The metabolic journey of microglia from early development to adulthood
Bibliographic record
Abstract
Microglia, the resident immune cells of the central nervous system (CNS), are vital for maintaining brain homeostasis during health and brain injury. Microglia exhibit diverse morphological adaptations across different brain regions and environmental cues, reflecting functional heterogeneity and regional differences. Although they comprise a smaller fraction of the total brain cells, microglia play critical roles in early brain development, which ranges from pruning weaker synapses to guiding neuronal responses, underscoring their importance in the formation of neural network as well as in the maintenance of CNS health. As bonafide brain-resident immune cells, they also partake in strong immune responses. We now recognize that different functional aspects of microglia are closely tied to changes in their metabolic requirements, which vary across different stages of development. However, a comprehensive coverage of microglial metabolism in light of its different roles in brain development remains limited. By examining the origins, colonization, and molecular signaling involved in early microgliogenesis and during adulthood, this review aims to highlight the significance of microglia metabolism in brain development. Additionally, the study investigates how metabolic changes during postnatal stages influence microglial activity, such as phagocytosis and neural sculpting, to maintain homeostasis. Exploring the metabolic profiles of microglia across their lifespan not only advances our understanding of brain homeostasis but also opens avenues for identifying metabolic pathways as potential therapeutic targets in neurodevelopmental and neurodegenerative diseases. This review contributes to the growing body of knowledge on microglial biology, emphasizing the need for further research into their metabolic regulation and its implications for CNS health.
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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) | 0.001 | 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 | 0.001 |
| 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".