Anti-apoptotic response during anoxia and recovery in a freeze-tolerant wood frog (<i>Rana sylvatica)</i>
Bibliographic record
Abstract
The common wood frog, Rana sylvatica, utilizes freeze tolerance as a means of winter survival. Concealed beneath a layer of leaf litter and blanketed by snow, these frogs withstand subzero temperatures by allowing approximately 65-70% of total body water to freeze. Freezing is generally considered to be an ischemic event in which the blood oxygen supply is impeded and may lead to low levels of ATP production and exposure to oxidative stress. Therefore, it is as important to selectively upregulate cytoprotective mechanisms such as the heat shock protein (HSP) response and expression of antioxidants as it is to shut down majority of ATP consuming processes in the cell. The objective of this study was to investigate another probable cytoprotective mechanism, anti-apoptosis during oxygen deprivation and recovery in the anoxia tolerant wood frog. In particular, relative protein expression levels of two important apoptotic regulator proteins, Bax and p-p53 (S46), and five anti-apoptotic/pro-survival proteins, Bcl-2, p-Bcl-2 (S70), Bcl-xL, x-IAP, and c-IAP in response to normoxic, 24 Hr anoxic exposure, and 4 Hr recovery stages were assessed in the liver and skeletal muscle using western immunoblotting. The results suggest a tissue-specific regulation of the anti-apoptotic pathway in the wood frog, where both liver and skeletal muscle shows an overall decrease in apoptosis and an increase in cell survival. This type of cytoprotective mechanism could be aimed at preserving the existing cellular components during long-term anoxia and oxygen recovery phases in the wood frog.
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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".