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Record W2050670566 · doi:10.1111/jne.12181

Long‐Term Effects of Early‐Life Exposure to Environmental Oestrogens on Ovarian Function: Role of Epigenetics

2014· review· en· W2050670566 on OpenAlexaff
Gonzalo Cruz, Warren G. Foster, Alfonso Paredes, Kun Yi, Mehmet Uzumcu

Bibliographic record

VenueJournal of Neuroendocrinology · 2014
Typereview
Languageen
FieldEnvironmental Science
TopicEffects and risks of endocrine disrupting chemicals
Canadian institutionsMcMaster University
FundersNational Institute of Environmental Health Sciences
KeywordsEpigeneticsInternal medicineEndocrinologyFunction (biology)OvaryTerm (time)MedicineBiologyPhysiologyGenetics

Abstract

fetched live from OpenAlex

Oestrogens play an important role in development and function of the brain and reproductive tract. Accordingly, it is considered that developmental exposure to environmental oestrogens can disrupt neural and reproductive tract development, potentially resulting in long-term alterations in neurobehaviour and reproductive function. Many chemicals have been shown to have oestrogenic activity, whereas others affect oestrogen production and turnover, resulting in the disruption of oestrogen signalling pathways. However, these mechanisms and the concentrations required to induce these effects cannot account for the myriad adverse effects of environmental toxicants on oestrogen-sensitive target tissues. Hence, alternative mechanisms are assumed to underlie the adverse effects documented in experimental animal models and thus could be important to human health. In this review, the epigenetic regulation of gene expression is explored as a potential target of environmental toxicants including oestrogenic chemicals. We suggest that toxicant-induced changes in epigenetic signatures are important mechanisms underlying the disruption of ovarian follicular development. In addition, we discuss how exposure to environmental oestrogens during early life can alter gene expression through effects on epigenetic control potentially leading to permanent changes in ovarian physiology.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.945
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.012
GPT teacher head0.307
Teacher spread0.295 · 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.

Study designOther design
Domainnot available
GenreReview

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

Citations41
Published2014
Admission routes1
Has abstractyes

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