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.

BACKGROUND:The lower cervical vertebral pedicle is the main stress site of the posterior column of the spine,which is of great significance for the maintenance of the stability of the human center of gravity and the reduction of shock.At present,there are few reports on the characteristics of the internal bone trabeculae,and the characteristics of the joint site of the vertebral pedicle with the articular process and the vertebral body.It is urgent to understand the fine anatomical structure of the vertebral pedicle and the relationship and function of each part. OBJECTIVE:To observe the microanatomical morphology of the vertebral pedicle by Micro-CT scanning of cervical vertebra specimens,and to measure and analyze the microstructure and morphometric parameters of the bone trabecula in the cervical pedicle under normal conditions to evaluate the safety performance of the cervical spine. METHODS:Micro-CT scanning was performed on 31 sets of cervical vertebrae C3-C7.By checking and reconstructing the areas of interest in the bone trabecular within the vertebral pedicle,the morphological characteristics and distribution direction of the bone trabecular within the cervical pedicle were observed,and the bone microstructure parameters were detected,and the differences in the bone microstructure of the C3-C7 vertebral pedicle were analyzed and compared. RESULTS AND CONCLUSION:(1)The Micro-CT images showed that the honeycomb bone trabeculae of the pedicle of the lower cervical spine presented a complex network of microstructures.The trabeculae near the cortical bone were lamellar and relatively compact,extending forward toward the vertebral body and backward toward the articular process lamina.Abatoid bone trabeculae extended into the medullary cavity and transformed into a network structure,and then into rod-shaped bone trabeculae.The rod-shaped bone trabeculae were sparsely distributed in the medullary cavity.(2)Statistical results of morphological parameters of bone trabeculae showed that bone volume fraction values in C4 and C5 were higher than that in C7(P＜0.05).The bone surface/bone volume value in C7 was higher than that in C3,C4 and C6(P＜0.05).The bone surface density of bone trabeculae in C7 was higher than that in C3,C4,C5 and C6(P＜0.05).Trabecular thickness in C7 was higher than that in C3,C4 and C5(P＜0.05).Bone surface/bone volume and bone surface density of the left pedicle bone trabecular were greater than those on the right side(P＜0.05).(3)The microstructural changes of C3-C7 were summarized,in which the load capacity and stress of the C7 pedicle were poor,and the risk of injury was high in this area.

Objective To observe the effects of pegylated losenatide injection combined with metformin tablets on serum metabolism,lipid levels and intestinal flora in obese type 2 diabetes mellitus(T2DM)patients after axial gastrectomy.Methods Obese T2DM patients who underwent axial gastrectomy were divided into treatment group and control group by cohort methods.The control group was treated with metformin hydrochloride tablet 0.5 g orally,tid.The treatment group was treated by subcutaneous injection of pegylated losenatide injection 0.2 mg once a week on the basis of control group.Both groups were treated continuously for 3 months.Body mass index(BMI),serum metabolic indexes,blood lipid levels,blood glucose levels,intestinal flora and adverse drug reactions were compared between the two groups.Results In this study,a total of 70 subjects were included in the treatment group,and 50 subjects were included in the control group.After three months of treatment,the BMI indices of the treatment and control groups were(26.35±2.36)and(29.34±3.59)kg·m-2,respectively;the glutathione peroxidase levels were(192.42±13.18)and(134.27±12.86)U;interleukin-6 levels were(6.14±1.78)and(7.65±2.09)μg·L-1;fasting blood glucose levels were(5.36±0.41)and(7.43±0.78)mmol·L-1;total cholesterol levels were(2.55±0.67)and(3.47±0.79)mmol·L-1 for the treatment and control groups,respectively.The levels of Bifidobacteria,Bacteroides,Lactobacilli,Enterobacteria,and Enterococci in the treatment group were(8.79±1.36),(9.62±1.37),(6.74±2.15),(7.98±0.61),and(7.23±1.29)logN·g-1,respectively;in the control group,these levels were(7.98±1.79),(8.13±1.45),(5.71±2.41),(9.21±0.88),and(8.15±1.54)logN·g-1.The differences in the above indicators between the treatment and control groups were statistically significant(all P＜0.05).The main adverse drug reactions in the treatment group included nausea,headache,dizziness,elevated blood pressure,and indigestion.In the control group,the main adverse drug reactions were nausea,headache,and indigestion.The total incidence of adverse drug reactions in the treatment and control groups was 8.57％and 6.00％,respectively,with no statistically significant difference(P＞0.05).Conclusion Pegylated losenatide injection combined with metformin tablets has a significant effect on axial gastrectomy in obese type 2 diabetes patients.

Objective To evaluate the bioequivalence and safety of the test formulation dapagliflozin tablets(10 mg)compared to the reference formulation in healthy adult subjects under fasting and fed conditions.Methods A single-center,randomized,open-label,two-period,two-sequence,crossover study design was employed.A total of 68 subjects were enrolled,with 32 subjects in the fasting group and 36 subjects in the fed group.Each subject received a single oral dose of either the test or reference formulation 10 mg.Plasma concentrations of dapagliflozin were measured using liquid chromatography-tandem mass spectrometry(LC-MS/MS).Pharmacokinetic parameters were calculated using Phoenix WinNonlin 8.2 to assess the bioequivalence of the two formulations and their safety.Results Key pharmacokinetic parameters of the test and reference formulations in the fasting group were as follows:Cmax were(195.08±58.24)and(200.22±45.20)ng·mL-1;tmax were 0.67 and 0.67 h;AUC0_t were(553.52±97.82)and(552.47±106.07)ng·h·mL-1;AUC0-∞ were(580.40±103.79)and(579.42±111.23)ng·h·mL-1.In the fed group,the parameters were:Cmax were(123.38±39.50)and(125.80±39.05)ng·mL-1;tmaxwere 2.00 and 2.50 h;AUC0-t were(606.05±129.44)and(596.73±131.97)ng·h·mL-1;AUC0-∞ were(637.12±138.77)and(629.38±136.81)ng·h·mL-1.The 90％confidence intervals for the geometric mean ratios of Cmax,AUC0-t and AUC0-∞ for the test and reference formulations were within the bioequivalence range of 80.00％to 125.00％.The incidence of adverse drug events was 3.23％in the fasting group and 5.56％in the fed group.Conclusion The test formulation of dapagliflozin tablets is bioequivalent to the reference formulation in healthy Chinese subjects and has a good safety profile.

Objective To investigate the effect and mechanism of Yiguan Decoction(YGJD)on the efficacy of M1 bone marrow-derived macrophages(M1-BMDMs)in the treatment of rats with liver cirrhosis induced by 2-AAF/CCl4.Methods BMDMs were isolated and induced into M1-BMDMs by lipopolysaccharide.A total of 50 male Wistar rats were randomly divided into normal group with 5 rats and model group with 45 rats.The rats for modeling were given subcutaneous injection of 50%CCl4 twice a week.Since week 7,the rats for modeling were randomly divided into model group(M group),YGJD group,M1-BMDM group,M1-BMDM+YGJD group,and sorafenib(SORA)group,and they were given subcutaneous injection of 30%CCl4 to maintain the progression of liver cirrhosis and intragastric administration of 2-AAF.CCR2 inhibitors were added to the drinking water,and each group was given the corresponding intervention.Related samples were collected at week 9.The rats were observed in terms of serum liver function parameters,liver pathology,hydroxyproline(Hyp)content in liver tissue,hepatic stellate cell activation,hepatic fibrosis and inflammation factors,and the expression levels of molecules associated with the Wnt signaling pathway.A one-way analysis of variance was used for comparison of continuous data between multiple groups,and the least significant difference t-test was used for further comparison between two groups.Results Compared with the M group,the M1-BMDM+YGJD group had significant reductions in the serum levels of alanine aminotransferase,aspartate aminotransferase,and total bilirubin(TBil)(all P<0.05)and a significant increase in the content of albumin(Alb)(P<0.05),and compared with the M1-BMDM group,the M1-BMDM+YGJD group had a significant reduction in the serum level of TBil(P<0.05)and a significant increase in the serum level of Alb(P<0.05).Compared with the M1-BMDM group,the M1-BMDM+YGJD group had significant reductions in the expression levels of CD68 and TNF-α(P<0.05).Compared with the M1-BMDM group,the M1-BMDM+YGJD group had significant reductions in Hyp content and Sirius red positive area(P<0.05).As for the non-canonical Wnt signaling pathway molecules,compared with the M1-BMDM group,the M1-BMDM+YGJD group had significantly lower mRNA and protein expression levels of Wnt5a(P<0.05)and mRNA expression level of Fzd2(P<0.05),as well as significant reductions in the mRNA expression levels of Wnt4,Wnt5b,and Fzd3(P<0.05),while there were no significant changes in the mRNA expression levels of the canonical Wnt signaling pathway molecules β-catenin,LRP5,LRP6,Fzd5,and TCF.Conclusion YGJD can enhance the therapeutic effect of M1-BMDMs on rats with liver cirrhosis induced by 2-AAF/CCl4,possibly by inhibiting the non-canonical Wnt5a/Fzd2 signaling pathway,which provides new ideas for the synergistic effect of traditional Chinese medicine on M1-BMDMs in the treatment of liver cirrhosis.

Pneumonia caused by severe acute respiratory syndrome coronavirus 2(SARS-CoV-2)infection poses a threat to human life and health,resulting in great socio-economic losses.The structural protein spike protein(S protein)of viruses has always been considered to primarily mediate virus invasion into host cells.S protein can act independently of viruses and cause inflammatory reactions on a variety of cells,therefore,understanding the impact of S protein on the respiratory tract can provide a new perspective for the prevention and treatment of COVID-19.This article reviews the advances in the possible mechanisms and clinical manifestations of SARS-CoV-2 structural protein S protein-induced inflammatory response in respiratory epithelial cells,aiming to provide reference for the prevention and treatment of diseases.