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Record W3187732005 · doi:10.3390/jfb12030045

Bioprinting and In Vitro Characterization of an Eggwhite-Based Cell-Laden Patch for Endothelialized Tissue Engineering Applications

2021· article· en· W3187732005 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Functional Biomaterials · 2021
Typearticle
Languageen
FieldEngineering
Topic3D Printing in Biomedical Research
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
Keywords3D bioprintingSodium alginateTissue engineeringMaterials scienceBiomedical engineeringNanotechnologySodiumEngineering

Abstract

fetched live from OpenAlex

Three-dimensional (3D) bioprinting is an emerging fabrication technique to create 3D constructs with living cells. Notably, bioprinting bioinks are limited due to the mechanical weakness of natural biomaterials and the low bioactivity of synthetic peers. This paper presents the development of a natural bioink from chicken eggwhite and sodium alginate for bioprinting cell-laden patches to be used in endothelialized tissue engineering applications. Eggwhite was utilized for enhanced biological properties, while sodium alginate was used to improve bioink printability. The rheological properties of bioinks with varying amounts of sodium alginate were examined with the results illustrating that 2.0–3.0% (w/v) sodium alginate was suitable for printing patch constructs. The printed patches were then characterized mechanically and biologically, and the results showed that the printed patches exhibited elastic moduli close to that of natural heart tissue (20–27 kPa) and more than 94% of the vascular endothelial cells survived in the examination period of one week post 3D bioprinting. Our research also illustrated the printed patches appropriate water uptake ability (>1800%).

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.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.076
Threshold uncertainty score0.403

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.013
GPT teacher head0.252
Teacher spread0.239 · 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