Abstract The prevention and control of myopia in Chinese children and adolescents has become a major public health issue. While maintaining increased outdoor activity as a cornerstone intervention, there is an urgent need to explore new complementary approaches that can be effectively implemented in both indoor and outdoor settings. In recent years, environmental spatial frequency has gained increasing attention as one of the key environmental factors influencing the development and progression of myopia. Both animal studies and human research have confirmed that indoor environments lacking mid to high spatial frequency components, often characterized as "visually impoverished", can promote axial elongation and myopia through mechanisms such as disruption of retinal neural signaling, impaired accommodative function, and altered expression of related molecules. Based on the scientific consensus, it is recommended that "enriching of environmental spatial frequency" should be integrated into the myopia prevention and control framework. Following the principles of schoolled organization, family cooperation, community involvement, and student participation, specific measures are put forward in three areas：optimizing school visual settings, improving home spatial environments, and promoting healthy visual behavior. The aim is to create "visually friendly" indoor environments as an important supplement to outdoor activity, thereby providing a novel perspective and strategy for comprehensively advancing myopia prevention and control among children and adolescents.

Abstract The study examines the development and application of microclimate standards for primary and secondary school classrooms, so as to ensure and promote the healthy growth of primary and secondary school students. The paper systematically reviews relevant domestic and international standards, analyzes the problems and shortcomings arising from their practical application and proposes effective countermeasures, in order to provide robust references aimed at optimizing the classroom environment in primary and secondary schools for student health, as well as offering practical support to advance the construction of a healthy China.

Objective: To evaluate the classroom environmental management and CO 2 volume concentration in primary and secondary schools from Liaoning, Tianjin, and Shanghai, thereby providing a scientific basis for developing targeted strategies to improve classroom air quality. Methods: From December 16 to 26, 2024, by using stratified random cluster sampling method, the questionnaire survey was conducted in 72 primary and secondary schools (24 each of primary, junior high, and regular high schools) across Liaoning, Tianjin and Shanghai. Information on heating, ventilation and other classroom environmental management was collected. Additionally, 108 classrooms were selected for on site microclimate measurements, including temperature, humidity, wind speed and CO 2 volume concentration. Univariate analysis and multiple linear regression models were employed to explore related factors of classroom CO 2 volume concentration. Results: Among the three provinces/municipalities, 20.8% of schools regularly monitored the microclimate. The overall compliance rate for classroom CO 2 volume concentration was 17.6%. Multiple linear regression analysis showed that CO 2 volume concentration in regular and junior high school classrooms were higher than in primary school classrooms ( β=0.067, 0.046, 95%CI =0.036-0.099, 0.013-0.080); classrooms ventilated regularly in the morning and afternoon had higher CO 2 volume concentration than those ventilated during every break between classes ( β=0.043, 95%CI = 0.007- 0.080); both temperature ( β=0.010, 95%CI =0.004-0.016) and humidity ( β=0.003, 95%CI =0.002-0.004) were positively correlated with CO 2 volume concentration (all P <0.05). Conclusions Excessive CO 2 volume concentration in primary and secondary school classrooms is a prominent issue, and ventilation frequency is a key intervenable factor for controlling CO 2 levels. It is recommended to promote ventilation during every break between classes as a core management measure and to emphasize air quality supervision in regular high school classrooms.

Intravitreal anti-vascular endothelial growth factor(anti-VEGF)therapy has been widely used, but the variability in its therapeutic efficacy limits individualized treatment. In recent years, the application of artificial intelligence(AI)has opened up new avenues for personalized treatment response prediction, and its core branches include machine learning(ML)and deep learning(DL). This review systematically retrieved and analyzed 41 relevant studies published up to April 2025. Comprehensive analysis reveals that AI predictive models are evolving from forecasting single endpoints(such as visual acuity or central retinal thickness)to integrating multi-dimensional endpoints(encompassing anatomical, functional, and treatment demand parameters)and generating predictive imaging outputs. In terms of technical approaches, DL models(28 studies, accounting for 68.3%)dominate this field due to their robust image interpretation capabilities, while ML models(10 studies, 24.4%)retain significant value in the analysis of structured clinical data. Cross-disease comparisons indicate that research efforts are most concentrated on age-related macular degeneration(ARMD)and diabetic macular edema(DME), with shared conceptual frameworks for model construction, yet distinct anatomical and functional indicators are prioritized for each disease. Currently, the field confronts several key challenges, including insufficient prospective clinical validation, limited model interpretability(the “black box problem”), and a scarcity of high-quality multi-center datasets. Moving forward, it is imperative to advance real-world validation and develop explainable AI techniques to expedite the clinical translation of these predictive models.

Objective: To investigate the distribution characteristics and related factors of weight loss behavior among middle school students in Shanghai, so as to provide a reference for guiding scientific weight loss among middle school students. Methods: From May to June 2021, a stratified cluster random sampling method was used to select 16 758 junior and high school students in 16 districts of Shanghai. Youth Risk Behavior Surveillance System was administered to assess the basic condition and weight loss behaviors of the students. An unordered multinomial Logistic regression model was employed to analyze the factors associated with weight loss behaviors. Results: A total of 5 881 (35.09%) reported engaging in exercise for weight loss, 6 344 (37.86%) reported dieting for weight loss, and 461 (2.75%) engaged in unhealthy weight loss behaviors. The unordered multinomial Logistic regression analysis indicated that compared with the no weight loss behavior group, students from urban areas( OR =1.35,95% CI =1.10-1.66), those with Internet addiction ( OR =1.71,95% CI =1.23-2.38), those with victims of bullying ( OR =2.09, 95% CI =1.68-2.61), those experiencing insomnia ( OR =2.33,95% CI = 1.74-3.11), those feelings of sadness or despair ( OR =3.10, 95% CI =2.42- 3.97 ), and those who perceived their body weight as slightly heavy ( OR =2.77, 95% CI = 2.17-3.55) or very heavy ( OR =3.41, 95% CI =2.44-4.75) were more likely to engage in unhealthy weight loss behaviors ( P <0.05). Conclusions There are significant differences in weight loss behaviors among middle school students with varying characteristics in Shanghai. Negative emotions such as insomnia and feelings of sadness or despair, Internet addiction, cognitive bias in weight and experiences of bullying are identified as related factors for unhealthy weight loss behaviors. Targeted intervention measures should be implemented to guide students towards scientific approaches to weight management.

Abstract In order to understand and analyze the current standards and application of school desks and chairs for primary and secondary schools, and to promote the healthy growth of primary and secondary school students. The article conducts a comprehensive review of the functional and dimensional standards for school furniture both domestically and internationally, and objectively analyzes the current utilization and existing issues concerning desks and chairs in schools. It further explores the multifaceted factors that influence the allocation of desks and chairs, and proposes effective countermeasures, so as to provide a reference for the risk factors of common diseases related to desks and chairs, such as myopia and abnormal spinal curvature.

Objective: To understand the subjective and objective comfort evaluations of students from different age groups on desks and chairs, so as to provide reference for standardized allocation and use of desks and chairs. Methods: From January to April 2024, a total of 2 446 students were selected from 26 schools in 13 districts (counties/cities) in Shanghai, Tianjin, and Wuxi from Jiangsu Province by using cluster random method, including students in kindergartens, primary schools, junior high schools,senior high schools, colleges and universities. Standardized procedures were used to measure the height and weight of participants, and the matching desks and chairs models were selected according to the height. The subjective comfort of students on matching desks and chairs was investigated, and their objective comfort was evaluated by using a self designed questionnaire. The χ 2 test was used to analyze the differences of subjective perception and objective evaluation in comfort between different types of desks and chairs. Results: About 84.1% of the students subjectively thought that large desks and small chairs were very comfortable or relatively comfortable, followed by large desks and chairs (75.7%), and the proportion of small desks and chairs was the lowest among the three types (46.2%), and the difference was statistically significant ( χ 2=722.46, P <0.01). The reporting rates of primary school, junior high school and senior high school students who subjectively considered large desks and chairs to be very comfortable/relatively comfortable were higher than that of other types of desks and chairs, and the differences were statistically significant ( χ 2=297.49, 252.82, 343.67, P <0.01). However, there was no significant difference in the subjective comfort evaluation of different types of desks and chairs among kindergarten children ( χ 2=3.21, P >0.05), and 66.3% of the students in colleges and universities felt very comfortable/relatively comfortable when they used the matching standard desks and chairs. The objective evaluation results of the comfort for the three types of desks and chairs were consistent with the subjective evaluation, but the proportions of the objective evaluation as very comfortable/relatively comfortable were higher than that of the subjective evaluation ( χ 2=20.76- 813.47, P <0.01). Conclusions Large desks and chairs, as well as large desks with small chairs are perceived comfortable, while small desks and chairs are perceived less comfortable. It is recommended to match the large desks and chairs or large desks and small chairs that are suitable for them according to the "standard", to promote physical and mental health of students.

Objective: To investigate the differences in the comfort of desks and chairs furniture among students with different body types according to the standard, so as to provide a reference for guiding students with overweight and obesity to choose the correct study furniture and revising the standards. Methods: From January to April 2024, 2 443 students from 26 schools in 13 districts (counties/cities) in Shanghai, Tianjin, and Jiangsu Province were selected by the cluster random sampling method to conduct physical examination. The subjective and objective evaluations of the comfort of height matched desks and chairs were investigated. The students were divided into non overweight, overweight, and obesity groups according to relevant criteria, and stratified analysis was performed. The χ 2 test was used to analyze differences in the comfort evaluations of desks and chairs among students with different body types. Results: Among the 2 443 students surveyed, 16.7% and 12.6% were respectively classified as overweight and obese. All students assigned the highest comfort ratings to large desks and small chairs (84.1%), and consistency was observed between students subjective and objective evaluations. The reporting rate of samll desks and chairs of obesity students subjective evaluation was lower (36.8%) than that of overweight and non overweight/obesity students (52.1%, 48.0%) ( χ 2=14.63, P <0.01). The overweight and obese group of primary school students had a worse evaluation of the comfort of large desks and chairs and small desks and chairs than those of the non overweight and obese groups( χ 2=15.78, 7.63, P <0.05). Among high school students, the overweight and obese group had worse evaluation of the comfort of large desks and chairs, as well as large desks and small chairs, than those of the non-overweight and obese groups( χ 2=9.62, 11.77, P <0.05). The objective evaluations revealed low compliance ratings on the posture of the thighs and calves for naturally forming an angle greater than 90° (55.6%), and headroom height under the table (50.3%) with small desks and chairs ( χ 2=94.05, 166.47, P <0.05). Conclusions Compared with non overweight/obese students, students with overweight and obese students report poor comfort evaluations of height matched desks and chairs. Revision of the standard should consider the body types of students, and evaluations of the comfort of desks and chairs furniture by students with overweight and obesity should be improved.

Objective: To analyze the temporal variation patterns of sickness absenteeism among primary and secondary school students in Shanghai, so as to explore models suitable for predicting peaks and intensity of absenteeism rates. Methods: The seasonal and trend decomposition using loess (STL) method was used to analyze the seasonal and long term trend changes in sickness absenteeism among primary and secondary school students from September 1 in 2010 to June 30 in 2018, in Shanghai. A hierarchical clustering method based on Dynamic Time Warping (DTW) was employed to classify absenteeism symptoms with similar temporal patterns. Based on historical data, the study constructed and evaluated different time series algorithms and machine learning models to optimize the accuracy of predicting the trend of sickness absenteeism. Results: During the research period, the average new absenteeism rate due to illness was 16.86 per 10 000 person day for every academic year, and the trend of sickness absenteeism exhibited both seasonality and a long term upward trend, reaching its highest point in the 2017 academic year (22.47 per 10 000 person day). The symptoms of absenteeism were divided into three categories: high incidence in winter and spring (respiratory symptoms, fever and general discomfort, etc.), high incidence in summer (eye symptoms, nosebleeds, etc.) and those without obvious seasonality (skin symptoms, accidental injuries, etc.).The constructed time series models effectively predicted the trend of absenteeism due to illness, although the accuracy of predicting peak intensity was relatively low. Among them, the multi layer perceptron (MLP) model performed the best, with an root mean squared error (RMSE) of 8.96 and an mean absolute error (MAE) of 4.37, reducing 36.51% and 39.02% compared to the baseline model. Conclusion Time series models and machine learning algorithms could effectively predict the trend of sickness absenteeism, and corresponding prevention and control measures can be taken for absenteeism caused by different symptoms during peak periods.

ObjectiveTo investigate the value of noninvasive imaging detection （FibroScan）， two serological models of gamma-glutamyl transpeptidase-to-platelet ratio （GPR） score and S index， and two inflammatory factors of interleukin-6 （IL-6） and tumor necrosis factor-α （TNF-α） in predicting liver fibrosis in patients with HBeAg-positive chronic hepatitis B （CHB）， as well as the consistency of liver biopsy in pathological staging， and to provide early warning for early intervention of CHB. MethodsA retrospective analysis was performed for 131 HBeAg-positive CHB patients who underwent liver biopsy in The Third People’s Hospital of Kunming from January 2019 to December 2023. The results of liver biopsy were collected from all patients， and related examinations were performed before liver biopsy， including total bilirubin， alanine aminotransferase， platelet count， gamma-glutamyl transpeptidase， albumin， IL-6， TNF-α， liver stiffness measurement （LSM）， and abdominal ultrasound. An analysis of variance was used for comparison of normally distributed continuous data between groups， and the Kruskal-Wallis H test was used for comparison of non-normally distributed continuous data between groups； the chi-square test was used for comparison of categorical data between groups. A Kappa analysis was used to investigate the consistency between LSM noninvasive histological staging and pathological staging based on liver biopsy， and the Spearman analysis was used to investigate the correlation between each variable and FibroScan in the diagnosis of liver fibrosis stage. The Logistic regression analysis was used to construct joint predictive factors. The receiver operating characteristic （ROC） curve was used to evaluate the value of each indicator alone and the joint predictive model in the diagnosis of liver fibrosis， and the Delong test was used for comparison of the area under the ROC curve （AUC）. ResultsIn the consistency check， inflammation degree based on liver biopsy had a Kappa value of 0.807 （P<0.001）， and liver fibrosis degree based on liver biopsy had a Kappa value of 0.827 （P<0.001）， suggesting that FibroScan noninvasive histological staging and liver biopsy showed good consistency in assessing inflammation degree and liver fibrosis stage. Age was positively correlated with LSM， GPR score， S index， IL-6， and TNF-α （all P<0.05）， and GPR score， S index， IL-6， and TNF-α were positively correlated with LSM （all P<0.05）. GPR score， S index， IL-6， and TNF-α were all independent risk factors for diagnosing significant liver fibrosis （≥S2） and progressive liver fibrosis （≥S3） （all P<0.05）. As for each indicator alone， GPR score had the highest value in the diagnosis of significant liver fibrosis （≥S2）， followed by S index， IL-6， and TNF-α， while S index had the highest value in the diagnosis of progressive liver fibrosis （≥S3）， followed by GPR score， TNF-α， and IL-6. The joint model had a higher predictive value than each indicator alone （all P<0.05）. ConclusionThere is a good consistency between FibroScan noninvasive histological staging and pathological staging based on liver biopsy. GPR score， S index， IL-6， and TNF-α are independent risk factors for evaluating different degree of liver fibrosis in CHB， and the combined prediction model established by them can better diagnose liver fibrosis.