Delayed administration of elezanumab, a human anti-RGMa neutralizing monoclonal antibody, promotes recovery following cervical spinal cord injury
Bibliographic record
Abstract
Spinal cord injury (SCI) elicits a cascade of degenerative events including cell death, axonal degeneration, and the upregulation of inhibitory molecules which limit repair. Repulsive guidance molecule A (RGMa) is an axon growth inhibitor which is also involved in neuronal cell death and differentiation. SCI causes upregulation of RGMa in the injured rodent, non-human primate, and human spinal cord. Recently, we showed that delayed administration of elezanumab, a high affinity human RGMa-specific monoclonal antibody, promoted neuroprotective and regenerative effects following thoracic SCI. Since most human traumatic SCI is at the cervical level, and level-dependent anatomical and molecular differences may influence pathophysiological responses to injury and treatment, we examined the efficacy of elezanumab and its therapeutic time window of administration in a clinically relevant rat model of cervical impact-compression SCI. Pharmacokinetic analysis of plasma and spinal cord tissue lysate showed comparable levels of RGMa antibodies with delayed administration following cervical SCI. At 12w after SCI, elezanumab promoted long term benefits including perilesional sparing of motoneurons and increased neuroplasticity of key descending pathways involved in locomotion and fine motor function. Elezanumab also promoted growth of corticospinal axons into spinal cord gray matter and enhanced serotonergic innervation of the ventral horn to form synaptic connections caudal to the cervical lesion. Significant recovery in grip and trunk/core strength, locomotion and gait, and spontaneous voiding ability was found in rats treated with elezanumab either immediately post-injury or at 3 h post-SCI, and improvements in specific gait parameters were found when elezanumab was delayed to 24 h post-injury. We also developed a new locomotor score, the Cervical Locomotor Score, a simple and sensitive measure of trunk/core and limb strength and stability during dynamic locomotion.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
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".