Regulation of Postnatal Forebrain Amoeboid Microglial Cell Proliferation and Development by the Transcription Factor Runx1
Bibliographic record
Abstract
Microglia are the immune cells of the nervous system, where they act as resident macrophages during inflammatory events underlying many neuropathological conditions. Microglia derive from primitive myeloid precursors that colonize the nervous system during embryonic development. In the postnatal brain, microglia are initially mitotic, rounded in shape (amoeboid), and phagocytically active. As brain development proceeds, they gradually undergo a transition to a surveillant nonphagocytic state characterized by a highly branched (ramified) morphology. This ramification process is almost recapitulated in reverse during the process of microglia activation in the adult brain, when surveillant microglia undergo a ramified-to-amoeboid morphological transformation and become phagocytic in response to injury or disease. Little is known about the mechanisms controlling amoeboid microglial cell proliferation, activation, and ramification during brain development, despite the critical role of these processes in the establishment of the adult microglia pool and their relevance to microglia activation in the adult brain. Here we show that the mouse transcription factor Runx1, a key regulator of myeloid cell proliferation and differentiation, is expressed in forebrain amoeboid microglia during the first two postnatal weeks. Runx1 expression is then downregulated in ramified microglia. Runx1 inhibits mouse amoeboid microglia proliferation and promotes progression to the ramified state. We show further that Runx1 expression is upregulated in microglia following nerve injury in the adult mouse nervous system. These findings provide insight into the regulation of postnatal microglia activation and maturation to the ramified state and have implications for microglia biology in the developing and injured brain.
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.
How this classification was reachedexpand
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 | 0.000 |
| 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".