Metal–Organic Frameworks for Overcoming the Blood–Brain Barrier in the Treatment of Brain Diseases: A Review
Bibliographic record
Abstract
The blood-brain barrier (BBB) plays a vital role in safeguarding the central nervous system by selectively controlling the movement of substances between the bloodstream and the brain, presenting a substantial obstacle for the administration of therapeutic agents to the brain. Recent breakthroughs in nanoparticle-based delivery systems, particularly metal-organic frameworks (MOFs), provide promising solutions for addressing the BBB. MOFs have become valuable tools in delivering medications to the brain with their ability to efficiently load drugs, release them over time, and modify their surface properties. This review focuses on the recent advancements in molecular-based approaches for treating brain disorders, such as glioblastoma multiforme, stroke, Parkinson's disease, and Alzheimer's disease. This paper highlights the significant impact of MOFs in overcoming the shortcomings of conventional brain drug delivery techniques and provides valuable insights for future research in the field of neurotherapeutics.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".