MétaCan
Menu
Back to cohort
Record W2966520883 · doi:10.1186/s40035-019-0164-x

Efficient RT-QuIC seeding activity for α-synuclein in olfactory mucosa samples of patients with Parkinson’s disease and multiple system atrophy

2019· article· en· W2966520883 on OpenAlexfundno aff
Chiara Maria Giulia De Luca, Antonio Emanuele Elia, Sara Maria Portaleone, Federico Angelo Cazzaniga, Edoardo Bistaffa, Elena De Cecco, Joanna Narkiewicz, Giulia Salzano, Olga Carletta, Luigi Romito, Grazia Devigili, Paola Soliveri, Pietro Tiraboschi, Giuseppe Legname, Fabrizio Tagliavini, Roberto Eleopra, Giorgio Giaccone, Fabio Moda

Bibliographic record

VenueTranslational Neurodegeneration · 2019
Typearticle
Languageen
FieldNeuroscience
TopicOlfactory and Sensory Function Studies
Canadian institutionsnot available
FundersNational Institute on AgingNational Institutes of HealthSchool of Medicine, Indiana UniversityUniversità degli Studi di VeronaUniversität WienMichael J. Fox Foundation for Parkinson's ResearchMinistero della SaluteWeston Brain InstituteAlzheimer's Association
KeywordsProgressive supranuclear palsyCorticobasal degenerationAtrophyPathologyParkinson's diseaseTau pathologyNeurologyMedicineDiseaseAlzheimer's diseasePsychiatry

Abstract

fetched live from OpenAlex

BACKGROUND: Parkinson's disease (PD) is a neurodegenerative disorder whose diagnosis is often challenging because symptoms may overlap with neurodegenerative parkinsonisms. PD is characterized by intraneuronal accumulation of abnormal α-synuclein in brainstem while neurodegenerative parkinsonisms might be associated with accumulation of either α-synuclein, as in the case of Multiple System Atrophy (MSA) or tau, as in the case of Corticobasal Degeneration (CBD) and Progressive Supranuclear Palsy (PSP), in other disease-specific brain regions. Definite diagnosis of all these diseases can be formulated only neuropathologically by detection and localization of α-synuclein or tau aggregates in the brain. Compelling evidence suggests that trace-amount of these proteins can appear in peripheral tissues, including receptor neurons of the olfactory mucosa (OM). METHODS: We have set and standardized the experimental conditions to extend the ultrasensitive Real Time Quaking Induced Conversion (RT-QuIC) assay for OM analysis. In particular, by using human recombinant α-synuclein as substrate of reaction, we have assessed the ability of OM collected from patients with clinical diagnoses of PD and MSA to induce α-synuclein aggregation, and compared their seeding ability to that of OM samples collected from patients with clinical diagnoses of CBD and PSP. RESULTS: Our results showed that a significant percentage of MSA and PD samples induced α-synuclein aggregation with high efficiency, but also few samples of patients with the clinical diagnosis of CBD and PSP caused the same effect. Notably, the final RT-QuIC aggregates obtained from MSA and PD samples owned peculiar biochemical and morphological features potentially enabling their discrimination. CONCLUSIONS: Our study provide the proof-of-concept that olfactory mucosa samples collected from patients with PD and MSA possess important seeding activities for α-synuclein. Additional studies are required for (i) estimating sensitivity and specificity of the technique and for (ii) evaluating its application for the diagnosis of PD and neurodegenerative parkinsonisms. RT-QuIC analyses of OM and cerebrospinal fluid (CSF) can be combined with the aim of increasing the overall diagnostic accuracy of these diseases, especially in the early stages.

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)0.001
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 score0.002

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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 head0.071
GPT teacher head0.222
Teacher spread0.151 · 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

Citations193
Published2019
Admission routes1
Has abstractyes

Explore more

Same venueTranslational NeurodegenerationSame topicOlfactory and Sensory Function StudiesFrench-language works237,207