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Record W3018962170

In vitro study of the impacts of exposure to mixtures of endocrine disrupting chemicals on the aryl hydrocarbon and steroid receptor transcriptional activity

2020· article· en· W3018962170 on OpenAlexfundno aff
Thi-Que Doan

Bibliographic record

VenueOpen Repository and Bibliography (University of Liège) · 2020
Typearticle
Languageen
FieldEnvironmental Science
TopicEffects and risks of endocrine disrupting chemicals
Canadian institutionsnot available
FundersH2020 Marie Skłodowska-Curie ActionsQueen's UniversityQueen's University BelfastEuropean CommissionEuropean Food Safety Authority
KeywordsAryl hydrocarbon receptorSteroidArylEndocrine systemChemistryIn vitroHydrocarbonBiochemistryOrganic chemistryHormoneTranscription factorGene
DOInot available

Abstract

fetched live from OpenAlex

Chemicals are undoubtedly important and beneficial for our modern life. As a result, we are exposed to mixtures of chemicals in our daily life through applying them for food production and preservation and for supporting human and animal health and recreation. However, risk assessment for the consumer is usually based on a chemical-by-chemical approach. Among these chemicals, endocrine disruptors (EDs) are of concern, in particular because they are able to alter the function(s) of the endocrine system, leading to adverse health effects in organism or (sub) population levels. In vitro Chemically Activated LUciferase gene eXpression (CALUX) assays involving several transgenic reporter cell lines are interesting tools to study the impacts of exposure to mixtures of EDs and their components on the transcriptional activity of the master xenobiotic receptor, which is the aryl hydrocarbon receptor (AhR), as well as the steroid (estrogen (ER), androgen (AR), progesterone (PR), and glucocorticoid (GR)) receptors. Three mixtures were being investigated as examples of compound groups of human everyday exposure to chemicals: (1) the “total POP mixture” consisting of 29 POPs (persistent organic pollutants) prevalent in Scandinavian human blood, (2) the “ED mixture” containing 18 potential EDs dominantly found in Wallonia raw water intended for drinking water production, and (3) the “polyphenol mixture” containing seven food-based polyphenols. The concentration of each component in the mixture was based on human-relevant exposure such as fold human blood level (the POP mixture), fold maximum quantified concentration in raw water (the ED mixture), or fold recommended intake dose from food supplements (the polyphenol mixture). Specific aims of the project were: (a) evaluating species (rat and human) and/or tissue-specific (hepatocytes and mammary gland) AhR responses to the POP mixture and the polyphenol mixture and their components, (b) profiling the endocrine disrupting activities of the EDs and the mixture thereof prevalent in raw water using AhR and steroid receptors, (c) identifying interactions among the chemicals (additive, antagonistic or synergic effects) on the transcriptional activity of the receptors, (d) identifying the actual chemical(s) the most active in the mixtures, and (e) predicting the effect of the mixtures based on the activity of single compounds. The results showed that 16 out of 29 POPs contaminating human blood were AhR antagonists. The total POP mixture also showed an AhR antagonistic activity although it contained each compound at the concentration below its lowest-observed-effect concentration (LOEC). Chlorinated compounds were the drivers of the activity of the total POP mixture, among which PCB-118 and PCB-138 contributed for 90% of the total POP mixture effect. From the 18 EDs prevalent in raw water, chlorpyrifos, bisphenol A, fluoranthene, phenanthrene, and benzo(a)pyrene demonstrated significant activities on several receptors. Noticeably, benzo(a)pyrene mixed with dioxin TCCD induced a synergistic response in AhR- i reporter human mammary gland cells (DR-T47-D), 10-fold higher than the cells’ response to TCDD alone, at a concentration which could be a realistic blood level after a food contamination incident or in a high exposed sub-population. The mixture of the 18 EDs compounds exerted AhR and ER agonistic activities, which can be explained by the activities of benzo(a)pyrene and bisphenol A in the mixture. While the rat AhR reporter cells (DR-H4IIE) was more sensitive to POP exposure, we showed for the first time that the AhR endogenous ligand FICZ, a tryptophan derivative was more potent than TCDD in the human AhR (DR- HepG2) (40 times more potent than TCDD) while both exhibited a similar potency in the rat cells (after 6h exposure). Two isoflavones (daidzein and genistein) induced a higher AhR agonistic/synergistic activity in the rat cells, while the others (a flavonol (quercetin) and two flavones (baicalin and chrysin), curcumin, and the mixture of the seven polyphenols) caused a stronger AhR antagonistic response in the human cells. Quercetin and resveratrol were the strongest AhR antagonists in the human cells, which contributed most for the antagonistic activity of the polyphenol mixture. Dose-response curves were predicted successfully by concentration addition and general concentration addition models for the POP mixture, while both concentration addition and independent action performed well for estimating the effect of the polyphenol mixture, indicating the additive activity of the components in these mixtures. The results suggested that the endocrine disrupting activities of chemicals in human daily life exposure could involve more than one mechanism: their (anta-) agonistic effects on different receptors with the potential for additive, inhibitory or synergistic effects of mixtures thereof should be considered in risk assessment.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.013
GPT teacher head0.259
Teacher spread0.247 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations0
Published2020
Admission routes1
Has abstractyes

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