Potential for ultrafast dynamic chemical imaging with few-cycle infrared lasers

We studied the photoelectron spectra generated by an intense few-cycle infrared laser pulse. By focusing on the angular distributions of the back rescattered high energy photoelectrons, we show that accurate differential elastic scattering cross sections of the target ion by free electrons can be extracted. Since the incident direction and the energy of the free electrons can be easily changed by manipulating the laser's polarization, intensity, and wavelength, these extracted elastic scattering cross sections, in combination with more advanced inversion algorithms, may be used to reconstruct the effective single-scattering potential of the molecule, thus opening up the possibility of using few-cycle infrared lasers as powerful table-top tools for imaging chemical and biological transformations, with the desired unprecedented temporal and spatial resolutions.Comment: 16 pages, 6 figure

Operator method in solving non-linear equations of the Hartree-Fock type

The operator method is used to construct the solutions of the problem of the polaron in the strong coupling limit and of the helium atom on the basis of the Hartree-Fock equation. $E_0=-0.1085128052\alpha^2$ is obtained for the polaron ground-state energy. Energies for 2s- and 3s-states are also calculated. The other excited states are briefly discussed.Comment: 7 page

More Is Not Always Better-the Double-Headed Role of Fibronectin in Staphylococcus aureus Host Cell Invasion

While Staphylococcus aureus has classically been considered an extracellular pathogen, these bacteria are also capable of being taken up by host cells, including nonprofessional phagocytes such as endothelial cells, epithelial cells, or osteoblasts. The intracellular S. aureus lifestyle contributes to infection development. The predominant recognition and internalization pathway appears to be the binding of the bacteria via a fibronectin bridge to the alpha 5 beta 1-integrin on the host cell membrane, followed by phagocytosis. Although osteoblasts showed high expression of alpha 5 beta 1-integrin and fibronectin, and bacteria adhered to osteoblasts to a high proportion, here we demonstrate by internalization assays and immunofluorescence microscopy that S. aureus was less engulfed in osteoblasts than in epithelial cells. The addition of exogenous fibronectin during the infection of cells with S. aureus resulted in an increased uptake by epithelial cells but not by osteoblasts. This contrasts with the previous conception of the uptake mechanism, where high expression of integrin and fibronectin would promote the bacterial uptake into host cells. Extracellular fibronectin surrounding osteoblasts, but not epithelial cells, is organized in a fibrillary network. The inhibition of fibril formation, the short interfering RNA-mediated reduction of fibronectin expression, and the disruption of the fibronectin-fibril meshwork all resulted in a significant increase in S. aureus uptake by osteoblasts. Thus, the network of fibronectin fibrils appears to strongly reduce the uptake of S. aureus into a given host cell, indicating that the supramolecular structure of fibronectin determines the capacity of particular host cells to internalize the pathogen. IMPORTANCE Traditionally, Staphylococcus aureus has been considered an extracellular pathogen. However, among other factors, the frequent failure of antimicrobial therapy and the ability of the pathogen to cause recurrent disease have established the concept of eukaryotic invasion of the pathogen, thereby evading the host's immune system. In the current model of host cell invasion, bacteria initially bind to alpha 5 beta 1 integrin on the host cell side via a fibronectin bridge, which eventually leads to phagocytosis of S. aureus by host cells. However, in this study, we demonstrate that not the crude amount but the supramolecular structure of fibronectin molecules deposited on the eukaryotic cell surface plays an essential role in bacterial uptake by host cells. Our findings explain the large differences of S. aureus uptake efficacy in different host cell types as well as in vivo differences between courses of bacterial infections and the localization of bacteria in different clinical settings

Reverse Engineering Gene Networks with ANN: Variability in Network Inference Algorithms

Motivation :Reconstructing the topology of a gene regulatory network is one of the key tasks in systems biology. Despite of the wide variety of proposed methods, very little work has been dedicated to the assessment of their stability properties. Here we present a methodical comparison of the performance of a novel method (RegnANN) for gene network inference based on multilayer perceptrons with three reference algorithms (ARACNE, CLR, KELLER), focussing our analysis on the prediction variability induced by both the network intrinsic structure and the available data. Results: The extensive evaluation on both synthetic data and a selection of gene modules of "Escherichia coli" indicates that all the algorithms suffer of instability and variability issues with regards to the reconstruction of the topology of the network. This instability makes objectively very hard the task of establishing which method performs best. Nevertheless, RegnANN shows MCC scores that compare very favorably with all the other inference methods tested. Availability: The software for the RegnANN inference algorithm is distributed under GPL3 and it is available at the corresponding author home page (http://mpba.fbk.eu/grimaldi/regnann-supmat

Influence of orbital symmetry on diffraction imaging with rescattering electron wave packets

Citation: Pullen, M. G., Wolter, B., Le, A. T., Baudisch, M., Sclafani, M., Pires, H., . . . Biegert, J. (2016). Influence of orbital symmetry on diffraction imaging with rescattering electron wave packets. Nature Communications, 7, 6. doi:10.1038/ncomms11922The ability to directly follow and time-resolve the rearrangement of the nuclei within molecules is a frontier of science that requires atomic spatial and few-femtosecond temporal resolutions. While laser-induced electron diffraction can meet these requirements, it was recently concluded that molecules with particular orbital symmetries (such as pi(g)) cannot be imaged using purely backscattering electron wave packets without molecular alignment. Here, we demonstrate, in direct contradiction to these findings, that the orientation and shape of molecular orbitals presents no impediment for retrieving molecular structure with adequate sampling of the momentum transfer space. We overcome previous issues by showcasing retrieval of the structure of randomly oriented O-2 and C2H2 molecules, with pi(g) and pi(u) symmetries, respectively, and where their ionization probabilities do not maximize along their molecular axes. While this removes a serious bottleneck for laser-induced diffraction imaging, we find unexpectedly strong backscattering contributions from low-Z atoms

Utilising biological geotextiles: Introduction to the BORASSUS project and global perspectives

Field and laboratory studies indicate that utilisation of biological geotextiles constructed from palm-leaves and other selected organic materials are an effective, sustainable and economically viable soil conservation technique. The three-year plus (1 July 2005–28 February 2009) EU-funded BORASSUS Project (contract no. INCO-CT-2005-510745) evaluated the long-term effectiveness of biological geotextiles in controlling soil erosion and assessing their sustainability and economic viability. These studies progressed in ten countries, both in the ‘industrial north’ (in Europe) and in the ‘developing south’ (Africa, South America and South East Asia). The studied countries in the ‘developing south’ included Brazil, China, The Gambia, South Africa, Thailand and Vietnam. The ‘industrial north’ countries included Belgium, Hungary, Lithuania and the UK. The main findings of these studies are summarised in this paper and thematic information is presented in the other four papers in this Special Issue. Biological geotextiles offer potentially novel bioengineering solutions to environmental problems, including technologies for soil conservation, sustainable plant production and use of indigenous plants, improved ecosystem management by decreasing deforestation, improving agroforestry and cost-effective biogeotextile applications in diverse environments. Biogeotextiles may provide socio-economic platforms for sustainable development and the benefits for developing countries may include poverty alleviation, engagement of local people as stakeholders, employment for disadvantaged groups, small and medium enterprise (SME) development, earning hard currency, environmental education and local community involvement in land reclamation and environmental education programmes. These benefits are achieved through: (i) promotion of sustainable and environmentally friendly palm-agriculture to discourage deforestation, promoting both reforestation and agroforestry; (ii) construction of biogeotextiles enabling development of a rural labour-intensive industry, particularly encouraging employment of socially disadvantaged groups and (iii) export of biogeotextiles to industrialised countries could earn hard currency for developing economies, based on the principles of fair trade. Research and development activities of the BORASSUS Project have improved our knowledge on the effect of biogeotextile mats on the micro- and macro-soil environments and at larger scales through controlled laboratory and field experiments in diverse environments

Social Contact Patterns in Vietnam and Implications for the Control of Infectious Diseases

BACKGROUND: The spread of infectious diseases from person to person is determined by the frequency and nature of contacts between infected and susceptible members of the population. Although there is a long history of using mathematical models to understand these transmission dynamics, there are still remarkably little empirical data on contact behaviors with which to parameterize these models. Even starker is the almost complete absence of data from developing countries. We sought to address this knowledge gap by conducting a household based social contact diary in rural Vietnam. METHODS AND FINDINGS: A diary based survey of social contact patterns was conducted in a household-structured community cohort in North Vietnam in 2007. We used generalized estimating equations to model the number of contacts while taking into account the household sampling design, and used weighting to balance the household size and age distribution towards the Vietnamese population. We recorded 6675 contacts from 865 participants in 264 different households and found that mixing patterns were assortative by age but were more homogenous than observed in a recent European study. We also observed that physical contacts were more concentrated in the home setting in Vietnam than in Europe but the overall level of physical contact was lower. A model of individual versus household vaccination strategies revealed no difference between strategies in the impact on R(0). CONCLUSIONS AND SIGNIFICANCE: This work is the first to estimate contact patterns relevant to the spread of infections transmitted from person to person by non-sexual routes in a developing country setting. The results show interesting similarities and differences from European data and demonstrate the importance of context specific data

Data-driven reverse engineering of signaling pathways using ensembles of dynamic models

Signaling pathways play a key role in complex diseases such as cancer, for which the development of novel therapies is a difficult, expensive and laborious task. Computational models that can predict the effect of a new combination of drugs without having to test it experimentally can help in accelerating this process. In particular, network-based dynamic models of these pathways hold promise to both understand and predict the effect of therapeutics. However, their use is currently hampered by limitations in our knowledge of the underlying biochemistry, as well as in the experimental and computational technologies used for calibrating the models. Thus, the results from such models need to be carefully interpreted and used in order to avoid biased predictions. Here we present a procedure that deals with this uncertainty by using experimental data to build an ensemble of dynamic models. The method incorporates steps to reduce overfitting and maximize predictive capability. We find that by combining the outputs of individual models in an ensemble it is possible to obtain a more robust prediction. We report results obtained with this method, which we call SELDOM (enSEmbLe of Dynamic lOgic-based Models), showing that it improves the predictions previously reported for several challenging problems.JRB and DH acknowledge funding from the EU FP7 project NICHE (ITN Grant number 289384). JRB acknowledges funding from the Spanish MINECO project SYNBIOFACTORY (grant number DPI2014-55276-C5-2-R). AFV acknowledges funding from the Galician government (Xunta de Galiza) through the I2C postdoctoral fellowship ED481B2014/133-0. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.info:eu-repo/semantics/publishedVersio

Gene Regulatory Network Reconstruction Using Bayesian Networks, the Dantzig Selector, the Lasso and Their Meta-Analysis

Modern technologies and especially next generation sequencing facilities are giving a cheaper access to genotype and genomic data measured on the same sample at once. This creates an ideal situation for multifactorial experiments designed to infer gene regulatory networks. The fifth “Dialogue for Reverse Engineering Assessments and Methods” (DREAM5) challenges are aimed at assessing methods and associated algorithms devoted to the inference of biological networks. Challenge 3 on “Systems Genetics” proposed to infer causal gene regulatory networks from different genetical genomics data sets. We investigated a wide panel of methods ranging from Bayesian networks to penalised linear regressions to analyse such data, and proposed a simple yet very powerful meta-analysis, which combines these inference methods. We present results of the Challenge as well as more in-depth analysis of predicted networks in terms of structure and reliability. The developed meta-analysis was ranked first among the teams participating in Challenge 3A. It paves the way for future extensions of our inference method and more accurate gene network estimates in the context of genetical genomics