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Record W1688654027 · doi:10.1139/cjpp-2013-0161

Cardiomyocyte culture — an update on the in vitro cardiovascular model and future challenges

2013· review· en· W1688654027 on OpenAlexafffundvenue
Sujeet Kumar, Rama Shanker Verma, Rajendra K. Sharma

Bibliographic record

VenueCanadian Journal of Physiology and Pharmacology · 2013
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicPluripotent Stem Cells Research
Canadian institutionsUniversity of Saskatchewan
FundersCollege of Pharmacy and Nutrition, University of SaskatchewanU.S. Food and Drug AdministrationDepartment of Science and Technology, Ministry of Science and Technology, India
KeywordsInduced pluripotent stem cellEmbryonic stem cellBiologyProgenitor cellStem cellMyocyteCell biologyIn vitroCell cultureTissue engineeringBioinformaticsGenetics

Abstract

fetched live from OpenAlex

The success of any work with isolated cardiomyocytes depends on the reproducibility of cell isolation, because the cells do not divide. To date, there is no suitable in vitro model to study human adult cardiac cell biology. Although embryonic stem cells and induced pluripotent stem cells are able to differentiate into cardiomyocytes in vitro, the efficiency of this process is low. Isolation and expansion of human cardiomyocyte progenitor cells from cardiac surgical waste or, alternatively, from fetal heart tissue is another option. However, to overcome various issues related to human tissue usage, especially ethical concerns, researchers use large- and small-animal models to study cardiac pathophysiology. A simple model to study the changes at the cellular level is cultures of cardiomyocytes. Although primary murine cardiomyocyte cultures have their own advantages and drawbacks, alternative strategies have been developed in the last two decades to minimise animal usage and interspecies differences. This review discusses the use of freshly isolated murine cardiomyocytes and cardiomyocyte alternatives for use in cardiac disease models and other related studies.

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)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.984
Threshold uncertainty score0.861

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 integrity0.0010.001
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 head0.037
GPT teacher head0.303
Teacher spread0.266 · 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 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

Citations44
Published2013
Admission routes3
Has abstractyes

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