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Record W4393071678 · doi:10.1158/1538-7445.am2024-3575

Abstract 3575: The estrogenic endocrine disrupting compounds bisphenol-a (BPA) and alpha-zeranol (aZAL) induce early mammary hyperplasia in female ACI rats

2024· article· en· W4393071678 on OpenAlexaff
Cassandra Winz, Liu Ba, Caroline Xie, Shlok Rohatagi, Eric Li, Philip Furmanski, Nanjoo Suh

Bibliographic record

VenueCancer Research · 2024
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicEstrogen and related hormone effects
Canadian institutionsUniversity of New Brunswick
Fundersnot available
KeywordsZeranolEndocrine systemBisphenol AInternal medicineEndocrinologyMedicineAlpha (finance)HyperplasiaPhysiologyChemistryHormoneSurgery

Abstract

fetched live from OpenAlex

Abstract Endocrine disrupting compounds (EDCs) found in food-grade plastics, drinking water, and foodstuffs, pose a threat to human health. Estrogenic EDCs are capable of binding and activating the estrogen receptor (ER). Since breast tissue relies on estrogen signaling for growth and renewal, excessive estrogen stimulation is associated with breast cancer development. Breast cancer is a leading cause of cancer-related death in women. Only 5-10% of all breast cancer cases can be attributed to genetic causes, and the proportion of breast cancers of the luminal subtype are increasing in the United States for reasons unknown. Estrogenic EDCs may be able to initiate breast cancers through their estrogenic activities. The present study assessed two EDCs: the plasticizer bisphenol-A (BPA) and the mycotoxin alpha-zeranol (aZAL). To assess the estrogenic effects of these EDCs in an in vivo model, we utilized the ACI rat strain due to its sensitivity to estrogen-induced mammary carcinogenesis. The hypothesis of this work was that BPA and aZAL will induce mammary gland proliferation and estrogen signaling at early timepoints post-exposure. Estrogen, BPA, or aZAL were implanted into the backs of female ACI rats in silastic tubes at either a 9 gram doses. At a timepoint of 5 days post implantation, we saw no overt toxicity of our treatment. Both BPA and aZAL resulted in increased glandular proliferation and hyperplasia in a comparable manner to estrogen. Immunohistochemistry and qPCR revealed that the estrogen signaling marker progesterone receptor (PGR) was significantly upregulated in the estrogen, BPA, and aZAL treatment groups compared to control. The percent positivity of PGR staining in the mammary glands were 21.5% +/- 4.2%, 25.7% +/- 1.7%, 27.9% +/- 3.8%, and 8.18% +/- 2.5% respectively. Additionally, PCNA, a marker of cell proliferation, was significantly upregulated in the estrogen and aZAL treatment groups. The percent positivity of PCNA staining in the mammary glands were 7.67% +/- 2.56%, 49.6% +/- 5.2%, and 41.0% +/- 11.5% respectively. Additionally, the weight of the pituitary gland, an estrogen-sensitive endocrine organ, significantly increased in both the estrogen and aZAL treatment groups. Overall, this study demonstrated that the estrogenic EDCs BPA and aZAL induced mammary gland proliferation and hyperplasia in a comparable manner to estrogen. This is concerning due to the routine detection of these two compounds in human biosamples. More information is needed to assess the risk of exposure to these compounds as it pertains to breast cancer and other hormonal cancers. Citation Format: Cassandra Winz, Ba Liu, Caroline Xie, Shlok Rohatagi, Eric Li, Philip Furmanski, Nanjoo Suh. The estrogenic endocrine disrupting compounds bisphenol-a (BPA) and alpha-zeranol (aZAL) induce early mammary hyperplasia in female ACI rats [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 3575.

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 score0.004
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.032
GPT teacher head0.362
Teacher spread0.329 · 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

Citations0
Published2024
Admission routes1
Has abstractyes

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