MétaCan
Menu
Back to cohort
Record W4383889912 · doi:10.1039/d3md00096f

Druggable targets for the immunopathy of Alzheimer's disease

2023· review· en· W4383889912 on OpenAlex
Donald F. Weaver

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueRSC Medicinal Chemistry · 2023
Typereview
Languageen
FieldNeuroscience
TopicNeuroinflammation and Neurodegeneration Mechanisms
Canadian institutionsUniversity of TorontoUniversity Health Network
FundersCanadian Institutes of Health ResearchKrembil FoundationWeston Brain Institute
KeywordsDruggabilityDiseaseComputational biologyNeuroscienceNeuroinflammationMechanism (biology)BioinformaticsIdentification (biology)NeurodegenerationMedicineBiologyGeneGeneticsPathology

Abstract

fetched live from OpenAlex

Alzheimer's disease (AD) is one of the leading threats to the health and socioeconomic well-being of humankind. Though research to develop disease modifying therapies for AD has traditionally focussed on the misfolding and aggregation of proteins, this approach has failed to yield a definitively curative agent. Accordingly, the search for additional or alternative approaches is a medicinal chemistry priority. Dysfunction of the brain's neuroimmune-neuroinflammation axis has emerged as a leading contender. Neuroimmunity however is mechanistically complex, rendering the recognition of candidate receptors a challenging task. Herein, a review of the role of neuroimmunity in the biomolecular pathogenesis of AD is presented with the identification of a 'druggable dozen' targets; in turn, each identified target represents one or more discrete receptors centred on a common biochemical mechanism. The druggable dozen is composed of both cellular and molecular messenger targets, with a 'targetable ten' microglial targets as well as two cytokine-based targets. For each target, the underlying molecular basis, with a consideration of strengths and weaknesses, is considered.

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)0.000
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.750
Threshold uncertainty score0.964

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.125
GPT teacher head0.355
Teacher spread0.230 · 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