Brain docosahexaenoic acid accretion is greater when supplied as phosphatidylcholine than as triacylglycerol in piglets (821.11)
Bibliographic record
Abstract
Introduction. Docosahexaenoic acid (DHA) is the most abundant n‐3 PUFA in the brain. Preformed DHA is more efficacious for brain DHA accretion than precursors, but the relative efficacy of DHA bound to phospholipid (PC) and/or triacylglycerol (TAG) has not been measured yet. Our aim was to determine the relative efficacy of DHA when provided in formula to the growing piglet as a dose of 13C‐DHA bound to the sn‐2 positions of either PC or TAG. Methods. Piglets (n=8 per group) were assigned to two identical formula diets from day 3 of life and provided with a single oral dose of TAG‐13C‐DHA or PC‐13C‐DHA at 16 days of life. At day 23, selected piglet organs were analyzed for 13C‐DHA and other fatty acid metabolites. Results. The PC‐13C‐DHA was 1.9‐fold greater in brain gray matter than TAG‐13C‐DHA, and was similarly more efficacious in synaptosomes, retina, liver, and RBC. Liver labeling was by far the greatest implying initial processing in that organ followed by export to other organs, and in turn that transfer from gut to bloodstream to liver in part drove the relative efficacy for tissue accretion. Apparent retroconversion to 22:5n‐3 was more than 2‐fold greater for PC and was much more prominent in neural tissue than in liver or RBC. Conclusions. These data directly support greater efficacy for PC as a carrier for LCPUFA compared to TAG, consistent with previous studies of arachidonic acid and DHA measured in other species. Grant Funding Source : Supported by NIH R01 AT007003
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".