Identification of quantitative trait loci for chemical/inflammatory nociception in mice
Bibliographic record
Abstract
Sensitivity to pain is widely variable, and much of this variability is genetic in origin. The specific genes responsible have begun to be identified, but only for thermal nociception. In order to facilitate the identification of polymorphic, pain-related genes with more clinical relevance, we performed quantitative trait locus (QTL) mapping studies of the most common assay of inflammatory nociception, the formalin test. QTL mapping is a technique that exploits naturally occurring variability among inbred strains for the identification of genomic locations containing genes contributing to that variability. An F2 intercross was constructed using inbred A/J and C57BL/6J mice as progenitors, strains previously shown to display resistance and sensitivity, respectively, to formalin-induced nociception. Following phenotypic testing (5% formalin, 25 microl intraplantar injection), mice were genotyped at 90 microsatellite markers spanning the genome. We provide evidence for two statistically significant formalin test QTLs - chromosomal regions whose inheritance is associated with trait variability - on distal mouse chromosomes 9 and 10. Identification of the genes underlying these QTLs may illuminate the basis of individual differences in inflammatory pain, and lead to novel analgesic treatment strategies.
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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 | 0.001 | 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".