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...... 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. 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.

  4. Biological Networks for Cancer Candidate Biomarkers Discovery

    Science.gov (United States)

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

    2016-01-01

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

  5. Biological Networks for Cancer Candidate Biomarkers Discovery.

    Science.gov (United States)

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

    2016-01-01

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

  6. 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...

  7. 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.

  8. Proteomics Discovery of Disease Biomarkers

    OpenAIRE

    Mamoun Ahram; Petricoin, Emanuel F.

    2008-01-01

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

  9. 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.

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

    OpenAIRE

    Jordan, Rick; Visweswaran, Shyam; Gopalakrishnan, Vanathi

    2014-01-01

    Background Computational methods for mining of biomedical literature can be useful in augmenting manual searches of the literature using keywords for disease-specific biomarker discovery from biofluids. In this work, we develop and apply a semi-automated literature mining method to mine abstracts obtained from PubMed to discover putative biomarkers of breast and lung cancers in specific biofluids. Methodology A positive set of abstracts was defined by the terms ‘breast cancer’ and ‘lung cance...

  11. Automated Knowledge Discovery From Simulators

    Science.gov (United States)

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

    2007-01-01

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

  12. 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

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

    Directory of Open Access Journals (Sweden)

    David Clark

    2012-01-01

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

  14. Biomarker Discovery by Novel Sensors Based on Nanoproteomics Approaches

    Directory of Open Access Journals (Sweden)

    Manuel Fuentes

    2012-02-01

    Full Text Available During the last years, proteomics has facilitated biomarker discovery by coupling high-throughput techniques with novel nanosensors. In the present review, we focus on the study of label-based and label-free detection systems, as well as nanotechnology approaches, indicating their advantages and applications in biomarker discovery. In addition, several disease biomarkers are shown in order to display the clinical importance of the improvement of sensitivity and selectivity by using nanoproteomics approaches as novel sensors.

  15. 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

  16. 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.

  17. 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

  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. PROFILEing idiopathic pulmonary fibrosis: rethinking biomarker discovery.

    Science.gov (United States)

    Maher, Toby M

    2013-06-01

    Despite major advances in the understanding of the pathogenesis of idiopathic pulmonary fibrosis (IPF), diagnosis and management of the condition continue to pose significant challenges. Clinical management of IPF remains unsatisfactory due to limited availability of effective drug therapies, a lack of accurate indicators of disease progression, and an absence of simple short-term measures of therapeutic response. The identification of more accurate predictors of prognosis and survival in IPF would facilitate counseling of patients and their families, aid communication among clinicians, and would guide optimal timing of referral for transplantation. Improvements in molecular techniques have led to the identification of new disease pathways and a more targeted approach to the development of novel anti-fibrotic agents. However, despite an increased interest in biomarkers of IPF disease progression there are a lack of measures that can be used in early phase clinical trials. Careful longitudinal phenotyping of individuals with IPF together with the application of novel omics-based technology should provide important insights into disease pathogenesis and should address some of the major issues holding back drug development in IPF. The PROFILE (Prospective Observation of Fibrosis in the Lung Clinical Endpoints) study is a currently enrolling, prospective cohort study designed to tackle these issues. PMID:23728868

  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

    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.

  3. 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.

  4. 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

  5. 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

  6. 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.

  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. Role of proteomics in the discovery of autism biomarkers

    International Nuclear Information System (INIS)

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

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

    Directory of Open Access Journals (Sweden)

    Judith R Denery

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

  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. The Use of Proteomics in Biomarker Discovery in Neurodegenerative Diseases

    Directory of Open Access Journals (Sweden)

    Pia Davidsson

    2005-01-01

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

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

    Science.gov (United States)

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

    2016-01-01

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

  14. 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

    2013-09-01

    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.

  15. 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.

  16. 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.

  17. Establishment of Protocols for Global Metabolomics by LC-MS for Biomarker Discovery.

    Science.gov (United States)

    Saigusa, Daisuke; Okamura, Yasunobu; Motoike, Ikuko N; Katoh, Yasutake; Kurosawa, Yasuhiro; Saijyo, Reina; Koshiba, Seizo; Yasuda, Jun; Motohashi, Hozumi; Sugawara, Junichi; Tanabe, Osamu; Kinoshita, Kengo; Yamamoto, Masayuki

    2016-01-01

    Metabolomics is a promising avenue for biomarker discovery. Although the quality of metabolomic analyses, especially global metabolomics (G-Met) using mass spectrometry (MS), largely depends on the instrumentation, potential bottlenecks still exist at several basic levels in the metabolomics workflow. Therefore, we established a precise protocol initially for the G-Met analyses of human blood plasma to overcome some these difficulties. In our protocol, samples are deproteinized in a 96-well plate using an automated liquid-handling system, and conducted either using a UHPLC-QTOF/MS system equipped with a reverse phase column or a LC-FTMS system equipped with a normal phase column. A normalization protocol of G-Met data was also developed to compensate for intra- and inter-batch differences, and the variations were significantly reduced along with our normalization, especially for the UHPLC-QTOF/MS data with a C18 reverse-phase column for positive ions. Secondly, we examined the changes in metabolomic profiles caused by the storage of EDTA-blood specimens to identify quality markers for the evaluation of the specimens' pre-analytical conditions. Forty quality markers, including lysophospholipids, dipeptides, fatty acids, succinic acid, amino acids, glucose, and uric acid were identified by G-Met for the evaluation of plasma sample quality and established the equation of calculating the quality score. We applied our quality markers to a small-scale study to evaluate the quality of clinical samples. The G-Met protocols and quality markers established here should prove useful for the discovery and development of biomarkers for a wider range of diseases. PMID:27579980

  18. Establishment of Protocols for Global Metabolomics by LC-MS for Biomarker Discovery

    Science.gov (United States)

    Okamura, Yasunobu; Motoike, Ikuko N.; Katoh, Yasutake; Kurosawa, Yasuhiro; Saijyo, Reina; Koshiba, Seizo; Yasuda, Jun; Motohashi, Hozumi; Sugawara, Junichi; Tanabe, Osamu; Kinoshita, Kengo; Yamamoto, Masayuki

    2016-01-01

    Metabolomics is a promising avenue for biomarker discovery. Although the quality of metabolomic analyses, especially global metabolomics (G-Met) using mass spectrometry (MS), largely depends on the instrumentation, potential bottlenecks still exist at several basic levels in the metabolomics workflow. Therefore, we established a precise protocol initially for the G-Met analyses of human blood plasma to overcome some these difficulties. In our protocol, samples are deproteinized in a 96-well plate using an automated liquid-handling system, and conducted either using a UHPLC-QTOF/MS system equipped with a reverse phase column or a LC-FTMS system equipped with a normal phase column. A normalization protocol of G-Met data was also developed to compensate for intra- and inter-batch differences, and the variations were significantly reduced along with our normalization, especially for the UHPLC-QTOF/MS data with a C18 reverse-phase column for positive ions. Secondly, we examined the changes in metabolomic profiles caused by the storage of EDTA-blood specimens to identify quality markers for the evaluation of the specimens’ pre-analytical conditions. Forty quality markers, including lysophospholipids, dipeptides, fatty acids, succinic acid, amino acids, glucose, and uric acid were identified by G-Met for the evaluation of plasma sample quality and established the equation of calculating the quality score. We applied our quality markers to a small-scale study to evaluate the quality of clinical samples. The G-Met protocols and quality markers established here should prove useful for the discovery and development of biomarkers for a wider range of diseases. PMID:27579980

  19. 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

  20. Role of Systems Biology in Brain Injury Biomarker Discovery: Neuroproteomics Application.

    Science.gov (United States)

    Jaber, Zaynab; Aouad, Patrick; Al Medawar, Mohamad; Bahmad, Hisham; Abou-Abbass, Hussein; Ghandour, Hiba; Mondello, Stefania; Kobeissy, Firas

    2016-01-01

    Years of research in the field of neurotrauma have led to the concept of applying systems biology as a tool for biomarker discovery in traumatic brain injury (TBI). Biomarkers may lead to understanding mechanisms of injury and recovery in TBI and can be potential targets for wound healing, recovery, and increased survival with enhanced quality of life. The literature available on neurotrauma studies from both animal and clinical studies has provided rich insight on the molecular pathways and complex networks of TBI, elucidating the proteomics of this disease for the discovery of biomarkers. With such a plethora of information available, the data from the studies require databases with tools to analyze and infer new patterns and associations. The role of different systems biology tools and their use in biomarker discovery in TBI are discussed in this chapter. PMID:27604718

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

    Science.gov (United States)

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

    2016-01-01

    Blood-based biomarkers for Alzheimer's disease would be very valuable because blood is a more accessible biofluid and is suitable for repeated sampling. However, currently there are no robust and reliable blood-based biomarkers for practical diagnosis. In this study we used a knowledge-based protein feature pool and two novel support vector machine embedded feature selection methods to find panels consisting of two and three biomarkers. We validated these biomarker sets using another serum cohort and an RNA profile cohort from the brain. Our panels included the proteins ECH1, NHLRC2, HOXB7, FN1, ERBB2, and SLC6A13 and demonstrated promising sensitivity (>87%), specificity (>91%), and accuracy (>89%). PMID:27418712

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

    Directory of Open Access Journals (Sweden)

    Debasish Paul

    2013-01-01

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

  3. 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.

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

    OpenAIRE

    Kasing Man; Junbo Wang; Chunchi Wu

    2013-01-01

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

  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. Computational and Experimental Approaches to Cancer Biomarker Discovery

    DEFF Research Database (Denmark)

    Krzystanek, Marcin

    Effective cancer treatment requires good biomarkers: measurable indicators of some biological state or condition that constitute the cornerstone of personalized medicine. Prognostic biomarkers provide information about the likely course of the disease, while predictive biomarkers enable prediction...... was sequenced, assembled and characterized, which is described in the thesis. We are currently using it as a model system in our framework for functional analysis study of DNA repair mechanisms and cytotoxic effects. We hope that the experimentally derived mutational signatures will be useful as a part...... are expected.This work, together with manifold of efforts being done all over the world, is hopefully a step towards implementation of personalized medicine and better treatments for cancer patients. ...

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

    OpenAIRE

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

    2012-01-01

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

  8. 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.

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

    Directory of Open Access Journals (Sweden)

    Bonella F

    2015-07-01

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

  10. 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.

  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. 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

  13. A Critical Assessment of Feature Selection Methods for Biomarker Discovery in Clinical Proteomics

    NARCIS (Netherlands)

    Christin, Christin; Hoefsloot, Huub C. J.; Smilde, Age K.; Hoekman, B.; Suits, Frank; Bischoff, Rainer; Horvatovich, Peter

    2013-01-01

    In this paper, we compare the performance of six different feature selection methods for LC-MS-based proteomics and metabolomics biomarker discovery-t test, the Mann-Whitney-Wilcoxon test (mww test), nearest shrunken centroid (NSC), linear support vector machine-recursive features elimination (SVM-R

  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. 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

  16. 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.

  17. 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.

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

    Science.gov (United States)

    Aghagolzadeh, Parisa; Radpour, Ramin

    2016-07-01

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

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

    Science.gov (United States)

    Aghagolzadeh, Parisa; Radpour, Ramin

    2016-01-01

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

  20. 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

  1. 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

  2. Proteomics in Cancer Biomarkers Discovery: Challenges and Applications

    Directory of Open Access Journals (Sweden)

    Reem M. Sallam

    2015-01-01

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

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

    OpenAIRE

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

    2013-01-01

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

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

    OpenAIRE

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

    2014-01-01

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

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

    OpenAIRE

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

    2011-01-01

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

  6. 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

  7. 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...

  8. 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.

  9. 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.

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

    Science.gov (United States)

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

    2014-08-01

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

  11. 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.

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

    Directory of Open Access Journals (Sweden)

    Barbara Di Camillo

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

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

    Science.gov (United States)

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

    2015-07-01

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

  14. 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.

  15. 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.

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

    Science.gov (United States)

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

    2012-11-01

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

  17. 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.

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

    OpenAIRE

    Suleimanov, Yury V.; Green, William H.

    2015-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Kramer Alon

    2009-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Tsubouchi Hirohito

    2010-12-01

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

  1. 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.

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

    Science.gov (United States)

    Bauer, Chris; Glintschert, Alexander; Schuchhardt, Johannes

    2014-05-01

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

  3. 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.

  4. 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

  5. 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).

  6. 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.

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

    International Nuclear Information System (INIS)

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

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

    Directory of Open Access Journals (Sweden)

    Timm eDanker

    2014-09-01

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

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

    Directory of Open Access Journals (Sweden)

    Dey Dipak K

    2008-01-01

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

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

    NARCIS (Netherlands)

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

    2015-01-01

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

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

    Science.gov (United States)

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

    2013-01-01

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

  12. 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.

  13. 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.

  14. 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...

  15. 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.

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

    Science.gov (United States)

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

    2016-01-01

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

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

    Science.gov (United States)

    Suleimanov, Yury V; Green, William H

    2015-09-01

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

  18. 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.

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

    Science.gov (United States)

    Suleimanov, Yury V; Green, William H

    2015-09-01

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

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

    Science.gov (United States)

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

    2012-02-01

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

  1. 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.

  2. 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

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

    Science.gov (United States)

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

    2015-01-01

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

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

    Science.gov (United States)

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

    2016-07-21

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

  5. 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.

  6. 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.

  7. 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.

  8. 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...

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

    Directory of Open Access Journals (Sweden)

    Yinhai Wang

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

  10. 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.

  11. 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

  12. 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

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

    Science.gov (United States)

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

    2015-01-01

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

  14. 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

    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...

  15. 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

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

    Directory of Open Access Journals (Sweden)

    Wilkinson Mark D

    2011-10-01

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

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

    Science.gov (United States)

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

    2016-08-15

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

  18. 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.

  19. 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.

  20. 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.

  1. 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.

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

    Directory of Open Access Journals (Sweden)

    Jianwen She

    2013-09-01

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

  3. 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

    and healthy individuals to identify circulating O-glycoproteins with the STn glycoform. We identified 37 O-glycoproteins in the pool of cancer sera, and only 9 of these were also found in sera from healthy individuals. Two identified candidate O-glycoprotein biomarkers (CD44 and GalNAc-T5) circulating...

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

    DEFF Research Database (Denmark)

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

    2010-01-01

    The EU multi-disciplinary personalised RNA interference to enhance the delivery of individualised chemotherapeutics and targeted therapies (PREDICT) consortium has recently initiated a framework to accelerate the development of predictive biomarkers of individual patient response to anti-cancer a...

  5. 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

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

    International Nuclear Information System (INIS)

    The discovery of novel protein biomarkers is essential in the clinical setting to enable early disease diagnosis and increase survivability rates. To facilitate differential expression analysis and biomarker discovery, a variety of tandem mass spectrometry (MS/MS)-based protein profiling techniques have been developed. For achieving sensitive detection and accurate quantitation, targeted MS screening approaches, such as multiple reaction monitoring (MRM), have been implemented. MCF-7 breast cancer protein cellular extracts were analyzed by 2D-strong cation exchange (SCX)/reversed phase liquid chromatography (RPLC) separations interfaced to linear ion trap MS detection. MS data were interpreted with the Sequest-based Bioworks software (Thermo Electron). In-house developed Perl-scripts were used to calculate the spectral counts and the representative fragment ions for each peptide. In this work, we report on the generation of a library of 9,677 peptides (p < 0.001), representing ~1,572 proteins from human breast cancer cells, that can be used for MRM/MS-based biomarker screening studies. For each protein, the library provides the number and sequence of detectable peptides, the charge state, the spectral count, the molecular weight, the parameters that characterize the quality of the tandem mass spectrum (p-value, DeltaM, Xcorr, DeltaCn, Sp, no. of matching a, b, y ions in the spectrum), the retention time, and the top 10 most intense product ions that correspond to a given peptide. Only proteins identified by at least two spectral counts are listed. The experimental distribution of protein frequencies, as a function of molecular weight, closely matched the theoretical distribution of proteins in the human proteome, as provided in the SwissProt database. The amino acid sequence coverage of the identified proteins ranged from 0.04% to 98.3%. The highest-abundance proteins in the cellular extract had a molecular weight (MW)<50,000. Preliminary experiments have

  7. 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

  8. TOFwave: reproducibility in biomarker discovery from time-of-flight mass spectrometry data.

    Science.gov (United States)

    Chierici, Marco; Albanese, Davide; Franceschi, Pietro; Furlanello, Cesare

    2012-11-01

    Many are the sources of variability that can affect reproducibility of disease biomarkers from time-of-flight (TOF) Mass Spectrometry (MS) data. Here we present TOFwave, a complete software pipeline for TOF-MS biomarker identification, that limits the impact of parameter tuning along the whole chain of preprocessing and model selection modules. Peak profiles are obtained by a preprocessing based on Continuous Wavelet Transform (CWT), coupled with a machine learning protocol aimed at avoiding selection bias effects. Only two parameters (minimum peak width and a signal to noise cutoff) have to be explicitly set. The TOFwave pipeline is built on top of the mlpy Python package. Examples on Matrix-Assisted Laser Desorption and Ionization (MALDI) TOF datasets are presented. Software prototype, datasets and details to replicate results in this paper can be found at http://mlpy.sf.net/tofwave/. PMID:22875362

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

    DEFF Research Database (Denmark)

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

    2010-01-01

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

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

    OpenAIRE

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

    2016-01-01

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

  11. 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.

  12. 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.

  13. Ensuring Sample Quality for Biomarker Discovery Studies - Use of ICT Tools to Trace Biosample Life-cycle.

    Science.gov (United States)

    Riondino, Silvia; Ferroni, Patrizia; Spila, Antonella; Alessandroni, Jhessica; D'Alessandro, Roberta; Formica, Vincenzo; Della-Morte, David; Palmirotta, Raffaele; Nanni, Umberto; Roselli, Mario; Guadagni, Fiorella

    2015-01-01

    The growing demand of personalized medicine marked the transition from an empirical medicine to a molecular one, aimed at predicting safer and more effective medical treatment for every patient, while minimizing adverse effects. This passage has emphasized the importance of biomarker discovery studies, and has led sample availability to assume a crucial role in biomedical research. Accordingly, a great interest in Biological Bank science has grown concomitantly. In biobanks, biological material and its accompanying data are collected, handled and stored in accordance with standard operating procedures (SOPs) and existing legislation. Sample quality is ensured by adherence to SOPs and sample whole life-cycle can be recorded by innovative tracking systems employing information technology (IT) tools for monitoring storage conditions and characterization of vast amount of data. All the above will ensure proper sample exchangeability among research facilities and will represent the starting point of all future personalized medicine-based clinical trials. PMID:26543078

  14. 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.

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

    Science.gov (United States)

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

    2016-07-01

    The goal of this study is to identify systematic biomarker panel for primary nephrotic syndromes from urine samples by applying a non-target metabolite profiling, and to validate their utility in independent sampling and analysis by multiplex statistical approaches. Nephrotic syndrome (NS) is a nonspecific kidney disorder, which is mostly represented by minimal change disease (MCD), focal segmental glomerulosclerosis (FSGS), and membranous glomerulonephritis (MGN). Since urine metabolites may mirror disease-specific functional perturbations in kidney injury, we examined urine samples for distinctive metabolic changes to identify biomarkers for clinical applications. We developed unbiased multi-component covarianced models from a discovery set with 48 samples (12 healthy controls, 12 MCD, 12 FSGS, and 12 MGN). To extensively validate their diagnostic potential, new batch from 54 patients with primary NS were independently examined a year after. In the independent validation set, the model including citric acid, pyruvic acid, fructose, ethanolamine, and cysteine effectively discriminated each NS using receiver operating characteristic (ROC) analysis except MCD-MGN comparison; nonetheless an additional metabolite multi-composite greatly improved the discrimination power between MCD and MGN. Finally, we proposed the re-constructed metabolic network distinctively dysregulated by the different NSs that may deepen comprehensive understanding of the disease mechanistic, and help the enhanced identification of NS and therapeutic plans for future. PMID:27247212

  16. 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

  17. 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

  18. 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

  19. 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.

  20. 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.

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

    Science.gov (United States)

    Walton, Jonathan; Banerjee, Goutami; Car, Suzana

    2011-01-01

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

  2. 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.

  3. 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.

  4. 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

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

    Directory of Open Access Journals (Sweden)

    Grate Leslie R

    2005-04-01

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

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

    Science.gov (United States)

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

    2014-10-01

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

  7. 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.

  8. 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.

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

    OpenAIRE

    Walton, Jonathan; Banerjee, Goutami; Car, Suzana

    2011-01-01

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

  10. 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.

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

    Science.gov (United States)

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

    2016-01-01

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

  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. 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.

  14. Biomarker discovery from the top down: Protein biomarkers for efficient virus transmission by insects (Homoptera: Aphididae) discovered by coupling genetics and 2-D DIGE.

    Science.gov (United States)

    Cilia, Michelle; Howe, Kevin; Fish, Tara; Smith, Dawn; Mahoney, Jaclyn; Tamborindeguy, Cecilia; Burd, John; Thannhauser, Theodore W; Gray, Stewart

    2011-06-01

    Yellow dwarf viruses cause the most economically important virus diseases of cereal crops worldwide and are vectored by aphids. The identification of vector proteins mediating virus transmission is critical to develop sustainable virus management practices and to understand viral strategies for circulative movement in all insect vectors. Previously, we applied 2-D DIGE to an aphid filial generation 2 population to identify proteins correlated with the transmission phenotype that were stably inherited and expressed in the absence of the virus. In the present study, we examined the expression of the DIGE candidates in previously unstudied, field-collected aphid populations. We hypothesized that the expression of proteins involved in virus transmission could be clinically validated in unrelated, virus transmission-competent, field-collected aphid populations. All putative biomarkers were expressed in the field-collected biotypes, and the expression of nine of these aligned with the virus transmission-competent phenotype. The strong conservation of the expression of the biomarkers in multiple field-collected populations facilitates new and testable hypotheses concerning the genetics and biochemistry of virus transmission. Integration of these biomarkers into current aphid-scouting methodologies will enable rational strategies for vector control aimed at judicious use and development of precision pest control methods that reduce plant virus infection. PMID:21648087

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

    DEFF Research Database (Denmark)

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

    2015-01-01

    The objective of this study was to implement a multivariate method which analyzes multi-block metabolomics data and performs variable selection in order to discover potential biomarkers, simultaneously. We call this method sparse multi-block partial least squares regression (Sparse MBPLSR...... the measurement variables of this multi-block data set. The results showed that Sparse MBPLSR with CMV is a useful tool for analyzing multi-block metabolomics data with a good prediction and for identifying potential biomarkers....

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

    OpenAIRE

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

    2016-01-01

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

  17. 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...

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

    DEFF Research Database (Denmark)

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

    2010-01-01

    In this study Atlantic cod (Gadus morhua) were exposed to different levels of North Sea produced water (PW) and 17beta-oestradiol (E(2)), a natural oestrogen, from egg to fry stage (90 days). By comparing changes in protein expression following E(2) exposure to changes induced by PW treatment, we...... changes that may be useful as biomarker candidates of produced water (PW) and oestradiol exposure in Atlantic cod fry. The biomarker candidates discovered in this study may, following validation, prove effective as diagnostic tools in monitoring exposure and effects of discharges from the petroleum...

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

    NARCIS (Netherlands)

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

    2007-01-01

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

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

    Science.gov (United States)

    Ramaiah, Shashi K; Walker, Dana B

    2016-02-01

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

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

    Science.gov (United States)

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

    2016-08-01

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

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

    Science.gov (United States)

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

    2016-10-01

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

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

    OpenAIRE

    Jianwen She; Wei Zou; Vladimir V. Tolstikov

    2013-01-01

    Current available biomarkers lack sensitivity and/or specificity for early detection of cancer. To address this challenge, a robust and complete workflow for metabolic profiling and data mining is described in details. Three independent and complementary analytical techniques for metabolic profiling are applied: hydrophilic interaction liquid chromatography (HILIC–LC), reversed-phase liquid chromatography (RP–LC), and gas chromatography (GC). All three techniques are coupled to a mass spectro...

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

    OpenAIRE

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

    2015-01-01

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

  5. 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.

  6. 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.

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

    Science.gov (United States)

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

    2016-07-01

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

  8. 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.

  9. 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.

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

    Science.gov (United States)

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

    2016-01-01

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

  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. 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.

  13. 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.

  14. 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

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

    Science.gov (United States)

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

    2016-01-01

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

  16. Mass spectrometry for biomarker development

    Energy Technology Data Exchange (ETDEWEB)

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

    2015-06-19

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

  17. 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.

  18. Shotgun Proteomics and Biomarker Discovery

    OpenAIRE

    W. Hayes McDonald; Yates, John R.

    2002-01-01

    Coupling large-scale sequencing projects with the amino acid sequence information that can be gleaned from tandem mass spectrometry (MS/MS) has made it much easier to analyze complex mixtures of proteins. The limits of this “shotgun” approach, in which the protein mixture is proteolytically digested before separation, can be further expanded by separating the resulting mixture of peptides prior to MS/MS analysis. Both single dimensional high pressure liquid chromatography (LC) and multidimens...

  19. 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.

  20. 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.

  1. 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

  2. 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......-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...... = 0.017. Treatment follow-up bone scans were available from 62 patients. Both change in BSI and percent change in PSA were predictive of OS. However, the combined predictive model of percent PSA change and change in automated BSI (C-index 0.77) was significantly higher than that of percent PSA change...

  3. 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

  4. 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...

  5. 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.

  6. 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

  7. Discovery of gene expression-based pharmacodynamic biomarker for a p53 context-specific anti-tumor drug Wee1 inhibitor

    Directory of Open Access Journals (Sweden)

    Mizuarai Shinji

    2009-06-01

    Full Text Available Abstract Background Wee1 is a tyrosine kinase regulating S-G2 cell cycle transition through the inactivating phosphorylation of CDC2. The inhibition of Wee1 kinase by a selective small molecule inhibitor significantly enhances the anti-tumor efficacy of DNA damaging agents, specifically in p53 negative tumors by abrogating S-G2 checkpoints, while normal cells with wild-type p53 are not severely damaged due to the intact function of the G1 checkpoint mediated by p53. Since the measurement of mRNA expression requires a very small amount of biopsy tissue and is highly quantitative, the development of a pharmacodynamic (PD biomarker leveraging mRNA expression is eagerly anticipated in order to estimate target engagement of anti-cancer agents. Results In order to find the Wee1 inhibition signature, mRNA expression profiling was first performed in both p53 positive and negative cancer cell lines treated with gemcitabine and a Wee1 inhibitor, MK-1775. We next carried out mRNA expression profiling of skin samples derived from xenograft models treated with the Wee1 inhibitor to identify a Wee1 inhibitor-regulatory gene set. Then, the genes that were commonly modulated in both cancer cell lines and rat skin samples were extracted as a Wee1 inhibition signature that could potentially be used as a PD biomarker independent of p53 status. The expression of the Wee1 inhibition signature was found to be regulated in a dose-dependent manner by the Wee1 inhibitor, and was significantly correlated with the inhibition level of a direct substrate, phosphorylated-CDC2. Individual genes in this Wee1 inhibition signature are known to regulate S-G2 cell cycle progression or checkpoints, which is consistent with the mode-of-action of the Wee1 inhibitor. Conclusion We report here the identification of an mRNA gene signature that was specifically changed by gemcitabine and Wee1 inhibitor combination treatment by molecular profiling. Given the common regulation of

  8. Biomarkers for neuromyelitis optica.

    Science.gov (United States)

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

    2015-02-01

    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.

  9. 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

  10. 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

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

    Science.gov (United States)

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

    2015-03-01

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

  12. Ultra-high throughput sequencing-based small RNA discovery and discrete statistical biomarker analysis in a collection of cervical tumours and matched controls

    Directory of Open Access Journals (Sweden)

    Gu Sam

    2010-05-01

    Full Text Available Abstract Background Ultra-high throughput sequencing technologies provide opportunities both for discovery of novel molecular species and for detailed comparisons of gene expression patterns. Small RNA populations are particularly well suited to this analysis, as many different small RNAs can be completely sequenced in a single instrument run. Results We prepared small RNA libraries from 29 tumour/normal pairs of human cervical tissue samples. Analysis of the resulting sequences (42 million in total defined 64 new human microRNA (miRNA genes. Both arms of the hairpin precursor were observed in twenty-three of the newly identified miRNA candidates. We tested several computational approaches for the analysis of class differences between high throughput sequencing datasets and describe a novel application of a log linear model that has provided the most effective analysis for this data. This method resulted in the identification of 67 miRNAs that were differentially-expressed between the tumour and normal samples at a false discovery rate less than 0.001. Conclusions This approach can potentially be applied to any kind of RNA sequencing data for analysing differential sequence representation between biological sample sets.

  13. Biomarkers for pancreatic carcinogenesis

    OpenAIRE

    Hustinx, S.R.

    2007-01-01

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

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

    Science.gov (United States)

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

    2014-05-01

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

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

    Science.gov (United States)

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

    2014-01-01

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

  16. 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.

  17. 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.

  18. 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.

  19. 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.

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

    Science.gov (United States)

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

    2016-05-01

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

  1. 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.

  2. [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.

  3. 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.

  4. Proteomics in biomarker discovery and drug development

    OpenAIRE

    He, Q.; Chiu, J

    2003-01-01

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

  5. Using Aptamers for Cancer Biomarker Discovery

    OpenAIRE

    Yun Min Chang; Donovan, Michael J; Weihong Tan

    2013-01-01

    Aptamers are single-stranded synthetic DNA- or RNA-based oligonucleotides that fold into various shapes to bind to a specific target, which includes proteins, metals, and molecules. Aptamers have high affinity and high specificity that are comparable to that of antibodies. They are obtained using iterative method, called (Systematic Evolution of Ligands by Exponential Enrichment) SELEX and cell-based SELEX (cell-SELEX). Aptamers can be paired with recent advances in nanotechnology, microarray...

  6. Proteomic Approaches for Biomarker Panels in Cancer.

    Science.gov (United States)

    Tanase, Cristiana; Albulescu, Radu; Neagu, Monica

    2016-01-01

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

  7. 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.

  8. Biomarkers in precision therapy in colorectal cancer

    OpenAIRE

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

    2013-01-01

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

  9. Exploring Biomarkers for Alzheimer's Disease.

    Science.gov (United States)

    Sharma, Neeti; Singh, Anshika Nikita

    2016-07-01

    Alzheimer's Disease (AD) is one of the most common form of dementia occurring in elderly population worldwide. Currently Aβ42, tau and p-tau in the cerebrospinal fluid is estimated for confirmation of AD. CSF which is being used as the potent source for biomarker screening is obtained by invasive lumbar punctures. Thus, there is an urgent need of minimal invasive methods for identification of diagnostic markers for early detection of AD. Blood serum and plasma serves as an appropriate source, due to minimal discomfort to the patients, promoting frequent testing, better follow-up and better consent to clinical trials. Hence, the need of the hour demands discovery of diagnostic and prognostic patient specific signature biomarkers by using emerging technologies of mass spectrometry, microarrays and peptidomics. In this review we summarize the present scenario of AD biomarkers such as circulatory biomarkers, blood based amyloid markers, inflammatory markers and oxidative stress markers being investigated and also some of the potent biomarkers which might be able to predict early onset of Alzheimer's and delay cognitive impairment. PMID:27630867

  10. 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......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......, procedural process modeling languages seem more suitable to describe structured and stable processes. However, in various cases, a process may incorporate parts that are better captured in a declarative fashion, while other parts are more suitable to be described procedurally. In this paper, we present...... a technique for discovering from an event log a so-called hybrid process model. A hybrid process model is hierarchical, where each of its sub-processes may be specified in a declarative or procedural fashion. We have implemented the proposed approach as a plug-in of the ProM platform. To evaluate the approach...

  11. 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.

  12. Automated motif discovery from glycan array data.

    Science.gov (United States)

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

    2012-10-01

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

  13. 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...

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

    Science.gov (United States)

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

    2015-05-15

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

  15. 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

  16. 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

  17. Translation of neurological biomarkers to clinically relevant platforms.

    Science.gov (United States)

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

    2009-01-01

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

  18. 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.

  19. 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.

  20. 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

  1. Process automation

    International Nuclear Information System (INIS)

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

  2. 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.

  3. 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.

  4. Volatility Discovery

    DEFF Research Database (Denmark)

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

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

  5. 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

  6. 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...

  7. 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.

  8. 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...

  9. 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:…

  10. Biomarkers in Computational Toxicology

    Science.gov (United States)

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

  11. 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....

  12. Biomarkers of Mercury Exposure in the Amazon

    OpenAIRE

    Nathália Santos Serrão de Castro; Marcelo de Oliveira Lima

    2014-01-01

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

  13. 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...... associated technologies. We then focus on the multivariate nature of cellular networks and how this has implications for biomarker and drug discovery using cancer metastasis as an example....

  14. Macrophage-Derived Biomarkers of Idiopathic Pulmonary Fibrosis

    OpenAIRE

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

    2011-01-01

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

  15. Biomarkers for Ectopic Pregnancy and Pregnancy of Unknown Location

    OpenAIRE

    Senapati, Suneeta; Barnhart, Kurt T.

    2013-01-01

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

  16. Automated Motivic Analysis

    DEFF Research Database (Denmark)

    Lartillot, Olivier

    2016-01-01

    Motivic analysis provides very detailed understanding of musical composi- tions, but is also particularly difficult to formalize and systematize. A computational automation of the discovery of motivic patterns cannot be reduced to a mere extraction of all possible sequences of descriptions....... The systematic approach inexorably leads to a proliferation of redundant structures that needs to be addressed properly. Global filtering techniques cause a drastic elimination of interesting structures that damages the quality of the analysis. On the other hand, a selection of closed patterns allows...... for lossless compression. The structural complexity resulting from successive repetitions of patterns can be controlled through a simple modelling of cycles. Generally, motivic patterns cannot always be defined solely as sequences of descriptions in a fixed set of dimensions: throughout the descriptions...

  17. 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...

  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. 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.

  20. 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.

  1. Exploring Biomarkers for Alzheimer’s Disease

    Science.gov (United States)

    Singh, Anshika Nikita

    2016-01-01

    Alzheimer’s Disease (AD) is one of the most common form of dementia occurring in elderly population worldwide. Currently Aβ42, tau and p-tau in the cerebrospinal fluid is estimated for confirmation of AD. CSF which is being used as the potent source for biomarker screening is obtained by invasive lumbar punctures. Thus, there is an urgent need of minimal invasive methods for identification of diagnostic markers for early detection of AD. Blood serum and plasma serves as an appropriate source, due to minimal discomfort to the patients, promoting frequent testing, better follow-up and better consent to clinical trials. Hence, the need of the hour demands discovery of diagnostic and prognostic patient specific signature biomarkers by using emerging technologies of mass spectrometry, microarrays and peptidomics. In this review we summarize the present scenario of AD biomarkers such as circulatory biomarkers, blood based amyloid markers, inflammatory markers and oxidative stress markers being investigated and also some of the potent biomarkers which might be able to predict early onset of Alzheimer’s and delay cognitive impairment. PMID:27630867

  2. 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.

  3. 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

  4. Discovery Mondays

    CERN Document Server

    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...

  5. 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

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

    Directory of Open Access Journals (Sweden)

    Gerald Li

    2012-01-01

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

  7. 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...

  8. 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...

  9. 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,...

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

    Science.gov (United States)

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

    2015-01-01

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

  11. Trends in Modern Drug Discovery.

    Science.gov (United States)

    Eder, Jörg; Herrling, Paul L

    2016-01-01

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

  12. 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.

  13. 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.

  14. 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.

  15. 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

  16. Biomarkers in Autism

    Directory of Open Access Journals (Sweden)

    Robert eHendren

    2014-08-01

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

  17. Biomarkers of Hypoxic Ischemic Encephalopathy in Newborns

    Directory of Open Access Journals (Sweden)

    Martha V. Douglas-Escobar

    2012-11-01

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

  18. 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.

  19. cNEUPRO: Novel Biomarkers for Neurodegenerative Diseases

    Directory of Open Access Journals (Sweden)

    Philipp Spitzer

    2010-01-01

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

  20. 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.

  1. [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.

  2. 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.

  3. 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.

  4. Biomarkers in Severe Asthma.

    Science.gov (United States)

    Wan, Xiao Chloe; Woodruff, Prescott G

    2016-08-01

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

  5. Validation of New Cancer Biomarkers

    DEFF Research Database (Denmark)

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

    2015-01-01

    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...

  6. 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.

  7. 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.

  8. Biomarkers for immune thrombocytopenia

    OpenAIRE

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

    2015-01-01

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

  9. 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.

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

    NARCIS (Netherlands)

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

    2009-01-01

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

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

    Science.gov (United States)

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

    2016-07-01

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

  12. Random glycopeptide bead libraries for seromic biomarker discovery

    DEFF Research Database (Denmark)

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

    2010-01-01

    have developed a random glycopeptide bead library screening platform for detection of autoantibodies and other binding proteins. Libraries were build on biocompatible PEGA beads including a safety-catch C-terminal amide linker (SCAL) that allowed mild cleavage conditions (I(2)/NaBH(4) and TFA) for...

  13. Sparse Mbplsr for Metabolomics Data and Biomarker Discovery

    DEFF Research Database (Denmark)

    Karaman, İbrahim

    2014-01-01

    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-knife...... of noise is comparable to the signal, the Jack-Knife PLSR could be the better choice. Extension of Sparse PLSR to multi-block setting as Sparse MBPLSR (multi-block partial least squares regression) was implemented for analyzing metabolomics data from several analytical platforms. By Sparse MBPLSR, variable...

  14. 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

  15. 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.

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

    Science.gov (United States)

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

    2015-09-01

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

  17. 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...

  18. 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.

  19. Human Cervicovaginal Fluid Biomarkers to Predict Term and Preterm Labour

    Directory of Open Access Journals (Sweden)

    Yujing Jan Heng

    2015-05-01

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

  20. 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.

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

    OpenAIRE

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

    2015-01-01

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

  2. 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.

  3. The importance of biomarkers in neonatology.

    Science.gov (United States)

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

    2013-02-01

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

  4. Biomarkers of the Dementia

    Directory of Open Access Journals (Sweden)

    Mikio Shoji

    2011-01-01

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

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

    Science.gov (United States)

    Chauhan, Ranjit; Lahiri, Nivedita

    2016-01-01

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

  6. Prognostic factors and biomarkers of congenital obstructive nephropathy.

    Science.gov (United States)

    Chevalier, Robert L

    2016-09-01

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

  7. MicroRNA Biomarkers of Toxicity in Biological Matrices.

    Science.gov (United States)

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

    2016-08-01

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

  8. Glial biomarkers in human central nervous system disease.

    Science.gov (United States)

    Garden, Gwenn A; Campbell, Brian M

    2016-10-01

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

  9. Shoe-String Automation

    Energy Technology Data Exchange (ETDEWEB)

    Duncan, M.L.

    2001-07-30

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

  10. 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.

  11. 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

  12. Proteomic Biomarkers of Atherosclerosis

    Directory of Open Access Journals (Sweden)

    Natacha Diaz-Prieto

    2008-01-01

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

  13. Proteomic Biomarkers of Atherosclerosis.

    Science.gov (United States)

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

    2008-01-01

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

  14. 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.

  15. 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.

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

    Science.gov (United States)

    Nielsen, Cydney B

    2016-02-01

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

  17. The State of the Art in Library Discovery 2010

    Science.gov (United States)

    Breeding, Marshall

    2010-01-01

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

  18. Role of New Biomarkers: Functional and Structural Damage

    OpenAIRE

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

    2013-01-01

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

  19. Strategies for modern biomarker and drug development in oncology

    OpenAIRE

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

    2014-01-01

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

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

    OpenAIRE

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

    2014-01-01

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

  1. 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

  2. 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.

  3. 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...

  4. 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.

  5. 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...

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

    Science.gov (United States)

    Kalia, Madhu

    2015-03-01

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

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2011-07-19

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

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

    International Nuclear Information System (INIS)

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

  9. Biomarkers of Ovarian Reserve

    Directory of Open Access Journals (Sweden)

    William E. Roudebush

    2008-01-01

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

  10. 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.

  11. 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.

  12. 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

  13. Work and Programmable Automation.

    Science.gov (United States)

    DeVore, Paul W.

    A new industrial era based on electronics and the microprocessor has arrived, an era that is being called intelligent automation. Intelligent automation, in the form of robots, replaces workers, and the new products, using microelectronic devices, require significantly less labor to produce than the goods they replace. The microprocessor thus…

  14. Library Automation Style Guide.

    Science.gov (United States)

    Gaylord Bros., Liverpool, NY.

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

  15. 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.

  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. 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. PMID:22988378

  18. 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...

  19. 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.

  20. Automated model building

    CERN Document Server

    Caferra, Ricardo; Peltier, Nicholas

    2004-01-01

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

  1. 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.

  2. 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

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

    Science.gov (United States)

    Chen, B; Butte, AJ

    2016-01-01

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

  4. 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

  5. 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.

  6. 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.

  7. 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.

  8. 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!

  9. Decades of Discovery

    Science.gov (United States)

    2011-06-01

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

  10. Academic Drug Discovery Centres

    DEFF Research Database (Denmark)

    Kirkegaard, Henriette Schultz; Valentin, Finn

    2014-01-01

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

  11. 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

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

    Science.gov (United States)

    Honavar, Vasant

    2015-01-01

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

  13. 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).

  14. 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...

  15. 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...

  16. 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.

  17. 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.

  18. 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.

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

    DEFF Research Database (Denmark)

    Williamson, James C; Scheipers, Peter; Schwämmle, Veit;

    2013-01-01

    The discovery of plasma biomarkers for psoriasis vulgaris may aid clinicians in disease grading and monitoring of treatment response. We have therefore developed a proteomics/mass spectrometry based workflow which enables biomarker discovery from psoriasis patient samples. We have utilised keratome...... a quantitative proteomics screen of four patients with psoriasis using stable isotope dimethyl labelling and identified over 50 proteins consistently altered in abundance in psoriasis lesional versus non-lesional skin. This includes several canonical psoriasis related proteins (e.g. S100A7 [Psoriasin] and FABP5...... [Epidermal Fatty Acid Binding Protein]) and more than 30 novel alterations. From this disease localised dataset we further assessed several proteins as potential biomarkers in the plasma of patients with psoriasis versus healthy controls utilising selected reaction monitoring mass spectrometry (SRM-MS/MS)....

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

    Science.gov (United States)

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

    2008-10-01

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

  1. 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.

  2. 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.

  3. Emerging biomarkers in psoriatic arthritis.

    Science.gov (United States)

    Paek, So Yeon; Han, Ling; Weiland, Matthew; Lu, Chuan-Jian; McKinnon, Kathleen; Zhou, Li; Lim, Henry W; Elder, James T; Mi, Qing-Sheng

    2015-12-01

    Psoriasis is an immune-mediated skin disease which affects 2-4% of the worldwide population. Approximately 20-30% of patients with psoriasis develop psoriatic arthritis (PsA), a frequently destructive and disabling condition. As skin manifestations precede joint symptoms in nearly all patients with PsA, identification of biomarkers for early prediction of joint damage is an important clinical need. Because not all patients with PsA respond to treatment in the same fashion, identification of biomarkers capable of predicting therapeutic response is also imperative. Here, we review existing literature and discuss current investigations to identify potential biomarkers for PsA disease activity, with particular emphasis on microRNAs as novel markers of interest. Serum (soluble) biomarkers, peripheral osteoclast precursor as cellular biomarkers, and genetic loci associated with skin and joint disease are also reviewed. PMID:26602058

  4. 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.

  5. 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

  6. 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.

  7. 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

  8. 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.

  9. 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.

  10. Biomarkers for lymphoma

    Energy Technology Data Exchange (ETDEWEB)

    Zangar, Richard C.; Varnum, Susan M.

    2014-09-02

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

  11. Biomarkers of manganese intoxication.

    Science.gov (United States)

    Zheng, Wei; Fu, Sherleen X; Dydak, Ulrike; Cowan, Dallas M

    2011-01-01

    Manganese (Mn), upon absorption, is primarily sequestered in tissue and intracellular compartments. For this reason, blood Mn concentration does not always accurately reflect Mn concentration in the targeted tissue, particularly in the brain. The discrepancy between Mn concentrations in tissue or intracellular components means that blood Mn is a poor biomarker of Mn exposure or toxicity under many conditions and that other biomarkers must be established. For group comparisons of active workers, blood Mn has some utility for distinguishing exposed from unexposed subjects, although the large variability in mean values renders it insensitive for discriminating one individual from the rest of the study population. Mn exposure is known to alter iron (Fe) homeostasis. The Mn/Fe ratio (MIR) in plasma or erythrocytes reflects not only steady-state concentrations of Mn or Fe in tested individuals, but also a biological response (altered Fe homeostasis) to Mn exposure. Recent human studies support the potential value for using MIR to distinguish individuals with Mn exposure. Additionally, magnetic resonance imaging (MRI), in combination with noninvasive assessment of γ-aminobutyric acid (GABA) by magnetic resonance spectroscopy (MRS), provides convincing evidence of Mn exposure, even without clinical symptoms of Mn intoxication. For subjects with long-term, low-dose Mn exposure or for those exposed in the past but not the present, neither blood Mn nor MRI provides a confident distinction for Mn exposure or intoxication. While plasma or erythrocyte MIR is more likely a sensitive measure, the cut-off values for MIR among the general population need to be further tested and established. Considering the large accumulation of Mn in bone, developing an X-ray fluorescence spectroscopy or neutron-based spectroscopy method may create yet another novel non-invasive tool for assessing Mn exposure and toxicity. PMID:20946915

  12. 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

    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...... 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...

  13. Toxins and drug discovery.

    Science.gov (United States)

    Harvey, Alan L

    2014-12-15

    Components from venoms have stimulated many drug discovery projects, with some notable successes. These are briefly reviewed, from captopril to ziconotide. However, there have been many more disappointments on the road from toxin discovery to approval of a new medicine. Drug discovery and development is an inherently risky business, and the main causes of failure during development programmes are outlined in order to highlight steps that might be taken to increase the chances of success with toxin-based drug discovery. These include having a clear focus on unmet therapeutic needs, concentrating on targets that are well-validated in terms of their relevance to the disease in question, making use of phenotypic screening rather than molecular-based assays, and working with development partners with the resources required for the long and expensive development process. PMID:25448391

  14. 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

  15. 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)

  16. 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...

  17. [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.

  18. 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.

  19. Towards temporal relation discovery from the clinical narrative.

    Science.gov (United States)

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

    2009-01-01

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

  20. iPTF Discoveries of Recent Type Ia Supernovae

    Science.gov (United States)

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

    2016-05-01

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

  1. Fractionated Marine Invertebrate Extract Libraries for Drug Discovery

    OpenAIRE

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

    2008-01-01

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

  2. 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.

  3. Biomarker in archaeological soils

    Science.gov (United States)

    Wiedner, Katja; Glaser, Bruno; Schneeweiß, Jens

    2015-04-01

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

  4. 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.

  5. 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....

  6. 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.

  7. Automated phantom assay system

    International Nuclear Information System (INIS)

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

  8. Automated gas chromatography

    Science.gov (United States)

    Mowry, Curtis D.; Blair, Dianna S.; Rodacy, Philip J.; Reber, Stephen D.

    1999-01-01

    An apparatus and process for the continuous, near real-time monitoring of low-level concentrations of organic compounds in a liquid, and, more particularly, a water stream. A small liquid volume of flow from a liquid process stream containing organic compounds is diverted by an automated process to a heated vaporization capillary where the liquid volume is vaporized to a gas that flows to an automated gas chromatograph separation column to chromatographically separate the organic compounds. Organic compounds are detected and the information transmitted to a control system for use in process control. Concentrations of organic compounds less than one part per million are detected in less than one minute.

  9. Cardiac Biomarkers and Cycling Race

    OpenAIRE

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

    2015-01-01

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

  10. Biomarkers in Acute Lung Injury

    OpenAIRE

    Bhargava, Maneesh; Wendt, Chris

    2012-01-01

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

  11. 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...

  12. A Decade of Discovery

    Energy Technology Data Exchange (ETDEWEB)

    None

    2008-01-01

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

  13. Automated sampling and data processing derived from biomimetic membranes

    DEFF Research Database (Denmark)

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

    2009-01-01

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

  14. 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

  15. Neuroimmune biomarkers in schizophrenia.

    Science.gov (United States)

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

    2016-09-01

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

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

    Science.gov (United States)

    Bonella, Francesco; Costabel, Ulrich

    2014-04-01

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

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

    Science.gov (United States)

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

    2016-10-01

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

  18. 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

  19. Automated solvent concentrator

    Science.gov (United States)

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

    1976-01-01

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

  20. 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...

  1. ELECTROPNEUMATIC AUTOMATION EDUCATIONAL LABORATORY

    OpenAIRE

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

    2013-01-01

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

  2. Building Automation Systems.

    Science.gov (United States)

    Honeywell, Inc., Minneapolis, Minn.

    A number of different automation systems for use in monitoring and controlling building equipment are described in this brochure. The system functions include--(1) collection of information, (2) processing and display of data at a central panel, and (3) taking corrective action by sounding alarms, making adjustments, or automatically starting and…

  3. Test Construction: Automated

    NARCIS (Netherlands)

    Veldkamp, Bernard P.

    2014-01-01

    Optimal test construction deals with automated assembly of tests for educational and psychological measurement. Items are selected from an item bank to meet a predefined set of test specifications. Several models for optimal test construction are presented, and two algorithms for optimal test assemb

  4. Test Construction: Automated

    NARCIS (Netherlands)

    Veldkamp, Bernard P.

    2016-01-01

    Optimal test construction deals with automated assembly of tests for educational and psychological measurement. Items are selected from an item bank to meet a predefined set of test specifications. Several models for optimal test construction are presented, and two algorithms for optimal test assemb

  5. 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.

  6. 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…

  7. 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.

  8. 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

  9. 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.

  10. 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.

  11. 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...

  12. 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.

  13. Evaluating ten discoveries

    Energy Technology Data Exchange (ETDEWEB)

    1973-02-01

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

  14. 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...

  15. 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.

  16. 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.

  17. 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.

  18. 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.

  19. 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.

  20. 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.

  1. Automated theorem proving.

    Science.gov (United States)

    Plaisted, David A

    2014-03-01

    Automated theorem proving is the use of computers to prove or disprove mathematical or logical statements. Such statements can express properties of hardware or software systems, or facts about the world that are relevant for applications such as natural language processing and planning. A brief introduction to propositional and first-order logic is given, along with some of the main methods of automated theorem proving in these logics. These methods of theorem proving include resolution, Davis and Putnam-style approaches, and others. Methods for handling the equality axioms are also presented. Methods of theorem proving in propositional logic are presented first, and then methods for first-order logic. WIREs Cogn Sci 2014, 5:115-128. doi: 10.1002/wcs.1269 CONFLICT OF INTEREST: The authors has declared no conflicts of interest for this article. For further resources related to this article, please visit the WIREs website. PMID:26304304

  2. ATLAS Distributed Computing Automation

    CERN Document Server

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

    2012-01-01

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

  3. Rapid automated nuclear chemistry

    International Nuclear Information System (INIS)

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

  4. 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.

  5. 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.

  6. Translating colorectal cancer genetics into clinically useful biomarkers.

    Science.gov (United States)

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

    2016-08-01

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

  7. 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.

  8. Plasma and urine biomarkers in acute viral hepatitis E

    Directory of Open Access Journals (Sweden)

    Aggarwal Rakesh

    2009-10-01

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

  9. Peripheral Biomarkers in Animal Models of Major Depressive Disorder

    Directory of Open Access Journals (Sweden)

    Lucia Carboni

    2013-01-01

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

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

    Science.gov (United States)

    Carboni, Lucia

    2013-01-01

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

  11. 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.

  12. Biomarkers in fibromyalgia: a review

    Directory of Open Access Journals (Sweden)

    Giacomelli C

    2014-02-01

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

  13. Bias in Peripheral Depression Biomarkers

    DEFF Research Database (Denmark)

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

    2016-01-01

    BACKGROUND: To aid in the differentiation of individuals with major depressive disorder (MDD) from healthy controls, numerous peripheral biomarkers have been proposed. To date, no comprehensive evaluation of the existence of bias favoring the publication of significant results or inflating effect...... sizes has been conducted. METHODS: Here, we performed a comprehensive review of meta-analyses of peripheral nongenetic biomarkers that could discriminate individuals with MDD from nondepressed controls. PubMed/MEDLINE, EMBASE, and PsycINFO databases were searched through April 10, 2015. RESULTS: From 15......-analyses, while 11 meta-analyses had evidence of small-study effects. CONCLUSIONS: Our findings suggest that there is an excess of studies with statistically significant results in the literature of peripheral biomarkers for MDD. The selective publication of 'positive studies' and the selective reporting...

  14. Biomarkers in inflammatory bowel diseases

    DEFF Research Database (Denmark)

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

    2014-01-01

    Unambiguous diagnosis of the two main forms of inflammatory bowel diseases (IBD): Ulcerative colitis (UC) and Crohn's disease (CD), represents a challenge in the early stages of the diseases. The diagnosis may be established several years after the debut of symptoms. Hence, protein biomarkers...... for early and accurate diagnostic could help clinicians improve treatment of the individual patients. Moreover, the biomarkers could aid physicians to predict disease courses and in this way, identify patients in need of intensive treatment. Patients with low risk of disease flares may avoid treatment...... with medications with the concomitant risk of adverse events. In addition, identification of disease and course specific biomarker profiles can be used to identify biological pathways involved in the disease development and treatment. Knowledge of disease mechanisms in general can lead to improved future...

  15. COPD Discovery Might Improve Treatment

    Science.gov (United States)

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

  16. 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.

  17. NEW TECHNIQUES USED IN AUTOMATED TEXT ANALYSIS

    Directory of Open Access Journals (Sweden)

    M. I strate

    2010-12-01

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

  18. The Automated Medical Office

    OpenAIRE

    Petreman, Mel

    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...

  19. 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.

  20. 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.

  1. Potential blood biomarkers for stroke.

    Science.gov (United States)

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

    2012-08-01

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

  2. 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...

  3. Biomarker Detection using PS2-Thioaptamers Project

    Data.gov (United States)

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

  4. 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.

  5. Opportunistic Adaptation Knowledge Discovery

    OpenAIRE

    Badra, Fadi; Cordier, Amélie; Lieber, Jean

    2009-01-01

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

  6. Discovery with FAST

    Science.gov (United States)

    Wilkinson, P.

    2016-02-01

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

  7. 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.

  8. Personalized medicine using DNA biomarkers: a review

    OpenAIRE

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

    2012-01-01

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

  9. Push-through direct injection NMR: an optimized automation method applied to metabolomics

    Science.gov (United States)

    There is a pressing need to increase the throughput of NMR analysis in fields such as metabolomics and drug discovery. Direct injection (DI) NMR automation is recognized to have the potential to meet this need due to its suitability for integration with the 96-well plate format. ...

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

    Directory of Open Access Journals (Sweden)

    Niels Lion

    2010-11-01

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

  11. Biomarker analysis of stored blood products: emphasis on pre-analytical issues.

    Science.gov (United States)

    Delobel, Julien; Rubin, Olivier; Prudent, Michel; Crettaz, David; Tissot, Jean-Daniel; Lion, Niels

    2010-01-01

    Millions of blood products are transfused every year; many lives are thus directly concerned by transfusion. The three main labile blood products used in transfusion are erythrocyte concentrates, platelet concentrates and fresh frozen plasma. Each of these products has to be stored according to its particular components. However, during storage, modifications or degradation of those components may occur, and are known as storage lesions. Thus, biomarker discovery of in vivo blood aging as well as in vitro labile blood products storage lesions is of high interest for the transfusion medicine community. Pre-analytical issues are of major importance in analyzing the various blood products during storage conditions as well as according to various protocols that are currently used in blood banks for their preparations. This paper will review key elements that have to be taken into account in the context of proteomic-based biomarker discovery applied to blood banking. PMID:21151459

  12. Biomarkers of brain injury in the premature infant

    Directory of Open Access Journals (Sweden)

    Martha V. Douglas-Escobar

    2013-01-01

    Full Text Available The term encephalopathy of prematurity encompasses not only the acute brain injury (such as intraventricular hemorrhage but also complex disturbance on the infant’s subsequent brain development. In premature infants, the most frequent recognized source of brain injury is intraventricular hemorrhage (IVH and periventricular leukomalacia (PVL. Furthermore 20-25% infants with birth weigh less than 1,500 g will have IVH and that proportion increases to 45% if the birth weight is less than 500-750 g. In addition, nearly 60% of very low birth weight newborns will have hypoxic-ischemic injury. Therefore permanent lifetime neurodevelopmental disabilities are frequent in premature infants. Innovative approach to prevent or decrease brain injury in preterm infants requires discovery of biomarkers able to discriminate infants at risk for injury, monitor the progression of the injury and assess efficacy of neuroprotective clinical trials. In this article, we will review biomarkers studied in premature infants with IVH, Post-hemorrhagic ventricular dilation (PHVD and PVL including: S100b, Activin A, erythropoietin, chemokine CCL 18, GFAP and NFL will also be examined. Some of the most promising biomarkers for IVH are S100β and Activin. The concentrations of TGF-β1, MMP-9 and PAI-1 in cerebrospinal fluid could be used to discriminate patients that will require shunt after post-hemorrhagic ventricular dilation. Neonatal brain injury is frequent in premature infants admitted to the neonatal intensive care and we hope to contribute to the awareness and interest in clinical validation of established as well as novel neonatal brain injury biomarkers.

  13. Biomarkers of brain injury in the premature infant.

    Science.gov (United States)

    Douglas-Escobar, Martha; Weiss, Michael D

    2012-01-01

    The term "encephalopathy of prematurity" encompasses not only the acute brain injury [such as intraventricular hemorrhage (IVH)] but also complex disturbance on the infant's subsequent brain development. In premature infants, the most frequent recognized source of brain injury is IVH and periventricular leukomalacia (PVL). Furthermore 20-25% infants with birth weigh less than 1,500 g will have IVH and that proportion increases to 45% if the birth weight is less than 500-750 g. In addition, nearly 60% of very low birth weight newborns will have hypoxic-ischemic injury. Therefore permanent lifetime neurodevelopmental disabilities are frequent in premature infants. Innovative approach to prevent or decrease brain injury in preterm infants requires discovery of biomarkers able to discriminate infants at risk for injury, monitor the progression of the injury, and assess efficacy of neuroprotective clinical trials. In this article, we will review biomarkers studied in premature infants with IVH, Post-hemorrhagic ventricular dilation (PHVD), and PVL including: S100b, Activin A, erythropoietin, chemokine CCL 18, GFAP, and NFL will also be examined. Some of the most promising biomarkers for IVH are S100β and Activin. The concentrations of TGF-β1, MMP-9, and PAI-1 in cerebrospinal fluid could be used to discriminate patients that will require shunt after PHVD. Neonatal brain injury is frequent in premature infants admitted to the neonatal intensive care and we hope to contribute to the awareness and interest in clinical validation of established as well as novel neonatal brain injury biomarkers.

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

    International Nuclear Information System (INIS)

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

  15. Biomarkers in sarcoidosis: a review

    Directory of Open Access Journals (Sweden)

    Ahmadzai H

    2014-08-01

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

  16. Biomarkers of satiation and satiety

    NARCIS (Netherlands)

    Graaf, C. de; Blom, W.A.M.; Smeets, P.A.M.; Stafleu, A.; Hendriks, H.F.J.

    2004-01-01

    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

  17. Biomarkers of replicative senescence revisited

    DEFF Research Database (Denmark)

    Nehlin, Jan

    2016-01-01

    of telomere length and associated damage, and the accompanying changes that take place elicit signals that have an impact on a number of molecules and downstream events. Precise measurements of replicative senescence biomarkers in biological samples from individuals could be clinically associated...

  18. Automation in organizations: Eternal conflict

    Science.gov (United States)

    Dieterly, D. L.

    1981-01-01

    Some ideas on and insights into the problems associated with automation in organizations are presented with emphasis on the concept of automation, its relationship to the individual, and its impact on system performance. An analogy is drawn, based on an American folk hero, to emphasize the extent of the problems encountered when dealing with automation within an organization. A model is proposed to focus attention on a set of appropriate dimensions. The function allocation process becomes a prominent aspect of the model. The current state of automation research is mentioned in relation to the ideas introduced. Proposed directions for an improved understanding of automation's effect on the individual's efficiency are discussed. The importance of understanding the individual's perception of the system in terms of the degree of automation is highlighted.

  19. Automated Assessment, Face to Face

    OpenAIRE

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

    2010-01-01

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

  20. Automation System Products and Research

    OpenAIRE

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

    2014-01-01

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

  1. Test Automation of Online Games

    OpenAIRE

    Schoenfeldt, Alexander

    2015-01-01

    State of the art browser games are increasingly complex pieces of software with extensive code basis. With increasing complexity, a software becomes harder to maintain. Automated regression testing can simplify these maintenance processes and thereby enable developers as well as testers to spend their workforce more efficiently. This thesis addresses the utilization of automated tests in web applications. As a use case test automation is applied to an online-based strategy game for the bro...

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

    OpenAIRE

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

    2016-01-01

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

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

    OpenAIRE

    Vincent Renaud; Kumarathasan Premkumari; Karthikeyan Subramanian

    2008-01-01

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

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

    OpenAIRE

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

    2015-01-01

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

  5. 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.

  6. Mechatronic Design Automation

    DEFF Research Database (Denmark)

    Fan, Zhun

    This book proposes a novel design method that combines both genetic programming (GP) to automatically explore the open-ended design space and bond graphs (BG) to unify design representations of multi-domain Mechatronic systems. Results show that the method, formally called GPBG method, can...... 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...

  7. The automated medical office.

    Science.gov (United States)

    Petreman, M

    1990-08-01

    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 clinic shows that practical thinking linked to advanced technology can greatly improve office efficiency.

  8. AUTOMATED API TESTING APPROACH

    Directory of Open Access Journals (Sweden)

    SUNIL L. BANGARE

    2012-02-01

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

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

    Directory of Open Access Journals (Sweden)

    Hung-Chung Huang

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

  10. Omic approaches to quality biomarkers for stored platelets: are we there yet?

    Science.gov (United States)

    Kulkarni, Sandhya; Kannan, Meganathan; Atreya, Chintamani D

    2010-07-01

    At present, there is no single biomarker that serves as the "gold standard" predictive of the quality of stored platelets used for transfusion. Some of the measurable features of platelets such as morphology, biochemical status, physiologic response to osmotic stress and agonist-induced changes, and measurement of process-associated activation indicators of platelets are considered useful in assessing the in vitro quality of stored platelets. Such in vitro measurements combined with in vivo survival estimations using radiolabeled platelets in healthy volunteers provide reasonable estimates of in vivo platelet function after transfusion. Thus, the current practice of estimating the quality and functional aspects of ex vivo stored platelets involves utilization of a battery of tests that dates back to pre-omic era. On the other hand, during the last decade, seminal discoveries have been made in platelet molecular and cell biology by using "omic"-based approaches such as proteomics, genomics, and transcriptomics. Can we mobilize some of these discoveries toward developing reliable quality biomarkers for stored platelets? To address this topic, we briefly review current practices and provide insights into some of the omic approaches that could be helpful in identifying quality storage biomarkers of platelets in the near future. We also briefly discuss here some of the challenges in using proteomic approaches and advantages of using one of the transcriptomics approaches toward platelet biomarker development.

  11. Potentials of single-cell biology in identification and validation of disease biomarkers.

    Science.gov (United States)

    Niu, Furong; Wang, Diane C; Lu, Jiapei; Wu, Wei; Wang, Xiangdong

    2016-09-01

    Single-cell biology is considered a new approach to identify and validate disease-specific biomarkers. However, the concern raised by clinicians is how to apply single-cell measurements for clinical practice, translate the message of single-cell systems biology into clinical phenotype or explain alterations of single-cell gene sequencing and function in patient response to therapies. This study is to address the importance and necessity of single-cell gene sequencing in the identification and development of disease-specific biomarkers, the definition and significance of single-cell biology and single-cell systems biology in the understanding of single-cell full picture, the development and establishment of whole-cell models in the validation of targeted biological function and the figure and meaning of single-molecule imaging in single cell to trace intra-single-cell molecule expression, signal, interaction and location. We headline the important role of single-cell biology in the discovery and development of disease-specific biomarkers with a special emphasis on understanding single-cell biological functions, e.g. mechanical phenotypes, single-cell biology, heterogeneity and organization of genome function. We have reason to believe that such multi-dimensional, multi-layer, multi-crossing and stereoscopic single-cell biology definitely benefits the discovery and development of disease-specific biomarkers.

  12. World-wide distribution automation systems

    Energy Technology Data Exchange (ETDEWEB)

    Devaney, T.M.

    1994-12-31

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

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

    OpenAIRE

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

    2013-01-01

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

  14. Automation from pictures

    International Nuclear Information System (INIS)

    The state transition diagram (STD) model has been helpful in the design of real time software, especially with the emergence of graphical computer aided software engineering (CASE) tools. Nevertheless, the translation of the STD to real time code has in the past been primarily a manual task. At Los Alamos we have automated this process. The designer constructs the STD using a CASE tool (Cadre Teamwork) using a special notation for events and actions. A translator converts the STD into an intermediate state notation language (SNL), and this SNL is compiled directly into C code (a state program). Execution of the state program is driven by external events, allowing multiple state programs to effectively share the resources of the host processor. Since the design and the code are tightly integrated through the CASE tool, the design and code never diverge, and we avoid design obsolescence. Furthermore, the CASE tool automates the production of formal technical documents from the graphic description encapsulated by the CASE tool. (author)

  15. Automated Test Case Generation

    CERN Document Server

    CERN. Geneva

    2015-01-01

    I would like to present the concept of automated test case generation. I work on it as part of my PhD and I think it would be interesting also for other people. It is also the topic of a workshop paper that I am introducing in Paris. (abstract below) Please note that the talk itself would be more general and not about the specifics of my PhD, but about the broad field of Automated Test Case Generation. I would introduce the main approaches (combinatorial testing, symbolic execution, adaptive random testing) and their advantages and problems. (oracle problem, combinatorial explosion, ...) Abstract of the paper: Over the last decade code-based test case generation techniques such as combinatorial testing or dynamic symbolic execution have seen growing research popularity. Most algorithms and tool implementations are based on finding assignments for input parameter values in order to maximise the execution branch coverage. Only few of them consider dependencies from outside the Code Under Test’s scope such...

  16. Automated Postediting of Documents

    CERN Document Server

    Knight, K; Knight, Kevin; Chander, Ishwar

    1994-01-01

    Large amounts of low- to medium-quality English texts are now being produced by machine translation (MT) systems, optical character readers (OCR), and non-native speakers of English. Most of this text must be postedited by hand before it sees the light of day. Improving text quality is tedious work, but its automation has not received much research attention. Anyone who has postedited a technical report or thesis written by a non-native speaker of English knows the potential of an automated postediting system. For the case of MT-generated text, we argue for the construction of postediting modules that are portable across MT systems, as an alternative to hardcoding improvements inside any one system. As an example, we have built a complete self-contained postediting module for the task of article selection (a, an, the) for English noun phrases. This is a notoriously difficult problem for Japanese-English MT. Our system contains over 200,000 rules derived automatically from online text resources. We report on l...

  17. Maneuver Automation Software

    Science.gov (United States)

    Uffelman, Hal; Goodson, Troy; Pellegrin, Michael; Stavert, Lynn; Burk, Thomas; Beach, David; Signorelli, Joel; Jones, Jeremy; Hahn, Yungsun; Attiyah, Ahlam; Illsley, Jeannette

    2009-01-01

    The Maneuver Automation Software (MAS) automates the process of generating commands for maneuvers to keep the spacecraft of the Cassini-Huygens mission on a predetermined prime mission trajectory. Before MAS became available, a team of approximately 10 members had to work about two weeks to design, test, and implement each maneuver in a process that involved running many maneuver-related application programs and then serially handing off data products to other parts of the team. MAS enables a three-member team to design, test, and implement a maneuver in about one-half hour after Navigation has process-tracking data. MAS accepts more than 60 parameters and 22 files as input directly from users. MAS consists of Practical Extraction and Reporting Language (PERL) scripts that link, sequence, and execute the maneuver- related application programs: "Pushing a single button" on a graphical user interface causes MAS to run navigation programs that design a maneuver; programs that create sequences of commands to execute the maneuver on the spacecraft; and a program that generates predictions about maneuver performance and generates reports and other files that enable users to quickly review and verify the maneuver design. MAS can also generate presentation materials, initiate electronic command request forms, and archive all data products for future reference.

  18. Meeting Report--NASA Radiation Biomarker Workshop

    Energy Technology Data Exchange (ETDEWEB)

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

    2008-05-01

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

  19. Oral Fluids that Detect Cardiovascular Disease Biomarkers

    Science.gov (United States)

    Foley, Joseph D.; Sneed, J. Darrell; Steinhubl, Steven R; Kolasa, Justin; Ebersole, Jeffrey L.; Lin, Yushun; Kryscio, Richard J.; McDevitt, John T.; Campbell, Charles L.; Miller, Craig S.

    2013-01-01

    Objective To determine the utility of oral fluids for assessment of coronary and cardiovascular (CVD) health. Study Design Twenty-nine patients with pre-existing CVD disease underwent an invasive cardiac procedure (alcohol septal ablation or percutaneous coronary intervention) and provided unstimulated whole saliva (UWS), sublingual swabs (LS), gingival swabs (GS) and serum at 0, 8, 16, 24, 48 hr. Concentrations of 13 relevant biomarkers were determined and correlated with levels in serum and the oral fluids. Results Concentrations of the majority of biomarkers were higher in UWS than LS and GS. Coronary and CVD disease biomarkers in UWS correlated better with serum than LS and GS based on group status and measures of time effect. Seven biomarkers demonstrated time effect changes consistent with serum biomarkers, including C-reactive protein and troponin I. Conclusions Changes in serum biomarker profiles are reflected in oral fluids suggesting that oral fluid biomarkers could aid in the assessment of cardiac ischemia/necrosis. PMID:22769406

  20. Get smart! automate your house!

    NARCIS (Netherlands)

    Van Amstel, P.; Gorter, N.; De Rouw, J.

    2016-01-01

    This "designers' manual" is made during the TIDO-course AR0531 Innovation and Sustainability This manual will help you in reducing both energy usage and costs by automating your home. It gives an introduction to a number of home automation systems that every homeowner can install.

  1. Automated Methods Of Corrosion Measurements

    DEFF Research Database (Denmark)

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

    1997-01-01

    The chapter describes the following automated measurements: Corrosion Measurements by Titration, Imaging Corrosion by Scanning Probe Microscopy, Critical Pitting Temperature and Application of the Electrochemical Hydrogen Permeation Cell.......The chapter describes the following automated measurements: Corrosion Measurements by Titration, Imaging Corrosion by Scanning Probe Microscopy, Critical Pitting Temperature and Application of the Electrochemical Hydrogen Permeation Cell....

  2. Automated separation for heterogeneous immunoassays

    OpenAIRE

    Truchaud, A.; Barclay, J; Yvert, J. P.; Capolaghi, B.

    1991-01-01

    Beside general requirements for modern automated systems, immunoassay automation involves specific requirements as a separation step for heterogeneous immunoassays. Systems are designed according to the solid phase selected: dedicated or open robots for coated tubes and wells, systems nearly similar to chemistry analysers in the case of magnetic particles, and a completely original design for those using porous and film materials.

  3. Automated Test-Form Generation

    Science.gov (United States)

    van der Linden, Wim J.; Diao, Qi

    2011-01-01

    In automated test assembly (ATA), the methodology of mixed-integer programming is used to select test items from an item bank to meet the specifications for a desired test form and optimize its measurement accuracy. The same methodology can be used to automate the formatting of the set of selected items into the actual test form. Three different…

  4. Translation: Aids, Robots, and Automation.

    Science.gov (United States)

    Andreyewsky, Alexander

    1981-01-01

    Examines electronic aids to translation both as ways to automate it and as an approach to solve problems resulting from shortage of qualified translators. Describes the limitations of robotic MT (Machine Translation) systems, viewing MAT (Machine-Aided Translation) as the only practical solution and the best vehicle for further automation. (MES)

  5. Opening up Library Automation Software

    Science.gov (United States)

    Breeding, Marshall

    2009-01-01

    Throughout the history of library automation, the author has seen a steady advancement toward more open systems. In the early days of library automation, when proprietary systems dominated, the need for standards was paramount since other means of inter-operability and data exchange weren't possible. Today's focus on Application Programming…

  6. Biomarkers in acute lung injury.

    Science.gov (United States)

    Mokra, Daniela; Kosutova, Petra

    2015-04-01

    Acute respiratory distress syndrome (ARDS) and its milder form acute lung injury (ALI) may result from various diseases and situations including sepsis, pneumonia, trauma, acute pancreatitis, aspiration of gastric contents, near-drowning etc. ALI/ARDS is characterized by diffuse alveolar injury, lung edema formation, neutrophil-derived inflammation, and surfactant dysfunction. Clinically, ALI/ARDS is manifested by decreased lung compliance, severe hypoxemia, and bilateral pulmonary infiltrates. Severity and further characteristics of ALI/ARDS may be detected by biomarkers in the plasma and bronchoalveolar lavage fluid (or tracheal aspirate) of patients. Changed concentrations of individual markers may suggest injury or activation of the specific types of lung cells-epithelial or endothelial cells, neutrophils, macrophages, etc.), and thereby help in diagnostics and in evaluation of the patient's clinical status and the treatment efficacy. This chapter reviews various biomarkers of acute lung injury and evaluates their usefulness in diagnostics and prognostication of ALI/ARDS.

  7. Genetic biomarkers in hypertrophic cardiomyopathy.

    Science.gov (United States)

    Coats, Caroline J; Elliott, Perry M

    2013-08-01

    Hypertrophic cardiomyopathy is a common inherited heart muscle disorder associated with sudden cardiac death, arrhythmias and heart failure. Genetic mutations can be identified in approximately 60% of patients; these are commonest in genes that encode proteins of the cardiac sarcomere. Similar to other Mendelian diseases these mutations are characterized by incomplete penetrance and variable clinical expression. Our knowledge of this genetic diversity is rapidly evolving as high-throughput DNA sequencing technology is now used to characterize an individual patient's disease. In addition, the genomic basis of several multisystem diseases associated with a hypertrophic cardiomyopathy phenotype has been elucidated. Genetic biomarkers can be helpful in making an accurate diagnosis and in identifying relatives at risk of developing the condition. In the clinical setting, genetic testing and genetic screening should be used pragmatically with appropriate counseling. Here we review the current role of genetic biomarkers in hypertrophic cardiomyopathy, highlight recent progress in the field and discuss future challenges.

  8. Chronic Obstructive Pulmonary Disease Biomarkers

    Directory of Open Access Journals (Sweden)

    Tatsiana Beiko

    2016-04-01

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

  9. Automating expert role to determine design concept in Kansei Engineering

    Science.gov (United States)

    Lokman, Anitawati Mohd; Haron, Mohammad Bakri Che; Abidin, Siti Zaleha Zainal; Khalid, Noor Elaiza Abd

    2016-02-01

    Affect has become imperative in product quality. In affective design field, Kansei Engineering (KE) has been recognized as a technology that enables discovery of consumer's emotion and formulation of guide to design products that win consumers in the competitive market. Albeit powerful technology, there is no rule of thumb in its analysis and interpretation process. KE expertise is required to determine sets of related Kansei and the significant concept of emotion. Many research endeavors become handicapped with the limited number of available and accessible KE experts. This work is performed to simulate the role of experts with the use of Natphoric algorithm thus providing sound solution to the complexity and flexibility in KE. The algorithm is designed to learn the process by implementing training datasets taken from previous KE research works. A framework for automated KE is then designed to realize the development of automated KE system. A comparative analysis is performed to determine feasibility of the developed prototype to automate the process. The result shows that the significant Kansei is determined by manual KE implementation and the automated process is highly similar. KE research advocates will benefit this system to automatically determine significant design concepts.

  10. Representation Discovery using Harmonic Analysis

    CERN Document Server

    Mahadevan, Sridhar

    2008-01-01

    Representations are at the heart of artificial intelligence (AI). This book is devoted to the problem of representation discovery: how can an intelligent system construct representations from its experience? Representation discovery re-parameterizes the state space - prior to the application of information retrieval, machine learning, or optimization techniques - facilitating later inference processes by constructing new task-specific bases adapted to the state space geometry. This book presents a general approach to representation discovery using the framework of harmonic analysis, in particu

  11. Finding good biomarkers for sarcopenia

    OpenAIRE

    Scharf, Gesine; Heineke, Joerg

    2012-01-01

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

  12. Cardiac Biomarkers in Hyperthyroid Cats

    OpenAIRE

    Sangster, Jodi Kirsten

    2013-01-01

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

  13. Cardiac Biomarkers in Hyperthyroid Cats

    OpenAIRE

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

    2013-01-01

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

  14. Salivary biomarkers in psychobiological medicine

    OpenAIRE

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

    2006-01-01

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

  15. Denton Vacuum Discovery-550 Sputterer

    Data.gov (United States)

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

  16. Optogenetics enlightens neuroscience drug discovery.

    Science.gov (United States)

    Song, Chenchen; Knöpfel, Thomas

    2016-02-01

    Optogenetics - the use of light and genetics to manipulate and monitor the activities of defined cell populations - has already had a transformative impact on basic neuroscience research. Now, the conceptual and methodological advances associated with optogenetic approaches are providing fresh momentum to neuroscience drug discovery, particularly in areas that are stalled on the concept of 'fixing the brain chemistry'. Optogenetics is beginning to translate and transit into drug discovery in several key domains, including target discovery, high-throughput screening and novel therapeutic approaches to disease states. Here, we discuss the exciting potential of optogenetic technologies to transform neuroscience drug discovery.

  17. Analytical validation considerations of multiplex mass-spectrometry-based proteomic platforms for measuring protein biomarkers.

    Science.gov (United States)

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

    2014-12-01

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

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

    Directory of Open Access Journals (Sweden)

    Laura Moreno

    2015-03-01

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

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

    Science.gov (United States)

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

  20. Update on biomarkers in systemic sclerosis: tools for diagnosis and treatment.

    Science.gov (United States)

    Affandi, Alsya J; Radstake, Timothy R D J; Marut, Wioleta

    2015-09-01

    Systemic sclerosis (SSc) is a complex autoimmune disease in which immune activation, vasculopathy, and extensive fibrosis of the skin and internal organs are among the principal features. SSc is a heterogeneous disease with varying manifestations and clinical outcomes. Currently, patients' clinical evaluation often relies on subjective measures, non-quantitative methods, or requires invasive procedures as markers able to predict disease trajectory or response to therapy are lacking. Therefore, current research is focusing on the discovery of useful biomarkers reflecting ongoing inflammatory or fibrotic activity in the skin and internal organs, as well as being predictive of future disease course. Recently, remarkable progress has been made towards a better understanding of numerous mechanisms involved in the pathogenesis of SSc. This has opened new possibilities for the development of novel biomarkers and therapy. However, current proposed biomarkers that could reliably describe various aspects of SSc still require further investigation. This review will summarize studies describing the commonly used and validated biomarkers, the newly emerging and promising SSc biomarkers identified to date, and consideration of future directions in this field.

  1. Melody-based knowledge discovery in musical pieces

    Science.gov (United States)

    Rybnik, Mariusz; Jastrzebska, Agnieszka

    2016-06-01

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

  2. Perspective: Data infrastructure for high throughput materials discovery

    Science.gov (United States)

    Pfeif, E. A.; Kroenlein, K.

    2016-05-01

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

  3. Dietary biomarkers: advances, limitations and future directions

    Directory of Open Access Journals (Sweden)

    Hedrick Valisa E

    2012-12-01

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

  4. Robust automated knowledge capture.

    Energy Technology Data Exchange (ETDEWEB)

    Stevens-Adams, Susan Marie; Abbott, Robert G.; Forsythe, James Chris; Trumbo, Michael Christopher Stefan; Haass, Michael Joseph; Hendrickson, Stacey M. Langfitt

    2011-10-01

    This report summarizes research conducted through the Sandia National Laboratories Robust Automated Knowledge Capture Laboratory Directed Research and Development project. The objective of this project was to advance scientific understanding of the influence of individual cognitive attributes on decision making. The project has developed a quantitative model known as RumRunner that has proven effective in predicting the propensity of an individual to shift strategies on the basis of task and experience related parameters. Three separate studies are described which have validated the basic RumRunner model. This work provides a basis for better understanding human decision making in high consequent national security applications, and in particular, the individual characteristics that underlie adaptive thinking.

  5. Automated Electrostatics Environmental Chamber

    Science.gov (United States)

    Calle, Carlos; Lewis, Dean C.; Buchanan, Randy K.; Buchanan, Aubri

    2005-01-01

    The Mars Electrostatics Chamber (MEC) is an environmental chamber designed primarily to create atmospheric conditions like those at the surface of Mars to support experiments on electrostatic effects in the Martian environment. The chamber is equipped with a vacuum system, a cryogenic cooling system, an atmospheric-gas replenishing and analysis system, and a computerized control system that can be programmed by the user and that provides both automation and options for manual control. The control system can be set to maintain steady Mars-like conditions or to impose temperature and pressure variations of a Mars diurnal cycle at any given season and latitude. In addition, the MEC can be used in other areas of research because it can create steady or varying atmospheric conditions anywhere within the wide temperature, pressure, and composition ranges between the extremes of Mars-like and Earth-like conditions.

  6. Automated Standard Hazard Tool

    Science.gov (United States)

    Stebler, Shane

    2014-01-01

    The current system used to generate standard hazard reports is considered cumbersome and iterative. This study defines a structure for this system's process in a clear, algorithmic way so that standard hazard reports and basic hazard analysis may be completed using a centralized, web-based computer application. To accomplish this task, a test server is used to host a prototype of the tool during development. The prototype is configured to easily integrate into NASA's current server systems with minimal alteration. Additionally, the tool is easily updated and provides NASA with a system that may grow to accommodate future requirements and possibly, different applications. Results of this project's success are outlined in positive, subjective reviews complete by payload providers and NASA Safety and Mission Assurance personnel. Ideally, this prototype will increase interest in the concept of standard hazard automation and lead to the full-scale production of a user-ready application.

  7. Automated synthetic scene generation

    Science.gov (United States)

    Givens, Ryan N.

    Physics-based simulations generate synthetic imagery to help organizations anticipate system performance of proposed remote sensing systems. However, manually constructing synthetic scenes which are sophisticated enough to capture the complexity of real-world sites can take days to months depending on the size of the site and desired fidelity of the scene. This research, sponsored by the Air Force Research Laboratory's Sensors Directorate, successfully developed an automated approach to fuse high-resolution RGB imagery, lidar data, and hyperspectral imagery and then extract the necessary scene components. The method greatly reduces the time and money required to generate realistic synthetic scenes and developed new approaches to improve material identification using information from all three of the input datasets.

  8. Magnetite as a prokaryotic biomarker: A review

    Science.gov (United States)

    Jimenez-Lopez, Concepcion; Romanek, Christopher S.; Bazylinski, Dennis A.

    2010-06-01

    Over the years, nanometer-sized magnetite (Fe3O4) crystals have been recovered from many modern and ancient environments including sediments and soils and even meteorites. In some cases these crystals have been used as "magnetofossils" for evidence of the past presence of specific microbes. Magnetite nanocrystals can be formed by a number of different biological and inorganic mechanisms resulting in crystals with different physical and magnetic characteristics. Prokaryotes (bacteria) biomineralize magnetite through two methods that differ mechanistically, including: biologically induced mineralization (BIM) and biologically controlled mineralization (BCM). Magnetite nanocrystals produced by BIM are known to be synthesized by the dissimilatory iron-reducing bacteria, are deposited external to the cell, and generally are physically indistinguishable from magnetite particles formed inorganically. BCM magnetites, in contrast, are synthesized by the magnetotactic bacteria and some higher organisms and are precipitated intracellularly as membrane-bounded structures called magnetosomes. These magnetites appear to have unique crystal morphologies and a narrow size range leading to their original use as magnetofossils. Because of the discovery of nanometer-sized crystals of magnetite in the Martian meteorite ALH84001, the use of these criteria for the determination of whether magnetite crystals could constitute a prokaryotic biomarker was questioned. Thus, there is currently great debate over what criteria to use in the determination of whether specific magnetite crystals are biogenic or not. In the last decade, additional criteria have been established (e.g., the Magnetite Assay for Biogenicity), and new tools and technologies have been developed to determine the origin of specific types of magnetite crystals.

  9. Machine-assisted discovery of relationships in astronomy

    CERN Document Server

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

    2013-01-01

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

  10. Automated Essay Scoring

    Directory of Open Access Journals (Sweden)

    Semire DIKLI

    2006-01-01

    Full Text Available Automated Essay Scoring Semire DIKLI Florida State University Tallahassee, FL, USA ABSTRACT The impacts of computers on writing have been widely studied for three decades. Even basic computers functions, i.e. word processing, have been of great assistance to writers in modifying their essays. The research on Automated Essay Scoring (AES has revealed that computers have the capacity to function as a more effective cognitive tool (Attali, 2004. AES is defined as the computer technology that evaluates and scores the written prose (Shermis & Barrera, 2002; Shermis & Burstein, 2003; Shermis, Raymat, & Barrera, 2003. Revision and feedback are essential aspects of the writing process. Students need to receive feedback in order to increase their writing quality. However, responding to student papers can be a burden for teachers. Particularly if they have large number of students and if they assign frequent writing assignments, providing individual feedback to student essays might be quite time consuming. AES systems can be very useful because they can provide the student with a score as well as feedback within seconds (Page, 2003. Four types of AES systems, which are widely used by testing companies, universities, and public schools: Project Essay Grader (PEG, Intelligent Essay Assessor (IEA, E-rater, and IntelliMetric. AES is a developing technology. Many AES systems are used to overcome time, cost, and generalizability issues in writing assessment. The accuracy and reliability of these systems have been proven to be high. The search for excellence in machine scoring of essays is continuing and numerous studies are being conducted to improve the effectiveness of the AES systems.

  11. Interpretation of a discovery

    Directory of Open Access Journals (Sweden)

    Vučković Vladan

    2006-01-01

    Full Text Available The paper presents the development of the theory of asynchronous motors since Tesla’s discovery until the present day. The theory of steady state, as we know it today, was completed already during the first dozen of years. That was followed by a period of stagnation during a number of decades, when the theory of asynchronous motors was developed only in the framework of the general theory of electric machines, which was stimulated by the problems of the development of synchronous generators and big electric networks. It is only in our time that this simple motor, which was used for a long time just to perform crude tasks, became again the inspiration for the researchers and engineers who enabled it, with the help of power electronics and semi-conductor technology, to be used in the finest drives.

  12. Automating the radiographic NDT process

    International Nuclear Information System (INIS)

    Automation, the removal of the human element in inspection, has not been generally applied to film radiographic NDT. The justication for automating is not only productivity but also reliability of results. Film remains in the automated system of the future because of its extremely high image content, approximately 8 x 109 bits per 14 x 17. The equivalent to 2200 computer floppy discs. Parts handling systems and robotics applied for manufacturing and some NDT modalities, should now be applied to film radiographic NDT systems. Automatic film handling can be achieved with the daylight NDT film handling system. Automatic film processing is becoming the standard in industry and can be coupled to the daylight system. Robots offer the opportunity to automate fully the exposure step. Finally, computer aided interpretation appears on the horizon. A unit which laser scans a 14 x 17 (inch) film in 6 - 8 seconds can digitize film information for further manipulation and possible automatic interrogations (computer aided interpretation). The system called FDRS (for Film Digital Radiography System) is moving toward 50 micron (*approx* 16 lines/mm) resolution. This is believed to meet the need of the majority of image content needs. We expect the automated system to appear first in parts (modules) as certain operations are automated. The future will see it all come together in an automated film radiographic NDT system (author)

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

    Science.gov (United States)

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

    2016-01-01

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

  14. Molecular biomarkers for grass pollen immunotherapy.

    Science.gov (United States)

    Popescu, Florin-Dan

    2014-03-26

    Grass pollen allergy represents a significant cause of allergic morbidity worldwide. Component-resolved diagnosis biomarkers are increasingly used in allergy practice in order to evaluate the sensitization to grass pollen allergens, allowing the clinician to confirm genuine sensitization to the corresponding allergen plant sources and supporting an accurate prescription of allergy immunotherapy (AIT), an important approach in many regions of the world with great plant biodiversity and/or where pollen seasons may overlap. The search for candidate predictive biomarkers for grass pollen immunotherapy (tolerogenic dendritic cells and regulatory T cells biomarkers, serum blocking antibodies biomarkers, especially functional ones, immune activation and immune tolerance soluble biomarkers and apoptosis biomarkers) opens new opportunities for the early detection of clinical responders for AIT, for the follow-up of these patients and for the development of new allergy vaccines.

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

    Science.gov (United States)

    Mehta, Shyamal H; Adler, Charles H

    2016-01-01

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

  16. Discovery Learning Strategies in English

    Science.gov (United States)

    Singaravelu, G.

    2012-01-01

    The study substantiates that the effectiveness of Discovery Learning method in learning English Grammar for the learners at standard V. Discovery Learning is particularly beneficial for any student learning a second language. It promotes peer interaction and development of the language and the learning of concepts with content. Reichert and…

  17. Discoveries of isotopes by fission

    Indian Academy of Sciences (India)

    M Thoennessen

    2015-09-01

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

  18. Service discovery using Bloom filters

    NARCIS (Netherlands)

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

    2006-01-01

    A protocol to perform service discovery in adhoc networks is introduced in this paper. Attenuated Bloom filters are used to distribute services to nodes in the neighborhood and thus enable local service discovery. The protocol has been implemented in a discrete event simulator to investigate the beh

  19. Peripheral Blood Biomarkers in Idiopathic Pulmonary Fibrosis

    OpenAIRE

    Vij, Rekha; Noth, Imre

    2012-01-01

    In this article, we review the evidence for peripheral blood biomarkers in idiopathic pulmonary fibrosis (IPF), a life-threatening fibrotic lung disease of unknown etiology. We focus on selected biomarkers present in peripheral blood, as they are easy to obtain, can be measured longitudinally, and have the greatest likelihood of achieving clinical utility. This article concentrates on biomarkers with mechanistic plausibility that may be directly involved in the development of IPF, including K...

  20. Biomarkers of HIV-associated Cancer

    OpenAIRE

    Brian Thabile Flepisi; Patrick Bouic; Gerhard Sissolak; Bernd Rosenkranz

    2014-01-01

    Cancer biomarkers have provided great opportunities for improving the management of cancer patients by enhancing the efficiency of early detection, diagnosis, and efficacy of treatment. Every cell type has a unique molecular signature, referred to as biomarkers, which are identifiable characteristics such as levels or activities of a myriad of genes, proteins, or other molecular features. Biomarkers can facilitate the molecular definition of cancer, provide information about the course of can...