Antimicrobial Resistance Genes in Multidrug-Resistant <i>Salmonella enterica</i> Isolated from Animals, Retail Meats, and Humans in the United States and Canada
Why this work is in the frame
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Bibliographic record
Abstract
Salmonella enterica is a prevalent foodborne pathogen that can carry multidrug resistance (MDR) and pose a threat to human health. Identifying the genetics associated with MDR in Salmonella isolated from animals, foods, and humans can help determine sources of MDR in food animals and their impact on humans. S. enterica serovars most frequently carrying MDR from healthy animals, retail meats, and human infections in the United States and Canada were identified and isolates resistant to the largest number of antimicrobials were chosen. Isolates were from U.S. slaughter (n=12), retail (9), and humans (9), and Canadian slaughter (9), retail (9), and humans (8; total n=56). These isolates were assayed by microarray for antimicrobial resistance and MDR plasmid genes. Genes detected encoded resistance to aminoglycosides (alleles of aac, aad, aph, strA/B); beta-lactams (bla(TEM), bla(CMY), bla(PSE-1)); chloramphenicol (cat, flo, cmlA); sulfamethoxazole (sulI); tetracycline (tet(A, B, C, D) and tetR); and trimethoprim (dfrA). Hybridization with IncA/C plasmid gene probes indicated that 27/56 isolates carried one of these plasmids; however, they differed in several variable regions. Cluster analysis based on genes detected separated most of the isolates into two groups, one with IncA/C plasmids and one without IncA/C plasmids. Other plasmid replicons were detected in all but one isolate, and included I1 (25/56), N (23/56), and FIB (10/56). The presence of different mobile elements along with similar resistance genes suggest that these genetic elements may acquire similar resistance cassettes, and serve as multiple sources for MDR in Salmonella from food animals, retail meats, and human infections.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| 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 it