Synthesis, Characterization and DNA Cleavage of Copper(II) Complex with D,L-Dithiothreitol

Purpose: To study deoxyribonucleic acid (DNA) shearing capability of copper(II) complex of dithiothreitol (DTT) and to fevaluate its potential application in cancer therapy.Methods: A parrot green complex was synthesized by grinding copper acetate monohydrate and DTT in 1:2 molar ratio in a mortar until no fumes of acetic acid were observed. The complex was characterized using attenuated total reflectance-Fourier transform infra-red (ATR-FTIR), and x-ray diffraction (XRD) techniques. Further information was also collected through Karl Fischer titration, thermogravimetric analysis (TGA) and (magnetic moment. Cleavage of DNA was determined by agarose gel electrophoresis. The gel was then stained, analyzed and photographed under ultraviolet (UV) light.Results: ATR-FTIR confirmed the formation of copper(II) complex with DTT by binding through thiol group based on the disappearance of the thiol (-SH) stretching peak at 2545 cm-1. The crystalline structure was elucidated by a sharp intense peak at 38.520 in XRD spectrum while the octahedral geometry of complex was inferred from a magnetic moment of 1.72 B.M. The results for water content obtained by Karl Fischer titration and TGA revealed that water molecules are not part of the coordination sphere of the complex. Cleavage study of DNA showed that the complex completely sheared the circular DNA compared to pure DTT.Conclusion: Solvent free synthesis of Copper(II)-DTT complex has been successfully achieved, and an anhydrous complex with octahedral geometry obtained. The complex has a greater potential to shear DNA molecule than pure DTT.Keywords: DNA shearing, Copper(II) complex, Dithiothreitol, Attenuated total reflectance-Fourier transform infra-red, Karl Fischer titration, Magnetic momen

Development of ANFIS Control System for Seismic Response Reduction using Multi-Objective Genetic Algorithm

Adaptive neuro fuzzy inference system (ANFIS) and Genetic algorithm (GA) was proposed in this study to reduce dynamic responses of a seismically excited building. A multi-objective genetic algorithm (MOGA) was used to optimize the ANFIS+GA controller. Two MR dampers were used as multiple control devices and a scaled five-story building model was selected as an example structure. A fuzzy control algorithm was compared with the proposed ANFIS and ANFIS+GA controller. Adaptive neuro-fuzzy inference system (ANFIS) and Ganetic algorithm with several outputs was proposed. In case study, after numerical simulation, it has been verified that the ANFIS control algorithm can present better control performance compared to the fuzzy control algorithm in reducing both displacement and acceleration responses

Efficient Non-Linear Covert Channel Detection in TCP Data Streams

Cyber-attacks are causing losses amounted to billions of dollars every year due to data breaches and vulnerabilities. The existing tools for data leakage prevention and detection are often bypassed by using various different types of sophisticated techniques such as network steganography for stealing the data. This is due to several weaknesses which can be exploited by a threat actor in existing detection systems. The weaknesses are high time and memory training complexities as well as large training datasets. These challenges become worse when the amount of generated data increases in every second in many realms. In addition, the number of false positives is high which makes them inaccurate. Finally, there is a lack of a framework catering for the needs such as raising alerts as well as data monitoring and updating/adapting of a threshold value used for checking the data packets for covert data. In order to overcome these weaknesses, this paper proposes a novel framework that includes elements such as continuous data monitoring, threshold maintenance, and alert notification. This paper also proposes a model based on statistical measures to detect covert data leakages, especially for non-linear chaotic data. The main advantage of the proposed model is its capability to provide results with tolerance/threshold values much more efficiently. Our experiments indicate that the proposed framework has low false positives and outperforms various existing techniques in terms of accuracy and efficiency

Changing pattern of antimicrobial susceptibility of organisms causing community acquired urinary tract infections

Objective: To assess common organisms causing Urinary Treat Infection (UTI) in this community and to see antimicrobial susceptibility pattern of these isolates. Design: Prospective study on urine samples. Setting: Tertiary care hospital in Karachi.Methods: Over a period of 8 years (1990-97) 9,892 urine samples grew significant bacteriuria for various organisms. All Gram negative rods and entercocci was identified by using API 20E and API 32 strips respectively. Staphylococci were identified by catalase, coagulase and D\u27Nase tests. Antimicrobial sensitivity testing of all isolates was performed on Diagnostic Sensitivity Test plates by Kerby Bauer method. The discs used were ampicillin, trimethoprim-sulfamethoxazole, cefotaxime, ceftriaxone, aztreonam, ofloxacin, carbenicillin, amikacin, gentamicin, penicillin, clindamycin, methicillin, vancomycin, ceftazidime, cefuroxime, Nalidixic acid, pipemedic acid and Nitrofurantoin. Results: Our results indicate that E. coli and Klebsiella aerogenes are the most common organisms causing UTI in this community. Other organisms involved are Pseudomonas aeroginosa, Enterobacter species, Enterococcus, Proteus mirabillus, Staphylococcus aureus and Staphylococcus saprophyticus. Organisms resistant to various antimicrobial agents such as gentamicin, Amikacin, Ofloxacin, Cefotaxime and Ceftazidime are increasing. Conclusion: In conclusion, E. coli and Klebsiella aerogenes are the most common organisms causing UTI in this community. Pattern of antibiotic susceptibility to first line antibiotics is changing. Antimicrobial susceptibility testing of all isolates is crucial for the treatment of UTI

Invariant Solutions for Nonhomogeneous Discrete Diffusion Equation

One-dimensional optimal systems for nonhomogeneous discrete heat equation with different source terms are calculated. By utilizing these optimal systems invariant solutions are found. Also generating solutions are calculated, using the elements of the symmetry algebra

Factors associated with long-term species composition in dry tropical forests of Central India

The long-term future of species composition in forests depends on regeneration. Many factors can affect regeneration, including human use, environmental conditions, and species' traits. This study examines the influence of these factors in a tropical deciduous forest of Central India, which is heavily used by local, forest-dependent residents for livestock grazing, fuel-wood extraction, construction and other livelihood needs. We measure size-class proportions (the ratio of abundance of a species at a site in a higher size class to total abundance in both lower and higher size classes) for 39 tree species across 20 transects at different intensities of human use. The size-class proportions for medium to large trees and for small to medium-sized trees were negatively associated with species that are used for local construction, while size class proportions for saplings to small trees were positively associated with those species that are fire resistant and negatively associated with livestock density. Results indicate that grazing and fire prevent non-fire resistant species from reaching reproductive age, which can alter the long term composition and future availability of species that are important for local use and ecosystem services. Management efforts to reduce fire and forest grazing could reverse these impacts on long-term forest composition

Identifying knowledge gaps in the research and management of invasive species in India

India, a megadiverse tropical country is grappling with the issue of biological invasions. As a signatory to the Convention on Biological Diversity, India is committed for managing its major biological invasions by 2020. Lack of prioritization of invasive species for control and management is the biggest hurdle for achieving this commitment. We reviewed 21 High Concern Invasive Species (HiCIS) across four major ecosystems (terrestrial mainland, island, freshwater, and marine) in India, utilizing the prioritization framework for understanding the existing knowledge and gaps. We reviewed the existing peer-reviewed and grey literature on HiCIS for information on their ecology, impacts, and management. Prioritization framework provided “priority scores” and “confidence scores” to each HiCIS, where priority score comprised of the species’ ecology and its management lacunae. Confidence score represented the reliability of the priority score. We found that invasions on terrestrial mainland ecosystem in India are the most studied invasions followed by freshwater, island, and marine ecosystem. Priority score of a given HiCIS was positively correlated with its impacts on biodiversity (R = 0.63), physical environment (R = 0.70), and ecosystem services (R = 0.60). This correlation supports scientific focus on deleterious species. The study also indicates policies and guidelines in place for management of invasions as a part of a larger scheme or Legal Act, resulting in their obscurity to the managers, and hindering management of HiCIS. This quantitative synthesis provides a model framework for countries struggling with channelizing management efforts to an overwhelmingly large number of invasive species