Lipoprotein-associated Phospholipase A2 Is Associated with Risk of Mild Cognitive Impairment in Chinese Patients with Type 2 Diabetes
Bibliographic record
Abstract
Type 2 diabetes mellitus (T2DM) is a low-grade chronic inflammatory diseases, which have been implicated in the pathogenesis of cognitive decline. We aim to evaluate associations between inflammatory markers and the risk of mild cognitive impairment (MCI) in T2DM. This study of 140 diabetic patients involved 71 with MCI and 69 controls. Clinical parameters, neuropsychological tests, high sensitivity C reactive protein (hsCRP), interleukin-6 (IL-6), lipoprotein-associated Phospholipase A2 (Lp-PLA2) mass and activity were measured. The results showed significantly higher plasma hsCRP, IL-6, Lp-PLA2 mass and activity in MCI group compared to controls. In T2DM with MCI, the Montreal Cognitive Assessment (MoCA) score was positively correlated with education level and high-density lipoprotein cholesterol (HDL-c), but inversely correlated with age, glycosylated hemoglobin, intima-media thickness (IMT), hsCRP, IL-6, and Lp-PLA2 mass and activity. Correlation analysis showed that both plasma Lp-PLA2 mass and activity were positively correlated with total cholesterol, low-density lipoprotein cholesterol, and IMT but negatively associated with MoCA score. Multivariable logistic regression analysis indicated higher hsCRP, Lp-PLA2 mass, Lp-PLA2 activity, and lower HDL-c to be independent risk factors increasing the possibility of MCI in T2DM. In conclusion, plasma Lp-PLA2 and hsCRP were found to be associated with the risk of MCI among T2DM patients.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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 | 0.001 |
| 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".