The Effect of Mitomycin C on Induction of Shiga Toxin Production in Clinical STEC Isolates
Bibliographic record
Abstract
Early determination of the Shiga toxin type of Shiga toxin-producing Escherichia coli (STEC) is crucial for guiding STEC-infected patients for proper and timely treatment and patient care. Most diagnostic microbiology laboratories rely on PCR assays to detect the presence of stx1 and/or stx2 and enzymatic immunoassays (EIA) to detect the presence of the Shiga toxins 1 and/or 2 in STEC-positive stool samples. Occasionally, the stool samples test positive for STEC by PCR assays but test negative for the presence of Shiga toxins. Insufficient toxin production under laboratory conditions is the main culprit of this discordance. To test whether EIA-based STEC detection could be improved, various clinical STEC strains were treated with mitomycin C, which is a commonly used inducer of Shiga toxin production. A dose-dependent increase in Shiga toxin production, in response to mitomycin C doses of up to 500 ng/mL, was observed without any bactericidal effects. Depending on the serotype, 5–50 times more Shiga toxin 2 was produced than Shiga toxin 1. Shiga toxin production was not induced by the mitomycin C treatment in certain STEC serotypes carrying the toxin subtypes stx1a, stx2a, 2b, 2f, or 2h. This diversity in toxin production indicates that other factors may determine toxin expression in certain STEC strains, which warrant further exploration.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".