Bibliographic record
Abstract
Macrophages play essential roles in tissue homeostasis, pathogen elimination, and tissue repair. A defining characteristic of these cells is their ability to efficiently adapt to a variety of abruptly changing and complex environments. This ability is intrinsically linked to a capacity to quickly alter their transcriptome, and this is tightly associated with the epigenomic organization of these cells and, in particular, their enhancer repertoire. Indeed, enhancers are genomic sites that serve as platforms for the integration of signaling pathways with the mechanisms that regulate mRNA transcription. Notably, transcription is pervasive at active enhancers and enhancer RNAs (eRNAs) are tightly coupled to regulated transcription of protein-coding genes. Furthermore, given that each cell type possesses a defining enhancer repertoire, studies on enhancers provide a powerful method to study how specialization of functions among the diverse macrophage subtypes may arise. Here, we review recent studies providing insights into the distinct mechanisms that contribute to the establishment of enhancers and their role in the regulation of transcription in macrophages.
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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 | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".