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Sample records for automated biomarker discovery

  1. Novel automated biomarker discovery work flow for urinary peptidomics

    DEFF Research Database (Denmark)

    Balog, Crina I.; Hensbergen, Paul J.; Derks, Rico; Verweij, Jaco J.; Dam, Govert J. van; Vennervald, Birgitte J; Deelder, André M.; Mayboroda, Oleg A.

    2009-01-01

    Urine is potentially a rich source of peptide biomarkers, but reproducible, high-throughput peptidomic analysis is often hampered by the inherent variability in factors such as pH and salt concentration. Our goal was to develop a generally applicable, rapid, and robust method for screening large...... numbers of urine samples, resulting in a broad spectrum of native peptides, as a tool to be used for biomarker discovery. METHODS: Peptide samples were trapped, desalted, pH-normalized, and fractionated on a miniaturized automatic reverse-phase strong cation exchange (RP-SCX) cartridge system. We analyzed...... samples from Schistosoma haematobium-infected individuals to evaluate clinical applicability. RESULTS: The automated RP-SCX sample cleanup and fractionation system exhibits a high qualitative and quantitative reproducibility, with both BSA standards and urine samples. Because of the relatively high...

  2. 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.

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

    OpenAIRE

    Vilém Guryča; Daniel Roeder; Paolo Piraino; Jens Lamerz; Axel Ducret; Hanno Langen; Paul Cutler

    2014-01-01

    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 t...

  4. Comprehensive and Scalable Highly Automated MS-Based Proteomic Workflow for Clinical Biomarker Discovery in Human Plasma.

    Science.gov (United States)

    Dayon, Loïc; Núñez Galindo, Antonio; Corthésy, John; Cominetti, Ornella; Kussmann, Martin

    2014-07-24

    Over the past decade, mass spectrometric performance has greatly improved in terms of sensitivity, dynamic range, and speed. By contrast, only limited progress has been accomplished with regard to automation, throughput, and robustness of the proteomic sample preparation process upstream of mass spectrometry. The present work delivers an optimized analysis of human plasma samples in both small preclinical and large clinical studies, enabled by the development of a highly automated quantitative proteomic workflow. Several iterative evaluation and validation steps were performed before process "design freeze" and development completion. A robotic liquid handling workflow and platform (including reduction, alkylation, digestion, TMT labeling, pooling, and purification) were shown to provide better quantitative trueness and precision than manual operation at the bench. Depletion of the most abundant human plasma proteins and subsequent buffer exchange were also developed and integrated. Finally, 96 identical pooled human plasma samples were prepared in a 96-well plate format, and each sample was individually subjected to our developed workflow. This test revealed increased throughput and robustness compared with to-date published manual or less automated workflows. Our workflow is ready-to-use for future (pre-) clinical studies. We expect our work to facilitate, accelerate, and improve clinical proteomic discovery in human blood plasma. PMID:25058407

  5. 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.

  6. 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.

  7. The proteomics in prostate cancer biomarker discovery

    Directory of Open Access Journals (Sweden)

    V. E. Shevchenko

    2015-06-01

    Full Text Available Prostate cancer (PC represents the second most frequent type of tumor in men worldwide. Proteomics represents a promising approach for the discovery of new biomarkers able to improve the management of PC patients. Markers more specific and sensitive than prostate-specific antigen are needed for PC diagnosis, prognosis and response to treatment. Moreover, proteomics could represent an important tool to identify new molecular targets for PC tailored therapy. Now several possible PC biomarkers sources, each with advantages and limitations, are under investigation, including tissues, urine, serum, plasma and prostatic fluids. Innovative high-throughput proteomic platforms are now identifying and quantifying new specific and sensitive biomarkers for PC detection, stratification and treatment. Nevertheless, many putative biomarkers are still far from being applied in clinical practice.This review aims to discuss the recent advances in PC proteomics, emphasizing biomarker discovery and their application to clinical utility for diagnosis and patient stratification.

  8. Biological Networks for Cancer Candidate Biomarkers Discovery

    Science.gov (United States)

    Yan, Wenying; Xue, Wenjin; Chen, Jiajia; Hu, Guang

    2016-01-01

    Due to its extraordinary heterogeneity and complexity, cancer is often proposed as a model case of a systems biology disease or network disease. There is a critical need of effective biomarkers for cancer diagnosis and/or outcome prediction from system level analyses. Methods based on integrating omics data into networks have the potential to revolutionize the identification of cancer biomarkers. Deciphering the biological networks underlying cancer is undoubtedly important for understanding the molecular mechanisms of the disease and identifying effective biomarkers. In this review, the networks constructed for cancer biomarker discovery based on different omics level data are described and illustrated from recent advances in the field.

  9. Biological Networks for Cancer Candidate Biomarkers Discovery.

    Science.gov (United States)

    Yan, Wenying; Xue, Wenjin; Chen, Jiajia; Hu, Guang

    2016-01-01

    Due to its extraordinary heterogeneity and complexity, cancer is often proposed as a model case of a systems biology disease or network disease. There is a critical need of effective biomarkers for cancer diagnosis and/or outcome prediction from system level analyses. Methods based on integrating omics data into networks have the potential to revolutionize the identification of cancer biomarkers. Deciphering the biological networks underlying cancer is undoubtedly important for understanding the molecular mechanisms of the disease and identifying effective biomarkers. In this review, the networks constructed for cancer biomarker discovery based on different omics level data are described and illustrated from recent advances in the field. PMID:27625573

  10. Automating Spreadsheet Discovery & Risk Assessment

    CERN Document Server

    Perry, Eric

    2008-01-01

    There have been many articles and mishaps published about the risks of uncontrolled spreadsheets in today's business environment, including non-compliance, operational risk, errors, and fraud all leading to significant loss events. Spreadsheets fall into the realm of end user developed applications and are often absent the proper safeguards and controls an IT organization would enforce for enterprise applications. There is also an overall lack of software programming discipline enforced in how spreadsheets are developed. However, before an organization can apply proper controls and discipline to critical spreadsheets, an accurate and living inventory of spreadsheets across the enterprise must be created, and all critical spreadsheets must be identified. As such, this paper proposes an automated approach to the initial stages of the spreadsheet management lifecycle - discovery, inventory and risk assessment. Without the use of technology, these phases are often treated as a one-off project. By leveraging techn...

  11. Stable Feature Selection for Biomarker Discovery

    CERN Document Server

    He, Zengyou

    2010-01-01

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

  12. Proteomics Discovery of Disease Biomarkers

    OpenAIRE

    Mamoun Ahram; Petricoin, Emanuel F.

    2008-01-01

    Recent technological developments in proteomics have shown promising initiatives in identifying novel biomarkers of various diseases. Such technologies are capable of investigating multiple samples and generating large amount of data end-points. Examples of two promising proteomics technologies are mass spectrometry, including an instrument based on surface enhanced laser desorption/ionization, and protein microarrays. Proteomics data must, however, undergo analytical processing using bioinfo...

  13. 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.

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

    OpenAIRE

    Jordan, Rick; Visweswaran, Shyam; Gopalakrishnan, Vanathi

    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 cance...

  15. 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.

  16. Network-Based Protein Biomarker Discovery Platforms.

    Science.gov (United States)

    Kim, Minhyung; Hwang, Daehee

    2016-03-01

    The advances in mass spectrometry-based proteomics technologies have enabled the generation of global proteome data from tissue or body fluid samples collected from a broad spectrum of human diseases. Comparative proteomic analysis of global proteome data identifies and prioritizes the proteins showing altered abundances, called differentially expressed proteins (DEPs), in disease samples, compared to control samples. Protein biomarker candidates that can serve as indicators of disease states are then selected as key molecules among these proteins. Recently, it has been addressed that cellular pathways can provide better indications of disease states than individual molecules and also network analysis of the DEPs enables effective identification of cellular pathways altered in disease conditions and key molecules representing the altered cellular pathways. Accordingly, a number of network-based approaches to identify disease-related pathways and representative molecules of such pathways have been developed. In this review, we summarize analytical platforms for network-based protein biomarker discovery and key components in the platforms. PMID:27103885

  17. Automated Knowledge Discovery From Simulators

    Science.gov (United States)

    Burl, Michael; DeCoste, Dennis; Mazzoni, Dominic; Scharenbroich, Lucas; Enke, Brian; Merline, William

    2007-01-01

    A computational method, SimLearn, has been devised to facilitate efficient knowledge discovery from simulators. Simulators are complex computer programs used in science and engineering to model diverse phenomena such as fluid flow, gravitational interactions, coupled mechanical systems, and nuclear, chemical, and biological processes. SimLearn uses active-learning techniques to efficiently address the "landscape characterization problem." In particular, SimLearn tries to determine which regions in "input space" lead to a given output from the simulator, where "input space" refers to an abstraction of all the variables going into the simulator, e.g., initial conditions, parameters, and interaction equations. Landscape characterization can be viewed as an attempt to invert the forward mapping of the simulator and recover the inputs that produce a particular output. Given that a single simulation run can take days or weeks to complete even on a large computing cluster, SimLearn attempts to reduce costs by reducing the number of simulations needed to effect discoveries. Unlike conventional data-mining methods that are applied to static predefined datasets, SimLearn involves an iterative process in which a most informative dataset is constructed dynamically by using the simulator as an oracle. On each iteration, the algorithm models the knowledge it has gained through previous simulation trials and then chooses which simulation trials to run next. Running these trials through the simulator produces new data in the form of input-output pairs. The overall process is embodied in an algorithm that combines support vector machines (SVMs) with active learning. SVMs use learning from examples (the examples are the input-output pairs generated by running the simulator) and a principle called maximum margin to derive predictors that generalize well to new inputs. In SimLearn, the SVM plays the role of modeling the knowledge that has been gained through previous simulation trials

  18. Proteomics in Discovery of Hepatocellular Carcinoma Biomarkers

    Institute of Scientific and Technical Information of China (English)

    2007-01-01

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

  19. Discovery of Invariants through Automated Theory Formation

    CERN Document Server

    Llano, Maria Teresa; Pease, Alison; 10.4204/EPTCS.55.1

    2011-01-01

    Refinement is a powerful mechanism for mastering the complexities that arise when formally modelling systems. Refinement also brings with it additional proof obligations -- requiring a developer to discover properties relating to their design decisions. With the goal of reducing this burden, we have investigated how a general purpose theory formation tool, HR, can be used to automate the discovery of such properties within the context of Event-B. Here we develop a heuristic approach to the automatic discovery of invariants and report upon a series of experiments that we undertook in order to evaluate our approach. The set of heuristics developed provides systematic guidance in tailoring HR for a given Event-B development. These heuristics are based upon proof-failure analysis, and have given rise to some promising results.

  20. 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. PMID:26703953

  1. Cancer biomarker discovery in saliva by mass spectrometry

    Directory of Open Access Journals (Sweden)

    Kiran S. Ambatipudi

    2014-05-01

    Full Text Available The quest for biomarkers has been much pursued to aid in the early diagnosis, monitor post-treatment progress and development of targeted therapies. Nevertheless, the translation of biomarker discovery to clinical use has been limited due to multiple reasons such as the long path from discovery to clinical assays, limitation of samples and incoherent pipeline for biomarker development. To date, diagnosis of cancer has been based on biopsies and histological examinations and often becomes difficult to get repeated sampling from patients for confirmation. Consequently, it is important for clinical researchers to look at multiple body fluids and different molecular techniques to identify biomarkers. One such bodyfluid is saliva, which is easily and non-invasively collected and contains thousands of potential protein biomarkers. Moreover, recent advances in the sensitivity and specificity of mass spectrometry based proteomics hold great promise to identify potential biomarkers. This review presents an overview of the potential use of saliva and mass spectrometry for global discovery and validation of biomarkers.

  2. 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

  3. 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

  4. Computational and Experimental Approaches to Cancer Biomarker Discovery

    DEFF Research Database (Denmark)

    Krzystanek, Marcin

    Effective cancer treatment requires good biomarkers: measurable indicators of some biological state or condition that constitute the cornerstone of personalized medicine. Prognostic biomarkers provide information about the likely course of the disease, while predictive biomarkers enable prediction...... of a patient’s response to a particular treatment, thus helping to avoid unnecessary treatment and unwanted side effects in non-responding individuals.Currently biomarker discovery is facilitated by recent advances in high-throughput technologies when association between a given biological phenotype...... 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...

  5. Application of “omics” to Prion Biomarker Discovery

    Directory of Open Access Journals (Sweden)

    Rhiannon L. C. H. Huzarewich

    2010-01-01

    Full Text Available The advent of genomics and proteomics has been a catalyst for the discovery of biomarkers able to discriminate biological processes such as the pathogenesis of complex diseases. Prompt detection of prion diseases is particularly desirable given their transmissibility, which is responsible for a number of human health risks stemming from exogenous sources of prion protein. Diagnosis relies on the ability to detect the biomarker PrPSc, a pathological isoform of the host protein PrPC, which is an essential component of the infectious prion. Immunochemical detection of PrPSc is specific and sensitive enough for antemortem testing of brain tissue, however, this is not the case in accessible biological fluids or for the detection of recently identified novel prions with unique biochemical properties. A complementary approach to the detection of PrPSc itself is to identify alternative, “surrogate” gene or protein biomarkers indicative of disease. Biomarkers are also useful to track the progress of disease, especially important in the assessment of therapies, or to identify individuals “at risk”. In this review we provide perspective on current progress and pitfalls in the use of “omics” technologies to screen body fluids and tissues for biomarker discovery in prion diseases.

  6. PROFILEing idiopathic pulmonary fibrosis: rethinking biomarker discovery.

    Science.gov (United States)

    Maher, Toby M

    2013-06-01

    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. PMID:23728868

  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. Metabolomics for Biomarker Discovery in Gastroenterological Cancer

    Directory of Open Access Journals (Sweden)

    Shin Nishiumi

    2014-07-01

    Full Text Available The study of the omics cascade, which involves comprehensive investigations based on genomics, transcriptomics, proteomics, metabolomics, etc., has developed rapidly and now plays an important role in life science research. Among such analyses, metabolome analysis, in which the concentrations of low molecular weight metabolites are comprehensively analyzed, has rapidly developed along with improvements in analytical technology, and hence, has been applied to a variety of research fields including the clinical, cell biology, and plant/food science fields. The metabolome represents the endpoint of the omics cascade and is also the closest point in the cascade to the phenotype. Moreover, it is affected by variations in not only the expression but also the enzymatic activity of several proteins. Therefore, metabolome analysis can be a useful approach for finding effective diagnostic markers and examining unknown pathological conditions. The number of studies involving metabolome analysis has recently been increasing year-on-year. Here, we describe the findings of studies that used metabolome analysis to attempt to discover biomarker candidates for gastroenterological cancer and discuss metabolome analysis-based disease diagnosis.

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

    International Nuclear Information System (INIS)

    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

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

    Directory of Open Access Journals (Sweden)

    Patrick Chames

    2011-06-01

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

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2011-06-09

    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.

  12. 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

  13. Data mining of spectroscopic data for biomarker discovery.

    Science.gov (United States)

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

    2001-05-01

    The goals of precise diagnosis, prevention and treatment of disease can be realized through the discovery of biological markers. Spectroscopic tools can simultaneously detect and quantify multiple small molecule and macromolecular components of biological samples, and are therefore ideal methods for the discovery of previously uncharacterized markers. However, the identification of meaningful spectral features is complicated by the lack of foreknowledge of the molecular nature of a disease, spectral noise and biological variability that is uncorrelated with the disease state. Pattern recognition techniques, both statistical and machine-learning, have been increasingly used in recent years with spectroscopic data to identify markers and classify patients into disease subsets. This review summarizes recent developments, limitations and future prospects in the use of data mining techniques with magnetic resonance spectroscopy, mass spectrometry and optical spectroscopy for the discovery of biomarkers. PMID:11560066

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

    Institute of Scientific and Technical Information of China (English)

    He Qing-Yu; Chiu Jen-Fu

    2004-01-01

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

  15. Role of proteomics in the discovery of autism biomarkers

    International Nuclear Information System (INIS)

    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)

  16. Metabolomics-based discovery of diagnostic biomarkers for onchocerciasis.

    Directory of Open Access Journals (Sweden)

    Judith R Denery

    Full Text Available BACKGROUND: Development of robust, sensitive, and reproducible diagnostic tests for understanding the epidemiology of neglected tropical diseases is an integral aspect of the success of worldwide control and elimination programs. In the treatment of onchocerciasis, clinical diagnostics that can function in an elimination scenario are non-existent and desperately needed. Due to its sensitivity and quantitative reproducibility, liquid chromatography-mass spectrometry (LC-MS based metabolomics is a powerful approach to this problem. METHODOLOGY/PRINCIPAL FINDINGS: Analysis of an African sample set comprised of 73 serum and plasma samples revealed a set of 14 biomarkers that showed excellent discrimination between Onchocerca volvulus-positive and negative individuals by multivariate statistical analysis. Application of this biomarker set to an additional sample set from onchocerciasis endemic areas where long-term ivermectin treatment has been successful revealed that the biomarker set may also distinguish individuals with worms of compromised viability from those with active infection. Machine learning extended the utility of the biomarker set from a complex multivariate analysis to a binary format applicable for adaptation to a field-based diagnostic, validating the use of complex data mining tools applied to infectious disease biomarker discovery and diagnostic development. CONCLUSIONS/SIGNIFICANCE: An LC-MS metabolomics-based diagnostic has the potential to monitor the progression of onchocerciasis in both endemic and non-endemic geographic areas, as well as provide an essential tool to multinational programs in the ongoing fight against this neglected tropical disease. Ultimately this technology can be expanded for the diagnosis of other filarial and/or neglected tropical diseases.

  17. Manifold Learning for Biomarker Discovery in MR Imaging

    Science.gov (United States)

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

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

  18. The Use of Proteomics in Biomarker Discovery in Neurodegenerative Diseases

    Directory of Open Access Journals (Sweden)

    Pia Davidsson

    2005-01-01

    Full Text Available Biomarkers for neurodegenerative diseases should reflect the central pathogenic processes of the diseases. The field of clinical proteomics is especially well suited for discovery of biomarkers in cerebrospinal fluid (CSF, which reflects the proteins in the brain under healthy conditions as well as in several neurodegenerative diseases. Known proteins involved in the pathology of neurodegenerative diseases are, respectively, normal tau protein, β-amyloid (1-42, synaptic proteins, amyloid precursor protein (APP, apolipoprotein E (apoE, which previously have been studied by protein immunoassays. The objective of this paper was to summarize results from proteomic studies of differential protein patterns in neurodegenerative diseases with focus on Alzheimer's disease (AD. Today, discrimination of AD from controls and from other neurological diseases has been improved by simultaneous analysis of both β-amyloid (1-42, total-tau, and phosphorylated tau, where a combination of low levels of CSF-β-amyloid 1-42 and high levels of CSF-tau and CSF-phospho-tau is associated with an AD diagnosis. Detection of new biomarkers will further strengthen diagnosis and provide useful information in drug trials. The combination of immunoassays and proteomic methods show that the CSF proteins express differential protein patterns in AD, FTD, and PD patients, which reflect divergent underlying pathophysiological mechanisms and neuropathological changes in these diseases.

  19. Proteomics and Mass Spectrometry for Cancer Biomarker Discovery

    Directory of Open Access Journals (Sweden)

    Ming Lu

    2007-01-01

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

  20. Mass Spectrometry-Based Biomarker Discovery: Toward a Global Proteome Index of Individuality

    Science.gov (United States)

    Hawkridge, Adam M.; Muddiman, David C.

    2009-07-01

    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.

  1. 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.

  2. Contribution of Automated Technologies to Ion Channel Drug Discovery.

    Science.gov (United States)

    Picones, Arturo; Loza-Huerta, Arlet; Segura-Chama, Pedro; Lara-Figueroa, Cesar O

    2016-01-01

    Automated technologies are now resolving the historical relegation that ion channels have endured as targets for the new drug discovery and development global efforts. The richness and adequacy of functional assay methodologies, remarkably fluorescence-based detection of ions fluxes and patch-clamp electrophysiology recording of ionic currents, are now automated and increasingly employed for the analysis of ion channel activity. While the former is currently the most commonly applied, the latter is finally reaching the throughput capacity to be engaged in the primary screening of chemical libraries conformed by hundreds of thousands of compounds. The use of automated instrumentation for the study of ion channel functionality (and dysfunctionality), particularly in the search for novel pharmacological agents with therapeutic purposes, has now reached out beyond the industrial setting, its original natural enclave, and is making its way into a growing number of academic labs and core facilities. The present chapter reviews the increasing contributions accomplished by a variety of different key automated technologies which have revolutionized the strategies to approach the discovery and development of new drugs targeting ion channels. PMID:27038379

  3. Predictive biomarkers for personalised anti-cancer drug use: discovery to clinical implementation.

    Science.gov (United States)

    Alymani, Nayef A; Smith, Murray D; Williams, David J; Petty, Russell D

    2010-03-01

    A priority translational research objective in cancer medicine is the discovery of novel therapeutic targets for solid tumours. Ideally, co-discovery of predictive biomarkers occurs in parallel to facilitate clinical development of agents and ultimately personalise clinical use. However, the identification of clinically useful predictive biomarkers for solid tumours has proven challenging with many initially promising biomarkers failing to translate into clinically useful applications. In particular, the 'failure' of a predictive biomarker has often only become apparent at a relatively late stage in investigation. Recently, the field has recognised the need to develop a robust clinical biomarker development methodology to facilitate the process. This review discusses the recent progress in this area focusing on the key stages in the biomarker development process: discovery, validation, qualification and implementation. Concentrating on predictive biomarkers for selecting systemic therapies for individual patients in the clinic, the advances and progress in each of these stages in biomarker development are outlined and the key remaining challenges are discussed. Specific examples are discussed to illustrate the challenges identified and how they have been addressed. Overall, we find that significant progress has been made towards a formalised biomarker developmental process. This holds considerable promise for facilitating the translation of predictive biomarkers from discovery to clinical implementation. Further enhancements could eventually be found through alignment with regulatory processes. PMID:20138504

  4. 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

    RNA screens to identify and validate functionally important genomic or transcriptomic predictive biomarkers of individual drug response in patients. PREDICT's approach to predictive biomarker discovery differs from conventional associative learning approaches, which can be susceptible to the detection of...... European network providing the technological and clinical platform for large-scale functional genomic biomarker discovery. Here we review our current understanding of molecular mechanisms driving resistance to anti-angiogenesis agents, the current limitations of laboratory and clinical trial strategies and...... how the PREDICT consortium will endeavour to identify a new generation of predictive biomarkers....

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

    Directory of Open Access Journals (Sweden)

    JoyGuingab-Cagmat

    2013-05-01

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

  6. 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

  7. 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.

  8. Biomarker Discovery in Animal Health and Disease: The Application of Post-Genomic Technologies

    Directory of Open Access Journals (Sweden)

    Rowan E. Moore

    2007-01-01

    Full Text Available The causes of many important diseases in animals are complex and multifactorial, which present unique challenges. Biomarkers indicate the presence or extent of a biological process, which is directly linked to the clinical manifestations and outcome of a particular disease. Identifying biomarkers or biomarker profiles will be an important step towards disease characterization and management of disease in animals. The emergence of post-genomic technologies has led to the development of strategies aimed at identifying specific and sensitive biomarkers from the thousands of molecules present in a tissue or biological fluid. This review will summarize the current developments in biomarker discovery and will focus on the role of transcriptomics, proteomics and metabolomics in biomarker discovery for animal health and disease.

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

    OpenAIRE

    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...

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

    OpenAIRE

    JoyGuingab-Cagmat

    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 thei...

  11. Proteomics of pediatric heart failure: from traditional biomarkers to new discovery strategies.

    Science.gov (United States)

    Xu, Mingguo; Ramirez-Correa, Genaro A; Murphy, Anne M

    2015-08-01

    Heart failure in children is a complex clinical syndrome with multiple aetiologies. The underlying disorders that lead to heart failure in children differ significantly from those in adults. Some clinical biomarkers for heart failure status and prognosis appear to be useful in both age groups. This review outlines the use and the present status of biomarkers for heart failure in paediatric cardiology. Furthermore, clinical scenarios in which development of new biomarkers might address management or prognosis are discussed. Finally, strategies for proteomic discovery of novel biomarkers and application to practice are described. PMID:26377710

  12. Discovery of Novel Biomarkers for Alzheimer's Disease from Blood

    Science.gov (United States)

    Long, Jintao; Pan, Genhua; Ifeachor, Emmanuel; Belshaw, Robert; Li, Xinzhong

    2016-01-01

    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%). PMID:27418712

  13. 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.

  14. Development and evaluation of statistical approaches in proteomic biomarker discovery

    OpenAIRE

    Patel, Amit

    2011-01-01

    A biomarker is a characteristic that is objectively measured and evaluated as an indicator of normal biological processes, pathogenic processes or pharmacological responses to a therapeutic intervention. The aim of this project was to deal with the identification of potential biomarker candidates from experimental data comparing samples displaying divergent physiological traits. Chapter 1 introduces the topic and the aims of the project. The primary aim was to identify the ideal statistical a...

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2016-01-01

    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.

  16. Effect of size and heterogeneity of samples on biomarker discovery: synthetic and real data assessment.

    OpenAIRE

    Barbara Di Camillo; Tiziana Sanavia; Matteo Martini; Giuseppe Jurman; Francesco Sambo; Annalisa Barla; Margherita Squillario; Cesare Furlanello; Gianna Toffolo; Claudio Cobelli

    2012-01-01

    MOTIVATION: The identification of robust lists of molecular biomarkers related to a disease is a fundamental step for early diagnosis and treatment. However, methodologies for the discovery of biomarkers using microarray data often provide results with limited overlap. These differences are imputable to 1) dataset size (few subjects with respect to the number of features); 2) heterogeneity of the disease; 3) heterogeneity of experimental protocols and computational pipelines employed in the a...

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

    OpenAIRE

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

    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,...

  18. Sparse Mbplsr for Metabolomics Data and Biomarker Discovery

    DEFF Research Database (Denmark)

    Karaman, İbrahim

    2014-01-01

    Metabolomics is part of systems biology and a rapidly evolving field. It is a tool to analyze multiple metabolic changes in biofluids and tissues and aims at determining biomarkers in the metabolism. LC-MS (liquid chromatography – mass spectrometry), GC-MS (gas chromatography – mass spectrometry...... conditions tested. Jack-knife PLSR, however, was to some extent improved by modifying the variable selection criterion, and was much less time-consuming to run. Sparse PLSR may therefore be the method of choice when dealing with spectroscopic data, where the level of noise is relatively low, while for...... model for humans. By Sparse MBPLSR, potential biomarkers from LC-MS and NMR data could be detected and the relationships among the measurement variables of both analytical methods could be studied. Detection of potential biomarkers is followed up by an identification process through online metabolite...

  19. Biomarker discovery in systemic sclerosis: state of the art

    Directory of Open Access Journals (Sweden)

    Bonella F

    2015-07-01

    Full Text Available Francesco Bonella,1 Giuseppe Patuzzo,2 Claudio Lunardi2 1Interstitial and Rare Lung Disease Unit, Ruhrlandklinik University Hospital, University of Duisburg-Essen, Essen, Germany; 2Department of Medicine, University of Verona, Verona, Italy Abstract: Systemic sclerosis (SSc is an autoimmune disease characterized by immune dysfunction and by abnormalities of the microvasculature with vascular obliteration, eventually leading to fibrosis of the skin, gastrointestinal tract, lungs, heart, and kidney. The etiology and pathogenesis of SSc remain unclear, despite recent significant progress in the field. Immune activation and microangiopathy are followed by widespread organ fibrosis, leading to organ failure and increased mortality. The production of inflammatory cytokines and growth factors after tissue injury, as well as the presence of circulating autoantibodies, provide a source of biomarkers with potential diagnostic and prognostic applications in the clinical routine. Two principal approaches exist to discover and characterize biomarkers. The proof-of-concept approach verifies the ability of known proteins, generally involved in the pathogenesis, to correlate with disease phenotype and outcome. A proteomic approach does not need prior knowledge of the proteins or of their function, but it requires high-performance and time-consuming techniques. In this review, we highlight the most recent findings in biomarkers used to characterize SSc organ involvement, to stratify the patients, and to assess the response to treatment. Keywords: systemic sclerosis, biomarkers, proteomics, gene expression profiling

  20. Biomarker discovery in asthma and COPD: Application of proteomics techniques in human and mice

    Directory of Open Access Journals (Sweden)

    Steven Haenen

    2014-09-01

    Full Text Available The use of advanced proteomics approaches in the search for biomarkers in chronic lung diseases, such as asthma and COPD, is rather limited. Asthma and COPD are complex disorders, which can be subdivided into several phenotypes. This results in a heterogeneity of differential expressed biological molecules. Furthermore, genetic differences between animals and humans make ‘translation’ of possible biomarkers challenging. Yet, the improved sensitivity and high throughput of proteomic techniques could be an important asset for (new protein biomarker discovery in either human or animal models. We have reviewed the literature that reported the use of different proteomics approaches performed on samples obtained from humans and murine models in asthma and COPD research for the discovery of new biomarkers of diseases, biomarkers of sensitization or for the refinement of treatment. There is an increasing trend in the use of proteomics to explore new biomarkers of asthma or COPD. Although several murine models have been developed to study these lung diseases, and proteomics studies have been performed, ‘translation’ of identified candidate biomarkers into clinical studies is often lacking.

  1. Price Discovery in the U.S. Treasury Market: Automation vs. Intermediation

    OpenAIRE

    Kasing Man; Junbo Wang; Chunchi Wu

    2013-01-01

    This paper examines the contribution to price discovery by electronic and voice-based trading systems in the U.S. Treasury market. Evidence shows that the electronic trading system has more price discovery and that trading automation increases the speed of incorporating information into prices. However, human trading generates significant price discovery, though its volume is low. The relative contribution of a trading system to price discovery depends on liquidity, volatility, volume, trade ...

  2. Immunodiagnosis of tuberculosis: a dynamic view of biomarker discovery

    OpenAIRE

    Kunnath-Velayudhan, S.; Gennaro, M L

    2011-01-01

    Summary: Infection with Mycobacterium tuberculosis causes a variety of clinical conditions ranging from life-long asymptomatic infection to overt disease with increasingly severe tissue damage and a heavy bacillary burden. Immune biomarkers should follow the evolution of infection and disease because the host immune response is at the core of protection against disease and tissue damage in M. tuberculosis infection. Moreover, levels of immune markers are often affected by the antigen load. We...

  3. The clinical impact of recent advances in LC-MS for cancer biomarker discovery and verification.

    Science.gov (United States)

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

    2016-01-01

    Mass spectrometry (MS) -based proteomics has become an indispensable tool with broad applications in systems biology and biomedical research. With recent advances in liquid chromatography (LC) and MS instrumentation, LC-MS is making increasingly significant contributions to clinical applications, especially in the area of cancer biomarker discovery and verification. To overcome challenges associated with analyses of clinical samples (for example, a wide dynamic range of protein concentrations in bodily fluids and the need to perform high throughput and accurate quantification of candidate biomarker proteins), significant efforts have been devoted to improve the overall performance of LC-MS-based clinical proteomics platforms. Reviewed here are the recent advances in LC-MS and its applications in cancer biomarker discovery and quantification, along with the potentials, limitations and future perspectives. PMID:26581546

  4. 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

  5. Statistical considerations of optimal study design for human plasma proteomics and biomarker discovery.

    Science.gov (United States)

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

    2012-04-01

    A mass spectrometry-based plasma biomarker discovery workflow was developed to facilitate biomarker discovery. Plasma from either healthy volunteers or patients with pancreatic cancer was 8-plex iTRAQ labeled, fractionated by 2-dimensional reversed phase chromatography and subjected to MALDI ToF/ToF mass spectrometry. Data were processed using a q-value based statistical approach to maximize protein quantification and identification. Technical (between duplicate samples) and biological variance (between and within individuals) were calculated and power analysis was thereby enabled. An a priori power analysis was carried out using samples from healthy volunteers to define sample sizes required for robust biomarker identification. The result was subsequently validated with a post hoc power analysis using a real clinical setting involving pancreatic cancer patients. This demonstrated that six samples per group (e.g., pre- vs post-treatment) may provide sufficient statistical power for most proteins with changes>2 fold. A reference standard allowed direct comparison of protein expression changes between multiple experiments. Analysis of patient plasma prior to treatment identified 29 proteins with significant changes within individual patient. Changes in Peroxiredoxin II levels were confirmed by Western blot. This q-value based statistical approach in combination with reference standard samples can be applied with confidence in the design and execution of clinical studies for predictive, prognostic, and/or pharmacodynamic biomarker discovery. The power analysis provides information required prior to study initiation. PMID:22338609

  6. New trends in molecular and cellular biomarker discovery for colorectal cancer

    Science.gov (United States)

    Aghagolzadeh, Parisa; Radpour, Ramin

    2016-01-01

    Colorectal cancer (CRC) is the third leading cause of cancer death worldwide, which is consequence of multistep tumorigenesis of several genetic and epigenetic events. Since CRC is mostly asymptomatic until it progresses to advanced stages, the early detection using effective screening approaches, selection of appropriate therapeutic strategies and efficient follow-up programs are essential to reduce CRC mortalities. Biomarker discovery for CRC based on the personalized genotype and clinical information could facilitate the classification of patients with certain types and stages of cancer to tailor preventive and therapeutic approaches. These cancer-related biomarkers should be highly sensitive and specific in a wide range of specimen(s) (including tumor tissues, patients’ fluids or stool). Reliable biomarkers which enable the early detection of CRC, can improve early diagnosis, prognosis, treatment response prediction, and recurrence risk. Advances in our understanding of the natural history of CRC have led to the development of different CRC associated molecular and cellular biomarkers. This review highlights the new trends and approaches in CRC biomarker discovery, which could be potentially used for early diagnosis, development of new therapeutic approaches and follow-up of patients. PMID:27433083

  7. 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

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

    Science.gov (United States)

    Swanton, Charles; Larkin, James M; Gerlinger, Marco; Eklund, Aron C; Howell, Michael; Stamp, Gordon; Downward, Julian; Gore, Martin; Futreal, P Andrew; Escudier, Bernard; Andre, Fabrice; Albiges, Laurence; Beuselinck, Benoit; Oudard, Stephane; Hoffmann, Jens; Gyorffy, Balázs; Torrance, Chris J; Boehme, Karen A; Volkmer, Hansjuergen; Toschi, Luisella; Nicke, Barbara; Beck, Marlene; Szallasi, Zoltan

    2010-01-01

    The European Union multi-disciplinary Personalised RNA interference to Enhance the Delivery of Individualised Cytotoxic and Targeted therapeutics (PREDICT) consortium has recently initiated a framework to accelerate the development of predictive biomarkers of individual patient response to anti-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 inhibitor. Through the analysis of tumor tissue derived from pre-operative renal cell carcinoma (RCC) clinical trials, the PREDICT consortium will use established and novel methods to integrate comprehensive tumor-derived genomic data with personalized tumor-derived small hairpin RNA and high-throughput small interfering RNA screens to identify and validate functionally important genomic or transcriptomic predictive biomarkers of individual drug response in patients. PREDICT's approach to predictive biomarker discovery differs from conventional associative learning approaches, which can be susceptible to the detection of chance associations that lead to overestimation of true clinical accuracy. These methods will identify molecular pathways important for survival and growth of RCC cells and particular targets suitable for therapeutic development. Importantly, our results may enable individualized treatment of RCC, reducing ineffective therapy in drug-resistant disease, leading to improved quality of life and higher cost efficiency, which in turn should broaden patient access to beneficial therapeutics, thereby enhancing clinical outcome and cancer survival. The consortium will also establish and consolidate a European network providing the technological and clinical platform for large-scale functional genomic biomarker discovery. Here we review our current understanding

  9. Proteomics in Cancer Biomarkers Discovery: Challenges and Applications

    Directory of Open Access Journals (Sweden)

    Reem M. Sallam

    2015-01-01

    Full Text Available With the introduction of recent high-throughput technologies to various fields of science and medicine, it is becoming clear that obtaining large amounts of data is no longer a problem in modern research laboratories. However, coherent study designs, optimal conditions for obtaining high-quality data, and compelling interpretation, in accordance with the evidence-based systems biology, are critical factors in ensuring the emergence of good science out of these recent technologies. This review focuses on the proteomics field and its new perspectives on cancer research. Cornerstone publications that have tremendously helped scientists and clinicians to better understand cancer pathogenesis; to discover novel diagnostic and/or prognostic biomarkers; and to suggest novel therapeutic targets will be presented. The author of this review aims at presenting some of the relevant literature data that helped as a step forward in bridging the gap between bench work results and bedside potentials. Undeniably, this review cannot include all the work that is being produced by expert research groups all over the world.

  10. Potential Approaches and Recent Advances in Biomarker Discovery in Clear-Cell Renal Cell Carcinoma

    Science.gov (United States)

    Majer, Weronika; Kluzek, Katarzyna; Bluyssen, Hans; Wesoły, Joanna

    2015-01-01

    The early diagnosis and monitoring of clear-cell Renal Cell Carcinoma (ccRCC), which is the most common renal malignancy, remains challenging. The late diagnosis and lack of tools that can be used to assess the progression of the disease and metastasis significantly influence the chance of survival of ccRCC patients. Molecular biomarkers have been shown to aid the diagnosis and disease monitoring for other cancers, but such markers are not currently available for ccRCC. Recently, plasma and serum circulating nucleic acids, nucleic acids present in urine, and plasma and urine proteins gained interest in the field of cancer biomarker discovery. Here, we describe the applicability of plasma and urine nucleic acids as cancer biomarkers with a particular focus on DNA, small RNA, and protein markers for ccRCC. PMID:26516358

  11. Isolation and Quantification of MicroRNAs from Urinary Exosomes/Microvesicles for Biomarker Discovery

    OpenAIRE

    Lv, Lin-Li; Cao, Yuhan; Liu, Dan; Xu, Min; Liu, Hong; Tang, Ri-Ning; Ma, Kun-Ling; Liu, Bi-Cheng

    2013-01-01

    Recent studies indicate that microRNA (miRNA) is contained within exosome. Here we sought to optimize the methodologies for the isolation and quantification of urinary exosomal microRNA as a prelude to biomarker discovery studies. Exosomes were isolated through ultracentrifugation and characterized by immunoelectron microscopy. To determine the RNA was confined inside exosomes, the pellet was treated with RNase before RNA isolation. The minimum urine volume, storage conditions for exosomes an...

  12. The impact of sample storage time on estimates of association in biomarker discovery studies

    OpenAIRE

    Kugler, Karl G; Hackl, Werner O; Mueller, Laurin AJ; Fiegl, Heidi; Graber, Armin; Ruth M Pfeiffer

    2011-01-01

    Background Using serum, plasma or tumor tissue specimens from biobanks for biomarker discovery studies is attractive as samples are often readily available. However, storage over longer periods of time can alter concentrations of proteins in those specimens. We therefore assessed the bias in estimates of association from case-control studies conducted using banked specimens when maker levels changed over time for single markers and also for multiple correlated markers in simulations. Data fro...

  13. Urinary proteomics as a novel tool for biomarker discovery in kidney diseases*

    OpenAIRE

    Wu, Jing; Chen, Yi-ding; Gu, Wei

    2010-01-01

    Urine has become one of the most attractive biofluids in clinical proteomics, for its procurement is easy and noninvasive and it contains sufficient proteins and peptides. Urinary proteomics has thus rapidly developed and has been extensively applied to biomarker discovery in clinical diseases, especially kidney diseases. In this review, we discuss two important aspects of urinary proteomics in detail, namely, sample preparation and proteomic technologies. In addition, data mining in urinary ...

  14. Two-dimensional SDS-PAGE fractionation of biological samples for biomarker discovery

    OpenAIRE

    Rabilloud, Thierry; Triboulet, Sarah

    2013-01-01

    Two-dimensional electrophoresis is still a very valuable tool in proteomics, due to its reproducibility and its ability to analyze complete proteins. However, due to its sensitivity to dynamic range issues, its most suitable use in the frame of biomarker discovery is not on very complex fluids such as plasma, but rather on more proximal, simpler fluids such as CSF, urine, or secretome samples. Here, we describe the complete workflow for the analysis of such dilute samples by two-dimensional e...

  15. Quantitative proteomics in resected renal cancer tissue for biomarker discovery and profiling

    OpenAIRE

    Atrih, A; Mudaliar, M A V; Zakikhani, P; Lamont, D J; Huang, J T-J; Bray, S.E.; Barton, G.; Fleming, S; Nabi, G.

    2014-01-01

    Background: Proteomics-based approaches for biomarker discovery are promising strategies used in cancer research. We present state-of-art label-free quantitative proteomics method to assess proteome of renal cell carcinoma (RCC) compared with noncancer renal tissues. Methods: Fresh frozen tissue samples from eight primary RCC lesions and autologous adjacent normal renal tissues were obtained from surgically resected tumour-bearing kidneys. Proteins were extracted by complete solubilisation of...

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

    OpenAIRE

    Venugopal Abhilash; Chaerkady Raghothama; Pandey Akhilesh

    2009-01-01

    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, espe...

  17. Mass spectrometry based translational proteomics for biomarker discovery and application in colorectal cancer.

    Science.gov (United States)

    Ma, Hong; Chen, Guilin; Guo, Mingquan

    2016-04-01

    Colorectal cancer (CRC) is a leading cause of cancer-related death in the world. Clinically, early detection of the disease is the most effective approach to tackle this tough challenge. Discovery and development of reliable and effective diagnostic tools for the assessment of prognosis and prediction of response to drug therapy are urgently needed for personalized therapies and better treatment outcomes. Among many ongoing efforts in search for potential CRC biomarkers, MS-based translational proteomics provides a unique opportunity for the discovery and application of protein biomarkers toward better CRC early detection and treatment. This review updates most recent studies that use preclinical models and clinical materials for the identification of CRC-related protein markers. Some new advances in the development of CRC protein markers such as CRC stem cell related protein markers, SRM/MRM-MS and MS cytometry approaches are also discussed in order to address future directions and challenges from bench translational research to bedside clinical application of CRC biomarkers. PMID:26616366

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

    International Nuclear Information System (INIS)

    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).

  19. A Combined Shotgun and Targeted Mass Spectrometry Strategy for Breast Cancer Biomarker Discovery.

    Science.gov (United States)

    Sjöström, Martin; Ossola, Reto; Breslin, Thomas; Rinner, Oliver; Malmström, Lars; Schmidt, Alexander; Aebersold, Ruedi; Malmström, Johan; Niméus, Emma

    2015-07-01

    It is of highest importance to find proteins responsible for breast cancer dissemination, for use as biomarkers or treatment targets. We established and performed a combined nontargeted LC-MS/MS and a targeted LC-SRM workflow for discovery and validation of protein biomarkers. Eighty breast tumors, stratified for estrogen receptor status and development of distant recurrence (DR ± ), were collected. After enrichment of N-glycosylated peptides, label-free LC-MS/MS was performed on each individual tumor in triplicate. In total, 1515 glycopeptides from 778 proteins were identified and used to create a map of the breast cancer N-glycosylated proteome. Based on this specific proteome map, we constructed a 92-plex targeted label-free LC-SRM panel. These proteins were quantified across samples by LC-SRM, resulting in 10 proteins consistently differentially regulated between DR+/DR- tumors. Five proteins were further validated in a separate cohort as prognostic biomarkers at the gene expression level. We also compared the LC-SRM results to clinically reported HER2 status, demonstrating its clinical accuracy. In conclusion, we demonstrate a combined mass spectrometry strategy, at large scale on clinical samples, leading to the identification and validation of five proteins as potential biomarkers for breast cancer recurrence. All MS data are available via ProteomeXchange and PASSEL with identifiers PXD001685 and PASS00643. PMID:25944384

  20. Effect of size and heterogeneity of samples on biomarker discovery: synthetic and real data assessment.

    Directory of Open Access Journals (Sweden)

    Barbara Di Camillo

    Full Text Available MOTIVATION: The identification of robust lists of molecular biomarkers related to a disease is a fundamental step for early diagnosis and treatment. However, methodologies for the discovery of biomarkers using microarray data often provide results with limited overlap. These differences are imputable to 1 dataset size (few subjects with respect to the number of features; 2 heterogeneity of the disease; 3 heterogeneity of experimental protocols and computational pipelines employed in the analysis. In this paper, we focus on the first two issues and assess, both on simulated (through an in silico regulation network model and real clinical datasets, the consistency of candidate biomarkers provided by a number of different methods. METHODS: We extensively simulated the effect of heterogeneity characteristic of complex diseases on different sets of microarray data. Heterogeneity was reproduced by simulating both intrinsic variability of the population and the alteration of regulatory mechanisms. Population variability was simulated by modeling evolution of a pool of subjects; then, a subset of them underwent alterations in regulatory mechanisms so as to mimic the disease state. RESULTS: The simulated data allowed us to outline advantages and drawbacks of different methods across multiple studies and varying number of samples and to evaluate precision of feature selection on a benchmark with known biomarkers. Although comparable classification accuracy was reached by different methods, the use of external cross-validation loops is helpful in finding features with a higher degree of precision and stability. Application to real data confirmed these results.

  1. Automating Discovery and Classification of Transients and Variable Stars in the Synoptic Survey Era

    CERN Document Server

    Bloom, J S; Nugent, P E; Quimby, R M; Kasliwal, M M; Starr, D L; Poznanski, D; Ofek, E O; Cenko, S B; Butler, N R; Kulkarni, S R; Gal-Yam, A; Law, N

    2011-01-01

    The rate of image acquisition in modern synoptic imaging surveys has already begun to outpace the feasibility of keeping astronomers in the real-time discovery and classification loop. Here we present the inner workings of a framework, based on machine-learning algorithms, that captures expert training and ground-truth knowledge about the variable and transient sky to automate 1) the process of discovery on image differences and, 2) the generation of preliminary science-type classifications of discovered sources. Since follow-up resources for extracting novel science from fast-changing transients are precious, self-calibrating classification probabilities must be couched in terms of efficiencies for discovery and purity of the samples generated. We estimate the purity and efficiency in identifying real sources with a two-epoch image-difference discovery algorithm for the Palomar Transient Factory (PTF) survey. Once given a source discovery, using machine-learned classification trained on PTF data, we distingu...

  2. 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.

  3. Automated assessment of bilateral breast volume asymmetry as a breast cancer biomarker during mammographic screening

    Science.gov (United States)

    Williams, Alex C.; Hitt, Austin; Voisin, Sophie; Tourassi, Georgia

    2013-03-01

    The biological concept of bilateral symmetry as a marker of developmental stability and good health is well established. Although most individuals deviate slightly from perfect symmetry, humans are essentially considered bilaterally symmetrical. Consequently, increased fluctuating asymmetry of paired structures could be an indicator of disease. There are several published studies linking bilateral breast size asymmetry with increased breast cancer risk. These studies were based on radiologists' manual measurements of breast size from mammographic images. We aim to develop a computerized technique to assess fluctuating breast volume asymmetry in screening mammograms and investigate whether it correlates with the presence of breast cancer. Using a large database of screening mammograms with known ground truth we applied automated breast region segmentation and automated breast size measurements in CC and MLO views using three well established methods. All three methods confirmed that indeed patients with breast cancer have statistically significantly higher fluctuating asymmetry of their breast volumes. However, statistically significant difference between patients with cancer and benign lesions was observed only for the MLO views. The study suggests that automated assessment of global bilateral asymmetry could serve as a breast cancer risk biomarker for women undergoing mammographic screening. Such biomarker could be used to alert radiologists or computer-assisted detection (CAD) systems to exercise increased vigilance if higher than normal cancer risk is suspected.

  4. Transcriptional responses to radiation exposure facilitate the discovery of biomarkers functioning as radiation biodosimeters

    International Nuclear Information System (INIS)

    The development of new methods for a retrospective quantification of the radiation dose of exposed individuals is of widespread interest. To this end, I developed a computational framework for biomarker discovery and radiation dose prediction and successfully identified gene signatures with which low and medium to high radiation doses can be accurately quantified. To enhance our understanding of the radiation-induced transcriptional response, I additionally analyzed microarray data of human PBLs after ex vivo gamma-irradiation and characterized affected functional processes and pathways.

  5. Transcriptional responses to radiation exposure facilitate the discovery of biomarkers functioning as radiation biodosimeters

    Energy Technology Data Exchange (ETDEWEB)

    Strunz, Sonja

    2014-05-13

    The development of new methods for a retrospective quantification of the radiation dose of exposed individuals is of widespread interest. To this end, I developed a computational framework for biomarker discovery and radiation dose prediction and successfully identified gene signatures with which low and medium to high radiation doses can be accurately quantified. To enhance our understanding of the radiation-induced transcriptional response, I additionally analyzed microarray data of human PBLs after ex vivo gamma-irradiation and characterized affected functional processes and pathways.

  6. Inside back cover: Biomarker discovery in mass spectrometry-based urinary proteomics.

    Science.gov (United States)

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

    2016-04-01

    DOI: 10.1002/prca.201500102 Urine is among the most valuable sample materials for studies of human diseases. These urine solutes are shown with increasing approximate diameter from metabolite at 1 nm to protein at 5 nm to a group of exosomes at 100 nm each to a cell at 10 000 nm. This article highlights promising technologies and strategies in the mass spectrometry-based urine proteomics and its application to disease biomarker discovery. Further details can be found in the article by Samuel Thomas et al. on page 358. PMID:27061328

  7. Flexible End2End Workflow Automation of Hit-Discovery Research.

    Science.gov (United States)

    Holzmüller-Laue, Silke; Göde, Bernd; Thurow, Kerstin

    2014-08-01

    The article considers a new approach of more complex laboratory automation at the workflow layer. The authors purpose the automation of end2end workflows. The combination of all relevant subprocesses-whether automated or manually performed, independently, and in which organizational unit-results in end2end processes that include all result dependencies. The end2end approach focuses on not only the classical experiments in synthesis or screening, but also on auxiliary processes such as the production and storage of chemicals, cell culturing, and maintenance as well as preparatory activities and analyses of experiments. Furthermore, the connection of control flow and data flow in the same process model leads to reducing of effort of the data transfer between the involved systems, including the necessary data transformations. This end2end laboratory automation can be realized effectively with the modern methods of business process management (BPM). This approach is based on a new standardization of the process-modeling notation Business Process Model and Notation 2.0. In drug discovery, several scientific disciplines act together with manifold modern methods, technologies, and a wide range of automated instruments for the discovery and design of target-based drugs. The article discusses the novel BPM-based automation concept with an implemented example of a high-throughput screening of previously synthesized compound libraries. PMID:24464814

  8. Towards Extending Service Discovery with Automated Composition Capabilities

    Czech Academy of Sciences Publication Activity Database

    Vaculín, Roman; Neruda, Roman; Sycara, K.

    Los Alamitos: IEEE Computer Society Press, 2008, s. 3-12. ISBN 978-0-7695-3399-5. [ECOWS'08. The IEEE European Conference on Web Services /6./. Dublin (IE), 12.11.2008-14.11.2008] R&D Projects: GA MŠk ME08095; GA ČR(CZ) GD201/05/H014 Institutional research plan: CEZ:AV0Z10300504 Keywords : web services discovery * web services composition * semantic web services * OWL-S Subject RIV: IN - Informatics, Computer Science

  9. 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.

  10. ProfileDB: a resource for proteomics and cross-omics biomarker discovery.

    Science.gov (United States)

    Bauer, Chris; Glintschert, Alexander; Schuchhardt, Johannes

    2014-05-01

    The increasing size and complexity of high-throughput datasets pose a growing challenge for researchers. Often very different (cross-omics) techniques with individual data analysis pipelines are employed making a unified biomarker discovery strategy and a direct comparison of different experiments difficult and time consuming. Here we present the comprehensive web-based application ProfileDB. The application is designed to integrate data from different high-throughput 'omics' data types (Transcriptomics, Proteomics, Metabolomics) with clinical parameters and prior knowledge on pathways and ontologies. Beyond data storage, ProfileDB provides a set of dedicated tools for study inspection and data visualization. The user can gain insights into a complex experiment with just a few mouse clicks. We will demonstrate the application by presenting typical use cases for the identification of proteomics biomarkers. All presented analyses can be reproduced using the public ProfileDB web server. The ProfileDB application is available by standard browser (Firefox 18+, Internet Explorer Version 9+) technology via http://profileDB.-microdiscovery.de/ (login and pass-word: profileDB). The installation contains several public datasets including different cross-'omics' experiments. This article is part of a Special Issue entitled: Biomarkers: A Proteomic Challenge. PMID:24270047

  11. 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.

  12. Clinical proteomics for liver disease: a promising approach for discovery of novel biomarkers

    Directory of Open Access Journals (Sweden)

    Tsubouchi Hirohito

    2010-12-01

    Full Text Available Abstract Hepatocellular carcinoma (HCC is the fifth most common cancer and advanced hepatic fibrosis is a major risk factor for HCC. Hepatic fibrosis including liver cirrhosis and HCC are mainly induced by persistent hepatitis B or C virus infection, with approximately 500 million people infected with hepatitis B or C virus worldwide. Furthermore, the number of patients with non-alcoholic fatty liver disease (NAFLD has recently increased and NAFLD can progress to cirrhosis and HCC. These chronic liver diseases are major causes of morbidity and mortality, and the identification of non-invasive biomarkers is important for early diagnosis. Recent advancements in quantitative and large-scale proteomic methods could be used to optimize the clinical application of biomarkers. Early diagnosis of HCC and assessment of the stage of hepatic fibrosis or NAFLD can also contribute to more effective therapeutic interventions and an improve prognosis. Furthermore, advancements of proteomic techniques contribute not only to the discovery of clinically useful biomarkers, but also in clarifying the molecular mechanisms of disease pathogenesis by using body fluids, such as serum, and tissue samples and cultured cells. In this review, we report recent advances in quantitative proteomics and several findings focused on liver diseases, including HCC, NAFLD, hepatic fibrosis and hepatitis B or C virus infections.

  13. Proteomic-driven biomarker discovery in gestational diabetes mellitus: a review.

    Science.gov (United States)

    Singh, Apoorva; Subramani, Elavarasan; Datta Ray, Chaitali; Rapole, Srikanth; Chaudhury, Koel

    2015-09-01

    Gestational diabetes mellitus (GDM) is defined as any degree of glucose intolerance with onset or first recognition during pregnancy and it affects 18% of pregnant women worldwide. GDM is considered a high-risk state which may lead to type II diabetes which is associated with an increase in a number of interrelated adverse perinatal outcomes. Given the fact that the progress of a successful pregnancy is dependent on the intricate communication between several biological molecules, identification of the proteomic profile perturbations in women with GDM is expected to help in understanding the disease pathogenesis and also discovery of clinical biomarker(s). In recent years, both gel-free and gel-based proteomics have been extensively investigated for improving maternal and child health. Although there are several reports integrating various aspects of proteomics in pregnancy related diseases such as preeclampsia, extensive Pubmed search shows no review so far on the application of proteomics in gestational diabetes. In this review, we focus on various high-throughput proteomic technologies for the identification of unique biosignatures and biomarkers responsible for the early prediction of GDM. Further, different analytical strategies and biological samples involved in proteomic analysis of this pregnancy-related disease are discussed.This article is part of a Special Issue entitled: Proteomics in India. PMID:26216595

  14. Recent patents and advances in genomic biomarker discovery for colorectal cancers.

    Science.gov (United States)

    Quyun, Chen; Ye, Zhiyun; Lin, Sheng-Cai; Lin, Biaoyang

    2010-06-01

    Colorectal cancer (CRC) is the third most common cancer in the world. Early diagnosis of colorectal cancer is the key to reducing the death rate of CRC patients. Predicting the response to current therapeutic modalities of CRC will also have a great impact on patient care. This review summarizes recent advances and patents in biomarker discovery in CRC under five major categories; including genomic changes, expression changes, mutations, epigenetic changes and microRNAs. The interesting patents include: 1) a patent for a method to differentiate normal exfoliated cells from cancer cells based on whether they were subjected to apoptosis and DNA degradation; 2) A model (PM-33 multiple molecular marker model) based on expression changes of up-regulation of the MDM2, DUSP6, and NFl genes down-regulation of the RNF4, MMD and EIF2S3 genes, which achieved an 88% sensitivity, and an 82% specificity for CRC diagnosis; 3) gene mutations in PTEN, KRAS, PIK3CA for predicting the response to anti-EGFR therapies, a common drug used for CRC treatment; 4) patents on epigenetic changes of ITGA4, SEPT9, ALX4, TFAP2E FOXL2, SARM1, ID4 etc. and many key miRNAs. Finally, future directions in the fields were commented on or suggested, including the combination of multiple categories of biomarkers and pathway central or network-based biomarker panels. PMID:20426761

  15. 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).

  16. Semi-automated knowledge discovery: identifying and profiling human trafficking

    Science.gov (United States)

    Poelmans, Jonas; Elzinga, Paul; Ignatov, Dmitry I.; Kuznetsov, Sergei O.

    2012-11-01

    We propose an iterative and human-centred knowledge discovery methodology based on formal concept analysis. The proposed approach recognizes the important role of the domain expert in mining real-world enterprise applications and makes use of specific domain knowledge, including human intelligence and domain-specific constraints. Our approach was empirically validated at the Amsterdam-Amstelland police to identify suspects and victims of human trafficking in 266,157 suspicious activity reports. Based on guidelines of the Attorney Generals of the Netherlands, we first defined multiple early warning indicators that were used to index the police reports. Using concept lattices, we revealed numerous unknown human trafficking and loverboy suspects. In-depth investigation by the police resulted in a confirmation of their involvement in illegal activities resulting in actual arrestments been made. Our human-centred approach was embedded into operational policing practice and is now successfully used on a daily basis to cope with the vastly growing amount of unstructured information.

  17. Automated discovery of functional generality of human gene expression programs.

    Directory of Open Access Journals (Sweden)

    Georg K Gerber

    2007-08-01

    Full Text Available An important research problem in computational biology is the identification of expression programs, sets of co-expressed genes orchestrating normal or pathological processes, and the characterization of the functional breadth of these programs. The use of human expression data compendia for discovery of such programs presents several challenges including cellular inhomogeneity within samples, genetic and environmental variation across samples, uncertainty in the numbers of programs and sample populations, and temporal behavior. We developed GeneProgram, a new unsupervised computational framework based on Hierarchical Dirichlet Processes that addresses each of the above challenges. GeneProgram uses expression data to simultaneously organize tissues into groups and genes into overlapping programs with consistent temporal behavior, to produce maps of expression programs, which are sorted by generality scores that exploit the automatically learned groupings. Using synthetic and real gene expression data, we showed that GeneProgram outperformed several popular expression analysis methods. We applied GeneProgram to a compendium of 62 short time-series gene expression datasets exploring the responses of human cells to infectious agents and immune-modulating molecules. GeneProgram produced a map of 104 expression programs, a substantial number of which were significantly enriched for genes involved in key signaling pathways and/or bound by NF-kappaB transcription factors in genome-wide experiments. Further, GeneProgram discovered expression programs that appear to implicate surprising signaling pathways or receptor types in the response to infection, including Wnt signaling and neurotransmitter receptors. We believe the discovered map of expression programs involved in the response to infection will be useful for guiding future biological experiments; genes from programs with low generality scores might serve as new drug targets that exhibit minimal

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

    International Nuclear Information System (INIS)

    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

  19. A highly automated assay for determining the aqueous equilibrium solubility of drug discovery compounds.

    Science.gov (United States)

    Wenlock, Mark C; Austin, Rupert P; Potter, Tim; Barton, Patrick

    2011-08-01

    Aqueous solubility is an important physicochemical parameter for any potential drug candidate, and high-throughput kinetic assays are frequently used in drug discovery to give an estimate of a compound's aqueous solubility. However, the aqueous solubility data from an equilibrium (thermodynamic) shake-flask technique is considered more relevant, but is slower and more labor intensive to generate. A highly automated aqueous equilibrium solubility shake-flask technique is described and validated on a set of 15 marketed drugs, whose aqueous solubilities cover four orders of magnitude. The assay uses a Tecan Freedom Evo 200 liquid handling robot (Tecan Group Ltd., Männerdorf, Switzerland) with integrated appliances for the transportation, decapping and recapping, and centrifugation of sample tubes. These bespoke automation solutions help overcome the labor intensive steps associated with performing conventional, gold standard, aqueous equilibrium solubility shake-flask measurements, enabling the assay to be used as a primary-wave drug discovery screen. PMID:21764023

  20. Automated Discovery of Elementary Chemical Reaction Steps Using Freezing String and Berny Optimization Methods

    OpenAIRE

    Suleimanov, Yury V.; Green, William H.

    2015-01-01

    We present a simple protocol which allows fully automated discovery of elementary chemical reaction steps using in cooperation single- and double-ended transition-state optimization algorithms - the freezing string and Berny optimization methods, respectively. To demonstrate the utility of the proposed approach, the reactivity of several systems of combustion and atmospheric chemistry importance is investigated. The proposed algorithm allowed us to detect without any human intervention not on...

  1. 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

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

    Directory of Open Access Journals (Sweden)

    Robert M Littleton

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

  3. Automated recognition of cell phenotypes in histology images based on membrane- and nuclei-targeting biomarkers

    International Nuclear Information System (INIS)

    Three-dimensional in vitro culture of cancer cells are used to predict the effects of prospective anti-cancer drugs in vivo. In this study, we present an automated image analysis protocol for detailed morphological protein marker profiling of tumoroid cross section images. Histologic cross sections of breast tumoroids developed in co-culture suspensions of breast cancer cell lines, stained for E-cadherin and progesterone receptor, were digitized and pixels in these images were classified into five categories using k-means clustering. Automated segmentation was used to identify image regions composed of cells expressing a given biomarker. Synthesized images were created to check the accuracy of the image processing system. Accuracy of automated segmentation was over 95% in identifying regions of interest in synthesized images. Image analysis of adjacent histology slides stained, respectively, for Ecad and PR, accurately predicted regions of different cell phenotypes. Image analysis of tumoroid cross sections from different tumoroids obtained under the same co-culture conditions indicated the variation of cellular composition from one tumoroid to another. Variations in the compositions of cross sections obtained from the same tumoroid were established by parallel analysis of Ecad and PR-stained cross section images. Proposed image analysis methods offer standardized high throughput profiling of molecular anatomy of tumoroids based on both membrane and nuclei markers that is suitable to rapid large scale investigations of anti-cancer compounds for drug development

  4. Isolation and quantification of microRNAs from urinary exosomes/microvesicles for biomarker discovery.

    Science.gov (United States)

    Lv, Lin-Li; Cao, Yuhan; Liu, Dan; Xu, Min; Liu, Hong; Tang, Ri-Ning; Ma, Kun-Ling; Liu, Bi-Cheng

    2013-01-01

    Recent studies indicate that microRNA (miRNA) is contained within exosome. Here we sought to optimize the methodologies for the isolation and quantification of urinary exosomal microRNA as a prelude to biomarker discovery studies. Exosomes were isolated through ultracentrifugation and characterized by immunoelectron microscopy. To determine the RNA was confined inside exosomes, the pellet was treated with RNase before RNA isolation. The minimum urine volume, storage conditions for exosomes and exosomal miRNA was evaluated. The presence of miRNAs in patients with various kidney diseases was validated with real-time PCR. The result shows that miRNAs extracted from the exosomal fraction were resistant to RNase digestion and with high quality confirmed by agarose electrophoresis. 16 ml of urine was sufficient for miRNA isolation by absolute quantification with 4.15×10(5) copies/ul for miR-200c. Exosomes was stable at 4℃ 24h for shipping before stored at -80℃ and was stable in urine when stored at -80°C for 12 months. Exosomal miRNA was detectable despite 5 repeat freeze-thaw cycles. The detection of miRNA by quantitative PCR showed high reproducibility (>94% for intra-assay and >76% for inter-assay), high sensitivity (positive call 100% for CKD patients), broad dynamic range (8-log wide) and good linearity for quantification (R(2)>0.99). miR-29c and miR-200c showed different expression in different types of kidney disease. In summary, the presence of urinary exosomal miRNA was confirmed for patients with a diversity of chronic kidney disease. The conditions of urine collection, storage and miRNA detection determined in this study may be useful for future biomarker discovery efforts. PMID:24250247

  5. Prostate cancer serum biomarker discovery through proteomic analysis of alpha-2 macroglobulin protein complexes

    Science.gov (United States)

    Burgess, Earle F.; Ham, Amy-Joan L.; Tabb, David L.; Billheimer, Dean; Roth, Bruce J.; Chang, Sam S.; Cookson, Michael S.; Hinton, Timothy J.; Cheek, Kristin L.; Hill, Salisha; Pietenpol, Jennifer A.

    2010-01-01

    Alpha-2 macroglobulin (A2M) functions as a universal protease inhibitor in serum and is capable of binding various cytokines and growth factors. In this study, we investigated if immunoaffinity enrichment and proteomic analysis of A2M protein complexes from human serum could improve detection of biologically relevant and novel candidate protein biomarkers in prostate cancer. Serum samples from six patients with androgen-independent, metastatic prostate cancer and six control patients without malignancy were analyzed by immunoaffinity enrichment of A2M protein complexes and MS identification of associated proteins. Known A2M substrates were reproducibly identified from patient serum in both cohorts, as well as proteins previously undetected in human serum. One example is heat shock protein 90 alpha (HSP90α), which was identified only in the serum of cancer patients in this study. Using an ELISA, the presence of HSP90α in human serum was validated on expanded test cohorts and found to exist in higher median serum concentrations in prostate cancer (n = 18) relative to control (n = 13) patients (median concentrations 50.7 versus 27.6 ng/mL, respectively, p = 0.001). Our results demonstrate the technical feasibility of this approach and support the analysis of A2M protein complexes for proteomic-based serum biomarker discovery. PMID:20107526

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

    Directory of Open Access Journals (Sweden)

    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.

  7. 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...

  8. Early identification of hERG liability in drug discovery programs by automated patch clamp

    Directory of Open Access Journals (Sweden)

    Timm eDanker

    2014-09-01

    Full Text Available Blockade of the cardiac ion channel coded by hERG can lead to cardiac arrhythmia, which has become a major concern in drug discovery and development. Automated electrophysiological patch clamp allows assessment of hERG channel effects early in drug development to aid medicinal chemistry programs and has become routine in pharmaceutical companies. However, a number of potential sources of errors in setting up hERG channel assays by automated patch clamp can lead to misinterpretation of data or false effects being reported. This article describes protocols for automated electrophysiology screening of compound effects on the hERG channel current. Protocol details and the translation of criteria known from manual patch clamp experiments to automated patch clamp experiments to achieve good quality data are emphasized. Typical pitfalls and artifacts that may lead to misinterpretation of data are discussed. While this article focuses on hERG channel recordings using the QPatch (Sophion A/S, Copenhagen, Denmark technology, many of the assay and protocol details given in this article can be transferred for setting up different ion channel assays by automated patch clamp and are similar on other planar patch clamp platforms.

  9. Feature Selection Methods for Early Predictive Biomarker Discovery Using Untargeted Metabolomic Data.

    Science.gov (United States)

    Grissa, Dhouha; Pétéra, Mélanie; Brandolini, Marion; Napoli, Amedeo; Comte, Blandine; Pujos-Guillot, Estelle

    2016-01-01

    Untargeted metabolomics is a powerful phenotyping tool for better understanding biological mechanisms involved in human pathology development and identifying early predictive biomarkers. This approach, based on multiple analytical platforms, such as mass spectrometry (MS), chemometrics and bioinformatics, generates massive and complex data that need appropriate analyses to extract the biologically meaningful information. Despite various tools available, it is still a challenge to handle such large and noisy datasets with limited number of individuals without risking overfitting. Moreover, when the objective is focused on the identification of early predictive markers of clinical outcome, few years before occurrence, it becomes essential to use the appropriate algorithms and workflow to be able to discover subtle effects among this large amount of data. In this context, this work consists in studying a workflow describing the general feature selection process, using knowledge discovery and data mining methodologies to propose advanced solutions for predictive biomarker discovery. The strategy was focused on evaluating a combination of numeric-symbolic approaches for feature selection with the objective of obtaining the best combination of metabolites producing an effective and accurate predictive model. Relying first on numerical approaches, and especially on machine learning methods (SVM-RFE, RF, RF-RFE) and on univariate statistical analyses (ANOVA), a comparative study was performed on an original metabolomic dataset and reduced subsets. As resampling method, LOOCV was applied to minimize the risk of overfitting. The best k-features obtained with different scores of importance from the combination of these different approaches were compared and allowed determining the variable stabilities using Formal Concept Analysis. The results revealed the interest of RF-Gini combined with ANOVA for feature selection as these two complementary methods allowed selecting the 48

  10. Automation of a phospho-STAT5 staining procedure for flow cytometry for application in drug discovery

    NARCIS (Netherlands)

    Malergue, Fabrice; van Agthoven, Andreas; Scifo, Caroline; Egan, Dave; Strous, Ger J

    2015-01-01

    Drug discovery often requires the screening of compound libraries on tissue cultured cells. Some major targets in drug discovery belong to signal transduction pathways, and PerFix EXPOSE* allows easy flow cytometry phospho assays. We thus investigated the possibility to further simplify and automate

  11. The path forward to biomarker discovery in psoriatic disease: a report from the GRAPPA 2010 annual meeting.

    Science.gov (United States)

    Gladman, Dafna D; Ritchlin, Christopher T; Fitzgerald, Oliver

    2012-02-01

    At the 2010 annual meeting of the Group for Research and Assessment of Psoriasis and Psoriatic Arthritis (GRAPPA), wide-ranging discussions were held regarding biomarker research in psoriatic disease. Consensus was reached on 2 areas of priority: (1) the study of soluble biomarkers of radiographic progression in psoriatic arthritis (PsA); and (2) the analysis of comorbidity biomarkers, specifically cardiovascular and articular, in a psoriasis inception cohort. For each of these areas, rigorous definition of the clinical phenotype of PsA will be essential. To date, 2 instruments have been identified to define the phenotype: the ClASsification of Psoriatic ARthritis criteria and various screening questionnaires. In this overview, we discuss the challenges of the clinical phenotype of PsA and review GRAPPA plans for developing a research program for biomarker discovery. PMID:22298275

  12. AutoDrug: fully automated macromolecular crystallography workflows for fragment-based drug discovery

    International Nuclear Information System (INIS)

    New software has been developed for automating the experimental and data-processing stages of fragment-based drug discovery at a macromolecular crystallography beamline. A new workflow-automation framework orchestrates beamline-control and data-analysis software while organizing results from multiple samples. AutoDrug is software based upon the scientific workflow paradigm that integrates the Stanford Synchrotron Radiation Lightsource macromolecular crystallography beamlines and third-party processing software to automate the crystallography steps of the fragment-based drug-discovery process. AutoDrug screens a cassette of fragment-soaked crystals, selects crystals for data collection based on screening results and user-specified criteria and determines optimal data-collection strategies. It then collects and processes diffraction data, performs molecular replacement using provided models and detects electron density that is likely to arise from bound fragments. All processes are fully automated, i.e. are performed without user interaction or supervision. Samples can be screened in groups corresponding to particular proteins, crystal forms and/or soaking conditions. A single AutoDrug run is only limited by the capacity of the sample-storage dewar at the beamline: currently 288 samples. AutoDrug was developed in conjunction with RestFlow, a new scientific workflow-automation framework. RestFlow simplifies the design of AutoDrug by managing the flow of data and the organization of results and by orchestrating the execution of computational pipeline steps. It also simplifies the execution and interaction of third-party programs and the beamline-control system. Modeling AutoDrug as a scientific workflow enables multiple variants that meet the requirements of different user groups to be developed and supported. A workflow tailored to mimic the crystallography stages comprising the drug-discovery pipeline of CoCrystal Discovery Inc. has been deployed and successfully

  13. AutoDrug: fully automated macromolecular crystallography workflows for fragment-based drug discovery

    Energy Technology Data Exchange (ETDEWEB)

    Tsai, Yingssu [Stanford University, 2575 Sand Hill Road, Menlo Park, CA 94025 (United States); Stanford University, 333 Campus Drive, Mudd Building, Stanford, CA 94305-5080 (United States); McPhillips, Scott E.; González, Ana; McPhillips, Timothy M. [Stanford University, 2575 Sand Hill Road, Menlo Park, CA 94025 (United States); Zinn, Daniel [LogicBlox Inc., 1349 West Peachtree Street NW, Atlanta, GA 30309 (United States); Cohen, Aina E. [Stanford University, 2575 Sand Hill Road, Menlo Park, CA 94025 (United States); Feese, Michael D.; Bushnell, David [Cocrystal Discovery Inc., 19805 North Creek Parkway, Bothell, WA 98011 (United States); Tiefenbrunn, Theresa; Stout, C. David [The Scripps Research Institute, 10550 North Torrey Pines Road, La Jolla, CA 92037 (United States); Ludaescher, Bertram [University of California, One Shields Avenue, Davis, CA 95616 (United States); Hedman, Britt; Hodgson, Keith O. [Stanford University, 2575 Sand Hill Road, Menlo Park, CA 94025 (United States); Stanford University, 333 Campus Drive, Mudd Building, Stanford, CA 94305-5080 (United States); Soltis, S. Michael, E-mail: soltis@slac.stanford.edu [Stanford University, 2575 Sand Hill Road, Menlo Park, CA 94025 (United States)

    2013-05-01

    New software has been developed for automating the experimental and data-processing stages of fragment-based drug discovery at a macromolecular crystallography beamline. A new workflow-automation framework orchestrates beamline-control and data-analysis software while organizing results from multiple samples. AutoDrug is software based upon the scientific workflow paradigm that integrates the Stanford Synchrotron Radiation Lightsource macromolecular crystallography beamlines and third-party processing software to automate the crystallography steps of the fragment-based drug-discovery process. AutoDrug screens a cassette of fragment-soaked crystals, selects crystals for data collection based on screening results and user-specified criteria and determines optimal data-collection strategies. It then collects and processes diffraction data, performs molecular replacement using provided models and detects electron density that is likely to arise from bound fragments. All processes are fully automated, i.e. are performed without user interaction or supervision. Samples can be screened in groups corresponding to particular proteins, crystal forms and/or soaking conditions. A single AutoDrug run is only limited by the capacity of the sample-storage dewar at the beamline: currently 288 samples. AutoDrug was developed in conjunction with RestFlow, a new scientific workflow-automation framework. RestFlow simplifies the design of AutoDrug by managing the flow of data and the organization of results and by orchestrating the execution of computational pipeline steps. It also simplifies the execution and interaction of third-party programs and the beamline-control system. Modeling AutoDrug as a scientific workflow enables multiple variants that meet the requirements of different user groups to be developed and supported. A workflow tailored to mimic the crystallography stages comprising the drug-discovery pipeline of CoCrystal Discovery Inc. has been deployed and successfully

  14. Automated Discovery and Modeling of Sequential Patterns Preceding Events of Interest

    Science.gov (United States)

    Rohloff, Kurt

    2010-01-01

    The integration of emerging data manipulation technologies has enabled a paradigm shift in practitioners' abilities to understand and anticipate events of interest in complex systems. Example events of interest include outbreaks of socio-political violence in nation-states. Rather than relying on human-centric modeling efforts that are limited by the availability of SMEs, automated data processing technologies has enabled the development of innovative automated complex system modeling and predictive analysis technologies. We introduce one such emerging modeling technology - the sequential pattern methodology. We have applied the sequential pattern methodology to automatically identify patterns of observed behavior that precede outbreaks of socio-political violence such as riots, rebellions and coups in nation-states. The sequential pattern methodology is a groundbreaking approach to automated complex system model discovery because it generates easily interpretable patterns based on direct observations of sampled factor data for a deeper understanding of societal behaviors that is tolerant of observation noise and missing data. The discovered patterns are simple to interpret and mimic human's identifications of observed trends in temporal data. Discovered patterns also provide an automated forecasting ability: we discuss an example of using discovered patterns coupled with a rich data environment to forecast various types of socio-political violence in nation-states.

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

    Directory of Open Access Journals (Sweden)

    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.

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

    Directory of Open Access Journals (Sweden)

    Garner Harold R

    2009-05-01

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

  17. Automated Discovery of Elementary Chemical Reaction Steps Using Freezing String and Berny Optimization Methods

    CERN Document Server

    Suleimanov, Yury V

    2015-01-01

    We present a simple protocol which allows fully automated discovery of elementary chemical reaction steps using in cooperation single- and double-ended transition-state optimization algorithms - the freezing string and Berny optimization methods, respectively. To demonstrate the utility of the proposed approach, the reactivity of several systems of combustion and atmospheric chemistry importance is investigated. The proposed algorithm allowed us to detect without any human intervention not only "known" reaction pathways, manually detected in the previous studies, but also new, previously "unknown", reaction pathways which involve significant atom rearrangements. We believe that applying such a systematic approach to elementary reaction path finding will greatly accelerate the possibility of discovery of new chemistry and will lead to more accurate computer simulations of various chemical processes.

  18. Automated Discovery of Elementary Chemical Reaction Steps Using Freezing String and Berny Optimization Methods.

    Science.gov (United States)

    Suleimanov, Yury V; Green, William H

    2015-09-01

    We present a simple protocol which allows fully automated discovery of elementary chemical reaction steps using in cooperation double- and single-ended transition-state optimization algorithms--the freezing string and Berny optimization methods, respectively. To demonstrate the utility of the proposed approach, the reactivity of several single-molecule systems of combustion and atmospheric chemistry importance is investigated. The proposed algorithm allowed us to detect without any human intervention not only "known" reaction pathways, manually detected in the previous studies, but also new, previously "unknown", reaction pathways which involve significant atom rearrangements. We believe that applying such a systematic approach to elementary reaction path finding will greatly accelerate the discovery of new chemistry and will lead to more accurate computer simulations of various chemical processes. PMID:26575920

  19. 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

  20. MetaBoot: a machine learning framework of taxonomical biomarker discovery for different microbial communities based on metagenomic data.

    Science.gov (United States)

    Wang, Xiaojun; Su, Xiaoquan; Cui, Xinping; Ning, Kang

    2015-01-01

    As more than 90% of species in a microbial community could not be isolated and cultivated, the metagenomic methods have become one of the most important methods to analyze microbial community as a whole. With the fast accumulation of metagenomic samples and the advance of next-generation sequencing techniques, it is now possible to qualitatively and quantitatively assess all taxa (features) in a microbial community. A set of taxa with presence/absence or their different abundances could potentially be used as taxonomical biomarkers for identification of the corresponding microbial community's phenotype. Though there exist some bioinformatics methods for metagenomic biomarker discovery, current methods are not robust, accurate and fast enough at selection of non-redundant biomarkers for prediction of microbial community's phenotype. In this study, we have proposed a novel method, MetaBoot, that combines the techniques of mRMR (minimal redundancy maximal relevance) and bootstrapping, for discover of non-redundant biomarkers for microbial communities through mining of metagenomic data. MetaBoot has been tested and compared with other methods on well-designed simulated datasets considering normal and gamma distribution as well as publicly available metagenomic datasets. Results have shown that MetaBoot was robust across datasets of varied complexity and taxonomical distribution patterns and could also select discriminative biomarkers with quite high accuracy and biological consistency. Thus, MetaBoot is suitable for robustly and accurately discover taxonomical biomarkers for different microbial communities. PMID:26213658

  1. Including network knowledge into Cox regression models for biomarker signature discovery.

    Science.gov (United States)

    Fröhlich, Holger

    2014-03-01

    Discovery of prognostic and diagnostic biomarker gene signatures for diseases, such as cancer, is seen as a major step toward a better personalized medicine. During the last decade various methods 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. Most of these methods focus on classification problems, that is learn a model from data that discriminates patients into distinct clinical groups. Far less has been published on approaches that predict a patient's event risk. In this paper, we investigate eight methods that integrate network information into multivariable Cox proportional hazard models for risk prediction in breast cancer. We compare the prediction performance of our tested algorithms via cross-validation as well as across different datasets. In addition, we highlight the stability and interpretability of obtained gene signatures. In conclusion, we find GeneRank-based filtering to be a simple, computationally cheap and highly predictive technique to integrate network information into event time prediction models. Signatures derived via this method are highly reproducible. PMID:24430933

  2. High-Sensitivity and Low-Toxicity Fucose Probe for Glycan Imaging and Biomarker Discovery.

    Science.gov (United States)

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

    2016-07-21

    Fucose, a terminal sugar in glycoconjugates, critically regulates various physiological and pathological phenomena, including cancer development and inflammation. However, there are currently no probes for efficient labeling and detection of this sugar. We chemically synthesized a novel series of alkynyl-fucose analogs as probe candidates and found that 7-alkynyl-fucose gave the highest labeling efficiency and low cytotoxicity. Among the fucose analogs, 7-alkynyl-fucose was the best substrate against all five fucosyltransferases examined. We confirmed its conversion to the corresponding guanosine diphosphate derivative in cells and found that cellular glycoproteins were labeled much more efficiently with 7-alkynyl-fucose than with an existing probe. 7-Alkynyl-fucose was detected in the N-glycan core by mass spectrometry, and 7-alkynyl-fucose-modified proteins mostly disappeared in core-fucose-deficient mouse embryonic fibroblasts, suggesting that this analog mainly labeled core fucose in these cells. These results indicate that 7-alkynyl-fucose is a highly sensitive and powerful tool for basic glycobiology research and clinical application for biomarker discovery. PMID:27447047

  3. 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

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

    Directory of Open Access Journals (Sweden)

    Yinhai Wang

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

  5. Automated microfluidic platform of bead-based electrochemical immunosensor integrated with bioreactor for continual monitoring of cell secreted biomarkers

    Science.gov (United States)

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

    2016-04-01

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

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

    DEFF Research Database (Denmark)

    Vieira Campos, Diana Alexandra; Freitas, Daniela; Gomes, Joana; Magalhães, Ana; Steentoft, Catharina; Gomes, Catarina; Vester-Christensen, Malene B; Ferreira, José Alexandre; Afonso, Luis P; Santos, Lúcio L; de Sousa, João Pinto; Mandel, Ulla; Clausen, Henrik; Vakhrushev, Sergey Y; Reis, Celso A

    2015-01-01

    Circulating O-glycoproteins shed from cancer cells represent important serum biomarkers for diagnostic and prognostic purposes. We have recently shown that selective detection of cancer-associated aberrant glycoforms of circulating O-glycoprotein biomarkers can increase specificity of cancer biom...

  7. Mass cytometry as a platform for the discovery of cellular biomarkers to guide effective rheumatic disease therapy.

    Science.gov (United States)

    Nair, Nitya; Mei, Henrik E; Chen, Shih-Yu; Hale, Matthew; Nolan, Garry P; Maecker, Holden T; Genovese, Mark; Fathman, C Garrison; Whiting, Chan C

    2015-01-01

    The development of biomarkers for autoimmune diseases has been hampered by a lack of understanding of disease etiopathogenesis and of the mechanisms underlying the induction and maintenance of inflammation, which involves complex activation dynamics of diverse cell types. The heterogeneous nature and suboptimal clinical response to treatment observed in many autoimmune syndromes highlight the need to develop improved strategies to predict patient outcome to therapy and personalize patient care. Mass cytometry, using CyTOF®, is an advanced technology that facilitates multiparametric, phenotypic analysis of immune cells at single-cell resolution. In this review, we outline the capabilities of mass cytometry and illustrate the potential of this technology to enhance the discovery of cellular biomarkers for rheumatoid arthritis, a prototypical autoimmune disease. PMID:25981462

  8. 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

  9. 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.

  10. 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.

  11. 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)

    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.

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

    DEFF Research Database (Denmark)

    Mikkelsen, Jens D.; Thomsen, Morten S.; Hansen, Henrik; Lichota, Jacek

    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...

  13. High-throughput profiling for discovery of non-coding RNA biomarkers of lung disease.

    OpenAIRE

    McKiernan, Paul J; Catherine M. Greene

    2016-01-01

    In respiratory medicine there is a need for clinical biomarkers for diagnosis, prognosis and assessment of response to therapy. Noncoding RNA (ncRNA) is expressed in all human cells; two major classes - long ncRNA and microRNA - are detectable extracellularly in the circulation and other biofluids. Altered ncRNA expression is associated with lung disease; collectively this indicates that ncRNA represents a potential biomarker class. This article presents and compares existing platforms for de...

  14. 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.

  15. The Semantic Automated Discovery and Integration (SADI Web service Design-Pattern, API and Reference Implementation

    Directory of Open Access Journals (Sweden)

    Wilkinson Mark D

    2011-10-01

    Full Text Available Abstract Background The complexity and inter-related nature of biological data poses a difficult challenge for data and tool integration. There has been a proliferation of interoperability standards and projects over the past decade, none of which has been widely adopted by the bioinformatics community. Recent attempts have focused on the use of semantics to assist integration, and Semantic Web technologies are being welcomed by this community. Description SADI - Semantic Automated Discovery and Integration - is a lightweight set of fully standards-compliant Semantic Web service design patterns that simplify the publication of services of the type commonly found in bioinformatics and other scientific domains. Using Semantic Web technologies at every level of the Web services "stack", SADI services consume and produce instances of OWL Classes following a small number of very straightforward best-practices. In addition, we provide codebases that support these best-practices, and plug-in tools to popular developer and client software that dramatically simplify deployment of services by providers, and the discovery and utilization of those services by their consumers. Conclusions SADI Services are fully compliant with, and utilize only foundational Web standards; are simple to create and maintain for service providers; and can be discovered and utilized in a very intuitive way by biologist end-users. In addition, the SADI design patterns significantly improve the ability of software to automatically discover appropriate services based on user-needs, and automatically chain these into complex analytical workflows. We show that, when resources are exposed through SADI, data compliant with a given ontological model can be automatically gathered, or generated, from these distributed, non-coordinating resources - a behaviour we have not observed in any other Semantic system. Finally, we show that, using SADI, data dynamically generated from Web services

  16. 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.

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

    Directory of Open Access Journals (Sweden)

    Lazar Iulia M

    2009-03-01

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

  18. molSimplify: A toolkit for automating discovery in inorganic chemistry.

    Science.gov (United States)

    Ioannidis, Efthymios I; Gani, Terry Z H; Kulik, Heather J

    2016-08-15

    We present an automated, open source toolkit for the first-principles screening and discovery of new inorganic molecules and intermolecular complexes. Challenges remain in the automatic generation of candidate inorganic molecule structures due to the high variability in coordination and bonding, which we overcome through a divide-and-conquer tactic that flexibly combines force-field preoptimization of organic fragments with alignment to first-principles-trained metal-ligand distances. Exploration of chemical space is enabled through random generation of ligands and intermolecular complexes from large chemical databases. We validate the generated structures with the root mean squared (RMS) gradients evaluated from density functional theory (DFT), which are around 0.02 Ha/au across a large 150 molecule test set. Comparison of molSimplify results to full optimization with the universal force field reveals that RMS DFT gradients are improved by 40%. Seamless generation of input files, preparation and execution of electronic structure calculations, and post-processing for each generated structure aids interpretation of underlying chemical and energetic trends. © 2016 Wiley Periodicals, Inc. PMID:27364957

  19. Current application of proteomics in biomarker discovery for inflammatory bowel disease.

    Science.gov (United States)

    Chan, Patrick Py; Wasinger, Valerie C; Leong, Rupert W

    2016-02-15

    Recently, the field of proteomics has rapidly expanded in its application towards clinical research with objectives ranging from elucidating disease pathogenesis to discovering clinical biomarkers. As proteins govern and/or reflect underlying cellular processes, the study of proteomics provides an attractive avenue for research as it allows for the rapid identification of protein profiles in a biological sample. Inflammatory bowel disease (IBD) encompasses several heterogeneous and chronic conditions of the gastrointestinal tract. Proteomic technology provides a powerful means of addressing major challenges in IBD today, especially for identifying biomarkers to improve its diagnosis and management. This review will examine the current state of IBD proteomics research and its use in biomarker research. Furthermore, we also discuss the challenges of translating proteomic research into clinically relevant tools. The potential application of this growing field is enormous and is likely to provide significant insights towards improving our future understanding and management of IBD. PMID:26909226

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

    International Nuclear Information System (INIS)

    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

  1. Profiling of circulating microRNAs for prostate cancer biomarker discovery

    DEFF Research Database (Denmark)

    Haldrup, Christa; Kosaka, Nobuyoshi; Ochiya, Takahiro;

    2014-01-01

    and T-stage of the primary PC. Better tools to assess PC aggressiveness could aid in treatment decisions. Recently, circulating miRNAs have been suggested as potential new biomarkers for PC with diagnostic and prognostic potential. Here, to identify new serum miRNA biomarker candidates for PC, we...... 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 % of...

  2. Microarray Meta-Analysis and Cross-Platform Normalization: Integrative Genomics for Robust Biomarker Discovery

    Directory of Open Access Journals (Sweden)

    Christopher J. Walsh

    2015-08-01

    Full Text Available The diagnostic and prognostic potential of the vast quantity of publicly-available microarray data has driven the development of methods for integrating the data from different microarray platforms. Cross-platform integration, when appropriately implemented, has been shown to improve reproducibility and robustness of gene signature biomarkers. Microarray platform integration can be conceptually divided into approaches that perform early stage integration (cross-platform normalization versus late stage data integration (meta-analysis. A growing number of statistical methods and associated software for platform integration are available to the user, however an understanding of their comparative performance and potential pitfalls is critical for best implementation. In this review we provide evidence-based, practical guidance to researchers performing cross-platform integration, particularly with an objective to discover biomarkers.

  3. Prostate cancer serum biomarker discovery through proteomic analysis of alpha-2 macroglobulin protein complexes

    OpenAIRE

    Burgess, Earle F.; Ham, Amy-Joan L.; Tabb, David L.; Billheimer, Dean; Roth, Bruce J.; Chang, Sam S.; Cookson, Michael S.; Hinton, Timothy J.; Cheek, Kristin L.; Hill, Salisha; Jennifer A Pietenpol

    2008-01-01

    Alpha-2 macroglobulin (A2M) functions as a universal protease inhibitor in serum and is capable of binding various cytokines and growth factors. In this study, we investigated if immunoaffinity enrichment and proteomic analysis of A2M protein complexes from human serum could improve detection of biologically relevant and novel candidate protein biomarkers in prostate cancer. Serum samples from six patients with androgen-independent, metastatic prostate cancer and six control patients without ...

  4. Targeted proteomics for biomarker discovery and validation of hepatocellular carcinoma in hepatitis C infected patients

    OpenAIRE

    Mustafa, Gul M; Larry, Denner; John R. Petersen; Elferink, Cornelis J.

    2015-01-01

    Hepatocellular carcinoma (HCC)-related mortality is high because early detection modalities are hampered by inaccuracy, expense and inherent procedural risks. Thus there is an urgent need for minimally invasive, highly specific and sensitive biomarkers that enable early disease detection when therapeutic intervention remains practical. Successful therapeutic intervention is predicated on the ability to detect the cancer early. Similar unmet medical needs abound in most fields of medicine and ...

  5. Microarray Meta-Analysis and Cross-Platform Normalization: Integrative Genomics for Robust Biomarker Discovery

    OpenAIRE

    Walsh, Christopher J.; Pingzhao Hu; Jane Batt; dos Santos, Claudia C.

    2015-01-01

    The diagnostic and prognostic potential of the vast quantity of publicly-available microarray data has driven the development of methods for integrating the data from different microarray platforms. Cross-platform integration, when appropriately implemented, has been shown to improve reproducibility and robustness of gene signature biomarkers. Microarray platform integration can be conceptually divided into approaches that perform early stage integration (cross-platform normalization) versus ...

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

    OpenAIRE

    Altadill, Tatiana; Campoy, Irene; Lanau, Lucia; Gill, Kirandeep; Rigau, Marina; Gil-Moreno, Antonio; Reventos, Jaume; Byers, Stephen; Colas, Eva; Cheema, Amrita K.

    2016-01-01

    Identification of sensitive and specific biomarkers with clinical and translational utility will require smart experimental strategies that would augment expanding the breadth and depth of molecular measurements within the constraints of currently available technologies. Exosomes represent an information rich matrix to discern novel disease mechanisms that are thought to contribute to pathologies such as dementia and cancer. Although proteomics and transcriptomic studies have been reported us...

  7. Synovial tissue analysis for the discovery of diagnostic and prognostic biomarkers in patients with early arthritis.

    Science.gov (United States)

    de Hair, Maria J H; Harty, Leonard C; Gerlag, Danielle M; Pitzalis, Costantino; Veale, Douglas J; Tak, Paul P

    2011-09-01

    Rheumatoid arthritis (RA) is a chronic disease of unspecified etiology that is manifest by persistent inflammation of the synovium. Considerable efforts have been undertaken globally to study the microenvironment of the inflamed synovium, with many encouraging and enlightening results that bring us closer to unmasking the precise etiologies of RA. Subsequent to these efforts, it has been discovered that CD68-positive macrophages present in abundance in the synovial sublining of the inflamed synovium rescind with treatments that induce clinical improvement in RA. Examination of serial synovial biopsies is now commonly used for screening purposes during early drug development, and the number of centers able to perform synovial tissue biopsy sampling according to standardized methods is increasing. Having implemented the use of serial synovial tissue biopsies to evaluate the effects of new treatments on the group level in early proof of principle studies, it is the ambition of the OMERACT Synovial Tissue Group to identify synovial diagnostic and prognostic biomarkers that could be used in individual patients. Therefore, we started a prospective study termed the Synoviomics Project aimed at the identification of novel diagnostic and prognostic synovial biomarkers. We will use straightforward and powerful technologies to analyze patient material and assess clinical parameters to identify such biomarkers. These markers may be used in the future to identify patients who are at risk of having persistent and destructive disease and to start tailor-made targeted therapies in an early phase to prevent autonomous disease progression and irreversible joint damage. PMID:21885519

  8. Deglycosylation and label-free quantitative LC-MALDI MS applied to efficient serum biomarker discovery of lung cancer

    Directory of Open Access Journals (Sweden)

    Kohno Nobuoki

    2011-04-01

    Full Text Available Abstract Background Serum is an ideal source of biomarker discovery and proteomic profiling studies are continuously pursued on serum samples. However, serum is featured by high level of protein glycosylations that often cause ionization suppression and confound accurate quantification analysis by mass spectrometry. Here we investigated the effect of N-glycan and sialic acid removal from serum proteins on the performance of label-free quantification results. Results Serum tryptic digests with or without deglycosylation treatment were analyzed by LC-MALDI MS and quantitatively compared on the Expressionist Refiner MS module. As a result, 345 out of 2,984 peaks (11.6% showed the specific detection or the significantly improved intensities in deglycosylated serum samples (P P Conclusions We demonstrated here that sample deglycosylation improves the quantitative performance of shotgun proteomics, which can be effectively applied to any samples with high glycoprotein contents.

  9. 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. PMID:27247212

  10. 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

  11. 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.

  12. Integration of metabolomics and proteomics in multiple sclerosis: From biomarkers discovery to personalized medicine.

    Science.gov (United States)

    Del Boccio, Piero; Rossi, Claudia; di Ioia, Maria; Cicalini, Ilaria; Sacchetta, Paolo; Pieragostino, Damiana

    2016-04-01

    Personalized medicine is the science of individualized prevention and therapy. In the last decade, advances in high-throughput approaches allowed the development of proteomic and metabolomic studies in evaluating the association of genetic and phenotypic variability with disease sensitivity and analgesic response. These considerations have more value in case of multiple sclerosis (MuS), a multifactorial disease with high heterogeneity in clinical course and treatment response. In this review, we reported and updated about proteomic and metabolomic studies for the research of new candidate biomarkers in MuS, and difficulties in their clinical applications. We focused especially on the description of both "omics" approaches that, once integrated, may synergically describe pathophysiology conditions. To prove this assumption, we rebuilt interaction between proteins and metabolites described in the literature as potential biomarkers for MuS, and a pathway analysis of these molecules was performed. The result of such speculation demonstrated a strong convergence of proteomic and metabolomic results in this field, showing also a poorness of available tools for incorporating "omics" approaches. In conclusion, the integration of Metabolomics and Proteomics may allow a more complete characterization of such a heterogeneous disease, providing further insights into personalized healthcare. PMID:27061322

  13. The proteome of Hypobaric Induced Hypoxic Lung: Insights from Temporal Proteomic Profiling for Biomarker Discovery

    Science.gov (United States)

    Ahmad, Yasmin; Sharma, Narendra K.; Ahmad, Mohammad Faiz; Sharma, Manish; Garg, Iti; Srivastava, Mousami; Bhargava, Kalpana

    2015-01-01

    Exposure to high altitude induces physiological responses due to hypoxia. Lungs being at the first level to face the alterations in oxygen levels are critical to counter and balance these changes. Studies have been done analysing pulmonary proteome alterations in response to exposure to hypobaric hypoxia. However, such studies have reported the alterations at specific time points and do not reflect the gradual proteomic changes. These studies also identify the various biochemical pathways and responses induced after immediate exposure and the resolution of these effects in challenge to hypobaric hypoxia. In the present study, using 2-DE/MS approach, we attempt to resolve these shortcomings by analysing the proteome alterations in lungs in response to different durations of exposure to hypobaric hypoxia. Our study thus highlights the gradual and dynamic changes in pulmonary proteome following hypobaric hypoxia. For the first time, we also report the possible consideration of SULT1A1, as a biomarker for the diagnosis of high altitude pulmonary edema (HAPE). Higher SULT1A1 levels were observed in rats as well as in humans exposed to high altitude, when compared to sea-level controls. This study can thus form the basis for identifying biomarkers for diagnostic and prognostic purposes in responses to hypobaric hypoxia. PMID:26022216

  14. Bovine Tuberculosis in Cattle: Vaccines, DIVA Tests, and Host Biomarker Discovery.

    Science.gov (United States)

    Vordermeier, H Martin; Jones, Gareth J; Buddle, Bryce M; Hewinson, R Glyn; Villarreal-Ramos, Bernardo

    2016-02-15

    Bovine tuberculosis remains a major economic and animal welfare concern worldwide. Cattle vaccination is being considered as part of control strategies. This approach, used alongside conventional control policies, also requires the development of vaccine-compatible diagnostic assays to distinguish vaccinated from infected animals (DIVA). We discuss progress made on optimizing the only potentially available vaccine, bacille Calmette Guérin (BCG), and on strategies to improve BCG efficacy. We also describe recent advances in DIVA development based on the detection of host cellular immune responses by blood-testing or skin-testing approaches. Finally, to accelerate vaccine development, definition of host biomarkers that provide meaningful stage-gating criteria to select vaccine candidates for further testing is highly desirable. Some progress has also been made in this area of research, and we summarize studies that defined either markers predicting vaccine success or markers that correlate with disease stage or severity. PMID:26884103

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

    Directory of Open Access Journals (Sweden)

    Kooren Joel A

    2011-09-01

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

  16. Microfluidic droplet-based PCR instrumentation for high-throughput gene expression profiling and biomarker discovery

    Directory of Open Access Journals (Sweden)

    Christopher J. Hayes

    2015-06-01

    Full Text Available PCR is a common and often indispensable technique used in medical and biological research labs for a variety of applications. Real-time quantitative PCR (RT-qPCR has become a definitive technique for quantitating differences in gene expression levels between samples. Yet, in spite of this importance, reliable methods to quantitate nucleic acid amounts in a higher throughput remain elusive. In the following paper, a unique design to quantify gene expression levels at the nanoscale in a continuous flow system is presented. Fully automated, high-throughput, low volume amplification of deoxynucleotides (DNA in a droplet based microfluidic system is described. Unlike some conventional qPCR instrumentation that use integrated fluidic circuits or plate arrays, the instrument performs qPCR in a continuous, micro-droplet flowing process with droplet generation, distinctive reagent mixing, thermal cycling and optical detection platforms all combined on one complete instrument. Detailed experimental profiling of reactions of less than 300 nl total volume is achieved using the platform demonstrating the dynamic range to be 4 order logs and consistent instrument sensitivity. Furthermore, reduced pipetting steps by as much as 90% and a unique degree of hands-free automation makes the analytical possibilities for this instrumentation far reaching. In conclusion, a discussion of the first demonstrations of this approach to perform novel, continuous high-throughput biological screens is presented. The results generated from the instrument, when compared with commercial instrumentation, demonstrate the instrument reliability and robustness to carry out further studies of clinical significance with added throughput and economic benefits.

  17. Many accurate small-discriminatory feature subsets exist in microarray transcript data: biomarker discovery

    Directory of Open Access Journals (Sweden)

    Grate Leslie R

    2005-04-01

    Full Text Available Abstract Background Molecular profiling generates abundance measurements for thousands of gene transcripts in biological samples such as normal and tumor tissues (data points. Given such two-class high-dimensional data, many methods have been proposed for classifying data points into one of the two classes. However, finding very small sets of features able to correctly classify the data is problematic as the fundamental mathematical proposition is hard. Existing methods can find "small" feature sets, but give no hint how close this is to the true minimum size. Without fundamental mathematical advances, finding true minimum-size sets will remain elusive, and more importantly for the microarray community there will be no methods for finding them. Results We use the brute force approach of exhaustive search through all genes, gene pairs (and for some data sets gene triples. Each unique gene combination is analyzed with a few-parameter linear-hyperplane classification method looking for those combinations that form training error-free classifiers. All 10 published data sets studied are found to contain predictive small feature sets. Four contain thousands of gene pairs and 6 have single genes that perfectly discriminate. Conclusion This technique discovered small sets of genes (3 or less in published data that form accurate classifiers, yet were not reported in the prior publications. This could be a common characteristic of microarray data, thus making looking for them worth the computational cost. Such small gene sets could indicate biomarkers and portend simple medical diagnostic tests. We recommend checking for small gene sets routinely. We find 4 gene pairs and many gene triples in the large hepatocellular carcinoma (HCC, Liver cancer data set of Chen et al. The key component of these is the "placental gene of unknown function", PLAC8. Our HMM modeling indicates PLAC8 might have a domain like part of lP59's crystal structure (a Non

  18. Fibroblasts from skin biopsies as a tool for biomarker discovery in Parkinson׳s disease.

    Science.gov (United States)

    Mastroberardino, Pier Giorgio; Ambrosi, Giulia; Blandini, Fabio; Milanese, Chiara; Sepe, Sara

    2014-10-01

    Parkinson׳s disease (PD) is a complex disease and the current interest and focus of scientific research is both investigating the variety of causes that underlie PD pathogenesis, and identifying reliable biomarkers to diagnose and monitor the progression of pathology. Investigation on pathogenic mechanisms in peripheral cells, such as fibroblasts derived from patients with sporadic PD and age/gender matched controls, might generate deeper understanding of the deficits affecting dopaminergic neurons and, possibly, new tools applicable to clinical practice. The chronic and slow progressing nature of PD may result from subtle yet persistent alterations in biological mechanisms, which might be undetectable in basal, unchallenged conditions. Unlike body fluids, dermal fibroblasts can be exposed to different challenges while in culture and can therefore generate information about the dynamic cellular responses to exogenous stressors. These studies may ultimately generate indicators highlighting the biological defects intrinsic to PD. In fact, fibroblasts from idiopathic PD patients' exhibit deficits typically sustaining the neurodegenerative process of PD, such as increased susceptibility to rotenone as well as deficits in protein homeostasis and mitochondrial bioenergetics Fibroblasts therefore represent a powerful and minimally invasive tool to investigate PD pathogenic mechanisms, which might translate into considerable advances in clinical management of the disease. PMID:26461279

  19. GENPLAT: an automated platform for biomass enzyme discovery and cocktail optimization.

    Science.gov (United States)

    Walton, Jonathan; Banerjee, Goutami; Car, Suzana

    2011-01-01

    The high cost of enzymes for biomass deconstruction is a major impediment to the economic conversion of lignocellulosic feedstocks to liquid transportation fuels such as ethanol. We have developed an integrated high throughput platform, called GENPLAT, for the discovery and development of novel enzymes and enzyme cocktails for the release of sugars from diverse pretreatment/biomass combinations. GENPLAT comprises four elements: individual pure enzymes, statistical design of experiments, robotic pipeting of biomass slurries and enzymes, and automated colorimeteric determination of released Glc and Xyl. Individual enzymes are produced by expression in Pichia pastoris or Trichoderma reesei, or by chromatographic purification from commercial cocktails or from extracts of novel microorganisms. Simplex lattice (fractional factorial) mixture models are designed using commercial Design of Experiment statistical software. Enzyme mixtures of high complexity are constructed using robotic pipeting into a 96-well format. The measurement of released Glc and Xyl is automated using enzyme-linked colorimetric assays. Optimized enzyme mixtures containing as many as 16 components have been tested on a variety of feedstock and pretreatment combinations. GENPLAT is adaptable to mixtures of pure enzymes, mixtures of commercial products (e.g., Accellerase 1000 and Novozyme 188), extracts of novel microbes, or combinations thereof. To make and test mixtures of ˜10 pure enzymes requires less than 100 μg of each protein and fewer than 100 total reactions, when operated at a final total loading of 15 mg protein/g glucan. We use enzymes from several sources. Enzymes can be purified from natural sources such as fungal cultures (e.g., Aspergillus niger, Cochliobolus carbonum, and Galerina marginata), or they can be made by expression of the encoding genes (obtained from the increasing number of microbial genome sequences) in hosts such as E. coli, Pichia pastoris, or a filamentous fungus such

  20. Upscaling and automation of electrophysiology: toward high throughput screening in ion channel drug discovery

    DEFF Research Database (Denmark)

    Asmild, Margit; Oswald, Nicholas; Krzywkowski, Karen M;

    2003-01-01

    Effective screening of large compound libraries in ion channel drug discovery requires the development of new electrophysiological techniques with substantially increased throughputs compared to the conventional patch clamp technique. Sophion Bioscience is aiming to meet this challenge by...

  1. 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.

  2. An Efficient Algorithm to Automated Discovery of Interesting Positive and Negative Association Rules

    Directory of Open Access Journals (Sweden)

    Ahmed Abdul-WahabAl-Opahi

    2015-06-01

    Full Text Available Association Rule mining is very efficient technique for finding strong relation between correlated data. The correlation of data gives meaning full extraction process. For the discovering frequent items and the mining of positive rules, a variety of algorithms are used such as Apriori algorithm and tree based algorithm. But these algorithms do not consider negation occurrence of the attribute in them and also these rules are not in infrequent form. The discovery of infrequent itemsets is far more difficult than their counterparts, that is, frequent itemsets. These problems include infrequent itemsets discovery and generation of interest negative association rules, and their huge number as compared with positive association rules. The interesting discovery of association rules is an important and active area within data mining research. In this paper, an efficient algorithm is proposed for discovering interesting positive and negative association rules from frequent and infrequent items. The experimental results show the usefulness and effectiveness of the proposed algorithm.

  3. Automating Knowledge Discovery for Toxicity Prediction Using Jumping Emerging Pattern Mining

    OpenAIRE

    Sherhod, R.; Gillet, V.J.; Judson, P.N.; Vessey, J.D.

    2012-01-01

    : The design of new alerts, that is, collections of structural features observed to result in toxicological activity, can be a slow process and may require significant input from toxicology and chemistry experts. A method has therefore been developed to help automate alert identification by mining descriptions of activating structural features directly from toxicity data sets. The method is based on jumping emerging pattern mining which is applied to a set of toxic and nontoxic compo...

  4. 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.

  5. GENPLAT: an Automated Platform for Biomass Enzyme Discovery and Cocktail Optimization

    OpenAIRE

    Walton, Jonathan; Banerjee, Goutami; Car, Suzana

    2011-01-01

    The high cost of enzymes for biomass deconstruction is a major impediment to the economic conversion of lignocellulosic feedstocks to liquid transportation fuels such as ethanol. We have developed an integrated high throughput platform, called GENPLAT, for the discovery and development of novel enzymes and enzyme cocktails for the release of sugars from diverse pretreatment/biomass combinations. GENPLAT comprises four elements: individual pure enzymes, statistical design of experiments, robot...

  6. Analytic Validation of the Automated Bone Scan Index as an Imaging Biomarker to Standardize Quantitative Changes in Bone Scans of Patients with Metastatic Prostate Cancer

    Science.gov (United States)

    Anand, Aseem; Morris, Michael J.; Kaboteh, Reza; Båth, Lena; Sadik, May; Gjertsson, Peter; Lomsky, Milan; Edenbrandt, Lars; Minarik, David; Bjartell, Anders

    2016-01-01

    A reproducible and quantitative imaging biomarker is needed to standardize the evaluation of changes in bone scans of prostate cancer patients with skeletal metastasis. We performed a series of analytic validation studies to evaluate the performance of the automated bone scan index (BSI) as an imaging biomarker in patients with metastatic prostate cancer. Methods Three separate analytic studies were performed to evaluate the accuracy, precision, and reproducibility of the automated BSI. Simulation study: bone scan simulations with predefined tumor burdens were created to assess accuracy and precision. Fifty bone scans were simulated with a tumor burden ranging from low to high disease confluence (0.10–13.0 BSI). A second group of 50 scans was divided into 5 subgroups, each containing 10 simulated bone scans, corresponding to BSI values of 0.5, 1.0, 3.0, 5.0, and 10.0. Repeat bone scan study: to assess the reproducibility in a routine clinical setting, 2 repeat bone scans were obtained from metastatic prostate cancer patients after a single 600-MBq 99mTc-methylene diphosphonate injection. Follow-up bone scan study: 2 follow-up bone scans of metastatic prostate cancer patients were analyzed to determine the interobserver variability between the automated BSIs and the visual interpretations in assessing changes. The automated BSI was generated using the upgraded EXINI boneBSI software (version 2). The results were evaluated using linear regression, Pearson correlation, Cohen κ measurement, coefficient of variation, and SD. Results Linearity of the automated BSI interpretations in the range of 0.10–13.0 was confirmed, and Pearson correlation was observed at 0.995 (n = 50; 95% confidence interval, 0.99–0.99; P cancer. PMID:26315832

  7. Automated solvent system screening for the preparative countercurrent chromatography of pharmaceutical discovery compounds.

    Science.gov (United States)

    Bradow, James; Riley, Frank; Philippe, Laurence; Yan, Qi; Schuff, Brandon; Harris, Guy H

    2015-12-01

    A fully automated countercurrent chromatography system has been constructed to rapidly screen the commonly used heptane/ethyl acetate/methanol/water solvent system series and translate the results to preparative scale separations. The system utilizes "on-demand" preparation of the heptane/ethyl acetate/methanol/water solvent system upper and lower phases. Elution-extrusion countercurrent chromatography was combined with non-dynamic equilibrium injection reducing the screening time for each heptane/ethyl acetate/methanol/water system to 17 min. The result enabled solvent system development to be reduced to under 2 h. The countercurrent chromatography system was interfaced with a mass spectrometer to allow selective detection of target components in crude medicinal chemistry reaction mixtures. Mass-directed preparative countercurrent chromatography purification was demonstrated for the first time using a synthetic tetrazole epoxide derived from a routine medicinal chemistry support workflow. PMID:26428946

  8. A signaling visualization toolkit to support rational design of combination therapies and biomarker discovery : SiViT

    OpenAIRE

    Brown, James L; Shovman, Mark; Robertson, Paul; Boiko, Andrei; Goltsov, Alexey; Mullen, Peter; Harrison, David James

    2016-01-01

    Targeted cancer therapy aims to disrupt aberrant cellular signalling pathways. Biomarkers are surrogates of pathway state, but there is limited success in translating candidate biomarkers to clinical practice due to the intrinsic complexity of pathway networks. Systems biology approaches afford better understanding of complex, dynamical interactions in signalling pathways targeted by anticancer drugs. However, adoption of dynamical modelling by clinicians and biologists is impeded by model in...

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

    Science.gov (United States)

    de Franciscis, Stefano; Metzinger, Laurent; Serra, Raffaele

    2016-01-01

    Cardiovascular disease (CD) and peripheral vascular disease (PVD) are leading causes of mortality and morbidity in western countries and also responsible of a huge burden in terms of disability, functional decline, and healthcare costs. Biomarkers are measurable biological elements that reflect particular physiological or pathological states or predisposition towards diseases and they are currently widely studied in medicine and especially in CD. In this context, biomarkers can also be used to assess the severity or the evolution of several diseases, as well as the effectiveness of particular therapies. Genomics, transcriptomics, and proteomics have opened new windows on disease phenomena and may permit in the next future an effective development of novel diagnostic and prognostic medicine in order to better prevent or treat CD. This review will consider the current evidence of novel biomarkers with clear implications in the improvement of risk assessment, prevention strategies, and medical decision making in the field of CD. PMID:27298828

  10. 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

    In this study Atlantic cod (Gadus morhua) were exposed to different levels of North Sea produced water (PW) and 17beta-oestradiol (E(2)), a natural oestrogen, from egg to fry stage (90 days). By comparing changes in protein expression following E(2) exposure to changes induced by PW treatment, we...... 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...

  11. 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

    stability of the selected variables. The performance of the method was evaluated using a simulated data set and a multi-block data set from a dietary intervention study with pigs used as model for humans. The objective of the study was to investigate the biochemical effects in plasma after dietary...... intervention with breads varying in types of dietary fiber and to identify potential biomarkers. By introducing Sparse MBPLSR, we aimed at identifying the biomarkers where data from LC–MS and NMR instruments were analyzed simultaneously and therefore in addition we intended to explore the relationships among...

  12. A “dose on demand” Biomarker Generator for automated production of [18F]F− and [18F]FDG

    International Nuclear Information System (INIS)

    The University of Oklahoma—College of Pharmacy has installed the first Biomarker Generator (BG75) comprising a self-shielded 7.5-MeV proton beam positive ion cyclotron and an aseptic automated chemistry production and quality control module for production of [18F]F− and clinical [18F]FDG. Performance, reliability, and safety of the system for the production of “dose on demand” were tested over several months. No-carrier-added [18F]F− was obtained through the 18O(p,n)18F nuclear reaction by irradiation (20–40 min) of a >95% enriched [18O]H2O target (280 μl) with a 7.5-MeV proton beam (3.5–5.0 μA). Automated quality control tests were performed on each dose. The HPLC-based analytical methods were validated against USP methods of quality control. [18F]FDG produced by BG75 was tested in a mouse tumor model implanted with H441 human lung adenocarcinoma cells. After initial installment and optimization, the [18F]F− production has been consistent since March 2011 with a maximum production of 400 to 450 mCi in a day. The average yield is 0.61 mCi/min and 0.92 mCi/min at 3.8 µA and 5 µA, respectively. The current target window has held up for over 25 weeks against >400 bombardment cycles. [18F]FDG production has been consistent since June 2012 with an average of six doses/day in an automated synthesis mode (RCY≈50%). The release criteria included USP-specified limits for pH, residual solvents (acetonitrile/ethanol), kryptofix, radiochemical purity/identity, and filter integrity test. The entire automated operation generated minimal radiation exposure hazard to the operator and environment. As expected, [18F]FDG produced by BG75 was found to delineate tumor volume in a mouse model of xenograft tumor. In summary, production and quality control of “[18F]FDG dose on demand” have been accomplished in an automated and safe manner by the first Biomarker Generator. The implementation of a cGMP quality system is under way towards the ANDA submission and

  13. Biomarker discovery with SELDI-TOF MS in human urine associated with early renal injury : evaluation with computational analytical tools.

    NARCIS (Netherlands)

    Houtte, K.J.A. van; Laarakkers, C.; Marchiori, E.; Pickkers, P.; Wetzels, J.F.M.; Willems, J.L.; Heuvel, L.P.W.J. van den; Russel, F.G.M.; Masereeuw, R.

    2007-01-01

    BACKGROUND: Urine proteomics is one of the key emerging technologies to discover new biomarkers for renal disease, which may be used in the early diagnosis, prognosis and treatment of patients. In the present study, we validated surface-enhanced laser desorption/ionization time-of-flight mass spectr

  14. Regulatory Forum Opinion Piece*: Veterinary Pathologists in Translational Pharmacology and Biomarker Integration in Drug Discovery and Development.

    Science.gov (United States)

    Ramaiah, Shashi K; Walker, Dana B

    2016-02-01

    This article highlights emerging roles for veterinary pathologists outside of traditional functions and in line with the translational research (TR) approach. Veterinary pathologists offer unique and valuable expertise toward addressing particular TR and associated translational pharmacology questions, identifying gaps and risks in biomarker and pathology strategies, and advancing TR team decision making. Veterinary pathologists' attributes that are integral to the TR approach include (i) well-developed understanding of comparative physiology, pathology, and disease; (ii) extensive experience in interpretation and integration of complex data sets on whole-body responses and utilizing this for deciphering pathogenesis and translating events between laboratory species and man; (iii) proficiency in recognizing differences in disease end points among individuals, animal species and strains, and assessing correlations between these differences and other investigative (including biomarker) findings; and (iv) strong background in a wide spectrum of research technologies that can address pathomechanistic questions and biomarker needs. Some of the more evident roles in which veterinary pathologists can offer their greatest contributions to address questions and strategies of TR and biomarker integration will be emphasized. PMID:26839329

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

    DEFF Research Database (Denmark)

    Ahluwalia, Tarunveer Singh; Allin, Kristine Højgaard; Sandholt, Camilla Helene;

    2015-01-01

    biomarkers associated with T2D: adiponectin, C-reactive protein, ferritin, heat shock 70-kDa protein 1B, IGF binding protein 1 and IGF binding protein 2, IL-18, IL-2 receptor-α, and leptin. DESIGN AND PARTICIPANTS: A population-based sample of 6215 adult Danes was genotyped for 16 340 coding single...... therapeutic strategies....

  16. A joint modeling approach for uncovering associations between gene expression, bioactivity and chemical structure in early drug discovery to guide lead selection and genomic biomarker development.

    Science.gov (United States)

    Perualila-Tan, Nolen; Kasim, Adetayo; Talloen, Willem; Verbist, Bie; Göhlmann, Hinrich W H; Shkedy, Ziv

    2016-08-01

    The modern drug discovery process involves multiple sources of high-dimensional data. This imposes the challenge of data integration. A typical example is the integration of chemical structure (fingerprint features), phenotypic bioactivity (bioassay read-outs) data for targets of interest, and transcriptomic (gene expression) data in early drug discovery to better understand the chemical and biological mechanisms of candidate drugs, and to facilitate early detection of safety issues prior to later and expensive phases of drug development cycles. In this paper, we discuss a joint model for the transcriptomic and the phenotypic variables conditioned on the chemical structure. This modeling approach can be used to uncover, for a given set of compounds, the association between gene expression and biological activity taking into account the influence of the chemical structure of the compound on both variables. The model allows to detect genes that are associated with the bioactivity data facilitating the identification of potential genomic biomarkers for compounds efficacy. In addition, the effect of every structural feature on both genes and pIC50 and their associations can be simultaneously investigated. Two oncology projects are used to illustrate the applicability and usefulness of the joint model to integrate multi-source high-dimensional information to aid drug discovery. PMID:27269248

  17. An evaluation of logic regression-based biomarker discovery across multiple intergenic regions for predicting host specificity in Escherichia coli.

    Science.gov (United States)

    Zhi, Shuai; Li, Qiaozhi; Yasui, Yutaka; Banting, Graham; Edge, Thomas A; Topp, Edward; McAllister, Tim A; Neumann, Norman F

    2016-10-01

    Several studies have demonstrated that E. coli appears to display some level of host adaptation and specificity. Recent studies in our laboratory support these findings as determined by logic regression modeling of single nucleotide polymorphisms (SNP) in intergenic regions (ITGRs). We sought to determine the degree of host-specific information encoded in various ITGRs across a library of animal E. coli isolates using both whole genome analysis and a targeted ITGR sequencing approach. Our findings demonstrated that ITGRs across the genome encode various degrees of host-specific information. Incorporating multiple ITGRs (i.e., concatenation) into logic regression model building resulted in greater host-specificity and sensitivity outcomes in biomarkers, but the overall level of polymorphism in an ITGR did not correlate with the degree of host-specificity encoded in the ITGR. This suggests that distinct SNPs in ITGRs may be more important in defining host-specificity than overall sequence variation, explaining why traditional unsupervised learning phylogenetic approaches may be less informative in terms of revealing host-specific information encoded in DNA sequence. In silico analysis of 80 candidate ITGRs from publically available E. coli genomes was performed as a tool for discovering highly host-specific ITGRs. In one ITGR (ydeR-yedS) we identified a SNP biomarker that was 98% specific for cattle and for which 92% of all E. coli isolates originating from cattle carried this unique biomarker. In the case of humans, a host-specific biomarker (98% specificity) was identified in the concatenated ITGR sequences of rcsD-ompC, ydeR-yedS, and rclR-ykgE, and for which 78% of E. coli originating from humans carried this biomarker. Interestingly, human-specific biomarkers were dominant in ITGRs regulating antibiotic resistance, whereas in cattle host-specific biomarkers were found in ITGRs involved in stress regulation. These data suggest that evolution towards host

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

    OpenAIRE

    Jianwen She; Wei Zou; Vladimir V. Tolstikov

    2013-01-01

    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 spectro...

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

    OpenAIRE

    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 typical...

  20. 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.

  1. Mass cytometry as a platform for the discovery of cellular biomarkers to guide effective rheumatic disease therapy

    OpenAIRE

    Nair, Nitya; Mei, Henrik E; Chen, Shih-Yu; Hale, Matthew; Garry P Nolan; Maecker, Holden T.; Genovese, Mark; Fathman, C. Garrison; Whiting, Chan C

    2015-01-01

    The development of biomarkers for autoimmune diseases has been hampered by a lack of understanding of disease etiopathogenesis and of the mechanisms underlying the induction and maintenance of inflammation, which involves complex activation dynamics of diverse cell types. The heterogeneous nature and suboptimal clinical response to treatment observed in many autoimmune syndromes highlight the need to develop improved strategies to predict patient outcome to therapy and personalize patient car...

  2. 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

  3. The Discovery and Validation of Biomarkers for the Diagnosis of Esophageal Squamous Dysplasia and Squamous Cell Carcinoma.

    Science.gov (United States)

    Couch, George; Redman, James E; Wernisch, Lorenz; Newton, Richard; Malhotra, Shalini; Dawsey, Sanford M; Lao-Sirieix, Pierre; Fitzgerald, Rebecca C

    2016-07-01

    The 5-year survival rate of esophageal cancer is less than 10% in developing countries, where more than 90% of these cancers are esophageal squamous cell carcinomas (ESCC). Endoscopic screening is undertaken in high incidence areas. Biomarker analysis could reduce the subjectivity associated with histologic assessment of dysplasia and thus improve diagnostic accuracy. The aims of this study were therefore to identify biomarkers for esophageal squamous dysplasia and carcinoma. A publicly available dataset was used to identify genes with differential expression in ESCC compared with normal esophagus. Each gene was ranked by a support vector machine separation score. Expression profiles were examined, before validation by qPCR and IHC. We found that 800 genes were overexpressed in ESCC compared with normal esophagus (P < 10(-5)). Of the top 50 genes, 33 were expressed in ESCC epithelium and not in normal esophagus epithelium or stroma using the Protein Atlas website. These were taken to qPCR validation, and 20 genes were significantly overexpressed in ESCC compared with normal esophagus (P < 0.05). TNFAIP3 and CHN1 showed differential expression with IHC. TNFAIP3 expression increased gradually through normal esophagus, mild, moderate and severe dysplasia, and SCC (P < 0.0001). CHN1 staining was rarely present in the top third of normal esophagus epithelium and extended progressively towards the surface in mild, moderate, and severe dysplasia, and SCC (P < 0.0001). Two novel promising biomarkers for ESCC were identified, TNFAIP3 and CHN1. CHN1 and TNFAIP3 may improve diagnostic accuracy of screening methods for ESCC. Cancer Prev Res; 9(7); 558-66. ©2016 AACR. PMID:27072986

  4. Discovery of a Metastatic Immune Escape Mechanism Initiated by the Loss of Expression of the Tumour Biomarker Interleukin-33.

    Science.gov (United States)

    Saranchova, Iryna; Han, Jeffrey; Huang, Hui; Fenninger, Franz; Choi, Kyung Bok; Munro, Lonna; Pfeifer, Cheryl; Welch, Ian; Wyatt, Alexander W; Fazli, Ladan; Gleave, Martin E; Jefferies, Wilfred A

    2016-01-01

    A new paradigm for understanding immune-surveillance and immune escape in cancer is described here. Metastatic carcinomas express reduced levels of IL-33 and diminished levels of antigen processing machinery (APM), compared to syngeneic primary tumours. Complementation of IL-33 expression in metastatic tumours upregulates APM expression and functionality of major histocompatibility complex (MHC)-molecules, resulting in reduced tumour growth rates and a lower frequency of circulating tumour cells. Parallel studies in humans demonstrate that low tumour expression of IL-33 is an immune biomarker associated with recurrent prostate and kidney renal clear cell carcinomas. Thus, IL-33 has a significant role in cancer immune-surveillance against primary tumours, which is lost during the metastatic transition that actuates immune escape in cancer. PMID:27619158

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

    Institute of Scientific and Technical Information of China (English)

    Wanling Yang; Dingge Ying; Yu-Lung Lau

    2009-01-01

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

  6. Phospholipid fatty acid biomarkers in a freshwater periphyton community exposed to uranium: discovery by non-linear statistical learning

    International Nuclear Information System (INIS)

    Phospholipid fatty acids (PLFA) have been widely used to characterize environmental microbial communities, generating community profiles that can distinguish phylogenetic or functional groups within the community. The poor specificity of organism groups with fatty acid biomarkers in the classic PLFA-microorganism associations is a confounding factor in many of the statistical classification/clustering approaches traditionally used to interpret PLFA profiles. In this paper we demonstrate that non-linear statistical learning methods, such as a support vector machine (SVM), can more accurately find patterns related to uranyl nitrate exposure in a freshwater periphyton community than linear methods, such as partial least squares discriminant analysis. In addition, probabilistic models of exposure can be derived from the identified lipid biomarkers to demonstrate the potential model-based approach that could be used in remediation. The SVM probability model separates dose groups at accuracies of ∼87.0%, ∼71.4%, ∼87.5%, and 100% for the four groups; Control (non-amended system), low dose (amended at 10 μg U L-1), medium dose (amended at 100 μg U L-1), and high dose (500 μg U L-1). The SVM model achieved an overall cross-validated classification accuracy of ∼87% in contrast to ∼59% for the best linear classifier. - Research highlights: →Linear statistical tools failed to find patterns in the periphyton PLFA profiles. →Support vector machines successfully identified key PLFAs indicative of U exposure. →U exposure stimulated more phototrophic populations, prokaryotic and eukaryotic.

  7. Discovery and Validation of Prognostic Biomarker Models to Guide Triage among Adult Dengue Patients at Early Infection

    Science.gov (United States)

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

    2016-01-01

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

  8. “Happiness Is . . . Library Automation”: The Rhetoric of Early Library Automation and the Future of Discovery and Academic Libraries

    OpenAIRE

    Kosrow, Lauren; Hinchliffe, Lisa

    2015-01-01

    During the second half of the twentieth century, the professional literature of academic librarianship imagined, speculated, and envisioned how impressive technological advancements might affect the future of academic libraries and the profession as a whole. Technology and automation, stalwarts of the Space Age, were portrayed as the panacea for librarians burdened with growing collections and overwhelming clerical processes. Many voices chimed in to predict how mechanization and automation w...

  9. 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.

  10. 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

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

    Directory of Open Access Journals (Sweden)

    Steven Carberry

    2013-12-01

    Full Text Available 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.

  12. 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

  13. Discovery of potential prognostic long non-coding RNA biomarkers for predicting the risk of tumor recurrence of breast cancer patients.

    Science.gov (United States)

    Zhou, Meng; Zhong, Lei; Xu, Wanying; Sun, Yifan; Zhang, Zhaoyue; Zhao, Hengqiang; Yang, Lei; Sun, Jie

    2016-01-01

    Deregulation of long non-coding RNAs (lncRNAs) expression has been proven to be involved in the development and progression of cancer. However, expression pattern and prognostic value of lncRNAs in breast cancer recurrence remain unclear. Here, we analyzed lncRNA expression profiles of breast cancer patients who did or did not develop recurrence by repurposing existing microarray datasets from the Gene Expression Omnibus database, and identified 12 differentially expressed lncRNAs that were closely associated with tumor recurrence of breast cancer patients. We constructed a lncRNA-focus molecular signature by the risk scoring method based on the expression levels of 12 relapse-related lncRNAs from the discovery cohort, which classified patients into high-risk and low-risk groups with significantly different recurrence-free survival (HR = 2.72, 95% confidence interval 2.07-3.57; p = 4.8e-13). The 12-lncRNA signature also represented similar prognostic value in two out of three independent validation cohorts. Furthermore, the prognostic power of the 12-lncRNA signature was independent of known clinical prognostic factors in at least two cohorts. Functional analysis suggested that the predicted relapse-related lncRNAs may be involved in known breast cancer-related biological processes and pathways. Our results highlighted the potential of lncRNAs as novel candidate biomarkers to identify breast cancer patients at high risk of tumor recurrence. PMID:27503456

  14. Proteomic response of mussels Mytilus galloprovincialis exposed to CuO NPs and Cu2+: An exploratory biomarker discovery

    International Nuclear Information System (INIS)

    associated with adhesion and mobility, precollagen-D that is associated with the detoxification mechanism of Cu2+. Protein identification clearly showed that the toxicity of CuO NPs is not solely due to Cu2+ 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. Robofurnace: A semi-automated laboratory chemical vapor deposition system for high-throughput nanomaterial synthesis and process discovery

    International Nuclear Information System (INIS)

    Laboratory research and development on new materials, such as nanostructured thin films, often utilizes manual equipment such as tube furnaces due to its relatively low cost and ease of setup. However, these systems can be prone to inconsistent outcomes due to variations in standard operating procedures and limitations in performance such as heating and cooling rates restrict the parameter space that can be explored. Perhaps more importantly, maximization of research throughput and the successful and efficient translation of materials processing knowledge to production-scale systems, relies on the attainment of consistent outcomes. In response to this need, we present a semi-automated lab-scale chemical vapor deposition (CVD) furnace system, called “Robofurnace.” Robofurnace is an automated CVD system built around a standard tube furnace, which automates sample insertion and removal and uses motion of the furnace to achieve rapid heating and cooling. The system has a 10-sample magazine and motorized transfer arm, which isolates the samples from the lab atmosphere and enables highly repeatable placement of the sample within the tube. The system is designed to enable continuous operation of the CVD reactor, with asynchronous loading/unloading of samples. To demonstrate its performance, Robofurnace is used to develop a rapid CVD recipe for carbon nanotube (CNT) forest growth, achieving a 10-fold improvement in CNT forest mass density compared to a benchmark recipe using a manual tube furnace. In the long run, multiple systems like Robofurnace may be linked to share data among laboratories by methods such as Twitter. Our hope is Robofurnace and like automation will enable machine learning to optimize and discover relationships in complex material synthesis processes

  16. 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.

  17. Shotgun Proteomics and Biomarker Discovery

    OpenAIRE

    W. Hayes McDonald; Yates, John R.

    2002-01-01

    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 multidimens...

  18. Automated Bone Scan Index as a quantitative imaging biomarker in metastatic castration-resistant prostate cancer patients being treated with enzalutamide

    DEFF Research Database (Denmark)

    Anand, Aseem; Morris, Michael J; Larson, Steven M;

    2016-01-01

    BACKGROUND: Having performed analytical validation studies, we are now assessing the clinical utility of the upgraded automated Bone Scan Index (BSI) in metastatic castration-resistant prostate cancer (mCRPC). In the present study, we retrospectively evaluated the discriminatory strength of the...... automated BSI in predicting overall survival (OS) in mCRPC patients being treated with enzalutamide. METHODS: Retrospectively, we included patients who received enzalutamide as a clinically approved therapy for mCRPC and had undergone bone scan prior to starting therapy. Automated BSI, prostate......-specific antigen (PSA), hemoglobin (HgB), and alkaline phosphatase (ALP) were obtained at baseline. Change in automated BSI and PSA were obtained from patients who have had bone scan at week 12 of treatment follow-up. Automated BSI was obtained using the analytically validated EXINI Bone(BSI) version 2. Kendall...

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2012-02-01

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

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

    OpenAIRE

    Kooren Joel A; Rhodus Nelson L; Tang Chuanning; Jagtap Pratik D; Horrigan Bryan J; Griffin Timothy J

    2011-01-01

    Abstract Introduction Early diagnosis of Oral Squamous Cell Carcinoma (OSCC) increases the survival rate of oral cancer. For early diagnosis, molecular biomarkers contained in samples collected non-invasively and directly from at-risk oral premalignant lesions (OPMLs) would be ideal. Methods In this pilot study we evaluated the potential of a novel method using commercial PerioPaper absorbent strips for non-invasive collection of oral lesion exudate material coupled with mass spectrometry-bas...

  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. 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. PMID:25322901

  3. Biomarkers for pancreatic carcinogenesis

    OpenAIRE

    Hustinx, S.R.

    2007-01-01

    Pancreatic cancer is a devastating disease. Most pancreatic cancers (approximately 85%) are diagnosed at a late, incurable stage. The poor prognosis and late presentation of pancreatic cancer patients underscore the importance of early detection, which is the sine qua non for the fight against pancreatic cancer. It is hoped for the future that the understanding of genetic alterations will lead to the rapid discovery of an effective biomarker of pancreatic carcinogenesis. In this thesis we vis...

  4. Evaluation of reverse phase protein array (RPPA)-based pathway-activation profiling in 84 non-small cell lung cancer (NSCLC) cell lines as platform for cancer proteomics and biomarker discovery.

    Science.gov (United States)

    Ummanni, Ramesh; Mannsperger, Heiko A; Sonntag, Johanna; Oswald, Marcus; Sharma, Ashwini K; König, Rainer; Korf, Ulrike

    2014-05-01

    The reverse phase protein array (RPPA) approach was employed for a quantitative analysis of 71 cancer-relevant proteins and phosphoproteins in 84 non-small cell lung cancer (NSCLC) cell lines and by monitoring the activation state of selected receptor tyrosine kinases, PI3K/AKT and MEK/ERK1/2 signaling, cell cycle control, apoptosis, and DNA damage. Additional information on NSCLC cell lines such as that of transcriptomic data, genomic aberrations, and drug sensitivity was analyzed in the context of proteomic data using supervised and non-supervised approaches for data analysis. First, the unsupervised analysis of proteomic data indicated that proteins clustering closely together reflect well-known signaling modules, e.g. PI3K/AKT- and RAS/RAF/ERK-signaling, cell cycle regulation, and apoptosis. However, mutations of EGFR, ERBB2, RAF, RAS, TP53, and PI3K were found dispersed across different signaling pathway clusters. Merely cell lines with an amplification of EGFR and/or ERBB2 clustered closely together on the proteomic, but not on the transcriptomic level. Secondly, supervised data analysis revealed that sensitivity towards anti-EGFR drugs generally correlated better with high level EGFR phosphorylation than with EGFR abundance itself. High level phosphorylation of RB and high abundance of AURKA were identified as candidates that can potentially predict sensitivity towards the aurora kinase inhibitor VX680. Examples shown demonstrate that the RPPA approach presents a useful platform for targeted proteomics with high potential for biomarker discovery. This article is part of a Special Issue entitled: Biomarkers: A Proteomic Challenge. PMID:24361481

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

    Science.gov (United States)

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

    2014-09-01

    A repeat expansion in C9ORF72 causes frontotemporal dementia and amyotrophic lateral sclerosis (c9FTD/ALS). RNA of the expanded repeat (r(GGGGCC)exp) forms nuclear foci or undergoes repeat-associated non-ATG (RAN) translation, producing "c9RAN proteins." Since neutralizing r(GGGGCC)exp could inhibit these potentially toxic events, we sought to identify small-molecule binders of r(GGGGCC)exp. Chemical and enzymatic probing of r(GGGGCC)8 indicate that it adopts a hairpin structure in equilibrium with a quadruplex structure. Using this model, bioactive small molecules targeting r(GGGGCC)exp were designed and found to significantly inhibit RAN translation and foci formation in cultured cells expressing r(GGGGCC)66 and neurons transdifferentiated from fibroblasts of repeat expansion carriers. Finally, we show that poly(GP) c9RAN proteins are specifically detected in c9ALS patient cerebrospinal fluid. Our findings highlight r(GGGGCC)exp-binding small molecules as a possible c9FTD/ALS therapeutic and suggest that c9RAN proteins could potentially serve as a pharmacodynamic biomarker to assess efficacy of therapies that target r(GGGGCC)exp. PMID:25132468

  6. Discovery of a Biomarker and Lead Small Molecules to Target r(GGGGCC)-Associated Defects in c9FTD/ALS

    Science.gov (United States)

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

    2014-01-01

    Summary A repeat expansion in C9ORF72 causes frontotemporal dementia and amyotrophic lateral sclerosis (c9FTD/ALS). RNA of the expanded repeat (r(GGGGCC)exp) forms nuclear foci or undergoes repeat-associated non-ATG (RAN) translation producing “c9RAN proteins”. Since neutralizing r(GGGGCC)exp could inhibit these potentially toxic events, we sought to identify small molecule binders of r(GGGGCC)exp. Chemical and enzymatic probing of r(GGGGCC)8 indicate it adopts a hairpin structure in equilibrium with a quadruplex structure. Using this model, bioactive small molecules targeting r(GGGGCC)exp were designed and found to significantly inhibit RAN translation and foci formation in cultured cells expressing r(GGGGCC)66 and neurons trans-differentiated from fibroblasts of repeat expansion carriers. Finally, we show that poly(GP) c9RAN proteins are specifically detected in c9ALS patient cerebrospinal fluid. Our findings highlight r(GGGGCC)exp-binding small molecules as a possible c9FTD/ALS therapeutic, and suggest c9RAN proteins could potentially serve as a pharmacodynamic biomarker to assess efficacy of therapies that target r(GGGGCC)exp. PMID:25132468

  7. Automated Voxel-Based Analysis of Volumetric Dynamic Contrast-Enhanced CT Data Improves Measurement of Serial Changes in Tumor Vascular Biomarkers

    International Nuclear Information System (INIS)

    Objectives: Development of perfusion imaging as a biomarker requires more robust methodologies for quantification of tumor physiology that allow assessment of volumetric tumor heterogeneity over time. This study proposes a parametric method for automatically analyzing perfused tissue from volumetric dynamic contrast-enhanced (DCE) computed tomography (CT) scans and assesses whether this 4-dimensional (4D) DCE approach is more robust and accurate than conventional, region-of-interest (ROI)-based CT methods in quantifying tumor perfusion with preliminary evaluation in metastatic brain cancer. Methods and Materials: Functional parameter reproducibility and analysis of sensitivity to imaging resolution and arterial input function were evaluated in image sets acquired from a 320-slice CT with a controlled flow phantom and patients with brain metastases, whose treatments were planned for stereotactic radiation surgery and who consented to a research ethics board-approved prospective imaging biomarker study. A voxel-based temporal dynamic analysis (TDA) methodology was used at baseline, at day 7, and at day 20 after treatment. The ability to detect changes in kinetic parameter maps in clinical data sets was investigated for both 4D TDA and conventional 2D ROI-based analysis methods. Results: A total of 7 brain metastases in 3 patients were evaluated over the 3 time points. The 4D TDA method showed improved spatial efficacy and accuracy of perfusion parameters compared to ROI-based DCE analysis (P<.005), with a reproducibility error of less than 2% when tested with DCE phantom data. Clinically, changes in transfer constant from the blood plasma into the extracellular extravascular space (Ktrans) were seen when using TDA, with substantially smaller errors than the 2D method on both day 7 post radiation surgery (±13%; P<.05) and by day 20 (±12%; P<.04). Standard methods showed a decrease in Ktrans but with large uncertainty (111.6 ± 150.5) %. Conclusions: Parametric

  8. Automated Voxel-Based Analysis of Volumetric Dynamic Contrast-Enhanced CT Data Improves Measurement of Serial Changes in Tumor Vascular Biomarkers

    Energy Technology Data Exchange (ETDEWEB)

    Coolens, Catherine, E-mail: catherine.coolens@rmp.uhn.on.ca [Radiation Medicine Program, Princess Margaret Cancer Center and University Health Network, Toronto, Ontario (Canada); Department of Radiation Oncology, University of Toronto, Toronto, Ontario (Canada); Institute of Biomaterials and Biomedical Engineering, University of Toronto, Toronto, Ontario (Canada); Driscoll, Brandon [Radiation Medicine Program, Princess Margaret Cancer Center and University Health Network, Toronto, Ontario (Canada); Chung, Caroline [Radiation Medicine Program, Princess Margaret Cancer Center and University Health Network, Toronto, Ontario (Canada); Department of Radiation Oncology, University of Toronto, Toronto, Ontario (Canada); Shek, Tina; Gorjizadeh, Alborz [Radiation Medicine Program, Princess Margaret Cancer Center and University Health Network, Toronto, Ontario (Canada); Ménard, Cynthia [Radiation Medicine Program, Princess Margaret Cancer Center and University Health Network, Toronto, Ontario (Canada); Department of Radiation Oncology, University of Toronto, Toronto, Ontario (Canada); Jaffray, David [Radiation Medicine Program, Princess Margaret Cancer Center and University Health Network, Toronto, Ontario (Canada); Department of Radiation Oncology, University of Toronto, Toronto, Ontario (Canada); Institute of Biomaterials and Biomedical Engineering, University of Toronto, Toronto, Ontario (Canada)

    2015-01-01

    Objectives: Development of perfusion imaging as a biomarker requires more robust methodologies for quantification of tumor physiology that allow assessment of volumetric tumor heterogeneity over time. This study proposes a parametric method for automatically analyzing perfused tissue from volumetric dynamic contrast-enhanced (DCE) computed tomography (CT) scans and assesses whether this 4-dimensional (4D) DCE approach is more robust and accurate than conventional, region-of-interest (ROI)-based CT methods in quantifying tumor perfusion with preliminary evaluation in metastatic brain cancer. Methods and Materials: Functional parameter reproducibility and analysis of sensitivity to imaging resolution and arterial input function were evaluated in image sets acquired from a 320-slice CT with a controlled flow phantom and patients with brain metastases, whose treatments were planned for stereotactic radiation surgery and who consented to a research ethics board-approved prospective imaging biomarker study. A voxel-based temporal dynamic analysis (TDA) methodology was used at baseline, at day 7, and at day 20 after treatment. The ability to detect changes in kinetic parameter maps in clinical data sets was investigated for both 4D TDA and conventional 2D ROI-based analysis methods. Results: A total of 7 brain metastases in 3 patients were evaluated over the 3 time points. The 4D TDA method showed improved spatial efficacy and accuracy of perfusion parameters compared to ROI-based DCE analysis (P<.005), with a reproducibility error of less than 2% when tested with DCE phantom data. Clinically, changes in transfer constant from the blood plasma into the extracellular extravascular space (K{sub trans}) were seen when using TDA, with substantially smaller errors than the 2D method on both day 7 post radiation surgery (±13%; P<.05) and by day 20 (±12%; P<.04). Standard methods showed a decrease in K{sub trans} but with large uncertainty (111.6 ± 150.5) %. Conclusions

  9. Highly selective and automated online SPE LC-MS3 method for determination of cortisol and cortisone in human hair as biomarker for stress related diseases.

    Science.gov (United States)

    Quinete, Natalia; Bertram, Jens; Reska, Marcus; Lang, Jessica; Kraus, Thomas

    2015-03-01

    Hair analysis has been increasingly used to establish long-term biomarkers of exposure to both endogenous and exogenous substances, with a special emphasis on steroidal hormones. Hair cortisol and cortisone have been associated to physiological and psychological strains, anxiety and depression. Hair is a very complex matrix, which might jeopardize analyte detection at low concentrations. A new, highly selective and sensitive method based on fragments of second order, MS(3) (MS/MS/MS), was developed and validated for the analysis of hair cortisol and cortisone. An online solid phase extraction was performed on a C8 restricted access material (RAM) phase following by separation on a reversed-phase C18 column using methanol and 0.02% ammonium hydroxide as mobile phase. The developed method required minimal sample preparation and the injection of only 50 µL of sample leading to a LOQ of 2 pg mg(-1). Good linear responses were observed in the range 2-200 pg mg(-1) (R(2)>0.99) and extraction recoveries ranged between 77-125% and 70-123% for cortisol and cortisone, respectively. Intra- and inter-assay coefficients of variation were between 1.4 and 14%. In order to evaluate the applicability of the method, preliminary tests (N=33) were conducted in 3 cm hair samples (close to scalp) of healthy volunteers with an age range of 4-63. Average concentrations in hair were 12.7±14 pg mg(-1) and 41.6±42 pg mg(-1) for cortisol and cortisone, respectively. Further investigations on cortisol and cortisone as biomarkers for chronic psychological strain will be assessed as a next step. PMID:25618673

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

    Directory of Open Access Journals (Sweden)

    Al-Hasani Hadi

    2011-05-01

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

  11. Biomarkers: A Challenging Conundrum in Cardiovascular Disease.

    Science.gov (United States)

    Libby, Peter; King, Kevin

    2015-12-01

    The use of biomarkers has proven utility in cardiovascular medicine and holds great promise for future advances, but their application requires considerable rigor in thinking and methodology. Numerous confounding factors can cloud the clinical and investigative uses of biomarkers. Yet, the thoughtful and critical use of biomarkers can doubtless aid discovery of new pathogenic pathways, identify novel therapeutic targets, and provide a bridge between the laboratory and the clinic. Biomarkers can provide diagnostic and prognostic tools to the practitioner. The careful application of biomarkers can also help design and guide clinical trials required to establish the efficacy of novel interventions to improve patient outcomes. Point of care testing, technological advances, such as microfluidic and wearable devices, and the power of omics approaches all promise to elevate the potential contributions of biomarkers to discovery science, translation, clinical trials, and the practice of cardiovascular medicine. PMID:26543097

  12. Fluid biomarkers in multiple system atrophy

    DEFF Research Database (Denmark)

    Laurens, Brice; Constantinescu, Radu; Freeman, Roy;

    2015-01-01

    Despite growing research efforts, no reliable biomarker currently exists for the diagnosis and prognosis of multiple system atrophy (MSA). Such biomarkers are urgently needed to improve diagnostic accuracy, prognostic guidance and also to serve as efficacy measures or surrogates of target engagem...... Parkinson's disease), metabolites of the catecholamine pathway and proteins such as α-synuclein, DJ-1 and total-tau. Beyond future efforts in biomarker discovery, the harmonization of standard operating procedures will be crucial for future success....

  13. Automated security management

    CERN Document Server

    Al-Shaer, Ehab; Xie, Geoffrey

    2013-01-01

    In this contributed volume, leading international researchers explore configuration modeling and checking, vulnerability and risk assessment, configuration analysis, and diagnostics and discovery. The authors equip readers to understand automated security management systems and techniques that increase overall network assurability and usability. These constantly changing networks defend against cyber attacks by integrating hundreds of security devices such as firewalls, IPSec gateways, IDS/IPS, authentication servers, authorization/RBAC servers, and crypto systems. Automated Security Managemen

  14. Automated tumor analysis for molecular profiling in lung cancer.

    Science.gov (United States)

    Hamilton, Peter W; Wang, Yinhai; Boyd, Clinton; James, Jacqueline A; Loughrey, Maurice B; Hougton, Joseph P; Boyle, David P; Kelly, Paul; Maxwell, Perry; McCleary, David; Diamond, James; McArt, Darragh G; Tunstall, Jonathon; Bankhead, Peter; Salto-Tellez, Manuel

    2015-09-29

    The discovery and clinical application of molecular biomarkers in solid tumors, increasingly relies on nucleic acid extraction from FFPE tissue sections and subsequent molecular profiling. This in turn requires the pathological review of haematoxylin & eosin (H&E) stained slides, to ensure sample quality, tumor DNA sufficiency by visually estimating the percentage tumor nuclei and tumor annotation for manual macrodissection. In this study on NSCLC, we demonstrate considerable variation in tumor nuclei percentage between pathologists, potentially undermining the precision of NSCLC molecular evaluation and emphasising the need for quantitative tumor evaluation. We subsequently describe the development and validation of a system called TissueMark for automated tumor annotation and percentage tumor nuclei measurement in NSCLC using computerized image analysis. Evaluation of 245 NSCLC slides showed precise automated tumor annotation of cases using Tissuemark, strong concordance with manually drawn boundaries and identical EGFR mutational status, following manual macrodissection from the image analysis generated tumor boundaries. Automated analysis of cell counts for % tumor measurements by Tissuemark showed reduced variability and significant correlation (p tissue samples for molecular profiling in discovery and diagnostics. PMID:26317646

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

    Energy Technology Data Exchange (ETDEWEB)

    Gomes, Tânia, E-mail: 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.

  16. Label-free LC-MS method for the identification of biomarkers.

    Science.gov (United States)

    Higgs, Richard E; Knierman, Michael D; Gelfanova, Valentina; Butler, Jon P; Hale, John E

    2008-01-01

    Pharmaceutical companies and regulatory agencies are pursuing biomarkers as a means to increase the productivity of drug development. Quantifying differential levels of proteins from complex biological samples like plasma or cerebrospinal fluid is one specific approach being used to identify markers of drug action, efficacy, toxicity, etc. Academic investigators are also interested in markers that are diagnostic or prognostic of disease states. We report a comprehensive, fully automated, and label-free approach to relative protein quantification including: sample preparation, proteolytic protein digestion, LCMS/MS data acquisition, de-noising, mass and charge state estimation, chromatographic alignment, and peptide quantification via integration of extracted ion chromatograms. Additionally, we describe methods for transformation and normalization of the quantitative peptide levels in multiplexed measurements to improve precision for statistical analysis. Lastly, we outline how the described methods can be used to design and power biomarker discovery studies. PMID:18287776

  17. Biomarkers for Colorectal Cancer

    Directory of Open Access Journals (Sweden)

    Rikako Ishigamori

    2010-09-01

    Full Text Available Colorectal cancer (CRC is the third most common epithelial malignancy in the world. Since CRC develops slowly from removable precancerous lesions, detection of the lesion at an early stage by regular health examinations can reduce the incidence and mortality of this malignancy. Colonoscopy significantly improves the detection rate of CRC, but the examination is expensive and inconvenient. Therefore, we need novel biomarkers that are non-invasive to enable us to detect CRC quite early. A number of validation studies have been conducted to evaluate genetic, epigenetic or protein markers for identification in the stool and/or serum. Currently, the fecal occult blood test is the most widely used method of screening for CRC. However, advances in genomics and proteomics will lead to the discovery of novel non-invasive biomarkers.

  18. Biomarkers for hepatocellular carcinoma.

    Science.gov (United States)

    Behne, Tara; Copur, M Sitki

    2012-01-01

    The hepatocellular carcinoma (HCC) is one of the most common malignant tumors and carries a poor survival rate. The management of patients at risk for developing HCC remains challenging. Increased understanding of cancer biology and technological advances have enabled identification of a multitude of pathological, genetic, and molecular events that drive hepatocarcinogenesis leading to discovery of numerous potential biomarkers in this disease. They are currently being aggressively evaluated to establish their value in early diagnosis, optimization of therapy, reducing the emergence of new tumors, and preventing the recurrence after surgical resection or liver transplantation. These markers not only help in prediction of prognosis or recurrence but may also assist in deciding appropriate modality of therapy and may represent novel potential targets for therapeutic interventions. In this paper, a summary of most relevant available data from published papers reporting various tissue and serum biomarkers involved in hepatocellular carcinoma was presented. PMID:22655201

  19. Aberrant glycosylation associated with enzymes as cancer biomarkers

    Directory of Open Access Journals (Sweden)

    Meany Danni L

    2011-06-01

    Full Text Available Abstract Background One of the new roles for enzymes in personalized medicine builds on a rational approach to cancer biomarker discovery using enzyme-associated aberrant glycosylation. A hallmark of cancer, aberrant glycosylation is associated with differential expressions of enzymes such as glycosyltransferase and glycosidases. The aberrant expressions of the enzymes in turn cause cancer cells to produce glycoproteins with specific cancer-associated aberrations in glycan structures. Content In this review we provide examples of cancer biomarker discovery using aberrant glycosylation in three areas. First, changes in glycosylation machinery such as glycosyltransferases/glycosidases could be used as cancer biomarkers. Second, most of the clinically useful cancer biomarkers are glycoproteins. Discovery of specific cancer-associated aberrations in glycan structures of these existing biomarkers could improve their cancer specificity, such as the discovery of AFP-L3, fucosylated glycoforms of AFP. Third, cancer-associated aberrations in glycan structures provide a compelling rationale for discovering new biomarkers using glycomic and glycoproteomic technologies. Summary As a hallmark of cancer, aberrant glycosylation allows for the rational design of biomarker discovery efforts. But more important, we need to translate these biomarkers from discovery to clinical diagnostics using good strategies, such as the lessons learned from translating the biomarkers discovered using proteomic technologies to OVA 1, the first FDA-cleared In Vitro Diagnostic Multivariate Index Assay (IVDMIA. These lessons, providing important guidance in current efforts in biomarker discovery and translation, are applicable to the discovery of aberrant glycosylation associated with enzymes as cancer biomarkers as well.

  20. Application of an automated natural language processing (NLP) workflow to enable federated search of external biomedical content in drug discovery and development.

    Science.gov (United States)

    McEntire, Robin; Szalkowski, Debbie; Butler, James; Kuo, Michelle S; Chang, Meiping; Chang, Man; Freeman, Darren; McQuay, Sarah; Patel, Jagruti; McGlashen, Michael; Cornell, Wendy D; Xu, Jinghai James

    2016-05-01

    External content sources such as MEDLINE(®), National Institutes of Health (NIH) grants and conference websites provide access to the latest breaking biomedical information, which can inform pharmaceutical and biotechnology company pipeline decisions. The value of the sites for industry, however, is limited by the use of the public internet, the limited synonyms, the rarity of batch searching capability and the disconnected nature of the sites. Fortunately, many sites now offer their content for download and we have developed an automated internal workflow that uses text mining and tailored ontologies for programmatic search and knowledge extraction. We believe such an efficient and secure approach provides a competitive advantage to companies needing access to the latest information for a range of use cases and complements manually curated commercial sources. PMID:26979546

  1. Proteomic Approaches for Biomarker Panels in Cancer.

    Science.gov (United States)

    Tanase, Cristiana; Albulescu, Radu; Neagu, Monica

    2016-01-01

    Proteomic technologies remain the main backbone of biomarkers discovery in cancer. The continuous development of proteomic technologies also enlarges the bioinformatics domain, thus founding the main pillars of cancer therapy. The main source for diagnostic/prognostic/therapy monitoring biomarker panels are molecules that have a dual role, being both indicators of disease development and therapy targets. Proteomic technologies, such as mass-spectrometry approaches and protein array technologies, represent the main technologies that can depict these biomarkers. Herein, we will illustrate some of the most recent strategies for biomarker discovery in cancer, including the development of immune-markers and the use of cancer stem cells as target therapy. The challenges of proteomic biomarker discovery need new forms of cross-disciplinary conglomerates that will result in increased and tailored access to treatments for patients; diagnostic companies would benefit from the enhanced co-development of companion diagnostics and pharmaceutical companies. In the technology optimization in biomarkers, immune assays are the leaders of discovery machinery. PMID:26565430

  2. Using Aptamers for Cancer Biomarker Discovery

    OpenAIRE

    Yun Min Chang; Donovan, Michael J; Weihong Tan

    2013-01-01

    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...

  3. Urine protein concentration estimation for biomarker discovery.

    Science.gov (United States)

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

    2013-10-01

    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-acid assay, which performed particularly poorly at higher protein concentrations. These data highlight the need to use amino-acid or BCA assays for unprocessed urine protein estimation. PMID:26103798

  4. Proteomics in biomarker discovery and drug development

    OpenAIRE

    He, Q.; Chiu, J

    2003-01-01

    Proteomics is a research field aiming to characterize molecular and cellular dynamics in protein expression and function on a global level. The introduction of proteomics has been greatly broadening our view and accelerating our path in various medical researches. The most significant advantage of proteomics is its ability to examine a whole proteome or sub-proteome in a single experiment so that the protein alterations corresponding to a pathological or biochemical condition at a given time ...

  5. Plasma proteomics to identify biomarkers – application to cardiovascular diseases

    Directory of Open Access Journals (Sweden)

    Hans Christian Beck

    2015-06-01

    Full Text Available 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 to the discovery of novel cardiovascular biomarkers.

  6. Biomarkers in precision therapy in colorectal cancer

    OpenAIRE

    Reimers, Marlies S.; Zeestraten, Eliane C.M.; Kuppen, Peter J.K.; Liefers, Gerrit Jan; van de Velde, Cornelis J. H.

    2013-01-01

    Colorectal cancer (CRC) is the most commonly diagnosed cancer in Europe. Because CRC is also a major cause of cancer-related deaths worldwide, a lot of research has been focused on the discovery and development of biomarkers to improve the diagnostic process and to predict treatment outcomes. Up till now only a few biomarkers are recommended by expert panels. Current TNM criteria, however, cause substantial under- and overtreatment of CRC patients. Consequently, there is a growing need for ne...

  7. Imaging Biomarkers or Biomarker Imaging?

    Directory of Open Access Journals (Sweden)

    Markus Mitterhauser

    2014-06-01

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

  8. Home Automation

    OpenAIRE

    Ahmed, Zeeshan

    2010-01-01

    In this paper I briefly discuss the importance of home automation system. Going in to the details I briefly present a real time designed and implemented software and hardware oriented house automation research project, capable of automating house's electricity and providing a security system to detect the presence of unexpected behavior.

  9. A new strategy for faster urinary biomarkers identification by Nano LC MALDI TOF/TOF mass spectrometry.

    OpenAIRE

    Le Meur Y; Rérolle JP; Marquet P.; Benkali K; Gastinel LN

    2008-01-01

    Abstract Background LC-MALDI-TOF/TOF analysis is a potent tool in biomarkers discovery characterized by its high sensitivity and high throughput capacity. However, methods based on MALDI-TOF/TOF for biomarkers discovery still need optimization, in particular to reduce analysis time and to evaluate their reproducibility for peak intensities measurement. The aims of this methodological study were: (i) to optimize and critically evaluate each step of urine biomarker discovery method based on Nan...

  10. Novel diagnostic biomarkers for prostate cancer

    Directory of Open Access Journals (Sweden)

    Chikezie O. Madu, Yi Lu

    2010-01-01

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

  11. Translation of neurological biomarkers to clinically relevant platforms.

    Science.gov (United States)

    Hayes, Ronald L; Robinson, Gillian; Muller, Uwe; Wang, Kevin K W

    2009-01-01

    Like proteomics more generally, neuroproteomics has recently been linked to the discovery of biochemical markers of central nervous system (CNS) injury and disease. Although neuroproteomics has enjoyed considerable success in discovery of candidate biomarkers, there are a number of challenges facing investigators interested in developing clinically useful platforms to assess biomarkers for damage to the CNS. These challenges include intrinsic physiological complications such as the blood-brain barrier. Effective translation of biomarkers to clinical practice also requires development of entirely novel pathways and product development strategies. Drawing from lessons learned from applications of biomarkers to traumatic brain injury, this study outlines major elements of such a pathway. As with other indications, biomarkers can have three major areas of application: (1) drug development; (2) diagnosis and prognosis; (3) patient management. Translation of CNS biomarkers to practical clinical platforms raises a number of integrated elements. Biomarker discovery and initial selection needs to be integrated at the earliest stages with components that will allow systematic prioritization and triage of biomarker candidates. A number of important criteria need to be considered in selecting clinical biomarker candidates. Development of proof of concept assays and their optimization and validation represent an often overlooked feature of biomarker translational research. Initial assay optimization should confirm that assays can detect biomarkers in relevant clinical samples. Since access to human clinical samples is critical to identification of biomarkers relevant to injury and disease as well as for assay development, design of human clinical validation studies is an important component of translational biomarker research platforms. Although these clinical studies share much in common with clinical trials for assessment of drug therapeutic efficacy, there are a number of

  12. 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

    2015-05-15

    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

  13. 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.

  14. 76 FR 82306 - Draft Guidance for Industry on Use of Histology in Biomarker Qualification Studies; Availability

    Science.gov (United States)

    2011-12-30

    ... biomarker studies, and outlines the scientific standards for histology used in biomarker characterization... Spring, MD 20993-0002. Send one self-addressed adhesive label to assist that office in processing your....'' The discovery, characterization, qualification, and implementation of biomarkers have been...

  15. The Automated Discovery of Hybrid Processes

    DEFF Research Database (Denmark)

    Slaats, Tijs; Reijers, Hajo; Maggi, Fabrizio Maria

    2014-01-01

    technique for discovering from an event log a so-called hybrid process model. A hybrid process model is hierarchical, where each of its sub-processes may be specified in a declarative or procedural fashion. We have implemented the proposed approach as a plug-in of the ProM platform. To evaluate the approach......, we used our plug-in to mine a real-life log from a financial context....

  16. The Automated Discovery of Hybrid Processes

    DEFF Research Database (Denmark)

    Slaats, Tijs; Reijers, Hajo; Maggi, Fabrizio Maria

    2014-01-01

    The declarative-procedural dichotomy is highly relevant when choosing the most suitable process modeling language to represent a discovered process. Less-structured processes with a high level of variability can be described in a more compact way using a declarative language. By contrast, procedu...

  17. Automated Discovery of Flight Track Anomalies

    Data.gov (United States)

    National Aeronautics and Space Administration — As new technologies are developed to handle the complexities of the Next Generation Air Transportation System (NextGen), it is increasingly important to address...

  18. Automating Information Discovery Within the Invisible Web

    Science.gov (United States)

    Sweeney, Edwina; Curran, Kevin; Xie, Ermai

    A Web crawler or spider crawls through the Web looking for pages to index, and when it locates a new page it passes the page on to an indexer. The indexer identifies links, keywords, and other content and stores these within its database. This database is searched by entering keywords through an interface and suitable Web pages are returned in a results page in the form of hyperlinks accompanied by short descriptions. The Web, however, is increasingly moving away from being a collection of documents to a multidimensional repository for sounds, images, audio, and other formats. This is leading to a situation where certain parts of the Web are invisible or hidden. The term known as the "Deep Web" has emerged to refer to the mass of information that can be accessed via the Web but cannot be indexed by conventional search engines. The concept of the Deep Web makes searches quite complex for search engines. Google states that the claim that conventional search engines cannot find such documents as PDFs, Word, PowerPoint, Excel, or any non-HTML page is not fully accurate and steps have been taken to address this problem by implementing procedures to search items such as academic publications, news, blogs, videos, books, and real-time information. However, Google still only provides access to a fraction of the Deep Web. This chapter explores the Deep Web and the current tools available in accessing it.

  19. Automated motif discovery from glycan array data.

    Science.gov (United States)

    Cholleti, Sharath R; Agravat, Sanjay; Morris, Tim; Saltz, Joel H; Song, Xuezheng; Cummings, Richard D; Smith, David F

    2012-10-01

    Assessing interactions of a glycan-binding protein (GBP) or lectin with glycans on a microarray generates large datasets, making it difficult to identify a glycan structural motif or determinant associated with the highest apparent binding strength of the GBP. We have developed a computational method, termed GlycanMotifMiner, that uses the relative binding of a GBP with glycans within a glycan microarray to automatically reveal the glycan structural motifs recognized by a GBP. We implemented the software with a web-based graphical interface for users to explore and visualize the discovered motifs. The utility of GlycanMotifMiner was determined using five plant lectins, SNA, HPA, PNA, Con A, and UEA-I. Data from the analyses of the lectins at different protein concentrations were processed to rank the glycans based on their relative binding strengths. The motifs, defined as glycan substructures that exist in a large number of the bound glycans and few non-bound glycans, were then discovered by our algorithm and displayed in a web-based graphical user interface ( http://glycanmotifminer.emory.edu ). The information is used in defining the glycan-binding specificity of GBPs. The results were compared to the known glycan specificities of these lectins generated by manual methods. A more complex analysis was also carried out using glycan microarray data obtained for a recombinant form of human galectin-8. Results for all of these lectins show that GlycanMotifMiner identified the major motifs known in the literature along with some unexpected novel binding motifs. PMID:22877213

  20. Automated methods of corrosion measurement

    DEFF Research Database (Denmark)

    Andersen, Jens Enevold Thaulov; Bech-Nielsen, Gregers; Reeve, John Ch;

    1997-01-01

    to revise assumptions regarding the basis of the method, which sometimes leads to the discovery of as-yet unnoticed phenomena. The present selection of automated methods for corrosion measurements is not motivated simply by the fact that a certain measurement can be performed automatically...

  1. 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.

  2. Biomarkers of An Autoimmune Skin Disease-Psoriasis

    Institute of Scientific and Technical Information of China (English)

    Shan Jiang; Taylor E Hinchliffe; Tianfu Wu

    2015-01-01

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

  3. Higgs Discovery

    DEFF Research Database (Denmark)

    Sannino, Francesco

    2013-01-01

    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 a...... 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...

  4. Volatility Discovery

    DEFF Research Database (Denmark)

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

    There is a large literature that investigates how homogenous securities traded on different markets incorporate new information (price discovery analysis). We extend this concept to the stochastic volatility process and investigate how markets contribute to the efficient stochastic volatility whi...

  5. Library Automation

    OpenAIRE

    Dhakne, B. N.; Giri, V. V; Waghmode, S. S.

    2010-01-01

    New technologies library provides several new materials, media and mode of storing and communicating the information. Library Automation reduces the drudgery of repeated manual efforts in library routine. By use of library automation collection, Storage, Administration, Processing, Preservation and communication etc.

  6. Quantitative imaging biomarker ontology (QIBO) for knowledge representation of biomedical imaging biomarkers.

    Science.gov (United States)

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

    2013-08-01

    A widening array of novel imaging biomarkers is being developed using ever more powerful clinical and preclinical imaging modalities. These biomarkers have demonstrated effectiveness in quantifying biological processes as they occur in vivo and in the early prediction of therapeutic outcomes. However, quantitative imaging biomarker data and knowledge are not standardized, representing a critical barrier to accumulating medical knowledge based on quantitative imaging data. We use an ontology to represent, integrate, and harmonize heterogeneous knowledge across the domain of imaging biomarkers. This advances the goal of developing applications to (1) improve precision and recall of storage and retrieval of quantitative imaging-related data using standardized terminology; (2) streamline the discovery and development of novel imaging biomarkers by normalizing knowledge across heterogeneous resources; (3) effectively annotate imaging experiments thus aiding comprehension, re-use, and reproducibility; and (4) provide validation frameworks through rigorous specification as a basis for testable hypotheses and compliance tests. We have developed the Quantitative Imaging Biomarker Ontology (QIBO), which currently consists of 488 terms spanning the following upper classes: experimental subject, biological intervention, imaging agent, imaging instrument, image post-processing algorithm, biological target, indicated biology, and biomarker application. We have demonstrated that QIBO can be used to annotate imaging experiments with standardized terms in the ontology and to generate hypotheses for novel imaging biomarker-disease associations. Our results established the utility of QIBO in enabling integrated analysis of quantitative imaging data. PMID:23589184

  7. 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.

  8. Automated Motivic Analysis

    DEFF Research Database (Denmark)

    Lartillot, Olivier

    2016-01-01

    Motivic analysis provides very detailed understanding of musical composi- tions, but is also particularly difficult to formalize and systematize. A computational automation of the discovery of motivic patterns cannot be reduced to a mere extraction of all possible sequences of descriptions....... The systematic approach inexorably leads to a proliferation of redundant structures that needs to be addressed properly. Global filtering techniques cause a drastic elimination of interesting structures that damages the quality of the analysis. On the other hand, a selection of closed patterns allows...

  9. Process automation

    International Nuclear Information System (INIS)

    Process automation technology has been pursued in the chemical processing industries and to a very limited extent in nuclear fuel reprocessing. Its effective use has been restricted in the past by the lack of diverse and reliable process instrumentation and the unavailability of sophisticated software designed for process control. The Integrated Equipment Test (IET) facility was developed by the Consolidated Fuel Reprocessing Program (CFRP) in part to demonstrate new concepts for control of advanced nuclear fuel reprocessing plants. A demonstration of fuel reprocessing equipment automation using advanced instrumentation and a modern, microprocessor-based control system is nearing completion in the facility. This facility provides for the synergistic testing of all chemical process features of a prototypical fuel reprocessing plant that can be attained with unirradiated uranium-bearing feed materials. The unique equipment and mission of the IET facility make it an ideal test bed for automation studies. This effort will provide for the demonstration of the plant automation concept and for the development of techniques for similar applications in a full-scale plant. A set of preliminary recommendations for implementing process automation has been compiled. Some of these concepts are not generally recognized or accepted. The automation work now under way in the IET facility should be useful to others in helping avoid costly mistakes because of the underutilization or misapplication of process automation. 6 figs

  10. Biomarkers in Parkinson's disease (recent update).

    Science.gov (United States)

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

    2013-09-01

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

  11. Beyond Discovery

    DEFF Research Database (Denmark)

    Korsgaard, Steffen; Sassmannshausen, Sean Patrick

    2015-01-01

    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 as their...... central concepts and conceptualization of the entrepreneurial function. On this basis we discuss three central themes that cut across the four alternatives: process, uncertainty, and agency. These themes provide new foci for entrepreneurship research and can help to generate new research questions and...

  12. 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.

  13. Towards Robot Scientists for autonomous scientific discovery

    OpenAIRE

    Sparkes, Andrew; Aubrey, Wayne; Byrne, Emma; Clare, Amanda; Khan, Muhammed N; Liakata, Maria; Markham, Magdalena; Rowland, Jem; Soldatova, Larisa N.; Whelan, Kenneth E; Young, Michael; King, Ross D.

    2010-01-01

    We review the main components of autonomous scientific discovery, and how they lead to the concept of a Robot Scientist. This is a system which uses techniques from artificial intelligence to automate all aspects of the scientific discovery process: it generates hypotheses from a computer model of the domain, designs experiments to test these hypotheses, runs the physical experiments using robotic systems, analyses and interprets the resulting data, and repeats the cycle. We describe our two ...

  14. 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....

  15. Biomarkers in Computational Toxicology

    Science.gov (United States)

    Biomarkers are a means to evaluate chemical exposure and/or the subsequent impacts on toxicity pathways that lead to adverse health outcomes. Computational toxicology can integrate biomarker data with knowledge of exposure, chemistry, biology, pharmacokinetics, toxicology, and e...

  16. 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

    Science.gov (United States)

    Emanueli, Costanza; Fiorentino, Francesca; Reeves, Barnaby C.; Beltrami, Cristina; Mumford, Andrew; Clayton, Aled; Gurney, Mark; Shantikumar, Saran; Angelini, Gianni D.

    2016-01-01

    Introduction 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. Methods and Results 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. Conclusions 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. PMID:27128471

  17. Discovery of new natural products by application of X-hitting, a novel algorithm for automated comparison of full UV-spectra, combined with structural determination by NMR spectroscophy

    DEFF Research Database (Denmark)

    Larsen, Thomas Ostenfeld; Petersen, Bent O.; Duus, Jens Øllgaard;

    2005-01-01

    X-hitting, a newly developed algorithm for automated comparison of UV data, has been used for the tracking of two novel spiro-quinazoline metabolites, lapatins A (1)andB(2), in a screening study targeting quinazolines. The structures of 1 and 2 were elucidated by analysis of spectroscopic data, p...

  18. Macrophage-Derived Biomarkers of Idiopathic Pulmonary Fibrosis

    OpenAIRE

    P. Rottoli; Muller-Quernheim, J.; C. Olivieri; Bargagli, E.; Prasse, A.

    2011-01-01

    Idiopathic pulmonary fibrosis (IPF) is a severe, rapidly progressive diffuse lung disease. Several pathogenetic mechanisms have been hypothesized on the basis of the fibrotic lung damage occurring in this disease, and a potential profibrotic role of activated alveolar macrophages and their mediators in the pathogenesis of IPF was recently documented. This paper focuses on recent literature on potential biomarkers of IPF derived from activated alveolar macrophages. Biomarker discovery and clin...

  19. 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...

  20. Proximity Ligation Assays for Disease Biomarkers Analysis

    OpenAIRE

    Nong, Rachel Yuan

    2011-01-01

    One of the pressing needs in the field of disease biomarker discovery is new technologies that could allow high performance protein analysis in different types of clinical material, such as blood and solid tissues. This thesis includes four approaches that address important limitations of current technologies, thus enabling highly sensitive, specific and parallel protein measurements. Paper I describes a method for sensitive singleplex protein detection in complex biological samples, namely s...

  1. Network-based drugs and biomarkers

    DEFF Research Database (Denmark)

    Erler, Janine Terra; Linding, Rune

    2010-01-01

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

  2. Biomarkers of Mercury Exposure in the Amazon

    OpenAIRE

    Nathália Santos Serrão de Castro; Marcelo de Oliveira Lima

    2014-01-01

    Mercury exposure in the Amazon has been studied since the 1980s decade and the assessment of human mercury exposure in the Amazon is difficult given that the natural occurrence of this metal is high and the concentration of mercury in biological samples of this population exceeds the standardized value of normality established by WHO. Few studies have focused on the discovery of mercury biomarkers in the region's population. In this way, some studies have used genetics as well as immunologica...

  3. Impact of biomarker development on drug safety assessment

    International Nuclear Information System (INIS)

    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.

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

    DEFF Research Database (Denmark)

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

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

  5. 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. PMID:25018902

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

    Directory of Open Access Journals (Sweden)

    Zhai G

    2012-06-01

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

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

    OpenAIRE

    Yahui Liu; Hong Qing; Yulin Deng

    2014-01-01

    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 potent...

  8. 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, ∼10

  9. 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...

  10. Automation Security

    OpenAIRE

    Mirzoev, Dr. Timur

    2014-01-01

    Web-based Automated Process Control systems are a new type of applications that use the Internet to control industrial processes with the access to the real-time data. Supervisory control and data acquisition (SCADA) networks contain computers and applications that perform key functions in providing essential services and commodities (e.g., electricity, natural gas, gasoline, water, waste treatment, transportation) to all Americans. As such, they are part of the nation s critical infrastructu...

  11. ESR statement on the stepwise development of imaging biomarkers.

    Science.gov (United States)

    2013-04-01

    Development of imaging biomarkers is a structured process in which new biomarkers are discovered, verified, validated and qualified against biological processes and clinical end-points. The validation process not only concerns the determination of the sensitivity and specificity but also the measurement of reproducibility. Reproducibility assessments and standardisation of the acquisition and data analysis methods are crucial when imaging biomarkers are used in multicentre trials for assessing response to treatment. Quality control in multicentre trials can be performed with the use of imaging phantoms. The cost-effectiveness of imaging biomarkers also needs to be determined. A lot of imaging biomarkers are being developed, but there are still unmet needs-for example, in the detection of tumour invasiveness. Main Messages • Using imaging biomarkers to streamline drug discovery and disease progression is a huge advancement in healthcare. • The qualification and technical validation of imaging biomarkers pose unique challenges in that the accuracy, methods, standardisations and reproducibility are strictly monitored. • The clinical value of new biomarkers is of the highest priority in terms of patient management, assessing risk factors and disease prognosis. PMID:23397519

  12. 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

  13. Trends in Modern Drug Discovery.

    Science.gov (United States)

    Eder, Jörg; Herrling, Paul L

    2016-01-01

    Drugs discovered by the pharmaceutical industry over the past 100 years have dramatically changed the practice of medicine and impacted on many aspects of our culture. For many years, drug discovery was a target- and mechanism-agnostic approach that was based on ethnobotanical knowledge often fueled by serendipity. With the advent of modern molecular biology methods and based on knowledge of the human genome, drug discovery has now largely changed into a hypothesis-driven target-based approach, a development which was paralleled by significant environmental changes in the pharmaceutical industry. Laboratories became increasingly computerized and automated, and geographically dispersed research sites are now more and more clustered into large centers to capture technological and biological synergies. Today, academia, the regulatory agencies, and the pharmaceutical industry all contribute to drug discovery, and, in order to translate the basic science into new medical treatments for unmet medical needs, pharmaceutical companies have to have a critical mass of excellent scientists working in many therapeutic fields, disciplines, and technologies. The imperative for the pharmaceutical industry to discover breakthrough medicines is matched by the increasing numbers of first-in-class drugs approved in recent years and reflects the impact of modern drug discovery approaches, technologies, and genomics. PMID:26330257

  14. Role of New Biomarkers: Functional and Structural Damage

    Directory of Open Access Journals (Sweden)

    Evdoxia Tsigou

    2013-01-01

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

  15. Automated Sputum Cytometry for Detection of Intraepithelial Neoplasias in the Lung

    Directory of Open Access Journals (Sweden)

    Gerald Li

    2012-01-01

    Full Text Available Background: Despite the benefits of early lung cancer detection, no effective strategy for early screening and treatment exists, partly due to a lack of effective surrogate biomarkers. Our novel sputum biomarker, the Combined Score (CS, uses automated image cytometric analysis of ploidy and nuclear morphology to detect subtle intraepithelial changes that often precede lung tumours.

  16. Determination of the oxidative stress biomarker urinary 8-hydroxy-2'-deoxyguanosine by automated on-line in-tube solid-phase microextraction coupled with liquid chromatography-tandem mass spectrometry.

    Science.gov (United States)

    Kataoka, Hiroyuki; Mizuno, Keisuke; Oda, Eri; Saito, Akihiro

    2016-04-15

    A simple and sensitive method for the determination of 8-hydroxy-2'-deoxyguanosine (8-OHdG), a marker of oxidative DNA damage in human urine, was developed using automated on-line in-tube solid-phase microextraction (SPME) coupled with stable isotope-dilution liquid chromatography-tandem mass spectrometry (LC-MS/MS). Creatinine was also analyzed simultaneously to normalize urine volume by the in-tube SPME LC-MS/MS method, and 8-OHdG and creatinine were separated within 3min using a Zorbax Eclipse XDB-C8 column. Electrospray MS/MS for these compounds was performed on an API 4000 triple quadruple mass spectrometer in the positive ion mode by multiple reaction monitoring. The optimum in-tube SPME conditions were 20 draw/eject cycles of 40μL of sample at a flow rate of 200μL/min using a Carboxen 1006 PLOT capillary column as an extraction device. The extracted compounds were easily desorbed from the capillary by passage of the mobile phase, and no carryover was observed. The calibration curve for 8-OHdG using its stable isotope-labeled internal standard was linear in the range of 0.05-10ng/mL, and the detection limit was 8.3pg/mL. The intra-day and inter-day precision (relative standard deviations) were below 3.1% and 9.6% (n=5), respectively. This method was applied successfully to the analysis of urine samples without any other pretreatment and interference peaks, with good recovery rates above 91% in spiked urine samples. The limits of quantification of 8-OHdG and creatinine in 0.1mL urine samples were about 0.32 and 0.69ng/mL (S/N=10), respectively. This method was utilized to assess the effects of smoking, green tea drinking and alcohol drinking on the urinary excretion of 8-OHdG. PMID:26349944

  17. 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.

  18. cNEUPRO: Novel Biomarkers for Neurodegenerative Diseases

    Directory of Open Access Journals (Sweden)

    Philipp Spitzer

    2010-01-01

    Full Text Available “clinical NEUroPROteomics of neurodegenerative diseases” (cNEUPRO is a Specific Targeted Research Project (STREP within the sixth framework program of the European Commission dedicated to the search for novel biomarker candidates for Alzheimer's disease and other neurodegenerative diseases. The ultimate goal of cNEUPRO is to identify one or more valid biomarker(s in blood and CSF applicable to support the early and differential diagnosis of dementia disorders. The consortium covers all steps required for the discovery of novel biomarker candidates such as acquisition of high quality CSF and blood samples from relevant patient groups and controls, analysis of body fluids by various methods, and finally assay development and assay validation. Here we report the standardized procedures for diagnosis and preanalytical sample-handling within the project, as well as the status of the ongoing research activities and some first results.

  19. 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.

  20. Biomarkers in Severe Asthma.

    Science.gov (United States)

    Wan, Xiao Chloe; Woodruff, Prescott G

    2016-08-01

    Biomarkers have been critical for studies of disease pathogenesis and the development of new therapies in severe asthma. In particular, biomarkers of type 2 inflammation have proven valuable for endotyping and targeting new biological agents. Because of these successes in understanding and marking type 2 inflammation, lack of knowledge regarding non-type 2 inflammatory mechanisms in asthma will soon be the major obstacle to the development of new treatments and management strategies in severe asthma. Biomarkers can play a role in these investigations as well by providing insight into the underlying biology in human studies of patients with severe asthma. PMID:27401625

  1. Automated Budget System

    Data.gov (United States)

    Department of Transportation — The Automated Budget System (ABS) automates management and planning of the Mike Monroney Aeronautical Center (MMAC) budget by providing enhanced capability to plan,...

  2. Validation of New Cancer Biomarkers

    DEFF Research Database (Denmark)

    Duffy, Michael J; Sturgeon, Catherine M; Söletormos, Georg; Barak, Vivian; Molina, Rafael; Hayes, Daniel F; Diamandis, Eleftherios P; Bossuyt, Patrick

    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...

  3. 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.

  4. Biomarkers for immune thrombocytopenia

    OpenAIRE

    Yu, Lingjia; Zhang, Chunmei; Zhang, Liping; Shi, Yongyu; Ji, Xuebin

    2015-01-01

    Immune thrombocytopenia is an autoimmune disease with abnormal biomarkers. Immune thrombocytopenia pathogenesis is a complicated process in which the patient’s immune system is activated by platelet autoantigens resulting in immune mediated platelet destruction or suppression of platelet production. The autoantibodies produced by autoreactive B cells against self antigens are considered to play a crucial role. In addition, biomarkers such as transforming growth factor-beta1,Toll-like receptor...

  5. Challenges in biomarker discovery with MALDI-TOF MS.

    Science.gov (United States)

    Hajduk, Joanna; Matysiak, Jan; Kokot, Zenon J

    2016-07-01

    MALDI-TOF MS technique is commonly used in system biology and clinical studies to search for new potential markers associated with pathological conditions. Despite numerous concerns regarding a sample preparation or processing of complex data, this strategy is still recognized as a popular tool and its awareness has risen in the proteomic community over the last decade. In this review, we present comprehensive application of MALDI mass spectrometry with special focus on profiling research. We also discuss major advantages and disadvantages of universal sample preparation methods such as micro-SPE columns, immunodepletion or magnetic beads, and we show the potential of nanostructured materials in capturing low molecular weight subproteomes. Furthermore, as the general protocol considerably affects spectra quality and interpretation, an alternative solution for improved ion detection, including hydrophobic constituents, data processing and statistical analysis is being considered in up-to-date profiling pattern. In conclusion, many reports involving MALDI-TOF MS indicated highly abundant proteins as valuable indicators, and at the same time showed the inaccuracy of available methods in the detection of low abundant proteome that is the most interesting from the clinical perspective. Therefore, the analytical aspects of sample preparation methods should be standardized to provide a reproducible, low sample handling and credible procedure. PMID:27134187

  6. 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) for...

  7. Integrating biomarkers in colorectal cancer trials in the West and China.

    Science.gov (United States)

    Tejpar, Sabine; Shen, Lin; Wang, Xicheng; Schilsky, Richard L

    2015-09-01

    The discovery of biomarkers that provide information on drug efficacy is recognized as essential for successful and cost-effective treatment of cancer. However, biomarker discovery is difficult, and requires multiple independent studies to identify a target that serves as a suitable predictor of efficacy and to ensure appropriate biomarker validation. Clinical trials that are performed, sometimes sequentially, in Europe, the USA or Asia, are often similar in their design, in part owing to regulatory, marketing, or safety considerations. We believe some of these trials offer additional unique opportunities for biomarker discovery or validation. There are multiple hurdles to overcome, such as homogenous tissue acquisition and analysis, defining and aligning biomarker hypotheses across trials, and the need to adapt sample sizes and trial designs. Nevertheless, we believe that a collaborative engagement of the academic, regulatory and pharmaceutical community can go a long way in addressing these issues and producing more-rapid results in the field of personalized medicine. In this Perspectives, we describe our views on the current fragmented approach to biomarker discovery and validation in relevant trials run within our own regions-that is, Europe, China, and the USA-and hope this article serves as a base for further reflection. PMID:25963094

  8. Programming with Conditionals: Epistemic Programming for Scientific Discovery

    Institute of Scientific and Technical Information of China (English)

    2001-01-01

    In order to provide scientists with a computational methodologyand some computa tional tools to program their epistemic processes in scientific discovery, we ar e establishing a novel programming paradigm, named ‘Epistemic Programming’, wh ic h regards conditionals as the subject of computing, takes primary epistemic oper ations as basic operations of computing, and regards epistemic processes as the subject of programming. This paper presents our fundamental observati ons and assumptions on scientific discovery processes and their automation, rese arch problems on modeling, automating, and programming epistemic processes, and an outline of our research project of Epistemic Programming.

  9. Manufacturing and automation

    OpenAIRE

    Ernesto Córdoba Nieto

    2010-01-01

    The article presents concepts and definitions from different sources concerning automation. The work approaches automation by virtue of the author’s experience in manufacturing production; why and how automation prolects are embarked upon is considered. Technological reflection regarding the progressive advances or stages of automation in the production area is stressed. Coriat and Freyssenet’s thoughts about and approaches to the problem of automation and its current state are taken and e...

  10. Fractionated Marine Invertebrate Extract Libraries for Drug Discovery

    Directory of Open Access Journals (Sweden)

    Chris M. Ireland

    2008-06-01

    Full Text Available The high-throughput screening and drug discovery paradigm has necessitated a change in preparation of natural product samples for screening programs. In an attempt to improve the quality of marine natural products samples for screening, several fractionation strategies were investigated. The final method used HP20SS as a solid support to effectively desalt extracts and fractionate the organic components. Additionally, methods to integrate an automated LCMS fractionation approach to shorten discovery time lines have been implemented.

  11. The importance of biomarkers in neonatology.

    Science.gov (United States)

    Mussap, M; Noto, A; Cibecchini, F; Fanos, V

    2013-02-01

    Despite a 35% decline in the mortality rate for infants aged years over the past two decades, every year nearly 40% of all deaths in this age group occur in the neonatal period, defined as the first 28 days of life. New knowledge on molecular and biochemical pathways in neonatal diseases will lead to the discovery of new candidate biomarkers potentially useful in clinical practice. In the era of personalized medicine, biomarkers may play a strategic role in accelerating the decline in neonatal mortality by assessing the risk of developing neonatal diseases, by implementing tailored therapeutic treatment, and by predicting the clinical outcome. However, there is an urgent need to reduce the gap in translating newly acquired knowledge from bench to bedside. Traditional and candidate biomarkers for neonatal sepsis and necrotizing enterocolitis will be discussed in this review, such as C-reactive protein (CRP), procalcitonin (PCT), serum amyloid A (SAA), soluble form of CD14 subtype presepsin (sCD14-ST), lipolysaccharide binding protein (LBP), angiopoietins (Ang)-1 and -2, soluble form of triggering receptor expressed on myeloid cells (sTREM-1), soluble form of urokinase-type plasminogen activator receptor (suPAR), platelet-activating factor (PAF) and calprotectin. New frontiers in managing critically ill newborns may be opened by metabolomics, a diagnostic tool based on the recognition of metabolites contained in biological fluids. Metabolomics represents the passage from a descriptive science to a predictive science, having the potential to translate benchtop research to real clinical benefits. PMID:23164809

  12. MicroRNA Biomarkers of Toxicity in Biological Matrices.

    Science.gov (United States)

    Harrill, Alison H; McCullough, Shaun D; Wood, Charles E; Kahle, Juliette J; Chorley, Brian N

    2016-08-01

    Biomarker measurements that reliably correlate with tissue injury and that can be measured within accessible biofluids offer benefits in terms of cost, time, and convenience when assessing chemical and drug-induced toxicity in model systems or human cohorts. MicroRNAs (miRNAs) have emerged in recent years as a promising new class of biomarker for monitoring toxicity. Recent enthusiasm for miRNA biomarker research has been fueled by evidence that certain miRNAs are cell-type specific and are released during injury, thus raising the possibility of using biofluid-based miRNAs as a "liquid biopsy" that may be obtained by sampling extracellular fluids. As biomarkers, miRNAs demonstrate improved stability as compared with many protein markers and sequences are largely conserved across species, simplifying analytical techniques. Recent efforts have sought to identify miRNAs that are released into accessible biofluids following xenobiotic exposure, using compounds that target specific organs. Whereas still early in the discovery phase, miRNA biomarkers will have an increasingly important role in the assessment of adverse effects of both environmental chemicals and pharmaceutical drugs. Here, we review the current findings of biofluid-based miRNAs, as well as highlight technical challenges in assessing toxicologic pathology using these biomarkers. PMID:27462126

  13. Glial biomarkers in human central nervous system disease.

    Science.gov (United States)

    Garden, Gwenn A; Campbell, Brian M

    2016-10-01

    There is a growing understanding that aberrant GLIA function is an underlying factor in psychiatric and neurological disorders. As drug discovery efforts begin to focus on glia-related targets, a key gap in knowledge includes the availability of validated biomarkers to help determine which patients suffer from dysfunction of glial cells or who may best respond by targeting glia-related drug mechanisms. Biomarkers are biological variables with a significant relationship to parameters of disease states and can be used as surrogate markers of disease pathology, progression, and/or responses to drug treatment. For example, imaging studies of the CNS enable localization and characterization of anatomical lesions without the need to isolate tissue for biopsy. Many biomarkers of disease pathology in the CNS involve assays of glial cell function and/or response to injury. Each major glia subtype (oligodendroglia, astroglia and microglia) are connected to a number of important and useful biomarkers. Here, we describe current and emerging glial based biomarker approaches for acute CNS injury and the major categories of chronic nervous system dysfunction including neurodegenerative, neuropsychiatric, neoplastic, and autoimmune disorders of the CNS. These descriptions are highlighted in the context of how biomarkers are employed to better understand the role of glia in human CNS disease and in the development of novel therapeutic treatments. GLIA 2016;64:1755-1771. PMID:27228454

  14. 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.

  15. Prognostic factors and biomarkers of congenital obstructive nephropathy.

    Science.gov (United States)

    Chevalier, Robert L

    2016-09-01

    Congenital obstructive nephropathy (CON) is the leading cause of chronic kidney disease (CKD) in children. Anomalies of the urinary tract are often associated with abnormal nephrogenesis, which is compounded by obstructive injury and by maternal risk factors associated with low birth weight. Currently available fetal and postnatal imaging and analytes of amniotic fluid, urine, or blood lack predictive value. For ureteropelvic junction obstruction, biomarkers are needed for optimal timing of pyeloplasty; for posterior urethral valves, biomarkers of long-term prognosis and CKD are needed. The initial nephron number may be a major determinant of progression of CKD, and most patients with CON who progress to renal failure reach this point in adulthood, presumably compounded by episodes of acute kidney injury. Biomarkers of tubular injury may be of particular value in predicting the need for surgical intervention or in tracking progression of CKD, and must be adjusted for patient age. Discovery of new biomarkers may depend on "unbiased" proteomics, whereby patterns of urinary peptide fragments from patients with CON are analyzed in comparison to controls. Most promising are the analysis of urinary exosomes (restricting biomarkers to relevant tubular cells) and quantitative magnetic resonance imaging techniques allowing precise determination of nephron number and tubular mass. The greatest need is for large prospective multicenter studies with centralized biomarker sample repositories to follow patients with CON from fetal life through adulthood. PMID:26667236

  16. A Cognitive Adopted Framework for IoT Big-Data Management and Knowledge Discovery Prospective

    OpenAIRE

    Nilamadhab Mishra; Chung-Chih Lin; Hsien-Tsung Chang

    2015-01-01

    In future IoT big-data management and knowledge discovery for large scale industrial automation application, the importance of industrial internet is increasing day by day. Several diversified technologies such as IoT (Internet of Things), computational intelligence, machine type communication, big-data, and sensor technology can be incorporated together to improve the data management and knowledge discovery efficiency of large scale automation applications. So in this work, we need to propos...

  17. 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.

  18. Biomarkers in Transplantation-Proteomics and Metabolomics.

    Science.gov (United States)

    Christians, Uwe; Klawitter, Jelena; Klawitter, Jost

    2016-04-01

    Modern multianalyte "omics" technologies allow for the identification of molecular signatures that confer significantly more information than measurement of a single parameter as typically used in current medical diagnostics. Proteomics and metabolomics bioanalytical assays capture a large set of proteins and metabolites in body fluids, cells, or tissues and, complementing genomics, assess the phenome. Proteomics and metabolomics contribute to the development of novel predictive clinical biomarkers in transplantation in 2 ways: they can be used to generate a diagnostic fingerprint or they can be used to discover individual proteins and metabolites of diagnostic potential. Much fewer metabolomics than proteomics biomarker studies in transplant patients have been reported, and, in contrast to proteomics discovery studies, new lead metabolite markers have yet to emerge. Most clinical proteomics studies have been discovery studies. Several of these studies have assessed diagnostic sensitivity and specificity. Nevertheless, none of these newly discovered protein biomarkers have yet been implemented in clinical decision making in transplantation. The currently most advanced markers discovered in proteomics studies in transplant patients are the chemokines CXCL-9 and CXCL-10, which have successfully been validated in larger multicenter trials in kidney transplant patients. These chemokines can be measured using standard immunoassay platforms, which should facilitate clinical implementation. Based on the published evidence, it is reasonable to expect that these chemokine markers can help guiding and individualizing immunosuppressive regimens, may be able to predict acute and chronic T-cell-mediated and antibody-mediated rejection, and may be useful tools for risk stratification of kidney transplant patients. PMID:26418702

  19. Biomarkers in Barrett's esophagus.

    Science.gov (United States)

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

    2003-04-01

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

  20. Manufacturing and automation

    Directory of Open Access Journals (Sweden)

    Ernesto Córdoba Nieto

    2010-04-01

    Full Text Available The article presents concepts and definitions from different sources concerning automation. The work approaches automation by virtue of the author’s experience in manufacturing production; why and how automation prolects are embarked upon is considered. Technological reflection regarding the progressive advances or stages of automation in the production area is stressed. Coriat and Freyssenet’s thoughts about and approaches to the problem of automation and its current state are taken and examined, especially that referring to the problem’s relationship with reconciling the level of automation with the flexibility and productivity demanded by competitive, worldwide manufacturing.

  1. 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.

  2. Searching for a system: The quest for ovarian cancer biomarkers

    Energy Technology Data Exchange (ETDEWEB)

    Rodland, Karin D.; Maihle, Nita J.

    2011-11-01

    The stark difference in clinical outcome for patients with ovarian cancer diagnosed at early stages (95% at 5 years) versus late stages (27.6% at 5 years) has driven a decades-long quest for effective biomarkers that will enable earlier detection of ovarian cancer. Yet despite intense efforts, including the application of modern high throughput technologies such as transcriptomics and proteomics, there has been little improvement in performance compared to the gold standard of quantifying serum CA125 immunoreactivity paired with transvaginal ultrasound. This review describes the strategies that have been used for identification of ovarian cancer biomarkers, including the recent introduction of novel bioinformatic approaches. Results obtained using high throughput-based vs. biologically rational approaches for the discovery of diagnostic early detection biomarkers are compared and analyzed for functional enrichment.

  3. Ovarian cyst fluid is a rich proteome resource for detection of new tumor biomarkers

    OpenAIRE

    Kristjansdottir Björg; Partheen Karolina; Fung Eric T; Marcickiewicz Janusz; Yip Christine; Brännström Mats; Sundfeldt Karin

    2012-01-01

    Abstract Background We aimed to investigate the use of ovarian cyst fluid as a source for biomarker discovery and to find novel biomarkers for use in the diagnosis of epithelial ovarian tumors. Results Ovarian cyst fluids from 218 women were collected and 192 (benign n = 129, malignant n = 63) were analyzed using mass spectrometry. 1180 peaks were detected, 221 of which were differently expressed between benign and malignant ovarian tumors. Seventeen peaks had receiver operating curve and are...

  4. The Extracellular Domain of Neurotrophin Receptor p75 as a Candidate Biomarker for Amyotrophic Lateral Sclerosis

    OpenAIRE

    Shepheard, Stephanie R.; Tim Chataway; David W Schultz; Rush, Robert A.; Mary-Louise Rogers

    2014-01-01

    Objective biomarkers for amyotrophic lateral sclerosis would facilitate the discovery of new treatments. The common neurotrophin receptor p75 is up regulated and the extracellular domain cleaved from injured neurons and peripheral glia in amyotrophic lateral sclerosis. We have tested the hypothesis that urinary levels of extracellular neurotrophin receptor p75 serve as a biomarker for both human motor amyotrophic lateral sclerosis and the SOD1(G93A) mouse model of the disease. The extracellul...

  5. Emerging Biomarkers in Glioblastoma

    Energy Technology Data Exchange (ETDEWEB)

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

    2013-08-22

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

  6. Proteomic Biomarkers of Atherosclerosis

    Directory of Open Access Journals (Sweden)

    Natacha Diaz-Prieto

    2008-01-01

    Full Text Available Biomarkers provide a powerful approach to understanding the spectrum of cardiovascular diseases. They have application in screening, diagnostic, prognostication, prediction of recurrences and monitoring of therapy. The “omics” tool are becoming very useful in the development of new biomarkers in cardiovascular diseases. Among them, proteomics is especially fitted to look for new proteins in health and disease and is playing a significant role in the development of new diagnostic tools in cardiovascular diagnosis and prognosis. This review provides an overview of progress in applying proteomics to atherosclerosis. First, we describe novel proteins identified analysing atherosclerotic plaques directly. Careful analysis of proteins within the atherosclerotic vascular tissue can provide a repertoire of proteins involved in vascular remodelling and atherogenesis. Second, we discuss recent data concerning proteins secreted by atherosclerotic plaques. The definition of the atheroma plaque secretome resides in that proteins secreted by arteries can be very good candidates of novel biomarkers. Finally we describe proteins that have been differentially expressed (versus controls by individual cells which constitute atheroma plaques (endothelial cells, vascular smooth muscle cells, macrophages and foam cells as well as by circulating cells (monocytes, platelets or novel biomarkers present in plasma.

  7. Proteomic Biomarkers of Atherosclerosis.

    Science.gov (United States)

    Vivanco, F; Padial, L R; Darde, V M; de la Cuesta, F; Alvarez-Llamas, G; Diaz-Prieto, Natacha; Barderas, M G

    2008-01-01

    SUMMARY: Biomarkers provide a powerful approach to understanding the spectrum of cardiovascular diseases. They have application in screening, diagnostic, prognostication, prediction of recurrences and monitoring of therapy. The "omics" tool are becoming very useful in the development of new biomarkers in cardiovascular diseases. Among them, proteomics is especially fitted to look for new proteins in health and disease and is playing a significant role in the development of new diagnostic tools in cardiovascular diagnosis and prognosis. This review provides an overview of progress in applying proteomics to atherosclerosis. First, we describe novel proteins identified analysing atherosclerotic plaques directly. Careful analysis of proteins within the atherosclerotic vascular tissue can provide a repertoire of proteins involved in vascular remodelling and atherogenesis. Second, we discuss recent data concerning proteins secreted by atherosclerotic plaques. The definition of the atheroma plaque secretome resides in that proteins secreted by arteries can be very good candidates of novel biomarkers. Finally we describe proteins that have been differentially expressed (versus controls) by individual cells which constitute atheroma plaques (endothelial cells, vascular smooth muscle cells, macrophages and foam cells) as well as by circulating cells (monocytes, platelets) or novel biomarkers present in plasma. PMID:19578499

  8. Strategies for modern biomarker and drug development in oncology

    OpenAIRE

    Alan D. Smith; Roda, Desam; Yap, Timothy A.

    2014-01-01

    Technological advancements in the molecular characterization of cancers have enabled researchers to identify an increasing number of key molecular drivers of cancer progression. These discoveries have led to multiple novel anticancer therapeutics, and clinical benefit in selected patient populations. Despite this, the identification of clinically relevant predictive biomarkers of response continues to lag behind. In this review, we discuss strategies for the molecular characterization of canc...

  9. Role of New Biomarkers: Functional and Structural Damage

    OpenAIRE

    Evdoxia Tsigou; Vasiliki Psallida; Christos Demponeras; Eleni Boutzouka; George Baltopoulos

    2013-01-01

    Traditional diagnosis of acute kidney injury (AKI) depends on detection of oliguria and rise of serum creatinine level, which is an unreliable and delayed marker of kidney damage. Delayed diagnosis of AKI in the critically ill patient is related to increased morbidity and mortality, prolonged length of stay, and cost escalation. The discovery of a reliable biomarker for early diagnosis of AKI would be very helpful in facilitating early intervention, evaluating the effectiveness of therapy, an...

  10. Tools for GPCR drug discovery

    Institute of Scientific and Technical Information of China (English)

    Ru ZHANG; Xin XIE

    2012-01-01

    G-protein-coupled receptors (GPCRs) mediate many important physiological functions and are considered as one of the most successful therapeutic targets for a broad spectrum of diseases.The design and implementation of high-throughput GPCR assays that allow the cost-effective screening of large compound libraries to identify novel drug candidates are critical in early drug discovery.Early functional GPCR assays depend primarily on the measurement of G-protein-mediated 2nd messenger generation.Taking advantage of the continuously deepening understanding of GPCR signal transduction,many G-protein-independent pathways are utilized to detect the activity of GPCRs,and may provide additional information on functional selectivity of candidate compounds.With the combination of automated imaging systems and label-free detection systems,such assays are now suitable for high-throughput screening (HTS).In this review,we summarize the most widely used GPCR assays and recent advances in HTS technologies for GPCR drug discovery.

  11. An automated swimming respirometer

    DEFF Research Database (Denmark)

    STEFFENSEN, JF; JOHANSEN, K; BUSHNELL, PG

    1984-01-01

    An automated respirometer is described that can be used for computerized respirometry of trout and sharks.......An automated respirometer is described that can be used for computerized respirometry of trout and sharks....

  12. Configuration Management Automation (CMA)

    Data.gov (United States)

    Department of Transportation — Configuration Management Automation (CMA) will provide an automated, integrated enterprise solution to support CM of FAA NAS and Non-NAS assets and investments. CMA...

  13. The State of the Art in Library Discovery 2010

    Science.gov (United States)

    Breeding, Marshall

    2010-01-01

    Resource discovery tops the charts as the foremost issue within the realm of library automation. As a new year commences, the author sees a more pressing need to accelerate the pace with which libraries deliver content and services in ways that users will find compelling, relevant, and convenient. The evolution of the web advances relentlessly,…

  14. Visualization: A Mind-Machine Interface for Discovery.

    Science.gov (United States)

    Nielsen, Cydney B

    2016-02-01

    Computation is critical for enabling us to process data volumes and model data complexities that are unthinkable by manual means. However, we are far from automating the sense-making process. Human knowledge and reasoning are critical for discovery. Visualization offers a powerful interface between mind and machine that should be further exploited in future genome analysis tools. PMID:26739384

  15. Workflow automation architecture standard

    Energy Technology Data Exchange (ETDEWEB)

    Moshofsky, R.P.; Rohen, W.T. [Boeing Computer Services Co., Richland, WA (United States)

    1994-11-14

    This document presents an architectural standard for application of workflow automation technology. The standard includes a functional architecture, process for developing an automated workflow system for a work group, functional and collateral specifications for workflow automation, and results of a proof of concept prototype.

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

    International Nuclear Information System (INIS)

    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

  17. Shoe-String Automation

    Energy Technology Data Exchange (ETDEWEB)

    Duncan, M.L.

    2001-07-30

    Faced with a downsizing organization, serious budget reductions and retirement of key metrology personnel, maintaining capabilities to provide necessary services to our customers was becoming increasingly difficult. It appeared that the only solution was to automate some of our more personnel-intensive processes; however, it was crucial that the most personnel-intensive candidate process be automated, at the lowest price possible and with the lowest risk of failure. This discussion relates factors in the selection of the Standard Leak Calibration System for automation, the methods of automation used to provide the lowest-cost solution and the benefits realized as a result of the automation.

  18. Imaging biomarkers in tauopathies.

    Science.gov (United States)

    Dani, Melanie; Edison, Paul; Brooks, David J

    2016-01-01

    Abnormally aggregated tau protein is central to the pathophysiology of Alzheimer's disease, frontotemporal dementia variants, progressive supranuclear palsy, corticobasal degeneration and chronic traumatic encephalopathy. The post-mortem cortical density of hyperphosphorylated tau tangles correlates with pre-morbid cognitive dysfunction and neuron loss. Selective PET ligands including [18F]THK5117, [18F]THK5351, [18F]AV1451 (T807) and [11C]PBB3 now provide in vivo imaging information about the timing and distribution of tau in the early phases of neurodegenerative diseases. They are potential imaging biomarkers for both supporting diagnosis and tracking disease progression. Here, we discuss the challenges posed in developing selective tau ligands as biomarkers, their state of development and the new clinical information that has been revealed. PMID:26299160

  19. Towards Improved Biomarker Research

    DEFF Research Database (Denmark)

    Kjeldahl, Karin

    actually identify strong biomarkers when strict validation is applied; the latter phenomenon is to some extentmasked by a publication bias, but has been widely observed among researchers working with omics data. In this thesis, the background of this apparent small effect size of the biomarkers is...... is used both for regression and classification purposes. This method has proven its strong worth in the multivariate data analysis throughout an enormous range of applications; a very classic data type is near infrared (NIR) data, but many similar data types have also be very successful. On that...... application types are different and introduce a larger complexity, weaker signals andmany potential sources of experimental and analytical bias and errors. The risk of the latter is further increased by the complexity of the entire omics experimental setup which often involves various project partners with...

  20. Epigenetic biomarkers in laboratory diagnostics: emerging approaches and opportunities.

    Science.gov (United States)

    Sandoval, Juan; Peiró-Chova, Lorena; Pallardó, Federico V; García-Giménez, José Luis

    2013-06-01

    Epigenetics has emerged as a new and promising field in recent years. Lifestyle, stress, drugs, physiopathological situations and pharmacological interventions have a great impact on the epigenetic code of the cells by altering the methylome, miRNA expression and the covalent histone modifications. Since there exists a need to find new biomarkers and improve diagnosis for several diseases, the research on epigenetic biomarkers for molecular diagnostics encourages the translation of this field from the bench to clinical practice. In this context, deciphering intricate epigenetic modifications involved in several molecular processes is a challenge that will be solved in the near future. In this review, the authors present an overview of the high-throughput technologies and laboratory techniques available for epigenetic studies, and also discuss which of them are more reliable to be used in a clinical diagnostic laboratory. In addition, the authors describe the most promising epigenetic biomarkers in lung, colorectal and prostate cancer, in which most advances have been achieved. Finally, the authors describe epigenetic biomarkers in some rare diseases; these rare syndromes are paradigms for a specific impaired molecular pathway, thus providing valuable information on the discovery of new epigenetic biomarkers. PMID:23782253

  1. Biomarkers of Ovarian Reserve

    Directory of Open Access Journals (Sweden)

    William E. Roudebush

    2008-01-01

    Full Text Available The primary function of the female ovary is the production of a mature and viable oocyte capable of fertilization and subsequent embryo development and implantation. At birth, the ovary contains a finite number of oocytes available for folliculogenesis. This finite number of available oocytes is termed “the ovarian reserve”. The determination of ovarian reserve is important in the assessment and treatment of infertility. As the ovary ages, the ovarian reserve will decline. Infertility affects approximately 15-20% of reproductive aged couples. The most commonly used biomarker assay to assess ovarian reserve is the measurement of follicle stimulating hormone (FSH on day 3 of the menstrual cycle. However, antimüllerian hormone and inhibin-B are other biomarkers of ovarian reserve that are gaining in popularity since they provide direct determination of ovarian status, whereas day 3 FSH is an indirect measurement. This review examines the physical tools and the hormone biomarkers used to evaluate ovarian reserve.

  2. Computational drug discovery

    Institute of Scientific and Technical Information of China (English)

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

    2012-01-01

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

  3. Automated Discovery and Refinement of Reactive Molecular Dynamics Pathways.

    Science.gov (United States)

    Wang, Lee-Ping; McGibbon, Robert T; Pande, Vijay S; Martinez, Todd J

    2016-02-01

    We describe a flexible and broadly applicable energy refinement method, "nebterpolation," for identifying and characterizing the reaction events in a molecular dynamics (MD) simulation. The new method is applicable to ab initio simulations with hundreds of atoms containing complex and multimolecular reaction events. A key aspect of nebterpolation is smoothing of the reactive MD trajectory in internal coordinates to initiate the search for the reaction path on the potential energy surface. We apply nebterpolation to analyze the reaction events in an ab initio nanoreactor simulation that discovers new molecules and mechanisms, including a C-C coupling pathway for glycolaldehyde synthesis. We find that the new method, which incorporates information from the MD trajectory that connects reactants with products, produces a dramatically distinct set of minimum energy paths compared to existing approaches that start from information for the reaction end points alone. The energy refinement method described here represents a key component of an emerging simulation paradigm where molecular dynamics simulations are applied to discover the possible reaction mechanisms. PMID:26683346

  4. Automated Semantic Enrichment for Data Discovery and Decision Support Project

    Data.gov (United States)

    National Aeronautics and Space Administration — The objective of this proposal is to demonstrate a set of methods for automatically extracting metadata from diverse data sets to serve as a common vocabulary by...

  5. Automated Atmospheric Composition Dataset Level Metadata Discovery. Difficulties and Surprises

    Science.gov (United States)

    Strub, R. F.; Falke, S. R.; Kempler, S.; Fialkowski, E.; Goussev, O.; Lynnes, C.

    2015-12-01

    The Atmospheric Composition Portal (ACP) is an aggregator and curator of information related to remotely sensed atmospheric composition data and analysis. It uses existing tools and technologies and, where needed, enhances those capabilities to provide interoperable access, tools, and contextual guidance for scientists and value-adding organizations using remotely sensed atmospheric composition data. The initial focus is on Essential Climate Variables identified by the Global Climate Observing System - CH4, CO, CO2, NO2, O3, SO2 and aerosols. This poster addresses our efforts in building the ACP Data Table, an interface to help discover and understand remotely sensed data that are related to atmospheric composition science and applications. We harvested GCMD, CWIC, GEOSS metadata catalogs using machine to machine technologies - OpenSearch, Web Services. We also manually investigated the plethora of CEOS data providers portals and other catalogs where that data might be aggregated. This poster is our experience of the excellence, variety, and challenges we encountered.Conclusions:1.The significant benefits that the major catalogs provide are their machine to machine tools like OpenSearch and Web Services rather than any GUI usability improvements due to the large amount of data in their catalog.2.There is a trend at the large catalogs towards simulating small data provider portals through advanced services. 3.Populating metadata catalogs using ISO19115 is too complex for users to do in a consistent way, difficult to parse visually or with XML libraries, and too complex for Java XML binders like CASTOR.4.The ability to search for Ids first and then for data (GCMD and ECHO) is better for machine to machine operations rather than the timeouts experienced when returning the entire metadata entry at once. 5.Metadata harvest and export activities between the major catalogs has led to a significant amount of duplication. (This is currently being addressed) 6.Most (if not all) Earth science atmospheric composition data providers store a reference to their data at GCMD.

  6. Automated Service Discovery using Autonomous Control Technologies Project

    Data.gov (United States)

    National Aeronautics and Space Administration — With the advent of mobile commerce technologies, the realization of pervasive computing and the formation of ad-hoc networks can be leveraged to the benefit of the...

  7. Reliable knowledge discovery

    CERN Document Server

    Dai, Honghua; Smirnov, Evgueni

    2012-01-01

    Reliable Knowledge Discovery focuses on theory, methods, and techniques for RKDD, a new sub-field of KDD. It studies the theory and methods to assure the reliability and trustworthiness of discovered knowledge and to maintain the stability and consistency of knowledge discovery processes. RKDD has a broad spectrum of applications, especially in critical domains like medicine, finance, and military. Reliable Knowledge Discovery also presents methods and techniques for designing robust knowledge-discovery processes. Approaches to assessing the reliability of the discovered knowledge are introduc

  8. Leveraging Big Data to Transform Target Selection and Drug Discovery

    Science.gov (United States)

    Chen, B; Butte, AJ

    2016-01-01

    The advances of genomics, sequencing, and high throughput technologies have led to the creation of large volumes of diverse datasets for drug discovery. Analyzing these datasets to better understand disease and discover new drugs is becoming more common. Recent open data initiatives in basic and clinical research have dramatically increased the types of data available to the public. The past few years have witnessed successful use of big data in many sectors across the whole drug discovery pipeline. In this review, we will highlight the state of the art in leveraging big data to identify new targets, drug indications, and drug response biomarkers in this era of precision medicine. PMID:26659699

  9. Biomarkers in inflammatory bowel diseases

    DEFF Research Database (Denmark)

    Bennike, Tue; Birkelund, Svend; Stensballe, Allan;

    2014-01-01

    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...... before. In this review, we report the current status of the proteomics IBD biomarkers and discuss various emerging proteomic strategies for identifying and characterizing novel biomarkers, as well as suggesting future targets for analysis....

  10. Knowledge Discovery in Databases and Libraries

    Directory of Open Access Journals (Sweden)

    Anil Kumar Dhiman

    2011-11-01

    Full Text Available The advancement in information and communication technology (ICT has outpaced our abilities to analyse, summarise, and extract knowledge from the data. Today, database technology has provided us with the basic tools for the efficient storage and lookup of large data sets, but the issue of how to help human beings to understand and analyse large bodies of data remains a difficult and unsolved problem. So, intelligent tools for automated data mining and knowledge discovery are needed to deal with enormous data. As library and information centre are considered the backbone of knowledge organisation, knowledge discovery in databases (KDD is also getting attention of library and information scientists. This paper highlights the basics of KDD process and its importance in digital libraries.

  11. 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.

  12. 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.

  13. 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.

  14. 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...

  15. Higgs Discovery Movie

    CERN Multimedia

    2014-01-01

    The ATLAS & CMS Experiments Celebrate the 2nd Anniversary of the Discovery of the Higgs boson. Here, are some images of the path from LHC startup to Nobel Prize, featuring a musical composition by Roger Zare, performed by the Donald Sinta Quartet, called “LHC”. Happy Discovery Day!

  16. 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

  17. "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…

  18. Revisiting the technical validation of tumour biomarker assays: how to open a Pandora's box.

    Science.gov (United States)

    Marchiò, Caterina; Dowsett, Mitch; Reis-Filho, Jorge S

    2011-01-01

    A tumour biomarker is a characteristic that is objectively measured and evaluated in tumour samples as an indicator of normal biological processes, pathogenic processes, or pharmacologic responses to a therapeutic intervention. The development of a biomarker contemplates distinct phases, including discovery by hypothesis-generating preclinical or exploratory studies, development and qualification of the assay for the identification of the biomarker in clinical samples, and validation of its clinical significance. Although guidelines for the development and validation of biomarkers are available, their implementation is challenging, owing to the diversity of biomarkers being developed. The term 'validation' undoubtedly has several meanings; however, in the context of biomarker research, a test may be considered valid if it is 'fit for purpose'. In the process of validation of a biomarker assay, a key point is the validation of the methodology. Here we discuss the challenges for the technical validation of immunohistochemical and gene expression assays to detect tumour biomarkers and provide suggestions of pragmatic solutions to address these challenges. PMID:21504565

  19. Revisiting the technical validation of tumour biomarker assays: how to open a Pandora's box

    Directory of Open Access Journals (Sweden)

    Dowsett Mitch

    2011-04-01

    Full Text Available Abstract A tumour biomarker is a characteristic that is objectively measured and evaluated in tumour samples as an indicator of normal biological processes, pathogenic processes, or pharmacologic responses to a therapeutic intervention. The development of a biomarker contemplates distinct phases, including discovery by hypothesis-generating preclinical or exploratory studies, development and qualification of the assay for the identification of the biomarker in clinical samples, and validation of its clinical significance. Although guidelines for the development and validation of biomarkers are available, their implementation is challenging, owing to the diversity of biomarkers being developed. The term 'validation' undoubtedly has several meanings; however, in the context of biomarker research, a test may be considered valid if it is 'fit for purpose'. In the process of validation of a biomarker assay, a key point is the validation of the methodology. Here we discuss the challenges for the technical validation of immunohistochemical and gene expression assays to detect tumour biomarkers and provide suggestions of pragmatic solutions to address these challenges.

  20. Analytical Aspects of the Implementation of Biomarkers in Clinical Transplantation.

    Science.gov (United States)

    Shipkova, Maria; López, Olga Millán; Picard, Nicolas; Noceti, Ofelia; Sommerer, Claudia; Christians, Uwe; Wieland, Eberhard

    2016-04-01

    In response to the urgent need for new reliable biomarkers to complement the guidance of the immunosuppressive therapy, a huge number of biomarker candidates to be implemented in clinical practice have been introduced to the transplant community. This includes a diverse range of molecules with very different molecular weights, chemical and physical properties, ex vivo stabilities, in vivo kinetic behaviors, and levels of similarity to other molecules, etc. In addition, a large body of different analytical techniques and assay protocols can be used to measure biomarkers. Sometimes, a complex software-based data evaluation is a prerequisite for appropriate interpretation of the results and for their reporting. Although some analytical procedures are of great value for research purposes, they may be too complex for implementation in a clinical setting. Whereas the proof of "fitness for purpose" is appropriate for validation of biomarker assays used in exploratory drug development studies, a higher level of analytical validation must be achieved and eventually advanced analytical performance might be necessary before diagnostic application in transplantation medicine. A high level of consistency of results between laboratories and between methods (if applicable) should be obtained and maintained to make biomarkers effective instruments in support of therapeutic decisions. This overview focuses on preanalytical and analytical aspects to be considered for the implementation of new biomarkers for adjusting immunosuppression in a clinical setting and highlights critical points to be addressed on the way to make them suitable as diagnostic tools. These include but are not limited to appropriate method validation, standardization, education, automation, and commercialization. PMID:26418704

  1. Automated stopcock actuator

    OpenAIRE

    Vandehey, N. T.; O'Neil, J.P.

    2015-01-01

    Introduction We have developed a low-cost stopcock valve actuator for radiochemistry automation built using a stepper motor and an Arduino, an open-source single-board microcontroller. The con-troller hardware can be programmed to run by serial communication or via two 5–24 V digital lines for simple integration into any automation control system. This valve actuator allows for automated use of a single, disposable stopcock, providing a number of advantages over stopcock manifold systems ...

  2. The Adaptive Automation Design

    OpenAIRE

    Calefato, Caterina; Montanari, Roberto; TESAURI, Francesco

    2008-01-01

    After considering the positive effects of adaptive automation implementation, this chapter focuses on two partly overlapping phenomena: on the one hand, the role of trust in automation is considered, particularly as to the effects of overtrust and mistrust in automation's reliability; on the other hand, long-term lack of exercise on specific operation may lead users to skill deterioration. As a future work, it will be interesting and challenging to explore the conjunction of adaptive automati...

  3. Service functional test automation

    OpenAIRE

    Hillah, Lom Messan; Maesano, Ariele-Paolo; Rosa, Fabio; Maesano, Libero; Lettere, Marco; Fontanelli, Riccardo

    2015-01-01

    This paper presents the automation of the functional test of services (black-box testing) and services architectures (grey-box testing) that has been developed by the MIDAS project and is accessible on the MIDAS SaaS. In particular, the paper illustrates the solutions of tough functional test automation problems such as: (i) the configuration of the automated test execution system against large and complex services architectures, (ii) the constraint-based test input generation, (iii) the spec...

  4. Automated Weather Observing System

    Data.gov (United States)

    Department of Transportation — The Automated Weather Observing System (AWOS) is a suite of sensors, which measure, collect, and disseminate weather data to help meteorologists, pilots, and flight...

  5. Laboratory Automation and Middleware.

    Science.gov (United States)

    Riben, Michael

    2015-06-01

    The practice of surgical pathology is under constant pressure to deliver the highest quality of service, reduce errors, increase throughput, and decrease turnaround time while at the same time dealing with an aging workforce, increasing financial constraints, and economic uncertainty. Although not able to implement total laboratory automation, great progress continues to be made in workstation automation in all areas of the pathology laboratory. This report highlights the benefits and challenges of pathology automation, reviews middleware and its use to facilitate automation, and reviews the progress so far in the anatomic pathology laboratory. PMID:26065792

  6. Automated cloning methods.; TOPICAL

    International Nuclear Information System (INIS)

    Argonne has developed a series of automated protocols to generate bacterial expression clones by using a robotic system designed to be used in procedures associated with molecular biology. The system provides plate storage, temperature control from 4 to 37 C at various locations, and Biomek and Multimek pipetting stations. The automated system consists of a robot that transports sources from the active station on the automation system. Protocols for the automated generation of bacterial expression clones can be grouped into three categories (Figure 1). Fragment generation protocols are initiated on day one of the expression cloning procedure and encompass those protocols involved in generating purified coding region (PCR)

  7. Recent advances in atherosclerosis-based proteomics: new biomarkers and a future perspective.

    Science.gov (United States)

    Alvarez-Llamas, Gloria; de la Cuesta, Fernando; Barderas, Maria Eugenia G; Darde, Veronica; Padial, Luis R; Vivanco, Fernando

    2008-10-01

    Vascular proteomics is providing two main types of data: proteins that actively participate in vascular pathophysiological processes and novel protein candidates that can potentially serve as useful clinical biomarkers. Although both types of proteins can be identified by similar proteomic strategies and methods, it is important to clearly distinguish biomarkers from mediators of disease. A particular protein, or group of proteins, may participate in a pathogenic process but not serve as an effective biomarker. Alternatively, a useful biomarker may not mediate pathogenic pathways associated with disease (i.e., C-reactive protein). To date, there are no clear successful examples in which discovery proteomics has led to a novel useful clinical biomarker in cardiovascular diseases. Nevertheless, new sources of biomarkers are being explored (i.e., secretomes, circulating cells, exosomes and microparticles), an increasing number of novel proteins involved in atherogenesis are constantly described, and new technologies and analytical strategies (i.e., quantitative proteomics) are being developed to access low abundant proteins. Therefore, this presages a new era of discovery and a further step in the practical application to diagnosis, prognosis and early action by medical treatment of cardiovascular diseases. PMID:18937558

  8. A proteomics approach to the identification of biomarkers for psoriasis utilising keratome biopsy

    DEFF Research Database (Denmark)

    Williamson, James C; Scheipers, Peter; Schwämmle, Veit; Zibert, John Robert; Beck, Hans Christian; Jensen, Ole N

    2013-01-01

    The discovery of plasma biomarkers for psoriasis vulgaris may aid clinicians in disease grading and monitoring of treatment response. We have therefore developed a proteomics/mass spectrometry based workflow which enables biomarker discovery from psoriasis patient samples. We have utilised keratome...... skin biopsy, which results in reduced cellular complexity compared to punch biopsy. Furthermore, we applied short term ex vivo culture in order to enrich for a "secretome" sub-proteome reflective of the disease and enriched in potential biomarkers. Using these sample preparation techniques we performed...... a quantitative proteomics screen of four patients with psoriasis using stable isotope dimethyl labelling and identified over 50 proteins consistently altered in abundance in psoriasis lesional versus non-lesional skin. This includes several canonical psoriasis related proteins (e.g. S100A7...

  9. Worldwide Discoveries Help People Everywhere

    Science.gov (United States)

    ... Home Current Issue Past Issues Special Section Worldwide Discoveries Help People Everywhere Past Issues / Spring 2008 Table ... shows examples of discoveries and their impact. Diseases Discoveries The Benefits for All Americans Huntington's Disease Venezuela— ...

  10. MicroRNA signatures as clinical biomarkers in lung cancer

    Directory of Open Access Journals (Sweden)

    Markou A

    2015-05-01

    Full Text Available Athina Markou, Martha Zavridou, Evi S Lianidou Analysis of Circulating Tumor Cells, Lab of Analytical Chemistry, Department of Chemistry, University of Athens, Athens, Greece Abstract: Even if early lung cancer detection has been recently significantly improved, the invasive nature of current diagnostic procedures, and a relatively high percentage of false positives, is limiting the application of modern detection tools. The discovery and clinical evaluation of novel specific and robust non-invasive biomarkers for diagnosis of lung cancer at an early stage, as well as for better prognosis and prediction of therapy response, is very challenging. MicroRNAs (miRNAs can play an important role in the diagnosis and management of lung cancer patients, as important and reliable biomarkers for cancer detection and prognostic prediction, and even as promising as novel targets for cancer therapy. miRNAs are important in cancer pathogenesis, and deregulation of their expression levels has been detected not only in lung cancer but in many other human tumor types. Numerous studies strongly support the potential of miRNAs as biomarkers in non-small-cell lung cancer, and there is increasing evidence that altered miRNA expression is associated with tumor progression and survival. It is worth mentioning also that detection of miRNAs circulating in plasma or serum has enormous potential, because miRNAs serve as non-invasive biomarkers not only for the diagnosis and prognosis of the disease, but also as novel response and sensitivity predictors for cancer treatment. In this review, we summarize the current findings on the critical role of miRNAs in lung cancer tumorigenesis and highlight their potential as circulating biomarkers in lung cancer. Our review is based on papers that have been published after 2011, and includes the key words “miRNAs” and “lung cancer”. Keywords: non-small-cell lung carcinoma, miRNAs, tumor biomarkers, circulating miRNAs, liquid

  11. Discovery informatics in biological and biomedical sciences: research challenges and opportunities.

    Science.gov (United States)

    Honavar, Vasant

    2015-01-01

    New discoveries in biological, biomedical and health sciences are increasingly being driven by our ability to acquire, share, integrate and analyze, and construct and simulate predictive models of biological systems. While much attention has focused on automating routine aspects of management and analysis of "big data", realizing the full potential of "big data" to accelerate discovery calls for automating many other aspects of the scientific process that have so far largely resisted automation: identifying gaps in the current state of knowledge; generating and prioritizing questions; designing studies; designing, prioritizing, planning, and executing experiments; interpreting results; forming hypotheses; drawing conclusions; replicating studies; validating claims; documenting studies; communicating results; reviewing results; and integrating results into the larger body of knowledge in a discipline. Against this background, the PSB workshop on Discovery Informatics in Biological and Biomedical Sciences explores the opportunities and challenges of automating discovery or assisting humans in discovery through advances (i) Understanding, formalization, and information processing accounts of, the entire scientific process; (ii) Design, development, and evaluation of the computational artifacts (representations, processes) that embody such understanding; and (iii) Application of the resulting artifacts and systems to advance science (by augmenting individual or collective human efforts, or by fully automating science). PMID:25592607

  12. 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.

  13. 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

  14. Advances in Computer, Communication, Control and Automation

    CERN Document Server

    011 International Conference on Computer, Communication, Control and Automation

    2012-01-01

    The volume includes a set of selected papers extended and revised from the 2011 International Conference on Computer, Communication, Control and Automation (3CA 2011). 2011 International Conference on Computer, Communication, Control and Automation (3CA 2011) has been held in Zhuhai, China, November 19-20, 2011. This volume  topics covered include signal and Image processing, speech and audio Processing, video processing and analysis, artificial intelligence, computing and intelligent systems, machine learning, sensor and neural networks, knowledge discovery and data mining, fuzzy mathematics and Applications, knowledge-based systems, hybrid systems modeling and design, risk analysis and management, system modeling and simulation. We hope that researchers, graduate students and other interested readers benefit scientifically from the proceedings and also find it stimulating in the process.

  15. Library Automation Style Guide.

    Science.gov (United States)

    Gaylord Bros., Liverpool, NY.

    This library automation style guide lists specific terms and names often used in the library automation industry. The terms and/or acronyms are listed alphabetically and each is followed by a brief definition. The guide refers to the "Chicago Manual of Style" for general rules, and a notes section is included for the convenience of individual…

  16. Automation in Warehouse Development

    NARCIS (Netherlands)

    Hamberg, R.; Verriet, J.

    2012-01-01

    The warehouses of the future will come in a variety of forms, but with a few common ingredients. Firstly, human operational handling of items in warehouses is increasingly being replaced by automated item handling. Extended warehouse automation counteracts the scarcity of human operators and support

  17. Automate functional testing

    Directory of Open Access Journals (Sweden)

    Ramesh Kalindri

    2014-06-01

    Full Text Available Currently, software engineers are increasingly turning to the option of automating functional tests, but not always have successful in this endeavor. Reasons range from low planning until over cost in the process. Some principles that can guide teams in automating these tests are described in this article.

  18. Biomarkers of HIV-1 associated dementia: proteomic investigation of sera

    Directory of Open Access Journals (Sweden)

    Duan Fenghai

    2009-03-01

    Full Text Available Abstract Background New, more sensitive and specific biomarkers are needed to support other means of clinical diagnosis of neurodegenerative disorders. Proteomics technology is widely used in discovering new biomarkers. There are several difficulties with in-depth analysis of human plasma/serum, including that there is no one proteomic platform that can offer complete identification of differences in proteomic profiles. Another set of problems is associated with heterogeneity of human samples in addition intrinsic variability associated with every step of proteomic investigation. Validation is the very last step of proteomic investigation and it is very often difficult to validate potential biomarker with desired sensitivity and specificity. Even though it may be possible to validate a differentially expressed protein, it may not necessarily prove to be a valid diagnostic biomarker. Results In the current study we report results of proteomic analysis of sera from HIV-infected individuals with or without cognitive impairment. Application of SELDI-TOF analysis followed by weak cation exchange chromatography and 1-dimensional electrophoresis led to discovery of gelsolin and prealbumin as differentially expressed proteins which were not detected in this cohort of samples when previously investigated by 2-dimensional electrophoresis with Difference Gel Electrophoresis technology. Conclusion Validation using western-blot analysis led us to conclude that relative change of the levels of these proteins in one patient during a timeframe might be more informative, sensitive and specific than application of average level estimated based on an even larger cohort of patients.

  19. Automation in Immunohematology

    Directory of Open Access Journals (Sweden)

    Meenu Bajpai

    2012-01-01

    Full Text Available There have been rapid technological advances in blood banking in South Asian region over the past decade with an increasing emphasis on quality and safety of blood products. The conventional test tube technique has given way to newer techniques such as column agglutination technique, solid phase red cell adherence assay, and erythrocyte-magnetized technique. These new technologies are adaptable to automation and major manufacturers in this field have come up with semi and fully automated equipments for immunohematology tests in the blood bank. Automation improves the objectivity and reproducibility of tests. It reduces human errors in patient identification and transcription errors. Documentation and traceability of tests, reagents and processes and archiving of results is another major advantage of automation. Shifting from manual methods to automation is a major undertaking for any transfusion service to provide quality patient care with lesser turnaround time for their ever increasing workload. This article discusses the various issues involved in the process.

  20. Automated model building

    CERN Document Server

    Caferra, Ricardo; Peltier, Nicholas

    2004-01-01

    This is the first book on automated model building, a discipline of automated deduction that is of growing importance Although models and their construction are important per se, automated model building has appeared as a natural enrichment of automated deduction, especially in the attempt to capture the human way of reasoning The book provides an historical overview of the field of automated deduction, and presents the foundations of different existing approaches to model construction, in particular those developed by the authors Finite and infinite model building techniques are presented The main emphasis is on calculi-based methods, and relevant practical results are provided The book is of interest to researchers and graduate students in computer science, computational logic and artificial intelligence It can also be used as a textbook in advanced undergraduate courses

  1. Automation in Warehouse Development

    CERN Document Server

    Verriet, Jacques

    2012-01-01

    The warehouses of the future will come in a variety of forms, but with a few common ingredients. Firstly, human operational handling of items in warehouses is increasingly being replaced by automated item handling. Extended warehouse automation counteracts the scarcity of human operators and supports the quality of picking processes. Secondly, the development of models to simulate and analyse warehouse designs and their components facilitates the challenging task of developing warehouses that take into account each customer’s individual requirements and logistic processes. Automation in Warehouse Development addresses both types of automation from the innovative perspective of applied science. In particular, it describes the outcomes of the Falcon project, a joint endeavour by a consortium of industrial and academic partners. The results include a model-based approach to automate warehouse control design, analysis models for warehouse design, concepts for robotic item handling and computer vision, and auton...

  2. Advances in inspection automation

    Science.gov (United States)

    Weber, Walter H.; Mair, H. Douglas; Jansen, Dion; Lombardi, Luciano

    2013-01-01

    This new session at QNDE reflects the growing interest in inspection automation. Our paper describes a newly developed platform that makes the complex NDE automation possible without the need for software programmers. Inspection tasks that are tedious, error-prone or impossible for humans to perform can now be automated using a form of drag and drop visual scripting. Our work attempts to rectify the problem that NDE is not keeping pace with the rest of factory automation. Outside of NDE, robots routinely and autonomously machine parts, assemble components, weld structures and report progress to corporate databases. By contrast, components arriving in the NDT department typically require manual part handling, calibrations and analysis. The automation examples in this paper cover the development of robotic thickness gauging and the use of adaptive contour following on the NRU reactor inspection at Chalk River.

  3. 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. PMID:25448391

  4. Leadership and Discovery

    CERN Document Server

    Goethals, George R

    2009-01-01

    This book, a collection of essays from scholars across disciplines, explores leadership of discovery, probing the guided and collaborative exploration and interpretation of the experience of our inner thoughts and feelings, and of our external worlds

  5. 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)

  6. 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...

  7. Higgs Discovery before LHC?

    OpenAIRE

    Chiarelli, Giorgio; Collaboration, for the CDF; The D0 Collaboration

    2001-01-01

    The proposed Run IIb of the Tevatron Collider will provide 15 fb-1 worth of ppbar data at c.o.m energy of 2 TeV per experiment by year 2007. We review the plans of the Tevatron accelerator complex upgrade and the plans for the upgrades of the experiments to match this challenge. Perspectives for the discovery of an Higgs particle are reviewed and the concrete possibility of a 5 sigmas discovery for a low mass Higgs are discussed.

  8. Imaging Biomarkers in Immunotherapy

    Science.gov (United States)

    Juergens, Rosalyn A.; Zukotynski, Katherine A.; Singnurkar, Amit; Snider, Denis P.; Valliant, John F.; Gulenchyn, Karen Y.

    2016-01-01

    Immune-based therapies have been in use for decades but recent work with immune checkpoint inhibitors has now changed the landscape of cancer treatment as a whole. While these advances are encouraging, clinicians still do not have a consistent biomarker they can rely on that can accurately select patients or monitor response. Molecular imaging technology provides a noninvasive mechanism to evaluate tumors and may be an ideal candidate for these purposes. This review provides an overview of the mechanism of action of varied immunotherapies and the current strategies for monitoring patients with imaging. We then describe some of the key researches in the preclinical and clinical literature on the current uses of molecular imaging of the immune system and cancer. PMID:26949344

  9. Biomarkers for lymphoma

    Energy Technology Data Exchange (ETDEWEB)

    Zangar, Richard C.; Varnum, Susan M.

    2014-09-02

    A biomarker, method, test kit, and diagnostic system for detecting the presence of lymphoma in a person are disclosed. The lymphoma may be Hodgkin's lymphoma or non-Hodgkin's lymphoma. The person may be a high-risk subject. In one embodiment, a plasma sample from a person is obtained. The level of at least one protein listed in Table S3 in the plasma sample is measured. The level of at least one protein in the plasma sample is compared with the level in a normal or healthy subject. The lymphoma is diagnosed based upon the level of the at least one protein in the plasma sample in comparison to the normal or healthy level.

  10. SEMANTIC WEB SERVICES – DISCOVERY, SELECTION AND COMPOSITION TECHNIQUES

    Directory of Open Access Journals (Sweden)

    Sowmya Kamath S

    2013-02-01

    Full Text Available Web services are already one of the most important resources on the Internet. As an integrated solution for realizing the vision of the Next Generation Web, semantic web services combine semantic web technology with web service technology, envisioning automated life cycle management of web services. This paper discusses the significance and importance of service discovery & selection to business logic, and the requisite current research in the various phases of the semantic web service lifecycle like discovery and selection. We also present several different composition strategies, based on current research, and provide an outlook towards critical future work.

  11. Automatic Discovery of Information Resources on the World Wide Web

    Institute of Scientific and Technical Information of China (English)

    ZHU Guo-jin; CHEN Jia-xun

    2002-01-01

    A basis for automatic discovery of information resources on the World Wide Web is characterized by three underlying equations. With these equations, the information universe on the Web is divided into three associated spaces. This model differs from the hypertext employed by the Web, in that the former supports the notion of automatic resource discovery. A private library, which is able to gather automatically from the Web the information useful to the library owner, is envisaged to illustrate that the basic equations and their derivations can be applied to Web automation, including crawling and classifying.

  12. 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.

  13. Towards temporal relation discovery from the clinical narrative.

    Science.gov (United States)

    Savova, Guergana; Bethard, Steven; Styler, Will; Martin, James; Palmer, Martha; Masanz, James; Ward, Wayne

    2009-01-01

    Disease progression and understanding relies on temporal concepts. Discovery of automated temporal relations and timelines from the clinical narrative allows for mining large data sets of clinical text to uncover patterns at the disease and patient level. Our overall goal is the complex task of building a system for automated temporal relation discovery. As a first step, we evaluate enabling methods from the general natural language processing domain - deep parsing and semantic role labeling in predicate-argument structures - to explore their portability to the clinical domain. As a second step, we develop an annotation schema for temporal relations based on TimeML. In this paper we report results and findings from these first steps. Our next efforts will scale up the data collection to develop domain-specific modules for the enabling technologies within Mayo's open-source clinical Text Analysis and Knowledge Extraction System. PMID:20351919

  14. Improvement of Test Automation

    OpenAIRE

    Räsänen, Timo

    2013-01-01

    The purpose for this study was to find out how to ensure that the automated testing of MME in the Network Verification will continue smooth and reliable while using the in-house developed test automation framework. The goal of this thesis was to reveal the reasons of the currently challenging situation and to find the key elements to be improved in the MME testing carried by the test automation. Also a reason for the study was to get solutions as to how to change the current procedures and wa...

  15. Chef infrastructure automation cookbook

    CERN Document Server

    Marschall, Matthias

    2013-01-01

    Chef Infrastructure Automation Cookbook contains practical recipes on everything you will need to automate your infrastructure using Chef. The book is packed with illustrated code examples to automate your server and cloud infrastructure.The book first shows you the simplest way to achieve a certain task. Then it explains every step in detail, so that you can build your knowledge about how things work. Eventually, the book shows you additional things to consider for each approach. That way, you can learn step-by-step and build profound knowledge on how to go about your configuration management

  16. Network biomarkers, interaction networks and dynamical network biomarkers in respiratory diseases

    OpenAIRE

    Wu, Xiaodan; Chen, Luonan; Wang, Xiangdong

    2014-01-01

    Identification and validation of interaction networks and network biomarkers have become more critical and important in the development of disease-specific biomarkers, which are functionally changed during disease development, progression or treatment. The present review headlined the definition, significance, research and potential application for network biomarkers, interaction networks and dynamical network biomarkers (DNB). Disease-specific interaction networks, network biomarkers, or DNB...

  17. iPTF Discoveries of Recent Type Ia Supernovae

    Science.gov (United States)

    Papadogiannakis, S.; Taddia, F.; Petrushevska, T.; Ferretti, R.; Fremling, C.; Karamehmetoglu, E.; Nyholm, A.; Roy, R.; Hangard, L.; Vreeswijk, P.; Horesh, A.; Manulis, I.; Rubin, A.; Yaron, O.; Leloudas, G.; Khazov, D.; Soumagnac, M.; Knezevic, S.; Johansson, J.; Nir, G.; Cao, Y.; Blagorodnova, N.; Kulkarni, S.

    2016-05-01

    The intermediate Palomar Transient Factory (ATel #4807) reports the discovery and classification of the following Type Ia SNe. Our automated candidate vetting to distinguish a real astrophysical source (1.0) from bogus artefacts (0.0) is powered by three generations of machine learning algorithms: RB2 (Brink et al. 2013MNRAS.435.1047B), RB4 (Rebbapragada et al. 2015AAS...22543402R) and RB5 (Wozniak et al. 2013AAS...22143105W).

  18. Fractionated Marine Invertebrate Extract Libraries for Drug Discovery

    OpenAIRE

    Ireland, Chris M.; Jason Reppart; McCulloch, Malcolm W.B.; Mary Kay Harper; Bugni, Tim S.

    2008-01-01

    The high-throughput screening and drug discovery paradigm has necessitated a change in preparation of natural product samples for screening programs. In an attempt to improve the quality of marine natural products samples for screening, several fractionation strategies were investigated. The final method used HP20SS as a solid support to effectively desalt extracts and fractionate the organic components. Additionally, methods to integrate an automated LCMS fractionation approach to shorten di...

  19. A Decade of Discovery

    Energy Technology Data Exchange (ETDEWEB)

    None

    2008-01-01

    This book provides a fascinating account of some of the most significant scientific discoveries and technological innovations coming out of the U.S. Department of Energy’s National Laboratories. This remarkable book illustrates how the men and women of the National Laboratories are keeping us on the cutting edge. Though few Americans are familiar with the scope and scale of the work conducted at these National Laboratories, their research is literally changing our lives and bettering our planet. The book describes the scientific discoveries and technological advancements "in recognition of the men and women working in DOE's seventeen national laboratories across the country." Through highly vivid and accessible stories, this book details recent breakthroughs in three critical areas: 1) Energy and Environment, 2) National Security and 3) Life and Physical Science. The book illustrates how this government-funded research has resulted in more energy-efficient buildings; new, cleaner alternative fuels that reduce greenhouse gas emissions; safer, more efficient, nuclear power plants; improved responses to disease outbreaks; more secure and streamlined airport security; more effective treatments for cancer and other diseases; and astonishing discoveries that are altering our understanding of the universe and enabling scientific breakthroughs in fields such as nanotechnology and particle physics. Specifically, it contains 37 stories. A Decade of Discovery is truly a recent history of discovery - and a fascinating look at what the next decade holds.

  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. 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.

  2. Biomarker in archaeological soils

    Science.gov (United States)

    Wiedner, Katja; Glaser, Bruno; Schneeweiß, Jens

    2015-04-01

    The use of biomarkers in an archaeological context allow deeper insights into the understanding of anthropogenic (dark) earth formation and from an archaeological point of view, a completely new perspective on cultivation practices in the historic past. During an archaeological excavation of a Slavic settlement (10th/11th C. A.D.) in Brünkendorf (Wendland region in Northern Germany), a thick black soil (Nordic Dark Earth) was discovered that resembled the famous terra preta phenomenon. For the humid tropics, terra preta could act as model for sustainable agricultural practices and as example for long-term CO2-sequestration into terrestrial ecosystems. The question was whether this Nordic Dark Earth had similar properties and genesis as the famous Amazonian Dark Earth in order to find a model for sustainable agricultural practices and long term CO2-sequestration in temperate zones. For this purpose, a multi-analytical approach was used to characterize the sandy-textured Nordic Dark Earth in comparison to less anthropogenically influenced soils in the adjacent area in respect of ecological conditions (e.g. amino sugar), input materials (faeces) and the presence of stable soil organic matter (black carbon). Amino sugar analyses showed that Nordic Dark Earth contained higher amounts of microbial residues being dominated by soil fungi. Faecal biomarkers such as stanols and bile acids indicated animal manure from omnivores and herbivores but also human excrements. Black carbon content of about 30 Mg ha-1 in the Nordic Dark Earth was about four times higher compared to the adjacent soil and in the same order of magnitude compared to terra preta. Our data strongly suggest parallels to anthropogenic soil formation in Amazonia and in Europe by input of organic wastes, faecal material and charred organic matter. An obvious difference was that in terra preta input of human-derived faecal material dominated while in NDE human-derived faecal material played only a minor role

  3. Biomarkers in Acute Lung Injury

    OpenAIRE

    Bhargava, Maneesh; Wendt, Chris

    2012-01-01

    Acute Respiratory Distress Syndrome (ARDS) and Acute Lung Injury (ALI) result in high permeability pulmonary edema causing hypoxic respiratory failure with high morbidity and mortality. As the population ages, the incidence of ALI is expected to rise. Over the last decade, several studies have identified biomarkers in plasma and bronchoalveolar lavage fluid providing important insights into the mechanisms involved in the pathophysiology of ALI. Several biomarkers have been validated in subjec...

  4. Cardiac Biomarkers and Cycling Race

    OpenAIRE

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

    2015-01-01

    In cycling as in other types of strenuous exercise, there exists a risk of sudden death. It is important both to understand its causes and to see if the behavior of certain biomarkers might highlight athletes at risk. Many reports describe changes in biomarkers after strenuous exercise (Nie et al., 2011), but interpreting these changes, and notably distinguishing normal physiological responses from pathological changes, is not easy. Here we have focused on the kinetics of different cardiac bi...

  5. Biomarkers of replicative senescence revisited

    DEFF Research Database (Denmark)

    Nehlin, Jan

    2016-01-01

    of telomere length and associated damage, and the accompanying changes that take place elicit signals that have an impact on a number of molecules and downstream events. Precise measurements of replicative senescence biomarkers in biological samples from individuals could be clinically associated...... with their chronological age and present health status, help define their current rate of aging and contribute to establish personalized therapy plans to reduce, counteract or even avoid the appearance of aging biomarkers....

  6. Biomarkers of environmental benzene exposure.

    OpenAIRE

    Weisel, C; Yu, R; Roy, A; Georgopoulos, P.

    1996-01-01

    Environmental exposures to benzene result in increases in body burden that are reflected in various biomarkers of exposure, including benzene in exhaled breath, benzene in blood and urinary trans-trans-muconic acid and S-phenylmercapturic acid. A review of the literature indicates that these biomarkers can be used to distinguish populations with different levels of exposure (such as smokers from nonsmokers and occupationally exposed from environmentally exposed populations) and to determine d...

  7. 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

  8. Automated Vehicles Symposium 2014

    CERN Document Server

    Beiker, Sven; Road Vehicle Automation 2

    2015-01-01

    This paper collection is the second volume of the LNMOB series on Road Vehicle Automation. The book contains a comprehensive review of current technical, socio-economic, and legal perspectives written by experts coming from public authorities, companies and universities in the U.S., Europe and Japan. It originates from the Automated Vehicle Symposium 2014, which was jointly organized by the Association for Unmanned Vehicle Systems International (AUVSI) and the Transportation Research Board (TRB) in Burlingame, CA, in July 2014. The contributions discuss the challenges arising from the integration of highly automated and self-driving vehicles into the transportation system, with a focus on human factors and different deployment scenarios. This book is an indispensable source of information for academic researchers, industrial engineers, and policy makers interested in the topic of road vehicle automation.

  9. I-94 Automation FAQs

    Data.gov (United States)

    Department of Homeland Security — In order to increase efficiency, reduce operating costs and streamline the admissions process, U.S. Customs and Border Protection has automated Form I-94 at air and...

  10. Automated Vehicles Symposium 2015

    CERN Document Server

    Beiker, Sven

    2016-01-01

    This edited book comprises papers about the impacts, benefits and challenges of connected and automated cars. It is the third volume of the LNMOB series dealing with Road Vehicle Automation. The book comprises contributions from researchers, industry practitioners and policy makers, covering perspectives from the U.S., Europe and Japan. It is based on the Automated Vehicles Symposium 2015 which was jointly organized by the Association of Unmanned Vehicle Systems International (AUVSI) and the Transportation Research Board (TRB) in Ann Arbor, Michigan, in July 2015. The topical spectrum includes, but is not limited to, public sector activities, human factors, ethical and business aspects, energy and technological perspectives, vehicle systems and transportation infrastructure. This book is an indispensable source of information for academic researchers, industrial engineers and policy makers interested in the topic of road vehicle automation.

  11. Hydrometeorological Automated Data System

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Office of Hydrologic Development of the National Weather Service operates HADS, the Hydrometeorological Automated Data System. This data set contains the last...

  12. An automated Certification Authority

    CERN Document Server

    Shamardin, L V

    2002-01-01

    This note describe an approach to building an automated Certification Authority. It is compatible with basic requirements of RFC2527. It also supports Registration Authorities and Globus Toolkit grid-cert-renew automatic certificate renewal.

  13. Disassembly automation automated systems with cognitive abilities

    CERN Document Server

    Vongbunyong, Supachai

    2015-01-01

    This book presents a number of aspects to be considered in the development of disassembly automation, including the mechanical system, vision system and intelligent planner. The implementation of cognitive robotics increases the flexibility and degree of autonomy of the disassembly system. Disassembly, as a step in the treatment of end-of-life products, can allow the recovery of embodied value left within disposed products, as well as the appropriate separation of potentially-hazardous components. In the end-of-life treatment industry, disassembly has largely been limited to manual labor, which is expensive in developed countries. Automation is one possible solution for economic feasibility. The target audience primarily comprises researchers and experts in the field, but the book may also be beneficial for graduate students.

  14. Automating Supplier Selection Procedures

    OpenAIRE

    Davidrajuh, Reggie

    2001-01-01

    This dissertation describes a methodology, tools, and implementation techniques of automating supplier selection procedures of a small and medium-sized agile virtual enterprise. Firstly, a modeling approach is devised that can be used to model the supplier selection procedures of an enterprise. This modeling approach divides the supplier selection procedures broadly into three stages, the pre-selection, selection, and post-selection stages. Secondly, a methodology is presented for automating ...

  15. Taiwan Automated Telescope Network

    OpenAIRE

    Shuhrat Ehgamberdiev; Alexander Serebryanskiy; Antonio Jimenez; Li-Han Wang; Ming-Tsung Sun; Javier Fernandez Fernandez; Dean-Yi Chou

    2010-01-01

    A global network of small automated telescopes, the Taiwan Automated Telescope (TAT) network, dedicated to photometric measurements of stellar pulsations, is under construction. Two telescopes have been installed in Teide Observatory, Tenerife, Spain and Maidanak Observatory, Uzbekistan. The third telescope will be installed at Mauna Loa Observatory, Hawaii, USA. Each system uses a 9-cm Maksutov-type telescope. The effective focal length is 225 cm, corresponding to an f-ratio of 25. The field...

  16. Automated Lattice Perturbation Theory

    Energy Technology Data Exchange (ETDEWEB)

    Monahan, Christopher

    2014-11-01

    I review recent developments in automated lattice perturbation theory. Starting with an overview of lattice perturbation theory, I focus on the three automation packages currently "on the market": HiPPy/HPsrc, Pastor and PhySyCAl. I highlight some recent applications of these methods, particularly in B physics. In the final section I briefly discuss the related, but distinct, approach of numerical stochastic perturbation theory.

  17. Automated functional software testing

    OpenAIRE

    Jelnikar, Kristina

    2009-01-01

    The following work describes an approach to software test automation of functional testing. In the introductory part we are introducing what testing problems development companies are facing. The second chapter describes some testing methods, what role does testing have in software development, some approaches to software development and the meaning of testing environment. Chapter 3 is all about test automation. After a brief historical presentation, we are demonstrating through s...

  18. Instant Sikuli test automation

    CERN Document Server

    Lau, Ben

    2013-01-01

    Get to grips with a new technology, understand what it is and what it can do for you, and then get to work with the most important features and tasks. A concise guide written in an easy-to follow style using the Starter guide approach.This book is aimed at automation and testing professionals who want to use Sikuli to automate GUI. Some Python programming experience is assumed.

  19. Neuroimmune biomarkers in schizophrenia.

    Science.gov (United States)

    Tomasik, Jakub; Rahmoune, Hassan; Guest, Paul C; Bahn, Sabine

    2016-09-01

    Schizophrenia is a heterogeneous psychiatric disorder with a broad spectrum of clinical and biological manifestations. Due to the lack of objective tests, the accurate diagnosis and selection of effective treatments for schizophrenia remains challenging. Numerous technologies have been employed in search of schizophrenia biomarkers. These studies have suggested that neuroinflammatory processes may play a role in schizophrenia pathogenesis, at least in a subgroup of patients. The evidence indicates alterations in both pro- and anti-inflammatory molecules in the central nervous system, which have also been found in peripheral tissues and may correlate with schizophrenia symptoms. In line with these findings, certain immunomodulatory interventions have shown beneficial effects on psychotic symptoms in schizophrenia patients, in particular those with distinct immune signatures. In this review, we evaluate these findings and their potential for more targeted drug interventions and the development of companion diagnostics. Although currently no validated markers exist for schizophrenia patient stratification or the prediction of treatment efficacy, we propose that utilisation of inflammatory markers for diagnostic and theranostic purposes may lead to novel therapeutic approaches and deliver more effective care for schizophrenia patients. PMID:25124519

  20. Biomarkers in connective tissue disease-associated interstitial lung disease.

    Science.gov (United States)

    Bonella, Francesco; Costabel, Ulrich

    2014-04-01

    This article reviews major biomarkers in serum and bronchoalveolar lavage fluid (BALF) with respect to their diagnostic and prognostic value in connective tissue disease-associated interstitial lung disease (CTD-ILD). In some CTD such as systemic sclerosis (SSc), the incidence of ILD is up to two-third of patients, and currently ILD represents the leading cause of death in SSc. Because of the extremely variable incidence and outcome of ILD in CTD, progress in the discovery and validation of biomarkers for diagnosis, prognosis, patients' subtyping, response to treatment, or as surrogate endpoints in clinical trials is extremely important. In contrast to idiopathic interstitial pneumonias, autoantibodies play a crucial role as biomarkers in CTD-ILD because their presence is strictly linked to the pathogenesis and tissue damage. Patterns of autoantibodies, for instance, anticitrullinated peptide antibodies in rheumatoid arthritis or aminoacyl-tRNA synthetases (ARS) in polymyositis/dermatomyositis, have been found to correlate with the presence and occasionally with the course of ILD in CTD. Besides autoantibodies, an increase in serum or BALF of a biomarker of pulmonary origin may be able to predict or reflect the development of fibrosis, the impairment of lung function, and ideally also the prognosis. Promising biomarkers are lung epithelium-derived proteins such as KL-6 (Krebs von den Lungen-6), SP-D (surfactant protein-D), SP-A (surfactant protein-A), YKL-40 (chitinase-3-like protein 1 [CHI3L1] or cytokines such as CCL18 [chemokine (C-C) motif ligand 18]). In the future, genetic/epigenetic markers, such as human leukocyte antigen (HLA) haplotypes, single nucleotide polymorphisms, and micro-RNA, may help to identify subtypes of patients with different needs of management and treatment strategies. PMID:24668534

  1. Computational chemistry, data mining, high-throughput synthesis and screening - informatics and integration in drug discovery

    OpenAIRE

    Charles J. Manly

    2001-01-01

    Drug discovery today includes considerable focus of laboratory automation and other resources on both combinatorial chemistry and high-throughput screening, and computational chemistry has been a part of pharmaceutical research for many years. The real benefit of these technologies is beyond the exploitation of each individually. Only recently have significant efforts focused on effectively integrating these and other discovery disciplines to realize their larger potential. This technical not...

  2. Evaluating ten discoveries

    Energy Technology Data Exchange (ETDEWEB)

    1973-02-01

    Mexico's state company, Pemex, announces 10 significant oil and gas discoveries in the states of Tamaulipas and Chiapas. Most promising finds are a new oil province in S. Mexico and a deeper pool strike at the offshore Arenque field. The latter seems to point to the existence of an attractive reefal trend extending on shore toward the State of Nuevo Leon.

  3. 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...

  4. Quantitative DMS mapping for automated RNA secondary structure inference

    OpenAIRE

    Cordero, Pablo; Kladwang, Wipapat; VanLang, Christopher C.; Das, Rhiju

    2012-01-01

    For decades, dimethyl sulfate (DMS) mapping has informed manual modeling of RNA structure in vitro and in vivo. Here, we incorporate DMS data into automated secondary structure inference using a pseudo-energy framework developed for 2'-OH acylation (SHAPE) mapping. On six non-coding RNAs with crystallographic models, DMS- guided modeling achieves overall false negative and false discovery rates of 9.5% and 11.6%, comparable or better than SHAPE-guided modeling; and non-parametric bootstrappin...

  5. 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.

  6. Collagen fragment biomarkers as serological biomarkers of lean body mass

    DEFF Research Database (Denmark)

    Nedergaard, A.; Dalgas, U.; Primdahl, H.;

    2015-01-01

    Background Loss of muscle mass and function is an important complication to ageing and a range of pathologies, including, but not restricted to, cancer, organ failures, and sepsis. A number of interventions have been proposed ranging from exercise to anabolic pharmacological therapy, with varying...... success. Easily applicable serological biomarkers of lean and/or muscle mass and change therein would benefit monitoring of muscle mass during muscle atrophy as well as during recovery. We set out to validate if novel peptide biomarkers derived from Collagen III and VI were markers of lean body mass (LBM...

  7. Fully Automated RNAscope In Situ Hybridization Assays for Formalin-Fixed Paraffin-Embedded Cells and Tissues.

    Science.gov (United States)

    Anderson, Courtney M; Zhang, Bingqing; Miller, Melanie; Butko, Emerald; Wu, Xingyong; Laver, Thomas; Kernag, Casey; Kim, Jeffrey; Luo, Yuling; Lamparski, Henry; Park, Emily; Su, Nan; Ma, Xiao-Jun

    2016-10-01

    Biomarkers such as DNA, RNA, and protein are powerful tools in clinical diagnostics and therapeutic development for many diseases. Identifying RNA expression at the single cell level within the morphological context by RNA in situ hybridization provides a great deal of information on gene expression changes over conventional techniques that analyze bulk tissue, yet widespread use of this technique in the clinical setting has been hampered by the dearth of automated RNA ISH assays. Here we present an automated version of the RNA ISH technology RNAscope that is adaptable to multiple automation platforms. The automated RNAscope assay yields a high signal-to-noise ratio with little to no background staining and results comparable to the manual assay. In addition, the automated duplex RNAscope assay was able to detect two biomarkers simultaneously. Lastly, assay consistency and reproducibility were confirmed by quantification of TATA-box binding protein (TBP) mRNA signals across multiple lots and multiple experiments. Taken together, the data presented in this study demonstrate that the automated RNAscope technology is a high performance RNA ISH assay with broad applicability in biomarker research and diagnostic assay development. J. Cell. Biochem. 117: 2201-2208, 2016. © 2016 Wiley Periodicals, Inc. PMID:27191821

  8. COPD Discovery Might Improve Treatment

    Science.gov (United States)

    ... nlm.nih.gov/medlineplus/news/fullstory_158852.html COPD Discovery Might Improve Treatment Study may help pinpoint ... will progress, a discovery they believe could improve COPD treatment. Their research might help doctors determine which ...

  9. COPD Discovery Might Improve Treatment

    Science.gov (United States)

    ... page: https://medlineplus.gov/news/fullstory_158852.html COPD Discovery Might Improve Treatment Study may help pinpoint ... will progress, a discovery they believe could improve COPD treatment. Their research might help doctors determine which ...

  10. Creating A Guided- discovery Lesson

    Institute of Scientific and Technical Information of China (English)

    田枫

    2005-01-01

    In a guided - discovery lesson, students sequentially uncover layers of mathematical information one step at a time and learn new mathematics. We have identified eight critical steps necessary in developing a successful guided- discovery lesson.

  11. 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.

  12. Plasma and urine biomarkers in acute viral hepatitis E

    Directory of Open Access Journals (Sweden)

    Aggarwal Rakesh

    2009-10-01

    Full Text Available Abstract Background Hepatitis E, caused by the hepatitis E virus (HEV, is endemic to developing countries where it manifests as waterborne outbreaks and sporadic cases. Though generally self-limited with a low mortality rate, some cases progress to fulminant hepatic failure (FHF with high mortality. With no identified predictive or diagnostic markers, the events leading to disease exacerbation are not known. Our aim is to use proteomic tools to identify biomarkers of acute and fulminant hepatitis E. Results We analyzed proteins in the plasma and urine of hepatitis E patients and healthy controls by two-dimensional Differential Imaging Gel Electrophoresis (DIGE and mass spectrometry, and identified over 30 proteins to be differentially expressed during acute hepatitis E. The levels of one plasma protein, transthyretin, and one urine protein, alpha-1-microglobulin (α1m, were then quantitated by enzyme immunoassay (EIA in clinical samples from a larger group of patients and controls. The results showed decreased plasma transthyretin levels (p Conclusion Our results demonstrate the utility of characterizing plasma and urine proteomes for signatures of the host response to HEV infection. We predict that plasma transthyretin and urine α1m could be reliable biomarkers of acute hepatitis E. Besides the utility of this approach to biomarker discovery, proteome-level changes in human biofluids would also guide towards a better understanding of host-virus interaction and disease.

  13. Translating colorectal cancer genetics into clinically useful biomarkers.

    Science.gov (United States)

    Morley-Bunker, A; Walker, L C; Currie, M J; Pearson, J; Eglinton, T

    2016-08-01

    Colorectal cancer (CRC) is a major health problem worldwide accounting for over a million deaths annually. While many patients with Stage II and III CRC can be cured with combinations of surgery, radiotherapy and chemotherapy, this is morbid costly treatment and a significant proportion will suffer recurrence and eventually die of CRC. Increased understanding of the molecular pathogenesis of CRC has the potential to identify high risk patients and target therapy more appropriately. Despite increased understanding of the molecular events underlying CRC development, established molecular techniques have only produced a limited number of biomarkers suitable for use in routine clinical practice to predict risk, prognosis and response to treatment. Recent rapid technological developments, however, have made genomic sequencing of CRC more economical and efficient, creating potential for the discovery of genetic biomarkers that have greater diagnostic, prognostic and therapeutic capabilities for the management of CRC. This paper reviews the current understanding of the molecular pathogenesis of CRC, and summarizes molecular biomarkers that surgeons will encounter in current clinical use as well as those under development in clinical and preclinical trials. New molecular technologies are reviewed together with their potential impact on the understanding of the molecular pathogenesis of CRC and their potential clinical utility in classification, diagnosis, prognosis and targeting of therapy. PMID:26990814

  14. Peripheral Biomarkers in Animal Models of Major Depressive Disorder

    Directory of Open Access Journals (Sweden)

    Lucia Carboni

    2013-01-01

    Full Text Available Investigations of preclinical biomarkers for major depressive disorder (MDD encompass the quantification of proteins, peptides, mRNAs, or small molecules in blood or urine of animal models. Most studies aim at characterising the animal model by including the assessment of analytes or hormones affected in depressive patients. The ultimate objective is to validate the model to better understand the neurobiological basis of MDD. Stress hormones or inflammation-related analytes associated with MDD are frequently measured. In contrast, other investigators evaluate peripheral analytes in preclinical models to translate the results in clinical settings afterwards. Large-scale, hypothesis-free studies are performed in MDD models to identify candidate biomarkers. Other studies wish to propose new targets for drug discovery. Animal models endowed with predictive validity are investigated, and the assessment of peripheral analytes, such as stress hormones or immune molecules, is comprised to increase the confidence in the target. Finally, since the mechanism of action of antidepressants is incompletely understood, studies investigating molecular alterations associated with antidepressant treatment may include peripheral analyte levels. In conclusion, preclinical biomarker studies aid the identification of new candidate analytes to be tested in clinical trials. They also increase our understanding of MDD pathophysiology and help to identify new pharmacological targets.

  15. Peripheral biomarkers in animal models of major depressive disorder.

    Science.gov (United States)

    Carboni, Lucia

    2013-01-01

    Investigations of preclinical biomarkers for major depressive disorder (MDD) encompass the quantification of proteins, peptides, mRNAs, or small molecules in blood or urine of animal models. Most studies aim at characterising the animal model by including the assessment of analytes or hormones affected in depressive patients. The ultimate objective is to validate the model to better understand the neurobiological basis of MDD. Stress hormones or inflammation-related analytes associated with MDD are frequently measured. In contrast, other investigators evaluate peripheral analytes in preclinical models to translate the results in clinical settings afterwards. Large-scale, hypothesis-free studies are performed in MDD models to identify candidate biomarkers. Other studies wish to propose new targets for drug discovery. Animal models endowed with predictive validity are investigated, and the assessment of peripheral analytes, such as stress hormones or immune molecules, is comprised to increase the confidence in the target. Finally, since the mechanism of action of antidepressants is incompletely understood, studies investigating molecular alterations associated with antidepressant treatment may include peripheral analyte levels. In conclusion, preclinical biomarker studies aid the identification of new candidate analytes to be tested in clinical trials. They also increase our understanding of MDD pathophysiology and help to identify new pharmacological targets. PMID:24167347

  16. Multiplex assays for biomarker research and clinical application: translational science coming of age.

    Science.gov (United States)

    Fu, Qin; Schoenhoff, Florian S; Savage, William J; Zhang, Pingbo; Van Eyk, Jennifer E

    2010-03-01

    Over the last decade, translational science has come into the focus of academic medicine, and significant intellectual and financial efforts have been made to initiate a multitude of bench-to-bedside projects. The quest for suitable biomarkers that will significantly change clinical practice has become one of the biggest challenges in translational medicine. Quantitative measurement of proteins is a critical step in biomarker discovery. Assessing a large number of potential protein biomarkers in a statistically significant number of samples and controls still constitutes a major technical hurdle. Multiplexed analysis offers significant advantages regarding time, reagent cost, sample requirements and the amount of data that can be generated. The two contemporary approaches in multiplexed and quantitative biomarker validation, antibody-based immunoassays and MS-based multiple (or selected) reaction monitoring, are based on different assay principles and instrument requirements. Both approaches have their own advantages and disadvantages and therefore have complementary roles in the multi-staged biomarker verification and validation process. In this review, we discuss quantitative immunoassay and multiple reaction monitoring/selected reaction monitoring assay principles and development. We also discuss choosing an appropriate platform, judging the performance of assays, obtaining reliable, quantitative results for translational research and clinical applications in the biomarker field. PMID:21137048

  17. Automated sampling and data processing derived from biomimetic membranes

    DEFF Research Database (Denmark)

    Perry, Mark; Vissing, Thomas; Boesen, P.;

    2009-01-01

    data processing software to analyze and organize the large amounts of data generated. In this work, we developed an automated instrumental voltage clamp solution based on a custom-designed software controller application (the WaveManager), which enables automated on-line voltage clamp data acquisition...... combined solution provides a cost efficient and fast way to acquire, process and administrate large amounts of voltage clamp data that may be too laborious and time consuming to handle manually....... applicable to long-time series experiments. We designed another software program for off-line data processing. The automation of the on-line voltage clamp data acquisition and off-line processing was furthermore integrated with a searchable database (DiscoverySheet (TM)) for efficient data management. The...

  18. Automated Camera Calibration

    Science.gov (United States)

    Chen, Siqi; Cheng, Yang; Willson, Reg

    2006-01-01

    Automated Camera Calibration (ACAL) is a computer program that automates the generation of calibration data for camera models used in machine vision systems. Machine vision camera models describe the mapping between points in three-dimensional (3D) space in front of the camera and the corresponding points in two-dimensional (2D) space in the camera s image. Calibrating a camera model requires a set of calibration data containing known 3D-to-2D point correspondences for the given camera system. Generating calibration data typically involves taking images of a calibration target where the 3D locations of the target s fiducial marks are known, and then measuring the 2D locations of the fiducial marks in the images. ACAL automates the analysis of calibration target images and greatly speeds the overall calibration process.

  19. Automated telescope scheduling

    Science.gov (United States)

    Johnston, Mark D.

    1988-08-01

    With the ever increasing level of automation of astronomical telescopes the benefits and feasibility of automated planning and scheduling are becoming more apparent. Improved efficiency and increased overall telescope utilization are the most obvious goals. Automated scheduling at some level has been done for several satellite observatories, but the requirements on these systems were much less stringent than on modern ground or satellite observatories. The scheduling problem is particularly acute for Hubble Space Telescope: virtually all observations must be planned in excruciating detail weeks to months in advance. Space Telescope Science Institute has recently made significant progress on the scheduling problem by exploiting state-of-the-art artificial intelligence software technology. What is especially interesting is that this effort has already yielded software that is well suited to scheduling groundbased telescopes, including the problem of optimizing the coordinated scheduling of more than one telescope.

  20. Biomarkers in fibromyalgia: a review

    Directory of Open Access Journals (Sweden)

    Giacomelli C

    2014-02-01

    Full Text Available Camillo Giacomelli,* Francesca Sernissi,* Alessandra Rossi, Stefano Bombardieri, Laura BazzichiRheumatology Unit, Department of Clinical and Experimental Medicine, University of Pisa, Pisa, Italy *These authors contributed equally to the manuscript Abstract: Fibromyalgia is a common syndrome diagnosed by clinical criteria. The main symptom of fibromyalgia is pain, but patients frequently also complain about other nonspecific symptoms, such as headache, sleep disturbance, mood disorder, and cognitive impairment. In the light of the multifactorial origin of the disease and of the lack of objective diagnostic findings, several attempts have been made to find a reliable biomarker. For this reason, over the years, a number of patients and various biological samples have been studied, using many different approaches and techniques. Despite this, none of these studies has been able to find the proper biomarker. The aim of this review is to provide a critical overview of the current environment characterizing the search for fibromyalgia biomarkers. Keywords: genetics, proteomics, oxidative stress, fibromyalgia

  1. Biomarkers of silicosis: Potential candidates

    Directory of Open Access Journals (Sweden)

    Tiwari R

    2005-01-01

    Full Text Available Silica dust is widely prevalent in the atmosphere and more common than the other types of dust, thus making silicosis the most frequently occurring pneumoconiosis. In India also, studies carried out by National Institute of Occupational Health have shown high prevalence of silicosis in small factories and even in nonoccupational exposed subjects. The postero-anterior chest radiographs remain the key tool in diagnosing and assessing the extent and severity of interstitial lung disease. Although Computed Tomography detects finer anatomical structure than radiography it could not get popularity because of its cost. On the basis of histological features of silicosis many potential biomarkers such as Cytokines, Tumor Necrosis Factor, Interleukin 1, Angiotensin Converting Enzyme, Serum Copper, Fas ligand (FasL, etc. have been tried. However, further studies are needed to establish these potential biomarkers as true biomarker of silicosis.

  2. Myths in test automation

    OpenAIRE

    Jazmine Francis

    2015-01-01

    Myths in automation of software testing is an issue of discussion that echoes about the areas of service in validation of software industry. Probably, the first though that appears in knowledgeable reader would be Why this old topic again? What's New to discuss the matter? But, for the first time everyone agrees that undoubtedly automation testing today is not today what it used to be ten or fifteen years ago, because it has evolved in scope and magnitude. What began as a simple linear script...

  3. Automated phantom assay system

    International Nuclear Information System (INIS)

    This paper describes an automated phantom assay system developed for assaying phantoms spiked with minute quantities of radionuclides. The system includes a computer-controlled linear-translation table that positions the phantom at exact distances from a spectrometer. A multichannel analyzer (MCA) interfaces with a computer to collect gamma spectral data. Signals transmitted between the controller and MCA synchronize data collection and phantom positioning. Measured data are then stored on disk for subsequent analysis. The automated system allows continuous unattended operation and ensures reproducible results

  4. Potential blood biomarkers for stroke.

    Science.gov (United States)

    Laborde, Carlos M; Mourino-Alvarez, Laura; Akerstrom, Finn; Padial, Luis R; Vivanco, Fernando; Gil-Dones, Felix; Barderas, Maria G

    2012-08-01

    Stroke is one of the most common causes of death worldwide and a major cause of acquired disability in adults. Despite advances in research during the last decade, prevention and treatment strategies still suffer from significant limitations, and therefore new theoretical and technical approaches are required. Technological advances in the proteomic and metabolomic areas, during recent years, have permitted a more effective search for novel biomarkers and therapeutic targets that may allow for effective risk stratification and early diagnosis with subsequent rapid treatment. This review provides a comprehensive overview of the latest candidate proteins and metabolites proposed as new potential biomarkers in stroke. PMID:22967080

  5. Discovery with FAST

    Science.gov (United States)

    Wilkinson, P.

    2016-02-01

    FAST offers "transformational" performance well-suited to finding new phenomena - one of which might be polarised spectral transients. But discoveries will only be made if "the system" provides its users with the necessary opportunities. In addition to designing in as much observational flexibility as possible, FAST should be operated with a philosophy which maximises its "human bandwidth". This band includes the astronomers of tomorrow - many of whom not have yet started school or even been born.

  6. Fateful discovery almost forgotten

    International Nuclear Information System (INIS)

    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.)

  7. Opportunistic Adaptation Knowledge Discovery

    OpenAIRE

    Badra, Fadi; Cordier, Amélie; Lieber, Jean

    2009-01-01

    The original publication is available at www.springerlink.com International audience Adaptation has long been considered as the Achilles' heel of case-based reasoning since it requires some domain-specific knowledge that is difficult to acquire. In this paper, two strategies are combined in order to reduce the knowledge engineering cost induced by the adaptation knowledge (CA) acquisition task: CA is learned from the case base by the means of knowledge discovery techniques, and the CA a...

  8. 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.

  9. Biomarker Detection using PS2-Thioaptamers Project

    Data.gov (United States)

    National Aeronautics and Space Administration — AM Biotechnologies (AM) will develop a system to detect and quantify bone demineralization biomarkers as outlined in SBIR Topic "Technologies to Detect Biomarkers"....

  10. Personalized medicine using DNA biomarkers: a review

    OpenAIRE

    Ziegler, Andreas; Koch, Armin; Krockenberger, Katja; Großhennig, Anika

    2012-01-01

    Biomarkers are of increasing importance for personalized medicine, with applications including diagnosis, prognosis, and selection of targeted therapies. Their use is extremely diverse, ranging from pharmacodynamics to treatment monitoring. Following a concise review of terminology, we provide examples and current applications of three broad categories of biomarkers—DNA biomarkers, DNA tumor biomarkers, and other general biomarkers. We outline clinical trial phases for identifying and validat...

  11. Biomarker Analysis of Stored Blood Products: Emphasis on Pre-Analytical Issues

    Directory of Open Access Journals (Sweden)

    Niels Lion

    2010-11-01

    Full Text Available Millions of blood products are transfused every year; many lives are thus directly concerned by transfusion. The three main labile blood products used in transfusion are erythrocyte concentrates, platelet concentrates and fresh frozen plasma. Each of these products has to be stored according to its particular components. However, during storage, modifications or degradation of those components may occur, and are known as storage lesions. Thus, biomarker discovery of in vivo blood aging as well as in vitro labile blood products storage lesions is of high interest for the transfusion medicine community. Pre-analytical issues are of major importance in analyzing the various blood products during storage conditions as well as according to various protocols that are currently used in blood banks for their preparations. This paper will review key elements that have to be taken into account in the context of proteomic-based biomarker discovery applied to blood banking.

  12. 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

  13. Automation Hooks Architecture for Flexible Test Orchestration - Concept Development and Validation

    Science.gov (United States)

    Lansdowne, C. A.; Maclean, John R.; Winton, Chris; McCartney, Pat

    2011-01-01

    The Automation Hooks Architecture Trade Study for Flexible Test Orchestration sought a standardized data-driven alternative to conventional automated test programming interfaces. The study recommended composing the interface using multicast DNS (mDNS/SD) service discovery, Representational State Transfer (Restful) Web Services, and Automatic Test Markup Language (ATML). We describe additional efforts to rapidly mature the Automation Hooks Architecture candidate interface definition by validating it in a broad spectrum of applications. These activities have allowed us to further refine our concepts and provide observations directed toward objectives of economy, scalability, versatility, performance, severability, maintainability, scriptability and others.

  14. Resolving breast cancer heterogeneity by searching reliable protein cancer biomarkers in the breast fluid secretome

    International Nuclear Information System (INIS)

    One of the major goals in cancer research is to find and evaluate the early presence of biomarkers in human fluids and tissues. To resolve the complex cell heterogeneity of a tumor mass, it will be useful to characterize the intricate biomolecular composition of tumor microenvironment (the so called cancer secretome), validating secreted proteins as early biomarkers of cancer initiation and progression. This approach is not broadly applicable because of the paucity of well validated and FDA-approved biomarkers and because most of the candidate biomarkers are mainly organ-specific rather than tumor-specific. For these reasons, there is an urgent need to identify and validate a panel of biomarker combinations for early detection of human tumors. This is especially important for breast cancer, the cancer spread most worldwide among women. It is well known that patients with early diagnosed breast cancer live longer, require less extensive treatment and fare better than patients with more aggressive and/or advanced disease. In the frame of searching breast cancer biomarkers (especially using nipple aspirate fluid mirroring breast microenvironment), studies have highlighted an optimal combination of well-known biomarkers: uPA + PAI-1 + TF. When individually investigated they did not show perfect accuracy in predicting the presence of breast cancer, whereas the triple combination has been demonstrated to be highly predictive of pre-cancer and/or cancerous conditions, approaching 97-100% accuracy. Despite the heterogeneous composition of breast cancer and the difficulties to find specific breast cancer biomolecules, the noninvasive analysis of the nipple aspirate fluid secretome may significantly improve the discovery of promising biomarkers, helping also the differentiation among benign and invasive breast diseases, opening new frontiers in early oncoproteomics

  15. Automated conflict resolution issues

    Science.gov (United States)

    Wike, Jeffrey S.

    1991-01-01

    A discussion is presented of how conflicts for Space Network resources should be resolved in the ATDRSS era. The following topics are presented: a description of how resource conflicts are currently resolved; a description of issues associated with automated conflict resolution; present conflict resolution strategies; and topics for further discussion.

  16. Protokoller til Home Automation

    DEFF Research Database (Denmark)

    Kjær, Kristian Ellebæk

    2008-01-01

    computer, der kan skifte mellem foruddefinerede indstillinger. Nogle gange kan computeren fjernstyres over internettet, så man kan se hjemmets status fra en computer eller måske endda fra en mobiltelefon. Mens nævnte anvendelser er klassiske indenfor home automation, er yderligere funktionalitet dukket op...

  17. Myths in test automation

    Directory of Open Access Journals (Sweden)

    Jazmine Francis

    2015-01-01

    Full Text Available Myths in automation of software testing is an issue of discussion that echoes about the areas of service in validation of software industry. Probably, the first though that appears in knowledgeable reader would be Why this old topic again? What's New to discuss the matter? But, for the first time everyone agrees that undoubtedly automation testing today is not today what it used to be ten or fifteen years ago, because it has evolved in scope and magnitude. What began as a simple linear scripts for web applications today has a complex architecture and a hybrid framework to facilitate the implementation of testing applications developed with various platforms and technologies. Undoubtedly automation has advanced, but so did the myths associated with it. The change in perspective and knowledge of people on automation has altered the terrain. This article reflects the points of views and experience of the author in what has to do with the transformation of the original myths in new versions, and how they are derived; also provides his thoughts on the new generation of myths.

  18. Automated data model evaluation

    International Nuclear Information System (INIS)

    Modeling process is essential phase within information systems development and implementation. This paper presents methods and techniques for analysis and evaluation of data model correctness. Recent methodologies and development results regarding automation of the process of model correctness analysis and relations with ontology tools has been presented. Key words: Database modeling, Data model correctness, Evaluation

  19. Automated solvent concentrator

    Science.gov (United States)

    Griffith, J. S.; Stuart, J. L.

    1976-01-01

    Designed for automated drug identification system (AUDRI), device increases concentration by 100. Sample is first filtered, removing particulate contaminants and reducing water content of sample. Sample is extracted from filtered residue by specific solvent. Concentrator provides input material to analysis subsystem.

  20. ELECTROPNEUMATIC AUTOMATION EDUCATIONAL LABORATORY

    OpenAIRE

    Dolgorukov, S. O.; National Aviation University; Roman, B. V.; National Aviation University

    2013-01-01

    The article reflects current situation in education regarding mechatronics learning difficulties. Com-plex of laboratory test benches on electropneumatic automation are considered as a tool in advancing through technical science. Course of laboratory works developed to meet the requirement of efficient and reliable way of practical skills acquisition is regarded the simplest way for students to learn the ba-sics of mechatronics.

  1. Proteomic Biomarkers for Spontaneous Preterm Birth

    DEFF Research Database (Denmark)

    Kacerovsky, Marian; Lenco, Juraj; Musilova, Ivana;

    2014-01-01

    This review aimed to identify, synthesize, and analyze the findings of studies on proteomic biomarkers for spontaneous preterm birth (PTB). Three electronic databases (Medline, Embase, and Scopus) were searched for studies in any language reporting the use of proteomic biomarkers for PTB published...... literature, there are no specific proteomic biomarkers capable of accurately predicting PTB....

  2. Cell-free microRNAs in blood and other body fluids, as cancer biomarkers.

    Science.gov (United States)

    Ortiz-Quintero, Blanca

    2016-06-01

    The discovery of cell-free microRNAs (miRNAs) in serum, plasma and other body fluids has yielded an invaluable potential source of non-invasive biomarkers for cancer and other non-malignant diseases. miRNAs in the blood and other body fluids are highly stable in biological samples and are resistant to environmental conditions, such as freezing, thawing or enzymatic degradation, which makes them convenient as potential biomarkers. In addition, they are more easily sampled than tissue miRNAs. Altered levels of cell-free miRNAs have been found in every type of cancer analysed, and increasing evidence indicates that they may participate in carcinogenesis by acting as cell-to-cell signalling molecules. This review summarizes the biological characteristics and mechanisms of release of cell-free miRNAs that make them promising candidates as non-invasive biomarkers of cancer. PMID:27218664

  3. The promise of biomarkers in diagnosing major depression in primary care: the present and future.

    Science.gov (United States)

    Redei, Eva E; Mehta, Neha S

    2015-08-01

    Major depressive disorder (MDD) is the most prevalent psychiatric disorder, but it can be underdiagnosed or misdiagnosed. Most people with depression are seen in primary care settings, where there are limited resources to diagnose and treat the patient. There is a lack of clinically validated objective laboratory-based diagnostic tests to diagnose MDD; however, it is clear that these tests could greatly improve the correct and timely diagnosis. This review aims to give a cross-sectional view of current efforts of DNA methylomic, transcriptomic, and proteomic approaches to identify biomarkers. We outline our view of the biomarker developmental steps from discovery to clinical application. We then propose that better cooperation will lead us closer to the common goal of identifying biological biomarkers for major depression. "The important thing is not to stop questioning. Curiosity has its own reason for existing." Albert Einstein. PMID:26081681

  4. Novel Approach to Meta-Analysis of Microarray Datasets Reveals Muscle Remodeling-related Drug Targets and Biomarkers in Duchenne Muscular Dystrophy

    OpenAIRE

    Kotelnikova, Ekaterina; Shkrob, Maria A.; Pyatnitskiy, Mikhail A.; Ferlini, Alessandra; Daraselia, Nikolai

    2012-01-01

    Elucidation of new biomarkers and potential drug targets from high-throughput profiling data is a challenging task due to a limited number of available biological samples and questionable reproducibility of differential changes in cross-dataset comparisons. In this paper we propose a novel computational approach for drug and biomarkers discovery using comprehensive analysis of multiple expression profiling datasets. The new method relies on aggregation of individual profiling experiments comb...

  5. Neuroscience-driven discovery and development of sleep therapeutics.

    Science.gov (United States)

    Dresler, M; Spoormaker, V I; Beitinger, P; Czisch, M; Kimura, M; Steiger, A; Holsboer, F

    2014-03-01

    Until recently, neuroscience has given sleep research and discovery of better treatments of sleep disturbances little attention, despite the fact that disturbed sleep has overwhelming impact on human health. Sleep is a complex phenomenon in which specific psychological, electrophysiological, neurochemical, endocrinological, immunological and genetic factors are involved. The brain as both the generator and main object of sleep is obviously of particular interest, which makes a neuroscience-driven view the most promising approach to evaluate clinical implications and applications of sleep research. Polysomnography as the gold standard of sleep research, complemented by brain imaging, neuroendocrine testing, genomics and other laboratory measures can help to create composite biomarkers that allow maximizing the effects of individualized therapies while minimizing adverse effects. Here we review the current state of the neuroscience of sleep, sleep disorders and sleep therapeutics and will give some leads to promote the discovery and development of sleep medicines that are better than those we have today. PMID:24189488

  6. Biomarkers in sarcoidosis: a review

    Directory of Open Access Journals (Sweden)

    Ahmadzai H

    2014-08-01

    Full Text Available Hasib Ahmadzai,1,2 Wei Sheng Joshua Loke,1 Shuying Huang,1 Cristan Herbert,1 Denis Wakefield,3 Paul S Thomas2 1Inflammation and Infection Research Centre (IIRC, Faculty of Medicine, University of New South Wales, Sydney, NSW, Australia; 2Department of Respiratory Medicine, Prince of Wales Hospital, Randwick, Sydney, NSW, Australia; 3Immunology of the Eye Clinic, St Vincent's Clinic, Darlinghurst, Sydney, NSW, Australia Abstract: Sarcoidosis is a systemic granulomatous disease of undetermined etiology invariably affecting the lungs and thoracic lymph nodes. It has been termed an “immune paradox”, as there is peripheral anergy despite exaggerated inflammation at disease sites. The disease is usually self-limiting, although some individuals experience unremitting inflammation that may progress into pulmonary fibrosis and death. The inflammatory process is largely a T helper-1-driven immune response. Given its heterogeneous clinical manifestations, diagnosis is usually a clinical conundrum. Clinical and radiological findings alone are often inadequate to confirm the diagnosis. At present, sarcoidosis is usually a diagnosis of exclusion, confirmed by histological evidence of noncaseating granulomas in the absence of known granulomagenic agents. This has compelled researchers to look for disease-specific biomarkers that can help diagnose sarcoidosis and delineate its disease course, severity, and prognosis. In this review we highlight various investigations used to diagnose sarcoidosis, outline proposed biomarkers, and discuss novel methods of sampling biomarkers. Keywords: sarcoidosis, biomarkers, inflammatory markers, exhaled breath condensate, proteomics, granuloma

  7. Bias in Peripheral Depression Biomarkers

    DEFF Research Database (Denmark)

    Carvalho, André F; Köhler, Cristiano A; Brunoni, André R;

    2016-01-01

    BACKGROUND: To aid in the differentiation of individuals with major depressive disorder (MDD) from healthy controls, numerous peripheral biomarkers have been proposed. To date, no comprehensive evaluation of the existence of bias favoring the publication of significant results or inflating effect...

  8. Automating spectral measurements

    Science.gov (United States)

    Goldstein, Fred T.

    2008-09-01

    This paper discusses the architecture of software utilized in spectroscopic measurements. As optical coatings become more sophisticated, there is mounting need to automate data acquisition (DAQ) from spectrophotometers. Such need is exacerbated when 100% inspection is required, ancillary devices are utilized, cost reduction is crucial, or security is vital. While instrument manufacturers normally provide point-and-click DAQ software, an application programming interface (API) may be missing. In such cases automation is impossible or expensive. An API is typically provided in libraries (*.dll, *.ocx) which may be embedded in user-developed applications. Users can thereby implement DAQ automation in several Windows languages. Another possibility, developed by FTG as an alternative to instrument manufacturers' software, is the ActiveX application (*.exe). ActiveX, a component of many Windows applications, provides means for programming and interoperability. This architecture permits a point-and-click program to act as automation client and server. Excel, for example, can control and be controlled by DAQ applications. Most importantly, ActiveX permits ancillary devices such as barcode readers and XY-stages to be easily and economically integrated into scanning procedures. Since an ActiveX application has its own user-interface, it can be independently tested. The ActiveX application then runs (visibly or invisibly) under DAQ software control. Automation capabilities are accessed via a built-in spectro-BASIC language with industry-standard (VBA-compatible) syntax. Supplementing ActiveX, spectro-BASIC also includes auxiliary serial port commands for interfacing programmable logic controllers (PLC). A typical application is automatic filter handling.

  9. Embracing an integromic approach to tissue biomarker research in cancer: Perspectives and lessons learned

    OpenAIRE

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

    2016-01-01

    Modern approaches to biomedical research and diagnostics targeted towards precision medicine are generating ‘big data’ across a range of high-throughput experimental and analytical platforms. Integrative analysis of this rich clinical, pathological, molecular and imaging data represents one of the greatest bottlenecks in biomarker discovery research in cancer and other diseases. Following on from the publication of our successful framework for multimodal data amalgamation and integrative anal...

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

    OpenAIRE

    Fryar-Williams, Stephanie; Strobel, Jörg E

    2015-01-01

    Background 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 ...

  11. Data mining of plasma peptide chromatograms for biomarkers of air contaminant exposures

    OpenAIRE

    Vincent Renaud; Kumarathasan Premkumari; Karthikeyan Subramanian

    2008-01-01

    Abstract Background Interrogation of chromatographic data for biomarker discovery becomes a tedious task due to stochastic variability in retention times arising from solvent and column performance. The difficulty is further compounded when the effects of exposure (e.g. to environmental contaminants) and biological variability result in varying numbers and intensities of peaks among chromatograms. Results We developed a software tool to correct the stochastic time shifts in chromatographic da...

  12. Host Protein Biomarkers Identify Active Tuberculosis in HIV Uninfected and Co-infected Individuals

    OpenAIRE

    Achkar, Jacqueline M.; Laetitia Cortes; Pascal Croteau; Corey Yanofsky; Marija Mentinova; Isabelle Rajotte; Michael Schirm; Yiyong Zhou; Ana Paula Junqueira-Kipnis; Kasprowicz, Victoria O.; Michelle Larsen; René Allard; Joanna Hunter; Eustache Paramithiotis

    2015-01-01

    Biomarkers for active tuberculosis (TB) are urgently needed to improve rapid TB diagnosis. The objective of this study was to identify serum protein expression changes associated with TB but not latent Mycobacterium tuberculosis infection (LTBI), uninfected states, or respiratory diseases other than TB (ORD). Serum samples from 209 HIV uninfected (HIV−) and co-infected (HIV+) individuals were studied. In the discovery phase samples were analyzed via liquid chromatography and mass spectrometry...

  13. New developments and future opportunities in biomarkers for amyotrophic lateral sclerosis

    OpenAIRE

    Chen, XuePing; Shang, Hui-Fang

    2015-01-01

    Modern technology has improved the ability to probe effectively the underlying biology of ALS by examination of genomic, proteomic and physiological changes in patients with ALS, as well as to monitor functional and structural changes during the course of disease. While effective treatments for ALS are lacking, the discovery of sensitive biomarkers to disease activity offers clinicians tools for rapid diagnosis and insights into the pathophysiology of ALS. The ultimate aim is to lessen relian...

  14. Classification of genes and putative biomarker identification using distribution metrics on expression profiles.

    Directory of Open Access Journals (Sweden)

    Hung-Chung Huang

    Full Text Available BACKGROUND: Identification of genes with switch-like properties will facilitate discovery of regulatory mechanisms that underlie these properties, and will provide knowledge for the appropriate application of Boolean networks in gene regulatory models. As switch-like behavior is likely associated with tissue-specific expression, these gene products are expected to be plausible candidates as tissue-specific biomarkers. METHODOLOGY/PRINCIPAL FINDINGS: In a systematic classification of genes and search for biomarkers, gene expression profiles (GEPs of more than 16,000 genes from 2,145 mouse array samples were analyzed. Four distribution metrics (mean, standard deviation, kurtosis and skewness were used to classify GEPs into four categories: predominantly-off, predominantly-on, graded (rheostatic, and switch-like genes. The arrays under study were also grouped and examined by tissue type. For example, arrays were categorized as 'brain group' and 'non-brain group'; the Kolmogorov-Smirnov distance and Pearson correlation coefficient were then used to compare GEPs between brain and non-brain for each gene. We were thus able to identify tissue-specific biomarker candidate genes. CONCLUSIONS/SIGNIFICANCE: The methodology employed here may be used to facilitate disease-specific biomarker discovery.

  15. Interpretation of a discovery

    OpenAIRE

    Vučković Vladan

    2006-01-01

    The paper presents the development of the theory of asynchronous motors since Tesla’s discovery until the present day. The theory of steady state, as we know it today, was completed already during the first dozen of years. That was followed by a period of stagnation during a number of decades, when the theory of asynchronous motors was developed only in the framework of the general theory of electric machines, which was stimulated by the problems of the development of synchronous generators a...

  16. The Necessity of Semantic Technologies in Grid Discovery

    Directory of Open Access Journals (Sweden)

    Serena Pastore

    2008-04-01

    Full Text Available Service discovery and its automation are some of the key features that a large scale, open distributed system must provide so that clients and users may take advantage of shared resources. Most actual distributed systems are built with several middleware applications developed by using grid and web service technologies that allow an infrastructure to be implemented where users work as if they were in a local system. The paper, starting from the work done within grid projects in which the INAF Institute was involved, examines issues encountered and solutions proposed in the optics of sharing and thus using web resources such as web services in a specific grid system. By guaranteeing the efficient use of such resources, different discovery mechanisms, developed within grid and web service areas, have been evaluated. The results show the necessity of an appropriate resources’ description in terms of the information data model, protocol and search tools that could integrate semantic technologies required for automating the process. Enabling automatic discovery means both the enriching of description with one of the semantic languages that are in constant development (i.e. OWL-S, WSDL-S and the availability of a mechanism able to interpret and process such information. This work aims at taking advantage of the improvement in semantic technologies to prove the efficacy of this approach in making use of applications that need a grid environment for their execution.

  17. NEW TECHNIQUES USED IN AUTOMATED TEXT ANALYSIS

    Directory of Open Access Journals (Sweden)

    M. I strate

    2010-12-01

    Full Text Available Automated analysis of natural language texts is one of the most important knowledge discovery tasks for any organization. According to Gartner Group, almost 90% of knowledge available at an organization today is dispersed throughout piles of documents buried within unstructured text. Analyzing huge volumes of textual information is often involved in making informed and correct business decisions. Traditional analysis methods based on statistics fail to help processing unstructured texts and the society is in search of new technologies for text analysis. There exist a variety of approaches to the analysis of natural language texts, but most of them do not provide results that could be successfully applied in practice. This article concentrates on recent ideas and practical implementations in this area.

  18. Meeting Report--NASA Radiation Biomarker Workshop

    Energy Technology Data Exchange (ETDEWEB)

    Straume, Tore; Amundson, Sally A,; Blakely, William F.; Burns, Frederic J.; Chen, Allen; Dainiak, Nicholas; Franklin, Stephen; Leary, Julie A.; Loftus, David J.; Morgan, William F.; Pellmar, Terry C.; Stolc, Viktor; Turteltaub, Kenneth W.; Vaughan, Andrew T.; Vijayakumar, Srinivasan; Wyrobek, Andrew J.

    2008-05-01

    A summary is provided of presentations and discussions from the NASA Radiation Biomarker Workshop held September 27-28, 2007, at NASA Ames Research Center in Mountain View, California. Invited speakers were distinguished scientists representing key sectors of the radiation research community. Speakers addressed recent developments in the biomarker and biotechnology fields that may provide new opportunities for health-related assessment of radiation-exposed individuals, including for long-duration space travel. Topics discussed include the space radiation environment, biomarkers of radiation sensitivity and individual susceptibility, molecular signatures of low-dose responses, multivariate analysis of gene expression, biomarkers in biodefense, biomarkers in radiation oncology, biomarkers and triage following large-scale radiological incidents, integrated and multiple biomarker approaches, advances in whole-genome tiling arrays, advances in mass-spectrometry proteomics, radiation biodosimetry for estimation of cancer risk in a rat skin model, and confounding factors. Summary conclusions are provided at the end of the report.

  19. Automated Preferences Elicitation

    Czech Academy of Sciences Publication Activity Database

    Kárný, Miroslav; Guy, Tatiana Valentine

    Prague : Institute of Information Theory and Automation, 2011, s. 20-25. ISBN 978-80-903834-6-3. [The 2nd International Workshop od Decision Making with Multiple Imperfect Decision Makers. Held in Conjunction with the 25th Annual Conference on Neural Information Processing Systems (NIPS 2011). Sierra Nevada (ES), 16.12.2011-16.12.2011] R&D Projects: GA MŠk 1M0572; GA ČR GA102/08/0567 Institutional research plan: CEZ:AV0Z10750506 Keywords : elicitation * decision making * Bayesian decision making * fully probabilistic design Subject RIV: BB - Applied Statistics, Operational Research http://library.utia.cas.cz/separaty/2011/AS/karny-automated preferences elicitation.pdf

  20. Automated drawing generation system

    International Nuclear Information System (INIS)

    Since automated CAD drawing generation systems still require human intervention, improvements were focussed on an interactive processing section (data input and correcting operation) which necessitates a vast amount of work. As a result, human intervention was eliminated, the original objective of a computerized system. This is the first step taken towards complete automation. The effects of development and commercialization of the system are as described below. (1) The interactive processing time required for generating drawings was improved. It was determined that introduction of the CAD system has reduced the time required for generating drawings. (2) The difference in skills between workers preparing drawings has been eliminated and the quality of drawings has been made uniform. (3) The extent of knowledge and experience demanded of workers has been reduced. (author)

  1. Terminal automation system maintenance

    Energy Technology Data Exchange (ETDEWEB)

    Coffelt, D.; Hewitt, J. [Engineered Systems Inc., Tempe, AZ (United States)

    1997-01-01

    Nothing has improved petroleum product loading in recent years more than terminal automation systems. The presence of terminal automation systems (TAS) at loading racks has increased operational efficiency and safety and enhanced their accounting and management capabilities. However, like all finite systems, they occasionally malfunction or fail. Proper servicing and maintenance can minimize this. And in the unlikely event a TAS breakdown does occur, prompt and effective troubleshooting can reduce its impact on terminal productivity. To accommodate around-the-clock loading at racks, increasingly unattended by terminal personnel, TAS maintenance, servicing and troubleshooting has become increasingly demanding. It has also become increasingly important. After 15 years of trial and error at petroleum and petrochemical storage and transfer terminals, a number of successful troubleshooting programs have been developed. These include 24-hour {open_quotes}help hotlines,{close_quotes} internal (terminal company) and external (supplier) support staff, and {open_quotes}layered{close_quotes} support. These programs are described.

  2. ATLAS Distributed Computing Automation

    CERN Document Server

    Schovancova, J; The ATLAS collaboration; Borrego, C; Campana, S; Di Girolamo, A; Elmsheuser, J; Hejbal, J; Kouba, T; Legger, F; Magradze, E; Medrano Llamas, R; Negri, G; Rinaldi, L; Sciacca, G; Serfon, C; Van Der Ster, D C

    2012-01-01

    The ATLAS Experiment benefits from computing resources distributed worldwide at more than 100 WLCG sites. The ATLAS Grid sites provide over 100k CPU job slots, over 100 PB of storage space on disk or tape. Monitoring of status of such a complex infrastructure is essential. The ATLAS Grid infrastructure is monitored 24/7 by two teams of shifters distributed world-wide, by the ATLAS Distributed Computing experts, and by site administrators. In this paper we summarize automation efforts performed within the ATLAS Distributed Computing team in order to reduce manpower costs and improve the reliability of the system. Different aspects of the automation process are described: from the ATLAS Grid site topology provided by the ATLAS Grid Information System, via automatic site testing by the HammerCloud, to automatic exclusion from production or analysis activities.

  3. Rapid automated nuclear chemistry

    International Nuclear Information System (INIS)

    Rapid Automated Nuclear Chemistry (RANC) can be thought of as the Z-separation of Neutron-rich Isotopes by Automated Methods. The range of RANC studies of fission and its products is large. In a sense, the studies can be categorized into various energy ranges from the highest where the fission process and particle emission are considered, to low energies where nuclear dynamics are being explored. This paper presents a table which gives examples of current research using RANC on fission and fission products. The remainder of this text is divided into three parts. The first contains a discussion of the chemical methods available for the fission product elements, the second describes the major techniques, and in the last section, examples of recent results are discussed as illustrations of the use of RANC

  4. Rapid automated nuclear chemistry

    Energy Technology Data Exchange (ETDEWEB)

    Meyer, R.A.

    1979-05-31

    Rapid Automated Nuclear Chemistry (RANC) can be thought of as the Z-separation of Neutron-rich Isotopes by Automated Methods. The range of RANC studies of fission and its products is large. In a sense, the studies can be categorized into various energy ranges from the highest where the fission process and particle emission are considered, to low energies where nuclear dynamics are being explored. This paper presents a table which gives examples of current research using RANC on fission and fission products. The remainder of this text is divided into three parts. The first contains a discussion of the chemical methods available for the fission product elements, the second describes the major techniques, and in the last section, examples of recent results are discussed as illustrations of the use of RANC.

  5. Automated Microbial Metabolism Laboratory

    Science.gov (United States)

    1973-01-01

    Development of the automated microbial metabolism laboratory (AMML) concept is reported. The focus of effort of AMML was on the advanced labeled release experiment. Labeled substrates, inhibitors, and temperatures were investigated to establish a comparative biochemical profile. Profiles at three time intervals on soil and pure cultures of bacteria isolated from soil were prepared to establish a complete library. The development of a strategy for the return of a soil sample from Mars is also reported.

  6. Components for automated microscopy

    Science.gov (United States)

    Determann, H.; Hartmann, H.; Schade, K. H.; Stankewitz, H. W.

    1980-12-01

    A number of devices, aiming at automated analysis of microscopic objects as regards their morphometrical parameters or their photometrical values, were developed. These comprise: (1) a device for automatic focusing tuned on maximum contrast; (2) a feedback system for automatic optimization of microscope illumination; and (3) microscope lenses with adjustable pupil distances for usage in the two previous devices. An extensive test program on histological and zytological applications proves the wide application possibilities of the autofocusing device.

  7. Automation of dissolution tests

    OpenAIRE

    Rolf Rolli

    2003-01-01

    Dissolution testing of drug formulations was introduced in the 1960s and accepted by health regulatory authorities in the 1970s. Since then, the importance of dissolution has grown rapidly as have the number of tests and demands in quality-control laboratories. Recent research works lead to the development of in-vitro dissolution tests as replacements for human and animal bioequivalence studies. For many years, a lot of time and effort has been invested in automation of dissolution tests. The...

  8. Automated uranium assays

    International Nuclear Information System (INIS)

    Precise, timely inventories of enriched uranium stocks are vital to help prevent the loss, theft, or diversion of this material for illicit use. A wet-chemistry analyzer has been developed at LLL to assist in these inventories by performing automated analyses of uranium samples from different stages in the nuclear fuel cycle. These assays offer improved accuracy, reduced costs, significant savings in manpower, and lower radiation exposure for personnel compared with present techniques

  9. Construction Automation and Robotics

    OpenAIRE

    Bock, Thomas

    2008-01-01

    Due to the high complexity of the construction process and the stagnating technological development a long-term preparation is necessary to adapt it to advanced construction methods. Architects, engineers and all other participants of the construction process have to be integrated in this adaptation process. The short- and long-term development of automation will take place step-by-step and will be oriented to the respective application and requirements. In the initial phase existing building...

  10. Shielded cells transfer automation

    International Nuclear Information System (INIS)

    Nuclear waste from shielded cells is removed, packaged, and transferred manually in many nuclear facilities. To reduce radiation exposure to operators, technological advances in remote handling and automation were employed. An industrial robot and a specially designed end effector, access port, and sealing machine were used to remotely bag waste containers out of a glove box. The system is operated from a control panel outside the work area via television cameras

  11. LINAC control automation system

    International Nuclear Information System (INIS)

    A 7 MeV Electron Beam Linear Accelerator (LINAC) being used for pulse radiolysis experiments at RC and CDD, B.A.R.C. has been automated with a PLC based control panel designed and developed by Computer Division, B.A.R.C.. The control panel after power on switches ON various units in a pre-defined sequence and intervals on a single turn of START key from OFF to ON position. The control panel also generates various ramp signals in a pre-defined sequence and rate and steady values and feeds to the LINAC bringing it to the ready for experiment condition. Similarly on a single turn of STOP key from OFF to ON position, the panel ramps down the various signals in pre-defined manners and makes OFF the various units in predefined sequence and timing providing safety to the machine. The steady values for various signals are on line settable as and when required so. This automation system relieves the operator from fatigue of time consuming manual ramping up or down of various signals and running around in four rooms for switching ON or OFF the various units enhancing efficiency and safety. This also facilitates the user scientist to do start up and shutdown operation in the absence of skilled operators and thus adds flexibility for working up to extended timing. This unit has been working satisfactorily since August 2002. For extraordinary condition automation to manual or vice versa change over has been provided. (author)

  12. 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

  13. Chronic Obstructive Pulmonary Disease Biomarkers

    Directory of Open Access Journals (Sweden)

    Tatsiana Beiko

    2016-04-01

    Full Text Available Despite significant decreases in morbidity and mortality of cardiovascular diseases (CVD and cancers, morbidity and cost associated with chronic obstructive pulmonary disease (COPD continue to be increasing. Failure to improve disease outcomes has been related to the paucity of interventions improving survival. Insidious onset and slow progression halter research successes in developing disease-modifying therapies. In part, the difficulty in finding new therapies is because of the extreme heterogeneity within recognized COPD phenotypes. Novel biomarkers are necessary to help understand the natural history and pathogenesis of the different COPD subtypes. A more accurate phenotyping and the ability to assess the therapeutic response to new interventions and pharmaceutical agents may improve the statistical power of longitudinal clinical studies. In this study, we will review known candidate biomarkers for COPD, proposed pathways of pathogenesis, and future directions in the field.

  14. Denton Vacuum Discovery-550 Sputterer

    Data.gov (United States)

    Federal Laboratory Consortium — Description: CORAL Name: Sputter 2 Similar to the existing 4-Gun Denton Discovery 22 Sputter system, with the following enhancements: Specifications / Capabilities:...

  15. Glycoprotein Biomarkers for the Early Detection of Aggressive Prostate Cancer — EDRN Public Portal

    Science.gov (United States)

    The Early Detection Research Network of the NCI is charged with the discovery, development and validation of biomarkers for early detection and prognosis related to neoplastic disease. Our laboratory is an NCI EDRN (U01CA152813) working on "Glycoprotein biomarkers for the early detection of aggressive prostate cancer". This EDRN administratiVE! supplement is a collaboration with Robert Veltri on his project to identify men with very low risk (indolent) prostate cancer (CaP) at the diagnostic biopsy at selection for active surveillance (AS). We will assess biopsy tissue using quantitative nuclear histomorphometric measurements and molecular biomarkers to predict an unexpected catastrophic CaP in such men with indolent CaP. At Johns Hopkins Hospital w1e use the Epstein criteria that includes; PSA density (PSAD) aggressive disease from a AS diagnostic biopsy. Our approach will combine nuclear morphometry measured by digital microscopy with a unique biopsy tissue biomarker profile (DNA content, Ki67, Her2neu, CACND1 and periostin). Fc•r the molecular targets we will us•e a multiplex tissue blot (MTB) immunohistochemistry method. The Aims o'f our work include 1) to utilize retrospective archival biopsy material from 70 AS cases where the outcome was unexpected and disastrous and collect an equal number of AS cases (n=140) and perform assays for morphology and biomarker targi ts proposed, 2) and predict failure using Cox proportional hazards statistical modeling.

  16. New perspectives in the search for reliable biomarkers in Alzheimer disease

    Directory of Open Access Journals (Sweden)

    Laura Moreno

    2015-03-01

    Full Text Available Background and Objectives: The search for accurate biomarkers in Alzheimer Disease (AD, on of the most devastating neurodegenerative diseases, remains essential to enable an early prognosis and diagnosis of the disease and to provide more efficient therapeutic strategies. A wide variety of potential biomarkers are has been identified by neuroimaging techniques and by the analysis of fluid samples, such as cerebrospinal fluid (CSF or blood. Recently, a growing number of studies are focused on the discovery of reliable blood-based biomarkers in blood, especially in the prodromal stage of AD, which can predict the conversion of asymptomatic cases to AD demented cases. In this review, the latest challenges in the search for accurate biomarkers of AD is revised, in particular, an update in blood-based biomarkers is described in depth. Conclusions: Finally, the close link among AD and other neurodegenerative diseases is discussed, mainly based on the last discovered mutation, the chromosome 9 open reading frame 72, C9ORF72.

  17. Cardiac Biomarkers in Hyperthyroid Cats

    OpenAIRE

    Sangster, Jodi Kirsten

    2013-01-01

    Background: Hyperthyroidism has substantial effects on the circulatory system. The cardiac biomarkers NT-proBNP and troponin I (cTNI) have proven useful in identifying cats with myocardial disease but have not been as extensively investigated in hyperthyroidism.Hypothesis: Plasma NT-proBNP and cTNI concentrations are higher in cats with primary cardiac disease than in cats with hyperthyroidism and higher in cats with hyperthyroidism than in healthy control cats.Animals: Twenty-three hyperthyr...

  18. Cardiac Biomarkers in Hyperthyroid Cats

    OpenAIRE

    Sangster, J.K.; Panciera, D L; Abbott, J.A.; Zimmerman, K.C.; Lantis, A.C.

    2013-01-01

    Background Hyperthyroidism has substantial effects on the circulatory system. The cardiac biomarkers NT‐proBNP and troponin I (cTNI) have proven useful in identifying cats with myocardial disease but have not been extensively investigated in hyperthyroidism. Hypothesis Plasma NT‐proBNP and cTNI concentrations are higher in cats with primary myocardial disease than in cats with hyperthyroidism and higher in cats with hyperthyroidism than in healthy control cats. Animals Twenty‐three hyperthyro...

  19. Salivary biomarkers in psychobiological medicine

    OpenAIRE

    Chiappelli, Francesco; Iribarren, Francisco Javier; Prolo, Paolo

    2006-01-01

    The value of salivary biomarkers for diagnostic and prognostic assessments has become increasingly well established in medicine, pharmacology, and dentistry. Certain salivary components mirror the neuro-endocrine status of the organism. Other saliva products are protein in nature, and can serve to reflect immune surveillance processes. The autonomic nervous system regulates the process of salivation, and the concentration of yet other salivary components, such as α-amylase, which provide a re...

  20. Epigenetic biomarkers in esophageal cancer.

    Science.gov (United States)

    Kaz, Andrew M; Grady, William M

    2014-01-28

    The aberrant DNA methylation of tumor suppressor genes is well documented in esophageal cancer, including adenocarcinoma (EAC) and squamous cell carcinoma (ESCC) as well as in Barrett's esophagus (BE), a pre-malignant condition that is associated with chronic acid reflux. BE is a well-recognized risk factor for the development of EAC, and consequently the standard of care is for individuals with BE to be placed in endoscopic surveillance programs aimed at detecting early histologic changes that associate with an increased risk of developing EAC. Yet because the absolute risk of EAC in individuals with BE is minimal, a clinical need in the management of BE is the identification of additional risk markers that will indicate individuals who are at a significant absolute risk of EAC so that they may be subjected to more intensive surveillance. The best currently available risk marker is the degree of dysplasia in endoscopic biopsies from the esophagus; however, this marker is suboptimal for a variety of reasons. To date, there are no molecular biomarkers that have been translated to widespread clinical practice. The search for biomarkers, including hypermethylated genes, for either the diagnosis of BE, EAC, or ESCC or for risk stratification for the development of EAC in those with BE is currently an area of active research. In this review, we summarize the status of identified candidate epigenetic biomarkers for BE, EAC, and ESCC. Most of these aberrantly methylated genes have been described in the context of early detection or diagnostic markers; others might prove useful for estimating prognosis or predicting response to treatment. Finally, special attention will be paid to some of the challenges that must be overcome in order to develop clinically useful esophageal cancer biomarkers. PMID:22406828

  1. Biomarkers of Peripheral Arterial Disease

    OpenAIRE

    Cooke, John P.; Wilson, Andrew M.

    2010-01-01

    Atherosclerotic arterial occlusive disease affecting the lower extremities is also known as peripheral arterial disease (PAD). This disorder affects 8 to 12 million individuals in the United States, and is also increasingly prevalent in Europe and Asia (1–4). Unfortunately, most patients are not diagnosed and are not optimally treated. A blood test for PAD, if sufficiently sensitive and specific, would be expected to improve recognition and treatment of these individuals. Even a biomarker pan...

  2. Finding good biomarkers for sarcopenia

    OpenAIRE

    Scharf, Gesine; Heineke, Joerg

    2012-01-01

    The term sarcopenia describes the age-related loss of skeletal muscle mass and function. While this process, in principal, occurs in every adult person and already starts around the age of 40, it is associated with disability, morbidity, and increased mortality in some individuals. In the absence of clear clinical manifestation, we today lack the ability to differentiate between physiological and pathological sarcopenia. In this regard, we need good biomarkers that can be quantified in a reli...

  3. Dietary biomarkers: advances, limitations and future directions

    Directory of Open Access Journals (Sweden)

    Hedrick Valisa E

    2012-12-01

    Full Text Available Abstract The subjective nature of self-reported dietary intake assessment methods presents numerous challenges to obtaining accurate dietary intake and nutritional status. This limitation can be overcome by the use of dietary biomarkers, which are able to objectively assess dietary consumption (or exposure without the bias of self-reported dietary intake errors. The need for dietary biomarkers was addressed by the Institute of Medicine, who recognized the lack of nutritional biomarkers as a knowledge gap requiring future research. The purpose of this article is to review existing literature on currently available dietary biomarkers, including novel biomarkers of specific foods and dietary components, and assess the validity, reliability and sensitivity of the markers. This review revealed several biomarkers in need of additional validation research; research is also needed to produce sensitive, specific, cost-effective and noninvasive dietary biomarkers. The emerging field of metabolomics may help to advance the development of food/nutrient biomarkers, yet advances in food metabolome databases are needed. The availability of biomarkers that estimate intake of specific foods and dietary components could greatly enhance nutritional research targeting compliance to national recommendations as well as direct associations with disease outcomes. More research is necessary to refine existing biomarkers by accounting for confounding factors, to establish new indicators of specific food intake, and to develop techniques that are cost-effective, noninvasive, rapid and accurate measures of nutritional status.

  4. M2m Automation: Matlab-To-Map Reduce Automation

    Directory of Open Access Journals (Sweden)

    Archana C S

    2014-06-01

    Full Text Available Abstract- MapReduce is a very popular parallel programming model for cloud computing platforms, and has become an effective method for processing massive data by using a cluster of computers. Program language -to-MapReduce Automator is a possible solution to help traditional programmers easily deploy an application to cloud systems through translating sequential codes to MapReduce codes.M2M Automation mainly focuses on automating numerical computations by using hadoop at the back end. M2M automates Hadoop, for faster execution of Matlab commands using MapReduce code.

  5. Burkitt Lymphoma: beyond discoveries.

    Science.gov (United States)

    Mbulaiteye, Sam M

    2013-01-01

    First described in 1958 in Uganda, Burkitt lymphoma (BL) attracted interest worldwide following reports of its uneven geographic distribution and rapidly fatal clinical course. Both suggested infectious etiology and curability. Seminal discoveries followed in quick succession. Viral etiology - due to Epstein-Barr virus (EBV) - was confirmed. Chromosomal translocations, involving cellular MYC, a protooncogene, were discovered, shown to be a hallmark of BL, and central to the genetic basis of cancer. Cure of BL using combination chemotherapy was demonstrated. Unfortunately, civil disturbance in Africa disrupted BL research and blunted its impact on education and oncology care in Africa. Important questions went unanswered. The risk of BL due to malaria or EBV was not quantified. Efforts to answer whether BL could be prevented - by preventing malaria or early EBV infection - were abandoned. The mechanism of malaria in BL is unknown. In Africa, BL remains mostly fatal and diagnosis is still made clinically. Unprecedented advances in molecular, genomics and proteomic technologies, promising to unlock mysteries of cancers, have re-awakened interest in BL. With return of stability to Africa, the unanswered questions about BL are re-attracting global interest. This interest now includes exploiting the knowledge gained about genetics, proteomics, and bioinformatics to enable the development of targeted less toxic treatment for BL; and simpler methods to diagnose BL with high accuracy and sensitivity. The articles in the Burkitt Lymphoma (BL): Beyond Discoveries in Infectious Agents and Cancer highlight BL as priority. Authors explore etiology, pathology, pathogenesis of BL, and whether knowledge gained in the studies of BL can catalyze sustainable cancer services in one of the world's poorest served regions. PMID:24079372

  6. Why Ontology Evolution is Essential in Modelling Scientific Discovery

    OpenAIRE

    Bundy, Alan

    2008-01-01

    We can model scientific discovery as automated reasoning and learning, e.g., using a logic-based representation of knowledge, which we will here call an ontology. Much of what Kuhn calls “normal science” may be modelled as problem solving within the shared ontology of a scientific community (Kuhn 1970). However, to model what Kuhn calls a “paradigm shift”, we need mechanisms for changing this ontology. This is what W3C call ontology evolution1. As we will see, ontology evolution can also happ...

  7. Melody-based knowledge discovery in musical pieces

    Science.gov (United States)

    Rybnik, Mariusz; Jastrzebska, Agnieszka

    2016-06-01

    The paper is focused on automated knowledge discovery in musical pieces, based on transformations of digital musical notation. Usually a single musical piece is analyzed, to discover the structure as well as traits of separate voices. Melody and rhythm is processed with the use of three proposed operators, that serve as meta-data. In this work we focus on melody, so the processed data is labeled using fuzzy labels, created for detecting various voice characteristics. A comparative analysis of two musical pieces may be performed as well, that compares them in terms of various rhythmic or melodic traits (as a whole or with voice separation).

  8. Perspective: Data infrastructure for high throughput materials discovery

    Science.gov (United States)

    Pfeif, E. A.; Kroenlein, K.

    2016-05-01

    Computational capability has enabled materials design to evolve from trial-and-error towards more informed methodologies that require large amounts of data. Expert-designed tools and their underlying databases facilitate modern-day high throughput computational methods. Standard data formats and communication standards increase the impact of traditional data, and applying these technologies to a high throughput experimental design provides dense, targeted materials data that are valuable for material discovery. Integrated computational materials engineering requires both experimentally and computationally derived data. Harvesting these comprehensively requires different methods of varying degrees of automation to accommodate variety and volume. Issues of data quality persist independent of type.

  9. Machine-assisted discovery of relationships in astronomy

    CERN Document Server

    Graham, Matthew J; Mahabal, Ashish A; Donalek, Ciro; Drake, Andrew J

    2013-01-01

    High-volume feature-rich data sets are becoming the bread-and-butter of 21st century astronomy but present significant challenges to scientific discovery. In particular, identifying scientifically significant relationships between sets of parameters is non-trivial. Similar problems in biological and geosciences have led to the development of systems which can explore large parameter spaces and identify potentially interesting sets of associations. In this paper, we describe the application of automated discovery systems of relationships to astronomical data sets, focussing on an evolutionary programming technique and an information-theory technique. We demonstrate their use with classical astronomical relationships - the Hertzsprung-Russell diagram and the fundamental plane of elliptical galaxies. We also show how they work with the issue of binary classification which is relevant to the next generation of large synoptic sky surveys, such as LSST. We find that comparable results to more familiar techniques, s...

  10. An automated algorithm for online detection of fragmented QRS and identification of its various morphologies

    OpenAIRE

    Maheshwari, Sidharth; Acharyya, Amit; Puddu, Paolo Emilio; Mazomenos, Evangelos B.; Leekha, Gourav; Maharatna, Koushik; Schiariti, Michele

    2013-01-01

    Fragmented QRS (f-QRS) has been proven to be an efficient biomarker for several diseases, including remote and acute myocardial infarction, cardiac sarcoidosis, non-ischaemic cardiomyopathy, etc. It has also been shown to have higher sensitivity and/or specificity values than the conventional markers (e.g. Q-wave, ST-elevation, etc.) which may even regress or disappear with time. Patients with such diseases have to undergo expensive and sometimes invasive tests for diagnosis. Automated detect...

  11. Automated Assessment, Face to Face

    OpenAIRE

    Rizik M. H. Al-Sayyed; Amjad Hudaib; Muhannad AL-Shboul; Yousef Majdalawi; Mohammed Bataineh

    2010-01-01

    This research paper evaluates the usability of automated exams and compares them with the paper-and-pencil traditional ones. It presents the results of a detailed study conducted at The University of Jordan (UoJ) that comprised students from 15 faculties. A set of 613 students were asked about their opinions concerning automated exams; and their opinions were deeply analyzed. The results indicate that most students reported that they are satisfied with using automated exams but they have sugg...

  12. Automation System Products and Research

    OpenAIRE

    Rintala, Mikko; Sormunen, Jussi; Kuisma, Petri; Rahkala, Matti

    2014-01-01

    Automation systems are used in most buildings nowadays. In the past they were mainly used in industry to control and monitor critical systems. During the past few decades the automation systems have become more common and are used today from big industrial solutions to homes of private customers. With the growing need for ecologic and cost-efficient management systems, home and building automation systems are becoming a standard way of controlling lighting, ventilation, heating etc. Auto...

  13. Software Testing and Documenting Automation

    OpenAIRE

    Tsybin, Anton; Lyadova, Lyudmila

    2008-01-01

    This article describes some approaches to problem of testing and documenting automation in information systems with graphical user interface. Combination of data mining methods and theory of finite state machines is used for testing automation. Automated creation of software documentation is based on using metadata in documented system. Metadata is built on graph model. Described approaches improve performance and quality of testing and documenting processes.

  14. Embedded system for building automation

    OpenAIRE

    Rolih, Andrej

    2014-01-01

    Home automation is a fast developing field of computer science and electronics. Companies are offering many different products for home automation. Ranging anywhere from complete systems for building management and control, to simple smart lights that can be connected to the internet. These products offer the user greater living comfort and lower their expenses by reducing the energy usage. This thesis shows the development of a simple home automation system that focuses mainly on the enhance...

  15. Discoveries of isotopes by fission

    Indian Academy of Sciences (India)

    M Thoennessen

    2015-09-01

    Of the about 3000 isotopes presently known, about 20% have been discovered in fission. The history of fission as it relates to the discovery of isotopes as well as the various reaction mechanisms leading to isotope discoveries involving fission are presented.

  16. Service discovery using Bloom filters

    NARCIS (Netherlands)

    Goering, Patrick; Heijenk, Geert; Lelieveldt, B.P.F.; Haverkort, B.R.H.M.; Laat, de C.T.A.M.; Heijnsdijk, J.W.J.

    2006-01-01

    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 beh

  17. Voltammetric aptasensors for protein disease biomarkers detection: A review.

    Science.gov (United States)

    Meirinho, Sofia G; Dias, Luís G; Peres, António M; Rodrigues, Lígia R

    2016-01-01

    An electrochemical aptasensor is a compact analytical device where the bioreceptor (aptamer) is coupled to a transducer surface to convert a biological interaction into a measurable signal (current) that can be easily processed, recorded and displayed. Since the discovery of the Systematic Evolution of Ligands by Enrichment (SELEX) methodology, the selection of aptamers and their application as bioreceptors has become a promising tool in the design of electrochemical aptasensors. Aptamers present several advantages that highlight their usefulness as bioreceptors such as chemical stability, cost effectiveness and ease of modification towards detection and immobilization at different transducer surfaces. In this review, a special emphasis is given to the potential use of electrochemical aptasensors for the detection of protein disease biomarkers using voltammetry techniques. Methods for the immobilization of aptamers onto electrode surfaces are discussed, as well as different electrochemical strategies that can be used for the design of aptasensors. PMID:27235188

  18. Advances in Biomarker Research in Parkinson's Disease.

    Science.gov (United States)

    Mehta, Shyamal H; Adler, Charles H

    2016-01-01

    Parkinson's disease (PD) is the second most common neurodegenerative disease, and the numbers are projected to double in the next two decades with the increase in the aging population. An important focus of current research is to develop interventions to slow the progression of the disease. However, prerequisites to it include the development of reliable biomarkers for early diagnosis which would identify at-risk groups and disease progression. In this review, we present updated evidence of already known clinical biomarkers (such as hyposmia and rapid eye movement (REM) sleep behavior disorder (RBD)) and neuroimaging biomarkers, as well as newer possible markers in the blood, CSF, and other tissues. While several promising candidates and methods to assess these biomarkers are on the horizon, it is becoming increasingly clear that no one candidate will clearly fulfill all the roles as a single biomarker. A multimodal and combinatorial approach to develop a battery of biomarkers will likely be necessary in the future. PMID:26711276

  19. World-wide distribution automation systems

    Energy Technology Data Exchange (ETDEWEB)

    Devaney, T.M.

    1994-12-31

    A worldwide power distribution automation system is outlined. Distribution automation is defined and the status of utility automation is discussed. Other topics discussed include a distribution management system, substation feeder, and customer functions, potential benefits, automation costs, planning and engineering considerations, automation trends, databases, system operation, computer modeling of system, and distribution management systems.

  20. AUTOMATED API TESTING APPROACH

    Directory of Open Access Journals (Sweden)

    SUNIL L. BANGARE

    2012-02-01

    Full Text Available Software testing is an investigation conducted to provide stakeholders with information about the quality of the product or service under test. With the help of software testing we can verify or validate the software product. Normally testing will be done after development of software but we can perform the software testing at the time of development process also. This paper will give you a brief introduction about Automated API Testing Tool. This tool of testing will reduce lots of headache after the whole development of software. It saves time as well as money. Such type of testing is helpful in the Industries & Colleges also.