Vertebrate Animal Models of RP59: Current Status and Future Prospects

Retinitis pigmentosa-59 (RP59) is a rare, recessive form of RP, caused by mutations in the gene encoding DHDDS (dehydrodolichyl diphosphate synthase). DHDDS forms a heterotetrameric complex with Nogo-B receptor (NgBR; gene NUS1) to form a cis-prenyltransferase (CPT) enzyme complex, which is required for the synthesis of dolichol, which in turn is required for protein N-glycosylation as well as other glycosylation reactions in eukaryotic cells. Herein, we review the published phenotypic characteristics of RP59 models extant, with an emphasis on their ocular phenotypes, based primarily upon knock-in of known RP59-associated DHDDS mutations as well as cell type- and tissue-specific knockout of DHDDS alleles in mice. We also briefly review findings in RP59 patients with retinal disease and other patients with DHDDS mutations causing epilepsy and other neurologic disease. We discuss these findings in the context of addressing “knowledge gaps” in our current understanding of the underlying pathobiology mechanism of RP59, as well as their potential utility for developing therapeutic interventions to block the onset or to dampen the severity or progression of RP59.     

Transmission pricing and recovery of investment costs in the deregulated power system based on optimal circuit prices

Transmission pricing has become a major issue in the discussions about the deregulated electricity markets.Consequently,open access to the transmission system is one of the basic topics to allow competition among participants in the energy market.Transmission costs have an important impact on relative competition among participants in the energy market as well as on short-and long-term economic efficiencies of the whole electricity industry,although they represent only close to 10% of the energy market price.This paper deals with the design and tests of a transmission pricing method based on the optimal circuit prices derived from the economically adapted network(EAN).Prices derived from the EAN have the advantage of being in tune with the maximum revenue allowed to the owner of transmission assets and simplifying the optimal allocation of transmission costs among participants.Beginning from the conceptual design,the proposed method is tested on a three-bus network and on the IEEE 24-bus reliability test system.     

Inactivation of Escherichia coli O157:H7, Listeria monocytogenes, Salmonella enterica and Shigella flexneri on spinach leaves by X-ray

Several recent foodborne disease outbreaks associated with leafy green vegetables, including spinach, have been reported. X-ray is a non-thermal technology that has shown promise for reducing pathogenic and spoilage bacteria on spinach leaves. Inactivation of inoculated Escherichia coli O157:H7, Listeria monocytogenes, Salmonella enterica and Shigella flexneri on spinach leaves using X-ray at different doses (0.1, 0.2, 0.3, 0.5, 0.75, 1.0, 1.5 and 2.0 kGy) was studied. The effect of X-ray on color quality and microflora counts (mesophilic counts, psychrotrophic counts and yeast and mold counts) of untreated and treated spinach was also determined. A mixture of three strains of each tested organism was spot inoculated (100 μl) onto the surface of spinach leaves (approximately 8–9 log ml⁻¹), separately, and air-dried, followed by treatment with X-ray at 22 °C and 55–60% relative humidity. Surviving bacterial populations on spinach leaves were evaluated using a nonselective medium (tryptic soy agar) with a selective medium overlay for each bacteria; E. coli O157:H7 (CT-SMAC agar), L. monocytogenes (MOA), and S. enterica and S. flexneri (XLD). More than a 5 log CFU reduction/leaf was achieved with 2.0 kGy X-ray for all tested pathogens. Furthermore, treatment with X-ray significantly reduced the initial inherent microflora on spinach leaves and inherent levels were significantly (p < 0.05) lower than the control sample throughout refrigerated storage for 30 days. Treatment with X-ray did not significantly affect the color of spinach leaves, even when the maximum dose (2.0 kGy) was used.     

Antioxidant properties of various solvent extracts of potato peel,sugar beet pulp and sesame cake

BACKGROUND: Growing interest in the replacement of synthetic food antioxidants by natural ones has fostered research on vegetable sources and screening of raw materials to identify new antioxidants. The food‐processing industry generates substantial quantities of phenolic‐rich by‐products that could be valuable natural sources of antioxidants. In this study the antioxidant properties and total phenolic, flavonoid and flavonol contents of three industrial by‐products, sugar beet pulp, sesame cake and potato peel, extracted with various solvents were examined. Since different antioxidant compounds have different mechanisms of action, several methods were used to assess the antioxidant efficacy of extracts. RESULTS: Among the six solvents tested, methanol gave the highest extract yield of potato peel and sugar beet pulp, while diethyl ether gave the highest extract yield of sesame cake. Methanol exhibited the highest extraction ability for phenolic compounds, with total phenolics amounting to 2.91, 1.79 and 0.81 mg gallic acid equivalent g^?1 dry weight in potato peel, sugar beet pulp and sesame cake extracts respectively, and also showed the strongest antioxidant capacity in the three assays used. All three methods proved that potato peel extract had the highest antioxidant activity owing to its high content of phenolic compounds and flavonoids. CONCLUSION: On the basis of the results obtained, potato peel, sugar beet pulp and sesame cake extracts could serve as natural antioxidants owing to their significant antioxidant activity. Therefore they could be used as preservative ingredients in the food and/or pharmaceutical industries. Copyright © 2009 Society of Chemical Industry     

Sensitivity analysis of machine interference in manufacturing systems

A class of manufacturing systems is presented in which the machine interference problem plays an important role in production. We consider a single server (robot) in addition to two types of random machine stoppages with priorities. A detailed analysis has been focused on two measures: robot utilization and machine efficiency. It has been shown that one has to make a compromise between the above two sensitive measures. We have further computed the optimum number of machines that can be served by a robot. A novel optimization technique is used to fulfill this requirement. The simulation results reveal that the number of machines as well as the service rate can be utilized as decision variables in the problem at hand.     

Fuzzy logistic regression based on the least squares approach with application in clinical studies

To model fuzzy binary observations, a new model named “Fuzzy Logistic Regression” is proposed and discussed in this study. In fact, due to the vague nature of binary observations, no probability distribution can be considered for these data. Therefore, the ordinary logistic regression may not be appropriate. This study attempts to construct a fuzzy model based on possibility of success. These possibilities are defined by some linguistic terms such as …, low, medium, high…. Then, by use of the Extension principle, the logarithm transformation of “possibilistic odds” is modeled based on a set of crisp explanatory variables observations. Also, to estimate parameters in the proposed model, the least squares method in fuzzy linear regression is used. For evaluating the model, a criterion named the “capability index” is calculated. At the end, because of widespread applications of logistic regression in clinical studies and also, the abundance of vague observations in clinical diagnosis, the suspected cases to Systematic Lupus Erythematosus (SLE) disease is modeled based on some significant risk factors to detect the application of the model. The results showed that the proposed model could be a rational substituted model of an ordinary one in modeling the clinical vague status.     

GRAIL: a scalable index for reachability queries in very large graphs

Given a large directed graph, rapidly answering reachability queries between source and target nodes is an important problem. Existing methods for reachability tradeoff indexing time and space versus query time performance. However, the biggest limitation of existing methods is that they do not scale to very large real-world graphs. We present a simple yet scalable reachability index, called GRAIL, that is based on the idea of randomized interval labeling and that can effectively handle very large graphs. Based on an extensive set of experiments, we show that while more sophisticated methods work better on small graphs, GRAIL is the only index that can scale to millions of nodes and edges. GRAIL has linear indexing time and space, and the query time ranges from constant time to being linear in the graph order and size. Our reference C++ implementations are open source and available for download at http://www.code.google.com/p/grail/.