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Sample records for biomarker discovery work

  1. Glycoscience aids in biomarker discovery

    Directory of Open Access Journals (Sweden)

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

    2012-06-01

    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.

  2. Proteomic and metabolomic approaches to biomarker discovery

    CERN Document Server

    Issaq, Haleem J

    2013-01-01

    Proteomic and Metabolomic Approaches to Biomarker Discovery demonstrates how to leverage biomarkers to improve accuracy and reduce errors in research. Disease biomarker discovery is one of the most vibrant and important areas of research today, as the identification of reliable biomarkers has an enormous impact on disease diagnosis, selection of treatment regimens, and therapeutic monitoring. Various techniques are used in the biomarker discovery process, including techniques used in proteomics, the study of the proteins that make up an organism, and metabolomics, the study of chemical fingerprints created from cellular processes. Proteomic and Metabolomic Approaches to Biomarker Discovery is the only publication that covers techniques from both proteomics and metabolomics and includes all steps involved in biomarker discovery, from study design to study execution.  The book describes methods, and presents a standard operating procedure for sample selection, preparation, and storage, as well as data analysis...

  3. Systems biology and biomarker discovery

    Energy Technology Data Exchange (ETDEWEB)

    Rodland, Karin D.

    2010-12-01

    Medical practitioners have always relied on surrogate markers of inaccessible biological processes to make their diagnosis, whether it was the pallor of shock, the flush of inflammation, or the jaundice of liver failure. Obviously, the current implementation of biomarkers for disease is far more sophisticated, relying on highly reproducible, quantitative measurements of molecules that are often mechanistically associated with the disease in question, as in glycated hemoglobin for the diagnosis of diabetes [1] or the presence of cardiac troponins in the blood for confirmation of myocardial infarcts [2]. In cancer, where the initial symptoms are often subtle and the consequences of delayed diagnosis often drastic for disease management, the impetus to discover readily accessible, reliable, and accurate biomarkers for early detection is compelling. Yet despite years of intense activity, the stable of clinically validated, cost-effective biomarkers for early detection of cancer is pathetically small and still dominated by a handful of markers (CA-125, CEA, PSA) first discovered decades ago. It is time, one could argue, for a fresh approach to the discovery and validation of disease biomarkers, one that takes full advantage of the revolution in genomic technologies and in the development of computational tools for the analysis of large complex datasets. This issue of Disease Markers is dedicated to one such new approach, loosely termed the 'Systems Biology of Biomarkers'. What sets the Systems Biology approach apart from other, more traditional approaches, is both the types of data used, and the tools used for data analysis - and both reflect the revolution in high throughput analytical methods and high throughput computing that has characterized the start of the twenty first century.

  4. Biomarkers: in medicine, drug discovery, and environmental health

    National Research Council Canada - National Science Library

    Vaidya, Vishal S; Bonventre, Joseph V

    2010-01-01

    ... Identification Using Mass Spectrometry Sample Preparation Protein Quantitation Examples of Biomarker Discovery and Evaluation Challenges in Proteomic Biomarker Discovery The Road Forward: Targeted ...

  5. Shotgun Proteomics and Biomarker Discovery

    Directory of Open Access Journals (Sweden)

    W. Hayes McDonald

    2002-01-01

    Full Text Available Coupling large-scale sequencing projects with the amino acid sequence information that can be gleaned from tandem mass spectrometry (MS/MS has made it much easier to analyze complex mixtures of proteins. The limits of this “shotgun” approach, in which the protein mixture is proteolytically digested before separation, can be further expanded by separating the resulting mixture of peptides prior to MS/MS analysis. Both single dimensional high pressure liquid chromatography (LC and multidimensional LC (LC/LC can be directly interfaced with the mass spectrometer to allow for automated collection of tremendous quantities of data. While there is no single technique that addresses all proteomic challenges, the shotgun approaches, especially LC/LC-MS/MS-based techniques such as MudPIT (multidimensional protein identification technology, show advantages over gel-based techniques in speed, sensitivity, scope of analysis, and dynamic range. Advances in the ability to quantitate differences between samples and to detect for an array of post-translational modifications allow for the discovery of classes of protein biomarkers that were previously unassailable.

  6. Mass Spectrometry-Based Biomarker Discovery.

    Science.gov (United States)

    Zhou, Weidong; Petricoin, Emanuel F; Longo, Caterina

    2017-01-01

    The discovery of candidate biomarkers within the entire proteome is one of the most important and challenging goals in proteomic research. Mass spectrometry-based proteomics is a modern and promising technology for semiquantitative and qualitative assessment of proteins, enabling protein sequencing and identification with exquisite accuracy and sensitivity. For mass spectrometry analysis, protein extractions from tissues or body fluids and subsequent protein fractionation represent an important and unavoidable step in the workflow for biomarker discovery. Following extraction of proteins, the protein mixture must be digested, reduced, alkylated, and cleaned up prior to mass spectrometry. The aim of our chapter is to provide comprehensible and practical lab procedures for sample digestion, protein fractionation, and subsequent mass spectrometry analysis.

  7. Using Aptamers for Cancer Biomarker Discovery

    Directory of Open Access Journals (Sweden)

    Yun Min Chang

    2013-01-01

    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.

  8. Novel ageing-biomarker discovery using data-intensive technologies.

    Science.gov (United States)

    Griffiths, H R; Augustyniak, E M; Bennett, S J; Debacq-Chainiaux, F; Dunston, C R; Kristensen, P; Melchjorsen, C J; Navarrete, Santos A; Simm, A; Toussaint, O

    2015-11-01

    Ageing is accompanied by many visible characteristics. Other biological and physiological markers are also well-described e.g. loss of circulating sex hormones and increased inflammatory cytokines. Biomarkers for healthy ageing studies are presently predicated on existing knowledge of ageing traits. The increasing availability of data-intensive methods enables deep-analysis of biological samples for novel biomarkers. We have adopted two discrete approaches in MARK-AGE Work Package 7 for biomarker discovery; (1) microarray analyses and/or proteomics in cell systems e.g. endothelial progenitor cells or T cell ageing including a stress model; and (2) investigation of cellular material and plasma directly from tightly-defined proband subsets of different ages using proteomic, transcriptomic and miR array. The first approach provided longitudinal insight into endothelial progenitor and T cell ageing. This review describes the strategy and use of hypothesis-free, data-intensive approaches to explore cellular proteins, miR, mRNA and plasma proteins as healthy ageing biomarkers, using ageing models and directly within samples from adults of different ages. It considers the challenges associated with integrating multiple models and pilot studies as rational biomarkers for a large cohort study. From this approach, a number of high-throughput methods were developed to evaluate novel, putative biomarkers of ageing in the MARK-AGE cohort. Crown Copyright © 2015. Published by Elsevier Ireland Ltd. All rights reserved.

  9. Cancer Biomarker Discovery: Lectin-Based Strategies Targeting Glycoproteins

    Directory of Open Access Journals (Sweden)

    David Clark

    2012-01-01

    Full Text Available Biomarker discovery can identify molecular markers in various cancers that can be used for detection, screening, diagnosis, and monitoring of disease progression. Lectin-affinity is a technique that can be used for the enrichment of glycoproteins from a complex sample, facilitating the discovery of novel cancer biomarkers associated with a disease state.

  10. Biomarker Gene Signature Discovery Integrating Network Knowledge

    Directory of Open Access Journals (Sweden)

    Holger Fröhlich

    2012-02-01

    Full Text Available Discovery of prognostic and diagnostic biomarker gene signatures for diseases, such as cancer, is seen as a major step towards a better personalized medicine. During the last decade various methods, mainly coming from the machine learning or statistical domain, have been proposed for that purpose. However, one important obstacle for making gene signatures a standard tool in clinical diagnosis is the typical low reproducibility of these signatures combined with the difficulty to achieve a clear biological interpretation. For that purpose in the last years there has been a growing interest in approaches that try to integrate information from molecular interaction networks. Here we review the current state of research in this field by giving an overview about so-far proposed approaches.

  11. Emerging Concepts and Methodologies in Cancer Biomarker Discovery.

    Science.gov (United States)

    Lu, Meixia; Zhang, Jinxiang; Zhang, Lanjing

    2017-01-01

    Cancer biomarker discovery is a critical part of cancer prevention and treatment. Despite the decades of effort, only a small number of cancer biomarkers have been identified for and validated in clinical settings. Conceptual and methodological breakthroughs may help accelerate the discovery of additional cancer biomarkers, particularly their use for diagnostics. In this review, we have attempted to review the emerging concepts in cancer biomarker discovery, including real-world evidence, open access data, and data paucity in rare or uncommon cancers. We have also summarized the recent methodological progress in cancer biomarker discovery, such as high-throughput sequencing, liquid biopsy, big data, artificial intelligence (AI), and deep learning and neural networks. Much attention has been given to the methodological details and comparison of the methodologies. Notably, these concepts and methodologies interact with each other and will likely lead to synergistic effects when carefully combined. Newer, more innovative concepts and methodologies are emerging as the current emerging ones became mainstream and widely applied to the field. Some future challenges are also discussed. This review contributes to the development of future theoretical frameworks and technologies in cancer biomarker discovery and will contribute to the discovery of more useful cancer biomarkers.

  12. Biomarker discovery in high grade sarcomas by mass spectrometry imaging

    OpenAIRE

    Lou, S.

    2017-01-01

    This thesis demonstrates a detailed biomarker discovery Mass Spectrometry Imaging workflow for histologically heterogeneous high grade sarcomas. Panels of protein and metabolite signatures were discovered either distinguishing different histological subtypes or stratifying high risk patients with poor survival.

  13. The path from biomarker discovery to regulatory qualification

    CERN Document Server

    Goodsaid, Federico

    2013-01-01

    The Path from Biomarker Discovery to Regulatory Qualification is a unique guide that focuses on biomarker qualification, its history and current regulatory settings in both the US and abroad. This multi-contributed book provides a detailed look at the next step to developing biomarkers for clinical use and covers overall concepts, challenges, strategies and solutions based on the experiences of regulatory authorities and scientists. Members of the regulatory, pharmaceutical and biomarker development communities will benefit the most from using this book-it is a complete and practical guide to biomarker qualification, providing valuable insight to an ever-evolving and important area of regulatory science. For complimentary access to chapter 13, 'Classic' Biomarkers of Liver Injury, by John R. Senior, Associate Director for Science, Food and Drug Administration, Silver Spring, Maryland, USA, please visit the following site:  http://tinyurl.com/ClassicBiomarkers Contains a collection of experiences of different...

  14. Cellular Models for Environmental Toxicant Biomarker Discovery

    National Research Council Canada - National Science Library

    Halverson, Kelly M; Lewsis, John A; Jackson, David A; Dennis, William; Brennan, Linda; Krakaner, Teresa

    2006-01-01

    ...) is the development of biomarkers of exposure, effect, and susceptibility. As exposure monitoring using environmental sampling equipment can be impractical and doesn't account for differences in individual responses, new methodologies must be sought...

  15. Implementation of proteomic biomarkers: making it work.

    Science.gov (United States)

    Mischak, Harald; Ioannidis, John P A; 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

    2012-09-01

    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. © 2012 The Authors. European Journal of Clinical Investigation © 2012 Stichting European Society for Clinical Investigation Journal Foundation.

  16. Implementation of proteomic biomarkers: making it work

    Science.gov (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

    2012-01-01

    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

  17. Mass spectrometry for protein quantification in biomarker discovery.

    Science.gov (United States)

    Wang, Mu; You, Jinsam

    2012-01-01

    Major technological advances have made proteomics an extremely active field for biomarker discovery in recent years due primarily to the development of newer mass spectrometric technologies and the explosion in genomic and protein bioinformatics. This leads to an increased emphasis on larger scale, faster, and more efficient methods for detecting protein biomarkers in human tissues, cells, and biofluids. Most current proteomic methodologies for biomarker discovery, however, are not highly automated and are generally labor-intensive and expensive. More automation and improved software programs capable of handling a large amount of data are essential to reduce the cost of discovery and to increase throughput. In this chapter, we discuss and describe mass spectrometry-based proteomic methods for quantitative protein analysis.

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

    CERN Document Server

    Azuaje, Francisco

    2010-01-01

    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

  19. Mass spectrometry imaging enriches biomarker discovery approaches with candidate mapping.

    Science.gov (United States)

    Scott, Alison J; Jones, Jace W; Orschell, Christie M; MacVittie, Thomas J; Kane, Maureen A; Ernst, Robert K

    2014-01-01

    Integral to the characterization of radiation-induced tissue damage is the identification of unique biomarkers. Biomarker discovery is a challenging and complex endeavor requiring both sophisticated experimental design and accessible technology. The resources within the National Institute of Allergy and Infectious Diseases (NIAID)-sponsored Consortium, Medical Countermeasures Against Radiological Threats (MCART), allow for leveraging robust animal models with novel molecular imaging techniques. One such imaging technique, MALDI (matrix-assisted laser desorption ionization) mass spectrometry imaging (MSI), allows for the direct spatial visualization of lipids, proteins, small molecules, and drugs/drug metabolites-or biomarkers-in an unbiased manner. MALDI-MSI acquires mass spectra directly from an intact tissue slice in discrete locations across an x, y grid that are then rendered into a spatial distribution map composed of ion mass and intensity. The unique mass signals can be plotted to generate a spatial map of biomarkers that reflects pathology and molecular events. The crucial unanswered questions that can be addressed with MALDI-MSI include identification of biomarkers for radiation damage that reflect the response to radiation dose over time and the efficacy of therapeutic interventions. Techniques in MALDI-MSI also enable integration of biomarker identification among diverse animal models. Analysis of early, sublethally irradiated tissue injury samples from diverse mouse tissues (lung and ileum) shows membrane phospholipid signatures correlated with histological features of these unique tissues. This paper will discuss the application of MALDI-MSI for use in a larger biomarker discovery pipeline.

  20. Multi-dimensional discovery of biomarker and phenotype complexes

    Directory of Open Access Journals (Sweden)

    Huang Kun

    2010-10-01

    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.

  1. Secreted proteins as a fundamental source for biomarker discovery

    Czech Academy of Sciences Publication Activity Database

    Šťastná, Miroslava; Van Eyk, J.E.

    2012-01-01

    Roč. 12, 4-5 (2012), s. 722-735 ISSN 1615-9853 Institutional research plan: CEZ:AV0Z40310501 Keywords : conditioned media * secreted proteins * proteomics * biomarker discovery Subject RIV: CB - Analytical Chemistry, Separation Impact factor: 4.132, year: 2012

  2. Proteomic Approaches in Biomarker Discovery: New Perspectives in Cancer Diagnostics

    Science.gov (United States)

    Kocevar, Nina; Komel, Radovan

    2014-01-01

    Despite remarkable progress in proteomic methods, including improved detection limits and sensitivity, these methods have not yet been established in routine clinical practice. The main limitations, which prevent their integration into clinics, are high cost of equipment, the need for highly trained personnel, and last, but not least, the establishment of reliable and accurate protein biomarkers or panels of protein biomarkers for detection of neoplasms. Furthermore, the complexity and heterogeneity of most solid tumours present obstacles in the discovery of specific protein signatures, which could be used for early detection of cancers, for prediction of disease outcome, and for determining the response to specific therapies. However, cancer proteome, as the end-point of pathological processes that underlie cancer development and progression, could represent an important source for the discovery of new biomarkers and molecular targets for tailored therapies. PMID:24550697

  3. Exhaled Breath Condensate for Proteomic Biomarker Discovery

    Directory of Open Access Journals (Sweden)

    Sean W. Harshman

    2014-07-01

    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.

  4. Towards Discovery and Targeted Peptide Biomarker Detection Using nanoESI-TIMS-TOF MS

    Energy Technology Data Exchange (ETDEWEB)

    Garabedian, Alyssa; Benigni, Paolo; Ramirez, Cesar; Baker, Erin M.; Liu, Tao; Smith, Richard D.; Fernandez-Lima, Francisco

    2018-05-01

    Abstract. In the present work, the potential of trapped ion mobility spectrometry coupled to TOF mass spectrometry (TIMS-TOF MS) for discovery and targeted monitoring of peptide biomarkers from human-in-mouse xenograft tumor tissue was evaluated. In particular, a TIMS-MS workflow was developed for the detection and quantification of peptide biomarkers using internal heavy analogs, taking advantage of the high mobility resolution (R = 150–250) prior to mass analysis. Five peptide biomarkers were separated, identified, and quantified using offline nanoESI-TIMSCID- TOF MS; the results were in good agreement with measurements using a traditional LC-ESI-MS/MS proteomics workflow. The TIMS-TOF MS analysis permitted peptide biomarker detection based on accurate mobility, mass measurements, and high sequence coverage for concentrations in the 10–200 nM range, while simultaneously achieving discovery measurements

  5. Cancer biomarker discovery: the entropic hallmark.

    Science.gov (United States)

    Berretta, Regina; Moscato, Pablo

    2010-08-18

    It is a commonly accepted belief that cancer cells modify their transcriptional state during the progression of the disease. We propose that the progression of cancer cells towards malignant phenotypes can be efficiently tracked using high-throughput technologies that follow the gradual changes observed in the gene expression profiles by employing Shannon's mathematical theory of communication. Methods based on Information Theory can then quantify the divergence of cancer cells' transcriptional profiles from those of normally appearing cells of the originating tissues. The relevance of the proposed methods can be evaluated using microarray datasets available in the public domain but the method is in principle applicable to other high-throughput methods. Using melanoma and prostate cancer datasets we illustrate how it is possible to employ Shannon Entropy and the Jensen-Shannon divergence to trace the transcriptional changes progression of the disease. We establish how the variations of these two measures correlate with established biomarkers of cancer progression. The Information Theory measures allow us to identify novel biomarkers for both progressive and relatively more sudden transcriptional changes leading to malignant phenotypes. At the same time, the methodology was able to validate a large number of genes and processes that seem to be implicated in the progression of melanoma and prostate cancer. We thus present a quantitative guiding rule, a new unifying hallmark of cancer: the cancer cell's transcriptome changes lead to measurable observed transitions of Normalized Shannon Entropy values (as measured by high-throughput technologies). At the same time, tumor cells increment their divergence from the normal tissue profile increasing their disorder via creation of states that we might not directly measure. This unifying hallmark allows, via the the Jensen-Shannon divergence, to identify the arrow of time of the processes from the gene expression profiles

  6. Biomarker discovery in mass spectrometry-based urinary proteomics.

    Science.gov (United States)

    Thomas, Samuel; Hao, Ling; Ricke, William A; Li, Lingjun

    2016-04-01

    Urinary proteomics has become one of the most attractive topics in disease biomarker discovery. MS-based proteomic analysis has advanced continuously and emerged as a prominent tool in the field of clinical bioanalysis. However, only few protein biomarkers have made their way to validation and clinical practice. Biomarker discovery is challenged by many clinical and analytical factors including, but not limited to, the complexity of urine and the wide dynamic range of endogenous proteins in the sample. This article highlights promising technologies and strategies in the MS-based biomarker discovery process, including study design, sample preparation, protein quantification, instrumental platforms, and bioinformatics. Different proteomics approaches are discussed, and progresses in maximizing urinary proteome coverage and standardization are emphasized in this review. MS-based urinary proteomics has great potential in the development of noninvasive diagnostic assays in the future, which will require collaborative efforts between analytical scientists, systems biologists, and clinicians. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  7. PROFILEing idiopathic pulmonary fibrosis: rethinking biomarker discovery

    Directory of Open Access Journals (Sweden)

    Toby M. Maher

    2013-06-01

    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.

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

    International Nuclear Information System (INIS)

    Even-Desrumeaux, Klervi; Baty, Daniel; Chames, Patrick

    2011-01-01

    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

  9. Maximizing biomarker discovery by minimizing gene signatures

    Directory of Open Access Journals (Sweden)

    Chang Chang

    2011-12-01

    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

  10. Computational and Experimental Approaches to Cancer Biomarker Discovery

    DEFF Research Database (Denmark)

    Krzystanek, Marcin

    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...... and the state or level of a large number of molecular entities is investigated. Such associative analysis could be confounded by several factors, leading to false discoveries. For example, it is assumed that with the exception of the true biomarkers most molecular entities such as gene expression levels show...... random distribution in a given cohort. However, gene expression levels may also be affected by technical bias when the actual measurement technology or sample handling may introduce a systematic error. If the distribution of systematic errors correlates with the biological phenotype then the risk...

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

    Science.gov (United States)

    Gold, Larry; Ayers, Deborah; Bertino, Jennifer; Bock, Christopher; Bock, Ashley; Brody, Edward N; Carter, Jeff; Dalby, Andrew B; Eaton, Bruce E; Fitzwater, Tim; Flather, Dylan; Forbes, Ashley; Foreman, Trudi; Fowler, Cate; Gawande, Bharat; Goss, Meredith; Gunn, Magda; Gupta, Shashi; Halladay, Dennis; Heil, Jim; Heilig, Joe; Hicke, Brian; Husar, Gregory; Janjic, Nebojsa; Jarvis, Thale; Jennings, Susan; Katilius, Evaldas; Keeney, Tracy R; Kim, Nancy; Koch, Tad H; Kraemer, Stephan; Kroiss, Luke; Le, Ngan; Levine, Daniel; Lindsey, Wes; Lollo, Bridget; Mayfield, Wes; Mehan, Mike; Mehler, Robert; Nelson, Sally K; Nelson, Michele; Nieuwlandt, Dan; Nikrad, Malti; Ochsner, Urs; Ostroff, Rachel M; Otis, Matt; Parker, Thomas; Pietrasiewicz, Steve; Resnicow, Daniel I; Rohloff, John; Sanders, Glenn; Sattin, Sarah; Schneider, Daniel; Singer, Britta; Stanton, Martin; Sterkel, Alana; Stewart, Alex; Stratford, Suzanne; Vaught, Jonathan D; Vrkljan, Mike; Walker, Jeffrey J; Watrobka, Mike; Waugh, Sheela; Weiss, Allison; Wilcox, Sheri K; Wolfson, Alexey; Wolk, Steven K; Zhang, Chi; Zichi, Dom

    2010-12-07

    The interrogation of proteomes ("proteomics") in a highly multiplexed and efficient manner remains a coveted and challenging goal in biology and medicine. 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. 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 generation of evidence-based medicine.

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

    Directory of Open Access Journals (Sweden)

    Larry Gold

    2010-12-01

    Full Text Available The interrogation of proteomes ("proteomics" in a highly multiplexed and efficient manner remains a coveted and challenging goal in biology and medicine.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.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 generation of evidence-based medicine.

  13. Metabolomics for Biomarker Discovery: Moving to the Clinic

    Science.gov (United States)

    Zhang, Aihua; Sun, Hui; Yan, Guangli; Wang, Ping; Wang, Xijun

    2015-01-01

    To improve the clinical course of diseases, more accurate diagnostic and assessment methods are required as early as possible. In order to achieve this, metabolomics offers new opportunities for biomarker discovery in complex diseases and may provide pathological understanding of diseases beyond traditional technologies. It is the systematic analysis of low-molecular-weight metabolites in biological samples and has become an important tool in clinical research and the diagnosis of human disease and has been applied to discovery and identification of the perturbed pathways. It provides a powerful approach to discover biomarkers in biological systems and offers a holistic approach with the promise to clinically enhance diagnostics. When carried out properly, it could provide insight into the understanding of the underlying mechanisms of diseases, help to identify patients at risk of disease, and predict the response to specific treatments. Currently, metabolomics has become an important tool in clinical research and the diagnosis of human disease and becomes a hot topic. This review will highlight the importance and benefit of metabolomics for identifying biomarkers that accurately screen potential biomarkers of diseases. PMID:26090402

  14. Biomarkers as drug development tools: discovery, validation, qualification and use.

    Science.gov (United States)

    Kraus, Virginia B

    2018-06-01

    The 21st Century Cures Act, approved in the USA in December 2016, has encouraged the establishment of the national Precision Medicine Initiative and the augmentation of efforts to address disease prevention, diagnosis and treatment on the basis of a molecular understanding of disease. The Act adopts into law the formal process, developed by the FDA, of qualification of drug development tools, including biomarkers and clinical outcome assessments, to increase the efficiency of clinical trials and encourage an era of molecular medicine. The FDA and European Medicines Agency (EMA) have developed similar processes for the qualification of biomarkers intended for use as companion diagnostics or for development and regulatory approval of a drug or therapeutic. Biomarkers that are used exclusively for the diagnosis, monitoring or stratification of patients in clinical trials are not subject to regulatory approval, although their qualification can facilitate the conduct of a trial. In this Review, the salient features of biomarker discovery, analytical validation, clinical qualification and utilization are described in order to provide an understanding of the process of biomarker development and, through this understanding, convey an appreciation of their potential advantages and limitations.

  15. Novel ageing-biomarker discovery using data-intensive technologies

    OpenAIRE

    Griffiths, H.R.; Augustyniak, E.M.; Bennett, S.J.; Debacq-Chainiaux, F.; Dunston, C.R.; Kristensen, P.; Melchjorsen, C.J.; Navarrete, Santos A.; Simm, A.; Toussaint, O.

    2015-01-01

    Ageing is accompanied by many visible characteristics. Other biological and physiological markers are also well-described e.g. loss of circulating sex hormones and increased inflammatory cytokines. Biomarkers for healthy ageing studies are presently predicated on existing knowledge of ageing traits. The increasing availability of data-intensive methods enables deep-analysis of biological samples for novel biomarkers. We have adopted two discrete approaches in MARK-AGE Work Package 7 for bioma...

  16. Proteomics for discovery of candidate colorectal cancer biomarkers

    Science.gov (United States)

    Álvarez-Chaver, Paula; Otero-Estévez, Olalla; Páez de la Cadena, María; Rodríguez-Berrocal, Francisco J; Martínez-Zorzano, Vicenta S

    2014-01-01

    Colorectal cancer (CRC) is the second most common cause of cancer-related deaths in Europe and other Western countries, mainly due to the lack of well-validated clinically useful biomarkers with enough sensitivity and specificity to detect this disease at early stages. Although it is well known that the pathogenesis of CRC is a progressive accumulation of mutations in multiple genes, much less is known at the proteome level. Therefore, in the last years many proteomic studies have been conducted to find new candidate protein biomarkers for diagnosis, prognosis and as therapeutic targets for this malignancy, as well as to elucidate the molecular mechanisms of colorectal carcinogenesis. An important advantage of the proteomic approaches is the capacity to look for multiple differentially expressed proteins in a single study. This review provides an overview of the recent reports describing the different proteomic tools used for the discovery of new protein markers for CRC such as two-dimensional electrophoresis methods, quantitative mass spectrometry-based techniques or protein microarrays. Additionally, we will also focus on the diverse biological samples used for CRC biomarker discovery such as tissue, serum and faeces, besides cell lines and murine models, discussing their advantages and disadvantages, and summarize the most frequently identified candidate CRC markers. PMID:24744574

  17. Role of proteomics in the discovery of autism biomarkers

    Energy Technology Data Exchange (ETDEWEB)

    Ayadhi, L. A.; Halepoto, D. M. [King Saud Univ., Riyadh (Saudi Arabia). Dept. of Physiology

    2013-02-15

    The epidemiology of autism is continuously increasing all over the world with social, behavioural and economical burdens. Autism is considered as a multi-factorial disorder, influenced by genetic, neurological, environmental and immunological aspects. Autism is still believed to be incurable disorder with little information about the role of proteins patterns in the diagnosis of the disease. Knowing the applications of proteomic tools, it is possible to identify quantitative and qualitative protein patterns in a wide variety of tissues and body fluids such as blood, urine, saliva and cerebrospinal fluid in order to establish specific diagnostic and prognostic biomarkers. The aim of this review is to provide an overview of the various protocols available for proteomics by using mass spectrometry analysis, discuss reports in which these techniques have been previously applied in biomarker discovery for the diagnosis of autism, and consider the future development of this area of research. (author)

  18. Role of proteomics in the discovery of autism biomarkers

    International Nuclear Information System (INIS)

    Ayadhi, L.A.; Halepoto, D.M.

    2013-01-01

    The epidemiology of autism is continuously increasing all over the world with social, behavioural and economical burdens. Autism is considered as a multi-factorial disorder, influenced by genetic, neurological, environmental and immunological aspects. Autism is still believed to be incurable disorder with little information about the role of proteins patterns in the diagnosis of the disease. Knowing the applications of proteomic tools, it is possible to identify quantitative and qualitative protein patterns in a wide variety of tissues and body fluids such as blood, urine, saliva and cerebrospinal fluid in order to establish specific diagnostic and prognostic biomarkers. The aim of this review is to provide an overview of the various protocols available for proteomics by using mass spectrometry analysis, discuss reports in which these techniques have been previously applied in biomarker discovery for the diagnosis of autism, and consider the future development of this area of research. (author)

  19. Random glycopeptide bead libraries for seromic biomarker discovery

    DEFF Research Database (Denmark)

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

    2010-01-01

    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...... to other tumor glycoforms by on-bead enzymatic glycosylation reactions with recombinant glycosyltransferases. Hence, we have developed a high-throughput flexible platform for rapid discovery of O-glycopeptide biomarkers and the method has applicability in other types of assays such as lectin...

  20. Metabolomics in cancer biomarker discovery: current trends and future perspectives.

    Science.gov (United States)

    Armitage, Emily G; Barbas, Coral

    2014-01-01

    Cancer is one of the most devastating human diseases that causes a vast number of mortalities worldwide each year. Cancer research is one of the largest fields in the life sciences and despite many astounding breakthroughs and contributions over the past few decades, there is still a considerable amount to unveil on the function of cancer. It is well known that cancer metabolism differs from that of normal tissue and an important hypothesis published in the 1950s by Otto Warburg proposed that cancer cells rely on anaerobic metabolism as the source for energy, even under physiological oxygen levels. Following this, cancer central carbon metabolism has been researched extensively and beyond respiration, cancer has been found to involve a wide range of metabolic processes, and many more are still to be unveiled. Studying cancer through metabolomics could reveal new biomarkers for cancer that could be useful for its future prognosis, diagnosis and therapy. Metabolomics is becoming an increasingly popular tool in the life sciences since it is a relatively fast and accurate technique that can be applied with either a particular focus or in a global manner to reveal new knowledge about biological systems. There have been many examples of its application to reveal potential biomarkers in different cancers that have employed a range of different analytical platforms. In this review, approaches in metabolomics that have been employed in cancer biomarker discovery are discussed and some of the most noteworthy research in the field is highlighted. Copyright © 2013 Elsevier B.V. All rights reserved.

  1. Towards Discovery and Targeted Peptide Biomarker Detection Using nanoESI-TIMS-TOF MS

    Science.gov (United States)

    Garabedian, Alyssa; Benigni, Paolo; Ramirez, Cesar E.; Baker, Erin S.; Liu, Tao; Smith, Richard D.; Fernandez-Lima, Francisco

    2017-09-01

    In the present work, the potential of trapped ion mobility spectrometry coupled to TOF mass spectrometry (TIMS-TOF MS) for discovery and targeted monitoring of peptide biomarkers from human-in-mouse xenograft tumor tissue was evaluated. In particular, a TIMS-MS workflow was developed for the detection and quantification of peptide biomarkers using internal heavy analogs, taking advantage of the high mobility resolution (R = 150-250) prior to mass analysis. Five peptide biomarkers were separated, identified, and quantified using offline nanoESI-TIMS-CID-TOF MS; the results were in good agreement with measurements using a traditional LC-ESI-MS/MS proteomics workflow. The TIMS-TOF MS analysis permitted peptide biomarker detection based on accurate mobility, mass measurements, and high sequence coverage for concentrations in the 10-200 nM range, while simultaneously achieving discovery measurements of not initially targeted peptides as markers from the same proteins and, eventually, other proteins. [Figure not available: see fulltext.

  2. Mass Spectrometry–Based Biomarker Discovery: Toward a Global Proteome Index of Individuality

    Science.gov (United States)

    Hawkridge, Adam M.; Muddiman, David C.

    2011-01-01

    Biomarker discovery and proteomics have become synonymous with mass spectrometry in recent years. Although this conflation is an injustice to the many essential biomolecular techniques widely used in biomarker-discovery platforms, it underscores the power and potential of contemporary mass spectrometry. Numerous novel and powerful technologies have been developed around mass spectrometry, proteomics, and biomarker discovery over the past 20 years to globally study complex proteomes (e.g., plasma). However, very few large-scale longitudinal studies have been carried out using these platforms to establish the analytical variability relative to true biological variability. The purpose of this review is not to cover exhaustively the applications of mass spectrometry to biomarker discovery, but rather to discuss the analytical methods and strategies that have been developed for mass spectrometry–based biomarker-discovery platforms and to place them in the context of the many challenges and opportunities yet to be addressed. PMID:20636062

  3. The application of mass-spectrometry-based protein biomarker discovery to theragnostics

    OpenAIRE

    Street, Jonathan M; Dear, James W

    2010-01-01

    Over the last decade rapid developments in mass spectrometry have allowed the identification of multiple proteins in complex biological samples. This proteomic approach has been applied to biomarker discovery in the context of clinical pharmacology (the combination of biomarker and drug now being termed ‘theragnostics’). In this review we provide a roadmap for early protein biomarker discovery studies, focusing on some key questions that regularly confront researchers.

  4. Mass spectrometric based approaches in urine metabolomics and biomarker discovery.

    Science.gov (United States)

    Khamis, Mona M; Adamko, Darryl J; El-Aneed, Anas

    2017-03-01

    Urine metabolomics has recently emerged as a prominent field for the discovery of non-invasive biomarkers that can detect subtle metabolic discrepancies in response to a specific disease or therapeutic intervention. Urine, compared to other biofluids, is characterized by its ease of collection, richness in metabolites and its ability to reflect imbalances of all biochemical pathways within the body. Following urine collection for metabolomic analysis, samples must be immediately frozen to quench any biogenic and/or non-biogenic chemical reactions. According to the aim of the experiment; sample preparation can vary from simple procedures such as filtration to more specific extraction protocols such as liquid-liquid extraction. Due to the lack of comprehensive studies on urine metabolome stability, higher storage temperatures (i.e. 4°C) and repetitive freeze-thaw cycles should be avoided. To date, among all analytical techniques, mass spectrometry (MS) provides the best sensitivity, selectivity and identification capabilities to analyze the majority of the metabolite composition in the urine. Combined with the qualitative and quantitative capabilities of MS, and due to the continuous improvements in its related technologies (i.e. ultra high-performance liquid chromatography [UPLC] and hydrophilic interaction liquid chromatography [HILIC]), liquid chromatography (LC)-MS is unequivocally the most utilized and the most informative analytical tool employed in urine metabolomics. Furthermore, differential isotope tagging techniques has provided a solution to ion suppression from urine matrix thus allowing for quantitative analysis. In addition to LC-MS, other MS-based technologies have been utilized in urine metabolomics. These include direct injection (infusion)-MS, capillary electrophoresis-MS and gas chromatography-MS. In this article, the current progresses of different MS-based techniques in exploring the urine metabolome as well as the recent findings in providing

  5. Crowdsourcing Disease Biomarker Discovery Research: The IP4IC Study.

    Science.gov (United States)

    Chancellor, Michael B; Bartolone, Sarah N; Veerecke, Andrew; Lamb, Laura E

    2018-05-01

    Biomarker discovery is limited by readily assessable, cost efficient human samples available in large numbers that represent the entire heterogeneity of the disease. We developed a novel, active participation crowdsourcing method to determine BP-RS (Bladder Permeability Defect Risk Score). It is based on noninvasive urinary cytokines to discriminate patients with interstitial cystitis/bladder pain syndrome who had Hunner lesions from controls and patients with interstitial cystitis/bladder pain syndrome but without Hunner lesions. We performed a national crowdsourcing study in cooperation with the Interstitial Cystitis Association. Patients answered demographic, symptom severity and urinary frequency questionnaires on a HIPAA (Health Insurance Portability and Accountability Act) compliant website. Urine samples were collected at home, stabilized with a preservative and sent to Beaumont Hospital for analysis. The expression of 3 urinary cytokines was used in a machine learning algorithm to develop BP-RS. The IP4IC study collected a total of 448 urine samples, representing 153 patients (147 females and 6 males) with interstitial cystitis/bladder pain syndrome, of whom 54 (50 females and 4 males) had Hunner lesions. A total of 159 female and 136 male controls also participated, who were age matched. A defined BP-RS was calculated to predict interstitial cystitis/bladder pain syndrome with Hunner lesions or a bladder permeability defect etiology with 89% validity. In this novel participation crowdsourcing study we obtained a large number of urine samples from 46 states, which were collected at home, shipped and stored at room temperature. Using a machine learning algorithm we developed BP-RS to quantify the risk of interstitial cystitis/bladder pain syndrome with Hunner lesions, which is indicative of a bladder permeability defect etiology. To our knowledge BP-RS is the first validated urine biomarker assay for interstitial cystitis/bladder pain syndrome and one of the

  6. Disease Classification and Biomarker Discovery Using ECG Data

    Directory of Open Access Journals (Sweden)

    Rong Huang

    2015-01-01

    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.

  7. Improving the quality of biomarker discovery research: the right samples and enough of them.

    Science.gov (United States)

    Pepe, Margaret S; Li, Christopher I; Feng, Ziding

    2015-06-01

    Biomarker discovery research has yielded few biomarkers that validate for clinical use. A contributing factor may be poor study designs. The goal in discovery research is to identify a subset of potentially useful markers from a large set of candidates assayed on case and control samples. We recommend the PRoBE design for selecting samples. We propose sample size calculations that require specifying: (i) a definition for biomarker performance; (ii) the proportion of useful markers the study should identify (Discovery Power); and (iii) the tolerable number of useless markers amongst those identified (False Leads Expected, FLE). We apply the methodology to a study of 9,000 candidate biomarkers for risk of colon cancer recurrence where a useful biomarker has positive predictive value ≥ 30%. We find that 40 patients with recurrence and 160 without recurrence suffice to filter out 98% of useless markers (2% FLE) while identifying 95% of useful biomarkers (95% Discovery Power). Alternative methods for sample size calculation required more assumptions. Biomarker discovery research should utilize quality biospecimen repositories and include sample sizes that enable markers meeting prespecified performance characteristics for well-defined clinical applications to be identified. The scientific rigor of discovery research should be improved. ©2015 American Association for Cancer Research.

  8. Integration of Proteomics, Bioinformatics, and Systems Biology in Traumatic Brain Injury Biomarker Discovery

    Science.gov (United States)

    Guingab-Cagmat, J.D.; Cagmat, E.B.; Hayes, R.L.; Anagli, J.

    2013-01-01

    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. PMID:23750150

  9. 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

    2013-12-13

    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.

  10. Biomarker Discovery in Gulf War Veterans: Development of a War Illness Diagnostic Panel

    Science.gov (United States)

    2016-12-01

    Award Number: W81XWH-12-1-0382 TITLE: Biomarker Discovery in Gulf War Veterans: Development of a War Illness Diagnostic Panel PRINCIPAL...SUBTITLE Biomarker Discovery in Gulf War Veterans: Development of a War Illness Diagnostic Panel 5a. CONTRACT NUMBER W81XWH-12-1-0382 5b. GRANT...of the 1990-1991 Gulf War are affected by Gulf War illness (GWI), the chronic condition currently defined only by veterans’ self-reported symptoms

  11. Application of mass spectrometry-based proteomics for biomarker discovery in neurological disorders

    Directory of Open Access Journals (Sweden)

    Venugopal Abhilash

    2009-01-01

    Full Text Available Mass spectrometry-based quantitative proteomics has emerged as a powerful approach that has the potential to accelerate biomarker discovery, both for diagnostic as well as therapeutic purposes. Proteomics has traditionally been synonymous with 2D gels but is increasingly shifting to the use of gel-free systems and liquid chromatography coupled to tandem mass spectrometry (LC-MS/MS. Quantitative proteomic approaches have already been applied to investigate various neurological disorders, especially in the context of identifying biomarkers from cerebrospinal fluid and serum. This review highlights the scope of different applications of quantitative proteomics in understanding neurological disorders with special emphasis on biomarker discovery.

  12. Comprehensive Analysis of MILE Gene Expression Data Set Advances Discovery of Leukaemia Type and Subtype Biomarkers.

    Science.gov (United States)

    Labaj, Wojciech; Papiez, Anna; Polanski, Andrzej; Polanska, Joanna

    2017-03-01

    Large collections of data in studies on cancer such as leukaemia provoke the necessity of applying tailored analysis algorithms to ensure supreme information extraction. In this work, a custom-fit pipeline is demonstrated for thorough investigation of the voluminous MILE gene expression data set. Three analyses are accomplished, each for gaining a deeper understanding of the processes underlying leukaemia types and subtypes. First, the main disease groups are tested for differential expression against the healthy control as in a standard case-control study. Here, the basic knowledge on molecular mechanisms is confirmed quantitatively and by literature references. Second, pairwise comparison testing is performed for juxtaposing the main leukaemia types among each other. In this case by means of the Dice coefficient similarity measure the general relations are pointed out. Moreover, lists of candidate main leukaemia group biomarkers are proposed. Finally, with this approach being successful, the third analysis provides insight into all of the studied subtypes, followed by the emergence of four leukaemia subtype biomarkers. In addition, the class enhanced DEG signature obtained on the basis of novel pipeline processing leads to significantly better classification power of multi-class data classifiers. The developed methodology consisting of batch effect adjustment, adaptive noise and feature filtration coupled with adequate statistical testing and biomarker definition proves to be an effective approach towards knowledge discovery in high-throughput molecular biology experiments.

  13. Mass Spectrometry-Based Proteomics in Molecular Diagnostics: Discovery of Cancer Biomarkers Using Tissue Culture

    Science.gov (United States)

    Paul, Debasish; Kumar, Avinash; Gajbhiye, Akshada; Santra, Manas K.; Srikanth, Rapole

    2013-01-01

    Accurate diagnosis and proper monitoring of cancer patients remain a key obstacle for successful cancer treatment and prevention. Therein comes the need for biomarker discovery, which is crucial to the current oncological and other clinical practices having the potential to impact the diagnosis and prognosis. In fact, most of the biomarkers have been discovered utilizing the proteomics-based approaches. Although high-throughput mass spectrometry-based proteomic approaches like SILAC, 2D-DIGE, and iTRAQ are filling up the pitfalls of the conventional techniques, still serum proteomics importunately poses hurdle in overcoming a wide range of protein concentrations, and also the availability of patient tissue samples is a limitation for the biomarker discovery. Thus, researchers have looked for alternatives, and profiling of candidate biomarkers through tissue culture of tumor cell lines comes up as a promising option. It is a rich source of tumor cell-derived proteins, thereby, representing a wide array of potential biomarkers. Interestingly, most of the clinical biomarkers in use today (CA 125, CA 15.3, CA 19.9, and PSA) were discovered through tissue culture-based system and tissue extracts. This paper tries to emphasize the tissue culture-based discovery of candidate biomarkers through various mass spectrometry-based proteomic approaches. PMID:23586059

  14. Mass Spectrometry-Based Proteomics in Molecular Diagnostics: Discovery of Cancer Biomarkers Using Tissue Culture

    Directory of Open Access Journals (Sweden)

    Debasish Paul

    2013-01-01

    Full Text Available Accurate diagnosis and proper monitoring of cancer patients remain a key obstacle for successful cancer treatment and prevention. Therein comes the need for biomarker discovery, which is crucial to the current oncological and other clinical practices having the potential to impact the diagnosis and prognosis. In fact, most of the biomarkers have been discovered utilizing the proteomics-based approaches. Although high-throughput mass spectrometry-based proteomic approaches like SILAC, 2D-DIGE, and iTRAQ are filling up the pitfalls of the conventional techniques, still serum proteomics importunately poses hurdle in overcoming a wide range of protein concentrations, and also the availability of patient tissue samples is a limitation for the biomarker discovery. Thus, researchers have looked for alternatives, and profiling of candidate biomarkers through tissue culture of tumor cell lines comes up as a promising option. It is a rich source of tumor cell-derived proteins, thereby, representing a wide array of potential biomarkers. Interestingly, most of the clinical biomarkers in use today (CA 125, CA 15.3, CA 19.9, and PSA were discovered through tissue culture-based system and tissue extracts. This paper tries to emphasize the tissue culture-based discovery of candidate biomarkers through various mass spectrometry-based proteomic approaches.

  15. A semiparametric modeling framework for potential biomarker discovery and the development of metabonomic profiles

    Directory of Open Access Journals (Sweden)

    Dey Dipak K

    2008-01-01

    Full Text Available Abstract Background The discovery of biomarkers is an important step towards the development of criteria for early diagnosis of disease status. Recently electrospray ionization (ESI and matrix assisted laser desorption (MALDI time-of-flight (TOF mass spectrometry have been used to identify biomarkers both in proteomics and metabonomics studies. Data sets generated from such studies are generally very large in size and thus require the use of sophisticated statistical techniques to glean useful information. Most recent attempts to process these types of data model each compound's intensity either discretely by positional (mass to charge ratio clustering or through each compounds' own intensity distribution. Traditionally data processing steps such as noise removal, background elimination and m/z alignment, are generally carried out separately resulting in unsatisfactory propagation of signals in the final model. Results In the present study a novel semi-parametric approach has been developed to distinguish urinary metabolic profiles in a group of traumatic patients from those of a control group consisting of normal individuals. Data sets obtained from the replicates of a single subject were used to develop a functional profile through Dirichlet mixture of beta distribution. This functional profile is flexible enough to accommodate variability of the instrument and the inherent variability of each individual, thus simultaneously addressing different sources of systematic error. To address instrument variability, all data sets were analyzed in replicate, an important issue ignored by most studies in the past. Different model comparisons were performed to select the best model for each subject. The m/z values in the window of the irregular pattern are then further recommended for possible biomarker discovery. Conclusion To the best of our knowledge this is the very first attempt to model the physical process behind the time-of flight mass

  16. Approach to cerebrospinal fluid (CSF) biomarker discovery and evaluation in HIV infection.

    Science.gov (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

    2013-12-01

    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.

  17. 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, Wei-Jun; Liu, Tao; Kagan, Jacob; Srivastava, Sudhir; Smith, Richard D.; Rodland, Karin D.; Camp, David G.

    2015-12-04

    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.

  18. Sparse Mbplsr for Metabolomics Data and Biomarker Discovery

    DEFF Research Database (Denmark)

    Karaman, İbrahim

    2014-01-01

    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...

  19. Revisiting biomarker discovery by plasma proteomics

    DEFF Research Database (Denmark)

    Geyer, Philipp E; Holdt, Lesca M; Teupser, Daniel

    2017-01-01

    slow rate. As described in this review, mass spectrometry (MS)-based proteomics has become a powerful technology in biological research and it is now poised to allow the characterization of the plasma proteome in great depth. Previous "triangular strategies" aimed at discovering single biomarker...

  20. The Knowledge-Integrated Network Biomarkers Discovery for Major Adverse Cardiac Events

    Science.gov (United States)

    Jin, Guangxu; Zhou, Xiaobo; Wang, Honghui; Zhao, Hong; Cui, Kemi; Zhang, Xiang-Sun; Chen, Luonan; Hazen, Stanley L.; Li, King; Wong, Stephen T. C.

    2010-01-01

    The mass spectrometry (MS) technology in clinical proteomics is very promising for discovery of new biomarkers for diseases management. To overcome the obstacles of data noises in MS analysis, we proposed a new approach of knowledge-integrated biomarker discovery using data from Major Adverse Cardiac Events (MACE) patients. We first built up a cardiovascular-related network based on protein information coming from protein annotations in Uniprot, protein–protein interaction (PPI), and signal transduction database. Distinct from the previous machine learning methods in MS data processing, we then used statistical methods to discover biomarkers in cardiovascular-related network. Through the tradeoff between known protein information and data noises in mass spectrometry data, we finally could firmly identify those high-confident biomarkers. Most importantly, aided by protein–protein interaction network, that is, cardiovascular-related network, we proposed a new type of biomarkers, that is, network biomarkers, composed of a set of proteins and the interactions among them. The candidate network biomarkers can classify the two groups of patients more accurately than current single ones without consideration of biological molecular interaction. PMID:18665624

  1. Implementation of proteomic biomarkers : Making it work

    NARCIS (Netherlands)

    Mischak, Harald; Ioannidis, John P. A.; 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, Gerarda; 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

    Eur J Clin Invest 2012; 42 (9): 10271036 Abstract 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

  2. Gaucher disease: a model disorder for biomarker discovery

    DEFF Research Database (Denmark)

    Boot, Rolf G; van Breemen, Mariëlle J; Wegdam, Wouter

    2009-01-01

    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 therape...... in clinical management of Gaucher patients are discussed. Moreover, the use of several modern proteomic technologies for the identification of Gaucher biomarkers is reviewed....

  3. Common Subcluster Mining in Microarray Data for Molecular Biomarker Discovery.

    Science.gov (United States)

    Sadhu, Arnab; Bhattacharyya, Balaram

    2017-10-11

    Molecular biomarkers can be potential facilitators for detection of cancer at early stage which is otherwise difficult through conventional biomarkers. Gene expression data from microarray experiments on both normal and diseased cell samples provide enormous scope to explore genetic relations of disease using computational techniques. Varied patterns of expressions of thousands of genes at different cell conditions along with inherent experimental error make the task of isolating disease related genes challenging. In this paper, we present a data mining method, common subcluster mining (CSM), to discover highly perturbed genes under diseased condition from differential expression patterns. The method builds heap through superposing near centroid clusters from gene expression data of normal samples and extracts its core part. It, thus, isolates genes exhibiting the most stable state across normal samples and constitute a reference set for each centroid. It performs the same operation on datasets from corresponding diseased samples and isolates the genes showing drastic changes in their expression patterns. The method thus finds the disease-sensitive genesets when applied to datasets of lung cancer, prostrate cancer, pancreatic cancer, breast cancer, leukemia and pulmonary arterial hypertension. In majority of the cases, few new genes are found over and above some previously reported ones. Genes with distinct deviations in diseased samples are prospective candidates for molecular biomarkers of the respective disease.

  4. Proteome analysis of body fluids for amyotrophic lateral sclerosis biomarker discovery.

    Science.gov (United States)

    Krüger, Thomas; Lautenschläger, Janin; Grosskreutz, Julian; Rhode, Heidrun

    2013-01-01

    Amyotrophic lateral sclerosis (ALS) is a progressive neurodegenerative disorder of motor neurons leading to death of the patients, mostly within 2-5 years after disease onset. The pathomechanism of motor neuron degeneration is only partially understood and therapeutic strategies based on mechanistic insights are largely ineffective. The discovery of reliable biomarkers of disease diagnosis and progression is the sine qua non of both the revelation of insights into the ALS pathomechanism and the assessment of treatment efficacies. Proteomic approaches are an important pillar in ALS biomarker discovery. Cerebrospinal fluid is the most promising body fluid for differential proteome analyses, followed by blood (serum, plasma), and even urine and saliva. The present study provides an overview about reported peptide/protein biomarker candidates that showed significantly altered levels in certain body fluids of ALS patients. These findings have to be discussed according to proposed pathomechanisms to identify modifiers of disease progression and to pave the way for the development of potential therapeutic strategies. Furthermore, limitations and advantages of proteomic approaches for ALS biomarker discovery in different body fluids and reliable validation of biomarker candidates have been addressed. © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  5. Proteomic biomarker discovery in 1000 human plasma samples with mass spectrometry

    DEFF Research Database (Denmark)

    Cominetti, Ornella; Núñez Galindo, Antonio; Corthésy, John

    2016-01-01

    automated proteomic biomarker discovery workflow. Herein, we have applied this approach to analyze 1000 plasma samples from the multicentered human dietary intervention study "DiOGenes". Study design, sample randomization, tracking, and logistics were the foundations of our large-scale study. We checked...

  6. 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

    2016-01-01

    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......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.......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...

  7. Biomarker discovery in neurological diseases: a metabolomic approach

    Directory of Open Access Journals (Sweden)

    Afaf El-Ansary

    2009-12-01

    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

  8. Enhancement of MS Signal Processing For Improved Cancer Biomarker Discovery

    Science.gov (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.

  9. Clinical proteomics: Applications for prostate cancer biomarker discovery and detection.

    Science.gov (United States)

    Petricoin, Emanuel F; Ornstein, David K; Liotta, Lance A

    2004-01-01

    The science of proteomics comprises much more than simply generating lists of proteins that change in expression as a cause of or consequence of pathophysiology. The goal of proteomics should be to characterize the information flow through the intercellular protein circuitry that communicates with the extracellular microenvironment and then ultimately to the serum/plasma macroenvironment. Serum proteomic pattern diagnostics is a new type of proteomic concept in which patterns of ion signatures generated from high dimensional mass spectrometry data are used as diagnostic classifiers. This recent approach has exciting potential for clinical utility of diagnostic patterns because low molecular weight metabolites, peptides, and protein fragments may have higher accuracy than traditional biomarkers of cancer detection. Intriguingly, we now have discovered that this diagnostic information exists in a bound state, complexed with circulating highly abundant carrier proteins. These diagnostic fragments may one day be harvested by circulating nanoparticles, designed to absorb, enrich, and amplify the repertoire of diagnostic biomarkers generated-even at the critical, initial stages of carcinogenesis. Copyright 2004 Elsevier Inc.

  10. Mass spectrometry based biomarker discovery, verification, and validation--quality assurance and control of protein biomarker assays.

    Science.gov (United States)

    Parker, Carol E; Borchers, Christoph H

    2014-06-01

    In its early years, mass spectrometry (MS)-based proteomics focused on the cataloging of proteins found in different species or different tissues. By 2005, proteomics was being used for protein quantitation, typically based on "proteotypic" peptides which act as surrogates for the parent proteins. Biomarker discovery is usually done by non-targeted "shotgun" proteomics, using relative quantitation methods to determine protein expression changes that correlate with disease (output given as "up-or-down regulation" or "fold-increases"). MS-based techniques can also perform "absolute" quantitation which is required for clinical applications (output given as protein concentrations). Here we describe the differences between these methods, factors that affect the precision and accuracy of the results, and some examples of recent studies using MS-based proteomics to verify cancer-related biomarkers. Copyright © 2014 Federation of European Biochemical Societies. Published by Elsevier B.V. All rights reserved.

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

    Science.gov (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

    2009-01-01

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

    Directory of Open Access Journals (Sweden)

    Rivoltini Licia

    2009-06-01

    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

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

    Directory of Open Access Journals (Sweden)

    Kirstin Mittelstrass

    2011-08-01

    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. Informatics-guided procurement of patient samples for biomarker discovery projects in cancer research.

    Science.gov (United States)

    Suh, K Stephen; Remache, Yvonne K; Patel, Jalpa S; Chen, Steve H; Haystrand, Russell; Ford, Peggy; Shaikh, Anadil M; Wang, Jian; Goy, Andre H

    2009-02-01

    Modern cancer research for biomarker discovery program requires solving several tasks that are directly involved with patient sample procurement. One requirement is to construct a highly efficient workflow on the clinical side for the procurement to generate a consistent supply of high quality samples for research. This undertaking needs a network of interdepartmental collaborations and participations at various levels, including physical human interactions, information technology implementations and a bioinformatics tool that is highly effective and user-friendly to busy clinicians and researchers associated with the sample procurement. Collegial participation that is sequential but continual from one department to another demands dedicated bioinformatics software coordinating between the institutional clinic and the tissue repository facility. Participants in the process include admissions, consenting process, phlebotomy, surgery center and pathology. During this multiple step procedures, clinical data are collected for detailed analytical endpoints to supplement logistics of defining and validating the discovery of biomarkers.

  15. Molecular correlates of trait anxiety: expanding biomarker discovery from protein expression to turnover

    OpenAIRE

    Zhang, Yaoyang

    2010-01-01

    Depression and anxiety disorders affect a great number of people in the world. Although remarkable efforts have been devoted to understanding the clinical and biological basis of these disorders, progress has been relatively slow. Furthermore, no laboratory test currently is available for diagnosis of anxiety and depression. These disorders are mainly diagnosed empirically on the basis of a doctor’s personal observations and experiences. Hence, discovery of biomarkers for these psychiatric di...

  16. From the endometrium physiology to a comprehensive strategy for the discovery of ovarian cancer biomarkers

    OpenAIRE

    Janos L. Tanyi; Nathalie Scholler

    2011-01-01

    The development of comprehensive strategies for biomarker discovery of gynecological cancers is needed. The unique physiology of the female genital track revolves around ovulatory cycles ending by the proteolysis of the endometrium triggered by progesterone decline during the last part of the luteal phase. Building on the known link between incessant ovulation and ovarian cancer, we hypothesize that life-long menstruations could damage neighboring organs such as fallopian tubes, ovaries and p...

  17. Biomarker Discovery in Human Prostate Cancer: an Update in Metabolomics Studies

    Directory of Open Access Journals (Sweden)

    Ana Rita Lima

    2016-08-01

    Full Text Available Prostate cancer (PCa is the most frequently diagnosed cancer and the second leading cause of cancer death among men in Western countries. Current screening techniques are based on the measurement of serum prostate specific antigen (PSA levels and digital rectal examination. A decisive diagnosis of PCa is based on prostate biopsies; however, this approach can lead to false-positive and false-negative results. Therefore, it is important to discover new biomarkers for the diagnosis of PCa, preferably noninvasive ones. Metabolomics is an approach that allows the analysis of the entire metabolic profile of a biological system. As neoplastic cells have a unique metabolic phenotype related to cancer development and progression, the identification of dysfunctional metabolic pathways using metabolomics can be used to discover cancer biomarkers and therapeutic targets. In this study, we review several metabolomics studies performed in prostatic fluid, blood plasma/serum, urine, tissues and immortalized cultured cell lines with the objective of discovering alterations in the metabolic phenotype of PCa and thus discovering new biomarkers for the diagnosis of PCa. Encouraging results using metabolomics have been reported for PCa, with sarcosine being one of the most promising biomarkers identified to date. However, the use of sarcosine as a PCa biomarker in the clinic remains a controversial issue within the scientific community. Beyond sarcosine, other metabolites are considered to be biomarkers for PCa, but they still need clinical validation. Despite the lack of metabolomics biomarkers reaching clinical practice, metabolomics proved to be a powerful tool in the discovery of new biomarkers for PCa detection.

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

    Directory of Open Access Journals (Sweden)

    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.

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

    Science.gov (United States)

    Villanova, Federica; Di Meglio, Paola; Inokuma, Margaret; Aghaeepour, Nima; Perucha, Esperanza; Mollon, Jennifer; Nomura, Laurel; Hernandez-Fuentes, Maria; Cope, Andrew; Prevost, A Toby; Heck, Susanne; Maino, Vernon; Lord, Graham; Brinkman, Ryan R; Nestle, Frank O

    2013-01-01

    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.

  20. Improving feature ranking for biomarker discovery in proteomics mass spectrometry data using genetic programming

    Science.gov (United States)

    Ahmed, Soha; Zhang, Mengjie; Peng, Lifeng

    2014-07-01

    Feature selection on mass spectrometry (MS) data is essential for improving classification performance and biomarker discovery. The number of MS samples is typically very small compared with the high dimensionality of the samples, which makes the problem of biomarker discovery very hard. In this paper, we propose the use of genetic programming for biomarker detection and classification of MS data. The proposed approach is composed of two phases: in the first phase, feature selection and ranking are performed. In the second phase, classification is performed. The results show that the proposed method can achieve better classification performance and biomarker detection rate than the information gain- (IG) based and the RELIEF feature selection methods. Meanwhile, four classifiers, Naive Bayes, J48 decision tree, random forest and support vector machines, are also used to further test the performance of the top ranked features. The results show that the four classifiers using the top ranked features from the proposed method achieve better performance than the IG and the RELIEF methods. Furthermore, GP also outperforms a genetic algorithm approach on most of the used data sets.

  1. The Proteomics Big Challenge for Biomarkers and New Drug-Targets Discovery

    Science.gov (United States)

    Savino, Rocco; Paduano, Sergio; Preianò, Mariaimmacolata; Terracciano, Rosa

    2012-01-01

    In the modern process of drug discovery, clinical, functional and chemical proteomics can converge and integrate synergies. Functional proteomics explores and elucidates the components of pathways and their interactions which, when deregulated, lead to a disease condition. This knowledge allows the design of strategies to target multiple pathways with combinations of pathway-specific drugs, which might increase chances of success and reduce the occurrence of drug resistance. Chemical proteomics, by analyzing the drug interactome, strongly contributes to accelerate the process of new druggable targets discovery. In the research area of clinical proteomics, proteome and peptidome mass spectrometry-profiling of human bodily fluid (plasma, serum, urine and so on), as well as of tissue and of cells, represents a promising tool for novel biomarker and eventually new druggable targets discovery. In the present review we provide a survey of current strategies of functional, chemical and clinical proteomics. Major issues will be presented for proteomic technologies used for the discovery of biomarkers for early disease diagnosis and identification of new drug targets. PMID:23203042

  2. Biomarker discovery for colon cancer using a 761 gene RT-PCR assay

    Directory of Open Access Journals (Sweden)

    Hackett James R

    2007-08-01

    Full Text Available Abstract Background Reverse transcription PCR (RT-PCR is widely recognized to be the gold standard method for quantifying gene expression. Studies using RT-PCR technology as a discovery tool have historically been limited to relatively small gene sets compared to other gene expression platforms such as microarrays. We have recently shown that TaqMan® RT-PCR can be scaled up to profile expression for 192 genes in fixed paraffin-embedded (FPE clinical study tumor specimens. This technology has also been used to develop and commercialize a widely used clinical test for breast cancer prognosis and prediction, the Onco typeDX™ assay. A similar need exists in colon cancer for a test that provides information on the likelihood of disease recurrence in colon cancer (prognosis and the likelihood of tumor response to standard chemotherapy regimens (prediction. We have now scaled our RT-PCR assay to efficiently screen 761 biomarkers across hundreds of patient samples and applied this process to biomarker discovery in colon cancer. This screening strategy remains attractive due to the inherent advantages of maintaining platform consistency from discovery through clinical application. Results RNA was extracted from formalin fixed paraffin embedded (FPE tissue, as old as 28 years, from 354 patients enrolled in NSABP C-01 and C-02 colon cancer studies. Multiplexed reverse transcription reactions were performed using a gene specific primer pool containing 761 unique primers. PCR was performed as independent TaqMan® reactions for each candidate gene. Hierarchal clustering demonstrates that genes expected to co-express form obvious, distinct and in certain cases very tightly correlated clusters, validating the reliability of this technical approach to biomarker discovery. Conclusion We have developed a high throughput, quantitatively precise multi-analyte gene expression platform for biomarker discovery that approaches low density DNA arrays in numbers of

  3. Candidate biomarker discovery and selection for ‘Granny Smith' superficial scald risk management and diagnosis, poster board

    Science.gov (United States)

    Discovery of candidate biomarkers for superficial scald, a peel disorder that develops during storage of susceptible apple cultivars, is part of a larger project aimed at developing biomarker-based risk-management and diagnostic tools for multiple apple postharvest disorders (http://www.tfrec.wsu.ed...

  4. Variable importance analysis based on rank aggregation with applications in metabolomics for biomarker discovery.

    Science.gov (United States)

    Yun, Yong-Huan; Deng, Bai-Chuan; Cao, Dong-Sheng; Wang, Wei-Ting; Liang, Yi-Zeng

    2016-03-10

    Biomarker discovery is one important goal in metabolomics, which is typically modeled as selecting the most discriminating metabolites for classification and often referred to as variable importance analysis or variable selection. Until now, a number of variable importance analysis methods to discover biomarkers in the metabolomics studies have been proposed. However, different methods are mostly likely to generate different variable ranking results due to their different principles. Each method generates a variable ranking list just as an expert presents an opinion. The problem of inconsistency between different variable ranking methods is often ignored. To address this problem, a simple and ideal solution is that every ranking should be taken into account. In this study, a strategy, called rank aggregation, was employed. It is an indispensable tool for merging individual ranking lists into a single "super"-list reflective of the overall preference or importance within the population. This "super"-list is regarded as the final ranking for biomarker discovery. Finally, it was used for biomarkers discovery and selecting the best variable subset with the highest predictive classification accuracy. Nine methods were used, including three univariate filtering and six multivariate methods. When applied to two metabolic datasets (Childhood overweight dataset and Tubulointerstitial lesions dataset), the results show that the performance of rank aggregation has improved greatly with higher prediction accuracy compared with using all variables. Moreover, it is also better than penalized method, least absolute shrinkage and selectionator operator (LASSO), with higher prediction accuracy or less number of selected variables which are more interpretable. Copyright © 2016 Elsevier B.V. All rights reserved.

  5. Plasma biomarker discovery in preeclampsia using a novel differential isolation technology for circulating extracellular vesicles.

    Science.gov (United States)

    Tan, Kok Hian; Tan, Soon Sim; Sze, Siu Kwan; Lee, Wai Kheong Ryan; Ng, Mor Jack; Lim, Sai Kiang

    2014-10-01

    To circumvent the complex protein milieu of plasma and discover robust predictive biomarkers for preeclampsia (PE), we investigate if phospholipid-binding ligands can reduce the milieu complexity by extracting plasma extracellular vesicles for biomarker discovery. Cholera toxin B chain (CTB) and annexin V (AV) which respectively binds GM1 ganglioside and phosphatidylserine were used to isolate extracellular vesicles from plasma of PE patients and healthy pregnant women. The proteins in the vesicles were identified using enzyme-linked immunosorbent assay, antibody array, and mass spectrometry. CTB and AV were found to bind 2 distinct groups of extracellular vesicles. Antibody array and enzyme-linked immunosorbent assay revealed that PE patients had elevated levels of CD105, interleukin-6, placental growth factor, tissue inhibitor of metallopeptidase 1, and atrial natriuretic peptide in cholera toxin B- but not AV-vesicles, and elevated levels of plasminogen activator inhibitor-1, pro-calcitonin, S100b, tumor growth factor β, vascular endothelial growth factor receptor 1, brain natriuretic peptide, and placental growth factor in both cholera toxin B- and AV-vesicles. CD9 level was elevated in cholera toxin B-vesicles but reduced in AV vesicles of PE patients. Proteome analysis revealed that in cholera toxin B-vesicles, 87 and 222 proteins were present only in PE patients and healthy pregnant women respectively while in AV-vesicles, 104 and 157 proteins were present only in PE and healthy pregnant women, respectively. This study demonstrated for the first time that CTB and AV bind unique extracellular vesicles, and their protein cargo reflects the disease state of the patient. The successful use of these 2 ligands to isolate circulating plasma extracellular vesicles for biomarker discovery in PE represents a novel technology for biomarker discovery that can be applied to other specialties. Copyright © 2014 Elsevier Inc. All rights reserved.

  6. Systems Biology Modeling of the Radiation Sensitivity Network: A Biomarker Discovery Platform

    International Nuclear Information System (INIS)

    Eschrich, Steven; Zhang Hongling; Zhao Haiyan; Boulware, David; Lee, Ji-Hyun; Bloom, Gregory; Torres-Roca, Javier F.

    2009-01-01

    Purpose: The discovery of effective biomarkers is a fundamental goal of molecular medicine. Developing a systems-biology understanding of radiosensitivity can enhance our ability of identifying radiation-specific biomarkers. Methods and Materials: Radiosensitivity, as represented by the survival fraction at 2 Gy was modeled in 48 human cancer cell lines. We applied a linear regression algorithm that integrates gene expression with biological variables, including ras status (mut/wt), tissue of origin and p53 status (mut/wt). Results: The biomarker discovery platform is a network representation of the top 500 genes identified by linear regression analysis. This network was reduced to a 10-hub network that includes c-Jun, HDAC1, RELA (p65 subunit of NFKB), PKC-beta, SUMO-1, c-Abl, STAT1, AR, CDK1, and IRF1. Nine targets associated with radiosensitization drugs are linked to the network, demonstrating clinical relevance. Furthermore, the model identified four significant radiosensitivity clusters of terms and genes. Ras was a dominant variable in the analysis, as was the tissue of origin, and their interaction with gene expression but not p53. Overrepresented biological pathways differed between clusters but included DNA repair, cell cycle, apoptosis, and metabolism. The c-Jun network hub was validated using a knockdown approach in 8 human cell lines representing lung, colon, and breast cancers. Conclusion: We have developed a novel radiation-biomarker discovery platform using a systems biology modeling approach. We believe this platform will play a central role in the integration of biology into clinical radiation oncology practice.

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

    International Nuclear Information System (INIS)

    Smolinska, Agnieszka; Blanchet, Lionel; Buydens, Lutgarde M.C.; Wijmenga, Sybren S.

    2012-01-01

    Highlights: ► Procedures for acquisition of different biofluids by NMR. ► Recent developments in metabolic profiling of different biofluids by NMR are presented. ► The crucial steps involved in data preprocessing and multivariate chemometric analysis are reviewed. ► 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).

  8. The Emerging Field of Quantitative Blood Metabolomics for Biomarker Discovery in Critical Illnesses

    Science.gov (United States)

    Serkova, Natalie J.; Standiford, Theodore J.

    2011-01-01

    Metabolomics, a science of systems biology, is the global assessment of endogenous metabolites within a biologic system and represents a “snapshot” reading of gene function, enzyme activity, and the physiological landscape. Metabolite detection, either individual or grouped as a metabolomic profile, is usually performed in cells, tissues, or biofluids by either nuclear magnetic resonance spectroscopy or mass spectrometry followed by sophisticated multivariate data analysis. Because loss of metabolic homeostasis is common in critical illness, the metabolome could have many applications, including biomarker and drug target identification. Metabolomics could also significantly advance our understanding of the complex pathophysiology of acute illnesses, such as sepsis and acute lung injury/acute respiratory distress syndrome. Despite this potential, the clinical community is largely unfamiliar with the field of metabolomics, including the methodologies involved, technical challenges, and, most importantly, clinical uses. Although there is evidence of successful preclinical applications, the clinical usefulness and application of metabolomics in critical illness is just beginning to emerge, the advancement of which hinges on linking metabolite data to known and validated clinically relevant indices. In addition, other important aspects, such as patient selection, sample collection, and processing, as well as the needed multivariate data analysis, have to be taken into consideration before this innovative approach to biomarker discovery can become a reliable tool in the intensive care unit. The purpose of this review is to begin to familiarize clinicians with the field of metabolomics and its application for biomarker discovery in critical illnesses such as sepsis. PMID:21680948

  9. Proteomic Biomarker Discovery in 1000 Human Plasma Samples with Mass Spectrometry.

    Science.gov (United States)

    Cominetti, Ornella; Núñez Galindo, Antonio; Corthésy, John; Oller Moreno, Sergio; Irincheeva, Irina; Valsesia, Armand; Astrup, Arne; Saris, Wim H M; Hager, Jörg; Kussmann, Martin; Dayon, Loïc

    2016-02-05

    The overall impact of proteomics on clinical research and its translation has lagged behind expectations. One recognized caveat is the limited size (subject numbers) of (pre)clinical studies performed at the discovery stage, the findings of which fail to be replicated in larger verification/validation trials. Compromised study designs and insufficient statistical power are consequences of the to-date still limited capacity of mass spectrometry (MS)-based workflows to handle large numbers of samples in a realistic time frame, while delivering comprehensive proteome coverages. We developed a highly automated proteomic biomarker discovery workflow. Herein, we have applied this approach to analyze 1000 plasma samples from the multicentered human dietary intervention study "DiOGenes". Study design, sample randomization, tracking, and logistics were the foundations of our large-scale study. We checked the quality of the MS data and provided descriptive statistics. The data set was interrogated for proteins with most stable expression levels in that set of plasma samples. We evaluated standard clinical variables that typically impact forthcoming results and assessed body mass index-associated and gender-specific proteins at two time points. We demonstrate that analyzing a large number of human plasma samples for biomarker discovery with MS using isobaric tagging is feasible, providing robust and consistent biological results.

  10. Progress and Potential of Imaging Mass Spectrometry Applied to Biomarker Discovery.

    Science.gov (United States)

    Quanico, Jusal; Franck, Julien; Wisztorski, Maxence; Salzet, Michel; Fournier, Isabelle

    2017-01-01

    Mapping provides a direct means to assess the impact of protein biomarkers and puts into context their relevance in the type of cancer being examined. To this end, mass spectrometry imaging (MSI) was developed to provide the needed spatial information which is missing in traditional liquid-based mass spectrometric proteomics approaches. Aptly described as a "molecular histology" technique, MSI gives an additional dimension in characterizing tumor biopsies, allowing for mapping of hundreds of molecules in a single analysis. A decade of developments focused on improving and standardizing MSI so that the technique can be translated into the clinical setting. This review describes the progress made in addressing the technological development that allows to bridge local protein detection by MSI to its identification and to illustrate its potential in studying various aspects of cancer biomarker discovery.

  11. 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.

  12. 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.

  13. Sample preparation and fractionation for proteome analysis and cancer biomarker discovery by mass spectrometry.

    Science.gov (United States)

    Ahmed, Farid E

    2009-03-01

    Sample preparation and fractionation technologies are one of the most crucial processes in proteomic analysis and biomarker discovery in solubilized samples. Chromatographic or electrophoretic proteomic technologies are also available for separation of cellular protein components. There are, however, considerable limitations in currently available proteomic technologies as none of them allows for the analysis of the entire proteome in a simple step because of the large number of peptides, and because of the wide concentration dynamic range of the proteome in clinical blood samples. The results of any undertaken experiment depend on the condition of the starting material. Therefore, proper experimental design and pertinent sample preparation is essential to obtain meaningful results, particularly in comparative clinical proteomics in which one is looking for minor differences between experimental (diseased) and control (nondiseased) samples. This review discusses problems associated with general and specialized strategies of sample preparation and fractionation, dealing with samples that are solution or suspension, in a frozen tissue state, or formalin-preserved tissue archival samples, and illustrates how sample processing might influence detection with mass spectrometric techniques. Strategies that dramatically improve the potential for cancer biomarker discovery in minimally invasive, blood-collected human samples are also presented.

  14. Novel automated biomarker discovery work flow for urinary peptidomics

    DEFF Research Database (Denmark)

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

    2009-01-01

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

    Directory of Open Access Journals (Sweden)

    Vilém Guryča

    2014-03-01

    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.

  16. Lung Cancer Serum Biomarker Discovery Using Label Free LC-MS/MS

    Science.gov (United States)

    Zeng, Xuemei; Hood, Brian L.; Zhao, Ting; Conrads, Thomas P.; Sun, Mai; Gopalakrishnan, Vanathi; Grover, Himanshu; Day, Roger S.; Weissfeld, Joel L.; Wilson, David O.; Siegfried, Jill M.; Bigbee, William L.

    2011-01-01

    Introduction Lung cancer remains the leading cause of cancer-related death with poor survival due to the late stage at which lung cancer is typically diagnosed. Given the clinical burden from lung cancer, and the relatively favorable survival associated with early stage lung cancer, biomarkers for early detection of lung cancer are of important potential clinical benefit. Methods We performed a global lung cancer serum biomarker discovery study using liquid chromatography-tandem mass spectrometry (LC-MS/MS) in a set of pooled non-small cell lung cancer (NSCLC) case sera and matched controls. Immunoaffinity subtraction was used to deplete the top most abundant serum proteins; the remaining serum proteins were subjected to trypsin digestion and analyzed in triplicate by LC-MS/MS. The tandem mass spectrum data were searched against the human proteome database and the resultant spectral counting data were used to estimate the relative abundance of proteins across the case/control serum pools. The spectral counting derived abundances of some candidate biomarker proteins were confirmed with multiple reaction monitoring MS assays. Results A list of 49 differentially abundant candidate proteins was compiled by applying a negative binomial regression model to the spectral counting data (pbiomarkers with statistically significant differential abundance across the lung cancer case/control pools which, when validated, could improve lung cancer early detection. PMID:21304412

  17. Schizophrenia genomics and proteomics: are we any closer to biomarker discovery?

    Directory of Open Access Journals (Sweden)

    Kramer Alon

    2009-01-01

    Full Text Available Abstract The field of proteomics has made leaps and bounds in the last 10 years particularly in the fields of oncology and cardiovascular medicine. In comparison, neuroproteomics is still playing catch up mainly due to the relative complexity of neurological disorders. Schizophrenia is one such disorder, believed to be the results of multiple factors both genetic and environmental. Affecting over 2 million people in the US alone, it has become a major clinical and public health concern worldwide. This paper gives an update of schizophrenia biomarker research as reviewed by Lakhan in 2006 and gives us a rundown of the progress made during the last two years. Several studies demonstrate the potential of cerebrospinal fluid as a source of neuro-specific biomarkers. Genetic association studies are making headway in identifying candidate genes for schizophrenia. In addition, metabonomics, bioinformatics, and neuroimaging techniques are aiming to complete the picture by filling in knowledge gaps. International cooperation in the form of genomics and protein databases and brain banks is facilitating research efforts. While none of the recent developments described here in qualifies as biomarker discovery, many are likely to be stepping stones towards that goal.

  18. Biomarker discovery and applications for foods and beverages: proteomics to nanoproteomics.

    Science.gov (United States)

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

    2013-11-20

    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

  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: A.Smolinska@science.ru.nl [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)

    2012-10-31

    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. Discovery of serum biomarkers predicting development of a subsequent depressive episode in social anxiety disorder.

    Science.gov (United States)

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

    2015-08-01

    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. Copyright © 2015 Elsevier Inc. All rights reserved.

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

    International Nuclear Information System (INIS)

    Yang, Xu; Lazar, Iulia M

    2009-01-01

    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. 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. In this work, we report on the generation of a library of 9,677 peptides (p < 0.001), representing ~1,572 proteins from human breast cancer cells, that can be used for MRM/MS-based biomarker screening studies. For each protein, the library provides the number and sequence of detectable peptides, the charge state, the spectral count, the molecular weight, the parameters that characterize the quality of the tandem mass spectrum (p-value, DeltaM, Xcorr, DeltaCn, Sp, no. of matching 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)<50,000. Preliminary experiments have

  2. The discovery and development of proteomic safety biomarkers for the detection of drug-induced liver toxicity

    International Nuclear Information System (INIS)

    Amacher, David E.

    2010-01-01

    Biomarkers are biometric measurements that provide critical quantitative information about the biological condition of the animal or individual being tested. In drug safety studies, established toxicity biomarkers are used along with other conventional study data to determine dose-limiting organ toxicity, and to define species sensitivity for new chemical entities intended for possible use as human medicines. A continuing goal of drug safety scientists in the pharmaceutical industry is to discover and develop better trans-species biomarkers that can be used to determine target organ toxicities for preclinical species in short-term studies at dose levels that are some multiple of the intended human dose and again later in full development for monitoring clinical trials at lower therapeutic doses. Of particular value are early, predictive, noninvasive biomarkers that have in vitro, in vivo, and clinical transferability. Such translational biomarkers bridge animal testing used in preclinical science and human studies that are part of subsequent clinical testing. Although suitable for in vivo preclinical regulatory studies, conventional hepatic safety biomarkers are basically confirmatory markers because they signal organ toxicity after some pathological damage has occurred, and are therefore not well-suited for short-term, predictive screening assays early in the discovery-to-development progression of new chemical entities (NCEs) available in limited quantities. Efforts between regulatory agencies and the pharmaceutical industry are underway for the coordinated discovery, qualification, verification and validation of early predictive toxicity biomarkers. Early predictive safety biomarkers are those that are detectable and quantifiable prior to the onset of irreversible tissue injury and which are associated with a mechanism of action relevant to a specific type of potential hepatic injury. Potential drug toxicity biomarkers are typically endogenous macromolecules in

  3. Protein biomarker discovery and fast monitoring for the identification and detection of Anisakids by parallel reaction monitoring (PRM) mass spectrometry.

    Science.gov (United States)

    Carrera, Mónica; Gallardo, José M; Pascual, Santiago; González, Ángel F; Medina, Isabel

    2016-06-16

    Anisakids are fish-borne parasites that are responsible for a large number of human infections and allergic reactions around the world. World health organizations and food safety authorities aim to control and prevent this emerging health problem. In the present work, a new method for the fast monitoring of these parasites is described. The strategy is divided in three steps: (i) purification of thermostable proteins from fish-borne parasites (Anisakids), (ii) in-solution HIFU trypsin digestion and (iii) monitoring of several peptide markers by parallel reaction monitoring (PRM) mass spectrometry. This methodology allows the fast detection of Anisakids in Biomarker Discovery and the Fast Monitoring for the identification and detection of Anisakids in fishery products. The strategy is based on the purification of thermostable proteins, the use of accelerated in-solution trypsin digestions under an ultrasonic field provided by High-Intensity Focused Ultrasound (HIFU) and the monitoring of several peptide biomarkers by Parallel Reaction Monitoring (PRM) Mass Spectrometry in a linear ion trap mass spectrometer. The workflow allows the unequivocal detection of Anisakids, in <2h. The present strategy constitutes the fastest method for Anisakids detection, whose application in the food quality control area, could provide to the authorities an effective and rapid method to guarantee the safety to the consumers. Copyright © 2016 Elsevier B.V. All rights reserved.

  4. Association of SNCA with Parkinson: replication in the Harvard NeuroDiscovery Center Biomarker Study

    Science.gov (United States)

    Ding, Hongliu; Sarokhan, Alison K.; Roderick, Sarah S.; Bakshi, Rachit; Maher, Nancy E.; Ashourian, Paymon; Kan, Caroline G.; Chang, Sunny; Santarlasci, Andrea; Swords, Kyleen E.; Ravina, Bernard M.; Hayes, Michael T.; Sohur, U. Shivraj; Wills, Anne-Marie; Flaherty, Alice W.; Unni, Vivek K.; Hung, Albert Y.; Selkoe, Dennis J.; Schwarzschild, Michael A.; Schlossmacher, Michael G.; Sudarsky, Lewis R.; Growdon, John H.; Ivinson, Adrian J.; Hyman, Bradley T.; Scherzer, Clemens R.

    2011-01-01

    Background Mutations in the α-synuclein gene (SNCA) cause autosomal dominant forms of Parkinson’s disease, but the substantial risk conferred by this locus to the common sporadic disease has only recently emerged from genome-wide association studies. Methods Here we genotyped a prioritized non-coding variant in SNCA intron-4 in 344 patients with Parkinson’s and 275 controls from the longitudinal Harvard NeuroDiscovery Center Biomarker Study. Results The common minor allele of rs2736990 was associated with elevated disease susceptibility (odds ratio = 1.40, P value = 0.0032). Conclusions This result increases confidence in the notion that in many clinically well-characterized patients genetic variation in SNCA contributes to “sporadic” disease. PMID:21953863

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

    DEFF Research Database (Denmark)

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

    2015-01-01

    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...

  6. A Standardized and Reproducible Urine Preparation Protocol for Cancer Biomarkers Discovery

    Directory of Open Access Journals (Sweden)

    Julia Beretov

    2014-01-01

    Full Text Available A suitable and standardized protein purification technique is essential to maintain consistency and to allow data comparison between proteomic studies for urine biomarker discovery. Ultimately, efforts should be made to standardize urine preparation protocols. The aim of this study was to develop an optimal analytical protocol to achieve maximal protein yield and to ensure that this method was applicable to examine urine protein patterns that distinguish disease and disease-free states. In this pilot study, we compared seven different urine sample preparation methods to remove salts, and to precipitate and isolate urinary proteins. Sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE profiles showed that the sequential preparation of urinary proteins by combining acetone and trichloroacetic acid (TCA alongside high speed centrifugation (HSC provided the best separation, and retained the most urinary proteins. Therefore, this approach is the preferred method for all further urine protein analysis.

  7. Recent mass spectrometry-based proteomics for biomarker discovery in lung cancer, COPD, and asthma.

    Science.gov (United States)

    Fujii, Kiyonaga; Nakamura, Haruhiko; Nishimura, Toshihide

    2017-04-01

    Lung cancer and related diseases have been one of the most common causes of deaths worldwide. Genomic-based biomarkers may hardly reflect the underlying dynamic molecular mechanism of functional protein interactions, which is the center of a disease. Recent developments in mass spectrometry (MS) have made it possible to analyze disease-relevant proteins expressed in clinical specimens by proteomic challenges. Areas covered: To understand the molecular mechanisms of lung cancer and its subtypes, chronic obstructive pulmonary disease (COPD), asthma and others, great efforts have been taken to identify numerous relevant proteins by MS-based clinical proteomic approaches. Since lung cancer is a multifactorial disease that is biologically associated with asthma and COPD among various lung diseases, this study focused on proteomic studies on biomarker discovery using various clinical specimens for lung cancer, COPD, and asthma. Expert commentary: MS-based exploratory proteomics utilizing clinical specimens, which can incorporate both experimental and bioinformatic analysis of protein-protein interaction and also can adopt proteogenomic approaches, makes it possible to reveal molecular networks that are relevant to a disease subgroup and that could differentiate between drug responders and non-responders, good and poor prognoses, drug resistance, and so on.

  8. From the endometrium physiology to a comprehensive strategy for the discovery of ovarian cancer biomarkers

    Directory of Open Access Journals (Sweden)

    Janos L. Tanyi

    2011-12-01

    Full Text Available The development of comprehensive strategies for biomarker discovery of gynecological cancers is needed. The unique physiology of the female genital track revolves around ovulatory cycles ending by the proteolysis of the endometrium triggered by progesterone decline during the last part of the luteal phase. Building on the known link between incessant ovulation and ovarian cancer, we hypothesize that life-long menstruations could damage neighboring organs such as fallopian tubes, ovaries and peritoneum via endometrial secretions, and thus endometrium neighboring structures may have developed highly efficient protective strategies that could, in turn, be hijacked by cancer cells for survival and invasion. After literature review, we could classify the molecules involved in ovulation and menstruation pathways in three main categories: proteases, proteases inhibitors and cell-surface protectors. Strikingly, all validated biomarkers for ovarian cancers belong to at least one of these categories. We thus propose the development of comprehensive methods for identification of early diagnostic markers for gynecological cancers using systematical mapping and characterization of surface or soluble molecules belonging to physiological pathways linked to menstruation and differently expressed during luteal cycles.

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

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    Astrid Wachter

    2015-11-01

    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.

  10. Biomarkers Discovery for Colorectal Cancer: A Review on Tumor Endothelial Markers as Perspective Candidates

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    Łukasz Pietrzyk

    2016-01-01

    Full Text Available Colorectal cancer (CRC is the third most common cancer in the world. The early detection of CRC, during the promotion/progression stages, is an enormous challenge for a successful outcome and remains a fundamental problem in clinical approach. Despite the continuous advancement in diagnostic and therapeutic methods, there is a need for discovery of sensitive and specific, noninvasive biomarkers. Tumor endothelial markers (TEMs are associated with tumor-specific angiogenesis and are potentially useful to discriminate between tumor and normal endothelium. The most promising TEMs for oncogenic signaling in CRC appeared to be the TEM1, TEM5, TEM7, and TEM8. Overexpression of TEMs especially TEM1, TEM7, and TEM8 in colorectal tumor tissue compared to healthy tissue suggests their role in tumor blood vessels formation. Thus TEMs appear to be perspective candidates for early detection, monitoring, and treatment of CRC patients. This review provides an update on recent data on tumor endothelial markers and their possible use as biomarkers for screening, diagnosis, and therapy of colorectal cancer patients.

  11. Biomarkers Discovery for Colorectal Cancer: A Review on Tumor Endothelial Markers as Perspective Candidates.

    Science.gov (United States)

    Pietrzyk, Łukasz

    2016-01-01

    Colorectal cancer (CRC) is the third most common cancer in the world. The early detection of CRC, during the promotion/progression stages, is an enormous challenge for a successful outcome and remains a fundamental problem in clinical approach. Despite the continuous advancement in diagnostic and therapeutic methods, there is a need for discovery of sensitive and specific, noninvasive biomarkers. Tumor endothelial markers (TEMs) are associated with tumor-specific angiogenesis and are potentially useful to discriminate between tumor and normal endothelium. The most promising TEMs for oncogenic signaling in CRC appeared to be the TEM1, TEM5, TEM7, and TEM8. Overexpression of TEMs especially TEM1, TEM7, and TEM8 in colorectal tumor tissue compared to healthy tissue suggests their role in tumor blood vessels formation. Thus TEMs appear to be perspective candidates for early detection, monitoring, and treatment of CRC patients. This review provides an update on recent data on tumor endothelial markers and their possible use as biomarkers for screening, diagnosis, and therapy of colorectal cancer patients.

  12. Averaged differential expression for the discovery of biomarkers in the blood of patients with prostate cancer.

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    V Uma Bai

    Full Text Available The identification of a blood-based diagnostic marker is a goal in many areas of medicine, including the early diagnosis of prostate cancer. We describe the use of averaged differential display as an efficient mechanism for biomarker discovery in whole blood RNA. The process of averaging reduces the problem of clinical heterogeneity while simultaneously minimizing sample handling.RNA was isolated from the blood of prostate cancer patients and healthy controls. Samples were pooled and subjected to the averaged differential display process. Transcripts present at different levels between patients and controls were purified and sequenced for identification. Transcript levels in the blood of prostate cancer patients and controls were verified by quantitative RT-PCR. Means were compared using a t-test and a receiver-operating curve was generated. The Ring finger protein 19A (RNF19A transcript was identified as having higher levels in prostate cancer patients compared to healthy men through the averaged differential display process. Quantitative RT-PCR analysis confirmed a more than 2-fold higher level of RNF19A mRNA levels in the blood of patients with prostate cancer than in healthy controls (p = 0.0066. The accuracy of distinguishing cancer patients from healthy men using RNF19A mRNA levels in blood as determined by the area under the receiving operator curve was 0.727.Averaged differential display offers a simplified approach for the comprehensive screening of body fluids, such as blood, to identify biomarkers in patients with prostate cancer. Furthermore, this proof-of-concept study warrants further analysis of RNF19A as a clinically relevant biomarker for prostate cancer detection.

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

    Directory of Open Access Journals (Sweden)

    Ding Yijun

    2012-07-01

    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

  14. atBioNet--an integrated network analysis tool for genomics and biomarker discovery.

    Science.gov (United States)

    Ding, Yijun; Chen, Minjun; Liu, Zhichao; Ding, Don; Ye, Yanbin; Zhang, Min; Kelly, Reagan; Guo, Li; Su, Zhenqiang; Harris, Stephen C; Qian, Feng; Ge, Weigong; Fang, Hong; Xu, Xiaowei; Tong, Weida

    2012-07-20

    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. 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. 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://www.fda.gov/ScienceResearch/BioinformaticsTools/ucm285284.htm.

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

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    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

  16. Application in pesticide analysis: Liquid chromatography - A review of the state of science for biomarker discovery and identification

    Science.gov (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...

  17. Topic model-based mass spectrometric data analysis in cancer biomarker discovery studies.

    Science.gov (United States)

    Wang, Minkun; Tsai, Tsung-Heng; Di Poto, Cristina; Ferrarini, Alessia; Yu, Guoqiang; Ressom, Habtom W

    2016-08-18

    A fundamental challenge in quantitation of biomolecules for cancer biomarker discovery is owing to the heterogeneous nature of human biospecimens. Although this issue has been a subject of discussion in cancer genomic studies, it has not yet been rigorously investigated in mass spectrometry based proteomic and metabolomic studies. Purification of mass spectometric data is highly desired prior to subsequent analysis, e.g., quantitative comparison of the abundance of biomolecules in biological samples. We investigated topic models to computationally analyze mass spectrometric data considering both integrated peak intensities and scan-level features, i.e., extracted ion chromatograms (EICs). Probabilistic generative models enable flexible representation in data structure and infer sample-specific pure resources. Scan-level modeling helps alleviate information loss during data preprocessing. We evaluated the capability of the proposed models in capturing mixture proportions of contaminants and cancer profiles on LC-MS based serum proteomic and GC-MS based tissue metabolomic datasets acquired from patients with hepatocellular carcinoma (HCC) and liver cirrhosis as well as synthetic data we generated based on the serum proteomic data. The results we obtained by analysis of the synthetic data demonstrated that both intensity-level and scan-level purification models can accurately infer the mixture proportions and the underlying true cancerous sources with small average error ratios (data, we found more proteins and metabolites with significant changes between HCC cases and cirrhotic controls. Candidate biomarkers selected after purification yielded biologically meaningful pathway analysis results and improved disease discrimination power in terms of the area under ROC curve compared to the results found prior to purification. We investigated topic model-based inference methods to computationally address the heterogeneity issue in samples analyzed by LC/GC-MS. We observed

  18. Discovery of prognostic biomarker candidates of lacunar infarction by quantitative proteomics of microvesicles enriched plasma.

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    Arnab Datta

    Full Text Available Lacunar infarction (LACI is a subtype of acute ischemic stroke affecting around 25% of all ischemic stroke cases. Despite having an excellent recovery during acute phase, certain LACI patients have poor mid- to long-term prognosis due to the recurrence of vascular events or a decline in cognitive functions. Hence, blood-based biomarkers could be complementary prognostic and research tools.Plasma was collected from forty five patients following a non-disabling LACI along with seventeen matched control subjects. The LACI patients were monitored prospectively for up to five years for the occurrence of adverse outcomes and grouped accordingly (i.e., LACI-no adverse outcome, LACI-recurrent vascular event, and LACI-cognitive decline without any recurrence of vascular events. Microvesicles-enriched fractions isolated from the pooled plasma of four groups were profiled by an iTRAQ-guided discovery approach to quantify the differential proteome. The data have been deposited to the ProteomeXchange with identifier PXD000748. Bioinformatics analysis and data mining revealed up-regulation of brain-specific proteins including myelin basic protein, proteins of coagulation cascade (e.g., fibrinogen alpha chain, fibrinogen beta chain and focal adhesion (e.g., integrin alpha-IIb, talin-1, and filamin-A while albumin was down-regulated in both groups of patients with adverse outcome.This data set may offer important insight into the mechanisms of poor prognosis and provide candidate prognostic biomarkers for validation on larger cohort of individual LACI patients.

  19. Predictive Power Estimation Algorithm (PPEA--a new algorithm to reduce overfitting for genomic biomarker discovery.

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    Jiangang Liu

    Full Text Available Toxicogenomics promises to aid in predicting adverse effects, understanding the mechanisms of drug action or toxicity, and uncovering unexpected or secondary pharmacology. However, modeling adverse effects using high dimensional and high noise genomic data is prone to over-fitting. Models constructed from such data sets often consist of a large number of genes with no obvious functional relevance to the biological effect the model intends to predict that can make it challenging to interpret the modeling results. To address these issues, we developed a novel algorithm, Predictive Power Estimation Algorithm (PPEA, which estimates the predictive power of each individual transcript through an iterative two-way bootstrapping procedure. By repeatedly enforcing that the sample number is larger than the transcript number, in each iteration of modeling and testing, PPEA reduces the potential risk of overfitting. We show with three different cases studies that: (1 PPEA can quickly derive a reliable rank order of predictive power of individual transcripts in a relatively small number of iterations, (2 the top ranked transcripts tend to be functionally related to the phenotype they are intended to predict, (3 using only the most predictive top ranked transcripts greatly facilitates development of multiplex assay such as qRT-PCR as a biomarker, and (4 more importantly, we were able to demonstrate that a small number of genes identified from the top-ranked transcripts are highly predictive of phenotype as their expression changes distinguished adverse from nonadverse effects of compounds in completely independent tests. Thus, we believe that the PPEA model effectively addresses the over-fitting problem and can be used to facilitate genomic biomarker discovery for predictive toxicology and drug responses.

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

    Energy Technology Data Exchange (ETDEWEB)

    Smith, Richard D.

    2012-03-01

    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

  1. Quantitative, multiplexed workflow for deep analysis of human blood plasma and biomarker discovery by mass spectrometry.

    Science.gov (United States)

    Keshishian, Hasmik; Burgess, Michael W; Specht, Harrison; Wallace, Luke; Clauser, Karl R; Gillette, Michael A; Carr, Steven A

    2017-08-01

    Proteomic characterization of blood plasma is of central importance to clinical proteomics and particularly to biomarker discovery studies. The vast dynamic range and high complexity of the plasma proteome have, however, proven to be serious challenges and have often led to unacceptable tradeoffs between depth of coverage and sample throughput. We present an optimized sample-processing pipeline for analysis of the human plasma proteome that provides greatly increased depth of detection, improved quantitative precision and much higher sample analysis throughput as compared with prior methods. The process includes abundant protein depletion, isobaric labeling at the peptide level for multiplexed relative quantification and ultra-high-performance liquid chromatography coupled to accurate-mass, high-resolution tandem mass spectrometry analysis of peptides fractionated off-line by basic pH reversed-phase (bRP) chromatography. The overall reproducibility of the process, including immunoaffinity depletion, is high, with a process replicate coefficient of variation (CV) of 4,500 proteins are detected and quantified per patient sample on average, with two or more peptides per protein and starting from as little as 200 μl of plasma. The approach can be multiplexed up to 10-plex using tandem mass tags (TMT) reagents, further increasing throughput, albeit with some decrease in the number of proteins quantified. In addition, we provide a rapid protocol for analysis of nonfractionated depleted plasma samples analyzed in 10-plex. This provides ∼600 quantified proteins for each of the ten samples in ∼5 h of instrument time.

  2. The use of time-resolved fluorescence in gel-based proteomics for improved biomarker discovery

    Science.gov (United States)

    Sandberg, AnnSofi; Buschmann, Volker; Kapusta, Peter; Erdmann, Rainer; Wheelock, Åsa M.

    2010-02-01

    This paper describes a new platform for quantitative intact proteomics, entitled Cumulative Time-resolved Emission 2-Dimensional Gel Electrophoresis (CuTEDGE). The CuTEDGE technology utilizes differences in fluorescent lifetimes to subtract the confounding background fluorescence during in-gel detection and quantification of proteins, resulting in a drastic improvement in both sensitivity and dynamic range compared to existing technology. The platform is primarily designed for image acquisition in 2-dimensional gel electrophoresis (2-DE), but is also applicable to 1-dimensional gel electrophoresis (1-DE), and proteins electroblotted to membranes. In a set of proof-of-principle measurements, we have evaluated the performance of the novel technology using the MicroTime 100 instrument (PicoQuant GmbH) in conjunction with the CyDye minimal labeling fluorochromes (GE Healthcare, Uppsala, Sweden) to perform differential gel electrophoresis (DIGE) analyses. The results indicate that the CuTEDGE technology provides an improvement in the dynamic range and sensitivity of detection of 3 orders of magnitude as compared to current state-of-the-art image acquisition instrumentation available for 2-DE (Typhoon 9410, GE Healthcare). Given the potential dynamic range of 7-8 orders of magnitude and sensitivities in the attomol range, the described invention represents a technological leap in detection of low abundance cellular proteins, which is desperately needed in the field of biomarker discovery.

  3. Analytical Pipeline for Discovery and Verification of Glycoproteins from Plasma-Derived Extracellular Vesicles as Breast Cancer Biomarkers.

    Science.gov (United States)

    Chen, I-Hsuan; Aguilar, Hillary Andaluz; Paez Paez, J Sebastian; Wu, Xiaofeng; Pan, Li; Wendt, Michael K; Iliuk, Anton B; Zhang, Ying; Tao, W Andy

    2018-05-15

    Glycoproteins comprise more than half of current FDA-approved protein cancer markers, but the development of new glycoproteins as disease biomarkers has been stagnant. Here we present a pipeline to develop glycoproteins from extracellular vesicles (EVs) through integrating quantitative glycoproteomics with a novel reverse phase glycoprotein array and then apply it to identify novel biomarkers for breast cancer. EV glycoproteomics show promise in circumventing the problems plaguing current serum/plasma glycoproteomics and allowed us to identify hundreds of glycoproteins that have not been identified in blood. We identified 1,453 unique glycopeptides representing 556 glycoproteins in EVs, among which 20 were verified significantly higher in individual breast cancer patients. We further applied a novel glyco-specific reverse phase protein array to quantify a subset of the candidates. Together, this study demonstrates the great potential of this integrated pipeline for biomarker discovery.

  4. Biomarker Discovery Using New Metabolomics Software for Automated Processing of High Resolution LC-MS Data

    Science.gov (United States)

    Hnatyshyn, S.; Reily, M.; Shipkova, P.; McClure, T.; Sanders, M.; Peake, D.

    2011-01-01

    Robust biomarkers of target engagement and efficacy are required in different stages of drug discovery. Liquid chromatography coupled to high resolution mass spectrometry provides sensitivity, accuracy and wide dynamic range required for identification of endogenous metabolites in biological matrices. LCMS is widely-used tool for biomarker identification and validation. Typical high resolution LCMS profiles from biological samples may contain greater than a million mass spectral peaks corresponding to several thousand endogenous metabolites. Reduction of the total number of peaks, component identification and statistical comparison across sample groups remains to be a difficult and time consuming challenge. Blood samples from four groups of rats (male vs. female, fully satiated and food deprived) were analyzed using high resolution accurate mass (HRAM) LCMS. All samples were separated using a 15 minute reversed-phase C18 LC gradient and analyzed in both positive and negative ion modes. Data was acquired using 15K resolution and 5ppm mass measurement accuracy. The entire data set was analyzed using software developed in collaboration between Bristol Meyers Squibb and Thermo Fisher Scientific to determine the metabolic effects of food deprivation on rats. Metabolomic LC-MS data files are extraordinarily complex and appropriate reduction of the number of spectral peaks via identification of related peaks and background removal is essential. A single component such as hippuric acid generates more than 20 related peaks including isotopic clusters, adducts and dimers. Plasma and urine may contain 500-1500 unique quantifiable metabolites. Noise filtering approaches including blank subtraction were used to reduce the number of irrelevant peaks. By grouping related signals such as isotopic peaks and alkali adducts, data processing was greatly simplified by reducing the total number of components by 10-fold. The software processes 48 samples in under 60minutes. Principle

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

    Directory of Open Access Journals (Sweden)

    Nodin Björn

    2012-01-01

    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

  6. SkyDiscovery: Humans and Machines Working Together

    Science.gov (United States)

    Donalek, Ciro; Fang, K.; Drake, A. J.; Djorgovski, S. G.; Graham, M. J.; Mahabal, A.; Williams, R.

    2011-01-01

    Synoptic sky surveys are now discovering tens to hundreds of transient events every clear night, and that data rate is expected to increase dramatically as we move towards the LSST. A key problem is classification of transients, which determines their scientific interest and possible follow-up. Some of the relevant information is contextual, and easily recognizable by humans looking at images, but it is very hard to encode in the data pipelines. Crowdsourcing (aka Citizen Science) provides one possible way to gather such information. SkyDiscovery.org is a website that allows experts and citizen science enthusiasts to work together and share information in a collaborative scientific discovery environment. Currently there are two projects running on the website. In the Event Classification project users help finding candidate transients through a series of questions related to the images shown. Event classification depends very much form the contextual information and humans are remarkably effective at recognizing noise in incomplete heterogeneous data and figuring out which contextual information is important. In the SNHunt project users are requested to look for new objects appearing on images of galaxies taken by the Catalina Real-time Transient Survey, in order to find all the supernovae occurring in nearby bright galaxies. Images are served alongside with other tools that can help the discovery. A multi level approach allows the complexity of the interface to be tailored to the expertise level of the user. An entry level user can just review images and validate events as being real, while a more advanced user would be able to interact with the data associated to an event. The data gathered will not be only analyzed and used directly for some specific science project, but also to train well-defined algorithms to be used in automating such data analysis in the future.

  7. Guidelines for Biomarker of Food Intake Reviews (BFIRev): how to conduct an extensive literature search for biomarker of food intake discovery.

    Science.gov (United States)

    Praticò, Giulia; Gao, Qian; Scalbert, Augustin; Vergères, Guy; Kolehmainen, Marjukka; Manach, Claudine; Brennan, Lorraine; Pedapati, Sri Harsha; Afman, Lydia A; Wishart, David S; Vázquez-Fresno, Rosa; Lacueva, Cristina Andres; Garcia-Aloy, Mar; Verhagen, Hans; Feskens, Edith J M; Dragsted, Lars O

    2018-01-01

    Identification of new biomarkers of food and nutrient intake has developed fast over the past two decades and could potentially provide important new tools for compliance monitoring and dietary intake assessment in nutrition and health science. In recent years, metabolomics has played an important role in identifying a large number of putative biomarkers of food intake (BFIs). However, the large body of scientific literature on potential BFIs outside the metabolomics area should also be taken into account. In particular, we believe that extensive literature reviews should be conducted and that the quality of all suggested biomarkers should be systematically evaluated. In order to cover the literature on BFIs in the most appropriate and consistent manner, there is a need for appropriate guidelines on this topic. These guidelines should build upon guidelines in related areas of science while targeting the special needs of biomarker methodology. This document provides a guideline for conducting an extensive literature search on BFIs, which will provide the basis to systematically validate BFIs. This procedure will help to prioritize future work on the identification of new potential biomarkers and on validating these as well as other biomarker candidates, thereby providing better tools for future studies in nutrition and health.

  8. Guidelines for Biomarker of Food Intake Reviews (BFIRev: how to conduct an extensive literature search for biomarker of food intake discovery

    Directory of Open Access Journals (Sweden)

    Giulia Praticò

    2018-02-01

    Full Text Available Abstract Identification of new biomarkers of food and nutrient intake has developed fast over the past two decades and could potentially provide important new tools for compliance monitoring and dietary intake assessment in nutrition and health science. In recent years, metabolomics has played an important role in identifying a large number of putative biomarkers of food intake (BFIs. However, the large body of scientific literature on potential BFIs outside the metabolomics area should also be taken into account. In particular, we believe that extensive literature reviews should be conducted and that the quality of all suggested biomarkers should be systematically evaluated. In order to cover the literature on BFIs in the most appropriate and consistent manner, there is a need for appropriate guidelines on this topic. These guidelines should build upon guidelines in related areas of science while targeting the special needs of biomarker methodology. This document provides a guideline for conducting an extensive literature search on BFIs, which will provide the basis to systematically validate BFIs. This procedure will help to prioritize future work on the identification of new potential biomarkers and on validating these as well as other biomarker candidates, thereby providing better tools for future studies in nutrition and health.

  9. Using MALDI-IMS and MRM to stablish a pipeline for discovery and validation of tumor neovasculature biomarker candidates. — EDRN Public Portal

    Science.gov (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

  10. SWATHtoMRM: Development of High-Coverage Targeted Metabolomics Method Using SWATH Technology for Biomarker Discovery.

    Science.gov (United States)

    Zha, Haihong; Cai, Yuping; Yin, Yandong; Wang, Zhuozhong; Li, Kang; Zhu, Zheng-Jiang

    2018-03-20

    The complexity of metabolome presents a great analytical challenge for quantitative metabolite profiling, and restricts the application of metabolomics in biomarker discovery. Targeted metabolomics using multiple-reaction monitoring (MRM) technique has excellent capability for quantitative analysis, but suffers from the limited metabolite coverage. To address this challenge, we developed a new strategy, namely, SWATHtoMRM, which utilizes the broad coverage of SWATH-MS technology to develop high-coverage targeted metabolomics method. Specifically, SWATH-MS technique was first utilized to untargeted profile one pooled biological sample and to acquire the MS 2 spectra for all metabolites. Then, SWATHtoMRM was used to extract the large-scale MRM transitions for targeted analysis with coverage as high as 1000-2000 metabolites. Then, we demonstrated the advantages of SWATHtoMRM method in quantitative analysis such as coverage, reproducibility, sensitivity, and dynamic range. Finally, we applied our SWATHtoMRM approach to discover potential metabolite biomarkers for colorectal cancer (CRC) diagnosis. A high-coverage targeted metabolomics method with 1303 metabolites in one injection was developed to profile colorectal cancer tissues from CRC patients. A total of 20 potential metabolite biomarkers were discovered and validated for CRC diagnosis. In plasma samples from CRC patients, 17 out of 20 potential biomarkers were further validated to be associated with tumor resection, which may have a great potential in assessing the prognosis of CRC patients after tumor resection. Together, the SWATHtoMRM strategy provides a new way to develop high-coverage targeted metabolomics method, and facilitates the application of targeted metabolomics in disease biomarker discovery. The SWATHtoMRM program is freely available on the Internet ( http://www.zhulab.cn/software.php ).

  11. 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.

    2010-01-01

    -cancer agents. The consortium focuses on the identification of reliable predictive biomarkers to approved agents with anti-angiogenic activity for which no reliable predictive biomarkers exist: sunitinib, a multi-targeted tyrosine kinase inhibitor and everolimus, a mammalian target of rapamycin (mTOR) pathway...

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

    Directory of Open Access Journals (Sweden)

    Kaur Parminder

    2012-08-01

    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

  13. Metabolomics as a Tool for Discovery of Biomarkers of Autism Spectrum Disorder in the Blood Plasma of Children

    Science.gov (United States)

    West, Paul R.; Amaral, David G.; Bais, Preeti; Smith, Alan M.; Egnash, Laura A.; Ross, Mark E.; Palmer, Jessica A.; Fontaine, Burr R.; Conard, Kevin R.; Corbett, Blythe A.; Cezar, Gabriela G.; Donley, Elizabeth L. R.; Burrier, Robert E.

    2014-01-01

    Background The diagnosis of autism spectrum disorder (ASD) at the earliest age possible is important for initiating optimally effective intervention. In the United States the average age of diagnosis is 4 years. Identifying metabolic biomarker signatures of ASD from blood samples offers an opportunity for development of diagnostic tests for detection of ASD at an early age. Objectives To discover metabolic features present in plasma samples that can discriminate children with ASD from typically developing (TD) children. The ultimate goal is to identify and develop blood-based ASD biomarkers that can be validated in larger clinical trials and deployed to guide individualized therapy and treatment. Methods Blood plasma was obtained from children aged 4 to 6, 52 with ASD and 30 age-matched TD children. Samples were analyzed using 5 mass spectrometry-based methods designed to orthogonally measure a broad range of metabolites. Univariate, multivariate and machine learning methods were used to develop models to rank the importance of features that could distinguish ASD from TD. Results A set of 179 statistically significant features resulting from univariate analysis were used for multivariate modeling. Subsets of these features properly classified the ASD and TD samples in the 61-sample training set with average accuracies of 84% and 86%, and with a maximum accuracy of 81% in an independent 21-sample validation set. Conclusions This analysis of blood plasma metabolites resulted in the discovery of biomarkers that may be valuable in the diagnosis of young children with ASD. The results will form the basis for additional discovery and validation research for 1) determining biomarkers to develop diagnostic tests to detect ASD earlier and improve patient outcomes, 2) gaining new insight into the biochemical mechanisms of various subtypes of ASD 3) identifying biomolecular targets for new modes of therapy, and 4) providing the basis for individualized treatment

  14. Metabolomics as a tool for discovery of biomarkers of autism spectrum disorder in the blood plasma of children.

    Directory of Open Access Journals (Sweden)

    Paul R West

    Full Text Available The diagnosis of autism spectrum disorder (ASD at the earliest age possible is important for initiating optimally effective intervention. In the United States the average age of diagnosis is 4 years. Identifying metabolic biomarker signatures of ASD from blood samples offers an opportunity for development of diagnostic tests for detection of ASD at an early age.To discover metabolic features present in plasma samples that can discriminate children with ASD from typically developing (TD children. The ultimate goal is to identify and develop blood-based ASD biomarkers that can be validated in larger clinical trials and deployed to guide individualized therapy and treatment.Blood plasma was obtained from children aged 4 to 6, 52 with ASD and 30 age-matched TD children. Samples were analyzed using 5 mass spectrometry-based methods designed to orthogonally measure a broad range of metabolites. Univariate, multivariate and machine learning methods were used to develop models to rank the importance of features that could distinguish ASD from TD.A set of 179 statistically significant features resulting from univariate analysis were used for multivariate modeling. Subsets of these features properly classified the ASD and TD samples in the 61-sample training set with average accuracies of 84% and 86%, and with a maximum accuracy of 81% in an independent 21-sample validation set.This analysis of blood plasma metabolites resulted in the discovery of biomarkers that may be valuable in the diagnosis of young children with ASD. The results will form the basis for additional discovery and validation research for 1 determining biomarkers to develop diagnostic tests to detect ASD earlier and improve patient outcomes, 2 gaining new insight into the biochemical mechanisms of various subtypes of ASD 3 identifying biomolecular targets for new modes of therapy, and 4 providing the basis for individualized treatment recommendations.

  15. Discovery of Novel Biomarkers for Alzheimer’s Disease from Blood

    Directory of Open Access Journals (Sweden)

    Jintao Long

    2016-01-01

    Full Text Available Blood-based biomarkers for Alzheimer’s disease would be very valuable because blood is a more accessible biofluid and is suitable for repeated sampling. However, currently there are no robust and reliable blood-based biomarkers for practical diagnosis. In this study we used a knowledge-based protein feature pool and two novel support vector machine embedded feature selection methods to find panels consisting of two and three biomarkers. We validated these biomarker sets using another serum cohort and an RNA profile cohort from the brain. Our panels included the proteins ECH1, NHLRC2, HOXB7, FN1, ERBB2, and SLC6A13 and demonstrated promising sensitivity (>87%, specificity (>91%, and accuracy (>89%.

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

    International Nuclear Information System (INIS)

    Kumar, Bhowmik Salil; Lee, Young-Joo; Yi, Hong Jae; Chung, Bong Chul; Jung, Byung Hwa

    2010-01-01

    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 -1 day -1 or 250 mg kg -1 day -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.

  17. 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: jbhluck@kist.re.kr [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)

    2010-02-19

    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.

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

    KAUST Repository

    Kaur, Mandeep

    2011-09-19

    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.

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

    KAUST Repository

    Kaur, Mandeep; MacPherson, Cameron R; Schmeier, Sebastian; Narasimhan, Kothandaraman; Choolani, Mahesh; Bajic, Vladimir B.

    2011-01-01

    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.

  20. 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

  1. A Comprehensive Workflow of Mass Spectrometry-Based Untargeted Metabolomics in Cancer Metabolic Biomarker Discovery Using Human Plasma and Urine

    Directory of Open Access Journals (Sweden)

    Jianwen She

    2013-09-01

    Full Text Available Current available biomarkers lack sensitivity and/or specificity for early detection of cancer. To address this challenge, a robust and complete workflow for metabolic profiling and data mining is described in details. Three independent and complementary analytical techniques for metabolic profiling are applied: hydrophilic interaction liquid chromatography (HILIC–LC, reversed-phase liquid chromatography (RP–LC, and gas chromatography (GC. All three techniques are coupled to a mass spectrometer (MS in the full scan acquisition mode, and both unsupervised and supervised methods are used for data mining. The univariate and multivariate feature selection are used to determine subsets of potentially discriminative predictors. These predictors are further identified by obtaining accurate masses and isotopic ratios using selected ion monitoring (SIM and data-dependent MS/MS and/or accurate mass MSn ion tree scans utilizing high resolution MS. A list combining all of the identified potential biomarkers generated from different platforms and algorithms is used for pathway analysis. Such a workflow combining comprehensive metabolic profiling and advanced data mining techniques may provide a powerful approach for metabolic pathway analysis and biomarker discovery in cancer research. Two case studies with previous published data are adapted and included in the context to elucidate the application of the workflow.

  2. 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

  3. voomDDA: discovery of diagnostic biomarkers and classification of RNA-seq data

    Directory of Open Access Journals (Sweden)

    Gokmen Zararsiz

    2017-10-01

    Full Text Available RNA-Seq is a recent and efficient technique that uses the capabilities of next-generation sequencing technology for characterizing and quantifying transcriptomes. One important task using gene-expression data is to identify a small subset of genes that can be used to build diagnostic classifiers particularly for cancer diseases. Microarray based classifiers are not directly applicable to RNA-Seq data due to its discrete nature. Overdispersion is another problem that requires careful modeling of mean and variance relationship of the RNA-Seq data. In this study, we present voomDDA classifiers: variance modeling at the observational level (voom extensions of the nearest shrunken centroids (NSC and the diagonal discriminant classifiers. VoomNSC is one of these classifiers and brings voom and NSC approaches together for the purpose of gene-expression based classification. For this purpose, we propose weighted statistics and put these weighted statistics into the NSC algorithm. The VoomNSC is a sparse classifier that models the mean-variance relationship using the voom method and incorporates voom’s precision weights into the NSC classifier via weighted statistics. A comprehensive simulation study was designed and four real datasets are used for performance assessment. The overall results indicate that voomNSC performs as the sparsest classifier. It also provides the most accurate results together with power-transformed Poisson linear discriminant analysis, rlog transformed support vector machines and random forests algorithms. In addition to prediction purposes, the voomNSC classifier can be used to identify the potential diagnostic biomarkers for a condition of interest. Through this work, statistical learning methods proposed for microarrays can be reused for RNA-Seq data. An interactive web application is freely available at http://www.biosoft.hacettepe.edu.tr/voomDDA/.

  4. voomDDA: discovery of diagnostic biomarkers and classification of RNA-seq data.

    Science.gov (United States)

    Zararsiz, Gokmen; Goksuluk, Dincer; Klaus, Bernd; Korkmaz, Selcuk; Eldem, Vahap; Karabulut, Erdem; Ozturk, Ahmet

    2017-01-01

    RNA-Seq is a recent and efficient technique that uses the capabilities of next-generation sequencing technology for characterizing and quantifying transcriptomes. One important task using gene-expression data is to identify a small subset of genes that can be used to build diagnostic classifiers particularly for cancer diseases. Microarray based classifiers are not directly applicable to RNA-Seq data due to its discrete nature. Overdispersion is another problem that requires careful modeling of mean and variance relationship of the RNA-Seq data. In this study, we present voomDDA classifiers: variance modeling at the observational level (voom) extensions of the nearest shrunken centroids (NSC) and the diagonal discriminant classifiers. VoomNSC is one of these classifiers and brings voom and NSC approaches together for the purpose of gene-expression based classification. For this purpose, we propose weighted statistics and put these weighted statistics into the NSC algorithm. The VoomNSC is a sparse classifier that models the mean-variance relationship using the voom method and incorporates voom's precision weights into the NSC classifier via weighted statistics. A comprehensive simulation study was designed and four real datasets are used for performance assessment. The overall results indicate that voomNSC performs as the sparsest classifier. It also provides the most accurate results together with power-transformed Poisson linear discriminant analysis, rlog transformed support vector machines and random forests algorithms. In addition to prediction purposes, the voomNSC classifier can be used to identify the potential diagnostic biomarkers for a condition of interest. Through this work, statistical learning methods proposed for microarrays can be reused for RNA-Seq data. An interactive web application is freely available at http://www.biosoft.hacettepe.edu.tr/voomDDA/.

  5. Mass Spectrometry-Based Serum Proteomics for Biomarker Discovery and Validation.

    Science.gov (United States)

    Bhosale, Santosh D; Moulder, Robert; Kouvonen, Petri; Lahesmaa, Riitta; Goodlett, David R

    2017-01-01

    Blood protein measurements are used frequently in the clinic in the assessment of patient health. Nevertheless, there remains the need for new biomarkers with better diagnostic specificities. With the advent of improved technology for bioanalysis and the growth of biobanks including collections from specific disease risk cohorts, the plasma proteome has remained a target of proteomics research toward the characterization of disease-related biomarkers. The following protocol presents a workflow for serum/plasma proteomics including details of sample preparation both with and without immunoaffinity depletion of the most abundant plasma proteins and methodology for selected reaction monitoring mass spectrometry validation.

  6. Mining PubMed for Biomarker-Disease Associations to Guide Discovery

    OpenAIRE

    Jessen, Walter; Landschulz, Katherine; Turi, Thomas; Reams, Rachel

    2012-01-01

    Biomedical knowledge is growing exponentially; however, meta-knowledge around the data is often lacking. PubMed is a database comprising more than 21 million citations for biomedical literature from MEDLINE and additional life science journals dating back to the 1950s. To explore the use and frequency of biomarkers across human disease, we mined PubMed for biomarker-disease associations. We then ranked the top 100 linked diseases by relevance and mapped them to medical subject headings (MeSH)...

  7. Proteomics pipeline for biomarker discovery of laser capture microdissected breast cancer tissue

    NARCIS (Netherlands)

    N.Q. Liu (Ning Qing); R.B.H. Braakman (René); C. Stingl (Christoph); T.M. Luider (Theo); J.W.M. Martens (John); J.A. Foekens (John); A. Umar (Arzu)

    2012-01-01

    textabstractMass spectrometry (MS)-based label-free proteomics offers an unbiased approach to screen biomarkers related to disease progression and therapy-resistance of breast cancer on the global scale. However, multi-step sample preparation can introduce large variation in generated data, while

  8. Quantitative proteomic analysis of microdissected oral epithelium for cancer biomarker discovery.

    Science.gov (United States)

    Xiao, Hua; Langerman, Alexander; Zhang, Yan; Khalid, Omar; Hu, Shen; Cao, Cheng-Xi; Lingen, Mark W; Wong, David T W

    2015-11-01

    Specific biomarkers are urgently needed for the detection and progression of oral cancer. The objective of this study was to discover cancer biomarkers from oral epithelium through utilizing high throughput quantitative proteomics approaches. Morphologically malignant, epithelial dysplasia, and adjacent normal epithelial tissues were laser capture microdissected (LCM) from 19 patients and used for proteomics analysis. Total proteins from each group were extracted, digested and then labelled with corresponding isobaric tags for relative and absolute quantitation (iTRAQ). Labelled peptides from each sample were combined and analyzed by liquid chromatography-mass spectrometry (LC-MS/MS) for protein identification and quantification. In total, 500 proteins were identified and 425 of them were quantified. When compared with adjacent normal oral epithelium, 17 and 15 proteins were consistently up-regulated or down-regulated in malignant and epithelial dysplasia, respectively. Half of these candidate biomarkers were discovered for oral cancer for the first time. Cornulin was initially confirmed in tissue protein extracts and was further validated in tissue microarray. Its presence in the saliva of oral cancer patients was also explored. Myoglobin and S100A8 were pre-validated by tissue microarray. These data demonstrated that the proteomic biomarkers discovered through this strategy are potential targets for oral cancer detection and salivary diagnostics. Copyright © 2015 Elsevier Ltd. All rights reserved.

  9. Discovery of Biochemical Biomarkers for Aggression: A Role for Metabolomics in Psychiatry

    NARCIS (Netherlands)

    Hagenbeek, F.A.; Kluft, C.; Hankemeier, T.; Bartels, M.; Draisma, H.H.M.; Middeldorp, C.M.; Berger, R.; Noto, A.; Lussu, M.; Pool, R.; Fanos, V.; Boomsma, D.I.

    2016-01-01

    Human aggression encompasses a wide range of behaviors and is related to many psychiatric disorders. We introduce the different classification systems of aggression and related disorders as a basis for discussing biochemical biomarkers and then present an overview of studies in humans (published

  10. Development of a universal metabolome-standard method for long-term LC-MS metabolome profiling and its application for bladder cancer urine-metabolite-biomarker discovery.

    Science.gov (United States)

    Peng, Jun; Chen, Yi-Ting; Chen, Chien-Lun; Li, Liang

    2014-07-01

    Large-scale metabolomics study requires a quantitative method to generate metabolome data over an extended period with high technical reproducibility. We report a universal metabolome-standard (UMS) method, in conjunction with chemical isotope labeling liquid chromatography-mass spectrometry (LC-MS), to provide long-term analytical reproducibility and facilitate metabolome comparison among different data sets. In this method, UMS of a specific type of sample labeled by an isotope reagent is prepared a priori. The UMS is spiked into any individual samples labeled by another form of the isotope reagent in a metabolomics study. The resultant mixture is analyzed by LC-MS to provide relative quantification of the individual sample metabolome to UMS. UMS is independent of a study undertaking as well as the time of analysis and useful for profiling the same type of samples in multiple studies. In this work, the UMS method was developed and applied for a urine metabolomics study of bladder cancer. UMS of human urine was prepared by (13)C2-dansyl labeling of a pooled sample from 20 healthy individuals. This method was first used to profile the discovery samples to generate a list of putative biomarkers potentially useful for bladder cancer detection and then used to analyze the verification samples about one year later. Within the discovery sample set, three-month technical reproducibility was examined using a quality control sample and found a mean CV of 13.9% and median CV of 9.4% for all the quantified metabolites. Statistical analysis of the urine metabolome data showed a clear separation between the bladder cancer group and the control group from the discovery samples, which was confirmed by the verification samples. Receiver operating characteristic (ROC) test showed that the area under the curve (AUC) was 0.956 in the discovery data set and 0.935 in the verification data set. These results demonstrated the utility of the UMS method for long-term metabolomics and

  11. Three-Dimensionally Functionalized Reverse Phase Glycoprotein Array for Cancer Biomarker Discovery and Validation.

    Science.gov (United States)

    Pan, Li; Aguilar, Hillary Andaluz; Wang, Linna; Iliuk, Anton; Tao, W Andy

    2016-11-30

    Glycoproteins have vast structural diversity that plays an important role in many biological processes and have great potential as disease biomarkers. Here, we report a novel functionalized reverse phase protein array (RPPA), termed polymer-based reverse phase glycoprotein array (polyGPA), to capture and profile glycoproteomes specifically, and validate glycoproteins. Nitrocellulose membrane functionalized with globular hydroxyaminodendrimers was used to covalently capture preoxidized glycans on glycoproteins from complex protein samples such as biofluids. The captured glycoproteins were subsequently detected using the same validated antibodies as in RPPA. We demonstrated the outstanding specificity, sensitivity, and quantitative capabilities of polyGPA by capturing and detecting purified as well as endogenous α-1-acid glycoprotein (AGP) in human plasma. We further applied quantitative N-glycoproteomics and the strategy to validate a panel of glycoproteins identified as potential biomarkers for bladder cancer by analyzing urine glycoproteins from bladder cancer patients or matched healthy individuals.

  12. Three-dimensionally Functionalized Reverse Phase Glycoprotein Array for Cancer Biomarker Discovery and Validation

    OpenAIRE

    Pan, Li; Aguilar, Hillary Andaluz; Wang, Linna; Iliuk, Anton; Tao, W. Andy

    2016-01-01

    Glycoproteins have vast structural diversity which plays an important role in many biological processes and have great potential as disease biomarkers. Here we report a novel functionalized reverse phase protein array (RPPA), termed polymer-based reverse phase GlycoProtein Array (polyGPA), to specifically capture and profile glycoproteomes, and validate glycoproteins. Nitrocellulose membrane functionalized with globular hydroxyaminodendrimers was used to covalently capture pre-oxidized glycan...

  13. Use of biomarkers in the discovery of novel anti-schizophrenia drugs

    DEFF Research Database (Denmark)

    Mikkelsen, Jens D; Thomsen, Morten S; Hansen, Henrik H

    2010-01-01

    Schizophrenia is characterized by a diverse symptomatology that often includes positive, cognitive and negative symptoms. Current anti-schizophrenic drugs act at multiple receptors, but little is known about how each of these receptors contributes to their mechanisms of action. Screening of novel...... anti-schizophrenic drug candidates targeting single receptors will be based on biomarker assays that measure signalling pathways, transcriptional factors, epigenetic mechanisms and synaptic function and translate these effects to behavioural effects in animals and humans. This review discusses current...

  14. 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.

  15. Isolation and characterization of urinary extracellular vesicles: implications for biomarker discovery

    NARCIS (Netherlands)

    Merchant, M.L.; Rood, I.M.; Deegens, J.K.J.; Klein, J.B.

    2017-01-01

    Urine is a valuable diagnostic medium and, with the discovery of urinary extracellular vesicles, is viewed as a dynamic bioactive fluid. Extracellular vesicles are lipid-enclosed structures that can be classified into three categories: exosomes, microvesicles (or ectosomes) and apoptotic bodies.

  16. 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

    2007-01-01

    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

  17. Discovery and identification of potential biomarkers of pediatric Acute Lymphoblastic Leukemia

    Directory of Open Access Journals (Sweden)

    Cui Ziyou

    2009-03-01

    Full Text Available Abstract Background Acute lymphoblastic leukemia (ALL is a common form of cancer in children. Currently, bone marrow biopsy is used for diagnosis. Noninvasive biomarkers for the early diagnosis of pediatric ALL are urgently needed. The aim of this study was to discover potential protein biomarkers for pediatric ALL. Methods Ninety-four pediatric ALL patients and 84 controls were randomly divided into a "training" set (45 ALL patients, 34 healthy controls and a test set (49 ALL patients, 30 healthy controls and 30 pediatric acute myeloid leukemia (AML patients. Serum proteomic profiles were measured using surface-enhanced laser desorption/ionization-time-of-flight mass spectroscopy (SELDI-TOF-MS. A classification model was established by Biomarker Pattern Software (BPS. Candidate protein biomarkers were purified by HPLC, identified by LC-MS/MS and validated using ProteinChip immunoassays. Results A total of 7 protein peaks (9290 m/z, 7769 m/z, 15110 m/z, 7564 m/z, 4469 m/z, 8937 m/z, 8137 m/z were found with differential expression levels in the sera of pediatric ALL patients and controls using SELDI-TOF-MS and then analyzed by BPS to construct a classification model in the "training" set. The sensitivity and specificity of the model were found to be 91.8%, and 90.0%, respectively, in the test set. Two candidate protein peaks (7769 and 9290 m/z were found to be down-regulated in ALL patients, where these were identified as platelet factor 4 (PF4 and pro-platelet basic protein precursor (PBP. Two other candidate protein peaks (8137 and 8937 m/z were found up-regulated in the sera of ALL patients, and these were identified as fragments of the complement component 3a (C3a. Conclusion Platelet factor (PF4, connective tissue activating peptide III (CTAP-III and two fragments of C3a may be potential protein biomarkers of pediatric ALL and used to distinguish pediatric ALL patients from healthy controls and pediatric AML patients. Further studies with

  18. Discovery and identification of potential biomarkers of pediatric Acute Lymphoblastic Leukemia

    Science.gov (United States)

    Shi, Linan; Zhang, Jun; Wu, Peng; Feng, Kai; Li, Jing; Xie, Zhensheng; Xue, Peng; Cai, Tanxi; Cui, Ziyou; Chen, Xiulan; Hou, Junjie; Zhang, Jianzhong; Yang, Fuquan

    2009-01-01

    Background Acute lymphoblastic leukemia (ALL) is a common form of cancer in children. Currently, bone marrow biopsy is used for diagnosis. Noninvasive biomarkers for the early diagnosis of pediatric ALL are urgently needed. The aim of this study was to discover potential protein biomarkers for pediatric ALL. Methods Ninety-four pediatric ALL patients and 84 controls were randomly divided into a "training" set (45 ALL patients, 34 healthy controls) and a test set (49 ALL patients, 30 healthy controls and 30 pediatric acute myeloid leukemia (AML) patients). Serum proteomic profiles were measured using surface-enhanced laser desorption/ionization-time-of-flight mass spectroscopy (SELDI-TOF-MS). A classification model was established by Biomarker Pattern Software (BPS). Candidate protein biomarkers were purified by HPLC, identified by LC-MS/MS and validated using ProteinChip immunoassays. Results A total of 7 protein peaks (9290 m/z, 7769 m/z, 15110 m/z, 7564 m/z, 4469 m/z, 8937 m/z, 8137 m/z) were found with differential expression levels in the sera of pediatric ALL patients and controls using SELDI-TOF-MS and then analyzed by BPS to construct a classification model in the "training" set. The sensitivity and specificity of the model were found to be 91.8%, and 90.0%, respectively, in the test set. Two candidate protein peaks (7769 and 9290 m/z) were found to be down-regulated in ALL patients, where these were identified as platelet factor 4 (PF4) and pro-platelet basic protein precursor (PBP). Two other candidate protein peaks (8137 and 8937 m/z) were found up-regulated in the sera of ALL patients, and these were identified as fragments of the complement component 3a (C3a). Conclusion Platelet factor (PF4), connective tissue activating peptide III (CTAP-III) and two fragments of C3a may be potential protein biomarkers of pediatric ALL and used to distinguish pediatric ALL patients from healthy controls and pediatric AML patients. Further studies with additional

  19. Systematic biomarker discovery and coordinative validation for different primary nephrotic syndromes using gas chromatography-mass spectrometry.

    Science.gov (United States)

    Lee, Jung-Eun; Lee, Yu Ho; Kim, Se-Yun; Kim, Yang Gyun; Moon, Ju-Young; Jeong, Kyung-Hwan; Lee, Tae Won; Ihm, Chun-Gyoo; Kim, Sooah; Kim, Kyoung Heon; Kim, Dong Ki; Kim, Yon Su; Kim, Chan-Duck; Park, Cheol Whee; Lee, Do Yup; Lee, Sang-Ho

    2016-07-01

    The goal of this study is to identify systematic biomarker panel for primary nephrotic syndromes from urine samples by applying a non-target metabolite profiling, and to validate their utility in independent sampling and analysis by multiplex statistical approaches. Nephrotic syndrome (NS) is a nonspecific kidney disorder, which is mostly represented by minimal change disease (MCD), focal segmental glomerulosclerosis (FSGS), and membranous glomerulonephritis (MGN). Since urine metabolites may mirror disease-specific functional perturbations in kidney injury, we examined urine samples for distinctive metabolic changes to identify biomarkers for clinical applications. We developed unbiased multi-component covarianced models from a discovery set with 48 samples (12 healthy controls, 12 MCD, 12 FSGS, and 12 MGN). To extensively validate their diagnostic potential, new batch from 54 patients with primary NS were independently examined a year after. In the independent validation set, the model including citric acid, pyruvic acid, fructose, ethanolamine, and cysteine effectively discriminated each NS using receiver operating characteristic (ROC) analysis except MCD-MGN comparison; nonetheless an additional metabolite multi-composite greatly improved the discrimination power between MCD and MGN. Finally, we proposed the re-constructed metabolic network distinctively dysregulated by the different NSs that may deepen comprehensive understanding of the disease mechanistic, and help the enhanced identification of NS and therapeutic plans for future. Copyright © 2016 Elsevier B.V. All rights reserved.

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

    Directory of Open Access Journals (Sweden)

    Parida Shreemanta K

    2010-01-01

    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

  1. Multiple reaction monitoring (MRM)-profiling for biomarker discovery applied to human polycystic ovarian syndrome.

    Science.gov (United States)

    Cordeiro, Fernanda B; Ferreira, Christina R; Sobreira, Tiago Jose P; Yannell, Karen E; Jarmusch, Alan K; Cedenho, Agnaldo P; Lo Turco, Edson G; Cooks, R Graham

    2017-09-15

    We describe multiple reaction monitoring (MRM)-profiling, which provides accelerated discovery of discriminating molecular features, and its application to human polycystic ovary syndrome (PCOS) diagnosis. The discovery phase of the MRM-profiling seeks molecular features based on some prior knowledge of the chemical functional groups likely to be present in the sample. It does this through use of a limited number of pre-chosen and chemically specific neutral loss and/or precursor ion MS/MS scans. The output of the discovery phase is a set of precursor/product transitions. In the screening phase these MRM transitions are used to interrogate multiple samples (hence the name MRM-profiling). MRM-profiling was applied to follicular fluid samples of 22 controls and 29 clinically diagnosed PCOS patients. Representative samples were delivered by flow injection to a triple quadrupole mass spectrometer set to perform a number of pre-chosen and chemically specific neutral loss and/or precursor ion MS/MS scans. The output of this discovery phase was a set of 1012 precursor/product transitions. In the screening phase each individual sample was interrogated for these MRM transitions. Principal component analysis (PCA) and receiver operating characteristic (ROC) curves were used for statistical analysis. To evaluate the method's performance, half the samples were used to build a classification model (testing set) and half were blinded (validation set). Twenty transitions were used for the classification of the blind samples, most of them (N = 19) showed lower abundances in the PCOS group and corresponded to phosphatidylethanolamine (PE) and phosphatidylserine (PS) lipids. Agreement of 73% with clinical diagnosis was found when classifying the 26 blind samples. MRM-profiling is a supervised method characterized by its simplicity, speed and the absence of chromatographic separation. It can be used to rapidly isolate discriminating molecules in healthy/disease conditions by

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

    Directory of Open Access Journals (Sweden)

    Russell M. Morphew

    2014-06-01

    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.

  3. 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

  4. Discovery of Metabolic Biomarkers for Duchenne Muscular Dystrophy within a Natural History Study.

    Directory of Open Access Journals (Sweden)

    Simina M Boca

    Full Text Available Serum metabolite profiling in Duchenne muscular dystrophy (DMD may enable discovery of valuable molecular markers for disease progression and treatment response. Serum samples from 51 DMD patients from a natural history study and 22 age-matched healthy volunteers were profiled using liquid chromatography coupled to mass spectrometry (LC-MS for discovery of novel circulating serum metabolites associated with DMD. Fourteen metabolites were found significantly altered (1% false discovery rate in their levels between DMD patients and healthy controls while adjusting for age and study site and allowing for an interaction between disease status and age. Increased metabolites included arginine, creatine and unknown compounds at m/z of 357 and 312 while decreased metabolites included creatinine, androgen derivatives and other unknown yet to be identified compounds. Furthermore, the creatine to creatinine ratio is significantly associated with disease progression in DMD patients. This ratio sharply increased with age in DMD patients while it decreased with age in healthy controls. Overall, this study yielded promising metabolic signatures that could prove useful to monitor DMD disease progression and response to therapies in the future.

  5. Automated Morphological and Morphometric Analysis of Mass Spectrometry Imaging Data: Application to Biomarker Discovery

    Science.gov (United States)

    Picard de Muller, Gaël; Ait-Belkacem, Rima; Bonnel, David; Longuespée, Rémi; Stauber, Jonathan

    2017-12-01

    Mass spectrometry imaging datasets are mostly analyzed in terms of average intensity in regions of interest. However, biological tissues have different morphologies with several sizes, shapes, and structures. The important biological information, contained in this highly heterogeneous cellular organization, could be hidden by analyzing the average intensities. Finding an analytical process of morphology would help to find such information, describe tissue model, and support identification of biomarkers. This study describes an informatics approach for the extraction and identification of mass spectrometry image features and its application to sample analysis and modeling. For the proof of concept, two different tissue types (healthy kidney and CT-26 xenograft tumor tissues) were imaged and analyzed. A mouse kidney model and tumor model were generated using morphometric - number of objects and total surface - information. The morphometric information was used to identify m/z that have a heterogeneous distribution. It seems to be a worthwhile pursuit as clonal heterogeneity in a tumor is of clinical relevance. This study provides a new approach to find biomarker or support tissue classification with more information. [Figure not available: see fulltext.

  6. Urinary metabonomics study on toxicity biomarker discovery in rats treated with Xanthii Fructus.

    Science.gov (United States)

    Lu, Fang; Cao, Min; Wu, Bin; Li, Xu-zhao; Liu, Hong-yu; Chen, Da-zhong; Liu, Shu-min

    2013-08-26

    Xanthii Fructus (XF) is commonly called "Cang-Erzi" in traditional Chinese medicine (TCM) and widely used for the treatment of sinusitis, headache, rheumatism, and skin itching. However, the clinical utilization of XF is relatively restricted owing to its toxicity. To discover the characteristic potential biomarkers in rats treated with XF by urinary metabonomics. Ultra-performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry (UPLC-QTOF-MS) was applied in the study. The total ion chromatograms obtained from control and different dosage groups were distinguishable by a multivariate statistical analysis method. The greatest difference in metabolic profile was observed between high dosage group and control group, and the metabolic characters in rats treated with XF were perturbed in a dose-dependent manner. The metabolic changes in response for XF treatment were observed in urinary samples, which were revealed by orthogonal projection to latent structures discriminate analysis (OPLS-DA), and 10 metabolites could be served as the potential toxicity biomarkers. In addition, the mechanism associated with the damages of lipid per-oxidation and the metabolic disturbances of fatty acid oxidation were investigated. These results indicate that metabonomics analysis in urinary samples may be useful for predicting the toxicity induced by XF. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

  7. Towards Precision Medicine in the Clinic: From Biomarker Discovery to Novel Therapeutics.

    Science.gov (United States)

    Collins, Dearbhaile C; Sundar, Raghav; Lim, Joline S J; Yap, Timothy A

    2017-01-01

    Precision medicine continues to be the benchmark to which we strive in cancer research. Seeking out actionable aberrations that can be selectively targeted by drug compounds promises to optimize treatment efficacy and minimize toxicity. Utilizing these different targeted agents in combination or in sequence may further delay resistance to treatments and prolong antitumor responses. Remarkable progress in the field of immunotherapy adds another layer of complexity to the management of cancer patients. Corresponding advances in companion biomarker development, novel methods of serial tumor assessments, and innovative trial designs act synergistically to further precision medicine. Ongoing hurdles such as clonal evolution, intra- and intertumor heterogeneity, and varied mechanisms of drug resistance continue to be challenges to overcome. Large-scale data-sharing and collaborative networks using next-generation sequencing (NGS) platforms promise to take us further into the cancer 'ome' than ever before, with the goal of achieving successful precision medicine. Copyright © 2016 Elsevier Ltd. All rights reserved.

  8. Proteomics and metabolomics for mechanistic insights and biomarker discovery in cardiovascular disease.

    Science.gov (United States)

    Barallobre-Barreiro, Javier; Chung, Yuen-Li; Mayr, Manuel

    2013-08-01

    In the last decade, proteomics and metabolomics have contributed substantially to our understanding of cardiovascular diseases. The unbiased assessment of pathophysiological processes without a priori assumptions complements other molecular biology techniques that are currently used in a reductionist approach. In this review, we highlight some of the "omics" methods used to assess protein and metabolite changes in cardiovascular disease. A discrete biological function is very rarely attributed to a single molecule; more often it is the combined input of many proteins. In contrast to the reductionist approach, in which molecules are studied individually, "omics" platforms allow the study of more complex interactions in biological systems. Combining proteomics and metabolomics to quantify changes in metabolites and their corresponding enzymes will advance our understanding of pathophysiological mechanisms and aid the identification of novel biomarkers for cardiovascular disease. Copyright © 2013 Sociedad Española de Cardiología. Published by Elsevier Espana. All rights reserved.

  9. Adipokines: a treasure trove for the discovery of biomarkers for metabolic disorders.

    Science.gov (United States)

    Lehr, Stefan; Hartwig, Sonja; Sell, Henrike

    2012-01-01

    Adipose tissue is a major endocrine organ, releasing signaling and mediator proteins, termed adipokines, via which adipose tissue communicates with other organs. Expansion of adipose tissue in obesity alters adipokine secretion which may contribute to the development of metabolic diseases. Consequently, this correlation has emphasized the importance to further characterize the adipocyte secretion profile, and several attempts have been made to characterize the complex nature of the adipose tissue secretome by utilizing diverse proteomic profiling approaches. Although the entirety of human adipokines is still incompletely characterized, to date more than 600 potentially secretory proteins were identified providing a rich source to identify putative novel biomarkers associated with metabolic diseases. Copyright © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  10. Metabolomic Discovery of Novel Urinary Galabiosylceramide Analogs as Fabry Disease Biomarkers

    Science.gov (United States)

    Boutin, Michel; Auray-Blais, Christiane

    2015-03-01

    Fabry disease is an X-linked, complex, multisystemic lysosomal storage disorder presenting marked phenotypic and genotypic variability among affected male and female patients. Glycosphingolipids, mainly globotriaosylceramide (Gb3) isoforms/analogs, globotriaosylsphingosine (lyso-Gb3) and analogs, as well as galabiosylceramide (Ga2) isoforms/analogs accumulate in the vascular endothelium, nerves, cardiomyocytes, renal glomerular and tubular epithelial cells, and biological fluids. The search for biomarkers reflecting disease severity and progression is still on-going. A metabolomic study using quadrupole time-of-flight mass spectrometry has revealed 22 galabiosylceramide isoforms/analogs in urine of untreated Fabry patients classified in seven groups according to their chemical structure: (1) Saturated fatty acid; (2) one extra double bond; (3) two extra double bonds; (4) hydroxylated saturated fatty acid; (5) hydroxylated fatty acid and one extra double bond; (6) hydrated sphingosine and hydroxylated fatty acid; (7) methylated amide linkage. Relative quantification of both Ga2 and Gb3 isoforms/analogs was performed. All these biomarkers are significantly more abundant in urine samples from untreated Fabry males compared with healthy male controls. A significant amount of Ga2 isoforms/analogs, accounting for 18% of all glycosphingolipids analyzed (Ga2 + Gb3 and respective isoforms/analogs), were present in urine of Fabry patients. Gb3 isoforms containing saturated fatty acids are the most abundant (60.9%) compared with 26.3% for Ga2. A comparison between Ga2 isoforms/analogs and their Gb3 counterparts also showed that the proportion of analogs with hydroxylated fatty acids is significantly greater for Ga2 (35.8%) compared with Gb3 (1.9%). These results suggest different biological pathways involved in the synthesis and/or degradation of Gb3 and Ga2 metabolites.

  11. Low molecular weight protein enrichment on mesoporous silica thin films for biomarker discovery.

    Science.gov (United States)

    Fan, Jia; Gallagher, James W; Wu, Hung-Jen; Landry, Matthew G; Sakamoto, Jason; Ferrari, Mauro; Hu, Ye

    2012-04-17

    The identification of circulating biomarkers holds great potential for non invasive approaches in early diagnosis and prognosis, as well as for the monitoring of therapeutic efficiency.(1-3) The circulating low molecular weight proteome (LMWP) composed of small proteins shed from tissues and cells or peptide fragments derived from the proteolytic degradation of larger proteins, has been associated with the pathological condition in patients and likely reflects the state of disease.(4,5) Despite these potential clinical applications, the use of Mass Spectrometry (MS) to profile the LMWP from biological fluids has proven to be very challenging due to the large dynamic range of protein and peptide concentrations in serum.(6) Without sample pre-treatment, some of the more highly abundant proteins obscure the detection of low-abundance species in serum/plasma. Current proteomic-based approaches, such as two-dimensional polyacrylamide gel-electrophoresis (2D-PAGE) and shotgun proteomics methods are labor-intensive, low throughput and offer limited suitability for clinical applications.(7-9) Therefore, a more effective strategy is needed to isolate LMWP from blood and allow the high throughput screening of clinical samples. Here, we present a fast, efficient and reliable multi-fractionation system based on mesoporous silica chips to specifically target and enrich LMWP.(10,11) Mesoporous silica (MPS) thin films with tunable features at the nanoscale were fabricated using the triblock copolymer template pathway. Using different polymer templates and polymer concentrations in the precursor solution, various pore size distributions, pore structures, connectivity and surface properties were determined and applied for selective recovery of low mass proteins. The selective parsing of the enriched peptides into different subclasses according to their physicochemical properties will enhance the efficiency of recovery and detection of low abundance species. In combination with mass

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

    Directory of Open Access Journals (Sweden)

    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

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

    Science.gov (United States)

    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

    2014-01-01

    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 markers.

  14. microRNA Biomarker Discovery and High-Throughput DNA Sequencing Are Possible Using Long-term Archived Serum Samples.

    Science.gov (United States)

    Rounge, Trine B; Lauritzen, Marianne; Langseth, Hilde; Enerly, Espen; Lyle, Robert; Gislefoss, Randi E

    2015-09-01

    The impacts of long-term storage and varying preanalytical factors on the quality and quantity of DNA and miRNA from archived serum have not been fully assessed. Preanalytical and analytical variations and degradation may introduce bias in representation of DNA and miRNA and may result in loss or corruption of quantitative data. We have evaluated DNA and miRNA quantity, quality, and variability in samples stored up to 40 years using one of the oldest prospective serum collections in the world, the Janus Serumbank, a biorepository dedicated to cancer research. miRNAs are present and stable in archived serum samples frozen at -25°C for at least 40 years. Long-time storage did not reduce miRNA yields; however, varying preanalytical conditions had a significant effect and should be taken into consideration during project design. Of note, 500 μL serum yielded sufficient miRNA for qPCR and small RNA sequencing and on average 650 unique miRNAs were detected in samples from presumably healthy donors. Of note, 500 μL serum yielded sufficient DNA for whole-genome sequencing and subsequent SNP calling, giving a uniform representation of the genomes. DNA and miRNA are stable during long-term storage, making large prospectively collected serum repositories an invaluable source for miRNA and DNA biomarker discovery. Large-scale biomarker studies with long follow-up time are possible utilizing biorepositories with archived serum and state-of-the-art technology. ©2015 American Association for Cancer Research.

  15. Profiling of circulating microRNAs for prostate cancer biomarker discovery

    DEFF Research Database (Denmark)

    Haldrup, Christa; Kosaka, Nobuyoshi; Ochiya, Takahiro

    2014-01-01

    Prostate cancer (PC) is the most frequent cancer in men in the Western world. Currently, serum prostate-specific antigen levels and digital rectal examinations are used to indicate the need for diagnostic prostate biopsy, but lack in specificity and sensitivity. Thus, many men undergo unnecessary...... performed genome-wide miRNA profiling of serum samples from 13 benign prostatic hyperplasia (BPH) control patients and 31 PC patients. Furthermore, we carefully reviewed the literature on circulating miRNA biomarkers for PC. Our results confirmed the de-regulation of miR-141 and miR-375, two of the most...... well-documented candidate miRNA markers for PC. Moreover, we identified several new potential serum miRNA markers for PC and developed three novel and highly specific (100 %) miRNA candidate marker panels able to identify 84 % of all PC patients (miR-562/miR-210/miR-501-3p/miR-375/miR-551b), 80...

  16. Biomarkers: Delivering on the expectation of molecularly driven, quantitative health.

    Science.gov (United States)

    Wilson, Jennifer L; Altman, Russ B

    2018-02-01

    Biomarkers are the pillars of precision medicine and are delivering on expectations of molecular, quantitative health. These features have made clinical decisions more precise and personalized, but require a high bar for validation. Biomarkers have improved health outcomes in a few areas such as cancer, pharmacogenetics, and safety. Burgeoning big data research infrastructure, the internet of things, and increased patient participation will accelerate discovery in the many areas that have not yet realized the full potential of biomarkers for precision health. Here we review themes of biomarker discovery, current implementations of biomarkers for precision health, and future opportunities and challenges for biomarker discovery. Impact statement Precision medicine evolved because of the understanding that human disease is molecularly driven and is highly variable across patients. This understanding has made biomarkers, a diverse class of biological measurements, more relevant for disease diagnosis, monitoring, and selection of treatment strategy. Biomarkers' impact on precision medicine can be seen in cancer, pharmacogenomics, and safety. The successes in these cases suggest many more applications for biomarkers and a greater impact for precision medicine across the spectrum of human disease. The authors assess the status of biomarker-guided medical practice by analyzing themes for biomarker discovery, reviewing the impact of these markers in the clinic, and highlight future and ongoing challenges for biomarker discovery. This work is timely and relevant, as the molecular, quantitative approach of precision medicine is spreading to many disease indications.

  17. Isolation and characterization of urinary extracellular vesicles: implications for biomarker discovery.

    Science.gov (United States)

    Merchant, Michael L; Rood, Ilse M; Deegens, Jeroen K J; Klein, Jon B

    2017-12-01

    Urine is a valuable diagnostic medium and, with the discovery of urinary extracellular vesicles, is viewed as a dynamic bioactive fluid. Extracellular vesicles are lipid-enclosed structures that can be classified into three categories: exosomes, microvesicles (or ectosomes) and apoptotic bodies. This classification is based on the mechanisms by which membrane vesicles are formed: fusion of multivesicular bodies with the plasma membranes (exosomes), budding of vesicles directly from the plasma membrane (microvesicles) or those shed from dying cells (apoptotic bodies). During their formation, urinary extracellular vesicles incorporate various cell-specific components (proteins, lipids and nucleic acids) that can be transferred to target cells. The rigour needed for comparative studies has fueled the search for optimal approaches for their isolation, purification, and characterization. RNA, the newest extracellular vesicle component to be discovered, has received substantial attention as an extracellular vesicle therapeutic, and compelling evidence suggests that ex vivo manipulation of microRNA composition may have uses in the treatment of kidney disorders. The results of these studies are building the case that urinary extracellular vesicles act as mediators of renal pathophysiology. As the field of extracellular vesicle studies is burgeoning, this Review focuses on primary data obtained from studies of human urine rather than on data from studies of laboratory animals or cultured immortalized cells.

  18. 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.

  19. Custom database development and biomarker discovery methods for MALDI-TOF mass spectrometry-based identification of high-consequence bacterial pathogens.

    Science.gov (United States)

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

    2017-03-01

    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. Crown Copyright © 2017. Published by Elsevier B.V. All rights reserved.

  20. Robust statistical methods for significance evaluation and applications in cancer driver detection and biomarker discovery

    DEFF Research Database (Denmark)

    Madsen, Tobias

    2017-01-01

    In the present thesis I develop, implement and apply statistical methods for detecting genomic elements implicated in cancer development and progression. This is done in two separate bodies of work. The first uses the somatic mutation burden to distinguish cancer driver mutations from passenger m...

  1. 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.

  2. What Marketing Strategy for Sacred Geometry Discoveries to Make Archaeotourism Work?

    OpenAIRE

    Mulaj, Isa

    2015-01-01

    Archaeotourism can take place in two main forms: i) on site or locations of discoveries; and ii) assembling the discoveries into museums or exhibitions. Given that the first option in Kosovo has not proven viable, a marketing strategy went on to be explored for the latter in broad terms by taking into account Bronze Age artifacts with engravings from the sacred geometry discovered by the Author of this paper during 2013-14, which were the work of ancient Illyrians. Yet, the results suggest a ...

  3. Work Stress Interventions in Hospital Care: Effectiveness of the DISCovery Method

    Directory of Open Access Journals (Sweden)

    Irene Niks

    2018-02-01

    Full Text Available Effective interventions to prevent work stress and to improve health, well-being, and performance of employees are of the utmost importance. This quasi-experimental intervention study presents a specific method for diagnosis of psychosocial risk factors at work and subsequent development and implementation of tailored work stress interventions, the so-called DISCovery method. This method aims at improving employee health, well-being, and performance by optimizing the balance between job demands, job resources, and recovery from work. The aim of the study is to quantitatively assess the effectiveness of the DISCovery method in hospital care. Specifically, we used a three-wave longitudinal, quasi-experimental multiple-case study approach with intervention and comparison groups in health care work. Positive changes were found for members of the intervention groups, relative to members of the corresponding comparison groups, with respect to targeted work-related characteristics and targeted health, well-being, and performance outcomes. Overall, results lend support for the effectiveness of the DISCovery method in hospital care.

  4. Work Stress Interventions in Hospital Care: Effectiveness of the DISCovery Method

    Science.gov (United States)

    Niks, Irene; Gevers, Josette

    2018-01-01

    Effective interventions to prevent work stress and to improve health, well-being, and performance of employees are of the utmost importance. This quasi-experimental intervention study presents a specific method for diagnosis of psychosocial risk factors at work and subsequent development and implementation of tailored work stress interventions, the so-called DISCovery method. This method aims at improving employee health, well-being, and performance by optimizing the balance between job demands, job resources, and recovery from work. The aim of the study is to quantitatively assess the effectiveness of the DISCovery method in hospital care. Specifically, we used a three-wave longitudinal, quasi-experimental multiple-case study approach with intervention and comparison groups in health care work. Positive changes were found for members of the intervention groups, relative to members of the corresponding comparison groups, with respect to targeted work-related characteristics and targeted health, well-being, and performance outcomes. Overall, results lend support for the effectiveness of the DISCovery method in hospital care. PMID:29438350

  5. Work Stress Interventions in Hospital Care: Effectiveness of the DISCovery Method.

    Science.gov (United States)

    Niks, Irene; de Jonge, Jan; Gevers, Josette; Houtman, Irene

    2018-02-13

    Effective interventions to prevent work stress and to improve health, well-being, and performance of employees are of the utmost importance. This quasi-experimental intervention study presents a specific method for diagnosis of psychosocial risk factors at work and subsequent development and implementation of tailored work stress interventions, the so-called DISCovery method. This method aims at improving employee health, well-being, and performance by optimizing the balance between job demands, job resources, and recovery from work. The aim of the study is to quantitatively assess the effectiveness of the DISCovery method in hospital care. Specifically, we used a three-wave longitudinal, quasi-experimental multiple-case study approach with intervention and comparison groups in health care work. Positive changes were found for members of the intervention groups, relative to members of the corresponding comparison groups, with respect to targeted work-related characteristics and targeted health, well-being, and performance outcomes. Overall, results lend support for the effectiveness of the DISCovery method in hospital care.

  6. Biomarker Qualification: Toward a Multiple Stakeholder Framework for Biomarker Development, Regulatory Acceptance, and Utilization.

    Science.gov (United States)

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

    2015-07-01

    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. © 2015 American Society for Clinical Pharmacology and Therapeutics.

  7. Work stress, anthropometry, lung function, blood pressure, and blood-based biomarkers

    DEFF Research Database (Denmark)

    Magnusson Hanson, Linda L.; Westerlund, Hugo; Goldberg, Marcel

    2017-01-01

    -based biomarkers. Linear regression analyses before and after multivariable adjustment for age, socioeconomic status, depressive symptoms, health-related behaviours, and chronic conditions showed that work stress was associated with higher BMI, waist circumference, waist-hip ratio, alanine transaminase, white......Work stress is a risk factor for cardio-metabolic diseases, but few large-scale studies have examined the clinical profile of individuals with work stress. To address this limitation, we conducted a cross-sectional study including 43,593 working adults from a French population-based sample aged 18......–72 years (the CONSTANCES cohort). According to the Effort-Reward Imbalance model, work stress was defined as an imbalance between perceived high efforts and low rewards at work. A standardized health examination included measures of anthropometry, lung function, blood pressure and standard blood...

  8. Discovery of putative salivary biomarkers for Sjögren's syndrome using high resolution mass spectrometry and bioinformatics.

    Science.gov (United States)

    Zoukhri, Driss; Rawe, Ian; Singh, Mabi; Brown, Ashley; Kublin, Claire L; Dawson, Kevin; Haddon, William F; White, Earl L; Hanley, Kathleen M; Tusé, Daniel; Malyj, Wasyl; Papas, Athena

    2012-03-01

    The purpose of the current study was to determine if saliva contains biomarkers that can be used as diagnostic tools for Sjögren's syndrome (SjS). Twenty seven SjS patients and 27 age-matched healthy controls were recruited for these studies. Unstimulated glandular saliva was collected from the Wharton's duct using a suction device. Two µl of salvia were processed for mass spectrometry analyses on a prOTOF 2000 matrix-assisted laser desorption/ionization orthogonal time of flight (MALDI O-TOF) mass spectrometer. Raw data were analyzed using bioinformatic tools to identify biomarkers. MALDI O-TOF MS analyses of saliva samples were highly reproducible and the mass spectra generated were very rich in peptides and peptide fragments in the 750-7,500 Da range. Data analysis using bioinformatic tools resulted in several classification models being built and several biomarkers identified. One model based on 7 putative biomarkers yielded a sensitivity of 97.5%, specificity of 97.8% and an accuracy of 97.6%. One biomarker was present only in SjS samples and was identified as a proteolytic peptide originating from human basic salivary proline-rich protein 3 precursor. We conclude that salivary biomarkers detected by high-resolution mass spectrometry coupled with powerful bioinformatic tools offer the potential to serve as diagnostic/prognostic tools for SjS.

  9. Sparse multi-block PLSR for biomarker discovery when integrating data from LC-MS and NMR metabolomics

    DEFF Research Database (Denmark)

    Karaman, Ibrahim; Nørskov, Natalja; Yde, Christian Clement

    2015-01-01

    The objective of this study was to implement a multivariate method which analyzes multi-block metabolomics data and performs variable selection in order to discover potential biomarkers, simultaneously. We call this method sparse multi-block partial least squares regression (Sparse MBPLSR). To ac...

  10. Glycoblotting method allows for rapid and efficient glycome profiling of human Alzheimer's disease brain, serum and cerebrospinal fluid towards potential biomarker discovery.

    Science.gov (United States)

    Gizaw, Solomon T; Ohashi, Tetsu; Tanaka, Masakazu; Hinou, Hiroshi; Nishimura, Shin-Ichiro

    2016-08-01

    Understanding of the significance of posttranslational glycosylation in Alzheimer's disease (AD) is of growing importance for the investigation of the pathogenesis of AD as well as discovery research of the disease-specific serum biomarkers. We designed a standard protocol for the glycoblotting combined with MALDI-TOFMS to perform rapid and quantitative profiling of the glycan parts of glycoproteins (N-glycans) and glycosphingolipids (GSLs) using human AD's post-mortem samples such as brain tissues (dissected cerebral cortices such as frontal, parietal, occipital, and temporal domains), serum and cerebrospinal fluid (CSF). The structural profiles of the major N-glycans released from glycoproteins and the total expression levels of the glycans were found to be mostly similar between the brain tissues of the AD patients and those of the normal control group. In contrast, the expression levels of the serum and CSF protein N-glycans such as bisect-type and multiply branched glycoforms were increased significantly in AD patient group. In addition, the levels of some gangliosides such as GM1, GM2 and GM3 appeared to alter in the AD patient brain and serum samples when compared with the normal control groups. Alteration of the expression levels of major N- and GSL-glycans in human brain tissues, serum and CSF of AD patients can be monitored quantitatively by means of the glycoblotting-based standard protocols. The changes in the expression levels of the glycans derived from the human post-mortem samples uncovered by the standardized glycoblotting method provides potential serum biomarkers in central nervous system disorders and can contribute to the insight into the molecular mechanisms in the pathogenesis of neurodegenerative diseases and future drug discovery. Most importantly, the present preliminary trials using human post-mortem samples of AD patients suggest that large-scale serum glycomics cohort by means of various-types of human AD patients as well as the normal

  11. Is functional integration of resting state brain networks an unspecific biomarker for working memory performance?

    Science.gov (United States)

    Alavash, Mohsen; Doebler, Philipp; Holling, Heinz; Thiel, Christiane M; Gießing, Carsten

    2015-03-01

    Is there one optimal topology of functional brain networks at rest from which our cognitive performance would profit? Previous studies suggest that functional integration of resting state brain networks is an important biomarker for cognitive performance. However, it is still unknown whether higher network integration is an unspecific predictor for good cognitive performance or, alternatively, whether specific network organization during rest predicts only specific cognitive abilities. Here, we investigated the relationship between network integration at rest and cognitive performance using two tasks that measured different aspects of working memory; one task assessed visual-spatial and the other numerical working memory. Network clustering, modularity and efficiency were computed to capture network integration on different levels of network organization, and to statistically compare their correlations with the performance in each working memory test. The results revealed that each working memory aspect profits from a different resting state topology, and the tests showed significantly different correlations with each of the measures of network integration. While higher global network integration and modularity predicted significantly better performance in visual-spatial working memory, both measures showed no significant correlation with numerical working memory performance. In contrast, numerical working memory was superior in subjects with highly clustered brain networks, predominantly in the intraparietal sulcus, a core brain region of the working memory network. Our findings suggest that a specific balance between local and global functional integration of resting state brain networks facilitates special aspects of cognitive performance. In the context of working memory, while visual-spatial performance is facilitated by globally integrated functional resting state brain networks, numerical working memory profits from increased capacities for local processing

  12. Biomarker candidate discovery in Atlantic cod (Gadus morhua) continuously exposed to North Sea produced water from egg to fry

    DEFF Research Database (Denmark)

    Bohne-Kjersem, Anneli; Bache, Nicolai; Meier, Sonnich

    2010-01-01

    were able to compare the induced changes by PW to the mode of action of oestrogens. Changes in the proteome in response to exposure in whole cod fry (approximately 80 days post-hatching, dph) were detected by two-dimensional gel electrophoresis and image analysis and identified by MALDI-ToF-ToF mass...... spectrometry, using a newly developed cod EST database and the NCBI database. Many of the protein changes occurred at low levels (0.01% and 0.1% PW) of exposure, indicating putative biological responses at lower levels than previously detected. Using discriminant analysis, we identified a set of protein...... changes that may be useful as biomarker candidates of produced water (PW) and oestradiol exposure in Atlantic cod fry. The biomarker candidates discovered in this study may, following validation, prove effective as diagnostic tools in monitoring exposure and effects of discharges from the petroleum...

  13. 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

    2016-05-01

    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.

  14. Metabolic profiling of yeast culture using gas chromatography coupled with orthogonal acceleration accurate mass time-of-flight mass spectrometry: application to biomarker discovery.

    Science.gov (United States)

    Kondo, Elsuida; Marriott, Philip J; Parker, Rhiannon M; Kouremenos, Konstantinos A; Morrison, Paul; Adams, Mike

    2014-01-07

    Yeast and yeast cultures are frequently used as additives in diets of dairy cows. Beneficial effects from the inclusion of yeast culture in diets for dairy mammals have been reported, and the aim of this study was to develop a comprehensive analytical method for the accurate mass identification of the 'global' metabolites in order to differentiate a variety of yeasts at varying growth stages (Diamond V XP, Yea-Sacc and Levucell). Microwave-assisted derivatization for metabolic profiling is demonstrated through the analysis of differing yeast samples developed for cattle feed, which include a wide range of metabolites of interest covering a large range of compound classes. Accurate identification of the components was undertaken using GC-oa-ToFMS (gas chromatography-orthogonal acceleration-time-of-flight mass spectrometry), followed by principal component analysis (PCA) and orthogonal partial least squares discriminant analysis (OPLS-DA) for data reduction and biomarker discovery. Semi-quantification (fold changes in relative peak areas) was reported for metabolites identified as possible discriminative biomarkers (p-value 2), including D-ribose (four fold decrease), myo-inositol (five fold increase), L-phenylalanine (three fold increase), glucopyranoside (two fold increase), fructose (three fold increase) and threitol (three fold increase) respectively. Copyright © 2013 Elsevier B.V. All rights reserved.

  15. 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.

  16. Combined serum and EPS-urine proteomic analysis using iTRAQ technology for discovery of potential prostate cancer biomarkers.

    Science.gov (United States)

    Zhang, Mo; Chen, Lizhu; Yuan, Zhengwei; Yang, Zeyu; Li, Yue; Shan, Liping; Yin, Bo; Fei, Xiang; Miao, Jianing; Song, Yongsheng

    2016-11-01

    Prostate cancer (PCa) is one of the most common malignant tumors and a major cause of cancer-related death for men worldwide. The aim of our study was to identify potential non-invasive serum and expressed prostatic secretion (EPS)-urine biomarkers for accurate diagnosis of PCa. Here, we performed a combined isobaric tags for relative and absolute quantification (iTRAQ) proteomic analysis to compare protein profiles using pooled serum and EPS-urine samples from 4 groups of patients: benign prostate hyperplasia (BPH), high grade prostatic intraepithelial neoplasia (HGPIN), localized PCa and metastatic PCa. The differentially expressed proteins were rigorously selected and further validated in a large and independent cohort using classical ELISA and Western blot assays. Finally, we established a multiplex biomarker panel consisting of 3 proteins (serum PF4V1, PSA, and urinary CRISP3) with an excellent diagnostic capacity to differentiate PCa from BPH [area under the receiver operating characteristic curve (AUC) of 0.941], which showed an evidently greater discriminatory ability than PSA alone (AUC, 0.757) (P<0.001). Importantly, even when PSA level was in the gray zone (4-10 ng/mL), a combination of PF4V1 and CRISP3 could achieve a relatively high diagnostic efficacy (AUC, 0.895). Furthermore, their combination also had the potential to distinguish PCa from HGPIN (AUC, 0.934). Our results demonstrated that the combined application of serum and EPS-urine biomarkers can improve the diagnosis of PCa and provide a new prospect for non-invasive PCa detection.

  17. Overview of Biomarkers and Surrogate Endpoints in Drug Development

    Directory of Open Access Journals (Sweden)

    John A. Wagner

    2002-01-01

    Full Text Available There are numerous factors that recommend the use of biomarkers in drug development including the ability to provide a rational basis for selection of lead compounds, as an aid in determining or refining mechanism of action or pathophysiology, and the ability to work towards qualification and use of a biomarker as a surrogate endpoint. Examples of biomarkers come from many different means of clinical and laboratory measurement. Total cholesterol is an example of a clinically useful biomarker that was successfully qualified for use as a surrogate endpoint. Biomarkers require validation in most circumstances. Validation of biomarker assays is a necessary component to delivery of high-quality research data necessary for effective use of biomarkers. Qualification is necessary for use of a biomarker as a surrogate endpoint. Putative biomarkers are typically identified because of a relationship to known or hypothetical steps in a pathophysiologic cascade. Biomarker discovery can also be effected by expression profiling experiment using a variety of array technologies and related methods. For example, expression profiling experiments enabled the discovery of adipocyte related complement protein of 30 kD (Acrp30 or adiponectin as a biomarker for in vivo activation of peroxisome proliferator-activated receptors (PPAR γ activity.

  18. Discovery of coding genetic variants influencing diabetes-related serum biomarkers and their impact on risk of type 2 diabetes

    DEFF Research Database (Denmark)

    Ahluwalia, Tarun Veer Singh; Allin, Kristine Højgaard; Sandholt, Camilla Helene

    2015-01-01

    CONTEXT: Type 2 diabetes (T2D) prevalence is spiraling globally, and knowledge of its pathophysiological signatures is crucial for a better understanding and treatment of the disease. OBJECTIVE: We aimed to discover underlying coding genetic variants influencing fasting serum levels of nine......-nucleotide polymorphisms and were tested for association with each biomarker. Identified loci were tested for association with T2D through a large-scale meta-analysis involving up to 17 024 T2D cases and up to 64 186 controls. RESULTS: We discovered 11 associations between single-nucleotide polymorphisms and five distinct......, of which the association with the CELSR2 locus has not been shown previously. CONCLUSION: The identified loci influence processes related to insulin signaling, cell communication, immune function, apoptosis, DNA repair, and oxidative stress, all of which could provide a rationale for novel diabetes...

  19. Metabolomic study of lipids in serum for biomarker discovery in Alzheimer's disease using direct infusion mass spectrometry.

    Science.gov (United States)

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

    2014-09-01

    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. Copyright © 2014 Elsevier B.V. All rights reserved.

  20. SELDI-TOF MS-based discovery of a biomarker in Cucumis sativus seeds exposed to CuO nanoparticles.

    Science.gov (United States)

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

    2014-11-01

    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. Copyright © 2014 Elsevier B.V. All rights reserved.

  1. Work Stress and Altered Biomarkers: A Synthesis of Findings Based on the Effort-Reward Imbalance Model.

    Science.gov (United States)

    Siegrist, Johannes; Li, Jian

    2017-11-10

    While epidemiological studies provide statistical evidence on associations of exposures such as stressful work with elevated risks of stress-related disorders (e.g., coronary heart disease or depression), additional information on biological pathways and biomarkers underlying these associations is required. In this contribution, we summarize the current state of the art on research findings linking stressful work, in terms of an established theoretical model-effort-reward imbalance-with a broad range of biomarkers. Based on structured electronic literature search and recent available systematic reviews, our synthesis of findings indicates that associations of work stress with heart rate variability, altered blood lipids, and risk of metabolic syndrome are rather consistent and robust. Significant relationships with blood pressure, heart rate, altered immune function and inflammation, cortisol release, and haemostatic biomarkers were also observed, but due to conflicting findings additional data will be needed to reach a firm conclusion. This narrative review of empirical evidence supports the argument that the biomarkers under study can act as mediators of epidemiologically established associations of work stress, as measured by effort-reward imbalance, with incident stress-related disorders.

  2. Work Stress and Altered Biomarkers: A Synthesis of Findings Based on the Effort–Reward Imbalance Model

    Science.gov (United States)

    Siegrist, Johannes; Li, Jian

    2017-01-01

    While epidemiological studies provide statistical evidence on associations of exposures such as stressful work with elevated risks of stress-related disorders (e.g., coronary heart disease or depression), additional information on biological pathways and biomarkers underlying these associations is required. In this contribution, we summarize the current state of the art on research findings linking stressful work, in terms of an established theoretical model—effort-reward imbalance—with a broad range of biomarkers. Based on structured electronic literature search and recent available systematic reviews, our synthesis of findings indicates that associations of work stress with heart rate variability, altered blood lipids, and risk of metabolic syndrome are rather consistent and robust. Significant relationships with blood pressure, heart rate, altered immune function and inflammation, cortisol release, and haemostatic biomarkers were also observed, but due to conflicting findings additional data will be needed to reach a firm conclusion. This narrative review of empirical evidence supports the argument that the biomarkers under study can act as mediators of epidemiologically established associations of work stress, as measured by effort–reward imbalance, with incident stress-related disorders. PMID:29125555

  3. Work Stress and Altered Biomarkers: A Synthesis of Findings Based on the Effort–Reward Imbalance Model

    Directory of Open Access Journals (Sweden)

    Johannes Siegrist

    2017-11-01

    Full Text Available While epidemiological studies provide statistical evidence on associations of exposures such as stressful work with elevated risks of stress-related disorders (e.g., coronary heart disease or depression, additional information on biological pathways and biomarkers underlying these associations is required. In this contribution, we summarize the current state of the art on research findings linking stressful work, in terms of an established theoretical model—effort-reward imbalance—with a broad range of biomarkers. Based on structured electronic literature search and recent available systematic reviews, our synthesis of findings indicates that associations of work stress with heart rate variability, altered blood lipids, and risk of metabolic syndrome are rather consistent and robust. Significant relationships with blood pressure, heart rate, altered immune function and inflammation, cortisol release, and haemostatic biomarkers were also observed, but due to conflicting findings additional data will be needed to reach a firm conclusion. This narrative review of empirical evidence supports the argument that the biomarkers under study can act as mediators of epidemiologically established associations of work stress, as measured by effort–reward imbalance, with incident stress-related disorders.

  4. Biomarkers of safety and immune protection for genetically modified live attenuated leishmania vaccines against visceral leishmaniasis - discovery and implications.

    Science.gov (United States)

    Gannavaram, Sreenivas; Dey, Ranadhir; Avishek, Kumar; Selvapandiyan, Angamuthu; Salotra, Poonam; Nakhasi, Hira L

    2014-01-01

    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, subunit, 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 Leishmania 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 LdCen(-/-) 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 in normal

  5. Biomarkers of Safety and Immune Protection for Genetically Modified Live Attenuated Leishmania Vaccines Against Visceral Leishmaniasis – Discovery and Implications

    Science.gov (United States)

    Gannavaram, Sreenivas; Dey, Ranadhir; Avishek, Kumar; Selvapandiyan, Angamuthu; Salotra, Poonam; Nakhasi, Hira L.

    2014-01-01

    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, subunit, 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 Leishmania 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 LdCen−/− 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 in normal

  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. 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

    2014-05-01

    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

  8. Application of Fluorescence Two-Dimensional Difference In-Gel Electrophoresis as a Proteomic Biomarker Discovery Tool in Muscular Dystrophy Research

    Science.gov (United States)

    Carberry, Steven; Zweyer, Margit; Swandulla, Dieter; Ohlendieck, Kay

    2013-01-01

    In this article, we illustrate the application of difference in-gel electrophoresis for the proteomic analysis of dystrophic skeletal muscle. The mdx diaphragm was used as a tissue model of dystrophinopathy. Two-dimensional gel electrophoresis is a widely employed protein separation method in proteomic investigations. Although two-dimensional gels usually underestimate the cellular presence of very high molecular mass proteins, integral membrane proteins and low copy number proteins, this method is extremely powerful in the comprehensive analysis of contractile proteins, metabolic enzymes, structural proteins and molecular chaperones. This gives rise to two-dimensional gel electrophoretic separation as the method of choice for studying contractile tissues in health and disease. For comparative studies, fluorescence difference in-gel electrophoresis has been shown to provide an excellent biomarker discovery tool. Since aged diaphragm fibres from the mdx mouse model of Duchenne muscular dystrophy closely resemble the human pathology, we have carried out a mass spectrometry-based comparison of the naturally aged diaphragm versus the senescent dystrophic diaphragm. The proteomic comparison of wild type versus mdx diaphragm resulted in the identification of 84 altered protein species. Novel molecular insights into dystrophic changes suggest increased cellular stress, impaired calcium buffering, cytostructural alterations and disturbances of mitochondrial metabolism in dystrophin-deficient muscle tissue. PMID:24833232

  9. Biomarkers of exposition to ionizing radiation and hematology parameters in fitness for work. Case Report

    International Nuclear Information System (INIS)

    Djokovic, J.; Milacic, S.; Rakic, B.; Pajic, J.; Petrovic, D.; Vuckovic, J.

    2009-01-01

    Ionizing radiation is frequently used in medicine, especially during diagnostic procedures. The workers who are exposed to radiation have obligation for periodic check up. Presented case shows changes in hematological parameters and biomarkers of exposition to ionizing radiation (chromosome aberrations, structural changes and micronucleus test). The aim of this case report is to indicate metodology of diagnostic procedures for chronicle radiation syndrome. (author) [sr

  10. Chemical Discovery

    Science.gov (United States)

    Brown, Herbert C.

    1974-01-01

    The role of discovery in the advance of the science of chemistry and the factors that are currently operating to handicap that function are considered. Examples are drawn from the author's work with boranes. The thesis that exploratory research and discovery should be encouraged is stressed. (DT)

  11. Biomarker discovery for cervical cancer

    NARCIS (Netherlands)

    Govorukhina, Natalia I.

    2007-01-01

    Proteomics of human boy fluids is still in its early stage of development with major methodological challenges ahead. This implies that much attention is given to improving the methods and strategies. One major challenge is that many samples that have been acquired in the past may not fulfill the

  12. Biomarker discovery in low-grade breast cancer using isobaric stable isotope tags and two-dimensional liquid chromatography-tandem mass spectrometry (iTRAQ-2DLC-MS/MS) based quantitative proteomic analysis.

    Science.gov (United States)

    Bouchal, Pavel; Roumeliotis, Theodoros; Hrstka, Roman; Nenutil, Rudolf; Vojtesek, Borivoj; Garbis, Spiros D

    2009-01-01

    The present pilot study constitutes a proof-of-principle in the use of a quantitative LC-MS/MS based proteomic method for the comparative analysis of representative low-grade breast primary tumor tissues with and without metastases and metastasis in lymph node relative to the nonmetastatic tumor type. The study method incorporated iTRAQ stable isotope labeling, two-dimensional liquid chromatography, nanoelectrospray ionization and high resolution tandem mass spectrometry using the hybrid QqTOF platform (iTRAQ-2DLC-MS/MS). The principal aims of this study were (1) to define the protein spectrum obtainable using this approach, and (2) to highlight potential candidates for verification and validation studies focused on biomarkers involved in metastatic processes in breast cancer. The study resulted in the reproducible identification of 605 nonredundant proteins (p biomarker discovery program.

  13. Qualitative and quantitative characterization of plasma proteins when incorporating traveling wave ion mobility into a liquid chromatography-mass spectrometry workflow for biomarker discovery: use of product ion quantitation as an alternative data analysis tool for label free quantitation.

    Science.gov (United States)

    Daly, Charlotte E; Ng, Leong L; Hakimi, Amirmansoor; Willingale, Richard; Jones, Donald J L

    2014-02-18

    Discovery of protein biomarkers in clinical samples necessitates significant prefractionation prior to liquid chromatography-mass spectrometry (LC-MS) analysis. Integrating traveling wave ion mobility spectrometry (TWIMS) enables in-line gas phase separation which when coupled with nanoflow liquid chromatography and data independent acquisition tandem mass spectrometry, confers significant advantages to the discovery of protein biomarkers by improving separation and inherent sensitivity. Incorporation of TWIMS leads to a packet of concentrated ions which ultimately provides a significant improvement in sensitivity. As a consequence of ion packeting, when present at high concentrations, accurate quantitation of proteins can be affected due to detector saturation effects. Human plasma was analyzed in triplicate using liquid-chromatography data independent acquisition mass spectrometry (LC-DIA-MS) and using liquid-chromatography ion-mobility data independent acquisition mass spectrometry (LC-IM-DIA-MS). The inclusion of TWIMS was assessed for the effect on sample throughput, data integrity, confidence of protein and peptide identification, and dynamic range. The number of identified proteins is significantly increased by an average of 84% while both the precursor and product mass accuracies are maintained between the modalities. Sample dynamic range is also maintained while quantitation is achieved for all but the most abundant proteins by incorporating a novel data interpretation method that allows accurate quantitation to occur. This additional separation is all achieved within a workflow with no discernible deleterious effect on throughput. Consequently, TWIMS greatly enhances proteome coverage and can be reliably used for quantification when using an alternative product ion quantification strategy. Using TWIMS in biomarker discovery in human plasma is thus recommended.

  14. Mass spectrometry for biomarker development

    Energy Technology Data Exchange (ETDEWEB)

    Wu, Chaochao; Liu, Tao; Baker, Erin Shammel; Rodland, Karin D.; Smith, Richard D.

    2015-06-19

    Biomarkers potentially play a crucial role in early disease diagnosis, prognosis and targeted therapy. In the past decade, mass spectrometry based proteomics has become increasingly important in biomarker development due to large advances in technology and associated methods. This chapter mainly focuses on the application of broad (e.g. shotgun) proteomics in biomarker discovery and the utility of targeted proteomics in biomarker verification and validation. A range of mass spectrometry methodologies are discussed emphasizing their efficacy in the different stages in biomarker development, with a particular emphasis on blood biomarker development.

  15. The mediating role of interpersonal conflict at work in the relationship between negative affectivity and biomarkers of stress.

    Science.gov (United States)

    Girardi, Damiano; Falco, Alessandra; De Carlo, Alessandro; Benevene, Paula; Comar, Manola; Tongiorgi, Enrico; Bartolucci, Giovanni Battista

    2015-12-01

    This study examined the association between interpersonal conflict at work (ICW) and serum levels of three possible biomarkers of stress, namely the pro-inflammatory cytokines Interleukin 1 beta (IL-1β), Interleukin 12 (IL-12), and Interleukin 17 (IL-17). Additionally, this study investigated the role of negative affectivity (NA) in the relationship between ICW and the pro-inflammatory cytokines. Data from 121 employees in an Italian healthcare organization were analyzed using structural equation modeling. Results showed that ICW was positively associated with IL-1β, IL-12, and IL-17, after controlling for the effect of gender. Moreover, ICW completely mediated the relationship between NA and the pro-inflammatory cytokines IL-1β, IL-12, and IL-17. This mediating effect was significant after controlling for the effect of gender. Overall, this study suggests that work-related stress may be associated with biomarkers of inflammation, and that negative affectivity may influence the stress process affecting the exposure to psychosocial stressors.

  16. Why archeological tourism does not work?: Evidence from two discoveries in Kosovo

    OpenAIRE

    Mulaj, Isa

    2014-01-01

    This paper brings the evidence about two unique archeological discoveries in Kosovo: i) Fingerprints in a rock from Pleistocene period; and ii) the Star of David, the Flower of Life, the Tree of Life, and “Eye of the Masonry” found together engraved in a marble stone 1 meter long and 30 centimeters wide. The carbon test (C14) of the latter puts the age of the engravings circa 2 500 BCE. It was found by the Author in 2013, located in the coordinate 42o48’41.50”N 20o34’16.00” E, 400 metres away...

  17. Work stress interventions in hospital care : Effectiveness of the DISCovery method

    NARCIS (Netherlands)

    Niks, I.M.W.; de Jonge, J.; Gevers, J.M.P.; Houtman, I.L.D.

    2018-01-01

    Effective interventions to prevent work stress and to improve health, well-being, and performance of employees are of the utmost importance. This quasi-experimental intervention study presents a specific method for diagnosis of psychosocial risk factors at work and subsequent development and

  18. Many Paths toward Discovery: A Module for Teaching How Science Works

    Science.gov (United States)

    Price, Rebecca M.; Perez, Kathryn E.

    2018-01-01

    Improving students' understanding of how science works requires explicit instruction. Here, we test the efficacy of a module based on two previously published activities (the "Cube Puzzle" and the case study "Asteroids and Dinosaurs") that teach how science works to college science majors. Students also use the How Science…

  19. Work Stress Interventions in Hospital Care: Effectiveness of the DISCovery Method

    NARCIS (Netherlands)

    Niks, I.M.W.; Gevers, J.M.P.; Jonge, J. de; Houtman, I.L.D.

    2018-01-01

    Effective interventions to prevent work stress and to improve health, well-being, and performance of employees are of the utmost importance. This quasi-experimental intervention study presents a specific method for diagnosis of psychosocial risk factors at work and subsequent development and

  20. Long-term effects of psychosocial factors of home and work on biomarkers of stress

    DEFF Research Database (Denmark)

    Eller, Nanna Hurwitz; Kristiansen, Jesper; Hansen, Åse Marie

    2011-01-01

    LF/HF. In work, lack of control was associated with low LnTP, and lack of support was associated with an increased LnLF/HF ratio. For men, high social status was associated with low LnTP, low LnHF and high LnCortisol. Greater number of hours spent doing housework was associated with both low LnLF/HF and low Ln...

  1. 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

    2015-01-01

    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

  2. Long-term effects of psychosocial factors of home and work on biomarkers of stress.

    Science.gov (United States)

    Eller, Nanna Hurwitz; Kristiansen, Jesper; Hansen, Ase Marie

    2011-02-01

    The current study analyzed the relationship between psychosocial factors measured at baseline and heart rate variability (HRV) and salivary cortisol measured at baseline and again, six years later. In 2002 and 2008, measurements of HRV and salivary cortisol at three time points were obtained from 70 healthy participants (48 women and 22 men). The associations between the psychosocial factors measured in 2002 and the dependent variables, HRV and salivary cortisol measured in 2002 and 2008, were examined using a series of repeated measures ANCOVAs. The dependent variables were as follows: the logarithmically transformed levels of total power (LnTP), high frequency power (LnHF), the ratio between low and high frequency power (LnLF/HF) and salivary cortisol (LnCortisol). For women, high social status was associated with high LnTP, high LnHF, and low LnLF/HF. In work, lack of control was associated with low LnTP, and lack of support was associated with an increased LnLF/HF ratio. For men, high social status was associated with low LnTP, low LnHF and high LnCortisol. Greater number of hours spent doing housework was associated with both low LnLF/HF and low LnCortisol, whereas a large imbalance between effort and reward was associated with low LnTP and high LnCortisol. Despite the small sample size, this study demonstrated that psychosocial factors impact levels of activity in the allostatic systems. Copyright © 2010 Elsevier B.V. All rights reserved.

  3. Discovery and Validation of Pyridoxic Acid and Homovanillic Acid as Novel Endogenous Plasma Biomarkers of Organic Anion Transporter (OAT) 1 and OAT3 in Cynomolgus Monkeys.

    Science.gov (United States)

    Shen, Hong; Nelson, David M; Oliveira, Regina V; Zhang, Yueping; Mcnaney, Colleen A; Gu, Xiaomei; Chen, Weiqi; Su, Ching; Reily, Michael D; Shipkova, Petia A; Gan, Jinping; Lai, Yurong; Marathe, Punit; Humphreys, W Griffith

    2018-02-01

    Perturbation of organic anion transporter (OAT) 1- and OAT3-mediated transport can alter the exposure, efficacy, and safety of drugs. Although there have been reports of the endogenous biomarkers for OAT1/3, none of these have all of the characteristics required for a clinical useful biomarker. Cynomolgus monkeys were treated with intravenous probenecid (PROB) at a dose of 40 mg/kg in this study. As expected, PROB increased the area under the plasma concentration-time curve (AUC) of coadministered furosemide, a known substrate of OAT1 and OAT3, by 4.1-fold, consistent with the values reported in humans (3.1- to 3.7-fold). Of the 233 plasma metabolites analyzed using a liquid chromatography-tandem mass spectrometry (LC-MS/MS)-based metabolomics method, 29 metabolites, including pyridoxic acid (PDA) and homovanillic acid (HVA), were significantly increased after either 1 or 3 hours in plasma from the monkeys pretreated with PROB compared with the treated animals. The plasma of animals was then subjected to targeted LC-MS/MS analysis, which confirmed that the PDA and HVA AUCs increased by approximately 2- to 3-fold by PROB pretreatments. PROB also increased the plasma concentrations of hexadecanedioic acid (HDA) and tetradecanedioic acid (TDA), although the increases were not statistically significant. Moreover, transporter profiling assessed using stable cell lines constitutively expressing transporters demonstrated that PDA and HVA are substrates for human OAT1, OAT3, OAT2 (HVA), and OAT4 (PDA), but not OCT2, MATE1, MATE2K, OATP1B1, OATP1B3, and sodium taurocholate cotransporting polypeptide. Collectively, these findings suggest that PDA and HVA might serve as blood-based endogenous probes of cynomolgus monkey OAT1 and OAT3, and investigation of PDA and HVA as circulating endogenous biomarkers of human OAT1 and OAT3 function is warranted. Copyright © 2018 by The American Society for Pharmacology and Experimental Therapeutics.

  4. Lessons for tumor biomarker trials: vicious cycles, scientific method & developing guidelines.

    Science.gov (United States)

    Hayes, Daniel; Raison, Claire

    2015-02-01

    Interview with Daniel Hayes, by Claire Raison (Commissioning Editor) Daniel F Hayes, M.D. is the Stuart A Padnos Professor of Breast Cancer Research and co-Director of the Breast Oncology Program at the University of Michigan Comprehensive Cancer Center (Ann Arbor, MI, USA). Dr Hayes has extensive experience in clinical and translational breast cancer biomarker research, and in drug development and clinical trials. Around 30 years ago, he led the discovery of the circulating breast tumor biomarker, CA15-3, which started his career into further tumor biomarker work. The main thrust of his work since then has been in clinical trials, tumor biomarkers and trying to integrate the two. Dr Hayes is Chair of the Correlative Sciences Committee of the North American Breast Cancer Group (now called the Breast Cancer Steering Committee), and co-chairs the Expert Panel for Tumor Biomarker Practice Guidelines for the American Society of Clinical Oncology.

  5. Metabolic profiling study on potential toxicity and immunotoxicity-biomarker discovery in rats treated with cyclophosphamide using HPLC-ESI-IT-TOF-MS.

    Science.gov (United States)

    Li, Jing; Lin, Wensi; Lin, Weiwei; Xu, Peng; Zhang, Jianmei; Yang, Haisong; Ling, Xiaomei

    2015-05-01

    Despite the recent advances in understanding toxicity mechanism of cyclophosphamide (CTX), the development of biomarkers is still essential. CTX-induced immunotoxicity in rats by a metabonomics approach was investigated using high-performance liquid chromatography coupled with ion trap time-of-flight mass spectrometry (HPLC-ESI-IT-TOF-MS). The rats were orally administered CTX (30 mg/kg/day) for five consecutive days, and on the fifth day samples of urine, thymus and spleen were collected and analyzed. A significant difference in metabolic profiling was observed between the CTX-treated group and the control group by partial least squares-discriminant analysis (PLS-DA), which indicated that metabolic disturbances of immunotoxicity in CTX-treated rats had occurred. One potential biomarker in spleen, three in urine and three in thymus were identified. It is suggested that the CTX-toxicity mechanism may involve the modulation of tryptophan metabolism, phospholipid metabolism and energy metabolism. This research can help to elucidate the CTX-influenced pathways at a low dose and can further help to indicate the patients' pathological status at earlier stages of toxicological progression after drug administration. Copyright © 2014 John Wiley & Sons, Ltd.

  6. Robust Selection Algorithm (RSA) for Multi-Omic Biomarker Discovery; Integration with Functional Network Analysis to Identify miRNA Regulated Pathways in Multiple Cancers.

    Science.gov (United States)

    Sehgal, Vasudha; Seviour, Elena G; Moss, Tyler J; Mills, Gordon B; Azencott, Robert; Ram, Prahlad T

    2015-01-01

    MicroRNAs (miRNAs) play a crucial role in the maintenance of cellular homeostasis by regulating the expression of their target genes. As such, the dysregulation of miRNA expression has been frequently linked to cancer. With rapidly accumulating molecular data linked to patient outcome, the need for identification of robust multi-omic molecular markers is critical in order to provide clinical impact. While previous bioinformatic tools have been developed to identify potential biomarkers in cancer, these methods do not allow for rapid classification of oncogenes versus tumor suppressors taking into account robust differential expression, cutoffs, p-values and non-normality of the data. Here, we propose a methodology, Robust Selection Algorithm (RSA) that addresses these important problems in big data omics analysis. The robustness of the survival analysis is ensured by identification of optimal cutoff values of omics expression, strengthened by p-value computed through intensive random resampling taking into account any non-normality in the data and integration into multi-omic functional networks. Here we have analyzed pan-cancer miRNA patient data to identify functional pathways involved in cancer progression that are associated with selected miRNA identified by RSA. Our approach demonstrates the way in which existing survival analysis techniques can be integrated with a functional network analysis framework to efficiently identify promising biomarkers and novel therapeutic candidates across diseases.

  7. Influences of Normalization Method on Biomarker Discovery in Gas Chromatography-Mass Spectrometry-Based Untargeted Metabolomics: What Should Be Considered?

    Science.gov (United States)

    Chen, Jiaqing; Zhang, Pei; Lv, Mengying; Guo, Huimin; Huang, Yin; Zhang, Zunjian; Xu, Fengguo

    2017-05-16

    Data reduction techniques in gas chromatography-mass spectrometry-based untargeted metabolomics has made the following workflow of data analysis more lucid. However, the normalization process still perplexes researchers, and its effects are always ignored. In order to reveal the influences of normalization method, five representative normalization methods (mass spectrometry total useful signal, median, probabilistic quotient normalization, remove unwanted variation-random, and systematic ratio normalization) were compared in three real data sets with different types. First, data reduction techniques were used to refine the original data. Then, quality control samples and relative log abundance plots were utilized to evaluate the unwanted variations and the efficiencies of normalization process. Furthermore, the potential biomarkers which were screened out by the Mann-Whitney U test, receiver operating characteristic curve analysis, random forest, and feature selection algorithm Boruta in different normalized data sets were compared. The results indicated the determination of the normalization method was difficult because the commonly accepted rules were easy to fulfill but different normalization methods had unforeseen influences on both the kind and number of potential biomarkers. Lastly, an integrated strategy for normalization method selection was recommended.

  8. Usability of Discovery Portals

    NARCIS (Netherlands)

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

    2013-01-01

    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

  9. Discovery of urinary biomarkers to discriminate between exogenous and semi-endogenous thiouracil in cattle: A parallel-like randomized design.

    Science.gov (United States)

    Van Meulebroek, Lieven; Wauters, Jella; Pomian, Beata; Vanden Bussche, Julie; Delahaut, Philippe; Fichant, Eric; Vanhaecke, Lynn

    2018-01-01

    In the European Union, the use of thyreostats for animal fattening purposes has been banned and monitoring plans have been established to detect potential abuse. However, this is not always straightforward as thyreostats such as thiouracil may also have a semi-endogenous origin. Therefore, this study aimed at defining urinary metabolites, which may aid in defining the origin of detected thiouracil. Hereto, a parallel-like randomized in vivo study was conducted in which calves (n = 8) and cows (n = 8) were subjected to either a control treatment, rapeseed-enriched diet to induce semi-endogenous formation, or thiouracil treatment. Urine samples (n = 330) were assessed through metabolic fingerprinting, employing liquid-chromatography and Q-ExactiveTM Orbitrap mass spectrometry. Urinary fingerprints comprised up to 40,000 features whereby multivariate discriminant analysis was able to point out significant metabolome differences between treatments (Q2(Y) ≥ 0.873). Using the validated models, a total of twelve metabolites (including thiouracil) were assigned marker potential. Combining these markers into age-dependent biomarker panels rendered a tool by which sample classification could be improved in comparison with thiouracil-based thresholds, and this during on-going thiouracil treatment (specificities ≥ 95.2% and sensitivities ≥ 85.7%), post-treatment (sensitivities ≥ 80% for ≥ 24 h after last administration), and simulated low-dose thiouracil treatment (exogenous thiouracil below 30 ng μL-1). Moreover, the metabolic relevance of revealed markers was supported by the suggested identities, for which a structural link with thiouracil could be determined in most cases. The proposed biomarker panels may contribute to a more justified decision-making in monitoring thiouracil abuse.

  10. Usability of Discovery Portals

    OpenAIRE

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

    2013-01-01

    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 are not spatial data experts but professionals with limited spatial knowledge, and a focus outside the spatial domain. An exploratory usability experiment was carried out in which three discovery p...

  11. Influence of PCOS in Obese vs. Non-Obese women from Mesenchymal Progenitors Stem Cells and Other Endometrial Cells: An in silico biomarker discovery.

    Science.gov (United States)

    Desai, Ashvini; Madar, Inamul Hasan; Asangani, Amjad Hussain; Ssadh, Hussain Al; Tayubi, Iftikhar Aslam

    2017-01-01

    Polycystic ovary syndrome (PCOS) is endocrine system disease which affect women ages 18 to 44 where the women's hormones are imbalance. Recently it has been reported to occur in early age. Alteration of normal gene expression in PCOS has shown negative effects on long-term health issues. PCOS has been the responsible factor for the infertility in women of reproductive age group. Early diagnosis and treatment can improve the women's health suffering from PCOS. Earlier Studies shows correlation of PCOS upon insulin resistance with significant outcome, Current study shows the linkage between PCOS with obesity and non-obese patients. Gene expression datasets has been downloaded from GEO (control and PCOS affected patients). Normalization of the datasets were performed using R based on RMA and differentially expressed gene (DEG) were selected on the basis of p-value 0.05 followed by functional annotation of selected gene using Enrich R and DAVID. The DEGs were significantly related to PCOS with obesity and other risk factors involved in disease. The Gene Enrichment Analysis suggests alteration of genes and associated pathway in case of obesity. Current study provides a productive groundwork for specific biomarkers identification for the accurate diagnosis and efficient target for the treatment of PCOS.

  12. The MURDOCK Study: a long-term initiative for disease reclassification through advanced biomarker discovery and integration with electronic health records

    Science.gov (United States)

    Tenenbaum, Jessica D; Christian, Victoria; Cornish, Melissa A; Dolor, Rowena J; Dunham, Ashley A; Ginsburg, Geoffrey S; Kraus, Virginia B; McHutchison, John G; Nahm, Meredith L; Newby, L Kristin; Svetkey, Laura P; Udayakumar, Krishna; Califf, Robert M

    2012-01-01

    Background Facing critically low return per dollar invested on clinical research and clinical care, the American biomedical enterprise is in need of a significant transformation. A confluence of high-throughput “omic” technologies and increasing adoption of the electronic health record has fueled excitement for a new paradigm for biomedical research and practice. The ability to simultaneously measure thousands of molecular variables and assess their relationships with clinical data collected during the course of care could enable reclassification of disease not only by gross phenotypic observation but according to underlying molecular mechanism and influence of social determinants.In turn, this reclassification could enable development of targeted therapeutic interventions as well as disease prevention strategies at the individual and population levels. Methods/Design The MURDOCK Study consists of distinct project “horizons” or stages. Horizon 1 entailed the generation and analysis of molecular data for existing large,clinically well-annotated cohorts in four disease areas. Horizon 1.5 involves creating and maintaining a 50,000-person,community volunteer registry for biomarker signature validation and prospective studies, including integration of environmental and social data. Horizon 2 leverages and prospectively recruits Horizon 1.5 volunteers, and extends the study to additional disease areas of interest. Horizon 3 will expand the study through regional, national,and international partnerships. Discussion The MURDOCK Study embodies a new model of team science investigation and represents a significant resource for translational research. The study team invites inquiries to form new collaborations to exploit the rich resources provided by these biospecimens and associated study data. PMID:22937207

  13. Human cervicovaginal fluid biomarkers to predict term and preterm labor

    Science.gov (United States)

    Heng, Yujing J.; Liong, Stella; Permezel, Michael; Rice, Gregory E.; Di Quinzio, Megan K. W.; Georgiou, Harry M.

    2015-01-01

    Preterm birth (PTB; birth before 37 completed weeks of gestation) remains the major cause of neonatal morbidity and mortality. The current generation of biomarkers predictive of PTB have limited utility. In pregnancy, the human cervicovaginal fluid (CVF) proteome is a reflection of the local biochemical milieu and is influenced by the physical changes occurring in the vagina, cervix and adjacent overlying fetal membranes. Term and preterm labor (PTL) share common pathways of cervical ripening, myometrial activation and fetal membranes rupture leading to birth. We therefore hypothesize that CVF biomarkers predictive of labor may be similar in both the term and preterm labor setting. In this review, we summarize some of the existing published literature as well as our team's breadth of work utilizing the CVF for the discovery and validation of putative CVF biomarkers predictive of human labor. Our team established an efficient method for collecting serial CVF samples for optimal 2-dimensional gel electrophoresis resolution and analysis. We first embarked on CVF biomarker discovery for the prediction of spontaneous onset of term labor using 2D-electrophoresis and solution array multiple analyte profiling. 2D-electrophoretic analyses were subsequently performed on CVF samples associated with PTB. Several proteins have been successfully validated and demonstrate that these biomarkers are associated with term and PTL and may be predictive of both term and PTL. In addition, the measurement of these putative biomarkers was found to be robust to the influences of vaginal microflora and/or semen. The future development of a multiple biomarker bed-side test would help improve the prediction of PTB and the clinical management of patients. PMID:26029118

  14. 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: tania.gomes@niva.no; Chora, Suze; Pereira, Catarina G.; Cardoso, Cátia; Bebianno, Maria João

    2014-10-15

    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.

  15. Radiation Biomarker Research Using Mass Spectrometry

    National Research Council Canada - National Science Library

    Bach, Stephan B; Hubert, Walter

    2007-01-01

    .... This review is intended to give an overview of mass spectrometry and its application to biological systems and biomarker discovery and how that might relate to relevant radiation dosimetry studies...

  16. How music training enhances working memory: a cerebrocerebellar blending mechanism that can lead equally to scientific discovery and therapeutic efficacy in neurological disorders.

    Science.gov (United States)

    Vandervert, Larry

    2015-01-01

    Following in the vein of studies that concluded that music training resulted in plastic changes in Einstein's cerebral cortex, controlled research has shown that music training (1) enhances central executive attentional processes in working memory, and (2) has also been shown to be of significant therapeutic value in neurological disorders. Within this framework of music training-induced enhancement of central executive attentional processes, the purpose of this article is to argue that: (1) The foundational basis of the central executive begins in infancy as attentional control during the establishment of working memory, (2) In accordance with Akshoomoff, Courchesne and Townsend's and Leggio and Molinari's cerebellar sequence detection and prediction models, the rigors of volitional control demands of music training can enhance voluntary manipulation of information in thought and movement, (3) The music training-enhanced blending of cerebellar internal models in working memory as can be experienced as intuition in scientific discovery (as Einstein often indicated) or, equally, as moments of therapeutic advancement toward goals in the development of voluntary control in neurological disorders, and (4) The blending of internal models as in (3) thus provides a mechanism by which music training enhances central executive processes in working memory that can lead to scientific discovery and improved therapeutic outcomes in neurological disorders. Within the framework of Leggio and Molinari's cerebellar sequence detection model, it is determined that intuitive steps forward that occur in both scientific discovery and during therapy in those with neurological disorders operate according to the same mechanism of adaptive error-driven blending of cerebellar internal models. It is concluded that the entire framework of the central executive structure of working memory is a product of the cerebrocerebellar system which can, through the learning of internal models

  17. 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.

  18. Discovery, detection and use of biomarkers

    Science.gov (United States)

    Swanson, Basil I.; Mukundan, Harshini; Sakamuri, Rama Murthy

    2017-12-05

    Provided herein are systems for and methods of capturing, detecting, quantifying, and characterizing target moieties that are characterized by having a lipophilic portion of sufficient size and chemical composition whereby the target moiety inserts (or partitions) into a lipid assembly. Examples of such assays employ synthetic lipid constructs such as supported bilayers which are used to capture target moieties; other example assays exploit the natural absorption of compounds into natural lipid constructs such as HDL or LDL particles or cell membranes to capture target moieties. In specific embodiments, the target moieties are bacterial pathogen associated molecular pattern (PAMP) molecules or compounds not yet identified as PAMP molecules. Also provided are methods of determining PAMP molecule fingerprints and profiles that are linked to (indicative of) bacterial infection, disease states or progression, development of antibiotic resistance, and so forth, as well as these fingerprints, profiles and methods of using them.

  19. Urine protein concentration estimation for biomarker discovery

    OpenAIRE

    Mistry, Hiten D.; Bramham, Kate; Weston, Andrew; Ward, Malcolm; Thompson, Andrew; Chappell, Lucy C.

    2013-01-01

    Recent advances have been made in the study of urinary proteomics as a diagnostic tool for renal disease and pre-eclampsia which requires accurate measurement of urinary protein. We compared different protein assays (Bicinchoninic acid (BCA), Lowry and Bradford) against the ‘gold standard’ amino-acid assay in urine from 43 women (8 non-pregnant, 34 pregnant, including 8 with pre-eclampsia. BCA assay was superior to both Lowry and Bradford assays (Bland Altman bias: 0.08) compared to amino-aci...

  20. 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......). Finally, we compute volatility discovery for 30 actively traded stocks in the U.S. and report that Nyse and Arca dominate Nasdaq....

  1. Sedentary behaviour and biomarkers for cardiovascular disease and diabetes in mid-life: the role of television-viewing and sitting at work.

    Directory of Open Access Journals (Sweden)

    Snehal M Pinto Pereira

    Full Text Available Knowledge of sedentary behaviour associations with health has relied mainly on television-viewing as a proxy and studies with other measures are less common. To clarify whether sedentary behaviour is associated with disease-risk, we examined associations for television-viewing and sitting at work.Using the 1958 British birth cohort (n = 7660, we analysed cross-sectional associations between television-viewing and work sitting (four categories, 0-1 to ≥ 3 h/d with total, high-density lipoprotein (HDL and low-density lipoprotein (LDL-cholesterol, triglycerides, blood pressure, glycated haemoglobin, fibrinogen, C-reactive protein, hypertension and metabolic syndrome at 45 y. We adjusted for lifestyle and socio-demographic factors and assessed mediation of associations by body mass index (BMI and diet. We also assessed whether the sedentary indicators are related similarly to factors linked to disease-risk.There was a general trend of adverse socio-demographic and lifestyle characteristics with higher h/d television-viewing, but trends in the opposite direction for work sitting. Television-viewing was associated with most biomarkers and associations were mediated by BMI: e.g. for each category increase in television-viewing, HDL-cholesterol in men was lower by 2.3% (95% CI: 1.5%, 3.2% and, in BMI and diet adjusted analyses, by 1.6% (0.8%, 2.4%; for women, by 2.0% (1.2%, 2.9% and 0.9% (0.1%, 1.6% respectively. Few, weaker associations for work sitting were found, in men only: e.g. corresponding values for HDL-cholesterol were 1.2% (0.5%, 1.9% and 0.9% (0.3%, 1.5%. Odds for metabolic syndrome were elevated by 82% and 33% respectively for men watching television or work sitting for ≥ 3 vs. 0-1 h/d.Associations with cardiovascular disease and diabetes biomarkers in mid-adulthood differed for television-viewing and work sitting. The role of sedentary behaviour may vary by leisure and work domains or the two indicators reflect differing associations

  2. Sedentary behaviour and biomarkers for cardiovascular disease and diabetes in mid-life: the role of television-viewing and sitting at work.

    Science.gov (United States)

    Pinto Pereira, Snehal M; Ki, Myung; Power, Chris

    2012-01-01

    Knowledge of sedentary behaviour associations with health has relied mainly on television-viewing as a proxy and studies with other measures are less common. To clarify whether sedentary behaviour is associated with disease-risk, we examined associations for television-viewing and sitting at work. Using the 1958 British birth cohort (n = 7660), we analysed cross-sectional associations between television-viewing and work sitting (four categories, 0-1 to ≥ 3 h/d) with total, high-density lipoprotein (HDL) and low-density lipoprotein (LDL)-cholesterol, triglycerides, blood pressure, glycated haemoglobin, fibrinogen, C-reactive protein, hypertension and metabolic syndrome at 45 y. We adjusted for lifestyle and socio-demographic factors and assessed mediation of associations by body mass index (BMI) and diet. We also assessed whether the sedentary indicators are related similarly to factors linked to disease-risk. There was a general trend of adverse socio-demographic and lifestyle characteristics with higher h/d television-viewing, but trends in the opposite direction for work sitting. Television-viewing was associated with most biomarkers and associations were mediated by BMI: e.g. for each category increase in television-viewing, HDL-cholesterol in men was lower by 2.3% (95% CI: 1.5%, 3.2%) and, in BMI and diet adjusted analyses, by 1.6% (0.8%, 2.4%); for women, by 2.0% (1.2%, 2.9%) and 0.9% (0.1%, 1.6%) respectively. Few, weaker associations for work sitting were found, in men only: e.g. corresponding values for HDL-cholesterol were 1.2% (0.5%, 1.9%) and 0.9% (0.3%, 1.5%). Odds for metabolic syndrome were elevated by 82% and 33% respectively for men watching television or work sitting for ≥ 3 vs. 0-1 h/d. Associations with cardiovascular disease and diabetes biomarkers in mid-adulthood differed for television-viewing and work sitting. The role of sedentary behaviour may vary by leisure and work domains or the two indicators reflect differing associations with

  3. Sedentary Behaviour and Biomarkers for Cardiovascular Disease and Diabetes in Mid-Life: The Role of Television-Viewing and Sitting at Work

    Science.gov (United States)

    Pinto Pereira, Snehal M.; Ki, Myung; Power, Chris

    2012-01-01

    Background Knowledge of sedentary behaviour associations with health has relied mainly on television-viewing as a proxy and studies with other measures are less common. To clarify whether sedentary behaviour is associated with disease-risk, we examined associations for television-viewing and sitting at work. Methods Using the 1958 British birth cohort (n = 7660), we analysed cross-sectional associations between television-viewing and work sitting (four categories, 0–1 to ≥3 h/d) with total, high-density lipoprotein (HDL) and low-density lipoprotein (LDL)-cholesterol, triglycerides, blood pressure, glycated haemoglobin, fibrinogen, C-reactive protein, hypertension and metabolic syndrome at 45 y. We adjusted for lifestyle and socio-demographic factors and assessed mediation of associations by body mass index (BMI) and diet. We also assessed whether the sedentary indicators are related similarly to factors linked to disease-risk. Results There was a general trend of adverse socio-demographic and lifestyle characteristics with higher h/d television-viewing, but trends in the opposite direction for work sitting. Television-viewing was associated with most biomarkers and associations were mediated by BMI: e.g. for each category increase in television-viewing, HDL-cholesterol in men was lower by 2.3% (95% CI: 1.5%, 3.2%) and, in BMI and diet adjusted analyses, by 1.6% (0.8%, 2.4%); for women, by 2.0% (1.2%, 2.9%) and 0.9% (0.1%, 1.6%) respectively. Few, weaker associations for work sitting were found, in men only: e.g. corresponding values for HDL-cholesterol were 1.2% (0.5%, 1.9%) and 0.9% (0.3%, 1.5%). Odds for metabolic syndrome were elevated by 82% and 33% respectively for men watching television or work sitting for ≥3 vs. 0–1 h/d. Conclusions Associations with cardiovascular disease and diabetes biomarkers in mid-adulthood differed for television-viewing and work sitting. The role of sedentary behaviour may vary by leisure and work domains or the two

  4. Design of the DISCovery project: tailored work-oriented interventions to improve employee health, well-being, and performance-related outcomes in hospital care.

    Science.gov (United States)

    Niks, Irene M W; de Jonge, Jan; Gevers, Josette M P; Houtman, Irene L D

    2013-02-19

    It is well-known that health care workers in today's general hospitals have to deal with high levels of job demands, which could have negative effects on their health, well-being, and job performance. A way to reduce job-related stress reactions and to optimize positive work-related outcomes is to raise the level of specific job resources and opportunities to recover from work. However, the question remains how to translate the optimization of the balance between job demands, job resources, and recovery opportunities into effective workplace interventions. The aim of the DISCovery project is to develop and implement tailored work-oriented interventions to improve health, well-being, and performance of health care personnel. A quasi-experimental field study with a non-equivalent control group pretest-posttest design will be conducted in a top general hospital. Four existing organizational departments will provide both an intervention and a comparison group. Two types of research methods are used: (1) a longitudinal web-based survey study, and (2) a longitudinal daily diary study. After base-line measures of both methods, existing and yet to be developed interventions will be implemented within the experimental groups. Follow-up measurements will be taken one and two years after the base-line measures to analyze short-term and long-term effects of the interventions. Additionally, a process evaluation and a cost-effectiveness analysis will be carried out. The DISCovery project fulfills a strong need for theory-driven and scientifically well-performed research on job stress and performance interventions. It will provide insight into (1) how a balance between job demands, job resources, and recovery from work can be optimized, (2) the short-term and long-term effects of tailored work-oriented effects, and (3) indicators for successful or unsuccessful implementation of interventions.

  5. Design of the DISCovery project: tailored work-oriented interventions to improve employee health, well-being, and performance-related outcomes in hospital care

    Directory of Open Access Journals (Sweden)

    Niks Irene MW

    2013-02-01

    Full Text Available Abstract Background It is well-known that health care workers in today’s general hospitals have to deal with high levels of job demands, which could have negative effects on their health, well-being, and job performance. A way to reduce job-related stress reactions and to optimize positive work-related outcomes is to raise the level of specific job resources and opportunities to recover from work. However, the question remains how to translate the optimization of the balance between job demands, job resources, and recovery opportunities into effective workplace interventions. The aim of the DISCovery project is to develop and implement tailored work-oriented interventions to improve health, well-being, and performance of health care personnel. Methods/Design A quasi-experimental field study with a non-equivalent control group pretest-posttest design will be conducted in a top general hospital. Four existing organizational departments will provide both an intervention and a comparison group. Two types of research methods are used: (1 a longitudinal web-based survey study, and (2 a longitudinal daily diary study. After base-line measures of both methods, existing and yet to be developed interventions will be implemented within the experimental groups. Follow-up measurements will be taken one and two years after the base-line measures to analyze short-term and long-term effects of the interventions. Additionally, a process evaluation and a cost-effectiveness analysis will be carried out. Discussion The DISCovery project fulfills a strong need for theory-driven and scientifically well-performed research on job stress and performance interventions. It will provide insight into (1 how a balance between job demands, job resources, and recovery from work can be optimized, (2 the short-term and long-term effects of tailored work-oriented effects, and (3 indicators for successful or unsuccessful implementation of interventions.

  6. Predictive Biomarkers for Asthma Therapy.

    Science.gov (United States)

    Medrek, Sarah K; Parulekar, Amit D; Hanania, Nicola A

    2017-09-19

    Asthma is a heterogeneous disease characterized by multiple phenotypes. Treatment of patients with severe disease can be challenging. Predictive biomarkers are measurable characteristics that reflect the underlying pathophysiology of asthma and can identify patients that are likely to respond to a given therapy. This review discusses current knowledge regarding predictive biomarkers in asthma. Recent trials evaluating biologic therapies targeting IgE, IL-5, IL-13, and IL-4 have utilized predictive biomarkers to identify patients who might benefit from treatment. Other work has suggested that using composite biomarkers may offer enhanced predictive capabilities in tailoring asthma therapy. Multiple biomarkers including sputum eosinophil count, blood eosinophil count, fractional concentration of nitric oxide in exhaled breath (FeNO), and serum periostin have been used to identify which patients will respond to targeted asthma medications. Further work is needed to integrate predictive biomarkers into clinical practice.

  7. Hepcidin- A Burgeoning Biomarker

    Directory of Open Access Journals (Sweden)

    Hemkant Manikrao Deshmukh

    2017-10-01

    Full Text Available The discovery of hepcidin has triggered a virtual ignition of studies on iron metabolism and related disorders. The peptide hormone hepcidin is a key homeostatic regulator of iron metabolism. The synthesis of hepcidin is induced by systemic iron levels and by inflammatory stimuli. Several human diseases are associated with variations in hepcidin concentrations. The evaluation of hepcidin in biological fluids is therefore a promising device in the diagnosis and management of medical situations in which iron metabolism is affected. Thus, it made us to recapitulate role of hepcidin as biomarker.

  8. Pharmacogenomic Biomarkers

    Directory of Open Access Journals (Sweden)

    Sandra C. Kirkwood

    2002-01-01

    Full Text Available Pharmacogenomic biomarkers hold great promise for the future of medicine and have been touted as a means to personalize prescriptions. Genetic biomarkers for disease susceptibility including both Mendelian and complex disease promise to result in improved understanding of the pathophysiology of disease, identification of new potential therapeutic targets, and improved molecular classification of disease. However essential to fulfilling the promise of individualized therapeutic intervention is the identification of drug activity biomarkers that stratify individuals based on likely response to a particular therapeutic, both positive response, efficacy, and negative response, development of side effect or toxicity. Prior to the widespread clinical application of a genetic biomarker multiple scientific studies must be completed to identify the genetic variants and delineate their functional significance in the pathophysiology of a carefully defined phenotype. The applicability of the genetic biomarker in the human population must then be verified through both retrospective studies utilizing stored or clinical trial samples, and through clinical trials prospectively stratifying patients based on the biomarker. The risk conferred by the polymorphism and the applicability in the general population must be clearly understood. Thus, the development and widespread application of a pharmacogenomic biomarker is an involved process and for most disease states we are just at the beginning of the journey towards individualized therapy and improved clinical outcome.

  9. Maternal shift work during pregnancy and biomarkers of reproductive function in the male offspring - a pilot follow-up study

    DEFF Research Database (Denmark)

    Ramlau-Hansen, Cecilia Høst; Håkonsen, Linn Berger; Christensen, Maria

    2011-01-01

    The aim of this study was to examine the associations between maternal shift work during pregnancy and measures of semen quantity and quality and level of reproductive hormones among young, adult men.......The aim of this study was to examine the associations between maternal shift work during pregnancy and measures of semen quantity and quality and level of reproductive hormones among young, adult men....

  10. Beyond Discovery

    DEFF Research Database (Denmark)

    Korsgaard, Steffen; Sassmannshausen, Sean Patrick

    2017-01-01

    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...

  11. Defining Creativity with Discovery

    OpenAIRE

    Wilson, Nicholas Charles; Martin, Lee

    2017-01-01

    The standard definition of creativity has enabled significant empirical and theoretical advances, yet contains philosophical conundrums concerning the nature of novelty and the role of recognition and values. In this work we offer an act of conceptual valeting that addresses these issues and in doing so, argue that creativity definitions can be extended through the use of discovery. Drawing on dispositional realist philosophy we outline why adding the discovery and bringing into being of new ...

  12. On the antiproton discovery

    International Nuclear Information System (INIS)

    Piccioni, O.

    1989-01-01

    The author of this article describes his own role in the discovery of the antiproton. Although Segre and Chamberlain received the Nobel Prize in 1959 for its discovery, the author claims that their experimental method was his idea which he communicated to them informally in December 1954. He describes how his application for citizenship (he was Italian), and other scientists' manipulation, prevented him from being at Berkeley to work on the experiment himself. (UK)

  13. Higgs Discovery

    DEFF Research Database (Denmark)

    Sannino, Francesco

    2013-01-01

    has been challenged by the discovery of a not-so-heavy Higgs-like state. I will therefore review the recent discovery \\cite{Foadi:2012bb} that the standard model top-induced radiative corrections naturally reduce the intrinsic non-perturbative mass of the composite Higgs state towards the desired...... via first principle lattice simulations with encouraging results. The new findings show that the recent naive claims made about new strong dynamics at the electroweak scale being disfavoured by the discovery of a not-so-heavy composite Higgs are unwarranted. I will then introduce the more speculative......I discuss the impact of the discovery of a Higgs-like state on composite dynamics starting by critically examining the reasons in favour of either an elementary or composite nature of this state. Accepting the standard model interpretation I re-address the standard model vacuum stability within...

  14. Toxins and drug discovery.

    Science.gov (United States)

    Harvey, Alan L

    2014-12-15

    Components from venoms have stimulated many drug discovery projects, with some notable successes. These are briefly reviewed, from captopril to ziconotide. However, there have been many more disappointments on the road from toxin discovery to approval of a new medicine. Drug discovery and development is an inherently risky business, and the main causes of failure during development programmes are outlined in order to highlight steps that might be taken to increase the chances of success with toxin-based drug discovery. These include having a clear focus on unmet therapeutic needs, concentrating on targets that are well-validated in terms of their relevance to the disease in question, making use of phenotypic screening rather than molecular-based assays, and working with development partners with the resources required for the long and expensive development process. Copyright © 2014 The Author. Published by Elsevier Ltd.. All rights reserved.

  15. 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.

    2016-01-01

    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...

  16. Biomarker discovery in biological specimens (plasma, hair, liver and kidney) of diabetic mice based upon metabolite profiling using ultra-performance liquid chromatography with electrospray ionization time-of-flight mass spectrometry.

    Science.gov (United States)

    Tsutsui, Haruhito; Maeda, Toshio; Min, Jun Zhe; Inagaki, Shinsuke; Higashi, Tatsuya; Kagawa, Yoshiyuki; Toyo'oka, Toshimasa

    2011-05-12

    The number of diabetic patients has recently been increasing worldwide. Diabetes is a multifactorial disorder based on environmental factors and genetic background. In many cases, diabetes is asymptomatic for a long period and the patient is not aware of the disease. Therefore, the potential biomarker(s), leading to the early detection and/or prevention of diabetes mellitus, are strongly required. However, the diagnosis of the prediabetic state in humans is a very difficult issue, because the lifestyle is variable in each person. Although the development of a diagnosis method in humans is the goal of our research, the extraction and structural identification of biomarker candidates in several biological specimens (i.e., plasma, hair, liver and kidney) of ddY strain mice, which undergo naturally occurring diabetes along with aging, were carried out based upon a metabolite profiling study. The low-molecular-mass compounds including metabolites in the biological specimens of diabetic mice (ddY-H) and normal mice (ddY-L) were globally separated by ultra-performance liquid chromatography (UPLC) using different reversed-phase columns (i.e., T3-C18 and HS-F5) and detected by electrospray ionization time-of-flight mass spectrometry (ESI-TOF-MS). The biomarker candidates related to diabetes mellitus were extracted from a multivariate statistical analysis, such as an orthogonal partial least-squares-discriminant analysis (OPLS-DA), followed by a database search, such as ChemSpider, KEGG and HMDB. Many metabolites and unknown compounds in each biological specimen were detected as the biomarker candidates related to diabetic mellitus. Among them, the elucidation of the chemical structures of several possible metabolites, including more than two biological specimens, was carried out along with the comparison of the tandem MS/MS analyses using authentic compounds. One metabolite was clearly identified as N-acetyl-L-leucine based upon the MS/MS spectra and the retention time on

  17. Bioinformatics in translational drug discovery.

    Science.gov (United States)

    Wooller, Sarah K; Benstead-Hume, Graeme; Chen, Xiangrong; Ali, Yusuf; Pearl, Frances M G

    2017-08-31

    Bioinformatics approaches are becoming ever more essential in translational drug discovery both in academia and within the pharmaceutical industry. Computational exploitation of the increasing volumes of data generated during all phases of drug discovery is enabling key challenges of the process to be addressed. Here, we highlight some of the areas in which bioinformatics resources and methods are being developed to support the drug discovery pipeline. These include the creation of large data warehouses, bioinformatics algorithms to analyse 'big data' that identify novel drug targets and/or biomarkers, programs to assess the tractability of targets, and prediction of repositioning opportunities that use licensed drugs to treat additional indications. © 2017 The Author(s).

  18. Standardized evaluation of tumor-infiltrating lymphocytes in breast cancer: results of the ring studies of the international immuno-oncology biomarker working group.

    Science.gov (United States)

    Denkert, Carsten; Wienert, Stephan; Poterie, Audrey; Loibl, Sibylle; Budczies, Jan; Badve, Sunil; Bago-Horvath, Zsuzsanna; Bane, Anita; Bedri, Shahinaz; Brock, Jane; Chmielik, Ewa; Christgen, Matthias; Colpaert, Cecile; Demaria, Sandra; Van den Eynden, Gert; Floris, Giuseppe; Fox, Stephen B; Gao, Dongxia; Ingold Heppner, Barbara; Kim, S Rim; Kos, Zuzana; Kreipe, Hans H; Lakhani, Sunil R; Penault-Llorca, Frederique; Pruneri, Giancarlo; Radosevic-Robin, Nina; Rimm, David L; Schnitt, Stuart J; Sinn, Bruno V; Sinn, Peter; Sirtaine, Nicolas; O'Toole, Sandra A; Viale, Giuseppe; Van de Vijver, Koen; de Wind, Roland; von Minckwitz, Gunter; Klauschen, Frederick; Untch, Michael; Fasching, Peter A; Reimer, Toralf; Willard-Gallo, Karen; Michiels, Stefan; Loi, Sherene; Salgado, Roberto

    2016-10-01

    Multiple independent studies have shown that tumor-infiltrating lymphocytes (TIL) are prognostic in breast cancer with potential relevance for response to immune-checkpoint inhibitor therapy. Although many groups are currently evaluating TIL, there is no standardized system for diagnostic applications. This study reports the results of two ring studies investigating TIL conducted by the International Working Group on Immuno-oncology Biomarkers. The study aim was to determine the intraclass correlation coefficient (ICC) for evaluation of TIL by different pathologists. A total of 120 slides were evaluated by a large group of pathologists with a web-based system in ring study 1 and a more advanced software-system in ring study 2 that included an integrated feedback with standardized reference images. The predefined aim for successful ring studies 1 and 2 was an ICC above 0.7 (lower limit of 95% confidence interval (CI)). In ring study 1 the prespecified endpoint was not reached (ICC: 0.70; 95% CI: 0.62-0.78). On the basis of an analysis of sources of variation, we developed a more advanced digital image evaluation system for ring study 2, which improved the ICC to 0.89 (95% CI: 0.85-0.92). The Fleiss' kappa value for international standardization project shows that reproducible evaluation of TIL is feasible in breast cancer. This opens the way for standardized reporting of tumor immunological parameters in clinical studies and diagnostic practice. The software-guided image evaluation approach used in ring study 2 may be of value as a tool for evaluation of TIL in clinical trials and diagnostic practice. The experience gained from this approach might be applicable to the standardization of other diagnostic parameters in histopathology.

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

    DEFF Research Database (Denmark)

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

    2015-01-01

    There is an unmet need for new cardiovascular biomarkers. Despite this only few biomarkers for the diagnosis or screening of cardiovascular diseases have been implemented in the clinic. Thousands of proteins can be analysed in plasma by mass spectrometry-based proteomics technologies. Therefore......, 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...

  20. Biomarkers for Detecting Mitochondrial Disorders

    Directory of Open Access Journals (Sweden)

    Josef Finsterer

    2018-01-01

    Full Text Available (1 Objectives: Mitochondrial disorders (MIDs are a genetically and phenotypically heterogeneous group of slowly or rapidly progressive disorders with onset from birth to senescence. Because of their variegated clinical presentation, MIDs are difficult to diagnose and are frequently missed in their early and late stages. This is why there is a need to provide biomarkers, which can be easily obtained in the case of suspecting a MID to initiate the further diagnostic work-up. (2 Methods: Literature review. (3 Results: Biomarkers for diagnostic purposes are used to confirm a suspected diagnosis and to facilitate and speed up the diagnostic work-up. For diagnosing MIDs, a number of dry and wet biomarkers have been proposed. Dry biomarkers for MIDs include the history and clinical neurological exam and structural and functional imaging studies of the brain, muscle, or myocardium by ultrasound, computed tomography (CT, magnetic resonance imaging (MRI, MR-spectroscopy (MRS, positron emission tomography (PET, or functional MRI. Wet biomarkers from blood, urine, saliva, or cerebrospinal fluid (CSF for diagnosing MIDs include lactate, creatine-kinase, pyruvate, organic acids, amino acids, carnitines, oxidative stress markers, and circulating cytokines. The role of microRNAs, cutaneous respirometry, biopsy, exercise tests, and small molecule reporters as possible biomarkers is unsolved. (4 Conclusions: The disadvantages of most putative biomarkers for MIDs are that they hardly meet the criteria for being acceptable as a biomarker (missing longitudinal studies, not validated, not easily feasible, not cheap, not ubiquitously available and that not all MIDs manifest in the brain, muscle, or myocardium. There is currently a lack of validated biomarkers for diagnosing MIDs.

  1. Convergence of biomarkers, bioinformatics and nanotechnology for individualized cancer treatment

    Science.gov (United States)

    Phan, John H.; Moffitt, Richard A.; Stokes, Todd H.; Liu, Jian; Young, Andrew N.; Nie, Shuming; Wang, May D.

    2013-01-01

    Recent advances in biomarker discovery, biocomputing, and nanotechnology have raised new opportunities for the emerging field of personalized medicine in which disease detection, diagnosis, and therapy are tailored to each individual’s molecular profile, and also for predictive medicine that uses genetic/molecular information to predict disease development, progression, and clinical outcome. Here we discuss advanced biocomputing tools for cancer biomarker discovery and multiplexed nanoparticle probes for cancer biomarker profiling, together with prospects and challenges in correlating biomolecular signatures with clinical outcome. This bio-nano-info convergence holds great promise for molecular diagnosis and individualized therapy of cancer and other human diseases. PMID:19409634

  2. DNA Methylation Biomarkers: Cancer and Beyond

    Directory of Open Access Journals (Sweden)

    Thomas Mikeska

    2014-09-01

    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.

  3. Working with Data: Discovering Knowledge through Mining and Analysis; Systematic Knowledge Management and Knowledge Discovery; Text Mining; Methodological Approach in Discovering User Search Patterns through Web Log Analysis; Knowledge Discovery in Databases Using Formal Concept Analysis; Knowledge Discovery with a Little Perspective.

    Science.gov (United States)

    Qin, Jian; Jurisica, Igor; Liddy, Elizabeth D.; Jansen, Bernard J; Spink, Amanda; Priss, Uta; Norton, Melanie J.

    2000-01-01

    These six articles discuss knowledge discovery in databases (KDD). Topics include data mining; knowledge management systems; applications of knowledge discovery; text and Web mining; text mining and information retrieval; user search patterns through Web log analysis; concept analysis; data collection; and data structure inconsistency. (LRW)

  4. Considerations on development, validation, application, and quality control of immuno(metric) biomarker assays in clinical cancer research: an EORTC-NCI working group report.

    NARCIS (Netherlands)

    Sweep, C.G.J.; Fritsche, H.A.; Gion, M.; Klee, G.G.; Schmitt, M.

    2003-01-01

    A major dilemma associated with immuno(metric) assays for biomarkers is that various kits employing antibodies with differing specificities and binding affinities may generate non-equivalent test results. Also, variation in sample processing and the use of different standards (reference material)

  5. The role of vascular biomarkers for primary and secondary prevention. A position paper from the European Society of Cardiology Working Group on peripheral circulation

    DEFF Research Database (Denmark)

    Vlachopoulos, Charalambos; Xaplanteris, Panagiotis; Aboyans, Victor

    2015-01-01

    as a substitute for a clinical endpoint. In order to be considered as a surrogate endpoint of cardiovascular events, a biomarker should satisfy several criteria, such as proof of concept, prospective validation, incremental value, clinical utility, clinical outcomes, cost-effectiveness, ease of use...

  6. 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

    2012-11-01

    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.

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

    Directory of Open Access Journals (Sweden)

    Seema Patel

    2011-01-01

    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.

  8. Biomarkers in psoriasis and psoriatic arthritis.

    Science.gov (United States)

    Villanova, Federica; Di Meglio, Paola; Nestle, Frank O

    2013-04-01

    Psoriasis is a common immune-mediated disease of the skin, which associates in 20-30% of patients with psoriatic arthritis (PsA). The immunopathogenesis of both conditions is not fully understood as it is the result of a complex interaction between genetic, environmental and immunological factors. At present there is no cure for psoriasis and there are no specific markers that can accurately predict disease progression and therapeutic response. Therefore, biomarkers for disease prognosis and response to treatment are urgently needed to help clinicians with objective indications to improve patient management and outcomes. Although many efforts have been made to identify psoriasis/PsA biomarkers none of them has yet been translated into routine clinical practice. In this review we summarise the different classes of possible biomarkers explored in psoriasis and PsA so far and discuss novel strategies for biomarker discovery.

  9. 42 CFR 3.516 - Discovery.

    Science.gov (United States)

    2010-10-01

    ... 42 Public Health 1 2010-10-01 2010-10-01 false Discovery. 3.516 Section 3.516 Public Health PUBLIC... AND PATIENT SAFETY WORK PRODUCT Enforcement Program § 3.516 Discovery. (a) A party may make a request... and any forms of discovery, other than those permitted under paragraph (a) of this section, are not...

  10. Discovery Mondays

    CERN Multimedia

    2003-01-01

    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...

  11. Executive summary—Biomarkers of Nutrition for Development: Building a Consensus123

    Science.gov (United States)

    Namasté, Sorrel; Brabin, Bernard; Combs, Gerald; L'Abbe, Mary R; Wasantwisut, Emorn; Darnton-Hill, Ian

    2011-01-01

    The ability to develop evidence-based clinical guidance and effective programs and policies to achieve global health promotion and disease prevention goals depends on the availability of valid and reliable data. With specific regard to the role of food and nutrition in achieving those goals, relevant data are developed with the use of biomarkers that reflect nutrient exposure, status, and functional effect. A need exists to promote the discovery, development, and use of biomarkers across a range of applications. In addition, a process is needed to harmonize the global health community's decision making about what biomarkers are best suited for a given use under specific conditions and settings. To address these needs, the Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, US Department of Health and Human Services, organized a conference entitled “Biomarkers of Nutrition for Development: Building a Consensus,” which was hosted by the International Atomic Energy Agency. Partners included key multilateral, US agencies and public and private organizations. The assembly endorsed the utility of this initiative and the need for the BOND (Biomarkers of Nutrition for Development) project to continue. A consensus was reached on the requirement to develop a process to inform the community about the relative strengths or weaknesses and specific applications of various biomarkers under defined conditions. The articles in this supplement summarize the deliberations of the 4 working groups: research, clinical, policy, and programmatic. Also described are content presentations on the harmonization processes, the evidence base for biomarkers for 5 case-study micronutrients, and new frontiers in science and technology. PMID:21733880

  12. Fateful discovery almost forgotten

    International Nuclear Information System (INIS)

    Anon.

    1989-01-01

    The paper reviews the discovery of the fission of uranium, which took place fifty years ago. A description is given of the work of Meitner and Frisch in interpreting the Fermi data on the bombardment of uranium nuclei with neutrons, i.e. proposing fission. The historical events associated with the development and exploitation of uranium fission are described, including the Manhattan Project, Hiroshima and Nagasaki, Shippingport, and Chernobyl. (U.K.)

  13. New biomarkers for sepsis

    Directory of Open Access Journals (Sweden)

    Li-xin XIE

    2013-01-01

    Full Text Available There is a higher sepsis rate in the intensive care unit (ICU patients, which is one of the most important causes for patient death, but the sepsis lacks specific clinical manifestations. Exploring sensitive and specific molecular markers for infection that accurately reflect infection severity and prognosis is very clinically important. In this article, based on our previous study, we introduce some new biomarkers with high sensitivity and specificity for the diagnosis and predicting the prognosis and severity of sepsis. Increase of serum soluble(s triggering receptor expressed on myeloid cells-1 (sTREM-1 suggests a poor prognosis of septic patients, and changes of locus rs2234237 of sTREM-1 may be the one of important mechanisms. Additionally, urine sTREM-1 can provide an early warning of possible secondary acute kidney injury (AKI in sepsis patients. Serum sCD163 level was found to be a more important factor than procalcitonin (PCT and C-reactive protein (CRP in prognosis of sepsis, especially severe sepsis. Moreover, urine sCD163 also shows excellent performance in the diagnosis of sepsis and sepsis-associated AKI. Circulating microRNAs, such as miR-150, miR-297, miR-574-5p, miR -146a , miR-223, miR -15a and miR-16, also play important roles in the evaluation of status of septic patients. In the foreseeable future, newly-emerging technologies, including proteomics, metabonomics and trans-omics, may exert profound effects on the discovery of valuable biomarkers for sepsis.

  14. Identification and localization of trauma-related biomarkers using matrix assisted laser desorption/ionization imaging mass spectrometry

    Science.gov (United States)

    Jones, Kirstin; Reilly, Matthew A.; Glickman, Randolph D.

    2017-02-01

    Current treatments for ocular and optic nerve trauma are largely ineffective and may have adverse side effects; therefore, new approaches are needed to understand trauma mechanisms. Identification of trauma-related biomarkers may yield insights into the molecular aspects of tissue trauma that can contribute to the development of better diagnostics and treatments. The conventional approach for protein biomarker measurement largely relies on immunoaffinity methods that typically can only be applied to analytes for which antibodies or other targeting means are available. Matrix assisted laser-assisted desorption/ionization imaging mass spectrometry (MALDI-IMS) is a specialized application of mass spectrometry that not only is well suited to the discovery of novel or unanticipated biomarkers, but also provides information about the spatial localization of biomarkers in tissue. We have been using MALDI-IMS to find traumarelated protein biomarkers in retina and optic nerve tissue from animal models subjected to ocular injury produced by either blast overpressure or mechanical torsion. Work to date by our group, using MALDI-IMS, found that the pattern of protein expression is modified in the injured ocular tissue as soon as 24 hr post-injury, compared to controls. Specific proteins may be up- or down-regulated by trauma, suggesting different tissue responses to a given injury. Ongoing work is directed at identifying the proteins affected and mapping their expression in the ocular tissue, anticipating that systematic analysis can be used to identify targets for prospective therapies for ocular trauma.

  15. Semi-automated literature mining to identify putative biomarkers of disease from multiple biofluids

    Science.gov (United States)

    2014-01-01

    Background Computational methods for mining of biomedical literature can be useful in augmenting manual searches of the literature using keywords for disease-specific biomarker discovery from biofluids. In this work, we develop and apply a semi-automated literature mining method to mine abstracts obtained from PubMed to discover putative biomarkers of breast and lung cancers in specific biofluids. Methodology A positive set of abstracts was defined by the terms ‘breast cancer’ and ‘lung cancer’ in conjunction with 14 separate ‘biofluids’ (bile, blood, breastmilk, cerebrospinal fluid, mucus, plasma, saliva, semen, serum, synovial fluid, stool, sweat, tears, and urine), while a negative set of abstracts was defined by the terms ‘(biofluid) NOT breast cancer’ or ‘(biofluid) NOT lung cancer.’ More than 5.3 million total abstracts were obtained from PubMed and examined for biomarker-disease-biofluid associations (34,296 positive and 2,653,396 negative for breast cancer; 28,355 positive and 2,595,034 negative for lung cancer). Biological entities such as genes and proteins were tagged using ABNER, and processed using Python scripts to produce a list of putative biomarkers. Z-scores were calculated, ranked, and used to determine significance of putative biomarkers found. Manual verification of relevant abstracts was performed to assess our method’s performance. Results Biofluid-specific markers were identified from the literature, assigned relevance scores based on frequency of occurrence, and validated using known biomarker lists and/or databases for lung and breast cancer [NCBI’s On-line Mendelian Inheritance in Man (OMIM), Cancer Gene annotation server for cancer genomics (CAGE), NCBI’s Genes & Disease, NCI’s Early Detection Research Network (EDRN), and others]. The specificity of each marker for a given biofluid was calculated, and the performance of our semi-automated literature mining method assessed for breast and lung cancer

  16. Biomarkers in Diabetic Retinopathy

    Science.gov (United States)

    Jenkins, Alicia J.; Joglekar, Mugdha V.; Hardikar, Anandwardhan A.; Keech, Anthony C.; O'Neal, David N.; Januszewski, Andrzej S.

    2015-01-01

    There is a global diabetes epidemic correlating with an increase in obesity. This coincidence may lead to a rise in the prevalence of type 2 diabetes. There is also an as yet unexplained increase in the incidence of type 1 diabetes, which is not related to adiposity. Whilst improved diabetes care has substantially improved diabetes outcomes, the disease remains a common cause of working age adult-onset blindness. Diabetic retinopathy is the most frequently occurring complication of diabetes; it is greatly feared by many diabetes patients. There are multiple risk factors and markers for the onset and progression of diabetic retinopathy, yet residual risk remains. Screening for diabetic retinopathy is recommended to facilitate early detection and treatment. Common biomarkers of diabetic retinopathy and its risk in clinical practice today relate to the visualization of the retinal vasculature and measures of glycemia, lipids, blood pressure, body weight, smoking, and pregnancy status. Greater knowledge of novel biomarkers and mediators of diabetic retinopathy, such as those related to inflammation and angiogenesis, has contributed to the development of additional therapeutics, in particular for late-stage retinopathy, including intra-ocular corticosteroids and intravitreal vascular endothelial growth factor inhibitors ('anti-VEGFs') agents. Unfortunately, in spite of a range of treatments (including laser photocoagulation, intraocular steroids, and anti-VEGF agents, and more recently oral fenofibrate, a PPAR-alpha agonist lipid-lowering drug), many patients with diabetic retinopathy do not respond well to current therapeutics. Therefore, more effective treatments for diabetic retinopathy are necessary. New analytical techniques, in particular those related to molecular markers, are accelerating progress in diabetic retinopathy research. Given the increasing incidence and prevalence of diabetes, and the limited capacity of healthcare systems to screen and treat

  17. Biomarkers in Diabetic Retinopathy.

    Science.gov (United States)

    Jenkins, Alicia J; Joglekar, Mugdha V; Hardikar, Anandwardhan A; Keech, Anthony C; O'Neal, David N; Januszewski, Andrzej S

    2015-01-01

    There is a global diabetes epidemic correlating with an increase in obesity. This coincidence may lead to a rise in the prevalence of type 2 diabetes. There is also an as yet unexplained increase in the incidence of type 1 diabetes, which is not related to adiposity. Whilst improved diabetes care has substantially improved diabetes outcomes, the disease remains a common cause of working age adult-onset blindness. Diabetic retinopathy is the most frequently occurring complication of diabetes; it is greatly feared by many diabetes patients. There are multiple risk factors and markers for the onset and progression of diabetic retinopathy, yet residual risk remains. Screening for diabetic retinopathy is recommended to facilitate early detection and treatment. Common biomarkers of diabetic retinopathy and its risk in clinical practice today relate to the visualization of the retinal vasculature and measures of glycemia, lipids, blood pressure, body weight, smoking, and pregnancy status. Greater knowledge of novel biomarkers and mediators of diabetic retinopathy, such as those related to inflammation and angiogenesis, has contributed to the development of additional therapeutics, in particular for late-stage retinopathy, including intra-ocular corticosteroids and intravitreal vascular endothelial growth factor inhibitors ('anti-VEGFs') agents. Unfortunately, in spite of a range of treatments (including laser photocoagulation, intraocular steroids, and anti-VEGF agents, and more recently oral fenofibrate, a PPAR-alpha agonist lipid-lowering drug), many patients with diabetic retinopathy do not respond well to current therapeutics. Therefore, more effective treatments for diabetic retinopathy are necessary. New analytical techniques, in particular those related to molecular markers, are accelerating progress in diabetic retinopathy research. Given the increasing incidence and prevalence of diabetes, and the limited capacity of healthcare systems to screen and treat

  18. The neutron discovery

    International Nuclear Information System (INIS)

    Six, J.

    1987-01-01

    The neutron: who had first the idea, who discovered it, who established its main properties. To these apparently simple questions, multiple answers exist. The progressive discovery of the neutron is a marvellous illustration of some characteristics of the scientific research, where the unforeseen may be combined with the expected. This discovery is replaced in the context of the 1930's scientific effervescence that succeeded the revolutionary introduction of quantum mechanics. This book describes the works of Bothe, the Joliot-Curie and Chadwick which led to the neutron in an unexpected way. A historical analysis allows to give a new interpretation on the hypothesis suggested by the Joliot-Curie. Some texts of these days will help the reader to revive this fascinating story [fr

  19. Breath biomarkers in toxicology.

    Science.gov (United States)

    Pleil, Joachim D

    2016-11-01

    Exhaled breath has joined blood and urine as a valuable resource for sampling and analyzing biomarkers in human media for assessing exposure, uptake metabolism, and elimination of toxic chemicals. This article focuses current use of exhaled gas, aerosols, and vapor in human breath, the methods for collection, and ultimately the use of the resulting data. Some advantages of breath are the noninvasive and self-administered nature of collection, the essentially inexhaustible supply, and that breath sampling does not produce potentially infectious waste such as needles, wipes, bandages, and glassware. In contrast to blood and urine, breath samples can be collected on demand in rapid succession and so allow toxicokinetic observations of uptake and elimination in any time frame. Furthermore, new technologies now allow capturing condensed breath vapor directly, or just the aerosol fraction alone, to gain access to inorganic species, lung pH, proteins and protein fragments, cellular DNA, and whole microorganisms from the pulmonary microbiome. Future applications are discussed, especially the use of isotopically labeled probes, non-targeted (discovery) analysis, cellular level toxicity testing, and ultimately assessing "crowd breath" of groups of people and the relation to dose of airborne and other environmental chemicals at the population level.

  20. Metabolomics as a tool in the identification of dietary biomarkers.

    Science.gov (United States)

    Gibbons, Helena; Brennan, Lorraine

    2017-02-01

    Current dietary assessment methods including FFQ, 24-h recalls and weighed food diaries are associated with many measurement errors. In an attempt to overcome some of these errors, dietary biomarkers have emerged as a complementary approach to these traditional methods. Metabolomics has developed as a key technology for the identification of new dietary biomarkers and to date, metabolomic-based approaches have led to the identification of a number of putative biomarkers. The three approaches generally employed when using metabolomics in dietary biomarker discovery are: (i) acute interventions where participants consume specific amounts of a test food, (ii) cohort studies where metabolic profiles are compared between consumers and non-consumers of a specific food and (iii) the analysis of dietary patterns and metabolic profiles to identify nutritypes and biomarkers. The present review critiques the current literature in terms of the approaches used for dietary biomarker discovery and gives a detailed overview of the currently proposed biomarkers, highlighting steps needed for their full validation. Furthermore, the present review also evaluates areas such as current databases and software tools, which are needed to advance the interpretation of results and therefore enhance the utility of dietary biomarkers in nutrition research.

  1. Allergic asthma biomarkers using systems approaches

    Directory of Open Access Journals (Sweden)

    Gaurab eSircar

    2014-01-01

    Full Text Available Asthma is characterized by lung inflammation caused by complex interaction between the immune system and environmental factors such as allergens and inorganic pollutants. Recent research in this field is focused on discovering new biomarkers associated with asthma pathogenesis. This review illustrates updated research associating biomarkers of allergic asthma and their potential use in systems biology of the disease. We focus on biomolecules with altered expression, which may serve as inflammatory, diagnostic and therapeutic biomarkers of asthma discovered in human or experimental asthma model using genomic, proteomic and epigenomic approaches for gene and protein expression profiling. These include high-throughput technologies such as state of the art microarray and proteomics Mass Spectrometry (MS platforms. Emerging concepts of molecular interactions and pathways may provide new insights in searching potential clinical biomarkers. We summarized certain pathways with significant linkage to asthma pathophysiology by analyzing the compiled biomarkers. Systems approaches with this data can identify the regulating networks, which will eventually identify the key biomarkers to be used for diagnostics and drug discovery.

  2. Big Biomedical data as the key resource for discovery science

    Energy Technology Data Exchange (ETDEWEB)

    Toga, Arthur W.; Foster, Ian; Kesselman, Carl; Madduri, Ravi; Chard, Kyle; Deutsch, Eric W.; Price, Nathan D.; Glusman, Gustavo; Heavner, Benjamin D.; Dinov, Ivo D.; Ames, Joseph; Van Horn, John; Kramer, Roger; Hood, Leroy

    2015-07-21

    Modern biomedical data collection is generating exponentially more data in a multitude of formats. This flood of complex data poses significant opportunities to discover and understand the critical interplay among such diverse domains as genomics, proteomics, metabolomics, and phenomics, including imaging, biometrics, and clinical data. The Big Data for Discovery Science Center is taking an “-ome to home” approach to discover linkages between these disparate data sources by mining existing databases of proteomic and genomic data, brain images, and clinical assessments. In support of this work, the authors developed new technological capabilities that make it easy for researchers to manage, aggregate, manipulate, integrate, and model large amounts of distributed data. Guided by biological domain expertise, the Center’s computational resources and software will reveal relationships and patterns, aiding researchers in identifying biomarkers for the most confounding conditions and diseases, such as Parkinson’s and Alzheimer’s.

  3. Use of biomarkers in ALS drug development and clinical trials.

    Science.gov (United States)

    Bakkar, Nadine; Boehringer, Ashley; Bowser, Robert

    2015-05-14

    The past decade has seen a dramatic increase in the discovery of candidate biomarkers for ALS. These biomarkers typically can either differentiate ALS from control subjects or predict disease course (slow versus fast progression). At the same time, late-stage clinical trials for ALS have failed to generate improved drug treatments for ALS patients. Incorporation of biomarkers into the ALS drug development pipeline and the use of biologic and/or imaging biomarkers in early- and late-stage ALS clinical trials have been absent and only recently pursued in early-phase clinical trials. Further clinical research studies are needed to validate biomarkers for disease progression and develop biomarkers that can help determine that a drug has reached its target within the central nervous system. In this review we summarize recent progress in biomarkers across ALS model systems and patient population, and highlight continued research directions for biomarkers that stratify the patient population to enrich for patients that may best respond to a drug candidate, monitor disease progression and track drug responses in clinical trials. It is crucial that we further develop and validate ALS biomarkers and incorporate these biomarkers into the ALS drug development process. This article is part of a Special Issue entitled ALS complex pathogenesis. Copyright © 2014 Elsevier B.V. All rights reserved.

  4. Mass spectrometry-based proteomic quest for diabetes biomarkers.

    Science.gov (United States)

    Shao, Shiying; Guo, Tiannan; Aebersold, Ruedi

    2015-06-01

    Diabetes mellitus (DM) is a metabolic disorder characterized by chronic hyperglycemia, which affects hundreds of millions of individuals worldwide. Early diagnosis and complication prevention of DM are helpful for disease treatment. However, currently available DM diagnostic markers fail to achieve the goals. Identification of new diabetic biomarkers assisted by mass spectrometry (MS)-based proteomics may offer solution for the clinical challenges. Here, we review the current status of biomarker discovery in DM, and describe the pressure cycling technology (PCT)-Sequential Window Acquisition of all Theoretical fragment-ion (SWATH) workflow for sample-processing, biomarker discovery and validation, which may accelerate the current quest for DM biomarkers. This article is part of a Special Issue entitled: Medical Proteomics. Copyright © 2014 Elsevier B.V. All rights reserved.

  5. Biomarkers for Ectopic Pregnancy and Pregnancy of Unknown Location

    OpenAIRE

    Senapati, Suneeta; Barnhart, Kurt T.

    2013-01-01

    Early pregnancy failure is the most common complication of pregnancy, and 1–2% of all pregnancies will be ectopic. As one of the leading causes of maternal morbidity and mortality, diagnosing ectopic pregnancy and determining the fate of a pregnancy of unknown location are of great clinical concern. Several serum and plasma biomarkers for ectopic pregnancy have been investigated independently and in combination. The following is a review of the state of biomarker discovery and development for...

  6. Mining biomarker information in biomedical literature

    Directory of Open Access Journals (Sweden)

    Younesi Erfan

    2012-12-01

    ://www.scaiview.com/scaiview-academia.html. Conclusions The approach presented in this paper demonstrates that using a dedicated biomarker terminology for automated analysis of the scientific literature maybe helpful as an aid to finding biomarker information in text. Successful extraction of candidate biomarkers information from published resources can be considered as the first step towards developing novel hypotheses. These hypotheses will be valuable for the early decision-making in the drug discovery and development process.

  7. Other biomarkers for detecting prostate cancer.

    Science.gov (United States)

    Nogueira, Lucas; Corradi, Renato; Eastham, James A

    2010-01-01

    Prostate-specific antigen (PSA) has been used for detecting prostate cancer since 1994. Although it is the best cancer biomarker available, PSA is not perfect. It lacks both the sensitivity and specificity to accurately detect the presence of prostate cancer. None of the PSA thresholds currently in use consistently identify patients with prostate cancer and exclude patients without cancer. Novel approaches to improve our ability to detect prostate cancer and predict the course of the disease are needed. Additional methods for detecting prostate cancer have been evaluated. Despite the discovery of many new biomarkers, only a few have shown some clinical value. These markers include human kallikrein 2, urokinase-type plasminogen activator receptor, prostate-specific membrane antigen, early prostate cancer antigen, PCA3, alpha-methylacyl-CoA racemase and glutathione S-transferase pi hypermethylation. We review the reports on biomarkers for prostate cancer detection, and their possible role in the clinical practice.

  8. Differential Proteomics Identification of HSP90 as Potential Serum Biomarker in Hepatocellular Carcinoma by Two-dimensional Electrophoresis and Mass Spectrometry

    Directory of Open Access Journals (Sweden)

    Yiyi Sun

    2010-03-01

    Full Text Available The aim of the current study is to identify the potential biomarkers involved in Hepatocellular carcinoma (HCC carcinogenesis. A comparative proteomics approach was utilized to identify the differentially expressed proteins in the serum of 10 HCC patients and 10 controls. A total of 12 significantly altered proteins were identified by mass spectrometry. Of the 12 proteins identified, HSP90 was one of the most significantly altered proteins and its over-expression in the serum of 20 HCC patients was confirmed using ELISA analysis. The observations suggest that HSP90 might be a potential biomarker for early diagnosis, prognosis, and monitoring in the therapy of HCC. This work demonstrates that a comprehensive strategy of proteomic identification combined with further validation should be adopted in the field of cancer biomarker discovery.

  9. Combination of biomarkers

    DEFF Research Database (Denmark)

    Thurfjell, Lennart; Lötjönen, Jyrki; Lundqvist, Roger

    2012-01-01

    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....

  10. Differential membrane proteomics using 18O-labeling to identify biomarkers for cholangiocarcinoma

    DEFF Research Database (Denmark)

    Kristiansen, Troels Zakarias; Harsha, H C; Grønborg, Mads

    2008-01-01

    Quantitative proteomic methodologies allow profiling of hundreds to thousands of proteins in a high-throughput fashion. This approach is increasingly applied to cancer biomarker discovery to identify proteins that are differentially regulated in cancers. Fractionation of protein samples based...

  11. Biomarkers of tolerance: searching for the hidden phenotype.

    Science.gov (United States)

    Perucha, Esperanza; Rebollo-Mesa, Irene; Sagoo, Pervinder; Hernandez-Fuentes, Maria P

    2011-08-01

    Induction of transplantation tolerance remains the ideal long-term clinical and logistic solution to the current challenges facing the management of renal allograft recipients. In this review, we describe the recent studies and advances made in identifying biomarkers of renal transplant tolerance, from study inceptions, to the lessons learned and their implications for current and future studies with the same goal. With the age of biomarker discovery entering a new dimension of high-throughput technologies, here we also review the current approaches, developments, and pitfalls faced in the subsequent statistical analysis required to identify valid biomarker candidates.

  12. Dumpling Discoveries

    Institute of Scientific and Technical Information of China (English)

    2008-01-01

    Americans have a taste for Chinese food,but is it authentic? It’s 12:30 p.m.on Tuesday,time for a break from the day’s busy work and time for a relaxing lunch with col- leagues or friends.Alex Steed and his friend Faith Rose are sitting at a table trying to pick out the most attractive names of dishes from a bilingual menu at a Chinese restaurant in New York City’s Chinatown, six blocks away from Steed’s office in lower Manhattan.

  13. Impact of biomarker development on drug safety assessment

    International Nuclear Information System (INIS)

    Marrer, Estelle; Dieterle, Frank

    2010-01-01

    Drug safety has always been a key aspect of drug development. Recently, the Vioxx case and several cases of serious adverse events being linked to high-profile products have increased the importance of drug safety, especially in the eyes of drug development companies and global regulatory agencies. Safety biomarkers are increasingly being seen as helping to provide the clarity, predictability, and certainty needed to gain confidence in decision making: early-stage projects can be stopped quicker, late-stage projects become less risky. Public and private organizations are investing heavily in terms of time, money and manpower on safety biomarker development. An illustrative and 'door opening' safety biomarker success story is the recent recognition of kidney safety biomarkers for pre-clinical and limited translational contexts by FDA and EMEA. This milestone achieved for kidney biomarkers and the 'know how' acquired is being transferred to other organ toxicities, namely liver, heart, vascular system. New technologies and molecular-based approaches, i.e., molecular pathology as a complement to the classical toolbox, allow promising discoveries in the safety biomarker field. This review will focus on the utility and use of safety biomarkers all along drug development, highlighting the present gaps and opportunities identified in organ toxicity monitoring. A last part will be dedicated to safety biomarker development in general, from identification to diagnostic tests, using the kidney safety biomarkers success as an illustrative example.

  14. 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)

    2013-01-01

    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,

  15. Biology and Biomarkers for Wound Healing

    Science.gov (United States)

    Lindley, Linsey E.; Stojadinovic, Olivera; Pastar, Irena; Tomic-Canic, Marjana

    2016-01-01

    Background As the population grows older, the incidence and prevalence of conditions which lead to a predisposition for poor wound healing also increases. Ultimately, this increase in non-healing wounds has led to significant morbidity and mortality with subsequent huge economic ramifications. Therefore, understanding specific molecular mechanisms underlying aberrant wound healing is of great importance. It has, and will continue to be the leading pathway to the discovery of therapeutic targets as well as diagnostic molecular biomarkers. Biomarkers may help identify and stratify subsets of non-healing patients for whom biomarker-guided approaches may aid in healing. Methods A series of literature searches were performed using Medline, PubMed, Cochrane Library, and Internet searches. Results Currently, biomarkers are being identified using biomaterials sourced locally, from human wounds and/or systemically using systematic high-throughput “omics” modalities (genomic, proteomic, lipidomic, metabolomic analysis). In this review we highlight the current status of clinically applicable biomarkers and propose multiple steps in validation and implementation spectrum including those measured in tissue specimens e.g. β-catenin and c-myc, wound fluid e.g. MMP’s and interleukins, swabs e.g. wound microbiota and serum e.g. procalcitonin and MMP’s. Conclusions Identification of numerous potential biomarkers utilizing different avenues of sample collection and molecular approaches is currently underway. A focus on simplicity, and consistent implementation of these biomarkers as well as an emphasis on efficacious follow-up therapeutics is necessary for transition of this technology to clinically feasible point-of-care applications. PMID:27556760

  16. Integrative analysis to select cancer candidate biomarkers to targeted validation

    Science.gov (United States)

    Heberle, Henry; Domingues, Romênia R.; Granato, Daniela C.; Yokoo, Sami; Canevarolo, Rafael R.; Winck, Flavia V.; Ribeiro, Ana Carolina P.; Brandão, Thaís Bianca; Filgueiras, Paulo R.; Cruz, Karen S. P.; Barbuto, José Alexandre; Poppi, Ronei J.; Minghim, Rosane; Telles, Guilherme P.; Fonseca, Felipe Paiva; Fox, Jay W.; Santos-Silva, Alan R.; Coletta, Ricardo D.; Sherman, Nicholas E.; Paes Leme, Adriana F.

    2015-01-01

    Targeted proteomics has flourished as the method of choice for prospecting for and validating potential candidate biomarkers in many diseases. However, challenges still remain due to the lack of standardized routines that can prioritize a limited number of proteins to be further validated in human samples. To help researchers identify candidate biomarkers that best characterize their samples under study, a well-designed integrative analysis pipeline, comprising MS-based discovery, feature selection methods, clustering techniques, bioinformatic analyses and targeted approaches was performed using discovery-based proteomic data from the secretomes of three classes of human cell lines (carcinoma, melanoma and non-cancerous). Three feature selection algorithms, namely, Beta-binomial, Nearest Shrunken Centroids (NSC), and Support Vector Machine-Recursive Features Elimination (SVM-RFE), indicated a panel of 137 candidate biomarkers for carcinoma and 271 for melanoma, which were differentially abundant between the tumor classes. We further tested the strength of the pipeline in selecting candidate biomarkers by immunoblotting, human tissue microarrays, label-free targeted MS and functional experiments. In conclusion, the proposed integrative analysis was able to pre-qualify and prioritize candidate biomarkers from discovery-based proteomics to targeted MS. PMID:26540631

  17. Accelerometer-assessed sedentary work, leisure time and cardio-metabolic biomarkers during one year: Effectiveness of a cluster randomized controlled trial in parents with a sedentary occupation and young children.

    Directory of Open Access Journals (Sweden)

    Arto J Pesola

    Full Text Available It is unknown whether reducing sedentary time at work and during leisure time is possible and effective during one year.Office workers with young children were recruited for this one-year cluster-randomized controlled trial through kindergartens and primary schools from 7 clusters in the city of Jyväskylä, Finland. After a lecture, face-to-face tailored counseling was used to set contractually binding goals regarding reducing and breaking up sitting periods and increasing light intensity physical activity during work and leisure time. Primary outcomes of total, work and leisure sedentary time (<100 counts/min, cpm, light activity time (<2020 cpm, moderate-to-vigorous activity time (MVPA and breaks/sedentary hour were assessed with a waist-worn Alive -accelerometer for 7 days, 5 times during the year. Anthropometrics (DXA, fasting biomarkers and self-reported diet were assessed as secondary outcomes. Data were collected between 2011-2013 and analyzed between 2013-2016 with a linear mixed-effects model fit by REML using likelihood ratio test and intention-to-treat-principle.Participants from intervention (N = 71 and control (N = 62 regions were assessed at baseline and 117 completed the study. Sedentary leisure time decreased [-21.2 (95% CI -37.3 to -5.1 min/8 hours, likelihood ratio P<0.001] and light activity time [13.4 (-2.2 to 29.0 min/8 hours, P = 0.008] and breaks per sedentary hour [1.0 (-0.2 to 2.2, P = 0.010] increased in the intervention group as compared to controls at 3 months. The decrease in sedentary leisure time was maintained throughout the year [-7.9 (-24.0 to 8.3 min/8 hours, P = 0.029]. Small decreases in the control group's work and leisure MVPA were observed mostly at 3 months. Small favorable intervention effects were observed for fasting plasma glucose at 3 months and for leg lean mass and apoB/apoA-1 ratio at 12 months, with no changes in other outcomes.Behavioral counseling induced a small decline in sedentary leisure

  18. Accelerometer-assessed sedentary work, leisure time and cardio-metabolic biomarkers during one year: Effectiveness of a cluster randomized controlled trial in parents with a sedentary occupation and young children.

    Science.gov (United States)

    Pesola, Arto J; Laukkanen, Arto; Heikkinen, Risto; Sipilä, Sarianna; Sääkslahti, Arja; Finni, Taija

    2017-01-01

    It is unknown whether reducing sedentary time at work and during leisure time is possible and effective during one year. Office workers with young children were recruited for this one-year cluster-randomized controlled trial through kindergartens and primary schools from 7 clusters in the city of Jyväskylä, Finland. After a lecture, face-to-face tailored counseling was used to set contractually binding goals regarding reducing and breaking up sitting periods and increasing light intensity physical activity during work and leisure time. Primary outcomes of total, work and leisure sedentary time (sedentary hour were assessed with a waist-worn Alive -accelerometer for 7 days, 5 times during the year. Anthropometrics (DXA), fasting biomarkers and self-reported diet were assessed as secondary outcomes. Data were collected between 2011-2013 and analyzed between 2013-2016 with a linear mixed-effects model fit by REML using likelihood ratio test and intention-to-treat-principle. Participants from intervention (N = 71) and control (N = 62) regions were assessed at baseline and 117 completed the study. Sedentary leisure time decreased [-21.2 (95% CI -37.3 to -5.1) min/8 hours, likelihood ratio Psedentary hour [1.0 (-0.2 to 2.2), P = 0.010] increased in the intervention group as compared to controls at 3 months. The decrease in sedentary leisure time was maintained throughout the year [-7.9 (-24.0 to 8.3) min/8 hours, P = 0.029]. Small decreases in the control group's work and leisure MVPA were observed mostly at 3 months. Small favorable intervention effects were observed for fasting plasma glucose at 3 months and for leg lean mass and apoB/apoA-1 ratio at 12 months, with no changes in other outcomes. Behavioral counseling induced a small decline in sedentary leisure time throughout one year in parents with a sedentary occupation and young children. Small concurrent changes in different biomarkers suggest that reducing sedentary leisure time during one year may be

  19. Design of the DISCovery project: tailored work-oriented interventions to improve employee health, well-being, and performance-related outcomes in hospital care

    OpenAIRE

    Niks Irene MW; de Jonge Jan; Gevers Josette MP; Houtman Irene LD

    2013-01-01

    Abstract Background It is well-known that health care workers in today’s general hospitals have to deal with high levels of job demands, which could have negative effects on their health, well-being, and job performance. A way to reduce job-related stress reactions and to optimize positive work-related outcomes is to raise the level of specific job resources and opportunities to recover from work. However, the question remains how to translate the optimization of the balance between job deman...

  20. Cardiac biomarkers in Neonatology

    OpenAIRE

    Vijlbrief, D.C.

    2015-01-01

    In this thesis, the role for cardiac biomarkers in neonatology was investigated. Several clinically relevant results were reported. In term and preterm infants, hypoxia and subsequent adaptation play an important role in cardiac biomarker elevation. The elevated natriuretic peptides are indicative of abnormal function; elevated troponins are suggestive for cardiomyocyte damage. This methodology makes these biomarkers of additional value in the treatment of newborn infants, separate or as a co...

  1. Design of the DISCovery project: Tailored work-oriented interventions to improve employee health, well-being, and performance-related outcomes in hospital care

    NARCIS (Netherlands)

    Niks, I.M.W.; Jonge, J. de; Gevers, J.M.P; Houtman, I.L.D.

    2013-01-01

    Background: It is well-known that health care workers in today's general hospitals have to deal with high levels of job demands, which could have negative effects on their health, well-being, and job performance. A way to reduce job-related stress reactions and to optimize positive work-related

  2. Design of the DISCovery project : tailored work-oriented interventions to improve employee health, well-being and performance-related outcomes in hospital care.

    NARCIS (Netherlands)

    Niks, I.M.W.; Jonge, de J.; Gevers, J.M.P.; Houtman, I.L.D.

    2013-01-01

    Background It is well-known that health care workers in today’s general hospitals have to deal with high levels of job demands, which could have negative effects on their health, well-being, and job performance. A way to reduce job-related stress reactions and to optimize positive work-related

  3. The discovery of the antiproton

    International Nuclear Information System (INIS)

    Chamberlain, Owen

    1989-01-01

    A number of groups of particle physicists competed to provide track evidence of the existence of Dirac's postulated antiproton in the mid-1950s. The work of the several teams is described briefly. The author describes the work of his own group on the Bevatron in more detail, and how they finally observed the antiproton. The article finishes with an assessment of the importance of this discovery. (UK)

  4. Discovery and the atom

    International Nuclear Information System (INIS)

    1989-01-01

    ''Discovery and the Atom'' tells the story of the founding of nuclear physics. This programme looks at nuclear physics up to the discovery of the neutron in 1932. Animation explains the science of the classic experiments, such as the scattering of alpha particles by Rutherford and the discovery of the nucleus. Archive film shows the people: Lord Rutherford, James Chadwick, Marie Curie. (author)

  5. Urine Exosomes: An Emerging Trove of Biomarkers.

    Science.gov (United States)

    Street, J M; Koritzinsky, E H; Glispie, D M; Star, R A; Yuen, P S T

    Exosomes are released by most cells and can be isolated from all biofluids including urine. Exosomes are small vesicles formed as part of the endosomal pathway that contain cellular material surrounded by a lipid bilayer that can be traced to the plasma membrane. Exosomes are potentially a more targeted source of material for biomarker discovery than unfractionated urine, and provide diagnostic and pathophysiological information without an invasive tissue biopsy. Cytoplasmic contents including protein, mRNA, miRNA, and lipids have all been studied within the exosomal fraction. Many prospective urinary exosomal biomarkers have been successfully identified for a variety of kidney or genitourinary tract conditions; detection of systemic conditions may also be possible. Isolation and analysis of exosomes can be achieved by several approaches, although many require specialized equipment or involve lengthy protocols. The need for timely analysis in the clinical setting has driven considerable innovation with several promising options recently emerging. Consensus on exosome isolation, characterization, and normalization procedures would resolve critical clinical translational bottlenecks for existing candidate exosomal biomarkers and provide a template for additional discovery studies. 2017 Published by Elsevier Inc.

  6. Urine biomarkers in the early stages of diseases: current status and perspective.

    Science.gov (United States)

    Jing, Jian; Gao, Youhe

    2018-02-01

    As a noninvasive and easily available biological fluid, the urine is becoming an important source for disease biomarker study. Change is essential for the usefulness of a biomarker. Without homeostasis mechanisms, urine can accommodate more changes, especially in the early stages of diseases. In this review, we summarize current status and discuss perspectives on the discovery of urine biomarkers in the early stages of diseases. We emphasize the advantages of urine biomarkers compared to plasma biomarkers for the diagnosis of diseases at early stages, propose a urine biomarker research roadmap, and highlight a novel membrane storage technique that enables large-scale urine sample collection and storage efficiently and economically. It is anticipated that urine biomarker studies will greatly promote early diagnosis, prevention, treatment, and prognosis of a variety of diseases, and provide strong support for translational and precision medicine.

  7. Serum Proteomics in Dementia : Discovery and Validation of Biomarkers

    NARCIS (Netherlands)

    L. IJsselstijn (Linda)

    2013-01-01

    textabstractDementia is a syndrome due to disease of the brain, usually of a chronic or progressive nature, in which there is disturbance of multiple higher cortical functions, including memory, thinking, orientation, comprehension, calculation, learning capacity, language, and

  8. Scalable Biomarker Discovery for Diverse High-Dimensional Phenotypes

    Science.gov (United States)

    2015-11-23

    William D. Shannon, Richard R. Sharp, Thomas J. Sharpton, Narmada Shenoy, Nihar U. Sheth, Gina A. Simone, Indresh Singh, Chris S. Smillie, Jack D... William D. Shannon, Richard R. Sharp, Thomas J. Sharpton, Narmada Shenoy, Nihar U. Sheth, Gina A. Simone, Indresh Singh, Christopher S. Smillie, Jack D...Susanne J. Szabo, Jeff Porter, Harri Lähdesmäki, Curtis Huttenhower, Dirk Gevers, Thomas W. Cullen , Mikael Knip, on behalf of the DIABIMMUNE Study Group

  9. THE DISCOVERY OF BIOMARKERS OF VIRAL INFECTIVITY BY MASS SPECTROMETRY

    Science.gov (United States)

    Over the past three decades, the CDC and the U.S. EPA have collected and reported data relating to occurrences and causes of waterborne-disease outbreaks in the United States. Thirty nine outbreaks associated with drinking water were reported during 1999-2000. According to CDC'...

  10. 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.

    2009-01-01

    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

  11. Seasonal allergic rhinitis and systems biology-oriented biomarker discovery

    NARCIS (Netherlands)

    Baars, E.W.; Nierop, A.F.M.; Savelkoul, H.F.J.

    2015-01-01

    There is an increasing interest in science and medicine in the systems approach. Instead of the reductionist approach that focuses on the physical and chemical properties of the individual components, systems biology aims to describe, understand, and explain from the complex biological systems

  12. Topology Discovery Using Cisco Discovery Protocol

    OpenAIRE

    Rodriguez, Sergio R.

    2009-01-01

    In this paper we address the problem of discovering network topology in proprietary networks. Namely, we investigate topology discovery in Cisco-based networks. Cisco devices run Cisco Discovery Protocol (CDP) which holds information about these devices. We first compare properties of topologies that can be obtained from networks deploying CDP versus Spanning Tree Protocol (STP) and Management Information Base (MIB) Forwarding Database (FDB). Then we describe a method of discovering topology ...

  13. Biomarkers for equine joint injury and osteoarthritis.

    Science.gov (United States)

    McIlwraith, C Wayne; Kawcak, Christopher E; Frisbie, David D; Little, Christopher B; Clegg, Peter D; Peffers, Mandy J; Karsdal, Morten A; Ekman, Stina; Laverty, Sheila; Slayden, Richard A; Sandell, Linda J; Lohmander, L S; Kraus, Virginia B

    2018-03-01

    We report the results of a symposium aimed at identifying validated biomarkers that can be used to complement clinical observations for diagnosis and prognosis of joint injury leading to equine osteoarthritis (OA). Biomarkers might also predict pre-fracture change that could lead to catastrophic bone failure in equine athletes. The workshop was attended by leading scientists in the fields of equine and human musculoskeletal biomarkers to enable cross-disciplinary exchange and improve knowledge in both. Detailed proceedings with strategic planning was written, added to, edited and referenced to develop this manuscript. The most recent information from work in equine and human osteoarthritic biomarkers was accumulated, including the use of personalized healthcare to stratify OA phenotypes, transcriptome analysis of anterior cruciate ligament (ACL) and meniscal injuries in the human knee. The spectrum of "wet" biomarker assays that are antibody based that have achieved usefulness in both humans and horses, imaging biomarkers and the role they can play in equine and human OA was discussed. Prediction of musculoskeletal injury in the horse remains a challenge, and the potential usefulness of spectroscopy, metabolomics, proteomics, and development of biobanks to classify biomarkers in different stages of equine and human OA were reviewed. The participants concluded that new information and studies in equine musculoskeletal biomarkers have potential translational value for humans and vice versa. OA is equally important in humans and horses, and the welfare issues associated with catastrophic musculoskeletal injury in horses add further emphasis to the need for good validated biomarkers in the horse. © 2017 Orthopaedic Research Society. Published by Wiley Periodicals, Inc. J Orthop Res 36:823-831, 2018. © 2017 Orthopaedic Research Society. Published by Wiley Periodicals, Inc.

  14. Biomarkers of Hypoxic Ischemic Encephalopathy in Newborns

    Directory of Open Access Journals (Sweden)

    Martha V. Douglas-Escobar

    2012-11-01

    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. Biomarkers in Autism

    Directory of Open Access Journals (Sweden)

    Robert eHendren

    2014-08-01

    Full Text Available Autism spectrum disorders (ASD are complex, heterogeneous disorders caused by an interaction between genetic vulnerability and environmental factors. In an effort to better target the underlying roots of ASD for diagnosis and treatment, efforts to identify reliable biomarkers in genetics, neuroimaging, gene expression and measures of the body’s metabolism are growing. For this article, we review the published studies of potential biomarkers in autism and conclude that while there is increasing promise of finding biomarkers that can help us target treatment, there are none with enough evidence to support routine clinical use unless medical illness is suspected. Promising biomarkers include those for mitochondrial function, oxidative stress, and immune function. Genetic clusters are also suggesting the potential for useful biomarkers.

  16. Towards understanding and predicting suicidality in women: biomarkers and clinical risk assessment.

    Science.gov (United States)

    Levey, D F; Niculescu, E M; Le-Niculescu, H; Dainton, H L; Phalen, P L; Ladd, T B; Weber, H; Belanger, E; Graham, D L; Khan, F N; Vanipenta, N P; Stage, E C; Ballew, A; Yard, M; Gelbart, T; Shekhar, A; Schork, N J; Kurian, S M; Sandusky, G E; Salomon, D R; Niculescu, A B

    2016-06-01

    Women are under-represented in research on suicidality to date. Although women have a lower rate of suicide completion than men, due in part to the less-violent methods used, they have a higher rate of suicide attempts. Our group has previously identified genomic (blood gene expression biomarkers) and clinical information (apps) predictors for suicidality in men. We now describe pilot studies in women. We used a powerful within-participant discovery approach to identify genes that change in expression between no suicidal ideation (no SI) and high suicidal ideation (high SI) states (n=12 participants out of a cohort of 51 women psychiatric participants followed longitudinally, with diagnoses of bipolar disorder, depression, schizoaffective disorder and schizophrenia). We then used a Convergent Functional Genomics (CFG) approach to prioritize the candidate biomarkers identified in the discovery step by using all the prior evidence in the field. Next, we validated for suicidal behavior the top-ranked biomarkers for SI, in a demographically matched cohort of women suicide completers from the coroner's office (n=6), by assessing which markers were stepwise changed from no SI to high SI to suicide completers. We then tested the 50 biomarkers that survived Bonferroni correction in the validation step, as well as top increased and decreased biomarkers from the discovery and prioritization steps, in a completely independent test cohort of women psychiatric disorder participants for prediction of SI (n=33) and in a future follow-up cohort of psychiatric disorder participants for prediction of psychiatric hospitalizations due to suicidality (n=24). Additionally, we examined how two clinical instruments in the form of apps, Convergent Functional Information for Suicidality (CFI-S) and Simplified Affective State Scale (SASS), previously tested in men, perform in women. The top CFI-S item distinguishing high SI from no SI states was the chronic stress of social isolation. We

  17. Detection of biomarkers for Hepatocellular Carcinoma using a hybrid univariate gene selection methods

    Directory of Open Access Journals (Sweden)

    Abdel Samee Nagwan M

    2012-08-01

    Full Text Available Abstract Background Discovering new biomarkers has a great role in improving early diagnosis of Hepatocellular carcinoma (HCC. The experimental determination of biomarkers needs a lot of time and money. This motivates this work to use in-silico prediction of biomarkers to reduce the number of experiments required for detecting new ones. This is achieved by extracting the most representative genes in microarrays of HCC. Results In this work, we provide a method for extracting the differential expressed genes, up regulated ones, that can be considered candidate biomarkers in high throughput microarrays of HCC. We examine the power of several gene selection methods (such as Pearson’s correlation coefficient, Cosine coefficient, Euclidean distance, Mutual information and Entropy with different estimators in selecting informative genes. A biological interpretation of the highly ranked genes is done using KEGG (Kyoto Encyclopedia of Genes and Genomes pathways, ENTREZ and DAVID (Database for Annotation, Visualization, and Integrated Discovery databases. The top ten genes selected using Pearson’s correlation coefficient and Cosine coefficient contained six genes that have been implicated in cancer (often multiple cancers genesis in previous studies. A fewer number of genes were obtained by the other methods (4 genes using Mutual information, 3genes using Euclidean distance and only one gene using Entropy. A better result was obtained by the utilization of a hybrid approach based on intersecting the highly ranked genes in the output of all investigated methods. This hybrid combination yielded seven genes (2 genes for HCC and 5 genes in different types of cancer in the top ten genes of the list of intersected genes. Conclusions To strengthen the effectiveness of the univariate selection methods, we propose a hybrid approach by intersecting several of these methods in a cascaded manner. This approach surpasses all of univariate selection methods when

  18. Biomarkers in Alzheimer’s Disease Analysis by Mass Spectrometry-Based Proteomics

    Directory of Open Access Journals (Sweden)

    Yahui Liu

    2014-05-01

    Full Text Available Alzheimer’s disease (AD is a common chronic and destructive disease. The early diagnosis of AD is difficult, thus the need for clinically applicable biomarkers development is growing rapidly. There are many methods to biomarker discovery and identification. In this review, we aim to summarize Mass spectrometry (MS-based proteomics studies on AD and discuss thoroughly the methods to identify candidate biomarkers in cerebrospinal fluid (CSF and blood. This review will also discuss the potential research areas on biomarkers.

  19. Metabolomics: beyond biomarkers and towards mechanisms

    Science.gov (United States)

    Johnson, Caroline H.; Ivanisevic, Julijana; Siuzdak, Gary

    2017-01-01

    Metabolomics, which is the profiling of metabolites in biofluids, cells and tissues, is routinely applied as a tool for biomarker discovery. Owing to innovative developments in informatics and analytical technologies, and the integration of orthogonal biological approaches, it is now possible to expand metabolomic analyses to understand the systems-level effects of metabolites. Moreover, because of the inherent sensitivity of metabolomics, subtle alterations in biological pathways can be detected to provide insight into the mechanisms that underlie various physiological conditions and aberrant processes, including diseases. PMID:26979502

  20. Prognostic biomarkers in osteoarthritis

    Science.gov (United States)

    Attur, Mukundan; Krasnokutsky-Samuels, Svetlana; Samuels, Jonathan; Abramson, Steven B.

    2013-01-01

    Purpose of review Identification of patients at risk for incident disease or disease progression in osteoarthritis remains challenging, as radiography is an insensitive reflection of molecular changes that presage cartilage and bone abnormalities. Thus there is a widely appreciated need for biochemical and imaging biomarkers. We describe recent developments with such biomarkers to identify osteoarthritis patients who are at risk for disease progression. Recent findings The biochemical markers currently under evaluation include anabolic, catabolic, and inflammatory molecules representing diverse biological pathways. A few promising cartilage and bone degradation and synthesis biomarkers are in various stages of development, awaiting further validation in larger populations. A number of studies have shown elevated expression levels of inflammatory biomarkers, both locally (synovial fluid) and systemically (serum and plasma). These chemical biomarkers are under evaluation in combination with imaging biomarkers to predict early onset and the burden of disease. Summary Prognostic biomarkers may be used in clinical knee osteoarthritis to identify subgroups in whom the disease progresses at different rates. This could facilitate our understanding of the pathogenesis and allow us to differentiate phenotypes within a heterogeneous knee osteoarthritis population. Ultimately, such findings may help facilitate the development of disease-modifying osteoarthritis drugs (DMOADs). PMID:23169101

  1. Molecular Elucidation of Disease Biomarkers at the Interface of Chemistry and Biology.

    Science.gov (United States)

    Zhang, Liqin; Wan, Shuo; Jiang, Ying; Wang, Yanyue; Fu, Ting; Liu, Qiaoling; Cao, Zhijuan; Qiu, Liping; Tan, Weihong

    2017-02-22

    Disease-related biomarkers are objectively measurable molecular signatures of physiological status that can serve as disease indicators or drug targets in clinical diagnosis and therapy, thus acting as a tool in support of personalized medicine. For example, the prostate-specific antigen (PSA) biomarker is now widely used to screen patients for prostate cancer. However, few such biomarkers are currently available, and the process of biomarker identification and validation is prolonged and complicated by inefficient methods of discovery and few reliable analytical platforms. Therefore, in this Perspective, we look at the advanced chemistry of aptamer molecules and their significant role as molecular probes in biomarker studies. As a special class of functional nucleic acids evolved from an iterative technology termed Systematic Evolution of Ligands by Exponential Enrichment (SELEX), these single-stranded oligonucleotides can recognize their respective targets with selectivity and affinity comparable to those of protein antibodies. Because of their fast turnaround time and exceptional chemical properties, aptamer probes can serve as novel molecular tools for biomarker investigations, particularly in assisting identification of new disease-related biomarkers. More importantly, aptamers are able to recognize biomarkers from complex biological environments such as blood serum and cell surfaces, which can provide direct evidence for further clinical applications. This Perspective highlights several major advancements of aptamer-based biomarker discovery strategies and their potential contribution to the practice of precision medicine.

  2. Maximum Entropy in Drug Discovery

    Directory of Open Access Journals (Sweden)

    Chih-Yuan Tseng

    2014-07-01

    Full Text Available Drug discovery applies multidisciplinary approaches either experimentally, computationally or both ways to identify lead compounds to treat various diseases. While conventional approaches have yielded many US Food and Drug Administration (FDA-approved drugs, researchers continue investigating and designing better approaches to increase the success rate in the discovery process. In this article, we provide an overview of the current strategies and point out where and how the method of maximum entropy has been introduced in this area. The maximum entropy principle has its root in thermodynamics, yet since Jaynes’ pioneering work in the 1950s, the maximum entropy principle has not only been used as a physics law, but also as a reasoning tool that allows us to process information in hand with the least bias. Its applicability in various disciplines has been abundantly demonstrated. We give several examples of applications of maximum entropy in different stages of drug discovery. Finally, we discuss a promising new direction in drug discovery that is likely to hinge on the ways of utilizing maximum entropy.

  3. COPD Exacerbation Biomarkers Validated Using Multiple Reaction Monitoring Mass Spectrometry.

    Directory of Open Access Journals (Sweden)

    Janice M Leung

    Full Text Available Acute exacerbations of chronic obstructive pulmonary disease (AECOPD result in considerable morbidity and mortality. However, there are no objective biomarkers to diagnose AECOPD.We used multiple reaction monitoring mass spectrometry to quantify 129 distinct proteins in plasma samples from patients with COPD. This analytical approach was first performed in a biomarker cohort of patients hospitalized with AECOPD (Cohort A, n = 72. Proteins differentially expressed between AECOPD and convalescent states were chosen using a false discovery rate 1.2. Protein selection and classifier building were performed using an elastic net logistic regression model. The performance of the biomarker panel was then tested in two independent AECOPD cohorts (Cohort B, n = 37, and Cohort C, n = 109 using leave-pair-out cross-validation methods.Five proteins were identified distinguishing AECOPD and convalescent states in Cohort A. Biomarker scores derived from this model were significantly higher during AECOPD than in the convalescent state in the discovery cohort (p<0.001. The receiver operating characteristic cross-validation area under the curve (CV-AUC statistic was 0.73 in Cohort A, while in the replication cohorts the CV-AUC was 0.77 for Cohort B and 0.79 for Cohort C.A panel of five biomarkers shows promise in distinguishing AECOPD from convalescence and may provide the basis for a clinical blood test to diagnose AECOPD. Further validation in larger cohorts is necessary for future clinical translation.

  4. The current status of biomarkers for predicting toxicity

    Science.gov (United States)

    Campion, Sarah; Aubrecht, Jiri; Boekelheide, Kim; Brewster, David W; Vaidya, Vishal S; Anderson, Linnea; Burt, Deborah; Dere, Edward; Hwang, Kathleen; Pacheco, Sara; Saikumar, Janani; Schomaker, Shelli; Sigman, Mark; Goodsaid, Federico

    2013-01-01

    Introduction There are significant rates of attrition in drug development. A number of compounds fail to progress past preclinical development due to limited tools that accurately monitor toxicity in preclinical studies and in the clinic. Research has focused on improving tools for the detection of organ-specific toxicity through the identification and characterization of biomarkers of toxicity. Areas covered This article reviews what we know about emerging biomarkers in toxicology, with a focus on the 2012 Northeast Society of Toxicology meeting titled ‘Translational Biomarkers in Toxicology.’ The areas covered in this meeting are summarized and include biomarkers of testicular injury and dysfunction, emerging biomarkers of kidney injury and translation of emerging biomarkers from preclinical species to human populations. The authors also provide a discussion about the biomarker qualification process and possible improvements to this process. Expert opinion There is currently a gap between the scientific work in the development and qualification of novel biomarkers for nonclinical drug safety assessment and how these biomarkers are actually used in drug safety assessment. A clear and efficient path to regulatory acceptance is needed so that breakthroughs in the biomarker toolkit for nonclinical drug safety assessment can be utilized to aid in the drug development process. PMID:23961847

  5. Biomarkers in Airway Diseases

    Directory of Open Access Journals (Sweden)

    Janice M Leung

    2013-01-01

    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.

  6. amphibian_biomarker_data

    Data.gov (United States)

    U.S. Environmental Protection Agency — Amphibian metabolite data used in Snyder, M.N., Henderson, W.M., Glinski, D.G., Purucker, S. T., 2017. Biomarker analysis of american toad (Anaxyrus americanus) and...

  7. Validation of New Cancer Biomarkers

    DEFF Research Database (Denmark)

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

    2015-01-01

    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...

  8. Developing novel blood-based biomarkers for Alzheimer's disease

    DEFF Research Database (Denmark)

    Snyder, Heather M; Carrillo, Maria C; Grodstein, Francine

    2014-01-01

    Alzheimer's disease is the public health crisis of the 21st century. There is a clear need for a widely available, inexpensive and reliable method to diagnosis Alzheimer's disease in the earliest stages, track disease progression, and accelerate clinical development of new therapeutics. One avenue...... of research being explored is blood based biomarkers. In April 2012, the Alzheimer's Association and the Alzheimer's Drug Discovery Foundation convened top scientists from around the world to discuss the state of blood based biomarker development. This manuscript summarizes the meeting and the resultant...

  9. Service Discovery At Home

    NARCIS (Netherlands)

    Sundramoorthy, V.; Scholten, Johan; Jansen, P.G.; Hartel, Pieter H.

    Service discovery is a fady 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 deviies. This paper provides an ovewiew and comparison of several prominent

  10. Academic Drug Discovery Centres

    DEFF Research Database (Denmark)

    Kirkegaard, Henriette Schultz; Valentin, Finn

    2014-01-01

    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...

  11. Decades of Discovery

    Science.gov (United States)

    2011-06-01

    For the past two-and-a-half decades, the Office of Science at the U.S. Department of Energy has been at the forefront of scientific discovery. Over 100 important discoveries supported by the Office of Science are represented in this document.

  12. Service discovery at home

    NARCIS (Netherlands)

    Sundramoorthy, V.; Scholten, Johan; Jansen, P.G.; Hartel, Pieter H.

    2003-01-01

    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

  13. Biomarkers in cancer screening: a public health perspective.

    Science.gov (United States)

    Srivastava, Sudhir; Gopal-Srivastava, Rashmi

    2002-08-01

    definitive technology, such as CT scan. The National Cancer Institute's Early Detection Research Network (EDRN) has begun an innovative, investigator-initiated project to improve methods for detecting the biomarkers of cancer cells. The EDRN is a consortium of more than 32 institutions to link discovery of biomarkers to the next steps in the process of developing early detection tests. These discoveries will lead to early clinical validation of tests with improved accuracy and reliability.

  14. "Eureka, Eureka!" Discoveries in Science

    Science.gov (United States)

    Agarwal, Pankaj

    2011-01-01

    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…

  15. Roentgen and the discovery of X rays

    International Nuclear Information System (INIS)

    Gueret, Ph.

    1998-01-01

    In 1901, the first Nobel price of physics was attributed to Roentgen for his discovery of X rays. This paper recalls through the career of this physicist and research worker, the different steps that led him to this discovery. This paper tries also to solve the 'Roentgen mystery', i.e. the reasons that led him to stop his research work just after this exploit. (J.S.)

  16. Improving the quality of biomarker candidates in untargeted metabolomics via peak table-based alignment of comprehensive two-dimensional gas chromatography-mass spectrometry data

    Science.gov (United States)

    Bean, Heather D.; Hill, Jane E.; Dimandja, Jean-Marie D.

    2015-01-01

    The potential of high-resolution analytical technologies like GC×GC/TOF MS in untargeted metabolomics and biomarker discovery has been limited by the development of fully automated software that can efficiently align and extract information from multiple chromatographic data sets. In this work we report the first investigation on a peak-by-peak basis of the chromatographic factors that impact GC×GC data alignment. A representative set of 16 compounds of different chromatographic characteristics were followed through the alignment of 63 GC×GC chromatograms. We found that varying the mass spectral match parameter had a significant influence on the alignment for poorly- resolved peaks, especially those at the extremes of the detector linear range, and no influence on well- chromatographed peaks. Therefore, optimized chromatography is required for proper GC×GC data alignment. Based on these observations, a workflow is presented for the conservative selection of biomarker candidates from untargeted metabolomics analyses. PMID:25857541

  17. [Artificial Intelligence in Drug Discovery].

    Science.gov (United States)

    Fujiwara, Takeshi; Kamada, Mayumi; Okuno, Yasushi

    2018-04-01

    According to the increase of data generated from analytical instruments, application of artificial intelligence(AI)technology in medical field is indispensable. In particular, practical application of AI technology is strongly required in "genomic medicine" and "genomic drug discovery" that conduct medical practice and novel drug development based on individual genomic information. In our laboratory, we have been developing a database to integrate genome data and clinical information obtained by clinical genome analysis and a computational support system for clinical interpretation of variants using AI. In addition, with the aim of creating new therapeutic targets in genomic drug discovery, we have been also working on the development of a binding affinity prediction system for mutated proteins and drugs by molecular dynamics simulation using supercomputer "Kei". We also have tackled for problems in a drug virtual screening. Our developed AI technology has successfully generated virtual compound library, and deep learning method has enabled us to predict interaction between compound and target protein.

  18. What is a biomarker? Research investments and lack of clinical integration necessitate a review of biomarker terminology and validation schema.

    Science.gov (United States)

    Ptolemy, Adam S; Rifai, Nader

    2010-01-01

    A continual trend of annual growth can be seen within research devoted to the discovery and validation of disease biomarkers within both the natural and clinical sciences. This expansion of intellectual endeavours was quantified through database searches of (a) research grant awards provided by the various branches of the National Institutes of Health (NIH) and (b) academic publications. A search of awards presented between 1986 and 2009 revealed a total of 28,856 grants awarded by the NIH containing the term "biomarker". The total funds for these awards in 2008 and 2009 alone were over $2.5 billion. During the same respective time frames, searches of "biomarker" and either "discovery", "genomics", "proteomics" or "metabolomics" yielded a total of 4,928 NIH grants whose combined funding exceeded $1.2 billion. The derived trend in NIH awards paralleled the annual expansion in "biomarker" literature. A PubMed search for the term, between 1990 and 2009, revealed a total of 441,510 published articles, with 38,457 published in 2008. These enormous investments and academic outputs however have not translated into the expected integration of new biomarkers for patient care. For example no proteomics derived biomarkers are currently being utilized in routine clinical management. This translational chasm necessitates a review of the previously proposed biomarker definitions and evaluation schema. A subsequent discussion of both the analytical and pre-analytical considerations for such research is also presented within. This required knowledge should aid scientists in their pursuit and validation of new biological markers of disease.

  19. Discovery Mondays: Surveyors' Tools

    CERN Multimedia

    2003-01-01

    Surveyors of all ages, have your rulers and compasses at the ready! This sixth edition of Discovery Monday is your chance to learn about the surveyor's tools - the state of the art in measuring instruments - and see for yourself how they work. With their usual daunting precision, the members of CERN's Surveying Group have prepared some demonstrations and exercises for you to try. Find out the techniques for ensuring accelerator alignment and learn about high-tech metrology systems such as deviation indicators, tracking lasers and total stations. The surveyors will show you how they precisely measure magnet positioning, with accuracy of a few thousandths of a millimetre. You can try your hand at precision measurement using different types of sensor and a modern-day version of the Romans' bubble level, accurate to within a thousandth of a millimetre. You will learn that photogrammetry techniques can transform even a simple digital camera into a remarkable measuring instrument. Finally, you will have a chance t...

  20. Biomarkers of a five-domain translational substrate for schizophrenia and schizoaffective psychosis.

    Science.gov (United States)

    Fryar-Williams, Stephanie; Strobel, Jörg E

    2015-01-01

    The Mental Health Biomarker Project (2010-2014) selected commercial biochemistry markers related to monoamine synthesis and metabolism and measures of visual and auditory processing performance. Within a case-control discovery design with exclusion criteria designed to produce a highly characterised sample, results from 67 independently DSM IV-R-diagnosed cases of schizophrenia and schizoaffective disorder were compared with those from 67 control participants selected from a local hospital, clinic and community catchment area. Participants underwent protocol-based diagnostic-checking, functional-rating, biological sample-collection for thirty candidate markers and sensory-processing assessment. Fifteen biomarkers were identified on ROC analysis. Using these biomarkers, odds ratios, adjusted for a case-control design, indicated that schizophrenia and schizoaffective disorder were highly associated with dichotic listening disorder, delayed visual processing, low visual span, delayed auditory speed of processing, low reverse digit span as a measure of auditory working memory and elevated levels of catecholamines. Other nutritional and biochemical biomarkers were identified as elevated hydroxyl pyrroline-2-one as a marker of oxidative stress, vitamin D, B6 and folate deficits with elevation of serum B12 and free serum copper to zinc ratio. When individual biomarkers were ranked by odds ratio and correlated with clinical severity, five functional domains of visual processing, auditory processing, oxidative stress, catecholamines and nutritional-biochemical variables were formed. When the strengths of their inter-domain relationships were predicted by Lowess (non-parametric) regression, predominant bidirectional relationships were found between visual processing and catecholamine domains. At a cellular level, the nutritional-biochemical domain exerted a pervasive influence on the auditory domain as well as on all other domains. The findings of this biomarker research

  1. Tissue- and Serum-Associated Biomarkers of Hepatocellular Carcinoma

    Science.gov (United States)

    Chauhan, Ranjit; Lahiri, Nivedita

    2016-01-01

    Hepatocellular carcinoma (HCC), one of the leading causes of cancer deaths in the world, is offering a challenge to human beings, with the current modes of treatment being a palliative approach. Lack of proper curative or preventive treatment methods encouraged extensive research around the world with an aim to detect a vaccine or therapeutic target biomolecule that could lead to development of a drug or vaccine against HCC. Biomarkers or biological disease markers have emerged as a potential tool as drug/vaccine targets, as they can accurately diagnose, predict, and even prevent the diseases. Biomarker expression in tissue, serum, plasma, or urine can detect tumor in very early stages of its development and monitor the cancer progression and also the effect of therapeutic interventions. Biomarker discoveries are driven by advanced techniques, such as proteomics, transcriptomics, whole genome sequencing, micro- and micro-RNA arrays, and translational clinics. In this review, an overview of the potential of tissue- and serum-associated HCC biomarkers as diagnostic, prognostic, and therapeutic targets for drug development is presented. In addition, we highlight recently developed micro-RNA, long noncoding RNA biomarkers, and single-nucleotide changes, which may be used independently or as complementary biomarkers. These active investigations going on around the world aimed at conquering HCC might show a bright light in the near future. PMID:27398029

  2. Tissue- and Serum-Associated Biomarkers of Hepatocellular Carcinoma

    Directory of Open Access Journals (Sweden)

    Ranjit Chauhan

    2016-01-01

    Full Text Available Hepatocellular carcinoma (HCC, one of the leading causes of cancer deaths in the world, is offering a challenge to human beings, with the current modes of treatment being a palliative approach. Lack of proper curative or preventive treatment methods encouraged extensive research around the world with an aim to detect a vaccine or therapeutic target biomolecule that could lead to development of a drug or vaccine against HCC. Biomarkers or biological disease markers have emerged as a potential tool as drug/vaccine targets, as they can accurately diagnose, predict, and even prevent the diseases. Biomarker expression in tissue, serum, plasma, or urine can detect tumor in very early stages of its development and monitor the cancer progression and also the effect of therapeutic interventions. Biomarker discoveries are driven by advanced techniques, such as proteomics, transcriptomics, whole genome sequencing, micro- and micro-RNA arrays, and translational clinics. In this review, an overview of the potential of tissue- and serum-associated HCC biomarkers as diagnostic, prognostic, and therapeutic targets for drug development is presented. In addition, we highlight recently developed micro-RNA, long noncoding RNA biomarkers, and single-nucleotide changes, which may be used independently or as complementary biomarkers. These active investigations going on around the world aimed at conquering HCC might show a bright light in the near future.

  3. Biomarkers of sepsis

    Science.gov (United States)

    2013-01-01

    Sepsis is an unusual systemic reaction to what is sometimes an otherwise ordinary infection, and it probably represents a pattern of response by the immune system to injury. A hyper-inflammatory response is followed by an immunosuppressive phase during which multiple organ dysfunction is present and the patient is susceptible to nosocomial infection. Biomarkers to diagnose sepsis may allow early intervention which, although primarily supportive, can reduce the risk of death. Although lactate is currently the most commonly used biomarker to identify sepsis, other biomarkers may help to enhance lactate’s effectiveness; these include markers of the hyper-inflammatory phase of sepsis, such as pro-inflammatory cytokines and chemokines; proteins such as C-reactive protein and procalcitonin which are synthesized in response to infection and inflammation; and markers of neutrophil and monocyte activation. Recently, markers of the immunosuppressive phase of sepsis, such as anti-inflammatory cytokines, and alterations of the cell surface markers of monocytes and lymphocytes have been examined. Combinations of pro- and anti-inflammatory biomarkers in a multi-marker panel may help identify patients who are developing severe sepsis before organ dysfunction has advanced too far. Combined with innovative approaches to treatment that target the immunosuppressive phase, these biomarkers may help to reduce the mortality rate associated with severe sepsis which, despite advances in supportive measures, remains high. PMID:23480440

  4. The Greatest Mathematical Discovery?

    Energy Technology Data Exchange (ETDEWEB)

    Bailey, David H.; Borwein, Jonathan M.

    2010-05-12

    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.

  5. Biomarkers of the Dementia

    Directory of Open Access Journals (Sweden)

    Mikio Shoji

    2011-01-01

    Full Text Available Recent advances in biomarker studies on dementia are summarized here. CSF Aβ40, Aβ42, total tau, and phosphorylated tau are the most sensitive biomarkers for diagnosis of Alzheimer's disease (AD and prediction of onset of AD from mild cognitive impairment (MCI. Based on this progress, new diagnostic criteria for AD, MCI, and preclinical AD were proposed by National Institute of Aging (NIA and Alzheimer's Association in August 2010. In these new criteria, progress in biomarker identification and amyloid imaging studies in the past 10 years have added critical information. Huge contributions of basic and clinical studies have established clinical evidence supporting these markers. Based on this progress, essential therapy for cure of AD is urgently expected.

  6. Inflammatory biomarkers and cancer

    DEFF Research Database (Denmark)

    Rasmussen, Line Jee Hartmann; Schultz, Martin; Gaardsting, Anne

    2017-01-01

    and previous cancer diagnoses compared to patients who were not diagnosed with cancer. Previous cancer, C-reactive protein (CRP) and suPAR were significantly associated with newly diagnosed cancer during follow-up in multiple logistic regression analyses adjusted for age, sex and CRP. Neither any of the PRRs......In Denmark, patients with serious nonspecific symptoms and signs of cancer (NSSC) are referred to the diagnostic outpatient clinics (DOCs) where an accelerated cancer diagnostic program is initiated. Various immunological and inflammatory biomarkers have been associated with cancer, including...... soluble urokinase plasminogen activator receptor (suPAR) and the pattern recognition receptors (PRRs) pentraxin-3, mannose-binding lectin, ficolin-1, ficolin-2 and ficolin-3. We aimed to evaluate these biomarkers and compare their diagnostic ability to classical biomarkers for diagnosing cancer...

  7. Multidimensional process discovery

    NARCIS (Netherlands)

    Ribeiro, J.T.S.

    2013-01-01

    Typically represented in event logs, business process data describe the execution of process events over time. Business process intelligence (BPI) techniques such as process mining can be applied to get strategic insight into business processes. Process discovery, conformance checking and

  8. Fateful discovery almost forgotten

    CERN Multimedia

    1989-01-01

    "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. Biomarkers in pancreatic adenocarcinoma: current perspectives.

    Science.gov (United States)

    Swords, Douglas S; Firpo, Matthew A; Scaife, Courtney L; Mulvihill, Sean J

    2016-01-01

    Pancreatic ductal adenocarcinoma (PDAC) has a poor prognosis, with a 5-year survival rate of 7.7%. Most patients are diagnosed at an advanced stage not amenable to potentially curative resection. A substantial portion of this review is dedicated to reviewing the current literature on carbohydrate antigen (CA 19-9), which is currently the only guideline-recommended biomarker for PDAC. It provides valuable prognostic information, can predict resectability, and is useful in decision making about neoadjuvant therapy. We also discuss carcinoembryonic antigen (CEA), CA 125, serum biomarker panels, circulating tumor cells, and cell-free nucleic acids. Although many biomarkers have now been studied in relation to PDAC, significant work still needs to be done to validate their usefulness in the early detection of PDAC and management of patients with PDAC.

  10. Discovering biomarkers for antidepressant response: protocol from the Canadian biomarker integration network in depression (CAN-BIND) and clinical characteristics of the first patient cohort.

    Science.gov (United States)

    Lam, Raymond W; Milev, Roumen; Rotzinger, Susan; Andreazza, Ana C; Blier, Pierre; Brenner, Colleen; Daskalakis, Zafiris J; Dharsee, Moyez; Downar, Jonathan; Evans, Kenneth R; Farzan, Faranak; Foster, Jane A; Frey, Benicio N; Geraci, Joseph; Giacobbe, Peter; Feilotter, Harriet E; Hall, Geoffrey B; Harkness, Kate L; Hassel, Stefanie; Ismail, Zahinoor; Leri, Francesco; Liotti, Mario; MacQueen, Glenda M; McAndrews, Mary Pat; Minuzzi, Luciano; Müller, Daniel J; Parikh, Sagar V; Placenza, Franca M; Quilty, Lena C; Ravindran, Arun V; Salomons, Tim V; Soares, Claudio N; Strother, Stephen C; Turecki, Gustavo; Vaccarino, Anthony L; Vila-Rodriguez, Fidel; Kennedy, Sidney H

    2016-04-16

    Major Depressive Disorder (MDD) is among the most prevalent and disabling medical conditions worldwide. Identification of clinical and biological markers ("biomarkers") of treatment response could personalize clinical decisions and lead to better outcomes. This paper describes the aims, design, and methods of a discovery study of biomarkers in antidepressant treatment response, conducted by the Canadian Biomarker Integration Network in Depression (CAN-BIND). The CAN-BIND research program investigates and identifies biomarkers that help to predict outcomes in patients with MDD treated with antidepressant medication. The primary objective of this initial study (known as CAN-BIND-1) is to identify individual and integrated neuroimaging, electrophysiological, molecular, and clinical predictors of response to sequential antidepressant monotherapy and adjunctive therapy in MDD. CAN-BIND-1 is a multisite initiative involving 6 academic health centres working collaboratively with other universities and research centres. In the 16-week protocol, patients with MDD are treated with a first-line antidepressant (escitalopram 10-20 mg/d) that, if clinically warranted after eight weeks, is augmented with an evidence-based, add-on medication (aripiprazole 2-10 mg/d). Comprehensive datasets are obtained using clinical rating scales; behavioural, dimensional, and functioning/quality of life measures; neurocognitive testing; genomic, genetic, and proteomic profiling from blood samples; combined structural and functional magnetic resonance imaging; and electroencephalography. De-identified data from all sites are aggregated within a secure neuroinformatics platform for data integration, management, storage, and analyses. Statistical analyses will include multivariate and machine-learning techniques to identify predictors, moderators, and mediators of treatment response. From June 2013 to February 2015, a cohort of 134 participants (85 outpatients with MDD and 49 healthy participants

  11. Discovery Driven Growth

    DEFF Research Database (Denmark)

    Bukh, Per Nikolaj

    2009-01-01

    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. The π discovery

    International Nuclear Information System (INIS)

    Fowler, P.H.

    1988-01-01

    The paper traces the discovery of the Π meson. The discovery was made by exposure of nuclear emulsions to cosmic radiation at high altitudes, with subsequent scanning of the emulsions for meson tracks. Disintegration of nuclei by a negative meson, and the decay of a Π meson were both observed. Further measurements revealed the mass of the meson. The studies carried out on the origin of the Π-mesons, and their mode of decay, are both described. (U.K.)

  13. Key drivers of biomedical innovation in cancer drug discovery

    OpenAIRE

    Huber, Margit A; Kraut, Norbert

    2014-01-01

    Discovery and translational research has led to the identification of a series of ?cancer drivers??genes that, when mutated or otherwise misregulated, can drive malignancy. An increasing number of drugs that directly target such drivers have demonstrated activity in clinical trials and are shaping a new landscape for molecularly targeted cancer therapies. Such therapies rely on molecular and genetic diagnostic tests to detect the presence of a biomarker that predicts response. Here, we highli...

  14. A New Universe of Discoveries

    Science.gov (United States)

    Córdova, France A.

    2016-01-01

    The convergence of emerging advances in astronomical instruments, computational capabilities and talented practitioners (both professional and civilian) is creating an extraordinary new environment for making numerous fundamental discoveries in astronomy, ranging from the nature of exoplanets to understanding the evolution of solar systems and galaxies. The National Science Foundation is playing a critical role in supporting, stimulating, and shaping these advances. NSF is more than an agency of government or a funding mechanism for the infrastructure of science. The work of NSF is a sacred trust that every generation of Americans makes to those of the next generation, that we will build on the body of knowledge we inherit and continue to push forward the frontiers of science. We never lose sight of NSF's obligation to "explore the unexplored" and inspire all of humanity with the wonders of discovery. As the only Federal agency dedicated to the support of basic research and education in all fields of science and engineering, NSF has empowered discoveries across a broad spectrum of scientific inquiry for more than six decades. The result is fundamental scientific research that has had a profound impact on our nation's innovation ecosystem and kept our nation at the very forefront of the world's science-and-engineering enterprise.

  15. Tumor antigens as proteogenomic biomarkers in invasive ductal carcinomas

    DEFF Research Database (Denmark)

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

    2014-01-01

    directly linked to the hallmarks of cancer. The results found by proteogenomic analysis of the 32 tumor antigens studied here, capture largely the same pathway irregularities as those elucidated from large-scale screening of genomics analyses, where several thousands of genes are often found......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...

  16. Update on Biomarkers for the Detection of Endometriosis

    Science.gov (United States)

    Fassbender, Amelie; Burney, Richard O.; O, Dorien F.; D'Hooghe, Thomas; Giudice, Linda

    2015-01-01

    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. PMID:26240814

  17. Update on Biomarkers for the Detection of Endometriosis

    Directory of Open Access Journals (Sweden)

    Amelie Fassbender

    2015-01-01

    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.

  18. Distinguishing prognostic and predictive biomarkers: An information theoretic approach.

    Science.gov (United States)

    Sechidis, Konstantinos; Papangelou, Konstantinos; Metcalfe, Paul D; Svensson, David; Weatherall, James; Brown, Gavin

    2018-05-02

    The identification of biomarkers to support decision-making is central to personalised medicine, in both clinical and research scenarios. The challenge can be seen in two halves: identifying predictive markers, which guide the development/use of tailored therapies; and identifying prognostic markers, which guide other aspects of care and clinical trial planning, i.e. prognostic markers can be considered as covariates for stratification. Mistakenly assuming a biomarker to be predictive, when it is in fact largely prognostic (and vice-versa) is highly undesirable, and can result in financial, ethical and personal consequences. We present a framework for data-driven ranking of biomarkers on their prognostic/predictive strength, using a novel information theoretic method. This approach provides a natural algebra to discuss and quantify the individual predictive and prognostic strength, in a self-consistent mathematical framework. Our contribution is a novel procedure, INFO+, which naturally distinguishes the prognostic vs predictive role of each biomarker and handles higher order interactions. In a comprehensive empirical evaluation INFO+ outperforms more complex methods, most notably when noise factors dominate, and biomarkers are likely to be falsely identified as predictive, when in fact they are just strongly prognostic. Furthermore, we show that our methods can be 1-3 orders of magnitude faster than competitors, making it useful for biomarker discovery in 'big data' scenarios. Finally, we apply our methods to identify predictive biomarkers on two real clinical trials, and introduce a new graphical representation that provides greater insight into the prognostic and predictive strength of each biomarker. R implementations of the suggested methods are available at https://github.com/sechidis. konstantinos.sechidis@manchester.ac.uk. Supplementary data are available at Bioinformatics online.

  19. Biomarkers of Nutrition for Development—Iodine Review1234

    Science.gov (United States)

    Rohner, Fabian; Zimmermann, Michael; Jooste, Pieter; Pandav, Chandrakant; Caldwell, Kathleen; Raghavan, Ramkripa; Raiten, Daniel J.

    2014-01-01

    The objective of the Biomarkers of Nutrition for Development (BOND) project is to provide state-of-the-art information and service with regard to selection, use, and interpretation of biomarkers of nutrient exposure, status, function, and effect. Specifically, the BOND project seeks to develop consensus on accurate assessment methodologies that are applicable to researchers (laboratory/clinical/surveillance), clinicians, programmers, and policy makers (data consumers). The BOND project is also intended to develop targeted research agendas to support the discovery and development of biomarkers through improved understanding of nutrient biology within relevant biologic systems. In phase I of the BOND project, 6 nutrients (iodine, vitamin A, iron, zinc, folate, and vitamin B-12) were selected for their high public health importance because they typify the challenges faced by users in the selection, use, and interpretation of biomarkers. For each nutrient, an expert panel was constituted and charged with the development of a comprehensive review covering the respective nutrient’s biology, existing biomarkers, and specific issues of use with particular reference to the needs of the individual user groups. In addition to the publication of these reviews, materials from each will be extracted to support the BOND interactive Web site (http://www.nichd.nih.gov/global_nutrition/programs/bond/pages/index.aspx). This review represents the first in the series of reviews and covers all relevant aspects of iodine biology and biomarkers. The article is organized to provide the reader with a full appreciation of iodine’s background history as a public health issue, its biology, and an overview of available biomarkers and specific considerations for the use and interpretation of iodine biomarkers across a range of clinical and population-based uses. The review also includes a detailed research agenda to address priority gaps in our understanding of iodine biology and assessment

  20. Big biomedical data as the key resource for discovery science.

    Science.gov (United States)

    Toga, Arthur W; Foster, Ian; Kesselman, Carl; Madduri, Ravi; Chard, Kyle; Deutsch, Eric W; Price, Nathan D; Glusman, Gustavo; Heavner, Benjamin D; Dinov, Ivo D; Ames, Joseph; Van Horn, John; Kramer, Roger; Hood, Leroy

    2015-11-01

    Modern biomedical data collection is generating exponentially more data in a multitude of formats. This flood of complex data poses significant opportunities to discover and understand the critical interplay among such diverse domains as genomics, proteomics, metabolomics, and phenomics, including imaging, biometrics, and clinical data. The Big Data for Discovery Science Center is taking an "-ome to home" approach to discover linkages between these disparate data sources by mining existing databases of proteomic and genomic data, brain images, and clinical assessments. In support of this work, the authors developed new technological capabilities that make it easy for researchers to manage, aggregate, manipulate, integrate, and model large amounts of distributed data. Guided by biological domain expertise, the Center's computational resources and software will reveal relationships and patterns, aiding researchers in identifying biomarkers for the most confounding conditions and diseases, such as Parkinson's and Alzheimer's. © The Author 2015. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

  1. Pathways to new drug discovery in neuropsychiatry

    Directory of Open Access Journals (Sweden)

    Berk Michael

    2012-11-01

    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 http://www.biomedcentral.com/1741-7015/10/150

  2. Identification of biomarkers for lung cancer in never smokers — EDRN Public Portal

    Science.gov (United States)

    The overall goal of this project is to identify, verify and apply biomarkers for the early diagnosis or risk assessment of lung cancer in never smokers. The first year will be regarded as a year of discovery. After successful demonstration of the feasibility of the approach for novel marker discovery, funding will be applied for to perform confirmation and preclinical studies on the biomarkers and validation studies (specific aims 2 and 3, to be performed in years two and three). Year two can be regarded as the year of confirmation and year three as the year of validation.

  3. Application of data mining and artificial intelligence techniques to mass spectrometry data for knowledge discovery

    Directory of Open Access Journals (Sweden)

    Hugo López-Fernández

    2016-05-01

    Full Text Available Mass spectrometry using matrix assisted laser desorption ionization coupled to time of flight analyzers (MALDI-TOF MS has become popular during the last decade due to its high speed, sensitivity and robustness for detecting proteins and peptides. This allows quickly analyzing large sets of samples are in one single batch and doing high-throughput proteomics. In this scenario, bioinformatics methods and computational tools play a key role in MALDI-TOF data analysis, as they are able handle the large amounts of raw data generated in order to extract new knowledge and useful conclusions. A typical MALDI-TOF MS data analysis workflow has three main stages: data acquisition, preprocessing and analysis. Although the most popular use of this technology is to identify proteins through their peptides, analyses that make use of artificial intelligence (AI, machine learning (ML, and statistical methods can be also carried out in order to perform biomarker discovery, automatic diagnosis, and knowledge discovery. In this research work, this workflow is deeply explored and new solutions based on the application of AI, ML, and statistical methods are proposed. In addition, an integrated software platform that supports the full MALDI-TOF MS data analysis workflow that facilitate the work of proteomics researchers without advanced bioinformatics skills has been developed and released to the scientific community.

  4. Biomarkers for anorexia nervosa

    DEFF Research Database (Denmark)

    Sjøgren, Jan Magnus

    2017-01-01

    Biomarkers for anorexia nervosa (AN) which reflect the pathophysiology and relate to the aetiology of the disease, are warranted and could bring us one step closer to targeted treatment of AN. Some leads may be found in the biochemistry which often is found disturbed in AN, although normalization...

  5. Biomarkers of cancer cachexia.

    Science.gov (United States)

    Loumaye, Audrey; Thissen, Jean-Paul

    2017-12-01

    Cachexia is a complex multifactorial syndrome, characterized by loss of skeletal muscle and fat mass, which affects the majority of advanced cancer patients and is associated with poor prognosis. Interestingly, reversing muscle loss in animal models of cancer cachexia leads to prolong survival. Therefore, detecting cachexia and maintaining muscle mass represent a major goal in the care of cancer patients. However, early diagnosis of cancer cachexia is currently limited for several reasons. Indeed, cachexia development is variable according to tumor and host characteristics. In addition, safe, accessible and non-invasive tools to detect skeletal muscle atrophy are desperately lacking in clinical practice. Finally, the precise molecular mechanisms and the key players involved in cancer cachexia remain poorly characterized. The need for an early diagnosis of cancer cachexia supports therefore the quest for a biomarker that might reflect skeletal muscle atrophy process. Current research offers different promising ways to identify such a biomarker. Initially, the quest for a biomarker of cancer cachexia has mostly focused on mediators of muscle atrophy, produced by both tumor and host, in an attempt to define new therapeutic approaches. In another hand, molecules released by the muscle into the circulation during the atrophy process have been also considered as potential biomarkers. More recently, several "omics" studies are emerging to identify new muscular or circulating markers of cancer cachexia. Some genetic markers could also contribute to identify patients more susceptible to develop cachexia. This article reviews our current knowledge regarding potential biomarkers of cancer cachexia. Copyright © 2017 The Canadian Society of Clinical Chemists. Published by Elsevier Inc. All rights reserved.

  6. Biomarkers for personalized oncology: recent advances and future challenges.

    Science.gov (United States)

    Kalia, Madhu

    2015-03-01

    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

  7. In search of biomarkers for autism: scientific, social and ethical challenges.

    Science.gov (United States)

    Walsh, Pat; Elsabbagh, Mayada; Bolton, Patrick; Singh, Ilina

    2011-09-20

    There is widespread hope that the discovery of valid biomarkers for autism will both reveal the causes of autism and enable earlier and more targeted methods for diagnosis and intervention. However, growing enthusiasm about recent advances in this area of autism research needs to be tempered by an awareness of the major scientific challenges and the important social and ethical concerns arising from the development of biomarkers and their clinical application. Collaborative approaches involving scientists and other stakeholders must combine the search for valid, clinically useful autism biomarkers with efforts to ensure that individuals with autism and their families are treated with respect and understanding.

  8. Sputum-Based Molecular Biomarkers for the Early Detection of Lung Cancer: Limitations and Promise

    Energy Technology Data Exchange (ETDEWEB)

    Kim, Connie E. [Department of Medicine, Division of Pulmonary, Critical Care and Sleep Medicine. 462 First Avenue, NBV 7N24, New York, NY 10016 (United States); Tchou-Wong, Kam-Meng; Rom, William N., E-mail: william.rom@nyumc.org [Department of Medicine, Division of Pulmonary, Critical Care and Sleep Medicine. 462 First Avenue, NBV 7N24, New York, NY 10016 (United States); Department of Environmental Medicine, New York University School of Medicine, 57 Old Forge Road, Tuxedo, NY 10987 (United States)

    2011-07-19

    Lung cancer is the leading cause of cancer deaths, with an overall survival of 15% at five years. Biomarkers that can sensitively and specifically detect lung cancer at early stage are crucial for improving this poor survival rate. Sputum has been the target for the discovery of non-invasive biomarkers for lung cancer because it contains airway epithelial cells, and molecular alterations identified in sputum are most likely to reflect tumor-associated changes or field cancerization caused by smoking in the lung. Sputum-based molecular biomarkers include morphology, allelic imbalance, promoter hypermethylation, gene mutations and, recently, differential miRNA expression. To improve the sensitivity and reproducibility of sputum-based biomarkers, we recommend standardization of processing protocols, bronchial epithelial cell enrichment, and identification of field cancerization biomarkers.

  9. Assessed and Emerging Biomarkers in Stroke and Training-Mediated Stroke Recovery: State of the Art

    Directory of Open Access Journals (Sweden)

    Marialuisa Gandolfi

    2017-01-01

    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.

  10. ALS Biomarkers for Therapy Development: State of the Field & Future Directions

    Science.gov (United States)

    Benatar, Michael; Boylan, Kevin; Jeromin, Andreas; Rutkove, Seward B.; Berry, James; Atassi, Nazem; Bruijn, Lucie

    2015-01-01

    Biomarkers have become the focus of intense research in the field of amyotrophic lateral sclerosis (ALS), with the hope that they might aid therapy development efforts. Notwithstanding the discovery of many candidate biomarkers, none have yet emerged as validated tools for drug development. In this review we present a nuanced view of biomarkers based on the perspective of the FDA; highlight the distinction between discovery and validation; describe existing and emerging resources; review leading biological fluid-based, electrophysiological and neuroimaging candidates relevant to therapy development efforts; discuss lessons learned from biomarker initiatives in related neurodegenerative diseases; and outline specific steps that we, as a field, might take in order to hasten the development and validation of biomarkers that will prove useful in enhancing efforts to develop effective treatments for ALS patients. Most important among these perhaps is the proposal to establish a federated ALS Biomarker Consortium (ABC) in which all interested and willing stakeholders may participate with equal opportunity to contribute to the broader mission of biomarker development and validation. PMID:26574709

  11. Biomarkers of Pediatric Brain Tumors

    Directory of Open Access Journals (Sweden)

    Mark D Russell

    2013-03-01

    Full Text Available Background and Need for Novel Biomarkers: Brain tumors are the leading cause of death by solid tumors in children. Although improvements have been made in their radiological detection and treatment, our capacity to promptly diagnose pediatric brain tumors in their early stages remains limited. This contrasts several other cancers where serum biomarkers such as CA 19-9 and CA 125 facilitate early diagnosis and treatment. Aim: The aim of this article is to review the latest literature and highlight biomarkers which may be of clinical use in the common types of primary pediatric brain tumor. Methods: A PubMed search was performed to identify studies reporting biomarkers in the bodily fluids of pediatric patients with brain tumors. Details regarding the sample type (serum, cerebrospinal fluid or urine, biomarkers analyzed, methodology, tumor type and statistical significance were recorded. Results: A total of 12 manuscripts reporting 19 biomarkers in 367 patients vs. 397 controls were identified in the literature. Of the 19 biomarkers identified, 12 were isolated from cerebrospinal fluid, 2 from serum, 3 from urine, and 2 from multiple bodily fluids. All but one study reported statistically significant differences in biomarker expression between patient and control groups.Conclusions: This review identifies a panel of novel biomarkers for pediatric brain tumors. It provides a platform for the further studies necessary to validate these biomarkers and, in addition, highlights several techniques through which new biomarkers can be discovered.

  12. A tuberculosis biomarker database: the key to novel TB diagnostics

    Directory of Open Access Journals (Sweden)

    Seda Yerlikaya

    2017-03-01

    Full Text Available New diagnostic innovations for tuberculosis (TB, including point-of-care solutions, are critical to reach the goals of the End TB Strategy. However, despite decades of research, numerous reports on new biomarker candidates, and significant investment, no well-performing, simple and rapid TB diagnostic test is yet available on the market, and the search for accurate, non-DNA biomarkers remains a priority. To help overcome this ‘biomarker pipeline problem’, FIND and partners are working on the development of a well-curated and user-friendly TB biomarker database. The web-based database will enable the dynamic tracking of evidence surrounding biomarker candidates in relation to target product profiles (TPPs for needed TB diagnostics. It will be able to accommodate raw datasets and facilitate the verification of promising biomarker candidates and the identification of novel biomarker combinations. As such, the database will simplify data and knowledge sharing, empower collaboration, help in the coordination of efforts and allocation of resources, streamline the verification and validation of biomarker candidates, and ultimately lead to an accelerated translation into clinically useful tools.

  13. Discovery of charm

    International Nuclear Information System (INIS)

    Goldhaber, G.

    1984-11-01

    In my talk I will cover the period 1973 to 1976 which saw the discoveries of the J/psi and psi' resonances and most of the Psion spectroscopy, the tau lepton and the D 0 ,D + charmed meson doublet. Occasionally I will refer briefly to more recent results. Since this conference is on the history of the weak-interactions I will deal primarily with the properties of naked charm and in particular the weakly decaying doublet of charmed mesons. Most of the discoveries I will mention were made with the SLAC-LBL Magnetic Detector or MARK I which we operated at SPEAR from 1973 to 1976. 27 references

  14. New developments and concepts related to biomarker application to vaccines

    Science.gov (United States)

    Ahmed, S. Sohail; Black, Steve; Ulmer, Jeffrey

    2012-01-01

    Summary This minireview will provide a perspective on new developments and concepts related to biomarker applications for vaccines. In the context of preventive vaccines, biomarkers have the potential to predict adverse events in select subjects due to differences in genetic make‐up/underlying medical conditions or to predict effectiveness (good versus poor response). When expanding them to therapeutic vaccines, their utility in identification of patients most likely to respond favourably (or avoid potentially negative effects of treatment) becomes self‐explanatory. Despite the progress made so far on dissection of various pathways of biological significance in humans, there is still plenty to unravel about the mysteries related to the quantitative and qualitative aspects of the human host response. This review will provide a focused overview of new concepts and developments in the field of vaccine biomarkers including (i) vaccine‐dependent signatures predicting subject response and safety, (ii) predicting therapeutic vaccine efficacy in chronic diseases, (iii) exploring the genetic make‐up of the host that may modulate subject‐specific adverse events or affect the quality of immune responses, and (iv) the topic of volunteer stratification as a result of biomarker screening (e.g. for therapeutic vaccines but also potentially for preventive vaccines) or as a reflection of an effort to compare select groups (e.g. vaccinated subjects versus patients recovering from infection) to enable the discovery of clinically relevant biomarkers for preventive vaccines. PMID:21895991

  15. Cancer therapy trials employing level-of-evidence-1 disease forecast cancer biomarkers uPA and its inhibitor PAI-1

    DEFF Research Database (Denmark)

    Schmitt, Manfred; Harbeck, Nadia; Brünner, Nils

    2011-01-01

    Clinical research on cancer biomarkers is essential in understanding recent discoveries in cancer biology and heterogeneity of the cancer disease. However, there are only a few examples of clinically useful studies that have identified cancer biomarkers with clinical benefit. Urokinase-type plasm...

  16. Reporting Astronomical Discoveries: Past, Now, and Future

    Science.gov (United States)

    Yamaoka, Hitoshi; Green, Daniel W. E.; Samus, Nikolai N.; West, Richard

    2015-08-01

    Many new astronomical objects have been discovered over the years by amateur astronomers, and this continues to be the case. They have traditionally reported them (as have professional astronomers) to the Central Bureau for Astronomical Telegrams (CBAT), which was established in the 19th century. This procedure has worked very well throughout the 20th century, moving under the umbrella of the newly established IAU in 1920. The discoverers have been honored by the formal announcement of their discoveries in the publications of the CBAT.In recent years, some professional research groups have established other ways of announcing their discoveries of explosive objects such as novae and supernovae; some do not now report their discoveries or spectroscopic confirmations of the transients to the CBAT, including often spectroscopic reports of objects posted to the CBAT "Transient Objects Confirmation Page" -- the highly successful TOCP webpage, which assigns official positional designations to new transients posted there by approved, registered users. This leads to a delay in formal announcements of discoveries by amateur astronomers in many cases, as well as inconsistent designations being put into use by individual groups. Amateur astronomers are feeling frustrated about this situation, and they hope that the IAU will help to settle the situation.We have proposed the new IAU commission NC-52, which will treat these phenomena in a continuation of Commission 6, through the CBAT. We hope to continuously support the reporting of the discoveries by amateur astronomers, as well as professional astronomers, who all deserve and desire proper recognition. Our strategy will maintain the firm trust between the amateur and professional astronomers, which is necessary for true collaboration. The plan is for the CBAT to work with collaborators to assure that discoveries posted on the TOCP are promptly designated and announced by the CBAT, even when confirmations are made elsewhere

  17. Novel biomarkers for sepsis

    DEFF Research Database (Denmark)

    Larsen, Frederik Fruergaard; Petersen, J Asger

    2017-01-01

    BACKGROUND: Sepsis is a prevalent condition among hospitalized patients that carries a high risk of morbidity and mortality. Rapid recognition of sepsis as the cause of deterioration is desirable, so effective treatment can be initiated rapidly. Traditionally, diagnosis was based on presence of two...... or more positive SIRS criteria due to infection. However, recently published sepsis-3 criteria put more emphasis on organ dysfunction caused by infection in the definition of sepsis. Regardless of this, no gold standard for diagnosis exist, and clinicians still rely on a number of traditional and novel...... biomarkers to discriminate between patients with and without infection, as the cause of deterioration. METHOD: Narrative review of current literature. RESULTS: A number of the most promising biomarkers for diagnoses and prognostication of sepsis are presented. CONCLUSION: Procalcitonin, presepsin, CD64, su...

  18. [Biomarkers of Alzheimer disease].

    Science.gov (United States)

    Rachel, Wojciech; Grela, Agatha; Zyss, Tomasz; Zieba, Andrzej; Piekoszewski, Wojciech

    2014-01-01

    Cognitive impairment is one of the most abundant age-related psychiatric disorders. The outcome of cognitive impairment in Alzheimer's disease has both individual (the patients and their families) and socio-economic effects. The prevalence of Alzheimer's disease doubles after the age of 65 years, every 4.5 years. An etiologically heterogenic group of disorders related to aging as well as genetic and environmental interactions probably underlie the impairment in Alzheimer's disease. Those factors cause the degeneration of brain tissue which leads to significant cognitive dysfunction. There are two main hypotheses that are linked to the process of neurodegeneration: (i) amyloid cascade and (ii) the role of secretases and dysfunction of mitochondria. From the therapeutic standpoint it is crucial to get an early diagnosis and start with an adequate treatment. The undeniable progress in the field of biomarker research should lead to a better understanding of the early stages of the disorder. So far, the best recognised and described biomarkers of Alzheimer's disease, which can be detected in both cerebrospinal fluid and blood, are: beta-amyloid, tau-protein and phosphorylated tau-protein (phospho-tau). The article discusses the usefulness of the known biomarkers of Alzheimer's disease in early diagnosis.

  19. Discovery: Pile Patterns

    Science.gov (United States)

    de Mestre, Neville

    2017-01-01

    Earlier "Discovery" articles (de Mestre, 1999, 2003, 2006, 2010, 2011) considered patterns from many mathematical situations. This article presents a group of patterns used in 19th century mathematical textbooks. In the days of earlier warfare, cannon balls were stacked in various arrangements depending on the shape of the pile base…

  20. Discovery and Innovation

    African Journals Online (AJOL)

    Discovery and Innovation is a journal of the African Academy of Sciences (AAS) ... World (TWAS) meant to focus attention on science and technology in Africa and the ... of Non-wood Forest Products: Potential Impacts and Challenges in Africa ...

  1. Discovery of TUG-770

    DEFF Research Database (Denmark)

    Christiansen, Elisabeth; Hansen, Steffen V F; Urban, Christian

    2013-01-01

    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...

  2. The discovery of fission

    International Nuclear Information System (INIS)

    McKay, H.A.C.

    1978-01-01

    In this article by the retired head of the Separation Processes Group of the Chemistry Division, Atomic Energy Research Establishment, Harwell, U.K., the author recalls what he terms 'an exciting drama, the unravelling of the nature of the atomic nucleus' in the years before the Second World War, including the discovery of fission. 12 references. (author)

  3. The Discovery of America

    Science.gov (United States)

    Martin, Paul S.

    1973-01-01

    Discusses a model for explaining the spread of human population explosion on North American continent since its discovery 12,000 years ago. The model may help to map the spread of Homo sapiens throughout the New World by using the extinction chronology of the Pleistocene megafauna. (Author/PS)

  4. The BioFIND study: Characteristics of a clinically typical Parkinson's disease biomarker cohort

    Science.gov (United States)

    Goldman, Jennifer G.; Alcalay, Roy N.; Xie, Tao; Tuite, Paul; Henchcliffe, Claire; Hogarth, Penelope; Amara, Amy W.; Frank, Samuel; Rudolph, Alice; Casaceli, Cynthia; Andrews, Howard; Gwinn, Katrina; Sutherland, Margaret; Kopil, Catherine; Vincent, Lona; Frasier, Mark

    2016-01-01

    ABSTRACT Background Identifying PD‐specific biomarkers in biofluids will greatly aid in diagnosis, monitoring progression, and therapeutic interventions. PD biomarkers have been limited by poor discriminatory power, partly driven by heterogeneity of the disease, variability of collection protocols, and focus on de novo, unmedicated patients. Thus, a platform for biomarker discovery and validation in well‐characterized, clinically typical, moderate to advanced PD cohorts is critically needed. Methods BioFIND (Fox Investigation for New Discovery of Biomarkers in Parkinson's Disease) is a cross‐sectional, multicenter biomarker study that established a repository of clinical data, blood, DNA, RNA, CSF, saliva, and urine samples from 118 moderate to advanced PD and 88 healthy control subjects. Inclusion criteria were designed to maximize diagnostic specificity by selecting participants with clinically typical PD symptoms, and clinical data and biospecimen collection utilized standardized procedures to minimize variability across sites. Results We present the study methodology and data on the cohort's clinical characteristics. Motor scores and biospecimen samples including plasma are available for practically defined off and on states and thus enable testing the effects of PD medications on biomarkers. Other biospecimens are available from off state PD assessments and from controls. Conclusion Our cohort provides a valuable resource for biomarker discovery and validation in PD. Clinical data and biospecimens, available through The Michael J. Fox Foundation for Parkinson's Research and the National Institute of Neurological Disorders and Stroke, can serve as a platform for discovering biomarkers in clinically typical PD and comparisons across PD's broad and heterogeneous spectrum. © 2016 The Authors. Movement Disorders published by Wiley Periodicals, Inc. on behalf of International Parkinson and Movement Disorder Society PMID:27113479

  5. In Vivo Imaging Biomarkers in Mouse Models of Alzheimer's Disease: Are We Lost in Translation or Breaking Through?

    Directory of Open Access Journals (Sweden)

    Benoît Delatour

    2010-01-01

    Full Text Available Identification of biomarkers of Alzheimer's Disease (AD is a critical priority to efficiently diagnose the patients, to stage the progression of neurodegeneration in living subjects, and to assess the effects of disease-modifier treatments. This paper addresses the development and usefulness of preclinical neuroimaging biomarkers of AD. It is today possible to image in vivo the brain of small rodents at high resolution and to detect the occurrence of macroscopic/microscopic lesions in these species, as well as of functional alterations reminiscent of AD pathology. We will outline three different types of imaging biomarkers that can be used in AD mouse models: biomarkers with clear translational potential, biomarkers that can serve as in vivo readouts (in particular in the context of drug discovery exclusively for preclinical research, and finally biomarkers that constitute new tools for fundamental research on AD physiopathogeny.

  6. The medical applications of the discoveries of Marie Sklodowska-Curie

    International Nuclear Information System (INIS)

    Krawczyk, M.

    2011-01-01

    In this work, the author indicates what have been the applications of the discoveries of Marie Curie in the field of medicine and how these discoveries have contributed in particular to the development of oncologic radiotherapy. (O.M.)

  7. Microscopy Opening Up New Cancer Discovery Avenues

    Science.gov (United States)

    Today’s high-powered microscopes are allowing researchers to study the fine details of individual cells and to peer into cells, opening up new avenues of discovery about the inner workings of cells, including the events that can cause healthy cells to tra

  8. (Self-) Discovery Service: Helping Students Help Themselves

    Science.gov (United States)

    Debonis, Rocco; O'Donnell, Edward; Thomes, Cynthia

    2012-01-01

    EBSCO Discovery Service (EDS) has been heavily used by UMUC students since its implementation in fall 2011, but experience has shown that it is not always the most appropriate source for satisfying students' information needs and that they often need assistance in understanding how the tool works and how to use it effectively. UMUC librarians have…

  9. 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

    2015-10-07

    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.

  10. Biomarkers in pancreatic adenocarcinoma: current perspectives

    Directory of Open Access Journals (Sweden)

    Swords DS

    2016-12-01

    Full Text Available Douglas S Swords, Matthew A Firpo, Courtney L Scaife, Sean J Mulvihill Department of Surgery, University of Utah Health Sciences, Salt Lake City, UT, USA Abstract: Pancreatic ductal adenocarcinoma (PDAC has a poor prognosis, with a 5-year survival rate of 7.7%. Most patients are diagnosed at an advanced stage not amenable to potentially curative resection. A substantial portion of this review is dedicated to reviewing the current literature on carbohydrate antigen (CA 19-9, which is currently the only guideline-recommended biomarker for PDAC. It provides valuable prognostic information, can predict resectability, and is useful in decision making about neoadjuvant therapy. We also discuss carcinoembryonic antigen (CEA, CA 125, serum biomarker panels, circulating tumor cells, and cell-free nucleic acids. Although many biomarkers have now been studied in relation to PDAC, significant work still needs to be done to validate their usefulness in the early detection of PDAC and management of patients with PDAC. Keywords: pancreatic cancer, biomarkers, screening, CA 19-9, CEA

  11. Plasma biomarker of dietary phytosterol intake.

    Directory of Open Access Journals (Sweden)

    Xiaobo Lin

    Full Text Available Dietary phytosterols, plant sterols structurally similar to cholesterol, reduce intestinal cholesterol absorption and have many other potentially beneficial biological effects in humans. Due to limited information on phytosterol levels in foods, however, it is difficult to quantify habitual dietary phytosterol intake (DPI. Therefore, we sought to identify a plasma biomarker of DPI.Data were analyzed from two feeding studies with a total of 38 subjects during 94 dietary periods. DPI was carefully controlled at low, intermediate, and high levels. Plasma levels of phytosterols and cholesterol metabolites were assessed at the end of each diet period. Based on simple ordinary least squares regression analysis, the best biomarker for DPI was the ratio of plasma campesterol to the endogenous cholesterol metabolite 5-α-cholestanol (R2 = 0.785, P 0.600; P < 0.01.The ratio of plasma campesterol to the coordinately regulated endogenous cholesterol metabolite 5-α-cholestanol is a biomarker of dietary phytosterol intake. Conversely, plasma phytosterol levels alone are not ideal biomarkers of DPI because they are confounded by large inter-individual variation in absorption and turnover of non-cholesterol sterols. Further work is needed to assess the relation between non-cholesterol sterol metabolism and associated cholesterol transport in the genesis of coronary heart disease.

  12. Delta: the first pion nucleon resonance - its discovery and applications

    International Nuclear Information System (INIS)

    Nagle, D.E.

    1984-07-01

    It is attempted to recapture some of the fun and excitement of the pion-scattering work that led to the discovery of what is now called the delta particle. How significant this discovery was became apparent only gradually. That the delta is alive today and thriving at Los Alamos (as well as other places) is described

  13. Discovery simulations and the assessment of intuitive knowledge

    NARCIS (Netherlands)

    Swaak, Janine; de Jong, Anthonius J.M.

    2001-01-01

    The objective of the present work is to have a closer look at the relations between the features of discovery simulations, the learning processes elicited, the knowledge that results, and the methods used to measure this acquired knowledge. It is argued that discovery simulations are ‘rich’, have a

  14. Trend analysis of time-series data: A novel method for untargeted metabolite discovery

    NARCIS (Netherlands)

    Peters, S.; Janssen, H.-G.; Vivó-Truyols, G.

    2010-01-01

    A new strategy for biomarker discovery is presented that uses time-series metabolomics data. Data sets from samples analysed at different time points after an intervention are searched for compounds that show a meaningful trend following the intervention. Obviously, this requires new data-analytical

  15. Bayesian methods for proteomic biomarker development

    Directory of Open Access Journals (Sweden)

    Belinda Hernández

    2015-12-01

    In this review we provide an introduction to Bayesian inference and demonstrate some of the advantages of using a Bayesian framework. We summarize how Bayesian methods have been used previously in proteomics and other areas of bioinformatics. Finally, we describe some popular and emerging Bayesian models from the statistical literature and provide a worked tutorial including code snippets to show how these methods may be applied for the evaluation of proteomic biomarkers.

  16. Measurement of Soluble Biomarkers by Flow Cytometry

    OpenAIRE

    Antal-Szalm?s, P?ter; Nagy, B?la; Debreceni, Ildik? Beke; Kappelmayer, J?nos

    2013-01-01

    Microparticle based flow cytometric assays for determination of the level of soluble biomarkers are widely used in several research applications and in some diagnostic setups. The major advantages of these multiplex systems are that they can measure a large number of analytes (up to 500) at the same time reducing assay time, costs and sample volume. Most of these assays are based on antigen-antibody interactions and work as traditional immunoassays, but nucleic acid alterations ? by using spe...

  17. Biomarkers in Prostate Cancer Epidemiology

    Directory of Open Access Journals (Sweden)

    Mudit Verma

    2011-09-01

    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.

  18. Biomarker Identification Using Text Mining

    Directory of Open Access Journals (Sweden)

    Hui Li

    2012-01-01

    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.

  19. Atlas of Astronomical Discoveries

    CERN Document Server

    Schilling, Govert

    2011-01-01

    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...

  20. Viral pathogen discovery

    Science.gov (United States)

    Chiu, Charles Y

    2015-01-01

    Viral pathogen discovery is of critical importance to clinical microbiology, infectious diseases, and public health. Genomic approaches for pathogen discovery, including consensus polymerase chain reaction (PCR), microarrays, and unbiased next-generation sequencing (NGS), have the capacity to comprehensively identify novel microbes present in clinical samples. Although numerous challenges remain to be addressed, including the bioinformatics analysis and interpretation of large datasets, these technologies have been successful in rapidly identifying emerging outbreak threats, screening vaccines and other biological products for microbial contamination, and discovering novel viruses associated with both acute and chronic illnesses. Downstream studies such as genome assembly, epidemiologic screening, and a culture system or animal model of infection are necessary to establish an association of a candidate pathogen with disease. PMID:23725672

  1. Accounting for control mislabeling in case-control biomarker studies.

    Science.gov (United States)

    Rantalainen, Mattias; Holmes, Chris C

    2011-12-02

    In biomarker discovery studies, uncertainty associated with case and control labels is often overlooked. By omitting to take into account label uncertainty, model parameters and the predictive risk can become biased, sometimes severely. The most common situation is when the control set contains an unknown number of undiagnosed, or future, cases. This has a marked impact in situations where the model needs to be well-calibrated, e.g., when the prediction performance of a biomarker panel is evaluated. Failing to account for class label uncertainty may lead to underestimation of classification performance and bias in parameter estimates. This can further impact on meta-analysis for combining evidence from multiple studies. Using a simulation study, we outline how conventional statistical models can be modified to address class label uncertainty leading to well-calibrated prediction performance estimates and reduced bias in meta-analysis. We focus on the problem of mislabeled control subjects in case-control studies, i.e., when some of the control subjects are undiagnosed cases, although the procedures we report are generic. The uncertainty in control status is a particular situation common in biomarker discovery studies in the context of genomic and molecular epidemiology, where control subjects are commonly sampled from the general population with an established expected disease incidence rate.

  2. Chiral Biomarkers in Meteorites

    Science.gov (United States)

    Hoover, Richard B.

    2010-01-01

    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

  3. Discovery as a process

    Energy Technology Data Exchange (ETDEWEB)

    Loehle, C.

    1994-05-01

    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.

  4. 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...... with very specific competencies. In order to optimize the basis of a sound and fruitful data analysis, suggestions are givenwhich focus on (1) collection of good data, (2) preparation of data for the data analysis and (3) a sound data analysis. If these steps are optimized, PLS is a also a very goodmethod...

  5. Systems-based biological concordance and predictive reproducibility of gene set discovery methods in cardiovascular disease.

    Science.gov (United States)

    Azuaje, Francisco; Zheng, Huiru; Camargo, Anyela; Wang, Haiying

    2011-08-01

    The discovery of novel disease biomarkers is a crucial challenge for translational bioinformatics. Demonstration of both their classification power and reproducibility across independent datasets are essential requirements to assess their potential clinical relevance. Small datasets and multiplicity of putative biomarker sets may explain lack of predictive reproducibility. Studies based on pathway-driven discovery approaches have suggested that, despite such discrepancies, the resulting putative biomarkers tend to be implicated in common biological processes. Investigations of this problem have been mainly focused on datasets derived from cancer research. We investigated the predictive and functional concordance of five methods for discovering putative biomarkers in four independently-generated datasets from the cardiovascular disease domain. A diversity of biosignatures was identified by the different methods. However, we found strong biological process concordance between them, especially in the case of methods based on gene set analysis. With a few exceptions, we observed lack of classification reproducibility using independent datasets. Partial overlaps between our putative sets of biomarkers and the primary studies exist. Despite the observed limitations, pathway-driven or gene set analysis can predict potentially novel biomarkers and can jointly point to biomedically-relevant underlying molecular mechanisms. Copyright © 2011 Elsevier Inc. All rights reserved.

  6. Opportunities and Challenges of Proteomics in Pediatric Patients: Circulating Biomarkers After Hematopoietic Stem Cell Transplantation As a Successful Example

    Science.gov (United States)

    Paczesny, Sophie; Duncan, Christine; Jacobsohn, David; Krance, Robert; Leung, Kathryn; Carpenter, Paul; Bollard, Catherine; Renbarger, Jamie; Cooke, Kenneth

    2015-01-01

    Biomarkers have the potential to improve diagnosis and prognosis, facilitate targeted treatment, and reduce health care costs. Thus, there is great hope that biomarkers will be integrated in all clinical decisions in the near future. A decade ago, the biomarker field was launched with great enthusiasm because mass spectrometry revealed that blood contains a rich library of candidate biomarkers. However, biomarker research has not yet delivered on its promise due to several limitations: (i) improper sample handling and tracking as well as limited sample availability in the pediatric population, (ii) omission of appropriate controls in original study designs, (iii) lability and low abundance of interesting biomarkers in blood, and (iv) the inability to mechanistically tie biomarker presence to disease biology. These limitations as well as successful strategies to overcome them are discussed in this review. Several advances in biomarker discovery and validation have been made in hematopoietic stem cell transplantation, the current most effective tumor immunotherapy, and these could serve as examples for other conditions. This review provides fresh optimism that biomarkers clinically relevant in pediatrics are closer to being realized based on: (i) a uniform protocol for low-volume blood collection and preservation, (ii) inclusion of well-controlled independent cohorts, (iii) novel technologies and instrumentation with low analytical sensitivity, and (iv) integrated animal models for exploring potential biomarkers and targeted therapies. PMID:25196024

  7. Biomarkers: refining diagnosis and expediting drug development - reality, aspiration and the role of open innovation.

    Science.gov (United States)

    Salter, H; Holland, R

    2014-09-01

    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. © 2014 The Association for the Publication of the Journal of Internal Medicine.

  8. Biomarkers in Vasculitis

    Science.gov (United States)

    Monach, Paul A.

    2014-01-01

    Purpose of review Better biomarkers are needed for guiding management of patients with vasculitis. Large cohorts and technological advances had led to an increase in pre-clinical studies of potential biomarkers. Recent findings The most interesting markers described recently include a gene expression signature in CD8+ T cells that predicts tendency to relapse or remain relapse-free in ANCA-associated vasculitis, and a pair of urinary proteins that are elevated in Kawasaki disease but not other febrile illnesses. Both of these studies used “omics” technologies to generate and then test hypotheses. More conventional hypothesis-based studies have indicated that the following circulating proteins have potential to improve upon clinically available tests: pentraxin-3 in giant cell arteritis and Takayasu’s arteritis; von Willebrand factor antigen in childhood central nervous system vasculitis; eotaxin-3 and other markers related to eosinophils or Th2 immune responses in eosinophilic granulomatosis with polyangiitis (Churg-Strauss syndrome); and MMP-3, TIMP-1, and CXCL13 in ANCA-associated vasculitis. Summary New markers testable in blood and urine have the potential to assist with diagnosis, staging, assessment of current disease activity, and prognosis. However, the standards for clinical usefulness, in particular the demonstration of either very high sensitivity or very high specificity, have yet to be met for clinically relevant outcomes. PMID:24257367

  9. Searching for new biomarkers in ovarian cancer patients: Rationale and design of a retrospective study under the Mermaid III project

    Directory of Open Access Journals (Sweden)

    Julie L. Hentze

    2017-12-01

    A thorough investigation of biomarkers in ovarian cancer, including large numbers of different markers, has never been done before. Besides from improving diagnosis and treatment, other outcomes could be markers for screening, knowledge of the molecular aspects of cancer and the discovery of new drugs. Moreover, biomarkers are a prerequisite for the development of precision medicine. This study will attack the ovarian cancer problem from several angles, thereby increasing the chance of successfully contributing to saving lives.

  10. From falling bodies to radiowaves: classical physicists and their discoveries

    International Nuclear Information System (INIS)

    Segre, E.

    1984-01-01

    This chronicle of physics and physicists traces the development of scientific thought from the works of the founding fathers - Galileo, Huggens and Newton - to the more recent discoveries of Maxwell, Boltzmann, and Gibbs

  11. Improved multimodal biomarkers for Alzheimer's disease and mild cognitive impairment diagnosis: data from ADNI

    Science.gov (United States)

    Martinez-Torteya, Antonio; Treviño-Alvarado, Víctor; Tamez-Peña, José

    2013-02-01

    The accurate diagnosis of Alzheimer's disease (AD) and mild cognitive impairment (MCI) confers many clinical research and patient care benefits. Studies have shown that multimodal biomarkers provide better diagnosis accuracy of AD and MCI than unimodal biomarkers, but their construction has been based on traditional statistical approaches. The objective of this work was the creation of accurate AD and MCI diagnostic multimodal biomarkers using advanced bioinformatics tools. The biomarkers were created by exploring multimodal combinations of features using machine learning techniques. Data was obtained from the ADNI database. The baseline information (e.g. MRI analyses, PET analyses and laboratory essays) from AD, MCI and healthy control (HC) subjects with available diagnosis up to June 2012 was mined for case/controls candidates. The data mining yielded 47 HC, 83 MCI and 43 AD subjects for biomarker creation. Each subject was characterized by at least 980 ADNI features. A genetic algorithm feature selection strategy was used to obtain compact and accurate cross-validated nearest centroid biomarkers. The biomarkers achieved training classification accuracies of 0.983, 0.871 and 0.917 for HC vs. AD, HC vs. MCI and MCI vs. AD respectively. The constructed biomarkers were relatively compact: from 5 to 11 features. Those multimodal biomarkers included several widely accepted univariate biomarkers and novel image and biochemical features. Multimodal biomarkers constructed from previously and non-previously AD associated features showed improved diagnostic performance when compared to those based solely on previously AD associated features.

  12. Discovery stories in the science classroom

    Science.gov (United States)

    Arya, Diana Jaleh

    School science has been criticized for its lack of emphasis on the tentative, dynamic nature of science as a process of learning more about our world. This criticism is the guiding force for this present body of work, which focuses on the question: what are the educational benefits for middle school students of reading texts that highlight the process of science in the form of a discovery narrative? This dissertation traces my journey through a review of theoretical perspectives of narrative, an analysis of first-hand accounts of scientific discovery, the complex process of developing age-appropriate, cohesive and engaging science texts for middle school students, and a comparison study (N=209) that seeks to determine the unique benefits of the scientific discovery narrative for the interest in and retained understanding of conceptual information presented in middle school science texts. A total of 209 middle school participants in nine different classrooms from two different schools participated in the experimental study. Each subject read two science texts that differed in topic (the qualities of and uses for radioactive elements and the use of telescopic technology to see planets in space) and genre (the discovery narrative and the "conceptually known exposition" comparison text). The differences between the SDN and CKE versions for each topic were equivalent in all possible ways (initial introduction, overall conceptual accuracy, elements of human interest, coherence and readability level), save for the unique components of the discovery narrative (i.e., love for their work, acknowledgement of the known, identification of the unknown and the explorative or experimental process to discovery). Participants generally chose the discovery narrative version as the more interesting of the two texts. Additional findings from the experimental study suggest that science texts in the form of SDNs elicit greater long-term retention of key conceptual information, especially

  13. Functional, Structural, and Neurotoxicity Biomarkers in Integrative Assessment of Concussions

    Directory of Open Access Journals (Sweden)

    Svetlana A Dambinova

    2016-10-01

    Full Text Available Concussion is a complex, heterogenous process affecting the brain. Accurate assessment and diagnosis and appropriate management of concussion are essential to ensure athletes do not prematurely return to play or others to work or active military duty, risking re-injury. To date, clinical diagnosis relies primarily on evaluating subjects for functional impairment using instruments that include neurocognitive testing, subjective symptom report, and neurobehavioral assessments, such as balance and vestibular-ocular reflex testing. Structural biomarkers, defined as advanced neuroimaging techniques and biomarkers assessing neurotoxicity and immunoexcitotoxicity may complement the use of functional biomarkers. We hypothesize that neurotoxicity AMPA, NMDA, and kainite receptor biomarkers might be utilized as a part of comprehensive approach to concussion evaluations, with the goal of increasing diagnostic accuracy and facilitating treatment planning and prognostic assessment.

  14. Current status of fluid biomarkers in mild traumatic brain injury

    Science.gov (United States)

    Kulbe, Jacqueline R.; Geddes, James W.

    2015-01-01

    Mild traumatic brain injury (mTBI) affects millions of people annually and is difficult to diagnose. Mild injury is insensitive to conventional imaging techniques and diagnoses are often made using subjective criteria such as self-reported symptoms. Many people who sustain a mTBI develop persistent post-concussive symptoms. Athletes and military personnel are at great risk for repeat injury which can result in second impact syndrome or chronic traumatic encephalopathy. An objective and quantifiable measure, such as a serum biomarker, is needed to aid in mTBI diagnosis, prognosis, return to play/duty assessments, and would further elucidate mTBI pathophysiology. The majority of TBI biomarker research focuses on severe TBI with few studies specific to mild injury. Most studies use a hypothesis-driven approach, screening biofluids for markers known to be associated with TBI pathophysiology. This approach has yielded limited success in identifying markers that can be used clinically, additional candidate biomarkers are needed. Innovative and unbiased methods such as proteomics, microRNA arrays, urinary screens, autoantibody identification and phage display would complement more traditional approaches to aid in the discovery of novel mTBI biomarkers. PMID:25981889

  15. Biomarkers in the diagnosis of lysosomal storage disorders: proteins, lipids, and inhibodies.

    Science.gov (United States)

    Aerts, Johannes M F G; Kallemeijn, Wouter W; Wegdam, Wouter; Joao Ferraz, Maria; van Breemen, Marielle J; Dekker, Nick; Kramer, Gertjan; Poorthuis, Ben J; Groener, Johanna E M; Cox-Brinkman, Josanne; Rombach, Saskia M; Hollak, Carla E M; Linthorst, Gabor E; Witte, Martin D; Gold, Henrik; van der Marel, Gijs A; Overkleeft, Herman S; Boot, Rolf G

    2011-06-01

    A biomarker is an analyte indicating the presence of a biological process linked to the clinical manifestations and outcome of a particular disease. In the case of lysosomal storage disorders (LSDs), primary and secondary accumulating metabolites or proteins specifically secreted by storage cells are good candidates for biomarkers. Clinical applications of biomarkers are found in improved diagnosis, monitoring disease progression, and assessing therapeutic correction. These are illustrated by reviewing the discovery and use of biomarkers for Gaucher disease and Fabry disease. In addition, recently developed chemical tools allowing specific visualization of enzymatically active lysosomal glucocerebrosidase are described. Such probes, coined inhibodies, offer entirely new possibilities for more sophisticated molecular diagnosis, enzyme replacement therapy monitoring, and fundamental research.

  16. Metabolomics-based promising candidate biomarkers and pathways in Alzheimer's disease.

    Science.gov (United States)

    Kang, Jian; Lu, Jingli; Zhang, Xiaojian

    2015-05-01

    Pathologically, loss of synapses and neurons, extracellular senile plaques and intracellular neurofibrillary tangles (NFTs) are observed in the brains of patients with Alzheimer's disease (AD). These features are associated with changes Aβ (amyloid β) 40, Aβ42, total tau and phosphorylated tau (p-tau), which are as definitely biomarkers for severe AD state. However, biomarkers for effectively diagnosing AD in the pre-clinical state for directing therapeutic strategies are lacking. Metabolic profiling as a powerful tool to identify new biomarkers is receiving increasing attention in AD. This review will focus on metabolomics-based detection of promising candidate biomarkers and pathways in AD to facilitate the discovery of new medicines and disease pathways.

  17. Integrated Detection of Pathogens and Host Biomarkers for Wounds

    Energy Technology Data Exchange (ETDEWEB)

    Jaing, C

    2012-03-19

    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.

  18. Convergent functional genomics of anxiety disorders: translational identification of genes, biomarkers, pathways and mechanisms.

    Science.gov (United States)

    Le-Niculescu, H; Balaraman, Y; Patel, S D; Ayalew, M; Gupta, J; Kuczenski, R; Shekhar, A; Schork, N; Geyer, M A; Niculescu, A B

    2011-05-24

    Anxiety disorders are prevalent and disabling yet understudied from a genetic standpoint, compared with other major psychiatric disorders such as bipolar disorder and schizophrenia. The fact that they are more common, diverse and perceived as embedded in normal life may explain this relative oversight. In addition, as for other psychiatric disorders, there are technical challenges related to the identification and validation of candidate genes and peripheral biomarkers. Human studies, particularly genetic ones, are susceptible to the issue of being underpowered, because of genetic heterogeneity, the effect of variable environmental exposure on gene expression, and difficulty of accrual of large, well phenotyped cohorts. Animal model gene expression studies, in a genetically homogeneous and experimentally tractable setting, can avoid artifacts and provide sensitivity of detection. Subsequent translational integration of the animal model datasets with human genetic and gene expression datasets can ensure cross-validatory power and specificity for illness. We have used a pharmacogenomic mouse model (involving treatments with an anxiogenic drug--yohimbine, and an anti-anxiety drug--diazepam) as a discovery engine for identification of anxiety candidate genes as well as potential blood biomarkers. Gene expression changes in key brain regions for anxiety (prefrontal cortex, amygdala and hippocampus) and blood were analyzed using a convergent functional genomics (CFG) approach, which integrates our new data with published human and animal model data, as a translational strategy of cross-matching and prioritizing findings. Our work identifies top candidate genes (such as FOS, GABBR1, NR4A2, DRD1, ADORA2A, QKI, RGS2, PTGDS, HSPA1B, DYNLL2, CCKBR and DBP), brain-blood biomarkers (such as FOS, QKI and HSPA1B), pathways (such as cAMP signaling) and mechanisms for anxiety disorders--notably signal transduction and reactivity to environment, with a prominent role for the

  19. 14 CFR 406.143 - Discovery.

    Science.gov (United States)

    2010-01-01

    ... 14 Aeronautics and Space 4 2010-01-01 2010-01-01 false Discovery. 406.143 Section 406.143... Transportation Adjudications § 406.143 Discovery. (a) Initiation of discovery. Any party may initiate discovery... after a complaint has been filed. (b) Methods of discovery. The following methods of discovery are...

  20. [Autoantibodies as biomarkers].

    Science.gov (United States)

    Tron, François

    2014-01-01

    Activation and differentiation of autoreactive B-lymphocytes lead to the production of autoantibodies, which are thus the direct consequence of the autoimmune process. They often constitute biomarkers of autoimmune diseases and are measured by tests displaying various diagnosis sensitivity and specificity. Autoantibody titers can be correlated to the disease activity and certain autoantibody populations associated with particular clinical manifestations or tissue lesions. The demonstration that autoantibodies appear years before the onset of autoimmune diseases indicates that their presence in healthy individuals may be a predictive marker of the occurrence of disease. Certain autoantibodies could also be predictive markers of a therapeutic response to biologics and of the occurrence of side effects as well. Thus, autoantibodies are useful tools in the diagnosis and the management of patients with organ specific or non-organ specific autoimmune diseases at different steps of the autoimmune process. Copyright © 2013. Published by Elsevier Masson SAS.

  1. Biomarkers of adverse drug reactions.

    Science.gov (United States)

    Carr, Daniel F; Pirmohamed, Munir

    2018-02-01

    Adverse drug reactions can be caused by a wide range of therapeutics. Adverse drug reactions affect many bodily organ systems and vary widely in severity. Milder adverse drug reactions often resolve quickly following withdrawal of the casual drug or sometimes after dose reduction. Some adverse drug reactions are severe and lead to significant organ/tissue injury which can be fatal. Adverse drug reactions also represent a financial burden to both healthcare providers and the pharmaceutical industry. Thus, a number of stakeholders would benefit from development of new, robust biomarkers for the prediction, diagnosis, and prognostication of adverse drug reactions. There has been significant recent progress in identifying predictive genomic biomarkers with the potential to be used in clinical settings to reduce the burden of adverse drug reactions. These have included biomarkers that can be used to alter drug dose (for example, Thiopurine methyltransferase (TPMT) and azathioprine dose) and drug choice. The latter have in particular included human leukocyte antigen (HLA) biomarkers which identify susceptibility to immune-mediated injuries to major organs such as skin, liver, and bone marrow from a variety of drugs. This review covers both the current state of the art with regard to genomic adverse drug reaction biomarkers. We also review circulating biomarkers that have the potential to be used for both diagnosis and prognosis, and have the added advantage of providing mechanistic information. In the future, we will not be relying on single biomarkers (genomic/non-genomic), but on multiple biomarker panels, integrated through the application of different omics technologies, which will provide information on predisposition, early diagnosis, prognosis, and mechanisms. Impact statement • Genetic and circulating biomarkers present significant opportunities to personalize patient therapy to minimize the risk of adverse drug reactions. ADRs are a significant heath issue

  2. Causality discovery technology

    Science.gov (United States)

    Chen, M.; Ertl, T.; Jirotka, M.; Trefethen, A.; Schmidt, A.; Coecke, B.; Bañares-Alcántara, R.

    2012-11-01

    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.

  3. Automated Supernova Discovery (Abstract)

    Science.gov (United States)

    Post, R. S.

    2015-12-01

    (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.

  4. A Preliminary ToF-SIMS Assessment of Preservation Potential of Organic Biomarkers in Modern Siliceous Sinter and Core, Yellowstone National Park, Wyoming

    Science.gov (United States)

    Guidry, S. A.; Chafetz, H. S.; Steele, A.; Toporski, J. K. W.

    2000-01-01

    Until recently, most biomarker work has focused on morphological body fossils. As a complement to this, three suites of siliceous precipitates were chosen for ToF-SIMS investigation in order to elucidate potential organic biomarkers.

  5. Image Biomarkers and Precision Medicine: need for validation

    International Nuclear Information System (INIS)

    Marti-Bonmati, L.; Alberich-Bayarri, A.; Garcia Castro, F.

    2016-01-01

    Personalized medicine aims to improve the diagnosis, classification and the best treatment for a particular patient. Today, radiologists are challenged to translate new biological discoveries, the different mechanisms of disease and advances in preclinical research, into a clinical reality through patients, images and their associated parameters. In this article we show how digital medical imaging and computational data processing extract numerous quantitative parameters from the obtained images as virtual biopsies. To be implemented in clinical practice, biomarkers should provide useful and relevant information, improving processes diagnostic, therapeutic and monitoring, for the benefit of patients. (Author)

  6. Searching for new biomarkers in ovarian cancer patients

    DEFF Research Database (Denmark)

    Hentze, Julie L.; Høgdall, Claus; Kjær, Susanne K.

    2017-01-01

    , will be examined. Relevant microRNAs and DNA methylation patterns will be investigated using array technology. Patient exomes will be fully sequenced, and identified genetic variations will be validated with Next Generation Sequencing. In all cases, data will be correlated with clinical information on the patient...... of cancer and the discovery of new drugs. Moreover, biomarkers are a prerequisite for the development of precision medicine. This study will attack the ovarian cancer problem from several angles, thereby increasing the chance of successfully contributing to saving lives....

  7. Multiple Sclerosis Cerebrospinal Fluid Biomarkers

    Directory of Open Access Journals (Sweden)

    Gavin Giovannoni

    2006-01-01

    Full Text Available Cerebrospinal fluid (CSF is the body fluid closest to the pathology of multiple sclerosis (MS. For many candidate biomarkers CSF is the only fluid that can be investigated. Several factors need to be standardized when sampling CSF for biomarker research: time/volume of CSF collection, sample processing/storage, and the temporal relationship of sampling to clinical or MRI markers of disease activity. Assays used for biomarker detection must be validated so as to optimize the power of the studies. A formal method for establishing whether or not a particular biomarker can be used as a surrogate end-point needs to be adopted. This process is similar to that used in clinical trials, where the reporting of studies has to be done in a standardized way with sufficient detail to permit a critical review of the study and to enable others to reproduce the study design. A commitment must be made to report negative studies so as to prevent publication bias. Pre-defined consensus criteria need to be developed for MS-related prognostic biomarkers. Currently no candidate biomarker is suitable as a surrogate end-point. Bulk biomarkers of the neurodegenerative process such as glial fibrillary acidic protein (GFAP and neurofilaments (NF have advantages over intermittent inflammatory markers.

  8. Unraveling the molecular repertoire of tears as a source of biomarkers: beyond ocular diseases.

    Science.gov (United States)

    Pieragostino, Damiana; D'Alessandro, Michele; di Ioia, Maria; Di Ilio, Carmine; Sacchetta, Paolo; Del Boccio, Piero

    2015-02-01

    Proteomics and metabolomics investigations of body fluids present several challenges for biomarker discovery of several diseases. The search for biomarkers is actually conducted in different body fluids, even if the ideal biomarker can be found in an easily accessible biological fluid, because, if validated, the biomarker could be sought in the healthy population. In this regard, tears could be considered an optimum material obtained by noninvasive procedures. In the past years, the scientific community has become more interested in the study of tears for the research of new biomarkers not only for ocular diseases. In this review, we provide a discussion on the current state of biomarkers research in tears and their relevance for clinical practice, and report the main results of clinical proteomics studies on systemic and eye diseases. We summarize the main methods for tear samples analyses and report recent advances in "omics" platforms for tears investigations. Moreover, we want to take stock of the emerging field of metabolomics and lipidomics as a new and integrated approach to study protein-metabolites interplay for biomarkers research, where tears represent a still unexplored and attractive field. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  9. Computational methods in drug discovery

    OpenAIRE

    Sumudu P. Leelananda; Steffen Lindert

    2016-01-01

    The process for drug discovery and development is challenging, time consuming and expensive. Computer-aided drug discovery (CADD) tools can act as a virtual shortcut, assisting in the expedition of this long process and potentially reducing the cost of research and development. Today CADD has become an effective and indispensable tool in therapeutic development. The human genome project has made available a substantial amount of sequence data that can be used in various drug discovery project...

  10. Representation Discovery using Harmonic Analysis

    CERN Document Server

    Mahadevan, Sridhar

    2008-01-01

    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

  11. Plasma biomarker of dietary phytosterol intake.

    Science.gov (United States)

    Lin, Xiaobo; Racette, Susan B; Ma, Lina; Wallendorf, Michael; Spearie, Catherine Anderson; Ostlund, Richard E

    2015-01-01

    Dietary phytosterols, plant sterols structurally similar to cholesterol, reduce intestinal cholesterol absorption and have many other potentially beneficial biological effects in humans. Due to limited information on phytosterol levels in foods, however, it is difficult to quantify habitual dietary phytosterol intake (DPI). Therefore, we sought to identify a plasma biomarker of DPI. Data were analyzed from two feeding studies with a total of 38 subjects during 94 dietary periods. DPI was carefully controlled at low, intermediate, and high levels. Plasma levels of phytosterols and cholesterol metabolites were assessed at the end of each diet period. Based on simple ordinary least squares regression analysis, the best biomarker for DPI was the ratio of plasma campesterol to the endogenous cholesterol metabolite 5-α-cholestanol (R2 = 0.785, P 0.600; P phytosterol intake. Conversely, plasma phytosterol levels alone are not ideal biomarkers of DPI because they are confounded by large inter-individual variation in absorption and turnover of non-cholesterol sterols. Further work is needed to assess the relation between non-cholesterol sterol metabolism and associated cholesterol transport in the genesis of coronary heart disease.

  12. Cardiac Biomarkers and Cycling Race

    Directory of Open Access Journals (Sweden)

    Caroline Le Goff, Jean-François Kaux, Sébastien Goffaux, Etienne Cavalier

    2015-06-01

    results we could think that we have too a notion of high and low responders as with the CK, well described in the work of Hody et al. (2013. Also interesting is the fact that both subjects showing the highest hsTnT levels at T1 had unexceptional NT-proBNP levels, and the two individuals having the highest NT-proBNP levels had unexceptional hsTnT values. These two markers would appear to give independent types of information on the effect of exercise on the heart. Due to the various mechanisms in cause, the impact on NT-pro-BNP and TnT is not the same. It should thus necessary to characterize the response of the left ventricle, the right ventricle and auricles to explain these different responses. To interpret these values, it is too necessary to remember that the intra-individual biological variations can go up to 70% for NT-proBNP and 30% for TnT (Vasile et al, 2010. However, as variations of 100% for TnT and from 11 to 200% for NT-pro-BNP were observed, these observations could be really due to the effort and not due only to intra-individual biological variations. Moreover, both of these markers are eliminated via the kidneys, but of course the serum level reflects a balance between release and degradation. One of the high-NT-proBNP cyclists had fairly high levels of renal markers, but the other did not. Perhaps our most interesting results concern cyclist number 6 (Table 1: this cyclist showed high values of CK and the highest levels of hsTnT and myoglobin. As myoglobinemia can be indicative of renal impairment (Neumayr et al., 2005 and as cTnT is degraded and then eliminated via the kidneys, this points to a particularly strong impact of exercise on renal function in this individual. Regarding hsTnT, however, it should be noted that the other cyclists showing an unusually high level of this biomarker had reasonable levels of myoglobinemia. In conclusion, concentrating on the most extreme observed rises in cardiospecific biomarkers (probably not indicative of any

  13. Biomarkers for the detection, prognois and evaluation of active tuberculosis

    Energy Technology Data Exchange (ETDEWEB)

    Shinimukundan, Harshini [Los Alamos National Laboratory

    2010-12-08

    The global TS surveillance workshop aims to address the problems with current methods for the detection of TB, and tracking emergence of resistant strains. The purpose of the attached presentation is to review the current methods in the detection of pathogen biomarkers for TB and if that technology has promise for diagnosis of TB. A summary of three biomarkers and some data on their detection strategies is presented. Some of the work is from LANL work but much of it is derived from literature references on the subject.

  14. Hippocampus discovery First steps

    Directory of Open Access Journals (Sweden)

    Eliasz Engelhardt

    Full Text Available The first steps of the discovery, and the main discoverers, of the hippocampus are outlined. Arantius was the first to describe a structure he named "hippocampus" or "white silkworm". Despite numerous controversies and alternate designations, the term hippocampus has prevailed until this day as the most widely used term. Duvernoy provided an illustration of the hippocampus and surrounding structures, considered the first by most authors, which appeared more than one and a half century after Arantius' description. Some authors have identified other drawings and texts which they claim predate Duvernoy's depiction, in studies by Vesalius, Varolio, Willis, and Eustachio, albeit unconvincingly. Considering the definition of the hippocampal formation as comprising the hippocampus proper, dentate gyrus and subiculum, Arantius and Duvernoy apparently described the gross anatomy of this complex. The pioneering studies of Arantius and Duvernoy revealed a relatively small hidden formation that would become one of the most valued brain structures.

  15. Investigations into Library Web-Scale Discovery Services

    Directory of Open Access Journals (Sweden)

    Jason Vaughan

    2008-03-01

    Full Text Available Web-scale discovery services for libraries provide deep discovery to a library’s local and licensed content, and represent an evolution, perhaps a revolution, for end user information discovery as pertains to library collections.  This article frames the topic of web-scale discovery, and begins by illuminating web-scale discovery from an academic library’s perspective – that is, the internal perspective seeking widespread staff participation in the discovery conversation.  This included the creation of a discovery task force, a group which educated library staff, conducted internal staff surveys, and gathered observations from early adopters.  The article next addresses the substantial research conducted with library vendors which have developed these services.  Such work included drafting of multiple comprehensive question lists distributed to the vendors, onsite vendor visits, and continual tracking of service enhancements.  Together, feedback gained from library staff, insights arrived at by the Discovery Task Force, and information gathered from vendors collectively informed the recommendation of a service for the UNLV Libraries.

  16. Performance Evaluation of Frequent Subgraph Discovery Techniques

    Directory of Open Access Journals (Sweden)

    Saif Ur Rehman

    2014-01-01

    Full Text Available Due to rapid development of the Internet technology and new scientific advances, the number of applications that model the data as graphs increases, because graphs have highly expressive power to model a complicated structure. Graph mining is a well-explored area of research which is gaining popularity in the data mining community. A graph is a general model to represent data and has been used in many domains such as cheminformatics, web information management system, computer network, and bioinformatics, to name a few. In graph mining the frequent subgraph discovery is a challenging task. Frequent subgraph mining is concerned with discovery of those subgraphs from graph dataset which have frequent or multiple instances within the given graph dataset. In the literature a large number of frequent subgraph mining algorithms have been proposed; these included FSG, AGM, gSpan, CloseGraph, SPIN, Gaston, and Mofa. The objective of this research work is to perform quantitative comparison of the above listed techniques. The performances of these techniques have been evaluated through a number of experiments based on three different state-of-the-art graph datasets. This novel work will provide base for anyone who is working to design a new frequent subgraph discovery technique.

  17. Integration of Antibody Array Technology into Drug Discovery and Development.

    Science.gov (United States)

    Huang, Wei; Whittaker, Kelly; Zhang, Huihua; Wu, Jian; Zhu, Si-Wei; Huang, Ruo-Pan

    Antibody arrays represent a high-throughput technique that enables the parallel detection of multiple proteins with minimal sample volume requirements. In recent years, antibody arrays have been widely used to identify new biomarkers for disease diagnosis or prognosis. Moreover, many academic research laboratories and commercial biotechnology companies are starting to apply antibody arrays in the field of drug discovery. In this review, some technical aspects of antibody array development and the various platforms currently available will be addressed; however, the main focus will be on the discussion of antibody array technologies and their applications in drug discovery. Aspects of the drug discovery process, including target identification, mechanisms of drug resistance, molecular mechanisms of drug action, drug side effects, and the application in clinical trials and in managing patient care, which have been investigated using antibody arrays in recent literature will be examined and the relevance of this technology in progressing this process will be discussed. Protein profiling with antibody array technology, in addition to other applications, has emerged as a successful, novel approach for drug discovery because of the well-known importance of proteins in cell events and disease development.

  18. Latent class models for joint analysis of disease prevalence and high-dimensional semicontinuous biomarker data.

    Science.gov (United States)

    Zhang, Bo; Chen, Zhen; Albert, Paul S

    2012-01-01

    High-dimensional biomarker data are often collected in epidemiological studies when assessing the association between biomarkers and human disease is of interest. We develop a latent class modeling approach for joint analysis of high-dimensional semicontinuous biomarker data and a binary disease outcome. To model the relationship between complex biomarker expression patterns and disease risk, we use latent risk classes to link the 2 modeling components. We characterize complex biomarker-specific differences through biomarker-specific random effects, so that different biomarkers can have different baseline (low-risk) values as well as different between-class differences. The proposed approach also accommodates data features that are common in environmental toxicology and other biomarker exposure data, including a large number of biomarkers, numerous zero values, and complex mean-variance relationship in the biomarkers levels. A Monte Carlo EM (MCEM) algorithm is proposed for parameter estimation. Both the MCEM algorithm and model selection procedures are shown to work well in simulations and applications. In applying the proposed approach to an epidemiological study that examined the relationship between environmental polychlorinated biphenyl (PCB) exposure and the risk of endometriosis, we identified a highly significant overall effect of PCB concentrations on the risk of endometriosis.

  19. Urinary Biomarkers of Brain Diseases

    Directory of Open Access Journals (Sweden)

    Manxia An

    2015-12-01

    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.

  20. Biomarkers of latent TB infection

    DEFF Research Database (Denmark)

    Ruhwald, Morten; Ravn, Pernille

    2009-01-01

    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....

  1. Mass spectrometry-driven drug discovery for development of herbal medicine.

    Science.gov (United States)

    Zhang, Aihua; Sun, Hui; Wang, Xijun

    2018-05-01

    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. © 2016 Wiley Periodicals, Inc.

  2. Recommendations for cerebrospinal fluid Alzheimer's disease biomarkers in the diagnostic evaluation of mild cognitive impairment

    DEFF Research Database (Denmark)

    Herukka, Sanna-Kaisa; Simonsen, Anja Hviid; Andreasen, Niels

    2017-01-01

    ) patient counseling. The working group recommended using CSF AD biomarkers in the diagnostic workup of MCI patients, after prebiomarker counseling, as an add-on to clinical evaluation to predict functional decline or conversion to AD dementia and to guide disease management. Because of insufficient...... evidence, it was uncertain whether CSF AD biomarkers outperform imaging biomarkers. Furthermore, the working group provided recommendations for interpretation of ambiguous CSF biomarker results and for pre- and post-biomarker counseling....... impairment (MCI). The recommendations were developed by a multidisciplinary working group and based on the available evidence and consensus from focused group discussions for 1) prediction of clinical progression to Alzheimer's disease (AD) dementia, 2) cost-effectiveness, 3) interpretation of results, and 4...

  3. 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

    2016-11-01

    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

  4. Analysis of biomarker data a practical guide

    CERN Document Server

    Looney, Stephen W

    2015-01-01

    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

  5. 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

    2011-01-01

    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...... sequences are united by DNA ligation upon simultaneous target binding forming a PCR amplicon. Multiplex PLA thereby converts multiple target analytes into real-time PCR amplicons that are individually quantificatied using microfluidic high capacity qPCR in nano liter volumes. The assay shows excellent...

  6. Recommendations for adaptation and validation of commercial kits for biomarker quantification in drug development.

    Science.gov (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

    2015-01-01

    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.

  7. OARSI Clinical Trials Recommendations: Soluble biomarker assessments in clinical trials in osteoarthritis.

    Science.gov (United States)

    Kraus, V B; Blanco, F J; Englund, M; Henrotin, Y; Lohmander, L S; Losina, E; Önnerfjord, P; Persiani, S

    2015-05-01

    The objective of this work was to describe requirements for inclusion of soluble biomarkers in osteoarthritis (OA) clinical trials and progress toward OA-related biomarker qualification. The Guidelines for Biomarkers Working Group, representing experts in the field of OA biomarker research from both academia and industry, convened to discuss issues related to soluble biomarkers and to make recommendations for their use in OA clinical trials based on current knowledge and anticipated benefits. This document summarizes current guidance on use of biomarkers in OA clinical trials and their utility at five stages, including preclinical development and phase I to phase IV trials. As demonstrated by this summary, biomarkers can provide value at all stages of therapeutics development. When resources permit, we recommend collection of biospecimens in all OA clinical trials for a wide variety of reasons but in particular, to determine whether biomarkers are useful in identifying those individuals most likely to receive clinically important benefits from an intervention; and to determine whether biomarkers are useful for identifying individuals at earlier stages of OA in order to institute treatment at a time more amenable to disease modification. Copyright © 2015 Osteoarthritis Research Society International. Published by Elsevier Ltd. All rights reserved.

  8. Materials Discovery | Materials Science | NREL

    Science.gov (United States)

    Discovery Materials Discovery Images of red and yellow particles NREL's research in materials characterization of sample by incoming beam and measuring outgoing particles, with data being stored and analyzed Staff Scientist Dr. Zakutayev specializes in design of novel semiconductor materials for energy

  9. Service discovery using Bloom filters

    NARCIS (Netherlands)

    Goering, P.T.H.; Heijenk, Geert; Lelieveldt, B.P.F.; Haverkort, Boudewijn R.H.M.; de Laat, C.T.A.M.; Heijnsdijk, J.W.J.

    A protocol to perform service discovery in adhoc networks is introduced in this paper. Attenuated Bloom filters are used to distribute services to nodes in the neighborhood and thus enable local service discovery. The protocol has been implemented in a discrete event simulator to investigate the

  10. On the pulse of discovery

    Science.gov (United States)

    2017-12-01

    What started 50 years ago as a `smudge' on paper has flourished into a fundamental field of astrophysics replete with unexpected applications and exciting discoveries. To celebrate the discovery of pulsars, we look at the past, present and future of pulsar astrophysics.

  11. Candidate proteomic biomarkers for non-alcoholic fatty liver disease (steatosis and non-alcoholic steatohepatitis) discovered with mass-spectrometry: a systematic review.

    Science.gov (United States)

    Lădaru, Anca; Bălănescu, Paul; Stan, Mihaela; Codreanu, Ioana; Anca, Ioana Alina

    2016-01-01

    Non-alcoholic fatty liver disease (NAFLD) is characterized by lipid accumulation in the liver which is accompanied by a series of metabolic deregulations. There are sustained research efforts focusing upon biomarker discovery for NAFLD diagnosis and its prognosis in order investigate and follow-up patients as minimally invasive as possible. The objective of this study is to critically review proteomic studies that used mass spectrometry techniques and summarize relevant proteomic NAFLD candidate biomarkers. Medline and Embase databases were searched from inception to December 2014. A final number of 22 records were included that identified 251 candidate proteomic biomarkers. Thirty-three biomarkers were confirmed - 14 were found in liver samples, 21 in serum samples, and two from both serum and liver samples. Some of the biomarkers identified have already been extensively studied regarding their diagnostic and prognostic capacity. However, there are also more potential biomarkers that still need to be addressed in future studies.

  12. Biomarkers of World Trade Center Particulate Matter Exposure: Physiology of distal airway and blood biomarkers that predict FEV1 decline

    Science.gov (United States)

    Weiden, Michael D.; Kwon, Sophia; Caraher, Erin; Berger, Kenneth I.; Reibman, Joan; Rom, William N.; Prezant, David J.; Nolan, Anna

    2016-01-01

    Biomarkers can be important predictors of disease severity and progression. The intense exposure to particulates and other toxins from the destruction of the World Trade Center (WTC) overwhelmed the lung’s normal protective barriers. The Fire Department of New York (FDNY) cohort not only had baseline pre-exposure lung function measures but also had serum samples banked soon after their WTC exposure. This well phenotyped group of highly exposed first responders is an ideal cohort for biomarker discovery and eventual validation. Disease progression was heterogeneous in this group in that some individuals subsequently developed abnormal lung function while others recovered. Airflow obstruction predominated in WTC exposed patients who were symptomatic. Multiple independent disease pathways may cause this abnormal FEV1 after irritant exposure. WTC exposure activates one or more of these pathways causing abnormal FEV1 in an individual. Our hypothesis was that serum biomarkers expressed within 6 months after World Trade Center (WTC) exposure reflect active disease pathways and predict subsequent development or protection from abnormal FEV1biomarkers of WTC-LI. We have identified biomarkers of Inflammation, metabolic derangement, protease/antiprotease balance and vascular injury expressed in serum within 6 months of WTC exposure that were predictive of their FEV1 up to 7 years after their WTC exposure. Predicting future risk of airway injury after particulate exposures can focus monitoring and early treatment on a subset of patients in greatest need of these services. PMID:26024341

  13. STS-95 Discovery in the VAB as launch preparations continue

    Science.gov (United States)

    1998-01-01

    United Space Alliance Forward Shop workers stand near the orbiter Discovery in the Vehicle Assembly Building . The orbiter is being prepared for mating with the external tank. Discovery displays the recently painted NASA logo, termed the 'meatball,' on its left, or port, wing. The logo also has been painted on both sides of the aft fuselage. Discovery (OV-103), the first of the orbiters to be launched with the new art work, is scheduled for its 25th flight, from Launch Pad 39B, on Oct. 29, 1998, for the STS-95 mission.

  14. 29 CFR 2700.56 - Discovery; general.

    Science.gov (United States)

    2010-07-01

    ...(c) or 111 of the Act has been filed. 30 U.S.C. 815(c) and 821. (e) Completion of discovery... 29 Labor 9 2010-07-01 2010-07-01 false Discovery; general. 2700.56 Section 2700.56 Labor... Hearings § 2700.56 Discovery; general. (a) Discovery methods. Parties may obtain discovery by one or more...

  15. 19 CFR 207.109 - Discovery.

    Science.gov (United States)

    2010-04-01

    ... 19 Customs Duties 3 2010-04-01 2010-04-01 false Discovery. 207.109 Section 207.109 Customs Duties... and Committee Proceedings § 207.109 Discovery. (a) Discovery methods. All parties may obtain discovery under such terms and limitations as the administrative law judge may order. Discovery may be by one or...

  16. 30 CFR 44.24 - Discovery.

    Science.gov (United States)

    2010-07-01

    ... 30 Mineral Resources 1 2010-07-01 2010-07-01 false Discovery. 44.24 Section 44.24 Mineral... Discovery. Parties shall be governed in their conduct of discovery by appropriate provisions of the Federal... discovery. Alternative periods of time for discovery may be prescribed by the presiding administrative law...

  17. 19 CFR 356.20 - Discovery.

    Science.gov (United States)

    2010-04-01

    ... 19 Customs Duties 3 2010-04-01 2010-04-01 false Discovery. 356.20 Section 356.20 Customs Duties... § 356.20 Discovery. (a) Voluntary discovery. All parties are encouraged to engage in voluntary discovery... sanctions proceeding. (b) Limitations on discovery. The administrative law judge shall place such limits...

  18. 24 CFR 180.500 - Discovery.

    Science.gov (United States)

    2010-04-01

    ... 24 Housing and Urban Development 1 2010-04-01 2010-04-01 false Discovery. 180.500 Section 180.500... OPPORTUNITY CONSOLIDATED HUD HEARING PROCEDURES FOR CIVIL RIGHTS MATTERS Discovery § 180.500 Discovery. (a) In general. This subpart governs discovery in aid of administrative proceedings under this part. Discovery in...

  19. 15 CFR 25.21 - Discovery.

    Science.gov (United States)

    2010-01-01

    ... 15 Commerce and Foreign Trade 1 2010-01-01 2010-01-01 false Discovery. 25.21 Section 25.21... Discovery. (a) The following types of discovery are authorized: (1) Requests for production of documents for..., discovery is available only as ordered by the ALJ. The ALJ shall regulate the timing of discovery. (d...

  20. 39 CFR 963.14 - Discovery.

    Science.gov (United States)

    2010-07-01

    ... 39 Postal Service 1 2010-07-01 2010-07-01 false Discovery. 963.14 Section 963.14 Postal Service... PANDERING ADVERTISEMENTS STATUTE, 39 U.S.C. 3008 § 963.14 Discovery. Discovery is to be conducted on a... such discovery as he or she deems reasonable and necessary. Discovery may include one or more of the...

  1. 22 CFR 224.21 - Discovery.

    Science.gov (United States)

    2010-04-01

    ... 22 Foreign Relations 1 2010-04-01 2010-04-01 false Discovery. 224.21 Section 224.21 Foreign....21 Discovery. (a) The following types of discovery are authorized: (1) Requests for production of... parties, discovery is available only as ordered by the ALJ. The ALJ shall regulate the timing of discovery...

  2. An integrative multi-platform analysis for discovering biomarkers of osteosarcoma

    International Nuclear Information System (INIS)

    Li, Guodong; Zhang, Wenjuan; Zeng, Huazong; Chen, Lei; Wang, Wenjing; Liu, Jilong; Zhang, Zhiyu; Cai, Zhengdong

    2009-01-01

    SELDI-TOF-MS (Surface Enhanced Laser Desorption/Ionization-Time of Flight-Mass Spectrometry) has become an attractive approach for cancer biomarker discovery due to its ability to resolve low mass proteins and high-throughput capability. However, the analytes from mass spectrometry are described only by their mass-to-charge ratio (m/z) values without further identification and annotation. To discover potential biomarkers for early diagnosis of osteosarcoma, we designed an integrative workflow combining data sets from both SELDI-TOF-MS and gene microarray analysis. After extracting the information for potential biomarkers from SELDI data and microarray analysis, their associations were further inferred by link-test to identify biomarkers that could likely be used for diagnosis. Immuno-blot analysis was then performed to examine whether the expression of the putative biomarkers were indeed altered in serum from patients with osteosarcoma. Six differentially expressed protein peaks with strong statistical significances were detected by SELDI-TOF-MS. Four of the proteins were up-regulated and two of them were down-regulated. Microarray analysis showed that, compared with an osteoblastic cell line, the expression of 653 genes was changed more than 2 folds in three osteosarcoma cell lines. While expression of 310 genes was increased, expression of the other 343 genes was decreased. The two sets of biomarkers candidates were combined by the link-test statistics, indicating that 13 genes were potential biomarkers for early diagnosis of osteosarcoma. Among these genes, cytochrome c1 (CYC-1) was selected for further experimental validation. Link-test on datasets from both SELDI-TOF-MS and microarray high-throughput analysis can accelerate the identification of tumor biomarkers. The result confirmed that CYC-1 may be a promising biomarker for early diagnosis of osteosarcoma

  3. Prognostic Biomarkers Used for Localised Prostate Cancer Management: A Systematic Review.

    Science.gov (United States)

    Lamy, Pierre-Jean; Allory, Yves; Gauchez, Anne-Sophie; Asselain, Bernard; Beuzeboc, Philippe; de Cremoux, Patricia; Fontugne, Jacqueline; Georges, Agnès; Hennequin, Christophe; Lehmann-Che, Jacqueline; Massard, Christophe; Millet, Ingrid; Murez, Thibaut; Schlageter, Marie-Hélène; Rouvière, Olivier; Kassab-Chahmi, Diana; Rozet, François; Descotes, Jean-Luc; Rébillard, Xavier

    2017-03-07

    Prostate cancer stratification is based on tumour size, pretreatment PSA level, and Gleason score, but it remains imperfect. Current research focuses on the discovery and validation of novel prognostic biomarkers to improve the identification of patients at risk of aggressive cancer or of tumour relapse. This systematic review by the Intergroupe Coopérateur Francophone de Recherche en Onco-urologie (ICFuro) analysed new evidence on the analytical validity and clinical validity and utility of six prognostic biomarkers (PHI, 4Kscore, MiPS, GPS, Prolaris, Decipher). All available data for the six biomarkers published between January 2002 and April 2015 were systematically searched and reviewed. The main endpoints were aggressive prostate cancer prediction, additional value compared to classical prognostic parameters, and clinical benefit for patients with localised prostate cancer. The preanalytical and analytical validations were heterogeneous for all tests and often not adequate for the molecular signatures. Each biomarker was studied for specific indications (candidates for a first or second biopsy, and potential candidates for active surveillance, radical prostatectomy, or adjuvant treatment) for which the level of evidence (LOE) was variable. PHI and 4Kscore were the biomarkers with the highest LOE for discriminating aggressive and indolent tumours in different indications. Blood biomarkers (PHI and 4Kscore) have the highest LOE for the prediction of more aggressive prostate cancer and could help clinicians to manage patients with localised prostate cancer. The other biomarkers show a potential prognostic value; however, they should be evaluated in additional studies to confirm their clinical validity. We reviewed studies assessing the value of six prognostic biomarkers for prostate cancer. On the basis of the available evidence, some biomarkers could help in discriminating between aggressive and non-aggressive tumours with an additional value compared to the

  4. Neopeptide Analyser: A software tool for neopeptide discovery in proteomics data [version 1; referees: 2 approved

    Directory of Open Access Journals (Sweden)

    Mandy Peffers

    2017-04-01

    Full Text Available Experiments involving mass spectrometry (MS-based proteomics are widely used for analyses of connective tissues. Common examples include the use of relative quantification to identify differentially expressed peptides and proteins in cartilage and tendon. We are working on characterising so-called ‘neopeptides’, i.e. peptides formed due to native cleavage of proteins, for example under pathological conditions. Unlike peptides typically quantified in MS workflows due to the in vitro use of an enzyme such as trypsin, a neopeptide has at least one terminus that was not due to the use of trypsin in the workflow. The identification of neopeptides within these datasets is important in understanding disease pathology, and the development of antibodies that could be utilised as diagnostic biomarkers for diseases, such as osteoarthritis, and targets for novel treatments. Our previously described neopeptide data analysis workflow was laborious and was not amenable to robust statistical analysis, which reduced confidence in the neopeptides identified. To overcome this, we developed ‘Neopeptide Analyser’, a user friendly neopeptide analysis tool used in conjunction with label-free MS quantification tool Progenesis QIP for proteomics. Neopeptide Analyser filters data sourced from Progenesis QIP output to identify neopeptide sequences, as well as give the residues that are adjacent to the peptide in its corresponding protein sequence. It also produces normalised values for the neopeptide quantification values and uses these to perform statistical tests, which are also included in the output. Neopeptide Analyser is available as a Java application for Mac, Windows and Linux. The analysis features and ease of use encourages data exploration, which could aid the discovery of novel pathways in extracellular matrix degradation, the identification of potential biomarkers and as a tool to investigate matrix turnover. Neopeptide Analyser is available from

  5. Evaluation of pathogen-specific biomarkers for the diagnosis of tuberculosis in white-tailed deer (Odocoileus virginianus)

    Science.gov (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 ...

  6. Chromosome 1q21.3 amplification is a trackable biomarker and actionable target for breast cancer recurrence

    DEFF Research Database (Denmark)

    Goh, Jian Yuan; Feng, Min; Wang, Wenyu

    2017-01-01

    Tumor recurrence remains the main reason for breast cancer-associated mortality, and there are unmet clinical demands for the discovery of new biomarkers and development of treatment solutions to benefit patients with breast cancer at high risk of recurrence. Here we report the identification of ...

  7. Biomarker Production and Preservation on Europa

    Science.gov (United States)

    Buffo, J.; Schmidt, B. E.

    2017-12-01

    Future landing site selection and sampling techniques for Europa will concentrate on locations of high potential biomarker preservation, however it is unclear what the best targets might be. On Europa, the scenario is quite unlike the depositional surface environments of terrestrial planets we've studied thus far-Europa's surface is passively communicating with putative habitable niches below that extend throughout the ice shell, ocean and sea floor. In this work, I approach biomarker production and preservation on Europa based by considering the many hypotheses that govern the its habitability, the processes that occur within the sea floor, ocean, and ice and exchange between them, and the geologic hypotheses for the formation of its various surfaces to establish, what journey through the planet a biomarker might take to arrive, if possible, at the surface where it is accessible to near-term landed missions. The goal of this project is to construct a simple model through which to consider the context for sampled material that will provide us with the ability to identify limitations in our intuition, understanding of the Europan system, our current hypotheses and data, and provide a road map for developing both areas for new research and identifying technology gaps that we must overcome before we can confidently select a landing site or analyze a sample from the near surface of Europa. I first consider the nature of the environment, i.e. at the sea floor interface, the ocean, or ocean-ice interface, in order to establish what the likely "biomarker" could be and then trace its path through the system: downwelling through the shell, mixing through the ocean, and pathways to the surface. Importantly, many models exist for the production of Europa's surface and subsurface geology that could affect the integrity of a putative biomarker. Often we modulate such considerations as a function of the time-scales over which the geologic process occurs, however such processes

  8. The discovery of long-term potentiation.

    Science.gov (United States)

    Lømo, Terje

    2003-04-29

    This paper describes circumstances around the discovery of long-term potentiation (LTP). In 1966, I had just begun independent work for the degree of Dr medicinae (PhD) in Per Andersen's laboratory in Oslo after an eighteen-month apprenticeship with him. Studying the effects of activating the perforant path to dentate granule cells in the hippocampus of anaesthetized rabbits, I observed that brief trains of stimuli resulted in increased efficiency of transmission at the perforant path-granule cell synapses that could last for hours. In 1968, Tim Bliss came to Per Andersen's laboratory to learn about the hippocampus and field potential recording for studies of possible memory mechanisms. The two of us then followed up my preliminary results from 1966 and did the experiments that resulted in a paper that is now properly considered to be the basic reference for the discovery of LTP.

  9. Polonium: 110th anniversary of its discovery

    International Nuclear Information System (INIS)

    Mould, R. F.

    2008-01-01

    It is appropriate that the 110 Th anniversary of the discovery of polonium by Marie and Pierre Curie is commemorated in a Polish journal since this element was named for Poland and was also the element discovered by the Curies before they discovered radium. Polonium's discovery and characteristics are described. Polonium has never been used in medicine, and was largely forgotten apart from a few minor industrial uses, and as a trigger for a nuclear weapon, until the murder in November 2006 in London using 210 Polonium, of the ex-KGB officer Alexander Litvinenko. Polonium had previously been linked, without any definite proof, with the deaths of a few scientists who had worked with the element, including Irene and Frederick Joliet-Curie. This review ends with possible evidence for such links. (authors)

  10. When whole-genome alignments just won't work: kSNP v2 software for alignment-free SNP discovery and phylogenetics of hundreds of microbial genomes.

    Science.gov (United States)

    Gardner, Shea N; Hall, Barry G

    2013-01-01

    Effective use of rapid and inexpensive whole genome sequencing for microbes requires fast, memory efficient bioinformatics tools for sequence comparison. The kSNP v2 software finds single nucleotide polymorphisms (SNPs) in whole genome data. kSNP v2 has numerous improvements over kSNP v1 including SNP gene annotation; better scaling for draft genomes available as assembled contigs or raw, unassembled reads; a tool to identify the optimal value of k; distribution of packages of executables for Linux and Mac OS X for ease of installation and user-friendly use; and a detailed User Guide. SNP discovery is based on k-mer analysis, and requires no multiple sequence alignment or the selection of a single reference genome. Most target sets with hundreds of genomes complete in minutes to hours. SNP phylogenies are built by maximum likelihood, parsimony, and distance, based on all SNPs, only core SNPs, or SNPs present in some intermediate user-specified fraction of targets. The SNP-based trees that result are consistent with known taxonomy. kSNP v2 can handle many gigabases of sequence in a single run, and if one or more annotated genomes are included in the target set, SNPs are annotated with protein coding and other information (UTRs, etc.) from Genbank file(s). We demonstrate application of kSNP v2 on sets of viral and bacterial genomes, and discuss in detail analysis of a set of 68 finished E. coli and Shigella genomes and a set of the same genomes to which have been added 47 assemblies and four "raw read" genomes of H104:H4 strains from the recent European E. coli outbreak that resulted in both bloody diarrhea and hemolytic uremic syndrome (HUS), and caused at least 50 deaths.

  11. Circulating microRNAs as Potential Biomarkers of Infectious Disease

    Science.gov (United States)

    Correia, Carolina N.; Nalpas, Nicolas C.; McLoughlin, Kirsten E.; Browne, John A.; Gordon, Stephen V.; MacHugh, David E.; Shaughnessy, Ronan G.

    2017-01-01

    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

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

    LENUS (Irish Health Repository)

    Dakna, Mohammed

    2010-12-10

    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.

  13. Recommendations and Standardization of Biomarker Quantification Using NMR-based Metabolomics with Particular Focus on Urinary Analysis

    KAUST Repository

    Emwas, Abdul-Hamid M.

    2016-01-08

    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.

  14. Can the Growth/Differentiation Factor-15 Be a Surrogate Target in Chronic Heart Failure Biomarker-Guided Therapy?

    Directory of Open Access Journals (Sweden)

    Alexander E. Berezin

    2017-03-01

    Full Text Available Heart failure (HF biomarker-guided therapy is a promising method, which directs to the improvement of clinical status, attenuation of admission/readmission to the hospital and reduction in mortality rate. Many biological markers, like inflammatory cytokines, are under consideration as a surrogate target for HF treatment, while there are known biomarkers with established predictive value, such as natriuretic peptides. However, discovery of new biomarkers reflecting various underlying mechanisms of HF and appearing to be surrogate targets for biomarker-guided therapy is fairly promising. Nowadays, growth/differentiation factor 15 (GDF-15 is suggested a target biomarker for HF treatment. Although elevated level of GDF-15 is associated with HF development, progression, and prognosis, there is no represented evidence regarding the direct comparison of this biomarker with other clinical risk predictors and biomarkers. Moreover, GDF-15 might serve as a contributor to endothelial progenitor cells (EPC dysfunction by inducing EPC death/autophagy and limiting their response to angiopoetic and reparative effects. The short communication was discussed whether GDF-15 is good molecular target for HF biomarker-guided therapy.

  15. Recommendations and Standardization of Biomarker Quantification Using NMR-based Metabolomics with Particular Focus on Urinary Analysis

    KAUST Repository

    Emwas, Abdul-Hamid M.; Roy, Raja; McKay, Ryan T.; Ryan, Danielle; Brennan, Lorraine; Tenori, Leonardo; Luchinat, Claudio; Gao, Xin; Zeri, Ana Carolina; Gowda, G. A. Nagana; Raftery, Daniel; Steinbeck, Christoph; Salek, Reza M; Wishart, David S.

    2016-01-01

    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.

  16. Swift: 10 Years of Discovery

    Science.gov (United States)

    2014-12-01

    The conference Swift: 10 years of discovery was held in Roma at La Sapienza University on Dec. 2-5 2014 to celebrate 10 years of Swift successes. Thanks to a large attendance and a lively program, it provided the opportunity to review recent advances of our knowledge of the high-energy transient Universe both from the observational and theoretical sides. When Swift was launched on November 20, 2004, its prime objective was to chase Gamma-Ray Bursts and deepen our knowledge of these cosmic explosions. And so it did, unveiling the secrets of long and short GRBs. However, its multi-wavelength instrumentation and fast scheduling capabilities made it the most versatile mission ever flown. Besides GRBs, Swift has observed, and contributed to our understanding of, an impressive variety of targets including AGNs, supernovae, pulsars, microquasars, novae, variable stars, comets, and much more. Swift is continuously discovering rare and surprising events distributed over a wide range of redshifts, out to the most distant transient objects in the Universe. Such a trove of discoveries has been addressed during the conference with sessions dedicated to each class of events. Indeed, the conference in Rome was a spectacular celebration of the Swift 10th anniversary. It included sessions on all types of transient and steady sources. Top scientists from around the world gave invited and contributed talks. There was a large poster session, sumptuous lunches, news interviews and a glorious banquet with officials attending from INAF and ASI. All the presentations, as well as several conference pictures, can be found in the conference website (http://www.brera.inaf.it/Swift10/Welcome.html). These proceedings have been collected owing to the efforts of Paolo D’Avanzo who has followed each paper from submission to final acceptance. Our warmest thanks to Paolo for all his work. The Conference has been made possible by the support from La Sapienza University as well as from the ARAP

  17. Strategies to design clinical studies to identify predictive biomarkers in cancer research.

    Science.gov (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

    2017-02-01

    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. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

  18. Circulating exosomes and exosomal microRNAs as biomarkers in gastrointestinal cancer.

    Science.gov (United States)

    Nedaeinia, R; Manian, M; Jazayeri, M H; Ranjbar, M; Salehi, R; Sharifi, M; Mohaghegh, F; Goli, M; Jahednia, S H; Avan, A; Ghayour-Mobarhan, M

    2017-02-01

    The most important biological function of exosomes is their possible use as biomarkers in clinical diagnosis. Compared with biomarkers identified in conventional specimens such as serum or urine, exosomal biomarkers provide the highest amount of sensitivity and specificity, which can be attributed to their excellent stability. Exosomes, which harbor different types of proteins, nucleic acids and lipids, are present in almost all bodily fluids. The molecular constituents of exosomes, especially exosomal proteins and microRNAs (miRNAs), are promising as biomarkers in clinical diagnosis. This discovery that exosomes also contain messenger RNAs and miRNAs shows that they could be carriers of genetic information. Although the majority of RNAs found in exosomes are degraded RNA fragments with a length of exosomal miRNAs have been found to be associated with certain diseases. Several studies have pointed out miRNA contents of circulating exosomes that are similar to those of originating cancer cells. In this review, the recent advances in circulating exosomal miRNAs as biomarkers in gastrointestinal cancers are discussed. These studies indicated that miRNAs can be detected in exosomes isolated from body fluids such as saliva, which suggests potential advantages of using exosomal miRNAs as noninvasive novel biomarkers.

  19. Biomarkers in Sports and Exercise: Tracking Health, Performance, and Recovery in Athletes.

    Science.gov (United States)

    Lee, Elaine C; Fragala, Maren S; Kavouras, Stavros A; Queen, Robin M; Pryor, John Luke; Casa, Douglas J

    2017-10-01

    Biomarker discovery and validation is a critical aim of the medical and scientific community. Research into exercise and diet-related biomarkers aims to improve health, performance, and recovery in military personnel, athletes, and lay persons. Exercise physiology research has identified individual biomarkers for assessing health, performance, and recovery during exercise training. However, there are few recommendations for biomarker panels for tracking changes in individuals participating in physical activity and exercise training programs. Our approach was to review the current literature and recommend a collection of validated biomarkers in key categories of health, performance, and recovery that could be used for this purpose. We determined that a comprehensive performance set of biomarkers should include key markers of (a) nutrition and metabolic health, (b) hydration status, (c) muscle status, (d) endurance performance, (e) injury status and risk, and (f) inflammation. Our review will help coaches, clinical sport professionals, researchers, and athletes better understand how to comprehensively monitor physiologic changes, as they design training cycles that elicit maximal improvements in performance while minimizing overtraining and injury risk.

  20. Biomarkers in acute heart failure.

    Science.gov (United States)

    Mallick, Aditi; Januzzi, James L

    2015-06-01

    The care of patients with acutely decompensated heart failure is being reshaped by the availability and understanding of several novel and emerging heart failure biomarkers. The gold standard biomarkers in heart failure are B-type natriuretic peptide and N-terminal pro-B-type natriuretic peptide, which play an important role in the diagnosis, prognosis, and management of acute decompensated heart failure. Novel biomarkers that are increasingly involved in the processes of myocardial injury, neurohormonal activation, and ventricular remodeling are showing promise in improving diagnosis and prognosis among patients with acute decompensated heart failure. These include midregional proatrial natriuretic peptide, soluble ST2, galectin-3, highly-sensitive troponin, and midregional proadrenomedullin. There has also been an emergence of biomarkers for evaluation of acute decompensated heart failure that assist in the differential diagnosis of dyspnea, such as procalcitonin (for identification of acute pneumonia), as well as markers that predict complications of acute decompensated heart failure, such as renal injury markers. In this article, we will review the pathophysiology and usefulness of established and emerging biomarkers for the clinical diagnosis, prognosis, and management of acute decompensated heart failure. Copyright © 2015 Sociedad Española de Cardiología. Published by Elsevier España, S.L.U. All rights reserved.

  1. 'The Lusiads', poem of discovery

    Directory of Open Access Journals (Sweden)

    Natasha Furlan Felizi

    2016-07-01

    Full Text Available The article proposes reading Os Lusíadas as a discovery journey. Discovery here read as aletheia or “revelation”, as proposed by Sophia de Mello Brey­ner Andresen in 1980. Using Martin Heidegger’s notion of aletheia in the book Parmenides along with Jorge de Sena and Sophia de Mello Breyner Andresen reflections on Camões, I’ll seek to point out alternative readings for Os Lusíadas as a “discovery journey”.

  2. Discovery of natural resources

    Science.gov (United States)

    Guild, P.W.

    1976-01-01

    Mankind will continue to need ores of more or less the types and grades used today to supply its needs for new mineral raw materials, at least until fusion or some other relatively cheap, inexhaustible energy source is developed. Most deposits being mined today were exposed at the surface or found by relatively simple geophysical or other prospecting techniques, but many of these will be depleted in the foreseeable future. The discovery of deeper or less obvious deposits to replace them will require the conjunction of science and technology to deduce the laws that governed the concentration of elements into ores and to detect and evaluate the evidence of their whereabouts. Great theoretical advances are being made to explain the origins of ore deposits and understand the general reasons for their localization. These advances have unquestionable value for exploration. Even a large deposit is, however, very small, and, with few exceptions, it was formed under conditions that have long since ceased to exist. The explorationist must suppress a great deal of "noise" to read and interpret correctly the "signals" that can define targets and guide the drilling required to find it. Is enough being done to ensure the long-term availability of mineral raw materials? The answer is probably no, in view of the expanding consumption and the difficulty of finding new deposits, but ingenuity, persistence, and continued development of new methods and tools to add to those already at hand should put off the day of "doing without" for many years. The possibility of resource exhaustion, especially in view of the long and increasing lead time needed to carry out basic field and laboratory studies in geology, geophysics, and geochemistry and to synthesize and analyze the information gained from them counsels against any letting down of our guard, however (17). Research and exploration by government, academia, and industry must be supported and encouraged; we cannot wait until an eleventh

  3. Supernovae Discovery Efficiency

    Science.gov (United States)

    John, Colin

    2018-01-01

    Abstract:We present supernovae (SN) search efficiency measurements for recent Hubble Space Telescope (HST) surveys. Efficiency is a key component to any search, and is important parameter as a correction factor for SN rates. To achieve an accurate value for efficiency, many supernovae need to be discoverable in surveys. This cannot be achieved from real SN only, due to their scarcity, so fake SN are planted. These fake supernovae—with a goal of realism in mind—yield an understanding of efficiency based on position related to other celestial objects, and brightness. To improve realism, we built a more accurate model of supernovae using a point-spread function. The next improvement to realism is planting these objects close to galaxies and of various parameters of brightness, magnitude, local galactic brightness and redshift. Once these are planted, a very accurate SN is visible and discoverable by the searcher. It is very important to find factors that affect this discovery efficiency. Exploring the factors that effect detection yields a more accurate correction factor. Further inquires into efficiency give us a better understanding of image processing, searching techniques and survey strategies, and result in an overall higher likelihood to find these events in future surveys with Hubble, James Webb, and WFIRST telescopes. After efficiency is discovered and refined with many unique surveys, it factors into measurements of SN rates versus redshift. By comparing SN rates vs redshift against the star formation rate we can test models to determine how long star systems take from the point of inception to explosion (delay time distribution). This delay time distribution is compared to SN progenitors models to get an accurate idea of what these stars were like before their deaths.

  4. Biomarker Analysis of Stored Blood Products: Emphasis on Pre-Analytical Issues

    Science.gov (United States)

    Delobel, Julien; Rubin, Olivier; Prudent, Michel; Crettaz, David; Tissot, Jean-Daniel; Lion, Niels

    2010-01-01

    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. PMID:21151459

  5. Students Excited by Stellar Discovery

    Science.gov (United States)

    2011-02-01

    In the constellation of Ophiuchus, above the disk of our Milky Way Galaxy, there lurks a stellar corpse spinning 30 times per second -- an exotic star known as a radio pulsar. This object was unknown until it was discovered last week by three high school students. These students are part of the Pulsar Search Collaboratory (PSC) project, run by the National Radio Astronomy Observatory (NRAO) in Green Bank, WV, and West Virginia University (WVU). The pulsar, which may be a rare kind of neutron star called a recycled pulsar, was discovered independently by Virginia students Alexander Snider and Casey Thompson, on January 20, and a day later by Kentucky student Hannah Mabry. "Every day, I told myself, 'I have to find a pulsar. I better find a pulsar before this class ends,'" said Mabry. When she actually made the discovery, she could barely contain her excitement. "I started screaming and jumping up and down." Thompson was similarly expressive. "After three years of searching, I hadn't found a single thing," he said, "but when I did, I threw my hands up in the air and said, 'Yes!'." Snider said, "It actually feels really neat to be the first person to ever see something like that. It's an uplifting feeling." As part of the PSC, the students analyze real data from NRAO's Robert C. Byrd Green Bank Telescope (GBT) to find pulsars. The students' teachers -- Debra Edwards of Sherando High School, Leah Lorton of James River High School, and Jennifer Carter of Rowan County Senior High School -- all introduced the PSC in their classes, and interested students formed teams to continue the work. Even before the discovery, Mabry simply enjoyed the search. "It just feels like you're actually doing something," she said. "It's a good feeling." Once the pulsar candidate was reported to NRAO, Project Director Rachel Rosen took a look and agreed with the young scientists. A followup observing session was scheduled on the GBT. Snider and Mabry traveled to West Virginia to assist in the

  6. Measuring and combining multiple diagnostic and prognostic sepsis biomarkers

    DEFF Research Database (Denmark)

    Kofoed, K.

    This PhD-thesis is based on work performed at Clinical Research Centre and Department of Infectious Diseases at Copenhagen University Hospital, Hvidovre, and includes a review, a method development study, and two clinical studies. The background of the thesis is, that timely and accurate diagnosis...... of sepsis is of great importance for choice of treatment, level of monitoring and prognosis. In this biomarkers could be a significant aid, and thus the search for and application of "new" sepsis biomarkers is of great importance. The thesis reviews the definitions and the epidemiology, and gives...

  7. Biomarkers in inflammatory bowel diseases

    DEFF Research Database (Denmark)

    Bennike, Tue; Birkelund, Svend; Stensballe, Allan

    2014-01-01

    Unambiguous diagnosis of the two main forms of inflammatory bowel diseases (IBD): Ulcerative colitis (UC) and Crohn's disease (CD), represents a challenge in the early stages of the diseases. The diagnosis may be established several years after the debut of symptoms. Hence, protein biomarkers...... for early and accurate diagnostic could help clinicians improve treatment of the individual patients. Moreover, the biomarkers could aid physicians to predict disease courses and in this way, identify patients in need of intensive treatment. Patients with low risk of disease flares may avoid treatment...... 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...

  8. Biomarkers of replicative senescence revisited

    DEFF Research Database (Denmark)

    Nehlin, Jan

    2016-01-01

    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...

  9. RAS - Screens & Assays - Drug Discovery

    Science.gov (United States)

    The RAS Drug Discovery group aims to develop assays that will reveal aspects of RAS biology upon which cancer cells depend. Successful assay formats are made available for high-throughput screening programs to yield potentially effective drug compounds.

  10. Antibody informatics for drug discovery

    DEFF Research Database (Denmark)

    Shirai, Hiroki; Prades, Catherine; Vita, Randi

    2014-01-01

    to the antibody science in every project in antibody drug discovery. Recent experimental technologies allow for the rapid generation of large-scale data on antibody sequences, affinity, potency, structures, and biological functions; this should accelerate drug discovery research. Therefore, a robust bioinformatic...... infrastructure for these large data sets has become necessary. In this article, we first identify and discuss the typical obstacles faced during the antibody drug discovery process. We then summarize the current status of three sub-fields of antibody informatics as follows: (i) recent progress in technologies...... for antibody rational design using computational approaches to affinity and stability improvement, as well as ab-initio and homology-based antibody modeling; (ii) resources for antibody sequences, structures, and immune epitopes and open drug discovery resources for development of antibody drugs; and (iii...

  11. Discovery of the iron isotopes

    International Nuclear Information System (INIS)

    Schuh, A.; Fritsch, A.; Heim, M.; Shore, A.; Thoennessen, M.

    2010-01-01

    Twenty-eight iron isotopes have been observed so far and the discovery of these isotopes is discussed here. For each isotope a brief summary of the first refereed publication, including the production and identification method, is presented.

  12. Discovery of the silver isotopes

    International Nuclear Information System (INIS)

    Schuh, A.; Fritsch, A.; Ginepro, J.Q.; Heim, M.; Shore, A.; Thoennessen, M.

    2010-01-01

    Thirty-eight silver isotopes have been observed so far and the discovery of these isotopes is discussed here. For each isotope a brief summary of the first refereed publication, including the production and identification method, is presented.

  13. Synthetic biology of antimicrobial discovery

    Science.gov (United States)

    Zakeri, Bijan; Lu, Timothy K.

    2012-01-01

    Antibiotic discovery has a storied history. From the discovery of penicillin by Sir Alexander Fleming to the relentless quest for antibiotics by Selman Waksman, the stories have become like folklore, used to inspire future generations of scientists. However, recent discovery pipelines have run dry at a time when multidrug resistant pathogens are on the rise. Nature has proven to be a valuable reservoir of antimicrobial agents, which are primarily produced by modularized biochemical pathways. Such modularization is well suited to remodeling by an interdisciplinary approach that spans science and engineering. Herein, we discuss the biological engineering of small molecules, peptides, and non-traditional antimicrobials and provide an overview of the growing applicability of synthetic biology to antimicrobials discovery. PMID:23654251

  14. Discovery of the cadmium isotopes

    International Nuclear Information System (INIS)

    Amos, S.; Thoennessen, M.

    2010-01-01

    Thirty-seven cadmium isotopes have been observed so far and the discovery of these isotopes is discussed here. For each isotope a brief summary of the first refereed publication, including the production and identification method, is presented.

  15. Discoveries of isotopes by fission

    Indian Academy of Sciences (India)

    country of discovery as well as the production mechanism used to produce the isotopes. ... the disintegration products of bombarded uranium, as a consequence of a ..... advanced accelerator and newly developed separation and detection ...

  16. Synthetic biology of antimicrobial discovery.

    Science.gov (United States)

    Zakeri, Bijan; Lu, Timothy K

    2013-07-19

    Antibiotic discovery has a storied history. From the discovery of penicillin by Sir Alexander Fleming to the relentless quest for antibiotics by Selman Waksman, the stories have become like folklore used to inspire future generations of scientists. However, recent discovery pipelines have run dry at a time when multidrug-resistant pathogens are on the rise. Nature has proven to be a valuable reservoir of antimicrobial agents, which are primarily produced by modularized biochemical pathways. Such modularization is well suited to remodeling by an interdisciplinary approach that spans science and engineering. Herein, we discuss the biological engineering of small molecules, peptides, and non-traditional antimicrobials and provide an overview of the growing applicability of synthetic biology to antimicrobials discovery.

  17. The discovery of 'heavy light'

    International Nuclear Information System (INIS)

    Anon.

    1983-01-01

    The history of the discoveries of fundamental quanta is described starting from Maxwell's theory of electromagnetism up to the development of a theory of weak interaction and the detection of the W and Z bosons. (HSI).

  18. Discovery – Development of Rituximab

    Science.gov (United States)

    NCI funded the development of rituximab, one of the first monoclonal antibody cancer treatments. With the discovery of rituximab, more than 70 percent of patients diagnosed with non-hodgkin lymphoma now live five years past their initial diagnosis.

  19. LABORATORY BIOMARKERS FOR ANKYLOSING SPONDYLITIS

    Directory of Open Access Journals (Sweden)

    E. N. Aleksandrova

    2017-01-01

    Full Text Available Ankylosing spondylitis (AS is a chronic inflammatory disease from a group of spondyloarthritis (SpA, which is characterized by lesions of the sacroiliac joints and spine with the common involvement of entheses and peripheral joints in the pathological process. Advances in modern laboratory medicine have contributed to a substantial expansion of the range of pathogenetic, diagnostic, and prognostic biomarkers of AS. As of now, there are key pathogenetic biomarkers of AS (therapeutic targets, which include tumor necrosis factor-α (TNF-α, interleukin 17 (IL-17, and IL-23. Among the laboratory diagnostic and prognostic biomarkers, HLA-B27 and C-reactive protein are of the greatest value in clinical practice; the former for the early diagnosis of the disease and the latter for the assessment of disease activity, the risk of radiographic progression and the efficiency of therapy. Anti-CD74 antibodies are a new biomarker that has high sensitivity and specificity values in diagnosing axial SpA at an early stage. A number of laboratory biomarkers, including calprotectin, matrix metalloproteinase-3 (MMP-3, vascular endothelial growth factor, Dickkopf-1 (Dkk-1, and C-terminal telopeptide of type II collagen (CTX II do not well reflect disease activity, but may predict progressive structural changes in the spine and sacroiliac joints in AS. Blood calprotectin level monitoring allows the effective prediction of a response to therapy with TNF inhibitors and anti-IL-17А monoclonal antibodies. The prospects for the laboratory diagnosis of AS are associated with the clinical validation of candidate biomarkers during large-scale prospective cohort studies and with a search for new proteomic, transcriptomic and genomic markers, by using innovative molecular and cellular technologies.

  20. 100 Years Jubilee for the discovery of the enzymes in yeast

    DEFF Research Database (Denmark)

    Berg, Rolf W.

    1997-01-01

    The work by Prof. E. Buchner 100 years ago which led to the discovery of the enzymes in yeast for brewing beer is reviewed.......The work by Prof. E. Buchner 100 years ago which led to the discovery of the enzymes in yeast for brewing beer is reviewed....