Validation of the performance of a GMO multiplex screening assay based on microarray detection

A new screening method for the detection and identification of GMO, based on the use of multiplex PCR followed by microarray, has been developed and is presented. The technology is based on the identification of quite ubiquitous GMO genetic target elements first amplified by PCR, followed by direct hybridisation of the amplicons on a predefined microarray (DualChip^® GMO, Eppendorf, Germany). The validation was performed within the framework of a European project (Co-Extra, contract no 007158) and in collaboration with 12 laboratories specialised in GMO detection. The present study reports the strategy and the results of an ISO complying validation of the method carried out through an inter-laboratory study. Sets of blind samples were provided consisting of DNA reference materials covering all the elements detectable by specific probes present on the array. The GMO concentrations varied from 1% down to 0.045%. In addition, a mixture of two GMO events (0.1% RRS diluted in 100% TOPAS19/2) was incorporated in the study to test the robustness of the assay in extreme conditions. Data were processed according to ISO 5725 standard. The method was evaluated with predefined performance criteria with respect to the EC CRL method acceptance criteria. The overall method performance met the acceptance criteria; in particular, the results showed that the method is suitable for the detection of the different target elements at 0.1% concentration of GMO with a 95% accuracy rate. This collaborative trial showed that the method can be considered as fit for the purpose of screening with respect to its intra- and inter-laboratory accuracy. The results demonstrated the validity of combining multiplex PCR with array detection as provided by the DualChip^® GMO (Eppendorf, Germany) for the screening of GMO. The results showed that the technology is robust, practical and suitable as a screening tool.     

Laser sintering of coated polyamide 12: a new way to improve flammability

Journal of Materials Science - In this study coatings of kaolin and talc particles were successfully applied on the surface of polyamide 12 powder intended for laser sintering (LS). Microscopic...     

Monitoring ligand modulation of protein-protein interactions by mass spectrometry: estrogen receptor alpha-SRC1

Many drugs and chemicals exert their biological effect by modulating protein-protein interactions. In vitro approaches to characterize these mechanisms are often based on indirect measurements (e.g., fluorescence). Here, we used mass spectrometry (MS) to directly monitor the effect of small-molecule ligands on the binding of a coactivator peptide (SRC1) by the human estrogen receptor alpha ligand binding domain (hERalpha LBD). Nanoelectrospray mass spectrometry (nanoESI-MS) and high-mass matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS) combined with chemical cross-linking were employed to follow these processes. The chemical cross-linking protocol used prior to high-mass MALDI analysis allows detection of intact noncovalent complexes. The binding of intact hERalpha LBD homodimer with two coactivator peptides was detected with nanoESI-MS and high-mass MALDI-MS only in the presence of an agonist ligand. Furthermore, high-mass MALDI-MS revealed an increase of the homodimer abundance after incubating the receptor with a ligand, independent of the ligand character (i.e., agonist, antagonist). The binding characteristics of the compounds tested by MS correlate very well with their biological activity reported by cell-based assays. High-mass MALDI appears to be an efficient and simple tool for directly monitoring ligand regulation mechanisms involved in protein-protein interactions. Furthermore, the combination of both MS methods allows identifying and characterizing endocrine-disrupting compounds or new drug compounds in an efficient way.     

Influence of hysteresis on the transient hygrothermal response of a hemp concrete wall

Building envelopes with bio-materials like hemp concrete are currently undergoing an increasing development due to their low environmental impact and their interesting hygrothermal properties. This kind of hygroscopic material is characterized by a hysteretic behaviour. In this paper, the influence of such behaviour on the hygrothermal response of a building wall is discussed. An experimental facility is designed to measure temperature and relative humidity within a hemp concrete wall submitted to climatic variations. This facility provides a set of experimental data suited for benchmarking. Numerical simulations are performed with a hysteresis model implemented in a heat and moisture transfer model. Comparisons between numerical and experimental results show that hysteresis modelling is relevant to simulate the hygrothermal response of the wall. The discussion is extended to the influence of the initial moisture content.     

In Silico Logical Modelling to Uncover Cooperative Interactions in Cancer

The multistep development of cancer involves the cooperation between multiple molecular lesions, as well as complex interactions between cancer cells and the surrounding tumour microenvironment. The search for these synergistic interactions using experimental models made tremendous contributions to our understanding of oncogenesis. Yet, these approaches remain labour-intensive and challenging. To tackle such a hurdle, an integrative, multidisciplinary effort is required. In this article, we highlight the use of logical computational models, combined with experimental validations, as an effective approach to identify cooperative mechanisms and therapeutic strategies in the context of cancer biology. In silico models overcome limitations of reductionist approaches by capturing tumour complexity and by generating powerful testable hypotheses. We review representative examples of logical models reported in the literature and their validation. We then provide further analyses of our logical model of Epithelium to Mesenchymal Transition (EMT), searching for additional cooperative interactions involving inputs from the tumour microenvironment and gain of function mutations in NOTCH.     

Dynamic and scalable multi-level trust management model for Social Internet of Things

The Internet of Things (IoT) is a paradigm that has made everyday objects intelligent by offering them the ability to connect to the Internet and communicate. Integrating the social component into IoT gave rise to the Social Internet of Things (SIoT), which has helped overcome various issues such as heterogeneity and navigability. In this kind of environment, participants compete to offer a variety of attractive services. Nevertheless, some of them resort to malicious behaviour to spread poor-quality services. They perform so-called Trust-Attacks and break the basic functionality of the system. Trust management mechanisms aim to counter these attacks and provide the user with an estimate of the trust degree they can place in other users, thus ensuring reliable and qualified exchanges and interactions. Several works in literature have interfered with this problem and have proposed different Trust-Models. The majority tried to adapt and reapply Trust-Models designed for common social networks or peer-to-peer ones. That is, despite the similarities between these types of networks, SIoT ones present specific peculiarities. In SIoT, users, devices and services are collaborating. Devices entities can present constrained computing and storage capabilities, and their number can reach some millions. The resulting network is complex, constrained and highly dynamic, and the attacks-implications can be more significant. In this paper, we propose DSL-STM a new dynamic and scalable multi-level Trust-Model, specifically designed for SIoT environments. We propose multidimensional metrics to describe and SIoT entities behaviours. The latter are aggregated via a Machine Learning-based method, allowing classifying users, detecting attack types and countering them. Finally, a hybrid propagation method is suggested to spread trust values in the network, while minimizing resource consumption and preserving scalability and dynamism. Experimentation made on various simulated scenarios allows us to prove the resilience and performance of DSL-STM.

     

Correlated changes in skeletal muscle connective tissue and flesh texture during starvation and re‐feeding in brown trout (Salmo trutta) reared in seawater

Quantitative and qualitative changes to muscle and collagen were analysed following starvation and re‐feeding of brown trout (Salmo trutta) reared in seawater. Fish were submitted to starvation for 2 months followed by re‐feeding for 1 month and compared with a control group continuously fed. Classical effects of starvation on growth and morphometrics traits were observed with only a partial recovery of these parameters after 1 month of re‐feeding. Muscle composition of starved fish was significantly affected (lower dry matter content and higher post‐mortem pH) compared with control fish and was partially recovered in re‐fed fish compared with continuously fed fish. Muscle structure and composition were affected with thinner muscle fibre and higher connective tissue content for the starved fish but similar thickness of myosepta compared with the control group. No difference was observed after 1 month of re‐feeding. Characteristics of the connective tissue were significantly affected by starvation (more high weight molecular collagen form, higher thermal stability of skin collagen). These differences remained significant after the re‐feeding period. Starved fish showed also higher mechanical resistance of the raw flesh compared with the control group, but no difference in rheological measurements was observed after 1 month of re‐feeding. The changes in texture and their relationships with muscle composition, muscle structure and collagen characteristics are discussed. Copyright © 2004 Society of Chemical Industry     

SIMULTANEOUS GC/MS ANALYSIS OF POLYCYCLIC AROMATIC HYDROCARBONS AND THEIR NITRATED DERIVATIVES IN ATMOSPHERIC PARTICULATE MATTER FROM WORKPLACES

Abstract

PAH are routinely analyzed using HPLC/FD. This technique is unsuitable for analyzing NPAH. This study aims at developing a reliable method, using GC/MS, and applying this technique to actual samples from small volumes of atmospheric particulate matter from workplaces. Mixtures of PAH and NPAH were separated by GC/MS and detected by electronic impact (EI) or negative ion chemical ionization (NICI). Analyses on twelve actual samples were thus carried out by sampling a small volume of atmosphere (≈0.5 m ³ ) from five different industrial workplaces. Samples displayed wide differences from one industrial workplace to another, and this can be explained by the specific methods applied. The PAH and NPAH concentrations also varied with time in the same industrial workplace. NPAH concentrations were not correlated with PAH concentrations, underscoring the complex chemical mechanisms involved in NPAH formation. PAH and NPAH formation appeared to be dependent on both industrial activities and uncontrolled physicochemical conditions.     

Targeting a polyketide synthase gene for Aspergillus carbonarius quantification and ochratoxin A assessment in grapes using real-time PCR

Aspergillus carbonarius is an ochratoxin producing fungus that has been considered to be responsible of the ochratoxin A (OTA) contamination in grapes and wine. In order to monitor and quantify A. carbonarius, a specific primer pair Ac12RL_OTAF/Ac12RL_OTAR has been designed from the acyltransferase (AT) domain of the polyketide synthase sequence Ac12RL3 to amplify 141 bp PCR product. Among the mycotoxigenic fungi tested, only A. carbonarius gave a positive result. This specific primer pair was also successfully employed in real-time PCR conjugated with SYBR Green I dye for the direct quantification of this fungus in grape samples. A positive correlation (R(2)=0.81) was found between A. carbonarius DNA content and OTA concentration in 72 grape samples, allowing for the estimation of the potential risk from OTA contamination. Consequently, this work offers a quick alternative to conventional methods of OTA quantification and mycological detection and quantification of A. carbonarius in grapes.