Exploration of the Fasting Hypoglycemic Mechanism of Casein Hydrolysate Enriched with Glu/Gln and Glu/Gln-Containing Peptides in db/db Diabetic-like Mice Using Multiomics Analysis
Bibliographic record
Abstract
The fasting hypoglycemic effect of casein hydrolysate (CH) was investigated in db/db diabetic-like mice using a multiomics integrated analysis of peptidome, transcriptome, and metabolome. Results showed that the oral administration of CH at a dose of 600 mg/kg/day for 4 weeks reduced the fasting blood glucose levels by 14.73 ± 9.77%, alleviated insulin resistance (HOMA-IR index) by 36.91 ± 22.62%, and mitigated hepatic damage in db/db diabetic-like mice. Hepatic differential metabolites after CH treatment were enriched in Glu-related metabolites, which acted as substrates for the TCA cycle, enhancing hepatic glucose consumption. The hepatic transcriptomic results revealed that CH treatment upregulated ( p < 0.05) hub gene expressions of pparg and pik3cb, leading to an activation of the PPAR signaling pathway, further improving the insulin/PI3K/AKT signaling pathway. The hub gene expressions were highly correlated with Glu-related metabolites in multiomics integrated analysis. Glx/Glx-containing peptides (Glx represents Glu and Gln) in CH, as a dietary supplement to increase hepatic Glu-related metabolites, might be the key active component responsible for its hypoglycemic effect. Particularly, the supplement of Glx was confirmed to effectively ( p < 0.05) enhance glucose consumption in hepatocytes. This provides a basis for the development of CHs as functional food.
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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) | 0.001 | 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".