Disseminated Toxoplasmosis in a Patient with Non-Hodgkin Lymphoma

Abstract : Toxoplasmosis is a well-recognized opportunistic disease in HIV-infected individuals that is caused by the reactivation of a previous infection, primarily in the central nervous system, during profound immunodeficiency. Toxoplasmosis has been described more rarely in patients with cancer and chemotherapy. We report a case of a patient with a history of chemotherapy for non-Hodgkin lymphoma who developed pain and progressive paresthesia of the right arm 6 weeks after remission. Relapsing lymphoma was suspected, and steroid and radiation treatment were initiated, but the patient died 5 days later due to multiple organ failure. Autopsy revealed disseminated toxoplasmosis. This case illustrates that toxoplasmosis should be suspected in patients with neoplastic disease, especially lymphomas, who present with unexplained neurologic, pulmonary, or febrile symptoms during or after chemotherap

A Spectral Algorithm with Additive Clustering for the Recovery of Overlapping Communities in Networks

This paper presents a novel spectral algorithm with additive clustering designed to identify overlapping communities in networks. The algorithm is based on geometric properties of the spectrum of the expected adjacency matrix in a random graph model that we call stochastic blockmodel with overlap (SBMO). An adaptive version of the algorithm, that does not require the knowledge of the number of hidden communities, is proved to be consistent under the SBMO when the degrees in the graph are (slightly more than) logarithmic. The algorithm is shown to perform well on simulated data and on real-world graphs with known overlapping communities.Comment: Journal of Theoretical Computer Science (TCS), Elsevier, A Para\^itr

Effects of Contact Network Models on Stochastic Epidemic Simulations

The importance of modeling the spread of epidemics through a population has led to the development of mathematical models for infectious disease propagation. A number of empirical studies have collected and analyzed data on contacts between individuals using a variety of sensors. Typically one uses such data to fit a probabilistic model of network contacts over which a disease may propagate. In this paper, we investigate the effects of different contact network models with varying levels of complexity on the outcomes of simulated epidemics using a stochastic Susceptible-Infectious-Recovered (SIR) model. We evaluate these network models on six datasets of contacts between people in a variety of settings. Our results demonstrate that the choice of network model can have a significant effect on how closely the outcomes of an epidemic simulation on a simulated network match the outcomes on the actual network constructed from the sensor data. In particular, preserving degrees of nodes appears to be much more important than preserving cluster structure for accurate epidemic simulations.Comment: To appear at International Conference on Social Informatics (SocInfo) 201

Comparing spectra of graph shift operator matrices

Typically network structures are represented by one of three different graph shift operator matrices: the adjacency matrix and unnormalised and normalised Laplacian matrices. To enable a sensible comparison of their spectral (eigenvalue) properties, an affine transform is first applied to one of them, which preserves eigengaps. Bounds, which depend on the minimum and maximum degree of the network, are given on the resulting eigenvalue differences. The monotonicity of the bounds and the structure of networks are related. Bounds, which again depend on the minimum and maximum degree of the network, are also given for normalised eigengap differences, used in spectral clustering. Results are illustrated on the karate dataset and a stochastic block model. If the degree extreme difference is large, different choices of graph shift operator matrix may give rise to disparate inference drawn from network analysis; contrariwise, smaller degree extreme difference results in consistent inference

Biological weed control to relieve millions from ambrosia allergies in Europe

Invasive alien species (IAS) can substantially affect ecosystem services and human well-being. However, quantitative assessments of their impact on human health are rare, and the benefits of implementing sustainable IAS management likely to be underestimated. Here we report the effects of the allergenic plant Ambrosia artemisiifolia on public health in Europe and the potential impact of the accidentally introduced leaf beetle Ophraella communa on the number of patients and healthcare costs. We find that, prior to the establishment of O. communa, some 13.5 million persons suffered from Ambrosia-induced allergies in Europe, causing costs of Euro 7.4 billion annually. Our projections reveal that biological control of A. artemisiifolia will reduce the number of patients by approximately 2.3 million and the health costs by Euro 1.1 billion per year. Our conservative calculations indicate that the currently discussed economic costs of IAS underestimate the real costs and thus also the benefits from biological control

Predicting Abundances of Invasive Ragweed Across Europe Using a “Top-down” Approach

Common ragweed (Ambrosia artemisiifolia L.) is a widely distributed and harmful invasive plant that is an important source of highly allergenic pollen grains and prominent crop weed. As a result, ragweed causes huge costs to both human health and agriculture in affected areas. Efficient mitigation requires accurate mapping of ragweed densities that, until now, has not been achieved accurately for the whole of Europe. Here we provide two inventories of common ragweed abundances with grid resolutions of 1 km and 10 km. These “top-down” inventories integrate pollen data from 349 stations in Europe with habitat and landscape management information, derived from land cover data and expert knowledge. This allows us to cover areas where surface observations are missing. Model results were validated using “bottom–up” data of common ragweed in Austria and Serbia. Results show high agreement between the two analytical methods. The inventory shows that areas with the lowest ragweed abundances are found in Northern and Southern European countries and the highest abundances are in parts of Russia, parts of Ukraine and the Pannonian Plain. Smaller hotspots are found in Northern Italy, the Rhône Valley in France and in Turkey. The top-down approach is based on a new approach that allows for cross continental studies and is applicable to other anemophilous species. Due to its simplicity, it can be used to investigate such species that are difficult and costly to identify at larger scales using traditional vegetation surveys or remote sensing. The final inventory is open source and available as a georeferenced tif file, allowing for multiple usages, reducing costs for health services and agriculture through well-targeted management interventions

Seed viability of common ragweed (Ambrosia artemisiifolia L.) is affected by seed origin and age, but also by testing method and laboratory

Plant science

Ecological Indicator Values for Europe (EIVE) 1.0

Aims: To develop a consistent ecological indicator value system for Europe for five of the main plant niche dimensions: soil moisture (M), soil nitrogen (N), soil reaction (R), light (L) and temperature (T). Study area: Europe (and closely adjacent regions). Methods: We identified 31 indicator value systems for vascular plants in Europe that contained assessments on at least one of the five aforementioned niche dimensions. We rescaled the indicator values of each dimension to a continuous scale, in which 0 represents the minimum and 10 the maximum value present in Europe. Taxon names were harmonised to the Euro+Med Plantbase. For each of the five dimensions, we calculated European values for niche position and niche width by combining the values from the individual EIV systems. Using T values as an example, we externally validated our European indicator values against the median of bioclimatic conditions for global occurrence data of the taxa. Results: In total, we derived European indicator values of niche position and niche width for 14,835 taxa (14,714 for M, 13,748 for N, 14,254 for R, 14,054 for L, 14,496 for T). Relating the obtained values for temperature niche position to the bioclimatic data of species yielded a higher correlation than any of the original EIV systems (r = 0.859). The database: The newly developed Ecological Indicator Values for Europe (EIVE) 1.0, together with all source systems, is available in a flexible, harmonised open access database. Conclusions: EIVE is the most comprehensive ecological indicator value system for European vascular plants to date. The uniform interval scales for niche position and niche width provide new possibilities for ecological and macroecological analyses of vegetation patterns. The developed workflow and documentation will facilitate the future release of updated and expanded versions of EIVE, which may for example include the addition of further taxonomic groups, additional niche dimensions, external validation or regionalisation

Buffered memory: a hypothesis for the maintenance of functional, virus-specific CD8(+) T cells during cytomegalovirus infection.

Chronic infections have been a major topic of investigation in recent years, but the mechanisms that dictate whether or not a pathogen is successfully controlled are incompletely understood. Cytomegalovirus (CMV) is a herpesvirus that establishes a persistent infection in the majority of people in the world. Like other herpesviruses, CMV is well controlled by an effective immune response and induces little, if any, pathology in healthy individuals. However, controlling CMV requires continuous immune surveillance, and thus, CMV is a significant cause of morbidity and death in immune-compromised individuals. T cells in particular play an important role in controlling CMV and both CD4(+) and CD8(+) CMV-specific T cells are essential. These virus-specific T cells persist in exceptionally large numbers during the infection, traffic into peripheral tissues and remain functional, making CMV an attractive vaccine vector for driving CMV-like T cell responses against recombinant antigens of choice. However, the mechanisms by which these T cells persist and differentiate while remaining functional are still poorly understood, and we have no means to promote their development in immune-compromised patients at risk for CMV disease. In this review, I will briefly summarize our current knowledge of CMV-specific CD8(+) T cells and propose a mechanism that may explain their maintenance and preservation of function during chronic infection