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John Berezowski

Researcher at University of Bern

Publications -  69
Citations -  776

John Berezowski is an academic researcher from University of Bern. The author has contributed to research in topics: Medicine & Population. The author has an hindex of 14, co-authored 57 publications receiving 572 citations. Previous affiliations of John Berezowski include Western University College of Veterinary Medicine & Ross University School of Veterinary Medicine.

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Assessing activity and location of individual laying hens in large groups using modern technology

TL;DR: Several tracking systems that are currently in use for laying hens are divided into two major categories (radio frequency identification and radio signal strength) and review the strengths and weaknesses of each, as well as environments or conditions for which they may be most suitable.

BRIEF COMMUNICATIONS An outbreak of sheep-associated malignant catarrhal fever in bison (Bison bison) after exposure to sheep at a public auction sale

TL;DR: An outbreak of malignant catarrhal fever among bison sold at an auction market was studied for an 18-month period and provides evidence that bison with MCF do not transmit MCF to other bison.
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An Outbreak of Sheep-Associated Malignant Catarrhal Fever in Bison (Bison Bison) after Exposure to Sheep at a Public Auction Sale

TL;DR: An outbreak of malignant catarrhal fever (MCF) among bison sold at an auction market was studied for an 18-month period as mentioned in this paper, and the outbreak began on day 50 after the sale, peaked between days 60 and 70, and ended on day 220.
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Prevalence, risk factors, O serogroups, and virulence profiles of Shiga toxin-producing bacteria from cattle production environments.

TL;DR: The results suggest that the prevalence of Stx-producing bacteria can be relatively high in cattle, and associated factors may not be entirely similar to those reported for serotype O157:H7.
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Mining free-text medical records for companion animal enteric syndrome surveillance.

TL;DR: A categorization dictionary is developed that could be used to automatically classify and extract enteric syndrome cases from the warehoused electronic medical records and provides an opportunity for community surveillance of enteric pathogens in companion animals.