Effect Of 17β-Estrdiol On MCF-7 And MDA-MB-231 Cell Lines On EGFR Expression
Bibliographic record
Abstract
In comparison to non-users, OCP users had a substantially higher incidence of breast tumors classified as Luminal B, Progesterone Receptor+ (PR+), and ER+. When comparing OCP users to nonusers, the age at admission for ER+ cancer was significantly lower in the former group (45.3 years) than in the latter (52.2 years). Alternatively, compared to non-users (45.4 years), patients with basal (TNBC) cancer who were OCP users were older at the time of admission (53.1 years). Logistic analysis showed that compared to non-users, OCP users had an 18% greater risk of TNBC and an 8% lower risk of ER+, PR+, and Luminal B, respectively, with each additional year of age. The in-vitro investigation found that the MDA-MB-231 cell line, when treated with β-estradiol and then chased with Cycloheximide, had a decreased expression of EGFR. It seems that estrogen destroys EGFR via the ubiquitination route, as EGFR expression did not decrease under treatment with MG-132 and E2. There may be a correlation between OCP usage and an uptick in ER+, PR+, and Luminal B breast cancer cases. In fact, there is some evidence that OCP usage is associated with a slowed advancement of TNBC. Results from an in vitro experiment showed that estrogen ubiquitinates EGFR in MDA-MB-231 cells, destroying the protein.
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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) | 0.001 | 0.001 |
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".