T. M. El-Achkar

DINAVID provides a cloud-based system for remote 3D microscopy image analysis and visualization, designed to handle large datasets and improve accessibility.

The paper introduces VTEA, a software tool that integrates machine learning and cytometry analysis for high-content imaging of human kidney tissue to classify cells and analyze their spatial neighborhoods.

This paper identifies uromodulin (THP) as a protective factor in sepsis, showing its role in enhancing mononuclear phagocyte function and reducing mortality in mice.

The paper describes a pipeline for generating 3D molecular atlases of human kidney biopsies using multi-OMICS and imaging technologies, emphasizing quality control and reproducibility across institutions.

This paper develops a deep learning method using 3D nuclear staining to classify cell types in human kidney tissue without requiring specific markers.

This study identifies a unique neutrophil signature in brushite kidney stone formers through multi-omics analysis, linking increased neutrophil infiltration and NETosis to tissue scarring and inflammation.