Shalev Itzkovitz

The paper presents the Human Gut Cell Atlas v1.0, a unified reference of gut cell diversity, revealing how tissue structure influences cellular composition and enabling disease and organoid analysis.

The paper integrates multiple datasets to create a comprehensive human liver cell atlas, identifying new cell types and associations with demographic factors.

The paper identifies persistent stromal reprogramming in mucosal healing of ulcerative colitis and links it to therapeutic response prediction.

This study uses spatial transcriptomics to map subcellular mRNA localization across tissues, revealing conserved and tissue-specific patterns.

Spatial transcriptomics of live healthy donor livers shows most hepatocyte genes are zonated, with key functions pericentrally shifted versus mouse, pig, boar and cow.

The paper uses spatial transcriptomics to analyze thyroid heterogeneity, identifying a damage-response thyrocyte state that balances with hormone-producing states across scales.

This study uses spatial and single-cell transcriptomics to show that celiac disease alters enterocyte states by promoting aberrant zonal co-expression and metaplastic cells.

The paper identifies five discrete metabolic domains in the mouse and human small intestine using transcriptional signatures and machine learning, showing how diet influences domain properties.

This study creates a spatiotemporally resolved single-cell atlas of Plasmodium liver stage infection, revealing zone-specific parasite gene expression and immune responses in hepatocytes.

The paper identifies a subset of fetal enteroendocrine cells expressing insulin and beta cell genes, suggesting an extra-pancreatic source of beta cells.

The paper identifies bi-fated tendon-to-bone attachment cells regulated by shared enhancers and KLF transcription factors, revealing how these cells integrate chondrocyte and tenocyte features.

This study uses single-cell RNA-seq to show that many liver genes are both zonated and rhythmic, with multiplicative space-time effects, revealing spatio-temporal compartmentalization of liver function.

The paper uses spatial sorting to characterize liver zonation by analyzing transcriptomics, microRNA arrays, and proteomics data.

The paper reconstructs the spatial expression of enterocytes along the intestinal villus axis and identifies zonation patterns in gene expression.