Cell contractility-induced mechanical stress triggers eIF2α-regulated translation during early adhesion of mesenchymal-like cells
Bibliographic record
Abstract
ABSTRACT Cellular invasion is a complex process that requires several interdependent biological mechanisms, which are initiated by changes in adhesion that establish a morphology favorable for migration. Hence, the regulation of adhesion potential is a rate-limiting step in metastasis. Our previous work revealed that de novo translation is necessary to regulate the adhesion of mesenchymal-like cells; however, the underlying translational regulatory mechanism and the identity of newly synthesized proteins needed for the adhesion process remain unidentified. Here, we identify a mechanotransduction pathway linking force-mediated protein unfolding to translational reprogramming via the activation of the integrated stress response (ISR). Specifically, we demonstrate that phosphorylation of eukaryotic translation initiation factor 2 alpha (eIF2α) during early adhesion events leads to selective translation of mRNAs encoding proteins critical for adhesion complex formation, mechanosensing, and contractility. These findings uncover a mechanosensitive translational control axis that links intracellular force generation to cell adhesion and stress adaptation, with implications for understanding mesenchymal cell adhesion and morphological behavior
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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".