The Evaluation of Magnesium Chloride within a Polyethylene Glycol Formulation in a Porcine Model of Acute Spinal Cord Injury
Bibliographic record
Abstract
A porcine model of spinal cord injury (SCI) was used to evaluate the neuroprotective effects of magnesium chloride (MgCl2) within a polyethylene glycol (PEG) formulation, called “AC105” (Acorda Therapeutics Inc., Ardsley, NY). Specifically, we tested the hypothesis that AC105 would lead to greater tissue sparing at the injury site and improved behavioral outcome when delivered in a clinically realistic time window post-injury. Four hours after contusion/compression injury, Yucatan minipigs were randomized to receive a 30-min intravenous infusion of AC105, magnesium sulfate (MgSO4), or saline. Animals received 4 additional infusions of the same dose at 6-h intervals. Behavioral recovery was tested for 12 weeks using two-dimensional (2D) kinematics during weight-supported treadmill walking and the Porcine Injury Behavior Scale (PTIBS), a 10-point locomotion scale. Spinal cords were evaluated ex vivo by diffusion-weighted magnetic resonance imaging (MRI) and subjected to histological analysis. Treatment with AC105 or MgSO4 did not result in improvements in locomotor recovery on the PTIBS or in 2D kinematics on weight-supported treadmill walking. Diffusion weighted imaging (DWI) showed severe loss of tissue integrity at the impact site, with decreased fractional anisotropy and increased mean diffusivity; this was not improved with AC105 or MgSO4 treatment. Histological analysis revealed no significant increase in gray or white matter sparing with AC105 or MgSO4 treatment. Finally, AC105 did not result in higher Mg2+ levels in CSF than with the use of standard MgSO4. In summary, when testing AC105 in a porcine model of SCI, we were unable to reproduce the promising therapeutic benefits observed previously in less-severe rodent models of SCI.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".