MRI-guided Disruption of the Blood-brain Barrier using Transcranial Focused Ultrasound in a Rat Model
Bibliographic record
Abstract
Focused ultrasound (FUS) disruption of the blood-brain barrier (BBB) is an increasingly investigated technique for circumventing the BBB(1-5). The BBB is a significant obstacle to pharmaceutical treatments of brain disorders as it limits the passage of molecules from the vasculature into the brain tissue to molecules less than approximately 500 Da in size(6). FUS induced BBB disruption (BBBD) is temporary and reversible(4) and has an advantage over chemical means of inducing BBBD by being highly localized. FUS induced BBBD provides a means for investigating the effects of a wide range of therapeutic agents on the brain, which would not otherwise be deliverable to the tissue in sufficient concentration. While a wide range of ultrasound parameters have proven successful at disrupting the BBB(2,5,7), there are several critical steps in the experimental procedure to ensure successful disruption with accurate targeting. This protocol outlines how to achieve MRI-guided FUS induced BBBD in a rat model, with a focus on the critical animal preparation and microbubble handling steps of the experiment.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".