bluuebunny/crossref_metadata_2025 huggingface dataset:
Measuring Chemotaxis and Chemokinesis: The Under-Agarose Cell Migration Assay
Authors: Heit Bryan , Kubes Paul
Published: May 2003

Chemotaxis is the primary mechanism by which cell movements are directed within multicellular organisms, and it is a major component of embryonic development, wound healing, and immune responses. Chemotaxis involves a complex cascade of events--formation of signaling complexes, receptor polarization, adhesion molecule activation, and cytoskeletal reorganization. Previous assay methods were limited in several ways that reduced users' abilities to obtain quantitative data or to control conditions precisely. We describe a unique chemotactic assay that can incorporate multiple chemotactic gradients in different spatial and temporal combinations. In addition, this assay is easily adapted for live-cell imaging and fluorescent microscopy. With its relative simplicity, flexibility, and precision, this method is a key tool for the study of cellular chemotactic responses and the signaling processes underlying them.
Book Review: A Widely Conserved Smell of DangerReview and commentary on
Toll-like Receptor Family Members and Their Ligands
, edited by Bruce Beutler and Hermann Wagner. Springer-Verlag, Berlin, Heidelberg, 2002, 192 pp. $95.00, ISBN: 3-540-43560-3
Authors: Ewbank Jonathan J. , Gorvel Jean-Pierre , Vivier Eric
Published: May 2003

With more than 150 original articles and more than a dozen reviews having been published in 2002 on the Toll-like receptor (TLR) family, the book
Toll-like Receptor Family Members and Their Ligands
provides a timely overview of the role of TLRs in innate immunity. The book provides chapters on the receptors, their ligands, and the signaling cascades activated. Highlighted in this book review are the chapters on the evolution of the TLRs, the receptor-ligand specificity, and the possible cross-talk between TLR signaling pathways and mitogen-activated protein kinase pathways.
The Interleukin-1 Receptor/Toll-Like Receptor Superfamily: Signal Transduction During Inflammation and Host Defense
Authors: Dunne Aisling , O'Neill Luke A. J.
Published: May 2003

The signal transduction pathways activated by the proinflammatory cytokine interleukin-1 (IL-1) have been the focus of much attention because of the important role that IL-1 plays in inflammatory diseases. A number of proteins have been described that participate in the post-receptor activation of the transcription factor nuclear factor κB (NF-κB), and stress-activated protein kinases such as p38 mitogen-activated protein kinase (MAPK). It has also emerged that the type I IL-1 receptor (IL-1RI) is a member of an expanding receptor superfamily. These related receptors all have sequence similarity in their cytosolic regions. The family includes the
Drosophila melanogaster
protein Toll, the IL-18 receptor (IL-18R), and 10 Toll-like receptors (TLRs), TLR-1 to TLR-10, which bind to microbial products, activating host defense responses. Because of the similarity of IL-1RI to Toll, the conserved sequence in the cytosolic region of these proteins has been termed the Toll-IL-1 receptor (TIR) domain. The same proteins activated during signaling by IL-1RI also participate in signaling by other receptors with TIR domains. The receptor superfamily is evolutionarily conserved; members also occur in plants and insects, where they also function in host defense. The signaling proteins that are activated are also conserved across species. Differences are, however, starting to emerge in signaling pathways activated by different receptors. This receptor superfamily, therefore, represents an ancient signaling system that is a critical determinant of the innate immune and inflammatory responses.
Physiologic and Pathologic Events Mediated by Intramembranous and Juxtamembranous Proteolysis
Authors: Golde Todd E. , Eckman Christopher B.
Published: May 2003

Intramembranous proteolysis (IP) is a recently recognized mechanism for transmembrane signal transduction that involves proteolysis of transmembrane proteins within their membrane-spanning domains. Juxtamembranous proteolysis (JP) is similar, but proteolytic cleavage of a transmembrane protein occurs at a site close to, but not within, the transmembrane domain of the target protein. In both IP and JP, a soluble domain of a transmembrane protein is released from its membrane tether. This domain can then transmit a signal either locally or at some distance from the site of cleavage. In certain signaling pathways, JP and IP are linked. JP on one side of the membrane results in secondary IP, which then releases a signaling domain from the membrane. Whereas well-characterized proteases such as caspases, the proteasome, and metalloprotease disintegrins, have been implicated in JP, three families of multipass membrane proteases (MpMPs) have now been shown to carry out IP. Recent studies of events mediated by IP and JP indicate that they regulate key cellular signaling events including pathways involved in sterol regulation, cell fate selection, and growth regulation. Moreover, IP and JP have important roles in certain diseases such as Alzheimer's disease. Because some of the proteases mediating IP and JP can be selectivity inhibited, inhibitors targeting these proteases are likely to alter both physiologic and pathologic events triggered by IP and JP.
The Many Forks in FOXO's Road
Authors: Tran Hien , Brunet Anne , Griffith Eric C. , Greenberg Michael E.
Published: May 2003

The FOXO family of transcription factors constitute an evolutionarily conserved subgroup within the larger family known as winged helix or Forkhead transcriptional regulators. Building upon work in the nematode, researchers have uncovered a role for these proteins in a diverse set of cellular responses that include glucose metabolism, stress response, cell cycle regulation, and apoptosis. At the organismal level, FOXO transcription factors are believed to function in various pathological processes ranging from cancer and diabetes to organismal aging. A number of studies have also shed light on the signaling pathways that regulate FOXO activity in response to external stimuli and have identified multiple FOXO target genes that mediate this varied set of biological responses.
Cellular Distribution of Bcl-2 Family Proteins
Authors: Germain Marc , Shore Gordon C.
Published: May 2003

Proteins synthesized in the cytosol can be inserted into or across organellar membranes depending on the signals present in their primary sequences. Proteins of the Bcl-2 family, which includes proteins that promote programmed cell death (apoptosis) and proteins that inhibit apoptosis, have signals that can target particular members to either the mitochondria or the endoplasmic reticulum (ER) or both. Germain and Shore discuss evidence for a role for the anti-apoptotic members of the family at the ER and describe an interaction with the FK506 binding protein, FKBP38, that may regulate the relative distribution of Bcl-2 proteins at the ER or mitochondria. This interaction may control the cell's sensitivity to apoptotic stimuli.
In Vivo Calcium Imaging of Brain Activity in
Drosophila
by Transgenic Cameleon Expression
Authors: Fiala André , Spall Thomas
Published: May 2003

Various genetically encoded fluorescent sensors that monitor changes in intracellular calcium concentration have been developed over the last few years. The ability to target these calcium indicators to cells and structures of interest makes them valuable tools for diverse applications and gives them distinct advantages over conventional fluorescent dyes in transgenically tractable organisms. In particular, the cameleon calcium sensors have been used successfully in a number of applications. For example, we use cameleon-2.1 to monitor in vivo brain activity in
Drosophila
. However, using cameleons to image intracellular calcium concentration changes in vivo is still evolving and is by no means a standard technique. Experimental details and "tricks" for dealing with equipment, techniques, and data evaluation are still restricted to a few laboratories. In this protocol for calcium imaging in
Drosophila
brain using cameleon-2.1, we provide guidelines to the basic principles of this novel technique in
Drosophila
neuroscience and, more generally, to the broad field of signal transduction research.
Cell Stress-Associated Caspase Activation: Intrinsically Complex?
Authors: Creagh Emma M. , Martin Seamus J.
Published: May 2003

Apoptosis, or programmed cell death, involves the activation of the caspases, a family of cysteine proteases that coordinate the process of cellular demolition. In the intrinsic--or mitochondrial--pathway to apoptosis, which is initiated in response to various types of cell stress, the prevailing view is that caspases become activated in a structure called the apoptosome after cytochrome c is released from the mitochondria. However, recent research challenges this view and suggests that one or more caspases are activated before mitochondrial release of cytochrome c and that the apoptosome acts as an amplifier, rather than as an initiator, of apoptosis-associated caspase activation. Here, we critically discuss the evidence in support of the latter view and suggest that revision of the established pathway may be premature.
Integration of Endocytosis and Signal Transduction by Lipoprotein Receptors
Authors: May Petra , Bock Hans H. , Herz Joachim
Published: May 2003

The members of the low density lipoprotein receptor (LDLR) gene family are cell surface molecules with diverse functions in cellular metabolism. All LDLR family members are endocytic receptors that mediate the uptake of extracellular cargo into the cell; recent research indicates that they also participate directly in signal transduction. Regulated proteolytic release of the intracellular domain of one of these lipoprotein receptors, the LDLR-related protein 1 (LRP1), has been described, along with the possible role of the released domain in transcriptional regulation. A recent study suggests that megalin, a member of the LDLR gene family that mediates the cellular uptake of vitamin D carrier protein, may also modulate vitamin D-related gene transcription through sequestration of a component of the vitamin D receptor transcriptional complex. May
et al
. discuss this research in the context of the integration of endocytosis and signaling by this receptor family.
Patch-Clamp Fluorometry Recording of Conformational Rearrangements of Ion Channels
Authors: Zheng Jie , Zagotta William N.
Published: May 2003

Conformational rearrangements are commonly observed in membrane proteins and constitute the molecular mechanisms through which they contribute to signal transduction. Information on structural changes in membrane proteins has mostly been inferred from functional studies. Recently, site-specific fluorescence recordings have made it possible to directly observe such molecular events in real time within the membrane environment. Here, we describe the patch-clamp fluorometry (PCF) technique that records simultaneously the local structural changes and the functional states of ion channels in isolated cell membranes. Combined with fluorescence resonance energy transfer (FRET), the technique should shed new light on ion channel activation, regulation, and interaction with other membrane proteins.
Dynamic Imaging in Living Cells: Windows into Local Signaling
Authors: Bers Donald M.
Published: May 2003

Highly localized changes in intracellular calcium concentration [Ca
2+
]
i
play a critical role in regulating numerous cellular functions, ranging from muscle contraction to neurotransmitter and hormone secretion to gene transcription. Fluorescent Ca
2+
indicators have been invaluable tools in elucidating the role of localized changes in [Ca
2+
]
i
in regulating ion channels and other key proteins in various signaling pathways. Other techniques used to investigate localized changes in [Ca
2+
]
i
include approaches based on fluorescence resonance energy transfer, and electrophysiological measurements of ionic flux through Ca
2+
-sensitive channels. This Perspective discusses research using fluorescent Ca
2+
indicators to study excitation-contraction coupling in cardiac myocytes, presenting both key findings and limitations of this approach. Complementary approaches useful in studying localized changes in Ca
2+
and other second messengers (such as cyclic adenosine monophosphate) are also discussed.
Image-Based Screening of Signal Transduction Assays
Authors: Ramm Peter , Thomas Nick
Published: May 2003

Imaging techniques have played a vital role in signal transduction research over several decades. Recently, industrialized macro- and micro-imaging systems have found application in drug discovery laboratories, where they increase the throughput and efficiency of drug screening. Macro-imagers are used for primary screening, where they favor compound conservation (through assay miniaturization), and achieve unprecedented rates of throughput. Micro-imaging systems achieve relatively high throughput, at the same time providing sub-cellular resolution with fixed or living cells. These micro-imaging analyses were previously conducted at very low throughput and, typically, were the sole domain of the academic researcher. Although both macro and micro forms of image-based screening remain technologies in development, they have already made substantial contributions to screening programs and will continue to do so.
High-Resolution Multicolor Imaging of Dynamic Signaling Complexes in T Cells Stimulated by Planar Substrates
Authors: Bunnell Stephen C. , Barr Valarie A. , Fuller Claudette L. , Samelson Lawrence E.
Published: May 2003

The dynamic visualization of developing immunological synapses has been hindered by the difficulty of imaging the contact between the T cell and the antigen-presenting cell (APC). Here, we describe a technique in which T cell responses are constrained to a planar stimulatory substrate. This approach, when used in conjunction with immunofluorescent staining procedures or fluorescent protein tags, greatly facilitates detection of the dynamic molecular rearrangements that accompany the formation of contacts and the initiation of signal transduction through the T cell receptor (TCR). Using this method, we have observed signaling complexes of dynamically varying compositions that possess distinct fates.
Observing Cell Surface Signaling Domains Using Electron Microscopy
Authors: Prior Ian A. , Parton Robert G , Hancock John F.
Published: May 2003

The plasma membrane is made up of a complex mosaic of different functional microdomains, but the tools required to accurately visualize them have always been limited. We present a protocol that allows both inner and outer leaflet domains to be visualized on a nanometer scale. With a combination of electron microscopic and statistical analysis approaches, it is possible to screen proteins associating with, and co-localizing within, lipid rafts and other morphologically featureless microdomains. The approach has enormous potential to determine plasma membrane organization and the spatial dynamics of regulated signaling and membrane trafficking events associated with the cell surface.
ADAPTIVE QUERY OPTIMIZATION IN DYNAMIC DATABASES
Authors: YU MIN J. , SHEU P. C-Y.
Published: May 2003

This paper addresses the problem of query optimization for databases in which objects frequently change their values. A greedy, adaptive query optimization algorithm is proposed to evaluate relational queries and queries containing complex objects. Rather than contructing a full plan for an access path and executing it, the algorithm constructs a partial plan, executes it, updates the statistics, and constructs a new partial plan. Since a partial plan is constructed based on the latest statistics, the algorithm is adaptive to data modifications and errors from the statistics. It is proved that the algorithm can produce an optimal solution for a class of queries. Furthermore, experiments show that the overhead associated with the algorithm is negligible and the algorithm is efficient for other cases.
LEARNING FEATURE WEIGHTS FROM SIMILARITY INFORMATION
Authors: WANG YONG , ISHII NAOHIRO
Published: May 2003

When employing a similarity function to measure the similarity between two cases, one large problem is how to determine the feature weights. This paper presents a new method for learning feature weights in a similarity function from the given similarity information. The similarity information can be divided into two kinds: One is called qualitative similarity information which represents the similarities between cases. The other is called relative similarity information which represents the relation between similarities of two case pairs both including a same case. We apply genetic algorithms to learn feature weights from these two kinds of information respectively. The proposed genetic algorithms are applicable to both linear and nonlinear similarty functions. Our experiments show the learning results are better even if the given similarity information include errors.
IMAGE ANALYSIS BASED ON FUZZY KNOWLEDGE
Authors: JÄGER MARKUS , HILTNER JENS , TRESP CHRISTOPHER , MOSER MICHAEL
Published: May 2003

Within this work a method for knowledge based fuzzy image segmentation, description and recognition is introduced. The basic idea comes from the field of automated medical MRI segmentation where the well-known standard methods have proven insufficient to solve the task. Therefore, a method especially for the problems concerning vagueness in medical imaging has been developed. Beside the central aspect of the improved segmentation procedures, the development has a general impact on the conventional model of image analysis, that includes object description and recognition.
DISTRIBUTED KNOWLEDGE-BASE: ADAPTIVE MULTI-AGENTS APPROACH
Authors: MERTOGUNO J. SUKARNO
Published: May 2003

This paper describes an approach of using Multi-agents theory to construct an adaptive knowledge base system. To represent the knowledge, frame base (graph) knowledge representation has been chosen. The driving force of this study is the intention of having a distributed (possibly across the net) adaptive knowledge base. The challenge of developing an adaptive knowledge base lays on how to evolve the knowledge (adaptability) and how to control the evolution (maintain the quality of the knowledge). In this paper the manifestation of both of the issues above on our model will be addressed.
AN IMPROVEMENT TO TOP-DOWN CLAUSE SPECIALIZATION
Authors: CHEN PO-CHI , LEE SUH-YIN
Published: May 2003

One remarkable progress of recent research in machine learning is inductive logic programming (ILP). In most ILP system, clause specialization is one of the most important tasks. Usually, the clause specialization is performed by adding a literal at a time using hill-climbing heuristics. However, the single-literal addition can be caught by local pits when more than one literal needs to be added at a time increase the accuracy. Several techniques have been proposed for this problem but are restricted to relational domains. In this paper, we propose a technique called structure subtraction to construct a set of candidates for adding literals, single-literal or multiple-literals. This technique can be employed in any ILP system using top-down specilization and is not restricted to relational domains. A theory revision system is described to illustrate the use of structural subtraction.
TEMPO: A TEMPORAL SUB-PARSER FOR MODERN GREEK
Authors: SGARBAS KYRIAKOS N. , FAKOTAKIS NIKOS D. , KOKKINAKIS GEORGE K.
Published: May 2003

This paper describes a temporal parser (TEMPO) introducing a semantic approach to the detection and analysis of quantifiers of time within simple texts. TEMPO processes expressions which implicitly contain a date, like "last Sunday", "two days ago" etc., and extracts the exact date. It uses a keyword-driven parsing technique to spot the quantifiers and then separates segments of the sentence around the keywords and passes them to a semantic DCG parser. Though developed for Greek, the presented scheme can be easily transferred to other languages. TEMPO might prove useful in the automatic processing of special kings of documents which require the extraction of time information, such as applications, legal documents, contracts, etc.
EFFICIENT PATH-CONSISTENCY PROPAGATION
Authors: CHMEISS ASSEF , JEGOU PHILIPPE
Published: May 2003

Recently, efficient algorithms have been proposed to achieve arc- and path-consistencey in constraint networks. For example, for arc-consistency, there are linear time algorithms (in the size of the problem) which are efficient in practice (e.g. AC-6 and AC-7). The best path-consistency algorithm proposed is PC-{5|6} which is a natural generalization of AC-6 to path-consistency. While its theoretical complexity is the best, experimentations show clearly that it is not very efficient in practice. In this paper, we propose two algorithms, one for arc-consistency, AC-8, and the second for path-consistency, PC-8. These algorithms are based on the same principle: to exploit minimal supports as AC-6 and PC-{5|6} do, but without recording them. While for AC-8, this approach is of limited interest, we show that for path-consistency, this new approach allows to outperform significantly existing algorithms.
AN EFFICIENT PARSING MODEL FOR UNIFICATION CATEGORIAL GRAMMAR WITH OBJECT-ORIENTED KNOWLEDGE REPRESENTATION AND SELECTION SETS
Authors: LI LI , BRYANT BARRETT R.
Published: May 2003

This paper describes an object-oriented lexical representation language based on Unification Categorial Grammar (UCG) that encodes linguistic and semantic information uniformly as classes and objects and an efficient bottom-up parsing method for UCG using selection sets technique. The lexical representation language, implemented in the logic and object-oriented programming language LIFE, introduces several new information sharing mechanisms to enable natural, declarative, modular and economial construction of large and complex computational lexicons. The selection sets are deduced from a transformation between UCG and Context-Free Grammar (CFG) and used to reduce search space for the table-driven algorithm. The experimental tests on a spoken English corpus show that the hierarchical lexicon achieves a dramatic reduction on redundant information and that selection sets significantly improve parsing UCG with a polynomial time complexity.
MULTI-AGENT ROBOT ARCHITECTURES: THE DECOMPOSITION ISSUE AND A CASE STUDY
Authors: TZAFESTAS ELPIDA S. , RAPTIS SPYROS N. , TZAFESTAS SPYROS G.
Published: May 2003

In this paper, some fundamental issues of modern multi-agent robot architectures are discussed. It is argued that the multi-agent approach provides the necessary flexibility and adaptivity for such architectures, and that the primary issue in designing a multi-agent robot architecture is the selection of the granularity level, i.e., the decision on decomposing the overall desired functionality physically or across tasks. It is explained why at the various system levels different decomposition grains are needed; physical components, tasks or hybrid. This granularity decision is made on the basis of specific criteria of control localization, knowledge decoupling and interaction minimization so as to identify the decision points of the overall functionality. The above criteria lead to a dual composition-decomposition relation, which provides a good basis for system scaling. The paper specializes the discussion to a proposed neuro-fuzzy multi-agent architecture, which is then applied to design the local path planning system of an indoor mobile robot.
MINING ASSOCIATION RULES FROM MARKET BASKET DATA USING SHARE MEASURES AND CHARACTERIZED ITEMSETS
Authors: HILDERMAN ROBERT J. , HAMILTON HOWARD J. , CARTER COLIN L. , CERCONE NICK
Published: May 2003

We propose the share-confidence framework for knowledge discovery from databases which addresses the problem of mining characterized association rules from market basket data (i.e., itemsets). Our goal is to not only discover the buying patterns of customers, but also to discover customer profiles by partitioning customers into distinct classes. We present a new algorithm for classifying itemsets based upon characteristic attributes extracted from census or lifestyle data. Our algorithm combines the A priori algorithm for discovering association rules between items in large databases, and the A O G algorithm for attribute-oriented generalization in large databases. We show how characterized itemsets can be generalized according to concept hierarchies associated with the characteristic attributes. Finally, we present experimental results that demonstrate the utility of the share-confidence framework.
INTEGRATING OBJECT-ORIENTED AND RULE-BASED PROGRAMMING FOR BUILDING AGENT SYSTEMS
Authors: POGGI AGOSTINO
Published: May 2003

To facilitate the success of agent technology, we need suitable tools both to reduce the effort in the development of agent systems and to obtain efficient implementations of them. This paper presents an agent-oriented language for the development of multi-agent systems, called ALL (Agent Level Language), that should offer both the two features. In fact, on the one hand, ALL integrates object-oriented and rule based programming to simplify the definition of agent systems and the management of interactions between agents. On the other hand, ALL can be translated into C++, Common Lisp and Java code and can encapsulate objects written in these three languages allowing the reuse of a large amount of pre-existent software and the realization of efficient applications in a large set of (different) domains. ALL rules derive from YACC rules and can simplify the management of agents interaction because they are suitable for the parsing of messages and because they can be reused thanks to object-oriented inheritance.
CAEP: AN EVOLUTION-BASED TOOL FOR REAL-VALUED FUNCTION OPTIMIZATION USING CULTURAL ALGORITHMS
Authors: Chung Chan-Jin , Reynolds Robert G.
Published: May 2003

Cultural Algorithms are computational self-adaptive models which consist of a population and a belief space. The problem-solving experience of individuals selected from the population space by the acceptance function is generalized and stored in the belief space. This knowledge can then control the evolution of the population component by means of the influence function. Here, we examine the role that different forms of knowledge can play in the self-adaptation process within cultural systems. In particular, we compare various approaches that use normative and situational knowledge in different ways to guide the function optimization process.

The results in this study demonstrate that Cultural Algorithms are a naturally useful framework for self-adaptation and that the use of a cultural framework to support self-adaptation in Evolutionary Programming can produce substantial performance improvements over population-only systems as expressed in terms of (1) systems success ratio, (2) execution CPU time, and (3) convergence (mean best solution) for a given set of 34 function minimization problems. The nature of these improvements and the type of knowledge that is most effective in producing them depend on the problem's functional landscape. In addition, it was found that the same held true for the population-only self-adaptive EP systems. Each level of self-adaptation (component, individual, and population) outperformed the others for problems with particular landscape features.
SCHEMA VERSIONING IN A TEMPORAL OBJECT-ORIENTED DATA MODEL
Authors: ROSE ELLEN , SEGEV ARIE
Published: May 2003

This paper proposes a means for schema versioning in a temporal, object-oriented data model called TOODM. A data definition language (DDL) is developed to describe evolving schema definitions. This DDL incorporates the concept of time sequences to store histories of a schema's properties. Update and retrieval operators for the manipulation of the schema are also developed. The data model has been implemented as a graphical front-end to POSTGRES.
TEMPORAL MEDIATORS: SUPPORTING UNIFORM ACCESSES TO HETEROGENEOUS TEMPORAL INFORMATION
Authors: WANG X. SEAN , JAJODIA SUSHIL , MOHAVNI SONA
Published: May 2003

In order to support uniform access to heterogeneous temporal information, we introduce the concept of a temporal mediator. A temporal mediator consists of three components: (i) a repository for windowing functions and conversion functions, (ii) a time granularity thesaurus and (iii) a query interpreter. There are two types of windowing functions: one associates each time point to a set of tuples, and the other associates each tuple to a set of time points. A conversion function transforms information in terms of one time granularity into that in terms of another time granularity. The time granularity thesaurus stores the knowledge about time granularities (e.g., names of time granularities and relationships among them). Users pose queries using the windowing functions and in terms of desired time granularities. (A query language, which can be used to form such queries, is given in the paper.) To answer such a user query, the query interpreter first employs the windowing functions together with the time granularity thesaurus to retrieve needed temporal data from the underlying databases and then uses the time granularity thesaurus to select suitable conversion functions which convert the responses to the desired time granularities. Thus, a temporal mediator provides a simple interface that supports uniform accesses to heterogeneous temporal databases.
MODELING AND MANAGEMENT OF TEMPORAL DATA IN OBJECT-ORIENTED KNOWLEDGE BASES
Authors: SU STANLEY Y. W. , CHEN HSIN-HSING M.
Published: May 2003

There has been a considerable amount of work on object-oriented databases, active databases, and deductive databases. The common objective of these efforts is to produce highly intelligent and active systems for supporting the next generation of database applications. These future systems must be capable of capturing the concepts of time and managing not just temporal data but temporal knowledge expressed by knowledge rules. In this paper, we describe our efforts on a temporal object-oriented knowledge model, OSAM*/T, its associated temporal query language, OQL/T, an underlying temporal algebra, TA-algebra, and some implementation techniques. In addition to the features of the traditional object-oriented paradigm, the model is characterized by its strong support of association types and its incorporation of temporal knowledge rules for specifying temporal and other types of semantic constraints associated with object classes and their temporal object instances. The query language is featured by its pattern-based specification of temporal object associations, which allows complex queries with various time constraints to be formulated in a relatively simple way. The temporal algebra provides a set of primitive operators for manipulating homogeneous and/or heterogeneous patterns of temporal object associations, thus providing the needed mathematical foundation for processing and optimizing temporal queries. The implementation techniques include a Delta-Instance and Multi-Snapshot Storage Model, as well as data partitioning and clustering schemes for storage management of temporal knowledge bases.
A CONSTRUCTIVE NEURAL NETWORK ALGORITHM FOR FUNCTION APPROXIMATION USING LOCALLY FIT SIGMOIDS
Authors: DRAELOS TIM , HUSH DON
Published: May 2003

A study of the function approximation capabilities of single hidden layer neural networks strongly motivates the investigation of constructive learning techniques as a means of realizing established error bounds. Learning characteristics employed by constructive algorithms provide ideas for development of new algorithms applicable to the function approximation problem. In addition, constructive techniques offer efficient methods for network construction and weight determination. The development of a novel neural network algorithm, the Constructive Locally Fit Sigmoids (CLFS) function approximation algorithm, is presented in detail. Basis functions of global extent (piecewise linear sigmoidal functions) are locally fit to the target function, resulting in a pool of candidate hidden layer nodes from which a function approximation is obtained. This algorithm provides a methodology of selecting nodes in a meaningful way from the infinite set of possibilities and synthesizes an n node single hidden layer network with empirical and analytical results that strongly indicate an O(1/n) mean squared training error bound under certain assumptions. The algorithm operates in polynomial time in the number of network nodes and the input dimension. Empirical results demonstrate its effectiveness on several multidimensional function approximate problems relative to contemporary constructive and nonconstructive algorithms.
GENERATING FUZZY RULES BY GENETIC METHOD AND ITS APPLICATIONS
Authors: LEE MAL-REY
Published: May 2003

This paper proposes a GA method for choosing an appropriate set of fuzzy rules for classification problems. The aim of the proposed method is to find a minimum set of fuzzy rules that can correctly classify all training patterns. The number of inference rules and the shapes of the membership functions in the antecedent part of the fuzzy rules are determined by the genetic algorithms. The real numbers in the consequent parts of the fuzzy rules are obtained through the use of the descent method. A fitness function is used to maximize the number of correctly classified patterns, and to minimize the number of fuzzy rules. A solution obtained by the genetic algorithm is a set of fuzzy rules, and its fitness is determined by the two objectives, in a combinatorial optimization problem. In order to demonstrate the effectiveness of the proposed method, computer simulation results are shown.
NEARLY OPTIMUM TIMETABLE CONSTRUCTION THROUGH CLP AND INTELLIGENT SEARCH
Authors: STAMATOPOULOS PANAGIOTIS , VIGLAS EFSTRATIOS , KARABOYAS SERAFEIM
Published: May 2003

The course timetable construction is a procedure that every academic department has to carry out at least twice annually, more times if some of the requirements change. These requirements indicate that a collection of elements must be taken in mind in order for an acceptable solution to be found. They come either from the inherent constraints of the problem or from the involved parties, namely teachers and students. A requirement that is very difficult to statisfy is the one of optimality, which means that the constructed timetable should be the best among the legal ones, according to some quantified quality criteria. In this paper, a method for tackling the course timetable construction problem for academic departments is presented, which is based on Constraint Logic Programming (CLP) for the early pruning of the search space and on the usage of intelligent heuristics in order to guide the search to the generation of nearly optimum solutions. A specific system is presented, named ACTS (Automated Course Timetabling System), which has been implemented in the ECL i PS e language. This system is currently in use by the Department of Informatics of the University of Athens for the purpose of aiding the semester course timetable construction.
INTERCONNECTION WIRE-LENGTH ESTIMATION IN VLSI STANDARD CELL PLACEMENT VIA NEURAL NETWORK
Authors: SAXENA ASHUTOSH , GEORGE SUJU M. , RAMBABU P.
Published: May 2003

Neural Network is used as a tool for estimating interconnection wire-length in VLSI standard cell placement problem. Conventional methods for estimating the interconnection wire-length viz., Bounding Rectangle method, provide inaccurate estimate of the interconnection wire-length and does not depict the interconnection procedure in a layout and separates routing and placement tasks distinctly. The proposed mechanism utilizes the neural network characteristics in understanding the functional mapping between input and output, to estimate the interconnection wire-length. Experiments were performed for different number of cells with varying complexity of interconnections. In all the cases, the performance of the Neural Network is found to be superior to the results obtained using Bounding Rectangle procedure.
CONSTRAINT LOGIC PROGRAMMING APPROACH OF NETWORK FLOW PROBLEMS WITHIN A DECISION SUPPORT SYSTEMS GENERATOR FOR TRANSPORTATION PLANNIG
Authors: FIERBINTEANU CRISTINA
Published: May 2003

In this paper we propose a model of a decision support systems (DSS) generator for unstructured problems. The model is developed within the constraint logic programming (CLP) paradigm. At the center of the generator there is an ontology defining the concepts and relationships necessary and sufficient to describe the domain to be reasoned about, in a manner suitable for a particular class of tasks. The constraint solver of the constraint logic programming host language has to be extended with constraints which are relevant to the domain studied, but can not be found among the general constraints provided by the constraint solver. The domain of transportation planning was chosen to illustrate the proposed concept of DSS generator for ustructured problems. In this case we need to extend the constraint solver with constraint manipulation techniques specific to network flow problems. This paper presents in detail our constraint logic programming approach of network flow problems.
FUZZY PETRI NETS FOR MODELING RULE-BASED REASONING
Authors: LEE JONATHAN , LIU KEVIN F. R. , CHIANG WEILING
Published: May 2003

In this paper, a fuzzy Petri nets for modeling fuzzy rule-based reasoning is proposed to bring together the possibilistic entailment and the fuzzy reasoning to handle uncertain and imprecise information. The three key components in our fuzzy rule-based reasoning: fuzzy propositions, truth-qualified fuzzy rules, and truth-qualified fuzzy facts, can be formulated as fuzzy places, uncertain transitions, and uncertain fuzzy tokens, respectively. Four types of uncertain transitions, inference, aggregation, duplication and aggregation-duplication transitions, are introduced to meet the mechanism of fuzzy rule-based reasoning. A reasoning algorithm based on fuzzy Petri nets is also presented to improve the efficiency of fuzzy rule-based reasoning. The reasoning algorithm is consistent with not only the rule-based reasoning but also the execution of Petri nets.
STRATEGY LEARNING: A SURVEY OF PROBLEMS, METHODS, AND ARCHITECTURES
Authors: MEHRA PANKAJ , WAH BENJAMIN W.
Published: May 2003

Problem solvers employ strategies in searching for solutions to given problem instances. Strategies have traditionally been designed by experts using prior knowledge and refined manually using trial and error. Recent attempts to automate these processes have produced strategy-learning systems. This paper shows how various issues in strategy learning are affected by the nature of performance tasks, problem solvers, and learning environments. Surveyed learning systems are grouped by the commonality of their approaches into four general architectures.
HDL Apolipoproteins and ABCA1
Authors: Oram John F.
Published: May 2003

It is widely believed that HDL protects against atherosclerosis by removing excess cholesterol from arterial cells. Lipid-poor HDL apolipoproteins promote efflux of cholesterol, phospholipids, and other lipophilic molecules from cells by an active process mediated by a cell-membrane transporter called the ATP binding cassette transporter A-1 (ABCA1). ABCA1 either directly or indirectly translocates phospholipids and cholesterol to the cell surface, where they appear to form lipid domains that interact with amphipathic α-helixes in apolipoproteins. This interaction solubilizes these lipids and generates nascent HDL particles that dissociate from the cell. Binding of apolipoproteins to ABCA1 may also enhance the activity of this lipid-transport pathway. Thus, the apolipoprotein/ABCA1 pathway efficiently clears cells of excess cholesterol that would otherwise accumulate as intracellular lipid droplets. ABCA1 expression is highly induced by cholesterol loading of cells and is also modulated by sterol-independent mechanisms at both the transcriptional and posttranslational level. Studies of human disease and animal models have shown that both an increased availability of apolipoproteins and an enhanced macrophage ABCA1 activity are atheroprotective. These findings implicate the apolipoprotein/ABCA1 pathway as an important therapeutic target for treating cardiovascular disease.
Importance of Different Pathways of Cellular Cholesterol Efflux
Authors: Yancey Patricia G. , Bortnick Anna E. , Kellner-Weibel Ginny , de la Llera-Moya Margarita , Phillips Michael C. , Rothblat George H.
Published: May 2003

The removal of excess free cholesterol from cells by HDL or its apolipoproteins is important for maintaining cellular cholesterol homeostasis. This process is most likely compromised in the atherosclerotic lesion because the development of atherosclerosis is associated with low HDL cholesterol. Multiple mechanisms for efflux of cell cholesterol exist. Efflux of free cholesterol via aqueous diffusion occurs with all cell types but is inefficient. Efflux of cholesterol is accelerated when scavenger receptor class-B type I (SR-BI) is present in the cell plasma membrane. Both diffusion-mediated and SR-BI–mediated efflux occur to phospholipid-containing acceptors (ie, HDL and lipidated apolipoproteins); in both cases, the flux of cholesterol is bidirectional, with the direction of net flux depending on the cholesterol gradient. The ATP-binding cassette transporter AI (ABCA1) mediates efflux of both cellular cholesterol and phospholipid. In contrast to SR-BI–mediated flux, efflux via ABCA1 is unidirectional, occurring to lipid-poor apolipoproteins. The relative importance of the SR-BI and ABCA1 efflux pathways in preventing the development of atherosclerotic plaque is not known but will depend on the expression levels of the two proteins and on the type of cholesterol acceptors available.
Combinatorial Control of Smooth Muscle–Specific Gene Expression
Authors: Kumar Meena S. , Owens Gary K.
Published: May 2003

Alterations in the differentiated state of vascular smooth muscle cells (SMCs) are known to play a key role in vascular diseases, yet the mechanisms controlling SMC differentiation are still poorly understand. In this review, we discuss our present knowledge of control of SMC differentiation at the transcriptional level, pointing out some common themes, important paradigms, and unresolved issues in SMC-specific gene regulation. We focus primarily on the serum response factor–CArG box–dependent pathway, because it has been shown to play a critical role in regulation of multiple SMC marker genes. However, we also highlight several other important regulatory elements, such as a transforming growth factor β control element, E-boxes, and MCAT motifs. We present evidence in support of the notion that SMC-specific gene regulation is not controlled by a few SMC-specific transcription factors but rather by complex combinatorial interactions between multiple general and tissue-specific proteins. Finally, we discuss the implications of chromatin remodeling on SMC differentiation.
LDL Containing Apolipoprotein CIII Is an Independent Risk Factor for Coronary Events in Diabetic Patients
Authors: Lee Sung-Joon , Campos Hannia , Moye Lemuel A. , Sacks Frank M.
Published: May 2003

Objective—

Triglyceride-rich lipoproteins that contain apolipoprotein CIII (apoCIII) are prominent in diabetic dyslipidemia. We hypothesized that these lipoproteins increase coronary disease risk in diabetic patients beyond that caused by standard lipid risk factors.

Methods and Results—

Diabetic patients with previous myocardial infarction were followed for 5 years, and 121 who had a recurrent coronary event were matched to 121 who did not. VLDL and LDL that contained or did not contain apoCIII (CIII+ or CIII−) were prepared by immunoaffinity chromatography and ultracentrifugation. IDL was included in the LDL fraction. LDL CIII+, rich in cholesterol and triglyceride, was the strongest predictor of coronary events (relative risk [RR] 6.6,
P
<0.0001, for 4th versus 1st quartile). LDL CIII+ comprised 10% of total LDL. The main type of LDL, LDL CIII−, was less strongly predictive (RR 2.2,
P
=0.07). The increased risk associated with LDL CIII+ was unaffected by adjustment for plasma lipids, apoB, non-HDL cholesterol, or the other VLDL and LDL types. For VLDL CIII+, RR 0.5,
P
=0.07; for VLDL CIII−, RR 2.3,
P
=0.046. The presence of apolipoprotein E with CIII on VLDL and LDL did not affect risk.

Conclusions—

LDL with apoCIII strongly predicts coronary events in diabetic patients independently of other lipids and may be an atherogenic remnant of triglyceride-rich VLDL metabolism.
Change in α
1
HDL Concentration Predicts Progression in Coronary Artery Stenosis
Authors: Asztalos Bela F. , Batista Marcelo , Horvath Katalin V. , Cox Caitlin E. , Dallal Gerard E. , Morse Josh S. , Brown Greg B. , Schaefer Ernst J.
Published: May 2003

Objective—

We examined the effects of simvastatin-niacin and antioxidant vitamins on changes in high-density lipoprotein (HDL) subpopulations and alterations in coronary artery stenosis, as assessed by angiography.

Methods and Results—

Lipids, lipoproteins, and HDL particles were measured on and off treatment in 123 subjects of the HDL-Atherosclerosis Treatment Study. Patients were assigned to 4 treatment groups, simvastatin-niacin, simvastatin-niacin-antioxidant vitamins, antioxidant vitamins, and placebo. Subjects were followed for 3 years on treatment and then for 2 months off treatment. Simvastatin-niacin significantly increased the 2 large apoA-I–containing HDL subpopulations, α
1
and preα
1
, and significantly decreased the 2 smallest particles, preβ
1
and α
3
, compared with values obtained from the same patients off treatment. Adding antioxidant vitamins to the lipid-modifying agents blunted these effects (not significant). A significant negative correlation (
r
=−0.235;
P
<0.01) between the changes in α
1
HDL particle concentration and coronary artery stenosis was noted. Subjects in the third tertile (157% increase in α
1
) had no progression of stenosis in the 3-year follow-up period, whereas subjects in the first tertile (15% decrease in α
1
) had an average of 2.1% increase in stenosis.

Conclusions—

Simvastatin-niacin therapy significantly increased the large apoA-I–containing α
1
HDL particles. This increase was significantly associated with less progression of coronary stenosis even after adjusting for traditional risk factors.
High Density Lipoprotein–Induced Angiogenesis Requires the Activation of Ras/MAP Kinase in Human Coronary Artery Endothelial Cells
Authors: Miura Shin-ichiro , Fujino Masahiro , Matsuo Yoshino , Kawamura Akira , Tanigawa Hiroyuki , Nishikawa Hiroaki , Saku Keijiro
Published: May 2003

Objective—

Plasma high density lipoprotein (HDL) levels have been shown to be inversely correlated with coronary artery disease, but the mechanisms of the direct protective effect of HDL on endothelial cells (ECs) are not fully understood. In this study, we investigated the role of the HDL-mediated promotion of angiogenesis in human coronary artery ECs (HCECs).

Methods and Results—

We developed an in vitro model of HCEC tube formation on a matrix gel. We optimized the maximum dose of HDL required to induce tube formation in initial experiments, in which the dose response showed that the maximum effective dose of HDL was 100 μg/mL. PD98059, an inhibitor of p42/44 mitogen-activated protein kinase (MAPK) activity, but not SB203580, an inhibitor of p38 MAPK activity, suppressed HDL-induced tube formation. Dominant-negative Ras N17 inhibited HDL-induced tube formation. HDL activated Ras according to a ras pull-down assay, and this effect was inhibited by pertussis toxin. Moreover, HDL activated phospho(p)-p42/44 MAPK, whereas Ras N17 blocked HDL-induced pp42/44 MAPK.

Conclusions—

These results indicate that HDL induced a potent signal through a Ras/MAPK pathway mediated by a pertussis toxin–sensitive G-protein coupled receptor to the angiogenic phenotype in HCECs.