Dietary Obesity Caused by a Specific Circadian Eating Pattern
Bibliographic record
Abstract
The eating pattern is altered by high-fat diet-induced obesity. To clarify whether this is dependent on the fatty acid profile of the diet, the authors conducted two studies on adult female Sprague-Dawley rats fed normal-fat chow or high-fat diets with varying fatty acid composition. Eating pattern and body weight were assessed in rats fed canola-based (low in saturated fatty acids) or lard-based (moderate in saturated fatty acids) diets for 7 days, and in animals fed chow or canola- or butter-based diets (rich in saturated fatty acids) for 43 days. These parameters were also determined when restricted amounts of low-fat canola- or butter-based diets were consumed for 25 days. Early exposure to canola or lard high-fat feeding or prolonged access to canola- or butter-based fat-rich diets (relative to chow feeding) did not alter the normal light-dark distribution of food and energy intake. All animals ingested most of their food during the dark phase. However, feeding the high-fat canola- and butter-based diets produced an altered eating pattern during the light phase characterized by a smaller number of meals, longer intermeal interval, and enhanced satiety ratio, and consumption of shorter-lasting meals than chow-fed animals. Relative to canola or chow feeding, butter-fed animals consumed a lower number of meals during the dark phase and had a higher eating rate in the light phase, but ate larger meals overall. Only butter feeding led to overeating and obesity. When given a restricted amount of low-fat canola- or butter-based diet at the start of the light phase, rats ate most of their food in that phase and diurnal rather than nocturnal feeding occurred with restriction. These findings underscore the role of saturated fatty acids and the resulting eating pattern alteration in the development of 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 | 0.001 |
| 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".