ObjectiveTo identify the independent risk factors for pyloric lymph node （PLN） metastasis in patients with upper gastric cancer （UGC） and to construct a nomogram prediction model applicable for UGC patients. MethodsClinical data of 823 UGC patients attended between January 2020 and November 2023 were retrospectively collected. Patients were randomly divided into a training set （n=576） and a validation set （n=247） at a 7∶3 ratio. Based on the training set， multivariate Logistic regression analysis was performed to identify independent risk factors for PLN metastasis， and a nomogram prediction model was constructed accordingly. The model's discriminative ability and calibration were assessed using receiver operating characteristic （ROC） curves and calibration curves. Finally， external validation was conducted using the validation set to evaluate the model's stability and generalizability. ResultsMultivariate Logistic regression analysis revealed that tumor size （OR=1.324， 95%CI： 1.053-1.667）， T3 stage （OR=5.738， 95%CI： 1.281-25.695）， T4 stage （OR=7.680， 95%CI： 1.542-38.247）， lymphovascular invasion （LVI） （OR=6.623， 95%CI： 1.384-31.708）， differentiation extent （OR=3.108， 95%CI： 1.545-6.251）， and fibrinogen degradation product （FDP） level （OR=4.849， 95%CI： 2.071-11.355） were independent risk factors for PLN metastasis in UGC patients.The nomogram model constructed based on these factors demonstrated areas under the ROC curve （AUC） of 0.815 （95%CI： 0.751-0.815） in the training set and 0.832 （95%CI： 0.731-0.933） in the validation set. Calibration curves indicated good agreement between predicted and observed outcomes. ConclusionThis nomogram prediction model exhibits good predictive performance for assessing the risk of PLN metastasis in UGC patients.

Background Public places are important areas for daily human activities. Frequent contact with public items promotes their role as vehicles for microbial spread, creating a substantial risk for the transmission of pathogenic microorganisms. Objective To understand the hygiene status and influencing factors of public items in typical public places in Shanghai from 2010 to 2024, and to provide a scientific basis for optimizing the hygiene management of public items. Methods Based on the monitoring data of public items in public places in Shanghai from 2010 to 2024, the hygiene status was evaluated in three stages: 2010–2019, 2020–2022, and 2023–2024. Chi-square test and logistic regression were used to analyze the impact of factors such as monitoring stages, public place types, and public item categories on the hygiene status. Results The public items in 13807 public places were monitored. A total of 1 022 bed sheets and 9 271 towels were tested for pH value, with qualified rates of 77.66% and 87.81%, respectively. The OR (95%CI) for the pH compliance of towels relative to bed sheets was 1.77 (1.45, 2.15). Compared with bathing places, the ORs for pH compliance of towels in hair salons and beauty salons were 2.24 (1.75, 2.87) and 2.15 (1.57, 2.95), respectively. Additionally, a total of 221 650 samples from various public items were tested for microorganisms, yielding 215554 qualified samples, with an average qualified rate of 97.25%. The qualified rates for total bacterial count, total fungal count, coliforms, and Staphylococcus aureus were 92.66%, 94.63%, 98.85%, and 99.84%, respectively. The logistic regression analysis showed that, compared to the 2016–2019 baseline, no statistically significant differences were observed in the qualified rates of total fungal count across different stages; however, significantly higher qualified rates for total bacterial count, total fungal count, coliforms, and Staphylococcus aureus were recorded during 2020–2022, with ORs (95%CI) of 1.27 (1.16, 1.38), 23.20 (8.42, 63.94), and 12.08 (1.63, 89.92), respectively. Conclusion The pH compliance ranks among the top tier nationwide for cotton textile goods in Shanghai, suggesting minimal detergent retention. Furthermore, continuous improvement in cleaning and disinfection measurements has markedly enhanced the microbial hygiene of public items in public places.

Background Swimming is becoming increasingly popular for its combined leisure and fitness benefits. However, polluted swimming pool water may pose various health risks. Previous studies have indicated that health indicators of swimming venues have lower qualification rates compared to other public places, highlighting the urgent need to optimize hygiene management measures. Objective To assess the overall hygiene status and identify the key factors influencing water quality in Shanghai’s swimming venues from 2010 to 2024, and to provide a scientific basis for optimizing water quality management. Methods Water quality was assessed in three stages (2010—2019, 2020—2022, and 2023—2024) based on the monitoring data of Shanghai’s swimming venues (2010—2024). The influences of monitoring stage, region, season, scale, day of week, and per capita attendance on water quality were analyzed using chi-square tests and logistic regression. Results From 2010 to 2024, water quality was monitored in 1478 swimming venues. The compliance rates of turbidity, pH, urea, oxidation-reduction potential, free residual chlorine, combined residual chlorine, total bacteria, coliforms, and heat-resistant coliforms in swimming pool water, and free residual chlorine in the foot disinfection basin water samples were 99.56%, 94.73%, 73.00%, 47.50%, 56.55%, 54.12%, 97.74%, 99.49%, 99.90%, and 69.19%, respectively. The overall water quality compliance rate was 85.28%. The main non-compliant indicators for swimming pool water were urea, ORP, free residual chlorine, and combined residual chlorine, along with free chlorine residual in the foot disinfection basin water samples. Using the period before the implementation of the new national standard as reference, the results of logistic regression revealed that the qualification rates of urea, ORP, and free residual chlorine in the swimming pool water samples, as well as free residual chlorine in foot disinfection basin water samples, were significantly higher during the two phases after launching the new standard (2020–2022 and 2023–2024), and the associated odds ratios (95%CI) were 1.28 (1.00, 1.64) and 1.48 (1.12, 1.95), 13.35 (7.63, 23.37) and 10.78 (7.00, 16.60), 2.54 (1.81, 3.58) and 3.18 (2.41, 4.20), and 3.14 (2.14, 4.60) and 2.83 (1.89, 4.23), respectively. Compared with the reference group, those sampled in urban pools and in non-summer seasons showed higher qualification rates of urea and ORP; in contrast, the pools with high visitor flow showed lower qualification rates of free residual chlorine in both water samples of swimming pools and foot disinfection basins (P<0.05). Conclusion The implementation of the new national standard has effectively enhanced the management standards and significantly improved overall water quality of swimming venues in Shanghai. However, the compliance rates of free residual chlorine and urea in swimming pool water still need further improvement. The compliance of some indicators is influenced by region, season, scale, and average passenger flow, particularly in small suburban swimming venues. Future efforts should focus on refining water quality management strategies and enhancing public health management.

Objective To explore the research hotspots and development trends in the field of cancer treatment in the past decade. Methods The CNKI and Web of Science Core Collection databases were searched for Chinese and English articles related to cancer treatment published over the last 10 years. Bibliometric research methods were employed, including keyword cluster analysis of published literature. Results A total of 45 455 Chinese articles and 866 958 English articles were retrieved. Combining the visualization analysis results and the current research dilemma of tumor treatment revealed that the current research hotspots of tumor treatment domestically and internationally can primarily focus on four key areas. In the realm of targeted therapy, efforts are directed towards the discovery of new drug targets, overcoming resistance to targeted therapy, and the development of monoclonal antibodies and antibody–drug conjugates. In the field of immunotherapy, the emphasis lies in enhancing the response rate to immune checkpoint inhibitors, determining the mechanisms behind resistance to immunotherapy, and improving the safety of treatment. The research in traditional Chinese medicine (TCM) covers evidence-based evaluation studies on TCM treatment, the identification of populations that can gain the most benefit from TCM, and strategies for improving the quality of life. In the area of novel drug development, cutting-edge technologies, such as organoid-based screening for anticancer drugs, synthetic biology, and artificial intelligence, are under investigation. Conclusion New targeted drugs, immune efficacy improvement, multidisciplinary integration, nano-delivery, and TCM innovation are the key research directions in the field of tumor therapy in the future.

Objective:To analyze the epidemiological features of pediatric sepsis in the Kashgar region and investigate factors associated with its prognosis, thereby providing evidence for implementing regional public health prevention and control policies.Methods:A single-center, retrospective observational study was conducted on the clinical data of pediatric sepsis patients admitted to the pediatric intensive care unit (PICU) of The First People′s Hospital of Kashgar between January 2022 and December 2023. For the assessment of clinical outcomes, this study utilized a composite endpoint comprising "length of hospital stay and survival status", classifying patients into two groups: Group A (survived with hospital stay <28 days) and Group B (hospital stay ≥28 days or in-hospital mortality). Univariate and binary logistic regression analyses were performed to identify independent risk factors associated with prognosis.Results:This study included a total of 79 pediatric patients with sepsis, with an age range of 1 month to 14 years and a median age of 8 months. Males accounted for 62.0% (49 males, 30 females). The rates of comorbid septic shock, sepsis-associated encephalopathy, and acute kidney injury were 73.4% (58/79), 24.1% (19/79), and 16.5% (13/79), respectively. The primary site of infection was the gastrointestinal tract, accounting for 34.2% (27/79), followed by the respiratory tract at 30.4% (24/79). Pathogens were detected in 59.5% (47/79) of the patients, with Staphylococcus aureus identified in 11 cases, Acinetobacter baumannii and Escherichia coli in 6 cases each, Klebsiella pneumoniae in 5 cases, and Candida albicans in 3 cases. The mechanical ventilation rate was 59.5% (47/79). The total hospital length of stay ranged from 1 to 55 days, with a median of 14 days, while the ICU length of stay ranged from 1 to 29 days, with a median of 6 days. In-hospital mortality occurred in 15 cases (19.0%). Group A comprised 56 patients (70.9%), and Group B comprised 23 patients (29.1%). Univariate analysis revealed that Group A had significantly higher mean arterial pressure (MAP), pediatric critical illness score (PCIS), and Glasgow coma scale (GCS) (all P<0.05), and significantly lower pediatric risk of mortality Ⅲ (PRISM Ⅲ), pediatric logistic organ dysfunction-2 (PELOD-2), lactate levels, pediatric multiple organ dysfunction score (P-MODS), pediatric sequential organ failure assessment (pSOFA), septic shock rate, and mechanical ventilation rate compared to Group B (all P<0.05). Binary logistic regression analysis identified a high PELOD-2 score ( OR: 1.38, 95% CI: 1.16-1.64, P<0.001) as an independent risk factor for poor prognosis, while a high GCS ( OR: 0.81, 95% CI: 0.74-0.88, P<0.001) served as a protective factor against poor prognosis. The combination of PELOD2 and GCS demonstrated good predictive ability for in-hospital outcomes in pediatric sepsis patients, with an area under the ROC curve of 0.82 (95% CI: 0.72-0.92). Conclusion:In children with sepsis in the Kashgar region, gastrointestinal tract infection represents the most common source of infection. Elevated PELOD-2 scores and reduced GCS are both indicative of a poorer prognosis, and a combined model integrating these two scoring systems may serve as a valuable tool for prognostic assessment.

Objective:To analyze the target signaling pathway of histone H3K27 methylation-induced podocyte injury, verify the regulatory effect of histone H3K27 methylation on podocyte injury in focal segmental glomerulosclerosis (FSGS) mice through target signaling pathway, and explore the mechanism of abnormal methylation of histone H3K27-induced podocyte injury in FSGS mice.Methods:(1) Cell experiments: primary cultured immortalized mouse podocytes MPC5 were cultured in vitro, and divided into control group, adriamycin (ADR) group, ADR+GSK-J4 (histone demethylase, KDM6B inhibitor) group, ADR+coumarin A1 (C-A1, JAK2 agonist) group and ADR+GSK-J4+C-A1 group. The transmission electron microscope was used to observe ultrastructure of podocytes. Immunofluorescence was used to detect the protein expression of H3K27me3 and nephrin in podocytes. The whole genome sequence of podocytes was obtained, the differentially expressed genes were screened, and Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) were used for enrichment analysis. Real time-quantitative PCR and Western blotting were used to detect the gene and protein expression of JAK2-STAT3 signaling pathway in podocytes respectively. Enzyme-linked immunosorbent assay was used to detect interleukin 6 (IL-6), monocyte chemotactic protein 1 (MCP-1), α-smooth muscle actin (α-SMA) and transforming growth factor β1 (TGF-β1). (2) Animal experiments: EZH2 gene knock out ( EZH2podKo)-FSGS (tail vein injection of ADR) mouse models were established, and divided into EZH2ctrl+control group ( n=20), EZH2ctrl+FSGS ( n=20), EZH2podKo+control group ( n=30) and EZH2podKo+FSGS group ( n=30). HE staining was used to observe the morphology of kidney tissues. Immunohistochemistry was used to detect the H3K27me3 protein expression in podocytes. Real time-quantitative PCR and Western blotting were used to verify the gene and protein expression of JAK2-STAT3 signaling pathway respectively. Enzyme-linked immunosorbent assay was used to detect IL-6, MCP-1, α-SMA and TGF-β1 of kidney tissues. Results:(1) Cell experiments: Compared with control group, the nucleus shrank and ruptured, the cytoplasm showed vacuole, and mitochondria and endoplasmic reticulum swelled in ADR group, which verified that the podocyte injury model of ADR nephropathy was successfully established. Compared with control group, the protein expression level of H3K27me3 in ADR group was significantly lower ( P<0.05). Compared with ADR group, the protein expression level of H3K27me3 in podocytes in ADR+GSK-J4 group was significantly higher ( P<0.05), and there were 502 increased genes and 443 decreased genes. GO enrichment analysis showed that the differentially enriched peaks were mainly in ribonucleoprotein complex biogenesis, ribosome biogenesis, establishment of protein localization to organelle, and involved in regulation of receptor signaling pathway via JAK-STAT and receptor signaling pathway via JAK-STAT. Differential expressed genes were Irf1, Tnfrsf1a, S ocs1, Notch1, Gadd45a, Hes1 and Socs3, involving in the regulation of JAK-STAT signaling pathway. KEGG enrichment analysis showed that the differentially enriched peaks were mainly in amyotrophic lateral sclerosis, and the target genes were Mcl1, Egfr, Socs1, Cdkn1a, Pdgfa and Socs3, involving in the regulation of JAK-STAT signaling pathway. Compared with ADR group, the mRNA and protein expression levels of JAK2 and STAT3 in the ADR+GSK-J4 group were significantly lower, and the downstream inflammatory factors of IL-6, MCP-1 and α-SMA were significantly higher (all P<0.05). Compared with ADR group, the protein expression level of nephrin in ADR+GSK-J4 group was higher ( P<0.05), and the protein expression level of nephrin in ADR+C-A1 group was lower ( P<0.05). Compared with ADR+GSK-J4 group, the protein expression level of nephrin in ADR+GSK-J4+C-A1 group was lower ( P<0.05). (2) Animal experiments: Compared with EZH2ctrl+FSGS group, EZH2podKo+FSGS group showed obvious renal tissue damage, matrix hyperplasia in mesangial area with massive homogeneous substance deposition, apoptosis and necrosis of renal tubular epithelial cells, obvious thickening and extensive fusion of glomerular epithelial cells, basement membrane collapse, and compression and narrowing of capillary structure. Compared with EZH2ctrl+FSGS group, the protein expression level of H3K27me3 in EZH2podKo+FSGS group was significantly lower, and the mRNA and protein expression levels of JAK2 and STAT3, and the levels of IL-6, MCP-1, α-SMA and TGF-β1 were higher (all P<0.05). Conclusions:Abnormal methylation modification of H3K27 leads to change of target gene expression, activation of JAK2-STAT3 signaling pathway, podocyte injury, glomerulosclerosis and renal tubular injury, participating in the development of FSGS.

Objective:To explore the influence of different scanning positions based on chest phantom of computed tomography(CT)scan on chest on image quality and radiation dose.Methods:A thermoluminescent dosimeter(TLD)was placed at the breast area of simulating anthropoid chest phantom.GE Revolution evo CT was used to conduct scan on the conventional supine position(supine group)and prone position(prone group)for chest phantom.Different noise indexes(NI=10-23)were adjusted to control ration doses,and other parameters were fixed,and each group collected 12 sequence images.The average value(AV),standard deviation(SD)of the CT scan at region of interest(ROI)under different scanning positions were recorded to calculate the signal-to-noise ratio(SNR)and contrast-to-noise ratio(CNR)of the image.The radiation dose at the breast area was measured by TLD,and the volume CT dose index(CTDIvol)and dose-length product(DLP)were recorded.Results:Under different scanning positions,the radiation dose of breast organs in the prone group was lower than that in the supine group,there was a statistically significant difference between the two groups(t=6.57,P<0.05),while there were not statistically significant differences in CTDIvol and DLP between the two groups(P>0.05).There were not statistically significant differences in the CT values,SD,SNR,CNR of lung tissue,and the CT values of breast tissue between the two groups of images(P>0.05).The SD,SNR and CNR of breast tissue in the prone group were lower than those in the supine group,and the differences were statistically significant(t=-13.33,-10.59,6.70,P<0.05).There were no statistically significant differences in the subjective scores of the clarity of the edge of the tissue within lung,the layers of soft tissue of the breast,noise,and artifacts in the bone tissue between the two groups of images(P>0.05).Conclusion:When low-dose CT physical examination on chest is conducted in clinical practice,the scanning of prone position during undergoing CT scan on chest can obtain image quality that can meet the requirements in diagnosing lung,and reduce the radiation dose on the breast,and conform to the technical principle of optimal radiation protection.

Perimenopausal depression seriously affects women's physical and mental health.It is caused primarily by gonadal function decline,which is typically characterized by low mood,anxiety,slow thinking,and loss of interest,and is accompanied by autonomic dysfunction and endocrine dysfunction.The pathogenesis of perimenopausal depression remains unclear and controversial.Many scholars have conducted scientific research that is based on animal models of perimenopausal depression.Indeed,a good animal model of perimenopausal depression is the basic premise for studying its pathophysiological mechanisms and for facilitating reliability of the scientific result.Therefore,this paper combines the modern research mechanisms of perimenopausal depression and the current status of animal models in China,and provides an overview,evaluation,and generalization of the modeling method,principles and result,to provide a scientific basis and reference for the selection of suitable animal models for scientific research experiments.

Objective To explore the factors influencing cognitive frailty in elderly inpatients with chronic heart failure(CHF)during hospitalisation,8 prediction models were developed with various machine learning algorithms to identify the best model as a guidance for medical staff on clinical interventions.Methods Convenience sampling method was used to select 650 elderly CHF inpatients who stayed in our hospital between September 2023 and June 2024 as the study objects in the cross-sectional investigation.A total of 607 patients had completed the study.The patients were divided into a cognitive frailty group and a non-cognitive frailty group according to the presence or absence of cognitive frailty.Variables were initially screened using univariate analysis and stepwise Logistic regression.The total sample was then randomly divided into a training set(n=424)and a testing set(n=183)of a 7:3 ratio.Eight predictive models were created using the algorithms of neural network(NN),k-nearest neighbour(KNN),linear discriminant analysis(LDA),support vector machine(SVM),naive Bayes(NB),logistic regression,decision tree(DT)and random forest(RF)on the training set.The predictive performance of the models was compared using the data of the testing set.Results The prevalence of cognitive frailty in elderly CHF inpatients was 48.3%.Results of Logistic regression showed that age,marital status,education,body mass index,multi-morbidity,nutritional status,medication,frequency of weekly exercise and the living conditions were the key factors(P<0.05).The overall accuracy in classification of the eight predictive models ranged from 0.803 to 0.847,with F1-values of 0.778 to 0.833,precision of 0.848 to 0.897,and recall rate of 0.700 to 0.778.The area under the receiver operating characteristic curve was 0.820 to 0.901.Conclusion Of the eight predictive models,the prediction model created with LDA shows the best performance and prediction in terms of comprehensive prediction metrics,while the prediction model created with NN shows the worst performance in comprehensive prediction.