Clive Henry Wasserfall

This paper develops a nanotherapy to reprogram antigen-presenting cells and induce T cell anergy, delaying type 1 diabetes onset in mice.

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.

The paper uses 3D imaging to analyze pancreatic islets in healthy and type 1 diabetes (T1D) individuals, finding that islet size and composition influence their loss in T1D.

The paper identifies a rare subset of CD4 and CD8 double positive T cells that form clusters with circulating tumor cells, promoting cancer metastasis through immune suppression and integrin-mediated interactions.

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 paper introduces a method for label-free single voxel proteomics using wcSOP, enabling spatial resolution of protein expression in tissue samples.

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.

The paper examines islet and acinar cell secretion in different pancreatic regions across diabetes stages, finding reduced insulin secretion and beta-cell volume in T1D with normal enzyme secretion.

The paper develops a statistical framework to estimate tissue spatial segregation, enabling optimal design of multiplexed imaging experiments by determining the necessary fields of view to capture all cell types.

The paper presents software tools and user interfaces for annotating and exploring tissue data in a human reference atlas, enabling data harmonization and public access.

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.

The paper compares metabolomic profiles of diabetic and healthy dogs to identify similarities with human type 1 diabetes.