The aim of this study was to establish a simple method for the rapid identification of Mycobacteria species by MALDI-TOF (Matrix-Assisted Laser Desorption/Ionization-Time of Flight Mass spectrometry) using the Bruker MALDI-TOF Biotyper system (Bruker Daltonik, Bremen, Germany). A multicentre, prospective, and single blind study was performed in three European Hospitals, two Spanish and one UK hospital from May to August 2018. The BD BACTEC MGIT (Becton Dickinson, Berks, UK) liquid culture system was used in all three centres for the growth of Mycobacteria. When signal positive, tubes were removed from the analyser and in addition to standard laboratory procedures were subcultured on blood agar plates for MALDI-TOF analysis. Plates were incubated aerobically for 1 to 7 days at 37 °C and inspected every day. Once any growth was visible, it was transferred to the steel target plate, overlaid with 1 μl of neat formic acid and 1 μl HCCA matrix (alpha hydroxyl 4 cinnamic acid), and analysed in a Bruker Biotyper MALDI-TOF. Results given by MALDI-TOF were compared with the reference methods used for identification in the different centres. At two Spanish hospitals, identification by MALDI-TOF was only attempted on presumptive non-tuberculosis mycobacteria (NTM) and the results were initially compared with the results obtained by a commercial reverse hybridisation assay, GenoType CM/AS (Hain Lifescience, Tübingen, Germany). At the UK Hospital, identification of any presumptive mycobacteria was attempted and compared with the results obtained by whole genome sequencing (WGS). Overall in 142/167 (85%) of cases the identifications obtained were concordant; all Mycobacterium tuberculosis (MTB) isolates 43/43 (100%), 57/76 (75%) of the rapid growing nontuberculous mycobacteria (NTM), and 42/48 (85%) slow growing NTM tested were identified correctly. We report a new, easy, cheap and quick method for isolation and identification of Mycobacterium spp. without the need for additional steps or equipment and this method is in routine used in all three centres.

The high reliability of NMR spectroscopy makes it an ideal tool for large-scale metabolomic studies. However, the complexity of biofluids and, in particular, the presence of macromolecules poses a significant challenge. Ultrafiltration and protein precipitation are established means of deproteinization and recovery of free or total metabolite content, but neither is ever complete. In addition, aside from cost and labor, all deproteinization methods constitute an additional source of experimental variation. The Carr-Purcell-Meiboom-Gill (CPMG) echo-train acquisition of NMR spectra obviates the need for prior deproteinization by attenuating signals from macromolecules, but concentration values of metabolites measured in blood plasma will not necessarily reflect total or free metabolite content. Here, in contrast to approaches that propose the determination of individual T and T relaxation times for the computation of correction factors, we demonstrate their determination by spike-in experiments with known amounts of metabolites in pooled samples of the matrix of interest to facilitate the measurement of total metabolite content. Provided that the protein content does not vary too much among individual samples, accurate quantitation of metabolites is feasible. Moreover, samples with significantly deviating protein content may be readily recognized by inclusion of a standard that shows moderate protein binding. It is also shown that urinary proteins when present in high concentrations may effect detection of common urinary metabolites prone to strong protein binding such as tryptophan.

No abstract

Information and communication technologies are increasingly pervasive in our everyday lives. Their use has greatly evolved from an ancillary service to a component of all our activities, anytime, anywhere. To this aim, we rely heavily on cloud computing and, more recently, on edge computing. Hence, their contribution (or obstruction) to the sustainability of our society at large is pivotal.Unfortunately, cloud/edge provisioning has a dark side: it too often prioritizes economic gain over the cost of long-lasting sustainability. Also, sustainability is often absent from the discussions in the cloud/edge research community.To start the discussion and highlight a number of sustainability shortcomings of the cloud and edge computing paradigms, we carry out an exploratory study involving experts-in-the-field, capture their inputs in the form of so-called unsustainable patterns, and complement them with examples of possible countermeasures. The results of our study include: (i) the definition of a Pattern Model, (ii) a catalog of unsustainable patterns for the cloud and edge computing paradigms, and (iii) the identification of preliminary countermeasures and takeaways in order to make these two paradigms more sustainable.