Production of a Discrete, Infectious, Double-stranded DNA by Reverse Transcription in Virions of Moloney Murine Leukemia Virus

One of the most unique viral replication schemes is that of the retroviruses (a class that includes the RNA tumor viruses). These viruses synthesize a double-stranded (DS) DNA copy of their single-stranded (SS) RNA genome as the initial event following infection of susceptible cells (see Weinberg 1977). The details of this process—called reverse transcription—are still obscure, but the general outlines have become clear during the last few years

State-Observation Sampling and the Econometrics of Learning Models

In nonlinearstate-spacemodels, sequentiallearningaboutthe hidden statecanproceed byparticlefilteringwhen thedensityoftheobservationconditionalonthe stateisavailable analytically (e.g. Gordon et al. 1993). This condition need not hold in complex environments, such as the incomplete-information equilibrium models considered in financial economics. In this paper, we make two contributions to the learning literature. First, we introduce a new filtering method, the state-observation sampling (SOS) filter, for general state-space models with intractable observation densities. Second, we develop an indirect inference-based estimator for a large class of incomplete-information economies. We demonstrate the good performance of these techniques on an asset pricing model with investor learning applied to over 80 years of daily equity returns

Apparent non-canonical trans-splicing is generated by reverse transcriptase in vitro

Trans-splicing, the in vivo joining of two RNA molecules, is well characterized in several groups of simple organisms but was long thought absent from fungi, plants and mammals. However, recent bioinformatic analyses of expressed sequence tag (EST) databases suggested widespread trans-splicing in mammals^1-2^. Splicing, including the characterised trans-splicing systems, involves conserved sequences at the splice junctions. Our analysis of a yeast non-coding RNA revealed that around 30% of the products of reverse transcription lacked an internal region of 117 nt, suggesting that the RNA was spliced. The junction sequences lacked canonical splice-sites but were flanked by direct repeats, and further analyses indicated that the apparent splicing actually arose because reverse transcriptase can switch templates during transcription^3^. Many newly identified, apparently trans-spliced, RNAs lacked canonical splice sites but were flanked by short regions of homology, leading us to question their authenticity. Here we report that all reported categories of non-canonical splicing could be replicated using an in vitro reverse transcription system with highly purified RNA substrates. We observed the reproducible occurrence of ostensible trans-splicing, exon shuffling and sense-antisense fusions. The latter generate apparent antisense non-coding RNAs, which are also reported to be abundant in humans^4^. Different reverse transcriptases can generate different products of template switching, providing a simple diagnostic. Many reported examples of splicing in the absence of canonical splicing signals may be artefacts of cDNA preparation

Searching for network modules

When analyzing complex networks a key target is to uncover their modular structure, which means searching for a family of modules, namely node subsets spanning each a subnetwork more densely connected than the average. This work proposes a novel type of objective function for graph clustering, in the form of a multilinear polynomial whose coefficients are determined by network topology. It may be thought of as a potential function, to be maximized, taking its values on fuzzy clusterings or families of fuzzy subsets of nodes over which every node distributes a unit membership. When suitably parametrized, this potential is shown to attain its maximum when every node concentrates its all unit membership on some module. The output thus is a partition, while the original discrete optimization problem is turned into a continuous version allowing to conceive alternative search strategies. The instance of the problem being a pseudo-Boolean function assigning real-valued cluster scores to node subsets, modularity maximization is employed to exemplify a so-called quadratic form, in that the scores of singletons and pairs also fully determine the scores of larger clusters, while the resulting multilinear polynomial potential function has degree 2. After considering further quadratic instances, different from modularity and obtained by interpreting network topology in alternative manners, a greedy local-search strategy for the continuous framework is analytically compared with an existing greedy agglomerative procedure for the discrete case. Overlapping is finally discussed in terms of multiple runs, i.e. several local searches with different initializations.Comment: 10 page

Positive approximations of the inverse of fractional powers of SPD M-matrices

This study is motivated by the recent development in the fractional calculus and its applications. During last few years, several different techniques are proposed to localize the nonlocal fractional diffusion operator. They are based on transformation of the original problem to a local elliptic or pseudoparabolic problem, or to an integral representation of the solution, thus increasing the dimension of the computational domain. More recently, an alternative approach aimed at reducing the computational complexity was developed. The linear algebraic system $\cal A^\alpha \bf u=\bf f$, $0< \alpha <1$ is considered, where $\cal A$ is a properly normalized (scalded) symmetric and positive definite matrix obtained from finite element or finite difference approximation of second order elliptic problems in $\Omega\subset\mathbb{R}^d$, $d=1,2,3$. The method is based on best uniform rational approximations (BURA) of the function $t^{\beta-\alpha}$ for $0 < t \le 1$ and natural $\beta$. The maximum principles are among the major qualitative properties of linear elliptic operators/PDEs. In many studies and applications, it is important that such properties are preserved by the selected numerical solution method. In this paper we present and analyze the properties of positive approximations of $\cal A^{-\alpha}$ obtained by the BURA technique. Sufficient conditions for positiveness are proven, complemented by sharp error estimates. The theoretical results are supported by representative numerical tests

Investment under ambiguity with the best and worst in mind

Recent literature on optimal investment has stressed the difference between the impact of risk and the impact of ambiguity - also called Knightian uncertainty - on investors' decisions. In this paper, we show that a decision maker's attitude towards ambiguity is similarly crucial for investment decisions. We capture the investor's individual ambiguity attitude by applying alpha-MEU preferences to a standard investment problem. We show that the presence of ambiguity often leads to an increase in the subjective project value, and entrepreneurs are more eager to invest. Thereby, our investment model helps to explain differences in investment behavior in situations which are objectively identical

Grey and white matter correlates of recent and remote autobiographical memory retrieval:Insights from the dementias

The capacity to remember self-referential past events relies on the integrity of a distributed neural network. Controversy exists, however, regarding the involvement of specific brain structures for the retrieval of recently experienced versus more distant events. Here, we explored how characteristic patterns of atrophy in neurodegenerative disorders differentially disrupt remote versus recent autobiographical memory. Eleven behavioural-variant frontotemporal dementia, 10 semantic dementia, 15 Alzheimer's disease patients and 14 healthy older Controls completed the Autobiographical Interview. All patient groups displayed significant remote memory impairments relative to Controls. Similarly, recent period retrieval was significantly compromised in behavioural-variant frontotemporal dementia and Alzheimer's disease, yet semantic dementia patients scored in line with Controls. Voxel-based morphometry and diffusion tensor imaging analyses, for all participants combined, were conducted to investigate grey and white matter correlates of remote and recent autobiographical memory retrieval. Neural correlates common to both recent and remote time periods were identified, including the hippocampus, medial prefrontal, and frontopolar cortices, and the forceps minor and left hippocampal portion of the cingulum bundle. Regions exclusively implicated in each time period were also identified. The integrity of the anterior temporal cortices was related to the retrieval of remote memories, whereas the posterior cingulate cortex emerged as a structure significantly associated with recent autobiographical memory retrieval. This study represents the first investigation of the grey and white matter correlates of remote and recent autobiographical memory retrieval in neurodegenerative disorders. Our findings demonstrate the importance of core brain structures, including the medial prefrontal cortex and hippocampus, irrespective of time period, and point towards the contribution of discrete regions in mediating successful retrieval of distant versus recently experienced events

Under stochastic dominance Choquet-expected utility and anticipated utility are identical

The aim of this paper is to convince the reader that Choquet-expected utility, as initiated by Schmeidler (1982, 1989) for decision making under uncertainty, when formulated for decision making under risk naturally leads to anticipated utility, as initiated by Quiggin/Yaari. Thus the two generalizations of expected utility in fact are one