Expression of three UDP-N-acetyl-alpha-D-galactosamine:polypeptide GalNAc N-acetylgalactosaminyltransferases in adenocarcinoma cell lines

The levels of mRNA expression of three UDP-N-acetyl-alpha-D-galactosamine:polypeptide GalNAc N-acetylgalactosaminyltransferases (GalNAc-transferases) were quantified for human adenocarcinoma cell lines from pancreas, colon, stomach, and breast. Two of the GalNAc-transferases, GalNAc-T1 and GalNAc-T2, were expressed constitutively and at low levels in most or all cell lines examined. A third GalNAc-transferase, GalNAc-T3, was differentially expressed. Well-differentiated adenocarcinoma cell lines expressed high levels and moderately differentiated cell lines expressed lower levels of GalNAc-T3. Cell lines classified as poorly differentiated failed to express GalNAc-T3 mRNA at levels that could be detected by Northern blot analysis. Differential expression of the GalNAc-T3 protein was confirmed in these cell lines by Western blotting. We propose that glycosylation in tumor cell lines may be regulated in part by differential expression of GalNAc-transferases, and we suggest that GalNAc-T3 gene expression may be a molecular indicator of differentiated adenocarcinoma.     

Differences in the yields of dicentrics and reciprocal translocations observed in the chromosomes of irradiated human skin fibroblasts and blood lymphocytes from the same healthy individuals

The modulatory role of locally produced cyclooxygenase products and endothelium-derived nitric oxide in controlling vascular tone was investigated in bovine intra-mammary artery. Vascular reactivity initiated by vasoactive compounds, endothelin-1 (ET-1), bradykinin (BK), and substance P (SP) was measured isometrically in an isolated tissue bath. The effects of a cyclooxygenase inhibitor, indomethacin (10(-5) M) and an inhibitor of nitric oxide production, N omega-Nitro L-Arginine (L-NNA: 3 x 10(-4) M) were determined during agonist-mediated responses. Indomethacin alone markedly enhanced vascular contraction produced by ET-1, while L-NNA did not. Inhibition of endothelium-derived nitric oxide synthesis by L-NNA, however, significantly attenuated BK- and SP-induced vascular relaxations, whereas indomethacin had slight influence. The potentiation between indomethacin and L-NNA in regulating vasomotor tone was not observed in this vascular bed. Thus, it appeared that both the cyclooxygenase and endothelium-derived nitric oxide pathways participated in modifying vascular reactivity. Domination of one pathway over the other depended upon the agonist used to stimulate vascular tissue.     

A unified diode model for circuit simulation

A new commercially available diode model is described. This unified model is capable of simulating the widest range of diode technologies of any presently available. The emphasis of this paper is on describing the model's extensive features and flexibility in the different domains of operation and is of particular interest in power applications     

Scientific and artistic investigation of multi-dimensional fractals on the AT & T pixel machine

The pipelined architecture and parallel organization of the AT&T Pixel Machine image computer are described and demonstrated with applications for the visualization of multidimensional fractals, particularly linear fractals and quaternion/ stacked Julia sets. Techniques for pushing the Pixel Machine to its peak abilities are described and apply to more recent parallel image computers as well.     

Constant-time parallel algorithms for image labeling on areconfigurable network of processors

A constant-time algorithm for labeling the connected components of an N×N image on a reconfigurable network of N³ processors is presented. The main contribution of the algorithm is a novel constant-time technique for determining the minimum-labeled PE in each component. The number of processors used by the algorithm can be reduced to N/sup 2+(1/d/), for any 1⩽d⩽log N, if O(d) time is allowed     

Unicast-based multicast communication in wormhole-routed networks

Multicast communication, in which the same message is delivered from a source node to an arbitrary number of destination nodes, is being increasingly demanded in parallel computing. System supported multicast services can potentially offer improved performance, increased functionality, and simplified programming, and may in turn be used to support various higher-level operations for data movement and global process control. This paper presents efficient algorithms to implement multicast communication in wormhole-routed direct networks, in the absence of hardware multicast support, by exploiting the properties of the switching technology. Minimum-time multicast algorithms are presented for n-dimensional meshes and hypercubes that use deterministic, dimension-ordered routing of unicast messages. Both algorithms can deliver a multicast message to m-1 destinations in [log ₂ m] message passing steps, while avoiding contention among the constituent unicast messages. Performance results of implementations on a 64-node nCUBE-2 hypercube and a 168-node Symult 2010 2-D mesh are given     

An algebraic theory of object-oriented systems

The paper presents an algebraic specification of net objects. By net objects we mean those that are defined in object-oriented paradigms and those defined with nested relations in complex database models. An algebraic specification is set up that involves structures of net objects, accesses of net objects, and some features of object-oriented programming, such as multiple inheritance and polymorphism. Objects and their relationships are then characterized formally in the modeling, which utilizes the hierarchical approach in the algebraic theory of abstract data types, and is further developed by adding mechanisms from existing object systems. Categories of net objects are presented with the properties of accesses among them     

ConClass: a framework for real-time distributed knowledge-basedprocessing

We have developed a problem-solving framework, called ConClass, that is capable of classifying continuous real-time problems dynamically and concurrently on a distributed system. ConClass provides an efficient development environment for describing and decomposing a classification problem and synthesizing solutions. In ConClass, decomposed concurrent subproblems specified by the application developer effectively correspond to the actual distributed hardware elements. This scheme is useful for designing and implementing efficient distributed processing, making it easier to anticipate and evaluate system behavior. The ConClass system provides an object replication feature that prevents any particular object from being overloaded. In order to deal with an indeterminate amount of problem data, ConClass dynamically creates object networks that justify hypothesized solutions, and thus achieves a dynamic load distribution. A number of efficient execution mechanisms that manage a variety of asynchronous aspects of distributed processing have been implemented without using schedulers or synchronization schemes that are liable to develop bottlenecks. We have confirmed the efficiency of parallel distributed processing and load balancing of ConClass with an experimental application     

On loop transformations for generalized cycle shrinking

This paper describes several loop transformation techniques for extracting parallelism from nested loop structures. Nested loops can then be scheduled to run in parallel so that execution time is minimized. One technique is called selective cycle shrinking, and the other is called true dependence cycle shrinking. It is shown how selective shrinking is related to linear scheduling of nested loops and how true dependence shrinking is related to conflict-free mappings of higher dimensional algorithms into lower dimensional processor arrays. Methods are proposed in this paper to find the selective and true dependence shrinkings with minimum total execution time by applying the techniques of finding optimal linear schedules and optimal and conflict-free mappings proposed by W. Shang and A.B. Fortes     

Neural network control of communications systems

Neural networks appear well suited to applications in the control of communications systems for two reasons: adaptivity and high speed. This paper describes application of neural networks to two problems, admission control and switch control, which exploit the adaptivity and speed property, respectively. The admission control problem is the selective admission of a set of calls from a number of inhomogeneous call classes, which may have widely differing characteristics as to their rate and variability of traffic, onto a network. It is usually unknown in advance which combinations of calls can be simultaneously accepted so as to ensure satisfactory performance. The approach adopted is that key network performance parameters are observed while carrying various combinations of calls, and their relationship is learned by a neural network structure. The network model chosen has the ability to interpolate or extrapolate from the past results and the ability to adapt to new and changing conditions. The switch control problem is the service policy used by a switch controller in transmitting packets. In a crossbar switch with input queueing, significant loss of throughput can occur when head-of-line service order is employed. A solution can be based on an algorithm which maximizes throughput. However since this solution is typically required in less than one microsecond, software implementation policy is infeasible. We will carry out an analysis of the benefits of such a policy, describe some existing proposed schemes for its implementation, and propose a further scheme that provides this submicrosecond optimization.