Impact of simulated brain interstitial fluid flow on the chemokine CXCL12 release from an alginate-based hydrogel in a new 3D in vitro model
Bibliographic record
Abstract
Introduction: Extensive investigation has been undertaken regarding drug delivery systems for the management of glioblastoma multiforme (GBM). The infiltrative behavior of GBM cells within the brain tissue is primarily attributed to their heterogeneity, the movement of interstitial fluid (IFF), and the presence of chemokines. These factors contribute to the limited effectiveness of current conventional treatments. To address the dissemination of GBM cells, a proposed therapeutic approach involves utilizing a controlled release gradient of CXC-chemokine-ligand-12 (CXCL12). However, the impact of IFF on GBM cell migration within the brain underscores its critical importance as a significant parameter, which, surprisingly, has not been extensively studied in the context of localized drug delivery targeting the brain. Methods: Hydrogels are known for their inherent capacity to entrap various agents and exert precise control over their subsequent release. In the present investigation, we aimed to elucidate the release kinetics of CXCL12, whether in its free form or encapsulated within nanoparticles, from alginate-based hydrogels, both under static and dynamic conditions. To investigate the impact of convective forces mimicking the interstitial fluid flow (IFF) within the peritumoral environment of the brain, a three-dimensional in vitro model was developed. This model enabled the evaluation of CXCL12 release as a function of time and position, specifically accounting for the contribution of simulated IFF on the release behavior. Results: We first demonstrated that the release kinetic profiles under static culture conditions were independent of the initial mass loading and the predominant phenomenon occurring was diffusion. Subsequently, we investigated the release of CXCL12, which was loaded into Alginate/Chitosan-Nanoparticles (Alg/Chit-NPs) and embedded within an alginate hydrogel matrix. Mathematical modeling results also indicated the presence of electrostatic interactions between alginate and CXCL12. The Alg/Chit-NPs effectively slowed down the initial burst release, leading to a reduction in the diffusion coefficient of CXCL12. To further study the release behavior, we developed a perfusion bioreactor with a unique culture chamber designed to recapitulate the peritumoral environment and varied the fluid flow rates at 0.5 µL/min, 3 µL/min, 6.5 µL/min, and 10 µL/min. As the flow rate increased, the cumulative amount of released CXCL12 also increased for all three initial mass loadings. Beyond 3 µL/min, convection became the dominant mechanism governing CXCL12 release, whereas below this threshold, diffusion played a more prominent role. Conclusion: The indirect perfusion flow had a crucial impact on CXCL12 release and distribution inside the hydrogel in and against its direction. This system highlights the importance of considering the IFF in brain targeting delivery system and will be used in the future to study GBM cell behaviors in response to CXCL12 gradient.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".