ArticleEnvironmental science & technology2019
Method Development for Effect-Directed Analysis of Endocrine Disrupting Compounds in Human Amniotic Fluid.
Article in Environmental science & technology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 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
6 citing papers in PubMed, 28 citations in OpenAlex.
- Combination of Chromatographic and Machine Learning-Driven Virtual Fractionation Identifies Aryl Hydrocarbon Receptor Agonists in Sediments.Environmental science & technology · 2026Article
- Quantifying PFAS-Omics Burden Scores for Nontargeted Analysis Using Multidimensional Item Response Theory: An Exploratory Analysis of Novel and Legacy PFAS in Cord Blood.Environmental science & technology · 2026Article
- The effect of endocrine-disrupting chemicals on placental development.Frontiers in endocrinology · 2023Review
- The impact of microplastics on female reproduction and early life.Animal reproduction · 2023Article
- In vitro effects-based method and water quality screening model for use in pre- and post-distribution treated waters.The Science of the total environment · 2021Article
- Oestrogenic Endocrine Disruptors in the Placenta and the Fetus.International journal of molecular sciences · 2020Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The developing fetus represents a highly sensitive period of exposure to endocrine disrupting compounds (EDCs). However, risk assessment of EDCs is hampered by the lack of data on direct in utero exposure. In this study, we developed a robust analytical methodology for the identification of a wide range of known and unknown EDCs in full-term amniotic fluid (AF). First, a method for extraction and fractionation of a broad range of polar and nonpolar EDCs was developed and validated. Maximal recoveries of reference compounds and minimal interference from the matrix were achieved with a combination of solid phase extraction and dispersive liquid/liquid extraction. Bioassay analysis using cell-based reporter gene assays revealed estrogenic, androgenic, and dioxin-like activity in AF extract corresponding to 1.4 nmol EEQ/L, 76.6 pmol DHT-EQ/L, and 10.1 pmol TEQ/L, respectively. Targeted analysis revealed 13 xenobiotics, phytoestrogens, and endogenous hormones in the AF extract that partly contributed to the bioassay activity. Separation of the complex mixture of chemicals in the AF extract with reversed-phase chromatographic fractionation and subsequent bioassay analysis revealed activity in fractions over a wide range of polarity, indicating diverse (unidentified) substances with potential ED activity. The method developed here represents the first methodological step in an effect-directed analysis approach to identify unknown biologically active compounds in the fetal environment.
Indexed as
Identifiers
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.