Photic and Pineal Modulation of Food Anticipatory Circadian Activity Rhythms in Rodents
Bibliographic record
Abstract
Restricted daily feeding schedules entrain circadian oscillators that generate food anticipatory activity (FAA) rhythms in nocturnal rodents. The location of food-entrainable oscillators (FEOs) necessary for FAA remains uncertain. The most common procedure for inducing circadian FAA is to limit food access to a few hours in the middle of the light period, when activity levels are normally low. Although light at night suppresses activity (negative masking) in nocturnal rodents, it does not prevent the expression of daytime FAA. Nonetheless, light could reduce the duration or magnitude of FAA. If so, then neural or genetic ablations designed to identify components of the food-entrainable circadian system could alter the expression of FAA by affecting behavioral responses to light. To assess the plausibility of light as a potential mediating variable in studies of FAA mechanisms, we quantified FAA in rats and mice alternately maintained in a standard full photoperiod (12h of light/day) and in a skeleton photoperiod (two 60 min light pulses simulating dawn and dusk). In both species, FAA was significantly and reversibly enhanced in the skeleton photoperiod compared to the full photoperiod. In a third experiment, FAA was found to be significantly attenuated in rats by pinealectomy, a procedure that has been reported to enhance some effects of light on behavioral circadian rhythms. These results indicate that procedures affecting behavioral responses to light can significantly alter the magnitude of food anticipatory rhythms in rodents.
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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 | 0.001 | 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 | 0.001 |
| 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".