Sample records for biomarker discovery platform

  1. Biomarker discovery by CE-MS enables sequence analysis via MS/MS with platform-independent separation. (United States)

    Zürbig, Petra; Renfrow, Matthew B; Schiffer, Eric; Novak, Jan; Walden, Michael; Wittke, Stefan; Just, Ingo; Pelzing, Matthias; Neusüss, Christian; Theodorescu, Dan; Root, Karen E; Ross, Mark M; Mischak, Harald


    CE-MS is a successful proteomic platform for the definition of biomarkers in different body fluids. Besides the biomarker defining experimental parameters, CE migration time and molecular weight, especially biomarker's sequence identity is an indispensable cornerstone for deeper insights into the pathophysiological pathways of diseases or for made-to-measure therapeutic drug design. Therefore, this report presents a detailed discussion of different peptide sequencing platforms consisting of high performance separation method either coupled on-line or off-line to different MS/MS devices, such as MALDI-TOF-TOF, ESI-IT, ESI-QTOF and Fourier transform ion cyclotron resonance, for sequencing indicative peptides. This comparison demonstrates the unique feature of CE-MS technology to serve as a reliable basis for the assignment of peptide sequence data obtained using different separation MS/MS methods to the biomarker defining parameters, CE migration time and molecular weight. Discovery of potential biomarkers by CE-MS enables sequence analysis via MS/MS with platform-independent sample separation. This is due to the fact that the number of basic and neutral polar amino acids of biomarkers sequences distinctly correlates with their CE-MS migration time/molecular weight coordinates. This uniqueness facilitates the independent entry of different sequencing platforms for peptide sequencing of CE-MS-defined biomarkers from highly complex mixtures.

  2. Automated Sample Preparation Platform for Mass Spectrometry-Based Plasma Proteomics and Biomarker Discovery

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    Vilém Guryča


    Full Text Available The identification of novel biomarkers from human plasma remains a critical need in order to develop and monitor drug therapies for nearly all disease areas. The discovery of novel plasma biomarkers is, however, significantly hampered by the complexity and dynamic range of proteins within plasma, as well as the inherent variability in composition from patient to patient. In addition, it is widely accepted that most soluble plasma biomarkers for diseases such as cancer will be represented by tissue leakage products, circulating in plasma at low levels. It is therefore necessary to find approaches with the prerequisite level of sensitivity in such a complex biological matrix. Strategies for fractionating the plasma proteome have been suggested, but improvements in sensitivity are often negated by the resultant process variability. Here we describe an approach using multidimensional chromatography and on-line protein derivatization, which allows for higher sensitivity, whilst minimizing the process variability. In order to evaluate this automated process fully, we demonstrate three levels of processing and compare sensitivity, throughput and reproducibility. We demonstrate that high sensitivity analysis of the human plasma proteome is possible down to the low ng/mL or even high pg/mL level with a high degree of technical reproducibility.

  3. Cell surface profiling using high-throughput flow cytometry: a platform for biomarker discovery and analysis of cellular heterogeneity.

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    Craig A Gedye

    Full Text Available Cell surface proteins have a wide range of biological functions, and are often used as lineage-specific markers. Antibodies that recognize cell surface antigens are widely used as research tools, diagnostic markers, and even therapeutic agents. The ability to obtain broad cell surface protein profiles would thus be of great value in a wide range of fields. There are however currently few available methods for high-throughput analysis of large numbers of cell surface proteins. We describe here a high-throughput flow cytometry (HT-FC platform for rapid analysis of 363 cell surface antigens. Here we demonstrate that HT-FC provides reproducible results, and use the platform to identify cell surface antigens that are influenced by common cell preparation methods. We show that multiple populations within complex samples such as primary tumors can be simultaneously analyzed by co-staining of cells with lineage-specific antibodies, allowing unprecedented depth of analysis of heterogeneous cell populations. Furthermore, standard informatics methods can be used to visualize, cluster and downsample HT-FC data to reveal novel signatures and biomarkers. We show that the cell surface profile provides sufficient molecular information to classify samples from different cancers and tissue types into biologically relevant clusters using unsupervised hierarchical clustering. Finally, we describe the identification of a candidate lineage marker and its subsequent validation. In summary, HT-FC combines the advantages of a high-throughput screen with a detection method that is sensitive, quantitative, highly reproducible, and allows in-depth analysis of heterogeneous samples. The use of commercially available antibodies means that high quality reagents are immediately available for follow-up studies. HT-FC has a wide range of applications, including biomarker discovery, molecular classification of cancers, or identification of novel lineage specific or stem cell

  4. Mass spectrometry in biomarker applications: from untargeted discovery to targeted verification, and implications for platform convergence and clinical application

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    Smith, Richard D.


    It is really only in the last ten years that mass spectrometry (MS) has had a truly significant (but still small) impact on biomedical research. Much of this impact can be attributed to proteomics and its more basic applications. Early biomedical applications have included a number of efforts aimed at developing new biomarkers; however, the success of these endeavors to date have been quite modest - essentially confined to preclinical applications - and have often suffered from combinations of immature technology and hubris. Now that MS-based proteomics is reaching adolescence, it is appropriate to ask if and when biomarker-related applications will extend to the clinical realm, and what developments will be essential for this transition. Biomarker development can be described as a multistage process consisting of discovery, qualification, verification, research assay optimization, validation, and commercialization (1). From a MS perspective, it is possible to 'bin' measurements into 1 of 2 categories - those aimed at discovering potential protein biomarkers and those seeking to verify and validate biomarkers. Approaches in both categories generally involve digesting proteins (e.g., with trypsin) as a first step to yield peptides that can be effectively detected and identified with MS. Discovery-based approaches use broad 'unbiased' or 'undirected' measurements that attempt to cover as many proteins as possible in the hope of revealing promising biomarker candidates. A key challenge with this approach stems from the extremely large dynamic range (i.e., relative stoichiometry) of proteins of potential interest in biofluids such as plasma and the expectation that biomarker proteins of the greatest clinical value for many diseases may very well be present at low relative abundances (2). Protein concentrations in plasma extend from approximately 10{sup 10} pg/mL for albumin to approximately 10 pg/mL and below for interleukins and other

  5. Glycoscience aids in biomarker discovery

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    Serenus Hua1,2 & Hyun Joo An1,2,*


    Full Text Available The glycome consists of all glycans (or carbohydrates within abiological system, and modulates a wide range of important biologicalactivities, from protein folding to cellular communications.The mining of the glycome for disease markers representsa new paradigm for biomarker discovery; however, this effortis severely complicated by the vast complexity and structuraldiversity of glycans. This review summarizes recent developmentsin analytical technology and methodology as applied tothe fields of glycomics and glycoproteomics. Mass spectrometricstrategies for glycan compositional profiling are described, as arepotential refinements which allow structure-specific profiling.Analytical methods that can discern protein glycosylation at aspecific site of modification are also discussed in detail.Biomarker discovery applications are shown at each level ofanalysis, highlighting the key role that glycoscience can play inhelping scientists understand disease biology.

  6. The Process Chain for Peptidomic Biomarker Discovery

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    Michael Schrader


    Full Text Available Over the last few years the interest in diagnostic markers for specific diseases has increased continuously. It is expected that they not only improve a patient's medical treatment but also contribute to accelerating the process of drug development. This demand for new biomarkers is caused by a lack of specific and sensitive diagnosis in many diseases. Moreover, diseases usually occur in different types or stages which may need different diagnostic and therapeutic measures. Their differentiation has to be considered in clinical studies as well. Therefore, it is important to translate a macroscopic pathological or physiological finding into a microscopic view of molecular processes and vice versa, though it is a difficult and tedious task. Peptides play a central role in many physiological processes and are of importance in several areas of drug research. Exploration of endogenous peptides in biologically relevant sources may directly lead to new drug substances, serve as key information on a new target and can as well result in relevant biomarker candidates. A comprehensive analysis of peptides and small proteins of a biological system corresponding to the respective genomic information (peptidomics®methods was a missing link in proteomics. A new peptidomic technology platform addressing peptides was recently presented, developed by adaptation of the striving proteomic technologies. Here, concepts of using peptidomics technologies for biomarker discovery are presented and illustrated with examples. It is discussed how the biological hypothesis and sample quality determine the result of the study. A detailed study design, appropriate choice and application of technology as well as thorough data interpretation can lead to significant results which have to be interpreted in the context of the underlying disease. The identified biomarker candidates will be characterised in validation studies before use. This approach for discovery of peptide

  7. Stable Feature Selection for Biomarker Discovery

    CERN Document Server

    He, Zengyou


    Feature selection techniques have been used as the workhorse in biomarker discovery applications for a long time. Surprisingly, the stability of feature selection with respect to sampling variations has long been under-considered. It is only until recently that this issue has received more and more attention. In this article, we review existing stable feature selection methods for biomarker discovery using a generic hierarchal framework. We have two objectives: (1) providing an overview on this new yet fast growing topic for a convenient reference; (2) categorizing existing methods under an expandable framework for future research and development.

  8. Using Aptamers for Cancer Biomarker Discovery

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    Yun Min Chang


    Full Text Available Aptamers are single-stranded synthetic DNA- or RNA-based oligonucleotides that fold into various shapes to bind to a specific target, which includes proteins, metals, and molecules. Aptamers have high affinity and high specificity that are comparable to that of antibodies. They are obtained using iterative method, called (Systematic Evolution of Ligands by Exponential Enrichment SELEX and cell-based SELEX (cell-SELEX. Aptamers can be paired with recent advances in nanotechnology, microarray, microfluidics, and other technologies for applications in clinical medicine. One particular area that aptamers can shed a light on is biomarker discovery. Biomarkers are important in diagnosis and treatment of cancer. In this paper, we will describe ways in which aptamers can be used to discover biomarkers for cancer diagnosis and therapeutics.

  9. Integration of Proteomics, Bioinformatics and Systems biology in Brain Injury Biomarker Discovery

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    Joy eGuingab-Cagmat


    Full Text Available Traumatic brain injury (TBI is a major medical crisis without any FDA-approved pharmacological therapies that have been demonstrated to improve functional outcomes. It has been argued that discovery of disease-relevant biomarkers might help to guide successful clinical trials for TBI. Major advances in mass spectrometry (MS have revolutionized the field of proteomic biomarker discovery and facilitated the identification of several candidate markers that are being further evaluated for their efficacy as TBI biomarkers. However, several hurdles have to be overcome even during the discovery phase which is only the first step in the long process of biomarker development. The high throughput nature of MS-based proteomic experiments generates a massive amount of mass spectral data presenting great challenges in downstream interpretation. Currently, different bioinformatics platforms are available for functional analysis and data mining of MS-generated proteomic data. These tools provide a way to convert data sets to biologically interpretable results and functional outcomes. A strategy that has promise in advancing biomarker development involves the triad of proteomics, bioinformatics and systems biology. In this review, a brief overview of how bioinformatics and systems biology tools analyze, transform and interpret complex MS datasets into biologically relevant results is discussed. In addition, challenges and limitations of proteomics, bioinformatics and systems biology in TBI biomarker discovery are presented. A brief survey of researches that utilized these three overlapping disciplines in TBI biomarker discovery is also presented. Finally, examples of TBI biomarkers and their applications are discussed.

  10. Current technological challenges in biomarker discovery and validation

    NARCIS (Netherlands)

    Horvatovich, Peter L.; Bischoff, Rainer


    In this review we will give an overview of the issues related to biomarker discovery studies with a focus on liquid chromatography-mass spectrometry (LC-MS) methods. Biomarker discovery is based on a close collaboration between clinicians, analytical scientists and chemometritians/statisticians. It

  11. Coherent pipeline for biomarker discovery using mass spectrometry and bioinformatics

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    Al-Shahib Ali


    Full Text Available Abstract Background Robust biomarkers are needed to improve microbial identification and diagnostics. Proteomics methods based on mass spectrometry can be used for the discovery of novel biomarkers through their high sensitivity and specificity. However, there has been a lack of a coherent pipeline connecting biomarker discovery with established approaches for evaluation and validation. We propose such a pipeline that uses in silico methods for refined biomarker discovery and confirmation. Results The pipeline has four main stages: Sample preparation, mass spectrometry analysis, database searching and biomarker validation. Using the pathogen Clostridium botulinum as a model, we show that the robustness of candidate biomarkers increases with each stage of the pipeline. This is enhanced by the concordance shown between various database search algorithms for peptide identification. Further validation was done by focusing on the peptides that are unique to C. botulinum strains and absent in phylogenetically related Clostridium species. From a list of 143 peptides, 8 candidate biomarkers were reliably identified as conserved across C. botulinum strains. To avoid discarding other unique peptides, a confidence scale has been implemented in the pipeline giving priority to unique peptides that are identified by a union of algorithms. Conclusions This study demonstrates that implementing a coherent pipeline which includes intensive bioinformatics validation steps is vital for discovery of robust biomarkers. It also emphasises the importance of proteomics based methods in biomarker discovery.

  12. Proteomics in Discovery of Hepatocellular Carcinoma Biomarkers

    Institute of Scientific and Technical Information of China (English)


    Objective: To discover new proteomic biomarkers of hepatocellular carcinoma. Methods: Surface enhanced laser desorption/ionization time-of-flight (SELDI-TOF) mass spectrometry was used to discover biomarkers for differentiating hepatocellular carcinoma and chronic liver disease. A population of 50 patients with hepatocellular carcinoma and 33 patients with chronic liver disease was studied. Results: Twelve proteomic biomarkers of hepatocellular carcinoma were detected in this study. Three proteomic biomarkers were highly expressed in hepatocellular carcinoma and nine proteomic biomarkers were highly expressed in chronic liver disease. The most valuable proteomic biomarker with m/z=11498 had no similar diagnostic value as α-fetoprotein. Conclusion:Some of the twelve proteomic biomarkers may become new biomarkers of hepatocellular carcinoma.

  13. Integration of lyoplate based flow cytometry and computational analysis for standardized immunological biomarker discovery.

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    Federica Villanova

    Full Text Available Discovery of novel immune biomarkers for monitoring of disease prognosis and response to therapy in immune-mediated inflammatory diseases is an important unmet clinical need. Here, we establish a novel framework for immunological biomarker discovery, comparing a conventional (liquid flow cytometry platform (CFP and a unique lyoplate-based flow cytometry platform (LFP in combination with advanced computational data analysis. We demonstrate that LFP had higher sensitivity compared to CFP, with increased detection of cytokines (IFN-γ and IL-10 and activation markers (Foxp3 and CD25. Fluorescent intensity of cells stained with lyophilized antibodies was increased compared to cells stained with liquid antibodies. LFP, using a plate loader, allowed medium-throughput processing of samples with comparable intra- and inter-assay variability between platforms. Automated computational analysis identified novel immunophenotypes that were not detected with manual analysis. Our results establish a new flow cytometry platform for standardized and rapid immunological biomarker discovery with wide application to immune-mediated diseases.

  14. Bioinformatics and biomarker discovery "Omic" data analysis for personalized medicine

    CERN Document Server

    Azuaje, Francisco


    This book is designed to introduce biologists, clinicians and computational researchers to fundamental data analysis principles, techniques and tools for supporting the discovery of biomarkers and the implementation of diagnostic/prognostic systems. The focus of the book is on how fundamental statistical and data mining approaches can support biomarker discovery and evaluation, emphasising applications based on different types of "omic" data. The book also discusses design factors, requirements and techniques for disease screening, diagnostic and prognostic applications. Readers are provided w

  15. Integrative Genomic Data Mining for Discovery of Potential Blood-Borne Biomarkers for Early Diagnosis of Cancer


    Yongliang Yang; Pavel Pospisil; Iyer, Lakshmanan K.; S. James Adelstein; Amin I. Kassis


    BACKGROUND: With the arrival of the postgenomic era, there is increasing interest in the discovery of biomarkers for the accurate diagnosis, prognosis, and early detection of cancer. Blood-borne cancer markers are favored by clinicians, because blood samples can be obtained and analyzed with relative ease. We have used a combined mining strategy based on an integrated cancer microarray platform, Oncomine, and the biomarker module of the Ingenuity Pathways Analysis (IPA) program to identify po...

  16. Application of chemical proteomics to biomarker discovery in cardiac research

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    Aye, T.T.


    This thesis is primarily focused on (i.) exploring chemical probes to increase sensitivity and specificity for the investigation of low abundant cardiac proteins applicable to both biology and biomarker discovery, and (ii.) exploiting different aspects of mass spectrometry-based proteomics for build

  17. Exhaled Breath Condensate for Proteomic Biomarker Discovery

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    Sean W. Harshman


    Full Text Available Exhaled breath condensate (EBC has been established as a potential source of respiratory biomarkers. Compared to the numerous small molecules identified, the protein content of EBC has remained relatively unstudied due to the methodological and technical difficulties surrounding EBC analysis. In this review, we discuss the proteins identified in EBC, by mass spectrometry, focusing on the significance of those proteins identified. We will also review the limitations surrounding mass spectral EBC protein analysis emphasizing recommendations to enhance EBC protein identifications by mass spectrometry. Finally, we will provide insight into the future directions of the EBC proteomics field.

  18. Computational and Experimental Approaches to Cancer Biomarker Discovery

    DEFF Research Database (Denmark)

    Krzystanek, Marcin

    with a purely biological, experimental approach where the effects of treatment with cytotoxic agents or defects in DNA repair mechanisms can be individually quantified and turned into mutational signatures.In the second part of the thesis I present work towards identification and improvement of the current......Effective cancer treatment requires good biomarkers: measurable indicators of some biological state or condition that constitute the cornerstone of personalized medicine. Prognostic biomarkers provide information about the likely course of the disease, while predictive biomarkers enable prediction...... of a patient’s response to a particular treatment, thus helping to avoid unnecessary treatment and unwanted side effects in non-responding individuals.Currently biomarker discovery is facilitated by recent advances in high-throughput technologies when association between a given biological phenotype...

  19. PROFILEing idiopathic pulmonary fibrosis: rethinking biomarker discovery

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    Toby M. Maher


    Full Text Available Despite major advances in the understanding of the pathogenesis of idiopathic pulmonary fibrosis (IPF, diagnosis and management of the condition continue to pose significant challenges. Clinical management of IPF remains unsatisfactory due to limited availability of effective drug therapies, a lack of accurate indicators of disease progression, and an absence of simple short-term measures of therapeutic response. The identification of more accurate predictors of prognosis and survival in IPF would facilitate counseling of patients and their families, aid communication among clinicians, and would guide optimal timing of referral for transplantation. Improvements in molecular techniques have led to the identification of new disease pathways and a more targeted approach to the development of novel anti-fibrotic agents. However, despite an increased interest in biomarkers of IPF disease progression there are a lack of measures that can be used in early phase clinical trials. Careful longitudinal phenotyping of individuals with IPF together with the application of novel omics-based technology should provide important insights into disease pathogenesis and should address some of the major issues holding back drug development in IPF. The PROFILE (Prospective Observation of Fibrosis in the Lung Clinical Endpoints study is a currently enrolling, prospective cohort study designed to tackle these issues.

  20. State of the Art in Tumor Antigen and Biomarker Discovery

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    Even-Desrumeaux, Klervi; Baty, Daniel; Chames, Patrick, E-mail: [INSERM U624, 163 avenue de Luminy, 13288 Marseille Cedex 09 (France)


    Our knowledge of tumor immunology has resulted in multiple approaches for the treatment of cancer. However, a gap between research of new tumors markers and development of immunotherapy has been established and very few markers exist that can be used for treatment. The challenge is now to discover new targets for active and passive immunotherapy. This review aims at describing recent advances in biomarkers and tumor antigen discovery in terms of antigen nature and localization, and is highlighting the most recent approaches used for their discovery including “omics” technology.

  1. State of the Art in Tumor Antigen and Biomarker Discovery

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    Patrick Chames


    Full Text Available Our knowledge of tumor immunology has resulted in multiple approaches for the treatment of cancer. However, a gap between research of new tumors markers and development of immunotherapy has been established and very few markers exist that can be used for treatment. The challenge is now to discover new targets for active and passive immunotherapy. This review aims at describing recent advances in biomarkers and tumor antigen discovery in terms of antigen nature and localization, and is highlighting the most recent approaches used for their discovery including “omics” technology.

  2. Aptamer-based multiplexed proteomic technology for biomarker discovery.

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    Larry Gold

    Full Text Available BACKGROUND: The interrogation of proteomes ("proteomics" in a highly multiplexed and efficient manner remains a coveted and challenging goal in biology and medicine. METHODOLOGY/PRINCIPAL FINDINGS: We present a new aptamer-based proteomic technology for biomarker discovery capable of simultaneously measuring thousands of proteins from small sample volumes (15 µL of serum or plasma. Our current assay measures 813 proteins with low limits of detection (1 pM median, 7 logs of overall dynamic range (~100 fM-1 µM, and 5% median coefficient of variation. This technology is enabled by a new generation of aptamers that contain chemically modified nucleotides, which greatly expand the physicochemical diversity of the large randomized nucleic acid libraries from which the aptamers are selected. Proteins in complex matrices such as plasma are measured with a process that transforms a signature of protein concentrations into a corresponding signature of DNA aptamer concentrations, which is quantified on a DNA microarray. Our assay takes advantage of the dual nature of aptamers as both folded protein-binding entities with defined shapes and unique nucleotide sequences recognizable by specific hybridization probes. To demonstrate the utility of our proteomics biomarker discovery technology, we applied it to a clinical study of chronic kidney disease (CKD. We identified two well known CKD biomarkers as well as an additional 58 potential CKD biomarkers. These results demonstrate the potential utility of our technology to rapidly discover unique protein signatures characteristic of various disease states. CONCLUSIONS/SIGNIFICANCE: We describe a versatile and powerful tool that allows large-scale comparison of proteome profiles among discrete populations. This unbiased and highly multiplexed search engine will enable the discovery of novel biomarkers in a manner that is unencumbered by our incomplete knowledge of biology, thereby helping to advance the next

  3. Maximizing biomarker discovery by minimizing gene signatures

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    Chang Chang


    Full Text Available Abstract Background The use of gene signatures can potentially be of considerable value in the field of clinical diagnosis. However, gene signatures defined with different methods can be quite various even when applied the same disease and the same endpoint. Previous studies have shown that the correct selection of subsets of genes from microarray data is key for the accurate classification of disease phenotypes, and a number of methods have been proposed for the purpose. However, these methods refine the subsets by only considering each single feature, and they do not confirm the association between the genes identified in each gene signature and the phenotype of the disease. We proposed an innovative new method termed Minimize Feature's Size (MFS based on multiple level similarity analyses and association between the genes and disease for breast cancer endpoints by comparing classifier models generated from the second phase of MicroArray Quality Control (MAQC-II, trying to develop effective meta-analysis strategies to transform the MAQC-II signatures into a robust and reliable set of biomarker for clinical applications. Results We analyzed the similarity of the multiple gene signatures in an endpoint and between the two endpoints of breast cancer at probe and gene levels, the results indicate that disease-related genes can be preferably selected as the components of gene signature, and that the gene signatures for the two endpoints could be interchangeable. The minimized signatures were built at probe level by using MFS for each endpoint. By applying the approach, we generated a much smaller set of gene signature with the similar predictive power compared with those gene signatures from MAQC-II. Conclusions Our results indicate that gene signatures of both large and small sizes could perform equally well in clinical applications. Besides, consistency and biological significances can be detected among different gene signatures, reflecting the

  4. Detection of biomarkers using recombinant antibodies coupled to nanostructured platforms

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    Michael R. Kierny


    Full Text Available The utility of biomarker detection in tomorrow's personalized health care field will mean early and accurate diagnosis of many types of human physiological conditions and diseases. In the search for biomarkers, recombinant affinity reagents can be generated to candidate proteins or post-translational modifications that differ qualitatively or quantitatively between normal and diseased tissues. The use of display technologies, such as phage-display, allows for manageable selection and optimization of affinity reagents for use in biomarker detection. Here we review the use of recombinant antibody fragments, such as scFvs and Fabs, which can be affinity-selected from phage-display libraries, to bind with both high specificity and affinity to biomarkers of cancer, such as Human Epidermal growth factor Receptor 2 (HER2 and Carcinoembryonic antigen (CEA. We discuss how these recombinant antibodies can be fabricated into nanostructures, such as carbon nanotubes, nanowires, and quantum dots, for the purpose of enhancing detection of biomarkers at low concentrations (pg/mL within complex mixtures such as serum or tissue extracts. Other sensing technologies, which take advantage of ‘Surface Enhanced Raman Scattering’ (gold nanoshells, frequency changes in piezoelectric crystals (quartz crystal microbalance, or electrical current generation and sensing during electrochemical reactions (electrochemical detection, can effectively provide multiplexed platforms for detection of cancer and injury biomarkers. Such devices may soon replace the traditional time consuming ELISAs and Western blots, and deliver rapid, point-of-care diagnostics to market.

  5. Data mining of spectroscopic data for biomarker discovery. (United States)

    Norton, S M; Huyn, P; Hastings, C A; Heller, J C


    The goals of precise diagnosis, prevention and treatment of disease can be realized through the discovery of biological markers. Spectroscopic tools can simultaneously detect and quantify multiple small molecule and macromolecular components of biological samples, and are therefore ideal methods for the discovery of previously uncharacterized markers. However, the identification of meaningful spectral features is complicated by the lack of foreknowledge of the molecular nature of a disease, spectral noise and biological variability that is uncorrelated with the disease state. Pattern recognition techniques, both statistical and machine-learning, have been increasingly used in recent years with spectroscopic data to identify markers and classify patients into disease subsets. This review summarizes recent developments, limitations and future prospects in the use of data mining techniques with magnetic resonance spectroscopy, mass spectrometry and optical spectroscopy for the discovery of biomarkers.

  6. Molecular biology tools: proteomics techniques in biomarker discovery. (United States)

    Lottspeich, Friedrich; Kellermann, Josef; Keidel, Eva-Maria


    Despite worldwide efforts biomarker discovery by plasma proteomics was not successful so far. Several reasons for this failure are obvious. Mainly, proteome diversity is remarkable between different individuals and is caused by genetic, environmental and life style parameters. To recognize disease related proteins that could serve as potential biomarkers is only feasible by investigating a non realizable large number of patients. Furthermore, plasma proteomics comprises enormous technical hurdles for quantitative analysis. High reproducibility of blood sampling in clinical routine is hard to achieve. Quantitative proteome analysis has to struggle with the complexity of millions of protein species comprising typical plasma proteins, cellular leakage proteins and antibodies and concentration differences of more than 1011 between high and low abundant proteins. Therefore, no successful quantitative and comprehensive plasma proteome analysis is reported so far. A novel proteomics strategy is proposed for biomarker discovery in plasma. Instead of comparing the plasma proteome of different individuals it is recommended to analyze the proteomes of different time points of a single individual during the development of a disease. This strategy is realized by the use of plasma of the Bavarian Red Cross Blood Bank, were three million samples are stored under standardized conditions. To achieve reliable data the isotope coded protein labelling proteomics technology was used.

  7. Proteomics and Its Application in Biomarker Discovery and Drug Development

    Institute of Scientific and Technical Information of China (English)

    He Qing-Yu; Chiu Jen-Fu


    Proteomics is a research field aiming to characterize molecular and cellular dynamics in protein expression and function on a global level. The introduction of proteomics has been greatly broadening our view and accelerating our path in various medical researches. The most significant advantage of proteomics is its ability to examine a whole proteome or sub-proteome in a single experiment so that the protein alterations corresponding to a pathological or biochemical condition at a given time can be considered in an integrated way. Proteomic technology has been extensively used to tackle a wide variety of medical subjects including biomarker discovery and drug development. By complement with other new technique advance in genomics and bioinformatics,proteomics has a great potential to make considerable contribution to biomarker identification and revolutionize drug development process. A brief overview of the proteomic technologies will be provided and the application of proteomics in biomarker discovery and drug development will be discussed using our current research projects as examples.

  8. Analytical validation considerations of multiplex mass-spectrometry-based proteomic platforms for measuring protein biomarkers. (United States)

    Boja, Emily S; Fehniger, Thomas E; Baker, Mark S; Marko-Varga, György; Rodriguez, Henry


    Protein biomarker discovery and validation in current omics era are vital for healthcare professionals to improve diagnosis, detect cancers at an early stage, identify the likelihood of cancer recurrence, stratify stages with differential survival outcomes, and monitor therapeutic responses. The success of such biomarkers would have a huge impact on how we improve the diagnosis and treatment of patients and alleviate the financial burden of healthcare systems. In the past, the genomics community (mostly through large-scale, deep genomic sequencing technologies) has been steadily improving our understanding of the molecular basis of disease, with a number of biomarker panels already authorized by the U.S. Food and Drug Administration (FDA) for clinical use (e.g., MammaPrint, two recently cleared devices using next-generation sequencing platforms to detect DNA changes in the cystic fibrosis transmembrane conductance regulator (CFTR) gene). Clinical proteomics, on the other hand, albeit its ability to delineate the functional units of a cell, more likely driving the phenotypic differences of a disease (i.e., proteins and protein-protein interaction networks and signaling pathways underlying the disease), "staggers" to make a significant impact with only an average ∼ 1.5 protein biomarkers per year approved by the FDA over the past 15-20 years. This statistic itself raises the concern that major roadblocks have been impeding an efficient transition of protein marker candidates in biomarker development despite major technological advances in proteomics in recent years.

  9. Random glycopeptide bead libraries for seromic biomarker discovery

    DEFF Research Database (Denmark)

    Kracun, Stjepan Kresimir; Cló, Emiliano; Clausen, Henrik


    Identification of disease-specific biomarkers is important to address early diagnosis and management of disease. Aberrant post-translational modifications (PTM) of proteins such as O-glycosylations (O-PTMs) are emerging as triggers of autoantibodies that can serve as sensitive biomarkers. Here we...... have developed a random glycopeptide bead library screening platform for detection of autoantibodies and other binding proteins. Libraries were build on biocompatible PEGA beads including a safety-catch C-terminal amide linker (SCAL) that allowed mild cleavage conditions (I(2)/NaBH(4) and TFA......) for release of glycopeptides and sequence determination by ESI-Orbitrap-MS(n). As proof-of-principle, tumor -specific glycopeptide reporter epitopes were built-in into the libraries and were detected by tumor-specific monoclonal antibodies and autoantibodies from cancer patients. Sequenced and identified...

  10. A flexible integration and visualisation system for biomarker discovery. (United States)

    Gaylord, Mary; Calley, John; Qiang, Huahong; Su, Eric W; Liao, Birong


    Biological data have accumulated at an unprecedented pace as a result of improvements in molecular technologies. However, the translation of data into information, and subsequently into knowledge, requires the intricate interplay of data access, visualisation and interpretation. Biological data are complex and are organised either hierarchically or non-hierarchically. For non-hierarchically organised data, it is difficult to view relationships among biological facts. In addition, it is difficult to make changes in underlying data storage without affecting the visualisation interface. Here, we demonstrate a platform where non-hierarchically organised data can be visualised through the application of a customised hierarchy incorporating medical subject headings (MeSH) classifications. This platform gives users flexibility in updating and manipulation. It can also facilitate fresh scientific insight by highlighting biological impacts across different hierarchical branches. An example of the integration of biomarker information from the curated Proteome database using MeSH and the StarTree visualisation tool is presented.

  11. Proteomics and Mass Spectrometry for Cancer Biomarker Discovery

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    Ming Lu


    Full Text Available Proteomics is a rapidly advancing field not only in the field of biology but also in translational cancer research. In recent years, mass spectrometry and associated technologies have been explored to identify proteins or a set of proteins specific to a given disease, for the purpose of disease detection and diagnosis. Such biomarkers are being investigated in samples including cells, tissues, serum/plasma, and other types of body fluids. When sufficiently refined, proteomic technologies may pave the way for early detection of cancer or individualized therapy for cancer. Mass spectrometry approaches coupled with bioinformatic tools are being developed for biomarker discovery and validation. Understanding basic concepts and application of such technology by investigators in the field may accelerate the clinical application of protein biomarkers in disease management.Abbreviations: 2DE: two-dimensional gel electrophoresis; ABPP: activity-based protein profiling; CEA: carcinoembryonic antigen; CI: confidence interval; ESI: electrospray ionization; FP: fluorophosphonate; HPLC: high performance liquid chromatography; ICAT: isotope coded affi nitytags; IEF: isoelectric focusing; iTRAQ: isobaric tags for relative and absolute quantification; LCMS: combined liquid chromatography-mass spectrometry; LCMSMS: liquid chromatography tandem mass spectrometry; LOD: limit of detection; m/z: mass to charge ratio; MALDI: matrix-assisted laser desorption ionization; MS: mass spectrometry; MUDPIT: multidimensional protein identification technology; NAF: nipple aspirate fluid; PMF: peptide mass fingerprinting; PSA: prostate specifi c antigen; PTMs: post-translational modifications; RPMA: reverse phase protein microarray; SELDI: surface enhanced laser desorption ionization; TOF: time-of-flight.

  12. Serum Glycoprotein Biomarker Discovery and Qualification Pipeline Reveals Novel Diagnostic Biomarker Candidates for Esophageal Adenocarcinoma. (United States)

    Shah, Alok K; Cao, Kim-Anh Lê; Choi, Eunju; Chen, David; Gautier, Benoît; Nancarrow, Derek; Whiteman, David C; Saunders, Nicholas A; Barbour, Andrew P; Joshi, Virendra; Hill, Michelle M


    We report an integrated pipeline for efficient serum glycoprotein biomarker candidate discovery and qualification that may be used to facilitate cancer diagnosis and management. The discovery phase used semi-automated lectin magnetic bead array (LeMBA)-coupled tandem mass spectrometry with a dedicated data-housing and analysis pipeline; GlycoSelector ( The qualification phase used lectin magnetic bead array-multiple reaction monitoring-mass spectrometry incorporating an interactive web-interface, Shiny mixOmics (, for univariate and multivariate statistical analysis. Relative quantitation was performed by referencing to a spiked-in glycoprotein, chicken ovalbumin. We applied this workflow to identify diagnostic biomarkers for esophageal adenocarcinoma (EAC), a life threatening malignancy with poor prognosis in the advanced setting. EAC develops from metaplastic condition Barrett's esophagus (BE). Currently diagnosis and monitoring of at-risk patients is through endoscopy and biopsy, which is expensive and requires hospital admission. Hence there is a clinical need for a noninvasive diagnostic biomarker of EAC. In total 89 patient samples from healthy controls, and patients with BE or EAC were screened in discovery and qualification stages. Of the 246 glycoforms measured in the qualification stage, 40 glycoforms (as measured by lectin affinity) qualified as candidate serum markers. The top candidate for distinguishing healthy from BE patients' group was Narcissus pseudonarcissus lectin (NPL)-reactive Apolipoprotein B-100 (p value = 0.0231; AUROC = 0.71); BE versus EAC, Aleuria aurantia lectin (AAL)-reactive complement component C9 (p value = 0.0001; AUROC = 0.85); healthy versus EAC, Erythroagglutinin Phaseolus vulgaris (EPHA)-reactive gelsolin (p value = 0.0014; AUROC = 0.80). A panel of 8 glycoforms showed an improved AUROC of 0.94 to discriminate EAC from BE. Two biomarker candidates

  13. Targeted discovery and validation of plasma biomarkers of Parkinson's disease. (United States)

    Pan, Catherine; Zhou, Yong; Dator, Romel; Ginghina, Carmen; Zhao, Yanchun; Movius, James; Peskind, Elaine; Zabetian, Cyrus P; Quinn, Joseph; Galasko, Douglas; Stewart, Tessandra; Shi, Min; Zhang, Jing


    Despite extensive research, an unmet need remains for protein biomarkers of Parkinson's disease (PD) in peripheral body fluids, especially blood, which is easily accessible clinically. The discovery of such biomarkers is challenging, however, due to the enormous complexity and huge dynamic range of human blood proteins, which are derived from nearly all organ systems, with those originating specifically from the central nervous system (CNS) being exceptionally low in abundance. In this investigation of a relatively large cohort (∼300 subjects), selected reaction monitoring (SRM) assays (a targeted approach) were used to probe plasma peptides derived from glycoproteins previously found to be altered in the CNS based on PD diagnosis or severity. Next, the detected peptides were interrogated for their diagnostic sensitivity and specificity as well as the correlation with PD severity, as determined by the Unified Parkinson's Disease Rating Scale (UPDRS). The results revealed that 12 of the 50 candidate glycopeptides were reliably and consistently identified in plasma samples, with three of them displaying significant differences among diagnostic groups. A combination of four peptides (derived from PRNP, HSPG2, MEGF8, and NCAM1) provided an overall area under curve (AUC) of 0.753 (sensitivity: 90.4%; specificity: 50.0%). Additionally, combining two peptides (derived from MEGF8 and ICAM1) yielded significant correlation with PD severity, that is, UPDRS (r = 0.293, p = 0.004). The significance of these results is at least two-fold: (1) it is possible to use a targeted approach to identify otherwise very difficult to detect CNS related biomarkers in peripheral blood and (2) the novel biomarkers, if validated in independent cohorts, can be employed to assist with clinical diagnosis of PD as well as monitoring disease progression.

  14. Novel automated biomarker discovery work flow for urinary peptidomics

    DEFF Research Database (Denmark)

    Balog, Crina I.; Hensbergen, Paul J.; Derks, Rico


    eluted peptides using MALDI-TOF, Fourier transform ion cyclotron resonance, and liquid chromatography-iontrap mass spectrometry. We determined qualitative and quantitative reproducibility of the system and robustness of the method using BSA digests and urine samples, and we used a selected set of urine...... numbers of urine samples, resulting in a broad spectrum of native peptides, as a tool to be used for biomarker discovery. METHODS: Peptide samples were trapped, desalted, pH-normalized, and fractionated on a miniaturized automatic reverse-phase strong cation exchange (RP-SCX) cartridge system. We analyzed...... samples from Schistosoma haematobium-infected individuals to evaluate clinical applicability. RESULTS: The automated RP-SCX sample cleanup and fractionation system exhibits a high qualitative and quantitative reproducibility, with both BSA standards and urine samples. Because of the relatively high...

  15. Multi-dimensional discovery of biomarker and phenotype complexes

    Directory of Open Access Journals (Sweden)

    Huang Kun


    Full Text Available Abstract Background Given the rapid growth of translational research and personalized healthcare paradigms, the ability to relate and reason upon networks of bio-molecular and phenotypic variables at various levels of granularity in order to diagnose, stage and plan treatments for disease states is highly desirable. Numerous techniques exist that can be used to develop networks of co-expressed or otherwise related genes and clinical features. Such techniques can also be used to create formalized knowledge collections based upon the information incumbent to ontologies and domain literature. However, reports of integrative approaches that bridge such networks to create systems-level models of disease or wellness are notably lacking in the contemporary literature. Results In response to the preceding gap in knowledge and practice, we report upon a prototypical series of experiments that utilize multi-modal approaches to network induction. These experiments are intended to elicit meaningful and significant biomarker-phenotype complexes spanning multiple levels of granularity. This work has been performed in the experimental context of a large-scale clinical and basic science data repository maintained by the National Cancer Institute (NCI funded Chronic Lymphocytic Leukemia Research Consortium. Conclusions Our results indicate that it is computationally tractable to link orthogonal networks of genes, clinical features, and conceptual knowledge to create multi-dimensional models of interrelated biomarkers and phenotypes. Further, our results indicate that such systems-level models contain interrelated bio-molecular and clinical markers capable of supporting hypothesis discovery and testing. Based on such findings, we propose a conceptual model intended to inform the cross-linkage of the results of such methods. This model has as its aim the identification of novel and knowledge-anchored biomarker-phenotype complexes.

  16. Novel avenues of drug discovery and biomarkers for diabetes mellitus. (United States)

    Maiese, Kenneth; Chong, Zhao Zhong; Shang, Yan Chen; Hou, Jinling


    Globally, developed nations spend a significant amount of their resources on health care initiatives that poorly translate into increased population life expectancy. As an example, the United States devotes 16% of its gross domestic product to health care, the highest level in the world, but falls behind other nations that enjoy greater individual life expectancy. These observations point to the need for pioneering avenues of drug discovery to increase life span with controlled costs. In particular, innovative drug development for metabolic disorders such as diabetes mellitus becomes increasingly critical given that the number of diabetic people will increase exponentially over the next 20 years. This article discusses the elucidation and targeting of novel cellular pathways that are intimately tied to oxidative stress in diabetes mellitus for new treatment strategies. Pathways that involve wingless, β-nicotinamide adenine dinucleotide (NAD(+)) precursors, and cytokines govern complex biological pathways that determine both cell survival and longevity during diabetes mellitus and its complications. Furthermore, the role of these entities as biomarkers for disease can further enhance their utility irrespective of their treatment potential. Greater understanding of the intricacies of these unique cellular mechanisms will shape future drug discovery for diabetes mellitus to provide focused clinical care with limited or absent long-term complications.

  17. As if Biomarker Discovery Isn't Hard Enough: the Consequences of Poorly Characterized Reagents

    Energy Technology Data Exchange (ETDEWEB)

    Rodland, Karin D.


    The advent of high throughput omic technologies over the past two decades has driven a vast expansion in the search for clinical biomarkers, as manifested by the plethora of publications on biomarker discovery (over 8,600) listed on PubMed since 2000. Unfortunately, the same time period has seen a relative dearth of clinically validated biomarkers that have received FDA approval; only 10 new cancer biomarkers have been approved by the FDA in the same time period [1].

  18. Sparse Mbplsr for Metabolomics Data and Biomarker Discovery

    DEFF Research Database (Denmark)

    Karaman, İbrahim


    the link between high throughput metabolomics data generated on different analytical platforms, discover important metabolites deriving from the digestion processes in the gut, and automate metabolic pathway discovery from mass spectrometry. PLS (partial least squares) based chemometric methods were...... the relationships between data-blocks and their contribution to predictive models. Among many variable selection techniques, we compared Sparse PLSR and Jack-knife PLSR according to the stability of the variable selection and the predictive ability. Further we used cross model validation (CMV) for assessing...... the importance of selected variables by plotting selection frequencies and correlation loading plots of the variables. In addition, predictive ability was studied by comparing errors of cross validation and CMV. According to the results, Sparse PLSR outperformed Jack-knife PLSR under the conditions tested. Jack...

  19. NMR and pattern recognition methods in metabolomics: From data acquisition to biomarker discovery: A review

    Energy Technology Data Exchange (ETDEWEB)

    Smolinska, Agnieszka, E-mail: [Institute for Molecules and Materials, Radboud University Nijmegen, Nijmegen (Netherlands); Blanchet, Lionel [Institute for Molecules and Materials, Radboud University Nijmegen, Nijmegen (Netherlands); Department of Biochemistry, Nijmegen Centre for Molecular Life Sciences, Radboud University Nijmegen Medical Centre, Nijmegen (Netherlands); Buydens, Lutgarde M.C.; Wijmenga, Sybren S. [Institute for Molecules and Materials, Radboud University Nijmegen, Nijmegen (Netherlands)


    Highlights: Black-Right-Pointing-Pointer Procedures for acquisition of different biofluids by NMR. Black-Right-Pointing-Pointer Recent developments in metabolic profiling of different biofluids by NMR are presented. Black-Right-Pointing-Pointer The crucial steps involved in data preprocessing and multivariate chemometric analysis are reviewed. Black-Right-Pointing-Pointer Emphasis is given on recent findings on Multiple Sclerosis via NMR and pattern recognition methods. - Abstract: Metabolomics is the discipline where endogenous and exogenous metabolites are assessed, identified and quantified in different biological samples. Metabolites are crucial components of biological system and highly informative about its functional state, due to their closeness to functional endpoints and to the organism's phenotypes. Nuclear Magnetic Resonance (NMR) spectroscopy, next to Mass Spectrometry (MS), is one of the main metabolomics analytical platforms. The technological developments in the field of NMR spectroscopy have enabled the identification and quantitative measurement of the many metabolites in a single sample of biofluids in a non-targeted and non-destructive manner. Combination of NMR spectra of biofluids and pattern recognition methods has driven forward the application of metabolomics in the field of biomarker discovery. The importance of metabolomics in diagnostics, e.g. in identifying biomarkers or defining pathological status, has been growing exponentially as evidenced by the number of published papers. In this review, we describe the developments in data acquisition and multivariate analysis of NMR-based metabolomics data, with particular emphasis on the metabolomics of Cerebrospinal Fluid (CSF) and biomarker discovery in Multiple Sclerosis (MScl).

  20. A platform for the discovery of new macrolide antibiotics (United States)

    Seiple, Ian B.; Zhang, Ziyang; Jakubec, Pavol; Langlois-Mercier, Audrey; Wright, Peter M.; Hog, Daniel T.; Yabu, Kazuo; Allu, Senkara Rao; Fukuzaki, Takehiro; Carlsen, Peter N.; Kitamura, Yoshiaki; Zhou, Xiang; Condakes, Matthew L.; Szczypiński, Filip T.; Green, William D.; Myers, Andrew G.


    The chemical modification of structurally complex fermentation products, a process known as semisynthesis, has been an important tool in the discovery and manufacture of antibiotics for the treatment of various infectious diseases. However, many of the therapeutics obtained in this way are no longer effective, because bacterial resistance to these compounds has developed. Here we present a practical, fully synthetic route to macrolide antibiotics by the convergent assembly of simple chemical building blocks, enabling the synthesis of diverse structures not accessible by traditional semisynthetic approaches. More than 300 new macrolide antibiotic candidates, as well as the clinical candidate solithromycin, have been synthesized using our convergent approach. Evaluation of these compounds against a panel of pathogenic bacteria revealed that the majority of these structures had antibiotic activity, some efficacious against strains resistant to macrolides in current use. The chemistry we describe here provides a platform for the discovery of new macrolide antibiotics and may also serve as the basis for their manufacture.

  1. Integrative genomic data mining for discovery of potential blood-borne biomarkers for early diagnosis of cancer.

    Directory of Open Access Journals (Sweden)

    Yongliang Yang

    Full Text Available BACKGROUND: With the arrival of the postgenomic era, there is increasing interest in the discovery of biomarkers for the accurate diagnosis, prognosis, and early detection of cancer. Blood-borne cancer markers are favored by clinicians, because blood samples can be obtained and analyzed with relative ease. We have used a combined mining strategy based on an integrated cancer microarray platform, Oncomine, and the biomarker module of the Ingenuity Pathways Analysis (IPA program to identify potential blood-based markers for six common human cancer types. METHODOLOGY/PRINCIPAL FINDINGS: In the Oncomine platform, the genes overexpressed in cancer tissues relative to their corresponding normal tissues were filtered by Gene Ontology keywords, with the extracellular environment stipulated and a corrected Q value (false discovery rate cut-off implemented. The identified genes were imported to the IPA biomarker module to separate out those genes encoding putative secreted or cell-surface proteins as blood-borne (blood/serum/plasma cancer markers. The filtered potential indicators were ranked and prioritized according to normalized absolute Student t values. The retrieval of numerous marker genes that are already clinically useful or under active investigation confirmed the effectiveness of our mining strategy. To identify the biomarkers that are unique for each cancer type, the upregulated marker genes that are in common between each two tumor types across the six human tumors were also analyzed by the IPA biomarker comparison function. CONCLUSION/SIGNIFICANCE: The upregulated marker genes shared among the six cancer types may serve as a molecular tool to complement histopathologic examination, and the combination of the commonly upregulated and unique biomarkers may serve as differentiating markers for a specific cancer. This approach will be increasingly useful to discover diagnostic signatures as the mass of microarray data continues to grow in the

  2. Disease Classification and Biomarker Discovery Using ECG Data

    Directory of Open Access Journals (Sweden)

    Rong Huang


    Full Text Available In the recent decade, disease classification and biomarker discovery have become increasingly important in modern biological and medical research. ECGs are comparatively low-cost and noninvasive in screening and diagnosing heart diseases. With the development of personal ECG monitors, large amounts of ECGs are recorded and stored; therefore, fast and efficient algorithms are called for to analyze the data and make diagnosis. In this paper, an efficient and easy-to-interpret procedure of cardiac disease classification is developed through novel feature extraction methods and comparison of classifiers. Motivated by the observation that the distributions of various measures on ECGs of the diseased group are often skewed, heavy-tailed, or multimodal, we characterize the distributions by sample quantiles which outperform sample means. Three classifiers are compared in application both to all features and to dimension-reduced features by PCA: stepwise discriminant analysis (SDA, SVM, and LASSO logistic regression. It is found that SDA applied to dimension-reduced features by PCA is the most stable and effective procedure, with sensitivity, specificity, and accuracy being 89.68%, 84.62%, and 88.52%, respectively.

  3. Approach to Cerebrospinal Fluid (CSF) Biomarker Discovery and Evaluation in HIV Infection

    Energy Technology Data Exchange (ETDEWEB)

    Price, Richard W.; Peterson, Julia; Fuchs, Dietmar; Angel, Thomas E.; Zetterberg, Henrik; Hagberg, Lars; Spudich, Serena S.; Smith, Richard D.; Jacobs, Jon M.; Brown, Joseph N.; Gisslen, Magnus


    Central nervous system (CNS) infection is a nearly universal facet of systemic HIV infection that varies in character and neurological consequences. While clinical staging and neuropsychological test performance have been helpful in evaluating patients, cerebrospinal fluid (CSF) biomarkers present a valuable and objective approach to more accurate diagnosis, assessment of treatment effects and understanding of evolving pathobiology. We review some lessons from our recent experience with CSF biomarker studies. We have used two approaches to biomarker analysis: targeted, hypothesis-driven and non-targeted exploratory discovery methods. We illustrate the first with data from a cross-sectional study of defined subject groups across the spectrum of systemic and CNS disease progression and the second with a longitudinal study of the CSF proteome in subjects initiating antiretroviral treatment. Both approaches can be useful and, indeed, complementary. The first is helpful in assessing known or hypothesized biomarkers while the second can identify novel biomarkers and point to broad interactions in pathogenesis. Common to both is the need for well-defined samples and subjects that span a spectrum of biological activity and biomarker concentrations. Previouslydefined guide biomarkers of CNS infection, inflammation and neural injury are useful in categorizing samples for analysis and providing critical biological context for biomarker discovery studies. CSF biomarkers represent an underutilized but valuable approach to understanding the interactions of HIV and the CNS and to more objective diagnosis and assessment of disease activity. Both hypothesis-based and discovery methods can be useful in advancing the definition and use of these biomarkers.

  4. Statistical spectroscopic tools for biomarker discovery and systems medicine. (United States)

    Robinette, Steven L; Lindon, John C; Nicholson, Jeremy K


    Metabolic profiling based on comparative, statistical analysis of NMR spectroscopic and mass spectrometric data from complex biological samples has contributed to increased understanding of the role of small molecules in affecting and indicating biological processes. To enable this research, the development of statistical spectroscopy has been marked by early beginnings in applying pattern recognition to nuclear magnetic resonance data and the introduction of statistical total correlation spectroscopy (STOCSY) as a tool for biomarker identification in the past decade. Extensions of statistical spectroscopy now compose a family of related tools used for compound identification, data preprocessing, and metabolic pathway analysis. In this Perspective, we review the theory and current state of research in statistical spectroscopy and discuss the growing applications of these tools to medicine and systems biology. We also provide perspectives on how recent institutional initiatives are providing new platforms for the development and application of statistical spectroscopy tools and driving the development of integrated "systems medicine" approaches in which clinical decision making is supported by statistical and computational analysis of metabolic, phenotypic, and physiological data.

  5. Analysis of Reverse Phase Protein Array Data: From Experimental Design towards Targeted Biomarker Discovery (United States)

    Wachter, Astrid; Bernhardt, Stephan; Beissbarth, Tim; Korf, Ulrike


    Mastering the systematic analysis of tumor tissues on a large scale has long been a technical challenge for proteomics. In 2001, reverse phase protein arrays (RPPA) were added to the repertoire of existing immunoassays, which, for the first time, allowed a profiling of minute amounts of tumor lysates even after microdissection. A characteristic feature of RPPA is its outstanding sample capacity permitting the analysis of thousands of samples in parallel as a routine task. Until today, the RPPA approach has matured to a robust and highly sensitive high-throughput platform, which is ideally suited for biomarker discovery. Concomitant with technical advancements, new bioinformatic tools were developed for data normalization and data analysis as outlined in detail in this review. Furthermore, biomarker signatures obtained by different RPPA screens were compared with another or with that obtained by other proteomic formats, if possible. Options for overcoming the downside of RPPA, which is the need to steadily validate new antibody batches, will be discussed. Finally, a debate on using RPPA to advance personalized medicine will conclude this article. PMID:27600238

  6. Analysis of Reverse Phase Protein Array Data: From Experimental Design towards Targeted Biomarker Discovery

    Directory of Open Access Journals (Sweden)

    Astrid Wachter


    Full Text Available Mastering the systematic analysis of tumor tissues on a large scale has long been a technical challenge for proteomics. In 2001, reverse phase protein arrays (RPPA were added to the repertoire of existing immunoassays, which, for the first time, allowed a profiling of minute amounts of tumor lysates even after microdissection. A characteristic feature of RPPA is its outstanding sample capacity permitting the analysis of thousands of samples in parallel as a routine task. Until today, the RPPA approach has matured to a robust and highly sensitive high-throughput platform, which is ideally suited for biomarker discovery. Concomitant with technical advancements, new bioinformatic tools were developed for data normalization and data analysis as outlined in detail in this review. Furthermore, biomarker signatures obtained by different RPPA screens were compared with another or with that obtained by other proteomic formats, if possible. Options for overcoming the downside of RPPA, which is the need to steadily validate new antibody batches, will be discussed. Finally, a debate on using RPPA to advance personalized medicine will conclude this article.

  7. Biomarker discovery in subclinical mycobacterial infections of cattle.

    Directory of Open Access Journals (Sweden)

    Meetu Seth

    Full Text Available BACKGROUND: Bovine tuberculosis is a highly prevalent infectious disease of cattle worldwide; however, infection in the United States is limited to 0.01% of dairy herds. Thus detection of bovine TB is confounded by high background infection with M. avium subsp. paratuberculosis. The present study addresses variations in the circulating peptidome based on the pathogenesis of two biologically similar mycobacterial diseases of cattle. METHODOLOGY/PRINCIPAL FINDINGS: We hypothesized that serum proteomes of animals in response to either M. bovis or M. paratuberculosis infection will display several commonalities and differences. Sera prospectively collected from animals experimentally infected with either M. bovis or M. paratuberculosis were analyzed using high-resolution proteomics approaches. iTRAQ, a liquid chromatography and tandem mass spectrometry approach, was used to simultaneously identify and quantify peptides from multiple infections and contemporaneous uninfected control groups. Four comparisons were performed: 1 M. bovis infection versus uninfected controls, 2 M. bovis versus M. paratuberculosis infection, 3 early, and 4 advanced M. paratuberculosis infection versus uninfected controls. One hundred and ten differentially elevated proteins (P < or = 0.05 were identified. Vitamin D binding protein precursor (DBP, alpha-1 acid glycoprotein, alpha-1B glycoprotein, fetuin, and serine proteinase inhibitor were identified in both infections. Transthyretin, retinol binding proteins, and cathelicidin were identified exclusively in M. paratuberculosis infection, while the serum levels of alpha-1-microglobulin/bikunin precursor (AMBP protein, alpha-1 acid glycoprotein, fetuin, and alpha-1B glycoprotein were elevated exclusively in M. bovis infected animals. CONCLUSIONS/SIGNIFICANCE: The discovery of these biomarkers has significant impact on the elucidation of pathogenesis of two mycobacterial diseases at the cellular and the molecular level and

  8. atBioNet– an integrated network analysis tool for genomics and biomarker discovery

    Directory of Open Access Journals (Sweden)

    Ding Yijun


    Full Text Available Abstract Background Large amounts of mammalian protein-protein interaction (PPI data have been generated and are available for public use. From a systems biology perspective, Proteins/genes interactions encode the key mechanisms distinguishing disease and health, and such mechanisms can be uncovered through network analysis. An effective network analysis tool should integrate different content-specific PPI databases into a comprehensive network format with a user-friendly platform to identify key functional modules/pathways and the underlying mechanisms of disease and toxicity. Results atBioNet integrates seven publicly available PPI databases into a network-specific knowledge base. Knowledge expansion is achieved by expanding a user supplied proteins/genes list with interactions from its integrated PPI network. The statistically significant functional modules are determined by applying a fast network-clustering algorithm (SCAN: a Structural Clustering Algorithm for Networks. The functional modules can be visualized either separately or together in the context of the whole network. Integration of pathway information enables enrichment analysis and assessment of the biological function of modules. Three case studies are presented using publicly available disease gene signatures as a basis to discover new biomarkers for acute leukemia, systemic lupus erythematosus, and breast cancer. The results demonstrated that atBioNet can not only identify functional modules and pathways related to the studied diseases, but this information can also be used to hypothesize novel biomarkers for future analysis. Conclusion atBioNet is a free web-based network analysis tool that provides a systematic insight into proteins/genes interactions through examining significant functional modules. The identified functional modules are useful for determining underlying mechanisms of disease and biomarker discovery. It can be accessed at: http

  9. Yeast display of antibody fragments: a discovery and characterization platform

    Energy Technology Data Exchange (ETDEWEB)

    Feldhaus, Michael; Siegel, Robert W.


    This review will focus on some of the novel attributes of the yeast surface display platform for the discovery and characterization of novel affinity reagents, optimization of those reagents, and novel uses of the platform. This is not intended to serve as an exhaustive review on the broader topic of general scFv technologies (see Winter et al., 1994; Smith and Petrenko, 1997; Bradbury et al., 2003) Furthermore, the scFv format of antibodies are easily manipulated through molecular cloning into a number of other formats such IgG, Fab, diabodies and such, for use in down steam applications and the reader is encouraged to read ?IgG?, ?Fab?, or your favorite format whenever scFv is seen in this review. This review is presented in 5 parts; (1) description of yeast display and its components, (2) library types and construction methods, (3) screening approaches for non-immune libraries and benefits, (4) screening approaches for directed evolution, kinetic on and off rates and (5) epitope complementation binning of clones.

  10. Approach to cerebrospinal fluid (CSF) biomarker discovery and evaluation in HIV infection. (United States)

    Price, Richard W; Peterson, Julia; Fuchs, Dietmar; Angel, Thomas E; Zetterberg, Henrik; Hagberg, Lars; Spudich, Serena; Smith, Richard D; Jacobs, Jon M; Brown, Joseph N; Gisslen, Magnus


    Central nervous system (CNS) infection is a nearly universal facet of systemic HIV infection that varies in character and neurological consequences. While clinical staging and neuropsychological test performance have been helpful in evaluating patients, cerebrospinal fluid (CSF) biomarkers present a valuable and objective approach to more accurate diagnosis, assessment of treatment effects and understanding of evolving pathobiology. We review some lessons from our recent experience with CSF biomarker studies. We have used two approaches to biomarker analysis: targeted, hypothesis-driven and non-targeted exploratory discovery methods. We illustrate the first with data from a cross-sectional study of defined subject groups across the spectrum of systemic and CNS disease progression and the second with a longitudinal study of the CSF proteome in subjects initiating antiretroviral treatment. Both approaches can be useful and, indeed, complementary. The first is helpful in assessing known or hypothesized biomarkers while the second can identify novel biomarkers and point to broad interactions in pathogenesis. Common to both is the need for well-defined samples and subjects that span a spectrum of biological activity and biomarker concentrations. Previously-defined guide biomarkers of CNS infection, inflammation and neural injury are useful in categorizing samples for analysis and providing critical biological context for biomarker discovery studies. CSF biomarkers represent an underutilized but valuable approach to understanding the interactions of HIV and the CNS and to more objective diagnosis and assessment of disease activity. Both hypothesis-based and discovery methods can be useful in advancing the definition and use of these biomarkers.

  11. The Clinical Impact of Recent Advances in LC-MS for Cancer Biomarker Discovery and Verification

    Energy Technology Data Exchange (ETDEWEB)

    Wang, Hui; Shi, Tujin; Qian, Weijun; Liu, Tao; Kagan, Jacob; Srivastava, Sudhir; Smith, Richard D.; Rodland, Karin D.; Camp, David G.


    Mass spectrometry-based proteomics has become an indispensable tool in biomedical research with broad applications ranging from fundamental biology, systems biology, and biomarker discovery. Recent advances in LC-MS have made it become a major technology in clinical applications, especially in cancer biomarker discovery and verification. To overcome the challenges associated with the analysis of clinical samples, such as extremely wide dynamic range of protein concentrations in biofluids and the need to perform high throughput and accurate quantification, significant efforts have been devoted to improve the overall performance of LC-MS bases clinical proteomics. In this review, we summarize the recent advances in LC-MS in the aspect of cancer biomarker discovery and quantification, and discuss its potentials, limitations, and future perspectives.

  12. Application of multiple statistical tests to enhance mass spectrometry-based biomarker discovery

    Directory of Open Access Journals (Sweden)

    Garner Harold R


    Full Text Available Abstract Background Mass spectrometry-based biomarker discovery has long been hampered by the difficulty in reconciling lists of discriminatory peaks identified by different laboratories for the same diseases studied. We describe a multi-statistical analysis procedure that combines several independent computational methods. This approach capitalizes on the strengths of each to analyze the same high-resolution mass spectral data set to discover consensus differential mass peaks that should be robust biomarkers for distinguishing between disease states. Results The proposed methodology was applied to a pilot narcolepsy study using logistic regression, hierarchical clustering, t-test, and CART. Consensus, differential mass peaks with high predictive power were identified across three of the four statistical platforms. Based on the diagnostic accuracy measures investigated, the performance of the consensus-peak model was a compromise between logistic regression and CART, which produced better models than hierarchical clustering and t-test. However, consensus peaks confer a higher level of confidence in their ability to distinguish between disease states since they do not represent peaks that are a result of biases to a particular statistical algorithm. Instead, they were selected as differential across differing data distribution assumptions, demonstrating their true discriminatory potential. Conclusion The methodology described here is applicable to any high-resolution MALDI mass spectrometry-derived data set with minimal mass drift which is essential for peak-to-peak comparison studies. Four statistical approaches with differing data distribution assumptions were applied to the same raw data set to obtain consensus peaks that were found to be statistically differential between the two groups compared. These consensus peaks demonstrated high diagnostic accuracy when used to form a predictive model as evaluated by receiver operating characteristics

  13. Platform for Plasmodium vivax vaccine discovery and development. (United States)

    Valencia, Sócrates Herrera; Rodríguez, Diana Carolina; Acero, Diana Lucía; Ocampo, Vanessa; Arévalo-Herrera, Myriam


    Plasmodium vivax is the most prevalent malaria parasite on the American continent. It generates a global burden of 80-100 million cases annually and represents a tremendous public health problem, particularly in the American and Asian continents. A malaria vaccine would be considered the most cost-effective measure against this vector-borne disease and it would contribute to a reduction in malaria cases and to eventual eradication. Although significant progress has been achieved in the search for Plasmodium falciparum antigens that could be used in a vaccine, limited progress has been made in the search for P. vivax components that might be eligible for vaccine development. This is primarily due to the lack of in vitro cultures to serve as an antigen source and to inadequate funding. While the most advanced P. falciparum vaccine candidate is currently being tested in Phase III trials in Africa, the most advanced P. vivax candidates have only advanced to Phase I trials. Herein, we describe the overall strategy and progress in P. vivax vaccine research, from antigen discovery to preclinical and clinical development and we discuss the regional potential of Latin America to develop a comprehensive platform for vaccine development.

  14. Discovery of biomarkers for oxidative stress based on cellular metabolomics. (United States)

    Wang, Ningli; Wei, Jianteng; Liu, Yewei; Pei, Dong; Hu, Qingping; Wang, Yu; Di, Duolong


    Oxidative stress has a close relationship with various pathologic physiology phenomena and the potential biomarkers of oxidative stress may provide evidence for clinical diagnosis or disease prevention. Metabolomics was employed to identify the potential biomarkers of oxidative stress. High-performance liquid chromatography-diode array detector, mass spectrometry and partial least squares discriminate analysis were used in this study. The 10, 15 and 13 metabolites were considered to discriminate the model group, vitamin E-treated group and l-glutathione-treated group, respectively. Some of them have been identified, namely, malic acid, vitamin C, reduced glutathione and tryptophan. Identification of other potential biomarkers should be conducted and their physiological significance also needs to be elaborated.

  15. Discovery and development of DNA methylation-based biomarkers for lung cancer. (United States)

    Walter, Kimberly; Holcomb, Thomas; Januario, Tom; Yauch, Robert L; Du, Pan; Bourgon, Richard; Seshagiri, Somasekar; Amler, Lukas C; Hampton, Garret M; S Shames, David


    Lung cancer remains the primary cause of cancer-related deaths worldwide. Improved tools for early detection and therapeutic stratification would be expected to increase the survival rate for this disease. Alterations in the molecular pathways that drive lung cancer, which include epigenetic modifications, may provide biomarkers to help address this major unmet clinical need. Epigenetic changes, which are defined as heritable changes in gene expression that do not alter the primary DNA sequence, are one of the hallmarks of cancer, and prevalent in all types of cancer. These modifications represent a rich source of biomarkers that have the potential to be implemented in clinical practice. This perspective describes recent advances in the discovery of epigenetic biomarkers in lung cancer, specifically those that result in the methylation of DNA at CpG sites. We discuss one approach for methylation-based biomarker assay development that describes the discovery at a genome-scale level, which addresses some of the practical considerations for design of assays that can be implemented in the clinic. We emphasize that an integrated technological approach will enable the development of clinically useful DNA methylation-based biomarker assays. While this article focuses on current literature and primary research findings in lung cancer, the principles we describe here apply to the discovery and development of epigenetic biomarkers for other types of cancer.

  16. Manifold Learning for Biomarker Discovery in MR Imaging (United States)

    Wolz, Robin; Aljabar, Paul; Hajnal, Joseph V.; Rueckert, Daniel

    We propose a framework for the extraction of biomarkers from low-dimensional manifolds representing inter- and intra-subject brain variation in MR image data. The coordinates of each image in such a low-dimensional space captures information about structural shape and appearance and, when a phenotype exists, about the subject's clinical state. A key contribution is that we propose a method for incorporating longitudinal image information in the learned manifold. In particular, we compare simultaneously embedding baseline and follow-up scans into a single manifold with the combination of separate manifold representations for inter-subject and intra-subject variation. We apply the proposed methods to 362 subjects enrolled in the Alzheimer's Disease Neuroimaging Initiative (ADNI) and classify healthy controls, subjects with Alzheimer's disease (AD) and subjects with mild cognitive impairment (MCI). Learning manifolds based on both the appearance and temporal change of the hippocampus, leads to correct classification rates comparable with those provided by state-of-the-art automatic segmentation estimates of hippocampal volume and atrophy. The biomarkers identified with the proposed method are data-driven and represent a potential alternative to a-priori defined biomarkers derived from manual or automated segmentations.

  17. Statistical design for biospecimen cohort size in proteomics-based biomarker discovery and verification studies. (United States)

    Skates, Steven J; Gillette, Michael A; LaBaer, Joshua; Carr, Steven A; Anderson, Leigh; Liebler, Daniel C; Ransohoff, David; Rifai, Nader; Kondratovich, Marina; Težak, Živana; Mansfield, Elizabeth; Oberg, Ann L; Wright, Ian; Barnes, Grady; Gail, Mitchell; Mesri, Mehdi; Kinsinger, Christopher R; Rodriguez, Henry; Boja, Emily S


    Protein biomarkers are needed to deepen our understanding of cancer biology and to improve our ability to diagnose, monitor, and treat cancers. Important analytical and clinical hurdles must be overcome to allow the most promising protein biomarker candidates to advance into clinical validation studies. Although contemporary proteomics technologies support the measurement of large numbers of proteins in individual clinical specimens, sample throughput remains comparatively low. This problem is amplified in typical clinical proteomics research studies, which routinely suffer from a lack of proper experimental design, resulting in analysis of too few biospecimens to achieve adequate statistical power at each stage of a biomarker pipeline. To address this critical shortcoming, a joint workshop was held by the National Cancer Institute (NCI), National Heart, Lung, and Blood Institute (NHLBI), and American Association for Clinical Chemistry (AACC) with participation from the U.S. Food and Drug Administration (FDA). An important output from the workshop was a statistical framework for the design of biomarker discovery and verification studies. Herein, we describe the use of quantitative clinical judgments to set statistical criteria for clinical relevance and the development of an approach to calculate biospecimen sample size for proteomic studies in discovery and verification stages prior to clinical validation stage. This represents a first step toward building a consensus on quantitative criteria for statistical design of proteomics biomarker discovery and verification research.

  18. Biomarker discovery by proteomics: challenges not only for the analytical chemist

    NARCIS (Netherlands)

    Horvatovich, P.; Govorukhina, N.I; Bischoff, Rainer


    This forum article outlines some of the major challenges in present day biomarker discovery research. Notably the dilemma of reaching sufficient concentration sensitivity versus the required analysis time per sample is highlighted using a model calculation. A number of possible developments and rece

  19. Biomarker discovery by proteomics : challenges not only for the analytical chemist

    NARCIS (Netherlands)

    Horvatovich, Peter; Govorukhina, Natalia; Bischoff, Rainer


    This forum article outlines some of the major challenges in present day biomarker discovery research. Notably the dilemma of reaching sufficient concentration sensitivity versus the required analysis time per sample is highlighted using a model calculation. A number of possible developments and rece

  20. Urinary Proteomics Pilot Study for Biomarker Discovery and Diagnosis in Heart Failure with Reduced Ejection Fraction

    DEFF Research Database (Denmark)

    Rossing, Kasper; Bosselmann, Helle Skovmand; Gustafsson, Finn


    BACKGROUND: Biomarker discovery and new insights into the pathophysiology of heart failure with reduced ejection fraction (HFrEF) may emerge from recent advances in high-throughput urinary proteomics. This could lead to improved diagnosis, risk stratification and management of HFrEF. METHODS...... AND RESULTS: Urine samples were analyzed by on-line capillary electrophoresis coupled to electrospray ionization micro time-of-flight mass spectrometry (CE-MS) to generate individual urinary proteome profiles. In an initial biomarker discovery cohort, analysis of urinary proteome profiles from 33 HFr.......6%) in individuals with diastolic left ventricular dysfunction (N = 176). The HFrEF-related peptide biomarkers mainly included fragments of fibrillar type I and III collagen but also, e.g., of fibrinogen beta and alpha-1-antitrypsin. CONCLUSION: CE-MS based urine proteome analysis served as a sensitive tool...

  1. Biomarker discovery by proteomics-based approaches for early detection and personalized medicine in colorectal cancer. (United States)

    Corbo, Claudia; Cevenini, Armando; Salvatore, Francesco


    About one million people per year develop colorectal cancer (CRC) and approximately half of them die. The extent of the disease (i.e. local invasion at the time of diagnosis) is a key prognostic factor. The 5-year survival rate is almost 90% in the case of delimited CRC and 10% in the case of metastasized CRC. Hence, one of the great challenges in the battle against CRC is to improve early diagnosis strategies. Large-scale proteomic approaches are widely used in cancer research to search for novel biomarkers. Such biomarkers can help in improving the accuracy of the diagnosis and in the optimization of personalized therapy. Herein, we provide an overview of studies published in the last 5 years on CRC that led to the identification of protein biomarkers suitable for clinical application by using proteomic approaches. We discussed these findings according to biomarker application, including also the role of protein phosphorylation and cancer stem cells in biomarker discovery. Our review provides a cross section of scientific approaches and can furnish suggestions for future experimental strategies to be used as reference by scientists, clinicians and researchers interested in proteomics for biomarker discovery.

  2. Cancer Stem Cell Biomarker Discovery Using Antibody Array Technology. (United States)

    Burgess, Rob; Huang, Ruo-Pan


    Cancer is a complex disease involving hundreds of pathways and numerous levels of disease progression. In addition, there is a growing body of evidence that the origins and growth rates of specific types of cancer may involve "cancer stem cells," which are defined as "cells within a tumor that possess the capacity to self-renew and to cause the development of heterogeneous lineages of cancer cells that comprise the tumor.(1)" Many types of cancer are now thought to harbor cancer stem cells. These cells themselves are thought to be unique in comparison to other cells types present within the tumor and to exhibit characteristics that allow for the promotion of tumorigenesis and in some cases metastasis. In addition, it is speculated that each type of cancer stem cell exhibits a unique set of molecular and biochemical markers. These markers, alone or in combination, may act as a signature for defining not only the type of cancer but also the progressive state. These biomarkers may also double as signaling entities which act autonomously or upon neighboring cancer stem cells or other cells within the local microenvironment to promote tumorigenesis. This review describes the heterogeneic properties of cancer stem cells and outlines the identification and application of biomarkers and signaling molecules defining these cells as they relate to different forms of cancer. Other examples of biomarkers and signaling molecules expressed by neighboring cells in the local tumor microenvironment are also discussed. In addition, biochemical signatures for cancer stem cell autocrine/paracrine signaling, local site recruitment, tumorigenic potential, and conversion to a stem-like phenotype are described.

  3. Comprehensive Phenotyping in Multiple Sclerosis: Discovery Based Proteomics and the Current Understanding of Putative Biomarkers

    Directory of Open Access Journals (Sweden)

    Kevin C. O’Connor


    Full Text Available Currently, there is no single test for multiple sclerosis (MS. Diagnosis is confirmed through clinical evaluation, abnormalities revealed by magnetic resonance imaging (MRI, and analysis of cerebrospinal fluid (CSF chemistry. The early and accurate diagnosis of the disease, monitoring of progression, and gauging of therapeutic intervention are important but elusive elements of patient care. Moreover, a deeper understanding of the disease pathology is needed, including discovery of accurate biomarkers for MS. Herein we review putative biomarkers of MS relating to neurodegeneration and contributions to neuropathology, with particular focus on autoimmunity. In addition, novel assessments of biomarkers not driven by hypotheses are discussed, featuring our application of advanced proteomics and metabolomics for comprehensive phenotyping of CSF and blood. This strategy allows comparison of component expression levels in CSF and serum between MS and control groups. Examination of these preliminary data suggests that several CSF proteins in MS are differentially expressed, and thus, represent putative biomarkers deserving of further evaluation.

  4. Enhancement of MS Signal Processing For Improved Cancer Biomarker Discovery (United States)

    Si, Qian

    Technological advances in proteomics have shown great potential in detecting cancer at the earliest stages. One way is to use the time of flight mass spectroscopy to identify biomarkers, or early disease indicators related to the cancer. Pattern analysis of time of flight mass spectra data from blood and tissue samples gives great hope for the identification of potential biomarkers among the complex mixture of biological and chemical samples for the early cancer detection. One of the keys issues is the pre-processing of raw mass spectra data. A lot of challenges need to be addressed: unknown noise character associated with the large volume of data, high variability in the mass spectroscopy measurements, and poorly understood signal background and so on. This dissertation focuses on developing statistical algorithms and creating data mining tools for computationally improved signal processing for mass spectrometry data. I have introduced an advanced accurate estimate of the noise model and a half-supervised method of mass spectrum data processing which requires little knowledge about the data.

  5. Biomarker discovery in neurological diseases: a metabolomic approach

    Directory of Open Access Journals (Sweden)

    Afaf El-Ansary


    Full Text Available Afaf El-Ansary, Nouf Al-Afaleg, Yousra Al-YafaeeBiochemistry Department, Science College, King Saud University, Riyadh, Saudi ArabiaAbstract: Biomarkers are pharmacological and physiological measurements or specific biochemicals in the body that have a particular molecular feature that makes them useful for measuring the progress of disease or the effects of treatment. Due to the complexity of neurological disorders, it is very difficult to have perfect markers. Brain diseases require plenty of markers to reflect the metabolic impairment of different brain cells. The recent introduction of the metabolomic approach helps the study of neurological diseases based on profiling a multitude of biochemical components related to brain metabolism. This review is a trial to elucidate the possibility to use this approach to identify plasma metabolic markers related to neurological disorders. Previous trials using different metabolomic analyses including nuclear magnetic resonance spectroscopy, gas chromatography combined with mass spectrometry, liquid chromatography combined with mass spectrometry, and capillary electrophoresis will be traced.Keywords: metabolic biomarkers, neurological disorders. metabolome, nuclear magnetic resonance, mass spectrometry, chromatography

  6. Aptamer-based detection of disease biomarkers in mouse models for chagas drug discovery.

    Directory of Open Access Journals (Sweden)

    Fernanda Fortes de Araujo


    Full Text Available Drug discovery initiatives, aimed at Chagas treatment, have been hampered by the lack of standardized drug screening protocols and the absence of simple pre-clinical assays to evaluate treatment efficacy in animal models. In this study, we used a simple Enzyme Linked Aptamer (ELA assay to detect T. cruzi biomarker in blood and validate murine drug discovery models of Chagas disease. In two mice models, Apt-29 ELA assay demonstrated that biomarker levels were significantly higher in the infected group compared to the control group, and upon Benznidazole treatment, their levels reduced. However, biomarker levels in the infected treated group did not reduce to those seen in the non-infected treated group, with 100% of the mice above the assay cutoff, suggesting that parasitemia was reduced but cure was not achieved. The ELA assay was capable of detecting circulating biomarkers in mice infected with various strains of T. cruzi parasites. Our results showed that the ELA assay could detect residual parasitemia in treated mice by providing an overall picture of the infection in the host. They suggest that the ELA assay can be used in drug discovery applications to assess treatment efficacy in-vivo.

  7. Aptamer-based detection of disease biomarkers in mouse models for chagas drug discovery. (United States)

    de Araujo, Fernanda Fortes; Nagarkatti, Rana; Gupta, Charu; Marino, Ana Paula; Debrabant, Alain


    Drug discovery initiatives, aimed at Chagas treatment, have been hampered by the lack of standardized drug screening protocols and the absence of simple pre-clinical assays to evaluate treatment efficacy in animal models. In this study, we used a simple Enzyme Linked Aptamer (ELA) assay to detect T. cruzi biomarker in blood and validate murine drug discovery models of Chagas disease. In two mice models, Apt-29 ELA assay demonstrated that biomarker levels were significantly higher in the infected group compared to the control group, and upon Benznidazole treatment, their levels reduced. However, biomarker levels in the infected treated group did not reduce to those seen in the non-infected treated group, with 100% of the mice above the assay cutoff, suggesting that parasitemia was reduced but cure was not achieved. The ELA assay was capable of detecting circulating biomarkers in mice infected with various strains of T. cruzi parasites. Our results showed that the ELA assay could detect residual parasitemia in treated mice by providing an overall picture of the infection in the host. They suggest that the ELA assay can be used in drug discovery applications to assess treatment efficacy in-vivo.

  8. Statistical considerations of optimal study design for human plasma proteomics and biomarker discovery. (United States)

    Zhou, Cong; Simpson, Kathryn L; Lancashire, Lee J; Walker, Michael J; Dawson, Martin J; Unwin, Richard D; Rembielak, Agata; Price, Patricia; West, Catharine; Dive, Caroline; Whetton, Anthony D


    A mass spectrometry-based plasma biomarker discovery workflow was developed to facilitate biomarker discovery. Plasma from either healthy volunteers or patients with pancreatic cancer was 8-plex iTRAQ labeled, fractionated by 2-dimensional reversed phase chromatography and subjected to MALDI ToF/ToF mass spectrometry. Data were processed using a q-value based statistical approach to maximize protein quantification and identification. Technical (between duplicate samples) and biological variance (between and within individuals) were calculated and power analysis was thereby enabled. An a priori power analysis was carried out using samples from healthy volunteers to define sample sizes required for robust biomarker identification. The result was subsequently validated with a post hoc power analysis using a real clinical setting involving pancreatic cancer patients. This demonstrated that six samples per group (e.g., pre- vs post-treatment) may provide sufficient statistical power for most proteins with changes>2 fold. A reference standard allowed direct comparison of protein expression changes between multiple experiments. Analysis of patient plasma prior to treatment identified 29 proteins with significant changes within individual patient. Changes in Peroxiredoxin II levels were confirmed by Western blot. This q-value based statistical approach in combination with reference standard samples can be applied with confidence in the design and execution of clinical studies for predictive, prognostic, and/or pharmacodynamic biomarker discovery. The power analysis provides information required prior to study initiation.

  9. A TMA de-arraying method for high throughput biomarker discovery in tissue research.

    Directory of Open Access Journals (Sweden)

    Yinhai Wang

    Full Text Available BACKGROUND: Tissue MicroArrays (TMAs represent a potential high-throughput platform for the analysis and discovery of tissue biomarkers. As TMA slides are produced manually and subject to processing and sectioning artefacts, the layout of TMA cores on the final slide and subsequent digital scan (TMA digital slide is often disturbed making it difficult to associate cores with their original position in the planned TMA map. Additionally, the individual cores can be greatly altered and contain numerous irregularities such as missing cores, grid rotation and stretching. These factors demand the development of a robust method for de-arraying TMAs which identifies each TMA core, and assigns them to their appropriate coordinates on the constructed TMA slide. METHODOLOGY: This study presents a robust TMA de-arraying method consisting of three functional phases: TMA core segmentation, gridding and mapping. The segmentation of TMA cores uses a set of morphological operations to identify each TMA core. Gridding then utilises a Delaunay Triangulation based method to find the row and column indices of each TMA core. Finally, mapping correlates each TMA core from a high resolution TMA whole slide image with its name within a TMAMap. CONCLUSION: This study describes a genuine robust TMA de-arraying algorithm for the rapid identification of TMA cores from digital slides. The result of this de-arraying algorithm allows the easy partition of each TMA core for further processing. Based on a test group of 19 TMA slides (3129 cores, 99.84% of cores were segmented successfully, 99.81% of cores were gridded correctly and 99.96% of cores were mapped with their correct names via TMAMaps. The gridding of TMA cores were also extensively tested using a set of 113 pseudo slide (13,536 cores with a variety of irregular grid layouts including missing cores, rotation and stretching. 100% of the cores were gridded correctly.

  10. Emerging concepts in biomarker discovery; The US-Japan workshop on immunological molecular markers in oncology

    Directory of Open Access Journals (Sweden)

    Rivoltini Licia


    Full Text Available Abstract Supported by the Office of International Affairs, National Cancer Institute (NCI, the "US-Japan Workshop on Immunological Biomarkers in Oncology" was held in March 2009. The workshop was related to a task force launched by the International Society for the Biological Therapy of Cancer (iSBTc and the United States Food and Drug Administration (FDA to identify strategies for biomarker discovery and validation in the field of biotherapy. The effort will culminate on October 28th 2009 in the "iSBTc-FDA-NCI Workshop on Prognostic and Predictive Immunologic Biomarkers in Cancer", which will be held in Washington DC in association with the Annual Meeting. The purposes of the US-Japan workshop were a to discuss novel approaches to enhance the discovery of predictive and/or prognostic markers in cancer immunotherapy; b to define the state of the science in biomarker discovery and validation. The participation of Japanese and US scientists provided the opportunity to identify shared or discordant themes across the distinct immune genetic background and the diverse prevalence of disease between the two Nations. Converging concepts were identified: enhanced knowledge of interferon-related pathways was found to be central to the understanding of immune-mediated tissue-specific destruction (TSD of which tumor rejection is a representative facet. Although the expression of interferon-stimulated genes (ISGs likely mediates the inflammatory process leading to tumor rejection, it is insufficient by itself and the associated mechanisms need to be identified. It is likely that adaptive immune responses play a broader role in tumor rejection than those strictly related to their antigen-specificity; likely, their primary role is to trigger an acute and tissue-specific inflammatory response at the tumor site that leads to rejection upon recruitment of additional innate and adaptive immune mechanisms. Other candidate systemic and/or tissue-specific biomarkers

  11. Emerging concepts in biomarker discovery; the US-Japan Workshop on Immunological Molecular Markers in Oncology. (United States)

    Tahara, Hideaki; Sato, Marimo; Thurin, Magdalena; Wang, Ena; Butterfield, Lisa H; Disis, Mary L; Fox, Bernard A; Lee, Peter P; Khleif, Samir N; Wigginton, Jon M; Ambs, Stefan; Akutsu, Yasunori; Chaussabel, Damien; Doki, Yuichiro; Eremin, Oleg; Fridman, Wolf Hervé; Hirohashi, Yoshihiko; Imai, Kohzoh; Jacobson, James; Jinushi, Masahisa; Kanamoto, Akira; Kashani-Sabet, Mohammed; Kato, Kazunori; Kawakami, Yutaka; Kirkwood, John M; Kleen, Thomas O; Lehmann, Paul V; Liotta, Lance; Lotze, Michael T; Maio, Michele; Malyguine, Anatoli; Masucci, Giuseppe; Matsubara, Hisahiro; Mayrand-Chung, Shawmarie; Nakamura, Kiminori; Nishikawa, Hiroyoshi; Palucka, A Karolina; Petricoin, Emanuel F; Pos, Zoltan; Ribas, Antoni; Rivoltini, Licia; Sato, Noriyuki; Shiku, Hiroshi; Slingluff, Craig L; Streicher, Howard; Stroncek, David F; Takeuchi, Hiroya; Toyota, Minoru; Wada, Hisashi; Wu, Xifeng; Wulfkuhle, Julia; Yaguchi, Tomonori; Zeskind, Benjamin; Zhao, Yingdong; Zocca, Mai-Britt; Marincola, Francesco M


    Supported by the Office of International Affairs, National Cancer Institute (NCI), the "US-Japan Workshop on Immunological Biomarkers in Oncology" was held in March 2009. The workshop was related to a task force launched by the International Society for the Biological Therapy of Cancer (iSBTc) and the United States Food and Drug Administration (FDA) to identify strategies for biomarker discovery and validation in the field of biotherapy. The effort will culminate on October 28th 2009 in the "iSBTc-FDA-NCI Workshop on Prognostic and Predictive Immunologic Biomarkers in Cancer", which will be held in Washington DC in association with the Annual Meeting. The purposes of the US-Japan workshop were a) to discuss novel approaches to enhance the discovery of predictive and/or prognostic markers in cancer immunotherapy; b) to define the state of the science in biomarker discovery and validation. The participation of Japanese and US scientists provided the opportunity to identify shared or discordant themes across the distinct immune genetic background and the diverse prevalence of disease between the two Nations. Converging concepts were identified: enhanced knowledge of interferon-related pathways was found to be central to the understanding of immune-mediated tissue-specific destruction (TSD) of which tumor rejection is a representative facet. Although the expression of interferon-stimulated genes (ISGs) likely mediates the inflammatory process leading to tumor rejection, it is insufficient by itself and the associated mechanisms need to be identified. It is likely that adaptive immune responses play a broader role in tumor rejection than those strictly related to their antigen-specificity; likely, their primary role is to trigger an acute and tissue-specific inflammatory response at the tumor site that leads to rejection upon recruitment of additional innate and adaptive immune mechanisms. Other candidate systemic and/or tissue-specific biomarkers were recognized that

  12. Intact-protein analysis system for discovery of serum-based disease biomarkers. (United States)

    Wang, Hong; Hanash, Samir


    Profiling of serum and plasma proteins has substantial relevance to the discovery of circulating disease biomarkers. However, the extreme complexity and vast dynamic range of protein abundance in serum and plasma present a formidable challenge for protein analysis. Thus, integration of multiple technologies is required to achieve high-resolution and high-sensitivity proteomic analysis of serum or plasma. In this chapter, we describe an orthogonal multidimensional intact-protein analysis system (IPAS) (Wang et al., Mol Cell Proteomics 4:618-625, 2005) coupled with protein tagging (Faca et al., J Proteome Res 5:2009-2018, 2006) to profile the serum and plasma proteomes quantitatively, which we have applied in our biomarker discovery studies (Katayama et al., Genome Med 1:47, 2009; Faca et al., PLoS Med 5:e123, 2008; Zhang et al. Genome Biol 9:R93, 2008).

  13. Discovery of sexual dimorphisms in metabolic and genetic biomarkers.

    Directory of Open Access Journals (Sweden)

    Kirstin Mittelstrass


    Full Text Available Metabolomic profiling and the integration of whole-genome genetic association data has proven to be a powerful tool to comprehensively explore gene regulatory networks and to investigate the effects of genetic variation at the molecular level. Serum metabolite concentrations allow a direct readout of biological processes, and association of specific metabolomic signatures with complex diseases such as Alzheimer's disease and cardiovascular and metabolic disorders has been shown. There are well-known correlations between sex and the incidence, prevalence, age of onset, symptoms, and severity of a disease, as well as the reaction to drugs. However, most of the studies published so far did not consider the role of sexual dimorphism and did not analyse their data stratified by gender. This study investigated sex-specific differences of serum metabolite concentrations and their underlying genetic determination. For discovery and replication we used more than 3,300 independent individuals from KORA F3 and F4 with metabolite measurements of 131 metabolites, including amino acids, phosphatidylcholines, sphingomyelins, acylcarnitines, and C6-sugars. A linear regression approach revealed significant concentration differences between males and females for 102 out of 131 metabolites (p-values<3.8×10(-4; Bonferroni-corrected threshold. Sex-specific genome-wide association studies (GWAS showed genome-wide significant differences in beta-estimates for SNPs in the CPS1 locus (carbamoyl-phosphate synthase 1, significance level: p<3.8×10(-10; Bonferroni-corrected threshold for glycine. We showed that the metabolite profiles of males and females are significantly different and, furthermore, that specific genetic variants in metabolism-related genes depict sexual dimorphism. Our study provides new important insights into sex-specific differences of cell regulatory processes and underscores that studies should consider sex-specific effects in design and

  14. Strategies for discovery and validation of methylated and hydroxymethylated DNA biomarkers. (United States)

    Olkhov-Mitsel, Ekaterina; Bapat, Bharati


    DNA methylation, consisting of the addition of a methyl group at the fifth-position of cytosine in a CpG dinucleotide, is one of the most well-studied epigenetic mechanisms in mammals with important functions in normal and disease biology. Disease-specific aberrant DNA methylation is a well-recognized hallmark of many complex diseases. Accordingly, various studies have focused on characterizing unique DNA methylation marks associated with distinct stages of disease development as they may serve as useful biomarkers for diagnosis, prognosis, prediction of response to therapy, or disease monitoring. Recently, novel CpG dinucleotide modifications with potential regulatory roles such as 5-hydroxymethylcytosine, 5-formylcytosine, and 5-carboxylcytosine have been described. These potential epigenetic marks cannot be distinguished from 5-methylcytosine by many current strategies and may potentially compromise assessment and interpretation of methylation data. A large number of strategies have been described for the discovery and validation of DNA methylation-based biomarkers, each with its own advantages and limitations. These strategies can be classified into three main categories: restriction enzyme digestion, affinity-based analysis, and bisulfite modification. In general, candidate biomarkers are discovered using large-scale, genome-wide, methylation sequencing, and/or microarray-based profiling strategies. Following discovery, biomarker performance is validated in large independent cohorts using highly targeted locus-specific assays. There are still many challenges to the effective implementation of DNA methylation-based biomarkers. Emerging innovative methylation and hydroxymethylation detection strategies are focused on addressing these gaps in the field of epigenetics. The development of DNA methylation- and hydroxymethylation-based biomarkers is an exciting and rapidly evolving area of research that holds promise for potential applications in diverse clinical

  15. Application of Glycoproteomics in the Discovery of Biomarkers for Lung Cancer (United States)

    Li, Qing Kay; Gabrielson, Edward; Zhang, Hui


    Lung cancer is the leading cause of cancer-related deaths in the United States. Approximately 40–60% of lung cancer patients present with locally advanced or metastatic disease at the time of diagnosis. In order to improve the survival rate of lung cancer patients, the discovery of early diagnostic and prognostic biomarkers is urgently needed. Lung cancer development and progression are a multistep process which is characterized by abnormal gene and protein expressions ultimately leading to phenotypic change. In lung cancer, the expression of cellular glycoproteins directly reflects the physiological and/or pathological status of the lung parenchyma. Glycoproteins have long been recognized to play fundamental roles in many physiological and pathological processes, particularly in cancer genesis and progression. Although numerous papers have already acknowledged the importance of the discovery of cancer biomarkers, the systemic study of glycoproteins in lung cancer using glycoproteomic approaches is still suboptimal. Herein, we review the recent technological development of glycoproteomics in highlighting their utility and limitations for the discovery of glycoprotein biomarkers in lung cancer. PMID:22641610

  16. Biomarker discovery by sparse canonical correlation analysis of complex clinical phenotypes of tuberculosis and malaria.

    Directory of Open Access Journals (Sweden)

    Juho Rousu


    Full Text Available Biomarker discovery aims to find small subsets of relevant variables in 'omics data that correlate with the clinical syndromes of interest. Despite the fact that clinical phenotypes are usually characterized by a complex set of clinical parameters, current computational approaches assume univariate targets, e.g. diagnostic classes, against which associations are sought for. We propose an approach based on asymmetrical sparse canonical correlation analysis (SCCA that finds multivariate correlations between the 'omics measurements and the complex clinical phenotypes. We correlated plasma proteomics data to multivariate overlapping complex clinical phenotypes from tuberculosis and malaria datasets. We discovered relevant 'omic biomarkers that have a high correlation to profiles of clinical measurements and are remarkably sparse, containing 1.5-3% of all 'omic variables. We show that using clinical view projections we obtain remarkable improvements in diagnostic class prediction, up to 11% in tuberculosis and up to 5% in malaria. Our approach finds proteomic-biomarkers that correlate with complex combinations of clinical-biomarkers. Using the clinical-biomarkers improves the accuracy of diagnostic class prediction while not requiring the measurement plasma proteomic profiles of each subject. Our approach makes it feasible to use omics' data to build accurate diagnostic algorithms that can be deployed to community health centres lacking the expensive 'omics measurement capabilities.

  17. A mouse informatics platform for phenotypic and translational discovery. (United States)

    Ring, Natalie; Meehan, Terrence F; Blake, Andrew; Brown, James; Chen, Chao-Kung; Conte, Nathalie; Di Fenza, Armida; Fiegel, Tanja; Horner, Neil; Jacobsen, Julius O B; Karp, Natasha; Lawson, Thomas; Mason, Jeremy C; Matthews, Peter; Morgan, Hugh; Relac, Mike; Santos, Luis; Smedley, Damian; Sneddon, Duncan; Pengelly, Alice; Tudose, Ilinca; Warren, Jonathan W G; Westerberg, Henrik; Yaikhom, Gagarine; Parkinson, Helen; Mallon, Ann-Marie


    The International Mouse Phenotyping Consortium (IMPC) is providing the world's first functional catalogue of a mammalian genome by characterising a knockout mouse strain for every gene. A robust and highly structured informatics platform has been developed to systematically collate, analyse and disseminate the data produced by the IMPC. As the first phase of the project, in which 5000 new knockout strains are being broadly phenotyped, nears completion, the informatics platform is extending and adapting to support the increasing volume and complexity of the data produced as well as addressing a large volume of users and emerging user groups. An intuitive interface helps researchers explore IMPC data by giving overviews and the ability to find and visualise data that support a phenotype assertion. Dedicated disease pages allow researchers to find new mouse models of human diseases, and novel viewers provide high-resolution images of embryonic and adult dysmorphologies. With each monthly release, the informatics platform will continue to evolve to support the increased data volume and to maintain its position as the primary route of access to IMPC data and as an invaluable resource for clinical and non-clinical researchers.

  18. Comprehensive serum profiling for the discovery of epithelial ovarian cancer biomarkers.

    Directory of Open Access Journals (Sweden)

    Ping Yip

    Full Text Available FDA-cleared ovarian cancer biomarkers are limited to CA-125 and HE4 for monitoring and recurrence and OVA1, a multivariate panel consisting of CA-125 and four additional biomarkers, for referring patients to a specialist. Due to relatively poor performance of these tests, more accurate and broadly applicable biomarkers are needed. We evaluated the dysregulation of 259 candidate cancer markers in serum samples from 499 patients. Sera were collected prospectively at 11 monitored sites under a single well-defined protocol. All stages of ovarian cancer and common benign gynecological conditions were represented. To ensure consistency and comparability of biomarker comparisons, all measurements were performed on a single platform, at a single site, using a panel of rigorously calibrated, qualified, high-throughput, multiplexed immunoassays and all analyses were conducted using the same software. Each marker was evaluated independently for its ability to differentiate ovarian cancer from benign conditions. A total of 175 markers were dysregulated in the cancer samples. HE4 (AUC=0.933 and CA-125 (AUC=0.907 were the most informative biomarkers, followed by IL-2 receptor α, α1-antitrypsin, C-reactive protein, YKL-40, cellular fibronectin, CA-72-4 and prostasin (AUC>0.800. To improve the discrimination between cancer and benign conditions, a simple multivariate combination of markers was explored using logistic regression. When combined into a single panel, the nine most informative individual biomarkers yielded an AUC value of 0.950, significantly higher than obtained when combining the markers in the OVA1 panel (AUC 0.912. Additionally, at a threshold sensitivity of 90%, the combination of the top 9 markers gave 88.9% specificity compared to 63.4% specificity for the OVA1 markers. Although a blinded validation study has not yet been performed, these results indicate that alternative biomarker combinations might lead to significant improvements in the

  19. The Matchmaker Exchange: a platform for rare disease gene discovery. (United States)

    Philippakis, Anthony A; Azzariti, Danielle R; Beltran, Sergi; Brookes, Anthony J; Brownstein, Catherine A; Brudno, Michael; Brunner, Han G; Buske, Orion J; Carey, Knox; Doll, Cassie; Dumitriu, Sergiu; Dyke, Stephanie O M; den Dunnen, Johan T; Firth, Helen V; Gibbs, Richard A; Girdea, Marta; Gonzalez, Michael; Haendel, Melissa A; Hamosh, Ada; Holm, Ingrid A; Huang, Lijia; Hurles, Matthew E; Hutton, Ben; Krier, Joel B; Misyura, Andriy; Mungall, Christopher J; Paschall, Justin; Paten, Benedict; Robinson, Peter N; Schiettecatte, François; Sobreira, Nara L; Swaminathan, Ganesh J; Taschner, Peter E; Terry, Sharon F; Washington, Nicole L; Züchner, Stephan; Boycott, Kym M; Rehm, Heidi L


    There are few better examples of the need for data sharing than in the rare disease community, where patients, physicians, and researchers must search for "the needle in a haystack" to uncover rare, novel causes of disease within the genome. Impeding the pace of discovery has been the existence of many small siloed datasets within individual research or clinical laboratory databases and/or disease-specific organizations, hoping for serendipitous occasions when two distant investigators happen to learn they have a rare phenotype in common and can "match" these cases to build evidence for causality. However, serendipity has never proven to be a reliable or scalable approach in science. As such, the Matchmaker Exchange (MME) was launched to provide a robust and systematic approach to rare disease gene discovery through the creation of a federated network connecting databases of genotypes and rare phenotypes using a common application programming interface (API). The core building blocks of the MME have been defined and assembled. Three MME services have now been connected through the API and are available for community use. Additional databases that support internal matching are anticipated to join the MME network as it continues to grow.

  20. Morph-X-Select: Morphology-based tissue aptamer selection for ovarian cancer biomarker discovery (United States)

    Wang, Hongyu; Li, Xin; Volk, David E.; Lokesh, Ganesh L.-R.; Elizondo-Riojas, Miguel-Angel; Li, Li; Nick, Alpa M.; Sood, Anil K.; Rosenblatt, Kevin P.; Gorenstein, David G.


    High affinity aptamer-based biomarker discovery has the advantage of simultaneously discovering an aptamer affinity reagent and its target biomarker protein. Here, we demonstrate a morphology-based tissue aptamer selection method that enables us to use tissue sections from individual patients and identify high-affinity aptamers and their associated target proteins in a systematic and accurate way. We created a combinatorial DNA aptamer library that has been modified with thiophosphate substitutions of the phosphate ester backbone at selected 5′dA positions for enhanced nuclease resistance and targeting. Based on morphological assessment, we used image-directed laser microdissection (LMD) to dissect regions of interest bound with the thioaptamer (TA) library and further identified target proteins for the selected TAs. We have successfully identified and characterized the lead candidate TA, V5, as a vimentin-specific sequence that has shown specific binding to tumor vasculature of human ovarian tissue and human microvascular endothelial cells. This new Morph-X-Select method allows us to select high-affinity aptamers and their associated target proteins in a specific and accurate way, and could be used for personalized biomarker discovery to improve medical decision-making and to facilitate the development of targeted therapies to achieve more favorable outcomes. PMID:27839510

  1. Microfluidic-Based Multi-Organ Platforms for Drug Discovery

    Directory of Open Access Journals (Sweden)

    Ahmad Rezaei Kolahchi


    Full Text Available Development of predictive multi-organ models before implementing costly clinical trials is central for screening the toxicity, efficacy, and side effects of new therapeutic agents. Despite significant efforts that have been recently made to develop biomimetic in vitro tissue models, the clinical application of such platforms is still far from reality. Recent advances in physiologically-based pharmacokinetic and pharmacodynamic (PBPK-PD modeling, micro- and nanotechnology, and in silico modeling have enabled single- and multi-organ platforms for investigation of new chemical agents and tissue-tissue interactions. This review provides an overview of the principles of designing microfluidic-based organ-on-chip models for drug testing and highlights current state-of-the-art in developing predictive multi-organ models for studying the cross-talk of interconnected organs. We further discuss the challenges associated with establishing a predictive body-on-chip (BOC model such as the scaling, cell types, the common medium, and principles of the study design for characterizing the interaction of drugs with multiple targets.

  2. MetaCoMET: a web platform for discovery and visualization of the core microbiome (United States)

    A key component of the analysis of microbiome datasets is the identification of OTUs shared between multiple experimental conditions, commonly referred to as the core microbiome. Results: We present a web platform named MetaCoMET that enables the discovery and visualization of the core microbiome an...

  3. Predictive biomarker discovery through the parallel integration of clinical trial and functional genomics datasets

    DEFF Research Database (Denmark)

    Swanton, C.; Larkin, J.M.; Gerlinger, M.


    RNA screens to identify and validate functionally important genomic or transcriptomic predictive biomarkers of individual drug response in patients. PREDICT's approach to predictive biomarker discovery differs from conventional associative learning approaches, which can be susceptible to the detection...... inhibitor. Through the analysis of tumour tissue derived from pre-operative renal cell carcinoma (RCC) clinical trials, the PREDICT consortium will use established and novel methods to integrate comprehensive tumour-derived genomic data with personalised tumour-derived shRNA and high throughput si......, reducing ineffective therapy in drug resistant disease, leading to improved quality of life and higher cost efficiency, which in turn should broaden patient access to beneficial therapeutics, thereby enhancing clinical outcome and cancer survival. The consortium will also establish and consolidate...

  4. Urinary Proteomics Pilot Study for Biomarker Discovery and Diagnosis in Heart Failure with Reduced Ejection Fraction.

    Directory of Open Access Journals (Sweden)

    Kasper Rossing

    Full Text Available Biomarker discovery and new insights into the pathophysiology of heart failure with reduced ejection fraction (HFrEF may emerge from recent advances in high-throughput urinary proteomics. This could lead to improved diagnosis, risk stratification and management of HFrEF.Urine samples were analyzed by on-line capillary electrophoresis coupled to electrospray ionization micro time-of-flight mass spectrometry (CE-MS to generate individual urinary proteome profiles. In an initial biomarker discovery cohort, analysis of urinary proteome profiles from 33 HFrEF patients and 29 age- and sex-matched individuals without HFrEF resulted in identification of 103 peptides that were significantly differentially excreted in HFrEF. These 103 peptides were used to establish the support vector machine-based HFrEF classifier HFrEF103. In a subsequent validation cohort, HFrEF103 very accurately (area under the curve, AUC = 0.972 discriminated between HFrEF patients (N = 94, sensitivity = 93.6% and control individuals with and without impaired renal function and hypertension (N = 552, specificity = 92.9%. Interestingly, HFrEF103 showed low sensitivity (12.6% in individuals with diastolic left ventricular dysfunction (N = 176. The HFrEF-related peptide biomarkers mainly included fragments of fibrillar type I and III collagen but also, e.g., of fibrinogen beta and alpha-1-antitrypsin.CE-MS based urine proteome analysis served as a sensitive tool to determine a vast array of HFrEF-related urinary peptide biomarkers which might help improving our understanding and diagnosis of heart failure.

  5. Biomarker discovery for ovine paratuberculosis (Johne's disease) by proteomic serum profiling. (United States)

    Zhong, L; Taylor, D; Begg, D J; Whittington, R J


    Paratuberculosis (Johne's disease) is a chronic granulomatous enteritis affecting ruminants and other species. It is caused by Mycobacterium avium subsp. paratuberculosis (MAP). In this study, surface enhanced laser desorption ionization time-of-flight mass spectrometry (SELDI TOF-MS) was used as a platform to identify candidate biomarkers from sheep serum. Multivariate biomarker models which aimed to differentiate sheep with paratuberculosis and vaccinated-exposed sheep from unexposed animals were proposed based on classification and regression tree (CART) and linear discriminant analysis (LDA) algorithms from two array types. The accuracy of classification of sheep into unexposed or exposed groups ranged from 75 to 100% among models. SELDI was used to monitor protein profile changes over time during an experimental infection trial by examining sera collected at 4-, 8- and 13-months post infection. Although three different SELDI instruments were used, nine consistent proteomic features were observed associated with exposure to MAP. Two of the putative serum biomarkers were purified from serum using chromatographic methods and were identified as transthyretin and alpha haemoglobin by tandem mass spectrometry. They belong to highly abundant, acute phase reactants in the serum proteome and have also been discovered as serum biomarkers in human inflammatory conditions and cancer. Their relationship to the pathogenesis of Johne's disease remains to be elucidated.

  6. Open for collaboration: an academic platform for drug discovery and development at SciLifeLab. (United States)

    Arvidsson, Per I; Sandberg, Kristian; Forsberg-Nilsson, Karin


    The Science for Life Laboratory Drug Discovery and Development (SciLifeLab DDD) platform reaches out to Swedish academia with an industry-standard infrastructure for academic drug discovery, supported by earmarked funds from the Swedish government. In this review, we describe the build-up and operation of the platform, and reflect on our first two years of operation, with the ambition to share learnings and best practice with academic drug discovery centers globally. We also discuss how the Swedish Teacher Exemption Law, an internationally unique aspect of the innovation system, has shaped the operation. Furthermore, we address how this investment in infrastructure and expertise can be utilized to facilitate international collaboration between academia and industry in the best interest of those ultimately benefiting the most from translational pharmaceutical research - the patients.

  7. Reproducible cancer biomarker discovery in SELDI-TOF MS using different pre-processing algorithms.

    Directory of Open Access Journals (Sweden)

    Jinfeng Zou

    Full Text Available BACKGROUND: There has been much interest in differentiating diseased and normal samples using biomarkers derived from mass spectrometry (MS studies. However, biomarker identification for specific diseases has been hindered by irreproducibility. Specifically, a peak profile extracted from a dataset for biomarker identification depends on a data pre-processing algorithm. Until now, no widely accepted agreement has been reached. RESULTS: In this paper, we investigated the consistency of biomarker identification using differentially expressed (DE peaks from peak profiles produced by three widely used average spectrum-dependent pre-processing algorithms based on SELDI-TOF MS data for prostate and breast cancers. Our results revealed two important factors that affect the consistency of DE peak identification using different algorithms. One factor is that some DE peaks selected from one peak profile were not detected as peaks in other profiles, and the second factor is that the statistical power of identifying DE peaks in large peak profiles with many peaks may be low due to the large scale of the tests and small number of samples. Furthermore, we demonstrated that the DE peak detection power in large profiles could be improved by the stratified false discovery rate (FDR control approach and that the reproducibility of DE peak detection could thereby be increased. CONCLUSIONS: Comparing and evaluating pre-processing algorithms in terms of reproducibility can elucidate the relationship among different algorithms and also help in selecting a pre-processing algorithm. The DE peaks selected from small peak profiles with few peaks for a dataset tend to be reproducibly detected in large peak profiles, which suggests that a suitable pre-processing algorithm should be able to produce peaks sufficient for identifying useful and reproducible biomarkers.

  8. Indications of success: Strategies for utilizing neuroimaging biomarkers in CNS drug discovery and development: CINP/JSNP working group report. (United States)

    Suhara, Tetsuya; Chaki, Shigeyuki; Kimura, Haruhide; Furusawa, Makoto; Matsumoto, Mitsuyuki; Ogura, Hiroo; Negishi, Takaaki; Saijo, Takeaki; Higuchi, Makoto; Omura, Tomohiro; Watanabe, Rira; Miyoshi, Sosuke; Nakatani, Noriaki; Yamamoto, Noboru; Liou, Shyh-Yuh; Takado, Yuhei; Maeda, Jun; Okamoto, Yasumasa; Okubo, Yoshiaki; Yamada, Makiko; Ito, Hiroshi; Walton, Noah M; Yamawaki, Shigeto


    Despite large unmet medical needs in the field for several decades, central nervous system (CNS) drug discovery and development has been largely unsuccessful. Biomarkers, particularly those utilizing neuroimaging, have played important roles in aiding CNS drug development, including dosing determination of investigational new drugs (INDs). The utility of biomarkers as tools to overcome issues of CNS drug development is the subject for this review.In this review aimed at employing biomarkers as tools to overcome issues surrounding CNS drug development, we first analyzed problems in utilizing biomarkers in processes of drug discovery and development for CNS disorders. Based on this analysis, we propose a new paradigm containing five distinct tiers to further clarify the use of biomarkers and establish new strategies for decision-making in the context of clinical drug development. Specifically, we discuss more rational ways to determine optimal dose for INDs with novel mechanisms and targets, and propose additional categorization criteria to further the use of biomarkers in patient stratification and efficacy prediction. Finally, we propose validation and development of new neuroimaging biomarkers through Public-Private-Partnerships to realize rational and successful drug discovery and development for CNS disorders.

  9. Enabling Metabolomics Based Biomarker Discovery Studies Using Molecular Phenotyping of Exosome-Like Vesicles.

    Directory of Open Access Journals (Sweden)

    Tatiana Altadill

    Full Text Available Identification of sensitive and specific biomarkers with clinical and translational utility will require smart experimental strategies that would augment expanding the breadth and depth of molecular measurements within the constraints of currently available technologies. Exosomes represent an information rich matrix to discern novel disease mechanisms that are thought to contribute to pathologies such as dementia and cancer. Although proteomics and transcriptomic studies have been reported using Exosomes-Like Vesicles (ELVs from different sources, exosomal metabolome characterization and its modulation in health and disease remains to be elucidated. Here we describe methodologies for UPLC-ESI-MS based small molecule profiling of ELVs from human plasma and cell culture media. In this study, we present evidence that indeed ELVs carry a rich metabolome that could not only augment the discovery of low abundance biomarkers but may also help explain the molecular basis of disease progression. This approach could be easily translated to other studies seeking to develop predictive biomarkers that can subsequently be used with simplified targeted approaches.

  10. Biomarker discovery and applications for foods and beverages: proteomics to nanoproteomics. (United States)

    Agrawal, Ganesh Kumar; Timperio, Anna Maria; Zolla, Lello; Bansal, Vipul; Shukla, Ravi; Rakwal, Randeep


    Foods and beverages have been at the heart of our society for centuries, sustaining humankind - health, life, and the pleasures that go with it. The more we grow and develop as a civilization, the more we feel the need to know about the food we eat and beverages we drink. Moreover, with an ever increasing demand for food due to the growing human population food security remains a major concern. Food safety is another growing concern as the consumers prefer varied foods and beverages that are not only traded nationally but also globally. The 21st century science and technology is at a new high, especially in the field of biological sciences. The availability of genome sequences and associated high-throughput sensitive technologies means that foods are being analyzed at various levels. For example and in particular, high-throughput omics approaches are being applied to develop suitable biomarkers for foods and beverages and their applications in addressing quality, technology, authenticity, and safety issues. Proteomics are one of those technologies that are increasingly being utilized to profile expressed proteins in different foods and beverages. Acquired knowledge and protein information have now been translated to address safety of foods and beverages. Very recently, the power of proteomic technology has been integrated with another highly sensitive and miniaturized technology called nanotechnology, yielding a new term nanoproteomics. Nanoproteomics offer a real-time multiplexed analysis performed in a miniaturized assay, with low-sample consumption and high sensitivity. To name a few, nanomaterials - quantum dots, gold nanoparticles, carbon nanotubes, and nanowires - have demonstrated potential to overcome the challenges of sensitivity faced by proteomics for biomarker detection, discovery, and application. In this review, we will discuss the importance of biomarker discovery and applications for foods and beverages, the contribution of proteomic technology in

  11. Top-down proteomics with mass spectrometry imaging: a pilot study towards discovery of biomarkers for neurodevelopmental disorders.

    Directory of Open Access Journals (Sweden)

    Hui Ye

    Full Text Available In the developing mammalian brain, inhibition of NMDA receptor can induce widespread neuroapoptosis, inhibit neurogenesis and cause impairment of learning and memory. Although some mechanistic insights into adverse neurological actions of these NMDA receptor antagonists exist, our understanding of the full spectrum of developmental events affected by early exposure to these chemical agents in the brain is still limited. Here we attempt to gain insights into the impact of pharmacologically induced excitatory/inhibitory imbalance in infancy on the brain proteome using mass spectrometric imaging (MSI. Our goal was to study changes in protein expression in postnatal day 10 (P10 rat brains following neonatal exposure to the NMDA receptor antagonist dizocilpine (MK801. Analysis of rat brains exposed to vehicle or MK801 and comparison of their MALDI MS images revealed differential relative abundances of several proteins. We then identified these markers such as ubiquitin, purkinje cell protein 4 (PEP-19, cytochrome c oxidase subunits and calmodulin, by a combination of reversed-phase (RP HPLC fractionation and top-down tandem MS platform. More in-depth large scale study along with validation experiments will be carried out in the future. Overall, our findings indicate that a brief neonatal exposure to a compound that alters excitatory/inhibitory balance in the brain has a long term effect on protein expression patterns during subsequent development, highlighting the utility of MALDI-MSI as a discovery tool for potential biomarkers.

  12. Discovery of serum biomarkers predicting development of a subsequent depressive episode in social anxiety disorder. (United States)

    Gottschalk, M G; Cooper, J D; Chan, M K; Bot, M; Penninx, B W J H; Bahn, S


    Although social anxiety disorder (SAD) is strongly associated with the subsequent development of a depressive disorder (major depressive disorder or dysthymia), no underlying biological risk factors are known. We aimed to identify biomarkers which predict depressive episodes in SAD patients over a 2-year follow-up period. One hundred sixty-five multiplexed immunoassay analytes were investigated in blood serum of 143 SAD patients without co-morbid depressive disorders, recruited within the Netherlands Study of Depression and Anxiety (NESDA). Predictive performance of identified biomarkers, clinical variables and self-report inventories was assessed using receiver operating characteristics curves (ROC) and represented by the area under the ROC curve (AUC). Stepwise logistic regression resulted in the selection of four serum analytes (AXL receptor tyrosine kinase, vascular cell adhesion molecule 1, vitronectin, collagen IV) and four additional variables (Inventory of Depressive Symptomatology, Beck Anxiety Inventory somatic subscale, depressive disorder lifetime diagnosis, BMI) as optimal set of patient parameters. When combined, an AUC of 0.86 was achieved for the identification of SAD individuals who later developed a depressive disorder. Throughout our analyses, biomarkers yielded superior discriminative performance compared to clinical variables and self-report inventories alone. We report the discovery of a serum marker panel with good predictive performance to identify SAD individuals prone to develop subsequent depressive episodes in a naturalistic cohort design. Furthermore, we emphasise the importance to combine biological markers, clinical variables and self-report inventories for disease course predictions in psychiatry. Following replication in independent cohorts, validated biomarkers could help to identify SAD patients at risk of developing a depressive disorder, thus facilitating early intervention.

  13. A comparison of methods for data-driven cancer outlier discovery, and an application scheme to semisupervised predictive biomarker discovery. (United States)

    Karrila, Seppo; Lee, Julian Hock Ean; Tucker-Kellogg, Greg


    A core component in translational cancer research is biomarker discovery using gene expression profiling for clinical tumors. This is often based on cell line experiments; one population is sampled for inference in another. We disclose a semisupervised workflow focusing on binary (switch-like, bimodal) informative genes that are likely cancer relevant, to mitigate this non-statistical problem. Outlier detection is a key enabling technology of the workflow, and aids in identifying the focus genes.We compare outlier detection techniques MOST, LSOSS, COPA, ORT, OS, and t-test, using a publicly available NSCLC dataset. Removing genes with Gaussian distribution is computationally efficient and matches MOST particularly well, while also COPA and OS pick prognostically relevant genes in their top ranks. Also our stability assessment is in favour of both MOST and COPA; the latter does not pair well with prefiltering for non-Gaussianity, but can handle data sets lacking non-cancer cases.We provide R code for replicating our approach or extending it.

  14. Probing the O-glycoproteome of Gastric Cancer Cell Lines for Biomarker Discovery

    DEFF Research Database (Denmark)

    Vieira Campos, Diana Alexandra; Freitas, Daniela; Gomes, Joana


    biomarker assays. However, the current knowledge of secreted and circulating O-glycoproteins is limited. Here, we used the COSMC KO "SimpleCell" (SC) strategy to characterize the O-glycoproteome of two gastric cancer SC lines (AGS, MKN45) as well as a gastric cell line (KATO III) which naturally expresses...... at least partially truncated O-glycans. Overall we identified 499 O-glycoproteins and 1,236 O-glycosites in gastric cancer SCs, and a total 47 O-glycoproteins and 73 O-glycosites in the KATO III cell line. We next modified the glycoproteomic strategy to apply it to pools of sera from gastric cancer...... with the STn glycoform were further validated as being expressed in gastric cancer tissue. A proximity ligation assay was used to demonstrate that CD44 was expressed with the STn glycoform in gastric cancer tissues. The study provides a discovery strategy for aberrantly glycosylated O-glycoproteins and a set...

  15. Targeted proteomics by selected reaction monitoring mass spectrometry: applications to systems biology and biomarker discovery. (United States)

    Elschenbroich, Sarah; Kislinger, Thomas


    Mass Spectrometry-based proteomics is now considered a relatively established strategy for protein analysis, ranging from global expression profiling to the identification of protein complexes and specific post-translational modifications. Recently, Selected Reaction Monitoring Mass Spectrometry (SRM-MS) has become increasingly popular in proteome research for the targeted quantification of proteins and post-translational modifications. Using triple quadrupole instrumentation (QqQ), specific analyte molecules are targeted in a data-directed mode. Used routinely for the quantitative analysis of small molecular compounds for at least three decades, the technology is now experiencing broadened application in the proteomics community. In the current review, we will provide a detailed summary of current developments in targeted proteomics, including some of the recent applications to biological research and biomarker discovery.

  16. Compact cancer biomarkers discovery using a swarm intelligence feature selection algorithm. (United States)

    Martinez, Emmanuel; Alvarez, Mario Moises; Trevino, Victor


    Biomarker discovery is a typical application from functional genomics. Due to the large number of genes studied simultaneously in microarray data, feature selection is a key step. Swarm intelligence has emerged as a solution for the feature selection problem. However, swarm intelligence settings for feature selection fail to select small features subsets. We have proposed a swarm intelligence feature selection algorithm based on the initialization and update of only a subset of particles in the swarm. In this study, we tested our algorithm in 11 microarray datasets for brain, leukemia, lung, prostate, and others. We show that the proposed swarm intelligence algorithm successfully increase the classification accuracy and decrease the number of selected features compared to other swarm intelligence methods.

  17. An integrated approach to blood-based cancer diagnosis and biomarker discovery. (United States)

    Min, Martin Renqiang; Chowdhury, Salim; Qi, Yanjun; Stewart, Alex; Ostroff, Rachel


    Disrupted or abnormal biological processes responsible for cancers often quantitatively manifest as disrupted additive and multiplicative interactions of gene/protein expressions correlating with cancer progression. However, the examination of all possible combinatorial interactions between gene features in most case-control studies with limited training data is computationally infeasible. In this paper, we propose a practically feasible data integration approach, QUIRE (QUadratic Interactions among infoRmative fEatures), to identify discriminative complex interactions among informative gene features for cancer diagnosis and biomarker discovery directly based on patient blood samples. QUIRE works in two stages, where it first identifies functionally relevant gene groups for the disease with the help of gene functional annotations and available physical protein interactions, then it explores the combinatorial relationships among the genes from the selected informative groups. Based on our private experimentally generated data from patient blood samples using a novel SOMAmer (Slow Off-rate Modified Aptamer) technology, we apply QUIRE to cancer diagnosis and biomarker discovery for Renal Cell Carcinoma (RCC) and Ovarian Cancer (OVC). To further demonstrate the general applicability of our approach, we also apply QUIRE to a publicly available Colorectal Cancer (CRC) dataset that can be used to prioritize our SOMAmer design. Our experimental results show that QUIRE identifies gene-gene interactions that can better identify the different cancer stages of samples, as compared to other state-of-the-art feature selection methods. A literature survey shows that many of the interactions identified by QUIRE play important roles in the development of cancer.

  18. Application in pesticide analysis: Liquid chromatography - A review of the state of science for biomarker discovery and identification (United States)

    Book Chapter 18, titled Application in pesticide analysis: Liquid chromatography - A review of the state of science for biomarker discovery and identification, will be published in the book titled High Performance Liquid Chromatography in Pesticide Residue Analysis (Part of the C...

  19. Translating discovery in zebrafish pancreatic development to human pancreatic cancer: biomarkers, targets, pathogenesis, and therapeutics. (United States)

    Yee, Nelson S; Kazi, Abid A; Yee, Rosemary K


    Abstract Experimental studies in the zebrafish have greatly facilitated understanding of genetic regulation of the early developmental events in the pancreas. Various approaches using forward and reverse genetics, chemical genetics, and transgenesis in zebrafish have demonstrated generally conserved regulatory roles of mammalian genes and discovered novel genetic pathways in exocrine pancreatic development. Accumulating evidence has supported the use of zebrafish as a model of human malignant diseases, including pancreatic cancer. Studies have shown that the genetic regulators of exocrine pancreatic development in zebrafish can be translated into potential clinical biomarkers and therapeutic targets in human pancreatic adenocarcinoma. Transgenic zebrafish expressing oncogenic K-ras and zebrafish tumor xenograft model have emerged as valuable tools for dissecting the pathogenetic mechanisms of pancreatic cancer and for drug discovery and toxicology. Future analysis of the pancreas in zebrafish will continue to advance understanding of the genetic regulation and biological mechanisms during organogenesis. Results of those studies are expected to provide new insights into how aberrant developmental pathways contribute to formation and growth of pancreatic neoplasia, and hopefully generate valid biomarkers and targets as well as effective and safe therapeutics in pancreatic cancer.

  20. Metabolic profiling of an Echinostoma caproni infection in the mouse for biomarker discovery.

    Directory of Open Access Journals (Sweden)

    Jasmina Saric

    Full Text Available BACKGROUND: Metabolic profiling holds promise with regard to deepening our understanding of infection biology and disease states. The objectives of our study were to assess the global metabolic responses to an Echinostoma caproni infection in the mouse, and to compare the biomarkers extracted from different biofluids (plasma, stool, and urine in terms of characterizing acute and chronic stages of this intestinal fluke infection. METHODOLOGY/PRINCIPAL FINDINGS: Twelve female NMRI mice were infected with 30 E. caproni metacercariae each. Plasma, stool, and urine samples were collected at 7 time points up to day 33 post-infection. Samples were also obtained from non-infected control mice at the same time points and measured using (1H nuclear magnetic resonance (NMR spectroscopy. Spectral data were subjected to multivariate statistical analyses. In plasma and urine, an altered metabolic profile was already evident 1 day post-infection, characterized by reduced levels of plasma choline, acetate, formate, and lactate, coupled with increased levels of plasma glucose, and relatively lower concentrations of urinary creatine. The main changes in the urine metabolic profile started at day 8 post-infection, characterized by increased relative concentrations of trimethylamine and phenylacetylglycine and lower levels of 2-ketoisocaproate and showed differentiation over the course of the infection. CONCLUSION/SIGNIFICANCE: The current investigation is part of a broader NMR-based metabonomics profiling strategy and confirms the utility of this approach for biomarker discovery. In the case of E. caproni, a diagnosis based on all three biofluids would deliver the most comprehensive fingerprint of an infection. For practical purposes, however, future diagnosis might aim at a single biofluid, in which case urine would be chosen for further investigation, based on quantity of biomarkers, ease of sampling, and the degree of differentiation from the non

  1. Unlocking biomarker discovery: large scale application of aptamer proteomic technology for early detection of lung cancer.

    Directory of Open Access Journals (Sweden)

    Rachel M Ostroff

    Full Text Available BACKGROUND: Lung cancer is the leading cause of cancer deaths worldwide. New diagnostics are needed to detect early stage lung cancer because it may be cured with surgery. However, most cases are diagnosed too late for curative surgery. Here we present a comprehensive clinical biomarker study of lung cancer and the first large-scale clinical application of a new aptamer-based proteomic technology to discover blood protein biomarkers in disease. METHODOLOGY/PRINCIPAL FINDINGS: We conducted a multi-center case-control study in archived serum samples from 1,326 subjects from four independent studies of non-small cell lung cancer (NSCLC in long-term tobacco-exposed populations. Sera were collected and processed under uniform protocols. Case sera were collected from 291 patients within 8 weeks of the first biopsy-proven lung cancer and prior to tumor removal by surgery. Control sera were collected from 1,035 asymptomatic study participants with ≥ 10 pack-years of cigarette smoking. We measured 813 proteins in each sample with a new aptamer-based proteomic technology, identified 44 candidate biomarkers, and developed a 12-protein panel (cadherin-1, CD30 ligand, endostatin, HSP90α, LRIG3, MIP-4, pleiotrophin, PRKCI, RGM-C, SCF-sR, sL-selectin, and YES that discriminates NSCLC from controls with 91% sensitivity and 84% specificity in cross-validated training and 89% sensitivity and 83% specificity in a separate verification set, with similar performance for early and late stage NSCLC. CONCLUSIONS/SIGNIFICANCE: This study is a significant advance in clinical proteomics in an area of high unmet clinical need. Our analysis exceeds the breadth and dynamic range of proteome interrogated of previously published clinical studies of broad serum proteome profiling platforms including mass spectrometry, antibody arrays, and autoantibody arrays. The sensitivity and specificity of our 12-biomarker panel improves upon published protein and gene expression panels

  2. Automated microfluidic platform of bead-based electrochemical immunosensor integrated with bioreactor for continual monitoring of cell secreted biomarkers (United States)

    Riahi, Reza; Shaegh, Seyed Ali Mousavi; Ghaderi, Masoumeh; Zhang, Yu Shrike; Shin, Su Ryon; Aleman, Julio; Massa, Solange; Kim, Duckjin; Dokmeci, Mehmet Remzi; Khademhosseini, Ali


    There is an increasing interest in developing microfluidic bioreactors and organs-on-a-chip platforms combined with sensing capabilities for continual monitoring of cell-secreted biomarkers. Conventional approaches such as ELISA and mass spectroscopy cannot satisfy the needs of continual monitoring as they are labor-intensive and not easily integrable with low-volume bioreactors. This paper reports on the development of an automated microfluidic bead-based electrochemical immunosensor for in-line measurement of cell-secreted biomarkers. For the operation of the multi-use immunosensor, disposable magnetic microbeads were used to immobilize biomarker-recognition molecules. Microvalves were further integrated in the microfluidic immunosensor chip to achieve programmable operations of the immunoassay including bead loading and unloading, binding, washing, and electrochemical sensing. The platform allowed convenient integration of the immunosensor with liver-on-chips to carry out continual quantification of biomarkers secreted from hepatocytes. Transferrin and albumin productions were monitored during a 5-day hepatotoxicity assessment in which human primary hepatocytes cultured in the bioreactor were treated with acetaminophen. Taken together, our unique microfluidic immunosensor provides a new platform for in-line detection of biomarkers in low volumes and long-term in vitro assessments of cellular functions in microfluidic bioreactors and organs-on-chips.

  3. Automated microfluidic platform of bead-based electrochemical immunosensor integrated with bioreactor for continual monitoring of cell secreted biomarkers. (United States)

    Riahi, Reza; Shaegh, Seyed Ali Mousavi; Ghaderi, Masoumeh; Zhang, Yu Shrike; Shin, Su Ryon; Aleman, Julio; Massa, Solange; Kim, Duckjin; Dokmeci, Mehmet Remzi; Khademhosseini, Ali


    There is an increasing interest in developing microfluidic bioreactors and organs-on-a-chip platforms combined with sensing capabilities for continual monitoring of cell-secreted biomarkers. Conventional approaches such as ELISA and mass spectroscopy cannot satisfy the needs of continual monitoring as they are labor-intensive and not easily integrable with low-volume bioreactors. This paper reports on the development of an automated microfluidic bead-based electrochemical immunosensor for in-line measurement of cell-secreted biomarkers. For the operation of the multi-use immunosensor, disposable magnetic microbeads were used to immobilize biomarker-recognition molecules. Microvalves were further integrated in the microfluidic immunosensor chip to achieve programmable operations of the immunoassay including bead loading and unloading, binding, washing, and electrochemical sensing. The platform allowed convenient integration of the immunosensor with liver-on-chips to carry out continual quantification of biomarkers secreted from hepatocytes. Transferrin and albumin productions were monitored during a 5-day hepatotoxicity assessment in which human primary hepatocytes cultured in the bioreactor were treated with acetaminophen. Taken together, our unique microfluidic immunosensor provides a new platform for in-line detection of biomarkers in low volumes and long-term in vitro assessments of cellular functions in microfluidic bioreactors and organs-on-chips.

  4. An automated Genomes-to-Natural Products platform (GNP) for the discovery of modular natural products. (United States)

    Johnston, Chad W; Skinnider, Michael A; Wyatt, Morgan A; Li, Xiang; Ranieri, Michael R M; Yang, Lian; Zechel, David L; Ma, Bin; Magarvey, Nathan A


    Bacterial natural products are a diverse and valuable group of small molecules, and genome sequencing indicates that the vast majority remain undiscovered. The prediction of natural product structures from biosynthetic assembly lines can facilitate their discovery, but highly automated, accurate, and integrated systems are required to mine the broad spectrum of sequenced bacterial genomes. Here we present a genome-guided natural products discovery tool to automatically predict, combinatorialize and identify polyketides and nonribosomal peptides from biosynthetic assembly lines using LC-MS/MS data of crude extracts in a high-throughput manner. We detail the directed identification and isolation of six genetically predicted polyketides and nonribosomal peptides using our Genome-to-Natural Products platform. This highly automated, user-friendly programme provides a means of realizing the potential of genetically encoded natural products.

  5. A Supramolecular Sensing Platform for Phosphate Anions and an Anthrax Biomarker in a Microfluidic Device

    Directory of Open Access Journals (Sweden)

    Jurriaan Huskens


    Full Text Available A supramolecular platform based on self-assembled monolayers (SAMs has been implemented in a microfluidic device. The system has been applied for the sensing of two different analyte types: biologically relevant phosphate anions and aromatic carboxylic acids, which are important for anthrax detection. A Eu(III-EDTA complex was bound to β-cyclodextrin monolayers via orthogonal supramolecular host-guest interactions. The self-assembly of the Eu(III-EDTA conjugate and naphthalene β-diketone as an antenna resulted in the formation of a highly luminescent lanthanide complex on the microchannel surface. Detection of different phosphate anions and aromatic carboxylic acids was demonstrated by monitoring the decrease in red emission following displacement of the antenna by the analyte. Among these analytes, adenosine triphosphate (ATP and pyrophosphate, as well as dipicolinic acid (DPA which is a biomarker for anthrax, showed a strong response. Parallel fabrication of five sensing SAMs in a single multichannel chip was performed, as a first demonstration of phosphate and carboxylic acid screening in a multiplexed format that allows a general detection platform for both analyte systems in a single test run with µM and nM detection sensitivity for ATP and DPA, respectively.

  6. Release of Tissue-specific Proteins into Coronary Perfusate as a Model for Biomarker Discovery in Myocardial Ischemia/Reperfusion Injury

    DEFF Research Database (Denmark)

    Cordwell, Stuart; Edwards, Alistair; Liddy, Kiersten


    Diagnosis of acute coronary syndromes is based on protein biomarkers, such as the cardiac troponins (cTnI/cTnT) and creatine kinase (CK-MB) that are released into the circulation. Biomarker discovery is focused on identifying very low abundance tissue-derived analytes from within albumin-rich pla......Diagnosis of acute coronary syndromes is based on protein biomarkers, such as the cardiac troponins (cTnI/cTnT) and creatine kinase (CK-MB) that are released into the circulation. Biomarker discovery is focused on identifying very low abundance tissue-derived analytes from within albumin...

  7. Weighted gene co-expression based biomarker discovery for psoriasis detection. (United States)

    Sundarrajan, Sudharsana; Arumugam, Mohanapriya


    Psoriasis is a chronic inflammatory disease of the skin with an unknown aetiology. The disease manifests itself as red and silvery scaly plaques distributed over the scalp, lower back and extensor aspects of the limbs. After receiving scant consideration for quite a few years, psoriasis has now become a prominent focus for new drug development. A group of closely connected and differentially co-expressed genes may act in a network and may serve as molecular signatures for an underlying phenotype. A weighted gene coexpression network analysis (WGCNA), a system biology approach has been utilized for identification of new molecular targets for psoriasis. Gene coexpression relationships were investigated in 58 psoriatic lesional samples resulting in five gene modules, clustered based on the gene coexpression patterns. The coexpression pattern was validated using three psoriatic datasets. 10 highly connected and informative genes from each module was selected and termed as psoriasis specific hub signatures. A random forest based binary classifier built using the expression profiles of signature genes robustly distinguished psoriatic samples from the normal samples in the validation set with an accuracy of 0.95 to 1. These signature genes may serve as potential candidates for biomarker discovery leading to new therapeutic targets. WGCNA, the network based approach has provided an alternative path to mine out key controllers and drivers of psoriasis. The study principle from the current work can be extended to other pathological conditions.

  8. High-Sensitivity and Low-Toxicity Fucose Probe for Glycan Imaging and Biomarker Discovery. (United States)

    Kizuka, Yasuhiko; Funayama, Sho; Shogomori, Hidehiko; Nakano, Miyako; Nakajima, Kazuki; Oka, Ritsuko; Kitazume, Shinobu; Yamaguchi, Yoshiki; Sano, Masahiro; Korekane, Hiroaki; Hsu, Tsui-Ling; Lee, Hsiu-Yu; Wong, Chi-Huey; Taniguchi, Naoyuki


    Fucose, a terminal sugar in glycoconjugates, critically regulates various physiological and pathological phenomena, including cancer development and inflammation. However, there are currently no probes for efficient labeling and detection of this sugar. We chemically synthesized a novel series of alkynyl-fucose analogs as probe candidates and found that 7-alkynyl-fucose gave the highest labeling efficiency and low cytotoxicity. Among the fucose analogs, 7-alkynyl-fucose was the best substrate against all five fucosyltransferases examined. We confirmed its conversion to the corresponding guanosine diphosphate derivative in cells and found that cellular glycoproteins were labeled much more efficiently with 7-alkynyl-fucose than with an existing probe. 7-Alkynyl-fucose was detected in the N-glycan core by mass spectrometry, and 7-alkynyl-fucose-modified proteins mostly disappeared in core-fucose-deficient mouse embryonic fibroblasts, suggesting that this analog mainly labeled core fucose in these cells. These results indicate that 7-alkynyl-fucose is a highly sensitive and powerful tool for basic glycobiology research and clinical application for biomarker discovery.

  9. Discovery of dachshund 2 protein as a novel biomarker of poor prognosis in epithelial ovarian cancer

    Directory of Open Access Journals (Sweden)

    Nodin Björn


    Full Text Available Abstract Background The Dachshund homolog 2 (DACH2 gene has been implicated in development of the female genital tract in mouse models and premature ovarian failure syndrome, but to date, its expression in human normal and cancerous tissue remains unexplored. Using the Human Protein Atlas as a tool for cancer biomarker discovery, DACH2 protein was found to be differentially expressed in epithelial ovarian cancer (EOC. Here, the expression and prognostic significance of DACH2 was further evaluated in ovarian cancer cell lines and human EOC samples. Methods Immunohistochemical expression of DACH2 was examined in tissue microarrays with 143 incident EOC cases from two prospective, population-based cohorts, including a subset of benign-appearing fallopian tubes (n = 32. A nuclear score (NS, i.e. multiplier of staining fraction and intensity, was calculated. For survival analyses, cases were dichotomized into low (NS 3 using classification and regression tree analysis. Kaplan Meier analysis and Cox proportional hazards modelling were used to assess the impact of DACH2 expression on survival. DACH2 expression was analysed in the cisplatin sensitive ovarian cancer cell line A2780 and its cisplatin resistant derivative A2780-Cp70. The specificity of the DACH2 antibody was tested using siRNA-mediated silencing of DACH2 in A2780-Cp70 cells. Results DACH2 expression was considerably higher in the cisplatin resistant A2780-Cp70 cells compared to the cisplatin-sensitive A2780 cells. While present in all sampled fallopian tubes, DACH2 expression ranged from negative to strong in EOC. In EOC, DACH2 expression correlated with several proteins involved in DNA integrity and repair, and proliferation. DACH2 expression was significantly higher in carcinoma of the serous subtype compared to non-serous carcinoma. In the full cohort, high DACH2 expression was significantly associated with poor prognosis in univariable analysis, and in carcinoma of the serous subtype

  10. Using MALDI-IMS and MRM to stablish a pipeline for discovery and validation of tumor neovasculature biomarker candidates. — EDRN Public Portal (United States)

    In an effort to circumvent the limitations associated with biomarker discovery workflows involving cell lines and cell cultures, histology-directed MALDI protein profiling and imaging mass spectrometry will be used for identification of vascular endothelial biomarkers suitable for early prostate cancer detection by CEUS targeted molecular imaging

  11. Plenario: A Spatio-Temporal Platform for Discovery and Exploration of Urban Science Data (United States)

    Engler, W. H.; Malik, T.; Catlett, C.; Foster, I.; Goldstein, B.


    The past decade has seen the widespread release of open data concerning city services, conditions, and activities by government bodies and public institutions of all sizes. Hundreds of open data portals now host thousands of datasets of many different types. These new data sources represent enormous potential for improved understanding of urban dynamics and processes—and, ultimately, for more livable, efficient, and prosperous communities. However, those who seek to realize this potential quickly discover that discovering and applying those data relevant to any particular question can be extraordinarily difficult, due to decentralized storage, heterogeneous formats, and poor documentation. In this context, we introduce Plenario, a platform designed to automating time-consuming tasks associated with the discovery, exploration, and application of open city data—and, in so doing, reduce barriers to data use for researchers, policymakers, service providers, journalists, and members of the general public. Key innovations include a geospatial data warehouse that allows data from many sources to be registered into a common spatial and temporal frame; simple and intuitive interfaces that permit rapid discovery and exploration of data subsets pertaining to a particular area and time, regardless of type and source; easy export of such data subsets for further analysis; a user-configurable data ingest framework for automated importing and periodic updating of new datasets into the data warehouse; cloud hosting for elastic scaling and rapid creation of new Plenario instances; and an open source implementation to enable community contributions. We describe here the architecture and implementation of the Plenario platform, discuss lessons learned from its use by several communities, and outline plans for future work.

  12. NETL's Energy Data Exchange (EDX) - a coordination, collaboration, and data resource discovery platform for energy science (United States)

    Rose, K.; Rowan, C.; Rager, D.; Dehlin, M.; Baker, D. V.; McIntyre, D.


    Multi-organizational research teams working jointly on projects often encounter problems with discovery, access to relevant existing resources, and data sharing due to large file sizes, inappropriate file formats, or other inefficient options that make collaboration difficult. The Energy Data eXchange (EDX) from Department of Energy's (DOE) National Energy Technology Laboratory (NETL) is an evolving online research environment designed to overcome these challenges in support of DOE's fossil energy goals while offering improved access to data driven products of fossil energy R&D such as datasets, tools, and web applications. In 2011, development of NETL's Energy Data eXchange (EDX) was initiated and offers i) a means for better preserving of NETL's research and development products for future access and re-use, ii) efficient, discoverable access to authoritative, relevant, external resources, and iii) an improved approach and tools to support secure, private collaboration and coordination between multi-organizational teams to meet DOE mission and goals. EDX presently supports fossil energy and SubTER Crosscut research activities, with an ever-growing user base. EDX is built on a heavily customized instance of the open source platform, Comprehensive Knowledge Archive Network (CKAN). EDX connects users to externally relevant data and tools through connecting to external data repositories built on different platforms and other CKAN platforms (e.g. EDX does not download and repost data or tools that already have an online presence. This leads to redundancy and even error. If a relevant resource already has an online instance, is hosted by another online entity, EDX will point users to that external host either using web services, inventorying URLs and other methods. EDX offers users the ability to leverage private-secure capabilities custom built into the system. The team is presently working on version 3 of EDX which will incorporate big data analytical

  13. Glycoproteomics using so-called ‘fluid-biopsy’ specimens in the discovery of lung cancer biomarkers. Promise and challenge (United States)

    Li, Qing Kay; Gabrielson, Ed; Askin, Frederic; Chan, Daniel W; Zhang, Hui


    Lung cancer is the number one cancer in the US and worldwide. In spite of the rapid progression in personalized treatments, the overall survival rate of lung cancer patients is still suboptimal. Over the past decade, tremendous efforts have been focused on the discovery of protein biomarkers to facilitate the early detection and monitoring lung cancer progression during treatment. In addition to tumor tissues and cancer cell lines, a variety of biological material has been studied. Particularly in recent years, studies using fluid-based specimen or so-called “fluid-biopsy” specimen have progressed rapidly. Fluid specimens are relatively easier to collect than tumor tissue, and they can be repeatedly sampled during the disease progression. Glycoproteins have long been recognized to play fundamental roles in many physiological and pathological processes. In this review, we focus the discussion on recent advances of glycoproteomics, particularly in the identification of potential protein biomarkers using so-called fluid-based specimens in lung cancer. The purpose of this review is to summarize current strategies, achievements and perspectives in the field. This insight will highlight the discovery of tumor-associated glycoprotein biomarkers in lung cancer and their potential clinical applications. PMID:23112109

  14. Integrated proteomic analysis of human cancer cells and plasma from tumor bearing mice for ovarian cancer biomarker discovery.

    Directory of Open Access Journals (Sweden)

    Sharon J Pitteri

    Full Text Available The complexity of the human plasma proteome represents a substantial challenge for biomarker discovery. Proteomic analysis of genetically engineered mouse models of cancer and isolated cancer cells and cell lines provide alternative methods for identification of potential cancer markers that would be detectable in human blood using sensitive assays. The goal of this work is to evaluate the utility of an integrative strategy using these two approaches for biomarker discovery.We investigated a strategy that combined quantitative plasma proteomics of an ovarian cancer mouse model with analysis of proteins secreted or shed by human ovarian cancer cells. Of 106 plasma proteins identified with increased levels in tumor bearing mice, 58 were also secreted or shed from ovarian cancer cells. The remainder consisted primarily of host-response proteins. Of 25 proteins identified in the study that were assayed, 8 mostly secreted proteins common to mouse plasma and human cancer cells were significantly upregulated in a set of plasmas from ovarian cancer patients. Five of the eight proteins were confirmed to be upregulated in a second independent set of ovarian cancer plasmas, including in early stage disease.Integrated proteomic analysis of cancer mouse models and human cancer cell populations provides an effective approach to identify potential circulating protein biomarkers.

  15. A Perspective on Implementing a Quantitative Systems Pharmacology Platform for Drug Discovery and the Advancement of Personalized Medicine (United States)

    Stern, Andrew M.; Schurdak, Mark E.; Bahar, Ivet; Berg, Jeremy M.; Taylor, D. Lansing


    Drug candidates exhibiting well-defined pharmacokinetic and pharmacodynamic profiles that are otherwise safe often fail to demonstrate proof-of-concept in phase II and III trials. Innovation in drug discovery and development has been identified as a critical need for improving the efficiency of drug discovery, especially through collaborations between academia, government agencies, and industry. To address the innovation challenge, we describe a comprehensive, unbiased, integrated, and iterative quantitative systems pharmacology (QSP)–driven drug discovery and development strategy and platform that we have implemented at the University of Pittsburgh Drug Discovery Institute. Intrinsic to QSP is its integrated use of multiscale experimental and computational methods to identify mechanisms of disease progression and to test predicted therapeutic strategies likely to achieve clinical validation for appropriate subpopulations of patients. The QSP platform can address biological heterogeneity and anticipate the evolution of resistance mechanisms, which are major challenges for drug development. The implementation of this platform is dedicated to gaining an understanding of mechanism(s) of disease progression to enable the identification of novel therapeutic strategies as well as repurposing drugs. The QSP platform will help promote the paradigm shift from reactive population-based medicine to proactive personalized medicine by focusing on the patient as the starting and the end point. PMID:26962875

  16. Application of proteomics in the discovery of candidate protein biomarkers in a diabetes autoantibody standardization program sample subset. (United States)

    Metz, Thomas O; Qian, Wei-Jun; Jacobs, Jon M; Gritsenko, Marina A; Moore, Ronald J; Polpitiya, Ashoka D; Monroe, Matthew E; Camp, David G; Mueller, Patricia W; Smith, Richard D


    Novel biomarkers of type 1 diabetes must be identified and validated in initial, exploratory studies before they can be assessed in proficiency evaluations. Currently, untargeted "-omics" approaches are underutilized in profiling studies of clinical samples. This report describes the evaluation of capillary liquid chromatography (LC) coupled with mass spectrometry (MS) in a pilot proteomic analysis of human plasma and serum from a subset of control and type 1 diabetic individuals enrolled in the Diabetes Autoantibody Standardization Program, with the goal of identifying candidate biomarkers of type 1 diabetes. Initial high-resolution capillary LC-MS/MS experiments were performed to augment an existing plasma peptide database, while subsequent LC-FTICR studies identified quantitative differences in the abundance of plasma proteins. Analysis of LC-FTICR proteomic data identified five candidate protein biomarkers of type 1 diabetes. alpha-2-Glycoprotein 1 (zinc), corticosteroid-binding globulin, and lumican were 2-fold up-regulated in type 1 diabetic samples relative to control samples, whereas clusterin and serotransferrin were 2-fold up-regulated in control samples relative to type 1 diabetic samples. Observed perturbations in the levels of all five proteins are consistent with the metabolic aberrations found in type 1 diabetes. While the discovery of these candidate protein biomarkers of type 1 diabetes is encouraging, follow up studies are required for validation in a larger population of individuals and for determination of laboratory-defined sensitivity and specificity values using blinded samples.

  17. Theoretical modeling of masking DNA application in aptamer-facilitated biomarker discovery. (United States)

    Cherney, Leonid T; Obrecht, Natalia M; Krylov, Sergey N


    In aptamer-facilitated biomarker discovery (AptaBiD), aptamers are selected from a library of random DNA (or RNA) sequences for their ability to specifically bind cell-surface biomarkers. The library is incubated with intact cells, and cell-bound DNA molecules are separated from those unbound and amplified by the polymerase chain reaction (PCR). The partitioning/amplification cycle is repeated multiple times while alternating target cells and control cells. Efficient aptamer selection in AptaBiD relies on the inclusion of masking DNA within the cell and library mixture. Masking DNA lacks primer regions for PCR amplification and is typically taken in excess to the library. The role of masking DNA within the selection mixture is to outcompete any nonspecific binding sequences within the initial library, thus allowing specific DNA sequences (i.e., aptamers) to be selected more efficiently. Efficient AptaBiD requires an optimum ratio of masking DNA to library DNA, at which aptamers still bind specific binding sites but nonaptamers within the library do not bind nonspecific binding sites. Here, we have developed a mathematical model that describes the binding processes taking place within the equilibrium mixture of masking DNA, library DNA, and target cells. An obtained mathematical solution allows one to estimate the concentration of masking DNA that is required to outcompete the library DNA at a desirable ratio of bound masking DNA to bound library DNA. The required concentration depends on concentrations of the library and cells as well as on unknown cell characteristics. These characteristics include the concentration of total binding sites on the cell surface, N, and equilibrium dissociation constants, K(nsL) and K(nsM), for nonspecific binding of the library DNA and masking DNA, respectively. We developed a theory that allows the determination of N, K(nsL), and K(nsM) based on measurements of EC50 values for cells mixed separately with the library and masking DNA

  18. Pairwise protein expression classifier for candidate biomarker discovery for early detection of human disease prognosis

    Directory of Open Access Journals (Sweden)

    Kaur Parminder


    Full Text Available Abstract Background An approach to molecular classification based on the comparative expression of protein pairs is presented. The method overcomes some of the present limitations in using peptide intensity data for class prediction for problems such as the detection of a disease, disease prognosis, or for predicting treatment response. Data analysis is particularly challenging in these situations due to sample size (typically tens being much smaller than the large number of peptides (typically thousands. Methods based upon high dimensional statistical models, machine learning or other complex classifiers generate decisions which may be very accurate but can be complex and difficult to interpret in simple or biologically meaningful terms. A classification scheme, called ProtPair, is presented that generates simple decision rules leading to accurate classification which is based on measurement of very few proteins and requires only relative expression values, providing specific targeted hypotheses suitable for straightforward validation. Results ProtPair has been tested against clinical data from 21 patients following a bone marrow transplant, 13 of which progress to idiopathic pneumonia syndrome (IPS. The approach combines multiple peptide pairs originating from the same set of proteins, with each unique peptide pair providing an independent measure of discriminatory power. The prediction rate of the ProtPair for IPS study as measured by leave-one-out CV is 69.1%, which can be very beneficial for clinical diagnosis as it may flag patients in need of closer monitoring. The “top ranked” proteins provided by ProtPair are known to be associated with the biological processes and pathways intimately associated with known IPS biology based on mouse models. Conclusions An approach to biomarker discovery, called ProtPair, is presented. ProtPair is based on the differential expression of pairs of peptides and the associated proteins. Using mass

  19. The future of liquid chromatography-mass spectrometry in metabolic profiling and metabolomic studies for biomarker discovery.

    Energy Technology Data Exchange (ETDEWEB)

    Metz, Thomas O.; Zhang, Qibin; Page, Jason S.; Shen, Yufeng; Callister, Stephen J.; Jacobs, Jon M.; Smith, Richard D.


    The future utility of liquid chromatography-mass spectrometry (LC-MS) in metabolic profiling and metabolomic studies for biomarker discover will be discussed, beginning with a brief description of the evolution of metabolomics and the utilization of the three most popular analytical platforms in such studies: NMR, GC-MS, and LC-MS. Emphasis is placed on recent developments in high-efficiency LC separations and sensitive electrospray ionization approaches and the benefits to incorporating both in LC-MS-based approaches. The advantages and disadvantages of various quantitative approaches are reviewed, followed by the current LC-MS-based tools available for candidate biomarker characterization and identification. Finally, a brief prediction on the future path of LC-MS-based methods in metabolic profiling and metabolomic studies is given.

  20. Discovery of safety biomarkers for atorvastatin in rat urine using mass spectrometry based metabolomics combined with global and targeted approach

    Energy Technology Data Exchange (ETDEWEB)

    Kumar, Bhowmik Salil [Bioanalysis and Biotransformation Research Center, Korea Institute of Science and Technology, P.O. Box 131, Cheongryang, Seoul 130-650 (Korea, Republic of); University of Science and Technology, (305-333) 113 Gwahangno, Yuseong-gu, Daejeon (Korea, Republic of); Lee, Young-Joo; Yi, Hong Jae [College of Pharmacy, Kyung Hee University, Hoegi-dong, Dongdaemun-gu, Seoul 130-791 (Korea, Republic of); Chung, Bong Chul [Bioanalysis and Biotransformation Research Center, Korea Institute of Science and Technology, P.O. Box 131, Cheongryang, Seoul 130-650 (Korea, Republic of); Jung, Byung Hwa, E-mail: [Bioanalysis and Biotransformation Research Center, Korea Institute of Science and Technology, P.O. Box 131, Cheongryang, Seoul 130-650 (Korea, Republic of); University of Science and Technology, (305-333) 113 Gwahangno, Yuseong-gu, Daejeon (Korea, Republic of)


    In order to develop a safety biomarker for atorvastatin, this drug was orally administrated to hyperlipidemic rats, and a metabolomic study was performed. Atorvastatin was given in doses of either 70 mg kg{sup -1} day{sup -1} or 250 mg kg{sup -1} day{sup -1} for a period of 7 days (n = 4 for each group). To evaluate any abnormal effects of the drug, physiological and plasma biochemical parameters were measured and histopathological tests were carried out. Safety biomarkers were derived by comparing these parameters and using both global and targeted metabolic profiling. Global metabolic profiling was performed using liquid chromatography/time of flight/mass spectrometry (LC/TOF/MS) with multivariate data analysis. Several safety biomarker candidates that included various steroids and amino acids were discovered as a result of global metabolic profiling, and they were also confirmed by targeted metabolic profiling using gas chromatography/mass spectrometry (GC/MS) and capillary electrophoresis/mass spectrometry (CE/MS). Serum biochemical and histopathological tests were used to detect abnormal drug reactions in the liver after repeating oral administration of atorvastatin. The metabolic differences between control and the drug-treated groups were compared using PLS-DA score plots. These results were compared with the physiological and plasma biochemical parameters and the results of a histopathological test. Estrone, cortisone, proline, cystine, 3-ureidopropionic acid and histidine were proposed as potential safety biomarkers related with the liver toxicity of atorvastatin. These results indicate that the combined application of global and targeted metabolic profiling could be a useful tool for the discovery of drug safety biomarkers.

  1. In Silico discovery of transcription factors as potential diagnostic biomarkers of ovarian cancer

    KAUST Repository

    Kaur, Mandeep


    Background: Our study focuses on identifying potential biomarkers for diagnosis and early detection of ovarian cancer (OC) through the study of transcription regulation of genes affected by estrogen hormone.Results: The results are based on a set of 323 experimentally validated OC-associated genes compiled from several databases, and their subset controlled by estrogen. For these two gene sets we computationally determined transcription factors (TFs) that putatively regulate transcription initiation. We ranked these TFs based on the number of genes they are likely to control. In this way, we selected 17 top-ranked TFs as potential key regulators and thus possible biomarkers for a set of 323 OC-associated genes. For 77 estrogen controlled genes from this set we identified three unique TFs as potential biomarkers.Conclusions: We introduced a new methodology to identify potential diagnostic biomarkers for OC. This report is the first bioinformatics study that explores multiple transcriptional regulators of OC-associated genes as potential diagnostic biomarkers in connection with estrogen responsiveness. We show that 64% of TF biomarkers identified in our study are validated based on real-time data from microarray expression studies. As an illustration, our method could identify CP2 that in combination with CA125 has been reported to be sensitive in diagnosing ovarian tumors. 2011 Kaur et al; licensee BioMed Central Ltd.

  2. Proteomic approaches to biomarker discovery in lung cancers by SELDI technology

    Institute of Scientific and Technical Information of China (English)

    肖雪媛; 卫秀平; 何大澄


    The purpose of the present work is to identify protein profiles that could be used to discover specific biomarkers in serum and discriminate lung cancer. Thirty serum samples from patients with lung cancer (15 cases of primary brochogenic carcinoma, 9 cases of metastasis lung cancer and 6 cases of lung cancer after chemotherapy) and twelve from healthy individuals were analyzed by SELDI (Surfaced Enhanced Laser Desorption/Ionization) technology. Anion-exchange columns were used to fractionate the sera with 6 designated pH washing solutions. Two types of protein chip arrays, IMAC-Cu and WCX2, were employed. Protein chips were examined in PBSII ProteinChip Reader (Ciphergen Biosystems Inc.) and the resulting profiles between cancer and normal were analyzed with Biomarker Wizard System. In total, 15 potential lung cancer biomarkers, of which 6 were up-regulated and 9 were down-regulated, were discovered in the serum samples from patients with lung cancer. 5 of 15 these biomarkers were able to be detected on both WCX2 and IMAC-Cu protein chips. The sensitivities provided by the individual markers range from 44.8% to 93.1% and the specificities were 85.0%-94.4%. Our results suggest that serum is a capable resource for detection of lung cancer with specific biomarkers. Moreover, protein chip array system was shown to be a useful tool for identification, as well as detection of disease biomarkers in sera.

  3. In Silico discovery of transcription factors as potential diagnostic biomarkers of ovarian cancer

    Directory of Open Access Journals (Sweden)

    Choolani Mahesh


    Full Text Available Abstract Background Our study focuses on identifying potential biomarkers for diagnosis and early detection of ovarian cancer (OC through the study of transcription regulation of genes affected by estrogen hormone. Results The results are based on a set of 323 experimentally validated OC-associated genes compiled from several databases, and their subset controlled by estrogen. For these two gene sets we computationally determined transcription factors (TFs that putatively regulate transcription initiation. We ranked these TFs based on the number of genes they are likely to control. In this way, we selected 17 top-ranked TFs as potential key regulators and thus possible biomarkers for a set of 323 OC-associated genes. For 77 estrogen controlled genes from this set we identified three unique TFs as potential biomarkers. Conclusions We introduced a new methodology to identify potential diagnostic biomarkers for OC. This report is the first bioinformatics study that explores multiple transcriptional regulators of OC-associated genes as potential diagnostic biomarkers in connection with estrogen responsiveness. We show that 64% of TF biomarkers identified in our study are validated based on real-time data from microarray expression studies. As an illustration, our method could identify CP2 that in combination with CA125 has been reported to be sensitive in diagnosing ovarian tumors.

  4. An In Vivo Platform for Rapid High-Throughput Antitubercular Drug Discovery

    Directory of Open Access Journals (Sweden)

    Kevin Takaki


    Full Text Available Treatment of tuberculosis, like other infectious diseases, is increasingly hindered by the emergence of drug resistance. Drug discovery efforts would be facilitated by facile screening tools that incorporate the complexities of human disease. Mycobacterium marinum-infected zebrafish larvae recapitulate key aspects of tuberculosis pathogenesis and drug treatment. Here, we develop a model for rapid in vivo drug screening using fluorescence-based methods for serial quantitative assessment of drug efficacy and toxicity. We provide proof-of-concept that both traditional bacterial-targeting antitubercular drugs and newly identified host-targeting drugs would be discovered through the use of this model. We demonstrate the model’s utility for the identification of synergistic combinations of antibacterial drugs and demonstrate synergy between bacterial- and host-targeting compounds. Thus, the platform can be used to identify new antibacterial agents and entirely new classes of drugs that thwart infection by targeting host pathways. The methods developed here should be widely applicable to small-molecule screens for other infectious and noninfectious diseases.

  5. A systematic approach to biomarker discovery; Preamble to "the iSBTc-FDA taskforce on immunotherapy biomarkers"

    Directory of Open Access Journals (Sweden)

    Schendel Dolores


    Full Text Available Abstract The International Society for the Biological Therapy of Cancer (iSBTc has initiated in collaboration with the United States Food and Drug Administration (FDA a programmatic look at innovative avenues for the identification of relevant parameters to assist clinical and basic scientists who study the natural course of host/tumor interactions or their response to immune manipulation. The task force has two primary goals: 1 identify best practices of standardized and validated immune monitoring procedures and assays to promote inter-trial comparisons and 2 develop strategies for the identification of novel biomarkers that may enhance our understating of principles governing human cancer immune biology and, consequently, implement their clinical application. Two working groups were created that will report the developed best practices at an NCI/FDA/iSBTc sponsored workshop tied to the annual meeting of the iSBTc to be held in Washington DC in the Fall of 2009. This foreword provides an overview of the task force and invites feedback from readers that might be incorporated in the discussions and in the final document.

  6. Development of urinary pseudotargeted LC-MS-based metabolomics method and its application in hepatocellular carcinoma biomarker discovery. (United States)

    Shao, Yaping; Zhu, Bin; Zheng, Ruiyin; Zhao, Xinjie; Yin, Peiyuan; Lu, Xin; Jiao, Binghua; Xu, Guowang; Yao, Zhenzhen


    Hepatocellular carcinoma (HCC) is one of the pestilent malignancies leading to cancer-related death. Discovering effective biomarkers for HCC diagnosis is an urgent demand. To identify potential metabolite biomarkers, we developed a urinary pseudotargeted method based on liquid chromatography-hybrid triple quadrupole linear ion trap mass spectrometry (LC-QTRAP MS). Compared with nontargeted method, the pseudotargeted method can achieve better data quality, which benefits differential metabolites discovery. The established method was applied to cirrhosis (CIR) and HCC investigation. It was found that urinary nucleosides, bile acids, citric acid, and several amino acids were significantly changed in liver disease groups compared with the controls, featuring the dysregulation of purine metabolism, energy metabolism, and amino metabolism in liver diseases. Furthermore, some metabolites such as cyclic adenosine monophosphate, glutamine, and short- and medium-chain acylcarnitines were the differential metabolites of HCC and CIR. On the basis of binary logistic regression, butyrylcarnitine (carnitine C4:0) and hydantoin-5-propionic acid were defined as combinational markers to distinguish HCC from CIR. The area under curve was 0.786 and 0.773 for discovery stage and validation stage samples, respectively. These data show that the established pseudotargeted method is a complementary one of targeted and nontargeted methods for metabolomics study.

  7. Quantitative label-free proteomics for discovery of biomarkers in cerebrospinal fluid: assessment of technical and inter-individual variation.

    Directory of Open Access Journals (Sweden)

    Richard J Perrin

    Full Text Available Biomarkers are required for pre-symptomatic diagnosis, treatment, and monitoring of neurodegenerative diseases such as Alzheimer's disease. Cerebrospinal fluid (CSF is a favored source because its proteome reflects the composition of the brain. Ideal biomarkers have low technical and inter-individual variability (subject variance among control subjects to minimize overlaps between clinical groups. This study evaluates a process of multi-affinity fractionation (MAF and quantitative label-free liquid chromatography tandem mass spectrometry (LC-MS/MS for CSF biomarker discovery by (1 identifying reparable sources of technical variability, (2 assessing subject variance and residual technical variability for numerous CSF proteins, and (3 testing its ability to segregate samples on the basis of desired biomarker characteristics.Fourteen aliquots of pooled CSF and two aliquots from six cognitively normal individuals were randomized, enriched for low-abundance proteins by MAF, digested endoproteolytically, randomized again, and analyzed by nano-LC-MS. Nano-LC-MS data were time and m/z aligned across samples for relative peptide quantification. Among 11,433 aligned charge groups, 1360 relatively abundant ones were annotated by MS2, yielding 823 unique peptides. Analyses, including Pearson correlations of annotated LC-MS ion chromatograms, performed for all pairwise sample comparisons, identified several sources of technical variability: i incomplete MAF and keratins; ii globally- or segmentally-decreased ion current in isolated LC-MS analyses; and iii oxidized methionine-containing peptides. Exclusion of these sources yielded 609 peptides representing 81 proteins. Most of these proteins showed very low coefficients of variation (CV<5% whether they were quantified from the mean of all or only the 2 most-abundant peptides. Unsupervised clustering, using only 24 proteins selected for high subject variance, yielded perfect segregation of pooled and

  8. MRM screening/biomarker discovery with linear ion trap MS: a library of human cancer-specific peptides

    Directory of Open Access Journals (Sweden)

    Lazar Iulia M


    Full Text Available Abstract Background The discovery of novel protein biomarkers is essential in the clinical setting to enable early disease diagnosis and increase survivability rates. To facilitate differential expression analysis and biomarker discovery, a variety of tandem mass spectrometry (MS/MS-based protein profiling techniques have been developed. For achieving sensitive detection and accurate quantitation, targeted MS screening approaches, such as multiple reaction monitoring (MRM, have been implemented. Methods MCF-7 breast cancer protein cellular extracts were analyzed by 2D-strong cation exchange (SCX/reversed phase liquid chromatography (RPLC separations interfaced to linear ion trap MS detection. MS data were interpreted with the Sequest-based Bioworks software (Thermo Electron. In-house developed Perl-scripts were used to calculate the spectral counts and the representative fragment ions for each peptide. Results In this work, we report on the generation of a library of 9,677 peptides (p a, b, y ions in the spectrum, the retention time, and the top 10 most intense product ions that correspond to a given peptide. Only proteins identified by at least two spectral counts are listed. The experimental distribution of protein frequencies, as a function of molecular weight, closely matched the theoretical distribution of proteins in the human proteome, as provided in the SwissProt database. The amino acid sequence coverage of the identified proteins ranged from 0.04% to 98.3%. The highest-abundance proteins in the cellular extract had a molecular weight (MW Conclusion Preliminary experiments have demonstrated that putative biomarkers, that are not detectable by conventional data dependent MS acquisition methods in complex un-fractionated samples, can be reliable identified with the information provided in this library. Based on the spectral count, the quality of a tandem mass spectrum and the m/z values for a parent peptide and its most abundant daughter

  9. Creating a Discovery Platform for Confined-Space Chemistry and Materials: Metal-Organic Frameworks.

    Energy Technology Data Exchange (ETDEWEB)

    Allendorf, Mark D.; Greathouse, Jeffery A.; Simmons, Blake


    Metal organic frameworks (MOF) are a recently discovered class of nanoporous, defect-free crystalline materials that enable rational design and exploration of porous materials at the molecular level. MOFs have tunable monolithic pore sizes and cavity environments due to their crystalline nature, yielding properties exceeding those of most other porous materials. These include: the lowest known density (91% free space); highest surface area; tunable photoluminescence; selective molecular adsorption; and methane sorption rivaling gas cylinders. These properties are achieved by coupling inorganic metal complexes such as ZnO4 with tunable organic ligands that serve as struts, allowing facile manipulation of pore size and surface area through reactant selection. MOFs thus provide a discovery platform for generating both new understanding of chemistry in confined spaces and novel sensors and devices based on their unique properties. At the outset of this project in FY06, virtually nothing was known about how to couple MOFs to substrates and the science of MOF properties and how to tune them was in its infancy. An integrated approach was needed to establish the required knowledge base for nanoscale design and develop methodologies integrate MOFs with other materials. This report summarizes the key accomplishments of this project, which include creation of a new class of radiation detection materials based on MOFs, luminescent MOFs for chemical detection, use of MOFs as templates to create nanoparticles of hydrogen storage materials, MOF coatings for stress-based chemical detection using microcantilevers, and "flexible" force fields that account for structural changes in MOFs that occur upon molecular adsorption/desorption. Eight journal articles, twenty presentations at scientific conferences, and two patent applications resulted from the work. The project created a basis for continuing development of MOFs for many Sandia applications and succeeded in securing $2.75 M in

  10. Application of systems biology principles to protein biomarker discovery: Urinary exosomal proteome in renal transplantation (United States)

    Das, Samarjit; Knepper, Mark A.; Bagnasco, Serena M.


    Purpose In MS-based studies to discover urinary protein biomarkers, an important question is how to analyze the data to find the most promising potential biomarkers to be advanced to large-scale validation studies. Here, we describe a ‘systems biology-based’ approach to address this question. Experimental design We analyzed large-scale LC-MS/MS data of urinary exosomes from renal allograft recipients with biopsy-proven evidence of immunological rejection or tubular injury. We asked whether bioinformatic analysis of urinary exosomal proteins can identify protein groups that correlate with biopsy findings and whether the protein groups fit with general knowledge of the pathophysiological mechanisms involved. Results LC-MS/MS analysis of urinary exosomal proteomes identified more than 1000 proteins in each pathologic group. These protein lists were analyzed computationally to identify Biological Process and KEGG Pathway terms that are significantly associated with each pathological group. Among the most informative terms for each group were: “sodium ion transport” for tubular injury; “immune response” for all rejection; “epithelial cell differentiation” for cell-mediated rejection; and “acute inflammatory response” for antibody-mediated rejection. Based on these terms, candidate biomarkers were identified using a novel strategy to allow a dichotomous classification between different pathologic categories. Conclusions and clinical relevance The terms and candidate biomarkers identified make rational connections to pathophysiological mechanisms, suggesting that the described bioinformatic approach will be useful in advancing large-scale biomarker identification studies toward a validation phase. PMID:22641613

  11. Implementation of proteomic biomarkers: making it work (United States)

    Mischak, Harald; Ioannidis, John PA; Argiles, Angel; Attwood, Teresa K; Bongcam-Rudloff, Erik; Broenstrup, Mark; Charonis, Aristidis; Chrousos, George P; Delles, Christian; Dominiczak, Anna; Dylag, Tomasz; Ehrich, Jochen; Egido, Jesus; Findeisen, Peter; Jankowski, Joachim; Johnson, Robert W; Julien, Bruce A; Lankisch, Tim; Leung, Hing Y; Maahs, David; Magni, Fulvio; Manns, Michael P; Manolis, Efthymios; Mayer, Gert; Navis, Gerjan; Novak, Jan; Ortiz, Alberto; Persson, Frederik; Peter, Karlheinz; Riese, Hans H; Rossing, Peter; Sattar, Naveed; Spasovski, Goce; Thongboonkerd, Visith; Vanholder, Raymond; Schanstra, Joost P; Vlahou, Antonia


    While large numbers of proteomic biomarkers have been described, they are generally not implemented in medical practice. We have investigated the reasons for this shortcoming, focusing on hurdles downstream of biomarker verification, and describe major obstacles and possible solutions to ease valid biomarker implementation. Some of the problems lie in suboptimal biomarker discovery and validation, especially lack of validated platforms with well-described performance characteristics to support biomarker qualification. These issues have been acknowledged and are being addressed, raising the hope that valid biomarkers may start accumulating in the foreseeable future. However, successful biomarker discovery and qualification alone does not suffice for successful implementation. Additional challenges include, among others, limited access to appropriate specimens and insufficient funding, the need to validate new biomarker utility in interventional trials, and large communication gaps between the parties involved in implementation. To address this problem, we propose an implementation roadmap. The implementation effort needs to involve a wide variety of stakeholders (clinicians, statisticians, health economists, and representatives of patient groups, health insurance, pharmaceutical companies, biobanks, and regulatory agencies). Knowledgeable panels with adequate representation of all these stakeholders may facilitate biomarker evaluation and guide implementation for the specific context of use. This approach may avoid unwarranted delays or failure to implement potentially useful biomarkers, and may expedite meaningful contributions of the biomarker community to healthcare. PMID:22519700

  12. Nutrition and biomarkers in psychiatry : research on micronutrient deficiencies in schizophrenia, the role of the intestine in the hyperserotonemia of autism, and a method for non-hypothesis driven discovery of biomarkers in urine

    NARCIS (Netherlands)

    Kemperman, Ramses Franciscus Jacobus


    This thesis describes the study of markers of nutrition and intestinal motility in mental disorders with a focus on schizophrenia and autism, and the development, evaluation and application of a biomarker discovery method for urine. The aim of the thesis is to investigate the role of long-chain poly

  13. Current and future trends in biomarker discovery and development of companion diagnostics for arthritis. (United States)

    Gibson, David S; Bustard, Michael J; McGeough, Cathy M; Murray, Helena A; Crockard, Martin A; McDowell, Andrew; Blayney, Jayne K; Gardiner, Philip V; Bjourson, Anthony J


    Musculoskeletal diseases such as rheumatoid arthritis are complex multifactorial disorders that are chronic in nature and debilitating for patients. A number of drug families are available to clinicians to manage these disorders but few tests exist to target these to the most responsive patients. As a consequence, drug failure and switching to drugs with alternate modes of action is common. In parallel, a limited number of laboratory tests are available which measure biological indicators or 'biomarkers' of disease activity, autoimmune status, or joint damage. There is a growing awareness that assimilating the fields of drug selection and diagnostic tests into 'companion diagnostics' could greatly advance disease management and improve outcomes for patients. This review aims to highlight: the current applications of biomarkers in rheumatology with particular focus on companion diagnostics; developments in the fields of proteomics, genomics, microbiomics, imaging and bioinformatics and how integration of these technologies into clinical practice could support therapeutic decisions.

  14. Discovery of Hyperpolarized Molecular Imaging Biomarkers in a Novel Prostate Tissue Slice Culture Model (United States)


    compatible bioreactor optimized in year 1 to identify hyperpolarized metabolic biomarkers of prostate cancer presence and aggressiveness. To...accomplish this goal my group finished the engineering of a 5 mm bioreactor and acquired hyperpolarized [1-13C]pyruvate data indicating that similar noise and quality data can be achieved with 4 to 5 prostate tissue slices in the 5 mm bioreactor as was acquired from 30-40 tissue slices in the

  15. Discovery and identification of serum biomarkers of Wilms' tumor in mice using proteomics technology

    Institute of Scientific and Technical Information of China (English)

    JIA Zhan-kui; WANG Jia-xiang; YANG Jin-jian; XUE Rui; ZHANG Da; WANG Guan-nan; MA Sheng-li; DUAN Zhen-feng


    Background Wilms' tumor (nephroblastoma) is a cancer of the kidneys that occurs typically in children and rarely in adults.Early diagnosis is very important for the treatment and prognosis of the disease.The aim of our study was to discover and identify potential non-invasive and convenient biomarkers for the diagnosis of Wilms' tumor.Methods Nude mice were used to construct a Wilms' tumor model by injecting nephroblastoma cells into their bilateral abdomen.We collected 94 serum samples from mice consisting of 45 samples with Wilms' tumor and 49 controls.The serum proteomic profiles of the samples were analyzed via surface-enhanced laser desorption/ionization time-of-flight mass spectrometry.The candidate biomarkers were purified by high-performance liquid chromatography,identified by liquid chromatography-mass spectrometry,and validated using ProteinChip immunoassays.Results We finally retrieved two differential proteins (m/z 4509.2; 6207.9),which were identified as apolipoprotein A-Ⅱ and polyubiquitin,respectively.The expression of apolipoprotein A-Ⅱ was higher in the Wilms' tumor group than in the control group (P<0.01).By contrast,the expression of polyubiquitin was lower in the Wilms' tumor group than in the control group.Conclusion Apolipoprotein A-Ⅱ and polyubiquitin may be used as potential biomarkers for nephroblastoma in children,and the analysis of apolipoprotein A-Ⅱ may help diagnose and treat Wilms' tumor.

  16. Lectin chromatography/mass spectrometry discovery workflow identifies putative biomarkers of aggressive breast cancers. (United States)

    Drake, Penelope M; Schilling, Birgit; Niles, Richard K; Prakobphol, Akraporn; Li, Bensheng; Jung, Kwanyoung; Cho, Wonryeon; Braten, Miles; Inerowicz, Halina D; Williams, Katherine; Albertolle, Matthew; Held, Jason M; Iacovides, Demetris; Sorensen, Dylan J; Griffith, Obi L; Johansen, Eric; Zawadzka, Anna M; Cusack, Michael P; Allen, Simon; Gormley, Matthew; Hall, Steven C; Witkowska, H Ewa; Gray, Joe W; Regnier, Fred; Gibson, Bradford W; Fisher, Susan J


    We used a lectin chromatography/MS-based approach to screen conditioned medium from a panel of luminal (less aggressive) and triple negative (more aggressive) breast cancer cell lines (n=5/subtype). The samples were fractionated using the lectins Aleuria aurantia (AAL) and Sambucus nigra agglutinin (SNA), which recognize fucose and sialic acid, respectively. The bound fractions were enzymatically N-deglycosylated and analyzed by LC-MS/MS. In total, we identified 533 glycoproteins, ∼90% of which were components of the cell surface or extracellular matrix. We observed 1011 glycosites, 100 of which were solely detected in ≥3 triple negative lines. Statistical analyses suggested that a number of these glycosites were triple negative-specific and thus potential biomarkers for this tumor subtype. An analysis of RNaseq data revealed that approximately half of the mRNAs encoding the protein scaffolds that carried potential biomarker glycosites were up-regulated in triple negative vs luminal cell lines, and that a number of genes encoding fucosyl- or sialyltransferases were differentially expressed between the two subtypes, suggesting that alterations in glycosylation may also drive candidate identification. Notably, the glycoproteins from which these putative biomarker candidates were derived are involved in cancer-related processes. Thus, they may represent novel therapeutic targets for this aggressive tumor subtype.

  17. Discovery and validation of DNA hypomethylation biomarkers for liver cancer using HRM-specific probes.

    Directory of Open Access Journals (Sweden)

    Barbara Stefanska

    Full Text Available Poor prognosis of hepatocellular carcinoma (HCC associated with late diagnosis necessitates the development of early diagnostic biomarkers. We have previously delineated the landscape of DNA methylation in HCC patients unraveling the importance of promoter hypomethylation in activation of cancer- and metastasis-driving genes. The purpose of the present study was to test the feasibility that genes that are hypomethylated in HCC could serve as candidate diagnostic markers. We use high resolution melting analysis (HRM as a simple translatable PCR-based method to define methylation states in clinical samples. We tested seven regions selected from the shortlist of genes hypomethylated in HCC and showed that HRM analysis of several of them distinguishes methylation states in liver cancer specimens from normal adjacent liver and chronic hepatitis in the Shanghai area. Such regions were identified within promoters of neuronal membrane glycoprotein M6-B (GPM6B and melanoma antigen family A12 (MAGEA12 genes. Differences in HRM in the immunoglobulin superfamily Fc receptor (FCRL1 separated invasive tumors from less invasive HCC. The identified biomarkers differentiated HCC from chronic hepatitis in another set of samples from Dhaka. Although the main thrust in DNA methylation diagnostics in cancer is on hypermethylated genes, our study for the first time illustrates the potential use of hypomethylated genes as markers for solid tumors. After further validation in a larger cohort, the identified DNA hypomethylated regions can become important candidate biomarkers for liver cancer diagnosis and prognosis, especially in populations with high risk for HCC development.

  18. Custom database development and biomarker discovery methods for MALDI-TOF mass spectrometry-based identification of high-consequence bacterial pathogens. (United States)

    Tracz, Dobryan M; Tyler, Andrea D; Cunningham, Ian; Antonation, Kym S; Corbett, Cindi R


    A high-quality custom database of MALDI-TOF mass spectral profiles was developed with the goal of improving clinical diagnostic identification of high-consequence bacterial pathogens. A biomarker discovery method is presented for identifying and evaluating MALDI-TOF MS spectra to potentially differentiate biothreat bacteria from less-pathogenic near-neighbour species.

  19. Endo-β-N-acetylglucosaminidase H de-N-glycosylation in a domestic microwave oven: application to biomarker discovery. (United States)

    Frisch, Elena; Schwedler, Christian; Kaup, Matthias; Iona Braicu, Elena; Gröne, Jörn; Lauscher, Johannes C; Sehouli, Jalid; Zimmermann, Matthias; Tauber, Rudolf; Berger, Markus; Blanchard, Véronique


    Sample preparation is the rate-limiting step in glycan analysis workflows. Among all of the steps, enzymatic digestions, which are usually performed overnight, are the most time-consuming. In the current study, we report an economical and fast preparation of N-glycans from serum, including microwave-assisted enzymatic digestion in the absence of denaturing chemicals and solvents during the release. To this end, we used a household microwave oven to accelerate both pronase and endo-β-N-acetylglucosaminidase H (Endo H) digestions. Purification was then performed using self-made SP20SS and carbon tips. We were able to prepare samples in 55 min instead of 21 h. Finally, the method was applied in the context of oncological biomarker discovery exemplarily to ovarian and colon cancer. We observed a significant downregulation of sialylated hybrid structures in ovarian cancer samples using capillary electrophoresis-laser-induced fluorescence (CE-LIF). Furthermore, sepsis, a systemic inflammatory response syndrome, was also included in the study to understand whether the changes observed in ovarian cancer patients were due to the cancer itself or to the inflammation that usually accompanies its development. Because sialylated hybrid structures were upregulated in sepsis samples, the downregulation of these structures in ovarian cancer is specific to the cancer itself and, therefore, could be used as a biomarker.

  20. Improving low-level plasma protein mass spectrometry-based detection for candidate biomarker discovery and validation

    Energy Technology Data Exchange (ETDEWEB)

    Page, Jason S.; Kelly, Ryan T.; Camp, David G.; Smith, Richard D.


    Methods. To improve the detection of low abundance protein candidate biomarker discovery and validation, particularly in complex biological fluids such as blood plasma, increased sensitivity is desired using mass spectrometry (MS)-based instrumentation. A key current limitation on the sensitivity of electrospray ionization (ESI) MS is due to the fact that many sample molecules in solution are never ionized, and the vast majority of the ions that are created are lost during transmission from atmospheric pressure to the low pressure region of the mass analyzer. Two key technologies, multi-nanoelectrospray emitters and the electrodynamic ion funnel have recently been developed and refined at Pacific Northwest National Laboratory (PNNL) to greatly improve the ionization and transmission efficiency of ESI MS based analyses. Multi-emitter based ESI enables the flow from a single source (typically a liquid chromatography [LC] column) to be divided among an array of emitters (Figure 1). The flow rate delivered to each emitter is thus reduced, allowing the well-documented benefits of nanoelectrospray 1 for both sensitivity and quantitation to be realized for higher flow rate separations. To complement the increased ionization efficiency afforded by multi-ESI, tandem electrodynamic ion funnels have also been developed at PNNL, and shown to greatly improve ion transmission efficiency in the ion source interface.2, 3 These technologies have been integrated into a triple quadrupole mass spectrometer for multiple reaction monitoring (MRM) of probable biomarker candidates in blood plasma and show promise for the identification of new species even at low level concentrations.

  1. Biomarker discovery in heterogeneous tissue samples -taking the in-silico deconfounding approach

    Directory of Open Access Journals (Sweden)

    Parida Shreemanta K


    Full Text Available Abstract Background For heterogeneous tissues, such as blood, measurements of gene expression are confounded by relative proportions of cell types involved. Conclusions have to rely on estimation of gene expression signals for homogeneous cell populations, e.g. by applying micro-dissection, fluorescence activated cell sorting, or in-silico deconfounding. We studied feasibility and validity of a non-negative matrix decomposition algorithm using experimental gene expression data for blood and sorted cells from the same donor samples. Our objective was to optimize the algorithm regarding detection of differentially expressed genes and to enable its use for classification in the difficult scenario of reversely regulated genes. This would be of importance for the identification of candidate biomarkers in heterogeneous tissues. Results Experimental data and simulation studies involving noise parameters estimated from these data revealed that for valid detection of differential gene expression, quantile normalization and use of non-log data are optimal. We demonstrate the feasibility of predicting proportions of constituting cell types from gene expression data of single samples, as a prerequisite for a deconfounding-based classification approach. Classification cross-validation errors with and without using deconfounding results are reported as well as sample-size dependencies. Implementation of the algorithm, simulation and analysis scripts are available. Conclusions The deconfounding algorithm without decorrelation using quantile normalization on non-log data is proposed for biomarkers that are difficult to detect, and for cases where confounding by varying proportions of cell types is the suspected reason. In this case, a deconfounding ranking approach can be used as a powerful alternative to, or complement of, other statistical learning approaches to define candidate biomarkers for molecular diagnosis and prediction in biomedicine, in

  2. High-resolution taxonomic profiling of the subgingival microbiome for biomarker discovery and periodontitis diagnosis. (United States)

    Szafranski, Szymon P; Wos-Oxley, Melissa L; Vilchez-Vargas, Ramiro; Jáuregui, Ruy; Plumeier, Iris; Klawonn, Frank; Tomasch, Jürgen; Meisinger, Christa; Kühnisch, Jan; Sztajer, Helena; Pieper, Dietmar H; Wagner-Döbler, Irene


    The oral microbiome plays a key role for caries, periodontitis, and systemic diseases. A method for rapid, high-resolution, robust taxonomic profiling of subgingival bacterial communities for early detection of periodontitis biomarkers would therefore be a useful tool for individualized medicine. Here, we used Illumina sequencing of the V1-V2 and V5-V6 hypervariable regions of the 16S rRNA gene. A sample stratification pipeline was developed in a pilot study of 19 individuals, 9 of whom had been diagnosed with chronic periodontitis. Five hundred twenty-three operational taxonomic units (OTUs) were obtained from the V1-V2 region and 432 from the V5-V6 region. Key periodontal pathogens like Porphyromonas gingivalis, Treponema denticola, and Tannerella forsythia could be identified at the species level with both primer sets. Principal coordinate analysis identified two outliers that were consistently independent of the hypervariable region and method of DNA extraction used. The linear discriminant analysis (LDA) effect size algorithm (LEfSe) identified 80 OTU-level biomarkers of periodontitis and 17 of health. Health- and periodontitis-related clusters of OTUs were identified using a connectivity analysis, and the results confirmed previous studies with several thousands of samples. A machine learning algorithm was developed which was trained on all but one sample and then predicted the diagnosis of the left-out sample (jackknife method). Using a combination of the 10 best biomarkers, 15 of 17 samples were correctly diagnosed. Training the algorithm on time-resolved community profiles might provide a highly sensitive tool to detect the onset of periodontitis.

  3. The role of quantitative mass spectrometry in the discovery of pancreatic cancer biomarkers for translational science. (United States)

    Ansari, Daniel; Aronsson, Linus; Sasor, Agata; Welinder, Charlotte; Rezeli, Melinda; Marko-Varga, György; Andersson, Roland


    In the post-genomic era, it has become evident that genetic changes alone are not sufficient to understand most disease processes including pancreatic cancer. Genome sequencing has revealed a complex set of genetic alterations in pancreatic cancer such as point mutations, chromosomal losses, gene amplifications and telomere shortening that drive cancerous growth through specific signaling pathways. Proteome-based approaches are important complements to genomic data and provide crucial information of the target driver molecules and their post-translational modifications. By applying quantitative mass spectrometry, this is an alternative way to identify biomarkers for early diagnosis and personalized medicine. We review the current quantitative mass spectrometric technologies and analyses that have been developed and applied in the last decade in the context of pancreatic cancer. Examples of candidate biomarkers that have been identified from these pancreas studies include among others, asporin, CD9, CXC chemokine ligand 7, fibronectin 1, galectin-1, gelsolin, intercellular adhesion molecule 1, insulin-like growth factor binding protein 2, metalloproteinase inhibitor 1, stromal cell derived factor 4, and transforming growth factor beta-induced protein. Many of these proteins are involved in various steps in pancreatic tumor progression including cell proliferation, adhesion, migration, invasion, metastasis, immune response and angiogenesis. These new protein candidates may provide essential information for the development of protein diagnostics and targeted therapies. We further argue that new strategies must be advanced and established for the integration of proteomic, transcriptomic and genomic data, in order to enhance biomarker translation. Large scale studies with meta data processing will pave the way for novel and unexpected correlations within pancreatic cancer, that will benefit the patient, with targeted treatment.

  4. In vitro biomarker discovery in the parasitic flatworm Fasciola hepatica for monitoring chemotherapeutic treatment

    Directory of Open Access Journals (Sweden)

    Russell M. Morphew


    Full Text Available The parasitic flatworm Fasciola hepatica is a global food security risk. With no vaccines, the sustainability of triclabendazole (TCBZ is threatened by emerging resistance. F. hepatica excretory/secretory (ES products can be detected in host faeces and used to estimate TCBZ success and failure. However, there are no faecal based molecular diagnostics dedicated to assessing drug failure or resistance to TCBZ in the field. Utilising in vitro maintenance and sub-proteomic approaches two TCBZ stress ES protein response fingerprints were identified: markers of non-killing and lethal doses. This study provides candidate protein/peptide biomarkers to validate for detection of TCBZ failure and resistance.

  5. Biomarker Discovery for Early Detection of Hepatocellular Carcinoma in Hepatitis C–infected Patients* (United States)

    Mustafa, Mehnaz G.; Petersen, John R.; Ju, Hyunsu; Cicalese, Luca; Snyder, Ned; Haidacher, Sigmund J.; Denner, Larry; Elferink, Cornelis


    Chronic hepatic disease damages the liver, and the resulting wound-healing process leads to liver fibrosis and the subsequent development of cirrhosis. The leading cause of hepatic fibrosis and cirrhosis is infection with hepatitis C virus (HCV), and of the patients with HCV-induced cirrhosis, 2% to 5% develop hepatocellular carcinoma (HCC), with a survival rate of 7%. HCC is one of the leading causes of cancer-related death worldwide, and the poor survival rate is largely due to late-stage diagnosis, which makes successful intervention difficult, if not impossible. The lack of sensitive and specific diagnostic tools and the urgent need for early-stage diagnosis prompted us to discover new candidate biomarkers for HCV and HCC. We used aptamer-based fractionation technology to reduce serum complexity, differentially labeled samples (six HCV and six HCC) with fluorescent dyes, and resolved proteins in pairwise two-dimensional difference gel electrophoresis. DeCyder software was used to identify differentially expressed proteins and spots picked, and MALDI-MS/MS was used to determine that ApoA1 was down-regulated by 22% (p < 0.004) in HCC relative to HCV. Differential expression quantified via two-dimensional difference gel electrophoresis was confirmed by means of 18O/16O stable isotope differential labeling with LC-MS/MS zoom scans. Technically independent confirmation was demonstrated by triple quadrupole LC-MS/MS selected reaction monitoring (SRM) assays with three peptides specific to human ApoA1 (DLATVYVDVLK, WQEEMELYR, and VSFLSALEEYTK) using 18O/16O-labeled samples and further verified with AQUA peptides as internal standards for quantification. In 50 patient samples (24 HCV and 26 HCC), all three SRM assays yielded highly similar differential expression of ApoA1 in HCC and HCV patients. These results validated the SRM assays, which were independently confirmed by Western blotting. Thus, ApoA1 is a candidate member of an SRM biomarker panel for early diagnosis

  6. Novel Altered Region for Biomarker Discovery in Hepatocellular Carcinoma (HCC Using Whole Genome SNP Array

    Directory of Open Access Journals (Sweden)

    Esraa M. Hashem


    Full Text Available cancer represents one of the greatest medical causes of mortality. The majority of Hepatocellular carcinoma arises from the accumulation of genetic abnormalities, and possibly induced by exterior etiological factors especially HCV and HBV infections. There is a need for new tools to analysis the large sum of data to present relevant genetic changes that may be critical for both understanding how cancers develop and determining how they could ultimately be treated. Gene expression profiling may lead to new biomarkers that may help develop diagnostic accuracy for detecting Hepatocellular carcinoma. In this work, statistical technique (discrete stationary wavelet transform for detection of copy number alternations to analysis high-density single-nucleotide polymorphism array of 30 cell lines on specific chromosomes, which are frequently detected in Hepatocellular carcinoma have been proposed. The results demonstrate the feasibility of whole-genome fine mapping of copy number alternations via high-density single-nucleotide polymorphism genotyping, Results revealed that a novel altered chromosomal region is discovered; region amplification (4q22.1 have been detected in 22 out of 30-Hepatocellular carcinoma cell lines (73%. This region strike, AFF1 and DSPP, tumor suppressor genes. This finding has not previously reported to be involved in liver carcinogenesis; it can be used to discover a new HCC biomarker, which helps in a better understanding of hepatocellular carcinoma.

  7. Enhanced Biosensor Platforms for Detecting the Atherosclerotic Biomarker VCAM1 Based on Bioconjugation with Uniformly Oriented VCAM1-Targeting Nanobodies (United States)

    Ta, Duy Tien; Guedens, Wanda; Vranken, Tom; Vanschoenbeek, Katrijn; Steen Redeker, Erik; Michiels, Luc; Adriaensens, Peter


    Surface bioconjugation of biomolecules has gained enormous attention for developing advanced biomaterials including biosensors. While conventional immobilization (by physisorption or covalent couplings using the functional groups of the endogenous amino acids) usually results in surfaces with low activity, reproducibility and reusability, the application of methods that allow for a covalent and uniformly oriented coupling can circumvent these limitations. In this study, the nanobody targeting Vascular Cell Adhesion Molecule-1 (NbVCAM1), an atherosclerotic biomarker, is engineered with a C-terminal alkyne function via Expressed Protein Ligation (EPL). Conjugation of this nanobody to azidified silicon wafers and Biacore™ C1 sensor chips is achieved via Copper(I)-catalyzed azide-alkyne cycloaddition (CuAAC) “click” chemistry to detect VCAM1 binding via ellipsometry and surface plasmon resonance (SPR), respectively. The resulting surfaces, covered with uniformly oriented nanobodies, clearly show an increased antigen binding affinity, sensitivity, detection limit, quantitation limit and reusability as compared to surfaces prepared by random conjugation. These findings demonstrate the added value of a combined EPL and CuAAC approach as it results in strong control over the surface orientation of the nanobodies and an improved detecting power of their targets—a must for the development of advanced miniaturized, multi-biomarker biosensor platforms. PMID:27399790

  8. A Supramolecular Sensing Platform for Phosphate Anions and an Anthrax Biomarker in a Microfluidic Device

    NARCIS (Netherlands)

    Eker, Bilge; Yilmaz, Mahmut Deniz; Schlautmann, Stefan; Gardeniers, Johannes G.E.; Huskens, Jurriaan


    A supramolecular platform based on self-assembled monolayers (SAMs) has been implemented in a microfluidic device. The system has been applied for the sensing of two different analyte types: biologically relevant phosphate anions and aromatic carboxylic acids, which are important for anthrax detecti

  9. Evaluating the potential of a novel oral lesion exudate collection method coupled with mass spectrometry-based proteomics for oral cancer biomarker discovery

    Directory of Open Access Journals (Sweden)

    Kooren Joel A


    Full Text Available Abstract Introduction Early diagnosis of Oral Squamous Cell Carcinoma (OSCC increases the survival rate of oral cancer. For early diagnosis, molecular biomarkers contained in samples collected non-invasively and directly from at-risk oral premalignant lesions (OPMLs would be ideal. Methods In this pilot study we evaluated the potential of a novel method using commercial PerioPaper absorbent strips for non-invasive collection of oral lesion exudate material coupled with mass spectrometry-based proteomics for oral cancer biomarker discovery. Results Our evaluation focused on three core issues. First, using an "on-strip" processing method, we found that protein can be isolated from exudate samples in amounts compatible with large-scale mass spectrometry-based proteomic analysis. Second, we found that the OPML exudate proteome was distinct from that of whole saliva, while being similar to the OPML epithelial cell proteome, demonstrating the fidelity of our exudate collection method. Third, in a proof-of-principle study, we identified numerous, inflammation-associated proteins showing an expected increase in abundance in OPML exudates compared to healthy oral tissue exudates. These results demonstrate the feasibility of identifying differentially abundant proteins from exudate samples, which is essential for biomarker discovery studies. Conclusions Collectively, our findings demonstrate that our exudate collection method coupled with mass spectrometry-based proteomics has great potential for transforming OSCC biomarker discovery and clinical diagnostics assay development.

  10. Blood diagnostic biomarkers for major depressive disorder using multiplex DNA methylation profiles: discovery and validation. (United States)

    Numata, Shusuke; Ishii, Kazuo; Tajima, Atsushi; Iga, Jun-ichi; Kinoshita, Makoto; Watanabe, Shinya; Umehara, Hidehiro; Fuchikami, Manabu; Okada, Satoshi; Boku, Shuken; Hishimoto, Akitoyo; Shimodera, Shinji; Imoto, Issei; Morinobu, Shigeru; Ohmori, Tetsuro


    Aberrant DNA methylation in the blood of patients with major depressive disorder (MDD) has been reported in several previous studies. However, no comprehensive studies using medication-free subjects with MDD have been conducted. Furthermore, the majority of these previous studies has been limited to the analysis of the CpG sites in CpG islands (CGIs) in the gene promoter regions. The main aim of the present study is to identify DNA methylation markers that distinguish patients with MDD from non-psychiatric controls. Genome-wide DNA methylation profiling of peripheral leukocytes was conducted in two set of samples, a discovery set (20 medication-free patients with MDD and 19 controls) and a replication set (12 medication-free patients with MDD and 12 controls), using Infinium HumanMethylation450 BeadChips. Significant diagnostic differences in DNA methylation were observed at 363 CpG sites in the discovery set. All of these loci demonstrated lower DNA methylation in patients with MDD than in the controls, and most of them (85.7%) were located in the CGIs in the gene promoter regions. We were able to distinguish patients with MDD from the control subjects with high accuracy in the discriminant analysis using the top DNA methylation markers. We also validated these selected DNA methylation markers in the replication set. Our results indicate that multiplex DNA methylation markers may be useful for distinguishing patients with MDD from non-psychiatric controls.

  11. A multiplexable, microfluidic platform for the rapid quantitation of a biomarker panel for early ovarian cancer detection at the point-of-care. (United States)

    Shadfan, Basil H; Simmons, Archana R; Simmons, Glennon W; Ho, Andy; Wong, Jorge; Lu, Karen H; Bast, Robert C; McDevitt, John T


    Point-of-care (POC) diagnostic platforms have the potential to enable low-cost, large-scale screening. As no single biomarker is shed by all ovarian cancers, multiplexed biomarker panels promise improved sensitivity and specificity to address the unmet need for early detection of ovarian cancer. We have configured the programmable bio-nano-chip (p-BNC)-a multiplexable, microfluidic, modular platform-to quantify a novel multi-marker panel comprising CA125, HE4, MMP-7, and CA72-4. The p-BNC is a bead-based immunoanalyzer system with a credit-card-sized footprint that integrates automated sample metering, bubble and debris removal, reagent storage and waste disposal, permitting POC analysis. Multiplexed p-BNC immunoassays demonstrated high specificity, low cross-reactivity, low limits of detection suitable for early detection, and a short analysis time of 43 minutes. Day-to-day variability, a critical factor for longitudinally monitoring biomarkers, ranged between 5.4% and 10.5%, well below the biologic variation for all four markers. Biomarker concentrations for 31 late-stage sera correlated well (R(2) = 0.71 to 0.93 for various biomarkers) with values obtained on the Luminex platform. In a 31 patient cohort encompassing early- and late-stage ovarian cancers along with benign and healthy controls, the multiplexed p-BNC panel was able to distinguish cases from controls with 68.7% sensitivity at 80% specificity. Utility for longitudinal biomarker monitoring was demonstrated with prediagnostic plasma from 2 cases and 4 controls. Taken together, the p-BNC shows strong promise as a diagnostic tool for large-scale screening that takes advantage of faster results and lower costs while leveraging possible improvement in sensitivity and specificity from biomarker panels.

  12. Differential expression profiling of serum proteins and metabolites for biomarker discovery (United States)

    Roy, Sushmita Mimi; Anderle, Markus; Lin, Hua; Becker, Christopher H.


    A liquid chromatography-mass spectrometry (LC-MS) proteomics and metabolomics platform is presented for quantitative differential expression analysis. Proteome profiles obtained from 1.5 [mu]L of human serum show ~5000 de-isotoped and quantifiable molecular ions. Approximately 1500 metabolites are observed from 100 [mu]L of serum. Quantification is based on reproducible sample preparation and linear signal intensity as a function of concentration. The platform is validated using human serum, but is generally applicable to all biological fluids and tissues. The median coefficient of variation (CV) for ~5000 proteomic and ~1500 metabolomic molecular ions is approximately 25%. For the case of C-reactive protein, results agree with quantification by immunoassay. The independent contributions of two sources of variance, namely sample preparation and LC-MS analysis, are respectively quantified as 20.4 and 15.1% for the proteome, and 19.5 and 13.5% for the metabolome, for median CV values. Furthermore, biological diversity for ~20 healthy individuals is estimated by measuring the variance of ~6500 proteomic and metabolomic molecular ions in sera for each sample; the median CV is 22.3% for the proteome and 16.7% for the metabolome. Finally, quantitative differential expression profiling is applied to a clinical study comparing healthy individuals and rheumatoid arthritis (RA) patients.

  13. Integrating medicinal chemistry, organic/combinatorial chemistry, and computational chemistry for the discovery of selective estrogen receptor modulators with Forecaster, a novel platform for drug discovery. (United States)

    Therrien, Eric; Englebienne, Pablo; Arrowsmith, Andrew G; Mendoza-Sanchez, Rodrigo; Corbeil, Christopher R; Weill, Nathanael; Campagna-Slater, Valérie; Moitessier, Nicolas


    As part of a large medicinal chemistry program, we wish to develop novel selective estrogen receptor modulators (SERMs) as potential breast cancer treatments using a combination of experimental and computational approaches. However, one of the remaining difficulties nowadays is to fully integrate computational (i.e., virtual, theoretical) and medicinal (i.e., experimental, intuitive) chemistry to take advantage of the full potential of both. For this purpose, we have developed a Web-based platform, Forecaster, and a number of programs (e.g., Prepare, React, Select) with the aim of combining computational chemistry and medicinal chemistry expertise to facilitate drug discovery and development and more specifically to integrate synthesis into computer-aided drug design. In our quest for potent SERMs, this platform was used to build virtual combinatorial libraries, filter and extract a highly diverse library from the NCI database, and dock them to the estrogen receptor (ER), with all of these steps being fully automated by computational chemists for use by medicinal chemists. As a result, virtual screening of a diverse library seeded with active compounds followed by a search for analogs yielded an enrichment factor of 129, with 98% of the seeded active compounds recovered, while the screening of a designed virtual combinatorial library including known actives yielded an area under the receiver operating characteristic (AU-ROC) of 0.78. The lead optimization proved less successful, further demonstrating the challenge to simulate structure activity relationship studies.

  14. A novel compact mass detection platform for the open access (OA) environment in drug discovery and early development. (United States)

    Gao, Junling; Ceglia, Scott S; Jones, Michael D; Simeone, Jennifer; Antwerp, John Van; Zhang, Li-Kang; Ross, Charles W; Helmy, Roy


    A new 'compact mass detector' co-developed with an instrument manufacturer (Waters Corporation) as an interface for liquid chromatography (LC), specifically Ultra-high performance LC(®) (UPLC(®) or UHPLC) analysis was evaluated as a potential new Open Access (OA) LC-MS platform in the Drug Discovery and Early Development space. This new compact mass detector based platform was envisioned to provide increased reliability and speed while exhibiting significant cost, noise, and footprint reductions. The new detector was evaluated in batch mode (typically 1-3 samples per run) to monitor reactions and check purity, as well as in High Throughput Screening (HTS) mode to run 24, 48, and 96 well plates. The latter workflows focused on screening catalysis conditions, process optimization, and library work. The objective of this investigation was to assess the performance, reliability, and flexibility of the compact mass detector in the OA setting for a variety of applications. The compact mass detector results were compared to those obtained by current OA LC-MS systems, and the capabilities and benefits of the compact mass detector in the open access setting for chemists in the drug discovery and development space are demonstrated.

  15. NMR metabolic fingerprints of murine melanocyte and melanoma cell lines: application to biomarker discovery (United States)

    Santana-Filho, Arquimedes Paixão de; Jacomasso, Thiago; Riter, Daniel Suss; Barison, Andersson; Iacomini, Marcello; Winnischofer, Sheila Maria Brochado; Sassaki, Guilherme Lanzi


    Melanoma is the most aggressive type of skin cancer and efforts to improve the diagnosis of this neoplasia are largely based on the use of cell lines. Metabolomics is currently undergoing great advancements towards its use to screening for disease biomarkers. Although NMR metabolomics includes both 1D and 2D methodologies, there is a lack of data in the literature regarding heteronuclear 2D NMR assignments of the metabolome from eukaryotic cell lines. The present study applied NMR-based metabolomics strategies to characterize aqueous and lipid extracts from murine melanocytes and melanoma cell lines with distinct tumorigenic potential, successfully obtaining fingerprints of the metabolites from the extracts of the cell lines by means of 2D NMR HSQC correlation maps. Relative amounts of the identified metabolites were compared between the 4 cell lines. Multivariate analysis of 1H NMR data was able not only to differentiate the melanocyte cell line from the tumorigenic ones but also distinguish among the 3 tumorigenic cell lines. We also investigated the effects of mitogenic agents, and found that they can markedly influence the metabolome of the melanocyte cell line, resembling the pattern of most proliferative cell lines. PMID:28198377

  16. Applying bioinformatics to proteomics: is machine learning the answer to biomarker discovery for PD and MSA? (United States)

    Mattison, Hayley A; Stewart, Tessandra; Zhang, Jing


    Bioinformatics tools are increasingly being applied to proteomic data to facilitate the identification of biomarkers and classification of patients. In the June, 2012 issue, Ishigami et al. used principal component analysis (PCA) to extract features and support vector machine (SVM) to differentiate and classify cerebrospinal fluid (CSF) samples from two small cohorts of patients diagnosed with either Parkinson's disease (PD) or multiple system atrophy (MSA) based on differences in the patterns of peaks generated with matrix-assisted desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS). PCA accurately segregated patients with PD and MSA from controls when the cohorts were combined, but did not perform well when segregating PD from MSA. On the other hand, SVM, a machine learning classification model, correctly classified the samples from patients with early PD or MSA, and the peak at m/z 6250 was identified as a strong contributor to the ability of SVM to distinguish the proteomic profiles of either cohort when trained on one cohort. This study, while preliminary, provides promising results for the application of bioinformatics tools to proteomic data, an approach that may eventually facilitate the ability of clinicians to differentiate and diagnose closely related parkinsonian disorders.

  17. ARQiv-HTS, a versatile whole-organism screening platform enabling in vivo drug discovery at high-throughput rates. (United States)

    White, David T; Eroglu, Arife Unal; Wang, Guohua; Zhang, Liyun; Sengupta, Sumitra; Ding, Ding; Rajpurohit, Surendra K; Walker, Steven L; Ji, Hongkai; Qian, Jiang; Mumm, Jeff S


    The zebrafish has emerged as an important model for whole-organism small-molecule screening. However, most zebrafish-based chemical screens have achieved only mid-throughput rates. Here we describe a versatile whole-organism drug discovery platform that can achieve true high-throughput screening (HTS) capacities. This system combines our automated reporter quantification in vivo (ARQiv) system with customized robotics, and is termed 'ARQiv-HTS'. We detail the process of establishing and implementing ARQiv-HTS: (i) assay design and optimization, (ii) calculation of sample size and hit criteria, (iii) large-scale egg production, (iv) automated compound titration, (v) dispensing of embryos into microtiter plates, and (vi) reporter quantification. We also outline what we see as best practice strategies for leveraging the power of ARQiv-HTS for zebrafish-based drug discovery, and address technical challenges of applying zebrafish to large-scale chemical screens. Finally, we provide a detailed protocol for a recently completed inaugural ARQiv-HTS effort, which involved the identification of compounds that elevate insulin reporter activity. Compounds that increased the number of insulin-producing pancreatic beta cells represent potential new therapeutics for diabetic patients. For this effort, individual screening sessions took 1 week to conclude, and sessions were performed iteratively approximately every other day to increase throughput. At the conclusion of the screen, more than a half million drug-treated larvae had been evaluated. Beyond this initial example, however, the ARQiv-HTS platform is adaptable to almost any reporter-based assay designed to evaluate the effects of chemical compounds in living small-animal models. ARQiv-HTS thus enables large-scale whole-organism drug discovery for a variety of model species and from numerous disease-oriented perspectives.

  18. A practical platform for blood biomarker study by using global gene expression profiling of peripheral whole blood.

    Directory of Open Access Journals (Sweden)

    Ze Tian

    Full Text Available BACKGROUND: Although microarray technology has become the most common method for studying global gene expression, a plethora of technical factors across the experiment contribute to the variable of genome gene expression profiling using peripheral whole blood. A practical platform needs to be established in order to obtain reliable and reproducible data to meet clinical requirements for biomarker study. METHODS AND FINDINGS: We applied peripheral whole blood samples with globin reduction and performed genome-wide transcriptome analysis using Illumina BeadChips. Real-time PCR was subsequently used to evaluate the quality of array data and elucidate the mode in which hemoglobin interferes in gene expression profiling. We demonstrated that, when applied in the context of standard microarray processing procedures, globin reduction results in a consistent and significant increase in the quality of beadarray data. When compared to their pre-globin reduction counterparts, post-globin reduction samples show improved detection statistics, lowered variance and increased sensitivity. More importantly, gender gene separation is remarkably clearer in post-globin reduction samples than in pre-globin reduction samples. Our study suggests that the poor data obtained from pre-globin reduction samples is the result of the high concentration of hemoglobin derived from red blood cells either interfering with target mRNA binding or giving the pseudo binding background signal. CONCLUSION: We therefore recommend the combination of performing globin mRNA reduction in peripheral whole blood samples and hybridizing on Illumina BeadChips as the practical approach for biomarker study.

  19. Knowledge Discovery for Smart Grid Operation, Control, and Situation Awareness -- A Big Data Visualization Platform

    Energy Technology Data Exchange (ETDEWEB)

    Gu, Yi; Jiang, Huaiguang; Zhang, Yingchen; Zhang, Jun Jason; Gao, Tianlu; Muljadi, Eduard


    In this paper, a big data visualization platform is designed to discover the hidden useful knowledge for smart grid (SG) operation, control and situation awareness. The spawn of smart sensors at both grid side and customer side can provide large volume of heterogeneous data that collect information in all time spectrums. Extracting useful knowledge from this big-data poll is still challenging. In this paper, the Apache Spark, an open source cluster computing framework, is used to process the big-data to effectively discover the hidden knowledge. A high-speed communication architecture utilizing the Open System Interconnection (OSI) model is designed to transmit the data to a visualization platform. This visualization platform uses Google Earth, a global geographic information system (GIS) to link the geological information with the SG knowledge and visualize the information in user defined fashion. The University of Denver's campus grid is used as a SG test bench and several demonstrations are presented for the proposed platform.

  20. A high-throughput O-glycopeptide discovery platform for seromic profiling

    DEFF Research Database (Denmark)

    Blixt, Ola; Cló, Emiliano; Nudelman, Aaron Samuel;


    Biomarker microarrays are becoming valuable tools for serological screening of disease-associated autoantibodies. Post-translational modifications (PTMs) such as glycosylation extend the range of protein function, and a variety of glycosylated proteins are known to be altered in disease progressi...... for serological screening. As proof-of-concept, we have demonstrated that MUC1 glycopeptides could be assembled and used to detect autoantibodies in vaccine-induced disease-free breast cancer patients and in patients with confirmed disease at time of diagnosis....

  1. Interesting Spatio-Temporal Region Discovery Computations Over Gpu and Mapreduce Platforms (United States)

    McDermott, M.; Prasad, S. K.; Shekhar, S.; Zhou, X.


    Discovery of interesting paths and regions in spatio-temporal data sets is important to many fields such as the earth and atmospheric sciences, GIS, public safety and public health both as a goal and as a preliminary step in a larger series of computations. This discovery is usually an exhaustive procedure that quickly becomes extremely time consuming to perform using traditional paradigms and hardware and given the rapidly growing sizes of today's data sets is quickly outpacing the speed at which computational capacity is growing. In our previous work (Prasad et al., 2013a) we achieved a 50 times speedup over sequential using a single GPU. We were able to achieve near linear speedup over this result on interesting path discovery by using Apache Hadoop to distribute the workload across multiple GPU nodes. Leveraging the parallel architecture of GPUs we were able to drastically reduce the computation time of a 3-dimensional spatio-temporal interest region search on a single tile of normalized difference vegetative index for Saudi Arabia. We were further able to see an almost linear speedup in compute performance by distributing this workload across several GPUs with a simple MapReduce model. This increases the speed of processing 10 fold over the comparable sequential while simultaneously increasing the amount of data being processed by 384 fold. This allowed us to process the entirety of the selected data set instead of a constrained window.

  2. Drug discovery applications for KNIME: an open source data mining platform. (United States)

    Mazanetz, Michael P; Marmon, Robert J; Reisser, Catherine B T; Morao, Inaki


    Technological advances in high-throughput screening methods, combinatorial chemistry and the design of virtual libraries have evolved in the pursuit of challenging drug targets. Over the last two decades a vast amount of data has been generated within these fields and as a consequence data mining methods have been developed to extract key pieces of information from these large data pools. Much of this data is now available in the public domain. This has been helpful in the arena of drug discovery for both academic groups and for small to medium sized enterprises which previously would not have had access to such data resources. Commercial data mining software is sometimes prohibitively expensive and the alternate open source data mining software is gaining momentum in both academia and in industrial applications as the costs of research and development continue to rise. KNIME, the Konstanz Information Miner, has emerged as a leader in open source data mining tools. KNIME provides an integrated solution for the data mining requirements across the drug discovery pipeline through a visual assembly of data workflows drawing from an extensive repository of tools. This review will examine KNIME as an open source data mining tool and its applications in drug discovery.

  3. Harvest: an open platform for developing web-based biomedical data discovery and reporting applications. (United States)

    Pennington, Jeffrey W; Ruth, Byron; Italia, Michael J; Miller, Jeffrey; Wrazien, Stacey; Loutrel, Jennifer G; Crenshaw, E Bryan; White, Peter S


    Biomedical researchers share a common challenge of making complex data understandable and accessible as they seek inherent relationships between attributes in disparate data types. Data discovery in this context is limited by a lack of query systems that efficiently show relationships between individual variables, but without the need to navigate underlying data models. We have addressed this need by developing Harvest, an open-source framework of modular components, and using it for the rapid development and deployment of custom data discovery software applications. Harvest incorporates visualizations of highly dimensional data in a web-based interface that promotes rapid exploration and export of any type of biomedical information, without exposing researchers to underlying data models. We evaluated Harvest with two cases: clinical data from pediatric cardiology and demonstration data from the OpenMRS project. Harvest's architecture and public open-source code offer a set of rapid application development tools to build data discovery applications for domain-specific biomedical data repositories. All resources, including the OpenMRS demonstration, can be found at

  4. High-Throughput Screening Platform for the Discovery of New Immunomodulator Molecules from Natural Product Extract Libraries. (United States)

    Pérez Del Palacio, José; Díaz, Caridad; de la Cruz, Mercedes; Annang, Frederick; Martín, Jesús; Pérez-Victoria, Ignacio; González-Menéndez, Víctor; de Pedro, Nuria; Tormo, José R; Algieri, Francesca; Rodriguez-Nogales, Alba; Rodríguez-Cabezas, M Elena; Reyes, Fernando; Genilloud, Olga; Vicente, Francisca; Gálvez, Julio


    It is widely accepted that central nervous system inflammation and systemic inflammation play a significant role in the progression of chronic neurodegenerative diseases such as Alzheimer's disease and Parkinson's disease, neurotropic viral infections, stroke, paraneoplastic disorders, traumatic brain injury, and multiple sclerosis. Therefore, it seems reasonable to propose that the use of anti-inflammatory drugs might diminish the cumulative effects of inflammation. Indeed, some epidemiological studies suggest that sustained use of anti-inflammatory drugs may prevent or slow down the progression of neurodegenerative diseases. However, the anti-inflammatory drugs and biologics used clinically have the disadvantage of causing side effects and a high cost of treatment. Alternatively, natural products offer great potential for the identification and development of bioactive lead compounds into drugs for treating inflammatory diseases with an improved safety profile. In this work, we present a validated high-throughput screening approach in 96-well plate format for the discovery of new molecules with anti-inflammatory/immunomodulatory activity. The in vitro models are based on the quantitation of nitrite levels in RAW264.7 murine macrophages and interleukin-8 in Caco-2 cells. We have used this platform in a pilot project to screen a subset of 5976 noncytotoxic crude microbial extracts from the MEDINA microbial natural product collection. To our knowledge, this is the first report on an high-throughput screening of microbial natural product extracts for the discovery of immunomodulators.

  5. Application of a high throughput method of biomarker discovery to improvement of the EarlyCDT(®-Lung Test.

    Directory of Open Access Journals (Sweden)

    Isabel K Macdonald

    Full Text Available BACKGROUND: The National Lung Screening Trial showed that CT screening for lung cancer led to a 20% reduction in mortality. However, CT screening has a number of disadvantages including low specificity. A validated autoantibody assay is available commercially (EarlyCDT®-Lung to aid in the early detection of lung cancer and risk stratification in patients with pulmonary nodules detected by CT. Recent advances in high throughput (HTP cloning and expression methods have been developed into a discovery pipeline to identify biomarkers that detect autoantibodies. The aim of this study was to demonstrate the successful clinical application of this strategy to add to the EarlyCDT-Lung panel in order to improve its sensitivity and specificity (and hence positive predictive value, (PPV. METHODS AND FINDINGS: Serum from two matched independent cohorts of lung cancer patients were used (n = 100 and n = 165. Sixty nine proteins were initially screened on an abridged HTP version of the autoantibody ELISA using protein prepared on small scale by a HTP expression and purification screen. Promising leads were produced in shake flask culture and tested on the full assay. These results were analyzed in combination with those from the EarlyCDT-Lung panel in order to provide a set of re-optimized cut-offs. Five proteins that still displayed cancer/normal differentiation were tested for reproducibility and validation on a second batch of protein and a separate patient cohort. Addition of these proteins resulted in an improvement in the sensitivity and specificity of the test from 38% and 86% to 49% and 93% respectively (PPV improvement from 1 in 16 to 1 in 7. CONCLUSION: This is a practical example of the value of investing resources to develop a HTP technology. Such technology may lead to improvement in the clinical utility of the EarlyCDT--Lung test, and so further aid the early detection of lung cancer.

  6. Autoantibody profiling on human proteome microarray for biomarker discovery in cerebrospinal fluid and sera of neuropsychiatric lupus.

    Directory of Open Access Journals (Sweden)

    Chaojun Hu

    Full Text Available Autoantibodies in cerebrospinal fluid (CSF from patients with neuropsychiatric systemic lupus erythematosus (NPSLE may be potential biomarkers for prediction, diagnosis, or prognosis of NPSLE. We used a human proteome microarray with~17,000 unique full-length human proteins to investigate autoantibodies associated with NPSLE. Twenty-nine CSF specimens from 12 NPSLE, 7 non-NPSLE, and 10 control (non-systemic lupus erythematosuspatients were screened for NPSLE-associated autoantibodies with proteome microarrays. A focused autoantigen microarray of candidate NPSLE autoantigens was applied to profile a larger cohort of CSF with patient-matched sera. We identified 137 autoantigens associated with NPSLE. Ingenuity Pathway Analysis revealed that these autoantigens were enriched for functions involved in neurological diseases (score = 43.Anti-proliferating cell nuclear antigen (PCNA was found in the CSF of NPSLE and non-NPSLE patients. The positive rates of 4 autoantibodies in CSF specimens were significantly different between the SLE (i.e., NPSLE and non-NPSLE and control groups: anti-ribosomal protein RPLP0, anti-RPLP1, anti-RPLP2, and anti-TROVE2 (also known as anti-Ro/SS-A. The positive rate for anti-SS-A associated with NPSLE was higher than that for non-NPSLE (31.11% cf. 10.71%; P = 0.045.Further analysis showed that anti-SS-A in CSF specimens was related to neuropsychiatric syndromes of the central nervous system in SLE (P = 0.009. Analysis with Spearman's rank correlation coefficient indicated that the titers of anti-RPLP2 and anti-SS-A in paired CSF and serum specimens significantly correlated. Human proteome microarrays offer a powerful platform to discover novel autoantibodies in CSF samples. Anti-SS-A autoantibodies may be potential CSF markers for NPSLE.

  7. Automated in vivo platform for the discovery of functional food treatments of hypercholesterolemia.

    Directory of Open Access Journals (Sweden)

    Robert M Littleton

    Full Text Available The zebrafish is becoming an increasingly popular model system for both automated drug discovery and investigating hypercholesterolemia. Here we combine these aspects and for the first time develop an automated high-content confocal assay for treatments of hypercholesterolemia. We also create two algorithms for automated analysis of cardiodynamic data acquired by high-speed confocal microscopy. The first algorithm computes cardiac parameters solely from the frequency-domain representation of cardiodynamic data while the second uses both frequency- and time-domain data. The combined approach resulted in smaller differences relative to manual measurements. The methods are implemented to test the ability of a methanolic extract of the hawthorn plant (Crataegus laevigata to treat hypercholesterolemia and its peripheral cardiovascular effects. Results demonstrate the utility of these methods and suggest the extract has both antihypercholesterolemic and postitively inotropic properties.

  8. Application of proteomics in the discovery of candidate protein biomarkers in a Diabetes Autoantibody Standardization Program sample subset

    Energy Technology Data Exchange (ETDEWEB)

    Metz, Thomas O.; Qian, Weijun; Jacobs, Jon M.; Gritsenko, Marina A.; Moore, Ronald J.; Polpitiya, Ashoka D.; Monroe, Matthew E.; Camp, David G.; mueller, Patricia W.; Smith, Richard D.


    Objective. Before biomarkers predictive of type 1 diabetes can be evaluated in proficiency evaluations, they must be identified and validated in initial, exploratory studies. Hypothesis-driven comparative studies may be performed to identify candidate biomarkers but are limited to the current knowledge of metabolic, signaling, and inflammatory pathways in the context of type 1 diabetes. Alternatively, untargeted “-omics” approaches may be employed in profiling studies to identify candidate biomarkers of type 1 diabetes.

  9. A drug discovery platform: a simplified immunoassay for analyzing HIV protease activity. (United States)

    Kitidee, Kuntida; Nangola, Sawitree; Hadpech, Sudarat; Laopajon, Witida; Kasinrerk, Watchara; Tayapiwatana, Chatchai


    Although numerous methods for the determination of HIV protease (HIV-PR) activity have been described, new high-throughput assays are required for clinical and pharmaceutical applications due to the occurrence of resistant strains. In this study, a simple enzymatic immunoassay to identify HIV-PR activity was developed based on a Ni(2+)-immobilized His(6)-Matrix-Capsid substrate (H(6)MA-CA) is cleaved by HIV protease-His(6) (HIV-PRH(6)) which removes the CA domain and exposes the free C terminus of MA. Following this cleavage, two monoclonal antibodies specific for either the free C-terminal MA or CA epitope are used to quantify the proteolytic activity using a standard ELISA-based system. Specificity for detection of the HIV-PRH(6) activity was confirmed with addition of protease inhibitor (PI), lopinavir. In addition, the assay was able to detect an HIV-PR variant activity indicating that this assay is capable of assessing viral mutation affect HIV-PR activity. The efficacy of commercially available PIs and their 50% inhibitory concentration (IC(50)) were determined. This assay provides a high-throughput method for both validating the efficiency of new drugs in vitro and facilitating the discovery of new PIs. In addition, it could serve as a method for examining the influence of various mutations in HIV-PRs isolated from drug-resistant strains.

  10. Biomarkers in Veterinary Medicine. (United States)

    Myers, Michael J; Smith, Emily R; Turfle, Phillip G


    This article summarizes the relevant definitions related to biomarkers; reviews the general processes related to biomarker discovery and ultimate acceptance and use; and finally summarizes and reviews, to the extent possible, examples of the types of biomarkers used in animal species within veterinary clinical practice and human and veterinary drug development. We highlight opportunities for collaboration and coordination of research within the veterinary community and leveraging of resources from human medicine to support biomarker discovery and validation efforts for veterinary medicine.

  11. Deep-sequencing of microRNA associated with Alzheimer’s disease in biological fluids: From biomarker discovery to diagnostic practice

    Directory of Open Access Journals (Sweden)

    Lesley eCheng


    Full Text Available Diagnostic tools for neurodegenerative diseases such as Alzheimer's disease (AD currently involve subjective neuropsychological testing and specialised brain imaging techniques. While definitive diagnosis requires a pathological brain evaluation at autopsy, neurodegenerative changes are believed to begin years before the clinical presentation of cognitive decline. Therefore, there is an essential need for reliable biomarkers to aid in the early detection of disease in order to implement preventative strategies. microRNAs (miRNA are small non-coding RNA species that are involved in post-transcriptional gene regulation. Expression levels of miRNA’s have potential as diagnostic biomarkers as they are known to circulate and tissue specific profiles can be identified in a number of bodily fluids such as plasma, CSF and urine. Recent developments in deep sequencing technology present a viable approach to develop biomarker discovery pipelines in order to profile microRNA signatures in bodily fluids specific to neurodegenerative diseases. Here we review the potential use of microRNA deep sequencing in biomarker identification from biological fluids and its translation into clinical practice.

  12. Comparison of protein, microRNA, and mRNA yields using different methods of urinary exosome isolation for the discovery of kidney disease biomarkers. (United States)

    Alvarez, M Lucrecia; Khosroheidari, Mahdieh; Kanchi Ravi, Rupesh; DiStefano, Johanna K


    Urinary exosomes are 40-100 nm vesicles containing protein, mRNA, and microRNA that may serve as biomarkers of renal dysfunction and structural injury. Currently, there is a need for more sensitive and specific biomarkers of renal injury and disease progression. Here we sought to identify the best exosome isolation methods for both proteomic analysis and RNA profiling as a first step for biomarker discovery. We used six different protocols; three were based on ultracentrifugation, one used a nanomembrane concentrator-based approach, and two utilized a commercial exosome precipitation reagent. The highest yield of exosomes was obtained using a modified exosome precipitation protocol, which also yielded the highest quantities of microRNA and mRNA and, therefore, is ideal for subsequent RNA profiling. This method is likewise suitable for downstream proteomic analyses if an ultracentrifuge is not available and/or a large number of samples are to be processed. Two of the ultracentrifugation methods, however, are better options for exosome isolation if an ultracentrifuge is available and few samples will be processed for proteomic analysis. Thus, our modified exosome precipitation method is a simple, fast, highly scalable, and effective alternative for the isolation of exosomes, and may facilitate the identification of exosomal biomarkers from urine.

  13. A Sorghum Mutant Resource as an Efficient Platform for Gene Discovery in Grasses. (United States)

    Jiao, Yinping; Burke, John; Chopra, Ratan; Burow, Gloria; Chen, Junping; Wang, Bo; Hayes, Chad; Emendack, Yves; Ware, Doreen; Xin, Zhanguo


    Sorghum (Sorghum bicolor) is a versatile C4 crop and a model for research in family Poaceae. High-quality genome sequence is available for the elite inbred line BTx623, but functional validation of genes remains challenging due to the limited genomic and germplasm resources available for comprehensive analysis of induced mutations. In this study, we generated 6400 pedigreed M4 mutant pools from EMS-mutagenized BTx623 seeds through single-seed descent. Whole-genome sequencing of 256 phenotyped mutant lines revealed >1.8 million canonical EMS-induced mutations, affecting >95% of genes in the sorghum genome. The vast majority (97.5%) of the induced mutations were distinct from natural variations. To demonstrate the utility of the sequenced sorghum mutant resource, we performed reverse genetics to identify eight genes potentially affecting drought tolerance, three of which had allelic mutations and two of which exhibited exact cosegregation with the phenotype of interest. Our results establish that a large-scale resource of sequenced pedigreed mutants provides an efficient platform for functional validation of genes in sorghum, thereby accelerating sorghum breeding. Moreover, findings made in sorghum could be readily translated to other members of the Poaceae via integrated genomics approaches.

  14. An Isogenic Human ESC Platform for Functional Evaluation of Genome-wide-Association-Study-Identified Diabetes Genes and Drug Discovery. (United States)

    Zeng, Hui; Guo, Min; Zhou, Ting; Tan, Lei; Chong, Chi Nok; Zhang, Tuo; Dong, Xue; Xiang, Jenny Zhaoying; Yu, Albert S; Yue, Lixia; Qi, Qibin; Evans, Todd; Graumann, Johannes; Chen, Shuibing


    Genome-wide association studies (GWASs) have increased our knowledge of loci associated with a range of human diseases. However, applying such findings to elucidate pathophysiology and promote drug discovery remains challenging. Here, we created isogenic human ESCs (hESCs) with mutations in GWAS-identified susceptibility genes for type 2 diabetes. In pancreatic beta-like cells differentiated from these lines, we found that mutations in CDKAL1, KCNQ1, and KCNJ11 led to impaired glucose secretion in vitro and in vivo, coinciding with defective glucose homeostasis. CDKAL1 mutant insulin+ cells were also hypersensitive to glucolipotoxicity. A high-content chemical screen identified a candidate drug that rescued CDKAL1-specific defects in vitro and in vivo by inhibiting the FOS/JUN pathway. Our approach of a proof-of-principle platform, which uses isogenic hESCs for functional evaluation of GWAS-identified loci and identification of a drug candidate that rescues gene-specific defects, paves the way for precision therapy of metabolic diseases.

  15. A High-Throughput Screening Platform of Microbial Natural Products for the Discovery of Molecules with Antibiofilm Properties against Salmonella (United States)

    Paytubi, Sonia; de La Cruz, Mercedes; Tormo, Jose R.; Martín, Jesús; González, Ignacio; González-Menendez, Victor; Genilloud, Olga; Reyes, Fernando; Vicente, Francisca; Madrid, Cristina; Balsalobre, Carlos


    In this report, we describe a High-Throughput Screening (HTS) to identify compounds that inhibit biofilm formation or cause the disintegration of an already formed biofilm using the Salmonella Enteritidis 3934 strain. Initially, we developed a new methodology for growing Salmonella biofilms suitable for HTS platforms. The biomass associated with biofilm at the solid-liquid interface was quantified by staining both with resazurin and crystal violet, to detect living cells and total biofilm mass, respectively. For a pilot project, a subset of 1120 extracts from the Fundación MEDINA's collection was examined to identify molecules with antibiofilm activity. This is the first validated HTS assay of microbial natural product extracts which allows for the detection of four types of activities which are not mutually exclusive: inhibition of biofilm formation, detachment of the preformed biofilm and antimicrobial activity against planktonic cells or biofilm embedded cells. Currently, several extracts have been selected for further fractionation and purification of the active compounds. In one of the natural extracts patulin has been identified as a potent molecule with antimicrobial activity against both, planktonic cells and cells within the biofilm. These findings provide a proof of concept that the developed HTS can lead to the discovery of new natural compounds with antibiofilm activity against Salmonella and its possible use as an alternative to antimicrobial therapies and traditional disinfectants. PMID:28303128

  16. The Discovery of Novel Genomic, Transcriptomic, and Proteomic Biomarkers in Cardiovascular and Peripheral Vascular Disease: The State of the Art

    Directory of Open Access Journals (Sweden)

    Stefano de Franciscis


    Full Text Available Cardiovascular disease (CD and peripheral vascular disease (PVD are leading causes of mortality and morbidity in western countries and also responsible of a huge burden in terms of disability, functional decline, and healthcare costs. Biomarkers are measurable biological elements that reflect particular physiological or pathological states or predisposition towards diseases and they are currently widely studied in medicine and especially in CD. In this context, biomarkers can also be used to assess the severity or the evolution of several diseases, as well as the effectiveness of particular therapies. Genomics, transcriptomics, and proteomics have opened new windows on disease phenomena and may permit in the next future an effective development of novel diagnostic and prognostic medicine in order to better prevent or treat CD. This review will consider the current evidence of novel biomarkers with clear implications in the improvement of risk assessment, prevention strategies, and medical decision making in the field of CD.

  17. Cell surface profiling using high-throughput flow cytometry : a platform for biomarker discovery and analysis of cellular heterogeneity

    NARCIS (Netherlands)

    Gedye, Craig A; Hussain, Ali; Paterson, Joshua; Smrke, Alannah; Saini, Harleen; Sirskyj, Danylo; Pereira, Keira; Lobo, Nazleen; Stewart, Jocelyn; Go, Christopher; Ho, Jenny; Medrano, Mauricio; Hyatt, Elzbieta; Yuan, Julie; Lauriault, Stevan; Meyer, Mona; Kondratyev, Maria; van den Beucken, Twan; Jewett, Michael; Dirks, Peter; Guidos, Cynthia J; Danska, Jayne; Wang, Jean; Wouters, Bradly; Neel, Benjamin; Rottapel, Robert; Ailles, Laurie E


    Cell surface proteins have a wide range of biological functions, and are often used as lineage-specific markers. Antibodies that recognize cell surface antigens are widely used as research tools, diagnostic markers, and even therapeutic agents. The ability to obtain broad cell surface protein profil

  18. Respiratory Toxicity Biomarkers (United States)

    The advancement in high throughput genomic, proteomic and metabolomic techniques have accelerated pace of lung biomarker discovery. A recent growth in the discovery of new lung toxicity/disease biomarkers have led to significant advances in our understanding of pathological proce...

  19. Proteome analysis of acute kidney injury - Discovery of new predominantly renal candidates for biomarker of kidney disease. (United States)

    Malagrino, Pamella Araujo; Venturini, Gabriela; Yogi, Patrícia Schneider; Dariolli, Rafael; Padilha, Kallyandra; Kiers, Bianca; Gois, Tamiris Carneiro; Cardozo, Karina Helena Morais; Carvalho, Valdemir Melechco; Salgueiro, Jéssica Silva; Girardi, Adriana Castello Costa; Titan, Silvia Maria de Oliveira; Krieger, José Eduardo; Pereira, Alexandre Costa


    The main bottleneck in studies aiming to identify novel biomarkers in acute kidney injury (AKI) has been the identification of markers that are organ and process specific. Here, we have used different tissues from a controlled porcine renal ischemia/reperfusion (I/R) model to identify new, predominantly renal biomarker candidates for kidney disease. Urine and serum samples were analyzed in pre-ischemia, ischemia (60min) and 4, 11 and 16h post-reperfusion, and renal cortex samples after 24h of reperfusion. Peptides were analyzed on the Q-Exactive™. In renal cortex proteome, we observed an increase in the synthesis of proteins in the ischemic kidney compared to the contralateral, highlighted by transcription factors and epithelial adherens junction proteins. Intersecting the set of proteins up- or down-regulated in the ischemic tissue with both serum and urine proteomes, we identified 6 proteins in the serum that may provide a set of targets for kidney injury. Additionally, we identified 49, being 4 predominantly renal, proteins in urine. As prove of concept, we validated one of the identified biomarkers, dipeptidyl peptidase IV, in a set of patients with diabetic nephropathy. In conclusion, we identified 55 systemic proteins, some of them predominantly renal, candidates for biomarkers of renal disease.

  20. An Integrated Analysis of Heterogeneous Drug Responses in Acute Myeloid Leukemia That Enables the Discovery of Predictive Biomarkers. (United States)

    Chen, Weihsu C; Yuan, Julie S; Xing, Yan; Mitchell, Amanda; Mbong, Nathan; Popescu, Andreea C; McLeod, Jessica; Gerhard, Gitte; Kennedy, James A; Bogdanoski, Goce; Lauriault, Stevan; Perdu, Sofie; Merkulova, Yulia; Minden, Mark D; Hogge, Donna E; Guidos, Cynthia; Dick, John E; Wang, Jean C Y


    Many promising new cancer drugs proceed through preclinical testing and early-phase trials only to fail in late-stage clinical testing. Thus, improved models that better predict survival outcomes and enable the development of biomarkers are needed to identify patients most likely to respond to and benefit from therapy. Here, we describe a comprehensive approach in which we incorporated biobanking, xenografting, and multiplexed phospho-flow (PF) cytometric profiling to study drug response and identify predictive biomarkers in acute myeloid leukemia (AML) patients. To test the efficacy of our approach, we evaluated the investigational JAK2 inhibitor fedratinib (FED) in 64 patient samples. FED robustly reduced leukemia in mouse xenograft models in 59% of cases and was also effective in limiting the protumorigenic activity of leukemia stem cells as shown by serial transplantation assays. In parallel, PF profiling identified FED-mediated reduction in phospho-STAT5 (pSTAT5) levels as a predictive biomarker of in vivo drug response with high specificity (92%) and strong positive predictive value (93%). Unexpectedly, another JAK inhibitor, ruxolitinib (RUX), was ineffective in 8 of 10 FED-responsive samples. Notably, this outcome could be predicted by the status of pSTAT5 signaling, which was unaffected by RUX treatment. Consistent with this observed discrepancy, PF analysis revealed that FED exerted its effects through multiple JAK2-independent mechanisms. Collectively, this work establishes an integrated approach for testing novel anticancer agents that captures the inherent variability of response caused by disease heterogeneity and in parallel, facilitates the identification of predictive biomarkers that can help stratify patients into appropriate clinical trials.

  1. Nonylphenol Toxicity Evaluation and Discovery of Biomarkers in Rat Urine by a Metabolomics Strategy through HPLC-QTOF-MS

    Directory of Open Access Journals (Sweden)

    Yan-Xin Zhang


    Full Text Available Nonylphenol (NP was quantified using liquid chromatography tandem mass spectrometry (LC-MS/MS in the urine and plasma of rats treated with 0, 50, and 250 mg/kg/day of NP for four consecutive days. A urinary metabolomic strategy was originally implemented by high performance liquid chromatography time of flight mass spectrometry (HPLC-QTOF-MS to explore the toxicological effects of NP and determine the overall alterations in the metabolite profiles so as to find potential biomarkers. It is essential to point out that from the observation, the metabolic data were clearly clustered and separated for the three groups. To further identify differentiated metabolites, multivariate analysis, including principal component analysis (PCA, orthogonal partial least-squares discriminant analysis (OPLS-DA, high-resolution MS/MS analysis, as well as searches of Metlin and Massbank databases, were conducted on a series of metabolites between the control and dose groups. Finally, five metabolites, including glycine, glycerophosphocholine, 5-hydroxytryptamine, malonaldehyde (showing an upward trend, and tryptophan (showing a downward trend, were identified as the potential urinary biomarkers of NP-induced toxicity. In order to validate the reliability of these potential biomarkers, an independent validation was performed by using the multiple reaction monitoring (MRM-based targeted approach. The oxidative stress reflected by urinary 8-oxo-deoxyguanosine (8-oxodG levels was elevated in individuals highly exposed to NP, supporting the hypothesis that mitochondrial dysfunction was a result of xenoestrogen accumulation. This study reveals a promising approach to find biomarkers to assist researchers in monitoring NP.

  2. 脂质组学在疾病生物标记物研究应用现状%Applications of lipidomics in disease biomarkers discovery

    Institute of Scientific and Technical Information of China (English)

    史蕾; 郭瑞臣; 魏春敏


    To clarify the lipid′s effects on diagnosis and treatment of dis-eases and to enhance the ability to predict the disease risks in advance, lipidomics focuses on the structures and functions of lipids and their me-tabolites.Common analytical methods include direct mass spectrometers ( shotgun lipidomics) or chromatography-mass spectrometers and nuclear magnetic resonance.Lipidomics plays an important role in early diagnosis of disease, biomarker discoveries, new drug development and system study.This article reviewed the applications of lipidomics in biomarkers discovery and the technical approaches in lipidome analysis.%脂质组学通过研究脂质的结构和功能及其在体内的代谢变化,明确其对疾病诊断和治疗的作用,以期提高疾病风险预测的能力。常用脂质组学分析方法包括直接质谱注入法(鸟枪法)、色谱质谱联用法和核磁共振法等。脂质组学在疾病早期诊断、生物标志物的发现、新药研发以及系统研究方面都发挥了很大作用。本文旨在介绍脂质组学在疾病生物标志物发现中的应用及其研究方法。

  3. A novel approach to the discovery of survival biomarkers in glioblastoma using a joint analysis of DNA methylation and gene expression. (United States)

    Smith, Ashley A; Huang, Yen-Tsung; Eliot, Melissa; Houseman, E Andres; Marsit, Carmen J; Wiencke, John K; Kelsey, Karl T


    Glioblastoma multiforme (GBM) is the most aggressive of all brain tumors, with a median survival of less than 1.5 years. Recently, epigenetic alterations were found to play key roles in both glioma genesis and clinical outcome, demonstrating the need to integrate genetic and epigenetic data in predictive models. To enhance current models through discovery of novel predictive biomarkers, we employed a genome-wide, agnostic strategy to specifically capture both methylation-directed changes in gene expression and alternative associations of DNA methylation with disease survival in glioma. Human GBM-associated DNA methylation, gene expression, IDH1 mutation status, and survival data were obtained from The Cancer Genome Atlas. DNA methylation loci and expression probes were paired by gene, and their subsequent association with survival was determined by applying an accelerated failure time model to previously published alternative and expression-based association equations. Significant associations were seen in 27 unique methylation/expression pairs with expression-based, alternative, and combinatorial associations observed (10, 13, and 4 pairs, respectively). The majority of the predictive DNA methylation loci were located within CpG islands, and all but three of the locus pairs were negatively correlated with survival. This finding suggests that for most loci, methylation/expression pairs are inversely related, consistent with methylation-associated gene regulatory action. Our results indicate that changes in DNA methylation are associated with altered survival outcome through both coordinated changes in gene expression and alternative mechanisms. Furthermore, our approach offers an alternative method of biomarker discovery using a priori gene pairing and precise targeting to identify novel sites for locus-specific therapeutic intervention.

  4. Use of the local false discovery rate for identification of metabolic biomarkers in rat urine following Genkwa Flos-induced hepatotoxicity.

    Directory of Open Access Journals (Sweden)

    Zuojing Li

    Full Text Available Metabolomics is concerned with characterizing the large number of metabolites present in a biological system using nuclear magnetic resonance (NMR and HPLC/MS (high-performance liquid chromatography with mass spectrometry. Multivariate analysis is one of the most important tools for metabolic biomarker identification in metabolomic studies. However, analyzing the large-scale data sets acquired during metabolic fingerprinting is a major challenge. As a posterior probability that the features of interest are not affected, the local false discovery rate (LFDR is a good interpretable measure. However, it is rarely used to when interrogating metabolic data to identify biomarkers. In this study, we employed the LFDR method to analyze HPLC/MS data acquired from a metabolomic study of metabolic changes in rat urine during hepatotoxicity induced by Genkwa flos (GF treatment. The LFDR approach was successfully used to identify important rat urine metabolites altered by GF-stimulated hepatotoxicity. Compared with principle component analysis (PCA, LFDR is an interpretable measure and discovers more important metabolites in an HPLC/MS-based metabolomic study.

  5. Discovery and validation of plasma biomarkers for major depressive disorder classification based on liquid chromatography-mass spectrometry. (United States)

    Liu, Xinyu; Zheng, Peng; Zhao, Xinjie; Zhang, Yuqing; Hu, Chunxiu; Li, Jia; Zhao, Jieyu; Zhou, Jingjing; Xie, Peng; Xu, Guowang


    Major depressive disorder (MDD) is a debilitating mental disease with a pronounced impact on the quality of life of many people; however, it is still difficult to diagnose MDD accurately. In this study, a nontargeted metabolomics approach based on ultra-high-performance liquid chromatography equipped with quadrupole time-of-flight mass spectrometry (UPLC-Q-TOF/MS) was used to find the differential metabolites in plasma samples from patients with MDD and healthy controls. Furthermore, a validation analysis focusing on the differential metabolites was performed in another batch of samples using a targeted approach based on the dynamic multiple reactions monitoring method. Levels of acyl carnitines, ether lipids, and tryptophan pronouncedly decreased, whereas LPCs, LPEs, and PEs markedly increased in MDD subjects as compared with the healthy controls. Disturbed pathways, mainly located in acyl carnitine metabolism, lipid metabolism, and tryptophan metabolism, were clearly brought to light in MDD subjects. The binary logistic regression result showed that carnitine C10:1, PE-O 36:5, LPE 18:1 sn-2, and tryptophan can be used as a combinational biomarker to distinguish not only moderate but also severe MDD from healthy control with good sensitivity and specificity. Our findings, on one hand, provide critical insight into the pathological mechanism of MDD and, on the other hand, supply a combinational biomarker to aid the diagnosis of MDD in clinical usage.

  6. Application of Holistic Liquid Chromatography-High Resolution Mass Spectrometry Based Urinary Metabolomics for Prostate Cancer Detection and Biomarker Discovery.

    Directory of Open Access Journals (Sweden)

    Tong Zhang

    Full Text Available Human exhibit wide variations in their metabolic profiles because of differences in genetic factors, diet and lifestyle. Therefore in order to detect metabolic differences between individuals robust analytical methods are required. A protocol was produced based on the use of Liquid Chromatography- High Resolution Mass Spectrometry (LC-HRMS in combination with orthogonal Hydrophilic Interaction (HILIC and Reversed Phase (RP liquid chromatography methods for the analysis of the urinary metabolome, which was then evaluated as a diagnostic tool for prostate cancer (a common but highly heterogeneous condition. The LC-HRMS method was found to be robust and exhibited excellent repeatability for retention times (0.9. In addition, using the receiver operator characteristics (ROC test, the area under curve (AUC for the combination of the four best characterised biomarker compounds was 0.896. The four biomarker compounds were also found to differ significantly (P<0.05 between an independent patient cohort and controls. This is the first time such a rigorous test has been applied to this type of model. If validated, the established protocol provides a robust approach with a potentially wide application to metabolite profiling of human biofluids in health and disease.

  7. In-depth cDNA Library Sequencing Provides Quantitative Gene Expression Profiling in Cancer Biomarker Discovery

    Institute of Scientific and Technical Information of China (English)

    Wanling Yang; Dingge Ying; Yu-Lung Lau


    procedures may allow detection of many expres-sion features for less abundant gene variants. With the reduction of sequencing cost and the emerging of new generation sequencing technology, in-depth sequencing of cDNA pools or libraries may represent a better and powerful tool in gene expression profiling and cancer biomarker detection. We also propose using sequence-specific subtraction to remove hundreds of the most abundant housekeeping genes to in-crease sequencing depth without affecting relative expression ratio of other genes, as transcripts from as few as 300 most abundantly expressed genes constitute about 20% of the total transcriptome. In-depth sequencing also represents a unique ad-vantage of detecting unknown forms of transcripts, such as alternative splicing variants, fusion genes, and regulatory RNAs, as well as detecting mutations and polymorphisms that may play important roles in disease pathogenesis.

  8. Metabolomic study of lipids in serum for biomarker discovery in Alzheimer's disease using direct infusion mass spectrometry. (United States)

    González-Domínguez, R; García-Barrera, T; Gómez-Ariza, J L


    In this study, we demonstrated the potential of direct infusion mass spectrometry for the lipidomic characterization of Alzheimer's disease. Serum samples were extracted for lipids recovery, and directly analyzed using an electrospray source. Metabolomic fingerprints were subjected to multivariate analysis in order to discriminate between groups of patients and healthy controls, and then some key-compounds were identified as possible markers of Alzheimer's disease. Major differences were found in lipids, although some low molecular weight metabolites also showed significant changes. Thus, important metabolic pathways involved in neurodegeneration could be studied on the basis of these perturbations, such as membrane breakdown (phospholipids and diacylglycerols), oxidative stress (prostaglandins, imidazole and histidine), alterations in neurotransmission systems (oleamide and putrescine) and hyperammonaemia (guanidine and arginine). Moreover, it is noteworthy that some of these potential biomarkers have not been previously described for Alzheimer's disease.

  9. Blood biomarker levels to aid discovery of cancer-related single-nucleotide polymorphisms: kallikreins and prostate cancer. (United States)

    Klein, Robert J; Halldén, Christer; Cronin, Angel M; Ploner, Alexander; Wiklund, Fredrik; Bjartell, Anders S; Stattin, Pär; Xu, Jianfeng; Scardino, Peter T; Offit, Kenneth; Vickers, Andrew J; Grönberg, Henrik; Lilja, Hans


    Polymorphisms associated with prostate cancer include those in three genes encoding major secretory products of the prostate: KLK2 (encoding kallikrein-related peptidase 2; hK2), KLK3 (encoding prostate-specific antigen; PSA), and MSMB (encoding beta-microseminoprotein). PSA and hK2, members of the kallikrein family, are elevated in sera of men with prostate cancer. In a comprehensive analysis that included sequencing of all coding, flanking, and 2 kb of putative promoter regions of all 15 kallikrein (KLK) genes spanning approximately 280 kb on chromosome 19q, we identified novel single-nucleotide polymorphisms (SNP) and genotyped 104 SNPs in 1,419 cancer cases and 736 controls in Cancer Prostate in Sweden 1, with independent replication in 1,267 cases and 901 controls in Cancer Prostate in Sweden 2. This verified prior associations of SNPs in KLK2 and in MSMB (but not in KLK3) with prostate cancer. Twelve SNPs in KLK2 and KLK3 were associated with levels of PSA forms or hK2 in plasma of control subjects. Based on our comprehensive approach, this is likely to represent all common KLK variants associated with these phenotypes. A T allele at rs198977 in KLK2 was associated with increased cancer risk and a striking decrease of hK2 levels in blood. We also found a strong interaction between rs198977 genotype and hK2 levels in blood in predicting cancer risk. Based on this strong association, we developed a model for predicting prostate cancer risk from standard biomarkers, rs198977 genotype, and rs198977 x hK2 interaction; this model had greater accuracy than did biomarkers alone (area under the receiver operating characteristic curve, 0.874 versus 0.866), providing proof in principle to clinical application for our findings.

  10. SELDI-TOF MS-based discovery of a biomarker in Cucumis sativus seeds exposed to CuO nanoparticles. (United States)

    Moon, Young-Sun; Park, Eun-Sil; Kim, Tae-Oh; Lee, Hoi-Seon; Lee, Sung-Eun


    Metal oxide nanoparticles (NPs) can inhibit plant seed germination and root elongation via the release of metal ions. In the present study, two acute phytotoxicity tests, seed germination and root elongation tests, were conducted on cucumber seeds (Cucumis sativus) treated with bulk copper oxide (CuO) and CuO NPs. Two concentrations of bulk CuO and CuO NPs, 200 and 600ppm, were used to test the inhibition rate of root germination; both concentrations of bulk CuO weakly inhibited seed germination, whereas CuO NPs significantly inhibited germination, showing a low germination rate of 23.3% at 600ppm. Root elongation tests demonstrated that CuO NPs were much stronger inhibitors than bulk CuO. SELDI-TOF MS analysis showed that 34 proteins were differentially expressed in cucumber seeds after exposure to CuO NPs, with the expression patterns of at least 9 proteins highly differing from those in seeds treated with bulk CuO and in control plants. Therefore, these 9 proteins were used to identify CuO NP-specific biomarkers in cucumber plants exposed to CuO NPs. A 5977-m/z protein was the most distinguishable biomarker for determining phytotoxicity by CuO NPs. Principal component analysis (PCA) of the SELDI-TOF MS results showed variability in the modes of inhibitory action on cucumber seeds and roots. To our knowledge, this is the first study to demonstrate that the phytotoxic effect of metal oxide NPs on plants is not caused by the same mode of action as other toxins.

  11. Discovery and Validation of Prognostic Biomarker Models to Guide Triage among Adult Dengue Patients at Early Infection (United States)

    Tolfvenstam, Thomas; Thein, Tun-Linn; Naim, Ahmad Nazri Mohamed; Ling, Ling; Chow, Angelia; Chen, Mark I-Cheng; Ooi, Eng Eong; Leo, Yee Sin; Hibberd, Martin L.


    Background Dengue results in a significant public health burden in endemic regions. The World Health Organization (WHO) recommended the use of warning signs (WS) to stratify patients at risk of severe dengue disease in 2009. However, WS is limited in stratifying adult dengue patients at early infection (Day 1–3 post fever), who require close monitoring in hospitals to prevent severe dengue. The aim of this study is to identify and validate prognostic models, built with differentially expressed biomarkers, that enable the early identification of those with early dengue infection that require close clinical monitoring. Methods RNA microarray and protein assays were performed to identify differentially expressed biomarkers of severity among 92 adult dengue patients recruited at early infection from years 2005–2008. This comprised 47 cases who developed WS after first presentation and required hospitalization (WS+Hosp), as well as 45 controls who did not develop WS after first presentation and did not require hospitalization (Non-WS+Non-Hosp). Independent validation was conducted with 80 adult dengue patients recruited from years 2009–2012. Prognostic models were developed based on forward stepwise and backward elimination estimation, using multiple logistic regressions. Prognostic power was estimated by the area under the receiver operating characteristic curve (AUC). Results The WS+Hosp group had significantly higher viral load (Pdengue patients at early infection, with sensitivity and specificity up to 83% and 84%, respectively. These results were tested in the independent validation group, showing sensitivity and specificity up to 96% and 54.6%, respectively. Conclusions At early infection, adult dengue patients who later presented WS and require hospitalization have significantly different pathophysiology compared with patients who consistently presented no WS and / or require no hospitalization. The molecular prognostic models developed and validated here

  12. Off surface matrix based on-chip electrochemical biosensor platform for protein biomarker detection in undiluted serum. (United States)

    Arya, Sunil K; Kongsuphol, Patthara; Park, Mi Kyoung


    The manuscript describes a concept of using off surface matrix modified with capturing biomolecule for on-chip electrochemical biosensing. 3D matrix made by laser engraving of polymethyl methacrylate (PMMA) sheet as off surface matrix was integrated in very close vicinity of the electrode surface. Laser engraving and holes in PMMA along with spacing from surface provide fluidic channel and incubation chamber. Covalent binding of capturing biomolecule (anti-TNF-α antibody) on off-surface matrix was achieved via azide group activity of 4-fluoro-3-nitro-azidobenzene (FNAB), which act as cross-linker and further covalently binds to anti-TNF-α antibody via thermal reaction. Anti-TNF-α/FNAB/PMMA matrix was then integrated over comb structured gold electrode array based sensor chip. Separate surface modification followed by integration of sensor helped to prevent the sensor chip surface from fouling during functionalization. Nonspecific binding was prevented using starting block T20 (PBS). Results for estimating protein biomarker (TNF-α) in undiluted serum using Anti-TNF-α/FNAB/PMMA/Au reveal that system can detect TNF-α in 100pg/ml to 100ng/ml range with high sensitivity of 119nA/(ng/ml), with negligible interference from serum proteins and other cytokines. Thus, use of off surface matrix may provide the opportunity to electrochemically sense biomarkers sensitively to ng/ml range with negligible nonspecific binding and false signal in undiluted serum.

  13. A superior strategy for single-cell mutational screening via multiplex-targeted QPCR using the BioMark HD microfluidic platform. (United States)

    Li, Guangliang; Teng, Lisong


    A major challenge in cancer therapy lies in its complexity and heterogeneity, with increasing recognition of many tumor subtypes that have different biological characteristics and responses to therapies. To effectively address this challenge, personalized medicine has been the 'vogue' currently. Dissecting the detailed clonal architecture of cancer by cancer genomics, which holds the promise of personalized medicine, has significant clinical implications. Substantial advances have been made in DNA-based, high-throughput genomic technologies. However, current methods are still in its infancy, significantly limited by error rates, low cell throughput, high cost and labor intensive. The study under evaluation develops a superior strategy for a comprehensive interrogation of the complex genomics of cancer cells by using multiplex-targeted DNA amplification from flow-sorted single cells followed by high-throughput quantitative PCR using the BioMark HD microfluidic platform. The platform demonstrated a successful rate of approximately 75%, a highly efficient single-cell sorting rate of 96-98%, a high-throughput analysis of 200-300 leukemic cells, and was able to simultaneously detected chimeric fusion genes, copy number alterations and single-nucleotide variants in a single cell sample.

  14. Application of quantitative proteomic analysis using tandem mass tags for discovery and identification of novel biomarkers in periodontal disease. (United States)

    Tsuchida, Sachio; Satoh, Mamoru; Kawashima, Yusuke; Sogawa, Kazuyuki; Kado, Sayaka; Sawai, Setsu; Nishimura, Motoi; Ogita, Mayumi; Takeuchi, Yasuo; Kobyashi, Hiroaki; Aoki, Akira; Kodera, Yoshio; Matsushita, Kazuyuki; Izumi, Yuichi; Nomura, Fumio


    Periodontal disease is a bacterial infection that destroys the gingiva and surrounding tissues of the oral cavity. Gingival crevicular fluid (GCF) is extracted from the gingival sulcus and pocket. Analysis of biochemical markers in GCF, which predict the progression of periodontal disease, may facilitate disease diagnosis. However, no useful GCF biochemical markers with high sensitivity for detecting periodontal disease have been identified. Thus, the search for biochemical markers of periodontal disease is of continued interest in experimental and clinical periodontal disease research. Using tandem mass tag (TMT) labeling, we analyzed GCF samples from healthy subjects and patients with periodontal disease, and identified a total of 619 GCF proteins based on proteomic analysis. Of these, we focused on two proteins, matrix metalloproteinase (MMP)-9 and neutrophil gelatinase-associated lipocalin (LCN2), which are involved in the progression of periodontal disease. Western blot analysis revealed that the levels of MMP-9 and LCN2 were significantly higher in patients with periodontal disease than in healthy subjects. In addition, ELISA also detected significantly higher levels of LCN2 in patients with periodontal disease than in healthy subjects. Thus, LC-MS/MS analyses of GCF using TMT labeling led to the identification of LCN2, which may be a promising GCF biomarker for the detection of periodontal disease.

  15. An integrative data analysis platform for gene set analysis and knowledge discovery in a data warehouse framework. (United States)

    Chen, Yi-An; Tripathi, Lokesh P; Mizuguchi, Kenji


    Data analysis is one of the most critical and challenging steps in drug discovery and disease biology. A user-friendly resource to visualize and analyse high-throughput data provides a powerful medium for both experimental and computational biologists to understand vastly different biological data types and obtain a concise, simplified and meaningful output for better knowledge discovery. We have previously developed TargetMine, an integrated data warehouse optimized for target prioritization. Here we describe how upgraded and newly modelled data types in TargetMine can now survey the wider biological and chemical data space, relevant to drug discovery and development. To enhance the scope of TargetMine from target prioritization to broad-based knowledge discovery, we have also developed a new auxiliary toolkit to assist with data analysis and visualization in TargetMine. This toolkit features interactive data analysis tools to query and analyse the biological data compiled within the TargetMine data warehouse. The enhanced system enables users to discover new hypotheses interactively by performing complicated searches with no programming and obtaining the results in an easy to comprehend output format. Database URL:

  16. Biomarkers of safety and immune protection for genetically modified live attenuated Leishmania vaccines against visceral leishmaniasis-Discovery and implications

    Directory of Open Access Journals (Sweden)

    Sreenivas eGannavaram


    Full Text Available Despite intense efforts there is no safe and efficacious vaccine against visceral leishmaniasis, which is fatal and endemic in many tropical countries. A major shortcoming in the vaccine development against blood borne parasitic agents such as Leishmania is the inadequate predictive power of the early immune responses mounted in the host against the experimental vaccines. Often immune correlates derived from in-bred animal models do not yield immune markers of protection that can be readily extrapolated to humans. The limited efficacy of vaccines based on DNA, sub-unit, heat killed parasites has led to the realization that acquisition of durable immunity against the protozoan parasites requires a controlled infection with a live attenuated organism. Recent success of irradiated malaria parasites as a vaccine candidate further strengthens this approach to vaccination. We developed several gene deletion mutants in L. donovani as potential live attenuated vaccines and reported extensively on the immunogenicity of LdCentrin1 deleted mutant in mice, hamsters and dogs. Additional limited studies using genetically modified live attenuated Leishmania parasites as vaccine candidates have been reported. However, for the live attenuated parasite vaccines, the primary barrier against widespread use remains the absence of clear biomarkers associated with protection and safety. Recent studies in evaluation of vaccines e.g., influenza and yellow fever vaccines, using systems biology tools demonstrated the power of such strategies in understanding the immunological mechanisms that underpin a protective phenotype. Applying similar tools in isolated human tissues such as PBMCs from healthy individuals infected with live attenuated parasites such as LdCen1-/- in vitro followed by human microarray hybridization experiments will enable us to understand how early vaccine-induced gene expression profiles and the associated immune responses are coordinately regulated

  17. Discovery and analysis of time delay sources in the USGS personal computer data collection platform (PCDCP) system (United States)

    White, Timothy C.; Sauter, Edward A.; Stewart, Duff C.


    Intermagnet is an international oversight group which exists to establish a global network for geomagnetic observatories. This group establishes data standards and standard operating procedures for members and prospective members. Intermagnet has proposed a new One-Second Data Standard, for that emerging geomagnetic product. The standard specifies that all data collected must have a time stamp accuracy of ±10 milliseconds of the top-of-the-second Coordinated Universal Time. Therefore, the U.S. Geological Survey Geomagnetism Program has designed and executed several tests on its current data collection system, the Personal Computer Data Collection Platform. Tests are designed to measure the time shifts introduced by individual components within the data collection system, as well as to measure the time shift introduced by the entire Personal Computer Data Collection Platform. Additional testing designed for Intermagnet will be used to validate further such measurements. Current results of the measurements showed a 5.0–19.9 millisecond lag for the vertical channel (Z) of the Personal Computer Data Collection Platform and a 13.0–25.8 millisecond lag for horizontal channels (H and D) of the collection system. These measurements represent a dynamically changing delay introduced within the U.S. Geological Survey Personal Computer Data Collection Platform.

  18. False-Positive Rate Determination of Protein Target Discovery using a Covalent Modification- and Mass Spectrometry-Based Proteomics Platform (United States)

    Strickland, Erin C.; Geer, M. Ariel; Hong, Jiyong; Fitzgerald, Michael C.


    Detection and quantitation of protein-ligand binding interactions is important in many areas of biological research. Stability of proteins from rates of oxidation (SPROX) is an energetics-based technique for identifying the proteins targets of ligands in complex biological mixtures. Knowing the false-positive rate of protein target discovery in proteome-wide SPROX experiments is important for the correct interpretation of results. Reported here are the results of a control SPROX experiment in which chemical denaturation data is obtained on the proteins in two samples that originated from the same yeast lysate, as would be done in a typical SPROX experiment except that one sample would be spiked with the test ligand. False-positive rates of 1.2-2.2 % and manassantin A. The impact of ion purity in the tandem mass spectral analyses and of background oxidation on the false-positive rate of protein target discovery using SPROX is also discussed.

  19. False Positive Rate Determination of Protein Target Discovery using a Covalent Modification- and Mass Spectrometry-Based Proteomics Platform (United States)

    Strickland, Erin C.; Geer, M. Ariel; Hong, Jiyong; Fitzgerald, Michael C.


    Detection and quantitation of protein-ligand binding interactions is important in many areas of biological research. The Stability of Proteins from Rates of Oxidation (SPROX) technique is an energetics-based technique for identifying the proteins targets of ligands in complex biological mixtures. Knowing the false positive rate of protein target discovery in proteome-wide SPROX experiments is important for the correct interpretation of results. Reported here are the results of a control SPROX experiment in which chemical denaturation data is obtained on the proteins in two samples that originated from the same yeast lysate, as would be done in a typical SPROX experiment except that one sample would be spiked with the test ligand. False positive rates of 1.2–2.2% and manassantin A. The impact of ion purity in the tandem mass spectral analyses and of background oxidation on the false positive rate of protein target discovery using SPROX is also discussed. PMID:24114261

  20. Discovery of colorectal cancer PIK3CA mutation as potential predictive biomarker: power and promise of molecular pathological epidemiology. (United States)

    Ogino, S; Lochhead, P; Giovannucci, E; Meyerhardt, J A; Fuchs, C S; Chan, A T


    Regular use of aspirin reduces incidence and mortality of various cancers, including colorectal cancer. Anticancer effect of aspirin represents one of the 'Provocative Questions' in cancer research. Experimental and clinical studies support a carcinogenic role for PTGS2 (cyclooxygenase-2), which is an important enzymatic mediator of inflammation, and a target of aspirin. Recent 'molecular pathological epidemiology' (MPE) research has shown that aspirin use is associated with better prognosis and clinical outcome in PIK3CA-mutated colorectal carcinoma, suggesting somatic PIK3CA mutation as a molecular biomarker that predicts response to aspirin therapy. The PI3K (phosphatidylinositol-4,5-bisphosphonate 3-kinase) enzyme has a pivotal role in the PI3K-AKT signaling pathway. Activating PIK3CA oncogene mutations are observed in various malignancies including breast cancer, ovarian cancer, brain tumor, hepatocellular carcinoma, lung cancer and colon cancer. The prevalence of PIK3CA mutations increases continuously from rectal to cecal cancers, supporting the 'colorectal continuum' paradigm, and an important interplay of gut microbiota and host immune/inflammatory reaction. MPE represents an interdisciplinary integrative science, conceptually defined as 'epidemiology of molecular heterogeneity of disease'. As exposome and interactome vary from person to person and influence disease process, each disease process is unique (the unique disease principle). Therefore, MPE concept and paradigm can extend to non-neoplastic diseases including diabetes mellitus, cardiovascular diseases, metabolic diseases, and so on. MPE research opportunities are currently limited by paucity of tumor molecular data in the existing large-scale population-based studies. However, genomic, epigenomic and molecular pathology testings (for example, analyses for microsatellite instability, MLH1 promoter CpG island methylation, and KRAS and BRAF mutations in colorectal tumors) are becoming routine

  1. Quick identification of xanthine oxidase inhibitor and antioxidant from Erycibe obtusifolia by a drug discovery platform composed of multiple mass spectrometric platforms and thin-layer chromatography bioautography. (United States)

    Chen, Zhiyong; Tao, Hongxun; Liao, Liping; Zhang, Zijia; Wang, Zhengtao


    As a final step of the purine metabolism process, xanthine oxidase catalyzes the oxidation of hypoxanthine and xanthine into uric acid. Our research has demonstrated that Erycibe obtusifolia has xanthine oxidase inhibitory properties. The purpose of this paper is to describe a new strategy based on a combination of multiple mass spectrometric platforms and thin-layer chromatography bioautography for effectively screening the xanthine oxidase inhibitory and antioxidant properties of E. obtusifolia. This strategy was accomplished through the following steps. (i) Separate the extract of E. obtusifolia into fractions by an autopurification system controlled by liquid chromatography with mass spectrometry. (ii) Determine the active fractions of E. obtusifolia by thin-layer chromatography bioautography. (iii) Identify the structure of the main active compounds with the information provided by direct analysis in real time mass spectrometry. (iv) Calculate the IC50 value of each compound against xanthine oxidase using high-performance liquid chromatography. Using the caulis of E. obtusifolia as the experimental material, seven target peaks were screened out as xanthine oxidase inhibitors or antioxidants. Our screening strategy allows for rapid analysis of small molecules with almost no sample preparation and can be completed within a week, making it a useful assay to identify unstable compounds and provide the empirical foundation for E. obtusifolia as a natural remedy for gout and oxidative-stress-related diseases.

  2. Novel technologies and emerging biomarkers for personalized cancer immunotherapy. (United States)

    Yuan, Jianda; Hegde, Priti S; Clynes, Raphael; Foukas, Periklis G; Harari, Alexandre; Kleen, Thomas O; Kvistborg, Pia; Maccalli, Cristina; Maecker, Holden T; Page, David B; Robins, Harlan; Song, Wenru; Stack, Edward C; Wang, Ena; Whiteside, Theresa L; Zhao, Yingdong; Zwierzina, Heinz; Butterfield, Lisa H; Fox, Bernard A


    The culmination of over a century's work to understand the role of the immune system in tumor control has led to the recent advances in cancer immunotherapies that have resulted in durable clinical responses in patients with a variety of malignancies. Cancer immunotherapies are rapidly changing traditional treatment paradigms and expanding the therapeutic landscape for cancer patients. However, despite the current success of these therapies, not all patients respond to immunotherapy and even those that do often experience toxicities. Thus, there is a growing need to identify predictive and prognostic biomarkers that enhance our understanding of the mechanisms underlying the complex interactions between the immune system and cancer. Therefore, the Society for Immunotherapy of Cancer (SITC) reconvened an Immune Biomarkers Task Force to review state of the art technologies, identify current hurdlers, and make recommendations for the field. As a product of this task force, Working Group 2 (WG2), consisting of international experts from academia and industry, assembled to identify and discuss promising technologies for biomarker discovery and validation. Thus, this WG2 consensus paper will focus on the current status of emerging biomarkers for immune checkpoint blockade therapy and discuss novel technologies as well as high dimensional data analysis platforms that will be pivotal for future biomarker research. In addition, this paper will include a brief overview of the current challenges with recommendations for future biomarker discovery.

  3. Semantic Registration and Discovery System of Subsystems and Services within an Interoperable Coordination Platform in Smart Cities. (United States)

    Rubio, Gregorio; Martínez, José Fernán; Gómez, David; Li, Xin


    Smart subsystems like traffic, Smart Homes, the Smart Grid, outdoor lighting, etc. are built in many urban areas, each with a set of services that are offered to citizens. These subsystems are managed by self-contained embedded systems. However, coordination and cooperation between them are scarce. An integration of these systems which truly represents a "system of systems" could introduce more benefits, such as allowing the development of new applications and collective optimization. The integration should allow maximum reusability of available services provided by entities (e.g., sensors or Wireless Sensor Networks). Thus, it is of major importance to facilitate the discovery and registration of available services and subsystems in an integrated way. Therefore, an ontology-based and automatic system for subsystem and service registration and discovery is presented. Using this proposed system, heterogeneous subsystems and services could be registered and discovered in a dynamic manner with additional semantic annotations. In this way, users are able to build customized applications across different subsystems by using available services. The proposed system has been fully implemented and a case study is presented to show the usefulness of the proposed method.

  4. Semantic Registration and Discovery System of Subsystems and Services within an Interoperable Coordination Platform in Smart Cities

    Directory of Open Access Journals (Sweden)

    Gregorio Rubio


    Full Text Available Smart subsystems like traffic, Smart Homes, the Smart Grid, outdoor lighting, etc. are built in many urban areas, each with a set of services that are offered to citizens. These subsystems are managed by self-contained embedded systems. However, coordination and cooperation between them are scarce. An integration of these systems which truly represents a “system of systems” could introduce more benefits, such as allowing the development of new applications and collective optimization. The integration should allow maximum reusability of available services provided by entities (e.g., sensors or Wireless Sensor Networks. Thus, it is of major importance to facilitate the discovery and registration of available services and subsystems in an integrated way. Therefore, an ontology-based and automatic system for subsystem and service registration and discovery is presented. Using this proposed system, heterogeneous subsystems and services could be registered and discovered in a dynamic manner with additional semantic annotations. In this way, users are able to build customized applications across different subsystems by using available services. The proposed system has been fully implemented and a case study is presented to show the usefulness of the proposed method.

  5. Semantic Registration and Discovery System of Subsystems and Services within an Interoperable Coordination Platform in Smart Cities (United States)

    Rubio, Gregorio; Martínez, José Fernán; Gómez, David; Li, Xin


    Smart subsystems like traffic, Smart Homes, the Smart Grid, outdoor lighting, etc. are built in many urban areas, each with a set of services that are offered to citizens. These subsystems are managed by self-contained embedded systems. However, coordination and cooperation between them are scarce. An integration of these systems which truly represents a “system of systems” could introduce more benefits, such as allowing the development of new applications and collective optimization. The integration should allow maximum reusability of available services provided by entities (e.g., sensors or Wireless Sensor Networks). Thus, it is of major importance to facilitate the discovery and registration of available services and subsystems in an integrated way. Therefore, an ontology-based and automatic system for subsystem and service registration and discovery is presented. Using this proposed system, heterogeneous subsystems and services could be registered and discovered in a dynamic manner with additional semantic annotations. In this way, users are able to build customized applications across different subsystems by using available services. The proposed system has been fully implemented and a case study is presented to show the usefulness of the proposed method. PMID:27347965

  6. Ratiometric fluorescence transduction by hybridization after isothermal amplification for determination of zeptomole quantities of oligonucleotide biomarkers with a paper-based platform and camera-based detection

    Energy Technology Data Exchange (ETDEWEB)

    Noor, M. Omair; Hrovat, David [Chemical Sensors Group, Department of Chemical and Physical Sciences, University of Toronto Mississauga, 3359 Mississauga Road, Mississauga, ON L5L 1C6 (Canada); Moazami-Goudarzi, Maryam [Department of Cell and Systems Biology, University of Toronto Mississauga, 3359 Mississauga Road, Mississauga, ON L5L 1C6 (Canada); Espie, George S. [Department of Cell and Systems Biology, University of Toronto Mississauga, 3359 Mississauga Road, Mississauga, ON L5L 1C6 (Canada); Department of Biology, University of Toronto Mississauga, 3359 Mississauga Road, Mississauga, ON L5L 1C6 (Canada); Krull, Ulrich J., E-mail: [Chemical Sensors Group, Department of Chemical and Physical Sciences, University of Toronto Mississauga, 3359 Mississauga Road, Mississauga, ON L5L 1C6 (Canada)


    Highlights: • Solid-phase QD-FRET transduction of isothermal tHDA amplicons on paper substrates. • Ratiometric QD-FRET transduction improves assay precision and lowers the detection limit. • Zeptomole detection limit by an iPad camera after isothermal amplification. • Tunable assay sensitivity by immobilizing different amounts of QD–probe bioconjugates. - Abstract: Paper is a promising platform for the development of decentralized diagnostic assays owing to the low cost and ease of use of paper-based analytical devices (PADs). It can be challenging to detect on PADs very low concentrations of nucleic acid biomarkers of lengths as used in clinical assays. Herein we report the use of thermophilic helicase-dependent amplification (tHDA) in combination with a paper-based platform for fluorescence detection of probe-target hybridization. Paper substrates were patterned using wax printing. The cellulosic fibers were chemically derivatized with imidazole groups for the assembly of the transduction interface that consisted of immobilized quantum dot (QD)–probe oligonucleotide conjugates. Green-emitting QDs (gQDs) served as donors with Cy3 as the acceptor dye in a fluorescence resonance energy transfer (FRET)-based transduction method. After probe-target hybridization, a further hybridization event with a reporter sequence brought the Cy3 acceptor dye in close proximity to the surface of immobilized gQDs, triggering a FRET sensitized emission that served as an analytical signal. Ratiometric detection was evaluated using both an epifluorescence microscope and a low-cost iPad camera as detectors. Addition of the tHDA method for target amplification to produce sequences of ∼100 base length allowed for the detection of zmol quantities of nucleic acid targets using the two detection platforms. The ratiometric QD-FRET transduction method not only offered improved assay precision, but also lowered the limit of detection of the assay when compared with the non

  7. High-throughput screening platform for natural product-based drug discovery against 3 neglected tropical diseases: human African trypanosomiasis, leishmaniasis, and Chagas disease. (United States)

    Annang, F; Pérez-Moreno, G; García-Hernández, R; Cordon-Obras, C; Martín, J; Tormo, J R; Rodríguez, L; de Pedro, N; Gómez-Pérez, V; Valente, M; Reyes, F; Genilloud, O; Vicente, F; Castanys, S; Ruiz-Pérez, L M; Navarro, M; Gamarro, F; González-Pacanowska, D


    African trypanosomiasis, leishmaniasis, and Chagas disease are 3 neglected tropical diseases for which current therapeutic interventions are inadequate or toxic. There is an urgent need to find new lead compounds against these diseases. Most drug discovery strategies rely on high-throughput screening (HTS) of synthetic chemical libraries using phenotypic and target-based approaches. Combinatorial chemistry libraries contain hundreds of thousands of compounds; however, they lack the structural diversity required to find entirely novel chemotypes. Natural products, in contrast, are a highly underexplored pool of unique chemical diversity that can serve as excellent templates for the synthesis of novel, biologically active molecules. We report here a validated HTS platform for the screening of microbial extracts against the 3 diseases. We have used this platform in a pilot project to screen a subset (5976) of microbial extracts from the MEDINA Natural Products library. Tandem liquid chromatography-mass spectrometry showed that 48 extracts contain potentially new compounds that are currently undergoing de-replication for future isolation and characterization. Known active components included actinomycin D, bafilomycin B1, chromomycin A3, echinomycin, hygrolidin, and nonactins, among others. The report here is, to our knowledge, the first HTS of microbial natural product extracts against the above-mentioned kinetoplastid parasites.

  8. Aspergillus nidulans as a platform for discovery and characterization of complex biosynthetic pathways

    DEFF Research Database (Denmark)

    Anyaogu, Diana Chinyere

    andfeed. Secondary metabolites therefore both have a positive and deleterious impact on the human health.The increase in available genome sequences of fungi has revealed that there is a large number of putativesecondary metabolite biosynthetic gene clusters to be discovered and potentially exploited...... of secondary metabolites and 2) Developing A. nidulans as a model systemfor protein production with human-like glycan structure.  The first part of this study resulted in the development of a method for the transfer and expression ofintact biosynthetic gene clusters to A. nidulans to facilitate pathway...... and product discovery. As proof ofconcept the biosynthetic gene cluster for production of the polyketide geodin was identified andtransferred from A. terreus to A. nidulans. The cluster was integrated in a well characterized locus in A.nidulans. Reconstitution of the cluster resulted in the production...

  9. Rapid, non-targeted discovery of biochemical transformation and biomarker candidates in oncovirus-infected cell lines using LAESI mass spectrometry. (United States)

    Shrestha, Bindesh; Sripadi, Prabhakar; Walsh, Callee M; Razunguzwa, Trust T; Powell, Matthew J; Kehn-Hall, Kylene; Kashanchi, Fatah; Vertes, Akos


    Finding insights into how viruses hijack metabolic processes and biomarkers for viral diseases often require hypotheses about target compounds and/or labelling techniques. Here we present a method based on laser ablation electrospray ionization mass spectrometry to rapidly identify potential protein and metabolite biomarkers of oncovirus infection in B lymphocytes.

  10. Dissecting the Syndrome of Schizophrenia: Progress toward Clinically Useful Biomarkers

    Directory of Open Access Journals (Sweden)

    Brian Dean


    Full Text Available The search for clinically useful biomarkers has been one of the holy grails of schizophrenia research. This paper will outline the evolving notion of biomarkers and then outline outcomes from a variety of biomarkers discovery strategies. In particular, the impact of high-throughput screening technologies on biomarker discovery will be highlighted and how new or improved technologies may allow the discovery of either diagnostic biomarkers for schizophrenia or biomarkers that will be useful in determining appropriate treatments for people with the disorder. History tells those involved in biomarker research that the discovery and validation of useful biomarkers is a long process and current progress must always be viewed in that light. However, the approval of the first biomarker screen with some value in predicting responsiveness to antipsychotic drugs suggests that biomarkers can be identified and that these biomarkers that will be useful in diagnosing and treating people with schizophrenia.

  11. Dissecting the Syndrome of Schizophrenia: Progress toward Clinically Useful Biomarkers. (United States)

    Dean, Brian


    The search for clinically useful biomarkers has been one of the holy grails of schizophrenia research. This paper will outline the evolving notion of biomarkers and then outline outcomes from a variety of biomarkers discovery strategies. In particular, the impact of high-throughput screening technologies on biomarker discovery will be highlighted and how new or improved technologies may allow the discovery of either diagnostic biomarkers for schizophrenia or biomarkers that will be useful in determining appropriate treatments for people with the disorder. History tells those involved in biomarker research that the discovery and validation of useful biomarkers is a long process and current progress must always be viewed in that light. However, the approval of the first biomarker screen with some value in predicting responsiveness to antipsychotic drugs suggests that biomarkers can be identified and that these biomarkers that will be useful in diagnosing and treating people with schizophrenia.

  12. Discovery, screening and evaluation of a plasma biomarker panel for subjects with psychological suboptimal health state using 1H-NMR-based metabolomics profiles (United States)

    Tian, Jun-sheng; Xia, Xiao-tao; Wu, Yan-fei; Zhao, Lei; Xiang, Huan; Du, Guan-hua; Zhang, Xiang; Qin, Xue-mei


    Individuals in the state of psychological suboptimal health keep increasing, only scales and questionnaires were used to diagnose in clinic under current conditions, and symptoms of high reliability and accuracy are destitute. Therefore, the noninvasive and precise laboratory diagnostic methods are needed. This study aimed to develop an objective method through screen potential biomarkers or a biomarker panel to facilitate the diagnosis in clinic using plasma metabolomics. Profiles were based on H-nuclear magnetic resonance (1H-NMR) metabolomics techniques combing with multivariate statistical analysis. Furthermore, methods of correlation analysis with Metaboanalyst 3.0 for selecting a biomarker panel, traditional Chinese medicine (TCM) drug intervention for validating the close relations between the biomarker panel and the state and the receiver operating characteristic curves (ROC curves) analysis for evaluation of clinical diagnosis ability were carried out. 9 endogenous metabolites containing trimethylamine oxide (TMAO), glutamine, N-acetyl-glycoproteins, citrate, tyrosine, phenylalanine, isoleucine, valine and glucose were identified and considered as potential biomarkers. Then a biomarker panel consisting of phenylalanine, glutamine, tyrosine, citrate, N-acetyl-glycoproteins and TMAO was selected, which exhibited the highest area under the curve (AUC = 0.971). This study provided critical insight into the pathological mechanism of psychological suboptimal health and would supply a novel and valuable diagnostic method. PMID:27650680

  13. A Short Survey on the State of the Art in Architectures and Platforms for Large Scale Data Analysis and Knowledge Discovery from Data

    Energy Technology Data Exchange (ETDEWEB)

    Begoli, Edmon [ORNL


    Intended as a survey for practicing architects and researchers seeking an overview of the state-of-the-art architectures for data analysis, this paper provides an overview of the emerg- ing data management and analytic platforms including par- allel databases, Hadoop-based systems, High Performance Computing (HPC) platforms and platforms popularly re- ferred to as NoSQL platforms. Platforms are presented based on their relevance, analysis they support and the data organization model they support.

  14. Multiplexed homogeneous proximity ligation assays for high throughput protein biomarker research in serological material

    DEFF Research Database (Denmark)

    Lundberg, Martin; Thorsen, Stine Buch; Assarsson, Erika;


    A high throughput protein biomarker discovery tool has been developed based on multiplexed proximity ligation assays (PLA) in a homogeneous format in the sense of no washing steps. The platform consists of four 24-plex panels profiling 74 putative biomarkers with sub pM sensitivity each consuming...... only 1 micro Litre of human plasma sample. The system uses either matched monoclonal antibody pairs or the more readily available single batches of affinity purified polyclonal antibodies to generate the target specific reagents by covalently linking with unique nucleic acid sequences. These paired...

  15. Methodological and analytic considerations for blood biomarkers. (United States)

    Christenson, Robert H; Duh, Show-Hong


    Biomarkers typically evolve from a research setting to use in clinical care as evidence for their independent contribution to patient management accumulates. This evidence relies heavily on knowledge of the preanalytical, analytical, and postanalytical characteristics of the biomarker's measurement. For the preanalytical phase, considerations such specimen type, acceptable anticoagulants for blood samples, biologic variation and stability of the biomarker under various conditions are key. The analytical phase entails critical details for development and maintenance of assays having performance characteristics that are "fit for service" for the clinical application at hand. Often, these characteristics describe the ability to measure minute quantities in the biologic matrix used for measurement. Although techniques such as mass spectrometry are used effectively for biomarker discovery, routine quantification often relies on use of immunoassays; early in development, the most common immunoassay used is the enzyme-linked immunosorbent assay format. As biomarkers evolve successfully, they will be adapted to large main laboratory platforms or, depending on the need for speed, point-of-care devices. Users must pay particular attention to performance parameters of assays they are considering for clinical implementation. These parameters include the limit of blank, a term used to describe the limit of analytical noise for an assay; limit of detection, which describes the lowest concentration that can reliably be discriminated from analytical noise; and perhaps most importantly, the limit of quantitation, which is the lowest concentration at which a biomarker can be reliably measured within some predefined specifications for total analytical error that is based on clinical requirements of the test. The postanalytical phase involves reporting biomarker values, which includes reporting units, any normalization factors, and interpretation. Standardization, a process that

  16. Discovery of biomarkers for glycaemic deterioration before and after the onset of type 2 diabetes: rationale and design of the epidemiological studies within the IMI DIRECT Consortium

    DEFF Research Database (Denmark)

    Koivula, Robert W.; Heggie, Alison; Barnett, Anna


    biomarkers that: (1) predict the rate of glycaemic deterioration before and after type 2 diabetes onset; (2) predict the response to diabetes therapies; and (3) help stratify type 2 diabetes into clearly definable disease subclasses that can be treated more effectively than without stratification. This paper...

  17. Discovery and identification of serum potential biomarkers for pulmonary tuberculosis using iTRAQ-coupled two-dimensional LC-MS/MS. (United States)

    Xu, Dan-Dan; Deng, Dan-Feng; Li, Xiang; Wei, Li-Liang; Li, Yan-Yuan; Yang, Xiu-Yun; Yu, Wei; Wang, Chong; Jiang, Ting-Ting; Li, Zhong-Jie; Chen, Zhong-Liang; Zhang, Xing; Liu, Ji-Yan; Ping, Ze-Peng; Qiu, Yun-Qing; Li, Ji-Cheng


    Pulmonary tuberculosis (TB) caused by Mycobacterium tuberculosis is a chronic disease. Currently, there are no sufficiently validated biomarkers for early diagnosis of TB infection. In this study, a panel of potential serum biomarkers was identified between patients with pulmonary TB and healthy controls by using iTRAQ-coupled 2D LC-MS/MS technique. Among 100 differentially expressed proteins screened, 45 proteins were upregulated (>1.25-fold at p HABP2), and retinol-binding protein 4 (RBP4) was further confirmed using immunoblotting and ELISA analysis. By forward stepwise multivariate regression analysis, a panel of serum biomarkers including APOCII, CD5L, and RBP4 was obtained to form the disease diagnostic model. The receiver operation characteristic curve of the diagnostic model was 0.98 (sensitivity = 93.42%, specificity = 92.86%). In conclusion, APOCII, CD5L, HABP2, and RBP4 may be potential protein biomarkers of pulmonary TB. Our research provides useful data for early diagnosis of TB.

  18. IgY14 and SuperMix immunoaffinity separations coupled with liquid chromatography-mass spectrometry for human plasma proteomic biomarker discovery

    Energy Technology Data Exchange (ETDEWEB)

    Shi, Tujin; Zhou, Jianying; Gritsenko, Marina A.; Hossain, Mahmud; Camp, David G.; Smith, Richard D.; Qian, Weijun


    Interest in the application of advanced proteomics technologies to human blood plasma- or serum-based clinical samples for the purpose of discovering disease biomarkers continues to grow; however, the enormous dynamic range of protein concentrations in these types of samples (often >10 orders of magnitude) represents a significant analytical challenge, particularly for detecting low-abundance candidate biomarkers. In response, immunoaffinity separation methods for depleting multiple high- and moderate-abundance proteins have become key tools for enriching low-abundance proteins and enhancing detection of these proteins in plasma proteomics. Herein, we describe IgY14 and tandem IgY14-Supermix separation methods for removing 14 high-abundance and up to 60 moderate-abundance proteins, respectively, from human blood plasma and highlight their utility when combined with liquid chromatography-tandem mass spectrometry for interrogating the human plasma proteome.

  19. IgY14 and SuperMix immunoaffinity separations coupled with liquid chromatography-mass spectrometry for human plasma proteomics biomarker discovery. (United States)

    Shi, Tujin; Zhou, Jian-Ying; Gritsenko, Marina A; Hossain, Mahmud; Camp, David G; Smith, Richard D; Qian, Wei-Jun


    Interest in the application of advanced proteomics technologies to human blood plasma- or serum-based clinical samples for the purpose of discovering disease biomarkers continues to grow; however, the enormous dynamic range of protein concentrations in these types of samples (often >10 orders of magnitude) represents a significant analytical challenge, particularly for detecting low-abundance candidate biomarkers. In response, immunoaffinity separation methods for depleting multiple high- and moderate-abundance proteins have become key tools for enriching low-abundance proteins and enhancing detection of these proteins in plasma proteomics. Herein, we describe IgY14 and tandem IgY14-Supermix separation methods for removing 14 high-abundance and up to 60 moderate-abundance proteins, respectively, from human blood plasma and highlight their utility when combined with liquid chromatography-tandem mass spectrometry for interrogating the human plasma proteome.

  20. Metabolomics study with gas chromatography-mass spectrometry for predicting valproic acid-induced hepatotoxicity and discovery of novel biomarkers in rat urine. (United States)

    Lee, Min Sun; Jung, Byung Hwa; Chung, Bong Chul; Cho, Sung Hee; Kim, Ki Young; Kwon, Oh Seoung; Nugraha, Boya; Lee, Young-Joo


    Three different doses of valproic acid (20, 100, and 500 mg/kg/d) are administered orally to Sprague-Dawley rats for 5 days, and the feasibility of metabolomics with gas chromatography-mass spectrometry as a predictor of the hepatotoxicity of valproic acid is evaluated. Body weight is found to decrease with the 100-mg/kg/d dose and significantly decrease with the 500-mg/kg/d dose. Mean excreted urine volume is lowest in the 500-mg/kg/d group among all groups. The plasma level of alpha-glutathione-S-transferase, a sensitive and earlier biomarker for hepatotoxicity, increases significantly with administration of 100 and 500 mg/kg/d; however, there is not a significant difference in alpha-glutathione-S-transferase plasma levels between the control and 20-mg/kg/d groups. Clusters in partial least squares discriminant analysis score plots show similar patterns, with changes in physiological conditions and plasma levels of alpha-glutathione-S-transferase; the cluster for the control and 20-mg/kg/d groups does not clearly separate, but the clusters are separate for 100- and 500-mg/kg/d groups. A biomarker of hepatotoxicity, 8-hydroxy-2'-deoxyguanosine and octanoylcarnitine, is identified from nontargeted and targeted metabolic profiling. These results validate that metabolic profiling using gas chromatography-mass spectrometry could be a useful tool for finding novel biomarkers. Thus, a nontargeted metabolic profiling method is established to evaluate the hepatotoxicity of valproic acid and demonstrates proof-of-concept that metabolomic approach with gas chromatography-mass spectrometry has great potential for predicting valproic acid-induced hepatotoxicity and discovering novel biomarkers.

  1. Nanostructured optical microchips for cancer biomarker detection. (United States)

    Zhang, Tianhua; He, Yuan; Wei, Jianjun; Que, Long


    Herein we report the label-free detection of a cancer biomarker using newly developed arrayed nanostructured Fabry-Perot interferometer (FPI) microchips. Specifically, the prostate cancer biomarker free prostate-specific antigen (f-PSA) has been detected with a mouse anti-human PSA monoclonal antibody (mAb) as the receptor. Experiments found that the limit-of-detection of current nanostructured FPI microchip for f-PSA is about 10 pg/mL and the upper detection range for f-PSA can be dynamically changed by varying the amount of the PSA mAb immobilized on the sensing surface. The control experiments have also demonstrated that the immunoassay protocol used in the experiments shows excellent specificity and selectivity, suggesting the great potential to detect the cancer biomarkers at trace levels in complex biofluids. In addition, given its nature of low cost, simple-to-operation and batch fabrication capability, the arrayed nanostructured FPI microchip-based platform could provide an ideal technical tool for point-of-care diagnostics application and anticancer drug screen and discovery.

  2. Analysis of Serum Metabolic Profile by Ultra-performance Liquid Chromatography-mass Spectrometry for Biomarkers Discovery: Application in a Pilot Study to Discriminate Patients with Tuberculosis

    Directory of Open Access Journals (Sweden)

    Shuang Feng


    Full Text Available Background: Tuberculosis (TB is a chronic wasting inflammatory disease characterized by multisystem involvement, which can cause metabolic derangements in afflicted patients. Metabolic signatures have been exploited in the study of several diseases. However, the serum that is successfully used in TB diagnosis on the basis of metabolic profiling is not by much. Methods: Orthogonal partial least-squares discriminant analysis was capable of distinguishing TB patients from both healthy subjects and patients with conditions other than TB. Therefore, TB-specific metabolic profiling was established. Clusters of potential biomarkers for differentiating TB active from non-TB diseases were identified using Mann-Whitney U-test. Multiple logistic regression analysis of metabolites was calculated to determine the suitable biomarker group that allows the efficient differentiation of patients with TB active from the control subjects. Results: From among 271 participants, 12 metabolites were found to contribute to the distinction between the TB active group and the control groups. These metabolites were mainly involved in the metabolic pathways of the following three biomolecules: Fatty acids, amino acids, and lipids. The receiver operating characteristic curves of 3D, 7D, and 11D-phytanic acid, behenic acid, and threoninyl-γ-glutamate exhibited excellent efficiency with area under the curve (AUC values of 0.904 (95% confidence interval [CI]: 0863-0.944, 0.93 (95% CI: 0.893-0.966, and 0.964 (95% CI: 00.941-0.988, respectively. The largest and smallest resulting AUCs were 0.964 and 0.720, indicating that these biomarkers may be involved in the disease mechanisms. The combination of lysophosphatidylcholine (18:0, behenic acid, threoninyl-γ-glutamate, and presqualene diphosphate was used to represent the most suitable biomarker group for the differentiation of patients with TB active from the control subjects, with an AUC value of 0.991. Conclusion: The

  3. Embracing an integromic approach to tissue biomarker research in cancer: Perspectives and lessons learned. (United States)

    Li, Gerald; Bankhead, Peter; Dunne, Philip D; O'Reilly, Paul G; James, Jacqueline A; Salto-Tellez, Manuel; Hamilton, Peter W; McArt, Darragh G


    Modern approaches to biomedical research and diagnostics targeted towards precision medicine are generating 'big data' across a range of high-throughput experimental and analytical platforms. Integrative analysis of this rich clinical, pathological, molecular and imaging data represents one of the greatest bottlenecks in biomarker discovery research in cancer and other diseases. Following on from the publication of our successful framework for multimodal data amalgamation and integrative analysis, Pathology Integromics in Cancer (PICan), this article will explore the essential elements of assembling an integromics framework from a more detailed perspective. PICan, built around a relational database storing curated multimodal data, is the research tool sitting at the heart of our interdisciplinary efforts to streamline biomarker discovery and validation. While recognizing that every institution has a unique set of priorities and challenges, we will use our experiences with PICan as a case study and starting point, rationalizing the design choices we made within the context of our local infrastructure and specific needs, but also highlighting alternative approaches that may better suit other programmes of research and discovery. Along the way, we stress that integromics is not just a set of tools, but rather a cohesive paradigm for how modern bioinformatics can be enhanced. Successful implementation of an integromics framework is a collaborative team effort that is built with an eye to the future and greatly accelerates the processes of biomarker discovery, validation and translation into clinical practice.

  4. Blood-based biomarkers for Parkinson's disease. (United States)

    Chahine, Lama M; Stern, Matthew B; Chen-Plotkin, Alice


    There is a pressing need for biomarkers to diagnose Parkinson's disease (PD), assess disease severity, and prognosticate course. Various types of biologic specimens are potential candidates for identifying biomarkers--defined here as surrogate indicators of physiological or pathophysiological states--but blood has the advantage of being minimally invasive to obtain. There are, however, several challenges to identifying biomarkers in blood. Several candidate biomarkers identified in other diseases or in other types of biological fluids are being pursued as blood-based biomarkers in PD. In addition, unbiased discovery is underway using techniques including metabolomics, proteomics, and gene expression profiling. In this review, we summarize these techniques and discuss the challenges and successes of blood-based biomarker discovery in PD. Blood-based biomarkers that are discussed include α-synuclein, DJ-1, uric acid, epidermal growth factor, apolipoprotein-A1, and peripheral inflammatory markers.

  5. Biomarkers for neuromyelitis optica. (United States)

    Chang, Kuo-Hsuan; Ro, Long-Sun; Lyu, Rong-Kuo; Chen, Chiung-Mei


    Neuromyelitis optica (NMO) is an acquired, heterogeneous inflammatory disorder, which is characterized by recurrent optic neuritis and longitudinally extensive spinal cord lesions. The discovery of the serum autoantibody marker, anti-aquaporin 4 (anti-AQP4) antibody, revolutionizes our understanding of pathogenesis of NMO. In addition to anti-AQP4 antibody, other biomarkers for NMO are also reported. These candidate biomarkers are particularly involved in T helper (Th)17 and astrocytic damages, which play a critical role in the development of NMO lesions. Among them, IL-6 in the peripheral blood is associated with anti-AQP4 antibody production. Glial fibrillary acidic protein (GFAP) in CSF demonstrates good correlations with clinical severity of NMO relapses. Detecting these useful biomarkers may be useful in the diagnosis and evaluation of disease activity of NMO. Development of compounds targeting these biomarkers may provide novel therapeutic strategies for NMO. This article will review the related biomarker studies in NMO and discuss the potential therapeutics targeting these biomarkers.

  6. Computational drug discovery

    Institute of Scientific and Technical Information of China (English)

    Si-sheng OU-YANG; Jun-yan LU; Xiang-qian KONG; Zhong-jie LIANG; Cheng LUO; Hualiang JIANG


    Computational drug discovery is an effective strategy for accelerating and economizing drug discovery and development process.Because of the dramatic increase in the availability of biological macromolecule and small molecule information,the applicability of computational drug discovery has been extended and broadly applied to nearly every stage in the drug discovery and development workflow,including target identification and validation,lead discovery and optimization and preclinical tests.Over the past decades,computational drug discovery methods such as molecular docking,pharmacophore modeling and mapping,de novo design,molecular similarity calculation and sequence-based virtual screening have been greatly improved.In this review,we present an overview of these important computational methods,platforms and successful applications in this field.

  7. Discovery of a biomarker and lead small molecules to target r(GGGGCC)-associated defects in c9FTD/ALS. (United States)

    Su, Zhaoming; Zhang, Yongjie; Gendron, Tania F; Bauer, Peter O; Chew, Jeannie; Yang, Wang-Yong; Fostvedt, Erik; Jansen-West, Karen; Belzil, Veronique V; Desaro, Pamela; Johnston, Amelia; Overstreet, Karen; Oh, Seok-Yoon; Todd, Peter K; Berry, James D; Cudkowicz, Merit E; Boeve, Bradley F; Dickson, Dennis; Floeter, Mary Kay; Traynor, Bryan J; Morelli, Claudia; Ratti, Antonia; Silani, Vincenzo; Rademakers, Rosa; Brown, Robert H; Rothstein, Jeffrey D; Boylan, Kevin B; Petrucelli, Leonard; Disney, Matthew D


    A repeat expansion in C9ORF72 causes frontotemporal dementia and amyotrophic lateral sclerosis (c9FTD/ALS). RNA of the expanded repeat (r(GGGGCC)exp) forms nuclear foci or undergoes repeat-associated non-ATG (RAN) translation, producing "c9RAN proteins." Since neutralizing r(GGGGCC)exp could inhibit these potentially toxic events, we sought to identify small-molecule binders of r(GGGGCC)exp. Chemical and enzymatic probing of r(GGGGCC)8 indicate that it adopts a hairpin structure in equilibrium with a quadruplex structure. Using this model, bioactive small molecules targeting r(GGGGCC)exp were designed and found to significantly inhibit RAN translation and foci formation in cultured cells expressing r(GGGGCC)66 and neurons transdifferentiated from fibroblasts of repeat expansion carriers. Finally, we show that poly(GP) c9RAN proteins are specifically detected in c9ALS patient cerebrospinal fluid. Our findings highlight r(GGGGCC)exp-binding small molecules as a possible c9FTD/ALS therapeutic and suggest that c9RAN proteins could potentially serve as a pharmacodynamic biomarker to assess efficacy of therapies that target r(GGGGCC)exp.

  8. Mass spectrometry-driven drug discovery for development of herbal medicine. (United States)

    Zhang, Aihua; Sun, Hui; Wang, Xijun


    Herbal medicine (HM) has made a major contribution to the drug discovery process with regard to identifying products compounds. Currently, more attention has been focused on drug discovery from natural compounds of HM. Despite the rapid advancement of modern analytical techniques, drug discovery is still a difficult and lengthy process. Fortunately, mass spectrometry (MS) can provide us with useful structural information for drug discovery, has been recognized as a sensitive, rapid, and high-throughput technology for advancing drug discovery from HM in the post-genomic era. It is essential to develop an efficient, high-quality, high-throughput screening method integrated with an MS platform for early screening of candidate drug molecules from natural products. We have developed a new chinmedomics strategy reliant on MS that is capable of capturing the candidate molecules, facilitating their identification of novel chemical structures in the early phase; chinmedomics-guided natural product discovery based on MS may provide an effective tool that addresses challenges in early screening of effective constituents of herbs against disease. This critical review covers the use of MS with related techniques and methodologies for natural product discovery, biomarker identification, and determination of mechanisms of action. It also highlights high-throughput chinmedomics screening methods suitable for lead compound discovery illustrated by recent successes.

  9. Biomarker Discovery and Redundancy Reduction towards Classification using a Multi-factorial MALDI-TOF MS T2DM Mouse Model Dataset

    Directory of Open Access Journals (Sweden)

    Al-Hasani Hadi


    Full Text Available Abstract Background Diabetes like many diseases and biological processes is not mono-causal. On the one hand multi-factorial studies with complex experimental design are required for its comprehensive analysis. On the other hand, the data from these studies often include a substantial amount of redundancy such as proteins that are typically represented by a multitude of peptides. Coping simultaneously with both complexities (experimental and technological makes data analysis a challenge for Bioinformatics. Results We present a comprehensive work-flow tailored for analyzing complex data including data from multi-factorial studies. The developed approach aims at revealing effects caused by a distinct combination of experimental factors, in our case genotype and diet. Applying the developed work-flow to the analysis of an established polygenic mouse model for diet-induced type 2 diabetes, we found peptides with significant fold changes exclusively for the combination of a particular strain and diet. Exploitation of redundancy enables the visualization of peptide correlation and provides a natural way of feature selection for classification and prediction. Classification based on the features selected using our approach performs similar to classifications based on more complex feature selection methods. Conclusions The combination of ANOVA and redundancy exploitation allows for identification of biomarker candidates in multi-dimensional MALDI-TOF MS profiling studies with complex experimental design. With respect to feature selection our method provides a fast and intuitive alternative to global optimization strategies with comparable performance. The method is implemented in R and the scripts are available by contacting the corresponding author.

  10. A critical assessment of SELDI-TOF-MS for biomarker discovery in serum and tissue of patients with an ovarian mass

    Directory of Open Access Journals (Sweden)

    Wegdam Wouter


    Full Text Available Abstract Background Less than 25% of patients with a pelvic mass who are presented to a gynecologist will eventually be diagnosed with epithelial ovarian cancer. Since there is no reliable test to differentiate between different ovarian tumors, accurate classification could facilitate adequate referral to a gynecological oncologist, improving survival. The goal of our study was to assess the potential value of a SELDI-TOF-MS based classifier for discriminating between patients with a pelvic mass. Methods Our study design included a well-defined patient population, stringent protocols and an independent validation cohort. We compared serum samples of 53 ovarian cancer patients, 18 patients with tumors of low malignant potential, and 57 patients with a benign ovarian tumor on different ProteinChip arrays. In addition, from a subset of 84 patients, tumor tissues were collected and microdissection was used to isolate a pure and homogenous cell population. Results Diagonal Linear Discriminant Analysis (DLDA and Support Vector Machine (SVM classification on serum samples comparing cancer versus benign tumors, yielded models with a classification accuracy of 71-81% (cross-validation, and 73-81% on the independent validation set. Cancer and benign tissues could be classified with 95-99% accuracy using cross-validation. Tumors of low malignant potential showed protein expression patterns different from both benign and cancer tissues. Remarkably, none of the peaks differentially expressed in serum samples were found to be differentially expressed in the tissue lysates of those same groups. Conclusion Although SELDI-TOF-MS can produce reliable classification results in serum samples of ovarian cancer patients, it will not be applicable in routine patient care. On the other hand, protein profiling of microdissected tumor tissue may lead to a better understanding of oncogenesis and could still be a source of new serum biomarkers leading to novel methods for

  11. Biomarkers in inflammatory bowel diseases

    DEFF Research Database (Denmark)

    Bennike, Tue; Birkelund, Svend; Stensballe, Allan


    with medications with the concomitant risk of adverse events. In addition, identification of disease and course specific biomarker profiles can be used to identify biological pathways involved in the disease development and treatment. Knowledge of disease mechanisms in general can lead to improved future...... development of preventive and treatment strategies. Thus, the clinical use of a panel of biomarkers represents a diagnostic and prognostic tool of potentially great value. The technological development in recent years within proteomic research (determination and quantification of the complete protein content......) has made the discovery of novel biomarkers feasible. Several IBD-associated protein biomarkers are known, but none have been successfully implemented in daily use to distinguish CD and UC patients. The intestinal tissue remains an obvious place to search for novel biomarkers, which blood, urine...

  12. A platform for discovery and quantification of modified ribonucleosides in RNA: Application to stress-induced reprogramming of tRNA modifications (United States)

    Cai, Weiling Maggie; Chionh, Yok Hian; Hia, Fabian; Gu, Chen; Kellner, Stefanie; McBee, Megan E.; Ng, Chee Sheng; Pang, Yan Ling Joy; Prestwich, Erin G.; Lim, Kok Seong; Babu, I. Ramesh; Begley, Thomas J.; Dedon, Peter C.


    Here we describe an analytical platform for systems-level quantitative analysis of modified ribonucleosides in any RNA species, with a focus on stress-induced reprogramming of tRNA as part of a system of translational control of cell stress response. The chapter emphasizes strategies and caveats for each of the seven steps of the platform workflow: 1) RNA isolation, 2) RNA purification, 3) RNA hydrolysis to individual ribonucleosides, 4) chromatographic resolution of ribonucleosides, 5) identification of the full set of modified ribonucleosides, 6) mass spectrometric quantification of ribonucleosides, 6) interrogation of ribonucleoside datasets, and 7) mapping the location of stress-sensitive modifications in individual tRNA molecules. We have focused on the critical determinants of analytical sensitivity, specificity, precision and accuracy in an effort to ensure the most biologically meaningful data on mechanisms of translational control of cell stress response. The methods described here should find wide use in virtually any analysis involving RNA modifications. PMID:26253965

  13. Immunohistochemistry in the Diagnosis of Mucinous Neoplasms Involving the Ovary: The Added Value of SATB2 and Biomarker Discovery Through Protein Expression Database Mining. (United States)

    Strickland, Sarah; Wasserman, Jason K; Giassi, Ana; Djordjevic, Bojana; Parra-Herran, Carlos


    77.1% sensitivity and 99% specificity, outperforming tumor laterality and size. Second-line markers such as CDX2, MUC2, estrogen receptor, MUC1, and β-catenin increased the sensitivity of immunohistochemistry in excluding lower GI origin. Biomarker search using proteomic databases has a value in diagnostic pathology, as shown with SATB2; however, as seen with POF1B, expression profiles in these databases are not always reproduced in larger cohorts.

  14. Proteomic response of mussels Mytilus galloprovincialis exposed to CuO NPs and Cu²⁺: an exploratory biomarker discovery. (United States)

    Gomes, Tânia; Chora, Suze; Pereira, Catarina G; Cardoso, Cátia; Bebianno, Maria João


    absence of the mussel genome precluded the identification of other proteins relevant to clarify the effects of CuO NPs in mussels' tissues, proteomics analysis provided additional knowledge of their potential effects at the protein level that after confirmation and validation can be used as putative new biomarkers in nanotoxicology.

  15. Proteomic response of mussels Mytilus galloprovincialis exposed to CuO NPs and Cu{sup 2+}: An exploratory biomarker discovery

    Energy Technology Data Exchange (ETDEWEB)

    Gomes, Tânia, E-mail:; Chora, Suze; Pereira, Catarina G.; Cardoso, Cátia; Bebianno, Maria João


    the other hand, Cu{sup 2+} affected a protein associated with adhesion and mobility, precollagen-D that is associated with the detoxification mechanism of Cu{sup 2+}. Protein identification clearly showed that the toxicity of CuO NPs is not solely due to Cu{sup 2+} dissolution and can result in mitochondrial and nucleus stress-induced cell signalling cascades that can lead to apoptosis. While the absence of the mussel genome precluded the identification of other proteins relevant to clarify the effects of CuO NPs in mussels’ tissues, proteomics analysis provided additional knowledge of their potential effects at the protein level that after confirmation and validation can be used as putative new biomarkers in nanotoxicology.

  16. Biomarker Qualification: Toward a Multiple Stakeholder Framework for Biomarker Development, Regulatory Acceptance, and Utilization. (United States)

    Amur, S; LaVange, L; Zineh, I; Buckman-Garner, S; Woodcock, J


    The discovery, development, and use of biomarkers for a variety of drug development purposes are areas of tremendous interest and need. Biomarkers can become accepted for use through submission of biomarker data during the drug approval process. Another emerging pathway for acceptance of biomarkers is via the biomarker qualification program developed by the Center for Drug Evaluation and Research (CDER, US Food and Drug Administration). Evidentiary standards are needed to develop and evaluate various types of biomarkers for their intended use and multiple stakeholders, including academia, industry, government, and consortia must work together to help develop this evidence. The article describes various types of biomarkers that can be useful in drug development and evidentiary considerations that are important for qualification. A path forward for coordinating efforts to identify and explore needed biomarkers is proposed for consideration.

  17. Addressing the Challenge of Defining Valid Proteomic Biomarkers and Classifiers

    LENUS (Irish Health Repository)

    Dakna, Mohammed


    Abstract Background The purpose of this manuscript is to provide, based on an extensive analysis of a proteomic data set, suggestions for proper statistical analysis for the discovery of sets of clinically relevant biomarkers. As tractable example we define the measurable proteomic differences between apparently healthy adult males and females. We choose urine as body-fluid of interest and CE-MS, a thoroughly validated platform technology, allowing for routine analysis of a large number of samples. The second urine of the morning was collected from apparently healthy male and female volunteers (aged 21-40) in the course of the routine medical check-up before recruitment at the Hannover Medical School. Results We found that the Wilcoxon-test is best suited for the definition of potential biomarkers. Adjustment for multiple testing is necessary. Sample size estimation can be performed based on a small number of observations via resampling from pilot data. Machine learning algorithms appear ideally suited to generate classifiers. Assessment of any results in an independent test-set is essential. Conclusions Valid proteomic biomarkers for diagnosis and prognosis only can be defined by applying proper statistical data mining procedures. In particular, a justification of the sample size should be part of the study design.

  18. Biomarkers in Parkinson's disease: a funder's perspective. (United States)

    Frasier, Mark; Chowdhury, Sohini; Eberling, Jamie; Sherer, Todd


    Therapeutic development in Parkinson's disease is hampered by the paucity of well-validated biomarkers that can assist with diagnosis and/or tracking the progression of the disease. Since its inception, the Michael J Fox Foundation for Parkinson's Research has invested heavily in biomarker research and continues to prioritize discovery and development efforts. This article summarizes the history and evolution of the Michael J Fox Foundation's role in supporting biomarker research and lays out the current challenges in successfully developing markers that can be used to test therapies, while also providing a vision of future funding efforts in Parkinson's disease biomarkers.

  19. [Novel biomarkers for diabetic nephropathy]. (United States)

    Araki, Shin-ichi


    Diabetic nephropathy is a leading cause of end-stage renal disease worldwide. An early clinical sign of this complication is an increase of urinary albumin excretion, called microalbuminuria, which is not only a predictor of the progression of nephropathy, but also an independent risk factor for cardiovascular disease. Although microalbuminuria is clinically important to assess the prognosis of diabetic patients, it may be insufficient as an early and specific biomarker of diabetic nephropathy because of a large day-to-day variation and lack of a good correlation of microalbuminuria with renal dysfunction and pathohistological changes. Thus, more sensitive and specific biomarkers are needed to improve the diagnostic capability of identifying patients at high risk. The factors involved in renal tubulo-interstitial damage, the production and degradation of extracellular matrix, microinflammation, etc., are investigated as candidate molecules. Despite numerous efforts so far, the assessment of these biomarkers is still a subject of ongoing investigations. Recently, a variety of omics and quantitative techniques in systems biology are rapidly emerging in the field of biomarker discovery, including proteomics, transcriptomics, and metabolomics, and they have been applied to search for novel putative biomarkers of diabetic nephropathy. Novel biomarkers or their combination with microalbuminuria provide a better diagnostic accuracy than microalbuminuria alone, and may be useful for establishing personal medicine. Furthermore, the identification of novel biomarkers may provide insight into the mechanisms underlying diabetic nephropathy.

  20. A pilot study to evaluate the application of a generic protein standard panel for quality control of biomarker detection technologies

    Directory of Open Access Journals (Sweden)

    Valdivia Hernan J


    Full Text Available Abstract Background Protein biomarker studies are currently hampered by a lack of measurement standards to demonstrate quality, reliability and comparability across multiple assay platforms. This is especially pertinent for immunoassays where multiple formats for detecting target analytes are commonly used. Findings In this pilot study a generic panel of six non-human protein standards (50 - 10^7 pg/mL of varying abundance was prepared as a quality control (QC material. Simulated "normal" and "diseased" panels of proteins were prepared in pooled human plasma and incorporated into immunoassays using the Meso Scale Discovery® (MSD® platform to illustrate reliable detection of the component proteins. The protein panel was also evaluated as a spike-in material for a model immunoassay involving detection of ovarian cancer biomarkers within individual human plasma samples. Our selected platform could discriminate between two panels of the proteins exhibiting small differences in abundance. Across distinct experiments, all component proteins exhibited reproducible signal outputs in pooled human plasma. When individual donor samples were used, half the proteins produced signals independent of matrix effects. These proteins may serve as a generic indicator of platform reliability. Each of the remaining proteins exhibit differential signals across the distinct samples, indicative of sample matrix effects, with the three proteins following the same trend. This subset of proteins may be useful for characterising the degree of matrix effects associated with the sample which may impact on the reliability of quantifying target diagnostic biomarkers. Conclusions We have demonstrated the potential utility of this panel of standards to act as a generic QC tool for evaluating the reproducibility of the platform for protein biomarker detection independent of serum matrix effects.

  1. Discovery and validation of prostate cancer biomarkers

    NARCIS (Netherlands)

    F.H. Jansen (Flip)


    textabstractThe prostate, derived from the Greek word προστάτης – prostates, meaning “the one who stands before”, is a walnut-sized exocrine gland, part of the male genitourinary tract. It produces and stores an alkaline fluid, which liquefies the semen and prolongs the life-span of the spermatozoa.

  2. Guided Discoveries. (United States)

    Ehrlich, Amos


    Presented are four mathematical discoveries made by students on an arithmetical function using the Fibonacci sequence. Discussed is the nature of the role of the teacher in directing the students' discovery activities. (KR)

  3. Volatility Discovery

    DEFF Research Database (Denmark)

    Dias, Gustavo Fruet; Scherrer, Cristina; Papailias, Fotis

    The price discovery literature investigates how homogenous securities traded on different markets incorporate information into prices. We take this literature one step further and investigate how these markets contribute to stochastic volatility (volatility discovery). We formally show...... that the realized measures from homogenous securities share a fractional stochastic trend, which is a combination of the price and volatility discovery measures. Furthermore, we show that volatility discovery is associated with the way that market participants process information arrival (market sensitivity...

  4. Impact of non-profit organizations on drug discovery: opportunities, gaps, solutions. (United States)

    Matter, Alex; Keller, Thomas H


    Non-profit organizations (NPO) play an increasingly important role in drug discovery and development for diseases that are neglected by the pharmaceutical industry because of low or absent commercial incentives. Governments and major private foundations such as the Wellcome Trust and the Bill & Melinda Gates Foundation increasingly step in to provide strategic direction, communication platforms and major resources, motivated by the fact that major healthcare problems remain unsolved. Drug discovery in the field of neglected diseases is fraught with complexities since, in many cases, important tools are lacking including readily available diagnostics, molecular epidemiology, appropriate model systems, representative strain collections, biomarkers, up-to-date trial methodologies and regulatory strategies. On top of this, the high hurdles addressing novel drug targets must be cleared.

  5. Imaging Biomarkers or Biomarker Imaging?

    Directory of Open Access Journals (Sweden)

    Markus Mitterhauser


    Full Text Available Since biomarker imaging is traditionally understood as imaging of molecular probes, we highly recommend to avoid any confusion with the previously defined term “imaging biomarkers” and, therefore, only use “molecular probe imaging (MPI” in that context. Molecular probes (MPs comprise all kinds of molecules administered to an organism which inherently carry a signalling moiety. This review highlights the basic concepts and differences of molecular probe imaging using specific biomarkers. In particular, PET radiopharmaceuticals are discussed in more detail. Specific radiochemical and radiopharmacological aspects as well as some legal issues are presented.

  6. Plasma proteomics to identify biomarkers - Application to cardiovascular diseases

    DEFF Research Database (Denmark)

    Beck, Hans Christian; Overgaard, Martin; Melholt Rasmussen, Lars


    , this technology may therefore identify new biomarkers that previously have not been associated with cardiovascular diseases. In this review, we summarize the key challenges and considerations, including strategies, recent discoveries and clinical applications in cardiovascular proteomics that may lead...

  7. Cellular Proteases as Cancer Biomarkers: A Review

    Directory of Open Access Journals (Sweden)

    Sarah R. Röthlisberger


    Full Text Available Over the past few decades a variety of biomolecules have been proposed as diagnostic biomarkers and predictors of severity for transmissible and nontransmissible diseases. Studies in a range of cancers have revealed many biomarkers with great potential in cancer diagnosis, in establishing tumor stage, progression, and response to therapies; such as the Kallikrein and Metalloproteinase families. Traditionally blood (serum and tissue have been the main biological sources of biomarker discovery, but in the past decade urine has emerged as a promising source of cancer biomarkers. In this review we will focus on two large families, the Kallikrein family of serine proteases discovered in serum, and the Metalloproteinase family of zinc proteases discovered in urine, as potential cancer biomarkers.

  8. Biomarkers of Parkinson's disease: current status and future perspectives. (United States)

    Wang, Jian; Hoekstra, Jake G; Zuo, Chuantao; Cook, Travis J; Zhang, Jing


    This review summarizes major advances in biomarker discovery for diagnosis, differential diagnosis and progression of Parkinson's disease (PD), with emphasis on neuroimaging and biochemical markers. Potential strategies to develop biomarkers capable of predicting PD in the prodromal stage before the appearance of motor symptoms or correlating with nonmotor symptoms, an active area of research, are also discussed.

  9. Discovery and validation of plasma-protein biomarker panels for the detection of colorectal cancer and advanced adenoma in a Danish collection of samples from patients referred for diagnostic colonoscopy

    DEFF Research Database (Denmark)

    Blume, John E.; Wilhelmsen, Michael; Benz, Ryan W.


    and utilization of such a resource is an important step in the development of blood-based biomarker tests for colorectal cancer.Methods: We have created a subject data and biological sample resource, Endoscopy II, which is based on 4698 individuals referred for diagnostic colonoscopy in Denmark between May 2010...

  10. Diabetes mellitus: channeling care through cellular discovery. (United States)

    Maiese, Kenneth; Shang, Yan Chen; Chong, Zhao Zhong; Hou, Jinling


    Diabetes mellitus (DM) impacts a significant portion of the world's population and care for this disorder places an economic burden on the gross domestic product for any particular country. Furthermore, both Type 1 and Type 2 DM are becoming increasingly prevalent and there is increased incidence of impaired glucose tolerance in the young. The complications of DM are protean and can involve multiple systems throughout the body that are susceptible to the detrimental effects of oxidative stress and apoptotic cell injury. For these reasons, innovative strategies are necessary for the implementation of new treatments for DM that are generated through the further understanding of cellular pathways that govern the pathological consequences of DM. In particular, both the precursor for the coenzyme beta-nicotinamide adenine dinucleotide (NAD(+)), nicotinamide, and the growth factor erythropoietin offer novel platforms for drug discovery that involve cellular metabolic homeostasis and inflammatory cell control. Interestingly, these agents and their tightly associated pathways that consist of cell cycle regulation, protein kinase B, forkhead transcription factors, and Wnt signaling also function in a broader sense as biomarkers for disease onset and progression.

  11. Novel diagnostic biomarkers for prostate cancer

    Directory of Open Access Journals (Sweden)

    Chikezie O. Madu, Yi Lu


    Full Text Available Prostate cancer is the most frequently diagnosed malignancy in American men, and a more aggressive form of the disease is particularly prevalent among African Americans. The therapeutic success rate for prostate cancer can be tremendously improved if the disease is diagnosed early. Thus, a successful therapy for this disease depends heavily on the clinical indicators (biomarkers for early detection of the presence and progression of the disease, as well as the prediction after the clinical intervention. However, the current clinical biomarkers for prostate cancer are not ideal as there remains a lack of reliable biomarkers that can specifically distinguish between those patients who should be treated adequately to stop the aggressive form of the disease and those who should avoid overtreatment of the indolent form.A biomarker is a characteristic that is objectively measured and evaluated as an indicator of normal biologic processes, pathogenic processes, or pharmacologic responses to a therapeutic intervention. A biomarker reveals further information to presently existing clinical and pathological analysis. It facilitates screening and detecting the cancer, monitoring the progression of the disease, and predicting the prognosis and survival after clinical intervention. A biomarker can also be used to evaluate the process of drug development, and, optimally, to improve the efficacy and safety of cancer treatment by enabling physicians to tailor treatment for individual patients. The form of the prostate cancer biomarkers can vary from metabolites and chemical products present in body fluid to genes and proteins in the prostate tissues.Current advances in molecular techniques have provided new tools facilitating the discovery of new biomarkers for prostate cancer. These emerging biomarkers will be beneficial and critical in developing new and clinically reliable indicators that will have a high specificity for the diagnosis and prognosis of

  12. Novel diagnostic biomarkers for prostate cancer. (United States)

    Madu, Chikezie O; Lu, Yi


    Prostate cancer is the most frequently diagnosed malignancy in American men, and a more aggressive form of the disease is particularly prevalent among African Americans. The therapeutic success rate for prostate cancer can be tremendously improved if the disease is diagnosed early. Thus, a successful therapy for this disease depends heavily on the clinical indicators (biomarkers) for early detection of the presence and progression of the disease, as well as the prediction after the clinical intervention. However, the current clinical biomarkers for prostate cancer are not ideal as there remains a lack of reliable biomarkers that can specifically distinguish between those patients who should be treated adequately to stop the aggressive form of the disease and those who should avoid overtreatment of the indolent form.A biomarker is a characteristic that is objectively measured and evaluated as an indicator of normal biologic processes, pathogenic processes, or pharmacologic responses to a therapeutic intervention. A biomarker reveals further information to presently existing clinical and pathological analysis. It facilitates screening and detecting the cancer, monitoring the progression of the disease, and predicting the prognosis and survival after clinical intervention. A biomarker can also be used to evaluate the process of drug development, and, optimally, to improve the efficacy and safety of cancer treatment by enabling physicians to tailor treatment for individual patients. The form of the prostate cancer biomarkers can vary from metabolites and chemical products present in body fluid to genes and proteins in the prostate tissues.Current advances in molecular techniques have provided new tools facilitating the discovery of new biomarkers for prostate cancer. These emerging biomarkers will be beneficial and critical in developing new and clinically reliable indicators that will have a high specificity for the diagnosis and prognosis of prostate cancer. The

  13. DNA Methylation Biomarkers: Cancer and Beyond

    Directory of Open Access Journals (Sweden)

    Thomas Mikeska


    Full Text Available Biomarkers are naturally-occurring characteristics by which a particular pathological process or disease can be identified or monitored. They can reflect past environmental exposures, predict disease onset or course, or determine a patient’s response to therapy. Epigenetic changes are such characteristics, with most epigenetic biomarkers discovered to date based on the epigenetic mark of DNA methylation. Many tissue types are suitable for the discovery of DNA methylation biomarkers including cell-based samples such as blood and tumor material and cell-free DNA samples such as plasma. DNA methylation biomarkers with diagnostic, prognostic and predictive power are already in clinical trials or in a clinical setting for cancer. Outside cancer, strong evidence that complex disease originates in early life is opening up exciting new avenues for the detection of DNA methylation biomarkers for adverse early life environment and for estimation of future disease risk. However, there are a number of limitations to overcome before such biomarkers reach the clinic. Nevertheless, DNA methylation biomarkers have great potential to contribute to personalized medicine throughout life. We review the current state of play for DNA methylation biomarkers, discuss the barriers that must be crossed on the way to implementation in a clinical setting, and predict their future use for human disease.

  14. Novel biomarkers for cancer detection and prognostication

    NARCIS (Netherlands)

    Mehra, N.


    In this thesis we used a variety of approaches for biomarker discovery; in Part I we assessed whether we could identify a non-invasive surrogate markers of angiogenesis, as new vessel formation plays critical roles in the growth and metastatic spread of tumors. Moreover, many agents targeting the va

  15. Current and emerging biomarkers of hepatotoxicity

    Directory of Open Access Journals (Sweden)

    Yang X


    Full Text Available Xi Yang, William F Salminen, Laura K SchnackenbergDivision of Systems Biology, National Center for Toxicological Research, US Food and Drug Administration, Jefferson, AR, USAAbstract: Drug-induced liver injury (DILI is of great concern to human health. Generally, liver function and injury is evaluated based upon clinical signs, a select group of serum clinical biomarkers, and occasionally liver biopsies. While alanine aminotransferase, the most commonly used biomarker of hepatocellular injury, is a sensitive marker of liver injury, it is not necessarily specific for liver injury. Furthermore, alanine aminotransferase levels may not always correlate with the extent of injury. Therefore, new hepatotoxicity biomarkers are needed that are more predictive and specific indicators of liver injury and altered function. In addition, no current biomarker provides prognostic information about ultimate outcome once injury occurs, and any new biomarker filling this need is desperately needed. The omics technologies, including genomics, proteomics, and metabolomics, are being used in preclinical animal studies as well as clinical studies to evaluate markers of hepatotoxicity in easily obtained biofluids, such as urine and serum. Recently, the evaluation of circulating microRNAs in urine and blood has also shown promise for the identification of novel, sensitive markers of liver injury. This review evaluates the current status of proposed biomarkers of hepatotoxicity from the omics platforms, as well as from analysis of microRNAs. A brief description of the qualification of proposed biomarkers is also given.Keywords: biomarkers, hepatotoxicity, metabolomics, microRNA, proteomics, transcriptomics

  16. 质谱在生物标志物研究中的应用%Mass Spectrometry in Biomarker Investigation

    Institute of Scientific and Technical Information of China (English)

    彭翱; 赵芊; 江骥; 胡蓓


    生物标志物是一个指示剂,可以对其进行测定并用以解释正常生理过程、病理过程及治疗药物的药理学效应,广泛的应用于药物研发和临床诊断中.生物标志物的研究涉及多种技术平台和方法,其中基于质谱的研究方法无论在生物标志物的发现还是确证过程中都有着广泛的应用.本文讨论了基于质谱的研究方法在通常的生物标志物以及阿尔茨海默氏症研究中的进展.%A biomarker is a characteristic, which is objectively measured and evaluated as an indicator of normal biological processes, pathogenic processes or pharmacologic responses to a therapeutic agent. They were increasingly used in drug development and clinical diagnostics. There were several platforms and methods used in biomarker investigation,and the mass-based methods had their contribution from the discovery stage to the qualification stage of biomarker investigation. In this review, we discussed the mass-based methods in general biomarker investigation and Alzheimer's disease.

  17. microRNAs as neuroregulators, biomarkers and therapeutic agents in neurodegenerative diseases. (United States)

    Basak, Indranil; Patil, Ketan S; Alves, Guido; Larsen, Jan Petter; Møller, Simon Geir


    The last decade has experienced the emergence of microRNAs as a key molecular tool for the diagnosis and prognosis of human diseases. Although the focus has mostly been on cancer, neurodegenerative diseases present an exciting, yet less explored, platform for microRNA research. Several studies have highlighted the significance of microRNAs in neurogenesis and neurodegeneration, and pre-clinical studies have shown the potential of microRNAs as biomarkers. Despite this, no bona fide microRNAs have been identified as true diagnostic or prognostic biomarkers for neurodegenerative disease. This is mainly due to the lack of precisely defined patient cohorts and the variability within and between individual cohorts. However, the discovery that microRNAs exist as stable molecules at detectable levels in body fluids has opened up new avenues for microRNAs as potential biomarker candidates. Furthermore, technological developments in microRNA biology have contributed to the possible design of microRNA-mediated disease intervention strategies. The combination of these advancements, with the availability of well-defined longitudinal patient cohort, promises to not only assist in developing invaluable diagnostic tools for clinicians, but also to increase our overall understanding of the underlying heterogeneity of neurodegenerative diseases. In this review, we present a comprehensive overview of the existing knowledge of microRNAs in neurodegeneration and provide a perspective of the applicability of microRNAs as a basis for future therapeutic intervention strategies.

  18. Parkinson's disease plasma biomarkers: an automated literature analysis followed by experimental validation. (United States)

    Alberio, Tiziana; Bucci, Enrico M; Natale, Massimo; Bonino, Dario; Di Giovanni, Marco; Bottacchi, Edo; Fasano, Mauro


    Diagnosis of Parkinson's disease (PD) is currently assessed by the clinical evaluation of extrapyramidal signs. The identification of specific biomarkers would be advisable, however most studies stop at the discovery phase, with no biomarkers reaching clinical exploitation. To this purpose, we developed an automated literature analysis procedure to retrieve all the background knowledge available in public databases. The bioinformatic platform allowed us to analyze more than 51,000 scientific papers dealing with PD, containing information on 4121 proteins. Out of these, we could track back 35 PD-related proteins as present in at least two published 2-DE maps of human plasma. Then, 9 different proteins (haptoglobin, transthyretin, apolipoprotein A-1, serum amyloid P component, apolipoprotein E, complement factor H, fibrinogen γ, thrombin, complement C3) split into 32 spots were identified as a potential diagnostic pattern. Eventually, we compared the collected literature data to experimental gels from 90 subjects (45 PD patients, 45 non-neurodegenerative control subjects) to experimentally verify their potential as plasma biomarkers of PD.

  19. Potential Peripheral Biomarkers for the Diagnosis of Alzheimer's Disease

    Directory of Open Access Journals (Sweden)

    Seema Patel


    Full Text Available Advances in the discovery of a peripheral biomarker for the diagnosis of Alzheimer's would provide a way to better detect the onset of this debilitating disease in a manner that is both noninvasive and universally available. This paper examines the current approaches that are being used to discover potential biomarker candidates available in the periphery. The search for a peripheral biomarker that could be utilized diagnostically has resulted in an extensive amount of studies that employ several biological approaches, including the assessment of tissues, genomics, proteomics, epigenetics, and metabolomics. Although a definitive biomarker has yet to be confirmed, advances in the understanding of the mechanisms of the disease and major susceptibility factors have been uncovered and reveal promising possibilities for the future discovery of a useful biomarker.

  20. Biomarkers of An Autoimmune Skin Disease-Psoriasis

    Institute of Scientific and Technical Information of China (English)

    Shan Jiang; Taylor E Hinchliffe; Tianfu Wu


    Psoriasis is one of the most prevalent autoimmune skin diseases. However, its etiology and pathogenesis are still unclear. Over the last decade, omics-based technologies have been exten-sively utilized for biomarker discovery. As a result, some promising markers for psoriasis have been identified at the genome, transcriptome, proteome, and metabolome level. These discoveries have provided new insights into the underlying molecular mechanisms and signaling pathways in psoriasis pathogenesis. More importantly, some of these markers may prove useful in the diagnosis of psoriasis and in the prediction of disease progression once they have been validated. In this review, we summarize the most recent findings in psoriasis biomarker discovery. In addition, we will discuss several emerging technologies and their potential for novel biomarker discovery and diagnostics for psoriasis.

  1. Beyond Discovery

    DEFF Research Database (Denmark)

    Korsgaard, Steffen; Sassmannshausen, Sean Patrick


    as their central concepts and conceptualization of the entrepreneurial function. On this basis we discuss three central themes that cut across the four alternatives: process, uncertainty, and agency. These themes provide new foci for entrepreneurship research and can help to generate new research questions......In this chapter we explore four alternatives to the dominant discovery view of entrepreneurship; the development view, the construction view, the evolutionary view, and the Neo-Austrian view. We outline the main critique points of the discovery presented in these four alternatives, as well...

  2. The discovery of how gender influences age immunological mechanisms in health and disease, and the identification of ageing gender-specific biomarkers, could lead to specifically tailored treatment and ultimately improve therapeutic success rates

    Directory of Open Access Journals (Sweden)

    Berghella Anna


    Full Text Available Abstract The control of human health and diseases in the elderly population is becoming a challenge, since mean age and life expectation are progressively increasing as well as chronic degenerative diseases. These disorders are of complex diagnosis and they are difficult to be treated, but it is hoped that the predictive medicine will lead to more specific and effective treatment by using specific markers to identify persons with high risk of developing disease, before the clinical manifestation. Peripheral blood targets and biomarkers are currently the most practical, non-invasive means of disease diagnosing, predicting prognosis and therapeutic response. Human longevity is directly correlated with the optimal functioning of the immune system. Recent findings indicate that the sexual dimorphism of T helper (Th cytokine pathways and the regulation of Th cell network homeostasis are normally present in the immune response and undergoes to adverse changes with ageing. Furthermore, immune senescence affects both men and women, but it does not affect them equally. Therefore, we hypothesize that the comprehension of the interferences between these gender specific pathways, the ageing immunological mechanism in pathological or healthy state and the current therapies, could lead to specifically tailored treatment and eventually improve the therapeutic success rates. Reaching this aim requires the identification of ageing gender-specific biomarkers that could easily reveal the above mentioned correlations.

  3. A Comparative Analysis of Biomarker Selection Techniques

    Directory of Open Access Journals (Sweden)

    Nicoletta Dessì


    Full Text Available Feature selection has become the essential step in biomarker discovery from high-dimensional genomics data. It is recognized that different feature selection techniques may result in different set of biomarkers, that is, different groups of genes highly correlated to a given pathological condition, but few direct comparisons exist which quantify these differences in a systematic way. In this paper, we propose a general methodology for comparing the outcomes of different selection techniques in the context of biomarker discovery. The comparison is carried out along two dimensions: (i measuring the similarity/dissimilarity of selected gene sets; (ii evaluating the implications of these differences in terms of both predictive performance and stability of selected gene sets. As a case study, we considered three benchmarks deriving from DNA microarray experiments and conducted a comparative analysis among eight selection methods, representatives of different classes of feature selection techniques. Our results show that the proposed approach can provide useful insight about the pattern of agreement of biomarker discovery techniques.

  4. The virtual heart as a platform for screening drug cardiotoxicity (United States)

    Yuan, Yongfeng; Bai, Xiangyun; Luo, Cunjin; Wang, Kuanquan


    To predict the safety of a drug at an early stage in its development is a major challenge as there is a lack of in vitro heart models that correlate data from preclinical toxicity screening assays with clinical results. A biophysically detailed computer model of the heart, the virtual heart, provides a powerful tool for simulating drug–ion channel interactions and cardiac functions during normal and disease conditions and, therefore, provides a powerful platform for drug cardiotoxicity screening. In this article, we first review recent progress in the development of theory on drug–ion channel interactions and mathematical modelling. Then we propose a family of biomarkers that can quantitatively characterize the actions of a drug on the electrical activity of the heart at multi‐physical scales including cellular and tissue levels. We also conducted some simulations to demonstrate the application of the virtual heart to assess the pro‐arrhythmic effects of cisapride and amiodarone. Using the model we investigated the mechanisms responsible for the differences between the two drugs on pro‐arrhythmogenesis, even though both prolong the QT interval of ECGs. Several challenges for further development of a virtual heart as a platform for screening drug cardiotoxicity are discussed. Linked Articles This article is part of a themed section on Chinese Innovation in Cardiovascular Drug Discovery. To view the other articles in this section visit PMID:25363597

  5. Quantitative imaging biomarker ontology (QIBO) for knowledge representation of biomedical imaging biomarkers. (United States)

    Buckler, Andrew J; Liu, Tiffany Ting; Savig, Erica; Suzek, Baris E; Ouellette, M; Danagoulian, J; Wernsing, G; Rubin, Daniel L; Paik, David


    A widening array of novel imaging biomarkers is being developed using ever more powerful clinical and preclinical imaging modalities. These biomarkers have demonstrated effectiveness in quantifying biological processes as they occur in vivo and in the early prediction of therapeutic outcomes. However, quantitative imaging biomarker data and knowledge are not standardized, representing a critical barrier to accumulating medical knowledge based on quantitative imaging data. We use an ontology to represent, integrate, and harmonize heterogeneous knowledge across the domain of imaging biomarkers. This advances the goal of developing applications to (1) improve precision and recall of storage and retrieval of quantitative imaging-related data using standardized terminology; (2) streamline the discovery and development of novel imaging biomarkers by normalizing knowledge across heterogeneous resources; (3) effectively annotate imaging experiments thus aiding comprehension, re-use, and reproducibility; and (4) provide validation frameworks through rigorous specification as a basis for testable hypotheses and compliance tests. We have developed the Quantitative Imaging Biomarker Ontology (QIBO), which currently consists of 488 terms spanning the following upper classes: experimental subject, biological intervention, imaging agent, imaging instrument, image post-processing algorithm, biological target, indicated biology, and biomarker application. We have demonstrated that QIBO can be used to annotate imaging experiments with standardized terms in the ontology and to generate hypotheses for novel imaging biomarker-disease associations. Our results established the utility of QIBO in enabling integrated analysis of quantitative imaging data.

  6. Biomarkers of (osteo)arthritis. (United States)

    Mobasheri, Ali; Henrotin, Yves


    Arthritic diseases are a major cause of disability and morbidity, and cause an enormous burden for health and social care systems globally. Osteoarthritis (OA) is the most common form of arthritis. The key risk factors for the development of OA are age, obesity, joint trauma or instability. Metabolic and endocrine diseases can also contribute to the pathogenesis of OA. There is accumulating evidence to suggest that OA is a whole-organ disease that is influenced by systemic mediators, inflammaging, innate immunity and the low-grade inflammation induced by metabolic syndrome. Although all joint tissues are implicated in disease progression in OA, articular cartilage has received the most attention in the context of aging, injury and disease. There is increasing emphasis on the early detection of OA as it has the capacity to target and treat the disease more effectively. Indeed it has been suggested that this is the era of "personalized prevention" for OA. However, the development of strategies for the prevention of OA require new and sensitive biomarker tools that can detect the disease in its molecular and pre-radiographic stage, before structural and functional alterations in cartilage integrity have occurred. There is also evidence to support a role for biomarkers in OA drug discovery, specifically the development of disease modifying osteoarthritis drugs. This Special Issue of Biomarkers is dedicated to recent progress in the field of OA biomarkers. The papers in this Special Issue review the current state-of-the-art and discuss the utility of OA biomarkers as diagnostic and prognostic tools.

  7. Warehousing re-annotated cancer genes for biomarker meta-analysis. (United States)

    Orsini, M; Travaglione, A; Capobianco, E


    Translational research in cancer genomics assigns a fundamental role to bioinformatics in support of candidate gene prioritization with regard to both biomarker discovery and target identification for drug development. Efforts in both such directions rely on the existence and constant update of large repositories of gene expression data and omics records obtained from a variety of experiments. Users who interactively interrogate such repositories may have problems in retrieving sample fields that present limited associated information, due for instance to incomplete entries or sometimes unusable files. Cancer-specific data sources present similar problems. Given that source integration usually improves data quality, one of the objectives is keeping the computational complexity sufficiently low to allow an optimal assimilation and mining of all the information. In particular, the scope of integrating intraomics data can be to improve the exploration of gene co-expression landscapes, while the scope of integrating interomics sources can be that of establishing genotype-phenotype associations. Both integrations are relevant to cancer biomarker meta-analysis, as the proposed study demonstrates. Our approach is based on re-annotating cancer-specific data available at the EBI's ArrayExpress repository and building a data warehouse aimed to biomarker discovery and validation studies. Cancer genes are organized by tissue with biomedical and clinical evidences combined to increase reproducibility and consistency of results. For better comparative evaluation, multiple queries have been designed to efficiently address all types of experiments and platforms, and allow for retrieval of sample-related information, such as cell line, disease state and clinical aspects.

  8. A review on airway biomarkers: exposure, effect and susceptibility. (United States)

    Corradi, Massimo; Goldoni, Matteo; Mutti, Antonio


    Current research in pulmonology requires the use of biomarkers to investigate airway exposure and diseases, for both diagnostic and prognostic purposes. The traditional approach based on invasive approaches (lung lavages and biopsies) can now be replaced, at least in part, through the use of non invasively collected specimens (sputum and breath), in which biomarkers of exposure, effect and susceptibility can be searched. The discovery of specific lung-related proteins, which can spill over in blood or excreted in urine, further enhanced the spectrum of airway specific biomarkers to be studied. The recent introduction of high-performance 'omic' technologies - genomics, proteomics and metabolomics, and the rate at which biomarker candidates are being discovered, will permit the use of a combination of biomarkers for a more precise selection of patient with different outcomes and responses to therapies. The aim of this review is to critically evaluate the use of airway biomarkers in the context of research and clinical practice.

  9. Platform contents


    Renault, Régis


    A monopoly platform hosts advertisers who compete on a market for horizontally differentiated products. These products may be either mass market products that appeal broadly to the entire consumer population or niche products that are tailored to the tastes of some particular group. Consumers search sequentially through ads incurring a surfing cost of moving to the next ad. They may click on an ad at some cost, which provides all relevant information and the opportunity to buy. The platform c...

  10. [Lens platform]. (United States)

    Łukaszewska-Smyk, Agnieszka; Kałuzny, Józef


    The lens platform defines lens structure and lens material. Evolution of lens comprises change in their shape, angulation of haptens and transition of three-piece lens into one-piece lens. The lens fall into two categories: rigid (PMMA) and soft (siliconic, acrylic, colameric). The main lens maaterials are polymers (hydrophilic and hydrophobic). The lens platform has an effect on biocompatibility, bioadhesion, stability of lens in capsule, degree of PCO evolution and sensitiveness to laser damages.

  11. Coronary Artery-Bypass-Graft Surgery Increases the Plasma Concentration of Exosomes Carrying a Cargo of Cardiac MicroRNAs: An Example of Exosome Trafficking Out of the Human Heart with Potential for Cardiac Biomarker Discovery.

    Directory of Open Access Journals (Sweden)

    Costanza Emanueli

    Full Text Available Exosome nanoparticles carry a composite cargo, including microRNAs (miRs. Cultured cardiovascular cells release miR-containing exosomes. The exosomal trafficking of miRNAs from the heart is largely unexplored. Working on clinical samples from coronary-artery by-pass graft (CABG surgery, we investigated if: 1 exosomes containing cardiac miRs and hence putatively released by cardiac cells increase in the circulation after surgery; 2 circulating exosomes and exosomal cardiac miRs correlate with cardiac troponin (cTn, the current "gold standard" surrogate biomarker of myocardial damage.The concentration of exosome-sized nanoparticles was determined in serial plasma samples. Cardiac-expressed (miR-1, miR-24, miR-133a/b, miR-208a/b, miR-210, non-cardiovascular (miR-122 and quality control miRs were measured in whole plasma and in plasma exosomes. Linear regression analyses were employed to establish the extent to which the circulating individual miRs, exosomes and exosomal cardiac miR correlated with cTn-I. Cardiac-expressed miRs and the nanoparticle number increased in the plasma on completion of surgery for up to 48 hours. The exosomal concentration of cardiac miRs also increased after CABG. Cardiac miRs in the whole plasma did not correlate significantly with cTn-I. By contrast cTn-I was positively correlated with the plasma exosome level and the exosomal cardiac miRs.The plasma concentrations of exosomes and their cargo of cardiac miRs increased in patients undergoing CABG and were positively correlated with hs-cTnI. These data provide evidence that CABG induces the trafficking of exosomes from the heart to the peripheral circulation. Future studies are necessary to investigate the potential of circulating exosomes as clinical biomarkers in cardiac patients.

  12. Biomarkers in Parkinson's disease (recent update). (United States)

    Sharma, Sushil; Moon, Carolyn Seungyoun; Khogali, Azza; Haidous, Ali; Chabenne, Anthony; Ojo, Comfort; Jelebinkov, Miriana; Kurdi, Yousef; Ebadi, Manuchair


    Parkinson's disease (PD) is the second most common neurodegenerative disorder mostly affecting the aging population over sixty. Cardinal symptoms including, tremors, muscle rigidity, drooping posture, drooling, walking difficulty, and autonomic symptoms appear when a significant number of nigrostriatal dopaminergic neurons are already destroyed. Hence we need early, sensitive, specific, and economical peripheral and/or central biomarker(s) for the differential diagnosis, prognosis, and treatment of PD. These can be classified as clinical, biochemical, genetic, proteomic, and neuroimaging biomarkers. Novel discoveries of genetic as well as nongenetic biomarkers may be utilized for the personalized treatment of PD during preclinical (premotor) and clinical (motor) stages. Premotor biomarkers including hyper-echogenicity of substantia nigra, olfactory and autonomic dysfunction, depression, hyposmia, deafness, REM sleep disorder, and impulsive behavior may be noticed during preclinical stage. Neuroimaging biomarkers (PET, SPECT, MRI), and neuropsychological deficits can facilitate differential diagnosis. Single-cell profiling of dopaminergic neurons has identified pyridoxal kinase and lysosomal ATPase as biomarker genes for PD prognosis. Promising biomarkers include: fluid biomarkers, neuromelanin antibodies, pathological forms of α-Syn, DJ-1, amyloid β and tau in the CSF, patterns of gene expression, metabolomics, urate, as well as protein profiling in the blood and CSF samples. Reduced brain regional N-acetyl-aspartate is a biomarker for the in vivo assessment of neuronal loss using magnetic resonance spectroscopy and T2 relaxation time with MRI. To confirm PD diagnosis, the PET biomarkers include [(18)F]-DOPA for estimating dopaminergic neurotransmission, [(18)F]dG for mitochondrial bioenergetics, [(18)F]BMS for mitochondrial complex-1, [(11)C](R)-PK11195 for microglial activation, SPECT imaging with (123)Iflupane and βCIT for dopamine transporter, and urinary

  13. Delivery of High-Quality Biomarker Assays

    Directory of Open Access Journals (Sweden)

    Brian N. Swanson


    Full Text Available Biomarker measurements now support key decisions throughout the drug development process, from lead optimization to regulatory approvals. They are essential for documenting exposure-response relationships, specificity and potency toward the molecular target, untoward effects, and therapeutic applications. In a broader sense, biomarkers constitute the basis of clinical pathology and laboratory medicine. The utility of biomarkers is limited by their specificity and sensitivity toward the drug or disease process and by their overall variability. Understanding and controlling sources of variability is not only imperative for delivering high-quality assay results, but ultimately for controlling the size and expense of research studies. Variability in biomarker measurements is affected by: biological and environmental factors (e.g., gender, age, posture, diet and biorhythms, sample collection factors (e.g., preservatives, transport and storage conditions, and collection technique, and analytical factors (e.g., purity of reference material, pipetting precision, and antibody specificity. The quality standards for biomarker assays used in support of nonclinical safety studies fall under GLP (FDA regulations, whereas, those assays used to support human diagnostics and healthcare are established by CLIA (CMS regulations and accrediting organizations such as the College of American Pathologists. While most research applications of biomarkers are not regulated, biomarker laboratories in all settings are adopting similar laboratory practices in order to deliver high-quality data. Because of the escalation in demand for biomarker measurements, the highly-parallel (multi-plexed assay platforms that have fueled the rise of genomics will likely evolve into the analytical engines that drive the biomarker laboratories of tomorrow.

  14. ITS Platform

    DEFF Research Database (Denmark)

    Tøfting, Svend; Lahrmann, Harry; Agerholm, Niels


    Aalborg University and two local companies have over the past four years developed and tested an ITS Platform, which can be used for communication with cars and for providing a number of services to the drivers. The purpose has been to perform a technological test of the possible use of a hidden ...... not have to be very intelligent. This is gradually taken over by applications on smart phones. The ITS Platform with 425 test drivers is now completely developed and can be used for technological testing of e.g. payment systems.......Aalborg University and two local companies have over the past four years developed and tested an ITS Platform, which can be used for communication with cars and for providing a number of services to the drivers. The purpose has been to perform a technological test of the possible use of a hidden...

  15. Association of oil seeps and chemosynthetic communities with oil discoveries, upper continental slope, Gulf of Mexico

    Energy Technology Data Exchange (ETDEWEB)

    Sassen, R.; Brooks, J.M.; MacDonald, I.R.; Kennicutt, M.C. II; Guinasso, N.L. Jr. (Texas A M Univ., College Station, TX (United States))


    A belt of sea-floor oil seeps and chemosynthetic communities has been mapped across the upper continental slope, offshore Louisiana, at depths ranging from 2000 to 1000 m. Visibly oil-stained sediments and thelmogenic gas hydrates have been recovered using piston cores and research submarines. Biomarker fingerprinting of seep oils suggests an origin from deeply buried Cretaceous or Jurassic source rocks characterized by marine kerogen. The abundance of seeps provides a unique opportunity to define their relationship to oil discoveries including Auger, Cooper, Jolliet, Marquette, Vancouver, Popeye, and Mars. Seeps are preferentially distributed over shallow salt ridges that rim intrasalt basin cooking pots, over salt diapirs, and along shallow fault traces near discoveries. Diagnostic seep-related features on the sea floor include gas hydrate mounds and outcrops, pockmarks and craters, mud volcanoes, and carbonate buildups. Many of the 50 chemosynthetic communities including tube worms, mussels, or clams thus far documented in the gulf occur near discoveries. Recent imagery from orbital platforms, including the space shuttle, shows that natural oil slicks are common on the sea surface in this area. Additional mapping of seep distributions should contribute to better defining of the limits of the deep Gulf play fairway.

  16. Candidate proteins, metabolites and transcripts in the Biomarkers for Spinal Muscular Atrophy (BforSMA clinical study.

    Directory of Open Access Journals (Sweden)

    Richard S Finkel

    Full Text Available BACKGROUND: Spinal Muscular Atrophy (SMA is a neurodegenerative motor neuron disorder resulting from a homozygous mutation of the survival of motor neuron 1 (SMN1 gene. The gene product, SMN protein, functions in RNA biosynthesis in all tissues. In humans, a nearly identical gene, SMN2, rescues an otherwise lethal phenotype by producing a small amount of full-length SMN protein. SMN2 copy number inversely correlates with disease severity. Identifying other novel biomarkers could inform clinical trial design and identify novel therapeutic targets. OBJECTIVE: To identify novel candidate biomarkers associated with disease severity in SMA using unbiased proteomic, metabolomic and transcriptomic approaches. MATERIALS AND METHODS: A cross-sectional single evaluation was performed in 108 children with genetically confirmed SMA, aged 2-12 years, manifesting a broad range of disease severity and selected to distinguish factors associated with SMA type and present functional ability independent of age. Blood and urine specimens from these and 22 age-matched healthy controls were interrogated using proteomic, metabolomic and transcriptomic discovery platforms. Analyte associations were evaluated against a primary measure of disease severity, the Modified Hammersmith Functional Motor Scale (MHFMS and to a number of secondary clinical measures. RESULTS: A total of 200 candidate biomarkers correlate with MHFMS scores: 97 plasma proteins, 59 plasma metabolites (9 amino acids, 10 free fatty acids, 12 lipids and 28 GC/MS metabolites and 44 urine metabolites. No transcripts correlated with MHFMS. DISCUSSION: In this cross-sectional study, "BforSMA" (Biomarkers for SMA, candidate protein and metabolite markers were identified. No transcript biomarker candidates were identified. Additional mining of this rich dataset may yield important insights into relevant SMA-related pathophysiology and biological network associations. Additional prospective studies are needed

  17. Fluid biomarkers in multiple system atrophy: A review of the MSA Biomarker Initiative. (United States)

    Laurens, Brice; Constantinescu, Radu; Freeman, Roy; Gerhard, Alexander; Jellinger, Kurt; Jeromin, Andreas; Krismer, Florian; Mollenhauer, Brit; Schlossmacher, Michael G; Shaw, Leslie M; Verbeek, Marcel M; Wenning, Gregor K; Winge, Kristian; Zhang, Jing; Meissner, Wassilios G


    Despite growing research efforts, no reliable biomarker currently exists for the diagnosis and prognosis of multiple system atrophy (MSA). Such biomarkers are urgently needed to improve diagnostic accuracy, prognostic guidance and also to serve as efficacy measures or surrogates of target engagement for future clinical trials. We here review candidate fluid biomarkers for MSA and provide considerations for further developments and harmonization of standard operating procedures. A PubMed search was performed until April 24, 2015 to review the literature with regard to candidate blood and cerebrospinal fluid (CSF) biomarkers for MSA. Abstracts of 1760 studies were retrieved and screened for eligibility. The final list included 60 studies assessing fluid biomarkers in patients with MSA. Most studies have focused on alpha-synuclein, markers of axonal degeneration or catecholamines. Their results suggest that combining several CSF fluid biomarkers may be more successful than using single markers, at least for the diagnosis. Currently, the clinically most useful markers may comprise a combination of the light chain of neurofilament (which is consistently elevated in MSA compared to controls and Parkinson's disease), metabolites of the catecholamine pathway and proteins such as α-synuclein, DJ-1 and total-tau. Beyond future efforts in biomarker discovery, the harmonization of standard operating procedures will be crucial for future success.

  18. The "Alzheimer's disease signature": potential perspectives for novel biomarkers


    Zella Davide; Di Costanzo Alfonso; Russo Claudio; Intrieri Mariano; Davinelli Sergio; Bosco Paolo; Scapagnini Giovanni


    Abstract Alzheimer's disease is a progressive and neurodegenerative disorder which involves multiple molecular mechanisms. Intense research during the last years has accumulated a large body of data and the search for sensitive and specific biomarkers has undergone a rapid evolution. However, the diagnosis remains problematic and the current tests do not accurately detect the process leading to neurodegeneration. Biomarkers discovery and validation are considered the key aspects to support cl...

  19. Advances in biomarkers of major depressive disorder. (United States)

    Huang, Tiao-Lai; Lin, Chin-Chuen


    Major depressive disorder (MDD) is characterized by mood, vegetative, cognitive, and even psychotic symptoms and signs that can cause substantial impairments in quality of life and functioning. Biomarkers are measurable indicators that could help diagnosing MDD or predicting treatment response. In this chapter, lipid profiles, immune/inflammation, and neurotrophic factor pathways that have long been implicated in the pathogenesis of MDD are discussed. Then, pharmacogenetics and epigenetics of serotonin transport and its metabolism pathway, brain-derived neurotrophic factor, and abnormality of hypothalamo-pituitary-adrenocortical axis also revealed new biomarkers. Lastly, new techniques, such as proteomics and metabolomics, which allow researchers to approach the studying of MDD with new directions and make new discoveries are addressed. In the future, more data are needed regarding pathophysiology of MDD, including protein levels, single nucleotide polymorphism, epigenetic regulation, and clinical data in order to better identify reliable and consistent biomarkers for diagnosis, treatment choice, and outcome prediction.

  20. Network-based drugs and biomarkers

    DEFF Research Database (Denmark)

    Erler, Janine Terra; Linding, Rune


    The structure and dynamics of protein signalling networks governs cell decision processes and the formation of tissue boundaries. Complex diseases such as cancer and diabetes are diseases of such networks. Therefore approaches that can give insight into how these networks change during disease pr...... associated technologies. We then focus on the multivariate nature of cellular networks and how this has implications for biomarker and drug discovery using cancer metastasis as an example....

  1. Combination of biomarkers

    DEFF Research Database (Denmark)

    Thurfjell, Lennart; Lötjönen, Jyrki; Lundqvist, Roger;


    The New National Institute on Aging-Alzheimer's Association diagnostic guidelines for Alzheimer's disease (AD) incorporate biomarkers in the diagnostic criteria and suggest division of biomarkers into two categories: Aβ accumulation and neuronal degeneration or injury.......The New National Institute on Aging-Alzheimer's Association diagnostic guidelines for Alzheimer's disease (AD) incorporate biomarkers in the diagnostic criteria and suggest division of biomarkers into two categories: Aβ accumulation and neuronal degeneration or injury....

  2. Platform computing

    CERN Multimedia


    "Platform Computing releases first grid-enabled workload management solution for IBM eServer Intel and UNIX high performance computing clusters. This Out-of-the-box solution maximizes the performance and capability of applications on IBM HPC clusters" (1/2 page) .

  3. Payment Platform

    DEFF Research Database (Denmark)

    Hjelholt, Morten; Damsgaard, Jan


    Payment transactions through the use of physical coins, bank notes or credit cards have for centuries been the standard formats of exchanging money. Recently online and mobile digital payment platforms has entered the stage as contenders to this position and possibly could penetrate societies tho...

  4. Biomarkers in Parkinson's disease: Advances and strategies. (United States)

    Delenclos, Marion; Jones, Daryl R; McLean, Pamela J; Uitti, Ryan J


    Parkinson's disease (PD) is a neurodegenerative disorder characterized by progressive motor disturbances and affects more than 1% of the worldwide population. Despite considerable progress in understanding PD pathophysiology, including genetic and biochemical causes, diagnostic approaches lack accuracy and interventions are restricted to symptomatic treatments. PD is a complex syndrome with different clinical subtypes and a wide variability in disorder course. In order to deliver better clinical management of PD patients and discovery of novel therapies, there is an urgent need to find sensitive, specific, and reliable biomarkers. The development of biomarkers will not only help the scientific community to identify populations at risk, but also facilitate clinical diagnosis. Furthermore, these tools could monitor progression, which could ultimately deliver personalized therapeutic strategies. The field of biomarker discovery in PD has attracted significant attention and there have been numerous contributions in recent years. Although none of the parameters have been validated for clinical practice, some candidates hold promise. This review summarizes recent advances in the development of PD biomarkers and discusses new strategies for their utilization.

  5. Functional analysis of OMICs data and small molecule compounds in an integrated "knowledge-based" platform. (United States)

    Nikolsky, Yuri; Kirillov, Eugene; Zuev, Roman; Rakhmatulin, Eugene; Nikolskaya, Tatiana


    Analysis of microarray, SNPs, proteomics, and other high-throughput (OMICs) data is challenging because of its biological complexity and high level of technical and biological noise. One way to deal with both problems is to perform analysis with a high-fidelity annotated knowledge base of protein interactions, pathways, and functional ontologies. This knowledge base has to be structured in a computer-readable format and must include software tools for managing experimental data, analysis, and reporting. Here we present MetaDiscovery, an integrated platform for functional data analysis which is being developed at GeneGo for the past 8 years. On the content side, MetaDiscovery encompasses a comprehensive database of protein interactions of different types, pathways, network models and 10 functional ontologies covering human, mouse, and rat proteins. The analytical toolkit includes tools for gene/protein list enrichment analysis, statistical "interactome" tool for identification of over- and under-connected proteins in the data set, and a network module made up of network generation algorithms and filters. The suite also features MetaSearch, an application for combinatorial search of the database content, as well as a Java-based tool called MapEditor for drawing and editing custom pathway maps. Applications of MetaDiscovery include identification of potential biomarkers and drug targets, pathway hypothesis generation, analysis of biological effects for novel small molecule compounds, and clinical applications (analysis of large cohorts of patients and translational and personalized medicine).

  6. Discovery Mondays

    CERN Multimedia


    Many people don't realise quite how much is going on at CERN. Would you like to gain first-hand knowledge of CERN's scientific and technological activities and their many applications? Try out some experiments for yourself, or pick the brains of the people in charge? If so, then the «Lundis Découverte» or Discovery Mondays, will be right up your street. Starting on May 5th, on every first Monday of the month you will be introduced to a different facet of the Laboratory. CERN staff, non-scientists, and members of the general public, everyone is welcome. So tell your friends and neighbours and make sure you don't miss this opportunity to satisfy your curiosity and enjoy yourself at the same time. You won't have to listen to a lecture, as the idea is to have open exchange with the expert in question and for each subject to be illustrated with experiments and demonstrations. There's no need to book, as Microcosm, CERN's interactive museum, will be open non-stop from 7.30 p.m. to 9 p.m. On the first Discovery M...


    Payne, Philip R O; Huang, Kun; Shah, Nigam H; Tenenbaum, Jessica


    The modern healthcare and life sciences ecosystem is moving towards an increasingly open and data-centric approach to discovery science. This evolving paradigm is predicated on a complex set of information needs related to our collective ability to share, discover, reuse, integrate, and analyze open biological, clinical, and population level data resources of varying composition, granularity, and syntactic or semantic consistency. Such an evolution is further impacted by a concomitant growth in the size of data sets that can and should be employed for both hypothesis discovery and testing. When such open data can be accessed and employed for discovery purposes, a broad spectrum of high impact end-points is made possible. These span the spectrum from identification of de novo biomarker complexes that can inform precision medicine, to the repositioning or repurposing of extant agents for new and cost-effective therapies, to the assessment of population level influences on disease and wellness. Of note, these types of uses of open data can be either primary, wherein open data is the substantive basis for inquiry, or secondary, wherein open data is used to augment or enrich project-specific or proprietary data that is not open in and of itself. This workshop is concerned with the key challenges, opportunities, and methodological best practices whereby open data can be used to drive the advancement of discovery science in all of the aforementioned capacities.

  8. New sepsis biomarkers

    Directory of Open Access Journals (Sweden)

    Dolores Limongi


    Full Text Available Sepsis remains a leading cause of death in the intensive care units and in all age groups worldwide. Early recognition and diagnosis are key to achieving improved outcomes. Therefore, novel biomarkers that might better inform clinicians treating such patients are surely needed. The main attributes of successful biomarkers would be high sensitivity, specificity, possibility of bedside monitoring and financial accessibility. A panel of sepsis biomarkers along with currently used laboratory tests will facilitate earlier diagnosis, timely treatment and improved outcome may be more effective than single biomarkers. In this review, we summarize the most recent advances on sepsis biomarkers evaluated in clinical and experimental studies.

  9. New sepsis biomarkers

    Institute of Scientific and Technical Information of China (English)

    Dolores Limongi; Cartesio D’Agostini; Marco Ciotti


    Sepsis remains a leading cause of death in the intensive care units and in all age groups worldwide. Early recognition and diagnosis are key to achieving improved outcomes.Therefore, novel biomarkers that might better inform clinicians treating such patients are surely needed. The main attributes of successful biomarkers would be high sensitivity,specificity, possibility of bedside monitoring and financial accessibility. A panel of sepsis biomarkers along with currently used laboratory tests will facilitate earlier diagnosis,timely treatment and improved outcome may be more effective than single biomarkers. In this review, we summarize the most recent advances on sepsis biomarkers evaluated in clinical and experimental studies.

  10. New sepsis biomarkers

    Institute of Scientific and Technical Information of China (English)

    Dolores Limongi; Cartesio DAgostini; Marco Ciotti


    Sepsis remains a leading cause of death in the intensive care units and in all age groups worldwide. Early recognition and diagnosis are key to achieving improved outcomes. Therefore, novel biomarkers that might better inform clinicians treating such patients are surely needed. The main attributes of successful biomarkers would be high sensitivity, specificity, possibility of bedside monitoring and financial accessibility. A panel of sepsis biomarkers along with currently used laboratory tests will facilitate earlier diagnosis, timely treatment and improved outcome may be more effective than single biomarkers. In this review, we summarize the most recent advances on sepsis biomarkers evaluated in clinical and experimental studies.

  11. Clinical states model for biomarkers in bladder cancer. (United States)

    Apolo, Andrea B; Milowsky, Matthew; Bajorin, Dean F


    Bladder cancer is a significant healthcare problem in the USA, with a high recurrence rate, the need for expensive continuous surveillance and limited treatment options for patients with advanced disease. Research has contributed to an understanding of the molecular pathways involved in the development and progression of bladder cancer, and that understanding has led to the discovery of potentially diagnostic, predictive and prognostic biomarkers. In this review, a clinical states model of bladder cancer is introduced and integrated into a paradigm for biomarker development. Biomarkers are systematically incorporated with predefined end points to aid in clinical management.

  12. The ongoing quest for biomarkers in Ankylosing Spondylitis. (United States)

    Danve, Abhijeet; O'Dell, James


    Ankylosing Spondylitis poses significant challenges in terms of early diagnosis, assessment of disease activity, predicting response to the treatment and monitoring radiographic progression. With better understanding of underlying immunopathogenesis, effective targeted therapies are available which improve symptoms, quality of life and possibly slow the radiographic progression. There has been a growing interest in the discovery of biomarkers for defining various aspects of disease assessment and management in Ankylosing Spondylitis. The C-reactive protein and HLA-B27 are most commonly used biomarkers. This review describes many other newer biomarkers which have potential clinical applications in this chronic inflammatory disease.

  13. Translational biomarkers of acetaminophen-induced acute liver injury. (United States)

    Beger, Richard D; Bhattacharyya, Sudeepa; Yang, Xi; Gill, Pritmohinder S; Schnackenberg, Laura K; Sun, Jinchun; James, Laura P


    Acetaminophen (APAP) is a commonly used analgesic drug that can cause liver injury, liver necrosis and liver failure. APAP-induced liver injury is associated with glutathione depletion, the formation of APAP protein adducts, the generation of reactive oxygen and nitrogen species and mitochondrial injury. The systems biology omics technologies (transcriptomics, proteomics and metabolomics) have been used to discover potential translational biomarkers of liver injury. The following review provides a summary of the systems biology discovery process, analytical validation of biomarkers and translation of omics biomarkers from the nonclinical to clinical setting in APAP-induced liver injury.

  14. Literature mining in support of drug discovery. (United States)

    Agarwal, Pankaj; Searls, David B


    The drug discovery enterprise provides strong drivers for data integration. While attention in this arena has tended to focus on integration of primary data from omics and other large platform technologies contributing to drug discovery and development, the scientific literature remains a major source of information valuable to pharmaceutical enterprises, and therefore tools for mining such data and integrating it with other sources are of vital interest and economic impact. This review provides a brief overview of approaches to literature mining as they relate to drug discovery, and offers an illustrative case study of a 'lightweight' approach we have implemented within an industrial context.

  15. Biomarkers in neonatology: the next generation of tests. (United States)

    Ng, Pak C; Lam, Hugh S


    Over the past two decades, neonatal clinicians have commonly used host response biomarkers to diagnose and assess the severity of systemic infection. Most of these biomarkers, such as acute-phase proteins or cytokines, are non-specific immunomodulating mediators of the inflammatory cascade. With advances in biochemical/genetic research, it is anticipated that future biomarkers will be 'organ and/or disease specific'. There is also the quest for discovery of 'novel' biomarkers to assist diagnosis and prognosis of neonatal diseases using powerful mass-screening techniques, e.g. the next-generation sequencing, proteomics and arrays. This article aims to introduce the concept of the next generation of biomarkers to practising neonatal clinicians, and, hopefully, to integrate basic science research into day-to-day clinical practice in the future.

  16. Platform Constellations

    DEFF Research Database (Denmark)

    Staykova, Kalina Stefanova; Damsgaard, Jan


    messaging apps KakaoTalk and LINE, we are able to gain valuable insights about the nature of these new constructions and to capture and synthesize their main characteristics in a framework. Our results show that platform constellations possess unique innovative capabilities, which can improve users......’ acquisition and users’ engagement rates as well as unlock new sources of value creation and diversify revenue streams....

  17. Fish metalloproteins as biomarkers of environmental contamination. (United States)

    Hauser-Davis, Rachel Ann; de Campos, Reinaldo Calixto; Ziolli, Roberta Lourenço


    Fish are well-recognized bioindicators of environmental contamination. Several recent proteomic studies have demonstrated the validity and value of using fish in the search and discovery of new biomarkers. Certain analytical tools, such as comparative protein expression analyses, both in field and lab exposure studies, have been used to improve the understanding of the potential for chemical pollutants to cause harmful effects. The metallomic approach is in its early stages of development, but has already shown great potential for use in ecological and environmental monitoring contexts. Besides discovering new metalloproteins that may be used as biomarkers for environmental contamination, metallomics can be used to more comprehensively elucidate existing biomarkers, which may enhance their effectiveness. Unfortunately, metallomic profiling for fish has not been explored, because only a few fish metalloproteins have thus far been discovered and studied. Of those that have, some have shown ecological importance, and are now successfully used as biomarkers of environmental contamination. These biomarkers have been shown to respond to several types of environmental contamination, such as cyanotoxins, metals, and sewage effluents, although many do not yet possess any known function. Examples of successes include MMPs, superoxide dismutases, selenoproteins, and iron-bound proteins. Unfortunately, none of these have, as yet, been extensively studied. As data are developed for them, valuable new information on their roles in fish physiology and in inducing environmental effects should become available.

  18. Reproducible Experiment Platform

    CERN Document Server

    Likhomanenko, Tatiana; Baranov, Alexander; Khairullin, Egor; Ustyuzhanin, Andrey


    Data analysis in fundamental sciences nowadays is an essential process that pushes frontiers of our knowledge and leads to new discoveries. At the same time we can see that complexity of those analyses increases fast due to a)~enormous volumes of datasets being analyzed, b)~variety of techniques and algorithms one have to check inside a single analysis, c)~distributed nature of research teams that requires special communication media for knowledge and information exchange between individual researchers. There is a lot of resemblance between techniques and problems arising in the areas of industrial information retrieval and particle physics. To address those problems we propose Reproducible Experiment Platform (REP), a software infrastructure to support collaborative ecosystem for computational science. It is a Python based solution for research teams that allows running computational experiments on shared datasets, obtaining repeatable results, and consistent comparisons of the obtained results. We present s...

  19. Quantitative multiplex detection of biomarkers on a waveguide-based biosensor using quantum dots

    Energy Technology Data Exchange (ETDEWEB)

    Xie, Hongzhi [Los Alamos National Laboratory; Mukundan, Harshini [Los Alamos National Laboratory; Martinez, Jennifer S [Los Alamos National Laboratory; Swanson, Basil I [Los Alamos National Laboratory; Anderson, Aaron S [Los Alamos National Laboratory; Grace, Kevin [Los Alamos National Laboratory


    The quantitative, simultaneous detection of multiple biomarkers with high sensitivity and specificity is critical for biomedical diagnostics, drug discovery and biomarker characterization [Wilson 2006, Tok 2006, Straub 2005, Joos 2002, Jani 2000]. Detection systems relying on optical signal transduction are, in general, advantageous because they are fast, portable, inexpensive, sensitive, and have the potential for multiplex detection of analytes of interest. However, conventional immunoassays for the detection of biomarkers, such as the Enzyme Linked Immunosorbant Assays (ELISAs) are semi-quantitative, time consuming and insensitive. ELISA assays are also limited by high non-specific binding, especially when used with complex biological samples such as serum and urine (REF). Organic fluorophores that are commonly used in such applications lack photostability and possess a narrow Stoke's shift that makes simultaneous detection of multiple fluorophores with a single excitation source difficult, thereby restricting their use in multiplex assays. The above limitations with traditional assay platforms have resulted in the increased use of nanotechnology-based tools and techniques in the fields of medical imaging [ref], targeted drug delivery [Caruthers 2007, Liu 2007], and sensing [ref]. One such area of increasing interest is the use of semiconductor quantum dots (QDs) for biomedical research and diagnostics [Gao and Cui 2004, Voura 2004, Michalet 2005, Chan 2002, Jaiswal 2004, Gao 2005, Medintz 2005, So 2006 2006, Wu 2003]. Compared to organic dyes, QDs provide several advantages for use in immunoassay platforms, including broad absorption bands with high extinction coefficients, narrow and symmetric emission bands with high quantum yields, high photostablility, and a large Stokes shift [Michalet 2005, Gu 2002]. These features prompted the use of QDs as probes in biodetection [Michalet 2005, Medintz 2005]. For example, Jaiswal et al. reported long term multiple

  20. Biomarkers for osteoarthritis: investigation, identification, and prognosis

    Directory of Open Access Journals (Sweden)

    Zhai G


    Full Text Available Guangju Zhai,1,2 Erfan Aref Eshghi11Faculty of Medicine, Memorial University of Newfoundland, St John's, NL, Canada; 2Department of Twin Research and Genetic Epidemiology, King's College London, London, UKAbstract: Osteoarthritis (OA is the most common form of arthritis and results in substantial morbidity and disability in the elderly, imposing a great economic burden on society. While there are drugs available on the market that mitigate pain and improve function, there are no disease-modifying osteoarthritis drugs, partly because there is no reliable method that can be used to identify early OA changes. There is a pressing need to develop reliable biomarkers that can inform on the process of joint destruction in OA. Such biomarkers could aid in drug development by identifying fast progressors and detecting early response to therapy, thus reducing patient numbers and time required for clinical trials. Over the last several years, dramatic advances in our understanding of the biochemistry of cartilage have led to a cascade of studies testing proteins as biomarkers of OA. Investigation of single-nucleotide polymorphisms as genetic biomarkers and the application of technologies such as metabolomics to OA are generating potentially additional biomarkers that could help detect early OA changes. This review summarizes the data on the investigation of biochemical and genetic markers in OA and highlights the new biomarkers that are recently reported and their application and limitation in the management of OA. However, despite the dramatic growth of knowledge concerning the discovery of a number of useful biomarkers, the real breakthrough in this area is still not achieved.Keywords: osteoarthritis, biochemical markers, metabolomics, genetics, epigenetics

  1. Proteomic profiling of exosomes leads to the identification of novel biomarkers for prostate cancer

    NARCIS (Netherlands)

    D. Duijvesz (Diederick); K.E. Burnum-Johnson (Kristin); M.A. Gritsenko (Marina); A.M. Hoogland (Marije); M.S. Vredenbregt-van den Berg (Mirella); R. Willemsen (Rob); T.M. Luider (Theo); L. Paša-Tolić (Ljiljana); G.W. Jenster (Guido)


    textabstractBackground: Current markers for prostate cancer, such as PSA lack specificity. Therefore, novel biomarkers are needed. Unfortunately, the complexity of body fluids often hampers biomarker discovery. An attractive alternative approach is the isolation of small vesicles, i.e. exosomes, ∼10

  2. Biomarkers in clinical medicine. (United States)

    Chen, Xiao-He; Huang, Shuwen; Kerr, David


    Biomarkers have been used in clinical medicine for decades. With the rise of genomics and other advances in molecular biology, biomarker studies have entered a whole new era and hold promise for early diagnosis and effective treatment of many diseases. A biomarker is a characteristic that is objectively measured and evaluated as an indicator of normal biological processes, pathogenic processes or pharmacologic responses to a therapeutic intervention (1). They can be classified into five categories based on their application in different disease stages: 1) antecedent biomarkers to identify the risk of developing an illness, 2) screening biomarkers to screen for subclinical disease, 3) diagnostic biomarkers to recognize overt disease, 4) staging biomarkers to categorise disease severity, and 5) prognostic biomarkers to predict future disease course, including recurrence, response to therapy, and monitoring efficacy of therapy (1). Biomarkers can indicate a variety of health or disease characteristics, including the level or type of exposure to an environmental factor, genetic susceptibility, genetic responses to environmental exposures, markers of subclinical or clinical disease, or indicators of response to therapy. This chapter will focus on how these biomarkers have been used in preventive medicine, diagnostics, therapeutics and prognostics, as well as public health and their current status in clinical practice.

  3. New serological biomarkers of inflammatory bowel disease. (United States)

    Li, Xuhang; Conklin, Laurie; Alex, Philip


    Serological biomarkers in inflammatory bowel disease (IBD) are a rapidly expanding list of non-invasive tests for objective assessments of disease activity, early diagnosis, prognosis evaluation and surveillance. This review summarizes both old and new biomarkers in IBD, but focuses on the development and characterization of new serological biomarkers (identified since 2007). These include five new anti-glycan antibodies, anti-chitobioside IgA (ACCA), anti-laminaribioside IgG (ALCA), anti-manobioside IgG (AMCA), and antibodies against chemically synthesized (Sigma) two major oligomannose epitopes, Man alpha-1,3 Man alpha-1,2 Man (SigmaMan3) and Man alpha-1,3 Man alpha-1,2 Man alpha-1,2 Man (SigmaMan4). These new biomarkers serve as valuable complementary tools to existing biomarkers not only in differentiating Crohn's disease (CD), ulcerative colitis (UC), normal and other non-IBD gut diseases, but also in predicting disease involvement (ileum vs colon), IBD risk (as subclinical biomarkers), and disease course (risk of complication and surgery). Interestingly, the prevalence of the antiglycan antibodies, including anti-Saccharomyces cerevisiae antibodies (ASCA), ALCA and AMCA, was found to be associated with single nucleotide polymorphisms (SNPs) of IBD susceptible genes such as NOD2/CARD15, NOD1/CARD4, toll-like receptors (TLR) 2 and 4, and beta-defensin-1. Furthermore, a gene dosage effect was observed: anti-glycan positivity became more frequent as the number of NOD2/CARD15 SNPS increased. Other new serum/plasma IBD biomarkers reviewed include ubiquitination factor E4A (UBE4A), CXCL16 (a chemokine), resistin, and apolipoprotein A-IV. This review also discusses the most recent studies in IBD biomarker discovery by the application of new technologies such as proteomics, fourier transform near-infrared spectroscopy, and multiplex enzyme-linked immunosorbent assay (ELISA)'s (with an emphasis on cytokine/chemokine profiling). Finally, the prospects of developing more

  4. Biomarkers for Parkinson's disease. (United States)

    Sherer, Todd B


    Biomarkers for detecting the early stages of Parkinson's disease (PD) could accelerate development of new treatments. Such biomarkers could be used to identify individuals at risk for developing PD, to improve early diagnosis, to track disease progression with precision, and to test the efficacy of new treatments. Although some progress has been made, there are many challenges associated with developing biomarkers for detecting PD in its earliest stages.

  5. Centrifuge-Based Fluidic Platforms (United States)

    Zoval, Jim; Jia, Guangyao; Kido, Horacio; Kim, Jitae; Kim, Nahui; Madou, Marc

    In this chapter centrifuge-based microfluidic platforms are reviewed and compared with other popular microfluidic propulsion methods. The underlying physical principles of centrifugal pumping in microfluidic systems are presented and the various centrifuge fluidic functions such as valving, decanting, calibration, mixing, metering, heating, sample splitting, and separation are introduced. Those fluidic functions have been combined with analytical measurements techniques such as optical imaging, absorbance and fluorescence spectroscopy and mass spectrometry to make the centrifugal platform a powerful solution for medical and clinical diagnostics and high-throughput screening (HTS) in drug discovery. Applications of a compact disc (CD)-based centrifuge platform analyzed in this review include: two-point calibration of an optode-based ion sensor, an automated immunoassay platform, multiple parallel screening assays and cellular-based assays. The use of modified commercial CD drives for high-resolution optical imaging is discussed as well. From a broader perspective, we compare the technical barriers involved in applying microfluidics for sensing and diagnostic as opposed to applying such techniques to HTS. The latter poses less challenges and explains why HTS products based on a CD fluidic platform are already commercially available, while we might have to wait longer to see commercial CD-based diagnostics.

  6. Pathogen specific biomarkers for the diagnosis of tuberculosis in deer (United States)

    Objective - To develop a noninvasive biomarker based Mycobacterium bovis specific detection system to track infection in domestic and wild animals. Design – Experimental longitudinal study for discovery and cross sectional design for validation Animals - Yearling white-tailed deer fawns (n=8) were ...

  7. A Virtual Microscopy System to Scan, Evaluate and Archive Biomarker Enhanced Cervical Cytology Slides

    Directory of Open Access Journals (Sweden)

    Niels Grabe


    Full Text Available Background: Although cytological screening for cervical precancers has led to a reduction of cervical cancer incidence worldwide it is a subjective and variable method with low single-test sensitivity. New biomarkers like p16 that specifically highlight abnormal cervical cells can improve cytology performance. Virtual microscopy offers an ideal platform for assisted evaluation and archiving of biomarker-stained slides.

  8. Role of New Biomarkers: Functional and Structural Damage

    Directory of Open Access Journals (Sweden)

    Evdoxia Tsigou


    Full Text Available Traditional diagnosis of acute kidney injury (AKI depends on detection of oliguria and rise of serum creatinine level, which is an unreliable and delayed marker of kidney damage. Delayed diagnosis of AKI in the critically ill patient is related to increased morbidity and mortality, prolonged length of stay, and cost escalation. The discovery of a reliable biomarker for early diagnosis of AKI would be very helpful in facilitating early intervention, evaluating the effectiveness of therapy, and eventually reducing cost and improving outcome. Innovative technologies such as genomics and proteomics have contributed to the discovery of new biomarkers, such as neutrophil gelatinase-associated lipocalin (NGAL, cystatin C (Cys C, kidney injury molecule-1 (KIM-1, interleukin-18 (IL-18, and liver-type fatty acid binding protein (L-FABP. The current status of the most promising of these novel AKI biomarkers, including NGAL, Cys C, KIM-1, L-FABP, and IL-18, is reviewed.

  9. New serological biomarkers of inflammatory bowel disease

    Institute of Scientific and Technical Information of China (English)

    Xuhang Li; Laurie Conldin; Philip Alex


    Serological biomarkers in inflammatory bowel disease(IBD)are a rapidty expanding list of non-invasive tests for objective assessments of disease activity,early diagnosis,prognosis evaluation and surveillance.This review summarizes both old and new biomarkers in IBD,but focuses on the development and characterization of new serological iomarkers(identified since 2007).These include five new anti-glycan antibodies,anti-chitobioside IgA(ACCA),anti-laminaribioside IgG(ALCA),anti-manobioside IgG(AMCA),and antibodies against chemically synthesized(∑)two major oligomannose epitopes,Man α-1,3 Man α-1,2 Man(∑Man3)and Man α-1,3 Man α-1,2 Man α-1,2 Man(∑Man4).These new biomarkers erve as valuable complementary tools to existing biomarkers not only in differentiating Crohn's disease(CD),ulcerative colitis(UC),normal and other non-IBD gut diseases,but also in predicting disease involvement(ileum vs colon),IBD risk(as subclinical biomarkers),and disease course(risk of complication and surgery).Interestingly,the prevalence of he antiglycan antibodies,including anti-Saccharomyces cerevisiae antibodies(ASCA),ALCA and AMCA,was found to be associated with single nucleotide polymorphisms(SNPs)of IBD susceptible genes such as NOD2/CARDl5,NOD1/CARD4,toll-like receptors(TLR)2 and 4,and β-defensin-1.Further more,a gene dosage effect was observed:anti-glycan positivity became more requent as the number of NOD2/CARDl5 SNPS increased.Other new serum/plasma IBD biomarkers reviewed include ubiquitination factor E4A(UBE4A),CXCL16(a chemokine),resistin,and apolipoprotein A-Ⅳ.This review also discusses the most recent studies in IBD biomarker discovery by the application of new technologies such as proteomics,fourier transform near-infrared spectroscopy,and multiplex enzyme-linked immunosorbent assay(ELISA)'s(with an emphasis on cytokine/chemokine profiling).Finally,the prospects of developing more clinically useful novel diagnostic algorithms by incorporating new technologies in

  10. Biomarkers of Parkinson's disease: present and future. (United States)

    Miller, Diane B; O'Callaghan, James P


    Sporadic or idiopathic Parkinson's disease (PD) is an age-related neurodegenerative disorder of unknown origin that ranks only second behind Alzheimer's disease (AD) in prevalence and its consequent social and economic burden. PD neuropathology is characterized by a selective loss of dopaminergic neurons in the substantia nigra pars compacta; however, more widespread involvement of other CNS structures and peripheral tissues now is widely documented. The onset of molecular and cellular neuropathology of PD likely occurs decades before the onset of the motor symptoms characteristic of PD. The hallmark symptoms of PD, resting tremors, rigidity and postural disabilities, are related to dopamine (DA) deficiency. Current therapies treat these symptoms by replacing or boosting existing DA. All current interventions have limited therapeutic benefit for disease progression because damage likely has progressed over an estimated period of ~5 to 15years to a loss of 60%-80% of the nigral DA neurons, before symptoms emerge. There is no accepted definitive biomarker of PD. An urgent need exists to develop early diagnostic biomarkers for two reasons: (1) to intervene at the onset of disease and (2) to monitor the progress of therapeutic interventions that may slow or stop the course of the disease. In the context of disease development, one of the promises of personalized medicine is the ability to predict, on an individual basis, factors contributing to the susceptibility for the development of a given disease. Recent advances in our understanding of genetic factors underlying or contributing to PD offer the potential for monitoring susceptibility biomarkers that can be used to identify at-risk individuals and possibly prevent the onset of disease through treatment. Finally, the exposome concept is new in the biomarker discovery arena and it is suggested as a way to move forward in identifying biomarkers of neurological diseases. It is a two-stage scheme involving a first stage

  11. On consensus biomarker selection

    Directory of Open Access Journals (Sweden)

    Gambin Anna


    Full Text Available Abstract Background Recent development of mass spectrometry technology enabled the analysis of complex peptide mixtures. A lot of effort is currently devoted to the identification of biomarkers in human body fluids like serum or plasma, based on which new diagnostic tests for different diseases could be constructed. Various biomarker selection procedures have been exploited in recent studies. It has been noted that they often lead to different biomarker lists and as a consequence, the patient classification may also vary. Results Here we propose a new approach to the biomarker selection problem: to apply several competing feature ranking procedures and compute a consensus list of features based on their outcomes. We validate our methods on two proteomic datasets for the diagnosis of ovarian and prostate cancer. Conclusion The proposed methodology can improve the classification results and at the same time provide a unified biomarker list for further biological examinations and interpretation.

  12. Biomarkers of Reflux Disease. (United States)

    Kia, Leila; Pandolfino, John E; Kahrilas, Peter J


    Gastroesophageal reflux disease (GERD) encompasses an array of disorders unified by the reflux of gastric contents. Because there are many potential disease manifestations, esophageal and extraesophageal, there is no single biomarker of the entire disease spectrum; a set of GERD biomarkers that each quantifies specific aspects of GERD-related pathology might be needed. We review recent reports of biomarkers of GERD, specifically in relation to endoscopically negative esophageal disease and excluding conventional pH-impedance monitoring. We consider histopathologic biomarkers, baseline impedance, and serologic assays to determine that most markers are based on manifestations of impaired esophageal mucosal integrity, which is based on increased ionic and molecular permeability, and/or destruction of tight junctions. Impaired mucosal integrity quantified by baseline mucosal impedance, proteolytic fragments of junctional proteins, or histopathologic features has emerged as a promising GERD biomarker.

  13. Biomarkers in Parkinson's disease. (United States)

    Morgan, John C; Mehta, Shyamal H; Sethi, Kapil D


    Biomarkers are objectively measured characteristics that are indicators of normal biological processes, pathogenic processes, or responses to therapeutic interventions. To date, clinical assessment remains the gold standard in the diagnosis of Parkinson's disease (PD) and clinical rating scales are well established as the gold standard for tracking progression of PD. Researchers have identified numerous potential biomarkers that may aid in the differential diagnosis of PD and/or tracking disease progression. Clinical, genetic, blood and cerebrospinal fluid (proteomics, transcriptomics, metabolomics), and neuroimaging biomarkers may provide useful tools in the diagnosis of PD and in measuring disease progression and response to therapies. Some potential biomarkers are inexpensive and do not require much technical expertise, whereas others are expensive or require specialized equipment and technical skills. Many potential biomarkers in PD show great promise; however, they need to be assessed for their sensitivity and specificity over time in large and varied samples of patients with and without PD.

  14. Biomarkers of Hypoxic Ischemic Encephalopathy in Newborns

    Directory of Open Access Journals (Sweden)

    Martha V. Douglas-Escobar


    Full Text Available As neonatal intensive care has evolved, the focus has shifted from improving mortality alone to an effort to improve both mortality and morbidity. The most frequent source of neonatal brain injury occurs as a result of hypoxic-ischemic injury. Hypoxic-ischemic injury occurs in about 2 of 1,000 full-term infants and severe injured infants will have lifetime disabilities and neurodevelopmental delays. Most recently, remarkable efforts toward neuroprotection have been started with the advent of therapeutic hypothermia and a key step in the evolution of neonatal neuroprotection is the discovery of biomarkers that enable the clinician-scientist to screen infants for brain injury, monitor progression of disease, identify injured brain regions, and assess efficacy of neuroprotective clinical trials. Lastly, biomarkers offer great hope identifying when an injury occurred shedding light on the potential pathophysiology and the most effective therapy. In this article, we will review biomarkers of HIE including S100b, neuron specific enolase, umbilical cord IL-6, CK-BB, GFAP, myelin basic protein, UCHL-1, and pNF-H. We hope to contribute to the awareness, validation and clinical use of established as well as novel neonatal brain injury biomarkers.

  15. From genome-wide arrays to tailor-made biomarker readout - Progress towards routine analysis of skin sensitizing chemicals with GARD. (United States)

    Forreryd, Andy; Zeller, Kathrin S; Lindberg, Tim; Johansson, Henrik; Lindstedt, Malin


    Allergic contact dermatitis (ACD) initiated by chemical sensitizers is an important public health concern. To prevent ACD, it is important to identify chemical allergens to limit the use of such compounds in various products. EU legislations, as well as increased mechanistic knowledge of skin sensitization have promoted development of non-animal based approaches for hazard classification of chemicals. GARD is an in vitro testing strategy based on measurements of a genomic biomarker signature. However, current GARD protocols are optimized for identification of predictive biomarker signatures, and not suitable for standardized screening. This study describes improvements to GARD to progress from biomarker discovery into a reliable and cost-effective assay for routine testing. Gene expression measurements were transferred to NanoString nCounter platform, normalization strategy was adjusted to fit serial arrival of testing substances, and a novel strategy to correct batch variations was presented. When challenging GARD with 29 compounds, sensitivity, specificity and accuracy could be estimated to 94%, 83% and 90%, respectively. In conclusion, we present a GARD workflow with improved sample capacity, retained predictive performance, and in a format adapted to standardized screening. We propose that GARD is ready to be considered as part of an integrated testing strategy for skin sensitization.

  16. Tumor antigens as proteogenomic biomarkers in invasive ductal carcinomas

    DEFF Research Database (Denmark)

    Olsen, Lars Rønn; Campos, Benito; Winther, Ole;


    Background: The majority of genetic biomarkers for human cancers are defined by statistical screening of high-throughput genomics data. While a large number of genetic biomarkers have been proposed for diagnostic and prognostic applications, only a small number have been applied in the clinic....... Similarly, the use of proteomics methods for the discovery of cancer biomarkers is increasing. The emerging field of proteogenomics seeks to enrich the value of genomics and proteomics approaches by studying the intersection of genomics and proteomics data. This task is challenging due to the complex nature...... of transcriptional and translation regulatory mechanisms and the disparities between genomic and proteomic data from the same samples. In this study, we have examined tumor antigens as potential biomarkers for breast cancer using genomics and proteomics data from previously reported laser capture microdissected ER...

  17. The Present and Future of Prostate Cancer Urine Biomarkers

    Directory of Open Access Journals (Sweden)

    Jeremy Clark


    Full Text Available In order to successfully cure patients with prostate cancer (PCa, it is important to detect the disease at an early stage. The existing clinical biomarkers for PCa are not ideal, since they cannot specifically differentiate between those patients who should be treated immediately and those who should avoid over-treatment. Current screening techniques lack specificity, and a decisive diagnosis of PCa is based on prostate biopsy. Although PCa screening is widely utilized nowadays, two thirds of the biopsies performed are still unnecessary. Thus the discovery of non-invasive PCa biomarkers remains urgent. In recent years, the utilization of urine has emerged as an attractive option for the non-invasive detection of PCa. Moreover, a great improvement in high-throughput “omic” techniques has presented considerable opportunities for the identification of new biomarkers. Herein, we will review the most significant urine biomarkers described in recent years, as well as some future prospects in that field.

  18. Current and emerging breast cancer biomarkers

    Directory of Open Access Journals (Sweden)

    Maryam Sana


    Full Text Available Breast cancer treatment has experienced several advancements in the past few decades with the discovery of specific predictive and prognostic biomarkers that make possible the application of individualized therapies. In addition to traditional prognostic factors of breast carcinoma, molecular biomarkers have played a significant role in tumor prediction and treatment. The most frequent genetic alterations of breast cancer are gained along chromosome 1q, 8q, 17q, 20q, and 11q and losses along 8p, 13q, 16q, 18q, and 11q. Interestingly, many of these chromosomal fragments harbor known proto oncogenes or tumor suppressor genes such as BRCA1, BRCA2, p53, HER2-neu, cyclin D1, and cyclin E, which are briefly described in this review.

  19. [Biomarkers in Alzheimer's disease]. (United States)

    García-Ribas, G; López-Sendón Moreno, J L; García-Caldentey, J


    The new diagnostic criteria for Alzheimer's disease (AD) include brain imaging and cerebrospinal fluid (CSF) biomarkers, with the aim of increasing the certainty of whether a patient has an ongoing AD neuropathologic process or not. Three CSF biomarkers, Aß42, total tau, and phosphorylated tau, reflect the core pathological features of AD. It is already known that these pathological processes of AD starts decades before the first symptoms, so these biomarkers may provide means of early disease detection. At least three stages of AD could be identified: preclinical AD, mild cognitive impairment due to AD, and dementia due to AD. In this review, we aim to summarize the CSF biomarker data available for each of these stages. We also review the actual research on blood-based biomarkers. Recent studies on healthy elderly subjects and on carriers of dominantly inherited AD mutations have also found biomarker changes that allow separate groups in these preclinical stages. These studies may aid for segregate populations in clinical trials and objectively evaluate if there are changes over the pathological processes of AD. Limits to widespread use of CSF biomarkers, apart from the invasive nature of the process itself, is the higher coefficient of variation for the analyses between centres. It requires strict pre-analytical and analytical procedures that may make feasible multi-centre studies and global cut-off points for the different stages of AD.

  20. Metabolic products as biomarkers (United States)

    Melancon, M.J.; Alscher, R.; Benson, W.; Kruzynski, G.; Lee, R.F.; Sikka, H.C.; Spies, R.B.; Huggett, Robert J.; Kimerle, Richard A.; Mehrle, Paul M.=; Bergman, Harold L.


    Ideally, endogenous biomarkers would indicate both exposure and environmental effects of toxic chemicals; however, such comprehensive biochemical and physiological indices are currently being developed and, at the present time, are unavailable for use in environmental monitoring programs. Continued work is required to validate the use of biochemical and physiological stress indices as useful components of monitoring programs. Of the compounds discussed only phytochelatins and porphyrins are currently in biomarkers in a useful state; however, glutathione,metallothioneins, stress ethylene, and polyamines are promising as biomarkers in environmental monitoring.

  1. Commentary: statistics for biomarkers. (United States)

    Lovell, David P


    This short commentary discusses Biomarkers' requirements for the reporting of statistical analyses in submitted papers. It is expected that submitters will follow the general instructions of the journal, the more detailed guidance given by the International Committee of Medical Journal Editors, the specific guidelines developed by the EQUATOR network, and those of various specialist groups. Biomarkers expects that the study design and subsequent statistical analyses are clearly reported and that the data reported can be made available for independent assessment. The journal recognizes that there is continuing debate about different approaches to statistical science. Biomarkers appreciates that the field continues to develop rapidly and encourages the use of new methodologies.

  2. Assessment of cisplatin-induced kidney injury using an integrated rodent platform

    Energy Technology Data Exchange (ETDEWEB)

    Chen, Yafei [Global Safety Assessment, AstraZeneca R and D Waltham, MA 02451 (United States); Brott, David [Patient Safety, AstraZeneca R and D Wilmington, DE 19850 (United States); Luo, Wenli [Discovery Statistics, AstraZeneca R and D Waltham, MA 02451 (United States); Gangl, Eric [DMPK, AstraZeneca R and D Waltham, MA 02451 (United States); Kamendi, Harriet; Barthlow, Herbert; Lengel, David; Fikes, James; Kinter, Lewis [Global Safety Assessment, AstraZeneca R and D Waltham, MA 02451 (United States); Valentin, Jean-Pierre [Global Safety Assessment, AstraZeneca R and D Alderley Park, Macclesfield, SK10 4TG (United Kingdom); Bialecki, Russell, E-mail: [Global Safety Assessment, AstraZeneca R and D Waltham, MA 02451 (United States)


    Current diagnosis of drug-induced kidney injury (DIKI) primarily relies on detection of elevated plasma creatinine (Cr) or blood urea nitrogen (BUN) levels; however, both are indices of overall kidney function and changes are delayed with respect to onset of nephron injury. Our aim was to investigate whether early changes in new urinary DIKI biomarkers predict plasma Cr, BUN, renal hemodynamic and kidney morphological changes associated with kidney injury following a single dose of cisplatin (CDDP) using an integrated platform in rodent. Conscious surgically prepared male Han Wistar rats were given a single intraperitoneal dose of CDDP (15 mg/kg). Glomerular filtration rate (GFR), effective renal plasma flow (ERPF), urinalysis, DIKI biomarkers, CDDP pharmacokinetics, blood pressures, heart rate, body temperature and electroencephalogram (EEG) were measured in the same vehicle- or CDDP-treated animals over 72 h. Plasma chemistry (including Cr and BUN) and renal tissues were examined at study termination. Cisplatin caused progressive reductions of GFR, ERPF, heart rate and body temperature from day 1 (0–24 h). DIKI biomarkers including alpha-glutathione S-transferase (α-GST) significantly increased as early as 6 h post-dose, which preceded significant declines of GFR and ERPF (24 h), increased plasma Cr and BUN (72 h), and associated with renal acute tubular necrosis at 72 h post-dose. The present study adds to the current understanding of CDDP action by demonstrating that early increases in urinary excretion of α-GST predict DIKI risk following acute exposure to CDDP in rats, before changes in traditional DIKI markers are evident. - Highlights: ► CDDP causes direct damage to kidneys without affecting EEG or CVS function. ► α-GST and albumin detect DIKI earlier when compared with traditional indices. ► Integrated “cardiovascular-EEG-renal” model to better understand DIKI mechanisms ► Promotes 3R's principles in drug discovery and development.

  3. Analytical strategies in lipidomics and applications in disease biomarker discovery

    NARCIS (Netherlands)

    Hu, C.; Heijden, R. van der; Wang, M.; Greef, J. van der; Hankemeier, T.; Xu, G.


    Lipidomics is a lipid-targeted metabolomics approach aiming at comprehensive analysis of lipids in biological systems. Recently, lipid profiling, or so-called lipidomics research, has captured increased attention due to the well-recognized roles of lipids in numerous human diseases to which lipid-as

  4. Gaucher disease: a model disorder for biomarker discovery

    NARCIS (Netherlands)

    Boot, R.G.; van Breemen, M.J.; Wegdam, W.; Sprenger, R.R.; de Jong, S.; Speijer, D.; Hollak, C.E.M.; van Dussen, L.; Hoefsloot, H.C.J.; Smilde, A.K.; de Koster, C.G.; Vissers, J.P.C.; Aerts, J.M.F.G.


    Gaucher disease is an inherited lysosomal storage disorder, characterized by massive accumulation of glucosylceramide-laden macrophages in the spleen, liver and bone marrow as a consequence of deficient activity of glucocerebrosidase. Gaucher disease has been the playground to develop new therapeuti

  5. Challenges for red blood cell biomarker discovery through proteomics

    NARCIS (Netherlands)

    Barasa, B.A.; Slijper, M.


    Red blood cells are rather unique body cells, since they have lost all organelles when mature, which results in lack of potential to replace proteins that have lost their function. They maintain only a few pathways for obtaining energy and reducing power for the key functions they need to fulfill. T

  6. Validation of New Cancer Biomarkers

    DEFF Research Database (Denmark)

    Duffy, Michael J; Sturgeon, Catherine M; Söletormos, Georg;


    BACKGROUND: Biomarkers are playing increasingly important roles in the detection and management of patients with cancer. Despite an enormous number of publications on cancer biomarkers, few of these biomarkers are in widespread clinical use. CONTENT: In this review, we discuss the key steps...... in advancing a newly discovered cancer candidate biomarker from pilot studies to clinical application. Four main steps are necessary for a biomarker to reach the clinic: analytical validation of the biomarker assay, clinical validation of the biomarker test, demonstration of clinical value from performance...... of the biomarker test, and regulatory approval. In addition to these 4 steps, all biomarker studies should be reported in a detailed and transparent manner, using previously published checklists and guidelines. Finally, all biomarker studies relating to demonstration of clinical value should be registered before...

  7. Biomarker time out. (United States)

    Petzold, Axel; Bowser, Robert; Calabresi, Paolo; Zetterberg, Henrik; Uitdehaag, Bernard M J


    The advancement of knowledge relies on scientific investigations. The timing between asking a question and data collection defines if a study is prospective or retrospective. Prospective studies look forward from a point in time, are less prone to bias and are considered superior to retrospective studies. This conceptual framework conflicts with the nature of biomarker research. New candidate biomarkers are discovered in a retrospective manner. There are neither resources nor time for prospective testing in all cases. Relevant sources for bias are not covered. Ethical questions arise through the time penalty of an overly dogmatic concept. The timing of sample collection can be separated from testing biomarkers. Therefore the moment of formulating a hypothesis may be after sample collection was completed. A conceptual framework permissive to asking research questions without the obligation to bow to the human concept of calendar time would simplify biomarker research, but will require new safeguards against bias.

  8. Biomarkers in Airway Diseases

    Directory of Open Access Journals (Sweden)

    Janice M Leung


    Full Text Available The inherent limitations of spirometry and clinical history have prompted clinicians and scientists to search for surrogate markers of airway diseases. Although few biomarkers have been widely accepted into the clinical armamentarium, the authors explore three sources of biomarkers that have shown promise as indicators of disease severity and treatment response. In asthma, exhaled nitric oxide measurements can predict steroid responsiveness and sputum eosinophil counts have been used to titrate anti-inflammatory therapies. In chronic obstructive pulmonary disease, inflammatory plasma biomarkers, such as fibrinogen, club cell secretory protein-16 and surfactant protein D, can denote greater severity and predict the risk of exacerbations. While the multitude of disease phenotypes in respiratory medicine make biomarker development especially challenging, these three may soon play key roles in the diagnosis and management of airway diseases.

  9. The role of metabolic biomarkers in drug toxicity studies. (United States)

    Schnackenberg, Laura K; Beger, Richard D


    ABSTRACT Metabolic profiling is a technique that can potentially provide more sensitive and specific biomarkers of toxicity than the current clinical measures benefiting preclinical and clinical drug studies. Both nuclear magnetic resonance (NMR) and mass spectrometry (MS) platforms have been used for metabolic profiling studies of drug toxicity. Not only can both techniques provide novel biomarker(s) of toxicity but the combination of both techniques gives a broader range of metabolites evaluated. Changes in metabolic patterns can provide insight into mechanism(s) of toxicity and help to eliminate a potentially toxic new chemical entity earlier in the developmental process. Metabolic profiling offers numerous advantages in toxicological research and screening as sample collection and preparation are relatively simple. Further, sample throughput, reproducibility, and accuracy are high. The area of drug toxicity of therapeutic compounds has already been impacted by metabolic profiling studies and will continue to be impacted as new, more specific biomarker(s) are found. In order for a biomarker or pattern of biomarkers to be accepted, it must be shown that they originate from the target tissue of interest. Metabolic profiling studies are amenable to any biofluid or tissue sample making it possible to link the changes noted in urine for instance as originating from renal injury. Additionally, the ease of sample collection makes it possible to follow a single animal or subject over time in order to determine whether and when the toxicity resolves itself. This review focuses on the advantages of metabolic profiling for drug toxicity studies.

  10. Biomarkers: refining diagnosis and expediting drug development - reality, aspiration and the role of open innovation. (United States)

    Salter, H; Holland, R


    In the last decade, there have been intensive efforts to invent, qualify and use novel biomarkers as a means to improve success rates in drug discovery and development. The biomarkers field is maturing and this article considers whether these research efforts have brought about the expected benefits. The characteristics of a clinically useful biomarker are described and the impact this area of research has had is evaluated by reviewing a few, key examples of emerging biomarkers. There is evidence that the impact has been genuine and is increasing in both the drug and the diagnostic discovery and development processes. Beneficial impact on patient health outcomes seems relatively limited thus far, with the greatest impact in oncology (again, both in terms of novel drugs and in terms of more refined diagnoses and therefore more individualized treatment). However, the momentum of research would indicate that patient benefits are likely to increase substantially and to broaden across multiple therapeutic areas. Even though this research was originally driven by a desire to improve the drug discovery and development process, and was therefore funded with this aim in mind, it seems likely that the largest impact may actually come from more refined diagnosis. Refined diagnosis will facilitate both better allocation of healthcare resources and the use of treatment regimens which are optimized for the individual patient. This article also briefly reviews emerging technological approaches and how they relate to the challenges inherent in biomarker discovery and validation, and discusses the role of public/private partnerships in innovative biomarker research.

  11. Usability of Discovery Portals

    NARCIS (Netherlands)

    Bulens, J.D.; Vullings, L.A.E.; Houtkamp, J.M.; Vanmeulebrouk, B.


    As INSPIRE progresses to be implemented in the EU, many new discovery portals are built to facilitate finding spatial data. Currently the structure of the discovery portals is determined by the way spatial data experts like to work. However, we argue that the main target group for discovery portals

  12. Exploration of new HCC biomarkers

    Directory of Open Access Journals (Sweden)

    Regina M. Santella


    Full Text Available

    Analysis of plasma/serum for levels of viral antigens or antibodies to viral proteins has been used extensively as an early biomarker of potential risk of HCC. In addition, detection of elevated levels of alpha-fetoprotein is commonly used for early identification of HCC. Unfortunately, both of these approaches are not highly sensitive or specific. As a result, there is continuing investigation to identify additional biomarkers that may help in the early identification of cases. The use of DNA isolated from plasma or serum for detection of gene specific methylation has been discussed previously. In addition, tumor DNA isolated from blood has been analyzed for the presence of p53 mutations and found in a subset of cases to be present years prior to diagnosis as for methylated DNA. The general level of DNA present in blood has also been suggested as a potential biomarker of cancer.

    Among the newer methods being tested are the detection of specific mutations in HBV. In many cases of HCC in China and Africa a double mutation, an A to T transversion at nucleotide 1762 and a G to A transition at nucleotide 1764 (1762T/1764A have been found. These mutations have been associated with increased severity of HBV infection and cirrhosis suggesting that they might be a useful biomarker for high risk subjects.

    The field of proteomics also holds promise for the development of new biomarkers. A number of groups are developing mass spectrometry methods for the identification of serum/plasma proteomic patterns that will distinguish bloods of HCC cases from those of controls. While some interesting preliminary data have been developed for several cancers, much additional work needs to be done in this area

  13. Biomarkers intersect with the exposome. (United States)

    Rappaport, Stephen M


    The exposome concept promotes use of omic tools for discovering biomarkers of exposure and biomarkers of disease in studies of diseased and healthy populations. A two-stage scheme is presented for profiling omic features in serum to discover molecular biomarkers and then for applying these biomarkers in follow-up studies. The initial component, referred to as an exposome-wide-association study (EWAS), employs metabolomics and proteomics to interrogate the serum exposome and, ultimately, to identify, validate and differentiate biomarkers of exposure and biomarkers of disease. Follow-up studies employ knowledge-driven designs to explore disease causality, prevention, diagnosis, prognosis and treatment.

  14. Parkinson's disease biomarkers program brain imaging repository. (United States)

    Ofori, Edward; Du, Guangwei; Babcock, Debra; Huang, Xuemei; Vaillancourt, David E


    The Parkinson's Disease Biomarkers Program (PDBP) is a multi-site study designed to identify Parkinson's disease (PD) biomarkers that can be used to improve the understanding of PD pathophysiology and to develop tools that provide novel measures to evaluate PD clinical trials. The PDBP consortium comprises numerous individual projects of which two are specifically geared to the development of brain imaging markers for diagnosis, progression, and prognosis of PD or related disorders. All study data from PD patients, atypical Parkinsonian patients, patients with essential tremor, and healthy controls collected from the sites are integrated in the PDBP database and will be publically available. All subjects are asked to submit blood samples, and undergo a battery of clinical evaluations that cover motor, cognitive, and other background information. In addition, a subset of subjects contributed cerebrospinal fluid samples. A restricted access, web-based Data Management Resource facilitates rapid sharing of data and biosamples across the entire PD research community. The PDBP consortium is a useful resource for research and collaboration aimed at the discovery of biomarkers and their use in understanding the pathophysiology of PD.

  15. Microfluidic Sensing Platforms for Medicine and Diagnostics

    DEFF Research Database (Denmark)

    Kiilerich-Pedersen, Katrine

    the specialized laboratory. Microfluidic cell migration devices, imitating in vivo conditions were developed with success, improving the in vitro experimental setup for basic research and drug discovery. Polymer biosensors have reached a new level of maturity, and pathogen detection could benefit from...... the integration of electrical sensors into low cost plastic microdevices pioneering point of care testing. The presented biosensing platforms have potential for scaling up towards high throughput screening, and are adaptable to other applications in medicine and diagnostics, and other fields....

  16. Product Platform Modeling

    DEFF Research Database (Denmark)

    Pedersen, Rasmus

    on the notion that reuse and encapsulation of platform elements are fundamental characteristics of a product platform. Reuse covers the desire to reuse and share certain assets across a family of products and/or across generations of products. Product design solutions and principles are often regarded...... as important assets in a product platform, yet activities, working patterns, processes and knowledge can also be reused in a platform approach. Encapsulation is seen as a process in which the different elements of a platform are grouped into well defined and self-contained units which are decoupled from each......This PhD thesis has the title Product Platform Modelling. The thesis is about product platforms and visual product platform modelling. Product platforms have gained an increasing attention in industry and academia in the past decade. The reasons are many, yet the increasing globalisation...

  17. Biomarkers for systemic lupus erythematosus. (United States)

    Ahearn, Joseph M; Liu, Chau-Ching; Kao, Amy H; Manzi, Susan


    The urgent need for lupus biomarkers was demonstrated in September 2011 during a Workshop sponsored by the Food and Drug Administration: Potential Biomarkers Predictive of Disease Flare. After 2 days of discussion and more than 2 dozen presentations from thought leaders in both industry and academia, it became apparent that highly sought biomarkers to predict lupus flare have not yet been identified. Even short of the elusive biomarker of flare, few biomarkers for systemic lupus erythematosus (SLE) diagnosis, monitoring, and stratification have been validated and employed for making clinical decisions. This lack of reliable, specific biomarkers for SLE hampers proper clinical management of patients with SLE and impedes development of new lupus therapeutics. As such, the intensity of investigation to identify lupus biomarkers is climbing a steep trajectory, lending cautious optimism that a validated panel of biomarkers for lupus diagnosis, monitoring, stratification, and prediction of flare may soon be in hand.

  18. Detecting Blood-Based Biomarkers in Metastatic Breast Cancer: A Systematic Review of Their Current Status and Clinical Utility (United States)

    Berghuis, A. M. Sofie; Koffijberg, Hendrik; Prakash, Jai; Terstappen, Leon W. M. M.; IJzerman, Maarten J.


    Reviews on circulating biomarkers in breast cancer usually focus on one single biomarker or a selective group of biomarkers. An overview summarizing the discovery and evaluation of all blood-based biomarkers in metastatic breast cancer is lacking. This systematic review aims to identify the available evidence of known blood-based biomarkers in metastatic breast cancer, regarding their clinical utility and state-of-the-art position in the validation process. The initial search yielded 1078 original studies, of which 420 were assessed for eligibility. A total of 320 studies were included in the final synthesis. A Development, Evaluation and Application Chart (DEAC) of all biomarkers was developed. Most studies focus on identifying new biomarkers and search for relations between these biomarkers and traditional molecular characteristics. Biomarkers are usually investigated in only one study (68.8%). Only 9.8% of all biomarkers was investigated in more than five studies. Circulating tumor cells, gene expression within tumor cells and the concentration of secreted proteins are the most frequently investigated biomarkers in liquid biopsies. However, there is a lack of studies focusing on identifying the clinical utility of these biomarkers, by which the additional value still seems to be limited according to the investigated evidence. PMID:28208771

  19. Biomarkers in Barrett's esophagus. (United States)

    Reid, Brian J; Blount, Patricia L; Rabinovitch, Peter S


    This article provides a framework for clinicians who are attempting the difficult task of interpreting the Barrett's biomarker literature with the goal of improving care for their patients. Although many articles. including more that 60 proposed biomarkers, have been published on this subject, only a few describe phase 3 and 4 studies that are of interest to the clinical gastroenterologist (Table 1). For year, dysplasia grade has been the sole means of risk stratification for patients with BE, and it likely will continue to be used in the foreseeable future. The current authors believe that dysplasia classification can be valuable using the team management approach and quality controls described previously. Significant problems, however, have emerged in phase 2 through 4 studies of dysplasia that make it imperative for the Barrett's field to incorporate additional biomarkers as they are validated. These problems include poor reproducibility of dysplasia interpretations, poor predictive value for negative, indefinite, and low-grade dysplasia, and inconsistent results for HGD in different centers, all of which makes it virtually impossible to develop national guidelines for surveillance. Some studies have even suggested that endoscopic biopsy surveillance using dysplasia may not be worthwhile. Currently, flow cytometric tetraploidy and aneuploidy have progressed furthest in biomarker validation (see Table 1). With proper handling, endoscopic biopsy specimens can be shipped to reference laboratories that have the instruments, computer analytic methods, and expertise to reproducibly detect tetraploidy and aneuploidy. The results of phase 4 studies indicate that flow cytometry appears to be useful in detecting a subset of patients who do not have HGD and yet have an increased risk of progression to cancer that cannot be identified by dysplasia grade. For many reasons, the authors anticipate that the number of validated biomarkers will increase substantially in the

  20. Update on Biomarkers for the Detection of Endometriosis

    Directory of Open Access Journals (Sweden)

    Amelie Fassbender


    Full Text Available Endometriosis is histologically characterized by the displacement of endometrial tissue to extrauterine locations including the pelvic peritoneum, ovaries, and bowel. An important cause of infertility and pelvic pain, the individual and global socioeconomic burden of endometriosis is significant. Laparoscopy remains the gold standard for the diagnosis of the condition. However, the invasive nature of surgery, coupled with the lack of a laboratory biomarker for the disease, results in a mean latency of 7–11 years from onset of symptoms to definitive diagnosis. Unfortunately, the delay in diagnosis may have significant consequences in terms of disease progression. The discovery of a sufficiently sensitive and specific biomarker for the nonsurgical detection of endometriosis promises earlier diagnosis and prevention of deleterious sequelae and represents a clear research priority. In this review, we describe and discuss the current status of biomarkers of endometriosis in plasma, urine, and endometrium.

  1. Biomarkers of Renal Tumor Burden and Progression in TSC (United States)


    TSC2 is overrepresented among patients requiring biopsy or embolization of renal lesions. The biomarker discovery of this project was disappointing...due to contiguous gene syndrome involving TSC2 and PKD1. • Approximately 67% of patients had renal masses that were primarily AMLs. Biopsies of...genotyping performed. • Of 13 patients requiring biopsy of suspicious renal lesions, 9 had TSC2 gene mutations, one had no mutation identified, and 2

  2. Urinary biomarkers in hexachloro-1:3-butadiene-induced acute kidney injury in the female Hanover Wistar rat; correlation of α-glutathione S-transferase, albumin and kidney injury molecule-1 with histopathology and gene expression. (United States)

    Swain, Aubrey; Turton, John; Scudamore, Cheryl L; Pereira, Ines; Viswanathan, Neeti; Smyth, Rosemary; Munday, Michael; McClure, Fiona; Gandhi, Mitul; Sondh, Surjit; York, Malcolm


    Hexachloro-1:3-butadiene (HCBD) causes kidney injury specific to the pars recta of the proximal tubule. In the present studies, injury to the nephron was characterized at 24 h following a single dose of HCBD, using a range of quantitative urinary measurements, renal histopathology and gene expression. Multiplexed renal biomarker measurements were performed using both the Meso Scale Discovery (MSD) and Rules Based Medicine platforms. In a second study, rats were treated with a single nephrotoxic dose of HCBD and the time course release of a range of traditional and newer urinary biomarkers was followed over a 25 day period. Urinary albumin (a marker of both proximal tubular function and glomerular integrity) and α-glutathione S-transferase (α-GST, a proximal tubular cell marker of cytoplasmic leakage) showed the largest fold change at 24 h (day 1) after dosing. Most other markers measured on either the MSD or RBM platforms peaked on day 1 or 2 post-dosing, whereas levels of kidney injury molecule-1 (KIM-1), a marker of tubular regeneration, peaked on day 3/4. Therefore, in rat proximal tubular nephrotoxicity, the measurement of urinary albumin, α-GST and KIM-1 is recommended as they potentially provide useful information about the function, degree of damage and repair of the proximal tubule. Gene expression data provided useful confirmatory information regarding exposure of the kidney and liver to HCBD, and the response of these tissues to HCBD in terms of metabolism, oxidative stress, inflammation, and regeneration and repair.

  3. A microfluidic platform with a flow-balanced fluidic network for osteoarthritis diagnosis (United States)

    Kim, Kangil; Park, Yoo Min; Yoon, Hyun C.; Yang, Sang Sik


    Osteoarthritis (OA) is one of the most common human diseases, and the occurrence of OA is likely to increase with the increase of population ages. The diagnosis of OA is based on patientrelevant measures, structural measures, and measurement of biomarkers that are released through joint metabolism. Traditionally, radiography or magnetic resonance imaging (MRI) is used to diagnose OA and predict its course. However, diagnostic imaging in OA provides only indirect information on pathology and treatment response. A sensing of OA based on the detection of biomarkers insignificantly improves the accuracy and sensitivity of diagnosis and reduces the cost compared with that of radiography or MRI. In our former study, we proposed microfluidic platform to detect biomarker of OA. But the platform can detect only one biomarker because it has one microfluidic channel. In this report, we proposes microfluidic platform that can detect several biomarkers. The proposed platform has three layers. The bottom layer has gold patterns on a Si substrate for optical sensing. The middle layer and top layer were fabricated by polydimethysiloxane (PDMS) using soft-lithography. The middle layer has four channels connecting top layer to bottom layer. The top layer consists of one sample injection inlet, and four antibody injection inlets. To this end, we designed a flow-balanced microfluidic network using analogy between electric and hydraulic systems. Also, the designed microfluidic network was confirmed by finite element model (FEM) analysis using COMSOL FEMLAB. To verify the efficiency of fabricated platform, the optical sensing test was performed to detect biomarker of OA using fluorescence microscope. We used cartilage oligomeric matrix protein (COMP) as biomarker because it reflects specific changes in joint tissues. The platform successfully detected various concentration of COMP (0, 100, 500, 1000 ng/ml) at each chamber. The effectiveness of the microfluidic platform was verified

  4. Emerging Biomarkers in Glioblastoma

    Energy Technology Data Exchange (ETDEWEB)

    McNamara, Mairéad G.; Sahebjam, Solmaz; Mason, Warren P., E-mail: [Pencer Brain Tumor Centre, Princess Margaret Cancer Centre, 610 University Avenue, Toronto, Ontario M5G 2M9 (Canada)


    Glioblastoma, the most common primary brain tumor, has few available therapies providing significant improvement in survival. Molecular signatures associated with tumor aggressiveness as well as with disease progression and their relation to differences in signaling pathways implicated in gliomagenesis have recently been described. A number of biomarkers which have potential in diagnosis, prognosis and prediction of response to therapy have been identified and along with imaging modalities could contribute to the clinical management of GBM. Molecular biomarkers including O(6)-methlyguanine-DNA-methyltransferase (MGMT) promoter and deoxyribonucleic acid (DNA) methylation, loss of heterozygosity (LOH) of chromosomes 1p and 19q, loss of heterozygosity 10q, isocitrate dehydrogenase (IDH) mutations, epidermal growth factor receptor (EGFR), epidermal growth factor, latrophilin, and 7 transmembrane domain-containing protein 1 on chromosome 1 (ELTD1), vascular endothelial growth factor (VEGF), tumor suppressor protein p53, phosphatase and tensin homolog (PTEN), p16INK4a gene, cytochrome c oxidase (CcO), phospholipid metabolites, telomerase messenger expression (hTERT messenger ribonucleic acid [mRNA]), microRNAs (miRNAs), cancer stem cell markers and imaging modalities as potential biomarkers are discussed. Inclusion of emerging biomarkers in prospective clinical trials is warranted in an effort for more effective personalized therapy in the future.

  5. Digital pathology and image analysis in tissue biomarker research. (United States)

    Hamilton, Peter W; Bankhead, Peter; Wang, Yinhai; Hutchinson, Ryan; Kieran, Declan; McArt, Darragh G; James, Jacqueline; Salto-Tellez, Manuel


    Digital pathology and the adoption of image analysis have grown rapidly in the last few years. This is largely due to the implementation of whole slide scanning, advances in software and computer processing capacity and the increasing importance of tissue-based research for biomarker discovery and stratified medicine. This review sets out the key application areas for digital pathology and image analysis, with a particular focus on research and biomarker discovery. A variety of image analysis applications are reviewed including nuclear morphometry and tissue architecture analysis, but with emphasis on immunohistochemistry and fluorescence analysis of tissue biomarkers. Digital pathology and image analysis have important roles across the drug/companion diagnostic development pipeline including biobanking, molecular pathology, tissue microarray analysis, molecular profiling of tissue and these important developments are reviewed. Underpinning all of these important developments is the need for high quality tissue samples and the impact of pre-analytical variables on tissue research is discussed. This requirement is combined with practical advice on setting up and running a digital pathology laboratory. Finally, we discuss the need to integrate digital image analysis data with epidemiological, clinical and genomic data in order to fully understand the relationship between genotype and phenotype and to drive discovery and the delivery of personalized medicine.

  6. Academic Drug Discovery Centres

    DEFF Research Database (Denmark)

    Kirkegaard, Henriette Schultz; Valentin, Finn


    Academic drug discovery centres (ADDCs) are seen as one of the solutions to fill the innovation gap in early drug discovery, which has proven challenging for previous organisational models. Prior studies of ADDCs have identified the need to analyse them from the angle of their economic and organi......Academic drug discovery centres (ADDCs) are seen as one of the solutions to fill the innovation gap in early drug discovery, which has proven challenging for previous organisational models. Prior studies of ADDCs have identified the need to analyse them from the angle of their economic...... their performance....

  7. Reliable knowledge discovery

    CERN Document Server

    Dai, Honghua; Smirnov, Evgueni


    Reliable Knowledge Discovery focuses on theory, methods, and techniques for RKDD, a new sub-field of KDD. It studies the theory and methods to assure the reliability and trustworthiness of discovered knowledge and to maintain the stability and consistency of knowledge discovery processes. RKDD has a broad spectrum of applications, especially in critical domains like medicine, finance, and military. Reliable Knowledge Discovery also presents methods and techniques for designing robust knowledge-discovery processes. Approaches to assessing the reliability of the discovered knowledge are introduc

  8. Neuroimaging Biomarkers for Psychosis (United States)

    Hager, Brandon M.


    Background Biomarkers provide clinicians with a predictable model for the diagnosis, treatment and follow-up of medical ailments. Psychiatry has lagged behind other areas of medicine in the identification of biomarkers for clinical diagnosis and treatment. In this review, we investigated the current state of neuroimaging as it pertains to biomarkers for psychosis. Methods We reviewed systematic reviews and meta-analyses of the structural (sMRI), functional (fMRI), diffusion-tensor (DTI), Positron emission tomography (PET) and spectroscopy (MRS) studies of subjects at-risk or those with an established schizophrenic illness. Only articles reporting effect-sizes and confidence intervals were included in an assessment of robustness. Results Out of the identified meta-analyses and systematic reviews, 21 studies met the inclusion criteria for assessment. There were 13 sMRI, 4 PET, 3 MRS, and 1 DTI studies. The search terms included in the current review encompassed familial high risk (FHR), clinical high risk (CHR), First episode (FES), Chronic (CSZ), schizophrenia spectrum disorders (SSD), and healthy controls (HC). Conclusions Currently, few neuroimaging biomarkers can be considered ready for diagnostic use in patients with psychosis. At least in part, this may be related to the challenges inherent in the current symptom-based approach to classifying these disorders. While available studies suggest a possible value of imaging biomarkers for monitoring disease progression, more systematic research is needed. To date, the best value of imaging data in psychoses has been to shed light on questions of disease pathophysiology, especially through the characterization of endophenotypes. PMID:25883891

  9. Continuous Platform Development

    DEFF Research Database (Denmark)

    Nielsen, Ole Fiil

    low risks and investments but also with relatively fuzzy results. When looking for new platform projects, it is important to make sure that the company and market is ready for the introduction of platforms, and to make sure that people from marketing and sales, product development, and downstream......, but continuous product family evolution challenges this strategy. The concept of continuous platform development is based on the fact that platform development should not be a one-time experience but rather an ongoing process of developing new platforms and updating existing ones, so that product family...... evolution does not make the platforms irrelevant. This research is based on case studies and applications in the two Danish companies, LEGO and Grundfos, where several platform development projects have been followed. LEGO is exceptional for their long experience with platform development and maintenance...

  10. Trace cancer biomarker quantification using polystyrene-functionalized gold nanorods (United States)

    Wu, Jian; Li, Wei; Hajisalem, Ghazal; Lukach, Ariella; Kumacheva, Eugenia; Hof, Fraser; Gordon, Reuven


    We demonstrate the application of polystyrene-functionalized gold nanorods (AuNRs) as a platform for surface enhanced Raman scattering (SERS) quantification of the exogenous cancer biomarker Acetyl Amantadine (AcAm). We utilize the hydrophobicity of the polystyrene attached to the AuNR surface to capture the hydrophobic AcAm from solution, followed by drying and detection using SERS. We achieve a detection limit of 16 ng/mL using this platform. This result shows clinical potential for low-cost early cancer detection. PMID:25574423

  11. Mobile platform security

    CERN Document Server

    Asokan, N; Dmitrienko, Alexandra


    Recently, mobile security has garnered considerable interest in both the research community and industry due to the popularity of smartphones. The current smartphone platforms are open systems that allow application development, also for malicious parties. To protect the mobile device, its user, and other mobile ecosystem stakeholders such as network operators, application execution is controlled by a platform security architecture. This book explores how such mobile platform security architectures work. We present a generic model for mobile platform security architectures: the model illustrat

  12. Platform development supportedby gaming

    DEFF Research Database (Denmark)

    Mikkola, Juliana Hsuan; Hansen, Poul H. Kyvsgård


    The challenge of implementing industrial platforms in practice can be described as a configuration problem caused by high number of variables, which often have contradictory influences on the total performance of the firm. Consequently, the specific platform decisions become extremely complex......, based on the portfolio management thinking, to measure the degree of modularity embedded in a given platform and to what extent it is aligned with other platforms....

  13. Biomarkers for personalized oncology: recent advances and future challenges. (United States)

    Kalia, Madhu


    Cancer is a group of diseases characterized by the uncontrolled growth and spread of abnormal cells and oncology is a branch of medicine that deals with tumors. The last decade has seen significant advances in the development of biomarkers in oncology that play a critical role in understanding molecular and cellular mechanisms which drive tumor initiation, maintenance and progression. Clinical molecular diagnostics and biomarker discoveries in oncology are advancing rapidly as we begin to understand the complex mechanisms that transform a normal cell into an abnormal one. These discoveries have fueled the development of novel drug targets and new treatment strategies. The standard of care for patients with advanced-stage cancers has shifted away from an empirical treatment strategy based on the clinical-pathological profile to one where a biomarker driven treatment algorithm based on the molecular profile of the tumor is used. Recent advances in multiplex genotyping technologies and high-throughput genomic profiling by next-generation sequencing make possible the rapid and comprehensive analysis of the cancer genome of individual patients even from very little tumor biopsy material. Predictive (diagnostic) biomarkers are helpful in matching targeted therapies with patients and in preventing toxicity of standard (systemic) therapies. Prognostic biomarkers identify somatic germ line mutations, changes in DNA methylation, elevated levels of microRNA (miRNA) and circulating tumor cells (CTC) in blood. Predictive biomarkers using molecular diagnostics are currently in use in clinical practice of personalized oncotherapy for the treatment of five diseases: chronic myeloid leukemia, colon, breast, lung cancer and melanoma and these biomarkers are being used successfully to evaluate benefits that can be achieved through targeted therapy. Examples of these molecularly targeted biomarker therapies are: tyrosine kinase inhibitors in chronic myeloid leukemia and

  14. ITS Platform North Denmark

    DEFF Research Database (Denmark)

    Lahrmann, Harry; Agerholm, Niels; Juhl, Jens;


    This paper presents the project entitled “ITS Platform North Denmark” which is used as a test platform for Intelligent Transportation System (ITS) solutions. The platform consists of a newly developed GNSS/GPRS On Board Unit (OBU) to be installed in 500 cars, a backend server and a specially...

  15. Proteomics for Cerebrospinal Fluid Biomarker Identification in Parkinsons Disease: Methods and Critical Aspects

    Directory of Open Access Journals (Sweden)

    Antonio Conti


    Full Text Available Parkinson's disease (PD, similar with other neurodegenerative disorders, would benefit from the identification of early biomarkers for differential diagnosis and prognosis to address prompt clinical treatments. Together with hypothesis driven approaches, PD has been investigated by high-throughput differential proteomic analysis of cerebrospinal fluid (CSF protein content. The principal methodologies and techniques utilized in the proteomics field for PD biomarker discovery from CSF are presented in this mini review. The positive aspects and challenges in proteome-based biomarker research are also discussed.

  16. Assessed and Emerging Biomarkers in Stroke and Training-Mediated Stroke Recovery: State of the Art

    Directory of Open Access Journals (Sweden)

    Marialuisa Gandolfi


    Full Text Available Since the increasing update of the biomolecular scientific literature, biomarkers in stroke have reached an outstanding and remarkable revision in the very recent years. Besides the diagnostic and prognostic role of some inflammatory markers, many further molecules and biological factors have been added to the list, including tissue derived cytokines, growth factor-like molecules, hormones, and microRNAs. The literatures on brain derived growth factor and other neuroimmune mediators, bone-skeletal muscle biomarkers, cellular and immunity biomarkers, and the role of microRNAs in stroke recovery were reviewed. To date, biomarkers represent a possible challenge in the diagnostic and prognostic evaluation of stroke onset, pathogenesis, and recovery. Many molecules are still under investigation and may become promising and encouraging biomarkers. Experimental and clinical research should increase this list and promote new discoveries in this field, to improve stroke diagnosis and treatment.

  17. Managing Clouds in Cloud Platforms

    CERN Document Server

    Ahmat, Kamal A


    Managing cloud services is a fundamental challenge in todays virtualized environments. These challenges equally face both providers and consumers of cloud services. The issue becomes even more challenging in virtualized environments that support mobile clouds. Cloud computing platforms such as Amazon EC2 provide customers with flexible, on demand resources at low cost. However, they fail to provide seamless infrastructure management and monitoring capabilities that many customers may need. For instance, Amazon EC2 doesn't fully support cloud services automated discovery and it requires a private set of authentication credentials., on the other hand, do not provide monitoring access to their underlying systems. Moreover, these systems fail to provide infrastructure monitoring of heterogenous and legacy systems that don't support agents. In this work, we explore how to build a cloud management system that combines heterogeneous management of virtual resources with comprehensive management of phys...

  18. Single cell analytic tools for drug discovery and development (United States)

    Heath, James R.; Ribas, Antoni; Mischel, Paul S.


    The genetic, functional, or compositional heterogeneity of healthy and diseased tissues presents major challenges in drug discovery and development.1-3 In cancers, heterogeneity may be essential for tumor stability,4 but its precise role in tumor biology is poorly resolved. This challenges the design of accurate disease models for use in drug development, and can confound the interpretation of biomarker levels, and of patient responses to specific therapies. The complex nature of heterogeneous tissues has motivated the development of tools for single cell genomic, transcriptomic, and multiplex proteomic analysis. We review these tools, assess their advantages and limitations, and explore their potential applications in drug discovery and development. PMID:26669673

  19. Single-cell analysis tools for drug discovery and development. (United States)

    Heath, James R; Ribas, Antoni; Mischel, Paul S


    The genetic, functional or compositional heterogeneity of healthy and diseased tissues presents major challenges in drug discovery and development. Such heterogeneity hinders the design of accurate disease models and can confound the interpretation of biomarker levels and of patient responses to specific therapies. The complex nature of virtually all tissues has motivated the development of tools for single-cell genomic, transcriptomic and multiplex proteomic analyses. Here, we review these tools and assess their advantages and limitations. Emerging applications of single cell analysis tools in drug discovery and development, particularly in the field of oncology, are discussed.

  20. Leveraging big data to transform target selection and drug discovery (United States)

    Butte, AJ


    The advances of genomics, sequencing, and high throughput technologies have led to the creation of large volumes of diverse datasets for drug discovery. Analyzing these datasets to better understand disease and discover new drugs is becoming more common. Recent open data initiatives in basic and clinical research have dramatically increased the types of data available to the public. The past few years have witnessed successful use of big data in many sectors across the whole drug discovery pipeline. In this review, we will highlight the state of the art in leveraging big data to identify new targets, drug indications, and drug response biomarkers in this era of precision medicine. PMID:26659699

  1. Higgs Discovery Movie

    CERN Multimedia


    The ATLAS & CMS Experiments Celebrate the 2nd Anniversary of the Discovery of the Higgs boson. Here, are some images of the path from LHC startup to Nobel Prize, featuring a musical composition by Roger Zare, performed by the Donald Sinta Quartet, called “LHC”. Happy Discovery Day!

  2. Serendipity and Scientific Discovery. (United States)

    Rosenman, Martin F.


    The discovery of penicillin is cited in a discussion of the role of serendipity as it relates to scientific discovery. The importance of sagacity as a personality trait is noted. Successful researchers have questioning minds, are willing to view data from several perspectives, and recognize and appreciate the unexpected. (JW)

  3. Friends' Discovery Camp (United States)

    Seymour, Seth


    This article features Friends' Discovery Camp, a program that allows children with and without autism spectrum disorder to learn and play together. In Friends' Discovery Camp, campers take part in sensory-rich experiences, ranging from hands-on activities and performing arts to science experiments and stories teaching social skills. Now in its 7th…

  4. Service discovery at home

    NARCIS (Netherlands)

    Sundramoorthy, Vasughi; Scholten, Hans; Jansen, Pierre; Hartel, Pieter


    Service discovery is a fairly new field that kicked off since the advent of ubiquitous computing and has been found essential in the making of intelligent networks by implementing automated discovery and remote control between devices. This paper provides an overview and comparison of several promin

  5. Early Stage Health Technology Assessment for Precision Biomarkers in Oral Health and Systems Medicine


    Steuten, Lotte M.G.


    Health technology assessment (HTA) is a crucial science that influences the responsible and evidence-based transition of new discoveries from laboratory to applications in the clinic and society. HTA has recently moved “upstream” so as to assess technologies from their onset at their discovery, design, or planning phase. Biomarker research is relatively recent in oral health, but growing rapidly with investments made to advance dentistry and oral health and importantly, to build effective bri...

  6. "Eureka, Eureka!" Discoveries in Science (United States)

    Agarwal, Pankaj


    Accidental discoveries have been of significant value in the progress of science. Although accidental discoveries are more common in pharmacology and chemistry, other branches of science have also benefited from such discoveries. While most discoveries are the result of persistent research, famous accidental discoveries provide a fascinating…

  7. Parallel Frequent Pattern Discovery: Challenges and Methodology

    Institute of Scientific and Technical Information of China (English)


    Parallel frequent pattern discovery algorithms exploit parallel and distributed computing resources to relieve the sequential bottlenecks of current frequent pattern mining (FPM) algorithms. Thus, parallel FPM algorithms achieve better scalability and performance, so they are attracting much attention in the data mining research community. This paper presents a comprehensive survey of the state-of-the-art parallel and distributed frequent pattern mining algorithms with more emphasis on pattern discovery from complex data (e.g., sequences and graphs) on various platforms. A review of typical parallel FPM algorithms uncovers the major challenges, methodologies, and research problems in the field of parallel frequent pattern discovery,such as work-load balancing, finding good data layouts, and data decomposition. This survey also indicates a dramatic shift of the research interest in the field from the simple parallel frequent itemset mining on traditional parallel and distributed platforms to parallel pattern mining of more complex data on emerging architectures, such as multi-core systems and the increasingly mature grid infrastructure.

  8. Biomarkers of Selenium Status

    Directory of Open Access Journals (Sweden)

    Gerald F. Combs, Jr.


    Full Text Available The essential trace element, selenium (Se, has multiple biological activities, which depend on the level of Se intake. Relatively low Se intakes determine the expression of selenoenzymes in which it serves as an essential constituent. Higher intakes have been shown to have anti-tumorigenic potential; and very high Se intakes can produce adverse effects. This hierarchy of biological activities calls for biomarkers informative at different levels of Se exposure. Some Se-biomarkers, such as the selenoproteins and particularly GPX3 and SEPP1, provide information about function directly and are of value in identifying nutritional Se deficiency and tracking responses of deficient individuals to Se-treatment. They are useful under conditions of Se intake within the range of regulated selenoprotein expression, e.g., for humans <55 μg/day and for animals <20 μg/kg diet. Other Se-biomarkers provide information indirectly through inferences based on Se levels of foods, tissues, urine or feces. They can indicate the likelihood of deficiency or adverse effects, but they do not provide direct evidence of either condition. Their value is in providing information about Se status over a wide range of Se intake, particularly from food forms. There is need for additional Se biomarkers particularly for assessing Se status in non-deficient individuals for whom the prospects of cancer risk reduction and adverse effects risk are the primary health considerations. This would include determining whether supranutritional intakes of Se may be required for maximal selenoprotein expression in immune surveillance cells. It would also include developing methods to determine low molecular weight Se-metabolites, i.e., selenoamino acids and methylated Se-metabolites, which to date have not been detectable in biological specimens. Recent analytical advances using tandem liquid chromatography-mass spectrometry suggest prospects for detecting these metabolites.

  9. Discovery of Early Permian Reefs in Xichang Basin, Southwestern China

    Institute of Scientific and Technical Information of China (English)

    Qin Jianxiong; Zeng Yunfu; Wu Yong


    @@ In 1992, Lower Permian reefs were found in various stratigraphic sections in such counties as Ganluo,Puge, and Butuo, in Xichang Basin. This discovery not only promotes the development of Lower Permain sedimentology in Xichang Basin, but also is of great significance for oil-gas exploration along the western margin of Yangtze platform.

  10. Nanomagnetic competition assay for low-abundance protein biomarker quantification in unprocessed human sera. (United States)

    Li, Yuanpeng; Srinivasan, Balasubramanian; Jing, Ying; Yao, Xiaofeng; Hugger, Marie A; Wang, Jian-Ping; Xing, Chengguo


    A novel giant magnetoresistive sensor and uniform high-magnetic-moment FeCo nanoparticles (12.8 nm)-based detecting platform with minimized detecting distance was developed for rapid biomolecule quantification from body fluids. Such a system demonstrates specific, accurate, and quick detection and quantification of interleukin-6, a low-abundance protein and a potential cancer biomarker, directly in 4 muL of unprocessed human sera. This platform is expected to facilitate the identification and validation of disease biomarkers. It may eventually lead to a low-cost personal medical device for chronic disease early detection, diagnosis, and prognosis.

  11. mySearch changed my life – a resource discovery journey



    mySearch: the federated years mySearch: choosing a new platform mySearch: EBSCO Discovery Service (EDS) Implementing a new system Technical challenges Has resource discovery enhanced experiences at BU? Ongoing challenges Implications for library management systems Implications for information literacy Questions

  12. IDBD: infectious disease biomarker database. (United States)

    Yang, In Seok; Ryu, Chunsun; Cho, Ki Joon; Kim, Jin Kwang; Ong, Swee Hoe; Mitchell, Wayne P; Kim, Bong Su; Oh, Hee-Bok; Kim, Kyung Hyun


    Biomarkers enable early diagnosis, guide molecularly targeted therapy and monitor the activity and therapeutic responses across a variety of diseases. Despite intensified interest and research, however, the overall rate of development of novel biomarkers has been falling. Moreover, no solution is yet available that efficiently retrieves and processes biomarker information pertaining to infectious diseases. Infectious Disease Biomarker Database (IDBD) is one of the first efforts to build an easily accessible and comprehensive literature-derived database covering known infectious disease biomarkers. IDBD is a community annotation database, utilizing collaborative Web 2.0 features, providing a convenient user interface to input and revise data online. It allows users to link infectious diseases or pathogens to protein, gene or carbohydrate biomarkers through the use of search tools. It supports various types of data searches and application tools to analyze sequence and structure features of potential and validated biomarkers. Currently, IDBD integrates 611 biomarkers for 66 infectious diseases and 70 pathogens. It is publicly accessible at and

  13. Network-based drugs and biomarkers. (United States)

    Erler, Janine T; Linding, Rune


    The structure and dynamics of protein signalling networks governs cell decision processes and the formation of tissue boundaries. Complex diseases such as cancer and diabetes are diseases of such networks. Therefore approaches that can give insight into how these networks change during disease progression are crucial for better understanding, detection and intervention. The era of network medicine has begun; however, there are fundamental principles associated with molecular networks that are essential to consider for this field to succeed. Here, we introduce network biology and some of its associated technologies. We then focus on the multivariate nature of cellular networks and how this has implications for biomarker and drug discovery using cancer metastasis as an example.

  14. The NINDS Parkinson's disease biomarkers program: The Ninds Parkinson's Disease Biomarkers Program

    Energy Technology Data Exchange (ETDEWEB)

    Rosenthal, Liana S. [Department of Neurology, Johns Hopkins University School of Medicine, Baltimore Maryland USA; Drake, Daniel [Department of Biostatistics, Columbia University, New York New York USA; Alcalay, Roy N. [Department of Neurology, Columbia University, New York New York USA; Babcock, Debra [National Institute of Neurological Diseases and Stroke, National Institutes of Health, Bethesda Maryland USA; Bowman, F. DuBois [Department of Biostatistics, Columbia University, New York New York USA; Chen-Plotkin, Alice [Department of Neurology, University of Pennsylvania, Philadelphia Pennsylvania USA; Dawson, Ted M. [Department of Neurology, Johns Hopkins University School of Medicine, Baltimore Maryland USA; Neuroregeneration and Stem Cell Programs, Institute for Cell Engineering, Solomon H. Snyder Department of Neuroscience, Pharmacology and Molecular Sciences, Johns Hopkins University School of Medicine, Baltimore Maryland USA; Dewey, Richard B. [Department of Neurology and Neurotherapeutics, University of Texas Southwestern Medical Center, Dallas USA; German, Dwight C. [Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas USA; Huang, Xuemei [Department of Neurology, Penn State Hershey Medical Center, Hershey Pennsylvania USA; Landin, Barry [Center for Information Technology, National Institutes of Health, Bethesda Maryland USA; McAuliffe, Matthew [Center for Information Technology, National Institutes of Health, Bethesda Maryland USA; Petyuk, Vladislav A. [Biological Sciences Division, Pacific Northwest National Laboratory, Richland Washington USA; Scherzer, Clemens R. [Department of Neurology, Brigham & Women' s Hospital, Harvard Medical School, Cambridge Massachusetts USA; Hillaire-Clarke, Coryse St. [National Institute of Neurological Diseases and Stroke, National Institutes of Health, Bethesda Maryland USA; Sieber, Beth-Anne [National Institute of Neurological Diseases and Stroke, National Institutes of Health, Bethesda Maryland USA; Sutherland, Margaret [National Institute of Neurological Diseases and Stroke, National Institutes of Health, Bethesda Maryland USA; Tarn, Chi [Coriell Institute for Medical Research, Camden New Jersey USA; West, Andrew [Department of Neurology, University of Alabama at Birmingham, Birmingham USA; Vaillancourt, David [Department of Applied Physiology and Kinesiology, University of Florida, Gainesville Florida USA; Zhang, Jing [Department of Pathology, University of Washington, Seattle Washington USA; Gwinn, Katrina [National Institute of Neurological Diseases and Stroke, National Institutes of Health, Bethesda Maryland USA


    Background: Neuroprotection for Parkinson Disease (PD) remains elusive. Biomarkers hold the promise of removing roadblocks to therapy development. The National Institute of Neurological Disorders and Stroke (NINDS) has therefore established the Parkinson’s Disease Biomarkers Program (PDBP) to promote discovery of biomarkers for use in phase II-III clinical trials in PD. Methods: The PDBP facilitates biomarker development to improve neuroprotective clinical trial design, essential for advancing therapeutics for PD. To date, eleven consortium projects in the PDBP are focused on the development of clinical and laboratory-based PD biomarkers for diagnosis, progression tracking, and/or the prediction of prognosis. Seven of these projects also provide detailed longitudinal data and biospecimens from PD patients and controls, as a resource for all PD researchers. Standardized operating procedures and pooled reference samples have been created in order to allow cross-project comparisons and assessment of batch effects. A web-based Data Management Resource facilitates rapid sharing of data and biosamples across the entire PD research community for additional biomarker projects. Results: Here we describe the PDBP, highlight standard operating procedures for the collection of biospecimens and data, and provide an interim report with quality control analysis on the first 1082 participants and 1033 samples with quality control analysis collected as of October 2014. Conclusions: By making samples and data available to academics and industry, encouraging the adoption of existing standards, and providing a resource which complements existing programs, the PDBP will accelerate the pace of PD biomarker research, with the goal of improving diagnostic methods and treatment.

  15. The Greatest Mathematical Discovery?

    Energy Technology Data Exchange (ETDEWEB)

    Bailey, David H.; Borwein, Jonathan M.


    What mathematical discovery more than 1500 years ago: (1) Is one of the greatest, if not the greatest, single discovery in the field of mathematics? (2) Involved three subtle ideas that eluded the greatest minds of antiquity, even geniuses such as Archimedes? (3) Was fiercely resisted in Europe for hundreds of years after its discovery? (4) Even today, in historical treatments of mathematics, is often dismissed with scant mention, or else is ascribed to the wrong source? Answer: Our modern system of positional decimal notation with zero, together with the basic arithmetic computational schemes, which were discovered in India about 500 CE.

  16. Platform switching and bone platform switching. (United States)

    Carinci, Francesco; Brunelli, Giorgio; Danza, Matteo


    Bone platform switching involves an inward bone ring in the coronal part of the implant that is in continuity with the alveolar bone crest. Bone platform switching is obtained by using a dental fixture with a reverse conical neck. A retrospective study was performed to evaluate the effectiveness of conventional vs reverse conical neck implants. In the period between May 2004 and November 2007, 86 patients (55 females and 31 males; median age, 53 years) were operated and 234 implants were inserted: 40 and 194 were conventional vs reverse conical neck implants, respectively. Kaplan-Meier algorithm and Cox regression were used to detect those variables associated with the clinical outcome. No differences in survival and success rates were detected between conventional vs reverse conical neck implants alone or in combination with any of the studied variables. Although bone platform switching leads to several advantages, no statistical difference in alveolar crest resorption is detected in comparison with reverse conical neck implants. We suppose that the proximity of the implant abutment junction to the alveolar crestal bone gives no protection against the microflora contained in the micrograph. Additional studies on larger series and a combination of platform switching and bone platform switching could lead to improved clinical outcomes.

  17. Early diagnosis of complex diseases by molecular biomarkers, network biomarkers, and dynamical network biomarkers. (United States)

    Liu, Rui; Wang, Xiangdong; Aihara, Kazuyuki; Chen, Luonan


    Many studies have been carried out for early diagnosis of complex diseases by finding accurate and robust biomarkers specific to respective diseases. In particular, recent rapid advance of high-throughput technologies provides unprecedented rich information to characterize various disease genotypes and phenotypes in a global and also dynamical manner, which significantly accelerates the study of biomarkers from both theoretical and clinical perspectives. Traditionally, molecular biomarkers that distinguish disease samples from normal samples are widely adopted in clinical practices due to their ease of data measurement. However, many of them suffer from low coverage and high false-positive rates or high false-negative rates, which seriously limit their further clinical applications. To overcome those difficulties, network biomarkers (or module biomarkers) attract much attention and also achieve better performance because a network (or subnetwork) is considered to be a more robust form to characterize diseases than individual molecules. But, both molecular biomarkers and network biomarkers mainly distinguish disease samples from normal samples, and they generally cannot ensure to identify predisease samples due to their static nature, thereby lacking ability to early diagnosis. Based on nonlinear dynamical theory and complex network theory, a new concept of dynamical network biomarkers (DNBs, or a dynamical network of biomarkers) has been developed, which is different from traditional static approaches, and the DNB is able to distinguish a predisease state from normal and disease states by even a small number of samples, and therefore has great potential to achieve "real" early diagnosis of complex diseases. In this paper, we comprehensively review the recent advances and developments on molecular biomarkers, network biomarkers, and DNBs in particular, focusing on the biomarkers for early diagnosis of complex diseases considering a small number of samples and high

  18. Neuroproteomics and Systems Biology Approach to Identify Temporal Biomarker Changes Post Experimental Traumatic Brain Injury in Rats

    Directory of Open Access Journals (Sweden)

    Firas H Kobeissy


    Full Text Available Traumatic brain injury (TBI represents a critical health problem of which diagnosis, management and treatment remain challenging. TBI is a contributing factor in approximately 1/3 of all injury-related deaths in the United States. The Centers for Disease Control and Prevention (CDC estimate that 1.7 million TBI people suffer a TBI in the United States annually. Efforts continue to focus on elucidating the complex molecular mechanisms underlying TBI pathophysiology and defining sensitive and specific biomarkers that can aid in improving patient management and care. Recently, the area of neuroproteomics-systems biology is proving to be a prominent tool in biomarker discovery for central nervous system (CNS injury and other neurological diseases. In this work, we employed the controlled cortical impact (CCI model of experimental TBI in rat model to assess the temporal-global proteome changes after acute (1 day and for the first time, subacute (7 days, post-injury time frame using the established CAX-PAGE LC-MS/MS platform for protein separation combined with discrete systems biology analyses to identify temporal biomarker changes related to this rat TBI model. Rather than focusing on any one individual molecular entities, we used in silico systems biology approach to understand the global dynamics that govern proteins that are differentially altered post-injury. In addition, gene ontology analysis of the proteomic data was conducted in order to categorize the proteins by molecular function, biological process, and cellular localization. Results show alterations in several proteins related to inflammatory responses and oxidative stress in both acute (1 day and subacute (7 days periods post TBI. Moreover, results suggest a differential upregulation of neuroprotective proteins at 7-days post-CCI involved in cellular functions such as neurite growth, regeneration, and axonal guidance. Our study is amongst the first to assess temporal neuroproteome

  19. Pathways to new drug discovery in neuropsychiatry

    Directory of Open Access Journals (Sweden)

    Berk Michael


    Full Text Available Abstract There is currently a crisis in drug discovery for neuropsychiatric disorders, with a profound, yet unexpected drought in new drug development across the spectrum. In this commentary, the sources of this dilemma and potential avenues to redress the issue are explored. These include a critical review of diagnostic issues and of selection of participants for clinical trials, and the mechanisms for identifying new drugs and new drug targets. Historically, the vast majority of agents have been discovered serendipitously or have been modifications of existing agents. Serendipitous discoveries, based on astute clinical observation or data mining, remain a valid option, as is illustrated by the suggestion in the paper by Wahlqvist and colleagues that treatment with sulfonylurea and metformin reduces the risk of affective disorder. However, the identification of agents targeting disorder-related biomarkers is currently proving particularly fruitful. There is considerable hope for genetics as a purist, pathophysiologically valid pathway to drug discovery; however, it is unclear whether the science is ready to meet this promise. Fruitful paradigms will require a break from the orthodoxy, and creativity and risk may well be the fingerprints of success. See related article

  20. Pathways to new drug discovery in neuropsychiatry. (United States)

    Berk, Michael


    There is currently a crisis in drug discovery for neuropsychiatric disorders, with a profound, yet unexpected drought in new drug development across the spectrum. In this commentary, the sources of this dilemma and potential avenues to redress the issue are explored. These include a critical review of diagnostic issues and of selection of participants for clinical trials, and the mechanisms for identifying new drugs and new drug targets. Historically, the vast majority of agents have been discovered serendipitously or have been modifications of existing agents. Serendipitous discoveries, based on astute clinical observation or data mining, remain a valid option, as is illustrated by the suggestion in the paper by Wahlqvist and colleagues that treatment with sulfonylurea and metformin reduces the risk of affective disorder. However, the identification of agents targeting disorder-related biomarkers is currently proving particularly fruitful. There is considerable hope for genetics as a purist, pathophysiologically valid pathway to drug discovery; however, it is unclear whether the science is ready to meet this promise. Fruitful paradigms will require a break from the orthodoxy, and creativity and risk may well be the fingerprints of success.See related article

  1. DFH-3 Satellite Platform

    Institute of Scientific and Technical Information of China (English)



    The DFH-3 satellite platform is designed and developed by China Academy of Space Technology (CAST). It is a medium capability communications satellite platform. The platform adopts threeaxis attitude stabilization control system, having solar array output power of 1.7kW by the end of its design lifetime of 8 years. Its mass is 2100kg with payload capacity of 220kg.

  2. Product Platform Replacements

    DEFF Research Database (Denmark)

    Sköld, Martin; Karlsson, Christer


    Purpose – It is argued in this article that too little is known about product platforms and how to deal with them from a manager's point of view. Specifically, little information exists regarding when old established platforms are replaced by new generations in R&D and production environments...... originality and value is achieved by focusing on product platform replacements believed to represent a growing management challenge....

  3. Biomarker Identification Using Text Mining

    Directory of Open Access Journals (Sweden)

    Hui Li


    Full Text Available Identifying molecular biomarkers has become one of the important tasks for scientists to assess the different phenotypic states of cells or organisms correlated to the genotypes of diseases from large-scale biological data. In this paper, we proposed a text-mining-based method to discover biomarkers from PubMed. First, we construct a database based on a dictionary, and then we used a finite state machine to identify the biomarkers. Our method of text mining provides a highly reliable approach to discover the biomarkers in the PubMed database.

  4. Biomarkers in Prostate Cancer Epidemiology

    Directory of Open Access Journals (Sweden)

    Mudit Verma


    Full Text Available Understanding the etiology of a disease such as prostate cancer may help in identifying populations at high risk, timely intervention of the disease, and proper treatment. Biomarkers, along with exposure history and clinical data, are useful tools to achieve these goals. Individual risk and population incidence of prostate cancer result from the intervention of genetic susceptibility and exposure. Biochemical, epigenetic, genetic, and imaging biomarkers are used to identify people at high risk for developing prostate cancer. In cancer epidemiology, epigenetic biomarkers offer advantages over other types of biomarkers because they are expressed against a person’s genetic background and environmental exposure, and because abnormal events occur early in cancer development, which includes several epigenetic alterations in cancer cells. This article describes different biomarkers that have potential use in studying the epidemiology of prostate cancer. We also discuss the characteristics of an ideal biomarker for prostate cancer, and technologies utilized for biomarker assays. Among epigenetic biomarkers, most reports indicate GSTP1 hypermethylation as the diagnostic marker for prostate cancer; however, NKX2-5, CLSTN1, SPOCK2, SLC16A12, DPYS, and NSE1 also have been reported to be regulated by methylation mechanisms in prostate cancer. Current challenges in utilization of biomarkers in prostate cancer diagnosis and epidemiologic studies and potential solutions also are discussed.

  5. The art of discovery

    Directory of Open Access Journals (Sweden)

    Susie J. Lee


    Full Text Available "The Art of Discovery" discusses an ambitious educational program taught by the artist which incorporated locative media, contemporary art, site specificity, and creative work as a proposal for the integration of art, technology and science.

  6. The Learning Discovery (United States)

    Prout, Joan


    The learning discovery of youngsters is a do-it-yourself teaching method for clerical, administrative, and accountant trainees at the Bankside House headquarters of the Central Electricity Generating Board's South Eastern Region, London. (Author)

  7. Leadership and Discovery

    CERN Document Server

    Goethals, George R


    This book, a collection of essays from scholars across disciplines, explores leadership of discovery, probing the guided and collaborative exploration and interpretation of the experience of our inner thoughts and feelings, and of our external worlds

  8. Fateful discovery almost forgotten

    CERN Multimedia


    "The discovery of the fission of uranium exactly half a century ago is at risk of passing unremarked because of the general ambivalence towards the consequences of this development. Can that be wise?" (4 pages)

  9. Omnidirectional holonomic platforms

    Energy Technology Data Exchange (ETDEWEB)

    Pin, F.G.; Killough, S.M.


    This paper presents the concepts for a new family of wheeled platforms which feature full omnidirectionality with simultaneous and independently controlled rotational and translational motion capabilities. The authors first present the orthogonal-wheels concept and the two major wheel assemblies on which these platforms are based. They then describe how a combination of these assemblies with appropriate control can be used to generate an omnidirectional capability for mobile robot platforms. The design and control of two prototype platforms are then presented and their respective characteristics with respect to rotational and translational motion control are discussed.

  10. The Creative Platform

    DEFF Research Database (Denmark)

    Byrge, Christian; Hansen, Søren

    This book is about introducing more creativity into general educational courses and cross-disciplinary activities. It is directed toward teachers at all levels in the educational system, but the Creative Platform is a general model, and thus the creative process will fundamentally be the same...... whether you consider thirdgrade teaching, human-resource development, or radical new thinking in product development in a company. The Creative Platform was developed at Aalborg University through a series of research-and-development activities in collaboration with educational institutions and private...... you can use in your work with the Creative Platform. This book is intended as an introduction on how to use the Creative Platform....

  11. Discovery Driven Growth

    DEFF Research Database (Denmark)

    Bukh, Per Nikolaj


    Anmeldelse af Discovery Driven Growh : A breakthrough process to reduce risk and seize opportunity, af Rita G. McGrath & Ian C. MacMillan, Boston: Harvard Business Press. Udgivelsesdato: 14 august......Anmeldelse af Discovery Driven Growh : A breakthrough process to reduce risk and seize opportunity, af Rita G. McGrath & Ian C. MacMillan, Boston: Harvard Business Press. Udgivelsesdato: 14 august...

  12. Chemoinformatics and Drug Discovery

    Directory of Open Access Journals (Sweden)

    Arnold Hagler


    Full Text Available This article reviews current achievements in the field of chemoinformatics and their impact on modern drug discovery processes. The main data mining approaches used in cheminformatics, such as descriptor computations, structural similarity matrices, and classification algorithms, are outlined. The applications of cheminformatics in drug discovery, such as compound selection, virtual library generation, virtual high throughput screening, HTS data mining, and in silico ADMET are discussed. At the conclusion, future directions of chemoinformatics are suggested.

  13. Can biomarkers help us hit targets in difficult-to-treat asthma? (United States)

    Fricker, Michael; Heaney, Liam G; Upham, John W


    Biomarkers may be a key foundation for the precision medicine of the future. In this article, we review current knowledge regarding biomarkers in difficult-to-treat asthma and their ability to guide the use of both conventional asthma therapies and novel (targeted) therapies. Biomarkers (as measured by tests including prednisolone and cortisol assays and the fractional exhaled nitric oxide (NO) suppression test) show promise in the assessment and management of non-adherence to inhaled and oral corticosteroids. Multiple markers of type 2 inflammation have been developed, including eosinophils in sputum and blood, exhaled NO, serum IgE and periostin. Although these show potential in guiding the selection of novel interventions for refractory type 2 inflammation in asthma, and in determining if the desired response is being achieved, it is becoming clear that different biomarkers reflect distinct components of the complex type 2 inflammatory pathways. Less progress has been made in identifying biomarkers for use in difficult-to-treat asthma that is not associated with type 2 inflammation. The future is likely to see further biomarker discovery, direct measurements of individual cytokines rather than surrogates of their activity and the increasing use of biomarkers in combination. If the promise of biomarkers is to be fulfilled, they will need to provide useful information that aids clinical decision-making, rather than being 'just another test' for clinicians to order.

  14. Chiral Biomarkers in Meteorites (United States)

    Hoover, Richard B.


    The chirality of organic molecules with the asymmetric location of group radicals was discovered in 1848 by Louis Pasteur during his investigations of the rotation of the plane of polarization of light by crystals of sodium ammonium paratartrate. It is well established that the amino acids in proteins are exclusively Levorotary (L-aminos) and the sugars in DNA and RNA are Dextrorotary (D-sugars). This phenomenon of homochirality of biological polymers is a fundamental property of all life known on Earth. Furthermore, abiotic production mechanisms typically yield recemic mixtures (i.e. equal amounts of the two enantiomers). When amino acids were first detected in carbonaceous meteorites, it was concluded that they were racemates. This conclusion was taken as evidence that they were extraterrestrial and produced by abiologically. Subsequent studies by numerous researchers have revealed that many of the amino acids in carbonaceous meteorites exhibit a significant L-excess. The observed chirality is much greater than that produced by any currently known abiotic processes (e.g. Linearly polarized light from neutron stars; Circularly polarized ultraviolet light from faint stars; optically active quartz powders; inclusion polymerization in clay minerals; Vester-Ulbricht hypothesis of parity violations, etc.). This paper compares the measured chirality detected in the amino acids of carbonaceous meteorites with the effect of these diverse abiotic processes. IT is concluded that the levels observed are inconsistent with post-arrival biological contamination or with any of the currently known abiotic production mechanisms. However, they are consistent with ancient biological processes on the meteorite parent body. This paper will consider these chiral biomarkers in view of the detection of possible microfossils found in the Orgueil and Murchison carbonaceous meteorites. Energy dispersive x-ray spectroscopy (EDS) data obtained on these morphological biomarkers will be

  15. Towards Improved Biomarker Research

    DEFF Research Database (Denmark)

    Kjeldahl, Karin

    This thesis takes a look at the data analytical challenges associated with the search for biomarkers in large-scale biological data such as transcriptomics, proteomics and metabolomics data. These studies aim to identify genes, proteins or metabolites which can be associated with e.g. a diet, dis...... is used both for regression and classification purposes. This method has proven its strong worth in the multivariate data analysis throughout an enormous range of applications; a very classic data type is near infrared (NIR) data, but many similar data types have also be very successful...

  16. Numeric computation and statistical data analysis on the Java platform

    CERN Document Server

    Chekanov, Sergei V


    Numerical computation, knowledge discovery and statistical data analysis integrated with powerful 2D and 3D graphics for visualization are the key topics of this book. The Python code examples powered by the Java platform can easily be transformed to other programming languages, such as Java, Groovy, Ruby and BeanShell. This book equips the reader with a computational platform which, unlike other statistical programs, is not limited by a single programming language. The author focuses on practical programming aspects and covers a broad range of topics, from basic introduction to the Python language on the Java platform (Jython), to descriptive statistics, symbolic calculations, neural networks, non-linear regression analysis and many other data-mining topics. He discusses how to find regularities in real-world data, how to classify data, and how to process data for knowledge discoveries. The code snippets are so short that they easily fit into single pages. Numeric Computation and Statistical Data Analysis ...

  17. MicroRNA signatures as clinical biomarkers in lung cancer

    Directory of Open Access Journals (Sweden)

    Markou A


    Full Text Available Athina Markou, Martha Zavridou, Evi S Lianidou Analysis of Circulating Tumor Cells, Lab of Analytical Chemistry, Department of Chemistry, University of Athens, Athens, Greece Abstract: Even if early lung cancer detection has been recently significantly improved, the invasive nature of current diagnostic procedures, and a relatively high percentage of false positives, is limiting the application of modern detection tools. The discovery and clinical evaluation of novel specific and robust non-invasive biomarkers for diagnosis of lung cancer at an early stage, as well as for better prognosis and prediction of therapy response, is very challenging. MicroRNAs (miRNAs can play an important role in the diagnosis and management of lung cancer patients, as important and reliable biomarkers for cancer detection and prognostic prediction, and even as promising as novel targets for cancer therapy. miRNAs are important in cancer pathogenesis, and deregulation of their expression levels has been detected not only in lung cancer but in many other human tumor types. Numerous studies strongly support the potential of miRNAs as biomarkers in non-small-cell lung cancer, and there is increasing evidence that altered miRNA expression is associated with tumor progression and survival. It is worth mentioning also that detection of miRNAs circulating in plasma or serum has enormous potential, because miRNAs serve as non-invasive biomarkers not only for the diagnosis and prognosis of the disease, but also as novel response and sensitivity predictors for cancer treatment. In this review, we summarize the current findings on the critical role of miRNAs in lung cancer tumorigenesis and highlight their potential as circulating biomarkers in lung cancer. Our review is based on papers that have been published after 2011, and includes the key words “miRNAs” and “lung cancer”. Keywords: non-small-cell lung carcinoma, miRNAs, tumor biomarkers, circulating miRNAs, liquid

  18. Product Platform Performance

    DEFF Research Database (Denmark)

    Munk, Lone

    of components (often around 50%) and • reduced production cost and investments (often around 25%). This verifies a significant, general improvement potential, a verification which has lacked in the literature. These findings underline the potential in platform-based product development as a way of creating......The aim of this research is to improve understanding of platform-based product development by studying platform performance in relation to internal effects in companies. Platform-based product development makes it possible to deliver product variety and at the same time reduce the needed resources......, and the subject has gained increased attention in industry and academia the past decade. Literature on platform-based product development is often based on single case studies and it is sparsely verified if expected effects are achieved. This makes it difficult to put forward realistic expectations for companies...

  19. Which biomarkers reveal neonatal sepsis?

    Directory of Open Access Journals (Sweden)

    Kun Wang

    Full Text Available We address the identification of optimal biomarkers for the rapid diagnosis of neonatal sepsis. We employ both canonical correlation analysis (CCA and sparse support vector machine (SSVM classifiers to select the best subset of biomarkers from a large hematological data set collected from infants with suspected sepsis from Yale-New Haven Hospital's Neonatal Intensive Care Unit (NICU. CCA is used to select sets of biomarkers of increasing size that are most highly correlated with infection. The effectiveness of these biomarkers is then validated by constructing a sparse support vector machine diagnostic classifier. We find that the following set of five biomarkers capture the essential diagnostic information (in order of importance: Bands, Platelets, neutrophil CD64, White Blood Cells, and Segs. Further, the diagnostic performance of the optimal set of biomarkers is significantly higher than that of isolated individual biomarkers. These results suggest an enhanced sepsis scoring system for neonatal sepsis that includes these five biomarkers. We demonstrate the robustness of our analysis by comparing CCA with the Forward Selection method and SSVM with LASSO Logistic Regression.

  20. Current advances in biomarkers for targeted therapy in triple-negative breast cancer

    Directory of Open Access Journals (Sweden)

    Fleisher B


    Full Text Available Brett Fleisher,1 Charlotte Clarke,2 Sihem Ait-Oudhia1 1Department of Pharmaceutics, Center for Pharmacometrics and Systems Pharmacology, College of Pharmacy, University of Florida, Orlando, FL, 2Department of Translational Research, UT MD Anderson Cancer Center, Houston, TX, USA Abstract: Triple-negative breast cancer (TNBC is a complex heterogeneous disease characterized by the absence of three hallmark receptors: human epidermal growth factor receptor 2, estrogen receptor, and progesterone receptor. Compared to other breast cancer subtypes, TNBC is more aggressive, has a higher prevalence in African-Americans, and more frequently affects younger patients. Currently, TNBC lacks clinically accepted targets for tailored therapy, warranting the need for candidate biomarkers. BiomarkerBase, an online platform used to find biomarkers reported in clinical trials, was utilized to screen all potential biomarkers for TNBC and select only the ones registered in completed TNBC trials through The selected candidate biomarkers were classified as surrogate, prognostic, predictive, or pharmacodynamic (PD and organized by location in the blood, on the cell surface, in the cytoplasm, or in the nucleus. Blood biomarkers include vascular endothelial growth factor/vascular endothelial growth factor receptor and interleukin-8 (IL-­8; cell surface biomarkers include EGFR, insulin-like growth factor binding protein, c-Kit, c-Met, and PD-L1; cytoplasm biomarkers include PIK3CA, pAKT/S6/p4E-BP1, PTEN, ALDH1, and the PIK3CA/AKT/mTOR-related metabolites; and nucleus biomarkers include BRCA1, the glucocorticoid receptor, TP53, and Ki67. Candidate biomarkers were further organized into a “cellular protein network” that demonstrates potential connectivity. This review provides an inventory and reference point for promising biomarkers for breakthrough targeted therapies in TNBC. Keywords: anti-cancer directed pharmacotherapy, difficult

  1. Epigenetic biomarkers in liver cancer. (United States)

    Banaudha, Krishna K; Verma, Mukesh


    Liver cancer (hepatocellular carcinoma or HCC) is a major cancer worldwide. Research in this field is needed to identify biomarkers that can be used for early detection of the disease as well as new approaches to its treatment. Epigenetic biomarkers provide an opportunity to understand liver cancer etiology and evaluate novel epigenetic inhibitors for treatment. Traditionally, liver cirrhosis, proteomic biomarkers, and the presence of hepatitis viruses have been used for the detection and diagnosis of liver cancer. Promising results from microRNA (miRNA) profiling and hypermethylation of selected genes have raised hopes of identifying new biomarkers. Some of these epigenetic biomarkers may be useful in risk assessment and for screening populations to identify who is likely to develop cancer. Challenges and opportunities in the field are discussed in this chapter.

  2. Definitions and validation criteria for biomarkers and surrogate endpoints: development and testing of a quantitative hierarchical levels of evidence schema

    DEFF Research Database (Denmark)

    Lassere, Marissa N; Johnson, Kent R; Boers, Maarten


    of the National Institutes of Health definitions of biomarker, surrogate endpoint, and clinical endpoint was useful. CONCLUSION: Further development and application of this schema provides incentives and guidance for effective biomarker and surrogate endpoint research, and more efficient drug discovery...... endpoints, and leading indicators, a quantitative surrogate validation schema was developed and subsequently evaluated at a stakeholder workshop. RESULTS: The search identified several classification schema and definitions. Components of these were incorporated into a new quantitative surrogate validation...

  3. Building a Community-Focused Data Platform

    Energy Technology Data Exchange (ETDEWEB)

    Turk, Matthew J. [Univ. of Illinois, Urbana-Champaign, IL (United States). National Center for Supercomputing Applications (NCSA); Warren, Michael S. [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Skillman, Samuel W. [Stanford Univ., CA (United States)


    The National Data Service (NDS) presents a broad-reaching vision of integrating discovery, publishing, and sharing of data. Metcalfe's Law states that the value of a network increases with the number of connections in the network, not the number of nodes. The NDS must develop and steward connections not only between data, as is in its vision statement, but between individuals as well. We propose that this be accomplished by explicitly developing it as a platform on which data exploration can be constructed by individual researchers.

  4. Translational paradigms in pharmacology and drug discovery. (United States)

    Mullane, Kevin; Winquist, Raymond J; Williams, Michael


    The translational sciences represent the core element in enabling and utilizing the output from the biomedical sciences and to improving drug discovery metrics by reducing the attrition rate as compounds move from preclinical research to clinical proof of concept. Key to understanding the basis of disease causality and to developing therapeutics is an ability to accurately diagnose the disease and to identify and develop safe and effective therapeutics for its treatment. The former requires validated biomarkers and the latter, qualified targets. Progress has been hampered by semantic issues, specifically those that define the end product, and by scientific issues that include data reliability, an overt reductionistic cultural focus and a lack of hierarchically integrated data gathering and systematic analysis. A necessary framework for these activities is represented by the discipline of pharmacology, efforts and training in which require recognition and revitalization.

  5. [Iron deficiency in elderly patients: use of biomarkers]. (United States)

    Le Petitcorps, Hélène; Monti, Alexandra; Pautas, Éric


    Iron deficiency, due to blood loss or malabsorption, is commonly observed in geriatric practice. In elderly people, association of inflammatory diseases to iron loss makes diagnosis of absolute iron deficiency sometimes difficult. In case of inflammation, the interpretation of usual biomarkers of iron deficiency (serum ferritin, transferrin saturation, serum iron) may be difficult. The recent discovery of the role of hepcidine in the iron homeostasis, in physiological and pathological situation, contributes to better understanding of the iron regulation. The aim of this short paper is to underline some specificities of elderly iron physiology, to explain hepcidine's role in physiological and pathological situations and to propose a diagnostic approach for a better interpretation of usual biomarkers, in order to differentiate absolute iron deficiency and functional iron deficiency.

  6. Integrated Detection of Pathogens and Host Biomarkers for Wounds

    Energy Technology Data Exchange (ETDEWEB)

    Jaing, C


    The increasing incidence and complications arising from combat wounds has necessitated a reassessment of methods for effective treatment. Infection, excessive inflammation, and incidence of drug-resistant organisms all contribute toward negative outcomes for afflicted individuals. The organisms and host processes involved in wound progression, however, are incompletely understood. We therefore set out, using our unique technical resources, to construct a profile of combat wounds which did or did not successfully resolve. We employed the Lawrence Livermore Microbial Detection Array and identified a number of nosocomial pathogens present in wound samples. Some of these identities corresponded with bacterial isolates previously cultured, while others were not obtained via standard microbiology. Further, we optimized proteomics protocols for the identification of host biomarkers indicative of various stages in wound progression. In combination with our pathogen data, our biomarker discovery efforts will provide a profile corresponding to wound complications, and will assist significantly in treatment of these complex cases.

  7. Biomarkers for lymphoma (United States)

    Zangar, Richard C.; Varnum, Susan M.


    A biomarker, method, test kit, and diagnostic system for detecting the presence of lymphoma in a person are disclosed. The lymphoma may be Hodgkin's lymphoma or non-Hodgkin's lymphoma. The person may be a high-risk subject. In one embodiment, a plasma sample from a person is obtained. The level of at least one protein listed in Table S3 in the plasma sample is measured. The level of at least one protein in the plasma sample is compared with the level in a normal or healthy subject. The lymphoma is diagnosed based upon the level of the at least one protein in the plasma sample in comparison to the normal or healthy level.

  8. Molecular biomarkers of neurodegeneration. (United States)

    Höglund, Kina; Salter, Hugh


    Neuronal dysfunction and degeneration are central events of a number of major diseases with significant unmet need. Neuronal dysfunction may not necessarily be the result of cell death, but may also be due to synaptic damage leading to impaired neuronal cell signaling or long-term potentiation. Once degeneration occurs, it is unclear whether axonal or synaptic loss comes first or whether this precedes neuronal cell death. In this review we summarize the pathophysiology of four major neurodegenerative diseases; Alzheimer's disease, Parkinson's disease, multiple sclerosis and amyotrophic lateral sclerosis (Lou Gehrig's disease) For each of these diseases, we describe how biochemical biomarkers are currently understood in relation to the pathophysiology and in terms of neuronal biology, and we discuss the clinical and diagnostic utility of these potential tools, which are at present limited. We discuss how markers may be used to drive drug development and clinical practice.

  9. Inflammatory biomarkers for AMD. (United States)

    Stanton, Chloe M; Wright, Alan F


    Age-related macular degeneration (AMD) is the leading cause of blindness worldwide, affecting an estimated 50 million individuals aged over 65 years.Environmental and genetic risk-factors implicate chronic inflammation in the etiology of AMD, contributing to the formation of drusen, retinal pigment epithelial cell dysfunction and photoreceptor cell death. Consistent with a role for chronic inflammation in AMD pathogenesis, several inflammatory mediators, including complement components, chemokines and cytokines, are elevated at both the local and systemic levels in AMD patients. These mediators have diverse roles in the alternative complement pathway, including recruitment of inflammatory cells, activation of the inflammasome, promotion of neovascularisation and in the resolution of inflammation. The utility of inflammatory biomarkers in assessing individual risk and progression of the disease is controversial. However, understanding the role of these inflammatory mediators in AMD onset, progression and response to treatment may increase our knowledge of disease pathogenesis and provide novel therapeutic options in the future.

  10. The Common HOL Platform


    Adams, Mark


    The Common HOL project aims to facilitate porting source code and proofs between members of the HOL family of theorem provers. At the heart of the project is the Common HOL Platform, which defines a standard HOL theory and API that aims to be compatible with all HOL systems. So far, HOL Light and hol90 have been adapted for conformance, and HOL Zero was originally developed to conform. In this paper we provide motivation for a platform, give an overview of the Common HOL Platform's theory and...

  11. Ladder attachment platform (United States)

    Swygert,; Richard, W [Springfield, SC


    A ladder attachment platform is provided that includes a base for attachment to a ladder that has first and second side rails and a plurality of rungs that extend between in a lateral direction. Also included is a user platform for having a user stand thereon that is carried by the base. The user platform may be positioned with respect to the ladder so that it is not located between a first plane that extends through the first side rail and is perpendicular to the lateral direction and a second plane that extends through the second side rail and is perpendicular to the lateral direction.

  12. Year 2 Report: Protein Function Prediction Platform

    Energy Technology Data Exchange (ETDEWEB)

    Zhou, C E


    Upon completion of our second year of development in a 3-year development cycle, we have completed a prototype protein structure-function annotation and function prediction system: Protein Function Prediction (PFP) platform (v.0.5). We have met our milestones for Years 1 and 2 and are positioned to continue development in completion of our original statement of work, or a reasonable modification thereof, in service to DTRA Programs involved in diagnostics and medical countermeasures research and development. The PFP platform is a multi-scale computational modeling system for protein structure-function annotation and function prediction. As of this writing, PFP is the only existing fully automated, high-throughput, multi-scale modeling, whole-proteome annotation platform, and represents a significant advance in the field of genome annotation (Fig. 1). PFP modules perform protein functional annotations at the sequence, systems biology, protein structure, and atomistic levels of biological complexity (Fig. 2). Because these approaches provide orthogonal means of characterizing proteins and suggesting protein function, PFP processing maximizes the protein functional information that can currently be gained by computational means. Comprehensive annotation of pathogen genomes is essential for bio-defense applications in pathogen characterization, threat assessment, and medical countermeasure design and development in that it can short-cut the time and effort required to select and characterize protein biomarkers.

  13. Probe into How to Use the Literature Retrieval & Delivery Platforms to Provide Information Service for Arab Research---Base on the Superstar Duxiu, Bailian and Chinese Discovery%利用文献检索平台为阿拉伯研究提供信息服务的对策探讨--以超星读秀、百链云和中文发现为例

    Institute of Scientific and Technical Information of China (English)

    张红燕; 来泽荣


    Since the implementation of the opening strategy of“One Belt and One Road”, the cooperation between Ningxia and Arab countries in the fields of economy and trade, culture, education, and science and technology, etc. is deeper and wider. Under such a background, Ningxia University established Chinese Research Institute of Arab. Based on the Superstar Duxiu, Bailian and Chinese Discovery, this paper probes into how to use the literature retrieval&delivery platforms to provide efficient, multi-channel and comprehensive literature information service for Arab research.%自我国“一带一路”对外开放战略实施以来,宁夏与阿拉伯国家在经贸、文化、教育和科技等领域的合作更加深入和广泛。在此背景下,宁夏大学成立了中国阿拉伯研究院。以超星读秀、百链云和中文发现为例,探讨了如何利用这些文献检索和传递服务平台,为阿拉伯研究提供高效率、多途径和全方位的文献信息服务。

  14. Platform-based production development

    DEFF Research Database (Denmark)

    Bossen, Jacob; Brunoe, Thomas Ditlev; Nielsen, Kjeld


    Platforms as a means for applying modular thinking in product development is relatively well studied, but platforms in the production system has until now not been given much attention. With the emerging concept of platform-based co-development the importance of production platforms is though...... indisputable. This paper presents state-of-the-art literature on platform research related to production platforms and investigates gaps in the literature. The paper concludes on findings by proposing future research directions....

  15. An integrated sample pretreatment platform for quantitative N-glycoproteome analysis with combination of on-line glycopeptide enrichment, deglycosylation and dimethyl labeling

    Energy Technology Data Exchange (ETDEWEB)

    Weng, Yejing; Qu, Yanyan; Jiang, Hao; Wu, Qi [National Chromatographic Research and Analysis Center, Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian 116023 (China); University of the Chinese Academy of Sciences, Beijing 100039 (China); Zhang, Lihua, E-mail: [National Chromatographic Research and Analysis Center, Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian 116023 (China); Yuan, Huiming [National Chromatographic Research and Analysis Center, Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian 116023 (China); Zhou, Yuan [National Chromatographic Research and Analysis Center, Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian 116023 (China); University of the Chinese Academy of Sciences, Beijing 100039 (China); Zhang, Xiaodan; Zhang, Yukui [National Chromatographic Research and Analysis Center, Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian 116023 (China)


    Highlights: • An integrated platform for quantitative N-glycoproteome analysis was established. • On-line enrichment, deglycosylation and labeling could be achieved within 160 min. • A N{sub 2}-assisted interface was applied to improve the compatibility of the platform. • The platform exhibited improved quantification accuracy, precision and throughput. - Abstract: Relative quantification of N-glycoproteomes shows great promise for the discovery of candidate biomarkers and therapeutic targets. The traditional protocol for quantitative analysis of glycoproteomes is usually off-line performed, and suffers from long sample preparation time, and the risk of sample loss or contamination due to manual manipulation. In this study, a novel integrated sample preparation platform for quantitative N-glycoproteome analysis was established, with combination of online N-glycopeptide capture by a HILIC column, sample buffer exchange by a N{sub 2}-assisted HILIC–RPLC interface, deglycosylation by a hydrophilic PNGase F immobilized enzymatic reactor (hIMER) and solid dimethyl labeling on a C18 precolumn. To evaluate the performance of such a platform, two equal aliquots of immunoglobulin G (IgG) digests were sequentially pretreated, followed by MALDI-TOF MS analysis. The signal intensity ratio of heavy/light (H/L) labeled deglycosylated peptides with the equal aliquots was 1.00 (RSD = 6.2%, n = 3), much better than those obtained by the offline protocol, with H/L ratio as 0.76 (RSD = 11.6%, n = 3). Additionally, the total on-line sample preparation time was greatly shortened to 160 min, much faster than that of offline approach (24 h). Furthermore, such an integrated pretreatment platform was successfully applied to analyze the two kinds of hepatocarcinoma ascites syngeneic cell lines with high (Hca-F) and low (Hca-P) lymph node metastasis rates. For H/L labeled Hca-P lysates with the equal aliquots, 99.6% of log 2 ratios (H/L) of quantified glycopeptides ranged from −1

  16. USA Hire Testing Platform (United States)

    Office of Personnel Management — The USA Hire Testing Platform delivers tests used in hiring for positions in the Federal Government. To safeguard the integrity of the hiring processes and ensure...

  17. The Common HOL Platform

    Directory of Open Access Journals (Sweden)

    Mark Adams


    Full Text Available The Common HOL project aims to facilitate porting source code and proofs between members of the HOL family of theorem provers. At the heart of the project is the Common HOL Platform, which defines a standard HOL theory and API that aims to be compatible with all HOL systems. So far, HOL Light and hol90 have been adapted for conformance, and HOL Zero was originally developed to conform. In this paper we provide motivation for a platform, give an overview of the Common HOL Platform's theory and API components, and show how to adapt legacy systems. We also report on the platform's successful application in the hand-translation of a few thousand lines of source code from HOL Light to HOL Zero.

  18. The Creative Platform

    DEFF Research Database (Denmark)

    Byrge, Christian; Hansen, Søren

    whether you consider thirdgrade teaching, human-resource development, or radical new thinking in product development in a company. The Creative Platform was developed at Aalborg University through a series of research-and-development activities in collaboration with educational institutions and private......This book is about introducing more creativity into general educational courses and cross-disciplinary activities. It is directed toward teachers at all levels in the educational system, but the Creative Platform is a general model, and thus the creative process will fundamentally be the same...... companies. It is a project in which the goal is to make a hands-on approach to a knowledge perspective on enhancing creativity. The underlying ambition of the Creative Platform is to make it easier to promote creativity. At, you can find extra materials and instructions...

  19. Development of Parkinson's disease biomarkers. (United States)

    Prakash, Kumar M; Tan, Eng-King


    Parkinson's disease (PD) is the most common neurodegenerative movement disorder, affecting over 6 million people worldwide. It is anticipated that the number of affected individuals may increase significantly in the most populous nations by 2030. During the past 20 years, much progress has been made in identifying and assessing various potential clinical, biochemical, imaging and genetic biomarkers for PD. Despite the wealth of information, development of a validated biomarker for PD is still ongoing. It is hoped that reliable and well-validated biomarkers will provide critical clues to assist in the diagnosis and management of Parkinson's disease patients in the near future.

  20. Genetic and Epigenetic Biomarkers for Recurrent Prostate Cancer After Radiotherapy (United States)


    Award Number: W81XWH-12-1-0113 TITLE: Genetic and epigenetic biomarkers for recurrent prostate cancer after radiotherapy PRINCIPAL INVESTIGATOR...Beadchip microarray, high density beadchip, for this study. This array includes 485,577 CpG sites and covers CpGs in 99% of genes and 96% of CpG ...differentially methylated CpG sites in 17 genes between recurrent and non-recurrent tumor tissues, with a false discovery rate (FDR) [12] q-value less than

  1. Ayurvedic drug discovery. (United States)

    Balachandran, Premalatha; Govindarajan, Rajgopal


    Ayurveda is a major traditional system of Indian medicine that is still being successfully used in many countries. Recapitulation and adaptation of the older science to modern drug discovery processes can bring renewed interest to the pharmaceutical world and offer unique therapeutic solutions for a wide range of human disorders. Eventhough time-tested evidences vouch immense therapeutic benefits for ayurvedic herbs and formulations, several important issues are required to be resolved for successful implementation of ayurvedic principles to present drug discovery methodologies. Additionally, clinical examination in the extent of efficacy, safety and drug interactions of newly developed ayurvedic drugs and formulations are required to be carefully evaluated. Ayurvedic experts suggest a reverse-pharmacology approach focusing on the potential targets for which ayurvedic herbs and herbal products could bring tremendous leads to ayurvedic drug discovery. Although several novel leads and drug molecules have already been discovered from ayurvedic medicinal herbs, further scientific explorations in this arena along with customization of present technologies to ayurvedic drug manufacturing principles would greatly facilitate a standardized ayurvedic drug discovery.

  2. Discovery of TUG-770

    DEFF Research Database (Denmark)

    Christiansen, Elisabeth; Hansen, Steffen V F; Urban, Christian;


    Free fatty acid receptor 1 (FFA1 or GPR40) enhances glucose-stimulated insulin secretion from pancreatic β-cells and currently attracts high interest as a new target for the treatment of type 2 diabetes. We here report the discovery of a highly potent FFA1 agonist with favorable physicochemical a...

  3. The Scholarship of Discovery. (United States)

    Dobos, Jean


    Contributes to a special issue on how the reconsideration of what scholarship is affects the way in which scholarship is assessed. Examines traditional criteria for evaluating faculty research. Identifies activities pertinent to the scholarship of discovery, and the assessment practices in the field of communication as well as in general use. (SR)

  4. Discovery Education: A Definition. (United States)

    Wilson, Harold C.


    Discovery Education is based on the writings of Henry David Thoreau, an early champion of experiential learning. After 2 months of preparation, 10th-grade students spent 4 days in the wilderness reenacting a piece of history, such as the Lewis and Clark Expedition. The interdisciplinary approach always included journal-writing. Students gained…

  5. Archaeological Discoveries in Liaoning

    Institute of Scientific and Technical Information of China (English)


    LIAONING Province, in northeastern China, has been inhabited by many ethnic groups since ancient times. It is one of the sites of China’s earliest civilization. Since the 1950s many archaeological discoveries from periods beginning with the Paleolithic of 200,000 years ago, and through all the following historic periods, have been made in the province.

  6. Discovery through Gossip

    CERN Document Server

    Haeupler, Bernhard; Peleg, David; Rajaraman, Rajmohan; Sun, Zhifeng


    We study randomized gossip-based processes in dynamic networks that are motivated by discovery processes in large-scale distributed networks like peer-to-peer or social networks. A well-studied problem in peer-to-peer networks is the resource discovery problem. There, the goal for nodes (hosts with IP addresses) is to discover the IP addresses of all other hosts. In social networks, nodes (people) discover new nodes through exchanging contacts with their neighbors (friends). In both cases the discovery of new nodes changes the underlying network - new edges are added to the network - and the process continues in the changed network. Rigorously analyzing such dynamic (stochastic) processes with a continuously self-changing topology remains a challenging problem with obvious applications. This paper studies and analyzes two natural gossip-based discovery processes. In the push process, each node repeatedly chooses two random neighbors and puts them in contact (i.e., "pushes" their mutual information to each oth...

  7. Photonic crystal enhanced fluorescence for early breast cancer biomarker detection. (United States)

    Cunningham, Brian T; Zangar, Richard C


    Photonic crystal surfaces offer a compelling platform for improving the sensitivity of surface-based fluorescent assays used in disease diagnostics. Through the complementary processes of photonic crystal enhanced excitation and enhanced extraction, a periodic dielectric-based nanostructured surface can simultaneously increase the electric field intensity experienced by surface-bound fluorophores and increase the collection efficiency of emitted fluorescent photons. Through the ability to inexpensively fabricate photonic crystal surfaces over substantial surface areas, they are amenable to single-use applications in biological sensing, such as disease biomarker detection in serum. In this review, we will describe the motivation for implementing high-sensitivity, multiplexed biomarker detection in the context of breast cancer diagnosis. We will summarize recent efforts to improve the detection limits of such assays though the use of photonic crystal surfaces. Reduction of detection limits is driven by low autofluorescent substrates for photonic crystal fabrication, and detection instruments that take advantage of their unique features.

  8. National Community Solar Platform

    Energy Technology Data Exchange (ETDEWEB)

    Rupert, Bart [Clean Energy Collective, Louisville, CO (United States)


    This project was created to provide a National Community Solar Platform (NCSP) portal known as Community Solar Hub, that is available to any entity or individual who wants to develop community solar. This has been done by providing a comprehensive portal to make CEC’s solutions, and other proven community solar solutions, externally available for everyone to access – making the process easy through proven platforms to protect subscribers, developers and utilities. The successful completion of this project provides these tools via a web platform and integration APIs, a wide spectrum of community solar projects included in the platform, multiple groups of customers (utilities, EPCs, and advocates) using the platform to develop community solar, and open access to anyone interested in community solar. CEC’s Incubator project includes web-based informational resources, integrated systems for project information and billing systems, and engagement with customers and users by community solar experts. The combined effort externalizes much of Clean Energy Collective’s industry-leading expertise, allowing third parties to develop community solar without duplicating expensive start-up efforts. The availability of this platform creates community solar projects that are cheaper to build and cheaper to participate in, furthering the goals of DOE’s SunShot Initiative. Final SF 425 Final SF 428 Final DOE F 2050.11 Final Report Narrative

  9. The Platformization of the Web: Making Web Data Platform Ready

    NARCIS (Netherlands)

    A. Helmond


    In this article, I inquire into Facebook’s development as a platform by situating it within the transformation of social network sites into social media platforms. I explore this shift with a historical perspective on, what I refer to as, platformization, or the rise of the platform as the dominant

  10. Improving tuberculosis diagnostics with biomarkers

    Directory of Open Access Journals (Sweden)

    Shu CC


    Full Text Available Chin-Chung Shu,1,2 Jann-Yuan Wang,2 Li-Na Lee,2,3 Chong-Jen Yu,2 Kwen-Tay Luh3 1Department of Traumatology, 2Department of Internal Medicine, 3Department of Laboratory Medicine, National Taiwan University Hospital, Taipei, Taiwan Abstract: Although many laboratory methods have been developed to expedite the diagnosis of active tuberculosis (TB and Mycobacterium tuberculosis (Mtb infection, delays in diagnosis remain a major problem in clinical practice. Biomarkers may contribute favorably or unfavorably to TB diagnosis in a clinical suspect TB case with inconclusive diagnostic findings. A good understanding of the effectiveness and practical limitations of these biomarkers is important to improve diagnosis. This review summarizes currently used biomarkers, mainly as validation, and focuses on latent TB infection, active pulmonary TB, and tuberculous pleural effusion. Keywords: tuberculosis, biomarker, diagnosis, latent tuberculosis infection, pleural effusion 

  11. Urinary Biomarkers of Brain Diseases

    Directory of Open Access Journals (Sweden)

    Manxia An


    Full Text Available Biomarkers are the measurable changes associated with a physiological or pathophysiological process. Unlike blood, urine is not subject to homeostatic mechanisms. Therefore, greater fluctuations could occur in urine than in blood, better reflecting the changes in human body. The roadmap of urine biomarker era was proposed. Although urine analysis has been attempted for clinical diagnosis, and urine has been monitored during the progression of many diseases, particularly urinary system diseases, whether urine can reflect brain disease status remains uncertain. As some biomarkers of brain diseases can be detected in the body fluids such as cerebrospinal fluid and blood, there is a possibility that urine also contain biomarkers of brain diseases. This review summarizes the clues of brain diseases reflected in the urine proteome and metabolome.

  12. Procalcitonine als biomarker voor infecties

    NARCIS (Netherlands)

    de Jonge, J C; de Lange, D W; Bij de Vaate, E A; van Leeuwen, H; Arends, J E


    - Inappropriate use of antibiotics in patients without bacterial infection contributes significantly to worldwide antibiotic resistance.- The goal of this review is to summarise evidence from randomised trials investigating the value of the biomarker procalcitonin (PCT) in patients with symptoms of

  13. Biomarkers of latent TB infection

    DEFF Research Database (Denmark)

    Ruhwald, Morten; Ravn, Pernille


    For the last 100 years, the tuberculin skin test (TST) has been the only diagnostic tool available for latent TB infection (LTBI) and no biomarker per se is available to diagnose the presence of LTBI. With the introduction of M. tuberculosis-specific IFN-gamma release assays (IGRAs), a new area...... of in vitro immunodiagnostic tests for LTBI based on biomarker readout has become a reality. In this review, we discuss existing evidence on the clinical usefulness of IGRAs and the indefinite number of potential new biomarkers that can be used to improve diagnosis of latent TB infection. We also present...... early data suggesting that the monocyte-derived chemokine inducible protein-10 may be useful as a novel biomarker for the immunodiagnosis of latent TB infection....

  14. Proxying UPnP service discovery and access to a non-IP Bluetooth network on a mobile phone

    NARCIS (Netherlands)

    Delphinanto, A.; Koonen, A.M.J.; Peeters, M.E.; Hartog, F.T.H. den


    The current service- and device discovery protocols are not platform- and network independent. Therefore, proxy servers will be needed to extend the range of IP-based discovery protocols to non-IP domains. We developed an architecture of a proxy that enables Universal Plug and Play (UPnP) devices an

  15. Creating A Guided- discovery Lesson

    Institute of Scientific and Technical Information of China (English)



    In a guided - discovery lesson, students sequentially uncover layers of mathematical information one step at a time and learn new mathematics. We have identified eight critical steps necessary in developing a successful guided- discovery lesson.

  16. Biomarkers in Prostate Cancer Epidemiology


    Mudit Verma; Mukesh Verma; Payal Patel


    Understanding the etiology of a disease such as prostate cancer may help in identifying populations at high risk, timely intervention of the disease, and proper treatment. Biomarkers, along with exposure history and clinical data, are useful tools to achieve these goals. Individual risk and population incidence of prostate cancer result from the intervention of genetic susceptibility and exposure. Biochemical, epigenetic, genetic, and imaging biomarkers are used to identify people at high ris...

  17. Biomarkers of satiation and satiety. (United States)

    de Graaf, Cees; Blom, Wendy A M; Smeets, Paul A M; Stafleu, Annette; Hendriks, Henk F J


    This review's objective is to give a critical summary of studies that focused on physiologic measures relating to subjectively rated appetite, actual food intake, or both. Biomarkers of satiation and satiety may be used as a tool for assessing the satiating efficiency of foods and for understanding the regulation of food intake and energy balance. We made a distinction between biomarkers of satiation or meal termination and those of meal initiation related to satiety and between markers in the brain [central nervous system (CNS)] and those related to signals from the periphery to the CNS. Various studies showed that physicochemical measures related to stomach distension and blood concentrations of cholecystokinin and glucagon-like peptide 1 are peripheral biomarkers associated with meal termination. CNS biomarkers related to meal termination identified by functional magnetic resonance imaging and positron emission tomography are indicators of neural activity related to sensory-specific satiety. These measures cannot yet serve as a tool for assessing the satiating effect of foods, because they are not yet feasible. CNS biomarkers related to satiety are not yet specific enough to serve as biomarkers, although they can distinguish between extreme hunger and fullness. Three currently available biomarkers for satiety are decreases in blood glucose in the short term (2-4 d) negative energy balance; and ghrelin concentrations, which have been implicated in both short-term and long-term energy balance. The next challenge in this research area is to identify food ingredients that have an effect on biomarkers of satiation, satiety, or both. These ingredients may help consumers to maintain their energy intake at a level consistent with a healthy body weight.

  18. Analysis of biomarker data a practical guide

    CERN Document Server

    Looney, Stephen W


    A "how to" guide for applying statistical methods to biomarker data analysis Presenting a solid foundation for the statistical methods that are used to analyze biomarker data, Analysis of Biomarker Data: A Practical Guide features preferred techniques for biomarker validation. The authors provide descriptions of select elementary statistical methods that are traditionally used to analyze biomarker data with a focus on the proper application of each method, including necessary assumptions, software recommendations, and proper interpretation of computer output. In addition, the book discusses

  19. Utilization of metabolomics to identify serum biomarkers for hepatocellular carcinoma in patients with liver cirrhosis

    Energy Technology Data Exchange (ETDEWEB)

    Ressom, Habtom W., E-mail: [Department of Oncology, Lombardi Comprehensive Cancer Center, Georgetown University Medical Center, Washington, DC 20057 (United States); Xiao, Jun Feng; Tuli, Leepika; Varghese, Rency S.; Zhou Bin; Tsai, Tsung-Heng; Nezami Ranjbar, Mohammad R.; Zhao Yi; Wang Jinlian; Di Poto, Cristina; Cheema, Amrita K. [Department of Oncology, Lombardi Comprehensive Cancer Center, Georgetown University Medical Center, Washington, DC 20057 (United States); Tadesse, Mahlet G. [Department of Mathematics and Statistics, Georgetown University, Washington, DC 20057 (United States); Goldman, Radoslav [Department of Oncology, Lombardi Comprehensive Cancer Center, Georgetown University Medical Center, Washington, DC 20057 (United States); Shetty, Kirti [Department of Surgery, Georgetown University Medical Center, Washington, DC 20057 (United States); Georgetown University Hospital, Washington, DC 20057 (United States)


    cholesterol metabolism) such as glycochenodeoxycholic acid 3-sulfate (3-sulfo-GCDCA), glycocholic acid (GCA), glycodeoxycholic acid (GDCA), taurocholic acid (TCA), and taurochenodeoxycholate (TCDCA). These results provide useful insights into HCC biomarker discovery utilizing metabolomics as an efficient and cost-effective platform. Our work shows that metabolomic profiling is a promising tool to identify candidate metabolic biomarkers for early detection of HCC cases in high risk population of cirrhotic patients.

  20. Transactional Network Platform: Applications

    Energy Technology Data Exchange (ETDEWEB)

    Katipamula, Srinivas; Lutes, Robert G.; Ngo, Hung; Underhill, Ronald M.


    In FY13, Pacific Northwest National Laboratory (PNNL) with funding from the Department of Energy’s (DOE’s) Building Technologies Office (BTO) designed, prototyped and tested a transactional network platform to support energy, operational and financial transactions between any networked entities (equipment, organizations, buildings, grid, etc.). Initially, in FY13, the concept demonstrated transactions between packaged rooftop air conditioners and heat pump units (RTUs) and the electric grid using applications or "agents" that reside on the platform, on the equipment, on a local building controller or in the Cloud. The transactional network project is a multi-lab effort with Oakridge National Laboratory (ORNL) and Lawrence Berkeley National Laboratory (LBNL) also contributing to the effort. PNNL coordinated the project and also was responsible for the development of the transactional network (TN) platform and three different applications associated with RTUs. This document describes two applications or "agents" in details, and also summarizes the platform. The TN platform details are described in another companion document.

  1. Atlas of Astronomical Discoveries

    CERN Document Server

    Schilling, Govert


    Four hundred years ago in Middelburg, in the Netherlands, the telescope was invented. The invention unleashed a revolution in the exploration of the universe. Galileo Galilei discovered mountains on the Moon, spots on the Sun, and moons around Jupiter. Christiaan Huygens saw details on Mars and rings around Saturn. William Herschel discovered a new planet and mapped binary stars and nebulae. Other astronomers determined the distances to stars, unraveled the structure of the Milky Way, and discovered the expansion of the universe. And, as telescopes became bigger and more powerful, astronomers delved deeper into the mysteries of the cosmos. In his Atlas of Astronomical Discoveries, astronomy journalist Govert Schilling tells the story of 400 years of telescopic astronomy. He looks at the 100 most important discoveries since the invention of the telescope. In his direct and accessible style, the author takes his readers on an exciting journey encompassing the highlights of four centuries of astronomy. Spectacul...

  2. Chronicles in drug discovery. (United States)

    Davies, Shelley L; Moral, Maria Angels; Bozzo, Jordi


    Chronicles in Drug Discovery features special interest reports on advances in drug discovery. This month we highlight agents that target and deplete immunosuppressive regulatory T cells, which are produced by tumor cells to hinder innate immunity against, or chemotherapies targeting, tumor-associated antigens. Antiviral treatments for respiratory syncytial virus, a severe and prevalent infection in children, are limited due to their side effect profiles and cost. New strategies currently under clinical development include monoclonal antibodies, siRNAs, vaccines and oral small molecule inhibitors. Recent therapeutic lines for Huntington's disease include gene therapies that target the mutated human huntingtin gene or deliver neuroprotective growth factors and cellular transplantation in apoptotic regions of the brain. Finally, we highlight the antiinflammatory and antinociceptive properties of new compounds targeting the somatostatin receptor subtype sst4, which warrant further study for their potential application as clinical analgesics.

  3. Recommendations for adaptation and validation of commercial kits for biomarker quantification in drug development. (United States)

    Khan, Masood U; Bowsher, Ronald R; Cameron, Mark; Devanarayan, Viswanath; Keller, Steve; King, Lindsay; Lee, Jean; Morimoto, Alyssa; Rhyne, Paul; Stephen, Laurie; Wu, Yuling; Wyant, Timothy; Lachno, D Richard


    Increasingly, commercial immunoassay kits are used to support drug discovery and development. Longitudinally consistent kit performance is crucial, but the degree to which kits and reagents are characterized by manufacturers is not standardized, nor are the approaches by users to adapt them and evaluate their performance through validation prior to use. These factors can negatively impact data quality. This paper offers a systematic approach to assessment, method adaptation and validation of commercial immunoassay kits for quantification of biomarkers in drug development, expanding upon previous publications and guidance. These recommendations aim to standardize and harmonize user practices, contributing to reliable biomarker data from commercial immunoassays, thus, enabling properly informed decisions during drug development.

  4. Discovery as a process

    Energy Technology Data Exchange (ETDEWEB)

    Loehle, C.


    The three great myths, which form a sort of triumvirate of misunderstanding, are the Eureka! myth, the hypothesis myth, and the measurement myth. These myths are prevalent among scientists as well as among observers of science. The Eureka! myth asserts that discovery occurs as a flash of insight, and as such is not subject to investigation. This leads to the perception that discovery or deriving a hypothesis is a moment or event rather than a process. Events are singular and not subject to description. The hypothesis myth asserts that proper science is motivated by testing hypotheses, and that if something is not experimentally testable then it is not scientific. This myth leads to absurd posturing by some workers conducting empirical descriptive studies, who dress up their study with a ``hypothesis`` to obtain funding or get it published. Methods papers are often rejected because they do not address a specific scientific problem. The fact is that many of the great breakthroughs in silence involve methods and not hypotheses or arise from largely descriptive studies. Those captured by this myth also try to block funding for those developing methods. The third myth is the measurement myth, which holds that determining what to measure is straightforward, so one doesn`t need a lot of introspection to do science. As one ecologist put it to me ``Don`t give me any of that philosophy junk, just let me out in the field. I know what to measure.`` These myths lead to difficulties for scientists who must face peer review to obtain funding and to get published. These myths also inhibit the study of science as a process. Finally, these myths inhibit creativity and suppress innovation. In this paper I first explore these myths in more detail and then propose a new model of discovery that opens the supposedly miraculous process of discovery to doser scrutiny.

  5. The discovery of quarks. (United States)

    Riordan, M


    Quarks are widely recognized today as being among the elementary particles of which matter is composed. The key evidence for their existence came from a series of inelastic electron-nucleon scattering experiments conducted between 1967 and 1973 at the Stanford Linear Accelerator Center. Other theoretical and experimental advances of the 1970s confirmed this discovery, leading to the present standard model of elementary particle physics.

  6. Discovery of Single Nucleotide Polymorphisms and Mutations by Pyrosequencing



    Comparative genomics, analyzing variation among individual genomes, is an area of intense investigation. DNA sequencing is usually employed to look for polymorphisms and mutations. Pyrosequencing, a real-time DNA sequencing method, is emerging as a popular platform for comparative genomics. Here we review the use of this technology for mutation scanning, polymorphism discovery and chemical haplotyping. We describe the methodology and accuracy of this technique and discuss how t...

  7. C. elegans in high-throughput drug discovery


    O’Reilly, Linda P.; Cliff J Luke; Perlmutter, David H.; Silverman, Gary A.; Pak, Stephen C.


    C. elegans has proven to be a useful model organism for investigating molecular and cellular aspects of numerous human diseases. More recently, investigators have explored the use of this organism as a tool for drug discovery. Although earlier drug screens were labor-intensive and low in throughput, recent advances in high-throughput liquid workflows, imaging platforms and data analysis software have made C. elegans a viable option for automated high-throughput drug screens. This review will ...

  8. Geostationary multipurpose platforms (United States)

    Bekey, I.; Bowman, R. M.


    In addition to the advantages generally associated with orbital platforms, such as improved reliability, economies of scale, simple connectivity of elements, reduced tracking demands and the restraint of orbital object population growth, geostationary platforms yield: (1) continuous access by fixed ground antennas for communications services; (2) continuous monitoring of phenomena over chosen regions of the earth's surface; (3) a preferred location for many solar-terrestrial physics experiments. The geostationary platform also offers a low-risk and economical solution to the impending saturation of the orbital arc/frequency spectrum, maximizing the capacity of individual slots and increasing the utility of the entire arc. It also allows the use of many small, simple and inexpensive earth stations through complexity inversion and high power per beam. Block diagram and operational flowcharts are provided.

  9. Identification of platform levels

    DEFF Research Database (Denmark)

    Mortensen, Niels Henrik


    reduction, ability to launch a wider product portfolio without increasing resources and reduction of complexity within the whole company. To support the multiple product development process, platform based product development has in many companies such as Philips, VW, Ford etc. proven to be a very effective...... because the nature of developing platforms and applications are very different. In single product development reuse is often determined by individual designers, in multiple product development reuse is to a large degree a management issue. It is difficult for a company to switch from single to multiple...... development will be examined. Based on the identification of the above characteristics five platform levels are described. The research presented in this paper is a result of MSc, Ph.D projects at the Technical University of Denmark and consultancy projects within the organisation of Institute of Product...

  10. Universal visualization platform (United States)

    Gee, Alexander G.; Li, Hongli; Yu, Min; Smrtic, Mary Beth; Cvek, Urska; Goodell, Howie; Gupta, Vivek; Lawrence, Christine; Zhou, Jainping; Chiang, Chih-Hung; Grinstein, Georges G.


    Although there are a number of visualization systems to choose from when analyzing data, only a few of these allow for the integration of other visualization and analysis techniques. There are even fewer visualization toolkits and frameworks from which one can develop ones own visualization applications. Even within the research community, scientists either use what they can from the available tools or start from scratch to define a program in which they are able to develop new or modified visualization techniques and analysis algorithms. Presented here is a new general-purpose platform for constructing numerous visualization and analysis applications. The focus of this system is the design and experimentation of new techniques, and where the sharing of and integration with other tools becomes second nature. Moreover, this platform supports multiple large data sets, and the recording and visualizing of user sessions. Here we introduce the Universal Visualization Platform (UVP) as a modern data visualization and analysis system.

  11. Core-shell hydrogel particles harvest, concentrate and preserve labile low abundance biomarkers.

    Directory of Open Access Journals (Sweden)

    Caterina Longo

    Full Text Available BACKGROUND: The blood proteome is thought to represent a rich source of biomarkers for early stage disease detection. Nevertheless, three major challenges have hindered biomarker discovery: a candidate biomarkers exist at extremely low concentrations in blood; b high abundance resident proteins such as albumin mask the rare biomarkers; c biomarkers are rapidly degraded by endogenous and exogenous proteinases. METHODOLOGY AND PRINCIPAL FINDINGS: Hydrogel nanoparticles created with a N-isopropylacrylamide based core (365 nm-shell (167 nm and functionalized with a charged based bait (acrylic acid were studied as a technology for addressing all these biomarker discovery problems, in one step, in solution. These harvesting core-shell nanoparticles are designed to simultaneously conduct size exclusion and affinity chromatography in solution. Platelet derived growth factor (PDGF, a clinically relevant, highly labile, and very low abundance biomarker, was chosen as a model. PDGF, spiked in human serum, was completely sequestered from its carrier protein albumin, concentrated, and fully preserved, within minutes by the particles. Particle sequestered PDGF was fully protected from exogenously added tryptic degradation. When the nanoparticles were added to a 1 mL dilute solution of PDGF at non detectable levels (less than 20 picograms per mL the concentration of the PDGF released from the polymeric matrix of the particles increased within the detection range of ELISA and mass spectrometry. Beyond PDGF, the sequestration and protection from degradation for a series of additional very low abundance and very labile cytokines were verified. CONCLUSIONS AND SIGNIFICANCE: We envision the application of harvesting core-shell nanoparticles to whole blood for concentration and immediate preservation of low abundance and labile analytes at the time of venipuncture.

  12. Early Stage Health Technology Assessment for Precision Biomarkers in Oral Health and Systems Medicine. (United States)

    Steuten, Lotte M G


    Health technology assessment (HTA) is a crucial science that influences the responsible and evidence-based transition of new discoveries from laboratory to applications in the clinic and society. HTA has recently moved "upstream" so as to assess technologies from their onset at their discovery, design, or planning phase. Biomarker research is relatively recent in oral health, but growing rapidly with investments made to advance dentistry and oral health and importantly, to build effective bridges between oral health and systems medicine since what happens in oral health affects systems pathophysiology, and vice versa. This article offers a synthesis of the latest trends and approaches in early phase HTA, with a view to near future applications in oral health, systems medicine, and biomarker-guided precision medicine. In brief, this review underscores that demonstrating health outcomes of biomarkers and next-generation diagnostics is particularly challenging because they do not always influence long-term outcomes directly, but rather impact subsequent care processes. Biomarker testing costs are typically less of a barrier to uptake in practice than the biomarker's impact on longer term health outcomes. As a single biomarker or next-generation diagnostic in oral health can inform decisions about numerous downstream diagnosis-treatment combinations, early stage "upstream" HTA is crucial in prioritizing the most valuable diagnostic applications to pursue first. For the vast array of oral health biomarkers currently developed, early HTA is necessary to timely and iteratively assess their comparative effectiveness and anticipate the inevitable questions about value for money from regulators and payers.

  13. Windows Azure Platform

    CERN Document Server

    Redkar, Tejaswi


    The Azure Services Platform is a brand-new cloud-computing technology from Microsoft. It is composed of four core components-Windows Azure, .NET Services, SQL Services, and Live Services-each with a unique role in the functioning of your cloud service. It is the goal of this book to show you how to use these components, both separately and together, to build flawless cloud services. At its heart Windows Azure Platform is a down-to-earth, code-centric book. This book aims to show you precisely how the components are employed and to demonstrate the techniques and best practices you need to know

  14. Windows Azure Platform

    CERN Document Server

    Redkar, Tejaswi


    The Windows Azure Platform has rapidly established itself as one of the most sophisticated cloud computing platforms available. With Microsoft working to continually update their product and keep it at the cutting edge, the future looks bright - if you have the skills to harness it. In particular, new features such as remote desktop access, dynamic content caching and secure content delivery using SSL make the latest version of Azure a more powerful solution than ever before. It's widely agreed that cloud computing has produced a paradigm shift in traditional architectural concepts by providin

  15. Biophysics in drug discovery: impact, challenges and opportunities. (United States)

    Renaud, Jean-Paul; Chung, Chun-Wa; Danielson, U Helena; Egner, Ursula; Hennig, Michael; Hubbard, Roderick E; Nar, Herbert


    Over the past 25 years, biophysical technologies such as X-ray crystallography, nuclear magnetic resonance spectroscopy, surface plasmon resonance spectroscopy and isothermal titration calorimetry have become key components of drug discovery platforms in many pharmaceutical companies and academic laboratories. There have been great improvements in the speed, sensitivity and range of possible measurements, providing high-resolution mechanistic, kinetic, thermodynamic and structural information on compound-target interactions. This Review provides a framework to understand this evolution by describing the key biophysical methods, the information they can provide and the ways in which they can be applied at different stages of the drug discovery process. We also discuss the challenges for current technologies and future opportunities to use biophysical methods to solve drug discovery problems.

  16. Sensitive multiplex detection of serological liver cancer biomarkers using SERS-active photonic crystal fiber probe. (United States)

    Dinish, U S; Balasundaram, Ghayathri; Chang, Young Tae; Olivo, Malini


    Surface-enhanced Raman scattering (SERS) spectroscopy possesses the most promising advantage of multiplex detection for biosensing applications, which is achieved due to the narrow 'fingerprint' Raman spectra from the analyte molecules. We developed an ultrasensitive platform for the multiplex detection of cancer biomarkers by combining the SERS technique with a hollow-core photonic crystal fiber (HCPCF). Axially aligned air channels inside the HCPCF provide an excellent platform for optical sensing using SERS. In addition to the flexibility of optical fibers, HCPCF provides better light confinement and a larger interaction length for the guided light and the analyte, resulting in an improvement in sensitivity to detect low concentrations of bioanalytes in extremely low sample volumes. Herein, for the first time, we demonstrate the sensitive multiplex detection of biomarkers immobilized inside the HCPCF using antibody-conjugated SERS-active nanoparticles (SERS nanotags). As a proof-of-concept for targeted multiplex detection, initially we carried out the sensing of epidermal growth factor receptor (EGFR) biomarker in oral squamous carcinoma cell lysate using three different SERS nanotags. Subsequently, we also achieved simultaneous detection of hepatocellular carcinoma (HCC) biomarkers-alpha fetoprotein (AFP) and alpha-1-antitrypsin (A1AT) secreted in the supernatant from Hep3b cancer cell line. Using a SERS-HCPCF sensing platform, we could successfully demonstrate the multiplex detection in an extremely low sample volume of ∼20 nL. In future, this study may lead to sensitive biosensing platform for the low concentration detection of biomarkers in an extremely low sample volume of body fluids to achieve early diagnosis of multiple diseases. (© 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim).

  17. Identification of Pharmacodynamic Transcript Biomarkers in Response to FGFR Inhibition by AZD4547. (United States)

    Delpuech, Oona; Rooney, Claire; Mooney, Lorraine; Baker, Dawn; Shaw, Robert; Dymond, Michael; Wang, Dennis; Zhang, Pei; Cross, Sarah; Veldman-Jones, Margaret; Wilson, Joanne; Davies, Barry R; Dry, Jonathan R; Kilgour, Elaine; Smith, Paul D


    The challenge of developing effective pharmacodynamic biomarkers for preclinical and clinical testing of FGFR signaling inhibition is significant. Assays that rely on the measurement of phospho-protein epitopes can be limited by the availability of effective antibody detection reagents. Transcript profiling enables accurate quantification of many biomarkers and provides a broader representation of pathway modulation. To identify dynamic transcript biomarkers of FGFR signaling inhibition by AZD4547, a potent inhibitor of FGF receptors 1, 2, and 3, a gene expression profiling study was performed in FGFR2-amplified, drug-sensitive tumor cell lines. Consistent with known signaling pathways activated by FGFR, we identified transcript biomarkers downstream of the RAS-MAPK and PI3K/AKT pathways. Using different tumor cell lines in vitro and xenografts in vivo, we confirmed that some of these transcript biomarkers (DUSP6, ETV5, YPEL2) were modulated downstream of oncogenic FGFR1, 2, 3, whereas others showed selective modulation only by FGFR2 signaling (EGR1). These transcripts showed consistent time-dependent modulation, corresponding to the plasma exposure of AZD4547 and inhibition of phosphorylation of the downstream signaling molecules FRS2 or ERK. Combination of FGFR and AKT inhibition in an FGFR2-mutated endometrial cancer xenograft model enhanced modulation of transcript biomarkers from the PI3K/AKT pathway and tumor growth inhibition. These biomarkers were detected on the clinically validated nanoString platform. Taken together, these data identified novel dynamic transcript biomarkers of FGFR inhibition that were validated in a number of in vivo models, and which are more robustly modulated by FGFR inhibition than some conventional downstream signaling protein biomarkers. Mol Cancer Ther; 15(11); 2802-13. ©2016 AACR.

  18. Recommendations and Standardization of Biomarker Quantification Using NMR-based Metabolomics with Particular Focus on Urinary Analysis

    KAUST Repository

    Emwas, Abdul-Hamid M.


    NMR-based metabolomics has shown considerable promise in disease diagnosis and biomarker discovery because it allows one to non-destructively identify and quantify large numbers of novel metabolite biomarkers in both biofluids and tissues. Indeed, precise metabolite quantification is a necessary prerequisite to move any chemical biomarker or biomarker panel from the lab into the clinic. Among the many biofluids (urine, serum, plasma, cerebrospinal fluid and saliva) commonly used for disease diagnosis and prognosis, urine has several advantages. It is abundant, sterile, easily obtained, needs little sample preparation and does not require any invasive medical procedures for collection. Furthermore, urine captures and concentrates many “unwanted” or “undesirable” compounds throughout the body, thereby providing a rich source of potentially useful disease biomarkers. However, the incredible variation in urine chemical concentrations due to effects such as gender, age, diet, life style, health conditions, and physical activity make the analysis of urine and the identification of useful urinary biomarkers by NMR quite challenging. In this review, we discuss a number of the most significant issues regarding NMR-based urinary metabolomics with a specific emphasis on metabolite quantification for disease biomarker applications. We also propose a number of data collection and instrumental recommendations regarding NMR pulse sequences, acceptable acquisition parameter ranges, relaxation effects on quantitation, proper handling of instrumental differences, as well as recommendations regarding sample preparation and biomarker assessment.

  19. Gene expression analysis in pregnant women and their infants identifies unique fetal biomarkers that circulate in maternal blood (United States)

    The discovery of fetal mRNA transcripts in the maternal circulation holds great promise for noninvasive prenatal diagnosis. To identify potential fetal biomarkers, we studied whole blood and plasma gene transcripts that were common to 9 term pregnant women and their newborns but absent or reduced in...

  20. Advances in induced pluripotent stem cells, genomics, biomarkers, and antiplatelet therapy highlights of the year in JCTR 2013. (United States)

    Barbato, Emanuele; Lara-Pezzi, Enrique; Stolen, Craig; Taylor, Angela; Barton, Paul J; Bartunek, Jozef; Iaizzo, Paul; Judge, Daniel P; Kirshenbaum, Lorrie; Blaxall, Burns C; Terzic, Andre; Hall, Jennifer L


    The Journal provides the clinician and scientist with the latest advances in discovery research, emerging technologies, preclinical research design and testing, and clinical trials. We highlight advances in areas of induced pluripotent stem cells, genomics, biomarkers, multimodality imaging, and antiplatelet biology and therapy. The top publications are critically discussed and presented along with anatomical reviews and FDA insight to provide context.

  1. Circulating microRNAs as Potential Biomarkers of Infectious Disease (United States)

    Correia, Carolina N.; Nalpas, Nicolas C.; McLoughlin, Kirsten E.; Browne, John A.; Gordon, Stephen V.; MacHugh, David E.; Shaughnessy, Ronan G.


    microRNAs (miRNAs) are a class of small non-coding endogenous RNA molecules that regulate a wide range of biological processes by post-transcriptionally regulating gene expression. Thousands of these molecules have been discovered to date, and multiple miRNAs have been shown to coordinately fine-tune cellular processes key to organismal development, homeostasis, neurobiology, immunobiology, and control of infection. The fundamental regulatory role of miRNAs in a variety of biological processes suggests that differential expression of these transcripts may be exploited as a novel source of molecular biomarkers for many different disease pathologies or abnormalities. This has been emphasized by the recent discovery of remarkably stable miRNAs in mammalian biofluids, which may originate from intracellular processes elsewhere in the body. The potential of circulating miRNAs as biomarkers of disease has mainly been demonstrated for various types of cancer. More recently, however, attention has focused on the use of circulating miRNAs as diagnostic/prognostic biomarkers of infectious disease; for example, human tuberculosis caused by infection with Mycobacterium tuberculosis, sepsis caused by multiple infectious agents, and viral hepatitis. Here, we review these developments and discuss prospects and challenges for translating circulating miRNA into novel diagnostics for infectious disease. PMID:28261201

  2. Peripheral biomarkers in animal models of major depressive disorder. (United States)

    Carboni, Lucia


    Investigations of preclinical biomarkers for major depressive disorder (MDD) encompass the quantification of proteins, peptides, mRNAs, or small molecules in blood or urine of animal models. Most studies aim at characterising the animal model by including the assessment of analytes or hormones affected in depressive patients. The ultimate objective is to validate the model to better understand the neurobiological basis of MDD. Stress hormones or inflammation-related analytes associated with MDD are frequently measured. In contrast, other investigators evaluate peripheral analytes in preclinical models to translate the results in clinical settings afterwards. Large-scale, hypothesis-free studies are performed in MDD models to identify candidate biomarkers. Other studies wish to propose new targets for drug discovery. Animal models endowed with predictive validity are investigated, and the assessment of peripheral analytes, such as stress hormones or immune molecules, is comprised to increase the confidence in the target. Finally, since the mechanism of action of antidepressants is incompletely understood, studies investigating molecular alterations associated with antidepressant treatment may include peripheral analyte levels. In conclusion, preclinical biomarker studies aid the identification of new candidate analytes to be tested in clinical trials. They also increase our understanding of MDD pathophysiology and help to identify new pharmacological targets.

  3. The "Alzheimer's disease signature": potential perspectives for novel biomarkers

    Directory of Open Access Journals (Sweden)

    Zella Davide


    Full Text Available Abstract Alzheimer's disease is a progressive and neurodegenerative disorder which involves multiple molecular mechanisms. Intense research during the last years has accumulated a large body of data and the search for sensitive and specific biomarkers has undergone a rapid evolution. However, the diagnosis remains problematic and the current tests do not accurately detect the process leading to neurodegeneration. Biomarkers discovery and validation are considered the key aspects to support clinical diagnosis and provide discriminatory power between different stages of the disorder. A considerable challenge is to integrate different types of data from new potent approach to reach a common interpretation and replicate the findings across studies and populations. Furthermore, long-term clinical follow-up and combined analysis of several biomarkers are among the most promising perspectives to diagnose and manage the disease. The present review will focus on the recent published data providing an updated overview of the main achievements in the genetic and biochemical research of the Alzheimer's disease. We also discuss the latest and most significant results that will help to define a specific disease signature whose validity might be clinically relevant for future AD diagnosis.

  4. Lipidomics applications for discovering biomarkers of diseases in clinical chemistry. (United States)

    Zhao, Ying-Yong; Cheng, Xian-long; Lin, Rui-Chao


    Lipids are the fundamental components of biological membranes as well as the metabolites of organisms. Lipids play diverse and important roles in biologicals. The lipid imbalance is closely associated with numerous human lifestyle-related diseases, such as atherosclerosis, obesity, diabetes, and Alzheimer's disease. Lipidomics or lipid profiling is a system-based study of all lipids aiming at comprehensive analysis of lipids in the biological system. Lipidomics has been accepted as a lipid-related research tool in lipid biochemistry, clinical biomarker discovery, disease diagnosis, and in understanding disease pathology. Lipidomics will not only provide insights into the specific functions of lipid species in health and disease, but will also identify potential biomarkers for establishing preventive or therapeutic programs for human diseases. This review presents an overview of lipidomics followed by in-depth discussion of its application to the study of human diseases, including extraction methods of lipids, analytical technologies, data analysis, and clinical research in cancer, neuropsychiatric disease, cardiovascular disease, kidney disease, and respiratory disease. We describe the current status of the identification of metabolic biomarkers in different diseases. We also discuss the lipidomics for the future perspectives and their potential problems. The application of lipidomics in clinical studies may provide new insights into lipid profiling and pathophysiological mechanisms.

  5. High Resolution Discovery Proteomics Reveals Candidate Disease Progression Markers of Alzheimer's Disease in Human Cerebrospinal Fluid.

    Directory of Open Access Journals (Sweden)

    Ronald C Hendrickson

    Full Text Available Disease modifying treatments for Alzheimer's disease (AD constitute a major goal in medicine. Current trends suggest that biomarkers reflective of AD neuropathology and modifiable by treatment would provide supportive evidence for disease modification. Nevertheless, a lack of quantitative tools to assess disease modifying treatment effects remains a major hurdle. Cerebrospinal fluid (CSF biochemical markers such as total tau, p-tau and Ab42 are well established markers of AD; however, global quantitative biochemical changes in CSF in AD disease progression remain largely uncharacterized. Here we applied a high resolution open discovery platform, dMS, to profile a cross-sectional cohort of lumbar CSF from post-mortem diagnosed AD patients versus those from non-AD/non-demented (control patients. Multiple markers were identified to be statistically significant in the cohort tested. We selected two markers SME-1 (p<0.0001 and SME-2 (p = 0.0004 for evaluation in a second independent longitudinal cohort of human CSF from post-mortem diagnosed AD patients and age-matched and case-matched control patients. In cohort-2, SME-1, identified as neuronal secretory protein VGF, and SME-2, identified as neuronal pentraxin receptor-1 (NPTXR, in AD were 21% (p = 0.039 and 17% (p = 0.026 lower, at baseline, respectively, than in controls. Linear mixed model analysis in the longitudinal cohort estimate a decrease in the levels of VGF and NPTXR at the rate of 10.9% and 6.9% per year in the AD patients, whereas both markers increased in controls. Because these markers are detected by mass spectrometry without the need for antibody reagents, targeted MS based assays provide a clear translation path for evaluating selected AD disease-progression markers with high analytical precision in the clinic.

  6. Strategies to design clinical studies to identify predictive biomarkers in cancer research. (United States)

    Perez-Gracia, Jose Luis; Sanmamed, Miguel F; Bosch, Ana; Patiño-Garcia, Ana; Schalper, Kurt A; Segura, Victor; Bellmunt, Joaquim; Tabernero, Josep; Sweeney, Christopher J; Choueiri, Toni K; Martín, Miguel; Fusco, Juan Pablo; Rodriguez-Ruiz, Maria Esperanza; Calvo, Alfonso; Prior, Celia; Paz-Ares, Luis; Pio, Ruben; Gonzalez-Billalabeitia, Enrique; Gonzalez Hernandez, Alvaro; Páez, David; Piulats, Jose María; Gurpide, Alfonso; Andueza, Mapi; de Velasco, Guillermo; Pazo, Roberto; Grande, Enrique; Nicolas, Pilar; Abad-Santos, Francisco; Garcia-Donas, Jesus; Castellano, Daniel; Pajares, María J; Suarez, Cristina; Colomer, Ramon; Montuenga, Luis M; Melero, Ignacio


    The discovery of reliable biomarkers to predict efficacy and toxicity of anticancer drugs remains one of the key challenges in cancer research. Despite its relevance, no efficient study designs to identify promising candidate biomarkers have been established. This has led to the proliferation of a myriad of exploratory studies using dissimilar strategies, most of which fail to identify any promising targets and are seldom validated. The lack of a proper methodology also determines that many anti-cancer drugs are developed below their potential, due to failure to identify predictive biomarkers. While some drugs will be systematically administered to many patients who will not benefit from them, leading to unnecessary toxicities and costs, others will never reach registration due to our inability to identify the specific patient population in which they are active. Despite these drawbacks, a limited number of outstanding predictive biomarkers have been successfully identified and validated, and have changed the standard practice of oncology. In this manuscript, a multidisciplinary panel reviews how those key biomarkers were identified and, based on those experiences, proposes a methodological framework-the DESIGN guidelines-to standardize the clinical design of biomarker identification studies and to develop future research in this pivotal field.

  7. Discovering plant metabolic biomarkers for phenotype prediction using an untargeted approach. (United States)

    Steinfath, Matthias; Strehmel, Nadine; Peters, Rolf; Schauer, Nicolas; Groth, Detlef; Hummel, Jan; Steup, Martin; Selbig, Joachim; Kopka, Joachim; Geigenberger, Peter; Van Dongen, Joost T


    Biomarkers are used to predict phenotypical properties before these features become apparent and, therefore, are valuable tools for both fundamental and applied research. Diagnostic biomarkers have been discovered in medicine many decades ago and are now commonly applied. While this is routine in the field of medicine, it is of surprise that in agriculture this approach has never been investigated. Up to now, the prediction of phenotypes in plants was based on growing plants and assaying the organs of interest in a time intensive process. For the first time, we demonstrate in this study the application of metabolomics to predict agronomic important phenotypes of a crop plant that was grown in different environments. Our procedure consists of established techniques to screen untargeted for a large amount of metabolites in parallel, in combination with machine learning methods. By using this combination of metabolomics and biomathematical tools metabolites were identified that can be used as biomarkers to improve the prediction of traits. The predictive metabolites can be selected and used subsequently to develop fast, targeted and low-cost diagnostic biomarker assays that can be implemented in breeding programs or quality assessment analysis. The identified metabolic biomarkers allow for the prediction of crop product quality. Furthermore, marker-assisted selection can benefit from the discovery of metabolic biomarkers when other molecular markers come to its limitation. The described marker selection method was developed for potato tubers, but is generally applicable to any crop and trait as it functions independently of genomic information.

  8. Games and Platform Decisions

    DEFF Research Database (Denmark)

    Hansen, Poul H. Kyvsgård; Mikkola, Juliana Hsuan


    is the application of on-line games in order to provide training for decision makers and in order to generate overview over the implications of platform decisions. However, games have to be placed in a context with other methods and we argue that a mixture of games, workshops, and simulations can provide improved...

  9. Biomarkers of silicosis: Potential candidates

    Directory of Open Access Journals (Sweden)

    Tiwari R


    Full Text Available Silica dust is widely prevalent in the atmosphere and more common than the other types of dust, thus making silicosis the most frequently occurring pneumoconiosis. In India also, studies carried out by National Institute of Occupational Health have shown high prevalence of silicosis in small factories and even in nonoccupational exposed subjects. The postero-anterior chest radiographs remain the key tool in diagnosing and assessing the extent and severity of interstitial lung disease. Although Computed Tomography detects finer anatomical structure than radiography it could not get popularity because of its cost. On the basis of histological features of silicosis many potential biomarkers such as Cytokines, Tumor Necrosis Factor, Interleukin 1, Angiotensin Converting Enzyme, Serum Copper, Fas ligand (FasL, etc. have been tried. However, further studies are needed to establish these potential biomarkers as true biomarker of silicosis.

  10. Biomarkers of replicative senescence revisited

    DEFF Research Database (Denmark)

    Nehlin, Jan


    Biomarkers of replicative senescence can be defined as those ultrastructural and physiological variations as well as molecules whose changes in expression, activity or function correlate with aging, as a result of the gradual exhaustion of replicative potential and a state of permanent cell cycle...... arrest. The biomarkers that characterize the path to an irreversible state of cell cycle arrest due to proliferative exhaustion may also be shared by other forms of senescence-inducing mechanisms. Validation of senescence markers is crucial in circumstances where quiescence or temporary growth arrest may...... be triggered or is thought to be induced. Pre-senescence biomarkers are also important to consider as their presence indicate that induction of aging processes is taking place. The bona fide pathway leading to replicative senescence that has been extensively characterized is a consequence of gradual reduction...

  11. Mobile Platforms and Development Environments

    CERN Document Server

    Helal, Sumi; Li, Wengdong


    Mobile platform development has lately become a technological war zone with extremely dynamic and fluid movement, especially in the smart phone and tablet market space. This Synthesis lecture is a guide to the latest developments of the key mobile platforms that are shaping the mobile platform industry. The book covers the three currently dominant native platforms -- iOS, Android and Windows Phone -- along with the device-agnostic HTML5 mobile web platform. The lecture also covers location-based services (LBS) which can be considered as a platform in its own right. The lecture utilizes a sampl

  12. Real-Time Discovery Services over Large, Heterogeneous and Complex Healthcare Datasets Using Schema-Less, Column-Oriented Methods

    Energy Technology Data Exchange (ETDEWEB)

    Begoli, Edmon [ORNL; Dunning, Ted [MapR Technologies; Charlie, Frasure [PYA Analytics


    We present a service platform for schema-leess exploration of data and discovery of patient-related statistics from healthcare data sets. The architecture of this platform is motivated by the need for fast, schema-less, and flexible approaches to SQL-based exploration and discovery of information embedded in the common, heterogeneously structured healthcare data sets and supporting components (electronic health records, practice management systems, etc.) The motivating use cases described in the paper are clinical trials candidate discovery, and a treatment effectiveness analysis. Following the use cases, we discuss the key features and software architecture of the platform, the underlying core components (Apache Parquet, Drill, the web services server), and the runtime profiles and performance characteristics of the platform. We conclude by showing dramatic speedup with some approaches, and the performance tradeoffs and limitations of others.

  13. Biomarker Analysis of Stored Blood Products: Emphasis on Pre-Analytical Issues

    Directory of Open Access Journals (Sweden)

    Niels Lion


    Full Text Available Millions of blood products are transfused every year; many lives are thus directly concerned by transfusion. The three main labile blood products used in transfusion are erythrocyte concentrates, platelet concentrates and fresh frozen plasma. Each of these products has to be stored according to its particular components. However, during storage, modifications or degradation of those components may occur, and are known as storage lesions. Thus, biomarker discovery of in vivo blood aging as well as in vitro labile blood products storage lesions is of high interest for the transfusion medicine community. Pre-analytical issues are of major importance in analyzing the various blood products during storage conditions as well as according to various protocols that are currently used in blood banks for their preparations. This paper will review key elements that have to be taken into account in the context of proteomic-based biomarker discovery applied to blood banking.

  14. Bias in Peripheral Depression Biomarkers

    DEFF Research Database (Denmark)

    Carvalho, André F; Köhler, Cristiano A; Brunoni, André R


    BACKGROUND: To aid in the differentiation of individuals with major depressive disorder (MDD) from healthy controls, numerous peripheral biomarkers have been proposed. To date, no comprehensive evaluation of the existence of bias favoring the publication of significant results or inflating effect...... sizes has been conducted. METHODS: Here, we performed a comprehensive review of meta-analyses of peripheral nongenetic biomarkers that could discriminate individuals with MDD from nondepressed controls. PubMed/MEDLINE, EMBASE, and PsycINFO databases were searched through April 10, 2015. RESULTS: From 15...

  15. Beyond graphene: Electrochemical sensors and biosensors for biomarkers detection. (United States)

    Bollella, Paolo; Fusco, Giovanni; Tortolini, Cristina; Sanzò, Gabriella; Favero, Gabriele; Gorton, Lo; Antiochia, Riccarda


    Graphene's success has stimulated great interest and research in the synthesis and characterization of graphene-like 2D materials, single and few-atom-thick layers of van der Waals materials, which show fascinating and technologically useful properties. This review presents an overview of recent electrochemical sensors and biosensors based on graphene and on graphene-like 2D materials for biomarkers detection. Initially, we will outline different electrochemical sensors and biosensors based on chemically derived graphene, including graphene oxide and reduced graphene oxide, properly functionalized for improved performances and we will discuss the various strategies to prepare graphene modified electrodes. Successively, we present electrochemical sensors and biosensors based on graphene-like 2D materials, such as boron nitride (BN), graphite-carbon nitride (g-C3N4), transition metal dichalcogenides (TMDs), transition metal oxides and graphane, outlining how the new modified 2D nanomaterials will improve the electrochemical performances. Finally, we will compare the results obtained with different sensors and biosensors for the detection of important biomarkers such as glucose, hydrogen peroxide and cancer biomarkers and highlight the advantages and disadvantages of the use of graphene and graphene-like 2D materials in different sensing platforms.

  16. The development of algorithms for parallel knowledge discovery using graphics accelerators (United States)

    Zieliński, Paweł; Mulawka, Jan


    The paper broaches topics of selected knowledge discovery algorithms. Different implementations have been verified on parallel platforms, including graphics accelerators using CUDA technology, multi-core microprocessors using OpenMP and many graphics accelerators. Results of investigations have been compared in terms of performance and scalability. Different types of data representation were also tested. The possibilities of both platforms, using the classification algorithms: the k-nearest neighbors, support vector machines and logistic regression are discussed.

  17. Automated Supernova Discovery (Abstract) (United States)

    Post, R. S.


    (Abstract only) We are developing a system of robotic telescopes for automatic recognition of Supernovas as well as other transient events in collaboration with the Puckett Supernova Search Team. At the SAS2014 meeting, the discovery program, SNARE, was first described. Since then, it has been continuously improved to handle searches under a wide variety of atmospheric conditions. Currently, two telescopes are used to build a reference library while searching for PSN with a partial library. Since data is taken every night without clouds, we must deal with varying atmospheric and high background illumination from the moon. Software is configured to identify a PSN, reshoot for verification with options to change the run plan to acquire photometric or spectrographic data. The telescopes are 24-inch CDK24, with Alta U230 cameras, one in CA and one in NM. Images and run plans are sent between sites so the CA telescope can search while photometry is done in NM. Our goal is to find bright PSNs with magnitude 17.5 or less which is the limit of our planned spectroscopy. We present results from our first automated PSN discoveries and plans for PSN data acquisition.

  18. Causality discovery technology (United States)

    Chen, M.; Ertl, T.; Jirotka, M.; Trefethen, A.; Schmidt, A.; Coecke, B.; Bañares-Alcántara, R.


    Causality is the fabric of our dynamic world. We all make frequent attempts to reason causation relationships of everyday events (e.g., what was the cause of my headache, or what has upset Alice?). We attempt to manage causality all the time through planning and scheduling. The greatest scientific discoveries are usually about causality (e.g., Newton found the cause for an apple to fall, and Darwin discovered natural selection). Meanwhile, we continue to seek a comprehensive understanding about the causes of numerous complex phenomena, such as social divisions, economic crisis, global warming, home-grown terrorism, etc. Humans analyse and reason causality based on observation, experimentation and acquired a priori knowledge. Today's technologies enable us to make observations and carry out experiments in an unprecedented scale that has created data mountains everywhere. Whereas there are exciting opportunities to discover new causation relationships, there are also unparalleled challenges to benefit from such data mountains. In this article, we present a case for developing a new piece of ICT, called Causality Discovery Technology. We reason about the necessity, feasibility and potential impact of such a technology.

  19. Biomarker Detection using PS2-Thioaptamers Project (United States)

    National Aeronautics and Space Administration — AM Biotechnologies (AM) will develop a system to detect and quantify bone demineralization biomarkers as outlined in SBIR Topic "Technologies to Detect Biomarkers"....

  20. Proteomic profiling of exosomes leads to the identification of novel biomarkers for prostate cancer.

    Directory of Open Access Journals (Sweden)

    Diederick Duijvesz

    Full Text Available BACKGROUND: Current markers for prostate cancer, such as PSA lack specificity. Therefore, novel biomarkers are needed. Unfortunately, the complexity of body fluids often hampers biomarker discovery. An attractive alternative approach is the isolation of small vesicles, i.e. exosomes, ∼100 nm, which contain proteins that are specific to the tissue from which they are derived and therefore can be considered as treasure chests for disease-specific biomarker discovery. MATERIALS AND METHODS: Exosomes were isolated from 2 immortalized primary prostate epithelial cells (PNT2C2 and RWPE-1 and 2 PCa cell lines (PC346C and VCaP by ultracentrifugation. After tryptic digestion, proteomic analyses utilized a nanoLC coupled with an LTQ-Orbitrap operated in tandem MS (MS/MS mode. Accurate Mass and Time (AMT tag approach was employed for peptide identification and quantitation. Candidate biomarkers were validated by Western blotting and Immunohistochemistry. RESULTS: Proteomic characterization resulted in the identification of 248, 233, 169, and 216 proteins by at least 2 peptides in exosomes from PNT2C2, RWPE-1, PC346C, and VCaP, respectively. Statistical analyses revealed 52 proteins differently abundant between PCa and control cells, 9 of which were more abundant in PCa. Validation by Western blotting confirmed a higher abundance of FASN, XPO1 and PDCD6IP (ALIX in PCa exosomes. CONCLUSIONS: Identification of exosomal proteins using high performance LC-FTMS resulted in the discovery of PDCD6IP, FASN, XPO1 and ENO1 as new candidate biomarkers for prostate cancer.

  1. Biomarkers and sustainable innovation in cardiovascular drug development: lessons from near and far afield. (United States)

    Medford, Russell M; Dagi, T Forcht; Rosenson, Robert S; Offermann, Margaret K


    Future innovative therapies targeting cardiovascular disease (CVD) have the potential to improve health outcomes and to contain rising healthcare costs. Unsustainable increases in the size, cost and duration of clinical trial programs necessary for regulatory approval, however, threaten the entire innovation enterprise. Rising costs for clinical trials are due in large part to increasing demands for hard cardiovascular clinical endpoints as measures of therapeutic efficacy. The development and validation of predictive and surrogate biomarkers, as laboratory or other objective measures predictive or reflective of clinical endpoints, are an important part of the solution to this challenge. This review will discuss insights applicable to CVD derived from the use of predictive biomarkers in oncologic drug development, the evolving role of high density lipoprotein (HDL) in CVD drug development and the impact biomarkers and surrogates have on the continued investment from multiple societal sources critical for innovative CVD drug discovery and development.

  2. Acute kidney injury biomarkers: renal angina and the need for a renal troponin I

    Directory of Open Access Journals (Sweden)

    Goldstein Stuart L


    Full Text Available Abstract Acute kidney injury (AKI in hospitalized patients is independently associated with increased morbidity and mortality in pediatric and adult populations. Continued reliance on serum creatinine and urine output to diagnose AKI has resulted in our inability to provide successful therapeutic and supportive interventions to prevent and mitigate AKI and its effects. Research efforts over the last decade have focused on the discovery and validation of novel urinary biomarkers to detect AKI prior to a change in kidney function and to aid in the differential diagnosis of AKI. The aim of this article is to review the AKI biomarker literature with a focus on the context in which they should serve to add to the clinical context facing physicians caring for patients with, or at-risk for, AKI. The optimal and appropriate utilization of AKI biomarkers will only be realized by understanding their characteristics and placing reasonable expectations on their performance in the clinical arena.

  3. Recent advances in biomarkers for Parkinson's disease focusing on biochemicals, omics and neuroimaging. (United States)

    Ren, Rutong; Sun, Yi; Zhao, Xin; Pu, Xiaoping


    Parkinson's disease (PD) is one of the most common neurodegenerative disorders, involving progressive loss of the nigro-striatal dopaminergic neurons. Cardinal symptoms including tremors, muscle rigidity, drooping posture, drooping, walking difficulty, and autonomic symptoms appear when a significant number of nigrostriatal dopaminergic neurons have already been destroyed. Hence, reliable biomarkers are needed for early and accurate diagnosis to measure disease progression and response to therapy. We review the current status of protein and small molecule biomarkers involved in oxidative stress, protein aggregation and inflammation etc. which are present in cerebrospinal fluid, human blood, urine or saliva. In recent years, advances in genomics, proteomics, metabolomics, and functional brain imaging techniques have led to new insights into the pathoetiology of PD. Further studies in the novel discovery of PD biomarkers will provide avenues to treat PD patients more effectively with few or no side effects.

  4. Cytokines: Their Role in Stroke and Potential Use as Biomarkers and Therapeutic Targets


    Doll, Danielle N.; Barr, Taura L.; Simpkins, James W.


    Inflammatory mechanisms both in the periphery and in the CNS are important in the pathophysiologic processes occurring after the onset of ischemic stroke (IS). Cytokines are key players in the inflammatory mechanism and contribute to the progression of ischemic damage. This literature review focuses on the effects of inflammation on ischemic stroke, and the role pro-inflammatory and anti-inflammatory cytokines play on deleterious or beneficial stroke outcome. The discovery of biomarkers and n...

  5. Ethylphenidate as a selective dopaminergic agonist and methylphenidate-ethanol transesterification biomarker


    Patrick, Kennerly S.; Corbin, Timothy R.; Murphy, Cristina E.


    We review the pharmaceutical science of ethylphenidate (EPH) in the contexts of drug discovery; drug interactions; biomarker for dl-methylphenidate (MPH)-ethanol exposure; potentiation of dl-MPH abuse liability; contemporary “designer drug”; pertinence to the newer transdermal and chiral switch MPH formulations; as well as problematic internal standard. d-EPH selectively targets the dopamine transporter while d-MPH exhibits equipotent actions at dopamine and norepinephrine transporters. This ...

  6. Representation Discovery using Harmonic Analysis

    CERN Document Server

    Mahadevan, Sridhar


    Representations are at the heart of artificial intelligence (AI). This book is devoted to the problem of representation discovery: how can an intelligent system construct representations from its experience? Representation discovery re-parameterizes the state space - prior to the application of information retrieval, machine learning, or optimization techniques - facilitating later inference processes by constructing new task-specific bases adapted to the state space geometry. This book presents a general approach to representation discovery using the framework of harmonic analysis, in particu

  7. Serum biomarkers predictive of depressive episodes in panic disorder. (United States)

    Gottschalk, M G; Cooper, J D; Chan, M K; Bot, M; Penninx, B W J H; Bahn, S


    Panic disorder with or without comorbid agoraphobia (PD/PDA) has been linked to an increased risk to develop subsequent depressive episodes, yet the underlying pathophysiology of these disorders remains poorly understood. We aimed to identify a biomarker panel predictive for the development of a depressive disorder (major depressive disorder and/or dysthymia) within a 2-year-follow-up period. Blood serum concentrations of 165 analytes were evaluated in 120 PD/PDA patients without depressive disorder baseline diagnosis (6-month-recency) in the Netherlands Study of Depression and Anxiety (NESDA). We assessed the predictive performance of serum biomarkers, clinical, and self-report variables using receiver operating characteristics curves (ROC) and the area under the ROC curve (AUC). False-discovery-rate corrected logistic regression model selection of serum analytes and covariates identified an optimal predictive panel comprised of tetranectin and creatine kinase MB along with patient gender and scores from the Inventory of Depressive Symptomatology (IDS) rating scale. Combined, an AUC of 0.87 was reached for identifying the PD/PDA patients who developed a depressive disorder within 2 years (n = 44). The addition of biomarkers represented a significant (p = 0.010) improvement over using gender and IDS alone as predictors (AUC = 0.78). For the first time, we report on a combination of biological serum markers, clinical variables and self-report inventories that can detect PD/PDA patients at increased risk of developing subsequent depressive disorders with good predictive performance in a naturalistic cohort design. After an independent validation our proposed biomarkers could prove useful in the detection of at-risk PD/PDA patients, allowing for early therapeutic interventions and improving clinical outcome.

  8. Biomarkers of brain injury in the premature infant

    Directory of Open Access Journals (Sweden)

    Martha V. Douglas-Escobar


    Full Text Available The term encephalopathy of prematurity encompasses not only the acute brain injury (such as intraventricular hemorrhage but also complex disturbance on the infant’s subsequent brain development. In premature infants, the most frequent recognized source of brain injury is intraventricular hemorrhage (IVH and periventricular leukomalacia (PVL. Furthermore 20-25% infants with birth weigh less than 1,500 g will have IVH and that proportion increases to 45% if the birth weight is less than 500-750 g. In addition, nearly 60% of very low birth weight newborns will have hypoxic-ischemic injury. Therefore permanent lifetime neurodevelopmental disabilities are frequent in premature infants. Innovative approach to prevent or decrease brain injury in preterm infants requires discovery of biomarkers able to discriminate infants at risk for injury, monitor the progression of the injury and assess efficacy of neuroprotective clinical trials. In this article, we will review biomarkers studied in premature infants with IVH, Post-hemorrhagic ventricular dilation (PHVD and PVL including: S100b, Activin A, erythropoietin, chemokine CCL 18, GFAP and NFL will also be examined. Some of the most promising biomarkers for IVH are S100β and Activin. The concentrations of TGF-β1, MMP-9 and PAI-1 in cerebrospinal fluid could be used to discriminate patients that will require shunt after post-hemorrhagic ventricular dilation. Neonatal brain injury is frequent in premature infants admitted to the neonatal intensive care and we hope to contribute to the awareness and interest in clinical validation of established as well as novel neonatal brain injury biomarkers.

  9. Biomarkers of brain injury in the premature infant. (United States)

    Douglas-Escobar, Martha; Weiss, Michael D


    The term "encephalopathy of prematurity" encompasses not only the acute brain injury [such as intraventricular hemorrhage (IVH)] but also complex disturbance on the infant's subsequent brain development. In premature infants, the most frequent recognized source of brain injury is IVH and periventricular leukomalacia (PVL). Furthermore 20-25% infants with birth weigh less than 1,500 g will have IVH and that proportion increases to 45% if the birth weight is less than 500-750 g. In addition, nearly 60% of very low birth weight newborns will have hypoxic-ischemic injury. Therefore permanent lifetime neurodevelopmental disabilities are frequent in premature infants. Innovative approach to prevent or decrease brain injury in preterm infants requires discovery of biomarkers able to discriminate infants at risk for injury, monitor the progression of the injury, and assess efficacy of neuroprotective clinical trials. In this article, we will review biomarkers studied in premature infants with IVH, Post-hemorrhagic ventricular dilation (PHVD), and PVL including: S100b, Activin A, erythropoietin, chemokine CCL 18, GFAP, and NFL will also be examined. Some of the most promising biomarkers for IVH are S100β and Activin. The concentrations of TGF-β1, MMP-9, and PAI-1 in cerebrospinal fluid could be used to discriminate patients that will require shunt after PHVD. Neonatal brain injury is frequent in premature infants admitted to the neonatal intensive care and we hope to contribute to the awareness and interest in clinical validation of established as well as novel neonatal brain injury biomarkers.

  10. Synthetic biology for pharmaceutical drug discovery. (United States)

    Trosset, Jean-Yves; Carbonell, Pablo


    Synthetic biology (SB) is an emerging discipline, which is slowly reorienting the field of drug discovery. For thousands of years, living organisms such as plants were the major source of human medicines. The difficulty in resynthesizing natural products, however, often turned pharmaceutical industries away from this rich source for human medicine. More recently, progress on transformation through genetic manipulation of biosynthetic units in microorganisms has opened the possibility of in-depth exploration of the large chemical space of natural products derivatives. Success of SB in drug synthesis culminated with the bioproduction of artemisinin by microorganisms, a tour de force in protein and metabolic engineering. Today, synthetic cells are not only used as biofactories but also used as cell-based screening platforms for both target-based and phenotypic-based approaches. Engineered genetic circuits in synthetic cells are also used to decipher disease mechanisms or drug mechanism of actions and to study cell-cell communication within bacteria consortia. This review presents latest developments of SB in the field of drug discovery, including some challenging issues such as drug resistance and drug toxicity.

  11. Common tester platform concept.

    Energy Technology Data Exchange (ETDEWEB)

    Hurst, Michael James


    This report summarizes the results of a case study on the doctrine of a common tester platform, a concept of a standardized platform that can be applicable across the broad spectrum of testing requirements throughout the various stages of a weapons program, as well as across the various weapons programs. The common tester concept strives to define an affordable, next-generation design that will meet testing requirements with the flexibility to grow and expand; supporting the initial development stages of a weapons program through to the final production and surveillance stages. This report discusses a concept investing key leveraging technologies and operational concepts combined with prototype tester-development experiences and practical lessons learned gleaned from past weapons programs.

  12. OGC Collaborative Platform undercover (United States)

    Buehler, G.; Arctur, D. K.; Bermudez, L. E.


    The mission of the Open Geospatial Consortium (OGC) is to serve as a global forum for the collaboration of developers and users of spatial data products and services, and to advance the development of international standards for geospatial interoperability. The OGC coordinates with over 400 institutions in the development of geospatial standards. OGC has a dedicated staff supported by a Collaborative Web Platform to enable sophisticated and successful coordination among its members. Since its origins in the early 1990s, the OGC Collaborative Web Platform has evolved organically to be the collaboration hub for standards development in the exchange of geospatial and related types of information, among a global network of thousands of technical, scientific and management professionals spanning numerous disparate application domains. This presentation describes the structure of this collaboration hub, the relationships enabled (both among and beyond OGC members), and how this network fits in a broader ecosystem of technology development and information standards organizations.

  13. Available: motorised platform

    CERN Multimedia

    The COMPASS collaboration


    The COMPASS collaboration would like to offer to a new owner the following useful and fully operational piece of equipment, which is due to be replaced with better adapted equipment.   Please contact Erwin Bielert ( or 160539) for further information.  Motorized platform (FOR FREE):   Fabricated by ACL (Alfredo Cardoso & Cia Ltd) in Portugal. The model number is MeXs 5-­‐30.  Specifications: 5 m wide, 1 m deep, adjustable height (1.5 m if folded). Maximum working floor height: 4 m. conforms to CERN regulations, number LV158. Type LD500, capacity 500 kg and weight 2000 kg.  If no interested party is found before December 2014, the platform will be thrown away.

  14. Denton Vacuum Discovery-550 Sputterer (United States)

    Federal Laboratory Consortium — Description: CORAL Name: Sputter 2 Similar to the existing 4-Gun Denton Discovery 22 Sputter system, with the following enhancements: Specifications / Capabilities:...

  15. Optogenetics enlightens neuroscience drug discovery. (United States)

    Song, Chenchen; Knöpfel, Thomas


    Optogenetics - the use of light and genetics to manipulate and monitor the activities of defined cell populations - has already had a transformative impact on basic neuroscience research. Now, the conceptual and methodological advances associated with optogenetic approaches are providing fresh momentum to neuroscience drug discovery, particularly in areas that are stalled on the concept of 'fixing the brain chemistry'. Optogenetics is beginning to translate and transit into drug discovery in several key domains, including target discovery, high-throughput screening and novel therapeutic approaches to disease states. Here, we discuss the exciting potential of optogenetic technologies to transform neuroscience drug discovery.

  16. Health-e-Child a grid platform for european paediatrics

    CERN Document Server

    Skaburskas, K; Shade, J; Manset, D; Revillard, J; Rios, A; Anjum, A; Branson, A; Bloodsworth, P; Hauer, T; McClatchey, R; Rogulin, D


    The Health-e-Child (HeC) project [1], [2] is an EC Framework Programme 6 Integrated Project that aims to develop a grid-based integrated healthcare platform for paediatrics. Using this platform biomedical informaticians will integrate heterogeneous data and perform epidemiological studies across Europe. The resulting Grid enabled biomedical information platform will be supported by robust search, optimization and matching techniques for information collected in hospitals across Europe. In particular, paediatricians will be provided with decision support, knowledge discovery and disease modelling applications that will access data in hospitals in the UK, Italy and France, integrated via the Grid. For economy of scale, reusability, extensibility, and maintainability, HeC is being developed on top of an EGEE/gLite [3] based infrastructure that provides all the common data and computation management services required by the applications. This paper discusses some of the major challenges in bio-medical data integr...

  17. Video analysis platform


    FLORES, Pablo; Arias, Pablo; Lecumberry, Federico; Pardo, Álvaro


    In this article we present the Video Analysis Platform (VAP) which is an open source software framework for video analysis, processing and description. The main goals of VAP are: to provide a multiplatform system which allows the easy implementation of video algorithms, provide structures and algorithms for the segmentation of video data in its different levels of abstraction: shots, frames, objects, regions, etc, permit the generation and comparison of MPEG7-like descriptors, and develop tes...

  18. HPC - Platforms Penta Chart

    Energy Technology Data Exchange (ETDEWEB)

    Trujillo, Angelina Michelle [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)


    Strategy, Planning, Acquiring- very large scale computing platforms come and go and planning for immensely scalable machines often precedes actual procurement by 3 years. Procurement can be another year or more. Integration- After Acquisition, machines must be integrated into the computing environments at LANL. Connection to scalable storage via large scale storage networking, assuring correct and secure operations. Management and Utilization – Ongoing operations, maintenance, and trouble shooting of the hardware and systems software at massive scale is required.

  19. Cloud Robotics Platforms

    Directory of Open Access Journals (Sweden)

    Busra Koken


    Full Text Available Cloud robotics is a rapidly evolving field that allows robots to offload computation-intensive and storage-intensive jobs into the cloud. Robots are limited in terms of computational capacity, memory and storage. Cloud provides unlimited computation power, memory, storage and especially collaboration opportunity. Cloud-enabled robots are divided into two categories as standalone and networked robots. This article surveys cloud robotic platforms, standalone and networked robotic works such as grasping, simultaneous localization and mapping (SLAM and monitoring.

  20. Recent developments in circulating biomarkers in Parkinson's disease: the potential use of miRNAs in a clinical setting. (United States)

    Teixeira Dos Santos, Marcia Cristina; Bell, Rosie; da Costa, Andre Nogueira


    Parkinson's disease (PD) is the second most common neurodegenerative disorder, affecting 5% of the elderly population. PD diagnosis is still based on the identification of neuromotor symptoms although nonmotor manifestations emerge years prior to diagnosis. The discovery of biomarkers at the earliest stages of PD is of extreme interest. miRNAs have been considered potential biomarkers for neurodegenerative diseases, but only a limited number have been found to be PD related. This review focuses on the current findings in the field of circulating miRNAs in PD and the challenges surrounding clinical utility and validation. We briefly describe the more established circulating biomarkers in PD and provide a more thorough review of miRNAs differentially expressed in PD. We highlight their potential for being considered as biomarkers for diagnosis while emphasizing the challenges for adequate validation of the findings and how miRNAs can be envisioned in a clinical setting satisfying regulatory bodies.