Regulation of heparin-binding EGF-like growth factor expression in Ha-ras transformed human Mammary epithelial cells
Bibliographic record
Abstract
Heparin-binding epidermal growth factor-like growth factor (HB-EGF) mRNA and protein expression is induced by EGF in MCF-10A nontransformed and Ha-ras transfected human mammary epithelial cells. The anti-EGF receptor (EGFR) blocking monoclonal antibody (MAb) 225 and the EGFR tyrosine kinase inhibitor PD153035 were able to inhibit the induction of HB-EGF mRNA levels in MCF-10A cells. However, the Ha-ras transformed MCF-10A cells were more refractory to inhibition by these agents and only a combination of the 225 MAb and PD153035 was able to significantly abrogate HB-EGF induction by EGF. The anti-erbB2 MAb L26 which interferes with heterodimer formation was able to block HB-EGF induction in response to EGF in MCF-10A cells and in the Ha-ras transformed cells only when used in combination with either the 225 MAb or PD153035. The MEK inhibitor PD90859 completely blocked EGF induction of HB-EGF mRNA levels in the nontransformed and Ha-ras transformed MCF-10A cells, which indicates that MAPK is involved in the signaling pathway of HB-EGF induction by EGF. An increase in the levels of HB-EGF may, therefore, be an important contributor to oncogenic transformation that is caused by Ha-ras overexpression in mammary epithelial cells. J. Cell. Physiol. 186:233-242, 2001. Published 2001 Wiley-Liss, Inc.
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 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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".