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Record W2998015000 · doi:10.1038/s41598-019-55629-2

The effect of transcranial focused ultrasound target location on the acoustic feedback control performance during blood-brain barrier opening with nanobubbles

2019· article· en· W2998015000 on OpenAlexaff
Bingbing Cheng, Chenchen Bing, Rajiv Chopra

Bibliographic record

VenueScientific Reports · 2019
Typearticle
Languageen
FieldEngineering
TopicUltrasound and Hyperthermia Applications
Canadian institutionsUniversity of Calgary
FundersCancer Prevention and Research Institute of Texas
KeywordsMicrobubblesUltrasoundTranscranial DopplerFocused ultrasoundOscillation (cell signaling)Computer scienceAcousticsBiomedical engineeringMaterials scienceNeuroscienceMedicineChemistryPsychologyPhysicsRadiology

Abstract

fetched live from OpenAlex

Abstract Real-time acoustic feedback control based on harmonic emissions of stimulated microbubbles may be important for facilitating the clinical adoption of focused ultrasound (FUS)-induced blood-brain barrier (BBB) opening, both to ensure safe acoustic exposures, and to achieve repeatable and consistent opening. Previously our group demonstrated that successful BBB opening was achievable with both commercially available microbubbles and custom-made nanobubbles under acoustic feedback control. In a recent study, we demonstrated the acoustic control performance was not sensitive to the nanobubble concentration within 10 9 –10 11 bubbles/ml. The goal of this study was to examine the effect of the ultrasound target location in the rat brain on the acoustic control quality during BBB opening with nanobubbles. Temporal analysis of the received acoustic signals during each ultrasound pulse indicated that stable nanobubble oscillation was present throughout the entire 10 ms ultrasound exposure. The acoustic feedback control signals were very sensitive to the brain spatial location in rats. There appears to be a shared pattern of acoustic control stability in the brain across different animals, suggesting anatomical features are an underlying cause. The findings emphasize the importance of tuning acoustic feedback control algorithms for specific rodent brain regions of interest to ensure optimal performance.

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)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.099
Threshold uncertainty score0.429

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.002
GPT teacher head0.166
Teacher spread0.164 · 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.

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

Citations21
Published2019
Admission routes1
Has abstractyes

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