Cage-lid hanging behavior as a translationally relevant measure of pain in mice
Bibliographic record
Abstract
ABSTRACT: The development of new analgesic drugs has been hampered by the inability to translate preclinical findings to humans. This failure is due in part to the weak connection between commonly used pain outcome measures in rodents and the clinical symptoms of chronic pain. Most rodent studies rely on the use of experimenter-evoked measures of pain and assess behavior under ethologically unnatural conditions, which limits the translational potential of preclinical research. Here, we addressed this problem by conducting an unbiased, prospective study of behavioral changes in mice within a natural homecage environment using conventional preclinical pain assays. Unexpectedly, we observed that cage-lid hanging, a species-specific elective behavior, was the only homecage behavior reliably impacted by pain assays. Noxious stimuli reduced hanging behavior in an intensity-dependent manner, and the reduction in hanging could be restored by analgesics. Finally, we developed an automated approach to assess hanging behavior. Collectively, our results indicate that the depression of hanging behavior is a novel, ethologically valid, and translationally relevant pain outcome measure in mice that could facilitate the study of pain and analgesic development.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.000 |
| 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) | 0.003 | 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".