Igor Jurišica

This study identifies differentially expressed genes and microenvironmental changes in oral epithelial dysplasia using spatial transcriptomics, highlighting potential regulators of malignant transformation.

LENS decodes musculoskeletal pain intensity from sEMG, showing strong generalization to chronic pain cohorts and revealing a conserved pain signature masked by motor variability.

The paper develops a human peritoneal explant model to study gastric cancer implantation, identifies key genes like ADAM12, and shows their role in peritoneal metastasis.

This study shows that galectin-1 modulates cell adhesions, caveolae, and vascular permeability in kidney endothelial cells through proteomic and phosphoproteomic analyses.

This study shows Bigh3 is essential for lung fibrosis by demonstrating its role in fibroblast-macrophage interactions and collagen expression.

This study identifies a bidirectional OSMR-CLIC1 crosstalk that drives oncogenic pathways in glioblastoma and suggests targeting this interaction as a therapeutic strategy.

This study creates a cellular atlas of synovium in human and mouse knee osteoarthritis, identifying BHLHE40 as a key regulator of fibroblast activation and fibrosis.

This study uses multi-omic approaches to analyze cellular and transcriptomic diversity in infrapatellar fat pad during knee osteoarthritis, identifying fibroblasts as key contributors to disease-related differences.

This study uses proteomics to show that NEVKP preserves mitochondrial proteins and metabolic pathways in porcine kidneys, potentially improving graft function through PPAR-family transcription factors.

The paper uses proteomics to identify ECM injury in kidney allografts with early AMR, finding decreased ECM proteins and increased LGALS1 and GSTO1 in affected tissues.

The paper curates a dataset of physical molecular interactions between SARS-CoV-2, SARS-CoV-1, and other Coronaviridae proteins, providing a resource for studying virus-host interactions.

The paper presents a dataset of 28,000 annotations describing how amino acid mutations affect protein interactions, available through the IntAct website.