AIM: To investigate variation patterns of corneal biomechanical parameters and binocular symmetry among children of different genders aged 8-16 years.METHODS:A retrospective study was conducted, and children who underwent optometric examinations at the ophthalmology department of our hospital were enrolled between January 2022 and December 2024. Measurements included the flat keratometry(K1), steep keratometry(K2), and mean curvature(Km)of the anterior corneal surface, horizontal visible iris diameter(HVID), central corneal thickness(CCT), corneal endothelial cell density(CECD), average cell size(ACS), coefficient of variation(CV), and hexagonality(HEX). Corneal parameters and binocular differences were compared between genders and across age groups.RESULTS:A total of 621 children(1 242 eyes)were enrolled in this study, including 284 males(568 eyes), 337 females(674 eyes), 528 children aged 8-12 years(1 056 eyes), and 93 children aged 13-16 years(186 eyes). In children aged 8-16 years, the K1, K2, Km and CV of both eyes, as well as the interocular CCT differences in boys were significantly lower than those in girls(all P<0.05), while the HVID and HEX of both eyes, as well as the CCT of the left eye in boys were significantly higher than those in girls(all P<0.05). Children aged 8-12 years had significantly higher K1, Km, CECD and HEX in both eyes, and significantly lower ACS in both eyes than those aged 13-16 years(all P<0.05). K1, K2, Km, CECD and HEX in both eyes were negatively correlated with age(P<0.05); ACS in both eyes was positively correlated with age(P<0.001); K1 and Km of the right eye were positively correlated with the CECD of the right eye(P<0.05), and K1 and CCT of the left eye were positively correlated with the CECD of the left eye(P<0.05).CONCLUSION:Significant gender differences exist in corneal parameters among children aged 8 to 16 years, while binocular symmetry remained stable.

Background Lead is a typical persistent environmental pollutant that can accumulate in bones for decades. During pregnancy, alterations in calcium metabolism promote the mobilization of bone lead, resulting in secondary exposure; however, the mechanisms by which pregnancy-associated bone lead mobilization affects maternal renal function remain unclear. Objective To investigate the role of mitochondrial dysfunction in pregnancy-related bone lead mobilization-induced renal injury. Methods Newly weaned female Wistar rats were randomly assigned to a control or a lead-exposed group administered either 0.05% sodium acetate or 0.05% lead acetate in drinking water. Following a 4-week lead exposure and a 4-week washout period, the females were co-housed with healthy age-matched males for mating. Rats were sacrificed at early (gestational day 3) and late (gestational day 17) pregnancystages, respectively. Renal histopathology was assessed using hematoxylin and eosin staining staining. Mitochondria-related indicators, including oxidative stress, inflammatory responses, and energy metabolism, were measured. Differential metabolites were identified using serum metabolomics. Results Renal injury in the lead-exposed pregnant rats progressed in a time-dependent manner, characterized by degeneration of proximal tubular epithelial cells, glomerular hyaline changes, and interstitial inflammatory cell infiltration. Repeated measures ANOVA indicated a significant interaction between the treatment factor (lead exposure) and the temporal factor (gestational stage) on renal injury (P<0.001). Further analysis of mitochondrial function-related indicators in late-pregnancy renal tissue revealed that the lead exposure group exhibited significantly increased levels of malondialdehyde (MDA) and reactive oxygen species (ROS) (P<0.05), accompanied by a reduction in superoxide dismutase (SOD) and reduced glutathione (GSH) activities (P<0.05); regarding inflammatory markers, levels of interleukin-18 (IL-18) and interleukin-1β (IL-1β) were elevated (P<0.01), whereas interleukin-33 (IL-33) was decreased in the lead-exposed group (P<0.05); energy metabolism-related indicators, including adenosine triphosphate (ATP) level, Na⁺-K⁺-ATPase and Ca²⁺-Mg²⁺-ATPase activities, and mitochondrial respiratory chain complexes I, III, and V activities, were significantly reduced (P<0.05) in the lead-exposed gorup. The typical differential metabolite N-methylisoleucine, identified through serum metabolomics analysis, was negatively correlated with blood lead levels, kidney injury scores, and IL-1β, while positively correlated with catalase (CAT) activity and Ca²⁺-Mg²⁺-ATPase. Conclusions Mitochondrial dysfunction may play a critical role in renal injury induced by bone lead mobilization during late gestation.

Background Long working hours, as a common risk factor for occupational stress, is closely related to the occurrence of depressive symptoms. Understanding how long working hours affect occupational stress and depressive symptoms will inform occupational health interventions. Objective To quantify the impact of long working hours exposure on occupational stress and depressive symptoms among Internet industry employees, translate black-box outputs into actionable insights, and demonstrate the value of interpretable machine learning for early-warning occupational-health surveillance. Methods A dataset was derived from a cross-sectional survey involving 2866 internet industry employees in China. This survey was part of the project Risk Assessment Of Long Working Hour Exposure And Its Adverse Health Effects, conducted by the National Institute for Occupational Health and Poisoning Control, Chinese Center for Disease Control and Prevention, from 2021 to 2023. Working hours, occupational stress and depressive symptoms were quantified with a set of structured questionnaires including the Core Occupational Stress Scale and the Patient Health Questionnaire. Pairwise associations were screened by Mantel tests and variance-inflation factors. Key predictors identified through feature selection were fed into six machine-learning risk-prediction models. Visual interpretation was provided by feature importance, Shapley additive explanations (SHAP) and local interpretable model-agnostic explanations (LIME), while directed causal effects and intervention impacts of prolonged working hours exposure on occupational stress and depressive symptoms were dissected with causal explanation of features techniques. Results The positive rates of occupational stress and depressive symptoms among internet employees were 12.9% and 77.8% respectively. Twelve core features for occupational stress and nine for depressive symptoms were retained after selection. After these features were supplied to six predictive algorithms and evaluated on five metrics, the Light Gradient Boosting Machine (LGBM) achieved the highest accuracy—0.89 for occupational stress and 0.79 for depressive symptoms on the hold-out test set. The feature-importance rankings converged on fatigue accumulation and life satisfaction as dominant drivers for both outcomes, whereas weekly working hours and daily overtime emerged as the principal exposure-related predictors. The SHAP summary plots revealed that longer weekly hours and daily overtime systematically elevated the probability of occupational stress. The causal feature explanation further quantified that ascending one category in weekly working hours increased the probability of occupational stress by 7.04%. Conclusion Exposure to long working hours is associated with both occupational stress and depressive symptoms among internet industry employees. Interpretable machine-learning frameworks translate these associations into transparent, defensible drivers, enabling precise identification of the pivotal factors and their interplay. This evidence base equips occupational-health practitioners with actionable insights for designing targeted prevention and intervention strategies.

Objective: To evaluate the effect of exercise prescription intervention among patients with type 2 diabetes mellitus (T2DM), so as to provide the evidence for guiding appropriate physical activity and glycemic control in this population. Methods: In July 2023, T2DM patients managed by two community health service centers in Qingjiangpu District, Huai'an City, Jiangsu Province, were selected as the study participants and randomly assigned divided into a control group and an intervention group. The control group received routine chronic disease management under the basic public health services, while the intervention group, in addition to receiving the same routine chronic disease management, was provided with exercise prescription to guide their physical activity at baseline (T0), after 3 months of intervention (T1), and after 6 months of intervention (T2). Data on weight-related indicators, glycated hemoglobin (HbA1c), and blood lipid were collected through physical examinations and laboratory tests at T0 and after 12 months of intervention (T3). The differences in indicators between the two groups before and after the intervention were analyzed using generalized estimating equations. Results: The intervention group consisted of 197 patients, including 99 males, accounting for 50.25%. The median disease duration was 7.10 (interquartile range, 7.80) years, and 113 patients had suboptimal HbA1c levels, accounting for 57.36%. The control group included 196 patients, including 99 females, accounting for 50.51%. The median disease duration was 6.10 (interquartile range, 7.00) years, and 100 patients had suboptimal HbA1c levels, accounting for 51.02%. Before the intervention, no statistically significant differences were observed between the two groups in gender, educational level, disease duration, pharmacological treatment, smoking, alcohol consumption, and HbA1c levels (all P>0.05). In the intervention group, the proportion of participants engaging in aerobic exercise and strength training increased from 78.17% and 8.12% at T0 to 85.79% and 16.24% at T3, respectively (both P<0.05). The results of the generalized estimating equations revealed significant interactions between group and time for waist-to-hip ratio, total cholesterol (TC), and low-density lipoprotein cholesterol (LDL-C) following the intervention (all P<0.05). A statistically significant difference in waist-to-hip ratio was found between the two groups (P<0.05), with a greater reduction observed in the intervention group compared to the control group. Significant differences in TC and LDL-C levels were noted across different intervention time points (both P<0.05). Specifically, the intervention group demonstrated reductions of 0.35 mmol/L in TC and 0.42 mmol/L in LDL-C from baseline to follow-up (both P<0.05). Conclusion The 12-month exercise prescription intervention can effectively enhance exercise participation and reduce waist-to-hip ratio, TC, and LDL-C levels among patients with T2DM.

Background Occupational stress has emerged as a critical public health concern affecting the physical and mental well-being of workers in the manufacturing sector. However, researchers typically evaluate its core driver—cumulative fatigue—using a crude binary “present/absent” variable, thereby overlooking the high-dimensional complexity and heterogeneity inherent in fatigue characteristics. This oversimplification constrains both the precision and predictive performance of occupational stress risk assessment model. Objective Leveraging a data-driven approach, to survey data on cumulative fatigue among manufacturing employees, and then use this new classification to develop and validate an occupational stress prediction model, with an ultimate aim of enhancing the accuracy and effectiveness of occupational stress assessment. Methods A set of cross-sectional survey data on 3871 manufacturing employees in 2021 were derived from the “Long working hours exposure and its adverse health effect risk assessment” program of the National Institute for Occupational Health and Poison Control, Chinese Center for Disease Control and Prevention. Occupational stress was assessed using the Core Occupational Stress Measurement Scale, while cumulative fatigue was evaluated via the Worker’s Self-Diagnostic Questionnaire for Fatigue Accumulation. Boruta method was applied to screen core variables from 20 occupational stress influencing factors. Dimensionality reduction of cumulative fatigue features was performed using a Bayesian sparse autoencoder (BASE), followed by comparison and application of clustering methods to achieve multi-class classification of the reduced features. Six machine learning classification models were then selected including logistic regression, support vector machine, decision tree, random forest, adaptive boosting, and lightweight gradient boosting machine (LightGBM) to construct and compare two occupational stress prediction models involving cumulative fatigue combined with ten other core variables: one utilizing the original binary cumulative fatigue label as a core variable, and another employing the novel fatigue classification proposed herein as a core variable. Results The positive rate of occupational stress among the manufacturing employees was 38.9%. The Boruta method identified 11 core variables of occupational stress: depressive symptoms, cumulative fatigue, age, length of service, tenure in current position, average weekly working hours, average daily overtime hours, average monthly income, low levels of exercise, life satisfaction, and sleep quality. The BSAE reduced the original cumulative fatigue factors to 12 dimensions, while the K-means clustering grouped the reduced fatigue features into three categories: no fatigue, moderate fatigue, and sever fatigue. Six occupational stress prediction models were constructed using the three-category labels of cumulative fatigue and ten additional factors. The results indicated that the LightGBM model performed best, achieving an area under the curve (AUC) of 0.78, an accuracy of 0.77, and an F1 score of 0.72. Compared with the model incorporating the traditional binary labels for cumulative fatigue, the best prediction AUC (0.72), accuracy (0.66), and F1 score (0.65) improved by 6%, 11%, and 7%, respectively. Conclusion Cumulative fatigue is a significant predictor of occupational stress among manufacturing employees. Applying data dimensionality reduction combined with three-class cluster analysis to characterize cumulative fatigue improves the performance of occupational stress prediction models. From a data-driven perspective, machine learning methods demonstrate strengths in processing complex datasets, capturing nonlinear relationships, and generating predictions based on key variables. This study therefore confirms that refined processing of core factors substantially enhances the predictive capability of machine learning models in assessing occupational stress risk in the manufacturing workforce.

Objective To investigate biological markers associated with psychotic symptoms in patients with bipolar disorder(BD)based on electronic medical records of patients,and to develop an interpretable risk prediction model that supports the identification of high-risk individuals and that facilitates decision-making for providing clinical intervention in a timely manner.Methods A total of 2 352 patients diagnosed with BD and admitted to West China Hospital,Sichuan University were enrolled using the electronic medical records system of the hospital.The participants were divided into two subgroups,the bipolar disorder depression(BDD)group and the bipolar disorder mania(BDM)group.The logistic regression algorithm was used to train and validate the prediction model,and interpretability methods were used to analyze the contribution of each feature to individuals and the effect of the features on specific target prediction decisions.Results The logistic regression model demonstrated robust predictive performance across the BD,BDD,and BDM cohorts,with areas under the curve(AUC)of the receiver operating characteristic curves always exceeding 81.6%.The core predictive features included platelet distribution width(PDW),fibrinogen(FIB),platelet large cell ratio(P-LCR),activated partial thromboplastin time(APTT),prothrombin time(PT),and triglyceride(TG).The logistic regression model exhibited strong interpretability and was combined with nomograms for intuitive risk quantification and individualized prediction.Conclusion The logistic regression model enables rapid and simple screening of BD patients with psychotic symptoms.Distinct patterns of changes observed in blood biomarkers of BDD and BDM subgroups enrich the understanding of the underlying pathophysiological mechanisms and highlight the importance of considering subtypes in the intervention and management of patients.

Objective To explore the efficacy of DSA-guided intrathecal drug delivery system combined with Zi Wu Liu Zhu Acupoint Therapy for management of cancer pain and provide reference for its standardized clinical application.Methods and Results Recommendations were formulated based on literature review and expert group discussion,and consensus was reached following expert consultation.The consensus recommendations are comprehensive,covering the entire treatment procedures from preoperative assessment and preparation,surgical operation process,postoperative management and traditional Chinese medicine treatment to individualized treatment planning.The study results showed that the treatment plans combining traditional Chinese with Western medicine effectively alleviated cancer pain,reduced the use of opioid drugs,and significantly improved the quality of life and enhanced immune function of the patients.Postoperative follow-up suggested good treatment tolerance among the patients without serious complications.Conclusion The formulated consensus is comprehensive and can provide reference for clinicians to use DSA-guided intrathecal drug delivery system combined with Zi Wu Liu Zhu Acupoint Therapy.The combined treatment has a high clinical value with a good safety profile for management of cancer pain.

ObjectiveTo improve the quality and service performance of community visual health services in Shanghai, and to establish a set of reasonable and effective evaluation index system for community visual health services. MethodsCentered on the national and Shanghai-based visual health policies and based on the current status and development trends of community visual health service program in Shanghai, the candidate indicators were formed through literature review and expert interviews, firstly. The framework of an evaluation index system was formulated through qualitative research successively, which was further revised and perfected using the Delphi method. Coefficient weights were calculated using the analytic hierarchy process (AHP), culminating in the establishment of the community visual health evaluation index system, lastly. ResultsA total of 22 visual health experts from district-level center for disease control, hospital ophthalmology and leaders in charging of visual health service in community health centers participated in the Delphi questionnaire survey, with a questionnaire recovery rate of 100% and an expert authority coefficient of 0.86, indicating high credibility. After a round of correspondence to experts’ importance ratings and discussions, a comprehensive evaluation index system comprising 3 primary indicators, 12 secondary indicators, and 47 tertiary indicators, along with 5 additional indicators, was finalized. ConclusionAn index system tailored to effective evaluation for community visual health initiatives was drawn up in this study, which can promote the capacity building in community eye health services, facilitating the high-quality development of visual health courses, and enhancing residents’ eye health.

BACKGROUND:Magnetic resonance imaging is the gold standard for the diagnosis of osteonecrosis of femoral head,and previous methods of predicting osteonecrosis of femoral head collapse based on magnetic resonance images mostly require the combined assessment of coronal and sagittal images.However,osteonecrosis of femoral head tends to occur bilaterally,most hospitals perform bilateral hip magnetic resonance imaging scans during clinical examinations,but the bilateral hip scans can only view coronal and cross-sectional images,and it is difficult to obtain sagittal images,which affects the assessment of the risk of collapse.Therefore,it is of clinical value to establish a method to assess the risk of early osteonecrosis of femoral head collapse by applying the images that can be obtained after bilateral hip magnetic resonance scanning. OBJECTIVE:To establish a method of applying coronal and cross-sectional images of bilateral hip magnetic resonance imaging to assess the risk of osteonecrosis of femoral head collapse. METHODS:The medical records of 111 patients(181 hips)with early-stage osteonecrosis of femoral head diagnosed at the outpatient clinic of Honghui Hospital Affiliated to Xi'an Jiaotong University from October 2017 to October 2019 were retrospectively analyzed.They were categorized into collapsed and non-collapsed groups according to the femoral head collapse at the final follow-up,with 69 hips in the collapsed group and 112 hips in the non-collapsed group.The angle of necrotic range on the images of median coronal plane,transverse plane or one level above and below it was measured on the magnetic resonance imaging system.The sum of the two angles of necrotic angle on the coronal and transverse planes was used as the combined necrotic angle.The average of the three combined necrotic angles of each hip was taken to get the average combined necrotic angle of each hip.Finally,the correlation between the three combined necrotic angles and the average combined necrotic angle with the collapse of osteonecrosis of femoral head was analyzed,and the specificity and sensitivity of the four combined necrotic angles in predicting collapse were evaluated by using receiver operating characteristic curves. RESULTS AND CONCLUSION:(1)Totally 69 hips(38.1%)had femoral head collapse at the last follow-up and were included in the collapsed group;112 hips(61.9%)did not have progression of collapse and were included in the non-collapsed group.(2)The difference between the collapsed group and the non-collapsed group in terms of Association Research Circulation Osseous(ARCO)stage was significant(P<0.001).The difference in age,body mass index,follow-up time,gender distribution,side of onset,and causative factors was not significant(P>0.05).(3)The results of independent samples t-test suggested that all four combined necrotic angles were significantly correlated with collapse(P<0.000 1);and the differences in combined necrotic angles between the collapsed group and the non-collapsed group of ARCO stage I and the two groups of ARCO stage II were all significant(P<0.000 1).(4)In the analysis of the receiver operating characteristic,the area under the curve of the average combined necrotic angle was greater than that of the combined necrotic angle on the lower level of the median,the middle level,and the upper level of the median.(5)The average combined necrotic angle had a higher accuracy in the prediction of collapse than the lower level of the median,the middle level,and the upper level of the combined necrotic angle.(6)It is concluded that the accuracy of the average combined necrotic angle in predicting the risk of osteonecrosis of femoral head collapse is higher,and the clinical practicability is stronger,so we can consider using this method to predict the risk of osteonecrosis of femoral head collapse.

ObjectiveTo investigate the effects of different concentrations of Shaoyaotang-containing serum on lipopolysaccharide （LPS）-induced inflammation of human colorectal adenocarcinoma （Caco-2） cells by inhibiting apoptosis via activating the tumor necrosis factor （TNF） receptor superfamily member 6 （Fas）/Fas ligand （FasL） pathway. MethodsCaco-2 cells were allocated into blank， model （LPS， 10 mg·L^-1）， Shaoyaotang-containing serum （5%， 10%， 15%， 20%）， and Fas inhibitor （KR-33493， 20 mmol·L^-1） groups. Except the blank group， the other groups were stimulated with 10 mg·L^-1 LPS for 24 h for the modeling of inflammation. After successful modeling， the blank， Fas inhibitor， and model groups were treated with blank serum， and the Shaoyaotang-containing serum groups were treated with the serum samples at corresponding concentrations for 24 h. The Fas inhibitor group was subjected to KR-33493 pretreatment for 1 h. Cell proliferation and viability were examined by the cell-counting kit-8 （CCK-8） method. The levels of interleukin （IL）-6， IL-1β， and TNF-α were measured by enzyme-linked immunosorbent assay. Apoptosis was detected by flow cytometry. The protein and mRNA levels of Fas， FasL， cysteinyl aspartate-specific proteinase （Caspase）-3， Caspase-9， B-cell lymphoma 2 （Bcl-2）， and Bcl-2-associated X protein （Bax） were determined by Western blot and Real-time fluorescence quantitative polymerase chain reaction （Real-time PCR）， respectively. ResultsCompared with the blank group， the model group presented a decrease in cell survival rate （P<0.01）. Compared with that in the model group， the cell survival rate showed no significant change in the 5% Shaoyaotang-containing serum group but increased in the 10%， 15%， and 20% Shaoyaotang-containing serum groups （P<0.01）. Since there was no statistical difference between the 5% Shaoyaotang-containing serum group and the model group， 10%， 15%， and 20% Shaoyaotang-containing sera were selected for the follow-up study. Compared with the blank group， the model group showed risen levels of IL-6， IL-1β， and TNF-α （P<0.01）， an increased apoptosis rate （P<0.01）， up-regulated protein and mRNA levels of Fas， FasL， Caspase-3， Caspase-9， and Bax （P<0.01）， and down-regulated protein and mRNA levels of Bcl-2 （P<0.01）. Compared with the model group， the Fas inhibitor group and the 10%， 15%， and 20% Shaoyaotang-containing serum groups showed declined levels of IL-6， IL-1β， and TNF-α （P<0.01）， decreased apoptosis rates （P<0.01）， down-regulated protein and mRNA levels of Fas， FasL， Caspase-3， Caspase-9， and Bax （P<0.05， P<0.01）， and up-regulated protein and mRNA levels of Bcl-2 （P<0.05， P<0.01）. In addition， the 15% and 20% Shaoyaotang-containing serum groups had lower levels of IL-6， IL-1β， and TNF-α （P<0.05， P<0.01）， lower apoptosis rates （P<0.05， P<0.01）， lower protein and mRNA levels of Fas， FasL， Caspase-3， Caspase-9， and Bax （P<0.05， P<0.01）， and higher protein and mRNA levels of Bcl-2 （P<0.05， P<0.01） than the 10% Shaoyaotang-containing serum group. ConclusionThe Shaoyaotang-containing serum can reduce the content of inflammatory factors in Caco-2 cells， down-regulate the protein and mRNA levels of Fas， FasL， Caspase-3， Caspase-9， and Bax， and up-regulate the protein and mRNA levels of Bcl-2 under the intervention of LPS by regulating the Fas/FasL pathway and inhibiting the apoptosis of intestinal epithelial cells in ulcerative colitis.