Modeling \u3ci\u3eEscherichia coli\u3c/i\u3e in the Missouri River near Omaha, Nebraska, 2012–16

The city of Omaha, Nebraska, has a combined sewer system in some areas of the city. In Omaha, Nebr., a moderate amount of rainfall will lead to the combination of stormwater and untreated sewage or wastewater being discharged directly into the Missouri River and Papillion Creek and is called a combined sewer overflow (CSO) event. In 2009, the city of Omaha began the implementation of their Long Term Control Plan (LTCP) to mitigate the effects of CSOs on the Missouri River and Papillion Creek. As part of the LTCP, the city partnered with the U.S. Geological Survey (USGS) in 2012 to begin monitoring in the Missouri River. Since 2012, monthly discrete water-quality samples for many constituents have been collected from the Missouri River at four sites. At 3 of the 4 sites, water quality has been monitored continuously for selected constituents and physical properties. These discrete water-quality samples and continuous water-quality monitoring data (from July 2012 to 2020) have been collected to better understand the water quality of the Missouri River, how it is changing with time, how it changes upstream from the city of Omaha to downstream, and how it varies during base-flow conditions and during periods of runoff. The purpose of this report is to document the development of Escherichia coli (E. coli) concentration models for these four Missouri River sites. Analysis was completed using the first 5 years of data (through 2016) to determine if the current approach is sufficient to meet future analysis goals and to understand if proposed models such as Load Estimator (LOADEST) models will be able to represent water-quality changes in the Missouri River. Multiple linear regression models were developed to estimate E. coli concentration using LOADEST as implemented in the rloadest package in the R statistical software program. A set of explanatory variables, including streamflow and streamflow anomalies, precipitation, information about CSOs, and continuous water quality, were evaluated for potential inclusion in regression models. The best model at Missouri River at NP Dodge Park at Omaha, Nebr. (USGS station 412126095565201; hereafter “NP Dodge”) included basin explanatory variables of upstream antecedent precipitation index measured at Tekamah, Nebr.; decimal time; season; and turbidity. The best model at Missouri River at Freedom Park Omaha, Nebr. (USGS station 411636095535401; hereafter “Freedom Park”) included the same explanatory variables as the NP Dodge model with the addition of turbidity anomalies and flow anomalies. The best models at the two downstream sites (Missouri River near Council Bluffs, Iowa, USGS station 06610505 and Missouri River near La Platte, Nebr., USGS station 410333095530101) included the same explanatory variables as the Freedom Park model with the addition of local antecedent precipitation index as measured at Eppley Airport in Omaha, Nebr., and additional turbidity and flow anomalies. The final selected models were the best models given our modeling design constraint in which explanatory variables included in the model for the upstream site were included in the downstream models. Explanatory variables currently (2020) being collected and included in the selected models through 2016 explained 64–75 percent of the variability of E. coli concentration in the Missouri River. Explaining 64–75 percent of the variability might be considered low when working with physical constituents (total nitrogen or sediment), but with the natural variability of biological constituents such as E. coli, the uncertainty of E. coli laboratory measurements, and the added complexity of modeling in a large drainage basin with multiple sources, these results are adequate and indicate that the explanatory variables being collected and models such as LOADEST can represent water-quality changes in the Missouri River for E. coli concentration from 2012 to 2016

Cloud optical depth retrievals from the Aerosol Robotic Network (AERONET) cloud mode observations

Cloud optical depth is one of the most poorly observed climate variables. The new “cloud mode” capability in the Aerosol Robotic Network (AERONET) will inexpensively yet dramatically increase cloud optical depth observations in both number and accuracy. Cloud mode optical depth retrievals from AERONET were evaluated at the Atmospheric Radiation Measurement program’s Oklahoma site in sky conditions ranging from broken clouds to overcast. For overcast cases, the 1.5 min average AERONET cloud mode optical depths agreed to within 15% of those from a standard ground‐based flux method. For broken cloud cases, AERONET retrievals also captured rapid variations detected by the microwave radiometer. For 3 year climatology derived from all nonprecipitating clouds, AERONET monthly mean cloud optical depths are generally larger than cloud radar retrievals because of the current cloud mode observation strategy that is biased toward measurements of optically thick clouds. This study has demonstrated a new way to enhance the existing AERONET infrastructure to observe cloud optical properties on a global scale

Can We Really Prevent Suicide?

Every year, suicide is among the top 20 leading causes of death globally for all ages. Unfortunately, suicide is difficult to prevent, in large part because the prevalence of risk factors is high among the general population. In this review, clinical and psychological risk factors are examined and methods for suicide prevention are discussed. Prevention strategies found to be effective in suicide prevention include means restriction, responsible media coverage, and general public education, as well identification methods such as screening, gatekeeper training, and primary care physician education. Although the treatment for preventing suicide is difficult, follow-up that includes pharmacotherapy, psychotherapy, or both may be useful. However, prevention methods cannot be restricted to the individual. Community, social, and policy interventions will also be essentia

Status of the LUX Dark Matter Search

The Large Underground Xenon (LUX) dark matter search experiment is currently being deployed at the Homestake Laboratory in South Dakota. We will highlight the main elements of design which make the experiment a very strong competitor in the field of direct detection, as well as an easily scalable concept. We will also present its potential reach for supersymmetric dark matter detection, within various timeframes ranging from 1 year to 5 years or more.Comment: 4 pages, in proceedings of the SUSY09 conferenc

Topology of the pore-region of a K+ channel revealed by the NMR-derived structures of scorpion toxins

AbstractThe architecture of the pore-region of a voltage-gated K+ channel, Kv1.3, was probed using four high affinity scorpion toxins as molecular calipers. We established the structural relatedness of these toxins by solving the structures of kaliotoxin and margatoxin and comparing them with the published structure of charybdotoxin; a homology model of noxiustoxin was then developed. Complementary mutagenesis of Kv1.3 and these toxins, combined with electrostatic compliance and thermodynamic mutant cycle analyses, allowed us to identify multiple toxin-challel interactions. Our analyses reveals the existence of a shallow vestibule at the external entrance to the pore. This vestibule is ∼28−32A˚wide at its outer margin, ∼28−34A˚wide at its base, and ∼4−8A˚deep. The pore is 9–14A˚wide at its external entrance and tapers to a width of 4–5A˚at a depth of ∼5−7A˚from the vestibule. This structural information should directly aid in developing topological models of the pores of related ion channels and facilitate therapeutic drug design

Concepts émergents dans le référentiel de compétences CanMEDS pour les médecins

Background: The CanMEDS physician competency framework will be updated in 2025. The revision occurs during a time of disruption and transformation to society, healthcare, and medical education caused by the COVID-19 pandemic and growing acknowledgement of the impacts of colonialism, systemic discrimination, climate change, and emerging technologies on healthcare and training. To inform this revision, we sought to identify emerging concepts in the literature related to physician competencies. Methods: Emerging concepts were defined as ideas discussed in the literature related to the roles and competencies of physicians that are absent or underrepresented in the 2015 CanMEDS framework. We conducted a literature scan, title and abstract review, and thematic analysis to identify emerging concepts. Metadata for all articles published in five medical education journals between October 1, 2018 and October 1, 2021 were extracted. Fifteen authors performed a title and abstract review to identify and label underrepresented concepts. Two authors thematically analyzed the results to identify emerging concepts. A member check was conducted. Results: 1017 of 4973 (20.5%) of the included articles discussed an emerging concept. The thematic analysis identified ten themes: Equity, Diversity, Inclusion, and Social Justice; Anti-racism; Physician Humanism; Data-Informed Medicine; Complex Adaptive Systems; Clinical Learning Environment; Virtual Care; Clinical Reasoning; Adaptive Expertise; and Planetary Health. All themes were endorsed by the authorship team as emerging concepts. Conclusion: This literature scan identified ten emerging concepts to inform the 2025 revision of the CanMEDS physician competency framework. Open publication of this work will promote greater transparency in the revision process and support an ongoing dialogue on physician competence. Writing groups have been recruited to elaborate on each of the emerging concepts and how they could be further incorporated into CanMEDS 2025.Contexte : Le référentiel de compétences CanMEDS pour les médecins sera mis à jour en 2025. Cette révision intervient à un moment où la société, les soins de santé et l’enseignement médical sont bouleversés et en pleine mutation à cause de la pandémie de la COVID-19; on est aussi à l’heure où l’on reconnaît de plus en plus les effets du colonialisme, de la discrimination systémique, des changements climatiques et des nouvelles technologies sur les soins de santé et la formation des médecins. Pour éclairer cette révision, nous avons tenté d’extraire de la littérature scientifique les concepts émergents se rapportant aux compétences des médecins. Méthodes : Les concepts émergents ont été définis comme des idées ayant trait aux rôles et aux compétences des médecins qui sont débattues dans la littérature, mais qui sont absentes ou sous-représentées dans le cadre CanMEDS 2015. Nous avons réalisé une recherche documentaire, un examen des titres et des résumés, et une analyse thématique pour repérer les concepts émergents. Les métadonnées de tous les articles publiés dans cinq revues d’éducation médicale entre le 1er octobre 2018 et le 1er octobre 2021 ont été extraites. Quinze auteurs ont effectué un examen des titres et des résumés pour relever et étiqueter les concepts sous-représentés. Deux auteurs ont procédé à une analyse thématique des résultats pour dégager les concepts émergents. Une vérification a été faite par les membres de l’équipe. Résultats : Parmi les 4973 articles dépouillés, 1017 (20,5 %) abordaient un concept émergent. Les dix thèmes suivants sont ressortis de l’analyse thématique : l’équité, la diversité, l’inclusion et la justice sociale; l’antiracisme; humanisme des médecin; la médecine fondée sur les données; les systèmes adaptatifs complexes; l’environnement de l’apprentissage clinique; les soins virtuels; le raisonnement clinique; l’expertise adaptative; et la santé planétaire. L’ensemble de ces thèmes ont été approuvés comme concepts émergents par l’équipe de rédaction. Conclusion : Cet examen de la littérature a permis de relever dix concepts émergents qui peuvent servir à éclairer la révision du référentiel de compétences CanMEDS pour les médecins qui aura lieu en 2025. La publication en libre accès de ce travail favorisera la transparence du processus de révision et le dialogue continu sur les compétences des médecins. Des groupes de rédaction ont été recrutés pour développer chacun des concepts émergents et pour examiner la façon dont ils pourraient être intégrés dans la version du référentiel CanMEDS de 2025