Unravelling the structure of the tetrahedral metal-binding site in METP3 through an experimental and computational approach

Understanding the structural determinants for metal ion coordination in metalloproteins is a fundamental issue for designing metal binding sites with predetermined geometry and activity. In order to achieve this, we report in this paper the design, synthesis and metal binding properties of METP3, a homodimer made up of a small peptide, which self assembles in the presence of tetra-hedrally coordinating metal ions. METP3 was obtained through a redesign approach, starting from the previously developed METP molecule. The undecapeptide sequence of METP, which dimerizes to house a Cys4 tetrahedral binding site, was redesigned in order to accommodate a Cys2His2 site. The binding properties of METP3 were determined toward different metal ions. Successful assem-bly of METP3 with Co(II), Zn(II) and Cd(II), in the expected 2:1 stoichiometry and tetrahedral geometry was proven by UV-visible spectroscopy. CD measurements on both the free and metal-bound forms revealed that the metal coordination drives the peptide chain to fold into a turned conformation. Finally, NMR data of the Zn(II)-METP3 complex, together with a retrostructural analysis of the Cys-X-X-His motif in metalloproteins, allowed us to define the model structure. All the results establish the suitability of the short METP sequence for accommodating tetrahedral metal binding sites, regardless of the first coordination ligands

N-nonyloxypentyl-l-deoxynojirimycin inhibits growth, biofilm formation and virulence factors expression of Staphylococcus aureus

Staphylococcus aureus is one of the major causes of hospital-and community-associated bacterial infections throughout the world, which are difficult to treat due to the rising number of drug-resistant strains. New molecules displaying potent activity against this bacterium are urgently needed. In this study, d-and l-deoxynojirimycin (DNJ) and a small library of their N-alkyl derivatives were screened against S. aureus ATCC 29213, with the aim to identify novel candidates with inhibitory potential. Among them, N-nonyloxypentyl-l-DNJ (l-NPDNJ) proved to be the most active compound against S. aureus ATCC 29213 and its clinical isolates, with the minimum inhibitory concentration (MIC) value of 128 µg/mL. l-NPDNJ also displayed an additive effect with gentamicin and oxacillin against the gentamicin-and methicillin-resistant S. aureus isolate 00717. Sub-MIC values of l-NPDNJ affected S. aureus biofilm development in a dose-dependent manner, inducing a strong reduction in biofilm biomass. Moreover, real-time reverse transcriptase PCR analysis revealed that l-NPDNJ effectively inhibited at sub-MIC values the transcription of the spa, hla, hlb and sea virulence genes, as well as the agrA and saeR response regulator genes

Performances' Estimation by Tests of Composite Material Structures With Respect to the Lay-Up Configuration and Mixing the Position of Tape and Fabric Laminae

Abstract This paper presents an estimation of performances by tests on composite material structures. In order to evaluate the effects on the structural behavior, tests changing the percentage of orientation of the fiber at 0, 45 and 90 degrees and mixing the unidirectional plies with the fabric ones have been done. Fixed the lay-up configuration and so the stacking sequence, two typology of structures have been analyzed; the first one having only unidirectional plies while the second one having a fabric ply (plain weave 0/90) in place of the top and bottom unidirectional plies. The openhole compressive strength and the filled-hole tensile strength and moduli have been characterized by test. A total of 72 specimens have been used in the test campaign. In order to well compare the test results a Performance Weight Index (PWI) has been introduced by authors in order to normalize the strength of each laminate with respect to its weight/unit of surface. Results and different laminate behaviors have been evaluated and discussed

Prikaz znanja u internetu stvari: semantičko modeliranje i njegove primjene

Semantic modelling provides a potential basis for interoperating among different systems and applications in the Internet of Things (IoT). However, current work has mostly focused on IoT resource management while not on the access and utilisation of information generated by the “Things”. We present the design of a comprehensive and lightweight semantic description model for knowledge representation in the IoT domain. The design follows the widely recognised best practices in knowledge engineering and ontology modelling. Users are allowed to extend the model by linking to external ontologies, knowledge bases or existing linked data. Scalable access to IoT services and resources is achieved through a distributed, semantic storage design. The usefulness of the model is also illustrated through an IoT service discovery method.Semantičko modeliranje pruža potencijalnu osnovu za me.udjelovanje različitih sustava i aplikacija unutar interneta stvari (IoT). Međutim, postojeći radovi uglavnom su fokusirani na upravljanje IoT resursima, ali ne i pristupu i korištenju informacija koje generira “stvar”. Predstavljamo projektiranje sveobuhvatnog i laganog semantičkog opisnog modela za prikaz znanja u IoT domeni. Projektiranje slijedi široko-priznate najbolje običaje u inženjerstvu znanja i ontološkom modeliranju. Korisnicima se dopušta proširenje modela povezivanjem na eksterne ontologije, baze znanja ili postoje će povezane podatke. Skalabilni pristup IoT uslugama i resursima postiže se kroz distribuirano, semantičko projektiranje pohrane. Upotrebljivost modela tako.er je ilustrirana kroz metodu pronalaska IoT usluga

Nat Genet

The function of the majority of genes in the mouse and human genomes remains unknown. The mouse embryonic stem cell knockout resource provides a basis for the characterization of relationships between genes and phenotypes. The EUMODIC consortium developed and validated robust methodologies for the broad-based phenotyping of knockouts through a pipeline comprising 20 disease-oriented platforms. We developed new statistical methods for pipeline design and data analysis aimed at detecting reproducible phenotypes with high power. We acquired phenotype data from 449 mutant alleles, representing 320 unique genes, of which half had no previous functional annotation. We captured data from over 27,000 mice, finding that 83% of the mutant lines are phenodeviant, with 65% demonstrating pleiotropy. Surprisingly, we found significant differences in phenotype annotation according to zygosity. New phenotypes were uncovered for many genes with previously unknown function, providing a powerful basis for hypothesis generation and further investigation in diverse systems.Comment in : Genetic differential calculus. [Nat Genet. 2015] Comment in : Scaling up phenotyping studies. [Nat Biotechnol. 2015

Skin-spar failure detection of a composite Winglet using fbg sensors

Winglets are introduced into modern aircraft to reduce wing aerodynamic drag and to consequently optimize the fuel burn per mission. In order to be aerodynamically effective, these devices are installed at the wing tip section; this wing region is generally characterized by relevant oscillations induced by flights maneuvers and gust. The present work is focused on the validation of a continuous monitoring system based on fiber Bragg grating sensors and frequency domain analysis to detect physical condition of a skin-spar bonding failure in a composite winglet for in-service purposes. Optical fibers are used as deformation sensors. Short Time Fast Fourier Transform (STFT) analysis is applied to analyze the occurrence of structural response deviations on the base of strain data. Obtained results showed high accuracy in estimating static and dynamic deformations and great potentials in detecting structural failure occurrences

Pharmacovigilance in the era of social media: Discovering adverse drug events cross-relating Twitter and PubMed

In pharmacovigilance, post-marketing surveillance is mainly supported by spontaneous reporting systems (SRS) collecting adverse drug events explicitly submitted by physicians alerted by their patients. Nowadays, this activity could leverage on mining opinions and experiences of individuals from social media by monitoring users’ posts citing symptoms, drugs, etc. The most critical problem is the reliability of the information sources. In order to address this challenge, the proposed method tries to cross-relate heterogeneous data sources with correspondingly different levels of trustworthiness. It filters out assertions quoted on social media on the basis of data validated by official information sources. The method adopts the Fuzzy Formal Concept Analysis (Fuzzy FCA) to evaluate the reliability of adverse drug events extracted on Twitter and PubMed. It keeps track of the difference between the co-citation frequencies by calculating a residual threshold τ. The main outcome is that with τ in the range [−4,+4], 91% of drug and side effect correlations extracted from tweets can be considered reliable, according to the official site (we used http://sideeffects.embl.de)

Multi-body model validation of a landing gear system for a general aviation aircraft

The present work is aimed to numerically validate the experimental drop test results [1], related to the landing gear of a general aviation aircraft, in order to define an appropriate simulation methodology able to save time, costs and risks due to structural design and experimental test campaign required in the certification phase. The aircraft selected for this research activity is the AP-68TP-300 Spartacus, an Italian nine-seat, twin-engined, high wing monoplane, realized by Vulcanair S.p.a.. The multi-body approach has been developed through the MSC Adams software, starting from a simplified 1D model up to a more detailed 3D one. The comparison between numerical and experimental results in terms of load factors has been carried out in accordance with CS-23 [2-3] (Certification Specifications for Normal, Utility, Aerobatic and Commuter Aeroplanes), and it has shown a good correlation, especially for the 3D model, since it better fits the real behavior of the entire system

Energy finite element analysis (EFEA) approach for fuselage noise prediction

This paper presents an approach used to determine the acoustic noise in a fuselage of a regional turboprop aircraft. The acoustic noise is due to diffuse field pressure (DFP) generated by turboprop engines and to the acoustic power generated by air vent of the Environmental Control Sub-System (ECS). Frequency dependency has been also taken into account. The analysis has been conducted by using new software distributed by MSC Software and developed by University of Michigan, MSC EFEA. It is based on Energy Finite Element Analysis (EFEA) that has been developed for evaluating the vibro-acoustic behavior of complex systems. A finite element approach is employed for solving the governing differential equations numerically. Joint finite element matrices are developed at all the locations where the primary variable of the EFEA formulation is discontinuous. The numerical model of the fuselage has been covered (externally and on the floor) by skins with proper structural characteristics associated with transmission loss to reproduce the real conditions. Acoustic treatments in the different part of the structure have been modeled in all their components. The acoustic effects of the seats and the passengers have been taken into account by defining the proper adsorption coefficients in the affected volumes of the cabin. DFP and ECS frequency dependency are also taken into account

Cross-relating heterogeneous Text Streams for Credibility Assessment

Network-enabled devices and the consecutive surge of internet users created a significant impact on the knowledge society. In the era of Social Media, the final user is the new reporter that embraces these tools to spread novelty and breaking news about specific subjects. Sometimes, this type of reporting is biased due to the level of the user's knowledge of the matter or to intentionally achieve a goal. The ability to share other users' post magnify this phenomenon and create a domino effect that can lead to the diffusion of biased information. Therefore, the reliability of the shared novelty about an event is becoming fundamental more than ever. The proposed method tries to deal with this drawback by cross-relating text streams with corresponding heterogeneous levels of reliability, for instance, Twitter and Google News. As Text Stream Mining technique, the method adopts the Fuzzy Formal Concept Analysis to incrementally carry out a fuzzy lattice for each text stream. These two fuzzy lattices are compared in time and context-aware manner to derive the trustworthiness of the relations among entities that are mentioned together in the same tweet content. Preliminary experimental results made on a real dataset show that the proposed credibility assessment system provides good performance depending on some parameters, like similarity threshold T (empirically fixed at 0.8) and time window, set at 1 hour