Effect of type-1 diabetes mellitus on the regulation of insulin and endothelin-1 receptors in rat hearts
Bibliographic record
Abstract
This project assesses the treatment role with insulin and (or) angiotensin II receptor subtype-1 (AT1-R) blocker (ARB) on insulin receptor and endothelin-1 receptor subtype (ETA-R and ETB-R) regulation in rat hearts suffering from insulin-dependent diabetes mellitus (IDDM). Animals were divided into 6 groups: groups 1, 3, and 5 were controls consisting of normal, diabetic (streptozotocin-treated, once at 0 time), and diabetic supplemented daily with insulin, respectively, whereas groups 2, 4, and 6 were the controls treated daily with losartan. One month after enrollment, rats were sacrificed and samples of cardiac tissue were snapped frozen for immunostaining and Western blotting. Insulin receptor density was observed to be upregulated in the cardiomyocytes of diabetic animals, but downregulated with insulin supplementation alone. Cotreatment with insulin and an ARB resulted in drastic increase in insulin-receptor density in the diabetic rats. In addition, expression of ETA-R in cardiomyocytes was upregulated and was consistently maintained within the various treatment modalities. However, ETB-R expression was significantly reduced in the diabetic group treated with both insulin and an ARB. The changes in the expression of the insulin, the ETA-Rs, and the ETB-Rs at the various sites of the myocardium and the effect of both insulin treatment and blockade of the AT1-R explain the new benefits related to the halting of myocardial remodeling in IDDM rats.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".