Dynamic cell–cell adhesion mediated by pericellular matrix interaction – a hypothesis
Bibliographic record
Abstract
Cell-cell adhesion strength, measured as tissue surface tension, spans an enormous 1000-fold range when different cell types are compared. However, the examination of basic mechanical principles of cell adhesion indicates that cadherin-based and related mechanisms are not able to promote the high-strength adhesion experimentally observed in many late embryonic or malignant tissues. Therefore, the hypothesis is explored that the interaction of the pericellular matrices of cells generates strong adhesion by a mechanism akin to the self-adhesion/self-healing of dynamically cross-linked hydrogels. Quantitative data from biofilm matrices support this model. The mechanism links tissue surface tension to pericellular matrix stiffness. Moreover, it explains the wide, matrix-filled spaces around cells in liquid-like, yet highly cohesive, tissues, and it rehabilitates aspects of the original interpretation of classical cell sorting experiments, as expressed in Steinberg's differential adhesion hypothesis: that quantitative differences in adhesion energies between cells are sufficient to drive sorting.
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".