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Record W4313246865 · doi:10.3390/biomedicines11010041

Emerging Roles of Cholinergic Receptors in Schwann Cell Development and Plasticity

2022· review· en· W4313246865 on OpenAlexafffund
Roberta Piovesana, Adam J. Reid, Ada Maria Tata

Bibliographic record

VenueBiomedicines · 2022
Typereview
Languageen
FieldNeuroscience
TopicVagus Nerve Stimulation Research
Canadian institutionsUniversité de Montréal
FundersFonds de Recherche du Québec - SantéAcademy of Medical Sciences
KeywordsNeuroscienceBiologySchwann cellMuscarinic acetylcholine receptorCholinergicNeurotransmitter receptorReceptorAcetylcholine receptorNicotinic agonistCell biologyNeurotransmitterCentral nervous system

Abstract

fetched live from OpenAlex

The cross talk between neurons and glial cells during development, adulthood, and disease, has been extensively documented. Among the molecules mediating these interactions, neurotransmitters play a relevant role both in myelinating and non-myelinating glial cells, thus resulting as additional candidates regulating the development and physiology of the glial cells. In this review, we summarise the contribution of the main neurotransmitter receptors in the regulation of the morphogenetic events of glial cells, with particular attention paid to the role of acetylcholine receptors in Schwann cell physiology. In particular, the M2 muscarinic receptor influences Schwann cell phenotype and the α7 nicotinic receptor is emerging as influential in the modulation of peripheral nerve regeneration and inflammation. This new evidence significantly improves our knowledge of Schwann cell development and function and may contribute to identifying interesting new targets to support the activity of these cells in pathological conditions.

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)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.996
Threshold uncertainty score0.858

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.122
GPT teacher head0.381
Teacher spread0.259 · 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 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

Citations14
Published2022
Admission routes2
Has abstractyes

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