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Roe, M. M.

Publications and source records attributed to Roe, M. M..

2 recordsLinked to original sources

A high-throughput metabolic microarray assay reveals antibacterial effects of black and red raspberries and blackberries against Helicobacter pylori infection

Helicobacter pylori is an important bacterial pathogen that causes chronic infection of the human stomach, leading to gastritis, peptic ulcer disease and gastric cancer. Treatment with appropriate antibiotics can eliminate H. pylori infection and reduce the risk for severe disease outcomes. However, since H. pylori is becoming increasingly resistant to standard antibiotic regimens, novel treatment strategies are needed. Previous studies have demonstrated that black and red berries may have antibacterial properties. Therefore, we analyzed organic extracts and powders from black and red raspberries and blackberries and determined their antibacterial effects on multiple H. pylori strains. We used high-performance liquid chromatography to measure berry anthocyanins, which are considered the major active ingredients. To monitor antibiotic effects of the berry preparations on H. pylori, we developed a high-throughput metabolic growth assay based on the OmniLog system. All berry preparations tested had significant bactericidal effects in vitro, with MIC90 values ranging from 0.49 to 4.17%. We next used human gastric epithelial organoids to evaluate biocompatibility of the berry preparations and showed that black raspberry extract, which had the strongest antimicrobial activity, was non-toxic at the concentration required for complete bacterial growth inhibition. To determine whether dietary black raspberry application could eliminate H. pylori infection in vivo, mice were infected with H. pylori and then were placed on a diet containing 10% black raspberry powder. However, this treatment did not significantly impact bacterial infection rates or gastric pathology. In summary, our data indicate that black and red raspberry and blackberry products have potential applications in the treatment and prevention of H. pylori infection, because of their antibacterial effects and good biocompatibility. However, delivery and formulation of berry compounds needs to be optimized to achieve significant antibacterial effects in vivo.

microbiology↗

PPPred: Classifying Protein-phenotype Co-mentions Extracted from Biomedical Literature

The MEDLINE database provides an extensive source of scientific articles and heterogeneous biomedical information in the form of unstructured text. One of the most important knowledge present within articles are the relations between human proteins and their phenotypes, which can stay hidden due to the exponential growth of publications. This has presented a range of opportunities for the development of computational methods to extract these biomedical relations from the articles. However, currently, no such method exists for the automated extraction of relations involving human proteins and human phenotype ontology (HPO) terms. In our previous work, we developed a comprehensive database composed of all co-mentions of proteins and phenotypes. In this study, we present a supervised machine learning approach called PPPred (Protein-Phenotype Predictor) for classifying the validity of a given sentence-level co-mention. Using an in-house developed gold standard dataset, we demonstrate that PPPred significantly outperforms several baseline methods. This two-step approach of co-mention extraction and classification constitutes a complete biomedical relation extraction pipeline for extracting protein-phenotype relations.\n\nCCS CONCEPTS*Computing methodologies [->] Information extraction; Supervised learning by classification; *Applied computing [->]Bioinformatics;

bioinformatics↗