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Record W2061226821 · doi:10.1097/fjc.0b013e3181edb22c

The Role of MicroRNA in Cardiac Excitability

2010· review· en· W2061226821 on OpenAlexafffund
Zhiguo Wang

Bibliographic record

VenueJournal of Cardiovascular Pharmacology · 2010
Typereview
Languageen
FieldMedicine
TopicCardiac electrophysiology and arrhythmias
Canadian institutionsMontreal Heart InstituteUniversité de Montréal
FundersCanadian Institutes of Health Research
KeywordsSudden cardiac deathIon channelmicroRNACardiac muscleCardiac function curveContraction (grammar)NeuroscienceMyocardial infarctionCardiac action potentialMembrane potentialCardiac myocyteRepolarizationMedicineCardiologyHeart failureInternal medicineChemistryElectrophysiologyBiologyGeneBiochemistryReceptor

Abstract

fetched live from OpenAlex

Cardiomyocytes are excitable cells that can generate and propagate excitations; excitability is a fundamental characteristic of these cells, which is reflected by action potential; the changes of transmembrane potential as a function of time; and orchestrated by ion channels, transporters, and cellular proteins. The electrical excitation evoked in muscles must be transformed into mechanical contraction through the so-called excitation-contraction coupling mechanism, and the proper contraction of cardiac muscles then drives pumping of blood to the body circulation. Arrhythmias are electrical disturbances that can result in irregular heart beating with consequent insufficient pumping of blood. Arrhythmias are often lethal, constituting a major cause for cardiac death, particularly sudden cardiac death, in myocardial infarction and heart failure. Recent studies have led to discovery of microRNAs (miRNAs) as a new player in the cardiac excitability by fine-tuning expression of ion channels, transporters, and cellular proteins, which determines the arrhythmogenicity in many conditions. This review article will give a comprehensive summary on the data available in the literature. The basics of cardiac excitability will first be introduced, followed by a brief introduction to the basics of miRNAs. Then, studies on regulation of cardiac excitability by miRNAs will be described and analyzed. Finally, concluding remarks will be provided.

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)0.004
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesResearch integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.983
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0050.010
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0000.000

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 head0.012
GPT teacher head0.313
Teacher spread0.301 · 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 designOther design
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

Citations20
Published2010
Admission routes2
Has abstractyes

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