Non-cooperative identification of civil aircraft using a generalised mutual subspace method

The subspace-based methods are effectively applied to classify sets of feature vectors by modelling them as subspaces. However, their application to the field of non-cooperative target identification of flying aircraft is barely seen in the literature. In these methods, setting the subspace dimensionality is always an issue. Here, it is demonstrated that a modified mutual subspace method, which uses softweights to set the importance of each subspace basis, is a promising classifier for identifying sets of range profiles coming from real in-flight targets with no need to set the subspace dimensionality in advance. The assembly of a recognition database is also a challenging task. In this study, this database comprises predicted range profiles coming from electromagnetic simulations. Even though the predicted and actual profiles differ, the high recognition rates achieved reveal that the algorithm might be a good candidate for its application in an operational target recognition system

Non-cooperative target identification based on singular value decomposition

Non-Cooperative Target Identification based on High Resolution Range Profiles is a key research domain in the Defense industry. In this paper a method based on the application of Singular Value Decomposition to a matrix of range profiles is defined. The decomposition is applied to reduce dimensionality and to accomplish recognition in the transformed domain. So as to confirm the feasibility of the methodology, identification experiments of profiles coming from electromagnetic simulations are conducted, revealing promising results

Structural basis for the dominant or recessive character of GLIALCAM mutations found in leukodystrophies

Megalencephalic leukoencephalopathy with subcortical cysts (MLC) is a type of leukodystrophy characterized by white matter edema, and it is caused mainly by recessive mutations in MLC1 and GLIALCAM genes. These variants are called MLC1 and MLC2A with both types of patients sharing the same clinical phenotype. In addition, dominant mutations in GLIALCAM have also been identified in a subtype of MLC patients with a remitting phenotype. This variant has been named MLC2B. GLIALCAM encodes for an adhesion protein containing two immunoglobulin (Ig) domains and it is needed for MLC1 targeting to astrocyte-astrocyte junctions. Most mutations identified in GLIALCAM abolish GlialCAM targeting to junctions. However, it is unclear why some mutations behave as recessive or dominant. Here, we used a combination of biochemistry methods with a new developed anti-GlialCAM nanobody, double-mutants and cysteine cross-links experiments, together with computer docking, to create a structural model of GlialCAM homo-interactions. Using this model, we suggest that dominant mutations affect different GlialCAM-GlialCAM interacting surfaces in the first Ig domain, which can occur between GlialCAM molecules present in the same cell (cis) or present in neighbouring cells (trans). Our results provide a framework that can be used to understand the molecular basis of pathogenesis of all identified GLIALCAM mutations

Phonon structure, infra-red and raman spectra of Li2MnO3 by first-principles calculations

The layer-structured monoclinic Li2MnO3 is a key material, mainly due to its role in Li-ion batteries and as a precursor for adsorbent used in lithium recovery from aqueous solutions. In the present work, we used first-principles calculations based on density functional theory (DFT) to study the crystal structure, optical phonon frequencies, infra-red (IR), and Raman active modes and compared the results with experimental data. First, Li2MnO3 powder was synthesized by the hydrothermal method and successively characterized by XRD, TEM, FTIR, and Raman spectroscopy. Secondly, by using Local Density Approximation (LDA), we carried out a DFT study of the crystal structure and electronic properties of Li2MnO3. Finally, we calculated the vibrational properties using Density Functional Perturbation Theory (DFPT). Our results show that simulated IR and Raman spectra agree well with the observed phonon structure. Additionally, the IR and Raman theoretical spectra show similar features compared to the experimental ones. This research is useful in investigations involving the physicochemical characterization of Li2MnO3 materia

El "entorno natural" en la docencia de lenguas extranjeras y geografía en los Grados en Turismo y Maestro en Educación Primaria. Elaboración de un glosario conceptual alemán-francés-español

Memoria ID-0066. Ayudas de la Universidad de Salamanca para la innovación docente, curso 2016-2017

Methionine Cycle Rewiring by Targeting miR-873-5p Modulates Ammonia Metabolism to Protect the Liver from Acetaminophen

Drug-induced liver injury (DILI) development is commonly associated with acetaminophen (APAP) overdose, where glutathione scavenging leads to mitochondrial dysfunction and hepatocyte death. DILI is a severe disorder without effective late-stage treatment, since N-acetyl cysteine must be administered 8 h after overdose to be efficient. Ammonia homeostasis is altered during liver diseases and, during DILI, it is accompanied by decreased glycine N-methyltransferase (GNMT) expression and S-adenosylmethionine (AdoMet) levels that suggest a reduced methionine cycle. Anti-miR-873-5p treatment prevents cell death in primary hepatocytes and the appearance of necrotic areas in liver from APAP-administered mice. In our study, we demonstrate a GNMT and methionine cycle activity restoration by the anti-miR-873-5p that reduces mitochondrial dysfunction and oxidative stress. The lack of hyperammoniemia caused by the therapy results in a decreased urea cycle, enhancing the synthesis of polyamines from ornithine and AdoMet and thus impacting the observed recovery of mitochondria and hepatocyte proliferation for regeneration. In summary, anti-miR-873-5p appears to be an effective therapy against APAP-induced liver injury, where the restoration of GNMT and the methionine cycle may prevent mitochondrial dysfunction while activating hepatocyte proliferative response.We thank Ministerio de Ciencia e Innovación, Programa Retos-Colaboración RTC2019- 007125-1 (for J.S. and M.L.M.-C.); Instituto de Salud Carlos III: Proyectos de Investigación en Salud DTS20/00138 (for J.S. and M.L.M.-C.), PI20/00690 (for R.J.) and PT20/000127 (for M.I.L.); CIBERehd: EHD21TRF01/2022 (to M.L.M.-C.); Departamento de Industria del Gobierno Vasco (for M.L.M.-C.); Ministerio de Ciencia, Innovación y Universidades MICINN: PID2020-117116RB-I00 and RTI2018- 096759-1-100 integrado en el Plan Estatal de Investigación Cientifica y Técnica y Innovación, cofinanciado con Fondos FEDER (for M.L.M.-C. and T.C.D., respectively); BIOEF (Basque Foundation for Innovation and Health Research); Asociación Española contra el Cáncer (AECC) (to M.L.M.-C., T.C.D.); AECC: GCTRA18006CARR (to A.C.); Fundación Científica de la Asociación Española Contra el Cancer (AECC Scientific Foundation) Rare Tumor Calls 2017 (for M.L.M.); La Caixa Foundation Program (for M.L.M.); BFU2015-70067-REDC, BFU2016-77408-R and BES-2017-080435 (MINECO/FEDER, UE); Ministerio de Ciencia, Innovación y universidades PID2019-108787RB-100 (to A.C.), PID2019- 109055RB-I00 (L.A.M.-C.), PID2020-117941RB-100 (to F.J.C.); Spanish Ministry of Economy and Competitiveness Grants BFU2013-47531-R and BFU2016-77408-R (L.A.M.-C.) and the FIGHT-CNNM2 project from the EJP RD Joint Transnational Call (JTC2019) (Ref. AC19/00073) (for L.A.M.-C.); Comunidad de Madrid: EXOHEP-CM S2017/BMD-3727 and NanoLiver-CM Y2018/NMT-4949 co-funded by European Structural and Investment Fund and COST Action CA17112 (to F.J.C.); Vencer el Cáncer Foundation (to A.C.); European Research Council: Consolidator Grant 819242 (to A.C.); CIBERONC and CIBERehd were funded by the Instituto de Salud Carlos III and Cofunded by FEDER funds. Partial funding for open access charge: Universidad de Málag

A Randomized Comparison of Drug-Eluting Balloon Versus Everolimus-Eluting Stent in Patients With Bare-Metal Stent–In-Stent Restenosis The RIBS V Clinical Trial (Restenosis Intra-stent of Bare Metal Stents: Paclitaxel-eluting Balloon vs. Everolimus-eluting Stent)

ObjectivesThis study sought to compare the efficacy of drug-eluting balloons (DEB) with that of everolimus-eluting stents (EES) in patients with bare-metal stents (BMS) in-stent restenosis (ISR).BackgroundTreatment of patients with ISR remains a challenge.MethodsThis was a prospective, multicenter, randomized trial comparing DEB with EES in patients with bare-metal stents (BMS) in-stent restenosis (ISR). The primary endpoint was the minimal lumen diameter at 9 months' follow-up.ResultsA total of 189 patients with BMS-ISR from 25 Spanish sites were included (95 were allocated to DEB and 94 to EES). Procedural success was achieved in all patients. At late angiography (median 249 days; 92% of eligible patients), patients in the EES arm had a significantly larger minimal lumen diameter (2.36 ± 0.6 mm vs. 2.01 ± 0.6 mm, p < 0.001; absolute mean difference: 0.35 mm; 95% confidence interval [CI]: 0.16 to 0.53) and a lower percent of diameter stenosis (13 ± 17% vs. 25 ± 20%, p < 0.001). However, late loss (0.04 ± 0.5 mm vs. 0.14 ± 0.5 mm, p = 0.14) and binary restenosis rate (4.7% vs. 9.5%, p = 0.22) were very low and similar in both groups. Clinical follow-up (median 365 days) was obtained in all (100%) patients. Occurrences of the combined clinical outcome measure (cardiac death, myocardial infarction, and target vessel revascularization; 6% vs. 8%; hazard ratio [HR]: 0.76; 95% CI: 0.26 to 2.18, p = 0.6) and the need for target vessel revascularization (2% vs. 6%; HR: 0.32: 95% CI: 0.07 to 1.59, p = 0.17) were similar in the 2 groups.ConclusionsIn patients with BMS-ISR, both DEB and EES provided excellent clinical results with a very low rate of clinical and angiographic recurrences. However, compared with DEB, EES provide superior late angiographic findings. (Restenosis Intra-stent of Bare Metal Stents: Paclitaxel-eluting Balloon vs. Everolimus-eluting Stent [RIBS V]; NCT01239953

Clonal chromosomal mosaicism and loss of chromosome Y in elderly men increase vulnerability for SARS-CoV-2

The pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2, COVID-19) had an estimated overall case fatality ratio of 1.38% (pre-vaccination), being 53% higher in males and increasing exponentially with age. Among 9578 individuals diagnosed with COVID-19 in the SCOURGE study, we found 133 cases (1.42%) with detectable clonal mosaicism for chromosome alterations (mCA) and 226 males (5.08%) with acquired loss of chromosome Y (LOY). Individuals with clonal mosaic events (mCA and/or LOY) showed a 54% increase in the risk of COVID-19 lethality. LOY is associated with transcriptomic biomarkers of immune dysfunction, pro-coagulation activity and cardiovascular risk. Interferon-induced genes involved in the initial immune response to SARS-CoV-2 are also down-regulated in LOY. Thus, mCA and LOY underlie at least part of the sex-biased severity and mortality of COVID-19 in aging patients. Given its potential therapeutic and prognostic relevance, evaluation of clonal mosaicism should be implemented as biomarker of COVID-19 severity in elderly people. Among 9578 individuals diagnosed with COVID-19 in the SCOURGE study, individuals with clonal mosaic events (clonal mosaicism for chromosome alterations and/or loss of chromosome Y) showed an increased risk of COVID-19 lethality

Non-Cooperative Target Recognition by Means of Singular Value Decomposition Applied to Radar High Resolution Range Profiles

Radar high resolution range profiles are widely used among the target recognition community for the detection and identification of flying targets. In this paper, singular value decomposition is applied to extract the relevant information and to model each aircraft as a subspace. The identification algorithm is based on angle between subspaces and takes place in a transformed domain. In order to have a wide database of radar signatures and evaluate the performance, simulated range profiles are used as the recognition database while the test samples comprise data of actual range profiles collected in a measurement campaign. Thanks to the modeling of aircraft as subspaces only the valuable information of each target is used in the recognition process. Thus, one of the main advantages of using singular value decomposition, is that it helps to overcome the notable dissimilarities found in the shape and signal-to-noise ratio between actual and simulated profiles due to their difference in nature. Despite these differences, the recognition rates obtained with the algorithm are quite promising