Ccn2 Deletion Reduces Cardiac Dysfunction, Oxidative Markers, and Fibrosis Induced by Doxorubicin Administration in Mice
Bibliographic record
Abstract
Cellular Communication Network Factor 2 (CCN2) is a matricellular protein implicated in cell communication and microenvironmental signaling. Overexpression of CCN2 has been documented in various cardiovascular pathologies, wherein it may exert either deleterious or protective effects depending on the pathological context, thereby suggesting that its role in the cardiovascular system is not yet fully elucidated. In this study, we aimed to investigate the effects of Ccn2 gene deletion on the progression of acute cardiac injury induced by doxorubicin (DOX), a widely utilized chemotherapeutic agent. To this end, we employed conditional knockout (KO) mice for the Ccn2 gene (CCN2-KO), which were administered DOX and compared to DOX-treated wild-type (WT) control mice. Our findings demonstrated that the ablation of CCN2 ameliorated DOX-induced cardiac dysfunction, as evidenced by improvements in ejection fraction (EF) and fractional shortening (FS) of the left ventricle. Furthermore, DOX-treated CCN2-KO mice exhibited a significant reduction in the gene expression and activation of oxidative stress markers (Hmox1 and Nfe2l2/NRF2) relative to DOX-treated WT controls. Additionally, the deletion of Ccn2 markedly attenuated DOX-induced cardiac fibrosis. Collectively, these results suggest that CCN2 plays a pivotal role in the pathogenesis of DOX-mediated cardiotoxicity by modulating oxidative stress and fibrotic pathways. These findings provide a novel avenue for future investigations to explore the therapeutic potential of targeting CCN2 in the prevention of DOX-induced cardiac dysfunction.
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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 | 0.001 | 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".