Formulation and Evaluation of PVA/Gelatin/Carrageenan Inks for 3D Printing and Development of Tissue‐Engineered Heart Valves
Bibliographic record
Abstract
Abstract Congenital and acquired valvular heart diseases (VHDs) are significant causes of mortality worldwide. With valve replacement being the primary solution for VHD, current options display shortcomings, including calcification, thrombogenicity, and hemodynamic alteration, leading to repetitive surgeries. Tissue engineering, however, has shown great potential for fabricating heart valves (HVs) with fewer complications. Here, a series of inks are developed, combining poly(vinyl alcohol), gelatin, and carrageenan for 3D printing of tissue‐engineered heart valves (TEHVs). The inks/hydrogels are investigated to characterize their physico‐chemical, morphological, mechanical, and rheological characteristics. In vitro and in vivo biocompatibility, immune response, hemolysis, and thrombogenicity of the inks/hydrogels are also evaluated. Moreover, in vitro hydrodynamics of the TEHVs under physiological conditions are reported. Inks demonstrate mechanical characteristics comparable to native leaflets. Subcutaneous implantation reveals that the hydrogels do not induce chronic inflammation and can undergo remodeling. In vitro hemocompatibility assessments of the hydrogels show minimal hemolysis with low thrombogenicity. Different sizes and types of HVs are successfully printed with high fidelity in the air. In vitro hydrodynamic assessment confirms that the TEHVs can withstand aortic conditions. Altogether, the 3D‐printed TEHVs can be a promising alternative for valve replacement to solve the problems associated with the current options.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 teacher head, 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".