Objective To investigate the effect of ketamine on the delayed rectifier outward potassium currents (IK) using whole-cell patch clamp technique. Methods Pyramidal neurons were enzymatically isolated from Wistar rat hippocampus. The effect of ketamine on the IK was assessed using whole-cell patch clamp technique. We measured the amplitude of the delayed outward rectifier IK by activating depolarizing pulse from -50 mV to 40 mV. Different concentrations of ketamine were added and potassium currents were measured. Results IK was inhibited by ketamine in a concentration-dependent manner. The five concentrations of ketamine (10, 30, 100, 300, 1000 ?mol/L) reduced peak IK currents by (10 ? 4)% , (19?4)%, (31 ?5)%, (50?7)%, (54?8) % respectively, with a mean IC50 of (100?18)?mol/L and Hill coefficient of 1.33?0.48. The V1/2 of activation curve was shifted from (1.82 ? 0.20) mV to (9.30 ? 1.03) mV (n = 8, P

OBJECTIVE: To explore the correlations of echocardiographic parameters in patients with gout. METHODS: The hospitalization data and medical records of patients with gout between January, 2012 and June, 2019 were retrieved from the database of Anhui Provincial Hospital of Traditional Chinese Medicine, and the echocardiographic parameters and clinical laboratory test results of the inflammatory, immunological and metabolic indicators were analyzed. SPSS 22.0, SPSS Clementine 11.1 Aprior and other statistical software were used to determine the association rules and carry out correlation analysis, heat map analysis and multi-factor logistic regression analysis of the indicators. RESULTS: Heat map analysis showed that the expressions of EF and SV were the most significant, followed by AODd, LADs, LVDd and FS. Cluster analysis showed that AODd, EF, FS, LADs, LVDd, and SV were all in cluster 1, and IVSTd, LVPWTd, MPAD, Pmax, and RVDd were in cluster 2. Correlation analysis showed that in the 383 patients, EF was negatively correlated with LVDd ( < 0.05) and positively correlated with FS and SV ( < 0.05); AODd was positively correlated with IVSTd, LADs, LVDd, LVPWTd, RVDd, SV, and ESR ( < 0.05); FS was positively correlated with EF and SV ( < 0.05) and negatively correlated with LVDd ( < 0.05);IVSTd was positively correlated with AODd, LADs, LVPWTd, and complement C4 ( < 0.05); LADs were positively correlated with AODd, IVSTd, MPAD, RVDd, and SV ( < 0.05); LVDd was positively correlated with AODd, IVSTd ( < 0.05), and negatively correlated with LVDd and complement C3 ( < 0.05); MPAD and LADs, HDLC and TC were positively correlated ( < 0.05)and negatively correlated with Pmax ( < 0.05); Pmax was positively correlated with LVDd, RVDd and SV ( < 0.05)and negatively correlated with FS and MPAD ( < 0.05); RVDd was positively correlated with AODd, LADs, LVDd, Pmax, SV ( < 0.05); SV was positively correlated with AODd, EF, LADs, LVDd, Pmax, and RVDd ( < 0.05); complement C3 was positively correlated with complement C4 and CRP ( < 0.05), and negatively correlated with LVPWTd ( < 0.05); complement C4 was positively correlated with IVSTd, complement C3, CRP, and ESR ( < 0.05); CRP was positively correlated with complement C3, complement C4, IgA, IgG ( < 0.05), and negatively correlated with TC, HDLC, and TG ( < 0.05); TG was positively correlated with HDLC, IgM, and TC ( < 0.05), and negatively correlated with CRP ( < 0.05); HDLC was positively correlated with MPAD, HDLC and TC ( < 0.05) and negatively correlated with CRP ( < 0.05); IgA was positively correlated with CRP, IgG and IgM ( < 0.05); IgG was positively correlated with CRP, IgA and IgM ( < 0.05); IgM is positively correlated with TG, IgA, IgG, UA ( < 0.05) and negatively correlated with CRP ( < 0.05); UA was positively correlated with IgM ( < 0.05); ESR was positively correlated with AODd and complement C4 ( < 0.05); HCY was negatively correlated with RVDd ( < 0.05); TC was positively correlated with MPAD and TG ( < 0.05), and negatively correlated with CRP ( < 0.05). The increase of Pmax was significantly associated with the increase of LDL-C, UA, complement C4, TG, HCY, HDL-C, IgG, ESR, CRP, and complement C3; the increase of SV was associated with the elevations of UA, LDL-C, complement C4, HDL-C, CRP, IgG, HCY, TC, ESR, TG, and complement C3. Multivariate logistic regression analysis indicated that FS was positively correlated with LDL-C ( < 0.05), Pmax was negatively correlated with IgM ( < 0.05), and SV was negatively correlated with ESR ( < 0.05). CONCLUSIONS The changes of echocardiographic parameters in patients with gout are correlated with the increase in inflammation, immunity, and metabolic indexes. Patients with a history of smoking and drinking do not show obvious changes in cardiac function. The changes in metabolic indexes are risk factors for changes in echocardiographic parameters.
Echocardiography ; Gout ; Humans ; Inflammation ; Retrospective Studies ; Risk Factors

OBJECTIVE: To detect the differentially expressed inflammatory proteins in acute gouty arthritis (AGA) with protein chip. METHODS: The Raybiotech cytokine antibody chip was used to screen the proteomic expression in serum samples of 10 AGA patients and 10 healthy individuals. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis were applied to determine the biological function annotation of differentially expressed proteins and the enrichment of signal pathways. ELISA method was used to verify the differential protein expression in 60 AGA patients and 60 healthy subjects. The ROC curve was employed to evaluate the diagnostic value of differential proteins in AGA patients. RESULTS: According to|log CONCLUSIONS Proteomics can be applied to identify the biomarkers of AGA, which may be used for risk prediction and diagnosis of AGA patients.
Arthritis, Gouty/diagnosis* ; Cytokines/genetics* ; Gene Expression Profiling ; Gene Expression Regulation ; Humans ; Inflammation ; Protein Array Analysis ; Proteomics

Purpose To explore the subcortical structure characteristics in autism spectrum disorder(ASD)aged 12-18 years old and the developmental characteristics of abnormal regions with age.Materials and Methods A total of 102 adolescents aged 12-18 years old meeting the diagnostic criteria for ASD in diagnostic and statistical manual,fifth edition and 42 gender and age matched typically developing controls were enrolled from March 2013 to January 2021 in Peking University Sixth Hospital.Structural magnetic resonance imaging scans were performed on all participants.The freeSurfer software was used to process the 3D T1 images of all participants and segment the subcortical regions.Covariance analysis was performed to compare the volumes of subcortical regions between the two groups.Analysis of variance and covariance were used to explore the developmental differences of brain regions with significant group differences within the ASD and control groups in the age groups of 12-13,14-15 and 16-18,as well as between the ASD and control groups in these age groups.Results Compared to the control group,the volumes of the right caudate,right pallidum,left hippocampus,and corpus callosum anterior region were significantly increased in the ASD group(F=4.522,5.955,7.191,5.326,P<0.05).The volume of the corpus callosum anterior region showed significant differences among the aged 12-13,14-15 and 16-18 years groups of the control group(F=5.248,P=0.01),while there was no significant difference among these three groups of the ASD group(F=2.345,P=0.101).Conclusion Adolescents with ASD aged 12-18 years show abnormalities in multiple subcortical structures,and the developmental characteristics of the corpus callosum anterior region are different from typically developing controls,suggesting that the brains of adolescents with ASD have distinct developmental features.