Bioreactor for modulation of cardiac microtissue phenotype by combined static stretch and electrical stimulation
Bibliographic record
Abstract
We describe here a bioreactor capable of applying electrical field stimulation in conjunction with static strain and on-line force of contraction measurements. It consisted of a polydimethylsiloxane (PDMS) tissue chamber and a pneumatically driven stretch platform. The chamber contained eight tissue microwells (8.05 mm in length and 2.5 mm in width) with a pair of posts (2.78 mm in height and 0.8 mm in diameter) in each well to serve as fixation points and for measurements of contraction force. Carbon rods, stimulating electrodes, were placed into the PDMS chamber such that one pair stimulated four microwells. For feasibility studies, neonatal rat cardiomyocytes were seeded in collagen gels into the microwells. Following 3 days of gel compaction, electrical field stimulation at 3-4 V cm(-1) and 1 Hz, mechanical stimulation of 5% static strain or electromechanical stimulation (field stimulation at 3-4 V cm(-1), 1 Hz and 5% static strain) were applied for 3 days. Cardiac microtissues subjected to electromechanical stimulation exhibited elevated amplitude of contraction and improved sarcomere structure as evidenced by sarcomeric α-actinin, actin and troponin T staining compared to microtissues subjected to electrical or mechanical stimulation alone or non-stimulated controls. The expression of atrial natriuretic factor and brain natriuretic peptide was also elevated in the electromechanically stimulated group.
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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 | 0.001 |
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".