Uncovering the overlapping community structure of complex networks in nature and society

Many complex systems in nature and society can be described in terms of networks capturing the intricate web of connections among the units they are made of. A key question is how to interpret the global organization of such networks as the coexistence of their structural subunits (communities) associated with more highly interconnected parts. Identifying these a priori unknown building blocks (such as functionally related proteins, industrial sectors and groups of people) is crucial to the understanding of the structural and functional properties of networks. The existing deterministic methods used for large networks find separated communities, whereas most of the actual networks are made of highly overlapping cohesive groups of nodes. Here we introduce an approach to analysing the main statistical features of the interwoven sets of overlapping communities that makes a step towards uncovering the modular structure of complex systems. After defining a set of new characteristic quantities for the statistics of communities, we apply an efficient technique for exploring overlapping communities on a large scale. We find that overlaps are significant, and the distributions we introduce reveal universal features of networks. Our studies of collaboration, word-association and protein interaction graphs show that the web of communities has non-trivial correlations and specific scaling properties.Comment: The free academic research software, CFinder, used for the publication is available at the website of the publication: http://angel.elte.hu/clusterin

Quantitative imaging of coronary blood flow

Positron emission tomography (PET) is a nuclear medicine imaging modality based on the administration of a positron-emitting radiotracer, the imaging of the distribution and kinetics of the tracer, and the interpretation of the physiological events and their meaning with respect to health and disease. PET imaging was introduced in the 1970s and numerous advances in radiotracers and detection systems have enabled this modality to address a wide variety of clinical tasks, such as the detection of cancer, staging of Alzheimer's disease, and assessment of coronary artery disease (CAD). This review provides a description of the logic and the logistics of the processes required for PET imaging and a discussion of its use in guiding the treatment of CAD. Finally, we outline prospects and limitations of nanoparticles as agents for PET imaging

MCL-CAw: A refinement of MCL for detecting yeast complexes from weighted PPI networks by incorporating core-attachment structure

Abstract Background The reconstruction of protein complexes from the physical interactome of organisms serves as a building block towards understanding the higher level organization of the cell. Over the past few years, several independent high-throughput experiments have helped to catalogue enormous amount of physical protein interaction data from organisms such as yeast. However, these individual datasets show lack of correlation with each other and also contain substantial number of false positives (noise). Over these years, several affinity scoring schemes have also been devised to improve the qualities of these datasets. Therefore, the challenge now is to detect meaningful as well as novel complexes from protein interaction (PPI) networks derived by combining datasets from multiple sources and by making use of these affinity scoring schemes. In the attempt towards tackling this challenge, the Markov Clustering algorithm (MCL) has proved to be a popular and reasonably successful method, mainly due to its scalability, robustness, and ability to work on scored (weighted) networks. However, MCL produces many noisy clusters, which either do not match known complexes or have additional proteins that reduce the accuracies of correctly predicted complexes. Results Inspired by recent experimental observations by Gavin and colleagues on the modularity structure in yeast complexes and the distinctive properties of "core" and "attachment" proteins, we develop a core-attachment based refinement method coupled to MCL for reconstruction of yeast complexes from scored (weighted) PPI networks. We combine physical interactions from two recent "pull-down" experiments to generate an unscored PPI network. We then score this network using available affinity scoring schemes to generate multiple scored PPI networks. The evaluation of our method (called MCL-CAw) on these networks shows that: (i) MCL-CAw derives larger number of yeast complexes and with better accuracies than MCL, particularly in the presence of natural noise; (ii) Affinity scoring can effectively reduce the impact of noise on MCL-CAw and thereby improve the quality (precision and recall) of its predicted complexes; (iii) MCL-CAw responds well to most available scoring schemes. We discuss several instances where MCL-CAw was successful in deriving meaningful complexes, and where it missed a few proteins or whole complexes due to affinity scoring of the networks. We compare MCL-CAw with several recent complex detection algorithms on unscored and scored networks, and assess the relative performance of the algorithms on these networks. Further, we study the impact of augmenting physical datasets with computationally inferred interactions for complex detection. Finally, we analyse the essentiality of proteins within predicted complexes to understand a possible correlation between protein essentiality and their ability to form complexes. Conclusions We demonstrate that core-attachment based refinement in MCL-CAw improves the predictions of MCL on yeast PPI networks. We show that affinity scoring improves the performance of MCL-CAw.http://deepblue.lib.umich.edu/bitstream/2027.42/78256/1/1471-2105-11-504.xmlhttp://deepblue.lib.umich.edu/bitstream/2027.42/78256/2/1471-2105-11-504-S1.PDFhttp://deepblue.lib.umich.edu/bitstream/2027.42/78256/3/1471-2105-11-504-S2.ZIPhttp://deepblue.lib.umich.edu/bitstream/2027.42/78256/4/1471-2105-11-504.pdfPeer Reviewe

Phytoestrogen intake and other dietary risk factors for low motile sperm count and poor sperm morphology

Background Few potentially modifiable risk factors of male infertility have been identified, and while different diets and food groups have been associated with male infertility, evidence linking dietary factors including phytoestrogens and semen quality is limited and contradictory. Objectives To study the associations between phytoestrogen intake and other dietary factors and semen quality. Materials and Methods A case‐referent study was undertaken of the male partners, of couples attempting conception with unprotected intercourse for 12 months or more without success, recruited from 14 UK assisted reproduction clinics. A total of 1907 participants completed occupational, lifestyle and dietary questionnaires before semen quality (concentration, motility and morphology) were assessed. Food intake was estimated by a 65‐item food frequency questionnaire (FFQ) covering the 12 months prior to recruitment. Analyses of dietary risk factors for low motile sperm concentration (MSC: <4.8 × 106/mL) and poor sperm morphology (PM: <4% normal morphology) used unconditional logistic regression, accounting for clustering of subjects within the clinics, first without, and then with, adjustment for confounders associated with that outcome. Results High consumption of daidzein (≥13.74 μg/d), a phytoestrogen found in soy products, was a protective factor for MSC with an odds ratio (95%CI) of 0.58 (0.42‐0.82) after adjustment for clustering and potential confounding. Dietary risk factors for PM after similar adjustment showed that drinking whole milk (OR 0.67, 95%CI 0.47‐0.96) and eating red meat were protective with an OR 0.67 (0.46‐0.99) for eating red meat >3 times/wk. Discussion In this case‐referent study of men attending an infertility clinic for fertility diagnosis, we have identified that low MSC is inversely associated with daidzein intake. In contrast, daidzein intake was not associated with PM but eating red milk and drinking whole milk were protective. Conclusions Dietary factors associated with semen quality were identified, suggesting that male fertility might be improved by dietary changes

Infectious Disease Ontology

Technological developments have resulted in tremendous increases in the volume and diversity of the data and information that must be processed in the course of biomedical and clinical research and practice. Researchers are at the same time under ever greater pressure to share data and to take steps to ensure that data resources are interoperable. The use of ontologies to annotate data has proven successful in supporting these goals and in providing new possibilities for the automated processing of data and information. In this chapter, we describe different types of vocabulary resources and emphasize those features of formal ontologies that make them most useful for computational applications. We describe current uses of ontologies and discuss future goals for ontology-based computing, focusing on its use in the field of infectious diseases. We review the largest and most widely used vocabulary resources relevant to the study of infectious diseases and conclude with a description of the Infectious Disease Ontology (IDO) suite of interoperable ontology modules that together cover the entire infectious disease domain

Randomized trials of alcohol-use interventions with college students and their parents: lessons from the Transitions Project

Background Matriculation from high school to college is typified by an increase in alcohol use and related harm for many students. Therefore, this transition period is an ideal time for preventive interventions to target alcohol use and related problems

Efficiency of Spermatogonial Dedifferentiation during Aging

Adult stem cells are critical for tissue homeostasis; therefore, the mechanisms utilized to maintain an adequate stem cell pool are important for the survival of an individual. In Drosophila, one mechanism utilized to replace lost germline stem cells (GSCs) is dedifferentiation of early progenitor cells. However, the average number of male GSCs decreases with age, suggesting that stem cell replacement may become compromised in older flies.Using a temperature sensitive allelic combination of Stat92E to control dedifferentiation, we found that germline dedifferentiation is remarkably efficient in older males; somatic cells are also effectively replaced. Surprisingly, although the number of somatic cyst cells also declines with age, the proliferation rate of early somatic cells, including cyst stem cells (CySCs) increases.These data indicate that defects in spermatogonial dedifferentiation are not likely to contribute significantly to an aging-related decline in GSCs. In addition, our findings highlight differences in the ways GSCs and CySCs age. Strategies to initiate or enhance the ability of endogenous, differentiating progenitor cells to replace lost stem cells could provide a powerful and novel strategy for maintaining tissue homeostasis and an alternative to tissue replacement therapy in older individuals

A Kinome RNAi Screen Identified AMPK as Promoting Poxvirus Entry through the Control of Actin Dynamics

Poxviruses include medically important human pathogens, yet little is known about the specific cellular factors essential for their replication. To identify genes essential for poxvirus infection, we used high-throughput RNA interference to screen the Drosophila kinome for factors required for vaccinia infection. We identified seven genes including the three subunits of AMPK as promoting vaccinia infection. AMPK not only facilitated infection in insect cells, but also in mammalian cells. Moreover, we found that AMPK is required for macropinocytosis, a major endocytic entry pathway for vaccinia. Furthermore, we show that AMPK contributes to other virus-independent actin-dependent processes including lamellipodia formation and wound healing, independent of the known AMPK activators LKB1 and CaMKK. Therefore, AMPK plays a highly conserved role in poxvirus infection and actin dynamics independent of its role as an energy regulator

Loss of balancing selection in the βS globin locus

<p>Abstract</p> <p>Background</p> <p>Probably the best example of the rise and maintenance of balancing selection as an evolutionary trend is the role of S-haemoglobin (HbS - rs334) in protecting from malaria. Yet, the dynamics of such a process remains poorly understood, particularly in relation to different malaria transmission rates and the genetic background of the affected populations.</p> <p>Methods</p> <p>We investigated the association of haemoglobin HbS in protection from clinical episodes of malaria in two populations/villages where malaria is endemic, but mostly presenting in mild clinical forms. Five-hundred and forty-six individuals comprising 65 and 82 families from the Hausa and Massalit villages respectively were genotyped for HbS. Allele and genotype frequencies as well as departure from Hardy-Weinberg Equilibrium were estimated from four-hundred and seventy independent genotypes across different age groups. Age-group frequencies were used to calculate the coefficient-of-fitness and to simulate the expected frequencies in future generations.</p> <p>Results</p> <p>Genotype frequencies were within Hardy-Weinberg expectations in Hausa and Massalit in the total sample set but not within the different age groups. There was a trend for a decrease of the HbS allele frequency in Hausa and an increase of frequency in Massalit. Although the HbS allele was able to confer significant protection from the clinical episodes of malaria in the two populations, as suggested by the odds ratios, the overall relative fitness of the HbS allele seems to have declined in Hausa.</p> <p>Conclusions</p> <p>Such loss of balancing selection could be due to a combined effect of preponderance of non-clinical malaria in Hausa, and the deleterious effect of the homozygous HbS under circumstances of endogamy.</p