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::Although the treatment of peripheral T-cell lymphoma (PTCL) has undergone advancements during the past several years, the response rate and long-term effects with respect to patients with PTCL remain unsatisfactory—particularly for relapsed or refractory (R/R) patients. This phase II trial was designed to explore the efficacy and safety of an all-oral regimen of chidamide plus prednisone, cyclophosphamide, and thalidomide (CPCT) for R/R PTCL patients who could not tolerate the standard chemotherapy for a variety of reasons.Methods::We conducted a multicenter phase II clinical trial in which we combined chidamide (30 mg twice weekly) with prednisone (20 mg daily after breakfast), cyclophosphamide (50 mg daily after lunch), and thalidomide (100 mg daily at bedtime) (the CPCT regimen) for a total of fewer than 12 cycles as an induction-combined treatment period, and then applied chidamide as single-drug maintenance. Forty-five patients were ultimately enrolled from August 2016 to April 2021 with respect to Chinese patients at nine centers. Our primary objective was to assess the overall response rate (ORR) after the treatment with CPCT.Results::Of the 45 enrolled patients, the optimal ORR and complete response (CR)/CR unconfirmed (CRu) were 71.1% (32/45) and 28.9% (13/45), respectively, and after a median follow-up period of 56 months, the median progression-free survival (PFS) and overall survival (OS) were 8.5 months and 17.2 months, respectively. The five-year PFS and OS rates were 21.2% (95% confidence interval [CI], 7.9-34.5%) and 43.8% (95% CI, 28.3-59.3%), respectively. The most common adverse event was neutropenia (20/45, 44.4%), but we observed no treatment-related death.Conclusion::The all-oral CPCT regimen was an effective and safe regimen for R/R PTCL patients who could not tolerate standard chemotherapy for various reasons.Trial Registration::ClinicalTrials.gov, NCT02879526.

Aim To observe the effects of Compound Dihuang Granules on α-syn,VAPB and PTPIP51 in the substantia nigra of Parkinson's disease(PD)rats with Yin deficiency and wind syndrome,and to explore the possible mechanisms of their actions.Methods The 6-hydroxydopamine-induced PD model of rats was constructed.The model rats were randomly divided into the model group,madopar group,CLD group,CMD group and CHD group,while the NC group did not re-ceive any treatment and the SO group was injected with ascorbic acid,with 13 rats in each group.The neurobe-havioral changes of the rats were observed,and the ex-pressions of α-syn,VAPB and PTPIP51 in the sub-stantia nigra were detected by Western blot,RT-PCR and Immunohistochemistry;the histopathological and morphological changes of the substantia nigra tissue were observed by HE staining,the changes of mito-chondrial ultrastructure in the substantia nigra cells were observed by transmission electron microscopy,and the changes of ATP content in substantia nigra tis-sue in each group were detected by ELISA.Results Compared with the NC and SO groups,rats in the model group showed that the number of rotational cir-cles and pole-climbing time increased,the expression of α-syn increased,the expression of VAPB and PTPIP 5 1 decreased,the number of neuronal cells decreased,the neuronal cells became crumpling,and mitochondrial swelling,disappearance of the mitochon-drial cristae,a larger distance between the ER-mito-chondrial contacts were observed;the ATP content de-creased.Compared with the model group,rats in Mado-par group and CLD group,CMD group and CHD group showed that the number of rotational circles and pole-climbing time decreased,the expression of α-syn de-creased,the expression of VAPB and PTPIP51 in-creased,the degree of neuronal damage was reduced,the morphology of mitochondria was improved and the content of ATP increased,showing the change of the difference in quantitative efficacy;the relative efficacy of Madopar group and CHD group was better,and there was no statistically significant difference.Con-clusions Compound Dihuang granules attenuate the behavioral symptoms in PD rats and may play a thera-peutic role in PD by down-regulating the expression ofα-syn,up-regulating the expression of PTPIP51 and VAPB and improving mitochondrial function.

Aim To investigate the preventive and therapeutic effects of the mfat-1 gene therapy on exper-imental autoimmune encephalomyelitis in mice.Meth-ods mfat-1 gene therapy was used to render the host endogenous capability of producing ω-3 PUFAs,con-comitantly reduce the levels of ω-6 PUFAs,and change the proportion of ω-3/ω-6 PUFAs.Then,the levels of PUFAs in blood were analyzed by gas chromatography.The neurological deficits in mice were evaluated by neurological dysfunction score.HE staining and LFB staining of mouse spinal cord slices were used to ob-serve central nervous system inflammation infiltration and demyelinating lesions.Flow cytometry microsphere microarray technology was used to detect the content of cytokines in serum.Results The mfat-1 gene therapy could significantly raise the proportion of ω-3/ω-6 PU-FAs(P＜0.05),markedly delay the incubation period and peak period and reduce neurological dysfunction scores(P＜0.05),and improve inflammation and de-myelination of spinal cords(P＜0.05).It could also greatly increase the levels of IL-2,IFN-γ,IL-4 and IL-17 in serum(P＜0.05).Conclusion The pro-portion of ω-3/ω-6 PUFAs in blood circulation en-hanced by mfat-1 gene therapy can effectively prevent and treat experimental autoimmune encephalomyelitis in mice.

Aim To explore the mechanism of modified Wuzi Yanzong pill to reduce testicular toxicity of Tripterygium wilfordii by means of network pharmacolo-gy.Methods The effective chemical composition and target of modified Wuzi Yanzong Pill to reduce testicu-lar toxicity of Tripterygium wilfordii were analyzed by using multiple databases to understand the mechanism of action.Results The first five compounds of modi-fied Wuzi Yanzong pill are quercetin,sucrose,kaempferol,galactose and ellagic acid,respectively.The first five targets were TP53,SRC,EP300,MAPK3,STAT3;KEGG pathway enrichment analysis mainly concentrated in cancer pathway,lipid and atherosclero-sis,hepatitis B,apoptosis,diabetes complications AGE-RAGE signaling pathway,PI3K-Akt signaling pathway and other signaling pathways.Conclusions The ac-tive components of modified Wuzi Yanzong pill can re-duce the testicular toxicity of Tripterygium wilfordii mainly by interfering with TP53,SRC,EP300,MAPK3,STAT3 and other targets,regulating apoptosis,PI3K-Akt signaling pathway,diabetes complications AGE-RAGE signaling pathway,lipid metabolism and other pathways.

Objective To compare the effectiveness of TiRobot assisted F screw technique and inverted triangle parallel nail internal fixation in the treatment of unstable femoral neck fractures.Methods A retrospective analysis was conducted on 72 patients with unstable femoral neck fractures who were treated with percutaneous cannulated screw fixation assisted with TiRobot Orthopaedic robot from December 2019 to April 2021.Among them,37 patients were treated with F screw internal fixa-tion,including 16 males and 21 females,aged47 to 64years old with an average of(53.87±5.28)years old;According to Pauwels classification,there were 1 case of type Ⅰ,19 cases of type Ⅱ,17 cases of type Ⅲ;8 cases of combined medical diseases;17 cases of falling,8 cases of traffic accident and 12 cases of falling from height;The time from injury to operation was 29 to 49 hours with average of(35.00±7.34)hours.Another 35 cases used internal fixation with an inverted triangle parallel nail,including 13 males and 22 females with an average age of 46 to 63 years old(52.36±5.05)years old;According to the Pauwels injury classifi-cation:there were 2 cases of type Ⅰ,21 cases of type Ⅱ,12 cases of type Ⅲ;6 cases of medical diseases,15 cases of falling in-jury,9 cases of traffic accident,11 cases of falling injury;The time from injury to operation was 30 to 45 hours with an average of(33.00±6.83)h.The intraoperative blood loss,operation time,intraoperative fluoroscopy times,follow-up time,fracture healing time,postoperative complications were observed and compared between the two groups.The hip joint function was e-valuated by Harris score at 6 months and 12 months after operation.Results There was no significant difference in operation time,intraoperative blood loss,intraoperative fluoroscopy times and other intraoperative data between two groups(P＞0.05).Both groups were followed up regularly,and the follow-up time was 12 to 16 months.The fracture healing time and Harris score of the F screw internal fixation group were better than those of the inverted triangle parallel nail internal fixation group(P＜0.05).There was 1 case of femoral neck shortening in the F screw internal fixation group,1 case of nonunion,1 case of nail withdrawal,and 1 case of lower extremity deep vein thrombosis in the inverted triangle internal fixation group.The incidence of complications in the F screw internal fixation group was lower than that in the inverted triangle parallel nail internal fixation group(P＜0.05).Conclusion Percutaneous cannulated F screw technique using Tirobot navigation positioning system is a safe and effective treatment for patients with unstable femoral neck fractures.It can significantly shorten the fracture healing time,reduce the incidence of postoperative complications,significantly improve hip joint function,and improve the quality of life.