Objective:To explore the interrelationship between brain functional networks and features in functional magnetic resonance imaging(fMRI)of patients with Alzheimer's disease(AD),and to construct mixed-function networks(MFN),and apply them in machine learning classification models to improve the accuracy of AD classification.Methods:102 AD patients and 227 healthy subjects in the Alzheimer's Neuroimaging Initiative(ADNI)dataset were retrospectively analyzed.The partial correlation brain network of the blood oxygen level dependent(BOLD)signal was calculated and fused with low-frequency wave amplitude(ALFF),fractional low-frequency wave amplitude(fALFF)and local consistency(ReHo)features to construct MFN.Network topology parameters were extracted,and a variety of machine learning classification models were constructed based on MFN topological parameters,accuracy,precision,recall and area under the curve(AUC)were used to evaluate the predictive efficiency of the models.Results:By constructed MFN and calculated intra group to inter group ratio(IIGR),35 features could be obtained from ALFF,fALFF and ReHo feature topological parameter analysis,after rank sum test and FDR correction,there were statistical differences among 28 features(P＜0.05).The classification results show that,all the five classifiers have high classification performance on the test data set.The accuracy,precision and recall rates of random forest(RF),adaptive lifting algorithm(AdaBoost),guided aggregation algorithm(Bagging)and support vector machine(SVM)were all 99.7％,and the AUC values were up to 100％,99.5％,99.1％and 99.5％,respectively.The accuracy(98.5％),precision(98.5％),recall(98.5％),and AUC(99.1％)of the multi-layer perceptron(MLP)were slightly lower than other models,but remained excellent.It was worth noting that RF has the highest AUC value of all models at 100.0％,while Bagging has the lowest AUC value(99.1％)in the integrated approach.The results of performance comparison show that,MFN classification model can significantly improve the recognition and classification of AD disease,and greatly improve the performance of various indicators of the classifier.The results showed that,MFN classification model was superior to intelligent classification based fusion,DBN-based multitask learning,PVT-TSVM,unsupervised learning and clustering,SVM and SVM of degree 3 polynomial kernel function in key indicators such as accuracy(99.13％),AUC(99.42％),recall rate(99.46％)and specificity(99.42％)with plasma proteins,machine learning algorithms.It was further proved that MFN classification model has good generalization ability and robustness in AD disease classification.Conclusion:The AD classification model constructed based on brain mixed function network topology parameters and machine learning can improve the accuracy of AD classification.

Objective:To explore the interrelationship between brain functional networks and features in functional magnetic resonance imaging(fMRI)of patients with Alzheimer's disease(AD),and to construct mixed-function networks(MFN),and apply them in machine learning classification models to improve the accuracy of AD classification.Methods:102 AD patients and 227 healthy subjects in the Alzheimer's Neuroimaging Initiative(ADNI)dataset were retrospectively analyzed.The partial correlation brain network of the blood oxygen level dependent(BOLD)signal was calculated and fused with low-frequency wave amplitude(ALFF),fractional low-frequency wave amplitude(fALFF)and local consistency(ReHo)features to construct MFN.Network topology parameters were extracted,and a variety of machine learning classification models were constructed based on MFN topological parameters,accuracy,precision,recall and area under the curve(AUC)were used to evaluate the predictive efficiency of the models.Results:By constructed MFN and calculated intra group to inter group ratio(IIGR),35 features could be obtained from ALFF,fALFF and ReHo feature topological parameter analysis,after rank sum test and FDR correction,there were statistical differences among 28 features(P＜0.05).The classification results show that,all the five classifiers have high classification performance on the test data set.The accuracy,precision and recall rates of random forest(RF),adaptive lifting algorithm(AdaBoost),guided aggregation algorithm(Bagging)and support vector machine(SVM)were all 99.7％,and the AUC values were up to 100％,99.5％,99.1％and 99.5％,respectively.The accuracy(98.5％),precision(98.5％),recall(98.5％),and AUC(99.1％)of the multi-layer perceptron(MLP)were slightly lower than other models,but remained excellent.It was worth noting that RF has the highest AUC value of all models at 100.0％,while Bagging has the lowest AUC value(99.1％)in the integrated approach.The results of performance comparison show that,MFN classification model can significantly improve the recognition and classification of AD disease,and greatly improve the performance of various indicators of the classifier.The results showed that,MFN classification model was superior to intelligent classification based fusion,DBN-based multitask learning,PVT-TSVM,unsupervised learning and clustering,SVM and SVM of degree 3 polynomial kernel function in key indicators such as accuracy(99.13％),AUC(99.42％),recall rate(99.46％)and specificity(99.42％)with plasma proteins,machine learning algorithms.It was further proved that MFN classification model has good generalization ability and robustness in AD disease classification.Conclusion:The AD classification model constructed based on brain mixed function network topology parameters and machine learning can improve the accuracy of AD classification.

Objective:To explore the relationship between the expressions of miR-217 and miR-4286 in gastric cancer tissues and gastric cancer complicated with Helicobacter pylori(HP)infection,as well as their predictive value for prognosis.Methods:A total of 225 patients who underwent radical gastrectomy for gastric cancer in the First Af-filiated Hospital of Xingtai Medical College from January 2021 to February 2023 were selected and divided into the HP+group and the HP-group according to whether they were complicated with HP infection.The expressions of miR-217 and miR-4286 in gastric cancer tissues were detected by real-time fluorescence quantitative PCR,the rela-tionship between the expressions of miR-217 and miR-4286 and HP infection in patients with gastric cancer was evaluated by Spearman correlation analysis.Regular outpatient reexaminations were conducted for a 2-year follow-up.Gastric cancer patients with recurrence or all-cause death during the follow-up period were included in the poor prognosis group,and the rest were included in the good prognosis group.Univariate and multivariate Logistic regres-sion analysis methods were used to screen the influencing factors of gastric cancer prognosis,the ROC curve was used to evaluate the predictive value of miR-217 and miR-4286 expressions for the prognosis of gastric cancer.Re-sults:Compared with the HP-group,the expressions of miR-217 and miR-4286 in the HP+group were up-regulated(P<0.05),and the expressions of miR-217 and miR-4286 were positively correlated with gastric cancer pa-tients with HP infection(r=0.652,0.485,P<0.05).Compared with the good prognosis group,the proportion of TNM stage Ⅲ,lymph node metastasis and HP infection in the poor prognosis group was higher,and the expressions of miR-217 and miR-4286 were up-regulated,with statistical significance(P<0.05).The results of multivariate Logistic regression analysis showed that TNM stage Ⅲ(OR=1.425),lymph node metastasis(OR=1.548),HP infection(OR=1.465),high expression of miR-217(OR=1.608),and high expression of miR-4286(OR=1.544)are the influencing fac-tors for poor prognosis of gastric cancer(P<0.05).The ROC curve showed that the AUC of the combined prediction of miR-217 and miR-4286 in gastric cancer tissues for poor prognosis in patients with gastric cancer was 0.922,which was higher than that of miR-217(0.817)and miR-4286(0.806)alone(Z=6.527,7.025;both P<0.05).Conclu-sion:The expressions of miR-217 and miR-4286 in gastric cancer tissues are closely related to HP infection in gas-tric cancer patients,and the combination of Mir-217 and Mir-4286 is effective in predicting the poor prognosis after radical gastritis.

Objective:To explore the relationship between the expressions of miR-217 and miR-4286 in gastric cancer tissues and gastric cancer complicated with Helicobacter pylori(HP)infection,as well as their predictive value for prognosis.Methods:A total of 225 patients who underwent radical gastrectomy for gastric cancer in the First Af-filiated Hospital of Xingtai Medical College from January 2021 to February 2023 were selected and divided into the HP+group and the HP-group according to whether they were complicated with HP infection.The expressions of miR-217 and miR-4286 in gastric cancer tissues were detected by real-time fluorescence quantitative PCR,the rela-tionship between the expressions of miR-217 and miR-4286 and HP infection in patients with gastric cancer was evaluated by Spearman correlation analysis.Regular outpatient reexaminations were conducted for a 2-year follow-up.Gastric cancer patients with recurrence or all-cause death during the follow-up period were included in the poor prognosis group,and the rest were included in the good prognosis group.Univariate and multivariate Logistic regres-sion analysis methods were used to screen the influencing factors of gastric cancer prognosis,the ROC curve was used to evaluate the predictive value of miR-217 and miR-4286 expressions for the prognosis of gastric cancer.Re-sults:Compared with the HP-group,the expressions of miR-217 and miR-4286 in the HP+group were up-regulated(P<0.05),and the expressions of miR-217 and miR-4286 were positively correlated with gastric cancer pa-tients with HP infection(r=0.652,0.485,P<0.05).Compared with the good prognosis group,the proportion of TNM stage Ⅲ,lymph node metastasis and HP infection in the poor prognosis group was higher,and the expressions of miR-217 and miR-4286 were up-regulated,with statistical significance(P<0.05).The results of multivariate Logistic regression analysis showed that TNM stage Ⅲ(OR=1.425),lymph node metastasis(OR=1.548),HP infection(OR=1.465),high expression of miR-217(OR=1.608),and high expression of miR-4286(OR=1.544)are the influencing fac-tors for poor prognosis of gastric cancer(P<0.05).The ROC curve showed that the AUC of the combined prediction of miR-217 and miR-4286 in gastric cancer tissues for poor prognosis in patients with gastric cancer was 0.922,which was higher than that of miR-217(0.817)and miR-4286(0.806)alone(Z=6.527,7.025;both P<0.05).Conclu-sion:The expressions of miR-217 and miR-4286 in gastric cancer tissues are closely related to HP infection in gas-tric cancer patients,and the combination of Mir-217 and Mir-4286 is effective in predicting the poor prognosis after radical gastritis.

OBJECTIVE: To explore the potential effects and mechanisms of Liang-Ge-San (LGS) for the treatment of acute respiratory distress syndrome (ARDS) through network pharmacology analysis and to verify LGS activity through biological experiments. METHODS: The key ingredients of LGS and related targets were obtained from the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform. ARDS-related targets were selected from GeneCards and DisGeNET databases. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses were performed using the Metascape Database. Molecular docking analysis was used to confirm the binding affinity of the core compounds with key therapeutic targets. Finally, the effects of LGS on key signaling pathways and biological processes were determined by in vitro and in vivo experiments. RESULTS: A total of LGS-related targets and 496 ARDS-related targets were obtained from the databases. Network pharmacological analysis suggested that LGS could treat ARDS based on the following information: LGS ingredients luteolin, wogonin, and baicalein may be potential candidate agents. Mitogen-activated protein kinase 14 (MAPK14), recombinant V-Rel reticuloendotheliosis viral oncogene homolog A (RELA), and tumor necrosis factor alpha (TNF-α) may be potential therapeutic targets. Reactive oxygen species metabolic process and the apoptotic signaling pathway were the main biological processes. The p38MAPK/NF-κ B signaling pathway might be the key signaling pathway activated by LGS against ARDS. Moreover, molecular docking demonstrated that luteolin, wogonin, and baicalein had a good binding affinity with MAPK14, RELA, and TNF α. In vitro experiments, LGS inhibited the expression and entry of p38 and p65 into the nucleation in human bronchial epithelial cells (HBE) cells induced by LPS, inhibited the inflammatory response and oxidative stress response, and inhibited HBE cell apoptosis (P<0.05 or P<0.01). In vivo experiments, LGS improved lung injury caused by ligation and puncture, reduced inflammatory responses, and inhibited the activation of p38MAPK and p65 (P<0.05 or P<0.01). CONCLUSION LGS could reduce reactive oxygen species and inflammatory cytokine production by inhibiting p38MAPK/NF-κ B signaling pathway, thus reducing apoptosis and attenuating ARDS.
Drugs, Chinese Herbal/pharmacology* ; Respiratory Distress Syndrome/enzymology* ; p38 Mitogen-Activated Protein Kinases/metabolism* ; NF-kappa B/metabolism* ; Animals ; Signal Transduction/drug effects* ; Molecular Docking Simulation ; Humans ; Male ; Network Pharmacology ; Apoptosis/drug effects* ; Mice

OBJECTIVE: To identify the underlying mechanism by which quercetin (Que) alleviates sepsis-related acute respiratory distress syndrome (ARDS). METHODS: In vivo, C57BL/6 mice were assigned to sham, cecal ligation and puncture (CLP), and CLP+Que (50 mg/kg) groups (n=15 per group) by using a random number table. The sepsisrelated ARDS mouse model was established using the CLP method. In vitro, the murine alveolar macrophages (MH-S) cells were classified into control, lipopolysaccharide (LPS), LPS+Que (10 μmol/L), and LPS+Que+acetylcysteine (NAC, 5 mmol/L) groups. The effect of Que on oxidative stress, inflammation, and apoptosis in mice lungs and MH-S cells was determined, and the mechanism with reactive oxygen species (ROS)/p38 mitogen-activated protein kinase (MAPK) pathway was also explored both in vivo and in vitro. RESULTS: Que alleviated lung injury in mice, as reflected by a reversal of pulmonary histopathologic changes as well as a reduction in lung wet/dry weight ratio and neutrophil infiltration (P<0.05 or P<0.01). Additionally, Que improved the survival rate and relieved gas exchange impairment in mice (P<0.01). Que treatment also remarkedly reduced malondialdehyde formation, superoxide dismutase and catalase depletion, and cell apoptosis both in vivo and in vitro (P<0.05 or P<0.01). Moreover, Que treatment diminished the release of inflammatory factors interleukin (IL)-1β, tumor necrosis factor-α, and IL-6 both in vivo and in vitro (P<0.05 or P<0.01). Mechanistic investigation clarifified that Que administration led to a decline in the phosphorylation of p38 MAPK in addition to the suppression of ROS expression (P<0.01). Furthermore, in LPS-induced MH-S cells, ROS inhibitor NAC further inhibited ROS/p38 MAPK pathway, as well as oxidative stress, inflammation, and cell apoptosis on the basis of Que treatment (P<0.05 or P<0.01). CONCLUSION Que was found to exert anti-oxidative, anti-inflammatory, and anti-apoptotic effects by suppressing the ROS/p38 MAPK pathway, thereby conferring protection for mice against sepsis-related ARDS.
Animals ; Sepsis/drug therapy* ; Quercetin/therapeutic use* ; Respiratory Distress Syndrome/enzymology* ; p38 Mitogen-Activated Protein Kinases/metabolism* ; Mice, Inbred C57BL ; Reactive Oxygen Species/metabolism* ; Apoptosis/drug effects* ; Male ; Oxidative Stress/drug effects* ; MAP Kinase Signaling System/drug effects* ; Lung/drug effects* ; Mice ; Lipopolysaccharides ; Macrophages, Alveolar/pathology* ; Inflammation/pathology* ; Protective Agents/therapeutic use*

Traf2- and Nck-interacting kinase (TNIK) is closely related to the cancer occurrence, development, and prognosis. TNIK plays an important role in regulating Wnt/β-catenin pathway, thus becoming a potential target for cancer treatment. Various small-molecule TNIK inhibitors with diverse structures and potent in vitro activities have been developed to treat tumors. However, no TNIK inhibitor has entered clinical phase mainly due to poor selectivity, toxicity, and unsatisfied in vivo anti-tumor efficiency. This review summarizes the research progress of small molecule inhibitors targeting TNIK, with the aim of giving some guidance for future research and development of small-molecule inhibitors.

In this study, ultra-performance liquid chromatography-quadrupole-time-of-flight tandem mass spectrometry(UPLC-Q-TOF-MS~E) was used to analyze the plasma components of Danzhi Xiaoyao Formula after oral administration. Forty-nine plasma components were found in the serum of rats by comparing the compound extract, drug-containing serum, and blank serum. Components, such as 6-hydroxycoumarin, poricoic acid F, deoxoglabrolide, 30-norhederagenin, kanzonol R, 3',6'-di-O-galloylpaeoniflorin, 16α-hydroxytrametenolic acid, 16-deoxyporicoic acid B, 3-O-acetyl-16α-hydroxytrametenolic acid, and 16α,25-dihydroxydehydroeburiconic acid, were first found in rat serum. Behavioral tests, including the tail suspension test, novel object recognition test, and novelty-suppressed feeding test, were conducted for behavioral analysis. It was confirmed that this formula had therapeutic effects on perimenopausal depression. Furthermore, in combination with the network pharmacology method, 53 core targets including MAPK1, HRAS, AKT1, EGFR, and ESR1 were screened, and these targets participated in 165 signaling pathways, including PI3K-AKT, AMPK, VEGFA, MAPK, and HIF-1. In summary, the potential effects of Danzhi Xiaoyao Formula in treating perimenopausal depression are associated with mechanisms in accelerating inflammation repair, improving neuroplasticity, affecting neurotransmitters, regulating estrogen levels, and promoting new blood vessel formation.
Animals ; Rats ; Chromatography, High Pressure Liquid ; Depression/drug therapy* ; Network Pharmacology ; Perimenopause ; Phosphatidylinositol 3-Kinases ; Drugs, Chinese Herbal/pharmacology* ; Molecular Docking Simulation

Abstract: Objective　To analyze the survival status of HIV/AIDS patients aged above 50 years receiving antiviral therapy (ART) in Shanxi Province from 2011 to 2019, and to provide evidence for further improvement of antiviral therapy. Methods　Basic information and follow-up information of HIV/AIDS patients aged above 50 years who first received HIV/AIDS antiviral therapy in Shanxi Province from 2011 to 2019 were collected. Excel database was established and SPSS23.0 software was used for analysis. Retrospective cohort study was conducted. Cox proportional risk regression model was used to analyze the factors influencing survival time. Results　A total of 1 183 subjects were included, of which 172 died, including 84(48.84%) from other causes, 74(43.02%) AIDS-related death and 14 (8.14%) from accidents, suicides and undetermined deaths. Setting AIDS-related deaths as an outcome event, life table analysis showed that the cumulative survival rates at 1, 3, 5, 7 and 9 years after receiving ART were 96.61%, 93.59%, 90.35%, 87.57% and 83.44%, respectively. Multivariate Cox proportional risk model analysis showed that the risk of death in patients aged 60-<70 years group and over 70 age group was 2.53 times (95%CI: 1.51-4.23) and 3.59 times (95%CI: 1.74-7.40) for patients aged the 50-<60 group , respectively. The risk of death in patients with baseline CD4+T lymphocyte (CD4) counts of ≥200/mm3, 50-<200 /mm3 was 0.22 times (95%CI: 0.12-0.41) and 0.37 times (95%CI: 0.21-0.67) for patients with CD4+T lymphocyte counts of <50/mm3. The risk of death in patients with opportunistic infections at baseline was 1.99 times (95%CI: 1.16-3.39) for patients without baseline opportunistic infections. Conclusions　The survival rate of HIV/AIDS patients aged above 50 who received antiviral therapy (ART) in Shanxi Province from 2011 to 2019 was relatively high. To further improve the quality of antiviral treatment in our province, the strategy of "early detection and early treatment" should be continued and improved in the future, and information collection of specific causes of non-AIDS-related deaths among this population should be further strengthened.

Objective:To investigate the clinical features of IgD multiple myeloma (MM) and the effect and prognosis of daratumumab-based combination therapy.Methods:The clinicopathological data of a IgD MM patient with disease progression and extramedullary infiltration treated with daratumumab in the Affiliated Hospital of Qingdao University in December 2019 were retrospectively analyzed.Results:The 74-year-old woman was diagnosed as IgD MM by bone marrow aspiration and immunofixation electrophoresis. The patient was given VD (bortezomib, dexamethasone), RD (lenalidomide, dexamethasone) and ID (ixazomib, dexamethasone) regimens. In June 2020, the patient developed multiple subcutaneous nodules, and she was assessed as progressive disease with extensive extramedullary infiltration. After treated with daratumumab-PAD (liposomal doxorubicin, bortezomib, dexamethasone) regimen, the patient's subcutaneous nodules were significantly reduced and partially disappeared, and the general condition was significantly improved. But the patient was in a cachexia state and finally died of the irregular treatment and disease progression.Conclusions:IgD MM has a low incidence and a short survival period, and there is no uniform standard treatment. The early application of daratumumab combined with proteasome inhibitors, immunomodulators, cytotoxic drugs and hematopoietic stem cell transplantation may improve the overall survival of patients.