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柱前衍生化结合气质联用技术测定实验性高脂血症大鼠血浆中代谢标志物OA

Determination of Metabolic Biomarkers in Plasma of Experimental Hyperlipidemia Rat Model by Pre-Column Derivatization Combined with GC-MS

中文摘要英文摘要

目的:建立柱前衍生化结合气质联用技术测定高脂血症大鼠血浆中内源性代谢物的分析方法,初步研究高脂血症大鼠血浆中内源性代谢标志物.方法:将SD大鼠随机分为正常对照组和模型组,采用高脂饲料喂养复制实验性高脂血症大鼠模型,眼眶取血,柱前衍生化,采用GC-MS建立分析测定方法并进行方法学考察,包括精密度、重现性、稳定性.对正常对照组与实验性高脂血症组两组大鼠的血浆样品进行检测,对潜在代谢标志物进行鉴定指认.结果:建立了基于GS-MS的实验性高脂血症血浆代谢组学分析方法,该方法精密度、重复性和稳定性试验的相对峰面积RSD值均小于10%.结论:该方法快速、准确、重复性好,可用于高脂血症大鼠血浆中代谢标志物的测定,该方法可为代谢组学在高脂血症的应用提供一定的参考.

Objective:By pre-column derivatization to establish a gas chromatography-mass spectrography method for determination of protential metabolic biomarkers,and was used to study the metabolic changes in the plasma of experimental hyperlipidemia rats.Methods:SD rats were ran-domly divided into normal control group and experimental hyperlipidemia model group.The experimental hyperlipidemia rat model was reproduced by feeding with high-fat diet.Orbital blood was taken and pre column derivatization was performed.The analytical method was established by GC-MS and investigated for methodology,including precision,reproducibility and stability.The plasma samples of normal control group and experimen-tal hyperlipidemia group were detected,and the potential metabolic markers were identified.Results:A metabonomic method based on GC-MS was established for the analysis of experimental hyperlipidemia plasma.The RSD of the relative peak areas in the precision,repeatability and stability tests of the method were less than 10%.Conclusion:The method is rapid,accurate,reproducible,and can be used for the determination of endog-enous metabolites in plasma of rats with hyperlipidemia.The method can provide some reference for the application of metabonomics in hyperlipid-emia.

徐文杰

广东省第二中医院(广东省中医药工程技术研究院),广东省中医药研究开发重点实验室,广东广州 510095

药学

气质联用技术高脂血症代谢组学代谢标志物大鼠

GC-MShyperlipidemia modelmetabonomicsmetabolic biomarkersrat

《中医康复》 2024 (001)

32-35 / 4

广东省自然科学基金自由申请项目(2017A030313628);广东省科技计划项目(2017A070701017)

10.19787/j.issn.2097-3128.2024.01.007

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