Bioprinting and In Vitro Characterization of an Eggwhite-Based Cell-Laden Patch for Endothelialized Tissue Engineering Applications
Bibliographic record
Abstract
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%).
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".