Electron Sources for Future Lightsources, Summary and Conclusions for the Activities during FLS 2012

This paper summarizes the discussions, presentations, and activity of the Future Light Sources Workshop 2012 (FLS 2012) working group dedicated to Electron Sources. The focus of the working group was to discuss concepts and technologies that might enable much higher peak and average brightness from electron beam sources. Furthermore the working group was asked to consider methods to greatly improve the robustness of operation and lower the costs of providing electrons.Comment: 11 pages, 7 figures, summary paper from working group Future Light Sources 2012 Workshop at Newport News, Virginia, USA (http://www.jlab.org/conferences/FLS2012/

An Sp185/333 gene cluster from the purple sea urchin and putative microsatellite-mediated gene diversification

Abstract Background The immune system of the purple sea urchin, Strongylocentrotus purpuratus, is complex and sophisticated. An important component of sea urchin immunity is the Sp185/333 gene family, which is significantly upregulated in immunologically challenged animals. The Sp185/333 genes are less than 2 kb with two exons and are members of a large diverse family composed of greater than 40 genes. The S. purpuratus genome assembly, however, contains only six Sp185/333 genes. This underrepresentation could be due to the difficulties that large gene families present in shotgun assembly, where multiple similar genes can be collapsed into a single consensus gene. Results To understand the genomic organization of the Sp185/333 gene family, a BAC insert containing Sp185/333 genes was assembled, with careful attention to avoiding artifacts resulting from collapse or artificial duplication/expansion of very similar genes. Twelve candidate BAC assemblies were generated with varying parameters and the optimal assembly was identified by PCR, restriction digests, and subclone sequencing. The validated assembly contained six Sp185/333 genes that were clustered in a 34 kb region at one end of the BAC with five of the six genes tightly clustered within 20 kb. The Sp185/333 genes in this cluster were no more similar to each other than to previously sequenced Sp185/333 genes isolated from three different animals. This was unexpected given their proximity and putative effects of gene homogenization in closely linked, similar genes. All six genes displayed significant similarity including both 5' and 3' flanking regions, which were bounded by microsatellites. Three of the Sp185/333 genes and their flanking regions were tandemly duplicated such that each repeated segment consisted of a gene plus 0.7 kb 5' and 2.4 kb 3' of the gene (4.5 kb total). Both edges of the segmental duplications were bounded by different microsatellites. Conclusions The high sequence similarity of the Sp185/333 genes and flanking regions, suggests that the microsatellites may promote genomic instability and are involved with gene duplication and/or gene conversion and the extraordinary sequence diversity of this family

First pilot trial of the STAR-Liege protocol for tight glycemic control in critically ill patients

peer reviewe

Mathematical model of the mitral valve and the cardiovascular system, application for studying, monitoring and in the diagnosis of valvular pathologies

peer reviewedA cardiovascular and circulatory system (CVS) model has been validated in silico, and in several animal model studies. It accounts for valve dynamics using Heaviside functions to simulate a physiological accurate “open on pressure, close on flow” law. Thus, it does not consider the real time scale of the valve aperture dynamics and thus doesn’t fully capture valve dysfunction particularly where the dysfunction involves partial closure. This research describes a new closed-loop CVS model including a model describing the progressive aperture of the mitral valve and valid over the full cardiac cycle. This new model is solved for a healthy and diseased mitral valve

The Iowa Homemaker vol.28, no.3

Memo to a Freshman, page 2 Money Planning Can Be Fun, Mary Alice Halverson, page 3 If Marriage Is in Your Future, Jo Ann Breckenridge, page 4 There’s Excitement Ahead, Katherine Williams, page 6 Activities Point Up Fun for Free Time, Margaret Edgar, page 7 Faculty Suggests Electives, Peggy Ann Krenek, page 8 All You Have To Do Is Eat, Janet Sutherland, page 9 Meet Your Counselors, Elinor Chase, page 10 Vicky, Jo Ann Breckenridge, page 12 What’s New, Peggy Ann Krenek, page 17 Testing Bureau, Barbara Allen, page 19 Keeping Up With Today, Mary West, page 2

Modeling Progressive Fibrosis with Pluripotent Stem Cells Identifies an Anti-fibrotic Small Molecule.

Progressive organ fibrosis accounts for one-third of all deaths worldwide, yet preclinical models that mimic the complex, progressive nature of the disease are lacking, and hence, there are no curative therapies. Progressive fibrosis across organs shares common cellular and molecular pathways involving chronic injury, inflammation, and aberrant repair resulting in deposition of extracellular matrix, organ remodeling, and ultimately organ failure. We describe the generation and characterization of an in vitro progressive fibrosis model that uses cell types derived from induced pluripotent stem cells. Our model produces endogenous activated transforming growth factor β (TGF-β) and contains activated fibroblastic aggregates that progressively increase in size and stiffness with activation of known fibrotic molecular and cellular changes. We used this model as a phenotypic drug discovery platform for modulators of fibrosis. We validated this platform by identifying a compound that promotes resolution of fibrosis in in vivo and ex vivo models of ocular and lung fibrosis

Mathematical multi-scale model of the cardiovascular system including mitral valve dynamics. Application to ischemic mitral insufficiency

Valve dysfunction is a common cardiovascular pathology. Despite significant clinical research, there is little formal study of how valve dysfunction affects overall circulatory dynamics. Validated models would offer the ability to better understand these dynamics and thus optimize diagnosis, as well as surgical and other interventions. A cardiovascular and circulatory system (CVS) model has already been validated in silico, and in several animal model studies. It accounts for valve dynamics using Heaviside functions to simulate a physiologically accurate “open on pressure, close on flow” law. However, it does not consider real-time valve opening dynamics and therefore does not fully capture valve dysfunction, particularly where the dysfunction involves partial closure. This research describes an updated version of this previous closed-loop CVS model that includes the progressive opening of the mitral valve, and is defined over the full cardiac cycle. Simulations of the cardiovascular system with healthy mitral valve are performed, and, the global hemodynamic behaviour is studied compared with previously validated results. The error between resulting pressure-volume (PV) loops of already validated CVS model and the new CVS model that includes the progressive opening of the mitral valve is assessed and remains within typical measurement error and variability. Simulations of ischemic mitral insufficiency are also performed. Pressure-Volume loops, transmitral flow evolution and mitral valve aperture area evolution follow reported measurements in shape, amplitude and trends. The resulting cardiovascular system model including mitral valve dynamics provides a foundation for clinical validation and the study of valvular dysfunction in vivo. The overall models and results could readily be generalised to other cardiac valves

Validation of a model-based virtual trials method for tight glycemic control in intensive care

peer reviewedBACKGROUND: In-silico virtual patients and trials offer significant advantages in cost, time and safety for designing effective tight glycemic control (TGC) protocols. However, no such method has fully validated the independence of virtual patients (or resulting clinical trial predictions) from the data used to create them. This study uses matched cohorts from a TGC clinical trial to validate virtual patients and in-silico virtual trial models and methods. METHODS: Data from a 211 patient subset of the Glucontrol trial in Liege, Belgium. Glucontrol-A (N = 142) targeted 4.4-6.1 mmol/L and Glucontrol-B (N = 69) targeted 7.8-10.0 mmol/L. Cohorts were matched by APACHE II score, initial BG, age, weight, BMI and sex (p > 0.25). Virtual patients are created by fitting a clinically validated model to clinical data, yielding time varying insulin sensitivity profiles (SI(t)) that drives in-silico patients.Model fit and intra-patient (forward) prediction errors are used to validate individual in-silico virtual patients. Self-validation (tests A protocol on Group-A virtual patients; and B protocol on B virtual patients) and cross-validation (tests A protocol on Group-B virtual patients; and B protocol on A virtual patients) are used in comparison to clinical data to assess ability to predict clinical trial results. RESULTS: Model fit errors were small (<0.25%) for all patients, indicating model fitness. Median forward prediction errors were: 4.3, 2.8 and 3.5% for Group-A, Group-B and Overall (A+B), indicating individual virtual patients were accurate representations of real patients. SI and its variability were similar between cohorts indicating they were metabolically similar.Self and cross validation results were within 1-10% of the clinical data for both Group-A and Group-B. Self-validation indicated clinically insignificant errors due to model and/or clinical compliance. Cross-validation clearly showed that virtual patients enabled by identified patient-specific SI(t) profiles can accurately predict the performance of independent and different TGC protocols. CONCLUSIONS: This study fully validates these virtual patients and in silico virtual trial methods, and clearly shows they can accurately simulate, in advance, the clinical results of a TGC protocol, enabling rapid in silico protocol design and optimization. These outcomes provide the first rigorous validation of a virtual in-silico patient and virtual trials methodology

Organ failure and tight glycemic control in the SPRINT study

INTRODUCTION: Intensive care unit mortality is strongly associated with organ failure rate and severity. The sequential organ failure assessment (SOFA) score is used to evaluate the impact of a successful tight glycemic control (TGC) intervention (SPRINT) on organ failure, morbidity, and thus mortality. METHODS: A retrospective analysis of 371 patients (3,356 days) on SPRINT (August 2005 - April 2007) and 413 retrospective patients (3,211 days) from two years prior, matched by Acute Physiology and Chronic Health Evaluation (APACHE) III. SOFA is calculated daily for each patient. The effect of the SPRINT TGC intervention is assessed by comparing the percentage of patients with SOFA 2) are also compared. Cumulative time in 4.0 to 7.0 mmol/L band (cTIB) was evaluated daily to link tightness and consistency of TGC (cTIB >/=0.5) to SOFA /=0.5 (37% Pre-SPRINT) reaching 100% by Day 7 (50% Pre-SPRINT). Conditional and joint probabilities indicate tighter, more consistent TGC under SPRINT (cTIB >/=0.5) increased the likelihood SOFA /=0.5 metric provides a first benchmark linking TGC quality to organ failure. These results support other physiological and clinical results indicating the role tight, consistent TGC can play in reducing organ failure, morbidity and mortality, and should be validated on data from randomised trials