Objective: To explore the association of vegetables and fruits intake with depressive symptoms among multi ethnic first year junior high school students in Yunnan Province, so as to provide data support for preventing and reducing depressive symptoms among first year junior high school students. Methods: From October to December 2022, a cluster random sampling method was used to select 8 500 first year junior high school students from 11 ethnic minority areas in Yunnan Province (Fugong County, Longling County, Longyang District, Luchun County, Mojiang County, Nanjian County, Qiaojia County, Shuangjiang County, Tengchong City, Yuanmou County, Zhenyuan County), to investigate with a questionnaire. The Dietary Frequency Questionnaire was used to collect dietary behavior datas, and the Chinese version of Depression Anxiety Stress Scale-21 (DASS-21) was used to assess depressive symptoms. The generalized linear model was used to analyze the association of vegetable and fruit intake with depressive symptoms in students, and stratified analysis was performed according to ethnicity. Results: The detection rate of depressive symptoms among first year junior high school students in Yunnan Province was 29.5%. The detection rates of depressive symptoms in Han and minority first year junior high school students were 26.9% and 31.6%. After controlling for demographic variables such as gender, age, family residence and other confounding factors, the generalized linear model analysis results showed that the intake of leafy vegetables ( β= -0.07 , 95%CI =-0.12 to -0.01), flat fruits ( β=-0.06, 95%CI =-0.12 to -0.00) and hot natured fruits ( β=0.11, 95%CI = 0.04- 0.17) were associated with depressive symptoms in Han first year junior high school students (all P <0.05). The intake of melon and fruit vegetables ( β=-0.06, 95%CI =-0.11 to -0.01) and hot natured fruits ( β=0.06, 95%CI =0.01-0.12) were associated with depressive symptoms in ethnic minority first year junior high school students (both P <0.05). Conclusions The intake of vegetables and fruits among multi ethnic first year junior high school students in Yunnan Province is related to the risk of depressive symptoms. It is suggested to strengthen the consumption guidance and education of vegetables and fruits to prevent depressive symptoms among first year junior high school students.

Doxorubicin (DOX)-induced cardiotoxicity and sepsis-induced myocardial injury (SIMI) represent significant clinical challenges in patients undergoing chemotherapy, sharing a common pathological basis of oxidative stress and mitochondrial dysfunction. Ferroptosis, an iron-dependent form of regulated cell death driven by lipid peroxidation, has recently been shown to play a critical role in DOX-induced cardiotoxicity and lipopolysaccharide (LPS)-induced SIMI. This article systematically reviews the mechanisms underlying myocardial injury caused by DOX and sepsis, identifying ferroptosis as a central common pathway. DOX triggers a burst of reactive oxygen species within mitochondria and inhibits glutathione peroxidase 4 (GPX4) activity through redox cycling of its quinone group and high-affinity accumulation in mitochondrial cardiolipin. LPS, by activating pattern recognition receptors and related inflammatory signaling pathways, provokes a cytokine storm and mitochondrial dysfunction. Both can disrupt the core regulatory axis of cysteine-glutathione (GSH)-GPX4, synergistically promoting ferroptosis in cardiomyocytes. Moreover, epigenetic regulation plays a key role in DOX- and LPS-induced cardiomyocyte ferroptosis and may serve as a promising therapeutic target. A deeper understanding of the ferroptosis mechanism and its epigenetic regulatory network in the synergistic injury induced by DOX and sepsis is of great importance for developing novel strategies to mitigate chemotherapy-related cardiotoxicity and improve outcomes in cancer patients with concurrent infections.

To develop and validate a model for predicting intensive care unit (ICU) mortality risk in patients with malignant tumors complicated by acute respiratory failure (ARF) based on an explainable machine learning framework.

ObjectiveTo construct and validate a clinical prediction model for inflammatory remission outcomes in rheumatoid arthritis （RA） patients with liver and kidney deficiency syndrome treated with Bushen Zhiwang Decoction （补肾治尪汤， BZD） based on metabolomics. MethodsA prospective cohort study was conducted， enrol-ling 60 RA patients with liver and kidney deficiency syndrome. All patients were treated with BZD and conventional-dose oral conventional synthetic disease-modifying antirheumatic drugs （csDMARDs） for 12 months. Clinical data were collected， and the change in disease activity score in 28 joints （DAS28） after treatment compared with baseline （△DAS28） was used as the primary outcome and grouping criterion. Peripheral blood samples were collected before treatment to analyze plasma metabolites. Differential analysis and least absolute shrinkage and selection operator （LASSO） regression were used to preliminarily screen differential metabolites， followed by machine learning algorithms to further identify a core metabolite combination. Based on the expression levels of the core metabolite combination， a novel metabolite index， namely the metabolomics-based inflammatory remission score （Met-IRS）， was calculated using standar-dized metabolite values， and its clinical applicability was evaluated. A clinical prediction model was constructed by integrating clinical characteristics and Met-IRS， and the model performance was assessed. ResultsAmong the 60 patients， those with △DAS28 ≥ 0.27 were assigned to the high inflammatory remission group， while those with △DAS28 ＜ 0.27 were assigned to the low inflammatory remission group， with 30 cases in each group. Compared to the low inflammatory remission group， the high inflammatory remission group showed a higher frequency of methotrexate use and a lower positive rate of rheumatoid factor （RF） （P＜0.05）. Seven core metabolites were identified as the optimal combination， including mangiferic acid， fatty acid-hydroxy fatty acid ester 40∶6， fatty acid-hydroxy fatty acid ester 18∶0， fatty acid-hydroxy fatty acid ester 36∶1， glucosylceramide， lysophosphatidylcholine 22∶5， and pregnanetriol ketone. The calculated Met-IRS comprehensively reflected the characteristics of differential metabolites and demonstrated clinical applicability. Met-IRS was significantly higher in the high inflammatory remission group than in the low inflammatory remission group， and was positively correlated with high inflammatory remission outcomes （P＜0.05）. Based on the variables Met-IRS， methotrexate use， leflunomide use， and RF positivity， a clinical prediction model for inflammatory remission in RA treatment （Cj-RTRM） was constructed. Model performance evaluation demonstrated that the model had good clinical predictive ability， with an area under the receiver operating characteristic curve （AUC） of 0.880， sensitivity 0.967， specificity 0.700 and Youden's index 0.667. ConclusionThe clinical prediction model Cj-RTRM constructed based on the metabolomics-based inflammatory remission score Met-IRS can effectively predict clinical inflammatory remission outcomes in RA patients treated with BZD and accurately identify the advantageous population for this treatment. This model provides guiding evidence for dynamic inflammation monitoring， targeted management， and identification of populations with advantages in traditional Chinese medicine.

As the core carrier of the inheritance and innovation of traditional Chinese medicine （TCM）， the modern expanded application of classic formulae is an inevitable trend for TCM to adapt to the changes in disease spectrum and achieve academic development. However， several challenges remain， including the vague definition of syndrome-formula ontology between ancient and modern times， the insufficient adaptability of the evidence grading system， and the disconnection between theory and clinical practice， having severely restricted the precise application and standardized development of classic formulae. Based on the current status of the modern expanded application of classic formulae， and grounded in the core theory of formula-syndrome correspondence in TCM， this paper constructs a theoretical framework of "syndrome-formula ontology reconstruction". The framework systematically expounds its core connotations， theoretical foundations and practical logic， and further clarifies the reconstruction direction of the TCM-specific evidence grading system by taking correspondence between formula and syndrome as the core， constructing a multi-dimensional and integrated evaluation framework， and adhering to the orientation of clinical application. The ultimate goal is to form a theoretical paradigm characterized by "syndrome-formula ontology reconstruction-evidence grading reconstruction-precise clinical application"， thereby providing theoretical support for the digital inheritance， evidence-based development， and modern application of classical prescriptions.

Objective: To analyze the status of outdoor activities on weekends among children and adolescents of different educational stages in Shanghai and their impact on myopia, so as to provide a basis for formulating more specific prevention and control protocol of myopia. Methods: From September to October 2022, a stratified cluster random sampling method was employed to select 84 schools (27 kindergartens, 21 primary schools, 15 junior high schools and 21 high schools) across Shanghai, enrolling a total of 28 654 children and adolescents aged 4 to 18 for the study. Ophthalmic examinations were conducted to ascertain the prevalence of myopia among children and adolescents. Additionally, a questionnaire survey was administered to collect data on outdoor activity duration and associated factors. Multivariate Logistic regression analysis was utilized to investigate the associated factors of outdoor activity levels on weekends. Results: The overall myopia detection rate among children and adolescents was 58.4%, with a higher rate observed in girls (59.2%) compared to boys (57.6%). The myopia detection rates for children and adolescents with an average daily outdoor activity duration of ≥2 h and <2 h on weekends were 54.6% and 68.8%, and the differences were statistically significant ( χ 2=8.12,460.89, P <0.01). Multivariable Logistic regression analysis revealed that girls ( OR =0.80), those with a myopic parent ( OR =0.68), schools from urban districts ( OR =0.72), higher education stages (primary school: OR =0.65, junior high school: OR =0.24, high school: OR =0.14) and spending≥2 h/d on homework during weekends ( OR =0.57) among children and adolescents were less likely to engage in outdoor activities for ≥2 h on weekends ( P <0.01). After incorporating gender, parental myopia status, educational stage, school location, average daily duration on weekends for spending on homework, electronic product usage and outdoor activities as dependent variables in a multivariate Logistic regression analysis, the results showed that children and adolescents with an average outdoor activity duration for ≥2 h on weekends had a lower risk of myopia ( OR =0.86, P < 0.01). Conclusions The level of outdoor activity among children and adolescents on weekends needs to be improved. Outdoor activities on weekends is an associated factor for myopia among children and adolescents. Particularly, girls, those with myopic parents, schools from urban districts, and spending long hours on homework during weekends among children and adolescents require increased attention.

Objective: To investigate the effect of loss of function of lanosterol synthase( LSS) gene on intestinal function in a mouse model of non-alcoholic fatty liver disease( NAFLD) induced by a high-fat diet． Methods: LSS gene heterozygous knockout C57 mice ( LSS + / －) were established using the CRISRP / Cas9 system．After being fed a high-fat diet with 60% fat content for 6 months，the fat deposition in liver tissues was detected by HE and Oil red O staining，the morphological changes of small intestine tissue were detected by HE staining．The changes in total cholesterol content in intestinal tissue were detected by kits．The gastrointestinal motility function of mice was detected by phenol red paste．The intestinal permeability was detected by Evans blue staining，and the expression of LSS，tight junction protein ( Claudin) -1，Claudin-5，cluster of differentiation 36 ( CD36) ，and Niemann-Pick type C1-like 1 protein ( NPC1L1) proteins in small intestinal tissues were detected by Western blot． Results : The results of HE and Oil red O staining of liver tissues showed that liver fat deposition in LSS gene heterozygous knockout mice was lower than that in wild-type mice in the high-fat diet group．The total cholesterol content in intestinal tis- sue of LSS gene heterozygous knockout mice decreased ( P ＜0. 01) ，but no morphological differences were ob- served between the two groups of mice by HE staining of intestinal tissues．The gastrointestinal motility function of LSS gene heterozygous knockout mice did not show significant changes．The intestinal permeability of LSS gene het- erozygous knockout mice in the high-fat diet group decreased as detected by Evans blue ( P＜0. 05) ．The expres- sion levels of Claudin-5 protein in the intestinal tissue of LSS gene heterozygous knockout mice in the high-fat diet group increased ( P ＜0. 05 ) ，while the expression of LSS protein in the intestinal tissues of LSS heterozygous knockout mice decreased ( P ＜0. 05) ． Conclusion In the NAFLD model induced by a high-fat diet，LSS gene heterozygous knockout reduces liver fat deposition induced by a high-fat diet and improves intestinal barrier function by regulating cholesterol metabolism in intestinal tissues and up-regulating the expression of Claudin-5．

Intestinal fibrosis is a significant clinical challenge in inflammatory bowel diseases, but no effective anti-fibrotic therapy is currently available. Glucagon receptor (GCGR) and glucagon-like peptide 1 receptor (GLP1R) are both peptide hormone receptors involved in energy metabolism of epithelial cells. However, their role in intestinal fibrosis and the underlying mechanisms remain largely unexplored. Herein GCGR and GLP1R were found to be reduced in the stenotic ileum of patients with Crohn's disease as well as in the fibrotic colon of mice with chronic colitis. The downregulation of GCGR and GLP1R led to the accumulation of the metabolic byproduct lactate, resulting in histone H3K9 lactylation and exacerbated intestinal fibrosis through epithelial-to-mesenchymal transition (EMT). Dual activating GCGR and GLP1R by peptide 1907B reduced the H3K9 lactylation in epithelial cells and ameliorated intestinal fibrosis in vivo. We uncovered the role of GCGR/GLP1R in regulating EMT involved in intestinal fibrosis via histone lactylation. Simultaneously activating GCGR/GLP1R with the novel dual agonist peptide 1907B holds promise as a treatment strategy for alleviating intestinal fibrosis.

OBJECTIVES: To evaluate the performance of a multi-constraint representation learning classification model for identifying ovarian cancer with missing laboratory indicators. METHODS: Tabular data with missing laboratory indicators were collected from 393 patients with ovarian cancer and 1951 control patients. The missing ovarian cancer laboratory indicator features were projected to the latent space to obtain a classification model using the representational learning classification model based on discriminative learning and mutual information coupled with feature projection significance score consistency and missing location estimation. The proposed constraint term was ablated experimentally to assess the feasibility and validity of the constraint term by accuracy, area under the ROC curve (AUC), sensitivity, and specificity. Cross-validation methods and accuracy, AUC, sensitivity and specificity were also used to evaluate the discriminative performance of this classification model in comparison with other interpolation methods for processing of the missing data. RESULTS: The results of the ablation experiments showed good compatibility among the constraints, and each constraint had good robustness. The cross-validation experiment showed that for identification of ovarian cancer with missing laboratory indicators, the AUC, accuracy, sensitivity and specificity of the proposed multi-constraints representation-based learning classification model was 0.915, 0.888, 0.774, and 0.910, respectively, and its AUC and sensitivity were superior to those of other interpolation methods. CONCLUSIONS The proposed model has excellent discriminatory ability with better performance than other missing data interpolation methods for identification of ovarian cancer with missing laboratory indicators.
Female ; Humans ; Ovarian Neoplasms/diagnosis* ; Machine Learning ; ROC Curve

Objective: To discover molecular markers associated with lung adenocarcinoma diagnosis/prognosis and drug resistance through screening of differentially expressed genes based on published chip data in gene expression databases using bioinformatics methods. Methods: Comprehensive analysis was performed in available mRNA microarray datasets including lung adenocarcinoma tissues dataset GSE32863 and lung adenocarcinoma taxane-platin resistance dataset GSE77209 from the gene expression omnibus(GEO) database. Gene ontology enrichment analysis, gene pathway enrichment analysis and protein interaction network analysis were performed based on significantly correlated genes. The expression level of genes was validated in the cancer genome atlas(TCGA) dataset. Survival differences were assessed by the log-rank test in TCGA lung adenocarcinoma dataset. Based on the publications genomics of drug sensitivity in cancer(GDSC) database in CellMiner cross database(CellMiner CDB), Pearson correlation analysis was used to analyze the correlation between differentially expressed genes and the half-maximal inhibitory concentration(IC50) of anticancer drugs. Results : There were a total of 77 genes which had a different expression in resistance lung adenocarcinoma cells and lung adenocarcinoma cancer tissues. The functional enrichment analysis showed that these co-different expression genes were mainly enriched in microtubule, extracellular exosome, cell cycle and signaling by nuclear receptors. Protein-protein interactions(PPI) network screened 6 most connected genes as molecular complex(MCODE). Among the MCODE, overexpressed ubiquitin conjugating enzyme E2 T(UBE2T), kinesin family member 20A(KIF20A), PCNA clamp associated factor(KIAA0101), pituitary tumor-transforming gene 1(PTTG1) and NIMA related kinase 2(NEK2) were associated with poor outcomes. Survival analysis results showed that these five genes were upregulated in lung adenocarcinoma tissues and drug-resistant cells and were significantly associated with poor prognosis in lung adenocarcinoma patients. Drug sensitivity analysis results suggested that high expression of PTTG1 and UBE2T was significantly associated with sensitivity to multiple anticancer drugs, including paclitaxel and docetaxel. RT-PCR validation showed that PTTG1 andUBE2T were highly expressed in docetaxel-resistant cells A549-TXR and H358-TXR. Conclusion PTTG1 andUBE2T holds the potential to be chemoresistance markers in lung adenocarcinoma.