Simulating the WFIRST coronagraph Integral Field Spectrograph

A primary goal of direct imaging techniques is to spectrally characterize the atmospheres of planets around other stars at extremely high contrast levels. To achieve this goal, coronagraphic instruments have favored integral field spectrographs (IFS) as the science cameras to disperse the entire search area at once and obtain spectra at each location, since the planet position is not known a priori. These spectrographs are useful against confusion from speckles and background objects, and can also help in the speckle subtraction and wavefront control stages of the coronagraphic observation. We present a software package, the Coronagraph and Rapid Imaging Spectrograph in Python (crispy) to simulate the IFS of the WFIRST Coronagraph Instrument (CGI). The software propagates input science cubes using spatially and spectrally resolved coronagraphic focal plane cubes, transforms them into IFS detector maps and ultimately reconstructs the spatio-spectral input scene as a 3D datacube. Simulated IFS cubes can be used to test data extraction techniques, refine sensitivity analyses and carry out design trade studies of the flight CGI-IFS instrument. crispy is a publicly available Python package and can be adapted to other IFS designs.Comment: 15 page

Living with severe allergy: an Anaphylaxis Campaign national survey of young people

<p>Abstract</p> <p>Background</p> <p>The transition to adulthood can be particularly challenging for young people with severe allergies, who must learn to balance personal safety with independent living. Information and support for young people and their families are crucial to successfully managing this transition. We sought to: gather insights into the impact of severe allergies on the lives of young people; explore where young people go for information about anaphylaxis and what information they want and need; identify areas where further support is needed.</p> <p>Methods</p> <p>An online questionnaire survey of young people aged 15–25 years with severe allergies in the United Kingdom (UK) was conducted on behalf of the Anaphylaxis Campaign, the main patient support organisation. Participants were recruited mainly from the Anaphylaxis Campaign membership database and also via allergy clinics and social media. The study was funded by the Anaphylaxis Campaign’s In Memoriam Fund.</p> <p>Results</p> <p>A total of 520 young people responded to the survey. The majority had lived with severe allergies since they were young children; 59% reported having attended Accident and Emergency units as a consequence of their allergies. Only 66% of respondents reported always carrying their epinephrine auto-injectors; only 23% had ever used these. Few were currently receiving specialist allergy care; younger respondents were more likely to be under specialist care (34%) than those 18 years and above (23%). Respondents wanted more information about eating out (56%), travelling (54%) and food labelling (43%). Almost a quarter of respondents (23%) reported needing more information on managing their allergies independently without parental help. Managing allergies in the context of social relationships was a concern for 22% of respondents.</p> <p>Conclusions</p> <p>This survey has identified the information and support needs and gaps in service provision for young people with severe allergies. Healthcare professionals and patient support organisations, with the support of the food industry, can help to meet these needs.</p

Immunohistochemical assessment of protein phosphorylation state: the dream and the reality

The development of phosphorylation state-specific antibodies (PSSAs) in the 1980s, and their subsequent proliferation promised to enable in situ analysis of the activation states of complex intracellular signaling networks. The extent to which this promise has been fulfilled is the topic of this review. I review some applications of PSSAs primarily in the assessment of solid tumor signaling pathway activation status. PSSAs have received considerable attention for their potential to reveal cell type-specific activation status, provide added prognostic information, aid in the prediction of response to therapy, and most recently, demonstrate the efficacy of kinase-targeted chemotherapies. However, despite some successes, many studies have failed to demonstrate added value of PSSAs over general antibody immunohistochemistry. Moreover, there is still a large degree of uncertainty about the interpretation of complex and heterogeneous staining patterns in tissue samples and their relationship to the actual phosphorylation states in vivo. The next phase of translational research in applications of PSSAs will entail the hard work of antibody validation, gathering of detailed information about epitope-specific lability, and implementation of methods for standardization

Altered Neural and Behavioral Dynamics in Huntington's Disease: An Entropy Conservation Approach

Background: Huntington’s disease (HD) is an inherited condition that results in neurodegeneration of the striatum, the forebrain structure that processes cortical information for behavioral output. In the R6/2 transgenic mouse model of HD, striatal neurons exhibit aberrant firing patterns that are coupled with reduced flexibility in the motor system. The aim of this study was to test the patterns of unpredictability in brain and behavior in wild-type (WT) and R6/2 mice. Methodology/Principal Findings: Striatal local field potentials (LFP) were recorded from 18 WT and 17 R6/2 mice (aged 8– 11 weeks) while the mice were exploring a plus-shaped maze. We targeted LFP activity for up to 2 s before and 2 s after each choice-point entry. Approximate Entropy (ApEn) was calculated for LFPs and Shannon Entropy was used to measure the probability of arm choice, as well as the likelihood of making consecutive 90-degree turns in the maze. We found that although the total number of choice-point crossings and entropy of arm-choice probability was similar in both groups, R6/2 mice had more predictable behavioral responses (i.e., were less likely to make 90-degree turns and perform them in alternation with running straight down the same arm), while exhibiting more unpredictable striatal activity, as indicated by higher ApEn values. In both WT and R6/2 mice, however, behavioral unpredictability was negatively correlated with LFP ApEn. Conclusions/Significance: HD results in a perseverative exploration of the environment, occurring in concert with mor

Environmental Determinants of Infectious Disease: A Framework for Tracking Causal Links and Guiding Public Health Research

BACKGROUND: Discoveries that emerging and re-emerging pathogens have their origin in environmental change has created an urgent need to understand how these environmental changes impact disease burden. In this article we present a framework that provides a context from which to examine the relationship between environmental changes and disease transmission and a structure from which to unite disparate pieces of information from a variety of disciplines. METHODS: The framework integrates three interrelated characteristics of environment–disease relationships: a) Environmental change manifests in a complex web of ecologic and social factors that may ultimately impact disease; these factors are represented as those more distally related and those more proximally related to disease. b) Transmission dynamics of infectious pathogens mediate the effects that environmental changes have on disease. c) Disease burden is the outcome of the interplay between environmental change and the transmission cycle of a pathogen. RESULTS: To put this framework into operation, we present a matrix formulation as a means to define important elements of this system and to summarize what is known and unknown about the these elements and their relationships. The framework explicitly expresses the problem at a systems level that goes beyond the traditional risk factor analysis used in public health, and the matrix provide

De novo insertions and deletions of predominantly paternal origin are associated with autism spectrum disorder

Whole-exome sequencing (WES) studies have demonstrated the contribution of de novo loss-of-function single-nucleotide variants (SNVs) to autism spectrum disorder (ASD). However, challenges in the reliable detection of de novo insertions and deletions (indels) have limited inclusion of these variants in prior analyses. By applying a robust indel detection method to WES data from 787 ASD families (2,963 individuals), we demonstrate that de novo frameshift indels contribute to ASD risk (OR= 1.6; 95% CI= 1.0-2.7; p= 0.03), are more common in female probands (p= 0.02), are enriched among genes encoding FMRP targets (p= 6× 10-9), and arise predominantly on the paternal chromosome (p< 0.001). On the basis of mutation rates in probands versus unaffected siblings, we conclude that de novo frameshift indels contribute to risk in approximately 3% of individuals with ASD. Finally, by observing clustering of mutations in unrelated probands, we uncover two ASD-associated genes: KMT2E (MLL5), a chromatin regulator, and RIMS1, a regulator of synaptic vesicle release

SIMS: A Hybrid Method for Rapid Conformational Analysis

Proteins are at the root of many biological functions, often performing complex tasks as the result of large changes in their structure. Describing the exact details of these conformational changes, however, remains a central challenge for computational biology due the enormous computational requirements of the problem. This has engendered the development of a rich variety of useful methods designed to answer specific questions at different levels of spatial, temporal, and energetic resolution. These methods fall largely into two classes: physically accurate, but computationally demanding methods and fast, approximate methods. We introduce here a new hybrid modeling tool, the Structured Intuitive Move Selector (SIMS), designed to bridge the divide between these two classes, while allowing the benefits of both to be seamlessly integrated into a single framework. This is achieved by applying a modern motion planning algorithm, borrowed from the field of robotics, in tandem with a well-established protein modeling library. SIMS can combine precise energy calculations with approximate or specialized conformational sampling routines to produce rapid, yet accurate, analysis of the large-scale conformational variability of protein systems. Several key advancements are shown, including the abstract use of generically defined moves (conformational sampling methods) and an expansive probabilistic conformational exploration. We present three example problems that SIMS is applied to and demonstrate a rapid solution for each. These include the automatic determination of ﾑﾑactiveﾒﾒ residues for the hinge-based system Cyanovirin-N, exploring conformational changes involving long-range coordinated motion between non-sequential residues in Ribose- Binding Protein, and the rapid discovery of a transient conformational state of Maltose-Binding Protein, previously only determined by Molecular Dynamics. For all cases we provide energetic validations using well-established energy fields, demonstrating this framework as a fast and accurate tool for the analysis of a wide range of protein flexibility problems

FimL Regulates cAMP Synthesis in Pseudomonas aeruginosa

Pseudomonas aeruginosa, a ubiquitous bacteria found in diverse ecological niches, is an important cause of acute infections in immunocompromised individuals and chronic infections in patients with Cystic Fibrosis. One signaling molecule required for the coordinate regulation of virulence factors associated with acute infections is 3′, 5′-cyclic adenosine monophosphate, (cAMP), which binds to and activates a catabolite repressor homolog, Vfr. Vfr controls the transcription of many virulence factors, including those associated with Type IV pili (TFP), the Type III secretion system (T3SS), the Type II secretion system, flagellar-mediated motility, and quorum sensing systems. We previously identified FimL, a protein with histidine phosphotransfer-like domains, as a regulator of Vfr-dependent processes, including TFP-dependent motility and T3SS function. In this study, we carried out genetic and physiologic studies to further define the mechanism of action of FimL. Through a genetic screen designed to identify suppressors of FimL, we found a putative cAMP-specific phosphodiesterase (CpdA), suggesting that FimL regulates cAMP levels. Inactivation of CpdA increases cAMP levels and restores TFP-dependent motility and T3SS function to fimL mutants, consistent with in vivo phosphodiesterase activity. By constructing combinations of double and triple mutants in the two adenylate cyclase genes (cyaA and cyaB), fimL, and cpdA, we show that ΔfimL mutants resemble ΔcyaB mutants in TM defects, decreased T3SS transcription, and decreased cAMP levels. Similar to some of the virulence factors that they regulate, we demonstrate that CyaB and FimL are polarly localized. These results reveal new complexities in the regulation of diverse virulence pathways associated with acute P. aeruginosa infections

A chemical survey of exoplanets with ARIEL

Thousands of exoplanets have now been discovered with a huge range of masses, sizes and orbits: from rocky Earth-like planets to large gas giants grazing the surface of their host star. However, the essential nature of these exoplanets remains largely mysterious: there is no known, discernible pattern linking the presence, size, or orbital parameters of a planet to the nature of its parent star. We have little idea whether the chemistry of a planet is linked to its formation environment, or whether the type of host star drives the physics and chemistry of the planet’s birth, and evolution. ARIEL was conceived to observe a large number (~1000) of transiting planets for statistical understanding, including gas giants, Neptunes, super-Earths and Earth-size planets around a range of host star types using transit spectroscopy in the 1.25–7.8 μm spectral range and multiple narrow-band photometry in the optical. ARIEL will focus on warm and hot planets to take advantage of their well-mixed atmospheres which should show minimal condensation and sequestration of high-Z materials compared to their colder Solar System siblings. Said warm and hot atmospheres are expected to be more representative of the planetary bulk composition. Observations of these warm/hot exoplanets, and in particular of their elemental composition (especially C, O, N, S, Si), will allow the understanding of the early stages of planetary and atmospheric formation during the nebular phase and the following few million years. ARIEL will thus provide a representative picture of the chemical nature of the exoplanets and relate this directly to the type and chemical environment of the host star. ARIEL is designed as a dedicated survey mission for combined-light spectroscopy, capable of observing a large and well-defined planet sample within its 4-year mission lifetime. Transit, eclipse and phase-curve spectroscopy methods, whereby the signal from the star and planet are differentiated using knowledge of the planetary ephemerides, allow us to measure atmospheric signals from the planet at levels of 10–100 part per million (ppm) relative to the star and, given the bright nature of targets, also allows more sophisticated techniques, such as eclipse mapping, to give a deeper insight into the nature of the atmosphere. These types of observations require a stable payload and satellite platform with broad, instantaneous wavelength coverage to detect many molecular species, probe the thermal structure, identify clouds and monitor the stellar activity. The wavelength range proposed covers all the expected major atmospheric gases from e.g. H2O, CO2, CH4 NH3, HCN, H2S through to the more exotic metallic compounds, such as TiO, VO, and condensed species. Simulations of ARIEL performance in conducting exoplanet surveys have been performed – using conservative estimates of mission performance and a full model of all significant noise sources in the measurement – using a list of potential ARIEL targets that incorporates the latest available exoplanet statistics. The conclusion at the end of the Phase A study, is that ARIEL – in line with the stated mission objectives – will be able to observe about 1000 exoplanets depending on the details of the adopted survey strategy, thus confirming the feasibility of the main science objectives.Peer reviewedFinal Published versio