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Record W4405796048 · doi:10.15420/ecr.2024.41

From Atrial Small-conductance Calcium-activated Potassium Channels to New Antiarrhythmics

2024· review· en· W4405796048 on OpenAlexaff
Arnela Saljic, Jordi Heijman, Dobromir Dobrev

Bibliographic record

VenueEuropean Cardiology Review · 2024
Typereview
Languageen
FieldMedicine
TopicCardiac electrophysiology and arrhythmias
Canadian institutionsUniversité de MontréalMontreal Heart Institute
FundersNational Heart, Lung, and Blood InstituteNational Institutes of HealthNederlandse Organisatie voor Wetenschappelijk OnderzoekDaiichi Sankyo EuropeDeutsche ForschungsgemeinschaftZonMwEuropean Society of CardiologyEuropean Commission
KeywordsMedicinePotassiumCalciumConductanceCardiologyPotassium channelCalcium-activated potassium channelInternal medicinePharmacologyMaterials science

Abstract

fetched live from OpenAlex

Despite significant advances in its management, AF remains a major healthcare burden affecting millions of individuals. Rhythm control with antiarrhythmic drugs or catheter ablation has been shown to improve symptoms and outcomes in AF patients, but current treatment options have limited efficacy and/or significant side-effects. Novel mechanism-based approaches could potentially be more effective, enabling improved therapeutic strategies for managing AF. Small-conductance calcium-activated potassium (SK or KCa2.x) channels encoded by KCNN1-3 have recently gathered interest as novel antiarrhythmic targets with potential atrial-predominant effects. Here, the molecular composition of small-conductance calcium-activated potassium channels and their complex regulation in AF as the basis for understanding the distinct mechanism of action of pore-blockers (apamin, UCL1684, ICAGEN) and modulators of calcium-dependent activation (NS8593, AP14145, AP30663) are summarised. Furthermore, the preclinical and early clinical evidence for the role of small-conductance calcium-activated potassium channel inhibitors in the treatment of AF are reviewed.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.753
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0090.005
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0000.011

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 head0.081
GPT teacher head0.352
Teacher spread0.271 · 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; both teacher heads agree on what is shown here.

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

Citations12
Published2024
Admission routes1
Has abstractyes

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