Herbivory in the previous generation primes plants for enhanced insect resistance.

Inducible defenses, which provide enhanced resistance after initial attack, are nearly universal in plants. This defense signaling cascade is mediated by the synthesis, movement, and perception of jasmonic acid and related plant metabolites. To characterize the long-term persistence of plant immunity, we challenged Arabidopsis (Arabidopsis thaliana) and tomato (Solanum lycopersicum) with caterpillar herbivory, application of methyl jasmonate, or mechanical damage during vegetative growth and assessed plant resistance in subsequent generations. Here, we show that induced resistance was associated with transgenerational priming of jasmonic acid-dependent defense responses in both species, caused caterpillars to grow up to 50% smaller than on control plants, and persisted for two generations in Arabidopsis. Arabidopsis mutants that are deficient in jasmonate perception (coronatine insensitive1) or in the biogenesis of small interfering RNA (dicer-like2 dicer-like3 dicer-like4 and nuclear RNA polymerase d2a nuclear RNA polymerase d2b) do not exhibit inherited resistance. The observation of inherited resistance in both the Brassicaceae and Solanaceae suggests that this trait may be more widely distributed in plants. Epigenetic resistance to herbivory thus represents a phenotypically plastic mechanism for enhanced defense across generations.

"Next-generation" Sequencing (NGS): The new genomic revolution

In the past 5 years "Next-generation" Sequencing (NGS) technologies have transformed genomics by delivering fast, inexpensive and accurate genomeinformation changing the way we think about scientific approaches in basic,applied and clinical research. The inexpensive production of large volumes ofsequence data is the main advantage over the automated Sanger method,making this new technology useful for many applications. In this chapter, a brieftechnical review of NGS technologies is given, along with the keys to NGSsuccess and a broad range of applications for NGS technologies.

Automatic prostate segmentation in cone-beam computed tomography images using rigid registration.

We propose to evaluate automatic three-dimensional gray-value rigid registration (RR) methods for prostate localization on cone-beam computed tomography (CBCT) scans. In total, 103 CBCT scans of 9 prostate patients have been analyzed. Each one was registered to the planning CT scan using different methods: (a) global RR, (b) pelvis bone structure RR, (c) bone RR refined by local soft-tissue RR using the CT clinical target volume (CTV) expanded with a 1, 3, 5, 8, 10, 12, 15 or 20-mm margin. To evaluate results, a radiation oncologist was asked to manually delineate the CTV on the CBCT scans. The Dice coefficients between each automatic CBCT segmentation - derived from the transformation of the manual CT segmentation - and the manual CBCT segmentation were calculated. Global or bone CT/CBCT RR has been shown to yield insufficient results in average. Local RR with an 8-mm margin around the CTV after bone RR was found to be the best candidate for systematically significantly improving prostate localization.

La Generation Sandwich en Suisse Romande: mieux comprendre les facteurs associés avec la santé perçue afin de mieux agir en promotion de la santé [Sandwich Generation in Roman Switzerland : a better understanding of factors linked with perceived health for better acting in health promotion].

The so-called < Sandwich Generation > (SG) is characterized by concurrent and competing professional, familial, and informal caregiving workloads. These stressors pose potential health risks. However, the current knowledge about SG characteristics and perceived state of health are insufficient to allow occupational health nurses to develop evidence-based interventions designed for health promotion. We aimed to describe this population and examine the relationships between these coexisting workloads and their perceived health. This study is based on a descriptive, correlational design. Employees of a Swiss public administration completed an electronic questionnaire. Of 844 respondents, 23 % are SG members. Ages of frailed parents or parents-in-law, co-residence with the latters, children still living at home predict that employees could be members of the SG. Perceived physical health status of SG members is rated better than mental health status. The heterogeneity of SG is reflected in three clusters. Finally, physical health score is the only that differs from the other health scores adjusting for clusters and sex. This study provides a foundation for developing preventive interventions targeting the SG.

Automatic filtering and substantiation of drug safety signals

Drug safety issues pose serious health threats to the population and constitute a major cause of mortality worldwide. Due to the prominent implications to both public health and the pharmaceutical industry, it is of great importance to unravel the molecular mechanisms by which an adverse drug reaction can be potentially elicited. These mechanisms can be investigated by placing the pharmaco-epidemiologically detected adverse drug reaction in an information-rich context and by exploiting all currently available biomedical knowledge to substantiate it. We present a computational framework for the biological annotation of potential adverse drug reactions. First, the proposed framework investigates previous evidences on the drug-event association in the context of biomedical literature (signal filtering). Then, it seeks to provide a biological explanation (signal substantiation) by exploring mechanistic connections that might explain why a drug produces a specific adverse reaction. The mechanistic connections include the activity of the drug, related compounds and drug metabolites on protein targets, the association of protein targets to clinical events, and the annotation of proteins (both protein targets and proteins associated with clinical events) to biological pathways. Hence, the workflows for signal filtering and substantiation integrate modules for literature and database mining, in silico drug-target profiling, and analyses based on gene-disease networks and biological pathways. Application examples of these workflows carried out on selected cases of drug safety signals are discussed. The methodology and workflows presented offer a novel approach to explore the molecular mechanisms underlying adverse drug reactions

Circulating miRNAs: a new generation of anti-doping biomarkers

MicroRNAs (miRNAs) are small non-coding RNAs that regulate a variety of biological processes. Cell-free miRNAs detected in blood plasma are used as specific and sensitive markers of physiological processes and some diseases. Circulating miRNAs are highly stable in body fluids, for example plasma. Therefore, profiles of circulating miRNAs have been investigated for potential use as novel, non-invasive anti-doping biomarkers. This review describes the biological mechanisms underlying the variation of circulating miRNAs, revealing that they have great potential as a new class of biomarker for detection of doping substances. The latest developments in extraction and profiling technology, and the technical design of experiments useful for anti-doping, are also discussed. Longitudinal measurements of circulating miRNAs in the context of the athlete biological passport are proposed as an efficient strategy for the use of these new markers. The review also emphasizes potential challenges for the translation of circulating miRNAs from research into practical anti-doping applications.

Learning form Nature to improve the heat generation of iron-oxide nanoparticles for magnetic hyperthermia applications.

The performance of magnetic nanoparticles is intimately entwined with their structure, mean size and magnetic anisotropy. Besides, ensembles offer a unique way of engineering the magnetic response by modifying the strength of the dipolar interactions between particles. Here we report on an experimental and theoretical analysis of magnetic hyperthermia, a rapidly developing technique in medical research and oncology. Experimentally, we demonstrate that single-domain cubic iron oxide particles resembling bacterial magnetosomes have superior magnetic heating efficiency compared to spherical particles of similar sizes. Monte Carlo simulations at the atomic level corroborate the larger anisotropy of the cubic particles in comparison with the spherical ones, thus evidencing the beneficial role of surface anisotropy in the improved heating power. Moreover we establish a quantitative link between the particle assembling, the interactions and the heating properties. This knowledge opens new perspectives for improved hyperthermia, an alternative to conventional cancer therapies.

Evolutionarily stable learning schedules and cumulative culture in discrete generation models.

Individual learning (e.g., trial-and-error) and social learning (e.g., imitation) are alternative ways of acquiring and expressing the appropriate phenotype in an environment. The optimal choice between using individual learning and/or social learning may be dictated by the life-stage or age of an organism. Of special interest is a learning schedule in which social learning precedes individual learning, because such a schedule is apparently a necessary condition for cumulative culture. Assuming two obligatory learning stages per discrete generation, we obtain the evolutionarily stable learning schedules for the three situations where the environment is constant, fluctuates between generations, or fluctuates within generations. During each learning stage, we assume that an organism may target the optimal phenotype in the current environment by individual learning, and/or the mature phenotype of the previous generation by oblique social learning. In the absence of exogenous costs to learning, the evolutionarily stable learning schedules are predicted to be either pure social learning followed by pure individual learning ("bang-bang" control) or pure individual learning at both stages ("flat" control). Moreover, we find for each situation that the evolutionarily stable learning schedule is also the one that optimizes the learned phenotype at equilibrium.

Generation and nonlinear evolution of shore-oblique/transverse sand bars

The coupling between topography, waves and currents in the surf zone may selforganize to produce the formation of shore-transverse or shore-oblique sand bars on an otherwise alongshore uniform beach. In the absence of shore-parallel bars, this has been shown by previous studies of linear stability analysis, but is now extended to the finite-amplitude regime. To this end, a nonlinear model coupling wave transformation and breaking, a shallow-water equations solver, sediment transport and bed updating is developed. The sediment flux consists of a stirring factor multiplied by the depthaveraged current plus a downslope correction. It is found that the cross-shore profile of the ratio of stirring factor to water depth together with the wave incidence angle primarily determine the shape and the type of bars, either transverse or oblique to the shore. In the latter case, they can open an acute angle against the current (upcurrent oriented) or with the current (down-current oriented). At the initial stages of development, both the intensity of the instability which is responsible for the formation of the bars and the damping due to downslope transport grow at a similar rate with bar amplitude, the former being somewhat stronger. As bars keep on growing, their finite-amplitude shape either enhances downslope transport or weakens the instability mechanism so that an equilibrium between both opposing tendencies occurs, leading to a final saturated amplitude. The overall shape of the saturated bars in plan view is similar to that of the small-amplitude ones. However, the final spacings may be up to a factor of 2 larger and final celerities can also be about a factor of 2 smaller or larger. In the case of alongshore migrating bars, the asymmetry of the longshore sections, the lee being steeper than the stoss, is well reproduced. Complex dynamics with merging and splitting of individual bars sometimes occur. Finally, in the case of shore-normal incidence the rip currents in the troughs between the bars are jet-like while the onshore return flow is wider and weaker as is observed in nature.

Generation of symmetric periodic orbits by a heteroclinic loop formed by two singular points and their invariant manifolds of dimension 1 and 2 in R3

In this paper we will find a continuous of periodic orbits passing near infinity for a class of polynomial vector fields in R3. We consider polynomial vector fields that are invariant under a symmetry with respect to a plane and that possess a “generalized heteroclinic loop” formed by two singular points e+ and e− at infinity and their invariant manifolds � and . � is an invariant manifold of dimension 1 formed by an orbit going from e− to e+, � is contained in R3 and is transversal to . is an invariant manifold of dimension 2 at infinity. In fact, is the 2–dimensional sphere at infinity in the Poincar´e compactification minus the singular points e+ and e−. The main tool for proving the existence of such periodic orbits is the construction of a Poincar´e map along the generalized heteroclinic loop together with the symmetry with respect to .

Dextramers: new generation of fluorescent MHC class I/peptide multimers for visualization of antigen-specific CD8+ T cells.

Direct identification as well as isolation of antigen-specific T cells became possible since the development of "tetramers" based on avidin-fluorochrome conjugates associated with mono-biotinylated class I MHC-peptide monomeric complexes. In principle, a series of distinct class I MHC-peptide tetramers, each labelled with a different fluorochrome, would allow to simultaneously enumerate as many unique antigen-specific CD8(+) T cells. Practically, however, only phycoerythrin and allophycocyanin conjugated tetramers have been generally available, imposing serious constraints for multiple labeling. To overcome this limitation, we have developed dextramers which are multimers based on a dextran backbone bearing multiple fluorescein and streptavidin moieties. Here we demonstrate the functionality and optimization of these new probes on human CD8(+) T cell clones with four independent antigen specificities. Their applications to the analysis of relatively low frequency antigen-specific T cells in peripheral blood, as well as their use in fluorescence microscopy, are demonstrated. The data show that dextramers produce a stronger signal than their fluoresceinated tetramer counterparts. Thus, these could become the reagents of choice as the antigen-specific T cell labeling transitions from basic research to clinical application.

Proof of Concept: Examining Characteristics of Roadway Infrastructure in Various 3D Visualization Modes, 2015

Utilizing enhanced visualization in transportation planning and design gained popularity in the last decade. This work aimed at demonstrating the concept of utilizing a highly immersive, virtual reality simulation engine for creating dynamic, interactive, full-scale, three-dimensional (3D) models of highway infrastructure. For this project, the highway infrastructure element chosen was a two-way, stop-controlled intersection (TWSCI). VirtuTrace, a virtual reality simulation engine developed by the principal investigator, was used to construct the dynamic 3D model of the TWSCI. The model was implemented in C6, which is Iowa State University’s Cave Automatic Virtual Environment (CAVE). Representatives from the Institute of Transportation at Iowa State University, as well as representatives from the Iowa Department of Transportation, experienced the simulated TWSCI. The two teams identified verbally the significant potential that the approach introduces for the application of next-generation simulated environments to road design and safety evaluation.

On the Selection of Non-Invasive Methods Based on Speech Analysis Oriented to Automatic Alzheimer Disease Diagnosis

The work presented here is part of a larger study to identify novel technologies and biomarkers for early Alzheimer disease (AD) detection and it focuses on evaluating the suitability of a new approach for early AD diagnosis by non-invasive methods. The purpose is to examine in a pilot study the potential of applying intelligent algorithms to speech features obtained from suspected patients in order to contribute to the improvement of diagnosis of AD and its degree of severity. In this sense, Artificial Neural Networks (ANN) have been used for the automatic classification of the two classes (AD and control subjects). Two human issues have been analyzed for feature selection: Spontaneous Speech and Emotional Response. Not only linear features but also non-linear ones, such as Fractal Dimension, have been explored. The approach is non invasive, low cost and without any side effects. Obtained experimental results were very satisfactory and promising for early diagnosis and classification of AD patients.

On Automatic Diagnosis of Alzheimer's Disease based on Spontaneous Speech Analysis and Emotional Temperature

Alzheimer's disease is the most prevalent form of progressive degenerative dementia; it has a high socio-economic impact in Western countries. Therefore it is one of the most active research areas today. Alzheimer's is sometimes diagnosed by excluding other dementias, and definitive confirmation is only obtained through a post-mortem study of the brain tissue of the patient. The work presented here is part of a larger study that aims to identify novel technologies and biomarkers for early Alzheimer's disease detection, and it focuses on evaluating the suitability of a new approach for early diagnosis of Alzheimer’s disease by non-invasive methods. The purpose is to examine, in a pilot study, the potential of applying Machine Learning algorithms to speech features obtained from suspected Alzheimer sufferers in order help diagnose this disease and determine its degree of severity. Two human capabilities relevant in communication have been analyzed for feature selection: Spontaneous Speech and Emotional Response. The experimental results obtained were very satisfactory and promising for the early diagnosis and classification of Alzheimer’s disease patients.