Measuring mechanodynamics in an unsupported epithelial monolayer grown at an air–water interface
Bibliographic record
Abstract
Actomyosin contraction and relaxation in a monolayer is a fundamental biophysical process in development and homeostasis. Current methods used to characterize the mechanodynamics of monolayers often involve cells grown on solid supports such as glass or gels. The results of these studies are fundamentally influenced by these supporting structures. Here we describe a new method for measuring the mechanodynamics of epithelial monolayers by culturing cells at an air-liquid interface. These model monolayers are grown in the absence of any supporting structures, removing cell-substrate effects. This method's potential was evaluated by observing and quantifying the generation and release of internal stresses upon actomyosin contraction (800 ± 100 Pa) and relaxation (600 ± 100 Pa) in response to chemical treatments. Although unsupported monolayers exhibited clear major and minor strain axes, they were not correlated with nuclear alignment as observed when the monolayers were grown on soft deformable gels. It was also observed that both gels and glass substrates led to the promotion of long-range cell nuclei alignment not seen in the hanging-drop model. This new approach provides us with a picture of basal actomyosin mechanodynamics in a simplified system, allowing us to infer how the presence of a substrate affects contractility and long-range multicellular organization and dynamics.
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.
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) | 0.000 | 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 | 0.001 |
| 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 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".