Transplant-associated arteriosclerosis remains an obstacle to long-term graft survival. To determine the contribution to transplant arteriosclerosis of MHC and adhesion molecules from cells of the donor vasculature, we allografted carotid artery loops from six mutant mouse strains into immunocompetent CBA/CaJ recipients. The donor mice were deficient in either MHC I molecules or MHC II molecules, both MHC I and MHC II molecules, the adhesion molecule P-selectin, intercellular adhesion molecule (ICAM)-1, or both P-selectin and ICAM-1. Donor arteries in which ICAM-1, MHC II, or both MHC I and MHC II were absent showed reductions in neointima formation of 52%, 33%, and 38%, respectively, due primarily to a reduction in smooth muscle cell (SMC) accumulation. In P-selectin–deficient donor arteries, neointima formation did not differ from that in controls. In donor arteries lacking both P-selectin and ICAM-1, the size of the neointima was similar to that in those lacking ICAM-1 alone. In contrast, neointima formation increased by 52% in MHC I–deficient donor arteries. The number of CD4-positive T cells increased by 2.8-fold in MHC I–deficient arteries, and that of α-actin–positive SMCs by twofold. These observations indicate that ICAM-1 and MHC II molecules expressed in the donor vessel wall may promote transplant-associated arteriosclerosis. MHC I molecules expressed in the donor may have a protective effect.
Chengwei Shi, Mark W. Feinberg, Dorothy Zhang, Anand Patel, Chang U. Sim, Zhao Ming Dong, Susan M. Chapman, Jose-Carlos Gutierrez-Ramos, Denisa D. Wagner, Nicholas E.S. Sibinga, Edgar Haber
Usage data is cumulative from March 2024 through March 2025.
Usage | JCI | PMC |
---|---|---|
Text version | 274 | 17 |
67 | 17 | |
Figure | 200 | 13 |
Table | 45 | 0 |
Citation downloads | 66 | 0 |
Totals | 652 | 47 |
Total Views | 699 |
Usage information is collected from two different sources: this site (JCI) and Pubmed Central (PMC). JCI information (compiled daily) shows human readership based on methods we employ to screen out robotic usage. PMC information (aggregated monthly) is also similarly screened of robotic usage.
Various methods are used to distinguish robotic usage. For example, Google automatically scans articles to add to its search index and identifies itself as robotic; other services might not clearly identify themselves as robotic, or they are new or unknown as robotic. Because this activity can be misinterpreted as human readership, data may be re-processed periodically to reflect an improved understanding of robotic activity. Because of these factors, readers should consider usage information illustrative but subject to change.