A Versatile Approach to Ullmann C−N Couplings at Room Temperature: New Families of Nucleophiles and Electrophiles for Photoinduced, Copper-Catalyzed Processes

The use of light to facilitate copper-catalyzed cross-couplings of nitrogen nucleophiles can enable C−N bond formation to occur under unusually mild conditions. In this study, we substantially expand the scope of such processes, establishing that this approach is not limited to reactions of carbazoles with iodobenzene and alkyl halides. Specifically, we demonstrate for the first time that other nitrogen nucleophiles (e.g., common pharmacophores such as indoles, benzimidazoles, and imidazoles) as well as other electrophiles (e.g., hindered/deactivated/heterocyclic aryl iodides, an aryl bromide, an activated aryl chloride, alkenyl halides, and an alkynyl bromide) serve as suitable partners. Photoinduced C−N bond formation can be achieved at room temperature using a common procedure with an inexpensive catalyst (CuI) that does not require a ligand coadditive and is tolerant of moisture and a variety of functional groups

Sistema de enfoque basado en dos espejos elípticos y un espejo plano rotatorio para un radar a 300 GHz

A focusing system for a 300 GHz radar with two target distances (5m and 10m) is proposed, having 1cm resolution in both cases. The focusing system is based on a gaussian telescope scheme and it has been designed using gaussian beam quasi-optical propagation theory with a homemade Matlab analysis tool. It has been translated into a real focusing system based on two elliptical mirrors and a plane mirror in order to have scanning capabilities and validated using the commercial antenna software GRAS

Knowledge representation tool for cognitiveprocesses modeling

In the last decades, neuropsychological theories tend to consider cognitive functions as a result of the whole brainwork and not as individual local areas of its cortex. Studies based on neuroimaging techniques have increased in the last years, promoting an exponential growth of the body of knowledge about relations between cognitive functions and brain structures [1]. However, so fast evolution make complicated to integrate them in verifiable theories and, even more, translated in to cognitive rehabilitation. The aim of this research work is to develop a cognitive process-modeling tool. The purpose of this system is, in the first term, to represent multidimensional data, from structural and functional connectivity, neuroimaging, data from lesion studies and derived data from clinical intervention [2][3]. This will allow to identify consolidated knowledge, hypothesis, experimental designs, new data from ongoing studies and emerging results from clinical interventions. In the second term, we pursuit to use Artificial Intelligence to assist in decision making allowing to advance towards evidence based and personalized treatments in cognitive rehabilitation. This work presents the knowledge base design of the knowledge representation tool. It is compound of two different taxonomies (structure and function) and a set of tags linking both taxonomies at different levels of structural and functional organization. The remainder of the abstract is organized as follows: Section 2 presents the web application used for gathering necessary information for generating the knowledge base, Section 3 describes knowledge base structure and finally Section 4 expounds reached conclusions

"Bioadsorption of silver ions by calcareous chitin, chitin and chitosan"

"Context: Calcareous chitin, chitin, chitosan, and their modifications are used as bioadsorbents of metals and dyes that cause environmental pollution, endocrine disruption, and human diseases. Aims: To evaluate the selective bioadsorption of silver ions (Ag+ ) by calcareous chitin, chitin, and chitosan. Methods: Experimental and prospective study. The presence of functional groups of the bioadsorbents was identified by Fourier-transformed infrared spectroscopy (FT-IR), 1H-NMR spectroscopy and scanning electron microscopy (SEM). The Langmuir, Freundlich, and Elovich models were applied to describe the adsorption capacity of bioadsorbents according to granule size (20-40, 40-60, 60-80 meshes) and temperature (10, 20, and 30°C). Results: The FT-IR spectrum of calcareous chitin indicates the presence of carbonate (CO3 = 1420 cm-1 ), amide III (1313 cm-1 ), –OH groups (3441.90 cm-1 ), and pyranose structure (952.83 cm-1 ); chitin has –OH groups (3441.90 cm-1 ), NH (3268 cm-1 ), amide I (1654 cm-1 ) and II (1559 cm-1 ); chitosan has –OH groups (3419.90 cm-1 ), –NH (3200 cm-1 ), amide I (1712.18 cm-1 ), –NH2 (1654.46 cm-1 ), amide III (1317.11 cm-1 ) and pyranose structure (1070.12 cm-1 and 1031 cm-1 ). The Langmuir model indicates greater bioadsorption of Ag+ ions at smaller particle sizes (60-80 = 0.25-0.18 mm) and at a temperature of 20-30°C. Conclusions: The bioadsorption of silver ions (Ag+ ) by chitosan is greater with respect to calcareous chitin and chitin; the Langmuir model fits for the Ag+ isotherm and suggests that the process is controlled by physisorption.

Methylglyoxal Produced by Amyloid- Peptide-Induced Nitrotyrosination of Triosephosphate Isomerase Triggers Neuronal Death in Alzheimer’s Disease

Amyloid-β peptide (Aβ) aggregates induce nitro-oxidative stress, contributing to the characteristic neurodegeneration found in Alzheimer's disease (AD). One of the most strongly nitrotyrosinated proteins in AD is the triosephosphate isomerase (TPI) enzyme which regulates glycolytic flow, and its efficiency decreased when it is nitrotyrosinated. The main aims of this study were to analyze the impact of TPI nitrotyrosination on cell viability and to identify the mechanism behind this effect. In human neuroblastoma cells (SH-SY5Y), we evaluated the effects of Aβ42 oligomers on TPI nitrotyrosination. We found an increased production of methylglyoxal (MG), a toxic byproduct of the inefficient nitro-TPI function. The proapoptotic effects of Aβ42 oligomers, such as decreasing the protective Bcl2 and increasing the proapoptotic caspase-3 and Bax, were prevented with a MG chelator. Moreover, we used a double mutant TPI (Y165F and Y209F) to mimic nitrosative modifications due to Aβ action. Neuroblastoma cells transfected with the double mutant TPI consistently triggered MG production and a decrease in cell viability due to apoptotic mechanisms. Our data show for the first time that MG is playing a key role in the neuronal death induced by Aβ oligomers. This occurs because of TPI nitrotyrosination, which affects both tyrosines associated with the catalytic center

Identification of Linearized RMS-Voltage Dip Patterns Based on Clustering in Renewable Plants

[EN] Generation units connected to the grid are currently required to meet low-voltage ride-through (LVRT) requirements. In most developed countries, these requirements also apply to renewable sources, mainly wind power plants and photovoltaic installations connected to the grid. This study proposes an alternative characterisation solution to classify and visualise a large number of collected events in light of current limits and requirements. The authors' approach is based on linearised root-mean-square-(RMS)-voltage trajectories, taking into account LRVT requirements, and a clustering process to identify the most likely pattern trajectories. The proposed solution gives extensive information on an event's severity by providing a simple but complete visualisation of the linearised RMS-voltage patterns. In addition, these patterns are compared to current LVRT requirements to determine similarities or discrepancies. A large number of collected events can then be automatically classified and visualised for comparative purposes. Real disturbances collected from renewable sources in Spain are used to assess the proposed solution. Extensive results and discussions are also included in this study.The authors thank the financial support from the 'Ministerio de Economia y Competitividad' (Spain) and the European Union - ENE2016-78214-C2-2-R, Fulbright/Spanish Ministry of Education Visiting Scholar - PRX14/00694. This work was also supported by the US Department of Energy under contract no. DE-AC36-08-GO28308 with the National Renewable Energy LaboratoryGarcía-Sánchez, TM.; Gómez-Lázaro, E.; Muljadi, E.; Kessler, M.; Muñoz-Benavente, I.; Molina-García, A. (2018). Identification of Linearized RMS-Voltage Dip Patterns Based on Clustering in Renewable Plants. IET Generation Transmission & Distribution. 12(6):1256-1262. https://doi.org/10.1049/iet-gtd.2017.0474S12561262126Craciun B. Kerekes T. Sera D.et al.: ‘Overview of recent grid codes for PV power integration’.13th Int. Conf. on Optimization of Electrical and Electronic Equipment (OPTIM) 2012 May2012 pp.959–965‘World Energy Outlook 2012’. Technical Report International Egency Agency (IEA) 2012. Available atwww.iea.orgBehrens C.E.: ‘Energy policy: 113th congress issues’.Congressional Research Service 2013Lopes, J. A. P., Hatziargyriou, N., Mutale, J., Djapic, P., & Jenkins, N. (2007). Integrating distributed generation into electric power systems: A review of drivers, challenges and opportunities. Electric Power Systems Research, 77(9), 1189-1203. doi:10.1016/j.epsr.2006.08.016Glassmire, J., Komor, P., & Lilienthal, P. (2012). Electricity demand savings from distributed solar photovoltaics. Energy Policy, 51, 323-331. doi:10.1016/j.enpol.2012.08.022Carvalho, D., Wemans, J., Lima, J., & Malico, I. (2011). Photovoltaic energy mini-generation: Future perspectives for Portugal. Energy Policy, 39(9), 5465-5473. doi:10.1016/j.enpol.2011.05.016Battaglini, A., Komendantova, N., Brtnik, P., & Patt, A. (2012). Perception of barriers for expansion of electricity grids in the European Union. Energy Policy, 47, 254-259. doi:10.1016/j.enpol.2012.04.065‘European Commission 2010a. Energy 2020. A strategy for competitive sustainable and secure energy’. Technical Report Brussels November2011Beurskens P.V.L.W.M. Hekkenberg M.: ‘Renewable energy projections as published in the national renewable energy action plans of the european member states’. Technical Report European Environment Agency (EEA) November2011Coll-Mayor, D., Paget, M., & Lightner, E. (2007). Future intelligent power grids: Analysis of the vision in the European Union and the United States. Energy Policy, 35(4), 2453-2465. doi:10.1016/j.enpol.2006.09.001Passey, R., Spooner, T., MacGill, I., Watt, M., & Syngellakis, K. (2011). The potential impacts of grid-connected distributed generation and how to address them: A review of technical and non-technical factors. Energy Policy, 39(10), 6280-6290. doi:10.1016/j.enpol.2011.07.027Sangroniz N. Mora J.A. Teixeira M.D.: ‘Review of international grid codes for wind generation’ 2009‘Global Market Outlook for Photovoltaics Until 2016’. Technical Report European Photovoltaic Industry Association 2012. Available atwww.epia.orgKim S. Bollen M.: ‘Towards the development of a set of grid code requirements for wind farms: transient reactive power requirements’. Technical Report Available as Elforsk Report 13 : 04. Part 3 Report of Vindforsk Project V‐369 Vindforsk III January2013Tsili, M., & Papathanassiou, S. (2009). A review of grid code technical requirements for wind farms. IET Renewable Power Generation, 3(3), 308. doi:10.1049/iet-rpg.2008.0070Hossain, J., & Mahmud, A. (Eds.). (2014). Renewable Energy Integration. Green Energy and Technology. doi:10.1007/978-981-4585-27-9Sourkounis C. Tourou P.: ‘Grid code requirements for wind power integration in Europe’.Conf. Papers in Energy 2013 pp.1–9Voltage Ride-Through Capability Verification of Wind Turbines With Fully-Rated Converters Using Reachability Analysis. (2014). IEEE Transactions on Energy Conversion, 29(2), 392-405. doi:10.1109/tec.2013.2295168Mohseni, M., & Islam, S. M. (2012). Review of international grid codes for wind power integration: Diversity, technology and a case for global standard. Renewable and Sustainable Energy Reviews, 16(6), 3876-3890. doi:10.1016/j.rser.2012.03.039‘Royal Decree 1565/2010 by which regulates and modifies certain aspects of the activity of production of electric energy in special regime. (In spanish)’. Technical Report November2010Sourkounis C. Tourou P.: ‘Grid code requirements for wind power integration in Europe’.Conf. Papers in Science 2013Jiménez, F., Gómez-Lázaro, E., Fuentes, J. A., Molina-García, A., & Vigueras-Rodríguez, A. (2011). Validation of a double fed induction generator wind turbine model and wind farm verification following the Spanish grid code. Wind Energy, 15(4), 645-659. doi:10.1002/we.498Montoro D.: ‘Recommendations for unified technical regulations for grid‐connected PV systems’. Technical Report SUNRISE project – European Photovoltaic Industry Association the European Construction Industry Federation the European Association of Electrical Contractors International Union of Architects 2009. Available athttp://www.pvsunrise.eu/Merino, J., Mendoza-Araya, P., & Veganzones, C. (2014). State of the Art and Future Trends in Grid Codes Applicable to Isolated Electrical Systems. Energies, 7(12), 7936-7954. doi:10.3390/en7127936deAlmeida P. Barbosa P. Duque C.et al.: ‘Grid connection considerations for the integration of PV and wind sources’.IEEE 16th Int. Conf. on Harmonics and Quality of Power (ICHQP) May2014 pp.6–9‘Network code requirements for grid connection applicable to all generators’. Technical Report European Network of Transmission System Operators for Electricity ENTSO‐E October2013. Available athttps://www.entsoe.eu/Kagan N. Ferrari E. Matsuo N.et al.: ‘Influence of rms variation measurement protocols on electrical system performance indices for voltage sags and swells’.Proc. Ninth Int. Conf. on Harmonics and Quality of Power 2000 2000 vol.3 pp.790–795Bollen, M. H. J. (2003). Algorithms for characterizing measured three-phase unbalanced voltage dips. IEEE Transactions on Power Delivery, 18(3), 937-944. doi:10.1109/tpwrd.2003.813879Bollen M.H.: ‘Comparing voltage dip survey results’.Power Engineering Society Winter Meeting 2002 2002 vol.2 pp.1130–1134Moreno‐Muñoz A. de laRosa J.: ‘Voltage sag in highly automated factories’.Industry Applications Society Annual Meeting IAS'08 2008 pp.1–6Gomez-Lazaro, E., Fuentes, J. A., Molina-Garcia, A., & Canas-Carreton, M. (2009). Characterization and Visualization of Voltage Dips in Wind Power Installations. IEEE Transactions on Power Delivery, 24(4), 2071-2078. doi:10.1109/tpwrd.2009.2027513Gunther, E. W., & Mebta, H. (1995). A survey of distribution system power quality-preliminary results. IEEE Transactions on Power Delivery, 10(1), 322-329. doi:10.1109/61.368382Belloni F. Chiappa C. Chiumeo R.et al.: ‘Voltage dip measurements along MV lines vs primary substations measurements’.Int. Conf. on Renewable Energies and Power Quality (ICREPQ'12) March2012 pp.28–30Garcia-Sanchez, T., Gomez-Lazaro, E., Muljadi, E., Kessler, M., & Molina-Garcia, A. (2016). Statistical and Clustering Analysis for Disturbances: A Case Study of Voltage Dips in Wind Farms. IEEE Transactions on Power Delivery, 31(6), 2530-2537. doi:10.1109/tpwrd.2016.2522946Barrera Nunez V. Melendez Frigola J. 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Localization of a bacterial group II intron-encoded protein in human cells

Group II introns are mobile retroelements that self-splice from precursor RNAs to form ribonucleoparticles (RNP), which can invade new specific genomic DNA sites. This specificity can be reprogrammed, for insertion into any desired DNA site, making these introns useful tools for bacterial genetic engineering. However, previous studies have suggested that these elements may function inefficiently in eukaryotes. We investigated the subcellular distribution, in cultured human cells, of the protein encoded by the group II intron RmInt1 (IEP) and several mutants. We created fusions with yellow fluorescent protein (YFP) and with a FLAG epitope. We found that the IEP was localized in the nucleus and nucleolus of the cells. Remarkably, it also accumulated at the periphery of the nuclear matrix. We were also able to identify spliced lariat intron RNA, which co-immunoprecipitated with the IEP, suggesting that functional RmInt1 RNPs can be assembled in cultured human cells.This work was supported by research grants CSD 2009–0006 from the Consolider-Ingenio, BIO2011-24401 and BIO2014-51953-P from the Spanish Ministerio de Economía y Competitividad all including ERDF (European Regional Development Funds). We thank Dr. Antonio Barrientos Durán for technical advice. MRC was supported by an FPI Ph.D grant. J.L.G.P´s laboratory is supported by CICE-FEDER-P09-CTS-4980, CICE-FEDER-P12-CTS-2256, Plan Nacional de I+D+I 2008–2011 and 2013–2016 (FIS-FEDER-PI11/01489 and FIS-FEDER-PI14/02152), PCIN-2014-115-ERA-NET NEURON II, the European Research Council (ERC-Consolidator ERC-STG-2012-233764) and by an International Early Career Scientist grant from the Howard Hughes Medical Institute (IECS-55007420).Peer Reviewe

Deciphering the complex interplay between pancreatic cancer, diabetes mellitus subtypes and obesity/BMI through causal inference and mediation analyses.

OBJECTIVES: To characterise the association between type 2 diabetes mellitus (T2DM) subtypes (new-onset T2DM (NODM) or long-standing T2DM (LSDM)) and pancreatic cancer (PC) risk, to explore the direction of causation through Mendelian randomisation (MR) analysis and to assess the mediation role of body mass index (BMI). DESIGN: Information about T2DM and related factors was collected from 2018 PC cases and 1540 controls from the PanGenEU (European Study into Digestive Illnesses and Genetics) study. A subset of PC cases and controls had glycated haemoglobin, C-peptide and genotype data. Multivariate logistic regression models were applied to derive ORs and 95% CIs. T2DM and PC-related single nucleotide polymorphism (SNP) were used as instrumental variables (IVs) in bidirectional MR analysis to test for two-way causal associations between PC, NODM and LSDM. Indirect and direct effects of the BMI-T2DM-PC association were further explored using mediation analysis. RESULTS: T2DM was associated with an increased PC risk when compared with non-T2DM (OR=2.50; 95% CI: 2.05 to 3.05), the risk being greater for NODM (OR=6.39; 95% CI: 4.18 to 9.78) and insulin users (OR=3.69; 95% CI: 2.80 to 4.86). The causal association between T2DM (57-SNP IV) and PC was not statistically significant (ORLSDM=1.08, 95% CI: 0.86 to 1.29, ORNODM=1.06, 95% CI: 0.95 to 1.17). In contrast, there was a causal association between PC (40-SNP IV) and NODM (OR=2.85; 95% CI: 2.04 to 3.98), although genetic pleiotropy was present (MR-Egger: p value=0.03). Potential mediating effects of BMI (125-SNPs as IV), particularly in terms of weight loss, were evidenced on the NODM-PC association (indirect effect for BMI in previous years=0.55). CONCLUSION: Findings of this study do not support a causal effect of LSDM on PC, but suggest that PC causes NODM. The interplay between obesity, PC and T2DM is complex