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Record W2962714555 · doi:10.3791/59588

Isolation of Atrial Myocytes from Adult Mice

2019· article· en· W2962714555 on OpenAlexafffund
Hailey J. Jansen, Robert A. Rose

Bibliographic record

VenueJournal of Visualized Experiments · 2019
Typearticle
Languageen
FieldMedicine
TopicCardiac electrophysiology and arrhythmias
Canadian institutionsLibin Cardiovascular Institute of AlbertaUniversity of Calgary
FundersCanadian Institutes of Health ResearchKillam TrustsHeart and Stroke Foundation of Canada
KeywordsElectrophysiologyAtrial fibrillationPatch clampAtrial action potentialCardiac electrophysiologyAtrial AppendageAtrial myocytesMyocyteIon channelAtrium (architecture)Internal medicineBiologyNeuroscienceCardiologyMedicineReceptorRepolarization

Abstract

fetched live from OpenAlex

The electrophysiological properties of atrial myocytes importantly affect overall cardiac function. Alterations in the underlying ionic currents responsible for the action potential can cause pro-arrhythmic substrates that underlie arrhythmias, such as atrial fibrillation, which are highly prevalent in many conditions and disease states. Isolating adult mouse atrial cardiomyocytes for use in patch-clamp experiments has greatly advanced our knowledge and understanding of the cellular electrophysiology in the healthy atrial myocardium and in the setting of atrial pathophysiology. In addition, studies using genetic mouse models have elucidated the role of a vast array of proteins in regulating atrial electrophysiology. Here we provide a detailed protocol for the isolation of cardiomyocytes from the atrial appendages of adult mice using a combination of enzymatic digestion and mechanical dissociation of these tissues. This approach consistently and reliably yields isolated atrial cardiomyocytes that can then be used to characterize cellular electrophysiology by measuring action potentials and ionic currents in patch-clamp experiments under a number of experimental conditions.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.015
Threshold uncertainty score0.400

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.014
GPT teacher head0.380
Teacher spread0.366 · 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.

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

Citations9
Published2019
Admission routes2
Has abstractyes

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