A New Role for Extracellular Vesicles in Cardiac Tissue Engineering and Regenerative Medicine
Why this work is in the frame
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Bibliographic record
Abstract
Cardiovascular diseases are the leading cause of death worldwide. Discovering new therapies to treat heart disease requires improved understanding of cardiac physiology at a cellular level. Extracellular vesicles (EVs) are plasma membrane-bound nano- and microparticles secreted by cells and known to play key roles in intercellular communication, often through transfer of biomolecular cargo. Advances in EV research have established techniques for EV isolation from tissue culture media or biofluids, as well as standards for quantitation and biomolecular characterization. EVs released by cardiac cells are known to be involved in regulating cardiac physiology as well as in the progression of myocardial diseases. Due to difficulty accessing the heart in vivo, advanced in vitro cardiac 'tissues-on-a-chip' have become a recent focus for studying EVs in the heart. These physiologically relevant models are producing new insight into the role of EVs in cardiac physiology and disease while providing a useful platform for screening novel EV-based therapeutics for cardiac tissue regeneration post-injury. Numerous hurdles have stalled the clinical translation of EV therapeutics for heart patients, but tissue-on-a-chip models are playing an important role in bridging the translational gap, improving mechanistic understanding of EV signalling in cardiac physiology, disease, and repair.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| 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) | 0.000 | 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 it