Exploring The Relationship Between Mitochondrial-linked Cell Death And Muscle Atrophy During Ovarian Cancer Progression
Bibliographic record
Abstract
The mechanisms underlying muscle atrophy during ovarian cancer are not fully understood. This study investigated the role of mitochondrial hydrogen peroxide (mH2O2)-mediated apoptosis and necroptosis in muscle atrophy using an orthotopic epithelial ovarian cancer (EOC) model at 40 and 80 days of tumor progression. We also examined the effects of the mitochondrial-targeted antioxidant SkQ1 on mH2O2 levels, regulation of apoptosis and necroptosis, and atrophy. Contrary to existing literature, muscle atrophy preceded EOC-induced changes in mH2O2 emission, and SkQ1, despite lowering mH2O2, did not prevent atrophy. Apoptotic markers (mPT, caspase-3, -9 activity) were elevated early in EOC progression and remained high, while necroptosis markers (RIPK1, phosphorylated MLKL/total MLKL) decreased with cancer progression. EOC-induced changes in necroptosis were unaffected by SkQ1, whereas markers of apoptosis (caspase-3/-9 activities) were downregulated by SkQ1. This study lays a crucial foundation for future research into regulated cell death pathways as mechanisms of cancer-induced atrophy.
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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) | 0.002 | 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".