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外部数据系统助力老旧的线性离子阱-轨道阱混合平台实现增强型(且可持续的)傅里叶变换质谱成像。

External Data Systems Enable Enhanced (and Sustainable) Fourier Transform Mass Spectrometry Imaging for Legacy Hybrid Linear Ion Trap-Orbitrap Platforms.

作者信息

Leach Franklin E, Nagornov Konstantin O, Kozhinov Anton N, Tsybin Yury O

机构信息

Department of Chemistry, University of Georgia, Athens, Georgia 30602, United States.

Spectroswiss, 1015 Lausanne, Switzerland.

出版信息

J Am Soc Mass Spectrom. 2024 Nov 6;35(11):2690-2698. doi: 10.1021/jasms.4c00145. Epub 2024 Jul 20.

Abstract

Legacy Fourier transform (FT) mass spectrometers provide robust platforms for bioanalytical mass spectrometry (MS) yet lack the most modern performance capabilities. For many laboratories, the routine investment in next generation instrumentation is cost prohibitive. Field-based upgrades provide a direct path to extend the usable lifespan of MS platforms which may be considered antiquated based on performance specifications at the time of manufacture. Here we demonstrate and evaluate the performance of a hybrid linear ion trap (LTQ)-Orbitrap mass spectrometer that has been enhanced via an external high-performance data acquisition and processing system to provide true absorption mode FT processing during an experimental acquisition. For the application to mass spectrometry imaging, several performance metrics have been improved including mass resolving power, mass accuracy, and dynamic range to provide an FTMS system comparable to current platforms. We also demonstrate, perhaps, the unexpected ability of these legacy platforms to detect usable time-domain signals up to 5 s in duration to achieve a mass resolving power 8× higher than the original platform specification.

摘要

传统傅里叶变换(FT)质谱仪为生物分析质谱(MS)提供了强大的平台,但缺乏最现代的性能。对于许多实验室来说,常规投资于下一代仪器的成本过高。基于现场的升级提供了一条直接途径来延长质谱平台的可用寿命,基于制造时的性能规格,这些平台可能被认为过时了。在这里,我们展示并评估了一种混合线性离子阱(LTQ)-轨道阱质谱仪的性能,该质谱仪通过外部高性能数据采集和处理系统进行了增强,以在实验采集期间提供真正的吸收模式FT处理。对于质谱成像应用,包括质量分辨率、质量准确度和动态范围在内的几个性能指标都得到了改善,从而提供了一个与当前平台相当的FTMS系统。我们还展示了这些传统平台可能具有的意想不到的能力,即能够检测持续时间长达5秒的可用时域信号,以实现比原始平台规格高8倍的质量分辨率。

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