Regulation of the Metastatic Process by E‐Selectin and Stress‐Activated Protein Kinase‐2/p38
Bibliographic record
Abstract
The formation of metastasis is a dreadful complication of cancer that is associated with a poor prognosis. Several clinical observations and experimental findings indicate that the metastatic process is nonrandom and involves a sequence of multistep events that may all be targeted for therapy. This includes angiogenesis of the primary neoplasm, release of malignant cells from this neoplasm, entry of cancer cells into the blood circulation, interaction of cancer cells with vascular endothelial cells in distant organs, and growth of blood-borne cancer cells locally in the vessels or distally following extravasation. Our working hypothesis is that metastatic cancer cells exploit the mechanisms of the inflammation process to successfully migrate into distant organs. This implies a pivotal role for specific adhesive interactions between cancer cells and vascular endothelial cells and activation of migratory pathways in the cancer cells. We review here the roles played by the endothelial adhesive molecule E-selectin and by the motogenic stress-activated protein kinase-2 (SAPK2/p38) pathway of cancer cells in modulating transendothelial migration of cancer cells.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.003 |
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".