Transcriptional Regulation of Macrophages Polarization by MicroRNAs
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
Diversity and plasticity are the hallmarks of cells from the monocyte-macrophage lineage. Macrophages undergo classical M1 or alternative M2 activation in response to the microenvironment signals. Several transcription factors, such as peroxisome proliferator-activated receptors, signal transducers and activators of transcription, CCAAT-enhancer-binding proteins, interferon regulatory factors, Kruppel-like factors, GATA binding protein 3, nuclear transcription factor-κB, and c-MYC, were found to promote the expression of specific genes, which dictate the functional polarization of macrophages. Importantly, these transcription factors can be regulated by microRNAs (miRNAs), a group of small non-coding RNAs, which regulate gene expression through translation repression or mRNA degradation. Recent studies have also revealed that miRNAs control macrophage polarization by regulating transcription factors in response to the microenvironment signals. This review will summarize recent progress of miRNAs in the transcriptional regulation of macrophage polarization and provide the insights into the development of macrophage-centered diagnostic and therapeutic strategies.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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