Metallo-beta-lactamase-producing <i>Escherichia coli</i> in the sewage of Mexico City: where do they come from?
Bibliographic record
Abstract
While monitoring the presence of antibiotic resistance in municipal wastewater bacteria from Mexico City, five Escherichia coli isolates were found to be resistant to carbapenems, antibiotics of “last resort” used mostly in hospitals. Further analysis revealed that these carbapenem-resistant isolates carried the gene encoding a metallo-beta-lactamase, NDM-5. The gene was found to be beared by a large, ∼145 kb conjugative plasmid, which also carries putative genes encoding resistance to sulfonamides, trimethoprim, tetracycline, ciprofloxacin, and chloramphenicol (although no phenotypic chloramphenicol resistance was detected) and quaternary-ammonium compounds. The plasmid also carried gene mobility determinants, such as integron integrase and two transposases. In addition to the direct public health threat posed by the presence of such multi-resistant organisms in wastewater released into the environment and used for crop irrigation; it is particularly concerning that carbapenem-resistant E. coli is rather rare in Mexican hospitals (<1%), but was found in small, 100 mL samples of municipal wastewater. This suggests that these organisms are under-reported by clinical microbiology laboratories, underlining the usefulness of wastewater monitoring, or that there is an unknown source of such carbapenem-resistant organisms that are being dumped into the wastewater. The source of these bacteria must be assessed and controlled to prevent further spread of this multi-resistance plasmid among other environmental and clinical microorganisms.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".