Influence of genotype, dose and sex on pruritogen-induced scratching behavior in the mouse
Bibliographic record
Abstract
Itch features considerable interindividual variability in humans, and initial studies using animal models have demonstrated a likely role of genetic factors in mediating such variability. In an attempt to systematically study genetic mediation of itch in the mouse such that gene identification by linkage mapping might be achieved, we examined scratching behavior induced by histamine and chloroquine in mice of 11 inbred mouse strains. Multiple chloroquine drug doses were used, revealing the existence of inverted-U dose-response relationships in every strain, allowing us to determine strain-dependent peak scratching behavior over the entire dose range. Peak chloroquine-induced scratching varied by 2.5-fold in this set of strains; scratching behavior shows moderate heritability in the mouse. The present data also reveal, for the first time, significant sex differences in pruritogen-induced scratching behavior, with female mice scratching an average of 23% more than males. Finally, a comparison of the strain means obtained here with previously collected data using nociceptive assays revealed a suggestive negative genetic correlation between chloroquine-induced itch and thermal pain, such that strains sensitive to pain are resistant to itch and vice versa. This finding may have implications both for our understanding of itch pathophysiology and for the identification of itch-related genes.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 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 | 0.001 |
| 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".