rpoB Targeted Loop-Mediated Isothermal Amplification (LAMP) Assay for Consensus Detection of Mycobacteria Associated With Pulmonary Infections
Bibliographic record
Abstract
Loop-mediated isothermal amplification (LAMP) is a nucleic acid method which has been used to identify mycobacteria including Mycobacterium tuberculosis in clinical microbiology laboratory and point-of-care settings. Previously published LAMP protocols for detection of mycobacterial species used conventional native primer and targeted the 16S rRNA, gyrB and insertion sequence genes. We developed and evaluated a LAMP assay targeting a mycobacterial rpoB gene conserved sequence and incorporating degenerate primers. This assay allowed consensus detection of mycobacterial species from pure culture, clinical respiratory tract samples and MGIT liquid-based culture medium. A panel of twenty mycobacterial species were successfully detected at detection thresholds of 102 CFU/mL and 103 CFU/mL when respectively performed on pure culture suspension or sputum and MGIT broth. The inclusion of degenerate bases in LAMP primers increased the diversity of mycobacterial species identified by the assay without negatively affecting analytical sensitivity. LAMP-based consensus detection of multiple pathogens can be achieved with degenerate primers therefore allowing the design of rapid multi-disease screening assays. Despite high analytical sensitivity, species specificity and the advantageous operational characteristics of LAMP over PCR, challenges such as potential ambiguity in visual interpretation of results and occasional non-specific amplification precludes the implementation of novel LAMP assay in routine diagnostics both in centralized and point-of-care laboratory.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".