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Record W2114894148 · doi:10.1101/cshperspect.a020503

Perisynaptic Schwann Cells at the Neuromuscular Synapse: Adaptable, Multitasking Glial Cells

2015· review· en· W2114894148 on OpenAlexafffund
Chien‐Ping Ko, Richard Robitaille

Bibliographic record

VenueCold Spring Harbor Perspectives in Biology · 2015
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicIon channel regulation and function
Canadian institutionsUniversité de Montréal
FundersCanadian Institutes of Health ResearchNational Institutes of Health
KeywordsBiologyNeuromuscular junctionNeuroscienceSynapseSynaptic plasticityNeurotransmissionHuman multitaskingSchwann cellCell biologyReceptor

Abstract

fetched live from OpenAlex

The neuromuscular junction (NMJ) is engineered to be a highly reliable synapse to carry the control of the motor commands of the nervous system over the muscles. Its development, organization, and synaptic properties are highly structured and regulated to support such reliability and efficacy. Yet, the NMJ is also highly plastic, able to react to injury and adapt to changes. This balance between structural stability and synaptic efficacy on one hand and structural plasticity and repair on another hand is made possible by the intricate regulation of perisynaptic Schwann cells, glial cells at this synapse. They regulate both the efficacy and structural plasticity of the NMJ in a dynamic, bidirectional manner owing to their ability to decode synaptic transmission and by their interactions via trophic-related factors.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0000.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.004

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 head0.035
GPT teacher head0.308
Teacher spread0.273 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations104
Published2015
Admission routes2
Has abstractyes

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