A high efficient and consistent method for harvesting large volumes of high-titre lentiviral vectors

Lentiviral vectors pseudotyped with vesicular stomatitis virus glycoprotein (VSV-G) are emerging as the vectors of choice for in vitro and in vivo gene therapy studies. However, the current method for harvesting lentivectors relies upon ultracentrifugation at 50 000 g for 2 h. At this ultra-high speed, rotors currently in use generally have small volume capacity. Therefore, preparations of large volumes of high-titre vectors are time-consuming and laborious to perform. In the present study, viral vector supernatant harvests from vector-producing cells (VPCs) were pre-treated with various amounts of poly-L-lysine (PLL) and concentrated by low speed centrifugation. Optimal conditions were established when 0.005% of PLL (w/v) was added to vector supernatant harvests, followed by incubation for 30 min and centrifugation at 10 000 g for 2 h at 4 degreesC. Direct comparison with ultracentrifugation demonstrated that the new method consistently produced larger volumes (6 ml) of high-titre viral vector at 1 x 10(8) transduction unit (TU)/ml (from about 3000 ml of supernatant) in one round of concentration. Electron microscopic analysis showed that PLL/viral vector formed complexes, which probably facilitated easy precipitation at low-speed concentration (10 000 g), a speed which does not usually precipitate viral particles efficiently. Transfection of several cell lines in vitro and transduction in vivo in the liver with the lentivector/PLL complexes demonstrated efficient gene transfer without any significant signs of toxicity. These results suggest that the new method provides a convenient means for harvesting large volumes of high-titre lentivectors, facilitate gene therapy experiments in large animal or human gene therapy trials, in which large amounts of lentiviral vectors are a prerequisite.

A mixture model-based approach to the clustering of microarray expression data

Motivation: This paper introduces the software EMMIX-GENE that has been developed for the specific purpose of a model-based approach to the clustering of microarray expression data, in particular, of tissue samples on a very large number of genes. The latter is a nonstandard problem in parametric cluster analysis because the dimension of the feature space (the number of genes) is typically much greater than the number of tissues. A feasible approach is provided by first selecting a subset of the genes relevant for the clustering of the tissue samples by fitting mixtures of t distributions to rank the genes in order of increasing size of the likelihood ratio statistic for the test of one versus two components in the mixture model. The imposition of a threshold on the likelihood ratio statistic used in conjunction with a threshold on the size of a cluster allows the selection of a relevant set of genes. However, even this reduced set of genes will usually be too large for a normal mixture model to be fitted directly to the tissues, and so the use of mixtures of factor analyzers is exploited to reduce effectively the dimension of the feature space of genes. Results: The usefulness of the EMMIX-GENE approach for the clustering of tissue samples is demonstrated on two well-known data sets on colon and leukaemia tissues. For both data sets, relevant subsets of the genes are able to be selected that reveal interesting clusterings of the tissues that are either consistent with the external classification of the tissues or with background and biological knowledge of these sets.

An action research report on the Korean national digital library

This paper presents the results of my action research. I was involved in establishing and running a digital library that was founded by the government of South Korea. The process involved understanding the relationship between the national IT infrastructure and the success factors of the digital library. In building, the national IT infrastructure, a digital library system was implemented; it combines all existing digitized university libraries and can provide overseas information, such as foreign journal articles, instantly and freely to every Korean researcher. An empirical survey was made as a part of the action research; the survey determined user satisfaction in the newly established national digital library. After obtaining the survey results, I suggested that the current way of running the nationwide government-owned digital library should be retained. (C) 2002 Elsevier Science B.V. All rights reserved.

A simulated annealing algorithm for finding consensus sequences

Motivation: A consensus sequence for a family of related sequences is, as the name suggests, a sequence that captures the features common to most members of the family. Consensus sequences are important in various DNA sequencing applications and are a convenient way to characterize a family of molecules. Results: This paper describes a new algorithm for finding a consensus sequence, using the popular optimization method known as simulated annealing. Unlike the conventional approach of finding a consensus sequence by first forming a multiple sequence alignment, this algorithm searches for a sequence that minimises the sum of pairwise distances to each of the input sequences. The resulting consensus sequence can then be used to induce a multiple sequence alignment. The time required by the algorithm scales linearly with the number of input sequences and quadratically with the length of the consensus sequence. We present results demonstrating the high quality of the consensus sequences and alignments produced by the new algorithm. For comparison, we also present similar results obtained using ClustalW. The new algorithm outperforms ClustalW in many cases.

Research commentary: Information systems and conceptual modeling - A research agenda

Within the information systems field, the task of conceptual modeling involves building a representation of selected phenomena in some domain. High-quality conceptual-modeling work is important because it facilitates early detection and correction of system development errors. It also plays an increasingly important role in activities like business process reengineering and documentation of best-practice data and process models in enterprise resource planning systems. Yet little research has been undertaken on many aspects of conceptual modeling. In this paper, we propose a framework to motivate research that addresses the following fundamental question: How can we model the world to better facilitate our developing, implementing, using, and maintaining more valuable information systems? The framework comprises four elements: conceptual-modeling grammars, conceptual-modeling methods, conceptual-modeling scripts, and conceptual-modeling contexts. We provide examples of the types of research that have already been undertaken on each element and illustrate research opportunities that exist.