Business Intelligence (BI) software aims to enable business users to easily access and analyze relevant enterprise information so that they can make timely and fact-based decisions. However, despite userfriendly features such as dashboards and other visualizations, business users still find BI software hard to use and inflexible for their needs. Furthermore, current BI initiatives require significant efforts by IT specialists to understand business operations and requirements, in order to build BI applications and help formulate queries. In this paper, we present a vision for BI that is driven by enterprise modeling. The Business Intelligence Model (BIM) aims to enable business users to conceptualize business operations and strategies and performance indicators in a way that can be connected to enterprise data through highly automated tools. The BIM draws upon well-established business practices such as Balanced Scorecard and Strategy Maps as well as requirements and conceptual modeling techniques such as goal modeling. The connection from BIM to databases is supported by a complementary research effort on conceptual data integration.
Enterococci are lactic acid bacteria that are commonly found in food and in animal gut. Since 16 S ribosomal RNA (rRNA) sequences, genetic markers for bacterial identification, are similar among several Enterococcus species, it is very difficult to determine the correct species based on only 16 S rRNA sequences. Therefore, we developed a rapid method for the identification of different Enterococcus species using comparative genomics. We compared 38 genomes of 13 Enterococcus species retrieved from the National Center of Biotechnology Information database and identified 25,623 orthologs. Among the orthologs, four genes were specific to four Enterococcus species (Enterococcus faecalis, Enterococcus faecium, Enterococcus hirae, and Enterococcus durans). We designed species-specific primer sets targeting the genes and developed a multiplex PCR using primer sets that could distinguish the four Enterococcus species among the nine strains of Enterococcus species that were available locally. The multiplex PCR method also distinguished the four species isolated from various environments, such as feces of chicken and cow, meat of chicken, cow, and pigs, and fermented soybeans (Cheonggukjang and Doenjang). These results indicated that our novel multiplex PCR using species-specific primers could identify the four Enterococcus species in a rapid and easy way. This method will be useful to distinguish Enterococcus species in food, feed, and clinical settings.
Boesenbergia pandurata
and its major active ingredient, panduratin A (PAN), exhibit antibacterial, anti-oxidant, anti-inflammatory, and anti-obesity effects. We explored the time course of the plasma and tissue (in the major organs, gums and skin) concentrations of PAN after oral administration of a
B. pandurata
extract to rats. Model-dependent analysis was used to quantify the skin distribution of PAN after systemic exposure. The PAN level peaked at 1.12 ± 0.22 μg/mL after 3 h, and then biexponentially decayed with a terminal half-life of 9 h. The mean clearance (Cl/F) was 2.33 ± 0.68 L/h/kg. The PAN levels in organs were in the following order (highest first): skin, lung, heart, gum, liver, spleen, kidney, and brain. For the first time, the time course of PAN levels in plasma and organs was investigated after oral administration of a BPE. This study helps to explain the pharmacological activities of PAN in the skin and gums. The pharmacokinetic model provided data in the plasma and skin concentrations of PAN, which are of fundamental importance to evaluate its efficacy.
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