Microglia protect against age-associated brain pathologies
Bibliographic record
Abstract
Microglia are brain-resident macrophages that contribute to central nervous system (CNS) development, maturation, and preservation. Here, we examine the consequences of permanent microglial deficiencies on brain aging using the Csf1r ΔFIRE/ΔFIRE mouse model. In juvenile Csf1r ΔFIRE/ΔFIRE mice, we show that microglia are dispensable for the transcriptomic maturation of other brain cell types. By contrast, with advancing age, pathologies accumulate in Csf1r ΔFIRE/ΔFIRE brains, macroglia become increasingly dysregulated, and white matter integrity declines, mimicking many pathological features of human CSF1R-related leukoencephalopathy. The thalamus is particularly vulnerable to neuropathological changes in the absence of microglia, with atrophy, neuron loss, vascular alterations, macroglial dysregulation, and severe tissue calcification. We show that populating Csf1r ΔFIRE/ΔFIRE brains with wild-type microglia protects against many of these pathological changes. Together with the accompanying study by Chadarevian and colleagues 1 , our results indicate that the lifelong absence of microglia results in an age-related neurodegenerative condition that can be counteracted via transplantation of healthy microglia.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".