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Record W2949862897 · doi:10.1242/jcs.211482

Neurochondrin interacts with the SMN protein suggesting a novel mechanism for spinal muscular atrophy pathology

2018· article· en· W2949862897 on OpenAlexfundno aff
Luke Thompson, Kim D. Morrison, Sally L. Shirran, Ewout J. N. Groen, Thomas H. Gillingwater, Catherine H. Botting, Judith Sleeman

Bibliographic record

VenueJournal of Cell Science · 2018
Typearticle
Languageen
FieldMedicine
TopicNeurogenetic and Muscular Disorders Research
Canadian institutionsnot available
FundersSpinal Muscular Atrophy TrustMedical Research Council CanadaWellcome Trust
KeywordsBiologySpinal muscular atrophyMechanism (biology)Cell biologyAnatomyPathologyAtrophyNeuroscienceGeneticsGene

Abstract

fetched live from OpenAlex

Spinal muscular atrophy (SMA) is an inherited neurodegenerative condition caused by a reduction in the amount of functional survival motor neuron (SMN) protein. SMN has been implicated in transport of mRNA in neural cells for local translation. We previously identified microtubule-dependent mobile vesicles rich in SMN and SNRPB, a member of the Sm family of small nuclear ribonucleoprotein (snRNP)-associated proteins, in neural cells. By comparing the interactomes of SNRPB and SNRPN, a neural-specific Sm protein, we now show that the essential neural protein neurochondrin (NCDN) interacts with Sm proteins and SMN in the context of mobile vesicles in neurites. NCDN has roles in protein localisation in neural cells and in maintenance of cell polarity. NCDN is required for the correct localisation of SMN, suggesting they may both be required for formation and transport of trafficking vesicles. NCDN may have potential as a therapeutic target for SMA together with, or in place of the targeting of SMN expression.This article has an associated First Person interview with the first author of the paper.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.039
Threshold uncertainty score0.220

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.024
GPT teacher head0.311
Teacher spread0.286 · 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 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

Citations17
Published2018
Admission routes1
Has abstractyes

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