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Record W2052604373 · doi:10.1371/journal.pbio.0060182

Spinal Cord Injury Reveals Multilineage Differentiation of Ependymal Cells

2008· article· en· W2052604373 on OpenAlexfundno aff
Konstantinos Meletis, Fanie Barnabé‐Heider, Marie Carlén, Emma Evergren, N.V. Tomilin, Oleg Shupliakov, Jonas Frisén

Bibliographic record

VenuePLoS Biology · 2008
Typearticle
Languageen
FieldNeuroscience
TopicNeurogenesis and neuroplasticity mechanisms
Canadian institutionsnot available
FundersCanadian Institutes of Health ResearchCancerfondenKarolinska InstitutetEuropean CommissionVetenskapsrådetChristopher and Dana Reeve Foundation
KeywordsEpendymal CellSpinal cord injurySpinal cordBiologyNeural stem cellTransplantationRegeneration (biology)Stem cellNeuroscienceCentral nervous systemAnatomyCell biologyPathologyMedicineSurgery

Abstract

fetched live from OpenAlex

Spinal cord injury often results in permanent functional impairment. Neural stem cells present in the adult spinal cord can be expanded in vitro and improve recovery when transplanted to the injured spinal cord, demonstrating the presence of cells that can promote regeneration but that normally fail to do so efficiently. Using genetic fate mapping, we show that close to all in vitro neural stem cell potential in the adult spinal cord resides within the population of ependymal cells lining the central canal. These cells are recruited by spinal cord injury and produce not only scar-forming glial cells, but also, to a lesser degree, oligodendrocytes. Modulating the fate of ependymal progeny after spinal cord injury may offer an alternative to cell transplantation for cell replacement therapies in spinal cord injury.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

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 integrity0.0000.001
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 head0.086
GPT teacher head0.302
Teacher spread0.216 · 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 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

Citations673
Published2008
Admission routes1
Has abstractyes

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