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Record W2969288074 · doi:10.1002/glia.23706

The fate and function of oligodendrocyte progenitor cells after traumatic spinal cord injury

2019· review· en· W2969288074 on OpenAlexaff
Greg J. Duncan, Sohrab B. Manesh, Brett J. Hilton, Peggy Assinck, Jason R. Plemel, Wolfram Tetzlaff

Bibliographic record

VenueGlia · 2019
Typereview
Languageen
FieldNeuroscience
TopicNeurogenesis and neuroplasticity mechanisms
Canadian institutionsWomen and Children’s Health Research InstituteUniversity of AlbertaInternational Collaboration On Repair DiscoveriesUniversity of British Columbia
Fundersnot available
KeywordsRemyelinationBiologyProgenitor cellOligodendrocyteNeuroscienceSpinal cord injuryRegeneration (biology)MyelinNeural stem cellStem cellSpinal cordPopulationCell biologyCentral nervous systemImmunologyMedicine

Abstract

fetched live from OpenAlex

Oligodendrocyte progenitor cells (OPCs) are the most proliferative and dispersed population of progenitor cells in the adult central nervous system, which allows these cells to rapidly respond to damage. Oligodendrocytes and myelin are lost after traumatic spinal cord injury (SCI), compromising efficient conduction and, potentially, the long-term health of axons. In response, OPCs proliferate and then differentiate into new oligodendrocytes and Schwann cells to remyelinate axons. This culminates in highly efficient remyelination following experimental SCI in which nearly all intact demyelinated axons are remyelinated in rodent models. However, myelin regeneration comprises only one role of OPCs following SCI. OPCs contribute to scar formation after SCI and restrict the regeneration of injured axons. Moreover, OPCs alter their gene expression following demyelination, express cytokines and perpetuate the immune response. Here, we review the functional contribution of myelin regeneration and other recently uncovered roles of OPCs and their progeny to repair following SCI.

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)0.001
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 score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.077
GPT teacher head0.323
Teacher spread0.246 · 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

Citations111
Published2019
Admission routes1
Has abstractyes

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