Mitochondrial dynamics and oxidative phosphorylation as critical targets in cancer
Bibliographic record
Abstract
It has long been recognised that cancer cells critically depend on reprogrammed patterns of metabolism that can enable robust and abnormally high levels of cell proliferation. As mitochondria form hubs of cellular metabolic activity, it is reasonable to propose that pathways within these organelles can form targets that can be manipulated to compromise the ability of cancer cells to cause disease. However, mitochondria are highly multi-functional, and the full range of mechanistic inter-connections are still being unravelled to enable the full potential of targeting mitochondria in cancer therapeutics. Here, we aim to highlight the potential of modulating mitochondrial dynamics to target key metabolic or apoptotic pathways in cancer cells. Distinct roles have been demonstrated for mitochondrial fission and fusion in different cancer contexts. Targeting of factors mediating mitochondrial dynamics may be directly related to impairment of oxidative phosphorylation, which is essential to sustain cancer cell growth and can also alter sensitivity to chemotherapeutic compounds. This area is still lacking a unified model, although further investigation will more comprehensively map the underlying molecular mechanisms to enable better rational therapeutic strategies based on these pathways.
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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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".