|عنوان مقاله||Standard operation protocol for analysis of lipid hydroperoxides in human serum using a fully automated method based on solid-phase extraction and liquid chromatography–mass spectrometry in selected reaction monitoring|
|ترجمه عنوان مقاله||پروتکل عملکرد استاندارد برای آنالیز لیپید هیدروپروکسید در خونابه انسان با استفاده از یک روش کاملا مکانیزه مبنی بر استخراج حالت جامد و کراماتوگرافی مایع طیف سنج جرمی در بازبینی واکنش منتخب|
|سال انتشار||مقاله سال ۲۰۱۱|
|تعداد صفحات مقاله||۷ صفحه|
|رشته های مرتبط||شیمی، داروسازی و زیست شناسی|
|گرایش های مرتبط||بیوشیمی|
|مجله||مجله کروماتوگرافی – Journal of Chromatography A|
|دانشگاه||Department of Analytical Chemistry, University of Córdoba, Spain|
|کلمات کلیدی||تمرکز متابولومیتی، پروتکل های عملیاتی استاندارد (SOPs) ، هیدروپراکسید لیپید، تجزیه و تحلیل ثبات، SRM ، اتوماسیون|
|وضعیت ترجمه مقاله||ترجمه آماده این مقاله موجود نمیباشد. میتوانید از طریق دکمه پایین سفارش دهید.|
|دانلود رایگان مقاله||دانلود رایگان مقاله انگلیسی|
|سفارش ترجمه این مقاله||سفارش ترجمه این مقاله|
|بخشی از متن مقاله:|
Sources of potential variability in metabolomics analysis can be ascribed to analytical or biological issues, the latter desirably correlated with physiological states or dietary, environmental, genetic or pathophysiological conditions. For this reason, metabolomics studies require in-depth validation in three progressive domains: (i) analytical issues, (ii) inter-/intra-personal biological variation, and (iii) correspondence with a given phenotype [1,2]. The control of the potential sources of variability is crucial to avoid errors in data interpretation.
Although metabolomics studies developed with different types of samples have revealed that biological variation is usually higher than that attributed to analytical variation, it is impor- tant to identify the main sources of analytical variability [3–۵]. Thus, in addition to inter-individual and intra-individual variations, the sources of error in metabolomics are mainly associated to sampling and post-collection procedures such as freeze–thaw cycles or inadequate storage conditions . It is well-known that unsuitable sampling and sample preparation protocols can lead to biased results owing anabolic or catabolic processes . There is increased interest in rapid collection and handling of samples for metabolomics purposes, as turnover kinetics of some metabolites is known to be extremely fast. Accordingly, the time window between sampling and analysis should be as short as possible. For instance, many intracellular metabolites such as ATP and glucose- 6-phosphate are extremely labile, with turnover rates of less than 2 s . Thus, with identification purposes cellular metabolism must be stopped immediately upon sampling of the cells to prevent/minimize metabolite turnover. In fact, sample representation in metabolomics is only achieved when metabolism is efficiently interrupted during sampling by quenching. This step aims at instantaneous stop ofmetabolism by inhibiting the activity of endogenous enzymes. In this way, changes in the metabolic profile duringsampling are suppressed. The common strategy for quenching is based on rapid modification of sample conditions, usually by a temperature shock .
Immediate analysis of the samples is not always possible and, therefore, sample storage is required (e.g. in banks of biological samples for research purposes). Sample storage is other critical source of error in metabolomics analysis. Most metabolites are preserved if samples are immediately frozen at temperature close to −۸۰ ◦C (e.g. by liquid nitrogen). However, itis worth noting that differences in storage time or frequent thaw–freeze cycles may have a strong influence on the development of metabolomics models. Metabolic activity during sampling and storage requires stopping or minimizing changes in the metabolic profile either in concentration or structure. For this purpose, decreased temperatures during sample preparation (4 ◦C) and storage (−۸۰ ◦C) are frequently implemented in analysis protocols [10,11]. For instance, appropriate storage and preparatory measures must immediately follow urine collection to ensure the quality of results in metabolomics analysis throughout the collection and analytical process. Thus, apart from samples storage at −۸۰ ◦C, freeze–thaw cycles should be avoided whenever possible. The addition of a bacteriostatic preservative such as sodium azide can be crucial to avoid bacterial contamination .