Characterization of pediatric porcine pulmonary valves as a model for tissue engineered heart valves
Bibliographic record
Abstract
Abstract Heart valve tissue engineering holds the potential to transform the surgical management of congenital heart defects affecting the pediatric pulmonary valve (PV) by offering a viable valve replacement with the compositional, architectural and mechanical properties required to function in situ . While aiming to recapitulate the native valve, the minimum requirement for tissue engineered heart valves (TEHVs) has historically been adequate mechanical function at implantation. However, long-term in situ functionality of TEHVs remains elusive, suggesting that a closer approximation of the native valve is required. The realization of biomimetic engineered pediatric PV is impeded by insufficient characterization of healthy pediatric tissue. In this study, we comprehensively characterized the planar biaxial tensile behaviour, extracellular matrix (ECM) composition and organization, and valvular interstitial cell (VIC) phenotypes of PVs from piglets to provide benchmarks for TEHVs. The piglet PV possessed an anisotropic and non-linear tension-strain profile from which material constants for a predictive constitutive model were derived. Further, the ECM of the pediatric PV possessed a trilayer organization populated by collagen, glycosaminoglycans, and elastin. Biochemical quantification of ECM proteins normalized to wet weight and DNA content of PV tissue revealed homogenous distribution of proteins across sampled regions of the leaflet. Finally, the predominant phenotype of VICs in the piglet PV was quiescent vimentin-expressing fibroblasts, with a small proportion of activated α-smooth muscle actin-expressing myofibroblasts residing primarily at the base of the leaflet. Overall, the properties characterized in this study can be used to inform TEHV design parameters towards generation of biomimetic pediatric PVs. Graphical Abstract
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 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".