This study was aimed to explore the associations between the combined effects of several polymorphisms in the PPAR-γ and RXR-α gene and environmental factors with the risk of metabolic syndrome by back-error propaga...This study was aimed to explore the associations between the combined effects of several polymorphisms in the PPAR-γ and RXR-α gene and environmental factors with the risk of metabolic syndrome by back-error propaga- tion artificial neural network （BPANN）. We established the model based on data gathered from metabolic syndrome patients （n = 1012） and normal controls （n = 1069） by BPANN. Mean impact value （MIV） for each input variable was calculated and the sequence of factors was sorted according to their absolute MIVs. Generalized multifactor dimensionality reduction （GMDR） confirmed a joint effect of PPAR-9＂ and RXR-a based on the results from BPANN. By BPANN analysis, the sequences according to the importance of metabolic syndrome risk fac- tors were in the order of body mass index （BMI）, serum adiponectin, rs4240711, gender, rs4842194, family history of type 2 diabetes, rs2920502, physical activity, alcohol drinking, rs3856806, family history of hypertension, rs1045570, rs6537944, age, rs17817276, family history of hyperlipidemia, smoking, rs1801282 and rs3132291. However, no polymorphism was statistically significant in multiple logistic regression analysis. After controlling for environmental factors, A1, A2, B1 and B2 （rs4240711, rs4842194, rs2920502 and rs3856806） models were the best models （cross-validation consistency 10/10, P = 0.0107） with the GMDR method. In conclusion, the interaction of the PPAR-γ and RXR-α gene could play a role in susceptibility to metabolic syndrome. A more realistic model is obtained by using BPANN to screen out determinants of diseases of multiple etiologies like metabolic syndrome.展开更多
目的基于分子对接技术探究天花粉活性成分与2型糖尿病(type 2 diabetes mellitus,T2DM)靶点的相互作用。方法通过中药系统药理学数据库与分析平台(Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform,T...目的基于分子对接技术探究天花粉活性成分与2型糖尿病(type 2 diabetes mellitus,T2DM)靶点的相互作用。方法通过中药系统药理学数据库与分析平台(Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform,TCMSP)和SwissTargetPrediction数据库获得天花粉活性成分及作用靶点,在GeneCards和DisGeNET数据库中获得T2DM靶点。将天花粉活性成分靶点与T2DM靶点取交集,获取药物-疾病共有靶点,导入DAVID数据库进行基因本体(gene ontology,GO)和京都基因与基因组百科全书(Kyoto Encyclopedia of Genes and Genomes,KEGG)通路富集分析。构建共有靶点的蛋白质互作网络(protein-protein interaction networks,PPI),分析得出关键靶点。最后,利用Sybyl软件进行分子对接,验证活性成分与关键靶点相互作用。结果天花粉活性成分为仙人掌甾醇(schottenol)和菠菜甾醇(spinasterol),获得药物-疾病共有靶点21个。PPI、GO和KEGG富集分析表明,天花粉可能作用于过氧化物酶体增殖物激活受体(peroxisome proliferator-activated receptors,PPARs),进而通过PPAR信号通路和胰岛素抵抗信号通路调节糖脂代谢。分子对接表明,天花粉活性成分仙人掌甾醇和菠菜甾醇均与关键靶点过氧化物酶体增殖物激活受体γ(PPARγ)有较强的结合作用。结论天花粉活性成分仙人掌甾醇和菠菜甾醇,可能通过作用于T2DM靶点PPARγ改善胰岛素抵抗。展开更多
Uncontrolled microglial activation is decisively involved in the neuroinflammatory pathogenesis of brain diseases. Consequently, suppression of microglial overactivation appears to be a strategy for the prevention of ...Uncontrolled microglial activation is decisively involved in the neuroinflammatory pathogenesis of brain diseases. Consequently, suppression of microglial overactivation appears to be a strategy for the prevention of nerve injury. In this paper, a novel vanadium complex, vanadyl N-(p-N,Ndimethylaminophenylcarbamoylmethyl)iminodiacetate(VO(p-dmada)), was synthesized from vanadyl sulfate and N,N-dimethyl-p-phenylenediamine, which was structurally characterized by Fourier transform infrared spectrum and ESI-MS analysis. The effect of VO(p-dmada) on neuroinflammation was investigated by using the models of lipopolysaccharide(LPS)-induced BV2 microglial cells and BALB/c mice.Our data demonstrated that VO(p-dmada) significantly suppressed microglial activation by downregulating inflammatory mediators and associated proteins, and inactivating nuclear factor-κ B(NF-κ B) signaling pathway. VO(p-dmada) also upregulated peroxisome proliferator activated receptor gamma(PPARγ) by reducing transglutaminase 2 and heat shock protein 60 expression. Co-treatment with PPARγ antagonist GW9662 significantly impeded the inhibitory effect of VO(p-dmada) on LPS-induced neuroinflammation.These cumulative findings demonstrated that VO(p-dmada) is a potential new drug for the treatment of neuroinflammation-related neurodegenerative diseases.展开更多
基金supported by the National Natural Science Foundation of China Grant No.30771858Jiangsu Provincial Natural Science Foundation Grant No.BK2007229Priority Academic Program Development of Jiangsu Higher Education Institutions(PAPD)
文摘This study was aimed to explore the associations between the combined effects of several polymorphisms in the PPAR-γ and RXR-α gene and environmental factors with the risk of metabolic syndrome by back-error propaga- tion artificial neural network （BPANN）. We established the model based on data gathered from metabolic syndrome patients （n = 1012） and normal controls （n = 1069） by BPANN. Mean impact value （MIV） for each input variable was calculated and the sequence of factors was sorted according to their absolute MIVs. Generalized multifactor dimensionality reduction （GMDR） confirmed a joint effect of PPAR-9＂ and RXR-a based on the results from BPANN. By BPANN analysis, the sequences according to the importance of metabolic syndrome risk fac- tors were in the order of body mass index （BMI）, serum adiponectin, rs4240711, gender, rs4842194, family history of type 2 diabetes, rs2920502, physical activity, alcohol drinking, rs3856806, family history of hypertension, rs1045570, rs6537944, age, rs17817276, family history of hyperlipidemia, smoking, rs1801282 and rs3132291. However, no polymorphism was statistically significant in multiple logistic regression analysis. After controlling for environmental factors, A1, A2, B1 and B2 （rs4240711, rs4842194, rs2920502 and rs3856806） models were the best models （cross-validation consistency 10/10, P = 0.0107） with the GMDR method. In conclusion, the interaction of the PPAR-γ and RXR-α gene could play a role in susceptibility to metabolic syndrome. A more realistic model is obtained by using BPANN to screen out determinants of diseases of multiple etiologies like metabolic syndrome.
文摘目的基于分子对接技术探究天花粉活性成分与2型糖尿病(type 2 diabetes mellitus,T2DM)靶点的相互作用。方法通过中药系统药理学数据库与分析平台(Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform,TCMSP)和SwissTargetPrediction数据库获得天花粉活性成分及作用靶点,在GeneCards和DisGeNET数据库中获得T2DM靶点。将天花粉活性成分靶点与T2DM靶点取交集,获取药物-疾病共有靶点,导入DAVID数据库进行基因本体(gene ontology,GO)和京都基因与基因组百科全书(Kyoto Encyclopedia of Genes and Genomes,KEGG)通路富集分析。构建共有靶点的蛋白质互作网络(protein-protein interaction networks,PPI),分析得出关键靶点。最后,利用Sybyl软件进行分子对接,验证活性成分与关键靶点相互作用。结果天花粉活性成分为仙人掌甾醇(schottenol)和菠菜甾醇(spinasterol),获得药物-疾病共有靶点21个。PPI、GO和KEGG富集分析表明,天花粉可能作用于过氧化物酶体增殖物激活受体(peroxisome proliferator-activated receptors,PPARs),进而通过PPAR信号通路和胰岛素抵抗信号通路调节糖脂代谢。分子对接表明,天花粉活性成分仙人掌甾醇和菠菜甾醇均与关键靶点过氧化物酶体增殖物激活受体γ(PPARγ)有较强的结合作用。结论天花粉活性成分仙人掌甾醇和菠菜甾醇,可能通过作用于T2DM靶点PPARγ改善胰岛素抵抗。
基金financially supported by grants from the National Natural Science Foundation of China(No.21877081)the China Postdoctoral Science Foundation(No.2021M692210)+2 种基金Guangdong Provincial Key S&T Program(No.2018B030336001)the Shenzhen Science and Technology Innovation Commission(No.JCYJ20200109110001818)the Shenzhen-Hong Kong Institute of brain Science-Shenzhen Fundamental Research institutions(No.2022SHIBS0003)。
文摘Uncontrolled microglial activation is decisively involved in the neuroinflammatory pathogenesis of brain diseases. Consequently, suppression of microglial overactivation appears to be a strategy for the prevention of nerve injury. In this paper, a novel vanadium complex, vanadyl N-(p-N,Ndimethylaminophenylcarbamoylmethyl)iminodiacetate(VO(p-dmada)), was synthesized from vanadyl sulfate and N,N-dimethyl-p-phenylenediamine, which was structurally characterized by Fourier transform infrared spectrum and ESI-MS analysis. The effect of VO(p-dmada) on neuroinflammation was investigated by using the models of lipopolysaccharide(LPS)-induced BV2 microglial cells and BALB/c mice.Our data demonstrated that VO(p-dmada) significantly suppressed microglial activation by downregulating inflammatory mediators and associated proteins, and inactivating nuclear factor-κ B(NF-κ B) signaling pathway. VO(p-dmada) also upregulated peroxisome proliferator activated receptor gamma(PPARγ) by reducing transglutaminase 2 and heat shock protein 60 expression. Co-treatment with PPARγ antagonist GW9662 significantly impeded the inhibitory effect of VO(p-dmada) on LPS-induced neuroinflammation.These cumulative findings demonstrated that VO(p-dmada) is a potential new drug for the treatment of neuroinflammation-related neurodegenerative diseases.
