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Record W2120259248 · doi:10.1002/elan.201200216

Analysis of Amyloid Beta Aggregation Kinetics Using Sym‐Triazine β‐Sheet Inhibitors

2012· article· en· W2120259248 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.

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

Bibliographic record

VenueElectroanalysis · 2012
Typearticle
Languageen
FieldMedicine
TopicAlzheimer's disease research and treatments
Canadian institutionsThe Scarborough HospitalUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of CanadaAlzheimer Society
KeywordsFibrilChemistryBiophysicsKineticsAmyloid (mycology)TriazineNucleationCyclic voltammetryIn vitroRedoxAmyloid betaElectrochemistryPeptideBiochemistryElectrodePolymer chemistryInorganic chemistryBiologyOrganic chemistryPhysical chemistry

Abstract

fetched live from OpenAlex

Abstract AD (Alzheimer’s disease) is a progressive neurodegenerative disorder characterized by the cerebral accumulation of fibrillar amyloid‐beta (Aβ) aggregates. Here we present the electrochemistry of two novel sym‐triazine derivatives (TAE‐1, TAE‐2) as modulators of Aβ 1–42 aggregation in vitro. Incubation studies conducted at physiological conditions demonstrated strong inhibition of β‐sheet fibril formation. Uniquely, square‐wave voltammetry indicated progressive changes in the surface‐availability of amyloid‐intercalated triazines for oxidation, mediated by competing peptide self‐assembly. Time‐resolved voltammetric analysis showed increasing anodic peak currents (≥3‐fold) and progressive shifts in redox potentials, measured over 24 h. The more potent aggregation modulator (TAE‐2) showed prolonged association during the pre‐nucleation states of Aβ.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.432
Threshold uncertainty score0.730

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.004
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.026
GPT teacher head0.319
Teacher spread0.293 · 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