Pauci- and Multibacillary Leprosy: Two Distinct, Genetically Neglected Diseases
Bibliographic record
Abstract
After sustained exposure to Mycobacterium leprae, only a subset of exposed individuals develops clinical leprosy. Moreover, leprosy patients show a wide spectrum of clinical manifestations that extend from the paucibacillary (PB) to the multibacillary (MB) form of the disease. This "polarization" of leprosy has long been a major focus of investigation for immunologists because of the different immune response in these two forms. But while leprosy per se has been shown to be under tight human genetic control, few epidemiological or genetic studies have focused on leprosy subtypes. Using PubMed, we collected available data in English on the epidemiology of leprosy polarization and the possible role of human genetics in its pathophysiology until September 2015. At the genetic level, we assembled a list of 28 genes from the literature that are associated with leprosy subtypes or implicated in the polarization process. Our bibliographical search revealed that improved study designs are needed to identify genes associated with leprosy polarization. Future investigations should not be restricted to a subanalysis of leprosy per se studies but should instead contrast MB to PB individuals. We show the latter approach to be the most powerful design for the identification of genetic polarization determinants. Finally, we bring to light the important resource represented by the nine-banded armadillo model, a unique animal model for leprosy.
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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) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".