Background:Choosing the appropriate antipsychotic drug(APD)treatment for patients with schizophrenia(SCZ)can be challenging,as the treatment response to APD is highly variable and difficult to predict due to the lack ...Background:Choosing the appropriate antipsychotic drug(APD)treatment for patients with schizophrenia(SCZ)can be challenging,as the treatment response to APD is highly variable and difficult to predict due to the lack of effective biomarkers.Previous studies have indicated the association between treatment response and genetic and epigenetic factors,but no effective biomarkers have been identified.Hence,further research is imperative to enhance precision medicine in SCZ treatment.Methods:Participants with SCZ were recruited from two randomized trials.The discovery cohort was recruited from the CAPOC trial(n=2307)involved 6 weeks of treatment and equally randomized the participants to the Olanzapine,Risperidone,Quetiapine,Aripiprazole,Ziprasidone,and Haloperidol/Perphenazine(subsequently equally assigned to one or the other)groups.The external validation cohort was recruited from the CAPEC trial(n=1379),which involved 8 weeks of treatment and equally randomized the participants to the Olanzapine,Risperidone,and Aripiprazole groups.Additionally,healthy controls(n=275)from the local community were utilized as a genetic/epigenetic reference.The genetic and epigenetic(DNA methylation)risks of SCZ were assessed using the polygenic risk score(PRS)and polymethylation score,respectively.The study also examined the genetic-epigenetic interactions with treatment response through differential methylation analysis,methylation quantitative trait loci,colocalization,and promoteranchored chromatin interaction.Machine learning was used to develop a prediction model for treatment response,which was evaluated for accuracy and clinical benefit using the area under curve(AUC)for classification,R^(2) for regression,and decision curve analysis.Results:Six risk genes for SCZ(LINC01795,DDHD2,SBNO1,KCNG2,SEMA7A,and RUFY1)involved in cortical morphology were identified as having a genetic-epigenetic interaction associated with treatment response.The developed and externally validated prediction model,which incorporated clinical information,PRS,genetic risk score(GRS),and proxy methylation level(proxyDNAm),demonstrated positive benefits for a wide range of patients receiving different APDs,regardless of sex[discovery cohort:AUC=0.874(95%CI 0.867-0.881),R^(2)=0.478;external validation cohort:AUC=0.851(95%CI 0.841-0.861),R^(2)=0.507].Conclusions:This study presents a promising precision medicine approach to evaluate treatment response,which has the potential to aid clinicians in making informed decisions about APD treatment for patients with SCZ.Trial registration Chinese Clinical Trial Registry(https://www.chictr.org.cn/),18 Aug 2009 retrospectively registered:CAPOC-ChiCTR-RNC-09000521(https://www.chictr.org.cn/showproj.aspx?proj=9014),CAPEC-ChiCTRRNC-09000522(https://www.chictr.org.cn/showproj.aspx?proj=9013).展开更多
目的:建立高效液相色谱-串联质谱法测定蜂王浆中草甘膦、氨甲基膦酸和N-乙酰草甘膦含量的分析方法。方法:样品经0.2mol/L碳酸氢铵水溶液提取,采用Waters PRIME HLB固相萃取小柱净化,以Dikma Polyamino HILIC色谱柱进行色谱分离,多反应监...目的:建立高效液相色谱-串联质谱法测定蜂王浆中草甘膦、氨甲基膦酸和N-乙酰草甘膦含量的分析方法。方法:样品经0.2mol/L碳酸氢铵水溶液提取,采用Waters PRIME HLB固相萃取小柱净化,以Dikma Polyamino HILIC色谱柱进行色谱分离,多反应监测(MRM)监测模式测定,外标法定量。结果:3种化合物在20~400μg/L的浓度范围内线性关系良好,检出限为20μg/kg,定量限位50μg/kg。空白蜂王浆样品的3水平加标回收率为74.0%~96.1%,相对标准偏差为5.1%~9.6%。结论:该方法适用于蜂王浆中草甘膦及其两种代谢物残留的检测。展开更多
伴随着拓扑材料的出现,拓扑物理学成为了当代凝聚态物理的前沿与热点之一.拓扑特性是描述材料的物理量在连续变换下会保持不变的性质(如陈数Chern number),种类包括拓扑绝缘体、外尔和狄拉克等拓扑半金属、拓扑磁材料等.一维手性磁孤子(...伴随着拓扑材料的出现,拓扑物理学成为了当代凝聚态物理的前沿与热点之一.拓扑特性是描述材料的物理量在连续变换下会保持不变的性质(如陈数Chern number),种类包括拓扑绝缘体、外尔和狄拉克等拓扑半金属、拓扑磁材料等.一维手性磁孤子(chiral magnetic solitons),类似于磁性斯格明子(skyrmions),是一类具有拓扑性和准粒子性的磁结构,具有丰富的物理特性和潜在应用价值.本文详细总结了一种具有一维手性磁孤子结构的晶体Cr1/3NbS2,包括其晶体构型、磁相互作用、磁结构、维度调控以及相变物理等物理特性.希望本综述能为研究拓扑磁材料的科研人员提供详实的参考,为将拓扑和手性磁性引入到二维层状材料家族提供研究思路,促进拓扑磁电子学的发展,为相关器件提供更多的材料选择和理论基础.展开更多
基金supported by the National Natural Science Foundation of China(81825009,82071505,81901358)the Chinese Academy of Medical Sciences Innovation Fund for Medical Sciences(2021-I2MC&T-B-099,2019-I2M-5–006)+2 种基金the Program of Chinese Institute for Brain Research Beijing(2020-NKX-XM-12)the King’s College London-Peking University Health Science Center Joint Institute for Medical Research(BMU2020KCL001,BMU2019LCKXJ012)the National Key R&D Program of China(2021YFF1201103,2016YFC1307000).
文摘Background:Choosing the appropriate antipsychotic drug(APD)treatment for patients with schizophrenia(SCZ)can be challenging,as the treatment response to APD is highly variable and difficult to predict due to the lack of effective biomarkers.Previous studies have indicated the association between treatment response and genetic and epigenetic factors,but no effective biomarkers have been identified.Hence,further research is imperative to enhance precision medicine in SCZ treatment.Methods:Participants with SCZ were recruited from two randomized trials.The discovery cohort was recruited from the CAPOC trial(n=2307)involved 6 weeks of treatment and equally randomized the participants to the Olanzapine,Risperidone,Quetiapine,Aripiprazole,Ziprasidone,and Haloperidol/Perphenazine(subsequently equally assigned to one or the other)groups.The external validation cohort was recruited from the CAPEC trial(n=1379),which involved 8 weeks of treatment and equally randomized the participants to the Olanzapine,Risperidone,and Aripiprazole groups.Additionally,healthy controls(n=275)from the local community were utilized as a genetic/epigenetic reference.The genetic and epigenetic(DNA methylation)risks of SCZ were assessed using the polygenic risk score(PRS)and polymethylation score,respectively.The study also examined the genetic-epigenetic interactions with treatment response through differential methylation analysis,methylation quantitative trait loci,colocalization,and promoteranchored chromatin interaction.Machine learning was used to develop a prediction model for treatment response,which was evaluated for accuracy and clinical benefit using the area under curve(AUC)for classification,R^(2) for regression,and decision curve analysis.Results:Six risk genes for SCZ(LINC01795,DDHD2,SBNO1,KCNG2,SEMA7A,and RUFY1)involved in cortical morphology were identified as having a genetic-epigenetic interaction associated with treatment response.The developed and externally validated prediction model,which incorporated clinical information,PRS,genetic risk score(GRS),and proxy methylation level(proxyDNAm),demonstrated positive benefits for a wide range of patients receiving different APDs,regardless of sex[discovery cohort:AUC=0.874(95%CI 0.867-0.881),R^(2)=0.478;external validation cohort:AUC=0.851(95%CI 0.841-0.861),R^(2)=0.507].Conclusions:This study presents a promising precision medicine approach to evaluate treatment response,which has the potential to aid clinicians in making informed decisions about APD treatment for patients with SCZ.Trial registration Chinese Clinical Trial Registry(https://www.chictr.org.cn/),18 Aug 2009 retrospectively registered:CAPOC-ChiCTR-RNC-09000521(https://www.chictr.org.cn/showproj.aspx?proj=9014),CAPEC-ChiCTRRNC-09000522(https://www.chictr.org.cn/showproj.aspx?proj=9013).
文摘目的:建立高效液相色谱-串联质谱法测定蜂王浆中草甘膦、氨甲基膦酸和N-乙酰草甘膦含量的分析方法。方法:样品经0.2mol/L碳酸氢铵水溶液提取,采用Waters PRIME HLB固相萃取小柱净化,以Dikma Polyamino HILIC色谱柱进行色谱分离,多反应监测(MRM)监测模式测定,外标法定量。结果:3种化合物在20~400μg/L的浓度范围内线性关系良好,检出限为20μg/kg,定量限位50μg/kg。空白蜂王浆样品的3水平加标回收率为74.0%~96.1%,相对标准偏差为5.1%~9.6%。结论:该方法适用于蜂王浆中草甘膦及其两种代谢物残留的检测。
文摘伴随着拓扑材料的出现,拓扑物理学成为了当代凝聚态物理的前沿与热点之一.拓扑特性是描述材料的物理量在连续变换下会保持不变的性质(如陈数Chern number),种类包括拓扑绝缘体、外尔和狄拉克等拓扑半金属、拓扑磁材料等.一维手性磁孤子(chiral magnetic solitons),类似于磁性斯格明子(skyrmions),是一类具有拓扑性和准粒子性的磁结构,具有丰富的物理特性和潜在应用价值.本文详细总结了一种具有一维手性磁孤子结构的晶体Cr1/3NbS2,包括其晶体构型、磁相互作用、磁结构、维度调控以及相变物理等物理特性.希望本综述能为研究拓扑磁材料的科研人员提供详实的参考,为将拓扑和手性磁性引入到二维层状材料家族提供研究思路,促进拓扑磁电子学的发展,为相关器件提供更多的材料选择和理论基础.
