ObjectiveThis paper aims to explore the in vitro anti-psoriasis activity and potential mechanism of Kangfuxin liquid （KFX liquid）， providing experimental evidence for the anti-psoriasis effect of KFX liquid. MethodsFirstly， the uninduced human immortalized keratinocyte cells （HaCaT cells） were divided into seven groups， namely the control group and KFX liquid groups with different doses （5， 10， 20， 40， 80， 160 g·L^-1）. After being treated with different concentrations of KFX liquid， the effect of KFX liquid on the normal cell proliferation was detected by using the cell counting kit-8 （CCK-8） method. Secondly， the uninduced HaCaT cells were divided into six groups， namely the control group and recombinant human interleukin-7A （rh-IL-7A） groups with different doses （5， 10， 50， 100， 120 g·L^-1）. After being treated with different concentrations of recombinant human interleukin-17A （rh IL-17A） liquid， the effect of rh IL-17A on cell proliferation was detected. The optimal induction concentration was screened. Then， normal HaCaT cells were divided into a control group and KFX liquid groups with different doses （5， 10， 20， 40， 80， 160 g·L^-1）. Except for the control group， the other groups established psoriasis cell models with the optimal induction concentration of rh IL-17A. After being treated with different concentrations of KFX liquid， the effects of KFX liquid on the psoriasis-like HaCaT cell proliferation were investigated. Finally， the uninduced HaCaT cells were divided into six groups， namely the control group， rh IL-17A group， methotrexate （MTX） group， and KFX liquid groups with different doses （20， 40， 80 g·L^-1）. Except for the control group， the other groups used the optimal induction concentration of rh IL-17A to establish psoriasis cell models. After being treated with different drugs， the cell migration levels were detected through scratch assays， and real-time quantitative polymerase chain reaction （Real-time PCR） was used to detect the relative mRNA expression levels of Ki-67 antigen （Ki67）， S100 calcium-binding protein A7 （S100A7）， S100 calcium-binding protein A8 （S100A8）， and S100 calcium-binding protein A9 （S100A9）， thereby comprehensively evaluating the in vitro anti-psoriasis activity of KFX liquid. By detecting the relative mRNA expression levels of interleukin-1β （IL-1β）， interleukin-6 （IL-6）， and chemokine-20 （CXCL-20） inflammatory-related factors in psoriasis-like HaCaT cells and the protein expression levels of Janus kinase 3 （JAK3）， phosphorylated Janus kinase 3 （p-JAK3）， signal transducer and activator of transcription 3 （STAT3）， and phosphorylated signal transducer and activator of transcription 3 （p-STAT3）， the mechanism was explored. ResultsCompared with that of control group， when treated with 80 g·L^-1 KFX liquid for 72 h （P<0.05） and at different times with 160 g·L^-1 KFX liquid， the HaCaT cell proliferation activity was significantly affected （P<0.01）， while the other concentrations of KFX liquid had no significant differences in cell morphology and cell proliferation activity at different times， indicating that the KFX liquid is relatively safe for HaCaT cells and has no obvious toxic side effects. Compared with that of control group， when treated with different concentrations of rh IL-17A for 24 h， the HaCaT cell proliferation activity was significantly enhanced， and the cell activity was the strongest when the concentration was 100 μg·L^-1 （P<0.05）， with a density close to 100% and intact cell morphology， indicating that 100 μg·L^-1 is the optimal concentration for inducing HaCaT cell proliferation. The results of the KFX liquid treatment on rh IL-17A-induced psoriasis-like cells show that the KFX liquid not only effectively inhibits the rh IL-17A-induced psoriasis-like HaCaT cell proliferation activity （P<0.01）， but also significantly reduces the migration ability of rh IL-17A-induced psoriasis-like HaCaT cells （P<0.01）， and the relative mRNA expression levels of Ki67， S100A7， S100A8， and S100A9 （P<0.01）. Moreover， the KFX liquid can significantly reduce the relative mRNA expression levels of IL-1β， IL-6， and CXCL-20 in rh IL-17A-induced psoriasis-like cells （P<0.01）， and significantly inhibit the phosphorylation levels of JAK3 and STAT3 proteins （P<0.05， P<0.01）. ConclusionThe KFX liquid has no obvious toxicity to uninduced HaCaT cells. It can inhibit rh IL-17A-induced psoriasis-like HaCaT cell proliferation， reduce the cell migration ability， and has good in vitro anti-psoriasis activity. Its action mechanism may be related to downregulating the expression levels of inflammation-related cytokines in the JAK3/STAT3 signaling pathway and inhibiting the phosphorylation levels of JAK3 and STAT3 proteins.

ObjectiveThis paper aims to explore the in vitro anti-psoriasis activity and potential mechanism of Kangfuxin liquid （KFX liquid）， providing experimental evidence for the anti-psoriasis effect of KFX liquid. MethodsFirstly， the uninduced human immortalized keratinocyte cells （HaCaT cells） were divided into seven groups， namely the control group and KFX liquid groups with different doses （5， 10， 20， 40， 80， 160 g·L^-1）. After being treated with different concentrations of KFX liquid， the effect of KFX liquid on the normal cell proliferation was detected by using the cell counting kit-8 （CCK-8） method. Secondly， the uninduced HaCaT cells were divided into six groups， namely the control group and recombinant human interleukin-7A （rh-IL-7A） groups with different doses （5， 10， 50， 100， 120 g·L^-1）. After being treated with different concentrations of recombinant human interleukin-17A （rh IL-17A） liquid， the effect of rh IL-17A on cell proliferation was detected. The optimal induction concentration was screened. Then， normal HaCaT cells were divided into a control group and KFX liquid groups with different doses （5， 10， 20， 40， 80， 160 g·L^-1）. Except for the control group， the other groups established psoriasis cell models with the optimal induction concentration of rh IL-17A. After being treated with different concentrations of KFX liquid， the effects of KFX liquid on the psoriasis-like HaCaT cell proliferation were investigated. Finally， the uninduced HaCaT cells were divided into six groups， namely the control group， rh IL-17A group， methotrexate （MTX） group， and KFX liquid groups with different doses （20， 40， 80 g·L^-1）. Except for the control group， the other groups used the optimal induction concentration of rh IL-17A to establish psoriasis cell models. After being treated with different drugs， the cell migration levels were detected through scratch assays， and real-time quantitative polymerase chain reaction （Real-time PCR） was used to detect the relative mRNA expression levels of Ki-67 antigen （Ki67）， S100 calcium-binding protein A7 （S100A7）， S100 calcium-binding protein A8 （S100A8）， and S100 calcium-binding protein A9 （S100A9）， thereby comprehensively evaluating the in vitro anti-psoriasis activity of KFX liquid. By detecting the relative mRNA expression levels of interleukin-1β （IL-1β）， interleukin-6 （IL-6）， and chemokine-20 （CXCL-20） inflammatory-related factors in psoriasis-like HaCaT cells and the protein expression levels of Janus kinase 3 （JAK3）， phosphorylated Janus kinase 3 （p-JAK3）， signal transducer and activator of transcription 3 （STAT3）， and phosphorylated signal transducer and activator of transcription 3 （p-STAT3）， the mechanism was explored. ResultsCompared with that of control group， when treated with 80 g·L^-1 KFX liquid for 72 h （P<0.05） and at different times with 160 g·L^-1 KFX liquid， the HaCaT cell proliferation activity was significantly affected （P<0.01）， while the other concentrations of KFX liquid had no significant differences in cell morphology and cell proliferation activity at different times， indicating that the KFX liquid is relatively safe for HaCaT cells and has no obvious toxic side effects. Compared with that of control group， when treated with different concentrations of rh IL-17A for 24 h， the HaCaT cell proliferation activity was significantly enhanced， and the cell activity was the strongest when the concentration was 100 μg·L^-1 （P<0.05）， with a density close to 100% and intact cell morphology， indicating that 100 μg·L^-1 is the optimal concentration for inducing HaCaT cell proliferation. The results of the KFX liquid treatment on rh IL-17A-induced psoriasis-like cells show that the KFX liquid not only effectively inhibits the rh IL-17A-induced psoriasis-like HaCaT cell proliferation activity （P<0.01）， but also significantly reduces the migration ability of rh IL-17A-induced psoriasis-like HaCaT cells （P<0.01）， and the relative mRNA expression levels of Ki67， S100A7， S100A8， and S100A9 （P<0.01）. Moreover， the KFX liquid can significantly reduce the relative mRNA expression levels of IL-1β， IL-6， and CXCL-20 in rh IL-17A-induced psoriasis-like cells （P<0.01）， and significantly inhibit the phosphorylation levels of JAK3 and STAT3 proteins （P<0.05， P<0.01）. ConclusionThe KFX liquid has no obvious toxicity to uninduced HaCaT cells. It can inhibit rh IL-17A-induced psoriasis-like HaCaT cell proliferation， reduce the cell migration ability， and has good in vitro anti-psoriasis activity. Its action mechanism may be related to downregulating the expression levels of inflammation-related cytokines in the JAK3/STAT3 signaling pathway and inhibiting the phosphorylation levels of JAK3 and STAT3 proteins.

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.

Jiuwei Xifeng Granules have become a Chinese patent medicine in the market. Because the formula contains Os Draconis, a top-level protected fossil of ancient organisms, the formula was to be improved by replacing Os Draconis with Ostreae Concha. To evaluate whether the improved formula has the same effectiveness and safety as the original formula, a randomized, double-blind, parallel-controlled, equivalence clinical trial was conducted. This study enrolled 288 tic disorder(TD) of children and assigned them into two groups in 1∶1. The treatment group and control group took the modified formula and original formula, respectively. The treatment lasted for 6 weeks, and follow-up visits were conducted at weeks 2, 4, and 6. The primary efficacy endpoint was the difference in Yale global tic severity scale(YGTSS)-total tic severity(TTS) score from baseline after 6 weeks of treatment. The results showed that after 6 weeks of treatment, the declines in YGTSS-TSS score showed no statistically significant difference between the two groups. The difference in YGTSS-TSS score(treatment group-control group) and the 95%CI of the full analysis set(FAS) were-0.17[-1.42, 1.08] and those of per-protocol set(PPS) were 0.29[-0.97, 1.56], which were within the equivalence boundary [-3, 3]. The equivalence test was therefore concluded. The two groups showed no significant differences in the secondary efficacy endpoints of effective rate for TD, total score and factor scores of YGTSS, clinical global impressions-severity(CGI-S) score, traditional Chinese medicine(TCM) response rate, or symptom disappearance rate, and thus a complete evidence chain with the primary outcome was formed. A total of 6 adverse reactions were reported, including 4(2.82%) cases in the treatment group and 2(1.41%) cases in the control group, which showed no statistically significant difference between the two groups. No serious suspected unexpected adverse reactions were reported, and no laboratory test results indicated serious clinically significant abnormalities. The results support the replacement of Os Draconis by Ostreae Concha in the original formula, and the efficacy and safety of the modified formula are consistent with those of the original formula.
Adolescent ; Child ; Child, Preschool ; Female ; Humans ; Male ; Double-Blind Method ; Drugs, Chinese Herbal/therapeutic use* ; Tic Disorders/drug therapy* ; Treatment Outcome

This paper aimed to investigate the therapeutic effect and mechanism of action of the Yiqi Fumai Formula(YQFM), a kind of traditional Chinese medicine(TCM), on mice with experimental heart failure based on the "heart-gut axis" theory. Based on the network pharmacology integrated with the group collaboration algorithm, the active ingredients were screened, a "component-target-disease" network was constructed, and the potential pathways regulated by the formula were predicted and analyzed. Next, the model of experimental heart failure was established by intraperitoneal injection of adriamycin at a single high dose(15 mg·kg~(-1)) in BALB/c mice. After intraperitoneal injection of YQFM(lyophilized) at 7.90, 15.80, and 31.55 mg·d~(-1) for 7 d, the protective effects of the formula on cardiac function were evaluated using indicators such as ultrasonic electrocardiography and myocardial injury markers. Combined with inflammatory factors in the cardiac and colorectal tissue, as well as targeted assays, the relevant indicators of potential pathways were verified. Meanwhile, 16S rDNA sequencing was performed on mouse fecal samples using the Illumina platform to detect changes in gut flora and analyze differential metabolic pathways. The results show that the administration of injectable YQFM(lyophilized) for 7 d significantly increased the left ventricular end-systolic internal diameter, fractional shortening, and ejection fraction of cardiac tissue of mice with experimental heart failure(P<0.05). Moreover, markers of myocardial injury were significantly decreased(P<0.05), indicating improved cardiac function, along with significantly suppressed inflammatory responses in cardiac and intestinal tissue(P<0.05). Additionally, the species of causative organisms was decreased, and the homeostasis of gut flora was improved, involving a modulatory effect on PI3K-Akt signaling pathway-related inflammation in cardiac and colorectal tissue. In conclusion, YQFM can affect the "heart-gut axis" immunity through the homeostasis of the gut flora, thereby exerting a therapeutic effect on heart failure. This finding provides a reference for the combination of TCM and western medicine to prevent and treat heart failure based on the "heart-gut axis" theory.
Animals ; Drugs, Chinese Herbal/administration & dosage* ; Heart Failure/microbiology* ; Mice ; Mice, Inbred BALB C ; Male ; Disease Models, Animal ; Gastrointestinal Microbiome/drug effects* ; Heart/physiopathology* ; Humans ; Signal Transduction/drug effects*

Gegen Qinlian Decoction(GQD) is a classic prescription for the clinical treatment of ulcerative colitis(UC). This study, based on the differences in efficacy observed in UC mice under different level of bile acids treated with GQD, aims to clarify the impact of bile acids on UC and its therapeutic effects. It further investigates the expression of bile acid receptors in the liver of UC mice, and preliminarily reveals the mechanism through which GQD affects bile acid synthesis in the treatment of UC. A UC mouse model was established using dextran sulfate sodium(DSS) induction. The efficacy of GQD was evaluated by assessing the general condition, disease activity index(DAI) score, colon length, and histopathological changes in colon tissue via hematoxylin and eosin(HE) staining. ELISA and Western blot were used to evaluate the inflammatory response in colon tissue. The total bile acid(TBA) level and liver damage were quantified using an automatic biochemistry analyzer. The expression levels of bile acid receptors and bile acid synthetases in liver tissue were detected by Western blot and RT-qPCR. The results showed that compared with the model group, GQD treatment significantly improved the DAI score, colon shortening, and histopathological damage in UC mice. The levels of pro-inflammatory factors TNF-α and IL-6 in the colon were significantly reduced. Serum TBA levels were significantly decreased, while alkaline phosphatase(ALP) levels significantly increased. After administration of cholic acid(CA), UC symptoms in the CA + GQD group were significantly aggravated compared with the GQD group. The DAI score, degree of weight loss, colon injury, serum TBA, and liver injury markers all increased significantly. However, compared with the CA group, the CA + GQD group showed a marked reduction in TBA levels and a significant improvement in UC-related symptoms, indicating that GQD can alleviate UC damage exacerbated by CA. Further investigation into the expression of bile acid receptors and synthetases in the liver showed that under GQD treatment, the expression of farnesoid X receptor(FXR) and small heterodimer partner(SHP) significantly increased, while the expression of G protein-coupled receptor 5(TGR5) and cholesterol 7α-hydroxylase(Cyp7A1) significantly decreased. These findings suggest that GQD may affect bile acid receptors and synthetases, inhibiting bile acid synthesis through the FXR/SHP pathway to treat UC.
Animals ; Colitis, Ulcerative/genetics* ; Bile Acids and Salts/biosynthesis* ; Drugs, Chinese Herbal/administration & dosage* ; Mice ; Male ; Humans ; Receptors, Cytoplasmic and Nuclear/metabolism* ; Colon/metabolism* ; Disease Models, Animal ; Liver/metabolism* ; Mice, Inbred C57BL