Objective: Machine learning (ML) has been reported to have better predictive capability than traditional statistical techniques. The aim of this study was to assess the efficacy of ML algorithms and logistic regression (LR) for predicting depressive symptoms during the COVID-19 pandemic. Methods: Analyses were carried out in a national cross-sectional study involving 21,916 participants. The ML algorithms in this study included random forest (RF), support vector machine (SVM), neural network (NN), and gradient boosting machine (GBM) methods. The performance indices were sensitivity, specificity, accuracy, precision, F1-score, and area under the receiver operating characteristic curve (AUC). Results: LR and NN had the best performance in terms of AUCs. The risk of overfitting was found to be negligible for most ML models except for RF, and GBM obtained the highest sensitivity, specificity, accuracy, precision, and F1-score. Therefore, LR, NN, and GBM models ranked among the best models. Conclusion Compared with ML models, LR model performed comparably to ML models in predicting depressive symptoms and identifying potential risk factors while also exhibiting a lower risk of overfitting.

Objective: Machine learning (ML) has been reported to have better predictive capability than traditional statistical techniques. The aim of this study was to assess the efficacy of ML algorithms and logistic regression (LR) for predicting depressive symptoms during the COVID-19 pandemic. Methods: Analyses were carried out in a national cross-sectional study involving 21,916 participants. The ML algorithms in this study included random forest (RF), support vector machine (SVM), neural network (NN), and gradient boosting machine (GBM) methods. The performance indices were sensitivity, specificity, accuracy, precision, F1-score, and area under the receiver operating characteristic curve (AUC). Results: LR and NN had the best performance in terms of AUCs. The risk of overfitting was found to be negligible for most ML models except for RF, and GBM obtained the highest sensitivity, specificity, accuracy, precision, and F1-score. Therefore, LR, NN, and GBM models ranked among the best models. Conclusion Compared with ML models, LR model performed comparably to ML models in predicting depressive symptoms and identifying potential risk factors while also exhibiting a lower risk of overfitting.

Objective: Machine learning (ML) has been reported to have better predictive capability than traditional statistical techniques. The aim of this study was to assess the efficacy of ML algorithms and logistic regression (LR) for predicting depressive symptoms during the COVID-19 pandemic. Methods: Analyses were carried out in a national cross-sectional study involving 21,916 participants. The ML algorithms in this study included random forest (RF), support vector machine (SVM), neural network (NN), and gradient boosting machine (GBM) methods. The performance indices were sensitivity, specificity, accuracy, precision, F1-score, and area under the receiver operating characteristic curve (AUC). Results: LR and NN had the best performance in terms of AUCs. The risk of overfitting was found to be negligible for most ML models except for RF, and GBM obtained the highest sensitivity, specificity, accuracy, precision, and F1-score. Therefore, LR, NN, and GBM models ranked among the best models. Conclusion Compared with ML models, LR model performed comparably to ML models in predicting depressive symptoms and identifying potential risk factors while also exhibiting a lower risk of overfitting.

Objective: Machine learning (ML) has been reported to have better predictive capability than traditional statistical techniques. The aim of this study was to assess the efficacy of ML algorithms and logistic regression (LR) for predicting depressive symptoms during the COVID-19 pandemic. Methods: Analyses were carried out in a national cross-sectional study involving 21,916 participants. The ML algorithms in this study included random forest (RF), support vector machine (SVM), neural network (NN), and gradient boosting machine (GBM) methods. The performance indices were sensitivity, specificity, accuracy, precision, F1-score, and area under the receiver operating characteristic curve (AUC). Results: LR and NN had the best performance in terms of AUCs. The risk of overfitting was found to be negligible for most ML models except for RF, and GBM obtained the highest sensitivity, specificity, accuracy, precision, and F1-score. Therefore, LR, NN, and GBM models ranked among the best models. Conclusion Compared with ML models, LR model performed comparably to ML models in predicting depressive symptoms and identifying potential risk factors while also exhibiting a lower risk of overfitting.

Objective To explore the correlation between the rs7296288 single nucleotide polymorphism(SNP)of the DHH gene and the onset of depression.Methods From March 2018 to December 2019,480 patients with depression in Sichuan Provincial People's Hospital,Jining Mental Hospital,Yunnan Mental Health Center were collected as the case group,and 329 patients without depression were collected as the control group.Peripheral blood samples were collected and DNA was extracted.After multiple amplification and high-throughput sequencing,statistical software was used to analyze the relevant data.Results The rs7296288 polymorphism of the DHH gene,the AA genotype was 32.9％in the control group and 36.7％in the case group,with no statistical difference;the AC genotype was 52.8％in the control group and 47.7％in the case group,with no statistical difference;the CC genotype was 14.3％in the control group and 15.6％in the case group,with no statistical difference.The co-dominant,dominant,and recessive statistical models were not statistically significant.Subgroup analysis of the degree of depressive episodes,suicide attempts,and first-episode patients did not find an association between the rs7296288 SNP locus of the DHH gene and the clinical features of depression,that is,the SNP rs7296288 of the DHH gene had no significant correlation with depression.Conclusion The rs7296288 polymorphism of DHH gene is not correlated with the pathogenesis of depression.

Objective To explore the relationship between NANOS3 and P-bodies in oocytes and the mechanism of their interaction during early oogenesis.Methods The co-localization of NANOS3 and dead box helicase 6(DDX6)in day post postnatal 1(1dpp)mouse oocytes was observed by immunofluorescence,and the interaction between NANOS3 and DDX6 was detected by immunoprecipitation.NANOS3 and DDX6 full-length plasmids were constructed to transfect HEK293T cells,and the mechanism of their interaction was investigated by immunofluorescence and immunoprecipitation.NANOS3 transfected HeLa cells to investigate whether NANOS3 had the ability of liquid-liquid phase separation(LLPS)by live-cell imaging.The proteins recruited by P-bodies in early oogenesis were identified by DDX6-immunoprecipitation-mass spectrometry(DDX6-IP-MS).Results NANOS3 and DDX6 colocalized and interacted with each other in 1dpp mouse oocytes.However,the co-localization of NANOS3 and DDX6 was not observed in HEK293T cells that had been transfected,but co-immunoprecipitation still demonstrated an interaction between these two proteins.Besides,live-cell imaging revealed that NANOS3 exhibited dynamic fluid-like properties within cells,which may promote the formation of P-bodies through LLPS.Finally,DDX6-IP-MS revealed that DDX6 might recruit NANOS3 into P-bodies by binding to the NANOS3 interacting protein Pumilio.Conclusion NANOS3 serves as a specific component of P-bodies in neonatal oocytes and may be involved in the regulation of early oogenesis.

Objective To investigate the effect of Huangqi Shengmai Yin(HSY)on myocardial fibrosis in rats with acute myocardial infarction(AMI)by adjusting P2X purinoceptor 7(P2X7R)/NOD-like receptor protein 3(NLRP3)pathway.Methods Sixty rats were divied into a sham operation group and model group(5 groups),with 10 rats in each group.The AMI rat model was constructed by ligating the left anterior descending branch and randomly grouped into AMI group,the HSY-low group(intragastric administration of 1.6 ml/kg HSY),the HSY group(intragastric administration of 6.2 ml/kg HSY),the compound miltiorhiza group(intragastric administration of 300 mg/kg),and the HSY-high+P2X7R agonist-ATP group(intragastric administration of 6.2 ml/kg HSY,and tail vein administration of 10 mmol/L ATP).After the intervention,cardiac function,myocardial injury and inflammatory factor markers were detected.The tissue sections were prepared to examine pathological changes,myocardial fibrosis,type Ⅰ and type Ⅲ collagen(COL1A1,COL3A1).Western blotting was performed to detecte the protein expression of P2X7R,NLRP3,tumor necrosis factor-α(TNF-α),interleukin-1β(IL-1β),and the expression of activated Caspase-1.Results Compared with the sham surgery group,the AMI group showed an increase in the left ventricular end diastolic diameter(LVEDD),the coatent of brain natriuretic peptide(BNP)and cardiac troponin I(cTn I),fibrosis volume fraction,the positive expression of COL1A1,COL3A1,TNF-α,IL-1β,P2X7R,NLRP3,and activated Caspase-1 proteins(P＜0.05),and a decrease in left ventricular ejection fraction(LVEF)(P＜0.05).The HSY-low group,HSY-high groups,and compound miltiorhiza group showed a decrease in LVEDD,the content of BNP and cTn I,fibrosis volume fraction,the positive expression of COL1A1 and COL3A1,TNF-α,IL-1β,P2X7R,NLRP3,and activated Caspase-1 proteins(P＜0.05),and an increase in LVEF than these in the AMI group(P＜0.05).The HSY-high+ATP group showed an increase in LVEDD,the content of BNP,cTn I,fibrosis volume fraction,the positive expression of COL1A1 and COL3A1,TNF-α,IL-1β,P2X7R,NLRP3,and activated Caspase-1 proteins(P＜0.05),and a decrease in LVEF than those in the HSY-high group(P＜0.05).Conclusion HSY inhibits P2X7R/NLRP3 pathway to alleviate myocardial fibrosis in AMI rats.

Accurate timing of myelination is crucial for the proper functioning of the central nervous system. Here, we identified a de novo heterozygous mutation in TMEM63A (c.1894G>A; p. Ala632Thr) in a 7-year-old boy exhibiting hypomyelination. A Ca²⁺ influx assay suggested that this is a loss-of-function mutation. To explore how TMEM63A deficiency causes hypomyelination, we generated Tmem63a knockout mice. Genetic deletion of TMEM63A resulted in hypomyelination at postnatal day 14 (P14) arising from impaired differentiation of oligodendrocyte precursor cells (OPCs). Notably, the myelin dysplasia was transient, returning to normal levels by P28. Primary cultures of Tmem63a^-/- OPCs presented delayed differentiation. Lentivirus-based expression of TMEM63A but not TMEM63A_A632T rescued the differentiation of Tmem63a^-/- OPCs in vitro and myelination in Tmem63a^-/- mice. These data thus support the conclusion that the mutation in TMEM63A is the pathogenesis of the hypomyelination in the patient. Our study further demonstrated that TMEM63A-mediated Ca²⁺ influx plays critical roles in the early development of myelin and oligodendrocyte differentiation.
Animals ; Cell Differentiation/physiology* ; Oligodendroglia/metabolism* ; Mice, Knockout ; Mice ; Male ; Myelin Sheath/metabolism* ; Humans ; Child ; Cells, Cultured ; Oligodendrocyte Precursor Cells/metabolism*

Objective:To investigate the efficacy and safety of lenvatinib plus drug-eluting bead transarterial chemoembolization (DEB-TACE) and FOLFOX-based hepatic arterial infusion chemotherapy (Len+DEB-TACE+HAIC) versus lenvatinib plus DEB-TACE (Len+DEB-TACE) for hepatocellular carcinoma (HCC) larger than 7 cm with portal vein tumor thrombosis (PVTT).Methods:The data from patients diagnosed with HCC (>7 cm) and PVTT who received either Len+DEB-TACE+HAIC ( n=99) or Len+DEB-TACE ( n=102) between July 2019 and June 2021 at six institutions in China were collected and retrospectively analyzed. Tumor responses were evaluated based on modified Response Evaluation Criteria in Solid Tumors. Objective response rate (ORR), disease control rate (DCR), time to progression (TTP), overall survival (OS), and treatment-related adverse event (TRAE) were compared between the two groups by propensity score matching. Subgroup analyses were performed for TTP and OS. Results:After propensity score matching, 83 pairs of patients were included in the study cohorts. The ORR for the Len+DEB-TACE+HAIC group and the Len+DEB-TACE group was 66.3% and 38.6% ( χ2=12.78, P<0.001), respectively. The DCR for the Len+DEB-TACE+HAIC group and the Len+DEB-TACE group was 91.6% and 79.5% ( χ2=4.87, P=0.027), respectively. The median TTP and median OS for the Len+DEB-TACE+HAIC group were significantly longer than those for the Len+DEB-TACE group (TTP, 10.1 months vs. 6.1 months, χ2=35.28, P<0.001; OS, 17.3 months vs. 12.9 months, χ2=16.84, P<0.001). The incidence of ≥grade 3 TRAEs was 38.6% in the Len+DEB-TACE+HAIC group and 33.7% in the Len+DEB-TACE group ( χ2=0.42, P=0.518). Conclusion:Compared with Len+DEB-TACE, Len+DEB-TACE+HAIC led to improved tumor response, TTP and OS with an acceptable safety profile in patients with large HCC and PVTT.

Objective To investigate Candida albicans(C.auris)colonization in patients and environmental con-tamination of non-intensive care unit(non-ICU)in a hospital,and evaluate the effectiveness of infection prevention and control measures in non-ICU.Methods In March 2024,a paraplegic patient admitted to the department of re-habilitation medicine was found to have C.auris in both urinary catheter and urine culture.The patient was immedia-tely isolated in single room,and patient transfer-in/out of non-ICU was suspended.Fungal cultures were performed on specimens from the ward environment,caregivers,doctors,nurses,and co-hospitalized patients.Mass spec-trometry and molecular biology techniques were used for strain identification and cluster analysis.Contact isolation was conducted on patient.Prevention and control measures were taken,including strict hand hygiene,1 000 mg/L chlorine-based(sodium hypochlorite)disinfection,2％chlorhexidine decolonization,and terminal disinfection of pa-tient-contact items.After discharge,these measures continued with regular C.auris surveillance.Results Five strains of C.auris were isolated from the patient's urine,urinary catheter,inguinal swab,perianal swab,and bed rail swab.Protein mass spectrometry cluster analysis confirmed clonal relatedness of all isolates.The strain showed resistance to fluconazole and amphotericin B,but susceptibility to echinocandins.No C.auris was detected from healthcare workers'hand/axillary/groin swabs.After intervention(such as decolonization and environmental disin-fection),follow-up cultures were negative for C.auris.Conclusion Based on the characteristics of admitted pa-tients,non-ICU should implement active prevention and control measures including:admission screening,contact precautions,object surface microbiological monitoring,decolonization,environmental disinfection,and community management.Hand hygiene,contact isolation,and terminal disinfection are crucial for preventing C.auris trans-mission.