Analysis of tear proteins by one- and two-dimensional thin-layer iosoelectric focusing, sodium dodecyl sulfate electrophoresis and lectin blotting. Detection of a new component: cystatin C

BACKGROUND: Isoelectric focusing (IEF) of tear proteins has not yet been carried out in a satisfactory way. Two-dimensional (2D) electrophoresis, especially in the combination of IEF with SDS, is able to differentiate between proteins in detail. The purpose of this study was therefore to analyze tear proteins by 1D IEF alone and in combination with a 2D pattern, and by IEF followed by lectin staining. METHODS: Ampholines, covering a broad range from pH 3 to pH 10, were applied. After IEF, semi-dry blotting and incubation with a group II lectin and two group V lectins was performed. RESULTS: Tear proteins could be separated into 31 single bands. Tear-specific pre-albumin (TSPA), lactoferrin, sIgA, IgG and lysozyme were found to be main components. Isoelectric points (IEPs, pls) of all proteins separated were determined by comparison with IEF standards. 2D patterns of IEF and SDS electrophoresis were obtained for the main subunit components of lactoferrin, sIgA, TSPA, and lysozyme. An additional new component of considerable concentration was focused at pI 8.6 with a subunit MW of 14 kDa. With s-WGA a component at an IEP of 5.2 was visualized, representing transferrin. With SNA, lactoferrin stained as a sharp main band at pI 5.1 with three additional weaker bands at IEPs from 4.8 to 4.9. At IEPs between 4.4 and 6.1, multiple components of sIgA were stained with MAA. The sugar specificity of transferrin at pI 5.2 was beta-GlcNAc. Lactoferrin showed glycation with NANA-alpha-2-6-Gal or NANA-alpha-2-6-GalNAc, whereas the sugar specificity of sIgA was NANA-alpha-2-3-Gal. CONCLUSIONS: The investigative strategy applied here, including IEF alone, in combination with SDS-electrophoresis, and SDS-electrophoresis followed by lectin staining proved to be a reproducible method for tear protein analysis of hitherto unexperienced capacity. Lectin-stained bands of native tear proteins are not uniformly glycated by one sugar residue, but show various sugar specificities. IgA as a whole molecule is specifically glycated with NANA-alpha-2-3-Gal.     

An analytical method for comparing natural diversity to DSMcontrolled diversity

The purpose of this paper is to report an analytical method of comparing natural diversity with controlled diversity, and to show the results of comparing the peak load resulting from natural diversity in a set of air conditioning units to the peak load that can be achieved with DSM control of the same set of air conditioners. In this study it is assumed that the energy use by the air conditioners is the same in both cases. Under this assumption, an analytical model for finding the probabilities of all the possible peak loads is developed and illustrated in case studies     

Results of a Computer Prediction of After-Radiation Reliability

This paper describes the results of predicting the reliability of a circuit at different radiation levels. The conditional mean and variance of circuit output and the conditional reliability are predicted using Sceptre and test data on components exposed to different levels of radiation. These predictions are compared with the results of tests of the circuit. The difference between predictions and tests are examined and explained. The conclusions suggest a minor modification of the proposed method. We also suggest that this method of computer-aided reliability prediction can be a valuable design aid. This is especially true when there is a significant effect due to environmental variation, such as the effect of radiation on semiconductors.     

Adaptive fuel allocation using pseudo fuel prices

The authors outline a practical adaptive fuel allocation approach. The approach uses pseudo fuel prices as decision variables. As a result, the fuel allocation decision can be conveniently implemented in system operation by using the pseudo fuel prices to dispatch generation. A lower pseudo price usually results in higher fuel consumption and a higher pseudo price usually results in lower fuel consumption. In the proposed approach, the systematic criterion for adaptively identifying the need for reschedulings is based on the absolute change in each pseudo fuel price. Various aspects of the proposed approach are discussed, and its application to a midwestern utility system is illustrated     

Evaluation of the variance of production cost using a stochasticoutage capacity state model

A stochastic outage capacity state model is presented for evaluating the random error in power system production cost which is estimated via the Baleriaux-Booth approach. The proposed model is thought to be the first model capable of evaluating the variance of production cost of a system of realistic size. The proposed model is used to evaluate the normalized standard random error of production cost for the IEEE Reliability Test System with an 168-hour simulation horizon. The result is about 13%. An extension approximation is suggested for estimating the normalized standard random error of production cost for a long simulation horizon (e.g. one year) from the results obtained from a short-term (e.g. a day, a week) simulation. Using this result the annual normalized standard random error is about 2.7%     

Estimating the variance of production cost using a stochastic loadmodel

The purpose of this paper is to provide a realistic load variation model to be used in short-term (one to three years) planning studies. A stochastic model is proposed, and this model is used to quantify the variation of the estimated production cost that is directly affected by the load uncertainty. The paper presents a method of estimating the variation of production cost. This is the first paper to use a Gauss-Markov stochastic model of load with a chronological production simulation model. This load model captures the stochastic load variation behavior and the correlation between weekly peak demand and weekly energy. A weekly Gauss-Markov sampling scheme is incorporated in the proposed approach to model load variation. This stochastic load model is used to generate sample chronological load profiles that represent the annual load variation in weekly detail. These load profiles are then used in annual Monte Carlo production simulation. Case studies illustrate the implementation of this stochastic load variation modeling. These case studies illustrate that load uncertainty has a significantly larger effect on cost uncertainty than does uncertainty in unit availability     

A Gauss-Markov load model for application in risk evaluation andproduction simulation

Load uncertainty contributes to system operational risk; thus the study of system operating reserve or unit commitment risk requires a load model that includes the uncertainty in load as well as the variation with time. The authors propose a Gauss-Markov load model. This random process model includes both the time variation and the uncertainty in load. This load model is used to predict, conditional on what is known at a previous hour, the mean and the variance of the system hourly load. This mean and variance are required for a system operating reserve study and a broad spectrum of production simulations. The proposed load model is described, the model is justified, and the model is illustrated via an example     

An adaptive production simulation structure for operationalplanning with annual emission/fuel constraints

This paper describes a production simulation structure for use in operational planning. The key features of the structure are: it captures the chronological aspects of power production; it models adaptive compliance with annual emission/fuel constraints; and it models generator availability using a conditional Monte Carlo sampling approach. The purpose of the paper is to demonstrate that this structure can produce unbiased and low variance results while modeling uncertainty with an acceptable computational requirement     

Stochastic production cost simulation

This paper describes a method of simulating the annual operational cost of an electrical power system. The significant aspects of this simulation method are: the method of simulation is chronological; the uncertainty of unit availability is modeled; and fuel/emission constraints are adaptively met (i.e. next week's fuel allocation is adjusted to account for past fuel usage and emissions).