How Do Immune Cells Support and Shape the Brain in Health, Disease, and Aging?
Bibliographic record
Abstract
For decades, several axioms have prevailed with respect to the relationships between the CNS and circulating immune cells. Specifically, immune cell entry was largely considered to be pathological or to mark the beginning of pathology within the brain. Moreover, local inflammation associated with neurodegenerative diseases such Alzheimer's disease or amyotrophic lateral sclerosis, were considered similar in their etiology to inflammatory diseases, such as remitting relapsing-multiple sclerosis. The ensuing confusion reflected a lack of awareness that the etiology of the disease as well as the origin of the immune cells determines the nature of the inflammatory response, and that inflammation resolution is an active cellular process. The last two decades have seen a revolution in these prevailing dogmas, with a significant contribution made by the authors. Microglia and infiltrating monocyte-derived macrophages are now known to be functionally distinct and of separate origin. Innate and adaptive immune cells are now known to have protective/healing properties in the CNS, as long as their activity is regulated, and their recruitment is well controlled; their role is appreciated in maintenance of brain plasticity in health, aging, and chronic neurodevelopmental and neurodegenerative diseases. Moreover, it is now understood that the barriers of the brain are not uniform in their interactions with the circulating immune cells. The implications of these new findings to the basic understanding of CNS repair processes, brain aging, and a wide spectrum of CNS disorders, including acute injuries, Rett syndrome, Alzheimer's disease, and multiple sclerosis, will be discussed.
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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 | 0.001 | 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 | 0.001 | 0.004 |
| Scholarly communication | 0.004 | 0.006 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".