Epitope mapping of cytochrome P450 cholesterol side-chain cleavage enzyme by sera from patients with autoimmune polyglandular syndrome type 1

OBJECTIVE: Autoimmune polyglandular syndrome type 1 (APS-1) is a disease associated with defects of the autoimmune regulator gene and is characterized by autoimmune lesions of several tissues, predominantly endocrine glands, with multiple autoantibodies. In this study we describe autoantigenic epitopes on cholesterol side-chain cleavage enzyme (P450scc) using sera from Finnish and Sardinian patients with APS-1, and analyze the epitope reactivities during disease follow-up. METHODS: A series of P450scc cDNA fragments were expressed in E. coli and tested by immunoblotting assay using the patients' sera. RESULTS: Epitope regions were found over the whole P450scc molecule except the last N- (amino acids (aa) 1-40) and C-termini (aa 456-521). The strongest reactivity with patients' sera was found with central and C-terminal regions of the P450scc protein. All studied patients had IgG1 subclass antibodies. CONCLUSIONS: The results show that Finnish and Sardinian patients with APS-1 have similar, polyclonal immune reactions against P450scc, and that epitope reactivities did not change during the disease course. These results support the opinion that autoantibodies against P450scc and their epitope reactivity pattern are formed at an early stage of steroidogenic autoimmunity

Visual Causality: Investigating Graph Layouts for Understanding Causal Processes

Causal diagrams provide a graphical formalism indicating how statistical models can be used to study causal processes. Despite the extensive research on the efficacy of aesthetic graphic layouts, the causal inference domain has not benefited from the results of this research. In this paper, we investigate the performance of graph visualisations for supporting users’ understanding of causal graphs. Two studies were conducted to compare graph visualisations for understanding causation and identifying confounding variables in a causal graph. The first study results suggest that while adjacency matrix layouts are better for understanding direct causation, node-link diagrams are better for understanding mediated causation along causal paths. The second study revealed that node-link layouts, and in particular layouts created by a radial algorithm, are more effective for identifying confounder and collider variables

Heavy metal and nitrogen concentrations in mosses are declining across Europe whilst some “hotspots” remain in 2010

In recent decades, naturally growing mosses have been used successfully as biomonitors of atmospheric deposition of heavy metals and nitrogen. Since 1990, the European moss survey has been repeated at five-yearly intervals. In 2010, the lowest concentrations of metals and nitrogen in mosses were generally found in northern Europe, whereas the highest concentrations were observed in (south-)eastern Europe for metals and the central belt for nitrogen. Averaged across Europe, since 1990, the median concentration in mosses has declined the most for lead (77%), followed by vanadium (55%), cadmium (51%), chromium (43%), zinc (34%), nickel (33%), iron (27%), arsenic (21%, since 1995), mercury (14%, since 1995) and copper (11%). Between 2005 and 2010, the decline ranged from 6% for copper to 36% for lead; for nitrogen the decline was 5%. Despite the Europe-wide decline, no changes or increases have been observed between 2005 and 2010 in some (regions of) countries

Modelling spatial patterns of correlations between concentrations of heavy metals in mosses and atmospheric deposition in 2010 across Europe

BackgroundThis paper aims to investigate the correlations between the concentrations of nine heavy metals in moss and atmospheric deposition within ecological land classes covering Europe. Additionally, it is examined to what extent the statistical relations are affected by the land use around the moss sampling sites. Based on moss data collected in 2010/2011 throughout Europe and data on total atmospheric deposition modelled by two chemical transport models (EMEP MSC-E, LOTOS-EUROS), correlation coefficients between concentrations of heavy metals in moss and in modelled atmospheric deposition were specified for spatial subsamples defined by ecological land classes of Europe (ELCE) as a spatial reference system. Linear discriminant analysis (LDA) and logistic regression (LR) were then used to separate moss sampling sites regarding their contribution to the strength of correlation considering the areal percentage of urban, agricultural and forestry land use around the sampling location. After verification LDA models by LR, LDA models were used to transform spatial information on the land use to maps of potential correlation levels, applicable for future network planning in the European Moss Survey.ResultsCorrelations between concentrations of heavy metals in moss and in modelled atmospheric deposition were found to be specific for elements and ELCE units. Land use around the sampling sites mainly influences the correlation level. Small radiuses around the sampling sites examined (5km) are more relevant for Cd, Cu, Ni, and Zn, while the areal percentage of urban and agricultural land use within large radiuses (75-100km) is more relevant for As, Cr, Hg, Pb, and V. Most valid LDA models pattern with error rates of <40% were found for As, Cr, Cu, Hg, Pb, and V. Land use-dependent predictions of spatial patterns split up Europe into investigation areas revealing potentially high (=above-average) or low (=below-average) correlation coefficients.ConclusionsLDA is an eligible method identifying and ranking boundary conditions of correlations between atmospheric deposition and respective concentrations of heavy metals in moss and related mapping considering the influence of the land use around moss sampling sites

Epitope mapping of cytochrome P450 cholesterol side-chain cleavage enzyme by sera from patients with autoimmune polyglandular syndrome type 1

OBJECTIVE: Autoimmune polyglandular syndrome type 1 (APS-1) is a disease associated with defects of the autoimmune regulator gene and is characterized by autoimmune lesions of several tissues, predominantly endocrine glands, with multiple autoantibodies. In this study we describe autoantigenic epitopes on cholesterol side-chain cleavage enzyme (P450scc) using sera from Finnish and Sardinian patients with APS-1, and analyze the epitope reactivities during disease follow-up. METHODS: A series of P450scc cDNA fragments were expressed in E. coli and tested by immunoblotting assay using the patients' sera. RESULTS: Epitope regions were found over the whole P450scc molecule except the last N- (amino acids (aa) 1-40) and C-termini (aa 456-521). The strongest reactivity with patients' sera was found with central and C-terminal regions of the P450scc protein. All studied patients had IgG1 subclass antibodies. CONCLUSIONS: The results show that Finnish and Sardinian patients with APS-1 have similar, polyclonal immune reactions against P450scc, and that epitope reactivities did not change during the disease course. These results support the opinion that autoantibodies against P450scc and their epitope reactivity pattern are formed at an early stage of steroidogenic autoimmunit