Long-chain n-3 fatty acids enhance neonatal insulin-regulated protein metabolism in piglets by differentially altering muscle lipid composition
Bibliographic record
Abstract
This study investigated the role of long-chain n-3 polyunsaturated fatty acids (LCn-3PUFAs) of muscle phospholipids in the regulation of neonatal metabolism. Twenty-eight piglets were weaned at 2 days of age and raised on one of two milk formulas that consisted of either a control formula supplying 0% or a formula containing 3.5% LCn-3PUFAs until 10 or 28 days of age. There was a developmental decline in the insulin sensitivity of amino acid disposal in control pigs during the first month of life, with a slope of -2.24 micromol.kg(-1).h(-1) (P = 0.01) per unit of insulin increment, as assessed using hyperinsulinemic-euglycemic-euaminoacidemic clamps. LCn-3PUFA feeding blunted this developmental decline, resulting in differing insulin sensitivities (P < 0.001). When protein metabolism was assessed under parenteral feeding-induced hyperinsulinemia, LCn-3PUFAs reduced by 16% whole body oxidative losses of amino acids (from 238 to 231 micromol.kg(-1).h(-1); P = 0.06), allowing 41% more amino acids to accrete into body proteins (from 90 to 127 micromol.kg(-1).h(-1); P = 0.06). The fractional synthetic rate of muscle mixed proteins remained unaltered by the LCn-3PUFA feeding. However, LCn-3PUFAs retarded a developmental increase in the essential-to-nonessential amino acid ratio of the muscle intracellular free pool (P = 0.05). Overall, alterations in metabolism were concomitant with a preferential incorporation of LCn-3PUFAs into muscle total membrane phospholipids (P < 0.001), in contrast to intramuscular triglycerides. These results underscore the potential role of LCn-3PUFAs as regulators of different aspects of protein metabolism in the neonate.
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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) | 0.001 | 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".