Though investigations into the use of massively parallel sequencing technologies for the generation of complete mitochondrial genome (mtGenome) profiles from difficult forensic specimens are well underway in multiple laboratories, the high quality population reference data necessary to support full mtGenome typing in the forensic context are lacking. To address this deficiency, we have developed 588 complete mtGenome haplotypes, spanning three U.S. population groups (African American, Caucasian and Hispanic) from anonymized, randomly-sampled specimens. Data production utilized an 8-amplicon, 135 sequencing reaction Sanger-based protocol, performed in semi-automated fashion on robotic instrumentation. Data review followed an intensive multi-step strategy that included a minimum of three independent reviews of the raw data at two laboratories; repeat screenings of all insertions, deletions, heteroplasmies, transversions and any additional private mutations; and a check for phylogenetic feasibility. For all three populations, nearly complete resolution of the haplotypes was achieved with full mtGenome sequences: 90.3-98.8% of haplotypes were unique per population, an improvement of 7.7-29.2% over control region sequencing alone, and zero haplotypes overlapped between populations. Inferred maternal biogeographic ancestry frequencies for each population and heteroplasmy rates in the control region were generally consistent with published datasets. In the coding region, nearly 90% of individuals exhibited length heteroplasmy in the 12418-12425 adenine homopolymer; and despite a relatively high rate of point heteroplasmy (23.8% of individuals across the entire molecule), coding region point heteroplasmies shared by more than one individual were notably absent, and transversion-type heteroplasmies were extremely rare. The ratio of nonsynonymous to synonymous changes among point heteroplasmies in the protein-coding genes (1:1.3) and average pathogenicity scores in comparison to data reported for complete substitutions in previous studies seem to provide some additional support for the role of purifying selection in the evolution of the human mtGenome. Overall, these thoroughly vetted full mtGenome population reference data can serve as a standard against which the quality and features of future mtGenome datasets (especially those developed via massively parallel sequencing) may be evaluated, and will provide a solid foundation for the generation of complete mtGenome haplotype frequency estimates for forensic applications.

A new real-time PCR detection system was developed for grapevine yellows (GY) using TaqMan minor groove binder probes and including two amplicons for group-specific detection of Flavescence dorée (FD) and Bois noir (BN) phytoplasmas, plus a universal phytoplasma amplicon. FD and BN amplicons were designed to amplify species-specific genomic DNA fragments and the universal amplicon to amplify the 16S ribosomal DNA region. Efficiency of PCR amplification, limit of detection, range of linearity and dynamic range were assessed for all three amplicons. The specificity of detection systems was tested on several other isolates of phytoplasmas and bacteria and on healthy field grapevine and insect samples. No cross-reactivity with other phytoplasma strains, plant or insect DNA was detected. The assay was compared with conventional PCR on more than 150 field grapevine, insect and field bindweed samples. Real-time PCR showed higher sensitivity as phytoplasmas were detected in several PCR-negative and in all PCR-positive samples. A data-mining analysis of results from both detection approaches also favoured real-time PCR over conventional PCR diagnostics. The developed procedure for detection of phytoplasmas in grapevine also included amplification of plant DNA co-extracted with phytoplasmic DNA, providing additional quality control for the DNA extraction and PCR amplification for each sample. The newly developed assay is a reliable, specific and sensitive method easily applicable to high-throughput diagnosis of GY.

Closed sets are being successfully applied in the context of compacted data representation for association rule learning. However, their use is mainly descriptive. This paper shows that, when considering labeled data, closed sets can be adapted for prediction and discrimination purposes by conveniently contrasting covering properties on positive and negative examples. We formally justify that these sets characterize the space of relevant combinations of features for discriminating the target class. In practice, identifying relevant/irrelevant combinations of features through closed sets is useful in many applications. Here we apply it to compacting emerging patterns and essential rules and to learn descriptions for subgroup discovery.

Benzene derivatives bearing at least one bulky alkyl group (i-Pr or t-Bu) were selectively and effectively iodinated using elemental iodine activated by 1-(chloromethyl)-4-fluoro-1,4-diazoniabicyclo[2.2.2]octane bis(tetrafluoroborate) (Selectfluor TM , F-TEDA-BF 4 ). Iodine atoms were progressively introduced at the most electron-rich and sterically less hindered position on the benzene ring. Not more than three iodine atoms could be progressively bonded to a target molecule bearing a i-Pr or t-Bu group.

Abstract. Contrast set mining aims at finding differences between different groups. This paper shows that a contrast set mining task can be transformed to a subgroup discovery task whose goal is to find descriptions of groups of individuals with unusual distributional characteristics with respect to the given property of interest. The proposed approach to contrast set mining through subgroup discovery was successfully applied to the analysis of records of patients with brain stroke (confirmed by a positive CT test), in contrast with patients with other neurological symptoms and disorders (having normal CT test results). Detection of coexisting risk factors, as well as description of characteristic patient subpopulations are important outcomes of the analysis.