Rapid Short-Pulses of Focused Ultrasound and Microbubbles Deliver a Range of Agent Sizes to the Brain
Bibliographic record
Abstract
Abstract Focused ultrasound and microbubbles can non-invasively and locally deliver therapeutics and imaging agents across the blood-brain barrier. Uniform treatment and minimal adverse bioeffects are critical to achieve reliable doses and enable safe routine use of this technique. Towards these aims, we have previously designed a rapid short-pulse ultrasound sequence and used it to deliver a 3 kDa model agent to mouse brains. We observed a homogeneous distribution in delivery and blood-brain barrier closing within 10 minutes. However, many therapeutics and imaging agents are larger than 3 kDa, such as antibody fragments and antisense oligonucleotides. Here, we evaluate the feasibility of using rapid short-pulses to deliver higher-molecular-weight model agents. 3, 10 and 70 kDa dextrans were successfully delivered to mouse brains, with decreasing doses and more heterogeneous distributions with increasing agent size. Minimal extravasation of endogenous albumin (66.5 kDa) was observed, while immunoglobulin (~ 150 kDa) and PEGylated liposomes (97.9 nm) were not detected. This study indicates that rapid short-pulses are versatile and, at an acoustic pressure of 0.35 MPa, can deliver therapeutics and imaging agents of sizes up to a hydrodynamic diameter between 8 nm (70 kDa dextran) and 11 nm (immunoglobulin). Increasing the acoustic pressure can extend the use of rapid short-pulses to deliver agents beyond this threshold, with little compromise on safety. This study demonstrates the potential for deliveries of higher-molecular-weight therapeutics and imaging agents using rapid short-pulses.
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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".