Synthesis of guanidinoacetate and creatine from amino acids by rat pancreas
Bibliographic record
Abstract
Creatine is an important molecule involved in cellular energy metabolism. Creatine is spontaneously converted to creatinine at a rate of 1·7% per d; creatinine is lost in the urine. Creatine can be obtained from the diet or synthesised from endogenous amino acids via the enzymes arginine:glycine amidinotransferase (AGAT) and guanidinoacetate N-methyltransferase (GAMT). The liver has high GAMT activity and the kidney has high AGAT activity. Although the pancreas has both AGAT and GAMT activities, its possible role in creatine synthesis has not been characterised. In the present study, we examined the enzymes involved in creatine synthesis in the pancreas as well as the synthesis of guanidinoacetate (GAA) and creatine by isolated pancreatic acini. We found significant AGAT activity and somewhat lower GAMT activity in the pancreas and that pancreatic acini had measurable activities of both AGAT and GAMT and the capacity to synthesise GAA and creatine from amino acids. Creatine supplementation led to a decrease in AGAT activity in the pancreas, though it did not affect its mRNA or protein abundance. This was in contrast with the reduction of AGAT activity and mRNA and protein abundance in the kidney, suggesting that the regulatory mechanisms that control the expression of this enzyme in the pancreas are different from those in the kidney. Dietary creatine increased the concentrations of GAA, creatine and phosphocreatine in the pancreas. Unexpectedly, creatine supplementation decreased the concentrations of S-adenosylmethionine, while those of S-adenosylhomocysteine were not altered significantly.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".