E. John Wherry

The paper identifies persistently activated virus-specific CD8 T cells in long COVID patients, suggesting chronic antigen stimulation by SARS-CoV-2 or herpesvirus.

This study evaluates the limits of marker information transfer in cross-panel cytometry imputation, finding that imputation preserves broad lineage classification but not fine-phenotype details, and that patient matching improves cross-platform distribution recovery.

This study identifies brain-resident CD8+ T cells that regulate neuronal activity and behavior through interferon-gamma secretion, showing their role in maintaining brain homeostasis.

The paper identifies soluble sialic acid as a conserved biomarker of inflammation through metabolomics in mouse tissues and cultured macrophages.

CytoGate-Bench evaluates LLMs for cross-panel cell gating in cytometry by reformulating manual gating as a zero-shot task using expert-annotated data.

The paper shows that vaccine imprinting influences susceptibility to SARS-CoV-2 variants in children by linking immune history, antibody neutralization, and infection risk.

The paper develops MAESTRO, a self-supervised deep learning framework to transform immune profiles into embeddings capturing immune health, enabling clinical prediction and precision immunotherapy.

The paper introduces VLP-Open HLA nanoparticles for high-throughput T cell screening, enabling efficient peptide exchange and antigen-specific T cell activation.

This study shows fractalkine-conjugated mRNA-LNP can target and modify CD8+ T cells in vivo, enabling transient expression of proteins like IL-2 and CD62L.

The paper shows that a drug holiday during PD-1 blockade improves reinvigoration of exhausted T cells by restoring progenitor cell function and reducing adaptive resistance.

This study shows that intermittent WEE1 inhibition preserves T cell function and enhances immune control of HPV+ tumors through non-cell-autonomous immune activation mechanisms.

The paper develops a CRISPRi platform to annotate functional enhancers in human T cells, identifying novel CREs and their regulatory roles in immune responses.

This study uses multi-omic profiling to analyze immune cell dynamics in healthy adults over time, finding age-related transcriptional changes in T cells and impaired memory B cell responses in older adults.

This paper develops a microengineered platform to study CAR T cell therapy in human solid tumors, showing improved trafficking and effector function, and identifying therapeutic targets and biomarkers.

The paper designs novel cytokines by fusing computationally generated receptor-binding domains, identifying several that activate signaling pathways and have specific biological effects.

This paper designs synthetic cytokine agonists with controlled receptor geometry to modulate signaling outcomes and functional effects.

Cleanet detects and classifies doublets in cytometry data using protein expression patterns, improving accuracy over traditional bivariate gating methods.

The paper identifies TR-TEX cells as distinct from TRM cells, showing they have unique transcriptional regulation and respond differently to PD-1 inhibition.

This study shows BATF is essential for early chromatin remodeling and effector CD8+ T cell differentiation through its interaction with IRF4.

The paper evaluates proteomic and polygenic risk scores for disease prediction, finding proteomic scores outperform polygenic scores in most traits and show temporal responsiveness.

This study identifies how histone modifications regulate gene expression in memory and exhausted CD8 T cells, revealing distinct epigenetic programs between these cell types.

This paper introduces UNITO, a deep learning framework for automated cytometric gating that matches human performance and provides interpretable results without requiring manual input.

This study shows that targeting TET2 in CAR T-cells improves their anti-tumor responses by limiting terminal exhaustion and enhancing therapeutic potential.

The paper introduces cyMAE, a masked autoencoder for automated immunophenotyping, showing it improves accuracy and interpretability over manual methods in cytometry data analysis.

This study uses temporal multi-modal single-cell profiling to show CAR-T cells interact dynamically with glioblastoma cells, including antigen-negative ones, and reduce their proliferation through IFN-gamma.

Lamian is a statistical framework for analyzing pseudotime differences across multiple scRNA-seq samples, improving generalizability by accounting for sample variability.

The paper identifies lipidomic biomarkers and therapeutic targets in sepsis patients, including those with COVID-19, and develops an interactive network analysis tool for multiomic data exploration.

This paper introduces CellANOVA, a statistical model to recover biological signals lost during single-cell data integration by distinguishing batch effects from true biological variation.