Microinjection of thyrotropin-releasing hormone analogue into the central nucleus of the amygdala stimulates gastric contractility in rats

The effect on gastric contractility following bilateral microinjection of thyrotropin-releasing hormone (TRH) analog, RX 77368, into the central nucleus of the amygdala was examined in fasted, urethane-anesthetized rats. Extraluminal force transducers were used to measure gastric corpus contractility. Bilateral microinjection of RX 77368 (0.5 microgram, 1.0 microgram, n = 6 each) stimulated gastric contractility for up to 120 min post-injection, P < 0.05. Gastric contractility was not significantly stimulated by microinjection of 0.1 microgram RX 77368, 0.1% bovine serum albumin (BSA) into the central nucleus or RX 77368 (0.5 microgram, 1.0 microgram) into sites adjacent to the central nucleus. Peak responses (1.0 microgram) occurred 40 min post-injection and represented a 16-26-fold increase over basal values. The frequency of gastric contraction waves was attenuated for 0-90 min in rats receiving central amygdaloid microinjection of RX 77368 (0.1, 0.5 or 1.0 microgram) versus rats microinjected with the vehicle or RX 77368 into sites adjacent to the central nuclei. The stimulatory effect of RX 77368 (1.0 microgram) on gastric contractility was abolished by subdiaphragmatic vagotomy. These results indicate that the TRH analog, RX 77368, acts within the central amygdala to vagally stimulate gastric contractility.     

A neural network model for the wire bonding process

A crucial step in manufacturing microcircuits is the wire bonding process in which a very thin gold wire must be formed to connect two surfaces in the microcircuit. The quality of the wire bond can be measured by visual inspection and a pull test—both of which are high-reliability, high-cost approaches to statistical process control. Westinghouse wanted to develop a high-reliability, low-cost quality assurance system. In this paper, we report on a year-long study to construct a neural network model that is capable of predicting the quality of wire bonds. The results of our modeling efforts reveal that neural networks are useful tools for statistical process control problems.     

Environment-assisted cracking in austenitic components

Stress corrosion cracking and corrosion fatigue have been responsible for some costly generic material failures in water cooled power reactors. This paper reviews the main features of two of the most widespread problems, namely intergranular stress corrosion cracking of sensitized stainless steel piping in boiling water reactors (BWR) and of nickel alloy steam generator tubes in pressurized water reactors (PWR). Mechanisms, in so far as they are known, are described together with remedial measures and crack growth models applicable to in-plant components.     

Psychopharmacotherapy for addictive and comorbid disorders: current studies

Proper diagnosis of comorbid disorders is crucial in treatment planning for the dually diagnosed. Since psychoactive substance use can obfuscate the diagnosis, special care must be taken to exclude organically based syndromes. Adequate periods of abstinence should first be achieved and subsequently the patient re-examined for residual symptoms compatible with a nonaddictive, nonsubstance-induced psychiatric disorder. The integration of concurrent treatment of both the mental and the addictive disorders appears to be the best approach for treatment of comorbid psychiatric and addictive disorders. An abstinence-based model that typically utilizes a 12-step group therapy is often employed for the addictive illnesses. Other forms of psychosocial therapies such as case managers are being used as well. Presently, physicians' prescribing practices for comorbid addicted patients are based on traditional approaches to use of medications in psychiatric patients, and their attitudes towards addictive disorders may play a significant role in determining the overall success of treatment.     

The design of experiments when there are errors in all the variables

The Error-in-Variables Model (EVM) applies to a large class of problems in parameter estimation in which there is error in all the variables. This property makes it of more general applicability than the widely used technique of ordinary Least Squares. While there is a voluminous literature on EVM there is nothing on a general method for designing experiments when EVM applies. In this paper we present an extension of the concept of D-optimality to provide such a general method. It is illustrated by applying it to the estimation of copolymer reactivity ratios and to fitting an ellipse.