ECM dimensionality tunes actin tension to modulate the endoplasmic reticulum and spheroid phenotype
Bibliographic record
Abstract
Abstract Primary tissue organoids and cell spheroids recapitulate tissue physiology with remarkable fidelity. We investigated how engagement with a three dimensional laminin-rich extracellular matrix supports the polarized, stress resilient spheroid phenotype of mammary epithelial cells. Cells within a three dimensional laminin-rich extracellular matrix decreased and redistributed the actin crosslinker filamin to reduce their cortical actin tension. Cells with low cortical actin tension had increased plasma membrane protrusions that promoted negative plasma membrane curvature and fostered protein associations with the plasma membrane, consistent with efficient protein secretion. By contrast, cells engaging a laminin-rich extracellular matrix in two dimensions had high filamin-dependent cortical actin tension, exhibited compromised endoplasmic reticulum function including increased expression of PKR-like Endoplasmic Reticulum Kinase signaling effectors, and had compromised protein secretion. Cells with low filamin-mediated cortical actin tension and reduced endoplasmic reticulum stress response signaling secreted, and assembled, a polarized endogenous basement membrane and survived better, and their spheroids were more resistant to exogenous stress. The findings implicate filamin-dependent cortical actin tension in endoplasmic reticulum function and highlight a role for mechanics in organoid homeostasis.
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".