充分利用灵活性资源的调节作用能够优化电网的可用输电能力(available transfer capability, ATC),提高系统运行的安全性和经济性,因此提出一种计及源荷储多调节资源的两阶段随机动态ATC优化方法。首先,采用动态场景分析法对新能源出力...充分利用灵活性资源的调节作用能够优化电网的可用输电能力(available transfer capability, ATC),提高系统运行的安全性和经济性,因此提出一种计及源荷储多调节资源的两阶段随机动态ATC优化方法。首先,采用动态场景分析法对新能源出力不确定性建模,建立激励型需求响应模型和基于放电深度的储能等效循环寿命成本模型。其次,第一阶段构建日前两阶段源荷储随机优化经济调度模型,以优化结果作为基态,建立日前随机动态ATC计算模型以确定阻塞时段。然后,第二阶段构建日前随机动态ATC双层优化模型,上层以阻塞时段的ATC最大为目标,下层以基态运行成本最小为目标,上层确定储能和负荷响应情况与下层基态机组出力情况相互交互,采用Karush-Kuhn-Tucker(KKT)条件将下层模型转化以实现双层模型的求解。算例分析表明,通过优化源荷储运行方式能够在提升ATC的同时兼顾系统运行的经济性。展开更多
KRAB相关蛋白1(KRAB-associated protein 1,KAP1)是最早于1996年通过亲合色谱分离并克隆得到的一种转录辅因子,因能与含KRAB结构域的锌指蛋白家族(zinc family proteins,ZFPs)成员结合而得名。KAP1是一种具有多功能的蛋白质,它参与组蛋...KRAB相关蛋白1(KRAB-associated protein 1,KAP1)是最早于1996年通过亲合色谱分离并克隆得到的一种转录辅因子,因能与含KRAB结构域的锌指蛋白家族(zinc family proteins,ZFPs)成员结合而得名。KAP1是一种具有多功能的蛋白质,它参与组蛋白修饰与染色质重塑、调节DNA甲基化、作为转录共调控因子参与基因调控、参与DNA损伤反应等,并存在磷酸化、乙酰化等多种翻译后修饰。KAP1的表达水平与多种人类恶性肿瘤的发生发展密切相关,并影响肿瘤预后。因此,KAP1有望成为恶性肿瘤的诊断标志物或治疗新靶点。本文主要综述KAP1的结构、功能及其与人类恶性肿瘤发生发展的关系,并进一步探讨KAP1在恶性肿瘤研究中的应用前景,以期为恶性肿瘤的临床诊断和治疗提供参考依据。展开更多
利用生物信息学数据库分析泛素样含PHD和环指结构域蛋白1(UHRF1)在恶性胸膜间皮瘤(MPM)中的表达水平及临床意义。基于TCGA数据库和GTEx数据库差异表达分析UHRF1 m RNA在MPM组织和正常肺组织中的表达水平;使用R软件分析UHRF1 mRNA表达量...利用生物信息学数据库分析泛素样含PHD和环指结构域蛋白1(UHRF1)在恶性胸膜间皮瘤(MPM)中的表达水平及临床意义。基于TCGA数据库和GTEx数据库差异表达分析UHRF1 m RNA在MPM组织和正常肺组织中的表达水平;使用R软件分析UHRF1 mRNA表达量与临床病理参数的相关性;构建Kaplan-Meier模型和单因素多因素COX回归模型分析UHRF1基因在MPM中的预后;利用TIMER2.0数据库分析UHRF1基因与免疫细胞浸润的关系;GSEA分析UHRF1基因发挥功能的主要富集通路。选取8例MPM组织及4例非MPM胸膜组织,通过RT-q PCR的方法验证UHRF1在MPM与非MPM胸膜组织的表达情况。数据库分析结果表明,与正常肺组织相比,UHRF1 m RNA在MPM组织中高表达;UHRF1高表达患者提示MPM患者预后不良;UHRF1基因表达量与CD4^(+)辅助型T细胞2、CD4^(+)效应记忆性T细胞、巨噬细胞等多种免疫细胞浸润水平具有显著的相关性(P<0.01),且显著影响MPM患者的预后。功能富集分析显示,UHRF1主要在DNA复制、蛋白酶体、同源重组等通路中起作用。在收集到的病例样本中,与非MPM胸膜组织相比,UHRF1 mRNA在MPM组织中的表达显著增高(P<0.001)。UHRF1在MPM组织中高表达,可能通过调节DNA甲基化和免疫细胞浸润来影响MPM患者预后,有望成为MPM治疗和预后评估的潜在靶点。展开更多
Objective:Osteosarcoma is a highly aggressive primary malignant bone tumor commonly seen in children and adolescents,with a poor prognosis.Anchorage-dependent cell death(anoikis)has been proven to be indispensable in ...Objective:Osteosarcoma is a highly aggressive primary malignant bone tumor commonly seen in children and adolescents,with a poor prognosis.Anchorage-dependent cell death(anoikis)has been proven to be indispensable in tumor metastasis,regulating the migration and adhesion of tumor cells at the primary site.However,as a type of programmed cell death,anoikis is rarely studied in osteosarcoma,especially in the tumor immune microenvironment.This study aims to clarify prognostic value of anoikis and tumor immune microenvironment-related gene in the treatment of osteosarcoma.Methods:Anoikis-related genes(ANRGs)were obtained from GeneCards.Clinical information and ANRGs expression profiles of osteosarcoma patients were sourced from the therapeutically applicable research to generate effective therapies and Gene Expression Omnibus(GEO)databases.ANRGs highly associated with tumor immune microenvironment were identified by the estimate package and the weighted gene coexpression network analysis(WGCNA)algorithm.Machine learning algorithms were performed to construct long-term survival predictive strategy,each sample was divided into high-risk and low-risk subgroups,which was further verified in the GEO cohort.Finally,based on single-cell RNA-seq from the GEO database,analysis was done on the function of signature genes in the osteosarcoma tumor microenvironment.Results:A total of 51 hub ANRGs closely associated with the tumor microenvironment were identified,from which 3 genes(MERTK,BNIP3,S100A8)were selected to construct the prognostic model.Significant differences in immune cell activation and immune-related signaling pathways were observed between the high-risk and low-risk groups based on tumor microenvironment analysis(all P<0.05).Additionally,characteristic genes within the osteosarcoma microenvironment were identified in regulation of intercellular crosstalk through the GAS6-MERTK signaling pathway.Conclusion:The prognostic model based on ANRGs and tumor microenvironment demonstrate good predictive power and provide more personalized treatment options for patients with osteosarcoma.展开更多
文摘充分利用灵活性资源的调节作用能够优化电网的可用输电能力(available transfer capability, ATC),提高系统运行的安全性和经济性,因此提出一种计及源荷储多调节资源的两阶段随机动态ATC优化方法。首先,采用动态场景分析法对新能源出力不确定性建模,建立激励型需求响应模型和基于放电深度的储能等效循环寿命成本模型。其次,第一阶段构建日前两阶段源荷储随机优化经济调度模型,以优化结果作为基态,建立日前随机动态ATC计算模型以确定阻塞时段。然后,第二阶段构建日前随机动态ATC双层优化模型,上层以阻塞时段的ATC最大为目标,下层以基态运行成本最小为目标,上层确定储能和负荷响应情况与下层基态机组出力情况相互交互,采用Karush-Kuhn-Tucker(KKT)条件将下层模型转化以实现双层模型的求解。算例分析表明,通过优化源荷储运行方式能够在提升ATC的同时兼顾系统运行的经济性。
文摘KRAB相关蛋白1(KRAB-associated protein 1,KAP1)是最早于1996年通过亲合色谱分离并克隆得到的一种转录辅因子,因能与含KRAB结构域的锌指蛋白家族(zinc family proteins,ZFPs)成员结合而得名。KAP1是一种具有多功能的蛋白质,它参与组蛋白修饰与染色质重塑、调节DNA甲基化、作为转录共调控因子参与基因调控、参与DNA损伤反应等,并存在磷酸化、乙酰化等多种翻译后修饰。KAP1的表达水平与多种人类恶性肿瘤的发生发展密切相关,并影响肿瘤预后。因此,KAP1有望成为恶性肿瘤的诊断标志物或治疗新靶点。本文主要综述KAP1的结构、功能及其与人类恶性肿瘤发生发展的关系,并进一步探讨KAP1在恶性肿瘤研究中的应用前景,以期为恶性肿瘤的临床诊断和治疗提供参考依据。
文摘利用生物信息学数据库分析泛素样含PHD和环指结构域蛋白1(UHRF1)在恶性胸膜间皮瘤(MPM)中的表达水平及临床意义。基于TCGA数据库和GTEx数据库差异表达分析UHRF1 m RNA在MPM组织和正常肺组织中的表达水平;使用R软件分析UHRF1 mRNA表达量与临床病理参数的相关性;构建Kaplan-Meier模型和单因素多因素COX回归模型分析UHRF1基因在MPM中的预后;利用TIMER2.0数据库分析UHRF1基因与免疫细胞浸润的关系;GSEA分析UHRF1基因发挥功能的主要富集通路。选取8例MPM组织及4例非MPM胸膜组织,通过RT-q PCR的方法验证UHRF1在MPM与非MPM胸膜组织的表达情况。数据库分析结果表明,与正常肺组织相比,UHRF1 m RNA在MPM组织中高表达;UHRF1高表达患者提示MPM患者预后不良;UHRF1基因表达量与CD4^(+)辅助型T细胞2、CD4^(+)效应记忆性T细胞、巨噬细胞等多种免疫细胞浸润水平具有显著的相关性(P<0.01),且显著影响MPM患者的预后。功能富集分析显示,UHRF1主要在DNA复制、蛋白酶体、同源重组等通路中起作用。在收集到的病例样本中,与非MPM胸膜组织相比,UHRF1 mRNA在MPM组织中的表达显著增高(P<0.001)。UHRF1在MPM组织中高表达,可能通过调节DNA甲基化和免疫细胞浸润来影响MPM患者预后,有望成为MPM治疗和预后评估的潜在靶点。
基金This work was supported by the National Natural Science Foundation(82172594 and 82373046)the Hunan Graduate Research Innovation Project(CX20230318),China.
文摘Objective:Osteosarcoma is a highly aggressive primary malignant bone tumor commonly seen in children and adolescents,with a poor prognosis.Anchorage-dependent cell death(anoikis)has been proven to be indispensable in tumor metastasis,regulating the migration and adhesion of tumor cells at the primary site.However,as a type of programmed cell death,anoikis is rarely studied in osteosarcoma,especially in the tumor immune microenvironment.This study aims to clarify prognostic value of anoikis and tumor immune microenvironment-related gene in the treatment of osteosarcoma.Methods:Anoikis-related genes(ANRGs)were obtained from GeneCards.Clinical information and ANRGs expression profiles of osteosarcoma patients were sourced from the therapeutically applicable research to generate effective therapies and Gene Expression Omnibus(GEO)databases.ANRGs highly associated with tumor immune microenvironment were identified by the estimate package and the weighted gene coexpression network analysis(WGCNA)algorithm.Machine learning algorithms were performed to construct long-term survival predictive strategy,each sample was divided into high-risk and low-risk subgroups,which was further verified in the GEO cohort.Finally,based on single-cell RNA-seq from the GEO database,analysis was done on the function of signature genes in the osteosarcoma tumor microenvironment.Results:A total of 51 hub ANRGs closely associated with the tumor microenvironment were identified,from which 3 genes(MERTK,BNIP3,S100A8)were selected to construct the prognostic model.Significant differences in immune cell activation and immune-related signaling pathways were observed between the high-risk and low-risk groups based on tumor microenvironment analysis(all P<0.05).Additionally,characteristic genes within the osteosarcoma microenvironment were identified in regulation of intercellular crosstalk through the GAS6-MERTK signaling pathway.Conclusion:The prognostic model based on ANRGs and tumor microenvironment demonstrate good predictive power and provide more personalized treatment options for patients with osteosarcoma.
文摘取1 g样品,加入10μg·L^(-1)混合同位素内标溶液、10 m L乙腈、1 m L水和0.5 g氯化钠,匀浆2 min,超声30 min,离心10 min,在上清液中加入2 m L正己烷,振荡5 min,静置分层,在下层相中依次加入200 mg N-丙基乙二胺(PSA)、200 mg C18和1 500 mg无水硫酸镁,振荡5 min,离心10 min。取1 m L上清液,于25℃氮吹至近干,加入1 m L乙酸乙酯复溶,过0.22μm聚四氟乙烯(PTFE)针式过滤头,滤液供气相色谱-串联质谱法分析。在HP-INNOWAX色谱柱上以程序升温条件分离各N-亚硝胺类化合物,以电子轰击离子源电离,多反应监测(MRM)模式检测,同位素内标法定量。结果显示:12种N-亚硝胺类化合物的质量浓度均在一定范围内和对应的响应值与内标响应值的比值呈线性关系,检出限(3S/N)为0.17~0.66μg·kg^(-1)。对5种类型化妆品空白基质进行5,20,100μg·kg^(-1)加标水平的回收试验,回收率为81.6%~117%,测定值的相对标准偏差(n=6)为1.2%~4.8%。方法用于市售5种类型化妆品样品的分析,均未检出12种N-亚硝胺类化合物。
