Innate immune response changes during the progression of Alzheimer’s disease
Bibliographic record
Abstract
Abstract Alzheimer’s disease (AD) is the most frequent type of dementia. It is primarily a neurodegenerative disease but neuroinflammation plays an important role in the pathogenesis. The dementia develops over decades and progresses from health to AD via a Mild cognitive impairment (MCI) stage. Neuroinflammation precedes the development of the other pathological hallmarks like amyloid plaque formation. Monocytes and macrophages play an important role in neuroinflammation. The aim of the present work was to determine the phenotypes and functions of peripheral monocytes and macrophages, differentiated from these monocytes, through various stages of the disease from health via subjective memory complaints and MCI to mild AD. After informed consent, we enrolled 9 individuals into each of the four groups. We studied phagoburst (flow cytometry), chemotaxis (Boyden chamber), cytokine production (Luminex) and phenotypes (flow cytometry). The results showed a progressive decrease from the healthy group to the mild AD group in both free radical production as well as chemotaxis concomitantly with an increase in inflammatory cytokine production. There was also a shift towards the more inflammatory phenotype (intermediate) of monocytes from healthy to AD. In contrast, monocytes showed increased M2 phenotype in AD compared to healthy. The results demonstrated an increased inflammatory status during progression towards AD, however the various parameters of the innate immune system showed differential changes during this progression depending on their differentiation status.
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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) | 0.001 | 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".