130 research outputs found

    Pharmaceutical Characterization of MyoNovin, a Novel Skeletal Muscle Regenerator: in silico, in vitro and in vivo Studies.

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    MyoNovin is a novel skeletal muscle-regenerating compound developed through synthesis of two nitro groups onto a guaifenesin backbone to deliver nitric oxide to skeletal muscle with a potential to treat muscle atrophy. The purpose of this study was to utilize in silico, in vitro, and in vivo approaches to characterize MyoNovin and examine its safety, biodistribution, and feasibility for drug delivery. In silico software packages were used to predict the physicochemical and biopharmaceutical properties of MyoNovin. In vitro cardiotoxicity was assessed using human cardiomyocytes (RL-14) while effects on CYP3A4 metabolic enzyme and antioxidant activity were examined using commercial kits. A novel HPLC assay was developed to measure MyoNovin concentration in serum, and delineate initial pharmacokinetic and acute toxicity after intravenous administration (20 mg/kg) to male Sprague-Dawley rats. MyoNovin showed relatively high lipophilicity with a LogP value of 3.49, a 20-fold higher skin permeability (19.89 cm/s*107) compared to guaifenesin (0.66 cm/s*107), and ~10-fold higher effective jejunal permeability (2.24 cm/s*104) compared to guaifenesin (0.26 cm/s*104). In vitro, MyoNovinwas not cytotoxic to cardiomyocytes at concentrations below 8 μM and did not inhibit CYP3A4 or show antioxidant activity. In vivo, MyoNovin had a short half-life (t1/2) of 0.16 h, and a volume of distribution Vss of 0.62 L/kg. Biomarkers of MyoNovincardiac and renal toxicity did not differ significantly from baseline control levels. The predicted high lipophilicity and skin permeability of MyoNovin render it a potential candidate for transdermal administration while its favourable intestinal permeation suggests it may be suitable for oral administration. Pharmacokinetics following IV administration of MyoNovin were delineated for the first time in a rat model. Preliminary single 20 mg/kg dose assessment of MyoNovin suggest no influenceon cardiac troponin or β-N-Acetylglucosaminidase. This article is open to POST-PUBLICATION REVIEW. Registered readers (see "For Readers") may comment by clicking on ABSTRACT on the issue's contents page

    Discovery and implementation of transcriptional biomarkers of synthetic LXR agonists in peripheral blood cells

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    <p>Abstract</p> <p>Background</p> <p>LXRs (Liver X Receptor α and β) are nuclear receptors that act as ligand-activated transcription factors. LXR activation causes upregulation of genes involved in reverse cholesterol transport (RCT), including ABCA1 and ABCG1 transporters, in macrophage and intestine. Anti-atherosclerotic effects of synthetic LXR agonists in murine models suggest clinical utility for such compounds.</p> <p>Objective</p> <p>Blood markers of LXR agonist exposure/activity were sought to support clinical development of novel synthetic LXR modulators.</p> <p>Methods</p> <p>Transcript levels of LXR target genes ABCA1 and ABCG1 were measured using quantitative reverse transcriptase/polymerase chain reaction assays (qRT-PCR) in peripheral blood from mice and rats (following a single oral dose) and monkeys (following 7 daily oral doses) of synthetic LXR agonists. LXRα, LXRβ, ABCA1, and ABCG1 mRNA were measured by qRT-PCR in human peripheral blood mononuclear cells (PBMC), monocytes, T- and B-cells treated <it>ex vivo </it>with WAY-252623 (LXR-623), and protein levels in human PBMC were measured by Western blotting. ABCA1/G1 transcript levels in whole-blood RNA were measured using analytically validated assays in human subjects participating in a Phase 1 SAD (Single Ascending Dose) clinical study of LXR-623.</p> <p>Results</p> <p>A single oral dose of LXR agonists induced ABCA1 and ABCG1 transcription in rodent peripheral blood in a dose- and time-dependent manner. Induction of gene expression in rat peripheral blood correlated with spleen expression, suggesting LXR gene regulation in blood has the potential to function as a marker of tissue gene regulation. Transcriptional response to LXR agonist was confirmed in primates, where peripheral blood ABCA1 and ABCG1 levels increased in a dose-dependent manner following oral treatment with LXR-623. Human PBMC, monocytes, T- and B cells all expressed both LXRα and LXRβ, and all cell types significantly increased ABCA1 and ABCG1 expression upon <it>ex vivo </it>LXR-623 treatment. Peripheral blood from a representative human subject receiving a single oral dose of LXR-623 showed significant time-dependent increases in ABCA1 and ABCG1 transcription.</p> <p>Conclusion</p> <p>Peripheral blood cells express LXRα and LXRβ, and respond to LXR agonist treatment by time- and dose-dependently inducing LXR target genes. Transcript levels of LXR target genes in peripheral blood are relevant and useful biological indicators for clinical development of synthetic LXR modulators.</p

    Alongshore variability of the California Current System from Central to Baja California in winter and spring 2003, physical, chemical and biological properties

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    Poster.-- American Society of Limnology and Oceanography and the Oceanography Society, Honolulu, Hawaii (USA), 15-20 febrero 2004Sixteen stations along the continental slope of western North America were occupied in February 18-27 and May 22-31, 2003, and form a meridional section from Monterey Bay, California (37º N, 122º W) to Cabo San Lucas, Mexico (23º N, 110º W). Our purpose was to compare trends in California Current (CC), Inshore Countercurrent (ICC) and California Undercurrent (CUC) properties with latitude, and between winter and spring conditions. In winter, coastal upwelling was near zero and the along-transect dynamic height was high and flat, allowing the ICC to advect tropical properties northward. In spring, coastal upwelling had commenced and surface flow along the transect presumably became equatorward. As a consequence of these dynamics, in winter the thermocline was deeper, SST was higher, macronutrients, chlorophyll and primary production were low along the entire transect, with most properties lacking strong latitudinal trends. In spring, the thermocline, macronutrients, chlorophyll and primary production rose along the entire section but most dramatically in the north where upwelling was stronger. Prochlorophytes and other small open-ocean phytoplankton were more abundant in winter along the entire transect and to the south in spring, whereas diatoms, a characteristic coastal group of phytoplankton, were more abundant in spring and in the north. Surface iron was higher in the north in winter, but lower there in spring, presumably reflecting drawdown by diatoms. These results are detailed in the figure captionsWe would like to express our gratitude to the David and Lucile Packard Foundation for funding this workN

    Metabolomics Reveals Metabolic Biomarkers of Crohn's Disease

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    The causes and etiology of Crohn's disease (CD) are currently unknown although both host genetics and environmental factors play a role. Here we used non-targeted metabolic profiling to determine the contribution of metabolites produced by the gut microbiota towards disease status of the host. Ion Cyclotron Resonance Fourier Transform Mass Spectrometry (ICR-FT/MS) was used to discern the masses of thousands of metabolites in fecal samples collected from 17 identical twin pairs, including healthy individuals and those with CD. Pathways with differentiating metabolites included those involved in the metabolism and or synthesis of amino acids, fatty acids, bile acids and arachidonic acid. Several metabolites were positively or negatively correlated to the disease phenotype and to specific microbes previously characterized in the same samples. Our data reveal novel differentiating metabolites for CD that may provide diagnostic biomarkers and/or monitoring tools as well as insight into potential targets for disease therapy and prevention

    Gene expression analyses in breast cancer epidemiology: the Norwegian Women and Cancer postgenome cohort study

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    Introduction The introduction of high-throughput technologies, also called -omics technologies, into epidemiology has raised the need for high-quality observational studies to reduce several sources of error and bias. Methods The Norwegian Women and Cancer (NOWAC) postgenome cohort study consists of approximately 50,000 women born between 1943 and 1957 who gave blood samples between 2003 and 2006 and filled out a two-page questionnaire. Blood was collected in such a way that RNA is preserved and can be used for gene expression analyses. The women are part of the NOWAC study consisting of 172,471 women 30 to 70 years of age at recruitment from 1991 to 2006 who answered one to three questionnaires on diet, medication use, and lifestyle. In collaboration with the Norwegian Breast Cancer Group, every NOWAC participant born between 1943 and 1957 who is admitted to a collaborating hospital for a diagnostic biopsy or for surgery of breast cancer will be asked to donate a tumor biopsy and two blood samples. In parallel, at least three controls are approached for each breast cancer case in order to obtain blood samples from at least two controls per case. The controls are drawn at random from NOWAC matched by time of follow-up and age. In addition, 400 normal breast tissues as well as blood samples will be collected among healthy women participating at the Norwegian Mammography Screening program at the Breast Imaging Center at the University Hospital of North-Norway, Tromsø. Results The NOWAC postgenome cohort offers a unique opportunity (a) to study blood-derived gene expression profiles as a diagnostic test for breast cancer in a nested case-control design with adjustment for confounding factors related to different exposures, (b) to improve the reliability and accuracy of this approach by adjusting for an individual's genotype (for example, variants in genes coding for hormone and drug-metabolizing and detoxifying enzymes), (c) to study gene expression profiles from peripheral blood as surrogate tissue to biomonitor defined exposure (for example, hormone) and its association with disease risk (that is, breast cancer), and (d) to study gene variants (single nucleotide polymorphisms and copy number variations) and environmental exposure (endogenous and exogenous hormones) and their influence on the incidence of different molecular subtypes of breast cancer. Conclusion The NOWAC postgenome cohort combining a valid epidemiological approach with richness of biological samples should make an important contribution to the study of the etiology and system biology of breast cancer

    SlimPLS: A Method for Feature Selection in Gene Expression-Based Disease Classification

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    A major challenge in biomedical studies in recent years has been the classification of gene expression profiles into categories, such as cases and controls. This is done by first training a classifier by using a labeled training set containing labeled samples from the two populations, and then using that classifier to predict the labels of new samples. Such predictions have recently been shown to improve the diagnosis and treatment selection practices for several diseases. This procedure is complicated, however, by the high dimensionality if the data. While microarrays can measure the levels of thousands of genes per sample, case-control microarray studies usually involve no more than several dozen samples. Standard classifiers do not work well in these situations where the number of features (gene expression levels measured in these microarrays) far exceeds the number of samples. Selecting only the features that are most relevant for discriminating between the two categories can help construct better classifiers, in terms of both accuracy and efficiency. In this work we developed a novel method for multivariate feature selection based on the Partial Least Squares algorithm. We compared the method's variants with common feature selection techniques across a large number of real case-control datasets, using several classifiers. We demonstrate the advantages of the method and the preferable combinations of classifier and feature selection technique

    Deciphering Normal Blood Gene Expression Variation—The NOWAC Postgenome Study

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    There is growing evidence that gene expression profiling of peripheral blood cells is a valuable tool for assessing gene signatures related to exposure, drug-response, or disease. However, the true promise of this approach can not be estimated until the scientific community has robust baseline data describing variation in gene expression patterns in normal individuals. Using a large representative sample set of postmenopausal women (N = 286) in the Norwegian Women and Cancer (NOWAC) postgenome study, we investigated variability of whole blood gene expression in the general population. In particular, we examined changes in blood gene expression caused by technical variability, normal inter-individual differences, and exposure variables at proportions and levels relevant to real-life situations. We observe that the overall changes in gene expression are subtle, implying the need for careful analytic approaches of the data. In particular, technical variability may not be ignored and subsequent adjustments must be considered in any analysis. Many new candidate genes were identified that are differentially expressed according to inter-individual (i.e. fasting, BMI) and exposure (i.e. smoking) factors, thus establishing that these effects are mirrored in blood. By focusing on the biological implications instead of directly comparing gene lists from several related studies in the literature, our analytic approach was able to identify significant similarities and effects consistent across these reports. This establishes the feasibility of blood gene expression profiling, if they are predicated upon careful experimental design and analysis in order to minimize confounding signals, artifacts of sample preparation and processing, and inter-individual differences

    RNA expression patterns in serum microvesicles from patients with glioblastoma multiforme and controls

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    <p>Abstract</p> <p>Background</p> <p>RNA from exosomes and other microvesicles contain transcripts of tumour origin. In this study we sought to identify biomarkers of glioblastoma multiforme in microvesicle RNA from serum of affected patients.</p> <p>Methods</p> <p>Microvesicle RNA from serum from patients with de-novo primary glioblastoma multiforme (N = 9) and normal controls (N = 7) were analyzed by microarray analysis. Samples were collected according to protocols approved by the Institutional Review Board. Differential expressions were validated by qRT-PCR in a separate set of samples (N = 10 in both groups).</p> <p>Results</p> <p>Expression profiles of microvesicle RNA correctly separated individuals in two groups by unsupervised clustering. The most significant differences pertained to down-regulated genes (121 genes > 2-fold down) in the glioblastoma multiforme patient microvesicle RNA, validated by qRT-PCR on several genes. Overall, yields of microvesicle RNA from patients was higher than from normal controls, but the additional RNA was primarily of size < 500 nt. Gene ontology of the down-regulated genes indicated these are coding for ribosomal proteins and genes related to ribosome production.</p> <p>Conclusions</p> <p>Serum microvesicle RNA from patients with glioblastoma multiforme has significantly down-regulated levels of RNAs coding for ribosome production, compared to normal healthy controls, but a large overabundance of RNA of unknown origin with size < 500 nt.</p

    Tobacco use induces anti-apoptotic, proliferative patterns of gene expression in circulating leukocytes of Caucasian males

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    Abstract Background Strong epidemiologic evidence correlates tobacco use with a variety of serious adverse health effects, but the biological mechanisms that produce these effects remain elusive. Results We analyzed gene transcription data to identify expression spectra related to tobacco use in circulating leukocytes of 67 Caucasian male subjects. Levels of cotinine, a nicotine metabolite, were used as a surrogate marker for tobacco exposure. Significance Analysis of Microarray and Gene Set Analysis identified 109 genes in 16 gene sets whose transcription levels were differentially regulated by nicotine exposure. We subsequently analyzed this gene set by hyperclustering, a technique that allows the data to be clustered by both expression ratio and gene annotation (e.g. Gene Ontologies). Conclusion Our results demonstrate that tobacco use affects transcription of groups of genes that are involved in proliferation and apoptosis in circulating leukocytes. These transcriptional effects include a repertoire of transcriptional changes likely to increase the incidence of neoplasia through an altered expression of genes associated with transcription and signaling, interferon responses and repression of apoptotic pathways

    Factors Influencing the Statistical Power of Complex Data Analysis Protocols for Molecular Signature Development from Microarray Data

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    Critical to the development of molecular signatures from microarray and other high-throughput data is testing the statistical significance of the produced signature in order to ensure its statistical reproducibility. While current best practices emphasize sufficiently powered univariate tests of differential expression, little is known about the factors that affect the statistical power of complex multivariate analysis protocols for high-dimensional molecular signature development.We show that choices of specific components of the analysis (i.e., error metric, classifier, error estimator and event balancing) have large and compounding effects on statistical power. The effects are demonstrated empirically by an analysis of 7 of the largest microarray cancer outcome prediction datasets and supplementary simulations, and by contrasting them to prior analyses of the same data.THE FINDINGS OF THE PRESENT STUDY HAVE TWO IMPORTANT PRACTICAL IMPLICATIONS: First, high-throughput studies by avoiding under-powered data analysis protocols, can achieve substantial economies in sample required to demonstrate statistical significance of predictive signal. Factors that affect power are identified and studied. Much less sample than previously thought may be sufficient for exploratory studies as long as these factors are taken into consideration when designing and executing the analysis. Second, previous highly-cited claims that microarray assays may not be able to predict disease outcomes better than chance are shown by our experiments to be due to under-powered data analysis combined with inappropriate statistical tests
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