Individual level covariate adjusted conditional autoregressive (indiCAR) model for disease mapping

© 2016 The Author(s). Background: Mapping disease rates over a region provides a visual illustration of underlying geographical variation of the disease and can be useful to generate new hypotheses on the disease aetiology. However, methods to fit the popular and widely used conditional autoregressive (CAR) models for disease mapping are not feasible in many applications due to memory constraints, particularly when the sample size is large. We propose a new algorithm to fit a CAR model that can accommodate both individual and group level covariates while adjusting for spatial correlation in the disease rates, termed indiCAR. Our method scales well and works in very large datasets where other methods fail. Results: We evaluate the performance of the indiCAR method through simulation studies. Our simulation results indicate that the indiCAR provides reliable estimates of all the regression and random effect parameters. We also apply indiCAR to the analysis of data on neutropenia admissions in New South Wales (NSW), Australia. Our analyses reveal that lower rates of neutropenia admissions are significantly associated with individual level predictors including higher age, male gender, residence in an outer regional area and a group level predictor of social disadvantage, the socio-economic index for areas. A large value for the spatial dependence parameter is estimated after adjusting for individual and area level covariates. This suggests the presence of important variation in the management of cancer patients across NSW. Conclusions: Incorporating individual covariate data in disease mapping studies improves the estimation of fixed and random effect parameters by utilizing information from multiple sources. Health registries routinely collect individual and area level information and thus could benefit by using indiCAR for mapping disease rates. Moreover, the natural applicability of indiCAR in a distributed computing framework enhances its application in the Big Data domain with a large number of individual/group level covariates. CI NSW Study Reference Number: 2012/07/410. Dated: July 2012

Tree-Independent Dual-Tree Algorithms

Dual-tree algorithms are a widely used class of branch-and-bound algorithms. Unfortunately, developing dual-tree algorithms for use with different trees and problems is often complex and burdensome. We introduce a four-part logical split: the tree, the traversal, the point-to-point base case, and the pruning rule. We provide a meta-algorithm which allows development of dual-tree algorithms in a tree-independent manner and easy extension to entirely new types of trees. Representations are provided for five common algorithms; for k-nearest neighbor search, this leads to a novel, tighter pruning bound. The meta-algorithm also allows straightforward extensions to massively parallel settings.Comment: accepted in ICML 201

Inclusive Masculinity and Facebook Photographs Among Early Emerging Adults at a British University

Central to debates about the construction of masculinity in sociology is the influence of culture and what constitutes acceptable displays of masculinity. This article adopts a novel approach in examining this question. It adopts a summative content analysis, combined with a semiotic analysis, of 1,100 Facebook photographs, in order to explore the underlying meanings within the photos and the performances of masculinity. Facebook photographs from 44, straight, White, male, early emerging adults attending the same university are used as a representation of an individual’s ideal self. These are then analyzed in order to determine the behaviors endorsed by peer culture. It was found that the sample overwhelmingly adopted inclusive behaviors (including homosocial tactility, dancing, and kissing each other), and inclusive masculinity theory was utilized to contextualize participants’ constructions of masculinity. Thus, this research shows that emerging adult males at this university construct their masculine identities away from previous orthodox archetypes. It is argued that the reducing importance of gendered behavior patterns may represent an adoption of what are perceived as wider cultural norms and act as a symbol of adulthood to these early emerging adults

An insulin signaling feedback loop regulates pancreas progenitor cell differentiation during islet development and regeneration

As one of the key nutrient sensors, insulin signaling plays an important role in integrating environmental energy cues with organism growth. In adult organisms, relative insufficiency of insulin signaling induces compensatory expansion of insulin-secreting pancreatic beta (β) cells. However, little is known about how insulin signaling feedback might influence neogenesis of β cells during embryonic development. Using genetic approaches and a unique cell transplantation system in developing zebrafish, we have uncovered a novel role for insulin signaling in the negative regulation of pancreatic progenitor cell differentiation. Blocking insulin signaling in the pancreatic progenitors hastened the expression of the essential β cell genes insulin and pdx1, and promoted β cell fate at the expense of alpha cell fate. In addition, loss of insulin signaling promoted β cell regeneration and destabilization of alpha cell character. These data indicate that insulin signaling constitutes a tunable mechanism for β cell compensatory plasticity during early development. Moreover, using a novel blastomere-to-larva transplantation strategy, we found that loss of insulin signaling in endoderm-committed blastomeres drove their differentiation into β cells. Furthermore, the extent of this differentiation was dependent on the function of the β cell mass in the host. Altogether, our results indicate that modulation of insulin signaling will be crucial for the development of β cell restoration therapies for diabetics; further clarification of the mechanisms of insulin signaling in β cell progenitors will reveal therapeutic targets for both in vivo and in vitro β cell generation

Quantum Cosmological Relational Model of Shape and Scale in 1-d

Relational particle models are useful toy models for quantum cosmology and the problem of time in quantum general relativity. This paper shows how to extend existing work on concrete examples of relational particle models in 1-d to include a notion of scale. This is useful as regards forming a tight analogy with quantum cosmology and the emergent semiclassical time and hidden time approaches to the problem of time. This paper shows furthermore that the correspondence between relational particle models and classical and quantum cosmology can be strengthened using judicious choices of the mechanical potential. This gives relational particle mechanics models with analogues of spatial curvature, cosmological constant, dust and radiation terms. A number of these models are then tractable at the quantum level. These models can be used to study important issues 1) in canonical quantum gravity: the problem of time, the semiclassical approach to it and timeless approaches to it (such as the naive Schrodinger interpretation and records theory). 2) In quantum cosmology, such as in the investigation of uniform states, robustness, and the qualitative understanding of the origin of structure formation.Comment: References and some more motivation adde

Polyamine biosynthesis is critical for growth and differentiation of the pancreas

The pancreas, in most studied vertebrates, is a compound organ with both exocrine and endocrine functions. The exocrine compartment makes and secretes digestive enzymes, while the endocrine compartment, organized into islets of Langerhans, produces hormones that regulate blood glucose. High concentrations of polyamines, which are aliphatic amines, are reported in exocrine and endocrine cells, with insulin-producing β cells showing the highest concentrations. We utilized zebrafish as a model organism, together with pharmacological inhibition or genetic manipulation, to determine how polyamine biosynthesis functions in pancreatic organogenesis. We identified that inhibition of polyamine biosynthesis reduces exocrine pancreas and β cell mass, and that these reductions are at the level of differentiation. Moreover, we demonstrate that inhibition of ornithine decarboxylase (ODC), the rate-limiting enzyme in polyamine biosynthesis, phenocopies inhibition or knockdown of the enzyme deoxyhypusine synthase (DHS). These data identify that the pancreatic requirement for polyamine biosynthesis is largely mediated through a requirement for spermidine for the downstream posttranslational modification of eIF5A by its enzymatic activator DHS, which in turn impacts mRNA translation. Altogether, we have uncovered a role for polyamine biosynthesis in pancreatic organogenesis and identified that it may be possible to exploit polyamine biosynthesis to manipulate pancreatic cell differentiation

Comparing predictive abilities of longitudinal child growth models

© 2018 John Wiley & Sons, Ltd. The Bill and Melinda Gates Foundation's Healthy Birth, Growth and Development knowledge integration project aims to improve the overall health and well-being of children across the world. The project aims to integrate information from multiple child growth studies to allow health professionals and policy makers to make informed decisions about interventions in lower and middle income countries. To achieve this goal, we must first understand the conditions that impact on the growth and development of children, and this requires sensible models for characterising different growth patterns. The contribution of this paper is to provide a quantitative comparison of the predictive abilities of various statistical growth modelling techniques based on a novel leave-one-out validation approach. The majority of existing studies have used raw growth data for modelling, but we show that fitting models to standardised data provide more accurate estimation and prediction. Our work is illustrated with an example from a study into child development in a middle income country in South America

One transition, many transitions? A corpus-based study of societal sustainability transition discourses in four civil society’s proposals

When the civil society makes ‘transition’ its label, it cannot be assumed that different civil society actors share compatible varieties of localist or radical transformationists discourses. This study has comparatively analyzed the discourses in four civil society sustainability transition proposals using a corpus-based methodology. We found that the proposals are similar as they identify the economy as an object and an entry point for transition, frame the economy as embedded in the socio–ecological system, ascribe agency to grassroots movements for transitions from the bottom–up. We also found crucial differences among the discourses regarding the role of the State, the degree of reform or radical innovation, the degree of imaginative character of the sustainability vision, the degree of opposition to capitalism. We suggest that insights on how the civil society employs notions of transition with respect to the themes of politics, emotions and place can help advance theorizations and practices of societal sustainability transitions led by the civil society