Effects of diabetes and insulin on betaine-homocysteine<i>S</i>-methyltransferase expression in rat liver
Bibliographic record
Abstract
Elevation of plasma homocysteine levels has been recognized as an independent risk factor for the development of cardiovascular disease, a major complication of diabetes. Plasma homocysteine reflects a balance between its synthesis via S-adenosyl-L-methionine-dependent methylation reactions and its removal through the transmethylation and the transsulfuration pathways. Betaine-homocysteine methyltransferase (BHMT, EC 2.1.1.5) is one of the enzymes involved in the remethylation pathway. BHMT, a major zinc metalloenzyme in the liver, catalyzes the transfer of methyl groups from betaine to homocysteine to form dimethylglycine and methionine. We have previously shown that plasma homocysteine levels and the transsulfuration pathway are affected by diabetes. In the present study, we found increased BHMT activity and mRNA levels in livers from streptozotocin-diabetic rats. In the rat hepatoma cell line (H4IIE cells), glucocorticoids (triamcinolone) increased the level and rate of BHMT mRNA synthesis. In the same cell line, insulin decreased the abundance of BHMT mRNA and the rate of de novo mRNA transcription of the gene. Thus the decreased plasma homocysteine in various models of diabetes could be due to enhanced homocysteine removal brought about by a combination of increased transsulfuration of homocysteine to cysteine and increased remethylation of homocysteine to methionine by BHMT.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".