Potential Involvement of Nicotinamide <i>N</i> -Methyltransferase in the Pathogenesis of Metabolic Syndrome
Bibliographic record
Abstract
BACKGROUND: Metabolic syndrome is a complex disorder characterized by the presence of insulin resistance (IR), type 2 diabetes mellitus (T2DM), impaired glucose tolerance (IGT), or impaired fasting glucose (IFG), plus at least two of the following conditions--hypertension, hyperlipidemia, obesity, and microalbuminuria. Metabolic syndrome exposes patients to a greater risk of developing cardiovascular disease (CVD) and is often associated with elevated levels of homocysteine (Hcy). In the current work, we analyzed the expression of nicotinamide N-methyltransferase (NNMT). Because NNMT is involved in Hcy metabolism and participates in the regulation of the cellular and plasma levels of this compound, we explored the role played by the enzyme in metabolic syndrome. METHODS: Real-time PCR, immunohistochemistry, western blot analysis, and catalytic activity assay were performed to evaluate NNMT expression levels in adipose tissue from 10 Wistar Ottawa Karlsburg W (WOKW) rats, which are an animal model for metabolic syndrome, and from 10 Dark Agouti (DA) rats as the disease-resistant control strain. RESULTS: NNMT mRNA, protein, and activity levels were significantly higher in adipose tissue obtained from WOKW rats compared with those observed in adipose tissue of DA rats. CONCLUSION: Data reported in this study represent the first evidence supporting the hypothesis that NNMT could play an important role in the pathogenesis of metabolic syndrome and could have a potential for the development of a targeted therapy.
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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) | 0.000 | 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 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".