The Index-Based Subgraph Matching Algorithm (ISMA): Fast Subgraph Enumeration in Large Networks Using Optimized Search Trees

Subgraph matching algorithms are designed to find all instances of predefined subgraphs in a large graph or network and play an important role in the discovery and analysis of so-called network motifs, subgraph patterns which occur more often than expected by chance. We present the index-based subgraph matching algorithm (ISMA), a novel tree-based algorithm. ISMA realizes a speedup compared to existing algorithms by carefully selecting the order in which the nodes of a query subgraph are investigated. In order to achieve this, we developed a number of data structures and maximally exploited symmetry characteristics of the subgraph. We compared ISMA to a naive recursive tree-based algorithm and to a number of well-known subgraph matching algorithms. Our algorithm outperforms the other algorithms, especially on large networks and with large query subgraphs. An implementation of ISMA in Java is freely available at http://sourceforge.net/projects/isma/.     

Exploiting recombinant antibodies in point-of-care (POC) diagnostics: the combinatorial advantage

Antibodies are ubiquitously deployed on in vitro diagnostic (IVD) platforms for detecting a panoply of analytes indicative of environmental and food contamination, residue adulteration and both veterinary and medical diagnostics. In the clinical realm, rapid and accurate determination of disease status is paramount. The significance of immunodiagnostic performance cannot be overemphasized and in many cases reliable diagnosis informs medical intervention which can mean the difference between patient recovery and demise. Cardiovascular disease (CVD) is the single biggest cause of adult mortality in the western world and principal burden on the healthcare services. Although the troponin (Tn) family, in particular troponin I (TnI), are regarded as the gold standard for diagnosis of myocardial damage, over the last decade much research has focused on the identification of alternative cardiac biomarker molecules that can either supplant or complement TnI metrics to add value to cardiac risk stratification criteria. In particular, markers that appear earlier than TnI in the pathophyisiology of cardiac disease are highly sought after. The subject?of this addendum represents part of a broader challenge to deliver novel rapid point-of-care (POC) diagnostics to provide a chip-based multi-plexed platform for more comprehensive profiling of cardiac status with additive diagnostic and prognostic value.?Specifically, it outlines proof-of-concept direct myeloperoxidase (MPO) detection, demonstrates the benefits of using recombinant antibodies in POC diagnostics and describes optimized strategies for generation of superior candidate antibody panels.     

The Mirror-Type Internal Symmetry in the Primary Structure of Proteins: Detection and Functional Role (Review)

This review summarized the data obtained by the author in studies on internal symmetry of the mirror type in primary structures of proteins. The methods for detection of symmetric segments in amino acid sequences are analyzed: (1) the method based on analysis of sequences of roots of amino acid codons; (2) the dot matrix method; (3) the method of internal symmetry scanning. The results of studies of internal symmetry in enzymes and signaling proteins are presented. The probable role of the internal symmetry in the structural-functional organization of proteins is discussed.     

Enumeration of chlorine-stressed organisms with acridine orange 2-(p-iodophenyl)-3-(p-nitrophenyl)-5-phenyl tetrazolium chloride (AOINT)

Direct microscopic enumeration ofEnterobacter cloacae with the acridine orange 2-(p-iodophenyl)-3-(p-nitrophenyl)-5-phenyl tetrazolium chloride technique (AOINT) was compared with spread plate counts on nonselective media to establish the usefulness of the former technique in the enumeration of chlorine-stressed cells. Results indicate that the techniques are comparable when the organisms are not stressed. However, AOINT is more sensitive than are plate counts in the detection of chlorine-stressed cells.     

The S(2)-Ensemble Fusion Algorithm

This paper presents a novel model for performing classification and visualization of high-dimensional data by means of combining two enhancing techniques. The first is a semi-supervised learning, an extension of the supervised learning used to incorporate unlabeled information to the learning process. The second is an ensemble learning to replicate the analysis performed, followed by a fusion mechanism that yields as a combined result of previously performed analysis in order to improve the result of a single model. The proposed learning schema, termed S(2)-Ensemble, is applied to several unsupervised learning algorithms within the family of topology maps, such as the Self-Organizing Maps and the Neural Gas. This study also includes a thorough research of the characteristics of these novel schemes, by means quality measures, which allow a complete analysis of the resultant classifiers from the viewpoint of various perspectives over the different ways that these classifiers are used. The study conducts empirical evaluations and comparisons on various real-world datasets from the UCI repository, which exhibit different characteristics, so to enable an extensive selection of situations where the presented new algorithms can be applied.     

Enumeration and Localization of N(2)-Fixing Bacteria Associated with Roots of Spartina alterniflora Loisel

Numbers and possible locations of N(2)-fixing bacteria were investigated in roots of Spartina alterniflora Loisel, which support nitrogenase activity in the undisturbed native habitat. N(2)-fixing bacteria were recovered in cultures both from S. alterniflora roots and from the surrounding sediment, and they formed a greater proportion of the bacteria recovered from root homogenates than from salt-marsh sediment. N(2)-fixing bacteria were recovered in high numbers from the rhizoplane of S. alterniflora after roots were treated with 1 or 5% chloramine-T for 1 h or with 1% NaOCl for 1 or 2 h. Immersing S. alterniflora roots in 5% NaOCl for 1 h was more effective in distinguishing bacteria inside the roots since this treatment nearly eliminated N(2)-fixing bacteria recoverable from the rhizoplane, although high numbers of N(2)-fixing bacteria were recovered from homogenates of roots treated with 5% NaOCl for 1 h. However, this treatment was less effective with roots of Zea mays L. (Funks G4646) and Sorghum bicolor (L.) Moench (CK-60 A), indicating that techniques to surface sterilize roots should be evaluated for different plants. Bacteria were observed by light and electron microscopy inter- and intracellularly in the cortex and in the aerenchyma of S. alterniflora roots. This study clearly shows that bacteria, including N(2) fixers, colonize the interior of roots of S. alterniflora growing in a Chesapeake Bay, Maryland, salt marsh.     

Global Patch Matching (GPM) for freehand 3D ultrasound reconstruction

Background

3D ultrasound volume reconstruction from B-model ultrasound slices can provide more clearly and intuitive structure of tissue and lesion for the clinician.

Methods

This paper proposes a novel Global Path Matching method for the 3D reconstruction of freehand ultrasound images. The proposed method composes of two main steps: bin-filling scheme and hole-filling strategy. For the bin-filling scheme, this study introduces two operators, including the median absolute deviation and the inter-quartile range absolute deviation, to calculate the invariant features of each voxel in the 3D ultrasound volume. And the best contribution range for each voxel is obtained by calculating the Euclidian distance between current voxel and the voxel with the minimum invariant features. Hence, the intensity of the filling vacant voxel can be obtained by weighted combination of the intensity distribution of pixels in the best contribution range. For the hole-filling strategy, three conditions, including the confidence term, the data term and the gradient term, are designed to calculate the weighting coefficient of the matching patch of the vacant voxel. While the matching patch is obtained by finding patches with the best similarity measure that defined by the three conditions in the whole 3D volume data.

Results

Compared with VNN, PNN, DW, FMM, BI and KR methods, the proposed Global Path Matching method can restore the 3D ultrasound volume with minimum difference.

Conclusions

Experimental results on phantom and clinical data sets demonstrate the effectiveness and robustness of the proposed method for the reconstruction of ultrasound volume.

     

Enumeration of Fe(II)-oxidizing and Fe(III)-reducing bacteria in the root zone of wetland plants: Implications for a rhizosphere iron cycle

Iron plaque occurs on the roots of most wetland and submersed aquatic plant species and is a large pool of oxidized Fe(III) in some environments. Because plaque formation in wetlands with circumneutral pH has been largely assumed to be an abiotic process, no systematic effort has been made to describe plaque-associated microbial communities or their role in plaque deposition. We hypothesized that Fe(II)-oxidizing bacteria (FeOB) and Fe(III)-reducing bacteria (FeRB) are abundant in the rhizosphere of wetland plants across a wide range of biogeochemical environments. In a survey of 13 wetland and aquatic habitats in the Mid-Atlantic region, FeOB were present in the rhizosphere of 92% of the plant specimens collected (n = 37), representing 25 plant species. In a subsequent study at six of these sites, bacterial abundances were determined in the rhizosphere and bulk soil using the most probable number technique. The soil had significantly more total bacteria than the roots on a dry mass basis (1.4 × 10⁹ cells/g soil vs. 8.6 × 10⁷ cells/g root; p < 0.05). The absolute abundance of aerobic, lithotrophic FeOB was higher in the soil than in the rhizosphere (3.7 × 10⁶/g soil vs. 5.9 × 10⁵/g root; p < 0.05), but there was no statistical difference between these habitats in terms of relative abundance (1% of the total cell number). In the rhizosphere, FeRB accounted for an average of 12% of all bacterial cells while in the soil they accounted for < 1% of the total bacteria. We concluded that FeOB are ubiquitous and abundant in wetland ecosystems, and that FeRB are dominant members of the rhizosphere microbial community. These observations provide a strong rationale for quantifying the contribution of FeOB to rhizosphere Fe(II) oxidation rates, and investigating the combined role of FeOB and FeRB in a rhizosphere iron cycle.     

Base-Calling Algorithm with Vocabulary (BCV) Method for Analyzing Population Sequencing Chromatograms

Sanger sequencing is a common method of reading DNA sequences. It is less expensive than high-throughput methods, and it is appropriate for numerous applications including molecular diagnostics. However, sequencing mixtures of similar DNA of pathogens with this method is challenging. This is important because most clinical samples contain such mixtures, rather than pure single strains. The traditional solution is to sequence selected clones of PCR products, a complicated, time-consuming, and expensive procedure. Here, we propose the base-calling with vocabulary (BCV) method that computationally deciphers Sanger chromatograms obtained from mixed DNA samples. The inputs to the BCV algorithm are a chromatogram and a dictionary of sequences that are similar to those we expect to obtain. We apply the base-calling function on a test dataset of chromatograms without ambiguous positions, as well as one with 3–14% sequence degeneracy. Furthermore, we use BCV to assemble a consensus sequence for an HIV genome fragment in a sample containing a mixture of viral DNA variants and to determine the positions of the indels. Finally, we detect drug-resistant Mycobacterium tuberculosis strains carrying frameshift mutations mixed with wild-type bacteria in the pncA gene, and roughly characterize bacterial communities in clinical samples by direct 16S rRNA sequencing.     

Exploiting plants for glutathione (GSH) production: Uncoupling GSH synthesis from cellular controls results in unprecedented GSH accumulation

Glutathione (GSH) is a key factor for cellular redox homeostasis and tolerance against abiotic and biotic stress ( May et al., 1998 ; Noctor et al., 1998a ). Previous attempts to increase GSH content in plants have met with moderate success ( Rennenberg et al., 2007 ), largely because of tight and multilevel control of its biosynthesis ( Rausch et al., 2007 ). Here, we report the in planta expression of the bifunctional γ‐glutamylcysteine ligase—glutathione synthetase enzyme from Streptococcus thermophilus (StGCL‐GS), which is shown to be neither redox‐regulated nor sensitive to feedback inhibition by GSH. Transgenic tobacco plants expressing StGCL‐GS under control of a constitutive promoter reveal an extreme accumulation of GSH in their leaves (up to 12 μmol GSH/gFW, depending on the developmental stage), which is more than 20‐ to 30‐fold above the levels observed in wild‐type (wt) plants and which can be even further increased by additional sulphate fertilization. Surprisingly, this dramatically increased GSH production has no impact on plant growth while enhancing plant tolerance to abiotic stress. Furthermore, StGCL‐GS‐expressing plants are a novel, cost‐saving source for GSH production, being competitive with current yeast‐based systems ( Li et al., 2004 ).     

The GRID: The General Repository for Interaction Datasets

We have developed a relational database, called the General Repository for Interaction Datasets (The GRID; ) to archive and display physical, genetic and functional interactions. The GRID displays data-rich interaction tables for any protein of interest, combines literature-derived and high throughput interaction datasets, and is readily accessible via the World Wide Web. Interactions parsed in the GRID can be viewed in graphical form with a versatile visualization tool called Osprey.     

The GRID: The General Repository for Interaction Datasets

We have developed a relational database, called the General Repository for Interaction Datasets (The GRID) to archive and display physical, genetic and functional interactions. The GRID displays data-rich interaction tables for any protein of interest, combines literature-derived and high-throughput interaction datasets, and is readily accessible via the web. Interactions parsed in The GRID can be viewed in graphical form with a versatile visualization tool called Osprey.