O157:H7 and O104:H4 Vero/Shiga toxin-producing Escherichia coli outbreaks: respective role of cattle and humans
Bibliographic record
Abstract
An enteroaggregative Verotoxin (Vtx)-producing Escherichia coli strain of serotype O104:H4 has recently been associated with an outbreak of haemolytic-uremic syndrome and bloody diarrhoea in humans mainly in Germany, but also in 14 other European countries, USA and Canada. This O104:H4 E. coli strain has often been described as an enterohaemorrhagic E. coli (EHEC), i.e. a Vtx-producing E. coli with attaching and effacing properties. Although both EHEC and the German O104:H4 E. coli strains indeed produce Vtx, they nevertheless differ in several other virulence traits, as well as in epidemiological characteristics. For instance, the primary sources and vehicles of typical EHEC infections in humans are ruminants, whereas no animal reservoir has been identified for enteroaggregative E. coli (EAggEC). The present article is introduced by a brief overview of the main characteristics of Vtx-producing E. coli and EAggEC. Thereafter, the O104:H4 E. coli outbreak is compared to typical EHEC outbreaks and the virulence factors and host specificity of EHEC and EAggEC are discussed. Finally, a renewed nomenclature of Vtx-producing E. coli is proposed to avoid more confusion in communication during future outbreaks and to replace the acronym EHEC that only refers to a clinical condition.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".