WorldWideScience

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

    2009-01-01

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

  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 Supernova Discovery (Abstract)

    Science.gov (United States)

    Post, R. S.

    2015-12-01

    (Abstract only) We are developing a system of robotic telescopes for automatic recognition of Supernovas as well as other transient events in collaboration with the Puckett Supernova Search Team. At the SAS2014 meeting, the discovery program, SNARE, was first described. Since then, it has been continuously improved to handle searches under a wide variety of atmospheric conditions. Currently, two telescopes are used to build a reference library while searching for PSN with a partial library. Since data is taken every night without clouds, we must deal with varying atmospheric and high background illumination from the moon. Software is configured to identify a PSN, reshoot for verification with options to change the run plan to acquire photometric or spectrographic data. The telescopes are 24-inch CDK24, with Alta U230 cameras, one in CA and one in NM. Images and run plans are sent between sites so the CA telescope can search while photometry is done in NM. Our goal is to find bright PSNs with magnitude 17.5 or less which is the limit of our planned spectroscopy. We present results from our first automated PSN discoveries and plans for PSN data acquisition.

  4. 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.

  5. 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...

  6. 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.

  7. Using Aptamers for Cancer Biomarker Discovery

    Directory of Open Access Journals (Sweden)

    Yun Min Chang

    2013-01-01

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

  8. The Process Chain for Peptidomic Biomarker Discovery

    Directory of Open Access Journals (Sweden)

    Michael Schrader

    2006-01-01

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

  9. Automated Discovery of Inductive Theorems

    OpenAIRE

    McCasland, Roy; Bundy, Alan; Serge, Autexier

    2007-01-01

    Inductive mathematical theorems have, as a rule, historically been quite difficult to prove – both for mathematics students and for auto- mated theorem provers. That said, there has been considerable progress over the past several years, within the automated reasoning community, towards proving some of these theorems. However, little work has been done thus far towards automatically discovering them. In this paper we present our methods of discovering (as well as proving) inductive theorems, ...

  10. Current technological challenges in biomarker discovery and validation

    NARCIS (Netherlands)

    Horvatovich, Peter L.; Bischoff, Rainer

    2010-01-01

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

  11. Serum Glycoprotein Biomarker Discovery and Qualification Pipeline Reveals Novel Diagnostic Biomarker Candidates for Esophageal Adenocarcinoma.

    Science.gov (United States)

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

    2015-11-01

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

  12. Exploiting background knowledge in automated discovery

    Energy Technology Data Exchange (ETDEWEB)

    Aronis, J.M.; Buchanan, B.G. [Univ. of Pittsburgh, PA (United States); Provost, F.J. [NYNEX Science and Technology, White Plains, NY (United States)

    1996-12-31

    Prior work in automated scientific discovery has been successful in finding patterns in data, given that a reasonably small set of mostly relevant features is specified. The work described in this paper places data in the context of large bodies of background knowledge. Specifically, data items are connected to multiple databases of background knowledge represented as inheritance networks. The system has made a practical impact on botanical toxicology research, which required linking examples of cases of plant exposures to databases of botanical, geographical, and climate background knowledge.

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

    Directory of Open Access Journals (Sweden)

    Al-Shahib Ali

    2010-08-01

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

  14. 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.

  15. 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

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

    NARCIS (Netherlands)

    Aye, T.T.

    2010-01-01

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

  17. Managing laboratory automation: integration and informatics in drug discovery

    OpenAIRE

    Manly, Charles J.

    2000-01-01

    Drug discovery today requires the focused use of laboratory automation and other resources in combinatorial chemistry and high-throughput screening (HTS). The ultimate value of both combinatorial chemistry and HTS technologies and the lasting impact they will have on the drug discovery process is a chapter that remains to be written. Central to their success and impact is how well they are integrated with each other and with the rest of the drug discovery processes-informatics is key to this ...

  18. Exhaled Breath Condensate for Proteomic Biomarker Discovery

    Directory of Open Access Journals (Sweden)

    Sean W. Harshman

    2014-07-01

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

  19. Computational and Experimental Approaches to Cancer Biomarker Discovery

    DEFF Research Database (Denmark)

    Krzystanek, Marcin

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

  20. 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.

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

    Directory of Open Access Journals (Sweden)

    Federica Villanova

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

  2. 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.

  3. 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.

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

    Directory of Open Access Journals (Sweden)

    Larry Gold

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

  5. 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

  6. 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.

  7. Automated Discovery of Speech Act Categories in Educational Games

    Science.gov (United States)

    Rus, Vasile; Moldovan, Cristian; Niraula, Nobal; Graesser, Arthur C.

    2012-01-01

    In this paper we address the important task of automated discovery of speech act categories in dialogue-based, multi-party educational games. Speech acts are important in dialogue-based educational systems because they help infer the student speaker's intentions (the task of speech act classification) which in turn is crucial to providing adequate…

  8. Molecular biology tools: proteomics techniques in biomarker discovery.

    Science.gov (United States)

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

    2010-01-01

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

  9. 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.

  10. 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.

  11. 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.

  12. Targeted discovery and validation of plasma biomarkers of Parkinson's disease.

    Science.gov (United States)

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

    2014-11-07

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

  13. Parkinson's disease plasma biomarkers: an automated literature analysis followed by experimental validation.

    Science.gov (United States)

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

    2013-09-02

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

  14. 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.

  15. Sparse Mbplsr for Metabolomics Data and Biomarker Discovery

    DEFF Research Database (Denmark)

    Karaman, İbrahim

    2014-01-01

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

  16. Novel avenues of drug discovery and biomarkers for diabetes mellitus.

    Science.gov (United States)

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

    2011-02-01

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

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

    Energy Technology Data Exchange (ETDEWEB)

    Rodland, Karin D.

    2014-02-04

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

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

    Directory of Open Access Journals (Sweden)

    Joy eGuingab-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.

  19. Disease Classification and Biomarker Discovery Using ECG Data

    Directory of Open Access Journals (Sweden)

    Rong Huang

    2015-01-01

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

  20. 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.

  1. Biomarker discovery in subclinical mycobacterial infections of cattle.

    Directory of Open Access Journals (Sweden)

    Meetu Seth

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

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

    Science.gov (United States)

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

    2013-12-01

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

  3. Automated Protein Biomarker Analysis: on-line extraction of clinical samples by Molecularly Imprinted Polymers

    Science.gov (United States)

    Rossetti, Cecilia; Świtnicka-Plak, Magdalena A.; Grønhaug Halvorsen, Trine; Cormack, Peter A.G.; Sellergren, Börje; Reubsaet, Léon

    2017-01-01

    Robust biomarker quantification is essential for the accurate diagnosis of diseases and is of great value in cancer management. In this paper, an innovative diagnostic platform is presented which provides automated molecularly imprinted solid-phase extraction (MISPE) followed by liquid chromatography-mass spectrometry (LC-MS) for biomarker determination using ProGastrin Releasing Peptide (ProGRP), a highly sensitive biomarker for Small Cell Lung Cancer, as a model. Molecularly imprinted polymer microspheres were synthesized by precipitation polymerization and analytical optimization of the most promising material led to the development of an automated quantification method for ProGRP. The method enabled analysis of patient serum samples with elevated ProGRP levels. Particularly low sample volumes were permitted using the automated extraction within a method which was time-efficient, thereby demonstrating the potential of such a strategy in a clinical setting. PMID:28303910

  4. Automated Protein Biomarker Analysis: on-line extraction of clinical samples by Molecularly Imprinted Polymers

    Science.gov (United States)

    Rossetti, Cecilia; Świtnicka-Plak, Magdalena A.; Grønhaug Halvorsen, Trine; Cormack, Peter A. G.; Sellergren, Börje; Reubsaet, Léon

    2017-03-01

    Robust biomarker quantification is essential for the accurate diagnosis of diseases and is of great value in cancer management. In this paper, an innovative diagnostic platform is presented which provides automated molecularly imprinted solid-phase extraction (MISPE) followed by liquid chromatography-mass spectrometry (LC-MS) for biomarker determination using ProGastrin Releasing Peptide (ProGRP), a highly sensitive biomarker for Small Cell Lung Cancer, as a model. Molecularly imprinted polymer microspheres were synthesized by precipitation polymerization and analytical optimization of the most promising material led to the development of an automated quantification method for ProGRP. The method enabled analysis of patient serum samples with elevated ProGRP levels. Particularly low sample volumes were permitted using the automated extraction within a method which was time-efficient, thereby demonstrating the potential of such a strategy in a clinical setting.

  5. 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.

  6. Discovery of biomarkers for oxidative stress based on cellular metabolomics.

    Science.gov (United States)

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

    2016-07-01

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

  7. Discovery and development of DNA methylation-based biomarkers for lung cancer.

    Science.gov (United States)

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

    2014-02-01

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

  8. Random glycopeptide bead libraries for seromic biomarker discovery

    DEFF Research Database (Denmark)

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

    2010-01-01

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

  9. Statistical design for biospecimen cohort size in proteomics-based biomarker discovery and verification studies.

    Science.gov (United States)

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

    2013-12-01

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

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

    NARCIS (Netherlands)

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

    2006-01-01

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

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

    NARCIS (Netherlands)

    Horvatovich, Peter; Govorukhina, Natalia; Bischoff, Rainer

    2006-01-01

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

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

    DEFF Research Database (Denmark)

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

    2016-01-01

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

  13. Biomarker discovery by proteomics-based approaches for early detection and personalized medicine in colorectal cancer.

    Science.gov (United States)

    Corbo, Claudia; Cevenini, Armando; Salvatore, Francesco

    2016-12-26

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

  14. Cancer Stem Cell Biomarker Discovery Using Antibody Array Technology.

    Science.gov (United States)

    Burgess, Rob; Huang, Ruo-Pan

    2016-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Kevin C. O’Connor

    2006-01-01

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

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

    Science.gov (United States)

    Si, Qian

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

  17. 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

  18. A flexible integration and visualisation system for biomarker discovery.

    Science.gov (United States)

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

    2006-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Fernanda Fortes de Araujo

    2015-01-01

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

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

    Science.gov (United States)

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

    2015-01-01

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

  1. 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.

  2. Automated Device for Asynchronous Extraction of RNA, DNA, or Protein Biomarkers from Surrogate Patient Samples.

    Science.gov (United States)

    Bitting, Anna L; Bordelon, Hali; Baglia, Mark L; Davis, Keersten M; Creecy, Amy E; Short, Philip A; Albert, Laura E; Karhade, Aditya V; Wright, David W; Haselton, Frederick R; Adams, Nicholas M

    2016-12-01

    Many biomarker-based diagnostic methods are inhibited by nontarget molecules in patient samples, necessitating biomarker extraction before detection. We have developed a simple device that purifies RNA, DNA, or protein biomarkers from complex biological samples without robotics or fluid pumping. The device design is based on functionalized magnetic beads, which capture biomarkers and remove background biomolecules by magnetically transferring the beads through processing solutions arrayed within small-diameter tubing. The process was automated by wrapping the tubing around a disc-like cassette and rotating it past a magnet using a programmable motor. This device recovered biomarkers at ~80% of the operator-dependent extraction method published previously. The device was validated by extracting biomarkers from a panel of surrogate patient samples containing clinically relevant concentrations of (1) influenza A RNA in nasal swabs, (2) Escherichia coli DNA in urine, (3) Mycobacterium tuberculosis DNA in sputum, and (4) Plasmodium falciparum protein and DNA in blood. The device successfully extracted each biomarker type from samples representing low levels of clinically relevant infectivity (i.e., 7.3 copies/µL of influenza A RNA, 405 copies/µL of E. coli DNA, 0.22 copies/µL of TB DNA, 167 copies/µL of malaria parasite DNA, and 2.7 pM of malaria parasite protein).

  3. 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

  4. Emerging concepts in biomarker discovery; the US-Japan Workshop on Immunological Molecular Markers in Oncology.

    Science.gov (United States)

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

    2009-06-17

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

  5. Statistical spectroscopic tools for biomarker discovery and systems medicine.

    Science.gov (United States)

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

    2013-06-04

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

  6. Intact-protein analysis system for discovery of serum-based disease biomarkers.

    Science.gov (United States)

    Wang, Hong; Hanash, Samir

    2011-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Kirstin Mittelstrass

    2011-08-01

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

  8. Strategies for discovery and validation of methylated and hydroxymethylated DNA biomarkers.

    Science.gov (United States)

    Olkhov-Mitsel, Ekaterina; Bapat, Bharati

    2012-10-01

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

  9. Application of Glycoproteomics in the Discovery of Biomarkers for Lung Cancer

    Science.gov (United States)

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

    2017-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Juho Rousu

    2013-04-01

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

  11. 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...

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

    Science.gov (United States)

    Asmild, Margit; Oswald, Nicholas; Krzywkowski, Karen M; Friis, Søren; Jacobsen, Rasmus B; Reuter, Dirk; Taboryski, Rafael; Kutchinsky, Jonathan; Vestergaard, Ras K; Schrøder, Rikke L; Sørensen, Claus B; Bech, Morten; Korsgaard, Mads P G; Willumsen, Niels J

    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 developing two lines of automated patch clamp products, a traditional pipette-based system called Apatchi-1, and a silicon chip-based system QPatch. The degree of automation spans from semi-automation (Apatchi-1) where a trained technician interacts with the system in a limited way, to a complete automation (QPatch 96) where the system works continuously and unattended until screening of a full compound library is completed. The performance of the systems range from medium to high throughputs.

  13. Morph-X-Select: Morphology-based tissue aptamer selection for ovarian cancer biomarker discovery

    Science.gov (United States)

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

    2016-01-01

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

  14. 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.

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

    Energy Technology Data Exchange (ETDEWEB)

    Williams, Alex C [ORNL; Hitt, Austin N [ORNL; Voisin, Sophie [ORNL; Tourassi, Georgia [ORNL

    2013-01-01

    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.

  16. 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...... inhibitor. Through the analysis of tumour tissue derived from pre-operative renal cell carcinoma (RCC) clinical trials, the PREDICT consortium will use established and novel methods to integrate comprehensive tumour-derived genomic data with personalised tumour-derived shRNA and high throughput si......, reducing ineffective therapy in drug resistant disease, leading to improved quality of life and higher cost efficiency, which in turn should broaden patient access to beneficial therapeutics, thereby enhancing clinical outcome and cancer survival. The consortium will also establish and consolidate...

  17. Semi-Automated Discovery of Application Session Structure

    Energy Technology Data Exchange (ETDEWEB)

    Kannan, J.; Jung, J.; Paxson, V.; Koksal, C.

    2006-09-07

    While the problem of analyzing network traffic at the granularity of individual connections has seen considerable previous work and tool development, understanding traffic at a higher level---the structure of user-initiated sessions comprised of groups of related connections---remains much less explored. Some types of session structure, such as the coupling between an FTP control connection and the data connections it spawns, have prespecified forms, though the specifications do not guarantee how the forms appear in practice. Other types of sessions, such as a user reading email with a browser, only manifest empirically. Still other sessions might exist without us even knowing of their presence, such as a botnet zombie receiving instructions from its master and proceeding in turn to carry them out. We present algorithms rooted in the statistics of Poisson processes that can mine a large corpus of network connection logs to extract the apparent structure of application sessions embedded in the connections. Our methods are semi-automated in that we aim to present an analyst with high-quality information (expressed as regular expressions) reflecting different possible abstractions of an application's session structure. We develop and test our methods using traces from a large Internet site, finding diversity in the number of applications that manifest, their different session structures, and the presence of abnormal behavior. Our work has applications to traffic characterization and monitoring, source models for synthesizing network traffic, and anomaly detection.

  18. 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.

  19. 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.

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

    Science.gov (United States)

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

    2015-09-28

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

  1. 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.

  2. Indications of success: Strategies for utilizing neuroimaging biomarkers in CNS drug discovery and development: CINP/JSNP working group report.

    Science.gov (United States)

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

    2016-12-28

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

  3. Automated Discovery of New Chemical Reactions and Accurate Calculation of Their Rates

    Science.gov (United States)

    2015-06-02

    of the Search Space Thermochemistry Calculations. Even for a small hydrocarbon system, the number of reaction pathways which can be generated using... reaction is considered to be too endothermic to be interesting if the standard enthalpy of reaction (denoted as Hr0 in Tables 2-5) is higher than 20 kcal...AFRL-OSR-VA-TR-2015-0169 Automated discovery of new chemical reactions and accurate calculation of their rates William Green MASSACHUSETTS INSTITUTE

  4. 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.

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

    Directory of Open Access Journals (Sweden)

    Tatiana Altadill

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

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

    Science.gov (United States)

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

    2013-11-20

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

  7. 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).

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

    OpenAIRE

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

    2008-01-01

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

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

    Science.gov (United States)

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

    2015-08-01

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

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

    Directory of Open Access Journals (Sweden)

    Tözeren Aydın

    2007-09-01

    Full Text Available Abstract Background 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. Methods 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. Results 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. Conclusion 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.

  11. A comparison of methods for data-driven cancer outlier discovery, and an application scheme to semisupervised predictive biomarker discovery.

    Science.gov (United States)

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

    2011-04-18

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

  12. 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

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

    DEFF Research Database (Denmark)

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

    2015-01-01

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

  14. Targeted proteomics by selected reaction monitoring mass spectrometry: applications to systems biology and biomarker discovery.

    Science.gov (United States)

    Elschenbroich, Sarah; Kislinger, Thomas

    2011-02-01

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

  15. Compact cancer biomarkers discovery using a swarm intelligence feature selection algorithm.

    Science.gov (United States)

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

    2010-08-01

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

  16. 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.

  17. An integrated approach to blood-based cancer diagnosis and biomarker discovery.

    Science.gov (United States)

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

    2014-01-01

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

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

    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...

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

    Science.gov (United States)

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

    2013-06-01

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

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

    Science.gov (United States)

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

    2015-01-01

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

  1. 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.

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

    Directory of Open Access Journals (Sweden)

    Ding Yijun

    2012-07-01

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

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

    Directory of Open Access Journals (Sweden)

    Jasmina Saric

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

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

    Science.gov (United States)

    Suleimanov, Yury V; Green, William H

    2015-09-08

    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.

  5. 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.

  6. Biomarker discovery by CE-MS enables sequence analysis via MS/MS with platform-independent separation.

    Science.gov (United States)

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

    2006-06-01

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

  7. 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

  8. Automated discovery of single nucleotide polymorphism and simple sequence repeat molecular genetic markers.

    Science.gov (United States)

    Batley, Jacqueline; Jewell, Erica; Edwards, David

    2007-01-01

    Molecular genetic markers represent one of the most powerful tools for the analysis of genomes. Molecular marker technology has developed rapidly over the last decade, and two forms of sequence-based markers, simple sequence repeats (SSRs), also known as microsatellites, and single nucleotide polymorphisms (SNPs), now predominate applications in modern genetic analysis. The availability of large sequence data sets permits mining for SSRs and SNPs, which may then be applied to genetic trait mapping and marker-assisted selection. Here, we describe Web-based automated methods for the discovery of these SSRs and SNPs from sequence data. SSRPrimer enables the real-time discovery of SSRs within submitted DNA sequences, with the concomitant design of PCR primers for SSR amplification. Alternatively, users may browse the SSR Taxonomy Tree to identify predetermined SSR amplification primers for any species represented within the GenBank database. SNPServer uses a redundancy-based approach to identify SNPs within DNA sequence data. Following submission of a sequence of interest, SNPServer uses BLAST to identify similar sequences, CAP3 to cluster and assemble these sequences, and then the SNP discovery software autoSNP to detect SNPs and insertion/deletion (indel) polymorphisms.

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

    DEFF Research Database (Denmark)

    Cordwell, Stuart; Edwards, Alistair; Liddy, Kiersten

    2012-01-01

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

  10. Predicting Causal Relationships from Biological Data: Applying Automated Casual Discovery on Mass Cytometry Data of Human Immune Cells

    KAUST Repository

    Triantafillou, Sofia

    2017-03-31

    Learning the causal relationships that define a molecular system allows us to predict how the system will respond to different interventions. Distinguishing causality from mere association typically requires randomized experiments. Methods for automated causal discovery from limited experiments exist, but have so far rarely been tested in systems biology applications. In this work, we apply state-of-the art causal discovery methods on a large collection of public mass cytometry data sets, measuring intra-cellular signaling proteins of the human immune system and their response to several perturbations. We show how different experimental conditions can be used to facilitate causal discovery, and apply two fundamental methods that produce context-specific causal predictions. Causal predictions were reproducible across independent data sets from two different studies, but often disagree with the KEGG pathway databases. Within this context, we discuss the caveats we need to overcome for automated causal discovery to become a part of the routine data analysis in systems biology.

  11. 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

  12. High-Dimensional Medial Lobe Morphometry: An Automated MRI Biomarker for the New AD Diagnostic Criteria

    Directory of Open Access Journals (Sweden)

    Simon Duchesne

    2014-01-01

    Full Text Available Introduction. Medial temporal lobe atrophy assessment via magnetic resonance imaging (MRI has been proposed in recent criteria as an in vivo diagnostic biomarker of Alzheimer’s disease (AD. However, practical application of these criteria in a clinical setting will require automated MRI analysis techniques. To this end, we wished to validate our automated, high-dimensional morphometry technique to the hypothetical prediction of future clinical status from baseline data in a cohort of subjects in a large, multicentric setting, compared to currently known clinical status for these subjects. Materials and Methods. The study group consisted of 214 controls, 371 mild cognitive impairment (147 having progressed to probable AD and 224 stable, and 181 probable AD from the Alzheimer’s Disease Neuroimaging Initiative, with data acquired on 58 different 1.5 T scanners. We measured the sensitivity and specificity of our technique in a hierarchical fashion, first testing the effect of intensity standardization, then between different volumes of interest, and finally its generalizability for a large, multicentric cohort. Results. We obtained 73.2% prediction accuracy with 79.5% sensitivity for the prediction of MCI progression to clinically probable AD. The positive predictive value was 81.6% for MCI progressing on average within 1.5 (0.3 s.d. year. Conclusion. With high accuracy, the technique’s ability to identify discriminant medial temporal lobe atrophy has been demonstrated in a large, multicentric environment. It is suitable as an aid for clinical diagnostic of AD.

  13. Weighted gene co-expression based biomarker discovery for psoriasis detection.

    Science.gov (United States)

    Sundarrajan, Sudharsana; Arumugam, Mohanapriya

    2016-11-15

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

  14. 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.

  15. An Automated Microscale Thermophoresis Screening Approach for Fragment-Based Lead Discovery.

    Science.gov (United States)

    Linke, Pawel; Amaning, Kwame; Maschberger, Melanie; Vallee, Francois; Steier, Valerie; Baaske, Philipp; Duhr, Stefan; Breitsprecher, Dennis; Rak, Alexey

    2016-04-01

    Fragment-based lead discovery has proved to be an effective alternative to high-throughput screenings in identifying chemical matter that can be developed into robust lead compounds. The search for optimal combinations of biophysical techniques that can correctly and efficiently identify and quantify binding can be challenging due to the physicochemical properties of fragments. In order to minimize the time and costs of screening, optimal combinations of biophysical techniques with maximal information content, sensitivity, and robustness are needed. Here we describe an approach utilizing automated microscale thermophoresis (MST) affinity screening to identify fragments active against MEK1 kinase. MST identified multiple hits that were confirmed by X-ray crystallography but not detected by orthogonal methods. Furthermore, MST also provided information about ligand-induced aggregation and protein denaturation. The technique delivered a large number of binders while reducing experimentation time and sample consumption, demonstrating the potential of MST to execute and maximize the efficacy of fragment screening campaigns.

  16. Automated Antibody De Novo Sequencing and Its Utility in Biopharmaceutical Discovery

    Science.gov (United States)

    Sen, K. Ilker; Tang, Wilfred H.; Nayak, Shruti; Kil, Yong J.; Bern, Marshall; Ozoglu, Berk; Ueberheide, Beatrix; Davis, Darryl; Becker, Christopher

    2017-01-01

    Applications of antibody de novo sequencing in the biopharmaceutical industry range from the discovery of new antibody drug candidates to identifying reagents for research and determining the primary structure of innovator products for biosimilar development. When murine, phage display, or patient-derived monoclonal antibodies against a target of interest are available, but the cDNA or the original cell line is not, de novo protein sequencing is required to humanize and recombinantly express these antibodies, followed by in vitro and in vivo testing for functional validation. Availability of fully automated software tools for monoclonal antibody de novo sequencing enables efficient and routine analysis. Here, we present a novel method to automatically de novo sequence antibodies using mass spectrometry and the Supernovo software. The robustness of the algorithm is demonstrated through a series of stress tests.

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

    Directory of Open Access Journals (Sweden)

    Yongliang Yang

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

  18. 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

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

    Science.gov (United States)

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

  20. 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.

  1. 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

    2016-04-21

    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.

  2. 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.

  3. Glycoproteomics using so-called ‘fluid-biopsy’ specimens in the discovery of lung cancer biomarkers. Promise and challenge

    Science.gov (United States)

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

    2016-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Sharon J Pitteri

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

  5. Autonomous Observing and Planet Discovery with the Automated Planet Finder (APF)

    Science.gov (United States)

    Burt, Jennifer; Hanson, Russell; Holden, Bradford; Butler, R. Paul; Vogt, Steven S.; Laughlin, Greg

    2015-01-01

    The Automated Planet Finder (APF) is a dedicated, ground-based precision radial velocity facility located at Lick Observatory, operated by University of California Observatories (UCO). The 2.4-m telescope and accompanying high-resolution echelle spectrograph were specifically designed for the purpose of detecting planets in the habitable zone of low-mass stars. The telescope is operated every night (weather permitting) to achieve meaningful signal-to-noise gains from high cadence observing and to avoid the aliasing problems inherent to planets whose periods are close to the lunar month.The APF has been taking science quality data for over a year and has contributed to two planet discovery papers with data at a 1 m/s level of precision. The detection of these planets, especially the Uranus mass planet around GL687, indicates that the APF telescope is well suited to the discovery of low-mass planets orbiting low-mass stars in the as-yet relatively un-surveyed region of the sky near the north celestial pole.To take full advantage of the consistent influx of data it is necessary to analyze each night's results before deciding the next evening's targets. We are in the process of developing a fully automated reduction pipeline that will take data from raw FITS files to final radial velocity values and integrate those values into a master database. The database is then run through the publicly available Systemic console, a publically available software package for the analysis and combined multiparameter fitting of Doppler radial velocity observations. Systemic will re-calculate the possibility of planetary signals in the data and use this value, along with other considerations such as the star's brightness and chromospheric activity level, to assign it a priority rating for future observations.When the telescope is again on sky it uses a suite of stellar and atmospheric calibrations derived from the part year's observations to calculate the expected exposure time for

  6. Application of proteomics in the discovery of candidate protein biomarkers in a diabetes autoantibody standardization program sample subset.

    Science.gov (United States)

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

    2008-02-01

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

  7. Theoretical modeling of masking DNA application in aptamer-facilitated biomarker discovery.

    Science.gov (United States)

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

    2013-04-16

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

  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. 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.

  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. Design of an automated multicapillary instrument with fraction collection for DNA mutation discovery by constant denaturant capillary electrophoresis (CDCE).

    Science.gov (United States)

    Li, Qingbo; Deka, Chiranjit; Glassner, Brian J; Arnold, Kevin; Li-Sucholeiki, Xiao-Cheng; Tomita-Mitchell, Aoy; Thilly, William G; Karger, Barry L

    2005-08-01

    A fundamental goal ingenomics is the discovery of genetic variation that contributes to disease states or to differential drug responses. Single nucleotide polymorphism (SNP) detection has been the focus of much attention in the study of genetic variation over the last decade. These SNPs typically occur at a frequency greater than 1% in the human genome. Recently, low-frequency alleles are also being increasingly recognized as critical to obtain an improved understanding of the correlation between genetic variation and disease. Although many methods have been reported for the discovery and scoringof SNPs, sensitive, automated, and cost-effective methods and platforms for the discovery of low-frequency alleles are not yet readily available. We describe here an automated multicapillary instrument for high-throughput detection of low-frequency alleles from pooled samples using constant denaturant capillary electrophoresis. The instrument features high optical sensitivity (1 x 10(-12) M fluorescein detection limit), precise and stable temperature control (+/- 0.01degrees C), and automation for sample delivery, injection, matrix replacement, and fraction collection. The capillary array is divided into six groups of four capillaries, each of which can be independently set at any temperature ranging from room temperature to 90 degrees C. The key performance characteristics of the instrument are reported.

  12. 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.

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

    Institute of Scientific and Technical Information of China (English)

    肖雪媛; 卫秀平; 何大澄

    2003-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Choolani Mahesh

    2011-09-01

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

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

    Directory of Open Access Journals (Sweden)

    Schendel Dolores

    2008-12-01

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

  16. Development of urinary pseudotargeted LC-MS-based metabolomics method and its application in hepatocellular carcinoma biomarker discovery.

    Science.gov (United States)

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

    2015-02-01

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

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

    Directory of Open Access Journals (Sweden)

    Ping Yip

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

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

    Directory of Open Access Journals (Sweden)

    Richard J Perrin

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

  19. 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

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

    Science.gov (United States)

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

    2011-07-01

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

  1. Application of systems biology principles to protein biomarker discovery: Urinary exosomal proteome in renal transplantation

    Science.gov (United States)

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

    2013-01-01

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

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

    NARCIS (Netherlands)

    Kemperman, Ramses Franciscus Jacobus

    2007-01-01

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

  3. Current and future trends in biomarker discovery and development of companion diagnostics for arthritis.

    Science.gov (United States)

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

    2015-02-01

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

  4. Discovery of Hyperpolarized Molecular Imaging Biomarkers in a Novel Prostate Tissue Slice Culture Model

    Science.gov (United States)

    2013-06-01

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

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

    Institute of Scientific and Technical Information of China (English)

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

    2012-01-01

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

  6. Lectin chromatography/mass spectrometry discovery workflow identifies putative biomarkers of aggressive breast cancers.

    Science.gov (United States)

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

    2012-04-06

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

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

    Directory of Open Access Journals (Sweden)

    Barbara Stefanska

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

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

    Science.gov (United States)

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

    2017-03-01

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

  9. Endo-β-N-acetylglucosaminidase H de-N-glycosylation in a domestic microwave oven: application to biomarker discovery.

    Science.gov (United States)

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

    2013-02-01

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

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2008-09-01

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

  11. 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

  12. High-resolution taxonomic profiling of the subgingival microbiome for biomarker discovery and periodontitis diagnosis.

    Science.gov (United States)

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

    2015-02-01

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

  13. The role of quantitative mass spectrometry in the discovery of pancreatic cancer biomarkers for translational science.

    Science.gov (United States)

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

    2014-04-05

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

  14. 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.

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

    Directory of Open Access Journals (Sweden)

    Rachel M Ostroff

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

  16. Biomarker Discovery for Early Detection of Hepatocellular Carcinoma in Hepatitis C–infected Patients*

    Science.gov (United States)

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

    2013-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Esraa M. Hashem

    2016-04-01

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

  18. 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.

  19. Blood diagnostic biomarkers for major depressive disorder using multiplex DNA methylation profiles: discovery and validation.

    Science.gov (United States)

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

    2015-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Craig A Gedye

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

  1. 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.

  2. NMR metabolic fingerprints of murine melanocyte and melanoma cell lines: application to biomarker discovery

    Science.gov (United States)

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

    2017-01-01

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

  3. Applying bioinformatics to proteomics: is machine learning the answer to biomarker discovery for PD and MSA?

    Science.gov (United States)

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

    2012-11-01

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

  4. 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.

  5. A High Throughput, 384-Well, Semi-Automated, Hepatocyte Intrinsic Clearance Assay for Screening New Molecular Entities in Drug Discovery.

    Science.gov (United States)

    Heinle, Lance; Peterkin, Vincent; de Morais, Sonia M; Jenkins, Gary J; Badagnani, Ilaria

    2015-01-01

    A high throughput, semi-automated clearance screening assay in hepatocytes was developed allowing a scientist to generate data for 96 compounds in one week. The 384-well format assay utilizes a Thermo Multidrop Combi and an optimized LC-MS/MS method. The previously reported LCMS/ MS method reduced the analytical run time by 3-fold, down to 1.2 min injection-to-injection. The Multidrop was able to deliver hepatocytes to 384-well plates with minimal viability loss. Comparison of results from the new 384-well and historical 24-well assays yielded a correlation of 0.95. In addition, results obtained for 25 marketed drugs with various metabolism pathways had a correlation of 0.75 when compared with literature values. Precision was maintained in the new format as 8 compounds tested in ≥39 independent experiments had coefficients of variation ≤21%. The ability to predict in vivo clearances using the new stability assay format was also investigated using 22 marketed drugs and 26 AbbVie compounds. Correction of intrinsic clearance values with binding to hepatocytes (in vitro data) and plasma (in vivo data) resulted in a higher in vitro to in vivo correlation when comparing 22 marketed compounds in human (0.80 vs 0.35) and 26 AbbVie Discovery compounds in rat (0.56 vs 0.17), demonstrating the importance of correcting for binding in clearance studies. This newly developed high throughput, semi-automated clearance assay allows for rapid screening of Discovery compounds to enable Structure Activity Relationship (SAR) analysis based on high quality hepatocyte stability data in sufficient quantity and quality to drive the next round of compound synthesis.

  6. 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...... (QPatch 96) where the system works continuously and unattended until screening of a full compound library is completed. The performance of the systems range from medium to high throughputs....

  7. 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.

  8. Automated discovery of novel drug formulations using predictive iterated high throughput experimentation.

    Directory of Open Access Journals (Sweden)

    Filippo Caschera

    Full Text Available BACKGROUND: We consider the problem of optimizing a liposomal drug formulation: a complex chemical system with many components (e.g., elements of a lipid library that interact nonlinearly and synergistically in ways that cannot be predicted from first principles. METHODOLOGY/PRINCIPAL FINDINGS: The optimization criterion in our experiments was the percent encapsulation of a target drug, Amphotericin B, detected experimentally via spectrophotometric assay. Optimization of such a complex system requires strategies that efficiently discover solutions in extremely large volumes of potential experimental space. We have designed and implemented a new strategy of evolutionary design of experiments (Evo-DoE, that efficiently explores high-dimensional spaces by coupling the power of computer and statistical modeling with experimentally measured responses in an iterative loop. CONCLUSIONS: We demonstrate how iterative looping of modeling and experimentation can quickly produce new discoveries with significantly better experimental response, and how such looping can discover the chemical landscape underlying complex chemical systems.

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2008-02-01

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

  10. Biomarkers in Veterinary Medicine.

    Science.gov (United States)

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

    2017-02-08

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

  11. Whole animal automated platform for drug discovery against multi-drug resistant Staphylococcus aureus.

    Directory of Open Access Journals (Sweden)

    Rajmohan Rajamuthiah

    Full Text Available Staphylococcus aureus, the leading cause of hospital-acquired infections in the United States, is also pathogenic to the model nematode Caenorhabditis elegans. The C. elegans-S. aureus infection model was previously carried out on solid agar plates where the bacteriovorous C. elegans feeds on a lawn of S. aureus. However, agar-based assays are not amenable to large scale screens for antibacterial compounds. We have developed a high throughput liquid screening assay that uses robotic instrumentation to dispense a precise amount of methicillin resistant S. aureus (MRSA and worms in 384-well assay plates, followed by automated microscopy and image analysis. In validation of the liquid assay, an MRSA cell wall defective mutant, MW2ΔtarO, which is attenuated for killing in the agar-based assay, was found to be less virulent in the liquid assay. This robust assay with a Z'-factor consistently greater than 0.5 was utilized to screen the Biomol 4 compound library consisting of 640 small molecules with well characterized bioactivities. As proof of principle, 27 of the 30 clinically used antibiotics present in the library conferred increased C. elegans survival and were identified as hits in the screen. Surprisingly, the antihelminthic drug closantel was also identified as a hit in the screen. In further studies, we confirmed the anti-staphylococcal activity of closantel against vancomycin-resistant S. aureus isolates and other Gram-positive bacteria. The liquid C. elegans-S. aureus assay described here allows screening for anti-staphylococcal compounds that are not toxic to the host.

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

    Directory of Open Access Journals (Sweden)

    Lesley eCheng

    2013-08-01

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

  13. Comparison of protein, microRNA, and mRNA yields using different methods of urinary exosome isolation for the discovery of kidney disease biomarkers.

    Science.gov (United States)

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

    2012-11-01

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

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

    Directory of Open Access Journals (Sweden)

    Stefano de Franciscis

    2016-01-01

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

  15. Respiratory Toxicity Biomarkers

    Science.gov (United States)

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

  16. Proteome analysis of acute kidney injury - Discovery of new predominantly renal candidates for biomarker of kidney disease.

    Science.gov (United States)

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

    2017-01-16

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

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2007-06-01

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

  18. An Integrated Analysis of Heterogeneous Drug Responses in Acute Myeloid Leukemia That Enables the Discovery of Predictive Biomarkers.

    Science.gov (United States)

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

    2016-03-01

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

  19. 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.

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

    Institute of Scientific and Technical Information of China (English)

    史蕾; 郭瑞臣; 魏春敏

    2014-01-01

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

  1. A novel approach to the discovery of survival biomarkers in glioblastoma using a joint analysis of DNA methylation and gene expression.

    Science.gov (United States)

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

    2014-06-01

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

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

    Directory of Open Access Journals (Sweden)

    Zuojing Li

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

  3. WebMOTIFS: automated discovery, filtering and scoring of DNA sequence motifs using multiple programs and Bayesian approaches.

    Science.gov (United States)

    Romer, Katherine A; Kayombya, Guy-Richard; Fraenkel, Ernest

    2007-07-01

    WebMOTIFS provides a web interface that facilitates the discovery and analysis of DNA-sequence motifs. Several studies have shown that the accuracy of motif discovery can be significantly improved by using multiple de novo motif discovery programs and using randomized control calculations to identify the most significant motifs or by using Bayesian approaches. WebMOTIFS makes it easy to apply these strategies. Using a single submission form, users can run several motif discovery programs and score, cluster and visualize the results. In addition, the Bayesian motif discovery program THEME can be used to determine the class of transcription factors that is most likely to regulate a set of sequences. Input can be provided as a list of gene or probe identifiers. Used with the default settings, WebMOTIFS accurately identifies biologically relevant motifs from diverse data in several species. WebMOTIFS is freely available at http://fraenkel.mit.edu/webmotifs.

  4. Discovery and validation of plasma biomarkers for major depressive disorder classification based on liquid chromatography-mass spectrometry.

    Science.gov (United States)

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

    2015-05-01

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

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

    Directory of Open Access Journals (Sweden)

    Tong Zhang

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

  6. Semi-automated high-throughput fluorescent intercalator displacement-based discovery of cytotoxic DNA binding agents from a large compound library.

    Science.gov (United States)

    Glass, Lateca S; Bapat, Aditi; Kelley, Mark R; Georgiadis, Millie M; Long, Eric C

    2010-03-01

    High-throughput fluorescent intercalator displacement (HT-FID) was adapted to the semi-automated screening of a commercial compound library containing 60,000 molecules resulting in the discovery of cytotoxic DNA-targeted agents. Although commercial libraries are routinely screened in drug discovery efforts, the DNA binding potential of the compounds they contain has largely been overlooked. HT-FID led to the rapid identification of a number of compounds for which DNA binding properties were validated through demonstration of concentration-dependent DNA binding and increased thermal melting of A/T- or G/C-rich DNA sequences. Selected compounds were assayed further for cell proliferation inhibition in glioblastoma cells. Seven distinct compounds emerged from this screening procedure that represent structures unknown previously to be capable of targeting DNA leading to cell death. These agents may represent structures worthy of further modification to optimally explore their potential as cytotoxic anti-cancer agents. In addition, the general screening strategy described may find broader impact toward the rapid discovery of DNA targeted agents with biological activity.

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

    Institute of Scientific and Technical Information of China (English)

    Wanling Yang; Dingge Ying; Yu-Lung Lau

    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.

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

    Science.gov (United States)

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

    2014-09-01

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

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

    Science.gov (United States)

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

    2010-05-01

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

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

    Science.gov (United States)

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

    2014-11-01

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

  11. 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

  12. Application of quantitative proteomic analysis using tandem mass tags for discovery and identification of novel biomarkers in periodontal disease.

    Science.gov (United States)

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

    2013-08-01

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

  13. Automated search for star clusters in large multiband surveys: II. Discovery and investigation of open clusters in the galactic plane

    Science.gov (United States)

    Glushkova, E. V.; Koposov, S. E.; Zolotukhin, I. Yu.; Beletsky, Yu. V.; Vlasov, A. D.; Leonova, S. I.

    2010-02-01

    Automated search for star clusters in J, H, K s data from 2MASS catalog has been performed using the method developed by Koposov et al. (2008). We have found and verified 153 new clusters in the interval of the galactic latitude -24° http://ocl.sai.msu.ru ocl.sai.msu.ru" TargetType="URL"/> has been developed to facilitate dissemination and scientific usage of the results.

  14. Robofurnace: A semi-automated laboratory chemical vapor deposition system for high-throughput nanomaterial synthesis and process discovery

    Science.gov (United States)

    Oliver, C. Ryan; Westrick, William; Koehler, Jeremy; Brieland-Shoultz, Anna; Anagnostopoulos-Politis, Ilias; Cruz-Gonzalez, Tizoc; Hart, A. John

    2013-11-01

    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.

  15. 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

  16. 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.

  17. Discovery of colorectal cancer PIK3CA mutation as potential predictive biomarker: power and promise of molecular pathological epidemiology.

    Science.gov (United States)

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

    2014-06-05

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

  18. Automated search for star clusters in large multiband surveys: II. Discovery and investigation of open clusters in the Galactic plane

    CERN Document Server

    Glushkova, Elena; Zolotukhin, Ivan; Beletsky, Yuri; Vlasov, Andrey; Leonova, Svetlana

    2009-01-01

    Automated search for star clusters in J,H,K_s data from 2MASS catalog has been performed using the method developed by Koposov et. al (2008). We have found and verified 153 new clusters in the interval of the galactic latitude -24 < b < 24 degrees. Color excesses E(B-V), distance moduli and ages were determined for 130 new and 14 yet-unstudied known clusters. In this paper, we publish a catalog of coordinates, diameters, and main parameters of all the clusters under study. A special web-site available at http://ocl.sai.msu.ru has been developed to facilitate dissemination and scientific usage of the results.

  19. Rapid, non-targeted discovery of biochemical transformation and biomarker candidates in oncovirus-infected cell lines using LAESI mass spectrometry.

    Science.gov (United States)

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

    2012-04-18

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

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

    Directory of Open Access Journals (Sweden)

    Brian Dean

    2011-01-01

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

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

    Science.gov (United States)

    Dean, Brian

    2011-01-01

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

  2. Heating automation

    OpenAIRE

    Tomažič, Tomaž

    2013-01-01

    This degree paper presents usage and operation of peripheral devices with microcontroller for heating automation. The main goal is to make a quality system control for heating three house floors and with that, increase efficiency of heating devices and lower heating expenses. Heat pump, furnace, boiler pump, two floor-heating pumps and two radiator pumps need to be controlled by this system. For work, we have chosen a development kit stm32f4 - discovery with five temperature sensors, LCD disp...

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

    Science.gov (United States)

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

    2016-01-01

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

  4. Service discovery at home

    NARCIS (Netherlands)

    Sundramoorthy, Vasughi; Scholten, Hans; Jansen, Pierre; Hartel, Pieter

    2003-01-01

    Service discovery is a fairly new field that kicked off since the advent of ubiquitous computing and has been found essential in the making of intelligent networks by implementing automated discovery and remote control between devices. This paper provides an overview and comparison of several promin

  5. 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 a......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......-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...... alone (C-index 0.73), p = 0.041. CONCLUSIONS: The upgraded and analytically validated automated BSI was found to be a strong predictor of OS in mCRPC patients. Additionally, the change in automated BSI demonstrated an additive clinical value to the change in PSA in mCRPC patients being treated...

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

    DEFF Research Database (Denmark)

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

    2014-01-01

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

  7. Discovery and identification of serum potential biomarkers for pulmonary tuberculosis using iTRAQ-coupled two-dimensional LC-MS/MS.

    Science.gov (United States)

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

    2014-02-01

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

  8. Automated planar electrode electrophysiology in drug discovery: examples of the use of QPatch in basic characterization and high content screening on Na(v), K(Ca)2.3, and K(v)11.1 channels.

    Science.gov (United States)

    Korsgaard, Mads P G; Strøbaek, Dorte; Christophersen, Palle

    2009-01-01

    Planar chip technology has strongly facilitated the progress towards fully automated electrophysiological systems that, in contrast to the traditional patch clamp technology, have the capability of parallel compound testing. The throughput has been increased from testing below 10 compounds per day to a realized capacity approaching high throughput levels. Many pharmaceutical companies have implemented automated planar chip electrophysiology in their drug discovery process, particularly at the levels of lead optimization, secondary screening and safety testing, whereas primary screening is generally not performed. In this review, we briefly discuss the technology and give examples from selected NeuroSearch ion channel programs, where one of the systems, the QPatch, has been evaluated for use in lead optimization and primary screening campaigns, where high information content was a requirement.

  9. 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.

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

    Science.gov (United States)

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

    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.

  11. Metabolomics study with gas chromatography-mass spectrometry for predicting valproic acid-induced hepatotoxicity and discovery of novel biomarkers in rat urine.

    Science.gov (United States)

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

    2009-01-01

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

  12. 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

  13. Blood-based biomarkers for Parkinson's disease.

    Science.gov (United States)

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

    2014-01-01

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

  14. 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

  15. Biomarkers for neuromyelitis optica.

    Science.gov (United States)

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

    2015-02-02

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

  16. 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

  17. 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.

  18. 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

    2014-09-03

    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.

  19. 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.

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

    Directory of Open Access Journals (Sweden)

    Wegdam Wouter

    2012-07-01

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

  1. 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...... development of preventive and treatment strategies. Thus, the clinical use of a panel of biomarkers represents a diagnostic and prognostic tool of potentially great value. The technological development in recent years within proteomic research (determination and quantification of the complete protein content......) has made the discovery of novel biomarkers feasible. Several IBD-associated protein biomarkers are known, but none have been successfully implemented in daily use to distinguish CD and UC patients. The intestinal tissue remains an obvious place to search for novel biomarkers, which blood, urine...

  2. Immunohistochemistry in the Diagnosis of Mucinous Neoplasms Involving the Ovary: The Added Value of SATB2 and Biomarker Discovery Through Protein Expression Database Mining.

    Science.gov (United States)

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

    2016-05-01

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

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

    Science.gov (United States)

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

    2014-10-01

    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.

  4. Implementation of proteomic biomarkers: making it work

    Science.gov (United States)

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

    2012-01-01

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

  5. 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.

  6. 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.

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

    Science.gov (United States)

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

    2015-07-01

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

  8. Toward fully automated high performance computing drug discovery: a massively parallel virtual screening pipeline for docking and molecular mechanics/generalized Born surface area rescoring to improve enrichment.

    Science.gov (United States)

    Zhang, Xiaohua; Wong, Sergio E; Lightstone, Felice C

    2014-01-27

    In this work we announce and evaluate a high throughput virtual screening pipeline for in-silico screening of virtual compound databases using high performance computing (HPC). Notable features of this pipeline are an automated receptor preparation scheme with unsupervised binding site identification. The pipeline includes receptor/target preparation, ligand preparation, VinaLC docking calculation, and molecular mechanics/generalized Born surface area (MM/GBSA) rescoring using the GB model by Onufriev and co-workers [J. Chem. Theory Comput. 2007, 3, 156-169]. Furthermore, we leverage HPC resources to perform an unprecedented, comprehensive evaluation of MM/GBSA rescoring when applied to the DUD-E data set (Directory of Useful Decoys: Enhanced), in which we selected 38 protein targets and a total of ∼0.7 million actives and decoys. The computer wall time for virtual screening has been reduced drastically on HPC machines, which increases the feasibility of extremely large ligand database screening with more accurate methods. HPC resources allowed us to rescore 20 poses per compound and evaluate the optimal number of poses to rescore. We find that keeping 5-10 poses is a good compromise between accuracy and computational expense. Overall the results demonstrate that MM/GBSA rescoring has higher average receiver operating characteristic (ROC) area under curve (AUC) values and consistently better early recovery of actives than Vina docking alone. Specifically, the enrichment performance is target-dependent. MM/GBSA rescoring significantly out performs Vina docking for the folate enzymes, kinases, and several other enzymes. The more accurate energy function and solvation terms of the MM/GBSA method allow MM/GBSA to achieve better enrichment, but the rescoring is still limited by the docking method to generate the poses with the correct binding modes.

  9. Biomarkers in Parkinson's disease: a funder's perspective.

    Science.gov (United States)

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

    2010-10-01

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

  10. [Novel biomarkers for diabetic nephropathy].

    Science.gov (United States)

    Araki, Shin-ichi

    2014-02-01

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

  11. Warehouse automation

    OpenAIRE

    Pogačnik, Jure

    2017-01-01

    An automated high bay warehouse is commonly used for storing large number of material with a high throughput. In an automated warehouse pallet movements are mainly performed by a number of automated devices like conveyors systems, trolleys, and stacker cranes. From the introduction of the material to the automated warehouse system to its dispatch the system requires no operator input or intervention since all material movements are done automatically. This allows the automated warehouse to op...

  12. Discovery and validation of prostate cancer biomarkers

    NARCIS (Netherlands)

    F.H. Jansen (Flip)

    2013-01-01

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

  13. Guided Discoveries.

    Science.gov (United States)

    Ehrlich, Amos

    1991-01-01

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

  14. Volatility Discovery

    DEFF Research Database (Denmark)

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

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

  15. Accounting Automation

    OpenAIRE

    Laynebaril1

    2017-01-01

    Accounting Automation   Click Link Below To Buy:   http://hwcampus.com/shop/accounting-automation/  Or Visit www.hwcampus.com Accounting Automation” Please respond to the following: Imagine you are a consultant hired to convert a manual accounting system to an automated system. Suggest the key advantages and disadvantages of automating a manual accounting system. Identify the most important step in the conversion process. Provide a rationale for your response. ...

  16. 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.

  17. 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.

  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. 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...

  20. 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 both...

  1. Automated Discovery of Simulation Between Programs

    Science.gov (United States)

    2014-10-18

    relation. These relations enable the refinement-step of SimAbs. We have implemented SimAbs using UFO framework and Z3 SMT-solver and applied it to...step of SimAbs. We implemented SimAbs and AE-VAL on the top of the UFO framework [1, 15] and an SMT-solver Z3 [8], respectively. We have evaluated SimAbs...ut 6 Evaluation We have implemented SimAbs in the UFO framework, and evaluated it on the Software Verification Competition (SVCOMP’14) benchmarks and

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

    DEFF Research Database (Denmark)

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

    2015-01-01

    , 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...

  3. Cellular Proteases as Cancer Biomarkers: A Review

    Directory of Open Access Journals (Sweden)

    Sarah R. Röthlisberger

    2010-12-01

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

  4. Biomarkers of Parkinson's disease: current status and future perspectives.

    Science.gov (United States)

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

    2013-02-01

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

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

    DEFF Research Database (Denmark)

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

    2016-01-01

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

  6. 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.

  7. Automated High Throughput Drug Target Crystallography

    Energy Technology Data Exchange (ETDEWEB)

    Rupp, B

    2005-02-18

    The molecular structures of drug target proteins and receptors form the basis for 'rational' or structure guided drug design. The majority of target structures are experimentally determined by protein X-ray crystallography, which as evolved into a highly automated, high throughput drug discovery and screening tool. Process automation has accelerated tasks from parallel protein expression, fully automated crystallization, and rapid data collection to highly efficient structure determination methods. A thoroughly designed automation technology platform supported by a powerful informatics infrastructure forms the basis for optimal workflow implementation and the data mining and analysis tools to generate new leads from experimental protein drug target structures.

  8. 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

  9. Novel diagnostic biomarkers for prostate cancer.

    Science.gov (United States)

    Madu, Chikezie O; Lu, Yi

    2010-10-06

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

  10. 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.

  11. Novel biomarkers for cancer detection and prognostication

    NARCIS (Netherlands)

    Mehra, N.

    2007-01-01

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

  12. Automation or De-automation

    Science.gov (United States)

    Gorlach, Igor; Wessel, Oliver

    2008-09-01

    In the global automotive industry, for decades, vehicle manufacturers have continually increased the level of automation of production systems in order to be competitive. However, there is a new trend to decrease the level of automation, especially in final car assembly, for reasons of economy and flexibility. In this research, the final car assembly lines at three production sites of Volkswagen are analysed in order to determine the best level of automation for each, in terms of manufacturing costs, productivity, quality and flexibility. The case study is based on the methodology proposed by the Fraunhofer Institute. The results of the analysis indicate that fully automated assembly systems are not necessarily the best option in terms of cost, productivity and quality combined, which is attributed to high complexity of final car assembly systems; some de-automation is therefore recommended. On the other hand, the analysis shows that low automation can result in poor product quality due to reasons related to plant location, such as inadequate workers' skills, motivation, etc. Hence, the automation strategy should be formulated on the basis of analysis of all relevant aspects of the manufacturing process, such as costs, quality, productivity and flexibility in relation to the local context. A more balanced combination of automated and manual assembly operations provides better utilisation of equipment, reduces production costs and improves throughput.

  13. 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.

  14. 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.

  15. Beyond Discovery

    DEFF Research Database (Denmark)

    Korsgaard, Steffen; Sassmannshausen, Sean Patrick

    2015-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Berghella Anna

    2012-11-01

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

  17. A Comparative Analysis of Biomarker Selection Techniques

    Directory of Open Access Journals (Sweden)

    Nicoletta Dessì

    2013-01-01

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

  18. 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.

  19. Biomarkers of (osteo)arthritis.

    Science.gov (United States)

    Mobasheri, Ali; Henrotin, Yves

    2015-01-01

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

  20. 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......, primarily 2D NMR....

  1. A review on airway biomarkers: exposure, effect and susceptibility.

    Science.gov (United States)

    Corradi, Massimo; Goldoni, Matteo; Mutti, Antonio

    2015-04-01

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

  2. 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.

  3. 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

  4. Automating Finance

    Science.gov (United States)

    Moore, John

    2007-01-01

    In past years, higher education's financial management side has been riddled with manual processes and aging mainframe applications. This article discusses schools which had taken advantage of an array of technologies that automate billing, payment processing, and refund processing in the case of overpayment. The investments are well worth it:…

  5. Fluid biomarkers in multiple system atrophy: A review of the MSA Biomarker Initiative.

    Science.gov (United States)

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

    2015-08-01

    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 engagement for future clinical trials. We here review candidate fluid biomarkers for MSA and provide considerations for further developments and harmonization of standard operating procedures. A PubMed search was performed until April 24, 2015 to review the literature with regard to candidate blood and cerebrospinal fluid (CSF) biomarkers for MSA. Abstracts of 1760 studies were retrieved and screened for eligibility. The final list included 60 studies assessing fluid biomarkers in patients with MSA. Most studies have focused on alpha-synuclein, markers of axonal degeneration or catecholamines. Their results suggest that combining several CSF fluid biomarkers may be more successful than using single markers, at least for the diagnosis. Currently, the clinically most useful markers may comprise a combination of the light chain of neurofilament (which is consistently elevated in MSA compared to controls and Parkinson's disease), metabolites of the catecholamine pathway and proteins such as α-synuclein, DJ-1 and total-tau. Beyond future efforts in biomarker discovery, the harmonization of standard operating procedures will be crucial for future success.

  6. Context-sensitive service discovery experimental prototype and evaluation

    DEFF Research Database (Denmark)

    Balken, Robin; Haukrogh, Jesper; L. Jensen, Jens;

    2007-01-01

    The amount of different networks and services available to users today are increasing. This introduces the need for a way to locate and sort out irrelevant services in the process of discovering available services to a user. This paper describes and evaluates a prototype of an automated discovery...... to increase network scalability. The experimental analysis of service discovery times for different scenarios is used to optimize parameter settings of the service discovery system in order to achieve short response times....

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

    OpenAIRE

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

    2011-01-01

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

  8. 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...

  9. Marketing automation

    OpenAIRE

    Raluca Dania TODOR

    2017-01-01

    The automation of the marketing process seems to be nowadays, the only solution to face the major changes brought by the fast evolution of technology and the continuous increase in supply and demand. In order to achieve the desired marketing results, businessis have to employ digital marketing and communication services. These services are efficient and measurable thanks to the marketing technology used to track, score and implement each campaign. Due to the...

  10. Advances in biomarkers of major depressive disorder.

    Science.gov (United States)

    Huang, Tiao-Lai; Lin, Chin-Chuen

    2015-01-01

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

  11. 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....

  12. Combination of biomarkers

    DEFF Research Database (Denmark)

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

    2012-01-01

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

  13. Biomarkers in Parkinson's disease: Advances and strategies.

    Science.gov (United States)

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

    2016-01-01

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

  14. 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...

  15. OPEN DATA FOR DISCOVERY SCIENCE.

    Science.gov (United States)

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

    2016-01-01

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

  16. New sepsis biomarkers

    Directory of Open Access Journals (Sweden)

    Dolores Limongi

    2016-06-01

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

  17. New sepsis biomarkers

    Institute of Scientific and Technical Information of China (English)

    Dolores Limongi; Cartesio D’Agostini; Marco Ciotti

    2016-01-01

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

  18. New sepsis biomarkers

    Institute of Scientific and Technical Information of China (English)

    Dolores Limongi; Cartesio DAgostini; Marco Ciotti

    2016-01-01

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

  19. Clinical states model for biomarkers in bladder cancer.

    Science.gov (United States)

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

    2009-09-01

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

  20. The ongoing quest for biomarkers in Ankylosing Spondylitis.

    Science.gov (United States)

    Danve, Abhijeet; O'Dell, James

    2015-11-01

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

  1. Translational biomarkers of acetaminophen-induced acute liver injury.

    Science.gov (United States)

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

    2015-09-01

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

  2. Biomarkers in neonatology: the next generation of tests.

    Science.gov (United States)

    Ng, Pak C; Lam, Hugh S

    2012-01-01

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

  3. Class Discovery in Galaxy Classification

    CERN Document Server

    Bazell, D; Bazell, David; Miller, David J.

    2004-01-01

    In recent years, automated, supervised classification techniques have been fruitfully applied to labeling and organizing large astronomical databases. These methods require off-line classifier training, based on labeled examples from each of the (known) object classes. In practice, only a small batch of labeled examples, hand-labeled by a human expert, may be available for training. Moreover, there may be no labeled examples for some classes present in the data, i.e. the database may contain several unknown classes. Unknown classes may be present due to 1) uncertainty in or lack of knowledge of the measurement process, 2) an inability to adequately ``survey'' a massive database to assess its content (classes), and/or 3) an incomplete scientific hypothesis. In recent work, new class discovery in mixed labeled/unlabeled data was formally posed, with a proposed solution based on mixture models. In this work we investigate this approach, propose a competing technique suitable for class discovery in neural network...

  4. 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.

  5. Fish metalloproteins as biomarkers of environmental contamination.

    Science.gov (United States)

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

    2012-01-01

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

  6. Robust automated mass spectra interpretation and chemical formula calculation using mixed integer linear programming.

    Science.gov (United States)

    Baran, Richard; Northen, Trent R

    2013-10-15

    Untargeted metabolite profiling using liquid chromatography and mass spectrometry coupled via electrospray ionization is a powerful tool for the discovery of novel natural products, metabolic capabilities, and biomarkers. However, the elucidation of the identities of uncharacterized metabolites from spectral features remains challenging. A critical step in the metabolite identification workflow is the assignment of redundant spectral features (adducts, fragments, multimers) and calculation of the underlying chemical formula. Inspection of the data by experts using computational tools solving partial problems (e.g., chemical formula calculation for individual ions) can be performed to disambiguate alternative solutions and provide reliable results. However, manual curation is tedious and not readily scalable or standardized. Here we describe an automated procedure for the robust automated mass spectra interpretation and chemical formula calculation using mixed integer linear programming optimization (RAMSI). Chemical rules among related ions are expressed as linear constraints and both the spectra interpretation and chemical formula calculation are performed in a single optimization step. This approach is unbiased in that it does not require predefined sets of neutral losses and positive and negative polarity spectra can be combined in a single optimization. The procedure was evaluated with 30 experimental mass spectra and was found to effectively identify the protonated or deprotonated molecule ([M + H](+) or [M - H](-)) while being robust to the presence of background ions. RAMSI provides a much-needed standardized tool for interpreting ions for subsequent identification in untargeted metabolomics workflows.

  7. 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

  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. Automated methods of corrosion measurement

    DEFF Research Database (Denmark)

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

    1997-01-01

    Measurements of corrosion rates and other parameters connected with corrosion processes are important, first as indicators of the corrosion resistance of metallic materials and second because such measurements are based on general and fundamental physical, chemical, and electrochemical relations....... Hence improvements and innovations in methods applied in corrosion research are likeliy to benefit basic disciplines as well. A method for corrosion measurements can only provide reliable data if the beckground of the method is fully understood. Failure of a method to give correct data indicates a need...... 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. Automation...

  10. Biomarkers in clinical medicine.

    Science.gov (United States)

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

    2011-01-01

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

  11. 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,...

  12. New serological biomarkers of inflammatory bowel disease.

    Science.gov (United States)

    Li, Xuhang; Conklin, Laurie; Alex, Philip

    2008-09-01

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

  13. Automation 2017

    CERN Document Server

    Zieliński, Cezary; Kaliczyńska, Małgorzata

    2017-01-01

    This book consists of papers presented at Automation 2017, an international conference held in Warsaw from March 15 to 17, 2017. It discusses research findings associated with the concepts behind INDUSTRY 4.0, with a focus on offering a better understanding of and promoting participation in the Fourth Industrial Revolution. Each chapter presents a detailed analysis of a specific technical problem, in most cases followed by a numerical analysis, simulation and description of the results of implementing the solution in a real-world context. The theoretical results, practical solutions and guidelines presented are valuable for both researchers working in the area of engineering sciences and practitioners looking for solutions to industrial problems. .

  14. Marketing automation

    Directory of Open Access Journals (Sweden)

    TODOR Raluca Dania

    2017-01-01

    Full Text Available The automation of the marketing process seems to be nowadays, the only solution to face the major changes brought by the fast evolution of technology and the continuous increase in supply and demand. In order to achieve the desired marketing results, businessis have to employ digital marketing and communication services. These services are efficient and measurable thanks to the marketing technology used to track, score and implement each campaign. Due to the technical progress, the marketing fragmentation, demand for customized products and services on one side and the need to achieve constructive dialogue with the customers, immediate and flexible response and the necessity to measure the investments and the results on the other side, the classical marketing approached had changed continue to improve substantially.

  15. Comparison: Discovery on WSMOLX and miAamics/jABC

    Science.gov (United States)

    Kubczak, Christian; Vitvar, Tomas; Winkler, Christian; Zaharia, Raluca; Zaremba, Maciej

    This chapter compares the solutions to the SWS-Challenge discovery problems provided by DERI Galway and the joint solution from the Technical University of Dortmund and University of Postdam. The two approaches are described in depth in Chapters 10 and 13. The discovery scenario raises problems associated with making service discovery an automated process. It requires fine-grained specifications of search requests and service functionality including support for fetching dynamic information during the discovery process (e.g., shipment price). Both teams utilize semantics to describe services, service requests and data models in order to enable search at the required fine-grained level of detail.

  16. Biomarkers for Parkinson's disease.

    Science.gov (United States)

    Sherer, Todd B

    2011-04-20

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

  17. Pathogen specific biomarkers for the diagnosis of tuberculosis in deer

    Science.gov (United States)

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

  18. Natural variation in biomarkers indicating mastitis in healthy cows

    DEFF Research Database (Denmark)

    Åkerstedt, Maria; Forsbäck, Linda; Larsen, Torben

    2010-01-01

    Dairy herds are expanding and, with increasing numbers of animals in each herd, there is a need for automatic recording of indicators in milk in order to detect mastitis, inflammation of the udder. A number of biomarkers for mastitis have been suggested over the years. Mastitis usually occurs...... in one of the four udder quarters and since it is now possible to milk each udder quarter separately in automated milking systems, it is important to evaluate the normal variation in the biomarkers at udder quarter level. This study evaluated the normal variations between milkings for some biomarkers...... in clinically healthy cows, determined by repeated somatic cell count and bacteriological analysis. The biomarkers studied were serum amyloid A (SAA), haptoglobin (Hp), lactate dehydrogenase (LDH), N-acetyl-β-d-glucosaminidase (NAGase) and alkaline phosphatase (AP), parameters that have been suggested...

  19. 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.

  20. Novel technologies and emerging biomarkers for personalized cancer immunotherapy.

    Science.gov (United States)

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

    2016-01-01

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

  1. New serological biomarkers of inflammatory bowel disease

    Institute of Scientific and Technical Information of China (English)

    Xuhang Li; Laurie Conldin; Philip Alex

    2008-01-01

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

  2. Methodological and analytic considerations for blood biomarkers.

    Science.gov (United States)

    Christenson, Robert H; Duh, Show-Hong

    2012-01-01

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

  3. Biomarkers of Parkinson's disease: present and future.

    Science.gov (United States)

    Miller, Diane B; O'Callaghan, James P

    2015-03-01

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

  4. On consensus biomarker selection

    Directory of Open Access Journals (Sweden)

    Gambin Anna

    2007-05-01

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

  5. Biomarkers of Reflux Disease.

    Science.gov (United States)

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

    2016-06-01

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

  6. Biomarkers in Parkinson's disease.

    Science.gov (United States)

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

    2010-11-01

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

  7. 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.

  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. Tumor antigens as proteogenomic biomarkers in invasive ductal carcinomas

    DEFF Research Database (Denmark)

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

    2014-01-01

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

  10. The Present and Future of Prostate Cancer Urine Biomarkers

    Directory of Open Access Journals (Sweden)

    Jeremy Clark

    2013-06-01

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

  11. Current and emerging breast cancer biomarkers

    Directory of Open Access Journals (Sweden)

    Maryam Sana

    2015-01-01

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

  12. [Biomarkers in Alzheimer's disease].

    Science.gov (United States)

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

    2014-04-01

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

  13. 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.

  14. Automated information extraction from web APIs documentation

    OpenAIRE

    Ly, Papa Alioune; Pedrinaci, Carlos; Domingue, John

    2012-01-01

    A fundamental characteristic of Web APIs is the fact that, de facto, providers hardly follow any standard practices while implementing, publishing, and documenting their APIs. As a consequence, the discovery and use of these services by third parties is significantly hampered. In order to achieve further automation while exploiting Web APIs we present an approach for automatically extracting relevant technical information from the Web pages documenting them. In particular we have devised two ...

  15. Metabolic products as biomarkers

    Science.gov (United States)

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

    1992-01-01

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

  16. Commentary: statistics for biomarkers.

    Science.gov (United States)

    Lovell, David P

    2012-05-01

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

  17. 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.

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

    NARCIS (Netherlands)

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

    2009-01-01

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

  19. Gaucher disease: a model disorder for biomarker discovery

    NARCIS (Netherlands)

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

    2009-01-01

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

  20. Challenges for red blood cell biomarker discovery through proteomics

    NARCIS (Netherlands)

    Barasa, B.A.; Slijper, M.

    2014-01-01

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

  1. Validation of New Cancer Biomarkers

    DEFF Research Database (Denmark)

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

    2015-01-01

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

  2. Biomarker time out.

    Science.gov (United States)

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

    2014-10-01

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

  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. 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....

  5. 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...

  6. Autonomy and Automation

    Science.gov (United States)

    Shively, Jay

    2017-01-01

    A significant level of debate and confusion has surrounded the meaning of the terms autonomy and automation. Automation is a multi-dimensional concept, and we propose that Remotely Piloted Aircraft Systems (RPAS) automation should be described with reference to the specific system and task that has been automated, the context in which the automation functions, and other relevant dimensions. In this paper, we present definitions of automation, pilot in the loop, pilot on the loop and pilot out of the loop. We further propose that in future, the International Civil Aviation Organization (ICAO) RPAS Panel avoids the use of the terms autonomy and autonomous when referring to automated systems on board RPA. Work Group 7 proposes to develop, in consultation with other workgroups, a taxonomy of Levels of Automation for RPAS.

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

    Science.gov (United States)

    Salter, H; Holland, R

    2014-09-01

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

  8. 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.

  9. Usability of Discovery Portals

    NARCIS (Netherlands)

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

    2013-01-01

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

  10. Biomarkers for the differentiation of anemia and their clinical usefulness

    Directory of Open Access Journals (Sweden)

    Northrop-Clewes CA

    2013-03-01

    Full Text Available Christine A Northrop-Clewes,1 David I Thurnham21Nutrition Consultant, Cambridge, UK; 2Northern Ireland Centre for Food and Health, School of Biomedical Sciences, University of Ulster, Coleraine, UKAbstract: The World Health Organization defines anemia as the point at which the amount of hemoglobin in the circulation falls below World Health Organization cutoffs for specific age and sex groups. Anemia is a worldwide problem of complex etiology and is associated with many factors. The purpose of this review was to describe the biomarkers used to identify the nature of anemia in patients and in the community. The important biomarkers are the automated red cell counts, tests for nutritional deficiencies, hemoglobinopathies, and inflammation. Diseases are important potential initiators of anemia, but biomarkers of specific diseases are not included in this review, only the underlying feature common to all disease – namely, inflammation.Keywords: iron deficiency, biological markers, blood cell count, inflammation, avitaminosis, hemoglobinopathies

  11. Automation in Clinical Microbiology

    Science.gov (United States)

    Ledeboer, Nathan A.

    2013-01-01

    Historically, the trend toward automation in clinical pathology laboratories has largely bypassed the clinical microbiology laboratory. In this article, we review the historical impediments to automation in the microbiology laboratory and offer insight into the reasons why we believe that we are on the cusp of a dramatic change that will sweep a wave of automation into clinical microbiology laboratories. We review the currently available specimen-processing instruments as well as the total laboratory automation solutions. Lastly, we outline the types of studies that will need to be performed to fully assess the benefits of automation in microbiology laboratories. PMID:23515547

  12. 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.

  13. Biomarkers intersect with the exposome.

    Science.gov (United States)

    Rappaport, Stephen M

    2012-09-01

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

  14. Nanostructured optical microchips for cancer biomarker detection.

    Science.gov (United States)

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

    2012-01-01

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

  15. Parkinson's disease biomarkers program brain imaging repository.

    Science.gov (United States)

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

    2016-01-01

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

  16. A Framework for Automatic Web Service Discovery Based on Semantics and NLP Techniques

    OpenAIRE

    Asma Adala; Nabil Tabbane; Sami Tabbane

    2011-01-01

    As a greater number of Web Services are made available today, automatic discovery is recognized as an important task. To promote the automation of service discovery, different semantic languages have been created that allow describing the functionality of services in a machine interpretable form using Semantic Web technologies. The problem is that users do not have intimate knowledge about semantic Web service languages and related toolkits. In this paper, we propose a discovery framework tha...

  17. Automated DNA Sequencing System

    Energy Technology Data Exchange (ETDEWEB)

    Armstrong, G.A.; Ekkebus, C.P.; Hauser, L.J.; Kress, R.L.; Mural, R.J.

    1999-04-25

    Oak Ridge National Laboratory (ORNL) is developing a core DNA sequencing facility to support biological research endeavors at ORNL and to conduct basic sequencing automation research. This facility is novel because its development is based on existing standard biology laboratory equipment; thus, the development process is of interest to the many small laboratories trying to use automation to control costs and increase throughput. Before automation, biology Laboratory personnel purified DNA, completed cycle sequencing, and prepared 96-well sample plates with commercially available hardware designed specifically for each step in the process. Following purification and thermal cycling, an automated sequencing machine was used for the sequencing. A technician handled all movement of the 96-well sample plates between machines. To automate the process, ORNL is adding a CRS Robotics A- 465 arm, ABI 377 sequencing machine, automated centrifuge, automated refrigerator, and possibly an automated SpeedVac. The entire system will be integrated with one central controller that will direct each machine and the robot. The goal of this system is to completely automate the sequencing procedure from bacterial cell samples through ready-to-be-sequenced DNA and ultimately to completed sequence. The system will be flexible and will accommodate different chemistries than existing automated sequencing lines. The system will be expanded in the future to include colony picking and/or actual sequencing. This discrete event, DNA sequencing system will demonstrate that smaller sequencing labs can achieve cost-effective the laboratory grow.

  18. Biomarkers for systemic lupus erythematosus.

    Science.gov (United States)

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

    2012-04-01

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

  19. Detecting Blood-Based Biomarkers in Metastatic Breast Cancer: A Systematic Review of Their Current Status and Clinical Utility

    Science.gov (United States)

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

    2017-01-01

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

  20. 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...

  1. 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.

  2. 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...

  3. 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

  4. 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.

  5. Biomarkers of Renal Tumor Burden and Progression in TSC

    Science.gov (United States)

    2013-09-01

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

  6. Digital transplantation pathology: combining whole slide imaging, multiplex staining and automated image analysis.

    Science.gov (United States)

    Isse, K; Lesniak, A; Grama, K; Roysam, B; Minervini, M I; Demetris, A J

    2012-01-01

    Conventional histopathology is the gold standard for allograft monitoring, but its value proposition is increasingly questioned. "-Omics" analysis of tissues, peripheral blood and fluids and targeted serologic studies provide mechanistic insights into allograft injury not currently provided by conventional histology. Microscopic biopsy analysis, however, provides valuable and unique information: (a) spatial-temporal relationships; (b) rare events/cells; (c) complex structural context; and (d) integration into a "systems" model. Nevertheless, except for immunostaining, no transformative advancements have "modernized" routine microscopy in over 100 years. Pathologists now team with hardware and software engineers to exploit remarkable developments in digital imaging, nanoparticle multiplex staining, and computational image analysis software to bridge the traditional histology-global "-omic" analyses gap. Included are side-by-side comparisons, objective biopsy finding quantification, multiplexing, automated image analysis, and electronic data and resource sharing. Current utilization for teaching, quality assurance, conferencing, consultations, research and clinical trials is evolving toward implementation for low-volume, high-complexity clinical services like transplantation pathology. Cost, complexities of implementation, fluid/evolving standards, and unsettled medical/legal and regulatory issues remain as challenges. Regardless, challenges will be overcome and these technologies will enable transplant pathologists to increase information extraction from tissue specimens and contribute to cross-platform biomarker discovery for improved outcomes.

  7. 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.

  8. 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.

  9. Digital pathology and image analysis in tissue biomarker research.

    Science.gov (United States)

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

    2014-11-01

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

  10. Academic Drug Discovery Centres

    DEFF Research Database (Denmark)

    Kirkegaard, Henriette Schultz; Valentin, Finn

    2014-01-01

    Academic drug discovery centres (ADDCs) are seen as one of the solutions to fill the innovation gap in early drug discovery, which has proven challenging for previous organisational models. Prior studies of ADDCs have identified the need to analyse them from the angle of their economic and organi......Academic drug discovery centres (ADDCs) are seen as one of the solutions to fill the innovation gap in early drug discovery, which has proven challenging for previous organisational models. Prior studies of ADDCs have identified the need to analyse them from the angle of their economic...... their performance....

  11. 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

  12. 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.

  13. Neuroimaging Biomarkers for Psychosis

    Science.gov (United States)

    Hager, Brandon M.

    2015-01-01

    Background Biomarkers provide clinicians with a predictable model for the diagnosis, treatment and follow-up of medical ailments. Psychiatry has lagged behind other areas of medicine in the identification of biomarkers for clinical diagnosis and treatment. In this review, we investigated the current state of neuroimaging as it pertains to biomarkers for psychosis. Methods We reviewed systematic reviews and meta-analyses of the structural (sMRI), functional (fMRI), diffusion-tensor (DTI), Positron emission tomography (PET) and spectroscopy (MRS) studies of subjects at-risk or those with an established schizophrenic illness. Only articles reporting effect-sizes and confidence intervals were included in an assessment of robustness. Results Out of the identified meta-analyses and systematic reviews, 21 studies met the inclusion criteria for assessment. There were 13 sMRI, 4 PET, 3 MRS, and 1 DTI studies. The search terms included in the current review encompassed familial high risk (FHR), clinical high risk (CHR), First episode (FES), Chronic (CSZ), schizophrenia spectrum disorders (SSD), and healthy controls (HC). Conclusions Currently, few neuroimaging biomarkers can be considered ready for diagnostic use in patients with psychosis. At least in part, this may be related to the challenges inherent in the current symptom-based approach to classifying these disorders. While available studies suggest a possible value of imaging biomarkers for monitoring disease progression, more systematic research is needed. To date, the best value of imaging data in psychoses has been to shed light on questions of disease pathophysiology, especially through the characterization of endophenotypes. PMID:25883891

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

    Science.gov (United States)

    Kalia, Madhu

    2015-03-01

    Cancer is a group of diseases characterized by the uncontrolled growth and spread of abnormal cells and oncology is a branch of medicine that deals with tumors. The last decade has seen significant advances in the development of biomarkers in oncology that play a critical role in understanding molecular and cellular mechanisms which drive tumor initiation, maintenance and progression. Clinical molecular diagnostics and biomarker discoveries in oncology are advancing rapidly as we begin to understand the complex mechanisms that transform a normal cell into an abnormal one. These discoveries have fueled the development of novel drug targets and new treatment strategies. The standard of care for patients with advanced-stage cancers has shifted away from an empirical treatment strategy based on the clinical-pathological profile to one where a biomarker driven treatment algorithm based on the molecular profile of the tumor is used. Recent advances in multiplex genotyping technologies and high-throughput genomic profiling by next-generation sequencing make possible the rapid and comprehensive analysis of the cancer genome of individual patients even from very little tumor biopsy material. Predictive (diagnostic) biomarkers are helpful in matching targeted therapies with patients and in preventing toxicity of standard (systemic) therapies. Prognostic biomarkers identify somatic germ line mutations, changes in DNA methylation, elevated levels of microRNA (miRNA) and circulating tumor cells (CTC) in blood. Predictive biomarkers using molecular diagnostics are currently in use in clinical practice of personalized oncotherapy for the treatment of five diseases: chronic myeloid leukemia, colon, breast, lung cancer and melanoma and these biomarkers are being used successfully to evaluate benefits that can be achieved through targeted therapy. Examples of these molecularly targeted biomarker therapies are: tyrosine kinase inhibitors in chronic myeloid leukemia and

  15. Proteomics for Cerebrospinal Fluid Biomarker Identification in Parkinsons Disease: Methods and Critical Aspects

    Directory of Open Access Journals (Sweden)

    Antonio Conti

    2015-01-01

    Full Text Available Parkinson's disease (PD, similar with other neurodegenerative disorders, would benefit from the identification of early biomarkers for differential diagnosis and prognosis to address prompt clinical treatments. Together with hypothesis driven approaches, PD has been investigated by high-throughput differential proteomic analysis of cerebrospinal fluid (CSF protein content. The principal methodologies and techniques utilized in the proteomics field for PD biomarker discovery from CSF are presented in this mini review. The positive aspects and challenges in proteome-based biomarker research are also discussed.

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

    Directory of Open Access Journals (Sweden)

    Marialuisa Gandolfi

    2017-01-01

    Full Text Available Since the increasing update of the biomolecular scientific literature, biomarkers in stroke have reached an outstanding and remarkable revision in the very recent years. Besides the diagnostic and prognostic role of some inflammatory markers, many further molecules and biological factors have been added to the list, including tissue derived cytokines, growth factor-like molecules, hormones, and microRNAs. The literatures on brain derived growth factor and other neuroimmune mediators, bone-skeletal muscle biomarkers, cellular and immunity biomarkers, and the role of microRNAs in stroke recovery were reviewed. To date, biomarkers represent a possible challenge in the diagnostic and prognostic evaluation of stroke onset, pathogenesis, and recovery. Many molecules are still under investigation and may become promising and encouraging biomarkers. Experimental and clinical research should increase this list and promote new discoveries in this field, to improve stroke diagnosis and treatment.

  17. Automation of plasma protein binding assay using rapid equilibrium dialysis device and Tecan workstation.

    Science.gov (United States)

    Ye, Zhengqi; Zetterberg, Craig; Gao, Hong

    2017-03-14

    Binding of drug molecules to plasma proteins is an important parameter in assessing drug ADME properties. Plasma protein binding (PPB) assays are routinely performed during drug discovery and development. A fully automated PPB assay was developed using rapid equilibrium dialysis (RED) device and Tecan workstation coupled to an automated incubator. The PPB assay was carried out in unsealed RED plates which allowed the assay to be fully automated. The plasma pH was maintained at 7.4 during the 6-h dialysis under 2% CO2 condition. The samples were extracted with acetonitrile and analyzed by liquid chromatography tandem mass spectrometry. The percent bound results of 10 commercial drugs in plasma protein binding were very similar between the automated and manual assays, and were comparable to literature values. The automated assay increases laboratory productivity and is applicable to high-throughput screening of drug protein binding in drug discovery.

  18. Single cell analytic tools for drug discovery and development

    Science.gov (United States)

    Heath, James R.; Ribas, Antoni; Mischel, Paul S.

    2016-01-01

    The genetic, functional, or compositional heterogeneity of healthy and diseased tissues presents major challenges in drug discovery and development.1-3 In cancers, heterogeneity may be essential for tumor stability,4 but its precise role in tumor biology is poorly resolved. This challenges the design of accurate disease models for use in drug development, and can confound the interpretation of biomarker levels, and of patient responses to specific therapies. The complex nature of heterogeneous tissues has motivated the development of tools for single cell genomic, transcriptomic, and multiplex proteomic analysis. We review these tools, assess their advantages and limitations, and explore their potential applications in drug discovery and development. PMID:26669673

  19. Single-cell analysis tools for drug discovery and development.

    Science.gov (United States)

    Heath, James R; Ribas, Antoni; Mischel, Paul S

    2016-03-01

    The genetic, functional or compositional heterogeneity of healthy and diseased tissues presents major challenges in drug discovery and development. Such heterogeneity hinders the design of accurate disease models and can confound the interpretation of biomarker levels and of patient responses to specific therapies. The complex nature of virtually all tissues has motivated the development of tools for single-cell genomic, transcriptomic and multiplex proteomic analyses. Here, we review these tools and assess their advantages and limitations. Emerging applications of single cell analysis tools in drug discovery and development, particularly in the field of oncology, are discussed.

  20. Leveraging big data to transform target selection and drug discovery

    Science.gov (United States)

    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

  1. Automated planar patch-clamp.

    Science.gov (United States)

    Milligan, Carol J; Möller, Clemens

    2013-01-01

    Ion channels are integral membrane proteins that regulate the flow of ions across the plasma membrane and the membranes of intracellular organelles of both excitable and non-excitable cells. Ion channels are vital to a wide variety of biological processes and are prominent components of the nervous system and cardiovascular system, as well as controlling many metabolic functions. Furthermore, ion channels are known to be involved in many disease states and as such have become popular therapeutic targets. For many years now manual patch-clamping has been regarded as one of the best approaches for assaying ion channel function, through direct measurement of ion flow across these membrane proteins. Over the last decade there have been many remarkable breakthroughs in the development of technologies enabling the study of ion channels. One of these breakthroughs is the development of automated planar patch-clamp technology. Automated platforms have demonstrated the ability to generate high-quality data with high throughput capabilities, at great efficiency and reliability. Additional features such as simultaneous intracellular and extracellular perfusion of the cell membrane, current clamp operation, fast compound application, an increasing rate of parallelization, and more recently temperature control have been introduced. Furthermore, in addition to the well-established studies of over-expressed ion channel proteins in cell lines, new generations of planar patch-clamp systems have enabled successful studies of native and primary mammalian cells. This technology is becoming increasingly popular and extensively used both within areas of drug discovery as well as academic research. Many platforms have been developed including NPC-16 Patchliner(®) and SyncroPatch(®) 96 (Nanion Technologies GmbH, Munich), CytoPatch™ (Cytocentrics AG, Rostock), PatchXpress(®) 7000A, IonWorks(®) Quattro and IonWorks Barracuda™, (Molecular Devices, LLC); Dynaflow(®) HT (Cellectricon

  2. 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!

  3. Serendipity and Scientific Discovery.

    Science.gov (United States)

    Rosenman, Martin F.

    1988-01-01

    The discovery of penicillin is cited in a discussion of the role of serendipity as it relates to scientific discovery. The importance of sagacity as a personality trait is noted. Successful researchers have questioning minds, are willing to view data from several perspectives, and recognize and appreciate the unexpected. (JW)

  4. Friends' Discovery Camp

    Science.gov (United States)

    Seymour, Seth

    2008-01-01

    This article features Friends' Discovery Camp, a program that allows children with and without autism spectrum disorder to learn and play together. In Friends' Discovery Camp, campers take part in sensory-rich experiences, ranging from hands-on activities and performing arts to science experiments and stories teaching social skills. Now in its 7th…

  5. 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.

  6. Early Stage Health Technology Assessment for Precision Biomarkers in Oral Health and Systems Medicine

    OpenAIRE

    Steuten, Lotte M.G.

    2016-01-01

    Health technology assessment (HTA) is a crucial science that influences the responsible and evidence-based transition of new discoveries from laboratory to applications in the clinic and society. HTA has recently moved “upstream” so as to assess technologies from their onset at their discovery, design, or planning phase. Biomarker research is relatively recent in oral health, but growing rapidly with investments made to advance dentistry and oral health and importantly, to build effective bri...

  7. Automating checks of plan check automation.

    Science.gov (United States)

    Halabi, Tarek; Lu, Hsiao-Ming

    2014-07-08

    While a few physicists have designed new plan check automation solutions for their clinics, fewer, if any, managed to adapt existing solutions. As complex and varied as the systems they check, these programs must gain the full confidence of those who would run them on countless patient plans. The present automation effort, planCheck, therefore focuses on versatility and ease of implementation and verification. To demonstrate this, we apply planCheck to proton gantry, stereotactic proton gantry, stereotactic proton fixed beam (STAR), and IMRT treatments.

  8. "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…

  9. 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

  10. 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.

  11. More Benefits of Automation.

    Science.gov (United States)

    Getz, Malcolm

    1988-01-01

    Describes a study that measured the benefits of an automated catalog and automated circulation system from the library user's point of view in terms of the value of time saved. Topics discussed include patterns of use, access time, availability of information, search behaviors, and the effectiveness of the measures used. (seven references)…

  12. 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.

  13. Automation in immunohematology.

    Science.gov (United States)

    Bajpai, Meenu; Kaur, Ravneet; Gupta, Ekta

    2012-07-01

    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.

  14. 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

  15. 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...

  16. 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.

  17. 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).

  18. Biomarkers of Selenium Status

    Directory of Open Access Journals (Sweden)

    Gerald F. Combs, Jr.

    2015-03-01

    Full Text Available The essential trace element, selenium (Se, has multiple biological activities, which depend on the level of Se intake. Relatively low Se intakes determine the expression of selenoenzymes in which it serves as an essential constituent. Higher intakes have been shown to have anti-tumorigenic potential; and very high Se intakes can produce adverse effects. This hierarchy of biological activities calls for biomarkers informative at different levels of Se exposure. Some Se-biomarkers, such as the selenoproteins and particularly GPX3 and SEPP1, provide information about function directly and are of value in identifying nutritional Se deficiency and tracking responses of deficient individuals to Se-treatment. They are useful under conditions of Se intake within the range of regulated selenoprotein expression, e.g., for humans <55 μg/day and for animals <20 μg/kg diet. Other Se-biomarkers provide information indirectly through inferences based on Se levels of foods, tissues, urine or feces. They can indicate the likelihood of deficiency or adverse effects, but they do not provide direct evidence of either condition. Their value is in providing information about Se status over a wide range of Se intake, particularly from food forms. There is need for additional Se biomarkers particularly for assessing Se status in non-deficient individuals for whom the prospects of cancer risk reduction and adverse effects risk are the primary health considerations. This would include determining whether supranutritional intakes of Se may be required for maximal selenoprotein expression in immune surveillance cells. It would also include developing methods to determine low molecular weight Se-metabolites, i.e., selenoamino acids and methylated Se-metabolites, which to date have not been detectable in biological specimens. Recent analytical advances using tandem liquid chromatography-mass spectrometry suggest prospects for detecting these metabolites.

  19. IDBD: infectious disease biomarker database.

    Science.gov (United States)

    Yang, In Seok; Ryu, Chunsun; Cho, Ki Joon; Kim, Jin Kwang; Ong, Swee Hoe; Mitchell, Wayne P; Kim, Bong Su; Oh, Hee-Bok; Kim, Kyung Hyun

    2008-01-01

    Biomarkers enable early diagnosis, guide molecularly targeted therapy and monitor the activity and therapeutic responses across a variety of diseases. Despite intensified interest and research, however, the overall rate of development of novel biomarkers has been falling. Moreover, no solution is yet available that efficiently retrieves and processes biomarker information pertaining to infectious diseases. Infectious Disease Biomarker Database (IDBD) is one of the first efforts to build an easily accessible and comprehensive literature-derived database covering known infectious disease biomarkers. IDBD is a community annotation database, utilizing collaborative Web 2.0 features, providing a convenient user interface to input and revise data online. It allows users to link infectious diseases or pathogens to protein, gene or carbohydrate biomarkers through the use of search tools. It supports various types of data searches and application tools to analyze sequence and structure features of potential and validated biomarkers. Currently, IDBD integrates 611 biomarkers for 66 infectious diseases and 70 pathogens. It is publicly accessible at http://biomarker.cdc.go.kr and http://biomarker.korea.ac.kr.

  20. Network-based drugs and biomarkers.

    Science.gov (United States)

    Erler, Janine T; 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 progression are crucial for better understanding, detection and intervention. The era of network medicine has begun; however, there are fundamental principles associated with molecular networks that are essential to consider for this field to succeed. Here, we introduce network biology and some of its associated technologies. We then focus on the multivariate nature of cellular networks and how this has implications for biomarker and drug discovery using cancer metastasis as an example.

  1. The NINDS Parkinson's disease biomarkers program: The Ninds Parkinson's Disease Biomarkers Program

    Energy Technology Data Exchange (ETDEWEB)

    Rosenthal, Liana S. [Department of Neurology, Johns Hopkins University School of Medicine, Baltimore Maryland USA; Drake, Daniel [Department of Biostatistics, Columbia University, New York New York USA; Alcalay, Roy N. [Department of Neurology, Columbia University, New York New York USA; Babcock, Debra [National Institute of Neurological Diseases and Stroke, National Institutes of Health, Bethesda Maryland USA; Bowman, F. DuBois [Department of Biostatistics, Columbia University, New York New York USA; Chen-Plotkin, Alice [Department of Neurology, University of Pennsylvania, Philadelphia Pennsylvania USA; Dawson, Ted M. [Department of Neurology, Johns Hopkins University School of Medicine, Baltimore Maryland USA; Neuroregeneration and Stem Cell Programs, Institute for Cell Engineering, Solomon H. Snyder Department of Neuroscience, Pharmacology and Molecular Sciences, Johns Hopkins University School of Medicine, Baltimore Maryland USA; Dewey, Richard B. [Department of Neurology and Neurotherapeutics, University of Texas Southwestern Medical Center, Dallas USA; German, Dwight C. [Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas USA; Huang, Xuemei [Department of Neurology, Penn State Hershey Medical Center, Hershey Pennsylvania USA; Landin, Barry [Center for Information Technology, National Institutes of Health, Bethesda Maryland USA; McAuliffe, Matthew [Center for Information Technology, National Institutes of Health, Bethesda Maryland USA; Petyuk, Vladislav A. [Biological Sciences Division, Pacific Northwest National Laboratory, Richland Washington USA; Scherzer, Clemens R. [Department of Neurology, Brigham & Women' s Hospital, Harvard Medical School, Cambridge Massachusetts USA; Hillaire-Clarke, Coryse St. [National Institute of Neurological Diseases and Stroke, National Institutes of Health, Bethesda Maryland USA; Sieber, Beth-Anne [National Institute of Neurological Diseases and Stroke, National Institutes of Health, Bethesda Maryland USA; Sutherland, Margaret [National Institute of Neurological Diseases and Stroke, National Institutes of Health, Bethesda Maryland USA; Tarn, Chi [Coriell Institute for Medical Research, Camden New Jersey USA; West, Andrew [Department of Neurology, University of Alabama at Birmingham, Birmingham USA; Vaillancourt, David [Department of Applied Physiology and Kinesiology, University of Florida, Gainesville Florida USA; Zhang, Jing [Department of Pathology, University of Washington, Seattle Washington USA; Gwinn, Katrina [National Institute of Neurological Diseases and Stroke, National Institutes of Health, Bethesda Maryland USA

    2015-10-07

    Background: Neuroprotection for Parkinson Disease (PD) remains elusive. Biomarkers hold the promise of removing roadblocks to therapy development. The National Institute of Neurological Disorders and Stroke (NINDS) has therefore established the Parkinson’s Disease Biomarkers Program (PDBP) to promote discovery of biomarkers for use in phase II-III clinical trials in PD. Methods: The PDBP facilitates biomarker development to improve neuroprotective clinical trial design, essential for advancing therapeutics for PD. To date, eleven consortium projects in the PDBP are focused on the development of clinical and laboratory-based PD biomarkers for diagnosis, progression tracking, and/or the prediction of prognosis. Seven of these projects also provide detailed longitudinal data and biospecimens from PD patients and controls, as a resource for all PD researchers. Standardized operating procedures and pooled reference samples have been created in order to allow cross-project comparisons and assessment of batch effects. A web-based Data Management Resource facilitates rapid sharing of data and biosamples across the entire PD research community for additional biomarker projects. Results: Here we describe the PDBP, highlight standard operating procedures for the collection of biospecimens and data, and provide an interim report with quality control analysis on the first 1082 participants and 1033 samples with quality control analysis collected as of October 2014. Conclusions: By making samples and data available to academics and industry, encouraging the adoption of existing standards, and providing a resource which complements existing programs, the PDBP will accelerate the pace of PD biomarker research, with the goal of improving diagnostic methods and treatment.

  2. Systematic review automation technologies

    Science.gov (United States)

    2014-01-01

    Systematic reviews, a cornerstone of evidence-based medicine, are not produced quickly enough to support clinical practice. The cost of production, availability of the requisite expertise and timeliness are often quoted as major contributors for the delay. This detailed survey of the state of the art of information systems designed to support or automate individual tasks in the systematic review, and in particular systematic reviews of randomized controlled clinical trials, reveals trends that see the convergence of several parallel research projects. We surveyed literature describing informatics systems that support or automate the processes of systematic review or each of the tasks of the systematic review. Several projects focus on automating, simplifying and/or streamlining specific tasks of the systematic review. Some tasks are already fully automated while others are still largely manual. In this review, we describe each task and the effect that its automation would have on the entire systematic review process, summarize the existing information system support for each task, and highlight where further research is needed for realizing automation for the task. Integration of the systems that automate systematic review tasks may lead to a revised systematic review workflow. We envisage the optimized workflow will lead to system in which each systematic review is described as a computer program that automatically retrieves relevant trials, appraises them, extracts and synthesizes data, evaluates the risk of bias, performs meta-analysis calculations, and produces a report in real time. PMID:25005128

  3. 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.

  4. Early diagnosis of complex diseases by molecular biomarkers, network biomarkers, and dynamical network biomarkers.

    Science.gov (United States)

    Liu, Rui; Wang, Xiangdong; Aihara, Kazuyuki; Chen, Luonan

    2014-05-01

    Many studies have been carried out for early diagnosis of complex diseases by finding accurate and robust biomarkers specific to respective diseases. In particular, recent rapid advance of high-throughput technologies provides unprecedented rich information to characterize various disease genotypes and phenotypes in a global and also dynamical manner, which significantly accelerates the study of biomarkers from both theoretical and clinical perspectives. Traditionally, molecular biomarkers that distinguish disease samples from normal samples are widely adopted in clinical practices due to their ease of data measurement. However, many of them suffer from low coverage and high false-positive rates or high false-negative rates, which seriously limit their further clinical applications. To overcome those difficulties, network biomarkers (or module biomarkers) attract much attention and also achieve better performance because a network (or subnetwork) is considered to be a more robust form to characterize diseases than individual molecules. But, both molecular biomarkers and network biomarkers mainly distinguish disease samples from normal samples, and they generally cannot ensure to identify predisease samples due to their static nature, thereby lacking ability to early diagnosis. Based on nonlinear dynamical theory and complex network theory, a new concept of dynamical network biomarkers (DNBs, or a dynamical network of biomarkers) has been developed, which is different from traditional static approaches, and the DNB is able to distinguish a predisease state from normal and disease states by even a small number of samples, and therefore has great potential to achieve "real" early diagnosis of complex diseases. In this paper, we comprehensively review the recent advances and developments on molecular biomarkers, network biomarkers, and DNBs in particular, focusing on the biomarkers for early diagnosis of complex diseases considering a small number of samples and high

  5. 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.

  6. 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.

  7. 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

  8. 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

  9. Pathways to new drug discovery in neuropsychiatry.

    Science.gov (United States)

    Berk, Michael

    2012-11-29

    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.

  10. 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.

  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. 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.

  13. The art of discovery

    Directory of Open Access Journals (Sweden)

    Susie J. Lee

    2009-06-01

    Full Text Available "The Art of Discovery" discusses an ambitious educational program taught by the artist which incorporated locative media, contemporary art, site specificity, and creative work as a proposal for the integration of art, technology and science.

  14. The Learning Discovery

    Science.gov (United States)

    Prout, Joan

    1975-01-01

    The learning discovery of youngsters is a do-it-yourself teaching method for clerical, administrative, and accountant trainees at the Bankside House headquarters of the Central Electricity Generating Board's South Eastern Region, London. (Author)

  15. 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

  16. 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)

  17. 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...

  18. Chemoinformatics and Drug Discovery

    Directory of Open Access Journals (Sweden)

    Arnold Hagler

    2002-08-01

    Full Text Available This article reviews current achievements in the field of chemoinformatics and their impact on modern drug discovery processes. The main data mining approaches used in cheminformatics, such as descriptor computations, structural similarity matrices, and classification algorithms, are outlined. The applications of cheminformatics in drug discovery, such as compound selection, virtual library generation, virtual high throughput screening, HTS data mining, and in silico ADMET are discussed. At the conclusion, future directions of chemoinformatics are suggested.

  19. Can biomarkers help us hit targets in difficult-to-treat asthma?

    Science.gov (United States)

    Fricker, Michael; Heaney, Liam G; Upham, John W

    2017-04-01

    Biomarkers may be a key foundation for the precision medicine of the future. In this article, we review current knowledge regarding biomarkers in difficult-to-treat asthma and their ability to guide the use of both conventional asthma therapies and novel (targeted) therapies. Biomarkers (as measured by tests including prednisolone and cortisol assays and the fractional exhaled nitric oxide (NO) suppression test) show promise in the assessment and management of non-adherence to inhaled and oral corticosteroids. Multiple markers of type 2 inflammation have been developed, including eosinophils in sputum and blood, exhaled NO, serum IgE and periostin. Although these show potential in guiding the selection of novel interventions for refractory type 2 inflammation in asthma, and in determining if the desired response is being achieved, it is becoming clear that different biomarkers reflect distinct components of the complex type 2 inflammatory pathways. Less progress has been made in identifying biomarkers for use in difficult-to-treat asthma that is not associated with type 2 inflammation. The future is likely to see further biomarker discovery, direct measurements of individual cytokines rather than surrogates of their activity and the increasing use of biomarkers in combination. If the promise of biomarkers is to be fulfilled, they will need to provide useful information that aids clinical decision-making, rather than being 'just another test' for clinicians to order.

  20. 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

  1. 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.

  2. 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...

  3. 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.

  4. 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 48...

  5. Automating the Media Center.

    Science.gov (United States)

    Holloway, Mary A.

    1988-01-01

    Discusses the need to develop more efficient information retrieval skills by the use of new technology. Lists four stages used in automating the media center. Describes North Carolina's pilot programs. Proposes benefits and looks at the media center's future. (MVL)

  6. Towards Improved Biomarker Research

    DEFF Research Database (Denmark)

    Kjeldahl, Karin

    This thesis takes a look at the data analytical challenges associated with the search for biomarkers in large-scale biological data such as transcriptomics, proteomics and metabolomics data. These studies aim to identify genes, proteins or metabolites which can be associated with e.g. a diet, dis...... is used both for regression and classification purposes. This method has proven its strong worth in the multivariate data analysis throughout an enormous range of applications; a very classic data type is near infrared (NIR) data, but many similar data types have also be very successful...

  7. 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.

  8. ACCOUNTING AUTOMATIONS RISKS

    OpenAIRE

    Муравський, В. В.; Хома, Н. Г.

    2015-01-01

    Accountant accepts active voice in organization of the automated account in the conditions of the informative systems introduction in enterprise activity. Effective accounting automation needs identification and warning of organizational risks. Authors researched, classified and generalized the risks of introduction of the informative accounting systems. The ways of liquidation of the organizational risks sources andminimization of their consequences are gives. The method of the effective con...

  9. 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.

  10. Automation of Diagrammatic Reasoning

    OpenAIRE

    Jamnik, Mateja; Bundy, Alan; Green, Ian

    1997-01-01

    Theorems in automated theorem proving are usually proved by logical formal proofs. However, there is a subset of problems which humans can prove in a different way by the use of geometric operations on diagrams, so called diagrammatic proofs. Insight is more clearly perceived in these than in the corresponding algebraic proofs: they capture an intuitive notion of truthfulness that humans find easy to see and understand. We are identifying and automating this diagrammatic reasoning on mathemat...

  11. 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.

  12. Marketing automation supporting sales

    OpenAIRE

    Sandell, Niko

    2016-01-01

    The past couple of decades has been a time of major changes in marketing. Digitalization has become a permanent part of marketing and at the same time enabled efficient collection of data. Personalization and customization of content are playing a crucial role in marketing when new customers are acquired. This has also created a need for automation to facilitate the distribution of targeted content. As a result of successful marketing automation more information of the customers is gathered ...

  13. Elements of EAF automation processes

    Science.gov (United States)

    Ioana, A.; Constantin, N.; Dragna, E. C.

    2017-01-01

    Our article presents elements of Electric Arc Furnace (EAF) automation. So, we present and analyze detailed two automation schemes: the scheme of electrical EAF automation system; the scheme of thermic EAF automation system. The application results of these scheme of automation consists in: the sensitive reduction of specific consummation of electrical energy of Electric Arc Furnace, increasing the productivity of Electric Arc Furnace, increase the quality of the developed steel, increasing the durability of the building elements of Electric Arc Furnace.

  14. C. elegans in high-throughput drug discovery

    OpenAIRE

    O’Reilly, Linda P.; Cliff J Luke; Perlmutter, David H.; Silverman, Gary A.; Pak, Stephen C.

    2013-01-01

    C. elegans has proven to be a useful model organism for investigating molecular and cellular aspects of numerous human diseases. More recently, investigators have explored the use of this organism as a tool for drug discovery. Although earlier drug screens were labor-intensive and low in throughput, recent advances in high-throughput liquid workflows, imaging platforms and data analysis software have made C. elegans a viable option for automated high-throughput drug screens. This review will ...

  15. 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

  16. Which biomarkers reveal neonatal sepsis?

    Directory of Open Access Journals (Sweden)

    Kun Wang

    Full Text Available We address the identification of optimal biomarkers for the rapid diagnosis of neonatal sepsis. We employ both canonical correlation analysis (CCA and sparse support vector machine (SSVM classifiers to select the best subset of biomarkers from a large hematological data set collected from infants with suspected sepsis from Yale-New Haven Hospital's Neonatal Intensive Care Unit (NICU. CCA is used to select sets of biomarkers of increasing size that are most highly correlated with infection. The effectiveness of these biomarkers is then validated by constructing a sparse support vector machine diagnostic classifier. We find that the following set of five biomarkers capture the essential diagnostic information (in order of importance: Bands, Platelets, neutrophil CD64, White Blood Cells, and Segs. Further, the diagnostic performance of the optimal set of biomarkers is significantly higher than that of isolated individual biomarkers. These results suggest an enhanced sepsis scoring system for neonatal sepsis that includes these five biomarkers. We demonstrate the robustness of our analysis by comparing CCA with the Forward Selection method and SSVM with LASSO Logistic Regression.

  17. Epigenetic biomarkers in liver cancer.

    Science.gov (United States)

    Banaudha, Krishna K; Verma, Mukesh

    2015-01-01

    Liver cancer (hepatocellular carcinoma or HCC) is a major cancer worldwide. Research in this field is needed to identify biomarkers that can be used for early detection of the disease as well as new approaches to its treatment. Epigenetic biomarkers provide an opportunity to understand liver cancer etiology and evaluate novel epigenetic inhibitors for treatment. Traditionally, liver cirrhosis, proteomic biomarkers, and the presence of hepatitis viruses have been used for the detection and diagnosis of liver cancer. Promising results from microRNA (miRNA) profiling and hypermethylation of selected genes have raised hopes of identifying new biomarkers. Some of these epigenetic biomarkers may be useful in risk assessment and for screening populations to identify who is likely to develop cancer. Challenges and opportunities in the field are discussed in this chapter.

  18. Multiplexed cancer biomarker detection using chip-integrated silicon photonic sensor arrays.

    Science.gov (United States)

    Washburn, Adam L; Shia, Winnie W; Lenkeit, Kimberly A; Lee, So-Hyun; Bailey, Ryan C

    2016-09-21

    The analysis of disease-specific biomarker panels holds promise for the early detection of a range of diseases, including cancer. Blood-based biomarkers, in particular, are attractive targets for minimally-invasive disease diagnosis. Specifically, a panel of organ-specific biomarkers could find utility as a general disease surveillance tool enabling earlier detection or prognostic monitoring. Using arrays of chip-integrated silicon photonic sensors, we describe the simultaneous detection of eight cancer biomarkers in serum in a relatively rapid (1 hour) and fully automated antibody-based sandwich assay. Biomarkers were chosen for their applicability to a range of organ-specific cancers, including disease of the pancreas, liver, ovary, breast, lung, colorectum, and prostate. Importantly, we demonstrate that selected patient samples reveal biomarker "fingerprints" that may be useful for a personalized cancer diagnosis. More generally, we show that the silicon photonic technology is capable of measuring multiplexed panels of protein biomarkers that may have broad utility in clinical diagnostics.

  19. Definitions and validation criteria for biomarkers and surrogate endpoints: development and testing of a quantitative hierarchical levels of evidence schema

    DEFF Research Database (Denmark)

    Lassere, Marissa N; Johnson, Kent R; Boers, Maarten

    2007-01-01

    of the National Institutes of Health definitions of biomarker, surrogate endpoint, and clinical endpoint was useful. CONCLUSION: Further development and application of this schema provides incentives and guidance for effective biomarker and surrogate endpoint research, and more efficient drug discovery...... endpoints, and leading indicators, a quantitative surrogate validation schema was developed and subsequently evaluated at a stakeholder workshop. RESULTS: The search identified several classification schema and definitions. Components of these were incorporated into a new quantitative surrogate validation...

  20. AUTOMATED DETECTION OF STRUCTURAL ALERTS (CHEMICAL FRAGMENTS IN (ECOTOXICOLOGY

    Directory of Open Access Journals (Sweden)

    Alban Lepailleur

    2013-02-01

    Full Text Available This mini-review describes the evolution of different algorithms dedicated to the automated discovery of chemical fragments associated to (ecotoxicological endpoints. These structural alerts correspond to one of the most interesting approach of in silico toxicology due to their direct link with specific toxicological mechanisms. A number of expert systems are already available but, since the first work in this field which considered a binomial distribution of chemical fragments between two datasets, new data miners were developed and applied with success in chemoinformatics. The frequency of a chemical fragment in a dataset is often at the core of the process for the definition of its toxicological relevance. However, recent progresses in data mining provide new insights into the automated discovery of new rules. Particularly, this review highlights the notion of Emerging Patterns that can capture contrasts between classes of data.

  1. Translational paradigms in pharmacology and drug discovery.

    Science.gov (United States)

    Mullane, Kevin; Winquist, Raymond J; Williams, Michael

    2014-01-01

    The translational sciences represent the core element in enabling and utilizing the output from the biomedical sciences and to improving drug discovery metrics by reducing the attrition rate as compounds move from preclinical research to clinical proof of concept. Key to understanding the basis of disease causality and to developing therapeutics is an ability to accurately diagnose the disease and to identify and develop safe and effective therapeutics for its treatment. The former requires validated biomarkers and the latter, qualified targets. Progress has been hampered by semantic issues, specifically those that define the end product, and by scientific issues that include data reliability, an overt reductionistic cultural focus and a lack of hierarchically integrated data gathering and systematic analysis. A necessary framework for these activities is represented by the discipline of pharmacology, efforts and training in which require recognition and revitalization.

  2. [Iron deficiency in elderly patients: use of biomarkers].

    Science.gov (United States)

    Le Petitcorps, Hélène; Monti, Alexandra; Pautas, Éric

    2015-01-01

    Iron deficiency, due to blood loss or malabsorption, is commonly observed in geriatric practice. In elderly people, association of inflammatory diseases to iron loss makes diagnosis of absolute iron deficiency sometimes difficult. In case of inflammation, the interpretation of usual biomarkers of iron deficiency (serum ferritin, transferrin saturation, serum iron) may be difficult. The recent discovery of the role of hepcidine in the iron homeostasis, in physiological and pathological situation, contributes to better understanding of the iron regulation. The aim of this short paper is to underline some specificities of elderly iron physiology, to explain hepcidine's role in physiological and pathological situations and to propose a diagnostic approach for a better interpretation of usual biomarkers, in order to differentiate absolute iron deficiency and functional iron deficiency.

  3. 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.

  4. Current status and future prospects for enabling chemistry technology in the drug discovery process

    Science.gov (United States)

    Djuric, Stevan W.; Hutchins, Charles W.; Talaty, Nari N.

    2016-01-01

    This review covers recent advances in the implementation of enabling chemistry technologies into the drug discovery process. Areas covered include parallel synthesis chemistry, high-throughput experimentation, automated synthesis and purification methods, flow chemistry methodology including photochemistry, electrochemistry, and the handling of “dangerous” reagents. Also featured are advances in the “computer-assisted drug design” area and the expanding application of novel mass spectrometry-based techniques to a wide range of drug discovery activities. PMID:27781094

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

    OpenAIRE

    Manly, Charles J.

    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...

  6. Biomarkers for lymphoma

    Science.gov (United States)

    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.

  7. Molecular biomarkers of neurodegeneration.

    Science.gov (United States)

    Höglund, Kina; Salter, Hugh

    2013-11-01

    Neuronal dysfunction and degeneration are central events of a number of major diseases with significant unmet need. Neuronal dysfunction may not necessarily be the result of cell death, but may also be due to synaptic damage leading to impaired neuronal cell signaling or long-term potentiation. Once degeneration occurs, it is unclear whether axonal or synaptic loss comes first or whether this precedes neuronal cell death. In this review we summarize the pathophysiology of four major neurodegenerative diseases; Alzheimer's disease, Parkinson's disease, multiple sclerosis and amyotrophic lateral sclerosis (Lou Gehrig's disease) For each of these diseases, we describe how biochemical biomarkers are currently understood in relation to the pathophysiology and in terms of neuronal biology, and we discuss the clinical and diagnostic utility of these potential tools, which are at present limited. We discuss how markers may be used to drive drug development and clinical practice.

  8. Inflammatory biomarkers for AMD.

    Science.gov (United States)

    Stanton, Chloe M; Wright, Alan F

    2014-01-01

    Age-related macular degeneration (AMD) is the leading cause of blindness worldwide, affecting an estimated 50 million individuals aged over 65 years.Environmental and genetic risk-factors implicate chronic inflammation in the etiology of AMD, contributing to the formation of drusen, retinal pigment epithelial cell dysfunction and photoreceptor cell death. Consistent with a role for chronic inflammation in AMD pathogenesis, several inflammatory mediators, including complement components, chemokines and cytokines, are elevated at both the local and systemic levels in AMD patients. These mediators have diverse roles in the alternative complement pathway, including recruitment of inflammatory cells, activation of the inflammasome, promotion of neovascularisation and in the resolution of inflammation. The utility of inflammatory biomarkers in assessing individual risk and progression of the disease is controversial. However, understanding the role of these inflammatory mediators in AMD onset, progression and response to treatment may increase our knowledge of disease pathogenesis and provide novel therapeutic options in the future.

  9. Advances in Nuclear Magnetic Resonance for Drug Discovery

    Science.gov (United States)

    Powers, Robert

    2010-01-01

    Background Drug discovery is a complex and unpredictable endeavor with a high failure rate. Current trends in the pharmaceutical industry have exasperated these challenges and are contributing to the dramatic decline in productivity observed over the last decade. The industrialization of science by forcing the drug discovery process to adhere to assembly-line protocols is imposing unnecessary restrictions, such as short project time-lines. Recent advances in nuclear magnetic resonance are responding to these self-imposed limitations and are providing opportunities to increase the success rate of drug discovery. Objective/Method A review of recent advancements in NMR technology that have the potential of significantly impacting and benefiting the drug discovery process will be presented. These include fast NMR data collection protocols and high-throughput protein structure determination, rapid protein-ligand co-structure determination, lead discovery using fragment-based NMR affinity screens, NMR metabolomics to monitor in vivo efficacy and toxicity for lead compounds, and the identification of new therapeutic targets through the functional annotation of proteins by FAST-NMR. Conclusion NMR is a critical component of the drug discovery process, where the versatility of the technique enables it to continually expand and evolve its role. NMR is expected to maintain this growth over the next decade with advancements in automation, speed of structure calculation, in-cell imaging techniques, and the expansion of NMR amenable targets. PMID:20333269

  10. Implementation of an Automated High-Throughput Plasmid DNA Production Pipeline.

    Science.gov (United States)

    Billeci, Karen; Suh, Christopher; Di Ioia, Tina; Singh, Lovejit; Abraham, Ryan; Baldwin, Anne; Monteclaro, Stephen

    2016-12-01

    Biologics sample management facilities are often responsible for a diversity of large-molecule reagent types, such as DNA, RNAi, and protein libraries. Historically, the management of large molecules was dispersed into multiple laboratories. As methodologies to support pathway discovery, antibody discovery, and protein production have become high throughput, the implementation of automation and centralized inventory management tools has become important. To this end, to improve sample tracking, throughput, and accuracy, we have implemented a module-based automation system integrated into inventory management software using multiple platforms (Hamilton, Hudson, Dynamic Devices, and Brooks). Here we describe the implementation of these systems with a focus on high-throughput plasmid DNA production management.

  11. Semi-automated software service integration in virtual organisations

    Science.gov (United States)

    Afsarmanesh, Hamideh; Sargolzaei, Mahdi; Shadi, Mahdieh

    2015-08-01

    To enhance their business opportunities, organisations involved in many service industries are increasingly active in pursuit of both online provision of their business services (BSs) and collaborating with others. Collaborative Networks (CNs) in service industry sector, however, face many challenges related to sharing and integration of their collection of provided BSs and their corresponding software services. Therefore, the topic of service interoperability for which this article introduces a framework is gaining momentum in research for supporting CNs. It contributes to generation of formal machine readable specification for business processes, aimed at providing their unambiguous definitions, as needed for developing their equivalent software services. The framework provides a model and implementation architecture for discovery and composition of shared services, to support the semi-automated development of integrated value-added services. In support of service discovery, a main contribution of this research is the formal representation of services' behaviour and applying desired service behaviour specified by users for automated matchmaking with other existing services. Furthermore, to support service integration, mechanisms are developed for automated selection of the most suitable service(s) according to a number of service quality aspects. Two scenario cases are presented, which exemplify several specific features related to service discovery and service integration aspects.

  12. Materials Testing and Automation

    Science.gov (United States)

    Cooper, Wayne D.; Zweigoron, Ronald B.

    1980-07-01

    The advent of automation in materials testing has been in large part responsible for recent radical changes in the materials testing field: Tests virtually impossible to perform without a computer have become more straightforward to conduct. In addition, standardized tests may be performed with enhanced efficiency and repeatability. A typical automated system is described in terms of its primary subsystems — an analog station, a digital computer, and a processor interface. The processor interface links the analog functions with the digital computer; it includes data acquisition, command function generation, and test control functions. Features of automated testing are described with emphasis on calculated variable control, control of a variable that is computed by the processor and cannot be read directly from a transducer. Three calculated variable tests are described: a yield surface probe test, a thermomechanical fatigue test, and a constant-stress-intensity range crack-growth test. Future developments are discussed.

  13. Automation of Taxiing

    Directory of Open Access Journals (Sweden)

    Jaroslav Bursík

    2017-01-01

    Full Text Available The article focuses on the possibility of automation of taxiing, which is the part of a flight, which, under adverse weather conditions, greatly reduces the operational usability of an airport, and is the only part of a flight that has not been affected by automation, yet. Taxiing is currently handled manually by the pilot, who controls the airplane based on information from visual perception. The article primarily deals with possible ways of obtaining navigational information, and its automatic transfer to the controls. Analyzed wand assessed were currently available technologies such as computer vision, Light Detection and Ranging and Global Navigation Satellite System, which are useful for navigation and their general implementation into an airplane was designed. Obstacles to the implementation were identified, too. The result is a proposed combination of systems along with their installation into airplane’s systems so that it is possible to use the automated taxiing.

  14. Automating the CMS DAQ

    CERN Document Server

    Bauer, Gerry; Behrens, Ulf; Branson, James; Chaze, Olivier; Cittolin, Sergio; Coarasa Perez, Jose Antonio; Darlea, Georgiana Lavinia; Deldicque, Christian; Dobson, Marc; Dupont, Aymeric; Erhan, Samim; Gigi, Dominique; Glege, Frank; Gomez Ceballos, Guillelmo; Gomez-Reino Garrido, Robert; Hartl, Christian; Hegeman, Jeroen Guido; Holzner, Andre Georg; Masetti, Lorenzo; Meijers, Franciscus; Meschi, Emilio; Mommsen, Remigius; Morovic, Srecko; Nunez Barranco Fernandez, Carlos; O'Dell, Vivian; Orsini, Luciano; Ozga, Wojciech Andrzej; Paus, Christoph Maria Ernst; Petrucci, Andrea; Pieri, Marco; Racz, Attila; Raginel, Olivier; Sakulin, Hannes; Sani, Matteo; Schwick, Christoph; Spataru, Andrei Cristian; Stieger, Benjamin Bastian; Sumorok, Konstanty; Veverka, Jan; Wakefield, Christopher Colin; Zejdl, Petr

    2014-01-01

    We present the automation mechanisms that have been added to the Data Acquisition and Run Control systems of the Compact Muon Solenoid (CMS) experiment during Run 1 of the LHC, ranging from the automation of routine tasks to automatic error recovery and context-sensitive guidance to the operator. These mechanisms helped CMS to maintain a data taking efficiency above 90\\% and to even improve it to 95\\% towards the end of Run 1, despite an increase in the occurrence of single-event upsets in sub-detector electronics at high LHC luminosity.

  15. Automating the CMS DAQ

    Energy Technology Data Exchange (ETDEWEB)

    Bauer, G.; et al.

    2014-01-01

    We present the automation mechanisms that have been added to the Data Acquisition and Run Control systems of the Compact Muon Solenoid (CMS) experiment during Run 1 of the LHC, ranging from the automation of routine tasks to automatic error recovery and context-sensitive guidance to the operator. These mechanisms helped CMS to maintain a data taking efficiency above 90% and to even improve it to 95% towards the end of Run 1, despite an increase in the occurrence of single-event upsets in sub-detector electronics at high LHC luminosity.

  16. Development of Parkinson's disease biomarkers.

    Science.gov (United States)

    Prakash, Kumar M; Tan, Eng-King

    2010-12-01

    Parkinson's disease (PD) is the most common neurodegenerative movement disorder, affecting over 6 million people worldwide. It is anticipated that the number of affected individuals may increase significantly in the most populous nations by 2030. During the past 20 years, much progress has been made in identifying and assessing various potential clinical, biochemical, imaging and genetic biomarkers for PD. Despite the wealth of information, development of a validated biomarker for PD is still ongoing. It is hoped that reliable and well-validated biomarkers will provide critical clues to assist in the diagnosis and management of Parkinson's disease patients in the near future.

  17. Genetic and Epigenetic Biomarkers for Recurrent Prostate Cancer After Radiotherapy

    Science.gov (United States)

    2015-07-01

    Award Number: W81XWH-12-1-0113 TITLE: Genetic and epigenetic biomarkers for recurrent prostate cancer after radiotherapy PRINCIPAL INVESTIGATOR...Beadchip microarray, high density beadchip, for this study. This array includes 485,577 CpG sites and covers CpGs in 99% of genes and 96% of CpG ...differentially methylated CpG sites in 17 genes between recurrent and non-recurrent tumor tissues, with a false discovery rate (FDR) [12] q-value less than

  18. Ayurvedic drug discovery.

    Science.gov (United States)

    Balachandran, Premalatha; Govindarajan, Rajgopal

    2007-12-01

    Ayurveda is a major traditional system of Indian medicine that is still being successfully used in many countries. Recapitulation and adaptation of the older science to modern drug discovery processes can bring renewed interest to the pharmaceutical world and offer unique therapeutic solutions for a wide range of human disorders. Eventhough time-tested evidences vouch immense therapeutic benefits for ayurvedic herbs and formulations, several important issues are required to be resolved for successful implementation of ayurvedic principles to present drug discovery methodologies. Additionally, clinical examination in the extent of efficacy, safety and drug interactions of newly developed ayurvedic drugs and formulations are required to be carefully evaluated. Ayurvedic experts suggest a reverse-pharmacology approach focusing on the potential targets for which ayurvedic herbs and herbal products could bring tremendous leads to ayurvedic drug discovery. Although several novel leads and drug molecules have already been discovered from ayurvedic medicinal herbs, further scientific explorations in this arena along with customization of present technologies to ayurvedic drug manufacturing principles would greatly facilitate a standardized ayurvedic drug discovery.

  19. 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 a...

  20. The Scholarship of Discovery.

    Science.gov (United States)

    Dobos, Jean

    2000-01-01

    Contributes to a special issue on how the reconsideration of what scholarship is affects the way in which scholarship is assessed. Examines traditional criteria for evaluating faculty research. Identifies activities pertinent to the scholarship of discovery, and the assessment practices in the field of communication as well as in general use. (SR)

  1. Discovery Education: A Definition.

    Science.gov (United States)

    Wilson, Harold C.

    2002-01-01

    Discovery Education is based on the writings of Henry David Thoreau, an early champion of experiential learning. After 2 months of preparation, 10th-grade students spent 4 days in the wilderness reenacting a piece of history, such as the Lewis and Clark Expedition. The interdisciplinary approach always included journal-writing. Students gained…

  2. Archaeological Discoveries in Liaoning

    Institute of Scientific and Technical Information of China (English)

    1996-01-01

    LIAONING Province, in northeastern China, has been inhabited by many ethnic groups since ancient times. It is one of the sites of China’s earliest civilization. Since the 1950s many archaeological discoveries from periods beginning with the Paleolithic of 200,000 years ago, and through all the following historic periods, have been made in the province.

  3. Discovery through Gossip

    CERN Document Server

    Haeupler, Bernhard; Peleg, David; Rajaraman, Rajmohan; Sun, Zhifeng

    2012-01-01

    We study randomized gossip-based processes in dynamic networks that are motivated by discovery processes in large-scale distributed networks like peer-to-peer or social networks. A well-studied problem in peer-to-peer networks is the resource discovery problem. There, the goal for nodes (hosts with IP addresses) is to discover the IP addresses of all other hosts. In social networks, nodes (people) discover new nodes through exchanging contacts with their neighbors (friends). In both cases the discovery of new nodes changes the underlying network - new edges are added to the network - and the process continues in the changed network. Rigorously analyzing such dynamic (stochastic) processes with a continuously self-changing topology remains a challenging problem with obvious applications. This paper studies and analyzes two natural gossip-based discovery processes. In the push process, each node repeatedly chooses two random neighbors and puts them in contact (i.e., "pushes" their mutual information to each oth...

  4. Altering user' acceptance of automation through prior automation exposure.

    Science.gov (United States)

    Bekier, Marek; Molesworth, Brett R C

    2016-08-22

    Air navigation service providers worldwide see increased use of automation as one solution to overcome the capacity constraints imbedded in the present air traffic management (ATM) system. However, increased use of automation within any system is dependent on user acceptance. The present research sought to determine if the point at which an individual is no longer willing to accept or cooperate with automation can be manipulated. Forty participants underwent training on a computer-based air traffic control programme, followed by two ATM exercises (order counterbalanced), one with and one without the aid of automation. Results revealed after exposure to a task with automation assistance, user acceptance of high(er) levels of automation ('tipping point') decreased; suggesting it is indeed possible to alter automation acceptance. Practitioner Summary: This paper investigates whether the point at which a user of automation rejects automation (i.e. 'tipping point') is constant or can be manipulated. The results revealed after exposure to a task with automation assistance, user acceptance of high(er) levels of automation decreased; suggesting it is possible to alter automation acceptance.

  5. 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.

  6. Improving tuberculosis diagnostics with biomarkers

    Directory of Open Access Journals (Sweden)

    Shu CC

    2015-05-01

    Full Text Available Chin-Chung Shu,1,2 Jann-Yuan Wang,2 Li-Na Lee,2,3 Chong-Jen Yu,2 Kwen-Tay Luh3 1Department of Traumatology, 2Department of Internal Medicine, 3Department of Laboratory Medicine, National Taiwan University Hospital, Taipei, Taiwan Abstract: Although many laboratory methods have been developed to expedite the diagnosis of active tuberculosis (TB and Mycobacterium tuberculosis (Mtb infection, delays in diagnosis remain a major problem in clinical practice. Biomarkers may contribute favorably or unfavorably to TB diagnosis in a clinical suspect TB case with inconclusive diagnostic findings. A good understanding of the effectiveness and practical limitations of these biomarkers is important to improve diagnosis. This review summarizes currently used biomarkers, mainly as validation, and focuses on latent TB infection, active pulmonary TB, and tuberculous pleural effusion. Keywords: tuberculosis, biomarker, diagnosis, latent tuberculosis infection, pleural effusion 

  7. 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.

  8. Procalcitonine als biomarker voor infecties

    NARCIS (Netherlands)

    de Jonge, J C; de Lange, D W; Bij de Vaate, E A; van Leeuwen, H; Arends, J E

    2016-01-01

    - Inappropriate use of antibiotics in patients without bacterial infection contributes significantly to worldwide antibiotic resistance.- The goal of this review is to summarise evidence from randomised trials investigating the value of the biomarker procalcitonin (PCT) in patients with symptoms of

  9. 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....

  10. Microcontroller for automation application

    Science.gov (United States)

    Cooper, H. W.

    1975-01-01

    The description of a microcontroller currently being developed for automation application was given. It is basically an 8-bit microcomputer with a 40K byte random access memory/read only memory, and can control a maximum of 12 devices through standard 15-line interface ports.

  11. Automated Composite Column Wrapping

    OpenAIRE

    ECT Team, Purdue

    2007-01-01

    The Automated Composite Column Wrapping is performed by a patented machine known as Robo-Wrapper. Currently there are three versions of the machine available for bridge retrofit work depending on the size of the columns being wrapped. Composite column retrofit jacket systems can be structurally just as effective as conventional steel jacketing in improving the seismic response characteristics of substandard reinforced concrete columns.

  12. Automated Web Applications Testing

    Directory of Open Access Journals (Sweden)

    Alexandru Dan CĂPRIŢĂ

    2009-01-01

    Full Text Available Unit tests are a vital part of several software development practicesand processes such as Test-First Programming, Extreme Programming andTest-Driven Development. This article shortly presents the software quality andtesting concepts as well as an introduction to an automated unit testingframework for PHP web based applications.

  13. Automated Student Model Improvement

    Science.gov (United States)

    Koedinger, Kenneth R.; McLaughlin, Elizabeth A.; Stamper, John C.

    2012-01-01

    Student modeling plays a critical role in developing and improving instruction and instructional technologies. We present a technique for automated improvement of student models that leverages the DataShop repository, crowd sourcing, and a version of the Learning Factors Analysis algorithm. We demonstrate this method on eleven educational…

  14. Automated Accounting. Instructor Guide.

    Science.gov (United States)

    Moses, Duane R.

    This curriculum guide was developed to assist business instructors using Dac Easy Accounting College Edition Version 2.0 software in their accounting programs. The module consists of four units containing assignment sheets and job sheets designed to enable students to master competencies identified in the area of automated accounting. The first…

  15. ERGONOMICS AND PROCESS AUTOMATION

    OpenAIRE

    Carrión Muñoz, Rolando; Docente de la FII - UNMSM

    2014-01-01

    The article shows the role that ergonomics in automation of processes, and the importance for Industrial Engineering.  El artículo nos muestra el papel que tiene la ergonomía en la automatización de los procesos, y la importancia para la Ingeniería Industrial.

  16. Mechatronic Design Automation

    DEFF Research Database (Denmark)

    Fan, Zhun

    successfully design analogue filters, vibration absorbers, micro-electro-mechanical systems, and vehicle suspension systems, all in an automatic or semi-automatic way. It also investigates the very important issue of co-designing plant-structures and dynamic controllers in automated design of Mechatronic...

  17. 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...

  18. 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.

  19. 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.

  20. Biomarkers in Prostate Cancer Epidemiology

    OpenAIRE

    Mudit Verma; Mukesh Verma; Payal Patel

    2011-01-01

    Understanding the etiology of a disease such as prostate cancer may help in identifying populations at high risk, timely intervention of the disease, and proper treatment. Biomarkers, along with exposure history and clinical data, are useful tools to achieve these goals. Individual risk and population incidence of prostate cancer result from the intervention of genetic susceptibility and exposure. Biochemical, epigenetic, genetic, and imaging biomarkers are used to identify people at high ris...

  1. Biomarkers of satiation and satiety.

    Science.gov (United States)

    de Graaf, Cees; Blom, Wendy A M; Smeets, Paul A M; Stafleu, Annette; Hendriks, Henk F J

    2004-06-01

    This review's objective is to give a critical summary of studies that focused on physiologic measures relating to subjectively rated appetite, actual food intake, or both. Biomarkers of satiation and satiety may be used as a tool for assessing the satiating efficiency of foods and for understanding the regulation of food intake and energy balance. We made a distinction between biomarkers of satiation or meal termination and those of meal initiation related to satiety and between markers in the brain [central nervous system (CNS)] and those related to signals from the periphery to the CNS. Various studies showed that physicochemical measures related to stomach distension and blood concentrations of cholecystokinin and glucagon-like peptide 1 are peripheral biomarkers associated with meal termination. CNS biomarkers related to meal termination identified by functional magnetic resonance imaging and positron emission tomography are indicators of neural activity related to sensory-specific satiety. These measures cannot yet serve as a tool for assessing the satiating effect of foods, because they are not yet feasible. CNS biomarkers related to satiety are not yet specific enough to serve as biomarkers, although they can distinguish between extreme hunger and fullness. Three currently available biomarkers for satiety are decreases in blood glucose in the short term (2-4 d) negative energy balance; and ghrelin concentrations, which have been implicated in both short-term and long-term energy balance. The next challenge in this research area is to identify food ingredients that have an effect on biomarkers of satiation, satiety, or both. These ingredients may help consumers to maintain their energy intake at a level consistent with a healthy body weight.

  2. 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

  3. 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.

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

    Science.gov (United States)

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

    2016-06-02

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

  5. Atlas of Astronomical Discoveries

    CERN Document Server

    Schilling, Govert

    2011-01-01

    Four hundred years ago in Middelburg, in the Netherlands, the telescope was invented. The invention unleashed a revolution in the exploration of the universe. Galileo Galilei discovered mountains on the Moon, spots on the Sun, and moons around Jupiter. Christiaan Huygens saw details on Mars and rings around Saturn. William Herschel discovered a new planet and mapped binary stars and nebulae. Other astronomers determined the distances to stars, unraveled the structure of the Milky Way, and discovered the expansion of the universe. And, as telescopes became bigger and more powerful, astronomers delved deeper into the mysteries of the cosmos. In his Atlas of Astronomical Discoveries, astronomy journalist Govert Schilling tells the story of 400 years of telescopic astronomy. He looks at the 100 most important discoveries since the invention of the telescope. In his direct and accessible style, the author takes his readers on an exciting journey encompassing the highlights of four centuries of astronomy. Spectacul...

  6. Chronicles in drug discovery.

    Science.gov (United States)

    Davies, Shelley L; Moral, Maria Angels; Bozzo, Jordi

    2007-03-01

    Chronicles in Drug Discovery features special interest reports on advances in drug discovery. This month we highlight agents that target and deplete immunosuppressive regulatory T cells, which are produced by tumor cells to hinder innate immunity against, or chemotherapies targeting, tumor-associated antigens. Antiviral treatments for respiratory syncytial virus, a severe and prevalent infection in children, are limited due to their side effect profiles and cost. New strategies currently under clinical development include monoclonal antibodies, siRNAs, vaccines and oral small molecule inhibitors. Recent therapeutic lines for Huntington's disease include gene therapies that target the mutated human huntingtin gene or deliver neuroprotective growth factors and cellular transplantation in apoptotic regions of the brain. Finally, we highlight the antiinflammatory and antinociceptive properties of new compounds targeting the somatostatin receptor subtype sst4, which warrant further study for their potential application as clinical analgesics.

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

    DEFF Research Database (Denmark)

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

    2011-01-01

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

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

    Science.gov (United States)

    Khan, Masood U; Bowsher, Ronald R; Cameron, Mark; Devanarayan, Viswanath; Keller, Steve; King, Lindsay; Lee, Jean; Morimoto, Alyssa; Rhyne, Paul; Stephen, Laurie; Wu, Yuling; Wyant, Timothy; Lachno, D Richard

    2015-01-01

    Increasingly, commercial immunoassay kits are used to support drug discovery and development. Longitudinally consistent kit performance is crucial, but the degree to which kits and reagents are characterized by manufacturers is not standardized, nor are the approaches by users to adapt them and evaluate their performance through validation prior to use. These factors can negatively impact data quality. This paper offers a systematic approach to assessment, method adaptation and validation of commercial immunoassay kits for quantification of biomarkers in drug development, expanding upon previous publications and guidance. These recommendations aim to standardize and harmonize user practices, contributing to reliable biomarker data from commercial immunoassays, thus, enabling properly informed decisions during drug development.

  9. 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.

  10. The discovery of quarks.

    Science.gov (United States)

    Riordan, M

    1992-05-29

    Quarks are widely recognized today as being among the elementary particles of which matter is composed. The key evidence for their existence came from a series of inelastic electron-nucleon scattering experiments conducted between 1967 and 1973 at the Stanford Linear Accelerator Center. Other theoretical and experimental advances of the 1970s confirmed this discovery, leading to the present standard model of elementary particle physics.

  11. Mapping the Stacks: Sustainability and User Experience of Animated Maps in Library Discovery Interfaces

    Science.gov (United States)

    McMillin, Bill; Gibson, Sally; MacDonald, Jean

    2016-01-01

    Animated maps of the library stacks were integrated into the catalog interface at Pratt Institute and into the EBSCO Discovery Service interface at Illinois State University. The mapping feature was developed for optimal automation of the update process to enable a range of library personnel to update maps and call-number ranges. The development…

  12. Automation in high-content flow cytometry screening.

    Science.gov (United States)

    Naumann, U; Wand, M P

    2009-09-01

    High-content flow cytometric screening (FC-HCS) is a 21st Century technology that combines robotic fluid handling, flow cytometric instrumentation, and bioinformatics software, so that relatively large numbers of flow cytometric samples can be processed and analysed in a short period of time. We revisit a recent application of FC-HCS to the problem of cellular signature definition for acute graft-versus-host-disease. Our focus is on automation of the data processing steps using recent advances in statistical methodology. We demonstrate that effective results, on par with those obtained via manual processing, can be achieved using our automatic techniques. Such automation of FC-HCS has the potential to drastically improve diagnosis and biomarker identification.

  13. Core-shell hydrogel particles harvest, concentrate and preserve labile low abundance biomarkers.

    Directory of Open Access Journals (Sweden)

    Caterina Longo

    Full Text Available BACKGROUND: The blood proteome is thought to represent a rich source of biomarkers for early stage disease detection. Nevertheless, three major challenges have hindered biomarker discovery: a candidate biomarkers exist at extremely low concentrations in blood; b high abundance resident proteins such as albumin mask the rare biomarkers; c biomarkers are rapidly degraded by endogenous and exogenous proteinases. METHODOLOGY AND PRINCIPAL FINDINGS: Hydrogel nanoparticles created with a N-isopropylacrylamide based core (365 nm-shell (167 nm and functionalized with a charged based bait (acrylic acid were studied as a technology for addressing all these biomarker discovery problems, in one step, in solution. These harvesting core-shell nanoparticles are designed to simultaneously conduct size exclusion and affinity chromatography in solution. Platelet derived growth factor (PDGF, a clinically relevant, highly labile, and very low abundance biomarker, was chosen as a model. PDGF, spiked in human serum, was completely sequestered from its carrier protein albumin, concentrated, and fully preserved, within minutes by the particles. Particle sequestered PDGF was fully protected from exogenously added tryptic degradation. When the nanoparticles were added to a 1 mL dilute solution of PDGF at non detectable levels (less than 20 picograms per mL the concentration of the PDGF released from the polymeric matrix of the particles increased within the detection range of ELISA and mass spectrometry. Beyond PDGF, the sequestration and protection from degradation for a series of additional very low abundance and very labile cytokines were verified. CONCLUSIONS AND SIGNIFICANCE: We envision the application of harvesting core-shell nanoparticles to whole blood for concentration and immediate preservation of low abundance and labile analytes at the time of venipuncture.

  14. Early Stage Health Technology Assessment for Precision Biomarkers in Oral Health and Systems Medicine.

    Science.gov (United States)

    Steuten, Lotte M G

    2016-01-01

    Health technology assessment (HTA) is a crucial science that influences the responsible and evidence-based transition of new discoveries from laboratory to applications in the clinic and society. HTA has recently moved "upstream" so as to assess technologies from their onset at their discovery, design, or planning phase. Biomarker research is relatively recent in oral health, but growing rapidly with investments made to advance dentistry and oral health and importantly, to build effective bridges between oral health and systems medicine since what happens in oral health affects systems pathophysiology, and vice versa. This article offers a synthesis of the latest trends and approaches in early phase HTA, with a view to near future applications in oral health, systems medicine, and biomarker-guided precision medicine. In brief, this review underscores that demonstrating health outcomes of biomarkers and next-generation diagnostics is particularly challenging because they do not always influence long-term outcomes directly, but rather impact subsequent care processes. Biomarker testing costs are typically less of a barrier to uptake in practice than the biomarker's impact on longer term health outcomes. As a single biomarker or next-generation diagnostic in oral health can inform decisions about numerous downstream diagnosis-treatment combinations, early stage "upstream" HTA is crucial in prioritizing the most valuable diagnostic applications to pursue first. For the vast array of oral health biomarkers currently developed, early HTA is necessary to timely and iteratively assess their comparative effectiveness and anticipate the inevitable questions about value for money from regulators and payers.

  15. 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.

  16. A Framework for Automatic Web Service Discovery Based on Semantics and NLP Techniques

    Directory of Open Access Journals (Sweden)

    Asma Adala

    2011-01-01

    Full Text Available As a greater number of Web Services are made available today, automatic discovery is recognized as an important task. To promote the automation of service discovery, different semantic languages have been created that allow describing the functionality of services in a machine interpretable form using Semantic Web technologies. The problem is that users do not have intimate knowledge about semantic Web service languages and related toolkits. In this paper, we propose a discovery framework that enables semantic Web service discovery based on keywords written in natural language. We describe a novel approach for automatic discovery of semantic Web services which employs Natural Language Processing techniques to match a user request, expressed in natural language, with a semantic Web service description. Additionally, we present an efficient semantic matching technique to compute the semantic distance between ontological concepts.

  17. Reliability of Using Retinal Vascular Fractal Dimension as a Biomarker in the Diabetic Retinopathy Detection

    Science.gov (United States)

    Zhang, Jiong; Bekkers, Erik; Abbasi-Sureshjani, Samaneh

    2016-01-01

    The retinal fractal dimension (FD) is a measure of vasculature branching pattern complexity. FD has been considered as a potential biomarker for the detection of several diseases like diabetes and hypertension. However, conflicting findings were found in the reported literature regarding the association between this biomarker and diseases. In this paper, we examine the stability of the FD measurement with respect to (1) different vessel annotations obtained from human observers, (2) automatic segmentation methods, (3) various regions of interest, (4) accuracy of vessel segmentation methods, and (5) different imaging modalities. Our results demonstrate that the relative errors for the measurement of FD are significant and FD varies considerably according to the image quality, modality, and the technique used for measuring it. Automated and semiautomated methods for the measurement of FD are not stable enough, which makes FD a deceptive biomarker in quantitative clinical applications.

  18. 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.

  19. 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.

  20. The automation of science.

    Science.gov (United States)

    King, Ross D; Rowland, Jem; Oliver, Stephen G; Young, Michael; Aubrey, Wayne; Byrne, Emma; Liakata, Maria; Markham, Magdalena; Pir, Pinar; Soldatova, Larisa N; Sparkes, Andrew; Whelan, Kenneth E; Clare, Amanda

    2009-04-03

    The basis of science is the hypothetico-deductive method and the recording of experiments in sufficient detail to enable reproducibility. We report the development of Robot Scientist "Adam," which advances the automation of both. Adam has autonomously generated functional genomics hypotheses about the yeast Saccharomyces cerevisiae and experimentally tested these hypotheses by using laboratory automation. We have confirmed Adam's conclusions through manual experiments. To describe Adam's research, we have developed an ontology and logical language. The resulting formalization involves over 10,000 different research units in a nested treelike structure, 10 levels deep, that relates the 6.6 million biomass measurements to their logical description. This formalization describes how a machine contributed to scientific knowledge.

  1. The Automated Medical Office

    OpenAIRE

    1990-01-01

    With shock and surprise many physicians learned in the 1980s that they must change the way they do business. Competition for patients, increasing government regulation, and the rapidly escalating risk of litigation forces physicians to seek modern remedies in office management. The author describes a medical clinic that strives to be paperless using electronic innovation to solve the problems of medical practice management. A computer software program to automate information management in a c...

  2. Automation of printing machine

    OpenAIRE

    Sušil, David

    2016-01-01

    Bachelor thesis is focused on the automation of the printing machine and comparing the two types of printing machines. The first chapter deals with the history of printing, typesettings, printing techniques and various kinds of bookbinding. The second chapter describes the difference between sheet-fed printing machines and offset printing machines, the difference between two representatives of rotary machines, technological process of the products on these machines, the description of the mac...

  3. Automated Cooperative Trajectories

    Science.gov (United States)

    Hanson, Curt; Pahle, Joseph; Brown, Nelson

    2015-01-01

    This presentation is an overview of the Automated Cooperative Trajectories project. An introduction to the phenomena of wake vortices is given, along with a summary of past research into the possibility of extracting energy from the wake by flying close parallel trajectories. Challenges and barriers to adoption of civilian automatic wake surfing technology are identified. A hardware-in-the-loop simulation is described that will support future research. Finally, a roadmap for future research and technology transition is proposed.

  4. 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.

  5. Gene expression analysis in pregnant women and their infants identifies unique fetal biomarkers that circulate in maternal blood

    Science.gov (United States)

    The discovery of fetal mRNA transcripts in the maternal circulation holds great promise for noninvasive prenatal diagnosis. To identify potential fetal biomarkers, we studied whole blood and plasma gene transcripts that were common to 9 term pregnant women and their newborns but absent or reduced in...

  6. Advances in induced pluripotent stem cells, genomics, biomarkers, and antiplatelet therapy highlights of the year in JCTR 2013.

    Science.gov (United States)

    Barbato, Emanuele; Lara-Pezzi, Enrique; Stolen, Craig; Taylor, Angela; Barton, Paul J; Bartunek, Jozef; Iaizzo, Paul; Judge, Daniel P; Kirshenbaum, Lorrie; Blaxall, Burns C; Terzic, Andre; Hall, Jennifer L

    2014-07-01

    The Journal provides the clinician and scientist with the latest advances in discovery research, emerging technologies, preclinical research design and testing, and clinical trials. We highlight advances in areas of induced pluripotent stem cells, genomics, biomarkers, multimodality imaging, and antiplatelet biology and therapy. The top publications are critically discussed and presented along with anatomical reviews and FDA insight to provide context.

  7. Automation in biological crystallization.

    Science.gov (United States)

    Stewart, Patrick Shaw; Mueller-Dieckmann, Jochen

    2014-06-01

    Crystallization remains the bottleneck in the crystallographic process leading from a gene to a three-dimensional model of the encoded protein or RNA. Automation of the individual steps of a crystallization experiment, from the preparation of crystallization cocktails for initial or optimization screens to the imaging of the experiments, has been the response to address this issue. Today, large high-throughput crystallization facilities, many of them open to the general user community, are capable of setting up thousands of crystallization trials per day. It is thus possible to test multiple constructs of each target for their ability to form crystals on a production-line basis. This has improved success rates and made crystallization much more convenient. High-throughput crystallization, however, cannot relieve users of the task of producing samples of high quality. Moreover, the time gained from eliminating manual preparations must now be invested in the careful evaluation of the increased number of experiments. The latter requires a sophisticated data and laboratory information-management system. A review of the current state of automation at the individual steps of crystallization with specific attention to the automation of optimization is given.

  8. Automation in biological crystallization

    Science.gov (United States)

    Shaw Stewart, Patrick; Mueller-Dieckmann, Jochen

    2014-01-01

    Crystallization remains the bottleneck in the crystallographic process leading from a gene to a three-dimensional model of the encoded protein or RNA. Automation of the individual steps of a crystallization experiment, from the preparation of crystallization cocktails for initial or optimization screens to the imaging of the experiments, has been the response to address this issue. Today, large high-throughput crystallization facilities, many of them open to the general user community, are capable of setting up thousands of crystallization trials per day. It is thus possible to test multiple constructs of each target for their ability to form crystals on a production-line basis. This has improved success rates and made crystallization much more convenient. High-throughput crystallization, however, cannot relieve users of the task of producing samples of high quality. Moreover, the time gained from eliminating manual preparations must now be invested in the careful evaluation of the increased number of experiments. The latter requires a sophisticated data and laboratory information-management system. A review of the current state of automation at the individual steps of crystallization with specific attention to the automation of optimization is given. PMID:24915074

  9. 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.

  10. Circulating microRNAs as Potential Biomarkers of Infectious Disease

    Science.gov (United States)

    Correia, Carolina N.; Nalpas, Nicolas C.; McLoughlin, Kirsten E.; Browne, John A.; Gordon, Stephen V.; MacHugh, David E.; Shaughnessy, Ronan G.

    2017-01-01

    microRNAs (miRNAs) are a class of small non-coding endogenous RNA molecules that regulate a wide range of biological processes by post-transcriptionally regulating gene expression. Thousands of these molecules have been discovered to date, and multiple miRNAs have been shown to coordinately fine-tune cellular processes key to organismal development, homeostasis, neurobiology, immunobiology, and control of infection. The fundamental regulatory role of miRNAs in a variety of biological processes suggests that differential expression of these transcripts may be exploited as a novel source of molecular biomarkers for many different disease pathologies or abnormalities. This has been emphasized by the recent discovery of remarkably stable miRNAs in mammalian biofluids, which may originate from intracellular processes elsewhere in the body. The potential of circulating miRNAs as biomarkers of disease has mainly been demonstrated for various types of cancer. More recently, however, attention has focused on the use of circulating miRNAs as diagnostic/prognostic biomarkers of infectious disease; for example, human tuberculosis caused by infection with Mycobacterium tuberculosis, sepsis caused by multiple infectious agents, and viral hepatitis. Here, we review these developments and discuss prospects and challenges for translating circulating miRNA into novel diagnostics for infectious disease. PMID:28261201

  11. 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.

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

    Directory of Open Access Journals (Sweden)

    Zella Davide

    2011-09-01

    Full Text Available Abstract Alzheimer's disease is a progressive and neurodegenerative disorder which involves multiple molecular mechanisms. Intense research during the last years has accumulated a large body of data and the search for sensitive and specific biomarkers has undergone a rapid evolution. However, the diagnosis remains problematic and the current tests do not accurately detect the process leading to neurodegeneration. Biomarkers discovery and validation are considered the key aspects to support clinical diagnosis and provide discriminatory power between different stages of the disorder. A considerable challenge is to integrate different types of data from new potent approach to reach a common interpretation and replicate the findings across studies and populations. Furthermore, long-term clinical follow-up and combined analysis of several biomarkers are among the most promising perspectives to diagnose and manage the disease. The present review will focus on the recent published data providing an updated overview of the main achievements in the genetic and biochemical research of the Alzheimer's disease. We also discuss the latest and most significant results that will help to define a specific disease signature whose validity might be clinically relevant for future AD diagnosis.

  13. Lipidomics applications for discovering biomarkers of diseases in clinical chemistry.

    Science.gov (United States)

    Zhao, Ying-Yong; Cheng, Xian-long; Lin, Rui-Chao

    2014-01-01

    Lipids are the fundamental components of biological membranes as well as the metabolites of organisms. Lipids play diverse and important roles in biologicals. The lipid imbalance is closely associated with numerous human lifestyle-related diseases, such as atherosclerosis, obesity, diabetes, and Alzheimer's disease. Lipidomics or lipid profiling is a system-based study of all lipids aiming at comprehensive analysis of lipids in the biological system. Lipidomics has been accepted as a lipid-related research tool in lipid biochemistry, clinical biomarker discovery, disease diagnosis, and in understanding disease pathology. Lipidomics will not only provide insights into the specific functions of lipid species in health and disease, but will also identify potential biomarkers for establishing preventive or therapeutic programs for human diseases. This review presents an overview of lipidomics followed by in-depth discussion of its application to the study of human diseases, including extraction methods of lipids, analytical technologies, data analysis, and clinical research in cancer, neuropsychiatric disease, cardiovascular disease, kidney disease, and respiratory disease. We describe the current status of the identification of metabolic biomarkers in different diseases. We also discuss the lipidomics for the future perspectives and their potential problems. The application of lipidomics in clinical studies may provide new insights into lipid profiling and pathophysiological mechanisms.

  14. 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.

  15. Strategies to design clinical studies to identify predictive biomarkers in cancer research.

    Science.gov (United States)

    Perez-Gracia, Jose Luis; Sanmamed, Miguel F; Bosch, Ana; Patiño-Garcia, Ana; Schalper, Kurt A; Segura, Victor; Bellmunt, Joaquim; Tabernero, Josep; Sweeney, Christopher J; Choueiri, Toni K; Martín, Miguel; Fusco, Juan Pablo; Rodriguez-Ruiz, Maria Esperanza; Calvo, Alfonso; Prior, Celia; Paz-Ares, Luis; Pio, Ruben; Gonzalez-Billalabeitia, Enrique; Gonzalez Hernandez, Alvaro; Páez, David; Piulats, Jose María; Gurpide, Alfonso; Andueza, Mapi; de Velasco, Guillermo; Pazo, Roberto; Grande, Enrique; Nicolas, Pilar; Abad-Santos, Francisco; Garcia-Donas, Jesus; Castellano, Daniel; Pajares, María J; Suarez, Cristina; Colomer, Ramon; Montuenga, Luis M; Melero, Ignacio

    2017-02-01

    The discovery of reliable biomarkers to predict efficacy and toxicity of anticancer drugs remains one of the key challenges in cancer research. Despite its relevance, no efficient study designs to identify promising candidate biomarkers have been established. This has led to the proliferation of a myriad of exploratory studies using dissimilar strategies, most of which fail to identify any promising targets and are seldom validated. The lack of a proper methodology also determines that many anti-cancer drugs are developed below their potential, due to failure to identify predictive biomarkers. While some drugs will be systematically administered to many patients who will not benefit from them, leading to unnecessary toxicities and costs, others will never reach registration due to our inability to identify the specific patient population in which they are active. Despite these drawbacks, a limited number of outstanding predictive biomarkers have been successfully identified and validated, and have changed the standard practice of oncology. In this manuscript, a multidisciplinary panel reviews how those key biomarkers were identified and, based on those experiences, proposes a methodological framework-the DESIGN guidelines-to standardize the clinical design of biomarker identification studies and to develop future research in this pivotal field.

  16. Discovering plant metabolic biomarkers for phenotype prediction using an untargeted approach.

    Science.gov (United States)

    Steinfath, Matthias; Strehmel, Nadine; Peters, Rolf; Schauer, Nicolas; Groth, Detlef; Hummel, Jan; Steup, Martin; Selbig, Joachim; Kopka, Joachim; Geigenberger, Peter; Van Dongen, Joost T

    2010-10-01

    Biomarkers are used to predict phenotypical properties before these features become apparent and, therefore, are valuable tools for both fundamental and applied research. Diagnostic biomarkers have been discovered in medicine many decades ago and are now commonly applied. While this is routine in the field of medicine, it is of surprise that in agriculture this approach has never been investigated. Up to now, the prediction of phenotypes in plants was based on growing plants and assaying the organs of interest in a time intensive process. For the first time, we demonstrate in this study the application of metabolomics to predict agronomic important phenotypes of a crop plant that was grown in different environments. Our procedure consists of established techniques to screen untargeted for a large amount of metabolites in parallel, in combination with machine learning methods. By using this combination of metabolomics and biomathematical tools metabolites were identified that can be used as biomarkers to improve the prediction of traits. The predictive metabolites can be selected and used subsequently to develop fast, targeted and low-cost diagnostic biomarker assays that can be implemented in breeding programs or quality assessment analysis. The identified metabolic biomarkers allow for the prediction of crop product quality. Furthermore, marker-assisted selection can benefit from the discovery of metabolic biomarkers when other molecular markers come to its limitation. The described marker selection method was developed for potato tubers, but is generally applicable to any crop and trait as it functions independently of genomic information.

  17. Tests detecting biomarkers for screening of colorectal cancer: What is on the horizon?

    Directory of Open Access Journals (Sweden)

    Phalguni, Angaja

    2015-06-01

    Full Text Available Aim: To identify new and emerging screening tests for colorectal cancer (CRC that involves detection of various biomarkers like blood, DNA and RNA in samples of faeces, tissue or blood. Current practice: Screening for CRC can be done by bowel visualisation techniques and tests that measure biomarkers. The Bowel Cancer Screening Programme (BCSP in England uses a guaiac faecal occult blood test. Methods: The strategy was to search available literature, identify developers and contact them for relevant information. Advice from experts was sought on potential utility and likely impact of identified technologies on the BCSP.Results: Ninety-three companies and five research groups were contacted. Sixty-nine relevant tests were identified. Detailed information was available for 48 tests, of these 73% were CE marked and the remainder were considered as emerging. Forty-nine tests use immunochemical methods to detect occult blood in faeces. Eight, four and two tests detect biomarkers in a sample of blood, or exfoliated cells either shed in faeces or collected from rectal mucosa respectively. Six tests were grouped as ‘other tests’. Most of the identified tests are performed manually and give qualitative detection of biomarkers. Conclusion: Variation in test performance and characteristics was observed amongst the 69 identified tests. Automated, quantitative FIT with a variable cut off are the preferred approach in the BSCP. However the units used to report FITs results do not enable comparison across products. Tests detecting biomarkers other than occult blood are more specific to neoplasms but have limited sensitivity due to the heterogeneity of cancer. Research is ongoing to identify an optimal panel of biomarkers, simplifying and automating the test, and reducing the cost.

  18. Contaminant analysis automation demonstration proposal

    Energy Technology Data Exchange (ETDEWEB)

    Dodson, M.G.; Schur, A.; Heubach, J.G.

    1993-10-01

    The nation-wide and global need for environmental restoration and waste remediation (ER&WR) presents significant challenges to the analytical chemistry laboratory. The expansion of ER&WR programs forces an increase in the volume of samples processed and the demand for analysis data. To handle this expanding volume, productivity must be increased. However. The need for significantly increased productivity, faces contaminant analysis process which is costly in time, labor, equipment, and safety protection. Laboratory automation offers a cost effective approach to meeting current and future contaminant analytical laboratory needs. The proposed demonstration will present a proof-of-concept automated laboratory conducting varied sample preparations. This automated process also highlights a graphical user interface that provides supervisory, control and monitoring of the automated process. The demonstration provides affirming answers to the following questions about laboratory automation: Can preparation of contaminants be successfully automated?; Can a full-scale working proof-of-concept automated laboratory be developed that is capable of preparing contaminant and hazardous chemical samples?; Can the automated processes be seamlessly integrated and controlled?; Can the automated laboratory be customized through readily convertible design? and Can automated sample preparation concepts be extended to the other phases of the sample analysis process? To fully reap the benefits of automation, four human factors areas should be studied and the outputs used to increase the efficiency of laboratory automation. These areas include: (1) laboratory configuration, (2) procedures, (3) receptacles and fixtures, and (4) human-computer interface for the full automated system and complex laboratory information management systems.

  19. 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.

  20. Biomarkers of replicative senescence revisited

    DEFF Research Database (Denmark)

    Nehlin, Jan

    2016-01-01

    Biomarkers of replicative senescence can be defined as those ultrastructural and physiological variations as well as molecules whose changes in expression, activity or function correlate with aging, as a result of the gradual exhaustion of replicative potential and a state of permanent cell cycle...... arrest. The biomarkers that characterize the path to an irreversible state of cell cycle arrest due to proliferative exhaustion may also be shared by other forms of senescence-inducing mechanisms. Validation of senescence markers is crucial in circumstances where quiescence or temporary growth arrest may...... be triggered or is thought to be induced. Pre-senescence biomarkers are also important to consider as their presence indicate that induction of aging processes is taking place. The bona fide pathway leading to replicative senescence that has been extensively characterized is a consequence of gradual reduction...