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S77 The G proteins Gαq/11 and Gα12/13 drive unique myofibroblast functions to promote pulmonary fibrosis

2021· article· en· W3121241785 on OpenAlexaff
Amanda Goodwin, Boris Hinz, Gísli Jenkins

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldMedicine
TopicInterstitial Lung Diseases and Idiopathic Pulmonary Fibrosis
Canadian institutionsUniversity of Toronto
FundersMedical Research Council
KeywordsMyofibroblastExtracellular matrixFibroblastFibrosisCell biologyMolecular biologyBiologyChemistryPathologyMedicineCell culture

Abstract

fetched live from OpenAlex

Introduction Idiopathic pulmonary fibrosis (IPF) is relentlessly progressive with a poor prognosis. In IPF, excessive scar tissue replaces normal lung parenchyma following alveolar injury. There is currently no treatment that can reverse fibrosis. Myofibroblasts drive fibrosis through contraction and extracellular matrix (ECM) generation. Increasing ECM stiffness promotes fibroblast-to-myofibroblast differentiation, ECM production, and activation of the profibrotic cytokine transforming growth factor-β (TGFβ). However, the precise mechanisms that drive this feedback loop are uncertain. Signalling by G protein coupled receptors (GPCRs) has been implicated in IPF. Messages from hundreds of GPCRs converges on four Gα subunit families, however the role of these molecules in myofibroblast activity in IPF is unknown. Aim Understand the role of Gαq/11 and Gα12/13 in profibrotic myofibroblast functions. Methods Wild-type (WT), Gnaq-/-;Gna11-/- (Gαq/11-/-), and Gna12-/-;Gna13-/- (Gα12/13-/-) murine embryonic fibroblasts (MEFs) and human lung fibroblasts (HLFs) were stimulated with lysophosphatidic acid (LPA, 50µM). TGFβ signalling was measured using Smad2 phosphorylation. MEFs were cultured on gels of fibrotic (100kPa, 36kPa) and physiological (5kPa) stiffness. Myofibroblast differentiation was assessed using α smooth muscle actin (αSMA) expression. MEFs and HLFs cultured on thin gels were stimulated with GPCR agonists (LPA 30µM, SFLLRN 20µM and TFLLRN 20µM), and time lapse images taken. Gel wrinkling was used to quantify contraction. Results Gαq/11 and Gα12/13 knockdown both reduced LPA-induced TGFβ signalling in MEFs and HLFs compared with controls (p<0.05, n=4). Rho-associated kinase (ROCK) inhibition reduced LPA-induced TGFβ signalling, suggesting that cellular contraction mediates LPA-induced TGFβ activation. HLFs from IPF donors were more contractile than non-diseased HLFs (91 vs 42 wrinkles/image, p=0.02, n=5 per group). MEFs and HLFs lacking Gα12/13 had reduced baseline and GPCR agonist-induced contraction (p<0.05), and Gα12/13-/- MEFs had abnormal cytoskeletal appearances on immunofluorescence. Gαq/11 knockdown did not affect contractility or cytoskeletal appearance. Gαq/11-/- MEFs had reduced αSMA expression when transferred to soft tissue culture conditions (p<0.05, n=4), whereas WT and Gα12/13-/- MEFs did not. Conclusions Myofibroblast activity is enhanced in IPF. Gαq/11 and Gα12/13 both mediate TGFβ signalling, but via different mechanisms, and they drive distinct myofibroblast profibrotic functions. A greater understanding of these processes could identify new treatments for IPF.

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 score0.012
Threshold uncertainty score0.039

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0120.003

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 head0.008
GPT teacher head0.233
Teacher spread0.224 · 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".

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Citations0
Published2021
Admission routes1
Has abstractyes

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