Objective To explore the influencing factors of different types of small intestinal bacterial overgrowth(SIBO).Methods A total of 539 patients who were hospitalized in the Department of Gastroenterology,the Sixth Medical Center of PLA General Hospital from June 2021 to December 2021 and who underwent methane-hydrogen breath test were retrospectively selected.Based on breath test results,patients were divided into SIBO-negative group(n=300)and SIBO-positive group(n=239).The clinical data were compared between two groups.According to the specific values of breath test results,SIBO-positive patients were further divided into hydrogen-producing bacterial overgrowth(hydrogen-positive,n=103),intestinal methanogen overgrowth(methanogen-positive,n=80),and simultaneous methanogen and hydrogen-producing bacterial overgrowth(double positive,n=56)groups.Multivariate logistic regression analysis was employed to identify influencing factors of different SIBO types.Additionally,SIBO-positive patients were categorized by age into<45 years(n=23),45-60 years(n=82),60-75 years(n=124),and≥75 years(n=10)to compare SIBO positivity rates across age groups.Results The patients in SIBO-positive and double positive groups were older and had a lower body mass index(BMI)than those in SIBO-negative group,with statistically significant differences(P<0.05).Compared with the patients in SIBO-negative group,those in hydrogen-positive group showed a higher proportion of history of coronary heart disease,those in methanogen-positive group were older,and higher proportion of statin use,with statistically significant differences(P<0.05).Multivariate logistic regression analysis revealed that,among different SIBO types,a history of coronary heart disease served as an independent risk factor for hydrogen-producing bacterial overgrowth(OR=2.728,95%CI 1.271-5.857,P=0.010).For methanogen overgrowth,increasing age was identified as an independent risk factor(OR=1.040,95%CI 1.009-1.063,P=0.010),while the application of statin played the role of an independent protective factor(OR=0.420,95%CI 0.236-0.754,P=0.003).As for the simultaneous overgrowth of methane-producing and hydrogen-producing bacteria,increased BMI was found to be an independent protective factor(OR=0.870,95%CI 0.786-0.964,P=0.008).In SIBO-positive group,it was found that for patients aged<45 years,both the methane-positive rate and the double-positive rate were significantly lower than the hydrogen positivity rate(P<0.05).Moreover,among patients aged 45-60 years,the double-positive rate was significantly lower than the hydrogen positivity rate(P<0.01).When it comes to the hydrogen-positive rate,it was significantly lower for patients aged 45-60 and 60-75 years compared with that of patients aged<45 years(P<0.05).In contrast,the methane-positive rate and the double-positive rate were significantly higher for patients aged 45-60 and 60-75 years than those of patients aged<45 years(P<0.01).Conclusion A history of coronary heart disease and increasing age are independent risk factors for intestinal hydrogen-producing bacterial overgrowth and methanogen overgrowth,respectively.The application of statins and increased BMI are independent protective factors for intestinal methanogen simultaneous overgrowth of methanogen and hydrogen-producing bacteria,respectively.

This paper systematically summarizes the practical experience of the 2025 Dingri earthquake emergency medical rescue in Tibet. It analyzes the requirements for earthquake medical rescue under conditions of high-altitude hypoxia, low temperature, and low air pressure. The paper provides a detailed discussion on the strategic layout of earthquake medical rescue at the national level, local government level, and through social participation. It covers the construction of rescue organizational systems, technical systems, material support systems, and information systems. The importance of building rescue teams is emphasized. In high-altitude and cold conditions, rapid response, scientific decision-making, and multi-party collaboration are identified as key elements to enhance rescue efficiency. By optimizing rescue organizational structures, strengthening the development of new equipment, and promoting telemedicine technologies, the precision and effectiveness of medical rescue can be significantly improved, providing important references for future similar disaster rescues.

OBJECTIVE: This study examines utilizes the advantages of machine learning algorithms to discern key determinants in prognosticate postoperative circulatory complications (PCCs) for older patients. METHODS: This secondary analysis of data from a randomized controlled trial involved 1,720 elderly participants in five tertiary hospitals in Beijing, China. Participants aged 60-90 years undergoing major non-cardiac surgery under general anesthesia. The primary outcome metric of the study was the occurrence of PCCs, according to the European Society of Cardiology and the European Society of Anaesthesiology diagnostic criteria. The analysis metrics contained 67 candidate variables, including baseline characteristics, laboratory tests, and scale assessments. RESULTS: Our feature selection process identified key variables that significantly impact patient outcomes, including the duration of ICU stay, surgery, and anesthesia; APACHE-II score; intraoperative average heart rate and blood loss; cumulative opioid use during surgery; patient age; VAS-Move-Median score on the 1st to 3rd day; Charlson comorbidity score; volumes of intraoperative plasma, crystalloid, and colloid fluids; cumulative red blood cell transfusion during surgery; and endotracheal intubation duration. Notably, our Random Forest model demonstrated exceptional performance with an accuracy of 0.9872. CONCLUSION We have developed and validated an algorithm for predicting PCCs in elderly patients by identifying key risk factors.
Aged ; Aged, 80 and over ; Female ; Humans ; Male ; Middle Aged ; Cardiovascular Diseases/etiology* ; Machine Learning ; Postoperative Complications/etiology* ; Risk Factors ; Randomized Controlled Trials as Topic ; Secondary Data Analysis

OBJECTIVE: Humans are exposed to complex mixtures of environmental chemicals and other factors that can affect their health. Analysis of these mixture exposures presents several key challenges for environmental epidemiology and risk assessment, including high dimensionality, correlated exposure, and subtle individual effects. METHODS: We proposed a novel statistical approach, the generalized functional linear model (GFLM), to analyze the health effects of exposure mixtures. GFLM treats the effect of mixture exposures as a smooth function by reordering exposures based on specific mechanisms and capturing internal correlations to provide a meaningful estimation and interpretation. The robustness and efficiency was evaluated under various scenarios through extensive simulation studies. RESULTS: We applied the GFLM to two datasets from the National Health and Nutrition Examination Survey (NHANES). In the first application, we examined the effects of 37 nutrients on BMI (2011-2016 cycles). The GFLM identified a significant mixture effect, with fiber and fat emerging as the nutrients with the greatest negative and positive effects on BMI, respectively. For the second application, we investigated the association between four pre- and perfluoroalkyl substances (PFAS) and gout risk (2007-2018 cycles). Unlike traditional methods, the GFLM indicated no significant association, demonstrating its robustness to multicollinearity. CONCLUSION GFLM framework is a powerful tool for mixture exposure analysis, offering improved handling of correlated exposures and interpretable results. It demonstrates robust performance across various scenarios and real-world applications, advancing our understanding of complex environmental exposures and their health impacts on environmental epidemiology and toxicology.
Humans ; Environmental Exposure/analysis* ; Linear Models ; Nutrition Surveys ; Environmental Pollutants ; Body Mass Index

Postoperative infection of internal fixation of closed fractures the lower limbs in adults represents a devastating complication, characterized by diagnostic challenges, prolonged treatment duration and high disability rates. Current management of these infections faces multiple challenges, such as difficulties in early accurate diagnosis, and various controversies about the treatment plan, leading to poor overall diagnosis and treatment results. To address these issues, based on evidence-based medicine and principles with emphasis on scientific rigor, clinical applicability and innovation, the Trauma Branch of the Chinese Medical Association, Orthopedic Branch of the Chinese Medical Doctor Association, Orthopedics Branch of the Chinese Medical Association, and Trauma Orthopedics and Polytrauma Group of the Resuscitation and Emergency Committee of the Chinese Medical Doctor Association have collaboratively organized a panel of relevant experts to develop the Guideline for diagnosis and treatment of infection after internal fixation of closed lower limb fractures in adults ( version 2025). The guideline proposed 10 recommendations, aiming to provide a foundation for standardized diagnosis and treatment of postoperative infection in adults with closed lower limb fractures.

Objective:To characterize the vaginal flora of pregnant women during the second trimester using full-length 16S rRNA sequencing.Methods:A total of 142 pregnant women were systematically sampled from a pregnancy cohort. Vaginal swabs were collected for full-length 16S rRNA gene sequencing，and bioinformatics analysis was performed to characterize the vaginal microbiota and identify associated influencing factors.Results:Among the 142 pregnant women，the most frequently detected species were Lactobacillus iners（83.10%，118/142）and Lactobacillus crispatus（49.30%，70/142）. The majority of samples（90.85%，129/142）were classified as Lactobacillus-dominant vagitypes，with the Lactobacillus iners vagitype accounting for 48.59%（69/142）and the Lactobacillus crispatus vagitype accounting for 38.73%（55/142）. The vaginal microbiota was clustered into five community state types（CSTs）：Ⅰa，Ⅰb，Ⅲa，Ⅲb，and Ⅳ. The most prevalent CSTs were Lactobacillus iners-dominated CST-Ⅲ（51.41%，73/142）and Lactobacillus crispatus-dominated CST-Ⅰ（24.65%，35/142）. No samples were classified as CST-Ⅱ or CST-Ⅴ. A significant negative correlation was observed between Lactobacill and vaginosis-associated bacteria. Age，alcohol consumption，smoking，and vaginal treatments showed significant associations or trends toward significance with various Alpha diversity indices. Vaginal douching was associated with CST clustering，while obstetric history（primiparity，previous miscarriage history）was associated with vagitype classification. However，no significant associations were identified between maternal baseline characteristics and Beta diversity indices. Conclusions:Full-length 16S rRNA gene sequencing reveals that the vaginal microbiota of pregnant women is dominated by Lactobacillus iners and Lactobacillus crispatus. Maternal age，lifestyle factors such as smoking and alcohol consumption，and obstetric history are significantly associated with variations in vaginal microbiota composition.

Previous studies have shown that the diversity and composition of intestinal microbiota are related to the effect of tumor immunotherapy,but the mechanism of intestinal microbiota affecting tumor immunotherapy resistance has rarely been sum-marized.This article not only expounds the current clinical sta-tus of tumor immunotherapy resistance,but also summarizes the correlation and regulatory mechanism between the composition and homeostasis of intestinal microbiota and drug resistance to different types of tumor immunotherapy,so as to provide a refer-ence for the study of potential targets for improving tumor immu-notherapy resistance based on intestinal microbiota.

The pathological mechanisms and related physiological indicators of acute mountain sickness(AMS)were introduced,and the present situation of wearable devices applied in AMS auxiliary detection and diagnosis were reviewed.The challenges and future development directions of wearable devices applied in auxiliary detection and diagnosis were pointed out.[Chinese Medical Equipment Journal,2025,46(9):100-107]

A growing body of research points out that gut microbiota plays a key role in tumor immunotherapy. By optimizing the composition of intestinal microbiota, it is possible to effectively improve immunotherapy resistance and enhance its therapeutic effect. This article comprehensively analyzes the mechanism of intestinal microbiota influencing tumor immunotherapy resistance, expounds the current strategies for targeted regulation of intestinal microbiota, such as traditional Chinese medicine and plant components, fecal microbiota transplantation, probiotics, prebiotics and dietary therapy, and explores the potential mechanisms of these strategies to improve patients' resistance to tumor immunotherapy. At the same time, the article also briefly discusses the prospects and challenges of targeting intestinal microbiota to improve tumor immunotherapy resistance, which provides a reference for related research to help the strategy research of reversing tumor immunotherapy resistance.