Mechanisms Underlying the Selection and Function of Macrophage-Specific Enhancers
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Macrophages populate every tissue of the body and play vital roles in homeostasis, pathogen elimination, and tissue healing. These cells possess the ability to adapt to a multitude of abruptly changing and complex environments. Furthermore, different populations of resident tissue macrophages each show their own defining gene signatures. The enhancer repertoire of these cells underlies both the cellular identity of a given subset of resident macrophage population and their ability to dynamically alter, in an efficient manner, their gene expression programs in response to internal and external signals. Notably, transcription is pervasive at active enhancers and enhancer RNAs, or eRNAs, are tightly correlated to regulated transcription of protein-coding genes. Furthermore, selection and establishment of enhancers is a dynamic and plastic process in which activation of intracellular signaling pathways by factors present in a macrophage's environment play a determining role. Here, we review recent studies providing insights into the distinct mechanisms that contribute to the selection and function of enhancers in macrophages and the relevance of studying these mechanisms to gain a better understanding of complex human diseases.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 it