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Record W4291016442 · doi:10.3390/cells11162488

Upregulation of Phospholipase C Gene Expression Due to Norepinephrine-Induced Hypertrophic Response

2022· review· en· W4291016442 on OpenAlexaff
Paramjit S. Tappia, Naranjan S. Dhalla

Bibliographic record

VenueCells · 2022
Typereview
Languageen
FieldMedicine
TopicCardiac electrophysiology and arrhythmias
Canadian institutionsUniversity of ManitobaSt. Boniface Hospital
Fundersnot available
KeywordsPhospholipase CGq alpha subunitSignal transductionDownregulation and upregulationAngiotensin IIDiacylglycerol kinaseBiologyCell biologyGene expressionIsozymeInositolPhospholipaseG proteinEndocrinologyProtein kinase CInternal medicineGeneMedicineBiochemistryReceptorEnzymeBlood pressure

Abstract

fetched live from OpenAlex

The activation of phospholipase C (PLC) is thought to have a key role in the cardiomyocyte response to several different hypertrophic agents such as norepinephrine, angiotensin II and endothelin-1. PLC activity results in the generation of diacylglycerol and inositol trisphosphate, which are downstream signal transducers for the expression of fetal genes, increased protein synthesis, and subsequent cardiomyocyte growth. In this article, we describe the signal transduction elements that regulate PLC gene expression. The discussion is focused on the norepinephrine- α1-adrenoceptor signaling pathway and downstream signaling processes that mediate an upregulation of PLC isozyme gene expression. Evidence is also indicated to demonstrate that PLC activities self-regulate the expression of PLC isozymes with the suggestion that PLC activities may be part of a coordinated signaling process for the perpetuation of cardiac hypertrophy. Accordingly, from the information provided, it is plausible that specific PLC isozymes could be targeted for the mitigation of cardiac hypertrophy.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.002

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 head0.037
GPT teacher head0.309
Teacher spread0.272 · 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 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

Citations7
Published2022
Admission routes1
Has abstractyes

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