ObjectiveBased on 16S rDNA technology and molecular biology methods， the molecular mechanism of Shenling Baizhusan in the treatment of diarrhea-predominant irritable bowel syndrome （IBS-D） was investigated. MethodsThe 42 SD rats with SPF were randomly divided into no control group， SLBZS-H， medium （SLBZS-M）， low （SLBZS-L） dose group， positive control group and model group， with 7 rats in each group. The rat model of IBS-D was prepared by ice-cold senna （0.45 g∙mL^-1） gavage （10 mL∙kg^-1） combined with restraint stress for 14 consecutive days. After successful modeling， the corresponding drugs were given to each group with a gavage volume of 10 mL∙kg^-1： The positive group was administered with 2.36 ， 1.18， 0.59 g∙mL^-1 of Shenling Baizhusan in the Positive group and the Model group with the same volume of normal saline for 14 d. The general condition of the rats： Weight， feces， mental state and death were observed and recorded. The body weight， abdominal wall retraction reflex score （AWR） and loose stool rate of rats in each group were measured before （the first day）， after the model （day 14） and after treatment （day 28）. Hematoxylin-eosin staining was used to observe the morphological characteristics of colon tissues of experimental animals. Enzyme-linked immunosorbent assay was used to quantitatively analyze the concentration of inflammatory mediators in the peripheral blood of experimental animals. Western blotting was used to detect the expression levels of key proteins of Toll-like receptor 4 （TLR4）， Toll-like receptor 2 （TLR2）， myeloid differentiation factor 88 （MyD88） and nuclear factor-κB （NF-κB） signaling pathway in rat colon tissue. 16S rDNA technology was used to detect the structural changes of intestinal microbiota in rats. ResultsCompared with Control， the colon of the Model group showed partial mucosal epithelial shedding and inflammatory cell infiltration. The contents of TNF-α， IL-1β， IL-6 and 5-HT in serum increased （P<0.05）， the protein expressions of TLR2， TLR4， MyD88 and NF-κB in colon tissue increased （P<0.05）， the diversity indices of Richness， Chao1， abundance-based coverage estimator（ACE） and Shannon decreased （P<0.05）， and the phylum Firmicutes， Actinobacteria， The relative richness of Bacteroides-H， Lactobacillus and Ligilactobacillus decreased （P<0.05）， while the relative richness of Bacteroidetes， Proteobacteria and Prevotella increased （P<0.05）. Compared with the model group， the colonic structure and organization of the SLBZS-H group， SLBZS-M group， SLBZS-L group and Positive group were clearer， and only a small number of inflammatory cells were present in some areas， and the serum contents of TNF-α， IL-1β， IL-6 and 5-HT were decreased （P<0.05）， TLR2， TLR4， The protein expressions of MyD88 and NF-κB decreased （P<0.05）， and compared with the model group， the diversity indices of Richness， Chao1， ACE and Shannon in the SLBZS-H， SLBZS-M and SLBZS-L groups increased （P<0.05）， and the richness of Firmicutes and Actinobacteria increased （P<0.05）. The richness of Proteobacteria and Prevotella decreased （P<0.05）， and the abundance of Prevotella decreased （P<0.05）， Bacteroides-H， Muribaculum， Lactobacillus and salivarius in the Positive group salivarius （P<0.05）. ConclusionShenling Baizhusan can effectively treat IBS-D， and its molecular mechanism may be to play a therapeutic role by improving intestinal flora and inhibiting the TLRS/MyD88/NF-κB signaling pathway to reduce inflammatory response.

To conduct a bibliometric and keyword analysis on the domestic and international literature of medical artificial intelligence （AI） ethics， explore the research frontiers， hotspots， and development trends in this field， and provide references for promoting the construction of China’s ethical governance system on medical AI. Utilizing CiteSpace software， a comparative analysis was conducted between the reviewed domestic and international literature regarding their publication volume， author and institutional collaboration networks， as well as keyword co-occurrence， clustering， timeline graph， and burst， to explore the research hotspots and development trends in the field. A total of 2 393 Chinese and English publications were included. In recent years， research topics in medical AI ethics both domestically and internationally focused on three aspects， encompassing their theoretical research， emerging domains and their ethical risks， as well as the ethical governance and regulation of medical AI. International research hotspots included federated learning， computer-aided detection， informed consent， and other aspects， whereas domestic research hotspots were smart healthcare， responsibility ethics， ethical values， and other aspects. Internationally， greater attention was placed on ethical issues concerning population health and healthcare in the public health domain， whereas domestic research topics tended to focus more on theoretical discussions and the establishment of ethical principles. The ethical governance of medical AI represents a shared global challenge， necessitating enhanced research into both the variances and commonalities in this field.

BACKGROUND: The global rise in diabetes prevalence is a pressing concern. Despite initiatives like "The Healthy Beijing Action 2020-2030" advocating for increased awareness, treatment, and control, the specific situation in Beijing remains unexplored. This study aimed to analyze the trends in diabetes prevalence, awareness, treatment, and control among Beijing adults. METHODS: Through a stratified multistage probability cluster sampling method, a series of representative cross-sectional surveys were conducted in Beijing from 2005 to 2022, targeting adults aged 18-79 years. A face-to-face questionnaire, along with body measurements and laboratory tests, were administered to 111,943 participants. Data from all survey were age- and/or gender-standardized based on the 2020 Beijing census population. Annual percentage rate change (APC) or average annual percentage rate change (AAPC) was calculated to determine prevalence trends over time. Complex sampling logistic regression models were employed to explore the relationship between various characteristics and diabetes. RESULTS: From 2005 to 2022, the total prevalence of diabetes among Beijing adults aged 18-79 years increased from 9.6% (95% CI: 8.8-10.4%) to 13.9% (95% CI: 13.1-14.7%), with an APC/AAPC of 2.1% (95% CI: 1.1-3.2%, P <0.05). Significant increases were observed among adults aged 18-39 years and rural residents. Undiagnosed diabetes rose from 3.5% (95% CI: 3.2-4.0%) to 7.2% (95% CI: 6.6-7.9%) with an APC/AAPC of 4.1% (95% CI: 0.5-7.3%, P <0.05). However, diabetes awareness and treatment rates showed annual declines of 1.4% (95% CI: -3.0% to -0.2%, P <0.05) and 1.3% (95% CI: -2.6% to -0.2%, P <0.05), respectively. The diabetes control rate decreased from 21.5% to 19.1%, although not statistically significant (APC/AAPC = -1.5%, 95% CI: -5.6% to 1.9%). Overweight and obesity were identified as risk factors for diabetes, with ORs of 1.65 (95% CI: 1.38-1.98) and 2.48 (95% CI: 2.07-2.99), respectively. CONCLUSIONS The prevalence of diabetes in Beijing has significantly increased between 2005 and 2022, particularly among young adults and rural residents. Meanwhile, there has been a concerning decrease in diabetes awareness and treatment rates, while control rates have remained stagnant. Regular blood glucose testing, especially among adults aged 18-59 years, should be warranted. Furthermore, being male, elderly, overweight, or obese was associated with higher diabetes risk, suggesting the needs for targeted management strategies.
Humans ; Adult ; Middle Aged ; Male ; Female ; Aged ; Adolescent ; Young Adult ; Cross-Sectional Studies ; Diabetes Mellitus/epidemiology* ; Beijing/epidemiology* ; Prevalence ; China/epidemiology* ; Surveys and Questionnaires

OBJECTIVES: To create a mixed valvular heart disease (MVHD)-related age-adjusted comorbidity index (MVACI) model for predicting mortality risk of patients with MVHD. METHODS: A total of 4080 patients with moderate or severe MVHD in the China-VHD study were included. The primary endpoint was 2-year all-cause mortality. A MVACI model prediction model was constructed based on the mortality risk factors identified by univariate and multivariate Cox regression analysis. Restricted cubic splines were used to assess the relationship between MVACI scores and 2-year all-cause mortality. The optimal threshold, determined by the maximum Youden index from receiver operator characteristic (ROC) curve analysis, was used to stratify patients. Kaplan-Meier method was used to calculate 2-year all-cause mortality and compared using the Log-rank test. Univariate and multivariate Cox proportional hazards models were employed to calculate hazard ratios (HR) and 95% confidence intervals (CI), evaluating the association between MVACI scores and mortality. Paired ROC curves were used to compare the discriminative ability of MVACI scores with the European System for Cardiac Operative Risk Evaluation Ⅱ(EuroSCORE Ⅱ) or the age-adjusted Charlson comorbidity index (ACCI) in predicting 2-year clinical outcomes, while calibration curves assessed the calibration of these models. Internal validation was performed using the Bootstrap method. Subgroup analyses were conducted based on etiology, treatment strategies, and disease severity. RESULTS: Multivariate analysis identified the following variables independently associated with 2-year all-cause mortality in patients: pulmonary hypertension, myocardiopathy, heart failure, low body weight (body mass index <18.5 kg/m²), anaemia, hypoalbuminemia, renal insufficiency, cancer, New York Heart Association (NYHA) class and age. The score was independently associated with the risk of all-cause mortality, and exhibited good discrimination (AUC=0.777, 95%CI: 0.755-0.799) and calibration (Brier score 0.062), with significantly better predictive performance than EuroSCORE Ⅱ or ACCI (both adjusted P<0.01). The internal validation showed that the MVACI model's predicted probability of 2-year all-cause mortality was generally consistent with the actual probability. The AUCs for predicting all-cause mortality risk were all above 0.750, and those for predicting adverse events were all above 0.630. The prognostic value of the score remained consistent in patients regardless of their etiology, therapeutic option, and disease severity. CONCLUSIONS The MVACI was constructed in this study based on age and comorbidities, and can be used for mortality risk prediction and risk stratification of MVHD patients. It is a simple algorithmic index and easy to use.
Humans ; Prognosis ; Comorbidity ; Heart Valve Diseases/epidemiology* ; Female ; Male ; Middle Aged ; Aged ; Proportional Hazards Models ; Risk Factors ; China/epidemiology* ; Age Factors ; Risk Assessment ; Adult ; ROC Curve

Computer-assisted methods for pathological image analysis can improve doctor's efficiency of image reading and diagnostic accuracy, effectively addressing the shortage of pathology diagnostic manpower. With the rapid development of artificial intelligence and digital pathology, deep learning technology has spurred a wealth of research in the field of histopathology. This article reviews the various applications of deep learning in digital pathological image analysis, such as pathological image segmentation, cancer auxiliary diagnosis, and cancer prognosis prediction, and discusses the challenges and solutions in its application. Furthermore, it predicts future trends in deep learning for pathological image analysis and proposes potential research directions.
Deep Learning ; Humans ; Image Processing, Computer-Assisted/methods* ; Artificial Intelligence ; Neoplasms

OBJECTIVE: To evaluate the dynamic changes of glucocorticoid (GC) dose and the feasibility of GC discontinuation in rheumatoid arthritis (RA) patients under the background of Chinese medicine (CM). METHODS: This multicenter retrospective cohort study included 1,196 RA patients enrolled in the China Rheumatoid Arthritis Registry of Patients with Chinese Medicine (CERTAIN) from September 1, 2019 to December 4, 2023, who initiated GC therapy. Participants were divided into the Western medicine (WM) and integrative medicine (IM, combination of CM and WM) groups based on medication regimen. Follow-up was performed at least every 3 months to assess dynamic changes in GC dose. Changes in GC dose were analyzed by generalized estimator equation, the probability of GC discontinuation was assessed using Kaplan-Meier curve, and predictors of GC discontinuation were analyzed by Cox regression. Patients with <12 months of follow-up were excluded for the sensitivity analysis. RESULTS: Among 1,196 patients (85.4% female; median age 56.4 years), 880 (73.6%) received IM. Over a median 12-month follow-up, 34.3% (410 cases) discontinued GC, with significantly higher rates in the IM group (40.8% vs. 16.1% in WM; P<0.05). GC dose declined progressively, with IM patients demonstrating faster reductions (median 3.75 mg vs. 5.00 mg in WM at 12 months; P<0.05). Multivariate Cox analysis identified age <60 years [P<0.001, hazard ratios (HR)=2.142, 95% confidence interval (CI): 1.523-3.012], IM therapy (P=0.001, HR=2.175, 95% CI: 1.369-3.456), baseline GC dose ⩽7.5 mg (P=0.003, HR=1.637, 95% CI: 1.177-2.275), and absence of non-steroidal anti-inflammatory drugs use (P=0.001, HR=2.546, 95% CI: 1.432-4.527) as significant predictors of GC discontinuation. Sensitivity analysis (545 cases) confirmed these findings. CONCLUSIONS RA patients receiving CM face difficulties in following guideline-recommended GC discontinuation protocols. IM can promote GC discontinuation and is a promising strategy to reduce GC dependency in RA management. (Trial registration: ClinicalTrials.gov, No. NCT05219214).
Adult ; Aged ; Female ; Humans ; Male ; Middle Aged ; Arthritis, Rheumatoid/drug therapy* ; Glucocorticoids/therapeutic use* ; Medicine, Chinese Traditional ; Retrospective Studies

Loss-of-function variants in CSDE1 have been strongly linked to neuropsychiatric disorders, yet the precise role of CSDE1 in neurogenesis remains elusive. In this study, we demonstrate that knockout of Csde1 during cortical development in mice results in impaired neural progenitor proliferation, leading to abnormal cortical lamination and embryonic lethality. Transcriptomic analysis revealed that Csde1 upregulates the transcription of genes involved in the cell cycle network. Applying a dual thymidine-labelling approach, we further revealed prolonged cell cycle durations of neuronal progenitors in Csde1-knockout mice, with a notable extension of the G1 phase. Intersection with CLIP-seq data demonstrated that Csde1 binds to the 3' untranslated region (UTR) of mRNA transcripts encoding cell cycle genes. Particularly, we uncovered that Csde1 directly binds to the 3' UTR of mRNA transcripts encoding Cdk6, a pivotal gene in regulating the transition from the G1 to S phases of the cell cycle, thereby maintaining its stability. Collectively, this study elucidates Csde1 as a novel regulator of Cdk6, sheds new light on its critical roles in orchestrating brain development, and underscores how mutations in Csde1 may contribute to the pathogenesis of neuropsychiatric disorders.
Animals ; Neurogenesis/genetics* ; Cell Cycle/genetics* ; Mice, Knockout ; Mice ; Neural Stem Cells/metabolism* ; DNA-Binding Proteins/metabolism* ; Cyclin-Dependent Kinase 6/genetics* ; Cell Proliferation ; 3' Untranslated Regions ; Cerebral Cortex/embryology* ; RNA-Binding Proteins ; Mice, Inbred C57BL

Background: Obesity and chronic pain are related in both directions, according to earlier observational research.This research aimed to analyze the causal association between obesity and chronic pain at the genetic level, as well as to assess whether common factors mediate this relationship. Methods: This study used bidirectional two sample Mendelian randomization (MR) technique to analyze the association between obesity and chronic pain. Obesity's summary genome-wide association data were obtained from European ancestry groups, as measured by body mass index (BMI), waist-to-hip ratio, waist circumference (WC), and hip circumference (HC), genome-wide association study data for chronic pain also came from the UK population, including chronic pain at three different sites (back, hip, and headache), chronic widespread pain (CWP), and multisite chronic pain (MCP). Secondly, a two-step MR and multivariate MR investigation was performed to evaluate the mediating effects of several proposed confounders. Results: The authors discovered a link between chronic pain and obesity. More specifically, a sensitivity analysis was done to confirm the associations between greater BMI, WC, and HC with an increased risk of CWP and MCP.Importantly, the intermediate MR results suggest that education levels and smoking initiation may mediate the causal relationship between BMI on CWP, with a mediation effect of 23.08% and 15.38%, respectively. Conclusions The authors’ findings demonstrate that the importance of education and smoking in understanding chronic pain’s pathogenesis, which is important for the primary prevention and prognosis of chronic pain.

Background: Obesity and chronic pain are related in both directions, according to earlier observational research.This research aimed to analyze the causal association between obesity and chronic pain at the genetic level, as well as to assess whether common factors mediate this relationship. Methods: This study used bidirectional two sample Mendelian randomization (MR) technique to analyze the association between obesity and chronic pain. Obesity's summary genome-wide association data were obtained from European ancestry groups, as measured by body mass index (BMI), waist-to-hip ratio, waist circumference (WC), and hip circumference (HC), genome-wide association study data for chronic pain also came from the UK population, including chronic pain at three different sites (back, hip, and headache), chronic widespread pain (CWP), and multisite chronic pain (MCP). Secondly, a two-step MR and multivariate MR investigation was performed to evaluate the mediating effects of several proposed confounders. Results: The authors discovered a link between chronic pain and obesity. More specifically, a sensitivity analysis was done to confirm the associations between greater BMI, WC, and HC with an increased risk of CWP and MCP.Importantly, the intermediate MR results suggest that education levels and smoking initiation may mediate the causal relationship between BMI on CWP, with a mediation effect of 23.08% and 15.38%, respectively. Conclusions The authors’ findings demonstrate that the importance of education and smoking in understanding chronic pain’s pathogenesis, which is important for the primary prevention and prognosis of chronic pain.

Background: Obesity and chronic pain are related in both directions, according to earlier observational research.This research aimed to analyze the causal association between obesity and chronic pain at the genetic level, as well as to assess whether common factors mediate this relationship. Methods: This study used bidirectional two sample Mendelian randomization (MR) technique to analyze the association between obesity and chronic pain. Obesity's summary genome-wide association data were obtained from European ancestry groups, as measured by body mass index (BMI), waist-to-hip ratio, waist circumference (WC), and hip circumference (HC), genome-wide association study data for chronic pain also came from the UK population, including chronic pain at three different sites (back, hip, and headache), chronic widespread pain (CWP), and multisite chronic pain (MCP). Secondly, a two-step MR and multivariate MR investigation was performed to evaluate the mediating effects of several proposed confounders. Results: The authors discovered a link between chronic pain and obesity. More specifically, a sensitivity analysis was done to confirm the associations between greater BMI, WC, and HC with an increased risk of CWP and MCP.Importantly, the intermediate MR results suggest that education levels and smoking initiation may mediate the causal relationship between BMI on CWP, with a mediation effect of 23.08% and 15.38%, respectively. Conclusions The authors’ findings demonstrate that the importance of education and smoking in understanding chronic pain’s pathogenesis, which is important for the primary prevention and prognosis of chronic pain.