Network Physiology reveals relations between network topology and physiological function

The human organism is an integrated network where complex physiologic systems, each with its own regulatory mechanisms, continuously interact, and where failure of one system can trigger a breakdown of the entire network. Identifying and quantifying dynamical networks of diverse systems with different types of interactions is a challenge. Here, we develop a framework to probe interactions among diverse systems, and we identify a physiologic network. We find that each physiologic state is characterized by a specific network structure, demonstrating a robust interplay between network topology and function. Across physiologic states the network undergoes topological transitions associated with fast reorganization of physiologic interactions on time scales of a few minutes, indicating high network flexibility in response to perturbations. The proposed system-wide integrative approach may facilitate the development of a new field, Network Physiology.Comment: 12 pages, 9 figure

Social representations and community attitudes towards spring breakers

Social representations theory has been adopted for explaining tourism impacts and local attitudes. However, its usefulness in segmenting local population in terms of their attitudes towards specific types of tourists has not been tested. This study identifies the attitudes of local people towards spring break, a North American young tourist phenomenon in the context of the Mexican beach resort of Acapulco. Although residents perceive an increase in alcohol consumption, drug use, noise and litter during the spring break season, they largely recognise economic benefits and are thus generally supportive for the phenomenon. Based on these attitudes, three clusters were identified: spring break supporters (identified by their high appreciation of spring break benefits), ambivalents (who are uncertain about both benefits and costs) and realistics (characterised by recognising both benefits and costs). The main contribution of this study lies in the confirmation of the usefulness of social representations theory in explaining residents’ attitudes towards a very specific type of tourists whose hedonist behaviours are a common characteristic

Introduction of an agent-based multi-scale modular architecture for dynamic knowledge representation of acute inflammation

<p>Abstract</p> <p>Background</p> <p>One of the greatest challenges facing biomedical research is the integration and sharing of vast amounts of information, not only for individual researchers, but also for the community at large. Agent Based Modeling (ABM) can provide a means of addressing this challenge via a unifying translational architecture for dynamic knowledge representation. This paper presents a series of linked ABMs representing multiple levels of biological organization. They are intended to translate the knowledge derived from in vitro models of acute inflammation to clinically relevant phenomenon such as multiple organ failure.</p> <p>Results and Discussion</p> <p>ABM development followed a sequence starting with relatively direct translation from in-vitro derived rules into a cell-as-agent level ABM, leading on to concatenated ABMs into multi-tissue models, eventually resulting in topologically linked aggregate multi-tissue ABMs modeling organ-organ crosstalk. As an underlying design principle organs were considered to be functionally composed of an epithelial surface, which determined organ integrity, and an endothelial/blood interface, representing the reaction surface for the initiation and propagation of inflammation. The development of the epithelial ABM derived from an in-vitro model of gut epithelial permeability is described. Next, the epithelial ABM was concatenated with the endothelial/inflammatory cell ABM to produce an organ model of the gut. This model was validated against in-vivo models of the inflammatory response of the gut to ischemia. Finally, the gut ABM was linked to a similarly constructed pulmonary ABM to simulate the gut-pulmonary axis in the pathogenesis of multiple organ failure. The behavior of this model was validated against in-vivo and clinical observations on the cross-talk between these two organ systems</p> <p>Conclusion</p> <p>A series of ABMs are presented extending from the level of intracellular mechanism to clinically observed behavior in the intensive care setting. The ABMs all utilize cell-level agents that encapsulate specific mechanistic knowledge extracted from in vitro experiments. The execution of the ABMs results in a dynamic representation of the multi-scale conceptual models derived from those experiments. These models represent a qualitative means of integrating basic scientific information on acute inflammation in a multi-scale, modular architecture as a means of conceptual model verification that can potentially be used to concatenate, communicate and advance community-wide knowledge.</p

Broadening INPP5E phenotypic spectrum: detection of rare variants in syndromic and non-syndromic IRD

Pathogenic variants in INPP5E cause Joubert syndrome (JBTS), a ciliopathy with retinal involvement. However, despite sporadic cases in large cohort sequencing studies, a clear association with non-syndromic inherited retinal degenerations (IRDs) has not been made. We validate this association by reporting 16 non-syndromic IRD patients from ten families with bi-allelic mutations in INPP5E. Additional two patients showed early onset IRD with limited JBTS features. Detailed phenotypic description for all probands is presented. We report 14 rare INPP5E variants, 12 of which have not been reported in previous studies. We present tertiary protein modeling and analyze all INPP5E variants for deleteriousness and phenotypic correlation. We observe that the combined impact of INPP5E variants in JBTS and non-syndromic IRD patients does not reveal a clear genotype–phenotype correlation, suggesting the involvement of genetic modifiers. Our study cements the wide phenotypic spectrum of INPP5E disease, adding proof that sequence defects in this gene can lead to early-onset non-syndromic IRD

CB2 Cannabinoid Receptors Contribute to Bacterial Invasion and Mortality in Polymicrobial Sepsis

BACKGROUND:Sepsis is a major healthcare problem and current estimates suggest that the incidence of sepsis is approximately 750,000 annually. Sepsis is caused by an inability of the immune system to eliminate invading pathogens. It was recently proposed that endogenous mediators produced during sepsis can contribute to the immune dysfunction that is observed in sepsis. Endocannabinoids that are produced excessively in sepsis are potential factors leading to immune dysfunction, because they suppress immune cell function by binding to G-protein-coupled CB(2) receptors on immune cells. Here we examined the role of CB(2) receptors in regulating the host's response to sepsis. METHODS AND FINDINGS:The role of CB(2) receptors was studied by subjecting CB(2) receptor wild-type and knockout mice to bacterial sepsis induced by cecal ligation and puncture. We report that CB(2) receptor inactivation by knockout decreases sepsis-induced mortality, and bacterial translocation into the bloodstream of septic animals. Furthermore, CB(2) receptor inactivation decreases kidney and muscle injury, suppresses splenic nuclear factor (NF)-kappaB activation, and diminishes the production of IL-10, IL-6 and MIP-2. Finally, CB(2) receptor deficiency prevents apoptosis in lymphoid organs and augments the number of CD11b(+) and CD19(+) cells during CLP. CONCLUSIONS:Taken together, our results establish for the first time that CB(2) receptors are important contributors to septic immune dysfunction and mortality, indicating that CB(2) receptors may be therapeutically targeted for the benefit of patients suffering from sepsis

Standing genetic variation and compensatory evolution in transgenic organisms: a growth-enhanced salmon simulation

Genetically modified strains usually are generated within defined genetic backgrounds to minimize variation for the engineered characteristic in order to facilitate basic research investigations or for commercial application. However, interactions between transgenes and genetic background have been documented in both model and commercial agricultural species, indicating that allelic variation at transgene-modifying loci are not uncommon in genomes. Engineered organisms that have the potential to allow entry of transgenes into natural populations may cause changes to ecosystems via the interaction of their specific phenotypes with ecosystem components and services. A transgene introgressing through natural populations is likely to encounter a range of natural genetic variation (among individuals or sub-populations) that could result in changes in phenotype, concomitant with effects on fitness and ecosystem consequences that differ from that seen in the progenitor transgenic strain. In the present study, using a growth hormone transgenic salmon example, we have modeled selection of modifier loci (single and multiple) in the presence of a transgene and have found that accounting for genetic background can significantly affect the persistence of transgenes in populations, potentially reducing or reversing a “Trojan gene” effect. Influences from altered life history characteristics (e.g., developmental timing, age of maturation) and compensatory demographic/ecosystem controls (e.g., density dependence) also were found to have a strong influence on transgene effects. Further, with the presence of a transgene in a population, genetic backgrounds were found to shift in non-transgenic individuals as well, an effect expected to direct phenotypes away from naturally selected optima. The present model has revealed the importance of understanding effects of selection for background genetics on the evolution of phenotypes in populations harbouring transgenes