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Record W7117129967 · doi:10.1002/alz70855_102284

Modeling Alzheimer's Disease as an Innate Immunity Persistent Activation Disorder

2025· article· en· W7117129967 on OpenAlexaff
Autumn Meek, Matthew Neal, Donald F. Weaver

Bibliographic record

VenueAlzheimer s & Dementia · 2025
Typearticle
Languageen
FieldMedicine
TopicAlzheimer's disease research and treatments
Canadian institutionsUniversity Health NetworkKrembil Foundation
Fundersnot available
KeywordsInnate immune systemImmunityDiseaseCellular immunityAnimal model

Abstract

fetched live from OpenAlex

BACKGROUND: Developing a comprehensive molecular pathogenesis model for Alzheimer's (AD) is a research priority; to-date, a range of different mechanistic proposals including proteopathy, immunopathy, gliopathy, synaptopathy, membranopathy, mitochondriopathy, oxidative stress, and metal dyshomeostasis have been proposed. Rather than unconditionally rejecting the role of any one specific disease mechanisms, the need for an innovative broadly-encompassing model of AD, which harmonizes multiple divergent theories into a single unified comprehensive explanation, emerges as a much-needed milestone on the road to a cure. Characterizing AD as an innate immunity mediated persistent neuroinflammatory disorder may provide such an all-encompassing model. METHOD: We performed a comprehensive series of in silico, in vitro and in vivo studies explicitly evaluating multiple biochemical processes implicated in the pathogenesis of AD: Aβ/tau oligomerization, Aβ-mediated membrane rupture, pro-inflammatory cytokine release, mitochondrial damage, synaptotoxicity, and metal-catalyzed reactive oxygen species generation. These analyses were then systematically probed for unifying mechanistic commonalities. RESULT: The following mechanistic model of AD was devised. Aβ has antimicrobial and immunomodulatory activities, functioning as a component of the innate immune system. In response to various stimuli (infection, trauma, ischemia, air pollution), Aβ is released as an early responder immunopeptide triggering an innate immunity cascade in which Aβ exhibits immunomodulatory and antimicrobial properties (whether bacteria are present, or not), resulting in a misdirected attack upon 'self' neurons, arising from analogous electronegative surface topologies between bacteria and neurons (particularly within the synaptic region), rendering them similarly susceptible to membrane-penetrating attack by antimicrobial peptides such as Aβ. In its role as an antimicrobial-immunomodulatory peptide, Aβ binds to monosialotetrahexosylganglioside (GM1) on the neuronal membrane surface to block viral entry, while intracellularly damaging mitochondria which are evolutionarily derived from endosymbiotic bacteria; concomitantly, Aβ binds to glial cells triggering release of neurotoxic pro-inflammatory cytokines. Following these self-directed attacks, the resulting neuronal breakdown products (particularly Aβ-GM1 co-aggregates) diffuse to adjacent neurons eliciting further release of Aβ, leading to chronic, persistent activation of innate immunity. AD thus emerges as a disorder of persistent innate immunity activation. CONCLUSION: A new unifying, comprehensive model of AD as an innate immunity persistent activation disorder has been devised.

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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0010.001
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 head0.038
GPT teacher head0.329
Teacher spread0.291 · 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 designTheoretical or conceptual
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
Published2025
Admission routes1
Has abstractyes

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