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Record W4306736746 · doi:10.3390/biomedicines10102622

Enlargement of the Nerve Fibers of Silenced Lumbosacral Motoneurons in Cats

2022· article· en· W4306736746 on OpenAlexafffund
Tessa Gordon, Lynn Eldridge, Saljae Aurora

Bibliographic record

VenueBiomedicines · 2022
Typearticle
Languageen
FieldMedicine
TopicNerve Injury and Rehabilitation
Canadian institutionsUniversity of British ColumbiaUniversity of Toronto
FundersAlberta Heritage Foundation for Medical ResearchFondation pour la Recherche Médicale
KeywordsAnatomySpinal cordAxonLumbosacral jointFascicleCATSSural nerveLumbarMotor nerveNerve rootSciatic nerveMedicineMyelin sheathMyelinChemistryBiologyNeuroscienceCentral nervous systemInternal medicine

Abstract

fetched live from OpenAlex

Whether neuromuscular activity influences the size of motor nerves is controversial. All neuromuscular activity in cat hindlimbs was eliminated by spinal cord isolation (SCI), namely, spinal cord transection above and below the medial gastrocnemius (MG) and soleus (SOL) motoneuron pools and L5-S3 dorsal root transection. MG, SOL and sural (SUR) nerves were removed for size measurements, eight months after SCI surgery and from age-matched control cats. Nerve fiber number, the linear relationship between axon size and myelin thickness, and the bimodal distributions of nerve fiber area and diameter were maintained in all three nerves after SCI. The distributions of myelinated sensory fibers were unchanged in SUR nerves in contrast to the myelinated motor fibers in the MG and SOL nerves that were significantly larger. These findings provide evidence that all lumbar motoneurons survive SCI and that their nerve fibers enlarge. Thus, motor nerve fiber size in addition to the properties of the motoneurons and their muscle fibers is dynamic, responding to neuromuscular activity.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.644
Threshold uncertainty score0.174

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.012
GPT teacher head0.273
Teacher spread0.261 · 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 designObservational
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

Citations1
Published2022
Admission routes2
Has abstractyes

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