Transplantation

Single recipient cell tracking of tellurium-labeled extracellular vesicle proteomes (TeLEV) identifies EV-driven immunomodulation

Extracellular vesicles (EVs) mediate tumor-immune cell communication by carrying protein cargo that can immediately modulate signaling and antigen presentation. Yet mapping the uptake of primary EV proteomes by human immune cells at single-cell resolution has been constrained by a lack of labeling strategies. We show here that TeLEV, a tellurium-based metabolic mass tagging approach that incorpora...

ELITE: E3 Ligase Inference for Tissue specific Elimination: A LLM Based E3 Ligase Prediction System for Precise Targeted Protein Degradation

Targeted protein degradation (TPD) has transformed modern drug discovery by harnessing the ubiquitin–proteasome system to eliminate disease-driving proteins previously deemed undruggable. However, current approaches predominantly rely on a narrow set of ubiquitously expressed E3 ligases, such as Cereblon (CRBN) and Von Hippel–Lindau (VHL), which limits tissue specificity, increases systemic toxici...

A Computational Pipeline for Glioblastoma Vaccine Development: Integrating Novel Omics-Driven OIP5 Target Discovery to Create a Deep Learning-Based Immunogenicity Framework for Personalized Immunotherapy

This work introduces a modular, open-source computational pipeline for glioblastoma (GBM) vaccine design that integrates omics-based OIP5 target disco...

Quantitative profiling of millions of nucleotides reveals sequence-encoded interactions that govern plasmid propagation

Plasmids are central to modern biotechnology, especially therapeutic development, yet their propagation in Escherichia coli remains difficult to predi...

GPTAnno: Ontology-tree-guided hierarchical cell type annotation based on GPT models for single-cell data

Cell type annotation is critical for interpreting single-cell transcriptomic data but remains challenging due to uncertain cellular clustering granula...

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 ...

Biologically Inspired Digital Histology for Deep Phenotyping of Placental Composition Changes Across Major Lesion Types

Placenta pathology provides diagnostic insights for understanding pregnancy complications and guides maternal and perinatal care. While placental abno...

Asymmetric Cross-Reactivity of Nuclear Receptors Reveals an Evolutionary Buffer Between Estrogen and Androgen Signaling

A comprehensive all-by-all receptor ligand affinity screen using Boltz-2, a deep learning framework for protein-ligand interaction prediction, reveals...

Ensemble-DeepSets: an interpretable deep learning framework for single-cell resolution profiling of immunological aging

Immunological aging (immunosenescence) drives increased susceptibility to infections and reduced vaccine efficacy in elderly populations. Current bulk...

MFAID-Net: A Multi-modal Feature Fusion Deep Learning Network for Robust Adaptive Introgression Detection Across Diverse Evolutionary Scenarios

Adaptive introgression (AI), the beneficial genetic transfer between species, is key to adaptation, yet its genomic identification is challenging. Exi...

Limitations of the refolding pipeline for de novo protein design

With the emergence of powerful deep learning-based tools, computational protein design has become a widely accessible technique. Nowadays, it is possi...

A Generalizable Machine Learning Framework for cfDNA based Early Detection of Hepatocellular Carcinoma: a Feasibility Study with Preclinical Validation

Early detection of hepatocellular carcinoma (HCC) is critical for improving patient outcomes, yet current screening tools lack sensitivity and specifi...

Pseudodynamics+: Reconstructing Population Dynamics from Time-Resolved Single Cell Landscapes with Physics Informed Neural Networks

Single-cell profiling provides snapshots of the heterogeneous states that characterise developmental processes, organ regeneration and progression tow...

Probabilistic Modelling of Prime Editing Variant Correction Efficiency

Prime editing has emerged as a versatile genome editing, technology capable of installing precise genetic modifications without requiring double-stran...

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...

Identification of a type 1 diabetes-associated T cell receptor repertoire signature from the human peripheral blood

Type 1 Diabetes (T1D) is a T-cell mediated disease with a strong immunogenetic HLA dependence. HLA allelic influence on the T cell receptor (TCR) repe...

MUTATE: A Human Genetic Atlas of Multi-organ AI Endophenotypes using GWAS Summary Statistics

Artificial intelligence (AI) has been increasingly integrated into imaging genetics to provide intermediate phenotypes (i.e., endophenotypes) that bri...

XGBoost-Based Prediction of ICU Mortality in Sepsis-Associated Acute Kidney Injury Patients Using MIMIC-IV Database with Validation from eICU Database

Sepsis-Associated Acute Kidney Injury (SA-AKI) leads to high mortality in intensive care. This study develops machine learning models using the Medica...

RNAseq-Based Machine Learning Models for Prognostication of Multiple Myeloma

Multiple myeloma (MM) is characterized by abnormal plasma cell proliferation in the bone marrow, leading to symptoms like osteolytic lesions, anemia, ...

Multi-organ metabolome biological age implicates cardiometabolic conditions and mortality risk

Biological aging clocks across organs and omics data, including clinical phenotypes, neuroimaging, proteomics, and epigenetics, have proven instrument...