First identification of Francisella noatunensis subsp. orientalis causing mortality in Mexican tilapia Oreochromis spp.

Francisellosis, an emerging disease in tilapia Oreochromis spp., is caused by the facultative, intracellular bacterium Francisella noatunensis subsp. orientalis, which is present in various countries where tilapia farming is commercially important. We confirmed the presence of francisellosis in Mexican tilapia cultures in association with an outbreak during the second semester of 2012. Broodstock fish presented a mortality rate of approximately 40%, and disease was characterized by histologically classified granulomas, or whitish nodules, in different organs, mainly the spleen and kidney. Through DNA obtained from infected tissue and pure cultures in a cysteine heart medium supplemented with hemoglobin, F. noatunensis subsp. orientalis was initially confirmed through the amplification and analysis of the 16S rRNA gene and the internal transcribed spacer region. Phylogenetic analysis of these genes demonstrated close similarity with previously reported F. noatunensis subsp. orientalis sequences obtained from infected tilapia from various countries. The identification of this subspecies as the causative agent of the outbreak was confirmed using the iglC gene as a target sequence, which showed 99.5% identity to 2 F. noatunensis subsp. orientalis strains (Ethime-1 and Toba04). These findings represent the first documented occurrence of francisellosis in Mexican tilapia cultures, which highlights the importance of establishing preventative measures to minimize the spread of this disease within the Mexican aquaculture industry.

Modeling Verdict Outcomes Using Social Network Measures: The Watergate and Caviar Network Cases.

Modelling criminal trial verdict outcomes using social network measures is an emerging research area in quantitative criminology. Few studies have yet analyzed which of these measures are the most important for verdict modelling or which data classification techniques perform best for this application. To compare the performance of different techniques in classifying members of a criminal network, this article applies three different machine learning classifiers-Logistic Regression, Naïve Bayes and Random Forest-with a range of social network measures and the necessary databases to model the verdicts in two real-world cases: the U.S. Watergate Conspiracy of the 1970's and the now-defunct Canada-based international drug trafficking ring known as the Caviar Network. In both cases it was found that the Random Forest classifier did better than either Logistic Regression or Naïve Bayes, and its superior performance was statistically significant. This being so, Random Forest was used not only for classification but also to assess the importance of the measures. For the Watergate case, the most important one proved to be betweenness centrality while for the Caviar Network, it was the effective size of the network. These results are significant because they show that an approach combining machine learning with social network analysis not only can generate accurate classification models but also helps quantify the importance social network variables in modelling verdict outcomes. We conclude our analysis with a discussion and some suggestions for future work in verdict modelling using social network measures.

Identification and genetic characterization of Piscirickettsia salmonis in native fish from southern Chile.

Piscirickettsia salmonis is the etiological agent of piscirickettsiosis, a severe disease causing high mortalities in salmonids. This bacterium has been previously identified and isolated in all cultivated salmonids in Chile and worldwide, including Salmo salar, Oncorhynchus kisutch, and O. mykiss, in addition to being found in non-salmonid species such as Dicentrarchus labrax and Atractoscion nobilis. In this study, the 16S rRNA gene and intergenic spacer ITS-1 of P. salmonis were amplified by PCR from DNA samples extracted from the native Chilean fish species Eleginops maclovinus, Odontesthes regia, Sebastes capensis, and Salilota australis. Analysis of the 16S rRNA sequences from O. regia demonstrated a close phylogenetic relationship with the 16S rRNA gene in the Chilean EM-90 strain. The 16S rRNA sequences from E. maclovinus, S. capensis, and S. australis were related to the Chilean LF-89 sequence and Scottish strains. To confirm these findings, analysis of P. salmonis ITS-1 sequences obtained from the 4 sampled native species demonstrated a high degree of identity and a close phylogenetic relationship with Chilean P. salmonis sequences, including LF-89 and EM-90. These results suggest a strong relationship between the nucleotide sequences from the 16S rRNA and ITS-1 genes amplified from native fish with those sequences described in the first P. salmonis strains to be identified and isolated in Chile.