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Updated: Aug 28, 2025

Reliable and High Efficiency Extraction of Kidney Immune Cells

Reliable and High Efficiency Extraction of Kidney Immune Cells

Published on: August 19, 2016

Profiling Immune Cells in the Kidney Using Tissue Cytometry and Machine Learning.

Seth Winfree¹, Mohammad Al Hasan², Tarek M El-Achkar^1,3

¹Division of Nephrology, Department of Medicine, Indiana University, Indianapolis, Indiana.

|September 21, 2022

Summary

This summary is machine-generated.

Quantitative profiling of kidney immune cells using advanced tissue cytometry reveals unique nephro-ecosystems. This imaging-based approach enhances understanding of renal homeostasis and disease pathobiology.

Keywords:

AKI CKD basic science imaging immunology inflammation machine learning pathology renal physiology

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Last Updated: Aug 28, 2025

Reliable and High Efficiency Extraction of Kidney Immune Cells

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Published on: August 19, 2016

Supervised Machine Learning for Semi-Quantification of Extracellular DNA in Glomerulonephritis

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Isolation of Mouse Kidney-Resident CD8+ T cells for Flow Cytometry Analysis

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Published on: June 27, 2020

Area of Science:

Immunology
Nephrology
Bio-imaging

Background:

The kidney's immune cells are crucial for maintaining homeostasis and responding to injury.
Kidney microenvironments have unique immune cell distributions impacting function.
Quantitative analysis of immune cells in intact kidney tissue is essential for understanding health and disease.

Purpose of the Study:

To review advancements in kidney tissue cytometry for immune cell profiling.
To highlight the role of Volumetric Tissue Exploration and Analysis (VTEA) software.
To discuss the integration of machine learning in cytometry for enhanced data analysis.

Main Methods:

Multiplexed confocal imaging of intact kidney tissue.
Analysis using Volumetric Tissue Exploration and Analysis (VTEA) software.
Application of machine learning algorithms to imaging data.

Main Results:

Tissue cytometry provides a quantitative, imaging-based "omics" assessment of kidney immune cells.
VTEA software improves understanding of immune cell roles in renal pathobiology.
Machine learning enhances the analytic potential and unbiased exploration of multidimensional cytometry data.

Conclusions:

Tissue cytometry is transforming kidney research from qualitative to quantitative analysis.
Advanced imaging and machine learning offer powerful tools for immune cell profiling in the kidney.
This approach complements other molecular technologies for comprehensive renal interrogation.