Homocysteine Metabolism in ZDF, Type 2 Diabetic rats: Effects of Rosiglitazone
Bibliographic record
Abstract
Hyperhomocysteinemia is an independent risk factor for vascular disease. The prevalence of atherosclerosis is 2‐to 6‐fold higher in diabetic patients compared to controls. This study focused on the effects of the insulin‐sensitizing drug, Rosiglitazone (RSG), on homocysteine metabolism. Male ZDF fa/fa and ZDF fa/+ (control) rats, aged 6 weeks were each divided into 2 groups: treated (RSG) and untreated (UN), and were killed at 12 weeks of age. RSG treatment was able to maintain a normal plasma glucose level in the ZDF fa/fa (RSG) rats. ZDF fa/fa (UN) rats developed type 2 diabetes as indicated by a 3‐fold increase in plasma glucose, while plasma insulin level was similar to control rats. The significant reduction observed in plasma homocysteine in the ZDF fa/fa (UN) rats was returned towards normal by RSG treatment. The elevated activity of the transsulfuration enzyme, Cystathionine γ‐lyase, in the ZDF fa/fa (UN) rats was corrected by RSG treatment while Cystathionine β‐synthase was unaffected. The elevated activity of Betaine:homocysteine methyltransferase (BHMT) observed in the ZDF fa/fa (UN) rats was further increased by RSG treatment. Whether the increased activity of BHMT in the ZDF fa/fa (RSG) rats is a function of increased lipid output from the liver in the face of the lipid redistribution seen with RSG needs further investigation. (Supported by CDA and 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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".