Radial distribution of RNA genome packaged inside spherical viruses

The problem of RNA genomes packaged inside spherical viruses is studied. The viral capsid is modeled as a hollowed sphere. The attraction between RNA molecules and the inner viral capsid is assumed to be non-specific and occurs at the inner capsid surface only. For small capsid attraction, it is found that monomer concentration of RNA molecules is maximum at the center of the capsid to maximize their configurational entropy. For stronger capsid attraction, RNA concentration peaks at some distance near the capsid. In the latter case, the competition between the branching of RNA secondary struture and its adsorption to the inner capsid results in the formation of a dense layer of RNA near capsid surface. The layer thickness is a slowly varying (logarithmic) function of the capsid inner radius. Consequently, for immediate strength of RNA-capsid interaction, the amount of RNA packaged inside a virus is proportional to the capsid {\em area} (or the number of proteins) instead of its volume. The numerical profiles describe reasonably well the experimentally observed RNA nucleotide concentration profiles of various viruses.Comment: 5 pages, 2 figures. Abstract, introduction rewritten. Comparison to actual virus profiles added. Submitted to PR

Consequences of temperature and temperature variability on swimming activity, group structure, and predation of endangered delta smelt

The effects of water temperature on individual and group movement behaviour in prey fish can affect ecological interactions such as competition and predation, but how variability in temperature influence fish behaviour is less understood. Of particular concern is how increased warming in tidally fluctuating estuaries may impact the native and endangered delta smelt (Hypomesus transpacificus, Osmeridae). To help address this issue, we tested the effects of increased water temperature (fluctuating [17–21°C] and warm [21°C] acclimated treatments) on juvenile delta smelt individual and group behaviour, response to chemical alarm and predator cues, as well as capacity to evade predation. In addition, predation of delta smelt was tested in the presence of a dominant invasive competitor, Mississippi silversides (Menidia beryllina, Atherinopsidae), as well as comparative predation mortality on Mississippi silversides when isolated. After 7 days of increased temperature treatments, delta smelt in the warm treatment increased swimming velocity, decreased turning angle, and altered group structure with larger inter-individual distances compared to fish in the control (17°C) and fluctuating temperature treatments. Following conspecific and predator chemical alarm cues, delta smelt showed anti-predator responses. Control and fluctuating treatment fish responded to conspecific cues with increased swimming speeds, decreased inter-individual distances and near-neighbour distances, and, after 15 min, fish recovered back to baseline behaviours. In contrast, fish in the warm treatment had not recovered after 15 min, and swimming speeds were maintained at roughly 25 cm/s, close to maximum capabilities. Fish in control and fluctuating treatments showed minimal responses to predator cues, whereas delta smelt exposed to warm conditions significantly increased swimming speeds and decreased turning angle. Predation of delta smelt by largemouth bass (Micropterus salmoides, Centrarchidae) was greatest under the warm treatment, correlating with altered behaviours of delta smelt; however, predation of Mississippi silversides was greater than delta smelt, independent of temperature. This study provides novel insight into the group behaviour of delta smelt, their response to predation, and how prolonged exposure to elevated temperature may induce negative individual and group behaviours causing alterations in predator–prey dynamics. This work highlights the importance of testing ecologically realistic temperature fluctuations in experiments as delta smelt had significantly altered responses to elevated temperature, dependent on variability of warming

Data-driven structural health monitoring using feature fusion and hybrid deep learning

Smart structural health monitoring (SHM) for large-scale infrastructures is an intriguing subject for engineering communities thanks to its significant advantages such as timely damage detection, optimal maintenance strategy, and reduced resource requirement. Yet, it is a challenging topic as it requires handling a large amount of collected sensors data continuously, which is inevitably contaminated by random noises. Therefore, this study developed a practical end-to-end framework that makes use of physical features embedded in raw data and an elaborated hybrid deep learning model, namely 1DCNN-LSTM, featuring two algorithms - Convolutional Neural Network (CNN) and Long-Short Term Memory (LSTM). In order to extract relevant features from sensory data, the method combines various signal processing techniques such as the autoregressive model, discrete wavelet transform, and empirical mode decomposition. The hybrid deep learning 1DCNN-LSTM is designed based on the CNN’s capacity of capturing local information and the LSTM network’s prominent ability to learn long-term dependencies. Through three case studies involving both experimental and synthetic datasets, it is demonstrated that the proposed approach achieves highly accurate damage detection, as accurate as the powerful two-dimensional CNN, but with a lower time and memory complexity, making it suitable for real-time SHM

Innovative in silico approaches to address avian flu using grid technology

The recent years have seen the emergence of diseases which have spread very quickly all around the world either through human travels like SARS or animal migration like avian flu. Among the biggest challenges raised by infectious emerging diseases, one is related to the constant mutation of the viruses which turns them into continuously moving targets for drug and vaccine discovery. Another challenge is related to the early detection and surveillance of the diseases as new cases can appear just anywhere due to the globalization of exchanges and the circulation of people and animals around the earth, as recently demonstrated by the avian flu epidemics. For 3 years now, a collaboration of teams in Europe and Asia has been exploring some innovative in silico approaches to better tackle avian flu taking advantage of the very large computing resources available on international grid infrastructures. Grids were used to study the impact of mutations on the effectiveness of existing drugs against H5N1 and to find potentially new leads active on mutated strains. Grids allow also the integration of distributed data in a completely secured way. The paper presents how we are currently exploring how to integrate the existing data sources towards a global surveillance network for molecular epidemiology.Comment: 7 pages, submitted to Infectious Disorders - Drug Target

Polyelectrolyte Persistence Length: Attractive Effect of Counterion Correlations and Fluctuations

The persistence length of a single, strongly charged, stiff polyelectrolyte chain is investigated theoretically. Path integral formulation is used to obtain the effective electrostatic interaction between the monomers. We find significant deviations from the classical Odijk, Skolnick and Fixman (OSF) result. An induced attraction between monomers is due to thermal fluctuations and correlations between bound counterions. The electrostatic persistence length is found to be smaller than the OSF value and indicates a possible mechanical instability (collapse) for highly charged polyelectrolytes with multivalent counterions. In addition, we calculate the amount of condensed counterions on a slightly bent polyelectrolyte. More counterions are found to be adsorbed as compared to the Manning condensation on a cylinder.Comment: 5 pages, 1 ps figur

Pitch contours of Northern Vietnamese tones vary with focus marking

Intonation is a means of structuring discourse and one of its functions is to highlight new or contrasting information, i.e., focus. Speakers of different languages use a range of prosodic cues to mark focus. Compared to non-tonal languages such as English, tonal languages use pitch to distinguish lexical tones and focus marking. Determining the interplay between intonation and lexical tone is therefore important. Previous studies found that tonal languages use different strategies to mark focus. For example, some use an increase (e.g., Mandarin Chinese), others a decrease in pitch (e.g., Kammu). The Vietnamese language has six lexical tones and is particularly interesting for examining pitch contours in focus marking. In this article, we present a production study with 70 Northern Vietnamese speakers. Participants read six sentences aloud under two different conditions (narrow/wide focus). In each sentence, focus marked a single noun (‘focus item’) which occurred in the final position of the sentence and carried one of the six tones. Acoustic analyses of the focus item showed that Vietnamese speakers realized focus with significant differences in pitch at the beginning of the word, but the strategies to increase or decrease pitch varied across tones. Our findings add important insights to the discussion about Information Structure and the role of intonation in tonal languages by analyzing the use of prosodic cues in a complex tone system. The large number of speakers in our study also adds further methodological rigor compared to other studies, which often rely on a few speakers.1 Introduction 2 Using intonation for focus marking 2.1 Focus marking with intonation in tonal languages 2.2 Using intonation to mark pragmatic functions and focus in Vietnamese 3 Method 3.1 Participants 3.3 Material 3.2 Procedure 3.3 Pitch Analysis 4 Results 5 Discussio

Gain of 20q11.21 in human pluripotent stem cells impairs TGF-β-dependent neuroectodermal commitment

Gain of 20q11.21 is one of the most common recurrent genomic aberrations in human pluripotent stem cells. Although it is known that overexpression of the antiapoptotic gene Bcl-xL confers a survival advantage to the abnormal cells, their differentiation capacity has not been fully investigated. RNA sequencing of mutant and control hESC lines, and a line transgenically overexpressing Bcl-xL, shows that overexpression of Bcl-xL is sufficient to cause most transcriptional changes induced by the gain of 20q11.21. Moreover, the differentially expressed genes in mutant and Bcl-xL overexpressing lines are enriched for genes involved in TGF-beta- and SMAD-mediated signaling, and neuron differentiation. Finally, we show that this altered signaling has a dramatic negative effect on neuroectodermal differentiation, while the cells maintain their ability to differentiate to mesendoderm derivatives. These findings stress the importance of thorough genetic testing of the lines before their use in research or the clinic

Selection of DNA nanoparticles with preferential binding to aggregated protein target.

High affinity and specificity are considered essential for affinity reagents and molecularly-targeted therapeutics, such as monoclonal antibodies. However, life's own molecular and cellular machinery consists of lower affinity, highly multivalent interactions that are metastable, but easily reversible or displaceable. With this inspiration, we have developed a DNA-based reagent platform that uses massive avidity to achieve stable, but reversible specific recognition of polyvalent targets. We have previously selected these DNA reagents, termed DeNAno, against various cells and now we demonstrate that DeNAno specific for protein targets can also be selected. DeNAno were selected against streptavidin-, rituximab- and bevacizumab-coated beads. Binding was stable for weeks and unaffected by the presence of soluble target proteins, yet readily competed by natural or synthetic ligands of the target proteins. Thus DeNAno particles are a novel biomolecular recognition agent whose orthogonal use of avidity over affinity results in uniquely stable yet reversible binding interactions