OMNIgene.SPUTUM suppresses contaminants while maintaining<i>Mycobacterium tuberculosis</i>viability and obviates cold-chain transport
Bibliographic record
Abstract
Tuberculosis (TB) diagnostics are centralised, requiring long-distance transportation of specimens in most resource-limited settings. We evaluated the ability of OMNIgene.SPUTUM (OM-S) to obviate cold-chain transport of TB specimens. A two-arm (same-day and after 5 days sample processing) study was conducted to assess contamination rates andMycobacterium tuberculosisviability in OM-S-treated samples against the standard decontamination procedure (SDP) in Mozambique, using Lowenstein Jensen (LJ) and mycobacterial growth indicator tube (MGIT) culture and molecular bacterial load assay. 270 specimens were processed using OM-S and SDP in same-day and 5-day arms. Contamination was lower in OM-S-treated than SDP-treated cultures: 12%versus15% and 2%versus27% in the same-day and 5-day arms, respectively.M. tuberculosisrecovery in OM-S-treated LJ cultures was 10% and 56% higher in the same-day and 5-day arms, respectively, than SDP-treated cultures, but lower in MGIT (52% and 28% lower in the same-day and 5-day arms, respectively).M. tuberculosisviable count was 1log estimated CFU·mL−1lower in 5-day OM-S-treated sputa. OM-S was more effective at liquefying sputum with a shorter sample processing time: 22 min for culture. OM-S is simple to use and has demonstrated a high potency to suppress contaminants, maintenance of viability at ambient temperatures and higherM. tuberculosisrecovery, particularly in the solid LJ cultures. Optimisation of OM-S to achieve higher MGIT culture positivity and shorter time to result will increase its application and utility in the clinical management of TB.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".