Fabrication of engineered heart tissue grafts from alginate/collagen barium composite microbeads
Bibliographic record
Abstract
Cardiac tissue engineering holds great promise for the treatment of myocardial infarction. However, insufficient cell migration into the scaffolds used and inflammatory reactions due to scaffold biodegradation remain as issues to be addressed. Engineered heart tissue (EHT) grafts fabricated by means of a cell encapsulation technique provide cells with a tissue-like environment, thereby potentially enhancing cellular processes such as migration, proliferation, and differentiation, and tissue regeneration. This paper presents a study on the fabrication and characterization of EHT grafts from novel alginate/collagen composite microbeads by means of cell encapsulation. Specifically, the microbeads were fabricated from alginate and collagen by barium ion cross-linking, with neonatal rat cardiomyocytes encapsulated in the composite microbeads during the fabrication of the EHT grafts. To evaluate the suitablity of these EHT grafts for heart muscle repair, the growth of cardiac cells in the microbeads was examined by means of confocal microscopy and staining with DAPI and F-actin. The EHT grafts were analyzed by scanning electron microscopy and transmission electron microscopy, and the contractile function of the EHT grafts monitored using a digital video camera at different time points. The results show the proliferation of cardiac cells in the microbeads and formation of interconnected multilayer heart-like tissues, the presence of well-organized and dense cell structures, the presence of intercalated discs and spaced Z lines, and the spontaneous synchronized contractility of EHT grafts (at a rate of 20-30 beats min(-1) after two weeks in culture). Taken together, these observations demonstrate that the novel alginate/collagen composite microbeads can provide a tissue-like microenvironment for cardiomyocytes that is suitable for fabricating native heart-like tissues.
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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".