Associations between Antimicrobial Resistance Genes in Fecal Generic <i>Escherichia coli</i> Isolates from Cow-Calf Herds in Western Canada
Bibliographic record
Abstract
The objective of this study was to examine associations among the genetic determinants of antimicrobial resistance (AMR) in 207 fecal generic Escherichia coli isolates obtained from 77 cow-calf herds in western Canada. Twenty-three resistance genes corresponding to six different antimicrobial families were assessed using DNA hybridization and PCR. The most common resistance genes in the study sample (207 isolates) were sul2 (48.3%), tet(B) (45.4%), and ant(3'')-Ia (aadA1) (19.3%). Several statistically significant associations between the examined resistance genes were detected. The strongest associations observed were those between genes for resistance to chloramphenicol (catI) and trimethoprim (dhfrI) (odds ratio [OR] = 214; P = 0.0001), sulfonamide (sul1) and chloramphenicol (catI) (OR = 96.9; P = 0.0001), streptomycin [ant(3'')-Ia (aadA1)] and trimethoprim (dhfrI) (OR = 96.2; P = 0.0001), sulfonamide (sul1) and streptomycin [ant(3'')-Ia (aadA1)] (OR = 79.3; P = 0.0001), and tetracycline [tet(B)] and sulfonamides (sul2) (OR = 25.7; P = 0.0001). At least one of the resistance genes corresponding to each nonaminoglycoside family of antimicrobials examined in this study was associated with the two aminoglycoside resistance genes ant(3'')-Ia (aadA1) and aph(3')-Ia. The multiple, strong associations between genes and the diverse nature of the associations described in this study demonstrate the complexity of resistance gene selection in cow-calf herds and should be considered in the planning of AMR control practices for cow-calf operations.
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How this classification was reachedexpand
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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".