Characterization of Recombination Events Leading to the Production of an Ecotropic Replication-Competent Retrovirus in a GP+envAM12-Derived Producer Cell Line

AbstractReplication-competent retrovirus (RCR) was identified in a GP+envAM12-derived producer cell, containing the MFG-S-Neo retroviral vector, using a marker rescue assay. Studies were undertaken to determine the origin and structure of this RCR. Receptor interference assays demonstrated that the virus was pseudotyped with an ecotropic envelope. Molecular analysis demonstrated the presence of a MoMLV ecotropic env recombinant where the neomycin resistance gene of the MFG-S-Neo vector was replaced by MoMLV ecotropic env. Additional recombinants linking the retroviral pol gene to neo and the neo gene to MoMLV env were also identified. A full-length MoMLV retroviral genome was detected by nested PCR in the contaminated amphotropic producer cells and in cells infected with its supernatant. Unexpectedly, this was also present in the GP+E86 packaging cells together with a previously undescribed envelope construct possessing a full 5′ and 3′ LTR, although these cells were consistently negative for the presence of RCR. These anomalies in the GP+E86 packaging cell line result in increased homology with the MFG-S-Neo vector, leading to an increased risk for the production of RCR. Our findings point to a need for increased vigilance when using these packaging lines to generate replication-defective retrovirus

Modeling Electricity Consumption using Modified Newton's Method

In this paper we present modified Newton’s model (MNM) to model electricity consumption data. A previous method to model electricity consumption data was done using forecasting technique (FT) and artificial neural networks (ANN). A drawback to previous techniques is that computations give less reliable results when compared to MNM. A comparative analysis is carried out for FT, ANN and MNM to investigate which of these methods is the most reliable technique. The results indicate that MNM model reduced mean absolute percentage error (MAPE) to 0.93%, while those of FT and ANN were 3.01% and 3.11%, respectively. Based on these error measures, the study shows that the three methods are highly accurate modeling techniques, but MNM was found to be the best technique when mining information. Experimental results indicate that MNM is the most accurate when compared to FT and ANN and thus has the best competitive performance level

A Comparative Analysis of Techniques for Forecasting Electricity Consumption

The issue of obtaining reliable forecasting methods for electricity consumption has been widely discussed by past research work. This is due to the increased demand for electricity and as a result, the development of efficient pricing models. Several techniques have been used in past research for forecasting electricity consumption. This includes the use of forecasting, time-series technique (FTST) and artificial neural networks (ANN). This paper introduces a modified Newton’s model (MNM) to forecast electricity consumption. Forecasting models are developed from historical data and predictive estimates are obtained. This research work utilizes data from Universiti Malaysia Sarawak, a public university in Malaysia, from 2009 to 2012. The variables considered in this research include electricity consumption for different months over the years

Nanostructure of cellulose microfibrils in spruce wood

The structure of cellulose microfibrils in wood is not known in detail, despite the abundance of cellulose in woody biomass and its importance for biology, energy, and engineering. The structure of the microfibrils of spruce wood cellulose was investigated using a range of spectroscopic methods coupled to small-angle neutron and wide-angle X-ray scattering. The scattering data were consistent with 24-chain microfibrils and favored a “rectangular” model with both hydrophobic and hydrophilic surfaces exposed. Disorder in chain packing and hydrogen bonding was shown to increase outwards from the microfibril center. The extent of disorder blurred the distinction between the I alpha and I beta allomorphs. Chains at the surface were distinct in conformation, with high levels of conformational disorder at C-6, less intramolecular hydrogen bonding and more outward-directed hydrogen bonding. Axial disorder could be explained in terms of twisting of the microfibrils, with implications for their biosynthesis

Synthesis, crystallization and characterization of diastereomeric salts formed by ephedrine and malic acid in water

A screening of crystallization conditions for the diastereomeric salts formed by L/D-malic acid and a common resolving agent, L-Ephedrine, in water is reported. So far, 7 different forms of salts with 1:1 and 2:1 stoichiometries were successfully crystallized, including one previously reported 1:1 LL salt. All new salts were characterized by differential scanning calorimetry, thermogravimetric and elemental analysis, infrared spectroscopy, solid-state NMR and powder XRD. 1:1 stoichiometry favours anhydrate formation while 2:1 stoichiometry tends to give monohydrate forms. Two monohydrates dehydrate on heating to produce anhydrous salts. A 2:1 LD trihydrate was discovered by vapor sorption experiments and is stable only at high relative humidity (>50%). Differences in stoichiometry and hydrate formation during salt crystallization, leading to differences in physicochemical properties could have a significant impact on resolution conditions and outcome

Perspective: Current advances in solid-state NMR spectroscopy

In contrast to the rapid and revolutionary impact of solution-state Nuclear Magnetic Resonance (NMR) on modern chemistry, the field of solid-state NMR has matured more slowly. This reflects the major technical challenges of much reduced spectral resolution and sensitivity in solid-state as compared to solution-state spectra, as well as the relative complexity of the solid state. In this perspective, we outline the technique developments that have pushed resolution to intrinsic limits and the approaches, including ongoing major developments in the field of Dynamic Nuclear Polarisation, that have enhanced spectral sensitivity. The information on local structure and dynamics that can be obtained using these gains in sensitivity and resolution is illustrated with a diverse range of examples from large biomolecules to energy materials and pharmaceuticals and from both ordered and highly disordered materials. We discuss how parallel developments in quantum chemical calculation, particularly density functional theory, have enabled experimental data to be translated directly into information on local structure and dynamics, giving rise to the developing field of “NMR crystallography

European LeukemiaNet laboratory recommendations for the diagnosis and management of chronic myeloid leukemia

From the laboratory perspective, effective management of patients with chronic myeloid leukemia (CML) requires accurate diagnosis, assessment of prognostic markers, sequential assessment of levels of residual disease and investigation of possible reasons for resistance, relapse or progression. Our scientific and clinical knowledge underpinning these requirements continues to evolve, as do laboratory methods and technologies. The European LeukemiaNet convened an expert panel to critically consider the current status of genetic laboratory approaches to help diagnose and manage CML patients. Our recommendations focus on current best practice and highlight the strengths and pitfalls of commonly used laboratory tests