Heart Transplantation

Auto-MedCalc: Automated Biomarkers Discovery and Risk Score Generation with AI Agents

Identifying biomarkers and generating risk scores are usually essential tasks in many biomedicine and clinical scenarios. However, this is a highly hypothesis-driven and experience-dependent process requiring extensive experiments as well. How to discover biomarkers from multi-modality, multi-source data and generate risk scores with higher precision motivates us to design the framework Auto-MedCa...

Mapping and reprogramming human tissue microenvironments with MintFlow

Tissue microenvironments reprogram local cellular states in disease, yet current computational spatial methods remain descriptive and do not simulate tissue perturbation. We present MintFlow, a generative AI algorithm that learns how the tissue microenvironment influences cell states and predicts how tissue perturbations can reprogram them. Applied to three human diseases, MintFlow uncovered disti...

Machine-Learning-Assisted Exploration of High Entropy-Atom Nanozyme for Anti-Tumor Immunotherapy by Enhancing Enzyme Activity and Disrupting Dual Energy Metabolism

Despite its potential in cancer therapy, single-atom nanozyme (SAzyme) faces challenges like low atomic loading and rapid cancer metabolism. Here, a h...

Clinical and molecular characterisation of primary refractoriness to atezolizumab plus bevacizumab in patients with unresectable hepatocellular carcinoma

Despite improved outcomes with atezolizumab plus bevacizumab (A+B) in hepatocellular carcinoma (HCC), primary refractoriness (PRef), characterised by ...

Large vision model framework for automated C. elegans analysis: From static morphometry to dynamic neural activity

Quantitative phenotyping of Caenorhabditis elegans is essential across numerous fields, yet data extraction remains a significant analytical bottlenec...

Machine learning–driven decoding of maternal immune signatures in repeated pregnancy loss

Repeated pregnancy loss (RPL) is a multifactorial condition in which the underlying immunological mechanisms remain incompletely understood. Although ...

Integrated analysis implicates novel insights of NMB into lactate metabolism and immune response prediction in primary glioblastoma

Glioblastoma (GBM), the most aggressive primary brain tumor in adults, exhibits profound treatment resistance and poor prognosis. Despite advances in ...

Histology and spatial transcriptomic integration revealed infiltration zone with specific cell composition as a prognostic hotspot in glioblastoma

Glioblastoma (GBM), the most aggressive primary brain tumor, has a median survival of approximately 15 months. Twenty percent of patients survive beyo...

Integrated Cross-Organ Transcriptomic Analysis Uncovers Conserved Gene Signatures Predictive of Allograft Rejection

Long-term transplant success is limited by allograft rejection, a complex process traditionally studied on an organ-specific basis. To establish a uni...

ROSIE-Enabled Spatial Mapping Reveals Architectural Fragmentation and Immune Reprogramming in Lung Adenocarcinoma Evolution

The progression of lung adenocarcinoma (LUAD) from precancerous lesions to invasive carcinoma entails extensive remodeling of tissue architecture and ...

Large language models outperform traditional structured data-based approaches in identifying immunosuppressed patients

Identifying immunosuppressed patients using structured data can be challenging. Large language models effectively extract structured concepts from uns...

Plasma Cell-Free RNA Captures Immune Dynamics and Predicts GVHD after Hematopoietic Stem Cell Transplantation

Despite long-standing success of hematopoietic stem cell transplantation (HSCT) in the treatment of blood cancers and severe immune disorders, monitor...

PyHFO 2.0: An Open-Source Platform for Deep Learning–Based Clinical High-Frequency Oscillations Analysis

Accurate detection and classification of high-frequency oscillations (HFOs) in electroencephalography (EEG) recordings have become increasingly import...

Identification of cellular senescence-related gene IFNG as a potential biomarker in acute rejection after kidney transplantation via weighted gene co-expression network analysis and multiple machine learning

Kidney transplantation is the best option for the treatment of end-stage kidney disease (ESKD). Acute rejection (AR) episodes are a major determinant ...

High-resolution multiplexed antibody-omics and interpretable machine learning unveil novel pathogenic mechanisms in kidney transplant rejection

Antibody-mediated rejection (AbMR), driven by donor-specific alloantibodies (DSAs), is a major cause of late-stage kidney allograft failure, leading t...

Invisible Text Injection: The Trojan Horse of AI-Assisted Medical Peer Review

Are large language models robust against adversarial attacks in medical peer review? In this factorial experimental study, invisible text injection at...

Symbolic Regression for Mycophenolic Acid Dosage Prediction in Kidney Transplant Recipients

Chronic kidney disease (CKD) affects millions worldwide and often progresses to end-stage renal disease (ESRD), for which kidney transplantation remai...

Predicting Rejection Risk in Heart Transplantation: An Integrated Clinical–Histopathologic Framework for Personalized Post-Transplant Care

Cardiac allograft rejection (CAR) remains the leading cause of early graft failure after heart transplantation (HT). Current diagnostics, including hi...

Early Identification of High-Risk Individuals for Mortality after Lung Transplantation: A Retrospective Cohort Study with Topological Transformers

Lung transplantation remains the only definitive treatment for patients with end-stage respiratory failure; however, it is burdened by a substantial r...

Explainable machine learning on weighted connectivity networks across frequencies for outcome prediction in comatose patients

Accurate early prediction of neurological outcomes in comatose patients after cardiac arrest is critical for guiding therapeutic decisions and improvi...