Defining critical factors in multi-country studies of assisted reproductive technologies (ART): data from the US and UK health systems

As the worldwide use of assisted reproductive technologies (ART) continues to grow, there is a critical need to assess the safety of these treatment parameters and the potential adverse health effects of their use in adults and their offspring. While key elements remain similar across nations, geographic variations both in treatments and populations make generalizability challenging. We describe and compare the demographic factors between the USA and the UK related to ART use and discuss implications for research. The USA and the UK share some common elements of ART practice and in how data are collected regarding long-term outcomes. However, the monitoring of ART in these two countries each brings strengths that complement each other’s limitations

Intraguild Predation and Native Lady Beetle Decline

Coccinellid communities across North America have experienced significant changes in recent decades, with declines in several native species reported. One potential mechanism for these declines is interference competition via intraguild predation; specifically, increased predation of native coccinellid eggs and larvae following the introduction of exotic coccinellids. Our previous studies have shown that agricultural fields in Michigan support a higher diversity and abundance of exotic coccinellids than similar fields in Iowa, and that the landscape surrounding agricultural fields across the north central U.S. influences the abundance and activity of coccinellid species. The goal of this study was to quantify the amount of egg predation experienced by a native coccinellid within Michigan and Iowa soybean fields and explore the influence of local and large-scale landscape structure. Using the native lady beetle Coleomegilla maculata as a model, we found that sentinel egg masses were subject to intense predation within both Michigan and Iowa soybean fields, with 60.7% of egg masses attacked and 43.0% of available eggs consumed within 48 h. In Michigan, the exotic coccinellids Coccinella septempunctata and Harmonia axyridis were the most abundant predators found in soybean fields whereas in Iowa, native species including C. maculata, Hippodamia parenthesis and the soft-winged flower beetle Collops nigriceps dominated the predator community. Predator abundance was greater in soybean fields within diverse landscapes, yet variation in predator numbers did not influence the intensity of egg predation observed. In contrast, the strongest predictor of native coccinellid egg predation was the composition of edge habitats bordering specific fields. Field sites surrounded by semi-natural habitats including forests, restored prairies, old fields, and pasturelands experienced greater egg predation than fields surrounded by other croplands. This study shows that intraguild predation by both native and exotic predators may contribute to native coccinellid decline, and that landscape structure interacts with local predator communities to shape the specific outcomes of predator-predator interactions

Evaluation of a Bayesian inference network for ligand-based virtual screening

Background Bayesian inference networks enable the computation of the probability that an event will occur. They have been used previously to rank textual documents in order of decreasing relevance to a user-defined query. Here, we modify the approach to enable a Bayesian inference network to be used for chemical similarity searching, where a database is ranked in order of decreasing probability of bioactivity. Results Bayesian inference networks were implemented using two different types of network and four different types of belief function. Experiments with the MDDR and WOMBAT databases show that a Bayesian inference network can be used to provide effective ligand-based screening, especially when the active molecules being sought have a high degree of structural homogeneity; in such cases, the network substantially out-performs a conventional, Tanimoto-based similarity searching system. However, the effectiveness of the network is much less when structurally heterogeneous sets of actives are being sought. Conclusion A Bayesian inference network provides an interesting alternative to existing tools for ligand-based virtual screening

Slow and fast diffusion in a lead sulphate gravity separation process

A model for the growth of lead sulphate particles in a gravity separation system from the crystal glassware industry is presented. The lead sulphate particles are an undesirable byproduct, and thus the model is used to ascertain the optimal system temperature configuration such that particle extraction is maximised. The model describes the evolution of a single, spherical particle due to the mass flux of lead particles from a surrounding acid solution. We divide the concentration field into two separate regions. Specifically, a relatively small boundary layer region around the particle is characterised by fast diffusion, and is thus considered quasistatic. In contrast, diffusion in the far-field is slower, and hence assumed to be time-dependent. The final system consisting of two nonlinear, coupled ordinary differential equations for the particle radius and lead concentration, is integrated numerically

Mathematical and Statistical Techniques for Systems Medicine: The Wnt Signaling Pathway as a Case Study

The last decade has seen an explosion in models that describe phenomena in systems medicine. Such models are especially useful for studying signaling pathways, such as the Wnt pathway. In this chapter we use the Wnt pathway to showcase current mathematical and statistical techniques that enable modelers to gain insight into (models of) gene regulation, and generate testable predictions. We introduce a range of modeling frameworks, but focus on ordinary differential equation (ODE) models since they remain the most widely used approach in systems biology and medicine and continue to offer great potential. We present methods for the analysis of a single model, comprising applications of standard dynamical systems approaches such as nondimensionalization, steady state, asymptotic and sensitivity analysis, and more recent statistical and algebraic approaches to compare models with data. We present parameter estimation and model comparison techniques, focusing on Bayesian analysis and coplanarity via algebraic geometry. Our intention is that this (non exhaustive) review may serve as a useful starting point for the analysis of models in systems medicine.Comment: Submitted to 'Systems Medicine' as a book chapte

Adaptation of the Ambulatory and Home Care Record for collecting palliative care service utilization data from family carers in the UK: a pilot study

Background: Measuring service use and costs is an important aspect of service delivery evaluation. In end-of-life care, there is heavy reliance on care by family/friends (informal carers) and this should be reflected in the total cost of care alongside formal services. The Ambulatory and Home Care Record, developed in Canada, is both comprehensive in coverage and validated for collecting data on formal and informal caring. This study aimed to adapt and pilot the Ambulatory and Home Care Record questionnaire for use in the UK within a study evaluating a new palliative care service. The objectives were to test if family carers could be recruited and assess acceptability and usability of data gathered. Methods: Single cohort pilot study using a structured telephone questionnaire carried out every other week. Family carers of patients newly added to the palliative care register or referred to hospice services in the South East of England were invited to participate by mail. Volunteers remained in the study for a maximum of six interviews or until the patient died. Results: In total, 194 carers were invited by mail to participate in the study, of which 23 (11.8%) completed at least one interview and 16 (8.2%) completed all possible interviews. Recruitment to the study was lower than anticipated, but most participants seemed to find the interviews acceptable. The modified questionnaire produced usable and relevant data for an economic evaluation of formal and informal caring costs. Conclusions: Modifications are needed to the process of recruitment as a postal recruitment strategy did not have a high response rate. The Ambulatory and Home Care Record has proved a viable tool for use in the UK setting, with a few minor modifications, and will be used in a larger study comparing hospice models

Particle Swarm Optimization with Reinforcement Learning for the Prediction of CpG Islands in the Human Genome

BACKGROUND: Regions with abundant GC nucleotides, a high CpG number, and a length greater than 200 bp in a genome are often referred to as CpG islands. These islands are usually located in the 5' end of genes. Recently, several algorithms for the prediction of CpG islands have been proposed. METHODOLOGY/PRINCIPAL FINDINGS: We propose here a new method called CPSORL to predict CpG islands, which consists of a complement particle swarm optimization algorithm combined with reinforcement learning to predict CpG islands more reliably. Several CpG island prediction tools equipped with the sliding window technique have been developed previously. However, the quality of the results seems to rely too much on the choices that are made for the window sizes, and thus these methods leave room for improvement. CONCLUSIONS/SIGNIFICANCE: Experimental results indicate that CPSORL provides results of a higher sensitivity and a higher correlation coefficient in all selected experimental contigs than the other methods it was compared to (CpGIS, CpGcluster, CpGProd and CpGPlot). A higher number of CpG islands were identified in chromosomes 21 and 22 of the human genome than with the other methods from the literature. CPSORL also achieved the highest coverage rate (3.4%). CPSORL is an application for identifying promoter and TSS regions associated with CpG islands in entire human genomic. When compared to CpGcluster, the islands predicted by CPSORL covered a larger region in the TSS (12.2%) and promoter (26.1%) region. If Alu sequences are considered, the islands predicted by CPSORL (Alu) covered a larger TSS (40.5%) and promoter (67.8%) region than CpGIS. Furthermore, CPSORL was used to verify that the average methylation density was 5.33% for CpG islands in the entire human genome

Lattice Boltzmann simulations of soft matter systems

This article concerns numerical simulations of the dynamics of particles immersed in a continuum solvent. As prototypical systems, we consider colloidal dispersions of spherical particles and solutions of uncharged polymers. After a brief explanation of the concept of hydrodynamic interactions, we give a general overview over the various simulation methods that have been developed to cope with the resulting computational problems. We then focus on the approach we have developed, which couples a system of particles to a lattice Boltzmann model representing the solvent degrees of freedom. The standard D3Q19 lattice Boltzmann model is derived and explained in depth, followed by a detailed discussion of complementary methods for the coupling of solvent and solute. Colloidal dispersions are best described in terms of extended particles with appropriate boundary conditions at the surfaces, while particles with internal degrees of freedom are easier to simulate as an arrangement of mass points with frictional coupling to the solvent. In both cases, particular care has been taken to simulate thermal fluctuations in a consistent way. The usefulness of this methodology is illustrated by studies from our own research, where the dynamics of colloidal and polymeric systems has been investigated in both equilibrium and nonequilibrium situations.Comment: Review article, submitted to Advances in Polymer Science. 16 figures, 76 page