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Record W2765398719 · doi:10.1089/ten.tec.2017.0346

UV-Assisted 3D Bioprinting of Nanoreinforced Hybrid Cardiac Patch for Myocardial Tissue Engineering

2017· article· en· W2765398719 on OpenAlexafffund
Mohammad Izadifar, Dean Chapman, Paul Babyn, Daniel Chen, Michael Kelly

Bibliographic record

VenueTissue Engineering Part C Methods · 2017
Typearticle
Languageen
FieldEngineering
Topic3D Printing in Biomedical Research
Canadian institutionsUniversity of SaskatchewanUniversity Health Network
FundersCanadian Institutes of Health ResearchUniversity of SaskatchewanSaskatchewan Health Research FoundationHeart and Stroke Foundation of Canada
KeywordsBiofabricationMaterials scienceBiomedical engineeringTissue engineeringSelf-healing hydrogels3D bioprintingExtracellular matrixCardiac muscleCarbon nanotubeViability assayNanotechnologyChemistryIn vitroAnatomyPolymer chemistry

Abstract

fetched live from OpenAlex

Biofabrication of cell supportive cardiac patches that can be directly implanted on myocardial infarct is a potential solution for myocardial infarction repair. Ideally, cardiac patches should be able to mimic myocardium extracellular matrix for rapid integration with the host tissue, raising the need to develop cardiac constructs with complex features. In particular, cardiac patches should be electrically conductive, mechanically robust and elastic, biologically active and prevascularized. In this study, we aim to biofabricate a nanoreinforced hybrid cardiac patch laden with human coronary artery endothelial cells (HCAECs) with improved electrical, mechanical, and biological behavior. A safe ultraviolet (UV) exposure time with insignificant effect on cell viability was identified for methacrylated collagen (MeCol) micropatterning. The effects of carboxyl functionalized carbon nanotubes (CNTs) on MeCol and alginate matrix morphology, mechanical properties, electrical behavior, and cellular response were investigated at different CNT mass ratios. A UV-integrated 3D-bioprinting technique was implemented to create hybrid hydrogel constructs consisting of CNT-incorporated alginate framework and cell-laden MeCol. The compressive modulus, impedance, and swelling degree of hybrid constructs were assessed over 20 days of incubation in culture medium at 37°C for different CNT mass ratios. The HCAEC viability, proliferation, and differentiation in the context of the bioprinted hybrid constructs were assessed over 10 days in vitro. The functionalized CNTs provided a highly interconnected nanofibrous meshwork that significantly improved viscoelastic behavior and electrical conductivity of photo-cross-linked MeCol. Alginate-coated CNTs provided a nanofilamentous network with fiber size of ∼25-500 nm, improving not only electrical and mechanical properties but also HCAEC attachment and elongation compared to pristine alginate. The CNT-reinforced 3D-printed hybrid constructs presented significantly higher stiffness and electrical conductivity particularly in the physiologically relevant frequency range (∼5 Hz). The CNT-reinforced hybrid implants maintained a significantly higher swelling degree over 20 days of culturing compared to CNT-free hybrid constructs. For a selected CNT mass ratio, HCAECs presented significant cellular proliferation, migration, and differentiation (lumen-like formation) over 10 days of incubation in vitro. Findings from this study deliver essential steps toward developing conductive, robust, and potentially prevascularized hybrid cardiac patches.

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)0.000
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 score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.361
Teacher spread0.324 · 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

Citations235
Published2017
Admission routes2
Has abstractyes

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