Microarray analysis of autoimmune diseases by machine learning procedures

—Microarray-based global gene expression profiling, with the use of sophisticated statistical algorithms is providing new insights into the pathogenesis of autoimmune diseases. We have applied a novel statistical technique for gene selection based on machine learning approaches to analyze microarray expression data gathered from patients with systemic lupus erythematosus (SLE) and primary antiphospholipid syndrome (PAPS), two autoimmune diseases of unknown genetic origin that share many common features. The methodology included a combination of three data discretization policies, a consensus gene selection method, and a multivariate correlation measurement. A set of 150 genes was found to discriminate SLE and PAPS patients from healthy individuals. Statistical validations demonstrate the relevance of this gene set from an univariate and multivariate perspective. Moreover, functional characterization of these genes identified an interferon-regulated gene signature, consistent with previous reports. It also revealed the existence of other regulatory pathways, including those regulated by PTEN, TNF, and BCL-2, which are altered in SLE and PAPS. Remarkably, a significant number of these genes carry E2F binding motifs in their promoters, projecting a role for E2F in the regulation of autoimmunity.

Search strategies and the automated control of plant diseases

We propose the use of the "infotaxis" search strategy as the navigation system of a robotic platform, able to search and localize infectious foci by detecting the changes in the profile of volatile organic compounds emitted by and infected plant. We builded a simple and cost effective robot platform that substitutes odour sensors in favour of light sensors and study their robustness and performance under non ideal conditions such as the exitence of obstacles due to land topology or weeds.

Fungal microbiota from rain water and pathogenicity of Fusarium species isolated from atmospheric dust and rainfall dust

In order to determine the presence of Fusarium spp. in atmospheric dust and rainfall dust, samples were collected during September 2007, and July, August, and October 2008. The results reveal the prevalence of airborne Fusarium species coming from the atmosphere of the South East coast of Spain. Five different Fusarium species were isolated from the settling dust: Fusarium oxysporum, F. solani, F. equiseti, F. dimerum, and F. proliferatum. Moreover, rainwater samples were obtained during significant rainfall events in January and February 2009. Using the dilution-plate method, 12 fungal genera were identified from these rainwater samples. Specific analyses of the rainwater revealed the presence of three species of Fusarium: F. oxysporum, F. proliferatum and F. equiseti. A total of 57 isolates of Fusarium spp. obtained from both rainwater and atmospheric rainfall dust sampling were inoculated onto melon (Cucumis melo L.) cv. Piñonet and tomato (Lycopersicon esculentum Mill.) cv. San Pedro. These species were chosen because they are the main herbaceous crops in Almeria province. The results presented in this work indicate strongly that spores or propagules of Fusarium are able to cross the continental barrier carried by winds from the Sahara (Africa) to crop or coastal lands in Europe. Results show differences in the pathogenicity of the isolates tested. Both hosts showed root rot when inoculated with different species of Fusarium, although fresh weight measurements did not bring any information about the pathogenicity. The findings presented above are strong indications that long-distance transmission of Fusarium propagules may occur. Diseases caused by species of Fusarium are common in these areas. They were in the past, and are still today, a problem for greenhouses crops in Almería, and many species have been listed as pathogens on agricultural crops in this region. Saharan air masses dominate the Mediterranean regions. The evidence of long distance dispersal of Fusarium spp. by atmospheric dust and rainwater together with their proved pathogenicity must be taken into account in epidemiological studies.