Targeted Inhibition of Calpain Reduces Myocardial Hypertrophy and Fibrosis in Mouse Models of Type 1 Diabetes
Bibliographic record
Abstract
OBJECTIVE: Recently we have shown that calpain-1 activation contributes to cardiomyocyte apoptosis induced by hyperglycemia. This study was undertaken to investigate whether targeted disruption of calpain would reduce myocardial hypertrophy and fibrosis in mouse models of type 1 diabetes. RESEARCH DESIGN AND METHODS: Diabetes in mice was induced by injection of streptozotocin (STZ), and OVE26 mice were also used as a type 1 diabetic model. The function of calpain was genetically manipulated by cardiomyocyte-specific knockout Capn4 in mice and the use of calpastatin transgenic mice. Myocardial hypertrophy and fibrosis were investigated 2 and 5 months after STZ injection or in OVE26 diabetic mice at the age of 5 months. Cultured isolated adult mouse cardiac fibroblast cells were also investigated under high glucose conditions. RESULTS: Calpain activity, cardiomyocyte cross-sectional areas, and myocardial collagen deposition were significantly increased in both STZ-induced and OVE26 diabetic hearts, and these were accompanied by elevated expression of hypertrophic and fibrotic collagen genes. Deficiency of Capn4 or overexpression of calpastatin reduced myocardial hypertrophy and fibrosis in both diabetic models, leading to the improvement of myocardial function. These effects were associated with a normalization of the nuclear factor of activated T-cell nuclear factor-κB and matrix metalloproteinase (MMP) activities in diabetic hearts. In cultured cardiac fibroblasts, high glucose-induced proliferation and MMP activities were prevented by calpain inhibition. CONCLUSIONS: Myocardial hypertrophy and fibrosis in diabetic mice are attenuated by reduction of calpain function. Thus targeted inhibition of calpain represents a potential novel therapeutic strategy for reversing diabetic cardiomyopathy.
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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 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".