Microwave Energy Increases Fatty Acid Methyl Ester Yield in Human Whole Blood Due to Increased Sphingomyelin Transesterification
Bibliographic record
Abstract
Dried blood spots (DBS) by fingertip prick collection for fatty acid profiling are becoming increasingly popular due to ease of collection, minimal invasiveness and its amenability to high-throughput analyses. Herein, we assess a microwave-assisted direct transesterification method for the production of fatty acid methyl esters (FAME) from DBS. Technical replicates of human whole blood were collected and 25-μL aliquots were applied to chromatography strips prior to analysis by a standard 3-h transesterification method or microwave-assisted direct transesterification method under various power (variable vs constant), time (1-5 min) and reagent (1-10% H2SO4 in methanol) conditions. In addition, a standard method was compared to a 5-min, 30-W power microwave in 1% H2SO4 method for FAME yield from whole blood sphingomyelin, and sphingomyelin standards alone and spiked in whole blood. Microwave-assisted direct transesterification yielded no significant differences in both quantitative (nmol/100 µL) and qualitative (mol%) fatty acid assessments after as little as 1.5- and 1-min reaction times, respectively, using the variable power method and 5% H2SO4 in methanol. However, 30-W power for 5 min increased total FAME yield of the technical replicates by 14%. This increase appears largely due to higher sphingomyelin-derived FAME yield of up to 109 and 399% compared to the standard method when determined from whole blood or pure standards, respectively. In conclusion, microwave-assisted direct transesterification of DBS achieved in as little as 1-min, and 5-min reaction times increase total fatty acids primarily by significantly improving sphingomyelin-derived fatty acid yield.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".