ClinicalTrials.gov
public full text
Public Domain
Identification of Non Invasive Biomarkers of Immune Endothelial Injury and Repair Associated With Cardiac Allograft Vasculopathy
Heart transplantation is the best option for patients with end-stage heart failure. Cardiac allograft vasculopathy (CAV) is the leading cause of death following cardiac transplantation and is not managed by current therapies. Its pathogenesis traduces in an accelerated form of coronary artery disease (CAD) with similarities to atherosclerosis but also particular features of endothelial dysfunction associated to the alloimmune conflict and humoral responses toward the graft. Intravascular ultrasound (IVUS) is the validated invasive method for late CAV diagnosis, but occurs lesions are established. Identification of reliable non-invasive early endothelial injury biomarkers that reflect mechanisms of cardiac damage thus remain a major challenge to optimize therapeutic management of post transplant morbidity. Endothelial dysfunction is a central feature of both CAV and CAD and results from a desquilibrium in the balance of endothelial lesion and repair that is partly controlled by recipient immune system. Through their expression of receptors sensing antibodies (FcR CD16) and endothelial stress-induced signals (CX3CR1 fractalkine receptor and NKG2D MICA receptors), Natural Killer (NK) cells represent effector cells with unique potential to generate both humoral and innate immune injury of graft endothelium.
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- Biomarkers and Cardiac CT#893878
- Less Invasive Detection and Treatment of Very Early Coronary Artery Disease in Patients With Diabetes Mellitus#1164970
- Proteomics and Genomics Combined With CT to Predict CVD#876161
- Trustworthy, Integrated Artificial Intelligence Tools for Predicting High-risk CORonary PlaqueS#881477
- Physiologic Assessment of Microvascular Function in Heart Transplant Patients#863983
Record · ID 1114277
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive