A Pilot Study to Detect Viable Salmonella spp. in Diarrheal Stool Using Viability Real-Time PCR as a Culture-Independent Diagnostic Tool in a Clinical Setting
Bibliographic record
Abstract
Frontline laboratories are adopting culture-independent diagnostic testing (CIDT) such as nucleic acid amplification tests (NAATs) due to numerous advantages over culture-based testing methods. Paradoxically, the viability of pathogens, a crucial factor determining active infections, cannot be confirmed with current NAATs alone. A recent development of viability PCR (vPCR) was introduced to mitigate this limitation associated with real-time PCR (qPCR) by using a DNA-intercalating dye to remove residual and dead cell DNA. This study assessed the applicability of the vPCR assay on diarrheal stools. Eighty-five diarrheal stools confirmed for Salmonellosis were tested via qPCR and vPCR using in-house primers and probe targeting the invA gene. vPCR-negative stools (Ct cut off > 31) were enriched in mannitol selenite broth (MSB) to verify low bacterial loads. vPCR assay showed ~89% sensitivity (qPCR- and vPCR-positive stools: 76/85). vPCR-negative stools (9/85; qPCR-positive: 5; qPCR-negative: 4) were qPCR- and culture-positive post-MSB-enrichment and confirmed the presence of low viable bacterial loads. Random sampling error, low bacterial loads, and receiving stools in batches could contribute to false negatives. This is a pilot study and further investigations are warranted to explore vPCR to assess pathogen viability in a clinical setting, especially when culture-based testing is unavailable.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 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".