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Although the yeast Saccharomyces cerevisiae is the best exemplified single-celled eukaryote, the vast number of protein-protein interactions of integral membrane proteins of Saccharomyces cerevisiae have not been characterized by experiments. Here, based on the kernel method of Greedy Kernel Principal Component analysis plus Linear Discriminant Analysis, we identify 300 protein-protein interactions involving 189 membrane proteins and get the outcome of a highly connected protein-protein interactions network. Furthermore, we study the global topological features of integral membrane proteins network of Saccharomyces cerevisiae. These results give the comprehensive description of protein-protein interactions of integral membrane proteins and reveal global topological and robustness of the interactome network at a system level. This work represents an important step towards a comprehensive understanding of yeast protein interactions.

In this paper, we adopted the bounded support vector machine to locate the key long-range interaction sites by the use of predicted local lowest B-factors. As a result, the key long-range interaction residues can be located based on information of local lowest B-factor sites.

Biological processes are often performed by a group of proteins rather than by individual proteins, and proteins in a same biological group form a densely connected subgraph in a protein-protein interaction network. Therefore, finding a densely connected subgraph provides useful information to predict the function or protein complex of uncharacterized proteins in the highly connected subgraph. We have developed an efficient algorithm and program for finding cliques and near-cliques in a protein-protein interaction network. Analysis of the interaction network of yeast proteins using the algorithm demonstrates that 59% of the near-cliques identified by our algorithm have at least one function shared by all the proteins within a near-clique, and that 56% of the near-cliques show a good agreement with the experimentally determined protein complexes catalogued in MIPS.

Objective: To investigate the association of 86 bp variable number tandem repeat (VNTR) polymorphism of interleukin-1 receptor antagonist (IL-1Ra) gene with lumbar disc disease and intervertebral disc degeneration., Methods: The 86 bp VNTR polymorphism of IL-1Ra gene was analyzed with PCR and electrophoresis for 81 patients with lumbar disc disease and 101 volunteers without sciatica (control). The grade of intervertebral disc degeneration was determined with magnetic resonance imaging, and the association of 86 bp VNTR polymorphisms with lumbar disc disease and intervertebral disc degeneration in those younger than 45 years was assessed., Results: The presence of 86bp VNTR polymorphisms of IL-1Ra gene was detected in both patients with lumbar disc disease and the control subjects. The distribution of 86 bp VNTR polymorphisms of IL-1Ra gene showed no significant difference between the two groups, but the distributions of 1/1, 1/2 and 2/2 or 1, 2 genotypes differed significantly. The current data did not support a significant association between the distribution of IL-1Ra gene 86bp VNTR polymorphism and lumbar disc degeneration., Conclusions: IL-1Ra gene 86bp VNTR polymorphism is present among Chinese population in association with lumbar disc disease, but not with lumbar disc degeneration.

Aim: To determine the apoptotic effect of recombinant rat Fas Ligand on rat intervertebral disc cells pre-treated with IL-1beta in vitro, and the expression of Fas in cultured rat intervertebral disc cells., Methods: Cells were isolated from the inner annulus fibrosus and transition zones of lumbar discs from Sprague-Dawley rats. The cells were grown in monolayer and divided in 5 treatment groups. IL-1beta (10 ng/mL), FasL (5, 20 ng/mL) with/without IL-1beta (10 ng/mL) pre-treatment was respectively added in Dulbeccoos modified Eagleos medium and Hamos F-12 medium with 1% fetal bovine serum. After 32 h, the cells were stained with annexin V-FITC and propidium iodide to evaluate apoptosis using flow cytometry and to analysis transcription of Fas using RT-PCR., Results: Compared with control group, FasL (20 ng/mL), IL-1beta (10 ng/mL)+FasL (5 ng/mL), and IL-1beta (10 ng/mL)+FasL (20 ng/mL) induced significant apoptosis of the disc cells (P<0.01). Apoptosis was also induced by FasL 5 ng/mL (P<0.05); whereas, apoptosis was not induced by IL-1beta (10 ng/mL) (P>0.05). IL-1beta (10 ng/mL) enhanced the apoptosis-inducing effects of FasL (5 ng/mL) and FasL (20 ng/mL) in disc cells. Fas gene transcription in all groups and Fas expression in the 5 treatment groups were approximately 1.2-2.1-fold greater than control group (respectively, P<0.05). Additionally, Fas expression in FasL with IL-1beta pre-treatment groups were significantly up-regulated than in FasL groups (P<0.01)., Conclusion: The results of this study showed disc cells pre-treated with IL-1beta increased apoptotic rate in response to FasL in vitro and provided insights to understand Fas/FasL system-mediated apoptosis in disc cells which would be enhanced due to inflammation factor in degenerative disc.

In this letter, a standard postnonlinear blind source separation algorithm is proposed, based on the MISEP method, which is widely used in linear and nonlinear independent component analysis. To best suit a wide class of postnonlinear mixtures, we adapt the MISEP method to incorporate a priori information of the mixtures. In particular, a group of three-layered perceptrons and a linear network are used as the unmixing system to separate sources in the postnonlinear mixtures, and another group of three-layered perceptron is used as the auxiliary network. The learning algorithm for the unmixing system is then obtained by maximizing the output entropy of the auxiliary network. The proposed method is applied to postnonlinear blind source separation of both simulation signals and real speech signals, and the experimental results demonstrate its effectiveness and efficiency in comparison with existing methods.

This study was to explore the relationships between (-511)T>C and (+3954)C>T single nucleotide polymorphisms(SNP) in IL-1beta gene with lumbar intervertebral disc disease. We analyzed (-511)T>C and (+3954)C>T SNP in IL-1beta gene by the polymerase chain reaction-restriction fragment length polymorphism and electrophoresis methods respectively in 81 cases with lumbar disc disease and 101 healthy controls. The relationship between (-511)T>C and (+3954)C>T SNP in IL-1beta gene and lumbar disc disease in two groups was measured, so does the relationship between (-511)T>C and (+3954)C>T SNP in IL-1beta gene and intervertebral disc degeneration in those younger than 45-year-old. The results showed there were (-511)T>C and (+3954)C>T SNP in IL-1beta gene. There was a significant difference in the distribution of TT, TC and CC genotype or T, C genotype of (-511)T>C of IL-1beta in two groups. And there was no significant difference in the distribution of (+3954)C>T SNP in IL-1beta gene in two groups. There was no significant difference between the distribution of (-511)T>C and (+3954)C>T SNP in IL-1beta gene and intervertebral disc degeneration in those younger than 45-year-old. It suggested (-511)T>C SNP in IL-1beta gene be one of the susceptible alleles for Lumbar disc disease.

Objective: To evaluate the effect of interleukin-6 (IL-6) on the biological behaviors of the chondrocytes in the cartilage endplate of rabbits., Methods: Chondrocytes isolated from the cartilage endplate of New Zealand rabbits, verified for their biological characteristics by such means as toluidine blue staining for type II collagen, were treated with IL-6 at different concentrations. The proliferation of the chondrocytes was evaluated by MTT assay at different time points following the treatment, the cell cycle changes were determined by flow cytometry and the changes of aggrecan and type II collagen mRNAs detected by RT-PCR., Results: At the concentrations of 10, 50 and 100 ng/ml, IL-6 did not obviously affect the rate of chondrocyte proliferation. IL-6 at 50 ng/ml resulted in no obvious changes of the cell cycle of the chondrocytes, but significantly decreased the expression of collagen IIa mRNA., Conclusion: IL-6 has no effect on the proliferation and cell cycle of the chondrocytes, but at higher concentrations, it inhibits matrix synthesis of the chondrocytes to promote intervertebral disc degeneration.

Objective: To explore the polymorphisms of vitamin D receptor (VDR) gene Tru I polymorphisms and the influence of this variation on Bsm I polymorphisms in Han nationality., Methods: Venous blood samples from 80 healthy individuals of Han nationality were collected and genomic DNA was extracted, VDR Bsm I and Tru I were tested by polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) to analyze the polymorphisms of VDR gene; After using another primers to test VDR Bsm I in the same samples, the consistence of each method was assessed., Results: The frequencies of the VDR Tru I genotype in the groups were: TT 68.7%, Tt 26.3%, tt 5.0%; VDR Bsm I were: BB 6.2%, Bb 52.5%, bb 41.3%; Both polymorphisms were under Hardy-Weinberg equilibrium. After using another pair of primer, the frequencies of Bsm I genotype were BB 20.0%, Bb 26.2%, bb 53.8%, 22 genotype Bb changed to genotype BB or genotype bb in comparison with the result of first detection., Conclusion: The VDR Tru I polymorphism is found in the Han nationality, the distribution of this site's polymorphism is different from that of other nationalities. The presence of Tru I variation can result in some allele of Bsm I genotype drop-out in some study.

In this paper, we propose the adoption of the bounded support vector machine (BSVM) to predict the B-factors of residues based on a number of distinctive properties of residues. Due to the ability of multi-class classification of the BSVM, we can elaborately distinguish our targets and obtain relatively higher accuracy.

Objective: To investigate effects of glucose and free fatty acid at different concentrations on phosphorylation of adenosine-5'-monophosphate activated protein kinase(AMPK) and acetyl CoA carboxylase (ACC) in INS-1 cells, and effects of globular adiponectin on phosphorylation of AMPK and ACC., Methods: INS-1 cells were cultured and treated with 5 mmol/L glucose or 0.25 mmol/L free fatty acids, and time courses and dose responses of different dosages of glucose and fatty acid on phosphorylation of AMPK and ACC were measured. We measured the effects of the pharmacological AMPK activator AICAR (5-aminoimidazole-4-carboxamide-riboside) and globular adiponectin on phosphorylation of AMPK and ACC., Results: Glucose and fatty acid at different concentrations inhibited the phosphorylation of AMPK and ACC at the end of 60 min, but AICAR increased the phosphorylation of AMPK and ACC significantly, while 2.5 mg/L globular adiponectin increased the phosphorylation of AMPK and ACC by 23% (P<0.05) and 50% (P<0.05) respectively, at baseline. In the presence of 5 mmol/L glucose, globular adiponectin increased AMPK and ACC phosphorylation by 1.4-fold (P<0.05) and 3-fold (P<0.01), respectively. In the presence of 0.25 mmol/L free fatty acid, globular adiponectin increased AMPK and ACC phosphorylation 3-fold (P<0.05) and 5-fold (P<0.01) respectively., Conclusion: In cultured islet cells, glucose and free fatty acid at various concentrations inhibit the phosphorylation of AMPK and ACC, but AICAR and globular adiponectin 2.5 mg/L increase the phosphorylation level. This may constitute a mechanism to increase fatty acid oxidation and decrease triglyceride accumulation in islet beta-cells.

The aim of this study was to investigate the hypothesis that particle size and diet form may affect the growth of mast cells and histamine release from the small intestine of broiler chickens. A total of 288, day-old male broiler chicks were randomly allocated to 1 of 4 corn-soy diets in a 2 x 2 factorial design. The factors included particle size (coarse vs. fine) and physical form (mash vs. pellet). The birds were housed in 90 x 60 cm pens containing 12 birds, and each treatment contained 6 replicate pens of birds from d 1 to 22. On d 22, 6 broilers from each treatment were slaughtered. Tissues from the small intestine (duodenum, jejunum, and ileum) were obtained to quantify mast cells using the toluidine blue staining technique. The results showed that mast cells in the jejunum were concentrated in the upper part of the villus in birds fed the coarsely ground mash diet, whereas mast cells were evenly distributed throughout the intestine in birds fed the other 3 diets. The number of mast cells was significantly lower in the duodenum (P = 0.04), jejunum (P < 0.01), and ileum (P = 0.01) of birds fed coarsely ground diets compared with finely ground diets, and there was no difference in mast cell numbers between birds fed mashed or pelleted diets at any site in the intestine. The histamine content (P = 0.02) and stem cell factor concentration (P = 0.03) were markedly lower in the jejunum of birds that were fed coarsely ground diets compared with finely ground diets. The stem cell factor concentration in the duodenum (P < 0.01) and jejunum (P = 0.05) was higher in birds fed pelleted compared with mash diets. The overall results of this experiment suggest that particle size and diet form affect mast cell number and histamine content in the small intestine by regulation of stem cell factor concentration.

This paper proposes a novel hybrid forward algorithm (HFA) for the construction of radial basis function (RBF) neural networks with tunable nodes. The main objective is to efficiently and effectively produce a parsimonious RBF neural network that generalizes well. In this study, it is achieved through simultaneous network structure determination and parameter optimization on the continuous parameter space. This is a mixed integer hard problem and the proposed HFA tackles this problem using an integrated analytic framework, leading to significantly improved network performance and reduced memory usage for the network construction. The computational complexity analysis confirms the efficiency of the proposed algorithm, and the simulation results demonstrate its effectiveness.

Motivation: Microarrays are capable of determining the expression levels of thousands of genes simultaneously. One important application of gene expression data is classification of samples into categories. In combination with classification methods, this technology can be useful to support clinical management decisions for individual patients, e.g. in oncology. Standard statistic methodologies in classification or prediction do not work well when the number of variables p (genes) far too exceeds the number of samples n. So, modification of existing statistical methodologies or development of new methodologies is needed for the analysis of microarray data., Results: This paper proposes a new method for tumor classification using gene expression data. In this method, we first employ independent component analysis to model the gene expression data, then apply optimal scoring algorithm to classify them. Further speaking, this approach can first make full use of the high-order statistical information contained in the gene expression data. Second, this approach also employs regularized regression models to handle the situation of large numbers of correlated predictor variables. Finally, the predictive models are developed for classifying tumors based on the entire gene expression profile. To show the validity of the proposed method, we apply it to classify four DNA microarray datasets involving various human normal and tumor tissue samples. The experimental results show that the method is efficient and feasible., Availability: Matlab scripts are available on request.

Identifying protein-protein interfaces is crucial for structural biology. Because of the constraints in wet experiments, many computational methods have been proposed. Without knowing any information about the partner chains, a new method of predicting protein-protein interaction interface residues purely based on evolutionary information in heterocomplexes is proposed here. Unlike traditional approaches using multiple sequence alignment profiles to represent the conservation level for each residue, we make predictions based on the concept of residue conservation scores so that the dimension of the feature vector for each residue can be drastically reduced, at least 20 times less than conventional methods. Based on the representation approach, a simple linear discriminant function is used to make predictions, so the computational complexity of the whole prediction procedure can also be greatly decreased. By testing our approach on 69 heterocomplex chains, experimental results demonstrate the performance of our approach is indeed superior to current existing methods.

An in vitro experiment and an in vivo experiment were conducted to investigate the effects of feed particle size (coarse and fine) and feed form (mash and pellet) on the survival of Salmonella typhimurium (ST) in the alimentary tract, and the reduction of cecal ST in growing broilers in a 2 x 2 factorial design. All diets in the 2 trials were corn and soybean meal-based diets that differed only in physical characteristics. Diets were provided for birds from d 1 to 22 of age. In the in vitro trial, the relative gizzard weight was lower in birds that were fed the pellet diet (P < 0.01), whereas the relative weight of the cecum was higher in these birds (P < 0.01). Broilers receiving the pellet diet had enhanced concentrations of volatile fatty acids in contents from both the gizzards and the ceca. In addition, there was an increase in gizzard pH (P < 0.01) with the pellet diet, but a reduction in cecal pH (P < 0.05). Pellet-fed birds showed a significantly decreased and increased in vitro death rate of ST in the contents from gizzards (P < 0.01) and ceca (P < 0.05), respectively. A higher in vitro ST death rate in the gizzard was observed in birds given the coarse mash diet compared with those given the fine mash diet. In the in vivo experiment, cecal volatile fatty acid concentrations were increased, whereas cecal pH was decreased significantly (P < 0.05) when birds were fed the pellet diet compared with the mash diet. Furthermore, cecal ST concentrations were higher (P < 0.05) in broilers fed the pellet diet than in those fed the mash diet. Results indicated that the pellet diet increases the incidence of ST in gizzards and ceca in growing broilers and provide evidence demonstrating that the gizzard may play a critical role in reducing ST contamination in growing broilers.

Objective: Neuroblastoma is a highly malignant tumor. Stage IV neuroblastoma has a very poor long-term outcome by conventional chemotherapy and surgery and better therapies are essential. This study aimed to explore the long-term effect of high dose induction chemotherapy combined with autologous peripheral blood stem cell transplantation and 13-cis retinoid acid treatment on stage IV neuroblastoma in children., Methods: Twenty-eight children with stage IV neuroblastoma, aged 2.1-11.5 years (mean 3.3 +/- 1.9 years), were employed for the study. Primary sites of the tumors included adrenal (n=23), chest (n=3), chest-abdomen (n=1) and sacrum (n=1). Before autologous peripheral blood stem cell transplantation the patients received 6 courses of intensive induction chemotherapy. During chemotherapy the autologous peripheral blood stem cells were harvested and the tumor excision was done. After transplantation the local radiation and 13-cis retinoid acid therapy were administered., Results: After 6 courses of induction chemotherapy 13 patients got complete remission (CR), 11 got partial remission (PR), and 4 had no response. The 24 patients who received CR or PR completed the full therapy. A 3.5 +/- 0.7 years follow-up showed that the 4-year event-free survival of the CR and PR patients was 29.2%. The median no-relapse survival time in CR patients was 4.1 +/- 0.7 years but 2.8 +/- 0.5 years in PR patients (t= 3.9, P < 0.01)., Conclusions: High dose chemotherapy combined with autologous peripheral stem cell transplantation and 13 cis-retinoid acid treatment can improve the long-term outcome of patients with stage IV neuroblastoma. The patients in CR before transplantation had better outcomes than those in PR.

Objective: To introduce the METRx microendoscopes diskectomy system in the treatment of far lateral lumbar disc herniation., Methods: Fourteen cases of far lateral lumbar disc herniation were operated with METRx from February 1999 to December 2002. Among them, the average age was 49 years old (range 41 - 55 years old), male in 10 cases, female in 4 cases. All cases were single disc herniation; L(4), 5 herniation in 6 discs, L(5)-S(1) herniation in 8 discs; foraminal disc herniation in 6 cases, extra-foraminal disc herniation in 8 cases., Results: All the cases were followed up from 12 to 46 months (average 26.5 months) with the results of excellence in 10 cases, good in 3 cases, fair in 1 case and no failure case. There were no disc infection, dura laceration, nerve root injury and herniation recurrence., Conclusions: METRx is suitable for far lateral lumbar disc herniation with the advantages of minimal invasive, complete decompression of nerve root and rapid recovery. The correct approach and precise surgical technique are the key points for this operation.

Objective: To analyze the risk factors of heterotopic (HO) ossification after total lumbar disc replacement and probe the preventive strategies for it., Methods: The radiographs and clinical data of 78 discs in 65 patients who received artificial lumbar disc replacement (ADR) from April 1998 to December 2003 were analyzed retrospectively by two radiologists and one orthopaedic surgeon and then postoperative HO were graded according to McAfee system. The bony formations in disc spaces, time of HO were found, and range of motion (ROM) of the operated levels were measured on radiographic films. In addition, the risk factors such as preoperative peri-annulus ossification, bony endplates injuries, and subsided or mal-position of the prostheses were also analyzed by Logistic regression analysis., Results: Postoperative HO was found in 10 spaces of 9 cases. Class I of HO were occurred in 7 patients at means 2.1 years postoperatively with normal range of motion preserved. Three of them turned into class II or III with 10 degrees of mean ROM in the following 2.5 years. Another 2 (2/9) cases with preoperative peri-annulus ossification had bridging trabecular bone (class III) between the endplates and 9 degrees of ROM 2 years after surgery, then turned into class IV at 6 years with 0 degrees and 4 degrees of motion in the operated levels. As the risk factors of HO, preoperative annulus ossification (2 cases), bony endplates injuries (5 cases), mal-positioned prostheses (2 cases) and subsided prostheses (2 cases) were found simultaneity with significant positive relation to HO occurred (P < 0.05)., Conclusions: Factors such as preoperative ossification of annulus, endplate injuries, prosthesis subsided and mal-position would have higher risks to have HO occurred after ADR, but ROM of most affected levels are preserved. Strict control indication and avoid all above risk factors can prevent HO occurring effectively.

In this paper, a new effective model is proposed to forecast how long the postoperative patients suffered from non-small cell lung cancer will survive. The new effective model which is based on the extreme learning machine (ELM) and principal component analysis (PCA) can forecast successfully the postoperative patients' survival time. The new model obtains better prediction accuracy and faster convergence rate which the model using backpropagation (BP) algorithm and the Levenberg-Marquardt (LM) algorithm to forecast the postoperative patients' survival time can not achieve. Finally, simulation results are given to verify the efficiency and effectiveness of our proposed new model.

This paper proposes a novel method that can predict protein interaction sites in heterocomplexes using residue spatial sequence profile and evolution rate approaches. The former represents the information of multiple sequence alignments while the latter corresponds to a residue's evolutionary conservation score based on a phylogenetic tree. Three predictors using a support vector machines algorithm are constructed to predict whether a surface residue is a part of a protein-protein interface. The efficiency and the effectiveness of our proposed approach is verified by its better prediction performance compared with other models. The study is based on a non-redundant data set of heterodimers consisting of 69 protein chains.

In this paper(1) we present a novel framework for protein secondary structure prediction. In this prediction framework, firstly we propose a novel parameterized semi-probability profile, which combines single sequence with evolutionary information effectively. Secondly, different semi-probability profiles are respectively applied as network input to predict protein secondary structure. Then a comparison among these different predictions is discussed in this article. Finally, naïve Bayes approaches are used to combine these predictions in order to obtain a better prediction performance than individual prediction. The experimental results show that our proposed framework can indeed improve the prediction accuracy.

This paper proposes a novel method using protein residue conservation and evolution information, i.e., spatial sequence profile, sequence information entropy and evolution rate, to infer protein binding sites. Some predictors based on support vector machines (SVMs) algorithm are constructed to predict the role of surface residues in protein-protein interface. By combining protein residue characters, the prediction performance can be improved obviously. We then made use of the predicted labels of neighbor residues to improve the performance of the predictors. The efficiency and the effectiveness of our proposed approach are verified by its better prediction performance based on a non-redundant data set of heterodimers.

In this paper, the tertiary structures of protein chains of heterocomplexes were mapped to 2D networks; based on the mapping approach, statistical properties of these networks were systematically studied. Firstly, our experimental results confirmed that the networks derived from protein structures possess small-world properties. Secondly, an interesting relationship between network average degree and the network size was discovered, which was quantified as an empirical function enabling us to estimate the number of residue contacts of the protein chains accurately. Thirdly, by analyzing the average clustering coefficient for nodes having the same degree in the network, it was found that the architectures of the networks and protein structures analyzed are hierarchically organized. Finally, network motifs were detected in the networks which are believed to determine the family or superfamily the networks belong to. The study of protein structures with the new perspective might shed some light on understanding the underlying laws of evolution, function and structures of proteins, and therefore would be complementary to other currently existing methods.

Objective: To study the effect and implication of nonmyeloablative donor specific bone marrow (DSBM) infusion on the immunoreaction of liver allotransplantation., Methods: Orthotopic liver transplantation model was used in this study. Groups were set as follows: Group I, syngeneic control (Wistar-to-Wistar); Group II, acute rejection (SD-to-Wistar); Group III, acute rejection treated with cyclosporine A (CsA) by intramuscular injection (SD-to-Wistar+CsA); Group IV, bone marrow infusion at 7 d pretransplantation followed by short-term CsA treatment (SD-to-Wistar+DSBM); Another group of short-term CsA treatment preoperatively without bone marrow infusion was also set as control. General characteristics and survival time were observed. Histological grades of rejection were determined by pathological examination. IL-2 and IFN-gamma level in peripheral blood and donor liver were detected respectively by Enzyme-Linked Immuno-Sorbent Assay (ELISA) and Western blot. Chimerism of donor cells was measured by PCR for a male-specific marker (Y-chromosome-specific sequence, Sry)., Results: No signs of rejection were found in Group I. Acute rejection occurred in both Group II and the short-term CsA treated group. All the recipients died at (9-15) d posttransplantation with a median survival time of (10.7+/-0.5) d and (11.2+/-2.4) d, respectively. Only mild rejection could be seen in Group III. In Group IV, 4 out of 6 recipients had long-term survival (>100 d), the histological grade of rejection was significantly lower than that of Group II, so did the expression level of IL-2 and IFN-gamma in both peripheral blood and grafted liver. Y-chromosome-specific sequence (Sry) of male SD rats could be detected in the bone marrow, spleen and thymus of female recipients at 15 d after bone marrow infusion., Conclusion: Mild preconditioning nonmyeloablative donor specific bone marrow infusion can enhance chimerism formation in recipients, alleviate the rejection of liver allotransplantation and prolong survival of liver allotransplantation.

Support vector machines (SVMs) have been extensively used. However, it is known that SVMs face difficulty in solving large complex problems due to the intensive computation involved in their training algorithms, which are at least quadratic with respect to the number of training examples. This paper proposes a new, simple, and efficient network architecture which consists of several SVMs each trained on a small subregion of the whole data sampling space and the same number of simple neural quantizer modules which inhibit the outputs of all the remote SVMs and only allow a single local SVM to fire (produce actual output) at any time. In principle, this region-computing based modular network method can significantly reduce the learning time of SVM algorithms without sacrificing much generalization performance. The experiments on a few real large complex benchmark problems demonstrate that our method can be significantly faster than single SVMs without losing much generalization performance.

In this paper we propose constructing an improved two-level neural network to predict protein secondary structure. Firstly, we code the whole protein composition information as the inputs to the first-level network besides the evolutionary information. Secondly, we calculate the reliability score for each residue position based on the output of the first-level network, and the role of the second-level network is to take full advantage of the residues with a higher reliability score to impact the neighboring residues with a lower one for improving the whole prediction accuracy. Thirdly, considering it is indeed a problem that the target protein can be lost in the multiple sequence alignment we propose to code single sequence into the second-level network. The experimental results show that our proposed method can efficiently improve the prediction accuracy.

This paper presents a novel approach to extracting features from motif content and protein composition for protein sequence classification. First, we formulate a protein sequence as a fixed-dimensional vector using the motif content and protein composition. Then, we further project the vectors into a low-dimensional space by the Principal Component Analysis (PCA) so that they can be represented by a combination of the eigenvectors of the covariance matrix of these vectors. Subsequently, the Genetic Algorithm (GA) is used to extract a subset of biological and functional sequence features from the eigen-space and to optimize the regularization parameter of the Support Vector Machine (SVM) simultaneously. Finally, we utilize the SVM classifiers to classify protein sequences into corresponding families based on the selected feature subsets. In comparison with the existing PSI-BLAST and SVM-pairwise methods, the experiments show the promising results of our approach.

The Smith-Waterman (SW) algorithm is a typical technique for local sequence alignment in computational biology. However, the SW algorithm does not consider the local behaviours of the amino acids, which may result in loss of some useful information. Inspired by the success of Markov Edit Distance (MED) method, this paper therefore proposes a novel Markov pairwise protein sequence alignment (MPPSA) method that takes the local context dependencies into consideration. The numerical results have shown its superiority to the SW for pairwise protein sequence comparison.

This paper proposes a modified radial basis function classification algorithm for non-linear cancer classification. In the algorithm, a modified simulated annealing method is developed and combined with the linear least square and gradient paradigms to optimize the structure of the radial basis function (RBF) classifier. The proposed algorithm can be adopted to perform non-linear cancer classification based on gene expression profiles and applied to two microarray data sets involving various human tumor classes: (1) Normal versus colon tumor; (2) acute myeloid leukemia (AML) versus acute lymphoblastic leukemia (ALL). Finally, accuracy and stability for the proposed algorithm are further demonstrated by comparing with the other cancer classification algorithms.

Objective: To investigate the effects of the selective cyclooxygenase-2 (COX-2) inhibitor NS398 on the growth of human pancreatic tumor BxPC-3 cell strain and its possible mechanisms., Methods: The effect of NS398 on cell growth was assessed by 3- (4,5-dimethylthiazol-2-yl) -2, 5-diphenyl thiazolyl blue (MTT) assay. Apoptosis was determined by fluorescence-activated cell scanning (FACS) analysis and assessment of the floating cell/attached cell ratio. Caspase-3 activation was evaluated by Active Caspase-3 Apoptosis Kit with flow cytometry. Reverse transcriptase-polymerase chain reaction analysis (RT-PCR) and Western blot were used to demonstrate expression levels of COX-1, COX-2 mRNA, and protein, as well as Caspase-3 protein in pancreatic tumor BxPC-3 cell strain., Results: Selective COX-2 inhibitor NS398 significantly decreased cell viability and induced apoptosis in pancreatic tumor BxPC-3 cell strain. The protein expression of Caspase-3 was induced by high-concentration NS398. Caspase-3 activity was strongly activated by NS398., Conclusions: Selective COX-2 inhibitor NS398 has antiproliferative and proapoptotic potential in pancreatic tumor BxPC-3 cells. Such effect is independent of COX-2, but correlates with Caspase-3 activation.

Objective: Extrahepatic bile duct carcinoma is a rare but dismal malignacy. This study is conducted to show retrospective review and analysis of the correlation between the prognosis and different treatment modalities., Methods: The data of 84 such patients treated by different modalities from January, 1992 to July, 2000 were retrospectively reviewed and analyzed using SPSS 10.0 statistical package. The survivals were estimated by the Kaplan-Meier method and the difference among groups was tested by the log-rank test. The prognostic factors were determined by Cox multivariate analysis., Results: Of the 84 patients, 33 had complete resection, 19 palliative resection, 12 exploration alone, and the remaining 20 were treated by chemotherapy and/or radiotherapy. The mean follow-up time was 592 days. The overall 5-year survival rate was 13.1%. The 1-, 3- and 5-year survival rate following complete resection was 76.8%, 52.6% and 30.5% respectively, which was significantly higher than those of palliative surgery or chemotherapy/radiotherapy (P < 0.01). Multivariate analysis revealed that lymph node status (P = 0), histopathological grade (P = 0.001) and distant metastasis (P = 0.002) were significant high risk factors., Conclusion: The prognosis of extrahepatic bile duct carcinoma remains poor even after complete resection as shown to have a 5-year survival of 30.5%. More effective adjuvant therapy is needed. Extended resection may be helpful in improving the prognosis for carefully selected patients. Early diagnosis and early treatment is still the key to improve the long-term survival of extrahepatic bile duct carcinoma.

With increasingly sophisticated laser applications in industry and science, a reliable method to characterize the intensity distribution of the laser beam has become a more and more important task. However, traditional optic and electronic methods can offer only a laser beam intensity profile but, cannot separate the main mode components in the laser beam intensity distribution. Recently, independent component analysis has been a surging and developing method in which the goal is to find a linear representation of a non-Gaussian data set. Such a linear representation seems to be able to capture the essential structure of a laser beam profile. After assembling image data of a laser spot, we propose a new analytical approach to extract laser beam mode components based on the independent component analysis technique. For noise reduction and laser spot area location, wavelet thresholding, Canny edge detection, and the Hough transform are also used in this method before extracting mode components. Finally, the experimental results show that our approach can separate the principal mode components in a real laser beam efficiently.

The objective of this study was to develop quantitative structure-activity relationships (QSARs) for the toxicity of mono-cyclic aromatic compounds in the Pseudomonas putida initial oxygen uptake assay. The QSARs were developed using response-surface based on descriptors for chemical hydrophobicity (logP) and electrophilicity (LUMO). The model log (Ki(-1)=0.434 (+/-0.011) log P-0.389 (+/-0.013) LUMO - 2.13(+/-0.031); n=155, r2=0.941, r2(adj)=0.940, s=0.119, F=1206 led us to conclude that the polar and non-polar narcotics were statistically indistinguishable. Pentafluorophenol, pentachlorophenol and most dinitrophenols classified as weak acid respiratory uncouplers in literature fit well into this model when they were treated as their corresponding phenoxides. This latter result suggests that the action mechanism of these phenols should be reevaluated.

This paper proposes new modified constrained learning neural root finders (NRFs) of polynomial constructed by backpropagation network (BPN). The technique is based on the relationships between the roots and the coefficients of polynomial as well as between the root moments and the coefficients of the polynomial. We investigated different resulting constrained learning algorithms (CLAs) based on the variants of the error cost functions (ECFs) in the constrained BPN and derived a new modified CLA (MCLA), and found that the computational complexities of the CLA and the MCLA based on the root-moment method (RMM) are the order of polynomial, and that the MCLA is simpler than the CLA. Further, we also discussed the effects of the different parameters with the CLA and the MCLA on the NRFs. In particular, considering the coefficients of the polynomials involved in practice to possibly be perturbed by noisy sources, thus, we also evaluated and discussed the effects of noises on the two NRFs. Finally, to demonstrate the advantage of our neural approaches over the nonneural ones, a series of simulating experiments are conducted.

A novel hybrid genetic algorithm (GA)/radial basis function neural network (RBFNN) technique, which selects features from the protein sequences and trains the RBF neural network simultaneously, is proposed in this paper. Experimental results show that the proposed hybrid GA/RBFNN system outperforms the BLAST and the HMMer.

Objective: To probe the accuracy and safety of using an aiming device in the transpedicular fixation of cervical spine., Methods: Eight cervical specimens were obtained. We used the computed tomography (CT) to scan C3 to C7, measured the medial angle of the pedicle, and determined the location of the pedicle projecting on the articular process. Then we took the oblique X-ray film, measured the cephalic/caudal angle of the pedicle, and determined the location of the pedicle projecting on the articular process. All the specimens were equally divided into two groups. Screws of 2.8 mm x 30 mm, were used. Specimens in one group were inserted with the transpedicular screw manually, while specimens in the other one inserted with the transpedicular screw using a self-designed aiming device that can be modulate at the three dimensions according to the angles of the pedicles., Results: The first group totally had 40 screws from C3 to C7. There were 13 screws in the pedicle, 9 violated the walls of the pedicle but not involved the adjunct structure, and 18 injured the important structure such as spinal cord, verteberal artery, or nerve root. In the other group, only 4 screws violated the walls of the pedicle but not involved the adjunct structure, and the others all in the pedicles. The difference was of statistical significance (P < 0.01)., Conclusion: In the cervical spine, transpedicular fixation using an aiming device can improve the accuracy and safety during operation.

A novel gene selection algorithm based on the gene regulation probability is proposed. In this algorithm, a probabilistic model is established to estimate gene regulation probabilities using the maximum likelihood estimation method and then these probabilities are used to select key genes related by class distinction. The application on the leukemia data-set suggests that the defined gene regulation probability can identify the key genes to the acute lymphoblastic leukemia (ALL)/acute myeloid leukemia (AML) class distinction and the result of our proposed algorithm is competitive to those of the previous algorithms.

We propose a new, to our knowledge, denoising method for lidar signals based on a regression model and a wavelet neural network (WNN) that permits the regression model not only to have a good wavelet approximation property but also to make a neural network that has a self-learning and adaptive capability for increasing the quality of lidar signals. Specifically, we investigate the performance of the WNN for antinoise approximation of lidar signals by simultaneously addressing simulated and real lidar signals. To clarify the antinoise approximation capability of the WNN for lidar signals, we calculate the atmosphere temperature profile with the real signal processed by the WNN. To show the contrast, we also demonstrate the results of the Monte Carlo moving average method and the finite impulse response filter. Finally, the experimental results show that our proposed approach is significantly superior to the traditional methods.

A methodology is presented for assessing the toxicity of chemical substances through their inhibitory action toward the Pseudomonas initial oxygen uptake (PIOU) rate. The current studies reveal that the PIOU assay is rapid, cost-efficient, and easy to perform. The oxygen uptake rate was found to be associated with a putative benzoate transporter and highly dependent on benzoate concentration. The putative benzoate transporter has been shown to follow Michaelis-Menten kinetics. Most phenols were found to be noncompetitive inhibitors of the benzoate transporter. The inhibition constant (Ki) of these noncompetitive inhibitors can be related to the concentration causing 50% oxygen uptake inhibition in Pseudomonas putida. Modeling these data by using the response-surface approach leads to the development of a quantitative structure-activity relationship (QSAR) for the toxicity of phenols ((1/Ki) = -0.435 (+/-0.038) lowest-unoccupied-molecular orbital + 0.517 (+/-0.027)log K(OW) - 2.340 (+/-0.068), n = 49, r2 = 0.930, s = 0.107, r2adj = 0.926, F = 303.1). A comparison of QSAR models derived from the Ki data of the PIOU method and the toxicity data of 40-h Tetrahymena pyrifomis growth inhibition assay (Tetratox) indicated that there was a high correlation between the two approaches (r2 = 0.925).

Aim: To evaluate the effects of NS-398, a cyclooxygenase-2 (COX-2) inhibitor, on the proliferation and apoptosis of HepG2 cells., Methods: The effects of NS-398 on the proliferation of HepG2 cells were evaluated by MTT. DNA fragmentation gel analysis was used to analyze the apoptotic cells. DNA ploidy and apoptotic cell percentage were calculated by flow cytometry. The expression of COX-2 and Bcl-2 mRNA was identified by competitive RT-PCR. Furthermore, expression level of Bcl-2 was detected using Western blot in HepG2 after treated with NS-398., Results: NS-398 inhibited cell proliferation and induced apoptosis of HepG2 cells in a concentration-dependent manner. DNA ploidy analysis showed that S phase cells were significantly decreased with increase of NS-398 concentration. The quiescent G0/G1 phase was accumulated with decrease of Bcl-2 mRNA. Whereas NS-398 had no effect on the expression of COX-2 mRNA, and no correlations were found between COX-2 mRNA and HepG2 cell proliferation and apoptosis induced by NS-398 (r = 0.056 and r = 0.119, respectively). Bcl-2 protein level was inhibited after treated with NS-398., Conclusion: NS-398 significantly inhibits the proliferation and induces apoptosis of HepG2 cells. Mechanisms involved may be accumulation of quiescent G0/G1 phase and decrease of Bcl-2 expression.

Objective: To investigate the role of artificial disc replacement (ADR) in restoring lumbar segment motion and intervertebral height (IH)., Methods: Seventy-five patients with intervertebral disc diseases underwent artificial disc replacement and were divided into 3 groups to be followed up for 2 years (group A, n = 32), 3 years (group B, n = 27), and 5 years (group C, n = 19) respectively. Before the operation and during the follow-up the range of motion (ROM) of the involved lumbar segments and IH were assessed., Results: The mean ROM and IH of the group A were 15 degrees and 14.1 mm respectively during the follow-up 2 years after operation. The mean ROM and IH of the group B were 14.2 degrees and 13.8 mm respectively during the follow-up 2 years after the operation and 13.7 degrees and 13.4 mm respectively during the follow-up 3 years after operation. The mean ROM and IH of the group C were 9.1 degrees and 11.5 mm respectively during the follow-up 2 years after the operation and 8.8 degrees and 11.0 mm respectively during the follow-up 3 years after operation, and 8.0 degrees and 10.3 mm respectively during the follow-up 5 years after operation. No significant differences in ROM and IH were found among different groups at any time point (all P > 0.05). Malposition was found in immediately after operation in 11 patients, all of the group C. During the follow-up, 3 cases of prostheses subsidence and 3 cases of annular ossification were found. No severe complications appeared., Conclusion: ADR is effective in restoring the ROM and IH of vertebrae suffering from intervertebral disc diseases.

Objective: To study vertebral body stress distribution of normal disc, post-Diskectomy and artificial disk respectively by 3-D finite element methods, and to explore artificial intervertebral disk insertion impact on stress distribution of vertebral body., Methods: Models of normal disk, post-Diskectomy, artificial disk and L(4 - 5) motion segment were established by using finite element software MSC. MARK, then vertebral body stress was analyzed through model of L(4 - 5) motion segment respectively., Results: The vertebral body's stress was the smallest after insertion of artificial intervertebral disk (AID), and its stress distributed equally. But the stress under post-discectomy was bigger than the normal disc's in all the motion state. On the other hand, the stress distribution state of the post-discectomy changed while the spine were in different motion state, during the spine flexion, the stress in the anterior of vertebral body was the biggest; While extension, in the posterior and in right flexion state, the biggest stress was in the right. While vertical compression and rotation, the stress distributed equally., Conclusion: The results illustrate that the vertebral body's stress is the smallest after insertion of AID in 3 groups of all motion state, and its stress distributes equally. But the level of vertebral body stress increases after discectomy comparing with the normal group. In generally, it is much more reasonable that the disc is reconstructed with AID because of the biomechanical effect on vertebral body made by AID insertion.

Aim: To study the application of artificial neural network (ANN) in forecasting the incidence of hepatitis A, which had an autoregression phenomenon., Methods: The data of the incidence of hepatitis A in Liaoning Province from 1981 to 2001 were obtained from Liaoning Disease Control and Prevention Center. We used the autoregressive integrated moving average (ARIMA) model of time series analysis to determine whether there was any autoregression phenomenon in the data. Then the data of the incidence were switched into [0,1] intervals as the network theoretical output. The data from 1981 to 1997 were used as the training and verifying sets and the data from 1998 to 2001 were made up into the test set. STATISTICA neural network (ST NN) was used to construct, train and simulate the artificial neural network., Results: Twenty-four networks were tested and seven were retained. The best network we found had excellent performance, its regression ratio was 0.73, and its correlation was 0.69. There were 2 input variables in the network, one was AR(1), and the other was time. The number of units in hidden layer was 3. In ARIMA time series analysis results, the best model was first order autoregression without difference and smoothness. The total sum square error of the ANN model was 9 090.21, the sum square error of the training set and testing set was 8 377.52 and 712.69, respectively, they were all less than that of ARIMA model. The corresponding value of ARIMA was 12 291.79, 8 944.95 and 3 346.84, respectively. The correlation coefficient of nonlinear regression (R(NL)) of ANN was 0.71, while the R(NL) of ARIMA linear autoregression model was 0.66., Conclusion: ANN is superior to conventional methods in forecasting the incidence of hepatitis A which has an autoregression phenomenon.

The spatial ordering information of amino acid residue in protein primary sequence is an important determinant of protein three-dimensional structure. In this paper, we describe a radial basis function neural network (RBFNN), whose hidden centers and basis function widths are optimized by a genetic algorithm (GA), for the purpose of predicting three dimensional spatial distance location from primary sequence information. Experimental evidence on soybean protein sequences indicates the utility of this approach.

Inter-residue contacts map prediction is one of the most important intermediate steps to the protein folding problem. In this paper, we focus on the problem of protein inter-residue contacts map prediction based on neural network technique. Firstly, we use a genetic algorithm (GA) to optimize the radial basis function widths and hidden centers of a radial basis function neural network (RBFNN), then a novel binary encoding scheme is employed to train the network for the purpose of learning and predicting the inter-residue contacts patterns of protein sequences got from the protein data bank (PDB). The experimental evidence indicates the utility of our proposed encoding strategy and GA optimized RBFNN. Moreover, the simulation results demonstrate that the network got a better performance for these proteins, whose residue length falls into the area of (100, 300), and the predicted accuracy with a contact threshold of 7 Angstroms scores higher than the other 3 values with 5, 6, and 8 Angstroms.