Publications by authors named "Michael D Kane"

To capitalize on the vast potential of patient genetic information to aid in assuring drug safety, a substantial effort is needed in both the training of healthcare professionals and the operational enablement of clinical environments. Our research aims to satisfy these needs through the development of a drug safety assurance information system (GeneScription) based on clinical genotyping that utilizes patient-specific genetic information to predict and prevent adverse drug responses. In this paper, we present the motivations for this work, the algorithms at the heart of GeneScription, and a discussion of our system and its uses.

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Objectives: To implement an elective course in pharmacogenomics designed to teach pharmacy students about the fundamentals of pharmacogenomics and the anticipated changes it will bring to the profession.

Design: The 8 sessions of the course covered the basics of pharmacogenomics, genomic biotechnology, implementation of pharmacogenetics in pharmacy, information security and privacy, ethical issues related to the use of genomic data, pharmacoepidemiology, and use and promotion of GeneScription, a software program designed to mimic the professional pharmacy environment.

Assessment: Student grades were based on completion of a patient education pamphlet, a 2-page paper on pharmacogenomics, and precourse and postcourse survey instruments.

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Endocrine disrupting chemicals (EDCs) are known to contaminate aquatic environments and alter the growth and reproduction of organisms. The objective of this study was to evaluate the sensitivity and utility of fathead minnow (Pimephales promelas) early life-stages as a model to measure effects of estrogenic and antiestrogenic EDCs on physiological and gene expression endpoints relative to growth and reproduction. Embryos (<24-h postfertilization, hpf) were exposed to a potent estrogen (17α-ethinyl estradiol, EE(2) , 2, 10, and 50 ng L(-1)); a weak estrogen (mycotoxin zearalenone, ZEAR, same concentrations as above); an antiestrogen (ZM 189, 154; 40, 250, and 1000 ng L(-1)); and to mixtures of EE(2) and ZM until swim-up stage (∼170 hpf).

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Knowledge of the central role of high-risk human papillomavirus (HPV) in cervical carcinogenesis, coupled with an emerging need to monitor the efficacy of newly introduced HPV vaccines, warrant development and evaluation of type-specific, quantitative HPV detection methods. In the present study, a prototype PCR and mass spectroscopy (PCR-MS)-based method to detect and quantitate 13 high-risk HPV types is compared to the Hybrid Capture 2 High-Risk HPV DNA test (HC2; Digene Corp., Gaithersburg, MD) in 199 cervical scraping samples and to DNA sequencing in 77 cervical tumor samples.

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Recently, researchers have begun looking at changes in gene expression in the fathead minnow (Pimephales promelas) after contaminant exposure as a way to develop biomarkers of exposure and effects. However, the bulk of this research has been conducted on adults, with few studies focusing on early life stages. Expression of selected genes important in growth, development, and reproduction in teleosts was quantified by quantitative polymerase chain reaction during different developmental time periods (from 0 to 28 d postfertilization [dpf]).

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The rationale and overall system-wide behavior of a clinical genotyping information system (both DNA analysis and data management) requires a near-term, scalable approach, which is emerging in the focused implementation of pharmacogenomics and drug safety assurance. The challenges to implementing a successful clinical genotyping system are described, as are how the benefits of a focused, near-term system for drug safety assessment and assurance overcome the logistical and operational challenges that perpetually hinder the development of a societal-scale clinical genotyping system. This rationale is based on the premise that a focused application domain for clinical genotyping, specifically drug safety assurance, provides a transition paradigm for both professionals and consumers of healthcare, thereby facilitating the movement of genotyping from bench to bedside and paving the way for the adoption of prognostic and diagnostic applications in clinical genomics.

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Background: Systems biology aims to understand biological systems on a comprehensive scale, such that the components that make up the whole are connected to one another and work through dependent interactions. Molecular correlations and comparative studies of molecular expression are crucial to establishing interdependent connections in systems biology. The existing software packages provide limited data mining capability.

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A DNA hybridization based optical detection platform for the detection of foodborne pathogens has been developed with virtually zero probability of the false negative signal. This portable, low-cost and real-time assaying detection platform utilizes the color changing molecular beacon as a probe for the optical detection of the target sequence. The computer-controlled detection platform exploits the target hybridization induced change of fluorescence color due to the Förster (fluorescence) resonance energy transfer (FRET) between a pair of spectrally shifted fluorophores conjugated to the opposite ends of a beacon (oligonucleotide probe).

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Polycyclic aromatic hydrocarbons (PAHs) are widespread environmental DNA-damaging agents regarded as risk factors for human disease, including lung and breast cancer. The biotransformation of PAHs to carcinogenic metabolites is mediated by the aromatic hydrocarbon receptor (AhR), which activates transcription at xenobiotic responsive elements (XREs = 5'-GCGTG-3') found in the promoter regions of genes encoding for detoxifying enzymes, including CYP1A1 and CYP1B1. In this study, we wished to identify novel biomarkers that may be useful in monitoring critical carcinogenic events of the breast induced by PAHs.

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Unprecedented growth in the interdisciplinary domain of biomedical informatics reflects the recent advancements in genomic sequence availability, high-content biotechnology screening systems, as well as the expectations of computational biology to command a leading role in drug discovery and disease characterization. These forces have moved much of life sciences research almost completely into the computational domain. Importantly, educational training in biomedical informatics has been limited to students enrolled in the life sciences curricula, yet much of the skills needed to succeed in biomedical informatics involve or augment training in information technology curricula.

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The adoption and utilization of genomic technologies in healthcare requires that many issues surrounding the integrity of these assay platforms, as well as their overall impact on human health, be definitive. Many concerns common to DNA microarray production must be addressed to exploit the high-content screening capabilities of this assay platform for both genotyping and gene expression profiling in the clinic. Equally important to the success of genomic technology in healthcare is the development of a supporting information system that offers impact at both the personal and population level, and facilitates the adoption, use and, ultimately, impact of genomic information in therapeutic decision support.

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The 3rd International Symposium on Early Toxicity Screening: Early ADME-Tox Screening Approaches included presentations by primarily non-academic scientists, including biotechnology companies, pharmaceutical scientists and contract research service leaders. A central theme heard throughout the presentations involved the fundamental objectives of and obstacles to ADME and toxicity testing during drug development. In summary, successful preclinical drug safety assessment involves understanding a model's limited ability to mimic the human drug response, increasing the model's ability to mimic the human drug response, and adopting new strategies that model better human drug responses, while simultaneously conducting safety assessment more quickly, more thoroughly and more cost effectively.

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The utility of genomic technology and bioinformatic analytical support to provide new and needed insight into the molecular basis of disease, development, and diversity continues to grow as more research model systems and populations are investigated. Yet deriving results that meet a specific set of research objectives requires aligning or coordinating the design of the experiment, the laboratory techniques, and the data analysis. The following paragraphs describe several important interdependent factors that need to be considered to generate high quality data from the microarray platform.

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