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Record W2322473773 · doi:10.1586/14737175.2015.1028369

Focused ultrasound-mediated drug delivery through the blood–brain barrier

2015· review· en· W2322473773 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueExpert Review of Neurotherapeutics · 2015
Typereview
Languageen
FieldEngineering
TopicUltrasound and Hyperthermia Applications
Canadian institutionsUniversity of TorontoSunnybrook Health Science Centre
FundersNational Institute of Biomedical Imaging and Bioengineering
KeywordsBlood–brain barrierMicrobubblesDrug deliveryMedicineDrug delivery to the brainFocused ultrasoundDrugBrain diseasePharmacologyNeuroscienceDiseaseUltrasoundCentral nervous systemPathologyNanotechnologyPsychologyInternal medicine

Abstract

fetched live from OpenAlex

Despite recent advances in blood-brain barrier (BBB) research, it remains a significant hurdle for the pharmaceutical treatment of brain diseases. Focused ultrasound (FUS) is one method to transiently increase permeability of the BBB to promote drug delivery to specific brain regions. An introduction to the BBB and a brief overview of the methods, which can be used to circumvent the BBB to promote drug delivery, is provided. In particular, we discuss the advantages and limitations of FUS technology and the efficacy of FUS-mediated drug delivery in models of disease. MRI for targeting and evaluating FUS treatments, combined with administration of microbubbles, allows for transient, reproducible BBB opening. The integration of a real-time acoustic feedback controller has improved treatment safety. Successful clinical translation of FUS has the potential to transform the treatment of brain disease worldwide without requiring the development of new pharmaceutical agents.

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.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.894
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.041
GPT teacher head0.319
Teacher spread0.277 · 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