Allergy & Immunology

CART-GPT: A T Cell-Informed AI Linguistic Framework for Interpreting Neurotoxicity and Therapeutic Outcomes in CAR-T Therapy

Chimeric antigen receptor (CAR) T cell therapy holds transformative potential for hematologic malignancies, yet predicting patient-specific treatment efficacy and neurotoxicity remains a major clinical challenge due to the complex and heterogeneous nature of the infused CAR-T cell populations. Here, we introduce CART-GPT, a transformer-based model fine-tuned on a curated atlas of 1.12 million CAR-...

Rapid CE–MS with Real-Time Eco–AI Resolves Proteomic Heterogeneity Among Single Human Neutrophils

Single-cell proteomics by mass spectrometry is advancing rapidly, yet throughput and sensitivity remain limiting—particularly for small, protein-poor cell types such as neutrophils. As the most abundant circulating leukocytes in humans, neutrophils are central to immune defense and inflammation, but their proteomes comprehensive single-cell level characterization has only concurrently been reporte...

Reengineering the antigen optimization process for superior neoantigen vaccine design

Identifying effective neoantigen sequences is essential for enhancing anti-tumor immunity. However, the vast sequence space (>109 possible peptides) a...

BRAVE: a highly accurate method for predicting HIV-1 antibody resistance using large language models for proteins

Broadly neutralizing antibodies (bNAbs) that target the envelope glycoprotein (Env) of human immunodeficiency virus-1 (HIV-1) have been utilized in cl...

Antibody immunogenicity prediction and optimization with ImmunoSeq

Therapeutic antibody development faces persistent immunogenicity challenges from anti-drug antibodies (ADA). Identifying peptide fragments presented b...

The hidden predictors of human haematopoietic clonal fate

Human haematopoietic stem and progenitor cells (HSPCs) exhibit heterogeneous lineage output, but the molecular programs underlying clonal fate remain ...

Pocket-based molecule generation with an SE(3)-equivariant language model leads to a potent and selective HPK1 inhibitor with in vivo efficacy

Deep learning shows promise in structure-based drug discovery, yet challenges persist in generating pharmacologically plausible molecules with valid 3...

Translating clinical gene sequencing into a foundational representation of tumor subtype

While gene sequencing is routine in cancer care, translating sequences into treatment decisions remains a challenge. Here we introduce MutationProject...

SpaPheno: Linking Spatial Transcriptomics to Clinical Phenotypes with Interpretable Machine Learning

Linking spatial transcriptomic data to clinically relevant phenotypes is essential for advancing spatially informed precision oncology. Here, we prese...

BLMPred: predicting linear B-cell epitopes using pre-trained protein language models and machine learning

B-cells get activated through interaction with B-cell epitopes, a specific portion of the antigen. Identification of B-cell epitopes is crucial for a ...

Fourier transform infrared spectroscopy enables rapid species discrimination across Malassezia and strain-level typing in M. pachydermatis

Malassezia pachydermatis is a zoophilic yeast found on the skin and in the outer ear canal of many mammals. It normally maintains a commensal lifestyl...

Single-cell transcriptomics and machine learning reveal RNF144B and C5AR1 as immune-related biomarkers and therapeutic targets in myocardial infarction

Myocardial infarction (MI) is a life-threatening cardiovascular disease characterized by high morbidity and mortality. Although advances in clinical m...

T-SCAPE: T-cell Immunogenicity Scoring via Cross-domain Aided Predictive Engine

T-cell immunogenicity, the ability of peptide fragments to elicit T-cell responses, is a critical determinant of the safety and efficacy of protein th...

Accurate and scalable multi-disease classification from adaptive immune repertoires

Machine learning models trained on paratope-similarity networks have shown superior accuracy compared with clonotype-based models in binary disease cl...

Pocket Restraints Guided by B-Cell Epitope Prediction Improves Chai-1 Antibody-Antigen Structure Modeling

The accurate prediction of antibody-antigen (AbAg) complexes is a key challenge for computational immunology, with applications in therapeutic antibod...

Hollow-fibre biomanufacturing and cell-free engineering of HEK293 extracellular vesicles

Extracellular vesicles (EVs) are lipid-delineated nanoparticles that are produced by most cell types. EVs contain complex molecular cargoes that can h...

CDCA7 facilitates MET1-mediated CG DNA methylation maintenance in centromeric heterochromatin via histone H1

DNA methylation is a conserved epigenetic modification essential for maintaining genome stability. However, how methyltransferases maintain CG methyla...

Iterative improvement of deep learning models using synthetic regulatory genomics

Deep learning models can accurately reconstruct genome-wide epigenetic tracks from the reference genome sequence alone. But it is unclear what predict...

Tricked by Edge Cases: Can Current Approaches Lead to Accurate Prediction of T-Cell Specificity with Machine Learning?

The ability to predict T cell receptor (TCR) specificity from sequence could transform immunotherapy, vaccine development, and our understanding of im...

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 ...