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Wang L, Shao J, Dong WW, Zheng SS, Zhu BQ, Shu Q, Chen W, Fan LC, Sun J, Gao Y, Hu YF, Wang NR, Wang ZH, Niu TT, Luo Y, Gao J, Tong ML, Hu Y, Xiang W, Zhao ZY, Mao M, Jiang F. [Epidemiological investigation of iron deficiency among preschool children in 10 provinces, autonomous regions, or municipalities in China]. Zhonghua Er Ke Za Zhi 2024; 62:416-422. [PMID: 38623008 DOI: 10.3760/cma.j.cn112140-20240131-00086] [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: 04/17/2024]
Abstract
Objective: To understand the current status of anemia, iron deficiency, and iron-deficiency anemia among preschool children in China. Methods: A cross-sectional study was conducted with a multi-stage stratified sampling method to select 150 streets or townships from 10 Chinese provinces, autonomous regions, or municipalities (East: Jiangsu, Zhejiang, Shandong, and Hainan; Central: Henan; West: Chongqing, Shaanxi, Guizhou, and Xinjiang; Northeast: Liaoning). From May 2022 to April 2023, a total of 21 470 children, including community-based children aged 0.5 to<3.0 years receiving child health care and kindergarten-based children aged 3.0 to<7.0 years, were surveyed. They were divided into 3 age groups: infants (0.5 to<1.0 year), toddlers (1.0 to<3.0 years), and preschoolers (3.0 to<7.0 years). Basic information such as sex and date of birth of the children was collected, and peripheral blood samples were obtained for routine blood tests and serum ferritin measurement. The prevalence rates of anemia, iron deficiency, and iron-deficiency anemia were analyzed, and the prevalence rate differences were compared among different ages, sex, urban and rural areas, and regions using the chi-square test. Results: A total of 21 460 valid responses were collected, including 10 780 boys (50.2%). The number of infants, toddlers, and preschoolers were 2 645 (12.3%), 6 244 (29.1%), and 12 571 (58.6%), respectively. The hemoglobin level was (126.7±14.8) g/L, and the serum ferritin level was 32.3 (18.5, 50.1) μg/L. The overall rates of anemia, iron deficiency, and iron-deficiency anemia were 10.4% (2 230/21 460), 28.3% (6 070/21 460), and 3.9% (845/21 460), respectively. The prevalence rate of anemia was higher for boys than for girls (10.9% (1 173/10 780) vs. 9.9% (1 057/10 680), χ2=5.58, P=0.018), with statistically significant differences in the rates for infants, toddlers and preschoolers (18.0% (475/2 645), 10.6% (662/6 244), and 8.7% (1 093/12 571), respectively, χ2=201.81, P<0.01), and the rate was significantly higher for children in rural than that in urban area (11.8% (1 516/12 883) vs. 8.3% (714/8 577), χ2=65.54, P<0.01), with statistically significant differences in the rates by region (χ2=126.60, P<0.01), with the highest rate of 15.8% (343/2 173) for children in Central region, and the lowest rate of 5.3% (108/2 053) in Northeastern region. The prevalence rates of iron deficiency were 33.8% (895/2 645), 32.2% (2 011/6 244), and 25.2% (3 164/12 571) in infants, toddlers, and preschoolers, respectively, and 30.0% (3 229/10 780) in boys vs. 26.6% (2 841/10 680) in girls, 21.7% (1 913/8 821), 40.0% (870/2 173), 27.1% (2 283/8 413), 48.9% (1 004/2 053) in Eastern, Central, Western, and Northeastern regions, respectively, and each between-group showed a significant statistical difference (χ2=147.71, 29.73, 773.02, all P<0.01). The prevalence rate of iron-deficiency anemia showed a significant statistical difference between urban and rural areas, 2.9% (251/8 577) vs. 4.6% (594/12 883) (χ2=38.62, P<0.01), while the difference in iron deficiency prevalence was not significant (χ2=0.51, P=0.476). Conclusions: There has been a notable improvement in iron deficiency and iron-deficiency anemia among preschool children in China, but the situation remains concerning. Particular attention should be paid to the prevention and control of iron deficiency and iron-deficiency anemia, especially among infants and children in the Central, Western, and Northeastern regions of China.
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Affiliation(s)
- L Wang
- Department of Child Health Care, Children's Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health, Hangzhou 310003, China
| | - J Shao
- Department of Child Health Care, Children's Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health, Hangzhou 310003, China
| | - W W Dong
- Department of Child Health Care, Children's Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health, Hangzhou 310003, China
| | - S S Zheng
- Department of Child Health Care, Children's Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health, Hangzhou 310003, China
| | - B Q Zhu
- Department of Child Health Care, Children's Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health, Hangzhou 310003, China
| | - Q Shu
- Department of Child Health Care, Children's Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health, Hangzhou 310003, China
| | - W Chen
- Department of Child Health Care, the Third Affiliated Hospital of Zhengzhou University (Maternal and Child Health Hospital of Henan Province), Zhengzhou 450052, China
| | - L C Fan
- Department of Child Health Care, Hainan Women and Children's Medical Center, Haikou 570206, China
| | - J Sun
- Department of Child Health Medicine, Dalian Women and Children's Medical Group, Dalian 116033, China
| | - Y Gao
- Department of Child Health Care, Urumqi Maternal and Child Health Hospital, Urumqi 830001, China
| | - Y F Hu
- Department of Children's Health Care, the First Affiliated Hospital of Nanjing Medical University, Jiangsu Province Hospital, Jiangsu Women and Children Health Hospital, Nanjing 210036, China
| | - N R Wang
- Department of Child Health Care, Chongqing Health Center for Women and Children, Women and Children's Hospital of Chongqing Medical University, Chongqing 401147, China
| | - Z H Wang
- Health Center of the Children, Xi'an People's Hospital (Xi'an Fourth Hospital), Xi'an 710004, China
| | - T T Niu
- Department of Child Health Care, Maternal and Child Health Care Hospital of Shandong Province, Jinan 250014, China
| | - Y Luo
- Department of Child Health Care, Guiyang Maternal and Child Health Care Hospital, Guiyang 550001, China
| | - J Gao
- Department of Hematology/Oncology, West China Second University Hospital, Sichuan University, National Health Commission Key Laboratory of Chronobiology, Sichuan University, Chengdu 610041, China
| | - M L Tong
- Department of Child Health Care, Women's Hospital of Nanjing Medical University (Nanjing Women and Children's Healthcare Hospital), Nanjing 210004, China
| | - Y Hu
- Health Care Center, Beijing Children's Hospital, Capital Medical University, Beijing 100045, China
| | - W Xiang
- Department of Child Health Care, Hainan Women and Children's Medical Center, Haikou 570206, China
| | - Z Y Zhao
- Department of Child Health Care, Children's Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health, Hangzhou 310003, China
| | - M Mao
- Department of Child Health Care, West China Second University Hospital, Sichun University, Chengdu 610041, China
| | - F Jiang
- Department of Developmental and Behavioral Pediatrics, Shanghai Children's Medical Center, Shanghai Jiao Tong University School of Medicine, National Children's Medical Center, Shanghai 200127, China
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Wang X, Xue L, Hua L, Shao J, Yan R, Yao Z, Lu Q. Structure-function coupling and hierarchy-specific antidepressant response in major depressive disorder. Psychol Med 2024:1-10. [PMID: 38571298 DOI: 10.1017/s0033291724000801] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 04/05/2024]
Abstract
BACKGROUND Extensive research has explored altered structural and functional networks in major depressive disorder (MDD). However, studies examining the relationships between structure and function yielded heterogeneous and inconclusive results. Recent work has suggested that the structure-function relationship is not uniform throughout the brain but varies across different levels of functional hierarchy. This study aims to investigate changes in structure-function couplings (SFC) and their relevance to antidepressant response in MDD from a functional hierarchical perspective. METHODS We compared regional SFC between individuals with MDD (n = 258) and healthy controls (HC, n = 99) using resting-state functional magnetic resonance imaging and diffusion tensor imaging. We also compared antidepressant non-responders (n = 55) and responders (n = 68, defined by a reduction in depressive severity of >50%). To evaluate variations in altered and response-associated SFC across the functional hierarchy, we ranked significantly different regions by their principal gradient values and assessed patterns of increase or decrease along the gradient axis. The principal gradient value, calculated from 219 healthy individuals in the Human Connectome Project, represents a region's position along the principal gradient axis. RESULTS Compared to HC, MDD patients exhibited increased SFC in unimodal regions (lower principal gradient) and decreased SFC in transmodal regions (higher principal gradient) (p < 0.001). Responders primarily had higher SFC in unimodal regions and lower SFC in attentional networks (median principal gradient) (p < 0.001). CONCLUSIONS Our findings reveal opposing SFC alterations in low-level unimodal and high-level transmodal networks, underscoring spatial variability in MDD pathology. Moreover, hierarchy-specific antidepressant effects provide valuable insights into predicting treatment outcomes.
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Affiliation(s)
- Xinyi Wang
- School of Biological Sciences & Medical Engineering, Southeast University, Nanjing, China
- Child Development and Learning Science, Key Laboratory of Ministry of Education, Southeast University, Nanjing, China
| | - Li Xue
- School of Biological Sciences & Medical Engineering, Southeast University, Nanjing, China
- Child Development and Learning Science, Key Laboratory of Ministry of Education, Southeast University, Nanjing, China
| | - Lingling Hua
- Department of Psychiatry, the Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China
| | - Junneng Shao
- School of Biological Sciences & Medical Engineering, Southeast University, Nanjing, China
- Child Development and Learning Science, Key Laboratory of Ministry of Education, Southeast University, Nanjing, China
| | - Rui Yan
- Department of Psychiatry, the Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China
| | - Zhijian Yao
- Department of Psychiatry, the Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China
- Nanjing Brain Hospital, Clinical Teaching Hospital of Medical School, Nanjing University, Nanjing, China
| | - Qing Lu
- School of Biological Sciences & Medical Engineering, Southeast University, Nanjing, China
- Child Development and Learning Science, Key Laboratory of Ministry of Education, Southeast University, Nanjing, China
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Wang X, Xue L, Shao J, Dai Z, Hua L, Yan R, Yao Z, Lu Q. Distinct MRI-based functional and structural connectivity for antidepressant response prediction in major depressive disorder. Clin Neurophysiol 2024; 160:19-27. [PMID: 38367310 DOI: 10.1016/j.clinph.2024.02.004] [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: 05/31/2023] [Revised: 12/28/2023] [Accepted: 02/06/2024] [Indexed: 02/19/2024]
Abstract
OBJECTIVE Emerging studies have identified treatment-related connectome predictors in major depressive disorder (MDD). However, quantifying treatment-responsive patterns in structural connectivity (SC) and functional connectivity (FC) simultaneously remains underexplored. We aimed to evaluate whether spatial distributions of FC and SC associated treatment responses are shared or unique. METHODS Diffusion tensor imaging and resting-state functional magnetic resonance imaging were collected from 210 patients with MDD at baseline. We separately developed connectome-based prediction models (CPM) to predict reduction of depressive severity after 6-week monotherapy based on structural, functional, and combined connectomes, then validated them on the external dataset. We identified the predictive SC and FC from CPM with high occurrence frequencies during the cross-validation. RESULTS Structural connectomes (r = 0.2857, p < 0.0001), functional connectomes (r = 0.2057, p = 0.0025), and their combined CPM (r = 0.4, p < 0.0001) can significantly predict a reduction of depressive severity. We didn't find shared connectivity between predictive FC and SC. Specifically, the most predictive FC stemmed from the default mode network, while predictive SC was mainly characterized by within-network SC of fronto-limbic networks. CONCLUSIONS These distinct patterns suggest that SC and FC capture unique connectivity concerning the antidepressant response. SIGNIFICANCE Our findings provide comprehensive insights into the neurophysiology of antidepressants response.
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Affiliation(s)
- Xinyi Wang
- School of Biological Sciences & Medical Engineering, Southeast University, Nanjing 210096, China; Child Development and Learning Science, Key Laboratory of Ministry of Education, Nanjing 210096, China
| | - Li Xue
- School of Biological Sciences & Medical Engineering, Southeast University, Nanjing 210096, China; Child Development and Learning Science, Key Laboratory of Ministry of Education, Nanjing 210096, China
| | - Junneng Shao
- School of Biological Sciences & Medical Engineering, Southeast University, Nanjing 210096, China; Child Development and Learning Science, Key Laboratory of Ministry of Education, Nanjing 210096, China
| | - Zhongpeng Dai
- School of Biological Sciences & Medical Engineering, Southeast University, Nanjing 210096, China; Child Development and Learning Science, Key Laboratory of Ministry of Education, Nanjing 210096, China
| | - Lingling Hua
- Department of Psychiatry, the Affiliated Brain Hospital of Nanjing Medical University, Nanjing 210029, China
| | - Rui Yan
- Department of Psychiatry, the Affiliated Brain Hospital of Nanjing Medical University, Nanjing 210029, China
| | - Zhijian Yao
- Department of Psychiatry, the Affiliated Brain Hospital of Nanjing Medical University, Nanjing 210029, China; Nanjing Brain Hospital, Medical School of Nanjing University, Nanjing 210093, China.
| | - Qing Lu
- School of Biological Sciences & Medical Engineering, Southeast University, Nanjing 210096, China; Child Development and Learning Science, Key Laboratory of Ministry of Education, Nanjing 210096, China.
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Shao J, Qin J, Wang H, Sun Y, Zhang W, Wang X, Wang T, Xue L, Yao Z, Lu Q. Capturing the Individual Deviations From Normative Models of Brain Structure for Depression Diagnosis and Treatment. Biol Psychiatry 2024; 95:403-413. [PMID: 37579934 DOI: 10.1016/j.biopsych.2023.08.005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/19/2023] [Revised: 07/20/2023] [Accepted: 08/03/2023] [Indexed: 08/16/2023]
Abstract
BACKGROUND The high heterogeneity of depression prevents us from obtaining reproducible and definite anatomical maps of brain structural changes associated with the disorder, which limits the individualized diagnosis and treatment of patients. In this study, we investigated the clinical issues related to depression according to individual deviations from normative ranges of gray matter volume. METHODS We enrolled 1092 participants, including 187 patients with depression and 905 healthy control participants. Structural magnetic resonance imaging data of healthy control participants from the Human Connectome Project (n = 510) and REST-meta-MDD Project (n = 229) were used to establish a normative model across the life span in adults 18 to 65 years old for each brain region. Deviations from the normative range for 187 patients and 166 healthy control participants recruited from two local hospitals were captured as normative probability maps, which were used to identify the disease risk and treatment-related latent factors. RESULTS In contrast to case-control results, our normative modeling approach revealed highly individualized patterns of anatomic abnormalities in depressed patients (less than 11% extreme deviation overlapping for any regions). Based on our classification framework, models trained with individual normative probability maps (area under the receiver operating characteristic curve range, 0.7146-0.7836) showed better performance than models trained with original gray matter volume values (area under the receiver operating characteristic curve range, 0.6800-0.7036), which was verified in an independent external test set. Furthermore, different latent brain structural factors in relation to antidepressant treatment were revealed by a Bayesian model based on normative probability maps, suggesting distinct treatment response and inclination. CONCLUSIONS Capturing personalized deviations from a normative range could help in understanding the heterogeneous neurobiology of depression and thus guide clinical diagnosis and treatment of depression.
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Affiliation(s)
- Junneng Shao
- School of Biological Sciences & Medical Engineering, Southeast University, Nanjing, China; Key Laboratory of Child Development and Learning Science, Ministry of Education, Southeast University, Nanjing, China
| | - Jiaolong Qin
- School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing, China
| | - Huan Wang
- School of Biological Sciences & Medical Engineering, Southeast University, Nanjing, China; Key Laboratory of Child Development and Learning Science, Ministry of Education, Southeast University, Nanjing, China
| | - Yurong Sun
- School of Biological Sciences & Medical Engineering, Southeast University, Nanjing, China; Key Laboratory of Child Development and Learning Science, Ministry of Education, Southeast University, Nanjing, China
| | - Wei Zhang
- School of Biological Sciences & Medical Engineering, Southeast University, Nanjing, China; Key Laboratory of Child Development and Learning Science, Ministry of Education, Southeast University, Nanjing, China
| | - Xinyi Wang
- School of Biological Sciences & Medical Engineering, Southeast University, Nanjing, China; Key Laboratory of Child Development and Learning Science, Ministry of Education, Southeast University, Nanjing, China
| | - Ting Wang
- School of Biological Sciences & Medical Engineering, Southeast University, Nanjing, China; Key Laboratory of Child Development and Learning Science, Ministry of Education, Southeast University, Nanjing, China
| | - Li Xue
- School of Biological Sciences & Medical Engineering, Southeast University, Nanjing, China; Key Laboratory of Child Development and Learning Science, Ministry of Education, Southeast University, Nanjing, China
| | - Zhijian Yao
- Department of Psychiatry, the Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China; Nanjing Brain Hospital, Medical School of Nanjing University, Nanjing, China.
| | - Qing Lu
- School of Biological Sciences & Medical Engineering, Southeast University, Nanjing, China; Key Laboratory of Child Development and Learning Science, Ministry of Education, Southeast University, Nanjing, China.
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Ye HP, Fu H, Shao J, Shan XY, Zhang L, Zhang L. [The method of determination for 2, 3-Butanedione in the air of workplace by high performance liquid chromatography with derivatization]. Zhonghua Lao Dong Wei Sheng Zhi Ye Bing Za Zhi 2024; 42:129-132. [PMID: 38403422 DOI: 10.3760/cma.j.cn121094-20221201-00574] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 02/27/2024]
Abstract
Objective: To establish a method for the determination of 2, 3-Butanedione (BUT) in the air of workplace, which including the process of collection by absorption in phosphoric acid aqueous solution and the process of analysis and detection by high performance liquid chromatography with derivatization. Methods: In October 2022, a porous glass plate absorption tube containing 10 ml of 0.01% phosphoric acid solution was used to collect BUT in the air of the workplace at a flow rate of 0.2 L/min. The absorption solution was derived by 2, 4-dinitrophenylhydrazine for 75 min and separated on a SB-C18 column (250 mm×4.6 mm, 5 μm) . At the column temperature of 30 ℃, the mixture of acetonitrile-water (V∶V, 1∶1) was eluted at the flow rate of 1.0 ml/min. It was detected by UV detector (λ=365 nm) , qualitatived by retention time and quantitatived by external standard. Results: It showed that BUT in phosphoric acid aqueous solution could be stored for at least 7 d at 4 ℃. There was a linear relationship within the determination range of 0.05-6.00 μg/ml, the linear regression equation was y=89.610x+0.133, r=0.9999. The sampling absorption efficiencies were 98.33%-100.00%, the detection limit of the method was 0.005 μg/ml, the minimum detection concentration was 0.016 mg/m(3) (based on V(0)=3.0 L) . The recovery rates were 95.96%-102.44%, the intra batch precision were 4.36%-7.78%, and the inter batch precision were 4.96%-6.06%. Conclusion: The method has the advantages of simple operation, high sensitivity and good accuracy. It can prevent the loss and degradation of BUT. It can be used for the determination of BUT in the air of workplace.
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Affiliation(s)
- H P Ye
- Health Testing Department, Hangzhou Occupational Disease Prevention and Control Hospital, Hangzhou 310014, China
| | - H Fu
- Health Testing Department, Hangzhou Occupational Disease Prevention and Control Hospital, Hangzhou 310014, China
| | - J Shao
- Health Testing Department, Hangzhou Occupational Disease Prevention and Control Hospital, Hangzhou 310014, China
| | - X Y Shan
- Health Testing Department, Hangzhou Occupational Disease Prevention and Control Hospital, Hangzhou 310014, China
| | - L Zhang
- Health Testing Department, Hangzhou Occupational Disease Prevention and Control Hospital, Hangzhou 310014, China
| | - L Zhang
- Health Testing Department, Hangzhou Occupational Disease Prevention and Control Hospital, Hangzhou 310014, China
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Wang H, Zhu R, Dai Z, Shao J, Xue L, Sun Y, Wang T, Liao Q, Yao Z, Lu Q. The altered temporal properties of dynamic functional connectivity associated with suicide attempt in bipolar disorders. Prog Neuropsychopharmacol Biol Psychiatry 2024; 129:110898. [PMID: 38030032 DOI: 10.1016/j.pnpbp.2023.110898] [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: 07/28/2023] [Revised: 09/15/2023] [Accepted: 11/16/2023] [Indexed: 12/01/2023]
Abstract
OBJECTIVE The suicide risk in bipolar disorder (BD) is the highest among psychiatric disorders, and the neurobiological mechanism of suicide in BD remains unclear. The study aimed to investigate the underlying relevance between the implicated abnormalities of dynamic functional connectivity (FC) and suicide attempt (SA) in BD. METHODS We used the sliding window method to analyze the dynamic FC patterns from resting-state functional MRI data in 81 healthy controls (HC) and 114 BD patients (50 with SA and 64 with none SA). Then, the temporal properties of dynamic FC and the relationship between altered measures and clinical variables were explored. RESULTS We found that one of the five captured brain functional states was more associated with SA. The SA patients showed significantly increased fractional window and dwell time in the suicide-related state, along with increased number of state transitions compared with none SA (NSA). In addition, the connections within subcortical network-subcortical network (SubC-SubC), default mode network-subcortical network (DMN-SubC), and attention network-subcortical network (AN-SubC) were significantly changed in SA patients relative to NSA and HC in the suicide-related state. Crucially, the above-altered measures were significantly correlated with suicide risk. CONCLUSIONS Our findings suggested that the impaired dynamic FC within SubC-SubC, DMN-SubC, and AN-SubC were the important underlying mechanism in understanding SA for BD patients. It highlights the temporal properties of whole-brain dynamic FC could serve as the valuable biomarker for suicide risk assessment in BD.
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Affiliation(s)
- Huan Wang
- School of Computer Science and Artificial Intelligence, Changzhou University, Changzhou 213164, China
| | - Rongxin Zhu
- Department of Psychiatry, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing 210029, China
| | - Zhongpeng Dai
- School of Biological Sciences & Medical Engineering, Southeast University, Nanjing 210096, China; Child Development and Learning Science, Key Laboratory of Ministry of Education, China
| | - Junneng Shao
- School of Biological Sciences & Medical Engineering, Southeast University, Nanjing 210096, China; Child Development and Learning Science, Key Laboratory of Ministry of Education, China
| | - Li Xue
- School of Biological Sciences & Medical Engineering, Southeast University, Nanjing 210096, China; Child Development and Learning Science, Key Laboratory of Ministry of Education, China
| | - Yurong Sun
- School of Biological Sciences & Medical Engineering, Southeast University, Nanjing 210096, China; Child Development and Learning Science, Key Laboratory of Ministry of Education, China
| | - Ting Wang
- School of Biological Sciences & Medical Engineering, Southeast University, Nanjing 210096, China; Child Development and Learning Science, Key Laboratory of Ministry of Education, China
| | - Qian Liao
- School of Biological Sciences & Medical Engineering, Southeast University, Nanjing 210096, China; Child Development and Learning Science, Key Laboratory of Ministry of Education, China
| | - Zhijian Yao
- Department of Psychiatry, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing 210029, China; Nanjing Brain Hospital, Medical School of Nanjing University, Nanjing 210093, China.
| | - Qing Lu
- School of Biological Sciences & Medical Engineering, Southeast University, Nanjing 210096, China; Child Development and Learning Science, Key Laboratory of Ministry of Education, China.
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Wang H, Zhu R, Tian S, Shao J, Dai Z, Xue L, Sun Y, Chen Z, Yao Z, Lu Q. Classification of bipolar disorders using the multilayer modularity in dynamic minimum spanning tree from resting state fMRI. Cogn Neurodyn 2023; 17:1609-1619. [PMID: 37974586 PMCID: PMC10640554 DOI: 10.1007/s11571-022-09907-x] [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] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/27/2021] [Revised: 07/19/2022] [Accepted: 10/28/2022] [Indexed: 12/04/2022] Open
Abstract
The diagnosis of bipolar disorders (BD) mainly depends on the clinical history and behavior observation, while only using clinical tools often limits the diagnosis accuracy. The study aimed to create a novel BD diagnosis framework using multilayer modularity in the dynamic minimum spanning tree (MST). We collected 45 un-medicated BD patients and 47 healthy controls (HC). The sliding window approach was utilized to construct dynamic MST via resting-state functional magnetic resonance imaging (fMRI) data. Firstly, we used three null models to explore the effectiveness of multilayer modularity in dynamic MST. Furthermore, the module allegiance exacted from dynamic MST was applied to train a classifier to discriminate BD patients. Finally, we explored the influence of the FC estimator and MST scale on the performance of the model. The findings indicated that multilayer modularity in the dynamic MST was not a random process in the human brain. And the model achieved an accuracy of 83.70% for identifying BD patients. In addition, we found the default mode network, subcortical network (SubC), and attention network played a key role in the classification. These findings suggested that the multilayer modularity in dynamic MST could highlight the difference between HC and BD patients, which opened up a new diagnostic tool for BD patients. Supplementary Information The online version contains supplementary material available at 10.1007/s11571-022-09907-x.
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Affiliation(s)
- Huan Wang
- School of Biological Sciences & Medical Engineering, Southeast University, No.2 Sipailou, Nanjing, 210096 Jiangsu Province China
- Child Development and Learning Science, Key Laboratory of Ministry of Education, Nanjing, China
| | - Rongxin Zhu
- Department of Psychiatry, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, 210029 China
| | - Shui Tian
- School of Biological Sciences & Medical Engineering, Southeast University, No.2 Sipailou, Nanjing, 210096 Jiangsu Province China
- Child Development and Learning Science, Key Laboratory of Ministry of Education, Nanjing, China
| | - Junneng Shao
- School of Biological Sciences & Medical Engineering, Southeast University, No.2 Sipailou, Nanjing, 210096 Jiangsu Province China
- Child Development and Learning Science, Key Laboratory of Ministry of Education, Nanjing, China
| | - Zhongpeng Dai
- School of Biological Sciences & Medical Engineering, Southeast University, No.2 Sipailou, Nanjing, 210096 Jiangsu Province China
- Child Development and Learning Science, Key Laboratory of Ministry of Education, Nanjing, China
| | - Li Xue
- School of Biological Sciences & Medical Engineering, Southeast University, No.2 Sipailou, Nanjing, 210096 Jiangsu Province China
- Child Development and Learning Science, Key Laboratory of Ministry of Education, Nanjing, China
| | - Yurong Sun
- School of Biological Sciences & Medical Engineering, Southeast University, No.2 Sipailou, Nanjing, 210096 Jiangsu Province China
- Child Development and Learning Science, Key Laboratory of Ministry of Education, Nanjing, China
| | - Zhilu Chen
- Department of Psychiatry, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, 210029 China
| | - Zhijian Yao
- School of Biological Sciences & Medical Engineering, Southeast University, No.2 Sipailou, Nanjing, 210096 Jiangsu Province China
- Department of Psychiatry, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, 210029 China
- Nanjing Brain Hospital, Medical School of Nanjing University, Nanjing, 210093 China
| | - Qing Lu
- School of Biological Sciences & Medical Engineering, Southeast University, No.2 Sipailou, Nanjing, 210096 Jiangsu Province China
- Child Development and Learning Science, Key Laboratory of Ministry of Education, Nanjing, China
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Zhang XY, Xu HQ, Wang CF, Shao J, Wan YH, Tao FB. [Application of entropy weight TOPSIS comprehensive method in the evaluation of students' physical health level]. Zhonghua Yu Fang Yi Xue Za Zhi 2023; 57:997-1003. [PMID: 37482736 DOI: 10.3760/cma.j.cn112150-20220712-00712] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Subscribe] [Scholar Register] [Indexed: 07/25/2023]
Abstract
Objective: To comprehensively evaluate the physical health level of students of different school-age segments in four regions of Anhui province using the entropy weight approximation ideal solution ranking method (TOPSIS), and to provide a scientific method and basis for conducting school health work evaluation. Methods: Using the physical fitness survey data of four regions in Anhui province, the entropy weight method was used to draw the weights of various indicators for different school-age segments of men and women. Then, the TOPSIS method was used to evaluate the school-age segments of men and women in the four regions. Finally, the physical health level of students in four regions was classified according to the results of entropy weight TOPSIS and the rank sum ratio method. Results: A total of 10 127 students were included in this study, with an average age of (11.85±3.82) years, including 5 050 males (49.8%) and 5 072 urban students (50.1%). The results of the entropy weight method showed that the weight of body mass index of boys was similar to that of girls in each school-age segment. According to the TOPSIS and rank sum ratio analysis, the physical health level of students in the four regions of Anhui province was different. The physical health score of Suzhou was 0.617 4 points, which was classified as the best grade. The scores of Hefei and Wuhu were 0.556 3 and 0.411 2, which were classified as middle. Jiju City scored 0.381 9 points, which was classified as poor. Conclusion: TOPSIS combined with rank sum ratio can reflect the level of students' physical health, which can be applied to the evaluation of students' physical health and provide a basis for monitoring students' physical health.
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Affiliation(s)
- X Y Zhang
- Department of Maternal, Child and Adolescent Health, School of Public Health, Anhui Medical University, Hefei 230032, China
| | - H Q Xu
- Department of Maternal, Child and Adolescent Health, School of Public Health, Anhui Medical University, Hefei 230032, China
| | - C F Wang
- Department of Maternal, Child and Adolescent Health, School of Public Health, Anhui Medical University, Hefei 230032, China
| | - J Shao
- Department of Maternal, Child and Adolescent Health, School of Public Health, Anhui Medical University, Hefei 230032, China
| | - Y H Wan
- Department of Maternal, Child and Adolescent Health, School of Public Health, Anhui Medical University, Hefei 230032, China Key Laboratory of Birth Population Health, Ministry of Education/Anhui Provincial Key Laboratory of Population Health and Eugenics/Key Laboratory of Gametes and Reproductive Tract Abnormalities, National Health Commission, Hefei 230032, China
| | - F B Tao
- Department of Maternal, Child and Adolescent Health, School of Public Health, Anhui Medical University, Hefei 230032, China Key Laboratory of Birth Population Health, Ministry of Education/Anhui Provincial Key Laboratory of Population Health and Eugenics/Key Laboratory of Gametes and Reproductive Tract Abnormalities, National Health Commission, Hefei 230032, China
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9
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Liu AN, Shen HQ, Xu CF, Jiang L, Shao J, Shu Q, Fu JF, Ni Y. [Characteristics of serum bile acids among healthy children in Zhejiang province]. Zhonghua Er Ke Za Zhi 2023; 61:509-514. [PMID: 37312461 DOI: 10.3760/cma.j.cn112140-20230127-00056] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
Objective: To characterize the serum bile acid profiles of healthy children in Zhejiang Province. Methods: A cross-sectional study was conducted on 245 healthy children who underwent imaging and laboratory biochemical tests during routine physical examinations at the Children's Hospital of Zhejiang University School of Medicine from January 2020 to July 2022. Overnight fasting venous blood samples were collected, and the concentrations of 18 individual bile acids in the serum were accurately quantitated using tandem mass spectrometry. The concentration difference of bile acid were compared between different genders and to explore the correlation between age and bile acid levels. Used the Mann-Whitney U test for intergroup comparison and Spearman test to correlation analysis. Results: A total of 245 health children with a age of 10 (8, 12) years including 125 boys and 120 girls. There were no significant differences in levels of total bile acids, primary and secondary bile acids, free and conjugated bile acids between the two gender groups (all P>0.05). The serum concentrations of ursodeoxycholic acid and glycoursodeoxycholic acid in girls were significantly higher than those in boys (199.0 (66.9, 276.5) vs. 154.7 (49.3, 205.0) nmol/L, 274.0 (64.8, 308.0) vs. 181.0 (43.8, 209.3) nmol/L, Z=2.06, 2.71, both P<0.05). The serum taurolithocholic acid in both boys and girls were positively correlated with age (r=0.31, 0.32, both P<0.05). The serum chenodeoxycholic acid and glycochenodeoxycholic acid in the boys group were positively correlated with age (r=0.20, 0.23, both P<0.05), whereas the serum tauroursodeoxycholic acid in the girls group was negatively correlated with age (r=-0.27, P<0.05), and the serum cholic acid was positively correlated with age (r=0.34, P<0.05). Conclusions: The total bile acid levels are relatively stable in healthy children in Zhejiang province. However, individual bile acids showed gender differences and were correlated with age.
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Affiliation(s)
- A N Liu
- Department of Clinical Laboratory, Children's Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health, Hangzhou 310005, China
| | - H Q Shen
- Department of Clinical Laboratory, Children's Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health, Hangzhou 310005, China
| | - C F Xu
- Department of Clinical Laboratory, Children's Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health, Hangzhou 310005, China
| | - L Jiang
- Department of Clinical Laboratory, Children's Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health, Hangzhou 310005, China
| | - J Shao
- Department of Child Healthcare, Children's Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health, Hangzhou 310005, China
| | - Q Shu
- Department of Clinical Laboratory, Children's Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health, Hangzhou 310005, China
| | - J F Fu
- Department of Clinical Laboratory, Children's Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health, Hangzhou 310005, China
| | - Y Ni
- Department of Clinical Laboratory, Children's Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health, Hangzhou 310005, China
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Tian S, Zhu R, Chen Z, Wang H, Chattun MR, Zhang S, Shao J, Wang X, Yao Z, Lu Q. Prediction of suicidality in bipolar disorder using variability of intrinsic brain activity and machine learning. Hum Brain Mapp 2023; 44:2767-2777. [PMID: 36852459 PMCID: PMC10089096 DOI: 10.1002/hbm.26243] [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: 07/27/2022] [Revised: 02/03/2023] [Accepted: 02/10/2023] [Indexed: 03/01/2023] Open
Abstract
Bipolar disorder (BD) is associated with marked suicidal susceptibility, particularly during a major depressive episode. However, the evaluation of suicidal risk remains challenging since it relies mainly on self-reported information from patients. Hence, it is necessary to complement neuroimaging features with advanced machine learning techniques in order to predict suicidal behavior in BD patients. In this study, a total of 288 participants, including 75 BD suicide attempters, 101 BD nonattempters and 112 healthy controls, underwent a resting-state functional magnetic resonance imaging (rs-fMRI). Intrinsic brain activity was measured by amplitude of low-frequency fluctuation (ALFF). We trained and tested a two-level k-nearest neighbors (k-NN) model based on resting-state variability of ALFF with fivefold cross-validation. BD suicide attempters had increased dynamic ALFF values in the right anterior cingulate cortex, left thalamus and right precuneus. Compared to other machine learning methods, our proposed framework had a promising performance with 83.52% accuracy, 78.75% sensitivity and 87.50% specificity. The trained models could also replicate and validate the results in an independent cohort with 72.72% accuracy. These findings based on a relatively large data set, provide a promising way of combining fMRI data with machine learning technique to reliably predict suicide attempt at an individual level in bipolar depression. Overall, this work might enhance our understanding of the neurobiology of suicidal behavior by detecting clinically defined disruptions in the dynamics of instinct brain activity.
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Affiliation(s)
- Shui Tian
- Department of RadiologyThe First Affiliated Hospital of Nanjing Medical UniversityNanjingChina
- Laboratory for Artificial Intelligence in Medical Imaging (LAIMI)Nanjing Medical UniversityNanjingChina
| | - Rongxin Zhu
- Department of PsychiatryThe Affiliated Nanjing Brain Hospital of Nanjing Medical UniversityNanjingChina
| | - Zhilu Chen
- Department of PsychiatryThe Affiliated Nanjing Brain Hospital of Nanjing Medical UniversityNanjingChina
| | - Huan Wang
- School of Biological Sciences and Medical EngineeringSoutheast UniversityNanjingChina
- Child Development and Learning ScienceKey Laboratory of Ministry of EducationBeijingChina
| | - Mohammad Ridwan Chattun
- Department of PsychiatryThe Affiliated Nanjing Brain Hospital of Nanjing Medical UniversityNanjingChina
| | - Siqi Zhang
- School of Biological Sciences and Medical EngineeringSoutheast UniversityNanjingChina
- Child Development and Learning ScienceKey Laboratory of Ministry of EducationBeijingChina
| | - Junneng Shao
- School of Biological Sciences and Medical EngineeringSoutheast UniversityNanjingChina
- Child Development and Learning ScienceKey Laboratory of Ministry of EducationBeijingChina
| | - Xinyi Wang
- School of Biological Sciences and Medical EngineeringSoutheast UniversityNanjingChina
- Child Development and Learning ScienceKey Laboratory of Ministry of EducationBeijingChina
| | - Zhijian Yao
- Department of PsychiatryThe Affiliated Nanjing Brain Hospital of Nanjing Medical UniversityNanjingChina
- Nanjing Brain HospitalMedical School of Nanjing UniversityNanjingChina
| | - Qing Lu
- School of Biological Sciences and Medical EngineeringSoutheast UniversityNanjingChina
- Child Development and Learning ScienceKey Laboratory of Ministry of EducationBeijingChina
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11
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Neustaeter A, Shao J, Xue M, Antonio Hernández Rocha C, Lee SH, Leibovitzh H, Madsen K, Meddings JB, Espin-Garcia O, Griffiths AM, Moayyedi P, Steinhart AH, Panancionne R, Huynh H, Jacobson K, Aumais G, Mack D, Bernstein C, Marshall JK, Xu W, Turpin W, Croitoru K. A238 BILE ACID COMPOSITION AND DIETARY FAT: IMPLICATIONS FOR CROHN’S DISEASE IN A COHORT OF HEALTHY FIRST-DEGREE RELATIVES. J Can Assoc Gastroenterol 2023. [PMCID: PMC9991268 DOI: 10.1093/jcag/gwac036.238] [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: 03/09/2023] Open
Abstract
Background Crohn’s disease (CD) is a chronic relapsing inflammatory disease of the gastrointestinal tract. The etiology of CD may arise from complex interactions including host genetics, diet, and the intestinal microbiome. Increased consumption of saturated fats, characteristic of the Western diet, is a known risk factor for CD. Dietary fat (DF) is absorbed by the host through the release of primary bile acids (PBAs) and bio-transformed by the microbiome into secondary bile acids (SBAs). Altogether, bile acids (BAs) can act as signaling molecules involved in host immune regulation and potentially in CD onset. Purpose To investigate the relationship between CD risk, BAs, and DF, and evaluate the predictive performance of CD onset of these factors by developing machine learning models. Method We used samples healthy first-degree relatives (FDRs) recruited as part of the Crohn’s Colitis Canada- Genes, Environment, Microbial (GEM) project. Those who developed CD (n=87) were matched 1:4 by age, sex, follow-up time, and geographic location with control FDRs remaining healthy (n=347). Serum, urine, and stool BA were measured using ultrahigh Performance Liquid Chromatography-Tandem Mass Spectroscopy. DF types were derived from food frequency questionnaire data. We used conditional logistic regressions to identify associations between CD onset, BAs (n=93), and DFs (n=9). We further explored the relationships of significant CD-related BAs and DF via Generalized Estimation Equations. Finally, we used a tree-based machine-learning algorithm (XGBoost) with 5-fold cross-validation to assess the prediction performance of CD onset using BA from all sources as well as DF. Two-sided p<0.05 was considered significant. Result(s) In total, 10 of 93 BAs, and two of nine DFs were significantly associated with increased odds of CD onset (p<0.05). Additionally, five BAs were significantly associated with DF (p<0.05). Serum-derived BAs had the best predictive performance for CD, with a mean AUC of 0.70 [95% CI: 0.63;0.76], followed by stool derived BAs with a mean AUC= 0.65 [0.55;0.75], and followed by urine derived Bas with a mean AUC= 0.57 [0.48;0.66]. Lastly DF was not a predictive marker of CD onset with a mean AUC= 0.50 [0.41;0.60]. Conclusion(s) This study suggests that BAs are associated with the pathogenesis of CD and the effects may be influenced by DF. Serum-derived BAs may be able to better predict the risk of CD than other stool or urine derived BA, while DF is not directly implicated in CD risk. Submitted on behalf of the CCC-GEM consortium. Funding Crohn’s and Colitis Canada Genetics Environment Microbial (CCC-GEM) III The Leona M. and Harry B. Helmsley Charitable Trust Kenneth Croitoru is the recipient of the Canada Research Chair in Inflammatory Bowel Diseases The International Organization for the Study of Inflammatory Bowel Diseases (IOIBD) Jingcheng Shao is the recipient of a Data Science Institute Summer Undergraduate Data Science award Disclosure of Interest None Declared
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Affiliation(s)
| | - J Shao
- University of Toronto, Toronto
| | - M Xue
- University of Toronto, Toronto
| | | | | | | | | | | | | | | | | | | | | | - H Huynh
- University of Alberta, Calgary
| | - K Jacobson
- University of British Columbia, Vancouver
| | | | - D Mack
- University of Ottawa, Ottawa
| | | | | | - W Xu
- University of Toronto, Toronto
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12
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Kong H, Chung M, Doran DS, Ha G, Kim SH, Kim JH, Liu W, Lu X, Power J, Seok JM, Shin S, Shao J, Whiteford C, Wisniewski E. Fabrication of THz corrugated wakefield structure and its high power test. Sci Rep 2023; 13:3207. [PMID: 36828881 PMCID: PMC9958108 DOI: 10.1038/s41598-023-29997-9] [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: 10/11/2022] [Accepted: 02/14/2023] [Indexed: 02/26/2023] Open
Abstract
We present overall process for developing terahertz (THz) corrugated structure and its beam-based measurement results. 0.2-THz corrugated structures were fabricated by die stamping method as the first step demonstration towards GW THz radiation source and GV/m THz wakefield accelerator. 150-[Formula: see text]m thick disks were produced from an OFHC (C10100) foil by stamping. Two types of disks were stacked alternately to form 46 mm structure with [Formula: see text] 170 corrugations. Custom assembly was designed to provide diffusion bonding with a high precision alignment of disks. The compliance of the fabricated structure have been verified through beam-based wakefield measurement at Argonne Wakefield Accelerator Facility. Both measured longitudinal and transverse wakefield showed good agreement with simulated wakefields. Measured peak gradients, 9.4 MV/m/nC for a long single bunch and 35.4 MV/m/nC for a four bunch trains, showed good agreement with the simulation.
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Affiliation(s)
- H Kong
- Pohang Accelerator Laboratory, POSTECH, Pohang, Gyungbuk, 37673, Korea.,Department of Physics, Kyungpook National University, Daegu, 41566, Korea
| | - M Chung
- Ulsan National Institute of Science and Technology, Ulsan, 44919, Korea
| | - D S Doran
- Argonne National Laboratory, Argonne, IL, 60439, USA
| | - G Ha
- Argonne National Laboratory, Argonne, IL, 60439, USA.
| | - S-H Kim
- Pohang Accelerator Laboratory, POSTECH, Pohang, Gyungbuk, 37673, Korea
| | - J-H Kim
- Pohang Accelerator Laboratory, POSTECH, Pohang, Gyungbuk, 37673, Korea
| | - W Liu
- Argonne National Laboratory, Argonne, IL, 60439, USA
| | - X Lu
- Argonne National Laboratory, Argonne, IL, 60439, USA.,Northern Illinois University, Dekalb, IL, 60115, USA
| | - J Power
- Argonne National Laboratory, Argonne, IL, 60439, USA
| | - J-M Seok
- Pohang Accelerator Laboratory, POSTECH, Pohang, Gyungbuk, 37673, Korea.,Argonne National Laboratory, Argonne, IL, 60439, USA
| | - S Shin
- Department of Accelerator Science, Korea University, Sejong, 30019, Korea.
| | - J Shao
- Argonne National Laboratory, Argonne, IL, 60439, USA
| | - C Whiteford
- Argonne National Laboratory, Argonne, IL, 60439, USA
| | - E Wisniewski
- Argonne National Laboratory, Argonne, IL, 60439, USA
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13
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Abstract
Porphyromonas gingivalis, a major periodontal pathogen, invades autophagosomes of cells, including gingival epithelial cells, endothelial cells, gingival fibroblasts, macrophages, and dendritic cells, to escape antimicrobial autophagy and lysosome fusion. However, it is not known how P. gingivalis resists autophagic immunity, survives within cells, and induces inflammation. Thus, we investigated whether P. gingivalis could escape antimicrobial autophagy by promoting lysosome efflux to block autophagic maturation, leading to intracellular survival, and whether the growth of P. gingivalis within cells results in cellular oxidative stress, causing mitochondrial damage and inflammatory responses. P. gingivalis invaded human immortalized oral epithelial cells in vitro and mouse oral epithelial cells of gingival tissues in vivo. The production of reactive oxygen species (ROS) increased upon bacterial invasion, as well as mitochondrial dysfunction-related parameters with downregulated mitochondrial membrane potential and intracellular adenosine triphosphate (ATP), upregulated mitochondrial membrane permeability, intracellular Ca2+ influx, mitochondrial DNA expression, and extracellular ATP. Lysosome excretion was elevated, the number of intracellular lysosomes was diminished, and lysosomal-associated membrane protein 2 was downregulated. Expression of autophagy-related proteins, microtubule-associated protein light chain 3, sequestosome-1, the NLRP3 inflammasome, and interleukin-1β increased with P. gingivalis infection. P. gingivalis may survive in vivo by promoting lysosome efflux, blocking autophagosome-lysosome fusion, and destroying autophagic flux. As a result, ROS and damaged mitochondria accumulated and activated the NLRP3 inflammasome, which recruited the adaptor protein ASC and caspase 1, leading to the production of proinflammatory factor interleukin-1β and inflammation.
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Affiliation(s)
- M Liu
- Department of Periodontology & Tissue Engineering and Regeneration, School and Hospital of Stomatology, Cheeloo College of Medicine, Shandong University & Shandong Key Laboratory of Oral Tissue Regeneration & Shandong Engineering Laboratory for Dental Materials and Oral Tissue Regeneration, Shandong Provincial Clinical Research Center for Oral Diseases, Jinan, China
| | - J Shao
- Department of Periodontology & Tissue Engineering and Regeneration, School and Hospital of Stomatology, Cheeloo College of Medicine, Shandong University & Shandong Key Laboratory of Oral Tissue Regeneration & Shandong Engineering Laboratory for Dental Materials and Oral Tissue Regeneration, Shandong Provincial Clinical Research Center for Oral Diseases, Jinan, China
| | - Y Zhao
- Department of Periodontology & Tissue Engineering and Regeneration, School and Hospital of Stomatology, Cheeloo College of Medicine, Shandong University & Shandong Key Laboratory of Oral Tissue Regeneration & Shandong Engineering Laboratory for Dental Materials and Oral Tissue Regeneration, Shandong Provincial Clinical Research Center for Oral Diseases, Jinan, China
| | - B Ma
- Department of Periodontology & Tissue Engineering and Regeneration, School and Hospital of Stomatology, Cheeloo College of Medicine, Shandong University & Shandong Key Laboratory of Oral Tissue Regeneration & Shandong Engineering Laboratory for Dental Materials and Oral Tissue Regeneration, Shandong Provincial Clinical Research Center for Oral Diseases, Jinan, China
| | - S Ge
- Department of Periodontology & Tissue Engineering and Regeneration, School and Hospital of Stomatology, Cheeloo College of Medicine, Shandong University & Shandong Key Laboratory of Oral Tissue Regeneration & Shandong Engineering Laboratory for Dental Materials and Oral Tissue Regeneration, Shandong Provincial Clinical Research Center for Oral Diseases, Jinan, China
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14
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Zhang Y, Shao J, Wang X, Pei C, Zhang S, Yao Z, Lu Q. Partly recovery and compensation in anterior cingulate cortex after SSRI treatment-evidence from multi-voxel pattern analysis over resting state fMRI in depression. J Affect Disord 2023; 320:404-412. [PMID: 36179779 DOI: 10.1016/j.jad.2022.09.071] [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: 11/03/2021] [Revised: 05/23/2022] [Accepted: 09/20/2022] [Indexed: 02/02/2023]
Abstract
BACKGROUND Anterior cingulate cortex (ACC) plays an essential role in the pathophysiology of major depressive disorder (MDD) and its treatment. However, it's still unclear whether the effects of disease and antidepressant treatment on ACC perform diversely in neural mechanisms. METHODS Fifty-nine MDD patients completed resting-state fMRI scanning twice at baseline and after 12-week selective serotonin reuptake inhibitor (SSRI) treatment, respectively in acute state and remission state. Fifty-nine demographically matched healthy controls were enrolled. Using fractional amplitude of low-frequency fluctuation (fALFF) in ACC as features, we performed multi-voxel pattern analysis over pretreatment MDD patients vs health control (HC), and over pretreatment MDD patients vs posttreatment MDD patients. RESULTS Discriminative regions in ACC for MDD impairment and changes after antidepressants were obtained. The intersection set and difference set were calculated to form ACC subregions of recovered, unrecovered and compensative, respectively. The recovered ACC subregion mainly distributed in rostral ACC (80 %) and the other two subregions had nearly equal distribution over dorsal ACC and rostral ACC. Furthermore, only the compensative subregion had significant changed functional connectivity with cingulo-opercular control network (CON) after antidepressant treatment. LIMITATIONS The number of subjects was relatively small. The results need to be validated with larger sample sizes and multisite data. CONCLUSIONS This finding suggested that the local function of ACC was partly recovered on regulating emotion after antidepressant by detecting the common subregional targets of depression impairment and antidepressive effect. Besides, changed fALFF in the compensative ACC subregion and its connectivity with CON may partly compensate for the cognition deficits.
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Affiliation(s)
- Yujie Zhang
- School of Biological Sciences & Medical Engineering, Southeast University, Nanjing 210096, China; Child Development and Learning Science, Key Laboratory of Ministry of Education, China
| | - Junneng Shao
- School of Biological Sciences & Medical Engineering, Southeast University, Nanjing 210096, China; Child Development and Learning Science, Key Laboratory of Ministry of Education, China
| | - Xinyi Wang
- School of Biological Sciences & Medical Engineering, Southeast University, Nanjing 210096, China; Child Development and Learning Science, Key Laboratory of Ministry of Education, China
| | - Cong Pei
- School of Biological Sciences & Medical Engineering, Southeast University, Nanjing 210096, China; Child Development and Learning Science, Key Laboratory of Ministry of Education, China
| | - Shuqiang Zhang
- School of Biological Sciences & Medical Engineering, Southeast University, Nanjing 210096, China; Child Development and Learning Science, Key Laboratory of Ministry of Education, China
| | - Zhijian Yao
- Department of Psychiatry, the Affiliated Brain Hospital of Nanjing Medical University, Nanjing 210029, China; Nanjing Brain Hospital, Medical School of Nanjing University, Nanjing 210093, China.
| | - Qing Lu
- School of Biological Sciences & Medical Engineering, Southeast University, Nanjing 210096, China; Child Development and Learning Science, Key Laboratory of Ministry of Education, China.
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15
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Shao J, Zhang Y, Xue L, Wang X, Wang H, Zhu R, Yao Z, Lu Q. Shared and disease-sensitive dysfunction across bipolar and unipolar disorder during depressive episodes: a transdiagnostic study. Neuropsychopharmacology 2022; 47:1922-1930. [PMID: 35177806 PMCID: PMC9485137 DOI: 10.1038/s41386-022-01290-9] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [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: 11/10/2021] [Revised: 01/21/2022] [Accepted: 01/28/2022] [Indexed: 02/05/2023]
Abstract
Patients with depressive episodes (PDE), such as unipolar disorder (UD) and bipolar disorder (BD), are often defined as distinct diagnostic categories, but increasing converging evidence indicated shared etiologies and pathophysiological characteristics across different clinical diagnoses. We explored whether these transdiagnostic deficits are caused by the common neural substrates across diseases or disease-sensitive mechanisms, or a combination of both. In this study, we utilized a Bayesian model to decompose the resting-state brain activity into multiple hyper- and hypo-activity patterns (refer to as "factors"), so as to explore the shared and disease-sensitive alteration patterns in PDE. The model was constructed over a total of 259 patients (131 UD and 128 BD) with 100 healthy controls as the reference. The other 32 initial depressive episode BD (IDE-BD) patients who had symptoms of mania or hypomania during follow-up were taken as an independent set to estimate the factor composition using the established model for further analysis. We revealed three transdiagnostic alteration factors in PDE. Based on the distribution of factors and the tendency of factor composition at the group level, these factors were defined as BD sensitive factor, UD sensitive factor and shared basic alteration factor. We further found that the factor composition and the ROIs-based alteration degree (mainly involving in orbitofrontal gyrus and part of parietal lobe) were associated with the bipolar index in IDE-BD patients. Our findings contributed to understanding the core transdiagnostic shared and disease-sensitive alterations in PDE and to predicting the risk of emotional state transition in IDE-BD patients.
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Affiliation(s)
- Junneng Shao
- School of Biological Sciences & Medical Engineering, Southeast University, Nanjing, 210096, China
- Key Laboratory of Child Development and Learning Science (Southeast University), Ministry of Education, Nanjing, China
| | - Yujie Zhang
- School of Biological Sciences & Medical Engineering, Southeast University, Nanjing, 210096, China
- Key Laboratory of Child Development and Learning Science (Southeast University), Ministry of Education, Nanjing, China
| | - Li Xue
- School of Biological Sciences & Medical Engineering, Southeast University, Nanjing, 210096, China
- Key Laboratory of Child Development and Learning Science (Southeast University), Ministry of Education, Nanjing, China
| | - Xinyi Wang
- School of Biological Sciences & Medical Engineering, Southeast University, Nanjing, 210096, China
- Key Laboratory of Child Development and Learning Science (Southeast University), Ministry of Education, Nanjing, China
| | - Huan Wang
- School of Biological Sciences & Medical Engineering, Southeast University, Nanjing, 210096, China
- Key Laboratory of Child Development and Learning Science (Southeast University), Ministry of Education, Nanjing, China
| | - Rongxin Zhu
- Department of Psychiatry, the Affiliated Brain Hospital of Nanjing Medical University, Nanjing, 210029, China
| | - Zhijian Yao
- Department of Psychiatry, the Affiliated Brain Hospital of Nanjing Medical University, Nanjing, 210029, China.
- Nanjing Brain Hospital, Medical School of Nanjing University, Nanjing, 210093, China.
| | - Qing Lu
- School of Biological Sciences & Medical Engineering, Southeast University, Nanjing, 210096, China.
- Key Laboratory of Child Development and Learning Science (Southeast University), Ministry of Education, Nanjing, China.
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16
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Xue L, Shao J, Wang H, Wang X, Zhu R, Yao Z, Lu Q. Shared and unique imaging-derived endo-phenotypes of two typical antidepressant-applicative depressive patients. Eur Radiol 2022; 33:645-655. [PMID: 35980436 DOI: 10.1007/s00330-022-09004-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2022] [Revised: 06/08/2022] [Accepted: 06/30/2022] [Indexed: 11/04/2022]
Abstract
OBJECTIVES Determining the clinical homogeneous and heterogeneous sets among depressive patients is the key to facilitate individual-level treatment decision. METHODS The diffusion tensor imaging (DTI) data of 62 patients with major depressive disorder (MDD) and 39 healthy controls were used to construct a Latent Dirichlet Allocation (LDA) Bayesian model. Another 48 MDD patients were used to verify the robustness. The LDA model was employed to identify both shared and unique imaging-derived factors of two typically antidepressant-targeted depressive patients, selective serotonin reuptake inhibitors (SSRIs) and serotonin norepinephrine reuptake inhibitors (SNRIs). Furthermore, we applied canonical correlation analysis (CCA) between each factor loading and Hamilton depression rating scale (HAMD) sub-score, to explore the potential neurophysiological significance of each factor. RESULTS The results revealed the imaging-derived connectional fingerprint of all patients could be situated along three latent factor dimensions; such results were also verified by the out-of-sample dataset. Factor 1, uniquely expressed by SNRI-targeted patients, was associated with retardation (r = 0.4, p = 0.037) and characterized by coupling patterns between default mode network and cognitive control network. Factor 3, uniquely expressed by SSRI-targeted patients, was associated with cognitive impairment (r = 0.36, p = 0.047) and characterized by coupling patterns within cognitive control and attention network, and the connectivity between threat and reward network. Shared factor 2, characterized by coupling patterns within default mode network, was associated with anxiety (r = 0.54, p = 0.005) and sleep disturbance (r = 0.37, p = 0.032). CONCLUSIONS Our findings suggested that quantification of both homogeneity and heterogeneity within MDD may have the potential to inform rational design of pharmacological therapies. KEY POINTS • The shared and unique manifestations guiding pharmacotherapy of depressive patients are caused by the homogeneity and heterogeneity of underlying structural connections of the brain. • Both shared and unique factor loadings were found in different antidepressant-targeted patients. • Significant correlations between factor loading and HAMD sub-scores were found.
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Affiliation(s)
- Li Xue
- School of Biological Science & Medical Engineering, Southeast University, No. 2 Sipailou, Nanjing, Jiangsu Province, 210096, China.,Child Development and Learning Science, Key Laboratory of Ministry of Education, Nanjing, China
| | - Junneng Shao
- School of Biological Science & Medical Engineering, Southeast University, No. 2 Sipailou, Nanjing, Jiangsu Province, 210096, China.,Child Development and Learning Science, Key Laboratory of Ministry of Education, Nanjing, China
| | - Huan Wang
- School of Biological Science & Medical Engineering, Southeast University, No. 2 Sipailou, Nanjing, Jiangsu Province, 210096, China.,Child Development and Learning Science, Key Laboratory of Ministry of Education, Nanjing, China
| | - Xinyi Wang
- School of Biological Science & Medical Engineering, Southeast University, No. 2 Sipailou, Nanjing, Jiangsu Province, 210096, China.,Child Development and Learning Science, Key Laboratory of Ministry of Education, Nanjing, China
| | - Rongxin Zhu
- Department of Psychiatry, the Affiliated Brain Hospital of Nanjing Medical University, Nanjing, 210029, China.,Nanjing Brain Hospital, Medical School of Nanjing University, Nanjing, 210093, China
| | - Zhijian Yao
- Department of Psychiatry, the Affiliated Brain Hospital of Nanjing Medical University, Nanjing, 210029, China. .,Nanjing Brain Hospital, Medical School of Nanjing University, Nanjing, 210093, China.
| | - Qing Lu
- School of Biological Science & Medical Engineering, Southeast University, No. 2 Sipailou, Nanjing, Jiangsu Province, 210096, China. .,Child Development and Learning Science, Key Laboratory of Ministry of Education, Nanjing, China.
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Zhang L, Tan SW, Shao J, Shi YP, Su KW, Shan XY, Ye HP. [Meta-analysis on the contents of trace elements in workers with occupational exposure to lead]. Zhonghua Lao Dong Wei Sheng Zhi Ye Bing Za Zhi 2022; 40:347-353. [PMID: 35680577 DOI: 10.3760/cma.j.cn121094-20210207-00085] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
Objective: To quantitatively evaluate the content differences of trace elements in workers with occupational exposure to lead. Methods: In January 2021, relevant literatures on the contents of trace elements in workers with occupational exposure to lead published from 1990 to 2020 were searched through CNKI, Wanfang, VIP, PubMed, web of science and Embase. Screened and extracted the literatures, and evaluated the quality of the included literatures with Newcastle Ottawa Scale. Meta analysis was performed with Review Manager 5.3 software, and standardized mean difference (SMD) and its 95% confidence interval were used as effect indicators. Results: A total of 20 literatures were included, and the quality scores were 5-7. The results of Meta-analysis showed that compared with the control group, the contents of blood zinc (SMD=-1.01, 95%CI: -1.53, -0.49) , hair zinc (SMD=-0.17, 95%CI: -0.33, -0.01) , hair copper (SMD=-0.50, 95%CI: -1.01, 0) , hair iron (SMD=-3.91, 95%CI: -5.80, -2.03) and hair manganese (SMD=-1.09, 95%CI: -2.02, -0.15) in occupational lead exposure group were significantly lower (P<0.05) . Compared with the control group, the content of cobalt in hair of occupational lead exposure group (SMD=1.41, 95%CI: 0.72, 2.10) was higher, and the difference was statistically significant (P<0.05) . There was no significant difference in the contents of blood chromium, blood copper, blood iron, blood manganese, blood selenium and hair nickel between the two groups (P>0.05) . Conclusion: Workers with occupational exposure to lead have abnormal trace elements.
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Affiliation(s)
- L Zhang
- Hangzhou Hospital for Prevention and Treatment of Occupational Disease, Department of Sanitation Test, Hangzhou 310014, China
| | - S W Tan
- Hangzhou Hospital for Prevention and Treatment of Occupational Disease, Department of Sanitation Test, Hangzhou 310014, China
| | - J Shao
- Hangzhou Hospital for Prevention and Treatment of Occupational Disease, Department of Sanitation Test, Hangzhou 310014, China
| | - Y P Shi
- Hangzhou Hospital for Prevention and Treatment of Occupational Disease, Department of Sanitation Test, Hangzhou 310014, China
| | - K W Su
- Hangzhou Hospital for Prevention and Treatment of Occupational Disease, Department of Sanitation Test, Hangzhou 310014, China
| | - X Y Shan
- Hangzhou Hospital for Prevention and Treatment of Occupational Disease, Department of Sanitation Test, Hangzhou 310014, China
| | - H P Ye
- Hangzhou Hospital for Prevention and Treatment of Occupational Disease, Department of Sanitation Test, Hangzhou 310014, China
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Wang H, Zhu R, Tian S, Zhang S, Dai Z, Shao J, Xue L, Yao Z, Lu Q. Dynamic connectivity alterations in anterior cingulate cortex associated with suicide attempts in bipolar disorders with a current major depressive episode. J Psychiatr Res 2022; 149:307-314. [PMID: 35325759 DOI: 10.1016/j.jpsychires.2022.03.010] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [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: 08/06/2021] [Revised: 03/03/2022] [Accepted: 03/07/2022] [Indexed: 10/18/2022]
Abstract
OBJECTIVE Considering that the physiological mechanism of the anterior cingulate cortex (ACC) in suicide brain remains elusive for bipolar disorder (BD) patients. The study aims to investigate the intrinsic relevance between ACC and suicide attempts (SA) through transient functional connectivity (FC). METHODS We enrolled 50 un-medicated BD patients with at least one SA, 67 none-suicide attempt patients (NSA) and 75 healthy controls (HCs). The sliding window approach was utilized to study the dynamic FC of ACC via resting-state functional MRI data. Subsequently, we probed into the temporal properties of dynamic FC and then estimated the relationship between dynamic characteristics and clinical variables using the Pearson correlation. RESULTS We found six distinct FC states in all populations, with one of them being more associated with SA. Compared with NSA and HCs, the suicide-related functional state showed significantly reduced dwell time in SA patients, accompanied by a significantly increased FC strength between the right ACC and the regions within the subcortical (SubC) network. In addition, the number of transitions was significantly increased in SA patients relative to other groups. All these altered indicators were significantly correlated with the suicide risk. CONCLUSIONS The results suggested that the dysfunction of ACC was relevant to SA from a dynamic FC perspective in BD patients. It highlights the temporal properties in dynamic FC of ACC that could be used as a putative target of suicide risk assessment for BD patients.
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Affiliation(s)
- Huan Wang
- School of Biological Sciences & Medical Engineering, Southeast University, Nanjing, 210096, China; Child Development and Learning Science, Key Laboratory of Ministry of Education, China
| | - Rongxin Zhu
- Department of Psychiatry, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, 210029, China
| | - Shui Tian
- School of Biological Sciences & Medical Engineering, Southeast University, Nanjing, 210096, China; Child Development and Learning Science, Key Laboratory of Ministry of Education, China
| | - Siqi Zhang
- School of Biological Sciences & Medical Engineering, Southeast University, Nanjing, 210096, China; Child Development and Learning Science, Key Laboratory of Ministry of Education, China
| | - Zhongpeng Dai
- School of Biological Sciences & Medical Engineering, Southeast University, Nanjing, 210096, China; Child Development and Learning Science, Key Laboratory of Ministry of Education, China
| | - Junneng Shao
- School of Biological Sciences & Medical Engineering, Southeast University, Nanjing, 210096, China; Child Development and Learning Science, Key Laboratory of Ministry of Education, China
| | - Li Xue
- School of Biological Sciences & Medical Engineering, Southeast University, Nanjing, 210096, China; Child Development and Learning Science, Key Laboratory of Ministry of Education, China
| | - Zhijian Yao
- School of Biological Sciences & Medical Engineering, Southeast University, Nanjing, 210096, China; Department of Psychiatry, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, 210029, China; Nanjing Brain Hospital, Medical School of Nanjing University, Nanjing, 210093, China.
| | - Qing Lu
- School of Biological Sciences & Medical Engineering, Southeast University, Nanjing, 210096, China; Child Development and Learning Science, Key Laboratory of Ministry of Education, China.
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Colevas A, Park J, Fang B, Shao J, U'Ren L, Odegard J, Lal I, Phan M, Thein K, Adkins D. A Phase 2 Study of Magrolimab Combination Therapy in Patients with Recurrent or Metastatic Head and Neck Squamous-Cell Carcinoma. Int J Radiat Oncol Biol Phys 2022. [DOI: 10.1016/j.ijrobp.2021.12.099] [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: 10/18/2022]
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Dai Z, Shao J, Zhou H, Chen Z, Zhang S, Wang H, Jiang H, Yao Z, Lu Q. Disrupted fronto-parietal network and default-mode network gamma interactions distinguishing suicidal ideation and suicide attempt in depression. Prog Neuropsychopharmacol Biol Psychiatry 2022; 113:110475. [PMID: 34780814 DOI: 10.1016/j.pnpbp.2021.110475] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [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: 09/09/2021] [Revised: 11/03/2021] [Accepted: 11/08/2021] [Indexed: 11/17/2022]
Abstract
BACKGROUND Precise suicide risk evaluation struggled in Major depressive disorder (MDD), especially for patients with only suicidal-ideation (SI) but without suicide attempt (SA). MDD patients have deficits in negative emotion processing, which is associated with the generation of SI and SA. Given the critical role of gamma oscillations in negative emotion processing, we hypothesize that the transition from SI to SA in MDD could be characterized by abnormal gamma interactions. METHODS We recruited 162 participants containing 106 MDD patients and 56 healthy controls (HCs). Participants performed facial recognition tasks while magnetoencephalography data were recorded. Time-frequency-representation (TFR) analysis was conducted to identify the dominant spectra differences between MDD and HCs, and then source analysis was applied to localize the region of interests. Furthermore, frequency-specific functional connectivity network were constructed and a semi-supervised clustering algorithm was utilized to predict potential suicide risk. RESULTS Gamma (50-70 Hz) power was found significantly increased in MDD, mainly residing in regions from fronto-parietal-control-network (FPN), visual-network (VN), default-mode-network (DMN) and salience-network (SN). Based on impaired gamma functional connectivity network between well-established SA group and non-SI group, semi-supervised algorithm clustered patients with only SI into two groups with different suicide risks. Moreover, Inter-network gamma connectivity between FPN and DMN significantly negatively correlated with suicide risk and not confounded by depression severity. CONCLUSION Inter-network gamma connectivity with FPN and DMN might be the key neuropathological interactions underling the progression from SI to SA. By applying semi-supervised clustering to electrophysiological data, it is possible to predict individual suicide risk.
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Affiliation(s)
- Zhongpeng Dai
- School of Biological Sciences & Medical Engineering, Southeast University, Nanjing 210096, China; Child Development and Learning Science, Key Laboratory of Ministry of Education, China
| | - Junneng Shao
- School of Biological Sciences & Medical Engineering, Southeast University, Nanjing 210096, China; Child Development and Learning Science, Key Laboratory of Ministry of Education, China
| | - Hongliang Zhou
- Department of Psychiatry, the Affiliated Brain Hospital of Nanjing Medical University, Nanjing 210029, China; Nanjing Brain Hospital, Medical School of Nanjing University, Nanjing 210093, China
| | - Zhilu Chen
- Department of Psychiatry, the Affiliated Brain Hospital of Nanjing Medical University, Nanjing 210029, China; Nanjing Brain Hospital, Medical School of Nanjing University, Nanjing 210093, China
| | - Siqi Zhang
- School of Biological Sciences & Medical Engineering, Southeast University, Nanjing 210096, China; Child Development and Learning Science, Key Laboratory of Ministry of Education, China
| | - Huan Wang
- School of Biological Sciences & Medical Engineering, Southeast University, Nanjing 210096, China; Child Development and Learning Science, Key Laboratory of Ministry of Education, China
| | - Haiteng Jiang
- School of Biological Sciences & Medical Engineering, Southeast University, Nanjing 210096, China; Child Development and Learning Science, Key Laboratory of Ministry of Education, China; Department of Biomedical Engineering, Carnegie Mellon University, Pittsburgh, PA, USA
| | - Zhijian Yao
- School of Biological Sciences & Medical Engineering, Southeast University, Nanjing 210096, China; Department of Psychiatry, the Affiliated Brain Hospital of Nanjing Medical University, Nanjing 210029, China; Nanjing Brain Hospital, Medical School of Nanjing University, Nanjing 210093, China.
| | - Qing Lu
- School of Biological Sciences & Medical Engineering, Southeast University, Nanjing 210096, China; Child Development and Learning Science, Key Laboratory of Ministry of Education, China.
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Chen T, Zhang Z, Lei H, Fen Z, Yuan Y, Jin X, Zhou H, Liu J, Wang W, Guo Q, Li L, Shao J. The relationship between serum 25-hydroxyvitamin-D level and sweat function in patients with type 2 diabetes mellitus. J Endocrinol Invest 2022; 45:361-368. [PMID: 34324162 DOI: 10.1007/s40618-021-01651-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] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/15/2021] [Accepted: 07/24/2021] [Indexed: 10/20/2022]
Abstract
AIMS The objective of this study is to explore the relationship between serum 25-hydroxyvitamin-D(25-(OH)2D3) level and sweat function in patients with type 2 diabetes mellitus (T2DM). METHODS A cross-sectional study of 1021 patients with T2DM who underwent 25-(OH)2D3 level detections and sweat function tests was carried out. These individuals were divided into deficient groups (n = 154 cases), insufficient groups (n = 593 cases) and sufficient groups (n = 274 cases). Spearman correlation analysis and multivariate stepwise linear regression analysis were implemented to determine the association of 25-(OH)2D3 level and sweat function. RESULTS The total presence of sweating dysfunction was 38.59%. Patients with a lower level of serum 25-(OH)2D3 had more severe sweat secretion impairment (P < 0.05). As the decrease of serum 25-(OH)2D3 level, the presence of sweating dysfunction increased (P < 0.05). 25-(OH)2D3 level was positively correlated with sweat function parameters, age and duration of T2DM were negatively correlated with sweat function parameter (P < 0.05). Multivariate stepwise linear regression analysis explored a significant association between serum 25-(OH)2D3 level with sweat function (P < 0.05). CONCLUSIONS Serum 25-(OH)2D3 level was positively correlated with sweat function in patients with T2DM.
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Affiliation(s)
- T Chen
- Department of Endocrinology, Jinling Hospital, Nanjing Medical University, 305 East Zhongshan Road, Nanjing, 210002, Jiangsu, China
| | - Z Zhang
- The Seventh Affiliated Hospital, Sun Yat-Sen University, Shenzhen, China
| | - H Lei
- Department of Endocrinology, Jinling Hospital, Southern Medical University, Nanjing, China
| | - Z Fen
- Department of Endocrinology, Jinling Hospital, Southern Medical University, Nanjing, China
| | - Y Yuan
- Department of Endocrinology, Jinling Hospital, Nanjing Medical University, 305 East Zhongshan Road, Nanjing, 210002, Jiangsu, China
| | - X Jin
- Department of Endocrinology, Jinling Hospital, School of Medicine, Nanjing University, Nanjing, China
| | - H Zhou
- Department of Endocrinology, Jinling Hospital, Southern Medical University, Nanjing, China
| | - J Liu
- Department of Endocrinology, Jinling Hospital, Southern Medical University, Nanjing, China
| | - W Wang
- Department of Endocrinology, Jinling Hospital, School of Medicine, Nanjing University, Nanjing, China
| | - Q Guo
- Department of Endocrinology, Jinling Hospital, School of Medicine, Nanjing University, Nanjing, China
| | - L Li
- Department of Endocrinology, Chinese Navy No.971.Hospital, 22Minjiang Road, Qingdao, 266000, Shandong, China.
| | - J Shao
- Department of Endocrinology, Jinling Hospital, Nanjing Medical University, 305 East Zhongshan Road, Nanjing, 210002, Jiangsu, China.
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Ye HP, Shao J, Tan SW, Shi YP, Su KW, Zhang L. [Determination of methyl isobutyl ketone in urine by headspace coupled with gas chromatography-mass spectrometry]. Zhonghua Lao Dong Wei Sheng Zhi Ye Bing Za Zhi 2022; 40:65-68. [PMID: 35255567 DOI: 10.3760/cma.j.cn121094-20201130-00658] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
Objective: To establish a method for the determination of methyl isobutyl ketone (MIBK) in urine samples by headspace-gas chromatography-mass spectrometry. Methods: Automatic headspace sampling technique was adopted to optimize the headspace conditions (headspace bottle heating temperature and equilibration time) and gas chromatographic conditions. A total of 5 ml samples were taken and added with 3.0 g ammonium sulfate into a 20 ml headspace bottle. After heated at 60 ℃ for 30 mins, gas from the upper part of headspace bottle was injected into gas chromatography with an injection volume of 100 μl. The target was separated by HP-5MS UI (30 m×0.25 mm×0.25 μm) capillary column and then detected by mass spectrometry detector. The retention time and external standard method were used for qualitative and quantitative analysis of MIBK in samples, respectively. Results: The standard curve of MIBK showed significant linearity between 20.0-1 000.0 μg/L. The standard curve was y=62.9x-652.5, and the correlation coefficient r=0.9998. The detection limit of MIBK was 5.0 μg/L and the quantification limit of MIBK was 16.0 μg/L. The average recovery rate was 95.3%~100.2% at three spiked concentrations of low (50.0 μg/L) , medium (200.0 μg/L) and high (500.0 μg/L) . The intra-day and inter-day precisions were 1.7%~3.8% (n=6) and 1.2%~4.0% (n=6) respectively. This method was stable for the determination of MIBK, and the urine could be kept 14 d at -20 ℃ without significantly loss. Conclusion: This method is proved to be simple, practical and highly sensitive. It can satisfy the request for the determination of urine samples of workers exposed to MIBK.
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Affiliation(s)
- H P Ye
- Department of Sanitary Analysis, Hangzhou Occupational Disease Prevention and Control Hospital, Hangzhou 310014, China
| | - J Shao
- Department of Sanitary Analysis, Hangzhou Occupational Disease Prevention and Control Hospital, Hangzhou 310014, China
| | - S W Tan
- Department of Sanitary Analysis, Hangzhou Occupational Disease Prevention and Control Hospital, Hangzhou 310014, China
| | - Y P Shi
- Department of Sanitary Analysis, Hangzhou Occupational Disease Prevention and Control Hospital, Hangzhou 310014, China
| | - K W Su
- Department of Sanitary Analysis, Hangzhou Occupational Disease Prevention and Control Hospital, Hangzhou 310014, China
| | - L Zhang
- Department of Sanitary Analysis, Hangzhou Occupational Disease Prevention and Control Hospital, Hangzhou 310014, China
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Pan HD, Zhang Y, Tang H, Yang JLX, Feng WW, Mu LJ, Yan DM, Shao J, Wang H, Gao XT, Zhu RK, Huang GW, Zhao DM, Luo Y, Lyu LQ, Sun J, Yang J, Yan SQ, Wang NR, Wang H. [Studies of the norm of Karitane Parenting Confidence Scale(KPCS)among parents of infants in urban areas of China]. Zhonghua Yu Fang Yi Xue Za Zhi 2021; 55:1209-1213. [PMID: 34706506 DOI: 10.3760/cma.j.cn112150-20210224-00180] [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: 11/05/2022]
Abstract
Objective: To establish the norm of the Chinese version of Karitane Parenting Confidence Scale (KPCS) in urban areas of China. Methods: From August to December 2017, the parents of 2 216 children (<36 months old) were selected from 15 cities (Beijing, Lianyungang, Hangzhou, Chengdu, Xi'an, Guangzhou, Changsha, Jinan, Guiyang, Ningbo, Dalian, Qinhuangdao, Maanshan, Chongqing and Wuhan) in 14 provinces by stratified random sampling. The general demographic characteristics and parents' parenting confidence were collected by a self-made questionnaire and KPCS Chinese version. The percentile norm was established. P3, P10 and P25 were used as the criteria to define the degree of lack of parenting confidence. Results: The age of mothers was (30.67±4.29). The age of the father was (32.50±4.99) years old. There were 726 (32.76%), 759 (34.25%) and 731 (32.99%) infants in 6-12, 12-23 and 24-35 months old groups. The total scores of P50, P25, P10 and P3 of KPCS (Chinese version) of infant parents in urban areas in China were 41, 38, 33, and 29 respectively. When the scores of parents were 34-37, 30-33, and ≤ 29, they were judged as mild, moderate, and severe lack of parenting confidence. There was no significant difference in the Chinese version of KPCS between parents of different age groups and parents of different gender (χ²=3.53, P=0.171; χ²=1.41, P=0.236). Each factor score≤P3 is defined as the boundary score, and the corresponding boundary scores of "parenting" "support" and "competence" were 13, 9, and 5 respectively. Conclusion: The Chinese version of KPCS can be used to assess the parenting confidence of infants in urban areas of China. It can used as one of the bases for scientific and objective evaluation of the parenting status of families.
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Affiliation(s)
- H D Pan
- National Center for Women and Children's Health, Chinese Center for Disease Control and Prevention, Beijing 100081, China
| | - Y Zhang
- National Center for Women and Children's Health, Chinese Center for Disease Control and Prevention, Beijing 100081, China
| | - H Tang
- National Center for Women and Children's Health, Chinese Center for Disease Control and Prevention, Beijing 100081, China
| | - J L X Yang
- National Center for Women and Children's Health, Chinese Center for Disease Control and Prevention, Beijing 100081, China
| | - W W Feng
- National Center for Women and Children's Health, Chinese Center for Disease Control and Prevention, Beijing 100081, China
| | - L J Mu
- Early Childhood Integrated Development Service Center,Fangshan District Maternal and Child Health Hospital, Beijing 102488, China
| | - D M Yan
- Child Growth & Development,Lianyungang Maternal and Child Health Hospital, Lianyungang 222000, China
| | - J Shao
- Children's Health Care Department, The Children's Hospital, Zhejiang University School of Medicine, Hangzhou 310003, China
| | - H Wang
- Children's Health Care Department, Sichuan Province Maternal and Child Health Hospital, Chengdu 610031, China
| | - X T Gao
- Children's Health Care Department, Northwest Women and Children's Hospital, Xi'an 710061, China
| | - R K Zhu
- Children's Health Care Department, Guangdong Province Maternal and Child Health Hospital, Guangzhou 510010, China
| | - G W Huang
- Children's Health Care Department, Hunan Province Maternal and Child Health Hospital, Changsha 410008, China
| | - D M Zhao
- Children's Health Care Department, Qilu Children's Hospital of Shandong University, Jinan 250022, China
| | - Y Luo
- Children's Health Care Department, Guiyang Maternal and Child Health Hospital, Guiyang 550003, China
| | - L Q Lyu
- Children's Health Care Department, Ningbo Women and Children's Hospital, Ningbo 315000, China
| | - J Sun
- Children's Health Care Department, Dalian Maternal and Child Health Hospital, Dalian 116033, China
| | - J Yang
- Children's Health Care Department, Qinhuangdao Maternal and Child Health Hospital, Qinhuangdao 066001, China
| | - S Q Yan
- Children's Health Care Department, Maanshan Maternal and Child Health Hospital, Maanshan 243011, China
| | - N R Wang
- Children's Health Care Department, Chongqing Maternal and Child Health Hospital, Chongqing 400013, China
| | - H Wang
- Children's Health Care Department, Hubei Province Maternal and Child Health Hospital, Wuhan 430070, China
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Lu S, Cheng Y, Huang D, Sun Y, Wu L, Zhou C, Zhou J, Guo Y, Chen L, Shao J. MA02.01 Efficacy and Safety of Selpercatinib in Chinese Patients With RET Fusion-Positive Non-Small Cell Lung Cancer: A Phase 2 Trial. J Thorac Oncol 2021. [DOI: 10.1016/j.jtho.2021.08.111] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
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Chen J, Wang W, Guo Z, Huang S, Lei H, Zang P, Lu B, Shao J, Gu P. Associations between gut microbiota and thyroidal function status in Chinese patients with Graves' disease. J Endocrinol Invest 2021; 44:1913-1926. [PMID: 33481211 DOI: 10.1007/s40618-021-01507-6] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [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: 10/31/2020] [Accepted: 01/09/2021] [Indexed: 12/12/2022]
Abstract
OBJECTIVE The imbalance of gut microbiota has been linked to manifold endocrine diseases, but the association with Graves' disease (GD) is still unclear. The purpose of this study was to investigate the correlation between human gut microbiota and clinical characteristics and thyroidal functional status of GD. METHODS 14 healthy volunteers (CG) and 15 patients with primary GD (HG) were recruited as subjects. 16SrDNA high-throughput sequencing was performed on IlluminaMiSeq platform to analyze the characteristics of gut microbiota in patients with GD. Among them, the thyroid function of 13 patients basically recovered after treatment with anti-thyroid drugs (oral administration of Methimazole for 3-5 months). The fecal samples of patients after treatment (TG) were sequenced again, to further explore and investigate the potential relationship between dysbacteriosis and GD. RESULTS In terms of alpha diversity index, the observed OTUs, Simpson and Shannon indices of gut microbiota in patients with GD were significantly lower than those in healthy volunteers (P < 0.05).The difference of bacteria species was mainly reflected in the genus level, in which the relative abundance of Lactobacillus, Veillonella and Streptococcus increased significantly in GD. After the improvement of thyroid function, a significant reduction at the genus level were Blautia, Corynebacter, Ruminococcus and Streptococcus, while Phascolarctobacterium increased significantly (P < 0.05). According to Spearman correlation analysis, the correlation between the level of thyrotropin receptor antibody (TRAb) and the relative abundance of Lactobacillus and Ruminococcus was positive, while Synergistetes and Phascolarctobacterium showed a negative correlation with TRAb. Besides, there were highly significant negative correlation between Synergistetes and clinical variables of TRAb, TPOAb and TGAb (P < 0.05, R < - 0.6). CONCLUSIONS This study revealed that functional status and TRAb level in GD were associated with composition and biological function in the gut microbiota, with Synergistetes and Phascolarctobacterium protecting the thyroid probably, while Ruminococcus and Lactobacillus may be novel biomarkers of GD.
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Affiliation(s)
- J Chen
- Department of Endocrinology, Jinling Hospital, Southeast Univ, Sch Med, Nanjing, China
| | - W Wang
- Department of Endocrinology, Jinling Hospital, Nanjing Univ, Sch Med, Nanjing, China
| | - Z Guo
- Department of Endocrinology, Jinling Hospital, Nanjing Med Univ, Nanjing, China
| | - S Huang
- Department of Endocrinology, Jinling Hospital, Nanjing Univ, Sch Med, Nanjing, China
| | - H Lei
- Department of Endocrinology, Jinling Hospital, Southern Medical University, Nanjing, China
| | - P Zang
- Department of Endocrinology, Jinling Hospital, Nanjing Univ, Sch Med, Nanjing, China
| | - B Lu
- Department of Endocrinology, Jinling Hospital, Nanjing Univ, Sch Med, Nanjing, China
| | - J Shao
- Department of Endocrinology, Jinling Hospital, Nanjing Univ, Sch Med, Nanjing, China.
| | - P Gu
- Department of Endocrinology, Jinling Hospital, Nanjing Univ, Sch Med, Nanjing, China.
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Xu LY, Lai ZC, Shao J, Li K, Zhang X, Ma JY, Liu B. [Endovascular treatment strategies for distal entry tear of Stanford type B aortic dissection]. Zhonghua Wai Ke Za Zhi 2021; 59:711-715. [PMID: 34192865 DOI: 10.3760/cma.j.cn112139-20201011-00746] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
Abstract
Currently, thoracic endovascular aortic repair (TEVAR) is the first-line treatment for patients with complicated Stanford type B aortic dissections. However, TEVAR does not occlude the distal entry tear of dissections, and blood flow persists in the false lumen. Dissections might progress in some patients. Studies showed that distal entry tear increased the possibility of late aortic events during follow-up. Thus, treatment of distal entry tear is necessary in some high-risk patients after TEVAR. In this article, the current treatment strategies of distal entry tear are summarized, which include PETTICOAT, STABILISE, covered stent, fenestrated and branched stent-grafts, false lumen embolization, vascular occluder, and Knickerbocker. However, the number of the cases of most approaches is so limited that the indications and effectiveness need to be further studied. Selecting the right treatment for the right patient is of great importance.
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Affiliation(s)
- L Y Xu
- Department of Vascular Surgery, Peking Union Medical College Hospital, Chinese Academy Medical Sciences and Peking Union Medical College, Beijing 100730, China
| | - Z C Lai
- Department of Vascular Surgery, Peking Union Medical College Hospital, Chinese Academy Medical Sciences and Peking Union Medical College, Beijing 100730, China
| | - J Shao
- Department of Vascular Surgery, Peking Union Medical College Hospital, Chinese Academy Medical Sciences and Peking Union Medical College, Beijing 100730, China
| | - K Li
- Department of Vascular Surgery, Peking Union Medical College Hospital, Chinese Academy Medical Sciences and Peking Union Medical College, Beijing 100730, China
| | - X Zhang
- Department of Vascular Surgery, Peking Union Medical College Hospital, Chinese Academy Medical Sciences and Peking Union Medical College, Beijing 100730, China
| | - J Y Ma
- Department of Vascular Surgery, Peking Union Medical College Hospital, Chinese Academy Medical Sciences and Peking Union Medical College, Beijing 100730, China
| | - B Liu
- Department of Vascular Surgery, Peking Union Medical College Hospital, Chinese Academy Medical Sciences and Peking Union Medical College, Beijing 100730, China
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27
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Amenomori M, Bao YW, Bi XJ, Chen D, Chen TL, Chen WY, Chen X, Chen Y, Cui SW, Ding LK, Fang JH, Fang K, Feng CF, Feng Z, Feng ZY, Gao Q, Gomi A, Gou QB, Guo YQ, Guo YY, He HH, He ZT, Hibino K, Hotta N, Hu H, Hu HB, Huang J, Jia HY, Jiang L, Jiang P, Jin HB, Kasahara K, Katayose Y, Kato C, Kato S, Kawata K, Kozai M, Kurashige D, Le GM, Li AF, Li HJ, Li WJ, Li Y, Lin YH, Liu B, Liu C, Liu JS, Liu LY, Liu MY, Liu W, Liu XL, Lou YQ, Lu H, Meng XR, Munakata K, Nakada H, Nakamura Y, Nakazawa Y, Nanjo H, Ning CC, Nishizawa M, Ohnishi M, Ohura T, Okukawa S, Ozawa S, Qian L, Qian X, Qian XL, Qu XB, Saito T, Sakata M, Sako T, Sako TK, Shao J, Shibata M, Shiomi A, Sugimoto H, Takano W, Takita M, Tan YH, Tateyama N, Torii S, Tsuchiya H, Udo S, Wang H, Wang YP, Wu HR, Wu Q, Xu JL, Xue L, Yamamoto Y, Yang Z, Yao YQ, Yin J, Yokoe Y, Yu NP, Yuan AF, Zhai LM, Zhang CP, Zhang HM, Zhang JL, Zhang X, Zhang XY, Zhang Y, Zhang Y, Zhang Y, Zhao SP, Zhou XX. Gamma-Ray Observation of the Cygnus Region in the 100-TeV Energy Region. Phys Rev Lett 2021; 127:031102. [PMID: 34328784 DOI: 10.1103/physrevlett.127.031102] [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] [Received: 01/26/2021] [Revised: 04/30/2021] [Accepted: 06/15/2021] [Indexed: 06/13/2023]
Abstract
We report observations of gamma-ray emissions with energies in the 100-TeV energy region from the Cygnus region in our Galaxy. Two sources are significantly detected in the directions of the Cygnus OB1 and OB2 associations. Based on their positional coincidences, we associate one with a pulsar PSR J2032+4127 and the other mainly with a pulsar wind nebula PWN G75.2+0.1, with the pulsar moving away from its original birthplace situated around the centroid of the observed gamma-ray emission. This work would stimulate further studies of particle acceleration mechanisms at these gamma-ray sources.
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Affiliation(s)
- M Amenomori
- Department of Physics, Hirosaki University, Hirosaki 036-8561, Japan
| | - Y W Bao
- School of Astronomy and Space Science, Nanjing University, Nanjing 210093, China
| | - X J Bi
- Key Laboratory of Particle Astrophysics, Institute of High Energy Physics, Chinese Academy of Sciences, Beijing 100049, China
| | - D Chen
- National Astronomical Observatories, Chinese Academy of Sciences, Beijing 100012, China
| | - T L Chen
- Department of Mathematics and Physics, Tibet University, Lhasa 850000, China
| | - W Y Chen
- Key Laboratory of Particle Astrophysics, Institute of High Energy Physics, Chinese Academy of Sciences, Beijing 100049, China
| | - Xu Chen
- Key Laboratory of Particle Astrophysics, Institute of High Energy Physics, Chinese Academy of Sciences, Beijing 100049, China
| | - Y Chen
- School of Astronomy and Space Science, Nanjing University, Nanjing 210093, China
| | - S W Cui
- Department of Physics, Hebei Normal University, Shijiazhuang 050016, China
| | - L K Ding
- Key Laboratory of Particle Astrophysics, Institute of High Energy Physics, Chinese Academy of Sciences, Beijing 100049, China
| | - J H Fang
- Key Laboratory of Particle Astrophysics, Institute of High Energy Physics, Chinese Academy of Sciences, Beijing 100049, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - K Fang
- Key Laboratory of Particle Astrophysics, Institute of High Energy Physics, Chinese Academy of Sciences, Beijing 100049, China
| | - C F Feng
- Institute of Frontier and Interdisciplinary Science and Key Laboratory of Particle Physics and Particle Irradiation (MOE), Shandong University, Qingdao 266237, China
| | - Zhaoyang Feng
- Key Laboratory of Particle Astrophysics, Institute of High Energy Physics, Chinese Academy of Sciences, Beijing 100049, China
| | - Z Y Feng
- Institute of Modern Physics, SouthWest Jiaotong University, Chengdu 610031, China
| | - Qi Gao
- Department of Mathematics and Physics, Tibet University, Lhasa 850000, China
| | - A Gomi
- Faculty of Engineering, Yokohama National University, Yokohama 240-8501, Japan
| | - Q B Gou
- Key Laboratory of Particle Astrophysics, Institute of High Energy Physics, Chinese Academy of Sciences, Beijing 100049, China
| | - Y Q Guo
- Key Laboratory of Particle Astrophysics, Institute of High Energy Physics, Chinese Academy of Sciences, Beijing 100049, China
| | - Y Y Guo
- Key Laboratory of Particle Astrophysics, Institute of High Energy Physics, Chinese Academy of Sciences, Beijing 100049, China
| | - H H He
- Key Laboratory of Particle Astrophysics, Institute of High Energy Physics, Chinese Academy of Sciences, Beijing 100049, China
| | - Z T He
- Department of Physics, Hebei Normal University, Shijiazhuang 050016, China
| | - K Hibino
- Faculty of Engineering, Kanagawa University, Yokohama 221-8686, Japan
| | - N Hotta
- Faculty of Education, Utsunomiya University, Utsunomiya 321-8505, Japan
| | - Haibing Hu
- Department of Mathematics and Physics, Tibet University, Lhasa 850000, China
| | - H B Hu
- Key Laboratory of Particle Astrophysics, Institute of High Energy Physics, Chinese Academy of Sciences, Beijing 100049, China
| | - J Huang
- Key Laboratory of Particle Astrophysics, Institute of High Energy Physics, Chinese Academy of Sciences, Beijing 100049, China
| | - H Y Jia
- Institute of Modern Physics, SouthWest Jiaotong University, Chengdu 610031, China
| | - L Jiang
- Key Laboratory of Particle Astrophysics, Institute of High Energy Physics, Chinese Academy of Sciences, Beijing 100049, China
| | - P Jiang
- National Astronomical Observatories, Chinese Academy of Sciences, Beijing 100012, China
| | - H B Jin
- National Astronomical Observatories, Chinese Academy of Sciences, Beijing 100012, China
| | - K Kasahara
- Faculty of Systems Engineering, Shibaura Institute of Technology, Omiya 330-8570, Japan
| | - Y Katayose
- Faculty of Engineering, Yokohama National University, Yokohama 240-8501, Japan
| | - C Kato
- Department of Physics, Shinshu University, Matsumoto 390-8621, Japan
| | - S Kato
- Institute for Cosmic Ray Research, University of Tokyo, Kashiwa 277-8582, Japan
| | - K Kawata
- Institute for Cosmic Ray Research, University of Tokyo, Kashiwa 277-8582, Japan
| | - M Kozai
- Institute of Space and Astronautical Science, Japan Aerospace Exploration Agency (ISAS/JAXA), Sagamihara 252-5210, Japan
| | - D Kurashige
- Faculty of Engineering, Yokohama National University, Yokohama 240-8501, Japan
| | - G M Le
- National Center for Space Weather, China Meteorological Administration, Beijing 100081, China
| | - A F Li
- Key Laboratory of Particle Astrophysics, Institute of High Energy Physics, Chinese Academy of Sciences, Beijing 100049, China
- Institute of Frontier and Interdisciplinary Science and Key Laboratory of Particle Physics and Particle Irradiation (MOE), Shandong University, Qingdao 266237, China
- School of Information Science and Engineering, Shandong Agriculture University, Taian 271018, China
| | - H J Li
- Department of Mathematics and Physics, Tibet University, Lhasa 850000, China
| | - W J Li
- Key Laboratory of Particle Astrophysics, Institute of High Energy Physics, Chinese Academy of Sciences, Beijing 100049, China
- Institute of Modern Physics, SouthWest Jiaotong University, Chengdu 610031, China
| | - Y Li
- National Astronomical Observatories, Chinese Academy of Sciences, Beijing 100012, China
| | - Y H Lin
- Key Laboratory of Particle Astrophysics, Institute of High Energy Physics, Chinese Academy of Sciences, Beijing 100049, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - B Liu
- Department of Astronomy, School of Physical Sciences, University of Science and Technology of China, Hefei, Anhui 230026, China
| | - C Liu
- Key Laboratory of Particle Astrophysics, Institute of High Energy Physics, Chinese Academy of Sciences, Beijing 100049, China
| | - J S Liu
- Key Laboratory of Particle Astrophysics, Institute of High Energy Physics, Chinese Academy of Sciences, Beijing 100049, China
| | - L Y Liu
- National Astronomical Observatories, Chinese Academy of Sciences, Beijing 100012, China
| | - M Y Liu
- Department of Mathematics and Physics, Tibet University, Lhasa 850000, China
| | - W Liu
- Key Laboratory of Particle Astrophysics, Institute of High Energy Physics, Chinese Academy of Sciences, Beijing 100049, China
| | - X L Liu
- National Astronomical Observatories, Chinese Academy of Sciences, Beijing 100012, China
| | - Y-Q Lou
- Department of Physics and Tsinghua Centre for Astrophysics (THCA), Tsinghua University, Beijing 100084, China
- Tsinghua University-National Astronomical Observatories of China (NAOC) Joint Research Center for Astrophysics, Tsinghua University, Beijing 100084, China
- Department of Astronomy, Tsinghua University, Beijing 100084, China
| | - H Lu
- Key Laboratory of Particle Astrophysics, Institute of High Energy Physics, Chinese Academy of Sciences, Beijing 100049, China
| | - X R Meng
- Department of Mathematics and Physics, Tibet University, Lhasa 850000, China
| | - K Munakata
- Department of Physics, Shinshu University, Matsumoto 390-8621, Japan
| | - H Nakada
- Faculty of Engineering, Yokohama National University, Yokohama 240-8501, Japan
| | - Y Nakamura
- Key Laboratory of Particle Astrophysics, Institute of High Energy Physics, Chinese Academy of Sciences, Beijing 100049, China
- Institute for Cosmic Ray Research, University of Tokyo, Kashiwa 277-8582, Japan
| | - Y Nakazawa
- College of Industrial Technology, Nihon University, Narashino 275-8575, Japan
| | - H Nanjo
- Department of Physics, Hirosaki University, Hirosaki 036-8561, Japan
| | - C C Ning
- Department of Mathematics and Physics, Tibet University, Lhasa 850000, China
| | - M Nishizawa
- National Institute of Informatics, Tokyo 101-8430, Japan
| | - M Ohnishi
- Institute for Cosmic Ray Research, University of Tokyo, Kashiwa 277-8582, Japan
| | - T Ohura
- Faculty of Engineering, Yokohama National University, Yokohama 240-8501, Japan
| | - S Okukawa
- Faculty of Engineering, Yokohama National University, Yokohama 240-8501, Japan
| | - S Ozawa
- National Institute of Information and Communications Technology, Tokyo 184-8795, Japan
| | - L Qian
- National Astronomical Observatories, Chinese Academy of Sciences, Beijing 100012, China
| | - X Qian
- National Astronomical Observatories, Chinese Academy of Sciences, Beijing 100012, China
| | - X L Qian
- Department of Mechanical and Electrical Engineering, Shangdong Management University, Jinan 250357, China
| | - X B Qu
- College of Science, China University of Petroleum, Qingdao 266555, China
| | - T Saito
- Tokyo Metropolitan College of Industrial Technology, Tokyo 116-8523, Japan
| | - M Sakata
- Department of Physics, Konan University, Kobe 658-8501, Japan
| | - T Sako
- Institute for Cosmic Ray Research, University of Tokyo, Kashiwa 277-8582, Japan
| | - T K Sako
- Institute for Cosmic Ray Research, University of Tokyo, Kashiwa 277-8582, Japan
| | - J Shao
- Key Laboratory of Particle Astrophysics, Institute of High Energy Physics, Chinese Academy of Sciences, Beijing 100049, China
- Institute of Frontier and Interdisciplinary Science and Key Laboratory of Particle Physics and Particle Irradiation (MOE), Shandong University, Qingdao 266237, China
| | - M Shibata
- Faculty of Engineering, Yokohama National University, Yokohama 240-8501, Japan
| | - A Shiomi
- College of Industrial Technology, Nihon University, Narashino 275-8575, Japan
| | - H Sugimoto
- Shonan Institute of Technology, Fujisawa 251-8511, Japan
| | - W Takano
- Faculty of Engineering, Kanagawa University, Yokohama 221-8686, Japan
| | - M Takita
- Institute for Cosmic Ray Research, University of Tokyo, Kashiwa 277-8582, Japan
| | - Y H Tan
- Key Laboratory of Particle Astrophysics, Institute of High Energy Physics, Chinese Academy of Sciences, Beijing 100049, China
| | - N Tateyama
- Faculty of Engineering, Kanagawa University, Yokohama 221-8686, Japan
| | - S Torii
- Research Institute for Science and Engineering, Waseda University, Tokyo 162-0044, Japan
| | - H Tsuchiya
- Japan Atomic Energy Agency, Tokai-mura 319-1195, Japan
| | - S Udo
- Faculty of Engineering, Kanagawa University, Yokohama 221-8686, Japan
| | - H Wang
- Key Laboratory of Particle Astrophysics, Institute of High Energy Physics, Chinese Academy of Sciences, Beijing 100049, China
| | - Y P Wang
- Department of Mathematics and Physics, Tibet University, Lhasa 850000, China
| | - H R Wu
- Key Laboratory of Particle Astrophysics, Institute of High Energy Physics, Chinese Academy of Sciences, Beijing 100049, China
| | - Q Wu
- Department of Mathematics and Physics, Tibet University, Lhasa 850000, China
| | - J L Xu
- National Astronomical Observatories, Chinese Academy of Sciences, Beijing 100012, China
| | - L Xue
- Institute of Frontier and Interdisciplinary Science and Key Laboratory of Particle Physics and Particle Irradiation (MOE), Shandong University, Qingdao 266237, China
| | - Y Yamamoto
- Department of Physics, Konan University, Kobe 658-8501, Japan
| | - Z Yang
- Key Laboratory of Particle Astrophysics, Institute of High Energy Physics, Chinese Academy of Sciences, Beijing 100049, China
| | - Y Q Yao
- National Astronomical Observatories, Chinese Academy of Sciences, Beijing 100012, China
| | - J Yin
- National Astronomical Observatories, Chinese Academy of Sciences, Beijing 100012, China
| | - Y Yokoe
- Institute for Cosmic Ray Research, University of Tokyo, Kashiwa 277-8582, Japan
| | - N P Yu
- National Astronomical Observatories, Chinese Academy of Sciences, Beijing 100012, China
| | - A F Yuan
- Department of Mathematics and Physics, Tibet University, Lhasa 850000, China
| | - L M Zhai
- National Astronomical Observatories, Chinese Academy of Sciences, Beijing 100012, China
| | - C P Zhang
- National Astronomical Observatories, Chinese Academy of Sciences, Beijing 100012, China
| | - H M Zhang
- Key Laboratory of Particle Astrophysics, Institute of High Energy Physics, Chinese Academy of Sciences, Beijing 100049, China
| | - J L Zhang
- Key Laboratory of Particle Astrophysics, Institute of High Energy Physics, Chinese Academy of Sciences, Beijing 100049, China
| | - X Zhang
- School of Astronomy and Space Science, Nanjing University, Nanjing 210093, China
| | - X Y Zhang
- Institute of Frontier and Interdisciplinary Science and Key Laboratory of Particle Physics and Particle Irradiation (MOE), Shandong University, Qingdao 266237, China
| | - Y Zhang
- Key Laboratory of Particle Astrophysics, Institute of High Energy Physics, Chinese Academy of Sciences, Beijing 100049, China
| | - Yi Zhang
- Key Laboratory of Dark Matter and Space Astronomy, Purple Mountain Observatory, Chinese Academy of Sciences, Nanjing 210034, China
| | - Ying Zhang
- Key Laboratory of Particle Astrophysics, Institute of High Energy Physics, Chinese Academy of Sciences, Beijing 100049, China
| | - S P Zhao
- Key Laboratory of Particle Astrophysics, Institute of High Energy Physics, Chinese Academy of Sciences, Beijing 100049, China
| | - X X Zhou
- Institute of Modern Physics, SouthWest Jiaotong University, Chengdu 610031, China
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Zhang Y, Shao J, Wang X, Chen Z, Liu H, Pei C, Zhang S, Yao Z, Lu Q. Functional impairment-based segmentation of anterior cingulate cortex in depression and its relationship with treatment effects. Hum Brain Mapp 2021; 42:4035-4047. [PMID: 34008911 PMCID: PMC8288091 DOI: 10.1002/hbm.25537] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2021] [Revised: 05/09/2021] [Accepted: 05/11/2021] [Indexed: 11/09/2022] Open
Abstract
In major depressive disorder (MDD), the anterior cingulate cortex (ACC) is widely related to depression impairment and antidepressant treatment response. The multiplicity of ACC subdivisions calls for a fine‐grained investigation of their functional impairment and recovery profiles. We recorded resting state fMRI signals from 59 MDD patients twice before and after 12‐week antidepressant treatment, as well as 59 healthy controls (HCs). With functional connectivity (FC) between each ACC voxel and four regions of interests (bilateral dorsolateral prefrontal cortex [DLPFC] and amygdalae), subdivisions with variable impairment were identified based on groups' dissimilarity values between MDD patients before treatment and HC. The ACC was subdivided into three impairment subdivisions named as MedialACC, DistalACC, and LateralACC according to their dominant locations. Furthermore, the impairment pattern and the recovery pattern were measured based on group statistical analyses. DistalACC impaired more on its FC with left DLPFC, whereas LateralACC showed more serious impairment on its FC with bilateral amygdalae. After treatment, FCs between DistalACC and left DLPFC, and between LateralACC and right amygdala were normalized while impaired FC between LateralACC and left amygdala kept dysfunctional. Subsequently, FC between DistalACC and left DLPFC might contribute to clinical outcome prediction. Our approach could provide an insight into how the ACC was impaired in depression and partly restored after antidepressant treatment, from the perspective of the interaction between ACC subregions and critical frontal and subcortical regions.
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Affiliation(s)
- Yujie Zhang
- School of Biological Sciences and Medical Engineering, Southeast University, Nanjing, China.,Key Laboratory of Child Development and Learning Science, Southeast University, Ministry of Education, Research Center for Learning Science, Nanjing, China
| | - Junneng Shao
- School of Biological Sciences and Medical Engineering, Southeast University, Nanjing, China.,Key Laboratory of Child Development and Learning Science, Southeast University, Ministry of Education, Research Center for Learning Science, Nanjing, China
| | - Xinyi Wang
- School of Biological Sciences and Medical Engineering, Southeast University, Nanjing, China.,Key Laboratory of Child Development and Learning Science, Southeast University, Ministry of Education, Research Center for Learning Science, Nanjing, China
| | - Zhilu Chen
- Department of Psychiatry, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China.,Nanjing Brain Hospital, Medical School of Nanjing University, Nanjing, China
| | - Haiyan Liu
- Department of Psychiatry, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China.,Nanjing Brain Hospital, Medical School of Nanjing University, Nanjing, China
| | - Cong Pei
- School of Biological Sciences and Medical Engineering, Southeast University, Nanjing, China.,Key Laboratory of Child Development and Learning Science, Southeast University, Ministry of Education, Research Center for Learning Science, Nanjing, China
| | - Shuqiang Zhang
- School of Biological Sciences and Medical Engineering, Southeast University, Nanjing, China.,Key Laboratory of Child Development and Learning Science, Southeast University, Ministry of Education, Research Center for Learning Science, Nanjing, China
| | - Zhijian Yao
- Department of Psychiatry, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China.,Nanjing Brain Hospital, Medical School of Nanjing University, Nanjing, China
| | - Qing Lu
- School of Biological Sciences and Medical Engineering, Southeast University, Nanjing, China.,Key Laboratory of Child Development and Learning Science, Southeast University, Ministry of Education, Research Center for Learning Science, Nanjing, China
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29
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Amenomori M, Bao YW, Bi XJ, Chen D, Chen TL, Chen WY, Chen X, Chen Y, Cui SW, Ding LK, Fang JH, Fang K, Feng CF, Feng Z, Feng ZY, Gao Q, Gou QB, Guo YQ, Guo YY, He HH, He ZT, Hibino K, Hotta N, Hu H, Hu HB, Huang J, Jia HY, Jiang L, Jin HB, Kasahara K, Katayose Y, Kato C, Kato S, Kawata K, Kihara W, Ko Y, Kozai M, Le GM, Li AF, Li HJ, Li WJ, Lin YH, Liu B, Liu C, Liu JS, Liu MY, Liu W, Lou YQ, Lu H, Meng XR, Munakata K, Nakada H, Nakamura Y, Nanjo H, Nishizawa M, Ohnishi M, Ohura T, Ozawa S, Qian XL, Qu XB, Saito T, Sakata M, Sako TK, Shao J, Shibata M, Shiomi A, Sugimoto H, Takano W, Takita M, Tan YH, Tateyama N, Torii S, Tsuchiya H, Udo S, Wang H, Wu HR, Xue L, Yamamoto Y, Yang Z, Yokoe Y, Yuan AF, Zhai LM, Zhang HM, Zhang JL, Zhang X, Zhang XY, Zhang Y, Zhang Y, Zhang Y, Zhao SP, Zhou XX. First Detection of sub-PeV Diffuse Gamma Rays from the Galactic Disk: Evidence for Ubiquitous Galactic Cosmic Rays beyond PeV Energies. Phys Rev Lett 2021; 126:141101. [PMID: 33891464 DOI: 10.1103/physrevlett.126.141101] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/06/2020] [Revised: 01/05/2021] [Accepted: 01/21/2021] [Indexed: 06/12/2023]
Abstract
We report, for the first time, the long-awaited detection of diffuse gamma rays with energies between 100 TeV and 1 PeV in the Galactic disk. Particularly, all gamma rays above 398 TeV are observed apart from known TeV gamma-ray sources and compatible with expectations from the hadronic emission scenario in which gamma rays originate from the decay of π^{0}'s produced through the interaction of protons with the interstellar medium in the Galaxy. This is strong evidence that cosmic rays are accelerated beyond PeV energies in our Galaxy and spread over the Galactic disk.
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Affiliation(s)
- M Amenomori
- Department of Physics, Hirosaki University, Hirosaki 036-8561, Japan
| | - Y W Bao
- School of Astronomy and Space Science, Nanjing University, Nanjing 210093, China
| | - X J Bi
- Key Laboratory of Particle Astrophysics, Institute of High Energy Physics, Chinese Academy of Sciences, Beijing 100049, China
| | - D Chen
- National Astronomical Observatories, Chinese Academy of Sciences, Beijing 100012, China
| | - T L Chen
- Physics Department of Science School, Tibet University, Lhasa 850000, China
| | - W Y Chen
- Key Laboratory of Particle Astrophysics, Institute of High Energy Physics, Chinese Academy of Sciences, Beijing 100049, China
| | - Xu Chen
- Key Laboratory of Particle Astrophysics, Institute of High Energy Physics, Chinese Academy of Sciences, Beijing 100049, China
| | - Y Chen
- School of Astronomy and Space Science, Nanjing University, Nanjing 210093, China
| | - S W Cui
- Department of Physics, Hebei Normal University, Shijiazhuang 050016, China
| | - L K Ding
- Key Laboratory of Particle Astrophysics, Institute of High Energy Physics, Chinese Academy of Sciences, Beijing 100049, China
| | - J H Fang
- Key Laboratory of Particle Astrophysics, Institute of High Energy Physics, Chinese Academy of Sciences, Beijing 100049, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - K Fang
- Key Laboratory of Particle Astrophysics, Institute of High Energy Physics, Chinese Academy of Sciences, Beijing 100049, China
| | - C F Feng
- Institute of Frontier and Interdisciplinary Science and Key Laboratory of Particle Physics and Particle Irradiation (MOE), Shandong University, Qingdao 266237, China
| | - Zhaoyang Feng
- Key Laboratory of Particle Astrophysics, Institute of High Energy Physics, Chinese Academy of Sciences, Beijing 100049, China
| | - Z Y Feng
- Institute of Modern Physics, SouthWest Jiaotong University, Chengdu 610031, China
| | - Qi Gao
- Physics Department of Science School, Tibet University, Lhasa 850000, China
| | - Q B Gou
- Key Laboratory of Particle Astrophysics, Institute of High Energy Physics, Chinese Academy of Sciences, Beijing 100049, China
| | - Y Q Guo
- Key Laboratory of Particle Astrophysics, Institute of High Energy Physics, Chinese Academy of Sciences, Beijing 100049, China
| | - Y Y Guo
- Key Laboratory of Particle Astrophysics, Institute of High Energy Physics, Chinese Academy of Sciences, Beijing 100049, China
| | - H H He
- Key Laboratory of Particle Astrophysics, Institute of High Energy Physics, Chinese Academy of Sciences, Beijing 100049, China
| | - Z T He
- Department of Physics, Hebei Normal University, Shijiazhuang 050016, China
| | - K Hibino
- Faculty of Engineering, Kanagawa University, Yokohama 221-8686, Japan
| | - N Hotta
- Faculty of Education, Utsunomiya University, Utsunomiya 321-8505, Japan
| | - Haibing Hu
- Physics Department of Science School, Tibet University, Lhasa 850000, China
| | - H B Hu
- Key Laboratory of Particle Astrophysics, Institute of High Energy Physics, Chinese Academy of Sciences, Beijing 100049, China
| | - J Huang
- Key Laboratory of Particle Astrophysics, Institute of High Energy Physics, Chinese Academy of Sciences, Beijing 100049, China
| | - H Y Jia
- Institute of Modern Physics, SouthWest Jiaotong University, Chengdu 610031, China
| | - L Jiang
- Key Laboratory of Particle Astrophysics, Institute of High Energy Physics, Chinese Academy of Sciences, Beijing 100049, China
| | - H B Jin
- National Astronomical Observatories, Chinese Academy of Sciences, Beijing 100012, China
| | - K Kasahara
- Faculty of Systems Engineering, Shibaura Institute of Technology, Omiya 330-8570, Japan
| | - Y Katayose
- Faculty of Engineering, Yokohama National University, Yokohama 240-8501, Japan
| | - C Kato
- Department of Physics, Shinshu University, Matsumoto 390-8621, Japan
| | - S Kato
- Institute for Cosmic Ray Research, University of Tokyo, Kashiwa 277-8582, Japan
| | - K Kawata
- Institute for Cosmic Ray Research, University of Tokyo, Kashiwa 277-8582, Japan
| | - W Kihara
- Department of Physics, Shinshu University, Matsumoto 390-8621, Japan
| | - Y Ko
- Department of Physics, Shinshu University, Matsumoto 390-8621, Japan
| | - M Kozai
- Institute of Space and Astronautical Science, Japan Aerospace Exploration Agency (ISAS/JAXA), Sagamihara 252-5210, Japan
| | - G M Le
- National Center for Space Weather, China Meteorological Administration, Beijing 100081, China
| | - A F Li
- Key Laboratory of Particle Astrophysics, Institute of High Energy Physics, Chinese Academy of Sciences, Beijing 100049, China
- Institute of Frontier and Interdisciplinary Science and Key Laboratory of Particle Physics and Particle Irradiation (MOE), Shandong University, Qingdao 266237, China
- School of Information Science and Engineering, Shandong Agriculture University, Taian 271018, China
| | - H J Li
- Physics Department of Science School, Tibet University, Lhasa 850000, China
| | - W J Li
- Key Laboratory of Particle Astrophysics, Institute of High Energy Physics, Chinese Academy of Sciences, Beijing 100049, China
- Institute of Modern Physics, SouthWest Jiaotong University, Chengdu 610031, China
| | - Y H Lin
- Key Laboratory of Particle Astrophysics, Institute of High Energy Physics, Chinese Academy of Sciences, Beijing 100049, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - B Liu
- Department of Astronomy, School of Physical Sciences, University of Science and Technology of China, Hefei, Anhui 230026, China
| | - C Liu
- Key Laboratory of Particle Astrophysics, Institute of High Energy Physics, Chinese Academy of Sciences, Beijing 100049, China
| | - J S Liu
- Key Laboratory of Particle Astrophysics, Institute of High Energy Physics, Chinese Academy of Sciences, Beijing 100049, China
| | - M Y Liu
- Physics Department of Science School, Tibet University, Lhasa 850000, China
| | - W Liu
- Key Laboratory of Particle Astrophysics, Institute of High Energy Physics, Chinese Academy of Sciences, Beijing 100049, China
| | - Y-Q Lou
- Department of Physics and Tsinghua Centre for Astrophysics (THCA), Tsinghua University, Beijing 100084, China
- Tsinghua University-National Astronomical Observatories of China (NAOC) Joint Research Center for Astrophysics, Tsinghua University, Beijing 100084, China
- Department of Astronomy, Tsinghua University, Beijing 100084, China
| | - H Lu
- Key Laboratory of Particle Astrophysics, Institute of High Energy Physics, Chinese Academy of Sciences, Beijing 100049, China
| | - X R Meng
- Physics Department of Science School, Tibet University, Lhasa 850000, China
| | - K Munakata
- Department of Physics, Shinshu University, Matsumoto 390-8621, Japan
| | - H Nakada
- Faculty of Engineering, Yokohama National University, Yokohama 240-8501, Japan
| | - Y Nakamura
- Key Laboratory of Particle Astrophysics, Institute of High Energy Physics, Chinese Academy of Sciences, Beijing 100049, China
| | - H Nanjo
- Department of Physics, Hirosaki University, Hirosaki 036-8561, Japan
| | - M Nishizawa
- National Institute of Informatics, Tokyo 101-8430, Japan
| | - M Ohnishi
- Institute for Cosmic Ray Research, University of Tokyo, Kashiwa 277-8582, Japan
| | - T Ohura
- Faculty of Engineering, Yokohama National University, Yokohama 240-8501, Japan
| | - S Ozawa
- National Institute of Information and Communications Technology, Tokyo 184-8795, Japan
| | - X L Qian
- Department of Mechanical and Electrical Engineering, Shandong Management University, Jinan 250357, China
| | - X B Qu
- College of Science, China University of Petroleum, Qingdao, 266555, China
| | - T Saito
- Tokyo Metropolitan College of Industrial Technology, Tokyo 116-8523, Japan
| | - M Sakata
- Department of Physics, Konan University, Kobe 658-8501, Japan
| | - T K Sako
- Institute for Cosmic Ray Research, University of Tokyo, Kashiwa 277-8582, Japan
| | - J Shao
- Key Laboratory of Particle Astrophysics, Institute of High Energy Physics, Chinese Academy of Sciences, Beijing 100049, China
- Institute of Frontier and Interdisciplinary Science and Key Laboratory of Particle Physics and Particle Irradiation (MOE), Shandong University, Qingdao 266237, China
| | - M Shibata
- Faculty of Engineering, Yokohama National University, Yokohama 240-8501, Japan
| | - A Shiomi
- College of Industrial Technology, Nihon University, Narashino 275-8575, Japan
| | - H Sugimoto
- Shonan Institute of Technology, Fujisawa 251-8511, Japan
| | - W Takano
- Faculty of Engineering, Kanagawa University, Yokohama 221-8686, Japan
| | - M Takita
- Institute for Cosmic Ray Research, University of Tokyo, Kashiwa 277-8582, Japan
| | - Y H Tan
- Key Laboratory of Particle Astrophysics, Institute of High Energy Physics, Chinese Academy of Sciences, Beijing 100049, China
| | - N Tateyama
- Faculty of Engineering, Kanagawa University, Yokohama 221-8686, Japan
| | - S Torii
- Research Institute for Science and Engineering, Waseda University, Tokyo 169-8555, Japan
| | - H Tsuchiya
- Japan Atomic Energy Agency, Tokai-mura 319-1195, Japan
| | - S Udo
- Faculty of Engineering, Kanagawa University, Yokohama 221-8686, Japan
| | - H Wang
- Key Laboratory of Particle Astrophysics, Institute of High Energy Physics, Chinese Academy of Sciences, Beijing 100049, China
| | - H R Wu
- Key Laboratory of Particle Astrophysics, Institute of High Energy Physics, Chinese Academy of Sciences, Beijing 100049, China
| | - L Xue
- Institute of Frontier and Interdisciplinary Science and Key Laboratory of Particle Physics and Particle Irradiation (MOE), Shandong University, Qingdao 266237, China
| | - Y Yamamoto
- Department of Physics, Konan University, Kobe 658-8501, Japan
| | - Z Yang
- Key Laboratory of Particle Astrophysics, Institute of High Energy Physics, Chinese Academy of Sciences, Beijing 100049, China
| | - Y Yokoe
- Institute for Cosmic Ray Research, University of Tokyo, Kashiwa 277-8582, Japan
| | - A F Yuan
- Physics Department of Science School, Tibet University, Lhasa 850000, China
| | - L M Zhai
- National Astronomical Observatories, Chinese Academy of Sciences, Beijing 100012, China
| | - H M Zhang
- Key Laboratory of Particle Astrophysics, Institute of High Energy Physics, Chinese Academy of Sciences, Beijing 100049, China
| | - J L Zhang
- Key Laboratory of Particle Astrophysics, Institute of High Energy Physics, Chinese Academy of Sciences, Beijing 100049, China
| | - X Zhang
- School of Astronomy and Space Science, Nanjing University, Nanjing 210093, China
| | - X Y Zhang
- Institute of Frontier and Interdisciplinary Science and Key Laboratory of Particle Physics and Particle Irradiation (MOE), Shandong University, Qingdao 266237, China
| | - Y Zhang
- Key Laboratory of Particle Astrophysics, Institute of High Energy Physics, Chinese Academy of Sciences, Beijing 100049, China
| | - Yi Zhang
- Key Laboratory of Dark Matter and Space Astronomy, Purple Mountain Observatory, Chinese Academy of Sciences, Nanjing 210034, China
| | - Ying Zhang
- Key Laboratory of Particle Astrophysics, Institute of High Energy Physics, Chinese Academy of Sciences, Beijing 100049, China
| | - S P Zhao
- Key Laboratory of Particle Astrophysics, Institute of High Energy Physics, Chinese Academy of Sciences, Beijing 100049, China
| | - X X Zhou
- Institute of Modern Physics, SouthWest Jiaotong University, Chengdu 610031, China
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Tian S, Zhu R, Chattun MR, Wang H, Chen Z, Zhang S, Shao J, Wang X, Yao Z, Lu Q. Temporal dynamics alterations of spontaneous neuronal activity in anterior cingulate cortex predict suicidal risk in bipolar II patients. Brain Imaging Behav 2021; 15:2481-2491. [PMID: 33656698 DOI: 10.1007/s11682-020-00448-7] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [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: 10/11/2020] [Revised: 11/25/2020] [Accepted: 12/29/2020] [Indexed: 12/17/2022]
Abstract
Bipolar disorder type II (BD-II) is linked to an increased suicidal risk. Since a prior suicide attempt (SA) is the single most important risk factor for sequent suicide, the elucidation of involved neural substrates is critical for its prevention. Therefore, we examined the spontaneous brain activity and its temporal variabilities in suicide attempters with bipolar II during a major depressive episode. In this cross-sectional study, 101 patients with BD-II, including 44 suicidal attempters and 57 non-attempters, and 60 non-psychiatric controls underwent a resting-state functional magnetic resonance imaging (fMRI). Participants were assessed with Hamilton Rating Scale for Depression (HAMD) and Nurses, Global Assessment of Suicide Risk (NGASR). The dynamics of low-frequency fluctuation (dALFF) was measured using sliding-window analysis and its correlation with suicidal risk was conducted using Pearson correlation. Compared to non-attempters, suicidal attempters showed an increase in brain activity and temporal dynamics in the anterior cingulate cortex (ACC). In addition, the temporal variabilities of ACC activity positively correlated with suicidal risk (R = 0.45, p = 0.004), while static ACC activity failed to (R = 0.08, p > 0.05). Our findings showed that an aberrant static ALFF and temporal variability could affect suicidal behavior in BD-II patients. However, temporal variability of neuronal activity was more sensitive than static amplitude in reflecting diathesis for suicide in BD-II. Dynamics of brain activity could be considered in developing neuromarkers for suicide prevention.
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Affiliation(s)
- Shui Tian
- School of Biological Sciences & Medical Engineering, Southeast University, No. 2 Sipailou, Jiangsu Province, Nanjing, 210096, China
- Child Development and Learning Science, Key Laboratory of Ministry of Education, Nanjing, 210096, China
| | - Rongxin Zhu
- Department of Psychiatry, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, 210029, China
| | - Mohammad Ridwan Chattun
- Department of Psychiatry, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, 210029, China
| | - Huan Wang
- School of Biological Sciences & Medical Engineering, Southeast University, No. 2 Sipailou, Jiangsu Province, Nanjing, 210096, China
- Child Development and Learning Science, Key Laboratory of Ministry of Education, Nanjing, 210096, China
| | - Zhilu Chen
- Department of Psychiatry, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, 210029, China
| | - Siqi Zhang
- School of Biological Sciences & Medical Engineering, Southeast University, No. 2 Sipailou, Jiangsu Province, Nanjing, 210096, China
- Child Development and Learning Science, Key Laboratory of Ministry of Education, Nanjing, 210096, China
| | - Junneng Shao
- School of Biological Sciences & Medical Engineering, Southeast University, No. 2 Sipailou, Jiangsu Province, Nanjing, 210096, China
- Child Development and Learning Science, Key Laboratory of Ministry of Education, Nanjing, 210096, China
| | - Xinyi Wang
- School of Biological Sciences & Medical Engineering, Southeast University, No. 2 Sipailou, Jiangsu Province, Nanjing, 210096, China
- Child Development and Learning Science, Key Laboratory of Ministry of Education, Nanjing, 210096, China
| | - Zhijian Yao
- School of Biological Sciences & Medical Engineering, Southeast University, No. 2 Sipailou, Jiangsu Province, Nanjing, 210096, China.
- Department of Psychiatry, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, 210029, China.
- Nanjing Brain Hospital, Medical School of Nanjing University, Nanjing, 210093, China.
| | - Qing Lu
- School of Biological Sciences & Medical Engineering, Southeast University, No. 2 Sipailou, Jiangsu Province, Nanjing, 210096, China.
- Child Development and Learning Science, Key Laboratory of Ministry of Education, Nanjing, 210096, China.
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Xiang C, Han Y, Teng H, Zhu L, Shao J, Zhao J, Ma S, Lin J, Zheng J, Lizaso A. P38.07 Comprehensive Investigation of Mutational Features of Various Lung Adenocarcinoma Histological Subtypes Among Chinese Patients. J Thorac Oncol 2021. [DOI: 10.1016/j.jtho.2021.01.788] [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: 11/15/2022]
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Chen Z, Tao S, Zhu R, Tian S, Sun Y, Wang H, Yan R, Shao J, Zhang Y, Zhang J, Yao Z, Lu Q. Aberrant functional connectivity between the suprachiasmatic nucleus and the superior temporal gyrus: Bridging RORA gene polymorphism with diurnal mood variation in major depressive disorder. J Psychiatr Res 2021; 132:123-130. [PMID: 33091686 DOI: 10.1016/j.jpsychires.2020.09.037] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [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: 05/17/2020] [Revised: 09/24/2020] [Accepted: 09/30/2020] [Indexed: 10/23/2022]
Abstract
Diurnal mood variation (DMV), a common symptom of major depressive disorder (MDD), is associated with circadian related genes and dysregulation of the suprachiasmatic nucleus (SCN). Previous research confirmed that the RORA gene is involved in the regulation of circadian rhythms. In this study, we hypothesized that polymorphisms of RORA may affect DMV symptoms of MDD through functional changes in the SCN. A total of 208 patients diagnosed with depression and 120 control subjects were enrolled and underwent a resting-state functional magnetic resonance imaging (rs-fMRI). Blood samples were collected and genotyping of 9 RORA gene SNPs were performed using next-generation sequencing technology. Patients were categorized as an AA genotype or C allele carriers based on RORA rs72752802 polymorphism. SCN-seed functional connectivity (FC) was compared between the two groups and correlation with severity of DMV was analyzed. Finally, a mediation analysis was performed to further determine FC intermediary effects. We observed that rs72752802 was significantly associated with patients' DMV symptoms. C allele carriers of rs72752802 showed significantly decreased FC between the right SCN and right superior temporal gyrus (rSTG). This was also correlated with DMV symptoms. In addition, the rs72752802 SNP influenced DMV symptoms through intermediary effects of SCN-rSTG connectivity. The study presented here provides a neurological and genetic basis for understanding depressed patients experiencing DMV.
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Affiliation(s)
- Zhilu Chen
- Department of Psychiatry, the Affiliated Brain Hospital of Nanjing Medical University, Nanjing, 210029, China
| | - Shiwan Tao
- Department of Psychiatry, the Affiliated Brain Hospital of Nanjing Medical University, Nanjing, 210029, China
| | - Rongxin Zhu
- Department of Psychiatry, the Affiliated Brain Hospital of Nanjing Medical University, Nanjing, 210029, China
| | - Shui Tian
- School of Biological Sciences & Medical Engineering, Southeast University, Nanjing, 210096, China; Child Development and Learning Science, Key Laboratory of Ministry of Education, 210096, China
| | - Yurong Sun
- School of Biological Sciences & Medical Engineering, Southeast University, Nanjing, 210096, China; Child Development and Learning Science, Key Laboratory of Ministry of Education, 210096, China
| | - Huan Wang
- School of Biological Sciences & Medical Engineering, Southeast University, Nanjing, 210096, China; Child Development and Learning Science, Key Laboratory of Ministry of Education, 210096, China
| | - Rui Yan
- Department of Psychiatry, the Affiliated Brain Hospital of Nanjing Medical University, Nanjing, 210029, China; Nanjing Brain Hospital, Medical School of Nanjing University, Nanjing, 210093, China
| | - Junneng Shao
- School of Biological Sciences & Medical Engineering, Southeast University, Nanjing, 210096, China; Child Development and Learning Science, Key Laboratory of Ministry of Education, 210096, China
| | - Yujie Zhang
- School of Biological Sciences & Medical Engineering, Southeast University, Nanjing, 210096, China; Child Development and Learning Science, Key Laboratory of Ministry of Education, 210096, China
| | - Jie Zhang
- Department of Psychiatry, the Affiliated Brain Hospital of Nanjing Medical University, Nanjing, 210029, China
| | - Zhijian Yao
- Department of Psychiatry, the Affiliated Brain Hospital of Nanjing Medical University, Nanjing, 210029, China; School of Biological Sciences & Medical Engineering, Southeast University, Nanjing, 210096, China; Nanjing Brain Hospital, Medical School of Nanjing University, Nanjing, 210093, China.
| | - Qing Lu
- School of Biological Sciences & Medical Engineering, Southeast University, Nanjing, 210096, China; Child Development and Learning Science, Key Laboratory of Ministry of Education, 210096, China.
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Jin XM, Xu B, Zhang Y, Liu SY, Shao J, Wu L, Tang JA, Yin T, Fan XB, Yang TY. LncRNA SND1-IT1 accelerates the proliferation and migration of osteosarcoma via sponging miRNA-665 to upregulate POU2F1. Eur Rev Med Pharmacol Sci 2020; 23:9772-9780. [PMID: 31799644 DOI: 10.26355/eurrev_201911_19540] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
Abstract
OBJECTIVE To clarify the role of long non-coding RNA (lncRNA) SND1-IT1 in accelerating the proliferative and migratory abilities of osteosarcoma (OS) via sponging miRNA-665 to upregulate POU2F1. PATIENTS AND METHODS The relative level of SND1-IT1 in OS tissues was determined by quantitative Real Time-Polymerase Chain Reaction (qRT-PCR). The target gene of SND1-IT1 was predicted by bioinformatics and verified by Dual-Luciferase reporter gene assay. Similarly, the target gene of miRNA-665 was identified. Correlation among SND1-IT1, miRNA-665 and POU2F1 was evaluated through linear regression test. Regulatory effects of SND1-IT1/miRNA-665/POU2F1 on cellular behaviors of MG63 and U2OS cells were evaluated. RESULTS SND1-IT1 was upregulated in OS, knockdown of which attenuated proliferative and migratory abilities of OS cells. MiRNA-665 was the target gene of SND1-IT1, which was negatively correlated to SND1-IT1 in OS. POU2F1 was the target gene of miRNA-665. Its level was negatively regulated by miRNA-665 and positively regulated by SND1-IT1. Inhibited proliferative and migratory abilities of OS cells with SND1-IT1 knockdown were partially elevated by transfection of miRNA-665 inhibitor, and further downregulated by POU2F1 knockdown. CONCLUSIONS LncRNA SND1-IT1 accelerates proliferative and migratory abilities of OS via sponging miRNA-665 to upregulate POU2F1, thus stimulating the progression of OS.
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Affiliation(s)
- X-M Jin
- Department of Orthopaedics, Gongli Hospital, the Second Military Medical University, Shanghai, China.
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Wu H, Xu B, Gao Q, Zhou X, Shao J, Liang Z, Ma D. Genetic testing procedures of BRCA1/2 mutation and their disparities: A national survey. Gynecol Oncol 2020. [DOI: 10.1016/j.ygyno.2020.05.670] [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: 10/23/2022]
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Ning SL, Zhu H, Shao J, Liu YC, Lan J, Miao J. MiR-21 inhibitor improves locomotor function recovery by inhibiting IL-6R/JAK-STAT pathway-mediated inflammation after spinal cord injury in model of rat. Eur Rev Med Pharmacol Sci 2020; 23:433-440. [PMID: 30720148 DOI: 10.26355/eurrev_201901_16852] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
Abstract
OBJECTIVE To investigate the function of miRNA-21 and interleukin-6 receptor/Janus Kinase-Signal transducer and activator of transcription (IL-6R/JAK-STAT) pathway in microglia on inflammatory responses after spinal cord injury (SCI). MATERIALS AND METHODS This study first detected respectively the protein level of inflammatory factor inducible nitric oxide synthase (iNOS) and tumor necrosis factor alpha (TNF-α) by Western blotting after transfection of miR-21 or administration of miR-21 inhibitor in activated microglia cells of rat in vitro. The quantitative Real-time polymerase chain reaction (qRT-PCR) was utilized to detect the expression of IL-6R under two different interventions. Next, we established a model of spinal cord injury in rat and inspected miR-21 and IL-6R in SCI rat by qRT-PCR. In addition, the protein levels of iNOS and TNF-α in SCI rat were detected by Western blotting. MiR-21 inhibitor was injected into the injured area of SCI rat to delve into the function of miR-21 down-expression on iNOS and TNF-α expression by Western blot as well as the RNA levels of IL-6R, JAK and STAT3 by qRT-PCR. Furthermore, the SCI rat with movement and coordination of hindlimbs was observed by Basso-Beattie-Bresnahan locomotor rating scale (BBB scale) after miR-21 down-expression. RESULTS Compared with the microglia transfected with miR-21, the execution of inhibitor in microglia effectively relieved the expression of IL-6R and the breakout of iNOS and TNF-α. Meanwhile, the increase of miR-21 was significantly observed in SCI rat along with significant improvement of inflammatory response-related factors including iNOS and TNF-α. After that, we injected SCI rat with miR-21 inhibitor into the spinal cord injury area and found the inhibition of miR-21 decreased the protein levels of iNOS and TNF-α. Simultaneously, down-expression of miR-21 evidently declined the RNA levels of IL-6R, JAK, and STAT3 in SCI rat. Compared with the sham-operated rat, the movement and coordination of hindlimbs of the SCI group displayed dramatic dysfunction. However, miR-21 down-expression elevated the movement and coordination of hindlimbs of the SCI rat than those of the only injury group. CONCLUSIONS Inhibition of miR-21 can promote the recovery of spinal cord injury by down-regulating IL-6R/JAK-STAT signaling pathway and inhibiting inflammation.
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Affiliation(s)
- S-L Ning
- Department of Spine Surgery, Tianjin Hospital, Tianjin, China.
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Makrinioti H, Mac Donald A, Lu X, Wallace S, Mathew J, Zhang F, Shao J, Bretherton J, Tariq M, Eyre E, Wong A, Pakkiri L, Saxena AK, Wong GW. Intussusception in 2 Children With Severe Acute Respiratory Syndrome Coronavirus-2 Infection. J Pediatric Infect Dis Soc 2020; 9:504-506. [PMID: 32770243 PMCID: PMC7454795 DOI: 10.1093/jpids/piaa096] [Citation(s) in RCA: 25] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/04/2020] [Accepted: 08/04/2020] [Indexed: 02/06/2023]
Abstract
We note that intussusception was likely associated with severe acute respiratory syndrome coronavirus-2 infection in 2 infants in Wuhan and London. The intussusception was reduced by enemas in Wuhan; the outcome was fatal. The intussusception was not reduced by enemas in London and required surgery; the outcome was favorable.
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Affiliation(s)
- Heidi Makrinioti
- West Middlesex University Hospital, Chelsea, and Westminster Hospital NHS Foundation Trust, London, UK,corresponding author: Heidi Makrinioti, e-mail
| | - Alexander Mac Donald
- Wuhan Children’s Hospital, Wuhan, Huazhong University of Science & Technology, Wuhan, China
| | - X Lu
- Wuhan Children’s Hospital, Wuhan, Huazhong University of Science & Technology, Wuhan, China
| | - S Wallace
- West Middlesex University Hospital, Chelsea, and Westminster Hospital NHS Foundation Trust, London, UK
| | - Jobson Mathew
- Chelsea and Westminster Hospital, Chelsea, and Westminster Hospital NHS Foundation Trust, London, UK
| | - F Zhang
- Wuhan Children’s Hospital, Wuhan, Huazhong University of Science & Technology, Wuhan, China
| | - J Shao
- Wuhan Children’s Hospital, Wuhan, Huazhong University of Science & Technology, Wuhan, China
| | - J Bretherton
- Chelsea and Westminster Hospital, Chelsea, and Westminster Hospital NHS Foundation Trust, London, UK
| | - Mehmood Tariq
- Chelsea and Westminster Hospital, Chelsea, and Westminster Hospital NHS Foundation Trust, London, UK
| | - E Eyre
- West Middlesex University Hospital, Chelsea, and Westminster Hospital NHS Foundation Trust, London, UK
| | - A Wong
- West Middlesex University Hospital, Chelsea, and Westminster Hospital NHS Foundation Trust, London, UK
| | - L Pakkiri
- West Middlesex University Hospital, Chelsea, and Westminster Hospital NHS Foundation Trust, London, UK
| | - Amulya K Saxena
- Chelsea and Westminster Hospital, Chelsea, and Westminster Hospital NHS Foundation Trust, London, UK
| | - G W Wong
- Department of Paediatrics, Prince of Wales Hospital, Chinese University of Hong Kong, China
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Xu HY, Shao J, Yin BZ, Zhang LM, Fang JC, Zhang JS, Xia GJ. Bovine bta-microRNA-1271 Promotes Preadipocyte Differentiation by Targeting Activation Transcription Factor 3. Biochemistry Moscow 2020; 85:749-757. [DOI: 10.1134/s0006297920070032] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
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38
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Tian S, Zhang S, Mo Z, Chattun MR, Wang Q, Wang L, Zhu R, Shao J, Wang X, Yao Z, Si T, Lu Q. Antidepressants normalize brain flexibility associated with multi-dimensional symptoms in major depressive patients. Prog Neuropsychopharmacol Biol Psychiatry 2020; 100:109866. [PMID: 31972187 DOI: 10.1016/j.pnpbp.2020.109866] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [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: 10/18/2019] [Revised: 01/06/2020] [Accepted: 01/15/2020] [Indexed: 11/29/2022]
Abstract
BACKGROUND The fundamental pathophysiology of major depressive disorder (MDD) could be characterized by functional brain networks which tightly and dynamically connect into groups as communities, making the flexible brain possible to external multifarious demands. We aim to scrutinize what brain dynamics go awry in MDD and antidepressants effects on multi-dimensional symptoms. METHODS Thirty-five patients and thirty-five controls underwent resting-state functional magnetic resonance imaging (MRI). Patients were scanned before and after 8 or 12 weeks of pharmacotherapy. Group independent component analysis decomposed resting-state images to instinct networks and networks' integrated flexibility was calculated. Network flexibility between patients at baseline and after therapy were compared. RESULTS All patients completed the clinical trial and MRI scans. Following antidepressants treatment, we found significant normalization of reduced network flexibility in default mode network (DMN) and cognitive control network (CCN) of MDD patients. Selectively significant correlations between network flexibility and multi-dimensional symptoms such as anxiety/somatization and hysteresis factor were also found. CONCLUSIONS "Hypoflexible" CCN may involve in anxiety syndrome. Low flexibility in DMN may be indicative of hysteresis. These suggest an important pathophysiology of depressive manifestation of MDD. The antidepressant-induced normalization of the "hypoflexibility" suggests a selective pathway through which antidepressants may alleviate symptoms in depression.
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Affiliation(s)
- Shui Tian
- School of Biological Sciences & Medical Engineering, Southeast University, Nanjing 210096, China; Child Development and Learning Science, Key Laboratory of Ministry of Education, China
| | - Siqi Zhang
- School of Biological Sciences & Medical Engineering, Southeast University, Nanjing 210096, China; Child Development and Learning Science, Key Laboratory of Ministry of Education, China
| | - Zhaoqi Mo
- School of Biological Sciences & Medical Engineering, Southeast University, Nanjing 210096, China; Child Development and Learning Science, Key Laboratory of Ministry of Education, China
| | - Mohammad Ridwan Chattun
- Department of Psychiatry,the Affiliated Nanjing Brain Hospital of Nanjing Medical University,Nanjing 210029, China
| | - Qiang Wang
- Nanjing Brain Hospital, Medical School of Nanjing University,Nanjing 210093, China
| | - Li Wang
- Peking University Institute of Mental Health & Sixth Hospital, Beijing 100191, China; National Clinical Research Center for Mental Disorder & The Key Laboratory of Mental Health, Ministry of Health, Ministry of Health (Peking University), Beijing 100191, China
| | - Rongxin Zhu
- Department of Psychiatry,the Affiliated Nanjing Brain Hospital of Nanjing Medical University,Nanjing 210029, China
| | - Junneng Shao
- School of Biological Sciences & Medical Engineering, Southeast University, Nanjing 210096, China; Child Development and Learning Science, Key Laboratory of Ministry of Education, China
| | - Xinyi Wang
- School of Biological Sciences & Medical Engineering, Southeast University, Nanjing 210096, China; Child Development and Learning Science, Key Laboratory of Ministry of Education, China
| | - Zhijian Yao
- Department of Psychiatry,the Affiliated Nanjing Brain Hospital of Nanjing Medical University,Nanjing 210029, China; Nanjing Brain Hospital, Medical School of Nanjing University,Nanjing 210093, China.
| | - Tianmei Si
- Peking University Institute of Mental Health & Sixth Hospital, Beijing 100191, China; National Clinical Research Center for Mental Disorder & The Key Laboratory of Mental Health, Ministry of Health, Ministry of Health (Peking University), Beijing 100191, China.
| | - Qing Lu
- School of Biological Sciences & Medical Engineering, Southeast University, Nanjing 210096, China; Child Development and Learning Science, Key Laboratory of Ministry of Education, China.
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Abstract
Objective: To explore the predictive values of routine blood test results for iron deficiency (ID) screening in children. Methods: Routine blood test results and serum ferritin (SF) levels from 1 443 healthy children (862 boys, 581 girls) aged 6 months to 18 years, who were seen for well-child visits between June 2017 and May 2019 in Children's Hospital, Zhejiang University School of Medicine, were retrospectively analyzed. ID was defined as SF<20 μg/L, iron deficiency anemia (IDA) as ID with anemia (hemoglobin(Hb)<110 g/L at 6 months-5 years of age, Hb<120 g/L at 6-18 years of age), non-anemia ID as ID without anemia, non-ID anemia as SF≥20 μg/L with anemia, and healthy control subjects as those with SF≥20 μg/L but without anemia. The blood test results including Hb, mean corpuscular volume (MCV), mean corpuscular hemoglobin concentration (MCHC), red blood cell distribution width (RDW), and the percentage of low hemoglobin density (LHD) of healthy control, non-anemia ID, non-ID anemia, and IDA groups were compared by analysis of variance (ANOVA) or non-parametric test, quantitative data were described as x±s or M(interquartile range), and receiver operating characteristic curve (ROC) analysis was applied to assess predictive values of routine blood test results and LHD for detecting IDA and ID. Results: Among 1 443 children with median age of 2.1(3.3) years, 1 061 children were in healthy control group, 292 in non-anemia ID group, 43 in non-ID anemia group and 47 in IDA group. The prevalence of ID was much higher than that of anemia (23.5% (339/1 443) vs. 6.2% (90/1 443) , χ(2)=169.76, P<0.01). Compared with control group, non-anemia ID group showed higher LHD (0.088 (0.093) vs.0.073 (0.068), P<0.01) and RDW (0.131±0.013 vs. 0.126±0.008, P<0.01), lower MCV ((80±4) vs. (83±4) fl, P<0.01) and MCHC values ((326±9) vs. (329±8) g/L, P<0.01). IDA group showed higher LHD (0.322(0.544)) and RDW (0.151±0.018), lower MCV ((73±6) fl) and MCHC values((309±14) g/L) than non-anemia ID group (all P<0.01). The area under curve (AUC) values of MCHC, LHD, RDW and MCV for detecting ID were 0.63 (95%CI: 0.60-0.67), 0.63 (95%CI:0.60-0.67), 0.67 (95%CI: 0.63-0.70) and 0.73 (95%CI: 0.69-0.76) respectively. With cutoff limits (MCV<80.2 fl, RDW>0.131 or MCHC<322 g/L), MCV, RDW and MCHC showed higher sensitivity for screening ID than hemoglobin (0.540, 0.469 and 0.336 vs. 0.139, χ(2)=121.70, 87.47, 35.56, all P<0.01). Conclusion: MCV, RDW and MCHC can be used to screen ID in primary health care settings.
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Affiliation(s)
- J Y Zhan
- Department of Pediatric Health Care, Children's Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health, Hangzhou 310003, China
| | - S S Zheng
- Department of Pediatric Health Care, Children's Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health, Hangzhou 310003, China
| | - W W Dong
- Department of Pediatric Health Care, Children's Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health, Hangzhou 310003, China
| | - J Shao
- Department of Pediatric Health Care, Children's Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health, Hangzhou 310003, China
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40
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Zhu R, Tian S, Wang H, Jiang H, Wang X, Shao J, Wang Q, Yan R, Tao S, Liu H, Yao Z, Lu Q. Discriminating Suicide Attempters and Predicting Suicide Risk Using Altered Frontolimbic Resting-State Functional Connectivity in Patients With Bipolar II Disorder. Front Psychiatry 2020; 11:597770. [PMID: 33324262 PMCID: PMC7725800 DOI: 10.3389/fpsyt.2020.597770] [Citation(s) in RCA: 4] [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] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/22/2020] [Accepted: 11/04/2020] [Indexed: 01/04/2023] Open
Abstract
Bipolar II disorder (BD-II) major depression episode is highly associated with suicidality, and objective neural biomarkers could be key elements to assist in early prevention and intervention. This study aimed to integrate altered brain functionality in the frontolimbic system and machine learning techniques to classify suicidal BD-II patients and predict suicidality risk at the individual level. A cohort of 169 participants were enrolled, including 43 BD-II depression patients with at least one suicide attempt during a current depressive episode (SA), 62 BD-II depression patients without a history of attempted suicide (NSA), and 64 demographically matched healthy controls (HCs). We compared resting-state functional connectivity (rsFC) in the frontolimbic system among the three groups and explored the correlation between abnormal rsFCs and the level of suicide risk (assessed using the Nurses' Global Assessment of Suicide Risk, NGASR) in SA patients. Then, we applied support vector machines (SVMs) to classify SA vs. NSA in BD-II patients and predicted the risk of suicidality. SA patients showed significantly decreased frontolimbic rsFCs compared to NSA patients. The left amygdala-right middle frontal gyrus (orbital part) rsFC was negatively correlated with NGASR in the SA group, but not the severity of depressive or anxiety symptoms. Using frontolimbic rsFCs as features, the SVMs obtained an overall 84% classification accuracy in distinguishing SA and NSA. A significant correlation was observed between the SVMs-predicted NGASR and clinical assessed NGASR (r = 0.51, p = 0.001). Our results demonstrated that decreased rsFCs in the frontolimbic system might be critical objective features of suicidality in BD-II patients, and could be useful for objective prediction of suicidality risk in individuals.
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Affiliation(s)
- Rongxin Zhu
- Department of Psychiatry, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China
| | - Shui Tian
- School of Biological Sciences and Medical Engineering, Southeast University, Nanjing, China.,Child Development and Learning Science, Key Laboratory of Ministry of Education, Southeast University, Nanjing, China
| | - Huan Wang
- School of Biological Sciences and Medical Engineering, Southeast University, Nanjing, China.,Child Development and Learning Science, Key Laboratory of Ministry of Education, Southeast University, Nanjing, China
| | - Haiteng Jiang
- Department of Psychiatry, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China
| | - Xinyi Wang
- School of Biological Sciences and Medical Engineering, Southeast University, Nanjing, China.,Child Development and Learning Science, Key Laboratory of Ministry of Education, Southeast University, Nanjing, China
| | - Junneng Shao
- School of Biological Sciences and Medical Engineering, Southeast University, Nanjing, China.,Child Development and Learning Science, Key Laboratory of Ministry of Education, Southeast University, Nanjing, China
| | - Qiang Wang
- Nanjing Brain Hospital, Medical School of Nanjing University, Nanjing, China
| | - Rui Yan
- Department of Psychiatry, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China
| | - Shiwan Tao
- Department of Psychiatry, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China
| | - Haiyan Liu
- Department of Psychiatry, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China
| | - Zhijian Yao
- Department of Psychiatry, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China.,School of Biological Sciences and Medical Engineering, Southeast University, Nanjing, China.,Nanjing Brain Hospital, Medical School of Nanjing University, Nanjing, China
| | - Qing Lu
- School of Biological Sciences and Medical Engineering, Southeast University, Nanjing, China.,Child Development and Learning Science, Key Laboratory of Ministry of Education, Southeast University, Nanjing, China
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Shao J, Dai Z, Zhu R, Wang X, Tao S, Bi K, Tian S, Wang H, Sun Y, Yao Z, Lu Q. Early identification of bipolar from unipolar depression before manic episode: Evidence from dynamic rfMRI. Bipolar Disord 2019; 21:774-784. [PMID: 31407477 DOI: 10.1111/bdi.12819] [Citation(s) in RCA: 26] [Impact Index Per Article: 5.2] [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] [Indexed: 01/01/2023]
Abstract
OBJECTIVE Misdiagnosis of bipolar disorder (BD) as unipolar disorder (UD) may cause improper treatment strategy to be chosen, especially in the early stages of disease. The aim of this study was to characterize alterations in specific brain networks for depressed patients who transformed into BD (tBD) from UD. METHOD The module allegiance from resting-fMRI by applying a multilayer modular method was estimated in 99 patients (33 tBD, 33 BD, 33 UD) and 33 healthy controls (HC). A classification model was trained on tBD and UD patients. HC was used to explore the functional declination patterns of BD, tBD, and UD. RESULTS Based on our classification model, difference mainly reflected in default-mode network (DMN). Compared with HC, both BD and tBD focused on the difference of somatomotor network (SMN), while UD on the abnormity of DMN. The patterns of brain network between patients with BD and tBD were well-overlapped, except for cognitive control network (CCN). CONCLUSION The functional declination of internal interaction in DMN was suggested to be useful for the identification of BD from UD in the early stage. The higher recruitment of DMN may predispose patients to depressive states, while higher recruitment of SMN makes them more sensitive to external stimuli and prone to mania. Furthermore, CCN may be a critical network for identifying different stages of BD, suggesting that the onset of mania in depressed patients is accompanied by CCN related cognitive impairments.
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Affiliation(s)
- Junneng Shao
- School of Biological Sciences & Medical Engineering, Southeast University, Nanjing, China.,Child Development and Learning Science, Key Laboratory of Ministry of Education, Nanjing, China
| | - Zhongpeng Dai
- School of Biological Sciences & Medical Engineering, Southeast University, Nanjing, China.,Child Development and Learning Science, Key Laboratory of Ministry of Education, Nanjing, China
| | - Rongxin Zhu
- Department of Psychiatry, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China.,Nanjing Brain Hospital, Medical School of Nanjing University, Nanjing, China
| | - Xinyi Wang
- School of Biological Sciences & Medical Engineering, Southeast University, Nanjing, China.,Child Development and Learning Science, Key Laboratory of Ministry of Education, Nanjing, China
| | - Shiwan Tao
- Department of Psychiatry, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China.,Nanjing Brain Hospital, Medical School of Nanjing University, Nanjing, China
| | - Kun Bi
- School of Biological Sciences & Medical Engineering, Southeast University, Nanjing, China.,Child Development and Learning Science, Key Laboratory of Ministry of Education, Nanjing, China
| | - Shui Tian
- School of Biological Sciences & Medical Engineering, Southeast University, Nanjing, China.,Child Development and Learning Science, Key Laboratory of Ministry of Education, Nanjing, China
| | - Huan Wang
- School of Biological Sciences & Medical Engineering, Southeast University, Nanjing, China.,Child Development and Learning Science, Key Laboratory of Ministry of Education, Nanjing, China
| | - Yurong Sun
- School of Biological Sciences & Medical Engineering, Southeast University, Nanjing, China.,Child Development and Learning Science, Key Laboratory of Ministry of Education, Nanjing, China
| | - Zhijian Yao
- Department of Psychiatry, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China.,Nanjing Brain Hospital, Medical School of Nanjing University, Nanjing, China
| | - Qing Lu
- School of Biological Sciences & Medical Engineering, Southeast University, Nanjing, China.,Child Development and Learning Science, Key Laboratory of Ministry of Education, Nanjing, China
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42
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Tian S, Sun Y, Shao J, Zhang S, Mo Z, Liu X, Wang Q, Wang L, Zhao P, Chattun MR, Yao Z, Si T, Lu Q. Predicting escitalopram monotherapy response in depression: The role of anterior cingulate cortex. Hum Brain Mapp 2019; 41:1249-1260. [PMID: 31758634 PMCID: PMC7268019 DOI: 10.1002/hbm.24872] [Citation(s) in RCA: 20] [Impact Index Per Article: 4.0] [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: 08/17/2019] [Revised: 11/04/2019] [Accepted: 11/12/2019] [Indexed: 12/22/2022] Open
Abstract
Neuroimaging biomarkers of treatment efficacy can be used to guide personalized treatment in major depressive disorder (MDD). Escitalopram is recommended as first-line therapy for MDD and severe depression. An interesting hypothesis suggests that the reconfiguration of dynamic brain networks might provide important insights into antidepressant mechanisms. The present study assesses whether the spatiotemporal modulation across functional brain networks could serve as a predictor of effective antidepressant treatment with escitalopram. A total of 106 first-episode, drug-naïve patients and 109 healthy controls from three different multicenters underwent resting-state functional magnetic resonance imaging. Patients were considered as responders if they had a reduction of at least 50% in Hamilton Rating Scale for Depression scores at endpoint (>2 weeks). Multilayer modularity framework was applied on the whole brain to construct features in relation to network dynamic characters that were used for multivariate pattern analysis. Linear soft-threshold support vector machine models were used to separate responders from nonresponders. The permutation tests demonstrated the robustness of discrimination performances. The discriminative regions formed a spatially distributed pattern with anterior cingulate cortex (ACC) as the hub in the default mode subnetwork. Interestingly, a significantly larger module allegiance of ACC was also found in treatment responders compared to nonresponders, suggesting high interactivities of ACC to other regions may be beneficial for the recovery after treatment. Consistent results across multicenters confirmed that ACC could serve as a predictor of escitalopram monotherapy treatment outcome, implying strong likelihood of replication in the future.
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Affiliation(s)
- Shui Tian
- School of Biological Sciences and Medical Engineering, Southeast University, Nanjing, China.,Child Development and Learning Science, Key Laboratory of Ministry of Education, Nanjing, China
| | - Yurong Sun
- School of Biological Sciences and Medical Engineering, Southeast University, Nanjing, China.,Child Development and Learning Science, Key Laboratory of Ministry of Education, Nanjing, China
| | - Junneng Shao
- School of Biological Sciences and Medical Engineering, Southeast University, Nanjing, China.,Child Development and Learning Science, Key Laboratory of Ministry of Education, Nanjing, China
| | - Siqi Zhang
- School of Biological Sciences and Medical Engineering, Southeast University, Nanjing, China.,Child Development and Learning Science, Key Laboratory of Ministry of Education, Nanjing, China
| | - Zhaoqi Mo
- School of Biological Sciences and Medical Engineering, Southeast University, Nanjing, China.,Child Development and Learning Science, Key Laboratory of Ministry of Education, Nanjing, China
| | - Xiaoxue Liu
- Department of Psychiatry, Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, China
| | - Qiang Wang
- Nanjing Brain Hospital, Medical School of Nanjing University, Nanjing, China
| | - Li Wang
- Peking University Institute of Mental Health & Sixth Hospital, Beijing, China.,National Clinical Research Center for Mental Disorder & The Key Laboratory of Mental Health, Ministry of Health, Ministry of Health (Peking University), Beijing, China
| | - Peng Zhao
- Department of Medical Psychology, Affiliated Nanjing Drum Tower Hospital, Medical School of Nanjing University, Nanjing, China
| | - Mohammad Ridwan Chattun
- Department of Psychiatry, Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, China
| | - Zhijian Yao
- Department of Psychiatry, Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, China.,Nanjing Brain Hospital, Medical School of Nanjing University, Nanjing, China
| | - Tianmei Si
- Peking University Institute of Mental Health & Sixth Hospital, Beijing, China.,National Clinical Research Center for Mental Disorder & The Key Laboratory of Mental Health, Ministry of Health, Ministry of Health (Peking University), Beijing, China
| | - Qing Lu
- School of Biological Sciences and Medical Engineering, Southeast University, Nanjing, China.,Child Development and Learning Science, Key Laboratory of Ministry of Education, Nanjing, China
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Zhan JY, Shao J. [The early detection and intervention of iron deficiency in infant]. Zhonghua Er Ke Za Zhi 2019; 57:813-815. [PMID: 31594073 DOI: 10.3760/cma.j.issn.0578-1310.2019.10.019] [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: 06/10/2023]
Affiliation(s)
- J Y Zhan
- Division of Child Health Care, Children's Hospital, Zhejiang University School of Medicine, Hangzhou 310003, China
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Ning T, Shao J, Zhang X, Luo X, Huang X, Wu H, Xu S, Wu B, Ma D. Ageing affects the proliferation and mineralization of rat dental pulp stem cells under inflammatory conditions. Int Endod J 2019; 53:72-83. [PMID: 31419325 DOI: 10.1111/iej.13205] [Citation(s) in RCA: 17] [Impact Index Per Article: 3.4] [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: 04/18/2019] [Accepted: 08/13/2019] [Indexed: 02/06/2023]
Abstract
AIM To comparatively evaluate changes in the proliferation and mineralization abilities of dental pulp stem cells (DPSCs) from juvenile and adult rats in a lipopolysaccharide (LPS)-induced inflammatory microenvironment to provide a theoretical basis for the age-related differences observed in DPSCs during repair of inflammatory injuries. METHODOLOGY DPSCs were isolated from juvenile (JDPSCs) and adult rats (ADPSCs), and senescence-associated β-galactosidase staining was used to compare senescence between JDPSCs and ADPSCs. Effects of LPS on JDPSCs and ADPSCs proliferation were investigated by cell counting kit-8 assays and flow cytometry. Alizarin red staining, quantitative reverse transcription polymerase chain reaction and Western blot assay were used to examine the effects of LPS on mineralization-related genes and proteins in JDPSCs and ADPSCs. Immunohistochemistry was used to compare interleukin-1β (IL-1β) and osteocalcin (OCN) expression in the pulpitis model. Unpaired Student's t-tests and one-way anova were used for statistical analysis. RESULTS DPSCs were isolated from juvenile and adult rat dental pulp tissues. At low concentrations (0.1-1 μg mL-1 ), LPS significantly promoted the proliferation of JDPSCs (P < 0.01) and ADPSCs (P < 0.01 or P < 0.05), with the effect being stronger in JDPSCs than in ADPSCs. In addition, mineralized nodules and the expression of mineralization-related genes (OCN, DSPP, ALP, BSP) increased significantly after stimulation with LPS (0.5 μg mL-1 ) in JDPSCs and ADPSCs (P < 0.01 or P < 0.05), and JDPSCs displayed a more obvious increase than ADPSCs. Western blots revealed OCN and ALP expression levels in JDPSCs treated with LPS were significantly upregulated (P < 0.05); meanwhile, ALP expression in ADPSCs increased slightly but significantly (P < 0.05), and OCN expression was not affected. Finally, IL-1β expression was significantly higher (P < 0.05) and OCN expression was significantly lower (P < 0.05) in the inflamed dental pulp of adult rats than in juvenile rats. CONCLUSIONS A certain degree of inflammatory stimulation promoted the proliferation and mineralization of DPSCs; however, this effect declined with age. The DPSCs of adult donors in an inflammatory microenvironment have a weaker repair ability than that of juvenile donors, who are better candidates for tissues damage repair.
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Affiliation(s)
- T Ning
- Department of Stomatology, Nanfang Hospital, Southern Medical University, Guangzhou, China.,College of Stomatology, Southern Medical University, Guangzhou, China.,Department of Endodontics, Stomatological Hospital, Southern Medical University, Guangzhou, China
| | - J Shao
- Department of Stomatology, Guangzhou Hospital of Integrated Traditional and West Medicine, Guangzhou, China
| | - X Zhang
- Department of Stomatology, Nanfang Hospital, Southern Medical University, Guangzhou, China.,College of Stomatology, Southern Medical University, Guangzhou, China
| | - X Luo
- Department of Stomatology, Nanfang Hospital, Southern Medical University, Guangzhou, China.,College of Stomatology, Southern Medical University, Guangzhou, China
| | - X Huang
- Department of Stomatology, Nanfang Hospital, Southern Medical University, Guangzhou, China.,College of Stomatology, Southern Medical University, Guangzhou, China
| | - H Wu
- Department of Stomatology, Nanfang Hospital, Southern Medical University, Guangzhou, China.,College of Stomatology, Southern Medical University, Guangzhou, China
| | - S Xu
- College of Stomatology, Southern Medical University, Guangzhou, China.,Department of Endodontics, Stomatological Hospital, Southern Medical University, Guangzhou, China
| | - B Wu
- Department of Stomatology, Nanfang Hospital, Southern Medical University, Guangzhou, China.,College of Stomatology, Southern Medical University, Guangzhou, China
| | - D Ma
- Department of Stomatology, Nanfang Hospital, Southern Medical University, Guangzhou, China.,College of Stomatology, Southern Medical University, Guangzhou, China
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Amenomori M, Bao YW, Bi XJ, Chen D, Chen TL, Chen WY, Chen X, Chen Y, Cui SW, Ding LK, Fang JH, Fang K, Feng CF, Feng Z, Feng ZY, Gao Q, Gou QB, Guo YQ, He HH, He ZT, Hibino K, Hotta N, Hu H, Hu HB, Huang J, Jia HY, Jiang L, Jin HB, Kajino F, Kasahara K, Katayose Y, Kato C, Kato S, Kawata K, Kozai M, Le GM, Li AF, Li HJ, Li WJ, Lin YH, Liu B, Liu C, Liu JS, Liu MY, Lou YQ, Lu H, Meng XR, Mitsui H, Munakata K, Nakamura Y, Nanjo H, Nishizawa M, Ohnishi M, Ohta I, Ozawa S, Qian XL, Qu XB, Saito T, Sakata M, Sako TK, Sengoku Y, Shao J, Shibata M, Shiomi A, Sugimoto H, Takita M, Tan YH, Tateyama N, Torii S, Tsuchiya H, Udo S, Wang H, Wu HR, Xue L, Yagisawa K, Yamamoto Y, Yang Z, Yuan AF, Zhai LM, Zhang HM, Zhang JL, Zhang X, Zhang XY, Zhang Y, Zhang Y, Zhang Y, Zhou XX. First Detection of Photons with Energy beyond 100 TeV from an Astrophysical Source. Phys Rev Lett 2019; 123:051101. [PMID: 31491288 DOI: 10.1103/physrevlett.123.051101] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/04/2019] [Revised: 05/21/2019] [Indexed: 06/10/2023]
Abstract
We report on the highest energy photons from the Crab Nebula observed by the Tibet air shower array with the underground water-Cherenkov-type muon detector array. Based on the criterion of a muon number measured in an air shower, we successfully suppress 99.92% of the cosmic-ray background events with energies E>100 TeV. As a result, we observed 24 photonlike events with E>100 TeV against 5.5 background events, which corresponds to a 5.6σ statistical significance. This is the first detection of photons with E>100 TeV from an astrophysical source.
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Affiliation(s)
- M Amenomori
- Department of Physics, Hirosaki University, Hirosaki 036-8561, Japan
| | - Y W Bao
- School of Astronomy and Space Science, Nanjing University, Nanjing 210093, China
| | - X J Bi
- Key Laboratory of Particle Astrophysics, Institute of High Energy Physics, Chinese Academy of Sciences, Beijing 100049, China
| | - D Chen
- National Astronomical Observatories, Chinese Academy of Sciences, Beijing 100012, China
| | - T L Chen
- Physics Department of Science School, Tibet University, Lhasa 850000, China
| | - W Y Chen
- Key Laboratory of Particle Astrophysics, Institute of High Energy Physics, Chinese Academy of Sciences, Beijing 100049, China
| | - Xu Chen
- Key Laboratory of Particle Astrophysics, Institute of High Energy Physics, Chinese Academy of Sciences, Beijing 100049, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Y Chen
- School of Astronomy and Space Science, Nanjing University, Nanjing 210093, China
| | - S W Cui
- Department of Physics, Hebei Normal University, Shijiazhuang 050016, China
| | - L K Ding
- Key Laboratory of Particle Astrophysics, Institute of High Energy Physics, Chinese Academy of Sciences, Beijing 100049, China
| | - J H Fang
- Key Laboratory of Particle Astrophysics, Institute of High Energy Physics, Chinese Academy of Sciences, Beijing 100049, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - K Fang
- Key Laboratory of Particle Astrophysics, Institute of High Energy Physics, Chinese Academy of Sciences, Beijing 100049, China
| | - C F Feng
- Department of Physics, Shandong University, Jinan 250100, China
| | - Zhaoyang Feng
- Key Laboratory of Particle Astrophysics, Institute of High Energy Physics, Chinese Academy of Sciences, Beijing 100049, China
| | - Z Y Feng
- Institute of Modern Physics, SouthWest Jiaotong University, Chengdu 610031, China
| | - Qi Gao
- Physics Department of Science School, Tibet University, Lhasa 850000, China
| | - Q B Gou
- Key Laboratory of Particle Astrophysics, Institute of High Energy Physics, Chinese Academy of Sciences, Beijing 100049, China
| | - Y Q Guo
- Key Laboratory of Particle Astrophysics, Institute of High Energy Physics, Chinese Academy of Sciences, Beijing 100049, China
| | - H H He
- Key Laboratory of Particle Astrophysics, Institute of High Energy Physics, Chinese Academy of Sciences, Beijing 100049, China
| | - Z T He
- Department of Physics, Hebei Normal University, Shijiazhuang 050016, China
| | - K Hibino
- Faculty of Engineering, Kanagawa University, Yokohama 221-8686, Japan
| | - N Hotta
- Faculty of Education, Utsunomiya University, Utsunomiya 321-8505, Japan
| | - Haibing Hu
- Physics Department of Science School, Tibet University, Lhasa 850000, China
| | - H B Hu
- Key Laboratory of Particle Astrophysics, Institute of High Energy Physics, Chinese Academy of Sciences, Beijing 100049, China
| | - J Huang
- Key Laboratory of Particle Astrophysics, Institute of High Energy Physics, Chinese Academy of Sciences, Beijing 100049, China
| | - H Y Jia
- Institute of Modern Physics, SouthWest Jiaotong University, Chengdu 610031, China
| | - L Jiang
- Key Laboratory of Particle Astrophysics, Institute of High Energy Physics, Chinese Academy of Sciences, Beijing 100049, China
| | - H B Jin
- National Astronomical Observatories, Chinese Academy of Sciences, Beijing 100012, China
| | - F Kajino
- Department of Physics, Konan University, Kobe 658-8501, Japan
| | - K Kasahara
- Research Institute for Science and Engineering, Waseda University, Tokyo 169-8555, Japan
| | - Y Katayose
- Faculty of Engineering, Yokohama National University, Yokohama 240-8501, Japan
| | - C Kato
- Department of Physics, Shinshu University, Matsumoto 390-8621, Japan
| | - S Kato
- Institute for Cosmic Ray Research, University of Tokyo, Kashiwa 277-8582, Japan
| | - K Kawata
- Institute for Cosmic Ray Research, University of Tokyo, Kashiwa 277-8582, Japan
| | - M Kozai
- Institute of Space and Astronautical Science, Japan Aerospace Exploration Agency (ISAS/JAXA), Sagamihara 252-5210, Japan
| | - G M Le
- National Center for Space Weather, China Meteorological Administration, Beijing 100081, China
| | - A F Li
- Key Laboratory of Particle Astrophysics, Institute of High Energy Physics, Chinese Academy of Sciences, Beijing 100049, China
- Department of Physics, Shandong University, Jinan 250100, China
- School of Information Science and Engineering, Shandong Agriculture University, Taian 271018, China
| | - H J Li
- Physics Department of Science School, Tibet University, Lhasa 850000, China
| | - W J Li
- Key Laboratory of Particle Astrophysics, Institute of High Energy Physics, Chinese Academy of Sciences, Beijing 100049, China
- Institute of Modern Physics, SouthWest Jiaotong University, Chengdu 610031, China
| | - Y H Lin
- Key Laboratory of Particle Astrophysics, Institute of High Energy Physics, Chinese Academy of Sciences, Beijing 100049, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - B Liu
- School of Astronomy and Space Science, Nanjing University, Nanjing 210093, China
| | - C Liu
- Key Laboratory of Particle Astrophysics, Institute of High Energy Physics, Chinese Academy of Sciences, Beijing 100049, China
| | - J S Liu
- Key Laboratory of Particle Astrophysics, Institute of High Energy Physics, Chinese Academy of Sciences, Beijing 100049, China
| | - M Y Liu
- Physics Department of Science School, Tibet University, Lhasa 850000, China
| | - Y-Q Lou
- Physics Department, Astronomy Department and Tsinghua Center for Astrophysics, Tsinghua-National Astronomical Observatories of China joint Research Center for Astrophysics, Tsinghua University, Beijing 100084, China
| | - H Lu
- Key Laboratory of Particle Astrophysics, Institute of High Energy Physics, Chinese Academy of Sciences, Beijing 100049, China
| | - X R Meng
- Physics Department of Science School, Tibet University, Lhasa 850000, China
| | - H Mitsui
- Faculty of Engineering, Yokohama National University, Yokohama 240-8501, Japan
| | - K Munakata
- Department of Physics, Shinshu University, Matsumoto 390-8621, Japan
| | - Y Nakamura
- Key Laboratory of Particle Astrophysics, Institute of High Energy Physics, Chinese Academy of Sciences, Beijing 100049, China
| | - H Nanjo
- Department of Physics, Hirosaki University, Hirosaki 036-8561, Japan
| | - M Nishizawa
- National Institute of Informatics, Tokyo 101-8430, Japan
| | - M Ohnishi
- Institute for Cosmic Ray Research, University of Tokyo, Kashiwa 277-8582, Japan
| | - I Ohta
- Sakushin Gakuin University, Utsunomiya 321-3295, Japan
| | - S Ozawa
- Research Institute for Science and Engineering, Waseda University, Tokyo 169-8555, Japan
| | - X L Qian
- Department of Mechanical and Electrical Engineering, Shandong Management University, Jinan 250357, China
| | - X B Qu
- College of Science, China University of Petroleum, Qingdao, 266555, China
| | - T Saito
- Tokyo Metropolitan College of Industrial Technology, Tokyo 116-8523, Japan
| | - M Sakata
- Department of Physics, Konan University, Kobe 658-8501, Japan
| | - T K Sako
- Institute for Cosmic Ray Research, University of Tokyo, Kashiwa 277-8582, Japan
| | - Y Sengoku
- Faculty of Engineering, Yokohama National University, Yokohama 240-8501, Japan
| | - J Shao
- Key Laboratory of Particle Astrophysics, Institute of High Energy Physics, Chinese Academy of Sciences, Beijing 100049, China
- Department of Physics, Shandong University, Jinan 250100, China
| | - M Shibata
- Faculty of Engineering, Yokohama National University, Yokohama 240-8501, Japan
| | - A Shiomi
- College of Industrial Technology, Nihon University, Narashino 275-8576, Japan
| | - H Sugimoto
- Shonan Institute of Technology, Fujisawa 251-8511, Japan
| | - M Takita
- Institute for Cosmic Ray Research, University of Tokyo, Kashiwa 277-8582, Japan
| | - Y H Tan
- Key Laboratory of Particle Astrophysics, Institute of High Energy Physics, Chinese Academy of Sciences, Beijing 100049, China
| | - N Tateyama
- Faculty of Engineering, Kanagawa University, Yokohama 221-8686, Japan
| | - S Torii
- Research Institute for Science and Engineering, Waseda University, Tokyo 169-8555, Japan
| | - H Tsuchiya
- Japan Atomic Energy Agency, Tokai-mura 319-1195, Japan
| | - S Udo
- Faculty of Engineering, Kanagawa University, Yokohama 221-8686, Japan
| | - H Wang
- Key Laboratory of Particle Astrophysics, Institute of High Energy Physics, Chinese Academy of Sciences, Beijing 100049, China
| | - H R Wu
- Key Laboratory of Particle Astrophysics, Institute of High Energy Physics, Chinese Academy of Sciences, Beijing 100049, China
| | - L Xue
- Department of Physics, Shandong University, Jinan 250100, China
| | - K Yagisawa
- Faculty of Engineering, Yokohama National University, Yokohama 240-8501, Japan
| | - Y Yamamoto
- Department of Physics, Konan University, Kobe 658-8501, Japan
| | - Z Yang
- Key Laboratory of Particle Astrophysics, Institute of High Energy Physics, Chinese Academy of Sciences, Beijing 100049, China
| | - A F Yuan
- Physics Department of Science School, Tibet University, Lhasa 850000, China
| | - L M Zhai
- National Astronomical Observatories, Chinese Academy of Sciences, Beijing 100012, China
| | - H M Zhang
- Key Laboratory of Particle Astrophysics, Institute of High Energy Physics, Chinese Academy of Sciences, Beijing 100049, China
| | - J L Zhang
- Key Laboratory of Particle Astrophysics, Institute of High Energy Physics, Chinese Academy of Sciences, Beijing 100049, China
| | - X Zhang
- School of Astronomy and Space Science, Nanjing University, Nanjing 210093, China
| | - X Y Zhang
- Department of Physics, Shandong University, Jinan 250100, China
| | - Y Zhang
- Key Laboratory of Particle Astrophysics, Institute of High Energy Physics, Chinese Academy of Sciences, Beijing 100049, China
| | - Yi Zhang
- Key Laboratory of Particle Astrophysics, Institute of High Energy Physics, Chinese Academy of Sciences, Beijing 100049, China
| | - Ying Zhang
- Key Laboratory of Particle Astrophysics, Institute of High Energy Physics, Chinese Academy of Sciences, Beijing 100049, China
| | - X X Zhou
- Institute of Modern Physics, SouthWest Jiaotong University, Chengdu 610031, China
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Shao J, Liang J, Zhong S. miR-30a-5p modulates traits of cutaneous squamous cell carcinoma (cSCC) via forkhead box protein G1 (FOXG1). Neoplasma 2019; 66:908-917. [PMID: 31307196 DOI: 10.4149/neo_2018_181205n923] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2018] [Accepted: 04/29/2019] [Indexed: 11/08/2022]
Abstract
miRNA has shown its potential in the regulation of squamous cell carcinoma (SCC). However, the mechanism of such an effect was not quite clear. Therefore, we aimed to investigate whether miR-30a-5p participated in the regulation of cutaneous SCC (cSCC) and the possible mechanism involved. 5-Ethynyl-2'-deoxyuridine (EdU) and cell cycle were measured using flow cytometry. The formation of cell colony was tested by colony formation assay. The capacities of migration and invasion were tested by wound healing assay and Transwell invasion assay, respectively. The target of miR-30a-5p was predicted by bioinformatics and identified by luciferase assay. Western blot was used for the determination of proteins and qPCR was for mRNA levels. miR-30a-5p expression was lowered in SCL-1 and A431 cells, and its upregulation suppressed EdU positive cells, colony numbers, migration, invasion and Bcl-2 expression, and elevated Bcl-2-associated X protein (Bax) and cleaved Caspase-3 expressions, arresting cell cycle in G1 phase. Moreover, forkhead box protein G1 (FOXG1) was proved to be the target of miR-30a-5p, and FOXG1 overexpression partially offsets the decreased colony numbers, migration and invasion rates due to miR-30a-5p overexpression in SCL-1 and A431 cells. miR-30a-5p showed a regulatory role on the expression of FOXG1 and further modulated the progressing of cSCC cells, which could be a novel pathway intervening the development of cSCC.
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Affiliation(s)
- J Shao
- Department of Dermatology, Yantai Yuhuangding Hospital, Yantai, China
| | - J Liang
- Department of Dermatology, Yantai Yuhuangding Hospital, Yantai, China
| | - S Zhong
- Department of Dermatology, Yantai Yeda Hospital, Yantai, China
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Zhang YH, Song J, Shen L, Shao J. Systematic identification of lncRNAs and circRNAs-associated ceRNA networks in human lumbar disc degeneration. Biotech Histochem 2019; 94:606-616. [PMID: 31271316 DOI: 10.1080/10520295.2019.1622782] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [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: 12/26/2022] Open
Abstract
Lumbar disc degeneration (LDD) is a common cause of low back and neck pain. The molecular mechanisms underlying LDD, however, are unclear. Noncoding RNAs have been reported to participate in human diseases. We investigated a series of public datasets (GSE67566, GSE56081 and GSE63492) and identified 568 mRNAs, 55 microRNAs (miRNAs), 765 long noncoding RNAs (lncRNAs), and 586 circular RNAs (circRNAs) that were expressed differently in LDD than in normal discs. We constructed lncRNAs and circRNAs regulated competing endogenous RNAs (ceRNA) networks in LDD. Four lncRNAs, DANCR, CASK-AS1, SCARNA2, and LINC00638), and three circRNAs, hsa_circ_0005139, hsa_circ_0037858, and hsa_circ_0087890, were identified as key regulators of LDD progression. We found that hsa-miR-486-5p regulated the crosstalk among circRNA hsa_circ_0000189, lncRNA DANCR and 6 mRNAs, PYCR2, TOB1, ARHGAP5, RBPJ, CD247, SLC34A1. Gene ontology (GO) analysis demonstrated that these differently expressed lncRNAs and circRNAs were involved in cellular component organization or biogenesis, gene expression and negative regulation of metabolic processes. Our findings provide useful information for exploring new mechanisms for LDD and candidates for therapeutic targets.
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Affiliation(s)
- Y-H Zhang
- Spine Center, Xin Hua Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - J Song
- Spine Center, Xin Hua Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - L Shen
- Spine Center, Xin Hua Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - J Shao
- Spine Center, Xin Hua Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China
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48
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Shao J, Rodrigues M, Corter AL, Baxter NN. Multidisciplinary care of breast cancer patients: a scoping review of multidisciplinary styles, processes, and outcomes. Curr Oncol 2019; 26:e385-e397. [PMID: 31285683 PMCID: PMC6588064 DOI: 10.3747/co.26.4713] [Citation(s) in RCA: 39] [Impact Index Per Article: 7.8] [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] [Indexed: 12/18/2022] Open
Abstract
Background Clinical practice guidelines recommend a multidisciplinary approach to cancer care that brings together all relevant disciplines to discuss optimal disease management. However, the literature is characterized by heterogeneous definitions and few reviews about the processes and outcomes of multidisciplinary care. The objective of this scoping review was to identify and classify the definitions and characteristics of multidisciplinary care, as well as outcomes and interventions for patients with breast cancer. Methods A systematic search for quantitative and qualitative studies about multidisciplinary care for patients with breast cancer was conducted for January 2001 to December 2017 in the following electronic databases: medline, embase, PsycInfo, and cinahl. Two reviewers independently applied our eligibility criteria at level 1 (title/abstract) and level 2 (full-text) screening. Data were extracted and synthesized descriptively. Results The search yielded 9537 unique results, of which 191 were included in the final analysis. Two main types of multidisciplinary care were identified: conferences and clinics. Most studies focused on outcomes of multidisciplinary care that could be variously grouped at the patient, provider, and system levels. Research into processes tended to focus on processes that facilitate implementation: team-working, meeting logistics, infrastructure, quality audit, and barriers and facilitators. Summary Approaches to multidisciplinary care using conferences and clinics are well described. However, studies vary by design, clinical context, patient population, and study outcome. The heterogeneity of the literature, including the patient populations studied, warrants further specification of multidisciplinary care practice and systematic reviews of the processes or contexts that make the implementation and operation of multidisciplinary care effective.
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Affiliation(s)
- J Shao
- Li Ka Shing Knowledge Institute, St. Michael's Hospital, Toronto, ON
| | - M Rodrigues
- Li Ka Shing Knowledge Institute, St. Michael's Hospital, Toronto, ON
| | - A L Corter
- Li Ka Shing Knowledge Institute, St. Michael's Hospital, Toronto, ON
| | - N N Baxter
- Li Ka Shing Knowledge Institute, St. Michael's Hospital, Toronto, ON
- Institute of Health Policy, Management and Evaluation, University of Toronto, Toronto, ON
- Department of Surgery, St. Michael's Hospital, Toronto, ON
- Institute for Clinical Evaluative Sciences, University of Toronto, Toronto, ON
- Division of General Surgery, Department of Surgery, University of Toronto, Toronto, ON
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49
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Amenomori M, Bi XJ, Chen D, Chen TL, Chen WY, Cui SW, Danzengluobu, Ding LK, Feng CF, Feng Z, Feng ZY, Gou QB, Guo YQ, He HH, He ZT, Hibino K, Hotta N, Hu H, Hu HB, Huang J, Jia HY, Jiang L, Kajino F, Kasahara K, Katayose Y, Kato C, Kawata K, Kozai M, Labaciren, Le GM, Li AF, Li HJ, Li WJ, Lin YH, Liu C, Liu JS, Liu MY, Lu H, Meng XR, Miyazaki T, Munakata K, Nakajima T, Nakamura Y, Nanjo H, Nishizawa M, Niwa T, Ohnishi M, Ohta I, Ozawa S, Qian XL, Qu XB, Saito T, Saito TY, Sakata M, Sako TK, Shao J, Shibata M, Shiomi A, Shirai T, Sugimoto H, Takita M, Tan YH, Tateyama N, Torii S, Tsuchiya H, Udo S, Wang H, Wu HR, Xue L, Yamamoto Y, Yamauchi K, Yang Z, Yuan AF, Zhai LM, Zhang HM, Zhang JL, Zhang XY, Zhang Y, Zhang Y, Zhang Y, Zhaxisangzhu, Zhou XX. The cosmic ray energy spectrum measured with the new Tibet hybrid experiment. EPJ Web Conf 2019. [DOI: 10.1051/epjconf/201920803001] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Abstract
We have upgraded the new Tibet ASgamma experiment in China since 2014 to measure the chemical composition of cosmic rays around the knee. This hybrid experiment consist of an air-shower-core detector array (YAC-II) to detect high energy electromagnetic component, the Tibet air-shower array (Tibet-III) and a large underground water-Cherenkov muon-detector array (MD). We have carried out a detailed air-shower Monte Carlo (MC) simulation to study the performance of the hybrid detectors by using CORSIKA (version 7.5000), which includes EPOS-LHC, QGSJETII-04, SIBYLL2.1 and SIBYLL2.3 hadronic interaction models. The preliminary results of the interaction model checking above 50 TeV energy region are reported in this paper, and the primary proton and helium spectra in the energy range 50 TeV to 1015 eV was derived from YAC-I data and is smoothly connected with direct observation data at lower energies and also with our previously reported works at higher energies within statistical errors. The knee of the (P+He) spectra is located around 400 TeV. The interaction model dependence in deriving the primary (P+He) spectra is found to be small (less than 25% in absolute intensity, 10% in position of the knee), and the composition model dependence is less than 10% in absolute intensity.
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50
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Yang JLX, Zhang Y, Feng WW, Tang H, Shao J, Wang NR, Wang H, Sun J, Luo Y, Lyu LQ, Yan SQ, Zhao DM, Mu LJ, Yan DM, Wang H, Gao XT, He MF, Yang J, Fu M, Sanders M, Haslam D. [Practice of parenting and related factors on children aged 0-5 in the urban areas of China]. Zhonghua Liu Xing Bing Xue Za Zhi 2019; 40:422-426. [PMID: 31006202 DOI: 10.3760/cma.j.issn.0254-6450.2019.04.010] [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] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 06/09/2023]
Abstract
Objective: To characterize the relations between the practice of parenting and associated factors on children (0-5 years old) in urban areas of China, in order to provide evidence for promoting the early development of children and to provide positive guidance and service programs on parenting. Methods: A total of 4 515 parents from 15 cities (14 provinces) were surveyed with a self-administered questionnaire. Parenting and Family Adjustment Scales (PAFAS) was used, including parameters as: consistency and coercive parenting, positive encouragement, parent-child relationship and parental emotion adjustment, family relationship and parental teamwork aspects, etc. Both single factor analysis and multiple linear regression were used to examine the associations between parenting practice, individual, parental and family factors. Results: The mean score of PAFAS was 21.00 (15.00-28.00), associated with factors as children's age, only-child family, premature delivery, father's education level, confidence on parenting, problems regarding the parental mood, annual family income, family structure and behavior on seeking professional help, etc. Results showed that there were big differences on the practice of parenting in China and influenced by variety of factors. Conclusions: The general situation of parenting was well, in the urban areas of China. The practice of parenting was associated with a series of individual, parental and family factors. Programs on improving the parenting skills and promoting the early development of children, should be highlighted.
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Affiliation(s)
- J L X Yang
- National Center for Women and Children's Health, Chinese Center for Disease Control and Prevention, Beijing 100081, China
| | - Y Zhang
- National Center for Women and Children's Health, Chinese Center for Disease Control and Prevention, Beijing 100081, China
| | - W W Feng
- National Center for Women and Children's Health, Chinese Center for Disease Control and Prevention, Beijing 100081, China
| | - H Tang
- National Center for Women and Children's Health, Chinese Center for Disease Control and Prevention, Beijing 100081, China
| | - J Shao
- Zhejiang University School of Medicine Affiliated Children's Hospital, Hangzhou 310003, China
| | - N R Wang
- Chongqing Maternal and Child Health Hospital, Chongqing 400013, China
| | - H Wang
- Maternal and Child Health Hospital of Sichuan Province, Chengdu 610031, China
| | - J Sun
- Dalian Maternal and Child Health Hospital of Liaoning Province, Dalian 116033, China
| | - Y Luo
- Guiyang Maternal and Child Health Hospital, Guiyang 550003, China
| | - L Q Lyu
- Ningbo Women and Children's Hospital of Zhejiang Province, Ningbo 315000, China
| | - S Q Yan
- Ma'anshan Maternal and Child Health Hospital of Anhui Province, Ma'anshan 243011, China
| | - D M Zhao
- Qilu Children's Hospital of Shandong University, Jinan 250022, China
| | - L J Mu
- Fangshan District Maternal and Child Health Hospital of Beijing, Beijing 102488, China
| | - D M Yan
- Lianyungang Maternal and Child Health Hospital of Jiangsu Province, Lianyungang 222000, China
| | - H Wang
- Maternal and Child Health Hospital of Hubei Province, Wuhan 430070, China
| | - X T Gao
- Northwest Women and Children's Hospital, Xi'an710061, China
| | - M F He
- Maternal and Child Health Hospital Hunan Province, Changsha 410008, China
| | - J Yang
- Qinhuangdao Maternal and Child Health Hospital of Hebei Province, Qinhuangdao 066001, China
| | - M Fu
- Maternal and Child Health Hospital of Guangdong Province, Guangzhou 510010, China
| | - M Sanders
- The University of Queensland, Australia, Queensland 4072, Australia
| | - D Haslam
- The University of Queensland, Australia, Queensland 4072, Australia
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