Approximate Bayesian Network Formulation for the Rapid Loss Assessment of Real-World Infrastructure Systems

This paper proposes to learn an approximate Bayesian Network (BN) model from Monte-Carlo simulations of an infrastructure system exposed to seismic hazard. Exploiting preliminary physical simulations has the twofold benefit of building a drastically simplified BN and of predicting complex system performance metrics. While the approximate BN cannot yield exact probabilities for predictive analyses, its use in backward analyses based on evidenced variables yields promising results as a decision support tool for post-earthquake rapid response. Only a reduced set of infrastructure components, whose importance is ranked through a random forest algorithm, is selected to predict the performance of the system. Further, owing to the higher importance of evidenced nodes, the ranking method is enhanced with a recursive evidence-driven BN-building algorithm, which iteratively inserts evidenced components into the subset identified by the random forest algorithm. This approach is applied to a French road network, where only 5 to 10 components out of 58 are kept to estimate the distribution of system performance metrics that are based on traffic flow. Sensitivity studies on the number of selected components, the number of off-line simulation runs and the discretization of variables reveal that the reduced BN applied to this specific example generates trustworthy estimates

Variations between foundation-level recordings and free-field earthquake ground motions: numerical study at soft-soil sites

Abstract It is typically assumed that accelerograms obtained from ground motion recording instruments adequately installed inside a building can be considered as representative of free-field conditions if the structure is less than 2-3 storeys high and does not feature a basement or a massive foundation system. In this work, such an assumption is verified through nonlinear soil-block finite element analyses, considering the induced seismicity Groningen gas field as a case-study and both types of structures. The capability of the numerical model in adequately reproducing nonlinear soil response and capturing interaction between soil and structure is first verified through a number of analyses and cross-checks. Considering soil profiles at the locations of different recording stations in the Groningen field, together with accelerograms from recent events in the region, the results obtained with the numerical model confirm that recordings from instruments located at the base of lightweight structures are not affected by Soil-Structure Interaction (SSI) effects, neither kinematic nor inertial. Heavy structures with a basement, however, do exhibit recordings with variations with respect to the free-field; these are identified and possible corrections to the recordings are analysed. Another set of analyses then demonstrates that soil consolidation prior to the construction of lightweight structures resting on shallow foundations may instead lead to foundation-level recordings that feature high-frequency ground motion amplitudes slightly lower than their free-field counterparts. Additional simplified analyses show the dependency of the recordings on inertial SSI effects due to deformability of the ground supporting the structure

Age and Gender Affect the Composition of Fungal Population of the Human Gastrointestinal Tract

The fungal component of the human gut microbiota has been neglected for long time due to the low relative abundance of fungi with respect to bacteria, and only recently few reports have explored its composition and dynamics in health or disease. The application of metagenomics methods to the full understanding of fungal communities is currently limited by the under representation of fungal DNA with respect to the bacterial one, as well as by the limited ability to discriminate passengers from colonizers. Here we investigated the gut mycobiota of a cohort of healthy subjects in order to reduce the gap of knowledge concerning fungal intestinal communities in the healthy status further screening for phenotypical traits that could reflect fungi adaptation to the host. We studied the fecal fungal populations of 111 healthy subjects by means of cultivation on fungal selective media and by amplicon-based ITS1 metagenomics analysis on a subset of 57 individuals. We then characterized the isolated fungi for their tolerance to gastrointestinal tract-like challenges and their susceptibility to antifungals. A total of 34 different fungal species were isolated showing several phenotypic characteristics associated with intestinal environment such as tolerance to body temperature (37°C), to acidic and oxidative stress and to bile salts exposure. We found a high frequency of azoles resistance in fungal isolates, with potential and significant clinical impact. Analyses of fungal communities revealed that the human gut mycobiota differs in function of individuals’ life stage in a gender-related fashion. The combination of metagenomics and fungal cultivation allowed an in-depth understanding of the fungal intestinal community structure associated to the healthy status and the commensalism-related traits of isolated fungi. We further discussed comparatively the results of sequencing and cultivation to critically evaluate the application of metagenomics-based approaches to fungal gut populations

IL-13 mRNA tissue content identifies two subsets of adult ulcerative colitis patients with different clinical and mucosa-associated microbiota profiles

BACKGROUND AND AIM: A personalized approach to therapy has great promise to improve disease outcomes. To this end, the identification of different subsets of patients according with the prevalent pathogenic process might guide in the choice of therapeutic strategy. We hypothesize that UC patients might be stratified according to distinctive cytokine profiles and/or to a specific mucosa-associated microbiota. METHODS: In a cohort of clinically and endoscopic active UC patients and controls, we analyzed by qPCR the mucosal cytokine mRNA content and the mucosa-associated microbiota composition assessed by the 16SrRNA gene sequencing. RESULTS: We demonstrate, by means of data-driven approach, the existence of a specific UC patient subgroup characterized by elevated IL-13mRNA tissue content separated by patients with low IL-13 mRNA tissue content. The two subsets differ in clinical-pathological characteristics. High IL-13mRNA patients are younger at diagnosis and show higher prevalence of extensive colitis than low IL-13mRNA ones. They also show a more frequent use of steroid/immunosuppressant/anti-TNFα therapy during a one-year follow-up. The two subgroups show a differential enrichment of mucosa associated microbiota genera with prevalence of Prevotella in patients with high IL-13mRNA tissue content and Sutterella and Acidaminococcus in patients with low IL-13mRNA tissue content. CONCLUSION: Assessment of mucosal IL-13mRNA might help in the identification of the patients' subgroup that might benefit from a therapeutic approach modulating IL-13

an application of damage detection methods to a real world structure subjected to ground motion excitation

This paper aims at investigating the efficacy of different state-of-art damage detection methods when applied to real world structures subjected to ground motion excitations, for which the literature contributions are, at present, still not fully comprehensive. To this purpose the paper analyses two test structures: (1) a four-story scaled steel frame tested on a shake table in a controlled laboratory conditions, and (2) a seven-story reinforced concrete building monitored during the seismic excitations of the 1999 Chi-Chi (Taiwan) Earthquake main shock and numerous fore and aftershocks. Some model based damage approaches and statistics based damage indexes are reviewed. The different methodologies and indexes are, then, applied to the two test structures with the final aim of analysing their performance and validity within the case of a laboratory scaled model and a real world structure subjected to input ground motion

Gut microbiota profiles and characterization of cultivable fungal isolates in IBS patients

Studies so far conducted on irritable bowel syndrome (IBS) have been focused mainly on the role of gut bacterial dysbiosis in modulating the intestinal permeability, inflammation, and motility, with consequences on the quality of life. Limited evidences showed a potential involvement of gut fungal communities. Here, the gut bacterial and fungal microbiota of a cohort of IBS patients have been characterized and compared with that of healthy subjects (HS). The IBS microbial community structure differed significantly compared to HS. In particular, we observed an enrichment of bacterial taxa involved in gut inflammation, such as Enterobacteriaceae, Streptococcus, Fusobacteria, Gemella, and Rothia, as well as depletion of health-promoting bacterial genera, such as Roseburia and Faecalibacterium. Gut microbial profiles in IBS patients differed also in accordance with constipation. Sequence analysis of the gut mycobiota showed enrichment of Saccharomycetes in IBS. Culturomics analysis of fungal isolates from feces showed enrichment of Candida spp. displaying from IBS a clonal expansion and a distinct genotypic profiles and different phenotypical features when compared to HS of Candida albicans isolates. Alongside the well-characterized gut bacterial dysbiosis in IBS, this study shed light on a yet poorly explored fungal component of the intestinal ecosystem, the gut mycobiota. Our results showed a differential fungal community in IBS compared to HS, suggesting potential for new insights on the involvement of the gut mycobiota in IBS. KEY POINTS: Comparison of gut microbiota and mycobiota between IBS and healthy subjects Investigation of cultivable fungi in IBS and healthy subjects Candida albicans isolates result more virulent in IBS subjects compared to healthy subjects

Dissecting the intracellular signalling and fate of a DNA nanosensor by super-resolution and quantitative microscopy

DNA nanodevices have been developed as platforms for the manipulation of gene expression, delivery of molecular payloads, and detection of various molecular targets within cells and in other complex biological settings. Despite efforts to translate DNA nanodevices from the test tube (in vitro) to living cells, their intracellular trafficking and functionality remain poorly understood. Herein, quantitative and super-resolution microscopy approaches were employed to track and visualise, with nanometric resolution, the molecular interactions between a synthetic DNA nanosensor and transcription factors in intracellular compartments. Specifically, fluorescence resonance energy transfer microscopy, fluorescence correlation spectroscopy, fluorescence lifetime imaging microscopy and multicolour single-molecule localisation microscopy were employed to probe the specific binding of the DNA nanosensor to the nuclear factor kappa-light-chain-enhancer of activated B cells (NF-kappa B). We monitored the mobility, subcellular localisation and degradation of the DNA nanosensor inside living prostate cancer PC3 cells. Super-resolution imaging enabled the direct visualisation of the molecular interactions between the synthetic DNA nanosensors and the NF-kappa B molecules in cells. This study represents a significant advance in the effective detection as well as understanding of the intracellular dynamics of DNA nanosensors in a complex biological milieu