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Record W4385629021 · doi:10.1016/j.envint.2023.108132

Estrogens and endocrine-disrupting chemicals differentially impact the bioenergetic fluxes of mammary epithelial cells in two- and three-dimensional models

2023· article· en· W4385629021 on OpenAlexafffund
Aurélie Lacouture, Yann Breton, Cindy Weidmann, S. Goulet, Lucas Germain, Martin Pelletier, Étienne Audet‐Walsh

Bibliographic record

VenueEnvironment International · 2023
Typearticle
Languageen
FieldEnvironmental Science
TopicEffects and risks of endocrine disrupting chemicals
Canadian institutionsCentre hospitalier de l'Université LavalUniversité Laval
FundersNatural Sciences and Engineering Research Council of CanadaCanada Foundation for InnovationFondation CHU de QuébecUniversité Laval
KeywordsEstrogen receptorOrganoidEstrogenMammary glandEndocrine systemBiologyCell biologyTranscriptomeBioenergeticsInternal medicineEndocrinologyChemistryHormoneGene expressionBiochemistryGeneMitochondrionMedicine

Abstract

fetched live from OpenAlex

Due to its sensitivity to hormonal signaling, the mammary gland is often referred to as a sentinel organ for the study of endocrine-disrupting chemicals (EDCs), environmental pollutants that can interfere with the estrogen signaling pathway and induce mammary developmental defects. If and how EDCs impact mammary epithelial cell metabolism has not yet been documented. Herein, to study how estrogens and EDCs modulate mammary gland metabolism, we performed bioenergetic flux analyses using mouse mammary epithelial organoids compared to cells grown in monolayer culture. Several EDCs were tested, including bisphenol A (BPA), its close derivative BPS, a new BPA replacement copolyester called TritanTM, and the herbicide glyphosate. We report that estrogens reprogrammed mammary epithelial cell metabolism differently when grown in two- and three-dimensional models. Specific EDCs were also demonstrated to alter bioenergetic fluxes, thus identifying a new potential adverse effect of these molecules. Notably, organoids were more sensitive to low EDC concentrations, highlighting them as a key model for screening the impact of various environmental pollutants. Mechanistically, transcriptomic analyses revealed that EDCs interfered with the regulation of estrogen target genes and the expression of metabolic genes in organoids. Furthermore, co-treatment with the anti-estrogen fulvestrant blocked these metabolic impacts of EDCs, suggesting that, at least partially, they act through modulation of the estrogen receptor activity. Finally, we demonstrate that mammary organoids can be used for long-term studies on EDC exposure to study alterations in organogenesis/morphogenesis and that past pregnancies can modulate the sensitivity of mammary epithelial organoids to specific EDCs. Overall, this study demonstrates that estrogens and EDCs modulate mammary epithelial cell metabolism in monolayer and organoid cultures. A better understanding of the metabolic impacts of EDCs will allow a better appreciation of their adverse effects on mammary gland development and function.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.608
Threshold uncertainty score0.494

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.010
GPT teacher head0.298
Teacher spread0.288 · 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 teacher head, 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".

Quick stats

Citations18
Published2023
Admission routes2
Has abstractyes

Explore more

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