Todd M. Brusko

This study generates hypoimmunogenic gastric insulin-secreting organoids (GINS) and shows PD-L1 engineering improves their survival under immune challenge.

This study uses spatial transcriptomics to identify inflammation signatures in pancreas and lymph node tissues of T1D patients, highlighting LTB and other genes involved in disease pathogenesis.

The paper identifies TCR subsequence motifs associated with type 1 diabetes using deep learning and shows their enrichment in T1D individuals based on HLA risk alleles.

TCR2HLA infers HLA genotypes from TCR repertoires, enabling identification of immunologically relevant metaclonotypes and discovery of HLA-associated TCRs.

This study shows that human stem cell-derived β-cells expressing a high-affinity CD155 variant reduce immune cell cytotoxicity, improving their potential for type 1 diabetes therapy.

This study shows OCA-B in T cells promotes ICI-induced autoimmunity but is not needed for anti-tumor immunity, suggesting it could be targeted to prevent autoimmunity without harming cancer treatments.

This study shows that ImmTAAI, a beta cell-targeted PD-1 agonist, inhibits T cell activity in human type 1 diabetes by increasing T cell motility and reducing cytokine secretion.

BayesCNet improves inference of cell type-specific regulatory networks by leveraging cell type hierarchy, outperforming existing methods, especially for rare cell types.

This study identifies aberrant immune regulation and stem-like CD8+ T cells in pancreatic lymph nodes during type 1 diabetes development using mass cytometry and single-cell RNA sequencing.

The paper analyzes immune cell changes in human pancreas-draining lymphatic tissues before and after T1D onset, identifying proinflammatory patterns and genetic risk correlations.

The paper uses imaging mass cytometry to analyze human pancreatic samples and identifies early β-cell dysfunction and immune changes in type 1 diabetes progression.

This study compares transcriptional profiles of memory T cells in infants and adults to identify age-specific regulatory mechanisms.

The paper introduces CRAWDAD, a tool for analyzing cell-type spatial relationships across scales in spatially resolved omics data, and demonstrates its application on simulated and real datasets.

This study shows that blocking CD226 reduces diabetes in NOD mice by enhancing Treg function and reducing effector T cell activity.

The paper introduces Escort, a framework to evaluate dataset suitability for trajectory inference and quantify trajectory properties, reducing analysis uncertainty through data-driven assessments.

geneBasis selects an optimal gene panel from scRNA-seq data by iteratively adding genes that maximize manifold distance, outperforming existing methods in resolving cell types and states.

immuneML provides an open-source ecosystem for reproducible and interoperable machine learning analysis of adaptive immune receptor repertoires, demonstrating its utility through benchmarking and novel methods.