This study focuses on characterizing mouse models of human disease.  While mitochondria play an important role in kidney pathology, the study explores the role of a Complex III gene mutation in renal tubular epithelial cell proliferation. Advanced automated image analysis techniques were employed in Python to quantify cell proliferation. Whole slide images (WSIs) of the kidney were first pre-processed through image tiling and contrast enhancement using Contrast Limited Adaptive Histogram Equalization (CLAHE). The pre-processing steps were followed by binarization and morphological operations for marker identification on the images.  Finally, a detailed marker analysis and data aggregation were used to quantify the number of Ki-67 marked cells.

 Despite methodological challenges, the preliminary findings of a small sample of mice suggested an increase in Ki-67-positive cells in Complex III-deficient mice. This contributes to a better understanding of kidney tubular morphology and mitochondrial impairment. The current approach not only speeds up the analysis process but also provides crucial support for pathologists in their diagnostic tasks in the field of genetic research.

Future research directions include refining the methodology by dividing the dataset into more homogeneous groups and defining specific thresholds for enhanced accuracy.