Objective To observe the effect of quercetin on mechanical allodynia,astrocyte activation,and upregulation of pain-related transient receptor potential vanilloid 1(TRPV1)and P2X purinoceptor 3(P2X3)in mice with paclitaxel-induced peripheral neuropathy.Methods Twenty-four C57BL/6 mice were divided randomly into control,model,and model+quercetin groups(n=8 mice per group).Paclitaxel(total dose 8 mg/kg)was injected intraperitoneally into mice in the model and model+quercetin groups to establish the model.Mice in the control group were injected intraperitoneally with the same volume of vehicle.On day 8 after the first injection,mice in the model+quercetin group were injected with 60 mg/kg quercetin solution orally and mice in the other groups were injected with the same volume of vehicle.Mechanical pain was measured by the von Frey test.Activation of astrocytes in the spinal dorsal horn was detected by immunofluorescence.Expression levels of TRPV1 and P2X3 in dorsal root ganglia were detected by immunofluorescence and Western Blot.Results(1)Compared with model group,the mechanical pain of mice in model+quercetin group were relieved.(2)Compared with model group,the activation of astrocytes and the expressions of TRPV1 and P2X3 in mice of model+quercetin group were alleviated(P＜0.05).Conclusions Quercetin can significantly reduce mechanical pain in mice with paclitaxel-induced peripheral neuropathy.This mechanism maybe related to alleviating the activation of astrocytes in the spinal dorsal horn and reducing expression of TRPV1 and P2X3 in the dorsal root ganglia.

OBJECTIVES: To explore ferroptosis-related genes in osteoporosis through bioinformatic analysis and in vitro study. METHODS: Osteoporosis-related genes were identified from dataset GSE35958 in the Gene Expression Omnibus database; and the ferroptosis-related genes were identified from the FerrDb database. These were intersected with the differentially expressed genes in GSE35958 to obtain ferroptosis-related genes in osteoporosis. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis were performed for the differentially expressed genes. And Spearman correlation and protein-protein interaction network analysis were performed. Then, the hub genes of ferroptosis in osteoporosis were screened by Degree, MNC, EPC, MCC and DMNC in Cytoscape software CytoHubba plugin; and analyzed with receiver operating characteristic (ROC) curves. The bone marrow mesenchymal stem cells from osteoporosis patients (osteoporosis group) and non-osteoporosis patients (control group) were subjected to quantitative reverse transcription polymerase chain reaction to detect the messenger RNA expression of ferroptosis hub genes in both groups. RESULTS: A total of 32 differentially expressed genes related to ferroptosis in osteoporosis were identified, including 26 up-regulated genes and 6 down-regulated genes. GO enrichment analysis showed that the identified genes were mainly involved in intercellular adhesion, lipid metabolism and cytokine response. KEGG enrichment analysis showed that the genes were mainly involved in signaling pathways of adhesive plaques, MAPK, PI3K-Akt, and Wnt. Spearman correlation analysis showed correlation among differentially expressed genes. Six hub genes for ferroptosis in osteoporosis were obtained, namely MAPK3, CDKN1A, MAP1LC3A, TNF, RELA, and TGF-β1. ROC curve analysis showed that these hub genes had good diagnostic performance in osteoporosis and may become potential biomarkers of osteoporosis. In vitro experiments confirmed significant differences in these hub genes between the control group and the osteoporosis group (all P<0.05). CONCLUSIONS This study has identified six ferroptosis-related hub genes in osteoporosis, which may be used as novel biomarkers for the early diagnosis and treatment of osteoporosis.
Osteoporosis/genetics* ; Humans ; Computational Biology ; Ferroptosis/genetics* ; Protein Interaction Maps/genetics* ; Gene Ontology ; Mesenchymal Stem Cells/metabolism* ; Gene Expression Profiling ; Databases, Genetic

Objective To set up an objective criterion for BI-RADS assessment.Methods The breast sonograms of 1 938 female cases were retrospectively studied which had been confirmed by pathology from January to September 2011 and 2012 January.1 660 cases during 2011 were model cases,and the importance of each single feature in distinguishing between benign and malignant was obtained with Chi square and OR value.A detailed criterion of BI-RADS assessment category was set up based on US-BI-RADS.Results Eighteen of 24 lexicons were statistically significant distinguished between benign and malignant breast masses(P ＜ 0.05).The lexicons were divided into major suspicious signs,middle ones and minor ones assigned 3 points,2 points and 1 point,and a scoring model was established as follows:Score =3 * (X1 + X2 + … + X6) + 2 * (X7 + X8 + … + X12) + (X9 + X10 + … + X18).Based on BI-RADS,the positive predictive value of model cases was 1.5％,6.9％,22.1％,62.5％,96.1％ followed by category 3,4A,4B,4C and 5,and it was 1.4％,3.4％,21.1％,69.4％,92.7％ in test cases.Conclusions The scoring model could be useful for BI-RADS final assessment more objectively,and could make it more convenient to predict the risk of breast cancer.