Differences in Plasma Lactoferrin Concentrations Between Subjects with Normal Cognitive Function and Mild Cognitive Impairment: An Observational Study
Bibliographic record
Abstract
Background: Previous studies suggested that decreased saliva lactoferrin (LF) levels might be used to differentiate subjects with mild cognitive impairment (MCI) from subjects with normal cognitive function (NCF). Here, we aimed to assess differences in plasma LF concentrations between subjects with NCF and MCI. Methods: In total, 113 NCF subjects and 113 MCI individuals were included in this study. Cognitive function was assessed using the Montreal Cognitive Assessment (MoCA) scale, and anthropometric parameters, body composition, physical activity, cardio-metabolic parameters, and LF levels were measured. Results: MCI subjects had significantly lower LF levels than NCF participants (p < 0.0001). There were also significant differences between the study groups in the smoking history (p = 0.0190), alcohol consumption (p = 0.0036), intake of hypoglycaemic drugs (p = 0.0140), vigorous activity (MET-min/day: p = 0.0223, min/day: p = 0.0133), and energy expenditure associated with activity (p = 0.0287). Moreover, the MoCA test results significantly correlated with LF levels (p = 0.0026), and there were significant differences between MoCA tertiles and LF levels (p = 0.0189). Also, adjusted logistic regression analysis results showed that LF concentrations (p = 0.0382), alcohol consumption (p = 0.0203), and intake of hypoglycaemic drugs (p = 0.0455) were independent predictors of MCI prevalence. Conclusions: In conclusion, MCI subjects are characterised by lower plasma LF concentrations than NCF individuals, but further studies are needed to confirm these findings.
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".