Exploring the Effect of Trauma Care Simulation on Undergraduate Critical Care Nursing Students’ Attitude at A College of Nursing, in Jeddah- An Intervention Study

Background: Patient safety has become a priority and pre-requisite for the provision for effective quality care. Simulation is seen as one method to ensure patient safety as this method allows for the attainment of skills and promotes the transference of these skills into safe clinical practice.Method: A pretest posttest research design was used. 34 Female critical care students were conveniently sampled from the College of Nursing, Jeddah, at the King Saud bin Abdul-Aziz University for Health Sciences. Data collection occurred in three phases: first phase pre simulation phase which included administering the KIDSIM Attitudes Questionnaire; second phase was the simulation on a trauma patient with hypovolemic shock; third phase was administering the KIDSIM Attitudes Questionnaire and Simulation Design Scale. Results: The majority of the students have positive attitudes in both pre and post simulation practice in relation to the relevance of simulation (with Mean + SD 4.3 + 0.6 pre & 4.4 + 0.5 post) with no significant difference between pre and post simulation practice. Approximately two thirds of students were able to able to care for a trauma patients with hypovolemic shock. Student’s feedback about the simulation practice highlights that the majority of students provided positive feedback regarding the simulation session attended.Discussion: One of the significant finding related to leadership provided during simulation was to ask non- response team members to leave when they are distracting. In addition, the results of this study revealed that within a team context, the roles on non- leading members of the team are just as important for good team functioning as the role of the leader.Limitations and recommendations: Limitations include space triangulation with a small sample size. Recommendations for future research propose qualitative studies to address the phenenomon at hand especially within a Saudi Arabian context. Keywords: Critical care students, simulation, trauma care, trauma care simulation

A Killing Disease Epidemic Among Displaced Sudanese Population Identified as Visceral Leishmaniasis.

A fatal disease epidemic affected the Bentiu area in southern Sudan and led to a mass migration of the Nuer tribe searching for treatment. The initially available information revealed a high mortality rate due to a possible occurrence of tuberculosis, malaria, enteric fever or visceral leishmaniasis (VL). Serological screening of 53 of the most severely affected patients in an enzyme-linked immunosorbent assay (ELISA) or an improved direct agglutination test (DAT) revealed positivity for VL. In 39 of those patients, diagnosis was confirmed by identification of Leishmania donovani amastigotes in lymph node or bone-marrow aspirates. In a total of 2714 patients observed, 1195 (44.0%) had clinical symptoms suggesting VL: DAT positive titers (1:3200-greater than or equal to 1:12800) were obtained in 654 (24.1%), of whom 325 were confirmed parasitologically. Forty-two VL cases died before or during treatment, giving a mortality rate of 6.4%. Among the intercurrent infections diagnosed in the VL population (654), respiratory involvements (31.7%) and malaria (10.7%) were most prevalent. With the exception of four (0.6%), all other VL patients (509) responded readily to sodium stibogluconate. The factors initiating the outbreak are discussed. Malnutrition and nomadic movements to potential VL endemic areas appeared to be the most important. HIV infection as a possible predisposition seemed remote considering the clinical and epidemiological similarity to VL occurring in East Africa, adequate humoral response in DAT, and immediate positive response to specific anti-Leishmania chemotherapy

Future life expectancy in Europe taking into account the impact of smoking, obesity, and alcohol

Introduction: In Europe, women can expect to live on average 82 years and men 75 years. Forecasting how life expectancy will develop in the future is essential for society. Most forecasts rely on a mechanical extrapolation of past mortality trends, which leads to unreliable outcomes because of temporal fluctuations in the past trends due to lifestyle ‘epidemics’. Methods: We project life expectancy for 18 European countries by taking into account the impact of smoking, obesity, and alcohol on mortality, and the mortality experiences of forerunner populations. Results: We project that life expectancy in these 18 countries will increase from, on average, 83.4 years for women and 78.3 years for men in 2014 to 92.8 years for women and 90.5 years for men in 2065. Compared to others (Lee–Carter, Eurostat, United Nations), we project higher future life expectancy values and more realistic differences between countries and sexes. Conclusions: Our results imply longer individual lifespans, and more elderly in society. Funding: Netherlands Organisation for Scientific Research (NWO) (grant no. 452-13-001)

Micro-Fluidic Diffusion Coefficient Measurement

A new method for diffusion coefficient measurement applicable to micro-fluidics is pre- sented. The method Iltilizes an analytical model describing laminar dispersion in rect- anglllar ~llicro_channe]s. The Illethod ~vas verified throllgh measllremen~ of fllloresceill diffusivity in water and aqueolls polymer solutions of differing concentration. The diffll- sivity of flllorescein was measlmed as 0.64 x 10-gm2/s in water, 0.49 x 10-gm2/s in the 4 gm/dl dextran solution and 0.38 x 10-9n12/s in the 8 gnl/dl dextran solution

Processing-Induced Disorder in Pharmaceutical Materials

This chapter focuses on the major types of pharmaceutical processing methods that have been widely reported to produce disordered material either intentionally or unintentionally. Milling is one of the most frequently used unit operations used by the pharmaceutical industry for reducing the particle size of solids. Thermal processing techniques are mainly used for controlling or improving the release and the subsequent bioavailability of an active pharmaceutical ingredient (API). Techniques such as melt-mixing, spray-congealing, sintering, melt-granulation, and hot-melt extrusion (HME) have developed and evolved rapidly for large-scale pharmaceutical production. Solvent-evaporation-based methods are important processing techniques for both raw materials, such as crystallization of the raw drug, and formulation manufacturing in the pharmaceutical industry. The chapter discusses the processing that can potentially induce the formation of the disordered state during the manufacture of formulations. The widely used solvent-evaporation-based processing techniques in pharmaceutical formulation production include spray-drying, freeze-drying, film casting, and film coating

A self-organized model for cell-differentiation based on variations of molecular decay rates

Systemic properties of living cells are the result of molecular dynamics governed by so-called genetic regulatory networks (GRN). These networks capture all possible features of cells and are responsible for the immense levels of adaptation characteristic to living systems. At any point in time only small subsets of these networks are active. Any active subset of the GRN leads to the expression of particular sets of molecules (expression modes). The subsets of active networks change over time, leading to the observed complex dynamics of expression patterns. Understanding of this dynamics becomes increasingly important in systems biology and medicine. While the importance of transcription rates and catalytic interactions has been widely recognized in modeling genetic regulatory systems, the understanding of the role of degradation of biochemical agents (mRNA, protein) in regulatory dynamics remains limited. Recent experimental data suggests that there exists a functional relation between mRNA and protein decay rates and expression modes. In this paper we propose a model for the dynamics of successions of sequences of active subnetworks of the GRN. The model is able to reproduce key characteristics of molecular dynamics, including homeostasis, multi-stability, periodic dynamics, alternating activity, differentiability, and self-organized critical dynamics. Moreover the model allows to naturally understand the mechanism behind the relation between decay rates and expression modes. The model explains recent experimental observations that decay-rates (or turnovers) vary between differentiated tissue-classes at a general systemic level and highlights the role of intracellular decay rate control mechanisms in cell differentiation.Comment: 16 pages, 5 figure

Improving statistical inference on pathogen densities estimated by quantitative molecular methods: malaria gametocytaemia as a case study

BACKGROUND: Quantitative molecular methods (QMMs) such as quantitative real-time polymerase chain reaction (q-PCR), reverse-transcriptase PCR (qRT-PCR) and quantitative nucleic acid sequence-based amplification (QT-NASBA) are increasingly used to estimate pathogen density in a variety of clinical and epidemiological contexts. These methods are often classified as semi-quantitative, yet estimates of reliability or sensitivity are seldom reported. Here, a statistical framework is developed for assessing the reliability (uncertainty) of pathogen densities estimated using QMMs and the associated diagnostic sensitivity. The method is illustrated with quantification of Plasmodium falciparum gametocytaemia by QT-NASBA. RESULTS: The reliability of pathogen (e.g. gametocyte) densities, and the accompanying diagnostic sensitivity, estimated by two contrasting statistical calibration techniques, are compared; a traditional method and a mixed model Bayesian approach. The latter accounts for statistical dependence of QMM assays run under identical laboratory protocols and permits structural modelling of experimental measurements, allowing precision to vary with pathogen density. Traditional calibration cannot account for inter-assay variability arising from imperfect QMMs and generates estimates of pathogen density that have poor reliability, are variable among assays and inaccurately reflect diagnostic sensitivity. The Bayesian mixed model approach assimilates information from replica QMM assays, improving reliability and inter-assay homogeneity, providing an accurate appraisal of quantitative and diagnostic performance. CONCLUSIONS: Bayesian mixed model statistical calibration supersedes traditional techniques in the context of QMM-derived estimates of pathogen density, offering the potential to improve substantially the depth and quality of clinical and epidemiological inference for a wide variety of pathogens

A combinatorial extracellular matrix platform identifies cell-extracellular matrix interactions that correlate with metastasis

Extracellular matrix interactions have essential roles in normal physiology and many pathological processes. Although the importance of extracellular matrix interactions in metastasis is well documented, systematic approaches to identify their roles in distinct stages of tumorigenesis have not been described. Here we report a novel-screening platform capable of measuring phenotypic responses to combinations of extracellular matrix molecules. Using a genetic mouse model of lung adenocarcinoma, we measure the extracellular matrix-dependent adhesion of tumour-derived cells. Hierarchical clustering of the adhesion profiles differentiates metastatic cell lines from primary tumour lines. Furthermore, we uncovered that metastatic cells selectively associate with fibronectin when in combination with galectin-3, galectin-8 or laminin. We show that these molecules correlate with human disease and that their interactions are mediated in part by α3β1 integrin. Thus, our platform allowed us to interrogate interactions between metastatic cells and their microenvironments, and identified extracellular matrix and integrin interactions that could serve as therapeutic targets.National Institutes of Health (U.S.) (Grant K99-CA151968)National Institutes of Health (U.S.). Ruth L. Kirschstein National Research Service AwardStand Up To Cancer (SU2C/AACR)David H. Koch Institute for Integrative Cancer Research at MIT (CTC Project)Harvard Stem Cell Institute (SG-0046-08-00)National Cancer Center (Postdoctoral Fellowship)National Cancer Institute (U.S.) (U54CA126515)National Cancer Institute (U.S.) (U54CA112967)Howard Hughes Medical InstituteMassachusetts Institute of Technology. Ludwig Center for Molecular Oncolog