Bilateral Contusion-Compression Model of Incomplete Traumatic Cervical Spinal Cord Injury
Bibliographic record
Abstract
Despite the increasing incidence and prevalence of cervical spinal cord injury (cSCI), we lack clinically relevant animal models that can be used to study the pathomechanisms of this injury and test new therapies. Here, we characterize a moderate cervical contusion-compression model in rats that is similar to incomplete traumatic cSCI in humans. We characterized the effects of 18-g clip-compression injury at cervical level C6 over an 8-week recovery period. Using Luxol fast blue/hematoxylin-eosin staining in combination with quantitative stereology, we determined that 18-g injury results in loss of gray matter (GM), white matter (WM), as well as in cavity formation. Magnetization transfer and T2-weighted magnetic resonance imaging were used to analyze lesion dynamics in vivo. This analysis demonstrated that both techniques are able to differentiate between the injury epicenter, subpial rim, and WM distal to the injury. Neurobehavioral assessment of locomotor function using Basso, Beattie, and Bresnahan (BBB) scoring and CatWalk revealed limited recovery from clip-compression injury at C6. Testing of forelimb function using grip strength demonstrated significant forelimb dysfunction, similar to the loss of upper-limb motor function observed in human cSCI. Sensory-evoked potentials recorded from the forelimb and Hoffman reflex recorded from the hindlimb confirmed the fore- and hindlimb deficits observed in our neurobehavioral analysis. Here, we have characterized a clip-compression model of incomplete cSCI that closely models this condition in humans. This work directly addresses the current lack of clinically relevant models of cSCI and will thus contribute to improved success in the translation of putative therapies into the clinic.
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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 | 0.001 | 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) | 0.000 | 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".