Iterative optimization of high-affinity proteases inhibitors using phage display. 1. Plasmin

We generated a series of libraries having variants of the first Kunitz domain of human lipoprotein-associated coagulation inhibitor (LACI-D1, also known as tissue-factor pathway inhibitor-I) displayed on bacteriophage M13 as pIII-fusions. We varied LACI-DI iteratively in two regions: the P1 region (positions 10-21) and the "second loop", (positions 31-39), which together form one end of the domain. Display-phage library Lib#1 allows 31 200 amino-acid sequences in P1 region (residues 13, 16-19). Preliminary, we screened Lib#1 against human plasmin (PLA, EC 3.4.21.7) immobolized on agarose to enrich for phage displaying variants with PLA affinity. We introduced a 1600-fold increase in second-loop diversity (residues 31, 32, 34, 39) into the population of selectants from Lib#1, yielding Lib#2. Lib#2 (allowing approximately 50 million amino-acid sequences) was screened against PLA-agarose to isolate highest affinity binders. Protein EPI-P211, derived from the best isolate of Lib#2, inhibits PLA with Ki = 2 nM (at least 500-fold better than LACI-D1) and with high specificity. We used amino-acid sequences of PLA-binding selectants to design a PLA-biased library (Lib#3) which we screened against PLA. The protein EPI-P302 (derived from the best binder obtained from Lib#3) has Ki for PLA inhibition of 87 pM, which is 25-fold better than the first-round best binder and > or = 12 500-fold better than LACI-D1. EPI-P302 also shows very high specificity for PLA vs other human proteases and is resistant to inactivation by oxidants and extremes of temperature or pH. Thus, one can use selectants from one library to design target-tailored combinatorial libraries and obtain quite stable, highly specific, very high-affinity binding molecules while maintaining an essentially human framework.     

Perinuclear antineutrophil cytoplasmic antibodies in patients with Crohn's disease define a clinical subgroup

BACKGROUND & AIMS: Antineutrophil cytoplasmic antibodies (ANCA) have been consistently detected in a subgroup of patients with Crohn's disease (CD). This study was designed to determine whether serum ANCA expression in patients with CD characterizes an identifiable clinical subgroup. METHODS: The study population consisted of 69 consecutive patients with an established diagnosis of CD as determined by a combination of characteristic clinical, radiographic, endoscopic, and histopathologic criteria. Sera from the patients were analyzed for the presence of ANCAs using the fixed neutrophil enzyme-linked immunosorbent assay (ELISA) assay. Perinuclear ANCA (pANCA)-positive and cytoplasmic ANCA (cANCA)-positive results by ELISA were confirmed by indirect immunofluorescence staining. Clinical profiles of the ANCA-positive patients with CD were compared with those of patients with CD not expressing ANCA (ANCA-negative). RESULTS: pANCA-positive patients with CD have endoscopically and/or histopathologically documented left-sided colitis and symptoms of left-sided colonic inflammation, clinically reflected by rectal bleeding and mucus discharge, urgency, and treatment with topical agents. One hundred percent of patients with CD expressing pANCA had "UC-like" features. CONCLUSIONS: In patients with CD, serum pANCA expression characterizes a UC-like clinical phenotype. Stratification of CD by serum pANCA provides evidence of heterogeneity within CD and suggests a common intestinal mucosal inflammatory process among a definable subgroup of patients with CD and UC expressing this marker.     

Visual information processing in primate cone pathways. I. A model

At the retinal level, the strategies utilized by biological visual systems allow them to outperform machine vision systems, serving to motivate the design of electronic or "smart" sensors based on similar principles. Design of such sensors in silicon first requires a model of retinal information processing which captures the essential features exhibited by biological retinas. In this paper, a simple retinal model is presented, which qualitatively accounts for the achromatic information processing in the primate cone system. The computer retina model exhibits many of the properties found in biological retinas such as data reduction through nonuniform sampling, adaptation to a large dynamic range of illumination levels, variation of visual acuity with illumination level, and enhancement of spatiotemporal contrast information. The main emphasis of the model presented here is to demonstrate how different adaptation mechanisms play a role in extending the operating range of the primate retina.     

Detection and quantification of valve stiction by the method of unknown input estimation

Valve stiction is one of the most common causes of oscillations in industrial process control loops. Such oscillations can degrade the overall performance of the loop and eventually the final product quality. The detection and quantification of valve stiction in industrial process control loops is thus important. From previous studies in the literature, a sticky valve has been shown to have a distinct signature of the stiction phenomena in its valve positioner data. However, the position of the modulating control valves is seldom available. We consider the problem of estimating the valve position as an unknown input estimation problem. In this work, we propose a novel application of the unknown input estimator in order to estimate the valve position given the process model and the data of the process variable and controller output. Using the estimated valve position, we can detect and also quantify the amount of stiction. We demonstrate the efficacy of the method through simulation examples where a sticky valve is deliberately introduced in the closed loop using a two-parameter stiction model available in the literature. Application of the proposed methodology to a laboratory scale flow control loop is presented. An industrial case study is also presented in which the algorithm accurately detects and quantifies stiction in the level control loop of a power plant.     

Consistency of noise covariance estimation in joint input–output closed-loop subspace identification with application in LQG benchmarking

The LQG trade-off curve has been used as a benchmark for control loop performance assessment. The subspace approach to estimating the LQG benchmark has been proposed in the literature which requires certain intermediate matrices in subspace identification as well as the covariance matrix of the noise. It is shown in this paper that many existing closed-loop identification methods do not give a consistent estimate of the noise covariance matrix. As a result, we propose an alternative subspace formulation for the joint input–output closed-loop identification for which the consistency of the required subspace matrices and noise covariance is guaranteed. Simulation studies and experimental results are provided to demonstrate the utility of the proposed method.     

Closed loop identification and control loop reconfiguration: an industrial case study

The results of a joint university–industry collaborative project for control loop reconfiguration using closed loop experimental data from a fuel gas pressure control system are described in this paper. The fuel gas pressure was being regulated using a butane stream. For economic reasons, it was necessary to switch control to the ethane stream. Previous attempts at effecting this changeover had proved unsuccessful. In this study, a powerful system identification technique namely Canonical Variate Analysis (CVA) was employed to obtain the empirical plant models. A PI controller was then designed using the direct synthesis method. Acceptable closed loop behavior was obtained with little online tuning.     

Computational haemodynamics: geometry and non-newtonian modelling using spectral/hp element methods

The increased availability of large scale computational facilities is enabling the use of computational modelling for the treatment of complex problems of industrial interest. Computational haemodynamics is an area where improved computational power and algorithmic development have permitted the application in biomechanics of techniques originally devised for direct numerical simulations in others areas of scientific interest. In this paper we present a highly accurate algorithm for the numerical solution of the incompressible Navier–Stokes equations which employs a spectral/hp element spatial discretisation and a high-order time splitting. Two important developments discussed in this paper are the coupling of these techniques with unstructured mesh generation, used in many everyday engineering applications, and the introduction of a non-Newtonian viscosity model to account for the shear thinning properties of blood. The proposed method will be applied to the analysis of shear stress distributions in flows of interest in haemodynamics. Received: 5 May 1999 / Accepted: 21 september 1999     

Diagnosis and treatment of aortic valve stenosis

The present review has attempted to summarize the classic symptoms and signs of aortic valve stenosis, especially in an adult. It is emphasized that all the classic signs rarely are present and their absence may mislead an unwary clinician. The diagnostic help provided by noninvasive tests, including echocardiography and phonocardiography, has been emphasized. A need for cardiac catheterization and angiography in most patients prior to corrective surgery is stressed. The natural history of the disease without operative intervention is dim and a significant risk of sudden death exists. The current surgical approach with immediate and long-term results is summarized. Finally, attention has been drawn to the special clinical circumstances when the aortic valve stenosis provides a strinkingly different clinical picture. We cannot find a better way to end this review than by quoting a warning note given by Thomas Lewis in 1920: "It is the faint cry of an anguished and fast failing muscle, which, when it comes, all should strain to hear, for it is not long repeated. A few months, a few years at most, and the end comes."     

Improving Water Supply Outlook in Korea with Ensemble Streamflow Prediction

Abstract

The purpose of this study is to propose an alternative forecasting approach for improving the current water supply outlook in Korea. Using a rainfall-runoff model, the existing technique for the water supply outlook in Korea produces monthly low, average, and high runoff forecasts. The proposed technique is called Ensemble Streamflow Prediction (ESP), and is currently implemented by the National Weather Service in the U.S.A. ESP appears particularly valid in Korea where the historical rainfall record is much more comprehensive than the historical streamflow record. This study applies ESP to runoff forecasting for a river basin in Korea to examine its applicability. An ensemble of one-month ahead runoff forecasts at the Gongju gauging station in the Keum River basin, Korea, was generated for each month. The resulting ESP forecasts were compared with the corresponding observed runoff data as well as the existing forecasts. Although this study is limited to one case study, the following conclusions can be made: (1) the ESP technique dominates the existing forecasting techniques in terms of both systematic and random errors; and (2) ESP is more accurate when high flows occur.     

Part-based spatio-temporal model for multi-person re-identification

In this paper we propose an adaptive part-based spatio-temporal model that characterizes person’s appearance using color and facial features. Face image selection based on low level cues is used to select usable face images to build a face model. Color features that capture the distribution of colors as well as the representative colors are used to build the color model. The model is built over a sequence of frames of an individual and hence captures the characteristic appearance as well as its variations over time. We also address the problem of multiple person re-identification in the absence of calibration data or prior knowledge about the camera layout. Multiple person re-identification is a open set matching problem with a dynamically evolving and open gallery set and an open probe set. Re-identification is posed as a rectangular assignment problem and is solved to find a bijection that minimizes the overall assignment cost. Open and closed set re-identification is tested on 30 videos collected with nine non-overlapping cameras spanning outdoor and indoor areas, with 40 subjects under observation. A false acceptance reduction scheme based on the developed model is also proposed.