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Record W4290653851 · doi:10.1152/ajpcell.00120.2022

The complicated lives of GPCRs in cardiac fibroblasts

2022· review· en· W4290653851 on OpenAlexafffund
Grace R. Mazarura, Juliana C.C. Dallagnol, David Chatenet, Bruce G. Allen, Terence E. Hébert

Bibliographic record

VenueAmerican Journal of Physiology-Cell Physiology · 2022
Typereview
Languageen
FieldMedicine
TopicCardiac Fibrosis and Remodeling
Canadian institutionsInstitut National de la Recherche ScientifiqueMontreal Heart InstituteMcGill University
FundersCanadian Institutes of Health ResearchNatural Sciences and Engineering Research Council of CanadaGovernment of Canada
KeywordsG protein-coupled receptorCell biologyReceptorStimulationBiologySignal transductionContractilityCellNeuroscienceEndocrinologyBiochemistry

Abstract

fetched live from OpenAlex

The role of different G protein-coupled receptors (GPCRs) in the cardiovascular system is well understood in cardiomyocytes and vascular smooth muscle cells (VSMCs). In the former, stimulation of Gs-coupled receptors leads to increases in contractility, whereas stimulation of Gq-coupled receptors modulates cellular survival and hypertrophic responses. In VSMCs, stimulation of GPCRs also modulates contractile and cell growth phenotypes. Here, we will focus on the relatively less well-studied effects of GPCRs in cardiac fibroblasts, focusing on key signaling events involved in the activation and differentiation of these cells. We also review the hierarchy of signaling events driving the fibrotic response and the communications between fibroblasts and other cells in the heart. We discuss how such events may be distinct depending on where the GPCRs and their associated signaling machinery are localized in these cells with an emphasis on nuclear membrane-localized receptors. Finally, we explore what such connections between the cell surface and nuclear GPCR signaling might mean for cardiac fibrosis.

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: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.002

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 head0.027
GPT teacher head0.307
Teacher spread0.281 · 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 designSystematic review
Domainnot available
GenreReview

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

Citations12
Published2022
Admission routes2
Has abstractyes

Explore more

Same venueAmerican Journal of Physiology-Cell PhysiologySame topicCardiac Fibrosis and RemodelingFrench-language works237,207