Leadership in complex networks: the importance of network position and strategic action in a translational cancer research network

BackgroundLeadership behaviour in complex networks is under-researched, and little has been written concerning leadership of translational research networks (TRNs) that take discoveries made ‘at the bench’ and translate them into practices used ‘at the bedside.’ Understanding leaders’ opportunities and behaviours within TRNs working to solve this key problem in implementing evidence into clinical practice is therefore important. This study explored the network position of governing body members and perceptions of their role in a new TRN in Sydney, Australia. The paper asks three questions: Firstly, do the formal, mandated leaders of this TRN hold key positions of centrality or brokerage in the informal social network of collaborative ties? Secondly, if so, do they recognise the leadership opportunities that their network positions afford them? Thirdly, what activities associated with these key roles do they believe will maximise the TRN’s success? MethodsSemi-structured interviews of all 14 governing body members conducted in early 2012 explored perceptions of their roles and sought comments on a list of activities drawn from review of successful transdisciplinary collaboratives combined with central and brokerage roles. An on-line, whole network survey of all 68 TRN members sought to understand and map existing collaborative connections. Leaders’ positions in the network were assessed using UCInet, and graphs were generated in NetDraw. ResultsSocial network analysis identified that governing body members had high centrality and high brokerage potential in the informal network of work-related ties. Interviews showed perceived challenges including ‘silos’ and the mismatch between academic and clinical goals of research. Governing body members recognised their central positions, which would facilitate the leadership roles of leading, making decisions, and providing expert advice necessary for the co-ordination of effort and relevant input across domains. Brokerage potential was recognised in their clearly understood role of representing a specialty, campus or research group on the governing body to provide strategic linkages. Facilitation, mentoring and resolving conflicts within more localised project teams were spoken of as something ‘we do all the time anyway,’ as well as something they would do if called upon. These leadership roles are all linked with successful collaborative endeavours in other fields. ConclusionsThis paper links the empirical findings of the social network analysis with the qualitative findings of the interviews to show that the leaders’ perceptions of their roles accord with both the potential inherent in their network positions as well as actual activities known to increase the success of transdisciplinary teams. Understanding this is key to successful TRNs

The quality control theory of aging

The quality control (QC) theory of aging is based on the concept that aging is the result of a reduction in QC of cellular systems designed to maintain lifelong homeostasis. Four QC systems associated with aging are 1) inadequate protein processing in a distressed endoplasmic reticulum (ER); 2) histone deacetylase (HDAC) processing of genomic histones and gene silencing; 3) suppressed AMPK nutrient sensing with inefficient energy utilization and excessive fat accumulation; and 4) beta-adrenergic receptor (BAR) signaling and environmental and emotional stress. Reprogramming these systems to maintain efficiency and prevent aging would be a rational strategy for increased lifespan and improved health. The QC theory can be tested with a pharmacological approach using three well-known and safe, FDA-approved drugs: 1) phenyl butyric acid, a chemical chaperone that enhances ER function and is also an HDAC inhibitor, 2) metformin, which activates AMPK and is used to treat type 2 diabetes, and 3) propranolol, a beta blocker which inhibits BAR signaling and is used to treat hypertension and anxiety. A critical aspect of the QC theory, then, is that aging is associated with multiple cellular systems that can be targeted with drug combinations more effectively than with single drugs. But more importantly, these drug combinations will effectively prevent, delay, or reverse chronic diseases of aging that impose such a tremendous health burden on our society

Does prior acute exercise affect postexercise substrate oxidation in response to a high carbohydrate meal?

<p>Abstract</p> <p>Background</p> <p>Consumption of a mixed meal increases postprandial carbohydrate utilization and decreases fat oxidation. On the other hand, acute endurance exercise increases fat oxidation and decreases carbohydrate utilization during the post-exercise recovery period. It is possible that the resulting post-exercise increase in circulating nonesterified fatty acids could attenuate the ability of ingested carbohydrate to inhibit lipid oxidation. The purpose of this study was to determine whether prior exercise attenuates the usual meal-induced decline in lipid oxidation.</p> <p>Methods</p> <p>Six healthy, physically active young subjects (x age = 26.3 years, 4 males, 2 females) completed three treatments in random order after a ~10 h fast: (a) Exercise/Carbohydrate (Ex/CHO) – subjects completed a bout of exercise at 70% VO_2peak(targeted net energy cost of 400 kcals), followed by consumption of a carbohydrate-rich meal; (b) Exercise/Placebo (Ex/Placebo) – subjects completed an identical bout of exercise followed by consumption of a placebo; and (c) No Exercise/Carbohydrate (NoEx/CHO) – subjects sat quietly rather than exercising and then consumed the carbohydrate-rich meal. Blood samples were obtained before and during the postprandial period to determine plasma glucose, insulin, and non-esterified fatty acids (NEFA). Respiratory gas exchange measures were used to estimate rates of fat and carbohydrate oxidation.</p> <p>Results</p> <p>Plasma NEFA were approximately two-fold higher immediately following the two exercise conditions compared to the no-exercise condition, while meal consumption significantly increased insulin and glucose in both Ex/CHO and NoEx/CHO. NEFA concentrations fell rapidly during the 2-h postprandial period, but remained higher compared to the NoEx/CHO treatment. Carbohydrate oxidation increased rapidly and fat oxidation decreased in response to the meal, with no differences in the rates of carbohydrate and fat oxidation during recovery between the Ex/CHO and NoEx/CHO conditions.</p> <p>Conclusion</p> <p>The plasma NEFA concentration is increased during the post exercise period, which is associated with elevated fat oxidation when no meal is consumed. However, when a mixed meal is consumed immediately following exercise, the initially elevated plasma NEFA concentration decreases rapidly, and postexercise fat oxidation during this 2-h postexercise, postprandial period is no higher than that of the 2-h postprandial period without prior exercise.</p

Scaling of swimming performance in baleen whales

The scale dependence of locomotor factors has long been studied in comparative biomechanics, but remains poorly understood for animals at the upper extremes of body size. Rorqual baleen whales include the largest animals, but we lack basic kinematic data about their movements and behavior below the ocean surface. Here, we combined morphometrics from aerial drone photogrammetry, whale-borne inertial sensing tag data and hydrodynamic modeling to study the locomotion of five rorqual species. We quantified changes in tail oscillatory frequency and cruising speed for individual whales spanning a threefold variation in body length, corresponding to an order of magnitude variation in estimated body mass. Our results showed that oscillatory frequency decreases with body length (proportional to length(-0.5)(3)) while cruising speed remains roughly invariant (proportional to length(0.08)) at 2 m s(-1). We compared these measured results for oscillatory frequency against simplified models of an oscillating cantilever beam (proportional to length(-1)) and an optimized oscillating Strouhal vortex generator (proportional to length(-1)). The difference between our length-scaling exponent and the simplified models suggests that animals are often swimming non-optimally in order to feed or perform other routine behaviors. Cruising speed aligned more closely with an estimate of the optimal speed required to minimize the energetic cost of swimming (proportional to length(-1)). Our results are among the first to elucidate the relationships between both oscillatory frequency and cruising speed and body size for free-swimming animals at the largest scale

Cannabis sativa and the endogenous cannabinoid system: therapeutic potential for appetite regulation

The herb Cannabis sativa (C. sativa) has been used in China and on the Indian subcontinent for thousands of years as a medicine. However, since it was brought to the UK and then the rest of the western world in the late 19th century, its use has been a source of controversy. Indeed, its psychotropic side effects are well reported but only relatively recently has scientific endeavour begun to find valuable uses for either the whole plant or its individual components. Here, we discuss evidence describing the endocannabinoid system, its endogenous and exogenous ligands and their varied effects on feeding cycles and meal patterns. Furthermore we also critically consider the mounting evidence which suggests non‐tetrahydrocannabinol phytocannabinoids play a vital role in C. sativa‐induced feeding pattern changes. Indeed, given the wide range of phytocannabinoids present in C. sativa and their equally wide range of intra‐, inter‐ and extra‐cellular mechanisms of action, we demonstrate that non‐Δ9tetrahydrocannabinol phytocannabinoids retain an important and, as yet, untapped clinical potential

Factors associated with initiation and completion of the quadrivalent human papillomavirus vaccine series in an ontario cohort of grade 8 girls

Abstract Background Although over a hundred million dollars have been invested in offering free quadrivalent human papillomavirus (HPV) vaccination to young girls in Ontario, there continues to be very little information about its usage. In order to successfully guide future HPV vaccine programming, it is important to monitor HPV vaccine use and determine factors associated with use in this population. Methods Linking administrative health and immunization databases, we conducted a population-based, retrospective cohort study of girls eligible for Ontario's Grade 8 HPV vaccination program in Kingston, Frontenac, Lennox, and Addington. We determined the proportion of girls who initiated (at least one dose) and completed (all three doses) the vaccination series overall and according to socio-demographics, vaccination history, health services utilization, medical history, and program year. Multivariable logistic regression was used to estimate the strength of association between individual factors and initiation and completion, adjusted for all other factors. Results We identified a cohort of 2519 girls, 56.6% of whom received at least one dose of the HPV vaccine. Among vaccinated girls, 85.3% received all three doses. Vaccination history was the strongest predictor of initiation in that girls who received the measles-mumps-rubella, meningococcal C, and hepatitis B vaccines were considerably more likely to also receive the HPV vaccine (odds ratio 4.89; 95% confidence interval 4.04-5.92). Nevertheless, HPV vaccine uptake was more than 20% lower than that of these other vaccines. In addition, while series initiation was not influenced by income, series completion was. In particular, girls of low income were the least likely to receive all three indicated doses of the HPV vaccine (odds ratio 0.45; 95% confidence interval 0.28-0.72). Conclusions The current low level of HPV vaccine acceptance in Kingston, Frontenac, Lennox, and Addington will likely have important implications in terms of the health benefits and cost-effectiveness of its publicly funded program. We identified important factors associated with series initiation and completion that should be considered in efforts to improve HPV vaccine use in this population

Signal transducer and activator of transcription 1 (STAT1) gain-of-function mutations and disseminated coccidioidomycosis and histoplasmosis

Background: Impaired signaling in the IFN-g/IL-12 pathway causes susceptibility to severe disseminated infections with mycobacteria and dimorphic yeasts. Dominant gain-of-function mutations in signal transducer and activator of transcription 1 (STAT1) have been associated with chronic mucocutaneous candidiasis. Objective: We sought to identify the molecular defect in patients with disseminated dimorphic yeast infections. Methods: PBMCs, EBV-transformed B cells, and transfected U3A cell lines were studied for IFN-g/IL-12 pathway function. STAT1 was sequenced in probands and available relatives. Interferon-induced STAT1 phosphorylation, transcriptional responses, protein-protein interactions, target gene activation, and function were investigated. Results: We identified 5 patients with disseminated Coccidioides immitis or Histoplasma capsulatum with heterozygous missense mutations in the STAT1 coiled-coil or DNA-binding domains. These are dominant gain-of-function mutations causing enhanced STAT1 phosphorylation, delayed dephosphorylation, enhanced DNA binding and transactivation, and enhanced interaction with protein inhibitor of activated STAT1. The mutations caused enhanced IFN-g–induced gene expression, but we found impaired responses to IFN-g restimulation. Conclusion: Gain-of-function mutations in STAT1 predispose to invasive, severe, disseminated dimorphic yeast infections, likely through aberrant regulation of IFN-g–mediated inflammationFil: Sampaio, Elizabeth P.. National Institutes of Health. National Institute of Allergy and Infectious Diseases. Laboratory of Clinical Infectious Diseases. Immunopathogenesis Section; Estados Unidos. Instituto Oswaldo Cruz. Laboratorio de Leprologia; BrasilFil: Hsu, Amy P.. National Institutes of Health. National Institute of Allergy and Infectious Diseases. Laboratory of Clinical Infectious Diseases. Immunopathogenesis Section; Estados UnidosFil: Pechacek, Joseph. National Institutes of Health. National Institute of Allergy and Infectious Diseases. Laboratory of Clinical Infectious Diseases. Immunopathogenesis Section; Estados UnidosFil: Hannelore I.. National Institutes of Health. National Institute of Allergy and Infectious Diseases. Laboratory of Clinical Infectious Diseases. Immunopathogenesis Section; Estados Unidos. Erasmus Medical Center. Department of Medical Microbiology and Infectious Disease; Países BajosFil: Dias, Dalton L.. National Institutes of Health. National Institute of Allergy and Infectious Diseases. Laboratory of Clinical Infectious Diseases. Immunopathogenesis Section; Estados UnidosFil: Paulson, Michelle L.. Clinical Research Directorate/CMRP; Estados UnidosFil: Chandrasekaran, Prabha. National Institutes of Health. National Institute of Allergy and Infectious Diseases. Laboratory of Clinical Infectious Diseases. Immunopathogenesis Section; Estados UnidosFil: Rosen, Lindsey B.. National Institutes of Health. National Institute of Allergy and Infectious Diseases. Laboratory of Clinical Infectious Diseases. Immunopathogenesis Section; Estados UnidosFil: Carvalho, Daniel S.. National Institutes of Health. National Institute of Allergy and Infectious Diseases. Laboratory of Clinical Infectious Diseases. Immunopathogenesis Section; Estados Unidos. Instituto Oswaldo Cruz, Laboratorio de Leprologia; BrasilFil: Ding, Li. National Institutes of Health. National Institute of Allergy and Infectious Diseases. Laboratory of Clinical Infectious Diseases. Immunopathogenesis Section; Estados UnidosFil: Vinh, Donald C.. McGill University Health Centre. Division of Infectious Diseases; CanadáFil: Browne, Sarah K.. National Institutes of Health. National Institute of Allergy and Infectious Diseases. Laboratory of Clinical Infectious Diseases. Immunopathogenesis Section; Estados UnidosFil: Datta, Shrimati. National Institutes of Health. National Institute of Allergy and Infectious Diseases. Laboratory of Allergic Diseases. Allergic Inflammation Unit; Estados UnidosFil: Milner, Joshua D.. National Institutes of Health. National Institute of Allergy and Infectious Diseases. Laboratory of Allergic Diseases. Allergic Inflammation Unit; Estados UnidosFil: Kuhns, Douglas B.. Clinical Services Program; Estados UnidosFil: Long Priel, Debra A.. Clinical Services Program; Estados UnidosFil: Sadat, Mohammed A.. National Institutes of Health. National Institute of Allergy and Infectious Diseases. Laboratory of Host Defenses. Infectious Diseases Susceptibility Unit; Estados UnidosFil: Shiloh, Michael. University of Texas. Southwestern Medical Center. Division of Infectious Diseases; Estados UnidosFil: De Marco, Brendan. University of Texas. Southwestern Medical Center. Division of Infectious Diseases; Estados UnidosFil: Alvares, Michael. University of Texas. Southwestern Medical Center. Division of Allergy and Immunology; Estados UnidosFil: Gillman, Jason W.. University of Texas. Southwestern Medical Center. Division of Infectious Diseases; Estados UnidosFil: Ramarathnam, Vivek. University of Texas. Southwestern Medical Center. Division of Infectious Diseases; Estados UnidosFil: de la Morena, Maite. University of Texas. Southwestern Medical Center. Division of Allergy and Immunology; Estados UnidosFil: Bezrodnik, Liliana. Gobierno de la Ciudad de Buenos Aires. Hospital General de Niños "Ricardo Gutierrez"; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Moreira, Ileana. Gobierno de la Ciudad de Buenos Aires. Hospital General de Niños "Ricardo Gutierrez"; ArgentinaFil: Uzel, Gulbu. National Institutes of Health. National Institute of Allergy and Infectious Diseases. Laboratory of Clinical Infectious Diseases. Immunopathogenesis Section; Estados UnidosFil: Johnson, Daniel. University of Chicago. Comer Children; Estados UnidosFil: Spalding, Christine. National Institutes of Health. National Institute of Allergy and Infectious Diseases. Laboratory of Clinical Infectious Diseases. Immunopathogenesis Section; Estados UnidosFil: Zerbe, Christa S.. National Institutes of Health. National Institute of Allergy and Infectious Diseases. Laboratory of Clinical Infectious Diseases. Immunopathogenesis Section; Estados UnidosFil: Wiley, Henry. National Eye Institute. Clinical Trials Branch; Estados UnidosFil: Greenberg, David E.. University of Texas. Southwestern Medical Center. Division of Infectious Diseases; Estados UnidosFil: Hoover, Susan E.. University of Arizona. College of Medicine. Valley Fever Center for Excellence; Estados UnidosFil: Rosenzweig, Sergio D.. National Institutes of Health. National Institute of Allergy and Infectious Diseases. Laboratory of Host Defenses Infectious Diseases Susceptibility Unit; Estados Unidos. National Institutes of Health. National Institute of Allergy and Infectious Diseases. Primary Immunodeficiency Clinic; Estados UnidosFil: Galgiani, John N.. University of Arizona. College of Medicine. Valley Fever Center for Excellence; Estados UnidosFil: Holland, Steven M.. National Institutes of Health. National Institute of Allergy and Infectious Diseases. Laboratory of Clinical Infectious Diseases. Immunopathogenesis Section; Estados Unido

Molecular and Antigenic Characterization of Reassortant H3N2 Viruses from Turkeys with a Unique Constellation of Pandemic H1N1 Internal Genes

Triple reassortant (TR) H3N2 influenza viruses cause varying degrees of loss in egg production in breeder turkeys. In this study we characterized TR H3N2 viruses isolated from three breeder turkey farms diagnosed with a drop in egg production. The eight gene segments of the virus isolated from the first case submission (FAV-003) were all of TR H3N2 lineage. However, viruses from the two subsequent case submissions (FAV-009 and FAV-010) were unique reassortants with PB2, PA, nucleoprotein (NP) and matrix (M) gene segments from 2009 pandemic H1N1 and the remaining gene segments from TR H3N2. Phylogenetic analysis of the HA and NA genes placed the 3 virus isolates in 2 separate clades within cluster IV of TR H3N2 viruses. Birds from the latter two affected farms had been vaccinated with a H3N4 oil emulsion vaccine prior to the outbreak. The HAl subunit of the H3N4 vaccine strain had only a predicted amino acid identity of 79% with the isolate from FAV-003 and 80% for the isolates from FAV-009 and FAV-0010. By comparison, the predicted amino acid sequence identity between a prototype TR H3N2 cluster IV virus A/Sw/ON/33853/2005 and the three turkey isolates from this study was 95% while the identity between FAV-003 and FAV-009/10 isolates was 91%. When the previously identified antigenic sites A, B, C, D and E of HA1 were examined, isolates from FAV-003 and FAV-009/10 had a total of 19 and 16 amino acid substitutions respectively when compared with the H3N4 vaccine strain. These changes corresponded with the failure of the sera collected from turkeys that received this vaccine to neutralize any of the above three isolates in vitro

Volatility as a concept to understand the impact of stress on the microbiome

The microbiome-gut-brain-axis is a complex phenomenon spanning several dynamic systems in the body which can be parsed at a molecular, cellular, physiological and ecological level. A growing body of evidence indicates that this axis is particularly sensitive to the effects of stress and that it may be relevant to stress resilience and susceptibility. Although stress-induced changes in the composition of the microbiome have been reported, the degree of compositional change over time, which we define as volatility, has not been the subject of in-depth scrutiny. Using a chronic psychosocial stress paradigm in male mice, we report that the volatility of the microbiome significantly correlated with several readouts of the stress response, including behaviour and corticosterone response. We then validated these findings in a second independent group of stressed mice. Additionally, we assessed the relationship between volatility and stress parameters in a cohort of health volunteers who were undergoing academic exams and report similar observations. Finally, we found inter-species similarities in the microbiome stress response on a functional level. Our research highlights the effects of stress on the dynamic microbiome and underscores the informative value of volatility as a parameter that should be considered in all future analyses of the microbiome