High-level expression of Egr-1 and Egr-1–inducible genes in mouse and human atherosclerosis
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
To understand the mRNA transcript profile in the human atherosclerotic lesion, RNA was prepared from the fibrous cap versus adjacent media of 13 patients undergoing carotid endarterectomy. cDNA expression arrays bearing 588 known genes indicated that lesions express unexpectedly high levels of the early growth response gene, Egr-1 (NGFI-A), a zinc-finger transcription factor that modulates a cluster of stress-responsive genes including PDGF and TGF-beta. Expression of Egr-1 was an average of 5-fold higher in the lesion than in the adjacent media, a result confirmed by RT-PCR, and many Egr-1-inducible genes were also strongly elevated in the lesion. Time-course analyses revealed that Egr-1 was not induced ex vivo. Immunocytochemistry indicated that Egr-1 was expressed prominently in the smooth muscle-actin positive cells, particularly in areas of macrophage infiltration, and in other cell types, including endothelial cells. Induction of atherosclerosis in LDL receptor-null mice by feeding them a high-fat diet resulted in a progressive increase in Egr-1 expression in the aorta. Thus, induction of Egr-1 by atherogenic factors may be a key step in coordinating the cellular events that result in vascular lesions.
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 | 0.001 | 0.001 |
| 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) | 0.000 | 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