A Recessive Major Gene Controls the Mitsuda Reaction in a Region Endemic for Leprosy
Bibliographic record
Abstract
BACKGROUND: Leprosy is a chronic infectious disease caused by Mycobacterium leprae. The Mitsuda reaction is a delayed granulomatous skin reaction elicited by intradermal injection of heat-killed M. leprae. Interestingly, results of the Mitsuda test are positive in the majority of individuals, even in areas not endemic for M. leprae. Like leprosy, the Mitsuda reaction is thought to be genetically controlled, but its mode of inheritance is unknown, although the role of the NRAMP1 gene has previously been reported. METHODS: We conducted a segregation analysis of quantitative Mitsuda reactivity in 168 Vietnamese nuclear families ascertained through patients with leprosy. RESULTS: We found strong evidence (P<10-9) for a major gene controlling the Mitsuda reaction independently of leprosy clinical status. Subsequent linkage analysis showed that this major gene was distinct from NRAMP1. Under the major-gene model, approximately 12% of individuals are homozygous for the recessive predisposing allele and are predicted to display high levels of Mitsuda reactivity (mean, approximately 10 mm, versus 5 mm in other individuals). CONCLUSION: We provide evidence that the Mitsuda reaction is controlled by a major gene. Our study paves the way for the identification of this gene and should provide novel insight into the mechanisms involved in granuloma formation, especially in M. leprae infection.
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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 | 0.001 |
| 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) | 0.003 | 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".