Cu_{2}O as nonmagnetic semiconductor for spin transport in crystalline oxide electronics

We probe spin transport in Cu_{2}O by measuring spin valve effect in La_{0.7}Sr_{0.3}MnO_{3}/Cu_{2}O/Co and La_{0.7}Sr_{0.3}MnO_{3}/Cu_{2}O/La_{0.7}Sr_{0.3}MnO_{3} epitaxial heterostructures. In La_{0.7}Sr_{0.3}MnO_{3}/Cu_{2}O/Co systems we find that a fraction of out-of-equilibrium spin polarized carrier actually travel across the Cu_{2}O layer up to distances of almost 100 nm at low temperature. The corresponding spin diffusion length dspin is estimated around 40 nm. Furthermore, we find that the insertion of a SrTiO_{3} tunneling barrier does not improve spin injection, likely due to the matching of resistances at the interfaces. Our result on dspin may be likely improved, both in terms of Cu_{2}O crystalline quality and sub-micrometric morphology and in terms of device geometry, indicating that Cu_{2}O is a potential material for efficient spin transport in devices based on crystalline oxides.Comment: 15 pages, 10 figure

Analysis of the Energy Consumption of a Novel DC Power Supplied Industrial Robot

The energy consumption and electrical characteristics of a novel direct current (DC) power supplied industrial robot prototype are compared and analyzed with a state of the art alternating current (AC) supplied industrial robot. An extensive set of experiments shows an important reduction of the total energy consumption for different electrical power profiles measured in various robot trajectories with specific working temperatures. The recuperated energy is also analyzed in the different scenarios. Experimental results show that a DC type robot can be up to 12.5% more energy-efficient than an equivalent AC type robot

Editorial: Exploiting wheat biodiversity and agricultural practices for tackling the effects of climate change

Editorial: Exploiting wheat biodiversity and agricultural practices for tackling the effects of climate chang

Editorial: Breeding Innovations in Underutilized Temperate Fruit Trees

The recent growing interest in minor species (i.e., fig, pomegranate, feijoa, etc.) has recently driven new research on breeding and genetics to address producer and consumer traits. Since these species have received little attention from the scientific community, they were less improved via conventional breeding, and lacked detailed genomic information on important traits. This lack of data, together with a general poor genetic knowledge of these species, has limited a wider cultivation of varieties with improved characteristics

Allelic Variation of Wheat Flour Allergens in a Collection of Wheat Genotypes

Wheat is the most widely grown crop in the world and provides 20% of the daily protein and food calories for 4.5 billion people. Together with rice, it is the most important food crop in the developing world. In the last decades, various symptoms have been recorded across the population due to the consumption of wheat products, also summarized as "wheat allergy." Wheat allergy is usually reported as a food allergy but can also be a contact allergy as a result of exposure to wheat. Several important wheat allergens have been characterized in the last years through biochemical, immunological, and molecular biological techniques. In the present work, the identification of allelic variation of genes involved in wheat allergy was reported. A collection of wheat genotypes was screened in order to identify new alleles. A total of 14 new alleles were identified forprofilin, triosephosphate-isomerase, dehydrin, glyceraldehyde-3-phosphate-dehydrogenase,α/βgliadin, GluB3-23,andGlutathione transferaseallergen genes (located on chromosomes 1B, 3B, 6A, and homoelogous groups 5 and 7), potentially related to a minor allergenicity and useful in breeding programs

Origin of interface magnetism in BiMnO3/SrTiO3 and LaAlO3/SrTiO3 heterostructures

Possible ferromagnetism induced in otherwise non-magnetic materials has been motivating intense research in complex oxide heterostructures. Here we show that a confined magnetism is realized at the interface between SrTiO3 and two insulating polar oxides, BiMnO3 and LaAlO3. By using polarization dependent x-ray absorption spectroscopy, we find that in both cases the magnetic order is stabilized by a negative exchange interaction between the electrons transferred to the interface and local magnetic moments. These local magnetic moments are associated to Ti3+ ions at the interface itself for LaAlO3/SrTiO3 and to Mn3+ ions in the overlayer for BiMnO3/SrTiO3. In LaAlO3/SrTiO3 the induced magnetic moments are quenched by annealing in oxygen, suggesting a decisive role of oxygen vacancies in the stabilization of interfacial magnetism.Comment: 5 pages, 4 figure

Prediction of Adverse Glycemic Events from Continuous Glucose Monitoring Signal

The most important objective of any diabetes therapy is to maintain the blood glucose concentration within the euglycemic range, avoiding or at least mitigating critical hypo/hyperglycemic episodes. Modern continuous glucose monitoring (CGM) devices bear the promise of providing the patients with an increased and timely awareness of glycemic conditions as these get dangerously near to hypo/hyperglycemia. The challenge is to detect, with reasonable advance, the patterns leading to risky situations, allowing the patient to make therapeutic decisions on the basis of future (predicted) glucose concentration levels. We underline that a technically sound performance comparison of the approaches proposed in recent years has yet to be done, thus it is unclear which one is preferred. The aim of this study is to fill this gap by carrying out a comparative analysis among the most common methods for glucose event prediction. Both regression and classification algorithms have been implemented and analyzed, including static and dynamic training approaches. The dataset consists of 89 CGM time series measured in diabetic subjects for 7 subsequent days. Performance metrics, specifically defined to assess and compare the event-prediction capabilities of the methods, have been introduced and analyzed. Our numerical results show that a static training approach exhibits better performance, in particular when regression methods are considered. However, classifiers show some improvement when trained for a specific event category, such as hyperglycemia, achieving performance comparable to the regressors, with the advantage of predicting the events sooner. © 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other work

The Impact of Concomitant Proton Pump Inhibitors on Immunotherapy Efficacy Among Patients with Urothelial Carcinoma: A Meta-Analysis

Background. Immune checkpoint inhibitors (ICIs) have recently represented a breakthrough in urothelial carcinoma (UC). Proton pump inhibitors (PPIs) are routinely used for extended time periods in UC patients, with these agents having potentially and frequently undervalued effects on ICIs efficacy. Methods. We performed a meta-analysis aimed at investigating the impact of concomitant PPI administration on progression-free survival (PFS) and overall survival (OS) among patients receiving immunotherapy for metastatic UC. Results. Two studies encompassing a total of 1015 patients were included. The pooled Hazard Ratios (HRs) for OS and PFS were 1.55 (95% CI, 1.31–1.84) and 1.43 (95% CI, 1.23–1.66), respectively, suggesting that the administration of PPIs was negatively associated with PFS and with OS in UC patients treated with ICIs. Conclusions. The current meta-analysis represents the first study to provide a systematic evaluation of the impact of concomitant PPI use in UC patients treated with ICIs. Further studies are warranted on this topic to clarify the relationship between gut microbiome, antiacid exposure, and cancer immunotherapy. In the current era of medical oncology, progress in this setting will require the collaboration of basic science and clinical research to optimize systemic treatment and to improve the outcomes of UC patients receiving ICIs

Integrating computational methods to predict mutagenicity of aromatic azo compounds

Azo dyes have several industrial uses. However, these azo dyes and their degradation products showed mutagenicity, inducing damage in environmental and human systems. Computational methods are proposed as cheap and rapid alternatives to predict the toxicity of azo dyes. A benchmark dataset of Ames data for 354 azo dyes was employed to develop three classification strategies using knowledge-based methods and docking simulations. Results were compared and integrated with three models from the literature, developing a series of consensus strategies. The good results confirm the usefulness of in silico methods as a support for experimental methods to predict the mutagenicity of azo compounds

A comprehensive meta-QTL analysis for yield-related traits of durum wheat (Triticum turgidum L. var. durum) grown under different water regimes

Abiotic stress strongly affects yield-related traits in durum wheat, in particular drought is one of the main environmental factors that have effect on grain yield and plant architecture. In order to obtain new genotypes well adapted to stress conditions, the highest number of desirable traits needs to be combined in the same genotype. In this context, hundreds of quantitative trait loci (QTL) have been identified for yield-related traits in different genetic backgrounds and environments. Meta-QTL (MQTL) analysis is a useful approach to combine data sets and for creating consensus positions for the QTL detected in independent studies for the reliability of their location and effects. MQTL analysis is a useful method to dissect the genetic architecture of complex traits, which provide an extensive allelic coverage, a higher mapping resolution and allow the identification of putative molecular markers useful for marker-assisted selection (MAS). In the present study, a complete and comprehensive MQTL analysis was carried out to identify genomic regions associated with grain-yield related traits in durum wheat under different water regimes. A total of 724 QTL on all 14 chromosomes (genomes A and B) were collected for the 19 yield-related traits selected, of which 468 were reported under rainfed conditions, and 256 under irrigated conditions. Out of the 590 QTL projected on the consensus map, 421 were grouped into 76 MQTL associated with yield components under both irrigated and rainfed conditions, 12 genomic regions containing stable MQTL on all chromosomes except 1A, 4A, 5A, and 6B. Candidate genes associated to MQTL were identified and an in-silico expression analysis was carried out for 15 genes selected among those that were differentially expressed under drought. These results can be used to increase durum wheat grain yields under different water regimes and to obtain new genotypes adapted to climate change