Photochemically-induced protein tyrosine nitration in vitro and in cellula by 5-methyl-1,4-dinitro-1H-imidazole (DNI): synthesis and biochemical characterization

Natalia Ríos: Departamento de Bioquímica, Facultad de Medicina, Universidad de la República, Montevideo, Uruguay; Centro de Investigaciones Biomédicas (CEINBIO), Facultad de Medicina, Universidad de la República, Montevideo, Uruguay -- Adrian Aicardo: Departamento de Bioquímica, Facultad de Medicina, Universidad de la República, Montevideo, Uruguay; Centro de Investigaciones Biomédicas (CEINBIO), Facultad de Medicina, Universidad de la República, Montevideo, Uruguay; Departamento de Nutrición Clínica, Escuela de Nutrición, Universidad de la República, Montevideo, Uruguay -- Cecilia Chavarría: Departamento de Bioquímica, Facultad de Medicina, Universidad de la República, Montevideo, Uruguay; Centro de Investigaciones Biomédicas (CEINBIO), Facultad de Medicina, Universidad de la República, Montevideo, Uruguay -- Rodrigo Ivagnes: Departamento de Bioquímica, Facultad de Medicina, Universidad de la República, Montevideo, Uruguay; Centro de Investigaciones Biomédicas (CEINBIO), Facultad de Medicina, Universidad de la República, Montevideo, Uruguay -- Mauricio Mastrogiovanni: Departamento de Bioquímica, Facultad de Medicina, Universidad de la República, Montevideo, Uruguay; Centro de Investigaciones Biomédicas (CEINBIO), Facultad de Medicina, Universidad de la República, Montevideo, Uruguay -- Rafael Radi: Departamento de Bioquímica, Facultad de Medicina, Universidad de la República, Montevideo, Uruguay; Centro de Investigaciones Biomédicas (CEINBIO), Facultad de Medicina, Universidad de la República, Montevideo, Uruguay -- José M. Souza: Departamento de Bioquímica, Facultad de Medicina, Universidad de la República, Montevideo, Uruguay; Centro de Investigaciones Biomédicas (CEINBIO), Facultad de Medicina, Universidad de la República, Montevideo, Uruguay. Contacto: [email protected] photochemical nitrating agent 5-methyl-1,4-dinitro-1H-imidazole (DNI) has been recently described as an effective tool for nitrating tyrosine residues in proteins under 390 nm irradiation (Long T. et al., 2021). Herein, we describe the one-step synthesis of DNI from the precursor 4-methyl-5-nitro-1H-imidazole with good yield (66%) and high purity (>99%). Spectral analysis of DNI reveals two maximum peaks (228 and 290 nm) with maximum nitration yields and kinetics occurring at 290 nm. Electron paramagnetic resonance (EPR)- and mass spectrometry (MS)- spin trapping analysis evidenced the formation of nitrogen dioxide (•NO2) upon irradiation of DNI, implying the homolysis of the N–N bond in the DNI molecule. Irradiation of DNI at 290, 390 nm, or UVA light (315–400 nm), produced tyrosine nitration, with yields approaching ca. 30% with respect to DNI at 290 nm exposure. Indeed, using alpha-synuclein as a model protein, the main protein post-translational modification triggered by DNI was the generation of 3-nitrotyrosine as shown by MS analysis. Additionally, the formation of di-tyrosine was also observed. Finally, intracellular •NO2 production upon DNI photolysis in bovine aortic endothelial cells was evidenced by the nitration of the tyrosine analog probe p-hydroxyphenylacetic acid (PHPA) and cellular protein tyrosine nitration

Utilizzo di un nuovo saggio molecolare per la rilevazione diretta di specie di <i>Candida</i> clinicamente rilevanti da emocolture positive

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Qualification Tests of Aerospace Composite Materials with Embedded Optical Fibers

Due to the high reliability requirements in aerospace components a test campaign to qualify composite materials with embedded optical fibers has been carried out. The majority of the tests performed are standard ones since they are described in ASTM specifications. Selection and choice of the tests to be performed is done in order to obtain mechanical data that can be used for structural analysis by designers and for process control by manufacturers. More specific tests, for aerospace applications, have been performed to study the effect thermal cycling has on the mechanical characteristics of the materials. These tests are important because they simulate the effects that space structures could have when subjected to not uniform heating such as when they move in and out from the Earth’s shadow. A fiber optic network embedded into a structure is on principle a nervous system capable to sense the external environment through the changes of the properties or of the path length of coherent light. In order to be able to actually measure the strain in the structure, the fiber should be perfectly bonded on the hosting material. Therefore further non conventional tests have been devised to check this important aspect both before and after thermal cycling

Extracellular Alpha-Synuclein: Mechanisms for Glial Cell Internalization and Activation

Alpha-synuclein (α-syn) is a small protein composed of 140 amino acids and belongs to the group of intrinsically disordered proteins. It is a soluble protein that is highly expressed in neurons and expressed at low levels in glial cells. The monomeric protein aggregation process induces the formation of oligomeric intermediates and proceeds towards fibrillar species. These α-syn conformational species have been detected in the extracellular space and mediate consequences on surrounding neurons and glial cells. In particular, higher-ordered α-syn aggregates are involved in microglial and oligodendrocyte activation, as well as in the induction of astrogliosis. These phenomena lead to mitochondrial dysfunction, reactive oxygen and nitrogen species formation, and the induction of an inflammatory response, associated with neuronal cell death. Several receptors participate in cell activation and/or in the uptake of α-syn, which can vary depending on the α-syn aggregated state and cell types. The receptors involved in this process are of outstanding relevance because they may constitute potential therapeutic targets for the treatment of PD and related synucleinopathies. This review article focuses on the mechanism associated with extracellular α-syn uptake in glial cells and the consequent glial cell activation that contributes to the neuronal death associated with synucleinopathies

Smart manufacturing in the framework of space industry. An industry 4.0 approach to large scale production of satellite constellations

One of the major trend in the so-called New Space Economy or Space 4.0 paradigm has seen a number of new commercial players entering the satellite industry and creating completely new business models, most of which based on very large constellations consisting of several hundreds or even thousands of satellites. The production of the high number of satellites involved in the modern mega-constellations is bringing in the Space Industry the necessity of improved and optimized manufacturing approaches suitable for serial production (standard environment/high number of platforms). In this framework, the adoption of Industry 4.0 methodologies into space industry will lead to a significant improvement and optimization of the whole Manufacturing Assembly Integration and Testing (MAIT) cycle. The main aim of Industry 4.0 is the creation of intelligent factories where manufacturing technologies are upgraded and transformed by Cyber-Physical Systems (CPSs) the Internet of Things (IoT), cloud computing and big data analytics with predictive monitoring features such as the ones that characterize Smart Structures [4]. One main element of the Industry 4.0 approach is the synergic use of embedded production technologies with intelligent production processes with positive and important modifications of the industrial values chains, production value chains, and business models. In the present work, developed in the frame of project of European Space Agency, possible scenarios of applications of the Industry 4.0 concepts are presented and discussed in terms of applicability and advantages for Satellite Manufacturing [10,17]. Particular focus will be given to development of a CPS, by establishing a control network of sensors (e.g. temperature, location, load) over a target MAIT process

SMART MANUFACTURING IN THE SPACE INDUSTRY. A CYBER-PHYSICAL SYSTEM ARCHITECTURE AND ITS IMPLEMENTATION TO A MAIT PROCESS FOR MEGA CONSTELLATIONS OF SATELLITES

Industry 4.0, or Smart Manufacturing, is driving the evolution of industrial scenarios worldwide through an extensive introduction of Information Technologies as an integration to Operational Technologies. Access and use of data have become determinant factors of the efficacy of innovation requested to answer the increasingly urgent need of lowering production costs. Reviewing the State-of-Art of Smart Manufacturing technologies in the space industry and beyond, the authors found that the newest tools, such as Digital Twins, Internet of Things and Cyber-Physical Systems, have started to be applied, following the principles of interoperability, connectivity and modularity. However, still huge improvements are possible to optimize space productions to reach the ambitious efficiency goals of new commercial businesses, first of which the rising trend of mega constellations of small satellites. RUAG’s Space satellite composite sandwich panel Manufacturing Assembly Integration and Testing process was selected as reference. The as-is process data measurements and collection nowadays still rely on human workers’ long-term expertise, mainly related to visual inspection of defects or physical standard equipment. Data is stored in remote databases, not connected to the process nor easily available to the personnel. Moreover, the process is far from low-cost high-pace mass-market production systems, being materials and processes customized based on the product and heavily depending on procurement logics. Considerable effort has been made toward innovation, resulting for example in the automation of highly repetitive operations, such as insert potting, with the introduction of an Automated insert Potting Machine (APM). Taking as reference this operation to measure process KPIs’ improvement, a two-level approach was applied to implement a Cyber-Physical System to the process: first, using the existing measurement systems (e.g. sensors, devices and equipment like APM) to gather data in a digital database and then introducing new data by the addition of new sensing equipment. The CPS is based on the interconnection of sensors through a networking infrastructure managed by a central processing unit. Data flows from physical devices, digitally twinned, up to an operator dashboard, where the results of intermediate processing steps, including normalization, categorization, storage and interpretation by a closed-feedback loop logic based on KPIs’ statistical predictive models, are displayed. In this paper, the CPS conceptual and system architecture will be presented: data detection and measurement systems, techniques and strategies for data treatment and correlation, how decision making and process control is activated in the process, how hardware and software components are interrelated