The same amount is not appropriate when testing for effects, as well as cancer and other diseases, of endocrine-disrupting chemicals (EDCs) or toxins, pointing to a number of factors. large, and estrogen receptor (ER). Most of the current review uses high-level experiments that focus on public observation and / or technical systems without considering phenotypic heterogeneity or cell-to-cell. cell-variability of endogenous receptors. Researchers at Baylor College of Medicine have developed a well -designed pipeline that involves looking at two images using the same different methods to evaluate chemical effects.
The findings, published in a recent issue of Community Life Ideasit was found that using this method, only a few EDCs occurred in the endogenous ER, which was not detected by the current trials.
“Most of the experiments currently used to determine the effects of EDCs in ERs do not consider individual cell responses in the cell population, and while this is an important factor, it is very few studies have tried those experiments, ”said Drs. Michael Mancini, senior author on the paper, is a professor of molecular and cellular biology and director of the Integrated Microscopy Core at Baylor. “When it comes to screening tools for most toxicology assays, people really want a single response or count from thousands to sometimes millions of phone calls. The phone is analyzed.”
Dr. Fabio Stossi, professor of molecular and cellular biology and lead author of the study, explained, “In this study we measured endogenous ER levels in thousands of cells to create an optimal pathway to to evaluate the reproducibility of cell-to-cell variation among populations.We measured cell-by-cell variability using imaging technologies to determine reproduction between populations. sources and variables, and then we have ways to measure transmission changes when you treat cells with EDCs.
Over the years, we have used this approach to create a pipeline and programs for others to use the powerful power of single -image experiments. “
To determine the accuracy of this approach, Stossi and his colleagues compared the results of several experiments currently used by the Environmental Protection Agency and the use of 42 alcohol substances. from the Agency for Toxic Substance and Disease Registry. These EDCs are common in the environment and are known to be associated with a number of diseases and other illnesses.
During the experiment, the researchers found that using this new method for single-cell image imaging, combined with current evidence, allows them to identify new EDCs. directly related to endogenous ER levels, an effect that affects the relationships between multiple pathways.
“We’ve seen a number of new drugs that directly or indirectly affect ER levels and performance,” Mancini said. “We were able to see a lot of heterogeneity and difference between similar cell populations that were previously thought to work the same way. We don’t have to get very accurate results. what our team has done is to make this image possible to see the most accurate results by using single-cell data across a large number of cells. “
Because this test site can be combined with most of the assays the government currently uses to test for intoxication, the next step is to look at other testers listed by the EDC. a variety of features and the use of innovative tools that support extensive research.
Other contributors to the research were Pankaj K. Singh, Ragini M. Mistry, Hannah L. Johnson, Radhika D. Dandekar, Maureen G. Mancini, Adam T. Szafran and Arvind U. Rao, as well as Baylor College. of Medicine, Texas A&M University or University of Michigan, Ann Arbor.
Recent research shows that transcription is stimulated by the estrogen receptor-α
Fabio Stossi et al, The Power of Single -Cell Image Disruption Using Endocrine Disruptor Modifications to Estrogen Receptor Expression, Community Life Ideas (2022). DOI: 10.1289 / EHP9297
Presented by Baylor College of Medicine
Directions: The company develops quality control for single cell imaging (2022, April 12) downloaded on 12 April 2022 from https://phys.org/news/2022-04-team-quality-cell-imaging .html
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