Electrospun and 3D printed scaffolds based on biocompatible polymers for 3D cultivation of glioblastoma cells in vitro
Bibliographic record
Abstract
Additive manufacturing techniques capable of fabricating biocompatible scaffolds with a given submicron/micron/supramicron structure are of growing interest for biomedical applications, including tissue engineering and tumor biology studies. Here, we propose antisolvent 3D printing and electrospinning techniques to obtain biopolymer scaffolds with different structural, mechanical, and surface properties to compare the cultivation patterns of glioblastoma cells. We found that human G01 cells, derived from human glioblastoma tumor tissue, were able to colonize the scaffolds in a time-dependent manner; the cells showed high viability as confirmed by colorimetric MTT assay, confocal fluorescence microscopy, and scanning electron microscopy data. Electrospun collagen scaffolds (low porosity, thin 2.75±0.22 μm fibers, low Young's modulus 0.076±0.033 MPa) provided monolayer-like growth of G01 glioblastoma cells with dense cell-cell contacts, while 3D-printed PLGA scaffolds (high porosity, thick ∼150 µm fibers, high Young's modulus 18±2 MPa) stimulated glioblastoma-specific spindle-like morphology. All scaffolds were non-toxic to cells and maintained cell growth for at least 2 weeks. The developed scaffolds could be further used for tumor research as a 3D model of glioblastoma in vitro or for tissue engineering of brain injury.
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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) | 0.000 | 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 | 0.000 | 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 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".