Hercules X-1: Empirical Models of UV Emission Lines

The UV emission lines of Hercules X-1, resolved with the HST GHRS and STIS, can be divided into broad (FWHM 750 km/s) and narrow (FWHM 150 km/s) components. The broad lines can be unambiguously identified with emission from an accretion disk which rotates prograde with the orbit. The narrow lines, previously identified with the X-ray illuminated atmosphere of the companion star, are blueshifted at both phi=0.2 and phi=0.8 and the line flux at phi=0.2 is 0.2 of the flux at phi=0.8. Line ratio diagnostics show that the density of the narrow line region is log n=13.4+/-0.2 and the temperature is T=1.0+/-0.2x10^5 K. The symmetry of the eclipse ingress suggests that the line emission on the surface of the disk is left-right symmetric relative to the orbit. Model fits to the O V, Si IV, and He II line profiles agree with this result, but fits to the N V lines suggest that the receding side of the disk is brighter. We note that there are narrow absorption components in the N V lines with blueshifts of 500 km/s.Comment: To be published in the Astrophysical Journa

Efficacy and safety of ipratropium bromide/albuterol compared with albuterol in patients with moderate-to-severe asthma: a randomized controlled trial

Abstract Background Many patients with asthma require frequent rescue medication for acute symptoms despite appropriate controller therapies. Thus, determining the most effective relief regimen is important in the management of more severe asthma. This study’s objective was to evaluate whether ipratropium bromide/albuterol metered-dose inhaler (CVT-MDI) provides more effective acute relief of bronchospasm in moderate-to-severe asthma than albuterol hydrofluoroalkaline (ALB-HFA) alone after 4 weeks. Methods In this double-blind, crossover study, patients who had been diagnosed with asthma for ≥1 year were randomized to two sequences of study medication “as needed” for symptom relief (1–7 day washout before second 4-week treatment period): CVT-MDI/ALB-HFA or ALB-HFA/CVT-MDI. On days 1 and 29 of each sequence, 6-hour serial spirometry was performed after administration of the study drug. Co-primary endpoints were FEV 1 area under the curve (AUC 0–6 ) and peak (post-dose) forced expiratory volume in 1 s (FEV 1 ) response (change from test day baseline) after 4 weeks. The effects of “as needed” treatment with ALB-HFA/CVT-MDI were analyzed using mixed effect model repeated measures (MMRM). Results A total of 226 patients, ≥18 years old, with inadequately controlled, moderate-to-severe asthma were randomized. The study met both co-primary endpoints demonstrating a statistically significant treatment benefit of CVT-MDI versus ALB-HFA. FEV 1 AUC 0-6h response was 167 ml for ALB-HFA, 252 ml for CVT-MDI (p <0.0001); peak FEV 1 response was 357 ml for ALB-HFA, 434 ml for CVT-MDI (p <0.0001). Adverse events were comparable across groups. Conclusions CVT-MDI significantly improved acute bronchodilation over ALB-HFA alone after 4 weeks of “as-needed” use for symptom relief, with a similar safety profile. This suggests additive bronchodilator effects of β 2 -agonist and anticholinergic treatment in moderate-to-severe, symptomatic asthma. Trial registration ClinicalTrials.gov No.: NCT00818454; Registered November 16, 2009

Snooping Around: Observation Planning for the Signals of Opportunity P-Band Investigation (SNOOPI)

Launching October 2022, the SigNals Of Opportunity P-band Investigation (SNOOPI) is a 6U CubeSat dedicated to demonstrating spaceborne remote sensing of root zone soil moisture and snow water equivalent using signals of opportunity. P-band (240-500 MHz) frequencies are required to penetrate dense vegetation or snow and into the top 200 cm of soil, but this band is heavily subscribed. Rather than transmitting its own signal SNOOPI will observe reflected signals from the U.S. Navy’s Mobile User Objective System satellites. This makes planning observations challenging. The point of reflection is a function of both the transmitter and receiver satellite positions as well as terrain. The direct signal must be observed simultaneously on the same antenna pattern with sufficient gain. Ionospheric delay must also be accounted for. To satisfy these requirements and maintain a cadence of one observation per day, the SNOOPI science operations center at Purdue University has developed custom software for scheduling activities onboard the satellite. The software is highly automated, involving the user only in the definition of observation targets, priorities, and giving final approval to the proposed schedule. Orbit, attitude, power, communication, memory, and observation constraints are handled by a combination of linear programming and pattern search optimization methods. The purpose of this paper is to describe the challenges of scheduling observations for a signals of opportunity mission and illustrate how they were solved for SNOOPI

[¹⁸F]FDG PET/CT Signal Correlates with Neoangiogenesis Markers in Patients with Fibrotic Interstitial Lung Disease Who Underwent Lung Biopsy: Implication for the Use of PET/CT in Diffuse Lung Diseases

The use of [¹⁸F]FDG PET/CT as a biomarker in diffuse lung diseases is increasingly recognized. We investigated the correlation between [¹⁸F]FDG uptake with histologic markers on lung biopsy of patients with fibrotic interstitial lung disease (fILD). // Methods: We recruited 18 patients with fILD awaiting lung biopsy for [¹⁸F]FDG PET/CT. We derived a target-to-background ratio (TBR) of maximum pulmonary uptake of [¹⁸F]FDG (SUVₘₐₓ) divided by the lung background (SUVₘᵢₙ). Consecutive paraffin-embedded lung biopsy sections were immunostained for alveolar and interstitial macrophages (CD68), microvessel density (MVD) (CD31 and CD105/endoglin), and glucose transporter 1. MVD was expressed as vessel area percentage per high-power field (Va%/hpf). Differences in imaging and angiogenesis markers between histologic usual interstitial pneumonia (UIP) and non-UIP were assessed using a nonparametric Mann–Whitney test. Correlation of imaging with angiogenesis markers was assessed using the nonparametric Spearman rank correlation. Univariate Kaplan–Meier survival analysis assessed the difference in the survival curves for each of the angiogenesis markers (separated by their respective optimal cutoff) using the log-rank test. Statistical analysis was performed using SPSS. // Results: In total, 18 patients were followed for an average of 41.36 mo (range, 5.69–132.46 mo; median, 30.07 mo). Only CD105 MVD showed a significantly positive correlation with [¹⁸F]FDG TBR (Spearman rank correlation, 0.556; P < 0.05, n = 13). There was no correlation between [¹⁸F]FDG uptake and macrophage expression of glucose transporter 1. CD105 and CD31 were higher for UIP than for non-UIP, with CD105 reaching statistical significance (P = 0.011). In all patients, MVD assessed with either CD105 or CD31 quantification on biopsy predicted overall survival. Patients with CD105 MVD of less than 12 Va%/hpf or CD31 MVD of less than 35 Va%/hpf had a significantly better prognosis (no deaths during follow-up in the case of CD105) than did patients with higher scores of CD105 MVD (median survival, 35 mo; P = 0.041, n = 13) or CD31 MVD (median survival, 28 mo; P = 0.014, n = 13). // Conclusion: Previous work has used [¹⁸F]FDG uptake in PET/CT as a biomarker in fILD. Here, we highlight a correlation between angiogenesis and [¹⁸F]FDG TBR. We show that MVD is higher for UIP than for non-UIP and is associated with mortality in patients with fILD. These data set the scene to investigate the potential role of vasculature and angiogenesis in fibrosis

Computational Protein Design to Re-Engineer Stromal Cell-Derived Factor-1α (SDF) Generates an Effective and Translatable Angiogenic Polypeptide Analog

BACKGROUND: Experimentally, exogenous administration of recombinant stromal cell-derived factor-1α (SDF) enhances neovasculogenesis and cardiac function after myocardial infarction. Smaller analogs of SDF may provide translational advantages including enhanced stability and function, ease of synthesis, lower cost, and potential modulated delivery via engineered biomaterials. In this study, computational protein design was used to create a more efficient evolution of the native SDF protein. METHODS AND RESULTS: Protein structure modeling was used to engineer an SDF polypeptide analog (engineered SDF analog [ESA]) that splices the N-terminus (activation and binding) and C-terminus (extracellular stabilization) with a diproline segment designed to limit the conformational flexibility of the peptide backbone and retain the relative orientation of these segments observed in the native structure of SDF. Endothelial progenitor cells (EPCs) in ESA gradient, assayed by Boyden chamber, showed significantly increased migration compared with both SDF and control gradients. EPC receptor activation was evaluated by quantification of phosphorylated AKT, and cells treated with ESA yielded significantly greater phosphorylated AKT levels than SDF and control cells. Angiogenic growth factor assays revealed a distinct increase in angiopoietin-1 expression in the ESA- and SDF-treated hearts. In addition, CD-1 mice (n=30) underwent ligation of the left anterior descending coronary artery and peri-infarct intramyocardial injection of ESA, SDF-1α, or saline. At 2 weeks, echocardiography demonstrated a significant gain in ejection fraction, cardiac output, stroke volume, and fractional area change in mice treated with ESA compared with controls. CONCLUSIONS: Compared with native SDF, a novel engineered SDF polypeptide analog (ESA) more efficiently induces EPC migration and improves post-myocardial infarction cardiac function and thus offers a more clinically translatable neovasculogenic therapy

Towards a Post-Graduate Level Curriculum for Biodiversity Informatics. Perspectives from the Global Biodiversity Information Facility (GBIF) Community

Biodiversity informatics is a new and evolving field, requiring efforts to develop capacity and a curriculum for this field of science. The main objective was to summarise the level of activity and the efforts towards developing biodiversity informatics curricula, for work-based training and/or academic teaching at universities, taking place within the Global Biodiversity Information Facility (GBIF) countries and its associated network. A survey approach was used to identify existing capacities and resources within the network. Most of GBIF Nodes survey respondents (80%) are engaged in onsite training activities, with a focus on work-based professionals, mostly researchers, policy-makers and students. Training topics include data mobilisation, digitisation, management, publishing, analysis and use, to enable the accessibility of analogue and digital biological data that currently reside as scattered datasets. An initial assessment of academic teaching activities highlighted that countries in most regions, to varying degrees, were already engaged in the conceptualisation, development and/or implementation of formal academic programmes in biodiversity informatics, including programmes in Benin, Colombia, Costa Rica, Finland, France, India, Norway, South Africa, Sweden, Taiwan and Togo. Digital e-learning platforms were an important tool to help build capacity in many countries. In terms of the potential in the Nodes network, 60% expressed willingness to be recruited or commissioned for capacity enhancement purposes. Contributions and activities of various country nodes across the network have been highlighted and a working curriculum framework has been defined. © 2021. Parker-Allie F et al. This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are creditedPeer reviewe

Evaluation of machine learning algorithms and structural features for optimal MRI-based diagnostic prediction in psychosis

A relatively large number of studies have investigated the power of structural magnetic resonance imaging (sMRI) data to discriminate patients with schizophrenia from healthy controls. However, very few of them have also included patients with bipolar disorder, allowing the clinically relevant discrimination between both psychotic diagnostics. To assess the efficacy of sMRI data for diagnostic prediction in psychosis we objectively evaluated the discriminative power of a wide range of commonly used machine learning algorithms (ridge, lasso, elastic net and L0 norm regularized logistic regressions, a support vector classifier, regularized discriminant analysis, random forests and a Gaussian process classifier) on main sMRI features including grey and white matter voxel-based morphometry (VBM), vertex-based cortical thickness and volume, region of interest volumetric measures and wavelet-based morphometry (WBM) maps. All possible combinations of algorithms and data features were considered in pairwise classifications of matched samples of healthy controls (N = 127), patients with schizophrenia (N = 128) and patients with bipolar disorder (N = 128). Results show that the selection of feature type is important, with grey matter VBM (without data reduction) delivering the best diagnostic prediction rates (averaging over classifiers: schizophrenia vs. healthy 75%, bipolar disorder vs. healthy 63% and schizophrenia vs. bipolar disorder 62%) whereas algorithms usually yielded very similar results. Indeed, those grey matter VBM accuracy rates were not even improved by combining all feature types in a single prediction model. Further multi-class classifications considering the three groups simultaneously made evident a lack of predictive power for the bipolar group, probably due to its intermediate anatomical features, located between those observed in healthy controls and those found in patients with schizophrenia. Finally, we provide MRIPredict (https://www.nitrc.org/projects/mripredict/), a free tool for SPM, FSL and R, to easily carry out voxelwise predictions based on VBM images

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