Disease prevention versus data privacy : using landcover maps to inform spatial epidemic models

The availability of epidemiological data in the early stages of an outbreak of an infectious disease is vital for modelers to make accurate predictions regarding the likely spread of disease and preferred intervention strategies. However, in some countries, the necessary demographic data are only available at an aggregate scale. We investigated the ability of models of livestock infectious diseases to predict epidemic spread and obtain optimal control policies in the event of imperfect, aggregated data. Taking a geographic information approach, we used land cover data to predict UK farm locations and investigated the influence of using these synthetic location data sets upon epidemiological predictions in the event of an outbreak of foot-and-mouth disease. When broadly classified land cover data were used to create synthetic farm locations, model predictions deviated significantly from those simulated on true data. However, when more resolved subclass land use data were used, moderate to highly accurate predictions of epidemic size, duration and optimal vaccination and ring culling strategies were obtained. This suggests that a geographic information approach may be useful where individual farm-level data are not available, to allow predictive analyses to be carried out regarding the likely spread of disease. This method can also be used for contingency planning in collaboration with policy makers to determine preferred control strategies in the event of a future outbreak of infectious disease in livestock

Global economic impacts of climate variability and change during the 20th century

Estimates of the global economic impacts of observed climate change during the 20th century obtained by applying five impact functions of different integrated assessment models (IAMs) are separated into their main natural and anthropogenic components. The estimates of the costs that can be attributed to natural variability factors and to the anthropogenic intervention with the climate system in general tend to show that: 1) during the first half of the century, the amplitude of the impacts associated with natural variability is considerably larger than that produced by anthropogenic factors and the effects of natural variability fluctuated between being negative and positive. These non-monotonic impacts are mostly determined by the low-frequency variability and the persistence of the climate system; 2) IAMs do not agree on the sign (nor on the magnitude) of the impacts of anthropogenic forcing but indicate that they steadily grew over the first part of the century, rapidly accelerated since the mid 1970's, and decelerated during the first decade of the 21st century. This deceleration is accentuated by the existence of interaction effects between natural variability and natural and anthropogenic forcing. The economic impacts of anthropogenic forcing range in the tenths of percentage of the world GDP by the end of the 20th century; 3) the impacts of natural forcing are about one order of magnitude lower than those associated with anthropogenic forcing and are dominated by the solar forcing; 4) the interaction effects between natural and anthropogenic factors can importantly modulate how impacts actually occur, at least for moderate increases in external forcing. Human activities became dominant drivers of the estimated economic impacts at the end of the 20th century, producing larger impacts than those of low-frequency natural variability. Some of the uses and limitations of IAMs are discussed

Edge centrality via the Holevo quantity

In the study of complex networks, vertex centrality measures are used to identify the most important vertices within a graph. A related problem is that of measuring the centrality of an edge. In this paper, we propose a novel edge centrality index rooted in quantum information. More specifically, we measure the importance of an edge in terms of the contribution that it gives to the Von Neumann entropy of the graph. We show that this can be computed in terms of the Holevo quantity, a well known quantum information theoretical measure. While computing the Von Neumann entropy and hence the Holevo quantity requires computing the spectrum of the graph Laplacian, we show how to obtain a simplified measure through a quadratic approximation of the Shannon entropy. This in turns shows that the proposed centrality measure is strongly correlated with the negative degree centrality on the line graph. We evaluate our centrality measure through an extensive set of experiments on real-world as well as synthetic networks, and we compare it against commonly used alternative measures

Acute febrile illness is associated with Rickettsia spp infection in dogs

BACKGROUND: Rickettsia conorii is transmitted by Rhipicephalus sanguineus ticks and causes Mediterranean Spotted Fever (MSF) in humans. Although dogs are considered the natural host of the vector, the clinical and epidemiological significance of R. conorii infection in dogs remains unclear. The aim of this prospective study was to investigate whether Rickettsia infection causes febrile illness in dogs living in areas endemic for human MSF. METHODS: Dogs from southern Italy with acute fever (n = 99) were compared with case–control dogs with normal body temperatures (n = 72). Serology and real-time PCR were performed for Rickettsia spp., Ehrlichia canis, Anaplasma phagocytophilum/A. platys and Leishmania infantum. Conventional PCR was performed for Babesia spp. and Hepatozoon spp. Acute and convalescent antibodies to R. conorii, E. canis and A. phagocytophilum were determined. RESULTS: The seroprevalence rates at first visit for R. conorii, E. canis, A. phagocytophilum and L. infantum were 44.8%, 48.5%, 37.8% and 17.6%, respectively. The seroconversion rates for R. conorii, E. canis and A. phagocytophilum were 20.7%, 14.3% and 8.8%, respectively. The molecular positive rates at first visit for Rickettsia spp., E. canis, A. phagocytophilum, A. platys, L. infantum, Babesia spp. and Hepatozoon spp. were 1.8%, 4.1%, 0%, 2.3%, 11.1%, 2.3% and 0.6%, respectively. Positive PCR for E. canis (7%), Rickettsia spp. (3%), Babesia spp. (4.0%) and Hepatozoon spp. (1.0%) were found only in febrile dogs. The DNA sequences obtained from Rickettsia and Babesia PCRs positive samples were 100% identical to the R. conorii and Babesia vogeli sequences in GenBank®, respectively. Febrile illness was statistically associated with acute and convalescent positive R. conorii antibodies, seroconversion to R. conorii, E. canis positive PCR, and positivity to any tick pathogen PCRs. Fourteen febrile dogs (31.8%) were diagnosed with Rickettsia spp. infection based on seroconversion and/or PCR while only six afebrile dogs (12.5%) seroconverted (P = 0.0248). The most common clinical findings of dogs with Rickettsia infection diagnosed by seroconversion and/or PCR were fever, myalgia, lameness, elevation of C-reactive protein, thrombocytopenia and hypoalbuminemia. CONCLUSIONS: This study demonstrates acute febrile illness associated with Rickettsia infection in dogs living in endemic areas of human MSF based on seroconversion alone or in combination with PCR

Spina bifida-predisposing heterozygous mutations in Planar Cell Polarity genes and Zic2 reduce bone mass in young mice

Fractures are a common comorbidity in children with the neural tube defect (NTD) spina bifida. Mutations in the Wnt/planar cell polarity (PCP) pathway contribute to NTDs in humans and mice, but whether this pathway independently determines bone mass is poorly understood. Here, we first confirmed that core Wnt/PCP components are expressed in osteoblasts and osteoclasts in vitro. In vivo, we performed detailed µCT comparisons of bone structure in tibiae from young male mice heterozygous for NTD-associated mutations versus WT littermates. PCP signalling disruption caused by Vangl2 (Vangl2Lp/+) or Celsr1 (Celsr1Crsh/+) mutations significantly reduced trabecular bone mass and distal tibial cortical thickness. NTD-associated mutations in non-PCP transcription factors were also investigated. Pax3 mutation (Pax3Sp2H/+) had minimal effects on bone mass. Zic2 mutation (Zic2Ku/+) significantly altered the position of the tibia/fibula junction and diminished cortical bone in the proximal tibia. Beyond these genes, we bioinformatically documented the known extent of shared genetic networks between NTDs and bone properties. 46 genes involved in neural tube closure are annotated with bone-related ontologies. These findings document shared genetic networks between spina bifida risk and bone structure, including PCP components and Zic2. Genetic variants which predispose to spina bifida may therefore independently diminish bone mass

Proinflammatory cytokine levels in fibromyalgia patients are independent of body mass index

<p>Abstract</p> <p>Background</p> <p>Fibromyalgia (FM) is characterized by chronic, widespread muscular pain and tenderness and is generally associated with other somatic and psychological symptoms. Further, circulatory levels of proinflammatory cytokines (IL-1β, TNF-α, and IL-6) may be altered in FM patients, possibly in association with their symptoms. Recently, rises in BMI have been suggested to contribute to increased circulating levels of proinflammatory cytokines in FM patients. Our aim was to measure the circulatory levels of proinflammatory cytokines to determine the influence of BMI on these levels in FM patients and healthy volunteers (HVs). In Spanish FM patients (n = 64) and HVs (n = 25), we measured BMI and serum concentrations of proinflammatory cytokines by capture ELISA.</p> <p>Findings</p> <p>There were significant differences in BMI levels between FM patients (26.40 ± 4.46) and HVs (23.64 ± 3.45) and significant increase in IL-6 in FM patients (16.28 ± 8.13 vs 0.92 ± 0.32 pg/ml) (P < 0.001). IL-1β and TNF-α decreased in FM patients compared with HVs. By ANCOVA, there was no significant association between BMI and TNF-α (F = 0.098, p = 0.75) or IL-6 (F = 0.221, p = 0.63) levels in FM patients.</p> <p>Conclusions</p> <p>Our analysis in FM patients of BMI as a covariate of proinflammatory cytokines levels showed that serum TNF-α and IL-6 levels are independent of BMI. Further studies are necessary to dissect these findings and their implication in future therapeutic approaches for FM patients.</p

Tear fluid biomarkers in ocular and systemic disease: potential use for predictive, preventive and personalised medicine

In the field of predictive, preventive and personalised medicine, researchers are keen to identify novel and reliable ways to predict and diagnose disease, as well as to monitor patient response to therapeutic agents. In the last decade alone, the sensitivity of profiling technologies has undergone huge improvements in detection sensitivity, thus allowing quantification of minute samples, for example body fluids that were previously difficult to assay. As a consequence, there has been a huge increase in tear fluid investigation, predominantly in the field of ocular surface disease. As tears are a more accessible and less complex body fluid (than serum or plasma) and sampling is much less invasive, research is starting to focus on how disease processes affect the proteomic, lipidomic and metabolomic composition of the tear film. By determining compositional changes to tear profiles, crucial pathways in disease progression may be identified, allowing for more predictive and personalised therapy of the individual. This article will provide an overview of the various putative tear fluid biomarkers that have been identified to date, ranging from ocular surface disease and retinopathies to cancer and multiple sclerosis. Putative tear fluid biomarkers of ocular disorders, as well as the more recent field of systemic disease biomarkers, will be shown

East and west separation of Rhipicephalus sanguineus mitochondrial lineages in the Mediterranean Basin

Background: Rhipicephalus sanguineus belongs to a complex of hard tick species with high veterinary-medical significance. Recently, new phylogenetic units have been discovered within R. sanguineus, which therefore needs taxonomic revision. The present study was initiated to provide new information on the phylogeography of relevant haplotypes from less studied regions of Europe and Africa. With this aim, molecular-phylogenetic analyses of two mitochondrial markers were performed on 50 ticks collected in Hungary, the Balkans, countries along the Mediterranean Sea, Kenya and Ivory Coast. Results: In the "temperate lineage" of R. sanguineus, based on cytochrome c oxidase subunit 1 (cox1) and 16S rRNA genes, Rhipicephalus sp. I was only found in the eastern part of the Mediterranean Basin (with relatively homogenous haplotypes), whereas Rhipicephalus sp. II occurred in the middle-to-western part of this region (with phylogenetically dichotomous haplotypes). Ticks identified as R. leporis (based on morphology and cox1 gene) were found in Kenya and Ivory Coast. These clustered phylogenetically within R. sanguineus (s.l.) ("tropical lineage"). Conclusions: In the Mediterranean Basin two mitochondrial lineages of R. sanguineus, i. e. Rhipicephalus sp. I and Rhipicephalus sp. II exist, which show different geographical distribution. Therefore, data from this study confirm limited gene flow between Rhipicephalus sp. I and Rhipicephalus sp. II, but more evidence (analyses of nuclear markers, extensive morphological and biological comparison etc.) are necessary to infer if they belong to different species or not. The phylogenetic relationships of eastern and western African ticks, which align with R. leporis, need to be studied further within R. sanguineus (s.l.) ("tropical lineage")

A New Measure of Centrality for Brain Networks

Recent developments in network theory have allowed for the study of the structure and function of the human brain in terms of a network of interconnected components. Among the many nodes that form a network, some play a crucial role and are said to be central within the network structure. Central nodes may be identified via centrality metrics, with degree, betweenness, and eigenvector centrality being three of the most popular measures. Degree identifies the most connected nodes, whereas betweenness centrality identifies those located on the most traveled paths. Eigenvector centrality considers nodes connected to other high degree nodes as highly central. In the work presented here, we propose a new centrality metric called leverage centrality that considers the extent of connectivity of a node relative to the connectivity of its neighbors. The leverage centrality of a node in a network is determined by the extent to which its immediate neighbors rely on that node for information. Although similar in concept, there are essential differences between eigenvector and leverage centrality that are discussed in this manuscript. Degree, betweenness, eigenvector, and leverage centrality were compared using functional brain networks generated from healthy volunteers. Functional cartography was also used to identify neighborhood hubs (nodes with high degree within a network neighborhood). Provincial hubs provide structure within the local community, and connector hubs mediate connections between multiple communities. Leverage proved to yield information that was not captured by degree, betweenness, or eigenvector centrality and was more accurate at identifying neighborhood hubs. We propose that this metric may be able to identify critical nodes that are highly influential within the network