The Link Between Dysregulated Immunometabolism and Vascular Damage: Implications for the Development of Atherosclerosis in Systemic Lupus Erythematosus and Other Rheumatic Diseases
Bibliographic record
Abstract
A bimodal pattern of mortality in systemic lupus erythematosus (SLE) exists. Early-stage deaths are predominantly caused by infection, whereas later-stage deaths are mainly caused by atherosclerotic disease. Further, although SLE-related mortality has reduced considerably in recent years, cardiovascular (CV) events remain one of the leading causes of death in people with SLE. Accelerated atherosclerosis in SLE is attributed to both an increase in traditional CV risk factors and the inflammatory effects of SLE itself. Many of these changes occur within the microenvironment of the vascular-immune interface, the site of atherosclerotic plaque development. Here, an intimate interaction between endothelial cells, vascular smooth muscle cells, and immune cells dictates physiological vs pathological responses to a chronic type 1 interferon environment. Low-density neutrophils (LDNs) have also been implicated in eliciting vasculature-damaging effects at such lesion sites. These changes are thought to be governed by dysfunctional metabolism of immune cells in this niche due at least in part to the chronic induction of type 1 interferons. Understanding these novel pathophysiological mechanisms and metabolic pathways may unveil potential innovative pharmacological targets and therapeutic opportunities for atherosclerosis, as well as shed light on the development of premature atherosclerosis in patients with SLE who develop CV events.
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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 | 0.000 | 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".