Frustration driven structural distortion in VOMoO4

Nuclear magnetic resonance (NMR), electron paramagnetic resonance (EPR), magnetization measurements and electronic structure calculations in VOMoO4 are presented. It is found that VOMoO4 is a frustrated two-dimensional antiferromagnet on a square lattice with competing exchange interactions along the side J1 and the diagonal J2 of the square. From magnetization measurements J1+J2 is estimated around 155 K, in satisfactory agreement with the values derived from electronic structure calculations. Around 100 K a structural distortion, possibly driven by the frustration, is evidenced. This distortion induces significant modifications in the NMR and EPR spectra which can be accounted for by valence fluctuations. The analysis of the spectra suggests that the size of the domains where the lattice is distorted progressively grows as the temperature approaches the transition to the magnetic ground state at Tc=42 K

Prediction-based classification for longitudinal biomarkers

Assessment of circulating CD4 count change over time in HIV-infected subjects on antiretroviral therapy (ART) is a central component of disease monitoring. The increasing number of HIV-infected subjects starting therapy and the limited capacity to support CD4 count testing within resource-limited settings have fueled interest in identifying correlates of CD4 count change such as total lymphocyte count, among others. The application of modeling techniques will be essential to this endeavor due to the typically nonlinear CD4 trajectory over time and the multiple input variables necessary for capturing CD4 variability. We propose a prediction-based classification approach that involves first stage modeling and subsequent classification based on clinically meaningful thresholds. This approach draws on existing analytical methods described in the receiver operating characteristic curve literature while presenting an extension for handling a continuous outcome. Application of this method to an independent test sample results in greater than 98% positive predictive value for CD4 count change. The prediction algorithm is derived based on a cohort of $n=270$ HIV-1 infected individuals from the Royal Free Hospital, London who were followed for up to three years from initiation of ART. A test sample comprised of $n=72$ individuals from Philadelphia and followed for a similar length of time is used for validation. Results suggest that this approach may be a useful tool for prioritizing limited laboratory resources for CD4 testing after subjects start antiretroviral therapy.Comment: Published in at http://dx.doi.org/10.1214/10-AOAS326 the Annals of Applied Statistics (http://www.imstat.org/aoas/) by the Institute of Mathematical Statistics (http://www.imstat.org

Atmospheric nitrogen deposition in a highly human impacted area in northern Italy

Nitrogen can enter the water cycle through atmospheric depositions on ground and water surfaces, leakages from point and diffuse sources (i.e., sewage treatment plants or sewage systems, fertilizer and manure applications), and erosion processes affecting nitrogen rich soils (EEA, 2005). However, integrating all nitrogen forms, processes and scales is still a major challenge for the understanding and the management of the nitrogen cycle

Post-Depositional Biodegradation Processes of Pollutants on Glacier Surfaces

Glaciers are important fresh-water reservoirs for our planet. Although they are often located at high elevations or in remote areas, glacial ecosystems are not pristine, as many pollutants can undergo long-range atmospheric transport and be deposited on glacier surface, where they can be stored for long periods of time, and then be released into the down-valley ecosystems. Understanding the dynamics of these pollutants in glaciers is therefore important for assessing their environmental fate. To this aim, it is important to study cryoconite holes, small ponds filled with water and with a layer of sediment, the cryoconite, at the bottom, which occur on the surface of most glaciers. Indeed, these environments are hotspots of biodiversity on glacier surface as they host metabolically active bacterial communities that include generalist taxa able to degrade pollutants. In this work, we aim to review the studies that have already investigated pollutant (e.g., chlorpyrifos and polychlorinated-biphenyls (PCBs)) degradation in cryoconite holes and other supraglacial environmental matrices. These studies have revealed that bacteria play a significant role in pollutant degradation in these habitats and can be positively selected in contaminated environments. We will also provide indication for future research in this field

Modeling an Industrial Revolution: How to Manage Large-Scale, Complex IoT Ecosystems?

Advancements around the modern digital industry gave birth to a number of closely interrelated concepts: in the age of the Internet of Things (IoT), System of Systems (SoS), Cyber-Physical Systems (CPS), Digital Twins and the fourth industrial revolution, everything revolves around the issue of designing well-understood, sound and secure complex systems while providing maximum flexibility, autonomy and dynamics.The aim of the paper is to present a concise overview of a comprehensive conceptual framework for integrated modeling and management of industrial IoT architectures, supported by actual evidence from the Arrowhead Tools project; in particular, we adopt a three-dimensional projection of our complex engineering space, from modeling the engineering process to SoS design and deployment.In particular, we start from modeling principles of the the engineering process itself. Then, we present a design-time SoS representation along with a toolchain concept aiding SoS design and deployment. This brings us to reasoning about what potential workflows are thinkable for specifying comprehensive toolchains along with their data exchange interfaces. We also discuss the potential of aligning our vision with RAMI4.0, as well as the utilization perspectives for real-life engineering use-cases

Poorly differentiated clusters (PDC) in colorectal cancer: Does their localization in tumor matter?

Poorly differentiated clusters (PDC) are aggregates of at least five neoplastic cells lacking evidence of glandular differentiation. By definition, they can be present at the invasive front (peripheral PDC or pPDC) and within the tumor stroma (central PDC or cPDC). In colorectal cancer (CRC), PDC are considered adverse prognosticators and seem to reflect epithelial mesenchymal transition (EMT). In this study, we have investigated the immuno-expression of two EMT-related proteins, E-cadherin and β-catenin, in PDC of primary CRCs and matched liver metastases. pPDC always showed nuclear β-catenin staining and diffusely reduced/absence of E-cadherin expression as opposed cPDC which showed nuclear β-catenin immunoreactivity and E-cadherin expression in about 50% of cases. In addition, the pattern of β-catenin and E-cadherin expression differed between PDC and the main tumor, and between primary CRC and liver metastasis (LM), in a percentage of cases. A discordant pattern of β-catenin and E-cadherin expression between pPDC and cPDC, between main tumor and cPDC, and between primary CRC and LM, confirms that EMT is a dynamic and reversible process in CRC. On the overall, this suggests that pPDC and cPDC are biologically different. We may advocate that PDC develop at the tumor center (cPDC) and then some of them migrate towards the tumor periphery while progressively completing EMT process (pPDC). Based on these results, PDC presence and counting may have different prognostic relevance if the assessment is done at the invasive front of the tumor or in the intratumor stroma