Higher Plasma Level of Nampt Presaging Memory Dysfunction in Chinese Type 2 Diabetes Patients with Mild Cognitive Impairment
Bibliographic record
Abstract
BACKGROUND: In addition to glucose metabolism, adipocytokine Nicotinamide phosphoribosyltransferase (Nampt) has been proposed as a multifunctional protein involved in insulin resistance. Insulin resistance always occurs before the onset of type 2 diabetes mellitus (T2DM) and damages the cognition of T2DM patients very early. OBJECTIVE: We aimed to investigate the role and potential clinical value of Nampt in early cognitive decline of T2DM. METHODS: A total of 195 Chinese T2DM patients were enrolled and divided into a mild cognition impairment (MCI) group and a healthy cognition group according to Montreal Cognitive Assessment (MoCA) score. Their cognitive function was extensively assessed. The plasma level of Nampt was measured via enzyme-linked immunosorbent assay. RESULTS: In the MCI group (n = 78, MoCA < 26), the plasma level of Nampt was significantly higher than the controls (p < 0.01). After adjusting for age, sex, and level of education, Nampt levels were negatively associated with most of the cognitive domains forecasting hypomnesia (all p < 0.007). Nevertheless, hierarchical regression analysis further revealed that Nampt was an independent risk factor of MCI in Chinese T2DM patients (all p < 0.05), including Logic Memory Test (β= -0.31, p < 0.01), Auditory Verbal Learning Test delayed recall (β= -0.26, p < 0.01), and so on, which represent memory function. Correlation analysis showed that Nampt related to insulin resistance (HOMA-IR), glycosylated hemoglobin (HbA1c), and lipid levels (all p < 0.05). CONCLUSIONS: We found that higher plasma level of Nampt presages memory dysfunction in MCI in Chinese T2DM patients. Further studies are necessary to confirm its scanning and prognosis prediction value of the disease clinically.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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".