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11. Melatonin attenuates cholestatic liver injury by improving bile acid metabolism in mice

Author

ZHANG Hongjia, TAN Ya, and ZHAO Nan

Subjects
liver injury, cholestasis, melatonin, bile acids metabolism, Medicine (General), R5-920
Abstract

Objective To explore the mechanism of melatonin (Mel) alleviating cholestatic liver injury in a mouse cholestasis model induced by cholic acid (CA) feeding. Methods A total of 15 8-week-old male C57BL/6J mice were randomly divided into control group, 1%CA group, and 1%CA+Mel group, with 5 animals in each group. The control group was fed with normal chow diet, and the other 2 groups were fed with a diet containing 1%CA for 14 d to construct a model of cholestasis, and intraperitoneal injection with 100 mg/kg Mel was given to the mice from the 1%CA+Mel group. Immunohistochemical assay of α-SMA was applied for the liver tissues in the 1%CA group and the 1%CA+Mel group. The mRNA expression levels of fibrosis-related indicators in mouse liver tissue were examined by RT-qPCR. Liquid chromatography tandem mass spectrometry (LC-MS/MS) and automated biochemical analyzer were used to detect the contents of bile acids in the liver tissues and the serum of mouse, respectively. Then real-time qPCR and Western blotting were applied to detect the expression of bile acid synthesis and liver detoxification enzymes related indicators at mRNA and protein levels, respectively, to further investigate the mechanism of bile acid metabolism. Results Compared with the 1%CA group, the mRNA levels of liver fibrosis indicators (such as Tgfβ1, ColⅠa1, ColⅡa1 and α-SMA) were significantly reduced (P

Published
2024
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20. Preference for Community Health Services of Patients with Multimorbidity

Author

WEI Lifang, ZHANG Ling, TAN Ya, LUO Xiu

Subjects
multimorbidity, community health services, preference, discrete selection experiment, Medicine
Abstract

Background As aging process continues to accelerate in China, multimorbidity have become a major public problem that threatens the health of the entire population. In the current context of "Healthy China 2030", the health management of patients with multimorbidity needs to be urgently addressed. Objective To understand the preferences influencing the choice of community health services for patients with multimorbidity, explore the willingness to pay (WTP) of patients, so as to provide recommendations for improvements to the existing community health service system for chronic diseases. Methods Patients with multimorbidity were randomly selected from eight community health service centers in Chengdu during the period from May to August 2022 as survey subjects. General patient data and preferences related to discrete choice experiments were collected through on-site questionnaire surveys. Based on different types of comorbidities, patients with type 2 diabetes combined with hypertension, hypertension combined with coronary heart disease, type 2 diabetes combined with hypertension and coronary heart disease were categorized into ClassⅠ, ClassⅡ, and ClassⅢ. Regression analysis was conducted using mixed Logit model to analyze the preferences of multimorbidity patients for community health services, and to quantitatively analyze their WTP for community health services. Result A total of 360 questionnaires were distributed and 296 valid questionnaires were recovered, with a valid recovery rate of 82.7%. ClassⅠpatients (β=3.260, 95%CI=2.610 to 3.910), ClassⅡpatients (β=3.697, 95%CI=2.612 to 4.781), and ClassⅢpatients (β=3.220, 95%CI=2.271 to 4.169) expressed the strongest preference for services with high accessibility to drugs, followed by appointment referral services and traditional Chinese medicine (TCM) services. Regarding physician types and prescription service duration, both ClassⅠpatients (β=0.971, 95%CI=0.585 to 1.357) and ClassⅡpatients (β=0.686, 95%CI=0.176 to 1.197) preferred services with extended prescription services, while ClassⅢpatients (β=0.804, 95%CI=0.196 to 1.413) preferred services provided by general practitioners (β=0.804, 95%CI=0.196 to 1.413). ClassⅠpatients (β=-0.049, 95%CI=-0.057 to -0.041), ClassⅡpatients (β=-0.040, 95%CI=-0.051 to -0.029), and ClassⅢpatients (β=-0.037, 95%CI=-0.048 to -0.027) preferred services with lower out-of-pocket expenses. The results of the regression analysis of WTP for patients with different chronic comorbidity types showed that the WTP of all 3 types of patients was related to their level of preference for each attribute, with ClassⅠ, ClassⅡ, and ClassⅢpatients all had the highest WTP for a high level of drug accessibility, which were RMB 66.77/month, RMB 91.97/month, and RMB 85.95/month, respectively. Conclusion Patients with multimorbidity exhibit significant preferences for six attributes considered in this study (physician type, TCM service, prescription service duration, drug accessibility, appointment referral, and monthly out-of-pocket costs). Drug accessibility is the most important attribute influencing multimorbidity patients' health service preferences. It is recommended to target patients' specific needs accurately, improve appointment referral services, establish standards for the management of chronic diseases in the community, and accelerate the integration of TCM into the prevention and treatment of chronic diseases in the community.

Published
2024
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28. Unique DUOX2+ACE2+ small cholangiocytes are pathogenic targets for primary biliary cholangitis

Author

Li, Xi, Li, Yan, Xiao, Jintao, Wang, Huiwen, Guo, Yan, Mao, Xiuru, Shi, Pan, Hou, Yanliang, Zhang, Xiaoxun, Zhao, Nan, Zheng, Minghua, He, Yonghong, Ding, Jingjing, Tan, Ya, Liao, Min, Li, Ling, Peng, Ying, Li, Xuan, Pan, Qiong, Xie, Qiaoling, Li, Qiao, Li, Jianwei, Li, Ying, Chen, Zhe, Huang, Yongxiu, Assis, David N., Cai, Shi-Ying, Boyer, James L., Huang, Xuequan, Tang, Can-E, Liu, Xiaowei, Peng, Shifang, and Chai, Jin

Published
2023
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36. Predicting 3D structure and stability of RNA pseudoknots in monovalent and divalent ion solutions

Author

Shi, Ya-Zhou, Jin, Lei, Feng, Chen-Jie, Tan, Ya-Lan, and Tan, Zhi-Jie

Subjects
Physics - Biological Physics, Condensed Matter - Soft Condensed Matter, Physics - Chemical Physics, Quantitative Biology - Biomolecules
Abstract

RNA pseudoknots are a kind of minimal RNA tertiary structural motifs, and their three-dimensional (3D) structures and stability play essential roles in a variety of biological functions. Therefore, to predict 3D structures and stability of RNA pseudoknots is essential for understanding their functions. In the work, we employed our previously developed coarse-grained model with implicit salt to make extensive predictions and comprehensive analyses on the 3D structures and stability for RNA pseudoknots in monovalent/divalent ion solutions. The comparisons with available experimental data show that our model can successfully predict the 3D structures of RNA pseudoknots from their sequences, and can also make reliable predictions for the stability of RNA pseudoknots with different lengths and sequences over a wide range of monovalent/divalent ion concentrations. Furthermore, we made comprehensive analyses on the unfolding pathway for various RNA pseudoknots in ion solutions. Our analyses for extensive pseudokonts and the wide range of monovalent/divalent ion concentrations verify that the unfolding pathway of RNA pseudoknots is mainly dependent on the relative stability of unfolded intermediate states, and show that the unfolding pathway of RNA pseudoknots can be significantly modulated by their sequences and solution ion conditions., Comment: 23 pages, 8 figures

Published
2019
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47. Machine learning valence force field model

Author

Wan, Jing, Tan, Ya-Wen, Jiang, Jin-Wu, Chang, Tienchong, and Guo, Xingming

Subjects
Physics - Computational Physics, Condensed Matter - Materials Science
Abstract

The valence force field (VFF) model is a concise physical interpretation of the atomic interaction in terms of the bond and angle variations in the explicit quadratic functional form, while the machine learning (ML) method is a flexible numerical approach to make predictions based on some pre-obtained training data without the need of any explicit functions. We propose a so-called ML-VFF model, by combining the clear physical essence of the VFF model and the numerical flexibility of the ML method. Instead of imposing any explicit functional forms for the atomic interaction, the ML-VFF model predicts the potential and force with the Gaussian regression approach. We take graphene as an example to illustrate the ability of the ML-VFF model to make accurate predictions with relatively low computational expenses. We also discuss some key advantages and drawbacks of the ML-VFF model., Comment: four figures

Published
2018

48. Tunable mechanical properties of the graphene/MoS2 tubal van der Waals heterostructure

Author

Tan, Ya-Wen and Jiang, Jin-Wu

Subjects
Condensed Matter - Materials Science
Abstract

We propose a tubal van der Waals heterostructure by rolling up the graphene and MoS2 atomic layers into a tubal form. We illustrate that the interlayer space for the tubal van der Waals heterostructure can be varied in a specific range, which is determined by the competition between the interlayer van der Waals force and the mechanical properties of the atomic layers. The variability of the interlayer space can be utilized to efficiently tune mechanical properties of the tubal van der Waals heterostructure. More specifically, we demonstrate that the Poisson's ratio of the tubal van der Waals heterostructure can be manipulated by a factor of two by varying the interlayer space from 1.44 to 4.44. Our work promotes a new member with tunable Poisson's ratio to the van der Waals heterostructure family.

Published
2018

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