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Chinese Journal of Experimental Traditional Medical Formulae ; (24): 205-213, 2019.
Article in Chinese | WPRIM | ID: wpr-802187

ABSTRACT

Gas chromatography (GC) is mainly used to detect the levels of short-chain fatty acids (SCFAs), but with the deepening of research,the drawbacks of GC have become more and more obvious in the fields of food,chemical engineering and clinical application. The analysis on existing research results showed that ultra performance convergence chromatography (UPC2) was appropriate for the analysis of lipid metabolism. The UPC2 is a new kind of chromatographic separation technology developed in recent five years and the level of SCFAs is associated with the research on multiple diseases. Therefore,application of UPC2 in the detection of SCFAs would be helpful for the scholars at home and abroad to carry out deeper researches,and also helpful to guide the treatment for various metabolic disorders. In this paper,the researches on SCFAs in recent ten years were reviewed; the shortcomings of GC and liquid chromatography (LC) in the detection of SCFAs were reviewed; the development process,basic characteristics and research status of UPC2 at home and abroad were introduced; feasibility and innovation of UPC2 in the detection of SCFAs were summarized. Pretreatment methods for UPC2 application to the detection of SCFAs in feces or serum were collected; the problems that should be noticed during the process of sample pretreatment were pointed out; meanwhile, an research outlook on methodology of UPC2 application in the detection of SCFAs was conducted. The effects of extracting solvent,mobile phase,and auxiliaryt solvent on chromatographic behavior as well as the physicochemical property, type and choice of UPC2 chromatographic column were mainly discussed in this paper. In addition, the choices of basic modifier,acid modifier,and salinity modifier were briefly outlined, in order to provide efficient,simple,environmental,and economic detection technologies for the research on SCFAs, and provide better reference solutions for the rapid detection of massive clinical samples.

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