A mechanobiological model of endothelial cell migration and proliferation
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
How angiogenesis is regulated by local environmental cues is still not fully understood despite its importance to many regenerative events. Although mechanics is known to influence angiogenesis, the specific cellular mechanisms influenced by mechanical loading are poorly understood. This study adopts a lattice-based modelling approach to simulate endothelial cell (EC) migration and proliferation in order to explore how mechanical stretch regulates their behaviour. The approach enables the explicit modelling of ECs and, in particular, their migration/proliferation (specifically, rate and directionality) in response to such mechanical cues. The model was first used to simulate previously reported experiments of EC migration and proliferation in an unloaded environment. Next, three potential effects (increased cell migration, increased cell proliferation and biased cellular migration) of mechanical stretch on EC behaviour were simulated using the model and the observed changes in cell population characteristics were compared to experimental findings. Combinations of these three potential drivers were also investigated. The model demonstrates that only by incorporating all three changes in cellular physiology (increased EC migration, increased EC proliferation and biased EC migration in the direction perpendicular to the applied strain) in response to dynamic loading, it is possible to successfully predict experimental findings. This provides support for the underlying model hypotheses for how mechanics regulates EC behaviour.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 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) | 0.000 | 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 it