The Activation of Prosurvival Pathways in <i>Myotis lucifugus</i> during Torpor
Bibliographic record
Abstract
, enter a long-term state of hibernation characterized by a period of deep torpor that can range from days to weeks. Torpid bats undergo metabolic rate depression that not only results in physiological changes but also promotes biochemical changes that favor survival. The present study utilizes multiplex technology to assess key early apoptosis markers and a select group of antioxidant enzymes in muscle, heart, and liver in euthermic controls and torpid bats. Muscle showed a significant decrease in the proapoptotic c-Jun N-terminal kinase and p53 and the antioxidant enzyme catalase but a significant increase in peroxiredoxin 2 levels. The heart responded similarly, with most proapoptotic proteins (caspase 8/9 and p53) remaining at low levels, while the antiapoptotic Bcl-2 protein significantly increased during torpor. There was no significant change in the antioxidant enzymes measured during torpor in the heart compared with the controls. The liver showed increases in catalase and Mn superoxide dismutase 2 enzymes during torpor, which correlated with activation of select antiapoptotic proteins and suppression of levels of proapoptotic ones. Overall, our data demonstrate that antiapoptotic and antioxidant defense responses have organ-specific regulation during torpor in bats. The induction of key antioxidant enzymes and antiapoptotic proteins may function as protective mechanisms that are necessary for surviving torpor.
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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".