Distribution of class 1 integrons among enteropathogenic<i>Escherichia coli</i>
Bibliographic record
Abstract
The aim of this study was to investigate the incidence of and resistance gene content of class 1 integrons among enteropathogenic Escherichia coli (EPEC) and non-EPEC and to investigate intraspecies genetic diversity of EPEC strains isolated from children with diarrhea in Iran. Twenty-eight EPEC and 16 non-EPEC strains isolated from children with diarrhea were tested for the presence of a class 1 integron associated integrase gene (int1). Sequence analysis was performed to identify the resistance gene content of integrons. Genetic diversity and cluster analysis of EPEC isolates were also investigated using enterobacterial repetitive intergenic concensus-polymerase chain reaction (ERIC-PCR) fingerprinting. Twenty-three (82%) EPEC isolates and 11 (68.7%) non-EPEC isolates harbored the int1 gene specific to the conserved integrase region of class 1 integrons. Sequence analysis revealed the dominance of dfrA and aadA gene cassettes among the isolates of both groups. ERIC-PCR fingerprinting of EPEC isolates revealed a high diversity among these isolates. The widespread distribution of 2 resistance gene families (dfrA and aadA) among both groups of EPEC and non-EPEC isolates indicates the significance of integrons in antibiotic resistance transfer among these bacteria. Furthermore, clonal diversity of EPEC isolates harbouring a class 1 integron also suggests the circulation of these mobile elements among a diverse population of EPEC in this country.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".