Beyond clustering: mean-field dynamics on networks with arbitrary subgraph composition

Clustering is the propensity of nodes that share a common neighbour to be connected. It is ubiquitous in many networks but poses many modelling challenges. Clustering typically manifests itself by a higher than expected frequency of triangles, and this has led to the principle of constructing networks from such building blocks. This approach has been generalised to networks being constructed from a set of more exotic subgraphs. As long as these are fully connected, it is then possible to derive mean-field models that approximate epidemic dynamics well. However, there are virtually no results for non-fully connected subgraphs. In this paper, we provide a general and automated approach to deriving a set of ordinary differential equations, or mean-field model, that describes, to a high degree of accuracy, the expected values of system-level quantities, such as the prevalence of infection. Our approach offers a previously unattainable degree of control over the arrangement of subgraphs and network characteristics such as classical node degree, variance and clustering. The combination of these features makes it possible to generate families of networks with different subgraph compositions while keeping classical network metrics constant. Using our approach, we show that higher-order structure realised either through the introduction of loops of different sizes or by generating networks based on different subgraphs but with identical degree distribution and clustering, leads to non-negligible differences in epidemic dynamics

Sending Your Grandparents to University Increases Cognitive Reserve: The Tasmanian Healthy Brain Project.

Increasing an individual’s level of cognitive reserve (CR) has been suggested as a nonpharmacological approach to reducing the risk for Alzheimer’s disease. We examined changes in CR in older adults participating over 4 years in the Tasmanian Healthy Brain Project. Method: A sample of 459 healthy older adults between 50 and 79 years of age underwent a comprehensive annual assessment of current CR, neuropsychological function, and psychosocial factors over a 4-year period. The intervention group of 359 older adults (M � 59.61 years, SD � 6.67) having completed a minimum of 12 months part-time university study were compared against a control reference group of 100 adults (M � 62.49 years, SD � 6.24) who did not engage in further education. Results: Growth mixture modeling demonstrated that 44.3% of the control sample showed no change in CR, whereas 92.5% of the further education participants displayed a significant linear increase in CR over the 4 years of the study. These results indicate that older adults engaging in high-level mental stimulation display an increase in CR over a 4-year period. Conclusion: Increasing mental activity in older adulthood may be a viable strategy to improve cognitive function and offset cognitive decline associated with normal aging

Fast variables determine the epidemic threshold in the pairwise model with an improved closure

Pairwise models are used widely to model epidemic spread on networks. These include the modelling of susceptible-infected-removed (SIR) epidemics on regular networks and extensions to SIS dynamics and contact tracing on more exotic networks exhibiting degree heterogeneity, directed and/or weighted links and clustering. However, extra features of the disease dynamics or of the network lead to an increase in system size and analytical tractability becomes problematic. Various `closures' can be used to keep the system tractable. Focusing on SIR epidemics on regular but clustered networks, we show that even for the most complex closure we can determine the epidemic threshold as an asymptotic expansion in terms of the clustering coefficient.We do this by exploiting the presence of a system of fast variables, specified by the correlation structure of the epidemic, whose steady state determines the epidemic threshold. While we do not find the steady state analytically, we create an elegant asymptotic expansion of it. We validate this new threshold by comparing it to the numerical solution of the full system and find excellent agreement over a wide range of values of the clustering coefficient, transmission rate and average degree of the network. The technique carries over to pairwise models with other closures [1] and we note that the epidemic threshold will be model dependent. This emphasises the importance of model choice when dealing with realistic outbreaks

Genetic variation in the HLA region is associated with susceptibility to herpes zoster.

Herpes zoster, commonly referred to as shingles, is caused by the varicella zoster virus (VZV). VZV initially manifests as chicken pox, most commonly in childhood, can remain asymptomatically latent in nerve tissues for many years and often re-emerges as shingles. Although reactivation may be related to immune suppression, aging and female sex, most inter-individual variability in re-emergence risk has not been explained to date. We performed a genome-wide association analyses in 22,981 participants (2280 shingles cases) from the electronic Medical Records and Genomics Network. Using Cox survival and logistic regression, we identified a genomic region in the combined and European ancestry groups that has an age of onset effect reaching genome-wide significance (P>1.0 × 10(-8)). This region tags the non-coding gene HCP5 (HLA Complex P5) in the major histocompatibility complex. This gene is an endogenous retrovirus and likely influences viral activity through regulatory functions. Variants in this genetic region are known to be associated with delay in development of AIDS in people infected by HIV. Our study provides further suggestion that this region may have a critical role in viral suppression and could potentially harbor a clinically actionable variant for the shingles vaccine

Individual variation in levels of haptoglobin-related protein in children from Gabon

Background: Haptoglobin related protein (Hpr) is a key component of trypanosome lytic factors (TLF), a subset of highdensity lipoproteins (HDL) that form the first line of human defence against African trypanosomes. Hpr, like haptoglobin (Hp) can bind to hemoglobin (Hb) and it is the Hpr-Hb complexes which bind to these parasites allowing uptake of TLF. This unique form of innate immunity is primate-specific. To date, there have been no population studies of plasma levels of Hpr, particularly in relation to hemolysis and a high prevalence of ahaptoglobinemia as found in malaria endemic areas. Methods and Principal Findings: We developed a specific enzyme-linked immunosorbent assay to measure levels of plasma Hpr in Gabonese children sampled during a period of seasonal malaria transmission when acute phase responses (APR), malaria infection and associated hemolysis were prevalent. Median Hpr concentration was 0.28 mg/ml (range 0.03-1.1). This was 5-fold higher than that found in Caucasian children (0.049 mg/ml, range 0.002-0.26) with no evidence of an APR. A general linear model was used to investigate associations between Hpr levels, host polymorphisms, parasitological factors and the acute phase proteins, Hp, C-reactive protein (CRP) and albumin. Levels of Hpr were associated with Hp genotype, decreased with age and were higher in females. Hpr concentration was strongly correlated with that of Hp, but not CRP

e-Roster Policy: Insights and implications of codifying nurse scheduling

Following a decade of dissemination, particularly within the British National Health Service (NHS), electronic rostering systems were recently endorsed within the Carter Review. However, e-rostering necessitates the formal codification of the roster process. This research investigates that codification through the lens of the 'Roster Policy', a formal document specifying the rules and procedures used to prepare staff rosters. This study is based upon analysis of twenty-seven publicly available policies, each approved within a four-year period from January 2010 to July 2014. This research finds that, at an executive level, codified knowledge is used as a proxy for the common language and experience otherwise acquired on a ward through everyday interaction, while at ward level the nurse rostering problem continues to resist all efforts at simplification. Ultimately, it is imperative that executives recognise that e-rostering is not a silver-bullet and that information from such systems requires careful interpretation and circumspection

Whole home exercise intervention for depression in older care home residents (the OPERA study) : a process evaluation

Background: The ‘Older People’s Exercise intervention in Residential and nursing Accommodation’ (OPERA) cluster randomised trial evaluated the impact of training for care home staff together with twice-weekly, physiotherapist-led exercise classes on depressive symptoms in care home residents, but found no effect. We report a process evaluation exploring potential explanations for the lack of effect. Methods: The OPERA trial included over 1,000 residents in 78 care homes in the UK. We used a mixed methods approach including quantitative data collected from all homes. In eight case study homes, we carried out repeated periods of observation and interviews with residents, care staff and managers. At the end of the intervention, we held focus groups with OPERA research staff. We reported our first findings before the trial outcome was known. Results: Homes showed large variations in activity at baseline and throughout the trial. Overall attendance rate at the group exercise sessions was low (50%). We considered two issues that might explain the negative outcome: whether the intervention changed the culture of the homes, and whether the residents engaged with the intervention. We found low levels of staff training, few home champions for the intervention and a culture that prioritised protecting residents from harm over encouraging activity. The trial team delivered 3,191 exercise groups but only 36% of participants attended at least 1 group per week and depressed residents attended significantly fewer groups than those who were not depressed. Residents were very frail and therefore most groups only included seated exercises. Conclusions: The intervention did not change the culture of the homes and, in the case study homes, activity levels did not change outside the exercise groups. Residents did not engage in the exercise groups at a sufficient level, and this was particularly true for those with depressive symptoms at baseline. The physical and mental frailty of care home residents may make it impossible to deliver a sufficiently intense exercise intervention to impact on depressive symptoms

"It's making contacts" : notions of social capital and implications for widening access to medical education

Acknowledgements Our thanks to the Medical Schools Council (MSC) of the UK for funding Study A; REACH Scotland for funding Study B; and Queen Mary University of London, and to the medical school applicants and students who gave their time to be interviewed. Our thanks also to Dr Sean Zhou and Dr Sally Curtis, and Manjul Medhi, for their help with data collection for studies A and B respectively. Our thanks also to Dr Lara Varpio, Uniformed Services University of the USA, for her advice and guidance on collating data sets and her comments on the draft manuscript.Peer reviewedPublisher PD

Large-scale associations between the leukocyte transcriptome and BOLD responses to speech differ in autism early language outcome subtypes.

Heterogeneity in early language development in autism spectrum disorder (ASD) is clinically important and may reflect neurobiologically distinct subtypes. Here, we identified a large-scale association between multiple coordinated blood leukocyte gene coexpression modules and the multivariate functional neuroimaging (fMRI) response to speech. Gene coexpression modules associated with the multivariate fMRI response to speech were different for all pairwise comparisons between typically developing toddlers and toddlers with ASD and poor versus good early language outcome. Associated coexpression modules were enriched in genes that are broadly expressed in the brain and many other tissues. These coexpression modules were also enriched in ASD-associated, prenatal, human-specific, and language-relevant genes. This work highlights distinctive neurobiology in ASD subtypes with different early language outcomes that is present well before such outcomes are known. Associations between neuroimaging measures and gene expression levels in blood leukocytes may offer a unique in vivo window into identifying brain-relevant molecular mechanisms in ASD

Mapping structural diversity in networks sharing a given degree distribution and global clustering: Adaptive resolution grid search evolution with Diophantine equation-based mutations

Methods that generate networks sharing a given degree distribution and global clustering can induce changes in structural properties other than that controlled for. Diversity in structural properties, in turn, can affect the outcomes of dynamical processes operating on those networks. Since exhaustive sampling is not possible, we propose a novel evolutionary framework for mapping this structural diversity. The three main features of this framework are: (a) subgraph-based encoding of networks, (b) exact mutations based on solving systems of Diophantine equations, and (c) heuristic diversity-driven mechanism to drive resolution changes in the MapElite algorithm.We show that our framework can elicit networks with diversity in their higher-order structure and that this diversity affects the behaviour of the complex contagion model. Through a comparison with state of the art clustered network generation methods, we demonstrate that our approach can uncover a comparably diverse range of networks without needing computationally unfeasible mixing times. Further, we suggest that the subgraph-based encoding provides greater confidence in the diversity of higher-order network structure for low numbers of samples and is the basis for explaining our results with complex contagion model. We believe that this framework could be applied to other complex landscapes that cannot be practically mapped via exhaustive sampling