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Record W2035771416 · doi:10.1517/14728214.13.1.63

Emerging drugs for spinal cord injury

2008· review· en· W2035771416 on OpenAlexaff
Darryl C. Baptiste, Michael G. Fehlings

Bibliographic record

VenueExpert Opinion on Emerging Drugs · 2008
Typereview
Languageen
FieldMedicine
TopicSpinal Cord Injury Research
Canadian institutionsKrembil FoundationUniversity of TorontoToronto Western Hospital
Fundersnot available
KeywordsMedicineNeuroprotectionClinical trialSpinal cord injuryNeuroscienceBioinformaticsIntensive care medicinePharmacologySpinal cordPathologyBiology

Abstract

fetched live from OpenAlex

BACKGROUND: This review summarizes several promising pharmacological approaches for the therapeutic management of traumatic spinal cord injury (SCI), which are either in early-phase clinical trials or nearing clinical translation. OBJECTIVE: This review provides the reader with an understanding of the key pathophysiological mechanisms that contribute to neurological deficits after SCI. Through discussion of the mechanism(s) of action of the selected therapeutic approaches potentially important targets to aid further drug discovery will be highlighted. METHODS: Systematic literature review of the pre-clinical literature and clinical SCI trials related to neuroprotective, immunomodulatory and regenerative therapeutic approaches. RESULTS/CONCLUSION: The next decade will witness an unprecedented number of clinical trials which will seek to translate key biomedical research discoveries. The promising drug-based therapeutic approaches include regenerative strategies to neutralize myelin-mediated neurite outgrowth inhibition, neuroprotective strategies to reduce apoptotic triggers, the targeting of cationic/glutamatergic toxicity, anti-inflammatory strategies and the use of approaches to stabilize disrupted cell membranes.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesMeta-epidemiology (narrow)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.873
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0020.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0000.001

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 head0.123
GPT teacher head0.493
Teacher spread0.370 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
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

Citations49
Published2008
Admission routes1
Has abstractyes

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