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Record W4281730928 · doi:10.3390/jdb10020021

Radial Glia and Neuronal-like Ependymal Cells Are Present within the Spinal Cord of the Trunk (Body) in the Leopard Gecko (Eublepharis macularius)

2022· article· en· W4281730928 on OpenAlexafffund
Sarah Donato, Matthew K. Vickaryous

Bibliographic record

VenueJournal of Developmental Biology · 2022
Typearticle
Languageen
FieldNeuroscience
TopicNeurogenesis and neuroplasticity mechanisms
Canadian institutionsUniversity of Guelph
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsEpendymal CellSpinal cordBiologyAnatomyLateral funiculusNeurosciencePopulationNeural stem cellProgenitor cellSpinal cord injuryCell biologyStem cellMedicine

Abstract

fetched live from OpenAlex

) can self-detach a portion of their tail to escape predation, and then regenerate a replacement complete with a spinal cord. Previous research has shown that endogenous populations of neural stem/progenitor cells (NSPCs) reside within the spinal cord of the original tail. In response to tail loss, these NSPCs are activated and contribute to regeneration. Here, we investigate whether similar populations of NSPCs are found within the spinal cord of the trunk (body). Using a long-duration 5-bromo-2'-deoxyuridine pulse-chase experiment, we determined that a population of cells within the ependymal layer are label-retaining following a 20-week chase. Tail loss does not significantly alter rates of ependymal cell proliferation within the trunk spinal cord. Ependymal cells of the trunk spinal cord express SOX2 and represent at least two distinct cell populations: radial glial-like (glial fibrillary acidic protein- and Vimentin-expressing) cells; and neuronal-like (HuCD-expressing) cells. Taken together, these data demonstrate that NSPCs of the trunk spinal cord closely resemble those of the tail and support the use of the tail spinal cord as a less invasive proxy for body spinal cord injury investigations.

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)0.001
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 score0.071
Threshold uncertainty score0.393

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 science0.0010.001
Research integrity0.0000.001
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 head0.036
GPT teacher head0.262
Teacher spread0.226 · 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

Citations5
Published2022
Admission routes2
Has abstractyes

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