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Record W1968739222 · doi:10.1016/j.jalz.2011.09.059

P4‐314: Reduced cerebrovascular tight junction integrity in Alzheimer's disease is directly linked to hypervascularity and angiogenesis

2011· article· en· W1968739222 on OpenAlexaff
Kaan E. Biron, Ray Gopaul, Wilfred A. Jefferies

Bibliographic record

VenueAlzheimer s & Dementia · 2011
Typearticle
Languageen
FieldNeuroscience
TopicBarrier Structure and Function Studies
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsHypervascularityOccludinAngiogenesisTight junctionBlood–brain barrierVascular permeabilityVascularityMedicineNeuroscienceArteriogenesisBiologyNeovascularizationApoptosisCell biologyCancer researchPathologyCentral nervous system

Abstract

fetched live from OpenAlex

A strong link between brain vascularity and Alzheimer's disease (AD) exits due to evidence of reduced blood-brain barrier (BBB) integrity preceding other AD neuropatholgies. Current dogma holds that BBB leakiness in AD is likely due to vascular deterioration and apoptosis. We propose an alternative hypothesis: angiogenesis and hypervascularization underlie increased vascular permeability in AD. Cerebrovascular integrity was characterized in Tg2576 AD model mice by examining the expression of tight junction (TJ) proteins (occludin and ZO-1) in conjunction with markers of apoptosis and angiogenesis. In aged AD mice, a significant increase in the incidence of disrupted TJs was directly linked to an increased microvascular density but not apoptosis, which strongly supports hypervascularity as a basis for BBB dysfunction. Our results demonstrate that AD related BBB disruption is due to neoangiogenesis, resulting in the redistribution of TJs that maintain the barrier thus providing a new paradigm for connecting vascular remodelling with AD.

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)0.000
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.071
GPT teacher head0.266
Teacher spread0.195 · 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 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

Citations0
Published2011
Admission routes1
Has abstractyes

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