Efficient and automatic methods for flexible regression on spatiotemporal data, with applications to groundwater monitoring

Fitting statistical models to spatiotemporal data requires finding the right balance between imposing smoothness and following the data. In the context of P-splines, we propose a Bayesian framework for choosing the smoothing parameter which allows the construction of fully-automatic data-driven methods for fitting flexible models to spatiotemporal data. An implementation, which is highly computationally efficient and which exploits the sparsity of the design and penalty matrices, is proposed. The findings are illustrated using a simulation study and two examples, all concerned with the modelling of contaminants in groundwater. This suggests that the proposed strategy is more stable that competing methods based on the use of criteria such as GCV and AIC

Assessing the outcome of orthognathic surgery by three-dimensional soft tissue analysis

Studies of orthognathic surgery often focus on pre-surgical versus post-surgical changes in facial shape. In contrast, this study provides an innovative comparison between post-surgical and control shape. Forty orthognathic surgery patients were included, who underwent three different types of surgical correction: Le Fort I maxillary advancement, bilateral sagittal split mandibular advancement, and bimaxillary advancement surgery. Control facial images were captured from volunteers from local communities in Glasgow, with patterns of age, sex, and ethnic background that matched those of the surgical patients. Facial models were fitted and Procrustes registration and principal components analysis used to allow quantitative analysis, including the comparison of group mean shape and mean asymmetry. The primary characteristic of the difference in shape was found to be residual mandibular prognathism in the group of female patients who underwent Le Fort I maxillary advancement. Individual cases were assessed against this type of shape difference, using a quantitative scale to aid clinical audit. Analysis of the combined surgical groups provided strong evidence that surgery reduces asymmetry in some parts of the face such as the upper lip region. No evidence was found that mean asymmetry in post-surgical patients is greater than that in controls

Chagas disease

Approximately 8 million people worldwide are infected by the protozoan parasite Trypanosoma cruzi, the causative agent of Chagas disease. After a latent period that can last years or decades, 10% to 30% of infected people develop serious complications, such as cardiomyopathy or gastrointestinal dysfunction. Contrary to popular belief, Chagas disease is not solely a vector-borne infection of Latin America. Clinicians in nonendemic regions must be aware of the potential for childhood T cruzi infections

Statistical modelling of groundwater contamination monitoring data: a comparison of spatial and spatiotemporal methods

Field monitoring of groundwater contamination plumes is an important component of managing risks for downgradient receptors and remedial strategies that rely on monitored natural attenuation. Collection of groundwater quality data can however take a considerable effort and be associated with high cost. Here, we investigated the relative merits of analyzing groundwater quality data using spatial compared to spatiotemporal statistical modelling and assessed the accuracy of both methods and implications for data collection requirements. The aim of this was to determine whether the quantity of data collected can be reduced, while retaining the same level of estimation accuracy, by analyzing groundwater contamination data using a spatiotemporal model which “borrows strength” across time, rather than a spatial model for individual sampling events. To capture the variability encountered under field conditions, we used three hypothetical groundwater contamination plumes with increasing complexity, and site data for a large groundwater gasoline additive plume. The results show that spatiotemporal methods can increase efficiency markedly so that, in comparison with repeated spatial analysis, spatiotemporal methods can achieve the same level of performance but with smaller sample sizes

Association of FCGR3A and FCGR3B haplotypes with rheumatoid arthritis and primary Sjögren's syndrome [POSTER PRESENTATION]

Background Rheumatoid arthritis (RA) is an autoimmune disease that is thought to arise from a complex interaction between multiple genetic factors and environmental triggers. We have previously demonstrated an association between a Fc gamma receptor (FcγR) haplotype and RA in a cross-sectional cohort of RA patients. We have sought to confirm this association in an inception cohort of RA patients and matched controls. We also extended our study to investigate a second autoanti-body associated rheumatic disease, primary Sjögren's syndrome (PSS). Methods The FCGR3A-158F/V and FCGR3B-NA1/NA2 functional polymorphisms were examined for association in an inception cohort of RA patients (n = 448), and a well-characterised PSS cohort (n = 83) from the United Kingdom. Pairwise disequilibrium coefficients (D') were calculated in 267 Blood Service healthy controls. The EHPlus program was used to estimate haplotype frequencies for patients and controls and to determine whether significant linkage disequilibrium was present. A likelihood ratio test is performed to test for differences between the haplotype frequencies in cases and controls. A permutation procedure implemented in this program enabled 1000 permutations to be performed on all haplotype associations to assess significance. Results There was significant linkage disequilibrium between FCGR3A and FCGR3B (D' = -0.445, P = 0.001). There was no significant difference in the FCGR3A or FCGR3B allele or genotype frequencies in the RA or PSS patients compared with controls. However, there was a significant difference in the FCGR3A-FCGR3B haplotype distributions with increased homozygosity for the FCGR3A-FCGR3B 158V-NA2 haplotype in both our inception RA cohort (odds ratio = 2.15, 95% confidence interval = 1.1–4.2 P = 0.027) and PSS (odds ratio = 2.83, 95% confidence interval = 1.0–8.2, P = 0.047) compared with controls. The reference group for these analyses comprised individuals who did not possess a copy of the FCGR3A-FCGR3B 158V-NA2 haplotype. Conclusions We have confirmed our original findings of association between the FCGR3A-FCGR3B 158V-NA2 haplotype and RA in a new inception cohort of RA patients. This suggests that there may be an RA-susceptibility gene at this locus. The significant increased frequency of an identical haplotype in PSS suggests the FcγR genetic locus may contribute to the pathogenesis of diverse autoantibody-mediated rheumatic diseases

Survey of nucleon electromagnetic form factors

A dressed-quark core contribution to nucleon electromagnetic form factors is calculated. It is defined by the solution of a Poincare' covariant Faddeev equation in which dressed-quarks provide the elementary degree of freedom and correlations between them are expressed via diquarks. The nucleon-photon vertex involves a single parameter; i.e., a diquark charge radius. It is argued to be commensurate with the pion's charge radius. A comprehensive analysis and explanation of the form factors is built upon this foundation. A particular feature of the study is a separation of form factor contributions into those from different diagram types and correlation sectors, and subsequently a flavour separation for each of these. Amongst the extensive body of results that one could highlight are: r_1^{n,u}>r_1^{n,d}, owing to the presence of axial-vector quark-quark correlations; and for both the neutron and proton the ratio of Sachs electric and magnetic form factors possesses a zero.Comment: 43 pages, 17 figures, 12 tables, 5 appendice

TRY plant trait database – enhanced coverage and open access

Plant traits—the morphological, anatomical, physiological, biochemical and phenological characteristics of plants—determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait‐based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits—almost complete coverage for ‘plant growth form’. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait–environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives