Assessment of Emergency Medicine Resident Performance in an Adult Simulation Using a Multisource Feedback Approach.

Introduction: The Accreditation Council for Graduate Medical Education (ACGME) specifically notes multisource feedback (MSF) as a recommended means of resident assessment in the emergency medicine (EM) Milestones. High-fidelity simulation is an environment wherein residents can receive MSF from various types of healthcare professionals. Previously, the Queen\u27s Simulation Assessment Tool (QSAT) has been validated for faculty to assess residents in five categories: assessment; diagnostic actions; therapeutic actions; interpersonal communication, and overall assessment. We sought to determine whether the QSAT could be used to provide MSF using a standardized simulation case. Methods: Prospectively after institutional review board approval, residents from a dual ACGME/osteopathic-approved postgraduate years (PGY) 1-4 EM residency were consented for participation. We developed a standardized resuscitation after overdose case with specific 1-5 Likert anchors used by the QSAT. A PGY 2-4 resident participated in the role of team leader, who completed a QSAT as self-assessment. The team consisted of a PGY-1 peer, an emergency medical services (EMS) provider, and a nurse. Two core faculty were present to administer the simulation case and assess. Demographics were gathered from all participants completing QSATs. We analyzed QSATs by each category and on cumulative score. Hypothesis testing was performed using intraclass correlation coefficients (ICC), with 95% confidence intervals. Interpretation of ICC results was based on previously published definitions. Results: We enrolled 34 team leader residents along with 34 nurses. A single PGY-1, a single EMS provider and two faculty were also enrolled. Faculty provided higher cumulative QSAT scores than the other sources of MSF. QSAT scores did not increase with team leader PGY level. ICC for inter-rater reliability for all sources of MSF was 0.754 (0.572-0.867). Removing the self-evaluation scores increased inter-rater reliability to 0.838 (0.733-0.910). There was lesser agreement between faculty and nurse evaluations than from the EMS or peer evaluation. Conclusion: In this single-site cohort using an internally developed simulation case, the QSAT provided MSF with excellent reliability. Self-assessment decreases the reliability of the MSF, and our data suggest self-assessment should not be a component of MSF. Use of the QSAT for MSF may be considered as a source of data for clinical competency committees

Rapid Divergence of Predator Functional Traits Affects Prey Composition in Aquatic Communities

AbstractIdentifying traits that underlie variation in individual performance of consumers (i.e., trait utility) can help reveal the ecological causes of population divergence and the subsequent consequences for species interactions and community structure. Here, we document a case of rapid divergence (over the past 100 generations, or ?150 years) in foraging traits and feeding efficiency between a lake and stream population pair of threespine stickleback. Building on predictions from functional trait models of fish feeding, we analyzed foraging experiments with a Bayesian path analysis and elucidated the traits explaining variation in foraging performance and the species composition of ingested prey. Despite extensive previous research on the divergence of foraging traits among populations and ecotypes of stickleback, our results provide novel experimental evidence of trait utility for jaw protrusion, gill raker length, and gill raker spacing when foraging on a natural zooplankton assemblage. Furthermore, we discuss how these traits might contribute to the differential effects of lake and stream stickleback on their prey communities, observed in both laboratory and mesocosm conditions. More generally, our results illustrate how the rapid divergence of functional foraging traits of consumers can impact the biomass, species composition, and trophic structure of prey communities

Bis(guanidinium) chloranilate

The asymmetric unit of the title co-crystal, 2CH6N3 +·C6Cl2O4 2−, contains one half of a chloranilate anion and one guanidinium cation, which are connected by strong N—H⋯O hydrogen bonds into a two-dimensional network

Social identity, social networks and recovery capital in emerging adulthood: a pilot study

Background It has been argued that recovery from substance dependence relies on a change in identity, with past research focused on ‘personal identity’. This study assessed support for a social identity model of recovery in emerging adults through examining associations between social identity, social networks, recovery capital, and quality of life. Methods Twenty participants aged 18–21 in residential treatment for substance misuse were recruited from four specialist youth drug treatment services - three detoxification facilities and one psychosocial rehabilitation facility in Victoria, Australia. Participants completed a detailed social network interview exploring the substance use of groups in their social networks and measures of quality of life, recovery capital, and social identity. Results Lower group substance use was associated with higher recovery capital, stronger identification with non-using groups, and greater importance of non-using groups in the social network. Additionally, greater identification with and importance of non-using groups were associated with better environmental quality of life, whereas greater importance conferred on using groups was associated with reduced environmental quality of life. Conclusions Support was found for the role of social identity processes in reported recovery capital and quality of life. Future research in larger, longitudinal samples is required to improve understanding of social identity processes during treatment and early recovery and its relationship to recovery stability. Keywords Social network Social identity Emerging adult Substance use Treatment Recovery Quality of lif

Quantifying measures to limit wind driven resuspension of sediments for improvement of the ecological quality in some shallow Dutch lakes

Although phosphorus loadings are considered the main pressure for most shallow lakes, wind-driven resuspension can cause additional problems for these aquatic ecosystems. We quantified the potential effectiveness of measures to reduce the contribution of resuspended sediments, resulting from wind action, to the overall light attenuation for three comparable shallow peat lakes with poor ecological status in the Netherlands: Loosdrecht, Nieuwkoop, and Reeuwijk (1.8–2.7 m depth, 1.6–2.5 km fetch). These measures are: 1. wave reducing barriers, 2. water level fluctuations, 3. capping of the sediment with sand, and 4. combinations of above. Critical shear stress of the sediments for resuspension (Vcrit), size distribution, and optical properties of the suspended material were quantified in the field (June 2009) and laboratory. Water quality monitoring data (2002–2009) showed that light attenuation by organic suspended matter in all lakes is high. Spatial modeling of the impact of these measures showed that in Lake Loosdrecht limiting wave action can have significant effects (reductions from 6% exceedance to 2% exceedance of Vcrit), whereas in Lake Nieuwkoop and Lake Reeuwijk this is less effective. The depth distribution and shape of Lake Nieuwkoop and Lake Reeuwijk limit the role of wind-driven resuspension in the total suspended matter concentration. Although the lakes are similar in general appearance (origin, size, and depth range) measures suitable to improve their ecological status differ. This calls for care when defining the programme of measures to improve the ecological status of a specific lake based on experience from other lakes.

Characterization of a Low-Cost Optical Flow Sensor When Using an External Laser as a Direct Illumination Source

In this paper, a low cost optical flow sensor is combined with an external laser device to measure surface displacements and mechanical oscillations. The measurement system is based on applying coherent light to a diffuser surface and using an optical flow sensor to analyze the reflected and transferred light to estimate the displacement of the surface or the laser spot. This work is focused on the characterization of this measurement system, which can have the optical flow sensor placed at different angles and distances from the diffuser surface. The results have shown that the displacement of the diffuser surface is badly estimated when the optical mouse sensor is placed in front of the diffuser surface (angular orientation >150°) while the highest sensitivity is obtained when the sensor is located behind the diffuser surface and on the axis of the laser source (angular orientation 0°). In this case, the coefficient of determination of the measured displacement, R2, was very high (>0.99) with a relative error of less than 1.29%. Increasing the distance between the surface and the sensor also increased the sensitivity which increases linearly, R2 = 0.99. Finally, this measurement setup was proposed to measure very low frequency mechanical oscillations applied to the laser device, up to 0.01 Hz in this work. The results have shown that increasing the distance between the surface and the optical flow sensor also increases the sensitivity and the measurement range

Deconstructing the lesbian, gay, bisexual, transgender victim of sex trafficking: Harm, exceptionality and religion–sexuality tensions

Contrary to widespread belief, sex trafficking also targets lesbian, gay, bisexual, transgender (LGBT) communities. Contemporary social and political constructions of victimhood lie at the heart of regulatory policies on sex trafficking. Led by the US Department of State, knowledge about LGBT victims of trafficking constitutes the newest frontier in the expansion of criminalization measures. These measures represent a crucial shift. From a burgeoning range of preemptive measures enacted to protect an amorphous class of ‘all potential victims’, now policies are heavily premised on the risk posed by traffickers to ‘victims of special interest’. These constructed identities, however, are at odds with established structures. Drawing on a range of literatures, the core task of this article is to confront some of the complexities and tensions surrounding constructions of LGBT trafficking victims. Specifically, the article argues that discourses of ‘exceptional vulnerability’ and the polarized notions of ‘innocence’ and ‘guilt’ inform hierarchies of victimhood. Based on these insights, the article argues for the need to move beyond monolithic understandings of victims, by reframing the politics of harm accordingly

imPlatelet classifier: image-converted RNA biomarker profiles enable blood-based cancer diagnostics

Liquid biopsies offer a minimally invasive sample collection, outperforming traditional biopsies employed for cancer evaluation. The widely used material is blood, which is the source of tumor-educated platelets. Here, we developed the imPlatelet classifier, which converts RNA-sequenced platelet data into images in which each pixel corresponds to the expression level of a certain gene. Biological knowledge from the Kyoto Encyclopedia of Genes and Genomes was also implemented to improve accuracy. Images obtained from samples can then be compared against standard images for specific cancers to determine a diagnosis. We tested imPlatelet on a cohort of 401 non-small cell lung cancer patients, 62 sarcoma patients, and 28 ovarian cancer patients. imPlatelet provided excellent discrimination between lung cancer cases and healthy controls, with accuracy equal to 1 in the independent dataset. When discriminating between noncancer cases and sarcoma or ovarian cancer patients, accuracy equaled 0.91 or 0.95, respectively, in the independent datasets. According to our knowledge, this is the first study implementing an image-based deep-learning approach combined with biological knowledge to classify human samples. The performance of imPlatelet considerably exceeds previously published methods and our own alternative attempts of sample discrimination. We show that the deep-learning image-based classifier accurately identifies cancer, even when a limited number of samples are available.publishedVersio