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

Discrimination of Type 2 diabetic patients from healthy controls by using metabonomics method based on their serum fatty acid profiles

Metabonomics, the study of metabolites and their roles in various disease states, is a novel methodology arising from the post-genomics era. This methodology has been applied in many fields, including work in cardiovascular research and drug toxicology. In this study, metabonomics method was employed to the diagnosis of Type 2 diabetes mellitus (DM2) based on serum lipid metabolites. The results suggested that serum fatty acid profiles determined by capillary gas chromatography combined with pattern recognition analysis of the data might provide an effective approach to the discrimination of Type 2 diabetic patients from healthy controls. And the applications of pattern recognition methods have improved the sensitivity and specificity greatly. (C) 2004 Elsevier B.V. All rights reserved.

Metabolic profiling of serum from gadolinium chloride-treated rats by H-1 NMR spectroscopy

Metabolic profiling of serum from gadolinium chloride (GdCl3, 10 and 50 mg/kg body weight, intraperitoneal [i.p.])-treated rats was investigated by the NMR spectroscopic-based metabonomic strategy. Serum samples were collected at 48, 96, and 168 h postdose (p.d.) after exposure to GdCl3. H-1 NMR spectra of serum were analyzed by pattern recognition using principal components analysis. The studies showed that there was a dose-related biochemical effect of GdCl3 treatment on the levels of a range of low-molecular weight compounds in serum. The liver damage induced by GdCl3 was characterized by the elevation of lactate, pyruvate, and creatine as well as the decrease of branched-chain amino acids (valine and isoleucine), alanine, glucose, and trimethylamine-N-oxide concentration in serum samples. The biochemical effects of GdCl3 in rats could be consulted when evaluating the biochemical profile of gadolinium-containing compounds that are being developed for nuclear magnetic resonance imaging.

Comparison of biochemical effects induced by Changle between male and female rats using NMR and ICP-MS techniques

Metabolic profiles caused by rare earth complex were investigated using NMR and ICP-MS techniques. Male and female Wistar rats were treated orally with Changle (A kind of rare earth complex applied in agriculture to raise the production of crops) at dose of 2, 5 and 20 mg (.) kg(-1) body weight/day respectively for 90 d. Urine and serum samples are collected on 90 d. The relative concentrations of important endogenous metabolites in urine and serum are determined from H-1 NMR spectra and the contents of the four rare earth elements ( La, Ce, Pr and Nd) constituting Changle in the serum samples are measured by ICP-MS technique. Changle-induced renal and liver damage in rats is found based on the increase in the amounts of the amino acids, trimethylamine N-oxide, N, N-dimethyglycine, dimethylamine, succinate, aketoglutarate and ethanol as well as rare earth concentrations. The similarities and differentiations are found in the alteration patterns of metabolites and rare earth concentrations in serum.

Investigation on acute biochemical effects of Ce(NO3)(3) on liver and kidney tissues by MAS H-1 NMR spectroscopic-based metabonontic approach

High resolution magic angle spinning (MAS)-H-1 nuclear magnetic resonance (NMR) spectroscopic-based metabonomic approach was applied to the investigation on the acute biochemical effects of Ce(No-3)(3). Male Wistar rats were administrated with various doses of Ce (NO3)(3)(2, 10, and 50 mg(.)kg(-1) body weight), and MAS H-1 NMR spectra of intact liver and kidney tissues were analyzed using principal component analysis to extract toxicity information. The biochemical effects of Ce (NO3)(3) were characterized by the increase of triglycerides and lactate and the decrease of glycogen in rat liver tissue, together with an elevation of the triglyceride level and a depletion of glycerophosphocholine and betaine in kidney tissues. The target lesions of Ce (NO3)(3) on liver and kidney were found by MAS NMR-based metabonomic method. This study demonstrates that the combination of MAS H-1 NMR and pattern recognition analysis can be an effective method for studies of biochemical effects of rare earths.

Ultrafast temporal pattern generation and recognition

Ultrafast temporal pattern generation and recognition with femtosecond laser technology is presented, analyzed, and experimentally implemented. Ultrafast temporal pattern generation and recognition are realized by taking advantage of two well-known techniques: the space-time conversion technique and the ultrafast pulse measurement technique. Here the temporal pattern for the designed multiple pulses, optimized with a preassumed Gaussian spectral distribution of an ultrashort pulse, is described. With the simulation of a Gaussian spectral distribution, we realize that the uniformity of the generated multiple ultrafast temporal pulses is relevant to the repeated number of modulation periods in the mask in the spectral plane. Moreover, the change of Gaussian spectral phases with the wavelengths in the modulated phase plate is considered. Experiments of ultrafast temporal pattern recognition by the frequency-resolved optical gating (FROG) characterization technique are also given. (C) 2004 Society of Photo-Optical Instrumentation Engineers.

Mathematical symbols and computing methods in high dimensional biomimetic informatics and their applications

High dimensional biomimetic informatics (HDBI) is a novel theory of informatics developed in recent years. Its primary object of research is points in high dimensional Euclidean space, and its exploratory and resolving procedures are based on simple geometric computations. However, the mathematical descriptions and computing of geometric objects are inconvenient because of the characters of geometry. With the increase of the dimension and the multiformity of geometric objects, these descriptions are more complicated and prolix especially in high dimensional space. In this paper, we give some definitions and mathematical symbols, and discuss some symbolic computing methods in high dimensional space systematically from the viewpoint of HDBI. With these methods, some multi-variables problems in high dimensional space can be solved easily. Three detailed algorithms are presented as examples to show the efficiency of our symbolic computing methods: the algorithm for judging the center of a circle given three points on this circle, the algorithm for judging whether two points are on the same side of a hyperplane, and the algorithm for judging whether a point is in a simplex constructed by points in high dimensional space. Two experiments in blurred image restoration and uneven lighting image correction are presented for all these algorithms to show their good behaviors.

Short and long peptidoglycan recognition proteins (PGRPs) in zebrafish, with findings of multiple PGRP homologs in teleost fish

Peptidoglycan recognition protein (PGRP) specifically binds to peptidoglycan and is considered to be one of the pattern recognition proteins in the innate immunity of insect and mammals. Using a database mining approach and RT-PCR, multiple peptidoglycan recognition protein (PGRP) like genes have been discovered in fish including zebrafish Danio rerio, Japanese pufferfish TakiFugu rubripes and spotted green pufferfish Tetraodon nigroviridis. They share the common features of those PGRPs in arthropod and mammals, by containing a conserved PGRP domain. Based on the predicted structures, the identified zebrafish PGRP homologs resemble short and long PGRP members in arthropod and mammals. The identified PGRP genes in T. nigroviridis and TakiFugu rubripes resemble the long PGRPs, and the short PGRP genes have not been found in T. nigroviridis and TakiFugu rubripes databases. Computer modelling of these molecules revealed the presence of three alpha-helices and five or six beta-strands in all fish PGRPs reported in the present study. The long PGRP in teleost fish have multiple alternatively spliced forms, and some of the identified spliced variants, e.g., tnPGRP-L3 and tnPGRP-L4 (in: Tetraodon nigroviridis), exhibited no characters present in the PGRP homologs domain. The coding regions of zfPGRP6 (zf: zebrafish), zfPGRP2-A, zfPGRP2-B and zfPGRP-L contain five exons and four introns; however, the other PGRP-like genes including zfPGRPSC1a, zfPGRPSC2, tnPGRP-L1-, tnPGRP-L2 and frPGRP-L (fr: Takifugu rubripes) contain four exons and three introns. In zebrafish, long and short PGRP genes identified are located in different chromosomes, and an unknown locus containing another long PGRP-like gene has also been found in zebrafish, demonstrating that multiple PGRP loci may be present in fish. In zebrafish, the constitutive expressions of zfPGRP-L, zfPGRP-6 and zfPGRP-SC during ontogeny from unfertilized eggs to larvae, in different organs of adult, and the inductive expression following stimulation by Flavobacterium columnare, were detected by real-time PCR, but the levels and patterns varied for different PGRP genes, implying that different short and long PGRPs may play different roles in innate immune response. (c) 2007 Elsevier Ltd. All rights reserved.

A Cancer Recognition Method Based on DNA Microarray

The accurate cancer classification is of great importance in clinical treatment. Recently, the DNA microarray technology provides a promising approach to the diagnosis and prognosis of cancer types. However, it has no perfect method for the multiclass classification problem. The difficulty lies in the fact that the data are of high dimensionality with small sample size. This paper proposed an automatic classification method of multiclass cancers based on Biomimetic pattern recognition (BPR). To the public GCM data set, the average correct classification rate reaches 80% under the condition that the correct rejection rate is 81%.

The application of DBF neural networks for object recognition

On the basis of DBF nets proposed by Wang Shoujue, the model and properties of DBF neural network were discussed in this paper. When applied in pattern recognition, the algorithm and implement on hardware were presented respectively. We did experiments on recognition of omnidirectionally oriented rigid objects on the same level, using direction basis function neural networks, which acts by the method of covering the high dimensional geometrical distribution of the sample set in the feature space. Many animal and vehicle models (even with rather similar shapes) were recognized omnidirectionally thousands of times. For total 8800 tests, the correct recognition rate is 98.75%, the error rate and the rejection rate are 0.5% and 1.25% respectively. (C) 2003 Elsevier Inc. All rights reserved.

Iris recognition algorithm based on point covering of high-dimensional space and neural network

In this paper, we constructed a Iris recognition algorithm based on point covering of high-dimensional space and Multi-weighted neuron of point covering of high-dimensional space, and proposed a new method for iris recognition based on point covering theory of high-dimensional space. In this method, irises are trained as "cognition" one class by one class, and it doesn't influence the original recognition knowledge for samples of the new added class. The results of experiments show the rejection rate is 98.9%, the correct cognition rate and the error rate are 95.71% and 3.5% respectively. The experimental results demonstrate that the rejection rate of test samples excluded in the training samples class is very high. It proves the proposed method for iris recognition is effective.

A novel face recognition method based on hypersausage neural networks

In this paper, we firstly give the nature of 'hypersausages', study its structure and training of the network, then discuss the nature of it by way of experimenting with ORL face database, and finally, verify its unsurpassable advantages compared with other means.

Hypersausage neural networks and its application in face recognition

In this paper, we firstly give the nature of 'hypersausages', study its structure and training of the network, then discuss the nature of it by way of experimenting with ORL face database, and finally, verify its unsurpassable advantages compared with other means.