Synthesis of Novel Aporphine-Inspired Neuroreceptor Ligands

Aporphines are a group of tetracyclic alkaloids that belong to the ubiquitous tetrahydroisoquinoline family. The aporphine template is known to be associated with a range of biological activities. Aporphines have been explored as antioxidants, anti-tuberculosis, antimicrobial and anticancer agents. Within the Central Nervous Systems (CNS), aporphine alkaloids are known to possess high affinity for several clinically valuable targets including dopamine receptors (predominantly D1 and D2), serotonin receptors (5-HT1A and 5-HT7) and α adrenergic receptors. Aporphines are also inhibitors of the acetylcholinesterase enzyme – a clinical target for the treatment of Alzheimer’s disease. Considering the diverse profile of aporphine alkaloids at CNS receptors they can be considered as “privileged scaffold” for the design of CNS drugs. The aporphine alkaloid nantenine is a 5-HT2A receptor antagonist and has moderate affinity for the 5-HT2A receptor. Selective 5-HT2A antagonists have therapeutic potential for the treatment of a number of neuropsychiatric disorders including depression, schizophrenia and sleep disorders. The aporphine core of nantenine serves as a valuable lead for the identification of selective 5-HT2A antagonists. In order to understand the structural tolerance of the aporphine core required for 5-HT2A antagonism an exhaustive Structure Activity Relationship (SAR) study was designed.Accordingly, a diverse library of nantenine analogues was synthesized and evaluated for affinity at the 5-HT2A receptor. Results from the SAR studies demonstrate that the nitrogen atom of nantenine is required for affinity and that introduction of a phenyl ring at the C4 position is detrimental for 5-HT2A receptor affinity. At the C3 position, introduction of halogen atoms is beneficial for 5-HT2A antagonistic activity. Furthermore, a library of C3 analogues having hydrophobic substituents as well as ring D indole analogues is currently being evaluated for affinity at the 5-HT2A receptors. These compounds will further expand our understanding of the tolerance of the aporphine core required for 5-HT2A antagonism. In order to rationalize the affinity of certain high affinity ligands, molecular docking studies were conducted. Selected compounds were docked into a homology model of the 5-HT2A receptor to extract information about possible binding modes. Based on results of these studies, it is concluded that the interaction of C3 halogenated aporphine analogues with Phe339/Phe340 residues might be responsible for their enhanced affinity. Information obtained from molecular docking studies is being utilized for design of advanced generations of analogues. Finally, a novel series of flexible tris-(phenylalkyl)amines were synthesized and evaluated to test the importance of a rigid aporphine core as well as incorporation of N-phenylalkyl substituents. These compounds featuring a halogen substituent in ring C, were found to have high affinity and selectivity for the 5-HT2B receptor, with some of the compounds being more potent than the selective 5-HT2B antagonist SB200646. Results from this study indicate that ring C of these compounds is generally tolerant for halogen substitution. The synthetic feasibility of this newly identified template ( 4 high-yielding synthetic steps from commercially available materials) makes this scaffold attractive for the synthesis of larger libraries of analogs and promise for optimization of 5-HT2B affinity and selectivity

Modern Radiation Further Improves Survival in Non-Small Cell Lung Cancer: An Analysis of 288,670 Patients

Background: Radiation therapy plays an increasingly important role in the treatment of patients with non-small-cell lung cancer (NSCLC). The purpose of the present study is to assess the survival outcomes of radiotherapy treatment compared to other treatment modalities and to determine the potential role of advanced technologies in radiotherapy on improving survival. Methods: We used cancer incidence and survival data from the Surveillance, Epidemiology, and End Results database linked to U.S. Census data to compare survival outcomes of 288,670 patients with stage I-IV NSCLC treated between 1999 and 2008. The primary endpoint was overall survival. Results: Among the 288,670 patients diagnosed with stage I-IV NSCLC, 92,374 (32%) patients received radiotherapy-almost double the number receiving surgery (51,961, 18%). Compared to other treatment groups and across all stages of NSCLC, patients treated with radiotherapy showed greater median and overall survival than patients without radiation treatment (p < 0.0001). Radiotherapy had effectively improved overall survival regardless of age, gender, and histological categorization. Radiotherapy treatment received during the recent time period 2004 - 2008 is correlated with enhanced survival compared to the earlier time period 1999 - 2003. Conclusion: Radiation therapy was correlated with increased overall survival for all patients with primary NSCLC across stages. Combined surgery and radiotherapy treatment also correlates with improved survival, signaling the value of bimodal or multimodal treatments. Population-based increases in overall survival were seen in the recent time period, suggesting the potential role of advanced radiotherapeutic technologies in enhancing survival outcomes for lung cancer patients

Active yellow pages: a pipelined resource management architecture for wide-area network computing

This paper describes a novel, pipelined resource management architecture for computational grids. The design is based on two key realizations. One is that resource management involves a sequence of tasks that is best handled by a pipeline. As shown in the paper, this approach results, in a scalable architecture for decentralized scheduling. The other realization is that static aggregation of resources for improved scheduling is inadequate in wide-area computing environments because the needs of users and jobs change with both, location and time. The described architecture addresses this problem by dynamically aggregating resources in a manner that continuously optimizes system response. This is accomplished by way of an active yellow pages directory that allows aggregation constraints to be (re)defined on the fly. An initial prototype of the active yellow pages service has been deployed in the PUNCH network computing environment. Experiences with the production PUNCH system and preliminary results from controlled experiments indicate that the active yellow pages service performs well.Peer Reviewe

NEK5 activity regulates the mesenchymal and migratory phenotype in breast cancer cells

Purpose Breast cancer remains a prominent global disease affecting women worldwide despite the emergence of novel therapeutic regimens. Metastasis is responsible for most cancer-related deaths, and acquisition of a mesenchymal and migratory cancer cell phenotypes contributes to this devastating disease. The utilization of kinase targets in drug discovery have revolutionized the field of cancer research but despite impressive advancements in kinase-targeting drugs, a large portion of the human kinome remains understudied in cancer. NEK5, a member of the Never-in-mitosis kinase family, is an example of such an understudied kinase. Here, we characterized the function of NEK5 in breast cancer. Methods Stably overexpressing NEK5 cell lines (MCF7) and shRNA knockdown cell lines (MDA-MB-231, TU-BcX-4IC) were utilized. Cell morphology changes were evaluated using immunofluorescence and quantification of cytoskeletal components. Cell proliferation was assessed by Ki-67 staining and transwell migration assays tested cell migration capabilities. In vivo experiments with murine models were necessary to demonstrate NEK5 function in breast cancer tumor growth and metastasis. Results NEK5 activation altered breast cancer cell morphology and promoted cell migration independent of effects on cell proliferation. NEK5 overexpression or knockdown does not alter tumor growth kinetics but promotes or suppresses metastatic potential in a cell type-specific manner, respectively. Conclusion While NEK5 activity modulated cytoskeletal changes and cell motility, NEK5 activity affected cell seeding capabilities but not metastatic colonization or proliferation in vivo. Here we characterized NEK5 function in breast cancer systems and we implicate NEK5 in regulating specific steps of metastatic progression

A SIMD SPARSE MATRIX-VECTOR MULTIPLICATION ALGORITHM FOR COMPUTATIONAL ELECTROMAGNETICS AND SCATTERING MATRIX MODELS

A large number of problems in numerical analysis require the multiplication of a sparse matrix by a vector. In spite of the large amount of fine-grained parallelism available in the process of sparse matrix-vector multiplication, it is difficult to design an algorithm for distributed memory SIMD computers that can efficiently multiply an arbitrary sparse matrix by a vector. The difficulty lies in the irregular nature of the data structures required to efficiently store arbitrary sparse matrices, and the architectural constraints of a SIMD computer. We propose a new algorithm that allows the regularity of a data structure that uses a row-major mapping to be varied by a changing a parameter (the block size ). The (block row) algorithm assumes that the number of non-zero elements in each row is a multiple of the blocksize; (additional) zero entries are stored to satisfy this condition. The blocksize can be varied from one to N, where N is the size of the matrix; a blocksize of one results in a rcw-major distribution of the non-zero elements of the matrix (no oveahead of storing zcxo elements), while a blocksize of N results in a row-major distribution corresponding to that of a dense matrix. The algorithm was irnplemerlted on a 16,384 processor MasPar MP-1, and for the matrices associated with ithe applications considered here (S-Matrix Approach to Device Simulation, and tlhe Modeling of Diffractive and Scattering Objects), the algorithm was faster than ainy of the other algorithms considered (the snake-like method, the segmented-scan method, and a randomized packing algorithm). For matrices that have a wide variation in the number of non-zero elements in each row, a procedure for an adaptive block row allgorithrn is briefly mentioned. The block row algorithm is applicable to unstructured sllarse matrices which have relatively sparse columns (dense rows arc: not a problem), and it can be implemented on any distributed memory computer

On the design of a demand -based network -computing system: The Purdue University Network-Computing Hubs

Demand-based network-computing systems are characterized by their universal accessibility and their ability to harness networked resources as and when necessary. This dissertation addresses key issues involved in the design of such a system: (1) the interface to the external world, (2) the internal system design, (3) support for legacy applications, and (4) resource management across administrative domains. An operational prototype, the Purdue University Network Computing Hubs (PUNCH), is presented. The interface to the external world is based on a unique network desktop that provides Web access to computing services by treating URLs as locations in a dynamic, virtual, and side-effect based address-apace. The internal system design accounts for scalability and reliability, works across administrative domains, and employs a novel encoding mechanism that allows O(1) access to all managed information. The internal architecture is designed around a three-level hierarchy with replicatable components, a choice driven by the nature of the information associated with run-time tradeoff decisions. Unmodified (legacy) applications are supported by way of a highly flexible tool-specification language and a metaprogramming environment specifically designed to adapt to the needs of different tools (to date, forty tools developed by four vendors and eight universities have been installed on PUNCH). Resource management across administrative domains is enabled by a metaprogramming environment that allows administrators to specify usage constraints and policies for users and resources; cost/performance decisions are made by the network-computing system at run-time on the basis of predicted resource-usage characteristics and specified usage constraints and policies

Resource-Usage Prediction for Demand-Based Network-Computing

This document reports on an application of artificial intelligence to achieve demand-based scheduling within the context of a network-computing infrastructure. The described A1 sub-system uses tool-specific, run-time input to predict the resoura:-usage characteristics of runs. Instance-based learning with locally weighted polynornial regression is employed because of the need to simultaneoi~sly learn multiplr: polynomial concepts and the fact that knowledge is acquired increnlentally in this dornain. An innovative combination of a two-level knowledge base, and age and usage s~.atisticsa re used to: a) detect inadequate and noisy feature-vectors, 13) account for short-term variations in compute-server and network performance, and c) exploit temporal and spatial locality of runs. Modifications to the basic learning algorithm allow the approach to be computationally feasible for extended use and noise tolerant by se1ec:tively adding feature-vectors into the knowledge base and discarding featurevectors that consistently result in inaccurate predictions, respectively. The learning system was tested on three semiconductor simulation tools during normal use of the Purdue University Network Computing Hub during Fall 1997, and on four synthetic data-sets. Results indicate that the described instance-based learning technique using locally weighted regression with a locally linear model works well for this domain