Abstract 2427: Alterations in gene expression after exposure of MDA-MB-231 cells to isobutylparaben
Bibliographic record
Abstract
Abstract Parabens are a group of chemical compounds extensively used as preservatives in consumer products such as cosmetics, pharmaceuticals and processed food. Parabens have been shown to have endocrine disrupting properties, to accumulate in breast tissue and to increase the proliferation of hormone receptor positive breast cancer cell lines through competitive binding to the estrogen receptor. Studies have shown that isobutylparaben has the highest binding affinity for the aryl hydrocarbon receptor (AhR), reported to bind environmental toxins. This study examined the alterations in gene expression correlated to exposure of the hormone receptor negative breast cancer cell line MDA-MB-231 to isobutylparaben over a 72 hour time frame. Exposure of the cells to concentrations of isobutylparabens commonly found in consumer products alters the genetic expression profile of the cells. In our study, detectable expression levels of AhR mRNA decreased, while cytochrome P450 (CYP1A1) and receptor activator of NFκB ligand (RANKL) mRNA levels increased, as analyzed by qPCR. The downregulation of AhR and altered expression levels of invasion related genes is suggestive of an increased metastatic phenotype with exposure to isobutylparaben. Citation Format: Christine Strelchuk, Holly Jones Taggart. Alterations in gene expression after exposure of MDA-MB-231 cells to isobutylparaben [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 2427. doi:10.1158/1538-7445.AM2017-2427
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".