Drug Delivery Systems in the Development of Novel Strategies for Glioblastoma Treatment
Bibliographic record
Abstract
Glioblastoma multiforme (GBM) is a grade IV glioma considered the most fatal cancer of the central nervous system (CNS), with less than a 5% survival rate after five years. The tumor heterogeneity, the high infiltrative behavior of its cells, and the blood-brain barrier (BBB) that limits the access of therapeutic drugs to the brain are the main reasons hampering the current standard treatment efficiency. Following the tumor resection, the infiltrative remaining GBM cells, which are resistant to chemotherapy and radiotherapy, can further invade the surrounding brain parenchyma. Consequently, the development of new strategies to treat parenchyma-infiltrating GBM cells, such as vaccines, nanotherapies, and tumor cells traps including drug delivery systems, is required. For example, the chemoattractant CXCL12, by binding to its CXCR4 receptor, activates signaling pathways that play a critical role in tumor progression and invasion, making it an interesting therapeutic target to properly control the direction of GBM cell migration for treatment proposes. Moreover, the interstitial fluid flow (IFF) is also implicated in increasing the GBM cell migration through the activation of the CXCL12-CXCR4 signaling pathway. However, due to its complex and variable nature, the influence of the IFF on the efficiency of drug delivery systems is not well understood yet. Therefore, this review discusses novel drug delivery strategies to overcome the GBM treatment limitations, focusing on chemokines such as CXCL12 as an innovative approach to reverse the migration of infiltrated GBM. Furthermore, recent developments regarding in vitro 3D culture systems aiming to mimic the dynamic peritumoral environment for the optimization of new drug delivery technologies are highlighted.
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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 | 0.000 |
| 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 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".