Comparison of CatWalk Analysis and von Frey Testing for Pain Assessment in a Rat Model of Nerve Crush Plus Inflammation
Bibliographic record
Abstract
STUDY DESIGN: Assessment of pain-related behavior and immunohistology of the dorsal root ganglion in a rat model. OBJECTIVE: To investigate pain-related behavior in a rat model of nerve crush plus inflammation using the CatWalk system. SUMMARY OF BACKGROUND DATA: A definitive method for evaluating animal models of lumbar disease has not been established. Von Frey testing has often been used in this type of study, but the reliability remains in question. The CatWalk system is a computer-assisted apparatus for analyzing gait that provides an automated way to assess gait function during pain. However, there have been few reports using this system for models of lumbar disease. METHODS: Fourteen rats were divided into 2 groups: a treatment group and a sham group. For the treatment group, nucleus pulposus was applied to the sciatic nerve and the sciatic nerve was pinched. Two different methods for assessment of pain-related behavior, von Frey testing and CatWalk analysis, were used before surgery and at 4 and 7 days after surgery. Immunohistochemistry was used to examine calcitonin gene-related peptide expression in L4 to L6 dorsal root ganglia. RESULTS: No significant differences were found between the treatment and sham control groups using von Frey testing. However, significant differences in 4 parameters were found between the 2 groups using the CatWalk system (P < 0.05). The proportion of calcitonin gene-related peptide-immunoreactive neurons was higher in the treatment group than in the control group (P < 0.05). CONCLUSION: Our results demonstrate that the CatWalk system is useful for the measurement of pain-related behavioral change in our rat model in which nociception was indicated at a cellular level. Although further studies are needed, we think that this system is a valid alternative method for the evaluation of models of lumbar disease in rodents.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 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".