Novel cryo-tomography workflow reveals nanometer-scale responses of epithelial cells to matrix stiffness and dimensionality
Bibliographic record
Abstract
Matrix stiffness and dimensionality have been shown to be major determinants of cell behavior. However, a workflow for examining nanometer-scale responses of the associated molecular machinery is not available. Here, we describe a comprehensive, quantitative workflow that permits the analysis of cells responding to mechanical and dimensionality cues in their native state at nanometer scale by cryogenic electron tomography. Using this approach, we quantified distinct cytoskeletal nanoarchitectures and vesicle phenotypes induced in human mammary epithelial cells in response to stiffness and dimensionality of reconstituted basement membrane. Our workflow closely recapitulates the microenvironment associated with acinar morphogenesis and identified distinct differences in situ at nanometer scale. Using drug treatment, we showed that molecular events and nanometer-scale rearrangements triggered by engagement of apical cell receptors with reconstituted basement membrane correspond to changes induced by reduction of cortical tension. Our approach is fully adaptable to any kind of stiffness regime, extracellular matrix composition, and drug treatment.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".