Low serum apelin levels are associated with mild cognitive impairment in Type 2 diabetic patients
Bibliographic record
Abstract
BACKGROUND: Apelin is a new adipokine that is secreted by adipocytes, and is associated with insulin resistance (IR), inflammation, and obesity. This study was designed to investigate the role of apelin in type 2 diabetes mellitus (T2DM) patients with mild cognitive impairment (MCI). METHODS: A total of 235 patients with T2DM were included. The cognitive function of patients was evaluated using Montreal Cognitive Assessment (MoCA) tool, then patients were divided into MCI group and non-MCI group according to the MoCA score. Blood sample was analyzed for the level of apelin by enzyme-linked immunosorbent assay (ELISA). RESULTS: The MCI group (n = 73) presented lower serum apelin levels compared with the patients with normal cognitive function (P < 0.001). Apelin levels showed significantly negative correlation with diabetes duration, triglyceride (TG), total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C, creatinine and high sensitivity C-reactive protein (hs-CRP), and positive correlation with high-density lipoprotein cholesterol (HDL-C) and brain-derived neurotrophic factor (BDNF). Multivariable logistic regression analysis indicated that serum apelin (OR = 0.304, 95%CI: 0.104-0.886, P = 0.029), as well as education levels, diabetes duration, cardiovascular disease, serum HbA1c, HDL-C, creatinine, and BDNF, were independent risk factors of MCI in patients with T2DM. CONCLUSIONS: Serum apelin level is reduced in T2DM patients with MCI. Apelin might has protective effect against cognitive impairment and serve as a serum biomarker 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 | 0.001 |
| 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".