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Record W2611142040 · doi:10.1136/vetreco-2016-000179

Efficacy of recombinant bovine epidermal growth factor in the treatment of experimental subclinical <i>Staphylococcus aureus</i> mastitis in a ewe model

2017· article· en· W2611142040 on OpenAlexaff
Kamal Gabadage, Manuel Chirino‐Trejo, John Campbell, Christopher D. Luby

Bibliographic record

VenueVeterinary Record Open · 2017
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicMilk Quality and Mastitis in Dairy Cows
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsUdderStaphylococcus aureusMastitisSalineMedicineMicrobiologyImmunologyBiologyInternal medicineBacteria

Abstract

fetched live from OpenAlex

Staphylococcus aureus is the most common contagious mastitis pathogen of dairy cattle. Antimicrobial treatment of infected cattle results in variable cure rates. Epidermal growth factor (EGF) plays an important role in the modulation of host innate immune responses and the regulation of mammary epithelial regeneration, indicating that EGF may be useful as a treatment for mastitis. A pilot study was conducted to evaluate the efficacy of recombinant bovine EGF (rbEGF) for the treatment of S aureus intramammary infection (IMI) using an ovine model. Each ewe was experimentally infected with S aureus in both udder halves. One udder half of each ewe received one of two treatments: EGF (n=13) or pirlimycin (n=13). The contralateral udder half of each ewe received sterile saline as a control. The bacteriological cure rate following rbEGF was significantly lower (15 per cent) than that attained with pirlimycin hydrochloride (61 per cent) and did not differ from that following treatment with sterile saline. Cure rates following treatment with rbEGF were not significantly different to those following sterile saline. Given that EGF is associated with modulation of host immunity and wound healing, future studies into EGF should not focus on whether EGF increases cure rates of S aureus IMI.

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 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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.651
Threshold uncertainty score0.999

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 science0.0010.000
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 head0.155
GPT teacher head0.360
Teacher spread0.205 · 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 teacher head, 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

Citations4
Published2017
Admission routes1
Has abstractyes

Explore more

Same venueVeterinary Record OpenSame topicMilk Quality and Mastitis in Dairy CowsFrench-language works237,207