Fractional protein synthesis rates of skin proteins are dramatically decreased in fed pigs during the postnatal development
Bibliographic record
Abstract
We investigated the postnatal changes in skin protein fractional synthesis rates (FSR) and their correlations with serum levels of hormones (insulin, growth hormone and cortisol), [growth factors insulin‐like growth factor‐I (IGF‐I) and glucagon‐like polypeptide‐2 (GLP‐2)] and plasma concentrations of free amino acids (AA) in fed pigs. Thirty‐six purebred Yorkshire gilts were used for sampling at d 1, 4, 6, 12, 20 and 28 (1 wk post‐weaning) of age. These pigs received an intraperitoneal injection of a flooding dose of Phe containing L‐[ring‐2H5]Phe (40 molar%) in saline. Serum samples prior to the tracer injection and plasma and skin samples at 30 min post‐injection were collected for the determinations of tracer Phe enrichments by GC‐MS, free AA by HPLC, and hormones and growth factors by RIA. Tracer Phe enrichments in the plasma and skin free AA pools were 26–27 molar%. Skin protein FSR (%/d) were 22.0, 16.1, 19.9, 11.0, 9.6, and 3.0 at the ages of d 1, 4, 6, 12, 20 and 28, respectively, with a 7‐fold decrease (P<0.05) from d 1 to 28. Of all the hormonal factors examined, postnatal changes of FSR were (P<0.05) positively correlated with serum insulin concentrations and negatively related with serum GLP‐2 levels. Postnatal changes of skin FSR were positively correlated (P<0.05) with the plasma concentrations of Asn, Gln, His, Leu, Phe, Ser, Tyr and Val (r=0.33–0.58) and negatively correlated (P<0.05, r=−0.42) with Gly. These results suggest that skin protein FSR decreases rapidly in fed pigs during the postnatal development and this reduction is well associated with some extracellular free AA concentrations as well as serum insulin and GLP‐2 levels. Supported by NSERC and OMAF of Canada.
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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 | 0.001 |
| 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".