Countervailing vascular effects of rosiglitazone in high cardiovascular risk mice: role of oxidative stress and PRMT-1
Bibliographic record
Abstract
In the present study, we tested the hypothesis that the PPARgamma (peroxisome-proliferator-activated receptor gamma) activator rosiglitazone improves vascular structure and function in aged hyperhomocysteinaemic MTHFR (methylene tetrahydrofolate reductase) gene heterozygous knockout (mthfr+/-) mice fed a HCD (high-cholesterol diet), a model of high cardiovascular risk. One-year-old mthfr+/- mice were fed or not HCD (6 mg x kg-1 of body weight x day-1) and treated or not with rosiglitazone (20 mg x kg-1 of body weight x day-1) for 90 days and compared with wild-type mice. Endothelium-dependent relaxation of carotid arteries was significantly impaired (-40%) only in rosiglitazone-treated HCD-fed mthfr+/- mice. Carotid M/L (media-to-lumen ratio) and CSA (cross-sectional area) were increased (2-fold) in mthfr+/- mice fed or not HCD compared with wild-type mice (P<0.05). Rosiglitazone reduced M/L and CSA only in mthfr+/- mice fed a normal diet. Superoxide production was increased in mthfr+/- mice fed HCD treated or not with rosiglitazone, whereas plasma nitrite was decreased by rosiglitazone in mice fed or not HCD. PRMT-1 (protein arginine methyltransferase-1), involved in synthesis of the NO (nitric oxide) synthase inhibitor ADMA (asymmetric omega-NG,NG-dimethylarginine), and ADMA were increased only in rosiglitazone-treated HCD-fed mthfr+/- mice. Rosiglitazone had both beneficial and deleterious vascular effects in this animal model of high cardiovascular risk: it prevented carotid remodelling, but impaired endothelial function in part through enhanced oxidative stress and increased ADMA production in mice at high cardiovascular risk.
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 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 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| 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".