Inflammatory cytokines associated with cancer growth induce mitochondria and cytoskeleton alterations in cardiomyocytes
Bibliographic record
Abstract
Cardiac dysfunction is often observed in patients with cancer also representing a serious problem limiting chemotherapeutic intervention and even patient survival. In view of the recently established role of the immune system in the control of cancer growth, the present work has been undertaken to investigate the effects of a panel of the most important inflammatory cytokines on the integrity and function of mitochondria, as well as of the cytoskeleton, two key elements in the functioning of cardiomyocytes. Either mitochondria features or actomyosin cytoskeleton organization of in vitro-cultured cardiomyocytes treated with different inflammatory cytokines were analyzed. In addition, to investigate the interplay between tumor growth and cardiac function in an in vivo system, immunocompetent female mice were inoculated with cancer cells and treated with the chemotherapeutic drug doxorubicin at a dosing schedule able to suppress tumor growth without inducing cardiac alterations. Analyses carried out in cardiomyocytes treated with the inflammatory cytokines, such as tumor necrosis factor α (TNF-α), interferon γ (IFN-γ), interleukin 6 (IL-6), IL-8, and IL-1β revealed severe phenotypic changes, for example, of contractile cytoskeletal elements, mitochondrial membrane potential, mitochondrial reactive oxygen species production and mitochondria network organization. Accordingly, in immunocompetent mice, the tumor growth was accompanied by increased levels of the inflammatory cytokines TNF-α, IFN-γ, IL-6, and IL-8, either in serum or in the heart tissue, together with a significant reduction of ventricular systolic function. The alterations of mitochondria and of microfilament system of cardiomyocytes, due to the systemic inflammation associated with cancer growth, could be responsible for remote cardiac injury and impairment of systolic function observed in vivo.
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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".