Genetic diversity of Shiga toxin-producing Escherichia coli O157 : H7 recovered from human and food sources
Bibliographic record
Abstract
The aim of this study was to identify an epidemiological association between Shiga toxin-producing Escherichia coli O157 : H7 strains associated with human infection and with food sources. Frequency distributions of different genetic markers of E. coli O157 : H7 strains recovered from human and food sources were compared using molecular assays to identify E. coli O157 : H7 genotypes associated with variation in pathogenic potential and host specificity. Genotypic characterization included: lineage-specific polymorphism assay (LSPA-6), clade typing, tir (A255T) polymorphism, Shiga toxin-encoding bacteriophage insertion site analysis and variant analysis of Shiga toxin 2 gene (stx2a and stx2c) and antiterminator Q genes (Q933 and Q21). The intermediate lineage (LI/II) dominated among both food and human strains. Compared to other clades, clades 7 and 8 were more frequent among food and human strains, respectively. The tir (255T) polymorphism occurred more frequently among human strains than food strains. Q21 and Q933 + Q21 were found at significantly higher frequencies among food and human strains, respectively. Moreover, stx2a and stx2a+c were detected at significantly higher frequencies among human strains compared to food strains. Bivariate analysis revealed significant concordance (P<0.05) between the LSPA-6 assay and the other typing methods. Multivariable regression analysis suggested that tir (255T) was the most distinctive genotype that can be used to detect bacterial clones with potential risk for human illness from food sources. This study supported previous reports of the existence of diversity in genetic markers among different isolation sources by including E. coli O157 : H7 strains from both food and human sources. This might enable tracking genotypes with potential risk for human illness from food sources.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".