Polyphenol‐Nanoengineered Monocyte Biohybrids for Targeted Cardiac Repair and Immunomodulation
Bibliographic record
Abstract
Myocardial infarction is one of the leading cause of cardiovascular death worldwide. Invasive interventional procedures and medications are applied to attenuate the attacks associated with ischemic heart disease by reestablishing blood flow and restoring oxygen supply. However, the overactivation of inflammatory responses and unsatisfactory drug delivery efficiency in the infarcted regions prohibit functional improvement. Here, a nanoengineered monocyte (MO)-based biohybrid system, referred to as CTAs @MOs, for the heart-targeted delivery of combinational therapeutic agents (CTAs) containing anti-inflammatory IL-10 and cardiomyogenic miR-19a to overcome the limitation of malperfusion within the infarcted myocardium through a polyphenol-mediated interfacial assembly, is reported. Systemic administration of CTAs@MOs bypasses extensive thoracotomy and intramyocardial administration risks, leading to infarcted heart-specific accumulation and sustained release of therapeutic agents, enabling immunomodulation of the proinflammatory microenvironment and promoting cardiomyocyte proliferation in sequence. Moreover, CTAs@MOs, which serve as a cellular biohybrid-based therapy, significantly improve cardiac function as evidenced by enhanced ejection fractions, increased fractional shortening, and diminished infarct sizes. This polyphenol nanoengineered biohybrid system represents a general and potent platform for the efficient treatment of cardiovascular disorders.
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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".