The cardioprotective effects of probucol against Anthracycline and Trastuzumab mediated cardiotoxicity
Bibliographic record
Abstract
Background: In breast cancer patients, the administration of Trastuzumab and Doxorubicin is associated with an increased risk of cardiotoxicity. The aim of the study was to determine if the antioxidant probucol would be useful in attenuating this drug induced cardiotoxicity. Methods: In an acute murine model of chemotherapy induced cardiomyopathy, wild-type C57Bl/6 mice received one of the following regimens: (1) control; (2) doxorubicin; (3) trastuzumab; (4) dox+trastuzumab; (5) probucol; (6) probucol +dox; (7) probucol+trastuzumab; (8) probucol+dox+trastuzumab. Serial murine echocardiography with tissue Doppler imaging was performed daily. Histological and biochemical studies were conducted at day 10 of the experiment. Results: Mice treated with prophylactic probucol demonstrated minimal cardiotoxicity compared with those treated with doxorubicin+trastuzumab. Survival rate was only 27% at day 3 of the experiment in the doxorubicin+trastuzumab group compared to 82% of mice receiving probucol+ doxorubicin+trastuzumab. Survival, apoptosis and histological remodeling were preserved in mice prophylactically treated with probucol following the administration of trastuzumab+doxorubicin. Conclusion: The synergistic cardiotoxicity of trastuzumab plus doxorubicin is attenuated by the antioxidant probucol.
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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".