Correlation between Blood Monocytes and CSF Tau in Alzheimer’s Disease: The Effect of Gender and Cognitive Decline
Bibliographic record
Abstract
Neuroinflammation is one of the main mechanisms contributing to the pathogenesis of Alzheimer’s disease (AD), although its key role and the immune cells involved have not yet been identified. Blood monocytes appear to play a role in the clearance of AD-related amyloid-β (Aβ) and tau protein. This retrospective study evaluated a possible correlation between blood monocytes; the concentrations of Aβ, total tau (t-Tau), and phosphorylated tau (p-Tau) in the cerebrospinal fluid (CSF); and cognitive decline assessed according to the Montreal Cognitive Assessment (MoCA). We collected data from 33 patients with AD or mild cognitive impairment (MCI) due to AD (15 men and 18 women) and found, along with a significant reduction in the concentration of blood monocytes in women (p-value = 0.083),significant correlations between the number of blood monocytes and the concentration of t-Tau in CSF (p-value = 0.045) and between blood monocytes and MoCA score (p-value = 0.037). These results confirm the role of blood monocytes in the pathogenesis of AD, provide further evidence of a gender difference in the neuroinflammatory process underlying AD, and show that blood monocyte count may reflect the cognitive impairment of AD 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 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".