Microglia in multiple sclerosis – pathogenesis and imaging
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
PURPOSE OF REVIEW: Microglia normally protects the central nervous system (CNS) against insults. However, their persistent activation in multiple sclerosis (MS) contributes to injury. Here, we review microglia activation in MS and their detection using positron emission tomography (PET). RECENT FINDINGS: During lesion evolution and the progression of MS, microglia activity may contribute to neurotoxicity through the release of pro-inflammatory cytokines, reactive oxidative species, proteases and glutamate. A means to detect and monitor microglia activation in individuals living with MS is provided by positron emission tomography (PET) imaging using the mitochondrial 18-kDa translocator protein (TSPO) ligand. TSPO PET imaging shows increased microglial activation within the normal appearing white matter that precedes radiological signs of neurodegeneration measured by T2 lesion enlargement. PET-detected microglia activation increases with progression of MS. These findings demand the use of CNS penetrant inhibitors that affect microglia. Such therapies may include hydroxychloroquine that is recently reported in a small study to reduce the expected progression in primary progressive MS, and Bruton's tyrosine kinase inhibitors for which there are now eleven Phase 3 registered trials in MS. SUMMARY: Microglial activation drives injury in MS. PET imaging with microglia-specific ligands offer new insights into progression of MS and as a monitor for treatment responses.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it