Absence of Mycobacterium intracellulare and Presence of Mycobacterium chimaera in Household Water and Biofilm Samples of Patients in the United States with Mycobacterium avium Complex Respiratory Disease
Bibliographic record
Abstract
Recent studies have shown that respiratory isolates from pulmonary disease patients and household water/biofilm isolates of Mycobacterium avium could be matched by DNA fingerprinting. To determine if this is true for Mycobacterium intracellulare, household water sources for 36 patients with Mycobacterium avium complex (MAC) lung disease were evaluated. MAC household water isolates from three published studies that included 37 additional MAC respiratory disease patients were also evaluated. Species identification was done initially using nonsequencing methods with confirmation by internal transcribed spacer (ITS) and/or partial 16S rRNA gene sequencing. M. intracellulare was identified by nonsequencing methods in 54 respiratory cultures and 41 household water/biofilm samples. By ITS sequencing, 49 (90.7%) respiratory isolates were M. intracellulare and 4 (7.4%) were Mycobacterium chimaera. In contrast, 30 (73%) household water samples were M. chimaera, 8 (20%) were other MAC X species (i.e., isolates positive with a MAC probe but negative with species-specific M. avium and M. intracellulare probes), and 3 (7%) were M. avium; none were M. intracellulare. In comparison, M. avium was recovered from 141 water/biofilm samples. These results indicate that M. intracellulare lung disease in the United States is acquired from environmental sources other than household water. Nonsequencing methods for identification of nontuberculous mycobacteria (including those of the MAC) might fail to distinguish closely related species (such as M. intracellulare and M. chimaera). This is the first report of M. chimaera recovery from household water. The study underscores the importance of taxonomy and distinguishing the many species and subspecies of the MAC.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".