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Record W2998859235 · doi:10.1093/braincomms/fcz052

Neuron-autonomous susceptibility to induced synuclein aggregation is exacerbated by endogenous Lrrk2 mutations and ameliorated by Lrrk2 genetic knock-out

2020· article· en· W2998859235 on OpenAlexafffund
Sarah MacIsaac, Thaiany Quevedo Melo, Yuting Zhang, Mattia Volta, Matthew J. Farrer, Austen J. Milnerwood

Bibliographic record

VenueBrain Communications · 2020
Typearticle
Languageen
FieldMedicine
TopicParkinson's Disease Mechanisms and Treatments
Canadian institutionsMontreal Neurological Institute and HospitalMcGill UniversityUniversity of British Columbia
FundersParkinson Canada
KeywordsLRRK2EndogenyGene knockinNeuroscienceMutationNeuronBiologyCell biologyGeneticsGeneBiochemistry

Abstract

fetched live from OpenAlex

Abstract Neuronal aggregates containing α-synuclein are a pathological hallmark of several degenerative diseases; including Parkinson’s disease, Parkinson’s disease with dementia and dementia with Lewy bodies. Understanding the process of α-synuclein aggregation, and discovering means of preventing it, may help guide therapeutic strategy and drug design. Recent advances provide tools to induce α-synuclein aggregation in neuronal cultures. Application of exogenous pre-formed fibrillar α-synuclein induces pathological phosphorylation and accumulation of endogenous α-synuclein, typical of that seen in disease. Genomic variability and mutations in α-synuclein and leucine-rich repeat kinase 2 proteins are the major genetic risk factors for Parkinson’s disease. Reports demonstrate fibril-induced α-synuclein aggregation is increased in cells from leucine-rich repeat kinase 2 pathogenic mutant (G2019S) overexpressing mice, and variously decreased by leucine-rich repeat kinase 2 inhibitors. Elsewhere in vivo antisense knock-down of leucine-rich repeat kinase 2 protein has been shown to protect mice from fibril-induced α-synuclein aggregation, whereas kinase inhibition did not. To help bring clarity to this issue, we took a purely genetic approach in a standardized neuron-enriched culture, lacking glia. We compared fibril treatment of leucine-rich repeat kinase 2 germ-line knock-out, and G2019S germ-line knock-in, mouse cortical neuron cultures with those from littermates. We found leucine-rich repeat kinase 2 knock-out neurons are resistant to α-synuclein aggregation, which predominantly forms within axons, and may cause axonal fragmentation. Conversely, leucine-rich repeat kinase 2 knock-in neurons are more vulnerable to fibril-induced α-synuclein accumulation. Protection and resistance correlated with basal increases in a lysosome marker in knock-out, and an autophagy marker in knock-in cultures. The data add to a growing number of studies that argue leucine-rich repeat kinase 2 silencing, and potentially kinase inhibition, may be a useful therapeutic strategy against synucleinopathy.

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 score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.065
GPT teacher head0.297
Teacher spread0.233 · 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

Citations33
Published2020
Admission routes2
Has abstractyes

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