Effect of glucose on growth and co-culture of Staphylococcus aureus and Pseudomonas aeruginosa in artificial sputum medium

People with cystic fibrosis-related diabetes (CFRD) suffer from chronic infections with Staphylococcus aureus and/or Pseudomonas aeruginosa. In people with CFRD, the concentration of glucose in the airway surface liquid (ASL) was shown to be elevated from 0.4 to 4 mM. The effect of glucose on bacterial growth/interactions in ASL is not well understood and here we studied the relationship between these lung pathogens in artificial sputum medium (ASM), an environment similar to ASL in vivo. S. aureus exhibited more rapid adaptation to growth in ASM than P. aeruginosa. Supplementation of ASM with glucose significantly increased the growth of S. aureus (p < 0.01, n = 5) and P. aeruginosa (p < 0.001, n = 3). ASM conditioned by the presence of S. aureus promoted growth of P. aeruginosa with less lag time compared with non-conditioned ASM, or conditioned medium that had been heated to 121 °C. Stable co-culture of S. aureus and P. aeruginosa could be established in a 50:50 mix of ASM and S. aureus-conditioned supernatant. These data indicate that glucose, in a nutrient depleted environment, can promote the growth of S. aureus and P. aeruginosa. In addition, heat labile factors present in S. aureus pre-conditioned ASM promoted the growth of P. aeruginosa. We suggest that the use of ASM allows investigation of the effects of nutrients such as glucose on common lung pathogens. ASM could be further used to understand the relationship between S. aureus and P. aeruginosa in a co-culture scenario. Our model of stable co-culture could be extrapolated to include other common lung pathogens and could be used to better understand disease progression in vitro

Towards an interoperable ecosystem of AI and LT platforms : a roadmap for the implementation of different levels of interoperability

With regard to the wider area of AI/LT platform interoperability, we concentrate on two core aspects: (1) cross-platform search and discovery of resources and services; (2) composition of cross-platform service workflows. We devise five different levels (of increasing complexity) of platform interoperability that we suggest to implement in a wider federation of AI/LT platforms. We illustrate the approach using the five emerging AI/LT platforms AI4EU, ELG, Lynx, QURATOR and SPEAKER

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

Cohort profile. the ESC-EORP chronic ischemic cardiovascular disease long-term (CICD LT) registry

The European Society of cardiology (ESC) EURObservational Research Programme (EORP) Chronic Ischemic Cardiovascular Disease registry Long Term (CICD) aims to study the clinical profile, treatment modalities and outcomes of patients diagnosed with CICD in a contemporary environment in order to assess whether these patients at high cardiovascular risk are treated according to ESC guidelines on prevention or on stable coronary disease and to determine mid and long term outcomes and their determinants in this population