African Swine Fever Virus Host-Pathogen Interactions.

African swine fever virus is a complex double-stranded DNA virus that exhibits tropism for cells of the mononuclear phagocytic system. Virus replication is a multi-step process that involves the nucleus of the host cell as well the formation of large perinuclear sites where progeny virions are assembled prior to transport to, and budding through, the plasma membrane. Like many viruses, African swine fever virus reorganises the cellular architecture to facilitate its replication and has evolved multiple mechanisms to avoid the potential deleterious effects of host cell stress response pathways. However, how viral proteins and virus-induced structures trigger cellular stress pathways and manipulate the subsequent responses is still relatively poorly understood. African swine fever virus alters nuclear substructures, modulates autophagy, apoptosis and the endoplasmic reticulum stress response pathways. The viral genome encodes for at least 150 genes, of which approximately 70 are incorporated into the virion. Many of the non-structural genes have not been fully characterised and likely play a role in host range and modifying immune responses. As the field moves towards approaches that take a broader view of the effect of expression of individual African swine fever genes, we summarise how the different steps in virus replication interact with the host cell and the current state of knowledge on how it modulates the resulting stress responses.

Metabolome-Scale Genome-Wide Association Studies Reveal Chemical Diversity and Genetic Control of Maize Specialized Metabolites.

Cultivated maize (Zea mays) has retained much of the genetic diversity of its wild ancestors. Here, we performed nontargeted liquid chromatography-mass spectrometry metabolomics to analyze the metabolomes of the 282 maize inbred lines in the Goodman Diversity Panel. This analysis identified a bimodal distribution of foliar metabolites. Although 15% of the detected mass features were present in >90% of the inbred lines, the majority were found in <50% of the samples. Whereas leaf bases and tips were differentiated by flavonoid abundance, maize varieties (stiff-stalk, nonstiff-stalk, tropical, sweet maize, and popcorn) showed differential accumulation of benzoxazinoid metabolites. Genome-wide association studies (GWAS), performed for 3,991 mass features from the leaf tips and leaf bases, showed that 90% have multiple significantly associated loci scattered across the genome. Several quantitative trait locus hotspots in the maize genome regulate the abundance of multiple, often structurally related mass features. The utility of maize metabolite GWAS was demonstrated by confirming known benzoxazinoid biosynthesis genes, as well as by mapping isomeric variation in the accumulation of phenylpropanoid hydroxycitric acid esters to a single linkage block in a citrate synthase-like gene. Similar to gene expression databases, this metabolomic GWAS data set constitutes an important public resource for linking maize metabolites with biosynthetic and regulatory genes.

Autophagy impairment by African swine fever virus.

African swine fever is a devastating disease of domestic swine and wild boar caused by a large double-stranded DNA virus that encodes for more than 150 open reading frames. There is no licensed vaccine for the disease and the most promising current candidates are modified live viruses that have been attenuated by deletion of virulence factors. Like many viruses African swine fever virus significantly alters the host cell machinery to benefit its replication and viral genes that modify host pathways represent promising targets for development of gene deleted vaccines. Autophagy is an important cellular pathway that is involved in cellular homeostasis, innate and adaptive immunity and therefore is manipulated by a number of different viruses. Autophagy is regulated by a complex protein cascade and here we show that African swine fever virus can block formation of autophagosomes, a critical functional step of the autophagy pathway through at least two different mechanisms. Interestingly this does not require the A179L gene that has been shown to interact with Beclin-1, an important autophagy regulator.

Capsid-Specific Antibody Responses of Domestic Pigs Immunized with Low-Virulent African Swine Fever Virus.

African swine fever (ASF) is a lethal disease in pigs that has grave socio-economic implications worldwide. For the development of vaccines against the African swine fever virus (ASFV), immunogenic antigens that generate protective immune responses need to be identified. There are over 150 viral proteins-many of which are uncharacterized-and humoral immunity to ASFV has not been closely examined. To profile antigen-specific antibody responses, we developed luciferase-linked antibody capture assays (LACAs) for a panel of ASFV capsid proteins and screened sera from inbred and outbred animals that were previously immunized with low-virulent ASFV before challenge with virulent ASFV. Antibodies to B646L/p72, D117L/p17, M1249L, and E120R/p14.5 were detected in this study; however, we were unable to detect B438L-specific antibodies. Anti-B646L/p72 and B602L antibodies were associated with recovery from disease after challenges with genotype I OUR T88/1 but not genotype II Georgia 2007/1. Antibody responses against M1249L and E120R/p14.5 were observed in animals with reduced clinical signs and viremia. Here, we present LACAs as a tool for the targeted profiling of antigen-specific antibody responses to inform vaccine development.

The 2017 Academic Emergency Medicine Consensus Conference: Catalyzing System Change Through Healthcare Simulation: Systems, Competency, and Outcomes.

Over the past decade, emergency medicine (EM) took a lead role in healthcare simulation in part due to its demands for successful interprofessional and multidisciplinary collaboration, along with educational needs in a diverse array of cognitive and procedural skills. Simulation-based methodologies have the capacity to support training and research platforms that model micro-, meso-, and macrosystems of healthcare. To fully capitalize on the potential of simulation-based research to improve emergency healthcare delivery will require the application of rigorous methods from engineering, social science, and basic science disciplines. The Academic Emergency Medicine (AEM) Consensus Conference "Catalyzing System Change Through Healthcare Simulation: Systems, Competency, and Outcome" was conceived to foster discussion among experts in EM, engineering, and social sciences, focusing on key barriers and opportunities in simulation-based research. This executive summary describes the overall rationale for the conference, conference planning, and consensus-building approaches and outlines the focus of the eight breakout sessions. The consensus outcomes from each breakout session are summarized in proceedings papers published in this issue of Academic Emergency Medicine. Each paper provides an overview of methodologic and knowledge gaps in simulation research and identifies future research targets aimed at improving the safety and quality of healthcare.

Simulation-based Education to Ensure Provider Competency Within the Health Care System.

The acquisition and maintenance of individual competency is a critical component of effective emergency care systems. This article summarizes consensus working group deliberations and recommendations focusing on the topic "Simulation-based education to ensure provider competency within the healthcare system." The authors presented this work for discussion and feedback at the 2017 Academic Emergency Medicine Consensus Conference on "Catalyzing System Change Through Healthcare Simulation: Systems, Competency, and Outcomes," held on May 16, 2017, in Orlando, Florida. Although simulation-based training is a quality and safety imperative in other high-reliability professions such as aviation, nuclear power, and the military, health care professions still lag behind in applying simulation more broadly. This is likely a result of a number of factors, including cost, assessment challenges, and resistance to change. This consensus subgroup focused on identifying current gaps in knowledge and process related to the use of simulation for developing, enhancing, and maintaining individual provider competency. The resulting product is a research agenda informed by expert consensus and literature review.

Simulation for Assessment of Milestones in Emergency Medicine Residents.

OBJECTIVES: All residency programs in the United States are required to report their residents' progress on the milestones to the Accreditation Council for Graduate Medical Education (ACGME) biannually. Since the development and institution of this competency-based assessment framework, residency programs have been attempting to ascertain the best ways to assess resident performance on these metrics. Simulation was recommended by the ACGME as one method of assessment for many of the milestone subcompetencies. We developed three simulation scenarios with scenario-specific milestone-based assessment tools. We aimed to gather validity evidence for this tool. METHODS: We conducted a prospective observational study to investigate the validity evidence for three mannequin-based simulation scenarios for assessing individual residents on emergency medicine (EM) milestones. The subcompetencies (i.e., patient care [PC]1, PC2, PC3) included were identified via a modified Delphi technique using a group of experienced EM simulationists. The scenario-specific checklist (CL) items were designed based on the individual milestone items within each EM subcompetency chosen for assessment and reviewed by experienced EM simulationists. Two independent live raters who were EM faculty at the respective study sites scored each scenario following brief rater training. The inter-rater reliability (IRR) of the assessment tool was determined by measuring intraclass correlation coefficient (ICC) for the sum of the CL items as well as the global rating scales (GRSs) for each scenario. Comparing GRS and CL scores between various postgraduate year (PGY) levels was performed with analysis of variance. RESULTS: Eight subcompetencies were chosen to assess with three simulation cases, using 118 subjects. Evidence of test content, internal structure, response process, and relations with other variables were found. The ICCs for the sum of the CL items and the GRSs were >0.8 for all cases, with one exception (clinical management GRS = 0.74 in sepsis case). The sum of CL items and GRSs (p < 0.05) discriminated between PGY levels on all cases. However, when the specific CL items were mapped back to milestones in various proficiency levels, the milestones in the higher proficiency levels (level 3 [L3] and 4 [L4]) did not often discriminate between various PGY levels. L3 milestone items discriminated between PGY levels on five of 12 occasions they were assessed, and L4 items discriminated only two of 12 times they were assessed. CONCLUSION: Three simulation cases with scenario-specific assessment tools allowed evaluation of EM residents on proficiency L1 to L4 within eight of the EM milestone subcompetencies. Evidence of test content, internal structure, response process, and relations with other variables were found. Good to excellent IRR and the ability to discriminate between various PGY levels was found for both the sum of CL items and the GRSs. However, there was a lack of a positive relationship between advancing PGY level and the completion of higher-level milestone items (L3 and L4).

Publication of Abstracts Presented at an International Healthcare Simulation Conference.

INTRODUCTION: We aimed to determine the publication rate for abstracts presented at the International Meeting for Simulation in Healthcare (IMSH) and the time between abstract presentation and publication. We also aimed to describe the study features influencing subsequent publication and the relationship between these features and journal impact factors (IFs). METHODS: All types of accepted abstracts from the 2012 and 2013 IMSH were reviewed. We extracted the following data from each abstract in duplicate: presentation format, subject, type of scholarship, research method, study design, outcome measure, number of institutions in authorship group, and number of study sites. PubMed and Google Scholar were searched (January 1, 2012 to August 1, 2016) using the names of the first, second, and last author for comparison with abstracts. Journal of publication and IF were recorded. Data were summarized with descriptive statistics. Bivariate and multivariate analysis was performed to explore the association between publication status and other variables. RESULTS: Of 541 abstracts, 22% (119/541) were published with a median time to publication of 16 months (interquartile range = 8.525), ranging from 0 to 43 months. The study characteristics associated with a greater likelihood of publication were the following: research-type abstract, quantitative studies, randomized trials, studies with patient or healthcare-related outcomes, multiple institutions represented in authorship group, and multicenter studies. Studies with multiple institutions in authorship group and multicenter studies were published in higher IF journals (P < 0.05). CONCLUSIONS: The publication rate of 22% for abstracts presented at IMSH is low, indicative of the relatively new nature of simulation-based research in healthcare.

Reporting Guidelines for Health Care Simulation Research: Extensions to the CONSORT and STROBE Statements.

INTRODUCTION: Simulation-based research (SBR) is rapidly expanding but the quality of reporting needs improvement. For a reader to critically assess a study, the elements of the study need to be clearly reported. Our objective was to develop reporting guidelines for SBR by creating extensions to the Consolidated Standards of Reporting Trials (CONSORT) and Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) Statements. METHODS: An iterative multistep consensus-building process was used on the basis of the recommended steps for developing reporting guidelines. The consensus process involved the following: (1) developing a steering committee, (2) defining the scope of the reporting guidelines, (3) identifying a consensus panel, (4) generating a list of items for discussion via online premeeting survey, (5) conducting a consensus meeting, and (6) drafting reporting guidelines with an explanation and elaboration document. RESULTS: The following 11 extensions were recommended for CONSORT: item 1 (title/abstract), item 2 (background), item 5 (interventions), item 6 (outcomes), item 11 (blinding), item 12 (statistical methods), item 15 (baseline data), item 17 (outcomes/estimation), item 20 (limitations), item 21 (generalizability), and item 25 (funding). The following 10 extensions were recommended for STROBE: item 1 (title/abstract), item 2 (background/rationale), item 7 (variables), item 8 (data sources/measurement), item 12 (statistical methods), item 14 (descriptive data), item 16 (main results), item 19 (limitations), item 21 (generalizability), and item 22 (funding). An elaboration document was created to provide examples and explanation for each extension. CONCLUSIONS: We have developed extensions for the CONSORT and STROBE Statements that can help improve the quality of reporting for SBR.

Reporting guidelines for health care simulation research: extensions to the CONSORT and STROBE statements.

BACKGROUND: Simulation-based research (SBR) is rapidly expanding but the quality of reporting needs improvement. For a reader to critically assess a study, the elements of the study need to be clearly reported. Our objective was to develop reporting guidelines for SBR by creating extensions to the Consolidated Standards of Reporting Trials (CONSORT) and Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) Statements. METHODS: An iterative multistep consensus-building process was used on the basis of the recommended steps for developing reporting guidelines. The consensus process involved the following: (1) developing a steering committee, (2) defining the scope of the reporting guidelines, (3) identifying a consensus panel, (4) generating a list of items for discussion via online premeeting survey, (5) conducting a consensus meeting, and (6) drafting reporting guidelines with an explanation and elaboration document. RESULTS: The following 11 extensions were recommended for CONSORT: item 1 (title/abstract), item 2 (background), item 5 (interventions), item 6 (outcomes), item 11 (blinding), item 12 (statistical methods), item 15 (baseline data), item 17 (outcomes/ estimation), item 20 (limitations), item 21 (generalizability), and item 25 (funding). The following 10 extensions were recommended for STROBE: item 1 (title/abstract), item 2 (background/rationale), item 7 (variables), item 8 (data sources/measurement), item 12 (statistical methods), item 14 (descriptive data), item 16 (main results), item 19 (limitations), item 21 (generalizability), and item 22 (funding). An elaboration document was created to provide examples and explanation for each extension. CONCLUSIONS: We have developed extensions for the CONSORT and STROBE Statements that can help improve the quality of reporting for SBR (Sim Healthcare 00:00-00, 2016).

Simulation as a new tool to establish benchmark outcome measures in obstetrics.

BACKGROUND: There are not enough clinical data from rare critical events to calculate statistics to decide if the management of actual events might be below what could reasonably be expected (i.e. was an outlier). OBJECTIVES: In this project we used simulation to describe the distribution of management times as an approach to decide if the management of a simulated obstetrical crisis scenario could be considered an outlier. DESIGN: Twelve obstetrical teams managed 4 scenarios that were previously developed. Relevant outcome variables were defined by expert consensus. The distribution of the response times from the teams who performed the respective intervention was graphically displayed and median and quartiles calculated using rank order statistics. RESULTS: Only 7 of the 12 teams performed chest compressions during the arrest following the 'cannot intubate/cannot ventilate' scenario. All other outcome measures were performed by at least 11 of the 12 teams. Calculation of medians and quartiles with 95% CI was possible for all outcomes. Confidence intervals, given the small sample size, were large. CONCLUSION: We demonstrated the use of simulation to calculate quantiles for management times of critical event. This approach could assist in deciding if a given performance could be considered normal and also point to aspects of care that seem to pose particular challenges as evidenced by a large number of teams not performing the expected maneuver. However sufficiently large sample sizes (i.e. from a national data base) will be required to calculate acceptable confidence intervals and to establish actual tolerance limits.