Positional cloning of a quantitative trait locus contributing to pain sensitivity: possible mediation by <i>Tyrp1</i>
Bibliographic record
Abstract
To identify novel pain-relevant genes, a set of 35 recombinant congenic strains derived from the sensitive C57BL/6 and resistant A/J strains were tested for their sensitivity to noxious heat on the radiant heat paw-withdrawal test. Nine strains were found to display differential sensitivity, and the two most extreme responders were used to generate independent secondary crosses for quantitative trait locus (QTL) mapping. From these genetic analyses, a QTL, which we call Tpnr5, was mapped to a 14-Mb interval of mouse chromosome 4 containing 39 genes. In addition to the paw-withdrawal test phenotype, Tpnr5 may be relevant to mechanical and inflammatory nociception. A series of strategies - including in silico analyses, reverse transcriptase polymerase chain reaction (RT-PCR) in multiple tissues and exonic DNA sequencing - were used to generate a list of six prioritized candidate genes. One of these, tyrosinase-related protein 1 (Tyrp1), displayed enriched expression in the dorsal root ganglia, an inactivating (C110Y) mutation in the resistant A/J strain, and a null mutant found to be more resistant to thermal nociception compared to its wild-type counterpart. Although other genes cannot be definitively ruled out, existing data are supportive of the candidacy of Tyrp1 as representing the Tpnr5 QTL. Tyrosinase-related protein 1 is the rate-limiting enzyme in the production of eumelanin, and possible relationships between eumelanin-expressing cells and thermal nociception are discussed. The positional cloning of Tpnr5 is also considered in light of the heuristic value but continuing challenges of QTL mapping in the mouse.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".