Mouse Model of Alloimmune-induced Vascular Rejection and Transplant Arteriosclerosis
Bibliographic record
Abstract
Vascular rejection that leads to transplant arteriosclerosis (TA) is the leading representation of chronic heart transplant failure. In TA, the immune system of the recipient causes damage of the arterial wall and dysfunction of endothelial cells and smooth muscle cells. This triggers a pathological repair response that is characterized by intimal thickening and luminal occlusion. Understanding the mechanisms by which the immune system causes vasculature rejection and TA may inform the development of novel ways to manage graft failure. Here, we describe a mouse aortic interposition model that can be used to study the pathogenic mechanisms of vascular rejection and TA. The model involves grafting of an aortic segment from a donor animal into an allogeneic recipient. Rejection of the artery segment involves alloimmune reactions and results in arterial changes that resemble vascular rejection. The basic technical approach we describe can be used with different mouse strains and targeted interventions to answer specific questions related to vascular rejection and TA.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.004 |
| 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".