Quantitative Endogenous Formate Analysis in Plasma Using Headspace Gas Chromatography Without a Headspace Analyzer
Bibliographic record
Abstract
The objective was to develop a simple routine method for quantitative measurement of endogenous formic acid in plasma and whole blood using headspace gas chromatography-flame ionization detection. (GC-FID). Two-hundred microliters of sample was placed in a 1-mL glass vial. Fifty microliters of aqueous ethanol (10%) was added as an internal standard and a derivatizing agent. Ethylformate formation was enhanced by addition of 200 microL concentrated sulfuric acid as a catalyst. The vials were then sealed immediately and placed in a water bath for 15 min at 60 degrees C. One milliliter of this headspace gas was siphoned using a gas-tight syringe and injected into a GC-FID fitted with a capillary column. Ethanol eluted at approximately 3.0 min, and ethylformate eluted around 4.7 min. The limit of quantitation for ethylformate was 0.026 mmol/L, and the limit of detection was 0.020 mmol/L. Imprecisions for spiked plasma samples at 0.25 and 1 mmol/L were 10% and 9%, respectively and recoveries were at 100% and 108%, respectively. A simple, reliable, and highly specific headspace analysis method for quantifying endogenous formate without the use of a headspace analyzer was developed. This method enables the routine clinical analysis of formate in plasma and whole blood samples.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".