Cardiomyocyte specific adipose triglyceride lipase overexpression prevents doxorubicin induced cardiac dysfunction in female mice
Bibliographic record
Abstract
OBJECTIVES: Anthracyclines such as doxorubicin are an effective class of antineoplastic agents. Despite its efficacy in the treatment of a variety of cancers, the clinical use of doxorubicin is limited by cardiac side effects. While it has been suggested that doxorubicin alters myocardial fatty acid metabolism, it is poorly understood whether this is the case and whether variations in myocardial triacylglycerol (TAG) metabolism contribute to doxorubicin induced cardiotoxicity. Since TAG catabolism in the heart is controlled by adipose triglyceride lipase (ATGL), this study examined the influence of doxorubicin on cardiac energy metabolism and TAG values as well as the consequence of forced expression of ATGL in the setting of doxorubicin induced cardiotoxicity. DESIGN AND SETTING: Wild type (WT) mice and mice with cardiomyocyte specific ATGL overexpression were divided into two groups per genotype that received a weekly intraperitoneal injection of saline or doxorubicin for 4 weeks. RESULTS: Four weeks of doxorubicin administration significantly impaired in vivo systolic function (11% reduction in ejection fraction, p<0.05), which was associated with increased lung wet to dry weight ratios. Furthermore, doxorubicin induced cardiac dysfunction was independent of changes in glucose and fatty acid oxidation in WT hearts. However, doxorubicin administration significantly reduced myocardial TAG content in WT mice (p<0.05). Importantly, cardiomyocyte specific ATGL overexpression and the resulting decrease in cardiac TAG accumulation attenuated the decrease in ejection fraction (p<0.05) and thus protected mice from doxorubicin induced cardiac dysfunction. CONCLUSIONS: Taken together, our data suggest that chronic reduction in myocardial TAG content by cardiomyocyte specific ATGL overexpression is able to prevent doxorubicin induced cardiac dysfunction.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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 teacher head, 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".