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.

PURPOSE: The retear rate of rotator cuff (RC) after surgery is high, and the rapid and functional enthesis regeneration remains a challenge. Whether acellular amniotic membrane (AAM) helps to promote the healing of tendon to bone and which treatment is better are both unclear. The study aims to investigate the effect of AAM on the healing of RC and the best treatment for RC repair. METHODS: Thirty-three Sprague Dawley rats underwent RC transection and repair using microsurgical techniques and were randomly divided into the suturing repair only (SRO) group (n = 11), the AAM overlaying (AOL) group (n = 11), and the AAM interposition (AIP) group (n = 11), respectively. Rats were sacrificed at 4 weeks, then examined by subsequent micro-CT, and evaluated by histologic and biomechanical tests. The statistical analyses of one-way ANOVA or Kruskal-Wallis test were performed using with SPSS 23.0. A p < 0.05 was considered a significant difference. RESULTS: AAM being intervened between tendon and bone (AIP group) or overlaid over tendon to bone junction (AOL group) in a rat model, promoted enthesis regeneration, increased new bone and cartilage generation, and improved collagen arrangement and biomechanical properties in comparison with suturing repair only (SRO group) (AOL vs. SRO, p < 0.001, p = 0.004, p = 0.003; AIP vs. SRO, p < 0.001, p < 0.001, p < 0.001). Compared with the AOL group, the AIP group had better results in micro-CT evaluation, histological score, and biomechanical testing (p = 0 0.039, p = 0.011, p = 0.003, respectively). CONCLUSION In the RC repair model, AAM enhanced regeneration of the tendon to bone junction. This regeneration was more effective when the AAM was intervened at the tendon to bone interface than overlaid above the tendon to bone junction.
Animals ; Rats, Sprague-Dawley ; Rotator Cuff Injuries/surgery* ; Amnion/transplantation* ; Rats ; Wound Healing ; Rotator Cuff/surgery* ; Male ; X-Ray Microtomography ; Tendons/surgery* ; Biomechanical Phenomena

Compounds isolated from Epimedium include the total flavonoids of Epimedium , icariin, and its metabolites (icaritin, icariside I, and icariside II), which have similar molecular structures. Modern pharmacological research and clinical practice have proved that Epimedium and its active components have a wide range of pharmacological effects, especially in improving sexual function, hormone regulation, anti-osteoporosis, immune function regulation, anti-oxidation, and anti-tumor activity. To date, we still need a comprehensive source of knowledge about the pharmacological effects of Epimedium and its bioactive compounds on the male reproductive system. However, their actions in other tissues have been reviewed in recent years. This review critically focuses on the Epimedium , its bioactive compounds, and the biochemical and molecular mechanisms that modulate vital pathways associated with the male reproductive system. Such intrinsic knowledge will significantly further studies on the Epimedium and its bioactive compounds that protect the male reproductive system and provide some guidances for clinical treatment of related male reproductive disorders.
Male ; Epimedium/chemistry* ; Humans ; Genitalia, Male/drug effects* ; Flavonoids/therapeutic use* ; Animals

A previous study showed that the length of the foreskin plays a role in the risk of sexually transmitted infections and chronic prostatitis, which can lead to poor quality of sexual life. Here, the association between foreskin length and sexual dysfunction was evaluated. A total of 5700 participants were recruited from the andrology clinic at The First Affiliated Hospital of University of Science and Technology of China (Hefei, China). Clinical characteristics, including foreskin length, were collected, and sexual function was assessed by the International Index of Erectile Function-5 (IIEF-5) and Premature Ejaculation Diagnostic Tool (PEDT) questionnaires. Men with sexual dysfunction were more likely to have redundant foreskin than men without sexual dysfunction. Among the 2721 erectile dysfunction (ED) patients and 1064 premature ejaculation (PE) patients, 301 (11.1%) ED patients and 135 (12.7%) PE patients had redundant foreskin, respectively. Men in the PE group were more likely to have redundant foreskin than men in the non-PE group ( P = 0.004). Logistic regression analyses revealed that the presence of redundant foreskin was associated with increased odds of moderate/severe ED (adjusted odds ratio [aOR] = 1.31, adjusted P = 0.04), moderate PE (aOR = 1.38, adjusted P = 0.02), and probable PE (aOR = 1.37, adjusted P = 0.03) after adjusting for confounding variables. Our study revealed a positive correlation between the presence of redundant foreskin and the risk of sexual dysfunction, especially in PE patients. Assessment of the length of the foreskin during routine clinical diagnosis may provide information for patients with sexual dysfunction.
Humans ; Male ; Foreskin ; Cross-Sectional Studies ; Adult ; Erectile Dysfunction/epidemiology* ; Premature Ejaculation/epidemiology* ; Middle Aged ; China/epidemiology* ; Surveys and Questionnaires ; Sexual Dysfunction, Physiological/epidemiology* ; Young Adult

OBJECTIVES: To explore the mediating role of sleep duration in the relationship between depression symptoms and myopia among middle school students. METHODS: This study was a cross-sectional research conducted using a stratified cluster random sampling method. A total of 1 728 middle school students were selected from two junior high schools and two senior high schools in certain urban areas and farms of the Xinjiang Production and Construction Corps. Questionnaire surveys and vision tests were conducted among the students. Spearman analysis was used to analyze the correlation between depression symptoms, sleep duration, and myopia. The Bootstrap method was employed to investigate the mediating effect of sleep duration between depression symptoms and myopia. RESULTS: The prevalence of myopia in the overall population was 74.02% (1 279/1 728), with an average sleep duration of (7.6±1.0) hours. The rate of insufficient sleep was 83.62% (1 445/1 728), and the proportion of students exhibiting depression symptoms was 25.29% (437/1 728). Correlation analysis showed significant negative correlations between visual acuity in both eyes and sleep duration with depressive emotions as measured by the Center for Epidemiologic Studies Depression Scale (with correlation coefficients of -0.064, -0.084, and -0.199 respectively; P<0.01), as well as with somatic symptoms and activities (with correlation coefficients of -0.104, -0.124, and -0.233 respectively; P<0.01) and interpersonal relationships (with correlation coefficients of -0.052, -0.059, and -0.071 respectively; P<0.05). The correlation coefficients for left and right eye visual acuity and sleep duration were 0.206 and 0.211 respectively (P<0.001). Sleep duration exhibited a mediating effect between depression symptoms and myopia (indirect effect=0.056, 95%CI: 0.029-0.088), with the mediating effect value for females (indirect effect=0.066, 95%CI: 0.024-0.119) being higher than that for males (indirect effect=0.042, 95%CI: 0.011-0.081). CONCLUSIONS Sleep duration serves as a partial mediator between depression symptoms and myopia in middle school students.
Humans ; Myopia/etiology* ; Male ; Female ; Depression/physiopathology* ; Cross-Sectional Studies ; Sleep ; Adolescent ; Students ; Child ; Time Factors ; Sleep Duration

OBJECTIVE: To investigate a family with hereditary coagulation factor XI (FXI) deficiency, identify its possible genetic etiology, analyze the bleeding risk of the proband, and provide a blood transfusion regimen. METHODS: The blood samples from the family members were collected, and the coagulation parameters of the proband and her family members were detected. Whole-exome sequencing was performed on the blood samples of the proband to identify gene variants, and validate the variants in the family using Sanger sequencing. Bioinformatics softwares were used to analyze the conservation of amino acid variant sites and the impact of the variations on protein function. The pathogenicity of the variant sites was analyzed according to the genetic variation classification criteria and guidelines of the American College of Medical Genetics and Genomics (ACMG). Thromboelastography (TEG) was used to assess the coagulation function of the family members and evaluate the transfusion regimen and its efficacy in the proband. RESULTS: The activated partial thromboplastin time (APTT) of the proband was significantly prolonged to 96.7 seconds, and FXI activity (FXI: C) and FXI antigen (FXI: Ag) decreased to 1.3% and 1%, respectively, both of which were extremely reduced. The FXI: C of the proband's father was also significantly lower than the normal value. The TEG results showed that the coagulation function of the proband was reduced, while the coagulation function of other family members was normal. The F11 gene of the proband exhibited compound heterozygous variants of c.738G>A (p.Trp246 *) and c.1288G>A (p.Ala430Thr). The proband's father carried a heterozygous missense variant of c.1288G>A (p.Ala430Thr), while her mother, her eldest daughter, and her youngest daughter carried a heterozygous nonsense variant of c.738G>A (p.Trp246 *). According to the ACMG genetic variation classification criteria and guidelines, c.738G>A (p.Trp246 *) is classified as a pathogenic variant (PVS1+PS3-Moderate+PP4), and c.1288G>A (p.Ala430Thr) is classified as a possible pathogenic variant (PS3-Moderate+PM1+PM3_Srong+PP4). p.Trp246 and p.Ala430 are highly conserved across different species. Swiss PdbViewer software analysis showed that p.Ala430Thr variant caused a change in the number of hydrogen bonds in FXI protein, affecting protein function. The following transfusion regimen was determined through TEG evaluation in vitro: 600 ml of fresh frozen plasma (FFP) was administered 24 hours before surgery to prevent bleeding. And there was no significant bleeding during or after the surgery. CONCLUSION The heterozygous nonsense variant ofc.738G>A (p.Trp246 *) and the heterozygous missense variant of c.1288G>A (p.Ala430Thr) in the F11 gene are the pathogenic factors of this hereditary FXI deficiency family.
Humans ; Factor XI Deficiency/therapy* ; Factor XI/genetics* ; Blood Transfusion ; Pedigree ; Female ; Male ; Mutation ; Thrombelastography ; Partial Thromboplastin Time ; Blood Coagulation ; Adult

OBJECTIVE: To evaluate the anti-hepatocellular carcinoma (HCC) activity of total alkaloids from Gelsemium elegans Benth. (TAG) in vivo and in vitro and to elucidate their potential mechanisms of action through transcriptomic analysis. METHODS: TAG extraction was conducted, and the primary components were quantified using high-performance liquid chromatography (HPLC). The effects of TAG (100, 150, and 200 µg/mL) on various tumor cells, including SMMC-7721, HepG2, H22, CAL27, MCF7, HT29, and HCT116, were assessed. Effects of TAG on HCC proliferation and apoptosis were detected by colony formation assays and cell stainings. Caspase-3, Bcl-2, and Bax protein levels were detected by Western blotting. In vivo, a tumor xenograft model was developed using H22 cells. Totally 40 Kunming mice were randomly assigned to model, cyclophosphamide (20 mg/kg), TAG low-dose (TAG-L, 0.5 mg/kg), and TAG high-dose (TAG-H, 1 mg/kg) groups, with 10 mice in each group. Tumor volume, body weight, and tumor weight were recorded and compared during 14-day treatment. Immune organ index were calculated. Tissue changes were oberseved by hematoxylin and eosin staining and immunohistochemistry. Additionally, transcriptomic and metabolomic analyses, as well as quatitative real-time polymerase chain reaction (RT-qPCR), were performed to detect mRNA and metabolite expressions. RESULTS: HPLC successfully identified the components of TAG extraction. Live cell imaging and analysis, along with cell viability assays, demonstrated that TAG inhibited the proliferation of SMMC-7721, HepG2, H22, CAL27, MCF7, HT29, and HCT116 cells. Colony formation assays, Hoechst 33258 staining, Rhodamine 123 staining, and Western blotting revealed that TAG not only inhibited HCC proliferation but also promoted apoptosis (P<0.05). In vivo experiments showed that TAG inhibited the growth of solid tumors in HCC in mice (P<0.05). Transcriptomic analysis and RT-qPCR indicated that the inhibition of HCC by TAG was associated with the regulation of the key gene CXCL13. CONCLUSION TAG inhibits HCC both in vivo and in vitro, with its inhibitory effect linked to the regulation of the key gene CXCL13.
Animals ; Apoptosis/drug effects* ; Liver Neoplasms/genetics* ; Carcinoma, Hepatocellular/genetics* ; Humans ; Alkaloids/therapeutic use* ; Gelsemium/chemistry* ; Cell Line, Tumor ; Cell Proliferation/drug effects* ; Mice ; Xenograft Model Antitumor Assays

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.