CysView: protein classification based on cysteine pairing patterns

CysView is a web-based application tool that identifies and classifies proteins according to their disulfide connectivity patterns. It accepts a dataset of annotated protein sequences in various formats and returns a graphical representation of cysteine pairing patterns. CysView displays cysteine patterns for those records in the data with disulfide annotations. It allows the viewing of records grouped by connectivity patterns. CysView's utility as an analysis tool was demonstrated by the rapid and correct classification of scorpion toxin entries from GenPept on the basis of their disulfide pairing patterns. It has proved useful for rapid detection of irrelevant and partial records, or those with incomplete annotations. CysView can be used to support distant homology between proteins. CysView is publicly available at http://research.i2r.a-star.edu.sg/CysView/.

Spray drift of pesticides arising from aerial application in cotton

This paper presents results from field studies carried out during the 1993-1998 Australian cotton (Gossypium hirsutum L.) seasons to monitor off-target droplet movement of endosulfan (6,7,8,9,10,10-hexachloro-1,5,5a,6,9,9a-hexahydro-6,9-methano-2,4,3-benzodioxathiepin 3-oxide) insecticide applied to a commercial cotton crop. Averaged over a wide range of conditions, off-target deposition 500 m downwind of the field boundary was approximately 2% of the field-applied rate with oil-based applications and 1% with water-based applications. Mean airborne drift values recorded 100 m downwind of a single flight line were a third as much with water-based application compared with oil-based application. Calculations using a Gaussian diffusion model and the U.S. Spray Drift Task Force AgDRIFT model produced downwind drift profiles that compared favorably with experimental data. Both models and data indicate that by adopting large droplet placement (LDP) application methods and incorporating crop buffer distances, spray drift can be effectively managed.

Melphalan dosing regimens for management of recurrent melanoma by isolated limb perfusion: Application of a physiological pharmacokinetic model based on melphalan distribution in the isolated perfused rat hindlimb

The optimal dosing schedule for melphalan therapy of recurrent malignant melanoma in isolated limb perfusions has been examined using a physiological pharmacokinetic model with data from isolated rat hindlimb perfusions (IRHP), The study included a comparison of melphalan distribution in IRHP under hyperthermia and normothermia conditions. Rat hindlimbs were perfused with Krebs-Henseleit buffer containing 4.7% bovine serum albumin at 37 or 41.5 degrees C at a flow rate of 4 ml/min. Concentrations of melphalan in perfusate and tissues were determined by high performance liquid chromatography with fluorescence detection, The concentration of melphalan in perfusate and tissues was linearly related to the input concentration. The rate and amount of melphalan uptake into the different tissues was higher at 41.5 degrees C than at 37 degrees C. A physiological pharmacokinetic model was validated from the tissue and perfusate time course of melphalan after melphalan perfusion. Application of the model involved the amount of melphalan exposure in the muscle, skin and fat in a recirculation system was related to the method of melphalan administration: single bolus > divided bolus > infusion, The peak concentration of melphalan in the perfusate was also related to the method of administration in the same order, Infusing the total dose of melphalan over 20 min during a 60 min perfusion optimized the exposure of tissues to melphalan whilst minimizing the peak perfusate concentration of melphalan. It is suggested that this method of melphalan administration may be preferable to other methods in terms of optimizing the efficacy of melphalan whilst minimizing the limb toxicity associated with its use in isolated limb perfusion.

The development and application of a novel safety-catch linker for BOC-based assembly of libraries of cyclic peptides

Cyclic peptides are appealing targets in the drug-discovery process. Unfortunately, there currently exist no robust solid-phase strategies that allow the synthesis of large arrays of discrete cyclic peptides. Existing strategies are complicated, when synthesizing large libraries, by the extensive workup that is required to extract the cyclic product from the deprotection/cleavage mixture. To overcome this, we have developed a new safety-catch linker. The safety-catch concept described here involves the use of a protected catechol derivative in which one of the hydroxyls is masked with a benzyl group during peptide synthesis, thus making the linker deactivated to aminolysis. This masked derivative of the linker allows BOC solid-phase peptide assembly of the linear precursor. Prior to cyclization, the linker is activated and the linear peptide deprotected using conditions commonly employed (TFMSA), resulting in deprotected peptide attached to the activated form of the linker. Scavengers and deprotection adducts are removed by simple washing and filtration. Upon neutralization of the N-terminal amine, cyclization with concomitant cleavage from the resin yields the cyclic peptide in DMF solution. Workup is simple solvent removal. To exemplify this strategy, several cyclic peptides were synthesized targeted toward the somatostatin and integrin receptors. From this initial study and to show the strength of this method, we were able to synthesize a cyclic-peptide library containing over 400 members. This linker technology provides a new solid-phase avenue to access large arrays of cyclic peptides.

Application of a simplified method based on regular regime approach to determine the effective moisture diffusivity of mixture of low molecular weight sugars and maltodextrin during desorption

The binary diffusivities of water in low molecular weight sugars; fructose, sucrose and a high molecular weight carbohydrate; maltodextrin (DE 11) and the effective diffusivities of water in mixtures of these sugars (sucrose, glucose, fructose) and maltodextrin (DE 11) were determined using a simplified procedure based on the Regular Regime Approach. The effective diffusivity of these mixtures exhibited both the concentration and molecular weight dependence. Surface stickiness was observed in all samples during desorption, with fructose exhibiting the highest and maltodextrin the lowest. (C) 2002 Elsevier Science Ltd. All rights reserved.

MR image-based measurement of rates of change in volumes of brain structures. Part II: Application to a study of Alzheimer's disease and normal aging

We present global and regional rates of brain atrophy measured on serially acquired T1-weighted brain MR images for a group of Alzheimer's disease (AD) patients and age-matched normal control (NC) subjects using the analysis procedure described in Part I. Three rates of brain atrophy: the rate of atrophy in the cerebrum, the rate of lateral ventricular enlargement and the rate of atrophy in the region of temporal lobes, were evaluated for 14 AD patients and 14 age-matched NC subjects. All three rates showed significant differences between the two groups, However, the greatest separation of the two groups was obtained when the regional rates were combined. This application has demonstrated that rates of brain atrophy, especially in specific regions of the brain, based on MR images can provide sensitive measures for evaluating the progression of AD. These measures will be useful for the evaluation of therapeutic effects of novel therapies for AD. (C) 2002 Elsevier Science Inc. All rights reserved.

Model-based clustering in gene expression microarrays: An application to breast cancer data

In microarray studies, the application of clustering techniques is often used to derive meaningful insights into the data. In the past, hierarchical methods have been the primary clustering tool employed to perform this task. The hierarchical algorithms have been mainly applied heuristically to these cluster analysis problems. Further, a major limitation of these methods is their inability to determine the number of clusters. Thus there is a need for a model-based approach to these. clustering problems. To this end, McLachlan et al. [7] developed a mixture model-based algorithm (EMMIX-GENE) for the clustering of tissue samples. To further investigate the EMMIX-GENE procedure as a model-based -approach, we present a case study involving the application of EMMIX-GENE to the breast cancer data as studied recently in van 't Veer et al. [10]. Our analysis considers the problem of clustering the tissue samples on the basis of the genes which is a non-standard problem because the number of genes greatly exceed the number of tissue samples. We demonstrate how EMMIX-GENE can be useful in reducing the initial set of genes down to a more computationally manageable size. The results from this analysis also emphasise the difficulty associated with the task of separating two tissue groups on the basis of a particular subset of genes. These results also shed light on why supervised methods have such a high misallocation error rate for the breast cancer data.

Construction of bacterial artificial chromosome libraries and their application in developing PCR-based markers closely linked to a major locus conditioning bruchid resistance in mungbean (Vigna radiata L. Wilczek)

Bacterial artificial chromosome (BAC) libraries have been widely used in different aspects of genome research. In this paper we report the construction of the first mungbean (Vigna radiata L. Wilczek) BAC libraries. These BAC clones were obtained from two ligations and represent an estimated 3.5 genome equivalents. This correlated well with the screening of nine random single-copy restriction fragment length polymorphism probes, which detected on average three BACs each. These mungbean clones were successfully used in the development of two PCR-based markers linked closely with a major locus conditioning bruchid (Callosobruchus chinesis) resistance. These markers will be invaluable in facilitating the introgression of bruchid resistance into breeding programmes as well as the further characterisation of the resistance locus.

Application of the cross-entropy method to the buffer allocation problem in a simulation-based environment

The buffer allocation problem (BAP) is a well-known difficult problem in the design of production lines. We present a stochastic algorithm for solving the BAP, based on the cross-entropy method, a new paradigm for stochastic optimization. The algorithm involves the following iterative steps: (a) the generation of buffer allocations according to a certain random mechanism, followed by (b) the modification of this mechanism on the basis of cross-entropy minimization. Through various numerical experiments we demonstrate the efficiency of the proposed algorithm and show that the method can quickly generate (near-)optimal buffer allocations for fairly large production lines.