OBJECTIVE To investigate the effects of galangin （GLA） on autophagy and apoptosis of chondrocytes in knee osteoarthritis （KOA） rats by regulating the adenosine monophosphate-activated protein kinase （AMPK）/mammalian target of rapamycin （mTOR）/UNC-51-like kinase 1 （ULK1） signaling pathway. METHODS KOA rat model was constructed and separated into model group， L-GLA， M-GLA， H-GLA groups [subcutaneous injection of 100， 200， 400 μg/kg GLA]， GLA+Compound C group [subcutaneous injection of 400 μg/kg GLA+0.2 mg/kg AMPK inhibitor Compound C]， with 10 rats in each group. Additionally， 10 normally fed rats were selected as the sham operation group. After the last medication， the degree of knee joint swelling of rats in each group was detected； the pathology of knee joints in KOA rats was observed. The serum expressions of matrix metalloproteinase 13 （MMP-13） and interleukin-1β （IL-1β） in KOA rats were detected； the autophagy of chondrocytes in KOA rats was observed； the chondrocyte apoptosis in KOA rats was detected； the phosphorylation of AMPK/mTOR/ULK1 pathway-related proteins in cartilage tissue of knee joint were detected in rats. RESULTS Compared with the sham operation group， the arrangement of articular chondrocytes in the model group was disordered， with nuclear pyknosis and severe fibrosis of the articular cartilage layer， accompanied by a large amount of inflammatory cell infiltration； the degree of joint swelling， the number of autophagic vacuoles and apoptosis rate of chondrocytes， serum levels of MMP-13 and IL-1β， and the phosphorylation of mTOR protein in cartilage tissue of knee joint were all increased significantly （P＜0.05）， while the phosphorylation of AMPK and ULK1 protein were all decreased significantly in cartilage tissue of knee joint （P＜0.05）. Compared with the model group， L- GLA， M-GLA， H-GLA groups showed significant improvement in joint cartilage injury and reduced infiltration of inflammatory cells in rats. The above quantitative indicators were significantly reversed in a dose-dependent manner，except the number of autophagic vacuoles increased significantly （P＜0.05）. Compared with the H-GLA group， the GLA+ Compound C group showed aggravated cartilage tissue of joint cartilage injury and inflammatory cell infiltration in rats， and the above quantitative indicators were reversed significantly （P＜0.05）. CONCLUSIONS GLA can promote autophagy and inhibit apoptosis of chondrocytes in KOA rats， the mechanism of which may be associated with activating AMPK/mTOR/ULK1 signaling pathway.

ObjectiveTo explore the effects of the Tibetan medicine Sanwei Doukoutang （SWDK） on cognitive dysfunction in mice suffering from Alzheimer's disease （AD） and its related mechanism. MethodsFifty SPF 5 × FAD mice were randomly divided into model group， total ginsenoside group（0.04 g·kg^-1）， high-， medium-， and low-dose groups of SWDK （32.60， 16.30， 8.15 g·kg^-1）， with 10 mice in each group， and ten wild-type mice of the same age were used as the normal group， male and female in 1∶1. Gavage administration was performed once daily for 8 weeks. The Morris water maze test and contextual fear memory experiment were used to observe learning and memory function. Hematoxylin-eosin （HE） staining was utilized to observe the changes in the pathomorphology of brain tissue in mice. The levels of synaptophysin （SYP） and postsynaptic dense substance 95 （PSD95） in mice serum were detected by enzyme-linked immunosorbent assay （ELISA）. The positive expression of brain-derived neurotrophic factor（BDNF） in the dentate gyrus （DG） region of mouse brain tissue was observed by immunohistochemistry （IHC）. The protein levels of BDNF， Wnt family member 3A（Wnt3a）， and β-catenin were detected in the hippocampus of mice by Western blot. ResultsCompared with the normal group of mice， the model group of mice had significantly more complex swimming routes and lower swimming speed （P<0.01）， significantly lower percentage of time spent in the target quadrant （P<0.01）， and a significantly lower percentage of freezing time （P<0.05）. The number of neurons in the hippocampal region of mice was obviously reduced and unevenly arranged. The levels of SYP and PSD95（P<0.01） in the serum of mice were reduced， and the positive expression of BDNF in the DG region of the brain tissue of mice was reduced. The levels of hippocampal BDNF， Wnt3a， and β-catenin proteins in the hippocampus of mice were obviously reduced （P<0.05， P<0.01）. Compared with the model group， the mice in the SWDK group and the total ginsenoside group had significantly shorter swimming routes， the high- and medium- dose SWDK groups significantly higher swimming speeds （P<0.01）， significantly higher percentage of time spent in the target quadrant （P<0.01）， obviously higher percentage of Freezing time （P<0.05）， and obviously more neurons in the hippocampal region of the mice with tighter arrangement. The mice had elevated levels of serum SYP （P<0.05， P<0.01）， PSD95 （P<0.01）， increased BDNF-positive cells in the DG region of brain tissue， and obviously elevated levels of BDNF， Wnt3a， and β-catenin proteins in the hippocampus of mice （P<0.05， P<0.01）. ConclusionSWDK can significantly improve the cognitive dysfunction of AD mice， and its mechanism may be related to regulating the Wnt/β-catenin signaling pathway， which promotes BDNF expression and thereby enhances synaptic plasticity， allowing neuronal signaling to be restored.

ObjectiveTo explore the effects of the Tibetan medicine Sanwei Doukoutang （SWDK） on cognitive dysfunction in mice suffering from Alzheimer's disease （AD） and its related mechanism. MethodsFifty SPF 5 × FAD mice were randomly divided into model group， total ginsenoside group（0.04 g·kg^-1）， high-， medium-， and low-dose groups of SWDK （32.60， 16.30， 8.15 g·kg^-1）， with 10 mice in each group， and ten wild-type mice of the same age were used as the normal group， male and female in 1∶1. Gavage administration was performed once daily for 8 weeks. The Morris water maze test and contextual fear memory experiment were used to observe learning and memory function. Hematoxylin-eosin （HE） staining was utilized to observe the changes in the pathomorphology of brain tissue in mice. The levels of synaptophysin （SYP） and postsynaptic dense substance 95 （PSD95） in mice serum were detected by enzyme-linked immunosorbent assay （ELISA）. The positive expression of brain-derived neurotrophic factor（BDNF） in the dentate gyrus （DG） region of mouse brain tissue was observed by immunohistochemistry （IHC）. The protein levels of BDNF， Wnt family member 3A（Wnt3a）， and β-catenin were detected in the hippocampus of mice by Western blot. ResultsCompared with the normal group of mice， the model group of mice had significantly more complex swimming routes and lower swimming speed （P<0.01）， significantly lower percentage of time spent in the target quadrant （P<0.01）， and a significantly lower percentage of freezing time （P<0.05）. The number of neurons in the hippocampal region of mice was obviously reduced and unevenly arranged. The levels of SYP and PSD95（P<0.01） in the serum of mice were reduced， and the positive expression of BDNF in the DG region of the brain tissue of mice was reduced. The levels of hippocampal BDNF， Wnt3a， and β-catenin proteins in the hippocampus of mice were obviously reduced （P<0.05， P<0.01）. Compared with the model group， the mice in the SWDK group and the total ginsenoside group had significantly shorter swimming routes， the high- and medium- dose SWDK groups significantly higher swimming speeds （P<0.01）， significantly higher percentage of time spent in the target quadrant （P<0.01）， obviously higher percentage of Freezing time （P<0.05）， and obviously more neurons in the hippocampal region of the mice with tighter arrangement. The mice had elevated levels of serum SYP （P<0.05， P<0.01）， PSD95 （P<0.01）， increased BDNF-positive cells in the DG region of brain tissue， and obviously elevated levels of BDNF， Wnt3a， and β-catenin proteins in the hippocampus of mice （P<0.05， P<0.01）. ConclusionSWDK can significantly improve the cognitive dysfunction of AD mice， and its mechanism may be related to regulating the Wnt/β-catenin signaling pathway， which promotes BDNF expression and thereby enhances synaptic plasticity， allowing neuronal signaling to be restored.

Objective:To explore the prognostic value of systemic immune-inflammatory index(SII)combined with tumor burden score (TBS) (hereinafter referred to as STS) in patients with intrahepatic cholangiocarcinoma (ICC) after radical resection, and to construct a nomogram model.Methods:The clinical data (including the degree of tumor differentiation, vascular cancer thrombus, and lymph node metastasis, etc.) of 258 ICC patients who received radical resection at People′s Hospital of Zhengzhou University (170 cases, training set) and Cancer Hospital of Zhengzhou University (88 cases, validation set) from January 1, 2016 to January 31, 2020 were retrospectively analyzed and graded by SII, TBS and STS. Multivariate Cox regression analysis were used to identify independent factors affecting the prognosis of patients with ICC. Kaplan-Meier survival curve and receiver operating characteristic curve (ROC) were drawn to evaluate the predictive efficiency of SII, TBS and STS in the overall survival of patients with ICC after radical resection. The nomogram prediction model was constructed and evaluate the performance of nomogram model using consistency index (C-index) and calibration curve.Results:Among 170 ICC patients in the training set, there were 106 cases of SII grade 1 and 64 cases of SII grade 2; 137 cases of TBS grade 1 and 33 cases of TBS grade 2; and 98 cases of STS grade 1, 47 cases of STS grade 2, and 25 cases of STS grade 3. Among 88 ICC patients in the validation set, there were 33 cases of SII grade 1 and 55 cases of SII grade 2; 66 cases of TBS grade 1 and 22 cases of TBS grade 2; and 30 case of STS grade 1, 39 cases of TBS grade 2, and 19 cases of TBS grade 3.The multivariate Cox regression analysis showed that tumor differentiation degree (highly differentiated vs. moderately differentiated HR=0.157, 95% confidence interval(95% CI) 0.045 to 0.546, highly differentiated vs. poorly differentiated HR=0.452, 95% CI 0.273 to 0.750), STS (grade 3 vs. grade 2 HR=1.966, 95% CI 1.148 to 3.469; grade 3 vs. grade 1 HR=1.405, 95% CI 0.890 to 2.216), vascular cancer thrombus ( HR=2.006, 95% CI 1.313 to 3.066), nerve invasion ( HR=1.865, 95% CI 1.221 to 2.850), and lymph node metastasis ( HR=1.802, 95% CI 1.121 to 2.896) were independent influencing factors of overall survival in ICC patients after radical resection (all P<0.05). The Kaplan-Meier survival curve showed that SII, TBS, and STS were independent influencing factors of overall survival in ICC patients (all P<0.05). The results of ROC analysis showed that the areas under the curve of SII, TBS and STS in predicting overall survival of ICC patients after radical resection were 0.566 (95% CI 0.479 to 0.652), 0.585 (95% CI 0.499 to 0.672), and 0.657 (95% CI 0.522 to 0.692), respectively. Tumor differentiation, vascular tumor thrombus, nerve invassion, lymph node metastasis, and STS were included to constract the nomogram model. The C-indexes of the training set and validation set based on the nomogram model were 0.792 (95% CI 0.699 to 0.825) and 0.776 (95% CI 0.716 to 0.833), respectively. The calibration curves of the survival rate of the training set and the validation set were close to the reference lines, and the nomogram model had better predictive ability in both the training set and the validation set. Conclusions:Preoperative STS grading is an effective and practical predictor of overall survival in ICC patients after radical section. Compared with SII and TBS alone, it has better predictive value for the prognosis of patients with ICC.

Precancerous lesions of gastric cancer is a key stage in the development of gastric cancer.The reprogramming of glucose metabolism is a prominent feature of precancerous lesions of gastric cancer.Hypoxic microenvironment and hypoxia-inducible factors are important factors influencing the occurrence of glucose metabolic reprogramming.This article summarized the relationship between hypoxic microenvironment and the reprogramming of glucose metabolism in precancerous lesions of gastric cancer,and concluded the relevant research on TCM compounds and effective components to improve hypoxic microenvironment and further regulate glycolysis for the treatment of this disease.It was concluded that the mechanism may be the inhibition of angiogenesis,regulation of signaling pathways and key proteins of glycolysis,expression of multiple enzymes,reduction of lactate secretion,inhibition of cell malignant proliferation and invasion.It explored the mechanism of Chinese materia medica in improving hypoxic microenvironment and regulating glycolysis,so as to provide reference for the prevention and treatment of precancerous lesions of gastric cancer.

Objective:To construct and validate a machine learning model for preoperative prediction of perineural invasion (PNI) status in intrahepatic cholangiocarcinoma (ICC).Methods:Clincial data of 329 patients, including 245 admitted to Zhengzhou University People's Hospital from January 2018 to June 2023 and 84 admitted to the Affiliated Cancer Hospital of Zhengzhou University from January 2013 to January 2020 were retrospectively analyzed. Patients were divided into a training set ( n=231) and a validation set ( n=98). Clinicopathological data including age, gender, hepatitis B virus (HBV) infection status were collected. Predictive variables were determined using least absolute shrinkage and selection operator (LASSO) regression analysis. Six machine learning algorithms including random forest (RF), logistic regression, and linear kernel-based support vector machine were selected to construct the preoperative prediction model for PNI in ICC. Performance metrics of the model were calculated using a confusion matrix, and the final model was selected. The model performance was evaluated in the validation set. Calibration curves were plotted to evaluate the final model, and a Pareto chart was used to visualize the importance of predictive variables. Results:LASSO regression identified nine predictive variables included in the prediction model, including carbohydrate antigen 19-9 (CA19-9), HBV infection status, alkaline phosphatase, alanine aminotransferase, prothrombin time, total bilirubin, albumin, neutrophil times gamma-glutamyl transferase to lymphocyte ratio, and tumor burden score. Among the trained six models, the area under the curve (AUC) of the RF model was 0.909, with a sensitivity of 0.842 and an accuracy of 0.870. Compared with the AUC of the RF model, the AUCs of the other 5 models were lower (all P<0.05). The AUC of the RF model for predicting PNI in ICC in validation set was 0.736. Calibration curves showed good fit of the RF model's prediction of PNI in ICC in both training and validation sets. The Pareto chart showed that CA19-9 was the most important predictive variable in the model, followed by HBV infection status. Conclusion:The machine learning model based on the RF algorithm has a high accuracy in preoperative prediction of PNI status in ICC.

Objective:A predictive nomogram model for the prognosis of intrahepatic cholangiocarcinoma (ICC) patients after curative resection was constructed based on the albumin-bilirubin score and tumor burden score (ATS) grade, and the predictive performance of the nomogram model was evaluated.Methods:Retrospective analysis of clinical data was made, from ICC patients who underwent curative resection at Zhengzhou University People's Hospital and Zhengzhou University Cancer Hospital from January 2016 to January 2020. A total of 258 patients were included in the study, with 140 males and 118 females, with an average age of (56.5±9.5) years. The 258 ICC patients were randomly divided into a training set ( n=174) and a testing set ( n=84) in a 7∶3 ratio. Single-factor and multi-factor Cox regression analyses were performed to identify prognostic factors for ICC patients of the training set, and then a nomogram model was constructed. The performance of the nomogram model was evaluated by using the concordance index (C-index), calibration curve, and risky decision curve analysis. Results:In the training set, univariate Cox regression analysis indicated that albumin-bilirubin (ALBI), tumor burden score (TBS), carcinoembryonic antigen (CEA), tumor differentitation, lymphvascular invasion and ATS significantly influenced overall survival after radical resection for ICC (all P<0.05). Multifactorial Cox regression analysis revealed that ATS grade, CEA, tumor differentiation, lymphovascular invasion, and AJCC N stage are independent risk factors for the prognosis of ICC patients after curative resection (all P<0.05). Assessment of the postoperative survival prediction model based on multifactorial Cox regression yielded a C-index of 0.775(95% CI: 0.747-0.841) for the training set and 0.731(95% CI: 0.668-0.828) for the testing set. The calibration curves for both the training and testing sets indicated strong predictive capability of the model. Additionally, the risk decision curve also suggested high net benefit of the model. Conclusions:The preoperative ATS grade is an independent factor affecting the survival after ICC radical resection. The nomogram model constructed based on ATS grade demonstrates excellent predictive value for postoperative prognosis in ICC patients.

Objective:To study the factors influencing survival after radical resection in patients with intrahepatic cholangiocarcinoma (ICC), and to construct a nomogram on survival prediction.Methods:The clinical data of 139 patients with ICC who underwent radical resection at the People's Hospital of Zhengzhou University from June 2018 to December 2021 were retrospectively analyzed. There are 69 males and 70 females, aged (59.5±10.2) years old. These patients were divided into two groups based on a 3: 1 ratio by using the random number method: the test group ( n=104) and the validation group ( n=35). Data from the test group was used to construct a nomagram and data from the validation group was used to validate the predictive power of the nomagram. Univariate and multivariate Cox regression analyses were used to analyse factors influencing survival on the test group patients and to construct a nomogram. The predictive accuracy of the nomogram was determined by receiver operating characteristic (ROC) curves, concordance index (C-index) and calibration curves. Results:The results of the multivariate regression analysis showed that a combined hemoglobin, albumin, lymphocyte and platelet immunoinflammation (HALP) score <37.1 ( HR=1.784, 95% CI: 1.047-3.040), CA19-9 > 35U/ml ( HR=2.352, 95% CI: 1.139-4.857), poorly differentiated tumor ( HR=2.475, 95% CI: 1.237-4.953) and vascular invasion ( HR=1.897, 95% CI: 1.110-3.244) were independent risk factors that affected prognosis of patients with ICC after radical resection (all P<0.05). The AUCs of the nomogram in the test group in predicting the overall survival at 1, 2 and 3 years of patients with ICC after radical resection were 0.808, 0.853 and 0.859, respectively. There was good consistency between the prediction of the nomogram and actual observation. The predicted C-index of the total survival period of the test group was 0.765 (95% CI: 0.704-0.826), and the C-index of the validation group was 0.759 (95% CI: 0.673-0.845). Conclusion:A HALP score <37.1, CA19-9>35 U/ml, poorly differentiated tumour and vascular invasion were independent risk factors for prognosis of ICC patients after radical resection. The nomogram was established based on the above factors and showed good performance in predicting overall survival after radical resection in patients with ICC.

Objective:To construct a nomogram prediction model for survival after radical surgical resection of intrahepatic cholangiocarcinoma (ICC) based on the albumin-bilirubin index (ALBI), and to evaluate its predictive efficacy.Methods:From January 2016 to January 2020, 170 patients with ICC who underwent radical surgical resection at the People's Hospital of Zhengzhou University were retrospectively analyzed. There were 90 males and 80 females, aged (58.5±10.6) years old. Based on a ratio of 7∶3 by the random number table, the patients were divided into the training set ( n=117) and the internal validation set ( n=53). The training set was used for nomogram model construction, and the validation set was used for model validation and evaluation. Follow up was conducted through outpatient reexamination and telephone contact. The Kaplan-Meier method was used for survival analysis, and a nomogram was drawn based on variables with a P<0.05 in multivariate Cox regression analysis. The predictive strength of the predictive model was evaluated by analyzing the consistency index (C-index), calibration curve, and clinical decision curve of the training and validation sets. Results:Multivariate Cox regression analysis showed that carbohydrate antigen 19-9 (CA19-9) ≥37 U/ml ( HR=1.99, 95% CI: 1.10-3.60, P=0.024), ALBI≥-2.80 ( HR=2.43, 95% CI: 1.40-4.22, P=0.002), vascular tumor thrombus ( HR=2.34, 95% CI: 1.40-3.92, P=0.001), and the 8th edition AJCC N1 staging ( HR=2.18, 95% CI: 1.21-3.95, P=0.010) were independent risk factors affecting postoperative survival of ICC patients after curative resection. The predictive model constructed based on the above variables was then evaluated, and the C-index of the model was 0.76. Calibration curve showed the predicted survival curve of ICC patients at 3 years after surgery based on the model was well-fitted to the 45° diagonal line which represented actual survival. Clinical decision curve analysis showed that the model had a significant positive net benefit in both the training and validation sets. Conclusion:The nomograph model for survival rate after radical resection of ICC was constructed based on four variables: ALBI, CA19-9, vascular tumor thrombus, and AJCC N staging (8th edition) in this study. This model provided a reference for more accurate prognosis evaluation and treatment selection plan for ICC patients.

Objective:To establish and validate a preoperative differentiateon model of intrahepatic cholangiocarcinoma (ICC) and combined hepatocellular carcinoma (CHC) based on the inflammatory markers and conventional clinical indicators.Methods:The clinical data of 116 patients with ICC or CHC admitted to Henan Provincial People's Hospital from January 2018 to March 2023 were retrospectively analyzed, including 74 males and 42 females, aged (58.5±9.4) years old. The data of 83 patients were used to establish the differentiation model as the training group, including 50 cases of ICC and 33 cases of CHC. The data of 33 patients were used to validate the model as the validation group, including 20 cases of ICC and 13 cases of CHC. The clinical data including the platelet-to-lymphocyte ratio (PLR), systemic immune inflammation index (SII), prognostic inflammatory index (PII), prognostic nutritional index (PNI), neutrophil-to-lymphocyte ratio (NLR) and lymphocyte-to-monocyte ratio (LMR) were collected and analyzed. The receiver operating characteristic (ROC) curve was used to analyze the best cut-off values of PLR, SII, PII, PNI, NLR and LMR. Univariate and multivariate logistic regression analysis were used to determine the differential factors between ICC and CHC. The R software was used to draw the nomogram, calculate the area under the curve (AUC) to evaluate the model accuracy, and draw the calibration chart and the decision curve to evaluate the predictive efficacy of the model.Results:Univariate logistic regression analysis showed that liver cirrhosis, history of hepatitis, alpha fetoprotein, carbohydrate antigen 199, gamma-glutamyltransferase (GGT), PLR, PNI and inflammation score (IS) could be used to differentiate ICC from CHC (all P<0.05). The indicators identified in univariate analysis were included in multivariate logistic regression analysis. The results showed that absence of liver cirrhosis, GGT>60 U/L, PNI>49.53, and IS<2 indicated the pathology of ICC (all P<0.05). Based on the above four factors, a nomogram model was established to differentiate the ICC and CHC. The AUC of ROC curve of the nomogram model in the training and validation groups were 0.851 (95% CI: 0.769-0.933) and 0.771 (95% CI: 0.594-0.949), respectively. The sensitivities were 0.760 and 0.750, and the specificities were 0.818 and 0.769, respectively. The calibration chart showed that the predicted curve fitted well to the reference line. The decision curve showed that the model has a clear positive net benefit. Conclusion:The nomogram model based on inflammatory markers showed a good differentiation performance of ICC and CHC, which could benefits the individualized treatment.