Contusion, dislocation, and distraction: primary hemorrhage and membrane permeability in distinct mechanisms of spinal cord injury
Bibliographic record
Abstract
OBJECT: In experimental models of spinal cord injury (SCI) researchers have typically focused on contusion and transection injuries. Clinically, however, other injury mechanisms such as fracture-dislocation and distraction also frequently occur. The objective of the present study was to compare the primary damage in three clinically relevant animal models of SCI. METHODS: Contusion, fracture-dislocation, and flexion-distraction animal models of SCI were developed. To visualize traumatic increases in cellular membrane permeability, fluorescein-dextran was infused into the cerebrospinal fluid prior to injury. High-speed injuries (approaching 100 cm/second) were produced in the cervical spine of deeply anesthetized Sprague-Dawley rats (28 SCI and eight sham treated) with a novel multimechanism SCI test system. The animals were killed immediately thereafter so that the authors could characterize the primary injury in the gray and white matter. Sections stained with H & E showed that contusion and dislocation injuries resulted in similar central damage to the gray matter vasculature whereas no overt hemorrhage was detected following distraction. Contusion resulted in membrane disruption of neuronal somata and axons localized within 1 mm of the lesion epicenter. In contrast, membrane compromise in the dislocation and distraction models was observed to extend rostrally up to 5 mm, particularly in the ventral and lateral white matter tracts. CONCLUSIONS: Given the pivotal nature of hemorrhagic necrosis and plasma membrane compromise in the initiation of downstream SCI pathomechanisms, the aforementioned differences suggest the presence of mechanism-specific injury regions, which may alter future clinical treatment paradigms.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".