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: 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.

This study aims to reveal the effect and mechanism of Gentianella turkestanorum total extract(GTI) in ameliorating non-alcoholic steatohepatitis(NASH). UPLC-Q-TOF-MS was employed to identify the chemical components in GTI. SwissTarget-Prediction, GeneCards, OMIM, and TTD were utilized to screen the targets of GTI components and NASH. The common targets shared by GTI components and NASH were filtered through the STRING database and Cytoscape 3.9.0 to identify core targets, followed by GO and KEGG enrichment analysis. AutoDock was used for molecular docking of key components with core targets. A mouse model of NASH was established with a methionine-choline-deficient high-fat diet. A 4-week drug intervention was conducted, during which mouse weight was monitored, and the liver-to-brain ratio was measured at the end. Hematoxylin-eosin staining, Sirius red staining, and oil red O staining were employed to observe the pathological changes in the liver tissue. The levels of various biomarkers, including aspartate aminotransferase(AST), alanine aminotransferase(ALT), hydroxyproline(HYP), total cholesterol(TC), triglycerides(TG), low-density lipoprotein cholesterol(LDL-C), high-density lipoprotein cholesterol(HDL-C), malondialdehyde(MDA), superoxide dismutase(SOD), and glutathione(GSH), in the serum and liver tissue were determined. RT-qPCR was conducted to measure the mRNA levels of interleukin 1β(IL-1β), interleukin 6(IL-6), tumor necrosis factor α(TNF-α), collagen type I α1 chain(COL1A1), and α-smooth muscle actin(α-SMA). Western blotting was conducted to determine the protein levels of IL-1β, IL-6, TNF-α, and potential drug targets identified through network pharmacology. UPLC-Q-TOF/MS identified 581 chemical components of GTI, and 534 targets of GTI and 1 157 targets of NASH were screened out. The topological analysis of the common targets shared by GTI and NASH identified core targets such as IL-1β, IL-6, protein kinase B(AKT), TNF, and peroxisome proliferator activated receptor gamma(PPARG). GO and KEGG analyses indicated that the ameliorating effect of GTI on NASH was related to inflammatory responses and the phosphoinositide 3-kinase(PI3K)/AKT pathway. The staining results demonstrated that GTI ameliorated hepatocyte vacuolation, swelling, ballooning, and lipid accumulation in NASH mice. Compared with the model group, high doses of GTI reduced the AST, ALT, HYP, TC, and TG levels(P<0.01) while increasing the HDL-C, SOD, and GSH levels(P<0.01). RT-qPCR results showed that GTI down-regulated the mRNA levels of IL-1β, IL-6, TNF-α, COL1A1, and α-SMA(P<0.01). Western blot results indicated that GTI down-regulated the protein levels of IL-1β, IL-6, TNF-α, phosphorylated PI3K(p-PI3K), phosphorylated AKT(p-AKT), phosphorylated inhibitor of nuclear factor kappa B alpha(p-IκBα), and nuclear factor kappa B(NF-κB)(P<0.01). In summary, GTI ameliorates inflammation, dyslipidemia, and oxidative stress associated with NASH by regulating the PI3K/AKT/NF-κB signaling pathway.
Animals ; Non-alcoholic Fatty Liver Disease/genetics* ; Mice ; Network Pharmacology ; Male ; Drugs, Chinese Herbal/administration & dosage* ; Chromatography, High Pressure Liquid ; Liver/metabolism* ; Mice, Inbred C57BL ; Humans ; Mass Spectrometry ; Tumor Necrosis Factor-alpha/metabolism* ; Disease Models, Animal ; Molecular Docking Simulation

This study aims to explore the mechanism through which Yishen Jiangtang Decoction(YSJTD) regulates endoplasmic reticulum stress(ERS)-mediated NOD-like receptor thermal protein domain associated protein 3(NLRP3) inflammasome to improve diabetic nephropathy(DN) in db/db mice. Thirty db/db mice were randomly divided into the model group, YSJTD group, ERS inhibitor 4-phenylbutyric acid(4-PBA) group, with 10 mice in each group. Additionally, 10 db/m mice were selected as the control group. The YSJTD group was orally administered YSJTD at a dose of 0.01 mL·g~(-1), the 4-PBA group was orally administered 4-PBA at a dose of 0.5 mg·g~(-1), and the control and model groups were given an equal volume of carboxylmethyl cellulose sodium. The treatments were administered once daily for 8 weeks. Food intake, water consumption, and body weight were recorded every 2 weeks. After the intervention, fasting blood glucose(FBG), glycosylated hemoglobin(HbA1c), urine microalbumin(U-mALB), 24-hour urine volume, serum creatinine(Scr), and blood urea nitrogen(BUN) were measured. Inflammatory markers interleukin-1β(IL-1β) and interleukin-18(IL-18) were detected using the enzyme-linked immunosorbent assay(ELISA). Renal pathology was assessed through hematoxylin-eosin(HE), periodic acid-Schiff(PAS), and Masson staining, and transmission electron microscopy(TEM). Western blot was used to detect the expression levels of glucose-regulated protein 78(GRP78), C/EBP homologous protein(CHOP), NLRP3, apoptosis-associated speck-like protein containing CARD(ASC), cysteinyl aspartate-specific proteinase(caspase-1), and gasdermin D(GSDMD) in kidney tissues. The results showed that compared to the control group, the model group exhibited poor general condition, increased weight and food and water intake, and significantly higher levels of FBG, HbA1c, U-mALB, kidney index, 24-hour urine volume, IL-1β, and IL-18. Compared to the model group, the YSJTD and 4-PBA groups showed improved general condition, increased body weight, decreased food intake, and lower levels of FBG, U-mALB, kidney index, 24-hour urine volume, and IL-1β. Specifically, the YSJTD group showed a significant reduction in IL-18 levels compared to the model group, while the 4-PBA group exhibited decreased water intake and HbA1c levels compared to the model group. Although there was a decreasing trend in water intake and HbA1c in the YSJTD group, the differences were not statistically significant. No significant differences were observed in BUN, Scr, and kidney weight among the groups. Renal pathology revealed that the model group exhibited more severe renal damage compared to the control group. Kidney sections from the model group showed diffuse mesangial proliferation in the glomeruli, tubular edema, tubular dilation, significant inflammatory cell infiltration in the interstitium, and increased glycogen staining and blue collagen deposition in the basement membrane. In contrast, the YSJTD and 4-PBA groups showed varying degrees of improvement in renal damage, glycogen staining, and collagen deposition, with the YSJTD group showing more significant improvements. TEM analysis indicated that the model group had extensive cytoplasmic edema, homogeneous thickening of the basement membrane, fewer foot processes, and widening of fused foot processes. In the YSJTD and 4-PBA groups, cytoplasmic swelling of renal tissues was reduced, the basement membrane remained intact and uniform, and foot process fusion improved.Western blot results indicated that compared to the control group, the model group showed upregulation of GRP78, CHOP, GSDMD, NLRP3, ASC, and caspase-1 expression. In contrast, both the YSJTD and 4-PBA groups showed downregulation of these markers compared to the model group. These findings suggest that YSJTD exerts a protective effect against DN by alleviating NLRP3 inflammasome activation through the inhibition of ERS, thereby improving the inflammatory response in db/db DN mice.
Animals ; Endoplasmic Reticulum Stress/drug effects* ; Diabetic Nephropathies/metabolism* ; NLR Family, Pyrin Domain-Containing 3 Protein/genetics* ; Drugs, Chinese Herbal/administration & dosage* ; Mice ; Inflammasomes/drug effects* ; Male ; Kidney/pathology* ; Endoplasmic Reticulum Chaperone BiP ; Humans ; Interleukin-18/genetics* ; Mice, Inbred C57BL

OBJECTIVE: To explore clinical efficacy of percutaneous endoscopic discectomy with a lateral approach and dual-channel method in treating highly free lumbar disc herniation(LDH). METHODS: A retrospective analysis was conducted on 54 patients with highly free LDH who were treated with spinal endoscopic techniques from January 2021 to December 2022. Twenty-seven patients were treated with lateral approach dual-channel(lateral approach dual-channel group), including 16 males and 11 females, with an average age of (54.6±10.5) years old. Twenty-seven patients were treated with unilateral biportal endoscopic (UBE group), including 17 males and 10 females, with an average age of (52.9±12.3) years old. The number of intraoperative fluoroscopy, operation time and hospital stay, as well as visual analogue scale (VAS) and Oswestry diability index (ODI) of low back and leg pain between two patients before operation, 1 day, 1, 3, and 12 months after operation, and the efficacy was evaluated by the modified MacNab criteria at 12 mohths after operation. RESULTS: All patients were successfully completed surgical and were followed up, the time raged from 12 to 22 months with an average of (13.57±4.12) months. There was no statistically significant difference in operation time between two groups (P>0.05). The hospital stay of lateral approach dual-channel group was (3.9±1.1) days, which was shorter than that of UBE group (6.5±1.4) days, the number of intraoperative fluoroscopy in lateral approach dual-channel group was (12.7±2.1) times, which was more than that in UBE group (6.6±1.3) times, the differences were statistically significant (t=5.197, -7.532;P<0.05). VAS and ODI for low back pain at 1 day and 1 month after operation, and VAS for leg pain at 1 day after operation of lateral approach dual-channel group were superior to those of UBE group, and the differences were statistically significant (P<0.05). However, there were no statistically significant differences in VAS and ODI for low back and leg pain between two groups before operation and 3 and 12 months after operation (P>0.05). VAS and ODI of low back and leg pain were significantly improved at each time point before and after operation in both groups, and the difference were statistically significant (P<0.05). At 12 months after operation, according to the modified MacNab criteria, the excellent and good rates of therapeutic effects between lateral approach dual-channel group and UBE group were 92.6% (25/27) and 88.9% (24/27), respectively, and the difference was not statistically significant (χ²=0.22, P>0.05). CONCLUSION For patients with highly free lumbar intervertebral disc protrusion, both of lateral approach dual-channel method and UBE endoscopic surgery are safe and effective. Endoscopic surgery with lateral approach and dual-channel method could be performed under local anesthesia, allowing for the removal of the nucleus pulposus under direct vision. It is simpler, more efficient.
Humans ; Male ; Female ; Intervertebral Disc Displacement/surgery* ; Middle Aged ; Diskectomy, Percutaneous/methods* ; Lumbar Vertebrae/surgery* ; Endoscopy/methods* ; Adult ; Retrospective Studies ; Aged

PURPOSE: The rate of complications among patients undergoing surgery has increased due to infection with SARS-CoV-2 and other variants of concern. However, Omicron has shown decreased pathogenicity, raising questions about the risk of postoperative complications among patients who are infected with this variant. This study aimed to investigate complications and related factors among patients with recent Omicron infection prior to undergoing orthopedic surgery. METHODS: A historical control study was conducted. Data were collected from all patients who underwent surgery during 2 distinct periods: (1) between Dec 12, 2022 and Jan 31, 2023 (COVID-19 positive group), (2) between Dec 12, 2021 and Jan 31, 2022 (COVID-19 negative control group). The patients were at least 18 years old. Patients who received conservative treatment after admission or had high-risk diseases or special circumstances (use of anticoagulants before surgery) were excluded from the study. The study outcomes were the total complication rate and related factors. Binary logistic regression analysis was used to identify related factors, and odds ratio (OR) and 95% confidence interval (CI) were calculated to assess the impact of COVID-19 infection on complications. RESULTS: In the analysis, a total of 847 patients who underwent surgery were included, with 275 of these patients testing positive for COVID-19 and 572 testing negative. The COVID-19-positive group had a significantly higher rate of total complications (11.27%) than the control group (4.90%, p < 0.001). After adjusting for relevant factors, the OR was 3.08 (95% CI: 1.45-6.53). Patients who were diagnosed with COVID-19 at 3-4 weeks (OR = 0.20 (95% CI: 0.06-0.59), p = 0.005), 5-6 weeks (OR = 0.16 (95% CI: 0.04-0.59), p = 0.010), or ≥7 weeks (OR = 0.26 (95% CI: 0.06-1.02), p = 0.069) prior to surgery had a lower risk of complications than those who were diagnosed at 0-2 weeks prior to surgery. Seven factors (age, indications for surgery, time of operation, time of COVID-19 diagnosis prior to surgery, C-reactive protein levels, alanine transaminase levels, and aspartate aminotransferase levels) were found to be associated with complications; thus, these factors were used to create a nomogram. CONCLUSION Omicron continues to be a significant factor in the incidence of postoperative complications among patients undergoing orthopedic surgery. By identifying the factors associated with these complications, we can determine the optimal surgical timing, provide more accurate prognostic information, and offer appropriate consultation for orthopedic surgery patients who have been infected with Omicron.
Humans ; COVID-19/complications* ; Male ; Female ; Middle Aged ; Postoperative Complications/epidemiology* ; SARS-CoV-2 ; Orthopedic Procedures/adverse effects* ; Aged ; Nomograms ; Adult ; Retrospective Studies ; Risk Factors

The circadian clock is an important internal time regulatory system for a range of physiological and behavioral rhythms within living organisms. Testosterone, as one of the most critical sex hormones, is essential for the development of the reproductive system, maintenance of reproductive function, and the overall health of males. The secretion of testosterone in mammals is characterized by distinct circadian rhythms and is closely associated with the regulation of circadian clock genes. Here we review the central and peripheral regulatory mechanisms underlying the influence of circadian clock genes upon testosterone synthesis. We also examined the specific effects of these genes on the occurrence, development, and treatment of common male diseases, including late-onset hypogonadism, erectile dysfunction, male infertility, and prostate cancer.
Testosterone/metabolism* ; Humans ; Male ; Circadian Clocks/genetics* ; Circadian Rhythm Signaling Peptides and Proteins/metabolism* ; Circadian Rhythm/physiology* ; Hypogonadism/metabolism* ; Erectile Dysfunction/metabolism* ; Infertility, Male/metabolism* ; Prostatic Neoplasms/metabolism* ; Men's Health