3D bioprinting of heterogeneous bi- and tri-layered hollow channels within gel scaffolds using scalable multi-axial microfluidic extrusion nozzle
Why this work is in the frame
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Bibliographic record
Abstract
Abstract One of the primary focuses in recent years in tissue engineering has been the fabrication and integration of vascular structures into artificial tissue constructs. However, most available methodologies lack the ability to create multi-layered concentric conduits inside natural extracellular matrices (ECMs) and gels that replicate more accurately the hierarchical architecture of biological blood vessels. In this work, we present a new microfluidic nozzle design capable of multi-axial extrusion in order to 3D print and pattern bi- and tri-layered hollow channel structures. This nozzle allows, for the first time, for these structures to be embedded within layers of gels and ECMs in a fast, simple and low-cost manner. By varying flow rates (1–6 ml min −1 ), printspeeds (1–16 m min −1 ), and material concentration (25–175 mM and 1.5%–2.5% for calcium chloride and alginate, respectively) we are able to accurately determine the operational printing range as well as achieve a wide range of conduit dimensions (0.69–2.31 mm) that can be printed within a few seconds. Our scalable design allows for multi-axial extrusion and versatility in material incorporation in order to create heterogeneous structures. We demonstrate the ability to print distinct concentric layers of different cell types, namely endothelial cells and fibroblasts. By incorporating various layers of different cell-friendly materials (such as collagen and fibrin) alongside materials with high mechanical strength (i.e. alginate), we were able to increase long-term cell viability and growth without compromising the structural integrity. In this way, we can improve cellular adhesion in our biocompatible constructs as well as allow them to remain structurally sound. We are able to realize complex heterogeneous, hierarchical architectures that have strong potential for use not only in vascular tissue applications, but also in other artificially fabricated tubular or fiber-like structures such as skeletal muscle or nerve conduits.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 |
| 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