Strong UV and X-ray variability of the Narrow Line Seyfert 1 Galaxy WPVS 007 -- on the nature of the X-ray low state

We report on multi-wavelength observations of the X-ray transient Narrow Line Seyfert 1 (NLS1) galaxy WPVS 007. The galaxy was monitored with Swift between October 2005 and July 2013, after it had undergone a dramatic drop in its X-ray flux earlier. For the first time, we are able to repeatedly detect this NLS1 in X-rays again. This increased number of detections in the last couple of years may suggest that the strong absorber that has been found in this AGN is starting to become leaky, and may eventually disappear. The X-ray spectra obtained for WPVS 007 are all consistent with a partial covering absorber model. A spectrum based on the data during the extreme low X-ray flux states shows that the absorption column density is of the order of 4 x 10^23 cm^-2 with a covering fraction of 95%. WPVS 007 also displays one of the strongest UV variabilities seen in Narrow Line Seyfert 1s. The UV continuum variability anti-correlates with the optical/UV slope alpha-UV which suggests that the variability primarily may be due to reddening. The UV variability time scales are consistent with moving dust `clouds' located beyond the dust sublimation radius of approximately 20 ld. We present for the first time near infrared JHK data of WPVS 007, which reveal a rich emission-line spectrum. Recent optical spectroscopy does not indicate significant variability in the broad and FeII emission lines, implying that the ionizing continuum seen by those gas clouds has not significantly changed over the last decades. All X-ray and UV observations are consistent with a scenario in which an evolving Broad Absorption Line (BAL) flow obscures the continuum emission. As such, WPVS 007 is an important target for our understanding of BAL flows in low-mass active galactic nuclei (AGN).Comment: Accepted for publications in the Astronomical Journal; 29 pages, 10 Figures, 7 Table

Longitudinal Assessment of Cortical Excitability in Children and Adolescents With Mild Traumatic Brain Injury and Persistent Post-concussive Symptoms

Introduction: Symptoms following a mild traumatic brain injury (mTBI) usually resolve quickly but may persist past 3 months in up to 15% of children. Mechanisms of mTBI recovery are poorly understood, but may involve alterations in cortical neurophysiology. Transcranial Magnetic Stimulation (TMS) can non-invasively investigate such mechanisms, but the time course of neurophysiological changes in mTBI are unknown.Objective/Hypothesis: To determine the relationship between persistent post-concussive symptoms (PPCS) and altered motor cortex neurophysiology over time.Methods: This was a prospective, longitudinal, controlled cohort study comparing children (8–18 years) with mTBI (symptomatic vs. asymptomatic) groups to controls. Cortical excitability was measured using TMS paradigms at 1 and 2 months post injury. The primary outcome was the cortical silent period (cSP). Secondary outcomes included short interval intracortical inhibition (SICI) and facilitation (SICF), and long-interval cortical inhibition (LICI). Generalized linear mixed model analyses were used to evaluate the effect of group and time on neurophysiological parameters.Results: One hundred seven participants (median age 15.1, 57% female) including 78 (73%) with symptomatic PPCS and 29 with asymptomatic mTBI, were compared to 26 controls. Cortical inhibition (cSP and SICI) was reduced in the symptomatic group compared to asymptomatic group and tended to increase over time. Measures of cortical facilitation (SICF and ICF) were increased in the asymptomatic group and decreased over time. TMS was well tolerated with no serious adverse events.Conclusions: TMS-assessed cortical excitability is altered in children following mild TBI and is dependent on recovery trajectory. Our findings support delayed return to contact sports in children even where clinical symptoms have resolved

Medical Grade Water Generation for Intravenous Fluid Production on Exploration Missions

This document describes the intravenous (IV) fluids requirements for medical care during NASA s future Exploration class missions. It further discusses potential methods for generating such fluids and the challenges associated with different fluid generation technologies. The current Exploration baseline mission profiles are introduced, potential medical conditions described and evaluated for fluidic needs, and operational issues assessed. Conclusions on the fluid volume requirements are presented, and the feasibility of various fluid generation options are discussed. A separate report will document a more complete trade study on the options to provide the required fluids.At the time this document was developed, NASA had not yet determined requirements for medical care during Exploration missions. As a result, this study was based on the current requirements for care onboard the International Space Station (ISS). While we expect that medical requirements will be different for Exploration missions, this document will provide a useful baseline for not only developing hardware to generate medical water for injection (WFI), but as a foundation for meeting future requirements. As a final note, we expect WFI requirements for Exploration will be higher than for ISS care, and system capacity may well need to be higher than currently specified

The effect of wave conditions and surfer ability on performance and the physiological response of recreational surfers.

This study investigated the effects of wave conditions on performance and the physiological responses of surfers. After institutional ethical approval 39 recreational surfers participated in 60 surfing sessions where performance and physiological response were measured using global positioning system (GPS) heart rate monitors. Using GPS, the percentage time spent in surfing activity categories was on average 41.6, 47.0, 8.1, and 3.1% for waiting, paddling, riding, and miscellaneous activities, respectively. Ability level of the surfers, wave size, and wave period are significantly associated with the physiological, ride, and performance parameters during surfing. As the ability level of the surfers increases there is a reduction in the relative exercise intensity (e.g., average heart rate as a percentage of laboratory maximum, rpartial = -0.412, p < 0.01) which is in contrast to increases in performance parameters (e.g., maximum ride speed (0.454, p < 0.01). As the wave size increased there were reductions in physiological demand (e.g., total energy expenditure rpartial = -0.351, p ≤ 0.05) but increases in ride speed and distance measures (e.g., the maximum ride speed, 0.454, p < 0.01). As the wave period increased there were increases in intensity (e.g., average heart rate as a percentage of laboratory maximum, rp = 0.490, p < 0.01) and increases in ride speed and distance measures (e.g., the maximum ride speed, rpartial = 0.371, p < 0.01). This original study is the first to show that wave parameters and surfer ability are significantly associated with the physiological response and performance characteristics of surfing

Enabling scalable clinical interpretation of ML-based phenotypes using real world data

The availability of large and deep electronic healthcare records (EHR) datasets has the potential to enable a better understanding of real-world patient journeys, and to identify novel subgroups of patients. ML-based aggregation of EHR data is mostly tool-driven, i.e., building on available or newly developed methods. However, these methods, their input requirements, and, importantly, resulting output are frequently difficult to interpret, especially without in-depth data science or statistical training. This endangers the final step of analysis where an actionable and clinically meaningful interpretation is needed.This study investigates approaches to perform patient stratification analysis at scale using large EHR datasets and multiple clustering methods for clinical research. We have developed several tools to facilitate the clinical evaluation and interpretation of unsupervised patient stratification results, namely pattern screening, meta clustering, surrogate modeling, and curation. These tools can be used at different stages within the analysis. As compared to a standard analysis approach, we demonstrate the ability to condense results and optimize analysis time. In the case of meta clustering, we demonstrate that the number of patient clusters can be reduced from 72 to 3 in one example. In another stratification result, by using surrogate models, we could quickly identify that heart failure patients were stratified if blood sodium measurements were available. As this is a routine measurement performed for all patients with heart failure, this indicated a data bias. By using further cohort and feature curation, these patients and other irrelevant features could be removed to increase the clinical meaningfulness. These examples show the effectiveness of the proposed methods and we hope to encourage further research in this field.Comment: 27 pages, 14 figure

Improving Community Advisory Board Engagement In Precision Medicine Research To Reduce Health Disparities

Community Advisory Boards (CABs) are used in efforts to reduce health disparities; however, there is little documentation in the literature regarding their use in precision medicine research. In this case study, an academic-CAB partnership developed a questionnaire and patient educational materials for two precision smoking cessation interventions that involved use of genetic information. The community-engaged research (CEnR) literature provided a framework for enhancing benefits to CAB members involved in developing research documents for use with a low-income, ethnically diverse population of smokers. The academic partners integrated three CEnR strategies: 1) in-meeting statements acknowledging their desire to learn from community partners, 2) in-meeting written feedback to and from community partners, and 3) a survey to obtain CAB member feedback post-meetings. Strategies 1 and 2 yielded modifications to pertinent study materials, as well as suggestions for improving meeting operations that were then adopted, as appropriate, by the academic partners. The survey indicated that CAB members valued the meeting procedure changes which appeared to have contributed to improvements in attendance and satisfaction with the meetings. Further operationalization of relevant partnership constructs and development of tools for measuring these aspects of community-academic partnerships is warranted to support community engagement in precision medicine research studies

Cardiorespiratory Fitness, Alcohol Intake, and Metabolic Syndrome Incidence in Men

Purpose To prospectively examine the independent and joint effects of alcohol consumption and cardiorespiratory fitness on the incidence of metabolic syndrome in a cohort of men. Methods A prospective examination of 3,411 apparently healthy men at baseline, who came to the Cooper Clinic (Dallas, Texas) for at least 2 preventive visits (1979–2010). Primary exposure variables were cardiorespiratory fitness and alcohol intake; the outcome measure was metabolic syndrome (MetS) and the components thereof. Cox proportional hazard models were computed to assess the relationship between the exposure variables and the incidence of MetS while adjusting for confounders. Results Over a mean follow-up period of 9 years (SD=7.8), 276 men developed MetS. In multivariable analysis, a dose-response relationship was observed between increased levels of fitness and reduced MetS risk (moderate fitness: HR=0.60, 95%CI 0.43–0.82; high fitness: HR=0.49, 95%CI 0.35–0.69). When examining the independent effects of alcohol, light drinking increased the risk for MetS by 66% (HR=1.66, 95%CI 1.11–2.48). No statistically significant interaction effect was observed between alcohol and fitness in relation to MetS (P = 0.32). When assessing the relation between each exposure and the components of MetS, higher fitness consistently reduced the risk of all components; whereas lower alcohol intake reduced the risk of elevated glucose and blood pressure and increased the risk for low HDL-c. Conclusions Among this cohort of men, higher fitness levels reduced the risk for MetS and its components. The relation between alcohol intake levels and metabolic risk was more complex and not reflected when examining MetS as a whole