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Updated: Mar 9, 2026
Supervised Machine Learning for Semi-Quantification of Extracellular DNA in Glomerulonephritis
Published on: June 18, 2020
Objective detection of apoptosis in rat renal tissue sections using light microscopy and free image analysis software
Nayana Damiani Macedo1, Aline Rodrigues Buzin1, Isabela Bastos Binotti Abreu de Araujo2
1Masters Program in Pharmaceutical Sciences, University Vila Velha, Vila Velha, ES, Brazil.
Objective:
The current study proposes an automated machine learning approach for the quantification of cells in cell death pathways according to DNA fragmentation.
Methods:
A total of 17 images of kidney histological slide samples from male Wistar rats were used. The slides were photographed using an Axio Zeiss Vert.A1 microscope with a 40x objective lens coupled with an Axio Cam MRC Zeiss camera and Zen 2012 software. The images were analyzed using CellProfiler (version 2.1.1) and CellProfiler Analyst open-source software.
Results:
Out of the 10,378 objects, 4970 (47,9%) were identified as TUNEL positive, and 5408 (52,1%) were identified as TUNEL negative. On average, the sensitivity and specificity values of the machine learning approach were 0.80 and 0.77, respectively.
Conclusion:
Image cytometry provides a quantitative analytical alternative to the more traditional qualitative methods more commonly used in studies.
