Testing the Benefits of Rat Tickling on a Rodent Model of Persistent Inflammatory Pain
Bibliographic record
Abstract
Chronic pain is a debilitating health problem that affects billions of people worldwide, requiring new, safe, and effective treatments. Current approaches to addressing this issue include nocifensive (pain-related) behaviour testing in animals and investigations of specific molecular determinants to observe how they influence pain behaviours in rodent models. Pain is a biopsychosocial phenomenon, even in rodents, and emotional/stressful states and basal experiences can modulate pain outputs, which can be a major confound in nocifensive behaviour testing. This project explored the effects of rat tickling (playful handling by the experimenter that mimics natural rough-and-tumble play) on the lab’s well-established persistent inflammatory pain model using von Frey filament (VFF) testing and recordings of 22- (alarm calls) and 50-kHz (indicative of positive affect) ultrasonic vocalizations (USVs). Adult male Sprague Dawley rats underwent tickle training or gentle handling followed by evoked somatosensory VFF testing. Baseline testing was followed by a subcutaneous left hind paw footpad injection of 0.3 mL of the pro-inflammatory substance Complete Freund’s Adjuvant (CFA) or vehicle. The animals then underwent VFF testing 24-, 48-, and 72-hours post-injection to verify that pain hypersensitivity was induced. Both tickled and gentle handled rats produced similar VFF testing results, but tickled rats produced more 50-kHz USVs than gentle handled rats. These results suggest both conditions are effective acclimation strategies, but that tickling seems to increase the production of 50-kHz USVs, suggesting improved welfare of the animals. We conclude that animal welfare is an important factor to consider when conducting VFF nocifensive behaviour testing.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".