Cytoprotective potential of anti-ischemic drugs against chemotherapy-induced cardiotoxicity in H9c2 myoblast cell line
Bibliographic record
Abstract
To investigate potential prevention or attenuation of anti- cancer drug induced cardiotoxicity using anti-ischemic drugs, a rat myoblast (H9c2) cell line was used as our in vitro cardiac model. Irinotecan and doxorubicin were found to be cytotoxic for the H9c2 cell line with IC50 of 30.69 ± 6.20 and 20.94 ± 6.05 mmol L-1, respectively. 5-Flurouracil and cladribine were not cytotoxic and thus IC50 could not be calculated. When 100 mmol L-1 doxorubicin was incubated for 72 hours with 50 mmol L-1 diltiazem, 100 mmol L-1 dexrazoxane and 100 mmol L-1 losartan, respectively, there was a 58.7 ± 10.2, 52.2 ± 11.7 and 44.7 ± 5.4 % reduction in cell death. When 200 mmol L-1 irinotecan was incubated for 72 hours with 100 mmol L-1 dexrazoxane, losartan and diltiazem, respectively, a 27.7 ± 6.9, 25.6 ± 5.1, and 19.1 ± 2.3 % reduction in cell death was observed. Our data suggests that losartan and diltiazem were as effective as dexrazoxane in protecting the cells against irinotecan- and doxorubicin-induced cell toxicity. These findings offer potential uses of anti- -ischemic drugs for ablation of cytotoxicity in response to mitochondrial injury, thereby improving patient outcomes and reducing health-care costs.
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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) | 0.001 | 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 | 0.001 |
| 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".