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Record W3008232610 · doi:10.1128/msystems.00629-19

Intranasal Bacterial Therapeutics Reduce Colonization by the Respiratory Pathogen Mannheimia haemolytica in Dairy Calves

2020· article· en· W3008232610 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenuemSystems · 2020
Typearticle
Languageen
FieldImmunology and Microbiology
TopicMicrobial infections and disease research
Canadian institutionsUniversity of CalgaryAgriculture and Agri-Food Canada
FundersAgriculture and Agri-Food CanadaGovernment of CanadaAlberta Agriculture and Forestry
KeywordsBovine respiratory diseasePathogenColonizationNasal administrationAntibioticsMicrobiologyBiologyDairy cattleImmunologyAnimal science

Abstract

fetched live from OpenAlex

Bovine respiratory disease (BRD) is one of the significant challenges for the modern dairy industry in North America, accounting for 23 to 47% of the total mortality among pre- and postweaned dairy heifers. Mass medication with antibiotics is a common practice to control BRD in dairy cattle. However, the emergence of multidrug-resistant BRD pathogens highlights the importance of developing alternatives to antibiotics for BRD mitigation. Using a targeted approach, we recently identified 6 Lactobacillus strains originating from the bovine respiratory microbiota as candidates to be used as bacterial therapeutics (BTs) for the mitigation of the BRD pathogen Mannheimia haemolytica . Here, we demonstrated that intranasal inoculation of the BT strains reduced nasal colonization by M. haemolytica in dairy calves experimentally challenged with this pathogen. This study, for the first time, shows the potential use of intranasal BTs as an alternative to mitigate BRD pathogens in 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.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.874
Threshold uncertainty score0.371

Codex and Gemma teacher scores by category

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

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 head0.048
GPT teacher head0.289
Teacher spread0.241 · 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