Pierre C. Dagher

The paper compares miRNA-mRNA profiles across human and murine AKI models to identify shared and specific molecular programs associated with different injury etiologies and biological heterogeneity.

This paper introduces STORM, a statistical framework for analyzing spatial patterns in multi-omics data, demonstrating reliable performance in detecting spatial structures and supporting study design decisions.

The paper introduces TubuleMAP, a semi-automated 3D tubule tracking pipeline for analyzing tubular networks, achieving high throughput and accuracy in reconstructing kidney and testis tubules.

The paper presents a multi-modal atlas of human kidney disease, identifying cellular and spatial mechanisms of injury resolution or failure and linking them to clinical outcomes.

This study shows cannabidiol increases T effector memory cells and has mixed inflammatory effects in humans.

This study identifies miRNA and mRNA signatures in human AKI tissue, revealing their roles in inflammation, immune activation, and epithelial-to-mesenchymal transition, and highlights the importance of using appropriate reference controls.

This study uses single-cell transcriptomics to analyze FGF23 bioactivity and identify novel inflammatory targets in the kidney, revealing interactions between FGF23 and TNF/NF-κB pathways.

The paper defines the chromatin landscape of healthy and injured kidney cells using multi-omics data, identifying regulatory elements and transcription factor networks involved in injury response.

This study identifies AZIN1 A-to-I editing as a marker of kidney recovery potential following inflammation.

The paper constructs a reference tissue atlas of the human kidney using multi-omics data to identify cell types, pathways, and genes across nephron segments and interstitium.

The paper identifies altered protein translation and carboxylic acid catabolism in diabetic kidney disease using human and mouse models.

The paper integrates spatial transcriptomics and single cell sequencing to identify immune and epithelial cell cross-talk patterns in acute kidney injury models.

This study uses single-cell RNA sequencing to define the temporal cellular and molecular changes in the kidney during sepsis, identifying key gene expression shifts and communication failures that mark critical points in the sepsis timeline.