Author

T. M. El-Achkar

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Biology Disciplines

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Cell Biology· 2 Immunology· 1 Pathology· 1 Physiology· 1 Scientific Communication & Education· 1

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Research Focus:cell type annotation· 4 Approach:experimental assay· 4 Organism:human· 4 Assay:imaging· 3 Approach:deep learning· 2 Assay:fluorescence / live-cell microscopy· 2 Research Focus:batch correction / integration· 1 Research Focus:benchmarking· 1

Frequent Co-Authors

S. Winfree· 6 shared K. W. Dunn· 4 shared D. Barwinska· 3 shared M. T. Eadon· 3 shared S. Khochare· 3 shared J. E. Lingeman· 2 shared K. J. Kelly· 2 shared P. C. Dagher· 2 shared

Activity by Year

2019-2022 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 36 mutual co-author links

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6 shared papersCell Biology

S. Winfree

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6 papers

Recent·Most cited

DINAVID: A Distributed and Networked Image Analysis System for Volumetric Image Data

S. Han, A. Chen, S. Lee, C. Fu, C. Yang, L. Wu, S. Winfree, T. M. El-Achkar, K. W. Dunn, P. Salama, E. J. Delp

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

bioRxiv · May 11, 2022 · PreprintCell Biology

Integrated cytometry with machine learning applied to high-content imaging of human kidney tissue for in-situ cell classification and neighborhood analysis

S. Winfree, A. T. McNutt, S. Khochare, T. J. Borgard, D. Barwinska, A. R. Sabo, M. J. Ferkowicz, J. C. Williams, J. E. Lingeman, C. J. Gulbronson, K. J. Kelly, T. A. Sutton, P. C. Dagher, M. T. Eadon, K. W. Dunn, T. M. El-Achkar

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.

bioRxiv · Dec 27, 2021Physiology

The kidney protects against sepsis by producing systemic uromodulin

K. LaFavers, C. Hage, V. Gaur, R. Micanovic, T. Hato, S. Khan, S. Winfree, S. Doshi, R. Moorthi, H. Twigg, X.-R. Wu, P. Dagher, E. Srour, T. M. El-Achkar

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

bioRxiv · Jan 8, 2021Immunology

A Multimodal and Integrated Approach to Interrogate Human Kidney Biopsies with Rigor and Reproducibility: The Kidney Precision Medicine Project

T. M. El-Achkar, M. T. Eadon, R. Menon, B. B. Lake, T. K. Sigdel, T. Alexandrov, S. Parikh, G. Zhang, D. Dobi, K. W. Dunn, E. A. Otto, C. R. Anderton, J. M. Carson, J. Luo, C. Park, , For the Kidney Precision Medicine Project

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.

bioRxiv · Aug 23, 2020 · PreprintScientific Communication & Education

In situ classification of cell types in human kidney tissue using 3D nuclear staining

A. Woloshuk, S. Khochare, A. F. Almulhim, A. McNutt, D. Dean, D. Barwinska, M. Ferkowicz, M. T. Eadon, K. J. Kelly, K. W. Dunn, M. A. Hasan, T. M. El-Achkar, S. Winfree

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

bioRxiv · Jun 24, 2020Cell Biology

A precision medicine approach uncovers a unique signature of neutrophils in patients with brushite kidney stones

M. S. Makki, S. Winfree, J. E. Lingeman, F. A. Witzmann, E. M. Worcester, A. Krambeck, F. Coe, A. P. Evan, S. Bledsoe, K. Bergsland, S. Khochare, D. Barwinska, J. C. Willliams, T. M. El-Achkar

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.

bioRxiv · Nov 16, 2019Pathology