Clinical and Immunologic Features of an Atypical Intracranial<i>Mycobacterium avium</i>Complex (MAC) Infection Compared with Those of Pulmonary MAC Infections
Bibliographic record
Abstract
Members of the Mycobacterium avium complex (MAC) may cause chronic pulmonary infections in otherwise healthy elderly persons but rarely invade parts of the body outside of the lungs in immunocompetent hosts. We present a case of an isolated intracranial MAC infection in an apparently immunocompetent individual and review previous reports. We studied the T-cell and monocyte responses in healthy volunteers, individuals with a pulmonary MAC infection, and one individual with an isolated intracranial MAC infection. Genomic DNA from the individual with the brain MAC infection was studied for gamma interferon (IFN-gamma) receptor mutations. Individuals with localized pulmonary MAC infections showed increased activation of monocytes and enhanced monocyte and T-cell tumor necrosis factor alpha (TNF-alpha) production in response to lipopolysaccharide and MAC antigens but defects in T-cell IFN-gamma secretion. The individual with an intracranial MAC infection showed a lack of monocyte activation and deficiencies in both monocyte and T-cell TNF-alpha production and monocyte interleukin-12 (IL-12) production but had preserved T-cell IFN-gamma production. Mutations or deletions in the IFN-gamma receptor were not detected in the individual with the intracranial MAC infection. Our data suggest that distinct immune defects characterize two different manifestations of MAC infection. A relative defect in IFN-gamma production in response to MAC may predispose an individual to localized but partially controlled lung disease, whereas defects leading to reduced IL-12 and TNF-alpha production may allow the dissemination of MAC. Further studies delineating the potential role of TNF-alpha in limiting the spread of MAC outside the lung are warranted.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".