Extraction of pure components from overlapped signals in gas chromatography-mass spectrometry (GC-MS)

Gas chromatography-mass spectrometry (GC-MS) is a widely used analytical technique for the identification and quantification of trace chemicals in complex mixtures. When complex samples are analyzed by GC-MS it is common to observe co-elution of two or more components, resulting in an overlap of signal peaks observed in the total ion chromatogram. In such situations manual signal analysis is often the most reliable means for the extraction of pure component signals; however, a systematic manual analysis over a number of samples is both tedious and prone to error. In the past 30 years a number of computational approaches were proposed to assist in the process of the extraction of pure signals from co-eluting GC-MS components. This includes empirical methods, comparison with library spectra, eigenvalue analysis, regression and others. However, to date no approach has been recognized as best, nor accepted as standard. This situation hampers general GC-MS capabilities, and in particular has implications for the development of robust, high-throughput GC-MS analytical protocols required in metabolic profiling and biomarker discovery. Here we first discuss the nature of GC-MS data, and then review some of the approaches proposed for the extraction of pure signals from co-eluting components. We summarize and classify different approaches to this problem, and examine why so many approaches proposed in the past have failed to live up to their full promise. Finally, we give some thoughts on the future developments in this field, and suggest that the progress in general computing capabilities attained in the past two decades has opened new horizons for tackling this important problem

Effect of dietary supplementation on lipid photooxidation in beef meat, during storage under commercial retail conditions

The effects of feeding composition on the photosensitized oxidation of lipids from beef meat, were evaluated during storage under commercial retail conditions. Feeding was enriched with linseed oil (LO), Dl-α tocopheryl acetate (vE) and conjugated linoleic acid (CLA) at different doses and provided for diverse periods, resulting in 7 diet groups (A-G). After slaughtering and 2 weeks of holding period, meat slices were packed in vessels with transparent shrink film and exposed to white fluorescent light for 8 h at 8 °C. Total cholesterol oxidation products (COPs) level varied from 4.0 to 13.0 μg/g of lipids, which corresponded to 0.1-0.6% oxidized cholesterol. The lowest peroxide value (PV) in the diet added with vE and LO for 90 days was found. Light exposure only had a significant impact on thiobarbituric acid reactive substances (TBARs). In general, Dl-α tocopheryl acetate supplemented for 90 days improved the oxidative stability of beef meat stored under commercial retail conditions