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Record W2046674326 · doi:10.1071/ch10334

Ion Mobility Mass Spectrometry Studies of the Inhibition of Alpha Synuclein Amyloid Fibril Formation by (–)-Epigallocatechin-3-Gallate

2011· article· en· W2046674326 on OpenAlexaff
Yanqin Liu, Lam Ho, John A. Carver, Tara L. Pukala

Bibliographic record

VenueAustralian Journal of Chemistry · 2011
Typearticle
Languageen
FieldMedicine
TopicAlzheimer's disease research and treatments
Canadian institutionsThe Audio Recording Academy
Fundersnot available
KeywordsChemistryFibrilGallateBiophysicsEpigallocatechin gallateAmyloid fibrilIon-mobility spectrometryAmyloid (mycology)Alpha-synucleinMass spectrometryProtein aggregationConformational changeCrystallographyBiochemistryAmyloid βPolyphenolChromatographyParkinson's disease

Abstract

fetched live from OpenAlex

Ion mobility-mass spectrometry (IM-MS) is emerging as an important biophysical technique for the structural analysis of proteins and their assemblies, in particular for structurally heterogeneous systems such as those on the protein misfolding and aggregation pathway. Using IM-MS we have monitored amyloid fibril formation of A53T α-synuclein, a mutant synuclein protein associated with Parkinson’s disease, and identified that a conformational change towards a more compact structure occurs during the initial stages of aggregation. Binding of A53T α-synuclein to a flavenoid based amyloid fibril inhibitor, (–)-epigallocatechin-3-gallate, has been observed with a 1:1 stoichiometry. By analysis of ion collision cross-sections, we show epigallocatechin gallate binding prevents protein conformational change, and in turn decreases the formation of fibrillar aggregates.

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 score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.050
GPT teacher head0.309
Teacher spread0.259 · 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

Citations21
Published2011
Admission routes1
Has abstractyes

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Same venueAustralian Journal of ChemistrySame topicAlzheimer's disease research and treatmentsFrench-language works237,207