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Record W4401808255 · doi:10.3390/nano14171379

Metal–Organic Frameworks for Overcoming the Blood–Brain Barrier in the Treatment of Brain Diseases: A Review

2024· review· en· W4401808255 on OpenAlexaff
Hafezeh Nabipour, Sohrab Rohani

Bibliographic record

VenueNanomaterials · 2024
Typereview
Languageen
FieldChemistry
TopicMetal-Organic Frameworks: Synthesis and Applications
Canadian institutionsWestern University
Fundersnot available
KeywordsBrain diseaseDrug deliveryBlood–brain barrierSafeguardingMedicineNeuroscienceDiseaseDrug delivery to the brainNanotechnologyCentral nervous systemIntensive care medicineMaterials sciencePsychologyPathology

Abstract

fetched live from OpenAlex

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.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.919
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0040.000

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.

Opus teacher head0.033
GPT teacher head0.331
Teacher spread0.298 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreReview

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".

Quick stats

Citations16
Published2024
Admission routes1
Has abstractyes

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