CycloZ Improves Hyperglycemia and Lipid Metabolism by Modulating Lysine Acetylation in KK-Ay Mice
Bibliographic record
Abstract
BACKGRUOUND: CycloZ, a combination of cyclo-His-Pro and zinc, has anti-diabetic activity. However, its exact mode of action remains to be elucidated. METHODS: KK-Ay mice, a type 2 diabetes mellitus (T2DM) model, were administered CycloZ either as a preventive intervention, or as a therapy. Glycemic control was evaluated using the oral glucose tolerance test (OGTT), and glycosylated hemoglobin (HbA1c) levels. Liver and visceral adipose tissues (VATs) were used for histological evaluation, gene expression analysis, and protein expression analysis. RESULTS: CycloZ administration improved glycemic control in KK-Ay mice in both prophylactic and therapeutic studies. Lysine acetylation of peroxisome proliferator-activated receptor gamma coactivator 1-alpha, liver kinase B1, and nuclear factor-κB p65 was decreased in the liver and VATs in CycloZ-treated mice. In addition, CycloZ treatment improved mitochondrial function, lipid oxidation, and inflammation in the liver and VATs of mice. CycloZ treatment also increased the level of β-nicotinamide adenine dinucleotide (NAD+), which affected the activity of deacetylases, such as sirtuin 1 (Sirt1). CONCLUSION: Our findings suggest that the beneficial effects of CycloZ on diabetes and obesity occur through increased NAD+ synthesis, which modulates Sirt1 deacetylase activity in the liver and VATs. Given that the mode of action of an NAD+ booster or Sirt1 deacetylase activator is different from that of traditional T2DM drugs, CycloZ would be considered a novel therapeutic option for the treatment of T2DM.
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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 | 0.000 |
| 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".