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Liu C, Zhuo Z, Qu L, Jin Y, Hua T, Xu J, Tan G, Li Y, Duan Y, Wang T, Zhang Z, Zhang Y, Chen R, Yu P, Zhang P, Shi Y, Zhang J, Tian D, Li R, Zhang X, Shi F, Wang Y, Jiang J, Carass A, Liu Y, Ye C. DeepWMH: A deep learning tool for accurate white matter hyperintensity segmentation without requiring manual annotations for training. Sci Bull (Beijing) 2024; 69:872-875. [PMID: 38320896 DOI: 10.1016/j.scib.2024.01.034] [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] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/08/2024]
Affiliation(s)
- Chenghao Liu
- School of Integrated Circuits and Electronics, Beijing Institute of Technology, Beijing 100081, China
| | - Zhizheng Zhuo
- Department of Radiology, Beijing Tiantan Hospital, Capital Medical University, Beijing 100070, China
| | - Liying Qu
- Department of Radiology, Beijing Tiantan Hospital, Capital Medical University, Beijing 100070, China
| | - Ying Jin
- Department of Radiology, Beijing Tiantan Hospital, Capital Medical University, Beijing 100070, China
| | - Tiantian Hua
- Department of Radiology, Beijing Tiantan Hospital, Capital Medical University, Beijing 100070, China
| | - Jun Xu
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing 100070, China
| | - Guirong Tan
- Department of Radiology, Beijing Tiantan Hospital, Capital Medical University, Beijing 100070, China
| | - Yuna Li
- Department of Radiology, Beijing Tiantan Hospital, Capital Medical University, Beijing 100070, China
| | - Yunyun Duan
- Department of Radiology, Beijing Tiantan Hospital, Capital Medical University, Beijing 100070, China
| | - Tingting Wang
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing 100070, China
| | - Zaiqiang Zhang
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing 100070, China
| | - Yanling Zhang
- Department of Radiology, Beijing Tiantan Hospital, Capital Medical University, Beijing 100070, China
| | - Rui Chen
- Department of Radiology, Beijing Tiantan Hospital, Capital Medical University, Beijing 100070, China
| | - Pinnan Yu
- Department of Radiology, Beijing Tiantan Hospital, Capital Medical University, Beijing 100070, China
| | - Peixin Zhang
- Department of Radiology, Beijing Tiantan Hospital, Capital Medical University, Beijing 100070, China
| | - Yulu Shi
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing 100070, China
| | - Jianguo Zhang
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing 100070, China; Beijing Key Laboratory of Neurostimulation, Beijing 100070, China
| | - Decai Tian
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing 100070, China; China National Clinical Research Center for Neurological Diseases, Beijing Tiantan Hospital, Beijing 100070, China; Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing 100070, China
| | - Runzhi Li
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing 100070, China; China National Clinical Research Center for Neurological Diseases, Beijing Tiantan Hospital, Beijing 100070, China
| | - Xinghu Zhang
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing 100070, China
| | - Fudong Shi
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing 100070, China; China National Clinical Research Center for Neurological Diseases, Beijing Tiantan Hospital, Beijing 100070, China; Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing 100070, China
| | - Yanli Wang
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing 100070, China; Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing 100070, China
| | - Jiwei Jiang
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing 100070, China; China National Clinical Research Center for Neurological Diseases, Beijing Tiantan Hospital, Beijing 100070, China
| | - Aaron Carass
- Department of Electrical and Computer Engineering, Johns Hopkins University, Baltimore 21205, USA
| | - Yaou Liu
- Department of Radiology, Beijing Tiantan Hospital, Capital Medical University, Beijing 100070, China.
| | - Chuyang Ye
- School of Integrated Circuits and Electronics, Beijing Institute of Technology, Beijing 100081, China.
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Wang Z, Xue F, Sui X, Han W, Song W, Jiang J. Personalised follow-up and management schema for patients with screen-detected pulmonary nodules: A dynamic modelling study. Pulmonology 2024:S2531-0437(24)00040-0. [PMID: 38614860 DOI: 10.1016/j.pulmoe.2024.02.010] [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] [Subscribe] [Scholar Register] [Received: 07/23/2023] [Revised: 02/28/2024] [Accepted: 02/29/2024] [Indexed: 04/15/2024] Open
Abstract
BACKGROUND Selecting the time target for follow-up testing in lung cancer screening is challenging. We aim to devise dynamic, personalized lung cancer screening schema for patients with pulmonary nodules detected through low-dose computed tomography. METHODS We developed and validated dynamic models using data of pulmonary nodule patients (aged 55-74 years) from the National Lung Screening Trial. We predicted patient-specific risk profiles at baseline (R0) and updated the risk evaluation results in repeated screening rounds (R1 and R2). We used risk cutoffs to optimize time-dependent sensitivity at an early decision point (3 months) and time-dependent specificity at a late decision point (1 year). RESULTS In validation, area under receiver operating characteristic curve for predicting 12-month lung cancer onset was 0.867 (95 % confidence interval: 0.827-0.894) and 0.807 (0.765-0.948) at R0 and R1-R2, respectively. The personalized schema, compared with National Comprehensive Cancer Network (NCCN) guideline and Lung-RADS, yielded lower rates of delayed diagnosis (1.7% vs. 1.7% vs. 6.9 %) and over-testing (4.9% vs. 5.6% vs. 5.6 %) at R0, and lower rates of delayed diagnosis (0.0% vs. 18.2% vs. 18.2 %) and over-testing (2.6% vs. 8.3% vs. 7.3 %) at R2. Earlier test recommendation among cancer patients was more frequent using the personalized schema (vs. NCCN: 29.8% vs. 20.9 %, p = 0.0065; vs. Lung-RADS: 33.2% vs. 22.8 %, p = 0.0025), especially for women, patients aged ≥65 years, and part-solid or non-solid nodules. CONCLUSIONS The personalized schema is easy-to-implement and more accurate compared with rule-based protocols. The results highlight value of personalized approaches in realizing efficient nodule management.
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Affiliation(s)
- Z Wang
- Department of Epidemiology and Biostatistics, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences, School of Basic Medicine, Peking Union Medical College. No. 5 Dongdansantiao Street, Dongcheng District, Beijing, China; Peking University People's Hospital, Peking University Hepatology Institute, Beijing Key Laboratory of Hepatitis C and Immunotherapy for Liver Diseases. No. 11 Xizhimen South Street, Beijing, China
| | - F Xue
- Department of Epidemiology and Biostatistics, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences, School of Basic Medicine, Peking Union Medical College. No. 5 Dongdansantiao Street, Dongcheng District, Beijing, China
| | - X Sui
- Department of Radiology, Peking Union Medical College Hospital. No.1 Shuaifuyuan Street, Dongcheng District, Beijing, China
| | - W Han
- Department of Epidemiology and Biostatistics, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences, School of Basic Medicine, Peking Union Medical College. No. 5 Dongdansantiao Street, Dongcheng District, Beijing, China
| | - W Song
- Department of Radiology, Peking Union Medical College Hospital. No.1 Shuaifuyuan Street, Dongcheng District, Beijing, China
| | - J Jiang
- Department of Epidemiology and Biostatistics, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences, School of Basic Medicine, Peking Union Medical College. No. 5 Dongdansantiao Street, Dongcheng District, Beijing, China.
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Zhan H, Ye M, Jiang J, Gao Y, Zheng C, Duan S. Structural performance of detachable precast concrete column-column joint. Heliyon 2024; 10:e27308. [PMID: 38495148 PMCID: PMC10943345 DOI: 10.1016/j.heliyon.2024.e27308] [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] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2023] [Revised: 02/22/2024] [Accepted: 02/27/2024] [Indexed: 03/19/2024] Open
Abstract
A novel type of detachable precast concrete column-column joint (DPC) is proposed in this study to solve the problems in current column-column dry connections including complex load path, uncertainty of structural stiffness of beam-column joints and inconvenience for disassembly. The dry connection technology is applied by composing of steel plate and concrete. Finite element models of DPC were created to study its structural performance including hysteresis curve, skeleton curve, ductility, and energy dissipation capacity. The benchmark models are firstly established and validated against the test data and after that a small-scale parametric study is prepared. The effect of axial pressure ratio and eccentricity distance size on the seismic performance of DPC was studied. Results indict that the optimal value of axial pressure ratio ranges from 0.5 to 0.7. With increase of the axial pressure ratio, the ductility coefficient shows a decreasing trend in general. The eccentricity has little effect on the energy dissipation capacity of the joint.
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Affiliation(s)
- H. Zhan
- Research Centre of Wind Engineering and Engineering Vibration, Guangzhou University, Guangzhou, 510006, China
| | - M. Ye
- Research Centre of Wind Engineering and Engineering Vibration, Guangzhou University, Guangzhou, 510006, China
| | - J. Jiang
- Department of Civil Engineering and Smart Cities, Shantou University, 515063, China
| | - Y. Gao
- School of Marine Engineering Equipment, Zhejiang Ocean University, 316022, China
| | - C.W. Zheng
- Research Centre of Wind Engineering and Engineering Vibration, Guangzhou University, Guangzhou, 510006, China
| | - S.C. Duan
- Research Centre of Wind Engineering and Engineering Vibration, Guangzhou University, Guangzhou, 510006, China
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Jiang J, Wang A, Shi H, Jiang S, Li W, Jiang T, Wang L, Zhang X, Sun M, Zhao M, Zou X, Xu J. Clinical and neuroimaging association between neuropsychiatric symptoms and nutritional status across the Alzheimer's disease continuum: a longitudinal cohort study. J Nutr Health Aging 2024; 28:100182. [PMID: 38336502 DOI: 10.1016/j.jnha.2024.100182] [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: 10/16/2023] [Revised: 01/24/2024] [Accepted: 01/26/2024] [Indexed: 02/12/2024]
Abstract
OBJECTIVES To investigate the association between neuropsychiatric symptoms (NPS) and nutritional status, and explore their shared regulatory brain regions on the Alzheimer's disease (AD) continuum. DESIGN A longitudinal, observational cohort study. SETTING Data were collected from the Chinese Imaging, Biomarkers, and Lifestyle study between June 1, 2021 and December 31, 2022. PARTICIPANTS Overall, 432 patients on the AD continuum, including amnestic mild cognitive impairment and AD dementia, were assessed at baseline, and only 165 patients completed the (10.37 ± 6.08) months' follow-up. MEASUREMENTS The Mini-Nutritional Assessment (MNA) and Neuropsychiatric Inventory (NPI) were used to evaluate nutritional status and NPS, respectively. The corrected cerebral blood flow (cCBF) measured by pseudo-continuous arterial spin labeling of the dietary nutrition-related brain regions was analyzed. The association between the NPS at baseline and subsequent change in nutritional status and the association between the changes in the severity of NPS and nutritional status were examined using generalized linear mixed models. RESULTS Increased cCBF in the left putamen was associated with malnutrition, general NPS, affective symptoms, and hyperactivity (P < 0.05). The presence of general NPS (β = -1.317, P = 0.003), affective symptoms (β = -1.887, P < 0.001), and appetite/eating disorders (β = -1.714, P < 0.001) at baseline were associated with a decline in the MNA scores during follow-up. The higher scores of general NPI (β = -0.048), affective symptoms (β = -0.181), and appetite/eating disorders (β = -0.416; all P < 0.001) were longitudinally associated with lower MNA scores after adjusting for confounding factors. CONCLUSIONS We found that baseline NPS were predictors of a decline in nutritional status on the AD continuum. The worse the severity of affective symptoms and appetite/eating disorders, the poorer the nutritional status. Furthermore, abnormal perfusion of the putamen may regulate the association between malnutrition and NPS, which suggests their potentially common neural regulatory basis.
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Affiliation(s)
- Jiwei Jiang
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, 100070, China; China National Clinical Research Center for Neurological Diseases, Beijing, 100070, China
| | - Anxin Wang
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, 100070, China; China National Clinical Research Center for Neurological Diseases, Beijing, 100070, China
| | - Hanping Shi
- Department of Gastrointestinal Surgery, Beijing Shijitan Hospital, Capital Medical University, Beijing, 100038, China; Department of Clinical Nutrition, Beijing Shijitan Hospital, Capital Medical University, Beijing, 100038, China; Beijing International Science and Technology Cooperation Base for Cancer Metabolism and Nutrition, Beijing, 100038, China
| | - Shirui Jiang
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, 100070, China; China National Clinical Research Center for Neurological Diseases, Beijing, 100070, China
| | - Wenyi Li
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, 100070, China; China National Clinical Research Center for Neurological Diseases, Beijing, 100070, China
| | - Tianlin Jiang
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, 100070, China; China National Clinical Research Center for Neurological Diseases, Beijing, 100070, China
| | - Linlin Wang
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, 100070, China; China National Clinical Research Center for Neurological Diseases, Beijing, 100070, China
| | - Xiaoli Zhang
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, 100070, China; China National Clinical Research Center for Neurological Diseases, Beijing, 100070, China
| | - Mengfan Sun
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, 100070, China; China National Clinical Research Center for Neurological Diseases, Beijing, 100070, China
| | - Min Zhao
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, 100070, China; China National Clinical Research Center for Neurological Diseases, Beijing, 100070, China
| | - Xinying Zou
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, 100070, China; China National Clinical Research Center for Neurological Diseases, Beijing, 100070, China
| | - Jun Xu
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, 100070, China; China National Clinical Research Center for Neurological Diseases, Beijing, 100070, China.
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Yeoh KH, Chang YHR, Chew KH, Jiang J, Yoon TL, Ong DS, Goh BT. Computational Screening of a Single-Atom Catalyst Supported by Monolayer Nb 2S 2C for Oxygen Reduction Reaction. Langmuir 2024. [PMID: 38329924 DOI: 10.1021/acs.langmuir.3c03188] [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] [Subscribe] [Scholar Register] [Indexed: 02/10/2024]
Abstract
The search for high-performance catalysts to improve the catalytic activity for an oxygen reduction reaction (ORR) is crucial for developing a proton exchange membrane fuel cell. Using the first-principles method, we have performed computational screening on a series of transition metal (TM) atoms embedded in monolayer Nb2S2C to enhance the ORR activity. Through the scaling relationship and volcano plot, our results reveal that the introduction of a single Ni or Rh atom through substitutional doping into monolayer Nb2S2C yields promising ORR catalysts with low overpotentials of 0.52 and 0.42 V, respectively. These doped atoms remain intact on the monolayer Nb2S2C even at elevated temperatures. Importantly, the catalytic activity of the Nb2S2C doped with a TM atom can be effectively correlated with an intrinsic descriptor, which can be computed based on the number of d orbital electrons and the electronegativity of TM and O atoms.
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Affiliation(s)
- K H Yeoh
- Jeffrey Sachs Center on Sustainable Development, Sunway University, No. 5, Jalan Universiti, Bandar Sunway, Selangor 47500, Malaysia
| | - Y H R Chang
- Faculty of Applied Sciences, Universiti Teknologi MARA, Cawangan Sarawak, Kota Samarahan, Sarawak 94300, Malaysia
| | - K-H Chew
- Zhejiang Expo New Materials Co. Ltd., 1066, Xincheng Times Avenue, Longgang, Wenzhou 325802, China
- Key Laboratory of Optical Field Manipulation of Zhejiang Province, Department of Physics, Zhejiang Sci-Tech University, Hangzhou 310018, China
| | - J Jiang
- Materials Simulation and Modelling, Department of Applied Physics, Eindhoven University of Technology, Eindhoven 5612, The Netherlands
| | - T L Yoon
- School of Physics, Universiti Sains Malaysia, Penang 11800 USM, Malaysia
| | - D S Ong
- Faculty of Engineering, Multimedia University, Persiaran Multimedia, Cyberjaya, Selangor 63100, Malaysia
| | - B T Goh
- Low Dimensional Materials Research Centre (LDMRC), Department of Physics, Faculty of Science, University of Malaya, Kuala Lumpur, 50603, Malaysia
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6
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Yan XQ, Ye MJ, Zou Q, Chen P, He ZS, Wu B, He DL, He CH, Xue XY, Ji ZG, Chen H, Zhang S, Liu YP, Zhang XD, Fu C, Xu DF, Qiu MX, Lv JJ, Huang J, Ren XB, Cheng Y, Qin WJ, Zhang X, Zhou FJ, Ma LL, Guo JM, Ding DG, Wei SZ, He Y, Guo HQ, Shi BK, Liu L, Liu F, Hu ZQ, Jin XM, Yang L, Zhu SX, Liu JH, Huang YH, Xu T, Liu B, Sun T, Wang ZJ, Jiang HW, Yu DX, Zhou AP, Jiang J, Luan GD, Jin CL, Xu J, Hu JX, Huang YR, Guo J, Zhai W, Sheng XN. Toripalimab plus axitinib versus sunitinib as first-line treatment for advanced renal cell carcinoma: RENOTORCH, a randomized, open-label, phase III study. Ann Oncol 2024; 35:190-199. [PMID: 37872020 DOI: 10.1016/j.annonc.2023.09.3108] [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: 09/03/2023] [Revised: 09/21/2023] [Accepted: 09/21/2023] [Indexed: 10/25/2023] Open
Abstract
BACKGROUND Immune checkpoint inhibitors in combination with tyrosine kinase inhibitors are standard treatments for advanced clear cell renal cell carcinoma (RCC). This phase III RENOTORCH study compared the efficacy and safety of toripalimab plus axitinib versus sunitinib for the first-line treatment of patients with intermediate-/poor-risk advanced RCC. PATIENTS AND METHODS Patients with intermediate-/poor-risk unresectable or metastatic RCC were randomized in a ratio of 1 : 1 to receive toripalimab (240 mg intravenously once every 3 weeks) plus axitinib (5 mg orally twice daily) or sunitinib [50 mg orally once daily for 4 weeks (6-week cycle) or 2 weeks (3-week cycle)]. The primary endpoint was progression-free survival (PFS) assessed by an independent review committee (IRC). The secondary endpoints were investigator-assessed PFS, overall response rate (ORR), overall survival (OS), and safety. RESULTS A total of 421 patients were randomized to receive toripalimab plus axitinib (n = 210) or sunitinib (n = 211). With a median follow-up of 14.6 months, toripalimab plus axitinib significantly reduced the risk of disease progression or death by 35% compared with sunitinib as assessed by an IRC [hazard ratio (HR) 0.65, 95% confidence interval (CI) 0.49-0.86; P = 0.0028]. The median PFS was 18.0 months in the toripalimab-axitinib group, whereas it was 9.8 months in the sunitinib group. The IRC-assessed ORR was significantly higher in the toripalimab-axitinib group compared with the sunitinib group (56.7% versus 30.8%; P < 0.0001). An OS trend favoring toripalimab plus axitinib was also observed (HR 0.61, 95% CI 0.40-0.92). Treatment-related grade ≥3 adverse events occurred in 61.5% of patients in the toripalimab-axitinib group and 58.6% of patients in the sunitinib group. CONCLUSION In patients with previously untreated intermediate-/poor-risk advanced RCC, toripalimab plus axitinib provided significantly longer PFS and higher ORR than sunitinib and had a manageable safety profile TRIAL REGISTRATION: ClinicalTrials.gov NCT04394975.
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Affiliation(s)
- X Q Yan
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Genitourinary Oncology, Peking University Cancer Hospital & Institute, Beijing
| | - M J Ye
- Department of Urology, Hunan Cancer Hospital, The Affiliated Cancer Hospital of Xiangya School of Medicine, Central South University, Changsha
| | - Q Zou
- Department of Urology, Jiangsu Cancer Hospital & Jiangsu Institute of Cancer Research & Affiliated Cancer Hospital of Nanjing Medical University, Nanjing
| | - P Chen
- Department of Urology, Affiliated Tumor Hospital of Xinjiang Medical University, Urumqi
| | - Z S He
- Department of Urology, First Hospital of Peking University, Beijing
| | - B Wu
- Department of Urology, Shengjing Hospital of China Medical University, Shenyang
| | - D L He
- Department of Urology, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an
| | - C H He
- Department of Urology, Cancer Hospital of Henan Province, Zhengzhou
| | - X Y Xue
- Department of Urology, The First Affiliated Hospital, Fujian Medical University, Fuzhou
| | - Z G Ji
- Department of Urology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing
| | - H Chen
- Department of Urology, Harbin Medical University Cancer Hospital, Harbin
| | - S Zhang
- Department of Biotherapy, Cancer Center, West China Hospital, Sichuan University, Chengdu
| | - Y P Liu
- Department of Oncology, The First Hospital of China Medical University, Shenyang
| | - X D Zhang
- Department of Urology, Beijing Chaoyang Hospital, Capital Medical University, Beijing
| | - C Fu
- Department of Urology, Cancer Hospital of China Medical University, Liaoning Cancer Hospital and Institute, Shenyang
| | - D F Xu
- Department of Urology, Ruijin Hospital, Shanghai Jiao Tong University, School of Medicine, Shanghai
| | - M X Qiu
- Department of Urology, Sichuan Academy of Medical Sciences and Sichuan Provincial People's Hospital, Chengdu
| | - J J Lv
- Department of Urology, Provincial Hospital Affiliated to Shandong First Medical University, Jinan
| | - J Huang
- Department of Urology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou
| | - X B Ren
- Department of Immunology and Biotherapy, Cancer Institute & Hospital, Tianjin Medical University, Tianjin
| | - Y Cheng
- Department of Medical Thoracic Oncology, Jilin Provincial Cancer Hospital, Changchun
| | - W J Qin
- Department of Urology, Xijing Hospital of Air Force Military Medical University, Xi'an
| | - X Zhang
- Department of Urology, The Third Medical Center, Chinese PLA General Hospital, Beijing
| | - F J Zhou
- Department of Urology, Sun Yat-sen University Cancer Center, Guangzhou
| | - L L Ma
- Department of Urology, Peking University Third Hospital, Beijing
| | - J M Guo
- Department of Urology, Zhongshan Hospital, Fudan University, Shanghai
| | - D G Ding
- Department of Urology, Zhengzhou University People's Hospital, Henan Provincial People's Hospital, Zhengzhou
| | - S Z Wei
- Department of Urology, Hubei Cancer Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan
| | - Y He
- Department of Urology, The Affiliated Hospital of Jiaxing University, Jiaxing
| | - H Q Guo
- Department of Urology, Affiliated Drum Tower Hospital, Medical School of Nanjing University, Nanjing
| | - B K Shi
- Department of Urology, Qilu Hospital of Shandong University, Jinan
| | - L Liu
- Department of Urology, Qilu Hospital of Shandong University, Jinan
| | - F Liu
- Department of Urology, Zhejiang Provincial People's Hospital, Affiliated People's Hospital, Hangzhou Medical College, Hangzhou
| | - Z Q Hu
- Department of Urology, Tongji Hospital affiliated to Tongji Medical College of Huazhong University of Science & Technology, Wuhan
| | - X M Jin
- Department of Oncology, General Hospital of Ningxia Medical University, Yinchuan
| | - L Yang
- Department of Urology, The Second Hospital of Lanzhou University, Lanzhou
| | - S X Zhu
- Department of Urology, Fujian Medical University Union Hospital, Fuzhou
| | - J H Liu
- Department of Urology, The Second Affiliated Hospital of Kunming Medical University, Kunming
| | - Y H Huang
- Department of Urology, The First Affiliated Hospital of Soochow University, Suzhou
| | - T Xu
- Department of Urology, Peking University People's Hospital, Beijing
| | - B Liu
- Department of Urology, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou
| | - T Sun
- Department of Urology, The First Affiliated Hospital of Nanchang University, Nanchang
| | - Z J Wang
- Department of Urology, The First Affiliated Hospital of Nanjing Medical University, Nanjing
| | - H W Jiang
- Department of Urology, Huashan Hospital, Fudan University, Shanghai
| | - D X Yu
- Department of Urology, The Second Affiliated Hospital of Anhui Medical University, Hefei
| | - A P Zhou
- Department of Medical Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing
| | - J Jiang
- Department of Urology, The PLA General Hospital Army Characteristic Medical Center, Chongqing
| | - G D Luan
- Shanghai Junshi Biosciences Co., Ltd., Shanghai
| | - C L Jin
- Shanghai Junshi Biosciences Co., Ltd., Shanghai
| | - J Xu
- Shanghai Junshi Biosciences Co., Ltd., Shanghai
| | - J X Hu
- Shanghai Junshi Biosciences Co., Ltd., Shanghai
| | - Y R Huang
- Department of Urology, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - J Guo
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Genitourinary Oncology, Peking University Cancer Hospital & Institute, Beijing
| | - W Zhai
- Department of Urology, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
| | - X N Sheng
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Genitourinary Oncology, Peking University Cancer Hospital & Institute, Beijing.
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7
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Li W, Jiang J, Yin X, Zhang Y, Zou X, Sun M, Jia J, Ma B, Xu J. Mediation of Regional Cerebral Blood Flow in the Relationship between Specific Gut Microbiota and Cognition in Vascular Cognitive Impairment. J Alzheimers Dis 2024; 97:435-445. [PMID: 38108351 DOI: 10.3233/jad-230709] [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: 12/19/2023]
Abstract
BACKGROUND Gut microbiota could affect the onset and development of vascular cognitive impairment (VCI) through modulating metabolic and immune pathways. However, the vascular mechanisms involved remain unclear. OBJECTIVE To investigate the gut microbiota associated with VCI and examine the mediating effects of regional cerebral blood flow (CBF) to explore potential therapeutic targets for VCI. METHODS This prospective study enrolled patients with VCI (n = 16) and healthy controls (n = 18) from the Chinese Imaging, Biomarkers, and Lifestyle study between January 1 and June 30, 2022. The gut microbiota composition and diversity were determined by 16 S ribosomal RNA gene sequencing. The association between gut microbiota and Montreal Cognitive Assessment (MoCA) scores was determined using Spearman's correlation analysis. Regional CBF was calculated using pseudo-continuous arterial spin labeling. The mediating effects of regional CBF on the relationship between specific gut microbiota and cognition in VCI were investigated using mediation analysis. RESULTS Compared to healthy controls, patients with VCI had significantly greater abundance of Bifidobacterium, Veillonella, R uminococcus gnavus , Fusobacterium, and Erysipelatoclostridium and smaller abundance of Collinsella. The abundance of Ruminococcus gnavus was negatively associated with MoCA scores in patients with VCI, with the CBF in the left hypothalamus, right hypothalamus, and left amygdala accounting for 63.96%, 48.22%, and 36.51%, respectively, of this association after adjusting for confounders. CONCLUSIONS Ruminococcus gnavus is associated with cognition in VCI, which is strongly mediated by CBF in the bilateral hypothalamus and left amygdala. These findings highlight the potential regulatory roles of nutrition and metabolism-related areas of the brain in VCI.
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Affiliation(s)
- Wenyi Li
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- China National Clinical Research Center for Neurological Diseases, Beijing, China
| | - Jiwei Jiang
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- China National Clinical Research Center for Neurological Diseases, Beijing, China
| | | | - Yuan Zhang
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- China National Clinical Research Center for Neurological Diseases, Beijing, China
| | - Xinying Zou
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- China National Clinical Research Center for Neurological Diseases, Beijing, China
| | - Mengfan Sun
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- China National Clinical Research Center for Neurological Diseases, Beijing, China
| | - Jianjun Jia
- Department of Geriatric Neurology, The Second Medical Centre, Chinese PLA General Hospital, Beijing, China
| | - Baiping Ma
- Beijing Institute of Radiation Medicine, Beijing, China
| | - Jun Xu
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- China National Clinical Research Center for Neurological Diseases, Beijing, China
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Jiang J, Xia Z, Zheng D, Li Y, Li F, Wang W, Ding S, Zhang J, Su X, Zhai Q, Zuo Y, Zhang Y, Gaisano HY, He Y, Sun J. Factors associated with nocturnal and diurnal glycemic variability in patients with type 2 diabetes: a cross-sectional study. J Endocrinol Invest 2024; 47:245-253. [PMID: 37354249 DOI: 10.1007/s40618-023-02142-z] [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] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/16/2023] [Accepted: 06/16/2023] [Indexed: 06/26/2023]
Abstract
PURPOSE There is little information on factors that influence the glycemic variability (GV) during the nocturnal and diurnal periods. We aimed to examine the relationship between clinical factors and GV during these two periods. METHODS This cross-sectional study included 134 patients with type 2 diabetes. 24-h changes in blood glucose were recorded by a continuous glucose monitoring system. Nocturnal and diurnal GV were assessed by standard deviation of blood glucose (SDBG), coefficient of variation (CV), and mean amplitude of glycemic excursions (MAGE), respectively. Robust regression analyses were performed to identify the factors associated with GV. Restricted cubic splines were used to determine dose-response relationship. RESULTS During the nocturnal period, age and glycemic level at 12:00 A.M. were positively associated with GV, whereas alanine aminotransferase was negatively associated with GV. During the diurnal period, homeostatic model assessment 2-insulin sensitivity (HOMA2-S) was positively associated with GV, whereas insulin secretion-sensitivity index-2 (ISSI2) was negatively associated with GV. Additionally, we found a J-shape association between the glycemic level at 12:00 A.M. and MAGE, with 9.0 mmol/L blood glucose level as a cutoff point. Similar nonlinear associations were found between ISSI2 and SDBG, and between ISSI2 and MAGE, with ISSI2 value of 175 as a cutoff point. CONCLUSION Factors associated with GV were different between nocturnal and diurnal periods. The cutoff points we found in this study may provide the therapeutic targets for beta-cell function and pre-sleep glycemic level in clinical practice.
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Affiliation(s)
- J Jiang
- Department of Endocrinology, Jining No. 1 People's Hospital, 6 Jiankang Road, Rencheng District, Jining, 272000, Shandong, China
- Postdoctoral of Shandong University of Traditional Chinese Medicine, Jinan, Shandong, China
| | - Z Xia
- Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, No.10 Xitoutiao, You'anmen Wai, Fengtai District, Beijing, 100069, China
| | - D Zheng
- Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, No.10 Xitoutiao, You'anmen Wai, Fengtai District, Beijing, 100069, China
- Beijing Municipal Key Laboratory of Clinical Epidemiology, Beijing, China
| | - Y Li
- Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, No.10 Xitoutiao, You'anmen Wai, Fengtai District, Beijing, 100069, China
| | - F Li
- Department of Endocrinology, Jining No. 1 People's Hospital, 6 Jiankang Road, Rencheng District, Jining, 272000, Shandong, China
| | - W Wang
- Department of Endocrinology, Jining No. 1 People's Hospital, 6 Jiankang Road, Rencheng District, Jining, 272000, Shandong, China
| | - S Ding
- Department of Endocrinology, Jining No. 1 People's Hospital, 6 Jiankang Road, Rencheng District, Jining, 272000, Shandong, China
| | - J Zhang
- Department of Endocrinology, Jining No. 1 People's Hospital, 6 Jiankang Road, Rencheng District, Jining, 272000, Shandong, China
| | - X Su
- Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, No.10 Xitoutiao, You'anmen Wai, Fengtai District, Beijing, 100069, China
| | - Q Zhai
- Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, No.10 Xitoutiao, You'anmen Wai, Fengtai District, Beijing, 100069, China
| | - Y Zuo
- Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, No.10 Xitoutiao, You'anmen Wai, Fengtai District, Beijing, 100069, China
| | - Y Zhang
- Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, No.10 Xitoutiao, You'anmen Wai, Fengtai District, Beijing, 100069, China
| | - H Y Gaisano
- Departments of Medicine and Physiology, University of Toronto, Toronto, ON, Canada
| | - Y He
- Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, No.10 Xitoutiao, You'anmen Wai, Fengtai District, Beijing, 100069, China.
- Beijing Municipal Key Laboratory of Clinical Epidemiology, Beijing, China.
| | - J Sun
- Department of Endocrinology, Jining No. 1 People's Hospital, 6 Jiankang Road, Rencheng District, Jining, 272000, Shandong, China.
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Petrella JR, Jiang J, Sreeram K, Dalziel S, Doraiswamy PM, Hao W. Personalized Computational Causal Modeling of the Alzheimer Disease Biomarker Cascade. J Prev Alzheimers Dis 2024; 11:435-444. [PMID: 38374750 DOI: 10.14283/jpad.2023.134] [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 Mathematical models of complex diseases, such as Alzheimer's disease, have the potential to play a significant role in personalized medicine. Specifically, models can be personalized by fitting parameters with individual data for the purpose of discovering primary underlying disease drivers, predicting natural history, and assessing the effects of theoretical interventions. Previous work in causal/mechanistic modeling of Alzheimer's Disease progression has modeled the disease at the cellular level and on a short time scale, such as minutes to hours. No previous studies have addressed mechanistic modeling on a personalized level using clinically validated biomarkers in individual subjects. OBJECTIVES This study aimed to investigate the feasibility of personalizing a causal model of Alzheimer's Disease progression using longitudinal biomarker data. DESIGN/SETTING/PARTICIPANTS/MEASUREMENTS We chose the Alzheimer Disease Biomarker Cascade model, a widely-referenced hypothetical model of Alzheimer's Disease based on the amyloid cascade hypothesis, which we had previously implemented mathematically as a mechanistic model. We used available longitudinal demographic and serial biomarker data in over 800 subjects across the cognitive spectrum from the Alzheimer's Disease Neuroimaging Initiative. The data included participants that were cognitively normal, had mild cognitive impairment, or were diagnosed with dementia (probable Alzheimer's Disease). The model consisted of a sparse system of differential equations involving four measurable biomarkers based on cerebrospinal fluid proteins, imaging, and cognitive testing data. RESULTS Personalization of the Alzheimer Disease Biomarker Cascade model with individual serial biomarker data yielded fourteen personalized parameters in each subject reflecting physiologically meaningful characteristics. These included growth rates, latency values, and carrying capacities of the various biomarkers, most of which demonstrated significant differences across clinical diagnostic groups. The model fits to training data across the entire cohort had a root mean squared error (RMSE) of 0.09 (SD 0.081) on a variable scale between zero and one, and were robust, with over 90% of subjects showing an RMSE of < 0.2. Similarly, in a subset of subjects with data on all four biomarkers in at least one test set, performance was high on the test sets, with a mean RMSE of 0.15 (SD 0.117), with 80% of subjects demonstrating an RMSE < 0.2 in the estimation of future biomarker points. Cluster analysis of parameters revealed two distinct endophenotypic groups, with distinct biomarker profiles and disease trajectories. CONCLUSION Results support the feasibility of personalizing mechanistic models based on individual biomarker trajectories and suggest that this approach may be useful for reclassifying subjects on the Alzheimer's clinical spectrum. This computational modeling approach is not limited to the Alzheimer Disease Biomarker Cascade hypothesis, and can be applied to any mechanistic hypothesis of disease progression in the Alzheimer's field that can be monitored with biomarkers. Thus, it offers a computational platform to compare and validate various disease hypotheses, personalize individual biomarker trajectories and predict individual response to theoretical prevention and therapeutic intervention strategies.
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Affiliation(s)
- J R Petrella
- Jeffrey R. Petrella, Department of Radiology, Duke University School of Medicine, DUMC - Box 3808 , 27710-3808, NC, USA
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Jiang T, Wang J, Wang Y, Jiang J, Zhou J, Wang X, Zhang D, Xu J. Mitochondrial protein prohibitin promotes learning memory recovery in mice following intracerebral hemorrhage via CAMKII/CRMP signaling pathway. Neurochem Int 2023; 171:105637. [PMID: 37923298 DOI: 10.1016/j.neuint.2023.105637] [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: 08/24/2023] [Revised: 10/26/2023] [Accepted: 10/31/2023] [Indexed: 11/07/2023]
Abstract
Prohibitin (PHB) is a mitochondrial inner membrane protein with neuroprotective, antioxidant, and apoptosis-reducing effects. This study aimed to explore the role of PHB in pathological symptoms, behavioral deficits, and cognitive impairment in a collagenase-IV-induced intracerebral hemorrhage (ICH) murine model. In this study, mice that received collagenase IV injection were pretreated with PHB or saline 21 days prior to modeling. The role of PHB in memory and learning ability was monitored using the Morris water maze, Y-maze, and rotarod, social, startle, and nest-building tests. The effect of PHB on depression-like symptoms was examined using the forced swimming, tail suspension, and sucrose preference tests. Subsequently, mouse samples were analyzed using immunohistochemistry, western blotting, Perls staining, Nissl staining, and gene sequencing. Results showed that collagenase IV significantly induced behavioral deficits, brain edema, cognitive impairment, and depressive symptoms. PHB overexpression effectively alleviated memory, learning, and motor deficits in mice with ICH. PHB markedly inhibited the number of terminal deoxynucleotidyl transferase-mediated deoxyuridine triphosphate nick-end labeling-positive cells and protein levels of ionized calcium-binding adapter molecule 1, glial fibrillary acidic protein, and interleukin-1β in the perihematomal region of ICH mice. PHB overexpression also remarkably promoted production of neurologin1 (NLGL1), and upregulated levels of Ca2+-calmodulin-dependent kinase II (CaMKII) and collapsin response mediator protein-1 (CRMP1) proteins. In conclusion, PHB overexpression can effectively alleviate the neurological deficits and neurodegeneration around the hematoma region. This may play a protective role by upregulating the expression of NLGL1 and promoting expression of CaMKII and CRMP1.
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Affiliation(s)
- Tianlin Jiang
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China; Institute of Translational Medicine, Medical College, Yangzhou University, Yangzhou, 225009, China
| | - Jiahua Wang
- Institute of Translational Medicine, Medical College, Yangzhou University, Yangzhou, 225009, China; Department of Anesthesia, Affiliated Hospital of Yangzhou University, Yangzhou, 225001, China
| | - Yanli Wang
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Jiwei Jiang
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Jiawei Zhou
- Institute of Translational Medicine, Medical College, Yangzhou University, Yangzhou, 225009, China; Jiangsu Key Laboratory of Experimental & Translational Non-coding RNA Research, Yangzhou University, YangZhou, 225001, China
| | - Xiaohong Wang
- Institute of Translational Medicine, Medical College, Yangzhou University, Yangzhou, 225009, China; Jiangsu Key Laboratory of Experimental & Translational Non-coding RNA Research, Yangzhou University, YangZhou, 225001, China.
| | - Deke Zhang
- Department of Pharmacy, Affiliated Hospital of Shandong University of Traditional Chinese Medicine, No. 16369, Jingshi Road, Lixia district, Jinan City, Shandong Province, China.
| | - Jun Xu
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.
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Jiang J, Liu Y, Wang A, Zhuo Z, Shi H, Zhang X, Li W, Sun M, Jiang S, Wang Y, Zou X, Zhang Y, Jia Z, Xu J. Development and validation of a nutrition-related genetic-clinical-radiological nomogram associated with behavioral and psychological symptoms in Alzheimer's disease. Chin Med J (Engl) 2023:00029330-990000000-00878. [PMID: 38031345 DOI: 10.1097/cm9.0000000000002914] [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: 03/13/2023] [Indexed: 12/01/2023] Open
Abstract
BACKGROUND Few evidence is available in the early prediction models of behavioral and psychological symptoms of dementia (BPSD) in Alzheimer's disease (AD). This study aimed to develop and validate a novel genetic-clinical-radiological nomogram for evaluating BPSD in patients with AD and explore its underlying nutritional mechanism. METHODS This retrospective study included 165 patients with AD from the Chinese Imaging, Biomarkers, and Lifestyle (CIBL) cohort between June 1, 2021, and March 31, 2022. Data on demoimagedatas, neuropsychological assessments, single-nucleotide polymorphisms of AD risk genes, and regional brain volumes were collected. A multivariate logistic regression model identified BPSD-associated factors, for subsequently constructing a diagnostic nomogram. This nomogram was internally validated through 1000-bootstrap resampling and externally validated using a time-series split based on the CIBL cohort data between June 1, 2022, and February 1, 2023. Area under receiver operating characteristic (ROC) curves, calibration curves, and decision curve analysis (DCA) were used to assess the discrimination, calibration, and clinical applicability of the nomogram. RESULTS Factors independently associated with BPSD were: CETP rs1800775 (odds ratio [OR] = 4.137, 95% confidence interval [CI]: 1.276-13.415, P = 0.018), decreased Mini Nutritional Assessment score (OR = 0.187, 95% CI: 0.086-0.405, P <0.001), increased caregiver burden inventory score (OR = 8.993, 95% CI: 3.830-21.119, P <0.001), and decreased brain stem volume (OR = 0.006, 95% CI: 0.001-0.191, P = 0.004). These variables were incorporated into the nomogram. The area under the ROC curve was 0.925 (95% CI: 0.884-0.967, P <0.001) in the internal validation and 0.791 (95% CI: 0.686-0.895, P <0.001) in the external validation. The calibration plots showed favorable consistency between the prediction of nomogram and actual observations, and the DCA showed that the model was clinically useful in both validations. CONCLUSION A novel nomogram was established and validated based on lipid metabolism-related genes, nutritional status, and brain stem volumes, which may allow patients with AD to benefit from early triage and more intensive monitoring of BPSD. REGISTRATION Chictr.org.cn, ChiCTR2100049131.
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Affiliation(s)
- Jiwei Jiang
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing 100070, China
- National Clinical Research Center for Neurological Diseases, Beijing 100070, China
| | - Yaou Liu
- National Clinical Research Center for Neurological Diseases, Beijing 100070, China
- Department of Radiology, Beijing Tiantan Hospital, Capital Medical University, Beijing 100070, China
| | - Anxin Wang
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing 100070, China
- National Clinical Research Center for Neurological Diseases, Beijing 100070, China
| | - Zhizheng Zhuo
- National Clinical Research Center for Neurological Diseases, Beijing 100070, China
- Department of Radiology, Beijing Tiantan Hospital, Capital Medical University, Beijing 100070, China
| | - Hanping Shi
- Department of Gastrointestinal Surgery, Beijing Shijitan Hospital, Capital Medical University, Beijing 100038, China
- Department of Clinical Nutrition, Beijing Shijitan Hospital, Capital Medical University, Beijing 100038, China
- Beijing International Science and Technology Cooperation Base for Cancer Metabolism and Nutrition, Beijing 100081, China
| | - Xiaoli Zhang
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing 100070, China
- National Clinical Research Center for Neurological Diseases, Beijing 100070, China
| | - Wenyi Li
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing 100070, China
- National Clinical Research Center for Neurological Diseases, Beijing 100070, China
| | - Mengfan Sun
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing 100070, China
- National Clinical Research Center for Neurological Diseases, Beijing 100070, China
| | - Shirui Jiang
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing 100070, China
- National Clinical Research Center for Neurological Diseases, Beijing 100070, China
| | - Yanli Wang
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing 100070, China
- National Clinical Research Center for Neurological Diseases, Beijing 100070, China
| | - Xinying Zou
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing 100070, China
- National Clinical Research Center for Neurological Diseases, Beijing 100070, China
| | - Yuan Zhang
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing 100070, China
- National Clinical Research Center for Neurological Diseases, Beijing 100070, China
| | - Ziyan Jia
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing 100070, China
- National Clinical Research Center for Neurological Diseases, Beijing 100070, China
| | - Jun Xu
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing 100070, China
- National Clinical Research Center for Neurological Diseases, Beijing 100070, China
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Jiang J, Liu B, Li YW, Hothi SS. Clinical service evaluation of the feasibility and reproducibility of novel artificial intelligence based-echocardiographic quantification of global longitudinal strain and left ventricular ejection fraction in trastuzumab-treated patients. Front Cardiovasc Med 2023; 10:1250311. [PMID: 38045908 PMCID: PMC10693341 DOI: 10.3389/fcvm.2023.1250311] [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] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2023] [Accepted: 10/16/2023] [Indexed: 12/05/2023] Open
Abstract
Introduction Cardiotoxicity is a potential prognostically important complication of certain chemotherapeutic agents that may result in preclinical or overt clinical heart failure. In some cases, chemotherapy must be withheld when left ventricular (LV) systolic function becomes significantly impaired, to protect cardiac function at the expense of a change in the oncological treatment plan, leading to associated changes in oncological prognosis. Accordingly, patients receiving potentially cardiotoxic chemotherapy undergo routine surveillance before, during and following completion of therapy, usually with transthoracic echocardiography (TTE). Recent advancements in AI-based cardiac imaging reveal areas of promise but key challenges remain. There are ongoing questions as to whether the ability of AI to detect subtle changes in individual patients is at a level equivalent to manual analysis. This raises the question as to whether AI-based left ventricular strain analysis could provide a potential solution to left ventricular systolic function analysis in a manner equivocal to or superior to conventional assessment, in a real-world clinical service. AI based automated analyses may represent a potential solution for addressing the pressure of increasing echocardiographic demands within limited service-capacity healthcare systems, in addition to facilitating more accurate diagnoses. Methods This clinical service evaluation aims to establish whether AI-automated analysis compared to conventional methods (1) is a feasible method for assessing LV-GLS and LVEF, (2) yields moderate to good correlation between the two approaches, and (3) would lead to different clinical recommendations with serial surveillance in a real-world clinical population. Results and Discussion We observed a moderate correlation (r = 0.541) in GLS between AI automated assessment compared to conventional methods. The LVEF quantification between methods demonstrated a strong correlation (r = 0.895). AI-generated GLS and LVEF values compared reasonably well with conventional methods, demonstrating a similar temporal pattern throughout echocardiographic surveillance. The apical-three chamber view demonstrated the lowest correlation (r = 0.423) and revealed to be least successful for acquisition of GLS and LVEF. Compared to conventional methodology, AI-automated analysis has a significantly lower feasibility rate, demonstrating a success rate of 14% (GLS) and 51% (LVEF).
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Affiliation(s)
- J. Jiang
- Heart and Lung Centre, New Cross Hospital, Royal Wolverhampton NHS Trust, Wolverhampton, United Kingdom
| | - B. Liu
- Department of Cardiology, Manchester University NHS Foundation Trust, Manchester, United Kingdom
- Institute of Cardiovascular Sciences, University of Birmingham, Birmingham, United Kingdom
| | - Y. W. Li
- Department of Anaesthesia, New Cross Hospital, Royal Wolverhampton NHS Trust, Wolverhampton, United Kingdom
| | - S. S. Hothi
- Heart and Lung Centre, New Cross Hospital, Royal Wolverhampton NHS Trust, Wolverhampton, United Kingdom
- Institute of Cardiovascular Sciences, University of Birmingham, Birmingham, United Kingdom
- Research Centre for Health and Life Sciences, Coventry University, Coventry, United Kingdom
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Abe K, Hayato Y, Hiraide K, Ieki K, Ikeda M, Kameda J, Kanemura Y, Kaneshima R, Kashiwagi Y, Kataoka Y, Miki S, Mine S, Miura M, Moriyama S, Nakano Y, Nakahata M, Nakayama S, Noguchi Y, Okamoto K, Sato K, Sekiya H, Shiba H, Shimizu K, Shiozawa M, Sonoda Y, Suzuki Y, Takeda A, Takemoto Y, Takenaka A, Tanaka H, Watanabe S, Yano T, Han S, Kajita T, Okumura K, Tashiro T, Tomiya T, Wang X, Xia J, Yoshida S, Megias GD, Fernandez P, Labarga L, Ospina N, Zaldivar B, Pointon BW, Kearns E, Raaf JL, Wan L, Wester T, Bian J, Griskevich NJ, Kropp WR, Locke S, Smy MB, Sobel HW, Takhistov V, Yankelevich A, Hill J, Park RG, Bodur B, Scholberg K, Walter CW, Bernard L, Coffani A, Drapier O, El Hedri S, Giampaolo A, Mueller TA, Santos AD, Paganini P, Quilain B, Ishizuka T, Nakamura T, Jang JS, Learned JG, Choi K, Cao S, Anthony LHV, Martin D, Scott M, Sztuc AA, Uchida Y, Berardi V, Catanesi MG, Radicioni E, Calabria NF, Machado LN, De Rosa G, Collazuol G, Iacob F, Lamoureux M, Mattiazzi M, Ludovici L, Gonin M, Pronost G, Fujisawa C, Maekawa Y, Nishimura Y, Friend M, Hasegawa T, Ishida T, Kobayashi T, Jakkapu M, Matsubara T, Nakadaira T, Nakamura K, Oyama Y, Sakashita K, Sekiguchi T, Tsukamoto T, Boschi T, Di Lodovico F, Gao J, Goldsack A, Katori T, Migenda J, Taani M, Zsoldos S, Kotsar Y, Ozaki H, Suzuki AT, Takeuchi Y, Bronner C, Feng J, Kikawa T, Mori M, Nakaya T, Wendell RA, Yasutome K, Jenkins SJ, McCauley N, Mehta P, Tsui KM, Fukuda Y, Itow Y, Menjo H, Ninomiya K, Lagoda J, Lakshmi SM, Mandal M, Mijakowski P, Prabhu YS, Zalipska J, Jia M, Jiang J, Jung CK, Wilking MJ, Yanagisawa C, Harada M, Ishino H, Ito S, Kitagawa H, Koshio Y, Nakanishi F, Sakai S, Barr G, Barrow D, Cook L, Samani S, Wark D, Nova F, Yang JY, Malek M, McElwee JM, Stone O, Thiesse MD, Thompson LF, Okazawa H, Kim SB, Seo JW, Yu I, Ichikawa AK, Nakamura KD, Tairafune S, Nishijima K, Iwamoto K, Nakagiri K, Nakajima Y, Taniuchi N, Yokoyama M, Martens K, de Perio P, Vagins MR, Kuze M, Izumiyama S, Inomoto M, Ishitsuka M, Ito H, Kinoshita T, Matsumoto R, Ommura Y, Shigeta N, Shinoki M, Suganuma T, Yamauchi K, Martin JF, Tanaka HA, Towstego T, Akutsu R, Gousy-Leblanc V, Hartz M, Konaka A, Prouse NW, Chen S, Xu BD, Zhang B, Posiadala-Zezula M, Hadley D, Nicholson M, O'Flaherty M, Richards B, Ali A, Jamieson B, Marti L, Minamino A, Pintaudi G, Sano S, Suzuki S, Wada K. Erratum: Search for Cosmic-Ray Boosted Sub-GeV Dark Matter Using Recoil Protons at Super-Kamiokande [Phys. Rev. Lett. 130, 031802 (2023)]. Phys Rev Lett 2023; 131:159903. [PMID: 37897794 DOI: 10.1103/physrevlett.131.159903] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/01/2023] [Indexed: 10/30/2023]
Abstract
This corrects the article DOI: 10.1103/PhysRevLett.130.031802.
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Xue W, Zhou Q, Cui X, Zhang J, Zuo S, Mo F, Jiang J, Zhu X, Lin Z. Atomically Dispersed FeN 2 P 2 Motif with High Activity and Stability for Oxygen Reduction Reaction Over the Entire pH Range. Angew Chem Int Ed Engl 2023; 62:e202307504. [PMID: 37345265 DOI: 10.1002/anie.202307504] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/28/2023] [Revised: 06/18/2023] [Accepted: 06/19/2023] [Indexed: 06/23/2023]
Abstract
The past decade has witnessed the great potential of Fe-based single-atom electrocatalysis in catalyzing oxygen reduction reaction (ORR). However, it remains a grand challenge to substantially improve their intrinsic activity and long-term stability in acidic electrolytes. Herein, we report a facile chemical vapor deposition strategy, by which high-density Fe atoms (3.97 wt%) are coordinated with square-planar para-positioned nitrogen and phosphorus atoms in a hierarchical carbon framework. The as-crafted atomically dispersed Fe catalyst (denoted Fe-SA/PNC) manifests an outstanding activity towards ORR over the entire pH range. Specifically, the half-wave potential of 0.92 V, 0.83 V, and 0.86 V vs. reversible hydrogen electrode (RHE) are attained in alkaline, neutral, and acidic electrolytes, respectively, representing the high performance among reported catalysts to date. Furthermore, after 30,000 durability cycles, the Fe-SA/PNC remains to be stable with no visible performance decay when tested in 0.1 M KOH and 0.5 M H2 SO4 , and only a minor negative shift of 40 mV detected in 0.1 M HClO4 , significantly outperforming commercial Pt/C counterpart. The coordination motif of Fe-SA/PNC is validated by density functional theory (DFT) calculations. This work provides atomic-level insight into improving the activity and stability of non-noble metal ORR catalysts, opening up an avenue to craft the desired single-atom electrocatalysts.
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Affiliation(s)
- Wendan Xue
- Key Laboratory of Pollution Processes and Environmental Criteria (Ministry of Education), Nankai University, Tianjin, 300071, P. R. China
- School of Materials Science and Engineering, Georgia Institute of Technology, Atlanta, GA, 30332, USA
| | - Qixing Zhou
- Key Laboratory of Pollution Processes and Environmental Criteria (Ministry of Education), Nankai University, Tianjin, 300071, P. R. China
| | - Xun Cui
- School of Materials Science and Engineering, Georgia Institute of Technology, Atlanta, GA, 30332, USA
| | - Jiawei Zhang
- School of Materials Science and Engineering, Georgia Institute of Technology, Atlanta, GA, 30332, USA
| | - Sijin Zuo
- School of Engineering, China Pharmaceutical University, Nanjing, 210009, P. R. China
| | - Fan Mo
- Key Laboratory of Pollution Processes and Environmental Criteria (Ministry of Education), Nankai University, Tianjin, 300071, P. R. China
| | - Jiwei Jiang
- Key Laboratory of Pollution Processes and Environmental Criteria (Ministry of Education), Nankai University, Tianjin, 300071, P. R. China
| | - Xuya Zhu
- Key Laboratory of Pollution Processes and Environmental Criteria (Ministry of Education), Nankai University, Tianjin, 300071, P. R. China
| | - Zhiqun Lin
- School of Materials Science and Engineering, Georgia Institute of Technology, Atlanta, GA, 30332, USA
- Department of Chemical and Biomolecular Engineering, National University of Singapore, Singapore, 117585, Singapore
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Sun Y, Ni YA, Xu HJ, Wang LZ, Yang J, Jiang J, Zhong R. [Two cases of refractory childhood acute B-lymphoblastic leukemia with positive KMT2A-USP2 treated with Belintouximab]. Zhonghua Er Ke Za Zhi 2023; 61:930-932. [PMID: 37803862 DOI: 10.3760/cma.j.cn112140-20230406-00244] [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: 10/08/2023]
Affiliation(s)
- Y Sun
- Pediatric Hematology and Oncology Department, the Affiliated Hospital of Qingdao University, Qingdao 266000, China
| | - Y A Ni
- Pediatric Hematology and Oncology Department, the Affiliated Hospital of Qingdao University, Qingdao 266000, China
| | - H J Xu
- Pediatric Hematology and Oncology Department, the Affiliated Hospital of Qingdao University, Qingdao 266000, China
| | - L Z Wang
- Pediatric Hematology and Oncology Department, the Affiliated Hospital of Qingdao University, Qingdao 266000, China
| | - J Yang
- Pediatric Hematology and Oncology Department, the Affiliated Hospital of Qingdao University, Qingdao 266000, China
| | - J Jiang
- Pediatric Hematology and Oncology Department, the Affiliated Hospital of Qingdao University, Qingdao 266000, China
| | - R Zhong
- Pediatric Hematology and Oncology Department, the Affiliated Hospital of Qingdao University, Qingdao 266000, China
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Choi C, Thor M, Jiang J, Rimner A, Veeraraghavan H. Determining the Dosimetric Accuracy of Deep Learning-Based Fully Automated Registration-Segmentation Approach for Thoracic Cancer Organs-at-Risk Contouring. Int J Radiat Oncol Biol Phys 2023; 117:e656-e657. [PMID: 37785947 DOI: 10.1016/j.ijrobp.2023.06.2087] [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) For adaptive radiation therapy (ART), the contours on the planning CT (pCT) are frequently propagated to cone-beam CT (CBCT) via deformable image registration and manually edited, which is observer-dependent and time-consuming. To automate this process, we created a fully automated workflow by combining a deep learning (DL)-based pCT segmentation model with a CT-to-CBCT registration-segmentation DL model. The purpose of our research is to determine how using the proposed workflow's automatically generated contours affects thoracic organs-at-risk sparing (OAR). MATERIALS/METHODS Seven patients with locally advanced non-small cell lung cancer who underwent treatment with intensity modulated radiation therapy were included in this study. Each patient's pCT was segmented using a published DL model that has been used for generating thoracic OAR segmentation and radiotherapy planning in the clinic since July of 2020. Next, pCT was deformably registered using a published recurrent deep registration-segmentation method. Whereas the original method's segmentation sub-network was only trained to segment esophagus, the registration sub-network was used to propagate contours for heart, esophagus, and the proximal bronchial tree (PBT). Geometric segmentation accuracy using the Dice Similarity Coefficient (DSC) and the 95th percentile Hausdorff Distance (HD) and dose metrics including the mean esophageal dose (MED) and D90% of the heart (D90) were computed from the total accumulated dose for the first two weeks of treatment. RESULTS The esophagus had a high DSC and a low HD (0.93 and 2.85mm) and conversely, the heart had lower accuracy (DSC = 0.85, HD = 22.06mm). PBT showed relatively high performance as well, with DSC of 0.91 and HD of 2.28mm, owing to its proximity to the esophagus. The accumulated MED for manual contour was slightly lower than AI-contours (11.34 vs 11.83 Gy), suggesting reliability of the proposed workflow. The reverse is seen for the D90 of the heart (manual = 1.74 and AI-contour = 1.56 Gy), likely due to the heart not being included in the original DL framework. CONCLUSION This study reported preliminary results on the feasibility of using a fully automated and patient-specific workflow for CBCT auto-segmentation in ART, confirming its role as a geometrically and dosimetrically accurate solution for thoracic OARs. However, because it is currently limited to the esophagus, we believe that re-training the algorithm will increase confidence in other OARs such as the heart and lungs.
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Affiliation(s)
- C Choi
- Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, NY
| | - M Thor
- Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, NY
| | - J Jiang
- Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, NY
| | - A Rimner
- Department of Radiation Oncology, Memorial Sloan Kettering Cancer Center, New York, NY
| | - H Veeraraghavan
- Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, NY
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Choi C, Mankuzhy NP, Jiang J, Elguindi S, Thor M, Rimner A, Veeraraghavan H. Clinical Feasibility of Deep Learning-Based CT during Treatment CBCT Tumor Registration-Segmentation in Thoracic Radiotherapy (RT). Int J Radiat Oncol Biol Phys 2023; 117:e656. [PMID: 37785946 DOI: 10.1016/j.ijrobp.2023.06.2086] [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) Accurate tumor segmentation on weekly cone-beam computed tomography (CBCT) images is critical for image-guided and adaptive radiation therapy (ART). In thoracic RT, low image contrast, imaging artifact, and geometry and image modality differences from the planning CT (pCT) typically limits accurate tumor segmentation and registration. Here, we explored the clinical feasibility of using 3D recurrent registration-segmentation deep learning (DL) that combines patient-specific anatomic and shape context from higher contrast pCT and planning contours (PACs) for tumor segmentation on during treatment CBCTs. MATERIALS/METHODS We included the pCT and CBCTs from six patients with locally advanced non-small cell lung cancer (LA-NSCLC) who had underwent RT. Cases were selected with a primary GTV contoured and labeled separately from the nodal GTV. Using rigidly aligned pCT and CBCT as inputs, DL auto-segmented the GTV on week 1 and 6 CBCTs, and these auto-segmented contours were manually inspected by a radiation oncologist that edited the GTV according to clinical standard quality. The Dice similarity coefficient (DSC), Hausdorff distance (HD95), mean surface distance (MSD), surface DSC (sDSC) and added path length (APL) were used to quantitively compare the DL and the edited GTV. RESULTS The primary GTV was in the right lung in five cases, and left lung in one case. Manual adjustments were typically made at the interface of GTV and lung parenchyma with partial inclusion of adjacent vessels. Hypodensities within the GTV were sometimes not segmented in all axial slices resulting in discontinuous components. The quantitative comparison between the edited and DL-generated GTV is shown in Table 1. For week 1, the average DSC and HD95 were 0.87 and 6.94 mm, respectively. The performance for week 6 was slightly lower than week 1, with a DSC of 0.85 and HD95 of 7.22 mm. CONCLUSION The agreement with the generated DL GTV and the edited GTV was high in week 1 and decreased somewhat later during the treatment course possibly due to a higher impact of geometric changes in tumor and adjacent structures. The proposed DL algorithm showed reasonable performance throughout the treatment, supporting its potential for use into clinical routine for LA-NSCLC.
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Affiliation(s)
- C Choi
- Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, NY
| | - N P Mankuzhy
- Department of Radiation Oncology, Memorial Sloan Kettering Cancer Center, New York, NY
| | - J Jiang
- Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, NY
| | - S Elguindi
- Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, NY
| | - M Thor
- Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, NY
| | - A Rimner
- Department of Radiation Oncology, Memorial Sloan Kettering Cancer Center, New York, NY
| | - H Veeraraghavan
- Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, NY
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Jiang J, Rezaeitaleshmahalleh M, Lyu Z, Mu N, Ahmed AS, Md CMS, Gemmete JJ, Pandey AS. Augmenting Prediction of Intracranial Aneurysms' Risk Status Using Velocity-Informatics: Initial Experience. J Cardiovasc Transl Res 2023; 16:1153-1165. [PMID: 37160546 PMCID: PMC10949935 DOI: 10.1007/s12265-023-10394-6] [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] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/14/2022] [Accepted: 04/26/2023] [Indexed: 05/11/2023]
Abstract
Our primary goal here is to demonstrate that innovative analytics of aneurismal velocities, named velocity-informatics, enhances intracranial aneurysm (IA) rupture status prediction. 3D computer models were generated using imaging data from 112 subjects harboring anterior IAs (4-25 mm; 44 ruptured and 68 unruptured). Computational fluid dynamics simulations and geometrical analyses were performed. Then, computed 3D velocity vector fields within the IA dome were processed for velocity-informatics. Four machine learning methods (support vector machine, random forest, generalized linear model, and GLM with Lasso or elastic net regularization) were employed to assess the merits of the proposed velocity-informatics. All 4 ML methods consistently showed that, with velocity-informatics metrics, the area under the curve and prediction accuracy both improved by approximately 0.03. Overall, with velocity-informatics, the support vector machine's prediction was most promising: an AUC of 0.86 and total accuracy of 77%, with 60% and 88% of ruptured and unruptured IAs being correctly identified, respectively.
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Affiliation(s)
- J Jiang
- Department of Biomedical Engineering, Michigan Technological University, Houghton, MI, 49931, USA.
- Center for Biocomputing and Digital Health, Health Research Institute, and Institute of Computing and Cybernetics, Michigan Technological University, Houghton, MI, USA.
- Department of Medical Physics, University of Wisconsin, Madison, WI, USA.
| | - M Rezaeitaleshmahalleh
- Department of Biomedical Engineering, Michigan Technological University, Houghton, MI, 49931, USA
- Center for Biocomputing and Digital Health, Health Research Institute, and Institute of Computing and Cybernetics, Michigan Technological University, Houghton, MI, USA
| | - Z Lyu
- Department of Biomedical Engineering, Michigan Technological University, Houghton, MI, 49931, USA
- Center for Biocomputing and Digital Health, Health Research Institute, and Institute of Computing and Cybernetics, Michigan Technological University, Houghton, MI, USA
| | - Nan Mu
- Department of Biomedical Engineering, Michigan Technological University, Houghton, MI, 49931, USA
- Center for Biocomputing and Digital Health, Health Research Institute, and Institute of Computing and Cybernetics, Michigan Technological University, Houghton, MI, USA
| | - A S Ahmed
- Department of Neurosurgery, University of Wisconsin, Madison, WI, USA
- Department of Radiology, University of Wisconsin, Madison, WI, USA
| | - C M Strother Md
- Department of Radiology, University of Wisconsin, Madison, WI, USA
| | - J J Gemmete
- Department of Radiology, University of Michigan, Ann Arbor, MI, USA
| | - A S Pandey
- Department of Neurosurgery, University of Michigan, Ann Arbor, MI, USA
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Deng LH, Geng JX, Xue Q, Jiang J, Chen LX, Wang JT. Correlation between nocturnal intermittent hypoxemia and mild cognitive impairment in the older adult and the role of BDNF Val66Met polymorphism: a hospital-based cross-sectional study. Sleep Breath 2023; 27:1945-1952. [PMID: 36567420 DOI: 10.1007/s11325-022-02772-2] [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: 02/27/2022] [Revised: 11/14/2022] [Accepted: 12/16/2022] [Indexed: 12/27/2022]
Abstract
PURPOSE To explore the prevalence of nocturnal intermittent hypoxemia (NIH) in a tertiary hospital geriatric department and the relationship between NIH and mild cognitive impairment (MCI) in older adults, and to examine the role of brain-derived neurotrophic factor (BDNF) Val66Met polymorphism. METHODS Older adults aged ≥ 60 were enrolled. NIH and cognitive assessments were conducted. BDNF concentrations and BDNF Val66Met polymorphism were detected for a preliminary exploration of the possible mechanism of the process. RESULTS Of 325 older adults enrolled, 157 (48%) had NIH and were further divided into mild, moderate, and severe NIH groups according to their oxygen desaturation of ≥ 4% per hour of sleep (ODI4). MCI detection rate in the four groups gradually increased, and the differences were statistically significant (chi-square = 4.457, P = 0.035). ODI4 was negatively correlated with MoCA score in all participants (r = - 0.115, P = 0.039) and patients with NIH (r = - 0.199, P = 0.012). After adjusting for sex, age, and cardiovascular risk factors, NIH and MCI remained independently associated (OR = 3.13, 95% CI 1.03-9.53, P = 0.045). BDNF levels were positively correlated with MoCA score (r = 0.169, P = 0.028) and negatively correlated with nocturnal average oxygen saturation in patients with NIH (r = - 0.288, P = 0.008). Older adults with different BDNF Val66Met genotypes did not show significant differences in MCI rate and BDNF levels (P > 0.05). CONCLUSION The older adults with NIH have a higher MCI detection rate. BDNF levels may be a potential biomarker for cognitive dysfunction in patients with NIH.
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Affiliation(s)
- L H Deng
- Department of Geriatrics, Peking University People's Hospital, No. 11 Xizhimen South Street, Xicheng District, 100044, Beijing, People's Republic of China
| | - J X Geng
- Peking University Health Science Center, Beijing, China
| | - Q Xue
- Department of Geriatrics, Peking University People's Hospital, No. 11 Xizhimen South Street, Xicheng District, 100044, Beijing, People's Republic of China
| | - J Jiang
- Department of Geriatrics, Peking University People's Hospital, No. 11 Xizhimen South Street, Xicheng District, 100044, Beijing, People's Republic of China
| | - L X Chen
- Department of Geriatrics, Peking University People's Hospital, No. 11 Xizhimen South Street, Xicheng District, 100044, Beijing, People's Republic of China
| | - J T Wang
- Department of Geriatrics, Peking University People's Hospital, No. 11 Xizhimen South Street, Xicheng District, 100044, Beijing, People's Republic of China.
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Sun R, Xi K, Song X, Yin W, Xi D, Shao Y, Gu W, Jiang J. The Effect of MDSC-Derived Exosomes Played in Esophageal Squamous Carcinoma Cells after Ionizing Radiation. Int J Radiat Oncol Biol Phys 2023; 117:e261. [PMID: 37785000 DOI: 10.1016/j.ijrobp.2023.06.1216] [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) Radiotherapy is the main treatment for esophageal cancer. Previous studies have shown that radiotherapy not only kills tumor cells directly, but also reshapes the immune microenvironment of the tumor. It has been reported an increase in the recruitment of myeloid-derived suppressor cells (MDSC) can occur in tumor tissue after ionizing radiation. Exosomes are mediators of intercellular information exchange and are also involved in the regulation of the tumor microenvironment. In this study, we wanted to understand whether MDSC in esophageal cancer tissue are involved in the regulation of tumor cell response to ionizing radiation via exosomes. MATERIALS/METHODS KYSE-150 was used to construct a subcutaneous transplantation tumor model in nude mice. And then mice irradiated with 5 Gy×5fx and 0 Gy×5fx respectively. After irradiation, the spleens of the mice were used to isolate MDSC, and collect the cell supernatants to extract the exosomes. Based on the exosomes, we divided the experiment into three groups (control, exosomes, exosomes+radiation). Exosomes were injected into a nude mouse model of esophageal cancer via the tail vein or co-cultured with KYSE-150 cells. Mice were irradiated with a 5 Gy×5fx after completion of injection, and KYSE-150 cells were irradiated with a single dose 4 Gy. After radiation, KYSE-150 cells were used to detect cell cloning, apoptosis and cell cycle by flow cytometry, cell proliferation by CCK 8. XRCC4,XRCC5,XRCC6,γH2AX,ATM expression in cells and tumor tissue were measured by Western blot and RT-PCR. RESULTS The tumor volume was significantly reduced after 5 Gy x 5fx radiation. When exosomes co-cultured with KYSE-150 cells, decrease in apoptosis and increase in cell cloning and cell proliferation were found in the exosomes+radiation group and exosomes group after radiation when compared with the control group, with this change being more pronounced in the exosome+radiation group. The results of the cell cycle assay showed that after ionizing radiation, the proportion of cells in the G0/G1 phase was significantly lower, and the proportion of cells in the S and G2/M phases were significantly higher in the exosomes+radiation group and exosomes group when compared to the Control group. The protein and mRNA expression of XRCC4,XRCC5,XRCC6,γH2AX,ATM in cells were increased in exosomes+radiation group and exosomes group after radiation when compared with the control group, with this change being more obvious in the exosome+radiation group. After irradiation, tumor volumes were measured in nude mice and the results showed that exosomes+radiation group tumors were the largest in volume, while the control group regressed most significantly after irradiation. CONCLUSION MDSC-derived exosomes have a tumor growth-promoting effect in esophageal squamous carcinoma, which is enhanced by ionizing radiation, and this may be related to the accelerated repair of damage in tumor tissue after radiation.
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Affiliation(s)
- R Sun
- Department of Radiotherapy & Oncology, The Third Affiliated Hospital of Soochow University, Chang Zhou, China
| | - K Xi
- Department of Oncology Radiotherapy, the Third Affiliated Hospital of Soochow University, Changzhou, Jiangsu, China
| | - X Song
- Department of Oncology Radiotherapy, the Third Affiliated Hospital of Soochow University, Changzhou, Jiangsu, China
| | - W Yin
- Department of Oncology Radiotherapy, the Third Affiliated Hospital of Soochow University, Changzhou, Jiangsu, China
| | - D Xi
- Department of Oncology Radiotherapy, the Third Affiliated Hospital of Soochow University, Changzhou, Jiangsu, China
| | - Y Shao
- Department of Oncology Radiotherapy, the Third Affiliated Hospital of Soochow University, Changzhou, Jiangsu, China
| | - W Gu
- Department of Oncology Radiotherapy, the Third Affiliated Hospital of Soochow University, Changzhou, Jiangsu, China
| | - J Jiang
- Department of Tumor Biological Treatment, the Third Affiliated Hospital of Soochow University, Changzhou, Jiangsu, China
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Jiang J, Shi H, Jiang S, Wang A, Zou X, Wang Y, Li W, Zhang Y, Sun M, Ren Q, Xu J. Nutrition in Alzheimer's disease: a review of an underappreciated pathophysiological mechanism. Sci China Life Sci 2023; 66:2257-2279. [PMID: 37058185 DOI: 10.1007/s11427-022-2276-6] [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] [Subscribe] [Scholar Register] [Received: 11/30/2022] [Accepted: 02/16/2023] [Indexed: 04/15/2023]
Abstract
Alzheimer's disease (AD) is the leading cause of dementia in older individuals and is an escalating challenge to global public health. Pharmacy therapy of AD is one of the well-funded areas; however, little progress has been made due to the complex pathogenesis. Recent evidence has demonstrated that modifying risk factors and lifestyle may prevent or delay the incidence of AD by 40%, which suggests that the management should pivot from single pharmacotherapy toward a multipronged approach because AD is a complex and multifaceted disease. Recently, the gut-microbiota-brain axis has gained tremendous traction in the pathogenesis of AD through bidirectional communication with multiple neural, immune, and metabolic pathways, providing new insights into novel therapeutic strategies. Dietary nutrition is an important and profound environmental factor that influences the composition and function of the microbiota. The Nutrition for Dementia Prevention Working Group recently found that dietary nutrition can affect cognition in AD-related dementia directly or indirectly through complex interactions of behavioral, genetic, systemic, and brain factors. Thus, considering the multiple etiologies of AD, nutrition represents a multidimensional factor that has a profound effect on AD onset and development. However, mechanistically, the effect of nutrition on AD is uncertain; therefore, optimal strategies or the timing of nutritional intervention to prevent or treat AD has not been established.Thus, this review summarizes the current state of knowledge concerning nutritional disorders, AD patient and caregiver burden, and the roles of nutrition in the pathophysiology of AD. We aim to emphasize knowledge gaps to provide direction for future research and to establish optimal nutrition-based intervention strategies for AD.
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Affiliation(s)
- Jiwei Jiang
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, 100070, China
- China National Clinical Research Center for Neurological Diseases, Beijing, 100070, China
| | - Hanping Shi
- Department of Gastrointestinal Surgery, Beijing Shijitan Hospital, Capital Medical University, Beijing, 100038, China
- Department of Clinical Nutrition, Beijing Shijitan Hospital, Capital Medical University, Beijing, 100038, China
- Beijing International Science and Technology Cooperation Base for Cancer Metabolism and Nutrition, Beijing, 100038, China
| | - Shirui Jiang
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, 100070, China
- China National Clinical Research Center for Neurological Diseases, Beijing, 100070, China
| | - Anxin Wang
- China National Clinical Research Center for Neurological Diseases, Beijing, 100070, China
| | - Xinying Zou
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, 100070, China
- China National Clinical Research Center for Neurological Diseases, Beijing, 100070, China
| | - Yanli Wang
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, 100070, China
- China National Clinical Research Center for Neurological Diseases, Beijing, 100070, China
| | - Wenyi Li
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, 100070, China
- China National Clinical Research Center for Neurological Diseases, Beijing, 100070, China
| | - Yuan Zhang
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, 100070, China
- China National Clinical Research Center for Neurological Diseases, Beijing, 100070, China
| | - Mengfan Sun
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, 100070, China
- China National Clinical Research Center for Neurological Diseases, Beijing, 100070, China
| | - Qiwei Ren
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, 100070, China
- China National Clinical Research Center for Neurological Diseases, Beijing, 100070, China
| | - Jun Xu
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, 100070, China.
- China National Clinical Research Center for Neurological Diseases, Beijing, 100070, China.
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Kennedy WR, Chang YW, Jiang J, Molloy J, Pennington-Krygier C, Harmon J, Hong A, Wanebo J, Braun K, Garcia MA, Barani IJ, Yoo W, Tovmasyan A, Tien AC, Li J, Mehta S, Sanai N. A Combined Phase 0/2 "Trigger" Trial Evaluating Pamiparib or Olaparib with Concurrent Radiotherapy in Patients with Newly-Diagnosed or Recurrent Glioblastoma. Int J Radiat Oncol Biol Phys 2023; 117:e115. [PMID: 37784657 DOI: 10.1016/j.ijrobp.2023.06.898] [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) This study evaluates the pharmacokinetic (PK) and pharmacodynamic (PD) profiles and clinical efficacy of PARP1/2 selective inhibitors, pamiparib and olaparib, in newly-diagnosed or recurrent glioblastoma (GBM) patients in combination with radiotherapy (RT). MATERIALS/METHODS In this combined phase 0/2 trial presumed newly-diagnosed (Arm A) or recurrent (Arm B) GBM patients received 4 days of pamiparib (60 mg BID) prior to resection either 2-4 or 8-12 hours following the final dose. Arm C enrolled patients with recurrent GBM to 4 days of olaparib (200 mg BID) prior to resection. Enhancing and nonenhancing tumor tissue, cerebrospinal fluid (CSF) and plasma were collected. Total and unbound drug concentrations were measured using validated LC-MS/MS methods. A PK 'trigger', defined as unbound drug and gt; 5-fold biochemical IC 50 in nonenhancing tumor, determined eligibility for the therapeutic expansion phase 2. PARP inhibition was assessed via ex vivo radiation and quantification of PAR levels compared to non-radiated control. Newly-diagnosed MGMT unmethylated GBMs and recurrent GBMs exceeding the PK threshold were eligible for an expansion phase of pamiparib (Arms A and B) or olaparib (Arm C) with concurrent RT followed by maintenance pamiparib or olaparib. RT was 60 Gy in 30 fractions in newly-diagnosed patients and 40 Gy in 15 fractions in recurrent patients, delivered using volumetric-modulated arc therapy (VMAT). RESULTS A total of 38 patients (Arm A, n = 16; Arm B, n = 16; Arm C, n = 6) were enrolled in the initial phase 0 study. The mean unbound concentrations of pamiparib in nonenhancing tumor region for Arm A and Arm B were 167.3 nM and 109.4 nM respectively, and in Arm C the mean unbound concentration of olaparib was 5.2 nM. All patients in the pamiparib arms (n = 32/32) but only 1 of 6 patients in the olaparib Arm C exceeded the PK threshold. Radiation-induced PAR expression was 2.44-fold in untreated control vs 1.16 in Arm A (p<0.05), 0.85 in Arm B (p<0.01) and 1.11 in Arm C patients, respectively. In Arm A, 11 patients had unmethylated tumors, and of those, 7 patients enrolled in phase 2. In Arm B, 9 of the 16 clinically eligible patients with positive PK results were enrolled in phase 2. At a median follow-up of 8.4 months [range: 1.3-15.7 months], the median progression-free survival (PFS) was 5.4, 6.0, and 3.8 months for Arms A (n = 7), B (n = 9), and C (n = 1), respectively. Grade 3+ toxicities related to pamiparib occurred in 4 patients, with 2 adverse events resulting in treatment discontinuation. No grade 3+ toxicities were documented in the olaparib arm. CONCLUSION Pamiparib achieved pharmacologically-relevant concentrations in nonenhancing GBM tissue and suppressed induction of PAR levels ex vivo post-radiation. The majority of patients with MGMT-unmethylated GBM advanced to the phase 2 portion of the trial, and pamiparib was generally well-tolerated in these patients.
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Affiliation(s)
- W R Kennedy
- Ivy Brain Tumor Center, Barrow Neurological Institute, Phoenix, AZ
| | - Y W Chang
- Ivy Brain Tumor Center, Barrow Neurological Institute, Phoenix, AZ
| | - J Jiang
- Wayne State University, Detroit, MI
| | - J Molloy
- Ivy Brain Tumor Center, Barrow Neurological Institute, Phoenix, AZ
| | | | - J Harmon
- Ivy Brain Tumor Center, Barrow Neurological Institute, Phoenix, AZ
| | - A Hong
- Ivy Brain Tumor Center, Barrow Neurological Institute, Phoenix, AZ
| | - J Wanebo
- Ivy Brain Tumor Center, Barrow Neurological Institute, Phoenix, AZ
| | - K Braun
- Ivy Brain Tumor Center, Barrow Neurological Institute, Phoenix, AZ
| | - M A Garcia
- Ivy Brain Tumor Center, Barrow Neurological Institute, Phoenix, AZ
| | - I J Barani
- Ivy Brain Tumor Center, Barrow Neurological Institute, Phoenix, AZ
| | - W Yoo
- Ivy Brain Tumor Center, Barrow Neurological Institute, Phoenix, AZ
| | - A Tovmasyan
- Ivy Brain Tumor Center, Barrow Neurological Institute, Phoenix, AZ
| | - A C Tien
- Ivy Brain Tumor Center, Barrow Neurological Institute, Phoenix, AZ
| | - J Li
- Wayne State University, Detroit, MI
| | - S Mehta
- Ivy Brain Tumor Center, Barrow Neurological Institute, Phoenix, AZ
| | - N Sanai
- Ivy Brain Tumor Center, Barrow Neurological Institute, Phoenix, AZ
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Veeraraghavan H, Jiang J, Jee J, Lebow ES, Deasy JO, Rimner A, Shaverdian N, Yu H, Gomez DR. AI Serial Image Prediction of Progression-Free Survival (PFS) for Locally Advanced Non-Small Cell Lung Cancer (LA-NSCLC) Patients Treated with Chemoradiation (CRT) and Durvalumab Consolidation. Int J Radiat Oncol Biol Phys 2023; 117:e68. [PMID: 37786001 DOI: 10.1016/j.ijrobp.2023.06.796] [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) Patient outcomes with definitive CRT for LA-NSCLC remain poor, with no imaging biomarkers to predict benefit. Hence, we developed a serial image AI model using paired planning CT (pCT) and first week cone-beam CT (CBCT) to predict PFS and measured AI model fairness defined as the bias in the classification with respect to gender as a protected attribute. MATERIALS/METHODS Sixty-four consecutive patients with LA-NSCLC treated with concurrent CRT to 60 Gy in 30 fractions and durvalumab consolidation were analyzed. Three prediction models were created. A previously developed AI image foundation model [1] was pre-trained with unlabeled 6,402 3D CT scans sourced from institutional and the Cancer Imaging Archive and modified to predict PFS as a binarized outcome (high PFS > 6 months and low PFS < 6 months) using pCT scans. Serial image AI model was created by adding the first week CBCT scan. The third model measured tumor growth rate (TGR) as relative change in tumor and nodal volume from pCT to CBCT derived using a different published AI model [2]. Association with PFS using univariable and multivariable Cox regression after adjusting for age, gender, planning tumor volume, and smoking status were measured using TGR and the two AI model predictions using a cutoff of > 50% probability for low PFS. AI model fairness metrics area under receiver operating curve (AUROC), precision, sensitivity, and specificity were computed. RESULTS TGR was not associated with PFS on univariate (Hazard ratio [HR] of 1.515, 95% confidence interval [CI] of 0.32 to 7.26, p = 0.60) or multivariate analysis (HR: 1.58, 95% CI: 0.32 to 7.80, p = 0.58) and resulted in a Harrell's C-index of 54.7%. The serial image AI model prediction was associated with PFS in both univariable (HR: 2.12, 95% CI: 1.02 to 4.40, p = 0.045) and multivariable analysis (HR 2.39, 95% CI of 1.09 to 5.25, p = 0.029), and a C-index of 62.5%. The pCT AI model was associated with PFS in univariate (HR 2.06, 95% CI of 1.06 to 4.01, p = 0.034) but not in multivariable analysis (HR 1.89, 95% CI of 0.93 to 3.87, p = 0.08), and a C-index of 59.9%. The serial image AI model reduced the parity in classification compared to pCT AI model indicating higher fairness (Table I). CONCLUSION The multi-image AI model predicted PFS with slightly higher accuracy and resulted in higher fairness than the pCT AI model. These results underscore the potential for incorporating multi-imaging biomarkers to predict treatment response.
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Affiliation(s)
- H Veeraraghavan
- Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, NY
| | - J Jiang
- Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, NY
| | - J Jee
- Memorial Sloan Kettering Cancer Center, New York, NY
| | - E S Lebow
- Department of Radiation Oncology, Memorial Sloan Kettering Cancer Center, New York, NY
| | - J O Deasy
- Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, NY
| | - A Rimner
- Department of Radiation Oncology, Memorial Sloan Kettering Cancer Center, New York, NY
| | - N Shaverdian
- Department of Radiation Oncology, Memorial Sloan Kettering Cancer Center, New York, NY
| | - H Yu
- Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY
| | - D R Gomez
- Department of Radiation Oncology, Memorial Sloan Kettering Cancer Center, New York, NY
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Wu X, Wu F, Jiang J, Yang L, He WW, Li N, Zhang K, Chen L, Ren SF, Wu J. [Comparison of long-term clinical outcomes between transvaginal mesh and pelvic floor reconstruction with native tissue repair in the treatment of advanced pelvic organ prolapse]. Zhonghua Fu Chan Ke Za Zhi 2023; 58:595-602. [PMID: 37599257 DOI: 10.3760/cma.j.cn112141-20230316-00123] [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 study the long-term clinical effect of transvaginal mesh (TVM) and pelvic floor reconstruction with native tissue repair (NTR) in the treatment of advanced pelvic organ prolapse (POP). Methods: Totally 207 patients with advanced POP who were treated in Hunan Provincial Maternal and Child Health Care Hospital from Jan. 2016 to Sep. 2019 were enrolled. The patient's pelvic organ prolapse quantification were all at degree Ⅲ or above, and they all complained for different degree of symptoms. They were divided into two groups according to the different surgical methods, TVM group and NTR group. In TVM group, the mesh was implanted through the vagina for pelvic floor reconstruction, while in NTR group, the traditional transvaginal hysterectomy combined with uterosacral ligament suspension and anterior and posterior wall repair, as well as perineal body repair were performed. The median follow-up time was 60 months, during the follow up time, 164 cases (79.2%, 164/207) had completed follow-up, including 76 cases in TVM group and 88 cases in NTR group. The perioperative data and complication rates of the two groups were compared, and the subjective and objective outcomes of the two groups at 1, 3 and 5 years were observed, respectively. The objective efficacy was evaluated by three composite criteria, namely: (1) the distance from the farthest end of the prolapse of the anterior and posterior wall of the vagina to the hymen is ≤0 cm, and the descending distance of the top is ≤1/2 of the total length of the vagina; (2) determine the disappearance of relevant POP symptoms according to "Do you often see or feel vaginal mass prolapse?"; (3) no further operation or pessary treatment was performed due to prolapse. If the above three criteria were met at the same time, the operation is successful; otherwise, it was recurrence. The subjective efficacy was evaluated by the pelvic floor distress inventory-short form 20 (PFDI-20) and pelvic floor impact questionnaire-short form 7 (PFIQ-7). Results: The median follow-up time of the two groups was 60 months (range: 41-82 months). Five years after the operation, the subjective and objective cure rates of TVM group were 89.5% (68/76) and 94.7% (72/76), respectively. The subjective and objective cure rates in NTR group were 80.7% (71/88) and 85.2% (75/88), respectively. There were significant differences in the subjective and objective cure rates between the two groups (χ2=9.869, P=0.002; χ2=3.969, P=0.046). The recurrence rate of TVM group was 5.3% (4/76), and that of NTR group was 14.8% (13/88). There was a significant difference between the two groups (P=0.046). The postoperative PFDI-20 and PFIQ-7 scores of the two groups were significantly lower than those before surgery, and there were significant differences of the two groups before and after surgery (all P<0.05). Postoperative mesh exposure in TVM group was 1.3% (1/76). Conclusions: The long-term outcomes between the two groups show that the subjective and objective outcomes of pelvic floor reconstruction in TVM group are significantly higher than those in NTR group, and the recurrence rate is significantly lower than that in NTR group. TVM has certain advantages in the treatment of advanced POP.
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Affiliation(s)
- X Wu
- Department of Gynecology, Hunan Provincial Maternal and Child Health Care Hospital, Changsha 410008, China
| | - F Wu
- Department of Gynecology, Hunan Provincial Maternal and Child Health Care Hospital, Changsha 410008, China
| | - J Jiang
- Department of Gynecology, Hunan Provincial Maternal and Child Health Care Hospital, Changsha 410008, China
| | - L Yang
- Department of Gynecology, Hunan Provincial Maternal and Child Health Care Hospital, Changsha 410008, China
| | - W W He
- Department of Gynecology, Hunan Provincial Maternal and Child Health Care Hospital, Changsha 410008, China
| | - N Li
- Department of Gynecology, Hunan Provincial Maternal and Child Health Care Hospital, Changsha 410008, China
| | - K Zhang
- Department of Gynecology, Hunan Provincial Maternal and Child Health Care Hospital, Changsha 410008, China
| | - L Chen
- Department of Gynecology, Hunan Provincial Maternal and Child Health Care Hospital, Changsha 410008, China
| | - S F Ren
- Department of Gynecology, Hunan Provincial Maternal and Child Health Care Hospital, Changsha 410008, China
| | - J Wu
- Department of Gynecology, Hunan Provincial Maternal and Child Health Care Hospital, Changsha 410008, China
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Tang HL, Jiang J, Yu WN, Zhao LL, Fan Q, Wang FY, Pan XH. [A clustered epidemic investigation of non-marital non-commercial heterosexual contact of HIV in Zhejiang Province]. Zhonghua Liu Xing Bing Xue Za Zhi 2023; 44:1270-1275. [PMID: 37661620 DOI: 10.3760/cma.j.cn112338-20230203-00056] [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 identify the transmission relationship between HIV infection cases the non-marital non-commercial heterosexual contact in Zhejiang Province. Methods: When HIV positive was informed during January 2020 to January 2022, the staff conducted an epidemiological investigation to collect cases information on sociodemographic characteristics, mobility information, past HIV testing history, high-risk sexual behaviors, sexual partners, and etcetera. At the same time, 6-8 ml of blood from the new diagnosis of people infected with HIV before antiviral treatment was collected to separate the bleeding plasma. pol gene was amplified by nucleic acid extraction and PCR, sequenced by Sequencer 5.0 software, and Cytoscape 3.6.0 software was used to draw HIV molecular transmission network. Results: From January 2020 to January 2022, 88 HIV infected individuals were found in Pujiang County, of which 74 were transmitted through heterosexual transmission, of which 31 were infected through non-marital non-commercial heterosexual contact. Preliminary case studies have found that three female cases have engaged in unprotected non-marital non-commercial heterosexual contact with one male case. Among the 4 infected individuals, 2 of their spouses tested positive for HIV antibodies. Molecular transmission network monitoring was carried out on 65 newly diagnosed cases of heterosexual transmission with acquired sequences, forming 9 transmission clusters. The largest cluster contained 10 cases. A total of 11 HIV-infected individuals were involved in this HIV cluster epidemic. They were 3 males and 8 females, all over 50 years old and were farmers or rural housewives. They were traced to 7 sexual partners (6 negatives of HIV, 1 undetected). Among the 18 respondents' sexual social network relationships, there were 6 couples, 8 permanent partners, and 3 temporary partners. Among 11 HIV infected individuals, there were 9 cases of non-marital non-commercial heterosexual transmission and 2 cases of intramarital transmission. The epidemiological association between 7 non-married non-commercial heterosexual partners and case 2 (56-year-old male farmer), 3 cases confirmed by epidemiological investigation and molecular transmission cluster results, 3 cases confirmed by molecular transmission cluster and epidemiological investigation results, and 1 case confirmed by epidemiological investigation results. Conclusions: The transmission mode of this cluster epidemic was to spread HIV through heterosexual sex with a male case as the core, then cause the transmission within marriage and between fixed sexual partners. The combination of epidemiological investigation and molecular transmission network traceability survey supports the conclusion of this study.
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Affiliation(s)
- H L Tang
- Jinhua Center for Disease Control and Prevention, Jinhua 321002, China Zhejiang Association of STD/AIDS Prevention and Control, Hangzhou 310051, China
| | - J Jiang
- Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou 310051, China
| | - W N Yu
- Pujiang County Center for Disease Control and Prevention of Zhejiang Province, Pujiang 322200, China
| | - L L Zhao
- Pujiang County Center for Disease Control and Prevention of Zhejiang Province, Pujiang 322200, China
| | - Q Fan
- Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou 310051, China
| | - F Y Wang
- Jinhua Center for Disease Control and Prevention, Jinhua 321002, China Zhejiang Association of STD/AIDS Prevention and Control, Hangzhou 310051, China
| | - X H Pan
- Zhejiang Association of STD/AIDS Prevention and Control, Hangzhou 310051, China Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou 310051, China
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Chen P, Jiang J, Zhang S, Wang X, Guo X, Li F. Enzymatic response and antibiotic resistance gene regulation by microbial fuel cells to resist sulfamethoxazole. Chemosphere 2023; 325:138410. [PMID: 36925019 DOI: 10.1016/j.chemosphere.2023.138410] [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] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/11/2022] [Revised: 01/28/2023] [Accepted: 03/13/2023] [Indexed: 06/18/2023]
Abstract
Microbial fuel cells (MFCs) are a promising and sustainable technology which can generate electricity and treat antibiotic wastewater simultaneously. However, the antibiotic resistance genes (ARGs) induced by antibiotics in MFCs increase risks to ecosystems and human health. In this study, the activities of enzymes and regulation genes related to ARGs in MFCs spiked with sulfamethoxazole (SMX) were evaluated to explore the induction mechanism of ARGs. Under lower doses of SMX (10 mg/L and 20 mg/L SMX in this study), microorganisms tend to up regulate catalase and RpoS regulon to induce sul1, sul3 and intI1. The microorganisms exposed to higher doses of SMX (30 mg/L and 40 mg/L SMX in this study) tend to up regulate superoxide dismutase and SOS response to generate sul2 and sulA. Moreover, the exposure concentrations of SMX had no significant effect on the electricity production of MFCs. This work suggested that the ARGs in MFCs might be inhibited by affecting enzymatic activities and regulatory genes according to the antibiotic concentration without affecting the electricity production.
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Affiliation(s)
- Ping Chen
- Key Laboratory of Environmental Remediation and Pollution Control, College of Environmental Science and Engineering, Nankai University, Tianjin, 300350, China; Key Laboratory of Pollution Processes and Environmental Criteria, Ministry of Education, Tianjin, 300350, China
| | - Jiwei Jiang
- Key Laboratory of Environmental Remediation and Pollution Control, College of Environmental Science and Engineering, Nankai University, Tianjin, 300350, China; Key Laboratory of Pollution Processes and Environmental Criteria, Ministry of Education, Tianjin, 300350, China
| | - Shixuan Zhang
- Key Laboratory of Environmental Remediation and Pollution Control, College of Environmental Science and Engineering, Nankai University, Tianjin, 300350, China; Key Laboratory of Pollution Processes and Environmental Criteria, Ministry of Education, Tianjin, 300350, China
| | - Xinyu Wang
- Key Laboratory of Environmental Remediation and Pollution Control, College of Environmental Science and Engineering, Nankai University, Tianjin, 300350, China; Key Laboratory of Pollution Processes and Environmental Criteria, Ministry of Education, Tianjin, 300350, China; Department of Environmental Engineering, School of Resource and Civil Engineering, Northeastern University, Shenyang, 110819, China
| | - Xiaoyan Guo
- Key Laboratory of Environmental Remediation and Pollution Control, College of Environmental Science and Engineering, Nankai University, Tianjin, 300350, China; Key Laboratory of Pollution Processes and Environmental Criteria, Ministry of Education, Tianjin, 300350, China
| | - Fengxiang Li
- Key Laboratory of Environmental Remediation and Pollution Control, College of Environmental Science and Engineering, Nankai University, Tianjin, 300350, China; Key Laboratory of Pollution Processes and Environmental Criteria, Ministry of Education, Tianjin, 300350, China.
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Xie XJ, Chen JY, Jiang J, Duan H, Wu Y, Zhang XW, Yang SJ, Zhao W, Shen SS, Wu L, He B, Ding YY, Luo H, Liu SY, Han D. [Development and validation of prognostic nomogram for malignant pleural mesothelioma]. Zhonghua Zhong Liu Za Zhi 2023; 45:415-423. [PMID: 37188627 DOI: 10.3760/cma.j.cn12152-20211124-00871] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Subscribe] [Scholar Register] [Indexed: 05/17/2023]
Abstract
Objective: To development the prognostic nomogram for malignant pleural mesothelioma (MPM). Methods: Two hundred and ten patients pathologically confirmed as MPM were enrolled in this retrospective study from 2007 to 2020 in the People's Hospital of Chuxiong Yi Autonomous Prefecture, the First and Third Affiliated Hospital of Kunming Medical University, and divided into training (n=112) and test (n=98) sets according to the admission time. The observation factors included demography, symptoms, history, clinical score and stage, blood cell and biochemistry, tumor markers, pathology and treatment. The Cox proportional risk model was used to analyze the prognostic factors of 112 patients in the training set. According to the results of multivariate Cox regression analysis, the prognostic prediction nomogram was established. C-Index and calibration curve were used to evaluate the model's discrimination and consistency in raining and test sets, respectively. Patients were stratified according to the median risk score of nomogram in the training set. Log rank test was performed to compare the survival differences between the high and low risk groups in the two sets. Results: The median overall survival (OS) of 210 MPM patients was 384 days (IQR=472 days), and the 6-month, 1-year, 2-year, and 3-year survival rates were 75.7%, 52.6%, 19.7%, and 13.0%, respectively. Cox multivariate regression analysis showed that residence (HR=2.127, 95% CI: 1.154-3.920), serum albumin (HR=1.583, 95% CI: 1.017-2.464), clinical stage (stage Ⅳ: HR=3.073, 95% CI: 1.366-6.910) and the chemotherapy (HR=0.476, 95% CI: 0.292-0.777) were independent prognostic factors for MPM patients. The C-index of the nomogram established based on the results of Cox multivariate regression analysis in the training and test sets were 0.662 and 0.613, respectively. Calibration curves for both the training and test sets showed moderate consistency between the predicted and actual survival probabilities of MPM patients at 6 months, 1 year, and 2 years. The low-risk group had better outcomes than the high-risk group in both training (P=0.001) and test (P=0.003) sets. Conclusion: The survival prediction nomogram established based on routine clinical indicators of MPM patients provides a reliable tool for prognostic prediction and risk stratification.
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Affiliation(s)
- X J Xie
- Department of Medical Imaging, the First Affiliated Hospital of Kunming Medical University, Kunming 650032, China
| | - J Y Chen
- Department of Radiology, the Third Affiliated Hospital of Kunming Medical University, Kunming 650106, China
| | - J Jiang
- Department of Medical Imaging, the First Affiliated Hospital of Kunming Medical University, Kunming 650032, China
| | - H Duan
- Department of Medical Imaging, the First Affiliated Hospital of Kunming Medical University, Kunming 650032, China
| | - Y Wu
- Department of Radiology, Chuxiong People's Hospital, Chuxiong 675099, China
| | - X W Zhang
- Department of Radiology, Chuxiong People's Hospital, Chuxiong 675099, China
| | - S J Yang
- Department of Thoracic Surgery, Chuxiong People's Hospital, Chuxiong 675099, China
| | - W Zhao
- Department of Medical Imaging, the First Affiliated Hospital of Kunming Medical University, Kunming 650032, China
| | - S S Shen
- Department of Medical Imaging, the First Affiliated Hospital of Kunming Medical University, Kunming 650032, China
| | - L Wu
- Department of Medical Imaging, the First Affiliated Hospital of Kunming Medical University, Kunming 650032, China
| | - B He
- Department of Medical Imaging, the First Affiliated Hospital of Kunming Medical University, Kunming 650032, China
| | - Y Y Ding
- Department of Radiology, the Third Affiliated Hospital of Kunming Medical University, Kunming 650106, China
| | - H Luo
- Deputy President's Office, Chuxiong People's Hospital, Chuxiong 675099, China
| | - S Y Liu
- GE Healthcare (China), Beijing 100176, China
| | - D Han
- Department of Medical Imaging, the First Affiliated Hospital of Kunming Medical University, Kunming 650032, China
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Chen H, Lin M, Jiang J, Liu M, Lai Z, Luo Y, Ye H, Chen H, Yang Z. 25P Furmonertinib plus icotinib for first-line treatment of EGFR-mutated non-small cell lung cancer. J Thorac Oncol 2023. [DOI: 10.1016/s1556-0864(23)00279-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/03/2023]
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Jiang J, Jain P, Adji A, Barua S, Hayward C. Afterload and LV Function, but Not Circuit Flow, Determine LV Filling Pressure During VA-ECMO. J Heart Lung Transplant 2023. [DOI: 10.1016/j.healun.2023.02.1529] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/05/2023] Open
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Jiang J, Jain P, Adji A, Barua S, Hayward C. Determinants of LV Filling Pressure During ECPR with VA-ECMO: A Mock Circulatory Loop Study. J Heart Lung Transplant 2023. [DOI: 10.1016/j.healun.2023.02.738] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/05/2023] Open
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Zhang H, Jiang J, He X, Zhou Q. Circ_0002111/miR-134-5p/FSTL1 signal axis regulates tumor progression and glycolytic metabolism in papillary thyroid carcinoma cells. J Endocrinol Invest 2023; 46:713-725. [PMID: 36227499 DOI: 10.1007/s40618-022-01921-4] [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] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/30/2022] [Accepted: 09/11/2022] [Indexed: 10/17/2022]
Abstract
BACKGROUND Circular RNAs (circRNAs) have essential roles in the malignant progression of papillary thyroid carcinoma (PTC). Circ_0002111 was reported to facilitate cell proliferation and invasion abilities in PTC. This study was performed to explore the regulatory mechanism of circ_0002111 in PTC progression. METHODS Reverse transcription-quantitative polymerase chain reaction (RT-qPCR) was used for the level detection of circ_0002111, microRNA-134-5p (miR-134-5p) and Follistatin Like 1 (FSTL1). Cell proliferation was assessed by 3-(4, 5-dimethylthiazol-2-y1)-2, 5-diphenyl tetrazolium bromide (MTT) assay, EdU assay and colony formation assay. Cell migration ability was determined by transwell assay. Glycolysis was analyzed by extracellular acidification rate (ECAR), oxygen consumption rate (OCR), glucose consumption and lactate production. The protein quantification was performed through western blot. Xenograft tumor assay was used for the functional analysis of circ_0002111 in vivo. The target interaction was confirmed by dual-luciferase reporter assay and RNA pull-down assay. RESULTS The significant upregulation of circ_0002111 was detected in PTC samples and cells. PTC cell proliferation, migration and glycolytic metabolism were suppressed after circ_0002111 downregulation. PTC tumorigenesis in vivo was also inhibited by circ_0002111 knockdown. In addition, circ_0002111 could target miR-134-5p and si-circ_0002111#1-induced inhibition of PTC progression was relieved by miR-134-5p expression downregulation. Furthermore, FSTL1 was a target gene for miR-134-5p and miR-134-5p served as a tumor repressor in PTC by targeting FSTL1. Moreover, circ_0002111 could increase the FSTL1 level via sponging miR-134-5p. CONCLUSION All results indicated that circ_0002111 promoted the malignant behaviors of PTC cells partly by regulating the miR-134-5p/FSTL1 molecular network.
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Affiliation(s)
- H Zhang
- Department of Ultrasound, The second affiliated hospital of Xi'an Jiaotong University, NO. 157 West Fifth Road, Xi'an, 710004, Shaanxi, China
| | - J Jiang
- Department of Ultrasound, The second affiliated hospital of Xi'an Jiaotong University, NO. 157 West Fifth Road, Xi'an, 710004, Shaanxi, China
| | - X He
- Department of Ultrasound, The second affiliated hospital of Xi'an Jiaotong University, NO. 157 West Fifth Road, Xi'an, 710004, Shaanxi, China
| | - Q Zhou
- Department of Ultrasound, The second affiliated hospital of Xi'an Jiaotong University, NO. 157 West Fifth Road, Xi'an, 710004, Shaanxi, China.
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Wang DY, Jiang J, Zhao KK. [HBV infection: antiviral therapy for viral replication]. Zhonghua Gan Zang Bing Za Zhi 2023; 31:316-318. [PMID: 37137860 DOI: 10.3760/cma.j.cn501113-20220328-00147] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Key Words] [Subscribe] [Scholar Register] [Indexed: 05/05/2023]
Affiliation(s)
- D Y Wang
- Department of Infectious Diseases, the First Affiliated Hospital of Ningbo University, Ningbo 315020, China
| | - J Jiang
- Department of Infectious Diseases, the First Affiliated Hospital of Ningbo University, Ningbo 315020, China
| | - K K Zhao
- Department of Infectious Diseases, the First Affiliated Hospital of Ningbo University, Ningbo 315020, China
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Mu N, Rezaeitaleshmahalleh M, Lyu Z, Wang M, Tang J, Strother CM, Gemmete JJ, Pandey AS, Jiang J. Can we explain machine learning-based prediction for rupture status assessments of intracranial aneurysms? Biomed Phys Eng Express 2023; 9:037001. [PMID: 36626819 PMCID: PMC9999353 DOI: 10.1088/2057-1976/acb1b3] [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] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2022] [Revised: 01/04/2023] [Accepted: 01/10/2023] [Indexed: 01/11/2023]
Abstract
Although applying machine learning (ML) algorithms to rupture status assessment of intracranial aneurysms (IA) has yielded promising results, the opaqueness of some ML methods has limited their clinical translation. We presented the first explainability comparison of six commonly used ML algorithms: multivariate logistic regression (LR), support vector machine (SVM), random forest (RF), extreme gradient boosting (XGBoost), multi-layer perceptron neural network (MLPNN), and Bayesian additive regression trees (BART). A total of 112 IAs with known rupture status were selected for this study. The ML-based classification used two anatomical features, nine hemodynamic parameters, and thirteen morphologic variables. We utilized permutation feature importance, local interpretable model-agnostic explanations (LIME), and SHapley Additive exPlanations (SHAP) algorithms to explain and analyze 6 Ml algorithms. All models performed comparably: LR area under the curve (AUC) was 0.71; SVM AUC was 0.76; RF AUC was 0.73; XGBoost AUC was 0.78; MLPNN AUC was 0.73; BART AUC was 0.73. Our interpretability analysis demonstrated consistent results across all the methods; i.e., the utility of the top 12 features was broadly consistent. Furthermore, contributions of 9 important features (aneurysm area, aneurysm location, aneurysm type, wall shear stress maximum during systole, ostium area, the size ratio between aneurysm width, (parent) vessel diameter, one standard deviation among time-averaged low shear area, and one standard deviation of temporally averaged low shear area less than 0.4 Pa) were nearly the same. This research suggested that ML classifiers can provide explainable predictions consistent with general domain knowledge concerning IA rupture. With the improved understanding of ML algorithms, clinicians' trust in ML algorithms will be enhanced, accelerating their clinical translation.
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Affiliation(s)
- N Mu
- Biomedical Engineering, Michigan Technological University, Houghton, MI, United States of America
| | - M Rezaeitaleshmahalleh
- Biomedical Engineering, Michigan Technological University, Houghton, MI, United States of America
| | - Z Lyu
- Biomedical Engineering, Michigan Technological University, Houghton, MI, United States of America
| | - M Wang
- Department of Management Science and Statistics, The University of Texas at San Antonio, San Antonino, TX, United States of America
| | - J Tang
- Department of Health Administration and Policy, George Mason University, Fairfax, VA, United States of America
| | - C M Strother
- Department of Radiology, University of Wisconsin, Madison, WI, United States of America
| | - J J Gemmete
- Department of Radiology, University of Michigan, Ann Arbor, MI, United States of America
| | - A S Pandey
- Department of Neurosurgery, University of Michigan, Ann Arbor, MI, United States of America
| | - J Jiang
- Biomedical Engineering, Michigan Technological University, Houghton, MI, United States of America
- Center for Biocomputing and Digital Health, Health Research Institute and Institute of Computing and Cybernetics, Michigan Technological University, Houghton, MI, United States of America
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Jiang J, Liang P, Li A, Xue Q, Yu H, You Z. Synthesis, Crystal Structures and Urease Inhibition of Zinc(II) and Copper(II) Complexes Derived from 2-Amino-N′-(1-(Pyridin-2-yl) Ethylidene)Benzohydrazide. J STRUCT CHEM+ 2023. [DOI: 10.1134/s0022476623030034] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/08/2023]
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Pan S, Wang F, Jiang J, Lin Z, Chen Z, Cao T, Yang L. Chimeric Antigen Receptor-Natural Killer Cells: A New Breakthrough in the Treatment of Solid Tumours. Clin Oncol (R Coll Radiol) 2023; 35:153-162. [PMID: 36437159 DOI: 10.1016/j.clon.2022.10.019] [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] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2022] [Revised: 09/30/2022] [Accepted: 10/26/2022] [Indexed: 11/25/2022]
Abstract
Natural killer (NK) cells can quickly and directly eradicate tumour cells without recognising tumour-specific antigens. NK cells also participate in immune surveillance, which arouses great interest in the development of novel cancer therapies. The chimeric antigen receptor (CAR) family is composed of receptor proteins that give immune cells extra capabilities to target specific antigen proteins or enhance their killing effects. CAR-T cell therapy has achieved initial success in haematological tumours, but is prone to adverse reactions, especially with cytokine release syndrome in clinical applications. Currently, CAR-NK cell therapy has been shown to successfully kill haematological tumour cells with allogeneic NK cells in clinical trials without adverse reactions, proving its potential to become an off-the-shelf product with broad clinical application prospects. Meanwhile, clinical trials of CAR-NK cells for solid tumours are currently underway. Here we will focus on the latest advances in CAR-NK cells, including preclinical and clinical trials in solid tumours, the advantages and challenges of CAR-NK cell therapy and new strategies to improve the safety and efficacy of CAR-NK cell therapy.
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Affiliation(s)
- S Pan
- Cancer Center, Department of Medical Oncology, Zhejiang Provincial People's Hospital (Affiliated People's Hospital, Hangzhou Medical College), Hangzhou, Zhejiang, China; The Second Clinical Medical College, Zhejiang Chinese Medical University, Hangzhou, Zhejiang, China
| | - F Wang
- Department of Orthopedic Surgery, The Fourth Affiliated Hospital, International Institutes of Medicine, Zhejiang University School of Medicine
| | - J Jiang
- Cancer Center, Department of Medical Oncology, Zhejiang Provincial People's Hospital (Affiliated People's Hospital, Hangzhou Medical College), Hangzhou, Zhejiang, China
| | - Z Lin
- Cancer Center, Department of Medical Oncology, Zhejiang Provincial People's Hospital (Affiliated People's Hospital, Hangzhou Medical College), Hangzhou, Zhejiang, China
| | - Z Chen
- Cancer Center, Department of Medical Oncology, Zhejiang Provincial People's Hospital (Affiliated People's Hospital, Hangzhou Medical College), Hangzhou, Zhejiang, China.
| | - T Cao
- Wenzhou Medical University, Wenzhou, Zhejiang, China.
| | - L Yang
- Cancer Center, Department of Medical Oncology, Zhejiang Provincial People's Hospital (Affiliated People's Hospital, Hangzhou Medical College), Hangzhou, Zhejiang, China; The Second Clinical Medical College, Zhejiang Chinese Medical University, Hangzhou, Zhejiang, China.
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36
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Du J, Jiang J, Wang H, Zuo Y, Sun J. Effect of clay supplementation on growth performance of broiler chickens: a systematic review and meta-analysis. Br Poult Sci 2023:1-11. [PMID: 36607319 DOI: 10.1080/00071668.2022.2160625] [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] [Subscribe] [Scholar Register] [Indexed: 01/07/2023]
Abstract
1. This review assessed the effect of dietary clay supplementation as a drug and toxin adsorbent on broiler growth performance as a meta-analysis.2. A total of 33 eligible studies were included in the present study after identification and evaluation from online databases. Standardised mean differences (SMD) with corresponding 95% confidence intervals were computed with a fixed-effects model.3. The results indicated that clay supplementation significantly improved broiler daily gain (P < 0.001) and feed conversion ratio (P < 0.001), but did not affect feed intake (P = 0.954). Results of subgroup analysis showed that zeolite clay had the most stable medium improvement effect on FCR, while kaolin had a large effect. In addition, male broilers and Cobb or Ross broilers were more sensitive to the addition of clay, and the best supplemental levels, in general, were 10 g/kg to 30 g/kg.4. Meta-regression analysis showed that clay supplemental level and sex of broilers may be important factors in the effect of clay on ADG and FCR of broilers, respectively. The sensitivity analysis showed high stability of the results and no significant publication bias was found with funnel plot analysis and Egger's or Begg's test (P > 0.05).5. In conclusion, an appropriate addition level is a prerequisite for effective clay application. Kaolin and zeolite clays seem to be more suitable for enhancing broiler growth performance, and the value of clay is amplified in specific broiler breeds.
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Affiliation(s)
- J Du
- Research and Development Centre, Research Centre of Nanjing Well Pharmaceutical Group Co. LTD, Nanjing, China
| | - J Jiang
- College of Animal Science and Technology, Northeast Agricultural University, Harbin, China
| | - H Wang
- College of Animal Science and Technology, Northeast Agricultural University, Harbin, China
| | - Y Zuo
- College of Veterinary Medicine, Nanjing Agricultural University, Nanjing, China
| | - J Sun
- College of Animal Science and Technology, Northeast Agricultural University, Harbin, China
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Lin Z, Wang H, Song J, Xu G, Lu F, Ma X, Xia X, Jiang J, Zou F. The role of mitochondrial fission in intervertebral disc degeneration. Osteoarthritis Cartilage 2023; 31:158-166. [PMID: 36375758 DOI: 10.1016/j.joca.2022.10.020] [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: 08/08/2022] [Revised: 10/06/2022] [Accepted: 10/31/2022] [Indexed: 11/13/2022]
Abstract
Low back pain (LBP) is an extremely common disorder and is a major cause of disability globally. Intervertebral disc degeneration (IVDD) is the main contributor to LBP. Nevertheless, the specific mechanisms underlying the pathogenesis of IVDD remain unclear. Mitochondria are highly dynamic organelles that continuously undergo fusion and fission, known as mitochondrial dynamics. Accumulating evidence has revealed that aberrantly activated mitochondrial fission leads to mitochondrial fragmentation and dysfunction, which are involved in the development and progression of IVDD. To date, research into mitochondrial dynamics in IVDD is at an early stage. The present narrative review aims to summarize the most recent findings about the role of mitochondrial fission in the pathogenesis of IVDD.
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Affiliation(s)
- Z Lin
- Department of Orthopedics, Huashan Hospital, Fudan University, Shanghai 200040, China.
| | - H Wang
- Department of Orthopedics, Huashan Hospital, Fudan University, Shanghai 200040, China.
| | - J Song
- Department of Orthopedics, Huashan Hospital, Fudan University, Shanghai 200040, China.
| | - G Xu
- Department of Orthopedics, Huashan Hospital, Fudan University, Shanghai 200040, China.
| | - F Lu
- Department of Orthopedics, Huashan Hospital, Fudan University, Shanghai 200040, China.
| | - X Ma
- Department of Orthopedics, Huashan Hospital, Fudan University, Shanghai 200040, China.
| | - X Xia
- Department of Orthopedics, Huashan Hospital, Fudan University, Shanghai 200040, China.
| | - J Jiang
- Department of Orthopedics, Huashan Hospital, Fudan University, Shanghai 200040, China.
| | - F Zou
- Department of Orthopedics, Huashan Hospital, Fudan University, Shanghai 200040, China.
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38
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Li S, Jiang J, Ho SH, Zhang S, Zeng W, Li F. Sustainable conversion of antibiotic wastewater using microbial fuel cells: Energy harvesting and resistance mechanism analysis. Chemosphere 2023; 313:137584. [PMID: 36529164 DOI: 10.1016/j.chemosphere.2022.137584] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [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: 08/25/2022] [Revised: 12/13/2022] [Accepted: 12/14/2022] [Indexed: 06/17/2023]
Abstract
In this study, tetracycline (TC) can be degraded in microbial fuel cells (MFCs) rapidly and efficiently for the synergistic effect of microbial metabolism and electrical stimulation. Different TC concentrations had different effects on the bioelectric performance of MFCs. Among them, 10 mg/L TC promoted the bioelectric properties of MFCs, the maximum power density reached 1744.4 ± 74.9 mW/cm2. In addition, we demonstrated that Geobacter and Chryseobacterium were the dominant species in the anode biofilm, while Azoarcus and Pseudomonas were the prominent species in the effluent, and the initial TC concentration affected the microbial community composition. Furthermore, the addition of TC increased the relative abundance of aadA3, sul1, adeF, cmlA, and tetC in reactors, indicating that a single antibiotic could promote the expression of self-related resistance as well as the expression of other ARGs. Moreover, the presence of TC can increase the relative content of mobile genetic elements (MGEs) and greatly increase the risk of antibiotic resistance genes (ARGs) spreading. Meanwhile, network analysis revealed that some microorganisms (such as Acidovorax caeni, Geobacter soil, and Pseudomonas thermotolerans) and MGEs may be potential hosts for multiple ARGs.
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Affiliation(s)
- Shengnan Li
- College of Environmental Science and Engineering, Nankai University, 38 Tongyan Road, Jinnan District, Tianjin, 300350, China; State Key Laboratory of Urban Water Resource and Environment, School of Environment, Harbin Institute of Technology, Harbin, Heilongjiang Province, 150090, China
| | - Jiwei Jiang
- College of Environmental Science and Engineering, Nankai University, 38 Tongyan Road, Jinnan District, Tianjin, 300350, China
| | - Shih-Hsin Ho
- State Key Laboratory of Urban Water Resource and Environment, School of Environment, Harbin Institute of Technology, Harbin, Heilongjiang Province, 150090, China
| | - Shixuan Zhang
- College of Environmental Science and Engineering, Nankai University, 38 Tongyan Road, Jinnan District, Tianjin, 300350, China
| | - Wenlu Zeng
- College of Environmental Science and Engineering, Nankai University, 38 Tongyan Road, Jinnan District, Tianjin, 300350, China
| | - Fengxiang Li
- College of Environmental Science and Engineering, Nankai University, 38 Tongyan Road, Jinnan District, Tianjin, 300350, China.
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Abe K, Hayato Y, Hiraide K, Ieki K, Ikeda M, Kameda J, Kanemura Y, Kaneshima R, Kashiwagi Y, Kataoka Y, Miki S, Mine S, Miura M, Moriyama S, Nakano Y, Nakahata M, Nakayama S, Noguchi Y, Okamoto K, Sato K, Sekiya H, Shiba H, Shimizu K, Shiozawa M, Sonoda Y, Suzuki Y, Takeda A, Takemoto Y, Takenaka A, Tanaka H, Watanabe S, Yano T, Han S, Kajita T, Okumura K, Tashiro T, Tomiya T, Wang X, Xia J, Yoshida S, Megias GD, Fernandez P, Labarga L, Ospina N, Zaldivar B, Pointon BW, Kearns E, Raaf JL, Wan L, Wester T, Bian J, Griskevich NJ, Kropp WR, Locke S, Smy MB, Sobel HW, Takhistov V, Yankelevich A, Hill J, Park RG, Bodur B, Scholberg K, Walter CW, Bernard L, Coffani A, Drapier O, El Hedri S, Giampaolo A, Mueller TA, Santos AD, Paganini P, Quilain B, Ishizuka T, Nakamura T, Jang JS, Learned JG, Choi K, Cao S, Anthony LHV, Martin D, Scott M, Sztuc AA, Uchida Y, Berardi V, Catanesi MG, Radicioni E, Calabria NF, Machado LN, De Rosa G, Collazuol G, Iacob F, Lamoureux M, Mattiazzi M, Ludovici L, Gonin M, Pronost G, Fujisawa C, Maekawa Y, Nishimura Y, Friend M, Hasegawa T, Ishida T, Kobayashi T, Jakkapu M, Matsubara T, Nakadaira T, Nakamura K, Oyama Y, Sakashita K, Sekiguchi T, Tsukamoto T, Boschi T, Di Lodovico F, Gao J, Goldsack A, Katori T, Migenda J, Taani M, Zsoldos S, Kotsar Y, Ozaki H, Suzuki AT, Takeuchi Y, Bronner C, Feng J, Kikawa T, Mori M, Nakaya T, Wendell RA, Yasutome K, Jenkins SJ, McCauley N, Mehta P, Tsui KM, Fukuda Y, Itow Y, Menjo H, Ninomiya K, Lagoda J, Lakshmi SM, Mandal M, Mijakowski P, Prabhu YS, Zalipska J, Jia M, Jiang J, Jung CK, Wilking MJ, Yanagisawa C, Harada M, Ishino H, Ito S, Kitagawa H, Koshio Y, Nakanishi F, Sakai S, Barr G, Barrow D, Cook L, Samani S, Wark D, Nova F, Yang JY, Malek M, McElwee JM, Stone O, Thiesse MD, Thompson LF, Okazawa H, Kim SB, Seo JW, Yu I, Ichikawa AK, Nakamura KD, Tairafune S, Nishijima K, Iwamoto K, Nakagiri K, Nakajima Y, Taniuchi N, Yokoyama M, Martens K, de Perio P, Vagins MR, Kuze M, Izumiyama S, Inomoto M, Ishitsuka M, Ito H, Kinoshita T, Matsumoto R, Ommura Y, Shigeta N, Shinoki M, Suganuma T, Yamauchi K, Martin JF, Tanaka HA, Towstego T, Akutsu R, Gousy-Leblanc V, Hartz M, Konaka A, Prouse NW, Chen S, Xu BD, Zhang B, Posiadala-Zezula M, Hadley D, Nicholson M, O'Flaherty M, Richards B, Ali A, Jamieson B, Marti L, Minamino A, Pintaudi G, Sano S, Suzuki S, Wada K. Search for Cosmic-Ray Boosted Sub-GeV Dark Matter Using Recoil Protons at Super-Kamiokande. Phys Rev Lett 2023; 130:031802. [PMID: 36763398 DOI: 10.1103/physrevlett.130.031802] [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] [Received: 09/30/2022] [Accepted: 11/30/2022] [Indexed: 06/18/2023]
Abstract
We report a search for cosmic-ray boosted dark matter with protons using the 0.37 megaton×years data collected at Super-Kamiokande experiment during the 1996-2018 period (SKI-IV phase). We searched for an excess of proton recoils above the atmospheric neutrino background from the vicinity of the Galactic Center. No such excess is observed, and limits are calculated for two reference models of dark matter with either a constant interaction cross section or through a scalar mediator. This is the first experimental search for boosted dark matter with hadrons using directional information. The results present the most stringent limits on cosmic-ray boosted dark matter and exclude the dark matter-nucleon elastic scattering cross section between 10^{-33}cm^{2} and 10^{-27}cm^{2} for dark matter mass from 1 MeV/c^{2} to 300 MeV/c^{2}.
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Affiliation(s)
- K Abe
- Kamioka Observatory, Institute for Cosmic Ray Research, University of Tokyo, Kamioka, Gifu 506-1205, Japan
- Kavli Institute for the Physics and Mathematics of the Universe (WPI), The University of Tokyo Institutes for Advanced Study, University of Tokyo, Kashiwa, Chiba 277-8583, Japan
| | - Y Hayato
- Kamioka Observatory, Institute for Cosmic Ray Research, University of Tokyo, Kamioka, Gifu 506-1205, Japan
- Kavli Institute for the Physics and Mathematics of the Universe (WPI), The University of Tokyo Institutes for Advanced Study, University of Tokyo, Kashiwa, Chiba 277-8583, Japan
| | - K Hiraide
- Kamioka Observatory, Institute for Cosmic Ray Research, University of Tokyo, Kamioka, Gifu 506-1205, Japan
- Kavli Institute for the Physics and Mathematics of the Universe (WPI), The University of Tokyo Institutes for Advanced Study, University of Tokyo, Kashiwa, Chiba 277-8583, Japan
| | - K Ieki
- Kamioka Observatory, Institute for Cosmic Ray Research, University of Tokyo, Kamioka, Gifu 506-1205, Japan
- Kavli Institute for the Physics and Mathematics of the Universe (WPI), The University of Tokyo Institutes for Advanced Study, University of Tokyo, Kashiwa, Chiba 277-8583, Japan
| | - M Ikeda
- Kamioka Observatory, Institute for Cosmic Ray Research, University of Tokyo, Kamioka, Gifu 506-1205, Japan
- Kavli Institute for the Physics and Mathematics of the Universe (WPI), The University of Tokyo Institutes for Advanced Study, University of Tokyo, Kashiwa, Chiba 277-8583, Japan
| | - J Kameda
- Kamioka Observatory, Institute for Cosmic Ray Research, University of Tokyo, Kamioka, Gifu 506-1205, Japan
- Kavli Institute for the Physics and Mathematics of the Universe (WPI), The University of Tokyo Institutes for Advanced Study, University of Tokyo, Kashiwa, Chiba 277-8583, Japan
| | - Y Kanemura
- Kamioka Observatory, Institute for Cosmic Ray Research, University of Tokyo, Kamioka, Gifu 506-1205, Japan
| | - R Kaneshima
- Kamioka Observatory, Institute for Cosmic Ray Research, University of Tokyo, Kamioka, Gifu 506-1205, Japan
| | - Y Kashiwagi
- Kamioka Observatory, Institute for Cosmic Ray Research, University of Tokyo, Kamioka, Gifu 506-1205, Japan
| | - Y Kataoka
- Kamioka Observatory, Institute for Cosmic Ray Research, University of Tokyo, Kamioka, Gifu 506-1205, Japan
- Kavli Institute for the Physics and Mathematics of the Universe (WPI), The University of Tokyo Institutes for Advanced Study, University of Tokyo, Kashiwa, Chiba 277-8583, Japan
| | - S Miki
- Kamioka Observatory, Institute for Cosmic Ray Research, University of Tokyo, Kamioka, Gifu 506-1205, Japan
| | - S Mine
- Kamioka Observatory, Institute for Cosmic Ray Research, University of Tokyo, Kamioka, Gifu 506-1205, Japan
- Department of Physics and Astronomy, University of California, Irvine, Irvine, California 92697-4575, USA
| | - M Miura
- Kamioka Observatory, Institute for Cosmic Ray Research, University of Tokyo, Kamioka, Gifu 506-1205, Japan
- Kavli Institute for the Physics and Mathematics of the Universe (WPI), The University of Tokyo Institutes for Advanced Study, University of Tokyo, Kashiwa, Chiba 277-8583, Japan
| | - S Moriyama
- Kamioka Observatory, Institute for Cosmic Ray Research, University of Tokyo, Kamioka, Gifu 506-1205, Japan
- Kavli Institute for the Physics and Mathematics of the Universe (WPI), The University of Tokyo Institutes for Advanced Study, University of Tokyo, Kashiwa, Chiba 277-8583, Japan
| | - Y Nakano
- Kamioka Observatory, Institute for Cosmic Ray Research, University of Tokyo, Kamioka, Gifu 506-1205, Japan
| | - M Nakahata
- Kamioka Observatory, Institute for Cosmic Ray Research, University of Tokyo, Kamioka, Gifu 506-1205, Japan
- Kavli Institute for the Physics and Mathematics of the Universe (WPI), The University of Tokyo Institutes for Advanced Study, University of Tokyo, Kashiwa, Chiba 277-8583, Japan
| | - S Nakayama
- Kamioka Observatory, Institute for Cosmic Ray Research, University of Tokyo, Kamioka, Gifu 506-1205, Japan
- Kavli Institute for the Physics and Mathematics of the Universe (WPI), The University of Tokyo Institutes for Advanced Study, University of Tokyo, Kashiwa, Chiba 277-8583, Japan
| | - Y Noguchi
- Kamioka Observatory, Institute for Cosmic Ray Research, University of Tokyo, Kamioka, Gifu 506-1205, Japan
| | - K Okamoto
- Kamioka Observatory, Institute for Cosmic Ray Research, University of Tokyo, Kamioka, Gifu 506-1205, Japan
| | - K Sato
- Kamioka Observatory, Institute for Cosmic Ray Research, University of Tokyo, Kamioka, Gifu 506-1205, Japan
| | - H Sekiya
- Kamioka Observatory, Institute for Cosmic Ray Research, University of Tokyo, Kamioka, Gifu 506-1205, Japan
- Kavli Institute for the Physics and Mathematics of the Universe (WPI), The University of Tokyo Institutes for Advanced Study, University of Tokyo, Kashiwa, Chiba 277-8583, Japan
| | - H Shiba
- Kamioka Observatory, Institute for Cosmic Ray Research, University of Tokyo, Kamioka, Gifu 506-1205, Japan
| | - K Shimizu
- Kamioka Observatory, Institute for Cosmic Ray Research, University of Tokyo, Kamioka, Gifu 506-1205, Japan
| | - M Shiozawa
- Kamioka Observatory, Institute for Cosmic Ray Research, University of Tokyo, Kamioka, Gifu 506-1205, Japan
- Kavli Institute for the Physics and Mathematics of the Universe (WPI), The University of Tokyo Institutes for Advanced Study, University of Tokyo, Kashiwa, Chiba 277-8583, Japan
| | - Y Sonoda
- Kamioka Observatory, Institute for Cosmic Ray Research, University of Tokyo, Kamioka, Gifu 506-1205, Japan
| | - Y Suzuki
- Kamioka Observatory, Institute for Cosmic Ray Research, University of Tokyo, Kamioka, Gifu 506-1205, Japan
| | - A Takeda
- Kamioka Observatory, Institute for Cosmic Ray Research, University of Tokyo, Kamioka, Gifu 506-1205, Japan
- Kavli Institute for the Physics and Mathematics of the Universe (WPI), The University of Tokyo Institutes for Advanced Study, University of Tokyo, Kashiwa, Chiba 277-8583, Japan
| | - Y Takemoto
- Kamioka Observatory, Institute for Cosmic Ray Research, University of Tokyo, Kamioka, Gifu 506-1205, Japan
- Kavli Institute for the Physics and Mathematics of the Universe (WPI), The University of Tokyo Institutes for Advanced Study, University of Tokyo, Kashiwa, Chiba 277-8583, Japan
| | - A Takenaka
- Kamioka Observatory, Institute for Cosmic Ray Research, University of Tokyo, Kamioka, Gifu 506-1205, Japan
| | - H Tanaka
- Kamioka Observatory, Institute for Cosmic Ray Research, University of Tokyo, Kamioka, Gifu 506-1205, Japan
- Kavli Institute for the Physics and Mathematics of the Universe (WPI), The University of Tokyo Institutes for Advanced Study, University of Tokyo, Kashiwa, Chiba 277-8583, Japan
| | - S Watanabe
- Kamioka Observatory, Institute for Cosmic Ray Research, University of Tokyo, Kamioka, Gifu 506-1205, Japan
| | - T Yano
- Kamioka Observatory, Institute for Cosmic Ray Research, University of Tokyo, Kamioka, Gifu 506-1205, Japan
| | - S Han
- Research Center for Cosmic Neutrinos, Institute for Cosmic Ray Research, University of Tokyo, Kashiwa, Chiba 277-8582, Japan
| | - T Kajita
- Research Center for Cosmic Neutrinos, Institute for Cosmic Ray Research, University of Tokyo, Kashiwa, Chiba 277-8582, Japan
- ILANCE, CNRS-University of Tokyo International Research Laboratory, Kashiwa, Chiba 277-8582, Japan
- Kavli Institute for the Physics and Mathematics of the Universe (WPI), The University of Tokyo Institutes for Advanced Study, University of Tokyo, Kashiwa, Chiba 277-8583, Japan
| | - K Okumura
- Research Center for Cosmic Neutrinos, Institute for Cosmic Ray Research, University of Tokyo, Kashiwa, Chiba 277-8582, Japan
- Kavli Institute for the Physics and Mathematics of the Universe (WPI), The University of Tokyo Institutes for Advanced Study, University of Tokyo, Kashiwa, Chiba 277-8583, Japan
| | - T Tashiro
- Research Center for Cosmic Neutrinos, Institute for Cosmic Ray Research, University of Tokyo, Kashiwa, Chiba 277-8582, Japan
| | - T Tomiya
- Research Center for Cosmic Neutrinos, Institute for Cosmic Ray Research, University of Tokyo, Kashiwa, Chiba 277-8582, Japan
| | - X Wang
- Research Center for Cosmic Neutrinos, Institute for Cosmic Ray Research, University of Tokyo, Kashiwa, Chiba 277-8582, Japan
| | - J Xia
- Research Center for Cosmic Neutrinos, Institute for Cosmic Ray Research, University of Tokyo, Kashiwa, Chiba 277-8582, Japan
| | - S Yoshida
- Research Center for Cosmic Neutrinos, Institute for Cosmic Ray Research, University of Tokyo, Kashiwa, Chiba 277-8582, Japan
| | - G D Megias
- Institute for Cosmic Ray Research, University of Tokyo, Kashiwa, Chiba 277-8582, Japan
| | - P Fernandez
- Department of Theoretical Physics, University Autonoma Madrid, 28049 Madrid, Spain
| | - L Labarga
- Department of Theoretical Physics, University Autonoma Madrid, 28049 Madrid, Spain
| | - N Ospina
- Department of Theoretical Physics, University Autonoma Madrid, 28049 Madrid, Spain
| | - B Zaldivar
- Department of Theoretical Physics, University Autonoma Madrid, 28049 Madrid, Spain
| | - B W Pointon
- Department of Physics, British Columbia Institute of Technology, Burnaby, British Columbia V5G 3H2, Canada
- TRIUMF, 4004 Wesbrook Mall, Vancouver, British Columbia V6T2A3, Canada
| | - E Kearns
- Department of Physics, Boston University, Boston, Massachusetts 02215, USA
- Kavli Institute for the Physics and Mathematics of the Universe (WPI), The University of Tokyo Institutes for Advanced Study, University of Tokyo, Kashiwa, Chiba 277-8583, Japan
| | - J L Raaf
- Department of Physics, Boston University, Boston, Massachusetts 02215, USA
| | - L Wan
- Department of Physics, Boston University, Boston, Massachusetts 02215, USA
| | - T Wester
- Department of Physics, Boston University, Boston, Massachusetts 02215, USA
| | - J Bian
- Department of Physics and Astronomy, University of California, Irvine, Irvine, California 92697-4575, USA
| | - N J Griskevich
- Department of Physics and Astronomy, University of California, Irvine, Irvine, California 92697-4575, USA
| | - W R Kropp
- Department of Physics and Astronomy, University of California, Irvine, Irvine, California 92697-4575, USA
| | - S Locke
- Department of Physics and Astronomy, University of California, Irvine, Irvine, California 92697-4575, USA
| | - M B Smy
- Department of Physics and Astronomy, University of California, Irvine, Irvine, California 92697-4575, USA
- Kavli Institute for the Physics and Mathematics of the Universe (WPI), The University of Tokyo Institutes for Advanced Study, University of Tokyo, Kashiwa, Chiba 277-8583, Japan
| | - H W Sobel
- Department of Physics and Astronomy, University of California, Irvine, Irvine, California 92697-4575, USA
- Kavli Institute for the Physics and Mathematics of the Universe (WPI), The University of Tokyo Institutes for Advanced Study, University of Tokyo, Kashiwa, Chiba 277-8583, Japan
| | - V Takhistov
- Department of Physics and Astronomy, University of California, Irvine, Irvine, California 92697-4575, USA
- High Energy Accelerator Research Organization (KEK), Tsukuba, Ibaraki 305-0801, Japan
- Kavli Institute for the Physics and Mathematics of the Universe (WPI), The University of Tokyo Institutes for Advanced Study, University of Tokyo, Kashiwa, Chiba 277-8583, Japan
| | - A Yankelevich
- Department of Physics and Astronomy, University of California, Irvine, Irvine, California 92697-4575, USA
| | - J Hill
- Department of Physics, California State University, Dominguez Hills, Carson, California 90747, USA
| | - R G Park
- Institute for Universe and Elementary Particles, Chonnam National University, Gwangju 61186, Korea
| | - B Bodur
- Department of Physics, Duke University, Durham, North Carolina 27708, USA
| | - K Scholberg
- Department of Physics, Duke University, Durham, North Carolina 27708, USA
- Kavli Institute for the Physics and Mathematics of the Universe (WPI), The University of Tokyo Institutes for Advanced Study, University of Tokyo, Kashiwa, Chiba 277-8583, Japan
| | - C W Walter
- Department of Physics, Duke University, Durham, North Carolina 27708, USA
- Kavli Institute for the Physics and Mathematics of the Universe (WPI), The University of Tokyo Institutes for Advanced Study, University of Tokyo, Kashiwa, Chiba 277-8583, Japan
| | - L Bernard
- Ecole Polytechnique, IN2P3-CNRS, Laboratoire Leprince-Ringuet, F-91120 Palaiseau, France
| | - A Coffani
- Ecole Polytechnique, IN2P3-CNRS, Laboratoire Leprince-Ringuet, F-91120 Palaiseau, France
| | - O Drapier
- Ecole Polytechnique, IN2P3-CNRS, Laboratoire Leprince-Ringuet, F-91120 Palaiseau, France
| | - S El Hedri
- Ecole Polytechnique, IN2P3-CNRS, Laboratoire Leprince-Ringuet, F-91120 Palaiseau, France
| | - A Giampaolo
- Ecole Polytechnique, IN2P3-CNRS, Laboratoire Leprince-Ringuet, F-91120 Palaiseau, France
| | - Th A Mueller
- Ecole Polytechnique, IN2P3-CNRS, Laboratoire Leprince-Ringuet, F-91120 Palaiseau, France
| | - A D Santos
- Ecole Polytechnique, IN2P3-CNRS, Laboratoire Leprince-Ringuet, F-91120 Palaiseau, France
| | - P Paganini
- Ecole Polytechnique, IN2P3-CNRS, Laboratoire Leprince-Ringuet, F-91120 Palaiseau, France
| | - B Quilain
- Ecole Polytechnique, IN2P3-CNRS, Laboratoire Leprince-Ringuet, F-91120 Palaiseau, France
| | - T Ishizuka
- Junior College, Fukuoka Institute of Technology, Fukuoka, Fukuoka 811-0295, Japan
| | - T Nakamura
- Department of Physics, Gifu University, Gifu, Gifu 501-1193, Japan
| | - J S Jang
- GIST College, Gwangju Institute of Science and Technology, Gwangju 500-712, Korea
| | - J G Learned
- Department of Physics and Astronomy, University of Hawaii, Honolulu, Hawaii 96822, USA
| | - K Choi
- Institute for Basic Science (IBS), Daejeon 34126, Korea
| | - S Cao
- Institute For Interdisciplinary Research in Science and Education, ICISE, Quy Nhon 55121, Vietnam
| | - L H V Anthony
- Department of Physics, Imperial College London, London SW7 2AZ, United Kingdom
| | - D Martin
- Department of Physics, Imperial College London, London SW7 2AZ, United Kingdom
| | - M Scott
- Department of Physics, Imperial College London, London SW7 2AZ, United Kingdom
| | - A A Sztuc
- Department of Physics, Imperial College London, London SW7 2AZ, United Kingdom
| | - Y Uchida
- Department of Physics, Imperial College London, London SW7 2AZ, United Kingdom
| | - V Berardi
- Dipartimento Interuniversitario di Fisica, INFN Sezione di Bari and Università e Politecnico di Bari, I-70125 Bari, Italy
| | - M G Catanesi
- Dipartimento Interuniversitario di Fisica, INFN Sezione di Bari and Università e Politecnico di Bari, I-70125 Bari, Italy
| | - E Radicioni
- Dipartimento Interuniversitario di Fisica, INFN Sezione di Bari and Università e Politecnico di Bari, I-70125 Bari, Italy
| | - N F Calabria
- Dipartimento di Fisica, INFN Sezione di Napoli and Università di Napoli, I-80126 Napoli, Italy
| | - L N Machado
- Dipartimento di Fisica, INFN Sezione di Napoli and Università di Napoli, I-80126 Napoli, Italy
| | - G De Rosa
- Dipartimento di Fisica, INFN Sezione di Napoli and Università di Napoli, I-80126 Napoli, Italy
| | - G Collazuol
- Dipartimento di Fisica, INFN Sezione di Padova and Università di Padova, I-35131 Padova, Italy
| | - F Iacob
- Dipartimento di Fisica, INFN Sezione di Padova and Università di Padova, I-35131 Padova, Italy
| | - M Lamoureux
- Dipartimento di Fisica, INFN Sezione di Padova and Università di Padova, I-35131 Padova, Italy
| | - M Mattiazzi
- Dipartimento di Fisica, INFN Sezione di Padova and Università di Padova, I-35131 Padova, Italy
| | - L Ludovici
- INFN Sezione di Roma and Università di Roma "La Sapienza," I-00185, Roma, Italy
| | - M Gonin
- ILANCE, CNRS-University of Tokyo International Research Laboratory, Kashiwa, Chiba 277-8582, Japan
| | - G Pronost
- ILANCE, CNRS-University of Tokyo International Research Laboratory, Kashiwa, Chiba 277-8582, Japan
| | - C Fujisawa
- Department of Physics, Keio University, Yokohama, Kanagawa 223-8522, Japan
| | - Y Maekawa
- Department of Physics, Keio University, Yokohama, Kanagawa 223-8522, Japan
| | - Y Nishimura
- Department of Physics, Keio University, Yokohama, Kanagawa 223-8522, Japan
| | - M Friend
- High Energy Accelerator Research Organization (KEK), Tsukuba, Ibaraki 305-0801, Japan
| | - T Hasegawa
- High Energy Accelerator Research Organization (KEK), Tsukuba, Ibaraki 305-0801, Japan
| | - T Ishida
- High Energy Accelerator Research Organization (KEK), Tsukuba, Ibaraki 305-0801, Japan
| | - T Kobayashi
- High Energy Accelerator Research Organization (KEK), Tsukuba, Ibaraki 305-0801, Japan
| | - M Jakkapu
- High Energy Accelerator Research Organization (KEK), Tsukuba, Ibaraki 305-0801, Japan
| | - T Matsubara
- High Energy Accelerator Research Organization (KEK), Tsukuba, Ibaraki 305-0801, Japan
| | - T Nakadaira
- High Energy Accelerator Research Organization (KEK), Tsukuba, Ibaraki 305-0801, Japan
| | - K Nakamura
- High Energy Accelerator Research Organization (KEK), Tsukuba, Ibaraki 305-0801, Japan
- Kavli Institute for the Physics and Mathematics of the Universe (WPI), The University of Tokyo Institutes for Advanced Study, University of Tokyo, Kashiwa, Chiba 277-8583, Japan
| | - Y Oyama
- High Energy Accelerator Research Organization (KEK), Tsukuba, Ibaraki 305-0801, Japan
| | - K Sakashita
- High Energy Accelerator Research Organization (KEK), Tsukuba, Ibaraki 305-0801, Japan
| | - T Sekiguchi
- High Energy Accelerator Research Organization (KEK), Tsukuba, Ibaraki 305-0801, Japan
| | - T Tsukamoto
- High Energy Accelerator Research Organization (KEK), Tsukuba, Ibaraki 305-0801, Japan
| | - T Boschi
- Department of Physics, King's College London, London WC2R 2LS, United Kingdom
| | - F Di Lodovico
- Department of Physics, King's College London, London WC2R 2LS, United Kingdom
| | - J Gao
- Department of Physics, King's College London, London WC2R 2LS, United Kingdom
| | - A Goldsack
- Department of Physics, King's College London, London WC2R 2LS, United Kingdom
| | - T Katori
- Department of Physics, King's College London, London WC2R 2LS, United Kingdom
| | - J Migenda
- Department of Physics, King's College London, London WC2R 2LS, United Kingdom
| | - M Taani
- Department of Physics, King's College London, London WC2R 2LS, United Kingdom
| | - S Zsoldos
- Department of Physics, King's College London, London WC2R 2LS, United Kingdom
- Kavli Institute for the Physics and Mathematics of the Universe (WPI), The University of Tokyo Institutes for Advanced Study, University of Tokyo, Kashiwa, Chiba 277-8583, Japan
| | - Y Kotsar
- Department of Physics, Kobe University, Kobe, Hyogo 657-8501, Japan
| | - H Ozaki
- Department of Physics, Kobe University, Kobe, Hyogo 657-8501, Japan
| | - A T Suzuki
- Department of Physics, Kobe University, Kobe, Hyogo 657-8501, Japan
| | - Y Takeuchi
- Department of Physics, Kobe University, Kobe, Hyogo 657-8501, Japan
- Kavli Institute for the Physics and Mathematics of the Universe (WPI), The University of Tokyo Institutes for Advanced Study, University of Tokyo, Kashiwa, Chiba 277-8583, Japan
| | - C Bronner
- Department of Physics, Kyoto University, Kyoto, Kyoto 606-8502, Japan
| | - J Feng
- Department of Physics, Kyoto University, Kyoto, Kyoto 606-8502, Japan
| | - T Kikawa
- Department of Physics, Kyoto University, Kyoto, Kyoto 606-8502, Japan
| | - M Mori
- Department of Physics, Kyoto University, Kyoto, Kyoto 606-8502, Japan
| | - T Nakaya
- Department of Physics, Kyoto University, Kyoto, Kyoto 606-8502, Japan
- Kavli Institute for the Physics and Mathematics of the Universe (WPI), The University of Tokyo Institutes for Advanced Study, University of Tokyo, Kashiwa, Chiba 277-8583, Japan
| | - R A Wendell
- Department of Physics, Kyoto University, Kyoto, Kyoto 606-8502, Japan
- Kavli Institute for the Physics and Mathematics of the Universe (WPI), The University of Tokyo Institutes for Advanced Study, University of Tokyo, Kashiwa, Chiba 277-8583, Japan
| | - K Yasutome
- Department of Physics, Kyoto University, Kyoto, Kyoto 606-8502, Japan
| | - S J Jenkins
- Department of Physics, University of Liverpool, Liverpool L69 7ZE, United Kingdom
| | - N McCauley
- Department of Physics, University of Liverpool, Liverpool L69 7ZE, United Kingdom
| | - P Mehta
- Department of Physics, University of Liverpool, Liverpool L69 7ZE, United Kingdom
| | - K M Tsui
- Department of Physics, University of Liverpool, Liverpool L69 7ZE, United Kingdom
| | - Y Fukuda
- Department of Physics, Miyagi University of Education, Sendai, Miyagi 980-0845, Japan
| | - Y Itow
- Institute for Space-Earth Environmental Research, Nagoya University, Nagoya, Aichi 464-8602, Japan
- Kobayashi-Maskawa Institute for the Origin of Particles and the Universe, Nagoya University, Nagoya, Aichi 464-8602, Japan
| | - H Menjo
- Institute for Space-Earth Environmental Research, Nagoya University, Nagoya, Aichi 464-8602, Japan
| | - K Ninomiya
- Institute for Space-Earth Environmental Research, Nagoya University, Nagoya, Aichi 464-8602, Japan
| | - J Lagoda
- National Centre For Nuclear Research, 02-093 Warsaw, Poland
| | - S M Lakshmi
- National Centre For Nuclear Research, 02-093 Warsaw, Poland
| | - M Mandal
- National Centre For Nuclear Research, 02-093 Warsaw, Poland
| | - P Mijakowski
- National Centre For Nuclear Research, 02-093 Warsaw, Poland
| | - Y S Prabhu
- National Centre For Nuclear Research, 02-093 Warsaw, Poland
| | - J Zalipska
- National Centre For Nuclear Research, 02-093 Warsaw, Poland
| | - M Jia
- Department of Physics and Astronomy, State University of New York at Stony Brook, New York 11794-3800, USA
| | - J Jiang
- Department of Physics and Astronomy, State University of New York at Stony Brook, New York 11794-3800, USA
| | - C K Jung
- Department of Physics and Astronomy, State University of New York at Stony Brook, New York 11794-3800, USA
| | - M J Wilking
- Department of Physics and Astronomy, State University of New York at Stony Brook, New York 11794-3800, USA
| | - C Yanagisawa
- Department of Physics and Astronomy, State University of New York at Stony Brook, New York 11794-3800, USA
| | - M Harada
- Department of Physics, Okayama University, Okayama, Okayama 700-8530, Japan
| | - H Ishino
- Department of Physics, Okayama University, Okayama, Okayama 700-8530, Japan
| | - S Ito
- Department of Physics, Okayama University, Okayama, Okayama 700-8530, Japan
| | - H Kitagawa
- Department of Physics, Okayama University, Okayama, Okayama 700-8530, Japan
| | - Y Koshio
- Department of Physics, Okayama University, Okayama, Okayama 700-8530, Japan
- Kavli Institute for the Physics and Mathematics of the Universe (WPI), The University of Tokyo Institutes for Advanced Study, University of Tokyo, Kashiwa, Chiba 277-8583, Japan
| | - F Nakanishi
- Department of Physics, Okayama University, Okayama, Okayama 700-8530, Japan
| | - S Sakai
- Department of Physics, Okayama University, Okayama, Okayama 700-8530, Japan
| | - G Barr
- Department of Physics, Oxford University, Oxford OX1 3PU, United Kingdom
| | - D Barrow
- Department of Physics, Oxford University, Oxford OX1 3PU, United Kingdom
| | - L Cook
- Department of Physics, Oxford University, Oxford OX1 3PU, United Kingdom
- Kavli Institute for the Physics and Mathematics of the Universe (WPI), The University of Tokyo Institutes for Advanced Study, University of Tokyo, Kashiwa, Chiba 277-8583, Japan
| | - S Samani
- Department of Physics, Oxford University, Oxford OX1 3PU, United Kingdom
| | - D Wark
- Department of Physics, Oxford University, Oxford OX1 3PU, United Kingdom
- STFC, Rutherford Appleton Laboratory, Harwell Oxford, and Daresbury Laboratory, Warrington OX11 0QX, United Kingdom
| | - F Nova
- Rutherford Appleton Laboratory, Harwell, Oxford OX11 0QX, United Kingdom
| | - J Y Yang
- Department of Physics, Seoul National University, Seoul 151-742, Korea
| | - M Malek
- Department of Physics and Astronomy, University of Sheffield, S3 7RH Sheffield, United Kingdom
| | - J M McElwee
- Department of Physics and Astronomy, University of Sheffield, S3 7RH Sheffield, United Kingdom
| | - O Stone
- Department of Physics and Astronomy, University of Sheffield, S3 7RH Sheffield, United Kingdom
| | - M D Thiesse
- Department of Physics and Astronomy, University of Sheffield, S3 7RH Sheffield, United Kingdom
| | - L F Thompson
- Department of Physics and Astronomy, University of Sheffield, S3 7RH Sheffield, United Kingdom
| | - H Okazawa
- Department of Informatics in Social Welfare, Shizuoka University of Welfare, Yaizu, Shizuoka 425-8611, Japan
| | - S B Kim
- Department of Physics, Sungkyunkwan University, Suwon 440-746, Korea
| | - J W Seo
- Department of Physics, Sungkyunkwan University, Suwon 440-746, Korea
| | - I Yu
- Department of Physics, Sungkyunkwan University, Suwon 440-746, Korea
| | - A K Ichikawa
- Department of Physics, Faculty of Science, Tohoku University, Sendai, Miyagi 980-8578, Japan
| | - K D Nakamura
- Department of Physics, Faculty of Science, Tohoku University, Sendai, Miyagi 980-8578, Japan
| | - S Tairafune
- Department of Physics, Faculty of Science, Tohoku University, Sendai, Miyagi 980-8578, Japan
| | - K Nishijima
- Department of Physics, Tokai University, Hiratsuka, Kanagawa 259-1292, Japan
| | - K Iwamoto
- Department of Physics, University of Tokyo, Bunkyo, Tokyo 113-0033, Japan
| | - K Nakagiri
- Department of Physics, University of Tokyo, Bunkyo, Tokyo 113-0033, Japan
| | - Y Nakajima
- Department of Physics, University of Tokyo, Bunkyo, Tokyo 113-0033, Japan
- Kavli Institute for the Physics and Mathematics of the Universe (WPI), The University of Tokyo Institutes for Advanced Study, University of Tokyo, Kashiwa, Chiba 277-8583, Japan
| | - N Taniuchi
- Department of Physics, University of Tokyo, Bunkyo, Tokyo 113-0033, Japan
| | - M Yokoyama
- Department of Physics, University of Tokyo, Bunkyo, Tokyo 113-0033, Japan
- Kavli Institute for the Physics and Mathematics of the Universe (WPI), The University of Tokyo Institutes for Advanced Study, University of Tokyo, Kashiwa, Chiba 277-8583, Japan
| | - K Martens
- Kavli Institute for the Physics and Mathematics of the Universe (WPI), The University of Tokyo Institutes for Advanced Study, University of Tokyo, Kashiwa, Chiba 277-8583, Japan
| | - P de Perio
- Kavli Institute for the Physics and Mathematics of the Universe (WPI), The University of Tokyo Institutes for Advanced Study, University of Tokyo, Kashiwa, Chiba 277-8583, Japan
| | - M R Vagins
- Department of Physics and Astronomy, University of California, Irvine, Irvine, California 92697-4575, USA
- Kavli Institute for the Physics and Mathematics of the Universe (WPI), The University of Tokyo Institutes for Advanced Study, University of Tokyo, Kashiwa, Chiba 277-8583, Japan
| | - M Kuze
- Department of Physics, Tokyo Institute of Technology, Meguro, Tokyo 152-8551, Japan
| | - S Izumiyama
- Department of Physics, Tokyo Institute of Technology, Meguro, Tokyo 152-8551, Japan
| | - M Inomoto
- Department of Physics, Faculty of Science and Technology, Tokyo University of Science, Noda, Chiba 278-8510, Japan
| | - M Ishitsuka
- Department of Physics, Faculty of Science and Technology, Tokyo University of Science, Noda, Chiba 278-8510, Japan
| | - H Ito
- Department of Physics, Faculty of Science and Technology, Tokyo University of Science, Noda, Chiba 278-8510, Japan
| | - T Kinoshita
- Department of Physics, Faculty of Science and Technology, Tokyo University of Science, Noda, Chiba 278-8510, Japan
| | - R Matsumoto
- Department of Physics, Faculty of Science and Technology, Tokyo University of Science, Noda, Chiba 278-8510, Japan
| | - Y Ommura
- Department of Physics, Faculty of Science and Technology, Tokyo University of Science, Noda, Chiba 278-8510, Japan
| | - N Shigeta
- Department of Physics, Faculty of Science and Technology, Tokyo University of Science, Noda, Chiba 278-8510, Japan
| | - M Shinoki
- Department of Physics, Faculty of Science and Technology, Tokyo University of Science, Noda, Chiba 278-8510, Japan
| | - T Suganuma
- Department of Physics, Faculty of Science and Technology, Tokyo University of Science, Noda, Chiba 278-8510, Japan
| | - K Yamauchi
- Department of Physics, Faculty of Science and Technology, Tokyo University of Science, Noda, Chiba 278-8510, Japan
| | - J F Martin
- Department of Physics, University of Toronto, Ontario M5S 1A7, Canada
| | - H A Tanaka
- Department of Physics, University of Toronto, Ontario M5S 1A7, Canada
| | - T Towstego
- Department of Physics, University of Toronto, Ontario M5S 1A7, Canada
| | - R Akutsu
- TRIUMF, 4004 Wesbrook Mall, Vancouver, British Columbia V6T2A3, Canada
| | - V Gousy-Leblanc
- TRIUMF, 4004 Wesbrook Mall, Vancouver, British Columbia V6T2A3, Canada
| | - M Hartz
- TRIUMF, 4004 Wesbrook Mall, Vancouver, British Columbia V6T2A3, Canada
| | - A Konaka
- TRIUMF, 4004 Wesbrook Mall, Vancouver, British Columbia V6T2A3, Canada
| | - N W Prouse
- TRIUMF, 4004 Wesbrook Mall, Vancouver, British Columbia V6T2A3, Canada
| | - S Chen
- Department of Engineering Physics, Tsinghua University, Beijing, 100084, China
| | - B D Xu
- Department of Engineering Physics, Tsinghua University, Beijing, 100084, China
| | - B Zhang
- Department of Engineering Physics, Tsinghua University, Beijing, 100084, China
| | | | - D Hadley
- Department of Physics, University of Warwick, Coventry, CV4 7AL, United Kingdom
| | - M Nicholson
- Department of Physics, University of Warwick, Coventry, CV4 7AL, United Kingdom
| | - M O'Flaherty
- Department of Physics, University of Warwick, Coventry, CV4 7AL, United Kingdom
| | - B Richards
- Department of Physics, University of Warwick, Coventry, CV4 7AL, United Kingdom
| | - A Ali
- TRIUMF, 4004 Wesbrook Mall, Vancouver, British Columbia V6T2A3, Canada
- Department of Physics, University of Winnipeg, Manitoba R3J 3L8, Canada
| | - B Jamieson
- Department of Physics, University of Winnipeg, Manitoba R3J 3L8, Canada
| | - Ll Marti
- Department of Physics, Yokohama National University, Yokohama, Kanagawa 240-8501, Japan
| | - A Minamino
- Department of Physics, Yokohama National University, Yokohama, Kanagawa 240-8501, Japan
| | - G Pintaudi
- Department of Physics, Yokohama National University, Yokohama, Kanagawa 240-8501, Japan
| | - S Sano
- Department of Physics, Yokohama National University, Yokohama, Kanagawa 240-8501, Japan
| | - S Suzuki
- Department of Physics, Yokohama National University, Yokohama, Kanagawa 240-8501, Japan
| | - K Wada
- Department of Physics, Yokohama National University, Yokohama, Kanagawa 240-8501, Japan
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Zhong QY, Zhang XY, Luo HH, Jiang X, Zeng XY, Jiang J, Xia HF, Peng Y, Lyu MH, Tang XW. [Analysis of the characteristics of retracted scientific papers in the field of global liver diseases published by Chinese scholars]. Zhonghua Gan Zang Bing Za Zhi 2023; 31:96-100. [PMID: 36948856 DOI: 10.3760/cma.j.cn501113-20210324-00138] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Indexed: 03/24/2023]
Abstract
Objective: To analyze the characteristics of scientific papers in the field of global liver diseases published by Chinese scholars that were retracted for diverse reasons from the Retraction Watch database, so as to provide a reference to publishing-related papers. Methods: The Retraction Watch database was retrieved for retracted papers in the field of global liver disease published by Chinese scholars from March 1, 2008 to January 28, 2021. The regional distribution, source journals, reasons for retraction, publication and retraction times, and others were analyzed. Results: A total of 101 retracted papers that were distributed across 21 provinces/cities were retrieved. Zhejiang area (n = 17) had the most retracted papers, followed by Shanghai (n = 14), and Beijing (n = 11). The vast majority were research papers (n = 95). The journal PLoS One had the highest number of retracted papers. In terms of time distribution, 2019 (n = 36) had the most retracted papers. 23 papers, accounting for 8.3% of all retractions, were retracted owing to journal or publisher concerns. Liver cancer (34%), liver transplantation (16%), hepatitis (14%), and others were the main areas of retracted papers. Conclusion: Chinese scholars have a large number of retracted articles in the field of global liver diseases. A journal or publisher chooses to retract a manuscript after investigating and discovering more flawed problems, which, however, require further support, revision, and supervision from the editorial and academic circles.
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Affiliation(s)
- Q Y Zhong
- Department of Gastenterology, The Affiliated Hospital of South West Medical University, Luzhou 646000, China Clinical College of South West Medical University, Luzhou 646000, China
| | - X Y Zhang
- Department of Gastenterology, The Affiliated Hospital of South West Medical University, Luzhou 646000, China Clinical College of South West Medical University, Luzhou 646000, China
| | - H H Luo
- Department of Gastenterology, The Affiliated Hospital of South West Medical University, Luzhou 646000, China Clinical College of South West Medical University, Luzhou 646000, China
| | - X Jiang
- Department of Gastenterology, The Affiliated Hospital of South West Medical University, Luzhou 646000, China
| | - X Y Zeng
- Department of Gastenterology, The Affiliated Hospital of South West Medical University, Luzhou 646000, China
| | - J Jiang
- Department of Gastenterology, The Affiliated Hospital of South West Medical University, Luzhou 646000, China
| | - H F Xia
- Department of Gastenterology, The Affiliated Hospital of South West Medical University, Luzhou 646000, China
| | - Y Peng
- Department of Gastenterology, The Affiliated Hospital of South West Medical University, Luzhou 646000, China
| | - M H Lyu
- Department of Gastenterology, The Affiliated Hospital of South West Medical University, Luzhou 646000, China
| | - X W Tang
- Department of Gastenterology, The Affiliated Hospital of South West Medical University, Luzhou 646000, China
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Yacheur D, Ackermann M, Li T, Kalyanov A, Russomanno E, Mata ADC, Wolf M, Jiang J. Imaging Cerebral Blood Vessels Using Near-Infrared Optical Tomography: A Simulation Study. Adv Exp Med Biol 2023; 1438:203-207. [PMID: 37845462 DOI: 10.1007/978-3-031-42003-0_32] [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] [Indexed: 10/18/2023]
Abstract
Cerebral veins have received increasing attention due to their importance in preoperational planning and the brain oxygenation measurement. There are different modalities to image those vessels, such as magnetic resonance angiography (MRA) and recently, contrast-enhanced (CE) 3D gradient-echo sequences. However, the current techniques have certain disadvantages, i.e., the long examination time, the requirement of contrast agents or inability to measure oxygenation. Near-infrared optical tomography (NIROT) is emerging as a viable new biomedical imaging modality that employs near infrared light (650-950 nm) to image biological tissue. It was proven to easily penetrate the skull and therefore enables the brain vessels to be assessed. NIROT utilizes safe non-ionizing radiation and can be applied in e.g., early detection of neonatal brain injury and ischemic strokes. The aim is to develop non-invasive label-free dynamic time domain (TD) NIROT to image the brain vessels. A simulation study was performed with the software (NIRFAST) which models light propagation in tissue with the finite element method (FEM). Both a simple shape mesh and a real head mesh including all the segmented vessels from MRI images were simulated using both FEM and a hybrid FEM-U-Net network, we were able to visualize the superficial vessels with NIROT with a Root Mean Square Error (RMSE) lower than 0.079.
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Affiliation(s)
- D Yacheur
- Biomedical Optics Research Laboratory (BORL), Department of Neonatology, University Hospital Zurich, University of Zurich, Zurich, Switzerland.
| | - M Ackermann
- Biomedical Optics Research Laboratory (BORL), Department of Neonatology, University Hospital Zurich, University of Zurich, Zurich, Switzerland
| | - T Li
- Biomedical Optics Research Laboratory (BORL), Department of Neonatology, University Hospital Zurich, University of Zurich, Zurich, Switzerland
| | - A Kalyanov
- Biomedical Optics Research Laboratory (BORL), Department of Neonatology, University Hospital Zurich, University of Zurich, Zurich, Switzerland
| | - E Russomanno
- Biomedical Optics Research Laboratory (BORL), Department of Neonatology, University Hospital Zurich, University of Zurich, Zurich, Switzerland
| | - A Di Costanzo Mata
- Biomedical Optics Research Laboratory (BORL), Department of Neonatology, University Hospital Zurich, University of Zurich, Zurich, Switzerland
| | - M Wolf
- Biomedical Optics Research Laboratory (BORL), Department of Neonatology, University Hospital Zurich, University of Zurich, Zurich, Switzerland
| | - J Jiang
- Biomedical Optics Research Laboratory (BORL), Department of Neonatology, University Hospital Zurich, University of Zurich, Zurich, Switzerland
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Jiang J, Hong Y, Li W, Wang A, Jiang S, Jiang T, Wang Y, Wang L, Yang S, Ren Q, Zou X, Xu J. Chain Mediation Analysis of the Effects of Nutrition and Cognition on the Association of Apolipoprotein E ɛ4 with Neuropsychiatric Symptoms in Alzheimer's Disease. J Alzheimers Dis 2023; 96:669-681. [PMID: 37840496 DOI: 10.3233/jad-230577] [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: 10/17/2023]
Abstract
BACKGROUND Apolipoprotein E (APOE) is the most recognized risk gene for cognitive decline and clinical progression of late-onset Alzheimer's disease (AD); nonetheless, its association with neuropsychiatric symptoms (NPSs) remains inconclusive. OBJECTIVE To investigate the association of APOE ɛ4 with NPSs and explore nutritional status and cognition as joint mediators of this association. METHODS Between June 2021 and October 2022, patients with amnestic mild cognitive impairment (aMCI) or AD were recruited from the Chinese Imaging, Biomarkers, and Lifestyle Study. NPSs were assessed using the Neuropsychiatric Inventory, while global cognition and nutritional status were evaluated using the Mini-Mental State Examination (MMSE) and Mini-Nutritional Assessment (MNA), respectively. Simple mediation and multiple chain mediation models were developed to examine the mediating effects of the MNA and MMSE scores on the relationship between APOE ɛ4 and specific neuropsychiatric symptom. RESULTS Among 310 patients, 229 (73.87%) had NPSs, and 110 (35.48%) carried APOE ɛ4. Patients with APOE ɛ4 were more likely to have hallucinations (p = 0.014), apathy (p = 0.008), and aberrant motor activity (p = 0.018). MNA and MMSE scores mediated the association between APOE ɛ4 and hallucinations (17.97% and 37.13%, respectively), APOE ɛ4 and apathy (30.73% and 57.72%, respectively), and APOE ɛ4 and aberrant motor activity (17.82% and 34.24%), respectively. Chain-mediating effects of MNA and MMSE scores on the association of APOE ɛ4 with hallucinations, apathy, and aberrant motor activity after adjusting for confounding factors were 6.84%, 11.54%, and 6.19%, respectively. CONCLUSION Nutritional status and cognition jointly mediate the association between APOE ɛ4 and neuropsychiatric symptoms in patients with aMCI or AD.
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Affiliation(s)
- Jiwei Jiang
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Fengtai District, Beijing, China
- National Clinical Research Center for Neurological Diseases, Fengtai District, Beijing, China
| | - Yin Hong
- Department of Health Management, Beijing Tian Tan Hospital, Capital Medical University, Fengtai District, Beijing, China
| | - Wenyi Li
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Fengtai District, Beijing, China
- National Clinical Research Center for Neurological Diseases, Fengtai District, Beijing, China
| | - Anxin Wang
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Fengtai District, Beijing, China
- National Clinical Research Center for Neurological Diseases, Fengtai District, Beijing, China
| | - Shirui Jiang
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Fengtai District, Beijing, China
- National Clinical Research Center for Neurological Diseases, Fengtai District, Beijing, China
| | - Tianlin Jiang
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Fengtai District, Beijing, China
- National Clinical Research Center for Neurological Diseases, Fengtai District, Beijing, China
| | - Yanli Wang
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Fengtai District, Beijing, China
- National Clinical Research Center for Neurological Diseases, Fengtai District, Beijing, China
| | - Linlin Wang
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Fengtai District, Beijing, China
- National Clinical Research Center for Neurological Diseases, Fengtai District, Beijing, China
| | - Shiyi Yang
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Fengtai District, Beijing, China
- National Clinical Research Center for Neurological Diseases, Fengtai District, Beijing, China
| | - Qiwei Ren
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Fengtai District, Beijing, China
- National Clinical Research Center for Neurological Diseases, Fengtai District, Beijing, China
| | - Xinying Zou
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Fengtai District, Beijing, China
- National Clinical Research Center for Neurological Diseases, Fengtai District, Beijing, China
| | - Jun Xu
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Fengtai District, Beijing, China
- National Clinical Research Center for Neurological Diseases, Fengtai District, Beijing, China
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Luo X, Jiang H, Liu XJ, Zhang Z, Deng K, Lin F, Jiang J, Wang YL, Yu J. Base MRI Imaging Characteristics of Meningioma Patients to Discuss the WHO Classification of Brain Invasion Otherwise Benign Meningiomas. Technol Cancer Res Treat 2023; 22:15330338231171470. [PMID: 37264676 DOI: 10.1177/15330338231171470] [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] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/03/2023] Open
Abstract
PURPOSE Compared and analyzed the MRI imaging features of brain invasion otherwise benign (BIOB) meningiomas and WHO grade 1, grade 2 meningiomas, discussed the WHO grading of BIOB from the perspective of imaging. MATERIALS AND METHODS A retrospective analysis was performed on 675 meningiomas patients who carried on MRI examination from January 2006 to February 2022. Setting the 2022 Central nervous system (CNS) WHO Guidelines as the gold standard for pathological diagnosis. Statistical analysis of age, gender, and MRI features of meningiomas in relation to WHO grade and brain invasion. RESULTS Among 675 cases meningiomas, 543 (80.4%) were WHO grade 1, 123 (18.2%) were WHO grade 2, and 9 (1.3%) were WHO grade 3. There were 108 cases meningiomas with brain invasion (BI) (16.0%) and 567 cases without BI (84.0%). Among BI cases, 67 cases were BIOB. Compared the MRI features between BIOB and WHO grade 1 meningiomas, multivariate analysis demonstrated that the most strongly factors associated with distinguish them were enhancement degree, peritumoral edema, tumor-brain interface, fingerlike protrusion, mushroom sign, and bone invasion (AUC: 0.925 (0.901∼0.945), sensitivity: 0.925, specificity: 0.801). Compared the MRI features between BIOB and WHO grade 2 meningiomas, multivariate analysis demonstrated that the most strongly factors associated with distinguish them were enhancement degree and the tumor-brain interface (AUC: 0.779 (0.686∼0.841), sensitivity: 0.746, specificity: 0.732), their efficacy was slightly weaker. CONCLUSIONS BIOB is more similar to WHO grade 2 meningiomas in clinical and imaging features than WHO grade 1, so we think that it may be reasonable to classify BIOB as WHO Grade 2 meningiomas in the guidelines.
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Affiliation(s)
- Xiao Luo
- Department of Radiology, The First Affiliated Hospital of Shenzhen University, Health Science Center, Shenzhen Second People's Hospital, Shenzhen, China
| | - Hong Jiang
- Faculty of Medicine, Macau university of science and technology, Macau University of Science and Technology, Taipa, Macau, China
| | - X J Liu
- Department of Radiology, The First Affiliated Hospital of Shenzhen University, Health Science Center, Shenzhen Second People's Hospital, Shenzhen, China
| | - Z Zhang
- Faculty of Medicine, Macau university of science and technology, Macau University of Science and Technology, Taipa, Macau, China
| | - K Deng
- Philips Healthcare, China International Center, Guangzhou, China
| | - F Lin
- Department of Radiology, The First Affiliated Hospital of Shenzhen University, Health Science Center, Shenzhen Second People's Hospital, Shenzhen, China
| | - J Jiang
- Department of Radiology, The First Affiliated Hospital of Shenzhen University, Health Science Center, Shenzhen Second People's Hospital, Shenzhen, China
| | - Y L Wang
- Department of Radiology, The First Affiliated Hospital of Shenzhen University, Health Science Center, Shenzhen Second People's Hospital, Shenzhen, China
| | - J Yu
- Department of Radiology, The First Affiliated Hospital of Shenzhen University, Health Science Center, Shenzhen Second People's Hospital, Shenzhen, China
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Wang X, Jiang J, Hu W, Hu Y, Qin LQ, Hao Y, Dong JY. Dynapenic Abdominal Obesity and Risk of Heart Disease among Middle-Aged and Older Adults: A Prospective Cohort Study. J Nutr Health Aging 2023; 27:752-758. [PMID: 37754215 DOI: 10.1007/s12603-023-1975-0] [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] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/05/2023] [Accepted: 07/29/2023] [Indexed: 09/28/2023]
Abstract
OBJECTIVES The vicious cycle of dynapenia and abdominal obesity may have synergistic detrimental impacts on health. We aim to investigate the prospective association between dynapenic abdominal obesity and the risk of heart disease among middle-aged and older adults. DESIGN A prospective cohort study. SETTING English Longitudinal Study of Ageing, 2002-2019. PARTICIPANTS A total of 4734 participants aged 50 years and older were included. MEASUREMENTS Individuals were divided into non-dynapenia/non-abdominal obesity (ND/NAO), non-dynapenia/abdominal obesity (ND/AO), dynapenia/non-abdominal obesity (D/NAO), and dynapenia/abdominal obesity (D/AO) according to grip strength and waist circumference at baseline. The Cox proportional hazards models were used to obtain the hazard ratios (HRs) of incident heart disease associated with dynapenia and abdominal obesity after adjusting for potential confounding factors. RESULTS During a median follow-up of 9.5 years, 1040 cases of heart disease were recorded. Compared with ND/NAO group, the multivariable HRs were 1.05 (0.92, 1.21) for ND/AO group, 1.31 (0.96, 1.81) for D/NAO group, and 1.39 (1.03, 1.88) for D/AO group. The significant association of D/AO with incident heart disease was detected in women but not in men [HR = 1.55 (1.07, 2.24) and 1.06 (0.60, 1.88), respectively]. Among middle-aged adults, significant associations of D/NAO and D/AO with incident heart disease were observed [HR = 2.46 (1.42, 4.29) and 1.74 (1.02, 2.97), respectively]. CONCLUSION Both D/NAO and D/AO might increase the risk of developing heart disease, highlighting the importance of dynapenia and obesity early screening for heart disease prevention.
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Affiliation(s)
- X Wang
- Yuantao Hao, Center for Public Health and Epidemic Preparedness and Response, Peking University, Beijing, 100191, China; Tel.: 010-82805061, E-mail: ; Jia-Yi Dong, Public Health, Department of Social Medicine, Osaka University Graduate School of Medicine, Osaka 5650871, Japan; Tel: 06-6879-3911,
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Jiang J, Wang A, Liu Y, Yao Z, Sun M, Jiang T, Li W, Jiang S, Zhang X, Wang Y, Zhang Y, Jia Z, Zou X, Xu J. Spatiotemporal Characteristics of Regional Brain Perfusion Associated with Neuropsychiatric Symptoms in Patients with Alzheimer's Disease. J Alzheimers Dis 2023; 95:981-993. [PMID: 37638444 DOI: 10.3233/jad-230499] [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] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/29/2023]
Abstract
BACKGROUND Current technology for exploring neuroimaging markers and neural circuits of neuropsychiatric symptoms (NPS) in patients with Alzheimer's disease (AD) is expensive and usually invasive, limiting its use in clinical practice. OBJECTIVE To investigate the cerebral morphology and perfusion characteristics of NPS and identify the spatiotemporal perfusion circuits of NPS sub-symptoms. METHODS This nested case-control study included 102 AD patients with NPS and 51 age- and sex-matched AD patients without NPS. Gray matter volume, cerebral blood flow (CBF), and arterial transit time (ATT) were measured and generated using time-encoded 7-delay pseudo-continuous arterial spin labeling (pCASL). Multiple conditional logistic regression analysis was used to identify neuroimaging markers of NPS. The associations between the CBF or ATT of affected brain areas and NPS sub-symptoms were evaluated after adjusting for confounding factors. The neural circuits of sub-symptoms were identified based on spatiotemporal perfusion sequencing. RESULTS Lower Mini-Mental State Examination scores (p < 0.001), higher Caregiver Burden Inventory scores (p < 0.001), and higher CBF (p = 0.001) and ATT values (p < 0.003) of the right anteroventral thalamic nucleus (ATN) were risk factors for NPS in patients with AD. Six spatiotemporal perfusion circuits were found from 12 sub-symptoms, including the anterior cingulate gyri-temporal pole/subcortical thalamus-cerebellum circuit, insula-limbic-cortex circuit, subcortical thalamus-temporal pole-cortex circuit, subcortical thalamus-cerebellum circuit, frontal cortex-cerebellum-occipital cortex circuit, and subcortical thalamus-hippocampus-dorsal raphe nucleus circuit. CONCLUSIONS Prolonged ATT and increased CBF of the right ATN may be neuroimaging markers for detecting NPS in patients with AD. Time-encoded pCASL could be a reliable technique to explore the neural perfusional circuits of NPS.
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Affiliation(s)
- Jiwei Jiang
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- National Clinical Research Center for Neurological Diseases, Beijing, China
| | - Anxin Wang
- National Clinical Research Center for Neurological Diseases, Beijing, China
| | - Yaou Liu
- National Clinical Research Center for Neurological Diseases, Beijing, China
- Department of Radiology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Zeshan Yao
- Beijing Institute of Collaborative Innovation Beijing Institute of Collaborative Innovation, Beijing, China
| | - Mengfan Sun
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- National Clinical Research Center for Neurological Diseases, Beijing, China
| | - Tianlin Jiang
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- National Clinical Research Center for Neurological Diseases, Beijing, China
| | - Wenyi Li
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- National Clinical Research Center for Neurological Diseases, Beijing, China
| | - Shirui Jiang
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- National Clinical Research Center for Neurological Diseases, Beijing, China
| | - Xiaoli Zhang
- National Clinical Research Center for Neurological Diseases, Beijing, China
| | - Yanli Wang
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- National Clinical Research Center for Neurological Diseases, Beijing, China
| | - Yuan Zhang
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- National Clinical Research Center for Neurological Diseases, Beijing, China
| | - Ziyan Jia
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- National Clinical Research Center for Neurological Diseases, Beijing, China
| | - Xinying Zou
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- National Clinical Research Center for Neurological Diseases, Beijing, China
| | - Jun Xu
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- National Clinical Research Center for Neurological Diseases, Beijing, China
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Ma HR, Zhang ZT, Jiang J, Li FF, Qiu Y. [Current application and prospect of accurate navigation technology in orthopaedic trauma]. Zhonghua Wai Ke Za Zhi 2023; 61:23-28. [PMID: 36603880 DOI: 10.3760/cma.j.cn112139-20220915-00393] [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: 01/07/2023]
Abstract
In the past decades,a dramatic development of navigation technology in orthopaedic surgery has been witnessed. By assisting the localization of surgical region,verification of target bony structure,preoperative planning of fixation,intraoperative identification of planned entry point and direction of instruments or even automated insertion of implants,its ability and potential to reduce operation time,intraoperative radiation,surgical trauma,and improve accuracy has been proved. However,in contrast to the widespread use of navigation technology in arthroplasty,orthopaedic tumor,and spine surgery,its application in orthopaedic trauma is relatively less. In this manuscript,the main purpose is to introduce the technical principles of navigation devices,outline the current clinical application of navigation systems in orthopaedic trauma,analyze the current challenges confronting its further application in clinical practice and its prospect in the future.
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Affiliation(s)
- H R Ma
- Department of Orthopaedic, Nanjing Drum Tower Hospital,the Affiliated Hospital of Nanjing University Medical School,Nanjing 210008,China
| | - Z T Zhang
- Department of Orthopaedic, Nanjing Drum Tower Hospital,the Affiliated Hospital of Nanjing University Medical School,Nanjing 210008,China
| | - J Jiang
- Department of Orthopaedic, Nanjing Drum Tower Hospital,the Affiliated Hospital of Nanjing University Medical School,Nanjing 210008,China
| | - F F Li
- Department of Orthopaedic, Nanjing Drum Tower Hospital,the Affiliated Hospital of Nanjing University Medical School,Nanjing 210008,China
| | - Y Qiu
- Department of Orthopaedic, Nanjing Drum Tower Hospital,the Affiliated Hospital of Nanjing University Medical School,Nanjing 210008,China
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Garcia-Molina G, Jiang J. Real-time implementation of sleep staging using interbeat intervals. Sleep Med 2022. [DOI: 10.1016/j.sleep.2022.05.813] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 10/17/2022]
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48
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Deb PQ, Jiang J. Clonal Evolution of t(8;21) Coexisting with t(9;22) in a Blastic Transformation of Chronic Myeloid Leukemia. Am J Clin Pathol 2022. [DOI: 10.1093/ajcp/aqac126.091] [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: 11/11/2022] Open
Abstract
Abstract
Introduction/Objective
Chronic myeloid leukemia (CML) is a myeloproliferative disorder characterized by chromosomal translocation t(9;22) and the production of the fusion protein BCR-ABL1. The clinical course of the disease is characterized by a chronic phase, accelerated phase, and blast phase. One of the criteria for the progress of chronic phase to accelerated phase is the presence of cytogenetic anomaly additional to t(9;22). The blast phase of CML usually presents as acute myelogenous leukemia (AML); however, its characteristics are different from de novo AML. One of the most common subtypes of de novo AML with balanced translocation is AML with t(8;21). Here, we present a case of the blast phase of CML that presents t(8;21).
Methods/Case Report
The peripheral blood from a 51-years-old-man presenting with fatigue and splenomegaly showed leukocytosis, mild anemia, marked neutrophilia with left shift, monocytosis, basophilia, and <1% blasts. Flow cytometry identified an increase in granulocyte events with the left shift. Chromosome studies detected t(9;22) by karyotyping and FISH. BCR-ABL1 transcript was detected at 41.98% on the International Scale by RT-PCR, consistent with chronic myeloid leukemia (CML). The following bone marrow biopsy confirmed a diagnosis of the chronic phase of CML with <5% myeloblasts. After a year of treatment with imatinib, the patient developed marked leukocytosis, anemia, and thrombocytopenia. Flow cytometry detected an immature cell population comprising ~50% of total cells positive for CD117, CD34 (partial), CD13 (dim), and CD33. A few blasts were also positive for cMPO and negative for CD14, CD64, TdT, Glycophorin A, cytoplasmic CD3, CD19, and other markers. BCR-ABL1 transcript was detected at 56.45% on the International Scale by RT-PCR. Chromosome analysis revealed all cells (20/20) exhibiting t(8;21) leading to a fusion between RUNX1 and RUNX1T1 genes with a maintained t(9;22). FISH analysis confirmed t(8;21) and t(9;22). These findings were consistent with a blast phase of CML.
Results (if a Case Study enter NA)
NA
Conclusion
Progression of CML is frequently accompanied by cytogenetic evolution. However, the development of t(8;21) in Ph+ clones is extremely rare. Only six cases have been previously reported. Misidentifying this blast phase of CML (in the absence of a clinical history of the chronic phase of CML) as AML with recurrent genetic abnormalities is a potential pitfall we should be aware of.
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Affiliation(s)
- P Q Deb
- Pathology, Immunology, and Laboratory Medicine, Rutgers New Jersey Medical School , Newark, New Jersey , United States
| | - J Jiang
- Pathology, Immunology, and Laboratory Medicine, Rutgers New Jersey Medical School , Newark, New Jersey , United States
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Li S, Gao M, Dong H, Jiang Y, Liang W, Jiang J, Ho SH, Li F. Deciphering the fate of antibiotic resistance genes in norfloxacin wastewater treated by a bio-electro-Fenton system. Bioresour Technol 2022; 364:128110. [PMID: 36252757 DOI: 10.1016/j.biortech.2022.128110] [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] [Subscribe] [Scholar Register] [Received: 09/07/2022] [Revised: 10/04/2022] [Accepted: 10/07/2022] [Indexed: 06/16/2023]
Abstract
The misuse of antibiotics has increased the prevalence of antibiotic resistance genes (ARGs), considered a class of critical environmental contaminants due to their ubiquitous and persistent nature. Previous studies reported the potentiality of bio-electro-Fenton processes for antibiotic removal and ARGs control. However, the production and fate of ARGs in bio-electro-Fenton processes triggered by microbial fuel cells are rare. In this study, the norfloxacin (NFLX) average residual concentrations within two days were 2.02, 6.07 and 14.84 mg/L, and the average removal efficiency of NFLX was 79.8 %, 69.6 % and 62.9 % at the initial antibiotic concentrations of 10, 20 and 40 mg/L, respectively. The most prevalent resistance gene type in all processes was the fluoroquinolone antibiotic gene. Furthermore, Proteobacteria was the dominant ARG-carrying bacteria. Overall, this study can provide theoretical support for the efficient treatment of high antibiotics-contained wastewater by bio-electro-Fenton systems to better control ARGs from the perspective of ecological security.
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Affiliation(s)
- Shengnan Li
- College of Environmental Science and Engineering, Nankai University, 38 Tongyan Road, Jinnan District, Tianjin 300350, China; State Key Laboratory of Urban Water Resource and Environment, School of Environment, Harbin Institute of Technology, Harbin, Heilongjiang Province 150090, China
| | - Mingsi Gao
- College of Environmental Science and Engineering, Nankai University, 38 Tongyan Road, Jinnan District, Tianjin 300350, China
| | - Heng Dong
- College of Environmental Science and Engineering, Nankai University, 38 Tongyan Road, Jinnan District, Tianjin 300350, China
| | - Yuxin Jiang
- College of Environmental Science and Engineering, Nankai University, 38 Tongyan Road, Jinnan District, Tianjin 300350, China
| | - Wanting Liang
- College of Environmental Science and Engineering, Nankai University, 38 Tongyan Road, Jinnan District, Tianjin 300350, China
| | - Jiwei Jiang
- College of Environmental Science and Engineering, Nankai University, 38 Tongyan Road, Jinnan District, Tianjin 300350, China
| | - Shih-Hsin Ho
- State Key Laboratory of Urban Water Resource and Environment, School of Environment, Harbin Institute of Technology, Harbin, Heilongjiang Province 150090, China
| | - Fengxiang Li
- College of Environmental Science and Engineering, Nankai University, 38 Tongyan Road, Jinnan District, Tianjin 300350, China.
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Kang A, Jiang J, Li X, Li D, Schuler P, Saha S, Terasaka N. Real-world assessment of anti-platelet therapies for recurrent stroke prevention in non-atrial fibrillation Japanese patients after recent ischemic stroke or transient ischemic attack. Eur Heart J 2022. [DOI: 10.1093/eurheartj/ehac544.2661] [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] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
Abstract
Background
Stroke is one of the leading causes of cardiovascular-related deaths and disability for adults in Japan and is more commonly seen among the elderly. The risks of developing a secondary stroke resulting in permanent damage after the incident ischemic stroke (IS)/transient ischemic stroke (TIA) are very high. It is critical to understand the treatment landscape for the secondary stroke prevention (SSP) and unmet needs of patients with prior IS/ TIA events.
Purpose
To evaluate the antiplatelet therapy (APT) treatment patterns for SSP after first hospitalization for IS/TIA events among the Japanese population.
Methods
Japan's Medical Data Vision (MDV) from Q12011 to Q22021 was used for this study. MDV is a hospital-based claims database covering approximately 35.5 million individuals in the inpatient and outpatient settings among 438 hospitals. Adult patients with an inpatient primary diagnosis of IS/TIA during the index period were identified. Patients require at least one medical claim each quarter within the 1 year before and after index date to ensure longitudinal analysis. Atrial fibrillation patients or patients on oral anticoagulant use were excluded. Patients' characteristics, treatment pattern and duration were evaluated.
Results
Of 18,948 patients in this study, the mean age was 75 years and 36.7% were female; 91.5% were treated with APT and 8.5% were untreated within 90 days of hospital discharge. Among 17,332 APT treated patients, 76.9% were initiated on single APT (SAPT), 22.7% were initiated on dual APT (DAPT), and <1% were initiated on multiple APT (MAPT). The most used SAPT were aspirin (ASA; 33.2%), clopidogrel (28.7%) or cilostazol (14.8%) and the most used DAPT were ASA+clopidogrel (15.1%), ASA+cilostazol (4.2%) or cilostazol+clopidogrel (2.7%). The median duration of APT was 320, 414 and 411 days for patients who initiated ASA, clopidogrel and cilostazol, respectively. The median duration of APT for patients who initiated ASA+clopidogrel, ASA+cilostazol and cilostazol+clopidogrel was 298, 359 and 473 days respectively. Of patients initiated on ASA+clopidogrel, 52.4% were de-escalated to SAPT (71% clopidogrel, 29% ASA; median duration of 20 days); 36.2% of patients initiated on ASA+cilostazol were de-escalated to SAPT within a median of 19 days (84% cilostazol, 16% ASA); lastly, 54.4% of patients initiated on cilostazol+clopidogrel de-escalated to SAPT within a median of 35 days (76% cilostazol, 24% clopidogrel). Two years after initial hospitalization of IS/TIA, 52%-56% discontinued APT treatments among those previously receiving SAPT while 46%-57% of patients receiving DAPT discontinued treatment.
Conclusion
Majority of patients at risk of secondary stroke received APT. Further analyses are needed to explore reasons for early APT discontinuation, for no APT use, and to evaluate outcomes of patients in this study.
Funding Acknowledgement
Type of funding sources: Private company. Main funding source(s): This study was sponsored by Bristol Myers Squibb and Janssen Research & Development, LLC. – Anonymised and used for statistical purposes only
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Affiliation(s)
- A Kang
- Bristol Myers Squibb , Lawrenceville , United States of America
| | - J Jiang
- Bristol Myers Squibb , Lawrenceville , United States of America
| | - X Li
- Bristol Myers Squibb , Lawrenceville , United States of America
| | - D Li
- Bristol Myers Squibb , Lawrenceville , United States of America
| | - P Schuler
- Bristol Myers Squibb , Lawrenceville , United States of America
| | - S Saha
- Mu Sigma Inc , Bangalore , India
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