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Record W3012486483 · doi:10.1080/19336950.2020.1740502

The quest to identify the mechanism underlying adrenergic regulation of cardiac Ca<sup>2+</sup> channels

2020· review· en· W3012486483 on OpenAlexaff
Daniel Roybal, Jessica A. Hennessey, Steven O. Marx

Bibliographic record

VenueChannels · 2020
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicIon channel regulation and function
Canadian institutionsColumbia College
FundersNational Heart, Lung, and Blood Institute
KeywordsDownregulation and upregulationAdrenergicHeterologousCell biologyMechanism (biology)Protein kinase ACardiac action potentialNeuroscienceChemistryBiologyKinaseInternal medicineElectrophysiologyMedicineBiochemistryPhysicsGeneReceptor

Abstract

fetched live from OpenAlex

Activation of protein kinase A by cyclic AMP results in a multi-fold upregulation of CaV1.2 currents in the heart, as originally reported in the 1970's and 1980's. Despite considerable interest and much investment, the molecular mechanisms responsible for this signature modulation remained stubbornly elusive for over 40 years. A key manifestation of this lack of understanding is that while this regulation is readily apparent in heart cells, it has not been possible to reconstitute it in heterologous expression systems. In this review, we describe the efforts of many investigators over the past decades to identify the mechanisms responsible for the β-adrenergic mediated activation of voltage-gated Ca2+ channels in the heart and other tissues.

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 score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.002

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 head0.055
GPT teacher head0.331
Teacher spread0.275 · 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

Citations14
Published2020
Admission routes1
Has abstractyes

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