Spinal cord injury in mice affects central and peripheral pathology in a severity-dependent manner
Bibliographic record
Abstract
ABSTRACT: Chronic pain is a common medical complication experienced by those living with spinal cord injury (SCI) and leads to worsened quality of life. The pathophysiology of SCI pain is poorly understood, hampering the development of safe and efficacious therapeutics. We therefore sought to develop a clinically relevant model of SCI with a strong pain phenotype and characterize the central and peripheral pathology after injury. A contusion (50 kdyn) injury, with and without sustained compression (60 seconds) of the spinal cord, was performed on female C57BL/6J mice. Mice with compression of the spinal cord exhibited significantly greater heat and mechanical hypersensitivity starting at 7 days postinjury, concomitant with reduced locomotor function, compared with those without compression. Immunohistochemical analysis of spinal cord tissue revealed significantly less myelin sparing and increased macrophage activation in mice with compression compared with those without. As measured by flow cytometry, immune cell infiltration and activation were significantly greater in the spinal cord (phagocytic myeloid cells and microglia) and dorsal root ganglia (Ly6C+ monocytes) after compression injury. We also decided to investigate the gastrointestinal microbiome, as it has been shown to be altered in patients with SCI and has recently been shown to play a role in immune system maturation and pain. We found increased dysbiosis of the gastrointestinal microbiome in an injury severity-dependent manner. The use of this contusion-compression model of SCI may help advance the preclinical assessment of acute and chronic SCI pain and lead to a better understanding of mechanisms contributing to this pain.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".