Transgene distribution and immune response after ultrasound delivery of rAAV9 and PHP.B to the brain in a mouse model of amyloidosis
Bibliographic record
Abstract
Efficient disease-modifying treatments for Alzheimer disease, the most common form of dementia, have yet to be established. Gene therapy has the potential to provide the long-term production of therapeutic in the brain following a single administration. However, the blood-brain barrier poses a challenge for gene delivery to the adult brain. We investigated the transduction efficiency and immunological response following non-invasive gene-delivery strategies to the brain of a mouse model of amyloidosis. Two emerging technologies enabling gene delivery across the blood-brain barrier were used to establish the minimal vector dosage required to reach the brain: (1) focused ultrasound combined with intravenous microbubbles, which increases the permeability of the blood-brain barrier at targeted sites and (2) the recombinant adeno-associated virus (rAAV)-based capsid named rAAV-PHP.B. We found that equal intravenous dosages of rAAV9 combined with focused ultrasound, or rAAV-PHP.B, were required for brain gene delivery. In contrast to rAAV9, focused ultrasound did not decrease the rAAV-PHP.B dosage required to transduce brain cells in a mouse model of amyloidosis. The non-invasive rAAV delivery to the brain using rAAV-PHP.B or rAAV9 with focused ultrasound triggered an immune reaction including major histocompatibility complex class II expression, complement system and microglial activation, and T cell infiltration.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".