Responses of the Acutely Injured Spinal Cord to Vibration that Simulates Transport in Helicopters or Mine-Resistant Ambush-Protected Vehicles
Bibliographic record
Abstract
In the military environment, injured soldiers undergoing medical evacuation via helicopter or mine-resistant ambush-protected vehicle (MRAP) are subjected to vibration and shock inherent to the transport vehicle. We conducted the present study to assess the consequences of such vibration on the acutely injured spinal cord. We used a porcine model of spinal cord injury (SCI). After a T10 contusion-compression injury, animals were subjected to 1) no vibration (n = 7-8), 2) whole body vibration at frequencies and amplitudes simulating helicopter transport (n = 8), or 3) whole body vibration simulating ground transportation in an MRAP ambulance (n = 7). Hindlimb locomotor function (using Porcine Thoracic Injury Behavior Scale [PTIBS]), Eriochrome Cyanine histochemistry and biochemical analysis of inflammatory and neural damage markers were analyzed. Cerebrospinal fluid (CSF) expression levels for monocyte chemoattractant protein-1 (MCP-1), interleukin (IL)-6, IL-8, and glial fibrillary acidic protein (GFAP) were similar between the helicopter or MRAP group and the unvibrated controls. Spared white/gray matter tended to be lower in the MRAP-vibrated animals than in the unvibrated controls, especially rostral to the epicenter. However, spared white/gray matter in the helicopter-vibrated group appeared normal. Although there was a relationship between the extent of sparing and the extent of locomotor recovery, no significant differences were found in PTIBS scores between the groups. In summary, exposures to vibration in the context of ground (MRAP) or aeromedical (helicopter) transportation did not significantly impair functional outcome in our large animal model of SCI. However, MRAP vibration was associated with increased tissue damage around the injury site, warranting caution around exposure to vehicle vibration acutely after SCI.
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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) | 0.000 | 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 | 0.001 |
| 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".