A Visible Light-Cross-Linkable, Fibrin–Gelatin-Based Bioprinted Construct with Human Cardiomyocytes and Fibroblasts
Bibliographic record
Abstract
In this study, fibrin was added to a photo-polymerizable gelatin-based bioink mixture to fabricate cardiac cell-laden constructs seeded with human induced pluripotent stem cell-derived cardiomyocytes (iPS-CM) or CM cell lines with cardiac fibroblasts (CF). The extensive use of platelet-rich fibrin, its capacity to offer patient specificity, and the similarity in composition to surgical glue prompted us to include fibrin in the existing bioink composition. The cell-laden bioprinted constructs were cross-linked to retain a herringbone pattern via a two-step procedure including the visible light cross-linking of furfuryl-gelatin followed by the chemical cross-linking of fibrinogen via thrombin and calcium chloride. The printed constructs revealed an extremely porous, networked structure that afforded long-term in vitro stability. Cardiomyocytes printed within the sheet structure showed excellent viability, proliferation, and expression of the troponin I cardiac marker. We extended the utility of this fibrin-gelatin bioink toward coculturing and coupling of CM and cardiac fibroblasts (CF), the interaction of which is extremely important for maintenance of normal physiology of the cardiac wall in vivo. This enhanced "cardiac construct" can be used for drug cytotoxicity screening or unraveling triggers for heart diseases in vitro.
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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".