Regulation of microglia function by neural stem cells
Bibliographic record
Abstract
Neural stem and precursor cells (NPCs) build and regenerate the central nervous system (CNS) by maintaining their pool (self-renewal) and differentiating into neurons, astrocytes, and oligodendrocytes (multipotency) throughout life. This has inspired research into pro-regenerative therapies that utilize transplantation of exogenous NPCs or recruitment of endogenous adult NPCs for CNS regeneration and repair. Recent advances in single-cell RNA sequencing and other "omics" have revealed that NPCs express not just traditional progenitor-related genes, but also genes involved in immune function. Here, we review how NPCs exert immunomodulatory function by regulating the biology of microglia, immune cells that are present in NPC niches and throughout the CNS. We discuss the role of transplanted and endogenous NPCs in regulating microglia fates, such as survival, proliferation, migration, phagocytosis and activation, in the developing, injured and degenerating CNS. We also provide a literature review on NPC-specific mediators that are responsible for modulating microglia biology. Our review highlights the immunomodulatory properties of NPCs and the significance of these findings in the context of designing pro-regenerative therapies for degenerating and diseased CNS.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".