Why is carbon from some polyunsaturates extensively recycled into lipid synthesis?
Bibliographic record
Abstract
We summarize here the evidence indicating that carbon from alpha-linolenate and linoleate is readily recycled into newly synthesized lipids. This pathway consumes the majority of these fatty acids that is not beta-oxidized as a fuel. Docosahexaenoate undergoes less beta-oxidation and carbon recycling than do alpha-linolenate or linoleate, but is it still actively metabolized by this pathway? Among polyunsaturates, arachidonate appears to undergo the least beta-oxidation and carbon recycling, an observation that may help account for the resistance of brain membranes to loss of arachidonate during dietary deficiency of n-6 polyunsaturates. Preliminary evidence suggests that de novo lipid synthesis consumes carbon from alpha-linolenate and linoleate in preference to palmitate, but this merits systematic study. Active beta-oxidation and carbon recycling of 18-carbon polyunsaturates does not diminish the importance of being able to convert alpha-linolenate and linoleate to long-chain polyunsaturates but suggests that a broad perspective is required in studying the metabolism of polyunsaturates in general and alpha-linolenate and linoleate in particular.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".