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Record W3080503232 · doi:10.3389/fnmol.2020.00153

A Critical LRRK at the Synapse? The Neurobiological Function and Pathophysiological Dysfunction of LRRK2

2020· review· en· W3080503232 on OpenAlexafffund
Naila Kuhlmann, Austen J. Milnerwood

Bibliographic record

VenueFrontiers in Molecular Neuroscience · 2020
Typereview
Languageen
FieldMedicine
TopicParkinson's Disease Mechanisms and Treatments
Canadian institutionsMcGill UniversityUniversity of British ColumbiaMontreal Neurological Institute and Hospital
FundersCanadian Institutes of Health ResearchParkinson CanadaUniversity of British ColumbiaMcGill UniversityFonds de Recherche du Québec - SantéMichael J. Fox Foundation for Parkinson's Research
KeywordsLRRK2NeuroscienceNeuroprotectionParkinson's diseaseSynapseBiologyDiseaseSubstantia nigraBasal gangliaMedicineCentral nervous systemPathologyDopaminergic

Abstract

fetched live from OpenAlex

mutations causal to Parkinson's disease (PD) in the early 2000s, the LRRK2 protein has been implicated in a plethora of cellular processes in which pathogenesis could occur, yet its physiological function remains elusive. The development of genetic models of LRRK2 PD has helped identify the etiological and pathophysiological underpinnings of the disease, and may identify early points of intervention. An important role for LRRK2 in synaptic function has emerged in recent years, which links LRRK2 to other genetic forms of PD, most notably those caused by mutations in the synaptic protein α-synuclein. This point of convergence may provide useful clues as to what drives dysfunction in the basal ganglia circuitry and eventual death of substantia nigra (SN) neurons. Here, we discuss the evolution and current state of the literature placing LRRK2 at the synapse, through the lens of knock-out, overexpression, and knock-in animal models. We hope that a deeper understanding of LRRK2 neurobiology, at the synapse and beyond, will aid the eventual development of neuroprotective interventions for PD, and the advancement of useful treatments in the interim.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.981
Threshold uncertainty score0.639

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.025
GPT teacher head0.288
Teacher spread0.262 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations38
Published2020
Admission routes2
Has abstractyes

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