The Tissue Engineering Grail: Seamless Biofabrication of Scaffold-free Hollow Constructs
Bibliographic record
Abstract
Abstract Scaffold-free tissue engineering enables the construction of biomimetic tissues and organs by preserving cell-cell and cell-matrix interactions while avoiding exogenous scaffolds and biomaterials. Yet current approaches are limited to thin sheets or simple spheroids and often lack cellular maturity and organized extracellular matrix (ECM). Here, Anchored Cell Sheet Engineering, a concept that previously introduced anchors to guide the remodeling of cell sheets into more mature fibers or sheets, is extended to achieve seamless, single-step biofabrication of scaffold-free hollow tubular and spherical constructs for sustained biological and mechanical functions under physiological conditions. Using custom culture devices with curved geometries for two-dimensional (2D) culture, continuous confluent cell-ECM layers were formed that were then delaminated and guided by strategically positioned central cores with different shapes and sizes to undergo tension-mediated remodeling into mechanically stable hollow structures. This approach allows modulation of wall thickness, supports multi-layered architectures, and yields constructs capable of withstanding fluid flow. By expanding scaffold-free biofabrication beyond sheets and fibers to robust hollow geometries, this work establishes a versatile set of physiologically relevant building blocks for scalable bottom-up assembly of complex, multi-tissue organ-like constructs within a bioassembloid framework. Graphic Abstract
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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) | 0.002 | 0.001 |
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".