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Record W1590831986 · doi:10.1002/glia.22851

Endogenous neural stem cell responses to stroke and spinal cord injury

2015· review· en· W1590831986 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueGlia · 2015
Typereview
Languageen
FieldNeuroscience
TopicNeurogenesis and neuroplasticity mechanisms
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsForebrainSubventricular zoneSpinal cord injuryNeural stem cellNeuroscienceBiologyStem cellSpinal cordEpendymal CellCentral nervous systemEndogenyRegeneration (biology)Stroke (engine)Cell biologyEndocrinology

Abstract

fetched live from OpenAlex

Stroke and spinal cord injury (SCI) are among the most frequent causes of central nervous system (CNS) dysfunction, affecting millions of people worldwide each year. The personal and financial costs for affected individuals, their families, and the broader communities are enormous. Although the mammalian CNS exhibits little spontaneous regeneration and self-repair, recent discoveries have revealed that subpopulations of glial cells in the adult forebrain subventricular zone and the spinal cord ependymal zone possess neural stem cell properties. These endogenous neural stem cells react to stroke and SCI by contributing a significant number of new neural cells to formation of the glial scar. These findings have raised hopes that new therapeutic strategies can be designed based on appropriate modulation of endogenous neural stem cell responses to CNS injury. Here, we review the responses of forebrain and spinal cord neural stem cells to stroke and SCI, the role of these responses in restricting injury-induced tissue loss, and the possibility of directing these responses to promote anatomical and functional repair of the CNS.

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.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.944
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

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 head0.209
GPT teacher head0.359
Teacher spread0.149 · 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