ObjectiveTo investigate the possible mechanism by which Zhiqiao Gancao Decoction （枳壳甘草汤， ZGD） delays intervertebral disc degeneration （IDD） based on the Hippo-yes-associated protein （YAP）/transcriptional co-activator with PDZ-binding motif （TAZ） signaling pathway. MethodsA total of 50 SD rats were randomly divided into sham surgery group， model group， low-dose ZGD group， high-dose ZGD group， and high-dose ZGD + inhibitor group， with 10 rats in each group. In the sham surgery group， the rats were pierced in the skin and muscle at the Co6/7/8 segments of the tail with a 21G needle （depth approximately 2 mm） without damaging the intervertebral disc. In the other groups， rats were injected with a 21G needle at the Co6/7/8 segments of the tail to establish an IDD model by piercing the tail intervertebral disc 5 mm. One week after modeling， rats in the low-dose and high-dose ZGD groups were given 6.24 and 12.24 g/（kg·d） of the decoction via gastric gavage， respectively. The high-dose ZGD + inhibitor group was given 12.24 g/（kg·d） of the decoction and an intraperitoneal injection of YAP/TAZ inhibitor Verteporfin 10 mg/kg. The sham surgery and model groups were given 5 ml/（kg·d） of normal saline via gavage. The gavage was given once a day， and the intraperitoneal injection was given every other day. After 4 weeks of continuous intervention， the pathological changes of the tail intervertebral discs were observed using HE staining， Oil Red O-Green staining， and Toluidine Blue staining. Immunohistochemistry was used to detect the expression of aggrecan and MMP3 in the nucleus pulposus. TUNEL fluorescence staining was performed to detect apoptosis in the nucleus pulposus， and the apoptosis rate was calculated. Western blot was used to detect the Hippo-YAP/TAZ signaling pathway， including YAP， phosphorylated YAP （p-YAP）， phosphorylated MST1/2 （p-MST1/2）， phosphorylated TAZ （p-TAZ） and apoptosis-related proteins， such as Cleaved Caspase 3， P53， Bcl-2 and Bax. ResultsCompared with sham surgery group， the rats in the model group showed significant degenerative changes in the intervertebral disc. The levels of aggrecan， Bcl-2， and YAP proteins in the nucleus pulposus decreased， while the levels of p-MST1/2， p-YAP， p-TAZ， P53， Bax， Cleaved Caspase 3， MMP3 proteins， and the apoptosis rate increased （P < 0.01）. Compared with the model group， the drug intervention groups showed partial recovery in intervertebral disc degeneration. The levels of aggrecan， Bcl-2， and YAP proteins increased， while the levels of p-MST1/2， p-YAP， p-TAZ， P53， Bax， Cleaved Caspase 3， MMP3 proteins， and the apoptosis rate decreased （P＜0.05 or P＜0.01）. The high-dose ZGD group showed more significant recovery in intervertebral disc degeneration compared to the low-dose ZGD group， with a decrease in the levels of p-MST1/2， p-YAP， p-TAZ， P53， Bax， Cleaved Caspase 3， MMP3 proteins， and apoptosis rate， and an increase in the levels of aggrecan， Bcl-2， and YAP proteins （P＜0.05 or P＜0.01）. Compared with the high-dose ZGD group， the high-dose ZGD + inhibitor group showed a reduced recovery in intervertebral disc degeneration， with an increase in the levels of p-MST1/2， p-YAP， p-TAZ， P53， Bax， Cleaved Caspase 3， MMP3 proteins， and apoptosis rate， and a decrease in the levels of aggrecan， Bcl-2， and YAP proteins （P＜0.05 or P＜0.01）. ConclusionZGD may delay intervertebral disc degeneration by inhibiting the phosphorylation of YAP in the nucleus pulposus， maintaining the function of the Hippo-YAP/TAZ signaling pathway， and reducing apoptosis of nucleus pulposus cells.

OBJECTIVE To explore the effect and mechanism of Zhiqiao gancao decoction （ZQGCD） on pathological angiogenesis of degenerative intervertebral disc. METHODS The rats were randomly divided into sham operation group （normal saline）， model group （normal saline）， hypoxia inducible factor-1α （HIF-1α） inhibitor （YC-1） group [2 mg/（kg·d）， tail vein injection]， and ZQGCD low-dose， medium-dose and high-dose groups [3.06， 6.12， 12.24 g/（kg·d）]， with 8 rats in each group. Except for sham operation group， lumbar disc degeneration model of rat was constructed in all other groups. After modeling， they were given relevant medicine once a day， for consecutive 3 weeks. After the last medication， pathological changes and angiogenesis of the intervertebral disc tissue in rats were observed； the levels of inflammatory factors [interleukin-1β （IL-1β）， IL-6， tumor necrosis factor-α （TNF-α）] and the expressions of angiogenesis-related proteins [HIF-1α， vascular endothelial growth factor （VEGF）， VEGF receptor 2 （VEGFR2）， angiotensin 1（Ang 1）， Ang 2] in the com intervertebral disc tissue in rats were all determined. In cell experiment， the primary nucleus pulposus cells were isolated and cultured from rats， and cellular degeneration was induced using 50 ng/mL TNF-α. The cells were divided into blank control group （10% blank control serum）， TNF-α group （10% blank control serum）， YC-1 group （10% blank control serum+0.2 mmol/L YC-1）， and 5%， 10%， 15% drug-containing serum group （5%， 10%， 15% drug-containing serum）. After 24 hours of intervention， the nucleus pulposus cells were co-cultured with HUVEC. The expressions of Collagen Ⅱ， matrix metalloproteinase-3 （MMP-3） in nucleus pulposus cells were detected. HUVEC proliferation， migration and tube forming ability were detected， and the expression levels of the HIF-1α/VEGF/Ang signal axis and angiogenesis- related proteins （add MMP-2， MMP-9） in HUVEC were detected. RESULTS Animal experiments had shown that compared with model group， the positive expression of CD31 in the intervertebral disc tissues of rats in each drug group was down-regulated （P＜ 0.05）， the levels of inflammatory factors and angiogenesis-related proteins were decreased significantly （P＜0.05）， and the pathological changes in the intervertebral disc were alleviated. Cell experiments had shown that compared with TNF-α group， the expression of Collagen Ⅱ in nucleus pulposus cells of all drug groups was significantly up-regulated （P＜0.05）， and the expression of MMP-3 was significantly down-regulated （P＜0.05）； the proliferation， migration and tubulogenesis of HUVEC were significantly weakened （P＜0.05）. The mRNA and protein expressions of HIF-1α， VEGF， Ang 2 as well as the expression of angiogenesis-related proteins （except for the expression of Ang 2 mRNA and HIF-1α， VEGFR2， Ang 2 protein in 5% drug- containing serum group） were significantly down-regulated （P＜0.05）. CONCLUSIONS ZQGCD may inhibit the HIF-1α/VEGF/ Ang signal axis to weaken the angiogenic ability of vascular endothelial cells， improve pathological angiogenesis in the intervertebral disc， and delay the degeneration of the intervertebral disc.

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.

Objective This study aimed to investigate the correlation between insulin resistance score after insulin treatment in elderly patients with coronary heart disease and type 2 diabetes mellitus and cardiovascular outcomes.Methods Elderly patients with coronary heart disease complicated with type 2 diabetes mellitus were selected as the study subjects.All enrolled patients received insulin treatment with an initial dose of 3 U,administered subcutaneously before meals.The total daily dose of insulin was controlled at 0.3-0.8 U·kg-1.The occurrence of major adverse cardiovascular events(MACE)was recorded,and the correlation between insulin resistance score(METS-IR)and cardiovascular outcomes,as well as the predictive value for the occurrence of adverse cardiovascular events was analyzed.Results Before and after insulin treatment in elderly patients with coronary heart disease and type 2 diabetes mellitus,the average body mass index(BMI)were(26.03±3.12)and(25.23±0.02)kg·m-2,triglycerides(TG)were(123.60±21.46)and(113.70±19.75)mg·dL-1,total cholesterol(TC)were(155.80±14.19)and(153.40±13.98)mg·dL-1,low-density lipoprotein cholesterol(LDL-C)were(94.58±9.85)and(91.74±9.56)mg·dL-1,high-density lipoprotein cholesterol(HDL-C)were(46.02±4.47)and(49.73±4.83)mg·dL-1,and fasting blood glucose(FBG)were(98.55±10.58)and(93.62±10.05)mg·dL-1,respectively.The METS-IR scores were 39.26±4.80 and 36.89±4.50,respectively.Except for plasma TC,the differences in the above indicators before and after treatment were statistically significant(all P＜0.05).Among the enrolled patients,a total of 48 cases(22.2％)experienced MACE,including 23 cases of hypertension,14 cases of angina pectoris,8 cases of hospitalization for myocardial infarction,3 cases of hospitalization for heart failure.Spearman correlation analysis showed that METS-IR was significantly positively correlated with the incidence of adverse cardiovascular events(P＜0.01).ROC curve analysis indicated that METS-IR had a high predictive value for the occurrence of MACE in elderly patients with coronary heart disease and type 2 diabetes mellitus.Conclusion After insulin treatment in elderly patients with coronary heart disease and type 2 diabetes mellitus,METS-IR was significantly positively correlated with the incidence of adverse cardiovascular events and had good predictive value for cardiovascular outcomes.

Objective To investigate the effect of Jichuan decoction on defecation in rats with slow transit constipation(STC).Methods A total of 36 SD rats were divided into model group,experimental group and control group.Except the control group,STC rat models were established in the other two groups by gavage of 2％rhein acid suspension.The experimental group was given 170％Jichuan decoction of 10 mL·kg-1 by gavage,while the control group and model group were given with 0.9％NaCl by gavage,once a day for 30 days.Fecal dry-wet weight ratio and colon transport time were observed by fecal weighing and recording of first fecal discharge time;substance P(SP)and vasoactive peptide(VIP)contents in plasma were detected by kit;changes in intestinal flora were detected by real-time fluorescent quantitative polymerase chain reaction(qRT-PCR).Results The dry-wet ratio of feces in control group,model group and experimental group were(44.86±4.40)％,(53.44±3.52)％and(44.28±4.33)％,respectively;the colon transport time were(340.17±34.91),(424.67±37.26)and(377.36±38.87)min,respectively;plasma SP were(79.86±7.56),(60.30±2.41)and(78.84±5.83)pg·mL-1,respectively;plasma VIP were(30.56±2.87),(23.38±6.62)and(28.39±2.37)pg·mL-1,respectively;the numbers of Bifidobacterium were 7.77±0.04,5.19±0.09 and 7.45±0.03,respectively;the numbers of Lactobacillus were 6.40±0.07,4.10±0.05 and 6.36±0.08,respectively.There were statistically significant differences in the above indexes between model group and control group,and between experimental group and model group(P＜0.01,P＜0.05).Conclusion Jichuan decoction can improve the defecation of rats with slow transit constipation.

Objective To explore the toxicity of Polygonum multiflorum alcohol extract on 3D hepatospheres.Methods Variations in culture conditions and cell ratios were implemented,followed by the assessment of cell sphere diameter,density,and roundness,aiming to explore the optimal culture conditions.The 3D hepatocyte spheres were divided into control group and experimental-L,-M,-H groups.The experimental-L,-M,-H groups were treated with 0.25,1.00 and 2.50 mg·mL-1 Polygounm multiforum alcohol extract,and the control group was given the same amount of culture medium.The cell viability of the cell spheroids was tested by CellTiter-Glo reagent,the expression level of liver function related genes was detected by fluorescent quantitative polymerase chain reaction(RT-qRCR).The toxicity of cell spheres was detected by double fluorescent staining of living and dead cells.Results The ideal culture condition of cell sphere was 500 cells per micropore,and the cell ratio was HepG2-Huvec-LX-2=8∶1∶1.It displayed the values of 0.91±0.07 for circularity,0.91±0.02 for firmness,1.12±0.14 for aspect ratio,and(170.97±14.79)μm for diameter.On the 3rd,7th,10th and 14th days,the expression levels of albumin(ALB)mRNA were 1.00±0.02,0.96±0.02,0.54±0.07,0.52±0.07,and the expression levels of cytochrome P450 1A2(CYP1A2)mRNA were 1.00±0.10,2.15±0.16,2.45±0.33,1.30±0.03,respectively.The expression levels of multidrug resistance protein 2(MPR2)in the control group and the experimental-L,-M,-H groups were 1.00±0.31,1.38±0.24,1.48±0.06 and 1.90±0.08,respectively;spheroid viability were(98.19±0.49)％,(88.53±0.90)％,(71.60±2.91)％and(56.65±5.41)％.There were statistically significant differences in the above indexes between the experimental-L,-M,-H groups and the control group(all P＜0.05).Conclusion The established hepatocyte sphere co-culture model showed varying degrees of expression of phase Ⅰ/Ⅱ drug metabolism enzymes,transporters,and liver cell specific marker molecule albumin and can be used to evaluate the toxicity of multiflorum multiflorum,which provides further reference for the clinical application of multiflorum multiflorum.