Julian A. Abrams

This study develops a machine learning model using oral microbiome data to predict esophageal squamous cell carcinoma, showing good performance across different geographic regions.

The paper develops scG2P to jointly capture DNA mutations and mRNA transcripts in single cells, revealing clonal architectures and phenotypes in aged esophageal tissue.

This study shows colibactin-producing E. coli promote GEAC carcinogenesis by increasing proliferation, DNA damage, and cancer pathways, while also inducing autophagy and differentiation.

This paper develops SMART-PTA for single-cell whole-genome and transcriptome sequencing, revealing clonal evolution in aged human esophageal tissue over 70 years.

This study uses spatiotemporal single-cell analysis to track T cell clonal dynamics and phenotypic plasticity in GVHD, revealing links between TCR features, clonal expansion, and disease severity.

This study shows that high-fat diets promote GEAC by altering the microbiota-Bile Acid axis and inhibiting FXR, with FXR agonists like OCA slowing disease progression.

This study optimizes ADF-based medium for normal human esophageal organoids and models pathological changes using inflammatory and pharmacological stimuli.