Bibliographic record
Abstract
Beyond the time-honoured targeting of protein misfolding and aggregation, Alzheimer's disease needs new, innovative therapeutic directions. When exploring alternative druggable mechanisms, multifaceted in vitro and in vivo data demonstrate that immune system dysfunction is a pivotal driver of Alzheimer's disease progression. In pursuing neuroimmunological targets, a major but often under-discussed consideration regards the issue of whether innate or adaptive immunity (or both) within the neuroimmune network should be the centre of focus when devising immunotherapeutic approaches to Alzheimer's. This perspective article briefly reviews current data, concluding that while both innate and adaptive immunity contributes to the immunopathology of Alzheimer's, the proinflammatory microglia and cytokines of innate immunity will provide higher yield targets with a greater likelihood of efficacy. Although it seems paradoxical to focus on a rapid, short-lived aspect of immunity when seeking approaches to a quintessentially chronic brain disease, accumulating evidence affords ample data to support the target-rich cascade of innate immunity for the development of much-needed new diagnostics and therapeutics.
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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.003 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".