Renal, retinal and cardiac changes in type 2 diabetes are attenuated by macitentan, a dual endothelin receptor antagonist
Bibliographic record
Abstract
AIMS: Diabetes is known to cause alteration of the endothelin (ET) system. We have previously demonstrated that ETs regulate augmented production of extracellular matrix proteins causing structural alterations in type 1 diabetes. Here we investigated the effects of macitentan, an orally-active, tissue-targeting dual ET receptor antagonist on chronic complications in type 2 diabetes. MAIN METHODS: db/db mice and their age- and sex-matched controls were examined after 2 and 4 months of diabetes. Groups of diabetic animals were treated with oral macitentan (25mg/kg/day). The animals were monitored with respect to body weight and blood glucose. Urine analyses were performed for albumin. Cardiac hemodynamic studies were carried out. Renal, cardiac and retinal tissues were analyzed for ET-1, transforming growth factor-β1 (TGF-β1), vascular endothelial growth factor (VEGF), fibronectin (FN), extradomain B containing FN (EDB(+)FN) and collagen α-I (IV) mRNA. Cardiac atrial natriuretic peptide (ANP) and brain natriuretic peptide (BNP) were measured. Protein expressions were measured by ELISA and Western blot. Microscopic analyses were performed in the kidneys. KEY FINDINGS: Diabetic animals showed hyperglycemia, increased urinary albumin and augmented serum creatinine levels. Diabetes caused increased renal, cardiac and retinal ET-1, TGF-β1, VEGF, FN, EDB(+)FN, collagen α-I(IV) mRNA expression along with increased FN and collagen protein and NF-κB activation. Diabetic mice also demonstrated mesangial expansion, cardiac dysfunction and increased expression of ANP and BNP. Treatment with macitentan attenuated such abnormalities. SIGNIFICANCE: These experiments confirmed that ET system plays a significant role in the pathogenesis of chronic complications in type 2 diabetes. Such diabetes induced changes can be reduced macitentan therapy.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".