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Record W3217504052 · doi:10.1139/cjc-2021-0180

Ruthenium(II)–arene complexes with chelating quinoline ligands as anti-amyloid agents

2021· article· en· W3217504052 on OpenAlexvenueno aff
Cade J. Meiss, Paige J. Bothwell, Michael I. Webb

Bibliographic record

VenueCanadian Journal of Chemistry · 2021
Typearticle
Languageen
FieldMedicine
TopicAlzheimer's disease research and treatments
Canadian institutionsnot available
Fundersnot available
KeywordsChemistryQuinolineRutheniumChelationPeptideCombinatorial chemistryNeurotoxicityMoleculeAmyloid (mycology)Small moleculeStereochemistryOrganic chemistryBiochemistryToxicityInorganic chemistry

Abstract

fetched live from OpenAlex

Recent recognition of the soluble form of the amyloid-beta (Aβ) peptide as a neurotoxic agent in Alzheimer’s disease (AD) has spurred the development of agents to target this species. Because Aβ is known to chelate metal ions in solution, metal-based therapeutics are uniquely suited to exploit this affinity, where coordination to Aβ has been shown to impact the neurotoxicity of the peptide. Ruthenium(II)–arene complexes are unique candidates for evaluation, as one face of the molecule is blocked by the hydrophobic arene ring, while coordination to the Aβ peptide can occur on the other side of the molecule. We have prepared and evaluated two Ru(II)–arene complexes with chelating quinoline-based ligands, Ru1 and Ru2, for their respective anti-amyloid abilities. Although both complexes decreased the aggregation of soluble Aβ, Ru1 displayed promise in disrupting formed aggregates of the peptide. These findings represent an exciting new avenue for therapeutic development in AD, where both sides of the aggregation equilibrium are affected.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
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 integrity0.0010.001
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 head0.023
GPT teacher head0.283
Teacher spread0.260 · 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 designBench or experimental
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

Citations10
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueCanadian Journal of Chemistry→Same topicAlzheimer's disease research and treatments→French-language works237,207→