Engineering of Oriented Myocardium on Three-Dimensional Micropatterned Collagen-Chitosan Hydrogel
Bibliographic record
Abstract
INTRODUCTION: Surface topography and electrical field stimulation are important guidance cues that aid the organization and contractility of cardiomyocytes in vivo. We report here on the use of these biomimetic cues in vitro to engineer an implantable contractile cardiac tissue. METHODS: Photocrosslinkable collagen-chitosan hydrogels with microgrooves of 10 µm, 20 µm and 100 µm in width were fabricated using polydimethylsiloxane (PDMS) molds. The hydrogels were seeded with cardiomyocytes, placed into a bioreactor array with the microgrooves aligned with the electrical field lines, and stimulated with biphasic square pulses at 1 Hz and 2.5 V/cm. RESULTS: At Day 6, cardiomyocytes were aligned in the direction of the microgrooves. When cultivated without electrical stimulation, the excitation threshold of engineered cardiac tissues using micropatterned hydrogels was significantly lower than using smooth hydrogels, thus showing the importance of cell alignment to cardiac function. The success rate of achieving beating constructs was higher with the application of electrical stimulation. In addition, formation of dense contractile cardiac organoids was observed in groups with both biomimetic cues. The cultivation of cardiomyocytes on hydrogels with 10 µm grooves yielded 100% beating tissues with or without electrical stimulation, thus suggesting a smaller groove width is necessary for cells to communicate and form proper gap junctions. However, electrical field stimulation further increased cell density and enhanced tissue morphology which may be essential for the integration of the tissue construct to the native heart tissue upon implantation. CONCLUSIONS: The biodegradability of the hydrogel substrate allows for the rapid translation of the engineered, oriented cardiac tissue to clinical applications.
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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".