Immune signatures of Alzheimer’s disease: profiles of neutrophils. (HUM1P.301)
Bibliographic record
Abstract
Abstract Alzheimer's disease (AD) is the most common form of dementia. Amyloïd plaques accumulation and microbial infections have been proposed as an important components of AD aetiology. Defects in amyloïd-β clearance by monocyte/macrophage/microglia, imply that the immune system may participate in development and progression of AD. Phenotype and functional analysis of polymorphonuclear neutrophils (PMN) in peripheral blood were performed by flow cytometry. Our cohort of patients comprised amnestic Mild Cognitive Impairment (aMCI) (n = 10), mild stage AD (mAD) (n = 10) and healthy elderly controls (n = 10). aMCI patients had memory impairment but no functional disorders. However, these patients have a 50% chance of developing AD within 3 years following the diagnostic. PMN number was unchanged between the three groups. In contrast, the CD177+ population was significantly increased in mAD patients (p < 0.05). Phagocytosis of opsonized bacteria was less in aMCI and AD patients than controls. This observation was associated in aMCI with a decrease in CD33 (siglec 3) and complement receptor for C5A expression. Decreased expression of CD14 (a pattern recognition receptor), CD15 (carbohydrate adhesion molecule) and CD16 (FcγRIII) expression was found in mAD patients. Our results describe for the first time alterations of neutrophils in aMCI patients. PMN analysis may provide a useful tool in early identification of AD patients.
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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 | 0.000 |
| 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) | 0.005 | 0.001 |
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".