Monitoring paxillin in astrocytes reveals the significance of the adhesion G protein coupled receptor VLGR1/ADGRV1 for focal adhesion assembly
Bibliographic record
Abstract
VLGR1/ADGRV1 (very large G protein-coupled receptor-1) is the largest adhesion G protein-coupled receptor (aGPCR). Mutations in VLGR1/ADGRV1 are associated with human Usher syndrome, the most common form of deaf-blindness, and also with epilepsy in humans and mice. VLGR1 is expressed almost ubiquitously but is mainly found in the CNS and in the sensory cells of the eye and inner ear. Little is known about the pathogenesis of the diseases related to VLGR1. We previously identified VLGR1 as a vital component of focal adhesions (FAs) serving as a metabotropic mechanoreceptor controls cell spreading and migration. FAs are highly dynamic and turnover in response to internal and external signals. Here, we aimed to elucidate how VLGR1 participates in FA turnover. Nocodazole washouts and live cell imaging of paxillin-DsRed2 consistently showed that FA disassembly was not altered, but de novo assembly of FA was significantly delayed in Vlgr1-deficient astrocytes, indicating that VLGR1 is enrolled in FA assembly. In FRAP experiments, recovery rates were significantly reduced in Vlgr1-deficient FAs, indicating reduced turnover kinetics in VLGR1-deficient FAs. We showed that VLGR1 regulates cell migration by controlling the FA turnover during their assembly and expect novel insights into pathomechanisms related to pathogenic dysfunctions of VLGR1.
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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".