Cadherins Mediate Intercellular Mechanical Signaling in Fibroblasts by Activation of Stretch-sensitive Calcium-permeable Channels
Bibliographic record
Abstract
Cells in mechanically active environments form extensive, cadherin-mediated intercellular junctions that are important in tissue remodeling and differentiation. Currently, it is unknown whether adherens junctions in connective tissue fibroblasts transmit mechanical signals and coordinate multicellular adaptations to physical forces. We hypothesized that cadherins mediate intercellular mechanotransduction by activating calcium-permeable, stretch-sensitive channels. Human gingival fibroblasts in suspension were plated on established homotypic monolayer cultures. The cells formed intercellular adherens junctions. Controlled mechanical forces were applied to intercellular junctions by electromagnets acting on cells containing internalized magnetite beads. At early but not later stages of intercellular attachment, force application visibly displaced magnetite bead-loaded cells and induced robust Ca(2+) transients (65 +/- 9.4 nm above base line). Similar Ca(2+) transients were induced by force application to anti-N-cadherin antibody-coated magnetite beads. Ca(2+) responses depended on influx of extracellular Ca(2+) through mechanosensitive channels because both Ca(2+) chelation and gadolinium chloride abolished the response and MnCl(2) quenched fura-2 fluorescence after force application. Force application induced accumulation of microinjected rhodamine-actin at intercellular contacts; actin assembly was inhibited by buffering intracellular calcium fluxes. Our results indicate that mechanical forces applied to adherens junctions activate stretch-sensitive calcium-permeable channels and increase actin polymerization. We suggest that N-cadherins in fibroblasts are intercellular mechanotransducers.
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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".