Building Cultural Competency among Emerging Public Health Professionals: Student Experiences in Panama

One of the prerequisite skills of effective public health and health practitioners is cultural competency. Cultural competency, however, requires a deep and profound understanding of individuals who are shaped by different life experiences than one’s own. Previous authors have described study abroad and service-learning as established strategies for enhancing cultural competency among emerging health professionals. This article describes how students made meaning of an international study abroad experience in Panama through analysis of student-produced work including reflective journal entries, blog posts, and photo journaling. In summer 2019, 13 undergraduate and graduate students participated in a four-week travel course to explore the complex and interrelated concepts of population health, health equity, and social determinants of health. Through visits to clinics and health facilities as well as service-learning activities, students identified strengths and challenges to health and health care in Panama. Furthermore, interactions with health officials and community members encouraged students to challenge their own biases and assumptions, which is a first step towards developing cultural competency. Despite the short duration of this travel course, instructors used intentional pre-departure activities and readings as well as daily reflective essays to scaffold student learning. Moreover, reflective writing assignments provided students an outlet to record their observations of external expressions of culture (i.e., customs, rituals, styles) and internal expressions of culture (i.e., attitudes, habits, norms) and discuss their relevance in terms of health behaviors. This level of deep reflection compelled students to engage more fully in their own learning experience

Modeling peer effect modification by network strength: The diffusion of implantable cardioverter defibrillators in the US hospital network

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/154422/1/sim8466.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/154422/2/sim8466_am.pd

The Global academic research organization network: Data sharing to cure diseases and enable learning health systems.

Introduction:Global data sharing is essential. This is the premise of the Academic Research Organization (ARO) Council, which was initiated in Japan in 2013 and has since been expanding throughout Asia and into Europe and the United States. The volume of data is growing exponentially, providing not only challenges but also the clear opportunity to understand and treat diseases in ways not previously considered. Harnessing the knowledge within the data in a successful way can provide researchers and clinicians with new ideas for therapies while avoiding repeats of failed experiments. This knowledge transfer from research into clinical care is at the heart of a learning health system. Methods:The ARO Council wishes to form a worldwide complementary system for the benefit of all patients and investigators, catalyzing more efficient and innovative medical research processes. Thus, they have organized Global ARO Network Workshops to bring interested parties together, focusing on the aspects necessary to make such a global effort successful. One such workshop was held in Austin, Texas, in November 2017. Representatives from Japan, Taiwan, Singapore, Europe, and the United States reported on their efforts to encourage data sharing and to use research to inform care through learning health systems. Results:This experience report summarizes presentations and discussions at the Global ARO Network Workshop held in November 2017 in Austin, TX, with representatives from Japan, Korea, Singapore, Taiwan, Europe, and the United States. Themes and recommendations to progress their efforts are explored. Standardization and harmonization are at the heart of these discussions to enable data sharing. In addition, the transformation of clinical research processes through disruptive innovation, while ensuring integrity and ethics, will be key to achieving the ARO Council goal to overcome diseases such that people not only live longer but also are healthier and happier as they age. Conclusions:The achievement of global learning health systems will require further exploration, consensus-building, funding aligned with incentives for data sharing, standardization, harmonization, and actions that support global interests for the benefit of patients

Determining eigenstates and thermal states on a quantum computer using quantum imaginary time evolution

The accurate computation of Hamiltonian ground, excited and thermal states on quantum computers stands to impact many problems in the physical and computer sciences, from quantum simulation to machine learning. Given the challenges posed in constructing large-scale quantum computers, these tasks should be carried out in a resource-efficient way. In this regard, existing techniques based on phase estimation or variational algorithms display potential disadvantages; phase estimation requires deep circuits with ancillae, that are hard to execute reliably without error correction, while variational algorithms, while flexible with respect to circuit depth, entail additional high-dimensional classical optimization. Here, we introduce the quantum imaginary time evolution and quantum Lanczos algorithms, which are analogues of classical algorithms for finding ground and excited states. Compared with their classical counterparts, they require exponentially less space and time per iteration, and can be implemented without deep circuits and ancillae, or high-dimensional optimization. We furthermore discuss quantum imaginary time evolution as a subroutine to generate Gibbs averages through an analogue of minimally entangled typical thermal states. Finally, we demonstrate the potential of these algorithms via an implementation using exact classical emulation as well as through prototype circuits on the Rigetti quantum virtual machine and Aspen-1 quantum processing unit

Determining eigenstates and thermal states on a quantum computer using quantum imaginary time evolution

The accurate computation of Hamiltonian ground, excited, and thermal states on quantum computers stands to impact many problems in the physical and computer sciences, from quantum simulation to machine learning. Given the challenges posed in constructing large-scale quantum computers, these tasks should be carried out in a resource-efficient way. In this regard, existing techniques based on phase estimation or variational algorithms display potential disadvantages; phase estimation requires deep circuits with ancillae, that are hard to execute reliably without error correction, while variational algorithms, while flexible with respect to circuit depth, entail additional high-dimensional classical optimization. Here, we introduce the quantum imaginary time evolution and quantum Lanczos algorithms, which are analogues of classical algorithms for finding ground and excited states. Compared to their classical counterparts, they require exponentially less space and time per iteration, and can be implemented without deep circuits and ancillae, or high-dimensional optimization. We furthermore discuss quantum imaginary time evolution as a subroutine to generate Gibbs averages through an analog of minimally entangled typical thermal states. Finally, we demonstrate the potential of these algorithms via an implementation using exact classical emulation as well as through prototype circuits on the Rigetti quantum virtual machine and Aspen-1 quantum processing unit.Comment: 18 pages, 7 figures; improved figures and tex

Dissecting the impact of environment, season and genotype on blackcurrant fruit quality traits.

This work aims to determine the effect of genotype x environment (GxE) interaction that influence blackcurrant (Ribes nigrum) fruit quality. We applied metabolomics-driven analysis on fruits from four cultivars grown in contrasting European-locations over two seasons. By integrating metabolomics and sensory analysis, we also defined specific metabolic signatures associated with consumer acceptance. Our results showed that rainfall is a crucial factor associated with accumulation of delphinidin- and cyanidin-3-O-glucoside, the two mayor blackcurrant pigments meanwhile temperature affects the main organic acid levels which can be decisive for fruit taste. Sensorial analysis showed that increases in terpenoid and acetate ester volatiles were strongly associated with higher appreciation score, while proacacipetalin, a cyanogenic-glycoside, was positively associated to bitter taste. Our results pave the way for the selection of high-quality cultivars and suitable production sites for blackcurrant cultivation.publishedVersio

Efficacy of Infection Control Interventions in Reducing the Spread of Multidrug-Resistant Organisms in the Hospital Setting

Multidrug-resistant organisms (MDRO) continue to spread in hospitals globally, but the population-level impact of recommended preventive strategies and the relative benefit of individual strategies targeting all MDRO in the hospital setting are unclear. To explore the dynamics of MDRO transmission in the hospital, we develop a model extending data from clinical individual-level studies to quantify the impact of hand hygiene, contact precautions, reducing antimicrobial exposure and screening surveillance cultures in decreasing the prevalence of MDRO colonization and infection. The effect of an ongoing increase in the influx of patients colonized with MDRO into the hospital setting is also quantified. We find that most recommended strategies have substantial effect in decreasing the prevalence of MDRO over time. However, screening for asymptomatic MDRO colonization among patients who are not receiving antimicrobials is of minimal value in reducing the spread of MDRO

The Impact of Different Antibiotic Regimens on the Emergence of Antimicrobial-Resistant Bacteria

Backgroud: The emergence and ongoing spread of antimicrobial-resistant bacteria is a major public health threat. Infections caused by antimicrobial-resistant bacteria are associated with substantially higher rates of morbidity and mortality compared to infections caused by antimicrobial-susceptible bacteria. The emergence and spread of these bacteria is complex and requires incorporating numerous interrelated factors which clinical studies cannot adequately address. Methods/Principal Findings: A model is created which incorporates several key factors contributing to the emergence and spread of resistant bacteria including the effects of the immune system, acquisition of resistance genes and antimicrobial exposure. The model identifies key strategies which would limit the emergence of antimicrobial-resistant bacterial strains. Specifically, the simulations show that early initiation of antimicrobial therapy and combination therapy with two antibiotics prevents the emergence of resistant bacteria, whereas shorter courses of therapy and sequential administration of antibiotics promote the emergence of resistant strains. Conclusions/Significance: The principal findings suggest that (i) shorter lengths of antibiotic therapy and early interruption of antibiotic therapy provide an advantage for the resistant strains, (ii) combination therapy with two antibiotics prevents the emergence of resistance strains in contrast to sequential antibiotic therapy, and (iii) early initiation of antibiotics is among the most important factors preventing the emergence of resistant strains. These findings provide new insights into strategies aimed at optimizing the administration of antimicrobials for the treatment of infections and the prevention of the emergence of antimicrobial resistance

SNAPSHOT USA 2019 : a coordinated national camera trap survey of the United States

This article is protected by copyright. All rights reserved.With the accelerating pace of global change, it is imperative that we obtain rapid inventories of the status and distribution of wildlife for ecological inferences and conservation planning. To address this challenge, we launched the SNAPSHOT USA project, a collaborative survey of terrestrial wildlife populations using camera traps across the United States. For our first annual survey, we compiled data across all 50 states during a 14-week period (17 August - 24 November of 2019). We sampled wildlife at 1509 camera trap sites from 110 camera trap arrays covering 12 different ecoregions across four development zones. This effort resulted in 166,036 unique detections of 83 species of mammals and 17 species of birds. All images were processed through the Smithsonian's eMammal camera trap data repository and included an expert review phase to ensure taxonomic accuracy of data, resulting in each picture being reviewed at least twice. The results represent a timely and standardized camera trap survey of the USA. All of the 2019 survey data are made available herein. We are currently repeating surveys in fall 2020, opening up the opportunity to other institutions and cooperators to expand coverage of all the urban-wild gradients and ecophysiographic regions of the country. Future data will be available as the database is updated at eMammal.si.edu/snapshot-usa, as well as future data paper submissions. These data will be useful for local and macroecological research including the examination of community assembly, effects of environmental and anthropogenic landscape variables, effects of fragmentation and extinction debt dynamics, as well as species-specific population dynamics and conservation action plans. There are no copyright restrictions; please cite this paper when using the data for publication.Publisher PDFPeer reviewe

A hymenopterists' guide to the hymenoptera anatomy ontology: utility, clarification, and future directions

Hymenoptera exhibit an incredible diversity of phenotypes, the result of ~240 million years of evolution and the primary subject of more than 250 years of research. Here we describe the history, development, and utility of the Hymenoptera Anatomy Ontology (HAO) and its associated applications. These resourc¬es are designed to facilitate accessible and extensible research on hymenopteran phenotypes. Outreach with the hymenopterist community is of utmost importance to the HAO project, and this paper is a direct response to questions that arose from project workshops. In a concerted attempt to surmount barriers of understanding, especially regarding the format, utility, and development of the HAO, we discuss the roles of homology, “preferred terms”, and “structural equivalency”. We also outline the use of Universal Resource Identifiers (URIs) and posit that they are a key element necessary for increasing the objectivity and repeatability of science that references hymenopteran anatomy. Pragmatically, we detail a mechanism (the “URI table”) by which authors can use URIs to link their published text to the HAO, and we describe an associated tool (the “Analyzer”) to derive these tables. These tools, and others, are available through the HAO Portal website (http://portal.hymao.org). We conclude by discussing the future of the HAO with respect to digital publication, cross-taxon ontology alignment, the advent of semantic phenotypes, and community-based curation.Katja C. Seltmann... Andrew D. Austin... John T. Jennings... et al