Impacts of global change on Mediterranean forests and their services

The increase in aridity, mainly by decreases in precipitation but also by higher temperatures, is likely the main threat to the diversity and survival of Mediterranean forests. Changes in land use, including the abandonment of extensive crop activities, mainly in mountains and remote areas, and the increases in human settlements and demand for more resources with the resulting fragmentation of the landscape, hinder the establishment of appropriate management tools to protect Mediterranean forests and their provision of services and biodiversity. Experiments and observations indicate that if changes in climate, land use and other components of global change, such as pollution and overexploitation of resources, continue, the resilience of many forests will likely be exceeded, altering their structure and function and changing, mostly decreasing, their capacity to continue to provide their current services. A consistent assessment of the impacts of the changes, however, remains elusive due to the difficulty of obtaining simultaneous and complete data for all scales of the impacts in the same forests, areas and regions. We review the impacts of climate change and other components of global change and their interactions on the terrestrial forests of Mediterranean regions, with special attention to their impacts on ecosystem services. Management tools for counteracting the negative effects of global change on Mediterranean ecosystem- services are finally discussed

Th17-Related Genes and Celiac Disease Susceptibility

Th17 cells are known to be involved in several autoimmune or inflammatory diseases. In celiac disease (CD), recent studies suggest an implication of those cells in disease pathogenesis. We aimed at studying the role of genes relevant for the Th17 immune response in CD susceptibility. A total of 101 single nucleotide polymorphisms (SNPs), mainly selected to cover most of the variability present in 16 Th17-related genes (IL23R, RORC, IL6R, IL17A, IL17F, CCR6, IL6, JAK2, TNFSF15, IL23A, IL22, STAT3, TBX21, SOCS3, IL12RB1 and IL17RA), were genotyped in 735 CD patients and 549 ethnically matched healthy controls. Case-control comparisons for each SNP and for the haplotypes resulting from the SNPs studied in each gene were performed using chi-square tests. Gene-gene interactions were also evaluated following different methodological approaches. No significant results emerged after performing the appropriate statistical corrections. Our results seem to discard a relevant role of Th17 cells on CD risk

Computational approaches to explainable artificial intelligence: Advances in theory, applications and trends

Deep Learning (DL), a groundbreaking branch of Machine Learning (ML), has emerged as a driving force in both theoretical and applied Artificial Intelligence (AI). DL algorithms, rooted in complex and non-linear artificial neural systems, excel at extracting high-level features from data. DL has demonstrated human-level performance in real-world tasks, including clinical diagnostics, and has unlocked solutions to previously intractable problems in virtual agent design, robotics, genomics, neuroimaging, computer vision, and industrial automation. In this paper, the most relevant advances from the last few years in Artificial Intelligence (AI) and several applications to neuroscience, neuroimaging, computer vision, and robotics are presented, reviewed and discussed. In this way, we summarize the state-of-the-art in AI methods, models and applications within a collection of works presented at the 9th International Conference on the Interplay between Natural and Artificial Computation (IWINAC). The works presented in this paper are excellent examples of new scientific discoveries made in laboratories that have successfully transitioned to real-life applications.MCIU - Nvidia(UMA18-FEDERJA-084

Computational Approaches to Explainable Artificial Intelligence:Advances in Theory, Applications and Trends

Deep Learning (DL), a groundbreaking branch of Machine Learning (ML), has emerged as a driving force in both theoretical and applied Artificial Intelligence (AI). DL algorithms, rooted in complex and non-linear artificial neural systems, excel at extracting high-level features from data. DL has demonstrated human-level performance in real-world tasks, including clinical diagnostics, and has unlocked solutions to previously intractable problems in virtual agent design, robotics, genomics, neuroimaging, computer vision, and industrial automation. In this paper, the most relevant advances from the last few years in Artificial Intelligence (AI) and several applications to neuroscience, neuroimaging, computer vision, and robotics are presented, reviewed and discussed. In this way, we summarize the state-of-the-art in AI methods, models and applications within a collection of works presented at the 9 International Conference on the Interplay between Natural and Artificial Computation (IWINAC). The works presented in this paper are excellent examples of new scientific discoveries made in laboratories that have successfully transitioned to real-life applications

Molecular characterization of occult hepatitis B virus infection in patients with end-stage liver disease in Colombia.

ABSTARCT: Hepatitis B virus (HBV) occult infection (OBI) is a risk factor to be taken into account in transfusion, hemodialysis and organ transplantation. The aim of this study was to identify and characterize at the molecular level OBI cases in patients with end-stage liver disease. METHODS: Sixty-six liver samples were obtained from patients with diagnosis of end-stage liver disease submitted to liver transplantation in Medellin (North West, Colombia). Samples obtained from patients who were negative for the surface antigen of HBV (n = 50) were tested for viral DNA detection by nested PCR for ORFs S, C, and X and confirmed by Southern-Blot. OBI cases were analyzed by sequencing the viral genome to determine the genotype and mutations; additionally, viral genome integration events were examined by the Alu-PCR technique. RESULTS: In five cases out of 50 patients (10%) the criteria for OBI was confirmed. HBV genotype F (subgenotypes F1 and F3), genotype A and genotype D were characterized in liver samples. Three integration events in chromosomes 5q14.1, 16p13 and 20q12 affecting Receptor-type tyrosine-protein phosphatase T, Ras Protein Specific Guanine Nucleotide Releasing Factor 2, and the zinc finger 263 genes were identified in two OBI cases. Sequence analysis of the viral genome of the 5 OBI cases showed several punctual missense and nonsense mutations affecting ORFs S, P, Core and X. CONCLUSIONS: This is the first characterization of OBI in patients with end-stage liver disease in Colombia. The OBI cases were identified in patients with HCV infection or cryptogenic cirrhosis. The integration events (5q14.1, 16p13 and 20q12) described in this study have not been previously reported. Further studies are required to validate the role of mutations and integration events in OBI pathogenesis

Effect of SGLT2 inhibitors on stroke and atrial fibrillation in diabetic kidney disease: Results from the CREDENCE trial and meta-analysis

BACKGROUND AND PURPOSE: Chronic kidney disease with reduced estimated glomerular filtration rate or elevated albuminuria increases risk for ischemic and hemorrhagic stroke. This study assessed the effects of sodium glucose cotransporter 2 inhibitors (SGLT2i) on stroke and atrial fibrillation/flutter (AF/AFL) from CREDENCE (Canagliflozin and Renal Events in Diabetes With Established Nephropathy Clinical Evaluation) and a meta-Analysis of large cardiovascular outcome trials (CVOTs) of SGLT2i in type 2 diabetes mellitus. METHODS: CREDENCE randomized 4401 participants with type 2 diabetes mellitus and chronic kidney disease to canagliflozin or placebo. Post hoc, we estimated effects on fatal or nonfatal stroke, stroke subtypes, and intermediate markers of stroke risk including AF/AFL. Stroke and AF/AFL data from 3 other completed large CVOTs and CREDENCE were pooled using random-effects meta-Analysis. RESULTS: In CREDENCE, 142 participants experienced a stroke during follow-up (10.9/1000 patient-years with canagliflozin, 14.2/1000 patient-years with placebo; hazard ratio [HR], 0.77 [95% CI, 0.55-1.08]). Effects by stroke subtypes were: ischemic (HR, 0.88 [95% CI, 0.61-1.28]; n=111), hemorrhagic (HR, 0.50 [95% CI, 0.19-1.32]; n=18), and undetermined (HR, 0.54 [95% CI, 0.20-1.46]; n=17). There was no clear effect on AF/AFL (HR, 0.76 [95% CI, 0.53-1.10]; n=115). The overall effects in the 4 CVOTs combined were: Total stroke (HRpooled, 0.96 [95% CI, 0.82-1.12]), ischemic stroke (HRpooled, 1.01 [95% CI, 0.89-1.14]), hemorrhagic stroke (HRpooled, 0.50 [95% CI, 0.30-0.83]), undetermined stroke (HRpooled, 0.86 [95% CI, 0.49-1.51]), and AF/AFL (HRpooled, 0.81 [95% CI, 0.71-0.93]). There was evidence that SGLT2i effects on total stroke varied by baseline estimated glomerular filtration rate (P=0.01), with protection in the lowest estimated glomerular filtration rate (45 mL/min/1.73 m2]) subgroup (HRpooled, 0.50 [95% CI, 0.31-0.79]). CONCLUSIONS: Although we found no clear effect of SGLT2i on total stroke in CREDENCE or across trials combined, there was some evidence of benefit in preventing hemorrhagic stroke and AF/AFL, as well as total stroke for those with lowest estimated glomerular filtration rate. Future research should focus on confirming these data and exploring potential mechanisms

Neutron emission from electromagnetic dissociation of Pb nuclei at √ s NN = 2.76 TeV measured with the ALICE ZDC

The ALICE Zero Degree Calorimeter system (ZDC) is composed of two identical sets of calorimeters, placed at opposite sides with respect to the interaction point, 114 meters away from it, complemented by two small forward electromagnetic calorimeters (ZEM). Each set of detectors consists of a neutron (ZN) and a proton (ZP) ZDC. They are placed at zero degrees with respect to the LHC axis and allow to detect particles emitted close to beam direction, in particular neutrons and protons emerging from hadronic heavy-ion collisions (spectator nucleons) and those emitted from electromagnetic processes. For neutrons emitted by these two processes, the ZN calorimeters have nearly 100% acceptance. During the √ sNN = 2.76 TeV Pb-Pb data-taking, the ALICE Collaboration studied forward neutron emission with a dedicated trigger, requiring a minimum energy deposition in at least one of the two ZN. By exploiting also the information of the two ZEM calorimeters it has been possible to separate the contributions of electromagnetic and hadronic processes and to study single neutron vs. multiple neutron emission. The measured cross sections of single and mutual electromagnetic dissociation of Pb nuclei at √ s NN = 2.76 TeV, with neutron emission, are σ single EMD = 187:4 ± 0.2 (stat.)-11.2 +13.2 (syst.) b and σmutual EMD = 5.7 ± 0.1 (stat.) ±0.4 (syst.) b, respectively [1]. This is the first measurement of electromagnetic dissociation of 208Pb nuclei at the LHC energies, allowing a test of electromagnetic dissociation theory in a new energy regime. The experimental results are compared to the predictions from a relativistic electromagnetic dissociation model'701st International Conference on New Frontiers in Physics, ICFP 20122012-06-10Kolymbari, Crete; Greecesem informaçã

Measurement of azimuthal correlations of D mesons with charged particles in pp collisions at √s=7 TeV and p-Pb collisions at √sNN=5.02 TeV

The azimuthal correlations of D mesons with charged particles were measured with the ALICE apparatus in pp collisions at root s = 7 TeV and p-Pb collisions at root sNN = 5.02 TeV at the Large Hadron Collider. D-0, D+, and D*+ mesons and their charge conjugates with transverse momentum 3 0.3 GeV/c. The yield of charged particles in the correlation peak induced by the jet containing the D meson and the peak width are compatible within uncertainties in the two collision systems. The data are described within uncertainties by Monte-Carlo simulations based on PYTHIA, POWHEG, and EPOS 3 event generators.Peer reviewe

Combined dark matter searches towards dwarf spheroidal galaxies with Fermi-LAT, HAWC, H.E.S.S., MAGIC, and VERITAS

Cosmological and astrophysical observations suggest that 85% of the total matter of the Universe is made of Dark Matter (DM). However, its nature remains one of the most challenging and fundamental open questions of particle physics. Assuming particle DM, this exotic form of matter cannot consist of Standard Model (SM) particles. Many models have been developed to attempt unraveling the nature of DM such as Weakly Interacting Massive Particles (WIMPs), the most favored particle candidates. WIMP annihilations and decay could produce SM particles which in turn hadronize and decay to give SM secondaries such as high energy \u1d6fe rays. In the framework of indirect DM search, observations of promising targets are used to search for signatures of DM annihilation. Among these, the dwarf spheroidal galaxies (dSphs) are commonly favored owing to their expected high DM content and negligible astrophysical background. In this work, we present the very first combination of 20 dSph observations, performed by the Fermi-LAT, HAWC, H.E.S.S., MAGIC, and VERITAS collaborations in order to maximize the sensitivity of DM searches and improve the current results. We use a joint maximum likelihood approach combining each experiment’s individual analysis to derive more constraining upper limits on the WIMP DM self-annihilation cross-section as a function of DM particle mass. We present new DM constraints over the widest mass range ever reported, extending from 5 GeV to 100 TeV thanks to the combination of these five different \u1d6fe-ray instruments