The effect of food access schedule and diet composition on the rhythmicity of serum melatonin and pineal N-acetyltransferase activity in rats /
Bibliographic record
Abstract
Melatonin is a hormone secreted by the pineal gland, which is known to modulate biological rhythms in mammals. This study investigated the effect of food access schedule and dietary composition on serum melatonin and pineal NAT activity in adult male Wistar rats. These rats were maintained on a 12:12 h light:dark schedule with lights on at 0800h. The rats were randomly assigned to two dietary groups. A group was simultaneously fed a protein-rich and carbohydrate-rich granulated diet and the other group fed granulated rat chow. Each dietary group was further divided based on dietary feeding schedules. Animals were fed between 0800--1600 h or fed ad libitum. The study revealed that protein intake of rats fed the dietary choice was lower with the restricted access than in the free access. In rats fed dietary choice, the nocturnal melatonin levels and pineal NAT activity were significantly lower under the restricted access feeding when compared to the ad libitum feeding schedule. This was not observed in rats fed single chow diet. In conclusion our data demonstrate that food composition does affect the nocturnal synthesis of melatonin as well as the activity of the enzyme NAT. This could be via dietary intake of tryptophan, which is a precursor melatonin synthesis in the pineal gland.
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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) | 0.001 | 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) | 0.002 | 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".