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Record W3095606106 · doi:10.1002/trc2.12100

Amyloid beta is an early responder cytokine and immunopeptide of the innate immune system

2020· article· en· W3095606106 on OpenAlexaff
Donald F. Weaver

Bibliographic record

VenueAlzheimer s & Dementia Translational Research & Clinical Interventions · 2020
Typearticle
Languageen
FieldNeuroscience
TopicNeuroinflammation and Neurodegeneration Mechanisms
Canadian institutionsUniversity of TorontoUniversity Health Network
Fundersnot available
KeywordsInnate immune systemChemokineImmunologyCytokineBiologyImmune systemEffectorNeuroscienceCell biology

Abstract

fetched live from OpenAlex

A molecular level conceptualization of the pathogenesis of Alzheimer's disease (AD) remains elusive with many competing hypotheses, particularly via proteopathic and immunopathic mechanisms. However, these need not be competitive. If amyloid beta (Aβ) is regarded as an "early responder cytokine," then proteopathic considerations become encompassed within an overarching hybrid proteopathic-immunopathic mechanism. As argued in this commentary, Aβ is in fact a molecular constituent of the innate immune system. Aβ is an antimicrobial peptide (AMP) functioning not only as a killer peptide, but also as a modulatory immunopeptide. Aβ satisfies the definition of a cytokine, exhibiting interdependency with other cytokines. Aβ also satisfies the functional definition of a chemokine, existing within the AMP-chemokine spectrum. Aβ, like conventional cytokines, both binds to and is released by microglial cells. Finally, Aβ interacts with the complement and Toll-like receptor systems analogously to established cytokines. Aβ may thus be regarded as an effector molecule of innate immunity.

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)0.002
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.002
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0010.000

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 head0.406
GPT teacher head0.454
Teacher spread0.048 · 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

Citations43
Published2020
Admission routes1
Has abstractyes

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