Systemic study of selected histone deacetylase inhibitors in cardiac complications associated with cancer cachexia
Bibliographic record
Abstract
Cancer cachexia is mainly characterized by wasting of skeletal muscles and fat and body weight loss, along with severe complications of major organs like liver, heart, brain and bone. There can be diminishing performance of these major organs as cancer cachexia progresses, one such drastic effect on the cardiac system. In the present study, differential effect of histone deacetylase inhibitors (HDACi) on cardiac complications associated with cancer cachexia is studied. Two models were used to induce cancer cachexia: B16F1 induced metastatic cancer cachexia and Lewis lung carcinoma cell - induced cancer cachexia. Potential of Class I HDACi entinostat, Class II HDACi MC1568, and nonspecific HDACi sodium butyrate on cardiac complications were evaluated using the cardiac hypertrophy markers, hemodynamic markers, and cardiac markers along with histopathological evaluation of heart sections by Periodic acid-Schiff staining, Masson's trichrome staining, Picro-sirius red staining, and haematoxylin and eosin staining. Immunohistochemistry evaluation by vimentin and caspase 3 protein expression was evaluated. Entinostat showed promising results by attenuating the cardiac complications, and MC1568 treatment further exacerbated the cardiac complications, while non-conclusive effect were recorded after treatment with sodium butyrate. This study will be helpful in evaluating other HDACi for potential in cardiac complications associated with cancer cachexia.
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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".