A Mixing System for Uniform, Reproducible Viscous Bioinks Preparation
Why this work is in the frame
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Bibliographic record
Abstract
Rationale: Extrusion 3D bioprinting is an additive manufacturing tissue engineering technique that uses cell-laden viscous biomaterials known as bioinks. Manually mixing cell suspensions into viscous biomaterials can be challenging due to the high viscosity ratio between the two fluids. Static mixers are an attractive approach as they can quickly and reproducibly mix two fluids, including those with a high viscosity ratio. However, static mixers intended for viscous applications have not been comprehensively investigated for bioink preparation. This work evaluates the mixing performance, shear stress, and cell viability using four different types of static mixers intended for high viscosity mixing. Methods: Three static mixers intended for mixing viscous solutions were designed based on the Sulzer SMX, Ross ISG, and serpentine mixers and fabricated using resin 3D printing. CELLMIXER, a Kenics-style static mixer commercially available through CELLINK, was used as a comparator. Two biomaterial inks based on PEGDA and methacrylated gelatin were used to characterize each mixer’s performance. Shear stress was estimated via fluid dynamics simulations using shear-thinning attributes measured experimentally through rheology. Mixing effectiveness was evaluated using fluorescent beads, from which the most effective design was chosen for live cell mixing experiments. Viability of cell lines (A549 and NIH-3T3) and primary human lung fibroblasts was evaluated postmixing. A demonstration of extrusion bioprinting was performed using the mixed bioinks. Results: The SMX-style mixer provided the most uniform mixing and yielded the lowest simulated shear stresses among the designs investigated. A549, NIH-3T3, and primary human lung fibroblasts maintained viabilities above 96% postmixing using the SMX-style mixer with a more homogeneous cell distribution compared to the CELLMIXER. The bioprinting demonstration validated our mixing system for producing viable tissue constructs with evenly distributed cells. Conclusions: We present a simple, reproducible, and flexible system for mixing cells into viscous biomaterial inks. Our approach facilitates standardized fabrication of cell-laden tissue constructs to ensure consistency in the growing field of extrusion 3D bioprinting.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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