Photoperiod influences visceral adiposity and the adipose molecular clock independent of temperature in wild‐derived <i>Peromyscus leucopus</i>
Bibliographic record
Abstract
Abstract Physiology is closely synchronized to daily and seasonal light/dark cycles. Humans artificially extend daylight and experience irregular light schedules, resulting in dysregulation of metabolism and body mass. In rodents, winter‐like conditions (cold and short photoperiod) can alter energy balance and adipose tissue mass. To determine if photoperiod alone, independent of temperature, is a strong enough signal to regulate adiposity, we compared the effects of long and short photoperiod at thermoneutrality on adiposity and WAT gene expression in photoperiod‐sensitive, F1 generation wild‐derived adult male white‐footed mice (Peromyscus leucopus). Mice were housed in long‐day (16:8 light:dark) or short‐day (8:16 light:dark) photoperiod conditions at thermoneutrality (27°C) for 4 weeks with the extended light being provided through artificial lighting. Photoperiod did not impact body weight or calorie consumption. However, mice housed in long photoperiod with extended artificial light selectively developed greater visceral WAT mass without changing subcutaneous WAT or interscapular BAT mass. This was accompanied by a decrease in Adrβ3 and Ucp1 mRNA expression in visceral WAT with no change in Pgc1a, Lpl, or Hsl. Expression of Per1, Per2, and Nr1d1 mRNA in visceral WAT differed between long and short photoperiods over time when aligned to circadian time but not onset of darkness, indicating alterations in clock gene expression with photoperiod. These findings suggest that extended photoperiod through artificial light can promote visceral fat accumulation alone, independent of temperature, supporting that artificial light may play a role in obesity.
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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".