GATA2 induces a stem cell–like transcriptional program in macrophages that promotes an atherogenic phenotype
Bibliographic record
Abstract
Atherosclerosis is a chronic inflammatory disease characterized by the accumulation of lipid-laden necrotic macrophages within blood vessels walls. GATA2 is a normally hematopoietic transcription factor which in the bone marrow helps maintain the proliferative, nondifferentiated phenotype of hematopoietic progenitors. Unexpectedly, GATA2 is upregulated in macrophages within atherosclerotic plaque, where it plays an unknown role in disease progression. Although GATA2 can be expressed from 2 promoters, we determined that the atherogenic stimuli oxidized low-density lipoprotein and tumor necrosis factor α induce GATA2 expression via the internal (IG) GATA2 promoter, with GATA2 transcription initiated by the transcription factors NF-κB, STAT1, and the aryl hydrocarbon receptor. GATA2 had a divergent effect on promoter activity, with GATA2 upregulating genes associated with stem cell maintenance, hematopoiesis, proliferation, reactive oxygen species production, and migration, while downregulating genes central to macrophage function including those for cholesterol efflux, pathogen phagocytosis, and the efferocytosis of apoptotic cells. Consequentially, GATA2-expressing macrophages had a proatherogenic phenotype typified by highly motile cells exhibiting poor cholesterol efflux and impaired phagocytosis and efferocytosis. These results indicate that GATA2 upregulation induces an immature, stem cell-like phenotype in atheroma macrophages, that may promote plaque cellularity while compromising atheroprotective mechanisms such as cholesterol clearance and apoptotic cell removal.
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.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".