Identification of mycobacterial species by PCR restriction enzyme analysis of the <i>hsp65</i> gene — an Indian experience
Bibliographic record
Abstract
Nowadays, nontuberculous mycobacteria (NTM) often cause pulmonary and extrapulmonary disease. Species identification of NTM determines the line of treatment and management of the disease. The routine diagnostic methods, i.e., smear microscopy and biochemical identification, of nontuberculous mycobacteria are tedious and time consuming and not all laboratories can perform these tests on a routine basis. A PCR targeting the hsp65 gene was implemented using standard strains and was applied to 109 clinical isolates. The PCR-amplified product was subjected to restriction enzyme analysis using BstEII and HaeIII. The results obtained were compared with that of biochemical tests. Of 109 NTM, 107 were identified to species level. PCR plus restriction enzyme analysis (PRA) identified 12 types of NTM. Common species identified were Mycobacterium chelonae (32), a rapid growing NTM, and Mycobacterium avium complex (21), among the slow growing NTM. PRA and biochemical identification showed 95.32% (102/107) concordant results. PRA is fast, cheap, and accurate for identification of potentially pathogenic NTM.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 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) | 0.002 | 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".