Molecular cloning and characterisation of a pattern recognition protein, lipopolysaccharide and beta-1,3-glucan binding protein (LGBP) from Chinese shrimp Fenneropenaeus chinensis

A pattern recognition protein (PRP), lipopolysaccharide and beta-1,3-glucan binding protein (LGBP) cDNA was cloned from the haemocyte of Chinese shrimp Fenneropenaeus chinensis by the techniques of homology cloning and RACE. Analysis of nucleotide sequence revealed that the full-length cDNA of 1,275 bp has an open reading frame of 1,098 bp encoding a protein of 366 amino acids including a 17 amino acid signal peptide. Sequence comparison of the deduced amino acid sequence of F. chinensis LGBP showed a high identity of 94%, 90%, 87%, 72% and 63% with Penaeus monodon BGBP, Litopenaeus stylirostris LGBP, Marsupenaeu japonicus BGBP, Homarus gammarus BGBP and Pacifastacus leniusculus LGBP, respectively. The calculated molecular mass of the mature protein is 39,857 Da with a deduced pI of 4.39. Two putative integrin binding motifs, RGD (Arg-Gly-Asp) and a potential recognition motif for beta-1,3-linkage of polysaccharides were observed in LGBP sequence. RT-PCR analysis showed that LGBP gene expresses in haemocyte and hepatopancreas only, but not in other tissues. Capillary electrophoresis RT-PCR method was used to quantify the variation of mRNA transcription level during artificial infection with heat-killed Vibrio anguillarum and Staphylococcus aureusin. A significant enhancement of LGBP transcription was appeared at 6 h post-injection in response to bacterial infection. These results have provided useful information to understand the function of LGBP in shrimp.

A fibrinogen-related protein from bay scallop Argopecten irradians involved in innate immunity as pattern recognition receptor

The family of fibrinogen-related proteins (FREPs) is a group of proteins with fibrinogen-like domains. Many members of this family play important roles as pattern recognition receptors in innate immune responses. The cDNA of bay scallop Argopecten irradians FREP (designated as AiFREP) was cloned by rapid amplification of cDNA ends (RACE) method based on the expressed sequence tag (EST). The full-length cDNA of AiFREP was of 990 bp. The open reading frame encoded a polypeptide of 251 amino acids, including a signal sequence and a 213 amino acids fibrinogen-like domain. The fibrinogen-like domain of AiFREP was highly similar to those of mammalian ficolins and other FREPs. The temporal expression of AiFREP mRNA in hemolymph was examined by fluorescent quantitative real-time PCR. The mRNA level of scallops challenged by Listonella anguillarum was significantly up-regulated, peaked to 9.39-fold at 9 h after stimulation, then dropped back to 4.37-fold at 12 h, while there was no significant change in the Micrococcus luteus challenged group in all periods of treatment. The function of AiFREP was investigated by recombination and expression of the cDNA fragment encoding its mature peptide in Escherichia coli Rosetta gami (DE3). The recombinant AiFREP (rAiFREP) agglutinated chicken erythrocytes and human A, B, O-type erythrocytes. The agglutinating activities were calcium-dependent and could be inhibited by acetyl group-containing carbohydrates. rAiFREP also agglutinated Gram-negative bacteria E. coli JM109, L anguillarum and Gram-positive bacteria M. luteus in the presence of calcium ions. These results collectively suggested that AiFREP functions as a pattern recognition receptor in the immune response of bay scallop and contributed to nonself recognition in invertebrates, which would also provide clues for elucidating the evolution of the lectin pathway of the complement system. (C) 2008 Elsevier Ltd. All rights reserved.

CfLGBP, a pattern recognition receptor in Chlamys farreri involved in the immune response against various bacteria

Lipopolysaccharide and beta-1, 3-glucan binding protein (LGBP) is a kind of pattern recognition receptor, which can recognize and bind LPS and beta-1, 3-glucan, and plays curial roles in the innate immune defense against Gram-negative bacteria and fungi. In this study, the functions of LGBP from Zhikong scallop Chlamys farreri performed in innate immunity were analyzed. Firstly, the mRNA expression of CfLGBP in hemocytes toward three typical PAMPS stimulation was examined by realtime PCR. It was up-regulated extremely (P < 0.01) post stimulation of LPS and beta-glucan, and also exhibited a moderate up-regulation (P < 0.01) after PGN injection. Further PAMPs binding assay with the polyclonal antibody specific for CfLGBP proved that the recombinant CfLGBP (designated as rCfLGBP) could bind not only LPS and beta-glucan, but also PGN in vitro. More importantly, rCfLGBP exhibited obvious agglutination activity towards Gram-negative bacteria Escherichia coil, Gram-positive bacteria Bacillus subtilis and fungi Pichia pastoris. Taking the results of immunofluorescence assay into account, which displayed CfLGBP was expressed specifically in the immune cells (hemocytes) and vulnerable organ (gill and mantle), we believed that LGBP in C farreri, serving as a multi-functional PRR, not only involved in the immune response against Gram-negative and fungi as LGBP in other invertebrates, but also played significant role in the event of anti-Gram-positive bacteria infection. As the first functional research of LGBP in mollusks, our study provided new implication into the innate immune defense mechanisms of C. farreri and mollusks. (C) 2010 Elsevier Ltd. All rights reserved.

Cflec-5, a pattern recognition receptor in scallop Chlamys farreri agglutinating yeast Pichia pastoris

C-type lectins are a superfamily of carbohydrate-recognition proteins which play crucial roles as pattern recognition receptors (PRRs) in the innate immunity. In this study, the full-length cDNA of a C-type lectin was cloned from scallop Chlamys farreri (designated as Cflec-5) by expression sequence tag (EST) analysis and rapid amplification of cDNA ends (RACE) approach The full-length cDNA of Cflec-5 was of 1412 bp. The open reading frame encoded a polypeptide of 153 amino acids, including a signal sequence and a conserved carbohydrate-recognition domain with the EPN motif determining the mannose-binding specificity The deduced amino acid sequence of Cflec-5 showed high similarity to members of C-type lectin superfamily. The quantitative real-time PCR was performed to investigate the tissue distribution of Cflec-5 mRNA and its temporal expression profiles in hemocytes post pathogen-associated molecular patterns (PAMPs) stimulation. In healthy scallops, the Cflec-5 mRNA was mainly detected in gill and mantle, and marginally in other tissues The mRNA expression of Cflec-5 could be significantly induced by lipopolysaccharide (LPS) and glucan stimulation and reached the maximum level at 6 h and 12 h, respectively But its expression level did not change significantly during peptidoglycan (PGN) stimulation The function of Cflec-5 was investigated by recombination and expression of the cDNA fragment encoding its mature peptide in Escherichia coli Rosetta Gami (DE3) The recombinant Cflec-5 agglutinated Pichia pastoris in a calcium-independent way The agglutinating activity could be inhibited by D-mannose. LPS and glucan, but not by D-galactose or PGN. These results collectively suggested that Cflec-5 was involved in the innate Immune response of scallops and might contribute to nonself-recognition through its interaction with various PAMPs (C) 2010 Elsevier Ltd All rights reserved

Some Aspects of Pattern Recognition by Computer

A computer may gather a lot of information from its environment in an optical or graphical manner. A scene, as seen for instance from a TV camera or a picture, can be transformed into a symbolic description of points and lines or surfaces. This thesis describes several programs, written in the language CONVERT, for the analysis of such descriptions in order to recognize, differentiate and identify desired objects or classes of objects in the scene. Examples are given in each case. Although the recognition might be in terms of projections of 2-dim and 3-dim objects, we do not deal with stereoscopic information. One of our programs (Polybrick) identifies parallelepipeds in a scene which may contain partially hidden bodies and non-parallelepipedic objects. The program TD works mainly with 2-dimensional figures, although under certain conditions successfully identifies 3-dim objects. Overlapping objects are identified when they are transparent. A third program, DT, works with 3-dim and 2-dim objects, and does not identify objects which are not completely seen. Important restrictions and suppositions are: (a) the input is assumed perfect (noiseless), and in a symbolic format; (b) no perspective deformation is considered. A portion of this thesis is devoted to the study of models (symbolic representations) of the objects we want to identify; different schemes, some of them already in use, are discussed. Focusing our attention on the more general problem of identification of general objects when they substantially overlap, we propose some schemes for their recognition, and also analyze some problems that are met.

Temporal pattern recognition in video clips detection

Temporal representation and reasoning plays an important role in Data Mining and Knowledge Discovery, particularly, in mining and recognizing patterns with rich temporal information. Based on a formal characterization of time-series and state-sequences, this paper presents the computational technique and algorithm for matching state-based temporal patterns. As a case study of real-life applications, zone-defense pattern recognition in basketball games is specially examined as an illustrating example. Experimental results demonstrate that it provides a formal and comprehensive temporal ontology for research and applications in video events detection.

Relating sardine recruitment in the Northern Benguela to satellite-derived sea surface height using a neural network pattern recognition approach

Processes of enrichment, concentration and retention are thought to be important for the successful recruitment of small pelagic fish in upwelling areas, but are difficult to measure. In this study, a novel approach is used to examine the role of spatio-temporal oceanographic variability on recruitment success of the Northern Benguela sardine Sardinops sagax. This approach applies a neural network pattern recognition technique, called a self-organising map (SOM), to a seven-year time series of satellite-derived sea level data. The Northern Benguela is characterised by quasi-perennial upwelling of cold, nutrient-rich water and is influenced by intrusions of warm, nutrient-poor Angola Current water from the north. In this paper, these processes are categorised in terms of their influence on recruitment success through the key ocean triad mechanisms of enrichment, concentration and retention. Moderate upwelling is seen as favourable for recruitment, whereas strong upwelling, weak upwelling and Angola Current intrusion appear detrimental to recruitment success. The SOM was used to identify characteristic patterns from sea level difference data and these were interpreted with the aid of sea surface temperature data. We found that the major oceanographic processes of upwelling and Angola Current intrusion dominated these patterns, allowing them to be partitioned into those representing recruitment favourable conditions and those representing adverse conditions for recruitment. A marginally significant relationship was found between the index of sardine recruitment and the frequency of recruitment favourable conditions (r super(2) = 0.61, p = 0.068, n = 6). Because larvae are vulnerable to environmental influences for a period of at least 50 days after spawning, the SOM was then used to identify windows of persistent favourable conditions lasting longer than 50 days, termed recruitment favourable periods (RFPs). The occurrence of RFPs was compared with back-calculated spawning dates for each cohort. Finally, a comparison of RFPs with the time of spawning and the index of recruitment showed that in years where there were 50 or more days of favourable conditions following spawning, good recruitment followed (Mann-Whitney U-test: p = 0.064, n = 6). These results show the value of the SOM technique for describing spatio-temporal variability in oceanographic processes. Variability in these processes appears to be an important factor influencing recruitment in the Northern Benguela sardine, although the available data time series is currently too short to be conclusive. Nonetheless, the analysis of satellite data, using a neural network pattern-recognition approach, provides a useful framework for investigating fisheries recruitment problems.

Experimental investigation of a wavelet based drive-by bridge inspection system incorporating pattern recognition

This paper presents the results of an experimental investigation, carried out in order to verify the feasibility of a ‘drive-by’ approach which uses a vehicle instrumented with accelerometers to detect and locate damage in a bridge. In theoretical simulations, a simplified vehicle-bridge interaction model is used to investigate the effectiveness of the approach in detecting damage in a bridge from vehicle accelerations. For this purpose, the accelerations are processed using a continuous wavelet transform and damage indicators are evaluated and compared. Alternative statistical pattern recognition techniques are incorporated to allow for repeated vehicle passes. Parameters such as vehicle speed, damage level, location and road roughness are varied in simulations to investigate the effect. A scaled laboratory experiment is carried out to assess the effectiveness of the approach in a more realistic environment, considering a number of bridge damage scenarios.

An indirect bridge inspection method incorporating a wavelet-based damage indicator and pattern recognition

In recent years, there has been a move towards the development of indirect structural health monitoring (SHM)techniques for bridges; the low-cost vibration-based method presented in this paper is such an approach. It consists of the use of a moving vehicle fitted with accelerometers on its axles and incorporates wavelet analysis and statistical pattern recognition. The aim of the approach is to both detect and locate damage in bridges while reducing the need for direct instrumentation of the bridge. In theoretical simulations, a simplified vehicle-bridge interaction model is used to investigate the effectiveness of the approach in detecting damage in a bridge from vehicle accelerations. For this purpose, the accelerations are processed using a continuous wavelet transform as when the axle passes over a damaged section, any discontinuity in the signal would affect the wavelet coefficients. Based on these coefficients, a damage indicator is formulated which can distinguish between different damage levels. However, it is found to be difficult to quantify damage of varying levels when the vehicle’s transverse position is varied between bridge crossings. In a real bridge field experiment, damage was applied artificially to a steel truss bridge to test the effectiveness of the indirect approach in practice; for this purpose a two-axle van was driven across the bridge at constant speed. Both bridge and vehicle acceleration measurements were recorded. The dynamic properties of the test vehicle were identified initially via free vibration tests. It was found that the resulting damage indicators for the bridge and vehicle showed similar patterns, however, it was difficult to distinguish between different artificial damage scenarios.