Regulating Internet Trade in CITES Species

Wild collection of species that are or may be endangered by collection from the wild for international commerce is regulated under the The Convention on International Trade in Endangered Species of Wild Fauna and Flora (CITES) for 176 member States. Internet commerce is a relatively a new route for such trade and is rarely included in CITES statistics. By comparing information from an international on-line auction system with official CITES records on international trade, we discovered that only around 10% of the specimens of cacti listed on CITES Appendix I traded in 2010 were even potentially legal. Clearly, such trade over the Internet easily bypasses CITES trade regulations and should be monitored in future to ensure the effective protection of CITES listed species

cglasso: An R Package for Conditional Graphical Lasso Inference with Censored and Missing Values

Sparse graphical models have revolutionized multivariate inference. With the advent of high-dimensional multivariate data in many applied fields, these methods are able to detect a much lower-dimensional structure, often represented via a sparse conditional independence graph. There have been numerous extensions of such methods in the past decade. Many practical applications have additional covariates or suffer from missing or censored data. Despite the development of these extensions of sparse inference methods for graphical models, there have been so far no implementations for, e.g., conditional graphical models. Here we present the general-purpose package cglasso for estimating sparse conditional Gaussian graphical models with potentially missing or censored data. The method employs an efficient expectation-maximization estimation of an ℓ1 -penalized likelihood via a block-coordinate descent algorithm. The package has a user-friendly data manipulation interface. It estimates a solution path and includes various automatic selection algorithms for the two ℓ1 tuning parameters, associated with the sparse precision matrix and sparse regression coefficients, respectively. The package pays particular attention to the visualization of the results, both by means of marginal tables and figures, and of the inferred conditional independence graphs. This package provides a unique and computational efficient implementation of a conditional Gaussian graphical model that is able to deal with the additional complications of missing and censored data. As such it constitutes an important contribution for empirical scientists wishing to detect sparse structures in high-dimensional data

Sparse relative risk regression models

Clinical studies where patients are routinely screened for many genomic features are becoming more routine. In principle, this holds the promise of being able to find genomic signatures for a particular disease. In particular, cancer survival is thought to be closely linked to the genomic constitution of the tumor. Discovering such signatures will be useful in the diagnosis of the patient, may be used for treatment decisions and, perhaps, even the development of new treatments. However, genomic data are typically noisy and high-dimensional, not rarely outstripping the number of patients included in the study. Regularized survival models have been proposed to deal with such scenarios. These methods typically induce sparsity by means of a coincidental match of the geometry of the convex likelihood and a (near) non-convex regularizer. The disadvantages of such methods are that they are typically non-invariant to scale changes of the covariates, they struggle with highly correlated covariates, and they have a practical problem of determining the amount of regularization. In this article, we propose an extension of the differential geometric least angle regression method for sparse inference in relative risk regression models. A software implementation of our met

Comparison of numerical models for Acoustic Emission propagation

Abstract Acoustic Emissions (AE) are at the basis of extremely accurate and reliable monitoring systems. Within the SmartBench project, data regarding structural health of components are gathered in a database in order to make safety integrated, operative and smart. An accurate modelling of wave propagation is a necessary requirement for a proper design of sensor networks as well as for data interpretation. Numerical simulations of the transient behavior of structural systems are well-established in this field but, on the minus side, they are very expensive in terms of computational time and resources. This paper reports different instances of AE propagation through metallic media. Bulk waves and guided waves are both investigated by means of 2D and 3D models and resorting to different software. Obtained results are cross-checked and computational times are compared as well. As a last point, High Performance Computing is applied to the case of waves simulation in order to get a significant reduction of the required computational time

Visible Light Induced Oxidation of Trans-ferulic Acid by TiO2 Photocatalysis

The oxidation of trans-ferulic acid (C 10H 10O 4) in aqueous TiO 2 dispersion occurs via the formation of a charge-transfer complex on the TiO 2 surface that is able to absorb visible light (\u3bb 65 400 nm). The main product is CO 2, whereas secondary oxidation products are organic species such as vanillin, caffeic acid, homovanillic acid, and vanillylmandelic acid. Oxidation through the formation of a charge-transfer complex occurs only in the presence of specific TiO 2 samples. Experiments in the absence of oxygen, in the presence of bromate ions and by using a phosphate-modified TiO 2, have been carried out for investigating the reaction mechanism. In order to study the interaction between trans-ferulic acid and TiO 2 surface and to characterize the charge-transfer complex, UV-Vis diffuse reflectance and FT-IR spectroscopies have been used. FT-IR characterization of TiO 2 samples in contact with the aqueous trans-ferulic acid solution indicates that the charge-transfer complex formation occurs via adsorption of bidentate ferulate species

Radioablation +/- hormonotherapy for prostate cancer oligorecurrences (Radiosa trial): Potential of imaging and biology (AIRC IG-22159)

Background: Prostate cancer (PCa) is the second most common cancer among men. New imaging-modalities have increased the diagnosed patients with limited number of metastasis after primary curative therapy, introducing so-called oligometastatic state. Stereotactic body radiotherapy (SBRT) is emerging as a low-toxicity treatment to erase PCa localizations and postpone androgen deprivation therapy (ADT). A deeper understanding of the predictive role of biomarkers is desirable for a targeted treatment selection and surveillance programs. The aims of the RADIOSA trial are: Compare SBRT +/- ADT for oligorecurrent-castration-sensitive PCa (OCS-PCa) in terms of efficacy, toxicity and Quality of Life (QoL).Develop biology/imaging based prognostic tool that allows identifying OCS-PCa subclasses. Methods This is a randomized phase II clinical trial, recruiting 160 OCS-PCa in 3years, with progression-free survival (PFS) as primary endpoint. Three tasks will be developed: Randomized clinical study (3years for accrual and 2years for follow-up and data analysis);Imaging study, including imaging registration and METastasis Reporting and Data System (MET-RADS) criteria;Pre-clinical study, development of a biobank of blood samples for the analysis of neutrophil-to-lymphocyte ratio and preparatory for a subsequent miRNA profiling.We aim to determine which arm is justified for testing in a subsequent Phase III trial. A decision-tree algorithm, based on prognosis, biological phenotype and imaging profile, will be developed. Discussion Recruiting will start in July 2019. SBRT will allow obtaining excellent PFS, local control, QoL and low toxicity. In SBRT arm, ADT deferral will allow for a drug-holiday, delaying the detrimental impact on QoL. A sufficient number of blood samples will be collected to perform biological patient profiling. A stratification tool will be established with an analysis of morphological and functional imaging, based on the use of MET-RADS criteria.So, in conclusion, RADIOSA aims to define the optimal management of bone/nodal PCa relapses in a SBRT regimen. This study will increase our knowledge on low-burden metastatic PCa in the era of high precision and high technology personalized medicine, offering highly effective therapy in terms of clinical outcome and cost-effectiveness. Trial registration The RADIOSA study was prospectively registered at clinicaltrials.gov (NCT03940235, May 2019)

Unassisted solar lignin valorisation using a compartmented photo-electro-biochemical cell

Lignin is a major component of lignocellulosic biomass. Although it is highly recalcitrant to break down, it is a very abundant natural source of valuable aromatic carbons. Thus, the effective valorisation of lignin is crucial for realising a sustainable biorefinery chain. Here, we report a compartmented photo-electro-biochemical system for unassisted, selective, and stable lignin valorisation, in which a TiO2 photocatalyst, an atomically dispersed Co-based electrocatalyst, and a biocatalyst (lignin peroxidase isozyme H8, horseradish peroxidase) are integrated, such that each system is separated using Nafion and cellulose membranes. This cell design enables lignin valorisation upon irradiation with sunlight without the need for any additional bias or sacrificial agent and allows the protection of the biocatalyst from enzymedamaging elements, such as reactive radicals, gas bubbles, and light. The photo-electrobiochemical system is able to catalyse lignin depolymerisation with a 98.7% selectivity and polymerisation with a 73.3% yield using coniferyl alcohol, a lignin monomer

Modulation of NKp30- and NKp46-Mediated Natural Killer Cell Responses by Poxviral Hemagglutinin

Natural killer (NK) cells are an important element in the immune defense against the orthopox family members vaccinia virus (VV) and ectromelia virus (ECTV). NK cells are regulated through inhibitory and activating signaling receptors, the latter involving NKG2D and the natural cytotoxicity receptors (NCR), NKp46, NKp44 and NKp30. Here we report that VV infection results in an upregulation of ligand structures for NKp30 and NKp46 on infected cells, whereas the binding of NKp44 and NKG2D was not significantly affected. Likewise, infection with ectromelia virus (ECTV), the mousepox agent, enhanced binding of NKp30 and, to a lesser extent, NKp46. The hemagglutinin (HA) molecules from VV and ECTV, which are known virulence factors, were identified as novel ligands for NKp30 and NKp46. Using NK cells with selectively silenced NCR expression and NCR-CD3ζ reporter cells, we observed that HA present on the surface of VV-infected cells, or in the form of recombinant soluble protein, was able to block NKp30-triggered activation, whereas it stimulated the activation through NKp46. The net effect of this complex influence on NK cell activity resulted in a decreased NK lysis susceptibility of infected cells at late time points of VV infection when HA was expression was pronounced. We conclude that poxviral HA represents a conserved ligand of NCR, exerting a novel immune escape mechanism through its blocking effect on NKp30-mediated activation at a late stage of infection