Endogenous microglia regulate development of embryonic cortical precursor cells
Bibliographic record
Abstract
Microglia play important roles in the damaged or degenerating adult nervous system. However, the role of microglia in embryonic brain development is still largely uncharacterized. Here we show that microglia are present in regions of the developing brain that contain neural precursors from E11 onward. To determine whether these microglia are important for neural precursor maintenance or self-renewal, we cultured embryonic neural precursors from the cortex of PU.1(-/-) mice, which we show lack resident microglia during embryogenesis. Cell survival and neurogenesis were similar in cultures from PU.1(-/-) vs. PU.1(+/+) mice, but precursor proliferation and astrogenesis were both reduced. Cortical precursors depleted of microglia also displayed decreased precursor proliferation and astrogenesis, and these deficits could be rescued when microglia were added back to the cultures. Moreover, when the number of microglia present in cortical precursor cultures was increased above normal levels, astrogenesis but not neurogenesis was increased. Together these results demonstrate that microglia present within the embryonic neural precursor niche can regulate neural precursor development and suggest that alterations in microglial number as a consequence of genetic or pathological events could perturb neural development by directly affecting embryonic neural precursors.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".