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PubMed2003

Metabolic networks of microbial systems.

In contrast to bioreactors the metabolites within the microbial cells are converted in an impure atmosphere, yet the productivity seems to be well regulated and not affected by changes in operation variables. These features are attributed to integral metabolic network within the microorganism. With the advent of neo-integrative proteomic approaches the understanding of integration of metabolic and protein-protein interaction networks have began. In this article we review the methods employed to determine the protein-protein interaction and their integration to define metabolite networks. We further present a review of current understanding of network properties, and benefit of studying the networks. The predictions using network structure, for example, in silico experiments help illustrate the importance of studying the network properties. The cells are regarded as complex system but their elements unlike complex systems interact selectively and nonlinearly to produce coherent rather than complex behaviors.

Journal Article↗

PubMed2006

The immune-body cytokine network defines a social architecture of cell interactions.

BACKGROUND: Three networks of intercellular communication can be associated with cytokine secretion; one limited to cells of the immune system (immune cells), one limited to parenchymal cells of organs and tissues (body cells), and one involving interactions between immune and body cells (immune-body interface). These cytokine connections determine the inflammatory response to injury and subsequent healing as well as the biologic consequences of the adaptive immune response to antigens. We informatically probed the cytokine database to uncover the underlying network architecture of the three networks. RESULTS: We now report that the three cytokine networks are among the densest of complex networks yet studied, and each features a characteristic profile of specific three-cell motifs. Some legitimate cytokine connections are shunned (anti-motifs). Certain immune cells can be paired by their input-output positions in a cytokine architecture tree of five tiers: macrophages (MPhi) and B cells (BC) comprise the first tier; the second tier is formed by T helper 1 (Th1) and T helper 2 (Th2) cells; the third tier includes dendritic cells (DC), mast cells (MAST), Natural Killer T cells (NK-T) and others; the fourth tier is formed by neutrophils (NEUT) and Natural Killer cells (NK); and the Cytotoxic T cell (CTL) stand alone as a fifth tier. The three-cell cytokine motif architecture of immune system cells places the immune system in a super-family that includes social networks and the World Wide Web. Body cells are less clearly stratified, although cells involved in wound healing and angiogenesis are most highly interconnected with immune cells. CONCLUSION: Cytokine network architecture creates an innate cell-communication platform that organizes the biologic outcome of antigen recognition and inflammation. Informatics sheds new light on immune-body systems organization. REVIEWERS: This article was reviewed by Neil Greenspan, Matthias von Herrath and Anne Cooke.

Journal Article↗

PubMed2006

Knowledge transfer & exchange through social networks: building foundations for a community of practice within tobacco control.

BACKGROUND: Health services and population health innovations advance when knowledge transfer and exchange (KTE) occurs among researchers, practitioners, policy-makers and consumers using high-quality evidence. However, few KTE models have been evaluated in practice. Communities of practice (CoP) - voluntary, self-organizing, and focused groups of individuals and organizations - may provide one option. This paper outlines an approach to lay the foundation for a CoP within the area of Web-assisted tobacco interventions (WATI). The objectives of the study were to provide a data-driven foundation to inform decisions about organizing a CoP within the geographically diverse, multi-disciplinary WATI group using evaluation and social network methodologies. METHODS: A single-group design was employed using a survey of expectations, knowledge, and interpersonal WATI-related relationships administered prior to a meeting of the WATI group followed by a 3-week post-meeting Web survey to assess short-term impact on learning and networking outcomes. RESULTS: Twenty-three of 27 WATI attendees (85%) from diverse disciplinary and practice backgrounds completed the baseline survey, with 21 (91%) of those participants completing the three-week follow-up. Participants had modest expectations of the meeting at baseline. A social network map produced from the data illustrated a centralized, yet sparse network comprising of interdisciplinary teams with little trans-sectoral collaboration. Three-week follow-up survey results showed that participants had made new network connections and had actively engaged in KTE activities with WATI members outside their original network. CONCLUSION: Data illustrating both the shape and size of the WATI network as well as member's interests and commitment to KTE, when shared and used to frame action steps, can positively influence the motivation to collaborate and create communities of practice. Guiding KTE planning through blending data and theory can create more informed transdisciplinary and trans-sectoral collaboration environments.

Journal Article↗

PubMed2004

Integrating phenotypic and expression profiles to map arsenic-response networks.

BACKGROUND: Arsenic is a nonmutagenic carcinogen affecting millions of people. The cellular impact of this metalloid in Saccharomyces cerevisiae was determined by profiling global gene expression and sensitivity phenotypes. These data were then mapped to a metabolic network composed of all known biochemical reactions in yeast, as well as the yeast network of 20,985 protein-protein/protein-DNA interactions. RESULTS: While the expression data unveiled no significant nodes in the metabolic network, the regulatory network revealed several important nodes as centers of arsenic-induced activity. The highest-scoring proteins included Fhl1, Msn2, Msn4, Yap1, Cad1 (Yap2), Pre1, Hsf1 and Met31. Contrary to the gene-expression analyses, the phenotypic-profiling data mapped to the metabolic network. The two significant metabolic networks unveiled were shikimate, and serine, threonine and glutamate biosynthesis. We also carried out transcriptional profiling of specific deletion strains, confirming that the transcription factors Yap1, Arr1 (Yap8), and Rpn4 strongly mediate the cell's adaptation to arsenic-induced stress but that Cad1 has negligible impact. CONCLUSIONS: By integrating phenotypic and transcriptional profiling and mapping the data onto the metabolic and regulatory networks, we have shown that arsenic is likely to channel sulfur into glutathione for detoxification, leads to indirect oxidative stress by depleting glutathione pools, and alters protein turnover via arsenation of sulfhydryl groups on proteins. Furthermore, we show that phenotypically sensitive pathways are upstream of differentially expressed ones, indicating that transcriptional and phenotypic profiling implicate distinct, but related, pathways.

Arsenic↗

PubMed2005

A compendium of Caenorhabditis elegans regulatory transcription factors: a resource for mapping transcription regulatory networks.

BACKGROUND: Transcription regulatory networks are composed of interactions between transcription factors and their target genes. Whereas unicellular networks have been studied extensively, metazoan transcription regulatory networks remain largely unexplored. Caenorhabditis elegans provides a powerful model to study such metazoan networks because its genome is completely sequenced and many functional genomic tools are available. While C. elegans gene predictions have undergone continuous refinement, this is not true for the annotation of functional transcription factors. The comprehensive identification of transcription factors is essential for the systematic mapping of transcription regulatory networks because it enables the creation of physical transcription factor resources that can be used in assays to map interactions between transcription factors and their target genes. RESULTS: By computational searches and extensive manual curation, we have identified a compendium of 934 transcription factor genes (referred to as wTF2.0). We find that manual curation drastically reduces the number of both false positive and false negative transcription factor predictions. We discuss how transcription factor splice variants and dimer formation may affect the total number of functional transcription factors. In contrast to mouse transcription factor genes, we find that C. elegans transcription factor genes do not undergo significantly more splicing than other genes. This difference may contribute to differences in organism complexity. We identify candidate redundant worm transcription factor genes and orthologous worm and human transcription factor pairs. Finally, we discuss how wTF2.0 can be used together with physical transcription factor clone resources to facilitate the systematic mapping of C. elegans transcription regulatory networks. CONCLUSION: wTF2.0 provides a starting point to decipher the transcription regulatory networks that control metazoan development and function.

Animals↗

PubMed2025

Causal effect of three autoimmune diseases on brain functional networks and cerebrospinal fluid metabolites to underlie the pathogenesis of autoimmune psychosis: a two-sample mendelian randomization analysis.

BACKGROUND: Autoimmune diseases such as Systemic Lupus Erythematosus (SLE), Sjögren's Syndrome (SS), and Hashimoto's Thyroiditis (HT) frequently exhibit neuropsychiatric manifestations, including cognitive impairment, depression, anxiety, and so on, yet the exact pathogenesis underlying this association remain incompletely understood. Dysfunction of brain resting-state functional networks and cerebrospinal fluid (CSF) metabolite disturbances have been widely reported in psychiatric disorders. However, the application of resting-state functional magnetic resonance imaging (rsfMRI) and CSF metabolomics in the diagnosis and monitoring of autoimmune psychosis is still limited. METHODS: A two-sample Mendelian randomization (MR) analysis was performed to investigate the causal relationships between three autoimmune diseases (SLE, SS, and HT, n = 14,267 to 402,090 individuals) and 191 rsfMRI phenotypes (n = 47,276 individuals), as well as 338 CSF metabolites. The genome-wide association study (GWAS) of three autoimmune diseases was used as the exposure, whereas rsfMRI phenotypes and 338 CSF metabolites were treated as the outcome. Inverse variance weighted (IVW) with P value < 0.05 was regarded as the primary approach for calculating causal estimates. Additionally, the false discovery rate (FDR)-adjusted P value (PFDR) < 0.05 was utilized to account for multiple testing. MR Egger method, weighted median method, simple mode method and weighted mode method were used for sensitive analysis. RESULTS: Our analyses identified 5 causal relationships between SLE and the 191 rsfMRI phenotypes, 48 between SS and the 191 rsfMRI phenotypes, and 4 between HT and the 191 rsfMRI phenotypes. Additionally, we found 8 causal relationships between HT and CSF metabolites. Furthermore, all three diseases were significantly associated with the temporal lobe and triple networks (default mode network (DMN), salience network (SN), and central executive network (CEN)), which are the core brain regions and functional networks for cognition. Following FDR correction, 6 causal relationships between SS and the 191 rsfMRI phenotypes were further validated. CONCLUSIONS: Our study pinpoints important brain functional networks and CSF metabolites potentially implicated in the pathogenesis of psychiatric disorders associated with autoimmune diseases and highlights critical brain regions for the development of novel therapeutics.

Humans↗

PubMed1983

Community networking for improved services to children with chronic illnesses and their families.

The authors describe a program, developed under the auspices of the Association for the Care of Children's Health (ACCH), that focuses on community networking among children with chronic illnesses and their families. The program rests on two beliefs: (a) that a network can successfully focus on the generic needs of children with chronic or handicapping conditions and of their families; and (b) that a network can improve care by enhancing coordinating collaboration among existing services without creating new ones. Efforts of the past two years have centered on three specific areas: preparation and dissemination of written materials; creation of new links among families, health and education professionals, organizations, associations, and community institutions; and training in networking techniques. ACCH has prepared two pamphlets for families, schools, and health professionals on community issues and on hospitalization. In addition, a demonstration model for community networking has been established in the Houston/Galveston area. Finally, training programs in the skills of community networking have been established. Work is beginning to replicate the community networking model through other ACCH regional affiliates.

Child↗

PubMed2001

Paranemin and the organization of desmin filament networks.

De novo expression of vimentin, GFAP or peripherin leads to the assembly of an extended intermediate filament network in intermediate filament-free SW13/cl.2 cells. Desmin, in contrast, does not form extended filament networks in either SW13/cl.2 or intermediate filament-free mouse fibroblasts. Rather, desmin formed short thickened filamentous structures and prominent spot-like cytoplasmic aggregates that were composed of densely packed 9-11 nm diameter filaments. Analysis of stably transfected cell lines indicates that the inability of desmin to form extended networks is not due to a difference in the level of transgene expression. Nestin, paranemin and synemin are large intermediate filament proteins that coassemble with desmin in muscle cells. Although each of these large intermediate filament proteins colocalized with desmin when coexpressed in SW-13 cells, expression of paranemin, but not synemin or nestin, led to the formation of an extended desmin network. A similar rescue of desmin network organization was observed when desmin was coexpressed with vimentin, which coassembles with desmin, or with keratins, which formed a distinct filament network. These studies demonstrate that desmin filaments differ in their organizational properties from the other vimentin-like intermediate filament proteins and appear to depend upon coassembly with paranemin, at least when they are expressed in non-muscle cells, in order to form an extended filament network.

Avian Proteins↗

PubMed2006

HIV risk behaviour patterns, predictors, and sexually transmitted disease prevalence in the social networks of young men who have sex with men in St Petersburg, Russia.

HIV seroconversions and sexually transmitted diseases (STDs) are often clustered in social networks within community populations. The present study was carried out among men who have sex with men in Russia, where a major HIV epidemic is unfolding, and where social networks have played a historically important role. In all, 38 social networks were recruited into the study, and members of all networks (n = 187) completed risk behaviour assessments and were tested for STDs. About 17% of participants had STDs, and 10% of men had syphilis. Over 64% of men had recent unprotected anal intercourse (UAI), including 51% who did so with main partners, 30% who did so with casual partners, and 32% who had UAI with multiple male partners. The strongest predictor of all risk behaviour indicators and STDs was the social network, to which an individual belonged, supplemented by peer norm perceptions and intentions to practise safer sex. There was a high level of correspondence in behaviour between the social leader of a network and its other members. Social networks should be directly targeted in HIV prevention efforts.

Adult↗

PubMed2004

The TAO-Gen algorithm for identifying gene interaction networks with application to SOS repair in E. coli.

One major unresolved issue in the analysis of gene expression data is the identification and quantification of gene regulatory networks. Several methods have been proposed for identifying gene regulatory networks, but these methods predominantly focus on the use of multiple pairwise comparisons to identify the network structure. In this article, we describe a method for analyzing gene expression data to determine a regulatory structure consistent with an observed set of expression profiles. Unlike other methods this method goes beyond pairwise evaluations by using likelihood-based statistical methods to obtain the network that is most consistent with the complete data set. The proposed algorithm performs accurately for moderate-sized networks with most errors being minor additions of linkages. However, the analysis also indicates that sample sizes may need to be increased to uniquely identify even moderate-sized networks. The method is used to evaluate interactions between genes in the SOS signaling pathway in Escherichia coli using gene expression data where each gene in the network is over-expressed using plasmids inserts.

Algorithms↗

PubMed1983

Towards more effective intervention in natural helping networks.

Fiscal constraints which are promoting a retreat from social welfare programming place increasing responsibility for care on natural helping networks of family and friends. Research has identified several characteristics of informal networks which are associated with support such as density, reciprocity, homogeneity, and multiplexity. Professional interventions have also responded to the potential supports available in networks. Professional practice concentrates primarily on self-help groups and the use of key persons in networks. There is, however, little correspondence between research findings and professional approaches to intervention. Little has been done to determine the possible impact of formal service provision on the dynamics of informal networks. More effective intervention in informal networks must consider the limitations of current practice, the development of assessment instruments, and the changes in network structures and processes over time.

Aged↗

PubMed2002

Social networks and changes in contraceptive use over time: evidence from a longitudinal study in rural Kenya.

The impacts of social networks on changes in contraception in rural Kenya are investigated using special data from a longitudinal household survey. An analytic model, informed by detailed knowledge of the setting, yielded estimates that indicate that (1) social networks have substantial effects even after unobserved factors (e.g., homophily) that may determine social networks are controlled; (2) controlling for these unobserved factors may substantially alter the estimated effects of networks (these controls were not used in previous studies); (3) network effects are important for both men and women; and (4) network effects are nonlinear and asymmetric, suggesting that networks provide information primarily through social learning, rather than by exerting social influence.

Contraception Behavior↗

PubMed2003

Engendering migrant networks: the case of Mexican migration.

This article compares the impact of family migrant and destination-specific networks on international and internal migration. We find that migrant networks are more important for international moves than for internal moves and that female networks are more important than male networks for moves within Mexico. For moves to the United States, male migrant networks are more important for prospective male migrants than for female migrants, and female migrant networks lower the odds of male migration, but significantly increase female migration. We suggest that distinguishing the gender composition and destination content of migrant networks deepens our understanding of how cumulative causation affects patterns of Mexican migration.

Adolescent↗

PubMed2005

Egocentric HIV risk networks among Puerto Rican crack users in New York and in Puerto Rico: impact on sex risk behaviors over time.

This study examined risk network characteristics of Puerto Rican crack users and the relationship between the network and HIV-related sex risk behavior over time. The participants (N = 383 in New York; N = 165 in Puerto Rico), recruited through street outreach, were interviewed at both baseline and 6-month follow-up. The majority of crack users (88%, New York; 92%, Puerto Rico) in the sample named one or more personal risk network members. As compared with New York participants, crack users in Puerto Rico reported larger risk networks and were more likely to engage in sex risk behaviors with strangers or acquaintances. In multivariate analyses, a significant variable in predicting sex risk behaviors at follow-up in both sites was the baseline measure of the dependent variable. Significant network variables were: having any known crack use member less than 6 months and having acquaintance/stranger in network in New York; communicating with network members about using condoms in Puerto Rico. More attention to sex risk behaviors are needed in HIV/AIDS prevention and education programs.

Adult↗

PubMed2004

Properties of metabolic networks: structure versus function.

Biological data from high-throughput technologies describing the network components (genes, proteins, metabolites) and their associated interactions have driven the reconstruction and study of structural (topological) properties of large-scale biological networks. In this article, we address the relation of the functional and structural properties by using extensively experimentally validated genome-scale metabolic network models to compute observable functional states of a microorganism and compare the "structure versus function" attributes of metabolic networks. It is observed that, functionally speaking, the essentiality of reactions in a node is not correlated with node connectivity as structural analyses of other biological networks have suggested. These findings are illustrated with the analysis of the genome-scale biochemical networks of three species with distinct modes of metabolism. These results also suggest fundamental differences among different biological networks arising out of their representation and functional constraints.

Algorithms↗

PubMed2000

Late effects of ionizing radiation on the microvascular networks in normal tissue.

Damage to the microvascular networks constitutes one of the most important components of ionizing radiation damage to normal tissue. Previously, we have reported the early (3, 7 and 30 days postirradiation) effects of ionizing radiation on the structure and function of normal tissue microvascular networks. Here we report on the late effects of ionizing radiation on the structural and functional changes in microvascular networks in locally irradiated (single 10-Gy dose) hamster cremaster muscles observed 60, 120 and 180 days postirradiation; age-matched animals were used as controls. As in the previous study, intravital microscopy was used to measure structural and functional parameters in complete microvascular networks in vivo. A factorial design was used to examine the effects of radiation status, time postirradiation, and network vessel type on the structure and function of microvascular networks. Our results indicate that the progression of radiation-induced microvascular damage continues during the late times but that there is partial recovery from radiation damage within 6 months postirradiation. Red blood cell flux, red blood cell velocity, and capillary blood flow in irradiated networks at 180 days postirradiation were significantly greater than control levels. As at the early times, all vessel types were not damaged equally by radiation at every time.

Animals↗

PubMed1988

Autonomic nerve networks in the rat exocrine pancreas as revealed by scanning and transmission electron microscopy.

The three-dimensional architecture of the autonomic nerve terminals in the rat exocrine pancreas was investigated by scanning electron microscopy using the HCl-digestion method as well as by transmission electron microscopy. Unmyelinated nerves presumed to be autonomic in nature were found in networks covering the outer layers of arterioles and their capillary extensions, with nerve fibers often leaving the capillaries to surround acini in the interacinar spaces. Schwann cells formed scaffolds for axons of the networks. No other distinct type of cells such as the so-called interstitial cells of Cajal were found to be associated with the formation of the networks. Although nerve fibers of the networks were locally in close association with the walls of the blood vessels or with the bases of acinar cells, no specialized axonal contacts with these tissues were found. However, local swellings, presumably varicosities, were observed by scanning electron microscopy on the surface of nerves. These findings suggest that the networks of unmyelinated nerves represent terminal apparatuses of the autonomic nerves in the pancreas. Schwann cells in the terminal networks were characterized by an unusual abundance of cell organelles. These "terminal Schwann cells" well correspond in location and reticular extension to the "interstitial cells of Cajal" as demonstrated by silver impregnation and vital methylene blue staining. The occurrence of well developed Golgi apparatuses, rough endoplasmic reticulum, and numerous ribosomes suggests that the cells are specialized Schwann cells which most likely require high levels of cellular activity in order to maintain their elaborate cytoplasmic processes extending along the terminal networks, and also to sustain the specific functions of axon terminals.

Animals↗

PubMed2005

A general framework for weighted gene co-expression network analysis.

Gene co-expression networks are increasingly used to explore the system-level functionality of genes. The network construction is conceptually straightforward: nodes represent genes and nodes are connected if the corresponding genes are significantly co-expressed across appropriately chosen tissue samples. In reality, it is tricky to define the connections between the nodes in such networks. An important question is whether it is biologically meaningful to encode gene co-expression using binary information (connected=1, unconnected=0). We describe a general framework for ;soft' thresholding that assigns a connection weight to each gene pair. This leads us to define the notion of a weighted gene co-expression network. For soft thresholding we propose several adjacency functions that convert the co-expression measure to a connection weight. For determining the parameters of the adjacency function, we propose a biologically motivated criterion (referred to as the scale-free topology criterion). We generalize the following important network concepts to the case of weighted networks. First, we introduce several node connectivity measures and provide empirical evidence that they can be important for predicting the biological significance of a gene. Second, we provide theoretical and empirical evidence that the ;weighted' topological overlap measure (used to define gene modules) leads to more cohesive modules than its ;unweighted' counterpart. Third, we generalize the clustering coefficient to weighted networks. Unlike the unweighted clustering coefficient, the weighted clustering coefficient is not inversely related to the connectivity. We provide a model that shows how an inverse relationship between clustering coefficient and connectivity arises from hard thresholding. We apply our methods to simulated data, a cancer microarray data set, and a yeast microarray data set.

Journal Article↗