The Possible Link Between Serum Lipocalin-2 Level and Mild Cognitive Impairment in Adults With Metabolic Syndrome
Bibliographic record
Abstract
Abstract Introduction: Metabolic syndrome (MetS) is associated with an increased risk of cognitive impairment. Lipocalin-2 (LCN2) or neutrophil gelatinase-associated lipocalin (NGAL), is an inflammatory protein, and participates in the innate immune response. LCN2 significantly decreased in the cerebrospinal fluid of individuals with mild cognitive impairment. A recent study reported that circulating lipocalin-2 is involved in early AD pathogenesis. However, the association of LCN2 and cognition in MetS patients are still unclear. Then, the present study aims to evaluate whether serum LCN2 levels are associated with the alteration of cognitive function in MetS subjects. Methods: Participants with MetS, but without dementia or prior psychiatric problems, were enrolled to the study. The demographic data and physical examination were assembled. Blood samples were collected to evaluate the metabolic parameters. Levels of serum LCN2 were determined with ELISA assay. The global score of the Thai version of Montreal cognitive assessment (MoCA) was used to assess cognitive function. Multivariable regression analysis was used to determine the associations. Results: Among 202 MetS participants, 111 (54.95 %) were female, and average age was 64.6 (SD 8.6). Mean serum LCN2 and MoCA score were 30.7 ng/ml (SD 17.6) and 19.3 (SD 4.8), respectively. Serum LCN2 levels were negatively associated with the MoCA scores in crude analysis (B=-0.053; 95%CI -0.090, -0.015; p 0.006). After adjustment for sex, age, waist circumference, and creatinine levels, there was an association between the higher serum LCN2 levels and the lower MoCA scores (B=-0.049; 95%CI -0.090, -0.008; p 0.019). Conclusion: These findings suggest the association between serum LCN2 levels and MCI in MetS subjects. However, further longitudinal study should be investigated to support the link between serum LCN2 levels and cognitive impairment.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".