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Record W4220924628 · doi:10.1073/pnas.2115308119

Bisphenol A replacement chemicals, BPF and BPS, induce protumorigenic changes in human mammary gland organoid morphology and proteome

2022· article· en· W4220924628 on OpenAlexfundno aff
Juliane Winkler, Pengyuan Liu, Kiet T. Phong, Johanna H. Hinrichs, Nassim Ataii, Katherine Williams, Elin Hadler‐Olsen, Susan L. Samson, Zev J. Gartner, Susan J. Fisher, Zena Werb

Bibliographic record

VenueProceedings of the National Academy of Sciences · 2022
Typearticle
Languageen
FieldEnvironmental Science
TopicEffects and risks of endocrine disrupting chemicals
Canadian institutionsnot available
FundersMcMaster UniversityCalifornia Breast Cancer Research ProgramDeutscher Akademischer AustauschdienstEuropean Molecular Biology Organization
KeywordsOrganoidBisphenol AHuman breastBisphenol SProteomeCell biologyHuman healthBisphenolBiologyChemistryComputational biologyBiochemistryMedicineBreast cancerCancerGenetics

Abstract

fetched live from OpenAlex

SignificanceBisphenol A (BPA), found in many plastic products, has weak estrogenic effects that can be harmful to human health. Thus, structurally related replacements-bisphenol S (BPS) and bisphenol F (BPF)-are coming into wider use with very few data about their biological activities. Here, we compared the effects of BPA, BPS, and BPF on human mammary organoids established from normal breast tissue. BPS disrupted organoid architecture and induced supernumerary branching. At a proteomic level, the bisphenols altered the abundance of common targets and those that were unique to each compound. The latter included proteins linked to tumor-promoting processes. These data highlighted the importance of testing the human health effects of replacements that are structurally related to chemicals of concern.

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)0.000
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 score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

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 science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.020
GPT teacher head0.317
Teacher spread0.298 · 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".

Quick stats

Citations61
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueProceedings of the National Academy of SciencesSame topicEffects and risks of endocrine disrupting chemicalsFrench-language works237,207