Focused Ultrasound Enhances Targeted Gene Delivery of Intravenous AAV to the Brain
Bibliographic record
Abstract
BACKGROUND: Recombinant adeno-associated viruses (AAVs) hold promise for brain disorders but often require intracranial injection, limiting therapeutic reach and being invasive. Intravenous (i.v.) AAV delivery is restricted by the blood-brain barrier (BBB), reducing efficiency. Recent AAV variants can cross the BBB, enabling widespread brain transduction. MRI-guided focused ultrasound (FUS) transiently modulates BBB permeability, enhancing gene delivery in small or large brain regions targeted. HYPOTHESIS: We hypothesize that combining IV BBB-penetrating AAVs with FUS will optimize gene delivery, enabling both widespread and region-specific transduction for neurodegenerative diseases. METHODS: Three-month-old C57BL/6 mice received i.v. AAV-PHP.V1.CAG.TdTomato (V1) and AAV9.CAG.EYFP, followed by FUS targeting various brain regions. Immunohistochemistry and confocal microscopy were done 3 weeks post-delivery. RESULTS: Our findings demonstrate that FUS enhances targeted gene delivery for AAV9 and V1 while maintaining global expression in the brain for V1, offering a non-invasive strategy for precise (AAV9) or widespread and locally enriched (V1) gene therapy. CONCLUSION: This approach could improve treatments for neurodegenerative disorders such as Alzheimer's and Parkinson's disease.
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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) | 0.002 | 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".