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Record W4367335589 · doi:10.14283/jpad.2023.54

Neuroinflammation Biomarkers in the AT(N) Framework Across the Alzheimer's Disease Continuum

2023· article· en· W4367335589 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueThe Journal of Prevention of Alzheimer s Disease · 2023
Typearticle
Languageen
FieldNeuroscience
TopicNeuroinflammation and Neurodegeneration Mechanisms
Canadian institutionsnot available
FundersCanadian Institutes of Health Research
KeywordsNeuroinflammationContext (archaeology)MicrogliaNeuroscienceDiseaseMedicineAlzheimer's diseaseAmyloid betaBiomarkerInflammationPsychologyBiologyImmunologyPathology

Abstract

fetched live from OpenAlex

In the past years, neuroinflammation has been widely investigated in Alzheimer's disease (AD). Evidence from animal, in vivo and post-mortem studies has shown that inflammatory changes are a common feature of the disease, apparently happening in response to amyloid-beta and tau accumulation. Progress in imaging and fluid biomarkers now allows for identifying surrogate markers of neuroinflammation in living individuals, which may offer unprecedented opportunities to better understand AD pathogenesis and progression. In this context, inflammatory mediators and glial proteins (mainly derived from microglial cells and astrocytes) seem to be the most promising biomarkers. Here, we discuss the biological basis of neuroinflammation in AD, revise the proposed neuroinflammation biomarkers, describe what we have learned from anti-inflammatory drug trials, and critically discuss the potential addition of these biomarkers in the AT(N) framework.

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.

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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
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 score0.358
Threshold uncertainty score0.488

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.062
GPT teacher head0.335
Teacher spread0.273 · 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