PREVALENCE AND CHARACTERISTICS OF<i>ESCHERICHIA COLI</i>AND<i>SALMONELLA</i>SPP. IN THE FECES OF WILD URBAN NORWAY AND BLACK RATS (<i>RATTUS NORVEGICUS</i>AND<i>RATTUS RATTUS</i>) FROM AN INNER-CITY NEIGHBORHOOD OF VANCOUVER, CANADA
Bibliographic record
Abstract
Although rat feces are widely suspected to be a source of pathogenic bacteria, few investigators have studied fecal pathogens in rats. We investigated the prevalence and characteristics of Escherichia coli and Salmonella spp. in Norway and black rats (Rattus norvegicus and Rattus rattus, respectively) from an urban neighborhood of Vancouver, Canada, collected September 2011-August 2012. Colon content was cultured for E. coli and Salmonella spp. and screened for the seven most-common enteropathogenic Shiga toxin-producing E. coli (STEC) serotypes by PCR. Isolates were tested for antimicrobial resistance and Salmonella isolates were serotyped. We detected E. coli in 397/633 (62.7%) urban rats. Forty-one of 397 (6.5%) E. coli isolates were resistant to ≥ 1 antimicrobial while 17 (4.3%) were multidrug resistant (including two isolates demonstrating extended-spectrum β-lactamase resistance). Ten of 633 (1.6%) urban rats were carrying STEC serotypes including O145, O103, O26, and O45. Norway rats were more likely to be carrying E. coli compared to black rats, and there was geographic clustering of specific resistance patterns and STEC serotypes. Salmonella spp. were detected in 3/633 (0.5%) rats including serotypes Derby, Indiana, and Enteritidis. In contrast to zoonotic pathogens for which rats are the natural reservoir (e.g., Leptospira interrogans, Rickettsia typhi, Seoul virus), rats likely acquired E. coli and Salmonella spp. from their environment. The ability of rats to be a 'sponge' for environmental pathogens has received little consideration, and the ecology and public health significance of these organisms in rats requires further investigation.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 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".