A gray-box neural network-based model identification and fault estimation scheme for nonlinear dynamic systems

A novel gray-box neural network model (GBNNM), including multi-layer perception (MLP) neural network (NN) and integrators, is proposed for a model identification and fault estimation (MIFE) scheme. With the GBNNM, both the nonlinearity and dynamics of a class of nonlinear dynamic systems can be approximated. Unlike previous NN-based model identification methods, the GBNNM directly inherits system dynamics and separately models system nonlinearities. This model corresponds well with the object system and is easy to build. The GBNNM is embedded online as a normal model reference to obtain the quantitative residual between the object system output and the GBNNM output. This residual can accurately indicate the fault offset value, so it is suitable for differing fault severities. To further estimate the fault parameters (FPs), an improved extended state observer (ESO) using the same NNs (IESONN) from the GBNNM is proposed to avoid requiring the knowledge of ESO nonlinearity. Then, the proposed MIFE scheme is applied for reaction wheels (RW) in a satellite attitude control system (SACS). The scheme using the GBNNM is compared with other NNs in the same fault scenario, and several partial loss of effect (LOE) faults with different severities are considered to validate the effectiveness of the FP estimation and its superiority.

Partial epilepsy syndrome in a Gypsy family linked to 5q31.3-q32

PURPOSE The restricted genetic diversity and homogeneous molecular basis of Mendelian disorders in isolated founder populations have rarely been explored in epilepsy research. Our long-term goal is to explore the genetic basis of epilepsies in one such population, the Gypsies. The aim of this report is the clinical and genetic characterization of a Gypsy family with a partial epilepsy syndrome. METHODS Clinical information was collected using semistructured interviews with affected subjects and informants. At least one interictal electroencephalography (EEG) recording was performed for each patient and previous data obtained from records. Neuroimaging included structural magnetic resonance imaging (MRI). Linkage and haplotype analysis was performed using the Illumina IVb Linkage Panel, supplemented with highly informative microsatellites in linked regions and Affymetrix SNP 5.0 array data. RESULTS We observed an early-onset partial epilepsy syndrome with seizure semiology strongly suggestive of temporal lobe epilepsy (TLE), with mild intellectual deficit co-occurring in a large proportion of the patients. Psychiatric morbidity was common in the extended pedigree but did not cosegregate with epilepsy. Linkage analysis definitively excluded previously reported loci, and identified a novel locus on 5q31.3-q32 with an logarithm of the odds (LOD) score of 3 corresponding to the expected maximum in this family. DISCUSSION The syndrome can be classified as familial temporal lobe epilepsy (FTLE) or possibly a new syndrome with mild intellectual deficit. The linked 5q region does not contain any ion channel-encoding genes and is thus likely to contribute new knowledge about epilepsy pathogenesis. Identification of the mutation in this family and in additional patients will define the full phenotypic spectrum.

Identification of viral and non-viral reverse transcribing elements in pineapple ( Ananas comosus ), including members of two new badnavirus species

A previously published partial sequence of pineapple bacilliform virus was shown to be from a retrotransposon (family Metaviridae) and not from a badnavirus as previously thought. Two newly discovered sequence groups isolated from pineapple were associated with bacilliform virions and were transmitted by mealybugs. Phylogenetic analyses indicated that they were members of new badnavirus species. A third caulimovirid sequence was also amplified from pineapple, but available evidence suggests that this DNA is not encapsidated, but more likely derived from an endogenous virus.

Identification of two distinct bovine parainfluenza virus type 3 genotypes

The partial gene sequencing of the matrix (M) protein from seven clinical isolates of bovine parainfluenza virus type 3 (BPIV-3), and the complete sequencing of a representative isolate (Q5592) was completed in this study. Nucleotide sequence analysis was initiated because of the failure of in-house BPIV-3 RT-PCR methods to yield expected products for four of the isolates. Phylogenetic reconstructions based on the nucleotide sequences for the M-protein and the entire genome, using all of the available BPIV-3 nucleotide sequences, demonstrated that there were two distinct BPIV-3 genotypes (BPIV-3a and BPIV-3b). These newly identified genotypes have implications for the development of BPIV-3 molecular detection methods and may also impact on BPIV-3 vaccine formulations.

Identification of a new Polerovirus (family Luteoviridae) associated with cotton bunchy top disease in Australia

Cotton bunchy top (CBT) disease has caused significant yield losses in Australia and is now managed by control of its vector, the cotton aphid (Aphis gossypii). Its mode of transmission and similarities in symptoms to cotton Blue Disease suggested it may also be caused by a luteovirus or related virus. Degenerate primers to conserved regions of the genomes of the family Luteoviridae were used to amplify viral cDNAs from CBT-affected cotton leaf tissue that were not present in healthy plants. Partial genome sequence of a new virus (Cotton bunchy top virus, CBTV) was obtained spanning part of the RNA-dependent-RNA-polymerase (RdRP), all of the coat protein and part of the aphid-transmission protein. CBTV sequences could be detected in viruliferous aphids able to transmit CBT, but not aphids from non-symptomatic plants, indicating that it is associated with the disease and may be the causal agent. All CBTV open-reading frames had their closest similarity to viruses of the genus Polerovirus. The partial RdRP had 90 % amino acid identity to the RdRP of Cotton leafroll dwarf virus (CLRDV) that causes cotton blue disease, while other parts of the genome were more similar to other poleroviruses. The sequence similarity and genome organization of CBTV suggest that it should be considered a new member of the genus Polerovirus. This partial genome sequence of CBTV opens up the possibility for developing diagnostic tests for detection of the virus in cotton plants, aphids and weeds as well as alternative strategies for engineering CBT resistance in cotton plants through biotechnology. © 2012 Australasian Plant Pathology Society Inc.

Modern techniques in detection, identification and quantification of bacteria and peptides from foods

Standards have been placed to regulate the microbial and preservative contents to assure that foods are safe to the consumer. In a case of a food-related disease outbreak, it is crucial to be able to detect and identify quickly and accurately the cause of the disease. In addition, for every day control of food microbial and preservative contents, the detection methods must be easily performed for numerous food samples. In this present study, quicker alternative methods were studied for identification of bacteria by DNA fingerprinting. A flow cytometry method was developed as an alternative to pulsed-field gel electrophoresis, the golden method . DNA fragment sizing by an ultrasensitive flow cytometer was able to discriminate species and strains in a reproducible and comparable manner to pulsed-field gel electrophoresis. This new method was hundreds times faster and 200,000 times more sensitive. Additionally, another DNA fingerprinting identification method was developed based on single-enzyme amplified fragment length polymorphism (SE-AFLP). This method allowed the differentiation of genera, species, and strains of pathogenic bacteria of Bacilli, Staphylococci, Yersinia, and Escherichia coli. These fingerprinting patterns obtained by SE-AFLP were simpler and easier to analyze than those by the traditional amplified fragment length polymorphism by double enzyme digestion. Nisin (E234) is added as a preservative to different types of foods, especially dairy products, around the world. Various detection methods exist for nisin, but they lack in sensitivity, speed or specificity. In this present study, a sensitive nisin-induced green fluorescent protein (GFPuv) bioassay was developed using the Lactococcus lactis two-component signal system NisRK and the nisin-inducible nisA promoter. The bioassay was extremely sensitive with detection limit of 10 pg/ml in culture supernatant. In addition, it was compatible for quantification from various food matrices, such as milk, salad dressings, processed cheese, liquid eggs, and canned tomatoes. Wine has good antimicrobial properties due to its alcohol concentration, low pH, and organic content and therefore often assumed to be microbially safe to consume. Another aim of this thesis was to study the microbiota of wines returned by customers complaining of food-poisoning symptoms. By partial 16S rRNA gene sequence analysis, ribotyping, and boar spermatozoa motility assay, it was identified that one of the wines contained a Bacillus simplex BAC91, which produced a heat-stable substance toxic to the mitochondria of sperm cells. The antibacterial activity of wine was tested on the vegetative cells and spores of B. simplex BAC91, B. cereus type strain ATCC 14579 and cereulide-producing B. cereus F4810/72. Although the vegetative cells and spores of B. simplex BAC91 were sensitive to the antimicrobial effects of wine, the spores of B. cereus strains ATCC 14579 and F4810/72 stayed viable for at least 4 months. According to these results, Bacillus spp., more specifically spores, can be a possible risk to the wine consumer.

Self-regularized pseudo time-marching schemes for structural system identification with static measurements

We explore the application of pseudo time marching schemes, involving either deterministic integration or stochastic filtering, to solve the inverse problem of parameter identification of large dimensional structural systems from partial and noisy measurements of strictly static response. Solutions of such non-linear inverse problems could provide useful local stiffness variations and do not have to confront modeling uncertainties in damping, an important, yet inadequately understood, aspect in dynamic system identification problems. The usual method of least-square solution is through a regularized Gauss-Newton method (GNM) whose results are known to be sensitively dependent on the regularization parameter and data noise intensity. Finite time,recursive integration of the pseudo-dynamical GNM (PD-GNM) update equation addresses the major numerical difficulty associated with the near-zero singular values of the linearized operator and gives results that are not sensitive to the time step of integration. Therefore, we also propose a pseudo-dynamic stochastic filtering approach for the same problem using a parsimonious representation of states and specifically solve the linearized filtering equations through a pseudo-dynamic ensemble Kalman filter (PD-EnKF). For multiple sets of measurements involving various load cases, we expedite the speed of thePD-EnKF by proposing an inner iteration within every time step. Results using the pseudo-dynamic strategy obtained through PD-EnKF and recursive integration are compared with those from the conventional GNM, which prove that the PD-EnKF is the best performer showing little sensitivity to process noise covariance and yielding reconstructions with less artifacts even when the ensemble size is small.

Self-regularized pseudo time-marching schemes for structural system identification with static measurements

We explore the application of pseudo time marching schemes, involving either deterministic integration or stochastic filtering, to solve the inverse problem of parameter identification of large dimensional structural systems from partial and noisy measurements of strictly static response. Solutions of such non-linear inverse problems could provide useful local stiffness variations and do not have to confront modeling uncertainties in damping, an important, yet inadequately understood, aspect in dynamic system identification problems. The usual method of least-square solution is through a regularized Gauss-Newton method (GNM) whose results are known to be sensitively dependent on the regularization parameter and data noise intensity. Finite time, recursive integration of the pseudo-dynamical GNM (PD-GNM) update equation addresses the major numerical difficulty associated with the near-zero singular values of the linearized operator and gives results that are not sensitive to the time step of integration. Therefore, we also propose a pseudo-dynamic stochastic filtering approach for the same problem using a parsimonious representation of states and specifically solve the linearized filtering equations through apseudo-dynamic ensemble Kalman filter (PD-EnKF). For multiple sets ofmeasurements involving various load cases, we expedite the speed of the PD-EnKF by proposing an inner iteration within every time step. Results using the pseudo-dynamic strategy obtained through PD-EnKF and recursive integration are compared with those from the conventional GNM, which prove that the PD-EnKF is the best performer showing little sensitivity to process noise covariance and yielding reconstructions with less artifacts even when the ensemble size is small. Copyright (C) 2009 John Wiley & Sons, Ltd.

Identification of molecules relevant for the invasiveness of fibrosarcomas and melanomas

Cancer is becoming the leading cause of deaths in the world. As 90% of all deaths from cancer are caused by metastasis, discovery of the mechanisms behind cancer cell invasion and metastasis is of utmost importance. Only new effective therapies targeting cancer progression can reduce cancer mortality rates. The aim of this study was to identify molecules that are relevant for tumor cell invasion and spreading in fibrosarcomas and melanomas, and to analyze their potential for cancer biomarkers or therapeutic targets. First, the gene expression changes of normal cells and transformed cells showing high invasiveness, S-adenosylmethionine decarboxylase (AdoMetDC)-transfected murine fibroblasts and human melanoma cells, were studied by microarray analyses. The function of the identified candidate molecules were then studied in detail in these cell lines. Finally, the physiological relevance of the identified changes was studied by immunohistochemical analyses of human sarcoma and melanoma specimens or by a mouse xenograft model. In fibrosarcoma cells, the most remarkable change detected was a dramatic up-regulation of the actin-sequestering molecule thymosin beta 4 (TB4), which was shown to be important for the transformed phenotype of the AdoMetDC-transfected cells (Amdc-s and -as). A sponge toxin latrunculin A, inhibiting the binding of TB4 to actin, was found to selectively inhibit the migration and invasion of these cells. Further, Amdc-s-induced mouse tumors and human high-grade sarcomas were found to show intense TB4 immunostaining. In addition to TB4, integrin subunits alfa 6 and beta 7 (ItgA6 and ItgB7) were found to be up-regulated in Amdc-s and -as cells. ItgA6 was shown to dimerize mainly with ItgB1 in Amdc-s. Inhibition of ItgA6 or ItgB1 function with neutralizing antibodies fully blocked the invasiveness of Amdc-s cells, and importantly also human HT-1080 fibrosarcoma cells, in three-dimensional (3D)-Matrigel mimicking tumor extracellular matrix (ECM). By immunohistochemical analyses, strong staining for ITGA6 was detected in human high-grade fibrosarcomas and other sarcomas, especially at the invasion fronts of the tumors. In the studied melanoma cell lines, the expression levels of the adhesion-related ECM proteins tenascin-C (TN-C), fibronectin (FN), and transforming growth factor beta-induced (TGFBI) were found to be highly up-regulated. By immunohistochemistry, intense TN-C and FN staining was detected in invasive and metastatic melanoma tumors, showing co-localization (together with procollagen-I) in tubular meshworks and channels around the invading melanoma cells. In vitro, TN-C and FN were further found to directly stimulate the migration of melanoma cells in 3D-collagen-I matrix. The third candidate protein, TGFBI, was found to be an anti-adhesive molecule for melanoma cells, and knockdown of its expression in metastatic melanoma cells (TGFBI-KD cells) led to dramatically impaired tumor growth in immunocompromized mice. Interestingly, the control tumors showed intense TGFBI immunostaining in the invasion fronts, showing partial co-localization with the fibrillar FN staining, whereas the small TGFBI-KD cell-induced tumors displayed amorphous, non-fibrillar FN staining. These data suggest an important role for TGFBI in FN fibrillogenesis and melanoma progression. In conclusion, we have identified several invasion-related molecules, which show potential for cancer diagnostic or prognostic markers, or therapeutic targets. Based on our previous and present fibrosarcoma studies, we propose the possibility of using ITGA6 antagonists (affecting tumor cell adhesion) in combination with TB4 inhibitors (affecting tumor cell migration) and cathepsin L inhibitors (affecting the degradation of basement membrane and ECM proteins) for the treatment of fibrosarcomas and other tumors overexpressing these molecules. With melanoma cells, in turn, we point to the importance of three secreted ECM proteins, TN-C, FN, and TGFBI, in melanoma progression. Of these, especially the potential of TN-C as a prognostic melanoma biomarker and TGFBI as a promising therapeutic target molecule are clearly worth additional studies.

Genetic identification of four Malaysian mackerel species off Coast of Peninsular Malaysia based on molecular marker

Random Amplified Polymorphic DNA (RAPD) markers and cytochrome b (Cyt-b) gene sequences were utilized to fingerprint and construct phylogenetic relationships among four species of mackerel commonly found in the Straits of Malacca namely Rastrelliger kanagurta, R. brachysoma, Decapterus maruadsi and D. russelli. The UPGMA dendogram and genetic distance clearly showed that the individuals clustered into their own genus and species except for the Decapterus. These results were also supported by partial mtDNA cytochrome b gene sequences (279 bp) which found monotypic sequence for all Decapterus studied. Cytochrome b sequence phylogeny generated through Neighbor Joining (NJ) method was congruent with RAPD data. Results showed clear discrimination between both genera with average nucleotide divergence about 25.43%. This marker also demonstrated R. brachysoma and R. kanagurta as distinct species separated with average nucleotide divergence about 2.76%. However, based on BLAST analysis, this study indicated that the fish initially identified as D. maruadsi was actually D. russelli. The results highlighted the importance of genetic analysis for taxonomic validation, in addition to morphological traits.

A Bayesian method for identification of stock mixtures from molecular marker data

Molecular markers have been demonstrated to be useful for the estimation of stock mixture proportions where the origin of individuals is determined from baseline samples. Bayesian statistical methods are widely recognized as providing a preferable strategy for such analyses. In general, Bayesian estimation is based on standard latent class models using data augmentation through Markov chain Monte Carlo techniques. In this study, we introduce a novel approach based on recent developments in the estimation of genetic population structure. Our strategy combines analytical integration with stochastic optimization to identify stock mixtures. An important enhancement over previous methods is the possibility of appropriately handling data where only partial baseline sample information is available. We address the potential use of nonmolecular, auxiliary biological information in our Bayesian model.

Mitochondrial gene sequences useful for species identification of western North Atlantic Ocean sharks

Molecular-based approaches for shark species identification have been driven largely by issues specific to the fishery. In an effort to establish a more comprehensive identification data set, we investigated DNA sequence variation of a 1.4-kb region from the mitochondrial genome covering partial sequences from the 12S rDNA, 16S rDNA, and the complete valine tRNA from 35 shark species from the Atlantic fishery. Generally, within-species variability was low in relation to interspecific divergence because species haloptypes formed monophyletic groups. Phylogenetic analyses resolved ordinal relationships among Carcharhiniformes and Lamniformes, and revealed support for the families Sphyrnidae and Triakidae (within Carcharhiniformes) and Lamnidae and Alopidae (within Lamniformes). The combination of limited intraspecific variability and sufficient between-species divergence indicates that this locus is suitable for species identification.

Identification and cloning of a trypsin inhibitor from skin secretions of Chinese red-belly toad Bombina maxima

A novel trypsin inhibitor was identified and purified from skin secretions of Chinese red-belly toad Bombina maxima. The partial N-terminal 29 amino acid residues of the peptide, named BMTI, were determined by automated Edman degradation. This allowed the cloning of a full-length cDNA encoding BMTI from a cDNA library prepared from the toad skin. The deduced complete amino acid sequence of BMTI indicates that mature BMTI is composed of 60 amino acids. A FASTA search in the databanks revealed that BMTI exhibits 81.7% sequence identity with BSTI, a trypsin/thrombin inhibitor from European toad Bombina bombina skin secretions. Sequence differences between BMTI and BSTI were due to 11 substitutions at positions 2, 9, 25, 27, 36-37, 39, 41-42, 50 and 56. BMTI potently inhibited trypsin with a K-i value of 0.06 muM, similar to that of BSTI. However, unlike BSTI, which also inhibited thrombin with a K-i value of 1 muM, no inhibitory effect of BMTI on thrombin was observed under the assay conditions. (C) 2002 Elsevier Science Inc. All rights reserved.

Molecular identification of symbiotic dinoflagellates (Zooxanthellae) of dominant reef-building corals off Kish Island

Scleractinian coral species harbour communities of photosynthetic taxa of the genus Symbiodinium. As many as eight genetic clades (A, B, C, D, E, F, G and H) of Symbiodinium have been discovered using molecular biology. These clades may differ from each other in their physiology, and thus influence the ecological distribution and resilience of their host corals to environmental stresses. Corals of the Persian Gulf are normally subject to extreme environmental conditions including high salinity and seasonal variation in temperature. This study is the first to use molecular techniques to identify the Symbiodinium of the Iranian coral reefs to the level of phylogenetic clades. Samples of eight coral species were collected at two different depths from the eastern part of Kish Island in the northern Persian Gulf. Partial 28S nuclear ribosomal (nr) DNA of Symbiodinium (D1/D2 domains) were amplified by Polymerase Chain Reaction (PCR). PCR products were analyzed using Single Stranded Conformational Polymorphism (SSCP) and phylogenetic analyses of the LSU DNA sequences from a subset of the samples. The results showed that Symbiodinium populations were generally uniform among and within the populations of 8 coral species studied, and there are at least two clades of Symbiodinium from Kish Island. Clade D was detected from 8 of the coral species while clade C90 was found in 2 of species only (one species hosted two clades simultaneously). The dominance of clade D might be explained by high temperatures or the extreme temperature variation, typical of the Persian Gulf.

Identification of Prorocentrum minimum and Takayama pulchella by fluorescence in situ hybridization through epifluorescence microscopy and flow cytometry

Partial rDNA sequences of Prorocentrum minimum and Takayama pulchella were amplified, cloned and sequenced. and these sequence data were deposited in the GenBank. Eight oligonucleotide probes (DNA probes) were designed based on the sequence analysis. The probes were employed to detect and identify P. minimum and T. pulchella in unialgal and mixed algal samples with a fluorescence in situ hybridization method using flow cytometry. Epifluorescence micrographs showed that these specific probes labeled with fluorescein isothiocyanate entered the algal cells and bound to target sequences, and the fluorescence signal resulting from whole-cell hybridization varied from probe to probe. These DNA probes and the hybridization protocol we developed were specific and effective for P. minimum and T. pulchella, without any specific binding to other algal species. The hybridization efficiency of different probes specific to P. minimum was in the order: PM18S02 > PM28S02 > PM28S01 > PM18S01, and that of the probes specific to T. pulchella was TP18S02 > TP28S01 > TP28S02 > TP18S01. The different hybridization efficiency of the DNA probes could also be shown in the fluorescent signals between the labeled and unlabeled cells demonstrated using flow cytometry. The DNA probes PM18S02, PM28S02; TP18S02 and TP28S01, and the protocol, were also useful for the detection of algae in natural samples.