A Polypyrrole‐Polycarbonate Polyurethane Elastomer Alleviates Cardiac Arrhythmias via Improving Bio‐Conductivity
Bibliographic record
Abstract
Myocardial fibrosis, resulting from myocardial infarction (MI), significantly alters cardiac electrophysiological properties. As fibrotic scar tissue forms, its resistance to incoming action potentials increases, leading to cardiac arrhythmia, and eventually sudden cardiac death or heart failure. Biomaterials are gaining increasing attention as an approach for addressing post-MI arrhythmias. The current study investigates the hypothesis that a bio-conductive epicardial patch can electrically synchronize isolated cardiomyocytes in vitro and rescue arrhythmic hearts in vivo. A new conceived biocompatible, conductive, and elastic polyurethane composite bio-membrane, referred to as polypyrrole-polycarbonate polyurethane (PPy-PCNU), is developed, in which solid-state conductive PPy nanoparticles are distributed throughout an electrospun aliphatic PCNU nanofiber patch in a controlled manner. Compared to PCNU alone, the resulting biocompatible patch demonstrates up to six times less impedance, with no conductivity loss over time, as well as being able to influence cellular alignment. Furthermore, PPy-PCNU promotes synchronous contraction of isolated neonatal rat cardiomyocytes and alleviates atrial fibrillation in rat hearts upon epicardial implantation. Taken together, epicardially-implanted PPy-PCNU could potentially serve as a novel alternative approach for the treatment of cardiac arrhythmias.
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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".