To a biochemist, the accuracy expectation for quantification is r

To a biochemist, the accuracy expectation for quantification is relatively loose since many uncertainties in the analysis of biological

samples are inevitably present in the whole process from sampling, sample preparation, and analysis. For example, the variations present in sampling of biological samples could be substantial and surpass any analytical errors. Therefore, employing some kinds of compromise methods or correction factors for quantification of a particular category of compounds might be acceptable and practical. Moreover, a statistical analysis of Inhibitors,research,lifescience,medical the data obtained is usually essential for quantification or comparison. Unfortunately, different statistical methods could lead an analyst to having different conclusions, particularly if the accuracy and/or Inhibitors,research,lifescience,medical reproducibility for acquiring analytical data are also relatively low. Therefore, while the accuracy of quantification is relatively loose, the higher accuracy and better reproducibility that a platform for quantification of lipid species can achieve, the more meaningful results can be obtained and eventually the more resources

and efforts can be saved. Many modern see more technologies (including mass spectrometry (MS), nuclear magnetic resonance spectroscopy, fluorescence spectroscopy, Inhibitors,research,lifescience,medical chromatography, and microfluidic devices) have been used in lipidomics for quantification of lipid species in biological systems [8]. Clearly, electrospray ionization mass spectrometry (ESI-MS) has evolved to be one of the most popular, powerful technologies

for quantitative analyses of individual lipid Inhibitors,research,lifescience,medical species [9-12]. There are two major platforms commonly employed for quantitative lipid analysis through ESI-MS, i.e., methods based on LC-MS and direct infusion. Inhibitors,research,lifescience,medical Herein, the principles, advantages and possible limitations of each methodology, as well as a few practical issues for accurate quantification of individual lipid species are discussed. 2. Principle of Quantification of Lipid Molecular Species with Mass Spectrometry Quantification of the concentration of an analyte with MS analysis, in principle, employs a correlation between the concentration Non-specific serine/threonine protein kinase and the ion intensity of the analyte which is linear within a pre-determined linear dynamic range: I=Iapp−b=a∗c (1) where c is the concentration of the analyte; Iapp is the apparent ion intensity of the analyte measured with MS; b is the spectral baseline resulting from baseline drift and/or chemical noise and can be determined as described recently [13]; I is the baseline-corrected ion intensity of the analyte (i.e., the actual ion intensity); and a is the response factor. When Iapp b (e.g., S/N > 10), I ≈ Iapp; otherwise, spectral baseline correction is required to obtain the actual ion intensity I from the measured apparent ion intensity Iapp of the analyte.

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