Mechanically induced deformation and strain dynamics in actin stress fibers
Bibliographic record
Abstract
It is becoming evident that physical forces in the microenvironment play a key role in regulating many important aspects of cell biology. However, although mechanical cues are known to have clear effects over the long-term (days), the short-term (seconds to minutes) cellular responses to mechanical stimuli are less well characterized. In our recent study, we exposed committed fibroblast cells to well controlled nanoscale forces while simultaneously imaging force transduction through the actin cytoskeleton. One of the earliest responses of a cell to physical force is rapid deformation of the cytoskeleton, taking place over the course of seconds. We were able to directly visualize deformation, force-propagation and strain dynamics in actin stress fibers in response to a relatively simple mechanical stimulus. Moreover, these dynamics were also dependent on myosin-driven contractility and the presence of an intact microtubule cytoskeleton. Interestingly, although stem cells are sensitive to mechanical cues, they do not display the same degree of stress fiber organization as observed in committed cells indicating the possibility of alternative sensing and mechanotransduction mechanisms.
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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) | 0.000 | 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) | 0.001 | 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".