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Record W2015112725 · doi:10.1021/cn300191b

Noninvasive and Targeted Drug Delivery to the Brain Using Focused Ultrasound

2013· review· en· W2015112725 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueACS Chemical Neuroscience · 2013
Typereview
Languageen
FieldEngineering
TopicUltrasound and Hyperthermia Applications
Canadian institutionsUniversity of TorontoSunnybrook Health Science Centre
FundersNational Institute of Biomedical Imaging and BioengineeringCanadian Institutes of Health ResearchNational Institutes of Health
KeywordsMicrobubblesBlood–brain barrierDrug delivery to the brainDrug deliveryMedicineNeuroscienceFocused ultrasoundDrugTargeted drug deliveryCentral nervous systemPharmacologyUltrasoundBiologyChemistryInternal medicineRadiology

Abstract

fetched live from OpenAlex

Brain diseases are notoriously difficult to treat due to the presence of the blood-brain barrier (BBB). Here, we review the development of focused ultrasound (FUS) as a noninvasive method for BBB disruption, aiding in drug delivery to the brain. FUS can be applied through the skull to a targeted region in the brain. When combined with microbubbles, FUS causes localized and reversible disruption of the BBB. The cellular mechanisms of BBB disruption are presented. Several therapeutic agents have been delivered to the brain resulting in significant improvements in pathology in models of glioblastoma and Alzheimer's disease. The requirements for clinical translation of FUS will be discussed.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.986
Threshold uncertainty score0.923

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
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 head0.032
GPT teacher head0.262
Teacher spread0.230 · 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