Transplantation

Evaluation of AI-Driven Automatic Segmentation Algorithms for Lung Shunt Fraction Estimation in 90Y-Labeled Microsphere Therapy.

90Y-labeled microsphere (90Y-microsphere) hepatic arterial radioembolization is a direct treatment for hepatic neoplasms. Before therapy, the fraction of 90Y-microspheres that may shunt past the liver to the lungs, or lung shunt fraction (LSF), is estimated using 99mTc-macroaggregated albumin. LSF is commonly estimated using regions of interest around the lungs and liver on planar images, a method...

Cigarette smoking and long-term incidence of colorectal cancer subclassified by tumor-infiltrating myeloid cells: A prospective cohort study.

Evidence indicates that cigarette smoking affects anti-tumor immunity. We tested a hypothesis that the association of smoking with long-term colorectal cancer (CRC) incidence might differ by myeloid cell infiltrates in tumors, which may play roles in cancer immune evasion. We utilized the prospective cohort incident-tumor biobank method on two longitudinal prospective cohort studies, namely the Nu...

Beyond HLA-Ia: A multidimensional framework for Neoantigen immunotherapy.

Glioblastoma (GBM) and other malignant gliomas are associated with aggressive progression, high recurrence rates, and poor long-term outcomes, while c...

Machine Learning Models Using Hospital Admission Characteristics Do Not Optimally Predict Nosocomial Infection Development in a Global Cirrhosis Cohort.

BACKGROUND: Nosocomial infections (NI) in cirrhosis are associated with high mortality but could be preventable. Logistic regression (LR) models have ...

The digital keystone: how artificial intelligence is reshaping HLA research and clinical practice.

DDA-BERT: end-to-end training for data-dependent acquisition mass spectrometry-based proteomics.

Peptide-spectrum match (PSM) rescoring is critical for accurate peptide identification in data-dependent acquisition (DDA)-based proteomics. Existing ...

Emerging multidimensional biomarker system for cardiovascular-kidney-metabolic syndrome: from multi-omics integration to clinical artificial intelligence.

Cardiovascular-kidney-metabolic (CKM) syndrome is an emerging clinical entity that highlights the complex, bidirectional interplay among cardiovascula...

A machine learning-driven framework integrating cell death and senescence signatures for multi-target drug design and immunotherapy optimization in ovarian cancer.

Ovarian cancer (OC) remains therapeutic challenge due to its complex molecular heterogeneity and therapy-induced adaptive resistance. While non-apopto...

Biological effects of ultrasonic cavitation in cancer therapy: from physics to mechanobiology.

The therapeutic efficacy of systemic treatments in cancer therapy is invariably limited by the biophysical barriers, including vascular endothelial ba...

A macrophage co-expression signature enables robust prognostic prediction in glioblastoma.

BACKGROUND: Glioblastoma (GBM) exhibits profound cellular heterogeneity and a highly immunosuppressive microenvironment in which tumor-associated macr...

Multi-stimuli and AI-guided electrically-responsive self-healing nanocomposites for low-temperature structural applications.

Self‑healing nanocomposites capable of operating under sub‑ambient aerospace conditions remain limited by slow reaction kinetics, single‑stimulus acti...

Delisting From Clinical Improvement in Liver Cirrhosis: A Machine Learning Decision Tree Analysis.

BACKGROUND: Following therapeutic advancements, recompensation has gained increasing recognition in patients on waitlist for liver transplantation (LT...

Applying microbial ecology frameworks to microbial therapies for wildlife.

Microbial ecology is increasingly incorporated into human and animal medicine via the study and purposeful manipulation of host-associated microbiomes...

Optimizing Ternary Preparation Parameters of Thin-Film Nanocomposite Membranes for Tailored Selectivity via Interpretable Machine Learning.

Novel thin-film nanocomposite (TFN) nanofiltration membranes have attracted wide attention for their generally boosted water permeability. However, th...

Time for a new category: "acute-on-chronic" hypertensive target organ damage.

INTRODUCTION: The aims of the paper are: 1) To analyze the evolution of understanding of hypertensive target organ damages (TODs)); 2) To see if the c...

Heterogeneity of depression and suicidal ideation among college students in Eastern China: a latent profile analysis and machine learning approach.

To investigate the heterogeneity of depression and suicidal ideation among Chinese college students and to examine the roles of family and individual ...

Predicting Expiration Among Potential Donation after Circulatory Death Donors at 30- and 120 Minutes Post Extubation.

PURPOSE: Many potential Donation After Circulatory Death (DCD) donors do not progress to circulatory death within meaningful timeframes, leading to wa...

Adapting the REVEAL Lite 2 score to the pediatric population through machine learning: insights from the REHIPED registry for pediatric pulmonary hypertension.

INTRODUCTION AND OBJECTIVES: Risk scores for pulmonary hypertension (PH) have been proven useful in adults. However, no risk score has been validated ...

Anatomically parameterised statistical shape modelling of LVAD-supported left ventricles for thrombosis risk assessment.

Heart failure remains a major global burden, and limited donor availability has made left ventricular assist devices (LVADs) a critical alternative. H...

Multi-modal machine learning highlights recipient genetic and clinical factors as primary drivers of post-transplant MASLD: A two-center study.