Expression of MEK-1 in regulation of αV integrin and E-cadherin of MCF-7 breast cancer cells
Bibliographic record
Abstract
Purpose:Expression of MEK-1 was studied by regulating αV integrin and E-cadherin on MCF-7 breast cancer cells.Methods:Using cell transfected techniques site-mutated genes were inserted into MCF-7 cells and made MCF-7 cells containing MEK-1-GFP,Ala 222 MEK-1-GFP,Asp 222 MEK-1-GFP ,respectively. These cells were tested with immunoblot analysis and immunofluoresence technique to determined the change of MEK-1 expression and location of MEK-1 in cells.Results:Deactivated Ala 222 MEK-1-GFP inhibited the activity of MAPK,active Asp 222 MEK-1-GFP increased the activity of MAPK. Ala 222 MEK-1-GFP increased the expression of E-cadherin,did not increase the expression of αV integrin and inhibited FAK phosphorylation. MEK-1-GFP and Asp 222 MEK-1-GFP did not affect the expression of E-cadherin ,but upregulated the expression of αV integrin,increased FAK phosphorylation.Conclusions:MEK-1 regulated the expression of αV integrin and E-cadherin,FAK is the key factor that induced signal pathway of αV integrin. It is possible that MEK-1 regulated FAK phosphorglation by regulating expression of αV integrin and E-cadherin.
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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) | 0.000 | 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) | 0.001 | 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 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".