Transplantation

immuneKG: An Immune-Cell-Aware Knowledge Graph Framework for Target Discovery in Immune-Mediated Diseases

Biomedical knowledge graphs have emerged as foundational infrastructure for AI-driven drug discovery, yet their translational impact on novel target identification in immune-mediated diseases remains limited. Here we present immuneKG, a multimodal knowledge graph centred on autoimmune diseases, constructed through biologically meaningful feature reprogramming of disease nodes to enable deep mechan...

Combinatorial epigenomic patterns define regulatory programs underlying disease heterogeneity

Disease is a heterogeneous process that involves multiple organs and cell types. Understanding how genomic variation contributes to disease requires approaches that move beyond the linear assumptions of additive models and resolve underlying disease pathways. While genome-wide association studies have catalogued hundreds of thousands of genomic variants linked to disease, our understanding of thei...

Approaching human parity in the quality of automated organoid image segmentation

Organoids are complex, three dimensional, self-organizing cell cultures which manifest organ-like features and represent a powerful platform for study...

A generative reference grammar of healthy TCR repertoires reveals cancer-associated immune remodeling

T-cell receptor (TCR) repertoires encode the organization of adaptive immunity and its reshaping by cancer and therapy, but disentangling treatment-as...

Selfie-Capture Dynamics as an Auxiliary Signal Against Deepfakes and Injection Attacks for Mobile Identity Verification

Mobile remote identity verification (RIdV) systems are exposed to attacks that manipulate or replace the facial video stream, including presentation a...

SAMe: A Semantic Anatomy Mapping Engine for Robotic Ultrasound

Robotic ultrasound has advanced local image-driven control, contact regulation, and view optimization, yet current systems lack the anatomical underst...

DeepTaxon: An Interpretable Retrieval-Augmented Multimodal Framework for Unified Species Identification and Discovery

Identifying species in biology among tens of thousands of visually similar taxa while discovering unknown species in open-world environments remains a...

EXACT: an explainable anomaly-aware vision foundation model for analysis of 3D chest CT

Chest computed tomography (CT) is central to the detection and management of thoracic disease, yet the growing scale and complexity of volumetric imag...

Leveraging Spatial Transcriptomics as Alternative to Manual Annotations for Deep Learning-Based Nuclei Analysis

Deep learning-based nuclei segmentation and classification in pathology images typically rely on large-scale pixel-level manual annotations, which are...

Identity-Decoupled Anonymization for Visual Evidence in Multi-modal Retrieval-Augmented Generation

Multi-modal retrieval-augmented generation (MRAG) systems retrieve visual evidence from large image corpora to ground the responses of large multi-mod...

A Deep Learning-Based Scoring Framework for Large-Scale Multi-Donor Cardiotoxicity Screening

Cardiotoxicity remains a major cause of drug attrition and post-market withdrawal, yet the vast majority of environmental chemicals to which humans ma...

Semaglutide is associated with improved breast cancer survival, lower metastatic burden, and a dose-survival relationship uncoupled from weight-loss magnitude

Metabolic dysfunction is increasingly recognized as a risk factor for poor outcomes in breast cancer, but whether incretin-based therapies confer surv...

Housekeeping Gene Expression Normalization in Transcriptomics Mitigates Data Leakage in Machine Learning Models

Background: Inappropriate normalization can lead to data leakage and overfitting in machine learning models. Accurately identifying housekeeping genes...

SNPic: SNP Topic Modeling for Interpretable Clustering of Complex phenotypes

Genome-wide association studies (GWAS) have cataloged thousands of disease-associated variants, yet a central challenge remains: decoding the shared, ...

GRAFT: Geometric Refinement and Fitting Transformer for Human Scene Reconstruction

Reconstructing physically plausible 3D human-scene interactions (HSI) from a single image currently presents a trade-off: optimization based methods o...

Speculative Decoding for Autoregressive Video Generation

Autoregressive video diffusion is emerging as a promising paradigm for streaming video synthesis, with step distillation serving as the primary means ...

Protocol for LLM-Generated CONSORT Report for Increased Reporting: A Parallel-Arm Randomized Controlled Trial (Protocol)

Background Randomized controlled trials (RCTs) often have incomplete methods reporting despite widespread adoption of the CONSORT guideline. The edito...

PrivateBoost: Rethinking Federated Learning for Patient-Owned Medical Data: Learning from Single Records at Scale

The translation of artificial intelligence into clinical practice depends, in large part, on access to data that patients are understandably reluctant...

Multiscale transcriptomic organization of the human brain with DigitalBrain

The human brain varies across anatomical regions, cell types, development, ageing and disease states, yet existing single-cell transcriptomic resource...

A generative AI framework for disease-specific lung microtissue bioengineering

Generative Lung Architecture Modeling (GLAM) is an integrated bioengineering framework that couples high-resolution three-dimensional tissue imaging w...