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2型糖尿病微血管病变的代谢组学标志物和预测模型研究 被引量:3
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作者 张益红 林云志 +1 位作者 魏永越 叶小龙 《江苏预防医学》 CAS 2022年第6期627-631,654,共6页
目的运用胆汁酸-脂肪酸代谢组学标志物建立2型糖尿病微血管病变预测模型。方法回顾性分析2019年6—10月某医院72例2型糖尿病住院患者,以是否发生糖尿病微血管病变分为病变组(20例)和无病变组(52例),利用患者临床资料,通过弹性网络回归... 目的运用胆汁酸-脂肪酸代谢组学标志物建立2型糖尿病微血管病变预测模型。方法回顾性分析2019年6—10月某医院72例2型糖尿病住院患者,以是否发生糖尿病微血管病变分为病变组(20例)和无病变组(52例),利用患者临床资料,通过弹性网络回归筛选与微血管病变相关危险因素,构建风险得分,将风险得分和微血管病变结局建立logistic回归模型,通过ROC曲线下面积(AUC)评估模型效果。结果弹性网络回归筛选十八碳二烯酸(C18∶2)、γ-十八碳三烯酸(γ-C18∶3)和AA/DHA比值3种代谢组学标志物,及糖化血红蛋白(HbA1c)、总胆红素(tbil)、间接胆红素(ibil)、谷丙转氨酶(ALT)、高密度脂蛋白(HDL)等5种生化指标,分别构建生化指标风险、代谢标志物风险、代谢标志物-生化指标综合模型,AUC分别为0.879(95%CI:0.791~0.967)、0.834(95%CI:0.724~0.943)、0.894(95%CI:0.812~0.971)。结论建立的代谢组学标志物-生化指标糖尿病微血管病变预测模型,预测效果较好,可为糖尿病患者预后评估提供参考。 展开更多
关键词 2型糖尿病 微血管病变 预测模型 代谢组学标志物 弹性网络回归模型
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Advances and Challenges of Exosome Metabolomics in Body Fluids
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作者 CAO Yiqing HOU Jingxin +1 位作者 LIU Jianye LI Yan 《高等学校化学学报》 SCIE EI CAS CSCD 北大核心 2024年第11期1-15,共15页
Exosomes,ubiquitously present in body fluids,serve as non-invasive biomarkers for disease diagnosis,monitoring,and treatment.As intercellular messengers,exosomes encapsulate a rich array of proteins,nucleic acids,and ... Exosomes,ubiquitously present in body fluids,serve as non-invasive biomarkers for disease diagnosis,monitoring,and treatment.As intercellular messengers,exosomes encapsulate a rich array of proteins,nucleic acids,and metabolites,although most studies have primarily focused on proteins and RNA.Recently,exosome metabolomics has demonstrated clinical value and potential advantages in disease detection and pathophysiology,despite significant challenges,particularly in exosome isolation and metabolite detection.This review discusses the significant technical challenges in exosome isolation and metabolite detection,highlighting the advancements in these areas that support the clinical application of exosome metabolomics,and illustrates the potential of exosomal metabolites from various body fluids as biomarkers for early disease diagnosis and treatment. 展开更多
关键词 EXOSOME Metabolomics Body fluid BIOMARKER Disease diagnosis
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预测抗甲状腺药物治疗Graves病复发的分子标志物 被引量:1
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作者 崔雯锦 相萍萍 +1 位作者 陈国芳 刘超 《中国临床研究》 CAS 2022年第1期110-115,共6页
抗甲状腺药物(ATD)治疗Graves病(GD)有较高的复发率,寻找可以判断ATD治疗GD预后的标志物十分重要。近来,核酸分子标志物,如单核苷酸基因多态性(SNP)和微小RNA(microRNAs)以及代谢组学标志物等分子标志物逐渐被用于GD的诊断和预后评估。... 抗甲状腺药物(ATD)治疗Graves病(GD)有较高的复发率,寻找可以判断ATD治疗GD预后的标志物十分重要。近来,核酸分子标志物,如单核苷酸基因多态性(SNP)和微小RNA(microRNAs)以及代谢组学标志物等分子标志物逐渐被用于GD的诊断和预后评估。其中,SNP在预测ATD治疗GD的缓解或复发中有较大价值。明确上述小分子物质与ATD治疗后GD复发的相关性,有助于寻找新的影响GD预后的因素,为治疗决策提供更精准的指导。本文对新型分子标志物在GD复发风险预测中的价值和未来研究方向做一综述。 展开更多
关键词 GRAVES病 复发 核酸分子标志 代谢组学标志物
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Nuclear magnetic resonance spectroscopy as a new approach for improvement of early diagnosis and risk stratification of prostate cancer 被引量:3
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作者 Bo YANG Guo-qiang LIAO +5 位作者 Xiao-fei WEN Wei-hua CHEN Sheng CHENG Jens-Uwe STOLZENBURG Roman GANZER Jochen NEUHAUS 《Journal of Zhejiang University-Science B(Biomedicine & Biotechnology)》 SCIE CAS CSCD 2017年第11期921-933,共13页
Prostate cancer (PCa) is the second most common male cancer worldwide and the fifth leading cause of death from cancer in men. Early detection and risk stratification is the most effective way to improve the surviva... Prostate cancer (PCa) is the second most common male cancer worldwide and the fifth leading cause of death from cancer in men. Early detection and risk stratification is the most effective way to improve the survival of PCa patients. Current PCa biomarkers lack sufficient sensitivity and specificity to cancer. Metabolite biomarkers are evolving as a new diagnostic tool. This review is aimed to evaluate the potential of metabolite biomarkers for early detection, risk assessment, and monitoring of PCa. Of the 154 identified publications, 27 and 38 were original papers on urine and serum metabolomics, respectively. Nuclear magnetic resonance (NMR) is a promising method for measuring concentrations of metabolites in complex samples with good reproducibility, high sensitivity, and simple sample processing. Especially urine-based NMR metabolomics has the potential to be a cost-efficient method for the early detection of PCa, risk stratification, and monitoring treatment eff^cacy. 展开更多
关键词 Prostate cancer Metabolomics Nuclear magnetic resonance (NMR) BIOMARKER
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