Discriminating Different Classes of Biological Networks by Analyzing the Graphs Spectra Distribution

The brain's structural and functional systems, protein-protein interaction, and gene networks are examples of biological systems that share some features of complex networks, such as highly connected nodes, modularity, and small-world topology. Recent studies indicate that some pathologies present topological network alterations relative to norms seen in the general population. Therefore, methods to discriminate the processes that generate the different classes of networks (e. g., normal and disease) might be crucial for the diagnosis, prognosis, and treatment of the disease. It is known that several topological properties of a network (graph) can be described by the distribution of the spectrum of its adjacency matrix. Moreover, large networks generated by the same random process have the same spectrum distribution, allowing us to use it as a "fingerprint". Based on this relationship, we introduce and propose the entropy of a graph spectrum to measure the "uncertainty" of a random graph and the Kullback-Leibler and Jensen-Shannon divergences between graph spectra to compare networks. We also introduce general methods for model selection and network model parameter estimation, as well as a statistical procedure to test the nullity of divergence between two classes of complex networks. Finally, we demonstrate the usefulness of the proposed methods by applying them to (1) protein-protein interaction networks of different species and (2) on networks derived from children diagnosed with Attention Deficit Hyperactivity Disorder (ADHD) and typically developing children. We conclude that scale-free networks best describe all the protein-protein interactions. Also, we show that our proposed measures succeeded in the identification of topological changes in the network while other commonly used measures (number of edges, clustering coefficient, average path length) failed.

Spectral-based mesh segmentation

In design and manufacturing, mesh segmentation is required for FACE construction in boundary representation (BRep), which in turn is central for featurebased design, machining, parametric CAD and reverse engineering, among others -- Although mesh segmentation is dictated by geometry and topology, this article focuses on the topological aspect (graph spectrum), as we consider that this tool has not been fully exploited -- We preprocess the mesh to obtain a edgelength homogeneous triangle set and its Graph Laplacian is calculated -- We then produce a monotonically increasing permutation of the Fiedler vector (2nd eigenvector of Graph Laplacian) for encoding the connectivity among part feature submeshes -- Within the mutated vector, discontinuities larger than a threshold (interactively set by a human) determine the partition of the original mesh -- We present tests of our method on large complex meshes, which show results which mostly adjust to BRep FACE partition -- The achieved segmentations properly locate most manufacturing features, although it requires human interaction to avoid over segmentation -- Future work includes an iterative application of this algorithm to progressively sever features of the mesh left from previous submesh removals

Altered structural connectivity in patients with medial temporal lobe epilepsy: A Diffusion Spectrum Imaging and Graph Analysis study

In this study we investigated the effect of medial temporal lobe epilepsy (MTLE) on the global characteristics of brain connectivity estimated by topological measures. We used DSI (Diffusion Spectrum Imaging) to construct a connectivity matrix where the nodes represents the anatomical ROIs and the edges are the connections between any pair of ROIs weighted by the mean GFA/FA values. A significant difference was found between the patient group vs control group in characteristic path length, clustering coefficient and small-worldness. This suggests that the MTLE network is less efficient compared to the network of the control group.

Trade spectrum of K4-e

A K-4 - e trade consists of two disjoint decompositions of some simple graph H into copies of K-4 - e. The number of vertices of H is referred to as the foundation of the trade, while the number of copies of K-4 - e in each of the decompositions is called the volume of the trade. We determine the values of v and s for which there exists a K-4 - e trade of volume s and foundation v.

On the spectrum for K_{m+2}/K_m designs

The spectrum problem for the decomposition of K-n into copies of the graph K_{m+2}\K_m is solved for n = 0 or 1 (mod 2m + 1). (C) 1997 John Wiley & Sons, Inc.

Studies on the Spectrum and the Energy of Graphs

Department of Mathematics, Cochin University of Science and Technology

A graph-based framework for thermal faceprint characterization

Thermal faceprint has been paramount in the last years. Since we can handle with face recognition using images acquired in the infrared spectrum, an unique individual's signature can be obtained through the blood vessels network of the face. In this work, we propose a novel framework for thermal faceprint extraction using a collection of graph-based techniques, which were never used to this task up to date. A robust method of thermal face segmentation is also presented. The experiments, which were conducted over the UND Collection C dataset, have showed promising results. © 2011 Springer-Verlag.

Quality of transmission estimation in WDM and elastic optical networks accounting for space-spectrum dependencies

We develop a framework for estimating the quality of transmission (QoT) of a new lightpath before it is established, as well as for calculating the expected degradation it will cause to existing lightpaths. The framework correlates the QoT metrics of established lightpaths, which are readily available from coherent optical receivers that can be extended to serve as optical performance monitors. Past similar studies used only space (routing) information and thus neglected spectrum, while they focused on oldgeneration noncoherent networks. The proposed framework accounts for correlation in both the space and spectrum domains and can be applied to both fixed-grid wavelength division multiplexing (WDM) and elastic optical networks. It is based on a graph transformation that exposes and models the interference between spectrum-neighboring channels. Our results indicate that our QoT estimates are very close to the actual performance data, that is, to having perfect knowledge of the physical layer. The proposed estimation framework is shown to provide up to 4 × 10-2 lower pre-forward error correction bit error ratio (BER) compared to theworst-case interference scenario,which overestimates the BER. The higher accuracy can be harvested when lightpaths are provisioned with low margins; our results showed up to 47% reduction in required regenerators, a substantial savings in equipment cost.

Packings and coverings of the complete graph with trees

In this thesis, we define the spectrum problem for packings (coverings) of G to be the problem of finding all graphs H such that a maximum G-packing (minimum G- covering) of the complete graph with the leave (excess) graph H exists. The set of achievable leave (excess) graphs in G-packings (G-coverings) of the complete graph is called the spectrum of leave (excess) graphs for G. Then, we consider this problem for trees with up to five edges. We will prove that for any tree T with up to five edges, if the leave graph in a maximum T-packing of the complete graph Kn has i edges, then the spectrum of leave graphs for T is the set of all simple graphs with i edges. In fact, for these T and i and H any simple graph with i edges, we will construct a maximum T-packing of Kn with the leave graph H. We will also show that for any tree T with k ≤ 5 edges, if the excess graph in a minimum T-covering of the complete graph Kn has i edges, then the spectrum of excess graphs for T is the set of all simple graphs and multigraphs with i edges, except for the case that T is a 5-star, for which the graph formed by four multiple edges is not achievable when n = 12.

Evaluation Of Characteristic-to-total Spectrum Ratio: Comparison Between Experimental And A Semi-empirical Model.

Primary X-ray spectra were measured in the range of 80-150kV in order to validate a computer program based on a semiempirical model. The ratio between the characteristic and total air Kerma was considered to compare computed results and experimental data. Results show that the experimental spectra have higher first HVL and mean energy than the calculated ones. The ratios between the characteristic and total air Kerma for calculated spectra are in good agreement with experimental results for all filtrations used.

Validity and reliability of the Structured Clinical Interview for Mood Spectrum: Brazilian version (SCIMOODS-VB)

OBJECTIVE: The aim of this study was to translate the Structured Clinical Interview for Mood Spectrum into Brazilian Portuguese, measuring its reliability, validity, and defining scores for bipolar disorders. METHOD: Questionnaire was translated (into Brazilian Portuguese) and back-translated into English. Sample consisted of 47 subjects with bipolar disorder, 47 with major depressive disorder, 18 with schizophrenia and 22 controls. Inter-rater reliability was tested in 20 subjects with bipolar disorder and MDD. Internal consistency was measured using the Kuder Richardson formula. Forward stepwise discriminant analysis was performed. Scores were compared between groups; manic (M), depressive (D) and total (T) threshold scores were calculated through receiver operating characteristic (ROC) curves. RESULTS: Kuder Richardson coefficients were between 0.86 and 0.94. Intraclass correlation coefficient was 0.96 (CI 95 % 0.93-0.97). Subjects with bipolar disorder had higher M and T, and similar D scores, when compared to major depressive disorder (ANOVA, p < 0.001). The sub-domains that best discriminated unipolar and bipolar subjects were manic energy and manic mood. M had the best area under the curve (0.909), and values of M equal to or greater than 30 yielded 91.5% sensitivity and 74.5% specificity. CONCLUSION: Structured Clinical Interview for Mood Spectrum has good reliability and validity. Cut-off of 30 best differentiates subjects with bipolar disorder vs. unipolar depression. A cutoff score of 30 or higher in the mania sub-domain is appropriate to help make a distinction between subjects with bipolar disorder and those with unipolar depression.

Emergence of Klebsiella pneumoniae carrying the novel extended-spectrum 'beta'-lactamase gene variants 'bla IND. SHV-40', 'bla IND. TEM-116' and the class I integron-associated 'bla IND. GES-7' in Brazil

A clinical Klebsiella pneumoniae isolate carrying the extended-spectrum beta-lactamase gene variants bla(SHV-40), bla(TEM-116) and bla(GES-7) was recovered. Cefoxitin and ceftazidime activity was most affected by the presence of these genes and an additional resistance to trimethoprim-sulphamethoxazole was observed. The bla(GES-7) gene was found to be inserted into a class 1 integron. These results show the emergence of novel bla(TEM) and bla(SHV) genes in Brazil. Moreover, the presence of class 1 integrons suggests a great potential for dissemination of bla(GES) genes into diverse nosocomial pathogens. Indeed, the bla(GES-7) gene was originally discovered in Enterobacter cloacae in Greece and, to our knowledge, has not been reported elsewhere

Extended-spectrum beta-lactamases among Enterobacteriaceae isolated in a public hospital in Brazil

Extended-spectrum beta-lactamases (ESBL) in enterobacteria are recognized worldwide as a great hospital problem. In this study, 127 ESBL-producing Enterobacteriaceae isolated in one year from inpatients and Outpatients at a public teaching hospital at Sao Paulo, Brazil, were Submitted to analysis by PCR with specific primers for bla(SHV), bla(TEM) and bla(CTX-M) genes. From the 127 isolates, 96 (75.6%) Klebsiella pneumoniae, 12 (9.3%) Escherichia coli, 8 (6.2%) Morganella morganii, 3 (2.3%) Proteus mirabilis, 2 (1.6%) Klebsiella oxytoca, 2 (1.6%) Providencia rettgeri, 2 (1.6%) Providencia stuartti, 1 (0.8%) Enterobacter aerogenes and 1 (0.8%) Enterobacter cloacae were identified as ESBL producers. Bla(SHV), bla(TEM), and bla(CTX-M) were detected in 63%, 17.3% and 33.9% strains, respectively. Pulsed field get eletrophoresis genotyping of K. pneumoniae revealed four main molecular patterns and 29 unrelated profiles. PCR results showed a high variety of ESBL groups among strains, in nine different species. The results Suggest the spread of resistance genes among genetically different strains of ESBL-producing K. pneumoniae in some hospital wards, and also that some strongly related strains were identified in different hospital wards, Suggesting clonal spread in the institutional environment

ESPECTRA: Searching the Bipolar Spectrum in Eating Disorder patients

Background: Bipolar Disorder (BD) is a chronic, recurrent and highly prevalent illness. Despite the need for correct diagnosis to allow proper treatment, studies have shown that reaching a diagnosis can take up to ten years due to the lack of recognition of the broader presentations of BD. Frequent comorbidities with other psychiatric disorders are a major cause of misdiagnosis and warrant thorough evaluation. Methods/Design: ESPECTRA (Occurrence of Bipolar Spectrum Disorders in Eating Disorder Patients) is a single-site cross-sectional study involving a comparison group, designed to evaluate the prevalence of bipolar spectrum in an eating disorder sample. Women aged 18-45 years will be evaluated using the SCID-P and Zurich criteria for diagnosis and the HAM-D, YOUNG, SCI-MOODS, HCL-32, BIS-11, BSQ, WHOQoL and EAS instruments for rating symptoms and measuring clinical correlates. Discussion: The classificatory systems in psychiatry are based on categorical models that have been criticized for simplifying the diagnosis and leading to an increase in comorbidities. Some dimensional approaches have been proposed aimed at improving the validity and reliability of psychiatric disorder assessments, especially in conditions with high rates of comorbidity such as BD and Eating Disorder (ED). The Bipolar Spectrum (BS) remains under-recognized in clinical practice and its definition is not well established in current diagnostic guidelines. Broader evaluation of psychiatric disorders combining categorical and dimensional views could contribute to a more realistic understanding of comorbidities and help toward establishing a prognosis.

High Prevalence of bla(CTX-M) Extended Spectrum Beta-Lactamase Genes in Klebsiella pneumoniae Isolates from a Tertiary Care Hospital: First report of bla(SHV-12), bla(SHV-31), bla(SHV-38), and bla(CTX-M-15) in Brazil

The aim of this study was to investigate the presence and prevalence of bla(TEM), bla(SHV), and bla(CTX-M) and bla(GES)-like genes, responsible for extended spectrum beta-lactamases (ESBLs) production in clinical isolates of Klebsiella pneumoniae collected from a Brazilian tertiary care hospital. Sixty-five ESBL producing K. pneumoniae isolates, collected between 2005 and 2007, were screened by polymerase chain reaction (PCR). Identification of bla genes was achieved by sequencing. Genotyping of ESBL producing K. pneumoniae was performed by the enterobacterial repetitive intergenic consensus-PCR with cluster analysis by the Dice coefficient. The presence of genes encoding ESBLs was confirmed in 59/65 (90.8%) isolates, comprising 20 bla(CTX-M-2), 14 bla(CTX-M-59), 12 bla(CTX-M-15), 9 bla(SHV-12), 1 bla(SHV-2), 1 bla(SHV-2a), 1 bla(SHV-5), and 1 bla(SHV-31) genes. The ESBL genes bla(SHV-12), bla(SHV-31), and bla(CTX-M-15), and the chromosome-encoded SHV-type beta-lactamase capable of hydrolyzing imipenem were detected in Brazil for the first time. The analysis of the enterobacterial repetitive intergenic consensus-PCR band patterns revealed a high rate of multiclonal bla(CTX-M) carrying K. pneumoniae isolates (70.8%), suggesting that dissemination of encoding plasmids is likely to be the major cause of the high prevalence of these genes among the K. pneumoniae isolates considered in this study.