Liquid chromatography/mass spectrometry determination of endogenous plasma acetyl and palmitoyl carnitines as potential biomarkers of <i>β</i> ‐oxidation in mice
Bibliographic record
Abstract
A robust bioanalytical method capable of measuring acetyl and palmitoyl carnitines was developed and validated. Application of hydrophilic interaction chromatography (HILIC) enabled retention of these highly polar and difficult to analyze compounds on a silica HPLC column. The chromatography was conducted with a high percentage of an organic component in the mobile phase, allowing high sensitivity for the pre-existing positively charged quaternary ammonium ions by electrospray ionization mass spectrometry. Successful application of the method to reliably quantify naturally occurring acyl carnitines in mouse plasma depended on the use of corresponding deuterated analogues. The specificity of the method, achieved through the use of stable isotope labeled compounds in combination with a mass spectral multiple reaction monitoring technique, permitted a non-invasive assessment of the overall change in the levels of these acyl carnitines in the plasma of intact animals administered peroxisome proliferator activated receptor (PPAR) agents. These acyl carnitines, as carriers of the corresponding long-chain fatty acids for transport into mitochondria, can be employed as potential biomarkers for significant alteration in the beta-oxidation process in an intact animal.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".