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Record W2611097488 · doi:10.3791/55373

Maturation of Human Stem Cell-derived Cardiomyocytes in Biowires Using Electrical Stimulation

2017· article· en· W2611097488 on OpenAlexafffund
Xuetao Sun, Sara S. Nunes

Bibliographic record

VenueJournal of Visualized Experiments · 2017
Typearticle
Languageen
FieldMedicine
TopicTissue Engineering and Regenerative Medicine
Canadian institutionsHeart and Stroke FoundationUniversity of TorontoUniversity Health Network
FundersCanadian Institutes of Health ResearchJ.P. Bickell FoundationHeart and Stroke Foundation of Canada
KeywordsInduced pluripotent stem cellRegenerative medicineTissue engineeringStimulationStem cellElectrophysiologyNeuroscienceMyocyteCell biologyBiomedical engineeringBiologyEmbryonic stem cellMedicineBiochemistry

Abstract

fetched live from OpenAlex

Human pluripotent stem cell-derived cardiomyocytes (hPSC-CMs) have been a promising cell source and have thus encouraged the investigation of their potential applications in cardiac research, including drug discovery, disease modeling, tissue engineering, and regenerative medicine. However, cells produced by existing protocols display a range of immaturity compared with native adult ventricular cardiomyocytes. Many efforts have been made to mature hPSC-CMs, with only moderate maturation attained thus far. Therefore, an engineered system, called biowire, has been devised by providing both physical and electrical cues to lead hPSC-CMs to a more mature state in vitro. The system uses a microfabricated platform to seed hPSC-CMs in collagen type I gel along a rigid template suture to assemble into aligned cardiac tissue (biowire), which is subjected to electrical field stimulation with a progressively increasing frequency. Compared to nonstimulated controls, stimulated biowired cardiomyocytes exhibit an enhanced degree of structural and electrophysiological maturation. Such changes are dependent upon the stimulation rate. This manuscript describes in detail the design and creation of biowires.

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 score0.046
Threshold uncertainty score0.332

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.065
GPT teacher head0.456
Teacher spread0.392 · 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

Citations24
Published2017
Admission routes2
Has abstractyes

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