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Record W2941432902 · doi:10.1121/1.5101234

Left ventricle blood flow patterns in a mouse model of temperature sensitive sodium channelopathy

2019· article· en· W2941432902 on OpenAlexaff
Jeffrey A. Ketterling, Orlando Aristizábal, Akshay Shekhar, Billy Y. S. Yiu, Colin K. L. Phoon, Glenn I. Fishman, Alfred C. H. Yu, Ronald H. Silverman

Bibliographic record

VenueThe Journal of the Acoustical Society of America · 2019
Typearticle
Languageen
FieldEngineering
TopicUltrasound and Hyperthermia Applications
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsVentricleBlood flowSodium channelInternal medicineSodiumCardiologyMaterials scienceChemistryBiophysicsBiomedical engineeringMedicineBiology

Abstract

fetched live from OpenAlex

Sophisticated methods of visualizing and analyzing the complex blood flow patterns in humans have been available for a number of years on ultrasound machines. To date, these methods have not been applied to healthy mouse models or mice with cardiac defects. Here, a high-speed plane-wave imaging approach was used to study left ventricle blood flow patterns in a model of sodium channelopathy using mice lacking fibroblast growth factor homologous factor 2 (Fhf2KO) and littermate wild-type (WT) controls. FHF2 binds to the cytoplasmic tails of voltage-gated sodium channels in mouse cardiomyocytes and modulates channel inactivation and cellular excitability. Fhf2KO mice have impaired cardiac sodium channel function that when body temperature rises causes a severe reduction in cardiac sodium currents, cardiomyocyte excitation, and conduction failure. The effect is reversible as body temperature returns to normothermia. Fhf2WT and Fhf2KO mice were imaged with a Verasonics Vantage 128 using an 18-MHz linear array with a 30 kHz absolute plane-wave transmission rate. The mice were supine on an imaging platform and a warm-air source was used to raise the body temperature. Surface ECGs were continuously recorded throughout the duration of the experiment. Data were post-processed using a least-squares, multi-angle Doppler analysis approach to obtain vector-flow estimates at all pixel locations. Vortex patterns, flow rates and ECG signals were compared between the Fhf2WT and Fhf2KO mice.

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)0.001
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.005
GPT teacher head0.192
Teacher spread0.186 · 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 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

Citations0
Published2019
Admission routes1
Has abstractyes

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