What Does the Measurement of Whole-Body Fatty Acid Rate of Appearance in Plasma by Using a Fatty Acid Tracer Really Mean?
Bibliographic record
Abstract
We evaluated the validity of using a single fatty acid tracer to assess total plasma long-chain free fatty acid (FFA) kinetics and the relationship between the rate of appearance (R(a)) of fatty acids in plasma and the fatty acid composition of adipose tissue triglyceride (TG). A mixture of [(13)C]-labeled myristate, palmitate, stearate, oleate, and linoleate was infused in healthy men during basal conditions and during conditions that stimulate (epinephrine infusion) and inhibit (insulin infusion) lipolysis of adipose tissue TGs. Calculated total FFA, R(a) based on palmitate, oleate, or linoleate tracers, was within 15% of the measured sum of the individual fatty acid R(a) under all conditions, whereas stearate and myristate tracers consistently underestimated and overestimated total FFA R(a), respectively. The fatty acid R(a) profile closely matched the fatty acid profile of subcutaneous adipose tissue TGs during epinephrine infusion, but not during basal conditions and insulin infusion. Our data support the common practice of using labeled palmitate or oleate as fatty acid tracers for assessing total plasma FFA kinetics and suggest that a source of lipids other than adipose tissue TG release fatty acids into the systemic circulation.
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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 | 0.096 | 0.250 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.011 |
| Scholarly communication | 0.005 | 0.010 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.010 | 0.004 |
| Insufficient payload (model declined to judge) | 0.001 | 0.002 |
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".