Nanoporous PEGDA ink for High-Resolution Additive Manufacturing of Scaffolds for Organ-on-a-Chip
Bibliographic record
Abstract
Abstract Polydimethylsiloxane (PDMS), commonly used in organ-on-a-chip (OoC) systems, faces limitations in replicating complex geometries, hindering its effectiveness in creating 3D OoC models. In contrast, poly(ethylene glycol)diacrylate (PEGDA-250), favored for its fabrication ease and resistance to small molecule absorption, is increasingly used for 3D printing microfluidic devices. However, applications in cell culture have been limited due to poor cell adhesion. Here, we introduce a nanoporous PEGDA ink (P-PEGDA) designed to enhance cell adhesion. P-PEGDA is formulated with a porogen, photopolymerized, followed by the porogen removal. Utilizing P-PEGDA, complex microstructures and membranes as thin as 27 µm were 3D-printed. Porogen concentrations from 10-30% were tested yielding constructs with increasing porosity and oxygen permeability surpassing PDMS, without compromising printing resolution. Tests across four cell lines showed >80% cell viability, with a notable 77-fold increase in MDA-MB-231 cell coverage on the porous scaffolds. Finally, we introduce an OoC model comprising a gyroid scaffold with a central opening filled with a cancer spheroid. This setup, after a 14-day co-culture, demonstrated significant endothelial sprouting and integration within the spheroid. The P-PEGDA formulation is suitable for high-resolution 3D printing of constructs for 3D cell culture and OoC owing to its printability, gas permeability, biocompatibility, and cell adhesion.
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How this classification was reachedexpand
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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".