Reduction of Real Power Loss and Safeguarding of Voltage Constancy by Artificial Immune System Algorithm

In this paper, Artificial Immune System (AIS) algorithm is used for solving reactive power problem. Artificial Immune System Algorithm, also termed as the machine learning approach to Artificial Intelligence, are powerful stochastic optimization techniques with potential features of random search, hill climbing, statistical sampling and competition. Artificial immune system algorithmic approach to power system optimization these ideas are embedded into proposed algorithm for solving reactive dispatch problem. In order to evaluate the proposed algorithm, it has been tested in standard IEEE 30,118 bus systems and compared to other specified algorithms. Simulation results show better performance of the proposed AIS algorithm in reducing the real power loss and preservation of voltage stability

Comparative Analyses of Pandemic H1N1 and Seasonal H1N1, H3N2, and Influenza B Infections Depict Distinct Clinical Pictures in Ferrets

Influenza A and B infections are a worldwide health concern to both humans and animals. High genetic evolution rates of the influenza virus allow the constant emergence of new strains and cause illness variation. Since human influenza infections are often complicated by secondary factors such as age and underlying medical conditions, strain or subtype specific clinical features are difficult to assess. Here we infected ferrets with 13 currently circulating influenza strains (including strains of pandemic 2009 H1N1 [H1N1pdm] and seasonal A/H1N1, A/H3N2, and B viruses). The clinical parameters were measured daily for 14 days in stable environmental conditions to compare clinical characteristics. We found that H1N1pdm strains had a more severe physiological impact than all season strains where pandemic A/California/07/2009 was the most clinically pathogenic pandemic strain. The most serious illness among seasonal A/H1N1 and A/H3N2 groups was caused by A/Solomon Islands/03/2006 and A/Perth/16/2009, respectively. Among the 13 studied strains, B/Hubei-Wujiagang/158/2009 presented the mildest clinical symptoms. We have also discovered that disease severity (by clinical illness and histopathology) correlated with influenza specific antibody response but not viral replication in the upper respiratory tract. H1N1pdm induced the highest and most rapid antibody response followed by seasonal A/H3N2, seasonal A/H1N1 and seasonal influenza B (with B/Hubei-Wujiagang/158/2009 inducing the weakest response). Our study is the first to compare the clinical features of multiple circulating influenza strains in ferrets. These findings will help to characterize the clinical pictures of specific influenza strains as well as give insights into the development and administration of appropriate influenza therapeutics

Enhanced Antifibrinolytic Efficacy of a Plasmin-Specific Kunitz-Inhibitor (60-Residue Y11T/L17R with C-Terminal IEK) of Human Tissue Factor Pathway Inhibitor Type-2 Domain1

Current antifibrinolytic agents reduce blood loss by inhibiting plasmin active sites (e.g., aprotinin) or by preventing plasminogen/tissue plasminogen activator (tPA) binding to fibrin clots (e.g., ε-aminocaproic acid and tranexamic acid); however, they have adverse side effects. Here, we expressed 60-residue (NH2NAE . . . IEKCOOH) Kunitz domain1 (KD1) mutants of human tissue factor pathway inhibitor type-2 that inhibit plasmin as well as plasminogen activation. A single (KD1-L17R-KCOOH) and a double mutant (KD1-Y11T/L17R- KCOOH) were expressed in Escherichia coli as His-tagged constructs, each with enterokinase cleavage sites. KD1-Y11T/L17R-KCOOH was also expressed in Pichia pastoris. KD1-Y11T/L17R-KCOOH inhibited plasmin comparably to aprotinin and bound to the kringle domains of plasminogen/plasmin and tPA with Kd of ~50 nM and ~35 nM, respectively. Importantly, compared to aprotinin, KD1-L17R-KCOOH and KD1-Y11T/L17R-KCOOH did not inhibit kallikrein. Moreover, the antifibrinolytic potential of KD1-Y11T/L17R-KCOOH was better than that of KD1-L17R-KCOOH and similar to that of aprotinin in plasma clot-lysis assays. In thromboelastography experiments, KD1-Y11T/L17R-KCOOH was shown to inhibit fibrinolysis in a dose dependent manner and was comparable to aprotinin at a higher concentration. Further, KD1-Y11T/L17R-KCOOH did not induce cytotoxicity in primary human endothelial cells or fibroblasts. We conclude that KD1-Y11T/L17R-KCOOH is comparable to aprotinin, the most potent known inhibitor of plasmin and can be produced in large amounts using Pichia

Optimization of production, biochemical characterization and In Vitro evaluation of the therapeutic potential of fibrinolytic enzymes from a new Bacillus Amyloliquefaciens

The capacity of fibrinolytic enzymes to degrade blood clots makes them of high relevance in medicine and in the pharmaceutical industry. In this work, forty-three microorganisms of the genus Bacillus were evaluated for their potential to produce fibrinolytic proteases. Thirty bacteria were confirmed as producers of fibrinolytic enzymes, the best results obtained for the strain Bacillus amyloliquefaciens UFPEDA 485. The optimization of the enzyme production conditions was done by a central composite design (CCD) star 23 that allowed to define the optimal conditions for soybean flour and glucose concentrations and agitation rate. The highest fibrinolytic activity (FA) of 813 U mL-1 and a degradation of blood clot in vitro of 62% were obtained in a medium with 2% (w/v) of soybean flour and 1% (w/v) glucose at 200 rpm after 48 h of cultivation, at pH 7.2 and 37 °C. The obtained fibrinolytic enzyme was characterized biochemically. Fibrinolytic activity was inhibited by PMSF (fluoride methylphenylsulfonyl - C7H7FO2S) 91.52% and EDTA (ethylenediaminetetraacetic acid - C10H16N2O8) 89.4%, confirming to be a serine- metallo protease. The optimum pH and temperature were 7.0 and 37 oC, respectively, and the enzyme was stable for 12 h. The fibrinolytic activity at physiological conditions of this enzyme produced by Bacillus amyloliquefaciens UFPEDA 485, as well as its long term stability, demonstrate that it has suitable characteristics for human and veterinary applications, and promises to be a powerful drug for the treatment of vascular diseases.We express our thanks to Coordination for the Improvement of Higher Level Education Personnel (CAPES) - Doctoral Sandwich Program (PDSE) Nº 0259/ 12-8 and National Council for Scientific and Technological Development (CNPq) - Nº 202026/2011-6 for the financial support

An Estimate of the Numbers and Density of Low-Energy Structures (or Decoys) in the Conformational Landscape of Proteins

The conformational energy landscape of a protein, as calculated by known potential energy functions, has several minima, and one of these corresponds to its native structure. It is however difficult to comprehensively estimate the actual numbers of low energy structures (or decoys), the relationships between them, and how the numbers scale with the size of the protein.We have developed an algorithm to rapidly and efficiently identify the low energy conformers of oligo peptides by using mutually orthogonal Latin squares to sample the potential energy hyper surface. Using this algorithm, and the ECEPP/3 potential function, we have made an exhaustive enumeration of the low-energy structures of peptides of different lengths, and have extrapolated these results to larger polypeptides.We show that the number of native-like structures for a polypeptide is, in general, an exponential function of its sequence length. The density of these structures in conformational space remains more or less constant and all the increase appears to come from an expansion in the volume of the space. These results are consistent with earlier reports that were based on other models and techniques

SUMO-Targeted Ubiquitin Ligase, Rad60, and Nse2 SUMO Ligase Suppress Spontaneous Top1–Mediated DNA Damage and Genome Instability

Through as yet undefined proteins and pathways, the SUMO-targeted ubiquitin ligase (STUbL) suppresses genomic instability by ubiquitinating SUMO conjugated proteins and driving their proteasomal destruction. Here, we identify a critical function for fission yeast STUbL in suppressing spontaneous and chemically induced topoisomerase I (Top1)–mediated DNA damage. Strikingly, cells with reduced STUbL activity are dependent on tyrosyl–DNA phosphodiesterase 1 (Tdp1). This is notable, as cells lacking Tdp1 are largely aphenotypic in the vegetative cell cycle due to the existence of alternative pathways for the removal of covalent Top1–DNA adducts (Top1cc). We further identify Rad60, a SUMO mimetic and STUbL-interacting protein, and the SUMO E3 ligase Nse2 as critical Top1cc repair factors in cells lacking Tdp1. Detection of Top1ccs using chromatin immunoprecipitation and quantitative PCR shows that they are elevated in cells lacking Tdp1 and STUbL, Rad60, or Nse2 SUMO ligase activity. These unrepaired Top1ccs are shown to cause DNA damage, hyper-recombination, and checkpoint-mediated cell cycle arrest. We further determine that Tdp1 and the nucleotide excision repair endonuclease Rad16-Swi10 initiate the major Top1cc repair pathways of fission yeast. Tdp1-based repair is the predominant activity outside S phase, likely acting on transcription-coupled Top1cc. Epistasis analyses suggest that STUbL, Rad60, and Nse2 facilitate the Rad16-Swi10 pathway, parallel to Tdp1. Collectively, these results reveal a unified role for STUbL, Rad60, and Nse2 in protecting genome stability against spontaneous Top1-mediated DNA damage

A comprehensive assessment of N-terminal signal peptides prediction methods

Background: Amino-terminal signal peptides (SPs) are short regions that guide the targeting of secretory proteins to the correct subcellular compartments in the cell. They are cleaved off upon the passenger protein reaching its destination. The explosive growth in sequencing technologies has led to the deposition of vast numbers of protein sequences necessitating rapid functional annotation techniques, with subcellular localization being a key feature. Of the myriad software prediction tools developed to automate the task of assigning the SP cleavage site of these new sequences, we review here, the performance and reliability of commonly used SP prediction tools. Results: The available signal peptide data has been manually curated and organized into three datasets representing eukaryotes, Gram-positive and Gram-negative bacteria. These datasets are used to evaluate thirteen prediction tools that are publicly available. SignalP (both the HMM and ANN versions) maintains consistency and achieves the best overall accuracy in all three benchmarking experiments, ranging from 0.872 to 0.914 although other prediction tools are narrowing the performance gap. Conclusion: The majority of the tools evaluated in this study encounter no difficulty in discriminating between secretory and non-secretory proteins. The challenge clearly remains with pinpointing the correct SP cleavage site. The composite scoring schemes employed by SignalP may help to explain its accuracy. Prediction task is divided into a number of separate steps, thus allowing each score to tackle a particular aspect of the prediction.12 page(s