Distorted Copulas: Constructions and Tail Dependence

Given a copula C, we examine under which conditions on an order isomorphism ψ of [0, 1] the distortion C ψ: [0, 1]2 → [0, 1], C ψ(x, y) = ψ{C[ψ−1(x), ψ−1(y)]} is again a copula. In particular, when the copula C is totally positive of order 2, we give a sufficient condition on ψ that ensures that any distortion of C by means of ψ is again a copula. The presented results allow us to introduce in a more flexible way families of copulas exhibiting different behavior in the tails

Modelling stochastic bivariate mortality

Stochastic mortality, i.e. modelling death arrival via a jump process with stochastic intensity, is gaining increasing reputation as a way to represent mortality risk. This paper represents a first attempt to model the mortality risk of couples of individuals, according to the stochastic intensity approach. On the theoretical side, we extend to couples the Cox processes set up, i.e. the idea that mortality is driven by a jump process whose intensity is itself a stochastic process, proper of a particular generation within each gender. Dependence between the survival times of the members of a couple is captured by an Archimedean copula. On the calibration side, we fit the joint survival function by calibrating separately the (analytical) copula and the (analytical) margins. First, we select the best fit copula according to the methodology of Wang and Wells (2000) for censored data. Then, we provide a sample-based calibration for the intensity, using a time-homogeneous, non mean-reverting, affine process: this gives the analytical marginal survival functions. Coupling the best fit copula with the calibrated margins we obtain, on a sample generation, a joint survival function which incorporates the stochastic nature of mortality improvements and is far from representing independency.On the contrary, since the best fit copula turns out to be a Nelsen one, dependency is increasing with age and long-term dependence exists

Short- and Long-Term Biomarkers for Bacterial Robustness: A Framework for Quantifying Correlations between Cellular Indicators and Adaptive Behavior

The ability of microorganisms to adapt to changing environments challenges the prediction of their history-dependent behavior. Cellular biomarkers that are quantitatively correlated to stress adaptive behavior will facilitate our ability to predict the impact of these adaptive traits. Here, we present a framework for identifying cellular biomarkers for mild stress induced enhanced microbial robustness towards lethal stresses. Several candidate-biomarkers were selected by comparing the genome-wide transcriptome profiles of our model-organism Bacillus cereus upon exposure to four mild stress conditions (mild heat, acid, salt and oxidative stress). These candidate-biomarkers—a transcriptional regulator (activating general stress responses), enzymes (removing reactive oxygen species), and chaperones and proteases (maintaining protein quality)—were quantitatively determined at transcript, protein and/or activity level upon exposure to mild heat, acid, salt and oxidative stress for various time intervals. Both unstressed and mild stress treated cells were also exposed to lethal stress conditions (severe heat, acid and oxidative stress) to quantify the robustness advantage provided by mild stress pretreatment. To evaluate whether the candidate-biomarkers could predict the robustness enhancement towards lethal stress elicited by mild stress pretreatment, the biomarker responses upon mild stress treatment were correlated to mild stress induced robustness towards lethal stress. Both short- and long-term biomarkers could be identified of which their induction levels were correlated to mild stress induced enhanced robustness towards lethal heat, acid and/or oxidative stress, respectively, and are therefore predictive cellular indicators for mild stress induced enhanced robustness. The identified biomarkers are among the most consistently induced cellular components in stress responses and ubiquitous in biology, supporting extrapolation to other microorganisms than B. cereus. Our quantitative, systematic approach provides a framework to search for these biomarkers and to evaluate their predictive quality in order to select promising biomarkers that can serve to early detect and predict adaptive traits

The Complete Genome Sequence of ‘Candidatus Liberibacter solanacearum’, the Bacterium Associated with Potato Zebra Chip Disease

Zebra Chip (ZC) is an emerging plant disease that causes aboveground decline of potato shoots and generally results in unusable tubers. This disease has led to multi-million dollar losses for growers in the central and western United States over the past decade and impacts the livelihood of potato farmers in Mexico and New Zealand. ZC is associated with ‘Candidatus Liberibacter solanacearum’, a fastidious alpha-proteobacterium that is transmitted by a phloem-feeding psyllid vector, Bactericera cockerelli Sulc. Research on this disease has been hampered by a lack of robust culture methods and paucity of genome sequence information for ‘Ca. L. solanacearum’. Here we present the sequence of the 1.26 Mbp metagenome of ‘Ca. L. solanacearum’, based on DNA isolated from potato psyllids. The coding inventory of the ‘Ca. L. solanacearum’ genome was analyzed and compared to related Rhizobiaceae to better understand ‘Ca. L. solanacearum’ physiology and identify potential targets to develop improved treatment strategies. This analysis revealed a number of unique transporters and pathways, all potentially contributing to ZC pathogenesis. Some of these factors may have been acquired through horizontal gene transfer. Taxonomically, ‘Ca. L. solanacearum’ is related to ‘Ca. L. asiaticus’, a suspected causative agent of citrus huanglongbing, yet many genome rearrangements and several gene gains/losses are evident when comparing these two Liberibacter. species. Relative to ‘Ca. L. asiaticus’, ‘Ca. L. solanacearum’ probably has reduced capacity for nucleic acid modification, increased amino acid and vitamin biosynthesis functionalities, and gained a high-affinity iron transport system characteristic of several pathogenic microbes

Whole Genome Sequencing and Complete Genetic Analysis Reveals Novel Pathways to Glycopeptide Resistance in Staphylococcus aureus

The precise mechanisms leading to the emergence of low-level glycopeptide resistance in Staphylococcus aureus are poorly understood. In this study, we used whole genome deep sequencing to detect differences between two isogenic strains: a parental strain and a stable derivative selected stepwise for survival on 4 µg/ml teicoplanin, but which grows at higher drug concentrations (MIC 8 µg/ml). We uncovered only three single nucleotide changes in the selected strain. Nonsense mutations occurred in stp1, encoding a serine/threonine phosphatase, and in yjbH, encoding a post-transcriptional negative regulator of the redox/thiol stress sensor and global transcriptional regulator, Spx. A missense mutation (G45R) occurred in the histidine kinase sensor of cell wall stress, VraS. Using genetic methods, all single, pairwise combinations, and a fully reconstructed triple mutant were evaluated for their contribution to low-level glycopeptide resistance. We found a synergistic cooperation between dual phospho-signalling systems and a subtle contribution from YjbH, suggesting the activation of oxidative stress defences via Spx. To our knowledge, this is the first genetic demonstration of multiple sensor and stress pathways contributing simultaneously to glycopeptide resistance development. The multifactorial nature of glycopeptide resistance in this strain suggests a complex reprogramming of cell physiology to survive in the face of drug challenge