Estrogen Receptor-β Mediates the Inhibition of DLD-1 Human Colon Adenocarcinoma Cells by Soy Isoflavones
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
To understand the relationship between the role of soy isoflavones and estrogen receptor (ER)-β in colon tumorigenesis, we investigated the cellular effects of soy isoflavones (composed of genistein, daidzein, and glycitein) in DLD-1 human colon adenocarcinoma cells with or without ER-β gene silencing by RNA interference (RNAi). Soy isoflavones decreased the expression of proliferating cell nuclear antigen (PCNA), extracellular signal-regulated kinase (ERK)-1/2, AKT, and nuclear factor (NF)-κB. Soy isoflavones dose-dependently caused G2/M cell cycle arrest and downregulated the expression of cyclin A. This was associated with inhibition of cyclin dependent kinase (CDK)-4 and up-regulation of its inhibitor p21(cip1) expressions. ER-β gene silencing lowered soy isoflavone-mediated suppression of cell viability and proliferation. ERK-1/2 and AKT expressions were unaltered and NF-κB was modestly upregulated by soy isoflavones after transient knockdown of ER-β expression. Soy isoflavone-mediated arrest of cells at G2/M phase and upregulation of p21(cip1) expression were not observed when ER-β gene was silenced. These findings suggest that maintaining the expression of ER-β is crucial in mediating the growth-suppressive effects of soy isoflavones against colon tumors. Thus upregulation of ER-β status by specific food-borne ER-ligands such as soy isoflavones could potentially be a dietary prevention or therapeutic strategy for colon cancer.
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.
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| 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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it