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Record W2612731932 · doi:10.1089/neu.2016.4640

Exercise and Peripheral Nerve Grafts as a Strategy To Promote Regeneration after Acute or Chronic Spinal Cord Injury

2017· review· en· W2612731932 on OpenAlexaff
Catherine C. Theisen, Rahul Sachdeva, Scarlett Austin, Danielle Kulich, Victoria A Kranz, John D. Houlé

Bibliographic record

VenueJournal of Neurotrauma · 2017
Typereview
Languageen
FieldNeuroscience
TopicNerve injury and regeneration
Canadian institutionsInternational Collaboration On Repair Discoveries
FundersNational Institutes of HealthCraig H. Neilsen Foundation
KeywordsMedicineSpinal cord injurySpinal cordNeuroprotectionRegeneration (biology)NeurosciencePeripheral nerve injuryPeripheralLesionLumbarNeuropathic painNerve injuryRehabilitationChronic painPhysical medicine and rehabilitationLumbar Spinal CordAnesthesiaPhysical therapySurgerySciatic nerveInternal medicinePsychologyBiology

Abstract

fetched live from OpenAlex

Therapeutic interventions after spinal cord injury (SCI) routinely are designed to address multiple aspects of the primary and/or secondary damage that occurs. Exercise has a demonstrated efficacy for post-SCI complications such as cardiovascular dysfunction, neuropathic pain, and chronic inflammation, yet there is little understanding of the mechanisms by which improvements might result from this non-invasive approach. Here we review several of our observations of molecular and cellular changes within the injured spinal cord following acute or delayed exercise regimens that illustrate the potential for positive effects on neuroprotection and rehabilitation. Further, we provide new information about the role of exercise in promoting the regeneration of spinal axons into peripheral nerve grafts (PNGs) placed immediately or 6 weeks after injury. Acute and chronically injured propriospinal neurons within the lumbar spinal cord displayed the greatest propensity for enhanced regeneration after exercise, which correlates with the direct sensory input to this region from exercised hindlimb muscles. Future studies will extend these observations by testing whether exercise will boost the regenerative effort of axons to extend beyond the graft, interact with intraspinal targets, and establish functional connections across a lesion.

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 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 score0.986
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
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 head0.172
GPT teacher head0.430
Teacher spread0.259 · 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.

Study designOther design
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

Citations32
Published2017
Admission routes1
Has abstractyes

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