Pre‐treatment of synthetic elastomeric scaffolds by cardiac fibroblasts improves engineered heart tissue
Bibliographic record
Abstract
Native myocardium consists of several cell types, of which approximately one-third are myocytes and most of the nonmyocytes are fibroblasts. By analogy with monolayer culture in which fibroblasts were removed to prevent overgrowth, early attempts to engineer myocardium utilized cell populations enriched for cardiac myocytes (CMs; approximately 80-90% of total cells). We hypothesized that the pre-treatment of synthetic elastomeric scaffolds with cardiac fibroblasts (CFs) will enhance the functional assembly of the engineered cardiac constructs by creating an environment supportive of cardiomyocyte attachment and function. Cells isolated from neonatal rat ventricles were prepared to form three distinct populations: rapidly plating cells identified as CFs, slowly plating cells identified as CMs, and unseparated initial population of cells (US). The cell fractions (3 x 10(6) cells total) were seeded into poly(glycerol sebacate) scaffolds (highly porous discs, 5 mm in diameter x 2-mm thick) using Matrigeltrade mark, either separately (CM or CF), concurrently (US), or sequentially (CF pre-treatment followed by CM culture, CF + CM), and cultured in spinner flasks. The CF + CM group had the highest amplitude of contraction and the lowest excitation threshold, superior DNA content, and higher glucose consumption rate. The CF + CM group exhibited compact 100- to 200-mum thick layers of elongated myocytes aligned in parallel over layers of collagen-producing fibroblasts, while US and CM groups exhibited scattered and poorly elongated myocytes. The sequential co-culture of CF and CM on a synthetic elastomer scaffold thus created an environment supportive of cardiomyocyte attachment, differentiation, and contractile function, presumably due to scaffold conditioning by cultured fibroblasts. When implanted over the infarcted myocardium in a nude rat model, cell-free poly(glycerol sebacate) remained at the ventricular wall after 2 weeks of in vivo, and was vascularized.
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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 | 0.000 | 0.001 |
| 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".