Mechanisms associated with mitochondrial-generated reactive oxygen species in cancerThis article is one of a selection of papers published in a Special Issue on Oxidative Stress in Health and Disease.
Bibliographic record
Abstract
The mitochondria are unique cellular organelles that contain their own genome and, in conjunction with the nucleus, are able to transcribe and translate genes encoding components of the electron transport chain (ETC). To do so, the mitochondria must communicate with the nucleus via the production of reactive oxygen species (ROS) such as hydrogen peroxide (H2O2), which are produced as a byproduct of aerobic respiration within the mitochondria. Mitochondrial signaling is proposed to be altered in cancer cells, where the mitochondria are frequently found to harbor mutations within their genome and display altered functional characteristics leading to increased glycolysis. As signaling molecules, ROS oxidize and inhibit MAPK phosphatases resulting in enhanced proliferation and survival, an effect particularly advantageous to cancer cells. In terms of transcriptional regulation, ROS affect the phosphorylation, activation, oxidation, and DNA binding of transcription factors such as AP-1, NF-kappaB, p53, and HIF-1alpha, leading to changes in target gene expression. Increased ROS production by defective cancer cell mitochondria also results in the upregulation of the transcription factor Ets-1, a factor that has been increasingly associated with aggressive cancers.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.004 |
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".