Control Strategies for Endemic Childhood Scabies

Human scabies is a major global public health issue, with an estimated 300 million cases per year worldwide. Prevalence rates are particularly high in many third-world regions and within various indigenous communities in developed countries. Infestation with Sarcoptes Scabiei is associated with group-A streptococcal pyoderma which in turn predisposes to rheumatic fever, acute glomerulonephritis and their respective long-term sequelae: rheumatic heart disease and chronic renal insufficiency. The documented difficulties inherent in achieving scabies control within affected communities have motivated us to develop a network-dependent Monte-Carlo model of the scabies contagion, with the dual aims of gaining insight into its dynamics, and in determining the effects of various treatment strategies. Here we show that scabies burden is adversely affected by increases in average network degree, prominent network clustering, and by a person-to-person transmissibility of greater magnitude. We demonstrate that creating a community-specific model allows for the determination of an effective treatment protocol that can satisfy any pre-defined target prevalence. We find frequent low-density treatment protocols are inherently advantageous in comparison with infrequent mass screening and treatment regimes: prevalence rates are lower when compared with protocols that administer the same number of treatments over a given time interval less frequently, and frequent low-density treatment protocols have economic, practical and public acceptance advantages that may facilitate their long-term implementation. This work demonstrates the importance of stochasticity, community structure and the heterogeneity of individuals in influencing the dynamics of the human scabies contagion, and provides a practical method for investigating the outcomes of various intervention strategies

Spatial distribution of land type in regression models of pollutant loading

This paper proposes a method to improve landscape-pollution interaction regression models through the inclusion of a variable that describes the spatial distribution of a land type with respect to the pattern of runoff within a drainage catchment. The proposed index is used as an independent variable to enhance the strength, as quantified by R² values, of regression relationships between empirical observations of in-stream pollutant concentrations and land type by considering the spatial distribution of key land-type categories within the sample point’s drainage area. We present an index that adds a new dimension of explanatory power when used in conjunction with a variable describing the proportion of the land type. We demonstrate the usefulness of this index by exploring the relationship between nitrate ( - 3 NO ) and land type within 40 drainage sub-catchments in the Ipswich River watershed, Massachusetts. Nutrient loads associated with non-point source pollution paths are related to land type within the up-stream drainage catchments of sample sites. Past studies have focused on the quantity of particular land type within a sample point’s drainage catchment. Quantifying the spatial distribution of key land-type categories in terms of location on a runoff surface can improve our understanding of the relationship between sampled - 3 NO concentrations and land type. Regressions that employ the proportion of residential and agricultural land type within catchments provide a fair fit (R² = 0.67). However, we find that a regression adding a variable that indicates the spatial distribution of residential land improves the overall relationship between instream - 3 NO measurements and associated land types (R² = 0.712). We test the sensitivity of the results with respect to variations in the surface definition in order to determine the conditions under which the spatial index variable is useful

An upper mass limit for the progenitor of the TypeII-P supernova SN1999gi

Masses and progenitor evolutionary states of TypeII supernovae remain almost unconstrained by direct observations. Only one robust observation of a progenitor (SN1987A) and one plausible observation (SN1993J) are available. Neither matched theoretical predictions and in this Letter we report limits on a third progenitor (SN1999gi). The Hubble Space Telescope has imaged the site of the TypeII-P supernova SN1999gi with the WFPC2 in two filters (F606W and F300W) prior to explosion. The distance to the host galaxy (NGC3184) of 7.9Mpc means that the most luminous, massive stars are resolved as single objects in the archive images. The supernova occurred in a resolved, young OB association 2.3kpc from the centre of NGC3184 with an association age of about 4Myrs. Follow-up images of SN1999gi with WFPC2 taken 14 months after discovery determine the precise position of the SN on the pre-explosion frames. An upper limit of the absolute magnitude of the progenitor is estimated (M_v >= -5.1). By comparison with stellar evolutionary tracks this can be interpreted as a stellar mass, and we determine an upper mass limit of 9(+3/-2)M_solar. We discuss the possibility of determining the masses or mass limits for numerous nearby core-collapse supernovae using the HST archive enhanced by our current SNAP programme.Comment: To appear in ApJ Letters, 16 pages, 3 figure

SBSI:an extensible distributed software infrastructure for parameter estimation in systems biology

Complex computational experiments in Systems Biology, such as fitting model parameters to experimental data, can be challenging to perform. Not only do they frequently require a high level of computational power, but the software needed to run the experiment needs to be usable by scientists with varying levels of computational expertise, and modellers need to be able to obtain up-to-date experimental data resources easily. We have developed a software suite, the Systems Biology Software Infrastructure (SBSI), to facilitate the parameter-fitting process. SBSI is a modular software suite composed of three major components: SBSINumerics, a high-performance library containing parallelized algorithms for performing parameter fitting; SBSIDispatcher, a middleware application to track experiments and submit jobs to back-end servers; and SBSIVisual, an extensible client application used to configure optimization experiments and view results. Furthermore, we have created a plugin infrastructure to enable project-specific modules to be easily installed. Plugin developers can take advantage of the existing user-interface and application framework to customize SBSI for their own uses, facilitated by SBSI’s use of standard data formats

Anatomical localization of progenitor cells in human breast tissue reveals enrichment of uncommitted cells within immature lobules

Introduction: Lineage tracing studies in mice have revealed the localization and existence of lineage-restricted mammary epithelial progenitor cells that functionally contribute to expansive growth during puberty and differentiation during pregnancy. However, extensive anatomical differences between mouse and human mammary tissues preclude the direct translation of rodent findings to the human breast. Therefore, here we characterize the mammary progenitor cell hierarchy and identify the anatomic location of progenitor cells within human breast tissues. Methods: Mammary epithelial cells (MECs) were isolated from disease-free reduction mammoplasty tissues and assayed for stem/progenitor activity in vitro and in vivo. MECs were sorted and evaluated for growth on collagen and expression of lineages markers. Breast lobules were microdissected and individually characterized based on lineage markers and steroid receptor expression to identify the anatomic location of progenitor cells. Spanning-tree progression analysis of density-normalized events (SPADE) was used to identify the cellular hierarchy of MECs within lobules from high-dimensional cytometry data. Results: Integrating multiple assays for progenitor activity, we identified the presence of luminal alveolar and basal ductal progenitors. Further, we show that Type I lobules of the human breast were the least mature, demonstrating an unrestricted pattern of expression of luminal and basal lineage markers. Consistent with this, SPADE analysis revealed that immature lobules were enriched for basal progenitor cells, while mature lobules consisted of increased hierarchal complexity of cells within the luminal lineages. Conclusions: These results reveal underlying differences in the human breast epithelial hierarchy and suggest that with increasing glandular maturity, the epithelial hierarchy also becomes more complex. Electronic supplementary material The online version of this article (doi:10.1186/s13058-014-0453-3) contains supplementary material, which is available to authorized users

A mechanochemical model of striae distensae

Striae distensae, otherwise known as stretch marks, are common skin lesions found in a variety of clinical settings. They occur frequently during adolescence or pregnancy where there is rapid tissue expansion and in clinical situations associated with corticosteroid excess. Heralding their onset is the appearance of parallel inflammatory streaks aligned perpendicular to the direction of skin tension. Despite a considerable amount of investigative research, the pathogenesis of striae remains obscure. The interpretation of histologic samples – the major investigative tool – demonstrates an association between dermal lymphocytic inflammation, elastolysis, and a scarring response. Yet the primary causal factor in their aetiology is mechanical; either skin stretching due to underlying tissue expansion or, less frequently, a compromised dermis affected by normal loads. In this paper, we investigate the pathogenesis of striae by addressing the coupling between mechanical forces and dermal pathology. We develop a mathematical model that incorporates the mechanical properties of cutaneous fibroblasts and dermal extracellular matrix. By using linear stability analysis and numerical simulations of our governing nonlinear equations, we show that this quantitative approach may provide a realistic framework that may account for the initiating events

Antibiotic Therapy and the Gut Microbiome:Investigating the Effect of Delivery Route on Gut Pathogens

The contribution of the gut microbiome to human health has long been established, with normal gut microbiota conferring protection against invasive pathogens. Antibiotics can disrupt the microbial balance of the gut, resulting in disease and the development of antimicrobial resistance. The effect of antibiotic administration route on gut dysbiosis remains under-studied to date, with conflicting evidence on the differential effects of oral and parenteral delivery. We have profiled the rat gut microbiome following treatment with commonly prescribed antibiotics (amoxicillin and levofloxacin), via either oral or intravenous administration. Fecal pellets were collected over a 13-day period and bacterial populations were analyzed by 16S rRNA gene sequencing. Significant dysbiosis was observed in all treatment groups, regardless of administration route. More profound dysbiotic effects were observed following amoxicillin treatment than those with levofloxacin, with population richness and diversity significantly reduced, regardless of delivery route. The effect on specific taxonomic groups was assessed, revealing significant disruption following treatment with both antibiotics. Enrichment of a number of groups containing known gut pathogens was observed, in particular, with amoxicillin, such as the family Enterobacteriaceae. Depletion of other commensal groups was also observed. The degree of dysbiosis was significantly reduced toward the end of the sampling period, as bacterial populations began to return to pretreatment composition. Richness and diversity levels appeared to return to pretreatment levels more quickly in intravenous groups, suggesting convenient parenteral delivery systems may have a role to play in reducing longer term gut dysbiosis in the treatment of infection

Non-functional properties in the model-driven development of service-oriented systems

Systems based on the service-oriented architecture (SOA) principles have become an important cornerstone of the development of enterprise-scale software applications. They are characterized by separating functions into distinct software units, called services, which can be published, requested and dynamically combined in the production of business applications. Service-oriented systems (SOSs) promise high flexibility, improved maintainability, and simple re-use of functionality. Achieving these properties requires an understanding not only of the individual artifacts of the system but also their integration. In this context, non-functional aspects play an important role and should be analyzed and modeled as early as possible in the development cycle. In this paper, we discuss modeling of non-functional aspects of service-oriented systems, and the use of these models for analysis and deployment. Our contribution in this paper is threefold. First, we show how services and service compositions may be modeled in UML by using a profile for SOA (UML4SOA) and how non-functional properties of service-oriented systems can be represented using the non-functional extension of UML4SOA (UML4SOA-NFP) and the MARTE profile. This enables modeling of performance, security and reliable messaging. Second, we discuss formal analysis of models which respect this design, in particular we consider performance estimates and reliability analysis using the stochastically timed process algebra PEPA as the underlying analytical engine. Last but not least, our models are the source for the application of deployment mechanisms which comprise model-to-model and model-to-text transformations implemented in the framework VIATRA. All techniques presented in this work are illustrated by a running example from an eUniversity case study