Anterior Fracture-Dislocation Is More Severe than Lateral: A Biomechanical and Neuropathological Comparison in Rat Thoracolumbar Spine
Bibliographic record
Abstract
ABSTRACT Fracture-dislocation is one of the most common causes of spinal cord injury (SCI) in human adults, yet it is not widely studied experimentally. Clinical studies have found that anterior fracture-dislocation occurs more commonly and produces greater neurological deficit than lateral fracture-dislocation. However, the effect of loading direction on SCI neuropathology has not been investigated experimentally and the reasons behind these clinical differences are not known. Thoracolumbar vertebrae T12-L1 of anaesthetized rats were dislocated anteriorly or laterally by 9 mm at 220 mm/sec. Spinal cord sections from animals euthanized at 1, 3, and 6 h post-injury, were stained with hematoxylin and eosin (H&E) to detect hemorrhage, the pathologic accumulation of beta-amyloid precursor protein (betaAPP) in white matter axons, and degenerating neurons (Fluoro-Jade and loss of NeuN) in the gray matter. The vertebral fracture load and maximum load were similar for both directions of dislocation; however, vertebral fracture occurred at 4.3 mm (+/-1.5 mm SD) during anterior dislocation compared to 1.1 mm (+/-0.7 mm SD) during lateral dislocation (p < 0.001). betaAPP accumulation and reduction of NeuN immunoreactivity (IR) were greatest along a diagonal band across the spinal cord angled at 45 degrees to the direction of loading (in different planes for each loading direction). Hemorrhage volume (p < 0.05), betaAPP-IR, and reduction of NeuN-IR (p < 0.05 in ventral horns) were more pronounced following anterior dislocation. In addition, there was a different spatial distribution of axonal damage for each direction of dislocation. The findings of this study may explain the greater severity of anterior fracture-dislocation observed clinically and reinforces the need to experimentally model differing human SCIs.
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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 | 0.000 | 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) | 0.000 | 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".