Simulating Season: The Effects of Photoperiod and Temperature on Thermogenesis in Deer Mice
Bibliographic record
Abstract
Ambient temperature is known to drive changes in the thermal physiology of mammals, such as an increase in the capacity for thermogenesis in winter. Previous work has shown that acclimation to chronic cold increases the capacity for non-shivering thermogenesis (NST) and thermogenic capacity (cold-induced maximal oxygen consumption, V̇O2max) in deer mice (Peromyscus maniculatus). Photoperiod, is an important driver of seasonal changes in physiology. In the wild, animals are attuned to seasonal changes in temperature and photoperiod. However, the independent and combined effects of temperature and photoperiod on the capacity for NST in small mammals, such as the deer mouse, are still not fully understood. To address this, we acclimated deer mice to long or short photoperiods (12h or 8h light), in either thermoneutral or cold conditions (30°C or 5°C). To simulate the fall conditions in their natural habitat (Nebraska) we gradually reduced either daylength, temperature, or both over 4 weeks and acclimated mice an additional 4 weeks at those conditions. After the 8 weeks of acclimation, we determined NST and V̇O2max. We found that cold and short photoperiod were necessary to increase NST, and either short photoperiod or cold was sufficient to increase V̇O2max. There were no corresponding differences in iBAT mass, lipid droplet morphology, nor in mitochondrial content. However, there was a corresponding increase in UCP1 content per unit mitochondria. These data highlight the importance of both photoperiod and temperature as cues to prepare thermogenic responses beneficial as winter approaches.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 teacher head, 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".