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Record W2122236429 · doi:10.1088/0957-4484/25/1/014009

Cardiac tissue engineering in magnetically actuated scaffolds

2013· article· en· W2122236429 on OpenAlexfundno aff
Yulia Sapir, Boris Polyak, Smadar Cohen

Bibliographic record

VenueNanotechnology · 2013
Typearticle
Languageen
FieldMedicine
TopicTissue Engineering and Regenerative Medicine
Canadian institutionsnot available
FundersNational Institutes of HealthNational Heart, Lung, and Blood InstituteAzrieli FoundationBen-Gurion University of the NegevDrexel University
KeywordsScaffoldTissue engineeringMaterials scienceCardiac cellBiomedical engineeringMicroscale chemistryNanotechnologyStimulationMagnetic nanoparticlesBiophysicsNanoparticleCell biologyNeuroscienceBiologyEngineering

Abstract

fetched live from OpenAlex

Cardiac tissue engineering offers new possibilities for the functional and structural restoration of damaged or lost heart tissue by applying cardiac patches created in vitro. Engineering such functional cardiac patches is a complex mission, involving material design on the nano- and microscale as well as the application of biological cues and stimulation patterns to promote cell survival and organization into a functional cardiac tissue. Herein, we present a novel strategy for creating a functional cardiac patch by combining the use of a macroporous alginate scaffold impregnated with magnetically responsive nanoparticles (MNPs) and the application of external magnetic stimulation. Neonatal rat cardiac cells seeded within the magnetically responsive scaffolds and stimulated by an alternating magnetic field of 5 Hz developed into matured myocardial tissue characterized by anisotropically organized striated cardiac fibers, which preserved its features for longer times than non-stimulated constructs. A greater activation of AKT phosphorylation in cardiac cell constructs after applying a short-term (20 min) external magnetic field indicated the efficacy of magnetic stimulation to actuate at a distance and provided a possible mechanism for its action. Our results point to a synergistic effect of magnetic field stimulation together with nanoparticulate features of the scaffold surface as providing the regenerating environment for cardiac cells driving their organization into functionally mature tissue.

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 score0.178
Threshold uncertainty score0.542

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 head0.005
GPT teacher head0.223
Teacher spread0.218 · 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

Citations75
Published2013
Admission routes1
Has abstractyes

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