Objective: To study the correlation between short sleep duration and screening myopia among primary and middle school students in Beijing, so as to provide a scientific basis for the comprehensive prevention and control of myopia among students. Methods: Using a stratified cluster random sampling, 25 593 primary and middle school students from 16 districts of Beijing were selected from September to November 2023. The National Common Diseases and Health Influencing Factors Monitoring Survey Questionnaire was used to conduct a questionnaire survey, and visual acuity was tested according to the Specification for the Screening of Refractive Error in Primary and Middle School Students. The reporting rates of short sleep duration and detection rates of screening myopia among primary and middle school students were compared using the Chi square test. Binary Logistic regression was used to analyze the correlation between short sleep duration and screening myopia. Results: About 68.63% of students reported short sleep duration. There was a statistically significant difference in the reporting rate of short sleep duration among students in different school stages ( χ 2=981.18, P <0.01), with the lowest reporting rate of vocational high school students (47.07%) and the highest reporting rate of ordinary high school students (76.17%). The detection rates of screening myopia among primary school students ( 57.09% ) and middle school students (76.53%) who reported short sleep duration were higher than those who reported enough sleep duration (52.65%, 71.94%), with satistically significant differences ( χ 2=14.83, 17.96, P <0.01). The results of binary Logistic regression analysis showed that primary and middle school students with short sleep duration had a higher risk of developing screening myopia, compared to students with enough sleep duration ( OR =1.25); after adjusting for confounding factors such as educational stage, gender, region, boarding situation, primary and secondary school students with short sleep duration still had a higher risk of screening myopia ( OR =1.26) ( P <0.01). The analysis results stratified by educational stage showed that primary school students from grades 4-6 and middle school students with short sleep duration had a higher risk of screening myopia ( OR=1.18, 1.20, P <0.01). Conclusions Primary and secondary school students in Beijing with short sleep duration sleep have a higher risk of developing screening myopia. Families, schools, and society should ensure enough sleep duration to reduce the occurrence of myopia among students.

Objective: To analyze the incidence of statutory and keymonitored infectious diseases among school students in Beijing from 2016 to 2020, so as to provide a reference for developing the prevention and control of infectious diseases in schools. Methods: A descriptive statistical analysis was conducted on student cases aged 6-22 years in Beijing from 2016 to 2020 selected from the China Disease Surveillance Information Reporting Management System. Rate comparisons were performed using the 2 test and trend 2 test. Results: From 2016 to 2020, the overall incidence of statutory and keymonitored infectious diseases among students in Beijing showed an upward trend (χ2trend=582.42), the incidence rates of Category B and other infectious diseases exhibited a downward trend (χ2trend=82.71, 18.34), while Category C infectious diseases demonstrated a significant upward trend (χ2trend=911.75) (P<0.01). Among Category B infectious diseases, scarlet fever, bacillary dysentery, tuberculosis, and HIV/AIDS were predominant, with annual average incidence rates of 61.33/100 000, 35.38/100 000, 13.88/100 000, and 3.78/100 000, respectively. Except for HIV/AIDS, the reported incidence rates of other infectious diseases showed a declining trend. Among Category C infectious diseases, influenza, other infectious diarrhea, hand-foot-mouth disease, and mumps were predominant, with annual average incidence rates of 956.13/100 000, 114.39/100 000, 111.37/100 000, and 28.24/100 000, respectively. Influenza showed a significant upward trend (χ2trend=1 508.30), while the other infectious diarrhea, hand-foot-mouth disease, and mumps exhibited a downward trend (χ2trend=13.84, 25.78, 6.13) (P<0.05). Among other infectious diseases, varicella was predominant (χ2trend=17.47, P<0.05). Scarlet fever, influenza, hand-foot-mouth disease, and mumps had higher incidence rates among primary and middle school students; other infectious diarrhea and varicella were more prevalent among high school students; tuberculosis and bacillary dysentery were more common among high school and college students; and HIV/AIDS had higher incidence rates among college and high school students. Conclusion From 2016 to 2020, the incidence of Category B infectious diseases among students in Beijing showed a declining trend, while influenza, a Category C infectious disease, exhibited a significant upward trend.

Idiopathic pulmonary fibrosis (IPF), a chronic interstitial lung disease, is characterized by aberrant wound healing, excessive scarring and the formation of myofibroblastic foci. Although the role of alternative splicing (AS) in the pathogenesis of organ fibrosis has garnered increasing attention, its specific contribution to pulmonary fibrosis remains incompletely understood. In this study, we identified an up-regulation of serine/arginine-rich splicing factor 7 (SRSF7) in lung fibroblasts derived from IPF patients and a bleomycin (BLM)-induced mouse model, and further characterized its functional role in both human fetal lung fibroblasts and mice. We demonstrated that enhanced expression of Srsf7 in mice spontaneously induced alveolar collagen accumulation. Mechanistically, we investigated alternative splicing events and revealed that SRSF7 modulates the alternative splicing of pyruvate kinase (PKM), leading to metabolic dysregulation and fibroblast activation. In vivo studies showed that fibroblast-specific knockout of Srsf7 in conditional knockout mice conferred resistance to bleomycin-induced pulmonary fibrosis. Importantly, through drug screening, we identified lomitapide as a novel modulator of SRSF7, which effectively mitigated experimental pulmonary fibrosis. Collectively, our findings elucidate a molecular pathway by which SRSF7 drives fibroblast metabolic dysregulation and propose a potential therapeutic strategy for pulmonary fibrosis.

Objective To develop and validate a scoring system to predict the possibility of laparoscopic cholecystectomy (LC) conversion to laparotomy based on preoperative clinical data, and to establish a grading management model of surgery. Methods A retrospective analysis was conducted on the clinical data of 9 414 patients who underwent LC at Renhe Hospital and Huashan Hospital from June 2013 to June 2018. The patients were divided into two groups: the LC group (9 246 patients who successfully underwent LC) and the conversion to laparotomy group (168 patients who required conversion to open surgery). The data of two groups were compared, and the risk factors affecting conversion to laparotomy were screened out by single factor analysis of Chi-square test. Then, the risk factors were analyzed by multiple Logistic regression, and the pre-coefficient of each variable of the risk factors was assigned according to the established conversion to laparotomy possibility function. After calculating the score of each case, the difference in the actual conversion rate of each group was compared. The area under receiver operating characteristic (ROC) curve was calculated to evaluate the performance of the scoring system. According to the scoring system, LC surgical grading management model was created and verified. Results The following factors were identified as significant risk factors for conversion to laparotomy (P < 0.001): body temperature ≥ 38.5℃, frequency of acute cholecystitis ≥3 times, maximum thickness of gallbladder wall ≥ 5 mm, gallbladder neck stone incarceration, diameter of common bile duct ≥8 mm, and surgical experience ≤50 cases were the risk factors for conversion to laparotomy (P < 0.001). A score >3 points was associated with a high risk of conversion to laparotomy. Conclusions The LC scoring system and surgical grading management are reliable and effective tools for predicting and reducing the conversion rate of LC to laparotomy.

Objective: To explore the intervention effects of high intensity interval training (HIIT) on glucose metabolism, cortisol (Cor), and sleep quality among college students with comorbid depressive symptoms and obesity, so as to provide a reference for improving sleep quality among college students with comorbid depressive symptoms and obesity. Methods: In March 2023, 45 college students with comorbid depressive symptoms and obesity were recruited and randomly assigned to an exercise group ( n =23) and a control group ( n =22) by random number table method. The exercise group received HIIT intervention for 12 weeks, three times a week, while the control group received no intervention. Blood samples were collected from participants to measure fasting insulin (FINS), fasting blood glucose (FBG), homeostatic model assessment of insulin resistance (HOMA-IR), Cor, and Pittsburgh Sleep Quality Index (PSQI) before and after intervention. Statistical analysis was performed using t-test, repeated measures analysis of variance (ANOVA), simple effect analysis. Results: The repeated measures ANOVA revealed statistically significant time×group interaction effects for body composition (weight, body mass index, percentage of body fat, fat mass, waist to hip ratio), depressive symptoms, PSQI scores and its subdimensions (subjective sleep quality, sleep onset time, sleep efficiency, sleep disorders, daytime dysfunction), as well as FBG, FINS, and HOMA-IR between the exercise group and control group before and after intervention ( F =7.10-53.38, all P <0.05). Simple effect analysis showed that compared to the control group, the exercise group demonstrated significant improvements in body composition (body mass index, fat mass, waist to hip ratio), depressive symptoms, PSQI scores and its sub dimensions (subjective sleep quality, sleep onset time, sleep efficiency, sleep disorders, daytime dysfunction), FBG, FINS, HOMA-IR, and Cor (all P <0.05). Conclusion HIIT can improve the sleep quality of college students with comorbid depressive symptoms and obesity by enhancing glucose metabolism and regulating Cor levels.

Objective To investigate the effects of transcranial direct current stimulation(tDCS)on the topologic attributes of brain functional network in the patients with mild cognitive impairment(MCI).Meth-ods Thirty-three included patients with MCI were randomly divided into the real stimulation group(18 ca-ses)and pseudo-stimulation group(15 cases).All patients received the tDCS treatment for consecutive 10 d.The left dorsolateral prefrontal cortex(DLPFC)was stimulated by the anode,while the right orbital socket DLPFC was stimulated by the cathode.The neuropsychological scale assessment and resting state functional magnetic resonance imaging(rs-fMRI)image collection were performed before and after treatment.The GRETNA software was used to preprocess the rs-fMRI images and analyze the graph theory.The Pearson correlation analysis was used to calculate the correlation between behavioral indicators and network attribute indicators of significant difference between the two groups.Results There were statistically significant differ-ences in the node attributes(intermediate number centrality,degree centrality and local efficiency of nodes)before and after treatment,and between the two groups after treatment(P＜0.05).Compared with before treatment,the scores of MMSE,MoCA,AVLT-N7 and BNT after treatment in the real stimulation group were significantly increased[(25.89±2.16)points,(21.16±2.77)points,(4.95±1.81)points,(19.47±3.13)points].Conclusion tDCS could effectively regulate the local topological attributes of nodes in the cognitive-related brain region of MCI and improve the cognitive function.

Objective To establish a diagnostic model for scleroderma by combining machine learning and artificial neural network based on mitochondria-related genes.Methods The GSE95065 and GSE59785 datasets of scleroderma from GEO database were used for analyzing expressions of mitochondria-related genes,and the differential genes were identified by Random forest,LASSO regression and SVM algorithms.Based on these differential genes,an artificial neural network model was constructed,and its diagnostic accuracy was evaluated by 10-fold crossover verification and ROC curve analysis using the verification dataset GSE76807.The mRNA expressions of the key genes were verified by RT-qPCR in a mouse model of scleroderma.The CIBERSORT algorithm was used to estimate the bioinformatic association between scleroderma and the screened biomarkers.Results A total of 24 differential genes were obtained,including 11 up-regulated and 13 down-regulated genes.Seven most relevant mitochondria-related genes(POLB,GSR,KRAS,NT5DC2,NOX4,IGF1,and TGM2)were screened using 3 machine learning algorithms,and the artificial neural network diagnostic model was constructed.The model showed an area under the ROC curves of 0.984 for scleroderma diagnosis(0.740 for the verification dataset and 0.980 for cross-over validation).RT-qPCR detected significant up-regulation of POLB,GSR,KRAS,NOX4,IGF1 and TGM2 mRNAs and significant down-regulation of NT5DC2 in the mouse models of scleroderma.Immune cell infiltration analysis showed that the differential genes in scleroderma were associated with follicular helper T cells,immature B cells,resting dendritic cells,memory activated CD4+T cells,M0 macrophages,monocytes,resting memory CD4+T cells and mast cell activation.Conclusion The artificial neural network diagnostic model for scleroderma established in this study provides a new perspective for exploring the pathogenesis of scleroderma.

Objective To establish a diagnostic model for scleroderma by combining machine learning and artificial neural network based on mitochondria-related genes.Methods The GSE95065 and GSE59785 datasets of scleroderma from GEO database were used for analyzing expressions of mitochondria-related genes,and the differential genes were identified by Random forest,LASSO regression and SVM algorithms.Based on these differential genes,an artificial neural network model was constructed,and its diagnostic accuracy was evaluated by 10-fold crossover verification and ROC curve analysis using the verification dataset GSE76807.The mRNA expressions of the key genes were verified by RT-qPCR in a mouse model of scleroderma.The CIBERSORT algorithm was used to estimate the bioinformatic association between scleroderma and the screened biomarkers.Results A total of 24 differential genes were obtained,including 11 up-regulated and 13 down-regulated genes.Seven most relevant mitochondria-related genes(POLB,GSR,KRAS,NT5DC2,NOX4,IGF1,and TGM2)were screened using 3 machine learning algorithms,and the artificial neural network diagnostic model was constructed.The model showed an area under the ROC curves of 0.984 for scleroderma diagnosis(0.740 for the verification dataset and 0.980 for cross-over validation).RT-qPCR detected significant up-regulation of POLB,GSR,KRAS,NOX4,IGF1 and TGM2 mRNAs and significant down-regulation of NT5DC2 in the mouse models of scleroderma.Immune cell infiltration analysis showed that the differential genes in scleroderma were associated with follicular helper T cells,immature B cells,resting dendritic cells,memory activated CD4+T cells,M0 macrophages,monocytes,resting memory CD4+T cells and mast cell activation.Conclusion The artificial neural network diagnostic model for scleroderma established in this study provides a new perspective for exploring the pathogenesis of scleroderma.

Objective: To analyze high myopia and dioptre changes in middle school students in Beijing from 2019 to 2022, so as to provide a basis for formulating preventive and control measures. Methods: Using stratified cluster random sampling, 16 districts of Beijing were divided into four groups, each of which was respectively composed of 83, 83, 84, and 84 middle schools, in order to examine non cycloplegic auto refraction among the senior grades 1 to 3 students from September to October in each year (from 2019 to 2022). Finally, the dataset results of each of the four groups (21 589, 21 161, 21 561, 21 123) were compared by the Chi square test and trend Chi square test. Trend changes were evaluated by annual percentage change (APC). Results: The rates of high myopia were higher in female students than in males from 2019 to 2022 (15.60%,14.59%; 15.33%, 14.44%; 14.65 %, 14.17%; 14.63%,13.84%), and the difference in 2019 was statistically significant ( χ 2=4.93, P <0.05). The rates of high myopia in middle school students in urban areas were significantly higher than those in rural areas(16.45%, 13.78%; 16.81 %, 13.00%; 15.84%, 13.06%; 15.85%, 12.72%), and the differences were statistically significant ( χ 2=30.18, 60.43, 33.92 , 42.23, P <0.05). With the increase of grade, the rates of high myopia increased ( χ 2 trend =674.56, 608.38, 655.21, 676.89, P <0.05), with junior grade 3 students being the most robust. The rate of high myopia in middle school students from 2019 to 2022 decreased from 15.09 to 14.22%, with an average annual rate of 2.08% ( APC=-2.08, t=-7.99, P ＜0.05). The refractive error of high myopia middle school students in 2019 and 2022 were -7.44(-10.25, -6.00) and -7.38(-10.00, -6.00)D, respectively, with no statistically significant difference ( H=4.30, P >0.05). Conclusions The rate of high myopia in middle school students in Beijing shows a decreasing trend, but it remains at a high level. It is necessary to classify the prevention and control strategy, and standardize the measures in order to manage early onset, high incidence rates, and severe myopia.