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Record W3207084414 · doi:10.1126/scitranslmed.abj4011

MR-guided focused ultrasound enhances delivery of trastuzumab to Her2-positive brain metastases

2021· article· en· W3207084414 on OpenAlexafffund
Ying Meng, Raymond M. Reilly, Rossanna C. Pezo, Maureen Trudeau, Arjun Sahgal, Amit Singnurkar, James Perry, Sten Myrehaug, Christopher B. Pople, Benjamin Davidson, Maheleth Llinas, Chinthaka Hyen, Yuexi Huang, Clement Hamani, Suganth Suppiah, Kullervo Hynynen, Nir Lipsman

Bibliographic record

VenueScience Translational Medicine · 2021
Typearticle
Languageen
FieldEngineering
TopicUltrasound and Hyperthermia Applications
Canadian institutionsHealth Sciences CentrePrincess Margaret Cancer CentreSunnybrook HospitalUniversity of TorontoSunnybrook Health Science Centre
FundersCanadian Institutes of Health Research
KeywordsMedicineTrastuzumabConcomitantDrug deliveryAdverse effectVoxelBreast cancerOncologyInternal medicinePharmacologyNuclear medicineRadiologyCancer

Abstract

fetched live from OpenAlex

In-BzDTPA-NLS-trastuzumab SPECT imaging. The standardized uptake value ratio (SUVR) of MRgFUS-treated lesions increased, on average, by 101 ± 71%, compared to −18 ± 26% in control lesions. MRgFUS enhanced drug uptake in 87 ± 17% of sonicated voxels (>20% increase in SUVR), with up to a 450% voxel-wise increase detected. Control lesions had 8 ± 8% voxels with >20% increase in SUVR. With treatment, unidimensional tumor measurements decreased by 19 ± 12%. This study provides first-in-human evidence of noninvasive, spatially targeted monoclonal antibody delivery across the BBB using MRgFUS, demonstrating the promise of this technology for a broad range of CNS diseases.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

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

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 head0.019
GPT teacher head0.274
Teacher spread0.255 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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

Citations220
Published2021
Admission routes2
Has abstractyes

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Same venueScience Translational MedicineSame topicUltrasound and Hyperthermia ApplicationsFrench-language works237,207