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The biomedical literature provides an extensive source of information in the form of unstructured text. One of the most important types of information hidden in biomedical literature is the relations between human proteins and their phenotypes, which, due to the exponential growth of publications, can remain hidden. This provides a range of opportunities for the development of computational methods to extract the biomedical relations from the unstructured text. In our previous work, we developed a supervised machine learning approach, called PPPred, for classifying the validity of a given sentence-level human protein-phenotype co-mention. In this work, we propose DeepPPPred, an ensemble classifier composed of PPPred and three deep neural network models: RNN, CNN, and BERT. Using an expanded gold-standard co-mention dataset, we demonstrate that the proposed ensemble method significantly outperforms its constituent components and provides a new state-of-the-art performance on classifying the co-mentions of human proteins and phenotype terms.

Mononuclear phagocytes (MNPs) such as dendritic cells and macrophages perform key sentinel functions in mucosal tissues and are responsible for inducing and maintaining adaptive immune responses to mucosal pathogens. Positioning of MNPs at the mucosal epithelial interface facilitates their access to luminally-derived antigens and may regulate MNP function through soluble mediators or surface receptor interactions. Therefore, accurately quantifying the distribution of MNPs within mucosal tissues as well as their spatial relationship with other cells is important to infer functional cellular interactions in health and disease. In this study, we developed and validated a MATLAB-based tissue cytometry platform, termed "MNP mapping application" (MNPmApp), that performs high throughput analyses of MNP density and distribution in the gastrointestinal mucosa based on digital multicolor fluorescence microscopy images and that integrates a Monte Carlo modeling feature to assess randomness of MNP distribution.MNPmApp identified MNPs in tissue sections of the human gastric mucosa with a specificity of 98.3 ± 1.6% and a sensitivity of 76.4 ± 15.1%. Monte Carlo modeling revealed that mean MNP-MNP distances were significantly lower than anticipated based on random cell placement, whereas MNP-epithelial distances did not significantly differ from those of randomly placed cells.Interestingly, H. pylori infection had no significant impact on MNP density or distribution with regards to MNP-epithelial distances or MNP-MNP distances in gastric tissue. Overall, our analysis demonstrates that MNPmApp is a useful tool for unbiased quantitation of MNPs and their distribution at mucosal sites.

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Mycoplasma ovipneumoniae (M. ovipneumoniae) is a respiratory pathogen associated with the development of mild to moderate respiratory disease in domestic lambs and severe pneumonia outbreaks in wild ruminants such as bighorn sheep. However, whether M. ovipneumoniae by itself causes clinical respiratory disease in domestic sheep in the absence of secondary bacterial pathogens is still a matter of debate. The goal of our study was to better understand the role of M. ovipneumoniae as a respiratory pathogen in domestic sheep and to explore potential antibiotic treatment approaches. Therefore, we inoculated four-month-old, specific-pathogen-free lambs with field isolates of M. ovipneumoniae and monitored the lambs for eight weeks for colonization with the bacteria, M. ovipneumoniae-specific antibodies, clinical symptoms, and cellular and molecular correlates of lung inflammation. After eight weeks, lambs were treated with the macrolide antibiotic gamithromycin and observed for an additional four weeks. Stable colonization of the upper respiratory tract with M. ovipneumoniae was established in all four M. ovipneumoniae-inoculated, but in none of the four mock-infected lambs. All M. ovipneumoniae-infected lambs developed a robust antibody response to M. ovipneumoniae within 2 weeks. However, we did not observe significant clinical symptoms or evidence of lung damage or inflammation in any of the infected lambs. Interestingly, treatment with gamithromycin failed to reduce M. ovipneumoniae colonization. These observations indicate that, in the absence of co-factors, M. ovipneumoniae causes asymptomatic colonization of the upper respiratory tract of that is resistant to clearance by the host immune response as well as by gamithromycin treatment in domestic lambs.