Visnagin protects against doxorubicin-induced cardiomyopathy through modulation of mitochondrial malate dehydrogenase
Bibliographic record
Abstract
Doxorubicin is a highly effective anticancer chemotherapy agent, but its use is limited by its cardiotoxicity. To develop a drug that prevents this toxicity, we established a doxorubicin-induced cardiomyopathy model in zebrafish that recapitulates the cardiomyocyte apoptosis and contractility decline observed in patients. Using this model, we screened 3000 compounds and found that visnagin (VIS) and diphenylurea (DPU) rescue the cardiac performance and circulatory defects caused by doxorubicin in zebrafish. VIS and DPU reduced doxorubicin-induced apoptosis in cultured cardiomyocytes and in vivo in zebrafish and mouse hearts. VIS treatment improved cardiac contractility in doxorubicin-treated mice. Further, VIS and DPU did not reduce the chemotherapeutic efficacy of doxorubicin in several cultured tumor lines or in zebrafish and mouse xenograft models. Using affinity chromatography, we found that VIS binds to mitochondrial malate dehydrogenase (MDH2), a key enzyme in the tricarboxylic acid cycle. As with VIS, treatment with the MDH2 inhibitors mebendazole, thyroxine, and iodine prevented doxorubicin cardiotoxicity, as did treatment with malate itself, suggesting that modulation of MDH2 activity is responsible for VIS' cardioprotective effects. Thus, VIS and DPU are potent cardioprotective compounds, and MDH2 is a previously undescribed, druggable target for doxorubicin-induced cardiomyopathy.
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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 | 0.000 |
| 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".