Tranilast attenuates diastolic dysfunction and structural injury in experimental diabetic cardiomyopathy
Bibliographic record
Abstract
Diastolic dysfunction is an increasingly recognized complication of diabetes that develops in relatively young patients as a result of diabetic cardiomyopathy (DCM). With recent advances in echocardiographic technology now permitting the reliable assessment of diastolic function in the rat, we examined cardiac function and structure in diabetic rodents and assessed the effects of intervening with tranilast, an antifibrotic compound that has been shown to attenuate the actions of transforming growth factor-beta (TGF-beta) in cardiac fibroblasts. We also sought to examine the mechanism whereby tranilast inhibits the actions of TGF-beta. Six-week-old heterozygous (mRen-2)27 rats were randomized to receive either streptozotocin or citrate buffer and then further randomized to receive either tranilast (400 mg x kg(-1) x day(-1) by twice daily gavage) or vehicle for another 8 wk. Cell signaling was examined in neonatal cardiac fibroblasts. After 8 wk, diabetic rats showed evidence of impaired diastolic function with reduced early-to-late atrial wave ratio and prolonged deceleration time in association with fibrosis, apoptosis, and hypertrophy (all P < 0.05). Treatment with tranilast prevented the development of diastolic dysfunction and the histopathological features of DCM. While tranilast did not affect Smad phosphorylation, it significantly attenuated TGF-beta-induced p44/42 mitogen-activated protein kinase phosphorylation.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".