An Upstream Open Reading Frame Controls Translation of var2csa, a Gene Implicated in Placental Malaria

Malaria, caused by the parasite Plasmodium falciparum, is responsible for substantial morbidity, mortality and economic losses in tropical regions of the world. Pregnant women are exceptionally vulnerable to severe consequences of the infection, due to the specific adhesion of parasite-infected erythrocytes in the placenta. This adhesion is mediated by a unique variant of PfEMP1, a parasite encoded, hyper-variable antigen placed on the surface of infected cells. This variant, called VAR2CSA, binds to chondroitin sulfate A on syncytiotrophoblasts in the intervillous space of placentas. VAR2CSA appears to only be expressed in the presence of a placenta, suggesting that its expression is actively repressed in men, children or non-pregnant women; however, the mechanism of repression is not understood. Using cultured parasite lines and reporter gene constructs, we show that the gene encoding VAR2CSA contains a small upstream open reading frame that acts to repress translation of the resulting mRNA, revealing a novel form of gene regulation in malaria parasites. The mechanism underlying this translational repression is reversible, allowing high levels of protein translation upon selection, thus potentially enabling parasites to upregulate expression of this variant antigen in the presence of the appropriate host tissue

Compressed representation of a partially defined integer function over multiple arguments

In OLAP (OnLine Analitical Processing) data are analysed in an n-dimensional cube. The cube may be represented as a partially defined function over n arguments. Considering that often the function is not defined everywhere, we ask: is there a known way of representing the function or the points in which it is defined, in a more compact manner than the trivial one

Impact of network structure and cellular response on spike time correlations

Novel experimental techniques reveal the simultaneous activity of larger and larger numbers of neurons. As a result there is increasing interest in the structure of cooperative -- or correlated -- activity in neural populations, and in the possible impact of such correlations on the neural code. A fundamental theoretical challenge is to understand how the architecture of network connectivity along with the dynamical properties of single cells shape the magnitude and timescale of correlations. We provide a general approach to this problem by extending prior techniques based on linear response theory. We consider networks of general integrate-and-fire cells with arbitrary architecture, and provide explicit expressions for the approximate cross-correlation between constituent cells. These correlations depend strongly on the operating point (input mean and variance) of the neurons, even when connectivity is fixed. Moreover, the approximations admit an expansion in powers of the matrices that describe the network architecture. This expansion can be readily interpreted in terms of paths between different cells. We apply our results to large excitatory-inhibitory networks, and demonstrate first how precise balance --- or lack thereof --- between the strengths and timescales of excitatory and inhibitory synapses is reflected in the overall correlation structure of the network. We then derive explicit expressions for the average correlation structure in randomly connected networks. These expressions help to identify the important factors that shape coordinated neural activity in such networks

Search for electron antineutrino appearance in a long-baseline muon antineutrino beam

Electron antineutrino appearance is measured by the T2K experiment in an accelerator-produced antineutrino beam, using additional neutrino beam operation to constrain parameters of the Pontecorvo-Maki-Nakagawa-Sakata (PMNS) mixing matrix. T2K observes 15 candidate electron antineutrino events with a background expectation of 9.3 events. Including information from the kinematic distribution of observed events, the hypothesis of no electron antineutrino appearance is disfavored with a significance of 2.40σ and no discrepancy between data and PMNS predictions is found. A complementary analysis that introduces an additional free parameter which allows non-PMNS values of electron neutrino and antineutrino appearance also finds no discrepancy between data and PMNS predictions