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Record W2004209700 · doi:10.1186/1750-1326-7-s1-o7

Upregulation of astrocytic α7 nicotinic receptors in Alzheimer's disease brain- possible relevant to amyloid pathology

2012· article· en· W2004209700 on OpenAlexafffund
Wenfeng Yu, Naguib Mechawar, Slavica Krantic, Jean‐Guy Chabot, Rémi Quirion

Bibliographic record

VenueMolecular Neurodegeneration · 2012
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicNicotinic Acetylcholine Receptors Study
Canadian institutionsMcGill UniversityDouglas Mental Health University Institute
FundersCanadian Institutes of Health Research
KeywordsSenile plaquesNeuroscienceNicotinic agonistAlzheimer's diseasePathogenesisAmyloid (mycology)PathologyReceptorMedicineBiologyDiseaseInternal medicine

Abstract

fetched live from OpenAlex

Background Alzheimer’s disease (AD) is characterized by extracellular deposits of b-amyloid (Ab), intracellular neurofibrillary tangles and inflammation response. The a7 nicotinic receptors (nAChRs) were proposed to be directly relevant to the pathogenesis of AD by interacting with Ab. The a7 nAChRs and Ab1-42 are co-localized in neuritic plaques and neurons and can form a high affinity stable complex. The up-regulation of a7 nAChRs on activated astrocytes has been reported in the AD brain. However, because of the poor specificity of currently available a7 nAChR antibodies, it is important to develop new ways to investigate the discrete distribution of a7 nAChRs in nervous tissue.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.007
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 integrity0.0000.000
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 head0.012
GPT teacher head0.263
Teacher spread0.251 · 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.

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

Citations13
Published2012
Admission routes2
Has abstractyes

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