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Record W2083872992 · doi:10.1155/2012/630182

Amyloid Beta and Tau Proteins as Therapeutic Targets for Alzheimer’s Disease Treatment: Rethinking the Current Strategy

2012· article· en· W2083872992 on OpenAlexafffund
Siddhartha Mondragón‐Rodríguez, George Perry, Xiongwei Zhu, Jannic Boehm

Bibliographic record

VenueInternational Journal of Alzheimer s Disease · 2012
Typearticle
Languageen
FieldMedicine
TopicAlzheimer's disease research and treatments
Canadian institutionsUniversité de MontréalMcGill UniversityDouglas Mental Health University Institute
FundersCanadian Institutes of Health ResearchAlzheimer SocietyAlzheimer's Association
KeywordsMedicineDiseaseAmyloid (mycology)Amyloid betaAlzheimer's diseaseCurrent (fluid)BETA (programming language)BioinformaticsNeuroscienceInternal medicinePathologyPsychologyComputer scienceBiology

Abstract

fetched live from OpenAlex

Alzheimer's disease (AD) is defined by the concurrence of accumulation of abnormal aggregates composed of two proteins: Amyloid beta (Aβ) and tau, and of cellular changes including neurite degeneration and loss of neurons and cognitive functions. Based on their strong association with disease, genetically and pathologically, it is not surprising that there has been a focus towards developing therapies against the aggregated structures. Unfortunately, current therapies have but mild benefit. With this in mind we will focus on the relationship of synaptic plasticity with Aβ and tau protein and their role as potential targets for the development of therapeutic drugs. Finally, we will provide perspectives in developing a multifactorial strategy for AD treatment.

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)0.009
metaresearch head score (Gemma)0.003
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: none
Teacher disagreement score0.009
Threshold uncertainty score0.046

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0020.001
Science and technology studies0.0010.004
Scholarly communication0.0050.008
Open science0.0020.003
Research integrity0.0050.007
Insufficient payload (model declined to judge)0.0040.001

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 head0.081
GPT teacher head0.383
Teacher spread0.302 · 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

Citations68
Published2012
Admission routes2
Has abstractyes

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