Immune dysregulation and lipid interactions in systemic lupus erythematosus-associated atherosclerosis: mechanisms and pathogenesis
Bibliographic record
Abstract
Atherosclerosis is increasingly recognized as a chronic inflammatory process, involving intricate interactions among the endothelium, lipids, coagulation system, and components of both the innate and adaptive immune systems. In the context of systemic lupus erythematosus (SLE), these interactions are even further disrupted, contributing to accelerated atherosclerosis. This narrative review explores how immune system dysregulation plays a central role in the development of atherosclerosis in SLE patients, where cardiovascular disease remains the leading cause of mortality despite recent advancements. We aim to present a model based on current scientific evidence that compares the immune mechanisms driving atherosclerosis in the general population with the accelerated form observed in SLE patients, highlighting the key immunological distinctions that set SLE-associated atherosclerosis apart. Particular emphasis was given to the interactions between interferon, lipid alterations and adaptive immunity as mediators of atherogenesis. This model may help identify gaps in our understanding and generate new hypotheses for potential therapeutic targets to modulate immune responses within atherosclerotic plaques.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".