Integration of knowledge-based metabolic predictions with liquid chromatography data-dependent tandem mass spectrometry for drug metabolism studies: application to studies on the biotransformation of indinavir

Despite recent advances in the application of data-dependent liquid chromatography/tandem mass spectrometry (LC/MS/MS) to the identification of drug metabolites in complex biological matrixes, a prior knowledge of the likely routes of biotransformation of the therapeutic agent of interest greatly facilitates the detection and structural characterization of its metabolites. Thus, prediction of the [M + H]+ m/z values of expected metabolites allows for the construction of user-defined MS(n) protocols that frequently reveal the presence of minor drug metabolites, even in the presence of a vast excess of coeluting endogenous constituents. However, this approach suffers from inherent user bias, as a result of which additional "survey scans" (e.g., precursor ion and constant neutral loss scans) are required to ensure detection of as many drug-related components in the sample as possible. In the present study, a novel approach to this problem has been evaluated, in which knowledge-based predictions of metabolic pathways are first derived from a commercial database, the output from which is used to formulate a list-dependent LC/MS(n) data acquisition protocol. Using indinavir as a model drug, a substructure similarity search on the MDL metabolism database with a similarity index of 60% yielded 188 "hits", pointing to the possible operation of two hydrolytic, two N-dealkylation, three N-glucuronidation, one N-methylation, and several aromatic and aliphatic oxidation pathways. Integration of this information with data-dependent LC/MS(n) analysis using an ion trap mass spectrometer led to the identification of 18 metabolites of indinavir following incubation of the drug with human hepatic postmitochondrial preparations. This result was accomplished with only a single LC/MS(n) run, representing significant savings in instrument use and operator time, and afforded an accurate view of the complex in vitro metabolic profile of this drug.     

Characterizing files in the modern Gnutella network

The Internet has witnessed an explosive increase in the popularity of Peer-to-Peer (P2P) file-sharing applications during the past few years. As these applications become more popular, it becomes increasingly important to characterize their behavior in order to improve their performance and quantify their impact on the network. In this paper, we present a measurement study on characteristics of available files in the modern Gnutella system. We develop two new methodologies to capture accurate snapshots of available files in a large-scale P2P system. These methodologies were implemented in a parallel crawler that captures the entire overlay topology of the system where each peer in the overlay is annotated with its available files. We have captured more than 50 snapshots of the Gnutella system that span over 1 year period. Using these snapshots, we conduct three types of analysis on available files: (1) Static analysis, (2) Topological analysis, and (3) dynamic analysis. Our results reveal several interesting properties of available files in Gnutella that can be leveraged to improve the design and evaluation of P2P file-sharing applications. This paper extends and supplants the earlier version of this paper presented at MMCN 2006 [1]. This material is based upon work supported by the National Science Foundation (NSF) under Grant No. Nets-NBD-0627202, CAREER Award CNS-0448639, and an unrestricted gift from Cisco Systems. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the NSF or Cisco.     

Modified multi-layered perceptron applied to packing and covering problems

Prior knowledge of the input–output problems often leads to supervised learning restrictions that can hamper the multi-layered perceptron’s (MLP) capacity to find an optimal solution. Restrictions such as fixing weights and modifying input variables may influence the potential convergence of the back-propagation algorithm. This paper will show mathematically how to handle such constraints in order to obtain a modified version of the traditional MLP capable of solving targeted problems. More specifically, it will be shown that fixing particular weights according to prior information as well as transforming incoming inputs can enable the user to limit the MLP search to a desired type of solution. The ensuing modifications pertaining to the learning algorithm will be established. Moreover, four supervised improvements will offer insight on how to control the convergence of the weights towards an optimal solution. Finally, applications involving packing and covering problems will be used to illustrate the potential and performance of this modified MLP.     

Face Detection Using Mixture of MLP Experts

This paper presents a face detection method which makes use of a modified mixture of experts. In order to improve the face detection accuracy, a novel structure is introduced which uses the multilayer perceptrons (MLPs), as expert and gating networks, and employs a new learning algorithm to adapt with the MLPs. We call this model Mixture of MLP Experts (MMLPE). Experiments using images from the CMU-130 test set demonstrate the robustness of our method in detecting faces with wide variations in pose, facial expression, illumination, and complex backgrounds. The MMLPE produces promising high detection rate of 98.8% with ten false positives.     

IT Consulting: Communication Skills Are Key

IT consultants are professionals who have joined an existing consultancy or have established a consulting business as a single individual or with colleagues. Regardless of their origin, IT consultants perform a variety of tasks, from idea generation to design to project management support. Chief among the success factors in IT consulting is effective communication - an idea that seems to have eluded most of the research purporting to help IT consultants. IT consultants must be proactive in opening communication lines with customers. Ensuring that expectations are clear is a major benefit of effective communication because it helps minimize the damage from an outcome in which the customer is unhappy     

Automated Two-Axes Optical Fiber Alignment Using Grayscale Technology

In this paper, we report a new method for actuating an optical fiber in two axes. This device enables in package active alignment of an optical fiber towards reducing the time and cost of optoelectronic packaging by eliminating the need for expensive and slow macroalignment machines. Opposing comb-drive actuators with integrated three-dimensional (3-D) wedges (fabricated using grayscale technology) create a dynamic v-groove to alter the horizontal and vertical alignment of an optical fiber cantilever. All structural components are fabricated in silicon using a single lithography and dry-etching step, making the system conducive to batch fabrication, an essential element to minimize the cost of including in-package alignment capabilities. Actuation of a cleaved fiber tip greater than 30 mum in each direction is demonstrated, with automated fiber alignment times on the order of 10s, comparable to those achieved using macroalignment systems. Alignment tolerances are held below 1.25 mum over a 20-by-20-mum actuation area for the first time. The influences of alignment target location, actuation parameters, and alignment algorithm on total alignment time are also presented     

Relationships among aging, IQ, and intracranial volume in alcoholics and control subjects.

The current article examined the relationships among aging, intelligence, intracranial volume, and brain shrinkage in alcoholics and nonalcoholic controls. Magnetic resonance imaging was used to measure intracranial and cerebral volumes in 146 subjects with alcohol use disorders and 42 comparison subjects who were not alcoholic. The authors' findings show that performance on Block Design decreases as alcoholics age, and this decrease is predicted by brain shrinkage. This is consistent with a process of cumulative brain damage related to alcohol use. However, the authors' data also show that vocabulary does not decrease with age and is correlated with premorbid brain size as measured by intracranial volume, suggesting that lower verbal ability precedes heavy alcohol use and may be a risk factor for alcoholism. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Experimental and numerical results of dynamics behavior of a nonlinear piezoelectric beam

This article presents a numerical formulation and experimental implementation for the dynamics behavior verification of the nonlinear piezoelectric beam through harmonic excitation. The nonlinear piezoelectric beam dynamic analysis program is developed with MATLAB software. To verify the nonlinear piezoelectric beam dynamic analysis results, the experimental results are used for the vibration analysis of a piezoelectric beam to the harmonic excitation of the base of the beam. Then, the piezoelectric effect on the output voltage, velocity, acceleration values, and the time response are obtained. Afterwards, the effects of the excitation velocity and the position of concentrated mass on the output voltage are verified.     

Optimizing a bi-objective multi-product EPQ model with defective items,rework and limited orders: NSGA-II and MOPSO algorithms

In this paper, a bi-objective multi-products economic production quantity (EPQ) model is developed, in which the number of orders is limited and imperfect items that are re-workable are produced. The objectives of the problem are minimization of the total inventory costs as well as minimizing the required warehouse space. The model is shown to be of a bi-objective nonlinear programming type, and in order to solve it two meta-heuristic algorithms namely, the non-dominated sorting genetic algorithm (NSGA-II) and multi-objective particle swarm optimization (MOPSO) algorithm, are proposed. To verify the solution obtained and to evaluate the performance of proposed algorithms, two-sample t-tests are employed to compare the means of the first objective value, the means of the second objective values, and the mean required CPU time of solving the problem using two algorithms. The results show while both algorithms are efficient to solve the model and the solution qualities of the two algorithms do not differ significantly, the computational CPU time of MOPSO is considerably lower than that of NSGA-II.