BackgroundThe issue of school absenteeism due to school refusal in adolescents has become increasingly prominent. Acceptance and Commitment Therapy （ACT） has been applied successfully to improve depression， anxiety， and psychological flexibility in adolescents， while few studies have tested the effect of ACT intervention on above-mentioned psychological aspects and return-to-school rate in adolescents with school absenteeism. ObjectiveTo explore the effect of ACT on depression， anxiety， psychological flexibility and return-to-school rate in school absenteeism adolescents， and to provide a broader evidence base for clinical interventions. MethodsFrom May to June 2024， a sample of 50 adolescents with Shenzhen school registration who had been suspended from school for more than a consecutive month for school refusal were recruited based on Wechat official account platform. The adolescents were divided into study group and control group by random number table method. Both groups received psychological education with the theme of 'Causes and Coping Strategies of School Refusal'， and study group added a 6-week ACT intervention with weekly 1-hour sessions. At baseline and after treatment， Patients’ Health Questionnaire Depression Scale-9 item （PHQ-9）， Generalized Anxiety Disorder Scale-7 item （GAD-7） and Comprehensive assessment of Acceptance and Commitment Therapy processes （CompACT） were used for the clinical evaluation. ResultsA total of 45 （90.00%）adolescents completed the study， including 25 in study group and 20 in control group. Analysis revealed that study group scored higher on PHQ-9 and GAD-7， while lower on total CompACT score， openness dimension and awareness dimension compared with control group， with statistical significance （F=7.786， 10.334， 12.922， 14.374， 3.075， P<0.05 or 0.01）. After intervention， the rate of return-to-school was higher in study group than in control group （40.00% vs 10.00%， χ²=5.114， P<0.05）. ConclusionACT intervention for adolescents with school absenteeism may alleviate depression and anxiety， improve their psychological flexibility and increase return-to-school rate.［Funded by the "14^th Five Year Plan" for Social Sciences Project in Jiangxi Province （number， 24JY41D）； Science and Technology Planning Project of Shenzhen Municipality （number， 20210617155253001）］

Objective To explore the feasibility of applying artificial intelligence (AI) technology in chromosomal aberration (CA) analysis for occupational health surveillance of radiation workers and in biological dose estimation during nuclear emergency responses. Methods Peripheral blood samples from healthy volunteers were irradiated in vitro with X-rays and cobalt-60 (⁶⁰Co) γ rays. Chromosome slides were prepared using an automated harvesting and dropping device. The data training and outcome evaluation of CA analysis was performed on the AI software using chromosome images from occupational medical examination of radiation workers from the current lab or chromosome slides from blood samples irradiated with X-rays. The trained AI software was then used to assist in CA analysis and biological dose estimation among occupational medical examination of radiation workers, with results compared with manual reading and actual exposure doses. Results The trained AI software achieved a CA recognition accuracy of 95.11%. In the occupational health examination of radiation workers, the positive CA detection rate using AI + manual review was 2.25% higher than that in manual reviewing alone. The errors in biological dose estimation for ⁶⁰Co γ rays and X-rays using AI + manual review analysis were 11.86% and 7.33%, respectively, both within the acceptable 20.00% error margin. Conclusion AI + manual review can be effectively applied in CA analysis for occupational health examination and biological dose estimation during nuclear emergencies, significantly improving analysis efficiency.

Objective To evaluate the efficacy and safety of dupilumab combined with 2％cleboride ointment in the treatment of moderate to severe atopic dermatitis,as well as its impact on serological indica-tors.Methods A retrospective analysis was conducted on the clinical data of 67 patients with moderate to se-vere atopic dermatitis(AD)admitted to the Department of Dermatology of Shaoxing University Affiliated Hospital from March 2021 to December 2024.The study subjects were divided into an experimental group(n=35)and a control group(n=32)according to the treatment method.The experimental group was treated with Dupilumab injection and 2％Cleboride ointment,while the control group was treated with ebastine tab-lets and 2％cleboride ointment.Clinical and related serological indicators of patients after 16 weeks of treat-ment were collected,and the itch digital scale score,eczema area and severity(EASI)score,IL-4,IL-13 levels,and incidence of local skin adverse reactions were analyzed before and after treatment in both groups.Results The total effective rate of the experimental group after treatment was 94.29％(33/35),which was higher than the control group[53.13％(17/32)],and the difference was statistically significant(x2=12.862,P＜0.001).There was no statistically significant difference in symptom scores,IL-4,and IL-13 levels between the two groups before treatment(P＞0.05).After treatment,the symptom scores of the experimental group were lower than those of the control group,and the difference was statistically significant(P＜0.05).The lev-els of IL-4 and IL-13 in the experimental group were lower than those in the control group,and the difference was statistically significant(P＜0.05).The incidence of adverse reactions in the experimental group was 2.86％(1/35),significantly lower than the 34.38％(11/32)in the control group,and the difference was sta-tistically significant(x2=9.252,P=0.002).Conclusion The combination of dupilumab injection and 2％cleboride ointment is effective in relieving skin symptoms,regulating cellular immune function,reducing in-flammatory reactions,and minimizing local skin adverse reactions in patients with moderate to severe AD.It is worthy of clinical promotion and use.

Objective To investigate the differential expression genes(DEGs)related to angiogenesis in rosacea(RA)by utilizing bioinformatics analysis in order to screen the key genes and verify their mRNA expression levels.Methods The gene microarray dataset GSE65914 was retrieved from the Gene Expression Omnibus(GEO)repository.Analyzed by R programming,the dataset was refined to identify DEGs related to RA,and then cross-referenced with angiogenesis-related genes from the GeneCards database to get a subset specific to RA angiogenesis.The process of identifying key genes was augmented by employing protein-protein interaction(PPI)network analysis and Cytoscape-based computational algorithms.The mRNA expression levels of the aforementioned pivotal genes were detected by real-time fluorescent quantitative reverse transcription PCR(RT-qPCR).Results A total of 947 RA-associated DEGs were identified from GEO dataset,and then 202 genes related to RA angiogenesis were further delineated.PPI network analysis and Cytoscape algorithm finally identified 3 key genes,that is,CXCL8,IL-1B,and STAT1.The results of RT-qPCR showed that the mRNA expression levels of MIP-2,GCP-2,IL-1B and STAT1 in RA lesions were significantly higher than those in normal controls(P<0.05).Conclusion With aid of bioinformatics analysis,our study has screened and validated key genes associated with angiogenesis in RA,namely CXCL8,IL-1B,and STAT1,which providing a theoretical basis for elucidating the potential mechanisms underlying RA-induced angiogenesis and developing targeted therapeutic strategies.

ObjectiveTo investigate the level of hepatitis B surface antibody (anti-HBs) among preschool children (aged 3‒6 years) and primary and secondary school students in Tonglu County, Zhejiang Province, to evaluate the effectiveness of hepatitis B vaccination, and to provide a basis for hepatitis B prevention and control in the region. MethodsAs part of the 2023 Tonglu County Urban and Rural Residents Health Examination Program, blood samples were collected during health check-ups. Fingertip blood samples were obtained from preschool children, while venous blood samples were collected from primary and secondary school children. The anti-HBs levels in blood (positive + / negative -) were qualitatively tested using hepatitis B surface antibody test kits (latex method). The differences in anti-HBs positivity rates among different age groups were analyzed. ResultsBetween April 1, 2023 and June 30, 2023, a total of 52 919 individuals were surveyed, including 11 973 preschool children and 40 946 primary and secondary school students. The overall anti-HBs positivity rate was 39.74%, with the highest positivity rate observed among preschool children (60.20%). Age was negatively correlated with the anti-HBs positivity rate (P<0.001). No significant gender differences in anti-HBs positivity rates were observed. The anti-HBs positive rate in rural areas was higher than that in urban areas, with statistically significant differences across school grade groups (primary grades 1‒3, grades 4‒6, middle school, and high school) (P<0.001). ConclusionThe anti-HBs positivity rate among preschool and school-age children in Tonglu County decreases with age and remains relatively low. It is recommended to strengthen the monitoring of hepatitis B antibody levels and promote health education among preschool and school-age children. Children who have not completed the full hepatitis B vaccination should receive timely catch-up vaccination.

Objective To investigate the effect of SerpinA5 on the malignant biological behavior of esophageal squamous cell carcinoma (ESCC) and its molecular mechanism. Methods The expression levels of the SerpinA5 gene in various tumors and adjacent normal tissues were analyzed by using the TIMER2.0 database. The expression levels of SerpinA5 in the ESCC cell line and esophageal epithelial cells were detected through Western blot analysis. Stably transfected KYSE150 cell line with overexpression of SerpinA5 was constructed through lentiviral transfection, and overexpression efficiency was detected via Western blot analysis. The effects of SerpinA5 overexpression on the proliferation, apoptosis, migration, and invasion of ESCC cells were detected by employing the CCK8, plate cloning, flow cytometry, wound healing, and Transwell invasion assays. The nude mice subcutaneous xenograft model with SerpinA5 overexpression was constructed. Tumor growth was observed, and tumor volume and mass were measured. The cell proliferation level of the subcutaneous xenograft tumors in nude mice was detected via immunohistochemistry (IHC). Coimmunoprecipitation (Co-IP) was employed to determine the interaction between SerpinA5 and Fn. Western blot analysis was applied to detect the expression levels of proteins (Fn, Integrin-β1, FAK, and p-FAK) related to the Fn/Integrin-β1 signaling pathway in transplanted tumors. Results SerpinA5 was expressed at low levels in ESCC tissues and cell lines. In ESCC cells, SerpinA5 overexpression can considerably inhibit cell proliferation, migration, and invasion and promote cell apoptosis. In the subcutaneous xenograft experiment on nude mice, the tumor volume and weight of the SerpinA5 overexpression group were lower than those of the negative control group. IHC results demonstrated that SerpinA5 overexpression significantly inhibited the proliferation of ESCC cells in tumor tissues. Co-IP confirmed the interaction between SerpinA5 and Fn. Western blot analysis results showed that the expression levels of Fn, Integrin-β1, and p-FAK in the Fn/Integrin-β1 signaling pathway of ESCC cells in the subcutaneous xenograft tumors of nude mice significantly decreased after SerpinA5 overexpression. Conclusion Serpin A5 may inhibit proliferation, migration, and invasion and promote apoptosis of ESCC cells by regulating the Fn/Integrin-β1 signaling pathway.

Objective To investigate the effects and related mechanisms of mitochondrial-derived peptide MOTS-c on glycochenodeoxycholic acid (GCDCA)-induced injury in human hepatocytes (THLE-3 cells). Methods THLE-3 cells were cultured in vitro and treated with different concentrations of GCDCA and MOTS-c. The optimal concentrations of GCDCA and MOTS-c were determined by cell counting kit (CCK)-8 method. Subsequently, THLE-3 cells were treated or pre-treated with GCDCA (200 µmol/L), MOTS-c (15, 30, 60 µmol/L), the multidrug resistance protein 2 (MRP2) inhibitor Probenecid (500 µmol/L), and the nuclear factor erythroid 2-related factor 2 (Nrf2) inhibitor ML385 (10 µmol/L). Cell proliferation was assessed by CCK-8 method. Lactate dehydrogenase (LDH) levels in the culture medium were measured by biochemical method. Cell apoptosis rates were determined by flow cytometry. MRP2 messenger RNA (mRNA) levels were detected by real-time quantitative polymerase chain reaction (RT-qPCR). MRP2 and Nrf2 protein expression levels were analyzed by Western blotting. Results As the concentration of GCDCA increased, the proliferation activity of THLE-3 cells gradually decreased, while LDH activity in the culture medium and apoptosis levels increased, and the expression levels of MRP2 in the cells decreased (all P<0.05). Treatment with 30 and 60 µmol/L MOTS-c significantly enhanced the proliferation activity of THLE-3 cells exposed to GCDCA, upregulated the expression of MRP2 and Nrf2, and reduced LDH activity and apoptosis levels (all P<0.05). Co-treatment with Probenecid partially reversed the protective effects of MOTS-c on GCDCA-induced THLE-3 cells injury, while co-treatment with ML385 partially inhibited the induction of MRP2 expression by MOTS-c in THLE-3 cells exposed to GCDCA. Conclusions MOTS-c may alleviate GCDCA-induced injury in human hepatocytes (THLE-3 cells), and its mechanism may be related to the upregulation of MRP2 expression mediated by Nrf2.

Objective: To analyze the association of eating dining locations and their association with nutritional status among Chinese children aged 6-17 years,so as to provide reference for guiding children s reasonable diet. Methods: Stratified random cluster sampling was used to select children aged 6 to 17 years from 28 cities and rural areas of 14 provinces in East, North, Central, South, Southwest, Northwest, Northeast of China, and a total of 52 535 children were included in the study from 2019 to 2021. Information including dining locations, demographic characteristics, dietary intakes and physical activity were collected through a questionnaire survey. Fasting body height and weight were measured in the morning. Unordered multiclass Logistic regression analysis was conducted to assess the relationship between dining locations and nutritional status in children. Results: Regarding children s dining locations, 66.3% ate breakfast at home,25.8% ate breakfast at school,7.9% ate breakfast outside (small dining tables, restaurants, stalls, etc.); 67.7% ate dinner at home,29.0% ate dinner at school,3.3% ate dinner outside; and 63.6% ate lunch at school,30.8% ate lunch at home,5.7% ate lunch outside. The prevalence rates of overweight/obesity and undernutrition were 28.6% and 9.3%, respectively. The adjusted multiclass Logistic regression analysis (controlling for age, region, parental education, household income, total energy intake, and moderate-to-vigorous physical activity) demonstrated that, compared to eating at home, school based breakfast and dinner consumption was associated with significantly lower overweight/obesity risks for both genders (boys: breakfast OR =0.70, 95% CI =0.65-0.75; dinner OR =0.80, 95% CI = 0.74- 0.86; girls: breakfast OR = 0.89 , 95% CI = 0.82-0.96; dinner OR =0.88, 95% CI =0.81-0.95), whereas eating lunch away from home significantly increased overweight/obesity risks (boys: OR =1.32, 95% CI =1.17-1.48; girls: OR =1.43, 95% CI =1.26- 1.62 ), with all associations being statistically significant ( P <0.05). After adjusting for confounding factors, boys who ate breakfast away from home showed a significantly reduced risk of undernutrition ( OR =0.80,95% CI =0.66-0.97), while those consuming lunch away from home had an increased risk ( OR =1.26, 95% CI =1.01-1.57) ( P <0.05). Conclusions The choice of dining locations for children is becoming more diverse, and a relatively high proportion of children eat meals outside the home and at school. Eating out have a higher risk of malnutrition for children. School feeding may be beneficial to children s physical health.

OBJECTIVE: To construct machine learning prediction model for sepsis-associated encephalopathy (SAE), and analyze the application value of the model on early identification of SAE risk in elderly septic patients. METHODS: Patients aged over 60 years with a primary diagnosis of sepsis admitted to intensive care unit (ICU) from 2008 to 2023 were selected from Medical Information Mart for Intensive Care-IV 2.2 (MIMIC-IV 2.2). Demographic variables, disease severity scores, comorbidities, interventions, laboratory indicators, and hospitalization details were collected. Key factors associated with SAE were identified using univariate Logistic regression analysis. The data were randomly divided into training and validation sets in a 7 : 3 ratio. Multivariable Logistic regression analysis was conducted in the training set and visualized using a nomogram model for prediction of SAE. The discrimination of the model was evaluated in the validation set using the receiver operator characteristic curve (ROC curve), and its calibration was assessed using calibration curve. Furthermore, multiple machine learning algorithms, including multi-layer perceptron (MLP), support vector machine (SVM), naive bayes (NB), gradient boosting machine (GBM), random forest (RF), and extreme gradient boosting (XGB), were constructed in the training set. Their predictive performance was subsequently evaluated on the validation set. Taking the XGB model as an example, the interpretability of the model through the SHapley Additive exPlanations (SHAP) algorithm was enhanced to identify the key predictive factors and their contributions. RESULTS: A total of 2 204 septic patients were finally enrolled, of whom 840 developed SAE (38.1%). A total of 21 variables associated with SAE were screened through univariate Logistic regression analysis. Multivariable Logistic regression analysis showed that endotracheal intubation [odds ratio (OR) = 0.40, 95% confidence interval (95%CI) was 0.19-0.88, P < 0.001], oxygen therapy (OR = 0.76, 95%CI was 0.53-0.95, P = 0.023), tracheotomy (OR = 0.20, 95%CI was 0.07-0.53, P < 0.001), continuous renal replacement therapy (CRRT; OR = 0.32, 95%CI was 0.15-0.70, P < 0.001), cerebrovascular disease (OR = 0.31, 95%CI was 0.16-0.60, P < 0.001), rheumatic disease (OR = 0.44, 95%CI was 0.19-0.99, P < 0.001), male (OR = 0.68, 95%CI was 0.54-0.86, P = 0.001), and maximum anion gap (AG; OR = 0.95, 95%CI was 0.93-0.97, P < 0.001) were associated with an decreased probability of SAE, and age (OR = 1.05, 95%CI was 1.03-1.06, P < 0.001), acute physiology score III (APSIII; OR = 1.02, 95%CI was 1.01-1.02, P < 0.001), Oxford acute severity of illness score (OASIS; OR = 1.04, 95%CI was 1.03-1.06, P < 0.001), and length of hospital stay (OR = 1.01, 95%CI was 1.01-1.02, P < 0.001) were associated with an increased probability of SAE. A nomogram model was constructed based on these variables. In the validation set, ROC curve analysis showed that the model achieved an area under the ROC curve (AUC) of 0.723, and the calibration curve showed good consistency between the predicted probability of the model and the observed probability. Among the machine learning algorithms, including MLP, SVM, NB, GBM, RF, and XGB, the SVM model and RF model demonstrated relatively good predictive performance, with AUC of 0.748 and 0.739, respectively, and the sensitivity was both exceeding 85%. The predictive performance of the XGB model was explained through SHAP analysis, and the results indicated that APSIII score (SHAP value was 0.871), age (SHAP value was 0.521), and OASIS score (SHAP value was 0.443) were important factors affecting the predictive performance of the model. CONCLUSIONS The machine learning-based SAE prediction model exhibits good predictive capability and holds significant application value for the early identification of SAE risk in elderly septic patients.
Humans ; Machine Learning ; Aged ; Sepsis-Associated Encephalopathy ; Sepsis/complications* ; Intensive Care Units ; Logistic Models ; Middle Aged ; Male ; ROC Curve ; Female ; Bayes Theorem ; Nomograms ; Support Vector Machine ; Algorithms

Background Psychological disturbances such as work-family conflict and depressive mood are prevalent among occupational groups and are closely related to eating behavior. Therefore, investigating the influencing factors of eating behavior is of great significance for promoting the health behaviors of occupational populations. Objective To clarify the current situation of eating behavior among the occupational populations aged 18 to 60 years in China, and to explore the relationship between work-family conflict, depressive mood, and eating behavior, and to test the mediating role of depressive mood in the relationship. Methods The study used a data set containing occupational populations aged 18 to 60 years extracted from the 2021 Psychology and Behavior Investigation of Chinese Residents. The Work-Family Conflict Scale, the Chinese version of the Sakata Eating Behavior Scale Short Form, and the Patient Health Questionnaire-Depression Scale were used. Potential influencing factors of eating behavior of the occupational populations were evaluated by multiple linear regression. Structural equation modeling was used to analyze the relationships between work-family conflict, depressive mood, and eating behavior, and the Bootstrap method was used to test the mediating effect of depressive mood on the relationship of work-family conflict and eating behavior. Results Among the occupational populations, the proportion of reporting high work-family conflict was 48.4%, and the proportion of reporting mild depression and above was 48.7%. The total score of eating behavior was (16.16±4.64), and the proportion of high abnormal eating behavior tendency was 39.1%. There were significant differences in eating behavior score among different age, educational level, marital status, number of offspring, occupation, smoking, and drinking groups (P<0.05). The partial correlation analysis showed that work-family conflict and depressive mood were positively correlated with abnormal eating behavior (r=0.367, 0.386, P<0.001); work-family conflict was positively correlated with depressive mood (r=0.466, P<0.001). The results of the multiple linear regression showed that depressive mood, work-family conflict, age, smoking, drinking, and education level were associated with eating behavior (P<0.05). The structural equation modeling indicated that work-family conflict positively associated with depressive mood (b=0.529, P<0.001), depressive mood positively associated with abnormal eating behavior (b=0.292, P<0.001), and work-family conflict positively associated with abnormal eating behavior (b=0.270, P<0.001). Depressive mood played a partial mediating role in the relationship between work-family conflict and eating behavior, and the effect value was 0.154 (95%CI: 0.132, 0.179) that accounted for 36.32% of the total effect. Conclusion Work-family conflict could directly affect the eating behavior among occupational populations, and also indirectly affect eating behavior through a mediating effect of depressive mood. Therefore, optimizing the allocation of tasks between work and family, providing psychological support in need, alleviating work-family conflict and depressive mood may improve the eating behavior and mental health of working populations.