Microglial functional alteration and increased diversity in the challenged brain: Insights into novel targets for intervention
Bibliographic record
Abstract
Microglia are the resident immune cells of the central nervous system (CNS) parenchyma, which perform beneficial physiological roles across life. These immune cells actively maintain CNS health by clearing toxic debris and removing dysfunctional or degenerating cells. They also modify the wiring of neuronal circuits, by acting on the formation, modification, and elimination of synapses-the connections between neurons. Microglia furthermore recently emerged as highly diverse cells comprising several structural and functional states, indicating a far more critical involvement in orchestrating brain development, plasticity, behaviour, and cognition. Various environmental factors, together with the individual genetic predispositions, confer an increased risk for neurodevelopmental and neuropsychiatric disorders, as well as neurodegenerative diseases that include autism spectrum disorders, schizophrenia, major depressive disorder, and Alzheimer's disease, across life. Microglia are highly sensitive to chronic psychological stress, inadequate diet, viral/bacterial infection, pollution, and insufficient or altered sleep, especially during critical developmental periods, but also throughout life. These environmental challenges can compromise microglial physiological functions, resulting notably in defective neuronal circuit wiring, altered brain functional connectivity, and the onset of behavioral deficits into adolescence, adulthood, and aging. This short review provides a historical and technical perspective, notably focused on my contribution to the field, on how environmental challenges affect microglia, particularly their physiological functions, and increase their diversity, which provides novel targets for intervention.
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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 | 0.001 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".