MétaCan
Menu
Back to cohort
Record W3018983332 · doi:10.32396/usurj.v6i2.425

Alpha-synuclein promotes dopaminergic neuron death in Parkinson’s disease through microglial and NLRP3 activation

2020· article· en· W3018983332 on OpenAlexaffvenue
Sarah R. Klein

Bibliographic record

VenueUSURJ University of Saskatchewan Undergraduate Research Journal · 2020
Typearticle
Languageen
FieldMedicine
TopicParkinson's Disease Mechanisms and Treatments
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsSubstantia nigraPars compactaNeurodegenerationNeuroinflammationAlpha-synucleinParkinson's diseaseNeuroscienceDopaminergicInflammasomeDopamineMicrogliaMedicineDiseaseBiologyInflammationPathologyImmunology

Abstract

fetched live from OpenAlex

Parkinson’s disease (PD) is a progressive neurodegenerative disorder that involves the death of dopaminergic neurons in the substantia nigra pars compacta (SNpc). After neuronal death, the subsequent reduction of dopamine levels in the brain induces motor deficits characteristic of this hypokinetic disorder. Although there is currently no known cause of PD, alpha-synuclein appears to have a prominent role in both microglial and NLRP3 inflammasome activation. The consequential release of the pro-inflammatory cytokine interleukin-1β (IL-1β) has been demonstrated to be responsible for neuroinflammation and neurodegeneration in PD. The present review highlights the role of alpha-synuclein aggregates in Parkinson’s disease pathogenesis. The PD alpha-synuclein preformed fibril (PFF) animal model permits the specific targeting of alpha-synuclein-mediated microglial and NLRP3 inflammasome activation in newly designed therapies. Studies using this model suggest MCC950 and its analogs as a potential new treatment to prevent neurodegeneration in Parkinson’s disease.

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 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 score0.154
Threshold uncertainty score0.834

Codex and Gemma teacher scores by category

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 integrity0.0000.001
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 head0.050
GPT teacher head0.287
Teacher spread0.237 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations3
Published2020
Admission routes2
Has abstractyes

Explore more

Same venueUSURJ University of Saskatchewan Undergraduate Research JournalSame topicParkinson's Disease Mechanisms and TreatmentsFrench-language works237,207