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Record W2319570303 · doi:10.5692/clinicalneurol.50.869

Promoting Remyelination by Reducing an Inhibitory Microenvironment

2010· article· en· W2319570303 on OpenAlexaff
V. Wee Yong

Bibliographic record

VenueRinsho Shinkeigaku · 2010
Typearticle
Languageen
FieldNeuroscience
TopicNeurogenesis and neuroplasticity mechanisms
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsRemyelinationInhibitory postsynaptic potentialChemistryNeuroscienceBiologyCentral nervous system

Abstract

fetched live from OpenAlex

Remyelination occurs in Multiple Sclerosis although its extent is limited in many patients. Approaches to induce remyelination include increasing trophic support or by overcoming impediments present in the microenvironment. We have examined the expression of extracellular matrix molecules around demyelinating lesions in the dorsal column of the mouse spinal cord. Demyelination was produced by the local deposition of a toxin, lysolecithin. We found that chondroitin sulfate proteoglycans (CSPGs) accumulated early following demyelination while laminins accumulated during the period of remyelination. Microglia macrophages and reactive astrocytes were sources of CSPGs and laminins, respectively. Significantly, CSPG expression was down-regulated during remyelination, emphasizing that demyelination was correspondent with accumulation of CSPGs while remyelination was concurrent with removal of CSPGs and accumulation of laminins. In vitro, CSPG were a poor substrate for oligodendrocyte adhesion and maturation while laminin facilitated these processes. To further elucidate the relevance of CSPGs in vivo, we utilized xyloside to reduce the production of CSPGs that occur following demyelination. Xyloside treatment reduced the content of CSPGs, increased the number of oligodendrocyte precursor cells, and resulted in enhanced remyelination. These results highlight the extracellular matrix proteins around demyelinating lesions in the regulation of remyelination. In particular, we document the inhibitory roles of CSPGs, the removal of which facilitated repair.

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 score0.005
Threshold uncertainty score0.922

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)0.0000.000

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 head0.019
GPT teacher head0.242
Teacher spread0.223 · 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

Citations3
Published2010
Admission routes1
Has abstractyes

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