Immunotherapy for Alzheimer’s Disease: IVIg Delivery to the Hippocampus in a Mouse Model of Amyloidosis
Bibliographic record
Abstract
Alzheimer’s disease (AD) is characterized by cognitive decline, neuronal degeneration and pathologies, which include toxic amyloid beta peptides (Aβ) and tau. To date, there is no cure for AD and therapies are only symptomatic. A Phase III clinical trial using intravenous immunoglobulins (IVIg) - natural antibodies collected from the plasma of healthy blood donors and shown to reduce AD-related pathologies in mouse models - recently failed to prevent cognitive decline in people living with AD. IVIg treatment efficacy may be suboptimal due to the blood-brain barrier (BBB), which restricts the bioavailability of IVIg to the brain. We propose to address this problem by administering IVIg intravenously combined with focused ultrasound (FUS) to temporarily increase BBB permeability. Our hypothesis is that IVIg will enter FUS-targeted hippocampi, promote neurogenesis and decrease amyloid pathology in the TgCRND8 (Tg) mouse model of amyloidosis. In 3-month-old Tg mice, we found that the hippocampal bioavailability of IVIg was increased by 7-fold with FUS. Within one week, IVIg was cleared from the hippocampus. We discovered that two weekly treatments of IVIg with FUS promoted hippocampal neurogenesis by 3-fold compared to IVIg-alone, significantly increasing both the proliferation and survival of neural progenitor cells in the dentate gyrus. Compared to IVIg-alone, IVIg-FUS also increased pro-neurogenic cytokine interleukin-2 in the serum and decreased pro-inflammatory cytokine tumor necrosis factor alpha in the hippocampus. Aβ pathology was significantly decreased by IVIg-FUS, IVIg-alone and FUS-alone treatments. The findings in this thesis point to the benefits of coupling IVIg therapy with FUS to enhance its bioavailability and engage neuronal systems, in addition to reducing Aβ pathology and modulating the inflammatory environment. Compared to traditional intravenous administration of IVIg and other amyloid targeted antibodies, brain targeted IVIg treatment using FUS could provide greater benefits in the treatment of AD.
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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) | 0.001 | 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 | 0.001 | 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".