Importance Sampling of Word Patterns in DNA and Protein Sequences

The use of Monte Carlo evaluation to compute p-values of pattern counting test statistics is especially attractive when an asymptotic theory is absent or when the search sequence or the word pattern is too short for an asymptotic formula to be accurate. The drawback of applying Monte Carlo simulations directly is its inefficiency when p-values are small, which precisely is the situation of importance. In this paper, we provide a general importance sampling algorithm for efficient Monte Carlo evaluation of small p-values of pattern counting test statistics and apply it on word patterns of biological interest, in particular palindromes and inverted repeats, patterns arising from position specific weight matrices, as well as co-occurrences of pairs of motifs. We also show that our importance sampling technique satisfies a log efficient criterion

Brain tissue oxygen amperometry in behaving rats demonstrates functional dissociation of dorsal and ventral hippocampus during spatial processing and anxiety

Traditionally, the function of the hippocampus (HPC) has been viewed in unitary terms, but there is growing evidence that the HPC is functionally differentiated along its septotemporal axis. Lesion studies in rodents and functional brain imaging in humans suggest a preferential role for the septal HPC in spatial learning and a preferential role for the temporal HPC in anxiety. To better enable cross-species comparison, we present an in vivo amperometric technique that measures changes in brain tissue oxygen at high temporal resolution in freely-moving rats. We recorded simultaneously from the dorsal (septal; dHPC) and ventral (temporal; vHPC) HPC during two anxiety tasks and two spatial tasks on the radial maze. We found a double-dissociation of function in the HPC, with increased vHPC signals during anxiety and increased dHPC signals during spatial processing. In addition, dHPC signals were modulated by spatial memory demands. These results add a new dimension to the growing consensus for a differentiation of HPC function, and highlight tissue oxygen amperometry as a valuable tool to aid translation between animal and human research

A Comparison of the Sensitivity and Fecal Egg Counts of the McMaster Egg Counting and Kato-Katz Thick Smear Methods for Soil-Transmitted Helminths

Currently, in public health, the reduction in the number of eggs excreted in stools after drug administration is used to monitor the efficacy of drugs against parasitic worms. Yet, studies comparing diagnostic methods for the enumeration of eggs in stool are few. We compared the Kato-Katz thick smear (Kato-Katz) and McMaster egg counting (McMaster) methods, which are commonly used diagnostic methods in public and animal health, respectively, for the diagnosis and enumeration of eggs of roundworms, whipworms and hookworms in 1,536 stool samples from children in five trials across Africa, Asia and South America. The Kato-Katz method was the most sensitive for the detection of roundworms, but there was no significant difference in sensitivity between the methods for hookworms and whipworms. The sensitivity of the methods differed across the trials and magnitude of egg counts. The Kato-Katz method resulted in significantly higher egg counts, but these were subject to lack of accuracy caused by intrinsic properties of this method. McMaster provided more reliable estimates of drug efficacies. We conclude that the McMaster is an alternative method for monitoring large-scale treatment programs. It allows accurate monitoring of drug efficacy and can be easily performed under field conditions

TRY plant trait database – enhanced coverage and open access

Plant traits - the morphological, anatomical, physiological, biochemical and phenological characteristics of plants - determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait‐based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits - almost complete coverage for ‘plant growth form’. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait–environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives

Murine in vitro cellular models to better understand adipogenesis and its potential applications

Adipogenesis has been extensively studied using in vitro models of cellular differentiation, enabling long-term regulation of fat cell metabolism in human adipose tissue (AT) material. Many studies promote the idea that manipulation of this process could potentially reduce the prevalence of obesity and its related diseases. It has now become essential to understand the molecular basis of fat cell development to tackle this pandemic disease, by identifying therapeutic targets and new biomarkers. This review explores murine cell models and their applications for study of the adipogenic differentiation process in vitro. We focus on the benefits and limitations of different cell line models to aid in interpreting data and selecting a good cell line model for successful understanding of adipose biology