Airports at Risk: The Impact of Information Sources on Security Decisions

Security decisions in high risk organizations such as airports involve obtaining ongoing and frequent information about potential threats. Utilizing questionnaire survey data from a sample of airport employees in European Airports across the continent, we analyzed how both formal and informal sources of security information affect employee's decisions to comply with the security rules and directives. This led us to trace information network flows to assess its impact on the degree employees making security decisions comply or deviate with the prescribed security rules. The results of the multivariate analysis showed that security information obtained through formal and informal networks differentially determine if employee will comply or not with the rules. Information sources emanating from the informal network tends to encourage employees to be more flexible in their security decisions while formal sources lead to be more rigid with complying with rules and protocols. These results suggest that alongside the formal administrative structure of airports, there exists a diverse and pervasiveness set of informal communications networks that are a potent factor in determining airport security levels

Technology mediator: a new role for the reference librarian?

The Arizona Health Sciences Library has collaborated with clinical faculty to develop a federated search engine that is useful for meeting real-time clinical information needs. This article proposes a technology mediation role for the reference librarian that was inspired by the project, and describes the collaborative model used for developing technology-mediated services for targeted users

A functional polymorphism in the 5HTR2C gene associated with stress responses also predicts incident cardiovascular events.

Previously we have shown that a functional nonsynonymous single nucleotide polymorphism (rs6318) of the 5HTR2C gene located on the X-chromosome is associated with hypothalamic-pituitary-adrenal axis response to a stress recall task, and with endophenotypes associated with cardiovascular disease (CVD). These findings suggest that individuals carrying the rs6318 Ser23 C allele will be at higher risk for CVD compared to Cys23 G allele carriers. The present study examined allelic variation in rs6318 as a predictor of coronary artery disease (CAD) severity and a composite endpoint of all-cause mortality or myocardial infarction (MI) among Caucasian participants consecutively recruited through the cardiac catheterization laboratory at Duke University Hospital (Durham, NC) as part of the CATHGEN biorepository. Study population consisted of 6,126 Caucasian participants (4,036 [65.9%] males and 2,090 [34.1%] females). A total of 1,769 events occurred (1,544 deaths and 225 MIs; median follow-up time = 5.3 years, interquartile range = 3.3-8.2). Unadjusted Cox time-to-event regression models showed, compared to Cys23 G carriers, males hemizygous for Ser23 C and females homozygous for Ser23C were at increased risk for the composite endpoint of all-cause death or MI: Hazard Ratio (HR) = 1.47, 95% confidence interval (CI) = 1.17, 1.84, p = .0008. Adjusting for age, rs6318 genotype was not related to body mass index, diabetes, hypertension, dyslipidemia, smoking history, number of diseased coronary arteries, or left ventricular ejection fraction in either males or females. After adjustment for these covariates the estimate for the two Ser23 C groups was modestly attenuated, but remained statistically significant: HR = 1.38, 95% CI = 1.10, 1.73, p = .005. These findings suggest that this functional polymorphism of the 5HTR2C gene is associated with increased risk for CVD mortality and morbidity, but this association is apparently not explained by the association of rs6318 with traditional risk factors or conventional markers of atherosclerotic disease

Glaciological Monitoring Using the Sun as a Radio Source for Echo Detection

Funder: NASA Cryospheric SciencesAbstract: Ice‐penetrating radar observations are critical for projecting ice‐sheet contribution to sea‐level rise; however, these prognostic models have significant uncertainties due to an incomplete understanding of glacial subsurface processes. Existing radars that can characterize subsurface conditions are too resource‐intensive to simultaneously monitor ice sheets at both the necessary temporal—daily to multiannual—and spatial—tributary to continental—scales. Here, we investigate using an ambient radio source, instead of transmitting a signal, for glaciological monitoring. We demonstrate, for the first time, passive radio sounding using the Sun to accurately measure ice thickness on Store Glacier, Greenland. Passive radar sounding could provide low‐resource time‐series measurements of the cryosphere, enabling us to observe and understand evolving englacial and subglacial conditions across Greenland and Antarctica with unprecedented coverage and resolution

Identifying Trustworthy Experts: How Do Policymakers Find and Assess Public Health Researchers Worth Consulting or Collaborating With?

This paper reports data from semi-structured interviews on how 26 Australian civil servants, ministers and ministerial advisors find and evaluate researchers with whom they wish to consult or collaborate. Policymakers valued researchers who had credibility across the three attributes seen as contributing to trustworthiness: competence (an exemplary academic reputation complemented by pragmatism, understanding of government processes, and effective collaboration and communication skills); integrity (independence, “authenticity”, and faithful reporting of research); and benevolence (commitment to the policy reform agenda). The emphases given to these assessment criteria appeared to be shaped in part by policymakers' roles and the type and phase of policy development in which they were engaged. Policymakers are encouraged to reassess their methods for engaging researchers and to maximise information flow and support in these relationships. Researchers who wish to influence policy are advised to develop relationships across the policy community, but also to engage in other complementary strategies for promoting research-informed policy, including the strategic use of mass media

The identification of informative genes from multiple datasets with increasing complexity

Background In microarray data analysis, factors such as data quality, biological variation, and the increasingly multi-layered nature of more complex biological systems complicates the modelling of regulatory networks that can represent and capture the interactions among genes. We believe that the use of multiple datasets derived from related biological systems leads to more robust models. Therefore, we developed a novel framework for modelling regulatory networks that involves training and evaluation on independent datasets. Our approach includes the following steps: (1) ordering the datasets based on their level of noise and informativeness; (2) selection of a Bayesian classifier with an appropriate level of complexity by evaluation of predictive performance on independent data sets; (3) comparing the different gene selections and the influence of increasing the model complexity; (4) functional analysis of the informative genes. Results In this paper, we identify the most appropriate model complexity using cross-validation and independent test set validation for predicting gene expression in three published datasets related to myogenesis and muscle differentiation. Furthermore, we demonstrate that models trained on simpler datasets can be used to identify interactions among genes and select the most informative. We also show that these models can explain the myogenesis-related genes (genes of interest) significantly better than others (P < 0.004) since the improvement in their rankings is much more pronounced. Finally, after further evaluating our results on synthetic datasets, we show that our approach outperforms a concordance method by Lai et al. in identifying informative genes from multiple datasets with increasing complexity whilst additionally modelling the interaction between genes. Conclusions We show that Bayesian networks derived from simpler controlled systems have better performance than those trained on datasets from more complex biological systems. Further, we present that highly predictive and consistent genes, from the pool of differentially expressed genes, across independent datasets are more likely to be fundamentally involved in the biological process under study. We conclude that networks trained on simpler controlled systems, such as in vitro experiments, can be used to model and capture interactions among genes in more complex datasets, such as in vivo experiments, where these interactions would otherwise be concealed by a multitude of other ongoing events

An integrated general practice and pharmacy-based intervention to promote the use of appropriate preventive medications among individuals at high cardiovascular disease risk: protocol for a cluster randomized controlled trial

Background: Cardiovascular diseases (CVD) are responsible for significant morbidity, premature mortality, and economic burden. Despite established evidence that supports the use of preventive medications among patients at high CVD risk, treatment gaps remain. Building on prior evidence and a theoretical framework, a complex intervention has been designed to address these gaps among high-risk, under-treated patients in the Australian primary care setting. This intervention comprises a general practice quality improvement tool incorporating clinical decision support and audit/feedback capabilities; availability of a range of CVD polypills (fixed-dose combinations of two blood pressure lowering agents, a statin ± aspirin) for prescription when appropriate; and access to a pharmacy-based program to support long-term medication adherence and lifestyle modification. Methods: Following a systematic development process, the intervention will be evaluated in a pragmatic cluster randomized controlled trial including 70 general practices for a median period of 18 months. The 35 general practices in the intervention group will work with a nominated partner pharmacy, whereas those in the control group will provide usual care without access to the intervention tools. The primary outcome is the proportion of patients at high CVD risk who were inadequately treated at baseline who achieve target blood pressure (BP) and low-density lipoprotein cholesterol (LDL-C) levels at the study end. The outcomes will be analyzed using data from electronic medical records, utilizing a validated extraction tool. Detailed process and economic evaluations will also be performed. Discussion: The study intends to establish evidence about an intervention that combines technological innovation with team collaboration between patients, pharmacists, and general practitioners (GPs) for CVD prevention. Trial registration: Australian New Zealand Clinical Trials Registry ACTRN1261600023342

S021-04 OA. A large-scale analysis of immunoglobulin sequences derived from plasmablasts/plasma cells in acute HIV-1 infection subjects

Background In acute HIV-1 infection (AHI) there are infectioninduced polyclonal shifts in blood and bone marrow Bcell subsets from naïve to memory cells and plasmablasts/ plasma cells (PCs) coupled with decreased numbers of naive B cells. To study the initial antibody response to HIV, we have used recombinant technology to create a database of PC antibody sequences derived from 3 early stage AHI subjects

Functional Diversity and Structural Disorder in the Human Ubiquitination Pathway

The ubiquitin-proteasome system plays a central role in cellular regulation and protein quality control (PQC). The system is built as a pyramid of increasing complexity, with two E1 (ubiquitin activating), few dozen E2 (ubiquitin conjugating) and several hundred E3 (ubiquitin ligase) enzymes. By collecting and analyzing E3 sequences from the KEGG BRITE database and literature, we assembled a coherent dataset of 563 human E3s and analyzed their various physical features. We found an increase in structural disorder of the system with multiple disorder predictors (IUPred - E1: 5.97%, E2: 17.74%, E3: 20.03%). E3s that can bind E2 and substrate simultaneously (single subunit E3, ssE3) have significantly higher disorder (22.98%) than E3s in which E2 binding (multi RING-finger, mRF, 0.62%), scaffolding (6.01%) and substrate binding (adaptor/substrate recognition subunits, 17.33%) functions are separated. In ssE3s, the disorder was localized in the substrate/adaptor binding domains, whereas the E2-binding RING/HECT-domains were structured. To demonstrate the involvement of disorder in E3 function, we applied normal modes and molecular dynamics analyses to show how a disordered and highly flexible linker in human CBL (an E3 that acts as a regulator of several tyrosine kinase-mediated signalling pathways) facilitates long-range conformational changes bringing substrate and E2-binding domains towards each other and thus assisting in ubiquitin transfer. E3s with multiple interaction partners (as evidenced by data in STRING) also possess elevated levels of disorder (hubs, 22.90% vs. non-hubs, 18.36%). Furthermore, a search in PDB uncovered 21 distinct human E3 interactions, in 7 of which the disordered region of E3s undergoes induced folding (or mutual induced folding) in the presence of the partner. In conclusion, our data highlights the primary role of structural disorder in the functions of E3 ligases that manifests itself in the substrate/adaptor binding functions as well as the mechanism of ubiquitin transfer by long-range conformational transitions. © 2013 Bhowmick et al