Atomic excitation during recollision-free ultrafast multi-electron tunnel ionization

Modern intense ultrafast pulsed lasers generate an electric field of sufficient strength to permit tunnel ionization of the valence electrons in atoms. This process is usually treated as a rapid succession of isolated events, in which the states of the remaining electrons are neglected. Such electronic interactions are predicted to be weak, the exception being recollision excitation and ionization caused by linearly-polarized radiation. In contrast, it has recently been suggested that intense field ionization may be accompanied by a two-stage `shake-up' reaction. Here we report a unique combination of experimental techniques that enables us to accurately measure the tunnel ionization probability for argon exposed to 50 femtosecond laser pulses. Most significantly for the current study, this measurement is independent of the optical focal geometry, equivalent to a homogenous electric field. Furthermore, circularly-polarized radiation negates recollision. The present measurements indicate that tunnel ionization results in simultaneous excitation of one or more remaining electrons through shake-up. From an atomic physics standpoint, it may be possible to induce ionization from specific states, and will influence the development of coherent attosecond XUV radiation sources. Such pulses have vital scientific and economic potential in areas such as high-resolution imaging of in-vivo cells and nanoscale XUV lithography.Comment: 17 pages, 4 figures, original format as accepted by Nature Physic

GEICO (Spanish Group for Investigation on Ovarian Cancer) treatment guidelines in ovarian cancer 2012

In 2006, under the auspices of The Spanish Research Group for Ovarian Cancer (Spanish initials GEICO), the first “Treatment Guidelines in Ovarian Cancer” were developed and then published in Clinical and Translational Oncology by Poveda Velasco et al. (Clin Transl Oncol 9(5):308–316, 2007). Almost 6 years have elapsed and over this time, we have seen some important developments in the treatment of ovarian cancer. Significant changes were also introduced after the GCIG-sponsored 4th Consensus Conference on Ovarian Cancer by Stuart et al. (Int J Gynecol Cancer 21:750–755, 2011). So we decided to update the treatment guidelines in ovarian cancer and, with this objective, a group of investigators of the GEICO group met in February 2012. This study summarizes the presentations, discussions and evidence that were reviewed during the meeting and during further discussions of the manuscript

Parps: Rapidly Evolving Weapons in the War against Viral Infection

Post-translational protein modifications such as phosphorylation and ubiquitinylation are common molecular targets of conflict between viruses and their hosts. However, the role of other post-translational modifications, such as ADP-ribosylation, in host-virus interactions is less well characterized. ADP-ribosylation is carried out by proteins encoded by the PARP (also called ARTD) gene family. The majority of the 17 human PARP genes are poorly characterized. However, one PARP protein, PARP13/ZAP, has broad antiviral activity and has evolved under positive (diversifying) selection in primates. Such evolution is typical of domains that are locked in antagonistic 'arms races' with viral factors. To identify additional PARP genes that may be involved in host-virus interactions, we performed evolutionary analyses on all primate PARP genes to search for signatures of rapid evolution. Contrary to expectations that most PARP genes are involved in 'housekeeping' functions, we found that nearly one-third of PARP genes are evolving under strong recurrent positive selection. We identified a >300 amino acid disordered region of PARP4, a component of cytoplasmic vault structures, to be rapidly evolving in several mammalian lineages, suggesting this region serves as an important host-pathogen specificity interface. We also found positive selection of PARP9, 14 and 15, the only three human genes that contain both PARP domains and macrodomains. Macrodomains uniquely recognize, and in some cases can reverse, protein mono-ADP-ribosylation, and we observed strong signatures of recurrent positive selection throughout the macro-PARP macrodomains. Furthermore, PARP14 and PARP15 have undergone repeated rounds of gene birth and loss during vertebrate evolution, consistent with recurrent gene innovation. Together with previous studies that implicated several PARPs in immunity, as well as those that demonstrated a role for virally encoded macrodomains in host immune evasion, our evolutionary analyses suggest that addition, recognition and removal of ADP-ribosylation is a critical, underappreciated currency in host-virus conflicts

A Second-Generation Device for Automated Training and Quantitative Behavior Analyses of Molecularly-Tractable Model Organisms

A deep understanding of cognitive processes requires functional, quantitative analyses of the steps leading from genetics and the development of nervous system structure to behavior. Molecularly-tractable model systems such as Xenopus laevis and planaria offer an unprecedented opportunity to dissect the mechanisms determining the complex structure of the brain and CNS. A standardized platform that facilitated quantitative analysis of behavior would make a significant impact on evolutionary ethology, neuropharmacology, and cognitive science. While some animal tracking systems exist, the available systems do not allow automated training (feedback to individual subjects in real time, which is necessary for operant conditioning assays). The lack of standardization in the field, and the numerous technical challenges that face the development of a versatile system with the necessary capabilities, comprise a significant barrier keeping molecular developmental biology labs from integrating behavior analysis endpoints into their pharmacological and genetic perturbations. Here we report the development of a second-generation system that is a highly flexible, powerful machine vision and environmental control platform. In order to enable multidisciplinary studies aimed at understanding the roles of genes in brain function and behavior, and aid other laboratories that do not have the facilities to undergo complex engineering development, we describe the device and the problems that it overcomes. We also present sample data using frog tadpoles and flatworms to illustrate its use. Having solved significant engineering challenges in its construction, the resulting design is a relatively inexpensive instrument of wide relevance for several fields, and will accelerate interdisciplinary discovery in pharmacology, neurobiology, regenerative medicine, and cognitive science

Cox process representation and inference for stochastic reaction-diffusion processes

Complex behaviour in many systems arises from the stochastic interactions of spatially distributed particles or agents. Stochastic reaction-diffusion processes are widely used to model such behaviour in disciplines ranging from biology to the social sciences, yet they are notoriously difficult to simulate and calibrate to observational data. Here we use ideas from statistical physics and machine learning to provide a solution to the inverse problem of learning a stochastic reaction-diffusion process from data. Our solution relies on a non-trivial connection between stochastic reaction-diffusion processes and spatio-temporal Cox processes, a well-studied class of models from computational statistics. This connection leads to an efficient and flexible algorithm for parameter inference and model selection. Our approach shows excellent accuracy on numeric and real data examples from systems biology and epidemiology. Our work provides both insights into spatio-temporal stochastic systems, and a practical solution to a long-standing problem in computational modelling

Chemotaxis

Push–pull networks, in which two antagonistic enzymes control the activity of a messenger protein, are ubiquitous in signal transduction pathways. A classical example is the chemotaxis system of the bacterium Escherichia coli, in which the kinase CheA and the phosphatase CheZ regulate the phosphorylation level of themessenger protein CheY. Recent experiments suggest that both the kinase and the phosphatase are localized at the receptor cluster, and Vaknin and Berg recently demonstrated that the spatial distribution of the phosphatase canmarkedly affect the dose–response curves. We argue, usingmathematical modeling, that the canonical model of the chemotaxis network cannot explain the experimental observations of Vaknin and Berg. We present a newmodel, in which a small fraction of the phosphatase is localized at the receptor cluster, while the remainder freely diffuses in the cytoplasm; moreover, the phosphatase at the cluster has a higher binding affinity for the messenger protein and a higher catalytic activity than the phosphatase in the cytoplasm. This model is consistent with a large body of experimental data and can explain many of the experimental observations of Vaknin and Berg. More generally, the combination of differential affinity and catalytic activity provides a generic mechanism for amplifying signals that could be exploited in other two-component signaling systems. If this model is correct, then a number of recent modeling studies, which aim to explain the chemotactic gain in terms of the activity of the receptor cluster, should be reconsidered