A hypothesis for the existence of two types of tuberculosis, reflecting two distinct types of immune failure to control the pathogen, based upon prevalence of mycobacterium‐specific IgG subclasses
Bibliographic record
Abstract
Most people infected by Mycobacterium tuberculosis, about 90%, contain the pathogen and are healthy. Most investigators have concluded that pathogen-specific Th1 cells contribute to protection. Pulmonary tuberculosis, the most prevalent form of disease, is associated with destructive granulomas, the formation of which also appears to involve Th1 cells. In what sense then do the two Th1 components of the response, in healthy infected individuals and patients, differ? An insight into this question might provide clues for attaining effective vaccination and better treatment. We approached this question by examining the relative prevalence of different IgG isotypes among anti-mycobacterium-specific antibodies in patients and healthy infected individuals as a surrogate marker for the Th1/Th2 phenotype of the response. Our observations lead us to agree that healthy infected individuals generate a predominant Th1 response. Our observations also lead us to propose that many patients make a similar kind of response as healthy infected individuals, but that this response is too weak to contain the infection. We refer to such individuals as having type I tuberculosis. Other patients appear to have a greater and detrimental Th2 component to their immune response than that of healthy infected individuals. We refer to these individuals as having type II tuberculosis. This proposal that there are two types of tuberculosis, reflecting two distinct types of failure by the immune system, will, if correct, be pertinent to vaccine design, treatment of tuberculosis and in making further progress in our understanding the genetics of susceptibility to M. tuberculosis.
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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 | 0.007 | 0.009 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.002 | 0.019 |
| Scholarly communication | 0.003 | 0.009 |
| Open science | 0.006 | 0.004 |
| Research integrity | 0.008 | 0.007 |
| Insufficient payload (model declined to judge) | 0.006 | 0.003 |
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".