Egg white hydrolysate enhances insulin sensitivity in high-fat diet-induced insulin-resistant rats via Akt activation
Bibliographic record
Abstract
Agents that block the renin-angiotensin system (RAS) improve glucoregulation in the metabolic syndrome disorder. We evaluated the effects of egg white hydrolysate (EWH), previously shown to modulate the protein abundance of RAS component in vivo, on glucose homeostasis in diet-induced insulin-resistant rats. Sprague-Dawley rats were fed a high-fat diet (HFD) for 6 weeks to induce insulin resistance. They were then randomly divided into four groups receiving HFD or HFD supplemented with different concentrations of EWH (1, 2 and 4 %) for another 6 weeks in the first trial. In the second trial, insulin-resistant rats were divided into two groups receiving only HFD or HFD+4 % EWH for 6 weeks. Glucose homeostasis was assessed by oral glucose tolerance and insulin tolerance tests. Insulin signalling and protein abundance of RAS components, gluconeogenesis enzymes and PPARγ were evaluated in muscle, fat and liver. Adipocyte morphology and inflammatory markers were evaluated. In vivo administration of EWH increased insulin sensitivity, improved oral glucose tolerance (P < 0·0001) and reduced systemic inflammation (P < 0·05). EWH potentiated insulin-induced Akt phosphorylation in muscle (P = 0·0341) and adipose tissue (P = 0·0276), but minimal differences in the protein abundance of tissue RAS components between the EWH and control groups were observed. EWH treatment also reduced adipocyte size (P = 0·0383) and increased PPARγ2 protein abundance (P = 0·0237). EWH treatment yielded positive effects on the inflammatory profile, glucose tolerance, insulin sensitivity and adipocyte differentiation in HFD-induced insulin resistance rats. The involvement of local RAS activity requires further investigation.
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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 | 0.001 |
| 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".