Differential survival of potentially pathogenic, septicemia- and meningitis-causing E. coli across the wastewater treatment train
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract A growing body of evidence indicates that extraintestinal pathogenic E. coli (ExPEC) readily survive wastewater treatment, raising concerns about the public health risks associated with exposure to wastewater-contaminated environments. In this study, E. coli isolates recovered from chlorinated sewage or treated wastewater effluents in Canada were screened for ExPEC virulence markers. Eighty-six isolates were identified as presumptive ExPEC, clustering within major pandemic lineages including ST131, ST95, and ST73 according to multilocus sequence typing analyses. Across the whole, core, and accessory genome, 37 isolates were extremely similar to clinical bloodborne E. coli (BBEC) and neonatal meningitic E. coli (NMEC) strains, suggesting that these wastewater isolates may exhibit a similar phenotypically related pathogenic potential. Interestingly, ExPEC strains also shared accessory gene content with naturalized wastewater strains, suggesting a common genetic capacity for surviving water treatment. Collectively, these findings suggest that E. coli strains that may cause septicemia and meningitis are surviving wastewater treatment and may be transmissible through wastewater effluents.
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.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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 it