Publications by authors named "Lindsey LaBella"

In April 2024, ten cats died in a rural South Dakota (SD) residence, showing respiratory and neurological symptoms. Necropsy and laboratory testing of two cats confirmed H5N1 clade 2.3.

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Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infects many mammals, and SARS-CoV-2 circulation in nonhuman animals may increase the risk of novel variant emergence. Cats are highly susceptible to SARS-CoV-2 infection, and there were cases of virus transmission between cats and humans. The objective of this study was to assess the prevalence of SARS-CoV-2 variant infection of cats in an urban setting.

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Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), believed to have originated from a bat species, can infect a wide range of non-human hosts. Bats are known to harbor hundreds of coronaviruses capable of spillover into human populations. Recent studies have shown a significant variation in the susceptibility among bat species to SARS-CoV-2 infection.

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We report a complete genome sequence of bovine coronavirus (BCoV) isolated from a goat in the state of Pennsylvania in 2022. BCoV often causes calf scours and winter dysentery in cattle.

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There is mounting evidence of SARS-CoV-2 spillover from humans into many domestic, companion, and wild animal species. Research indicates that humans have infected white-tailed deer, and that deer-to-deer transmission has occurred, indicating that deer could be a wildlife reservoir and a source of novel SARS-CoV-2 variants. We examined the hypothesis that the Omicron variant is actively and asymptomatically infecting the free-ranging deer of New York City.

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Multiple domestic and wild animal species are susceptible to SARS-CoV-2 infection. Cattle and swine are susceptible to experimental SARS-CoV-2 infection. The unchecked transmission of SARS-CoV-2 in animal hosts could lead to virus adaptation and the emergence of novel variants.

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The cellular entry of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) involves the association of its receptor binding domain (RBD) with human angiotensin converting enzyme 2 (hACE2) as the first crucial step. Efficient and reliable prediction of RBD-hACE2 binding affinity changes upon amino acid substitutions can be valuable for public health surveillance and monitoring potential spillover and adaptation into non-human species. Here, we introduce a convolutional neural network (CNN) model trained on protein sequence and structural features to predict experimental RBD-hACE2 binding affinities of 8,440 variants upon single and multiple amino acid substitutions in the RBD or ACE2.

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