Effect of Chitosan on Alginate-Based Macroporous Hydrogels for the Capture of Glioblastoma Cancer Cells
Bibliographic record
Abstract
Glioblastoma multiforme is a type of brain cancer associated with a very low survival rate since a large number of cancer cells remain infiltrated in the brain despite the treatments currently available. This work presents a macroporous hydrogel trap, destined to be implanted in the surgical cavity following tumor resection and designed to attract and retain cancer cells, in order to eliminate them afterward with a lethal dose of stereotactic radiotherapy. The biocompatible hydrogel formulation comprises sodium alginate (SA) and chitosan (CHI) bearing complementary electrostatic charges and stabilizing the gels in saline and cell culture media, as compared to pristine SA gels. The highly controlled and interconnected porosity, characterized by X-ray microCT, yields mechanical properties comparable to those of brain tissues and allows F98 glioblastoma cells to penetrate the gels within the entire volume, as confirmed by fluorescence microscopy. The addition of a grafted -RGD peptide on SA, combined with CHI, significantly enhances the adhesion and retention of F98 cells within the gels. Overall, the best compromise between low proliferation and a high level of accumulation and retention of F98 cells was obtained with the hydrogel formulated with 1% SA and 0.2% CHI, without the -RGD adhesion peptide.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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 source (direct Gemma or distilled Codex), 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".