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Record W2158441334 · doi:10.1073/pnas.0709379104

The Parkinson's disease gene DJ-1 is also a key regulator of stroke-induced damage

2007· article· en· W2158441334 on OpenAlexaff
Hossein Aleyasin, Maxime W.C. Rousseaux, Maryam Phillips, Raymond H. Kim, Ross Bland, Steve Callaghan, Ruth S. Slack, Matthew J. During, Tak W. Mak, David S. Park

Bibliographic record

VenueProceedings of the National Academy of Sciences · 2007
Typearticle
Languageen
FieldMedicine
TopicParkinson's Disease Mechanisms and Treatments
Canadian institutionsOntario Institute for Cancer ResearchUniversity of Ottawa
Fundersnot available
KeywordsNeuroprotectionOxidative stressStroke (engine)ExcitotoxicityParkinson's diseaseNeuroscienceDiseaseRegulatorIschemiaIn vivoMedicineBiologyBioinformaticsGeneProgrammed cell deathInternal medicineGeneticsApoptosis

Abstract

fetched live from OpenAlex

Recent evidence has indicated that common mechanisms play roles among multiple neurological diseases. However, the specifics of these pathways are not completely understood. Stroke is caused by the interruption of blood flow to the brain, and cumulative evidence supports the critical role of oxidative stress in the ensuing neuronal death process. DJ-1 (PARK7) has been identified as the gene linked to early-onset familial Parkinson's disease. Currently, our work also shows that DJ-1 is central to death in both in Vitro and in Vivo models of stroke. Loss of DJ-1 increases the sensitivity to excitotoxicity and ischemia, whereas expression of DJ-1 can reverse this sensitivity and indeed provide further protection. Importantly, DJ-1 expression decreases markers of oxidative stress after stroke insult in Vivo, suggesting that DJ-1 protects through alleviation of oxidative stress. Consistent with this finding, we demonstrate the essential role of the oxidation-sensitive cysteine-106 residue in the neuroprotective activity of DJ-1 after stroke. Our work provides an important example of how a gene seemingly specific for one disease, in this case Parkinson's disease, also appears to be central in other neuropathological conditions such as stroke. It also highlights the important commonalities among differing neuropathologies.

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 score0.005

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 communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.038
GPT teacher head0.317
Teacher spread0.279 · 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

Citations163
Published2007
Admission routes1
Has abstractyes

Explore more

Same venueProceedings of the National Academy of SciencesSame topicParkinson's Disease Mechanisms and TreatmentsFrench-language works237,207