Bio‐Conductive Polymers for Treating Myocardial Conductive Defects: Long‐Term Efficacy Study
Bibliographic record
Abstract
Abstract Following myocardial infarction (MI), the resulting fibrotic scar is nonconductive and leads to ventricular dysfunction via electrical uncoupling of the remaining viable cardiomyocytes. The uneven conductive properties between normal myocardium and scar tissue result in arrhythmia, yielding sudden cardiac death/heart failure. A conductive biopolymer, poly‐3‐amino‐4‐methoxybenzoic acid‐gelatin (PAMB‐G), is able to resynchronize myocardial contractions in vivo. Intravenous PAMB‐G injections into mice show that it does not cause any acute toxicity, up to the maximum tolerated dose (1.6 mL kg−1), which includes the determined therapeutic dose (0.4 mL kg−1). There is also no short‐ or long‐term toxicity when PAMB‐G is injected into the myocardium of MI rats, with no significant changes in body weight, organ–brain ratio, hematologic, and histological parameters for up to 12 months post‐injection. At the therapeutic dose, PAMB‐G restores electrical conduction in infarcted rat hearts, resulting in lowered arrhythmia susceptibility and improved cardiac function. PAMB‐G is also durable, as mass spectrometry detected the biopolymer for up to 12 months post‐injection. PAMB‐G did not impact reproductive organ function or offspring characteristics when given intravenously into healthy adult rats. Thus, PAMB‐G is a nontoxic, durable, and conductive biomaterial that is able to improve cardiac function for up to 1 year post‐implantation.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 | 0.001 |
| 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".