Speed of reaction-diffusion fronts in spatially heterogeneous media

The front speed problem for nonuniform reaction rate and diffusion coefficient is studied by using singular perturbation analysis, the geometric approach of Hamilton-Jacobi dynamics, and the local speed approach. Exact and perturbed expressions for the front speed are obtained in the limit of large times. For linear and fractal heterogeneities, the analytic results have been compared with numerical results exhibiting a good agreement. Finally we reach a general expression for the speed of the front in the case of smooth and weak heterogeneities

Cross-species and cross-platform gene expression studies with the Bioconductor-compliant R package 'annotationTools'.

Background: The variety of DNA microarray formats and datasets presently available offers an unprecedented opportunity to perform insightful comparisons of heterogeneous data. Cross-species studies, in particular, have the power of identifying conserved, functionally important molecular processes. Validation of discoveries can now often be performed in readily available public data which frequently requires cross-platform studies.Cross-platform and cross-species analyses require matching probes on different microarray formats. This can be achieved using the information in microarray annotations and additional molecular biology databases, such as orthology databases. Although annotations and other biological information are stored using modern database models ( e. g. relational), they are very often distributed and shared as tables in text files, i.e. flat file databases. This common flat database format thus provides a simple and robust solution to flexibly integrate various sources of information and a basis for the combined analysis of heterogeneous gene expression profiles.Results: We provide annotationTools, a Bioconductor-compliant R package to annotate microarray experiments and integrate heterogeneous gene expression profiles using annotation and other molecular biology information available as flat file databases. First, annotationTools contains a specialized set of functions for mining this widely used database format in a systematic manner. It thus offers a straightforward solution for annotating microarray experiments. Second, building on these basic functions and relying on the combination of information from several databases, it provides tools to easily perform cross-species analyses of gene expression data.Here, we present two example applications of annotationTools that are of direct relevance for the analysis of heterogeneous gene expression profiles, namely a cross-platform mapping of probes and a cross-species mapping of orthologous probes using different orthology databases. We also show how to perform an explorative comparison of disease-related transcriptional changes in human patients and in a genetic mouse model.Conclusion: The R package annotationTools provides a simple solution to handle microarray annotation and orthology tables, as well as other flat molecular biology databases. Thereby, it allows easy integration and analysis of heterogeneous microarray experiments across different technological platforms or species.

Metabolic equivalent: one size does not fit all.

The metabolic equivalent (MET) is a widely used physiological concept that represents a simple procedure for expressing energy cost of physical activities as multiples of resting metabolic rate (RMR). The value equating 1 MET (3.5 ml O2 x kg(-1) x min(-1) or 1 kcal x kg(-1) x h(-1)) was first derived from the resting O2 consumption (VO2) of one person, a 70-kg, 40-yr-old man. Given the extensive use of MET levels to quantify physical activity level or work output, we investigated the adequacy of this scientific convention. Subjects consisted of 642 women and 127 men, 18-74 yr of age, 35-186 kg in weight, who were weight stable and healthy, albeit obese in some cases. RMR was measured by indirect calorimetry using a ventilated hood system, and the energy cost of walking on a treadmill at 5.6 km/h was measured in a subsample of 49 men and 49 women (26-45 kg/m2; 29-47 yr). Average VO2 and energy cost corresponding with rest (2.6 +/- 0.4 ml O2 x kg(-1) x min(-1) and 0.84 +/- 0.16 kcal x kg(-1) x h(-1), respectively) were significantly lower than the commonly accepted 1-MET values of 3.5 ml O2 x kg(-1) x min(-1) and 1 kcal x kg(-1) x h(-1), respectively. Body composition (fat mass and fat-free mass) accounted for 62% of the variance in resting VO2 compared with age, which accounted for only 14%. For a large heterogeneous sample, the 1-MET value of 3.5 ml O2 x kg(-1) x min(-1) overestimates the actual resting VO2 value on average by 35%, and the 1-MET of 1 kcal/h overestimates resting energy expenditure by 20%. Using measured or predicted RMR (ml O2 x kg(-1) x min(-1) or kcal x kg(-1) x h(-1)) as a correction factor can appropriately adjust for individual differences when estimating the energy cost of moderate intensity walking (5.6 km/h).

Seismic attenuation and velocity dispersion in heterogeneous partially saturated porous rocks

Using a numerical approach, we explore wave-induced fluid flow effects in partially saturated porous rocks in which the gas-water saturation patterns are governed by mesoscopic heterogeneities associated with the dry frame properties. The link between the dry frame properties and the gas saturation is defined by the assumption of capillary pressure equilibrium, which in the presence of heterogeneity implies that neighbouring regions can exhibit different levels of saturation. To determine the equivalent attenuation and phase velocity of the synthetic rock samples considered in this study, we apply a numerical upscaling procedure, which permits to take into account mesoscopic heterogeneities associated with the dry frame properties as well as spatially continuous variations of the pore fluid properties. The multiscale nature of the fluid saturation is taken into account by locally computing the physical properties of an effective fluid, which are then used for the larger-scale simulations. We consider two sets of numerical experiments to analyse such effects in heterogeneous partially saturated porous media, where the saturation field is determined by variations in porosity and clay content, respectively. In both cases we also evaluate the seismic responses of corresponding binary, patchy-type saturation patterns. Our results indicate that significant attenuation and modest velocity dispersion effects take place in this kind of media for both binary patchy-type and spatially continuous gas saturation patterns and in particular in the presence of relatively small amounts of gas. The numerical experiments also show that the nature of the gas distribution patterns is a critical parameter controlling the seismic responses of these environments, since attenuation and velocity dispersion effects are much more significant and occur over a broader saturation range for binary patchy-type gas-water distributions. This analysis therefore suggests that the physical mechanisms governing partial saturation should be accounted for when analysing seismic data in a poroelastic framework. In this context, heterogeneities associated with the dry frame properties, which do not play important roles in wave-induced fluid flow processes per se, should be taken into account since they may determine the kind of gas distribution pattern taking place in the porous rock.

Bgee: integrating and comparing heterogeneous transcriptome data among species

Gene expression patterns are a key feature in understanding gene function, notably in development. Comparing gene expression patterns between animals is a major step in the study of gene function as well as of animal evolution. It also provides a link between genes and phenotypes. Thus we have developed Bgee, a database designed to compare expression patterns between animals, by implementing ontologies describing anatomies and developmental stages of species, and then designing homology relationships between anatomies and comparison criteria between developmental stages. To define homology relationships between anatomical features we have developed the software Homolonto, which uses a modified ontology alignment approach to propose homology relationships between ontologies. Bgee then uses these aligned ontologies, onto which heterogeneous expression data types are mapped. These already include microarrays and ESTs.

Predicting cancer involvement of genes from heterogeneous data

Background: Systematic approaches for identifying proteins involved in different types of cancer are needed. Experimental techniques such as microarrays are being used to characterize cancer, but validating their results can be a laborious task. Computational approaches are used to prioritize between genes putatively involved in cancer, usually based on further analyzing experimental data. Results: We implemented a systematic method using the PIANA software that predicts cancer involvement of genes by integrating heterogeneous datasets. Specifically, we produced lists of genes likely to be involved in cancer by relying on: (i) protein-protein interactions; (ii) differential expression data; and (iii) structural and functional properties of cancer genes. The integrative approach that combines multiple sources of data obtained positive predictive values ranging from 23% (on a list of 811 genes) to 73% (on a list of 22 genes), outperforming the use of any of the data sources alone. We analyze a list of 20 cancer gene predictions, finding that most of them have been recently linked to cancer in literature. Conclusion: Our approach to identifying and prioritizing candidate cancer genes can be used to produce lists of genes likely to be involved in cancer. Our results suggest that differential expression studies yielding high numbers of candidate cancer genes can be filtered using protein interaction networks.

@neurIST infrastructure for advanced disease management through integration of heterogeneous data, computing, and complex processing services

The increasing volume of data describing humandisease processes and the growing complexity of understanding, managing, and sharing such data presents a huge challenge for clinicians and medical researchers. This paper presents the@neurIST system, which provides an infrastructure for biomedical research while aiding clinical care, by bringing together heterogeneous data and complex processing and computing services. Although @neurIST targets the investigation and treatment of cerebral aneurysms, the system’s architecture is generic enough that it could be adapted to the treatment of other diseases.Innovations in @neurIST include confining the patient data pertaining to aneurysms inside a single environment that offers cliniciansthe tools to analyze and interpret patient data and make use of knowledge-based guidance in planning their treatment. Medicalresearchers gain access to a critical mass of aneurysm related data due to the system’s ability to federate distributed informationsources. A semantically mediated grid infrastructure ensures that both clinicians and researchers are able to seamlessly access andwork on data that is distributed across multiple sites in a secure way in addition to providing computing resources on demand forperforming computationally intensive simulations for treatment planning and research.

Managing Quality under Heterogeneous Consumer Demand and Product Quality, October 2005

Based on accepted advances in the marketing, economics, consumer behavior, and satisfaction literatures, we develop a micro-foundations model of a firm that needs to manage the quality of a product that is inherently heterogeneous in the presence of varying customer tastes or expectations for quality. Our model blends elements of the returns to quality, customer lifetime value, and service profit chain approaches to marketing. The model is then used to explain several empirical results pertaining to the marketing literature by explicitly articulating the trade-offs between customer satisfaction and costs (including opportunity costs) of quality. In this environment firms will find it optimal to allow some customers to go unsatisfied. We show that the relationship between the expected number of repeated purchases by an individual customer is endogenous to the choice of quality by the firm, indicating that the number of purchases cannot be chosen freely to estimate a customer’s lifetime value.

Simple estimation of incident HIV infection rates in notification cohorts based on window periods of algorithms for evaluation of line-immunoassay result patterns.

BACKGROUND: Tests for recent infections (TRIs) are important for HIV surveillance. We have shown that a patient's antibody pattern in a confirmatory line immunoassay (Inno-Lia) also yields information on time since infection. We have published algorithms which, with a certain sensitivity and specificity, distinguish between incident (< = 12 months) and older infection. In order to use these algorithms like other TRIs, i.e., based on their windows, we now determined their window periods. METHODS: We classified Inno-Lia results of 527 treatment-naïve patients with HIV-1 infection < = 12 months according to incidence by 25 algorithms. The time after which all infections were ruled older, i.e. the algorithm's window, was determined by linear regression of the proportion ruled incident in dependence of time since infection. Window-based incident infection rates (IIR) were determined utilizing the relationship 'Prevalence = Incidence x Duration' in four annual cohorts of HIV-1 notifications. Results were compared to performance-based IIR also derived from Inno-Lia results, but utilizing the relationship 'incident = true incident + false incident' and also to the IIR derived from the BED incidence assay. RESULTS: Window periods varied between 45.8 and 130.1 days and correlated well with the algorithms' diagnostic sensitivity (R(2) = 0.962; P<0.0001). Among the 25 algorithms, the mean window-based IIR among the 748 notifications of 2005/06 was 0.457 compared to 0.453 obtained for performance-based IIR with a model not correcting for selection bias. Evaluation of BED results using a window of 153 days yielded an IIR of 0.669. Window-based IIR and performance-based IIR increased by 22.4% and respectively 30.6% in 2008, while 2009 and 2010 showed a return to baseline for both methods. CONCLUSIONS: IIR estimations by window- and performance-based evaluations of Inno-Lia algorithm results were similar and can be used together to assess IIR changes between annual HIV notification cohorts.

Presence of an oligodendroglioma-like component in newly diagnosed glioblastoma identifies a pathogenetically heterogeneous subgroup and lacks prognostic value: central pathology review of the EORTC_26981/NCIC_CE.3 trial.

Glioblastoma (GBM) is a morphologically heterogeneous tumor type with a median survival of only 15 months in clinical trial populations. However, survival varies greatly among patients. As part of a central pathology review, we addressed the question if patients with GBM displaying distinct morphologic features respond differently to combined chemo-radiotherapy with temozolomide. Morphologic features were systematically recorded for 360 cases with particular focus on the presence of an oligodendroglioma-like component and respective correlations with outcome and relevant molecular markers. GBM with an oligodendroglioma-like component (GBM-O) represented 15% of all confirmed GBM (52/339) and was not associated with a more favorable outcome. GBM-O encompassed a pathogenetically heterogeneous group, significantly enriched for IDH1 mutations (19 vs. 3%, p = 0.003) and EGFR amplifications (71 vs. 48%, p = 0.04) compared with other GBM, while co-deletion of 1p/19q was found in only one case and the MGMT methylation frequency was alike (47 vs. 46%). Expression profiles classified most of the GBM-O into two subtypes, 36% (5/14 evaluable) as proneural and 43% as classical GBM. The detection of pseudo-palisading necrosis (PPN) was associated with benefit from chemotherapy (p = 0.0002), while no such effect was present in the absence of PPN (p = 0.86). In the adjusted interaction model including clinical prognostic factors and MGMT status, PPN was borderline nonsignificant (p = 0.063). Taken together, recognition of an oligodendroglioma-like component in an otherwise classic GBM identifies a pathogenetically mixed group without prognostic significance. However, the presence of PPN may indicate biological features of clinical relevance for further improvement of therapy.

Scalable inference of heterogeneous reaction kinetics from pooled single-cell recordings.

Mathematical methods combined with measurements of single-cell dynamics provide a means to reconstruct intracellular processes that are only partly or indirectly accessible experimentally. To obtain reliable reconstructions, the pooling of measurements from several cells of a clonal population is mandatory. However, cell-to-cell variability originating from diverse sources poses computational challenges for such process reconstruction. We introduce a scalable Bayesian inference framework that properly accounts for population heterogeneity. The method allows inference of inaccessible molecular states and kinetic parameters; computation of Bayes factors for model selection; and dissection of intrinsic, extrinsic and technical noise. We show how additional single-cell readouts such as morphological features can be included in the analysis. We use the method to reconstruct the expression dynamics of a gene under an inducible promoter in yeast from time-lapse microscopy data.

Stoneley wave modeling in heterogeneous porous media with viscous pore fluids

We implemented Biot-type porous wave equations in a pseudo-spectral numerical modeling algorithm for the simulation of Stoneley waves in porous media. Fourier and Chebyshev methods are used to compute the spatial derivatives along the horizontal and vertical directions, respectively. To prevent from overly short time steps due to the small grid spacing at the top and bottom of the model as a consequence of the Chebyshev operator, the mesh is stretched in the vertical direction. As a large benefit, the Chebyshev operator allows for an explicit treatment of interfaces. Boundary conditions can be implemented with a characteristics approach. The characteristic variables are evaluated at zero viscosity. We use this approach to model seismic wave propagation at the interface between a fluid and a porous medium. Each medium is represented by a different mesh and the two meshes are connected through the above described characteristics domain-decomposition method. We show an experiment for sealed pore boundary conditions, where we first compare the numerical solution to an analytical solution. We then show the influence of heterogeneity and viscosity of the pore fluid on the propagation of the Stoneley wave and surface waves in general.

Seismic attenuation in heterogeneous partially saturated rocks

We study wave-induced fluid flow effects in porous rocks partially saturated with gas and water, where the saturation patterns are governed by mesoscopic heterogeneities associated with the dry frame properties. The link between the dry frame properties and the gas saturation is defined by the assumption of capillary pressure equilibrium, which in the presence of heterogeneity implies that neighboring regions can exhibit different levels of saturation. In order to determine the equivalent attenuation and phase velocity of the synthetic rock samples considered in this study, we apply a numerical upscaling procedure, which permits to take into account mesoscopic heterogeneities associated with the dry frame properties as well as spatially continuous variations of the pore fluid properties. We consider numerical experiments to analyze such effects in heterogeneous partially saturated porous media, where the saturation field is determined by realistic variations in porosity. Our results indicate that the spatially continuous nature of gas saturation inherent to this study is a critical parameter controlling the seismic response of these environments, which in turn suggests that the physical mechanisms governing partial saturation should be accounted for when analyzing seismic data in a poro-elastic context.