Physical Characterization to Improve Scalability and Potential of Anesthetic-Loaded Nanodroplets
Bibliographic record
Abstract
Drug-loaded perfluorocarbon nanodroplets (NDs) can be activated non-invasively by focused ultrasound (FUS) and allow for precise drug-delivery. Anesthetic-loaded NDs and transcranial FUS have previously achieved targeted neuromodulation. To assess the clinical potential of anesthetic-loaded NDs, in depth physical characterization and investigation of storage strategies and triggered-activation is necessary. Pentobarbital-loaded decafluorobutane nanodroplets (PBNDs) with a Definity-derived lipid shell (237 nm; 4.08 × 109 particles/mL) were fabricated and assessed. Change in droplet stability, concentration, and drug-release efficacy were tested for PBNDs frozen at −80 °C over 4 weeks. PBND diameter and the polydispersity index of thawed droplets remained consistent up to 14 days frozen. Cryo-TEM images revealed NDs begin to lose circularity at 7 days, and by 14 days, perfluorocarbon dissolution and lipid fragmentation occurred. The level of acoustic response and drug release decreases through prolonged storage. PBNDs showed no hemolytic activity at clinically relevant concentrations and conditions. At increasing sonication pressures, liquid PBNDs vaporized into gas microbubbles, and acoustic activity at the second harmonic frequency (2 f0) peaked at lower pressures than the subharmonic frequency (1/2 f0). Definity-based PBNDs have been thoroughly characterized, cryo-TEM has been shown to be suitable to image the internal structure of volatile NDs, and PBNDs can be reliably stored at −80 °C for future use up to 7 days without significant degradation, loss of acoustic response, or reduction in ultrasound-triggered drug release.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".