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Record W4379878263 · doi:10.1016/j.xnsj.2023.100235

Neuroplasticity and regeneration after spinal cord injury

2023· article· en· W4379878263 on OpenAlexaff
Nayaab Punjani, Dylan Deska‐Gauthier, Laureen D. Hachem, Madlene Abramian, Michael G. Fehlings

Bibliographic record

VenueNorth American Spine Society Journal (NASSJ) · 2023
Typearticle
Languageen
FieldMedicine
TopicSpinal Cord Injury Research
Canadian institutionsToronto Western HospitalUniversity of TorontoUniversity Health Network
Fundersnot available
KeywordsSpinal cord injuryNeuroscienceNeuroplasticityRegeneration (biology)MedicineReprogrammingProgenitor cellSpinal cordTransplantationStem cellRehabilitationNeurogenesisNeural stem cellPhysical medicine and rehabilitationPsychologyBiologyCellSurgery

Abstract

fetched live from OpenAlex

Spinal cord injury (SCI) is a debilitating condition with significant personal, societal, and economic burden. The highest proportion of traumatic injuries occur at the cervical level, which results in severe sensorimotor and autonomic deficits. Following the initial physical damage associated with traumatic injuries, secondary pro-inflammatory, excitotoxic, and ischemic cascades are initiated further contributing to neuronal and glial cell death. Additionally, emerging evidence has begun to reveal that spinal interneurons undergo subtype specific neuroplastic circuit rearrangements in the weeks to months following SCI, contributing to or hindering functional recovery. The current therapeutic guidelines and standards of care for SCI patients include early surgery, hemodynamic regulation, and rehabilitation. Additionally, preclinical work and ongoing clinical trials have begun exploring neuroregenerative strategies utilizing endogenous neural stem/progenitor cells, stem cell transplantation, combinatorial approaches, and direct cell reprogramming. This review will focus on emerging cellular and noncellular regenerative therapies with an overview of the current available strategies, the role of interneurons in plasticity, and the exciting research avenues enhancing tissue repair following SCI.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.343
Threshold uncertainty score0.962

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.030
GPT teacher head0.361
Teacher spread0.332 · 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

Citations29
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueNorth American Spine Society Journal (NASSJ)Same topicSpinal Cord Injury ResearchFrench-language works237,207