Biosynthesis of long-chain omega-3 fatty acids by the nestlings of a generalist seabird
Bibliographic record
Abstract
Docosahexaenoic acid (DHA), a long-chain omega-3 fatty acid (n3-LCPUFA), is an integral component of vertebrate brains. Vertebrates maintain their DHA levels through biosynthesis using alpha-linolenic acid (ALA; omega-3 precursor) or by consuming preformed DHA and other n3-LCPUFAs which abound in the natural diets of marine predators. Yet, numerous marine predators, including generalist seabirds, now exploit anthropogenic resources potentially deficient in n3-LCPUFAs. Whether they can offset such deficiency by bioconverting ALA into DHA remains unknown. Here, we tested whether chicks of the ring-billed gull (Larus delawarensis), a generalist seabird thriving in cities, can biosynthesize n3-LCPUFAs, including DHA, from ALA. We brought into captivity 12 hatchlings from an urban colony and 12 from a natural colony. Nine hatchlings per colony were gavaged 490 μl of ALA-rich flaxseed oil daily for 3 days. The control groups (N=3 urban hatchlings, 3 natural hatchlings) received an omega-3-free caloric equivalent in place of the ALA supplement. All chicks received an omega-3-free diet throughout captivity (72 h). We also attempted to follow ALA's potential bioconversion into n3-LCPUFAs using an oral 13C1-enriched ALA tracer. Unfortunately, compound-specific isotope analyses of brain and liver tissue failed to detect any 13C enrichment. Nevertheless, the flaxseed oil supplementation study provided evidence of some ALA bioconversion. Compared with controls, supplemented chicks from both colonies accumulated more of all ALA derivates in their tissues except for DHA. We demonstrate for the first time that a seabird shows incomplete omega-3 bioconversion abilities, leaving them potentially vulnerable to deficiencies associated with urban foraging and shifting marine ecosystems.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".