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Record W2083124467 · doi:10.1007/s13311-011-0076-7

Cellular Treatments for Spinal Cord Injury: The Time is Right for Clinical Trials

2011· review· en· W2083124467 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

VenueNeurotherapeutics · 2011
Typereview
Languageen
FieldNeuroscience
TopicNerve injury and regeneration
Canadian institutionsToronto Western HospitalUniversity Health Network
Fundersnot available
KeywordsSpinal cord injuryClinical trialMedicineNeuroscienceNeurologyNeurosurgeryPhysical medicine and rehabilitationMedical physicsIntensive care medicineSpinal cordPsychologyPathologySurgery

Abstract

fetched live from OpenAlex

More than 1 million people in the United States live with a spinal cord injury (SCI). Despite medical advances, many patients with SCIs still experience substantial neurological disability, with loss of motor, sensory, and autonomic function. Cell therapy is ideally suited to address the multifactorial nature of the secondary events following SCI. Remarkable advances in our understanding of the pathophysiology of SCI, structural and functional magnetic resonance imaging, image-guided micro-neurosurgical techniques, and transplantable cell biology have enabled the use of cell-based regenerative techniques in the clinic. It is important to note that there are more than a dozen recently completed, ongoing, or recruiting cell therapy clinical trials for SCI that reflect the views of many key stakeholders. The field of regenerative neuroscience has reached a stage in which the clinical trials are scientifically and ethically justified. Although experimental models and analysis methods and techniques continue to evolve, no model will completely replicate the human condition. It is recognized that more work with cervical models of contusive/compressive SCI are required in parallel with clinical trials. It is also important that the clinical translation of advances made through well-established and validated experimental approaches in animal models move forward to meet the compelling needs of individuals with SCI and to advance the field of regenerative neuroscience. However, it is imperative that such efforts at translation be done in the most rigorous and informed fashion to determine safety and possible efficacy, and to provide key information to clinicians and basic scientists, which will allow improvements in regenerative techniques and the validation and refinement of existing preclinical animal models and research approaches. The field of regenerative neuroscience should not be stalled at the animal model stage, but instead the clinical trials need to be focused, safe, and ethical, backed up by a robust, translationally relevant preclinical research strategy.

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)0.002
metaresearch head score (Gemma)0.001
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 score0.990
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.000
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 head0.590
GPT teacher head0.544
Teacher spread0.046 · 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