Perspectives in Cell Cycle Regulation: Lessons from an Anoxic Vertebrate
Bibliographic record
Abstract
The ability of an animal, normally dependent on aerobic respiration, to suspend breathing and enter an anoxic state for long term survival is clearly a fascinating feat, and has been the focus of numerous biochemical studies. When anoxia tolerant turtles are faced with periods of oxygen deprivation, numerous physiological and biochemical alterations take place in order to facilitate vital reductions in ATP consumption. Such strategies include reversible post-translational modifications as well as the implementation of translation and transcription controls facilitating metabolic depression. Although it is clear that anoxic survival relies on the suppression of ATP consuming processes, the state of the cell cycle in anoxia tolerant vertebrates remain elusive. Several anoxia tolerant invertebrate and embryonic vertebrate models display cell cycle arrest when presented with anoxic stress. Despite this, the cell cycle has not yet been characterized for anoxia tolerant turtles. Understanding how vertebrates respond to anoxia can have important clinical implications. Uncontrollable cellular proliferation and hypoxic tumor progression are inescapably linked in vertebrate tissues. Consequentially, the molecular mechanisms controlling these processes have profound clinical consequences. This review article will discuss the theory of cell cycle arrest in anoxic vertebrates and more specifically, the control of the retinoblastoma pathway, the molecular markers of cell cycle arrest, the activation of checkpoint kinases, and the possibility of translational controls implemented by microRNAs.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.002 | 0.005 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.006 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".