Bioinspired trilayer poly(ε-caprolactone) scaffolds with native-like structures and mechanical property for heart valve constructs
Bibliographic record
Abstract
Although valve replacement surgery is one of the primary treatments for patients with severe heart valve disease, current artificial valve options are lack of regenerative and remodeling potential, not suitable for pediatric and young patients. Inspired by the natural structures of heart valve leaflets, this study employed electrospinning technology to fabricate bioinspired trilayer poly(ε-caprolactone) scaffolds, aiming to replicate the microstructures and mechanical properties of native leaflets for tissue-engineered heart valves (TEHVs). Specifically, a collector with a honeycomb pattern was used to fabricate the middle layer, mimicking the spongiosa layer of native leaflets, while a roller collector was used to produce the orthogonal fiber alignment in the upper and lower layers. The prepared biomimetic tri-layered scaffold (BTS) not only mimicked the fiber alignment of native leaflets but also successfully reproduced the natural corrugation structure found in heart valve leaflets, generating a nonlinear stress-strain behavior resembling the “J-curve” observed in native leaflets. Furthermore, the anisotropic BTS exhibited elastic moduli (BTS-X: 12.50 ± 1.88 MPa; BTS-Y: 7.01 ± 1.12 MPa) and ultimate tensile strengths (UTS) (BTS-X: 8.09 ± 1.16 MPa; BTS-Y: 4.60 ± 0.75 MPa) in the orthogonal directions, close to those of native valve leaflets. In vitro cell culture demonstrated that BTS is non-cytotoxic, and cell alignment and proliferation behavior are influenced by the fiber orientation of the electrospun scaffold. Hemodynamic tests showed that the effective orifice area and regurgitation rate of the artificial valve can meet the requirements of the ISO 5840-2 standard. In summary, the tailored BTS mimicking natural microstructures exhibits isotropic mechanical properties similar to those of native leaflets, along with excellent biocompatibility, demonstrating great potential as a scaffold for TEHVs.
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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 | 0.000 | 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 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".