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.

Based on ultra-high performance liquid chromatography-quadrupole-Exactive Orbitrap mass spectrometry(UPLC-Q-Exactive Orbitrap-MS) technology and network pharmacology, this study explored the pharmacodynamic substances and potential mechanisms of Huazhuo Sanjie Chubi Decoction in the treatment of gouty arthritis(GA). UPLC-Q-Exactive Orbitrap-MS technology was used to identify the components in Huazhuo Sanjie Chubi Decoction, and the qualitative analysis of its active ingredients was carried out, with a total of 184 active ingredients identified. A total of 897 active ingredient targets were screened through the PharmMapper database, and 491 GA-related disease targets were obtained from the OMIM, GeneCards, CTD databases. After Venn analysis, 60 intersecting targets were obtained. The component target-GA target network was constructed through the Cytoscape platform, and the STRING database was used to construct a protein-protein interaction network, with 16 core targets screened. The core targets were subjected to Gene Ontology(GO) and Kyoto Encyclopedia of Genes and Genomes(KEGG) pathway enrichment analyses, and the component-target-pathway network was constructed. It was found that the main active ingredients of the formula for the treatment of GA were phenols, flavonoids, alkaloids, and terpenoids, and the key targets were SRC, MMP3, MMP9, REN, ALB, IGF1R, PPARG, MAPK1, HPRT1, and CASP1. Through GO analysis, it was found that the treatment of GA mainly involved biological processes such as lipid response, bacterial response, and biostimulus response. KEGG analysis showed that the pathways related to the treatment of GA included lipids and atherosclerosis, neutrophil extracellular traps(NETs), IL-17, and so on. In summary, phenols, flavonoids, alkaloids, and terpenoids may be the core pharmacodynamic substances of Huazhuo Sanjie Chubi Decoction in the treatment of GA, and the pharmacodynamic mechanism may be related to SRC, MMP3, MMP9, and other targets, as well as lipids and atherosclerosis, NETs, IL-17, and other pathways.
Drugs, Chinese Herbal/therapeutic use* ; Network Pharmacology ; Arthritis, Gouty/metabolism* ; Chromatography, High Pressure Liquid/methods* ; Humans ; Mass Spectrometry/methods* ; Protein Interaction Maps/drug effects*

Children with bronchopulmonary dysplasia (BPD) often exhibit severe respiratory problems and significant pulmonary dysfunction during school age and adulthood. Exercise tests show a decline in cardiopulmonary function and physical performance in children with BPD, who also have a higher incidence of pulmonary hypertension. These children generally perform poorly in terms of intelligence, language, and motor development. As they age, the risk of neurodevelopmental disorders increases, and health-related quality of life is also affected. This article reviews the prognosis of the respiratory system, physical capacity, cardiovascular system, nervous system, and health-related quality of life in children with BPD, aiming to improve the management of these patients and enhance their subsequent quality of life.
Humans ; Bronchopulmonary Dysplasia/complications* ; Prognosis ; Quality of Life ; Child

OBJECTIVE: As an age-related neurodegenerative disease, the prevalence of mild cognitive impairment (MCI) increases with age. Within the framework of traditional Chinese medicine, spleen-kidney deficiency syndrome (SKDS) is recognized as the most frequent MCI subtype. Due to the covert and gradual onset of MCI, in community settings it poses a significant challenge for patients and their families to discern between typical aging and pathological changes. There exists an urgent need to devise a preliminary diagnostic tool designed for community-residing older adults with MCI attributed to SKDS (MCI-SKDS). METHODS: This investigation enrolled 312 elderly individuals diagnosed with MCI, who were randomly distributed into training and test datasets at a 3:1 ratio. Five machine learning methods, including logistic regression (LR), decision tree (DT), naive Bayes (NB), support vector machine (SVM), and gradient boosting (GB), were used to build a diagnostic prediction model for MCI-SKDS. Accuracy, sensitivity, specificity, precision, F1 score, and area under the curve were used to evaluate model performance. Furthermore, the clinical applicability of the model was evaluated through decision curve analysis (DCA). RESULTS: The accuracy, precision, specificity and F1 score of the DT model performed best in the training set (test set), with scores of 0.904 (0.845), 0.875 (0.795), 0.973 (0.875) and 0.973 (0.875). The sensitivity of the training set (test set) of the SVM model performed best among the five models with a score of 0.865 (0.821). The area under the curve of all five models was greater than 0.9 for the training dataset and greater than 0.8 for the test dataset. The DCA of all models showed good clinical application value. The study identified ten indicators that were significant predictors of MCI-SKDS. CONCLUSION The risk prediction index derived from machine learning for the MCI-SKDS prediction model is simple and practical; the model demonstrates good predictive value and clinical applicability, and the DT model had the best performance. Please cite this article as: Ai YT, Zhou S, Wang M, Zheng TY, Hu H, Wang YC, Li YC, Wang XT, Zhou PJ. Development of a machine learning-based risk prediction model for mild cognitive impairment with spleen-kidney deficiency syndrome in the elderly. J Integr Med. 2025; 23(4): 390-397.
Humans ; Cognitive Dysfunction/diagnosis* ; Aged ; Male ; Female ; Machine Learning ; Spleen ; Aged, 80 and over ; Kidney ; Medicine, Chinese Traditional

AIM To establish a UPLC-MS/MS method for the simultaneous content determination of Asp,Guad,Adeno,Arg,Ade,Cyti,Phe,Leu,Ile,Glu,Ser,Gln,Gly,Ala,Hyp,Thr,Pro and Lys in Asini Corii Colla.METHODS The analysis was performed on a 45℃ thermostatic Waters BEH C18column(2.1 mm×50 mm,1.7 μm),with the mobile phase comprising of acetonitrile(containing 0.1% formic acid)-water flowing at 0.35 mL/min in a gradient elution manner,and electron spray ionization source was adopted in positive ion scanning with multiple reaction monitoring mode.Subsequently,chemical pattern recognition was performed by hierarchical clustering analysis,principal component analysis and orthogonal partial least squares-discriminant analysis.RESULTS Eighteen nucleosides and free amino acids showed good linear relationships within their own ranges(r≥0.999 0),whose average recoveries were 98.0%-104.9% with the RSDs of 1.6%-4.9% .Seventeen batches of samples were clustered into two categories,two principal components demonstrated the accumulative variance contribution rate of 60.75%,Leu,Phe,Ade and Guad were potential index constituents.CONCLUSION This stable and reliable method can be used for the quality control of Asini Corii Colla.

To establish and optimize a method for the detection of recombinant human midkine (rhMK) activity and verify its methodology, cell counting kit-8 (cck-8) method was used to measure the proliferation activity of rat knee chondrocytes. The specificity, accuracy, precision, linearity and robustness of the method were also verified in this study. The established method was proven to have good specificity because the buffer of rhMK and recombinant human interleukin-1 receptor antagonist have no obvious active effect; the recoveries of the samples with relative activities of 50%, 75%, 100%, 125%, 150% were in the range of 80.0% to 124.0% by statistical analysis, the relative standard deviations (RSD) of relative potency were all within 20%, the linear correlation coefficient, R² ≥ 0.98, suggesting that the accuracy, precision and linearity of the method were good; the robustness correlation coefficient, R² ≥ 0.92 and the ratio of maximum to minimum of sigmoidal dose-response were no less than 1.5, indicating that robustness of the methods was good. In conclusion, a bioactivity measurement method for rhMK was established and fully validated in this study and it provides a reliable method for the bioactivity analysis of rhMK routine samples during the development. This study was approved by the Animal Care and Use Committee of Shanghai Model Organisms Center, Inc. (approval number: 2019-0008-06).

Objective To analyze the literature on artificial intelligence in forensic research from 2012 to 2022 in the Web of Science Core Collection Database,to explore research hotspots and developmen-tal trends.Methods A total of 736 articles on artificial intelligence in forensic medicine in the Web of Science Core Collection Database from 2012 to 2022 were visualized and analyzed through the litera-ture measuring tool CiteSpace.The authors,institution,country(region),title,journal,keywords,cited references and other information of relevant literatures were analyzed.Results A total of 736 articles published in 220 journals by 355 authors from 289 institutions in 69 countries(regions)were identi-fied,with the number of articles published showing an increasing trend year by year.Among them,the United States had the highest number of publications and China ranked the second.Academy of Forensic Science had the highest number of publications among the institutions.Forensic Science Inter-national,Journal of Forensic Sciences,International Journal of Legal Medicine ranked high in publica-tion and citation frequency.Through the analysis of keywords,it was found that the research hotspots of artificial intelligence in the forensic field mainly focused on the use of artificial intelligence technol-ogy for sex and age estimation,cause of death analysis,postmortem interval estimation,individual identification and so on.Conclusion It is necessary to pay attention to international and institutional cooperation and to strengthen the cross-disciplinary research.Exploring the combination of advanced ar-tificial intelligence technologies with forensic research will be a hotspot and direction for future re-search.

AIM To investigate the variation rules of main secondary metabolites in Hedysari Radix before and after rubbing strip.METHODS UPLC-MS/MS was adopted in the content determination of formononetin,ononin,calycosin,calycosin-7-glucoside,medicarpin,genistein,luteolin,liquiritigenin,isoliquiritigenin,vanillic acid,ferulic acid,γ-aminobutyric acid,adenosine and betaine,after which cluster analysis,principal component analysis and orthogonal partial least squares discriminant analysis were used for chemical pattern recognition to explore differential components.RESULTS After rubbing strip,formononetin,calycosin,liquiritigenin and γ-aminobutynic acid demonstrated increased contents,along with decreased contents of ononin,calycosin-7-glucoside and vanillic acid.The samples with and without rubbing strip were clustered into two types,calycosin-7-glucoside,formononetin,γ-aminobutynic acid,vanillic acid,calycosin-7-glucoside and formononetin were differential components.CONCLUSION This experiment clarifies the differences of chemical constituents in Hedysari Radix before and after rubbing strip,which can provide a reference for the research on rubbing strip mechanism of other medicinal materials.

Objective To clarify the understanding of types of laboratories and manufacturers for GB 9706.1-2020 Medical electrical equipment-Part 1:General requirements for basic safety and essential performance by laboratory proficiency testing for creepage distance and electrical clearance test.Methods An operation guide was formed according to the testing program in GB 9706.1-2020,and the homogeneity and stability of the samples were evaluated according to CNAS-GL003:2018 Guidance on Evaluating the Homogenneity and Stability of Samples Used for Proficiency Testing.Robust statistic methods were used to assess the quantitative parameters of the test results of the participating laboratories according to the requirements in GB/T 28043-2019 Statistical methods for use in proficiency testing by interlaboratory comparison;the results reported by the expert laboratories were used as the specified values of the qualitative parameters.SPSS 25.0 statistical software was used for data analysis.Results All the results of the crreepage distance and electrical clearance tests met the requirements for homogeneity and stability.Of the 46 laboratories involved in,37 ones did have comprehensive satisfactory determinations while the remained 9 ones not.Conclusion Some laboratories don't behave well in understanding the standard,which have to be reformed accordingly to enhance their proficiencies.[Chinese Medical Equipment Journal,2024,45(10):54-59]

Objective: To construct a prognostic model for unsuccessful removal of nasogastric tube (NGT) was the aim of our study. Methods: This study examined patients with swallowing disorders receiving NGT feeding due to stroke or traumatic brain injury in a regional hospital. Clinical data was collected, such as age, sex, body mass index (BMI), level of activities of daily living (ADLs) dependence. Additionally, gather information regarding the enhancement in Functional Oral Intake Scale (FOIS) levels and the increase in food types according to the International Dysphagia Diet Standardization Initiative (IDDSI) after one month of swallowing training. A stepwise logistic regression analysis model was employed to predict NGT removal failure using these parameters. Results: Out of 203 patients, 53 patients (26.1%) had experienced a failed removal of NGT after six months of follow-up. The strongest predictors for failed removal were age over 60 years, underweight BMI, total dependence in ADLs, and ischemic stroke. The admission prediction model categorized patients into high, moderate, and low-risk groups for removal failure. The failure rate of NGT removal was high not only in the high-risk group but also in the moderate-risk groups when there was no improvement in FOIS levels and IDDSI food types. Conclusion Our predictive model categorizes patients with brain insults into risk groups for swallowing disorders, enabling advanced interventions such as percutaneous endoscopic gastrostomy for high-risk patients struggling with NGT removal, while follow-up assessments using FOIS and IDDSI aid in guiding rehabilitation decisions for those at moderate risk.