Streptolysin-O reversible permeabilisation is an effective method to transfect siRNAs into myeloma cells

RNA interference (RNAi) has been shown to be a valuable tool to specifically target gene expression in a number of organisms becoming an indispensable weapon in the arsenal in functional genomics. In this study, we demonstrate that streptolysin-O (SLO) reversible permeabilisation is an efficient method to deliver small interfering RNAs (siRNAs) to hard-to-transfect human myeloma cell lines. We used published, pre-validated siRNAs for ERK2 and non-silencing siRNA control. We transfected siRNAs into human myeloma cell lines using SLO reversible permeabilisation method. Flow cytometry and western blot analysis were performed to assess the effect of SLO on transfection efficiency and ERK2 knockdown. These experiments demonstrate that SLO reversible permeabilisation method is an efficient and easy-to-use method to deliver siRNAs into human myeloma cell lines. Optimised SLO permeabilisation method showed to transfect >80% of JIM-3, H929, RPM18226 and U266 cells, with minimal effect on cell viability (<10%) and cell cycle. Equally important, SLO permeabilisation induced a substantial knockdown of ERK2 at the protein level. These studies demonstrate that reversible SLO permeabilisation can successfully be applied to hard-to-transfect human myeloma cell lines to effectively silence genes. (C) 2008 Published by Elsevier B.V.

Efficient Learning of Bayesian Networks with Bounded Tree-width

Learning Bayesian networks with bounded tree-width has attracted much attention recently, because low tree-width allows exact inference to be performed efficiently. Some existing methods \cite{korhonen2exact, nie2014advances} tackle the problem by using $k$-trees to learn the optimal Bayesian network with tree-width up to $k$. Finding the best $k$-tree, however, is computationally intractable. In this paper, we propose a sampling method to efficiently find representative $k$-trees by introducing an informative score function to characterize the quality of a $k$-tree. To further improve the quality of the $k$-trees, we propose a probabilistic hill climbing approach that locally refines the sampled $k$-trees. The proposed algorithm can efficiently learn a quality Bayesian network with tree-width at most $k$. Experimental results demonstrate that our approach is more computationally efficient than the exact methods with comparable accuracy, and outperforms most existing approximate methods.

Detecting stealthy attacks: Efficient monitoring of suspicious activities on computer networks

Stealthy attackers move patiently through computer networks - taking days, weeks or months to accomplish their objectives in order to avoid detection. As networks scale up in size and speed, monitoring for such attack attempts is increasingly a challenge. This paper presents an efficient monitoring technique for stealthy attacks. It investigates the feasibility of proposed method under number of different test cases and examines how design of the network affects the detection. A methodological way for tracing anonymous stealthy activities to their approximate sources is also presented. The Bayesian fusion along with traffic sampling is employed as a data reduction method. The proposed method has the ability to monitor stealthy activities using 10-20% size sampling rates without degrading the quality of detection.

Efficient simulations with electronic open boundaries

We present a reformulation of the hairy-probe method for introducing electronic open boundaries that is appropriate for steady-state calculations involving nonorthogonal atomic basis sets. As a check on the correctness of the method we investigate a perfect atomic wire of Cu atoms and a perfect nonorthogonal chain of H atoms. For both atom chains we find that the conductance has a value of exactly one quantum unit and that this is rather insensitive to the strength of coupling of the probes to the system, provided values of the coupling are of the same order as the mean interlevel spacing of the system without probes. For the Cu atom chain we find in addition that away from the regions with probes attached, the potential in the wire is uniform, while within them it follows a predicted exponential variation with position. We then apply the method to an initial investigation of the suitability of graphene as a contact material for molecular electronics. We perform calculations on a carbon nanoribbon to determine the correct coupling strength of the probes to the graphene and obtain a conductance of about two quantum units corresponding to two bands crossing the Fermi surface. We then compute the current through a benzene molecule attached to two graphene contacts and find only a very weak current because of the disruption of the π conjugation by the covalent bond between the benzene and the graphene. In all cases we find that very strong or weak probe couplings suppress the current.

Activated lignin‒chitosan extruded blends for efficient adsorption of methylene blue

This work investigates the production of activated lignin-chitosan extruded (ALiCE) pellets with controlled particle size distribution (almost spherical: dp ~500‒1000µm) for efficient methylene blue adsorption. The novel preparation method employed in this study successfully produced activated lignin-chitosan pellets. Structural and morphological characterizations were performed using BET, FTIR and SEM-EDX analyses. The influence of contact time, solution pH, ionic strength, initial adsorbate concentration and desorption studies was investigated. The experimental data fitted well with the Langmuir isotherm (R2 = 0.997), yielding a maximum adsorption capacity of 36.25mg/g. The kinetic data indicated that methylene blue (MB) adsorption onto ALiCE can be represented by the pseudo second-order-model with intraparticle processes initially controlling the process of MB adsorption. Overall, these results indicate that the novel ALiCE offers great potential for removing cationic organic pollutants from rivers and streams.

An Efficient Precoder Design for Multiuser MIMO Cognitive Radio Networks with Interference Constraints

We consider a linear precoder design for an underlay cognitive radio multiple-input multiple-output broadcast channel, where the secondary system consisting of a secondary base-station (BS) and a group of secondary users (SUs) is allowed to share the same spectrum with the primary system. All the transceivers are equipped with multiple antennas, each of which has its own maximum power constraint. Assuming zero-forcing method to eliminate the multiuser interference, we study the sum rate maximization problem for the secondary system subject to both per-antenna power constraints at the secondary BS and the interference power constraints at the primary users. The problem of interest differs from the ones studied previously that often assumed a sum power constraint and/or single antenna employed at either both the primary and secondary receivers or the primary receivers. To develop an efficient numerical algorithm, we first invoke the rank relaxation method to transform the considered problem into a convex-concave problem based on a downlink-uplink result. We then propose a barrier interior-point method to solve the resulting saddle point problem. In particular, in each iteration of the proposed method we find the Newton step by solving a system of discrete-time Sylvester equations, which help reduce the complexity significantly, compared to the conventional method. Simulation results are provided to demonstrate fast convergence and effectiveness of the proposed algorithm. 

Efficient and Selectable Production of Reactive Species Using a Nanosecond Pulsed Discharge in Gas Bubbles in Liquid

A plasma gas bubble-in-liquid method for high production of selectable reactive species using a nanosecond pulse generator has been developed. The gas of choice is fed through a hollow needle in a point-to-plate bubble discharge, enabling improved selection of reactive species. The increased interface reactions, between the gas-plasma and water through bubbles, give higher productivity. H₂O₂ was the predominant species produced using Ar plasma, while predominantly  and NO₂ were generated using air plasma, in good agreement with the observed emission spectra. This method has nearly 100% selectivity for H₂O₂, with seven times higher production, and 92% selectivity for , with nearly twice the production, compared with a plasma above the water.