Simple sequence repeat (SSR) markers are widely used in many plant and animal genomes due to their abundance, hypervariability, and suitability for high-throughput analysis. Development of SSR markers using molecular methods is time consuming, laborious, and expensive. Use of computational approaches to mine ever-increasing sequences such as expressed sequence tags (ESTs) in public databases permits rapid and economical discovery of SSRs. Most of such efforts to date focused on mining SSRs from monocotyledonous ESTs. In this study, we have computationally mined and examined the abundance of SSRs in more than 1.54 million ESTs belonging to 55 dicotyledonous species. The frequency of ESTs containing SSRs among species ranged from 2.65% to 16.82%. Dinucleotide repeats were found to be the most abundant followed by tri- or mono-nucleotide repeats. The motifs A/T, AG/GA/CT/TC, and AAG/AGA/GAA/CTT/TTC/TCT were the predominant mono-, di-, and tri-nucleotide SSRs, respectively. Most of the mononucleotide SSRs contained 15-25 repeats, whereas the majority of the di- and tri-nucleotide SSRs contained 5-10 repeats. The comprehensive SSR survey data presented here demonstrates the potential of in silico mining of ESTs for rapid development of SSR markers for genetic analysis and applications in dicotyledonous crops.

The NARMA model is an exact representation of the input-output behavior of finite-dimensional nonlinear discrete-time dynamical systems in a neighborhood of the equilibrium state. However, it is not convenient for purposes of adaptive control using neural networks due to its nonlinear dependence on the control input. Hence, quite often, approximate methods are used for realizing the neural controllers to overcome computational complexity. In this paper, we introduce two classes of models which are approximations to the NARMA model, and which are linear in the control input. The latter fact substantially simplifies both the theoretical analysis as well as the practical implementation of the controller. Extensive simulation studies have shown that the neural controllers designed using the proposed approximate models perform very well, and in many cases even better than an approximate controller designed using the exact NARMA model. In view of their mathematical tractability as well as their success in simulation studies, a case is made in this paper that such approximate input-output models warrant a detailed study in their own right.

Objective To assess the safety and efficacy of etoricoxib, a selective cyclo-oxygenase-2 inhibitor, in comparison with indometacin in the treatment of acute gouty arthritis. Design Randomised, double blind, active comparator controlled trial. Setting 43 outpatient study centres in 11 countries. Participants 142 men and eight women (75 patients per treatment group) aged 18 years or over presenting with clinically diagnosed acute gout within 48 hours of onset. Interventions Etoricoxib 120 mg administered orally once daily versus indometacin 50 mg administered orally three times daily, both for 8 days Main outcome measures Patients' assessment of pain in the study joint over days 2 to 5 (primary end point); investigators' and patients' global assessments of response to treatment and tenderness of the study joint (key secondary end points). Results Etoricoxib showed efficacy comparable to indometacin. Patients' assessment of pain in the study joint (0-4 point Likert scale, "no pain" to "extreme pain") over days 2 to 5 showed a least squares mean change from baseline of − 1.72 (95% confidence interval − 1.90 to − 1.55) for etoricoxib and − 1.83 ( − 2.01 to − 1.65) for indometacin. The difference between treatment groups met prespecified comparability criteria. All other efficacy end points, including those reflecting reduction in inflammation and analgesia, provided corroborative evidence of comparable efficacy. Significant pain relief was evident at the first measurement, 4 hours after the first dose of treatment. Prespecified safety analyses revealed that drug related adverse experiences occurred significantly less frequently with etoricoxib (22.7%) than with indometacin (46.7%) (P=0.003), although overall adverse experience rates were similar between the two treatment groups. Conclusion Etoricoxib 120 mg once daily provides rapid and effective treatment for acute gouty arthritis comparable to indometacin 50 mg three times daily. Etoricoxib was generally safe and well tolerated in this study.

Research in bioinformatics in the past decade has generated a large volume of textual biological data stored in databases such as MEDLINE. It takes a copious amount of effort and time, even for expert users, to manually extract useful information embedded in such a large volume of retrieved data and automated intelligent text analysis tools are increasingly becoming essential. In this article, we present a simple analysis and knowledge discovery method that can identify related genes as well as their shared functionality (if any) based on a collection of relevant retrieved relevant MEDLINE documents. The relative computational simplicity of the proposed method makes it possible to process and analyze large volumes of data in a short time. Hence, it significantly contributes to and enhances a user's ability to discover such embedded information. Two case studies are presented that indicate the usefulness of the proposed method.

In information-filtering environments, uncertainties associated with changing interests of the user and the dynamic document stream must be handled efficiently. In this article, a filtering model is proposed that decomposes the overall task into subsystem functionalities and highlights the need for multiple adaptation techniques to cope with uncertainties. A filtering system, SIFTER, has been implemented based on the model, using established techniques in information retrieval and artificial intelligence. These techniques include document representation by a vector-space model, document classification by unsupervised learning, and user modeling by reinforcement learning. The system can filter information based on content and a user's specific interests. The user's interests are automatically learned with only limited user intervention in the form of optional relevance feedback for documents. We also describe experimental studies conducted with SIFTER to filter computer and information science documents collected from the Internet and commercial database services. The experimental results demonstrate that the system performs very well in filtering documents in a realistic problem setting.

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This 2-part, double-blind, placebo-controlled study was conducted to determine the safety and efficacy of etoricoxib, a COX-2 selective inhibitor, for the treatment of hemophilic arthropathy. In part 1 (6 weeks), 102 patients (> 12 years old) with hemophilic arthropathy were randomized to receive 90 mg etoricoxib once daily or placebo (1:1 ratio). In part 2 (6 months), 51 patients taking placebo in part 1 were randomized to receive 90 mg etoricoxib or 25 mg rofecoxib once daily; patients taking etoricoxib in part 1 continued the same treatment. Efficacy end points included