A Qualitative Evaluation of IoT-driven eHealth: Knowledge Management, Business Models and Opportunities, Deployment and Evolution

eHealth has a major potential, and its adoption may be considered necessary to achieve increased ambulant and remote medical care, increased quality, reduced personnel needs, and reduced costs potential in healthcare. In this paper the authors try to give a reasonable, qualitative evaluation of IoT-driven eHealth from theoretical and practical viewpoints. They look at associated knowledge management issues and contributions of IoT to eHealth, along with requirements, benefits, limitations and entry barriers. Important attention is given to security and privacy issues. Finally, the conditions for business plans and accompanying value chains are realistically analyzed. The resulting implementation issues and required commitments are also discussed based on a case study analysis. The authors confirm that IoT-driven eHealth can happen and will happen; however, much more needs to be addressed to bring it back in sync with medical and general technological developments in an industrial state-of-the-art perspective and to get recognized and get timely the benefits

NMR-based metabolic characterization of chicken tissues and biofluids: a model for avian research

Introduction Poultry is one of the most consumed meat in the world and its related industry is always looking for ways to improve animal welfare and productivity. It is therefore essential to understand the metabolic response of the chicken to new feed formulas, various supplements, infections and treatments. Objectives As a basis for future research investigating the impact of diet and infections on chicken’s metabolism, we established a high-resolution proton nuclear magnetic resonance (NMR)-based metabolic atlas of the healthy chicken (Gallus gallus). Methods Metabolic extractions were performed prior to 1H-NMR and 2D NMR spectra acquisition on twelve biological matrices: liver, kidney, spleen, plasma, egg yolk and white, colon, caecum, faecal water, ileum, pectoral muscle and brain of 6 chickens. Metabolic profiles were then exhaustively characterized. Results Nearly 80 metabolites were identified. A cross-comparison of these matrices was performed to determine metabolic variations between and within each section and highlighted that only eight core metabolites were systematically found in every matrice. Conclusion This work constitutes a database for future NMR-based metabolomic investigations in relation to avian production and health

Genome-wide association mapping identifies a new arsenate reductase enzyme critical for limiting arsenic accumulation in plants

Inorganic arsenic is a carcinogen, and its ingestion through foods such as rice presents a significant risk to human health. Plants chemically reduce arsenate to arsenite. Using genome-wide association (GWA) mapping of loci controlling natural variation in arsenic accumulation in Arabidopsis thaliana allowed us to identify the arsenate reductase required for this reduction, which we named High Arsenic Content 1 (HAC1). Complementation verified the identity of HAC1, and expression in Escherichia coli lacking a functional arsenate reductase confirmed the arsenate reductase activity of HAC1. The HAC1 protein accumulates in the epidermis, the outer cell layer of the root, and also in the pericycle cells surrounding the central vascular tissue. Plants lacking HAC1 lose their ability to efflux arsenite from roots, leading to both increased transport of arsenic into the central vascular tissue and on into the shoot. HAC1 therefore functions to reduce arsenate to arsenite in the outer cell layer of the root, facilitating efflux of arsenic as arsenite back into the soil to limit both its accumulation in the root and transport to the shoot. Arsenate reduction by HAC1 in the pericycle may play a role in limiting arsenic loading into the xylem. Loss of HAC1-encoded arsenic reduction leads to a significant increase in arsenic accumulation in shoots, causing an increased sensitivity to arsenate toxicity. We also confirmed the previous observation that the ACR2 arsenate reductase in A. thaliana plays no detectable role in arsenic metabolism. Furthermore, ACR2 does not interact epistatically with HAC1, since arsenic metabolism in the acr2 hac1 double mutant is disrupted in an identical manner to that described for the hac1 single mutant. Our identification of HAC1 and its associated natural variation provides an important new resource for the development of low arsenic-containing food such as rice