Docosahexaenoic acid is both a product of and a precursor to tetracosahexaenoic acid in the rat
Bibliographic record
Abstract
Tetracosahexaeoic acid (THA; 24:6n-3) is thought to be the immediate precursor of DHA in rodents; however, the relationship between THA and DHA metabolism has not been assessed in vivo. Here, we infused unesterified 2 H 5 -THA and 13 C 22 -DHA, at a steady state, into two groups of male Long-Evans rats and determined the synthesis-secretion kinetics, including daily synthesis-secretion rates of all 20-24 carbon n-3 PUFAs. We determined that the synthesis-secretion coefficient (a measure of the capacity to synthesize a given fatty acid) for the synthesis of DHA from plasma unesterified THA to be 134-fold higher than for THA from DHA. However, when considering the significantly higher endogenous plasma unesterified DHA pool, the daily synthesis-secretion rates were only 7-fold higher for DHA synthesis from THA (96.3 ± 31.3 nmol/d) compared with that for THA synthesis from DHA (11.4 ± 4.1 nmol/d). Furthermore, plasma unesterified THA was converted to DHA and secreted into the plasma at a 2.5-fold faster rate than remaining as THA itself (26.2 ± 6.3 nmol/d), supporting THA's primary role as a precursor to DHA. In conclusion, using a 3 h infusion model in rats, we demonstrate for the first time in vivo that DHA is both a product and a precursor to THA.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".