Localized anesthesia of a specific brain region using ultrasound-responsive barbiturate nanodroplets
Bibliographic record
Abstract
Background: Targeted neuromodulation is a valuable technique for the study and treatment of the brain.Using focused ultrasound to target the local delivery of anesthetics in the brain offers a safe and reproducible option for suppressing neuronal activity.Objective: To develop a potential new tool for localized neuromodulation through the triggered release of pentobarbital from ultrasound-responsive nanodroplets.Method: The commercial microbubble contrast agent, Definity, was filled with decafluorobutane gas and loaded with a lipophilic anesthetic drug, before being condensed into liquid-filled nanodroplets of 210 ± 80 nm.Focused ultrasound at 0.58 MHz was found to convert nanodroplets into microbubbles, simultaneously releasing the drug and inducing local anesthesia in the motor cortex of rats (n=8).Results: Behavioral analysis indicated a 19.1 ± 13% motor deficit on the contralateral side of treated animals, assessed through the cylinder test and gait analysis, illustrating successful local anesthesia, without compromising the blood-brain barrier.Conclusion: Pentobarbital-loaded decafluorobutane-core Definity-based nanodroplets are a potential agent for ultrasound-triggered and targeted neuromodulation.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
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".