Scandium complexes bearing bis(oxazolinylphenyl)amide ligands: an analysis of their reactivity, solution-state structures and photophysical properties

The coordination chemistry of scandium supported by bis(oxazolinylphenyl)amide (R-BOPA) ligands is reported. The R-BOPA ligand is too sterically demanding to afford bis(amide) complexes [Sc(R-BOPA){N(SiMe3)2}2], but reaction of the protio-ligand with [Sc{N(SiMe3)2}2Cl(THF)] (1) afforded the mixed amido-chloride complexes [Sc(R-BOPA){N(SiMe3)2}Cl] (2). The selective reaction of the amido and chloride co-ligands in 2 has been investigated; whilst the chloride ligand can be removed cleanly by metathesis, protonation of the N(SiMe3)2 ligand results in competitive protonation of the R-BOPA ligand. The complexes [Sc(R-BOPA)(CH2SiMe2Ph)2] (5) have been synthesised. Each R-BOPA-containing complex exists in two isomeric forms. The equilibrium has been investigated both experimentally and computationally, and the data suggest that a concerted rotation of the phenyl rings interconverts the two diastereomeric isomers. All of the R-BOPA complexes were found to be luminescent; an analysis of the photophysics, aided by TD-DFT calculations, suggests ligand-centred luminescence with distinct emission lifetimes for each isomer

IT-Security Risk Based Approach for Secure Operation of Distributed Data Platforms in Supply Chains

This research paper examines the topic of secure data exchange in a supply chain within the manufacturing sector. The objective is the development of a data platform that optimizes operational efficiency and promotes cross-company collaboration. To achieve this, helpful tools are utilized and suitable standards are followed to create a secure system. Security measures are determined by conducting a risk analysis to identify, evaluate, and compensate for potential threats. Furthermore, the utilization of non-transparent federated learning models in combination with a method of security design of components contributes to the information sovereignty of data owners. In conclusion, secure data sharing practices play a pivotal role in supporting collaboration and operational effectiveness in the manufacturing industry

In Vivo Ligands of MDA5 and RIG-I in Measles Virus-Infected Cells

RIG-I-like receptors (RLRs: RIG-I, MDA5 and LGP2) play a major role in the innate immune response against viral infections and detect patterns on viral RNA molecules that are typically absent from host RNA. Upon RNA binding, RLRs trigger a complex downstream signaling cascade resulting in the expression of type I interferons and proinflammatory cytokines. In the past decade extensive efforts were made to elucidate the nature of putative RLR ligands. In vitro and transfection studies identified 5'-triphosphate containing blunt-ended double-strand RNAs as potent RIG-I inducers and these findings were confirmed by next-generation sequencing of RIG-I associated RNAs from virus-infected cells. The nature of RNA ligands of MDA5 is less clear. Several studies suggest that double-stranded RNAs are the preferred agonists for the protein. However, the exact nature of physiological MDA5 ligands from virus-infected cells needs to be elucidated. In this work, we combine a crosslinking technique with next-generation sequencing in order to shed light on MDA5-associated RNAs from human cells infected with measles virus. Our findings suggest that RIG-I and MDA5 associate with AU-rich RNA species originating from the mRNA of the measles virus L gene. Corresponding sequences are poorer activators of ATP-hydrolysis by MDA5 in vitro, suggesting that they result in more stable MDA5 filaments. These data provide a possible model of how AU-rich sequences could activate type I interferon signaling

Abschlussbericht Zukunftslabor Produktion - Teilprojekt 5: IT-Infrastruktur und IT-Sicherheit

Ziel des Verbundvorhabens „Zukunftslabor Produktion“ war die Untersuchung durchgängiger digitaler Prozessketten, welche die Vernetzung von Systemen in der Produktion, die Modellierung von Produktionsprozessen sowie innovative Ansätze zur Optimierung von Arbeitsvorgängen umfasst. Die möglichen ökonomischen, organisationalen und qualitativen Vorteile digitaler Prozessketten werden im Zukunftslabor am Beispiel des Aluminiumdruckgussverfahrens untersucht. Das Projekt wurde in verschiedene Arbeitspakete aufgeteilt, die von verschiedenen Hochschulen bearbeitet wurden. Das Arbeitspaket IT-Infrastruktur und Sicherheit, welches von der Hochschule Hannover und von der Hochschule Emden/Leer bearbeitet wurde, hatte das Ziel eine Plattform zur Unterstützung zu schaffen, welche Daten in einer Schicht aggregiert und einer Analyseplattform zur unternehmensübergreifenden Analyse zur Verfügung stellt. Darüber hinaus wurden in diesem Arbeitspaket die IT-Security-Aspekte des Projektes bearbeitet. Dieser Bericht beschreibt die Ausgangslage, die Methodik und die Ergebnisse des Arbeitspakets. Vielfach werden Ergebnisse und Arbeitsinhalte zusammengefasst, aber keine vollständigen Auswertungen präsentiert. Weiterführende Informationen finden Sie in einer der 12 wissenschaftlichen Veröffentlichungen, sowie einigen internen Projektberichten. Eine Auflistung der im Rahmen des Verbundvorhabens „Zukunftslabor Produktion“ entstandenen Veröffentlichungen ist in Kapitel 9 aufgeführt

Sunfall: a collaborative visual analytics system for astrophysics

Computational and experimental sciences produce and collect ever-larger and complex datasets, often in large-scale, multi-institution projects. The inability to gain insight into complex scientific phenomena using current software tools is a bottleneck facing virtually all endeavors of science. In this paper, we introduce Sunfall, a collaborative visual analytics system developed for the Nearby Supernova Factory, an international astrophysics experiment and the largest data volume supernova search currently in operation. Sunfall utilizes novel interactive visualization and analysis techniques to facilitate deeper scientific insight into complex, noisy, high-dimensional, high-volume, time-critical data. The system combines novel image processing algorithms, statistical analysis, and machine learning with highly interactive visual interfaces to enable collaborative, user-driven scientific exploration of supernova image and spectral data. Sunfall is currently in operation at the Nearby Supernova Factory; it is the first visual analytics system in production use at a major astrophysics project

Cyber-Sicherheit in vernetzten Lieferketten

Mit zunehmender Komplexität der Lieferketten durch Globalisierung und Entwicklung der Technologie steigt auch die Notwendigkeit des Austausches von Informationen zwischen kooperierenden, aber unabhängigen Unternehmen. Dabei stehen sie vor der Herausforderung, eine Balance zwischen der erforderlichen Transparenz zur übergreifenden Optimierung der Lieferkette und dem Schutz sensibler Daten aus ihren Produktionssystemen zu finden. Angesichts zunehmender Bedrohungen durch Cyberkriminalität, von gezielten Angriffen auf Produktionssysteme bis hin zum Datendiebstahl geistigen Eigentums, ist der Schutz digitaler Infrastrukturen für Unternehmen unverzichtbar. Im Rahmen des Teilprojekts „IT-Infrastruktur und IT-Sicherheit“ hat das Zukunftslabor Produktion den Prototyp einer Unterstützungsplattform für einen unternehmensübergreifenden Datenaustausch unter Bewahrung von Datensouveränität entwickelt und zusammen mit Praxispartnern evaluiert. Ihre Funktionsweise wird in diesem Beitrag erläutert, der den vierten und letzten einer Serie bildet, in der die Projektpartner jeweils ihre Teilergebnisse vorstellen

Seeking supernovae in the clouds: a performance study,”

ABSTRACT Today, our picture of the Universe radically differs from that of just over a decade ago. We now know that the Universe is not only expanding as Hubble discovered in 1929, but that the rate of expansion is accelerating, propelled by mysterious new physics dubbed "Dark Energy." This revolutionary discovery was made by comparing the brightness of nearby Type Ia supernovae (which exploded in the past billion years) to that of much more distant ones (from up to seven billion years ago). The reliability of this comparison hinges upon a very detailed understanding of the physics of the nearby events. As part of its effort to further this understanding, the Nearby Supernova Factory (SNfactory) relies upon a complex pipeline of serial processes that execute various image processing algorithms in parallel on ~10TBs of data. This pipeline has traditionally been run on a local cluster. Cloud computing offers many features that make it an attractive alternative. The ability to completely control the software environment in a Cloud is appealing when dealing with a community developed science pipeline with many unique library and platform requirements. In this context we study the feasibility of porting the SNfactory pipeline to the Amazon Web Services environment. Specifically we: describe the tool set we developed to manage a virtual cluster on Amazon EC2, explore the various design options available for application data placement, and offer detailed performance results and lessons learned from each of the above design options

Ovidio nella riscrittura di Albrecht von Halberstadt

The reworking of Ovid's Metamorphoses by Albrecht von Halberstadt, dating back to the end of the twelfth century, survives only in few Fragments. In this essay, I will analyse Fragment B, which contains tales from Book XI of the Metamorphoses, in order to assess Albrecht's rewriting techniques, and his simplification of both matter and style. Indeed, Albrecht employs the middle style, while his Latin source was written in a rhetorical and elevated style. Albrecht's Fragments will be compared with the Ovidian source and with the Eneit of Heinrich von Veldeke, highlighting the features shared by the two rewritings of classical texts, which were both commissioned by the Landgrave Hermann of Thuringia

Crystal Structure of the PAC1R Extracellular Domain Unifies a Consensus Fold for Hormone Recognition by Class B G-Protein Coupled Receptors

Pituitary adenylate cyclase activating polypeptide (PACAP) is a member of the PACAP/glucagon family of peptide hormones, which controls many physiological functions in the immune, nervous, endocrine, and muscular systems. It activates adenylate cyclase by binding to its receptor, PAC1R, a member of class B G-protein coupled receptors (GPCR). Crystal structures of a number of Class B GPCR extracellular domains (ECD) bound to their respective peptide hormones have revealed a consensus mechanism of hormone binding. However, the mechanism of how PACAP binds to its receptor remains controversial as an NMR structure of the PAC1R ECD/PACAP complex reveals a different topology of the ECD and a distinct mode of ligand recognition. Here we report a 1.9 Å crystal structure of the PAC1R ECD, which adopts the same fold as commonly observed for other members of Class B GPCR. Binding studies and cell-based assays with alanine-scanned peptides and mutated receptor support a model that PAC1R uses the same conserved fold of Class B GPCR ECD for PACAP binding, thus unifying the consensus mechanism of hormone binding for this family of receptors

Causal Modeling Using Network Ensemble Simulations of Genetic and Gene Expression Data Predicts Genes Involved in Rheumatoid Arthritis

Tumor necrosis factor α (TNF-α) is a key regulator of inflammation and rheumatoid arthritis (RA). TNF-α blocker therapies can be very effective for a substantial number of patients, but fail to work in one third of patients who show no or minimal response. It is therefore necessary to discover new molecular intervention points involved in TNF-α blocker treatment of rheumatoid arthritis patients. We describe a data analysis strategy for predicting gene expression measures that are critical for rheumatoid arthritis using a combination of comprehensive genotyping, whole blood gene expression profiles and the component clinical measures of the arthritis Disease Activity Score 28 (DAS28) score. Two separate network ensembles, each comprised of 1024 networks, were built from molecular measures from subjects before and 14 weeks after treatment with TNF-α blocker. The network ensemble built from pre-treated data captures TNF-α dependent mechanistic information, while the ensemble built from data collected under TNF-α blocker treatment captures TNF-α independent mechanisms. In silico simulations of targeted, personalized perturbations of gene expression measures from both network ensembles identify transcripts in three broad categories. Firstly, 22 transcripts are identified to have new roles in modulating the DAS28 score; secondly, there are 6 transcripts that could be alternative targets to TNF-α blocker therapies, including CD86 - a component of the signaling axis targeted by Abatacept (CTLA4-Ig), and finally, 59 transcripts that are predicted to modulate the count of tender or swollen joints but not sufficiently enough to have a significant impact on DAS28