Nutritional control of mRNA isoform expression during developmental arrest and recovery in C. elegans.

Nutrient availability profoundly influences gene expression. Many animal genes encode multiple transcript isoforms, yet the effect of nutrient availability on transcript isoform expression has not been studied in genome-wide fashion. When Caenorhabditis elegans larvae hatch without food, they arrest development in the first larval stage (L1 arrest). Starved larvae can survive L1 arrest for weeks, but growth and post-embryonic development are rapidly initiated in response to feeding. We used RNA-seq to characterize the transcriptome during L1 arrest and over time after feeding. Twenty-seven percent of detectable protein-coding genes were differentially expressed during recovery from L1 arrest, with the majority of changes initiating within the first hour, demonstrating widespread, acute effects of nutrient availability on gene expression. We used two independent approaches to track expression of individual exons and mRNA isoforms, and we connected changes in expression to functional consequences by mining a variety of databases. These two approaches identified an overlapping set of genes with alternative isoform expression, and they converged on common functional patterns. Genes affecting mRNA splicing and translation are regulated by alternative isoform expression, revealing post-transcriptional consequences of nutrient availability on gene regulation. We also found that phosphorylation sites are often alternatively expressed, revealing a common mode by which alternative isoform expression modifies protein function and signal transduction. Our results detail rich changes in C. elegans gene expression as larvae initiate growth and post-embryonic development, and they provide an excellent resource for ongoing investigation of transcriptional regulation and developmental physiology.

Uma abordagem da lógica fuzzy no ensino médio

O uso cada vez mais intenso de conceitos subjetivos - provenientes da lógica fuzzy - aplicados a problemas reais nos motivou a desenvolver procedimentos para a introdução destas idéias no âmbito do ensino médio. O projeto propõe inicialmente o estudo de conjuntos fuzzy que podem ser entendidos com exemplos - de variação populacional, de controle de pragas e de epidemias. Posteriormente, usar as “operações fuzzy” Sup e Inf em produtos de matrizes para realizar diagnósticos e avaliações subjetivas. As situações abordadas já estão na literatura (Barros e Bassanezi, 2006), entretanto não como fonte para o Ensino Médio. Um dos objetivos principais deste trabalho é contrapor a crença de exatidão da matemática clássica com os resultados provenientes de lógica subjetiva, utilizando conceitos apropriados para os estudantes destas séries: teoria dos conjuntos, relações e funções, matrizes, equações de diferenças e outros.

Maximising heat transfer efficiency in the cold crucible induction melting process

Induction heating is an efficient method used to melt electrically conductive materials, particularly if melting takes place in a ceramic crucible. This form of melting is particularly good for alloys, as electromagnetic forces set up by the induction coil lead to vigorous stirring of the melt ensuring homogeneity and uniformity in temperature. However, for certain reactive alloys, or where high purity is required, ceramic crucibles cannot be used, but a water-cooled segmented copper crucible is employed instead. Water cooling prevents meltdown or distortion of the metal wall, but much of the energy goes into the coolant. To reduce this loss, the electromagnetic force generated by the coil is used to push the melt away from the walls and so minimise contact with water-cooled surfaces. Even then, heat is lost through the crucible base where contact is inevitable. In a collaborative programme between Greenwich and Birmingham Universities, computer modelling has been used in conjunction with experiments to improve the superheat attainable in the melt for a,number of alloys, especially for y-TiAl intermetallics to cast aeroengine turbine blades. The model solves the discretised form of the turbulent Navier-Stokes, thermal energy conservation and Maxwell equations using a Spectral Collocation technique. The time-varying melt envelope is followed explicitly during the computation using an adaptive mesh. This paper briefly describes the mathematical model used to represent the interaction between the magnetic field, fluid flow, heat transfer and change of phase in the crucible and identifies the proportions of energy used in the melt, lost in the crucible base and in the crucible walls. The role of turbulence is highlighted as important in controlling heat losses and turbulence damping is introduced as a means of improving superheat. Model validation is against experimental results and shows good agreement with measured temperatures and energy losses in the cooling fluid throughout the melting cycle.

Determining surface tension using DC magnetic levitation

The values of material physical properties are vital for the successful use of numerical simulations for electromagnetic processing of materials. The surface tension of materials can be determined from the experimental measurement of the surface oscillation frequency of liquid droplets. In order for this technique to be used, a positioning field is required that results in a modification to the oscillation frequency. A number of previous analytical models have been developed that mainly focus on electrically conducting droplets positioned using an A.C. electromagnetic field, but due to the turbulent flow resulting from the high electromagnetic fields required to balance gravity, reliable measurements have largely been limited to microgravity. In this work axisymmetric analytical and numerical models are developed, which allow the surface tension of a diamagnetic droplet positioned in a high DC magnetic field to be determined from the surface oscillations. In the case of D.C. levitation there is no internal electric currents with resulting Joule heating, Marangoni flow and other effects that introduce additional physics that complicates the measurement process. The analytical solution uses the linearised Navier-Stokes equations in the inviscid case. The body force from a DC field is potential, in contrast to the AC case, and it can be derived from Maxwell equations giving a solution for the magnetic field in the form of a series expansion of Legendre polynomials. The first few terms in this expansion represent a constant and gradient magnetic field valid close to the origin, which can be used to position the droplet. Initially the mathematical model is verified in microgravity conditions using a numerical model developed to solve the transient electromagnetics, fluid flow and thermodynamic equations. In the numerical model (as in experiment) the magnetic field is obtained using electrical current carrying coils, which provides the confinement force for a liquid droplet. The model incorporates free surface deformation to accurately model the oscillations that result from the interaction between the droplet and the non-uniform external magnetic field. A comparison is made between the analytical perturbation theory and the numerical pseudo spectral approximation solutions for small amplitude oscillations.

Spatio-temporal Bayesian network models with latent variables for revealing trophic dynamics and functional networks in fisheries ecology

Ecosystems consist of complex dynamic interactions among species and the environment, the understanding of which has implications for predicting the environmental response to changes in climate and biodiversity. However, with the recent adoption of more explorative tools, like Bayesian networks, in predictive ecology, few assumptions can be made about the data and complex, spatially varying interactions can be recovered from collected field data. In this study, we compare Bayesian network modelling approaches accounting for latent effects to reveal species dynamics for 7 geographically and temporally varied areas within the North Sea. We also apply structure learning techniques to identify functional relationships such as prey–predator between trophic groups of species that vary across space and time. We examine if the use of a general hidden variable can reflect overall changes in the trophic dynamics of each spatial system and whether the inclusion of a specific hidden variable can model unmeasured group of species. The general hidden variable appears to capture changes in the variance of different groups of species biomass. Models that include both general and specific hidden variables resulted in identifying similarity with the underlying food web dynamics and modelling spatial unmeasured effect. We predict the biomass of the trophic groups and find that predictive accuracy varies with the models' features and across the different spatial areas thus proposing a model that allows for spatial autocorrelation and two hidden variables. Our proposed model was able to produce novel insights on this ecosystem's dynamics and ecological interactions mainly because we account for the heterogeneous nature of the driving factors within each area and their changes over time. Our findings demonstrate that accounting for additional sources of variation, by combining structure learning from data and experts' knowledge in the model architecture, has the potential for gaining deeper insights into the structure and stability of ecosystems. Finally, we were able to discover meaningful functional networks that were spatially and temporally differentiated with the particular mechanisms varying from trophic associations through interactions with climate and commercial fisheries.

The influence of transforming growth factor-beta1 gene polymorphisms on the severity of gingival overgrowth associated with concomitant use of cyclosporin A and a calcium channel blocker

The purpose of this study was to determine whether the prevalence and severity of gingival overgrowth in renal transplant recipients concomitantly treated with cyclosporin and a calcium channel blocker was associated with functional polymorphisms within the signal sequence of the transforming growth factor-(TGF)beta1 gene.