ArticleGene2011
High content imaging-based assay to classify estrogen receptor-α ligands based on defined mechanistic outcomes.
Article in Gene, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
23 citing papers in PubMed, 35 citations in OpenAlex.
- A novel ERβ high throughput microscopy platform for testing endocrine disrupting chemicals.Heliyon · 2024Article
- Machine Learning Methods for Endocrine Disrupting Potential Identification Based on Single-Cell Data.Chemical engineering science · 2023Article
- Binary Classification of the Endocrine Disrupting Chemicals by Artificial Neural Networks.ESCAPE. European Symposium on Computer Aided Process Engineering · 2023Article
- Sensitive image-based chromatin binding assays using inducible ERα to rapidly characterize estrogenic chemicals and mixtures.iScience · 2022Article
- Quality Control for Single Cell Imaging Analytics Using Endocrine Disruptor-Induced Changes in Estrogen Receptor Expression.Environmental health perspectives · 2022Article
- Predicting the Estrogen Receptor Activity of Environmental Chemicals by Single-Cell Image Analysis and Data-driven Modeling.ESCAPE. European Symposium on Computer Aided Process Engineering · 2021Article
- Mitochondrial Epigenetics and Environmental Health: Making a Case for Endocrine Disrupting Chemicals.Toxicological sciences : an official journal of the Society of Toxicology · 2020Review
- Classification of estrogenic compounds by coupling high content analysis and machine learning algorithms.PLoS computational biology · 2020Article
- A Mechanistic High-Content Analysis Assay Using a Chimeric Androgen Receptor That Rapidly Characterizes Androgenic Chemicals.SLAS discovery : advancing life sciences R & D · 2020Article
- Evidence for Bisphenol B Endocrine Properties: Scientific and Regulatory Perspectives.Environmental health perspectives · 2019Review
- Leveraging Image-Derived Phenotypic Measurements for Drug-Target Interaction Predictions.Cancer informatics · 2019Article
- Characterizing properties of non-estrogenic substituted bisphenol analogs using high throughput microscopy and image analysis.PloS one · 2017Article
- High throughput microscopy identifies bisphenol AP, a bisphenol A analog, as a novel AR down-regulator.Oncotarget · 2016Article
- Use of HCA in subproteome-immunization and screening of hybridoma supernatants to define distinct antibody binding patterns.Methods (San Diego, Calif.) · 2016Article
- Differential Regulation of Progesterone Receptor-Mediated Transcription by CDK2 and DNA-PK.Molecular endocrinology (Baltimore, Md.) · 2016Article
- Article
- Defining estrogenic mechanisms of bisphenol A analogs through high throughput microscopy-based contextual assays.Chemistry & biology · 2014Article
- Inhibitors of SCF-Skp2/Cks1 E3 ligase block estrogen-induced growth stimulation and degradation of nuclear p27kip1: therapeutic potential for endometrial cancer.Endocrinology · 2013Article
- Profiling 976 ToxCast chemicals across 331 enzymatic and receptor signaling assays.Chemical research in toxicology · 2013Article
- Coactivators enable glucocorticoid receptor recruitment to fine-tune estrogen receptor transcriptional responses.Nucleic acids research · 2013Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors at 1 institution in 1 country.
Funding
Abstract
Estrogen receptor-α (ER) is an important target both for therapeutic compounds and endocrine disrupting chemicals (EDCs); however, the mechanisms involved in chemical modulation of regulating ER transcriptional activity are inadequately understood. Here, we report the development of a high content analysis-based assay to describe ER activity that uniquely exploits a microscopically visible multi-copy integration of an ER-regulated promoter. Through automated single-cell analyses, we simultaneously quantified promoter occupancy, recruitment of transcriptional cofactors and large-scale chromatin changes in response to a panel of ER ligands and EDCs. Image-derived multi-parametric data was used to classify a panel of ligand responses at high resolution. We propose this system as a novel technology providing new mechanistic insights into EDC activities in a manner useful for both basic mechanistic studies and drug testing.
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.