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Record W4394683596 · doi:10.3390/cells13080664

Focal Adhesion’s Role in Cardiomyocytes Function: From Cardiomyogenesis to Mechanotransduction

2024· review· en· W4394683596 on OpenAlexaff
Simona Casarella, Federica Ferla, Dalila Di Francesco, Elena Canciani, Manuela Rizzi, Francesca Boccafoschi

Bibliographic record

VenueCells · 2024
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCellular Mechanics and Interactions
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsMechanotransductionFocal adhesionCell biologyPaxillinIntegrinVinculinExtracellular matrixCell adhesionCrosstalkSignal transductionPI3K/AKT/mTOR pathwayBiologyChemistryAdhesionCell

Abstract

fetched live from OpenAlex

Mechanotransduction refers to the ability of cells to sense mechanical stimuli and convert them into biochemical signals. In this context, the key players are focal adhesions (FAs): multiprotein complexes that link intracellular actin bundles and the extracellular matrix (ECM). FAs are involved in cellular adhesion, growth, differentiation, gene expression, migration, communication, force transmission, and contractility. Focal adhesion signaling molecules, including Focal Adhesion Kinase (FAK), integrins, vinculin, and paxillin, also play pivotal roles in cardiomyogenesis, impacting cell proliferation and heart tube looping. In fact, cardiomyocytes sense ECM stiffness through integrins, modulating signaling pathways like PI3K/AKT and Wnt/β-catenin. Moreover, FAK/Src complex activation mediates cardiac hypertrophic growth and survival signaling in response to mechanical loads. This review provides an overview of the molecular and mechanical mechanisms underlying the crosstalk between FAs and cardiac differentiation, as well as the role of FA-mediated mechanotransduction in guiding cardiac muscle responses to mechanical stimuli.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.961
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0000.001

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 head0.019
GPT teacher head0.281
Teacher spread0.262 · 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 teacher head, not a consensus.

Study designNot applicable
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

Citations29
Published2024
Admission routes1
Has abstractyes

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