Plant-Made Bet v 1 for Molecular Diagnosis

Allergic disease diagnosis is currently experiencing a breakthrough due to the use of allergenic molecules in serum-based assays rather than allergen extracts in skin tests. The former methodology is considered a very innovative technology compared with the latter, since it is characterized by flexibility and adaptability to the patient’s clinical history and to microtechnology, allowing multiplex analysis. Molecular-based analysis requires pure allergens to detect IgE sensitization, and a major goal, to maintain the diagnosis cost-effective, is to limit their production costs. In addition, for the production of recombinant eukaryotic proteins similar to natural ones, plant-based protein production is preferred to bacterial-based systems due to its ability to perform most of the post-translational modifications of eukaryotic molecules. In this framework, Plant Molecular Farming (PMF) may be useful, being a production platform able to produce complex recombinant proteins in short time-frames at low cost. As a proof of concept, PMF has been exploited for the production of Bet v 1a, a major allergen associated with birch (Betula verrucosa) pollen allergy. Bet v 1a has been produced using two different transient expression systems in Nicotiana benthamiana plants, purified and used in a new generation multiplex allergy diagnosis system, the patient-Friendly Allergen nano-BEad Array (FABER). Plant-made Bet v 1a is immunoreactive, binding IgE and inhibiting IgE-binding to the Escherichia coli expressed allergen currently available in the FABER test, thus suggesting an overall similar though non-overlapping immune activity compared with the E. coli expressed form

Improving the analysis of dependable systems by mapping fault trees into Bayesian networks

Bayesian Networks (BN) provide a robust probabilistic method of reasoning under uncertainty. They have been successfully applied in a variety of real-world tasks but they have received little attention in the area of dependability. The present paper is aimed at exploring the capabilities of the BN formalism in the analysis of dependable systems. To this end, the paper compares BN with one of the most popular techniques for dependability analysis of large, safety critical systems, namely Fault Trees (FT). The paper shows that any FT can be directly mapped into a BN and that basic inference techniques on the latter may be used to obtain classical parameters computed from the former (i.e. reliability of the Top Event or of any sub-system, criticality of components, etc). Moreover, by using BN, some additional power can be obtained, both at the modeling and at the analysis level. At the modeling level, several restrictive assumptions implicit in the FT methodology can be removed and various kinds of dependencies among components can be accommodated. At the analysis level, a general diagnostic analysis can be performed. The comparison of the two methodologies is carried out by means of a running example, taken from the literature, that consists of a redundant multiprocessor system. # 2001 Elsevier Science Ltd. All rights reserved. Keywords: Dependable systems; Probabilistic methods; Bayesian networks; Fault tree analysis 1

Improving the analysis of dependable systems by mapping fault trees into Bayesian networks

Bayesian Networks (BN) provide a robust probabilistic method of reasoning under uncertainty. They have been successfully applied in a variety of real-world tasks but they have received little attention in the area of dependability. The present paper is aimed at exploring the capabilities of the BN formalism in the analysis of dependable systems. To this end, the paper compares BN with one of the most popular techniques for dependability analysis of large, safety critical systems, namely Fault Trees (FT). The paper shows that any FT can be directly mapped into a BN and that basic inference techniques on the latter may be used to obtain classical parameters computed from the former (i.e. reliability of the Top Event or of any sub-system, criticality of components, etc). Moreover, by using BN, some additional power can be obtained, both at the modeling and at the analysis level. At the modeling level, several restrictive assumptions implicit in the FT methodology can be removed and various kinds of dependencies among components can be accommodated. At the analysis level, a general diagnostic analysis can be performed. The comparison of the two methodologies is carried out by means of a running example, taken from the literature, that consists of a redundant multiprocessor system

Reliability Analysis of Multi-source Multi-sink Critical Interacting Systems

Traditional reliability studies on probabilistic networks are devoted to evaluate the probability that two nodes or K nodes are connected, assuming that nodes are undifferentiated. In flow networks, however, we need to distinguish between source nodes where the flow is generated and sink nodes where the flow is utilized. Sink nodes may usually be fed by many sources. To this end, we have extended the traditional studies to include multi-source multi-sink networks. A case study is analysed consisting in a portion of an electrical grid controlled by a its SCADA system through a public telecommunication network

Comparing fault trees and bayesian networks for dependability analysis

Bayesian Networks (BN) provide a robust probabilistic method of reasoning under uncertainty. They have been successfully applied in a variety of real-world tasks and their suitability for de- pendability analysis is now considered by several researchers. In the present paper, we aim at dening a formal comparison between BN and one of the most popular technique for dependability analysis: Fault Trees (FT). We will show that any FT can be easily mapped into a BN and that basic inference techniques on the latter may be used to obtain classical parameters computed using the former (i.e. reliability of the Top Event or of any sub-system, criticality of components, etc...). Moreover, we will discuss how, by using BN, some additional power can be obtained, both at the modeling and at the analysis level. In particular, dependency among components and noisy gates can be easily accommodated in the BN framework, together with the possibility of performing general diagnostic analysis. The comparison of the two methodologies is carried on through the analysis of an example that consists of a redundant multiprocessor system, with local and shared memories, local mirrored disks and a single bus

Functional Analysis of a Telecontrol System and Stochastic Measures of its GSM/GPRS Connections

Archives of Transport, Polish Academy of Sciences - Committee of Transpor