Essential contributions of enhancer genomic regulatory elements to microglial cell identity and functions
Bibliographic record
Abstract
Microglia are the specialized macrophages of the brain and play essential roles in ensuring its proper functioning. Accumulating evidence suggests that these cells coordinate the inflammatory response that accompanies various clinical brain conditions, including neurodegenerative diseases and psychiatric disorders. Therefore, investigating the functions of these cells and how these are regulated have become important areas of research in neuroscience over the past decade. In this regards, recent efforts to characterize the epigenomic mechanisms underlying microglial gene transcription have provided significant insights into the mechanisms that control the ontogeny and the cellular competences of microglia. In particular, these studies have established that a substantial proportion of the microglial repertoire of promoter-distal genomic regulatory elements, or enhancers, is relatively specific to these cells compared to other tissue-resident macrophages. Notably, this specificity is under the regulation of factors present in the brain that modulate activity of target axes of signaling pathways-transcription factors in microglia. Thus, the microglial enhancer repertoire is highly responsive to perturbations in the cerebral tissue microenvironment and this responsiveness has profound implications on the activity of these cells in brain diseases. This article is categorized under: Physiology > Mammalian Physiology in Health and Disease Models of Systems Properties and Processes > Mechanistic Models Biological Mechanisms > Cell Fates Developmental Biology > Lineages.
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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 | 0.001 |
| 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 | 0.002 |
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".