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一种通过加速器质谱法直接分析非挥发性样品中碳-14的界面。

An interface for direct analysis of (14)c in nonvolatile samples by accelerator mass spectrometry.

作者信息

Liberman Rosa G, Tannenbaum Steven R, Hughey Barbara J, Shefer Ruth E, Klinkowstein Robert E, Prakash Chandra, Harriman Shawn P, Skipper Paul L

机构信息

Biological Engineering Division, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA.

出版信息

Anal Chem. 2004 Jan 15;76(2):328-34. doi: 10.1021/ac030181y.

DOI:10.1021/ac030181y
PMID:14719879
Abstract

We describe here apparatus and methods for direct analysis of (14)C in biological specimens by accelerator mass spectrometry (AMS). Liquid samples, including plasma and urine, are deposited by pipet into a bed of CuO powder that fills a space within a rigid, refractory support. Volatile components are removed under reduced pressure prior to analysis. The CuO matrix is locally heated with an infrared laser while it is contained within a sealed chamber that is swept with He carrier gas. Heating induces combustion of the applied sample, and the carrier gas transports the CO(2) that is formed to the AMS instrument's ion source, which is appropriately modified for use with CO(2). A rodent study of drug clearance with [(14)C]-acetaminophen was performed to provide plasma and urine specimens, which were analyzed with this overall approach and by liquid scintillation counting for comparison. Results presented here confirm the potential utility of laser-induced sample combustion as an alternative to graphite production for AMS analysis of (14)C. Anticipated benefits of the present approach include reduced risk of sample cross-contamination, decreased analysis time, and greater compatibility with robotics.

摘要

我们在此描述通过加速器质谱法(AMS)直接分析生物样本中¹⁴C的仪器和方法。液体样本,包括血浆和尿液,用移液管滴加到填充在刚性耐火支架内部空间的CuO粉末床中。在分析之前,在减压条件下去除挥发性成分。当CuO基质置于充满氦载气的密封腔室内时,用红外激光对其进行局部加热。加热促使所施加的样本燃烧,载气将生成的CO₂输送到AMS仪器的离子源,该离子源经过适当改装以用于CO₂分析。进行了一项用[¹⁴C] - 对乙酰氨基酚进行药物清除的啮齿动物研究,以提供血浆和尿液样本,这些样本采用这种整体方法进行分析,并与液体闪烁计数法进行比较。此处呈现的结果证实了激光诱导样本燃烧作为AMS分析¹⁴C替代石墨生产方法的潜在效用。本方法预期的优点包括降低样本交叉污染风险、缩短分析时间以及与机器人技术具有更高的兼容性。

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