Creatine synthesis and methionine partitioning during TPN in Yucatan miniature piglets
Bibliographic record
Abstract
Methionine is an indispensable amino acid in the diet of neonates and has a \nmetabolic role in the synthesis of creatine, phosphatidylcholine (PC) as well as \nprotein synthesis and other transmethylation reactions. Creatine synthesis consumes \nsignificant amounts of arginine (a conditionally essential amino acid) and methionine, \nwhile PC requires methionine for its synthesis. Total parenteral nutrition (TPN) is \ntypically marginal in these amino acids, and devoid in creatine. Therefore, our \nobjective was to quantify the partitioning of methyl groups among transmethylation \nreactions and the sparing effect of dietary creatine and GAA on protein synthesis. \nAdequate supply of dietary methionine resulted in significantly greater hepatic \nfractional synthesis rate (FSR) of PC. Furthermore, GAA supplementation increased \nFSR of creatine by approximately 175%, but only when adequate dietary methionine \nwas supplied. Moreover, piglet weight gain was similar to that of piglets receiving \nadequate arginine, suggesting arginine was spared for growth. Overall, supplemental \nGAA could be considered as a novel TPN ingredient to increase the synthesis of \ncreatine and spare arginine for growth, but only when adequate methionine is \nprovided.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".