Higher atypical enteropathogenic Escherichia coli (a-EPEC) bacterial loads in children with diarrhea are associated with PCR detection of the EHEC factor for adherence 1/lymphocyte inhibitory factor A (efa1/lifa) gene
Bibliographic record
Abstract
BACKGROUND: Typical enteropathogenic Escherichia coli (t-EPEC) are known to cause diarrhea in children but it is uncertain whether atypical EPEC (a-EPEC) do, since a-EPEC lack the bundle-forming pilus (bfp) gene that encodes a key adherence factor in t-EPEC. In culture-based studies of a-EPEC, the presence of another adherence factor, called EHEC factor for adherence/lymphocyte activation inhibitor (efa1/lifA), was strongly associated with diarrhea. Since a-EPEC culture is not feasible in clinical laboratories, we designed an efa1/lifA quantitative PCR assay and examined whether the presence of efa1/lifA was associated with higher a-EPEC bacterial loads in pediatric diarrheal stool samples. METHODS: Fecal samples from children with diarrhea were tested by qPCR for EPEC (presence of eae gene) and for shiga toxin genes to exclude enterohemorrhagic E. coli, which also contain the eae gene. EPEC containing samples were then tested for the bundle-forming pilus gene found in t-EPEC and efa1/lifA. The eae gene quantity in efa1/lifA-positive and negative samples was compared. RESULTS: Thirty-nine of 320 (12%) fecal samples tested positive for EPEC and 38/39 (97%) contained a-EPEC. The efa1/lifA gene was detected in 16/38 (42%) a-EPEC samples. The median eae concentration for efa1/lifA positive samples was significantly higher than for efa1/lifA negative samples (median 16,745 vs. 1183 copies/µL, respectively, p = 0.006). CONCLUSIONS: Atypical enteropathogenic E. coli-positive diarrheal stool samples containing the efa1/lifA gene had significantly higher bacterial loads than samples lacking this gene. This supports the idea that efa1/lifA contributes to diarrheal pathogenesis and suggests that, in EPEC-positive samples, efa/lifA may be a useful additional molecular biomarker.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".