Force transduction and strain dynamics in actin stress fibres in response to nanonewton forces
Bibliographic record
Abstract
It is becoming clear that mechanical stimuli are crucial factors in regulating the biology of the cell, but the short-term structural response of a cell to mechanical forces remains relatively poorly understood. We mechanically stimulated cells transiently expressing actin-EGFP with controlled forces (0-20 nN) in order to investigate the structural response of the cell. Two clear force-dependent responses were observed: a short-term (seconds) local deformation of actin stress fibres and a long-term (minutes) force-induced remodelling of stress fibres at cell edges, far from the point of contact. By photobleaching markers along stress fibres we were also able to quantify strain dynamics occurring along the fibres throughout the cell. The results reveal that the cell exhibits complex heterogeneous negative and positive strain fluctuations along stress fibres in resting cells that indicate localized contraction and stretch dynamics. The application of mechanical force results in the activation of myosin contractile activity reflected in an ~50% increase in strain fluctuations. This approach has allowed us to directly observe the activation of myosin in response to mechanical force and the effects of cytoskeletal crosslinking on local deformation and strain dynamics. The results demonstrate that force application does not result in simplistic isotropic deformation of the cytoarchitecture, but rather a complex and localized response that is highly dependent on an intact microtubule network. Direct visualization of force-propagation and stress fibre strain dynamics have revealed several crucial phenomena that take place and ultimately govern the downstream response of a cell to a mechanical stimulus.
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 | 0.000 |
| 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".