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Record W2997404986 · doi:10.1038/s41467-019-13781-3

ROCK inhibitors upregulate the neuroprotective Parkin-mediated mitophagy pathway

2020· article· en· W2997404986 on OpenAlexafffund
Natalia Moskal, Victoria Riccio, Mikhail Bashkurov, Rediet Taddese, Alessandro Datti, Peter N. Lewis, G. Angus McQuibban

Bibliographic record

VenueNature Communications · 2020
Typearticle
Languageen
FieldMedicine
TopicParkinson's Disease Mechanisms and Treatments
Canadian institutionsMount Sinai HospitalUniversity of Toronto
FundersCanadian Institutes of Health Research
KeywordsParkinMitophagyNeuroprotectionPINK1MitochondrionCell biologyParkinson's diseaseBiologyDownregulation and upregulationAutophagyChemistryNeuroscienceMedicineBiochemistryDiseaseApoptosisGene

Abstract

fetched live from OpenAlex

The accumulation of damaged mitochondria causes the death of dopaminergic neurons. The Parkin-mediated mitophagy pathway functions to remove these mitochondria from cells. Targeting this pathway represents a therapeutic strategy for several neurodegenerative diseases, most notably Parkinson's disease. We describe a discovery pipeline to identify small molecules that increase Parkin recruitment to damaged mitochondria and ensuing mitophagy. We show that ROCK inhibitors promote the activity of this pathway by increasing the recruitment of HK2, a positive regulator of Parkin, to mitochondria. This leads to the increased targeting of mitochondria to lysosomes and removal of damaged mitochondria from cells. Furthermore, ROCK inhibitors demonstrate neuroprotective effects in flies subjected to paraquat, a parkinsonian toxin that induces mitochondrial damage. Importantly, parkin and rok are required for these effects, revealing a signaling axis which controls Parkin-mediated mitophagy that may be exploited for the development of Parkinson's disease therapeutics.

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)0.0000.000
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)0.0020.001

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 head0.022
GPT teacher head0.271
Teacher spread0.249 · 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

Citations143
Published2020
Admission routes2
Has abstractyes

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Same venueNature CommunicationsSame topicParkinson's Disease Mechanisms and TreatmentsFrench-language works237,207