Repeatability of a Dislocation Spinal Cord Injury Model in a Rat—A High-Speed Biomechanical Analysis
Bibliographic record
Abstract
Dislocation is the most common, and severe, spinal cord injury (SCI) mechanism in humans, yet there are few preclinical models. While dislocation in the rat model has been shown to produce unique outcomes, like other closed column models it exhibits higher outcome variability. Refinement of the dislocation model will enhance the testing of neuroprotective strategies, further biomechanical understanding, and guide therapeutic decisions. The overall objective of this study is to improve biomechanical repeatability of a dislocation SCI model in the rat, through the following specific aims: (i) design new injury clamps that pivot and self-align to the vertebrae; (ii) measure intervertebral kinematics during injury using the existing and redesigned clamps; and (iii) compare relative motion at the vertebrae-clamp interface to determine which clamps provide the most rigid connection. Novel clamps that pivot and self-align were developed based on the quantitative rat vertebral anatomy. A dislocation injury was produced in 34 rats at C4/C5 using either the existing or redesigned clamps, and a high-speed X-ray device recorded the kinematics. Relative motion between the caudal clamp and C5 was significantly greater in the existing clamps compared to the redesigned clamps in dorsoventral translation and sagittal rotation. This study demonstrates that relative motions can be of magnitudes that likely affect injury outcomes. We recommend such biomechanical analyses be applied to other SCI models when repeatability is an issue. For this dislocation model, the results show the importance of using clamps that pivot and self-align to the vertebrae.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".