Physiological roles of thyrotrophin-releasing hormone and vasoactive intestinal peptide on the pulsatile secretory patterns of prolactin in pituitary-grafted female rats

Much is known about the fact that thyrotrophin-releasing hormone (TRH) and vasoactive intestinal peptide (VIP) stimulate prolactin secretion but areas of uncertainty remain. This work was undertaken to describe the effects of TRH and VIP on the pulsatile secretion pattern of prolactin, in adult sham-operated and pituitary-grafted hyperprolactinaemic female rats. Two pulses of TRH (1 microgram/rat) or one pulse of VIP (20 micrograms/rat) were given 60 or 120 min after the period of blood sampling. Pituitary grafting increased the mean values of prolactin, absolute amplitude and duration of the peaks and decreased their frequency, compared with control animals. In sham-operated rats, TRH elevated prolactin levels by increasing the absolute and relative amplitudes and duration of the pulses, along with a decrease in their frequency. No priming effects of TRH were observed in this study. Hyperprolactinaemia blunted TRH effects on the pulsatile secretion pattern of prolactin. In sham-operated rats, VIP administration increased the absolute and relative amplitudes of the prolactin peaks. None of the other parameters studied were changed. In pituitary-grafted animals, VIP administration increased the absolute and relative amplitudes of the prolactin peaks but to a lesser extent compared with controls. These data suggest that TRH and VIP affect prolactin pulsatility differentially. The effects of TRH and VIP were blunted to some extent by exposure to previously elevated circulating prolactin levels.     

Turn of the century refueling: A review of innovations in early gasoline refueling methods and analogies for hydrogen

During the first decades of the 20th century, a variety of gasoline refueling methods supported early US gasoline vehicles and successfully alleviated consumer concerns over refueling availability. The refueling methods employed included cans, barrels, home refueling outfits, parking garage refueling facilities, mobile stations, hand carts and curb pumps. Only after robust markets for gasoline vehicles had been firmly established did the gasoline service station become the dominant refueling method. The present study reviews this history and draws analogies with current and future efforts to introduce hydrogen as a fuel for vehicles. These comparisons hold no predictive power; however, there is heuristic value in an historical review of the first successful and large-scale introduction of a vehicle fuel. From an energy policy perspective, these comparisons reinforce the importance of a long-term and portfolio approach to support for technology development and innovation.     

Dietary L-arginine reduces the progression of atherosclerosis in cholesterol-fed rabbits: comparison with lovastatin

BACKGROUND: We investigated whether L-arginine induces regression of preexisting atheromatous lesions and reversal of endothelial dysfunction in hypercholesterolemic rabbits, whether similar effects can be obtained by cholesterol-lowering therapy with lovastatin, and which mechanism leads to these effects. METHODS AND RESULTS: Rabbits were fed 1% cholesterol for 4 weeks and 0.5% cholesterol for an additional 12 weeks. Two groups of cholesterol-fed rabbits were treated with L-arginine (2.0% in drinking water) or lovastatin (10 mg/d) during weeks 5 through 16. Systemic nitric oxide (NO) formation was assessed as the urinary excretion rates of nitrate and cGMP in weekly intervals. Cholesterol feeding progressively reduced urinary nitrate excretion to approximately 40% of baseline (P<.05) and increased plasma concentrations of asymmetrical dimethylarginine (ADMA), an endogenous NO synthesis inhibitor. Dietary L-arginine reversed the reduction in plasma L-arginine/ADMA ratio and partly restored urinary excretion of nitrate and cGMP (each P<.05 vs cholesterol) but did not change plasma cholesterol levels. L-Arginine completely blocked the progression of carotid intimal plaques, reduced aortic intimal thickening, and preserved endothelium-dependent vasodilator function. Lovastatin treatment reduced plasma cholesterol by 32% but did not improve urinary nitrate or cGMP excretion or endothelium-dependent vasodilation. Lovastatin had a weaker inhibitory effect on carotid plaque formation and aortic intimal thickening than L-arginine. L-Arginine inhibited but lovastatin potentiated superoxide radical generation in the atherosclerotic vascular wall. CONCLUSIONS: Dietary L-arginine improves NO-dependent vasodilator function in cholesterol-fed rabbits and completely blocks the progression of plaques via restoration of NO synthase substrate availability and reduction of vascular oxidative stress. Lovastatin treatment has a weaker inhibitory effect on the progression of atherosclerosis and no effect on vascular NO elaboration, which may be due to its stimulatory effect on vascular superoxide radical generation.     

Referate

Ohne ZusammenfassungIn die Zusammenstellung der Referate sind auch die Originalmitteilungen nochmals aufgenommen und durch Kursiv-Typen der Seitenzahlen kenntlich gemacht.     

Application of principal component analysis to the prediction of lucerne forage protein content and in vitro dry matter digestibility by NIR spectroscopy

Application of principal component regression (PCR) was proposed for the development of a prediction equation of forage composition by near infra-red spectroscopy. PCR involves two steps: (a) the creation of new synthetic variables by principal component analysis (PCA) of spectral data, and (b) multiple linear regression with these new variables. Results obtained by this procedure have been compared with those generated by the conventional application of multiple linear regression (MLR) on spectral data. The comparison used the determination of protein content and in vitro dry matter digestibility (IVDMD) in 345 samples of lucerne forages. For protein determination, results of both procedures were quite similar (correlation coefficients: 0.978 and 0.980; standard errors of calibration: 0.86 and 0.84% DM; standard errors of prediction: 0.81 and 0.80% DM respectively for MLR and PCR prediction equations). The same was observed for IVDMD determination (correlation coefficients: 0.942 and 0.951; standard errors of calibration: 1.89 and 1.71% DM; standard errors of prediction: 2.22 and 2.22% DM, respectively). A large number of PCA variables were necessary for an accurate prediction of both constituents. The influence of the number of regression terms introduced in the PCR equation has been studied. The criterion for stopping the introduction of new terms in PCR did not seem as critical as in MLR.     

Computer aided engineering of automated guided vehicle systems

Automated Guided Vehicle Systems (AGVS) are becoming more and more the main material handling devices in flexible manufacturing systems. The design of an AGVS network is a complex, iterative process. It requires a sequence of geometrical layout drawings and an analytical and computational evaluations. The ability to analyze the AGVS design directly and interactively from the layout drawing would substantially increase the productivity of the design engineer.

A Computer Aided Engineering (CAE) design tool must provide the following three capabilities. First, it must allow the easy, interactive and graphical definition of the system by providing standard drawing symbols and the required operations on those symbols. Second, it must support direct, interactive analysis of the design from within the drafting package. Third, it must provide for the necessary output to interface with off line simulation, analysis and verification programs.

The possibility of extending the prominent CAD packages CADAM and AutoCad to perform CAE of AGVS is examined. A prototype of such a CAE tool has been developed based upon the Autocad package and implemented on a microcomputer. Design and implementation issues, as well as future research areas, will be reported on.     

Accurate value-at-risk forecasting based on the normal-GARCH model

A resampling method based on the bootstrap and a bias-correction step is developed for improving the Value-at-Risk (VaR) forecasting ability of the normal-GARCH model. Compared to the use of more sophisticated GARCH models, the new method is fast, easy to implement, numerically reliable, and, except for having to choose a window length L for the bias-correction step, fully data driven. The results for several different financial asset returns over a long out-of-sample forecasting period, as well as use of simulated data, strongly support use of the new method, and the performance is not sensitive to the choice of L.