Objective To explore the mechanism of Jiawei Jisheng Shenqi Decoction in improving the hypoxic microenvironment and antagonizing liver cirrhosis.Methods In vivo experiments were conducted using a rat model of carbon tetrachloride(CCL4)-induced liver cirrhosis.Rats were divided into normal,model,colchicine,JWJSSQ low-dose,JWJSSQ medium-dose,and JWJSSQ high-dose group.Pathological changes in liver tissues in each group were examined by hematoxylin and eosin(HE)and Masson staining,changes in serum liver function were detected using test kits,levels of hyaluronic acid(HA),laminin(LN),procollagen Ⅲ(PC Ⅲ),and collagen typeⅣ(COL4)were detected by enzyme-linked immunosorbent assay(ELISA),and protein expression levels of hypoxia-inducible factor-1α(HIF-1α),Notch1,Jagged1,and α-smooth muscle actin(α-SMA)were detected by Western blot.In vitro experiments were conducted in HSC-T6 cells,and the optimal concentration of CoCl2(100 μ mol/L,200μmol/L,400 μmol/L,600 μmol/L and 800 μmol/L)in the cultured cells and the optimal concentration of drug-containing serum(5％,10％,15％,20％)were determined by Cell Counting Kit-8(CCK-8)assay.The migration ability of cells in each group was detected by scratch testing,and changes in the apoptosis rates were determined by flow cytometry.Protein expression levels of HIF-1α,Notch1,Jagged1,α-SMA,matrix metallopeptidase 9(MMP9),and tissue inhibitor of metalloproteinases 1(TIMP-1)were detected by Western blot.Results In the in vivo experiments,liver swelling,inflammatory cell infiltration,collagen deposition,and the appearance of pseudolobules were significantly increased in the model group compared with those in the normal group.Serum levels of alanine aminotransferase(ALT),aspartate aminotransferase(AST),HA,LN,PCⅢ,and COL4 were significantly increased and albumin(ALB)was significantly decreased in the model group,while liver levels of HIF-1α,Notch1,Jagged1,and α-SMA proteins were significantly increased(P＜0.01).Liver swelling,inflammatory cell infiltration,and collagen deposition were significantly reduced in each treatment group compared with those in the model group,and the degree of fibrosis was reduced.Serum ALT,AST,HA,LN,PCⅢ,and COL4 were significantly decreased and ALB was significantly increased,while liver levels of HIF-1α,Notch1,Jagged1,and α-SMA proteins were also significantly decreased to varying degrees(P＜0.05).In the in vitro experiments,hypoxia promoted HSC-T6 migration and reduced apoptosis,increased the protein expression levels of HIF-1α,Notch1,Jagged1,α-SMA,and TIMP-1,and reduced the expression levels of MMP9(P＜0.01).Serum containing Jiawei Jisheng Shenqi Decoction inhibited HSC-T6 migration,promoted HSC-T6 apoptosis,lowered the expression of HIF-1α,Notch1,Jagged1,α-SMA,and TIMP-1 proteins,and enhanced the expression of MMP9 protein(P＜0.01).The inhibitory effect of Jiawei Jisheng Shenqi on HSC-T6 cell activation was reversed by the HIF-1α agonist dimethyloxalylglycine.Conclusions Jiawei Jisheng Shenqi Decoction can improve the hypoxic microenvironment via the HIF-1α/Notch pathway,thereby exerting an anti-liver cirrhosis effect.

Objective To analyze the application characteristics,trends,and special advantages of anti-infection research using the Bayesian method,and to provide methodological reference for the development of anti-infection research.Methods PubMed,CNKI and WanFang Data were electronically searched for the studies on anti-infection using Bayesian method published from January 1,2015 to November 21,2023.The relevant information of publication time,anti-infection type,sample size,Bayesian characteristics and Bayesian application pattern were analyzed descriptively and reviewed.Results A total of 86 studies were included,of which 41.9％were observational studies,only 7.0％were enterprise-initiated studies,and 48.8％were mentioning prior information studies.There was no domestic intervention study.The application characteristics and advantages of Bayesian method in intervention study,observational study and pharmacokinetic study are different.In intervention researches and observational researches,the application of Bayesian design decision and the application of Bayesian analysis and estimation accounts for 69.2％and 52.8％at most,respectively.Conclusions The Bayesian method is flexible,can be used for small sample sizes and complex model research,and can deal with uncertainty.In intervention studies in the field of anti-infection in China,the Bayesian method has not been applied widely.Only a handful of studies applying Bayesian method have been initiated by companies.In the future,it is still necessary to promote the advantages and application scenarios of Bayesian methods in the field of anti-infection research and strengthen the standardization of the application of Bayesian method.

Arsenic (organoarsenic) compound is one of the oldest drugs used by humans to treat various diseases. From its initial application in treating various skin diseases to the 1970s when arsenic trioxide (ATO) was proven to be able to significantly relieve acute promyelocytic leukemia (APL), arsenic (organoarsenic) compounds gradually occupied an important position in the history of medical development. This article reviews the pharmaceutical research progress of inorganic arsenic compounds and organic arsine compounds, covering anticancer, antiparasitic, antiviral and antibiotic aspects. It further explores the potential for developing new arsenic (organoarsenic) drugs with higher efficacy and lower toxicity, aiming to provide new research directions and ideas for the application of arsenic (organoarsenic) compounds in disease treatment.

Objective:To explore the feasibility of automatic target volume tracing in the Elekta Unity magnetic resonance imaging (MRI)-guided radiotherapy system and to further enhance the real-time target volume tracing performance of MRI-guided radiotherapy by introducing the deep learning technology based on a large Transformer model.Methods:A total of 4 661 frames of cine MRI binary images from 75 patients with malignant tumors in the chest/abdomen who were treated with MRI-guided radiotherapy were retrospectively collected as a training set. Another 500 frames of cine MRI binary images from 10 patients were collected as an independent test set. A module for medical image format conversion was developed to convert binary images into medical meta-images. The outer contours of tumor target volumes in the cine MRI images of the test set were manually delineated as actual control labels. With the first frame of the cine MRI images of each patient as the reference image and the other frames as motion images, a Transformer-based deep learning model was constructed to describe the deformable vector field (DVF) of motion images relative to the reference image. The Dice similarity coefficient (DSC), the 95% Hausdorff distance (HD 95), the negative Jacobian determinant (NegJ), and the average processing time per frame of cine MRI images were calculated. These values were compared to those of the conventional B-Spline scheme to quantitatively assess the target volume tracing accuracy, DVF physical plausibility, and execution efficiency of the Transformer-based deep learning model. Results:The Transformer-based deep learning model constructed in this study delivered superior target volume tracing performance, with improved DSC [(0.84 ± 0.05) vs. (0.74 ± 0.16), t = 11.44, P < 0.05] and HD 95 [(9.25 ± 2.98) vs. (14.70 ± 8.55) mm, t = -11.83, P < 0.05]. Furthermore, this model reduced the average image processing time from 1.95 s to 30.99 ms, enhancing the efficiency by two orders of magnitude. Besides, this model yielded NegJ similar to that of the B-Spline scheme. This suggests that the DVF extracted using this model had comparable physical plausibility with that obtained using the B-Spline scheme. Conclusions:The Transformer-based deep learning model for automatic target volume tracing fills the functional gap of the Elekta Unity MRI-guided radiotherapy system, facilitating relatively accurate, efficient automatic tracing of moving tumor targets in the chest and abdomen.

Arsenic (organoarsenic) compound is one of the oldest drugs used by humans to treat various diseases. From its initial application in treating various skin diseases to the 1970s when arsenic trioxide (ATO) was proven to be able to significantly relieve acute promyelocytic leukemia (APL), arsenic (organoarsenic) compounds gradually occupied an important position in the history of medical development. This article reviews the pharmaceutical research progress of inorganic arsenic compounds and organic arsine compounds, covering anticancer, antiparasitic, antiviral and antibiotic aspects. It further explores the potential for developing new arsenic (organoarsenic) drugs with higher efficacy and lower toxicity, aiming to provide new research directions and ideas for the application of arsenic (organoarsenic) compounds in disease treatment.

Objective:To analyze the mediating effect of cardiovascular health status (CVH) on the association between educational level and cardiovascular disease (CVD).Methods:The participants were from Shanghai Suburban Adult Cohort and Biobank, and questionnaire survey, physical examination, blood biochemistry were conducted from 2016 to 2020 for baseline information collection, and follow up was conducted until March 31, 2024 based on the medical data, CVD incidence data and death surveillance data at different levels. The associations of educational level, CVH and time to CVD onset of the study population were analyzed using the accelerated failure time model to analyze the mediating effects of CVH, health behaviors, and health factors in the association of educational level and time to CVD onset. The mediating effects of educational level, gender, and age moderated associations were also analyzed.Results:A total of 57 312 participants were included, with 2 780 new cases of CVD during a median follow-up of 6.71 (6.71-6.72) years, and a mean incidence density of 7.77/1 000 person-years (95% CI: 7.48/1 000 person-years -8.06/1 000 person-years). In total, the less educational level and the lower CVH, the higher CVD incidence density ( P<0.05). The results of accelerated failure time models showed that the time ratio for CVD-free survival was 1.15 (95% CI: 1.06-1.24) and 1.33 (95% CI: 1.10-1.60) for moderate and high educational level, respectively. The results of the mediation effect analysis showed that the association between moderate and high educational level and time to CVD onset was 29.60% (20.50%-50.00%) and 36.10% (23.80%-59.00%), 9.97% (5.07%-20.00%) and 13.84% (6.84%-29.00%), 15.24% (9.64%-27.00%) and 17.55% (11.58%-33.00%) of mediators mediated by CVH, health behaviors, health factors, respectively. Among them, there was an exposure-mediated interaction of educational level and a positive moderating effect of age. Conclusion:CVH, health behaviors and health factors had a proportionate mediating effect in the association between educational level and risk of CVD development.

Objective:To analyze the association of sedentary time and physical activity with the risk of developing chronic obstructive pulmonary disease (COPD) in non-smoking women aged 40 years and above in Songjiang District, Shanghai.Methods:Based on a natural population-based cohort in Songjiang, a total of 18 707 non-smoking women who were aged 40 years and above and without COPD at baseline survey were enrolled in the study. Cox proportional risk regression model was used to analyze the associations of the duration of sedentary behavior, physical activity with the risk for COPD at baseline survey, and the hazard ratio ( HR) of risk for COPD and its 95% CI were calculated. Stratified analyses were performed based on age, BMI, history of respiratory diseases and so on. Sensitivity analyses were conducted by excluding the cases diagnosed with COPD within one year after the baseline survey. Results:As of March 31, 2024, a total of 691 new COPD cases had been recorded after a median follow-up time of 6.96 years with an incidence density of 53.22 per 10 000 person-years. After adjusting for relevant confounders, in the tertile subgroups of sedentary time, the risk for COPD reduced by 17% in the short sedentary time group compared with the long sedentary time group ( HR=0.83,95% CI:0.70-0.99). Compared with the low physical activity level and long sedentary time group, the risk for COPD reduced by 24% in the high physical activity level and short sedentary time group ( HR=0.76, 95% CI: 0.61-0.95) and by 23% in the low physical activity level and short sedentary time group ( HR=0.77, 95% CI: 0.60-0.97). Compared with the non-physical exercise and long sedentary time group, the risk for COPD reduced by 28% in the non-physical exercise and short sedentary time group ( HR=0.72, 95% CI: 0.60-0.87). These associations remained when the cases diagnosed with COPD within one year of the baseline survey were excluded. Conclusions:Increasing physical activity and reducing sedentary time have beneficial effects to prevent COPD in non-smoking women, and reducing sedentary time alone may also reduce the risk for COPD if increasing physical exercise or other physical activity is not possible.

Objective:To understand the status and influencing factors of social isolation in elderly individuals with chronic diseases.Methods:A multi-stage sampling method was used to select elderly individuals from eight communities or villages in Hefei from July to September 2022. The study employed a general information survey, the Lubben Social Network Scale (LSNS-6) , the Geriatric Depression Scale (GDS-15) , the Social Support Rating Scale (SSRS) , and the Personal Social Capital Scale 16 (PSCS-16) . Binary Logistic regression analysis was used to explore the factors influencing social isolation in elderly individuals with chronic diseases.Results:A total of 1 133 elderly individuals were surveyed, among which 538 had chronic diseases. Among the 538 elderly individuals with chronic diseases, 209 were socially isolated, resulting in a social isolation rate of 38.8%. Binary Logistic regression analysis revealed that living area, fear of falling, depression, social capital, and social support were significant factors influencing social isolation ( P<0.05) . Conclusions:The social isolation rate among elderly individuals with chronic diseases is high. Special attention should be given to elderly individuals living in rural areas, those who fear falling, and those experiencing depression. Additionally, improving social capital and social support can help alleviate social isolation in these elderly individuals.

Objective:To optimize the smart follow-up workflow for day-case breast surgery patients using an action research approach and evaluate its effectiveness.Methods:A total of 648 post-discharge patients who underwent day-case breast surgery at the Day Surgery Unit of Peking Union Medical College Hospital, Chinese Academy of Medical Sciences between February and May 2024 were selected by convenience sampling. Patients who received routine smart follow-up (automated+telephone) from February to March 2024 served as the baseline group. Patients enrolled in April 2024 ( n=218) and May 2024 ( n=202) formed the first and second cycle groups, respectively, in which the smart follow-up workflow was optimized iteratively using action research. Outcome indicators included automated recovery rate and total recovery rate of follow-up forms, as well as the incidence of postoperative discomfort symptoms. Results:The automated and total recovery rates of follow-up forms in the first and second cycle groups were significantly higher than those in the baseline group, with statistically significant differences observed ( P<0.01). The proportion of patients experiencing persistent chest distress was significantly lower in the first and second cycle groups compared to the baseline group, and further reduced in the second cycle group compared to the first, with statistically significant differences observed ( P<0.01). Pain levels in the first and second cycle groups were also significantly lower than those in the baseline group, with statistically significant differences observed ( P<0.01) . Conclusions:Optimizing the smart follow-up workflow for day-case breast surgery patients based on an action research approach can significantly improve the automated and overall recovery rates of follow-up forms, reduce postoperative discomfort, and enhance both the efficiency and quality of follow-up care.