Suppression of tumorigenicity and metastasis of human renal carcinoma cells by infection with retroviral vectors harboring the murine inducible nitric oxide synthase gene

The purpose of this study was to determine whether retrovirus-mediated transfer of the murine macrophage inducible nitric oxide synthase (iNOS) gene can inhibit tumorigenicity and metastasis of human renal cancer cells. Retroviral vectors encoding murine macrophage iNOS were constructed in the pLXSN retroviral vector with the iNOS gene under the control of a long terminal repeat promoter and a neomycin resistance gene under the control of an internal simian virus 40 promoter. Highly metastatic human renal carcinoma SN12PM6 cells were infected with control or iNOS retrovirus. Expression of iNOS was confirmed by Northern and Western blot analyses, and expression of the functional iNOS protein, i.e., production of nitric oxide (NO), was determined by measuring nitrite accumulation in culture supernatants. Noninfected or control cells produced large orthotopic tumors in the kidney of nude mice and a larger number of experimental lung metastases, whereas iNOS-infected cells produced small tumors in the kidneys and few to no lung metastases. The data indicate that the infection of human renal cancer cells by retroviruses harboring the murine iNOS gene can induce the production of high levels of NO, which is associated with autocytotoxicity, suppression of tumorigenicity, and abrogation of metastasis.     

A novel process to form cobalt silicided p+ poly-Sigates by BF2+ implantation into bilayeredCoSi/a-Si films and subsequent anneal

A novel process that implants BF₂⁺ ions into thin bilayered CoSi/a-Si films has been shown to form cobalt silicided p ⁺ poly-Si gates with excellent gate oxide integrity and very small flatband shift. The effects of not only using the CoSi layer as an implantation barrier but also keeping the a-Si underlayer during the initial silicide formation both significantly suppress the boron penetration through thin gate oxide     

Technical advances in digital audio radio broadcasting

The move to digital is a natural progression taking place in all aspects of broadcast media applications from document processing in newspapers to video processing in television distribution. This is no less true for audio broadcasting which has taken a unique development path in the United States. This path has been heavily influenced by a combination of regulatory and migratory requirements specific to the U.S. market. In addition, competition between proposed terrestrial and satellite systems combined with increasing consumer expectations have set ambitious, and often changing, requirements for the systems. The result has been a unique set of evolving requirements on source coding, channel coding, and modulation technologies to make these systems a reality. This paper outlines the technical development of the terrestrial wireless and satellite audio broadcasting systems in the U.S., providing details on specific source and channel coding designs and adding perspective on why specific designs were selected in the final systems. These systems are also compared to other systems such as Eureka-147, DRM, and Worldspace, developed under different requirements.     

Hidden Markov models with first-order equalization for noisy speechrecognition

A particularly effective distortion measure that takes into account the norm shrinkage bias in the noisy cepstrum is considered. A first-order equalization mechanism, specifically aiming at avoiding the norm shrinkage problem, is incorporated in a hidden Markov model (HMM) framework to model the speech cepstral sequence. Such a modeling technique requires special care, as the formulation inevitably involves parameter estimation from a set of data with singular dispersion. Solutions to this HMM stochastic modeling problem are provided, and algorithms for estimating the necessary model parameters are given. It is experimentally shown that incorporation of the first-order mean equalization model makes the HMM-based speech recognizer robust to noise. With respect to a conventional HMM recognizer, this leads to an improvement in recognition performance which is equivalent to a gain of about 15-20 dB in signal-to-noise ratio     

Pattern recognition using a family of design algorithms based uponthe generalized probabilistic descent method

This paper provides a comprehensive introduction to a novel approach to pattern recognition which is based on the generalized probabilistic descent method (GPD) and its related design algorithms. The paper contains a survey of recent recognizer design techniques, the formulation of GPD, the concept of minimum classification error learning that is closely related to the GPD formalization, a relational analysis between GPD and other important design methods, and various embodiments of GPD-based design, including segmental-GPD, minimum spotting error training, discriminative utterance verification, and discriminative feature extraction. GPD development has its origins in basic pattern recognition and Bayes decision theory. It represents a simple but careful re-investigation of the classical theory and successfully leads to an innovative framework. For clarity of presentation, detailed discussions about its embodiments are provided for examples of speech pattern recognition tasks that use a distance-based classifier. Experimental results in speech pattern recognition tasks clearly demonstrate the remarkable utility of the family of GPD-based design algorithms     

APC-mediated proteolysis of Ase1 and the morphogenesis of the mitotic spindle

The molecular mechanisms that link cell-cycle controls to the mitotic apparatus are poorly understood. A component of the Saccharomyces cerevisiae spindle, Ase1, was observed to undergo cell cycle-specific degradation mediated by the cyclosome, or anaphase promoting complex (APC). Ase1 was degraded when cells exited from mitosis and entered G1. Inappropriate expression of stable Ase1 during G1 produced a spindle defect that is sensed by the spindle assembly checkpoint. In addition, loss of ASE1 function destabilized telophase spindles, and expression of a nondegradable Ase1 mutant delayed spindle disassembly. APC-mediated proteolysis therefore appears to regulate both spindle assembly and disassembly.     

Modelling of the extraction equilibrium of zinc from chloride solutions with tri-n-octylphosphine oxide

The extraction of zinc from chloride solutions with tri-n-octylphosphine oxide (TOPO) dissolved in benzene has been thermodynamically studied based on the law of mass action. A model employing the simplified Pitzer equations for stoichiometric activity coefficient estimations is found to be effective for the explanation and prediction of the distribution data, and the thermodynamic extraction constant is determined as log K_et = 5.16 ± 0.11 at 20°C.     

Pattern recognition using discriminative feature extraction

We propose a new design method, called discriminative feature extraction for practical modular pattern recognizers. A key concept of discriminative feature extraction is the design of an overall recognizer in a manner consistent with recognition error minimization. The utility of the method is demonstrated in a Japanese vowel recognition task     

Speech, audio, and acoustic processing for multimedia

The primary advances in speech and audio signal processing that contributed to the maturing of multimedia applications are discussed in the areas of speech and audio signal compression, speech synthesis, acoustic processing and echo control, and network echo cancellation     

Efficient algorithms for optimistic crash recovery

Summary Recovery from transient processor failures can be achieved by using optimistic message logging and checkpointing. The faulty processorsroll back, and some/all of the non-faulty processors also may have to roll back. This paper formulates the rollback problem as a closure problem. A centralized closure algorithm is presented together with two efficient distributed implementations. Several related problems are also considered and distributed algorithms are presented for solving them. S. Venkatesan received the B. Tech. and M. Tech degrees from the Indian Institute of Technology, Madras in 1981 and 1983, respectively and the M.S. and Ph.D. degrees in Computer Science from the University of Pittsburgh in 1985 and 1988. He joined the University of Texas at Dallas in January 1989, where he is currently an Assistant Professor of Computer Science. His research interests are in fault-tolerant distributed systems, distributed algorithms, testing and debugging distributed programs, fault-tolerant telecommunication networks, and mobile computing. Tony Tony-Ying Juang is an Associate Professor of Computer Science at the Chung-Hwa Polytechnic Institute. He received the B.S. degree in Naval Architecture from the National Taiwan University in 1983 and his M.S. and Ph.D. degrees in Computer Science from the University of Texas at Dallas in 1989 and 1992, respectively. His research interests include distributed algorithms, fault-tolerant distributed computing, distributed operating systems and computer communications.This research was supported in part by NSF under Grant No. CCR-9110177 and by the Texas Advanced Technology Program under Grant No. 9741-036