Nontuberculous mycobacteria in patients with suspected tuberculosis and the genetic diversity of Mycobacterium avium in the extreme south of Brazil
Bibliographic record
Abstract
OBJECTIVE: Nontuberculous mycobacteria (NTM) are a heterogeneous group of bacteria that are widely distributed in nature and associated with opportunistic infections in humans. The aims of this study were to identify NTM in patients with suspected tuberculosis who presented positive cultures and to evaluate the genetic diversity of strains identified as Mycobacterium avium. METHODS: We studied pulmonary and extrapulmonary samples obtained from 1,248 patients. The samples that tested positive on culture and negative for the M. tuberculosis complex by molecular identification techniques were evaluated by detection of the hsp65 and rpoB genes and sequencing of conserved fragments of these genes. All strains identified as M. avium were genotyped using the eight-locus mycobacterial interspersed repetitive unit-variable-number tandem-repeat method. RESULTS: We found that NTM accounted for 25 (7.5%) of the 332 mycobacteria isolated. Of those 25, 18 (72%) were M. avium, 5 (20%) were M. abscessus, 1 (4%) was M. gastri, and 1 (4%) was M. kansasii. The 18 M. avium strains showed high diversity, only two strains being genetically related. CONCLUSIONS: These results highlight the need to consider the investigation of NTM in patients with suspected active tuberculosis who present with positive cultures, as well as to evaluate the genetic diversity of M. avium strains.
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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 | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".