A Modular Approach to Cardiac Tissue Engineering
Why this work is in the frame
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Bibliographic record
Abstract
Functional cardiac tissue was prepared using a modular tissue engineering approach with the goal of creating vascularized tissue. Rat aortic endothelial cells (RAEC) were seeded onto submillimeter-sized modules made of type I bovine collagen supplemented with Matrigel™ (25% v/v) embedded with cardiomyocyte (CM)-enriched neonatal rat heart cells and assembled into a contractile, macroporous, sheet-like construct. Modules (without RAEC) cultured in 10% bovine serum (BS) were more contractile and responsive to external stimulus (lower excitation threshold, higher maximum capture rate, and greater en face fractional area changes) than modules cultured in 10% fetal BS. Incorporating 25% Matrigel in the matrix reduced the excitation threshold and increased the fractional area change relative to collagen only modules (without RAEC). A coculture medium, containing 10% BS, low Mg2+ (0.814mM), and normal glucose (5.5mM), was used to maintain RAEC junction morphology (VE-cadherin) and CM contractility, although the responsiveness of CM was attenuated with RAEC on the modules. Macroporous, sheet-like module constructs were assembled by partially immobilizing a layer of modules in alginate gel until day 8, with or without RAEC. RAEC/CM module sheets were electrically responsive; however, like modules with RAEC this responsiveness was attenuated relative to CM-only sheets. Muscle bundles coexpressing cardiac troponin I and connexin-43 were evident near the perimeter of modules and at intermodule junctions. These results suggest the potential of the modular approach as a platform for building vascularized cardiac tissue.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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 it