Improving the 3D Printability of Sugar Glass to Engineer Sacrificial Vascular Templates
Bibliographic record
Abstract
A prominent obstacle in scaling up tissue engineering technologies for human applications is engineering an adequate supply of oxygen and nutrients throughout artificial tissues. Sugar glass has emerged as a promising 3D-printable, sacrificial material that can be used to embed perfusable networks within cell-laden matrices to improve mass transfer. To characterize and optimize a previously published sugar ink, we investigated the effects of sucrose, glucose, and dextran concentration on the glass transition temperature ( T g ), printability, and stability of 3D-printed sugar glass constructs. We identified a sucrose ink formulation with a significantly higher T g (40.0 ± 0.9°C) than the original formulation (sucrose-glucose blend, T g = 26.2 ± 0.4°C), which demonstrated a pronounced improvement in printability, resistance to bending, and final print stability, all without changing dissolution kinetics and decomposition temperature. This formulation allowed printing of 10-cm-long horizontal cantilever filaments, which can enable the printing of complex vascular segments along the x-, y-, and z-axes without the need for supporting structures. Vascular templates with a single inlet and outlet branching into nine channels were 3D printed using the improved formulation and subsequently used to generate perfusable alginate constructs. The printed lattice showed high fidelity with respect to the input geometry, although with some channel deformation after alginate casting and gelation—likely due to alginate swelling. Compared with avascular controls, no significant acute cytotoxicity was noted when casting pancreatic beta cell-laden alginate constructs around improved ink filaments, whereas a significant decrease in cell viability was observed with the original ink. The improved formulation lends more flexibility to sugar glass 3D printing by facilitating the fabrication of larger, more complex, and more stable sacrificial networks. Rigorous characterization and optimization methods for improving sacrificial inks may facilitate the fabrication of functional cellular constructs for tissue engineering, cellular biology, and other biomedical applications.
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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".