Organizing a tête-à -tête between cell adhesion molecules and extracellular proteases: a risky business that could lead to the survival of tumor cells
Bibliographic record
Abstract
Several membrane-bound molecules expressed at the surface of tumor cells have been shown to be released in a soluble form, thereby affecting cell-cell interactions by reduction of ligand densities. Moreover, since the binding domain of the soluble molecules often remains functional, proteolytic cleavage can also reduce the recognition of tumor cells by effector cells bearing the corresponding receptor. Proteolytic cleavage of cell adhesion molecules (CAMs) at the surface of stromal cells, most notably at the surface of vascular endothelial cells, can also limit the recruitment of effector cells at tumor sites. It is noteworthy that, in most cases, the signals that regulate the expression of extracellular proteases are mediated by the same adhesion molecules than those that are targeted by the proteases, suggesting that there is an intimate relationship between extracellular proteases and cell surface adhesion molecules. In this review, we will discuss the functional relationship between CAMs and proteases and how this may lead to tumor evasion.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".