No isolate, no problem: Using a novel insertion sequence PCR to link rats to human shigellosis cases in an underserved urban community
Bibliographic record
Abstract
Abstract Introduction During an investigation into a cluster of Shigella flexneri serotype 2a cases in an underserved community, we assessed the relatedness of human and rat S. flexneri isolates utilizing a novel PCR targeting insertion sites (IS-PCR) of mobile elements in the Shigella genome characteristic of the cluster strain. Methods Whole genome sequences of S. flexneri (n=50) associated with the cluster were analyzed. de novo genome assemblies were analyzed by a Geneious V10.2.6 motif search, and 2 unique IS were identified in all human Shigella sequences of the local cluster. Hydrolysis probe PCR assays were designed to detect these sequences consisting of forward and reverse primers to amplify across each insertion site, and a hydrolysis probe spanning the insertion site. IS-PCR was performed for three Shigella PCR-positive culture-negative rat intestine specimens from this community. Results Both insertion sites were detected in the de novo genome assemblies of all clinical S. flexneri isolates (n=50). Two of the three PCR-positive culture-negative rat samples were positive for both unique IS identified in the human S. flexneri isolates, suggesting that the rat Shigella spp. strains were closely related to the human strains in the cluster. The cycle threshold (Ct) values were >35, indicating that the bacterial load was very low in the rat samples. Conclusions Two unique IS were identified in clinical isolates from a community S. flexneri cluster. Both IS targets were identified in PCR-positive ( Shigella spp.), culture-negative rat tissue and clinical isolates from humans, indicating relatedness.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".