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Record W2163336238 · doi:10.1111/jnc.12502

Neuronal cytoskeleton in synaptic plasticity and regeneration

2013· review· en· W2163336238 on OpenAlexafffund
Phillip R. Gordon‐Weeks, Alyson E. Fournier

Bibliographic record

VenueJournal of Neurochemistry · 2013
Typereview
Languageen
FieldNeuroscience
TopicNerve injury and regeneration
Canadian institutionsMontreal Neurological Institute and Hospital
FundersCanadian Institutes of Health ResearchMultiple Sclerosis SocietyCanada Research ChairsMultiple Sclerosis Society of CanadaMcGill University
KeywordsNeuroscienceSynaptic plasticityBiologyNonsynaptic plasticityHomosynaptic plasticityMetaplasticityLong-term potentiationNeuroplasticitySynaptic scalingHomeostatic plasticityCytoskeletonPlasticityRegeneration (biology)SynapseSynaptic augmentationCell biologyInhibitory postsynaptic potentialExcitatory postsynaptic potentialReceptor

Abstract

fetched live from OpenAlex

During development, dynamic changes in the axonal growth cone and dendrite are necessary for exploratory movements underlying initial axo-dendritic contact and ultimately the formation of a functional synapse. In the adult central nervous system, an impressive degree of plasticity is retained through morphological and molecular rearrangements in the pre- and post-synaptic compartments that underlie the strengthening or weakening of synaptic pathways. Plasticity is regulated by the interplay of permissive and inhibitory extracellular cues, which signal through receptors at the synapse to regulate the closure of critical periods of developmental plasticity as well as by acute changes in plasticity in response to experience and activity in the adult. The molecular underpinnings of synaptic plasticity are actively studied and it is clear that the cytoskeleton is a key substrate for many cues that affect plasticity. Many of the cues that restrict synaptic plasticity exhibit residual activity in the injured adult CNS and restrict regenerative growth by targeting the cytoskeleton. Here, we review some of the latest insights into how cytoskeletal remodeling affects neuronal plasticity and discuss how the cytoskeleton is being targeted in an effort to promote plasticity and repair following traumatic injury in the central nervous system.

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 score0.011

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 studies0.0010.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0030.003

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 head0.060
GPT teacher head0.318
Teacher spread0.258 · 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

Citations114
Published2013
Admission routes2
Has abstractyes

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