28 research outputs found
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Use and cost of disease-modifying therapies by Sonya Slifka Study participants: has anything really changed since 2000 and 2009?
Background:Disease-modifying therapies benefit individuals with relapsing forms of multiple sclerosis, but their utility remains unclear for those without relapses. Objective:To determine disease-modifying therapy use and costs in 2009, compare use in 2009 and 2000, and examine compliance with evidence-based guidelines. Methods:We determined the extent and characteristics of disease-modifying therapy use by participants in the Sonya Slifka Longitudinal Multiple Sclerosis Study (Slifka) in 2000 (n=2156) and 2009 (n=2361) and estimated out-of-pocket and total (payer) costs for 2009. Two multivariable logistic regressions predicted disease-modifying therapy use. Results:Disease-modifying therapy use increased from 55.3% in 2000 to 61.5% in 2009. In 2009, disease-modifying therapy use was reported by 76.5% of participants with relapsing-remitting multiple sclerosis, 73.2% with progressive-relapsing multiple sclerosis, 62.5% with secondary progressive multiple sclerosis, and 41.8% with primary progressive multiple sclerosis. Use was significantly associated with relapsing-remitting multiple sclerosis, shorter duration of illness, one to two relapses per year, non-ambulatory symptoms, using a cane, younger age, higher family income, and having health insurance. Average annual costs in 2009 were US16,302-18,928 for payers. Conclusion:Use rates were highest for individuals with relapsing-remitting multiple sclerosis, but substantial for those with progressive courses although clinical trials have not demonstrated significant benefits for them
TRY plant trait database â 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 traitâbased 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 âplant growth formâ. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and traitâenvironmental 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
pHMA, a pH-sensitive GFP reporter for cell engulfment in Drosophila embryos, tissues and cells
Engulfment of apoptotic cells by phagocytosis ensures the removal of unwanted and defective cells. We developed a genetically encoded marker for cell engulfment, pHMA, which consists of the pH-sensitive derivative of GFP, pHluorin, fused to the actin-binding domain of Moesin. In healthy cells of Drosophila embryos and cultured cells, pHMA resides at the cell cortex. In dying cells, pHMA loses its cortical localization and reports a modest decrease in pH. In embryos, the dying cells lose their apical contacts, then move basally and are ultimately engulfed by neighboring cells or macrophages. The cell corpse material is strongly acidified soon after engulfment and persists in the phagocytic cell for several hours. Changes in the pHMA signal correlate well with increases or decreases in apoptosis. These data show that pHMA is a useful reporter for cell engulfment and can be used in screening for mutations that affect cell engulfment
Immunoproteomics technologies in the discovery of autoantigens in autoimmune diseases
AbstractProteomics technologies are often used for the identification of protein targets of the immune system. Here, we discuss the immunoproteomics technologies used for the discovery of autoantigens in autoimmune diseases where immune system dysregulation plays a central role in disease onset and progression. These autoantigens and associated autoantibodies can be used as potential biomarkers for disease diagnostics, prognostics and predicting/monitoring drug responsiveness (theranostics). Here, we compare a variety of methods such as mass spectrometry (MS)-based [serological proteome analysis (SERPA), antibody mediated identification of antigens (AMIDA), circulating immune complexome (CIC) analysis, surface enhanced laser desorption/ionization-time of flight (SELDI-TOF)], nucleic acid based serological analysis of antigens by recombinant cDNA expression cloning (SEREX), phage immunoprecipitation sequencing (PhIP-seq) and array-based immunoscreening (proteomic microarrays), luciferase immunoprecipitation systems (LIPS), nucleic acid programmable protein array (NAPPA) methods. We also review the relevance of immunoproteomic data generated in the last 10 years, with a focus on the aforementioned MS based methods