AI Article Synopsis
- Chronic kidney disease (CKD) is a significant global health issue linked to high rates of illness and death, with fibrosis assessment being crucial in research using animal models.
- A newly developed pipeline using CellProfiler™ can streamline the analysis of kidney histology images stained with Masson's trichrome, allowing for the processing of multiple images at once, unlike traditional methods.
- When compared to ImageJ, the CellProfiler™ results for fibrosis quantification showed no significant differences, confirming its reliability and efficiency as an analytical tool in CKD research.
Article Abstract
Chronic kidney disease (CKD) is a common and worldwide health problem and one of the most important causes of morbidity and mortality. Most primary research on this disease requires evaluating the fibrosis index in animal model kidneys, specifically using Masson's trichrome stain. Different programs are used to calculate the percentage of fibrosis; however, the analysis is time-consuming since one image must be performed at a time. CellProfiler™ is a program designed to analyze data obtained from biological samples and can process multiple images through pipelines, and the results can be exported to databases. This article explains how CellProfiler™ can be used to automatically analyze kidney histology photomicrographs from samples stained with Masson's trichrome stain to assess the percentage of fibrosis in an experimental animal model of CKD. A pipeline was created to analyze Masson's trichrome-stained slides in a model of CDK induced by adenine at doses of 50 mg/kg and 100 mg/kg, in addition to samples with the vehicle (75% glycerin). The results were compared with those obtained by ImageJ, and no significant differences were found between both programs. The CellProfiler™ pipeline made here is a reliable, fast, and easy alternative for kidney fibrosis analysis and quantification in experimental animal models.
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| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9404825 | PMC |
| http://dx.doi.org/10.3390/biology11081227 | DOI Listing |
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