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A Real Time Gas Chromatograph-Mass Spectrometer Minicomputer System for Selected Ion Analysis

  • J. A. Steinborn
  • R. W. Silverman
  • D. J. Jenden

Abstract

The use of selected ion analysis (selected ion monitoring, mass fragmentography) in quantitative applications of mass spectrometry is now well established (1, 2). For many purpose the output, consisting of a few selected ion profiles representing the mass peaks of interest, can be quite satisfactorily handled without automatic data processing as from a gas chromatograph flame ionization detector (FID) system. In contrast, the more critical demands of repetitive MS scanning require a computer system for complete utilization of the data. An automatic data system becomes increasingly necessary also for selected ion analysis when large numbers of samples are to be run and when more than two isotopic variants are to be simultaneously analyzed. The latter situation arises particularly when stable isotopic labels are used as quantitative tracers, as well as in their more conventional application as internal standards (3,4). Unlike radioisotopic tracers, stable isotopic labels, in conjunction with GC-MS, allow the use of multiple tracer variants of the same compounds which can be discriminated from each other by their mass spectra and separately measured (5). However, interpretation of the relative ion abundances requires solution of a set of simultaneous linear equations for each analysis, which may be impractical without computer assistance, and a set of controls in which mass spectra of the individual variants and of a mixture of known composition are precisely measured (6). These controls allow the construction of an n-dimensional “standard curve” from which the results of subsequent individual analyses are obtained by interpolation.

Keywords

Control Word Stable Isotopic Label Mass Defect Print Circuit Assembly Board Memory Resident 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

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Copyright information

© Plenum Press, New York 1977

Authors and Affiliations

  • J. A. Steinborn
    • 1
  • R. W. Silverman
    • 1
  • D. J. Jenden
    • 1
  1. 1.Department Pharmacology and Brain Research InstituteUniversity CaliforniaLos AngelesUSA

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