Low Plasma Leptin and High Soluble Leptin Receptor Levels Are Associated With Mild Cognitive Impairment in Type 2 Diabetic Patients
Bibliographic record
Abstract
Background: Metabolic disturbances, such as hyperglycemia, hyperlipidemia, and obesity, are thought to be risk factors for Alzheimer's disease. Objective: This study aimed to investigate whether adipokine leptin and soluble leptin receptor (sOBR) levels are correlated with mild cognitive impairment (MCI) and metabolic status of the patients of type 2 diabetes mellitus (T2DM). Methods: Total of 169 T2DM patients were recruited and divided according to the Montreal Cognitive Assessment (MoCA) score. Their cognition and metabolic parameters were extensively assessed. Plasma leptin and sOBR levels were determined by RIA and ELISA, respectively. Free leptin index (FLI) was calculated. Results: Of 124 enrolled T2DM patients, 61 were diagnosed with MCI (MoCA< 26). In MCI group and female subgroup, leptin levels and FLI were significantly lower and sOBR concentrations were higher when compared with their respective health cognition controls (all p < 0.05). Leptin levels and FLI were positively associated with the most cognitive domains and their Waist-to-Hip Ratio (WHR), a traditional index of central obesity. Leptin, sOBR, and WHR were independent variables of MCI in all individuals (all p < 0.05). For the females, MoCA was also positively correlated with leptin (β= 0.893, p < 0.001) and negatively correlated with WHR (β= -0.363, p = 0.014). Leptin was positively correlated only with WHR (β= 0.441, p = 0.025). Conclusions: This study showed that a high level of leptin and low level of sOBR are associated with the improved cognitive function in T2DM patients and more significantly in female individuals, while WHR, as an indicator of the visceral obesity, contributes to cognitive deficits.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".