Diets enriched in whey or casein improve energy balance and prevent morbidity and renal damage in salt-loaded and high-fat-fed spontaneously hypertensive stroke-prone rats.
Bibliographic record
Abstract
High-fat diets induce obesity and increase risks of diabetes and cardiovascular and renal disorders. Whey- or casein-enriched diets decrease food intake and weight gain; however, their cardiovascular and renal benefits are unclear. We determined whether whey- and casein-enriched diets improve energy balance and are protective against renal damage and morbidity associated with stroke in an obesogenic and hypertensive experimental setting. We also assessed whether the hypophagic effects of these diets were due to reduced diet preference. In experiment 1, spontaneously hypertensive stroke-prone rats were randomized to (a) control (CON; 14% kcal protein, 33% fat), (b) whey (WHY; 40% protein, 33% fat), (c) casein (CAS; 40% protein, 33% fat) or (d) chow (CHW; 24% protein, 13% fat) for 12 weeks with 1% salt in drinking water for CON, WHY and CAS groups. Our results demonstrated that both WHY and CAS produced short-term hypophagia, moderately increased energy expenditure and decreased respiratory quotient, body weight and lean mass, with effects of WHY being more prolonged. Further, only WHY decreased fat mass and blood pressure. Importantly, both WHY and CAS prevented morbidity associated with stroke and decreased indices of renal inflammation (tumor necrosis factor-α, interleukin-6) and damage (osteopontin, renal lesions). In experiment 2, following four initial conditioning trials, the preference for CON, WHY or CAS diet was determined. Both WHY and CAS decreased food intake during conditioning and decreased preference. In conclusion, diets enriched in whey or casein improved energy balance, increased survival and prevented renal damage in salt-loaded and high-fat-fed spontaneously hypertensive stroke-prone rats.
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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 | 0.001 |
| 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".