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Record W2021255508 · doi:10.1096/fj.05-3956com

Aβ peptide immunization restores blood‐brain barrier integrity in Alzheimer disease

2006· article· en· W2021255508 on OpenAlexaff
Dara L. Dickstein, Kaan E. Biron, Maki Ujiie, Cheryl G. Pfeifer, Andrew R. Jeffries, Wilfred A. Jefferies

Bibliographic record

VenueThe FASEB Journal · 2006
Typearticle
Languageen
FieldMedicine
TopicAlzheimer's disease research and treatments
Canadian institutionsCanada's Michael Smith Genome Sciences CentreUniversity of British Columbia
Fundersnot available
KeywordsBlood–brain barrierNeuropathologyImmune systemImmunizationMedicineSenile plaquesNeuroinflammationNeuroscienceImmunologyDiseaseAlzheimer's diseasePathologyCentral nervous systemBiologyInternal medicine

Abstract

fetched live from OpenAlex

Immunization with amyloid beta (Abeta) peptides or passive immunization with antibodies against Abeta has been reported to reduce plaque burden, neuritic dystrophy, early Tau pathology, microgliosis as well as reversing learning and memory deficits. This has created a central paradox: how does vaccination in peripheral tissues reduce plaque burden in the brain? No single explanation for these phenomena has yet been presented. To reconcile these observations, we demonstrate that the integrity of the blood-brain barrier (BBB), a structural barrier between the brain and the blood, is compromised in Tg2576 Alzheimer disease (AD) model mice. We immunized Tg2576 mice with Abeta before and after the onset of AD-type neuropathology and observed that BBB permeability, amyloid burden, and microgliosis are decreased in immunized mice. It is concluded that the integrity of the BBB is disrupted in AD mice, and after Abeta immunization the immune system clears Abeta from sources in the brain as it would in peripheral organs lacking barriers. Once Abeta is removed, the integrity of the BBB is restored. The data therefore provide an intellectual framework for understanding how the immune system can clear amyloid deposits from AD brains and suggest new strategies for limiting disease progression in amyloidopathies.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.021
Threshold uncertainty score0.478

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.027
GPT teacher head0.305
Teacher spread0.278 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations111
Published2006
Admission routes1
Has abstractyes

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