Development of a Synthetic, Injectable Hydrogel to Capture Residual Glioblastoma and Glioblastoma Stem‐Like Cells with CXCL12‐Mediated Chemotaxis
Bibliographic record
Abstract
Glioblastoma (GBM), characterized by high infiltrative capacity, is the most common and deadly type of primary brain tumor in adults. GBM cells, including therapy-resistant glioblastoma stem-like cells (GSCs), invade the healthy brain parenchyma to form secondary tumors even after patients undergo surgical resection and chemoradiotherapy. New techniques are therefore urgently needed to eradicate these residual tumor cells. A thiol-Michael addition injectable hydrogel for compatibility with GBM therapy is previously characterized and optimized. This study aims to develop the hydrogel further to capture GBM/GSCs through CXCL12-mediated chemotaxis. The release kinetics of hydrogel payloads are investigated, migration and invasion assays in response to chemoattractants are performed, and the GBM-hydrogel interactions in vitro are studied. With a novel dual-layer hydrogel platform, it is demonstrated that CXCL12 released from the synthetic hydrogel can induce the migration of U251 GBM cells and GSCs from the extracellular matrix microenvironment and promote invasion into the synthetic hydrogel via amoeboid migration. The survival of GBM cells entrapped deep into the synthetic hydrogel is limited, while live cells near the surface reinforce the hydrogel through fibronectin deposition. This synthetic hydrogel, therefore, demonstrates a promising method to attract and capture migratory GBM cells and GSCs responsive to CXCL12 chemotaxis.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 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".