Highly Elastic and Moldable Polyester Biomaterial for Cardiac Tissue Engineering Applications
Bibliographic record
Abstract
Polyester biomaterials are used in tissue engineering as scaffolds for implantation of tissues developed in vitro. An ideal biodegradable elastomer for cardiac tissue engineering exhibits a relatively low Young's modulus, with high elongation and tensile strength. Here we describe a novel polyester biomaterial that exhibits improved elastic properties for cardiac tissue engineering applications. We synthesized poly(octamethylene maleate (anhydride) 1,2,4-butanetricarboxylate) (124 polymer) prepolymer gel in a one-step polycondensation reaction. The prepolymer was then molded as desired and exposed to ultraviolet (UV) light to produce a cross-linked elastomer. 124 polymer exhibited highly elastic properties under aqueous conditions that were tunable according to the UV light exposure, monomer composition, and porosity of the cured elastomer. Its elastomeric properties fell within the range of adult heart myocardium, but they could also be optimized for higher elasticity for weaker immature constructs. The polymer showed relatively stable degradation characteristics, both hydrolytically and in a cellular environment, suggesting maintenance of material properties as a scaffold support for potential tissue implants. When assessed for cell interaction, this polymer supported rat cardiac cell attachment in vitro as well as comparable acute in vivo host response when compared to poly(l-lactic acid) control. This suggests the potential applicability of this material as an elastomer for cardiac tissue engineered constructs.
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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) | 0.001 | 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 | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".