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Record W2795226545 · doi:10.1002/glia.23333

<scp>T</scp>he extracellular matrix: <scp>F</scp>ocus on oligodendrocyte biology and targeting <scp>CSPG</scp>s for remyelination therapies

2018· review· en· W2795226545 on OpenAlexafffund
Annie Pu, Erin L. Stephenson, V. Wee Yong

Bibliographic record

VenueGlia · 2018
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicProteoglycans and glycosaminoglycans research
Canadian institutionsUniversity of Calgary
FundersMultiple Sclerosis Society of CanadaCanadian Institutes of Health ResearchAlberta Innovates - Health Solutions
KeywordsRemyelinationOligodendrocyteBiologyMyelinExtracellular matrixCell biologyNeuroscienceRegeneration (biology)Multiple sclerosisCentral nervous systemExtracellularChondroitin sulfate proteoglycanImmunologyProteoglycan

Abstract

fetched live from OpenAlex

The repair of myelin, termed remyelination, is a regenerative process that occurs within the central nervous system in conditions such as multiple sclerosis. Remyelination is enabled by oligodendrocytes that mature from oligodendrocyte precursor cells. Many factors influence the biology of oligodendrocytes and their capacity to reform myelin, and considerable evidence now implicates the extracellular matrix within the injured central nervous system as a major modifier of remyelination. Herein, we review current knowledge of components of the brain extracellular matrix that are beneficial or inhibitory for oligodendrocyte recruitment and maturation, and for their capacity to remyelinate where evidence exists. We highlight the detrimental roles of the chondroitin sulfate proteoglycans in remyelination and discuss approaches to alter the brain extracellular matrix for the wellbeing of oligodendrocytes and their capacity for myelin regeneration.

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 score0.006
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.003

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 head0.031
GPT teacher head0.342
Teacher spread0.311 · 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

Citations72
Published2018
Admission routes2
Has abstractyes

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