Applications of Focused Ultrasound for Reducing Amyloid-β in a Mouse Model of Alzheimer's Disease
Bibliographic record
Abstract
Focused ultrasound (FUS) can temporarily increase blood-brain barrier (BBB) permeability and locally deliver therapeutic agents to the brain. To date, applications of FUS for treatment of Alzheimer’s disease (AD) have not been explored. Here, I propose that FUS can facilitate a rapid reduction in amyloid-β peptide (Aβ) pathology in a mouse model of AD.\n\nFirstly, FUS was used to enhance delivery of an antibody directed against Aβ, which aggregates and forms extracellular plaques. FUS mediated the delivery of antibodies to the targeted right cortex by 4 hours post-treatment and antibodies remained bound to Aβ plaques for 4 days. At 4 days post-treatment, stereological quantification of plaque burden demonstrated a significant reduction of 23%. Secondly, FUS treatment alone resulted in a significant reduction in plaque load (13%). I then investigated effects of FUS that may contribute to Aβ plaque reduction, specifically the delivery of endogenous antibodies to the brain and, activation of microglia and astrocytes.\n\nEndogenous immunoglobulin was found bound to plaques within the treated cortex at 4 days post-FUS. Western blot analysis confirmed that immunoglobulin levels were increased significantly. Further, FUS led to a time-dependent increase in glial response. The expression of ionized calcium-binding adaptor molecule 1, a marker of phagocytic microglia, was increased at 4 hours and 4 days, and it was resolved by 15 days. Astrocytes had a slightly delayed response, with an increase in the expression of glial fibrillary acidic protein at 4 days, which declined by 15 days. After 4 days, microglia and astrocytes had significantly greater volumes and surface areas, signifying enhanced activation in the FUS-treated cortex, without an apparent increase in cell count. Co-localization of Aβ within activated glia revealed a significant increase in Aβ internalization following FUS.\n\nIn conclusion, it was demonstrated that the delivery of exogenous antibodies by FUS, and FUS alone can lead to plaque reduction. Mechanisms by which FUS alone reduces plaque load may include entry of endogenous antibodies to the brain and the induction of a transient glial response. This work details acute effects of FUS that highlight the promise of this delivery method for AD treatment.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 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".