Dietary lactalbumin and lactoferrin interact with inulin to modulate energy balance in obese rats.
Bibliographic record
Abstract
Objective To determine whether diets enriched with the whey protein components lactalbumin and lactoferrin interact additively with inulin to improve energy balance by decreasing food intake and body weight (BW). Methods In four experiments, diet-induced obese rats were randomized to diets containing either lactalbumin or lactoferrin at low (20% kcal) or high (40% kcal) doses, and inulin at low (7.5% w/w) or high (15% w/w) doses, alone or in combination. Energy intake (EI), energy expenditure (EE), respiratory quotient (RQ), BW, body composition, plasma insulin, and leptin concentrations were measured. Results Lactalbumin and inulin at low doses were ineffective, whereas high doses additively decreased EI and RQ. Low doses of lactoferrin and inulin additively decreased EI, BW, fat and lean mass, and RQ. High doses of lactoferrin and inulin additively decreased EI, supra-additively decreased BW, fat, and lean mass, and also decreased RQ and plasma leptin concentrations. Conclusions High doses of lactalbumin and inulin additively decreased EI. Importantly, lactoferrin and inulin at both low and high dose combinations, additively or supra-additively, decreased EI, BW, and adiposity.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".