Presence of erm gene classes in Gram-positive bacteria of animal and human origin in Denmark

A classification of the different erm gene classes based on published sequences was performed, and specific primers to detect some of these classes designed. The presence of ermA (Tn554), ermB (class IV) and ermC (class VI) was determined by PCR in a total of 113 enterococcal, 77 streptococcal and 68 staphylococcal erythromycin resistant isolates of animal and human origin. At least one of these genes was detected in 88% of the isolates. Four isolates contained more than one ei il? gene. ermB dominated among the enterococci (88%) and streptococci (90%) and ermC among staphylococci (75%) with ermA (Tn554) present in some isolates (16%). Variations in the presence of the different genes when comparing staphylococcal isolates of human and animal origin were observed

Data Science in Healthcare: Benefits, Challenges and Opportunities

The advent of digital medical data has brought an exponential increase in information available for each patient, allowing for novel knowledge generation methods to emerge. Tapping into this data brings clinical research and clinical practice closer together, as data generated in ordinary clinical practice can be used towards rapid-learning healthcare systems, continuously improving and personalizing healthcare. In this context, the recent use of Data Science technologies for healthcare is providing mutual benefits to both patients and medical professionals, improving prevention and treatment for several kinds of diseases. However, the adoption and usage of Data Science solutions for healthcare still require social capacity, knowledge and higher acceptance. The goal of this chapter is to provide an overview of needs, opportunities, recommendations and challenges of using (Big) Data Science technologies in the healthcare sector. This contribution is based on a recent whitepaper (http://www.bdva.eu/sites/default/files/Big%20Data%20Technologies%20in%20Healthcare.pdf) provided by the Big Data Value Association (BDVA) (http://www.bdva.eu/), the private counterpart to the EC to implement the BDV PPP (Big Data Value PPP) programme, which focuses on the challenges and impact that (Big) Data Science may have on the entire healthcare chain

Whole genomes from bacteria collected at diagnostic units around the world 2020

Abstract The Two Weeks in the World research project has resulted in a dataset of 3087 clinically relevant bacterial genomes with pertaining metadata, collected from 59 diagnostic units in 35 countries around the world during 2020. A relational database is available with metadata and summary data from selected bioinformatic analysis, such as species prediction and identification of acquired resistance genes