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Record W3135178773 · doi:10.1016/j.isci.2021.102283

Adhesion G protein-coupled receptor VLGR1/ADGRV1 regulates cell spreading and migration by mechanosensing at focal adhesions

2021· article· en· W3135178773 on OpenAlexfundno aff
Deva Krupakar Kusuluri, Baran E. Güler, Barbara Knapp, Nicola Horn, Karsten Boldt, Marius Ueffing, Gabriela Aust, Uwe Wolfrum

Bibliographic record

VenueiScience · 2021
Typearticle
Languageen
FieldMedicine
TopicCell Adhesion Molecules Research
Canadian institutionsnot available
FundersSixth Framework ProgrammeDeutsche ForschungsgemeinschaftFoundation Fighting Blindness
KeywordsHaploinsufficiencyInteractomeFocal adhesionCell biologyCell adhesionReceptorCell migrationBiologyProteomicsChemistryCellPhenotypeGeneticsSignal transduction

Abstract

fetched live from OpenAlex

VLGR1 (very large G protein-coupled receptor-1) is by far the largest adhesion G protein-coupled receptor in humans. Homozygous pathologic variants of VLGR1 cause hereditary deaf blindness in Usher syndrome 2C and haploinsufficiency of VLGR1 is associated with epilepsy. However, its molecular function remains elusive. Herein, we used affinity proteomics to identify many components of focal adhesions (FAs) in the VLGR1 interactome. VLGR1 is localized in FAs and assembles in FA protein complexes in situ . Depletion or loss of VLGR1 decreases the number and length of FAs in hTERT-RPE1 cells and in astrocytes of Vlgr1 mutant mice. VLGR1 depletion reduces cell spread and migration kinetics as well as the response to mechanical stretch characterizing VLGR1 as a metabotropic mechanosensor in FAs. Our data reveal a critical role of VLGR1 in the FA function and enlighten potential pathomechanisms in diseases related to VLGR1.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.001

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.

Opus teacher head0.017
GPT teacher head0.273
Teacher spread0.256 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations46
Published2021
Admission routes1
Has abstractyes

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