Background/Aims: Obesity is associated with several gastrointestinal (GI) disorders and has been identified as a potential risk factor for various GI symptoms. Bowel frequency is an important indicator of bowel function. However, the causal link between obesity and gastrointestinal motility remains uncertain. This study aims to determine the causal effect of overall and central obesity on stool frequency. Methods: Four obesity-related anthropometric indicators–body mass index, body fat percentage, waist circumference (WC), and waist-tohip ratio (WHR)–were investigated. Individual-level baseline information from the UK Biobank was used to explore observational associations between obesity and stool frequency. Additionally, summary-level data from published genome-wide association studies were subjected to two-sample Mendelian randomization (MR) analyses to examine causal associations. Results: For all 4 indicators of obesity, higher levels of obesity were associated with more frequent bowel movements after adjusting for demographic characteristics, lifestyle, and dietary factors. After rigorous screening, 482 body mass index single nucleotide polymorphisms (SNPs), 7 body fat percentage SNPs, 48 WC SNPs, and 287 WHR SNPs were identified as instrument variables for MR analysis. The MR results were generally consistent with observational findings, proving that the associations observed in the overall obesity indicators were causal. For central obesity, the association between WHR and stool frequency remained consistent in both analysis phases, whereas WC showed a multidirectional association. Conclusions Obesity-related anthropometric indicators were causally associated with increased stool frequency in the overall and central obesity groups. Weight loss could be a potential approach to improve gastrointestinal regularity in individuals with obesity.

Objective: To explore the longitudinal associations between dietary macronutrients and lung function in schoolaged children, so as to provide the nutritional research evidence for promoting children s lung health. Methods: In November 2021, two primary schools located in Chengdu, Sichuan Province were selected from the Southwest China Childhood Nutrition and Growth (SCCNG) cohort by a stratified cluster random sampling method, enrolling a total of 1 112 school aged children aged 8 to 13 years. At baseline, the dietary and sociodemographic characteristics of the children were assessed. One year later, the forced vital capacity (FVC) of the children was measured and converted into Z scores (FVC- Z ), while the vital capacity index (VCI) was also calculated. Generalized linear regression analysis was employed to examine the associations between dietary macronutrients and lung function, considering interactions with gender and age, followed by stratified analysis. Results: After adjusting for confounding factors, the analysis results of the generalized linear regression model showed that the carbohydrate energy ratio was negatively correlated with FVC- Z ( β =-0.02) and VCI ( β =-0.16), while the fat energy ratio showed a positive correlation with FVC- Z ( β =0.03) and VCI ( β =0.23) ( P <0.05). The protein energy ratio was positively correlated with FVC- Z ( β =0.09) and VCI ( β =0.60) specifically in girls ( P <0.05). Additionally, there was an interaction effect of age on the associations between macronutrients and lung function ( P <0.01); in children aged 8-9 and 10-11, the carbohydrate energy supply ratio was negatively correlated with FVC- Z ( β =-0.04, -0.03) and VCI ( β =-0.29, -0.21), and fat energy supply ratio was positively correlated with FVC- Z ( β =0.07, 0.05) and VCI ( β =0.46, 0.32) ( P <0.05). Conclusions There are age and sex differences in the association of dietary macronutrients with lung function, with a low carbohydrate, high fat diet promoting lung function in children. Additionally, protein intake appears to have a positive influence on the lung function of girls. The early school age period may represent a critical window for dietary interventions aimed at promoting lung health.

Background/Aims: Obesity is associated with several gastrointestinal (GI) disorders and has been identified as a potential risk factor for various GI symptoms. Bowel frequency is an important indicator of bowel function. However, the causal link between obesity and gastrointestinal motility remains uncertain. This study aims to determine the causal effect of overall and central obesity on stool frequency. Methods: Four obesity-related anthropometric indicators–body mass index, body fat percentage, waist circumference (WC), and waist-tohip ratio (WHR)–were investigated. Individual-level baseline information from the UK Biobank was used to explore observational associations between obesity and stool frequency. Additionally, summary-level data from published genome-wide association studies were subjected to two-sample Mendelian randomization (MR) analyses to examine causal associations. Results: For all 4 indicators of obesity, higher levels of obesity were associated with more frequent bowel movements after adjusting for demographic characteristics, lifestyle, and dietary factors. After rigorous screening, 482 body mass index single nucleotide polymorphisms (SNPs), 7 body fat percentage SNPs, 48 WC SNPs, and 287 WHR SNPs were identified as instrument variables for MR analysis. The MR results were generally consistent with observational findings, proving that the associations observed in the overall obesity indicators were causal. For central obesity, the association between WHR and stool frequency remained consistent in both analysis phases, whereas WC showed a multidirectional association. Conclusions Obesity-related anthropometric indicators were causally associated with increased stool frequency in the overall and central obesity groups. Weight loss could be a potential approach to improve gastrointestinal regularity in individuals with obesity.

Background/Aims: Obesity is associated with several gastrointestinal (GI) disorders and has been identified as a potential risk factor for various GI symptoms. Bowel frequency is an important indicator of bowel function. However, the causal link between obesity and gastrointestinal motility remains uncertain. This study aims to determine the causal effect of overall and central obesity on stool frequency. Methods: Four obesity-related anthropometric indicators–body mass index, body fat percentage, waist circumference (WC), and waist-tohip ratio (WHR)–were investigated. Individual-level baseline information from the UK Biobank was used to explore observational associations between obesity and stool frequency. Additionally, summary-level data from published genome-wide association studies were subjected to two-sample Mendelian randomization (MR) analyses to examine causal associations. Results: For all 4 indicators of obesity, higher levels of obesity were associated with more frequent bowel movements after adjusting for demographic characteristics, lifestyle, and dietary factors. After rigorous screening, 482 body mass index single nucleotide polymorphisms (SNPs), 7 body fat percentage SNPs, 48 WC SNPs, and 287 WHR SNPs were identified as instrument variables for MR analysis. The MR results were generally consistent with observational findings, proving that the associations observed in the overall obesity indicators were causal. For central obesity, the association between WHR and stool frequency remained consistent in both analysis phases, whereas WC showed a multidirectional association. Conclusions Obesity-related anthropometric indicators were causally associated with increased stool frequency in the overall and central obesity groups. Weight loss could be a potential approach to improve gastrointestinal regularity in individuals with obesity.

ObjectiveThis study aims to explore the potential mechanism of the Xiezhuo Jiedu formula in regulating pyroptosis for the treatment of ulcerative colitis （UC） using bioinformatics and in vivo animal experiments. MethodsDifferentially expressed genes （DEGs） in colon tissues of UC patients were retrieved from the Gene Expression Omnibus （GEO） database. Pyroptosis-related genes were obtained from the GEO and GeneCards databases. The intersection of these datasets yielded pyroptosis-related DEGs （Pyro-DEGs）. Pyro-DEGs were subjected to Gene Ontology （GO） and Kyoto Encyclopedia of Genes and Genomes （KEGG） enrichment analysis using the Metascape database. A protein-protein interaction （PPI） network was constructed using the STRING database. Least absolute shrinkage and selection operator （LASSO） prediction model and receiver operating characteristic （ROC） analysis were conducted to identify core Pyro-DEGs with diagnostic and therapeutic potential. Immune infiltration analysis of the UC datasets was performed using the deconvolution method （CIBERSORT）， along with correlation analysis with core Pyro-DEGs. Sixty male Sprague-Dawley （SD） rats were randomly divided into a control group， a model group， high-， medium-， and low-dose groups of Xiezhuo Jiedu formula （26.64， 13.32， 6.66 g·kg^-1）， and a mesalazine group （0.27 g·kg^-1）， with 10 rats in each group. UC was established by intrarectal administration of 3，5-trinitrobenzenesulfonic acid （TNBS） dissolved in ethanol. The control and model groups were given distilled water by gavage， while the treatment groups were administered the corresponding drugs for 7 consecutive days. Hematoxylin-eosin （HE） staining was used to observe the colon histopathology. Enzyme-linked immunosorbent assay （ELISA） was used to detect the levels of inflammatory factors such as interleukin-1β （IL-1β）， IL-10， IL-18， and transforming growth factor-β （TGF-β）. Immunohistochemistry （IHC） and Western blot were applied to detect the expression of Caspase-1， gap junction alpha-1 protein （GJA1）， peroxisome proliferator-activated receptor gamma （PPARG）， and S100 calcium-binding protein A8 （S100A8）. Real-time quantitative polymerase chain reaction （Real-time PCR） was utilized to measure mRNA expression of Caspase-1， GJA1， PPARG， and S100A8. Western blot was performed to assess protein expression levels of Caspase-1， GJA1， PPARG， and S100A8. ResultsGEO datasets GSE87466 and GSE87473 yielded 64 Pyro-DEGs. KEGG analysis indicated that these genes were enriched in the NOD-like receptor signaling pathway， tumor necrosis factor （TNF） signaling pathway， and hypoxia-inducible factor 1 （HIF-1） signaling pathway. Four core Pyro-DEGs （Caspase-1， GJA1， PPARG， and S100A8） were identified. Immune infiltration analysis showed that expression of these genes was positively correlated with mast cells， neutrophils， M0 macrophages， M1 macrophages， and dendritic cells. Animal experimental results indicated that compared with the control group， the model group had significantly increased levels of IL-1β and IL-18， significantly decreased levels of IL-10 and TGF-β. The model group showed enhanced Caspase-1， GJA1， and S100A8 staining， and significantly increased mRNA and protein expression of Caspase-1， GJA1， and S100A8 （P<0.01）. In contrast， the expression of PPARG was reduced in the model group （P<0.01）. After treatment， all dosage groups showed varying degrees of improvement （P<0.05， P<0.01）， with the high-dose group showing the most significant improvement （P<0.01）. ConclusionCaspase-1， GJA1， PPARG， and S100A8 are core Pyro-DEGs closely associated with the pathogenesis of UC. These genes may collaborate with immune cells such as mast cells， neutrophils， and M0 macrophages to mediate disease development. The Xiezhuo Jiedu formula may regulate the expression of core Pyro-DEGs through the NOD-like receptor， TNF， and HIF-1 core signaling pathways， thereby modulating immune homeostasis in UC rats and effectively alleviating UC.

Objective: To investigate the characteristics and HIV confirmed positive status among individuals attending HIV voluntary counseling and testing (VCT) clinics in Inner Mongolia Autonomous Region, so as to provide the basis for enhancing interventions targeting high-risk populations for AIDS. Methods: Demographic information, reasons for consultation, consulting institutions, and HIV antibody testing data of individuals attending VCT clinics in Inner Mongolia Autonomous Region from 2019 to 2023 were collected through the VCT database of the Chinese Center for Disease Control and Prevention. The characteristics of individuals attending VCT were described. Factors affecting HIV confirmed positive among VCT clinic attendees were analyzed using a multivariable logistic regression model. Results: A total of 249 919 individuals attended VCT clinics in Inner Mongolia Autonomous Region from 2019 to 2023, including 128 069 males (51.24%) and 121 850 females (48.76%). The majority of attendees were aged 25-<35 years, accounting for 92 445 cases (36.99%). Among them, 785 cases were confirmed as HIV positive, with a positivity rate of 0.31%. Multivariable logistic regression analysis revealed that males (OR=4.787, 95%CI: 3.562-6.434), 45-<65 years of age (45-<55 years, OR=7.723, 95%CI: 1.786-33.406; 55-<65 years, OR=7.689, 95%CI: 1.757-33.653), being unmarried (OR=2.143, 95%CI: 1.580-2.906), junior high school education or below (OR=1.147, 95%CI: 1.042-2.430), having the history of high-risk behaviors or exposure risks (commercial heterosexual behaviors, OR=2.717, 95%CI: 1.707-4.324; non-commercial non-fixed heterosexual behaviors, OR=5.421, 95%CI: 3.763-7.809; homosexual behaviors, OR=70.774, 95%CI: 48.409-103.473; having an HIV-positive spouse/fixed partner/mother, OR=100.024, 95%CI: 62.490-160.100; drug injection, OR=5.366, 95%CI: 2.213-13.014), and seeking general hospitals or traditional Chinese medicine hospitals (OR=1.973, 95%CI: 1.650-2.360) were associated with a higher risk of HIV confirmed positive. Conclusions HIV confirmed positive among individuals attending VCT clinics in Inner Mongolia Autonomous Region is associated with gender, age, marital status, educational level, reasons for consultation, and consulting institutions. It is recommended to strengthen health education and targeted interventions for high-risk populations to reduce the risk of HIV infection.

Objective: To investigate whether fibroblast growth factor 18(FGF18) can induce human gingival fibroblasts(HGFs) isolatedin vitroto differentiate into osteoblast-like cells, and to explore the mechanism of osteogenesis. Methods : HGFs were isolated, cultured and identified by tissue block method. The third generation of HGFs were divided into experimental group and control group. FGF18 and L-DMEM was added to the experimental group while L-DMEM was added to the control group.The effects of different concentrations of FGF18(0, 0.01, 0.02, 0.04, 0.06 mg/L) on proliferation of HGFs were detected by Methylthiazolyldiphenyl-tetrazolium bromide(MTT) assay. Alkaline phosphatase(ALP) and alizarin red staining were used to detect the osteogenesis and mineralization ability of the cells after induction. RT-PCR, immunocytochemistry staining, and Western blot were used to detect the expression of genes and proteins related to osteogenesis and BMP2 in the BMP signaling pathway. Results: Compared with the control group, the experimental group could promote the proliferation of HGFs at 3, 5, 7, 9, and 11days(P<0.05),ALP activity and mineral salt deposition increased after induction at 14 and 21 days(P<0.05), and the expressions of ALP, OPN, OCN mRNA and BMP2 mRNA in BMP signaling pathway significantly increased(P<0.01). The expressions of OPN, OCN and BMP2 protein at 21 days were significantly higher than those at 14 days(P<0.01). Conclusion FGF18 can promote the proliferation of HGFs, and induce the differentiation of HGFs into functional osteoblasts. The osteogenic mechanism is related to the upregulation of BMP2.

ObjectiveKey microRNAs （miRNAs） of colorectal adenoma （CRA） were identified and analyzed by bioinformatics methods， and differentially expressed genes （DEGs） were screened to construct regulatory relationships. The mechanism of Xiezhuo Jiedu recipe in preventing CRA was speculated and verified by animal experiments. MethodThe miRNAs dataset GSE50194 was obtained from the Gene Expression Omnibus （GEO） database of intestinal mucosal tissue of CRA patients， and the differentially expressed miRNAs were screened by GEO2R and Excel. TargetScan， miRTarbase， and miRDB databases were used to predict the target genes of the differentially expressed miRNAs， and an intersection was obtained. Key DEGs were screened through the STRING database and Cytoscape software， and the TRRUST database was used to predict downstream binding transcription factors （TFs）. The mRNA intersection was enriched by gene ontology （GO） and Kyoto encyclopedia of genes and genomes （KEGG） in the Metascape database. DIANA TOOLS were applied to perform KEGG enrichment analysis of key miRNAs， and the key signaling pathways were selected for animal experiments. In animal experiments， the CRA mice model was established by using sodium glycan sulfate （DSS） drinking combined with intraperitoneal injection of azomethane oxide （AOM）， and Xiezhuo Jiedu recipe and aspirin were given by intragastric administration at the same time. The experiment lasted for nine weeks. The pathological changes in intestinal tissue were observed by hematoxylin-eosin （HE） staining. Real-time fluorescence quantitative polymerase chain reaction （Real-time PCR） was used to detect the mRNA expression of miR-34a-5p in adenoma tissue. Protein expression levels of phosphatidylinositol 3-kinase （PI3K）， protein kinase B （Akt）， phosphoryl-PI3K （p-PI3K）， phosphoryl-Akt （p-Akt）， and B cell lymphoma （Bcl）-2 were detected by Western blot. The expression of Cyclin D1 （CCND1） was detected by immunohistochemistry （IHC）. In situ terminal transferase labeling （TUNEL） was used to detect apoptosis of adenoma tissue cells. ResultThe GEO database screened the GSE50194 dataset， and miR-34a-5p was selected as the research object from CRA and normal tissue. A total of 93 DEGs were selected. Among them， GO and KEGG enrichment analyses were closely related to biological processes such as transcriptional regulatory complex， RNA polymerase Ⅱ transcriptional regulatory complex， enzyme-linked receptor protein signaling pathway， and DNA-binding transcriptional activator activity， cancer pathway， PI3K/Akt pathway， etc. miR-34a-5p is mainly enriched in PI3K/Akt， cell cycle， and colorectal cancer pathways. Five key DEGs were screened out through the Matescape database， among which Bcl-2 and CCND1 were the key DEGs of miR-34a-5p. Further screening of the TFs of key DEGs revealed that E2F transcription factor 1 （E2F1） and tumor protein P53 （TP53） were the main TFs of Bcl-2 and CCND1. Animal experiments showed that Xiezhuo Jiedu recipe could effectively up-regulate mRNA level of miR-34a-5p， down-regulate the expression of PI3K， Akt， Bcl-2， p-PI3K， and p-Akt proteins in the intestinal tissue of CRA mice， down-regulate the positive expression rate of CCND1， and increase the apoptosis rate of intestinal epithelial cells. ConclusionIt is speculated that Xiezhuo Jiedu recipe may inhibit the abnormal proliferation and promote the apoptosis of intestinal epithelial cells in CRA mice by regulating the miR-34a-5p/PI3K/Akt signaling pathway， thus playing a role in the prevention of CRA.

BACKGROUND:Sepsis is one of the main causes of mortality in intensive care units(ICUs).Early prediction is critical for reducing injury.As approximately 36%of sepsis occur within 24 h after emergency department(ED)admission in Medical Information Mart for Intensive Care(MIMIC-IV),a prediction system for the ED triage stage would be helpful.Previous methods such as the quick Sequential Organ Failure Assessment(qSOFA)are more suitable for screening than for prediction in the ED,and we aimed to find a light-weight,convenient prediction method through machine learning. METHODS:We accessed the MIMIC-IV for sepsis patient data in the EDs.Our dataset comprised demographic information,vital signs,and synthetic features.Extreme Gradient Boosting(XGBoost)was used to predict the risk of developing sepsis within 24 h after ED admission.Additionally,SHapley Additive exPlanations(SHAP)was employed to provide a comprehensive interpretation of the model's results.Ten percent of the patients were randomly selected as the testing set,while the remaining patients were used for training with 10-fold cross-validation. RESULTS:For 10-fold cross-validation on 14,957 samples,we reached an accuracy of 84.1%±0.3%and an area under the receiver operating characteristic(ROC)curve of 0.92±0.02.The model achieved similar performance on the testing set of 1,662 patients.SHAP values showed that the five most important features were acuity,arrival transportation,age,shock index,and respiratory rate. CONCLUSION:Machine learning models such as XGBoost may be used for sepsis prediction using only a small amount of data conveniently collected in the ED triage stage.This may help reduce workload in the ED and warn medical workers against the risk of sepsis in advance.