Bibliographic record
Abstract
Cell adhesion responses to in-depth physical properties such as substrate roughness and topography are well described but little is known about the influence of lateral physical cues such as tissue boundaries on the function of adherent cells. Accordingly, we developed a model system to examine remote cell sensing of lateral boundaries. The model employs floating thin collagen gels supported by rigid grids of varying widths. The dynamics, lengths, and numbers of cell extensions were regulated by grid opening size, which in turn determined the distance of cells from rigid physical boundaries. In smaller grids (200 μm and 500 μm wide), cell-induced deformation fields extended to, and were resisted by, the grid boundaries. However, in larger grids (1700 μm wide), the deformation field did not extend to the grid boundaries, which strongly affected the mean length and number of cell extensions (∼60% reduction). The generation of cell extensions in collagen gels required expression of the β1 integrin, focal adhesion kinase and actomyosin activity. We conclude that the presence of physical boundaries interrupts the process of cell-mediated collagen compaction and fiber alignment in the collagen matrix and enhances the formation of cell extensions. This new cell culture platform provides a geometry that more closely approximates the native basement membrane and will help to elucidate the roles of cell extensions and lateral mechanosensing on extracellular matrix remodeling by invasion and degradation.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| 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 | 0.001 | 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 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".