Risk models and scores for type 2 diabetes: Systematic review

This article is published under a Creative Commons Attribution Non Commercial (CC BY-NC 3.0) licence that allows reuse subject only to the use being non-commercial and to the article being fully attributed (http://creativecommons.org/licenses/by-nc/3.0).Objective - To evaluate current risk models and scores for type 2 diabetes and inform selection and implementation of these in practice. Design - Systematic review using standard (quantitative) and realist (mainly qualitative) methodology. Inclusion - criteria Papers in any language describing the development or external validation, or both, of models and scores to predict the risk of an adult developing type 2 diabetes. Data sources - Medline, PreMedline, Embase, and Cochrane databases were searched. Included studies were citation tracked in Google Scholar to identify follow-on studies of usability or impact. Data extraction - Data were extracted on statistical properties of models, details of internal or external validation, and use of risk scores beyond the studies that developed them. Quantitative data were tabulated to compare model components and statistical properties. Qualitative data were analysed thematically to identify mechanisms by which use of the risk model or score might improve patient outcomes. Results - 8864 titles were scanned, 115 full text papers considered, and 43 papers included in the final sample. These described the prospective development or validation, or both, of 145 risk prediction models and scores, 94 of which were studied in detail here. They had been tested on 6.88 million participants followed for up to 28 years. Heterogeneity of primary studies precluded meta-analysis. Some but not all risk models or scores had robust statistical properties (for example, good discrimination and calibration) and had been externally validated on a different population. Genetic markers added nothing to models over clinical and sociodemographic factors. Most authors described their score as “simple” or “easily implemented,” although few were specific about the intended users and under what circumstances. Ten mechanisms were identified by which measuring diabetes risk might improve outcomes. Follow-on studies that applied a risk score as part of an intervention aimed at reducing actual risk in people were sparse. Conclusion - Much work has been done to develop diabetes risk models and scores, but most are rarely used because they require tests not routinely available or they were developed without a specific user or clear use in mind. Encouragingly, recent research has begun to tackle usability and the impact of diabetes risk scores. Two promising areas for further research are interventions that prompt lay people to check their own diabetes risk and use of risk scores on population datasets to identify high risk “hotspots” for targeted public health interventions.Tower Hamlets, Newham, and City and Hackney primary care trusts and National Institute of Health Research

Extremism propagation in social networks with hubs

One aspect of opinion change that has been of academic interest is the impact of people with extreme opinions (extremists) on opinion dynamics. An agent-based model has been used to study the role of small-world social network topologies on general opinion change in the presence of extremists. It has been found that opinion convergence to a single extreme occurs only when the average number of network connections for each individual is extremely high. Here, we extend the model to examine the effect of positively skewed degree distributions, in addition to small-world structures, on the types of opinion convergence that occur in the presence of extremists. We also examine what happens when extremist opinions are located on the well-connected nodes (hubs) created by the positively skewed distribution. We find that a positively skewed network topology encourages opinion convergence on a single extreme under a wider range of conditions than topologies whose degree distributions were not skewed. The importance of social position for social influence is highlighted by the result that, when positive extremists are placed on hubs, all population convergence is to the positive extreme even when there are twice as many negative extremists. Thus, our results have shown the importance of considering a positively skewed degree distribution, and in particular network hubs and social position, when examining extremist transmission

Magnificat in A Minor

A Magnificat, or Canticle of Mary, composed by T. Tertius Noble for a mixed choir (soprano, alto, tenor, and bass voice parts) with organ accompaniment.https://ecommons.udayton.edu/imri_sheetmusic/1075/thumbnail.jp

Explaining cooperative groups via social niche construction

Cooperative behaviours can be defined as those that benefit others at an apparent cost to self. How these kinds of behaviours evolve has been a topic of great interest in evolutionary biology, as the Darwinian paradigm seems to suggest that nature will be “red in tooth and claw” and that we would not expect one organism to evolve to help another. The evolution-of-cooperation literature has therefore generally been about showing how the altruism involved in these cases is only apparent (see Bergstrom 2002 for an excellent review). Consider kin selection, in which interactions are more likely to occur between related individuals. The cost of altruism to the individual is real but, having identified the correct score-keeping level as the genetic one, it turns out that the cooperative act is not costly but profitable. More generally, successful explanations for cooperation rely on the presence of a population structure that clusters cooperators together, such that they enjoy the benefits of each others' actions. However, the question that has been left largely unaddressed is how does this structure itself evolve? If we want to really explain why organisms cooperate, then we need to explain not just their adaptation to their social environment, but how they came to live in that environment. Recent work by Powers (2010) and Powers et al. (in press) has addressed this question. They show that social behaviour can exert indirect selection pressure on population structure-modifying traits, causing individuals to adaptively modify their population structure to support greater cooperation. Moreover, they argue that any component of selection on structure-modifying traits that is due to social behaviour must be in the direction of increased cooperation; that component of selection cannot be in favour of the conditions for greater selfishness. Powers et al. then examine the conditions under which this component of selection on population structure exists. They argue that not only can population structure drive the evolution of cooperation, as in classical models, but that the benefits of greater cooperation can in turn drive the evolution of population structure: a positive feedback process that they refer to as social niche construction (after Odling-Smee et al. 2003). Maynard Smith and Szathmary (1995) note that most of the big unanswered questions in biology are not about how a particular behaviour is selected for at one level of organization but about the emergence of whole new levels of organization, e.g., the transition from single- to multi-celled organisms, or from solitary insects to eusocial colonies. Any satisfactory account of these transitions must explain how the individuals came to live in a population structure that supported high degrees of cooperation, as well as showing that cooperation is individually advantageous given that structure. The social niche construction process identified by Powers et al. can explain some of the major transitions, by showing how a new selective level can begin through evolution of individual characters, such as group size preference or dispersal tendency. The potential emergence of reliable cooperation via the co-evolution of individual cooperative and population-structuring behaviours demonstrates that groups of cooperating agents can create an environment in which they become so “locked in” to their group identity that the group warrants redescription as an individual in its own right. Consider the move from independent protozoans, to an intermediate cooperative stage as in slime moulds, to fully multi-cellular animals. Such creation of population structures that support cooperation parallels negotiation of a social contract. What are the philosophical implications of this perspective for understanding and explaining human social behaviour? On the one hand, it gives respectability and unique explanatory value to group-selectionist accounts. Explaining the origin of within-group cooperation and the origin of the groups themselves become part of the same project, which in turn means that we cannot understand social and cooperative behaviour in humans without understanding human population-structuring traits, e.g., living in family groups, group fission-fusion behaviours, migratory behaviours, etc. What will the explanations we seek look like? de Pinedo and Noble (2008) have argued that the description of evolved behaviour cannot be exclusively in mechanistic terms: we need both explanations that focus on an agent’s interaction with its environment, and explanations that focus on the physical or computational enabling conditions of such an interaction. In a context in which what counts as an agent is taken for granted, de Pinedo and Noble argue that both agent and sub-agent level explanations will be required. The perspective being outlined here forces an expansion of that position and reminds us that agency is not to be taken for granted; that it emerges from a lower level of organization after a history of selection brings simpler entities together in a coherent cooperative whole. The implication is that truly multi-level explanations will be necessary in the area of social behaviour. We explain the origin of the multi-cellular organism as the result of a cooperative merger of single-celled organisms, and we explain the origin of a super-organism such as an ant colony in a similar way. At each transition, the autonomous agents of the previous level become component mechanisms in the next, but no explanatory level can be entirely done away with. A human being is an example of a multi-cellular organism with a highly developed social aspect, occupying an intermediate point between radical individual independence and total group cohesion. To fully explain human behaviour, we need to know about the cellular machinery that enables personal-level agency. But we also need to know how human machinery fits together into families, communities and nations that will, at least partially, have their own emergent goals and purposes: “partially” because we are not yet a super-organism, of course. In conclusion, the perspective we outline suggests a view of the social contract as not at all unique to Hobbesian rational agents who have become tired of an insecure and violent lifestyle. Instead the ongoing negotiation of the social contract amongst ourselves can be seen as echoing earlier, now-successfully-concluded negotiations between the entities that became our genes and then our cells

Navigating Through the Fog of Cloud Computing Contracts, 30 J. Marshall J. Info. Tech. & Privacy L.13 (2013)

This paper explores legal issues associated with cloud computing, provides analysis and commentary on typical clauses found in contracts offered by well-known cloud service providers, and identifies strategies to mitigate the risk of exposure to cloud-based legal claims in the critical areas of data security, privacy, and confidentiality. While current research offers numerous case studies, viewpoints, and technical descriptions of cloud processes, our research provides a close examination of the language used in cloud contract terms. Analysis of these contract terms supports the finding that most standard cloud computing contracts are unevenly balanced in favor of the cloud service provider. The implication for cloud users is that additional measures, both legal and practical, are necessary in order to achieve a reasonable level of data security, privacy, and confidentiality, and to mitigate the inherent risks in cloud computing solutions. This research was limited to an analysis of some of the leading cloud computing service providers and the con-tract clauses they offer to cloud users. Although the selected cloud provider contracts are representative of the currently available contract terms throughout the industry, these terms are evolving along with the practices of the cloud providers and cloud users

Inductive and Electrostatic Acceleration in Relativistic Jet-Plasma Interactions

We report on the observation of rapid particle acceleration in numerical simulations of relativistic jet-plasma interactions and discuss the underlying mechanisms. The dynamics of a charge-neutral, narrow, electron-positron jet propagating through an unmagnetized electron-ion plasma was investigated using a three-dimensional, electromagnetic, particle-in-cell computer code. The interaction excited magnetic filamentation as well as electrostatic plasma instabilities. In some cases, the longitudinal electric fields generated inductively and electrostatically reached the cold plasma wave-breaking limit, and the longitudinal momentum of about half the positrons increased by 50% with a maximum gain exceeding a factor of 2 during the simulation period. Particle acceleration via these mechanisms occurred when the criteria for Weibel instability were satisfied.Comment: Revised for Phys. Rev. Lett. Please see publised version for best graphic

Comparative Microbial Dynamics in Crassostrea virginica and Crassostrea ariakensis

Considerations to introduce the Suminoe or Asian oyster Crassostrea ariakensis along the East Coast have raised many questions regarding ecology, economics, and human health. To date, research has focused primarily on the ecological and socioeconomic implications of this initiative, yet few studies have assessed its potential impact on public health. Our work compares the rates of bioaccumulation, depuration and post harvest decay of indicator organisms (such as E. coli) and Vibrio sp. between Crassostrea virginica and Crassostrea ariakensis in the laboratory. Preliminary results suggest that the rates of bioaccumulation of E. coli in Crassostrea ariakensis were significantly lower than those for Crassostrea virginica, depuration of E. coli was variable between the two species, and Crassostrea ariakensis post harvest decay rates of Vibrio sp. were significantly lower than Crassostrea virginica. This research provides coastal managers with insight into the response of Crassostrea ariakensis to bacteria, an important consideration for determining appropriate management strategies for this species. Further field-based studies will be necessary to elucidate the mechanisms responsible for the differences in rates of bioaccumulation and depuration. (PDF contains 40 pages

Intensifying agricultural sustainability: an analysis of impacts and drivers in the development of ‘bright spots’

Food security / Farming systems / Sustainable agriculture / Productivity / Investment / Thailand / Palestine / Latin America / Africa