ObjectiveTo investigate the current status of latent tuberculosis infection (LTBI) among the elderly population in rural areas of Changxing County, Zhejiang Province, and to provide an evidence for the development of LTBI prevention and control measures. MethodsBetween January and May 2024, elderly individuals participating in urban and rural residents’ health checkups were screened for Mycobacterium tuberculosis infection using a domestically produced interferon-γ release assay (IGRA) kit. Individuals tested positive by IGRA but without active tuberculosis were classified as LTBI cases. The prevalence of LTBI among the participants was subsequently analyzed. ResultsAmong the 6 765 subjects, 637 tested positive by IGRA, including one identified active tuberculosis patient, resulting in a LTBI prevalence rate of 9.40%. There was a statistically significant difference in positivity rates across different IGRA methodologies (χ²=35.530, P<0.001). Higher LTBI rate was observed in males, individuals with a history of diabetes mellitus, and those with a history of pulmonary tuberculosis, exhibiting statistically significant differences (χ²=32.401, P<0.001; χ²=5.789, P=0.020; χ²=39.248, P<0.001, respectively.) No statistically significant difference in LTBI rate was found across different age groups (χ²=0.238, P=0.971). ConclusionThe prevalence of LTBI among the elderly rural residents in Changxing County is relatively low. Male, individuals with a history of diabetes mellitus, and those with a history of pulmonary tuberculosis have an increased risk of LTBI, warranting targeted risk monitoring and timely interventions.

BACKGROUND:Rheumatoid arthritis is a chronic systemic autoimmune disease.It is important to study the immunological changes involved in it for diagnosis and treatment. OBJECTIVE:To identify immune-related biomarkers associated with rheumatoid arthritis utilizing bioinformatics techniques and examine alterations in immune cell infiltration as well as the relationship between immune cells and biomarkers. METHODS:Differential expression analysis was used to identify the immune-related genes that were up-regulated in rheumatoid arthritis based on the GEO and Immport databases.Kyoto encyclopedia of genes and genomes(KEGG)and gene ontology(GO)enrichment analyses were used to investigate the possible function of these elevated genes.The immunological characteristic genes associated with rheumatoid arthritis were screened using least absolute shrinkage and selection operator(Lasso)and support vector machine recursive feature elimination(SVM-RFE).Independent datasets were used for difference validation,and the diagnostic performance was evaluated by plotting receiver operating characteristic curves for feature genes.Immune cell infiltration was used to analyze the differential profile of immune cells in rheumatoid arthritis and the correlation between the characterized genes and immune cells.In order to ascertain the causal relationship between monocytes and rheumatoid arthritis in immune cells,Mendelian randomization analysis was ultimately employed. RESULTS AND CONCLUSION:There were 39 upregulated differentially expressed genes in rheumatoid arthritis.The genes were primarily enriched in chemotaxis,cytokine activity,and immune receptor activity,according to GO enrichment analysis,while kEGG enrichment analysis revealed that the genes were considerably enriched in the tumor necrosis factor signaling pathway and peripheral leukocyte migration.Lasso and SVM-RFE identified five feature genes:CXCL13,SDC1,IGLC1,PLXNC1,and SLC29A3.Independent dataset validation of the feature genes found them to be similarly highly expressed in rheumatoid arthritis samples,with area under the curve values greater than 0.8 for all five feature genes in both datasets.Immune cell infiltration indicated that most immune cells,including natural killer cells and monocytes,exhibited increased levels of infiltration in rheumatoid arthritis samples.The correlation analysis revealed a significant positive correlation between memory B cells and immature B cells and these five feature genes.Correlation analysis showed that the five feature genes were positively correlated with memory B cells and immature B cells.The inverse variance weighting method revealed that monocytes were associated with the risk of developing rheumatoid arthritis.

Objective To assess the efficacy of endoscopic ultrasound-guided enteroenterostomy(EUS-EE)in the management of malignant bowel obstruction(MBO).Methods Retrospective analysis was conducted on clinical data from 14 patients who underwent EUS-EE for MBO from June 2022 to December 2023.A modified intestinal preparation protocol was employed prior to the procedure,and the resolution of symptoms,improvement in nutritional status,and occurrence of complications were statistically analyzed post-EUS-EE.Results EUS-EE was successfully performed in all 14 cases.The Colorectal obstruction scoring system(CrOSS)was used to evaluate preoperative and postoperative symptom relief and alleviation of bowel obstruction.One week after the procedure,CrOSS scores increased from 1 to 2 before surgery to 2～4.The patient-generated subjective global assessment(PG-SGA)score for malignancy patients demonstrated a mean score of(9.64±3.13)one week after surgery among the study cohort of 14 patients.This score showed a significant decrease compared to their preoperative PG-SGA score(12.36±3.22),with a statistical difference(t=2.26,P=0.032).Postoperatively,five patients experienced elevated body temperature,three had pneumoperitoneum,and two developed short bowel syndrome;However,these complications were effectively managed through symptomatic treatment resulting in recovery or relief thereof.At one-year follow-up,the median survival time was recorded as 81(41,500)d with a one-year survival rate at 64.29％.Conclusion EUS-EE offers advantages such as high remission rates for symptoms,minimal trauma,and low reintervention rates.For patients with poor baseline conditions or limited life expectancy,EUS-EE can alleviate physical discomfort symptoms,improve quality of life,and prolong survival period.

Background/Aims: Low educational attainment is a well-established risk factor for nonalcoholic fatty liver disease (NAFLD) in developed areas. However, the association between educational attainment and the risk of NAFLD is less clear in China. Methods: A cross-sectional study including over 200,000 Chinese adults across mainland China was conducted. Information on education level and lifestyle factors were obtained through standard questionnaires, while NAFLD and advanced fibrosis were diagnosed using validated formulas. Outcomes included the risk of NAFLD in the general population and high probability of fibrosis among patients with NAFLD. Logistic regression analysis was employed to estimate the risk of NAFLD and fibrosis across education levels. A causal mediation model was used to explore the potential mediators. Results: Comparing with those receiving primary school education, the multi-adjusted odds ratios (95% confidence intervals) for NAFLD were 1.28 (1.16 to 1.41) for men and 0.94 (0.89 to 0.99) for women with college education after accounting for body mass index. When considering waist circumference, the odds ratios (95% CIs) were 0.94 (0.86 to 1.04) for men and 0.88 (0.80 to 0.97) for women, respectively. The proportions mediated by general and central obesity were 51.00% and 68.04% for men, while for women the proportions were 48.58% and 32.58%, respectively. Furthermore, NAFLD patients with lower educational attainment showed an incremental increased risk of advanced fibrosis in both genders. Conclusions In China, a low education level was associated with a higher risk of prevalent NAFLD in women, as well as high probability of fibrosis in both genders.

The synergistic effect of drug combinations can solve the problem of acquired resistance to single drug therapy and has great potential for the treatment of complex diseases such as cancer. In this study, to explore the impact of interactions between different drug molecules on the effect of anticancer drugs, we proposed a Transformer-based deep learning prediction model-SMILESynergy. First, the drug text data-simplified molecular input line entry system (SMILES) were used to represent the drug molecules, and drug molecule isomers were generated through SMILES Enumeration for data augmentation. Then, the attention mechanism in the Transformer was used to encode and decode the drug molecules after data augmentation, and finally, a multi-layer perceptron (MLP) was connected to obtain the synergy value of the drugs. Experimental results showed that our model had a mean squared error of 51.34 in regression analysis, an accuracy of 0.97 in classification analysis, and better predictive performance than the DeepSynergy and MulinputSynergy models. SMILESynergy offers improved predictive performance to assist researchers in rapidly screening optimal drug combinations to improve cancer treatment outcomes.
Electric Power Supplies ; Neural Networks, Computer ; Antineoplastic Agents/pharmacology*

Abstract Fear of missing out is an emerging type of anxiety disorder in the context of the Internet and has showed significant impacts on physical and mental health of college students. The review provides an overview on the connotation, extension, and adverse effects, as well as potential underlying mechanisms of fear of missing out in mobile social media among college students, which aims to highlight future attention, as well as prevention and intervention reference on fear of missing out in college students.

Objective:To study disease spectrum and genetic profiles of inborn errors of metabolism (IEM) among newborns in selected areas of Nanning city.Methods:From July 2019 to December 2021, neonates born and received IEM screening in our hospital were prospectively enrolled. Heel blood samples were tested using tandem mass spectrometry as IEM screening. Neonates with positive results were called back for recheck. Whole exome sequencing was used to detect possible pathogenic genes in suspected cases and IEM was diagnosed combining clinical manifestations. Sanger sequencing method was used for the diagnosed neonates and their parents to confirm the diagnoses.Results:A total of 16 207 live-birth neonates were enrolled. For initial IEM screening, 1 423 neonates were positive (8.8%) and 1 311 were called back (92.1%). 15 cases were suspected with IEM and 8 were diagnosed. The overall detection rate was 1∶2 026. Among 8 confirmed cases, 4 cases had amino acid metabolism disorders (2 cases of phenylketonuria, 1 case of Citrin deficiency and 1 case of tyrosinemia), 2 cases had organic acid metabolism disorders (1 case of methylmalonic acidemia and 1 case of glutaric acidemia) and 2 cases had fatty acid oxidation disorders (1 case of carnitine palmitotransferaseⅡdeficiency and 1 case of primary carnitine deficiency). 5 cases had homozygous genetic variants (2 in PAH, and 1 in SLC25A13, SLC22A5 and FAH, respectively) and 3 had heterozygous genetic variants (1 in CPT2, MUT, and GCDH, respectively). During follow-up, all 8 cases had normal growth and developmental outcomes after standardized treatment.Conclusions:The overall detection rate of IEM is high, with varied genetic profiles in selected areas of Nanning. Timely genetic testing may lead to early diagnosis and treatment and improve the quality of life of neonates.

Objective To rapidly explore the chemical components of Xiaotan Tongfu formula, and to provide scientific basis for the basic research and clinical treatment of the formula. Methods Analysis was performed on an Agilent 1290 ultra-performance liquid chromatography system coupled with an Agilent 6530 accurate quality Q-TOF/MS system, by using a Waters ACQUITY UPLC BEH C₁₈ column (2.1 mm × 100 mm, 1.7 μm), with a gradient elution applying 0.1% aqueous formic acid solution and acetonitrile as a mobile phase. The flow rate was 0.3 ml/min. The column temperature was 30°C. The injection volume was 1 μl, and the detection wavelength was 254 nm. Mass spectrometry (MS) data were collected in both positive and negative ESI ion modes. Components in the formula were identified by using the in-house compound database, and comparing the retention time (tR), MS1 and MS2 data with the standard compounds, and the online compound MS database. Results A total of 55 compounds were identified from Coptis coptidis, Pseudomonas solani, Rhubarb, Araceae artemisiae and Pinellia chinensis. Conclusion The established UHPLC-Q-TOF/MS method could systematically and accurately identify the chemical components from Xiaotan Tongfu formula, and provided a reference for the quality marker selection and the research on the active ingredient.

Different cell lines have different perturbation signals in response to specific compounds, and it is important to predict cell viability based on these perturbation signals and to uncover the drug sensitivity hidden underneath the phenotype. We developed an SAE-XGBoost cell viability prediction algorithm based on the LINCS-L1000 perturbation signal. By matching and screening three major dataset, LINCS-L1000, CTRP and Achilles, a stacked autoencoder deep neural network was used to extract the gene information. These information were combined with the RW-XGBoost algorithm to predict the cell viability under drug induction, and then to complete drug sensitivity inference on the NCI60 and CCLE datasets. The model achieved good results compared to other methods with a Pearson correlation coefficient of 0.85. It was further validated on an independent dataset, corresponding to a Pearson correlation coefficient of 0.68. The results indicate that the proposed method can help discover novel and effective anti-cancer drugs for precision medicine.
Algorithms ; Antineoplastic Agents/pharmacology* ; Cell Survival ; Pharmaceutical Preparations