Dynamics of multi-stage infections on networks

This paper investigates the dynamics of infectious diseases with a nonexponentially distributed infectious period. This is achieved by considering a multistage infection model on networks. Using pairwise approximation with a standard closure, a number of important characteristics of disease dynamics are derived analytically, including the final size of an epidemic and a threshold for epidemic outbreaks, and it is shown how these quantities depend on disease characteristics, as well as the number of disease stages. Stochastic simulations of dynamics on networks are performed and compared to output of pairwise models for several realistic examples of infectious diseases to illustrate the role played by the number of stages in the disease dynamics. These results show that a higher number of disease stages results in faster epidemic outbreaks with a higher peak prevalence and a larger final size of the epidemic. The agreement between the pairwise and simulation models is excellent in the cases we consider

TBK1 Kinase Addiction in Lung Cancer Cells Is Mediated via Autophagy of Tax1bp1/Ndp52 and Non-Canonical NF-kappa B Signalling

K-Ras dependent non-small cell lung cancer (NSCLC) cells are 'addicted' to basal autophagy that reprograms cellular metabolism in a lysosomal-sensitive manner. Here we demonstrate that the xenophagy-associated kinase TBK1 drives basal autophagy, consistent with its known requirement in K-Ras-dependent NSCLC proliferation. Furthermore, basal autophagy in this context is characterised by sequestration of the xenophagy cargo receptor Ndp52 and its paralogue Tax1bp1, which we demonstrate here to be a bona fide cargo receptor. Autophagy of these cargo receptors promotes non-canonical NF-κB signalling. We propose that this TBK1-dependent mechanism for NF-κB signalling contributes to autophagy addiction in K-Ras driven NSCLC

Individualization as driving force of clustering phenomena in humans

One of the most intriguing dynamics in biological systems is the emergence of clustering, the self-organization into separated agglomerations of individuals. Several theories have been developed to explain clustering in, for instance, multi-cellular organisms, ant colonies, bee hives, flocks of birds, schools of fish, and animal herds. A persistent puzzle, however, is clustering of opinions in human populations. The puzzle is particularly pressing if opinions vary continuously, such as the degree to which citizens are in favor of or against a vaccination program. Existing opinion formation models suggest that "monoculture" is unavoidable in the long run, unless subsets of the population are perfectly separated from each other. Yet, social diversity is a robust empirical phenomenon, although perfect separation is hardly possible in an increasingly connected world. Considering randomness did not overcome the theoretical shortcomings so far. Small perturbations of individual opinions trigger social influence cascades that inevitably lead to monoculture, while larger noise disrupts opinion clusters and results in rampant individualism without any social structure. Our solution of the puzzle builds on recent empirical research, combining the integrative tendencies of social influence with the disintegrative effects of individualization. A key element of the new computational model is an adaptive kind of noise. We conduct simulation experiments to demonstrate that with this kind of noise, a third phase besides individualism and monoculture becomes possible, characterized by the formation of metastable clusters with diversity between and consensus within clusters. When clusters are small, individualization tendencies are too weak to prohibit a fusion of clusters. When clusters grow too large, however, individualization increases in strength, which promotes their splitting.Comment: 12 pages, 4 figure

The association of health literacy with adherence in older 2 adults, and its role in interventions: a systematic meta-review

Background: Low health literacy is a common problem among older adults. It is often suggested to be associated with poor adherence. This suggested association implies a need for effective adherence interventions in low health literate people. However, previous reviews show mixed results on the association between low health literacy and poor adherence. A systematic meta-review of systematic reviews was conducted to study the association between health literacy and adherence in adults above the age of 50. Evidence for the effectiveness of adherence interventions among adults in this older age group with low health literacy was also explored. Methods: Eight electronic databases (MEDLINE, ERIC, EMBASE, PsycINFO, CINAHL, DARE, the Cochrane Library, and Web of Knowledge) were searched using a variety of keywords regarding health literacy and adherence. Additionally, references of identified articles were checked. Systematic reviews were included if they assessed the association between health literacy and adherence or evaluated the effectiveness of interventions to improve adherence in adults with low health literacy. The AMSTAR tool was used to assess the quality of the included reviews. The selection procedure, data-extraction, and quality assessment were performed by two independent reviewers. Seventeen reviews were selected for inclusion. Results: Reviews varied widely in quality. Both reviews of high and low quality found only weak or mixed associations between health literacy and adherence among older adults. Reviews report on seven studies that assess the effectiveness of adherence interventions among low health literate older adults. The results suggest that some adherence interventions are effective for this group. The interventions described in the reviews focused mainly on education and on lowering the health literacy demands of adherence instructions. No conclusions could be drawn about which type of intervention could be most beneficial for this population. Conclusions: Evidence on the association between health literacy and adherence in older adults is relatively weak. Adherence interventions are potentially effective for the vulnerable population of older adults with low levels of health literacy, but the evidence on this topic is limited. Further research is needed on the association between health literacy and general health behavior, and on the effectiveness of interventions

Clinical evaluation of iron treatment efficiency among non-anemic but iron-deficient female blood donors: a randomized controlled trial

ABSTRACT: Iron deficiency without anemia (IDWA) is related to adverse symptoms that can be relieved by supplementation. Since a blood donation can induce such an iron deficiency, we investigated the clinical impact of an iron treatment after blood donation. METHODS: One week after donation, we randomly assigned 154 female donors with IDWA aged <50 years to a 4-week oral treatment of ferrous sulfate vs. placebo. The main outcome was the change in the level of fatigue before and after the intervention. Also evaluated were aerobic capacity, mood disorder, quality of life, compliance and adverse events. Biological markers were hemoglobin and ferritin. RESULTS: Treatment effect from baseline to 4 weeks for hemoglobin and ferritin were 5.2 g/L (p < 0.01) and 14.8 ng/mL (p < 0.01) respectively. No significant clinical effect was observed for fatigue (-0.15 points, 95% confidence interval -0.9 to 0.6, p = 0.697) or for other outcomes. Compliance and interruption for side effects was similar in both groups. Additionally, blood donation did not induce overt symptoms of fatigue in spite of the significant biological changes it produces. CONCLUSIONS: These data are valuable as they enable us to conclude that donors with IDWA after a blood donation would not clinically benefit from iron supplementation. Trial registration: NCT00689793

A cross-national study on the antecedents of work–life balance from the fit and balance perspective

Drawing on the perceived work–family fit and balance perspective, this study investigates demands and resources as antecedents of work–life balance (WLB) across four countries (New Zealand, France, Italy and Spain), so as to provide empirical cross-national evidence. Using structural equation modelling analysis on a sample of 870 full time employees, we found that work demands, hours worked and family demands were negatively related to WLB, while job autonomy and supervisor support were positively related to WLB. We also found evidence that resources (job autonomy and supervisor support) moderated the relationships between demands and work–life balance, with high resources consistently buffering any detrimental influence of demands on WLB. Furthermore, our study identified additional predictors of WLB that were unique to some national contexts. For example, in France and Italy, overtime hours worked were negatively associated with WLB, while parental status was positively associated with WLB. Overall, the implications for theory and practice are discussed.Peer ReviewedPostprint (author's final draft

Generation of Long Insert Pairs Using a Cre-LoxP Inverse PCR Approach

Large insert mate pair reads have a major impact on the overall success of de novo assembly and the discovery of inherited and acquired structural variants. The positional information of mate pair reads generally improves genome assembly by resolving repeat elements and/or ordering contigs. Currently available methods for building such libraries have one or more of limitations, such as relatively small insert size; unable to distinguish the junction of two ends; and/or low throughput. We developed a new approach, Cre-LoxP Inverse PCR Paired-End (CLIP-PE), which exploits the advantages of (1) Cre-LoxP recombination system to efficiently circularize large DNA fragments, (2) inverse PCR to enrich for the desired products that contain both ends of the large DNA fragments, and (3) the use of restriction enzymes to introduce a recognizable junction site between ligated fragment ends and to improve the self-ligation efficiency. We have successfully created CLIP-PE libraries up to 22 kb that are rich in informative read pairs and low in small fragment background. These libraries have demonstrated the ability to improve genome assemblies. The CLIP-PE methodology can be implemented with existing and future next-generation sequencing platforms

An Analysis of the Abstracts Presented at the Annual Meetings of the Society for Neuroscience from 2001 to 2006

Annual meeting abstracts published by scientific societies often contain rich arrays of information that can be computationally mined and distilled to elucidate the state and dynamics of the subject field. We extracted and processed abstract data from the Society for Neuroscience (SFN) annual meeting abstracts during the period 2001–2006 in order to gain an objective view of contemporary neuroscience. An important first step in the process was the application of data cleaning and disambiguation methods to construct a unified database, since the data were too noisy to be of full utility in the raw form initially available. Using natural language processing, text mining, and other data analysis techniques, we then examined the demographics and structure of the scientific collaboration network, the dynamics of the field over time, major research trends, and the structure of the sources of research funding. Some interesting findings include a high geographical concentration of neuroscience research in the north eastern United States, a surprisingly large transient population (66% of the authors appear in only one out of the six studied years), the central role played by the study of neurodegenerative disorders in the neuroscience community, and an apparent growth of behavioral/systems neuroscience with a corresponding shrinkage of cellular/molecular neuroscience over the six year period. The results from this work will prove useful for scientists, policy makers, and funding agencies seeking to gain a complete and unbiased picture of the community structure and body of knowledge encapsulated by a specific scientific domain