Susceptibility of rhabdomyosarcoma cells to macrophage-mediated cytotoxicity

The prognosis of advanced stage rhabdomyosarcoma (RMS) is still sobering. In recent years, outcome has not been further improved by conventional therapy. Therefore, novel treatment options such as macrophage-directed immunotherapy have to be investigated. The aim of this study was to analyze the phagocytosis of RMS cells by macrophages and to modulate the susceptibility using monoclonal antibodies and cytotoxic drugs

Estimating Animal Abundance in Ground Beef Batches Assayed with Molecular Markers

Estimating animal abundance in industrial scale batches of ground meat is important for mapping meat products through the manufacturing process and for effectively tracing the finished product during a food safety recall. The processing of ground beef involves a potentially large number of animals from diverse sources in a single product batch, which produces a high heterogeneity in capture probability. In order to estimate animal abundance through DNA profiling of ground beef constituents, two parameter-based statistical models were developed for incidence data. Simulations were applied to evaluate the maximum likelihood estimate (MLE) of a joint likelihood function from multiple surveys, showing superiority in the presence of high capture heterogeneity with small sample sizes, or comparable estimation in the presence of low capture heterogeneity with a large sample size when compared to other existing models. Our model employs the full information on the pattern of the capture-recapture frequencies from multiple samples. We applied the proposed models to estimate animal abundance in six manufacturing beef batches, genotyped using 30 single nucleotide polymorphism (SNP) markers, from a large scale beef grinding facility. Results show that between 411∼1367 animals were present in six manufacturing beef batches. These estimates are informative as a reference for improving recall processes and tracing finished meat products back to source

A population of luminous accreting black holes with hidden mergers

Major galaxy mergers are thought to play an important part in fuelling the growth of supermassive black holes. However, observational support for this hypothesis is mixed, with some studies showing a correlation between merging galaxies and luminous quasars and others showing no such association. Recent observations have shown that a black hole is likely to become heavily obscured behind merger-driven gas and dust, even in the early stages of the merger, when the galaxies are well separated (5 to 40 kiloparsecs). Merger simulations further suggest that such obscuration and black-hole accretion peaks in the final merger stage, when the two galactic nuclei are closely separated (less than 3 kiloparsecs). Resolving this final stage requires a combination of high-spatial-resolution infrared imaging and high-sensitivity hard-X-ray observations to detect highly obscured sources. However, large numbers of obscured luminous accreting supermassive black holes have been recently detected nearby (distances below 250 megaparsecs) in X-ray observations. Here we report high-resolution infrared observations of hard-X-ray-selected black holes and the discovery of obscured nuclear mergers, the parent populations of supermassive-black-hole mergers. We find that obscured luminous black holes (bolometric luminosity higher than 2x10^44 ergs per second) show a significant (P<0.001) excess of late-stage nuclear mergers (17.6 per cent) compared to a sample of inactive galaxies with matching stellar masses and star formation rates (1.1 per cent), in agreement with theoretical predictions. Using hydrodynamic simulations, we confirm that the excess of nuclear mergers is indeed strongest for gas-rich major-merger hosts of obscured luminous black holes in this final stage.Comment: To appear in the 8 November 2018 issue of Nature. This is the authors' version of the wor

Constructal blade shape in nanofluids

Blade configuration of nanofluids has been proven to perform much better than dispersed configuration for some heat conduction systems. The analytical analysis and numerical calculation are made for the cylinder--shaped and regular-rectangular-prism--shaped building blocks of the blade-configured heat conduction systems (using nanofluids as the heat conduction media) to find the optimal cross-sectional shape for the nanoparticle blade under the same composing materials, composition ratio, volumetric heat generation rate, and total building block volume. The regular-triangular-prism--shaped blade has been proven to perform better than all the other three kinds of blades, namely, the regular-rectangular-prism--shaped blade, the regular-hexagonal-prism--shaped blade, and the cylinder--shaped blade. Thus, the regular-triangular-prism--shaped blade is selected as the optimally shaped blade for the two kinds of building blocks that are considered in this study. It is also proven that the constructal cylinder--regular-triangular-prism building block performs better than the constructal regular-rectangular-prism--regular-triangular-prism building block

What traits are carried on mobile genetic elements, and why?

Although similar to any other organism, prokaryotes can transfer genes vertically from mother cell to daughter cell, they can also exchange certain genes horizontally. Genes can move within and between genomes at fast rates because of mobile genetic elements (MGEs). Although mobile elements are fundamentally self-interested entities, and thus replicate for their own gain, they frequently carry genes beneficial for their hosts and/or the neighbours of their hosts. Many genes that are carried by mobile elements code for traits that are expressed outside of the cell. Such traits are involved in bacterial sociality, such as the production of public goods, which benefit a cell's neighbours, or the production of bacteriocins, which harm a cell's neighbours. In this study we review the patterns that are emerging in the types of genes carried by mobile elements, and discuss the evolutionary and ecological conditions under which mobile elements evolve to carry their peculiar mix of parasitic, beneficial and cooperative genes

One Is Enough: In Vivo Effective Population Size Is Dose-Dependent for a Plant RNA Virus

Effective population size (Ne) determines the strength of genetic drift and the frequency of co-infection by multiple genotypes, making it a key factor in viral evolution. Experimental estimates of Ne for different plant viruses have, however, rendered diverging results. The independent action hypothesis (IAH) states that each virion has a probability of infection, and that virions act independent of one another during the infection process. A corollary of IAH is that Ne must be dose dependent. A test of IAH for a plant virus has not been reported yet. Here we perform a test of an IAH infection model using a plant RNA virus, Tobacco etch virus (TEV) variants carrying GFP or mCherry fluorescent markers, in Nicotiana tabacum and Capsicum annuum plants. The number of primary infection foci increased linearly with dose, and was similar to a Poisson distribution. At high doses, primary infection foci containing both genotypes were found at a low frequency (<2%). The probability that a genotype that infected the inoculated leaf would systemically infect that plant was near 1, although in a few rare cases genotypes could be trapped in the inoculated leaf by being physically surrounded by the other genotype. The frequency of mixed-genotype infection could be predicted from the mean number of primary infection foci using the independent-action model. Independent action appears to hold for TEV, and Ne is therefore dose-dependent for this plant RNA virus. The mean number of virions causing systemic infection can be very small, and approaches 1 at low doses. Dose-dependency in TEV suggests that comparison of Ne estimates for different viruses are not very meaningful unless dose effects are taken into consideration

The conventional gait model - success and limitations

The Conventional Gait Model (CGM) is a generic name for a family of closely related and very widely used biomechanical models for gait analysis. After describing its history, the core attributes of the model are described followed by evaluation of its strengths and weaknesses. An analysis of the current and future requirements for practical biomechanical models for clinical and other gait analysis purposes which have been rigorously calibrated suggests that the CGM is better suited for this purpose than any other currently available model. Modifications are required, however, and a number are proposed

A new accuracy measure based on bounded relative error for time series forecasting

Many accuracy measures have been proposed in the past for time series forecasting comparisons. However, many of these measures suffer from one or more issues such as poor resistance to outliers and scale dependence. In this paper, while summarising commonly used accuracy measures, a special review is made on the symmetric mean absolute percentage error. Moreover, a new accuracy measure called the Unscaled Mean Bounded Relative Absolute Error (UMBRAE), which combines the best features of various alternative measures, is proposed to address the common issues of existing measures. A comparative evaluation on the proposed and related measures has been made with both synthetic and real-world data. The results indicate that the proposed measure, with user selectable benchmark, performs as well as or better than other measures on selected criteria. Though it has been commonly accepted that there is no single best accuracy measure, we suggest that UMBRAE could be a good choice to evaluate forecasting methods, especially for cases where measures based on geometric mean of relative errors, such as the geometric mean relative absolute error, are preferred

3-Methyl-1-butanol production in Escherichia coli: random mutagenesis and two-phase fermentation

Interest in producing biofuels from renewable sources has escalated due to energy and environmental concerns. Recently, the production of higher chain alcohols from 2-keto acid pathways has shown significant progress. In this paper, we demonstrate a mutagenesis approach in developing a strain of Escherichia coli for the production of 3-methyl-1-butanol by leveraging selective pressure toward l-leucine biosynthesis and screening for increased alcohol production. Random mutagenesis and selection with 4-aza-d,l-leucine, a structural analogue to l-leucine, resulted in the development of a new strain of E. coli able to produce 4.4 g/L of 3-methyl-1-butanol. Investigation of the host’s sensitivity to 3-methyl-1-butanol directed development of a two-phase fermentation process in which titers reached 9.5 g/L of 3-methyl-1-butanol with a yield of 0.11 g/g glucose after 60 h