Glycomacropeptide for Management of Insulin Resistance and Liver Metabolic Perturbations
Bibliographic record
Abstract
BACKGROUND AND AIMS: The increasing prevalence and absence of effective global treatment for metabolic syndrome (MetS) are alarming given the potential progression to severe non-communicable disorders such as type 2 diabetes and nonalcoholic fatty liver disease. The purpose of this study was to investigate the regulatory role of glycomacropeptide (GMP), a powerful milk peptide, in insulin resistance and liver dysmetabolism, two central MetS conditions. MATERIALS AND METHODS: C57BL/6 male mice were fed a chow (Ctrl), high-fat, high-sucrose (HFHS) diet or HFHS diet along with GMP (200 mg/kg/day) administered by gavage for 12 weeks. RESULTS: GMP lowered plasma insulin levels (in response to oral glucose tolerance test) and HOMA-IR index, indicating a more elevated systemic insulin sensitivity. GMP was also able to decrease oxidative stress and inflammation in the circulation as reflected by the decline of malondialdehyde, F2 isoprostanes and lipopolysaccharide. In the liver, GMP raised the protein expression of the endogenous anti-oxidative enzyme GPx involving the NRF2 signaling pathway. Moreover, the administration of GMP reduced the gene expression of hepatic pro-inflammatory COX-2, TNF-α and IL-6 via inactivation of the TLR4/NF-κB signaling pathway. Finally, GMP improved hepatic insulin sensitization given the modulation of AKT, p38 MAPK and SAPK/JNK activities, thereby restoring liver homeostasis as revealed by enhanced fatty acid β-oxidation, reduced lipogenesis and gluconeogenesis. CONCLUSIONS: Our study provides evidence that GMP represents a promising dietary nutraceutical in view of its beneficial regulation of systemic insulin resistance and hepatic insulin signaling pathway, likely via its powerful antioxidant and anti-inflammatory properties.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".