Exploring Thermal Sensitivities and Adaptations of Oxidative Phosphorylation Pathways
Bibliographic record
Abstract
Temperature shifts are a major challenge to animals; they drive adaptations in organisms and species, and affect all physiological functions in ectothermic organisms. Understanding the origin and mechanisms of these adaptations is critical for determining whether ectothermic organisms will be able to survive when faced with global climate change. Mitochondrial oxidative phosphorylation is thought to be an important metabolic player in this regard, since the capacity of the mitochondria to produce energy greatly varies according to temperature. However, organism survival and fitness depend not only on how much energy is produced, but, more precisely, on how oxidative phosphorylation is affected and which step of the process dictates thermal sensitivity. These questions need to be addressed from a new perspective involving a complex view of mitochondrial oxidative phosphorylation and its related pathways. In this review, we examine the effect of temperature on the commonly measured pathways, but mainly focus on the potential impact of lesser-studied pathways and related steps, including the electron-transferring flavoprotein pathway, glycerophosphate dehydrogenase, dihydroorotate dehydrogenase, choline dehydrogenase, proline dehydrogenase, and sulfide:quinone oxidoreductase. Our objective is to reveal new avenues of research that can address the impact of temperature on oxidative phosphorylation in all its complexity to better portray the limitations and the potential adaptations of aerobic metabolism.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".