Modulating Nrf2 transcription factor activity: Revealing the regulatory mechanisms of antioxidant defenses during hibernation in 13‐lined ground squirrels
Bibliographic record
Abstract
Mammalian hibernators undergo major behavioural, physiological and biochemical changes to survive hypothermia, ischaemia-reperfusion and finite fuel reserves during days or weeks of continuous torpor. During hibernation, the 13-lined ground squirrel (Ictidomys tridecemlineatus) undergoes a global suppression of energetically expensive processes such as transcription and translation, while selectively upregulating certain genes/proteins to mitigate torpor-related damage. Antioxidant defenses are critical for preventing damage caused by reactive oxygen species (ROS) during torpor and arousal, and Nrf2 is a critical regulator of these antioxidant genes. This study analysed the relative protein expression levels of Nrf2, KEAP1, small Mafs (MafF, MafK and MafG) and catalase and the regulation of Nrf2 transcription factors by post-translational modifications (PTMs) and protein-protein interactions with a negative regulator (KEAP1) during hibernation. It was found that a significant increase in MafK during late torpor predicated an increase in relative Nrf2 and catalase levels seen in arousal. Additionally, Nrf2-KEAP1 protein-protein interactions and Nrf2 PTMs, including serine phosphorylation and lysine acetylation, were responsive to cycles of torpor-arousal with peak responses occurring during arousal. These peaks seen during arousal correspond to a surge in oxygen consumption, which causes increased ROS production. Thus, these regulatory mechanisms could be important during hibernation because they provide mechanisms for mitigating the deleterious effects of oxidative stress by modifying Nrf2 expression and function in an energetically inexpensive manner.
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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".