Are Ohio's Nursing Homes Ready for an Emergency?

On any given day in Ohio's nursing homes, there are nearly 78,000 residents with physical or cognitive impairments. This means that nursing homes may be vulnerable during emergencies that require either evacuation or necessitate sheltering in place. A module regarding preparedness and planning in Ohio nursing homes was included in the 2013 Biennial Long-term Care Survey administered by the Scripps Gerontology Center. Findings and implications are discussed

Structural and magnetic properties of β\beta-Li2_2IrO3_3 after grazing-angle focused ion beam thinning

Manipulating the size and orientation of quantum materials is often used to tune emergent phenomena, but precise control of these parameters is also necessary from an experimental point of view. Various synthesis techniques already exist, such as epitaxial thin film growth and chemical etching, that are capable of producing specific sample dimensions with high precision. However, certain materials exist as single crystals that are often difficult to manipulate, thereby limiting their studies to a certain subset of experimental techniques. One particular class of these materials are the lithium and sodium iridates that are promising candidates for hosting a Kitaev quantum spin liquid state. Here we present a controlled method of using a focused ion beam at grazing incidence to reduce the size of a $\beta$-Li$_2$IrO$_3$ single crystal to a thickness of 1 $\mu m$. Subsequent x-ray diffraction measurements show the lattice remains intact, albeit with a larger mosaic spread. The integrity of the magnetic order is also preserved as the temperature dependent magnetic diffraction peak follows the same trend as its bulk counterpart with a transition temperature at TN = 37.5 K. Our study demonstrates a technique that opens up the possibility of nonequilibrium experiments where submicron thin samples are often essential

Investigating Multi-cancer Biomarkers and Their Cross-predictability in the Expression Profiles of Multiple Cancer Types

Microarray technology has been widely applied to the analysis of many malignancies, however, integrative analyses across multiple studies are rarely investigated. In this study we performed a meta-analysis on the expression profiles of four published studies analyzing organ donor, benign tissues adjacent to tumor and tumor tissues from liver, prostate, lung and bladder samples. We identified 99 distinct multi-cancer biomarkers in the comparison of all three tissues in liver and prostate and 44 in the comparison of normal versus tumor in liver, prostate and lung. The bladder samples appeared to have a different list of biomarkers from the other three cancer types. The identified multi-cancer biomarkers achieved high accuracy similar to using whole genome in the within-cancer-type prediction. They also performed superior than the one using whole genome in inter-cancer-type prediction. To test the validity of the multi-cancer biomarkers, 23 independent prostate cancer samples were evaluated and 96% accuracy was achieved in inter-study prediction from the original prostate, liver and lung cancer data sets respectively. The result suggests that the compact lists of multi-cancer biomarkers are important in cancer development and represent the common signatures of malignancies of multiple cancer types. Pathway analysis revealed important tumorogenesis functional categories

An RNA aptamer that interferes with the DNA binding of the HSF transcription activator

Heat shock factor (HSF) is a conserved and highly potent transcription activator. It is involved in a wide variety of important biological processes including the stress response and specific steps in normal development. Reagents that interfere with HSF function would be useful for both basic studies and practical applications. We selected an RNA aptamer that binds to HSF with high specificity. Deletion analysis defined the minimal binding motif of this aptamer to be two stems and one stem–loop joined by a three-way junction. This RNA aptamer interferes with normal interaction of HSF with its DNA element, which is a key regulatory step for HSF function. The DNA-binding domain plus a flanking linker region on the HSF (DL) is essential for the RNA binding. Additionally, this aptamer inhibits HSF-induced transcription in vitro in the complex milieu of a whole cell extract. In contrast to the previously characterized NF-κB aptamer, the HSF aptamer does not simply mimic DNA binding, but rather binds to HSF in a manner distinct from DNA binding to HSF

Translating Glucose Variability Metrics into the Clinic via Continuous Glucose Monitoring: A Graphical User Interface for Diabetes Evaluation (CGM-GUIDE)

Background: Several metrics of glucose variability have been proposed to date, but an integrated approach that provides a complete and consistent assessment of glycemic variation is missing. As a consequence, and because of the tedious coding necessary during quantification, most investigators and clinicians have not yet adopted the use of multiple glucose variability metrics to evaluate glycemic variation. Methods: We compiled the most extensively used statistical techniques and glucose variability metrics, with adjustable hyper- and hypoglycemic limits and metric parameters, to create a user-friendly Continuous Glucose Monitoring Graphical User Interface for Diabetes Evaluation (CGM-GUIDE-). In addition, we introduce and demonstrate a novel transition density profile that emphasizes the dynamics of transitions between defined glucose states. Results: Our combined dashboard of numerical statistics and graphical plots support the task of providing an integrated approach to describing glycemic variability. We integrated existing metrics, such as SD, area under the curve, and mean amplitude of glycemic excursion, with novel metrics such as the slopes across critical transitions and the transition density profile to assess the severity and frequency of glucose transitions per day as they move between critical glycemic zones. Conclusions: By presenting the above-mentioned metrics and graphics in a concise aggregate format, CGM-GUIDE provides an easy to use tool to compare quantitative measures of glucose variability. This tool can be used by researchers and clinicians to develop new algorithms of insulin delivery for patients with diabetes and to better explore the link between glucose variability and chronic diabetes complications.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/90437/1/dia-2E2011-2E0099.pd

<em>Escherichia coli</em>: A Versatile Platform for Recombinant Protein Expression

Among the living organisms, Escherichia coli has been the most common choice employed for recombinant protein expression. In addition to its well-characterized genetics, E. coli is fast growing, relatively cheap, and easy to handle. These fine properties, in conjunction with the success achieved in transforming plasmid DNA into E. coli, as well as the advent of various genetic engineering techniques in the 1970s, have enabled E. coli to be considered as the most favorable host for genetic manipulations. The recent advances in better comprehension of regulatory controls of gene expression and the availability of various novel approaches, which include both intracellular, e.g., through intein-mediated expression and self-cleavages, and extracellular, e.g., through the use of secretion signals, to achieve successful expression of the target proteins in E. coli further support the view that E. coli is the most promising host choice for heterologous protein expression

Genome Abnormalities Precede Prostate Cancer and Predict Clinical Relapse

The prediction of prostate cancer clinical outcome remains a major challenge after the diagnosis, even with improved early detection by prostate-specific antigen (PSA) monitoring. To evaluate whether copy number variation (CNV) of the genomes in prostate cancer tumor, in benign prostate tissues adjacent to the tumor (AT), and in the blood of patients with prostate cancer predicts biochemical (PSA) relapse and the kinetics of relapse, 241 samples (104 tumor, 49 matched AT, 85 matched blood, and 3 cell lines) were analyzed using Affymetrix SNP 6.0 chips. By using gene-specific CNV from tumor, the genome model correctly predicted 73% (receiver operating characteristic P = 0.003) cases for relapse and 75% (P < 0.001) cases for short PSA doubling time (PSADT, <4 months). The gene-specific CNV model from AT correctly predicted 67% (P = 0.041) cases for relapse and 77% (P = 0.015) cases for short PSADT. By using median-sized CNV from blood, the genome model correctly predicted 81% (P < 0.001) cases for relapse and 69% (P = 0.001) cases for short PSADT. By using median-sized CNV from tumor, the genome model correctly predicted 75% (P < 0.001) cases for relapse and 80% (P < 0.001) cases for short PSADT. For the first time, our analysis indicates that genomic abnormalities in either benign or malignant tissues are predictive of the clinical outcome of a malignancy