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Record W2082487916 · doi:10.1002/ana.22435

Restless legs syndrome‐associated <i>MEIS1</i> risk variant influences iron homeostasis

2011· article· en· W2082487916 on OpenAlexafffund
Hélène Catoire, Patrick A. Dion, Lan Xiong, Mourabit Amari, Rébecca Gaudet, Simon Girard, Anne Noreau, Cláudia Gaspar, Gustavo Turecki, Jacques Montplaisir, J. Alex Parker, Guy A. Rouleau

Bibliographic record

VenueAnnals of Neurology · 2011
Typearticle
Languageen
FieldMedicine
TopicRestless Legs Syndrome Research
Canadian institutionsCentre Hospitalier Universitaire Sainte-JustineHôpital du Sacré-Cœur de MontréalMontreal Neurological Institute and HospitalUniversité de MontréalMcGill UniversityDouglas Mental Health University InstituteCentre Hospitalier de l’Université de Montréal
FundersCanadian Institutes of Health Research
KeywordsFerritinRestless legs syndromeCaenorhabditis elegansIron homeostasisHaplotypeBiologyHomeostasisGeneGene expressionGeneticsEndocrinologyRNA interferenceInternal medicineRNAAlleleMedicineNeuroscienceBiochemistry

Abstract

fetched live from OpenAlex

Restless legs syndrome (RLS) is a frequent sleep disorder that is linked to disturbed iron homeostasis. Genetic studies identified MEIS1 as an RLS-predisposing gene, where the RLS risk haplotype is associated with decreased MEIS1 mRNA and protein expression. We show here that RNA interference treatment of the MEIS1 worm orthologue increases ferritin expression in Caenorhabditis elegans and that the RLS-associated haplotype leads to increased expression of ferritin and DMT1 in RLS brain tissues. Additionally, human cells cultured under iron-deficient conditions show reduced MEIS1 expression. Our data establish a link between the RLS MEIS1 gene and iron metabolism.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.009

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 integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.143
GPT teacher head0.355
Teacher spread0.212 · 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 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

Citations94
Published2011
Admission routes2
Has abstractyes

Explore more

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