Automated Author ProfileVerner, Miroslav
Verner, Miroslav
Current S-Index
Sum of Dataset Indices for all datasets
Average Dataset Index per Dataset
Average Dataset Index per dataset
Total Datasets
Total datasets for this author
Average FAIR Score
Average FAIR Score per dataset
Total Citations
Total citations to the author's datasets
Total Mentions
Total mentions of the author's datasets
S-Index Interpretation
The S-Index (Sharing Index) is a comprehensive metric that represents the cumulative impact of all your datasets. It is calculated as the sum of Dataset Index scores across all your claimed datasets.
What it means:
- A higher S-index indicates greater overall impact of your datasets relative to typical datasets in their fields of research
- The S-Index grows as you add more datasets or as existing datasets gain more citations and mentions
- It provides a single number to track your research data impact over time
Current S-Index: 0.7 (sum of 2 datasets Dataset Index scores)
More information here.
S-Index Over Time
Cumulative Citations Over Time
Cumulative Mentions Over Time
Datasets
Fatty acids (FAs) represent ubiquitous and important class of nonpolar alkyl 11 carboxylate metabolites with diverse biological functions in every organism. Nutrition, 12 metabolism, endogenous, and exogenous stress influence the overall FA metabolic status 13 and transport via the bloodstream to tissues and back. There is growing evidence that FAs 14 are powerful biomarkers of pathological conditions and why analysis of FA metabolism 15 is a valuable tool in biomedical research and clinical diagnostics, especially for polyun-16 saturated FAs (PUFAs). However, FAs represent a broad spectrum of homologous struc-17 tures that differ in isomerism and position of double bonds, necessitating their detailed 18 analysis by highly efficient separation techniques, usually in conjunction with mass spec-19 trometric (MS) detection. FAs esterified in lipids, their circulation, and metabolism are of 20 particular interest as they represent promising biomarkers of pathological diseases and 21 nutritional status. Here we report a validated GC-MS method for the quantitative analysis 22 of 32 FAs exclusively bound in esterified lipids. The developed sample preparation pro-23 tocol includes extraction of FAs and their release from lipids in three steps using only 5 24 μL of human serum for Folch extraction, sodium methoxide-catalyzed transesterification 25 in tert-butyl methyl ether, and re-extraction in isooctane prior to quantitative GC-MS anal-26 ysis with positive ion chemical ionization (PICI) and selected ion monitoring (SIM). The 27 base-catalyzed transmethylation step was studied in detail for 14 lipid classes and was 28 found to be efficient under mild conditions for all major esterified lipid classes but not for 29 free FAs, lipid amides, and sphingolipids. To minimize matrix effects and instrument bias 30 internal D3-FAME standards were prepared by isotope-coded derivatization with D3-la-31 beled methylchloroformate/methanol medium mixed with each transmethylated serum 32 extract for the assay. The method was validated according to FDA guidelines and evalu-33 ated by analyzing NIST SRM 2378 Serum 1 and sera from three healthy donors. The meas-34 ured quantitative FA values are consistent with the reference data of SRM 2378 and 35 demonstrate the application potential of the described method for general FA analysis in 36 esterified lipids as a novel complementary tool for lipidomics as well as for the analysis 37 of membrane FAs in dry blood spots and red blood cells.
Authors
- Moos, Martin ;
- Vodražka, Petr ;
- Berkova, Petra ;
- Vojtíšek, Jan ;
- Verner, Miroslav ;
- Šimek, Petr
Fatty acids (FAs) represent ubiquitous and important class of nonpolar alkyl 11 carboxylate metabolites with diverse biological functions in every organism. Nutrition, 12 metabolism, endogenous, and exogenous stress influence the overall FA metabolic status 13 and transport via the bloodstream to tissues and back. There is growing evidence that FAs 14 are powerful biomarkers of pathological conditions and why analysis of FA metabolism 15 is a valuable tool in biomedical research and clinical diagnostics, especially for polyun-16 saturated FAs (PUFAs). However, FAs represent a broad spectrum of homologous struc-17 tures that differ in isomerism and position of double bonds, necessitating their detailed 18 analysis by highly efficient separation techniques, usually in conjunction with mass spec-19 trometric (MS) detection. FAs esterified in lipids, their circulation, and metabolism are of 20 particular interest as they represent promising biomarkers of pathological diseases and 21 nutritional status. Here we report a validated GC-MS method for the quantitative analysis 22 of 32 FAs exclusively bound in esterified lipids. The developed sample preparation pro-23 tocol includes extraction of FAs and their release from lipids in three steps using only 5 24 μL of human serum for Folch extraction, sodium methoxide-catalyzed transesterification 25 in tert-butyl methyl ether, and re-extraction in isooctane prior to quantitative GC-MS anal-26 ysis with positive ion chemical ionization (PICI) and selected ion monitoring (SIM). The 27 base-catalyzed transmethylation step was studied in detail for 14 lipid classes and was 28 found to be efficient under mild conditions for all major esterified lipid classes but not for 29 free FAs, lipid amides, and sphingolipids. To minimize matrix effects and instrument bias 30 internal D3-FAME standards were prepared by isotope-coded derivatization with D3-la-31 beled methylchloroformate/methanol medium mixed with each transmethylated serum 32 extract for the assay. The method was validated according to FDA guidelines and evalu-33 ated by analyzing NIST SRM 2378 Serum 1 and sera from three healthy donors. The meas-34 ured quantitative FA values are consistent with the reference data of SRM 2378 and 35 demonstrate the application potential of the described method for general FA analysis in 36 esterified lipids as a novel complementary tool for lipidomics as well as for the analysis 37 of membrane FAs in dry blood spots and red blood cells.
Authors
- Moos, Martin ;
- Vodražka, Petr ;
- Berkova, Petra ;
- Vojtíšek, Jan ;
- Verner, Miroslav ;
- Šimek, Petr