MétaCan
Menu
Back to cohort
Record W2265639153 · doi:10.1002/mus.25078

Functional ionotropic glutamate receptors on peripheral axons and myelin

2016· article· en· W2265639153 on OpenAlexafffund
Pia Crone Christensen, Nicole C. Welch, Craig Brideau, Peter K. Stys

Bibliographic record

VenueMuscle & Nerve · 2016
Typearticle
Languageen
FieldNeuroscience
TopicNerve injury and regeneration
Canadian institutionsUniversity of Calgary
FundersCanadian Institutes of Health ResearchCanada Research ChairsMultiple Sclerosis Society of Canada
KeywordsAMPA receptorGlutamate receptorAxonNMDA receptorNeuroscienceBiologyMyelinMetabotropic glutamate receptorCell biologyIonotropic effectKainate receptorReceptorMetabotropic glutamate receptor 1ChemistryCentral nervous systemBiochemistry

Abstract

fetched live from OpenAlex

INTRODUCTION: Neurotransmitter-dependent signaling is traditionally restricted to axon terminals. However, receptors are present on myelinating glia, suggesting that chemical transmission may also occur along axons. METHODS: Confocal microscopy and Ca(2+) -imaging using an axonally expressed FRET-based reporter was used to measure Ca(2+) changes and morphological alterations in myelin in response to stimulation of glutamate receptors. RESULTS: Activation of α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid (AMPA) or N-methyl-D-aspartate (NMDA) receptors induced a Ca(2+) increase in axon cylinders. However, only the latter caused structural alterations in axons, despite similar Ca(2+) increases. Myelin morphology was significantly altered by NMDA receptor activation, but not by AMPA receptors. Cu(2+) ions influenced the NMDA receptor-dependent response, suggesting that this metal modulates axonal receptors. Glutamate increased ribosomal signal in Schwann cell cytoplasm. CONCLUSIONS: Axon cylinders and myelin of peripheral nervous system axons respond to glutamate, with a consequence being an increase in Schwann cell ribosomes. This may have implications for nerve pathology and regeneration. Muscle Nerve 54: 451-459, 2016.

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)0.000
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 score0.063
Threshold uncertainty score0.796

Codex and Gemma teacher scores by category

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 head0.034
GPT teacher head0.241
Teacher spread0.207 · 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

Citations19
Published2016
Admission routes2
Has abstractyes

Explore more

Same venueMuscle & NerveSame topicNerve injury and regenerationFrench-language works237,207