The study of complex hereditary diseases is a very challenging area of research. The expanding set of in silico approaches offers a flourishing ground for the acceleration of meaningful findings in this area by exploitation of rich and diverse sources of omic data. These approaches are cheap, flexible, extensible, often complementary and can continuously integrate new information and tests to improve the selection of genes responsible for hereditary diseases. Following this principle, we improved and extended our web-service TOM for the identification of candidate genes in the study of complex hereditary diseases.

Glioblastoma multiforme (GBM) is,the most common and lethal primary brain tumor in adults. We combined neuroimaging and DNA microarray analysis to create a multidimensional map of gene-expression patterns in GBM that provided clinically relevant insights into tumor biology. Tumor contrast enhancement and mass effect predicted activation of specific hypoxia and proliferation gene-expression programs, respectively. Overexpression of EGFR, a receptor tyrosine kinase and potential therapeutic target, was also directly inferred by neuroimaging and was validated in an independent set of tumors by immunohistochemistry. Furthermore, imaging provided insights into the intratumoral distribution of gene-expression patterns within GBM. Most notably, an "infiltrative" imaging phenotype was identified that predicted patient outcome. Patients with this imaging phenotype had a greater tendency toward having multiple tumor foci and demonstrated significantly shorter survival than their counterparts. Our findings provide an in vivo portrait of genome-wide gene expression in GBM and offer a potential strategy for noninvasively selecting patients who may be candidates for individualized therapies.

Biotechnology is an area of great innovations that promises to have deep impact on everyday life thanks to profound changes in biology, medicine, and health care. This article will span from the description of the biochemical principles of molecular biology to the definition of the physics that supports the technology and to the devices and algorithms necessary to observe molecular events in a controlled, portable, and highly parallel manner. Throughout this discussion, constant attention will be given to the ultimate goals and applications of these innovations as well as to the related issues.

Il bioventing e' una tecnologia di decontaminazione del sottosuolo. Alcune specie batteriche presenti nel sottosuolo stesso biodegradano l'inquinante - ad esempio un idrocarburo - mediante un processo che richiede ossigeno; quest'ultimo e' fornito per mezzo di iniezione di aria in pozzi praticati nella zona inquinata del sottosuolo. Verra' presentato un modello matematico - basato sulla teoria del moto dei fluidi multifase in mezzi porosi e sulle equazioni della dinamica delle popolazioni - descrivente il fenomeno fisico ed utile per la simulazione numerica. Il problema della progettazione ottimale dell'intervento di bonifica consiste nel determinare numero, posizione e portata dei pozzi di iniezione di aria, al fine di massimizzare la velocita' di biodegradazione.

An account of the error and the convergence theory is given for Gauss-Laguerre and Gauss-Radau-Laguerre quadrature formulae. We develop also truncated models of the original Gauss rules to compute integrals extended over the positive real axis. Numerical examples confirming the theoretical results are given comparing these rules among themselves and with different quadrature formulae proposed by other authors (Evans, Int. J. Comput. Math. 82:721-730, 2005; Gautschi, BIT 31:438-446, 1991).

For host survival, the immune system (IS) is required to deliver high-level, specific and continuous performance, dealing with a very complex universe of stimuli and functions, as well as physical and resource constraints. From this perspective, the immune system needs an effective strategy to assure the requested operational functions, to survive and to evolve. The concept of degeneracy discussed in this chapter, is the ability of some immune receptors to bind many types of ligands and it would appear to be a fundamental characteristic for immune system functioning as well as a formidable weapon in the architecture of complex biological structures and systems. In this chapter, we will discuss how degeneracy acts as a strategy to optimize the necessary trade-off between the inescapable promiscuity of receptors and ligands, with the necessity to produce a specific response, and how the degeneracy principle acts to set up a memory of each immunological event, thus contributing to the fitness of the organism, and how degeneracy can be considered among the underlying causes for the evolution and robustness of the IS.

The search for longevity genes has greatly developed in recent years basing on the idea that a consistent part of longevity is determined by genetics. The ultimate goal of this research is to identify possible genetic determinants of human aging and longevity, but studies on humans are limited by a series of critical restrictions. For this reason, most of the studies in this field have been, and still are, performed on animal models, basing on the assumption that fundamental biological mechanisms are highly conserved throughout evolution and that, accordingly, extrapolation from model systems to humans is quite reasonable. Indeed, many comparative data obtained on single genes or gene families fit with this assumption. However, it is also clear that, despite such a basic conservative scenario, major changes also occurred in evolution, particularly regarding biological regulatory processes and integration between and among pathways. This consideration raises the fundamental question of the transferability of the results obtained from model systems to humans. In this review, we discuss the differences between animal models and men regarding the genetics of aging and longevity, and the possible reasons that can explain such discrepancies, with a particular emphasis on the phenomena of conservation and evolvability of biological systems. Finally we will suggest a possible strategy to identify putative longevity genes basing on their position inside conserved metabolic structures.

We study the numerical approximation of solutions for parabolic integro-differential equations (PIDE). Similar models arise in option pricing, to generalize the Black-Scholes equation, when the processes which generate the underlying stock returns may contain both a continuous part and jumps. Due to the non-local nature of the integral term, unconditionally stable implicit difference schemes are not practically feasible. Here we propose using implicit-explicit (IMEX) Runge-Kutta methods for the time integration to solve the integral term explicitly, giving higher-order accuracy schemes under weak stability time-step restrictions. Numerical tests are presented to show the computational efficiency of the approximation.

The multiyear problem of a two-body system consisting of a Reissner–Nordström black hole and a charged massive particle at rest is here solved by an exact perturbative solution of the full Einstein–Maxwell system of equations. The expressions of the metric and of the electromagnetic field, including the effects of the electromagnetically induced gravitational perturbation and of the gravitationally induced electromagnetic perturbation, are presented in closed analytic formulas.

Can a directed graph be completed to a directed line graph? If possible, how many arcs must be added? In this paper we address the above questions characterizing partial directed line (PDL) graphs, i.e., partial subgraph of directed line graphs. We show that for such class of graphs a forbidden configuration criterion and a Krausz's like theorem are equivalent characterizations. Furthermore, the latter leads to a recognition algorithm that requires worst case time, where m is the number of arcs in the graph. Given a partial line digraph, our characterization allows us to find a minimum completion to a directed line graph within the same time bound. The class of PDL graphs properly contains the class of directed line graphs, characterized in [J. Blazewicz, A. Hertz, D. Kobler, D. de Werra, On some properties of DNA graphs, Discrete Appl. Math. 98(1-2) (1999) 1-19], hence our results generalize those already known for directed line graphs. In the undirected case, we show that finding a minimum line graph edge completion is NP-hard, while the problem of deciding whether or not an undirected graph is a partial graph of a simple line graph is trivial.

A novel method is described that combines high-resolution scanning microdiffraction techniques, Rietveld quantitative phase analysis and a statistical method known as canonical correlation analysis (CCA). The method has been applied to a sample taken from a bone-tissue-engineered bioceramic porous scaffold implanted in a mouse for six months. The CCA technique allows the detection of those pixels throughout the investigated sample that best correlate with signal models. Besides the standard usage of this approach, which requires theoretical profiles as signal models, a novel application is presented here, which consists of picking the model spectra out of the experimental data set. Patterns representative of a reasonable range of phase compositions were selected among the huge number of two-dimensional patterns ( folded in onedimensional profiles) to extract quantitative phase fractions. At this stage, the CCA approach was also used to overcome the low Poisson statistic of signal models, so making Rietveld quantitative analysis more reliable. These patterns have been used as profile models for CCA. The final classification map, obtained by assigning the considered pixel to the model spectrum with the highest canonical coefficient, provides the spatial variation of phase concentration.

Most operational models in atmospheric physics, meteorology and climatology nowadays adopt spherical geodesic grids and require “ad hoc” developed interpolation procedures. The author does a comparison between chosen representatives of linear, distance-based and cubic interpolation schemes outlining their advantages and drawbacks in this specific application field. Numerical experiments on a standard test problem, while confirming a good performance of linear and distance-based schemes in a single interpolation step, also show their minor accuracy with respect to the cubic scheme in the more realistic simulation of advection of a meteorological field.

We present a set of difference equations which represents the discrete counterpart of a large class of continuous model concerning the dynamics of an infection in an organism or in a host population. The limiting behavior of the discrete model is studied and a threshold parameter playing the role of the basic reproduction number is derived.

The annotation of transcription binding sites in new sequenced genomes is an important and challenging problem. We have previously shown how a regression model that linearly relates gene expression levels to the matching scores of nucleotide patterns allows us to identify DNA-binding sites from a collection of co-regulated genes and their nearby non-coding DNA sequences. Our methodology uses Bayesian models and stochastic search techniques to select transcription factor binding site candidates. Here we show that this methodology allows us to identify binding sites in nearby species. We present examples of annotation crossing from Schizosaccharomyces pombe to Schizosaccharomyces japonicus. We found that the eng1 motif is also regulating a set of 9 genes in S. japonicus. Our framework may have an effective interest in conveying information in the annotation process of a new species. Finally we discuss a number of statistical and biological issues related to the identification of binding sites through covariates of genes expression and sequences.

The speciality index function ${\mathcal S}$ for any Petrov type I, II or D spacetime is shown to be a natural function of a single complex scalar quantity $\mu$ (natural modulo permutation symmetries). For the family of Kasner spacetimes, this quantity is a function of the Kasner indices alone which coincides with the real Lifshitz-Khalatnikov parameter $u$ for those indices.

An innovative analytical/computational approach is presented to provide maximum allowed probabilities (MAPs) of conformations in protein domains not rigidly connected. The approach is applied to calmodulin and to its adduct with R-synuclein. Calmodulin is a protein constituted by two rigid domains, each of them composed by two calcium-binding EF-hand motifs, which in solution are largely free to move with respect to one another. We used the N60D mutant of calmodulin, which had been engineered to selectively bind a paramagnetic lanthanide ion to only one of its four calcium binding sites, specifically in the second EF-hand motif of the N-terminal domain. In this way, pseudocontact shifts (pcs’s) and selforientation residual dipolar couplings (rdc’s) measured on the C-terminal domain provide information on its relative mobility with respect to the domain hosting the paramagnetic center. Available NMR data for terbium(III) and thulium(III) calmodulin were supplemented with additional data for dysprosium(III), analogous data were generated for the R-synuclein adduct, and the conformations with the largest MAPs were obtained for both systems. The MAP analysis for calmodulin provides further information on the variety of conformations experienced by the system. Such variety is somewhat reduced in the calmodulin-R-synuclein adduct, which however still retains high flexibility. The flexibility of the calmodulin-R-synuclein adduct is an unexpected result of this research.