Below is a podcast and transcript of the interview concerning the 1st chapter of the book Bifurquer
Abstract
Endocrine disruptors alter mammary gland development, impair the ability to nourish offspring, and increase the cancer risk in animal models. Epidemiological studies reveal trends towards early mammary development, nursing problems, and breast cancer in younger women. Morphological changes in mouse postnatal mammary gland development are considered sensitive markers of endocrine disruption. While the mouse mammary gland is easily amenable to morphometric measurements from the fetal stage to full maturity, the rat mammary gland grows more conspicuously into the third dimension, hindering conventional morphometric analysis. However, since rats are more commonly used in international toxicological reproductive studies, it would be beneficial to include mammary gland whole-mount analysis in these studies. Using our quantitative software to perform computer-driven analysis of the rat mammary epithelium we examined the effects of gestational and postnatal exposure to ketoconazole, an antifungal medication that affects steroidogenesis, and to the estrogen diethylstilbestrol in the mammary glands of 6- and 22-day-old females. Both treatments produced effects at both ages; the epithelium was smaller and less complex in exposed animals compared to controls. Global analysis with the permutation test showed that morphological evaluation of the PND22 mammary gland is sensitive to endocrine disruption and possibly non-monotonic. In addition to revealing that ketoconazole altered the mammary gland structure, these results suggest that for future toxicology studies, day 22 (at weaning) is more suitable than day 6 because it showed significant measurements and trends. If the collection of mammary glands is added to existing international test methods, PND22 could be a relevant time point.
We can and should take advantage of nonmonotonic properties to perform statistical analysis rigorously by new statistical and morphometric methods.
Abstract
We aimed to a) determine whether BPA showed effects on the developing rat mammary gland using new quantitative and established semiquantitative methods in two laboratories, b) develop a software tool for automatic evaluation of quantifiable aspects of the mammary ductal tree, and c) compare those methods. Conclusions: Both the semiquantitative and the quantitative methods revealed nonmonotonic effects of BPA. The quantitative unsupervised analysis used 91 measurements and produced the most striking nonmonotonic dose–response curves. At all time points, lower doses resulted in larger effects, consistent with the core study, which revealed a significant increase of mammary adenocarcinoma incidence in the stop-dose animals at the lowest BPA dose tested.
Software for Automated Morphological Analysis is a method by which epithelial structures grown in 3D cultures can be imaged, reconstructed and analyzed.
Abstract
Three-dimensional (3D) culture models are critical tools for understanding tissue morphogenesis. A key requirement for their analysis is the ability to reconstruct the tissue into computational models that allow quantitative evaluation of the formed structures. Here, we present Software for Automated Morphological Analysis (SAMA), a method by which epithelial structures grown in 3D cultures can be imaged, reconstructed and analyzed with minimum human intervention. SAMA allows quantitative analysis of key features of epithelial morphogenesis such as ductal elongation, branching and lumen formation that distinguish different hormonal treatments. SAMA is a user-friendly set of customized macros operated via FIJI (http://fiji.sc/Fiji), an open-source image analysis platform in combination with a set of functions in R (http://www.r-project.org/), an open-source program for statistical analysis. SAMA enables a rapid, exhaustive and quantitative 3D analysis of the shape of a population of structures in a 3D image. SAMA is cross-platform, licensed under the GPLv3 and available at http://montevil.theobio.org/content/sama.
Documentation for Software for Automated Morphological Analysis, a method by which epithelial structures grown in 3D cultures can be imaged, reconstructed and analyzed.
Abstract
Three-dimensional (3D) culture models are critical tools for understanding tissue morphogenesis. A key requirement for their analysis is the ability to reconstruct the tissue into computational models that allow quantitative evaluation of the formed structures. Here, we present Software for Automated Morphological Analysis (SAMA), a method by which epithelial structures grown in 3D cultures can be imaged, reconstructed and analyzed with minimum human intervention. SAMA allows quantitative analysis of key features of epithelial morphogenesis such as ductal elongation, branching and lumen formation that distinguish different hormonal treatments. SAMA is a user-friendly set of customized macros operated via FIJI (http://fiji.sc/Fiji), an open-source image analysis platform in combination with a set of functions in R (http://www.r-project.org/), an open-source program for statistical analysis. SAMA enables a rapid, exhaustive and quantitative 3D analysis of the shape of a population of structures in a 3D image. SAMA is cross-platform, licensed under the GPLv3 and available at http://montevil.theobio.org/content/sama.
