Transplantation

Vulnerability and short clinical outcomes in patients on the deceased-donor kidney transplant waiting list.

BACKGROUND: With prolonged waiting times for deceased-donor kidney transplantation (DDKT) in Japan, objective data on frailty among wait-listed patients are limited. We assessed frailty using body composition and nutritional measures to identify predictors of 1 year mortality or hospitalization. METHODS: We retrospectively analyzed 134 patients on the DDKT waiting list starting December 2023. Body...

Nanoengineering of non-aqueous liquid electrolyte solutions for future lithium metal batteries.

Research and development of non-aqueous electrolyte solutions are essential for practical advancement towards the production of high-energy lithium metal batteries (LMBs). An ideal LMB electrolyte solution should enable highly efficient, uniform and prolonged lithium metal plating and stripping, preserve the electrodes' electro(chemo)mechanical properties and ensure compatibility with all cell com...

Advances and Future Challenges in Monolithic 3D Integrated Logic, Power, and Optoelectronics Technologies for Tightly Interconnected Intelligent Systems.

The emergence of ultralarge-scale hardware systems for artificial intelligence is driving demand for high-performance heterogeneous integration. At th...

Identification of clinical phenotypes and disease trajectories in SLE using AI through a natural language processing framework.

OBJECTIVES: Electronic Health Records (EHRs) contain a wealth of unstructured patient data that can be leveraged using Artificial Intelligence (AI). T...

[Optogenetic reactivation of dormant cone photoreceptors].

Optogenetics enable the restoration of light sensitivity in various retinal cell types. In degenerated retinas, dormant cones whose cell bodies are in...

Ethical dilemmas in the use of artificial intelligence in transfusion medicine.

Artificial intelligence (AI) and machine learning (ML) are beginning to enhance key workflows across blood banking (BB) and transfusion medicine (TM),...

A novel AI-coupled flow chamber method quantifying erythrocyte osmotic fragility.

Osmotic fragility (OF) is widely used to evaluate red blood cell (RBC) membrane stability, water transport dynamics and hemoglobinopathies, traditiona...

Assessment and AI-Based Prediction of Complications in Reduction Mammoplasty: A Combined Statistical and Fuzzy Inference Approach in a 10-Year Cohort from Tehran Hospitals (2013-2023).

INTRODUCTION: Gigantomastia causes physical, psychological, and dermatological issues, often with ptosis; reduction mammoplasty effectively relieves s...

Identification and Validation of Liver Transplantation-Induced Acute Lung Injury Biomarkers Using a Bioinformatics and Experimental Approach.

BACKGROUND Acute lung injury (ALI) after liver transplantation (LT) is a critical complication negatively affecting transplant outcomes and patient su...

Advancements and challenges in CAR-NK cell therapy for cancer treatment.

Chimeric antigen receptor natural killer (CAR-NK) cell therapy is an emerging cancer treatment offering advantages over CAR-T therapy, including reduc...

The BIOPREVENT machine-learning algorithm predicts chronic graft-versus-host disease and mortality risk using posttransplant biomarkers.

BACKGROUNDChronic graft-versus-host disease (cGVHD) is a major contributor to nonrelapse mortality (NRM) following hematopoietic cell transplantation ...

A Flexible Hybrid Quantum-classical Training Framework of Organ-at-Risk and Tumor Segmentation Models for Radiation Therapy Planning.

Deep learning-based Organ-at-Risk (OAR) and tumor segmentation is vital for radiation therapy planning but often suffers from over-parameterization, r...

A multi-level segmentation-guided diffusion model for streak artifact reduction in routine non-contrast chest CT.

Streak artifacts in non-contrast computed tomography (NCCT) can obscure anatomical details and even confuse radiologic signs. Existing methods for art...

Automatic detection of single-electron regime and virtual gate definition in quantum dots using U-Net and clustering.

To realize practical quantum computers, a large number of quantum bits (qubits) will be required. Semiconductor spin qubits offer advantages such as h...

Construction of a deep learning-based predictive model for delayed graft function in kidney transplantation.

BACKGROUND: Delayed graft function (DGF) is a major complication of kidney transplantation that adversely affects long-term graft survival. This study...

Interpretable prognostic modeling of glioblastoma using cross-cohort transcriptome integration and machine learning approaches.

Glioblastoma (GBM) is an aggressive brain tumor with highly variable patient outcomes due to pronounced molecular heterogeneity. Prognosis remains dis...

Long-Term Follow-Up in Liver Transplantation and Combined Cardiac Surgery: Validation and Refinement of the LT+CS Risk Score Using Advanced Machine Learning.

BACKGROUND: Combined liver transplantation (LT) and cardiac surgery (LT+CS) is a therapeutic option for patients with end-stage liver disease (ESLD) a...

Explainability-informed benchmarking of two deep learning models for organ-at-risk segmentation in MR-guided adaptive radiotherapy.

INTRODUCTION/BACKGROUND: Segmentation of gastrointestinal (GI) organs-at-risk (OARs) is a critical yet time-consuming step in MR-guided adaptive radio...

Machine Learning-Assisted Detection of Phosgene and Acetyl Chloride via a Dual-Probe Fluorescent Platform with Differential Reactivity.

Phosgene and acyl chlorides are highly toxic chemicals that pose serious threats to human health and environmental safety, yet their rapid and reliabl...

Molecular fluorophore dimerization: a new paradigm for precision phototheranostics.

Molecular fluorophore dimerization has recently emerged as a powerful and versatile design strategy in phototheranostics, offering a distinct regulato...