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Ultrasensitive Measurement of Estrogens

Ultrasensitive Measurement of Estrogens
雌激素的超灵敏测量
批准号:
7195258
负责人:
ROGER Wallace GIESE
金额:
$7.85万
依托单位:
依托单位国家:
美国
项目类别:
财政年份:
2006
资助国家:
美国
项目状态:
已结题
起止时间:
2006-09-20 至 2008-07-31

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项目成果

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中文摘要
翻译
描述(由申请人提供):雌激素的测量是为了更好地了解它们在健康和疾病中的作用,特别是乳腺癌中的作用。在这个项目中,我们将开发一种测量血清和血浆中雌激素(雌二醇及其代谢物)的超灵敏方法。该方法主要包括五个步骤:(1)在稳定同位素内标存在下从血清中提取雌激素;(2)通过蒸发和进一步的溶剂分配和/或固相萃取来净化萃取物;(3)用电子电话试剂和封盖试剂衍生雌激素;(四)进行衍生后样品清理;(5)采用近年来兴起的气相色谱-电子捕获飞行时间质谱(GC-EC-TOF-MS)技术检测雌激素衍生物。该项目的部分工作将涉及制备新的电子电话衍生剂,预计这些衍生剂将比目前测量雌激素的试剂提供更高的灵敏度。我们试图在单个程序中测量15种雌激素,其量在200 μ l血清或血浆中小至200 fg。具有这种性能的方法可用于测量流行病学研究队列样本、绝经后妇女血清和组织显微活检样本中的雌激素。虽然需要这样的分析,但现有方法的灵敏度无法达到实际样品的这一水平。
英文摘要
DESCRIPTION (provided by applicant): The measurement of estrogens is of interest for a better understanding of their role in both health and disease, especially breast cancer. In this project we will develop an ultrasensitive method for measuring estrogens (estradiol and its metabolites) in serum and plasma. The method will basically consist of five steps: (1) extract the estrogens from serum in the presence of stable isotope internal standards; (2) clean up the extract by evaporation and further solvent partitioning and/or solid phase extraction; (3) derivatize the estrogens with an electrophone reagent and capping reagent; (4) conduct post derivatization sample cleanup; (5) detect the estrogen derivatives by gas chromatography electron capture time-of-flight mass spectrometry (GC-EC-TOF-MS), a technique that has emerged recently. Part of the work in the project will involve the preparation of new electrophone derivatizing agents that are anticipated to provide higher sensitivity than current reagents for measurement of estrogens. We seek to measure 15 estrogens in a single procedure in amounts as small as 200 fg in 200 mu l of serum or plasma. A method with this performance could be used to measure estrogens in cohort samples from epidemiology studies, in serum of postmenopausal women, and in tissue microbiopsy samples. While there is a need for such analysis, the sensitivity of current methods fails to reach this level for real samples.
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