The cytoskeleton as a smart composite material: A unified pathway linking microtubules, myosin-II filaments and integrin adhesions
Bibliographic record
Abstract
Abstract The interrelationship between microtubules and the actin cytoskeleton in mechanoregulation of integrin-mediated adhesions is poorly understood. Here, we show that the effects of microtubules on two major types of cell-matrix adhesions, focal adhesions and podosomes, are mediated by KANK family proteins connecting the adhesion protein talin with microtubule tips. Both total microtubule disruption and microtubule uncoupling from adhesions by manipulations with KANKs trigger a massive assembly of myosin-IIA filaments. Myosin-IIA filaments, augmenting the focal adhesions and disrupting the podosomes, are indispensable effectors in the microtubule-dependent regulation of integrin-mediated adhesions. Myosin-IIA filament assembly depends on Rho activation by the RhoGEF, GEF-H1, which is trapped by microtubules when they are connected with integrin-mediated adhesions via KANK proteins but released after their disconnection. Thus, microtubule capturing by integrin-mediated adhesions modulates the GEF-H1-dependent effect of microtubules on the myosin-IIA filaments. Subsequent actomyosin reorganization then remodels the focal adhesions and podosomes, closing the regulatory loop.
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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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".