Allograft Vasculopathy Versus Atherosclerosis
Bibliographic record
Abstract
Over the last 4 decades, heart transplantation (HTx) has evolved as a mainstream therapy for heart failure. Approximately half of patients needing HTx have organ failure consequent to atherosclerosis. Despite advances in immunosuppressive drugs, long-term success of HTx is limited by the development of a particular type of coronary atherosclerosis, referred to as cardiac allograft vasculopathy (CAV). Although the exact pathogenesis of CAV remains to be established, there is strong evidence that CAV involves immunologic mechanisms operating in a milieu of nonimmunologic risk factors. The immunologic events constitute the principal initiating stimuli, resulting in endothelial injury and dysfunction, altered endothelial permeability, with consequent myointimal hyperplasia and extracellular matrix synthesis. Lipid accumulation in allograft arteries is prominent, with lipoprotein entrapment in the subendothelial tissue, through interactions with proteoglycans. The apparent endothelial "intactness" in human coronary arteries of the transplanted heart suggest that permeability and function of the endothelial barrier altered. Various insults to the vascular bed result in vascular smooth muscle cell (SMC) activation. Activated SMCs migrate from the media into the intima, proliferate, and elaborate cytokines and extracellular matrix proteins, resulting in luminal narrowing and impaired vascular function. Arteriosclerosis is a broad term that is used to encompass all diseases that lead to arterial hardening, including native atherosclerosis, postangioplasty restenosis, vein bypass graft occlusion, and CAV. These diseases exhibit many similarities; however, they are distinct from one another in numerous ways as well. The present review summarizes the current understanding of the risk factors and the pathophysiological similarities and differences between CAV and atherosclerosis.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".