Evaluation of mTOR-regulated mRNA translation.

mTOR, the mammalian target of rapamycin, regulates protein synthesis (mRNA translation) by affecting the phosphorylation or activity of several translation factors. Here, we describe methods for studying the impact of mTOR signalling on protein synthesis, using inhibitors of mTOR such as rapamycin (which impairs some of its functions) or mTOR kinase inhibitors (which probably block all functions).To assess effects of mTOR inhibition on general protein synthesis in cells, the incorporation of radiolabelled amino acids into protein is measured. This does not yield information on the effects of mTOR on the synthesis of specific proteins. To do this, two methods are described. In one, stable-isotope labelled amino acids are used, and their incorporation into new proteins is determined using mass spectrometric methods. The proportions of labelled vs. unlabeled versions of each peptide from a given protein provide quantitative information about the rate of that protein's synthesis under different conditions. Actively translated mRNAs are associated with ribosomes in polyribosomes (polysomes); thus, examining which mRNAs are found in polysomes under different conditions provides information on the translation of specific mRNAs under different conditions. A method for the separation of polysomes from non-polysomal mRNAs is describe

Magnetism and Charge Dynamics in Iron Pnictides

In a wide variety of materials, such as copper oxides, heavy fermions, organic salts, and the recently discovered iron pnictides, superconductivity is found in close proximity to a magnetically ordered state. The character of the proximate magnetic phase is thus believed to be crucial for understanding the differences between the various families of unconventional superconductors and the mechanism of superconductivity. Unlike the AFM order in cuprates, the nature of the magnetism and of the underlying electronic state in the iron pnictide superconductors is not well understood. Neither density functional theory nor models based on atomic physics and superexchange, account for the small size of the magnetic moment. Many low energy probes such as transport, STM and ARPES measured strong anisotropy of the electronic states akin to the nematic order in a liquid crystal, but there is no consensus on its physical origin, and a three dimensional picture of electronic states and its relations to the optical conductivity in the magnetic state is lacking. Using a first principles approach, we obtained the experimentally observed magnetic moment, optical conductivity, and the anisotropy of the electronic states. The theory connects ARPES, which measures one particle electronic states, optical spectroscopy, probing the particle hole excitations of the solid and neutron scattering which measures the magnetic moment. We predict a manifestation of the anisotropy in the optical conductivity, and we show that the magnetic phase arises from the paramagnetic phase by a large gain of the Hund's rule coupling energy and a smaller loss of kinetic energy, indicating that iron pnictides represent a new class of compounds where the nature of magnetism is intermediate between the spin density wave of almost independent particles, and the antiferromagnetic state of local moments.Comment: 4+ pages with additional one-page supplementary materia

Efficient human cytomegalovirus reactivation is maturation dependent in the Langerhans dendritic cell lineage and can be studied using a CD14+ experimental latency model

Studies from a number of laboratories have shown that the myeloid lineage is prominent in human cytomegalovirus (HCMV) latency, reactivation, dissemination, and pathogenesis. Existing as a latent infection in CD34(+) progenitors and circulating CD14(+) monocytes, reactivation is observed upon differentiation to mature macrophage or dendritic cell (DC) phenotypes. Langerhans' cells (LCs) are a subset of periphery resident DCs that represent a DC population likely to encounter HCMV early during primary infection. Furthermore, we have previously shown that CD34(+) derived LCs are a site of HCMV reactivation ex vivo. Accordingly, we have utilized healthy-donor CD34(+) cells to study latency and reactivation of HCMV in LCs. However, the increasing difficulty acquiring healthy-donor CD34(+) cells--particularly from seropositive donors due to the screening regimens used--led us to investigate the use of CD14(+) monocytes to generate LCs. We show here that CD14(+) monocytes cultured with transforming growth factor β generate Langerin-positive DCs (MoLCs). Consistent with observations using CD34(+) derived LCs, only mature MoLCs were permissive for HCMV infection. The lytic infection of mature MoLCs is productive and results in a marked inhibition in the capacity of these cells to promote T cell proliferation. Pertinently, differentiation of experimentally latent monocytes to the MoLC phenotype promotes reactivation in a maturation and interleukin-6 (IL-6)-dependent manner. Intriguingly, however, IL-6-mediated effects were restricted to mature LCs, in contrast to observations with classical CD14(+) derived DCs. Consequently, elucidation of the molecular basis behind the differential response of the two DC subsets should further our understanding of the fundamental mechanisms important for reactivation

Identifying component modules

A computer-based system for modelling component dependencies and identifying component modules is presented. A variation of the Dependency Structure Matrix (DSM) representation was used to model component dependencies. The system utilises a two-stage approach towards facilitating the identification of a hierarchical modular structure. The first stage calculates a value for a clustering criterion that may be used to group component dependencies together. A Genetic Algorithm is described to optimise the order of the components within the DSM with the focus of minimising the value of the clustering criterion to identify the most significant component groupings (modules) within the product structure. The second stage utilises a 'Module Strength Indicator' (MSI) function to determine a value representative of the degree of modularity of the component groupings. The application of this function to the DSM produces a 'Module Structure Matrix' (MSM) depicting the relative modularity of available component groupings within it. The approach enabled the identification of hierarchical modularity in the product structure without the requirement for any additional domain specific knowledge within the system. The system supports design by providing mechanisms to explicitly represent and utilise component and dependency knowledge to facilitate the nontrivial task of determining near-optimal component modules and representing product modularity

Kinetic frustration and the nature of the magnetic and paramagnetic states in iron pnictides and iron chalcogenides

The iron pnictide and chalcogenide compounds are a subject of intensive investigations due to their high temperature superconductivity.\cite{a-LaFeAsO} They all share the same structure, but there is significant variation in their physical properties, such as magnetic ordered moments, effective masses, superconducting gaps and T$_c$. Many theoretical techniques have been applied to individual compounds but no consistent description of the trends is available \cite{np-review}. We carry out a comparative theoretical study of a large number of iron-based compounds in both their magnetic and paramagnetic states. We show that the nature of both states is well described by our method and the trends in all the calculated physical properties such as the ordered moments, effective masses and Fermi surfaces are in good agreement with experiments across the compounds. The variation of these properties can be traced to variations in the key structural parameters, rather than changes in the screening of the Coulomb interactions. Our results provide a natural explanation of the strongly Fermi surface dependent superconducting gaps observed in experiments\cite{Ding}. We propose a specific optimization of the crystal structure to look for higher T$_c$ superconductors.Comment: 5 pages, 3 figures with a 5-page supplementary materia

First measurement of the T-violating muon polarization in the decay K^+ --> mu^+ nu gamma

We present the result of the first measurement of the T-violating muon polarization P_T in the decay K^+ --> mu^+ nu gamma. This polarization is sensitive to new sources of CP-violation in the Higgs sector. Using data accumulated in the period 1996-98 we have obtained P_T = (-0.64 +- 1.85(stat) +- 0.10(syst))x10^{-2} which is consistent with no T-violation in this decay.Comment: 11 pages, 8 figure

Learning Graph-Convolutional Representations for Point Cloud Denoising

Point clouds are an increasingly relevant data type but they are often corrupted by noise. We propose a deep neural network based on graph-convolutional layers that can elegantly deal with the permutation-invariance problem encountered by learning-based point cloud processing methods. The network is fully-convolutional and can build complex hierarchies of features by dynamically constructing neighborhood graphs from similarity among the high-dimensional feature representations of the points. When coupled with a loss promoting proximity to the ideal surface, the proposed approach significantly outperforms state-of-the-art methods on a variety of metrics. In particular, it is able to improve in terms of Chamfer measure and of quality of the surface normals that can be estimated from the denoised data. We also show that it is especially robust both at high noise levels and in presence of structured noise such as the one encountered in real LiDAR scans.Comment: European Conference on Computer Vision (ECCV) 202

Do mutual funds have consistency in their performance?

Using a comprehensive data set of 714 Chinese mutual funds from 2004 to 2015, the study investigates these funds’ performance persistence by using the Capital Asset Pricing model, the Fama-French three-factor model and the Carhart Four-factor model. For persistence analysis, we categorize mutual funds into eight octiles based on their one year lagged performance and then observe their performance for the subsequent 12 months. We also apply Cross-Product Ratio technique to assess the performance persistence in these Chinese funds. The study finds no significant evidence of persis- tence in the performance of the mutual funds. Winner (loser) funds do not continue to be winner (loser) funds in the subsequent time period. These findings suggest that future performance of funds cannot be predicted based on their past performance.info:eu-repo/semantics/publishedVersio