Doxorubicin-induced apoptosis enhances monocyte infiltration and adverse cardiac remodeling in diabetic animals
Bibliographic record
Abstract
Diabetic cancer patients were treated with doxorubicin (DOX), a potent chemotherapeutic drug that induces cardiac toxicity; however, molecular mechanisms of cardiac toxicity in this specific disease progression in patients and animal models are completely unknown. Therefore, we designed a study to understand the effects of DOX-induced cardiac toxicity in diabetic animals and the involved pathophysiological mechanisms. C57BL/6 J mice were divided into four DOX- and diabetic (streptozotocin; STZ) – treated groups; control, STZ, DOX, and DOX+STZ. At day 14, animals were sacrificed, echocardiography was used to examine heart function, and heart and blood samples were collected to investigate apoptotic mechanisms (caspase 3, BAX, B-Cell leukemia/lymphoma 2 (Bcl2)), inflammation, and cardiac remodeling. Our data shows a significant (p < 0.05) increase in glucose levels, apoptotic markers, and monocyte infiltration at the site of apoptosis and triggered inflammatory immune response (tumor necrosis factor α (TNF-α) and interleukin 6 (IL-6)), in DOX+STZ animals compared with control and experimental groups. We also observed significant (p < 0.05) increase in myofibrillar area, fibrosis, and significantly decreased (p < 0.05) cardiac function in DOX-treated diabetic animals compared with controls. In conclusion, our data suggest that DOX induces significantly increased apoptosis, fibrosis, and structural alterations in diabetic hearts compared with non-diabetic animals.
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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 | 0.001 |
| 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".