Microfabricated perfusable cardiac biowire: a platform that mimics native cardiac bundle
Bibliographic record
Abstract
Tissue engineering enables the generation of three-dimensional (3D) functional cardiac tissue for pre-clinical testing in vitro, which is critical for new drug development. However, current tissue engineering methods poorly recapitulate the architecture of oriented cardiac bundles with supporting capillaries. In this study, we designed a microfabricated bioreactor to generate 3D micro-tissues, termed biowires, using both primary neonatal rat cardiomyocytes and human embryonic stem cell (hESC) derived cardiomyocytes. Perfusable cardiac biowires were generated with polytetrafluoroethylene (PTFE) tubing template, and were integrated with electrical field stimulation using carbon rod electrodes. To demonstrate the feasibility of this platform for pharmaceutical testing, nitric oxide (NO) was released from perfused sodium nitroprusside (SNP) solution and diffused through the tubing. The NO treatment slowed down the spontaneous beating of cardiac biowires based on hESC derived cardiomyocytes and degraded the myofibrillar cytoskeleton of the cardiomyocytes within the biowires. The biowires were also integrated with electrical stimulation using carbon rod electrodes to further improve phenotype of cardiomyocytes, as indicated by organized contractile apparatus, higher Young's modulus, and improved electrical properties. This microfabricated platform provides a unique opportunity to assess pharmacological effects on cardiac tissue in vitro by perfusion in a cardiac bundle model, which could provide improved physiological relevance.
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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) | 0.000 | 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".