MétaCan
Menu
Back to cohort
Record W2069432272 · doi:10.1002/dvg.20658

Loss of Necdin impairs myosin activation and delays cell polarization

2010· article· en· W2069432272 on OpenAlexafffund
Jason Bush, Rachel Wevrick

Bibliographic record

Venuegenesis · 2010
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetic Syndromes and Imprinting
Canadian institutionsUniversity of Alberta
FundersNational Institute of General Medical SciencesRIKENCanadian Institutes of Health ResearchHeritage Medical Research Institute
KeywordsCell polarityMyosinCell biologyBiologyNull cellPAX3NeuroscienceCellGeneticsCell cultureGeneTranscription factor

Abstract

fetched live from OpenAlex

NDN is one of several genes inactivated in Prader-Willi syndrome (PWS), a developmental disorder characterized by obesity, hypotonia, and developmental delay. We demonstrate that loss of Necdin in murine and human fibroblasts impairs polarity initiation through a Cdc42-myosin-dependent pathway, thereby reducing cell migration. We identified defective polarization in both primary neuron cultures and in the developing limb in Ndn-null mice. Ndn-null neurons fail to activate myosin light chain and display defective polarization with respect to a brain-derived neurotrophic factor gradient. Pax3+ muscle progenitors in Ndn-null developing forelimbs display defective polarization, do not adequately migrate into the dorsal limb bud, and extensor muscles are consequently smaller. These results provide strong evidence that Necdin is a key protein regulating polarization of the cytoskeleton during development. Furthermore, this is the first demonstration of a cellular defect in PWS and suggests a novel molecular mechanism to explain neurological and muscular pathophysiologies in PWS.

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 score0.001
Threshold uncertainty score0.004

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)0.0010.000

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 head0.005
GPT teacher head0.207
Teacher spread0.203 · 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

Citations16
Published2010
Admission routes2
Has abstractyes

Explore more

Same venuegenesisSame topicGenetic Syndromes and ImprintingFrench-language works237,207