Data_Sheet_1_Multidrug Resistance in Pasteurellaceae Associated With Bovine Respiratory Disease Mortalities in North America From 2011 to 2016.docx
Bibliographic record
Abstract
<p>Multidrug-resistant (MDR; resistance to ≥3 antimicrobial classes) members of the Pasteurellaceae family may compromise the efficacy of therapies used to prevent and treat bovine respiratory disease (BRD) in feedlot cattle. This study examined the prevalence of multidrug resistance in strains of Mannheimia haemolytica and Pasteurella multocida collected from BRD cattle mortalities in North America. Isolates of M. haemolytica (n = 147) and P. multocida (n = 70) spanning 69 Alberta feedlots from 2011 to 2016 and two United States feedlots from 2011 to 2012 were examined for antimicrobial resistance (AMR) in association with integrative and conjugative elements (ICEs). Overall, resistance was high in both bacterial species with an increase in the prevalence of MDR isolates between 2011 and 2016. Resistance to >7 antimicrobial drugs occurred in 31% of M. haemolytica and 83% of P. multocida isolates. Resistance to sulfadimethoxine, trimethoprim/sulfamethoxazole, neomycin, clindamycin oxytetracycline, spectinomycin, tylosin, tilmicosin, and tulathromycin was most common. Although >80% of strains harbored three or more ICE-associated genes, only 12% of M. haemolytica and 77% of P. multocida contained all six, reflecting the diversity of ICEs. There was evidence of clonal spread as P. multocida and M. haemolytica isolates with the same pulsed-field gel electrophoresis profile from the United States in 2011 were isolated in Alberta in 2015–2016. This work highlights that MDR strains of Pasteurellaceae containing ICEs are widespread and may be contributing to BRD therapy failure in feedlot cattle. Given the antimicrobial resistance gene profiles identified, these MDR isolates may be selected for by the use of macrolides, tetracyclines, and/or in-feed supplements containing heavy metals.</p>
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 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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.114 | 0.015 |
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; both teacher heads agree on what is shown here.
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".