Partially Bayesian active learning cubature for structural reliability analysis with extremely small failure probabilities

The Bayesian failure probability inference (BFPI) framework provides a well-established Bayesian approach to quantifying our epistemic uncertainty about the failure probability resulting from a limited number of performance function evaluations. However, it is still challenging to perform Bayesian active learning of the failure probability by taking advantage of the BFPI framework. In this work, three Bayesian active learning methods are proposed under the name ‘partially Bayesian active learning cubature’ (PBALC), based on a cleaver use of the BFPI framework for structural reliability analysis, especially when small failure probabilities are involved. Since the posterior variance of the failure probability is computationally expensive to evaluate, the underlying idea is to exploit only the posterior mean of the failure probability to design two critical components for Bayesian active learning, i.e., the stopping criterion and the learning function. On this basis, three sets of stopping criteria and learning functions are proposed, resulting in the three proposed methods PBALC1, PBALC2 and PBALC3. Furthermore, the analytically intractable integrals involved in the stopping criteria are properly addressed from a numerical point of view. Five numerical examples are studied to demonstrate the performance of the three proposed methods. It is found empirically that the proposed methods can assess very small failure probabilities and significantly outperform several existing methods in terms of accuracy and efficiency

Operator norm-based determination of failure probability of nonlinear oscillators with fractional derivative elements subject to imprecise stationary Gaussian loads

An approximate analytical technique is developed for bounding the first-passage probability of lightly damped nonlinear and hysteretic oscillators endowed with fractional derivative elements and subjected to imprecise stationary Gaussian loads. In particular, the statistical linearization and stochastic averaging methodologies are integrated with an operator norm-based approach to formulate a numerically efficient proxy for the first-passage probability. This proxy is employed to determine the realizations of the interval-valued parameters of the excitation model that yield the extrema of the failure probability function. Ultimately, each failure probability bound is determined in a fully decoupled manner by solving a standard optimization problem followed by a single evaluation of the first-passage probability. The proposed approximate technique can be construed as an extension of a recently developed operator norm scheme to account for oscillators with fractional derivative elements. In addition, it can readily treat a wide range of nonlinear and hysteretic behaviors. To illustrate the applicability and effectiveness of the proposed technique, a hardening Duffing and a bilinear hysteretic nonlinear oscillators with fractional derivative elements subject to imprecise stationary Gaussian loads are considered as numerical examples

The hypoxia-regulated ectonucleotidase CD73 is a host determinant of HIV latency

Deciphering the mechanisms underlying viral persistence is critical to achieving a cure for human immunodeficiency virus (HIV) infection. Here, we implement a systems approach to discover molecular signatures of HIV latently infected CD4+ T cells, identifying the immunosuppressive, adenosine-producing ectonucleotidase CD73 as a key surface marker of latent cells. Hypoxic conditioning, reflecting the lymphoid tissue microenvironment, increases the frequency of CD73+ CD4+ T cells and promotes HIV latency. Transcriptomic profiles of CD73+ CD4+ T cells favor viral quiescence, immune evasion, and cell survival. CD73+ CD4+ T cells are capable of harboring a functional HIV reservoir and reinitiating productive infection ex vivo. CD73 or adenosine receptor blockade facilitates latent HIV reactivation in vitro, mechanistically linking adenosine signaling to viral quiescence. Finally, tissue imaging of lymph nodes from HIV-infected individuals on antiretroviral therapy reveals spatial association between CD73 expression and HIV persistence in vivo. Our findings warrant development of HIV-cure strategies targeting the hypoxia-CD73-adenosine axis

New Insights into Alleviating Diabetes Mellitus: Role of Gut Microbiota and a Nutrigenomic Approach

The scientific literature has shown that diet is able to modify the gut microbiota and contribute to obesity and diabetes development. This process—characterized by inflammation and gut barrier disruption—can affect the immune system and alter the adipogenesis and insulin resistance. This chapter describes the advances in nutrigenomics and Human Intestinal Microbiota (HIM) modification, and its relation with diabetes mellitus type two (DM2). In context where health and feeding are the main concerns of the human being, food innovation takes a special interest to people that look for a healthy diet or demand a functional aliments, such as nutraceutical. Some products derived from diet and interaction with HIM module the expression of many genes on the host, the so-called epigenome, with favorable effects. Novel functional fiber like low-glycemic oligosaccharides and sweeteners shows a potential prebiotic activity giving a new focus of nutritional guidelines for control and prevention of DM2. The use of prebiotics derived from functional fiber sources, such as fructo-oligosaccharides and beta-glucans as well as lignin and keffir, can contribute to the development of a healthy HIM by promoting the growth of specific bacteria, some of them associated with the prevention of obesity and diabetes

The Microbiome and the Epigenetics of Diabetes Mellitus

Gut microbiota (GM) in the epigenetic mechanisms of diabetes mellitus and the reprogramming of the cells is a novel and emerging concept. The purpose of this chapter is to describe the modification of the GM and its relation with DM2. The increased risk of this disease is associated with changes in the amount of Bacteroides/Clostridium in the Firmicutes/Bacteroidetes ratio of people having DM. A dysbiosis state associated generates low-grade inflammation with similar characteristics that occur under metabolic syndrome, whose pattern is recognized by Toll-like receptor that recognizes important patterns of immunity. The synthesis of butyrate generated by intestinal microorganisms inhibits the metabolic pathway of histone deacetylase, promoting cellular differentiation, proliferation, and insulin resistance. On the other hand, the direct relationship between the neuroendocrine system and the GM has been demonstrated through the production of serotonin by enterochromaffin cells, whose action could influence the etiopathogenic factors of DM2

Quantitative Metabolomics Reveals an Epigenetic Blueprint for Iron Acquisition in Uropathogenic Escherichia coli

Bacterial pathogens are frequently distinguished by the presence of acquired genes associated with iron acquisition. The presence of specific siderophore receptor genes, however, does not reliably predict activity of the complex protein assemblies involved in synthesis and transport of these secondary metabolites. Here, we have developed a novel quantitative metabolomic approach based on stable isotope dilution to compare the complement of siderophores produced by Escherichia coli strains associated with intestinal colonization or urinary tract disease. Because uropathogenic E. coli are believed to reside in the gut microbiome prior to infection, we compared siderophore production between urinary and rectal isolates within individual patients with recurrent UTI. While all strains produced enterobactin, strong preferential expression of the siderophores yersiniabactin and salmochelin was observed among urinary strains. Conventional PCR genotyping of siderophore receptors was often insensitive to these differences. A linearized enterobactin siderophore was also identified as a product of strains with an active salmochelin gene cluster. These findings argue that qualitative and quantitative epi-genetic optimization occurs in the E. coli secondary metabolome among human uropathogens. Because the virulence-associated biosynthetic pathways are distinct from those associated with rectal colonization, these results suggest strategies for virulence-targeted therapies

The anti-bacterial iron-restriction defence mechanisms of egg white; the potential role of three lipocalin-like proteins in resistance against Salmonella

Salmonella enterica serovar Enteritidis (SE) is the most frequently-detected Salmonella in foodborne outbreaks in the European Union. Among such outbreaks, egg and egg products were identified as the most common vehicles of infection. Possibly, the major antibacterial property of egg white is iron restriction, which results from the presence of the iron-binding protein, ovotransferrin. To circumvent iron restriction, SE synthesise catecholate siderophores (i.e. enterobactin and salmochelin) that can chelate iron from host iron-binding proteins. Here, we highlight the role of lipocalin-like proteins found in egg white that could enhance egg-white iron restriction through sequestration of certain siderophores, including enterobactin. Indeed, it is now apparent that the egg-white lipocalin, Ex-FABP, can inhibit bacterial growth via its siderophore-binding capacity in vitro. However, it remains unclear whether ex-FABP performs such a function in egg white or during bird infection. Regarding the two other lipocalins of egg white (Cal-γ and α-1-glycoprotein), there is currently no evidence to indicate that they sequester siderophores

Association of insularity and body condition to cloacal bacteria prevalence in a small shorebird

Do islands harbour less diverse disease communities than mainland? The island biogeography theory predicts more diverse communities on mainland than on islands due to more niches, more diverse habitats and availability of greater range of hosts. We compared bacteria prevalences ofCampylobacter,ChlamydiaandSalmonellain cloacal samples of a small shorebird, the Kentish plover (Charadrius alexandrinus) between two island populations of Macaronesia and two mainland locations in the Iberian Peninsula. Bacteria were found in all populations but, contrary to the expectations, prevalences did not differ between islands and mainland. Females had higher prevalences than males forSalmonellaand when three bacteria genera were pooled together. Bacteria infection was unrelated to bird's body condition but females from mainland were heavier than males and birds from mainland were heavier than those from islands. Abiotic variables consistent throughout breeding sites, like high salinity that is known to inhibit bacteria growth, could explain the lack of differences in the bacteria prevalence between areas. We argue about the possible drivers and implications of sex differences in bacteria prevalence in Kentish plovers

Structural reliability analysis with extremely small failure probabilities: A quasi-Bayesian active learning method

The concept of Bayesian active learning has recently been introduced from machine learning to structural reliability analysis. Although several specific methods have been successfully developed, significant efforts are still needed to fully exploit their potential and to address existing challenges. This work proposes a quasi-Bayesian active learning method, called ‘Quasi-Bayesian Active Learning Cubature’, for structural reliability analysis with extremely small failure probabilities. The method is established based on a cleaver use of the Bayesian failure probability inference framework. To reduce the computational burden associated with the exact posterior variance of the failure probability, we propose a quasi posterior variance instead. Then, two critical elements for Bayesian active learning, namely the stopping criterion and the learning function, are developed subsequently. The stopping criterion is defined based on the quasi posterior coefficient of variation of the failure probability, whose numerical solution scheme is also tailored. The learning function is extracted from the quasi posterior variance, with the introduction of an additional parameter that allows multi-point selection and hence parallel distributed processing. By testing on four numerical examples, it is empirically shown that the proposed method can assess extremely small failure probabilities with desired accuracy and efficiency