Satellite DNA as a target for TaqMan real-time PCR detection of the pinewood nematode, Bursaphelenchus xylophilus

The pinewood nematode (PWN), Bursaphelenchus xylophilus , is a major pathogen of conifers, which impacts on forest health, natural ecosystem stability and international trade. As a consequence, it has been listed as a quarantine organism in Europe. A real-time PCR approach based on TaqMan chemistry was developed to detect this organism. Specific probe and primers were designed based on the sequence of the Msp I satellite DNA family previously characterized in the genome of the nematode. The method proved to be specific in tests with target DNA from PWN isolates from worldwide origin. From a practical point of view, detection limit was 1 pg of target DNA or one individual nematode. In addition, PWN genomic DNA or single individuals were positively detected in mixed samples in which B. xylophilius was associated with the closely related non-pathogenic species B. mucronatus , up to the limit of 0.01% or 1% of the mixture, respectively. The real-time PCR assay was also used in conjunction with a simple DNA extraction method to detect PWN directly in artificially infested wood samples. These results demonstrate the potential of this assay to provide rapid, accurate and sensitive molecular identification of the PWN in relation to pest risk assessment in the field and quarantine regulation.

Screening a Case Base for Stroke Disease Detection

Stroke stands for one of the most frequent causes of death, without distinguishing age or genders. Despite representing an expressive mortality fig-ure, the disease also causes long-term disabilities with a huge recovery time, which goes in parallel with costs. However, stroke and health diseases may also be prevented considering illness evidence. Therefore, the present work will start with the development of a decision support system to assess stroke risk, centered on a formal framework based on Logic Programming for knowledge rep-resentation and reasoning, complemented with a Case Based Reasoning (CBR) approach to computing. Indeed, and in order to target practically the CBR cycle, a normalization and an optimization phases were introduced, and clustering methods were used, then reducing the search space and enhancing the cases re-trieval one. On the other hand, and aiming at an improvement of the CBR theo-retical basis, the predicates` attributes were normalized to the interval 0…1, and the extensions of the predicates that match the universe of discourse were re-written, and set not only in terms of an evaluation of its Quality-of-Information (QoI), but also in terms of an assessment of a Degree-of-Confidence (DoC), a measure of one`s confidence that they fit into a given interval, taking into account their domains, i.e., each predicate attribute will be given in terms of a pair (QoI, DoC), a simple and elegant way to represent data or knowledge of the type incomplete, self-contradictory, or even unknown.