Role of Oxidative Stress in the Mechanisms of Anthracycline‐Induced Cardiotoxicity: Effects of Preventive Strategies
Bibliographic record
Abstract
Anthracycline‐induced cardiotoxicity (AIC) persists as a significant cause of morbidity and mortality in cancer survivors. Although many protective strategies have been evaluated, cardiotoxicity remains an ongoing threat. The mechanisms of AIC remain unclear; however, several pathways have been proposed, suggesting a multifactorial origin. When the central role of topoisomerase 2 β in the pathophysiology of AIC was described some years ago, the classical reactive oxygen species (ROS) hypothesis shifted to a secondary position. However, new insights have reemphasized the importance of the role of oxidative stress‐mediated signaling as a common pathway and a critical modulator of the different mechanisms involved in AIC. A better understanding of the mechanisms of cardiotoxicity is crucial for the development of treatment strategies. It has been suggested that the available therapeutic interventions for AIC could act on the modulation of oxidative balance, leading to a reduction in oxidative stress injury. These indirect antioxidant effects make them an option for the primary prevention of AIC. In this review, our objective is to provide an update of the accumulated knowledge on the role of oxidative stress in AIC and the modulation of the redox balance by potential preventive strategies.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".