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.

Aim To screen and study the expression of long non-coding RNA (IncRNA) in rats with middle cerebral artery occlusion (MCAO) with MCAO treated with Tao Hong Si Wu decoction (THSWD) and determine the possible molecular mechanism of THSWD in treating MCAO rats. Methods Three cerebral hemisphere tissue were obtained from the control group, MCAO group and MCAO + THSWD group. RNA sequencing technology was used to identify IncRNA gene expression in the three groups. THSWD-regulated IncRNA genes were identified, and then a THSWD-regu-lated IncRNA-mRNA network was constructed. MCODE plug-in units were used to identify the modules of IncRNA-mRNA networks. Gene ontology (GO) and kyoto encyclopedia of genes and genomes (KEGG) were used to analyze the enriched biological functions and signaling pathways. Cis- and trans-regulatory genes for THSWD-regulated IncRNAs were identified. Reverse transcription real-time quantitative pol-ymerase chain reaction (RT-qPCR) was used to verify IncRNAs. Molecular docking was used to identify IncRNA-mRNA network targets and pathway-associated proteins. Results In MCAO rats, THSWD regulated a total of 302 IncRNAs. Bioinformatics analysis suggested that some core IncRNAs might play an important role in the treatment of MCAO rats with THSWD, and we further found that THSWD might also treat MCAO rats through multiple pathways such as IncRNA-mRNA network and network-enriched complement and coagulation cascades. The results of molecular docking showed that the active compounds gallic acid and a-mygdalin of THSWD had a certain binding ability to protein targets. Conclusions THSWD can protect the brain injury of MCAO rats through IncRNA, which may provide new insights for the treatment of ischemic stroke with THSWD.

Objective To investigate different doses of the analgesic effects of dezocine comparing with sufentanil after laryngectomy.Methods A total of 129 patients who underwent elective partial laryngectomy from Feb 2022 to Jan 2023 were randomly assigned to dezocine 0.5 mg/kg group(group D1),dezocine 0.6 mg/kg group(group D2)and sufentanil 2 μg/kg group(group S).Twenty-four hours amount of drugs,the visual analogue scale(visual analogue scale,VAS)and 48 h total pressing times of PCA(patient-controlled intravenous analgesia,PCIA)were compared among the three groups at 6,12,24 and 48 h after operation,and the postoperative adverse reactions(nausea,vomiting,dizziness,urinary retention and respiratory depression)were recorded.Results There was no significant difference in 24 h amount of drugs among the three groups.The VAS score of group D1 was higher than that of group S at 6 h postoperatively(P＜0.05),but did not differ significantly among the three groups at 12,24 and 48 h.There was no significant differences in the number of compressions and postoperative adverse reactions among the three groups.Conclusion Compared with sufentanil,0.6 mg/kg dezocine can provide the same degree of analgesic effect.However,no advantage was found to reduce adverse reactions.

Objective To construct a lentiviral vector for overexpression of bone morphogenetic protein 7(BMP7)in mice,and the effect of BMP7 overexpression on the expression of Jagged1 in mouse aortic endothelial cells and the calcification of the co-cultured vascular smooth muscle cells(VSMCs)were analyzed.Methods According to the target gene information Mouse-BMP7(NM_007557.3)and plasmid information pLVX-zsGreen-C1,gene sequence synthesis was carried out to construct BMP7 overexpression lentivirus.The efficiency of BMP7 overexpression lentivirus infection was detected by qPCR;the expression of Jagged1 protein in aortic endothelial cells from infected mice was detected by Western blot.The endothelial cells with lentivirus overexpressing BMP7 were co-cultured with VSMCs,and the calcification of VSMCs was observed by alizarin red staining.Results BMP7 overexpression lentiviral vector was successfully constructed and transfected into aortic endothelial cells.qPCR test results showed that the expression level of BMP7 mRNA was significantly increased in the BMP7 overexpression group than that in the normal control group(P<0.01),while there was no significant difference in the expression of BMP7 mRNA between the empty vector control group and the normal control group(P>0.05).Western blot results showed that the expression level of Jagged1 protein in endothelial cells of mouse in the BMP7 overexpression group was significantly lower than that in the normal control group(P<0.01),while there was no significant difference in the expression level of Jagged1 protein in endothelial cells between the empty vector control group and the normal control group(P>0.05).The results of alizarin red staining showed that the calcification of VSMCs was significantly increased after co-cultured with endothelial cells infected with BMP7 lentivirus.Conclusion Mouse BMP7 overexpression lentiviral vector was successfully constructed,and overexpression of BMP7 can reduce the expression of Jagged1 in mouse aortic endothelial cells and promote the calcification of co-cultured VSMCs.

In the past few decades,supercritical fluid chromatography(SFC)as a supplement to liquid chromatography(LC)separation technology has attracted people's interest,especially in the combination of SFC and mass spectrometry(MS),which has shown important application prospects in metabolomics,lipidomics,and other fields.Compared to the interface of LC-MS,the interface of SFC-MS presents some unique challenges that require special solutions to be designed.This article categorizes and summarizes the existing interfaces used for SFC-MS,focuses on the impact of different interface designs on detection performance,provides the applicable characteristics of different types of interfaces,and finally briefly introduces the application progress of SFC-MS in different fields.

Objective To observe the therapeutic effect and mechanism of acupuncture at Zusanli-Zhongwan combined matching points on rats with exercise-induced stress gastric ulcer.Methods Forty male SD rats were randomly divided into blank group,model group,acupuncture group and Omeprazole group,with 10 rats in each group.Except for the blank group,the rats in the other groups were used to construct the model of exercise stress gastric ulcer by daily exhaustive swimming.After successful modeling,the acupuncture group was intervened by acupuncture at Zusanli(ST36)and Zhongwan(RN12),once a day,10 minutes each time.Rats in the Omeprazole group were given Omeprazole Enteric-Coated Tablets distilled water suspension by gavage two hours before daily swimming.After continuous 7-day intervention,the overall state and behavior of rats were observed,the gastric mucosal injury index was calculated by Guth method,the pathological morphology of gastric mucosa was observed by hematoxylin-eosin(HE)staining,the contents of superoxide dismutase(SOD),glutathione peroxidase(GSH-PX)and malondialdehyde(MDA)in serum were correspondingly determined by WST-1 method,colorimetry and TBA method,respectively,enzyme-linked immunosorbent assay(ELISA)was used to detect the contents of gastrin(GAS),somatostatin(SS),tumor necrosis factor-α(TNF-α),interleukin-1 β(IL-1β),interleukin-6(IL-6)and interleukin-10(IL-10)in serum,the expression levels of epidermal growth factor receptor(EGFR),matrix metalloproteinase 3(MMP3),nuclear factor erythroid-related factor 2(NRF2),heme oxygenase 1(HO-1)and mitochondrial SOD2,TNF-α,IL-1β,IL-6 and IL-10 mRNA in gastric mucosa were detected by real-time fluorescence quantitative polymerase chain reaction(qPCR).Results Compared with the blank group,the body mass of rats in the model group was increased slowly,the activity distance and activity in the open field test were decreased,the gastric mucosal ulcer index was increased significantly,the gastric mucosal function indexes involving GAS level was increased and SS level was decreased in serum,the mRNA expression level of EGFR in gastric mucosa was decreased and the mRNA expression level of MMP3 in gastric mucosa was increased.The serum levels of antioxidant substances SOD and GSH-PX were decreased significantly,and the serum level of oxidation product MDA was increased significantly.The mRNA expression levels of antioxidant genes NRF2,HO-1 and SOD2 in gastric mucosa were significantly decreased.The serum contents and the gastric mucosa mRNA levels of inflammatory factors TNF-α,IL-1α,IL-6 were significantly increased,while the serum content and the gastric mucosa mRNA level of IL-10 were significantly decreased.The differences were statistically significant(P＜0.05 or P＜0.01 or P＜0.001).HE staining showed obvious gastric mucosal injury.Compared with the model group,the above indexes in the acupuncture group and the Omeprazole group were significantly improved(P＜0.05 or P＜0.01 or P＜0.001).HE staining showed that the gastric mucosal injury was significantly reduced.Conclusion Acupuncture at Zusanli-Zhongwan combined matching points can reduce the local oxidative stress and inflammatory response in rats with exercise-induced stress gastric ulcer,reduce gastric mucosal injury,improve the emotional state of rats,and maintain the overall vitality of rats.