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Record W7162197060 · doi:10.82308/6382

G protein-coupled receptor-mediated transcriptional regulation in pathological cardiac remodelling

2020· dissertation· en· W7162197060 on OpenAlexaboutno aff
Ryan Martin

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicReceptor Mechanisms and Signaling
Canadian institutionsnot available
Fundersnot available
KeywordsHeart failurePathologicalContractilityCardiac function curveVentricleReceptorDiseaseSignal transductionFibrosis

Abstract

fetched live from OpenAlex

Pathological cardiac remodelling is an adaptive response to various stressors placed on the heart, such as sustained hypertension or following myocardial infarction. The remodelling attempts to preserve cardiac function and contractility through increased left ventricular wall thickness via a hypertrophic response in cardiomyocytes. At the same time, cardiac fibroblasts are activated and mediate a fibrotic response in damaged areas to maintain structural integrity and aid in wound healing. While initially adaptative, chronic activation of these processes can lead to left ventricle dilation and heart failure, where the heart is no longer able to maintain the necessary cardiac output. This remodelling is predominantly mediated through neurohormonal activation of multiple G protein-coupled receptors (GPCRs), as well as their Gα and Gβγ partner proteins, to elicit intracellular signalling cascades in the different cell types. Currently, the primary therapies are aimed at blocking these receptors. Despite modest clinical success of these therapies, heart failure remains a leading cause of mortality in Canada. Therefore, development of new approaches are required to understand and impact disease progression and improve patient prognosis. GPCR signalling pathways converge on the transcriptional machinery to regulate gene expression changes critical for the development of pathological cardiac remodelling. Due to the integration of multiple pathological signals by the transcriptional machinery, therapies targeting these processes are an attractive prospect that may have greater efficacy than current options. This thesis describes how GPCR signalling pathways alter the activity of the transcriptional machinery to regulate the gene expression changes underlying pathological cardiac remodelling. Herein, we identify the differential activation of Gαs/cAMP/PKA signalling between two GPCRs that drive hypertrophy, the α1-adrenergic receptor and the endothelin-1 receptor, in both primary rat neonatal cardiomyocytes and a heterologous HEK 293 cell system. Furthermore, we demonstrate the implications of the differential signalling between the α1-adrenergic and endothelin-1 receptors on positive transcription elongation factor b (P-TEFb) recruitment mechanisms employed by either receptor to promote cardiomyocyte hypertrophy. Additionally, we demonstrate the regulatory role of an interaction between Gβγ and RNA polymerase II on fibrotic gene expression downstream of the angiotensin II type I receptor in primary rat neonatal cardiac fibroblasts. Overall, this thesis expands our understanding of how GPCR signalling regulates the transcriptional machinery and proposes important considerations for the use and development of therapies for heart failure

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 score0.007

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 communication0.0010.000
Open science0.0000.000
Research integrity0.0010.001
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 head0.013
GPT teacher head0.230
Teacher spread0.217 · 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

Citations0
Published2020
Admission routes1
Has abstractyes

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