Causal relationship between depression and metabolic dysfunction-associated steatotic liver disease: a bidirectional Mendelian randomized study.

Background: With the global rise in obesity, metabolic dysfunction-associated steatotic liver disease (MASLD) has emerged as the most common chronic liver disease. Concurrently, depression is a highly prevalent mental disorder. As the incidence of MASLD and depression continues to increase, a growing body of research indicates a potential association between the two conditions. However, the direction of causality between depression and MASLD remains uncertain. To address this gap, our study utilizes a two-sample Mendelian randomization (MR) approach to explore the bidirectional causal relationship between depression and MASLD. Methods: We extracted single nucleotide polymorphisms (SNPs) associated with depression and MASLD from pooled data of genome-wide association studies (GWAS). A comprehensive assessment of possible causality was also performed. Possible mediating effects of liver enzymes on MASLD were also assessed. Results: A total of three GWAS pooled data on depression as well as GWAS data related to MASLD and GWAS data on four liver enzymes were used in this study. Our findings indicated a strong causal relationship between depression and MASLD (OR, 1.557; 95% CI, 1.097-2.211; P = 0.016). And we found a mediating effect of gamma-glutamyl transferase (GGT), alanine aminotransferase (ALT) and aspartate aminotransferase (AST). ALT 10% (95% CI: 7% - 13%, P< 0.0002). AST, 4.14% (95% CI: 2.34% - 5.94%, P < 0.05). GGT 0.19% (95% CI: 0.15% - 0.22%, P< 0.000000002). However, we did not find a mediating effect of alkaline phosphatase (ALP). Our inverse MR analysis did not reveal any causal relationship between MASLD and depression. Conclusions: The MR analysis revealed a positive causal relationship between depression and MASLD, while no reverse causal relationship was identified. Liver enzymes may mediate the role between depression and MASLD.

Does the disclosure of medical insurance information affect patients' willingness to adopt the diagnosis related groups system.

Introduction: Medical insurance information disclosure is not only a direct way for the public to understand and master social insurance information and resource use benefits, but also an important way for the public to participate in medical service governance and supervision. Some studies have shown that information disclosure can significantly reduce the risk perception of user groups, strengthen their trust and reduce the negative impact of information asymmetry. Methods: Based on risk perception and trust perception theories, this paper focuses on the mechanisms influencing patients' attitudes in the process of implementing a Diagnosis Related Groups payment system. Using medical insurance information disclosure from a governance perspective as the research object, the impact of medical insurance information disclosure on patients' willingness to adopt the Diagnosis Related Groups payment system was analyzed by means of a questionnaire survey, Data analysis and hypothesis testing via SPSS while the mechanism of the impact of medical insurance information disclosure on patients' attitudes was explored in depth. Results: It was found that medical insurance information disclosure had a significant positive effect on patients' trust perceptions and a significant negative effect on patients' risk perceptions. The more comprehensive information patients received, the stronger their trust and the lower their perceived risk. Discussion: This paper conducts an empirical study from patients' perspective, broadens the scope of research on medical insurance Diagnosis related groups, enriches the application of risk perception and trust perception theories in the medical field, and provides management suggestions for medical institutions in the management of medical insurance information disclosure.

Commercial dishes with gelatin-free microstructured inserts for elongated stem cell self-renewal and pluripotency.

Here, we report the scalable fabrication of 2i-functionalized micro-pyramid-array (µPyA/+2i) inserts for use in commercial multi-well plates, as the alternative cultivation platform for maintaining long-term self-renewal and pluripotency of multiple mESCs and mouse induced pluripotent stem cells. Relevant evidence including cell morphology characterization increased alkaline phosphatase activity, high expression of mESC self-renewal markers, decreased levels of differentiation-associated markers, and high proportion of self-renewal marker cells are provided. Further studies demonstrated that µPyA/+2i could cause a higher cell density in mESC colony, and induce gene expression changes. Subsequent studies showed that µPyA/+2i can influence the cytoskeleton and promote cell adhesion through Cldn-7 upregulation. In summary, these µPyA/+2i inserts offer flexible and gelatin-free micro-envriomnets to maintain long-term self-renewal and pluripotency of mESCs. Enabled by the microstructured inserst, the facile stem cell manipulation and transfer among culture dishes will broaden stem cells both in routine and translational applications.

Targets and Potential Mechanism of Scutellaria baicalensis in Treatment of Primary Hepatocellular Carcinoma Based on Bioinformatics Analysis.

OBJECTIVE: To analyze the target and potential mechanism of Scutellaria baicalensis (SB) in the treatment of HCC based on bioinformatics, so as to provide suggestions for the diagnosis, treatment, and drug development of hepatocellular carcinoma (HCC). METHODS: The regulated gene targets of SB were screened by gene expression pattern clustering and differential analysis of gene expression data of HepG2 cells treated with SB at 0 h, 1 h, 3 h, 6 h, 12 h, and 24 h. The module genes related to HCC were identified by the weighted gene coexpression network analysis (WGCNA). KEGG and GO enrichment were used to analyze the molecular function and structure of the module, and GSEA was used to evaluate the different functional pathways between normal people and patients with HCC. Then, the module gene was used for univariate Cox proportional hazard analysis and the least absolute shrinkage and selection operator (LASSO) Cox regression analysis to build a prognostic model. The protein-protein interaction network (PPI) was used to analyze the core genes regulated by SB (CGRSB) of the module, and the survival curve revealed the CGRSB impact on patient survival. The CIBERSORT algorithm combined with correlation analysis to explore the relationship between CGRSB and immune infiltration. Finally, the single-cell sequencing technique was used to analyze the distribution of CGRSB at the cellular level. RESULTS: SB could regulate 903 genes, of which 234 were related to the occurrence of HCC. The prognosis model constructed by these genes has a good effect in evaluating the survival of patients. KEGG and GO enrichment analysis showed that the regulation of SB on HCC mainly focused on some cell proliferation, apoptosis, and immune-related functions. GSEA enrichment analysis showed that these functions are related to the occurrence of HCC. A total of 24 CGRSB were obtained after screening, of which 13 were significantly related to survival, and most of them were unfavorable factors for patient survival. The correlation analysis of gene expression showed that most of CGRSB was significantly correlated with T cells, macrophages, and other functions. The results of single-cell analysis showed that the distribution of CGRSB in macrophages was the most. CONCLUSION: SB has high credibility in the treatment of HCC, such as CDK2, AURKB, RRM2, CENPE, ESR1, and PRIM2. These targets can be used as potential biomarkers for clinical diagnosis. The research also shows that the p53 signal pathway, MAPK signal pathway, apoptosis pathway, T cell receptor pathway, and macrophage-mediated tumor immunity play the most important role in the mechanism of SB in treating HCC.

Seasonal variation of window opening behaviors in two naturally ventilated hospital wards.

Natural ventilation enables personal control, and occupant behaviors in window opening play a decisive role on natural ventilation performance, indoor air quality (IAQ), and/or airborne infection risk in a hospital setting. The occupant behaviors differ significantly from different building types with different functions and living habits. Based on a one-year field measurement in two general hospital wards in Nanjing, China, the effects of air quality (i.e. indoor CO2 concentration and outdoor PM2.5 concentration) and the climatic parameters (i.e. indoor/outdoor temperature, relative humidity, and outdoor wind speed, wind direction and rainfall) on window opening/closing behaviors are analyzed. Indoor air temperature or relative humidity is found to be a dominant factor for window opening behaviors. Seasonal differences are observed for the different influences of physical factors. The outdoor temperature is found to be associated with the window opening probability negatively during the cooling season, but positively during the transition and heating seasons. The indoor relative humidity positively affects the window opening probability during the transition season while a negative impact appears during the cooling and heating seasons. Based on the seasonal variation of window opening behaviors, Logistic regression models in different seasons (cooling, transition and heating seasons) are developed to predict the window opening/closing state and are verified to be promisingly adaptable with results of accuracy bigger than 70%.