Objective: To evaluate the intervention effectiveness of co-occurrence and prevention for myopia and obesity among primary and secondary school students, so as to provide a scientific basis for the development of comprehensive intervention measures in myopia and obesity. Methods: From September 2022 to September 2023, a cluster random sampling method was used to select 6 primary schools and 6 junior high schools from Tongzhou District, Beijing. Participants were randomly assigned to an intervention group (914 before intervention and 754 after intervention) and a control group (868 before intervention and 652 after intervention), with an expected duration of one academic year. Based on the RE-AIM framework, integrate resources from families, schools, communities, and medical institutions to develop a school-based intervention technology packagefor the co-occurrence and prevention of myopia and obesity in children. The intervention group received intervention according to the comprehensive intervention technology package, while the control group did not receive any intervention measures. Relevant health indicators during the baseline period and after intervention were measured and collected, and groups were compared by Chi quest test, t-test and Wilcoxon rank sum test. Results: After intervention, the uncorrected visual acuity of primary and secondary school students in the intervention group (4.79±0.30) and the control group (4.77±0.33) both decreased compared to those before intervention (4.80±0.30, 4.90±0.32) ( t =-7.00,-5.24); the decrease in uncorrected visual acuity in the intervention group was smaller than that in the control group( t =5.33)( P <0.01). After intervention, body mass index, waist circumference, hip circumference, and body fat percentage of primary and secondary school students in the intervention group decreased compared to those before intervention. However, the changes in these indicators were not statistically significant ( t/Z =-0.03, - 0.36，- 0.30，- 0.01, P >0.05); the above indicators in the control group increased compared to those before intervention, but only hip circumference and body fat percentage showed statistically significant changes ( t/Z =2.17, 2.62, P <0.05). After intervention, both the intervention group and the control group showed increases in systolic and diastolic blood pressure compared to those before intervention(intervention group: t =2.16,5.29; control group: t =6.84,5.07); the intervention group had lower systolic and diastolic blood pressure than the control group( t = -5.27 , -2.08)( P <0.05). After intervention, the intervention and the control groups had statistically significant differences in cognitive accuracy(92.48%, 69.33%) in terms of "outdoor exercise can prevent myopia" and "having 5 servings of adult fist sized vegetables and fruits every day" ( χ 2=6.30, 7.86, P <0.05). There was a statistically significant difference in the proportion of primary and secondary school students in the intervention group (40.98%) and the control group (35.43%) for "who did not drink sugary drinks for every day in the past 7 days" ( χ 2=4.32, P <0.05). After intervention, the intervention group and the control group showed increases in "school outdoor activity duration on school days" and "outdoor activity duration on rest days" compared to those before intervention ( t/Z =-13.32,-9.71;- 2.59，-2.69）；the behavior rate of "visual acuity measurement frequency at least once every 3 months" in the intervention group (46.68%) and the control group (52.76%) increased compared to those before intervention (36.43%, 44.01%), and the increases in the intervention group were greater than that in the control group ( χ 2=17.52,11.08) ( P <0.05). Conclusions Comprehensive intervention measures have significant intervention effects on controlling the occurrence and development of comorbidity of myopia and obesity in children. It could actively promote collaboration and cooperation among families, schools, communities and medical institutions to reduce the occurrence of myopia and obesity among primary and secondary school students.

Objective To explore the relationship between PANoptosis and hepatic ischemia-reperfusion injury (HIRI), and to screen the key genes of PANoptosis in HIRI. Methods PANoptosis-related differentially expressed genes (PDG) were obtained through the Gene Expression Omnibus database and GeneCards database. Gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and Gene Set Enrichment Analysis (GSEA) were used to explore the biological pathways related to PDG. A protein-protein interaction network was constructed. Key genes were selected, and their diagnostic value was assessed and validated in the HIRI mice. Immune cell infiltration analysis was performed based on the cell-type identification by estimating relative subsets of RNA transcripts. Results A total of 16 PDG were identified. GO analysis showed that PDG were closely related to cellular metabolism. KEGG analysis indicated that PDG were mainly enriched in cellular death pathways such as apoptosis and immune-related signaling pathways such as the tumor necrosis factor signaling pathway. GSEA results showed that key genes were mainly enriched in immune-related signaling pathways such as the mitogen-activated protein kinase (MAPK) signaling pathway. Two key genes, DFFB and TNFSF10, were identified with high accuracy in diagnosing HIRI, with areas under the curve of 0.964 and 1.000, respectively. Immune infiltration analysis showed that the control group had more infiltration of resting natural killer cells, M2 macrophages, etc., while the HIRI group had more infiltration of M0 macrophages, neutrophils, and naive B cells. Real-time quantitative polymerase chain reaction results showed that compared with the Sham group, the relative expression of DFFB messenger RNA in liver tissue of HIRI group mice increased, and the relative expression of TNFSF10 messenger RNA decreased. Cibersort analysis showed that the infiltration abundance of naive B cells was positively correlated with DFFB expression (r=0.70, P=0.035), and the infiltration abundance of M2 macrophages was positively correlated with TNFSF10 expression (r=0.68, P=0.045). Conclusions PANoptosis-related genes DFFB and TNFSF10 may be potential biomarkers and therapeutic targets for HIRI.

Purpose: Biomarkers predicting clinically significant prostate cancer (sPC) before biopsy are currently lacking. This study aimed to develop a non-invasive urine test to predict sPC in at-risk men using urinary metabolomic profiles. Materials and Methods: Urine samples from 934 at-risk subjects and 268 treatment-naïve PC patients were subjected to liquid chromatography/mass spectrophotometry (LC-MS)-based metabolomics profiling using both C18 and hydrophilic interaction liquid chromatography (HILIC) column analyses. Four models were constructed (training cohort [n=647]) and validated (validation cohort [n=344]) for different purposes. Model I differentiates PC from benign cases. Models II, III, and a Gleason score model (model GS) predict sPC that is defined as National Comprehensive Cancer Network (NCCN)-categorized favorable-intermediate risk group or higher (Model II), unfavorable-intermediate risk group or higher (Model III), and GS ≥7 PC (model GS), respectively. The metabolomic panels and predicting models were constructed using logistic regression and Akaike information criterion. Results: The best metabolomic panels from the HILIC column include 25, 27, 28 and 26 metabolites in Models I, II, III, and GS, respectively, with area under the curve (AUC) values ranging between 0.82 and 0.91 in the training cohort and between 0.77 and 0.86 in the validation cohort. The combination of the metabolomic panels and five baseline clinical factors that include serum prostate-specific antigen, age, family history of PC, previously negative biopsy, and abnormal digital rectal examination results significantly increased AUCs (range 0.88–0.91). At 90% sensitivity (validation cohort), 33%, 34%, 41%, and 36% of unnecessary biopsies were avoided in Models I, II, III, and GS, respectively. The above results were successfully validated using LC-MS with the C18 column. Conclusions Urinary metabolomic profiles with baseline clinical factors may accurately predict sPC in men with elevated risk before biopsy.

Purpose: This study assessed the performance of the ultrasound-guided attenuation parameter (UGAP) in diagnosing and grading hepatic steatosis in patients with metabolic dysfunctionassociated steatotic liver disease (MASLD). Magnetic resonance imaging proton density fat fraction (MRI-PDFF) served as the reference standard. Methods: Patients with hepatic steatosis were enrolled in this prospective study and underwent UGAP measurements. MRI-PDFF values of ≥5%, ≥15%, and ≥25% were used as references for the diagnosis of steatosis grades ≥S1, ≥S2, and S3, respectively. Spearman correlation coefficients and area under the receiver operating characteristic curves (AUCs) were calculated. Results: Between July 2023 and June 2024, the study included 88 patients (median age, 40 years; interquartile range [IQR], 36 to 46 years), of whom 54.5% (48/88) were men and 45.5% (40/88) were women. Steatosis grades exhibited the following distribution: 22.7% (20/88) had S0, 50.0% (44/88) had S1, 21.6% (19/88) had S2, and 5.7% (5/88) had S3. The success rate for UGAP measurements was 100%. The median UGAP value was 0.74 dB/cm/MHz (IQR, 0.65 to 0.82 dB/ cm/MHz), and UGAP values were positively correlated with MRI-PDFF (r=0.77, P<0.001). The AUCs of UGAP for the diagnoses of ≥S1, ≥S2, and S3 steatosis were 0.91, 0.90, and 0.88, respectively. In the subgroup analysis, 98.4% (60/61) of patients had valid controlled attenuation parameter (CAP) values. UGAP measurements were positively correlated with CAP values (r=0.65, P<0.001). Conclusion Using MRI-PDFF as the reference standard, UGAP demonstrates good diagnostic performance in the detection and grading of hepatic steatosis in patients with MASLD.

Purpose: This study aimed to evaluate the contrast-enhanced ultrasound with Sonazoid (Sonazoid-CEUS) features of hepatocellular carcinoma (HCC) in patients with non-alcoholic fatty liver disease (NAFLD). Methods: In this retrospective study, patients who underwent surgical resection and were histopathologically diagnosed with NAFLD or cirrhosis-related HCC were included. All patients received Sonazoid-CEUS examinations within 1 week prior to hepatic surgery. The enhancement patterns of HCC lesions were evaluated and compared between the two groups according to the current World Federation for Ultrasound in Medicine and Biology guidelines. Multivariate logistic regression analysis was used to assess the correlations between Sonazoid-CEUS enhancement patterns and clinicopathologic characteristics. Results: From March 2022 to April 2023, a total of 151 patients with HCC were included, comprising 72 with NAFLD-related HCC and 79 with hepatitis B virus (HBV) cirrhosis–related HCC. On Sonazoid-CEUS, more than half of the NAFLD-related HCCs exhibited relatively early and mild washout within 60 seconds (54.2%, 39/72), whereas most HBV cirrhosis–related HCCs displayed washout between 60 and 120 seconds (46.8%, 37/79) or after 120 seconds (39.2%, 31/79) (P<0.001). In the patients with NAFLD-related HCC, multivariate analysis revealed that international normalized ratio (odds ratio [OR], 0.002; 95% confidence interval [CI], 0.000 to 0.899; P=0.046) and poor tumor differentiation (OR, 21.930; 95% CI, 1.960 to 245.319; P=0.012) were significantly associated with washout occurring within 60 seconds. Conclusion Characteristic Sonazoid-CEUS features are useful for diagnosing HCC in patients with NAFLD.

ObjectiveThe primary objective of this study was to investigate the effects of carbohydrate intake order on post-exercise recovery and metabolic regulation under heat stress, particularly in models of exercise induced fatigue. Given the increasing significance of optimizing nutritional strategies to support performance in extreme environmental conditions, this study aimed to provide experimental evidence that contributes to a better understanding of how the sequence in which carbohydrates are consumed impacts exercise recovery, metabolic homeostasis, and fatigue alleviation in a high-temperature environment. MethodsA mouse model of exercise-induced fatigue was established under high-temperature (35°C) to simulate heat stress. The subjects were divided into 3 distinct groups based on their carbohydrate intake order: the “mixed intake” group (HOT_MIX), where all macronutrients (carbohydrates, proteins, and fats) were consumed in a balanced ratio; the “carbohydrate-first intake” group (HOT_CHO), where carbohydrates were consumed first followed by other macronutrients; the “carbohydrate-later intake” group (HOT_PRO), where proteins and fats were consumed prior to carbohydrates. Each group underwent a 7 d intervention period with daily intake according to their designated group. Exercise performance was assessed using rotarod retention time test, and biomarkers of muscle damage, such as lactate dehydrogenase (LDH), creatine kinase (CK), lactate (LD), alanine aminotransferase (ALT), and non-esterified fatty acids (NEFA), were measured. Furthermore, targeted metabolomics analyses were conducted to investigate metabolic shifts in response to different dietary strategies, and KEGG pathway enrichment analysis was employed to explore the biological mechanisms underlying these changes. ResultsThe findings demonstrated that the HOT_PRO group exhibited a significantly improved performance in the rotarod test, with a longer retention time compared to both the HOT_MIX and HOT_CHO groups (P<0.05). Additionally, this group showed significantly reduced levels of muscle damage markers such as LDH and CK, indicating that the carbohydrate-later intake strategy helped alleviate exercise-induced muscle injury. Metabolomic profiling of the HOT_PRO group showed marked increases in alanine, creatine, and flavin adenine dinucleotide (FAD), indicating shifts in amino acid metabolism and oxidative metabolism. Conversely, metabolites such as spermidine, cholesterol sulfate, cholesterol, and serine were significantly reduced in the HOT_PRO group, pointing to alterations in lipid and sterol metabolism. Further analysis of the differential metabolites revealed that these changes were primarily associated with key metabolic pathways, including glycine-serine-threonine metabolism, primary bile acid biosynthesis, taurine and hypotaurine metabolism, and steroid hormone biosynthesis. These pathways are essential for energy production, antioxidant defense, and muscle recovery, suggesting that the carbohydrate-later feeding strategy may promote metabolic homeostasis and improve exercise recovery by enhancing these critical metabolic processes. ConclusionThe results of this study support the hypothesis that consuming carbohydrates after proteins and fats during exercise recovery enhances metabolic homeostasis and accelerates recovery under heat stress. This strategy effectively modulates energy, amino acid, and lipid-related pathways, which are crucial for improving endurance performance and mitigating fatigue in high-temperature environments. The findings suggest that carbohydrate-later intake could be a promising nutritional strategy for athletes and individuals exposed to heat during physical activity. Furthermore, the study provides valuable insights into how different nutrient timing strategies can impact exercise recovery and metabolic regulation, paving the way for more personalized and effective nutritional interventions in extreme environmental conditions.

ObjectiveBased on functional near-infrared spectroscopy (fNIRS), we investigated the brain activity characteristics of gross motor tasks in children with autism spectrum disorder (ASD) and motor dysfunctions (MDs) to provide a theoretical basis for further understanding the mechanism of MDs in children with ASD and designing targeted intervention programs from a central perspective. MethodsAccording to the inclusion and exclusion criteria, 48 children with ASD accompanied by MDs were recruited into the ASD group and 40 children with typically developing (TD) into the TD group. The fNIRS device was used to collect the information of blood oxygen changes in the cortical motor-related brain regions during single-handed bag throwing and tiptoe walking, and the differences in brain activation and functional connectivity between the two groups of children were analyzed from the perspective of brain activation and functional connectivity. ResultsCompared to the TD group, in the object manipulative motor task (one-handed bag throwing), the ASD group showed significantly reduced activation in both left sensorimotor cortex (SMC) and right secondary visual cortex (V2) (P<0.05), whereas the right pre-motor and supplementary motor cortex (PMC&SMA) had significantly higher activation (P<0.01) and showed bilateral brain region activity; in terms of brain functional integration, there was a significant decrease in the strength of brain functional connectivity (P<0.05) and was mainly associated with dorsolateral prefrontal cortex (DLPFC) and V2. In the body stability motor task (tiptoe walking), the ASD group had significantly higher activation in motor-related brain regions such as the DLPFC, SMC, and PMC&SMA (P<0.05) and showed bilateral brain region activity; in terms of brain functional integration, the ASD group had lower strength of brain functional connectivity (P<0.05) and was mainly associated with PMC&SMA and V2. ConclusionChildren with ASD exhibit abnormal brain functional activity characteristics specific to different gross motor tasks in object manipulative and body stability, reflecting insufficient or excessive compensatory activation of local brain regions and impaired cross-regions integration, which may be a potential reason for the poorer gross motor performance of children with ASD, and meanwhile provides data support for further unraveling the mechanisms underlying the occurrence of MDs in the context of ASD and designing targeted intervention programs from a central perspective.

ObjectiveTobacco-related diseases remain one of the leading preventable public health challenges worldwide and are among the primary causes of premature death. In recent years, accumulating evidence has supported the classification of nicotine addiction as a chronic brain disease, profoundly affecting both brain structure and function. Despite the urgency, effective diagnostic methods for smoking addiction remain lacking, posing significant challenges for early intervention and treatment. To address this issue and gain deeper insights into the neural mechanisms underlying nicotine dependence, this study proposes a novel graph neural network framework, termed TI-GNN. This model leverages functional magnetic resonance imaging (fMRI) data to identify complex and subtle abnormalities in brain connectivity patterns associated with smoking addiction. MethodsThe study utilizes fMRI data to construct functional connectivity matrices that represent interaction patterns among brain regions. These matrices are interpreted as graphs, where brain regions are nodes and the strength of functional connectivity between them serves as edges. The proposed TI-GNN model integrates a Transformer module to effectively capture global interactions across the entire brain network, enabling a comprehensive understanding of high-level connectivity patterns. Additionally, a spatial attention mechanism is employed to selectively focus on informative inter-regional connections while filtering out irrelevant or noisy features. This design enhances the model’s ability to learn meaningful neural representations crucial for classification tasks. A key innovation of TI-GNN lies in its built-in causal interpretation module, which aims to infer directional and potentially causal relationships among brain regions. This not only improves predictive performance but also enhances model interpretability—an essential attribute for clinical applications. The identification of causal links provides valuable insights into the neuropathological basis of addiction and contributes to the development of biologically plausible and trustworthy diagnostic tools. ResultsExperimental results demonstrate that the TI-GNN model achieves superior classification performance on the smoking addiction dataset, outperforming several state-of-the-art baseline models. Specifically, TI-GNN attains an accuracy of 0.91, an F1-score of 0.91, and a Matthews correlation coefficient (MCC) of 0.83, indicating strong robustness and reliability. Beyond performance metrics, TI-GNN identifies critical abnormal connectivity patterns in several brain regions implicated in addiction. Notably, it highlights dysregulations in the amygdala and the anterior cingulate cortex, consistent with prior clinical and neuroimaging findings. These regions are well known for their roles in emotional regulation, reward processing, and impulse control—functions that are frequently disrupted in nicotine dependence. ConclusionThe TI-GNN framework offers a powerful and interpretable tool for the objective diagnosis of smoking addiction. By integrating advanced graph learning techniques with causal inference capabilities, the model not only achieves high diagnostic accuracy but also elucidates the neurobiological underpinnings of addiction. The identification of specific abnormal brain networks and their causal interactions deepens our understanding of addiction pathophysiology and lays the groundwork for developing targeted intervention strategies and personalized treatment approaches in the future.

Objective: To explore the bidirectional associations among body mass index Z scores (BMI Z scores) and weight stigma with depressive symptoms in adolescents, thereby providing evidence for targeted intervention strategies. Methods: A stratified cluster random sampling method was employed to select 18 301 adolescents aged 12-18 years from all 12 prefectures (103 counties) in the Inner Mongolia Autonomous Region, and two waves of longitudinal surveys were conducted in September 2023 (T1) and September 2024 (T2) among the adolescents. Weight stigma was assessed by using a self developed questionnaire, depressive symptom was measured with the Center for Epidemiologic Studies Depression Scale (CES-D), and BMI Z scores were calculated according to the World Health Organization standards. Pearson correlation analysis was used to examine associations among variables, and cross lagged panel models were constructed to investigate the dynamic bidirectional relationships among the three variables. Results: Adolescents BMI Z scores and weight stigma with depressive symptoms all exhibited autoregressive stability across the two time points (autoregressive paths, all P <0.01). Cross lagged model comparisons indicated that the bidirectional path model achieved the best fit ( χ 2=12.65, RMSEA =0.017, CFI =1.000; △ χ 2=193.39, P <0.01), supporting dynamic bidirectional associations among the three variables. After adjusting for gender, age, subjective social status and only child status, T1 BMI Z scores among adolescents positively predicted T2 weight stigma ( β =0.061), and T1 weight stigma positively predicted T2 depressive symptoms ( β =0.608); in the reverse direction, T1 depressive symptoms predicted T2 weight stigma ( β =0.003), and T1 weight stigma predicted T2 BMI Z scores ( β =0.081) (all P <0.01). Conclusions There is a bidirectional cross lagged relationship among adolescents BMI Z scores and weight stigma with depressive symptoms, suggesting that weight stigma may serve as a key psychological variable linking obesity and depressive symptoms. Greater attention should be paid to the potential threat of weight stigma to adolescents mental health, with intervention strategies expanded from a solely physiological focus to encompass psychosocial dimensions.

Objective: To investigate the changing trends for associations of anxiety and depressive symptoms with smartphone addiction among middle school students, so as to provide a scientific basis for preventing smartphone addiction in middle school students. Methods: From 2022 to 2023, a method of combining convenient sampling with cluster sampling was used to select 8 923 middle school students from 27 junior high schools and 3 senior high schools in a district of Shenzhen City between September 2022 (baseline, T1) and September 2023 (follow up, T2). The Smartphone Addiction Scale-Short Version (SAS-SV), Patients Health Questionnaire-9 Item (PHQ-9), and Generalized Anxiety Disorder 7-item Scale (GAD-7) were administered to assess smartphone addiction, anxiety and depressive symptoms. Mixed effects models were used to analyze the association of anxiety and depressive symptoms with smartphone addiction among middle school students. Results: From September 2022 to September 2023, the reported prevalence of smartphone addiction increased from 24.22% to 25.25% ( χ 2=45.71); and smartphone addiction scores [ 24.00 (16.00, 32.00),25.00(16.00, 33.00)], anxiety symptom scores [2.00(0.00, 7.00),3.00(0.00, 7.00)] and depressive symptom scores[3.00(0.00, 8.00),5.00(0.00, 9.00)] all significantly increased ( Z =-17.43, -42.38, -41.57) (all P <0.05). There were statistically significant difference in the distribution of anxiety and depression symptom levels among middle school students in 2022 and 2023 ( χ 2=85.15, 106.85, both P <0.05). After adjusting for covariates such as age, gender and family background, mixed effects models revealed dose response associations of anxiety and depressive symptoms with smartphone addiction among middle school students:mild anxiety symptom( OR =3.22), moderate to severe anxiety symptom ( OR =5.36), mild depressive symptom ( OR =3.32) and moderate to severe depressive symptom ( OR =6.13) were significantly associated with higher risks of smartphone addiction (all P <0.05). Interaction effect analysis found that co existing anxiety and depressive symptoms synergistically increased addiction risk by 5.60 times ( OR =5.60) compared to the asymptomatic group, with 32% of the combined risk attributable to their interaction ( S=1.64, AP =0.32)(both P < 0.05 ). Conclusions Anxiety and depressive symptoms are significantly associated with smartphone addiction, exhibiting a synergistic effect. Attention should be paid to emotional issues and smartphone addiction among middle school students.