Partitioning of [methyl‐3H]methionine to methylated products under normal and high demand conditions in young Yucatan miniature pigs
Bibliographic record
Abstract
Methionine is the main source of 1‐carbon molecules which are partitioned to synthesize various methylated products including creatine, phosphatidylcholine, sarcosine and methylated DNA. Guanidinoacetate (GAA) is methylated to form creatine and because hepatic creatine synthesis in rats appears to be proportional to GAA availability, we hypothesized that when GAA is in excess, increased creatine synthesis will create a higher demand for available methyl groups. The objective of this study was to characterize the partitioning of the methyl groups of methionine with or without excess GAA. Anaesthetized piglets (15–18 d old) were intraportally infused with either GAA (n=5) or saline (n=5) for 2 h. A bolus of [methyl‐ 3 H]methionine was intraportally infused at 1 h and liver samples were excised by cautery 30, 45 and 60 min later. Various methylated metabolites in the liver were analyzed for specific activity. As hypothesized, excess GAA led to increased creatine synthesis, resulting in a ~200% increase in methyl‐ 3 H incorporation (P<0.05). We further hypothesized that this increased creatine synthesis would attenuate methyl‐ 3 H incorporation into other products. However, incorporation into DNA was ~240% greater with GAA (P<0.05). In neonatal piglets, creatine synthesis is increased by excess GAA availability but instead of sequestering available methyl groups, this led to increased methylation of DNA. (CIHR)
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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 | 0.001 |
| 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".