Riluzole as a Neuroprotective Drug for Spinal Cord Injury: From Bench to Bedside
Bibliographic record
Abstract
Spinal cord injury (SCI) is a devastating event resulting in permanent loss of neurological function. To date, effective therapies for SCI have not been established. With recent progress in neurobiology, however, there is hope that drug administration could improve outcomes after SCI. Riluzole is a benzothiazole anticonvulsant with neuroprotective effects. It has been approved by the U.S. Food and Drug Administration as a safe and well-tolerated treatment for patients with amyotrophic lateral sclerosis. The mechanism of action of riluzole involves the inhibition of pathologic glutamatergic transmission in synapses of neurons via sodium channel blockade. There is convincing evidence that riluzole diminishes neurological tissue destruction and promotes functional recovery in animal SCI models. Based on these results, a phase I/IIa clinical trial with riluzole was conducted for patients with SCI between 2010 and 2011. This trial demonstrated significant improvement in neurological outcomes and showed it to be a safe drug with no serious adverse effects. Currently, an international, multi-center clinical trial (Riluzole in Acute Spinal Cord Injury Study: RISCIS) in phase II/III is in progress with riluzole for patients with SCI (clinicaltrials.gov, registration number NCT01597518). This article reviews the pharmacology and neuroprotective mechanisms of riluzole, and focuses on existing preclinical evidence, and emerging clinical data in the treatment of SCI.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".