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Record W7132886204

Gene Immunotherapy Against Amyloid Pathology in a Mouse Model of Alzheimer’s Disease

2021· dissertation· W7132886204 on OpenAlexaff
Zeinab Noroozian

Bibliographic record

VenueTSpace · 2021
Typedissertation
Language
FieldMedicine
TopicMultiple Sclerosis Research Studies
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsImmunotherapyMicrogliaAntibodyNeuriteDiseaseIn vitroGenetic enhancementIn vivoImmunogenicityImmune system
DOInot available

Abstract

fetched live from OpenAlex

Alzheimer’s disease is characterized by progressive accumulation of amyloid-beta peptides (Aβ) in the brain and severe cognitive decline. Several anti-Aβ immunotherapies failed to efficiently slow disease progression and improve cognition in clinical trials. The blood-brain barrier (BBB) limits the bioavailability of intravenously administered antibodies to the brain, potentially contributing to reduce efficacy. I hypothesized that engineering neurons to continuously produce anti-Aβ antibodies in the brain will increase therapeutic efficacy. To evaluate this hypothesis, I developed a gene immunotherapy approach; delivering adeno-associated virus 6 (AAV6) that encoded for a recombinant anti-Aβ single-chain variable fragment (rSol), AAV6-rSol, into the brain of TgCRND8 mice, a preclinical model of amyloidosis. rSol was derived from Solanezumab, a human antibody against soluble Aβ. I tested my hypothesis by completing three objectives. Firstly, I designed, constructed, and purified rSol, and then I confirmed its high affinity for soluble Aβ. Secondly, I engineered rSol under the control of synapsin promoter into an AAV6 and demonstrated that the expression of rSol was neuronal-specific in vitro and in vivo. In TgCRND8 mice, I found that rSol had prolonged neuronal expression for over 14 months, efficiently preventing Aβ deposition into Aβ plaques, reducing associated dystrophic neurites and decreasing the activation of astrocytes and microglia at 6-month post-intracranial delivery in neonates. Thirdly, I delivered AAV6-rSol into the brain of adult TgCRND8 mice non-invasively and evaluated the impact of this treatment on mice behaviour. Focused ultrasound (FUS), guided by magnetic resonance imaging (MRIgFUS) was used to temporarily increase the permeability of the BBB, allowing AAV6-rSol to reach the brain. No amelioration was detected in nest building activity and locomotion of TgCRND8 mice. Low gene delivery in these experiments likely contributed to the lack of robust effect on behaviour. I suggest that MRIgFUS-mediated gene delivery can be optimized using higher AAV dosage or more efficient serotypes such as AAV9, guided by the methodological protocol outlined in this thesis. In conclusion, I developed a neuronal gene immunotherapy with therapeutic efficacy against Aβ deposition. Combined with promising non-invasive gene delivery to the brain, gene immunotherapy could lead to clinical benefits in the future.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0020.001

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.

Opus teacher head0.074
GPT teacher head0.384
Teacher spread0.310 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2021
Admission routes1
Has abstractyes

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