Pedagogical foundations of cybercivility in health professions education: a scoping review

Background Teaching cybercivility requires thoughtful attention to curriculum development and content delivery. Theories, models, and conceptual and theoretical frameworks (hereafter “tools”) provide useful foundations for integrating new knowledge and skills into existing professional practice and education. We conducted this scoping review to identify tools used for teaching cybercivility in health professions education. Methods Using Arksey and O’Malley’s scoping review framework, we searched six biomedical and educational databases and three grey literature databases for articles available in English published between January 1, 2000 and March 31, 2020. Following the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews), we screened and extracted relevant data, and reported the results of the search. Results The search resulted in 2272 articles, with 8 articles included in this review after inclusion criteria were applied. Four articles (50%) were peer-reviewed journal papers while the other 4 (50%) were dissertations. Eleven unique tools were identified by this review: (1) Transpersonal Caring Theory, (2) Theory of Workplace Incivility, (3) Conceptualization of Incivility, (4) Media Ecology Theory, (5) Principlism, (6) Salmon’s Five Stage Model of Online Learning, (7) Learner-Centered Educational Theory, (8) Gallant and Drinan’s 4-Stage Model of Institutionalization of Academic Integrity, (9) Theory of Planned Behavior, (10) Communication Privacy Management Theory, and (11) Moral Development Theory. Based on the tools analyzed in our scoping review, we determined three features of cybercivility pedagogy to which the tools provided a guide: (1) behavioral manifestations, (2) academic integrity, and (3) digital professionalism. Conclusions The reviewed tools provide a pedagogical foundation and guidance for teaching various properties of cybercivility. Future studies should be expanded to include a broader literature body and non-English literature to provide the global perspective and global skills needed by a diverse population of learners

Teleological role of L-2-hydroxyglutarate dehydrogenase in the kidney

L-2-hydroxyglutarate (L-2HG) is an oncometabolite found elevated in renal tumors. However, this molecule might have physiological roles that extend beyond its association with cancer, as L-2HG levels are elevated in response to hypoxia and during Drosophila larval development. L-2HG is known to be metabolized by L-2HG dehydrogenase (L2HGDH), and loss of L2HGDH leads to elevated L-2HG levels. Despite L2HGDH being highly expressed in the kidney, its role in renal metabolism has not been explored. Here, we report our findings utilizing a novel CRISPR/Cas9 murine knockout model, with a specific focus on the role of L2HGDH in the kidney. Histologically, L2hgdh knockout kidneys have no demonstrable histologic abnormalities. However, GC-MS metabolomics demonstrates significantly reduced levels of the TCA cycle intermediate succinate in multiple tissues. Isotope labeling studies with [U-13C] glucose demonstrate that restoration of L2HGDH in renal cancer cells (which lowers L-2HG) leads to enhanced incorporation of label into TCA cycle intermediates. Subsequent biochemical studies demonstrate that L-2HG can inhibit the TCA cycle enzyme α-ketoglutarate dehydrogenase. Bioinformatic analysis of mRNA expression data from renal tumors demonstrates that L2HGDH is co-expressed with genes encoding TCA cycle enzymes as well as the gene encoding the transcription factor PGC-1α, which is known to regulate mitochondrial metabolism. Restoration of PGC-1α in renal tumor cells results in increased L2HGDH expression with a concomitant reduction in L-2HG levels. Collectively, our analyses provide new insight into the physiological role of L2HGDH as well as mechanisms that promote L-2HG accumulation in disease states

The Internet as a Small Business E-Commerce Ecosystem.

The purpose of this chapter is to analyse how the ecosystem concept can be applied to small businesses and how the Internet and e-commerce can help SMEs harness the required resources to enhance their competitive performance in the marketplace. The chapter will investigate the wide variety of e-commerce applications that are available to small businesses to help address the issue of limited resources. It will provide an ecosystem map illustrating how each functional area of a small business can utilise Internet e-commerce applications to enhance their resource base. The chapter also explores the opportunities and threats that the e-commerce ecosystem model poses for small, medium-sized enterprises (SMEs). This is based upon empirical research consisting of three focus group interviews undertaken with small and medium-sized retail service firms located in the Herefordshire and Worcestershire regions of the United Kingdom in January–February 2014

Cost analysis of depression using the national insurance system in South Korea: a comparison of depression and treatment-resistant depression

The incidence and burden of depressive disorders are increasing in South Korea. There are many differences between pharmaceutically treated depression (PTD) and treatment-resistant depression (TRD), including the economic consequences; however, to our knowledge, the economic burden of depression is understudied in South Korea. Therefore, the objective of the present study was to calculate the different economic costs of PTD and TRD in South Korea, specifically by comparing several aspects of medical care. This study comprised patients aged 18 and over who were newly prescribed antidepressants for more than 28 days with a depression code included from January 1, 2012, to December 31, 2012, by the Health Insurance Review and Assessment Service (HIRA). TRD was classified as more than two antidepressant regimen failures in PTD patients. The cost was calculated based on the cost reflected on the receipt registered with HIRA. Of the 834,694 patients with PTD, 34,812 patients (4.17%) were converted to TRD. The cost of medical care for TRD (6,610,487 KRW, 5881 USD) was approximately 5 times higher than the cost of non-TRD (1,273,045 KRW, 1133 USD) and was significantly higher for patients with or without depression and suicide codes. Medical expenses incurred by non-psychiatrists were roughly 1.7 times higher than those incurred by psychiatrists. TRD patients had significantly higher healthcare costs than PTD patients. Identifying these financial aspects of care for depression can help to establish a more effective policy to reduce the burden on mentally ill patients.This study was funded by the Janssen Korea Ltd. (RRA-17716), and also confirms that Jansen has the author of the study. Two authors (G.J.C. and M.K.2) and the Janssen Korea contributed for conceptualization, investigation, funding acquisition and wrting original draft. However, the funder (Jansen and its employees) had no possibilities to influence the analyses, interpretation of data and and in writing the manuscript

Synthesis of Novel Double-Layer Nanostructures of SiC–WOxby a Two Step Thermal Evaporation Process

A novel double-layer nanostructure of silicon carbide and tungsten oxide is synthesized by a two-step thermal evaporation process using NiO as the catalyst. First, SiC nanowires are grown on Si substrate and then high density W18O49nanorods are grown on these SiC nanowires to form a double-layer nanostructure. XRD and TEM analysis revealed that the synthesized nanostructures are well crystalline. The growth of W18O49nanorods on SiC nanowires is explained on the basis of vapor–solid (VS) mechanism. The reasonably better turn-on field (5.4 V/μm) measured from the field emission measurements suggest that the synthesized nanostructures could be used as potential field emitters

A Reparametrization Approach for Dynamic Space-Time Models

Researchers in diverse areas such as environmental and health sciences are increasingly working with data collected across space and time. The space-time processes that are generally used in practice are often complicated in the sense that the auto-dependence structure across space and time is non-trivial, often non-separable and nonstationary in space and time. Moreover, the dimension of such data sets across both space and time can be very large leading to computational difficulties due to numerical instabilities. Hence, space-time modeling is a challenging task and in particular parameter estimation based on complex models can be problematic due to the such curse of dimensionality. We propose a novel reparametrization approach to fit dynamic space-time models which allows the use of a very general form for the spatial covariance function. Our modeling contribution is to present an unconstrained reparametrization for a covariance function within the dynamic space-time models. A major benefit of the proposed unconstrained reparametrization method is that we are able to implement the modeling of a very high dimensional covariance matrix that automatically maintains the positive definiteness constraint. We demonstrate the applicability of our proposed reparametrized dynamic space-time models for a large data set of total nitrate concentrations