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Record W3211065767 · doi:10.3389/fvets.2021.764701

Prevalence, Risk Factors, and Antimicrobial Resistance Profile of Respiratory Pathogens Isolated From Suckling Beef Calves to Reprocessing at the Feedlot: A Longitudinal Study

2021· article· en· W3211065767 on OpenAlexafffund
Diego B. Nóbrega, Sara Andrés-Lasheras, Rahat Zaheer, Tim A. McAllister, Elizabeth R. Homerosky, R. Michele Anholt, Craig Dorin

Bibliographic record

VenueFrontiers in Veterinary Science · 2021
Typearticle
Languageen
FieldImmunology and Microbiology
TopicMicrobial infections and disease research
Canadian institutionsAgriculture and Agri-Food CanadaUniversity of CalgaryUniversity of Guelph
FundersAgriculture and Agri-Food CanadaAlberta Livestock and Meat AgencyAlberta Beef Producers
KeywordsFeedlotPasteurella multocidaTylosinBiologyFlorfenicolAntibiotic resistanceWeaningVeterinary medicineBovine respiratory diseaseBeef cattleMicrobiologyAntimicrobialAnimal scienceAntibioticsMedicineBacteria

Abstract

fetched live from OpenAlex

Here, we investigated the prevalence and risk factors for the presence ofHistophilus somni, Mannheimia haemolytica, Mycoplasma bovis, andPasteurella multocidain the respiratory tract of calves from the spring processing to the reprocessing at feedlots. Additionally, we characterized, phenotypically and genotypically, the antimicrobial resistance (AMR) profile of the four species. Calves from 22 cow–calf operations were enrolled in the study (n= 30 calves per operation) and sampled by deep nasopharyngeal swabs at three time points: spring processing, weaning, or induction into feedlots, and at reprocessing at the feedlot. Isolates were tested for susceptibility using the minimum inhibitory concentration (MIC) test against commonly administered antimicrobials. Additionally, a subset of isolates underwent whole-genome sequencing to infer presence of AMR genes and resistance determinants. Among studied pathogens,P. multocidawas the most prevalent species, regardless of time point, followed byM. haemolytica, M. bovis, andH. somni. ForM. bovis, a sharp increase in prevalence was detected at the reprocessing sampling, whereas forP. multocida, an increase in prevalence was observed at the weaning/induction sampling. Comingling and co-location of feedlots were not associated with prevalence of any respiratory pathogen. In terms of AMR, resistance against macrolides was prevalent inM. bovis, with most isolates resistant against tildipirosin, tilmicosin, and tylosin. In general, there was limited evidence to support an increase in resistance rates of respiratory bacteria from the spring processing to reprocessing at feedlots, with the exception of florfenicol resistance inM. bovis, which increased at reprocessing. Metaphylactic administration of tetracyclines at feedlot induction was not associated with the MIC of tetracyclines in any respiratory bacteria. Conversely, there were clear associations between the parenteral use of macrolides as metaphylaxis at the feedlot induction, and increased MIC against macrolides inP. multocida, M. haemolytica, andH. somni. Overall, the AMR phenotypes were corroborated by presence of AMR genes. We hypothesize that the administration of macrolides such as tulathromycin at feedlot induction contributes to historical changes in macrolides MIC data of respiratory bacteria of beef cattle.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.030
GPT teacher head0.298
Teacher spread0.269 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations30
Published2021
Admission routes2
Has abstractyes

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