Building the framework for bioprinted human heart tissue: recent developments and future prospects
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Cardiac bioprinting holds great promise for creating patient-specific grafts and physiologically relevant drug-testing platforms, yet several critical challenges remain. This review identifies key barriers in current cardiac bioprinting approaches, including limitations in bioprinting precision, bioink development, vascularization, functional maturation, and scalable cell sourcing and processing. Recent advances, such as multimodal printing, hybrid bioinks, and perfusable constructs, are discussed with a focus on their application to drug discovery and graft fabrication. We emphasize that targeted maturation may suffice for drug screening, while graft applications demand greater complexity, scale, and immune compatibility. Addressing these challenges through integrated, multidisciplinary strategies will be essential to advance cardiac bioprinting toward clinical and preclinical impact.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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