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Modern society is mostly dependent on online activities like official or social communications, fund transfers and so on. Unauthorized system access is one of the utmost concerns than ever before in cyber systems. For any cyber system, robust authentication is an absolute necessity for ensuring security and reliable access to all type of transactions. However, more than 80% of the current authentication systems are password based, and surprisingly, they are prone to direct and indirect cracking via guessing or side channel attacks. The inspiration of Negative Authentication System (NAS) is based on the negative selection algorithm. In NAS, the password-based authentication data for valid users are termed as password profile or self-region (positive profile); any element other than the self-region is defined as non-self-region in the same representative space. The anti-password detectors are generated which covers most of the non-self-region. There are also some uncovered regions left in the non-self-region for inducing uncertainty to the attackers. In this work, we describe the design and implementation of three approaches of NAS and its efficacy over the other authentication methods. These three approaches represent three different ways to achieve obfuscation of password points with non-password space. The experiments are conducted with both real and simulated password profiles to justify the efficiency of different implementations of NAS. [ABSTRACT FROM AUTHOR]

Introduction: Metabolic tracer analysis (MTA) is a collection of principles, rules and tools for the interpretation of stable isotope incorporation patterns. One example is the GAIMS algorithm for the deconvolution of the UDP-GlcNAc C mass isotopologue profile. GAIMS has been presented as a powerful, yet currently unavailable, proof-of-concept-only technique. Objectives: We aimed to build a tool inspired by the original GAIMS algorithm, providing identical functionality and straightforward extensibility towards alternative composite metabolites. Methods: We implemented MAIMS by applying Multistart metaheuristics combined with an efficient hybrid stopping rule to solve the non-convex optimization underlying the deconvolution problem. By testing our tool on several theoretical datasets, we were able to confirm its robust and reproducible performance. Results: MAIMS is capable of finding the individual contributions of specifically labeled molecular subunits to large composite metabolites (such as UDP-GlcNAc and ATP) upon U-C-glucose administration and thereby hinting on the activity of several metabolic pathway activities. Applied to proliferating endothelial cells (ECs), MAIMS led to several interesting metabolic insights and generally proved to be a sensitive way for relatively measuring specific pathway activities and for detecting compartmentalized pools of precursor metabolites. Conclusion: MAIMS is a powerful and extendible tool for isotopologue profile deconvolution tasks and is freely available on github as an open-source Python (Python 2.7 and 3.5 + compliant) script for command line usage. (). [ABSTRACT FROM AUTHOR]

The Sleeping Beauty (SB) transposon is a promising technology platform for gene transfer in vertebrates; however, its efficiency of gene insertion can be a bottleneck in primary cell types. A large-scale genetic screen in mammalian cells yielded a hyperactive transposase (SB100X) with ∼100-fold enhancement in efficiency when compared to the first-generation transposase. SB100X supported 35–50% stable gene transfer in human CD34+ cells enriched in hematopoietic stem or progenitor cells. Transplantation of gene-marked CD34+ cells in immunodeficient mice resulted in long-term engraftment and hematopoietic reconstitution. In addition, SB100X supported sustained (>1 year) expression of physiological levels of factor IX upon transposition in the mouse liver in vivo. Finally, SB100X reproducibly resulted in 45% stable transgenesis frequencies by pronuclear microinjection into mouse zygotes. The newly developed transposase yields unprecedented stable gene transfer efficiencies following nonviral gene delivery that compare favorably to stable transduction efficiencies with integrating viral vectors and is expected to facilitate widespread applications in functional genomics and gene therapy. [ABSTRACT FROM AUTHOR]