Development and Characterization of a Novel, Graded Model of Clip Compressive Spinal Cord Injury in the Mouse: Part 1. Clip Design, Behavioral Outcomes, and Histopathology
Bibliographic record
Abstract
In order to take advantage of various genetically manipulated mice available to study the pathophysiology of spinal cord injury (SCI), we adapted an extradural clip compression injury model to the mouse (FEJOTA mouse clip). The dimensions of the modified aneurysm clip blades were customized for application to the mouse spinal cord. Three clips with different springs were made to produce differing magnitudes of closing force (3, 8, and 24 g). The clips were calibrated regularly to ensure that the closing force remained constant. The surgical procedure involved a laminectomy at T3 and T4, followed by extradural application of the clip at this level for 1 min to produce SCI. Three injury severities (3, 8, and 24 g), sham (passage of dissector extradurally at T3-4), and transection control groups were examined (n = 12/group). Quantitative behavioural assessments using the Basso, Beattie, and Bresnahan (BBB; H > 46; df = 4; p < 0.001; Kruskal-Wallis one-way ANOVA) and inclined plane (IP; F = 123; df = 4; p < 0.0001; two-way repeated measures ANOVA) tests showed a significant graded increase in neurological deficits with increasing severity of injury. By day 14, the motor recovery of the mice plateaued. Qualitative examination of the injury site morphology indicated that microcystic cavitation, degenerating axons, and robust astrogliosis were characteristic of the murine response to clip compressive SCI. Morphometric analyses of H&E/Luxol Fast Blue stained sections at every 50 microm from the injury epicenter indicated that with greater injury severity there was a progressive decrease in residual tissue (F = 220, df = 3; p < 0.0001; two-way ANOVA). In addition, statistically significant differences were found in the amount of residual tissue at the injury epicenter between all of the injury severities (p < 0.05, SNK test). This novel, graded compressive model of SCI will facilitate future studies of the pathological mechanisms of SCI using transgenic and knockout murine systems.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".