Age-impaired remyelination is associated with dysregulated microglial transitions
Bibliographic record
Abstract
Multiple sclerosis (MS) is a chronic, inflammatory condition characterized by neurodegeneration and lost myelin, or demyelination. This lost myelin may be regenerated in people with MS through a process called remyelination, that is prone to failure and is impaired with age. Remyelination is facilitated by microglia but our understanding of the microglial response during remyelination is incomplete. Here, we profile the microglial response during remyelination in the lysolecithin mouse model using single-cell RNA sequencing and find several distinct microglial states during the early stages of remyelination that coalesce into a resolved state defined by the presence of myelin transcripts, a state also present in MS brains. We also observe a delay in the appearance of several microglial states with age, in concordance with delayed remyelination. This multi-faceted microglial response during efficient remyelination provides the basis of multi-faceted microglia-specific targets for future MS therapies. Microglial states throughout remyelination are incompletely understood. Here, the authors show that microglia form several states during the early stages of remyelination that coalesce into a partially resolved state that is dysregulated with age.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".