A Novel Conductive Polypyrrole‐Chitosan Hydrogel Containing Human Endometrial Mesenchymal Stem Cell‐Derived Exosomes Facilitated Sustained Release for Cardiac Repair
Bibliographic record
Abstract
Abstract Myocardial infarction (MI) results in cardiomyocyte necrosis and conductive system damage, leading to sudden cardiac death and heart failure. Studies have shown that conductive biomaterials can restore cardiac conduction, but cannot facilitate tissue regeneration. This study aims to add regenerative capabilities to the conductive biomaterial by incorporating human endometrial mesenchymal stem cell (hEMSC)‐derived exosomes (hEMSC‐Exo) into poly‐pyrrole‐chitosan (PPY‐CHI), to yield an injectable hydrogel that can effectively treat MI. In vitro, PPY‐CHI/hEMSC‐Exo, compared to untreated controls, PPY‐CHI, or hEMSC‐Exo alone, alleviates H 2 O 2 ‐induced apoptosis and promotes tubule formation, while in vivo, PPY‐CHI/hEMSC‐Exo improves post‐MI cardiac functioning, along with counteracting against ventricular remodeling and fibrosis. All these activities are facilitated via increased epidermal growth factor (EGF)/phosphoinositide 3‐kinase (PI3K)/AKT signaling. Furthermore, the conductive properties of PPY‐CHI/hEMSC‐Exo are able to resynchronize cardiac electrical transmission to alleviate arrythmia. Overall, PPY‐CHI/hEMSC‐Exo synergistically combines the cardiac regenerative capabilities of hEMSC‐Exo with the conductive properties of PPY‐CHI to improve cardiac functioning, via promoting angiogenesis and inhibiting apoptosis, as well as resynchronizing electrical conduction, to ultimately enable more effective MI treatment. Therefore, incorporating exosomes into a conductive hydrogel provides dual benefits in terms of maintaining conductivity, along with facilitating long‐term exosome release and sustained application of their beneficial effects.
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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".