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'Retention Projection' Enables Reliable Use of Shared Gas Chromatographic Retention Data Across Laboratories, Instruments, and Methods

机译:“保留投影”可确保跨实验室,仪器和方法可靠地使用共享的气相色谱保留数据

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Gas chromatography/mass spectrometry (GC/ MS) is a primary tool used to identify compounds in complex samples. Both mass spectra and GC retention times are matched to those of standards; however, it is often impractical to have standards on hand for every compound of interest, so we must rely on shared databases of MS data and GC retention information. Unfortunately, retention databases (e.g., linear retention index libraries) are experimentally restrictive, notoriously unreliable, and strongly instrument dependent, relegating GC retention information to a minor, often negligible role in compound identification despite its potential power. A new methodology called "retention projection" has great potential to overcome the limitations of shared chromatographic databases. In this work, we tested the reliability of the methodology in five independent laboratories. We found that, even when each lab ran nominally the same method, the methodology was 3-fold more accurate than retention indexing because it properly accounted for unintentional differences between the GC/MS systems. When the laboratories used different methods of their own choosing, retention projections were 4-to 165-fold more accurate. More importantly, the distribution of error in the retention projections was predictable across different methods and laboratories, thus enabling automatic calculation of retention time tolerance windows. Tolerance windows at 99% confidence were generally narrower than those widely used even when physical standards are on hand to measure their retention. With its high accuracy and reliability, the new retention projection methodology makes GC retention a reliable, precise tool for compound identification, even when standards are not available to the user.
机译:气相色谱/质谱法(GC / MS)是用于鉴定复杂样品中化合物的主要工具。质谱和GC保留时间均与标准品相匹配;但是,为每种目标化合物制定标准常常是不切实际的,因此我们必须依靠MS数据和GC保留信息的共享数据库。不幸的是,保留数据库(例如线性保留指数库)在实验上具有局限性,众所周知是不可靠的,并且在很大程度上取决于仪器,因此将GC保留信息仅赋予化合物鉴定中次要的,通常可忽略的角色,尽管它具有潜在的功能。一种称为“保留投影”的新方法具有巨大的潜力,可以克服共享色谱数据库的局限性。在这项工作中,我们在五个独立的实验室中测试了该方法的可靠性。我们发现,即使每个实验室名义上使用相同的方法,该方法也比保留索引准确度高了3倍,因为它可以正确解释GC / MS系统之间的意外差异。当实验室使用自己选择的不同方法时,保留预测的准确度要高4到165倍。更重要的是,保留预测中的误差分布在不同方法和实验室之间是可预测的,因此可以自动计算保留时间容限窗口。即使使用现有的物理标准物来测量其保留率,在99%置信度下的公差窗口通常也比广泛使用的窄。凭借其高准确性和可靠性,即使用户无法获得标准品,新的保留时间预测方法也使GC保留成为可靠,精确的化合物鉴定工具。

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