Violence Related Injuries among Individuals Admitted to a Level I Trauma Center in Atlanta, 2011-2013

Background: Violence related injuries (VRIs) are a major public health problem in the United States (US). According to the Centers for Disease Control and Prevention (CDC), homicide is the 11th leading cause of death in the US and the third leading cause of death among persons aged 15-24 years old. Among African Americans aged 10-34, homicide is the leading cause of death and is the fifth leading cause of death among those 35-44 years old. One form of homicide that can result in injury resulting in death is firearm violence. The objective of this study is to assess the rates of VRIs among African American males who have been admitted to a Level I trauma center serving metropolitan Atlanta, Georgia. Methods: A retrospective analysis of trauma patients admitted to a level 1 trauma center for VRIs over a 3 year period from 2011 to 2013. Data were obtained from the Grady Memorial Hospital (GMH) trauma registry, which serves metropolitan Atlanta, GA. De-identified variables selected included gender, race/ethnicity, age, type of VRI, and year of admission. All analyses were conducted utilizing SAS version 9.2. Results: Of the total number of patients (n=2859) the majority were male (89%), African- American (80%) and between the ages of 20-40 years (61%). The majority of patients (55%) were admitted to the hospital for gunshot wounds followed by assault (33%) and stab wounds (12%). The numbers of VRI patients admitted were similar in each of the years 2011, 2012, and 2013, which represent 31%, 35%, and 34% of the total, respectively. Conclusions: Statistically significant differences were observed between gender, race and age with respect to all VRIs included in the analyses, particularly among African American males. Policy makers may consider targeting interventions accordingly to address VRIs. Further research is needed to identify other factors potentially associated with VRIs

Adaptive Behavior in Autism and Pervasive Developmental Disorder-Not Otherwise Specified: Microanalysis of Scores on the Vineland Adaptive Behavior Scales

The purpose of this study is to provide a microanalysis of differences in adaptive functioning seen between well-matched groups of school-aged children with autism and those diagnosed as having Pervasive Developmental Disorder-Not Otherwise Specified, all of whom functioned in the mild to moderate range of intellectual impairment. Findings indicate that the major area of difference between children with autism and those with Pervasive Developmental Disorder-Not Otherwise Specified, was expressive communication; specifically, the use of elaborations in syntax and morphology and in pragmatic use of language to convey and to seek information in discourse. Linear discriminant function analysis revealed that scores on just three of these expressive communication item sets correctly identified subjects in the two diagnostic categories with 80% overall accuracy. Implications of these findings for both diagnosis and intervention with children with Autism Spectrum Disorders will be discussed

Sources, behaviour and mitigation strategies influencing indoor air quality

The particulate impact on air quality of typical domestic behaviours (e.g. cleaning and cooking) and their potential mitigation strategies (e.g. increasing ventilation) was investigated in the DOMESTIC unit at University of Chester. A 'typical day' based on the UK Time Use Survey of 2014-15 and tested under 2 separate ventilation conditions for 2 days each. This clearly indicated the impacts of different activities and the reduction of particulate levels with higher ventilation

Experimental mapping of soluble protein domains using a hierarchical approach

Exploring the function and 3D space of large multidomain protein targets often requires sophisticated experimentation to obtain the targets in a form suitable for structure determination. Screening methods capable of selecting well-expressed, soluble fragments from DNA libraries exist, but require the use of automation to maximize chances of picking a few good candidates. Here, we describe the use of an insertion dihydrofolate reductase (DHFR) vector to select in-frame fragments and a split-GFP assay technology to filter-out constructs that express insoluble protein fragments. With the incorporation of an IPCR step to create high density, focused sublibraries of fragments, this cost-effective method can be performed manually with no a priori knowledge of domain boundaries while permitting single amino acid resolution boundary mapping. We used it on the well-characterized p85α subunit of the phosphoinositide-3-kinase to demonstrate the robustness and efficiency of our methodology. We then successfully tested it onto the polyketide synthase PpsC from Mycobacterium tuberculosis, a potential drug target involved in the biosynthesis of complex lipids in the cell envelope. X-ray quality crystals from the acyl-transferase (AT), dehydratase (DH) and enoyl-reductase (ER) domains have been obtained

False negative rates in Drosophila cell-based RNAi screens: a case study

<p>Abstract</p> <p>Background</p> <p>High-throughput screening using RNAi is a powerful gene discovery method but is often complicated by false positive and false negative results. Whereas false positive results associated with RNAi reagents has been a matter of extensive study, the issue of false negatives has received less attention.</p> <p>Results</p> <p>We performed a meta-analysis of several genome-wide, cell-based <it>Drosophila </it>RNAi screens, together with a more focused RNAi screen, and conclude that the rate of false negative results is at least 8%. Further, we demonstrate how knowledge of the cell transcriptome can be used to resolve ambiguous results and how the number of false negative results can be reduced by using multiple, independently-tested RNAi reagents per gene.</p> <p>Conclusions</p> <p>RNAi reagents that target the same gene do not always yield consistent results due to false positives and weak or ineffective reagents. False positive results can be partially minimized by filtering with transcriptome data. RNAi libraries with multiple reagents per gene also reduce false positive and false negative outcomes when inconsistent results are disambiguated carefully.</p