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Record W2034950850 · doi:10.1126/science.1246448

Dlk1 Promotes a Fast Motor Neuron Biophysical Signature Required for Peak Force Execution

2014· article· en· W2034950850 on OpenAlexafffund
Daniel Müller, Pitchaiah Cherukuri, Kristine A. Henningfeld, Chor Hoon Poh, Lars Wittler, Phillip Grote, Oliver M. Schlüter, Jennifer V. Schmidt, Jorge Laborda, Steven R. Bauer, Robert M. Brownstone, Till Marquardt

Bibliographic record

VenueScience · 2014
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicZebrafish Biomedical Research Applications
Canadian institutionsDalhousie University
FundersCanadian Institutes of Health ResearchEunice Kennedy Shriver National Institute of Child Health and Human DevelopmentUniversitätsmedizin GöttingenCanada Research ChairsEuropean CommissionDeutsche ForschungsgemeinschaftCincinnati Children's Hospital Medical Center
KeywordsNeuroscienceNeuronMotor neuronJumpingSignature (topology)Computer scienceBiophysicsBiologyChemistryMathematicsPhysiologySpinal cord

Abstract

fetched live from OpenAlex

Motor neurons, which relay neural commands to drive skeletal muscle movements, encompass types ranging from "slow" to "fast," whose biophysical properties govern the timing, gradation, and amplitude of muscle force. Here we identify the noncanonical Notch ligand Delta-like homolog 1 (Dlk1) as a determinant of motor neuron functional diversification. Dlk1, expressed by ~30% of motor neurons, is necessary and sufficient to promote a fast biophysical signature in the mouse and chick. Dlk1 suppresses Notch signaling and activates expression of the K(+) channel subunit Kcng4 to modulate delayed-rectifier currents. Dlk1 inactivation comprehensively shifts motor neurons toward slow biophysical and transcriptome signatures, while abolishing peak force outputs. Our findings provide insights into the development of motor neuron functional diversity and its contribution to the execution of movements.

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 score0.006

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 head0.011
GPT teacher head0.292
Teacher spread0.281 · 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

Citations77
Published2014
Admission routes2
Has abstractyes

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