Serum Level of Endogenous Secretory Receptor for Advanced Glycation End Products and Other Factors in Type 2 Diabetic Patients With Mild Cognitive Impairment
Bibliographic record
Abstract
OBJECTIVE: Determine the serum levels of endogenous secretory receptor for advanced glycation end products (esRAGEs) in patients with type 2 diabetes and mild cognitive impairment (MCI) and in control patients with type 2 diabetes but no MCI, and examine the relationship of esRAGE and MCI with other clinical factors. RESEARCH DESIGN AND METHODS: A total of 101 patients with type 2 diabetes who were hospitalized in the Department of Endocrinology at Fujian Provincial Hospital between January 2010 and January 2011 were enrolled. There were 58 patients with MCI and 43 patients without MCI (control). Serum levels of esRAGE were measured using an enzyme-linked immunosorbent assay (ELISA). Other clinical parameters were also measured. RESULTS: Type 2 diabetic patients with MCI had a longer duration of diabetes; elevated HbA(1c), total cholesterol (CHOL), LDL cholesterol (LDL-C), triglyceride (TG), intima-media thickness, C-reactive protein (CRP), and brachial-ankle pulse wave velocity (ba-PWV); and lower ankle brachial index (ABI) and esRAGE relative to the control group. Among patients with MCI, the Montreal Cognitive Assessment (MoCA) score was positively correlated with serum esRAGE but negatively correlated with CHOL. Spearman rank correlation analysis indicated that esRAGE was positively correlated with MoCA score and ABI but negatively correlated with ba-PWV, CHOL, TG, and CRP in all subjects. CONCLUSIONS: Our results suggest that esRAGE may be a potential protective factor for dyslipidemia, atherosclerosis, and MCI in patients with type 2 diabetes.
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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 | 0.000 | 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".