Campylobacter jejuni loss of culturability in aqueous microcosms and ability to resuscitate in a mouse model

Water is known as one of the main transmission routes of Campylobacter and contributes to increase the number of sporadic infections and outbreaks. Campylobacter jejuni persists in the environment, especially in water, in a viable but non-culturable (VBNC) form that is thought to be a possible cause of water-borne outbreaks. In this study, we evaluated the loss of culturability and viability of 9 C. jejuni strains of clinical origin and one ATCC reference strain when kept at 4 degrees C in artificial sea water (ASW). Culturability was measured as colony-forming units while viability was evaluated by CTC-DAPI double staining and the combined CTC-specific fluorescent antibody technique (CTC-FA). When cultured on Columbia Agar plates, strains exhibited different growth profiles which allowed to classify them into three different groups. Both techniques used to monitor the viability of the bacterial cells showed that C. jejuni strains survived in the VBNC form in the microcosms through a period lasting from 138 to 152 days. The recovery of C. jejuni VBNC forms to culturability, as evidenced by cell division, was obtained by passage in the mouse intestine. Our results indicate that C. jejuni VBNC cells were able to remain in this state for a few months and regain their culturability after in vivo passage depending on their lasting in the VBNC state, which affects the number of respiring bacteria. In fact, the resuscitation was achieved when the number of respiring bacteria became higher than 10(4) cell/ml. Therefore, a relatively high microbial titer of respiring bacteria in the VBNC state seems to be important for the resuscitation and subsequent intestinal colonisation.     

In-House Validation and Comparison of Two Wheat (<Emphasis Type="Italic">Triticum aestivum</Emphasis>) Taxon-Specific Real-Time PCR Methods for GMO Quantification Supported by Droplet Digital PCR

Common wheat is one of the most important staple food crops worldwide. However, unlike other important staple crops such as maize or soybean, genetically modified (GM) wheat is not yet present in the global food market. Nonetheless, in the recent past, the adventitious presence of GM glyphosate-tolerant volunteers was reported in open wheat fields in the USA. The European Union Reference Laboratory for GM Food and Feed (EURL-GMFF) was therefore called to develop a strategy to detect such unauthorised GM wheat in wheat samples by using both taxon-specific and screening tests. Two candidate common wheat taxon-specific real-time PCR methods were suggested, one targeting ssII-D gene coding for starch synthase and the other targeting waxy-D1 gene, coding for granule-bound starch synthase. In the present study, the two above-mentioned real-time PCR taxon-specific methods were in-house verified and compared, proposing droplet digital PCR (ddPCR) as a new tool for supporting the application of the European Network of GMO Laboratories (ENGL) established method performance criteria. Preliminary performance data of waxy-D1 and ssII-D methods in ddPCR format are shown too to give a contribution to the bridging process from the consolidated to the emerging quantitative PCR methodology.     

Microfibrillated cellulose as reinforcement for Li-ion battery polymer electrolytes with excellent mechanical stability

Methacrylic-based thermo-set gel-polymer electrolyte membranes obtained by a very easy, fast and reliable free radical photo-polymerisation process and reinforced with microfibrillated cellulose particles are here presented. The morphology of the composite electrolytes is investigated by scanning electron microscopy and their thermal behaviour (characteristic temperatures, degradation temperature) are investigated by thermo-gravimetric analysis and differential scanning calorimetry. The composite membranes prepared exhibit excellent mechanical properties, with a Young's modulus as high as about 80 MPa at ambient temperature. High ionic conductivity (approaching 10⁻³ S cm⁻¹ at 25 °C) and good overall electrochemical performances are maintained, enlightening that such specific approach would make these hybrid organic, cellulose-based composite polymer electrolyte systems a strong contender in the field of thin and flexible lithium based power sources.     

Mycotoxin occurrence in beer produced in several European countries

The occurrence of ochratoxin A, trichothecenes, fumonisins and aflatoxins in a sample of 106 beers produced in several European countries, was investigated. The analyses were conducted using high-performance liquid chromatography with fluorimetric detection for ochratoxin A and aflatoxins, gas-chromatography and high-performance liquid chromatography, both coupled with mass spectrometer, for trichothecenes and fumonisins, respectively. Aflatoxins were not detected in any samples, whereas ochratoxin A, deoxynivalenol and fumonisins were found in a relatively high number of samples. Their presence was at low levels in all samples; however, some differences were observed between the European countries. As regards ochratoxin A, beer samples from southern Europe showed levels always lower than 0.040 μg l^?1, while the samples from other European countries showed significantly higher values, up to 0.189 μg l^?1 (P < 0.001). For fumonisins, the levels of Italian beers were significantly higher compared to the samples from other countries (P = 0.006).     

Push &; Pull: autonomous deployment of mobile sensors for a complete coverage

Mobile sensor networks are important for several strategic applications devoted to monitoring critical areas. In such hostile scenarios, sensors cannot be deployed manually and are either sent from a safe location or dropped from an aircraft. Mobile devices permit a dynamic deployment reconfiguration that improves the coverage in terms of completeness and uniformity. In this paper we propose a distributed algorithm for the autonomous deployment of mobile sensors called Push & Pull. According to our proposal, movement decisions are made by each sensor on the basis of locally available information and do not require any prior knowledge of the operating conditions or any manual tuning of key parameters. We formally prove that, when a sufficient number of sensors are available, our approach guarantees a complete and uniform coverage. Furthermore, we demonstrate that the algorithm execution always terminates preventing movement oscillations. Numerous simulations show that our algorithm reaches a complete coverage within reasonable time with moderate energy consumption, even when the target area has irregular shapes. Performance comparisons between Push & Pull and one of the most acknowledged algorithms show how the former one can efficiently reach a more uniform and complete coverage under a wide range of working scenarios.     

Identification of new epidemiological molecular markers by comparative proteomics of serogroup A meningococcal isolates from three pandemic waves

We previously described the first reference map for the proteome of one strain of serogroup A Neisseria meningitidis (MenA), a major cause of epidemic meningitis in humans. As a preliminary finding, in that work we noted that 2‐DE protein maps of closely related MenA isolates from different epidemics spreads could be easily compared to detect minor differences and that 2‐DE phenotypes attributable to the well‐known epidemiological marker tbpB agreed with the genoclouds model of MenA epidemiological variation during pandemic waves. We explored here the possibility that an extended comparative study of 2‐DE maps of isolates representative of the nine genoclouds described by Achtman and collaborators could be used to discriminate between strains otherwise undistinguishable. We showed the example of 14 proteins with different 2‐DE spot patterns in different genoclouds that could be considered as putative tracers for alike‐strains discrimination. We introduce the novel concept that comparative proteomics can be useful in identifying new epidemiological markers for N. meningitidis.     

Effect of uncertainties on substructure coupling: Modelling and reduction strategies

Different strategies for modelling and reducing the effect of uncertainties on the dynamic behaviour of coupled structures are discussed in this paper. In assembled structures, each component satisfies specifications about material properties and dimensional tolerances. Variability of design specifications within the tolerance field may affect the dynamic behaviour of the assembled structure more than that of any individual component substructure. Among modelling strategies, non-predictive techniques such as post-processing of data from a set of randomly assembled structures and analysis of sensitivities to uncertain variables are considered. However, emphasis is placed on a less trivial yet simple strategy such as the use of design of experiments to fit a regression model. Different reduction strategies are considered according to whether small design changes (even revised tolerance allocation) are still possible or not. In the latter case, selective assembly is extended to problems where the performance requirement is not the clearance between two parts, but a prescribed dynamic behaviour.     

Environmental data processing by clustering methods for energy forecast and planning

This paper presents a statistical approach based on the k-means clustering technique to manage environmental sampled data to evaluate and to forecast of the energy deliverable by different renewable sources in a given site. In particular, wind speed and solar irradiance sampled data are studied in association to the energy capability of a wind generator and a photovoltaic (PV) plant, respectively. The proposed method allows the sub-sets of useful data, describing the energy capability of a site, to be extracted from a set of experimental observations belonging the considered site. The data collection is performed in Sicily, in the south of Italy, as case study. As far as the wind generation is concerned, a suitable generator, matching the wind profile of the studied sites, has been selected for the evaluation of the producible energy. With respect to the photovoltaic generation, the irradiance data have been taken from the acquisition system of an actual installation. It is demonstrated, in both cases, that the use of the k-means clustering method allows data that do not contribute to the produced energy to be grouped into a cluster, moreover it simplifies the problem of the energy assessment since it permits to obtain the desired information on energy capability by managing a reduced amount of experimental samples. In the studied cases, the proposed method permitted a reduction of the 50% of the data with a maximum discrepancy of 10% in energy estimation compared to the classical statistical approach. Therefore, the adopted k-means clustering technique represents an useful tool for an appropriate and less demanding energy forecast and planning in distributed generation systems.