Bioprinting Pattern-Dependent Electrical/Mechanical Behavior of Cardiac Alginate Implants: Characterization and <i>Ex Vivo</i> Phase-Contrast Microtomography Assessment
Bibliographic record
Abstract
Three-dimensional (3D)-bioprinting techniques may be used to modulate electrical/mechanical properties and porosity of hydrogel constructs for fabrication of suitable cardiac implants. Notably, characterization of these properties after implantation remains a challenge, raising the need for the development of novel quantitative imaging techniques for monitoring hydrogel implant behavior in situ. This study aims at (i) assessing the influence of hydrogel bioprinting patterns on electrical/mechanical behavior of cardiac implants based on a 3D-printing technique and (ii) investigating the potential of synchrotron X-ray phase-contrast imaging computed tomography (PCI-CT) for estimating elastic modulus/impedance/porosity and microstructural features of 3D-printed cardiac implants in situ via an ex vivo study. Alginate laden with human coronary artery endothelial cells was bioprinted layer by layer, forming cardiac constructs with varying architectures. The elastic modulus, impedance, porosity, and other structural features, along with the cell viability and degradation of printed implants were examined in vitro over 25 days. Two selected cardiac constructs were surgically implanted onto the myocardium of rats and 10 days later, the rat hearts with implants were imaged ex vivo by means of PCI-CT at varying X-ray energies and CT-scan times. The elastic modulus/impedance, porosity, and structural features of the implant were inferred from the PCI-CT images by using statistical models and compared with measured values. The printing patterns had significant effects on implant porosity, elastic modulus, and impedance. A particular 3D-printing pattern with an interstrand distance of 900 μm and strand alignment angle of 0/45/90/135° provided relatively higher stiffness and electrical conductivity with a suitable porosity, maintaining high cell viability over 7 days. The X-ray photon energy of 30-33 keV utilizing a CT-scan time of 1-1.2 h resulted in a low-dose PCI-CT, which provided a good visibility of the low-X-ray absorbent alginate implants. After 10 days postimplantation, the PCI-CT provided a reasonably accurate estimation of implant strand thickness and alignment, pore size and interconnectivity, porosity, elastic modulus, and impedance, which were consistent with our measurements. Findings from this study suggest that 3D-printing patterns can be used to modulate electrical/mechanical behavior of alginate implants, and PCI-CT can be potentially used as a 3D quantitative imaging tool for assessing structural and electrical/mechanical behavior of hydrogel cardiac implants in small animal models.
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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 | 0.001 |
| 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".