AIMC Topic: Graft Rejection

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Unveiling the intricate interplay: Exploring biological bridges between renal ischemia-reperfusion injury and T cell-mediated immune rejection in kidney transplantation.

PloS one
UNLABELLED: Although the link between ischemia-reperfusion injury (IRI) and T cell-mediated rejection (TCMR) in kidney transplantation (KT) is well known, the mechanism remains unclear. We investigated essential genes and biological processes involve...

Pediatric Liver Transplant Pathology: An Update and Practical Consideration.

Surgical pathology clinics
This review provides a summary of the diagnostic approach to pediatric liver transplantation (LT) pathology. It emphasizes the pathologic features of T-cell-mediated rejection, the most common finding on liver allograft biopsies, and discusses other ...

Deciphering the impact of senescence in kidney transplant rejection: An integrative machine learning and multi-omics analysis via bulk and single-cell RNA sequencing.

PloS one
BACKGROUND: The demographic shift towards an older population presents significant challenges for kidney transplantation (KTx), particularly due to the vulnerability of aged donor kidneys to ischemic damage, delayed graft function, and reduced graft ...

Machine learning methods to identify risk factors for corneal graft rejection in keratoconus.

Scientific reports
Machine learning can be used to identify risk factors associated with graft rejection after corneal transplantation for keratoconus. The study included all keratoconus eyes that underwent primary corneal transplantation from 1994 to 2021. Data relati...

Predicting graft survival in paediatric kidney transplant recipients using machine learning.

Pediatric nephrology (Berlin, Germany)
BACKGROUND: Identification of factors that affect graft survival in kidney transplantation can increase graft survival and reduce mortality. Artificial intelligence modelling enables impartial evaluation of clinician bias. This study aimed to examine...

APOD: A biomarker associated with oxidative stress in acute rejection of kidney transplants based on multiple machine learning algorithms and animal experimental validation.

Transplant immunology
BACKGROUND: Oxidative stress is an unavoidable process in kidney transplantation and is closely related to the development of acute rejection after kidney transplantation. This study aimed to investigate the biomarkers associated with oxidative stres...

Predicting graft and patient outcomes following kidney transplantation using interpretable machine learning models.

Scientific reports
The decision to accept a deceased donor organ offer for transplant, or wait for something potentially better in the future, can be challenging. Clinical decision support tools predicting transplant outcomes are lacking. This project uses interpretabl...

Deep learning-enabled classification of kidney allograft rejection on whole slide histopathologic images.

Frontiers in immunology
BACKGROUND: Diagnosis of kidney transplant rejection currently relies on manual histopathological assessment, which is subjective and susceptible to inter-observer variability, leading to limited reproducibility. We aim to develop a deep learning sys...