The Benefits and Detriments of Macrophages/Microglia in Models of Multiple Sclerosis
Bibliographic record
Abstract
The central nervous system (CNS) is immune privileged with access to leukocytes being limited. In several neurological diseases, however, infiltration of immune cells from the periphery into the CNS is largely observed and accounts for the increased representation of macrophages within the CNS. In addition to extensive leukocyte infiltration, the activation of microglia is frequently observed. The functions of activated macrophages/microglia within the CNS are complex. In three animal models of multiple sclerosis (MS), namely, experimental autoimmune encephalomyelitis (EAE) and cuprizone- and lysolecithin-induced demyelination, there have been many reported detrimental roles associated with the involvement of macrophages and microglia. Such detriments include toxicity to neurons and oligodendrocyte precursor cells, release of proteases, release of inflammatory cytokines and free radicals, and recruitment and reactivation of T lymphocytes in the CNS. Many studies, however, have also reported beneficial roles of macrophages/microglia, including axon regenerative roles, assistance in promoting remyelination, clearance of inhibitory myelin debris, and the release of neurotrophic factors. This review will discuss the evidence supporting the detrimental and beneficial aspects of macrophages/microglia in models of MS, provide a discussion of the mechanisms underlying the dichotomous roles, and describe a few therapies in clinical use in MS that impinge on the activity of macrophages/microglia.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".