Objective: The cross sectional study aimed to identify predominant co-occurrence patterns among six common mental health issues in college students, so as to provide empirical basis for designing targeted interventions. Methods: From October 2024, a total of 9 837 students from 4 universities in Xiangtan City, Hunan Province, participated in the current study by multistage random cluster sampling method. Participants completed self report measures, including the Patient Health Questionnaire-9 (PHQ-9), Generalized Anxiety Disorder 7 item Scale (GAD-7), Young s Internet Addiction Diagnostic Questionnaire, the Adolescent Insomnia Symptom Self rating Scale, the Ottawa Self injury Inventory, and the Brief Community Assessment of Psychic Experiences Questionnaire. Demographic and co-occurrence characteristics were first compared using Chi square or trend Chi-square tests, followed by application of the Apriori algorithm to mine association rules for primary co-occurrence patterns. Results: The detection rate of co-occuring the common mental health issues was 46.44%. The detection rate was significantly higher in female than in male students (50.42%, 43.61%; χ 2=44.46) and in students from rural versus urban areas (47.22%, 44.60%; χ 2=5.67) (both P <0.05). Significant differences were observed among freshmen, sophomores, juniors, and seniors (46.63%, 48.35%, 45.05% , 43.66%, respectively; χ 2=9.22, P <0.05), although no statistically significant trend was detected ( χ 2 trend =3.75, P = 0.05 ). Association rule mining identified “anxiety + depression” “anxiety + psychotic experiences + depression” and “anxiety + sleep disorder + depression” as the combinations with the highest support. In addition, “anxiety+depression+Internet addiction+psychotic experiences =>sleep disorder (>= refered to the occurrence of the latter item under the condition that the former item occurs)” and “anxiety + depression+Internet addiction=>sleep disorder” were combinations with relatively high confidence. Conclusions Co-occurrence of these mental health issues among college students is high and exhibits diverse patterns. Strategies to address this burden should prioritize integrated interventions that target these specific combinations of factors.

Objective: To understand the impact of childhood trauma on psychological distress among upper grade elemetary school students, and to explore the mediating role of leisure activities in the relationship, so as to provide a basis for developing mental health intervention strategies. Methods: From August to November 2024, a combination of convenience sampling and stratified cluster random sampling was employed to recruit 1 373 fourth to sixth grade students from four primary schools in Harbin. The Childhood Trauma Questionnaire(CTQ), a self designed leisure activity scale (including active and passive leisure activities), and the Kessler Psychological Distress Scale (K10) were used to assess childhood trauma experiences, leisure activities, and levels of psychological distress. Spearman correlation analysis and linear regression analysis were conducted to explore the relationships among childhood trauma, leisure types, leisure time, and psychological distress. Based on the mediation analysis framework proposed by Hayes (Model 4), the mediating role of leisure types in the relationship between childhood trauma and psychological distress was examined. Results: Totally 19.1% of the upper elemetary school students exhibited psychological distress, while 30.2% had experienced childhood trauma. During school days, 64.6% of the students were reported of having leisure time concentrated between 1 and 5 hours per day, whereas 67.4% reported leisure time exceeding 5 hours per day on weekends. After controlling for potential demographic confounders such as gender, grade, ethnicity, household registration, being an only child, parents educational level, co residence, and whether parents are first time married,linear regression analysis showed that childhood trauma experience had positive predictive effect on psychological distress in upper primary school students( β =0.20, P <0.01). Leisure time showed no statistically significant association with psychological distress, both on school days ( β =-0.58 to -0.56) and weekends ( β =0.26- 0.98 )(all P >0.05). Active leisure activities were negatively associated with psychological distress ( β =-0.20), while passive leisure activities were positively associated with psychological distress ( β =0.29)(both P <0.01). Leisure type partially mediated the relationship between childhood trauma and psychological distress, accounting for 11.7% of the indirect effect. Conclusion Childhood trauma experiences positively predict psychological distress in upper elementary school students, and affect psychological distress through active leisure and passive leisure.

Background: Influenza A virus (IAV) is a negative-sense RNA virus of the Orthomyxoviridae family and is the etiological agent of a highly contagious acute respiratory disease that can lead to acute lung injury. Objective: To elucidate the molecular mechanisms of IAV infection, an integrative research approach combining gene expression profiling, multinetwork analysis, and in vivo experimental validations was employed. Methods: First, a series of network-based analyses were performed, including protein-protein interaction network construction, weighted gene co-expression network analysis, and subsequent gene set enrichment analysis, to identify the major underlying mechanisms of IAV infection. Following gene expression analysis, core targets, both direct and indirect regulators, were screened. An IAV (H1N1) strain A/PR/8/34-induced acute lung injury mouse model was constructed for in vivo validations. Batch one included two groups to evaluate findings from the multi-network analysis: Mock (n = 10; 5 males and 5 females) and IAV (n = 10; 5 males and 5 females). Batch two included three groups to assess the role of toll-like receptor 3 (TLR3) in IAV infection: Mock (n = 6; 3 males and 3 females), IAV (n = 6; 3 males and 3 females), and TLR3 inhibitor (n = 6; 3 males and 3 females). Body weight was measured on days 0, 3, and 5 after infection. On day 5, lung tissues were collected to assess viral load and histopathological changes. Key targets were examined using enzyme-linked immunosorbent assay, Western blotting, and immunofluorescence staining, both in sera and lung tissues. Results: IAV infection was significantly associated with dysregulation of the immune-inflammation system, such as the LTR, nucle-otide-binding oligomerization domain-(NOD) like receptor, retinoic acid-inducible gene I-like receptor, and nuclear factor kappa-B signaling pathways. Gene set enrichment analysis further indicated that the TLR and necroptosis signaling pathways played crucial roles in the progression of IAV infection (TLR signaling pathway normalized enrichment score = 2.3941, P = 1.00 × 10 ⁻¹⁰; necroptosis normalized enrichment score = 1.9421, P = 6.21 × 10 ⁻⁷). Among the core targets, TLR3 and mixed lineage kinase domain-like protein (MLKL) may regulate gene expression at the transcriptional level (all P < 0.05). In vivo validation using an IAV (PR8) infected acute lung injury mouse model demonstrated increased viral load and lung index, alveolar structural damage, and inflammatory cell infiltration. Immunofluorescence staining exhibited large gaps in Lamin B1 staining and breaches in Emerin signals following IAV-PR8 infection. Expression levels of TLR3, p-receptor-interacting serine/threonine-protein kinase 3 (RIPK3)/RIPK3, and p-mixed lineage kinase domain-like protein (MLKL)/MLKL proteins in lung tissues, as well as proinflammatory factors and mediators in sera, were significantly elevated after IAV infection. Moreover, enhanced neutrophil infiltration (myeloperoxidase) and citrullinated histone H3 (a neutrophil extracellular trap-specific marker), both established indicators of neutrophil extracellular trap formation, were observed. Notably, treatment with a TLR3 inhibitor significantly ameliorated IAV-induced acute lung injury by regulating necroptosis-related targets. Conclusion: Our study provides network-based in vivo evidence that TLR3-receptor-interacting serine/threonine-protein kinase 3-MLKL-mediated necroptosis may underlie IAV-induced acute lung injury and could serve as a potential therapeutic target in severe influenza cases.

ObjectiveHepatocellular carcinoma (HCC) represents 90% of all primary liver cancers. The main risk factors associated with HCC include viral hepatitis (B and/or C), alcohol abuse, and metabolic dysfunction-associated steatotic liver disease (MASLD), which progressively advance to liver fibrosis, cirrhosis, and ultimately evolve into HCC. Surgical resection represents the most effective treatment for HCC, while recent advances in immunotherapy, including immune checkpoint inhibitors and adoptive cell therapies, have provided improved treatment prospects for patients with unresectable HCC. However, the complex metabolic heterogeneity of HCC limits the therapeutic efficacy. Metabolic intermediates acyl-CoA not only provide energy and substrates for numerous biochemical reactions but also serve as donors for protein lysine acylation, a major class of post-translational modification (PTM). Therefore, a deeper understanding of the molecular mechanisms underlying protein lysine acylation and hepatocarcinogenesis is urgently needed. MethodsThe levels of protein lysine acylation and silence information regulator 5 (SIRT5) expression levels in clinical HCC samples were analyzed by Western blot. Quantitative malonylome and succinylome of HCC samples were analyzed by antibody-based affinity enrichment coupled with tandem mass spectrometry. The proliferation of HCC cells was analyzed with Cell Counting Kit-8 (CCK-8) assays, the apoptosis was quantified by Annexin V-FITC/propidium iodide (PI) staining coupled with flow cytometry, and the ability of cells to migrate was assayed by Transwell assays. The enzymatic activity of glutathione S-transferase Mu 1 (GSTM1) was quantified. Transgenic mice with hepatic overexpression of SIRT5 were constructed using CRISPR-Cas9, and primary hepatocarcinogenesis was induced by administration of diethylnitrosamine. ResultsWestern blot analysis indicated that the expression level of SIRT5 was elevated in clinical samples from HCC patients, and the levels of lysine malonylation, glutarylation, and succinylation were significantly reduced in HCC tissues. Knockout of SIRT5 in MHCC-97H and MHCC-97L hepatoma cells suppressed cell proliferation, and increased the percentage of apoptotic cells significantly. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses of the differentially malonylome and succinylome of HCC samples revealed significant enrichment in two major classes of biological processes: core energy metabolism (e.g., glycolysis/gluconeogenesis, tricarboxylic acid metabolic process, fatty acid beta oxidation) and detoxification and oxidative stress response (e.g., response to toxic substance, chemical carcinogenesis, reactive oxygen species (ROS)). SIRT5 removes malonylation from lysine residues in GSTM1 and restores its detoxification activity, which is crucial for the survival of hepatocytes under stressed conditions. More importantly, in vivo experiment indicated that hepatic-specific overexpression of SIRT5 in mice accelerated diethylnitrosamine-induced liver fibrosis and hepatocarcinogenesis, indicating the critical role of SIRT5 in HCC progression. ConclusionThis study highlights the previously unrecognized SIRT5-GSTM1 axis as a key regulator in hepatocarcinogenesis, and suggests a potential target for the treatment of patients with HCC.

ObjectiveType I interferon (IFN-I) signaling is essential for antiviral innate immunity, yet its sustained or excessive activation contributes to the pathogenesis of several autoimmune diseases and interferonopathies, such as systemic lupus erythematosus and Aicardi-Goutières syndrome. Current strategies targeting this pathway, exemplified by JAK inhibitors, act mainly on downstream signal transduction and provide limited direct control over upstream IFN-I production, while also carrying the risk of broad immunosuppression. Phyllanthus emblica L. has long been used in traditional medicine for inflammatory disorders, but the bioactive constituent responsible for its regulation of IFN-I signaling and the underlying molecular mechanism have not been clearly defined. This study aimed to identify the active anti-inflammatory component of P. emblica and to characterize its mechanism of action on the IFN-I pathway in macrophages. MethodsActive components ofP. emblica and their candidate targets were screened by network pharmacology using the TCMSP and DrugBank databases (oral bioavailability≥30%, drug-likeness≥0.18) and intersected with inflammation-related genes retrieved from public databases. The predicted interaction between EGCG and IFN-I pathway proteins (TBK1, IRF3, STAT1) was evaluated by molecular docking, with BX795 and GSK8612 used as reference TBK1 inhibitors. Mechanistic experiments were performed in THP-1-derived macrophages and primary bone marrow-derived macrophages (BMDM). Upstream signaling was activated by transfection of the nucleic acid analogs poly(I∶C) and poly(dA∶dT) or by lipopolysaccharide (LPS) stimulation, whereas downstream signaling was activated by exogenous IFN-β. An siRNA-mediated TREX1 knockdown model was used to mimic endogenous nucleic acid-driven interferonopathy. Expression of IFN-β1 and interferon-stimulated genes (ISGs) was measured by RT-qPCR, protein phosphorylation by Western blot, and IFN-β secretion by ELISA. Cellular thermal shift assay (CETSA) and drug affinity responsive target stability (DARTS) were used to probe the interactionbetween EGCG and IRF3. ResultsNetwork pharmacology identified (-)-epigallocatechin-3-gallate (EGCG) as a candidate IFN-I-suppressive constituent of P. emblica, with predicted binding to TBK1, IRF3, and STAT1. Molecular docking yielded binding energies of -9.2, -7.2, and -8.2 kcal/mol for TBK1, IRF3, and STAT1, respectively, indicating an affinity for TBK1 comparable to that of the reference inhibitors BX795 (-5.7 kcal/mol) and GSK8612 (-6.4 kcal/mol). EGCG suppressed IFN-β1 and ISG mRNA expression under poly (I∶C), poly (dA∶dT), and LPS stimulation in both THP-1 macrophages and BMDM. At the protein level, EGCG reduced the phosphorylation of TBK1 and IRF3 without affecting the levels of the upstream sensors cGAS and RIG-I, and lowered IFN-β secretion in a concentration-dependent manner. CETSA and DARTS showed that EGCG did not enhance the thermal stability or protease resistance of IRF3, indicating that its effect on IRF3 is indirect. Following IFN-β stimulation, prolonged EGCG treatment reduced STAT1 phosphorylation in a time-dependent manner without an apparent change in IRF9, and partially attenuated ISG transcription; this effect was not monotonicly concentration-dependent, and CXCL10 showed the most consistent suppression. In TREX1-knockdown cells, the elevated mRNA levels of ISG15, ISG56, and CXCL10 were reduced by EGCG. ConclusionEGCG suppresses IFN-I responses by concurrently inhibiting TBK1-IRF3-dependent IFN‑β production and JAK-STAT1-mediated downstream transcription. These in vitro findings provide a mechanistic basis for the anti-inflammatory use of P. emblica in traditional medicine and identify EGCG as a candidate for further evaluation in interferon-driven autoimmune disease models.

Background: and Purpose Symptomatic intracranial hemorrhage (sICH) following endovascular thrombectomy (EVT) is a severe complication associated with adverse functional outcomes and increased mortality rates. Currently, a reliable predictive model for sICH risk after EVT is lacking. Methods: This study used data from patients aged ≥20 years who underwent EVT for anterior circulation stroke from the nationwide Taiwan Registry of Endovascular Thrombectomy for Acute Ischemic Stroke (TREAT-AIS). A predictive model including factors associated with an increased risk of sICH after EVT was developed to differentiate between patients with and without sICH. This model was compared existing predictive models using nationwide registry data to evaluate its relative performance. Results: Of the 2,507 identified patients, 158 developed sICH after EVT. Factors such as diastolic blood pressure, Alberta Stroke Program Early CT Score, platelet count, glucose level, collateral score, and successful reperfusion were associated with the risk of sICH after EVT. The TREAT-AIS score demonstrated acceptable predictive accuracy (area under the curve [AUC]=0.694), with higher scores being associated with an increased risk of sICH (odds ratio=2.01 per score increase, 95% confidence interval=1.64–2.45, P<0.001). The discriminatory capacity of the score was similar in patients with symptom onset beyond 6 hours (AUC=0.705). Compared to existing models, the TREAT-AIS score consistently exhibited superior predictive accuracy, although this difference was marginal. Conclusions The TREAT-AIS score outperformed existing models, and demonstrated an acceptable discriminatory capacity for distinguishing patients according to sICH risk levels. However, the differences between models were only marginal. Further research incorporating periprocedural and postprocedural factors is required to improve the predictive accuracy.

Purpose: The genomic characteristics of uterine sarcomas have not been fully elucidated. This study aimed to explore the genomic landscape of the uterine sarcomas (USs). Materials and Methods: Comprehensive genomic analysis through RNA-sequencing was conducted. Gene fusion, differentially expressed genes (DEGs), signaling pathway enrichment, immune cell infiltration, and prognosis were analyzed. A deep learning model was constructed to predict the survival of US patients. Results: A total of 71 US samples were examined, including 47 endometrial stromal sarcomas (ESS), 18 uterine leiomyosarcomas (uLMS), three adenosarcomas, two carcinosarcomas, and one uterine tumor resembling an ovarian sex-cord tumor. ESS (including high-grade ESS [HGESS] and low-grade ESS [LGESS]) and uLMS showed distinct gene fusion signatures; a novel gene fusion site, MRPS18A–PDC-AS1 could be a potential diagnostic marker for the pathology differential diagnosis of uLMS and ESS; 797 and 477 uterine sarcoma DEGs (uDEGs) were identified in the ESS vs. uLMS and HGESS vs. LGESS groups, respectively. The uDEGs were enriched in multiple pathways. Fifteen genes including LAMB4 were confirmed with prognostic value in USs; immune infiltration analysis revealed the prognositic value of myeloid dendritic cells, plasmacytoid dendritic cells, natural killer cells, macrophage M1, monocytes and hematopoietic stem cells in USs; the deep learning model named Max-Mean Non-Local multi-instance learning (MMN-MIL) showed satisfactory performance in predicting the survival of US patients, with the area under the receiver operating curve curve reached 0.909 and accuracy achieved 0.804. Conclusion USs harbored distinct gene fusion characteristics and gene expression features between HGESS, LGESS, and uLMS. The MMN-MIL model could effectively predict the survival of US patients.

BACKGROUND:Osteoporotic fracture is the most serious complication of osteoporosis.Previous studies have demonstrated that gut microbiota has a regulatory effect on skeletal tissue and that gut microbiota has an important relationship with osteoporotic fracture,but the causal relationship between the two is unclear. OBJECTIVE:To explore the causal relationship between gut microbiota and osteoporotic fractures using Mendelian randomization method. METHODS:The genome-wide association study(GWAS)datasets of gut microbiota and osteoporotic fracture were obtained from the IEU Open GWAS database and the Finnish database R9,respectively.Using gut microbiota as the exposure factor and osteoporotic fracture as the outcome variable,Mendelian randomization analyses with random-effects inverse variance weighted,MR-Egger regression,weighted median,simple model,and weighted model methods were performed to assess whether there is a causal relationship between gut microbiota and osteoporotic fracture.Sensitivity analyses were performed to test the reliability and robustness of the results.Reverse Mendelian randomization analyses were performed to further validate the causal relationship identified in the forward Mendelian randomization analyses. RESULTS AND CONCLUSION:The results of this Mendelian randomization analysis indicated a causal relationship between gut microbiota and osteoporotic fracture.Elevated abundance of Actinomycetales[odds ratio(OR)=1.562,95%confidence interval(CI):1.027-2.375,P=0.037),Actinomycetaceae(OR=1.561,95%CI:1.027-2.374,P=0.037),Actinomyces(OR=1.544,95%CI:1.130-2.110,P=0.006),Butyricicoccus(OR=1.781,95%CI:1.194-2.657,P=0.005),Coprococcus 2(OR=1.550,95%CI:1.068-2.251,P=0.021),Family ⅩⅢ UCG-001(OR=1.473,95%CI:1.001-2.168,P=0.049),Methanobrevibacter(OR=1.274,95%CI:1.001-1.621,P=0.049),and Roseburia(OR=1.429,95%CI:1.015-2.013,P=0.041)would increase the risk of osteoporotic fractures in patients.Elevated abundance of Bacteroidia(OR=0.660,95%CI:0.455-0.959,P=0.029),Bacteroidales(OR=0.660,95%CI:0.455-0.959,P=0.029),Christensenellacea(OR=0.725,95%CI:0.529-0.995,P=0.047),Ruminococcaceae(OR=0.643,95%CI:0.443-0.933,P=0.020),Enterorhabdus(OR=0.558,95%CI:0.395-0.788,P=0.001),Eubacterium rectale group(OR=0.631,95%CI:0.435-0.916,P=0.016),Lachnospiraceae UCG008(OR=0.738,95%CI:0.546-0.998,P=0.048),and Ruminiclostridium 9(OR=0.492,95%CI:0.324-0.746,P=0.001)would reduce the risk of osteoporotic fractures in patients.We identified 16 gut microbiota associated with osteoporotic fracture by the Mendelian randomization method.That is,using gut microbiota as the exposure factor and osteoporotic fracture as the outcome variable,eight gut microbiota showed positive causal associations with osteoporotic fracture and another eight gut microbiota showed negative causal associations with osteoporotic fracture.The results of this study not only identify new biomarkers for the early prediction of osteoporotic fracture and potential therapeutic targets in clinical practice,but also provide an experimental basis and theoretical basis for the study of improving the occurrence and prognosis of osteoporotic fracture through gut microbiota in bone tissue engineering.

Testicular histology based on testicular biopsy is an important factor for determining appropriate testicular sperm extraction surgery and predicting sperm retrieval outcomes in patients with azoospermia. Therefore, we developed a deep learning (DL) model to establish the associations between testicular grayscale ultrasound images and testicular histology. We retrospectively included two-dimensional testicular grayscale ultrasound from patients with azoospermia (353 men with 4357 images between July 2017 and December 2021 in The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, China) to develop a DL model. We obtained testicular histology during conventional testicular sperm extraction. Our DL model was trained based on ultrasound images or fusion data (ultrasound images fused with the corresponding testicular volume) to distinguish spermatozoa presence in pathology (SPP) and spermatozoa absence in pathology (SAP) and to classify maturation arrest (MA) and Sertoli cell-only syndrome (SCOS) in patients with SAP. Areas under the receiver operating characteristic curve (AUCs), accuracy, sensitivity, and specificity were used to analyze model performance. DL based on images achieved an AUC of 0.922 (95% confidence interval [CI]: 0.908-0.935), a sensitivity of 80.9%, a specificity of 84.6%, and an accuracy of 83.5% in predicting SPP (including normal spermatogenesis and hypospermatogenesis) and SAP (including MA and SCOS). In the identification of SCOS and MA, DL on fusion data yielded better diagnostic performance with an AUC of 0.979 (95% CI: 0.969-0.989), a sensitivity of 89.7%, a specificity of 97.1%, and an accuracy of 92.1%. Our study provides a noninvasive method to predict testicular histology for patients with azoospermia, which would avoid unnecessary testicular biopsy.
Humans ; Male ; Azoospermia/diagnostic imaging* ; Deep Learning ; Testis/pathology* ; Retrospective Studies ; Adult ; Ultrasonography/methods* ; Sperm Retrieval ; Sertoli Cell-Only Syndrome/diagnostic imaging*

Nonobstructive azoospermia (NOA), one of the most severe types of male infertility, etiology often remains unclear in most cases. Therefore, this study aimed to detect four biallelic detrimental variants (0.5%) in the minichromosome maintenance domain containing 2 ( MCMDC2 ) genes in 768 NOA patients by whole-exome sequencing (WES). Hematoxylin and eosin (H&E) demonstrated that MCMDC2 deleterious variants caused meiotic arrest in three patients (c.1360G>T, c.1956G>T, and c.685C>T) and hypospermatogenesis in one patient (c.94G>T), as further confirmed through immunofluorescence (IF) staining. The single-cell RNA sequencing data indicated that MCMDC2 was substantially expressed during spermatogenesis. The variants were confirmed as deleterious and responsible for patient infertility through bioinformatics and in vitro experimental analyses. The results revealed four MCMDC2 variants related to NOA, which contributes to the current perception of the function of MCMDC2 in male fertility and presents new perspectives on the genetic etiology of NOA.
Humans ; Male ; Azoospermia/genetics* ; Meiosis/genetics* ; Spermatogenesis/genetics* ; Adult ; Exome Sequencing ; Microtubule-Associated Proteins/genetics* ; Alleles ; Infertility, Male/genetics*