Biphasic Electrical Field Stimulation Aids in Tissue Engineering of Multicell-Type Cardiac Organoids
Bibliographic record
Abstract
The main objectives of current work were (1) to compare the effects of monophasic or biphasic electrical field stimulation on structure and function of engineered cardiac organoids based on enriched cardiomyocytes (CM) and (2) to determine if electrical field stimulation will enhance electrical excitability of cardiac organoids based on multiple cell types. Organoids resembling cardiac myofibers were cultivated in Matrigel-coated microchannels fabricated of poly(ethylene glycol)-diacrylate. We found that field stimulation using symmetric biphasic square pulses at 2.5 V/cm, 1 Hz, 1 ms (per pulse phase) was an improved stimulation protocol, as compared to no stimulation and stimulation using monophasic square pulses of identical total amplitude and duration (5 V/cm, 1 Hz, 2 ms). This was supported by the highest success rate for synchronous contractions, low excitation threshold, the highest cell density, and the highest expression of Connexin-43 in the biphasic group. Subsequently, enriched CM were seeded on the networks of (1) cardiac fibroblasts (FB), (2) D4T endothelial cells (EC), or (3) a mixture of FB and EC that were precultured for 2 days prior to the addition of enriched CM. Biphasic field stimulation was also effective at improving electrical excitability of these cardiac organoids by improving the three-dimensional organization of the cells, increasing cellular elongation and enhancing Connexin-43 presence.
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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".