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International audience; Maintenance actions constitute critical tasks that ensure the availability of industrial systems and improve their operating safety. However, maintenance faces numerous challenges and is no longer limited to guarantying availability. It has become a strategic concern and abides by imposing quality, safety, and cost requirements. Finding optimal grouping strategies of maintenance activities is an NP-hard problem that is well studied in the literature, and for which various economic models and optimization approaches are proposed. While most models found in literature use heuristics, such as evolutionary algorithms, to locate cost-reducing grouping strategies, context-specific constraints that could arise within each system are not taken into consideration. For large complex systems, heuristic approaches cannot guarantee the convergence to a feasible solution. Therefore, we propose a new scalable and adaptive optimization algorithm based on a clustering approach to group maintenance activities in multi-component complex systems. The proposed Constrained Clustering-based approach takes into consideration domain-dependant constraints and provides grouping strategies in negligible times.

ESREL 2020 - PSAM 15 - 30th European Safety and Reliability Conference and the 15th Probabilistic Safety Assessment and Management Conference, VENISE, ITALIE, 01-/11/2020 - 05/11/2020; The quality of the road infrastructure plays a major role in the road safety, especially for the autonomous vehicles (AV). The AV contains cameras and lidars able to detect the road markings, obstacles and the other vehicles. The road markings help the AV to identify the path runway and to understand their localization. Thus, the AV must interact with the road infrastructure to drive around without any human interactions with a high automatization level. The failures of the components of the road infrastructure (pavement and road markings) are incompatible phenomena with the operation of AV. To ensure a good evolution of this kind of vehicles, the infrastructure and the vehicles must coordinate, each providing a certain level of service. Thus, an efficient road maintenance must be considered. The proposed paper suggests a maintenance policy for the road infrastructure by grouping the maintenance strategies of the road markings and the pavement. This strategy considers the road infrastructure as serial system. A genetic algorithm is used to group the maintenance activities. This methodology is applied to feedback datasets from both the French National Road 4 and the American pavement using the Long-Term Pavement Performance (LTPP) database.

Clostridium difficile must form a spore to survive outside the gastrointestinal tract. The factors that trigger sporulation in C. difficile remain poorly understood. Previous studies have suggested that a link exists between nutritional status and sporulation initiation in C. difficile . In this study, we investigated the impact of the global nutritional regulator CodY on sporulation in C. difficile strains from the historical 012 ribotype and the current epidemic 027 ribotype. Sporulation frequencies were increased in both backgrounds, demonstrating that CodY represses sporulation in C. difficile . The 027 codY mutant exhibited a greater increase in spore formation than the 012 codY mutant. To determine the role of CodY in the observed sporulation phenotypes, we examined several factors that are known to influence sporulation in C. difficile . Using transcriptional reporter fusions and quantitative reverse transcription-PCR (qRT-PCR) analysis, we found that two loci associated with the initiation of sporulation, opp and sinR , are regulated by CodY. The data demonstrate that CodY is a repressor of sporulation in C. difficile and that the impact of CodY on sporulation and expression of specific genes is significantly influenced by the strain background. These results suggest that the variability of CodY-dependent regulation is an important contributor to virulence and sporulation in current epidemic isolates. This report provides further evidence that nutritional state, virulence, and sporulation are linked in C. difficile . IMPORTANCE This study sought to examine the relationship between nutrition and sporulation in C. difficile by examining the global nutritional regulator CodY. CodY is a known virulence and nutritional regulator of C. difficile , but its role in sporulation was unknown. Here, we demonstrate that CodY is a negative regulator of sporulation in two different ribotypes of C. difficile . We also demonstrate that CodY regulates known effectors of sporulation, Opp and SinR. These results support the idea that nutrient limitation is a trigger for sporulation in C. difficile and that the response to nutrient limitation is coordinated by CodY. Additionally, we demonstrate that CodY has an altered role in sporulation regulation for some strains.

ESREL 2019 - 29th European Safety and Reliability Conference, Hanovre, ALLEMAGNE, 22-/09/2019 - 26/09/2019; The quality and reliability of road infrastructure and its equipment play a major role in road safety. This is especially true if we are interested in autonomous vehicle traffic. Markings line are detected by camera. This option needs an accurate maintenance strategy. In that way, their retroreflection luminance is measured for evaluating their degradation. A line is replaced according to the yearly inspection. The consensus strategy is to define a degradation models of markings based on a regression method. Such models provide a prediction of failure occurrences and a preventive replacement is engaged before this instant. This paper proposes alternatively a systematic age-based replacement by strategic areas. In previous study, an Agglomerative Hierarchical Clustering identifies markings with the same degradation model. The feedback database is strongly censored because the exact failure time isn't observed. To deal with this drawback, an WEM Algoritm was proposed to determine a Weibull model. For each strategic area, a cost function can therefore be defined according to both maintenance costs and the associated Weibull model. The optimum replacement period was finally defined as the minimum point of the cost function. The French National Road 4 (NR4) brocken centerline illustrates this approach. Segmented into five clusters, each one admits its own optimum replacement step. The proposed replacement strategy is generic its application is not limited to our case study.

ESREL 2019, 29th European Safety and Reliability Conference,; Road markings channel traffic flows and guide road users visually, especially at night. Their quality and reliability are, therefore, important issues which must be closely followed to ensure the safety of road users and especially their perceptibility for the future autonomous cars. Thus, previous study has shown that it is possible to segment markings of the center line into maintenance strategic areas. However, this study didn't take into account all the characteristics of road infrastructures that could have an impact on the degradation of markings. Indeed, depending on the structure and complexity of all road infrastructures, these road markings could present a different degradation process over the time and in specific areas. So, the identification of these areas can help road managers to develop localized maintenance strategies. In this study, a Factor Analysis of Mixed Data (FAMD) combined with an Agglomerative Hierarchical Clustering (AHC) is proposed as the method to identify these areas or clusters in the case of the French National Road 4 (NR4).

The quality and reliability of road infrastructure and its equipment play a major role in road safety. This is especially true for autonomous car traffic guided mainly by a GPS system that is, unfortunately, neither precise nor reliable. In order to improve the guidance systems, one option could be to equip the vehicle with a camera reading road markings. Such solution requires maintenance strategies guaranteeing markings' perceptibility to the human eye or the autonomous car camera. Currently, the retroreflection luminance of markings is measured for evaluating marking degradation. An important remaining step is a life time analysis depending on the inspection strategy. Since the exact failure time isn't generally observed, feedback database contain many censured data: the left-censure corresponding to a marking failing before the first inspection, the interval censure that corresponds to markings failing between two inspections, and the right-censure corresponding to a marking that never fails. In the literature, a Weibull analysis was proposed to estimate the markings reliable distributions using the Maximum Likelihood through the Newton-Raphson method. Facing with censored data, this approach couldn't be computed without introducing strong bias in the reliability estimation. For generic interval-censored data, Pradhan and Kundu proposed an alternative, based on the EM algorithm. In our study an extension of the EM algorithm processing left and right censures is proposed. Finally, this algorithm is applicable for all kind of observations, whatever the censure nature. After introducing this EM extension, the paper focuses on the fact that computations are simpler than the Newton-Raphson methods and censored-data are directly estimated. The French National Road 4 markings case is considered to illustrate the proposed approach. Moreover, the proposed algorithm being generic, its application is, of course, not limited to our road marking case study.

The increasing incidence and severity of infection by Clostridium difficile have stimulated attempts to develop new antimicrobial therapies. We report here the relative abilities of two antibiotics (metronidazole and vancomycin) in current use for treating C. difficile infection and of a third antimicrobial, surotomycin, to kill C. difficile cells at various stages of development and to inhibit the production of the toxin proteins that are the major virulence factors. The results indicate that none of the drugs affects the viability of spores at 8× MIC or 80× MIC and that all of the drugs kill exponential-phase cells when provided at 8× MIC. In contrast, none of the drugs killed stationary-phase cells or inhibited toxin production when provided at 8× MIC and neither vancomycin nor metronidazole killed stationary-phase cells when provided at 80× MIC. Surotomycin, on the other hand, did kill stationary-phase cells when provided at 80× MIC but did so without inducing lysis.

International audience; Synthesis of the major toxin proteins of the diarrheal pathogen, Clostridium difficile, is dependent on the activity of TcdR, an initiation (sigma) factor of RNA polymerase. The synthesis of TcdR and the activation of toxin gene expression are responsive to multiple components in the bacterium's nutritional environment, such as the presence of certain sugars, amino acids, and fatty acids. This review summarizes current knowledge about the mechanisms responsible for repression of toxin synthesis when glucose or branched-chain amino acids or proline are in excess and the pathways that lead to synthesis of butyrate, an activator of toxin synthesis. The regulatory proteins implicated in these mechanisms also play key roles in modulating bacterial metabolic pathways, suggesting that C. difficile pathogenesis is intimately connected to the bacterium's metabolic state.

The maintenance of road infrastructure is a classic social challenge, especially in the context of a decreasing maintenance budget and the advent of autonomous vehicle traffic. Road markings need an accurate replacement strategy to guarantee that the markings remain perceptible. The retroreflective luminance of markings is currently dynamically quantifiable only by using a retroreflectometer such as the Ecodyn from MLPC. The main objective of this research is to construct a performance-based approach for retroreflective marking replacement adapted to a given road network. This approach involves three main tasks: localize the strategic area based on past inspections, determine an adapted decay model for a given area, and evaluate the economic impact of replacing markings. This paper focuses on the first task. We apply the Agglomerative Hierarchical Clustering (AHC) method to a given dataset to obtain a suitable markings line segmentation. Markings whose retroreflective luminance exhibits similar evolution over time are interpreted to belong to a specific area of the road network. When no follow-up replacement has occurred, a replacement detector deduces the date at which markings were laid from the clusters. The broken center line of the French National Road 4 illustrates the proposed approach; the road is divided into 5 clusters and 34 lifecycles. A study of markings laid in 2008 and replaced in 2012 shows important variations in the decay of the retroreflective luminance as identified by the clustering approach. Even for a single road, an optimal replacement strategy for retroreflective road markings is necessary and is composed of several local maintenance strategies.

Clostridium difficile -associated disease (CDAD) constitutes a large majority of nosocomial diarrhea cases in industrialized nations and is mediated by the effects of two secreted toxins, toxin A (TcdA) and toxin B (TcdB). Patients who develop strong antitoxin antibody responses can clear C. difficile infection and remain disease free. Key toxin-neutralizing epitopes have been found within the carboxy-terminal receptor binding domains (RBDs) of TcdA and TcdB, which has generated interest in developing the RBD as a viable vaccine target. While numerous platforms have been studied, very little data describes the potential of DNA vaccination against CDAD. Therefore, we created highly optimized plasmids encoding the RBDs from TcdA and TcdB in which any putative N -linked glycosylation sites were altered. Mice and nonhuman primates were immunized intramuscularly, followed by in vivo electroporation, and in these animal models, vaccination induced significant levels of both anti-RBD antibodies (blood and stool) and RBD-specific antibody-secreting cells. Further characterization revealed that sera from immunized mice and nonhuman primates could detect RBD protein from transfected cells, as well as neutralize purified toxins in an in vitro cytotoxicity assay. Mice that were immunized with plasmids or given nonhuman-primate sera were protected from a lethal challenge with purified TcdA and/or TcdB. Moreover, immunized mice were significantly protected when challenged with C. difficile spores from homologous (VPI 10463) and heterologous, epidemic (UK1) strains. These data demonstrate the robust immunogenicity and efficacy of a TcdA/B RBD-based DNA vaccine in preclinical models of acute toxin-associated and intragastric, spore-induced colonic disease.

Reliability analysis has become an integral part of system design and operation. This is especially true for systems performing critical tasks, such as mass transportation systems. This explains the numerous advances in the field of reliability modeling. More recently, some studies involving the use of Bayesian networks have been proven relevant to represent complex systems and perform reliability studies. In previous works, a generic methodology was introduced for developing a decision support tool to evaluate complex systems maintenance strategies. This article deals with development of such a decision tool dedicated to the maintenance of Paris metro rails. Indeed, owing to fulfillment of high-performance levels of safety and availability (the latter being especially critical at peak hours), operators need to estimate, hour by hour their ability to prevent or to detect broken rails. To address this problem, a decision support tool was developed, the aim of this article is to evaluate, compare and optimize various operating and maintenance strategies.

Nowadays, railway operation is characterized by increasingly high speed and large transport capacity. Safety is the core issue in railway operation, and as witnessed by accident/incident statistics, railway level crossing (LX) safety is one of the most critical points in railways. In the present paper, the causal reasoning analysis of LX accidents is carried out based on Bayesian risk model. The causal reasoning analysis aims to investigate various influential factors which may cause LX accidents, and quantify the contribution of these factors so as to identify the crucial factors which contribute most to the accidents at LXs. A detailed statistical analysis is firstly carried out based on the accident/incident data. Then, a Bayesian risk model is established according to the causal relationships and statistical results. Based on the Bayesian risk model, the prediction of LX accident can be made through forward inference. Moreover, accident cause identification and influential factor evaluation can be performed through reverse inference. The main outputs of our study allow for providing improvement measures to reduce risk and lessen consequences related to LX accidents.

Clostridium difficile, a proteolytic Gram-positive anaerobe, has emerged as a significant nosocomial pathogen. Stickland fermentation reactions are thought to be important for growth of C. difficile and appear to influence toxin production. In Stickland reactions, pairs of amino acids donate and accept electrons, generating ATP and reducing power in the process. Reduction of the electron acceptors proline and glycine requires the d-proline reductase (PR) and the glycine reductase (GR) enzyme complexes, respectively. Addition of proline in the medium increases the level of PR protein but decreases the level of GR. We report the identification of PrdR, a protein that activates transcription of the PR-encoding genes in the presence of proline and negatively regulates the GR-encoding genes. The results suggest that PrdR is a central metabolism regulator that controls preferential utilization of proline and glycine to produce energy via the Stickland reactions.

Clostridium perfringens is an anaerobic Gram-positive pathogen that causes many human and animal diseases, including food poisoning and gas gangrene. C. perfringens lacks flagella but possesses type IV pili (TFP). We have previously shown that C. perfringens can glide across an agar surface in long filaments composed of individual bacteria attached end to end and that two TFP-associated proteins, PilT and PilC, are needed for this. To discover additional gene products that play a role in gliding, we developed a plasmid-based mariner transposon mutagenesis system that works effectively in C. perfringens. More than 10,000 clones were screened for mutants that lacked the ability to move away from the edge of a colony. Twenty-four mutants (0.24%) were identified that fit the criteria. The genes containing insertions that affected gliding motility fell into nine different categories. One gene, CPE0278, which encodes a homolog of the SagA cell wall-dependent endopeptidase, acquired distinct transposon insertions in two independent mutants. sagA mutants were unable to form filaments due to a complete lack of end-to-end connections essential for gliding motility. Complementation of the sagA mutants with a wild-type copy of the gene restored gliding motility. We constructed an in-frame deletion mutation in the sagA gene and found that this mutant had a phenotype similar to those of the transposon mutants. We hypothesize that the sagA mutant strains are unable to form the molecular complexes which are needed to keep the cells in an end-to-end orientation, leading to separation of daughter cells and the inability to carry out gliding motility.

Fidaxomicin (FDX) is a novel antimicrobial agent with narrow-spectrum and potent bactericidal activity against Clostridium difficile. In recent clinical trials, FDX was superior to vancomycin in preventing recurrences of C. difficile infection. A possible mechanism of reducing recurrence may be through an inhibitory effect on sporulation. The effect of FDX and its major metabolite, OP-1118, on C. difficile growth and sporulation kinetics was compared with that of vancomycin, metronidazole, and rifaximin. Drugs at subminimum inhibitory concentrations (sub-MICs) were added to cells at an early stationary phase of growth; this was followed by collection of cells at various intervals for quantitation of total viable cell and heat-resistant spore counts on taurocholate-containing media. The effect of the drugs at 2–2.5× MIC on the expression of sporulation genes in C. difficile was also compared using quantitative reverse-transcriptase polymerase chain reaction. Both FDX and OP-1118 (1/4× MIC) inhibited sporulation when added to early-stationary-phase cells in C. difficile strains, including the epidemic NAP1/BI/027 strain. In contrast, vancomycin, metronidazole, and rifaximin (at similar sub-MICs) did not inhibit sporulation. The number of spores following treatment with comparator drugs increased to the same level as the no-drug control treatment. Expression of mother cell–specific (spoIIID) and forespore-specific (spoIIR) sporulation genes also was inhibited by FDX and OP-1118 but not significantly by vancomycin. Both FDX and OP-1118 (unlike vancomycin, rifaximin, and metronidazole) effectively inhibited sporulation by C. difficile. The inhibitory effect of FDX on C. difficile sporulation may contribute to its superior performance in sustaining clinical response and reducing recurrences and may also be beneficial in decreasing shedding and transmission of this pathogen.

Reliability analysis is an integral part of system design and operating. Moreover, it can be an input to optimize maintenance policies. Recently, Bayesian Networks (BN) and Dynamic Bayesian Networks (DBN) have been proved relevant to represent complex systems and perform reliability studies. The major drawback of this approach comes from the constraint on the state sojourn times which are necessarily exponentially distributed, as in usual markovian approaches. Therefore, a new formalism was introduced to avoid this constraint: the Graphical Duration Models (GDM). This paper aims to quantify the reliability estimation error due to an exponential approximation when the system follows other kinds of sojourn time's distributions. Finally results obtained by DBN and GDM will be compared.

This article describes a hybrid diagnosis system based on the combined use of sensor data (local information) and structural knowledge (global information). The approach is illustrated on an application that involves the detection of broken rail for railway infrastructure. Recently, there have been a large number of attempts to solve diagnosis problems by mixing low-level and high-level data. The inherent difficulty of combining different levels of data is offset by the benefits that accrue from additional knowledge: prior information can improve the understanding of sensor data. To introduce the application context, the paper describes first the importance of rail diagnosis. The technological solutions for broken rail detection are then listed. Since the used sensor is able to detect other kind of rail defects or singularities, the defect classification phase also involves the problem of distinguishing between real (broken rail) and false defects (rail singularities). With the help of prior information extracted from an infrastructure database, a Bayesian network is designed to infer the probabilities of membership of real or false defect classes on the basis of previous decisions. The performance of the combined use of these probabilities and sensor processing are finally presented. They demonstrate the advantage of the approach based on both a local description of the defect and a description of its environment.

Fidaxomicin (FDX) is a novel antimicrobial agent with narrow-spectrum and potent bactericidal activity against Clostridium difficile. In recent clinical trials, FDX was superior to vancomycin in preventing recurrences of C. difficile infection. A possible mechanism of reducing recurrence may be through an inhibitory effect on sporulation. The effect of FDX and its major metabolite, OP-1118, on C. difficile growth and sporulation kinetics was compared with that of vancomycin, metronidazole, and rifaximin. Drugs at subminimum inhibitory concentrations (sub-MICs) were added to cells at an early stationary phase of growth; this was followed by collection of cells at various intervals for quantitation of total viable cell and heat-resistant spore counts on taurocholate-containing media. The effect of the drugs at 2–2.5× MIC on the expression of sporulation genes in C. difficile was also compared using quantitative reverse-transcriptase polymerase chain reaction. Both FDX and OP-1118 (1/4× MIC) inhibited sporulation when added to early-stationary-phase cells in C. difficile strains, including the epidemic NAP1/BI/027 strain. In contrast, vancomycin, metronidazole, and rifaximin (at similar sub-MICs) did not inhibit sporulation. The number of spores following treatment with comparator drugs increased to the same level as the no-drug control treatment. Expression of mother cell–specifi c( spoIIID) and forespore-specifi c( spoIIR) sporulation genes also was inhibited by FDX and OP-1118 but not significantly by vancomycin. Both FDX and OP-1118 (unlike vancomycin, rifaximin, and metronidazole) effectively inhibited sporulation by C. difficile. The inhibitory effect of FDX on C. difficile sporulation may contribute to its superior performance in sustaining clinical response and reducing recurrences and may also be beneficial in decreasing shedding and transmission of this pathogen.

Clostridium difficile is a Gram-positive, spore forming, anaerobic, intestinal bacterium and is the most common cause of antibiotic-associated colitis. For many years this organism was considered genetically intractable, but in the past 10 years, multiple methods have been developed or adapted for genetic manipulation of C. difficile. This unit describes the molecular techniques used for genetic modification of this organism, including methods for gene disruption, complementation, plasmid introduction and integration, and cross-species conjugations.

Clostridium difficile is a Gram-positive, spore forming, anaerobic, intestinal bacterium and is the most common cause of antibiotic-associated colitis. For many years this organism was considered genetically intractable, but in the past 10 years, multiple methods have been developed or adapted for genetic manipulation of C. difficile. This unit describes the molecular techniques used for genetic modification of this organism, including methods for gene disruption, complementation, plasmid introduction and integration, and cross-species conjugations.

Clostridium difficile-associated disease (CDAD) constitutes a large majority of nosocomial diarrhea cases within industrialized nations and is mediated by the effects of two secreted toxins, toxin A (TcdA) and toxin B (TcdB). Key toxin-neutralizing epitopes have been discovered within the carboxy-terminal receptor-binding domain (RBD) of the toxins, which has generated interest in developing the RBD as a vaccine target. While numerous platforms have been studied, very few data describe the potential of DNA vaccination against CDAD. Therefore, we created highly optimized plasmids encoding the RBD from TcdA and TcdB and immunized C57BL/6 mice and rhesus macaques intramuscularly followed by in vivo electroporation. In these animal models, vaccination induced significant levels of anti-RBD antibodies within the serum and feces that could neutralize toxins in an in vitro cytotoxicity assay. Moreover, mice that were either immunized with plasmids or given non-human primate immune sera were protected from a lethal intraperitoneal challenge of purified C. difficile toxins. Finally, immunized mice were significantly protected when challenged with strains of C. difficile spores that were homologous (VPI 10463; n=10/10) and heterologous (UK1; n=4/8) to our vaccine antigens. These data demonstrate the robust immunogenicity and efficacy of a TcdA/B RBD-based DNA vaccine in preclinical models of acute toxin-associated disease.

Hidden Markov Random Fields (HMRF) are widely used in solving various problems. Image segmentation is an example of such HMRF success. This paper presents a post-processing tool based on such a model and designed to increase the relevancy of a diagnosis system for rail defects detection. In this application, the hidden Markov field is not only used to define a spatial smoothness prior as it is often done in image segmentation, but it is used to learn the spatial interaction between track singular points, and so the track label patterns. For this, an approach based on a semi-parametric model is presented.