with an eGFR of 45 to less than 90 mL/min per 1·73 m2 with a urinary albumin-to-creatinine ratio (uACR) of 200 mg/g or higher. We explored the effects of 10 mg oral empagliflozin once daily versus placebo on the annualised rate of change in estimated glomerular filtration rate (eGFR slope), a tertiary outcome. We studied the acute slope (from randomisation to 2 months) and chronic slope (from 2 months onwards) separately, using shared parameter models to estimate the latter. Analyses were done in all randomly assigned participants by intention to treat. EMPA-KIDNEY is registered at ClinicalTrials.gov, NCT03594110. FINDINGS Between May 15, 2019, and April 16, 2021, 6609 participants were randomly assigned and then followed up for a median of 2·0 years (IQR 1·5-2·4). Prespecified subgroups of eGFR included 2282 (34·5%) participants with an eGFR of less than 30 mL/min per 1·73 m2, 2928 (44·3%) with an eGFR of 30 to less than 45 mL/min per 1·73 m2, and 1399 (21·2%) with an eGFR 45 mL/min per 1·73 m2 or higher. Prespecified subgroups of uACR included 1328 (20·1%) with a uACR of less than 30 mg/g, 1864 (28·2%) with a uACR of 30 to 300 mg/g, and 3417 (51·7%) with a uACR of more than 300 mg/g. Overall, allocation to empagliflozin caused an acute 2·12 mL/min per 1·73 m2 (95% CI 1·83-2·41) reduction in eGFR, equivalent to a 6% (5-6) dip in the first 2 months. After this, it halved the chronic slope from -2·75 to -1·37 mL/min per 1·73 m2 per year (relative difference 50%, 95% CI 42-58). The absolute and relative benefits of empagliflozin on the magnitude of the chronic slope varied significantly depending on diabetes status and baseline levels of eGFR and uACR. In particular, the absolute difference in chronic slopes was lower in patients with lower baseline uACR, but because this group progressed more slowly than those with higher uACR, this translated to a larger relative difference in chronic slopes in this group (86% [36-136] reduction in the chronic slope among those with baseline uACR <30 mg/g compared with a 29% [19-38] reduction for those with baseline uACR ≥2000 mg/g; ptrend<0·0001). INTERPRETATION Empagliflozin slowed the rate of progression of chronic kidney disease among all types of participant in the EMPA-KIDNEY trial, including those with little albuminuria. Albuminuria alone should not be used to determine whether to treat with an SGLT2 inhibitor. FUNDING Boehringer Ingelheim and Eli Lilly.
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Hou XL, Liu JY, Fan XH, Zhang N, Cao GL, Guo ZB, Zhang YY, Yu YH, Tian YQ, Sun XX, Tian FM. Correction to: Secular trends of incidence and hospitalization cost of hip fracture in Tangshan, China. Osteoporos Int 2024; 35:201. [PMID: 38032495 DOI: 10.1007/s00198-023-06987-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/01/2023]
Affiliation(s)
- X-L Hou
- School of Public Health, North China University of Science and Technology, Bohai Road 21, Caofeidian Dis, Tangshan, 063210, People's Republic of China
| | - J-Y Liu
- The Second Hospital of Tangshan City, Tangshan, People's Republic of China
| | - X-H Fan
- Kailuan General Hospital, Tangshan, People's Republic of China
| | - N Zhang
- Kailuan General Hospital, Tangshan, People's Republic of China
| | - G-L Cao
- Gongren Hospital, Tangshan, People's Republic of China
| | - Z-B Guo
- Kailuan General Hospital, Tangshan, People's Republic of China
| | - Y-Y Zhang
- School of Public Health, North China University of Science and Technology, Bohai Road 21, Caofeidian Dis, Tangshan, 063210, People's Republic of China
| | - Y-H Yu
- School of Public Health, North China University of Science and Technology, Bohai Road 21, Caofeidian Dis, Tangshan, 063210, People's Republic of China
| | - Y-Q Tian
- School of Public Health, North China University of Science and Technology, Bohai Road 21, Caofeidian Dis, Tangshan, 063210, People's Republic of China
| | - X-X Sun
- Department of Orthopedic Surgery, Affiliated Hospital of North China University of Science and Technology, Jianshe South Road 73, Tangshan, 063000, People's Republic of China.
| | - F-M Tian
- School of Public Health, North China University of Science and Technology, Bohai Road 21, Caofeidian Dis, Tangshan, 063210, People's Republic of China.
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Impact of primary kidney disease on the effects of empagliflozin in patients with chronic kidney disease: secondary analyses of the EMPA-KIDNEY trial. Lancet Diabetes Endocrinol 2024; 12:51-60. [PMID: 38061372 DOI: 10.1016/s2213-8587(23)00322-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/05/2023] [Revised: 10/24/2023] [Accepted: 10/25/2023] [Indexed: 12/23/2023]
Abstract
BACKGROUND The EMPA-KIDNEY trial showed that empagliflozin reduced the risk of the primary composite outcome of kidney disease progression or cardiovascular death in patients with chronic kidney disease mainly through slowing progression. We aimed to assess how effects of empagliflozin might differ by primary kidney disease across its broad population. METHODS EMPA-KIDNEY, a randomised, controlled, phase 3 trial, was conducted at 241 centres in eight countries (Canada, China, Germany, Italy, Japan, Malaysia, the UK, and the USA). Patients were eligible if their estimated glomerular filtration rate (eGFR) was 20 to less than 45 mL/min per 1·73 m2, or 45 to less than 90 mL/min per 1·73 m2 with a urinary albumin-to-creatinine ratio (uACR) of 200 mg/g or higher at screening. They were randomly assigned (1:1) to 10 mg oral empagliflozin once daily or matching placebo. Effects on kidney disease progression (defined as a sustained ≥40% eGFR decline from randomisation, end-stage kidney disease, a sustained eGFR below 10 mL/min per 1·73 m2, or death from kidney failure) were assessed using prespecified Cox models, and eGFR slope analyses used shared parameter models. Subgroup comparisons were performed by including relevant interaction terms in models. EMPA-KIDNEY is registered with ClinicalTrials.gov, NCT03594110. FINDINGS Between May 15, 2019, and April 16, 2021, 6609 participants were randomly assigned and followed up for a median of 2·0 years (IQR 1·5-2·4). Prespecified subgroupings by primary kidney disease included 2057 (31·1%) participants with diabetic kidney disease, 1669 (25·3%) with glomerular disease, 1445 (21·9%) with hypertensive or renovascular disease, and 1438 (21·8%) with other or unknown causes. Kidney disease progression occurred in 384 (11·6%) of 3304 patients in the empagliflozin group and 504 (15·2%) of 3305 patients in the placebo group (hazard ratio 0·71 [95% CI 0·62-0·81]), with no evidence that the relative effect size varied significantly by primary kidney disease (pheterogeneity=0·62). The between-group difference in chronic eGFR slopes (ie, from 2 months to final follow-up) was 1·37 mL/min per 1·73 m2 per year (95% CI 1·16-1·59), representing a 50% (42-58) reduction in the rate of chronic eGFR decline. This relative effect of empagliflozin on chronic eGFR slope was similar in analyses by different primary kidney diseases, including in explorations by type of glomerular disease and diabetes (p values for heterogeneity all >0·1). INTERPRETATION In a broad range of patients with chronic kidney disease at risk of progression, including a wide range of non-diabetic causes of chronic kidney disease, empagliflozin reduced risk of kidney disease progression. Relative effect sizes were broadly similar irrespective of the cause of primary kidney disease, suggesting that SGLT2 inhibitors should be part of a standard of care to minimise risk of kidney failure in chronic kidney disease. FUNDING Boehringer Ingelheim, Eli Lilly, and UK Medical Research Council.
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Yang F, Zhang N, Ou GY, Xu SW. Integrated Bioinformatic Analysis and Validation Identifies Immune Microenvironment-Related Potential Biomarkers in Alzheimer's Disease. J Prev Alzheimers Dis 2024; 11:495-506. [PMID: 38374756 DOI: 10.14283/jpad.2024.5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/21/2024]
Abstract
BACKGROUND Alzheimer's disease (AD) is one of the most common neurodegenerative diseases, accompanied by cognitive and memory impairment, accounting for about 60% - 80% of dementia types. The pathogenesis of AD has not been clarified, and there is no effective therapy to prevent or treat AD. In this study, we aimed to identify the potential biomarkers involved in the brain immune microenvironment in AD. METHODS AD datasets from GEO database were obtained to identify the differentially expressed disease-related genes (DEDRGs) in AD through weighted gene co-expression network analysis (WGCNA) and differential expression analysis. Functional Enrichment analysis was performed to explore the potential biological function of DEDRGs. The hub DEDRGs were identified through the protein-protein interaction (PPI) network. Furthermore, the CIBERSORT algorithm was employed to bulk gene expression profiles of AD to depict the immune microenvironment characteristics in AD. Pearson's correlation analysis was utilized to depict the correlation between each of immune cells and hub DEDRGs. RESULTS A total of 27 DEDRGs were identified through WGCNA and differential expression analysis. Functional enrichment analysis of 27 DEDRGs indicated that chemokine signaling pathway was the most significantly enriched KEGG pathway, response to biotic stimulus was the most significantly enriched GO term, and most of DEDRGs were enriched into urinary system cancer in DO analysis. 6 hub DEDRGs, ANGPT1, CCL2, CD44, CXCR4, GJA1 and VCAM1, were screened through PPI network and all of them were up-regulated in AD. Immune infiltration analysis revealed that there were higher infiltration levels of T cells CD4 memory activated, T cells gamma delta, NK cells resting and macrophages M0, and lower infiltration level of NK cell activated in AD, and macrophages M2 owned the highest positively association with VCAM1 and CXCR4, but VCAM1 was statistically and negatively correlated to T cells CD8. CONCLUSION Our study identified 6 hub DEDRGs, ANGPT1, CCL2, CD44, CXCR4, GJA1 and VCAM1, were statistically associated with immune infiltrating cells, and were significantly related to the pathological development of AD, which may provide a theoretical basis for developing potential biomarkers and implementing effective therapies against AD.
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Affiliation(s)
- F Yang
- Shu-wen Xu, Department of Geriatric Neurology, Guangdong Provincial Geriatrics Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, 106 Zhongshan 2nd Road, Guangzhou 510080, China. ; Tel: +86 135 030 161 78; +86-20 -8382-7812
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12
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Yang GG, Wang CJ, Liu ZY, He PJ, Wang D, Ji CH, Yuan YM, Xiao SM, Zhang N, Ying T. [Epidemiological investigation of constipation in urban areas of Hangzhou, China]. Zhonghua Wei Chang Wai Ke Za Zhi 2023; 26:1147-1153. [PMID: 38110276 DOI: 10.3760/cma.j.cn441530-20230811-00046] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Subscribe] [Scholar Register] [Indexed: 12/20/2023]
Abstract
Objective: To determine the prevalence and risk factors of constipation in Hangzhou urban areas by analyzing data from a recent epidemiological survey. Methods: From August 2022 to June 2023, a cross-sectional survey was conducted on 43 communities on eight streets in suburbs of Hangzhou, including Wangjiang, Sijiqing, Puyan, Changhe, Ziyang, Xiaoshanchengxiang, Zhuantang, and Banshan. Written questionnaires were filled out face to face by community doctors. The prevalence of constipation was investigated using a combination of the Bristol stool typing method and the Rome IV criteria. The risk factors for constipation were analyzed using multivariate logistic regression analysis. Results: The study cohort comprised 10,479 participants, 5551 of whom were male (53.0%) and 4928 female (47.0%). The overall prevalence of constipation was 10.6% (1107/10,479). The prevalence was 11.0% (613/5551) for male and 10.0% (494/4928) for female participants; this difference is not statistically significant (P>0.05).There were no significant differences in the prevalence of constipation between different categories of body mass index (P>0.05). The prevalence of constipation was highest in individuals aged 70 years and above, accounting for 15.4% (264/1717) of all cases. There were significant differences in the prevalence of constipation between different occupations, marital statuses, and educational levels (P<0.001). Patients with hypertension or diabetes mellitus had a higher prevalence of constipation than those without these conditions, those who had been taking long-term medication had a higher prevalence of constipation than those who did not, parents of children with constipation had a higher prevalence of constipation than those with children who did not have constipation, and there were other significant differences in various variables (P<0.001). Multivariate logistic regression analysis of modifiable factors revealed that eating less fruit (OR=1.284, 95%CI: 1.061-1.553, P=0.010), liking spicy and salty food (OR=1.234, 95%CI: 1.039-1.466, P=0.016), sleeping for too long (OR=1.644, 95%CI: 1.260-2.144, P<0.001), irregular sleep patterns (OR=1.370, 95%CI: 1.127-1.665, P=0.002) and minimal exercise (OR=1.388, 95% CI: 1.168-1.649, P<0.001) were all risk factors for constipation; whereas mix diets (OR=0.709,95%CI:0.608-0.826, P<0.001), meat diets (OR=0.604,95%CI: 0.495-0.736, P<0.001), moderate alcohol consumption (OR=0.659, 95% CI: 0.534-0.812, P<0.001), less or no drinking (OR=0.523, 95% CI: 0.428-0.638, P<0.001), and non-smoking (OR=0.819, 95%CI:0.674-0.995, P<0.001) protected against constipation. We found no association between dietary preferences and the risk of constipation (refined grains: OR=1.147, 95%CI:0.944-1.393, P=0.167; no specific preference: OR=0.935, 95%CI:0.783-1.117, P=0.459). The rate of agreement between self-evaluation of constipation by the respondents and objective criteria was higher for negatives (95.8%) than for positives (38.0%). Conclusion: The prevalence of constipation is relatively high in the urban population of Hangzhou. A good lifestyle and diet can significantly reduce its incidence. There should be more emphasis on preventive education, promotion of prevention of constipation, and advocacy for a healthy lifestyle.
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Affiliation(s)
- G G Yang
- Department of Anal-Colorectal Surgery, Hangzhou Third People's Hospital, Hangzhou 310009, China
| | - C J Wang
- Department of Anal-Colorectal Surgery, Hangzhou Third People's Hospital, Hangzhou 310009, China
| | - Z Y Liu
- Department of Anal-Colorectal Surgery, Hangzhou Third People's Hospital, Hangzhou 310009, China
| | - P J He
- School of Public Health, Zhejiang Chinese Medical University, Hangzhou 310053, China
| | - D Wang
- Department of Anal-Colorectal Surgery, Hangzhou Third People's Hospital, Hangzhou 310009, China
| | - C H Ji
- School of Public Health, Zhejiang Chinese Medical University, Hangzhou 310053, China
| | - Y M Yuan
- Department of Anal-Colorectal Surgery, Hangzhou Third People's Hospital, Hangzhou 310009, China
| | - S M Xiao
- Department of Anal-Colorectal Surgery, Hangzhou Third People's Hospital, Hangzhou 310009, China
| | - N Zhang
- Department of Anal-Colorectal Surgery, Hangzhou Third People's Hospital, Hangzhou 310009, China
| | - T Ying
- Department of Anal-Colorectal Surgery, Hangzhou Third People's Hospital, Hangzhou 310009, China
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Kamens HM, Cramer S, Hanley RN, Chase S, Wickenheisser A, Horton WJ, Zhang N. Neuroimaging of opioid exposure: a review of preclinical animal models to inform addiction research. Psychopharmacology (Berl) 2023; 240:2459-2482. [PMID: 37857897 DOI: 10.1007/s00213-023-06477-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/25/2023] [Accepted: 10/01/2023] [Indexed: 10/21/2023]
Abstract
Opioid use results in thousands of overdose deaths each year. To address this crisis, we need a better understanding of the neurobiological mechanisms that drive opioid abuse. The noninvasive imaging tools positron emission tomography (PET), functional magnetic resonance imaging (fMRI), and manganese-enhanced magnetic resonance imaging (MEMRI) can be used to identify how brain activity responds to acute opioid exposure and adapts to chronic drug treatment. These techniques can be performed in humans and animal models, and brain networks identified in animals closely map to the human brain. Animal models have the advantage of being able to systematically examine the independent effects of opioid exposure in a controlled environment accounting for the complex factors that drive opioid misuse in humans. This review synthesizes literature that utilized noninvasive neuroimaging tools (PET, fMRI, and MEMRI) measuring brain activity correlates in animals to understand the neurobiological consequences of exposure to abused opioids. A PubMed search in September 2023 identified 25 publications. These manuscripts were divided into 4 categories based on the route and duration of drug exposure (acute/chronic, active/passive administration). Within each category, the results were generally consistent across drug and imaging protocols. These papers cover a 20-year range and highlight the advancements in neuroimaging methodology during that time. These advances have enabled researchers to achieve greater resolution of brain regions altered by opioid exposure and to identify patterns of brain activation across regions (i.e., functional connectivity) and within subregions of structures. After describing the existing literature, we suggest areas where additional research is needed.
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Affiliation(s)
- Helen M Kamens
- Department of Biobehavioral Health, The Pennsylvania State University, University Park, PA, 16802, USA.
| | - Samuel Cramer
- The Huck Institutes of the Life Sciences, The Pennsylvania State University, University Park, PA, 16802, USA
| | - Rachel N Hanley
- Department of Biobehavioral Health, The Pennsylvania State University, University Park, PA, 16802, USA
| | - Spencer Chase
- The Huck Institutes of the Life Sciences, The Pennsylvania State University, University Park, PA, 16802, USA
| | - Anna Wickenheisser
- Department of Biobehavioral Health, The Pennsylvania State University, University Park, PA, 16802, USA
| | - William J Horton
- Department of Biobehavioral Health, The Pennsylvania State University, University Park, PA, 16802, USA
| | - Nanyin Zhang
- Department of Biomedical Engineering, The Pennsylvania State University, University Park, PA, 16802, USA
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14
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Zhang N, Yue Q, Yang L, Song WH, Wang X, Wu SL, Liu T. [Associations between risk factor control and survival among cancer patients]. Zhonghua Yi Xue Za Zhi 2023; 103:3402-3409. [PMID: 37963738 DOI: 10.3760/cma.j.cn112137-20230905-00397] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Subscribe] [Scholar Register] [Indexed: 11/16/2023]
Abstract
Objective: This study aimed to evaluate the associations between the number of cardiovascular risk factor goals achieved with all-cause mortality, atherosclerotic cardiovascular diseases (ASCVD)-related mortality, and cancer-related mortality amongst cancer patients. Methods: From 2006 to 2020, a total of 2 079 individuals with newly diagnosed cancer, free of ASCVD, were enrolled in this study from the Kailuan cohort. Patients were classified into three groups (group 1,≤1 risk factor at goal, n=407; group 2, 2 risk factors at goal, n=865; group 3,≥3 risk factors at goal, n=807) according to the control status of blood pressure, fasting blood glucose, low-density lipoprotein cholesterol and high-sensitivity C-reactive protein, using health checkup results of the latest survey after cancer diagnosis. Multivariable Cox regression analyses were performed to examine the associations between the number of risk factors at goals with all-cause mortality, ASCVD-related mortality, and cancer-related mortality. Results: The mean age at diagnosis was (60.4±10.4) years, and 71.2% were male. During a median follow-up of 2.95 (1.38, 5.12) years, 600 cases of all-cause mortality, 63 cases of ASCVD-related mortality, and 314 cases of cancer-related mortality were observed. After adjusting for age, gender, education level, smoking status, alcohol consumption, salt intake, physical activity, body mass index, triglyceride, high-density lipoprotein cholesterol, family history of cardiovascular diseases, antihypertensive drugs, hypoglycemic drugs, lipid-lowering drugs, and anti-cancer medications, compared with cancer patients achieving ≤1 risk factor goal, those achieving ≥3 risk factor goals showed significantly decreased risk of all-cause mortality, ASCVD mortality, and cancer mortality, with HR (95%CI) of 0.68 (0.54-0.86), 0.35 (0.16-0.77), and 0.60 (0.43-0.82), respectively (all P values <0.05). Significant relationships between the number of risk factor goals achieved and decreased mortality of all kinds were observed (all P values for trend<0.05). Results of the subgroup analyses suggested that the associations between the number of risk factor goals achieved and lower mortality of all kinds were more prominent among individuals who were ≥60 years, male, and those with respiratory and reproductive cancers (all P values <0.05). Conclusions: This study suggested a significant association between the number of cardiovascular risk factor goals achieved and survival in cancer patients, especially amongst those who were older, male, with respiratory cancers and reproductive cancers.
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Affiliation(s)
- N Zhang
- Tianjin Key Laboratory of Ionic-Molecular Function of Cardiovascular Disease, Department of Cardiology, Tianjin Institute of Cardiology, Second Hospital of Tianjin Medical University, Tianjin 300211, China
| | - Q Yue
- Department of Preventive Medicine, School of Public Health, North China University of Science and Technology, Tangshan 063210, China
| | - L Yang
- Department of Preventive Medicine, School of Public Health, North China University of Science and Technology, Tangshan 063210, China
| | - W H Song
- Tianjin Key Laboratory of Ionic-Molecular Function of Cardiovascular Disease, Department of Cardiology, Tianjin Institute of Cardiology, Second Hospital of Tianjin Medical University, Tianjin 300211, China
| | - X Wang
- Tianjin Key Laboratory of Ionic-Molecular Function of Cardiovascular Disease, Department of Cardiology, Tianjin Institute of Cardiology, Second Hospital of Tianjin Medical University, Tianjin 300211, China
| | - S L Wu
- Department of Cardiology, Kailuan Hospital, North China University of Science and Technology, Tangshan 063001, China
| | - T Liu
- Tianjin Key Laboratory of Ionic-Molecular Function of Cardiovascular Disease, Department of Cardiology, Tianjin Institute of Cardiology, Second Hospital of Tianjin Medical University, Tianjin 300211, China
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15
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Zhang N, Duan YL, Zhou CJ, Jin L, Yang J, Huang S, Zhang M, Li N. [Clinical study of mature B-cell lymphoma in 11 children with chromosome 11 long-arm abnormalities]. Zhonghua Xue Ye Xue Za Zhi 2023; 44:924-929. [PMID: 38185522 PMCID: PMC10753258 DOI: 10.3760/cma.j.issn.0253-2727.2023.11.007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Subscribe] [Scholar Register] [Received: 03/30/2023] [Indexed: 01/09/2024]
Abstract
Objective: To explore the clinical, pathological, diagnostic, treatment, and prognostic features of children with mature B-cell lymphoma (MBCL) . Methods: This retrospective study included pediatric patients with MBCL with chromosome 11 long-arm abnormalities who were diagnosed and treated at our hospital from December 2018 to February 2023. Results: Among the 11 pediatric patients with MBCL, nine were male and two were female, with a median age of 9 (2-13) years and a median disease course of 1.8 (0.5-24) months. The clinical manifestations were cervical lymph node enlargement in four patients, nasal congestion and snoring in four patients, abdominal pain in two patients, and difficulty breathing in one patient. There were seven cases of Burkitt's lymphoma, two of follicular lymphoma, and two of advanced B-cell lymphoma according to the pathological morphology examination. No patients had central nervous system or bone marrow involvement, and no extensive metastasis was observed on B-ultrasound or positron emission tomography-computed tomography (PET/CT). One patient had a huge tumor lesion. The Revised International Pediatric Non-Hodgkin Lymphoma Staging System classified four patients as stage Ⅱ, five as stage Ⅲ, and two as stage Ⅳ. 11q probe detection showed five cases of 11q gain, three of 11q loss, and three of both gain and loss. FISH showed positive MYC expression in three patients, including eight with advanced B-cell lymphoma with 11q abnormalities and three with Burkitt's lymphoma with 11q abnormalities. According to the 2019 edition of the National Health Commission's diagnostic and treatment guidelines for invasive MBCL in children, one patient was classified as Group A, two as Group B, and eight as Group C. Early evaluation of the efficacy showed complete remission. After mid-term evaluation, the intensity of chemotherapy was reduced in Group B and Group C. Among two cases of chemotherapy, the remaining nine cases had a median follow-up of 32 (6-45) months, and none had event-related survival. Conclusion: The incidence of MBCL with 11q abnormalities in children is low, clinical symptoms are mild, and progression is slow. The absence of MYC, BCL2, BCL6 rearrangements, C-MYC negative and 11q abnormalities on FISH is an important diagnostic indicator, and reducing the intensity of chemotherapy can improve prognosis.
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Affiliation(s)
- N Zhang
- Medical Oncology Department, Pediatric Oncology Center, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health, Beijing Key Laboratory of Pediatric Hematology Oncology, Key Laboratory of Major Diseases in Children, Ministry of Education, Beijing 100045, China
| | - Y L Duan
- Medical Oncology Department, Pediatric Oncology Center, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health, Beijing Key Laboratory of Pediatric Hematology Oncology, Key Laboratory of Major Diseases in Children, Ministry of Education, Beijing 100045, China
| | - C J Zhou
- Medical Oncology Department, Pediatric Oncology Center, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health, Department of Pathology
| | - L Jin
- Medical Oncology Department, Pediatric Oncology Center, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health, Beijing Key Laboratory of Pediatric Hematology Oncology, Key Laboratory of Major Diseases in Children, Ministry of Education, Beijing 100045, China
| | - J Yang
- Medical Oncology Department, Pediatric Oncology Center, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health, Beijing Key Laboratory of Pediatric Hematology Oncology, Key Laboratory of Major Diseases in Children, Ministry of Education, Beijing 100045, China
| | - S Huang
- Medical Oncology Department, Pediatric Oncology Center, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health, Beijing Key Laboratory of Pediatric Hematology Oncology, Key Laboratory of Major Diseases in Children, Ministry of Education, Beijing 100045, China
| | - M Zhang
- Medical Oncology Department, Pediatric Oncology Center, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health, Beijing Key Laboratory of Pediatric Hematology Oncology, Key Laboratory of Major Diseases in Children, Ministry of Education, Beijing 100045, China
| | - N Li
- Medical Oncology Department, Pediatric Oncology Center, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health, Beijing Key Laboratory of Pediatric Hematology Oncology, Key Laboratory of Major Diseases in Children, Ministry of Education, Beijing 100045, China
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Chen H, Mirg S, Gaddale P, Agrawal S, Li M, Nguyen V, Xu T, Li Q, Liu J, Tu W, Liu X, Drew PJ, Zhang N, Gluckman BJ, Kothapalli SR. Dissecting Multiparametric Cerebral Hemodynamics using Integrated Ultrafast Ultrasound and Multispectral Photoacoustic Imaging. bioRxiv 2023:2023.11.07.566048. [PMID: 37986863 PMCID: PMC10659547 DOI: 10.1101/2023.11.07.566048] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/22/2023]
Abstract
Understanding brain-wide hemodynamic responses to different stimuli at high spatiotemporal resolutions can help study neuro-disorders and brain functions. However, the existing brain imaging technologies have limited resolution, sensitivity, imaging depth and provide information about only one or two hemodynamic parameters. To address this, we propose a multimodal functional ultrasound and photoacoustic (fUSPA) imaging platform, which integrates ultrafast ultrasound and multispectral photoacoustic imaging methods in a compact head-mountable device, to quantitatively map cerebral blood volume (CBV), cerebral blood flow (CBF), oxygen saturation (SO2) dynamics as well as contrast agent enhanced brain imaging with high spatiotemporal resolutions. After systematic characterization, the fUSPA system was applied to quantitatively study the changes in brain hemodynamics and vascular reactivity at single vessel resolution in response to hypercapnia stimulation. Our results show an overall increase in brain-wide CBV, CBF, and SO2, but regional differences in singular cortical veins and arteries and a reproducible anti-correlation pattern between venous and cortical hemodynamics, demonstrating the capabilities of the fUSPA system for providing multiparametric cerebrovascular information at high-resolution and sensitivity, that can bring insights into the complex mechanisms of neurodiseases.
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Affiliation(s)
- Haoyang Chen
- Department of Biomedical Engineering, The Pennsylvania State University, University Park, PA 16802, USA
- Center for Neural Engineering, The Pennsylvania State University, University Park, PA 16802, USA
| | - Shubham Mirg
- Department of Biomedical Engineering, The Pennsylvania State University, University Park, PA 16802, USA
- Center for Neural Engineering, The Pennsylvania State University, University Park, PA 16802, USA
| | - Prameth Gaddale
- Department of Biomedical Engineering, The Pennsylvania State University, University Park, PA 16802, USA
| | - Sumit Agrawal
- Department of Biomedical Engineering, The Pennsylvania State University, University Park, PA 16802, USA
| | - Menghan Li
- Department of Biomedical Engineering, The Pennsylvania State University, University Park, PA 16802, USA
| | - Van Nguyen
- Department of Biomedical Engineering, The Pennsylvania State University, University Park, PA 16802, USA
| | - Tianbao Xu
- Department of Biomedical Engineering, The Pennsylvania State University, University Park, PA 16802, USA
| | - Qiong Li
- Department of Biomedical Engineering, The Pennsylvania State University, University Park, PA 16802, USA
| | - Jinyun Liu
- Department of Biomedical Engineering, The Pennsylvania State University, University Park, PA 16802, USA
| | - Wenyu Tu
- Department of Biomedical Engineering, The Pennsylvania State University, University Park, PA 16802, USA
| | - Xiao Liu
- Department of Biomedical Engineering, The Pennsylvania State University, University Park, PA 16802, USA
- Institute for Computational and Data Sciences, The Pennsylvania State University, University Park, PA 16802, USA
| | - Patrick J. Drew
- Department of Biomedical Engineering, The Pennsylvania State University, University Park, PA 16802, USA
- Center for Neural Engineering, The Pennsylvania State University, University Park, PA 16802, USA
- Department of Engineering Science and Mechanics, The Pennsylvania State University, University Park, PA 16802, USA
- Department of Biology, The Pennsylvania State University, University Park, PA 16802, USA
- Department of Neurosurgery, The Pennsylvania State University, University Park, PA 16802, USA
| | - Nanyin Zhang
- Department of Biomedical Engineering, The Pennsylvania State University, University Park, PA 16802, USA
- Center for Neural Engineering, The Pennsylvania State University, University Park, PA 16802, USA
| | - Bruce J. Gluckman
- Department of Biomedical Engineering, The Pennsylvania State University, University Park, PA 16802, USA
- Center for Neural Engineering, The Pennsylvania State University, University Park, PA 16802, USA
- Department of Engineering Science and Mechanics, The Pennsylvania State University, University Park, PA 16802, USA
- Department of Neurosurgery, The Pennsylvania State University, University Park, PA 16802, USA
| | - Sri-Rajasekhar Kothapalli
- Department of Biomedical Engineering, The Pennsylvania State University, University Park, PA 16802, USA
- Center for Neural Engineering, The Pennsylvania State University, University Park, PA 16802, USA
- Penn State Cancer Institute, The Pennsylvania State University, Hershey, PA 17033, USA
- Graduate Program in Acoustics, The Pennsylvania State University, University Park, PA 16802, USA
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Xu ZQ, Xu ZH, Zhang N. Comprehensive systematic review and meta-analysis on anticoagulants and aspirin for stroke prevention in non-valvular atrial fibrillation patients. Eur Rev Med Pharmacol Sci 2023; 27:11002-11012. [PMID: 38039031 DOI: 10.26355/eurrev_202311_34469] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 12/02/2023]
Abstract
OBJECTIVE Non-valvular atrial fibrillation (NVAF) is a common manifestation of cardiac arrhythmia, whose significance is heightened in the context of an aging global population and changing lifestyles, leading to an increased incidence. Stroke prevention in NVAF is a complex challenge that requires a comprehensive exploration of interventions. The emergence of Direct Oral Anticoagulants (DOACs) is a potential treatment, necessitating a thorough evaluation of their safety and efficacy. As the quest for the best strategy for thrombotic risk in these patients continues, the interaction between DOAC and aspirin has become the focus of research. MATERIALS AND METHODS With a rigorous methodological approach, we conducted a thorough search of scientific databases up to August 2023. The methodology involved meticulous screening, careful data extraction, and rigorous assessment of trial quality, all conducted by two independent investigators. The results were synthesized through standardized mean differences, accompanied by 95% confidence intervals. RESULTS DOACs demonstrated significant enhancements in stroke prevention for NVAF, which was indicated by favorable outcomes in bleeding (RR = 4.04, 95% CI: 3.96, 4.12), coronary artery disease (RR = 2.45, 95% CI: 2.42, 2.48), mortality (RR = 0.49, 95% CI: 0.43, 0.56), myocardial infarction (RR = 1.85, 95% CI: 1.81, 1.88), and stroke (RR = 1.50, 95% CI: 1.47, 1.54). Notably, DOACs demonstrated optimal efficacy for NVAF patients with stroke. CONCLUSIONS DOACs may be potentially effective for preventing stroke after NVAF.
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Affiliation(s)
- Z-Q Xu
- Department of Internal Medicine, Mengcheng County Hospital of Integrated Chinese and Western Medicine, Bozhou, China.
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Zhang N, Ding J, Li J, Wang L, Wei Y. Effects of Bacillus pumilus on growth performance, serum indexes and muscle development-related gene expression of weanling Jintang black goat. Benef Microbes 2023; 14:493-501. [PMID: 38350482 DOI: 10.1163/18762891-20220093] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2022] [Accepted: 05/01/2023] [Indexed: 02/15/2024]
Abstract
Antibiotic misuse has been a severe problem in animal husbandry. It is meaningful to replace antibiotics with Bacillus, as feed additives are indeed a research hotspot. Bacillus pumilus plays a certain role in promoting the growth performance and immunological indicators of animals. There are few reports about the function of goat-derived B. pumilus in animals until now. This study aimed to investigate the effects of B. pumilus fsznc-09 on growth performance and immune function of Jintang black goats. B. pumilus-treated group was fed with 1 ml freeze-dried agent of B. pumilus fsznc-09 at a concentration of 109 cfu/ml every 2 days. The growth performance, serum biochemical indexes, the expressions of muscle development and metabolism related genes of Jintang black goats were measured after 30 days. The results showed that the average daily gain and average daily feed intake were significantly increased, and feed conversion ratio was significantly decreased. The activities of total superoxide dismutase, alkaline phosphatase, immunoglobulin G and interferon-γ in serum of goats were significantly increased. However, the activity of malondialdehyde in serum was significantly decreased. The diameters and areas in longissimus dorsi fibre and gluteus fibre of goats were significantly decreased, while the densities in gluteus fibre of goats were significantly increased. The expressions of FAS, LPL, PPAR-γ, CAT, MYOD1, MYOG, MYF5 and MyHCI in longissimus dorsi and gluteus of goats were significantly improved. The expressions of TGFβ1, SREBP-1, MyHCIIb and MyHCIIx in longissimus dorsi and gluteus of goats were significantly increased. The expressions of FN1 in longissimus dorsi and MyHCIIa in gluteus of goats were significantly decreased. In conclusion, B. pumilus fsznc-09 can effectively improve the growth performance, immunological indicators and the expressions of muscle development and metabolism related genes of Jintang black goat.
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Affiliation(s)
- N Zhang
- Key Laboratory of Animal Science of National Ethnic Affairs Commission of China, Southwest Minzu University, Chengdu, 610041, China P.R
- Key Laboratory of Qinghai-Tibetan Plateau Animal Genetic Resource Reservation and Utilization of Ministry of Education, Chengdu, 610041, China P.R
| | - J Ding
- Center for Agricultural Ecology and Resource Protection of Sichuan, Chengdu, 610041, China P.R
| | - J Li
- Key Laboratory of Animal Science of National Ethnic Affairs Commission of China, Southwest Minzu University, Chengdu, 610041, China P.R
- Key Laboratory of Qinghai-Tibetan Plateau Animal Genetic Resource Reservation and Utilization of Ministry of Education, Chengdu, 610041, China P.R
| | - L Wang
- Key Laboratory of Animal Science of National Ethnic Affairs Commission of China, Southwest Minzu University, Chengdu, 610041, China P.R
- Key Laboratory of Qinghai-Tibetan Plateau Animal Genetic Resource Reservation and Utilization of Ministry of Education, Chengdu, 610041, China P.R
| | - Y Wei
- Animal Genetics and Breeding Key Laboratory of Sichuan Province, Sichuan Animal Sciences Academy, Chengdu, 610066, China P.R
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Zhao WY, Zhu XY, Li L, Zhang N, Huang PX, Liao MZ, Li YJ, Wang GY, Kang DM. [Analysis of factors influencing AIDS-related deaths among HIV-infected people in Shandong Province, 2017-2021]. Zhonghua Liu Xing Bing Xue Za Zhi 2023; 44:1634-1640. [PMID: 37875453 DOI: 10.3760/cma.j.cn112338-20230310-00138] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Subscribe] [Scholar Register] [Indexed: 10/26/2023]
Abstract
Objective: To explore the influencing factors of AIDS-related deaths among HIV-infected patients in Shandong Province, to help reduce the risk of death and prolong survival time. Methods: The study population was HIV-infected patients in Shandong Province from 2017-2021, and Cox proportional hazards regression model was used to analyze the influencing factors of AIDS-related deaths and deaths within one year of confirmation. Results: Among 14 700 HIV- infected patients reported in Shandong Province in 2017-2021, 351 AIDS-related deaths occurred, accounting for 2.4% (351/14 700). The results of multifactorial Cox proportional hazards regression model analysis showed that the risk factors for AIDS-related deaths among HIV-infected patients included education level of junior high school, high school, and secondary school (aHR=1.37, 95%CI:1.01-1.84), sample source from healthcare institutions (aHR=1.61, 95%CI:1.22-2.12), duration of disease in AIDS stage (aHR=9.86,95%CI:6.86-14.19), baseline CD4+T lymphocytes (CD4) undetected (aHR=3.93, 95%CI:2.69-5.75), duration of antiviral treatment (ART) <6 months (aHR=3.46, 95%CI:2.42-4.93) and no ART (aHR=1.45, 95%CI:1.02-2.07), final CD4 <200 cells/μl (aHR=3.51, 95%CI:2.18-5.65) and final CD4 undetected (aHR=10.58, 95%CI:6.15-18.19), and final viral load (VL) values of 50-999 copies/ml,≥1 000 copies/ml and undetected (aHR=2.59, 95%CI:1.07-6.26; aHR=9.50, 95%CI:5.60-16.12; aHR=15.33, 95%CI:8.91-26.36). Factors with higher risk of AIDS-related deaths within one year of confirmation of HIV-infected patients included samples originating from healthcare facilities (aHR=1.68, 95%CI: 1.19-2.36), AIDS stage of disease (aHR=10.60, 95%CI:7.13-15.75), baseline CD4 undetected (aHR=3.71, 95%CI:2.34-5.90), duration of ART <6 months (aHR=4.30, 95%CI:2.85-6.49) and no ART (aHR=2.05, 95%CI:1.35-3.13), final CD4 <200 cells/μl (aHR=5.45,95%CI:2.04-14.60) and final CD4 undetected (aHR=20.95, 95%CI: 7.69- 57.04), and final VL values of 50-999 copies/ml, ≥1 000 copies/ml and undetected (aHR=15.21, 95%CI: 2.54-91.21; aHR=42.93, 95%CI:9.64-191.20; aHR=61.35, 95%CI:13.85-271.77). Conclusions: Expanding the coverage of testing, promoting early detection and treatment, strengthening regular follow-up and the test of HIV-infected patients, grasping the progress of the disease to provide accurate management and treatment are important for reducing the disease mortality rate and prolonging the survival time of HIV-infected patients.
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Affiliation(s)
- W Y Zhao
- School of Public Health and Health Management, Shandong First Medical University & Shandong Academy of Medical Sciences, Ji'nan 250117, China
| | - X Y Zhu
- Institute of AIDS Control and Prevention, Shandong Center for Disease Control and Prevention, Ji'nan 250014, China
| | - L Li
- Institute of AIDS Control and Prevention, Shandong Center for Disease Control and Prevention, Ji'nan 250014, China
| | - N Zhang
- Institute of AIDS Control and Prevention, Shandong Center for Disease Control and Prevention, Ji'nan 250014, China
| | - P X Huang
- Institute of AIDS Control and Prevention, Shandong Center for Disease Control and Prevention, Ji'nan 250014, China
| | - M Z Liao
- Institute of AIDS Control and Prevention, Shandong Center for Disease Control and Prevention, Ji'nan 250014, China
| | - Y J Li
- Institute of AIDS Control and Prevention, Shandong Center for Disease Control and Prevention, Ji'nan 250014, China
| | - G Y Wang
- Institute of AIDS Control and Prevention, Shandong Center for Disease Control and Prevention, Ji'nan 250014, China
| | - D M Kang
- School of Public Health and Health Management, Shandong First Medical University & Shandong Academy of Medical Sciences, Ji'nan 250117, China
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20
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Qu C, He R, Hou W, Ye W, Cao H, Zhang H, Zhang N, Cheng Q, Zhang Q, Luo P. Global burden of neoplasms attributable to specific occupational carcinogens over 30 years: a population-based study. Public Health 2023; 223:145-155. [PMID: 37657137 DOI: 10.1016/j.puhe.2023.07.032] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/10/2023] [Revised: 07/16/2023] [Accepted: 07/25/2023] [Indexed: 09/03/2023]
Abstract
OBJECTIVES The study aimed to analyze the global burden of occupational neoplasms from various epidemiological perspectives. STUDY DESIGN In this cross-sectional study, secondary analyses were conducted to assess the burden of neoplasms attributable to occupational carcinogens and their distribution characteristics using data from GBD 2019 and the World Bank database. METHODS Based on the GBD 2019 and the World Bank database, we analyzed the global burden of occupational neoplasms including the age-period-cohort model, decomposition analysis, health inequality analysis, and panel model. All analyses were conducted in R (version 4.0.3) and Joinpoint (version 4.9.1). RESULTS The absolute number of neoplasms burden attributable to occupational carcinogens has continued to rise over 30 years. In 2019, occupational neoplasms caused 333,867 [95% uncertainty interval (UI): 263,491 to 404,641] mortalities and 6,964,775 (95% UI: 5,467,884 to 8,580,431) disability-adjusted life years (DALYs) globally. Greenland, Monaco, the Netherlands, and Andorra suffered the highest burden. The burden was higher in countries with a higher sociodemographic index. The age effect was prominent in the elderly, and the 1925 birth cohort had the highest cohort effect. Population growth was the most significant driver of the mortalities (89%) and DALYs (111%) change. Moreover, the proportion of urban population was significantly positively associated with the disease burden, while GDP per capita was negatively correlated with the disease burden. CONCLUSIONS The burden of occupational neoplasms was unevenly distributed across locations and populations. The need for rational allocation of healthcare resources was urgent.
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Affiliation(s)
- C Qu
- Department of Neurosurgery, Xiangya Hospital, Central South University, Changsha, Hunan, China; National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, Hunan, China; XiangYa School of Medicine, Central South University, Changsha, Hunan, China
| | - R He
- Department of Neurosurgery, Xiangya Hospital, Central South University, Changsha, Hunan, China; National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, Hunan, China; XiangYa School of Medicine, Central South University, Changsha, Hunan, China
| | - W Hou
- Department of Neurosurgery, Xiangya Hospital, Central South University, Changsha, Hunan, China; National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, Hunan, China; XiangYa School of Medicine, Central South University, Changsha, Hunan, China
| | - W Ye
- Department of Neurosurgery, Xiangya Hospital, Central South University, Changsha, Hunan, China; National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, Hunan, China
| | - H Cao
- Department of Psychiatry, Brain Hospital of Hunan Province (The Second People's Hospital of Hunan Province), Changsha, Hunan, China
| | - H Zhang
- Department of Neurosurgery, Xiangya Hospital, Central South University, Changsha, Hunan, China; Department of Neurosurgery, The Second Affiliated Hospital, Chongqing Medical University, Chongqing, China
| | - N Zhang
- College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Q Cheng
- Department of Neurosurgery, Xiangya Hospital, Central South University, Changsha, Hunan, China; National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, Hunan, China.
| | - Q Zhang
- Division of Gastroenterology and Hepatology, NHC Key Laboratory of Digestive Diseases, Shanghai Institute of Digestive Disease, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China.
| | - P Luo
- Department of Oncology, Zhujiang Hospital, Southern Medical University, Guangzhou, Guangdong, China.
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21
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Zhao X, Fang H, Jing H, Zhang N, Zhang J, Jin J, Zhong Q, Yang WF, Zhong Y, Dong L, Tie J, Wu HF, Wang XH, Lu Y, Hou X, Zhao L, Qi S, Song Y, Liu Y, Tang Y, Lu N, Chen B, Tang Y, Li Y, Wang S. Lymphocyte Count Kinetics and the Effect of Different Radiotherapy Techniques on Radiation-Induced Lymphopenia in Patients with Breast Cancer Receiving Hypofractionated Postmastectomy Radiotherapy. Int J Radiat Oncol Biol Phys 2023; 117:e216-e217. [PMID: 37784888 DOI: 10.1016/j.ijrobp.2023.06.1112] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/04/2023]
Abstract
PURPOSE/OBJECTIVE(S) Radiation-induced lymphopenia (RIL) is associated with poor prognosis in solid tumors. This study aimed to describe the lymphocyte kinetics in patients with breast cancer receiving hypofractionated postmastectomy radiotherapy (RT) and to investigate the association of different RT techniques with RIL. MATERIALS/METHODS We assessed 607 patients who received hypofractionated postmastectomy RT for breast cancer in our prospective clinical database from 8 hospitals. All patients received irradiation to the chest wall and supraclavicular fossa. RT techniques included integrated RT with the photon-based intensity modulated techniques to irradiate all target volumes (integrated RT) and a hybrid approach combining photon irradiation to supraclavicular nodes and electron irradiation to the chest wall (hybrid RT). Peripheral lymphocyte counts (PLC) were tested prior to RT (baseline), weekly during RT, at 1, 2 weeks, 3, 6 months after RT, and then every 6 months. Grade 3+ RIL was defined as PLC nadir during RT of <0.5 ×103/ml. Mean PLC was compared by the t test. Univariate, multivariate, and propensity score matching (PSM) analyses were used to evaluate the effect of different RT techniques on grade 3+ RIL. RESULTS During RT, 121 (19.9%) of patients had grade 3+ RIL. The PLC started to recover at 1 week and reached baseline levels 1 year after RT. A greater proportion of the patients treated with the integrated RT (90/269, 33.5%) developed grade 3+ PLC compared with those receiving hybrid RT (31/338, 9.2%, P < 0.001). After conducting PSM, multivariate analyses showed lower baseline PLC (HR = 0.15, P<0.001) and RT technique (the integrated RT vs. hybrid RT, HR = 4.76, P<0.001) were independent risk factors for grade 3+ RIL. The PLC in patients receiving the integrated RT after RT were higher than that in those receiving hybrid RT (p<0.05). CONCLUSION RT technique affect the risk of and recovery from RIL, which may impact survival. Choosing appropriate RT technique to minimize RIL might be considered to benefit their outcomes.
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Affiliation(s)
- X Zhao
- Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - H Fang
- Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - H Jing
- Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - N Zhang
- Department of Radiation Oncology, Cancer Hospital of China Medical University, Liaoning Cancer Hospital & Institute, Shenyang, China
| | - J Zhang
- Department of Radiation Oncology, Forth Hospital of Hebei Medical University, Shijiazhuang, China
| | - J Jin
- Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Q Zhong
- Department of Radiation Oncology, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, China
| | - W F Yang
- Department of Radiation Oncology, Affiliated Taizhou hospital of Wenzhou Medical University, Taizhou, China
| | - Y Zhong
- Department of Radiation and Medical Oncology, Zhongnan Hospital of Wuhan University, Wuhan, China
| | - L Dong
- Department of Radiation Oncology, The First Hospital, Jilin University, Changchun, China
| | - J Tie
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education), Department of Radiation Oncology, Peking University Cancer Hospital and Institute, Beijing, China
| | - H F Wu
- Department of Radiation Oncology, Jilin Cancer Hospital, Changchun, China
| | - X H Wang
- Department of Radiochemotherapy, People's Hospital of Tangshan City, Tangshan, China
| | - Y Lu
- Department of Radiation Oncology, Cancer Hospital of Henan Province, Zhengzhou, Henan, China
| | - X Hou
- Department of Radiation Oncology, Peking Union Medical College Hospital, Chinese Academy of medical Sciences & Peking Union Medical College, Beijing, China
| | - L Zhao
- Department of Radiation Oncology, Xijing Hospital, Fourth Military Medical University, Xi'an, China
| | - S Qi
- Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Y Song
- Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Y Liu
- Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Y Tang
- Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - N Lu
- Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - B Chen
- Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Y Tang
- GCP center/Clinical research center, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Y Li
- Department of Radiation Oncology, National Cancer Center/ National Clinical Research Center for Cancer/ Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - S Wang
- Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
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Wang DQ, Zhang N, Dong L, Wu HF, Zhong Q, Jin J, Hou X, Jing H, Fang H, Li YX, Wang S. Dose-Volume Predictors for Radiation Esophagitis in Breast Cancer Patients Undergoing Hypofractionated Regional Nodal Radiotherapy. Int J Radiat Oncol Biol Phys 2023; 117:e211-e212. [PMID: 37784878 DOI: 10.1016/j.ijrobp.2023.06.1101] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/04/2023]
Abstract
PURPOSE/OBJECTIVE(S) Radiation esophagitis (RE) is often overlooked in breast cancer radiotherapy. This study aimed to assess the incidence and dose-volume predictors of RE in breast cancer patients undergoing hypofractionated regional nodal irradiation (RNI). MATERIALS/METHODS Eligible patients were included who received intensity-modulated radiotherapy (RT) at the chest wall, the supraclavicular/infraclavicular fossa, level II axilla, and/or the internal mammary chain after mastectomy. The prescribed dose was 43.5 Gy in 15 fractions. The dose constraint for the esophagus was maximum dose <48 Gy. RE was evaluated weekly during RT and at 1 and 2 weeks, followed by 3 and 6 months after RT, and was graded according to the Common Toxicity Criteria for Adverse Events v3.0. The esophagus was contoured from the lower border level of the cricoid cartilage to the lower margin of the aortic arch. Esophageal total volume, mean dose (Dmean), maximum dose (Dmax), and the relative and absolute volumes receiving at least 5-45 Gy by 5 Gy increments (RV5-RV45 and AV5-AV45) were evaluated. Univariable and multivariable logistics regression analyses were performed to determine risk factors for RE, and receiver operating characteristic curves were obtained to identify the thresholds of esophageal dosimetric parameters. RESULTS In total, 298 patients were included between May 8, 2020 and January 5, 2022 (minimum post-RT follow-up: 6 months). A total of 153 (51.3%) patients had left-sided breast cancer and 145 (48.7%) patients received internal mammary nodal irradiation (IMNI). Grade 2 and 3 RE incidence was 40.9% (122/298) and 0.3% (1/298), respectively. No grade 4 or 5 RE was observed. All RE cases resolved within 1 month after RT, and the median duration of RE was 3 weeks (range, 1-5). Based on univariable analyses, tumor laterality (p < .001), IMNI (p = .056) and esophageal Dmean, Dmax, RV10-RV40, and AV10-AV40 were risk factors of ≥grade 2 RE. Esophageal RV10-RV40 and AV35-AV40 were significantly associated with the risk of ≥grade 2 RE after adjusting for tumor laterality and IMNI. Based on multivariable analyses, RV25 and AV35 were optimum dose-volume predictors for ≥grade 2 RE at thresholds 20% for RV25 (35.9% vs. 60.9%, p = .04) and 0.27 mL for AV35 (31.0% vs. 54.6%, p = .04). CONCLUSION RE is common in breast cancer patients undergoing hypofractionated RNI. With the same esophageal contouring standard, maintaining the upper esophageal V25 at <20% and V35 at <0.27 mL may decrease the risk of RE and improve the quality of life of patients.
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Affiliation(s)
- D Q Wang
- Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - N Zhang
- Department of Radiation Oncology, Cancer Hospital of China Medical University, Liaoning Cancer Hospital & Institute, Shenyang, China
| | - L Dong
- Department of Radiation Oncology, The First Hospital, Jilin University, Changchun, China
| | - H F Wu
- Department of Radiation Oncology, Jilin Cancer Hospital, Changchun, China
| | - Q Zhong
- Department of Radiation Oncology, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, China
| | - J Jin
- Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - X Hou
- Department of Radiation Oncology, Peking Union Medical College Hospital, Chinese Academy of medical Sciences & Peking Union Medical College, Beijing, China
| | - H Jing
- Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - H Fang
- Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Y X Li
- Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - S Wang
- Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, 100021, Beijing, China, Beijing, China
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Zhang N, Yang M. LINC00921 Diminishes Lung Cancer Radiosensitivity by Bestabilizing NUDT21 and Driving Aberrant MED23 Alternative Polyadenylation. Int J Radiat Oncol Biol Phys 2023; 117:e277-e278. [PMID: 37785040 DOI: 10.1016/j.ijrobp.2023.06.1255] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/04/2023]
Abstract
PURPOSE/OBJECTIVE(S) Alternative polyadenylation (APA) plays a major role in controlling transcriptome diversity and therapeutic resistance of cancers. However, long-noncoding RNAs (lncRNAs) involved in pathological APA remain poorly defined. Here, we functionally identified a MED13L/P300-induced oncogenic lncRNA, LINC00921, diminished lung cancer radiosensitivity by destabilizing NUDT21 and driving aberrant MED23 alternative polyadenylation. MATERIALS/METHODS ChIP-seq screening, RNA-seq and real-time PCR were used to identified LINC00921 in NSCLC. We performed RNA pulldown, RIP-qPCR, western blotting and Co-immunoprecipitation to investigate the function of LINC00921, which induced destabilization of NUDT21 and promoted 3' UTR shortening of MED23 via APA. RESULTS Through H3K27ac ChIP-seq screening, we functionally characterize LINC00921, a MED13L/P300-induced oncogenic lncRNA, required for global regulation of APA in non-small-cell lung cancer (NSCLC). LINC00921 shows significant potential for reducing radiosensitivity of NSCLC and high LINC00921 levels were associated with poor prognosis for NSCLC patients treated with radiotherapy. Mechanistically, LINC00921 directly interacts withNUDT21 via binding to its RNA-binding motif-2. LINC00921 controls NUDT21 stability via facilitating binding of NUDT21 with its newly identified E3 ligase TRIP12. Intriguingly, 3'UTR APA profiles reveal that LINC00921-induced destabilization of NUDT21 decreases the percentage of distal polyadenylation sites (PAS) usage index, resulting in the 3' UTR shortening of MED23 mRNA, which, in turn, leads to elevated MED23 protein levels in cancer cells. MED23 further increases nuclear translocation of β-catenin, and, thereby, activates expression of multiple β-Catenin/TCF/LEF-regulated core oncogenes (c-Myc, CCND1, and BMP4). CONCLUSION Taken together, our data revealed a novel model that integrates a lncRNA into regulation of malignant APA, radiotherapy resistance and NSCLC progression. These findings highlight the importance of functionally annotating lncRNAs controlling APA and unlock the clinical potential of novel therapeutics for advanced NSCLC.
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Affiliation(s)
- N Zhang
- Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, China
| | - M Yang
- Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, China
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Song Y, Hu Z, Yan XN, Fang H, Yu T, Jing H, Men K, Zhang N, Zhang J, Jin J, Zhong Q, Ma J, Yang WF, Zhong Y, Dong L, Wang XH, Wu HF, Du XH, Hou X, Tie J, Lu Y, Zhao L, Li YX, Wang S. Quality Assurance in a Phase III, Multicenter, Randomized Trial of POstmastectomy radioThErapy in Node posiTive Breast Cancer with or without Internal mAmmary nodaL Irradiation (POTENTIAL): A Planning Dummy Run. Int J Radiat Oncol Biol Phys 2023; 117:S97. [PMID: 37784615 DOI: 10.1016/j.ijrobp.2023.06.431] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/04/2023]
Abstract
PURPOSE/OBJECTIVE(S) To report the planning dummy run results of the POstmastectomy radioThErapy in Node posiTive breast cancer with or without Internal mAmmary nodaL irradiation (POTENTIAL) trial-a multicenter, randomized, phase 3 trial-to evaluate postmastectomy radiotherapy, with or without internal mammary nodal irradiation, for patients with high-risk breast cancer. MATERIALS/METHODS All participating institutions were provided the contours of the dummy run case, and they generated radiotherapy (RT) plans per protocol guidelines. The plans were reviewed and feedback were provided by the quality assurance team, after which the institutions resubmitted revised plans. The information on beams arrangement, skin flash, inhomogeneity corrections, and protocol compliance was assessed both in the primary and final submission. RESULTS Theplans from 26 institutions were included in the analysis. A number of major deviations were found in the primary submission, such as less strict constraint on organs at risk (OARs) V5Gy, and no application of chest wall skin flash. The protocol compliance rates of the dose coverage for the planning target volume of the chest wall (PTVcw), PTV of supra/infraclavicular fossa plus axilla levels I, II, III (PTVsc+ax), and PTV of the IMN region (PTVim) were all significantly improved in the final submission compared with those in the primary submission, which were 96.2% vs. 69.2%, 100% vs. 76.9%, and 88.4% vs. 53.8, respectively. For OARs, the protocol compliance rates of heart Dmean, left anterior descending coronary artery V40Gy, ipsilateral lung V5Gy, and stomach V5Gy were significantly improved. CONCLUSION All major deviations were corrected and protocol compliance was significantly improved and of high level in the final submission. Moreover, the variations were reduced. Therefore, a planning dummy run was essential to guarantee good RT plan quality and inter-institutional consistency for multicenter trials.
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Affiliation(s)
- Y Song
- Department of Radiation Oncology, National Cancer Center/ National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Z Hu
- Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - X N Yan
- Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - H Fang
- Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - T Yu
- Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - H Jing
- Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - K Men
- Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - N Zhang
- 2. Department of Radiation Oncology, Cancer Hospital of China Medical University, Liaoning Cancer Hospital & Institute, Shenyang, Liaoning, China
| | - J Zhang
- Department of Radiation Oncology, Forth Hospital of Hebei Medical University, Shijiazhuang, China
| | - J Jin
- Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Q Zhong
- Department of Radiation Oncology, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, China
| | - J Ma
- Department of Radiation Oncology, Jiangsu Province Hospital of Chinese medicine, Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing, Jiangsu, China
| | - W F Yang
- Department of Radiation Oncology, Affiliated Taizhou hospital of Wenzhou Medical University, Taizhou, China
| | - Y Zhong
- Department of Radiation and Medical Oncology, Zhongnan Hospital of Wuhan University, Wuhan, China
| | - L Dong
- Department of Radiation Oncology, The First Hospital, Jilin University, Changchun, China
| | - X H Wang
- Department of Radiochemotherapy, People's Hospital of Tangshan City, Tangshan, China
| | - H F Wu
- Department of Radiation Oncology, Jilin Cancer Hospital, Changchun, China
| | - X H Du
- Department of Radiation Oncology, Zhejiang Cancer Hospital, Hangzhou, China
| | - X Hou
- Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - J Tie
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education), Department of Radiation Oncology, Peking University Cancer Hospital and Institute, Beijing, China
| | - Y Lu
- Department of Radiation Oncology, Cancer Hospital of Henan Province, Zhengzhou, Henan, China
| | - L Zhao
- Department of Radiation Oncology, Xijing Hospital, Fourth Military Medical University, Xi'an, China
| | - Y X Li
- Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - S Wang
- Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
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Han F, Yang XK, He T, Wang LX, Zhang N, Han JT. [Curative effects of medial plantar free flap in reconstructing electric burn wound and scar contracture in the palm]. Zhonghua Shao Shang Yu Chuang Mian Xiu Fu Za Zhi 2023; 39:820-825. [PMID: 37805797 DOI: 10.3760/cma.j.cn501225-20230601-00197] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 10/09/2023]
Abstract
Objective: To explore the curative effects of medial plantar free flap in reconstructing electric burn wound and scar contracture in the palm. Methods: A retrospective observational study was conducted. From January 2020 to January 2023, 6 patients with electric burn wounds or scar contracture in the palm who met the inclusion criteria were admitted to the First Affiliated Hospital of Air Force Medical University, including 5 males and 1 female, aged 35 to 55 years. The wound area was 5.0 cm×3.0 cm-8.0 cm×7.0 cm after the debridement of electric burn wounds or resection of scar in the palm. The medial plantar free flap anastomosed with cutaneous nerve was used for wound reconstruction, with flap area of 5.5 cm×3.5 cm-8.5 cm×7.5 cm. The wound in the donor site was repaired with transplantation of abdominal full-thickness skin graft. After surgery, the survival of flaps and skin grafts were observed, the shape and texture of flap and the recovery of donor site of flap were observed, and the holding function of the affected hand was assessed. At the last follow-up, the two-point discrimination distance of flap was measured, the sensory recovery of flap was evaluated with the trial standard for the evaluation of the functions of the upper limbs of the Hand Surgery Society of the Chinese Medical Association, and the function recovery of flap was evaluated by post-surgery flap function evaluation scale. Results: After surgery, 5 flaps survived well, while the distal part of 1 flap was partially necrotic, which was repaired by medium-thickness skin graft from lateral thigh after debridement. All the skin grafts at the donor sites survived well. During follow-up of 3 to 24 months, the flap was not bloated, the texture and color were good, the match with the surrounding tissue was high, with no obvious scar contracture occurred at the donor site. The affected hand had good holding function. At the last follow-up, the two-point discrimination distance of flap was 6-8 mm, the flap sensation recovery was as follows: 5 flaps recovered to grade S3+, 1 flap recovered to grade S3, and the functional evaluation of flaps was excellent in 5 cases and good in 1 case. The patients basically returned to normal life and work. Conclusions: The medial plantar free flap with cutaneous nerve anastomosis has many advantages, such as high matching degree of appearance, good sensory recovery, and holding function of the affected hand. It is an ideal choice for the reconstruction of the electric burn wound and scar contracture in the palm.
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Affiliation(s)
- F Han
- Department of Burns and Cutaneous Surgery, Burn Center of PLA, the First Affiliated Hospital of Air Force Medical University, Xi'an 710032, China
| | - X K Yang
- Department of Burns and Cutaneous Surgery, Burn Center of PLA, the First Affiliated Hospital of Air Force Medical University, Xi'an 710032, China
| | - T He
- Department of Burns and Cutaneous Surgery, Burn Center of PLA, the First Affiliated Hospital of Air Force Medical University, Xi'an 710032, China
| | - L X Wang
- Department of Burns and Cutaneous Surgery, Burn Center of PLA, the First Affiliated Hospital of Air Force Medical University, Xi'an 710032, China
| | - N Zhang
- Department of Burns and Cutaneous Surgery, Burn Center of PLA, the First Affiliated Hospital of Air Force Medical University, Xi'an 710032, China
| | - J T Han
- Department of Burns and Cutaneous Surgery, Burn Center of PLA, the First Affiliated Hospital of Air Force Medical University, Xi'an 710032, China
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Zhang XN, Yan K, You XD, Li JH, Zhang N, Wang GY, Liao MZ, Ma W. [Acceptance of pre-exposure prophylaxis and post-exposure prophylaxis against HIV and related factors in men who have sex with men in Shandong Province]. Zhonghua Liu Xing Bing Xue Za Zhi 2023; 44:1352-1357. [PMID: 37743265 DOI: 10.3760/cma.j.cn112338-20230202-00052] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Subscribe] [Scholar Register] [Indexed: 09/26/2023]
Abstract
Objectives: To understand the use of pre-exposure prophylaxis (PrEP) and post-exposure prophylaxis (PEP) and related factors in men who have sex with men (MSM) in Shandong Province, and provide reference for the promotion of PrEP and PEP in MSM. Methods: From April to July in 2022, MSM were recruited from 7 sentinel surveillance sites in Shandong Province for a questionnaire survey, and the sample size of each city site was 400. The information about sociodemographic characteristics, sexual behaviors, the uses of PrEP and PEP and others were collected from the MSM, and blood samples were collected from them for HIV and syphilis testing. Results: A total of 2 815 MSM were investigated, the majority of them were aged less than 30 years (55.7%, 1 569/2 815), unmarried (68.6%, 1 931/2 815) and had education background of college and above (56.5%, 1 590/2 815). Only 9.2% (258/2 815) had used PrEP and 10.8% (305/2 815) had used PEP. Multivariate logistic regression showed that factors associated with high likelihood of PrEP use in MSM included age ≤30 years (aOR=4.04, 95%CI:1.25-13.01), self-perceived lower risk of HIV infection (aOR=1.76, 95%CI:1.16-2.68), group sex and commercial sex in the past six months (aOR=1.51, 95%CI: 1.10-2.09; aOR=1.69, 95%CI: 1.16-2.47), new-type drug use (aOR=1.53, 95%CI: 1.11-2.11), receiving peer education (aOR=1.56, 95%CI: 1.03-2.37), other people using PrEP (aOR=3.29, 95%CI: 2.48-4.36), and being HIV negative (aOR=8.40, 95%CI:1.12-63.12). Factor associated with low likelihood of PrEP use in MSM was anal sex with casual partner (aOR=0.67, 95%CI:0.49-0.90). Factors associated with high likelihood of PEP use in MSM included age under 50 years (≤30 years old: aOR=2.41, 95%CI:1.02-5.69; 31-49 years old: aOR=3.33, 95%CI:1.42-7.85), no self-perceived risk for HIV infection (aOR=1.87, 95%CI:1.12-3.11), group sex in the past six months (aOR=1.68, 95%CI:1.23-2.29), new-type drug use (aOR=3.86, 95%CI:2.94-5.07) and receiving no peer education (aOR=1.54, 95%CI:1.12-2.12). Conclusions: In Shandong, a higher proportion of MSM used PrEP and PEP. Peer education and self-perceived HIV infection risk education should be strengthened to increase the rates of PrEP and PEP use in MSM.
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Affiliation(s)
- X N Zhang
- Department of Epidemiology, School of Public Health, Cheeloo College of Medicine, Shandong University, Ji'nan 250012, China
| | - K Yan
- Department of AIDS/STD Control and Prevention, Shandong Provincial Center for Disease Control and Prevention, Ji'nan 250014, China
| | - X D You
- Department of AIDS/STD Control and Prevention, Shandong Provincial Center for Disease Control and Prevention, Ji'nan 250014, China
| | - J H Li
- Department of AIDS/STD Control and Prevention, Shandong Provincial Center for Disease Control and Prevention, Ji'nan 250014, China
| | - N Zhang
- Department of AIDS/STD Control and Prevention, Shandong Provincial Center for Disease Control and Prevention, Ji'nan 250014, China
| | - G Y Wang
- Department of AIDS/STD Control and Prevention, Shandong Provincial Center for Disease Control and Prevention, Ji'nan 250014, China
| | - M Z Liao
- Department of AIDS/STD Control and Prevention, Shandong Provincial Center for Disease Control and Prevention, Ji'nan 250014, China
| | - W Ma
- Department of Epidemiology, School of Public Health, Cheeloo College of Medicine, Shandong University, Ji'nan 250012, China
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Zhuang X, Chen YY, Wang C, Zhang N, Zhang Y, Lin JH. [Difference of urinary protein components and the correlation between urinary protein quantification and glomerular filtration rate in pregnant women with pre-eclampsia]. Zhonghua Fu Chan Ke Za Zhi 2023; 58:582-588. [PMID: 37599255 DOI: 10.3760/cma.j.cn112141-20230215-00069] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Subscribe] [Scholar Register] [Indexed: 08/22/2023]
Abstract
Objective: To investigate the difference of urinary protein components in pregnant women with pre-eclampsia (PE) with different degrees of proteinuria and the correlation between 24-hour urinary protein quantification and estimated glomerular filtration rate (eGFR). Methods: Clinical data of 101 PE pregnant women who were delivered in Renji Hospital, Shanghai Jiao Tong University School of Medicine from July 2018 to June 2022 were retrospectively analyzed. According to 24-hour urinary protein quantification, they were divided into 3 groups, including 40 cases of mild proteinuria group (24-hour urinary protein quantification ≤2.0 g), 21 cases of moderate proteinuria group (2.0 g<24-hour urinary protein quantification ≤5.0 g), 40 cases of severe proteinuria group (24-hour urinary protein quantification >5.0 g). The general clinical data, urinary protein index and renal function index of PE pregnant women in 3 groups were compared. The eGFR was calculated based on age, serum creatinine (sCr), blood urea nitrogen (BUN) and serum albumin (sAlb). Correlation analysis was conducted between 24-hour urinary protein quantification and each index of eGFR. Results: (1) General clinical data: the median PE onset week (31 weeks) and delivery gestational week [(36.4±3.6) weeks] of PE pregnant women in the mild proteinuria group were later than those in the moderate proteinuria group [median PE onset: 22 weeks, delivery: (32.2±4.2) weeks] and severe proteinuria group [median PE onset: 25 weeks, delivery: (29.6±3.4) weeks]; systolic blood pressure, diastolic blood pressure, alanine aminotransferase, aspartate aminotransferase levels and the incidence of fetal growth restriction were lower than those in the moderate and severe proteinuria groups; median newborn birth weight (3 150 g) was higher than those in the moderate proteinuria group (1 305 g) and the severe proteinuria group (1 042 g), respectively. The differences were statistically significant (all P<0.05). (2) Urinary protein index: the 24-hour urinary protein quantification, urinary microalbumin (mAlb) and urinary transferrin (TRF) levels of PE pregnant women in the mild proteinuria group, moderate proteinuria group and severe proteinuria group were increased successively, and the differences were statistically significant (all P<0.05). The median urinary α1-microglobulin (α1-MG) level of PE pregnant women in the severe proteinuria group (50 mg/L) was significantly higher than those in the mild proteinuria group (17 mg/L) and moderate proteinuria group (22 mg/L; all P<0.05), but there was no significant difference between the mild proteinuria group and the moderate proteinuria group (P>0.05). There was no significant difference in the median urinary β2-microglobulin (β2-MG) level among the 3 groups (P=0.632). (3) Renal function index: sAlb and eGFR of PE pregnant women in the mild proteinuria group, moderate proteinuria group and severe proteinuria group were successively decreased, and BUN was successively increased, respectively, and the differences were statistically significant (all P<0.05). The sCr level of PE pregnant women in the severe proteinuria group was significantly higher than those in the mild proteinuria group and the moderate proteinuria group (all P<0.05), but there was no significant difference between the mild proteinuria group and the moderate proteinuria group (P>0.05). (4) Correlation analysis: the 24-hour urinary protein quantification of PE pregnant women was significantly negatively correlated with eGFR (r=-0.645, P<0.001), and was correlated with the variables sAlb (r=-0.549, P<0.001), sCr (r=0.582, P<0.001) and BUN (r=-0.657, P<0.001) in the eGFR calculation formula. The 24-hour urinary protein quantification were significantly negatively correlated with the gestational weeks of PE onset, gestational weeks of termination of pregnancy and newborn birth weight (all P<0.05). Conclusions: The protein composition in the urine of PE pregnant women with different degrees of proteinuria is not different, but the protein level is significantly different. There is a significant negative correlation between the increase of 24-hour urinary protein quantification and the decrease of eGFR.
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Affiliation(s)
- X Zhuang
- Department of Obstetrics and Gynecology, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200127, China
| | - Y Y Chen
- Department of Obstetrics and Gynecology, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200127, China
| | - C Wang
- Department of Obstetrics and Gynecology, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200127, China
| | - N Zhang
- Department of Obstetrics and Gynecology, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200127, China
| | - Y Zhang
- Department of Obstetrics and Gynecology, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200127, China
| | - J H Lin
- Department of Obstetrics and Gynecology, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200127, China
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Wang LN, Liu DY, Huang PX, Zhu XY, Zhang N, Wang GY, Liao MZ, Ma W. [Analysis of characteristics of types of primary sexual partners and related factors of not being tested for HIV among men who have sex with men]. Zhonghua Liu Xing Bing Xue Za Zhi 2023; 44:1276-1282. [PMID: 37661621 DOI: 10.3760/cma.j.cn112338-20221011-00871] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Subscribe] [Scholar Register] [Indexed: 09/05/2023]
Abstract
Objective: To compare the characteristics of MSM with different types of primary sexual partners and to analyze the factors associated with MSM not being tested for HIV in the last six months. Methods: MSM were recruited in nine cities of Shandong Province from April to July 2021, and face-to-face questionnaires were conducted to collect information on sociodemographic characteristics, high-risk behaviors, and HIV testing of MSM. Blood samples were taken for serological tests of HIV and syphilis antibodies. Results: A total of 3 008 men who had anal sex with men in the last six months were divided into three groups according to the type of primary sexual partner in the last six months: the fixed sexual partner group (36.83%, 1 108/3 008), the commercial sexual partner group (3.06%, 92/3 008), and casual sexual partner group (60.11%, 1 808/3 008). There were statistically significant differences in the distribution of age, local residence time, education level, the primary place to find male sexual partners, use of new-type drugs in the last six months, consistent condom use every time during same-sex anal sex in the last six months, group sex in the last six months, no HIV testing in the last six months, having had a sexually transmitted disease in the last year, receiving peer education in the last year, and frequency of syphilis testing in the last year among different groups (P<0.05). Multivariable logistic regression analysis showed that related factors of not being tested for HIV in the last six months in MSM were those aged less than 30 years old (aOR=1.39, 95%CI: 1.06-1.83), married/cohabiting (aOR=1.74, 95%CI: 1.39-2.16), high school education or less (aOR=1.39, 95%CI: 1.15-1.67), had not used new-type drugs in the last six months (aOR=2.27, 95%CI: 1.89-2.71), had not received peer education in the last year (aOR=1.59, 95%CI: 1.28-1.98), had never been tested for syphilis (aOR=11.30, 95%CI: 8.15-15.66), had not been tested in the last year but had been previously tested for syphilis (aOR=5.65, 95%CI: 4.19-7.62), the type of primary sexual partner in the last six months being a commercial sexual partner (aOR=1.80, 95%CI: 1.01-3.20), and the type of primary sexual partner in the last six months being a casual sexual partner (aOR=1.50, 95%CI: 1.26-1.80). Conclusions: The characteristics of MSM with different types of primary sexual partners are different, and the proportion of HIV testing still needs to be improved. In the future, we should make full use of the Internet and peer education to expand the coverage of HIV testing for MSM, targeting the characteristics of MSM with different types of primary sexual partners.
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Affiliation(s)
- L N Wang
- Department of Epidemiology, School of Public Health, Cheeloo College of Medicine, Shandong University, Ji'nan 250012, China
| | - D Y Liu
- Department of AIDS/STD Control and Prevention, Weifang City Center for Disease Control and Prevention, Weifang 261061, China
| | - P X Huang
- Department of AIDS/STD Control and Prevention, Shandong Center for Disease Control and Prevention, Ji'nan 250014, China
| | - X Y Zhu
- Department of AIDS/STD Control and Prevention, Shandong Center for Disease Control and Prevention, Ji'nan 250014, China
| | - N Zhang
- Department of AIDS/STD Control and Prevention, Shandong Center for Disease Control and Prevention, Ji'nan 250014, China
| | - G Y Wang
- Department of AIDS/STD Control and Prevention, Shandong Center for Disease Control and Prevention, Ji'nan 250014, China
| | - M Z Liao
- Department of AIDS/STD Control and Prevention, Shandong Center for Disease Control and Prevention, Ji'nan 250014, China
| | - W Ma
- Department of Epidemiology, School of Public Health, Cheeloo College of Medicine, Shandong University, Ji'nan 250012, China
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Gheres KW, Ünsal HS, Han X, Zhang Q, Turner KL, Zhang N, Drew PJ. Arousal state transitions occlude sensory-evoked neurovascular coupling in neonatal mice. Commun Biol 2023; 6:738. [PMID: 37460780 PMCID: PMC10352318 DOI: 10.1038/s42003-023-05121-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2023] [Accepted: 07/07/2023] [Indexed: 07/20/2023] Open
Abstract
In the adult sensory cortex, increases in neural activity elicited by sensory stimulation usually drive vasodilation mediated by neurovascular coupling. However, whether neurovascular coupling is the same in neonatal animals as adults is controversial, as both canonical and inverted responses have been observed. We investigated the nature of neurovascular coupling in unanesthetized neonatal mice using optical imaging, electrophysiology, and BOLD fMRI. We find in neonatal (postnatal day 15, P15) mice, sensory stimulation induces a small increase in blood volume/BOLD signal, often followed by a large decrease in blood volume. An examination of arousal state of the mice revealed that neonatal mice were asleep a substantial fraction of the time, and that stimulation caused the animal to awaken. As cortical blood volume is much higher during REM and NREM sleep than the awake state, awakening occludes any sensory-evoked neurovascular coupling. When neonatal mice are stimulated during an awake period, they showed relatively normal (but slowed) neurovascular coupling, showing that that the typically observed constriction is due to arousal state changes. These result show that sleep-related vascular changes dominate over any sensory-evoked changes, and hemodynamic measures need to be considered in the context of arousal state changes.
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Affiliation(s)
- Kyle W Gheres
- Molecular Cellular and Integrative Bioscience program, The Pennsylvania State University, University Park, PA, 16802, USA
| | - Hayreddin S Ünsal
- Department of Biomedical Engineering, The Pennsylvania State University, University Park, PA, 16802, USA
- Department of Electrical and Electronics Engineering, Abdullah Gul University, Kayseri, Türkiye
| | - Xu Han
- Molecular Cellular and Integrative Bioscience program, The Pennsylvania State University, University Park, PA, 16802, USA
| | - Qingguang Zhang
- Department of Engineering Science and Mechanics, The Pennsylvania State University, University Park, PA, 16802, USA
| | - Kevin L Turner
- Department of Biomedical Engineering, The Pennsylvania State University, University Park, PA, 16802, USA
| | - Nanyin Zhang
- Molecular Cellular and Integrative Bioscience program, The Pennsylvania State University, University Park, PA, 16802, USA
- Department of Biomedical Engineering, The Pennsylvania State University, University Park, PA, 16802, USA
- Center for Neural Engineering, The Pennsylvania State University, University Park, PA, 16802, USA
- Center for Neurotechnology in Mental Health Research, The Pennsylvania State University, University Park, PA, 16802, USA
| | - Patrick J Drew
- Molecular Cellular and Integrative Bioscience program, The Pennsylvania State University, University Park, PA, 16802, USA.
- Department of Biomedical Engineering, The Pennsylvania State University, University Park, PA, 16802, USA.
- Department of Engineering Science and Mechanics, The Pennsylvania State University, University Park, PA, 16802, USA.
- Center for Neural Engineering, The Pennsylvania State University, University Park, PA, 16802, USA.
- Center for Neurotechnology in Mental Health Research, The Pennsylvania State University, University Park, PA, 16802, USA.
- Departments of Neurosurgery and Biology, The Pennsylvania State University, University Park, PA, 16802, USA.
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Chen YJ, Qin Y, Yu H, Zhu Z, Shen C, Lu Y, Cheng TT, Zhang N, Gu SJ, Zhou JY, Wu M, Su J. [A prospective cohort study of long-term fasting blood glucose variability and risk of mortality in patients with type 2 diabetes]. Zhonghua Liu Xing Bing Xue Za Zhi 2023; 44:1099-1105. [PMID: 37482713 DOI: 10.3760/cma.j.cn112338-20221226-01084] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Subscribe] [Scholar Register] [Indexed: 07/25/2023]
Abstract
Objective: To investigate the association between long-term fasting blood glucose (FPG) variability and all-cause mortality in patients with type 2 diabetes. Methods: A total of 7 174 type 2 diabetic patients included in National Basic Public Health Service Program in Changshu of Jiangsu Province were recruited as participants. Long-term glucose variability was assessed using standard deviation (SD), coefficient of variation (CV), average real variability (ARV), and variability independent of the mean (VIM) across FPG measurements at the more than three visits. Death information were mainly obtained from the death registry system in Jiangsu. Then Cox proportional hazards regression models were used to estimate the associations of four variability indicators and all-cause mortality's hazard ratios (HRs) and their 95%CIs. Results: Among 55 058.50 person-years of the follow-up, the mean follow-up time was 7.67 years, and 898 deaths occurred during the follow-up period. After adjustment, compared with T1 group, the Cox regression model showed that HRs of T3 group in SD, CV, ARV and VIM were 1.24 (95%CI: 1.03-1.49), 1.20 (95%CI: 1.01-1.43), 1.28 (95%CI: 1.07-1.55) and 1.20 (95%CI:1.01-1.41), respectively. HRs of per 1 SD higher SD, CV, ARV and VIM were 1.13 (95%CI: 1.06-1.21), 1.08 (95%CI: 1.01-1.15), 1.05 (95%CI: 1.00-1.12) and 1.09 (95%CI: 1.02-1.16) for all-cause mortality, respectively. In the stratified analysis, age, gender, hypoglycemic agent and insulin uses had no effect on the above associations (all P for interaction >0.05). Conclusion: Long-term FPG glycemic variability was positively associated with the risk of all-cause mortality in type 2 diabetes patients.
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Affiliation(s)
- Y J Chen
- Department of Non-communicable Chronic Disease Prevention, Nanjing Municipal Center for Disease Control and Prevention, Nanjing 210003, China
| | - Y Qin
- Department of Non-communicable Chronic Disease Control, Jiangsu Provincial Center for Disease Control and Prevention, Nanjing 210009, China
| | - H Yu
- Department of Non-communicable Chronic Disease Control, Jiangsu Provincial Center for Disease Control and Prevention, Nanjing 210009, China
| | - Z Zhu
- Department of Non-communicable Chronic Disease Control, Jiangsu Provincial Center for Disease Control and Prevention, Nanjing 210009, China
| | - C Shen
- Department of Epidemiology and Biostatistics, School of Public Health, Nanjing Medical University, Nanjing 211166, China
| | - Y Lu
- Department of Non-communicable Chronic Disease Prevention, Suzhou Prefectural Center for Disease Control and Prevention, Suzhou 215004, China
| | - T T Cheng
- Department of Infectious Disease Control Division, Suzhou National New & Hi-Tech Industrial Development Zone (Huqiu District) Center for Disease Control and Prevention, Suzhou 215163, China
| | - N Zhang
- Changshu County Center for Disease Control and Prevention, Changshu 215500, China
| | - S J Gu
- Department of Non-communicable Chronic Disease Prevention, Changshu County Center for Disease Control and Prevention, Changshu 215500, China
| | - J Y Zhou
- Department of Non-communicable Chronic Disease Control, Jiangsu Provincial Center for Disease Control and Prevention, Nanjing 210009, China
| | - M Wu
- Department of Non-communicable Chronic Disease Control, Jiangsu Provincial Center for Disease Control and Prevention, Nanjing 210009, China
| | - J Su
- Department of Non-communicable Chronic Disease Control, Jiangsu Provincial Center for Disease Control and Prevention, Nanjing 210009, China
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Zhang N, Chen L, He LJ. [Interpretation of the 5th edition WHO classification of pediatric tumors]. Zhonghua Bing Li Xue Za Zhi 2023; 52:661-664. [PMID: 37408394 DOI: 10.3760/cma.j.cn112151-20221205-01022] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Subscribe] [Scholar Register] [Indexed: 07/07/2023]
Affiliation(s)
- N Zhang
- Department of Pathology, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health, Beijing 100045, China
| | - L Chen
- Department of Pathology, Children's Hospital of Fudan University, Shanghai 201102, China
| | - L J He
- Department of Pathology, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health, Beijing 100045, China
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Li Q, Zhang N. Sex differences in resting-state functional networks in awake rats. Brain Struct Funct 2023; 228:1411-1423. [PMID: 37261489 DOI: 10.1007/s00429-023-02657-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2023] [Accepted: 05/18/2023] [Indexed: 06/02/2023]
Abstract
Sex-related differences can be found in many brain disorders and psychophysiological traits, highlighting the importance to systematically understand the sex differences in brain function in humans and animal models. Despite emerging effort to address sex differences in behaviors and disease models in rodents, how brain-wide functional connectivity (FC) patterns differ between male and female rats remains largely unknown. Here, we used resting-state functional magnetic resonance imaging (rsfMRI) to investigate regional and systems-level differences between female and male rats. Our data show that female rats display stronger hypothalamus connectivity, whereas male rats exhibit more prominent striatum-related connectivity. At the global scale, female rats demonstrate stronger segregation within the cortical and subcortical systems, while male rats display more prominent cortico-subcortical interactions, particularly between the cortex and striatum. Taken together, these data provide a comprehensive framework of sex differences in resting-state connectivity patterns in the awake rat brain, and offer a reference for studies aiming to reveal sex-related FC differences in different animal models of brain disorders.
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Affiliation(s)
- Qiong Li
- Department of Biomedical Engineering, The Pennsylvania State University, University Park, State College, USA
| | - Nanyin Zhang
- Department of Biomedical Engineering, The Pennsylvania State University, University Park, State College, USA.
- Center for Neurotechnology in Mental Health Research, The Pennsylvania State University, University Park, State College, 16802, USA.
- Center for Neural Engineering, The Pennsylvania State University, University Park, State College, 16802, USA.
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Jian ZZ, Zhang N, Ma Y, Man WW. Incidence and trends of nosocomial infection in a tertiary general hospital in China from 2018 to 2021: a retrospective observational study. Eur Rev Med Pharmacol Sci 2023; 27:6760-6768. [PMID: 37522697 DOI: 10.26355/eurrev_202307_33146] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Subscribe] [Scholar Register] [Indexed: 08/01/2023]
Abstract
OBJECTIVE This study aimed to investigate the current status and changing trend of nosocomial infection in a tertiary general hospital in China, to provide a reference for the prevention and control of healthcare-associated/acquired infection (HAI). PATIENTS AND METHODS A retrospective investigation of the clinical data of HAI patients in Dongying People's Hospital in China from January 1, 2018, to December 31, 2021, was carried out. The incidence of HAI in different units and sites, distribution of pathogenic microorganisms, and antimicrobial use were investigated. RESULTS The incidence of HAI was 0.93%. It was on the rise from 2018 to 2020 but declined in 2021. The departments with the highest rate of HAI were the Intensive Care Unit (ICU), neurosurgery department, cardiothoracic surgery department, and hematology department. HAI often occurs in the lower respiratory tract, urinary tract, and in blood. The most common pathogenic microorganisms in cases of HAI were Escherichia coli, Klebsiella pneumoniae, Pseudomonas aeruginosa, Acinetobacter baumannii, and Staphylococcus aureus. The rate of bacterial culture delivery for therapeutic drugs has increased from year to year. CONCLUSIONS This study shows that the incidence of HAI in the hospital is generally low. Gram-negative bacteria are still the main source of HAI. The rate of bacterial culture delivery for therapeutic use improved over the years and has gradually been standardized. It is necessary to focus on the management of HAI in the ICU, neurosurgery, cardiothoracic surgery, and hematology departments.
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Affiliation(s)
- Z-Z Jian
- Department of Infection Management, Dongying People's Hospital, Dongying, Shandong, China.
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Xing J, Zhang N, Chen B, Tong ZC, Liu HM, Zhou HZ. Rare adult Kaposiform hemangioendothelioma with multiple-bone invasion - clinical experience and literature review. Eur Rev Med Pharmacol Sci 2023; 27:6653-6661. [PMID: 37522676 DOI: 10.26355/eurrev_202307_33135] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 08/01/2023]
Abstract
BACKGROUND Kaposiform hemangioendothelioma (KHE) is a borderline vascular tumor between hemangioma and malignant angiosarcoma. While KHE has strong local invasion with rare spontaneous regression, it is not observed with distant metastasis. Even if KHE is asymptomatic or without the Kasabach-Merritt phenomenon (KMP), bone or joint invasion should clearly receive proactive treatment. KHE commonly affects infants/children but is rarely seen in adults. CASE REPORT We reported a rare adult KHE case with an invasion of >10 separate forearm/hand bones, who underwent multiple-lesion resection and finger amputation after tumor recurrence. Tumor recurrence and KMP were not observed during the 6-month follow-up after the final operation. During the hospitalization and follow-up period, the patient only received medications for infection prevention and pain relief. CONCLUSIONS Multiple resectable lesions were found in the distal limb, for which complete resection might not present typical features (high-intensity T2-weighted MRI), which might fail to detect all KHE lesions. Therefore, complete excision is not optimal for multiple resectable KHE lesions.
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Affiliation(s)
- J Xing
- Department of Orthopedics and Traumatology, Honghui Hospital, Xi'an JiaoTong University, Xi'an, China.
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Hong BA, Zhao Q, Ji YP, Cao YD, Yang Y, Zhang N. [The preliminary efficacy of "quadri-combination" therapy on the treatment of bladder cancer]. Zhonghua Yi Xue Za Zhi 2023; 103:1855-1859. [PMID: 37357192 DOI: 10.3760/cma.j.cn112137-20230314-00395] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Subscribe] [Scholar Register] [Indexed: 06/27/2023]
Abstract
To investigate the safety and efficacy of "quadri-combination" therapy including maximal transurethral resection of bladder tumor (mTURBT), combined with systemic chemotherapy and immunotherapy, concurrent radiotherapy, and immune maintenance therapy. The clinical data of 8 patients with bladder cancer who could not tolerate or refused radical cystectomy at the Department of Urology, Peking University Cancer Hospital from November 2019 to October 2021 were retrospectively analyzed. There were 5 males and 3 females with a mean age of 69 years. The Eastern Cooperative Oncology Group(ECOG) score was 0 in 6 cases and 1 in 2 cases. There were 5 cases of high-grade urothelial carcinoma (1 case of T3b; 2 cases were T2; 2 cases of T1 stage, with multiple tumors and repeated recurrence), 1 case of high-grade urothelial carcinoma with carcinoma in situ (T1/Tis stage), 1 case of high-grade urothelial carcinoma with squamous differentiation (T3b stage), and 1 case of high-grade urothelial carcinoma with glandular differentiation (T2). All patients underwent "quadri-combination" therapy.The patient's tolerance, success rate of bladder preservation and prognosis were evaluated.The median follow-up time was 22.5 (12-35) months. One patient with high-grade muscle-invasive bladder cancer (T2) received mTURBT, albumin-bound paclitaxel and durvalumab combined therapy for 3 cycles, concurrent radiotherapy, and immune maintenance therapy for 18 months, and the tumor recurrence was found. The pathology was high-grade urothelial carcinoma. Salvage radical cystectomy combined with pelvic lymph node dissection is recommended. The remaining 7 patients were regularly reexamined, and no recurrence or metastasis was found.The 2-year progression-free survival rate was 80%, and the success rate of bladder preservation was 87.5%(7/8). Treatment-related adverse reactions were resolved by symptomatic treatment, and patients' compliance and tolerance were acceptable.The "quadri-combination" bladder-preserving therapy is feasible and well tolerated, but further studies are needed.
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Affiliation(s)
- B A Hong
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Urology, Peking University Cancer Hospital & Institute, Beijing 100142, China
| | - Q Zhao
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Urology, Peking University Cancer Hospital & Institute, Beijing 100142, China
| | - Y P Ji
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Urology, Peking University Cancer Hospital & Institute, Beijing 100142, China
| | - Y D Cao
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Urology, Peking University Cancer Hospital & Institute, Beijing 100142, China
| | - Y Yang
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Urology, Peking University Cancer Hospital & Institute, Beijing 100142, China
| | - N Zhang
- Department of Urology, Beijing Anzhen Hospital, Capital Medical University, Beijing 100029, China
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Zhao HQ, Ma J, Zhang N, Feng T. [The clinical characteristics of Parkinson's disease patients with concomitant periodic limb movements in sleep]. Zhonghua Yi Xue Za Zhi 2023; 103:1793-1796. [PMID: 37305940 DOI: 10.3760/cma.j.cn112137-20230227-00291] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Subscribe] [Scholar Register] [Indexed: 06/13/2023]
Abstract
The current study aimed to investigate the clinical characteristics of Parkinson's disease (PD) patients with concomitant periodic limb movements in sleep (PLMS). The clinical data of 36 PD patients who underwent polysomnography (PSG) in Beijing Tiantan Hospital from October 2018 to July 2022 were collected. Unified Parkinson's Disease Rating Scale 3.0 and Hoehn & Yahr (H-Y) stage were used to evaluate the disease severity. Patients were divided into two groups: the PLMS+group periodic limb movements in sleep index [(PLMSI)≥15 times/h] and the PLMS-group (PLMSI<15 times/h), using the PLMSI 15 times/h as the cut-off value. The clinical characteristics between the two groups were compared. There were 15 patients (42%) in the PLMS+group and 21 patients (58%) in the PLMS-group, among which 12 patients (12/15) in the PLMS+group and 9 patients (42.9%) in the PLMS-group had rapid eye movement sleep behavior disorder (RBD). The rate of RBD in PLMS+group was higher than that in PLMS-group (P<0.05). There was statistically significant difference in the blood folate level between the PLMS-group and PLMS+group [6.20 (5.14, 11.70) ng/ml vs 4.41 (3.07, 5.64) ng/ml] (P<0.01). Folate deficiency was more common in the PLMS+group, while no statistically significant differences were found in homocysteine and ferritin levels (both P>0.05). Four patients in the PLMS+group had falling experience, while 14.3% (3/21) patients in the PLMS-group had falling experience. Patients in the PLMS+group were more likely to fall. The PLMS+group had higher arousal index according to PSG [PLMS-group: 11.90 (9.10, 15.80) times/h; PLMS+group: 21.50 (19.35, 29.90) times/h] (P<0.05). No statistically significant differences in other sleep parameters were detected between the two groups (all P>0.05). Meanwhile, the apnea-hypopnea index (AHI) in both groups was higher than normal (<5 times/h), of which the PLMS-group was 9.80 (4.70, 22.20) times/h and the PLMS+group was 8.20 (1.70, 11.15) times/h, indicating that PD patients were more likely to experience sleep apnea and hypopnea. PD patients with PLMS had lower folate level, higher risk for falls, higher sleep arousal index, more sleep fragmentation, and higher prevalence of RBD.
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Affiliation(s)
- H Q Zhao
- Department of Movement Disorders, Centre of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing 100071, China
| | - J Ma
- Department of Clinical Psychology and Sleep, Beijing Tiantan Hospital, Capital Medical University, Beijing 100071, China
| | - N Zhang
- Department of Clinical Psychology and Sleep, Beijing Tiantan Hospital, Capital Medical University, Beijing 100071, China
| | - T Feng
- Department of Movement Disorders, Centre of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing 100071, China
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Shao R, Yang Z, Zhang W, Zhang N, Zhao Y, Zhang X, Zuo L, Ge S. [Pachymic acid protects against Crohn's disease-like intestinal barrier injury and colitis in miceby suppressingintestinal epithelial cell apoptosis via inhibiting PI3K/AKT signaling]. Nan Fang Yi Ke Da Xue Xue Bao 2023; 43:935-942. [PMID: 37439165 DOI: 10.12122/j.issn.1673-4254.2023.06.08] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Indexed: 07/14/2023]
Abstract
OBJECTIVE To investigate the effect of pachymic acid (PA) against TNBS-induced Crohn's disease (CD)-like colitis in mice and explore the possible mechanism. METHODS Twenty-four C57BL/6J mice were randomized equally into control group, TNBS-induced colitis model group and PA treatment group. PA treatment was administered via intraperitoneal injection at the daily dose of 5 mg/kg for 7 days, and the mice in the control and model groups were treated with saline. After the treatments, the mice were euthanized for examination of the disease activity index (DAI) of colitis, body weight changes, colon length, intestinal inflammation, intestinal barrier function and apoptosis of intestinal epithelial cells, and the expressions of TNF-α, IL-6 and IL-1β in the colonic mucosa were detected using ELISA. The possible treatment targets of PA in CD were predicted by network pharmacology. String platform and Cytoscape 3.7.2 software were used to construct the protein-protein interaction (PPI) network. David database was used to analyze the GO function and KEGG pathway; The phosphorylation of PI3K/AKT in the colonic mucosal was detected with Western blotting. RESULTS PA significantly alleviated colitis in TNBS-treated mice as shown by improvements in the DAI, body weight loss, colon length, and histological inflammation score and lowered levels of TNF-α, IL-6 and IL-1β. PA treatment also significantly improved FITC-dextran permeability, serum I-FABP level and colonic transepithelial electrical resistance, and inhibited apoptosis of the intestinal epithelial cells in TNBS-treated mice. A total of 248 intersection targets were identified between PA and CD, and the core targets included EGFR, HRAS, SRC, MMP9, STAT3, AKT1, CASP3, ALB, HSP90AA1 and HIF1A. GO and KEGG analysis showed that PA negatively regulated apoptosis in close relation with PI3K/AKT signaling. Molecular docking showed that PA had a strong binding ability with AKT1, ALB, EGFR, HSP90AA1, SRC and STAT3. In TNBS-treated mice, PA significantly decreased p-PI3K and p-AKT expressions in the colonic mucosa. CONCLUSION PA ameliorates TNBS-induced intestinal barrier injury in mice by antagonizing apoptosis of intestinal epithelial cells possibly by inhibiting PI3K/AKT signaling.
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Affiliation(s)
- R Shao
- Cardiogram Room, First Affiliated Hospital of Bengbu Medical College, Bengbu 233004, China
| | - Z Yang
- Clinical Medical School, Bengbu 233000, China
- Department of Gastrointestinal Surgery, First Affiliated Hospital of Bengbu Medical College, Bengbu 233004, China
| | - W Zhang
- Department of Clinical Laboratory, First Affiliated Hospital of Bengbu Medical College, Bengbu 233004, China
| | - N Zhang
- Department of Clinical Laboratory, First Affiliated Hospital of Bengbu Medical College, Bengbu 233004, China
| | - Y Zhao
- Clinical Medical School, Bengbu 233000, China
- Anhui Provincial Key Laboratory of Tissue Transplantation, Bengbu 233000, China
| | - X Zhang
- Central Laboratory, First Affiliated Hospital of Bengbu Medical College, Bengbu 233004, China
| | - L Zuo
- Department of Gastrointestinal Surgery, First Affiliated Hospital of Bengbu Medical College, Bengbu 233004, China
| | - S Ge
- Department of Gastrointestinal Surgery, First Affiliated Hospital of Bengbu Medical College, Bengbu 233004, China
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Li J, Wang F, Ma J, Zhang Z, Zhang N, Cui S, Ye Z. A CT-based radiomics nomogram for differentiating ovarian cystadenomas and endometriotic cysts. Clin Radiol 2023:S0009-9260(23)00215-5. [PMID: 37336676 DOI: 10.1016/j.crad.2023.05.004] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2022] [Revised: 04/25/2023] [Accepted: 05/05/2023] [Indexed: 06/21/2023]
Abstract
AIM To construct and validate a computed tomography (CT)-based radiomics nomogram integrating radiomics signature and clinical factors to distinguish ovarian cystadenomas and endometriotic cysts. MATERIALS AND METHODS A total of 287 patients with ovarian cystadenomas (n=196) or endometriotic cysts (n=91) were divided randomly into a training cohort (n=200) and a validation cohort (n=87). Radiomics features based on the portal venous phase of CT images were extracted by PyRadiomics. The least absolute shrinkage and selection operation regression was applied to select the significant features and develop the radiomics signature. A radiomics score (rad-score) was calculated. The clinical model was built by the significant clinical factors. Multivariate logistic regression analysis was employed to construct the radiomics nomogram based on significant clinical factors and rad-score. The diagnostic performances of the radiomics nomogram, radiomics signature, and clinical model were evaluated and compared in the training and validation cohorts. Diagnostic confusion matrices of these models were calculated for the validation cohort and compared with those of the radiologists. RESULTS Seventeen radiomics features from CT images were used to build the radiomics signature. The radiomics nomogram incorporating cancer antigen 125 (CA-125) level and rad-score showed the best performance in both the training and validation cohorts with AUCs of 0.925 (95% confidence interval [CI]: 0.885-0.965), and 0.942 (95% CI: 0.891-0.993), respectively. The accuracy of radiomics nomogram in the confusion matrix outperformed the radiologists. CONCLUSIONS The radiomics nomogram performed well for differentiating ovarian cystadenomas and endometriotic cysts, and may help in clinical decision-making process.
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Affiliation(s)
- J Li
- Department of Radiology, First Affiliated Hospital of Hebei North University, Zhangjiakou 075000, China; Department of Radiology, National Clinical Research Center for Cancer, Tianjin Key Laboratory of Cancer Prevention and Therapy, Tianjin's Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin 300060, China
| | - F Wang
- Department of Radiology, National Clinical Research Center for Cancer, Tianjin Key Laboratory of Cancer Prevention and Therapy, Tianjin's Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin 300060, China
| | - J Ma
- Department of Radiology, National Clinical Research Center for Cancer, Tianjin Key Laboratory of Cancer Prevention and Therapy, Tianjin's Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin 300060, China
| | - Z Zhang
- Department of Radiology, Tianjin Medical University General Hospital, Tianjin 300052, China
| | - N Zhang
- Department of Radiology, Tianjin Medical University General Hospital, Tianjin 300052, China
| | - S Cui
- Department of Radiology, First Affiliated Hospital of Hebei North University, Zhangjiakou 075000, China.
| | - Z Ye
- Department of Radiology, National Clinical Research Center for Cancer, Tianjin Key Laboratory of Cancer Prevention and Therapy, Tianjin's Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin 300060, China.
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Crous PW, Osieck ER, Shivas RG, Tan YP, Bishop-Hurley SL, Esteve-Raventós F, Larsson E, Luangsa-Ard JJ, Pancorbo F, Balashov S, Baseia IG, Boekhout T, Chandranayaka S, Cowan DA, Cruz RHSF, Czachura P, De la Peña-Lastra S, Dovana F, Drury B, Fell J, Flakus A, Fotedar R, Jurjević Ž, Kolecka A, Mack J, Maggs-Kölling G, Mahadevakumar S, Mateos A, Mongkolsamrit S, Noisripoom W, Plaza M, Overy DP, Piątek M, Sandoval-Denis M, Vauras J, Wingfield MJ, Abell SE, Ahmadpour A, Akulov A, Alavi F, Alavi Z, Altés A, Alvarado P, Anand G, Ashtekar N, Assyov B, Banc-Prandi G, Barbosa KD, Barreto GG, Bellanger JM, Bezerra JL, Bhat DJ, Bilański P, Bose T, Bozok F, Chaves J, Costa-Rezende DH, Danteswari C, Darmostuk V, Delgado G, Denman S, Eichmeier A, Etayo J, Eyssartier G, Faulwetter S, Ganga KGG, Ghosta Y, Goh J, Góis JS, Gramaje D, Granit L, Groenewald M, Gulden G, Gusmão LFP, Hammerbacher A, Heidarian Z, Hywel-Jones N, Jankowiak R, Kaliyaperumal M, Kaygusuz O, Kezo K, Khonsanit A, Kumar S, Kuo CH, Læssøe T, Latha KPD, Loizides M, Luo SM, Maciá-Vicente JG, Manimohan P, Marbach PAS, Marinho P, Marney TS, Marques G, Martín MP, Miller AN, Mondello F, Moreno G, Mufeeda KT, Mun HY, Nau T, Nkomo T, Okrasińska A, Oliveira JPAF, Oliveira RL, Ortiz DA, Pawłowska J, Pérez-De-Gregorio MÀ, Podile AR, Portugal A, Privitera N, Rajeshkumar KC, Rauf I, Rian B, Rigueiro-Rodríguez A, Rivas-Torres GF, Rodriguez-Flakus P, Romero-Gordillo M, Saar I, Saba M, Santos CD, Sarma PVSRN, Siquier JL, Sleiman S, Spetik M, Sridhar KR, Stryjak-Bogacka M, Szczepańska K, Taşkın H, Tennakoon DS, Thanakitpipattana D, Trovão J, Türkekul I, van Iperen AL, van 't Hof P, Vasquez G, Visagie CM, Wingfield BD, Wong PTW, Yang WX, Yarar M, Yarden O, Yilmaz N, Zhang N, Zhu YN, Groenewald JZ. Fungal Planet description sheets: 1478-1549. Persoonia 2023; 50:158-310. [PMID: 38567263 PMCID: PMC10983837 DOI: 10.3767/persoonia.2023.50.05] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 04/01/2023] [Accepted: 05/10/2023] [Indexed: 04/04/2024]
Abstract
Novel species of fungi described in this study include those from various countries as follows: Australia, Aschersonia mackerrasiae on whitefly, Cladosporium corticola on bark of Melaleuca quinquenervia, Penicillium nudgee from soil under Melaleuca quinquenervia, Pseudocercospora blackwoodiae on leaf spot of Persoonia falcata, and Pseudocercospora dalyelliae on leaf spot of Senna alata. Bolivia, Aspicilia lutzoniana on fully submersed siliceous schist in high-mountain streams, and Niesslia parviseta on the lower part and apothecial discs of Erioderma barbellatum on a twig. Brazil, Cyathus bonsai on decaying wood, Geastrum albofibrosum from moist soil with leaf litter, Laetiporus pratigiensis on a trunk of a living unknown hardwood tree species, and Scytalidium synnematicum on dead twigs of unidentified plant. Bulgaria, Amanita abscondita on sandy soil in a plantation of Quercus suber. Canada, Penicillium acericola on dead bark of Acer saccharum, and Penicillium corticola on dead bark of Acer saccharum. China, Colletotrichum qingyuanense on fruit lesion of Capsicum annuum. Denmark, Helminthosphaeria leptospora on corticioid Neohypochnicium cremicolor. Ecuador (Galapagos), Phaeosphaeria scalesiae on Scalesia sp. Finland, Inocybe jacobssonii on calcareous soils in dry forests and park habitats. France, Cortinarius rufomyrrheus on sandy soil under Pinus pinaster, and Periconia neominutissima on leaves of Poaceae. India, Coprinopsis fragilis on decaying bark of logs, Filoboletus keralensis on unidentified woody substrate, Penicillium sankaranii from soil, Physisporinus tamilnaduensis on the trunk of Azadirachta indica, and Poronia nagaraholensis on elephant dung. Iran, Neosetophoma fici on infected leaves of Ficus elastica. Israel, Cnidariophoma eilatica (incl. Cnidariophoma gen. nov.) from Stylophora pistillata. Italy, Lyophyllum obscurum on acidic soil. Namibia, Aureobasidium faidherbiae on dead leaf of Faidherbia albida, and Aureobasidium welwitschiae on dead leaves of Welwitschia mirabilis. Netherlands, Gaeumannomycella caricigena on dead culms of Carex elongata, Houtenomyces caricicola (incl. Houtenomyces gen. nov.) on culms of Carex disticha, Neodacampia ulmea (incl. Neodacampia gen. nov.) on branch of Ulmus laevis, Niesslia phragmiticola on dead standing culms of Phragmites australis, Pseudopyricularia caricicola on culms of Carex disticha, and Rhodoveronaea nieuwwulvenica on dead bamboo sticks. Norway, Arrhenia similis half-buried and moss-covered pieces of rotting wood in grass-grown path. Pakistan, Mallocybe ahmadii on soil. Poland, Beskidomyces laricis (incl. Beskidomyces gen. nov.) from resin of Larix decidua ssp. polonica, Lapidomyces epipinicola from sooty mould community on Pinus nigra, and Leptographium granulatum from a gallery of Dendroctonus micans on Picea abies. Portugal, Geoglossum azoricum on mossy areas of laurel forest areas planted with Cryptomeria japonica, and Lunasporangiospora lusitanica from a biofilm covering a biodeteriorated limestone wall. Qatar, Alternaria halotolerans from hypersaline sea water, and Alternaria qatarensis from water sample collected from hypersaline lagoon. South Africa, Alfaria thamnochorti on culm of Thamnochortus fraternus, Knufia aloeicola on Aloe gariepensis, Muriseptatomyces restionacearum (incl. Muriseptatomyces gen. nov.) on culms of Restionaceae, Neocladosporium arctotis on nest of cases of bag worm moths (Lepidoptera, Psychidae) on Arctotis auriculata, Neodevriesia scadoxi on leaves of Scadoxus puniceus, Paraloratospora schoenoplecti on stems of Schoenoplectus lacustris, Tulasnella epidendrea from the roots of Epidendrum × obrienianum, and Xenoidriella cinnamomi (incl. Xenoidriella gen. nov.) on leaf of Cinnamomum camphora. South Korea, Lemonniera fraxinea on decaying leaves of Fraxinus sp. from pond. Spain, Atheniella lauri on the bark of fallen trees of Laurus nobilis, Halocryptovalsa endophytica from surface-sterilised, asymptomatic roots of Salicornia patula, Inocybe amygdaliolens on soil in mixed forest, Inocybe pityusarum on calcareous soil in mixed forest, Inocybe roseobulbipes on acidic soils, Neonectria borealis from roots of Vitis berlandieri × Vitis rupestris, Sympoventuria eucalyptorum on leaves of Eucalyptus sp., and Tuber conchae from soil. Sweden, Inocybe bidumensis on calcareous soil. Thailand, Cordyceps sandindaengensis on Lepidoptera pupa, buried in soil, Ophiocordyceps kuchinaraiensis on Coleoptera larva, buried in soil, and Samsoniella winandae on Lepidoptera pupa, buried in soil. Taiwan region (China), Neophaeosphaeria livistonae on dead leaf of Livistona rotundifolia. Türkiye, Melanogaster anatolicus on clay loamy soils. UK, Basingstokeomyces allii (incl. Basingstokeomyces gen. nov.) on leaves of Allium schoenoprasum. Ukraine, Xenosphaeropsis corni on recently dead stem of Cornus alba. USA, Nothotrichosporon aquaticum (incl. Nothotrichosporon gen. nov.) from water, and Periconia philadelphiana from swab of coil surface. Morphological and culture characteristics for these new taxa are supported by DNA barcodes. Citation: Crous PW, Osieck ER, Shivas RG, et al. 2023. Fungal Planet description sheets: 1478-1549. Persoonia 50: 158- 310. https://doi.org/10.3767/persoonia.2023.50.05.
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Affiliation(s)
- P W Crous
- Westerdijk Fungal Biodiversity Institute, P.O. Box 85167, 3508AD Utrecht, The Netherlands
- Department of Biochemistry, Genetics and Microbiology, Forestry and Agricultural Biotechnology Institute (FABI), University of Pretoria, Pretoria, South Africa
| | - E R Osieck
- Jkvr. C.M. van Asch van Wijcklaan 19, 3972 ST Driebergen-Rijsenburg, Netherlands
| | - R G Shivas
- Centre for Crop Health, University of Southern Queensland, Toowoomba 4350, Queensland, Australia
| | - Y P Tan
- Queensland Plant Pathology Herbarium, Department of Agriculture and Fisheries, Dutton Park 4102, Queensland, Australia
| | - S L Bishop-Hurley
- Queensland Plant Pathology Herbarium, Department of Agriculture and Fisheries, Dutton Park 4102, Queensland, Australia
| | - F Esteve-Raventós
- Universidad de Alcalá, Facultad de Ciencias, Departamento de Ciencias de la Vida (Botánica). 28805 Alcalá de Henares, Madrid, Spain
| | - E Larsson
- Biological and Environmental Sciences, University of Gothenburg, and Gothenburg Global Biodiversity Centre, Box 461, SE40530 Göteborg, Sweden
| | - J J Luangsa-Ard
- BIOTEC, National Science and Technology Development Agency (NSTDA), 111 Thailand Science Park, Phahonyothin Road, Khlong Nueng, Khlong Luang, Pathum Thani, 12120, Thailand
| | - F Pancorbo
- Sociedad Micológica de Madrid, Real Jardín Botánico, C/ Claudio Moyano 1, 28014 Madrid, Spain
| | - S Balashov
- EMSLAnalytical, Inc., 200 Route 130 North, Cinnaminson, NJ 08077 USA
| | - I G Baseia
- Departamento de Botânica e Zoologia, Universidade Federal do Rio Grande do Norte, Natal, Rio Grande do Norte, Brazil
| | - T Boekhout
- College of Science, King Saud University, P.O. Box 2455, Riyadh-11451, Saudi Arabia
| | - S Chandranayaka
- Department of Studies in Biotechnology, University of Mysore, Manasagangotri, Mysore - 570006, Karnataka, India
| | - D A Cowan
- Centre for Microbial Ecology and Genomics, Department of Biochemistry, Genetics and Microbiology, University of Pretoria, Private Bag X20, Hatfield 0028, Pretoria, South Africa
| | - R H S F Cruz
- Centro das Ciências Biológicas e da Saúde, Universidade Federal do Oeste da Bahia, Barreiras, 47810-047, Brazil
| | - P Czachura
- W. Szafer Institute of Botany, Polish Academy of Sciences, Lubicz 46, PL-31-512 Kraków, Poland
| | | | - F Dovana
- Via Quargnento, 17, 15029 Solero, Italy
| | - B Drury
- Queensland College of Teachers, Mount Alvernia College, Kedron 4031, Queensland, Australia
| | - J Fell
- Rosenstiel School of Marine and Atmospheric Sciences, University of Miami, Key Biscayne, Florida, USA
| | - A Flakus
- W. Szafer Institute of Botany, Polish Academy of Sciences, Lubicz 46, PL-31-512 Kraków, Poland
| | - R Fotedar
- Department of Genetic Engineering, Biotechnology Centre, Ministry of Environment, Doha, State of Qatar
| | - Ž Jurjević
- EMSLAnalytical, Inc., 200 Route 130 North, Cinnaminson, NJ 08077 USA
| | - A Kolecka
- Westerdijk Fungal Biodiversity Institute, P.O. Box 85167, 3508AD Utrecht, The Netherlands
| | - J Mack
- Ottawa Research & Development Centre, Agriculture &AgriFood Canada, 960 Carling Ave., Ottawa, Ontario, Canada, K1A 0C6
| | - G Maggs-Kölling
- Gobabeb Namib Research Institute, Walvis Bay, Namibia
- Unit for Environmental Sciences and Management, North-West University, P. Bag X1290, Potchefstroom, 2520, South Africa
| | - S Mahadevakumar
- Forest Pathology Department, Forest Health Division, KSCSTE-Kerala Forest Research Institute, Peechi - 680653, Thrissur, Kerala, India
- Botanical Survey of India, Andaman and Nicobar Regional Center, Haddo - 744102, Port Blair, South Andaman, India
| | - A Mateos
- Sociedad Micológica Extremeña, C/ Sagitario 14, 10001 Cáceres, Spain
| | - S Mongkolsamrit
- BIOTEC, National Science and Technology Development Agency (NSTDA), 111 Thailand Science Park, Phahonyothin Road, Khlong Nueng, Khlong Luang, Pathum Thani, 12120, Thailand
| | - W Noisripoom
- BIOTEC, National Science and Technology Development Agency (NSTDA), 111 Thailand Science Park, Phahonyothin Road, Khlong Nueng, Khlong Luang, Pathum Thani, 12120, Thailand
| | - M Plaza
- C/ La Angostura, 20, 11370 Los Barrios, Cádiz, Spain
| | - D P Overy
- Ottawa Research & Development Centre, Agriculture &AgriFood Canada, 960 Carling Ave., Ottawa, Ontario, Canada, K1A 0C6
| | - M Piątek
- W. Szafer Institute of Botany, Polish Academy of Sciences, Lubicz 46, PL-31-512 Kraków, Poland
| | - M Sandoval-Denis
- Westerdijk Fungal Biodiversity Institute, P.O. Box 85167, 3508AD Utrecht, The Netherlands
| | - J Vauras
- Biological Collections of Åbo Akademi University, Biodiversity Unit, Herbarium, FI-20014 University of Turku, Finland
| | - M J Wingfield
- Department of Biochemistry, Genetics and Microbiology, Forestry and Agricultural Biotechnology Institute (FABI), University of Pretoria, Pretoria, South Africa
| | - S E Abell
- Australian Tropical Herbarium, James Cook University, Smithfield 4878, Queensland, Australia
| | - A Ahmadpour
- Higher Education Centre of Shahid Bakeri, Urmia University, Miyandoab, Iran
| | - A Akulov
- Department of Mycology and Plant Resistance, V. N. Karazin Kharkiv National University, Maidan Svobody 4, 61022 Kharkiv, Ukraine
| | - F Alavi
- Higher Education Centre of Shahid Bakeri, Urmia University, Miyandoab, Iran
| | - Z Alavi
- Higher Education Centre of Shahid Bakeri, Urmia University, Miyandoab, Iran
| | - A Altés
- Universidad de Alcalá, Facultad de Ciencias, Departamento de Ciencias de la Vida (Botánica). 28805 Alcalá de Henares, Madrid, Spain
| | - P Alvarado
- ALVALAB, Dr. Fernando Bongera st., Severo Ochoa bldg. S1.04, 33006 Oviedo, Spain
| | - G Anand
- National Fungal Culture Collection of India (NFCCI), Biodiversity and Palaeobiology (Fungi) group, MACS Agharkar Research Institute, GG Agharkar Road, Pune, Maharashtra State 411004, India
| | - N Ashtekar
- National Fungal Culture Collection of India (NFCCI), Biodiversity and Palaeobiology (Fungi) group, MACS Agharkar Research Institute, GG Agharkar Road, Pune, Maharashtra State 411004, India
| | - B Assyov
- Institute of Biodiversity and Ecosystem Research, Bulgarian Academy of Sciences, 2 Gagarin Str., 1113 Sofia, Bulgaria
| | - G Banc-Prandi
- Laboratory for Biological Geochemistry, School of Architecture, Civil and Environmental Engineering, École Polytechnique Fédérale de Lausanne (EPFL), 1015, Lausanne, Switzerland
| | - K D Barbosa
- Programa de Pós-Graduação em Sistemática e Evolução, Centro de Biociências, Universidade Federal do Rio Grande do Norte, Av. Senador Salgado Filho, 3000, 59072-970, Natal, Rio Grande do Norte, Brazil
| | - G G Barreto
- Department of Biology, State University of Feira de Santana, Transnordestina s/n, Novo Horizonte, 44036-900, Feira de Santana, Brazil
| | - J-M Bellanger
- CEFE, CNRS, Université de Montpellier, EPHE, IRD, INSERM, Campus CNRS, 1919 Route de Mende, F-34293 Montpellier, France
| | - J L Bezerra
- Federal University of Pernambuco, Pernambuco, Brazil
| | - D J Bhat
- College of Science, King Saud University, P.O. Box 2455, Riyadh-11451, Saudi Arabia
| | - P Bilański
- Department of Forest Ecosystems Protection, University of Agriculture in Krakow, Al. 29 Listopada 46, 31-425 Krakow, Poland
| | - T Bose
- Department of Biochemistry, Genetics and Microbiology, Forestry and Agricultural Biotechnology Institute (FABI), University of Pretoria, Pretoria, South Africa
| | - F Bozok
- Department of Biology, Faculty ofArts and Science, Osmaniye KorkutAta University, 80000 Osmaniye, Türkiye
| | - J Chaves
- Universidad San Francisco de Quito USFQ, Colegio de Ciencias Biológicas y Ambientales, Diego de Robles s/n, 170901, Quito, Ecuador
- San Francisco State University, Department of Biology, 1600 Holloway Av, San Francisco CA 94132, USA
| | - D H Costa-Rezende
- Department of Biology, State University of Feira de Santana, Transnordestina s/n, Novo Horizonte, 44036-900, Feira de Santana, Brazil
| | - C Danteswari
- Department of Plant Sciences, University of Hyderabad, Hyderabad, Telangana, India
| | - V Darmostuk
- W. Szafer Institute of Botany, Polish Academy of Sciences, Lubicz 46, PL-31-512 Kraków, Poland
| | - G Delgado
- Eurofins Built Environment, 6110 W. 34th St, Houston, TX 77092, USA
| | - S Denman
- Forest Research, Alice Holt Lodge, Farnham, Surrey, UK
| | - A Eichmeier
- Mendeleum - Institute of Genetics, Mendel University in Brno, Valticka 334, Lednice, 69144, Czech Republic
| | - J Etayo
- Navarro Villoslada 16, 3º cha., E-31003 Pamplona, Navarra, Spain
| | - G Eyssartier
- Institut de systématique, évolution, biodiversité (UMR 7205-MNHN, CNRS, Sorbonne Université, EPHE, Université des Antilles), 45 rue Buffon, F-75005 Paris, France
| | - S Faulwetter
- Department of Geology, University of Patras, 26504 Rio Patras, Greece
| | - K G G Ganga
- Department of Botany, University of Calicut, Kerala, 673 635, India
| | - Y Ghosta
- Department of Plant Protection, Faculty of Agriculture, Urmia University, Urmia, Iran
| | - J Goh
- Fungal Research Team, Microbial Research Department, Nakdonggang National Institute of Biological Resources, Korea
| | - J S Góis
- Programa de Pós-Graduação em Sistemática e Evolução, Centro de Biociências, Universidade Federal do Rio Grande do Norte, Av. Senador Salgado Filho, 3000, 59072-970, Natal, Rio Grande do Norte, Brazil
| | - D Gramaje
- Instituto de Ciencias de la Vid y del Vino (ICVV), CSIC - Universidad de La Rioja - Gobierno de La Rioja, Ctra. LO-20 Salida 13, 26007 Logroño, Spain
| | - L Granit
- Department of Plant Pathology and Microbiology, The Robert H. Smith Faculty of Agriculture Food and Environment, The Hebrew University of Jerusalem, Rehovot, Israel & Interuniversity Institute of Marine Sciences, Eilat, Israel
| | - M Groenewald
- Westerdijk Fungal Biodiversity Institute, P.O. Box 85167, 3508AD Utrecht, The Netherlands
| | - G Gulden
- Natural History Museum, University of Oslo, PO Box 1172 Blindern, NO-0318 Oslo, Norway
| | - L F P Gusmão
- Department of Biology, State University of Feira de Santana, Transnordestina s/n, Novo Horizonte, 44036-900, Feira de Santana, Brazil
| | - A Hammerbacher
- Department of Zoology and Entomology, Forestry and Agricultural Biotechnology Institute (FABI), University of Pretoria, South Africa
| | - Z Heidarian
- Higher Education Centre of Shahid Bakeri, Urmia University, Miyandoab, Iran
| | - N Hywel-Jones
- Zhejiang BioAsia Institute of Life Sciences, Pinghu 314200, Zhejiang, People's Republic of China
| | - R Jankowiak
- Department of Forest Ecosystems Protection, University of Agriculture in Krakow, Al. 29 Listopada 46, 31-425 Krakow, Poland
| | - M Kaliyaperumal
- CAS in Botany, University of Madras, Chennai, Tamil Nadu, India
| | - O Kaygusuz
- Department of Plant and Animal Production, Atabey Vocational School, Isparta University of Applied Sciences, 32670 Isparta, Türkiye
| | - K Kezo
- CAS in Botany, University of Madras, Chennai, Tamil Nadu, India
| | - A Khonsanit
- BIOTEC, National Science and Technology Development Agency (NSTDA), 111 Thailand Science Park, Phahonyothin Road, Khlong Nueng, Khlong Luang, Pathum Thani, 12120, Thailand
| | - S Kumar
- Forest Pathology Department, Forest Health Division, KSCSTE-Kerala Forest Research Institute, Peechi - 680653, Thrissur, Kerala, India
| | - C H Kuo
- Department of Plant Medicine, National Chiayi University, 300 Syuefu Road, Chiayi City 60004, Taiwan
| | - T Læssøe
- Globe Institute/Department of Biology, University of Copenhagen, Universitetsparken 15, 2100 Copenhagen Ø, Denmark
| | - K P D Latha
- Department of Botany, University of Calicut, Kerala, 673 635, India
| | | | - S M Luo
- University of Sydney, Plant Breeding Institute, 107 Cobbitty Rd, Cobbitty, New South Wales, Australia
| | - J G Maciá-Vicente
- Plant Ecology and Nature Conservation, Wageningen University & Research, P.O. Box 47, 6700 AA Wageningen, The Netherlands
- Department of Microbial Ecology, Netherlands Institute for Ecology (NIOO-KNAW), P.O. Box 50, 6700 AB Wageningen, The Netherlands
| | - P Manimohan
- Department of Botany, University of Calicut, Kerala, 673 635, India
| | - P A S Marbach
- Recôncavo da Bahia Federal University, Bahia, Brazil
| | - P Marinho
- Departamento de Biologia Celular e Genética, Universidade Federal do Rio Grande do Norte, Natal, Rio Grande do Norte, Brazil
| | - T S Marney
- Queensland Plant Pathology Herbarium, Department of Agriculture and Fisheries, Dutton Park 4102, Queensland, Australia
| | - G Marques
- CITAB-University of Trás-os-Montes and Alto Douro, 5000-801 Vila Real, Portugal
| | - M P Martín
- Departamento de Micología, Real Jardín Botánico RJB-CSIC, Plaza de Murillo 2, 28014 Madrid, Spain
| | - A N Miller
- University of Illinois Urbana-Champaign, Illinois Natural History Survey, 1816 South Oak Street, Champaign, Illinois, 61820, USA
| | - F Mondello
- Via B. da Neocastro, 26, 98123 Messina, Italy
| | - G Moreno
- Universidad de Alcalá, Facultad de Ciencias, Departamento de Ciencias de la Vida (Botánica). 28805 Alcalá de Henares, Madrid, Spain
| | - K T Mufeeda
- Forest Pathology Department, Forest Health Division, KSCSTE-Kerala Forest Research Institute, Peechi - 680653, Thrissur, Kerala, India
| | - H Y Mun
- Fungal Research Team, Microbial Research Department, Nakdonggang National Institute of Biological Resources, Korea
| | - T Nau
- Institute of Ecology, Evolution and Diversity, Goethe University Frankfurt, Max-von-Laue-Str. 13, 60438 Frankfurt am Main, Germany
| | - T Nkomo
- Department of Biochemistry, Genetics and Microbiology, Forestry and Agricultural Biotechnology Institute (FABI), University of Pretoria, Pretoria, South Africa
| | - A Okrasińska
- Institute of Evolutionary Biology, Faculty of Biology, Biological and Chemical Research Centre, University of Warsaw, ul. Zwirki i Wigury 101, 02-089 Warsaw, Poland
| | | | - R L Oliveira
- Programa de Pós-Graduação em Sistemática e Evolução, Centro de Biociências, Universidade Federal do Rio Grande do Norte, Av. Senador Salgado Filho, 3000, 59072-970, Natal, Rio Grande do Norte, Brazil
| | - D A Ortiz
- Universidad San Francisco de Quito USFQ, Galapagos Science Center GSC, San Cristóbal 200101, Galápagos, Ecuador
| | - J Pawłowska
- Institute of Evolutionary Biology, Faculty of Biology, Biological and Chemical Research Centre, University of Warsaw, ul. Zwirki i Wigury 101, 02-089 Warsaw, Poland
| | | | - A R Podile
- Department of Plant Sciences, University of Hyderabad, Hyderabad, Telangana, India
| | - A Portugal
- Centre for Functional Ecology, Department of Life Sciences, University of Coimbra, 3004-531 Coimbra, Portugal
- Fitolab - Laboratory for Phytopathology, Instituto Pedro Nunes, 3030-199 Coimbra, Portugal
| | - N Privitera
- Associazione Micologica Bresadola Gruppo di Catania, Via Macallè 18, I-95125 Catania, Italy
| | - K C Rajeshkumar
- National Fungal Culture Collection of India (NFCCI), Biodiversity and Palaeobiology (Fungi) group, MACS Agharkar Research Institute, GG Agharkar Road, Pune, Maharashtra State 411004, India
| | - I Rauf
- Department of Plant Sciences, Quaid-i-Azam University, 45320, Islamabad, Pakistan
| | - B Rian
- Natural History Museum, University of Oslo, PO Box 1172 Blindern, NO-0318 Oslo, Norway
| | | | - G F Rivas-Torres
- Universidad San Francisco de Quito USFQ, Colegio de Ciencias Biológicas y Ambientales, Diego de Robles s/n, 170901, Quito, Ecuador
- Geography, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
- Universidad San Francisco de Quito USFQ, Galapagos Science Center GSC, San Cristóbal 200101, Galápagos, Ecuador
| | - P Rodriguez-Flakus
- W. Szafer Institute of Botany, Polish Academy of Sciences, Lubicz 46, PL-31-512 Kraków, Poland
| | | | - I Saar
- Institute of Ecology and Earth Sciences, University of Tartu, J. Liivi Street 2, 50409 Tartu, Estonia
| | - M Saba
- Department of Plant Sciences, Quaid-i-Azam University, 45320, Islamabad, Pakistan
| | - C D Santos
- Federal Institute of the Sertão Pernambucano, Pernambuco, Brazil
| | - P V S R N Sarma
- Department of Plant Sciences, University of Hyderabad, Hyderabad, Telangana, India
| | - J L Siquier
- Interdisciplinary Ecology Group, University of the Balearic Islands, crtra. to Valldemossa km 7.5, 07122 Mallorca, Spain
| | - S Sleiman
- Project Manager, Council of Environment, Akkar, North Lebanon
| | - M Spetik
- Mendeleum - Institute of Genetics, Mendel University in Brno, Valticka 334, Lednice, 69144, Czech Republic
| | - K R Sridhar
- Department of Biosciences, Mangalore University, Mangalagangotri, Mangalore - 574199, Karnataka, India
| | - M Stryjak-Bogacka
- W. Szafer Institute of Botany, Polish Academy of Sciences, Lubicz 46, PL-31-512 Kraków, Poland
| | - K Szczepańska
- Department of Botany and Plant Ecology, Wrocław University of Environmental and Life Sciences, pl. Grunwaldzki 24a, PL-50-363 Wrocław, Poland
| | - H Taşkın
- Department of Horticulture, Faculty of Agriculture, Cukurova University, 01330 Adana, Türkiye
| | - D S Tennakoon
- Faculty of Science, Department of Biology, Chiang Mai University, 50200, Chiang Mai, Thailand
| | - D Thanakitpipattana
- BIOTEC, National Science and Technology Development Agency (NSTDA), 111 Thailand Science Park, Phahonyothin Road, Khlong Nueng, Khlong Luang, Pathum Thani, 12120, Thailand
| | - J Trovão
- Centre for Functional Ecology, Department of Life Sciences, University of Coimbra, 3004-531 Coimbra, Portugal
| | - I Türkekul
- Department of Biology, Faculty of Science and Arts, Gaziosmanpaşa University, 60010 Tokat, Türkiye
| | - A L van Iperen
- Westerdijk Fungal Biodiversity Institute, P.O. Box 85167, 3508AD Utrecht, The Netherlands
| | - P van 't Hof
- Universidad San Francisco de Quito USFQ, Colegio de Ciencias Biológicas y Ambientales, Diego de Robles s/n, 170901, Quito, Ecuador
- Universidad San Francisco de Quito USFQ, Galapagos Science Center GSC, San Cristóbal 200101, Galápagos, Ecuador
| | - G Vasquez
- Department of Biology, Geology and Environmental Science, University of Catania, Via A. Longo 19, I-95125 Catania, Italy
| | - C M Visagie
- Department of Biochemistry, Genetics and Microbiology, Forestry and Agricultural Biotechnology Institute (FABI), University of Pretoria, Pretoria, South Africa
| | - B D Wingfield
- Department of Biochemistry, Genetics and Microbiology, Forestry and Agricultural Biotechnology Institute (FABI), University of Pretoria, Pretoria, South Africa
| | - P T W Wong
- University of Sydney, Plant Breeding Institute, 107 Cobbitty Rd, Cobbitty, New South Wales, Australia
| | - W X Yang
- College of Plant Protection, Hebei Agricultural University, 289 Lingyusi Street, Baoding, Hebei Province, China
| | - M Yarar
- Department of Biotechnology, Institute of Natural and Applied Sciences, Cukurova University, 01330 Adana, Türkiye
| | - O Yarden
- Department of Plant Pathology and Microbiology, The Robert H. Smith Faculty of Agriculture Food and Environment, The Hebrew University of Jerusalem, Rehovot, Israel & Interuniversity Institute of Marine Sciences, Eilat, Israel
| | - N Yilmaz
- Department of Biochemistry, Genetics and Microbiology, Forestry and Agricultural Biotechnology Institute (FABI), University of Pretoria, Pretoria, South Africa
| | - N Zhang
- College of Plant Protection, Hebei Agricultural University, 289 Lingyusi Street, Baoding, Hebei Province, China
| | - Y N Zhu
- College of Plant Protection, Hebei Agricultural University, 289 Lingyusi Street, Baoding, Hebei Province, China
| | - J Z Groenewald
- Westerdijk Fungal Biodiversity Institute, P.O. Box 85167, 3508AD Utrecht, The Netherlands
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Liu JH, Xie HK, Su J, Zhu Z, Pan EC, Lu Y, Wan FP, Yan QY, Zhang N, Gu SJ, Wu M, Zhou JY, Shen C. [The distribution of blood pressure and associated factors of the elderly with type 2 diabetes in Jiangsu Province]. Zhonghua Yu Fang Yi Xue Za Zhi 2023; 57:614-625. [PMID: 37165808 DOI: 10.3760/cma.j.cn112150-20221111-01101] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Subscribe] [Scholar Register] [Indexed: 05/12/2023]
Abstract
Objective: To investigate the distribution of blood pressure and analyze the associated factors of blood pressure of the elderly with type 2 diabetes in Jiangsu Province. Methods: The elderly over 60 years old participants with type 2 diabetes in the communities of Huai'an City and Changshu City, Jiangsu Province were selected in this study. They were divided into two groups: taking antihypertensive drugs and not taking antihypertensive drugs. The demographic characteristics, such as age and sex, and relevant factors were collected by questionnaire. The systolic blood pressure (SBP) and diastolic blood pressure (DBP) were measured by physical examination. The percentile of SBP and DBP in each age group of men and women were described. The kernel density estimation curve was used to show the blood pressure distribution. The trend of blood pressure with age was fitted by locally weighted regression. The logistic regression model was used to analyze relevant factors of blood pressure. Results: A total of 12 949 participants were included in this study, including 7 775 patients in the antihypertensive drug group and 5 174 patients in the group without antihypertensive drugs. The SBP of participants was concentrated at 140-160 mmHg, and their DBP was concentrated at 75-85 mmHg. There were significant differences in the distribution of blood pressure among the subgroups of body mass index (BMI) and rural areas whether taking antihypertensive drugs and not. For participants aged under 80 years old, the SBP showed an increasing trend with age and the DBP showed a decreasing trend with age. Age, BMI ≥24 kg/m2, fasting blood glucose ≥7.0 mmol/L, living in rural areas and no smoking were influencing factors of the elevated SBP; BMI ≥24 kg/m2, male, living in rural areas, no smoking, drinking alcohol and not receiving drug hypoglycemic treatment were influencing factors of the elevated DBP. Conclusion: The SBP of older diabetic adults in Jiangsu Province is at a high level, and the distribution of blood pressure is significantly different between men and women in taking antihypertensive drugs group. The SBP presents a rising trend and the DBP is decreasing at the age of 60-80 years. The blood pressure level of this population are mainly affected by age, BMI, urban and rural areas, smoking.
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Affiliation(s)
- J H Liu
- Department of Epidemiology, School of Public Health, Nanjing Medical University, Nanjing 211166, China
| | - H K Xie
- Department of Epidemiology, School of Public Health, Nanjing Medical University, Nanjing 211166, China
| | - J Su
- Department of Non-communicable Chronic Disease Control, Jiangsu Provincial Center for Disease Control and Prevention, Nanjing 210009, China
| | - Z Zhu
- Department of Non-communicable Chronic Disease Control, Jiangsu Provincial Center for Disease Control and Prevention, Nanjing 210009, China
| | - E C Pan
- Center for Disease Control and Prevention of Huai'an City, Huai'an 223002, China
| | - Y Lu
- Department of Non-communicable Chronic Disease Control, Center for Disease Control and Prevention of Suzhou City, Suzhou 215004, China
| | - F P Wan
- Department of Non-communicable Chronic Disease Control, Center for Disease Control and Prevention of Qingjiangpu District in Huai'an City, Huai'an 223021, China
| | - Q Y Yan
- Department of Non-communicable Chronic Disease Control, Center for Disease Control and Prevention of Huai'an District in Huai'an City, Huai'an 223229, China
| | - N Zhang
- Center for Disease Control and Prevention of Changshu and Suzhou City, Suzhou 215500, China
| | - S J Gu
- Center for Disease Control and Prevention of Changshu and Suzhou City, Suzhou 215500, China
| | - M Wu
- Department of Non-communicable Chronic Disease Control, Jiangsu Provincial Center for Disease Control and Prevention, Nanjing 210009, China
| | - J Y Zhou
- Department of Non-communicable Chronic Disease Control, Jiangsu Provincial Center for Disease Control and Prevention, Nanjing 210009, China
| | - C Shen
- Department of Epidemiology, School of Public Health, Nanjing Medical University, Nanjing 211166, China
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Hou JG, Zhang N, Chen GD. Factors affecting cement leakage in percutaneous vertebroplasty: a retrospective cohort study of 309 patients. Eur Rev Med Pharmacol Sci 2023; 27:3877-3886. [PMID: 37203859 DOI: 10.26355/eurrev_202305_32293] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 05/20/2023]
Abstract
OBJECTIVE Percutaneous vertebroplasty has been widely applied as a treatment for osteoporotic vertebral compression fracture. However, the incidence of cement leakage is high. The purpose of study is to identify the independent risk factors for cement leakage. PATIENTS AND METHODS A total of 309 patients who suffered from osteoporotic vertebral compression fracture (OVCF) and underwent percutaneous vertebroplasty (PVP) were enrolled in this respective cohort study from January 2014 to January 2020. Clinical and radiological characteristics were assessed to identify independent predictors for each type of cement leakage, including age, gender, course of disease, fracture level, morphology of vertebral fracture, fracture severity, cortical disruption in vertebral wall or endplate, fracture line connected with basivertebral foramen, type of cement dispersion, and intravertebral cement volume. RESULTS In leakage of B-type, fracture line connected with basivertebral foramen was identified as an independent risk factor [Adjusted OR: 2.837, 95% CI: (1.295, 6.211), p = 0.009]. For leakage of C-type, acute course of the disease, more severity of the fractured body, wall disruption and intravertebral cement volume (IVCV) were identified as independent risk factors [Adjusted OR: 0.409, 95% CI: (0.257, 0.650), p = 0.000]; [Adjusted OR: 3.128, 95% CI: (2.202, 4.442), p = 0.000]; [Adjusted OR: 6.387, 95% CI: (3.077, 13.258), p = 0.000]; [Adjusted OR: 1.619, 95% CI: (1.308, 2.005), p = 0.000]. Regarding leakage of D-type, biconcave fracture and endplate disruption were identified as independent risk factors [Adjusted OR: 6.499, 95% CI: (2.752, 15.348), p = 0.000]; [Adjusted OR: 3.037, 95% CI: (1.421, 6.492), p = 0.004]. For S-type, fracture in thoracic level and less severity of the fractured body were identified as independent risk factors [Adjusted OR: 0.105, 95% CI: (0.059, 0.188), p = 0.000]; [Adjusted OR: 0.580, 95% CI: (0.436, 0.773), p = 0.000]. CONCLUSIONS Cement leakage was very common with PVP. Each cement leakage had its own influence factors. Preoperative identification of above influence factors for cement leakage could avoid the occurrence of severe sequelae.
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Affiliation(s)
- J-G Hou
- Department of Orthopedics, The First Hospital of Qinhuangdao, Qinhuangdao, Hebei, China.
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Grandjean J, Desrosiers-Gregoire G, Anckaerts C, Angeles-Valdez D, Ayad F, Barrière DA, Blockx I, Bortel A, Broadwater M, Cardoso BM, Célestine M, Chavez-Negrete JE, Choi S, Christiaen E, Clavijo P, Colon-Perez L, Cramer S, Daniele T, Dempsey E, Diao Y, Doelemeyer A, Dopfel D, Dvořáková L, Falfán-Melgoza C, Fernandes FF, Fowler CF, Fuentes-Ibañez A, Garin CM, Gelderman E, Golden CEM, Guo CCG, Henckens MJAG, Hennessy LA, Herman P, Hofwijks N, Horien C, Ionescu TM, Jones J, Kaesser J, Kim E, Lambers H, Lazari A, Lee SH, Lillywhite A, Liu Y, Liu YY, López-Castro A, López-Gil X, Ma Z, MacNicol E, Madularu D, Mandino F, Marciano S, McAuslan MJ, McCunn P, McIntosh A, Meng X, Meyer-Baese L, Missault S, Moro F, Naessens DMP, Nava-Gomez LJ, Nonaka H, Ortiz JJ, Paasonen J, Peeters LM, Pereira M, Perez PD, Pompilus M, Prior M, Rakhmatullin R, Reimann HM, Reinwald J, Del Rio RT, Rivera-Olvera A, Ruiz-Pérez D, Russo G, Rutten TJ, Ryoke R, Sack M, Salvan P, Sanganahalli BG, Schroeter A, Seewoo BJ, Selingue E, Seuwen A, Shi B, Sirmpilatze N, Smith JAB, Smith C, Sobczak F, Stenroos PJ, Straathof M, Strobelt S, Sumiyoshi A, Takahashi K, Torres-García ME, Tudela R, van den Berg M, van der Marel K, van Hout ATB, Vertullo R, Vidal B, Vrooman RM, Wang VX, Wank I, Watson DJG, Yin T, Zhang Y, Zurbruegg S, Achard S, Alcauter S, Auer DP, Barbier EL, Baudewig J, Beckmann CF, Beckmann N, Becq GJPC, Blezer ELA, Bolbos R, Boretius S, Bouvard S, Budinger E, Buxbaum JD, Cash D, Chapman V, Chuang KH, Ciobanu L, Coolen BF, Dalley JW, Dhenain M, Dijkhuizen RM, Esteban O, Faber C, Febo M, Feindel KW, Forloni G, Fouquet J, Garza-Villarreal EA, Gass N, Glennon JC, Gozzi A, Gröhn O, Harkin A, Heerschap A, Helluy X, Herfert K, Heuser A, Homberg JR, Houwing DJ, Hyder F, Ielacqua GD, Jelescu IO, Johansen-Berg H, Kaneko G, Kawashima R, Keilholz SD, Keliris GA, Kelly C, Kerskens C, Khokhar JY, Kind PC, Langlois JB, Lerch JP, López-Hidalgo MA, Manahan-Vaughan D, Marchand F, Mars RB, Marsella G, Micotti E, Muñoz-Moreno E, Near J, Niendorf T, Otte WM, Pais-Roldán P, Pan WJ, Prado-Alcalá RA, Quirarte GL, Rodger J, Rosenow T, Sampaio-Baptista C, Sartorius A, Sawiak SJ, Scheenen TWJ, Shemesh N, Shih YYI, Shmuel A, Soria G, Stoop R, Thompson GJ, Till SM, Todd N, Van Der Linden A, van der Toorn A, van Tilborg GAF, Vanhove C, Veltien A, Verhoye M, Wachsmuth L, Weber-Fahr W, Wenk P, Yu X, Zerbi V, Zhang N, Zhang BB, Zimmer L, Devenyi GA, Chakravarty MM, Hess A. Author Correction: A consensus protocol for functional connectivity analysis in the rat brain. Nat Neurosci 2023:10.1038/s41593-023-01328-1. [PMID: 37072562 DOI: 10.1038/s41593-023-01328-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/20/2023]
Affiliation(s)
- Joanes Grandjean
- Donders Institute for Brain, Behaviour, and Cognition, Radboud University, Nijmegen, The Netherlands.
- Department for Medical Imaging, Radboud University Medical Center, Nijmegen, The Netherlands.
| | - Gabriel Desrosiers-Gregoire
- Cerebral Imaging Centre, Douglas Mental Health University Institute, Verdun, QC, Canada
- Integrated Program in Neuroscience, McGill University, Montreal, QC, Canada
| | - Cynthia Anckaerts
- Bio-imaging Lab, University of Antwerp, Antwerp, Belgium
- µNEURO Research Centre of Excellence, University of Antwerp, Antwerp, Belgium
| | - Diego Angeles-Valdez
- Instituto de Neurobiología, Universidad Nacional Autónoma de México, Campus Juriquilla, Querétaro, Mexico
| | - Fadi Ayad
- Biological and Biomedical Engineering, McGill University, Montreal, QC, Canada
- McConnell Brain Imaging Centre, McGill University, Montreal, QC, Canada
- Montreal Neurological Institute, McGill University, Montreal, QC, Canada
| | - David A Barrière
- UMR INRAE/CNRS 7247 Physiologie des Comportements et de la Reproduction, Physiologie de la reproduction et des comportements, Centre de recherche INRAE de Nouzilly, Tours, France
| | - Ines Blockx
- Bio-imaging Lab, University of Antwerp, Antwerp, Belgium
- µNEURO Research Centre of Excellence, University of Antwerp, Antwerp, Belgium
| | - Aleksandra Bortel
- McConnell Brain Imaging Centre, McGill University, Montreal, QC, Canada
- Montreal Neurological Institute, McGill University, Montreal, QC, Canada
- Department of Neurology and Neurosurgery, McGill University, Montreal, QC, Canada
| | - Margaret Broadwater
- Center for Animal MRI, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Department of Neurology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Biomedical Research Imaging Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Beatriz M Cardoso
- Preclinical MRI, Champalimaud Research, Champalimaud Centre for the Unknown, Lisbon, Portugal
| | - Marina Célestine
- Laboratoire des Maladies Neurodégénératives, Molecular Imaging Research Center (MIRCen), Université Paris-Saclay, Commissariat à l'Énergie Atomique et aux Énergies Alternatives (CEA), CNRS, Fontenay-aux-Roses, France
| | - Jorge E Chavez-Negrete
- Departamento de Neurobiología Conductual y Cognitiva, Instituto de Neurobiología, Universidad Nacional Autónoma de México, Campus Juriquilla, Querétaro, México
| | - Sangcheon Choi
- Translational Neuroimaging and Neural Control Group, High-Field Magnetic Resonance, Max Planck Institute for Biological Cybernetics, Tuebingen, Germany
- Graduate Training Centre of Neuroscience, International Max Planck Research School, University of Tuebingen, Tuebingen, Germany
| | - Emma Christiaen
- Institute Biomedical Technology (IBiTech), Electronics and Information Systems (ELIS), Ghent University, Gent, Belgium
| | - Perrin Clavijo
- Department of Biomedical Engineering, Emory University/Georgia Institute of Technology, Atlanta, GA, USA
| | - Luis Colon-Perez
- Department of Pharmacology & Neuroscience, University of North Texas Health Science Center, Fort Worth, TX, USA
| | - Samuel Cramer
- Translational Neuroimaging and Systems Neuroscience Lab, Biomedical Engineering, Pennsylvania State University, University Park, PA, USA
| | - Tolomeo Daniele
- Centre for Advanced Biomedical Imaging, University College London, London, UK
| | - Elaine Dempsey
- Neuropsychopharmacology Research Group, School of Pharmacy and Pharmaceutical Sciences, Trinity College Dublin, Dublin, Ireland
- Trinity College Institute of Neuroscience, Trinity College Dublin, Dublin, Ireland
| | - Yujian Diao
- CIBM Center for Biomedical Imaging, Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
- Laboratory for Functional and Metabolic Imaging, Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
| | - Arno Doelemeyer
- Musculoskeletal Diseases Department, Novartis Institutes for BioMedical Research, Basel, Switzerland
| | - David Dopfel
- Translational Neuroimaging and Systems Neuroscience Lab, Biomedical Engineering, Pennsylvania State University, University Park, PA, USA
| | - Lenka Dvořáková
- Biomedical Imaging Unit, A.I.V. Institute for Molecular Sciences, University of Eastern Finland, Kuopio, Finland
| | - Claudia Falfán-Melgoza
- Translational Imaging, Department of Neuroimaging, Central Institute of Mental Health, Medical Faculty Mannheim, Mannheim, Germany
| | - Francisca F Fernandes
- Preclinical MRI, Champalimaud Research, Champalimaud Centre for the Unknown, Lisbon, Portugal
| | - Caitlin F Fowler
- Cerebral Imaging Centre, Douglas Mental Health University Institute, Verdun, QC, Canada
- Biological and Biomedical Engineering, McGill University, Montreal, QC, Canada
| | - Antonio Fuentes-Ibañez
- Departamento de Neurobiología Conductual y Cognitiva, Instituto de Neurobiología, Universidad Nacional Autónoma de México, Campus Juriquilla, Querétaro, México
| | - Clément M Garin
- Laboratoire des Maladies Neurodégénératives, Molecular Imaging Research Center (MIRCen), Université Paris-Saclay, Commissariat à l'Énergie Atomique et aux Énergies Alternatives (CEA), CNRS, Fontenay-aux-Roses, France
| | - Eveline Gelderman
- Donders Institute for Brain, Behaviour, and Cognition, Radboud University, Nijmegen, The Netherlands
| | - Carla E M Golden
- Seaver Autism Center for Research & Treatment, Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York City, NY, USA
| | - Chao C G Guo
- Donders Institute for Brain, Behaviour, and Cognition, Radboud University, Nijmegen, The Netherlands
| | - Marloes J A G Henckens
- Donders Institute for Brain, Behaviour, and Cognition, Radboud University, Nijmegen, The Netherlands
- Department of Neuroscience and Pharmacology, Rudolf Magnus Institute of Neuroscience, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Lauren A Hennessy
- Experimental and Regenerative Neurosciences, School of Biological Sciences, University of Western Australia, Crawley, WA, Australia
- Brain Plasticity Group, Perron Institute for Neurological and Translational Science, Nedlands, WA, Australia
| | - Peter Herman
- Radiology and Biomedical Imaging, Yale University School of Medicine, New Haven, CT, USA
- Quantitative Neuroscience with Magnetic Resonance (QNMR) Core Center, Yale University School of Medicine, New Haven, CT, USA
| | - Nita Hofwijks
- Donders Institute for Brain, Behaviour, and Cognition, Radboud University, Nijmegen, The Netherlands
| | - Corey Horien
- Radiology and Biomedical Imaging, Yale University School of Medicine, New Haven, CT, USA
| | - Tudor M Ionescu
- Werner Siemens Imaging Center, Department of Preclinical Imaging and Radiopharmacy, University of Tuebingen, Tuebingen, Germany
| | - Jolyon Jones
- Department of Psychology, University of Cambridge, Cambridge, UK
| | - Johannes Kaesser
- Institute of Experimental and Clinical Pharmacology and Toxicology, FAU Erlangen-Nürnberg, Erlangen, Germany
| | - Eugene Kim
- Biomarker Research And Imaging in Neuroscience (BRAIN) Centre, Department of Neuroimaging King's College London, London, UK
| | - Henriette Lambers
- Experimental Magnetic Resonance Group, Clinic of Radiology, University of Münster, Münster, Germany
| | - Alberto Lazari
- Nuffield Department of Clinical Neurosciences, Wellcome Centre for Integrative Neuroimaging, FMRIB, University of Oxford, John Radcliffe Hospital, Headington, Oxford, UK
| | - Sung-Ho Lee
- Center for Animal MRI, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Department of Neurology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Biomedical Research Imaging Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Amanda Lillywhite
- School of Life Sciences, University of Nottingham, Nottingham, UK
- Pain Centre Versus Arthritis, University of Nottingham, Nottingham, UK
| | - Yikang Liu
- Translational Neuroimaging and Systems Neuroscience Lab, Biomedical Engineering, Pennsylvania State University, University Park, PA, USA
| | - Yanyan Y Liu
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing, China
| | - Alejandra López-Castro
- Instituto de Neurobiología, Universidad Nacional Autónoma de México, Campus Juriquilla, Querétaro, Mexico
| | - Xavier López-Gil
- Magnetic Imaging Resonance Core Facility, Institut d'Investigacions Biomèdiques August Pi I Sunyer (IDIBAPS), Barcelona, Spain
| | - Zilu Ma
- Translational Neuroimaging and Systems Neuroscience Lab, Biomedical Engineering, Pennsylvania State University, University Park, PA, USA
| | - Eilidh MacNicol
- Biomarker Research And Imaging in Neuroscience (BRAIN) Centre, Department of Neuroimaging King's College London, London, UK
| | - Dan Madularu
- Biological and Biomedical Engineering, McGill University, Montreal, QC, Canada
- Center for Translational Neuroimaging, Northeastern University, Boston, MA, USA
| | - Francesca Mandino
- Radiology and Biomedical Imaging, Yale University School of Medicine, New Haven, CT, USA
| | - Sabina Marciano
- Werner Siemens Imaging Center, Department of Preclinical Imaging and Radiopharmacy, University of Tuebingen, Tuebingen, Germany
| | - Matthew J McAuslan
- Neuropsychopharmacology Research Group, School of Pharmacy and Pharmaceutical Sciences, Trinity College Dublin, Dublin, Ireland
| | - Patrick McCunn
- Khokhar Lab, Department of Anatomy and Cell Biology, Western University, London, ON, Canada
| | - Alison McIntosh
- Neuropsychopharmacology Research Group, School of Pharmacy and Pharmaceutical Sciences, Trinity College Dublin, Dublin, Ireland
- Trinity College Institute of Neuroscience, Trinity College Dublin, Dublin, Ireland
| | - Xianzong Meng
- Donders Institute for Brain, Behaviour, and Cognition, Radboud University, Nijmegen, The Netherlands
| | - Lisa Meyer-Baese
- Department of Biomedical Engineering, Emory University/Georgia Institute of Technology, Atlanta, GA, USA
| | - Stephan Missault
- Bio-imaging Lab, University of Antwerp, Antwerp, Belgium
- µNEURO Research Centre of Excellence, University of Antwerp, Antwerp, Belgium
| | - Federico Moro
- Laboratory of Acute Brain Injury and Therapeutic Strategies, Department of NeuroscienceIstituto di Ricerche Farmacologiche Mario Negri, IRCCS, Milan, Italy
| | - Daphne M P Naessens
- Biomedical Engineering and Physics, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands
| | - Laura J Nava-Gomez
- Facultad de Medicina, Universidad Autónoma de Querétaro, Querétaro, México
- Escuela Nacional de Estudios Superiores, Juriquilla, Universidad Nacional Autónoma de México, Querétaro, México
| | - Hiroi Nonaka
- Institute of Development, Aging and Cancer, Tohoku University, Sendai, Japan
| | - Juan J Ortiz
- Departamento de Neurobiología Conductual y Cognitiva, Instituto de Neurobiología, Universidad Nacional Autónoma de México, Campus Juriquilla, Querétaro, México
| | - Jaakko Paasonen
- Biomedical Imaging Unit, A.I.V. Institute for Molecular Sciences, University of Eastern Finland, Kuopio, Finland
| | - Lore M Peeters
- Bio-imaging Lab, University of Antwerp, Antwerp, Belgium
- µNEURO Research Centre of Excellence, University of Antwerp, Antwerp, Belgium
| | - Mickaël Pereira
- Lyon Neuroscience Research Center, Université Claude Bernard Lyon 1, INSERM, CNRS, Lyon, France
| | - Pablo D Perez
- Translational Neuroimaging and Systems Neuroscience Lab, Biomedical Engineering, Pennsylvania State University, University Park, PA, USA
| | - Marjory Pompilus
- Febo Laboratory, Department of Psychiatry, University of Florida, Gainesville, FL, USA
| | - Malcolm Prior
- School of Medicine, University of Nottingham, Nottingham, UK
| | | | - Henning M Reimann
- Berlin Ultrahigh Field Facility (B.U.F.F.), Max-Delbrück Center for Molecular Medicine in the Helmholtz Association, Berlin, Germany
| | - Jonathan Reinwald
- Translational Imaging, Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany
| | - Rodrigo Triana Del Rio
- Psychiatric neurosciences, Center for Psychiatric Neuroscience, Lausanne University and University Hospital Center, Unicentre, Lausanne, Switzerland
| | - Alejandro Rivera-Olvera
- Donders Institute for Brain, Behaviour, and Cognition, Radboud University, Nijmegen, The Netherlands
| | | | - Gabriele Russo
- Department of Neurophysiology, Medical Faculty, Ruhr University Bochum, Bochum, Germany
| | - Tobias J Rutten
- Donders Institute for Brain, Behaviour, and Cognition, Radboud University, Nijmegen, The Netherlands
| | - Rie Ryoke
- Institute of Development, Aging and Cancer, Tohoku University, Sendai, Japan
| | - Markus Sack
- Translational Imaging, Department of Neuroimaging, Central Institute of Mental Health, Medical Faculty Mannheim, Mannheim, Germany
| | - Piergiorgio Salvan
- Nuffield Department of Clinical Neurosciences, Wellcome Centre for Integrative Neuroimaging, FMRIB, University of Oxford, John Radcliffe Hospital, Headington, Oxford, UK
| | - Basavaraju G Sanganahalli
- Radiology and Biomedical Imaging, Yale University School of Medicine, New Haven, CT, USA
- Quantitative Neuroscience with Magnetic Resonance (QNMR) Core Center, Yale University School of Medicine, New Haven, CT, USA
| | - Aileen Schroeter
- Institute for Biomedical Engineering, University and ETH Zurich, Zurich, Switzerland
| | - Bhedita J Seewoo
- Experimental and Regenerative Neurosciences, School of Biological Sciences, University of Western Australia, Crawley, WA, Australia
- Brain Plasticity Group, Perron Institute for Neurological and Translational Science, Nedlands, WA, Australia
- Centre for Microscopy, Characterisation & Analysis, Research Infrastructure Centres, University of Western Australia, Nedlands, WA, Australia
| | | | - Aline Seuwen
- Institute for Biomedical Engineering, University and ETH Zurich, Zurich, Switzerland
| | - Bowen Shi
- iHuman Institute, ShanghaiTech University, Shanghai, China
| | - Nikoloz Sirmpilatze
- Functional Imaging Laboratory, German Primate Center - Leibniz Institute for Primate Research, Göttingen, Germany
- Faculty of Biology and Psychology, Georg-August University of Göttingen, Göttingen, Germany
- DFG Research Center for Nanoscale Microscopy and Molecular Physiology of the Brain (CNMPB), Göttingen, Germany
| | - Joanna A B Smith
- Simons Initiative for the Developing Brain, University of Edinburgh, Edinburgh, UK
- Patrick Wild Centre, University of Edinburgh, Edinburgh, UK
- Centre for Discovery Brain Sciences, University of Edinburgh, Edinburgh, UK
| | - Corrie Smith
- Department of Biomedical Engineering, Emory University/Georgia Institute of Technology, Atlanta, GA, USA
| | - Filip Sobczak
- Translational Neuroimaging and Neural Control Group, High-Field Magnetic Resonance, Max Planck Institute for Biological Cybernetics, Tuebingen, Germany
- Graduate Training Centre of Neuroscience, International Max Planck Research School, University of Tuebingen, Tuebingen, Germany
| | - Petteri J Stenroos
- Univ. Grenoble Alpes, Inserm, U1216, Grenoble Institut Neurosciences, Grenoble, France
| | - Milou Straathof
- Biomedical MR Imaging and Spectroscopy Group, Center for Image Sciences, University Medical Center Utrecht & Utrecht University, Utrecht, The Netherlands
| | - Sandra Strobelt
- Institute of Experimental and Clinical Pharmacology and Toxicology, FAU Erlangen-Nürnberg, Erlangen, Germany
| | - Akira Sumiyoshi
- Institute of Development, Aging and Cancer, Tohoku University, Sendai, Japan
- National Institutes for Quantum Science and Technology, Chiba, Japan
| | - Kengo Takahashi
- Translational Neuroimaging and Neural Control Group, High-Field Magnetic Resonance, Max Planck Institute for Biological Cybernetics, Tuebingen, Germany
- Graduate Training Centre of Neuroscience, International Max Planck Research School, University of Tuebingen, Tuebingen, Germany
| | - Maria E Torres-García
- Departamento de Neurobiología Conductual y Cognitiva, Instituto de Neurobiología, Universidad Nacional Autónoma de México, Campus Juriquilla, Querétaro, México
| | - Raul Tudela
- Group of Biomedical Imaging, Consorcio Centro de Investigación Biomédica en Red (CIBER) de Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN), University of Barcelona, Barcelona, Spain
| | - Monica van den Berg
- Bio-imaging Lab, University of Antwerp, Antwerp, Belgium
- µNEURO Research Centre of Excellence, University of Antwerp, Antwerp, Belgium
| | - Kajo van der Marel
- Biomedical MR Imaging and Spectroscopy Group, Center for Image Sciences, University Medical Center Utrecht & Utrecht University, Utrecht, The Netherlands
| | - Aran T B van Hout
- Donders Institute for Brain, Behaviour, and Cognition, Radboud University, Nijmegen, The Netherlands
| | - Roberta Vertullo
- Donders Institute for Brain, Behaviour, and Cognition, Radboud University, Nijmegen, The Netherlands
| | - Benjamin Vidal
- Lyon Neuroscience Research Center, Université Claude Bernard Lyon 1, INSERM, CNRS, Lyon, France
| | - Roël M Vrooman
- Donders Institute for Brain, Behaviour, and Cognition, Radboud University, Nijmegen, The Netherlands
| | - Victora X Wang
- BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York City, NY, USA
| | - Isabel Wank
- Institute of Experimental and Clinical Pharmacology and Toxicology, FAU Erlangen-Nürnberg, Erlangen, Germany
| | - David J G Watson
- School of Life Sciences, University of Nottingham, Nottingham, UK
| | - Ting Yin
- Animal Imaging and Technology Section, Center for Biomedical Imaging, École polytechnique fédérale de Lausanne, Lausanne, Switzerland
| | - Yongzhi Zhang
- Focused Ultrasound Laboratory, Department of Radiology Brigham and Women's Hospital, Boston, MA, USA
| | - Stefan Zurbruegg
- Neurosciences Department, Novartis Institutes for BioMedical Research, Basel, Switzerland
| | - Sophie Achard
- Inria, University Grenoble Alpes, CNRS, Grenoble, France
| | - Sarael Alcauter
- Departamento de Neurobiología Conductual y Cognitiva, Instituto de Neurobiología, Universidad Nacional Autónoma de México, Campus Juriquilla, Querétaro, México
| | - Dorothee P Auer
- School of Medicine, University of Nottingham, Nottingham, UK
- NIHR Biomedical Research Centre, University of Nottingham, Nottingham, UK
| | - Emmanuel L Barbier
- Univ. Grenoble Alpes, Inserm, U1216, Grenoble Institut Neurosciences, Grenoble, France
| | - Jürgen Baudewig
- Functional Imaging Laboratory, German Primate Center - Leibniz Institute for Primate Research, Göttingen, Germany
| | - Christian F Beckmann
- Donders Institute for Brain, Behaviour, and Cognition, Radboud University, Nijmegen, The Netherlands
- Nuffield Department of Clinical Neurosciences, Wellcome Centre for Integrative Neuroimaging, FMRIB, University of Oxford, John Radcliffe Hospital, Headington, Oxford, UK
| | - Nicolau Beckmann
- Musculoskeletal Diseases Department, Novartis Institutes for BioMedical Research, Basel, Switzerland
| | | | - Erwin L A Blezer
- Biomedical MR Imaging and Spectroscopy Group, Center for Image Sciences, University Medical Center Utrecht & Utrecht University, Utrecht, The Netherlands
| | | | - Susann Boretius
- Functional Imaging Laboratory, German Primate Center - Leibniz Institute for Primate Research, Göttingen, Germany
- Faculty of Biology and Psychology, Georg-August University of Göttingen, Göttingen, Germany
- DFG Research Center for Nanoscale Microscopy and Molecular Physiology of the Brain (CNMPB), Göttingen, Germany
| | - Sandrine Bouvard
- Lyon Neuroscience Research Center, Université Claude Bernard Lyon 1, INSERM, CNRS, Lyon, France
| | - Eike Budinger
- Combinatorial NeuroImaging Core Facility, Leibniz Institute for Neurobiology, Magdeburg, Germany
- Center for Behavioral Brain Sciences, Magdeburg, Germany
| | - Joseph D Buxbaum
- Seaver Autism Center for Research & Treatment, Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York City, NY, USA
| | - Diana Cash
- Biomarker Research And Imaging in Neuroscience (BRAIN) Centre, Department of Neuroimaging King's College London, London, UK
| | - Victoria Chapman
- School of Life Sciences, University of Nottingham, Nottingham, UK
- Pain Centre Versus Arthritis, University of Nottingham, Nottingham, UK
- NIHR Biomedical Research Centre, University of Nottingham, Nottingham, UK
| | - Kai-Hsiang Chuang
- Queensland Brain Institute and Centre for Advanced Imaging, University of Queensland, St. Lucia, QLD, Australia
| | | | - Bram F Coolen
- Biomedical Engineering and Physics, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands
| | - Jeffrey W Dalley
- Department of Psychology, University of Cambridge, Cambridge, UK
| | - Marc Dhenain
- Laboratoire des Maladies Neurodégénératives, Molecular Imaging Research Center (MIRCen), Université Paris-Saclay, Commissariat à l'Énergie Atomique et aux Énergies Alternatives (CEA), CNRS, Fontenay-aux-Roses, France
| | - Rick M Dijkhuizen
- Biomedical MR Imaging and Spectroscopy Group, Center for Image Sciences, University Medical Center Utrecht & Utrecht University, Utrecht, The Netherlands
| | - Oscar Esteban
- Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Cornelius Faber
- Experimental Magnetic Resonance Group, Clinic of Radiology, University of Münster, Münster, Germany
| | - Marcelo Febo
- Febo Laboratory, Department of Psychiatry, University of Florida, Gainesville, FL, USA
| | - Kirk W Feindel
- Centre for Microscopy, Characterisation & Analysis, Research Infrastructure Centres, University of Western Australia, Nedlands, WA, Australia
| | - Gianluigi Forloni
- Biology of Neurodogenerative Disorders, Department of Neuroscience Istituto di Ricerche Farmacologiche Mario Negri, IRCCS, Milan, Italy
| | - Jérémie Fouquet
- Cerebral Imaging Centre, Douglas Mental Health University Institute, Verdun, QC, Canada
| | - Eduardo A Garza-Villarreal
- Instituto de Neurobiología, Universidad Nacional Autónoma de México, Campus Juriquilla, Querétaro, Mexico
| | - Natalia Gass
- Translational Imaging, Department of Neuroimaging, Central Institute of Mental Health, Medical Faculty Mannheim, Mannheim, Germany
| | - Jeffrey C Glennon
- Conway Institute of Biomedical and Biomolecular Sciences, School of Medicine, University College Dublin, Dublin, Ireland
| | - Alessandro Gozzi
- Functional Neuroimaging Laboratory, Center for Neuroscience and Cognitive Systems, Istituto Italiano di Tecnologia, Rovereto, Italy
| | - Olli Gröhn
- Biomedical Imaging Unit, A.I.V. Institute for Molecular Sciences, University of Eastern Finland, Kuopio, Finland
| | - Andrew Harkin
- Neuropsychopharmacology Research Group, School of Pharmacy and Pharmaceutical Sciences, Trinity College Dublin, Dublin, Ireland
- Trinity College Institute of Neuroscience, Trinity College Dublin, Dublin, Ireland
| | - Arend Heerschap
- Department for Medical Imaging, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Xavier Helluy
- Department of Neurophysiology, Medical Faculty, Ruhr University Bochum, Bochum, Germany
- Department of Biopsychology, Institute of Cognitive Neuroscience, Ruhr University Bochum, Bochum, Germany
| | - Kristina Herfert
- Werner Siemens Imaging Center, Department of Preclinical Imaging and Radiopharmacy, University of Tuebingen, Tuebingen, Germany
| | - Arnd Heuser
- Max-Delbrück Center for Molecular Medicine in the Helmholtz Association, Berlin, Germany
| | - Judith R Homberg
- Donders Institute for Brain, Behaviour, and Cognition, Radboud University, Nijmegen, The Netherlands
| | - Danielle J Houwing
- Donders Institute for Brain, Behaviour, and Cognition, Radboud University, Nijmegen, The Netherlands
| | - Fahmeed Hyder
- Radiology and Biomedical Imaging, Yale University School of Medicine, New Haven, CT, USA
- Quantitative Neuroscience with Magnetic Resonance (QNMR) Core Center, Yale University School of Medicine, New Haven, CT, USA
| | | | - Ileana O Jelescu
- CIBM Center for Biomedical Imaging, Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
| | - Heidi Johansen-Berg
- Nuffield Department of Clinical Neurosciences, Wellcome Centre for Integrative Neuroimaging, FMRIB, University of Oxford, John Radcliffe Hospital, Headington, Oxford, UK
| | - Gen Kaneko
- School of Arts & Sciences, University of Houston-Victoria, Victoria, TX, USA
| | - Ryuta Kawashima
- Institute of Development, Aging and Cancer, Tohoku University, Sendai, Japan
| | - Shella D Keilholz
- Department of Biomedical Engineering, Emory University/Georgia Institute of Technology, Atlanta, GA, USA
| | - Georgios A Keliris
- Bio-imaging Lab, University of Antwerp, Antwerp, Belgium
- µNEURO Research Centre of Excellence, University of Antwerp, Antwerp, Belgium
| | - Clare Kelly
- Trinity College Institute of Neuroscience, Trinity College Dublin, Dublin, Ireland
- School of Psychology, Trinity College Dublin, Dublin, Ireland
- Department of Psychiatry, School of Medicine, Trinity College Dublin, Dublin, Ireland
| | - Christian Kerskens
- Trinity College Institute of Neuroscience, Trinity College Dublin, Dublin, Ireland
- Trinity Centre for Biomedical Engineering, School of Medicine, Trinity College Dublin, Dublin, Ireland
| | - Jibran Y Khokhar
- Khokhar Lab, Department of Anatomy and Cell Biology, Western University, London, ON, Canada
| | - Peter C Kind
- Simons Initiative for the Developing Brain, University of Edinburgh, Edinburgh, UK
- Patrick Wild Centre, University of Edinburgh, Edinburgh, UK
- Centre for Discovery Brain Sciences, University of Edinburgh, Edinburgh, UK
- Centre for Brain Development and Repair, Institute for Stem Cell Biology and Regenerative Medicine, Bangalore, India
| | | | - Jason P Lerch
- Nuffield Department of Clinical Neurosciences, Wellcome Centre for Integrative Neuroimaging, FMRIB, University of Oxford, John Radcliffe Hospital, Headington, Oxford, UK
- Department of Medical Biophysics, University of Toronto, Toronto, QC, Canada
| | - Monica A López-Hidalgo
- Escuela Nacional de Estudios Superiores, Juriquilla, Universidad Nacional Autónoma de México, Querétaro, México
| | | | - Fabien Marchand
- Université Clermont Auvergne, Inserm U1107 Neuro-Dol, Pharmacologie Fondamentale et Clinique de la Douleur, Clermont-Ferrand, France
| | - Rogier B Mars
- Donders Institute for Brain, Behaviour, and Cognition, Radboud University, Nijmegen, The Netherlands
- Nuffield Department of Clinical Neurosciences, Wellcome Centre for Integrative Neuroimaging, FMRIB, University of Oxford, John Radcliffe Hospital, Headington, Oxford, UK
| | - Gerardo Marsella
- Animal Care Unit, Istituto di Ricerche Farmacologiche Mario Negri, IRCCS, Milan, Italy
| | - Edoardo Micotti
- Biology of Neurodogenerative Disorders, Department of Neuroscience Istituto di Ricerche Farmacologiche Mario Negri, IRCCS, Milan, Italy
| | - Emma Muñoz-Moreno
- Magnetic Imaging Resonance Core Facility, Institut d'Investigacions Biomèdiques August Pi I Sunyer (IDIBAPS), Barcelona, Spain
| | - Jamie Near
- Cerebral Imaging Centre, Douglas Mental Health University Institute, Verdun, QC, Canada
- Physical Sciences Platform, Sunnybrook Research Institute, Toronto, QC, Canada
| | - Thoralf Niendorf
- Berlin Ultrahigh Field Facility (B.U.F.F.), Max-Delbrück Center for Molecular Medicine in the Helmholtz Association, Berlin, Germany
- Experimental and Clinical Research Center, A Joint Cooperation Between the Charité Medical Faculty and the Max-Delbrück Center for Molecular Medicine in the Helmholtz Association, Berlin, Germany
| | - Willem M Otte
- Biomedical MR Imaging and Spectroscopy Group, Center for Image Sciences, University Medical Center Utrecht & Utrecht University, Utrecht, The Netherlands
- Department of Pediatric Neurology, UMC Utrecht Brain Center, University Medical Center Utrecht & Utrecht University, Utrecht, The Netherlands
| | - Patricia Pais-Roldán
- Translational Neuroimaging and Neural Control Group, High-Field Magnetic Resonance, Max Planck Institute for Biological Cybernetics, Tuebingen, Germany
- Medical Imaging Physics (INM-4), Institute of Neuroscience and Medicine, Forschungszentrum Juelich, Juelich, Germany
| | - Wen-Ju Pan
- Department of Biomedical Engineering, Emory University/Georgia Institute of Technology, Atlanta, GA, USA
| | - Roberto A Prado-Alcalá
- Departamento de Neurobiología Conductual y Cognitiva, Instituto de Neurobiología, Universidad Nacional Autónoma de México, Campus Juriquilla, Querétaro, México
| | - Gina L Quirarte
- Departamento de Neurobiología Conductual y Cognitiva, Instituto de Neurobiología, Universidad Nacional Autónoma de México, Campus Juriquilla, Querétaro, México
| | - Jennifer Rodger
- Experimental and Regenerative Neurosciences, School of Biological Sciences, University of Western Australia, Crawley, WA, Australia
- Brain Plasticity Group, Perron Institute for Neurological and Translational Science, Nedlands, WA, Australia
| | - Tim Rosenow
- Centre for Microscopy, Characterisation and Analysis, University of Western Australia, Crawley, WA, Australia
| | - Cassandra Sampaio-Baptista
- Nuffield Department of Clinical Neurosciences, Wellcome Centre for Integrative Neuroimaging, FMRIB, University of Oxford, John Radcliffe Hospital, Headington, Oxford, UK
- School of Psychology and Neuroscience, University of Glasgow, Glasgow, UK
| | - Alexander Sartorius
- Translational Imaging, Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany
| | - Stephen J Sawiak
- Translational Neuroimaging Laboratory, Physiology, Development and Neuroscience, University of Cambridge, Cambridge, UK
| | - Tom W J Scheenen
- Department for Medical Imaging, Radboud University Medical Center, Nijmegen, The Netherlands
- Erwin L. Hahn Institute for MR Imaging, University of Duisburg-Essen, Essen, Germany
| | - Noam Shemesh
- Preclinical MRI, Champalimaud Research, Champalimaud Centre for the Unknown, Lisbon, Portugal
| | - Yen-Yu Ian Shih
- Center for Animal MRI, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Department of Neurology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Biomedical Research Imaging Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Biomedical Engineering, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Amir Shmuel
- Biological and Biomedical Engineering, McGill University, Montreal, QC, Canada
- McConnell Brain Imaging Centre, McGill University, Montreal, QC, Canada
- Montreal Neurological Institute, McGill University, Montreal, QC, Canada
- Department of Neurology and Neurosurgery, McGill University, Montreal, QC, Canada
- Department of Physiology, McGill University, Montreal, QC, Canada
| | - Guadalupe Soria
- Laboratory of Surgical Neuroanatomy, Institute of Neuroscience, University of Barcelona, Barcelona, Spain
| | - Ron Stoop
- Psychiatric neurosciences, Center for Psychiatric Neuroscience, Lausanne University and University Hospital Center, Unicentre, Lausanne, Switzerland
| | | | - Sally M Till
- Simons Initiative for the Developing Brain, University of Edinburgh, Edinburgh, UK
- Patrick Wild Centre, University of Edinburgh, Edinburgh, UK
- Centre for Discovery Brain Sciences, University of Edinburgh, Edinburgh, UK
| | - Nick Todd
- Focused Ultrasound Laboratory, Department of Radiology Brigham and Women's Hospital, Boston, MA, USA
| | - Annemie Van Der Linden
- Bio-imaging Lab, University of Antwerp, Antwerp, Belgium
- µNEURO Research Centre of Excellence, University of Antwerp, Antwerp, Belgium
| | - Annette van der Toorn
- Biomedical MR Imaging and Spectroscopy Group, Center for Image Sciences, University Medical Center Utrecht & Utrecht University, Utrecht, The Netherlands
| | - Geralda A F van Tilborg
- Biomedical MR Imaging and Spectroscopy Group, Center for Image Sciences, University Medical Center Utrecht & Utrecht University, Utrecht, The Netherlands
| | - Christian Vanhove
- Institute Biomedical Technology (IBiTech), Electronics and Information Systems (ELIS), Ghent University, Gent, Belgium
| | - Andor Veltien
- Department for Medical Imaging, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Marleen Verhoye
- Bio-imaging Lab, University of Antwerp, Antwerp, Belgium
- µNEURO Research Centre of Excellence, University of Antwerp, Antwerp, Belgium
| | - Lydia Wachsmuth
- Experimental Magnetic Resonance Group, Clinic of Radiology, University of Münster, Münster, Germany
| | - Wolfgang Weber-Fahr
- Translational Imaging, Department of Neuroimaging, Central Institute of Mental Health, Medical Faculty Mannheim, Mannheim, Germany
| | - Patricia Wenk
- Combinatorial NeuroImaging Core Facility, Leibniz Institute for Neurobiology, Magdeburg, Germany
| | - Xin Yu
- Translational Neuroimaging and Neural Control Group, High-Field Magnetic Resonance, Max Planck Institute for Biological Cybernetics, Tuebingen, Germany
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA, USA
| | - Valerio Zerbi
- Neuro-X Institute, School of Engineering (STI), EPFL, Lausanne, Switzerland
- Centre for Biomedical Imaging (CIBM), Lausanne, Switzerland
| | - Nanyin Zhang
- Translational Neuroimaging and Systems Neuroscience Lab, Biomedical Engineering, Pennsylvania State University, University Park, PA, USA
| | - Baogui B Zhang
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing, China
| | - Luc Zimmer
- Lyon Neuroscience Research Center, Université Claude Bernard Lyon 1, INSERM, CNRS, Lyon, France
- CERMEP - Imagerie du vivant, Lyon, France
- Hospices Civils de Lyon, Lyon, France
| | - Gabriel A Devenyi
- Cerebral Imaging Centre, Douglas Mental Health University Institute, Verdun, QC, Canada
- Department of Psychiatry, McGill University, Montreal, QC, Canada
| | - M Mallar Chakravarty
- Cerebral Imaging Centre, Douglas Mental Health University Institute, Verdun, QC, Canada
- Biological and Biomedical Engineering, McGill University, Montreal, QC, Canada
- Department of Psychiatry, McGill University, Montreal, QC, Canada
| | - Andreas Hess
- Institute of Experimental and Clinical Pharmacology and Toxicology, FAU Erlangen-Nürnberg, Erlangen, Germany
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43
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Wang Q, Li Y, Gu X, Zhang N, Xie J, Niu B, Xing Y, He Y. Imaging diagnosis of intravenous leiomyomatosis: an institutional experience. Clin Radiol 2023:S0009-9260(23)00138-1. [PMID: 37365113 DOI: 10.1016/j.crad.2023.03.017] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2022] [Revised: 03/14/2023] [Accepted: 03/28/2023] [Indexed: 06/28/2023]
Abstract
AIM To review and summarise the clinical and imaging characteristics of intravenous leiomyomatosis (IVL), a rare smooth muscle tumour originating from the uterus. MATERIALS AND METHODS Twenty-seven patients with a histopathological diagnosis of IVL who underwent surgery were reviewed retrospectively. All patients underwent pelvic ultrasonography, inferior vena cava (IVC) ultrasonography, and echocardiography before surgery. Computed tomography (CT) with contrast enhancement was performed in patients with extrapelvic IVL. Some patients underwent pelvic magnetic resonance imaging (MRI). RESULTS Mean age was 44.81 years. Clinical symptoms were non-specific. IVL was intrapelvic in seven patients and extrapelvic in 20. Preoperative pelvic ultrasonography missed the diagnosis in 85.7% of patients with intrapelvic IVL. Pelvic MRI was useful to evaluate the parauterine vessels. Incidence of cardiac involvement was 59.26%. Echocardiography showed a highly mobile sessile mass in the right atrium with moderate-to-low echogenicity that originates from the IVC. Ninety per cent of extrapelvic lesions showed unilateral growth. The most common growth pattern was via the right uterine vein-internal iliac vein-IVC pathway. CONCLUSION The clinical symptoms of IVL are non-specific. For patients with intrapelvic IVL, early diagnosis is difficult. Pelvic ultrasound should focus on the parauterine vessels, the iliac and ovarian veins should be explored carefully. MRI has obvious advantages in evaluating parauterine vessel involvement, which is helpful for early diagnosis. For patients with extrapelvic IVL, CT should be performed before surgery as part of a comprehensive evaluation. IVC ultrasonography and echocardiography are recommended when IVL is highly suspected.
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Affiliation(s)
- Q Wang
- Echocardiography Medical Center, Beijing Anzhen Hospital, Capital Medical University, China
| | - Y Li
- Department of Radiology, The Seventh Affiliated Hospital of Sun Yat-sen University, China
| | - X Gu
- Echocardiography Medical Center, Beijing Anzhen Hospital, Capital Medical University, China
| | - N Zhang
- Department of Radiology, Beijing Anzhen Hospital, Capital Medical University, China
| | - J Xie
- Department of Cardiology, Jiahui International Hospital, China
| | - B Niu
- Echocardiography Medical Center, Beijing Anzhen Hospital, Capital Medical University, China
| | - Y Xing
- Department of Comprehensive Ultrasound, Beijing Anzhen Hospital, Capital Medical University, China
| | - Y He
- Echocardiography Medical Center, Beijing Anzhen Hospital, Capital Medical University, China.
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44
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Grandjean J, Desrosiers-Gregoire G, Anckaerts C, Angeles-Valdez D, Ayad F, Barrière DA, Blockx I, Bortel A, Broadwater M, Cardoso BM, Célestine M, Chavez-Negrete JE, Choi S, Christiaen E, Clavijo P, Colon-Perez L, Cramer S, Daniele T, Dempsey E, Diao Y, Doelemeyer A, Dopfel D, Dvořáková L, Falfán-Melgoza C, Fernandes FF, Fowler CF, Fuentes-Ibañez A, Garin CM, Gelderman E, Golden CEM, Guo CCG, Henckens MJAG, Hennessy LA, Herman P, Hofwijks N, Horien C, Ionescu TM, Jones J, Kaesser J, Kim E, Lambers H, Lazari A, Lee SH, Lillywhite A, Liu Y, Liu YY, López-Castro A, López-Gil X, Ma Z, MacNicol E, Madularu D, Mandino F, Marciano S, McAuslan MJ, McCunn P, McIntosh A, Meng X, Meyer-Baese L, Missault S, Moro F, Naessens DMP, Nava-Gomez LJ, Nonaka H, Ortiz JJ, Paasonen J, Peeters LM, Pereira M, Perez PD, Pompilus M, Prior M, Rakhmatullin R, Reimann HM, Reinwald J, Del Rio RT, Rivera-Olvera A, Ruiz-Pérez D, Russo G, Rutten TJ, Ryoke R, Sack M, Salvan P, Sanganahalli BG, Schroeter A, Seewoo BJ, Selingue E, Seuwen A, Shi B, Sirmpilatze N, Smith JAB, Smith C, Sobczak F, Stenroos PJ, Straathof M, Strobelt S, Sumiyoshi A, Takahashi K, Torres-García ME, Tudela R, van den Berg M, van der Marel K, van Hout ATB, Vertullo R, Vidal B, Vrooman RM, Wang VX, Wank I, Watson DJG, Yin T, Zhang Y, Zurbruegg S, Achard S, Alcauter S, Auer DP, Barbier EL, Baudewig J, Beckmann CF, Beckmann N, Becq GJPC, Blezer ELA, Bolbos R, Boretius S, Bouvard S, Budinger E, Buxbaum JD, Cash D, Chapman V, Chuang KH, Ciobanu L, Coolen BF, Dalley JW, Dhenain M, Dijkhuizen RM, Esteban O, Faber C, Febo M, Feindel KW, Forloni G, Fouquet J, Garza-Villarreal EA, Gass N, Glennon JC, Gozzi A, Gröhn O, Harkin A, Heerschap A, Helluy X, Herfert K, Heuser A, Homberg JR, Houwing DJ, Hyder F, Ielacqua GD, Jelescu IO, Johansen-Berg H, Kaneko G, Kawashima R, Keilholz SD, Keliris GA, Kelly C, Kerskens C, Khokhar JY, Kind PC, Langlois JB, Lerch JP, López-Hidalgo MA, Manahan-Vaughan D, Marchand F, Mars RB, Marsella G, Micotti E, Muñoz-Moreno E, Near J, Niendorf T, Otte WM, Pais-Roldán P, Pan WJ, Prado-Alcalá RA, Quirarte GL, Rodger J, Rosenow T, Sampaio-Baptista C, Sartorius A, Sawiak SJ, Scheenen TWJ, Shemesh N, Shih YYI, Shmuel A, Soria G, Stoop R, Thompson GJ, Till SM, Todd N, Van Der Linden A, van der Toorn A, van Tilborg GAF, Vanhove C, Veltien A, Verhoye M, Wachsmuth L, Weber-Fahr W, Wenk P, Yu X, Zerbi V, Zhang N, Zhang BB, Zimmer L, Devenyi GA, Chakravarty MM, Hess A. A consensus protocol for functional connectivity analysis in the rat brain. Nat Neurosci 2023; 26:673-681. [PMID: 36973511 PMCID: PMC10493189 DOI: 10.1038/s41593-023-01286-8] [Citation(s) in RCA: 19] [Impact Index Per Article: 19.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2022] [Accepted: 02/15/2023] [Indexed: 03/29/2023]
Abstract
Task-free functional connectivity in animal models provides an experimental framework to examine connectivity phenomena under controlled conditions and allows for comparisons with data modalities collected under invasive or terminal procedures. Currently, animal acquisitions are performed with varying protocols and analyses that hamper result comparison and integration. Here we introduce StandardRat, a consensus rat functional magnetic resonance imaging acquisition protocol tested across 20 centers. To develop this protocol with optimized acquisition and processing parameters, we initially aggregated 65 functional imaging datasets acquired from rats across 46 centers. We developed a reproducible pipeline for analyzing rat data acquired with diverse protocols and determined experimental and processing parameters associated with the robust detection of functional connectivity across centers. We show that the standardized protocol enhances biologically plausible functional connectivity patterns relative to previous acquisitions. The protocol and processing pipeline described here is openly shared with the neuroimaging community to promote interoperability and cooperation toward tackling the most important challenges in neuroscience.
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Affiliation(s)
- Joanes Grandjean
- Donders Institute for Brain, Behaviour, and Cognition, Radboud University, Nijmegen, The Netherlands.
- Department for Medical Imaging, Radboud University Medical Center, Nijmegen, The Netherlands.
| | - Gabriel Desrosiers-Gregoire
- Cerebral Imaging Centre, Douglas Mental Health University Institute, Verdun, QC, Canada
- Integrated Program in Neuroscience, McGill University, Montreal, QC, Canada
| | - Cynthia Anckaerts
- Bio-imaging Lab, University of Antwerp, Antwerp, Belgium
- µNEURO Research Centre of Excellence, University of Antwerp, Antwerp, Belgium
| | - Diego Angeles-Valdez
- Instituto de Neurobiología, Universidad Nacional Autónoma de México, Campus Juriquilla, Querétaro, Mexico
| | - Fadi Ayad
- Biological and Biomedical Engineering, McGill University, Montreal, QC, Canada
- McConnell Brain Imaging Centre, McGill University, Montreal, QC, Canada
- Montreal Neurological Institute, McGill University, Montreal, QC, Canada
| | - David A Barrière
- UMR INRAE/CNRS 7247 Physiologie des Comportements et de la Reproduction, Physiologie de la reproduction et des comportements, Centre de recherche INRAE de Nouzilly, Tours, France
| | - Ines Blockx
- Bio-imaging Lab, University of Antwerp, Antwerp, Belgium
- µNEURO Research Centre of Excellence, University of Antwerp, Antwerp, Belgium
| | - Aleksandra Bortel
- McConnell Brain Imaging Centre, McGill University, Montreal, QC, Canada
- Montreal Neurological Institute, McGill University, Montreal, QC, Canada
- Department of Neurology and Neurosurgery, McGill University, Montreal, QC, Canada
| | - Margaret Broadwater
- Center for Animal MRI, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Department of Neurology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Biomedical Research Imaging Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Beatriz M Cardoso
- Preclinical MRI, Champalimaud Research, Champalimaud Centre for the Unknown, Lisbon, Portugal
| | - Marina Célestine
- Laboratoire des Maladies Neurodégénératives, Molecular Imaging Research Center (MIRCen), Université Paris-Saclay, Commissariat à l'Énergie Atomique et aux Énergies Alternatives (CEA), CNRS, Fontenay-aux-Roses, France
| | - Jorge E Chavez-Negrete
- Departamento de Neurobiología Conductual y Cognitiva, Instituto de Neurobiología, Universidad Nacional Autónoma de México, Campus Juriquilla, Querétaro, México
| | - Sangcheon Choi
- Translational Neuroimaging and Neural Control Group, High-Field Magnetic Resonance, Max Planck Institute for Biological Cybernetics, Tuebingen, Germany
- Graduate Training Centre of Neuroscience, International Max Planck Research School, University of Tuebingen, Tuebingen, Germany
| | - Emma Christiaen
- Institute Biomedical Technology (IBiTech), Electronics and Information Systems (ELIS), Ghent University, Gent, Belgium
| | - Perrin Clavijo
- Department of Biomedical Engineering, Emory University/Georgia Institute of Technology, Atlanta, GA, USA
| | - Luis Colon-Perez
- Department of Pharmacology & Neuroscience, University of North Texas Health Science Center, Fort Worth, TX, USA
| | - Samuel Cramer
- Translational Neuroimaging and Systems Neuroscience Lab, Biomedical Engineering, Pennsylvania State University, University Park, PA, USA
| | - Tolomeo Daniele
- Centre for Advanced Biomedical Imaging, University College London, London, UK
| | - Elaine Dempsey
- Neuropsychopharmacology Research Group, School of Pharmacy and Pharmaceutical Sciences, Trinity College Dublin, Dublin, Ireland
- Trinity College Institute of Neuroscience, Trinity College Dublin, Dublin, Ireland
| | - Yujian Diao
- CIBM Center for Biomedical Imaging, Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
- Laboratory for Functional and Metabolic Imaging, Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
| | - Arno Doelemeyer
- Musculoskeletal Diseases Department, Novartis Institutes for BioMedical Research, Basel, Switzerland
| | - David Dopfel
- Translational Neuroimaging and Systems Neuroscience Lab, Biomedical Engineering, Pennsylvania State University, University Park, PA, USA
| | - Lenka Dvořáková
- Biomedical Imaging Unit, A.I.V. Institute for Molecular Sciences, University of Eastern Finland, Kuopio, Finland
| | - Claudia Falfán-Melgoza
- Translational Imaging, Department of Neuroimaging, Central Institute of Mental Health, Medical Faculty Mannheim, Mannheim, Germany
| | - Francisca F Fernandes
- Preclinical MRI, Champalimaud Research, Champalimaud Centre for the Unknown, Lisbon, Portugal
| | - Caitlin F Fowler
- Cerebral Imaging Centre, Douglas Mental Health University Institute, Verdun, QC, Canada
- Biological and Biomedical Engineering, McGill University, Montreal, QC, Canada
| | - Antonio Fuentes-Ibañez
- Departamento de Neurobiología Conductual y Cognitiva, Instituto de Neurobiología, Universidad Nacional Autónoma de México, Campus Juriquilla, Querétaro, México
| | - Clément M Garin
- Laboratoire des Maladies Neurodégénératives, Molecular Imaging Research Center (MIRCen), Université Paris-Saclay, Commissariat à l'Énergie Atomique et aux Énergies Alternatives (CEA), CNRS, Fontenay-aux-Roses, France
| | - Eveline Gelderman
- Donders Institute for Brain, Behaviour, and Cognition, Radboud University, Nijmegen, The Netherlands
| | - Carla E M Golden
- Seaver Autism Center for Research & Treatment, Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York City, NY, USA
| | - Chao C G Guo
- Donders Institute for Brain, Behaviour, and Cognition, Radboud University, Nijmegen, The Netherlands
| | - Marloes J A G Henckens
- Donders Institute for Brain, Behaviour, and Cognition, Radboud University, Nijmegen, The Netherlands
- Department of Neuroscience and Pharmacology, Rudolf Magnus Institute of Neuroscience, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Lauren A Hennessy
- Experimental and Regenerative Neurosciences, School of Biological Sciences, University of Western Australia, Crawley, WA, Australia
- Brain Plasticity Group, Perron Institute for Neurological and Translational Science, Nedlands, WA, Australia
| | - Peter Herman
- Radiology and Biomedical Imaging, Yale University School of Medicine, New Haven, CT, USA
- Quantitative Neuroscience with Magnetic Resonance (QNMR) Core Center, Yale University School of Medicine, New Haven, CT, USA
| | - Nita Hofwijks
- Donders Institute for Brain, Behaviour, and Cognition, Radboud University, Nijmegen, The Netherlands
| | - Corey Horien
- Radiology and Biomedical Imaging, Yale University School of Medicine, New Haven, CT, USA
| | - Tudor M Ionescu
- Werner Siemens Imaging Center, Department of Preclinical Imaging and Radiopharmacy, University of Tuebingen, Tuebingen, Germany
| | - Jolyon Jones
- Department of Psychology, University of Cambridge, Cambridge, UK
| | - Johannes Kaesser
- Institute of Experimental and Clinical Pharmacology and Toxicology, FAU Erlangen-Nürnberg, Erlangen, Germany
| | - Eugene Kim
- Biomarker Research And Imaging in Neuroscience (BRAIN) Centre, Department of Neuroimaging King's College London, London, UK
| | - Henriette Lambers
- Experimental Magnetic Resonance Group, Clinic of Radiology, University of Münster, Münster, Germany
| | - Alberto Lazari
- Nuffield Department of Clinical Neurosciences, Wellcome Centre for Integrative Neuroimaging, FMRIB, University of Oxford, John Radcliffe Hospital, Headington, Oxford, UK
| | - Sung-Ho Lee
- Center for Animal MRI, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Department of Neurology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Biomedical Research Imaging Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Amanda Lillywhite
- School of Life Sciences, University of Nottingham, Nottingham, UK
- Pain Centre Versus Arthritis, University of Nottingham, Nottingham, UK
| | - Yikang Liu
- Translational Neuroimaging and Systems Neuroscience Lab, Biomedical Engineering, Pennsylvania State University, University Park, PA, USA
| | - Yanyan Y Liu
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing, China
| | - Alejandra López-Castro
- Instituto de Neurobiología, Universidad Nacional Autónoma de México, Campus Juriquilla, Querétaro, Mexico
| | - Xavier López-Gil
- Magnetic Imaging Resonance Core Facility, Institut d'Investigacions Biomèdiques August Pi I Sunyer (IDIBAPS), Barcelona, Spain
| | - Zilu Ma
- Translational Neuroimaging and Systems Neuroscience Lab, Biomedical Engineering, Pennsylvania State University, University Park, PA, USA
| | - Eilidh MacNicol
- Biomarker Research And Imaging in Neuroscience (BRAIN) Centre, Department of Neuroimaging King's College London, London, UK
| | - Dan Madularu
- Biological and Biomedical Engineering, McGill University, Montreal, QC, Canada
- Center for Translational Neuroimaging, Northeastern University, Boston, MA, USA
| | - Francesca Mandino
- Radiology and Biomedical Imaging, Yale University School of Medicine, New Haven, CT, USA
| | - Sabina Marciano
- Werner Siemens Imaging Center, Department of Preclinical Imaging and Radiopharmacy, University of Tuebingen, Tuebingen, Germany
| | - Matthew J McAuslan
- Neuropsychopharmacology Research Group, School of Pharmacy and Pharmaceutical Sciences, Trinity College Dublin, Dublin, Ireland
| | - Patrick McCunn
- Khokhar Lab, Department of Anatomy and Cell Biology, Western University, London, ON, Canada
| | - Alison McIntosh
- Neuropsychopharmacology Research Group, School of Pharmacy and Pharmaceutical Sciences, Trinity College Dublin, Dublin, Ireland
- Trinity College Institute of Neuroscience, Trinity College Dublin, Dublin, Ireland
| | - Xianzong Meng
- Donders Institute for Brain, Behaviour, and Cognition, Radboud University, Nijmegen, The Netherlands
| | - Lisa Meyer-Baese
- Department of Biomedical Engineering, Emory University/Georgia Institute of Technology, Atlanta, GA, USA
| | - Stephan Missault
- Bio-imaging Lab, University of Antwerp, Antwerp, Belgium
- µNEURO Research Centre of Excellence, University of Antwerp, Antwerp, Belgium
| | - Federico Moro
- Laboratory of Acute Brain Injury and Therapeutic Strategies, Department of NeuroscienceIstituto di Ricerche Farmacologiche Mario Negri, IRCCS, Milan, Italy
| | - Daphne M P Naessens
- Biomedical Engineering and Physics, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands
| | - Laura J Nava-Gomez
- Facultad de Medicina, Universidad Autónoma de Querétaro, Querétaro, México
- Escuela Nacional de Estudios Superiores, Juriquilla, Universidad Nacional Autónoma de México, Querétaro, México
| | - Hiroi Nonaka
- Institute of Development, Aging and Cancer, Tohoku University, Sendai, Japan
| | - Juan J Ortiz
- Departamento de Neurobiología Conductual y Cognitiva, Instituto de Neurobiología, Universidad Nacional Autónoma de México, Campus Juriquilla, Querétaro, México
| | - Jaakko Paasonen
- Biomedical Imaging Unit, A.I.V. Institute for Molecular Sciences, University of Eastern Finland, Kuopio, Finland
| | - Lore M Peeters
- Bio-imaging Lab, University of Antwerp, Antwerp, Belgium
- µNEURO Research Centre of Excellence, University of Antwerp, Antwerp, Belgium
| | - Mickaël Pereira
- Lyon Neuroscience Research Center, Université Claude Bernard Lyon 1, INSERM, CNRS, Lyon, France
| | - Pablo D Perez
- Translational Neuroimaging and Systems Neuroscience Lab, Biomedical Engineering, Pennsylvania State University, University Park, PA, USA
| | - Marjory Pompilus
- Febo Laboratory, Department of Psychiatry, University of Florida, Gainesville, FL, USA
| | - Malcolm Prior
- School of Medicine, University of Nottingham, Nottingham, UK
| | | | - Henning M Reimann
- Berlin Ultrahigh Field Facility (B.U.F.F.), Max-Delbrück Center for Molecular Medicine in the Helmholtz Association, Berlin, Germany
| | - Jonathan Reinwald
- Translational Imaging, Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany
| | - Rodrigo Triana Del Rio
- Psychiatric neurosciences, Center for Psychiatric Neuroscience, Lausanne University and University Hospital Center, Unicentre, Lausanne, Switzerland
| | - Alejandro Rivera-Olvera
- Donders Institute for Brain, Behaviour, and Cognition, Radboud University, Nijmegen, The Netherlands
| | | | - Gabriele Russo
- Department of Neurophysiology, Medical Faculty, Ruhr University Bochum, Bochum, Germany
| | - Tobias J Rutten
- Donders Institute for Brain, Behaviour, and Cognition, Radboud University, Nijmegen, The Netherlands
| | - Rie Ryoke
- Institute of Development, Aging and Cancer, Tohoku University, Sendai, Japan
| | - Markus Sack
- Translational Imaging, Department of Neuroimaging, Central Institute of Mental Health, Medical Faculty Mannheim, Mannheim, Germany
| | - Piergiorgio Salvan
- Nuffield Department of Clinical Neurosciences, Wellcome Centre for Integrative Neuroimaging, FMRIB, University of Oxford, John Radcliffe Hospital, Headington, Oxford, UK
| | - Basavaraju G Sanganahalli
- Radiology and Biomedical Imaging, Yale University School of Medicine, New Haven, CT, USA
- Quantitative Neuroscience with Magnetic Resonance (QNMR) Core Center, Yale University School of Medicine, New Haven, CT, USA
| | - Aileen Schroeter
- Institute for Biomedical Engineering, University and ETH Zurich, Zurich, Switzerland
| | - Bhedita J Seewoo
- Experimental and Regenerative Neurosciences, School of Biological Sciences, University of Western Australia, Crawley, WA, Australia
- Brain Plasticity Group, Perron Institute for Neurological and Translational Science, Nedlands, WA, Australia
- Centre for Microscopy, Characterisation & Analysis, Research Infrastructure Centres, University of Western Australia, Nedlands, WA, Australia
| | | | - Aline Seuwen
- Institute for Biomedical Engineering, University and ETH Zurich, Zurich, Switzerland
| | - Bowen Shi
- iHuman Institute, ShanghaiTech University, Shanghai, China
| | - Nikoloz Sirmpilatze
- Functional Imaging Laboratory, German Primate Center - Leibniz Institute for Primate Research, Göttingen, Germany
- Faculty of Biology and Psychology, Georg-August University of Göttingen, Göttingen, Germany
- DFG Research Center for Nanoscale Microscopy and Molecular Physiology of the Brain (CNMPB), Göttingen, Germany
| | - Joanna A B Smith
- Simons Initiative for the Developing Brain, University of Edinburgh, Edinburgh, UK
- Patrick Wild Centre, University of Edinburgh, Edinburgh, UK
- Centre for Discovery Brain Sciences, University of Edinburgh, Edinburgh, UK
| | - Corrie Smith
- Department of Biomedical Engineering, Emory University/Georgia Institute of Technology, Atlanta, GA, USA
| | - Filip Sobczak
- Translational Neuroimaging and Neural Control Group, High-Field Magnetic Resonance, Max Planck Institute for Biological Cybernetics, Tuebingen, Germany
- Graduate Training Centre of Neuroscience, International Max Planck Research School, University of Tuebingen, Tuebingen, Germany
| | - Petteri J Stenroos
- Univ. Grenoble Alpes, Inserm, U1216, Grenoble Institut Neurosciences, Grenoble, France
| | - Milou Straathof
- Biomedical MR Imaging and Spectroscopy Group, Center for Image Sciences, University Medical Center Utrecht & Utrecht University, Utrecht, The Netherlands
| | - Sandra Strobelt
- Institute of Experimental and Clinical Pharmacology and Toxicology, FAU Erlangen-Nürnberg, Erlangen, Germany
| | - Akira Sumiyoshi
- Institute of Development, Aging and Cancer, Tohoku University, Sendai, Japan
- National Institutes for Quantum Science and Technology, Chiba, Japan
| | - Kengo Takahashi
- Translational Neuroimaging and Neural Control Group, High-Field Magnetic Resonance, Max Planck Institute for Biological Cybernetics, Tuebingen, Germany
- Graduate Training Centre of Neuroscience, International Max Planck Research School, University of Tuebingen, Tuebingen, Germany
| | - Maria E Torres-García
- Departamento de Neurobiología Conductual y Cognitiva, Instituto de Neurobiología, Universidad Nacional Autónoma de México, Campus Juriquilla, Querétaro, México
| | - Raul Tudela
- Group of Biomedical Imaging, Consorcio Centro de Investigación Biomédica en Red (CIBER) de Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN), University of Barcelona, Barcelona, Spain
| | - Monica van den Berg
- Bio-imaging Lab, University of Antwerp, Antwerp, Belgium
- µNEURO Research Centre of Excellence, University of Antwerp, Antwerp, Belgium
| | - Kajo van der Marel
- Biomedical MR Imaging and Spectroscopy Group, Center for Image Sciences, University Medical Center Utrecht & Utrecht University, Utrecht, The Netherlands
| | - Aran T B van Hout
- Donders Institute for Brain, Behaviour, and Cognition, Radboud University, Nijmegen, The Netherlands
| | - Roberta Vertullo
- Donders Institute for Brain, Behaviour, and Cognition, Radboud University, Nijmegen, The Netherlands
| | - Benjamin Vidal
- Lyon Neuroscience Research Center, Université Claude Bernard Lyon 1, INSERM, CNRS, Lyon, France
| | - Roël M Vrooman
- Donders Institute for Brain, Behaviour, and Cognition, Radboud University, Nijmegen, The Netherlands
| | - Victora X Wang
- BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York City, NY, USA
| | - Isabel Wank
- Institute of Experimental and Clinical Pharmacology and Toxicology, FAU Erlangen-Nürnberg, Erlangen, Germany
| | - David J G Watson
- School of Life Sciences, University of Nottingham, Nottingham, UK
| | - Ting Yin
- Animal Imaging and Technology Section, Center for Biomedical Imaging, École polytechnique fédérale de Lausanne, Lausanne, Switzerland
| | - Yongzhi Zhang
- Focused Ultrasound Laboratory, Department of Radiology Brigham and Women's Hospital, Boston, MA, USA
| | - Stefan Zurbruegg
- Neurosciences Department, Novartis Institutes for BioMedical Research, Basel, Switzerland
| | - Sophie Achard
- Inria, University Grenoble Alpes, CNRS, Grenoble, France
| | - Sarael Alcauter
- Departamento de Neurobiología Conductual y Cognitiva, Instituto de Neurobiología, Universidad Nacional Autónoma de México, Campus Juriquilla, Querétaro, México
| | - Dorothee P Auer
- School of Medicine, University of Nottingham, Nottingham, UK
- NIHR Biomedical Research Centre, University of Nottingham, Nottingham, UK
| | - Emmanuel L Barbier
- Univ. Grenoble Alpes, Inserm, U1216, Grenoble Institut Neurosciences, Grenoble, France
| | - Jürgen Baudewig
- Functional Imaging Laboratory, German Primate Center - Leibniz Institute for Primate Research, Göttingen, Germany
| | - Christian F Beckmann
- Donders Institute for Brain, Behaviour, and Cognition, Radboud University, Nijmegen, The Netherlands
- Nuffield Department of Clinical Neurosciences, Wellcome Centre for Integrative Neuroimaging, FMRIB, University of Oxford, John Radcliffe Hospital, Headington, Oxford, UK
| | - Nicolau Beckmann
- Musculoskeletal Diseases Department, Novartis Institutes for BioMedical Research, Basel, Switzerland
| | | | - Erwin L A Blezer
- Biomedical MR Imaging and Spectroscopy Group, Center for Image Sciences, University Medical Center Utrecht & Utrecht University, Utrecht, The Netherlands
| | | | - Susann Boretius
- Functional Imaging Laboratory, German Primate Center - Leibniz Institute for Primate Research, Göttingen, Germany
- Faculty of Biology and Psychology, Georg-August University of Göttingen, Göttingen, Germany
- DFG Research Center for Nanoscale Microscopy and Molecular Physiology of the Brain (CNMPB), Göttingen, Germany
| | - Sandrine Bouvard
- Lyon Neuroscience Research Center, Université Claude Bernard Lyon 1, INSERM, CNRS, Lyon, France
| | - Eike Budinger
- Combinatorial NeuroImaging Core Facility, Leibniz Institute for Neurobiology, Magdeburg, Germany
- Center for Behavioral Brain Sciences, Magdeburg, Germany
| | - Joseph D Buxbaum
- Seaver Autism Center for Research & Treatment, Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York City, NY, USA
| | - Diana Cash
- Biomarker Research And Imaging in Neuroscience (BRAIN) Centre, Department of Neuroimaging King's College London, London, UK
| | - Victoria Chapman
- School of Life Sciences, University of Nottingham, Nottingham, UK
- Pain Centre Versus Arthritis, University of Nottingham, Nottingham, UK
- NIHR Biomedical Research Centre, University of Nottingham, Nottingham, UK
| | - Kai-Hsiang Chuang
- Queensland Brain Institute and Centre for Advanced Imaging, University of Queensland, St. Lucia, QLD, Australia
| | | | - Bram F Coolen
- Biomedical Engineering and Physics, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands
| | - Jeffrey W Dalley
- Department of Psychology, University of Cambridge, Cambridge, UK
| | - Marc Dhenain
- Laboratoire des Maladies Neurodégénératives, Molecular Imaging Research Center (MIRCen), Université Paris-Saclay, Commissariat à l'Énergie Atomique et aux Énergies Alternatives (CEA), CNRS, Fontenay-aux-Roses, France
| | - Rick M Dijkhuizen
- Biomedical MR Imaging and Spectroscopy Group, Center for Image Sciences, University Medical Center Utrecht & Utrecht University, Utrecht, The Netherlands
| | - Oscar Esteban
- Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Cornelius Faber
- Experimental Magnetic Resonance Group, Clinic of Radiology, University of Münster, Münster, Germany
| | - Marcelo Febo
- Febo Laboratory, Department of Psychiatry, University of Florida, Gainesville, FL, USA
| | - Kirk W Feindel
- Centre for Microscopy, Characterisation & Analysis, Research Infrastructure Centres, University of Western Australia, Nedlands, WA, Australia
| | - Gianluigi Forloni
- Biology of Neurodogenerative Disorders, Department of Neuroscience Istituto di Ricerche Farmacologiche Mario Negri, IRCCS, Milan, Italy
| | - Jérémie Fouquet
- Cerebral Imaging Centre, Douglas Mental Health University Institute, Verdun, QC, Canada
| | - Eduardo A Garza-Villarreal
- Instituto de Neurobiología, Universidad Nacional Autónoma de México, Campus Juriquilla, Querétaro, Mexico
| | - Natalia Gass
- Translational Imaging, Department of Neuroimaging, Central Institute of Mental Health, Medical Faculty Mannheim, Mannheim, Germany
| | - Jeffrey C Glennon
- Conway Institute of Biomedical and Biomolecular Sciences, School of Medicine, University College Dublin, Dublin, Ireland
| | - Alessandro Gozzi
- Functional Neuroimaging Laboratory, Center for Neuroscience and Cognitive Systems, Istituto Italiano di Tecnologia, Rovereto, Italy
| | - Olli Gröhn
- Biomedical Imaging Unit, A.I.V. Institute for Molecular Sciences, University of Eastern Finland, Kuopio, Finland
| | - Andrew Harkin
- Neuropsychopharmacology Research Group, School of Pharmacy and Pharmaceutical Sciences, Trinity College Dublin, Dublin, Ireland
- Trinity College Institute of Neuroscience, Trinity College Dublin, Dublin, Ireland
| | - Arend Heerschap
- Department for Medical Imaging, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Xavier Helluy
- Department of Neurophysiology, Medical Faculty, Ruhr University Bochum, Bochum, Germany
- Department of Biopsychology, Institute of Cognitive Neuroscience, Ruhr University Bochum, Bochum, Germany
| | - Kristina Herfert
- Werner Siemens Imaging Center, Department of Preclinical Imaging and Radiopharmacy, University of Tuebingen, Tuebingen, Germany
| | - Arnd Heuser
- Max-Delbrück Center for Molecular Medicine in the Helmholtz Association, Berlin, Germany
| | - Judith R Homberg
- Donders Institute for Brain, Behaviour, and Cognition, Radboud University, Nijmegen, The Netherlands
| | - Danielle J Houwing
- Donders Institute for Brain, Behaviour, and Cognition, Radboud University, Nijmegen, The Netherlands
| | - Fahmeed Hyder
- Radiology and Biomedical Imaging, Yale University School of Medicine, New Haven, CT, USA
- Quantitative Neuroscience with Magnetic Resonance (QNMR) Core Center, Yale University School of Medicine, New Haven, CT, USA
| | | | - Ileana O Jelescu
- CIBM Center for Biomedical Imaging, Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
| | - Heidi Johansen-Berg
- Nuffield Department of Clinical Neurosciences, Wellcome Centre for Integrative Neuroimaging, FMRIB, University of Oxford, John Radcliffe Hospital, Headington, Oxford, UK
| | - Gen Kaneko
- School of Arts & Sciences, University of Houston-Victoria, Victoria, TX, USA
| | - Ryuta Kawashima
- Institute of Development, Aging and Cancer, Tohoku University, Sendai, Japan
| | - Shella D Keilholz
- Department of Biomedical Engineering, Emory University/Georgia Institute of Technology, Atlanta, GA, USA
| | - Georgios A Keliris
- Bio-imaging Lab, University of Antwerp, Antwerp, Belgium
- µNEURO Research Centre of Excellence, University of Antwerp, Antwerp, Belgium
| | - Clare Kelly
- Trinity College Institute of Neuroscience, Trinity College Dublin, Dublin, Ireland
- School of Psychology, Trinity College Dublin, Dublin, Ireland
- Department of Psychiatry, School of Medicine, Trinity College Dublin, Dublin, Ireland
| | - Christian Kerskens
- Trinity College Institute of Neuroscience, Trinity College Dublin, Dublin, Ireland
- Trinity Centre for Biomedical Engineering, School of Medicine, Trinity College Dublin, Dublin, Ireland
| | - Jibran Y Khokhar
- Khokhar Lab, Department of Anatomy and Cell Biology, Western University, London, ON, Canada
| | - Peter C Kind
- Simons Initiative for the Developing Brain, University of Edinburgh, Edinburgh, UK
- Patrick Wild Centre, University of Edinburgh, Edinburgh, UK
- Centre for Discovery Brain Sciences, University of Edinburgh, Edinburgh, UK
- Centre for Brain Development and Repair, Institute for Stem Cell Biology and Regenerative Medicine, Bangalore, India
| | | | - Jason P Lerch
- Nuffield Department of Clinical Neurosciences, Wellcome Centre for Integrative Neuroimaging, FMRIB, University of Oxford, John Radcliffe Hospital, Headington, Oxford, UK
- Department of Medical Biophysics, University of Toronto, Toronto, QC, Canada
| | - Monica A López-Hidalgo
- Escuela Nacional de Estudios Superiores, Juriquilla, Universidad Nacional Autónoma de México, Querétaro, México
| | | | - Fabien Marchand
- Université Clermont Auvergne, Inserm U1107 Neuro-Dol, Pharmacologie Fondamentale et Clinique de la Douleur, Clermont-Ferrand, France
| | - Rogier B Mars
- Donders Institute for Brain, Behaviour, and Cognition, Radboud University, Nijmegen, The Netherlands
- Nuffield Department of Clinical Neurosciences, Wellcome Centre for Integrative Neuroimaging, FMRIB, University of Oxford, John Radcliffe Hospital, Headington, Oxford, UK
| | - Gerardo Marsella
- Animal Care Unit, Istituto di Ricerche Farmacologiche Mario Negri, IRCCS, Milan, Italy
| | - Edoardo Micotti
- Biology of Neurodogenerative Disorders, Department of Neuroscience Istituto di Ricerche Farmacologiche Mario Negri, IRCCS, Milan, Italy
| | - Emma Muñoz-Moreno
- Magnetic Imaging Resonance Core Facility, Institut d'Investigacions Biomèdiques August Pi I Sunyer (IDIBAPS), Barcelona, Spain
| | - Jamie Near
- Cerebral Imaging Centre, Douglas Mental Health University Institute, Verdun, QC, Canada
- Physical Sciences Platform, Sunnybrook Research Institute, Toronto, QC, Canada
| | - Thoralf Niendorf
- Berlin Ultrahigh Field Facility (B.U.F.F.), Max-Delbrück Center for Molecular Medicine in the Helmholtz Association, Berlin, Germany
- Experimental and Clinical Research Center, A Joint Cooperation Between the Charité Medical Faculty and the Max-Delbrück Center for Molecular Medicine in the Helmholtz Association, Berlin, Germany
| | - Willem M Otte
- Biomedical MR Imaging and Spectroscopy Group, Center for Image Sciences, University Medical Center Utrecht & Utrecht University, Utrecht, The Netherlands
- Department of Pediatric Neurology, UMC Utrecht Brain Center, University Medical Center Utrecht & Utrecht University, Utrecht, The Netherlands
| | - Patricia Pais-Roldán
- Translational Neuroimaging and Neural Control Group, High-Field Magnetic Resonance, Max Planck Institute for Biological Cybernetics, Tuebingen, Germany
- Medical Imaging Physics (INM-4), Institute of Neuroscience and Medicine, Forschungszentrum Juelich, Juelich, Germany
| | - Wen-Ju Pan
- Department of Biomedical Engineering, Emory University/Georgia Institute of Technology, Atlanta, GA, USA
| | - Roberto A Prado-Alcalá
- Departamento de Neurobiología Conductual y Cognitiva, Instituto de Neurobiología, Universidad Nacional Autónoma de México, Campus Juriquilla, Querétaro, México
| | - Gina L Quirarte
- Departamento de Neurobiología Conductual y Cognitiva, Instituto de Neurobiología, Universidad Nacional Autónoma de México, Campus Juriquilla, Querétaro, México
| | - Jennifer Rodger
- Experimental and Regenerative Neurosciences, School of Biological Sciences, University of Western Australia, Crawley, WA, Australia
- Brain Plasticity Group, Perron Institute for Neurological and Translational Science, Nedlands, WA, Australia
| | - Tim Rosenow
- Centre for Microscopy, Characterisation and Analysis, University of Western Australia, Crawley, WA, Australia
| | - Cassandra Sampaio-Baptista
- Nuffield Department of Clinical Neurosciences, Wellcome Centre for Integrative Neuroimaging, FMRIB, University of Oxford, John Radcliffe Hospital, Headington, Oxford, UK
- School of Psychology and Neuroscience, University of Glasgow, Glasgow, UK
| | - Alexander Sartorius
- Translational Imaging, Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany
| | - Stephen J Sawiak
- Translational Neuroimaging Laboratory, Physiology, Development and Neuroscience, University of Cambridge, Cambridge, UK
| | - Tom W J Scheenen
- Department for Medical Imaging, Radboud University Medical Center, Nijmegen, The Netherlands
- Erwin L. Hahn Institute for MR Imaging, University of Duisburg-Essen, Essen, Germany
| | - Noam Shemesh
- Preclinical MRI, Champalimaud Research, Champalimaud Centre for the Unknown, Lisbon, Portugal
| | - Yen-Yu Ian Shih
- Center for Animal MRI, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Department of Neurology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Biomedical Research Imaging Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Biomedical Engineering, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Amir Shmuel
- Biological and Biomedical Engineering, McGill University, Montreal, QC, Canada
- McConnell Brain Imaging Centre, McGill University, Montreal, QC, Canada
- Montreal Neurological Institute, McGill University, Montreal, QC, Canada
- Department of Neurology and Neurosurgery, McGill University, Montreal, QC, Canada
- Department of Physiology, McGill University, Montreal, QC, Canada
| | - Guadalupe Soria
- Laboratory of Surgical Neuroanatomy, Institute of Neuroscience, University of Barcelona, Barcelona, Spain
| | - Ron Stoop
- Psychiatric neurosciences, Center for Psychiatric Neuroscience, Lausanne University and University Hospital Center, Unicentre, Lausanne, Switzerland
| | | | - Sally M Till
- Simons Initiative for the Developing Brain, University of Edinburgh, Edinburgh, UK
- Patrick Wild Centre, University of Edinburgh, Edinburgh, UK
- Centre for Discovery Brain Sciences, University of Edinburgh, Edinburgh, UK
| | - Nick Todd
- Focused Ultrasound Laboratory, Department of Radiology Brigham and Women's Hospital, Boston, MA, USA
| | - Annemie Van Der Linden
- Bio-imaging Lab, University of Antwerp, Antwerp, Belgium
- µNEURO Research Centre of Excellence, University of Antwerp, Antwerp, Belgium
| | - Annette van der Toorn
- Biomedical MR Imaging and Spectroscopy Group, Center for Image Sciences, University Medical Center Utrecht & Utrecht University, Utrecht, The Netherlands
| | - Geralda A F van Tilborg
- Biomedical MR Imaging and Spectroscopy Group, Center for Image Sciences, University Medical Center Utrecht & Utrecht University, Utrecht, The Netherlands
| | - Christian Vanhove
- Institute Biomedical Technology (IBiTech), Electronics and Information Systems (ELIS), Ghent University, Gent, Belgium
| | - Andor Veltien
- Department for Medical Imaging, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Marleen Verhoye
- Bio-imaging Lab, University of Antwerp, Antwerp, Belgium
- µNEURO Research Centre of Excellence, University of Antwerp, Antwerp, Belgium
| | - Lydia Wachsmuth
- Experimental Magnetic Resonance Group, Clinic of Radiology, University of Münster, Münster, Germany
| | - Wolfgang Weber-Fahr
- Translational Imaging, Department of Neuroimaging, Central Institute of Mental Health, Medical Faculty Mannheim, Mannheim, Germany
| | - Patricia Wenk
- Combinatorial NeuroImaging Core Facility, Leibniz Institute for Neurobiology, Magdeburg, Germany
| | - Xin Yu
- Translational Neuroimaging and Neural Control Group, High-Field Magnetic Resonance, Max Planck Institute for Biological Cybernetics, Tuebingen, Germany
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA, USA
| | - Valerio Zerbi
- Neuro-X Institute, School of Engineering (STI), EPFL, Lausanne, Switzerland
- Centre for Biomedical Imaging (CIBM), Lausanne, Switzerland
| | - Nanyin Zhang
- Translational Neuroimaging and Systems Neuroscience Lab, Biomedical Engineering, Pennsylvania State University, University Park, PA, USA
| | - Baogui B Zhang
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing, China
| | - Luc Zimmer
- Lyon Neuroscience Research Center, Université Claude Bernard Lyon 1, INSERM, CNRS, Lyon, France
- CERMEP - Imagerie du vivant, Lyon, France
- Hospices Civils de Lyon, Lyon, France
| | - Gabriel A Devenyi
- Cerebral Imaging Centre, Douglas Mental Health University Institute, Verdun, QC, Canada
- Department of Psychiatry, McGill University, Montreal, QC, Canada
| | - M Mallar Chakravarty
- Cerebral Imaging Centre, Douglas Mental Health University Institute, Verdun, QC, Canada
- Biological and Biomedical Engineering, McGill University, Montreal, QC, Canada
- Department of Psychiatry, McGill University, Montreal, QC, Canada
| | - Andreas Hess
- Institute of Experimental and Clinical Pharmacology and Toxicology, FAU Erlangen-Nürnberg, Erlangen, Germany
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45
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Hu CY, Achari A, Rowe P, Xiao H, Suran S, Li Z, Huang K, Chi C, Cherian CT, Sreepal V, Bentley PD, Pratt A, Zhang N, Novoselov KS, Michaelides A, Nair RR. pH-dependent water permeability switching and its memory in MoS 2 membranes. Nature 2023; 616:719-723. [PMID: 37076621 DOI: 10.1038/s41586-023-05849-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2022] [Accepted: 02/15/2023] [Indexed: 04/21/2023]
Abstract
Intelligent transport of molecular species across different barriers is critical for various biological functions and is achieved through the unique properties of biological membranes1-4. Two essential features of intelligent transport are the ability to (1) adapt to different external and internal conditions and (2) memorize the previous state5. In biological systems, the most common form of such intelligence is expressed as hysteresis6. Despite numerous advances made over previous decades on smart membranes, it remains a challenge to create a synthetic membrane with stable hysteretic behaviour for molecular transport7-11. Here we demonstrate the memory effects and stimuli-regulated transport of molecules through an intelligent, phase-changing MoS2 membrane in response to external pH. We show that water and ion permeation through 1T' MoS2 membranes follows a pH-dependent hysteresis with a permeation rate that switches by a few orders of magnitude. We establish that this phenomenon is unique to the 1T' phase of MoS2, due to the presence of surface charge and exchangeable ions on the surface. We further demonstrate the potential application of this phenomenon in autonomous wound infection monitoring and pH-dependent nanofiltration. Our work deepens understanding of the mechanism of water transport at the nanoscale and opens an avenue for the development of intelligent membranes.
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Affiliation(s)
- C Y Hu
- National Graphene Institute, University of Manchester, Manchester, UK
- Department of Chemical Engineering, University of Manchester, Manchester, UK
- Department of Physics and Astronomy, University of Manchester, Manchester, UK
- College of Chemistry and Chemical Engineering, iChEM, Innovation Laboratory for Sciences and Technologies of Energy Materials of Fujian Province (IKKEM), Xiamen University, Xiamen, China
| | - A Achari
- National Graphene Institute, University of Manchester, Manchester, UK.
- Department of Chemical Engineering, University of Manchester, Manchester, UK.
| | - P Rowe
- Yusuf Hamied Department of Chemistry, University of Cambridge, Cambridge, UK
| | - H Xiao
- National Graphene Institute, University of Manchester, Manchester, UK
- Department of Chemical Engineering, University of Manchester, Manchester, UK
| | - S Suran
- National Graphene Institute, University of Manchester, Manchester, UK
- Department of Chemical Engineering, University of Manchester, Manchester, UK
| | - Z Li
- School of Chemical Engineering, Dalian University of Technology, Panjin, China
| | - K Huang
- National Graphene Institute, University of Manchester, Manchester, UK
- Department of Chemical Engineering, University of Manchester, Manchester, UK
| | - C Chi
- National Graphene Institute, University of Manchester, Manchester, UK
- Department of Chemical Engineering, University of Manchester, Manchester, UK
| | - C T Cherian
- National Graphene Institute, University of Manchester, Manchester, UK
- Department of Chemical Engineering, University of Manchester, Manchester, UK
- Department of Physics and Electronics, Christ University, Bangalore, India
| | - V Sreepal
- National Graphene Institute, University of Manchester, Manchester, UK
- Department of Chemical Engineering, University of Manchester, Manchester, UK
| | - P D Bentley
- School of Physics, Engineering and Technology, University of York, York, UK
| | - A Pratt
- School of Physics, Engineering and Technology, University of York, York, UK
| | - N Zhang
- National Graphene Institute, University of Manchester, Manchester, UK
- Department of Chemical Engineering, University of Manchester, Manchester, UK
- School of Chemical Engineering, Dalian University of Technology, Panjin, China
| | - K S Novoselov
- Department of Physics and Astronomy, University of Manchester, Manchester, UK
- Institute for Functional Intelligent Materials, National University of Singapore, Singapore, Singapore
| | - A Michaelides
- Yusuf Hamied Department of Chemistry, University of Cambridge, Cambridge, UK
| | - R R Nair
- National Graphene Institute, University of Manchester, Manchester, UK.
- Department of Chemical Engineering, University of Manchester, Manchester, UK.
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46
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Li Q, Zhang N. Sex differences in resting-state functional networks in awake rats. Res Sq 2023:rs.3.rs-2684325. [PMID: 36993730 PMCID: PMC10055639 DOI: 10.21203/rs.3.rs-2684325/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/13/2023]
Abstract
Sex-related differences can be found in many brain disorders and psychophysiological traits, highlighting the importance to systematically understand the sex differences in brain function in humans and animal models. Despite emerging effort to address sex differences in behaviors and disease models in rodents, how brain-wide functional connectivity (FC) patterns differ between male and female rats remains largely unknown. Here we used resting-state functional magnetic resonance imaging (rsfMRI) to investigate regional and systems-level differences between female and male rats. Our data show that female rats display stronger hypothalamus connectivity, whereas male rats exhibit more prominent striatum-related connectivity. At the global scale, female rats demonstrate stronger segregation within the cortical and subcortical systems, while male rats display more prominent cortico-subcortical interactions, particularly between the cortex and striatum. Taken together, these data provide a comprehensive framework of sex differences in resting-state connectivity patterns in the awake rat brain, and offer a reference for studies aiming to reveal sex-related FC differences in different animal models of brain disorders.
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Affiliation(s)
- Qiong Li
- The Pennsylvania State University
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47
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Zhang Q, Cramer SR, Turner KL, Neuberger T, Drew PJ, Zhang N. High-frequency neuronal signal better explains multi-phase BOLD response. Neuroimage 2023; 268:119887. [PMID: 36681134 PMCID: PMC9962576 DOI: 10.1016/j.neuroimage.2023.119887] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2022] [Revised: 01/16/2023] [Accepted: 01/17/2023] [Indexed: 01/20/2023] Open
Abstract
Visual stimulation-evoked blood-oxygen-level dependent (BOLD) responses can exhibit more complex temporal dynamics than a simple monophasic response. For instance, BOLD responses sometimes include a phase of positive response followed by a phase of post-stimulus undershoot. Whether the BOLD response during these phases reflects the underlying neuronal signal fluctuations or is contributed by non-neuronal physiological factors remains elusive. When presenting blocks of sustained (i.e. DC) light ON-OFF stimulations to unanesthetized rats, we observed that the response following a decrease in illumination (i.e. OFF stimulation-evoked BOLD response) in the visual cortices displayed reproducible multiple phases, including an initial positive BOLD response, followed by an undershoot and then an overshoot before the next ON trial. This multi-phase BOLD response did not result from the entrainment of the periodic stimulation structure. When we measured the neural correlates of these responses, we found that the high-frequency band from the LFP power (300 - 3000 Hz, multi-unit activity (MUA)), but not the power in the gamma band (30 - 100 Hz) exhibited the same multiphasic dynamics as the BOLD signal. This study suggests that the post-stimulus phases of the BOLD response can be better explained by the high-frequency neuronal signal.
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Affiliation(s)
- Qingqing Zhang
- Department of Biomedical Engineering, The Pennsylvania State University, University Park, USA; Center for Neurotechnology in Mental Health Research, The Pennsylvania State University, University Park 16802, USA; Center for Neural Engineering, The Pennsylvania State University, University Park 16802, USA
| | - Samuel R Cramer
- The Neuroscience Graduate Program, The Huck Institutes of the Life Sciences, The Pennsylvania State University, University Park, USA; Center for Neurotechnology in Mental Health Research, The Pennsylvania State University, University Park 16802, USA; Center for Neural Engineering, The Pennsylvania State University, University Park 16802, USA
| | - Kevin L Turner
- Department of Biomedical Engineering, The Pennsylvania State University, University Park, USA; Center for Neurotechnology in Mental Health Research, The Pennsylvania State University, University Park 16802, USA; Center for Neural Engineering, The Pennsylvania State University, University Park 16802, USA
| | - Thomas Neuberger
- Department of Biomedical Engineering, The Pennsylvania State University, University Park, USA; Center for Neurotechnology in Mental Health Research, The Pennsylvania State University, University Park 16802, USA
| | - Patrick J Drew
- Department of Biomedical Engineering, The Pennsylvania State University, University Park, USA; The Neuroscience Graduate Program, The Huck Institutes of the Life Sciences, The Pennsylvania State University, University Park, USA; Center for Neurotechnology in Mental Health Research, The Pennsylvania State University, University Park 16802, USA; Center for Neural Engineering, The Pennsylvania State University, University Park 16802, USA; Departments of Engineering Science and Mechanics, Neurosurgery, and Biology, The Pennsylvania State University, University Park, USA
| | - Nanyin Zhang
- Department of Biomedical Engineering, The Pennsylvania State University, University Park, USA; The Neuroscience Graduate Program, The Huck Institutes of the Life Sciences, The Pennsylvania State University, University Park, USA; Center for Neurotechnology in Mental Health Research, The Pennsylvania State University, University Park 16802, USA; Center for Neural Engineering, The Pennsylvania State University, University Park 16802, USA.
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48
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He D, Pan C, Zhao Y, Wei W, Qin X, Cai Q, Shi S, Chu X, Zhang N, Jia Y, Wen Y, Cheng B, Liu H, Feng R, Zhang F, Xu P. Exome-wide screening identifies novel rare risk variants for bone mineral density. Osteoporos Int 2023; 34:965-975. [PMID: 36849660 DOI: 10.1007/s00198-023-06710-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/28/2022] [Accepted: 02/14/2023] [Indexed: 03/01/2023]
Abstract
UNLABELLED Bone mineral density (BMD) is an independent risk factor of osteoporosis-related fractures. We performed gene-based burden tests to assess the association between rare variants and BMD, and identified several BMD candidate genes. PURPOSE BMD is highly heritable and a major predictor of osteoporotic fractures, but its genetic basis remains unclear. We aimed to identify rare risk variants contributing to BMD. METHODS Utilizing the newly released UK Biobank 200,643 exome dataset, we conducted a gene-based exome-wide association study in males and females, respectively. First, 100,639 males and 117,338 females with BMD values were included in the polygenic risk scores (PRS) analysis. Among individuals with lower 30% PRS, cases were individuals with top 10% BMD, and individuals with bottom 10% BMD were the controls. Considering the effects of vitamin D (VD), individuals with the highest 30% VD concentration were selected for VD-BMD analysis. After quality control, 741 males and 697 females were included in the BMD analysis, and 717 males and 708 females were included in the VD-BMD analysis. The variants were annotated by ANNOVAR software, then BMD and VD-BMD qualified variants were imported into the SKAT R-package to perform gene-based burden tests, respectively. RESULTS The gene-based burden test of the exonic variants identified genome-wide candidate associations in ANKRD18A (P = 1.60 × 10-5, PBonferroni adjust = 2.11 × 10-3), C22orf31 (P = 3.49 × 10-4, PBonferroni adjust = 3.17 × 10-2), and SPATC1L (P = 1.09 × 10-5, PBonferroni adjust = 8.80 × 10-3). For VD-BMD analysis, three genes were associated with BMD, such as NIPAL1 (P = 1.06 × 10-3, PBonferroni adjust = 3.91 × 10-2). CONCLUSIONS Our study suggested that rare variants contribute to BMD, providing new sights for broadening the genetic structure of BMD.
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Affiliation(s)
- D He
- Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, Xi'an Jiaotong University, Xi'an, China
- Key Laboratory of Environment and Genes Related to Diseases of Ministry of Education of China, Xi'an Jiaotong University, Xi'an, China
- Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, Xi'an Jiaotong University, Xi'an, China
| | - C Pan
- Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, Xi'an Jiaotong University, Xi'an, China
- Key Laboratory of Environment and Genes Related to Diseases of Ministry of Education of China, Xi'an Jiaotong University, Xi'an, China
- Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, Xi'an Jiaotong University, Xi'an, China
| | - Y Zhao
- Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, Xi'an Jiaotong University, Xi'an, China
- Key Laboratory of Environment and Genes Related to Diseases of Ministry of Education of China, Xi'an Jiaotong University, Xi'an, China
- Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, Xi'an Jiaotong University, Xi'an, China
| | - W Wei
- Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, Xi'an Jiaotong University, Xi'an, China
- Key Laboratory of Environment and Genes Related to Diseases of Ministry of Education of China, Xi'an Jiaotong University, Xi'an, China
- Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, Xi'an Jiaotong University, Xi'an, China
| | - X Qin
- Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, Xi'an Jiaotong University, Xi'an, China
- Key Laboratory of Environment and Genes Related to Diseases of Ministry of Education of China, Xi'an Jiaotong University, Xi'an, China
- Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, Xi'an Jiaotong University, Xi'an, China
| | - Q Cai
- Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, Xi'an Jiaotong University, Xi'an, China
- Key Laboratory of Environment and Genes Related to Diseases of Ministry of Education of China, Xi'an Jiaotong University, Xi'an, China
- Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, Xi'an Jiaotong University, Xi'an, China
| | - S Shi
- Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, Xi'an Jiaotong University, Xi'an, China
- Key Laboratory of Environment and Genes Related to Diseases of Ministry of Education of China, Xi'an Jiaotong University, Xi'an, China
- Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, Xi'an Jiaotong University, Xi'an, China
| | - X Chu
- Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, Xi'an Jiaotong University, Xi'an, China
- Key Laboratory of Environment and Genes Related to Diseases of Ministry of Education of China, Xi'an Jiaotong University, Xi'an, China
- Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, Xi'an Jiaotong University, Xi'an, China
| | - N Zhang
- Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, Xi'an Jiaotong University, Xi'an, China
- Key Laboratory of Environment and Genes Related to Diseases of Ministry of Education of China, Xi'an Jiaotong University, Xi'an, China
- Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, Xi'an Jiaotong University, Xi'an, China
| | - Y Jia
- Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, Xi'an Jiaotong University, Xi'an, China
- Key Laboratory of Environment and Genes Related to Diseases of Ministry of Education of China, Xi'an Jiaotong University, Xi'an, China
- Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, Xi'an Jiaotong University, Xi'an, China
| | - Y Wen
- Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, Xi'an Jiaotong University, Xi'an, China
- Key Laboratory of Environment and Genes Related to Diseases of Ministry of Education of China, Xi'an Jiaotong University, Xi'an, China
- Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, Xi'an Jiaotong University, Xi'an, China
| | - B Cheng
- Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, Xi'an Jiaotong University, Xi'an, China
- Key Laboratory of Environment and Genes Related to Diseases of Ministry of Education of China, Xi'an Jiaotong University, Xi'an, China
- Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, Xi'an Jiaotong University, Xi'an, China
| | - H Liu
- Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, Xi'an Jiaotong University, Xi'an, China
- Key Laboratory of Environment and Genes Related to Diseases of Ministry of Education of China, Xi'an Jiaotong University, Xi'an, China
- Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, Xi'an Jiaotong University, Xi'an, China
| | - R Feng
- Department of Joint Surgery, HongHui Hospital, Xi'an Jiaotong University, Xi'an, China
| | - F Zhang
- Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, Xi'an Jiaotong University, Xi'an, China.
- Key Laboratory of Environment and Genes Related to Diseases of Ministry of Education of China, Xi'an Jiaotong University, Xi'an, China.
- Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, Xi'an Jiaotong University, Xi'an, China.
- School of Public Health, Xi'an Jiaotong University Health Science Center, Xi'an, China.
| | - P Xu
- Department of Joint Surgery, HongHui Hospital, Xi'an Jiaotong University, Xi'an, China.
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Gheres KW, Ãœnsal HS, Han X, Zhang Q, Turner KL, Zhang N, Drew PJ. Arousal state transitions occlude sensory-evoked neurovascular coupling in neonatal mice. bioRxiv 2023:2023.02.18.529057. [PMID: 36824895 PMCID: PMC9949139 DOI: 10.1101/2023.02.18.529057] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/20/2023]
Abstract
In the adult sensory cortex, increases in neural activity elicited by sensory stimulation usually drives vasodilation mediated by neurovascular coupling. However, whether neurovascular coupling is the same in neonatal animals as adults is controversial, as both canonical and inverted responses have been observed. We investigated the nature of neurovascular coupling in unanesthetized neonatal mice using optical imaging, electrophysiology, and BOLD fMRI. We find in neonatal (postnatal day 15, P15) mice, sensory stimulation induces a small increase in blood volume/BOLD signal, often followed by a large decrease in blood volume. An examination of arousal state of the mice revealed that neonatal mice were asleep a substantial fraction of the time, and that stimulation caused the animal to awaken. As cortical blood volume is much higher during REM and NREM sleep than the awake state, awakening occludes any sensory-evoked neurovascular coupling. When neonatal mice are stimulated during an awake period, they showed relatively normal (but slowed) neurovascular coupling, showing that that the typically observed constriction is due to arousal state changes. These result show that sleep-related vascular changes dominate over any sensory-evoked changes, and hemodynamic measures need to be considered in the context of arousal state changes. Significance Statement In the adult brain, increases in neural activity are often followed by vasodilation, allowing activity to be monitored using optical or magnetic resonance imaging. However, in neonates, sensory stimulation can drive vasoconstriction, whose origin was not understood. We used optical and magnetic resonance imaging approaches to investigate hemodynamics in neonatal mice. We found that sensory-induced vasoconstriction occurred when the mice were asleep, as sleep is associated with dilation of the vasculature of the brain relative to the awake state. The stimulus awakens the mice, causing a constriction due to the arousal state change. Our study shows the importance of monitoring arousal state, particularly when investigating subjects that may sleep, and the dominance arousal effects on brain hemodynamics.
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Yao MY, Zhang N, Zhang Q, Lu YF, Huang Y, He DF, Chen YX, Luo GX. [Effects of interleukin-4-modified gold nanozymes on the full-thickness skin defects in diabetic mice]. Zhonghua Shao Shang Yu Chuang Mian Xiu Fu Za Zhi 2023; 39:15-24. [PMID: 36740422 DOI: 10.3760/cma.j.cn501225-20220630-00275] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
Objective: To investigate the effects and mechanism of interleukin-4-modified gold nanoparticle (IL-4-AuNP) on the wound healing of full-thickness skin defects in diabetic mice. Methods: Experimental research methods were adopted. Gold nanoparticle (AuNP) and IL-4-AuNP were synthesized by improving the methods described in published literature. The morphology of those two particles were photographed by transmission electron microscopy, and their particle sizes were calculated. The surface potential and hydration particle size of the two particles were detected by nanoparticle potentiometer and particle size analyzer, respectively. The clearance rate of IL-4-AuNP to hydrogen peroxide and superoxide anion was measured by hydrogen peroxide and superoxide anion kits, respectively. Mouse fibroblast line 3T3 cells were used and divided into the following groups by the random number table (the same below): blank control group, hydrogen peroxide alone group treated with hydrogen peroxide only, hydrogen peroxide+IL-4-AuNP group treated with IL-4-AuNP for 0.5 h and then treated with hydrogen peroxide. After 24 h of culture, the reactive oxygen species (ROS) levels of cells were detected by immunofluorescence method; cell count kit 8 was used to detect relative cell survival rate. The macrophage Raw264.7 mouse cells were then used and divided into blank control group and IL-4-AuNP group that treated with IL-4-AuNP. After 24 h of culture, the expression of arginase 1 (Arg-1) in cells was observed by immunofluorescence method. Twelve male BALB/c mice (mouse age, sex, and strain, the same below) aged 8 to 10 weeks were divided into IL-4-AuNP group and blank control group, treated accordingly. On the 16th day of treatment, whole blood samples were collected from mice for analysis of white blood cell count (WBC), red blood cell count (RBC), hemoglobin level, or platelet count and the level of aspartate aminotransferase (AST), alanine transaminase (ALT), urea, or creatinine. The inflammation, bleeding, or necrosis in the heart, liver, spleen, lung, and kidney tissue of mice were detected by hematoxylin-eosin (HE). Another 36 mice were selected to make diabetic model, and the full-thickness skin defect wounds were made on the back of these mice. The wounds were divided into blank control group, AuNP alone group, and IL-4-AuNP group, with 12 mice in each group, and treated accordingly. On the 0 (immediately), 4th, 9th, and 15th day of treatment, the wound condition was observed and the wound area was calculated. On the 9th day of treatment, HE staining was used to detect the length of neonatal epithelium and the thickness of granulation tissue in the wound. On the 15th day of treatment, immunofluorescence method was used to detect ROS level and the number of Arg-1 positive cells in the wound tissue. The number of samples was 6 in all cases. Data were statistically analyzed with independent sample t test, corrected t test, Tukey test, or Dunnett T3 test. Results: The size of prepared AuNP and IL-4-AuNP were uniform. The particle size, surface potential, and hydration particle size of AuNP and IL-4-AuNP were (13.0±2.1) and (13.9±2.5) nm, (-45.8±3.2) and (-20.3±2.2) mV, (14±3) and (16±4) nm, respectively. For IL-4-AuNP, the clearance rate to hydrogen peroxide and superoxide anion were (69±4)% and (52±5)%, respectively. After 24 h of culture, the ROS level of 3T3 in hydrogen peroxide alone group was significantly higher than that in blank control group (q=26.12, P<0.05); the ROS level of hydrogen peroxide+IL-4-AuNP group was significantly lower than that in hydrogen peroxide alone group (q=25.12, P<0.05) and close to that in blank control group (P>0.05). After 24 h of culture, the relative survival rate of 3T3 cells in hydrogen peroxide+IL-4-AuNP group was significantly higher than that in hydrogen peroxide alone group (t=51.44, P<0.05). After 24 h of culture, Arg-1 expression of Raw264.7 cells in IL-4-AuNP group was significantly higher than that in blank control group (t'=8.83, P<0.05).On the 16th day of treatment, there were no significant statistically differences in WBC, RBC, hemoglobin level, or platelet count and the level of AST, ALT, urea, or creatinine of mice between blank control group and IL-4-AuNP group (P>0.05). No obvious inflammation, bleeding or necrosis was observed in the heart, liver, spleen, lung, and kidney of important organs in IL-4-AuNP group, and no significant changes were observed compared with blank control group. On the 0 and 4th day of treatment, the wound area of diabetic mice in blank control group, AuNP alone group, and IL-4-AuNP group had no significant difference (P>0.05). On the 9th day of treatment, the wound areas both in AuNP alone group and IL-4-AuNP group were significantly smaller than that in blank control group (with q values of 9.45 and 14.87, respectively, P<0.05), the wound area in IL-4-AuNP group was significantly smaller than that in AuNP alone group (q=5.42, P<0.05). On the 15th day of treatment, the wound areas both in AuNP alone group and IL-4-AuNP group were significantly smaller than that in blank control group (with q values of 4.84 and 20.64, respectively, P<0.05), the wound area in IL-4-AuNP group was significantly smaller than that in AuNP alone group (q=15.80, P<0.05); moreover, inflammations such as redness and swelling were significantly reduced in IL-4-AuNP group compared with the other two groups. On the 9th day of treatment, compared with blank control group and AuNP alone group, the length of neonatal epithelium in the wound of diabetic mice in IL-4-AuNP group was significantly longer (all P<0.05), and the thickness of the granulation tissue in the wound was significantly increased (with q values of 11.33 and 9.65, respectively, all P<0.05). On the 15th day of treatment, compared with blank control group, ROS levels in wound tissue of diabetic mice in AuNP alone group and IL-4-AuNP group were significantly decreased (P<0.05). On the 15th day of treatment, the number of Arg-1 positive cells in the wounds of diabetic mice in IL-4-AuNP group was significantly more than that in blank control group and AuNP alone group, respectively (all P<0.05). Conclusions: IL-4-AuNP is safe in vivo, and can improve the oxidative microenvironment by removing ROS and induce macrophage polarization towards M2 phenotype, thus promote efficient diabetic wound healing and regeneration of full-thickness skin defects in diabetic mice.
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Affiliation(s)
- M Y Yao
- State Key Laboratory of Trauma, Burns and Combined Injury, Institute of Burn Research, the First Affiliated Hospital of Army Medical University (the Third Military Medical University), Chongqing Key Laboratory for Disease Proteomics, Chongqing 400038, China
| | - N Zhang
- State Key Laboratory of Trauma, Burns and Combined Injury, Institute of Burn Research, the First Affiliated Hospital of Army Medical University (the Third Military Medical University), Chongqing Key Laboratory for Disease Proteomics, Chongqing 400038, China
| | - Q Zhang
- State Key Laboratory of Trauma, Burns and Combined Injury, Institute of Burn Research, the First Affiliated Hospital of Army Medical University (the Third Military Medical University), Chongqing Key Laboratory for Disease Proteomics, Chongqing 400038, China
| | - Y F Lu
- State Key Laboratory of Trauma, Burns and Combined Injury, Institute of Burn Research, the First Affiliated Hospital of Army Medical University (the Third Military Medical University), Chongqing Key Laboratory for Disease Proteomics, Chongqing 400038, China
| | - Y Huang
- State Key Laboratory of Trauma, Burns and Combined Injury, Institute of Burn Research, the First Affiliated Hospital of Army Medical University (the Third Military Medical University), Chongqing Key Laboratory for Disease Proteomics, Chongqing 400038, China
| | - D F He
- State Key Laboratory of Trauma, Burns and Combined Injury, Institute of Burn Research, the First Affiliated Hospital of Army Medical University (the Third Military Medical University), Chongqing Key Laboratory for Disease Proteomics, Chongqing 400038, China
| | - Y X Chen
- State Key Laboratory of Trauma, Burns and Combined Injury, Institute of Burn Research, the First Affiliated Hospital of Army Medical University (the Third Military Medical University), Chongqing Key Laboratory for Disease Proteomics, Chongqing 400038, China
| | - G X Luo
- State Key Laboratory of Trauma, Burns and Combined Injury, Institute of Burn Research, the First Affiliated Hospital of Army Medical University (the Third Military Medical University), Chongqing Key Laboratory for Disease Proteomics, Chongqing 400038, China
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