A novel microfluidic microplate as the next generation assay platform for enzyme linked immunoassays (ELISA).

PubMed

Kai, Junhai; Puntambekar, Aniruddha; Santiago, Nelson; Lee, Se Hwan; Sehy, David W; Moore, Victor; Han, Jungyoup; Ahn, Chong H

2012-11-07

In this work we introduce a novel microfluidic enzyme linked immunoassays (ELISA) microplate as the next generation assay platform for unparalleled assay performances. A combination of microfluidic technology with standard SBS-configured 96-well microplate architecture, in the form of microfluidic microplate technology, allows for the improvement of ELISA workflows, conservation of samples and reagents, improved reaction kinetics, and the ability to improve the sensitivity of the assay by multiple analyte loading. This paper presents the design and characterization of the microfluidic microplate, and its application in ELISA.

Thermotropic Liquid Crystal-Assisted Chemical and Biological Sensors

PubMed Central

Honaker, Lawrence W.; Usol’tseva, Nadezhda; Mann, Elizabeth K.

2017-01-01

In this review article, we analyze recent progress in the application of liquid crystal-assisted advanced functional materials for sensing biological and chemical analytes. Multiple research groups demonstrate substantial interest in liquid crystal (LC) sensing platforms, generating an increasing number of scientific articles. We review trends in implementing LC sensing techniques and identify common problems related to the stability and reliability of the sensing materials as well as to experimental set-ups. Finally, we suggest possible means of bridging scientific findings to viable and attractive LC sensor platforms. PMID:29295530

A Multimodal Deep Log-Based User Experience (UX) Platform for UX Evaluation

PubMed Central

Ali Khan, Wajahat; Hur, Taeho; Muhammad Bilal, Hafiz Syed; Ul Hassan, Anees; Lee, Sungyoung

2018-01-01

The user experience (UX) is an emerging field in user research and design, and the development of UX evaluation methods presents a challenge for both researchers and practitioners. Different UX evaluation methods have been developed to extract accurate UX data. Among UX evaluation methods, the mixed-method approach of triangulation has gained importance. It provides more accurate and precise information about the user while interacting with the product. However, this approach requires skilled UX researchers and developers to integrate multiple devices, synchronize them, analyze the data, and ultimately produce an informed decision. In this paper, a method and system for measuring the overall UX over time using a triangulation method are proposed. The proposed platform incorporates observational and physiological measurements in addition to traditional ones. The platform reduces the subjective bias and validates the user’s perceptions, which are measured by different sensors through objectification of the subjective nature of the user in the UX assessment. The platform additionally offers plug-and-play support for different devices and powerful analytics for obtaining insight on the UX in terms of multiple participants. PMID:29783712

A Multimodal Deep Log-Based User Experience (UX) Platform for UX Evaluation.

PubMed

Hussain, Jamil; Khan, Wajahat Ali; Hur, Taeho; Bilal, Hafiz Syed Muhammad; Bang, Jaehun; Hassan, Anees Ul; Afzal, Muhammad; Lee, Sungyoung

2018-05-18

The user experience (UX) is an emerging field in user research and design, and the development of UX evaluation methods presents a challenge for both researchers and practitioners. Different UX evaluation methods have been developed to extract accurate UX data. Among UX evaluation methods, the mixed-method approach of triangulation has gained importance. It provides more accurate and precise information about the user while interacting with the product. However, this approach requires skilled UX researchers and developers to integrate multiple devices, synchronize them, analyze the data, and ultimately produce an informed decision. In this paper, a method and system for measuring the overall UX over time using a triangulation method are proposed. The proposed platform incorporates observational and physiological measurements in addition to traditional ones. The platform reduces the subjective bias and validates the user's perceptions, which are measured by different sensors through objectification of the subjective nature of the user in the UX assessment. The platform additionally offers plug-and-play support for different devices and powerful analytics for obtaining insight on the UX in terms of multiple participants.

Multiplexed Colorimetric Solid-Phase Extraction

NASA Technical Reports Server (NTRS)

Gazda, Daniel B.; Fritz, James S.; Porter, Marc D.

2009-01-01

Multiplexed colorimetric solid-phase extraction (MC-SPE) is an extension of colorimetric solid-phase extraction (C-SPE) an analytical platform that combines colorimetric reagents, solid phase extraction, and diffuse reflectance spectroscopy to quantify trace analytes in water. In CSPE, analytes are extracted and complexed on the surface of an extraction membrane impregnated with a colorimetric reagent. The analytes are then quantified directly on the membrane surface using a handheld diffuse reflectance spectrophotometer. Importantly, the use of solid-phase extraction membranes as the matrix for impregnation of the colorimetric reagents creates a concentration factor that enables the detection of low concentrations of analytes in small sample volumes. In extending C-SPE to a multiplexed format, a filter holder that incorporates discrete analysis channels and a jig that facilitates the concurrent operation of multiple sample syringes have been designed, enabling the simultaneous determination of multiple analytes. Separate, single analyte membranes, placed in a readout cartridge create unique, analyte-specific addresses at the exit of each channel. Following sample exposure, the diffuse reflectance spectrum of each address is collected serially and the Kubelka-Munk function is used to quantify each water quality parameter via calibration curves. In a demonstration, MC-SPE was used to measure the pH of a sample and quantitate Ag(I) and Ni(II).

A highly efficient, high-throughput lipidomics platform for the quantitative detection of eicosanoids in human whole blood.

PubMed

Song, Jiao; Liu, Xuejun; Wu, Jiejun; Meehan, Michael J; Blevitt, Jonathan M; Dorrestein, Pieter C; Milla, Marcos E

2013-02-15

We have developed an ultra-performance liquid chromatography-multiple reaction monitoring/mass spectrometry (UPLC-MRM/MS)-based, high-content, high-throughput platform that enables simultaneous profiling of multiple lipids produced ex vivo in human whole blood (HWB) on treatment with calcium ionophore and its modulation with pharmacological agents. HWB samples were processed in a 96-well plate format compatible with high-throughput sample processing instrumentation. We employed a scheduled MRM (sMRM) method, with a triple-quadrupole mass spectrometer coupled to a UPLC system, to measure absolute amounts of 122 distinct eicosanoids using deuterated internal standards. In a 6.5-min run, we resolved and detected with high sensitivity (lower limit of quantification in the range of 0.4-460 pg) all targeted analytes from a very small HWB sample (2.5 μl). Approximately 90% of the analytes exhibited a dynamic range exceeding 1000. We also developed a tailored software package that dramatically sped up the overall data quantification and analysis process with superior consistency and accuracy. Matrix effects from HWB and precision of the calibration curve were evaluated using this newly developed automation tool. This platform was successfully applied to the global quantification of changes on all 122 eicosanoids in HWB samples from healthy donors in response to calcium ionophore stimulation. Copyright © 2012 Elsevier Inc. All rights reserved.

Detection of mercury(II) ions using colorimetric gold nanoparticles on paper-based analytical devices.

PubMed

Chen, Guan-Hua; Chen, Wei-Yu; Yen, Yu-Chun; Wang, Chia-Wei; Chang, Huan-Tsung; Chen, Chien-Fu

2014-07-15

An on-field colorimetric sensing strategy employing gold nanoparticles (AuNPs) and a paper-based analytical platform was investigated for mercury ion (Hg(2+)) detection at water sources. By utilizing thymine-Hg(2+)-thymine (T-Hg(2+)-T) coordination chemistry, label-free detection oligonucleotide sequences were attached to unmodified gold nanoparticles to provide rapid mercury ion sensing without complicated and time-consuming thiolated or other costly labeled probe preparation processes. Not only is this strategy's sensing mechanism specific toward Hg(2+), rather than other metal ions, but also the conformational change in the detection oligonucleotide sequences introduces different degrees of AuNP aggregation that causes the color of AuNPs to exhibit a mixture variance. To eliminate the use of sophisticated equipment and minimize the power requirement for data analysis and transmission, the color variance of multiple detection results were transferred and concentrated on cellulose-based paper analytical devices, and the data were subsequently transmitted for the readout and storage of results using cloud computing via a smartphone. As a result, a detection limit of 50 nM for Hg(2+) spiked pond and river water could be achieved. Furthermore, multiple tests could be performed simultaneously with a 40 min turnaround time. These results suggest that the proposed platform possesses the capability for sensitive and high-throughput on-site mercury pollution monitoring in resource-constrained settings.

A high-performance spatial database based approach for pathology imaging algorithm evaluation

PubMed Central

Wang, Fusheng; Kong, Jun; Gao, Jingjing; Cooper, Lee A.D.; Kurc, Tahsin; Zhou, Zhengwen; Adler, David; Vergara-Niedermayr, Cristobal; Katigbak, Bryan; Brat, Daniel J.; Saltz, Joel H.

2013-01-01

Background: Algorithm evaluation provides a means to characterize variability across image analysis algorithms, validate algorithms by comparison with human annotations, combine results from multiple algorithms for performance improvement, and facilitate algorithm sensitivity studies. The sizes of images and image analysis results in pathology image analysis pose significant challenges in algorithm evaluation. We present an efficient parallel spatial database approach to model, normalize, manage, and query large volumes of analytical image result data. This provides an efficient platform for algorithm evaluation. Our experiments with a set of brain tumor images demonstrate the application, scalability, and effectiveness of the platform. Context: The paper describes an approach and platform for evaluation of pathology image analysis algorithms. The platform facilitates algorithm evaluation through a high-performance database built on the Pathology Analytic Imaging Standards (PAIS) data model. Aims: (1) Develop a framework to support algorithm evaluation by modeling and managing analytical results and human annotations from pathology images; (2) Create a robust data normalization tool for converting, validating, and fixing spatial data from algorithm or human annotations; (3) Develop a set of queries to support data sampling and result comparisons; (4) Achieve high performance computation capacity via a parallel data management infrastructure, parallel data loading and spatial indexing optimizations in this infrastructure. Materials and Methods: We have considered two scenarios for algorithm evaluation: (1) algorithm comparison where multiple result sets from different methods are compared and consolidated; and (2) algorithm validation where algorithm results are compared with human annotations. We have developed a spatial normalization toolkit to validate and normalize spatial boundaries produced by image analysis algorithms or human annotations. The validated data were formatted based on the PAIS data model and loaded into a spatial database. To support efficient data loading, we have implemented a parallel data loading tool that takes advantage of multi-core CPUs to accelerate data injection. The spatial database manages both geometric shapes and image features or classifications, and enables spatial sampling, result comparison, and result aggregation through expressive structured query language (SQL) queries with spatial extensions. To provide scalable and efficient query support, we have employed a shared nothing parallel database architecture, which distributes data homogenously across multiple database partitions to take advantage of parallel computation power and implements spatial indexing to achieve high I/O throughput. Results: Our work proposes a high performance, parallel spatial database platform for algorithm validation and comparison. This platform was evaluated by storing, managing, and comparing analysis results from a set of brain tumor whole slide images. The tools we develop are open source and available to download. Conclusions: Pathology image algorithm validation and comparison are essential to iterative algorithm development and refinement. One critical component is the support for queries involving spatial predicates and comparisons. In our work, we develop an efficient data model and parallel database approach to model, normalize, manage and query large volumes of analytical image result data. Our experiments demonstrate that the data partitioning strategy and the grid-based indexing result in good data distribution across database nodes and reduce I/O overhead in spatial join queries through parallel retrieval of relevant data and quick subsetting of datasets. The set of tools in the framework provide a full pipeline to normalize, load, manage and query analytical results for algorithm evaluation. PMID:23599905

ToxPi Graphical User Interface 2.0: Dynamic exploration, visualization, and sharing of integrated data models.

PubMed

Marvel, Skylar W; To, Kimberly; Grimm, Fabian A; Wright, Fred A; Rusyn, Ivan; Reif, David M

2018-03-05

Drawing integrated conclusions from diverse source data requires synthesis across multiple types of information. The ToxPi (Toxicological Prioritization Index) is an analytical framework that was developed to enable integration of multiple sources of evidence by transforming data into integrated, visual profiles. Methodological improvements have advanced ToxPi and expanded its applicability, necessitating a new, consolidated software platform to provide functionality, while preserving flexibility for future updates. We detail the implementation of a new graphical user interface for ToxPi (Toxicological Prioritization Index) that provides interactive visualization, analysis, reporting, and portability. The interface is deployed as a stand-alone, platform-independent Java application, with a modular design to accommodate inclusion of future analytics. The new ToxPi interface introduces several features, from flexible data import formats (including legacy formats that permit backward compatibility) to similarity-based clustering to options for high-resolution graphical output. We present the new ToxPi interface for dynamic exploration, visualization, and sharing of integrated data models. The ToxPi interface is freely-available as a single compressed download that includes the main Java executable, all libraries, example data files, and a complete user manual from http://toxpi.org .

Single cell multiplexed assay for proteolytic activity using droplet microfluidics.

PubMed

Ng, Ee Xien; Miller, Miles A; Jing, Tengyang; Chen, Chia-Hung

2016-07-15

Cellular enzymes interact in a post-translationally regulated fashion to govern individual cell behaviors, yet current platform technologies are limited in their ability to measure multiple enzyme activities simultaneously in single cells. Here, we developed multi-color Förster resonance energy transfer (FRET)-based enzymatic substrates and use them in a microfluidics platform to simultaneously measure multiple specific protease activities from water-in-oil droplets that contain single cells. By integrating the microfluidic platform with a computational analytical method, Proteolytic Activity Matrix Analysis (PrAMA), we are able to infer six different protease activity signals from individual cells in a high throughput manner (~100 cells/experimental run). We characterized protease activity profiles at single cell resolution for several cancer cell lines including breast cancer cell line MDA-MB-231, lung cancer cell line PC-9, and leukemia cell line K-562 using both live-cell and in-situ cell lysis assay formats, with special focus on metalloproteinases important in metastasis. The ability to measure multiple proteases secreted from or expressed in individual cells allows us to characterize cell heterogeneity and has potential applications including systems biology, pharmacology, cancer diagnosis and stem cell biology. Copyright © 2016 Elsevier B.V. All rights reserved.

A survey on platforms for big data analytics.

PubMed

Singh, Dilpreet; Reddy, Chandan K

The primary purpose of this paper is to provide an in-depth analysis of different platforms available for performing big data analytics. This paper surveys different hardware platforms available for big data analytics and assesses the advantages and drawbacks of each of these platforms based on various metrics such as scalability, data I/O rate, fault tolerance, real-time processing, data size supported and iterative task support. In addition to the hardware, a detailed description of the software frameworks used within each of these platforms is also discussed along with their strengths and drawbacks. Some of the critical characteristics described here can potentially aid the readers in making an informed decision about the right choice of platforms depending on their computational needs. Using a star ratings table, a rigorous qualitative comparison between different platforms is also discussed for each of the six characteristics that are critical for the algorithms of big data analytics. In order to provide more insights into the effectiveness of each of the platform in the context of big data analytics, specific implementation level details of the widely used k-means clustering algorithm on various platforms are also described in the form pseudocode.

Single-indicator-based Multidimensional Sensing: Detection and Identification of Heavy Metal Ions and Understanding the Foundations from Experiment to Simulation

PubMed Central

Leng, Yumin; Qian, Sihua; Wang, Yuhui; Lu, Cheng; Ji, Xiaoxu; Lu, Zhiwen; Lin, Hengwei

2016-01-01

Multidimensional sensing offers advantages in accuracy, diversity and capability for the simultaneous detection and discrimination of multiple analytes, however, the previous reports usually require complicated synthesis/fabrication process and/or need a variety of techniques (or instruments) to acquire signals. Therefore, to take full advantages of this concept, simple designs are highly desirable. Herein, a novel concept is conceived to construct multidimensional sensing platforms based on a single indicator that has capability of showing diverse color/fluorescence responses with the addition of different analytes. Through extracting hidden information from these responses, such as red, green and blue (RGB) alterations, a triple-channel-based multidimensional sensing platform could consequently be fabricated, and the RGB alterations are further applicable to standard statistical methods. As a proof-of-concept study, a triple-channel sensing platform is fabricated solely using dithizone with assistance of cetyltrimethylammonium bromide (CTAB) for hyperchromicity and sensitization, which demonstrates superior capabilities in detection and identification of ten common heavy metal ions at their standard concentrations of wastewater-discharge of China. Moreover, this sensing platform exhibits promising applications in semi-quantitative and even quantitative analysis individuals of these heavy metal ions with high sensitivity as well. Finally, density functional theory calculations are performed to reveal the foundations for this analysis. PMID:27146105

A Versatile Integrated Ambient Ionization Source Platform.

PubMed

Ai, Wanpeng; Nie, Honggang; Song, Shiyao; Liu, Xiaoyun; Bai, Yu; Liu, Huwei

2018-04-30

The pursuit of high-throughput sample analysis from complex matrix demands development of multiple ionization techniques with complementary specialties. A versatile integrated ambient ionization source (iAmIS) platform is proposed in this work, based on the idea of integrating multiple functions, enhancing the efficiency of current ionization techniques, extending the applications, and decreasing the cost of the instrument. The design of the iAmIS platform combines flowing atmospheric pressure afterglow (FAPA) source/direct analysis in real time (DART), dielectric barrier discharge ionization (DBDI)/low-temperature plasma (LTP), desorption electrospray ionization (DESI), and laser desorption (LD) technique. All individual and combined ionization modes can be easily attained by modulating parameters. In particular, the FAPA/DART&DESI mode can realize the detection of polar and nonpolar compounds at the same time with two different ionization mechanisms: proton transfer and charge transfer. The introduction of LD contributes to the mass spectrometry imaging and the surface-assisted laser desorption (SALDI) under ambient condition. Compared with other individual or multi-mode ion source, the iAmIS platform provides the flexibility of choosing different ionization modes, broadens the scope of the analyte detection, and facilitates the analysis of complex samples. Graphical abstract ᅟ.

A Versatile Integrated Ambient Ionization Source Platform

NASA Astrophysics Data System (ADS)

Ai, Wanpeng; Nie, Honggang; Song, Shiyao; Liu, Xiaoyun; Bai, Yu; Liu, Huwei

2018-04-01

The pursuit of high-throughput sample analysis from complex matrix demands development of multiple ionization techniques with complementary specialties. A versatile integrated ambient ionization source (iAmIS) platform is proposed in this work, based on the idea of integrating multiple functions, enhancing the efficiency of current ionization techniques, extending the applications, and decreasing the cost of the instrument. The design of the iAmIS platform combines flowing atmospheric pressure afterglow (FAPA) source/direct analysis in real time (DART), dielectric barrier discharge ionization (DBDI)/low-temperature plasma (LTP), desorption electrospray ionization (DESI), and laser desorption (LD) technique. All individual and combined ionization modes can be easily attained by modulating parameters. In particular, the FAPA/DART&DESI mode can realize the detection of polar and nonpolar compounds at the same time with two different ionization mechanisms: proton transfer and charge transfer. The introduction of LD contributes to the mass spectrometry imaging and the surface-assisted laser desorption (SALDI) under ambient condition. Compared with other individual or multi-mode ion source, the iAmIS platform provides the flexibility of choosing different ionization modes, broadens the scope of the analyte detection, and facilitates the analysis of complex samples. [Figure not available: see fulltext.

Stakeholder perspectives on decision-analytic modeling frameworks to assess genetic services policy.

PubMed

Guzauskas, Gregory F; Garrison, Louis P; Stock, Jacquie; Au, Sylvia; Doyle, Debra Lochner; Veenstra, David L

2013-01-01

Genetic services policymakers and insurers often make coverage decisions in the absence of complete evidence of clinical utility and under budget constraints. We evaluated genetic services stakeholder opinions on the potential usefulness of decision-analytic modeling to inform coverage decisions, and asked them to identify genetic tests for decision-analytic modeling studies. We presented an overview of decision-analytic modeling to members of the Western States Genetic Services Collaborative Reimbursement Work Group and state Medicaid representatives and conducted directed content analysis and an anonymous survey to gauge their attitudes toward decision-analytic modeling. Participants also identified and prioritized genetic services for prospective decision-analytic evaluation. Participants expressed dissatisfaction with current processes for evaluating insurance coverage of genetic services. Some participants expressed uncertainty about their comprehension of decision-analytic modeling techniques. All stakeholders reported openness to using decision-analytic modeling for genetic services assessments. Participants were most interested in application of decision-analytic concepts to multiple-disorder testing platforms, such as next-generation sequencing and chromosomal microarray. Decision-analytic modeling approaches may provide a useful decision tool to genetic services stakeholders and Medicaid decision-makers.

Proteomics: from hypothesis to quantitative assay on a single platform. Guidelines for developing MRM assays using ion trap mass spectrometers.

PubMed

Han, Bomie; Higgs, Richard E

2008-09-01

High-throughput HPLC-mass spectrometry (HPLC-MS) is routinely used to profile biological samples for potential protein markers of disease, drug efficacy and toxicity. The discovery technology has advanced to the point where translating hypotheses from proteomic profiling studies into clinical use is the bottleneck to realizing the full potential of these approaches. The first step in this translation is the development and analytical validation of a higher throughput assay with improved sensitivity and selectivity relative to typical profiling assays. Multiple reaction monitoring (MRM) assays are an attractive approach for this stage of biomarker development given their improved sensitivity and specificity, the speed at which the assays can be developed and the quantitative nature of the assay. While the profiling assays are performed with ion trap mass spectrometers, MRM assays are traditionally developed in quadrupole-based mass spectrometers. Development of MRM assays from the same instrument used in the profiling analysis enables a seamless and rapid transition from hypothesis generation to validation. This report provides guidelines for rapidly developing an MRM assay using the same mass spectrometry platform used for profiling experiments (typically ion traps) and reviews methodological and analytical validation considerations. The analytical validation guidelines presented are drawn from existing practices on immunological assays and are applicable to any mass spectrometry platform technology.

Scalable Rapidly Deployable Convex Optimization for Data Analytics

DTIC Science & Technology

SOCPs , SDPs, exponential cone programs, and power cone programs. CVXPY supports basic methods for distributed optimization, on...multiple heterogenous platforms. We have also done basic research in various application areas , using CVXPY , to demonstrate its usefulness. See attached report for publication information....Over the period of the contract we have developed the full stack for wide use of convex optimization, in machine learning and many other areas .

Programmable bio-nano-chip system for saliva diagnostics

NASA Astrophysics Data System (ADS)

Christodoulides, Nicolaos; De La Garza, Richard; Simmons, Glennon W.; McRae, Michael P.; Wong, Jorge; Kosten, Thomas R.; Miller, Craig S.; Ebersole, Jeffrey L.; McDevitt, John

2014-06-01

This manuscript describes programmable Bio-Nano-Chip (p-BNC) approach that serves as miniaturized assay platform designed for the rapid detection and quantitation of multiple analytes in biological fluids along with the specific applications in salivary diagnostics intended for the point of need (PON). Included here are oral fluid-based tests for local periodontal disease, systemic cardiac disease and multiplexed tests for drugs of abuse.

The NASA Reanalysis Ensemble Service - Advanced Capabilities for Integrated Reanalysis Access and Intercomparison

NASA Astrophysics Data System (ADS)

Tamkin, G.; Schnase, J. L.; Duffy, D.; Li, J.; Strong, S.; Thompson, J. H.

2017-12-01

NASA's efforts to advance climate analytics-as-a-service are making new capabilities available to the research community: (1) A full-featured Reanalysis Ensemble Service (RES) comprising monthly means data from multiple reanalysis data sets, accessible through an enhanced set of extraction, analytic, arithmetic, and intercomparison operations. The operations are made accessible through NASA's climate data analytics Web services and our client-side Climate Data Services Python library, CDSlib; (2) A cloud-based, high-performance Virtual Real-Time Analytics Testbed supporting a select set of climate variables. This near real-time capability enables advanced technologies like Spark and Hadoop-based MapReduce analytics over native NetCDF files; and (3) A WPS-compliant Web service interface to our climate data analytics service that will enable greater interoperability with next-generation systems such as ESGF. The Reanalysis Ensemble Service includes the following: - New API that supports full temporal, spatial, and grid-based resolution services with sample queries - A Docker-ready RES application to deploy across platforms - Extended capabilities that enable single- and multiple reanalysis area average, vertical average, re-gridding, standard deviation, and ensemble averages - Convenient, one-stop shopping for commonly used data products from multiple reanalyses including basic sub-setting and arithmetic operations (e.g., avg, sum, max, min, var, count, anomaly) - Full support for the MERRA-2 reanalysis dataset in addition to, ECMWF ERA-Interim, NCEP CFSR, JMA JRA-55 and NOAA/ESRL 20CR… - A Jupyter notebook-based distribution mechanism designed for client use cases that combines CDSlib documentation with interactive scenarios and personalized project management - Supporting analytic services for NASA GMAO Forward Processing datasets - Basic uncertainty quantification services that combine heterogeneous ensemble products with comparative observational products (e.g., reanalysis, observational, visualization) - The ability to compute and visualize multiple reanalysis for ease of inter-comparisons - Automated tools to retrieve and prepare data collections for analytic processing

Development of a Multiplexed Liquid Chromatography Multiple-Reaction-Monitoring Mass Spectrometry (LC-MRM/MS) Method for Evaluation of Salivary Proteins as Oral Cancer Biomarkers*

PubMed Central

Chen, Hsiao-Wei; Wu, Chun-Feng; Chu, Lichieh Julie; Chiang, Wei-Fang; Wu, Chih-Ching; Yu, Jau-Song; Tsai, Cheng-Han; Liang, Kung-Hao; Chang, Yu-Sun; Wu, Maureen; Ou Yang, Wei-Ting

2017-01-01

Multiple (selected) reaction monitoring (MRM/SRM) of peptides is a growing technology for target protein quantification because it is more robust, precise, accurate, high-throughput, and multiplex-capable than antibody-based techniques. The technique has been applied clinically to the large-scale quantification of multiple target proteins in different types of fluids. However, previous MRM-based studies have placed less focus on sample-preparation workflow and analytical performance in the precise quantification of proteins in saliva, a noninvasively sampled body fluid. In this study, we evaluated the analytical performance of a simple and robust multiple reaction monitoring (MRM)-based targeted proteomics approach incorporating liquid chromatography with mass spectrometry detection (LC-MRM/MS). This platform was used to quantitatively assess the biomarker potential of a group of 56 salivary proteins that have previously been associated with human cancers. To further enhance the development of this technology for assay of salivary samples, we optimized the workflow for salivary protein digestion and evaluated quantification performance, robustness and technical limitations in analyzing clinical samples. Using a clinically well-characterized cohort of two independent clinical sample sets (total n = 119), we quantitatively characterized these protein biomarker candidates in saliva specimens from controls and oral squamous cell carcinoma (OSCC) patients. The results clearly showed a significant elevation of most targeted proteins in saliva samples from OSCC patients compared with controls. Overall, this platform was capable of assaying the most highly multiplexed panel of salivary protein biomarkers, highlighting the clinical utility of MRM in oral cancer biomarker research. PMID:28235782

Real-Time Visualization of Network Behaviors for Situational Awareness

DOE Office of Scientific and Technical Information (OSTI.GOV)

Best, Daniel M.; Bohn, Shawn J.; Love, Douglas V.

Plentiful, complex, and dynamic data make understanding the state of an enterprise network difficult. Although visualization can help analysts understand baseline behaviors in network traffic and identify off-normal events, visual analysis systems often do not scale well to operational data volumes (in the hundreds of millions to billions of transactions per day) nor to analysis of emergent trends in real-time data. We present a system that combines multiple, complementary visualization techniques coupled with in-stream analytics, behavioral modeling of network actors, and a high-throughput processing platform called MeDICi. This system provides situational understanding of real-time network activity to help analysts takemore » proactive response steps. We have developed these techniques using requirements gathered from the government users for which the tools are being developed. By linking multiple visualization tools to a streaming analytic pipeline, and designing each tool to support a particular kind of analysis (from high-level awareness to detailed investigation), analysts can understand the behavior of a network across multiple levels of abstraction.« less

Immunohistochemistry for predictive biomarkers in non-small cell lung cancer.

PubMed

Mino-Kenudson, Mari

2017-10-01

In the era of targeted therapy, predictive biomarker testing has become increasingly important for non-small cell lung cancer. Of multiple predictive biomarker testing methods, immunohistochemistry (IHC) is widely available and technically less challenging, can provide clinically meaningful results with a rapid turn-around-time and is more cost efficient than molecular platforms. In fact, several IHC assays for predictive biomarkers have already been implemented in routine pathology practice. In this review, we will discuss: (I) the details of anaplastic lymphoma kinase (ALK) and proto-oncogene tyrosine-protein kinase ROS (ROS1) IHC assays including the performance of multiple antibody clones, pros and cons of IHC platforms and various scoring systems to design an optimal algorithm for predictive biomarker testing; (II) issues associated with programmed death-ligand 1 (PD-L1) IHC assays; (III) appropriate pre-analytical tissue handling and selection of optimal tissue samples for predictive biomarker IHC.

Immunohistochemistry for predictive biomarkers in non-small cell lung cancer

PubMed Central

2017-01-01

In the era of targeted therapy, predictive biomarker testing has become increasingly important for non-small cell lung cancer. Of multiple predictive biomarker testing methods, immunohistochemistry (IHC) is widely available and technically less challenging, can provide clinically meaningful results with a rapid turn-around-time and is more cost efficient than molecular platforms. In fact, several IHC assays for predictive biomarkers have already been implemented in routine pathology practice. In this review, we will discuss: (I) the details of anaplastic lymphoma kinase (ALK) and proto-oncogene tyrosine-protein kinase ROS (ROS1) IHC assays including the performance of multiple antibody clones, pros and cons of IHC platforms and various scoring systems to design an optimal algorithm for predictive biomarker testing; (II) issues associated with programmed death-ligand 1 (PD-L1) IHC assays; (III) appropriate pre-analytical tissue handling and selection of optimal tissue samples for predictive biomarker IHC. PMID:29114473

Parallel Agent-Based Simulations on Clusters of GPUs and Multi-Core Processors

DOE Office of Scientific and Technical Information (OSTI.GOV)

Aaby, Brandon G; Perumalla, Kalyan S; Seal, Sudip K

2010-01-01

An effective latency-hiding mechanism is presented in the parallelization of agent-based model simulations (ABMS) with millions of agents. The mechanism is designed to accommodate the hierarchical organization as well as heterogeneity of current state-of-the-art parallel computing platforms. We use it to explore the computation vs. communication trade-off continuum available with the deep computational and memory hierarchies of extant platforms and present a novel analytical model of the tradeoff. We describe our implementation and report preliminary performance results on two distinct parallel platforms suitable for ABMS: CUDA threads on multiple, networked graphical processing units (GPUs), and pthreads on multi-core processors. Messagemore » Passing Interface (MPI) is used for inter-GPU as well as inter-socket communication on a cluster of multiple GPUs and multi-core processors. Results indicate the benefits of our latency-hiding scheme, delivering as much as over 100-fold improvement in runtime for certain benchmark ABMS application scenarios with several million agents. This speed improvement is obtained on our system that is already two to three orders of magnitude faster on one GPU than an equivalent CPU-based execution in a popular simulator in Java. Thus, the overall execution of our current work is over four orders of magnitude faster when executed on multiple GPUs.« less

Recent developments in OLED-based chemical and biological sensors

NASA Astrophysics Data System (ADS)

Shinar, Joseph; Zhou, Zhaoqun; Cai, Yuankun; Shinar, Ruth

2007-09-01

Recent developments in the structurally integrated OLED-based platform of luminescent chemical and biological sensors are reviewed. In this platform, an array of OLED pixels, which is structurally integrated with the sensing elements, is used as the photoluminescence (PL) excitation source. The structural integration is achieved by fabricating the OLED array and the sensing element on opposite sides of a common glass substrate or on two glass substrates that are attached back-to-back. As it does not require optical fibers, lens, or mirrors, it results in a uniquely simple, low-cost, and potentially rugged geometry. The recent developments on this platform include the following: (1) Enhancing the performance of gas-phase and dissolved oxygen sensors. This is achieved by (a) incorporating high-dielectric TiO II nanoparticles in the oxygen-sensitive Pt and Pd octaethylporphyrin (PtOEP and PdOEP, respectively)- doped polystyrene (PS) sensor films, and (b) embedding the oxygen-sensitive dyes in a matrix of polymer blends such as PS:polydimethylsiloxane (PDMS). (2) Developing sensor arrays for simultaneous detection of multiple serum analytes, including oxygen, glucose, lactate, and alcohol. The sensing element for each analyte consists of a PtOEP-doped PS oxygen sensor, and a solution containing the oxidase enzyme specific to the analyte. Each sensing element is coupled to two individually addressable OLED pixels and a Si photodiode photodetector (PD). (3) Enhancing the integration of the platform, whereby a PD array is also structurally integrated with the OLED array and sensing elements. This enhanced integration is achieved by fabricating an array of amorphous or nanocrystalline Si-based PDs, followed by fabrication of the OLED pixels in the gaps between these Si PDs.

KOLAM: a cross-platform architecture for scalable visualization and tracking in wide-area imagery

NASA Astrophysics Data System (ADS)

Fraser, Joshua; Haridas, Anoop; Seetharaman, Guna; Rao, Raghuveer M.; Palaniappan, Kannappan

2013-05-01

KOLAM is an open, cross-platform, interoperable, scalable and extensible framework supporting a novel multi- scale spatiotemporal dual-cache data structure for big data visualization and visual analytics. This paper focuses on the use of KOLAM for target tracking in high-resolution, high throughput wide format video also known as wide-area motion imagery (WAMI). It was originally developed for the interactive visualization of extremely large geospatial imagery of high spatial and spectral resolution. KOLAM is platform, operating system and (graphics) hardware independent, and supports embedded datasets scalable from hundreds of gigabytes to feasibly petabytes in size on clusters, workstations, desktops and mobile computers. In addition to rapid roam, zoom and hyper- jump spatial operations, a large number of simultaneously viewable embedded pyramid layers (also referred to as multiscale or sparse imagery), interactive colormap and histogram enhancement, spherical projection and terrain maps are supported. The KOLAM software architecture was extended to support airborne wide-area motion imagery by organizing spatiotemporal tiles in very large format video frames using a temporal cache of tiled pyramid cached data structures. The current version supports WAMI animation, fast intelligent inspection, trajectory visualization and target tracking (digital tagging); the latter by interfacing with external automatic tracking software. One of the critical needs for working with WAMI is a supervised tracking and visualization tool that allows analysts to digitally tag multiple targets, quickly review and correct tracking results and apply geospatial visual analytic tools on the generated trajectories. One-click manual tracking combined with multiple automated tracking algorithms are available to assist the analyst and increase human effectiveness.

Current and future bioanalytical approaches for stroke assessment.

PubMed

Pullagurla, Swathi R; Baird, Alison E; Adamski, Mateusz G; Soper, Steven A

2015-01-01

Efforts are underway to develop novel platforms for stroke diagnosis to meet the criteria for effective treatment within the narrow time window mandated by the FDA-approved therapeutic (<3 h). Blood-based biomarkers could be used for rapid stroke diagnosis and coupled with new analytical tools, could serve as an attractive platform for managing stroke-related diseases. In this review, we will discuss the physiological processes associated with stroke and current diagnostic tools as well as their associated shortcomings. We will then review information on blood-based biomarkers and various detection technologies. In particular, point of care testing that permits small blood volumes required for the analysis and rapid turn-around time measurements of multiple markers will be presented.

openECA Detailed Design Document

DOE Office of Scientific and Technical Information (OSTI.GOV)

Robertson, Russell

This document describes the functional and non-functional requirements for: The openECA platform The included analytic systems that will: Validate the operational readiness and performance of the openECA platform Provide out-of-box value to those that implement the openECA platform with an initial collection of analytics

Development of a Multiplexed Liquid Chromatography Multiple-Reaction-Monitoring Mass Spectrometry (LC-MRM/MS) Method for Evaluation of Salivary Proteins as Oral Cancer Biomarkers.

PubMed

Chen, Yi-Ting; Chen, Hsiao-Wei; Wu, Chun-Feng; Chu, Lichieh Julie; Chiang, Wei-Fang; Wu, Chih-Ching; Yu, Jau-Song; Tsai, Cheng-Han; Liang, Kung-Hao; Chang, Yu-Sun; Wu, Maureen; Ou Yang, Wei-Ting

2017-05-01

Multiple (selected) reaction monitoring (MRM/SRM) of peptides is a growing technology for target protein quantification because it is more robust, precise, accurate, high-throughput, and multiplex-capable than antibody-based techniques. The technique has been applied clinically to the large-scale quantification of multiple target proteins in different types of fluids. However, previous MRM-based studies have placed less focus on sample-preparation workflow and analytical performance in the precise quantification of proteins in saliva, a noninvasively sampled body fluid. In this study, we evaluated the analytical performance of a simple and robust multiple reaction monitoring (MRM)-based targeted proteomics approach incorporating liquid chromatography with mass spectrometry detection (LC-MRM/MS). This platform was used to quantitatively assess the biomarker potential of a group of 56 salivary proteins that have previously been associated with human cancers. To further enhance the development of this technology for assay of salivary samples, we optimized the workflow for salivary protein digestion and evaluated quantification performance, robustness and technical limitations in analyzing clinical samples. Using a clinically well-characterized cohort of two independent clinical sample sets (total n = 119), we quantitatively characterized these protein biomarker candidates in saliva specimens from controls and oral squamous cell carcinoma (OSCC) patients. The results clearly showed a significant elevation of most targeted proteins in saliva samples from OSCC patients compared with controls. Overall, this platform was capable of assaying the most highly multiplexed panel of salivary protein biomarkers, highlighting the clinical utility of MRM in oral cancer biomarker research. © 2017 by The American Society for Biochemistry and Molecular Biology, Inc.

A multi-analyte biosensor for the simultaneous label-free detection of pathogens and biomarkers in point-of-need animal testing.

PubMed

Ewald, Melanie; Fechner, Peter; Gauglitz, Günter

2015-05-01

For the first time, a multi-analyte biosensor platform has been developed using the label-free 1-lambda-reflectometry technique. This platform is the first, which does not use imaging techniques, but is able to perform multi-analyte measurements. It is designed to be portable and cost-effective and therefore allows for point-of-need testing or on-site field-testing with possible applications in diagnostics. This work highlights the application possibilities of this platform in the field of animal testing, but is also relevant and transferable to human diagnostics. The performance of the platform has been evaluated using relevant reference systems like biomarker (C-reactive protein) and serology (anti-Salmonella antibodies) as well as a panel of real samples (animal sera). The comparison of the working range and limit of detection shows no loss of performance transferring the separate assays to the multi-analyte setup. Moreover, the new multi-analyte platform allows for discrimination between sera of animals infected with different Salmonella subtypes.

The Ophidia Stack: Toward Large Scale, Big Data Analytics Experiments for Climate Change

NASA Astrophysics Data System (ADS)

Fiore, S.; Williams, D. N.; D'Anca, A.; Nassisi, P.; Aloisio, G.

2015-12-01

The Ophidia project is a research effort on big data analytics facing scientific data analysis challenges in multiple domains (e.g. climate change). It provides a "datacube-oriented" framework responsible for atomically processing and manipulating scientific datasets, by providing a common way to run distributive tasks on large set of data fragments (chunks). Ophidia provides declarative, server-side, and parallel data analysis, jointly with an internal storage model able to efficiently deal with multidimensional data and a hierarchical data organization to manage large data volumes. The project relies on a strong background on high performance database management and On-Line Analytical Processing (OLAP) systems to manage large scientific datasets. The Ophidia analytics platform provides several data operators to manipulate datacubes (about 50), and array-based primitives (more than 100) to perform data analysis on large scientific data arrays. To address interoperability, Ophidia provides multiple server interfaces (e.g. OGC-WPS). From a client standpoint, a Python interface enables the exploitation of the framework into Python-based eco-systems/applications (e.g. IPython) and the straightforward adoption of a strong set of related libraries (e.g. SciPy, NumPy). The talk will highlight a key feature of the Ophidia framework stack: the "Analytics Workflow Management System" (AWfMS). The Ophidia AWfMS coordinates, orchestrates, optimises and monitors the execution of multiple scientific data analytics and visualization tasks, thus supporting "complex analytics experiments". Some real use cases related to the CMIP5 experiment will be discussed. In particular, with regard to the "Climate models intercomparison data analysis" case study proposed in the EU H2020 INDIGO-DataCloud project, workflows related to (i) anomalies, (ii) trend, and (iii) climate change signal analysis will be presented. Such workflows will be distributed across multiple sites - according to the datasets distribution - and will include intercomparison, ensemble, and outlier analysis. The two-level workflow solution envisioned in INDIGO (coarse grain for distributed tasks orchestration, and fine grain, at the level of a single data analytics cluster instance) will be presented and discussed.

A large-scale superhydrophobic surface-enhanced Raman scattering (SERS) platform fabricated via capillary force lithography and assembly of Ag nanocubes for ultratrace molecular sensing.

PubMed

Tan, Joel Ming Rui; Ruan, Justina Jiexin; Lee, Hiang Kwee; Phang, In Yee; Ling, Xing Yi

2014-12-28

An analytical platform with an ultratrace detection limit in the atto-molar (aM) concentration range is vital for forensic, industrial and environmental sectors that handle scarce/highly toxic samples. Superhydrophobic surface-enhanced Raman scattering (SERS) platforms serve as ideal platforms to enhance detection sensitivity by reducing the random spreading of aqueous solution. However, the fabrication of superhydrophobic SERS platforms is generally limited due to the use of sophisticated and expensive protocols and/or suffers structural and signal inconsistency. Herein, we demonstrate a high-throughput fabrication of a stable and uniform superhydrophobic SERS platform for ultratrace molecular sensing. Large-area box-like micropatterns of the polymeric surface are first fabricated using capillary force lithography (CFL). Subsequently, plasmonic properties are incorporated into the patterned surfaces by decorating with Ag nanocubes using the Langmuir-Schaefer technique. To create a stable superhydrophobic SERS platform, an additional 25 nm Ag film is coated over the Ag nanocube-decorated patterned template followed by chemical functionalization with perfluorodecanethiol. Our resulting superhydrophobic SERS platform demonstrates excellent water-repellency with a static contact angle of 165° ± 9° and a consequent analyte concentration factor of 59-fold, as compared to its hydrophilic counterpart. By combining the analyte concentration effect of superhydrophobic surfaces with the intense electromagnetic "hot spots" of Ag nanocubes, our superhydrophobic SERS platform achieves an ultra-low detection limit of 10(-17) M (10 aM) for rhodamine 6G using just 4 μL of analyte solutions, corresponding to an analytical SERS enhancement factor of 10(13). Our fabrication protocol demonstrates a simple, cost- and time-effective approach for the large-scale fabrication of a superhydrophobic SERS platform for ultratrace molecular detection.

A versatile electrophoresis-based self-test platform.

PubMed

Staal, Steven; Ungerer, Mathijn; Floris, Arjan; Ten Brinke, Hans-Willem; Helmhout, Roy; Tellegen, Marian; Janssen, Kjeld; Karstens, Erik; van Arragon, Charlotte; Lenk, Stefan; Staijen, Erik; Bartholomew, Jody; Krabbe, Hans; Movig, Kris; Dubský, Pavel; van den Berg, Albert; Eijkel, Jan

2015-03-01

This paper reports on recent research creating a family of electrophoresis-based point of care devices for the determination of a wide range of ionic analytes in various sample matrices. These devices are based on a first version for the point-of-care measurement of Li(+), reported in 2010 by Floris et al. (Lab Chip 2010, 10, 1799-1806). With respect to this device, significant improvements in accuracy, precision, detection limit, and reliability have been obtained especially by the use of multiple injections of one sample on a single chip and integrated data analysis. Internal and external validation by clinical laboratories for the determination of analytes in real patients by a self-test is reported. For Li(+) in blood better precision than the standard clinical determination for Li(+) was achieved. For Na(+) in human urine the method was found to be within the clinical acceptability limits. In a veterinary application, Ca(2+) and Mg(2+) were determined in bovine blood by means of the same chip, but using a different platform. Finally, promising preliminary results are reported with the Medimate platform for the determination of creatinine in whole blood and quantification of both cations and anions through replicate measurements on the same sample with the same chip. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Data visualisation in surveillance for injury prevention and control: conceptual bases and case studies

PubMed Central

Martinez, Ramon; Ordunez, Pedro; Soliz, Patricia N; Ballesteros, Michael F

2016-01-01

Background The complexity of current injury-related health issues demands the usage of diverse and massive data sets for comprehensive analyses, and application of novel methods to communicate data effectively to the public health community, decision-makers and the public. Recent advances in information visualisation, availability of new visual analytic methods and tools, and progress on information technology provide an opportunity for shaping the next generation of injury surveillance. Objective To introduce data visualisation conceptual bases, and propose a visual analytic and visualisation platform in public health surveillance for injury prevention and control. Methods The paper introduces data visualisation conceptual bases, describes a visual analytic and visualisation platform, and presents two real-world case studies illustrating their application in public health surveillance for injury prevention and control. Results Application of visual analytic and visualisation platform is presented as solution for improved access to heterogeneous data sources, enhance data exploration and analysis, communicate data effectively, and support decision-making. Conclusions Applications of data visualisation concepts and visual analytic platform could play a key role to shape the next generation of injury surveillance. Visual analytic and visualisation platform could improve data use, the analytic capacity, and ability to effectively communicate findings and key messages. The public health surveillance community is encouraged to identify opportunities to develop and expand its use in injury prevention and control. PMID:26728006

Multiplexed detection of anthrax-related toxin genes.

PubMed

Moser, Michael J; Christensen, Deanna R; Norwood, David; Prudent, James R

2006-02-01

Simultaneous analysis of three targets in three colors on any real-time polymerase chain reaction (PCR) instrument would increase the flexibility of real-time PCR. For the detection of Bacillus strains that can cause inhalation anthrax-related illness, this ability would be valuable because two plasmids confer virulence, and internal positive controls are needed to monitor the testing in cases lacking target-specific signals. Using a real-time PCR platform called MultiCode-RTx, multiple assays were developed that specifically monitor the presence of Bacillus anthracis-specific virulence plasmid-associated genes. In particular for use on LightCycler-1, two triplex RTx systems demonstrated high sensitivity with limits of detection nearing single-copy levels for both plasmids. Specificity was established using a combination of Ct values and correct amplicon melting temperatures. All reactions were further verified by detection of an internal positive control. For these two triplex RTx assays, the analytical detection limit was one to nine plasmid copy equivalents, 100% analytical specificity with a 95% confidence interval (CI) of 9%, and 100% analytical sensitivity with a CI of 2%. Although further testing using clinical or environmental samples will be required to assess diagnostic sensitivity and specificity, the RTx platform achieves similar results to those of probe-based real-time systems.

A microfluidic device integrating dual CMOS polysilicon nanowire sensors for on-chip whole blood processing and simultaneous detection of multiple analytes.

PubMed

Kuan, Da-Han; Wang, I-Shun; Lin, Jiun-Rue; Yang, Chao-Han; Huang, Chi-Hsien; Lin, Yen-Hung; Lin, Chih-Ting; Huang, Nien-Tsu

2016-08-02

The hemoglobin-A1c test, measuring the ratio of glycated hemoglobin (HbA1c) to hemoglobin (Hb) levels, has been a standard assay in diabetes diagnosis that removes the day-to-day glucose level variation. Currently, the HbA1c test is restricted to hospitals and central laboratories due to the laborious, time-consuming whole blood processing and bulky instruments. In this paper, we have developed a microfluidic device integrating dual CMOS polysilicon nanowire sensors (MINS) for on-chip whole blood processing and simultaneous detection of multiple analytes. The micromachined polymethylmethacrylate (PMMA) microfluidic device consisted of a serpentine microchannel with multiple dam structures designed for non-lysed cells or debris trapping, uniform plasma/buffer mixing and dilution. The CMOS-fabricated polysilicon nanowire sensors integrated with the microfluidic device were designed for the simultaneous, label-free electrical detection of multiple analytes. Our study first measured the Hb and HbA1c levels in 11 clinical samples via these nanowire sensors. The results were compared with those of standard Hb and HbA1c measurement methods (Hb: the sodium lauryl sulfate hemoglobin detection method; HbA1c: cation-exchange high-performance liquid chromatography) and showed comparable outcomes. Finally, we successfully demonstrated the efficacy of the MINS device's on-chip whole blood processing followed by simultaneous Hb and HbA1c measurement in a clinical sample. Compared to current Hb and HbA1c sensing instruments, the MINS platform is compact and can simultaneously detect two analytes with only 5 μL of whole blood, which corresponds to a 300-fold blood volume reduction. The total assay time, including the in situ sample processing and analyte detection, was just 30 minutes. Based on its on-chip whole blood processing and simultaneous multiple analyte detection functionalities with a lower sample volume requirement and shorter process time, the MINS device can be effectively applied to real-time diabetes diagnostics and monitoring in point-of-care settings.

Method and platform standardization in MRM-based quantitative plasma proteomics.

PubMed

Percy, Andrew J; Chambers, Andrew G; Yang, Juncong; Jackson, Angela M; Domanski, Dominik; Burkhart, Julia; Sickmann, Albert; Borchers, Christoph H

2013-12-16

There exists a growing demand in the proteomics community to standardize experimental methods and liquid chromatography-mass spectrometry (LC/MS) platforms in order to enable the acquisition of more precise and accurate quantitative data. This necessity is heightened by the evolving trend of verifying and validating candidate disease biomarkers in complex biofluids, such as blood plasma, through targeted multiple reaction monitoring (MRM)-based approaches with stable isotope-labeled standards (SIS). Considering the lack of performance standards for quantitative plasma proteomics, we previously developed two reference kits to evaluate the MRM with SIS peptide approach using undepleted and non-enriched human plasma. The first kit tests the effectiveness of the LC/MRM-MS platform (kit #1), while the second evaluates the performance of an entire analytical workflow (kit #2). Here, these kits have been refined for practical use and then evaluated through intra- and inter-laboratory testing on 6 common LC/MS platforms. For an identical panel of 22 plasma proteins, similar concentrations were determined, regardless of the kit, instrument platform, and laboratory of analysis. These results demonstrate the value of the kit and reinforce the utility of standardized methods and protocols. The proteomics community needs standardized experimental protocols and quality control methods in order to improve the reproducibility of MS-based quantitative data. This need is heightened by the evolving trend for MRM-based validation of proposed disease biomarkers in complex biofluids such as blood plasma. We have developed two kits to assist in the inter- and intra-laboratory quality control of MRM experiments: the first kit tests the effectiveness of the LC/MRM-MS platform (kit #1), while the second evaluates the performance of an entire analytical workflow (kit #2). In this paper, we report the use of these kits in intra- and inter-laboratory testing on 6 common LC/MS platforms. This article is part of a Special Issue entitled: Standardization and Quality Control in Proteomics. © 2013.

Metal-enhanced fluorescence/visual bimodal platform for multiplexed ultrasensitive detection of microRNA with reusable paper analytical devices.

PubMed

Liang, Linlin; Lan, Feifei; Yin, Xuemei; Ge, Shenguang; Yu, Jinghua; Yan, Mei

2017-09-15

Convenient biosensor for simultaneous multi-analyte detection was increasingly required in biological analysis. A novel flower-like silver (FLS)-enhanced fluorescence/visual bimodal platform for the ultrasensitive detection of multiple miRNAs was successfully constructed for the first time based on the principle of multi-channel microfluidic paper-based analytical devices (µPADs). Fluorophore-functionalized DNA 1 (DNA 1 -N-CDs) was combined with FLS, which was hybridized with quencher-carrying strand (DNA 2 -CeO 2 ) to form FLS-enhanced fluorescence biosensor. Upon the addition of the target miRNA, the fluorescent intensity of DNA 1 -N-CDs within the proximity of the FLS was strengthened. The disengaged DNA/CeO 2 complex could result in color change after joining H 2 O 2 , leading to real-time visual detection of miRNA firstly. If necessary, then the fluorescence method was applied for a accurate determination. In this strategy, the growth of FLS in µPADs not only reduced the background fluorescence but also provided an enrichment of "hot spots" for surface enhanced fluorescence detection of miRNAs. Results also showed versatility of the FLS in the enhancement of sensitivity and selectivity of the miRNA biosensor. Remarkably, this biosensor could detect as low as 0.03fM miRNA210 and 0.06fM miRNA21. Interestingly, the proposed biosensor also possessed good capability of recycling in three cycles upon change of the supplementation of DNA 2 -CeO 2 and visual substitutive device. This method opened new opportunities for further studies of miRNA related bioprocesses and will provide a new instrument for simultaneous detection of multiple low-level biomarkers. Copyright © 2017 Elsevier B.V. All rights reserved.

Attractive design: an elution solvent optimization platform for magnetic-bead-based fractionation using digital microfluidics and design of experiments.

PubMed

Lafrenière, Nelson M; Mudrik, Jared M; Ng, Alphonsus H C; Seale, Brendon; Spooner, Neil; Wheeler, Aaron R

2015-04-07

There is great interest in the development of integrated tools allowing for miniaturized sample processing, including solid phase extraction (SPE). We introduce a new format for microfluidic SPE relying on C18-functionalized magnetic beads that can be manipulated in droplets in a digital microfluidic platform. This format provides the opportunity to tune the amount (and potentially the type) of stationary phase on-the-fly, and allows the removal of beads after the extraction (to enable other operations in same device-space), maintaining device reconfigurability. Using the new method, we employed a design of experiments (DOE) operation to enable automated on-chip optimization of elution solvent composition for reversed phase SPE of a model system. Further, conditions were selected to enable on-chip fractionation of multiple analytes. Finally, the method was demonstrated to be useful for online cleanup of extracts from dried blood spot (DBS) samples. We anticipate this combination of features will prove useful for separating a wide range of analytes, from small molecules to peptides, from complex matrices.

Integrated genome browser: visual analytics platform for genomics.

PubMed

Freese, Nowlan H; Norris, David C; Loraine, Ann E

2016-07-15

Genome browsers that support fast navigation through vast datasets and provide interactive visual analytics functions can help scientists achieve deeper insight into biological systems. Toward this end, we developed Integrated Genome Browser (IGB), a highly configurable, interactive and fast open source desktop genome browser. Here we describe multiple updates to IGB, including all-new capabilities to display and interact with data from high-throughput sequencing experiments. To demonstrate, we describe example visualizations and analyses of datasets from RNA-Seq, ChIP-Seq and bisulfite sequencing experiments. Understanding results from genome-scale experiments requires viewing the data in the context of reference genome annotations and other related datasets. To facilitate this, we enhanced IGB's ability to consume data from diverse sources, including Galaxy, Distributed Annotation and IGB-specific Quickload servers. To support future visualization needs as new genome-scale assays enter wide use, we transformed the IGB codebase into a modular, extensible platform for developers to create and deploy all-new visualizations of genomic data. IGB is open source and is freely available from http://bioviz.org/igb aloraine@uncc.edu. © The Author 2016. Published by Oxford University Press.

Inkjet-printed point-of-care immunoassay on a nanoscale polymer brush enables subpicomolar detection of analytes in blood

NASA Astrophysics Data System (ADS)

Joh, Daniel Y.; Hucknall, Angus M.; Wei, Qingshan; Mason, Kelly A.; Lund, Margaret L.; Fontes, Cassio M.; Hill, Ryan T.; Blair, Rebecca; Zimmers, Zackary; Achar, Rohan K.; Tseng, Derek; Gordan, Raluca; Freemark, Michael; Ozcan, Aydogan; Chilkoti, Ashutosh

2017-08-01

The ELISA is the mainstay for sensitive and quantitative detection of protein analytes. Despite its utility, ELISA is time-consuming, resource-intensive, and infrastructure-dependent, limiting its availability in resource-limited regions. Here, we describe a self-contained immunoassay platform (the “D4 assay”) that converts the sandwich immunoassay into a point-of-care test (POCT). The D4 assay is fabricated by inkjet printing assay reagents as microarrays on nanoscale polymer brushes on glass chips, so that all reagents are “on-chip,” and these chips show durable storage stability without cold storage. The D4 assay can interrogate multiple analytes from a drop of blood, is compatible with a smartphone detector, and displays analytical figures of merit that are comparable to standard laboratory-based ELISA in whole blood. These attributes of the D4 POCT have the potential to democratize access to high-performance immunoassays in resource-limited settings without sacrificing their performance.

Data visualisation in surveillance for injury prevention and control: conceptual bases and case studies.

PubMed

Martinez, Ramon; Ordunez, Pedro; Soliz, Patricia N; Ballesteros, Michael F

2016-04-01

The complexity of current injury-related health issues demands the usage of diverse and massive data sets for comprehensive analyses, and application of novel methods to communicate data effectively to the public health community, decision-makers and the public. Recent advances in information visualisation, availability of new visual analytic methods and tools, and progress on information technology provide an opportunity for shaping the next generation of injury surveillance. To introduce data visualisation conceptual bases, and propose a visual analytic and visualisation platform in public health surveillance for injury prevention and control. The paper introduces data visualisation conceptual bases, describes a visual analytic and visualisation platform, and presents two real-world case studies illustrating their application in public health surveillance for injury prevention and control. Application of visual analytic and visualisation platform is presented as solution for improved access to heterogeneous data sources, enhance data exploration and analysis, communicate data effectively, and support decision-making. Applications of data visualisation concepts and visual analytic platform could play a key role to shape the next generation of injury surveillance. Visual analytic and visualisation platform could improve data use, the analytic capacity, and ability to effectively communicate findings and key messages. The public health surveillance community is encouraged to identify opportunities to develop and expand its use in injury prevention and control. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/

"Shoot and Sense" Janus Micromotors-Based Strategy for the Simultaneous Degradation and Detection of Persistent Organic Pollutants in Food and Biological Samples.

PubMed

Rojas, D; Jurado-Sánchez, B; Escarpa, A

2016-04-05

A novel Janus micromotor-based strategy for the direct determination of diphenyl phthalate (DPP) in food and biological samples is presented. Mg/Au Janus micromotors are employed as novel analytical platforms for the degradation of the non-electroactive DPP into phenol, which is directly measured by difference pulse voltammetry on disposable screen-printed electrodes. The self-movement of the micromotors along the samples result in the generation of hydrogen microbubbles and hydroxyl ions for DPP degradation. The increased fluid transport improves dramatically the analytical signal, increasing the sensitivity while lowering the detection potential. The method has been successfully applied to the direct analysis of DPP in selected food and biological samples, without any sample treatment and avoiding any potential contamination from laboratory equipment. The developed approach is fast (∼5 min) and accurate with recoveries of ∼100%. In addition, efficient propulsion of multiple Mg/Au micromotors in complex samples has also been demonstrated. The advantages of the micromotors-assisted technology, i.e., disposability, portability, and the possibility to carry out multiple analysis simultaneously, hold considerable promise for its application in food and biological control in analytical applications with high significance.

Lab on a CD.

PubMed

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

2006-01-01

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

Chemical and Biological Dynamics Using Droplet-Based Microfluidics.

PubMed

Dressler, Oliver J; Casadevall I Solvas, Xavier; deMello, Andrew J

2017-06-12

Recent years have witnessed an increased use of droplet-based microfluidic techniques in a wide variety of chemical and biological assays. Nevertheless, obtaining dynamic data from these platforms has remained challenging, as this often requires reading the same droplets (possibly thousands of them) multiple times over a wide range of intervals (from milliseconds to hours). In this review, we introduce the elemental techniques for the formation and manipulation of microfluidic droplets, together with the most recent developments in these areas. We then discuss a wide range of analytical methods that have been successfully adapted for analyte detection in droplets. Finally, we highlight a diversity of studies where droplet-based microfluidic strategies have enabled the characterization of dynamic systems that would otherwise have remained unexplorable.

MyDiabetesMyWay: An Evolving National Data Driven Diabetes Self-Management Platform.

PubMed

Wake, Deborah J; He, Jinzhang; Czesak, Anna Maria; Mughal, Fezan; Cunningham, Scott G

2016-09-01

MyDiabetesMyWay (MDMW) is an award-wining national electronic personal health record and self-management platform for diabetes patients in Scotland. This platform links multiple national institutional and patient-recorded data sources to provide a unique resource for patient care and self-management. This review considers the current evidence for online interventions in diabetes and discusses these in the context of current and ongoing developments for MDMW. Evaluation of MDMW through patient reported outcomes demonstrates a positive impact on self-management. User feedback has highlighted barriers to uptake and has guided platform evolution from an education resource website to an electronic personal health record now encompassing remote monitoring, communication tools and personalized education links. Challenges in delivering digital interventions for long-term conditions include integration of data between institutional and personal recorded sources to perform big data analytics and facilitating technology use in those with disabilities, low digital literacy, low socioeconomic status and in minority groups. The potential for technology supported health improvement is great, but awareness and adoption by health workers and patients remains a significant barrier. © 2016 Diabetes Technology Society.

Technical aspects and inter-laboratory variability in native peptide profiling: the CE-MS experience.

PubMed

Mischak, Harald; Vlahou, Antonia; Ioannidis, John P A

2013-04-01

Mass spectrometry platforms have attracted a lot of interest in the last 2 decades as profiling tools for native peptides and proteins with clinical potential. However, limitations associated with reproducibility and analytical robustness, especially pronounced with the initial SELDI systems, hindered the application of such platforms in biomarker qualification and clinical implementation. The scope of this article is to give a short overview on data available on performance and on analytical robustness of the different platforms for peptide profiling. Using the CE-MS platform as a paradigm, data on analytical performance are described including reproducibility (short-term and intermediate repeatability), stability, interference, quantification capabilities (limits of detection), and inter-laboratory variability. We discuss these issues by using as an example our experience with the development of a 273-peptide marker for chronic kidney disease. Finally, we discuss pros and cons and means for improvement and emphasize the need to test in terms of comparative clinical performance and impact, different platforms that pass reasonably well analytical validation tests. Copyright © 2012 The Canadian Society of Clinical Chemists. Published by Elsevier Inc. All rights reserved.

Functionalization and Characterization of Nanomaterial Gated Field-Effect Transistor-Based Biosensors and the Design of a Multi-Analyte Implantable Biosensing Platform

NASA Astrophysics Data System (ADS)

Croce, Robert A., Jr.

Advances in semiconductor research and complementary-metal-oxide semiconductor fabrication allow for the design and implementation of miniaturized metabolic monitoring systems, as well as advanced biosensor design. The first part of this dissertation will focus on the design and fabrication of nanomaterial (single-walled carbon nanotube and quantum dot) gated field-effect transistors configured as protein sensors. These novel device structures have been functionalized with single-stranded DNA aptamers, and have shown sensor operation towards the protein Thrombin. Such advanced transistor-based sensing schemes present considerable advantages over traditional sensing methodologies in view of its miniaturization, low cost, and facile fabrication, paving the way for the ultimate realization of a multi-analyte lab-on-chip. The second part of this dissertation focuses on the design and fabrication of a needle-implantable glucose sensing platform which is based solely on photovoltaic powering and optical communication. By employing these powering and communication schemes, this design negates the need for bulky on-chip RF-based transmitters and batteries in an effort to attain extreme miniaturization required for needle-implantable/extractable applications. A complete single-sensor system coupled with a miniaturized amperometric glucose sensor has been demonstrated to exhibit reality of this technology. Furthermore, an optical selection scheme of multiple potentiostats for four different analytes (glucose, lactate, O 2 and CO2) as well as the optical transmission of sensor data has been designed for multi-analyte applications. The last part of this dissertation will focus on the development of a computational model for the amperometric glucose sensors employed in the aforementioned implantable platform. This model has been applied to single-layer single-enzyme systems, as well as multi-layer (single enzyme) systems utilizing glucose flux limiting layer-by-layer assembled outer membranes. The concentration of glucose and hydrogen peroxide within the sensor geometry, the transient response and the device response time has been simulated for both systems.

An analytical platform for cumulative impact assessment based on multiple futures: the impact of petroleum drilling and forest harvesting on moose (Alces alces) and marten (Martes americana) habitats in northeastern British Columbia.

PubMed

Strimbu, Bogdan; Innes, John

2011-07-01

The combined influence on the environment of all projects occurring in a single area is evaluated through cumulative impact assessments (CIA), which consider the consequences of multiple projects, each insignificant on its own, yet important when evaluated collectively. Traditionally, future human activities are included in CIA using an analytical platform, commonly based on complex models that supply precise predictions but with reduced accuracy. To compensate for the lack of accuracy in current CIA approaches, we propose a shift in the paradigm governing CIA. The paradigm shift involves a change in the focus of CIA investigations from the detailed analysis of one unlikely future to the identification of the patterns describing multiple potential future changes in the environment. To illustrate the approach, a set of 144 possible and equally likely futures were developed that aimed to identify the potential impacts of forest harvesting and petroleum drilling on the habitat suitability of moose and marten in northeast British Columbia, Canada. The evolution of two measures of habitat suitability (average habitat suitability index and surface of the stands with habitat suitability index >0.5) revealed that the human activities could induce cycles in the habitat dynamics of moose and marten. The planning period of 100 years was separated into three distinct periods following a sinusoidal pattern (i.e., increase - constant - decrease in the habitat suitability measures). The attributes that could induce significant changes in the assessment of environment are the choice of harvesting age and species. Copyright © 2011 Elsevier Ltd. All rights reserved.

Computing Platforms for Big Biological Data Analytics: Perspectives and Challenges.

PubMed

Yin, Zekun; Lan, Haidong; Tan, Guangming; Lu, Mian; Vasilakos, Athanasios V; Liu, Weiguo

2017-01-01

The last decade has witnessed an explosion in the amount of available biological sequence data, due to the rapid progress of high-throughput sequencing projects. However, the biological data amount is becoming so great that traditional data analysis platforms and methods can no longer meet the need to rapidly perform data analysis tasks in life sciences. As a result, both biologists and computer scientists are facing the challenge of gaining a profound insight into the deepest biological functions from big biological data. This in turn requires massive computational resources. Therefore, high performance computing (HPC) platforms are highly needed as well as efficient and scalable algorithms that can take advantage of these platforms. In this paper, we survey the state-of-the-art HPC platforms for big biological data analytics. We first list the characteristics of big biological data and popular computing platforms. Then we provide a taxonomy of different biological data analysis applications and a survey of the way they have been mapped onto various computing platforms. After that, we present a case study to compare the efficiency of different computing platforms for handling the classical biological sequence alignment problem. At last we discuss the open issues in big biological data analytics.

Aspiring to Spectral Ignorance in Earth Observation

NASA Astrophysics Data System (ADS)

Oliver, S. A.

2016-12-01

Enabling robust, defensible and integrated decision making in the Era of Big Earth Data requires the fusion of data from multiple and diverse sensor platforms and networks. While the application of standardised global grid systems provides a common spatial analytics framework that facilitates the computationally efficient and statistically valid integration and analysis of these various data sources across multiple scales, there remains the challenge of sensor equivalency; particularly when combining data from different earth observation satellite sensors (e.g. combining Landsat and Sentinel-2 observations). To realise the vision of a sensor ignorant analytics platform for earth observation we require automation of spectral matching across the available sensors. Ultimately, the aim is to remove the requirement for the user to possess any sensor knowledge in order to undertake analysis. This paper introduces the concept of spectral equivalence and proposes a methodology through which equivalent bands may be sourced from a set of potential target sensors through application of equivalence metrics and thresholds. A number of parameters can be used to determine whether a pair of spectra are equivalent for the purposes of analysis. A baseline set of thresholds for these parameters and how to apply them systematically to enable relation of spectral bands amongst numerous different sensors is proposed. The base unit for comparison in this work is the relative spectral response. From this input, determination of a what may constitute equivalence can be related by a user, based on their own conceptualisation of equivalence.

Strategic Integration of Multiple Bioinformatics Resources for System Level Analysis of Biological Networks.

PubMed

D'Souza, Mark; Sulakhe, Dinanath; Wang, Sheng; Xie, Bing; Hashemifar, Somaye; Taylor, Andrew; Dubchak, Inna; Conrad Gilliam, T; Maltsev, Natalia

2017-01-01

Recent technological advances in genomics allow the production of biological data at unprecedented tera- and petabyte scales. Efficient mining of these vast and complex datasets for the needs of biomedical research critically depends on a seamless integration of the clinical, genomic, and experimental information with prior knowledge about genotype-phenotype relationships. Such experimental data accumulated in publicly available databases should be accessible to a variety of algorithms and analytical pipelines that drive computational analysis and data mining.We present an integrated computational platform Lynx (Sulakhe et al., Nucleic Acids Res 44:D882-D887, 2016) ( http://lynx.cri.uchicago.edu ), a web-based database and knowledge extraction engine. It provides advanced search capabilities and a variety of algorithms for enrichment analysis and network-based gene prioritization. It gives public access to the Lynx integrated knowledge base (LynxKB) and its analytical tools via user-friendly web services and interfaces. The Lynx service-oriented architecture supports annotation and analysis of high-throughput experimental data. Lynx tools assist the user in extracting meaningful knowledge from LynxKB and experimental data, and in the generation of weighted hypotheses regarding the genes and molecular mechanisms contributing to human phenotypes or conditions of interest. The goal of this integrated platform is to support the end-to-end analytical needs of various translational projects.

Opportunity and Challenges for Migrating Big Data Analytics in Cloud

NASA Astrophysics Data System (ADS)

Amitkumar Manekar, S.; Pradeepini, G., Dr.

2017-08-01

Big Data Analytics is a big word now days. As per demanding and more scalable process data generation capabilities, data acquisition and storage become a crucial issue. Cloud storage is a majorly usable platform; the technology will become crucial to executives handling data powered by analytics. Now a day’s trend towards “big data-as-a-service” is talked everywhere. On one hand, cloud-based big data analytics exactly tackle in progress issues of scale, speed, and cost. But researchers working to solve security and other real-time problem of big data migration on cloud based platform. This article specially focused on finding possible ways to migrate big data to cloud. Technology which support coherent data migration and possibility of doing big data analytics on cloud platform is demanding in natute for new era of growth. This article also gives information about available technology and techniques for migration of big data in cloud.

Signal-on electrochemical detection of antibiotics at zeptomole level based on target-aptamer binding triggered multiple recycling amplification.

PubMed

Wang, Hongzhi; Wang, Yu; Liu, Su; Yu, Jinghua; Guo, Yuna; Xu, Ying; Huang, Jiadong

2016-06-15

In the work, a signal-on electrochemical DNA sensor based on multiple amplification for ultrasensitive detection of antibiotics has been reported. In the presence of target, the ingeniously designed hairpin probe (HP1) is opened and the polymerase-assisted target recycling amplification is triggered, resulting in autonomous generation of secondary target. It is worth noting that the produced secondary target could not only hybridize with other HP1, but also displace the Helper from the electrode. Consequently, methylene blue labeled HP2 forms a "close" probe structure, and the increase of signal is monitored. The increasing current provides an ultrasensitive electrochemical detection for antibiotics down to 1.3 fM. To our best knowledge, such work is the first report about multiple recycling amplification combing with signal-on sensing strategy, which has been utilized for quantitative determination of antibiotics. It would be further used as a general strategy associated with more analytical techniques toward the detection of a wide spectrum of analytes. Thus, it holds great potential for the development of ultrasensitive biosensing platform for the applications in bioanalysis, disease diagnostics, and clinical biomedicine. Copyright © 2016 Elsevier B.V. All rights reserved.

Design, implementation and multisite evaluation of a system suitability protocol for the quantitative assessment of instrument performance in liquid chromatography-multiple reaction monitoring-MS (LC-MRM-MS).

PubMed

Abbatiello, Susan E; Mani, D R; Schilling, Birgit; Maclean, Brendan; Zimmerman, Lisa J; Feng, Xingdong; Cusack, Michael P; Sedransk, Nell; Hall, Steven C; Addona, Terri; Allen, Simon; Dodder, Nathan G; Ghosh, Mousumi; Held, Jason M; Hedrick, Victoria; Inerowicz, H Dorota; Jackson, Angela; Keshishian, Hasmik; Kim, Jong Won; Lyssand, John S; Riley, C Paige; Rudnick, Paul; Sadowski, Pawel; Shaddox, Kent; Smith, Derek; Tomazela, Daniela; Wahlander, Asa; Waldemarson, Sofia; Whitwell, Corbin A; You, Jinsam; Zhang, Shucha; Kinsinger, Christopher R; Mesri, Mehdi; Rodriguez, Henry; Borchers, Christoph H; Buck, Charles; Fisher, Susan J; Gibson, Bradford W; Liebler, Daniel; Maccoss, Michael; Neubert, Thomas A; Paulovich, Amanda; Regnier, Fred; Skates, Steven J; Tempst, Paul; Wang, Mu; Carr, Steven A

2013-09-01

Multiple reaction monitoring (MRM) mass spectrometry coupled with stable isotope dilution (SID) and liquid chromatography (LC) is increasingly used in biological and clinical studies for precise and reproducible quantification of peptides and proteins in complex sample matrices. Robust LC-SID-MRM-MS-based assays that can be replicated across laboratories and ultimately in clinical laboratory settings require standardized protocols to demonstrate that the analysis platforms are performing adequately. We developed a system suitability protocol (SSP), which employs a predigested mixture of six proteins, to facilitate performance evaluation of LC-SID-MRM-MS instrument platforms, configured with nanoflow-LC systems interfaced to triple quadrupole mass spectrometers. The SSP was designed for use with low multiplex analyses as well as high multiplex approaches when software-driven scheduling of data acquisition is required. Performance was assessed by monitoring of a range of chromatographic and mass spectrometric metrics including peak width, chromatographic resolution, peak capacity, and the variability in peak area and analyte retention time (RT) stability. The SSP, which was evaluated in 11 laboratories on a total of 15 different instruments, enabled early diagnoses of LC and MS anomalies that indicated suboptimal LC-MRM-MS performance. The observed range in variation of each of the metrics scrutinized serves to define the criteria for optimized LC-SID-MRM-MS platforms for routine use, with pass/fail criteria for system suitability performance measures defined as peak area coefficient of variation <0.15, peak width coefficient of variation <0.15, standard deviation of RT <0.15 min (9 s), and the RT drift <0.5min (30 s). The deleterious effect of a marginally performing LC-SID-MRM-MS system on the limit of quantification (LOQ) in targeted quantitative assays illustrates the use and need for a SSP to establish robust and reliable system performance. Use of a SSP helps to ensure that analyte quantification measurements can be replicated with good precision within and across multiple laboratories and should facilitate more widespread use of MRM-MS technology by the basic biomedical and clinical laboratory research communities.

Design, Implementation and Multisite Evaluation of a System Suitability Protocol for the Quantitative Assessment of Instrument Performance in Liquid Chromatography-Multiple Reaction Monitoring-MS (LC-MRM-MS)*

PubMed Central

Abbatiello, Susan E.; Mani, D. R.; Schilling, Birgit; MacLean, Brendan; Zimmerman, Lisa J.; Feng, Xingdong; Cusack, Michael P.; Sedransk, Nell; Hall, Steven C.; Addona, Terri; Allen, Simon; Dodder, Nathan G.; Ghosh, Mousumi; Held, Jason M.; Hedrick, Victoria; Inerowicz, H. Dorota; Jackson, Angela; Keshishian, Hasmik; Kim, Jong Won; Lyssand, John S.; Riley, C. Paige; Rudnick, Paul; Sadowski, Pawel; Shaddox, Kent; Smith, Derek; Tomazela, Daniela; Wahlander, Asa; Waldemarson, Sofia; Whitwell, Corbin A.; You, Jinsam; Zhang, Shucha; Kinsinger, Christopher R.; Mesri, Mehdi; Rodriguez, Henry; Borchers, Christoph H.; Buck, Charles; Fisher, Susan J.; Gibson, Bradford W.; Liebler, Daniel; MacCoss, Michael; Neubert, Thomas A.; Paulovich, Amanda; Regnier, Fred; Skates, Steven J.; Tempst, Paul; Wang, Mu; Carr, Steven A.

2013-01-01

Multiple reaction monitoring (MRM) mass spectrometry coupled with stable isotope dilution (SID) and liquid chromatography (LC) is increasingly used in biological and clinical studies for precise and reproducible quantification of peptides and proteins in complex sample matrices. Robust LC-SID-MRM-MS-based assays that can be replicated across laboratories and ultimately in clinical laboratory settings require standardized protocols to demonstrate that the analysis platforms are performing adequately. We developed a system suitability protocol (SSP), which employs a predigested mixture of six proteins, to facilitate performance evaluation of LC-SID-MRM-MS instrument platforms, configured with nanoflow-LC systems interfaced to triple quadrupole mass spectrometers. The SSP was designed for use with low multiplex analyses as well as high multiplex approaches when software-driven scheduling of data acquisition is required. Performance was assessed by monitoring of a range of chromatographic and mass spectrometric metrics including peak width, chromatographic resolution, peak capacity, and the variability in peak area and analyte retention time (RT) stability. The SSP, which was evaluated in 11 laboratories on a total of 15 different instruments, enabled early diagnoses of LC and MS anomalies that indicated suboptimal LC-MRM-MS performance. The observed range in variation of each of the metrics scrutinized serves to define the criteria for optimized LC-SID-MRM-MS platforms for routine use, with pass/fail criteria for system suitability performance measures defined as peak area coefficient of variation <0.15, peak width coefficient of variation <0.15, standard deviation of RT <0.15 min (9 s), and the RT drift <0.5min (30 s). The deleterious effect of a marginally performing LC-SID-MRM-MS system on the limit of quantification (LOQ) in targeted quantitative assays illustrates the use and need for a SSP to establish robust and reliable system performance. Use of a SSP helps to ensure that analyte quantification measurements can be replicated with good precision within and across multiple laboratories and should facilitate more widespread use of MRM-MS technology by the basic biomedical and clinical laboratory research communities. PMID:23689285

Developing AN Emergency Response Model for Offshore Oil Spill Disaster Management Using Spatial Decision Support System (sdss)

NASA Astrophysics Data System (ADS)

Balogun, Abdul-Lateef; Matori, Abdul-Nasir; Wong Toh Kiak, Kelvin

2018-04-01

Environmental resources face severe risks during offshore oil spill disasters and Geographic Information System (GIS) Environmental Sensitivity Index (ESI) maps are increasingly being used as response tools to minimize the huge impacts of these spills. However, ESI maps are generally unable to independently harmonize the diverse preferences of the multiple stakeholders' involved in the response process, causing rancour and delay in response time. This paper's Spatial Decision Support System (SDSS) utilizes the Analytic Hierarchy Process (AHP) model to perform tradeoffs in determining the most significant resources to be secured considering the limited resources and time available to perform the response operation. The AHP approach is used to aggregate the diverse preferences of the stakeholders and reach a consensus. These preferences, represented as priority weights, are incorporated in a GIS platform to generate Environmental sensitivity risk (ESR) maps. The ESR maps provide a common operational platform and consistent situational awareness for the multiple parties involved in the emergency response operation thereby minimizing discord among the response teams and saving the most valuable resources.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Akyol, Bora A.; Allwardt, Craig H.; Beech, Zachary W.

VOLTTRON is a flexible, reliable, and scalable platform for distributed control and sensing. VOLTTRON serves in four primary roles: •A reference platform for researchers to quickly develop control applications for transactive energy. •A reference platform with flexible data store support for energy analytics applications either in academia or in commercial enterprise. •A platform from which commercial enterprise can develop products without license issues and easily integrate into their product line. •An accelerator to drive industry adoption of transactive energy and advanced building energy analytics. Pacific Northwest National Laboratory, with funding from the U.S. Department of Energy’s Building Technologies Office, developedmore » and maintains VOLTTRON as an open-source community project. VOLTTRON source code includes agent execution software; agents that perform critical services that enable and enhance VOLTTRON functionality; and numerous agents that utilize the platform to perform a specific function (fault detection, demand response, etc.). The platform supports energy, operational, and financial transactions between networked entities (equipment, organizations, buildings, grid, etc.) and enhance the control infrastructure of existing buildings through the use of open-source device communication, control protocols, and integrated analytics.« less

A silver nanoislands on silica spheres platform: enriching trace amounts of analytes for ultrasensitive and reproducible SERS detection.

PubMed

Wang, Zhongshun; Feng, Lei; Xiao, Dongyang; Li, Ning; Li, Yao; Cao, Danfeng; Shi, Zuosen; Cui, Zhanchen; Lu, Nan

2017-11-09

The performance of surface-enhanced Raman scattering (SERS) for detecting trace amounts of analytes depends highly on the enrichment of the diluted analytes into a small region that can be detected. A super-hydrophobic delivery (SHD) process is an excellent process to enrich even femtomolar analytes for SERS detection. However, it is still challenging to easily fabricate a low detection limit, high sensitivity and reproducible SHD-SERS substrate. In this article, we present a cost-effective and fewer-step method to fabricate a SHD-SERS substrate, named the "silver nanoislands on silica spheres" (SNOSS) platform. It is easily prepared via the thermal evaporation of silver onto a layer of super-hydrophobic paint, which contains single-scale surface-fluorinated silica spheres. The SNOSS platform performs reproducible detection, which brings the relative standard deviation down to 8.85% and 5.63% for detecting 10 -8 M R6G in one spot and spot-to-spot set-ups, respectively. The coefficient of determination (R 2 ) is 0.9773 for R6G. The SNOSS platform can be applied to the quantitative detection of analytes whose concentrations range from sub-micromolar to femtomolar levels.

Shifting from Stewardship to Analytics of Massive Science Data

NASA Astrophysics Data System (ADS)

Crichton, D. J.; Doyle, R.; Law, E.; Hughes, S.; Huang, T.; Mahabal, A.

2015-12-01

Currently, the analysis of large data collections is executed through traditional computational and data analysis approaches, which require users to bring data to their desktops and perform local data analysis. Data collection, archiving and analysis from future remote sensing missions, be it from earth science satellites, planetary robotic missions, or massive radio observatories may not scale as more capable instruments stress existing architectural approaches and systems due to more continuous data streams, data from multiple observational platforms, and measurements and models from different agencies. A new paradigm is needed in order to increase the productivity and effectiveness of scientific data analysis. This paradigm must recognize that architectural choices, data processing, management, analysis, etc are interrelated, and must be carefully coordinated in any system that aims to allow efficient, interactive scientific exploration and discovery to exploit massive data collections. Future observational systems, including satellite and airborne experiments, and research in climate modeling will significantly increase the size of the data requiring new methodological approaches towards data analytics where users can more effectively interact with the data and apply automated mechanisms for data reduction, reduction and fusion across these massive data repositories. This presentation will discuss architecture, use cases, and approaches for developing a big data analytics strategy across multiple science disciplines.

DREAM: Distributed Resources for the Earth System Grid Federation (ESGF) Advanced Management

NASA Astrophysics Data System (ADS)

Williams, D. N.

2015-12-01

The data associated with climate research is often generated, accessed, stored, and analyzed on a mix of unique platforms. The volume, variety, velocity, and veracity of this data creates unique challenges as climate research attempts to move beyond stand-alone platforms to a system that truly integrates dispersed resources. Today, sharing data across multiple facilities is often a challenge due to the large variance in supporting infrastructures. This results in data being accessed and downloaded many times, which requires significant amounts of resources, places a heavy analytic development burden on the end users, and mismanaged resources. Working across U.S. federal agencies, international agencies, and multiple worldwide data centers, and spanning seven international network organizations, the Earth System Grid Federation (ESGF) has begun to solve this problem. Its architecture employs a system of geographically distributed peer nodes that are independently administered yet united by common federation protocols and application programming interfaces. However, significant challenges remain, including workflow provenance, modular and flexible deployment, scalability of a diverse set of computational resources, and more. Expanding on the existing ESGF, the Distributed Resources for the Earth System Grid Federation Advanced Management (DREAM) will ensure that the access, storage, movement, and analysis of the large quantities of data that are processed and produced by diverse science projects can be dynamically distributed with proper resource management. This system will enable data from an infinite number of diverse sources to be organized and accessed from anywhere on any device (including mobile platforms). The approach offers a powerful roadmap for the creation and integration of a unified knowledge base of an entire ecosystem, including its many geophysical, geographical, social, political, agricultural, energy, transportation, and cyber aspects. The resulting aggregation of data combined with analytics services has the potential to generate an informational universe and knowledge system of unprecedented size and value to the scientific community, downstream applications, decision makers, and the public.

Highly sensitive microfluidic paper-based photoelectrochemical sensing platform based on reversible photo-oxidation products and morphology-preferable multi-plate ZnO nanoflowers.

PubMed

Kong, Qingkun; Wang, Yanhu; Zhang, Lina; Xu, Caixia; Yu, Jinghua

2018-07-01

A microfluidic paper-based analytical device (μPAD) was simply constructed for highly sensitive detection of L-glutamic acid and L-cysteine. The μPAD featured with two functional zones on one strip of paper achieved by preferable multi-plate ZnO nanoflowers (ZnO NFs) and molecularly imprinting polymer (MIP) membranes. The as-designed μPAD was established based on the inherent relation between the photo-oxidation products and photoelectrochemical (PEC) performance with the highly sensitive detection of biomolecules. The ZnO NFs were utilized to produce photo-oxidation products by driving the reaction between ferrocenemethanol and photogenerated holes under ultraviolet light. The photo-oxidation products easily flowed to MIP membranes along the hydrophilic channel via capillary action. MIP membranes as the receptors specifically recognized the analytes as well as decreased the electron loss by blocking the reduction reaction between electrons and photo-oxidation products. The PEC response was obtained in the processes of electrons transfer and exhibited the direct relationships corresponding to the concentrations of target analytes. The μPAD showed the detection limits toward L-glutamic acid and L-cysteine as low as 9.6 pM and 24 pM, respectively. Moreover, it is interesting to point out that ZnO NFs nanostructure shows superior PEC signal compared with those of ZnO nanospheres, nanosheets, and nanorod arrays. In current work, photo-oxidation products are utilized to achieve highly sensitive PEC detection for biomolecules under ultraviolet light as well as avoid the effects of multiple modifications in the same region on the reproducibility, which is beneficial for opening up rich possibility for designing more efficient analytical strategy. Copyright © 2018 Elsevier B.V. All rights reserved.

eTRIKS platform: Conception and operation of a highly scalable cloud-based platform for translational research and applications development.

PubMed

Bussery, Justin; Denis, Leslie-Alexandre; Guillon, Benjamin; Liu, Pengfeï; Marchetti, Gino; Rahal, Ghita

2018-04-01

We describe the genesis, design and evolution of a computing platform designed and built to improve the success rate of biomedical translational research. The eTRIKS project platform was developed with the aim of building a platform that can securely host heterogeneous types of data and provide an optimal environment to run tranSMART analytical applications. Many types of data can now be hosted, including multi-OMICS data, preclinical laboratory data and clinical information, including longitudinal data sets. During the last two years, the platform has matured into a robust translational research knowledge management system that is able to host other data mining applications and support the development of new analytical tools. Copyright © 2018 Elsevier Ltd. All rights reserved.

Citrate-based fluorescent materials for low-cost chloride sensing in the diagnosis of Cystic Fibrosis.

PubMed

Kim, Jimin P; Xie, Zhiwei; Creer, Michael; Liu, Zhiwen; Yang, Jian

2017-01-01

Chloride is an essential electrolyte that maintains homeostasis within the body, where abnormal chloride levels in biological fluids may indicate various diseases such as Cystic Fibrosis. However, current analytical solutions for chloride detection fail to meet the clinical needs of both high performance and low material or labor costs, hindering translation into clinical settings. Here we present a new class of fluorescence chloride sensors derived from a facile citrate -based synthesis platform that utilize dynamic quenching mechanisms. Based on this low-cost platform, we demonstrate for the first time a selective sensing strategy that uses a single fluorophore to detect multiple halides simultaneously, promising both selectivity and automation to improve performance and reduce labor costs. We also demonstrate the clinical utility of citrate-based sensors as a new sweat chloride test method for the diagnosis of Cystic Fibrosis by performing analytical validation with sweat controls and clinical validation with sweat from individuals with or without Cystic Fibrosis. Lastly, molecular modeling studies reveal the structural mechanism behind chloride sensing, serving to expand this class of fluorescence sensors with improved chloride sensitivities. Thus citrate-based fluorescent materials may enable low-cost, automated multi-analysis systems for simpler, yet accurate, point-of-care diagnostics that can be readily translated into clinical settings. More broadly, a wide range of medical, industrial, and environmental applications can be achieved with such a facile synthesis platform, demonstrated in our citrate-based biodegradable polymers with intrinsic fluorescence sensing.

Reverse phase protein microarrays: fluorometric and colorimetric detection.

PubMed

Gallagher, Rosa I; Silvestri, Alessandra; Petricoin, Emanuel F; Liotta, Lance A; Espina, Virginia

2011-01-01

The Reverse Phase Protein Microarray (RPMA) is an array platform used to quantitate proteins and their posttranslationally modified forms. RPMAs are applicable for profiling key cellular signaling pathways and protein networks, allowing direct comparison of the activation state of proteins from multiple samples within the same array. The RPMA format consists of proteins immobilized directly on a nitrocellulose substratum. The analyte is subsequently probed with a primary antibody and a series of reagents for signal amplification and detection. Due to the diversity, low concentration, and large dynamic range of protein analytes, RPMAs require stringent signal amplification methods, high quality image acquisition, and software capable of precisely analyzing spot intensities on an array. Microarray detection strategies can be either fluorescent or colorimetric. The choice of a detection system depends on (a) the expected analyte concentration, (b) type of microarray imaging system, and (c) type of sample. The focus of this chapter is to describe RPMA detection and imaging using fluorescent and colorimetric (diaminobenzidine (DAB)) methods.

openECA Platform and Analytics Alpha Test Results

DOE Office of Scientific and Technical Information (OSTI.GOV)

Robertson, Russell

The objective of the Open and Extensible Control and Analytics (openECA) Platform for Phasor Data project is to develop an open source software platform that significantly accelerates the production, use, and ongoing development of real-time decision support tools, automated control systems, and off-line planning systems that (1) incorporate high-fidelity synchrophasor data and (2) enhance system reliability while enabling the North American Electric Reliability Corporation (NERC) operating functions of reliability coordinator, transmission operator, and/or balancing authority to be executed more effectively.

openECA Platform and Analytics Beta Demonstration Results

DOE Office of Scientific and Technical Information (OSTI.GOV)

Robertson, Russell

The objective of the Open and Extensible Control and Analytics (openECA) Platform for Phasor Data project is to develop an open source software platform that significantly accelerates the production, use, and ongoing development of real-time decision support tools, automated control systems, and off-line planning systems that (1) incorporate high-fidelity synchrophasor data and (2) enhance system reliability while enabling the North American Electric Reliability Corporation (NERC) operating functions of reliability coordinator, transmission operator, and/or balancing authority to be executed more effectively.

Poly(dimethylsiloxane) microchip-based immunoassay with multiple reaction zones: Toward on-chip multiplex detection platform

DOE Office of Scientific and Technical Information (OSTI.GOV)

Shao, Guocheng; Wang, Jun; Li, Zhaohui

2011-09-20

In this work, a poly(dimethylsiloxane) (PDMS) microchip-based immuno-sensing platform with integrated pneumatic micro valves is described. The microchip was fabricated with multiple layer soft lithography technology. By controlling the activation status of corresponding valves, reagent flows in the microchannel network can be well manipulated so that immuno-reactions only take place at designated reaction zones (DRZs). Four DRZs are included in the prototype microchip. Since these DRZs are all isolated from each other by micro valves, cross contamination is prevented. Using the inner surface of the all-PDMS microchannel as immunoassay substrate, on-chip sandwich format solid phase immunoassay was performed to demonstratemore » the feasibility of this immuno-sensing platform. Mouse IgG and fluorescein isothiocyanate (FITC) were used as the model analyte and the signal reporter respectively. Only 10 ul sample is needed for the assay and low detection limit of 5 ng/ml (≈33 pM) was achieved though low-cost polyclonal antibodies were used in our experiment for feasibility study only. The encouraging results from mouse IgG immunoassay proved the feasibility of our microchip design. With slight modification of the assay protocol, the same chip design can be used for multi-target detection and can provide a simple, cost-effective and integrated microchip solution for multiplex immunoassay applications.« less

Analytical interference of HBOC-201 (Hemopure, a synthetic hemoglobin-based oxygen carrier) on four common clinical chemistry platforms.

PubMed

Korte, Erik A; Pozzi, Nicole; Wardrip, Nina; Ayyoubi, M Tayyeb; Jortani, Saeed A

2018-07-01

There are 13 million blood transfusions each year in the US. Limitations in the donor pool, storage capabilities, mass casualties, access in remote locations and reactivity of donors all limit the availability of transfusable blood products to patients. HBOC-201 (Hemopure®) is a second-generation glutaraldehyde-polymer of bovine hemoglobin, which can serve as an "oxygen bridge" to maintain oxygen carrying capacity while transfusion products are unavailable. Hemopure presents the advantages of extended shelf life, ambient storage, and limited reactive potential, but its extracellular location can also cause significant interference in modern laboratory analyzers similar to severe hemolysis. Observed error in 26 commonly measured analytes was determined on 4 different analytical platforms in plasma from a patient therapeutically transfused Hemopure as well as donor blood spiked with Hemopure at a level equivalent to the therapeutic loading dose (10% v/v). Significant negative error ratios >50% of the total allowable error (>0.5tAE) were reported in 23/104 assays (22.1%), positive bias of >0.5tAE in 26/104 assays (25.0%), and acceptable bias between -0.5tAE and 0.5tAE error ratio was reported in 44/104 (42.3%). Analysis failed in the presence of Hemopure in 11/104 (10.6%). Observed error is further subdivided by platform, wavelength, dilution and reaction method. Administration of Hemopure (or other hemoglobin-based oxygen carriers) presents a challenge to laboratorians tasked with analyzing patient specimens. We provide laboratorians with a reference to evaluate patient samples, select optimal analytical platforms for specific analytes, and predict possible bias beyond the 4 analytical platforms included in this study. Copyright © 2018 Elsevier B.V. All rights reserved.

Multiplexed Liquid Chromatography-Multiple Reaction Monitoring Mass Spectrometry Quantification of Cancer Signaling Proteins

PubMed Central

Chen, Yi; Fisher, Kate J.; Lloyd, Mark; Wood, Elizabeth R.; Coppola, Domenico; Siegel, Erin; Shibata, David; Chen, Yian A.; Koomen, John M.

2017-01-01

Quantitative evaluation of protein expression across multiple cancer-related signaling pathways (e.g. Wnt/β-catenin, TGF-β, receptor tyrosine kinases (RTK), MAP kinases, NF-κB, and apoptosis) in tumor tissues may enable the development of a molecular profile for each individual tumor that can aid in the selection of appropriate targeted cancer therapies. Here, we describe the development of a broadly applicable protocol to develop and implement quantitative mass spectrometry assays using cell line models and frozen tissue specimens from colon cancer patients. Cell lines are used to develop peptide-based assays for protein quantification, which are incorporated into a method based on SDS-PAGE protein fractionation, in-gel digestion, and liquid chromatography-multiple reaction monitoring mass spectrometry (LC-MRM/MS). This analytical platform is then applied to frozen tumor tissues. This protocol can be broadly applied to the study of human disease using multiplexed LC-MRM assays. PMID:28808993

E-HOSPITAL - A Digital Workbench for Hospital Operations and Services Planning Using Information Technology and Algebraic Languages.

PubMed

Gartner, Daniel; Padman, Rema

2017-01-01

In this paper, we describe the development of a unified framework and a digital workbench for the strategic, tactical and operational hospital management plan driven by information technology and analytics. The workbench can be used not only by multiple stakeholders in the healthcare delivery setting, but also for pedagogical purposes on topics such as healthcare analytics, services management, and information systems. This tool combines the three classical hierarchical decision-making levels in one integrated environment. At each level, several decision problems can be chosen. Extensions of mathematical models from the literature are presented and incorporated into the digital platform. In a case study using real-world data, we demonstrate how we used the workbench to inform strategic capacity planning decisions in a multi-hospital, multi-stakeholder setting in the United Kingdom.

SOCRAT Platform Design: A Web Architecture for Interactive Visual Analytics Applications

PubMed Central

Kalinin, Alexandr A.; Palanimalai, Selvam; Dinov, Ivo D.

2018-01-01

The modern web is a successful platform for large scale interactive web applications, including visualizations. However, there are no established design principles for building complex visual analytics (VA) web applications that could efficiently integrate visualizations with data management, computational transformation, hypothesis testing, and knowledge discovery. This imposes a time-consuming design and development process on many researchers and developers. To address these challenges, we consider the design requirements for the development of a module-based VA system architecture, adopting existing practices of large scale web application development. We present the preliminary design and implementation of an open-source platform for Statistics Online Computational Resource Analytical Toolbox (SOCRAT). This platform defines: (1) a specification for an architecture for building VA applications with multi-level modularity, and (2) methods for optimizing module interaction, re-usage, and extension. To demonstrate how this platform can be used to integrate a number of data management, interactive visualization, and analysis tools, we implement an example application for simple VA tasks including raw data input and representation, interactive visualization and analysis. PMID:29630069

SOCRAT Platform Design: A Web Architecture for Interactive Visual Analytics Applications.

PubMed

Kalinin, Alexandr A; Palanimalai, Selvam; Dinov, Ivo D

2017-04-01

The modern web is a successful platform for large scale interactive web applications, including visualizations. However, there are no established design principles for building complex visual analytics (VA) web applications that could efficiently integrate visualizations with data management, computational transformation, hypothesis testing, and knowledge discovery. This imposes a time-consuming design and development process on many researchers and developers. To address these challenges, we consider the design requirements for the development of a module-based VA system architecture, adopting existing practices of large scale web application development. We present the preliminary design and implementation of an open-source platform for Statistics Online Computational Resource Analytical Toolbox (SOCRAT). This platform defines: (1) a specification for an architecture for building VA applications with multi-level modularity, and (2) methods for optimizing module interaction, re-usage, and extension. To demonstrate how this platform can be used to integrate a number of data management, interactive visualization, and analysis tools, we implement an example application for simple VA tasks including raw data input and representation, interactive visualization and analysis.

MyDiabetesMyWay

PubMed Central

Wake, Deborah J.; He, Jinzhang; Czesak, Anna Maria; Mughal, Fezan; Cunningham, Scott G.

2016-01-01

MyDiabetesMyWay (MDMW) is an award-wining national electronic personal health record and self-management platform for diabetes patients in Scotland. This platform links multiple national institutional and patient-recorded data sources to provide a unique resource for patient care and self-management. This review considers the current evidence for online interventions in diabetes and discusses these in the context of current and ongoing developments for MDMW. Evaluation of MDMW through patient reported outcomes demonstrates a positive impact on self-management. User feedback has highlighted barriers to uptake and has guided platform evolution from an education resource website to an electronic personal health record now encompassing remote monitoring, communication tools and personalized education links. Challenges in delivering digital interventions for long-term conditions include integration of data between institutional and personal recorded sources to perform big data analytics and facilitating technology use in those with disabilities, low digital literacy, low socioeconomic status and in minority groups. The potential for technology supported health improvement is great, but awareness and adoption by health workers and patients remains a significant barrier. PMID:27162192

Hybrid Integrated Label-Free Chemical and Biological Sensors

PubMed Central

Mehrabani, Simin; Maker, Ashley J.; Armani, Andrea M.

2014-01-01

Label-free sensors based on electrical, mechanical and optical transduction methods have potential applications in numerous areas of society, ranging from healthcare to environmental monitoring. Initial research in the field focused on the development and optimization of various sensor platforms fabricated from a single material system, such as fiber-based optical sensors and silicon nanowire-based electrical sensors. However, more recent research efforts have explored designing sensors fabricated from multiple materials. For example, synthetic materials and/or biomaterials can also be added to the sensor to improve its response toward analytes of interest. By leveraging the properties of the different material systems, these hybrid sensing devices can have significantly improved performance over their single-material counterparts (better sensitivity, specificity, signal to noise, and/or detection limits). This review will briefly discuss some of the methods for creating these multi-material sensor platforms and the advances enabled by this design approach. PMID:24675757

Launching genomics into the cloud: deployment of Mercury, a next generation sequence analysis pipeline.

PubMed

Reid, Jeffrey G; Carroll, Andrew; Veeraraghavan, Narayanan; Dahdouli, Mahmoud; Sundquist, Andreas; English, Adam; Bainbridge, Matthew; White, Simon; Salerno, William; Buhay, Christian; Yu, Fuli; Muzny, Donna; Daly, Richard; Duyk, Geoff; Gibbs, Richard A; Boerwinkle, Eric

2014-01-29

Massively parallel DNA sequencing generates staggering amounts of data. Decreasing cost, increasing throughput, and improved annotation have expanded the diversity of genomics applications in research and clinical practice. This expanding scale creates analytical challenges: accommodating peak compute demand, coordinating secure access for multiple analysts, and sharing validated tools and results. To address these challenges, we have developed the Mercury analysis pipeline and deployed it in local hardware and the Amazon Web Services cloud via the DNAnexus platform. Mercury is an automated, flexible, and extensible analysis workflow that provides accurate and reproducible genomic results at scales ranging from individuals to large cohorts. By taking advantage of cloud computing and with Mercury implemented on the DNAnexus platform, we have demonstrated a powerful combination of a robust and fully validated software pipeline and a scalable computational resource that, to date, we have applied to more than 10,000 whole genome and whole exome samples.

Hybrid integrated label-free chemical and biological sensors.

PubMed

Mehrabani, Simin; Maker, Ashley J; Armani, Andrea M

2014-03-26

Label-free sensors based on electrical, mechanical and optical transduction methods have potential applications in numerous areas of society, ranging from healthcare to environmental monitoring. Initial research in the field focused on the development and optimization of various sensor platforms fabricated from a single material system, such as fiber-based optical sensors and silicon nanowire-based electrical sensors. However, more recent research efforts have explored designing sensors fabricated from multiple materials. For example, synthetic materials and/or biomaterials can also be added to the sensor to improve its response toward analytes of interest. By leveraging the properties of the different material systems, these hybrid sensing devices can have significantly improved performance over their single-material counterparts (better sensitivity, specificity, signal to noise, and/or detection limits). This review will briefly discuss some of the methods for creating these multi-material sensor platforms and the advances enabled by this design approach.

Analytical aspects of plant metabolite profiling platforms: current standings and future aims.

PubMed

Seger, Christoph; Sturm, Sonja

2007-02-01

Over the past years, metabolic profiling has been established as a comprehensive systems biology tool. Mass spectrometry or NMR spectroscopy-based technology platforms combined with unsupervised or supervised multivariate statistical methodologies allow a deep insight into the complex metabolite patterns of plant-derived samples. Within this review, we provide a thorough introduction to the analytical hard- and software requirements of metabolic profiling platforms. Methodological limitations are addressed, and the metabolic profiling workflow is exemplified by summarizing recent applications ranging from model systems to more applied topics.

A multiple pointing-mount control strategy for space platforms

NASA Technical Reports Server (NTRS)

Johnson, C. D.

1992-01-01

A new disturbance-adaptive control strategy for multiple pointing-mount space platforms is proposed and illustrated by consideration of a simplified 3-link dynamic model of a multiple pointing-mount space platform. Simulation results demonstrate the effectiveness of the new platform control strategy. The simulation results also reveal a system 'destabilization phenomena' that can occur if the set of individual platform-mounted experiment controllers are 'too responsive.'

An integrated platform for directly widely-targeted quantitative analysis of feces part I: Platform configuration and method validation.

PubMed

Song, Yuelin; Song, Qingqing; Li, Jun; Zheng, Jiao; Li, Chun; Zhang, Yuan; Zhang, Lingling; Jiang, Yong; Tu, Pengfei

2016-07-08

Direct analysis is of great importance to understand the real chemical profile of a given sample, notably biological materials, because either chemical degradation or diverse errors and uncertainties might be resulted from sophisticated protocols. In comparison with biofluids, it is still challenging for direct analysis of solid biological samples using high performance liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS). Herein, a new analytical platform was configured by online hyphenating pressurized liquid extraction (PLE), turbulent flow chromatography (TFC), and LC-MS/MS. A facile, but robust PLE module was constructed based on the phenomenon that noticeable back-pressure can be generated during rapid fluid passing through a narrow tube. TFC column that is advantageous at extracting low molecular analytes from rushing fluid was employed to link at the outlet of the PLE module to capture constituents-of-interest. An electronic 6-port/2-position valve was introduced between TFC column and LC-MS/MS to fragment each measurement into extraction and elution phases, whereas LC-MS/MS took the charge of analyte separation and monitoring. As a proof of concept, simultaneous determination of 24 endogenous substances including eighteen steroids, five eicosanoids, and one porphyrin in feces was carried out in this paper. Method validation assays demonstrated the analytical platform to be qualified for directly simultaneous measurement of diverse endogenous analytes in fecal matrices. Application of this integrated platform on homolog-focused profiling of feces is discussed in a companion paper. Copyright © 2016 Elsevier B.V. All rights reserved.

Simultaneous, untargeted metabolic profiling of polar and nonpolar metabolites by LC-Q-TOF mass spectrometry.

PubMed

Kirkwood, Jay S; Maier, Claudia; Stevens, Jan F

2013-05-01

At its most ambitious, untargeted metabolomics aims to characterize and quantify all of the metabolites in a given system. Metabolites are often present at a broad range of concentrations and possess diverse physical properties complicating this task. Performing multiple sample extractions, concentrating sample extracts, and using several separation and detection methods are common strategies to overcome these challenges but require a great amount of resources. This protocol describes the untargeted, metabolic profiling of polar and nonpolar metabolites with a single extraction and using a single analytical platform. © 2013 by John Wiley & Sons, Inc.

ICDA: A Platform for Intelligent Care Delivery Analytics

PubMed Central

Gotz, David; Stavropoulos, Harry; Sun, Jimeng; Wang, Fei

2012-01-01

The identification of high-risk patients is a critical component in improving patient outcomes and managing costs. This paper describes the Intelligent Care Delivery Analytics platform (ICDA), a system which enables risk assessment analytics that process large collections of dynamic electronic medical data to identify at-risk patients. ICDA works by ingesting large volumes of data into a common data model, then orchestrating a collection of analytics that identify at-risk patients. It also provides an interactive environment through which users can access and review the analytics results. In addition, ICDA provides APIs via which analytics results can be retrieved to surface in external applications. A detailed review of ICDA’s architecture is provided. Descriptions of four use cases are included to illustrate ICDA’s application within two different data environments. These use cases showcase the system’s flexibility and exemplify the types of analytics it enables. PMID:23304296

Engineering of Surface Chemistry for Enhanced Sensitivity in Nanoporous Interferometric Sensing Platforms.

PubMed

Law, Cheryl Suwen; Sylvia, Georgina M; Nemati, Madieh; Yu, Jingxian; Losic, Dusan; Abell, Andrew D; Santos, Abel

2017-03-15

We explore new approaches to engineering the surface chemistry of interferometric sensing platforms based on nanoporous anodic alumina (NAA) and reflectometric interference spectroscopy (RIfS). Two surface engineering strategies are presented, namely (i) selective chemical functionalization of the inner surface of NAA pores with amine-terminated thiol molecules and (ii) selective chemical functionalization of the top surface of NAA with dithiol molecules. The strong molecular interaction of Au 3+ ions with thiol-containing functional molecules of alkane chain or peptide character provides a model sensing system with which to assess the sensitivity of these NAA platforms by both molecular feature and surface engineering. Changes in the effective optical thickness of the functionalized NAA photonic films (i.e., sensing principle), in response to gold ions, are monitored in real-time by RIfS. 6-Amino-1-hexanethiol (inner surface) and 1,6-hexanedithiol (top surface), the most sensitive functional molecules from approaches i and ii, respectively, were combined into a third sensing strategy whereby the NAA platforms are functionalized on both the top and inner surfaces concurrently. Engineering of the surface according to this approach resulted in an additive enhancement in sensitivity of up to 5-fold compared to previously reported systems. This study advances the rational engineering of surface chemistry for interferometric sensing on nanoporous platforms with potential applications for real-time monitoring of multiple analytes in dynamic environments.

Rapid prototyping and evaluation of programmable SIMD SDR processors in LISA

NASA Astrophysics Data System (ADS)

Chen, Ting; Liu, Hengzhu; Zhang, Botao; Liu, Dongpei

2013-03-01

With the development of international wireless communication standards, there is an increase in computational requirement for baseband signal processors. Time-to-market pressure makes it impossible to completely redesign new processors for the evolving standards. Due to its high flexibility and low power, software defined radio (SDR) digital signal processors have been proposed as promising technology to replace traditional ASIC and FPGA fashions. In addition, there are large numbers of parallel data processed in computation-intensive functions, which fosters the development of single instruction multiple data (SIMD) architecture in SDR platform. So a new way must be found to prototype the SDR processors efficiently. In this paper we present a bit-and-cycle accurate model of programmable SIMD SDR processors in a machine description language LISA. LISA is a language for instruction set architecture which can gain rapid model at architectural level. In order to evaluate the availability of our proposed processor, three common baseband functions, FFT, FIR digital filter and matrix multiplication have been mapped on the SDR platform. Analytical results showed that the SDR processor achieved the maximum of 47.1% performance boost relative to the opponent processor.

The BioExtract Server: a web-based bioinformatic workflow platform

PubMed Central

Lushbough, Carol M.; Jennewein, Douglas M.; Brendel, Volker P.

2011-01-01

The BioExtract Server (bioextract.org) is an open, web-based system designed to aid researchers in the analysis of genomic data by providing a platform for the creation of bioinformatic workflows. Scientific workflows are created within the system by recording tasks performed by the user. These tasks may include querying multiple, distributed data sources, saving query results as searchable data extracts, and executing local and web-accessible analytic tools. The series of recorded tasks can then be saved as a reproducible, sharable workflow available for subsequent execution with the original or modified inputs and parameter settings. Integrated data resources include interfaces to the National Center for Biotechnology Information (NCBI) nucleotide and protein databases, the European Molecular Biology Laboratory (EMBL-Bank) non-redundant nucleotide database, the Universal Protein Resource (UniProt), and the UniProt Reference Clusters (UniRef) database. The system offers access to numerous preinstalled, curated analytic tools and also provides researchers with the option of selecting computational tools from a large list of web services including the European Molecular Biology Open Software Suite (EMBOSS), BioMoby, and the Kyoto Encyclopedia of Genes and Genomes (KEGG). The system further allows users to integrate local command line tools residing on their own computers through a client-side Java applet. PMID:21546552

AI based HealthCare Platform for Real Time, Predictive and Prescriptive Analytics using Reactive Programming

NASA Astrophysics Data System (ADS)

Kaur, Jagreet; Singh Mann, Kulwinder, Dr.

2018-01-01

AI in Healthcare needed to bring real, actionable insights and Individualized insights in real time for patients and Doctors to support treatment decisions., We need a Patient Centred Platform for integrating EHR Data, Patient Data, Prescriptions, Monitoring, Clinical research and Data. This paper proposes a generic architecture for enabling AI based healthcare analytics Platform by using open sources Technologies Apache beam, Apache Flink Apache Spark, Apache NiFi, Kafka, Tachyon, Gluster FS, NoSQL- Elasticsearch, Cassandra. This paper will show the importance of applying AI based predictive and prescriptive analytics techniques in Health sector. The system will be able to extract useful knowledge that helps in decision making and medical monitoring in real-time through an intelligent process analysis and big data processing.

System Architecture Development for Energy and Water Infrastructure Data Management and Geovisual Analytics

NASA Astrophysics Data System (ADS)

Berres, A.; Karthik, R.; Nugent, P.; Sorokine, A.; Myers, A.; Pang, H.

2017-12-01

Building an integrated data infrastructure that can meet the needs of a sustainable energy-water resource management requires a robust data management and geovisual analytics platform, capable of cross-domain scientific discovery and knowledge generation. Such a platform can facilitate the investigation of diverse complex research and policy questions for emerging priorities in Energy-Water Nexus (EWN) science areas. Using advanced data analytics, machine learning techniques, multi-dimensional statistical tools, and interactive geovisualization components, such a multi-layered federated platform is being developed, the Energy-Water Nexus Knowledge Discovery Framework (EWN-KDF). This platform utilizes several enterprise-grade software design concepts and standards such as extensible service-oriented architecture, open standard protocols, event-driven programming model, enterprise service bus, and adaptive user interfaces to provide a strategic value to the integrative computational and data infrastructure. EWN-KDF is built on the Compute and Data Environment for Science (CADES) environment in Oak Ridge National Laboratory (ORNL).

MRMPlus: an open source quality control and assessment tool for SRM/MRM assay development.

PubMed

Aiyetan, Paul; Thomas, Stefani N; Zhang, Zhen; Zhang, Hui

2015-12-12

Selected and multiple reaction monitoring involves monitoring a multiplexed assay of proteotypic peptides and associated transitions in mass spectrometry runs. To describe peptide and associated transitions as stable, quantifiable, and reproducible representatives of proteins of interest, experimental and analytical validation is required. However, inadequate and disparate analytical tools and validation methods predispose assay performance measures to errors and inconsistencies. Implemented as a freely available, open-source tool in the platform independent Java programing language, MRMPlus computes analytical measures as recommended recently by the Clinical Proteomics Tumor Analysis Consortium Assay Development Working Group for "Tier 2" assays - that is, non-clinical assays sufficient enough to measure changes due to both biological and experimental perturbations. Computed measures include; limit of detection, lower limit of quantification, linearity, carry-over, partial validation of specificity, and upper limit of quantification. MRMPlus streamlines assay development analytical workflow and therefore minimizes error predisposition. MRMPlus may also be used for performance estimation for targeted assays not described by the Assay Development Working Group. MRMPlus' source codes and compiled binaries can be freely downloaded from https://bitbucket.org/paiyetan/mrmplusgui and https://bitbucket.org/paiyetan/mrmplusgui/downloads respectively.

Engineering of a miniaturized, robotic clinical laboratory

PubMed Central

Nourse, Marilyn B.; Engel, Kate; Anekal, Samartha G.; Bailey, Jocelyn A.; Bhatta, Pradeep; Bhave, Devayani P.; Chandrasekaran, Shekar; Chen, Yutao; Chow, Steven; Das, Ushati; Galil, Erez; Gong, Xinwei; Gessert, Steven F.; Ha, Kevin D.; Hu, Ran; Hyland, Laura; Jammalamadaka, Arvind; Jayasurya, Karthik; Kemp, Timothy M.; Kim, Andrew N.; Lee, Lucie S.; Liu, Yang Lily; Nguyen, Alphonso; O'Leary, Jared; Pangarkar, Chinmay H.; Patel, Paul J.; Quon, Ken; Ramachandran, Pradeep L.; Rappaport, Amy R.; Roy, Joy; Sapida, Jerald F.; Sergeev, Nikolay V.; Shee, Chandan; Shenoy, Renuka; Sivaraman, Sharada; Sosa‐Padilla, Bernardo; Tran, Lorraine; Trent, Amanda; Waggoner, Thomas C.; Wodziak, Dariusz; Yuan, Amy; Zhao, Peter; Holmes, Elizabeth A.

2018-01-01

Abstract The ability to perform laboratory testing near the patient and with smaller blood volumes would benefit patients and physicians alike. We describe our design of a miniaturized clinical laboratory system with three components: a hardware platform (ie, the miniLab) that performs preanalytical and analytical processing steps using miniaturized sample manipulation and detection modules, an assay‐configurable cartridge that provides consumable materials and assay reagents, and a server that communicates bidirectionally with the miniLab to manage assay‐specific protocols and analyze, store, and report results (i.e., the virtual analyzer). The miniLab can detect analytes in blood using multiple methods, including molecular diagnostics, immunoassays, clinical chemistry, and hematology. Analytical performance results show that our qualitative Zika virus assay has a limit of detection of 55 genomic copies/ml. For our anti‐herpes simplex virus type 2 immunoglobulin G, lipid panel, and lymphocyte subset panel assays, the miniLab has low imprecision, and method comparison results agree well with those from the United States Food and Drug Administration‐cleared devices. With its small footprint and versatility, the miniLab has the potential to provide testing of a range of analytes in decentralized locations. PMID:29376134

Engineering of a miniaturized, robotic clinical laboratory.

PubMed

Nourse, Marilyn B; Engel, Kate; Anekal, Samartha G; Bailey, Jocelyn A; Bhatta, Pradeep; Bhave, Devayani P; Chandrasekaran, Shekar; Chen, Yutao; Chow, Steven; Das, Ushati; Galil, Erez; Gong, Xinwei; Gessert, Steven F; Ha, Kevin D; Hu, Ran; Hyland, Laura; Jammalamadaka, Arvind; Jayasurya, Karthik; Kemp, Timothy M; Kim, Andrew N; Lee, Lucie S; Liu, Yang Lily; Nguyen, Alphonso; O'Leary, Jared; Pangarkar, Chinmay H; Patel, Paul J; Quon, Ken; Ramachandran, Pradeep L; Rappaport, Amy R; Roy, Joy; Sapida, Jerald F; Sergeev, Nikolay V; Shee, Chandan; Shenoy, Renuka; Sivaraman, Sharada; Sosa-Padilla, Bernardo; Tran, Lorraine; Trent, Amanda; Waggoner, Thomas C; Wodziak, Dariusz; Yuan, Amy; Zhao, Peter; Young, Daniel L; Robertson, Channing R; Holmes, Elizabeth A

2018-01-01

The ability to perform laboratory testing near the patient and with smaller blood volumes would benefit patients and physicians alike. We describe our design of a miniaturized clinical laboratory system with three components: a hardware platform (ie, the miniLab) that performs preanalytical and analytical processing steps using miniaturized sample manipulation and detection modules, an assay-configurable cartridge that provides consumable materials and assay reagents, and a server that communicates bidirectionally with the miniLab to manage assay-specific protocols and analyze, store, and report results (i.e., the virtual analyzer). The miniLab can detect analytes in blood using multiple methods, including molecular diagnostics, immunoassays, clinical chemistry, and hematology. Analytical performance results show that our qualitative Zika virus assay has a limit of detection of 55 genomic copies/ml. For our anti-herpes simplex virus type 2 immunoglobulin G, lipid panel, and lymphocyte subset panel assays, the miniLab has low imprecision, and method comparison results agree well with those from the United States Food and Drug Administration-cleared devices. With its small footprint and versatility, the miniLab has the potential to provide testing of a range of analytes in decentralized locations.

Fabrication of Three-dimensional Paper-based Microfluidic Devices for Immunoassays.

PubMed

Fernandes, Syrena C; Wilson, Daniel J; Mace, Charles R

2017-03-09

Paper wicks fluids autonomously due to capillary action. By patterning paper with hydrophobic barriers, the transport of fluids can be controlled and directed within a layer of paper. Moreover, stacking multiple layers of patterned paper creates sophisticated three-dimensional microfluidic networks that can support the development of analytical and bioanalytical assays. Paper-based microfluidic devices are inexpensive, portable, easy to use, and require no external equipment to operate. As a result, they hold great promise as a platform for point-of-care diagnostics. In order to properly evaluate the utility and analytical performance of paper-based devices, suitable methods must be developed to ensure their manufacture is reproducible and at a scale that is appropriate for laboratory settings. In this manuscript, a method to fabricate a general device architecture that can be used for paper-based immunoassays is described. We use a form of additive manufacturing (multi-layer lamination) to prepare devices that comprise multiple layers of patterned paper and patterned adhesive. In addition to demonstrating the proper use of these three-dimensional paper-based microfluidic devices with an immunoassay for human chorionic gonadotropin (hCG), errors in the manufacturing process that may result in device failures are discussed. We expect this approach to manufacturing paper-based devices will find broad utility in the development of analytical applications designed specifically for limited-resource settings.

Graphene Nanoplatelet-Polymer Chemiresistive Sensor Arrays for the Detection and Discrimination of Chemical Warfare Agent Simulants.

PubMed

Wiederoder, Michael S; Nallon, Eric C; Weiss, Matt; McGraw, Shannon K; Schnee, Vincent P; Bright, Collin J; Polcha, Michael P; Paffenroth, Randy; Uzarski, Joshua R

2017-11-22

A cross-reactive array of semiselective chemiresistive sensors made of polymer-graphene nanoplatelet (GNP) composite coated electrodes was examined for detection and discrimination of chemical warfare agents (CWA). The arrays employ a set of chemically diverse polymers to generate a unique response signature for multiple CWA simulants and background interferents. The developed sensors' signal remains consistent after repeated exposures to multiple analytes for up to 5 days with a similar signal magnitude across different replicate sensors with the same polymer-GNP coating. An array of 12 sensors each coated with a different polymer-GNP mixture was exposed 100 times to a cycle of single analyte vapors consisting of 5 chemically similar CWA simulants and 8 common background interferents. The collected data was vector normalized to reduce concentration dependency, z-scored to account for baseline drift and signal-to-noise ratio, and Kalman filtered to reduce noise. The processed data was dimensionally reduced with principal component analysis and analyzed with four different machine learning algorithms to evaluate discrimination capabilities. For 5 similarly structured CWA simulants alone 100% classification accuracy was achieved. For all analytes tested 99% classification accuracy was achieved demonstrating the CWA discrimination capabilities of the developed system. The novel sensor fabrication methods and data processing techniques are attractive for development of sensor platforms for discrimination of CWA and other classes of chemical vapors.

Ultrasensitive microchip based on smart microgel for real-time online detection of trace threat analytes.

PubMed

Lin, Shuo; Wang, Wei; Ju, Xiao-Jie; Xie, Rui; Liu, Zhuang; Yu, Hai-Rong; Zhang, Chuan; Chu, Liang-Yin

2016-02-23

Real-time online detection of trace threat analytes is critical for global sustainability, whereas the key challenge is how to efficiently convert and amplify analyte signals into simple readouts. Here we report an ultrasensitive microfluidic platform incorporated with smart microgel for real-time online detection of trace threat analytes. The microgel can swell responding to specific stimulus in flowing solution, resulting in efficient conversion of the stimulus signal into significantly amplified signal of flow-rate change; thus highly sensitive, fast, and selective detection can be achieved. We demonstrate this by incorporating ion-recognizable microgel for detecting trace Pb(2+), and connecting our platform with pipelines of tap water and wastewater for real-time online Pb(2+) detection to achieve timely pollution warning and terminating. This work provides a generalizable platform for incorporating myriad stimuli-responsive microgels to achieve ever-better performance for real-time online detection of various trace threat molecules, and may expand the scope of applications of detection techniques.

JGME-ALiEM Hot Topics in Medical Education: Analysis of a Multimodal Online Discussion About Team-Based Learning.

PubMed

Riddell, Jeff; Patocka, Catherine; Lin, Michelle; Sherbino, Jonathan

2017-02-01

Team-based learning (TBL) is an instructional method that is being increasingly incorporated in health professions education, although use in graduate medical education (GME) has been more limited. To curate and describe themes that emerged from a virtual journal club discussion about TBL in GME, held across multiple digital platforms, while also evaluating the use of social media in online academic discussions. The Journal of Graduate Medical Education ( JGME ) and the Academic Life in Emergency Medicine blog facilitated a weeklong, open-access, virtual journal club on the 2015 JGME article "Use of Team-Based Learning Pedagogy for Internal Medicine Ambulatory Resident Teaching." Using 4 stimulus questions (hosted on a blog as a starting framework), we facilitated discussions via the blog, Twitter, and Google Hangouts on Air platforms. We evaluated 2-week web analytics and performed a thematic analysis of the discussion. The virtual journal club reached a large international audience as exemplified by the blog page garnering 685 page views from 241 cities in 42 countries. Our thematic analysis identified 4 domains relevant to TBL in GME: (1) the benefits and barriers to TBL; (2) the design of teams; (3) the role of assessment and peer evaluation; and (4) crowdsourced TBL resources. The virtual journal club provided a novel forum across multiple social media platforms, engaging authors, content experts, and the health professions education community in a discussion about the importance, impediments to implementation, available resources, and logistics of adopting TBL in GME.

Big Data Analytics with Datalog Queries on Spark.

PubMed

Shkapsky, Alexander; Yang, Mohan; Interlandi, Matteo; Chiu, Hsuan; Condie, Tyson; Zaniolo, Carlo

2016-01-01

There is great interest in exploiting the opportunity provided by cloud computing platforms for large-scale analytics. Among these platforms, Apache Spark is growing in popularity for machine learning and graph analytics. Developing efficient complex analytics in Spark requires deep understanding of both the algorithm at hand and the Spark API or subsystem APIs (e.g., Spark SQL, GraphX). Our BigDatalog system addresses the problem by providing concise declarative specification of complex queries amenable to efficient evaluation. Towards this goal, we propose compilation and optimization techniques that tackle the important problem of efficiently supporting recursion in Spark. We perform an experimental comparison with other state-of-the-art large-scale Datalog systems and verify the efficacy of our techniques and effectiveness of Spark in supporting Datalog-based analytics.

Big Data Analytics with Datalog Queries on Spark

PubMed Central

Shkapsky, Alexander; Yang, Mohan; Interlandi, Matteo; Chiu, Hsuan; Condie, Tyson; Zaniolo, Carlo

2017-01-01

There is great interest in exploiting the opportunity provided by cloud computing platforms for large-scale analytics. Among these platforms, Apache Spark is growing in popularity for machine learning and graph analytics. Developing efficient complex analytics in Spark requires deep understanding of both the algorithm at hand and the Spark API or subsystem APIs (e.g., Spark SQL, GraphX). Our BigDatalog system addresses the problem by providing concise declarative specification of complex queries amenable to efficient evaluation. Towards this goal, we propose compilation and optimization techniques that tackle the important problem of efficiently supporting recursion in Spark. We perform an experimental comparison with other state-of-the-art large-scale Datalog systems and verify the efficacy of our techniques and effectiveness of Spark in supporting Datalog-based analytics. PMID:28626296

Dual-colored graphene quantum dots-labeled nanoprobes/graphene oxide: functional carbon materials for respective and simultaneous detection of DNA and thrombin

NASA Astrophysics Data System (ADS)

Qian, Zhao Sheng; Shan, Xiao Yue; Chai, Lu Jing; Chen, Jian Rong; Feng, Hui

2014-10-01

Convenient and simultaneous detection of multiple biomarkers such as DNA and proteins with biocompatible materials and good analytical performance still remains a challenge. Herein, we report the respective and simultaneous detection of DNA and bovine α-thrombin (thrombin) entirely based on biocompatible carbon materials through a specially designed fluorescence on-off-on process. Colorful fluorescence, high emission efficiency, good photostability and excellent compatibility enables graphene quantum dots (GQDs) as the best choice for fluorophores in bioprobes, and thus two-colored GQDs as labeling fluorophores were chemically bonded with specific oligonucleotide sequence and aptamer to prepare two probes targeting the DNA and thrombin, respectively. Each probe can be assembled on the graphene oxide (GO) platform spontaneously by π-π stacking and electrostatic attraction; as a result, fast electron transfer in the assembly efficiently quenches the fluorescence of probe. The presence of DNA or thrombin can trigger the self-recognition between capturing a nucleotide sequence and its target DNA or between thrombin and its aptamer due to their specific hybridization and duplex DNA structures or the formation of apatamer-substrate complex, which is taken advantage of in order to achieve a separate quantitative analysis of DNA and thrombin. A dual-functional biosensor for simultaneous detection of DNA and thrombin was also constructed by self-assembly of two probes with distinct colors and GO platform, and was further evaluated with the presence of various concentrations of DNA and thrombin. Both biosensors serving as a general detection model for multiple species exhibit outstanding analytical performance, and are expected to be applied in vivo because of the excellent biocompatibility of their used materials.

Machine Learning Technologies Translates Vigilant Surveillance Satellite Big Data into Predictive Alerts for Environmental Stressors

NASA Astrophysics Data System (ADS)

Johnson, S. P.; Rohrer, M. E.

2017-12-01

The application of scientific research pertaining to satellite imaging and data processing has facilitated the development of dynamic methodologies and tools that utilize nanosatellites and analytical platforms to address the increasing scope, scale, and intensity of emerging environmental threats to national security. While the use of remotely sensed data to monitor the environment at local and global scales is not a novel proposition, the application of advances in nanosatellites and analytical platforms are capable of overcoming the data availability and accessibility barriers that have historically impeded the timely detection, identification, and monitoring of these stressors. Commercial and university-based applications of these technologies were used to identify and evaluate their capacity as security-motivated environmental monitoring tools. Presently, nanosatellites can provide consumers with 1-meter resolution imaging, frequent revisits, and customizable tasking, allowing users to define an appropriate temporal scale for high resolution data collection that meets their operational needs. Analytical platforms are capable of ingesting increasingly large and diverse volumes of data, delivering complex analyses in the form of interpretation-ready data products and solutions. The synchronous advancement of these technologies creates the capability of analytical platforms to deliver interpretable products from persistently collected high-resolution data that meet varying temporal and geographic scale requirements. In terms of emerging environmental threats, these advances translate into customizable and flexible tools that can respond to and accommodate the evolving nature of environmental stressors. This presentation will demonstrate the capability of nanosatellites and analytical platforms to provide timely, relevant, and actionable information that enables environmental analysts and stakeholders to make informed decisions regarding the prevention, intervention, and prediction of emerging environmental threats.

Analysis of Pre-Analytic Factors Affecting the Success of Clinical Next-Generation Sequencing of Solid Organ Malignancies.

PubMed

Chen, Hui; Luthra, Rajyalakshmi; Goswami, Rashmi S; Singh, Rajesh R; Roy-Chowdhuri, Sinchita

2015-08-28

Application of next-generation sequencing (NGS) technology to routine clinical practice has enabled characterization of personalized cancer genomes to identify patients likely to have a response to targeted therapy. The proper selection of tumor sample for downstream NGS based mutational analysis is critical to generate accurate results and to guide therapeutic intervention. However, multiple pre-analytic factors come into play in determining the success of NGS testing. In this review, we discuss pre-analytic requirements for AmpliSeq PCR-based sequencing using Ion Torrent Personal Genome Machine (PGM) (Life Technologies), a NGS sequencing platform that is often used by clinical laboratories for sequencing solid tumors because of its low input DNA requirement from formalin fixed and paraffin embedded tissue. The success of NGS mutational analysis is affected not only by the input DNA quantity but also by several other factors, including the specimen type, the DNA quality, and the tumor cellularity. Here, we review tissue requirements for solid tumor NGS based mutational analysis, including procedure types, tissue types, tumor volume and fraction, decalcification, and treatment effects.

Microarray-integrated optoelectrofluidic immunoassay system

PubMed Central

Han, Dongsik

2016-01-01

A microarray-based analytical platform has been utilized as a powerful tool in biological assay fields. However, an analyte depletion problem due to the slow mass transport based on molecular diffusion causes low reaction efficiency, resulting in a limitation for practical applications. This paper presents a novel method to improve the efficiency of microarray-based immunoassay via an optically induced electrokinetic phenomenon by integrating an optoelectrofluidic device with a conventional glass slide-based microarray format. A sample droplet was loaded between the microarray slide and the optoelectrofluidic device on which a photoconductive layer was deposited. Under the application of an AC voltage, optically induced AC electroosmotic flows caused by a microarray-patterned light actively enhanced the mass transport of target molecules at the multiple assay spots of the microarray simultaneously, which reduced tedious reaction time from more than 30 min to 10 min. Based on this enhancing effect, a heterogeneous immunoassay with a tiny volume of sample (5 μl) was successfully performed in the microarray-integrated optoelectrofluidic system using immunoglobulin G (IgG) and anti-IgG, resulting in improved efficiency compared to the static environment. Furthermore, the application of multiplex assays was also demonstrated by multiple protein detection. PMID:27190571

Microarray-integrated optoelectrofluidic immunoassay system.

PubMed

Han, Dongsik; Park, Je-Kyun

2016-05-01

A microarray-based analytical platform has been utilized as a powerful tool in biological assay fields. However, an analyte depletion problem due to the slow mass transport based on molecular diffusion causes low reaction efficiency, resulting in a limitation for practical applications. This paper presents a novel method to improve the efficiency of microarray-based immunoassay via an optically induced electrokinetic phenomenon by integrating an optoelectrofluidic device with a conventional glass slide-based microarray format. A sample droplet was loaded between the microarray slide and the optoelectrofluidic device on which a photoconductive layer was deposited. Under the application of an AC voltage, optically induced AC electroosmotic flows caused by a microarray-patterned light actively enhanced the mass transport of target molecules at the multiple assay spots of the microarray simultaneously, which reduced tedious reaction time from more than 30 min to 10 min. Based on this enhancing effect, a heterogeneous immunoassay with a tiny volume of sample (5 μl) was successfully performed in the microarray-integrated optoelectrofluidic system using immunoglobulin G (IgG) and anti-IgG, resulting in improved efficiency compared to the static environment. Furthermore, the application of multiplex assays was also demonstrated by multiple protein detection.

Comparison of standard- and nano-flow liquid chromatography platforms for MRM-based quantitation of putative plasma biomarker proteins.

PubMed

Percy, Andrew J; Chambers, Andrew G; Yang, Juncong; Domanski, Dominik; Borchers, Christoph H

2012-09-01

The analytical performance of a standard-flow ultra-high-performance liquid chromatography (UHPLC) and a nano-flow high-performance liquid chromatography (HPLC) system, interfaced to the same state-of-the-art triple-quadrupole mass spectrometer, were compared for the multiple reaction monitoring (MRM)-mass spectrometry (MS)-based quantitation of a panel of 48 high-to-moderate-abundance cardiovascular disease-related plasma proteins. After optimization of the MRM transitions for sensitivity and testing for chemical interference, the optimum sensitivity, loading capacity, gradient, and retention-time reproducibilities were determined. We previously demonstrated the increased robustness of the standard-flow platform, but we expected that the standard-flow platform would have an overall lower sensitivity. This study was designed to determine if this decreased sensitivity could be compensated for by increased sample loading. Significantly fewer interferences with the MRM transitions were found for the standard-flow platform than for the nano-flow platform (2 out of 103 transitions compared with 42 out of 103 transitions, respectively), which demonstrates the importance of interference-testing when nano-flow systems are used. Using only interference-free transitions, 36 replicate LC/MRM-MS analyses resulted in equal signal reproducibilities between the two platforms (9.3 % coefficient of variation (CV) for 88 peptide targets), with superior retention-time precision for the standard-flow platform (0.13 vs. 6.1 % CV). Surprisingly, for 41 of the 81 proteotypic peptides in the final assay, the standard-flow platform was more sensitive while for 9 of 81 the nano-flow platform was more sensitive. For these 81 peptides, there was a good correlation between the two sets of results (R(2) = 0.98, slope = 0.97). Overall, the standard-flow platform had superior performance metrics for most peptides, and is a good choice if sufficient sample is available.

Target-responsive DNA hydrogel mediated "stop-flow" microfluidic paper-based analytic device for rapid, portable and visual detection of multiple targets.

PubMed

Wei, Xiaofeng; Tian, Tian; Jia, Shasha; Zhu, Zhi; Ma, Yanli; Sun, Jianjun; Lin, Zhenyu; Yang, Chaoyong James

2015-04-21

A versatile point-of-care assay platform was developed for simultaneous detection of multiple targets based on a microfluidic paper-based analytic device (μPAD) using a target-responsive hydrogel to mediate fluidic flow and signal readout. An aptamer-cross-linked hydrogel was used as a target-responsive flow regulator in the μPAD. In the absence of a target, the hydrogel is formed in the flow channel, stopping the flow in the μPAD and preventing the colored indicator from traveling to the final observation spot, thus yielding a "signal off" readout. In contrast, in the presence of a target, no hydrogel is formed because of the preferential interaction of target and aptamer. This allows free fluidic flow in the μPAD, carrying the indicator to the observation spot and producing a "signal on" readout. The device is inexpensive to fabricate, easy to use, and disposable after detection. Testing results can be obtained within 6 min by the naked eye via a simple loading operation without the need for any auxiliary equipment. Multiple targets, including cocaine, adenosine, and Pb(2+), can be detected simultaneously, even in complex biological matrices such as urine. The reported method offers simple, low cost, rapid, user-friendly, point-of-care testing, which will be useful in many applications.

A Laboratory-Based System for Managing and Distributing Publically Funded Geochemical Data in a Collaborative Environment

NASA Astrophysics Data System (ADS)

McInnes, B.; Brown, A.; Liffers, M.

2015-12-01

Publically funded laboratories have a responsibility to generate, archive and disseminate analytical data to the research community. Laboratory managers know however, that a long tail of analytical effort never escapes researchers' thumb drives once they leave the lab. This work reports on a research data management project (Digital Mineralogy Library) where integrated hardware and software systems automatically archive and deliver analytical data and metadata to institutional and community data portals. The scientific objective of the DML project was to quantify the modal abundance of heavy minerals extracted from key lithological units in Western Australia. The selected analytical platform was a TESCAN Integrated Mineral Analyser (TIMA) that uses EDS-based mineral classification software to image and quantify mineral abundance and grain size at micron scale resolution. The analytical workflow used a bespoke laboratory information management system (LIMS) to orchestrate: (1) the preparation of grain mounts with embedded QR codes that serve as enduring links between physical samples and analytical data, (2) the assignment of an International Geo Sample Number (IGSN) and Digital Object Identifier (DOI) to each grain mount via the System for Earth Sample Registry (SESAR), (3) the assignment of a DOI to instrument metadata via Research Data Australia, (4) the delivery of TIMA analytical outputs, including spatially registered mineralogy images and mineral abundance data, to an institutionally-based data management server, and (5) the downstream delivery of a final data product via a Google Maps interface such as the AuScope Discovery Portal. The modular design of the system permits the networking of multiple instruments within a single site or multiple collaborating research institutions. Although sharing analytical data does provide new opportunities for the geochemistry community, the creation of an open data network requires: (1) adopting open data reporting standards and conventions, (2) requiring instrument manufacturers and software developers to deliver and process data in formats compatible with open standards, and (3) public funding agencies to incentivise researchers, laboratories and institutions to make their data open and accessible to consumers.

ArcGIS Framework for Scientific Data Analysis and Serving

NASA Astrophysics Data System (ADS)

Xu, H.; Ju, W.; Zhang, J.

2015-12-01

ArcGIS is a platform for managing, visualizing, analyzing, and serving geospatial data. Scientific data as part of the geospatial data features multiple dimensions (X, Y, time, and depth) and large volume. Multidimensional mosaic dataset (MDMD), a newly enhanced data model in ArcGIS, models the multidimensional gridded data (e.g. raster or image) as a hypercube and enables ArcGIS's capabilities to handle the large volume and near-real time scientific data. Built on top of geodatabase, the MDMD stores the dimension values and the variables (2D arrays) in a geodatabase table which allows accessing a slice or slices of the hypercube through a simple query and supports animating changes along time or vertical dimension using ArcGIS desktop or web clients. Through raster types, MDMD can manage not only netCDF, GRIB, and HDF formats but also many other formats or satellite data. It is scalable and can handle large data volume. The parallel geo-processing engine makes the data ingestion fast and easily. Raster function, definition of a raster processing algorithm, is a very important component in ArcGIS platform for on-demand raster processing and analysis. The scientific data analytics is achieved through the MDMD and raster function templates which perform on-demand scientific computation with variables ingested in the MDMD. For example, aggregating monthly average from daily data; computing total rainfall of a year; calculating heat index for forecasting data, and identifying fishing habitat zones etc. Addtionally, MDMD with the associated raster function templates can be served through ArcGIS server as image services which provide a framework for on-demand server side computation and analysis, and the published services can be accessed by multiple clients such as ArcMap, ArcGIS Online, JavaScript, REST, WCS, and WMS. This presentation will focus on the MDMD model and raster processing templates. In addtion, MODIS land cover, NDFD weather service, and HYCOM ocean model will be used to illustrate how ArcGIS platform and MDMD model can facilitate scientific data visualization and analytics and how the analysis results can be shared to more audience through ArcGIS Online and Portal.

Large-scale monitoring of shorebird populations using count data and N-mixture models: Black Oystercatcher (Haematopus bachmani) surveys by land and sea

USGS Publications Warehouse

Lyons, James E.; Andrew, Royle J.; Thomas, Susan M.; Elliott-Smith, Elise; Evenson, Joseph R.; Kelly, Elizabeth G.; Milner, Ruth L.; Nysewander, David R.; Andres, Brad A.

2012-01-01

Large-scale monitoring of bird populations is often based on count data collected across spatial scales that may include multiple physiographic regions and habitat types. Monitoring at large spatial scales may require multiple survey platforms (e.g., from boats and land when monitoring coastal species) and multiple survey methods. It becomes especially important to explicitly account for detection probability when analyzing count data that have been collected using multiple survey platforms or methods. We evaluated a new analytical framework, N-mixture models, to estimate actual abundance while accounting for multiple detection biases. During May 2006, we made repeated counts of Black Oystercatchers (Haematopus bachmani) from boats in the Puget Sound area of Washington (n = 55 sites) and from land along the coast of Oregon (n = 56 sites). We used a Bayesian analysis of N-mixture models to (1) assess detection probability as a function of environmental and survey covariates and (2) estimate total Black Oystercatcher abundance during the breeding season in the two regions. Probability of detecting individuals during boat-based surveys was 0.75 (95% credible interval: 0.42–0.91) and was not influenced by tidal stage. Detection probability from surveys conducted on foot was 0.68 (0.39–0.90); the latter was not influenced by fog, wind, or number of observers but was ~35% lower during rain. The estimated population size was 321 birds (262–511) in Washington and 311 (276–382) in Oregon. N-mixture models provide a flexible framework for modeling count data and covariates in large-scale bird monitoring programs designed to understand population change.

A platform for real-time online health analytics during spaceflight

NASA Astrophysics Data System (ADS)

McGregor, Carolyn

Monitoring the health and wellbeing of astronauts during spaceflight is an important aspect of any manned mission. To date the monitoring has been based on a sequential set of discontinuous samplings of physiological data to support initial studies on aspects such as weightlessness, and its impact on the cardiovascular system and to perform proactive monitoring for health status. The research performed and the real-time monitoring has been hampered by the lack of a platform to enable a more continuous approach to real-time monitoring. While any spaceflight is monitored heavily by Mission Control, an important requirement within the context of any spaceflight setting and in particular where there are extended periods with a lack of communication with Mission Control, is the ability for the mission to operate in an autonomous manner. This paper presents a platform to enable real-time astronaut monitoring for prognostics and health management within space medicine using online health analytics. The platform is based on extending previous online health analytics research known as the Artemis and Artemis Cloud platforms which have demonstrated their relevance for multi-patient, multi-diagnosis and multi-stream temporal analysis in real-time for clinical management and research within Neonatal Intensive Care. Artemis and Artemis Cloud source data from a range of medical devices capable of transmission of the signal via wired or wireless connectivity and hence are well suited to process real-time data acquired from astronauts. A key benefit of this platform is its ability to monitor their health and wellbeing onboard the mission as well as enabling the astronaut's physiological data, and other clinical data, to be sent to the platform components at Mission Control at each stage when that communication is available. As a result, researchers at Mission Control would be able to simulate, deploy and tailor predictive analytics and diagnostics during the same spaceflight for - reater medical support.

Information Management Platform for Data Analytics and Aggregation (IMPALA) System Design Document

NASA Technical Reports Server (NTRS)

Carnell, Andrew; Akinyelu, Akinyele

2016-01-01

The System Design document tracks the design activities that are performed to guide the integration, installation, verification, and acceptance testing of the IMPALA Platform. The inputs to the design document are derived from the activities recorded in Tasks 1 through 6 of the Statement of Work (SOW), with the proposed technical solution being the completion of Phase 1-A. With the documentation of the architecture of the IMPALA Platform and the installation steps taken, the SDD will be a living document, capturing the details about capability enhancements and system improvements to the IMPALA Platform to provide users in development of accurate and precise analytical models. The IMPALA Platform infrastructure team, data architecture team, system integration team, security management team, project manager, NASA data scientists and users are the intended audience of this document. The IMPALA Platform is an assembly of commercial-off-the-shelf (COTS) products installed on an Apache-Hadoop platform. User interface details for the COTS products will be sourced from the COTS tools vendor documentation. The SDD is a focused explanation of the inputs, design steps, and projected outcomes of every design activity for the IMPALA Platform through installation and validation.

A new paper-based platform technology for point-of-care diagnostics.

PubMed

Gerbers, Roman; Foellscher, Wilke; Chen, Hong; Anagnostopoulos, Constantine; Faghri, Mohammad

2014-10-21

Currently, the Lateral flow Immunoassays (LFIAs) are not able to perform complex multi-step immunodetection tests because of their inability to introduce multiple reagents in a controlled manner to the detection area autonomously. In this research, a point-of-care (POC) paper-based lateral flow immunosensor was developed incorporating a novel microfluidic valve technology. Layers of paper and tape were used to create a three-dimensional structure to form the fluidic network. Unlike the existing LFIAs, multiple directional valves are embedded in the test strip layers to control the order and the timing of mixing for the sample and multiple reagents. In this paper, we report a four-valve device which autonomously directs three different fluids to flow sequentially over the detection area. As proof of concept, a three-step alkaline phosphatase based Enzyme-Linked ImmunoSorbent Assay (ELISA) protocol with Rabbit IgG as the model analyte was conducted to prove the suitability of the device for immunoassays. The detection limit of about 4.8 fm was obtained.

Platform for Automated Real-Time High Performance Analytics on Medical Image Data.

PubMed

Allen, William J; Gabr, Refaat E; Tefera, Getaneh B; Pednekar, Amol S; Vaughn, Matthew W; Narayana, Ponnada A

2018-03-01

Biomedical data are quickly growing in volume and in variety, providing clinicians an opportunity for better clinical decision support. Here, we demonstrate a robust platform that uses software automation and high performance computing (HPC) resources to achieve real-time analytics of clinical data, specifically magnetic resonance imaging (MRI) data. We used the Agave application programming interface to facilitate communication, data transfer, and job control between an MRI scanner and an off-site HPC resource. In this use case, Agave executed the graphical pipeline tool GRAphical Pipeline Environment (GRAPE) to perform automated, real-time, quantitative analysis of MRI scans. Same-session image processing will open the door for adaptive scanning and real-time quality control, potentially accelerating the discovery of pathologies and minimizing patient callbacks. We envision this platform can be adapted to other medical instruments, HPC resources, and analytics tools.

pH-Triggered Molecular Alignment for Reproducible SERS Detection via an AuNP/Nanocellulose Platform

PubMed Central

Wei, Haoran; Vikesland, Peter J.

2015-01-01

The low affinity of neutral and hydrophobic molecules towards noble metal surfaces hinders their detection by surface-enhanced Raman spectroscopy (SERS). Herein, we present a method to enhance gold nanoparticle (AuNP) surface affinity by lowering the suspension pH below the analyte pKa. We developed an AuNP/bacterial cellulose (BC) nanocomposite platform and applied it to two common pollutants, carbamazepine (CBZ) and atrazine (ATZ) with pKa values of 2.3 and 1.7, respectively. Simple mixing of the analytes with AuNP/BC at pH < pKa resulted in consistent electrostatic alignment of the CBZ and ATZ molecules across the nanocomposite and highly reproducible SERS spectra. Limits of detection of 3 nM and 11 nM for CBZ and ATZ, respectively, were attained. Tests with additional analytes (melamine, 2,4-dichloroaniline, 4-chloroaniline, 3-bromoaniline, and 3-nitroaniline) further illustrate that the AuNP/BC platform provides reproducible analyte detection and quantification while avoiding the uncontrolled aggregation and flocculation of AuNPs that often hinder low pH detection. PMID:26658696

pH-Triggered Molecular Alignment for Reproducible SERS Detection via an AuNP/Nanocellulose Platform

NASA Astrophysics Data System (ADS)

Wei, Haoran; Vikesland, Peter J.

2015-12-01

The low affinity of neutral and hydrophobic molecules towards noble metal surfaces hinders their detection by surface-enhanced Raman spectroscopy (SERS). Herein, we present a method to enhance gold nanoparticle (AuNP) surface affinity by lowering the suspension pH below the analyte pKa. We developed an AuNP/bacterial cellulose (BC) nanocomposite platform and applied it to two common pollutants, carbamazepine (CBZ) and atrazine (ATZ) with pKa values of 2.3 and 1.7, respectively. Simple mixing of the analytes with AuNP/BC at pH < pKa resulted in consistent electrostatic alignment of the CBZ and ATZ molecules across the nanocomposite and highly reproducible SERS spectra. Limits of detection of 3 nM and 11 nM for CBZ and ATZ, respectively, were attained. Tests with additional analytes (melamine, 2,4-dichloroaniline, 4-chloroaniline, 3-bromoaniline, and 3-nitroaniline) further illustrate that the AuNP/BC platform provides reproducible analyte detection and quantification while avoiding the uncontrolled aggregation and flocculation of AuNPs that often hinder low pH detection.

Rapid Molecular Diagnostics, Antibiotic Treatment Decisions, and Developing Approaches to Inform Empiric Therapy: PRIMERS I and II.

PubMed

Evans, Scott R; Hujer, Andrea M; Jiang, Hongyu; Hujer, Kristine M; Hall, Thomas; Marzan, Christine; Jacobs, Michael R; Sampath, Rangarajan; Ecker, David J; Manca, Claudia; Chavda, Kalyan; Zhang, Pan; Fernandez, Helen; Chen, Liang; Mediavilla, Jose R; Hill, Carol B; Perez, Federico; Caliendo, Angela M; Fowler, Vance G; Chambers, Henry F; Kreiswirth, Barry N; Bonomo, Robert A

2016-01-15

Rapid molecular diagnostic (RMD) platforms may lead to better antibiotic use. Our objective was to develop analytical strategies to enhance the interpretation of RMDs for clinicians. We compared the performance characteristics of 4 RMD platforms for detecting resistance against β-lactams in 72 highly resistant isolates of Escherichia coli and Klebsiella pneumoniae (PRIMERS I). Subsequently, 2 platforms were used in a blinded study in which a heterogeneous collection of 196 isolates of E. coli and K. pneumoniae (PRIMERS II) were examined. We evaluated the genotypic results as predictors of resistance or susceptibility against β-lactam antibiotics. We designed analytical strategies and graphical representations of platform performance, including discrimination summary plots and susceptibility and resistance predictive values, that are readily interpretable by practitioners to inform decision-making. In PRIMERS I, the 4 RMD platforms detected β-lactamase (bla) genes and identified susceptibility or resistance in >95% of cases. In PRIMERS II, the 2 platforms identified susceptibility against extended-spectrum cephalosporins and carbapenems in >90% of cases; however, against piperacillin/tazobactam, susceptibility was identified in <80% of cases. Applying the analytical strategies to a population with 15% prevalence of ceftazidime-resistance and 5% imipenem-resistance, RMD platforms predicted susceptibility in >95% of cases, while prediction of resistance was 69%-73% for ceftazidime and 41%-50% for imipenem. RMD platforms can help inform empiric β-lactam therapy in cases where bla genes are not detected and the prevalence of resistance is known. Our analysis is a first step in bridging the gap between RMDs and empiric treatment decisions. © The Author 2015. Published by Oxford University Press for the Infectious Diseases Society of America. All rights reserved. For permissions, e-mail journals.permissions@oup.com.

The Benefits and Complexities of Operating Geographic Information Systems (GIS) in a High Performance Computing (HPC) Environment

NASA Astrophysics Data System (ADS)

Shute, J.; Carriere, L.; Duffy, D.; Hoy, E.; Peters, J.; Shen, Y.; Kirschbaum, D.

2017-12-01

The NASA Center for Climate Simulation (NCCS) at the Goddard Space Flight Center is building and maintaining an Enterprise GIS capability for its stakeholders, to include NASA scientists, industry partners, and the public. This platform is powered by three GIS subsystems operating in a highly-available, virtualized environment: 1) the Spatial Analytics Platform is the primary NCCS GIS and provides users discoverability of the vast DigitalGlobe/NGA raster assets within the NCCS environment; 2) the Disaster Mapping Platform provides mapping and analytics services to NASA's Disaster Response Group; and 3) the internal (Advanced Data Analytics Platform/ADAPT) enterprise GIS provides users with the full suite of Esri and open source GIS software applications and services. All systems benefit from NCCS's cutting edge infrastructure, to include an InfiniBand network for high speed data transfers; a mixed/heterogeneous environment featuring seamless sharing of information between Linux and Windows subsystems; and in-depth system monitoring and warning systems. Due to its co-location with the NCCS Discover High Performance Computing (HPC) environment and the Advanced Data Analytics Platform (ADAPT), the GIS platform has direct access to several large NCCS datasets including DigitalGlobe/NGA, Landsat, MERRA, and MERRA2. Additionally, the NCCS ArcGIS Desktop Windows virtual machines utilize existing NetCDF and OPeNDAP assets for visualization, modelling, and analysis - thus eliminating the need for data duplication. With the advent of this platform, Earth scientists have full access to vast data repositories and the industry-leading tools required for successful management and analysis of these multi-petabyte, global datasets. The full system architecture and integration with scientific datasets will be presented. Additionally, key applications and scientific analyses will be explained, to include the NASA Global Landslide Catalog (GLC) Reporter crowdsourcing application, the NASA GLC Viewer discovery and analysis tool, the DigitalGlobe/NGA Data Discovery Tool, the NASA Disaster Response Group Mapping Platform (https://maps.disasters.nasa.gov), and support for NASA's Arctic - Boreal Vulnerability Experiment (ABoVE).

Retention prediction and separation optimization under multilinear gradient elution in liquid chromatography with Microsoft Excel macros.

PubMed

Fasoula, S; Zisi, Ch; Gika, H; Pappa-Louisi, A; Nikitas, P

2015-05-22

A package of Excel VBA macros have been developed for modeling multilinear gradient retention data obtained in single or double gradient elution mode by changing organic modifier(s) content and/or eluent pH. For this purpose, ten chromatographic models were used and four methods were adopted for their application. The methods were based on (a) the analytical expression of the retention time, provided that this expression is available, (b) the retention times estimated using the Nikitas-Pappa approach, (c) the stepwise approximation, and (d) a simple numerical approximation involving the trapezoid rule for integration of the fundamental equation for gradient elution. For all these methods, Excel VBA macros have been written and implemented using two different platforms; the fitting and the optimization platform. The fitting platform calculates not only the adjustable parameters of the chromatographic models, but also the significance of these parameters and furthermore predicts the analyte elution times. The optimization platform determines the gradient conditions that lead to the optimum separation of a mixture of analytes by using the Solver evolutionary mode, provided that proper constraints are set in order to obtain the optimum gradient profile in the minimum gradient time. The performance of the two platforms was tested using experimental and artificial data. It was found that using the proposed spreadsheets, fitting, prediction, and optimization can be performed easily and effectively under all conditions. Overall, the best performance is exhibited by the analytical and Nikitas-Pappa's methods, although the former cannot be used under all circumstances. Copyright © 2015 Elsevier B.V. All rights reserved.

Supporting Building Portfolio Investment and Policy Decision Making through an Integrated Building Utility Data Platform

DOE Office of Scientific and Technical Information (OSTI.GOV)

Aziz, Azizan; Lasternas, Bertrand; Alschuler, Elena

The American Recovery and Reinvestment Act stimulus funding of 2009 for smart grid projects resulted in the tripling of smart meters deployment. In 2012, the Green Button initiative provided utility customers with access to their real-time1 energy usage. The availability of finely granular data provides an enormous potential for energy data analytics and energy benchmarking. The sheer volume of time-series utility data from a large number of buildings also poses challenges in data collection, quality control, and database management for rigorous and meaningful analyses. In this paper, we will describe a building portfolio-level data analytics tool for operational optimization, businessmore » investment and policy assessment using 15-minute to monthly intervals utility data. The analytics tool is developed on top of the U.S. Department of Energy’s Standard Energy Efficiency Data (SEED) platform, an open source software application that manages energy performance data of large groups of buildings. To support the significantly large volume of granular interval data, we integrated a parallel time-series database to the existing relational database. The time-series database improves on the current utility data input, focusing on real-time data collection, storage, analytics and data quality control. The fully integrated data platform supports APIs for utility apps development by third party software developers. These apps will provide actionable intelligence for building owners and facilities managers. Unlike a commercial system, this platform is an open source platform funded by the U.S. Government, accessible to the public, researchers and other developers, to support initiatives in reducing building energy consumption.« less

Portable Enzyme-Paper Biosensors Based on Redox-Active CeO2 Nanoparticles.

PubMed

Karimi, A; Othman, A; Andreescu, S

2016-01-01

Portable, nanoparticle (NP)-enhanced enzyme sensors have emerged as powerful devices for qualitative and quantitative analysis of a variety of analytes for biomedicine, environmental applications, and pharmaceutical fields. This chapter describes a method for the fabrication of a portable, paper-based, inexpensive, robust enzyme biosensor for the detection of substrates of oxidase enzymes. The method utilizes redox-active NPs of cerium oxide (CeO2) as a sensing platform which produces color in response to H2O2 generated by the action of oxidase enzymes on their corresponding substrates. This avoids the use of peroxidases which are routinely used in conjunction with glucose oxidase. The CeO2 particles serve dual roles, as high surface area supports to anchor high loadings of the enzyme as well as a color generation reagent, and the particles are recycled multiple times for the reuse of the biosensor. These sensors are small, light, disposable, inexpensive, and they can be mass produced by standard, low-cost printing methods. All reagents needed for the analysis are embedded within the paper matrix, and sensors stored over extended periods of time without performance loss. This novel sensor is a general platform for the in-field detection of analytes that are substrates for oxidase enzymes in clinical, food, and environmental samples. © 2016 Elsevier Inc. All rights reserved.

Arc4nix: A cross-platform geospatial analytical library for cluster and cloud computing

NASA Astrophysics Data System (ADS)

Tang, Jingyin; Matyas, Corene J.

2018-02-01

Big Data in geospatial technology is a grand challenge for processing capacity. The ability to use a GIS for geospatial analysis on Cloud Computing and High Performance Computing (HPC) clusters has emerged as a new approach to provide feasible solutions. However, users lack the ability to migrate existing research tools to a Cloud Computing or HPC-based environment because of the incompatibility of the market-dominating ArcGIS software stack and Linux operating system. This manuscript details a cross-platform geospatial library "arc4nix" to bridge this gap. Arc4nix provides an application programming interface compatible with ArcGIS and its Python library "arcpy". Arc4nix uses a decoupled client-server architecture that permits geospatial analytical functions to run on the remote server and other functions to run on the native Python environment. It uses functional programming and meta-programming language to dynamically construct Python codes containing actual geospatial calculations, send them to a server and retrieve results. Arc4nix allows users to employ their arcpy-based script in a Cloud Computing and HPC environment with minimal or no modification. It also supports parallelizing tasks using multiple CPU cores and nodes for large-scale analyses. A case study of geospatial processing of a numerical weather model's output shows that arcpy scales linearly in a distributed environment. Arc4nix is open-source software.

Functionalized poly(ethylene glycol) diacrylate microgels by microfluidics: In situ peptide encapsulation for in serum selective protein detection.

PubMed

Celetti, Giorgia; Natale, Concetta Di; Causa, Filippo; Battista, Edmondo; Netti, Paolo A

2016-09-01

Polymeric microparticles represent a robustly platform for the detection of clinically relevant analytes in biological samples; they can be functionalized encapsulating a multiple types of biologics entities, enhancing their applications as a new class of colloid materials. Microfluidic offers a versatile platform for the synthesis of monodisperse and engineered microparticles. In this work, we report microfluidic synthesis of novel polymeric microparticles endowed with specific peptide due to its superior specificity for target binding in complex media. A peptide sequence was efficiently encapsulated into the polymeric network and protein binding occurred with high affinity (KD 0.1-0.4μM). Fluidic dynamics simulation was performed to optimize the production conditions for monodisperse and stable functionalized microgels. The results demonstrate the easy and fast realization, in a single step, of functionalized monodisperse microgels using droplet-microfluidic technique, and how the inclusion of the peptide within polymeric network improve both the affinity and the specificity of protein capture. Copyright © 2016 Elsevier B.V. All rights reserved.

Launching genomics into the cloud: deployment of Mercury, a next generation sequence analysis pipeline

PubMed Central

2014-01-01

Background Massively parallel DNA sequencing generates staggering amounts of data. Decreasing cost, increasing throughput, and improved annotation have expanded the diversity of genomics applications in research and clinical practice. This expanding scale creates analytical challenges: accommodating peak compute demand, coordinating secure access for multiple analysts, and sharing validated tools and results. Results To address these challenges, we have developed the Mercury analysis pipeline and deployed it in local hardware and the Amazon Web Services cloud via the DNAnexus platform. Mercury is an automated, flexible, and extensible analysis workflow that provides accurate and reproducible genomic results at scales ranging from individuals to large cohorts. Conclusions By taking advantage of cloud computing and with Mercury implemented on the DNAnexus platform, we have demonstrated a powerful combination of a robust and fully validated software pipeline and a scalable computational resource that, to date, we have applied to more than 10,000 whole genome and whole exome samples. PMID:24475911

Performing data analytics on information obtained from various sensors on an OSUS compliant system

NASA Astrophysics Data System (ADS)

Cashion, Kelly; Landoll, Darian; Klawon, Kevin; Powar, Nilesh

2017-05-01

The Open Standard for Unattended Sensors (OSUS) was developed by DIA and ARL to provide a plug-n-play platform for sensor interoperability. Our objective is to use the standardized data produced by OSUS in performing data analytics on information obtained from various sensors. Data analytics can be integrated in one of three ways: within an asset itself; as an independent plug-in designed for one type of asset (i.e. camera or seismic sensor); or as an independent plug-in designed to incorporate data from multiple assets. As a proof-of-concept, we develop a model that can be used in the second of these types - an independent component for camera images. The dataset used was collected as part of a demonstration and test of OSUS capabilities. The image data includes images of empty outdoor scenes and scenes with human or vehicle activity. We design, test, and train a convolution neural network (CNN) to analyze these images and assess the presence of activity in the image. The resulting classifier labels input images as empty or activity with 86.93% accuracy, demonstrating the promising opportunities for deep learning, machine learning, and predictive analytics as an extension of OSUS's already robust suite of capabilities.

In house validation of a high resolution mass spectrometry Orbitrap-based method for multiple allergen detection in a processed model food.

PubMed

Pilolli, Rosa; De Angelis, Elisabetta; Monaci, Linda

2018-02-13

In recent years, mass spectrometry (MS) has been establishing its role in the development of analytical methods for multiple allergen detection, but most analyses are being carried out on low-resolution mass spectrometers such as triple quadrupole or ion traps. In this investigation, performance provided by a high resolution (HR) hybrid quadrupole-Orbitrap™ MS platform for the multiple allergens detection in processed food matrix is presented. In particular, three different acquisition modes were compared: full-MS, targeted-selected ion monitoring with data-dependent fragmentation (t-SIM/dd2), and parallel reaction monitoring. In order to challenge the HR-MS platform, the sample preparation was kept as simple as possible, limited to a 30-min ultrasound-aided protein extraction followed by clean-up with disposable size exclusion cartridges. Selected peptide markers tracing for five allergenic ingredients namely skim milk, whole egg, soy flour, ground hazelnut, and ground peanut were monitored in home-made cookies chosen as model processed matrix. Timed t-SIM/dd2 was found the best choice as a good compromise between sensitivity and accuracy, accomplishing the detection of 17 peptides originating from the five allergens in the same run. The optimized method was validated in-house through the evaluation of matrix and processing effects, recoveries, and precision. The selected quantitative markers for each allergenic ingredient provided quantification of 60-100 μg ingred /g allergenic ingredient/matrix in incurred cookies.

Learning Analytics across a Statewide System

ERIC Educational Resources Information Center

Buyarski, Catherine; Murray, Jim; Torstrick, Rebecca

2017-01-01

This chapter explores lessons learned from two different learning analytics efforts at a large, public, multicampus university--one internally developed and one vended platform. It raises questions about how to best use analytics to support students while keeping students responsible for their own learning and success.

Comparison of plasma ammonia results from seven different automated platforms in use throughout Central Australia.

PubMed

Markus, Corey; Metz, Michael

2017-04-01

The clinical catchment area for the Metabolic service at the Women's and Children's Hospital in Adelaide, South Australia, covers nearly 2.5millionkm 2 . Care of children with metabolic disorders in these remote areas is assisted from Adelaide, and at times, using plasma ammonia results from laboratories up to 3000km away. There are seven different platforms measuring plasma ammonia within this vast clinical catchment area. Hence, a correlation study was conducted to examine the relationship between plasma ammonia results from the seven different platforms in use throughout central Australia. Multiple aliquots of plasma from remainder EDTA samples for haematological investigations were frozen. Samples were then dispatched on dry ice to the laboratories being correlated. At an agreed date and time correlation samples were thawed and plasma ammonia measured. Passing-Bablok regression analysis showed slopes ranging from 1.00 to 1.10 and y-intercepts ranging from -10μmol/L to 1μmol/L. Despite the absence of a reference method or reference material and troublesome pre-analytical effects in ammonia measurement, plasma ammonia results from the different platforms in general compare well. The study also demonstrates that samples for ammonia measurement can be transported over great distances and still correlate well. Furthermore, a common reference interval for plasma ammonia may be a possibility. Crown Copyright © 2016. Published by Elsevier Inc. All rights reserved.

Suspension arrays based on nanoparticle-encoded microspheres for high-throughput multiplexed detection

PubMed Central

Leng, Yuankui

2017-01-01

Spectrometrically or optically encoded microsphere based suspension array technology (SAT) is applicable to the high-throughput, simultaneous detection of multiple analytes within a small, single sample volume. Thanks to the rapid development of nanotechnology, tremendous progress has been made in the multiplexed detecting capability, sensitivity, and photostability of suspension arrays. In this review, we first focus on the current stock of nanoparticle-based barcodes as well as the manufacturing technologies required for their production. We then move on to discuss all existing barcode-based bioanalysis patterns, including the various labels used in suspension arrays, label-free platforms, signal amplification methods, and fluorescence resonance energy transfer (FRET)-based platforms. We then introduce automatic platforms for suspension arrays that use superparamagnetic nanoparticle-based microspheres. Finally, we summarize the current challenges and their proposed solutions, which are centered on improving encoding capacities, alternative probe possibilities, nonspecificity suppression, directional immobilization, and “point of care” platforms. Throughout this review, we aim to provide a comprehensive guide for the design of suspension arrays, with the goal of improving their performance in areas such as multiplexing capacity, throughput, sensitivity, and cost effectiveness. We hope that our summary on the state-of-the-art development of these arrays, our commentary on future challenges, and some proposed avenues for further advances will help drive the development of suspension array technology and its related fields. PMID:26021602

Functional comparison of microarray data across multiple platforms using the method of percentage of overlapping functions.

PubMed

Li, Zhiguang; Kwekel, Joshua C; Chen, Tao

2012-01-01

Functional comparison across microarray platforms is used to assess the comparability or similarity of the biological relevance associated with the gene expression data generated by multiple microarray platforms. Comparisons at the functional level are very important considering that the ultimate purpose of microarray technology is to determine the biological meaning behind the gene expression changes under a specific condition, not just to generate a list of genes. Herein, we present a method named percentage of overlapping functions (POF) and illustrate how it is used to perform the functional comparison of microarray data generated across multiple platforms. This method facilitates the determination of functional differences or similarities in microarray data generated from multiple array platforms across all the functions that are presented on these platforms. This method can also be used to compare the functional differences or similarities between experiments, projects, or laboratories.

Fully suspended slot waveguide platform

NASA Astrophysics Data System (ADS)

Zhou, Wen; Cheng, Zhenzhou; Wu, Xinru; Sun, Xiankai; Tsang, Hon Ki

2018-02-01

A fully suspended slot waveguide (FSSWG) platform, including straight slot waveguides, 90° bends, high-Q racetrack resonators, and strip-to-slot mode converters, is demonstrated for broadband and low-loss operation in the mid-infrared spectral region. The proposed FSSWG platform has inherent merits of a broad spectral range of transparency which is limited only by the absorption of silicon, strong light-analyte interaction, good mechanical stability, and single lithography step fabrication process. By using asymmetric FSSWGs, the propagation loss, bending loss, and intrinsic optical Q factor are demonstrated to be 2.8 dB/cm, 0.15 dB/90°, and 12 600, respectively. The average conversion efficiency of a mode converter is 95.4% over a bandwidth of 170 nm and 97.0% at 2231 nm. The FSSWG platform would be promising for a long-range and cavity-enhanced light-analyte interaction.

JGME-ALiEM Hot Topics in Medical Education: Analysis of a Multimodal Online Discussion About Team-Based Learning

PubMed Central

Riddell, Jeff; Patocka, Catherine; Lin, Michelle; Sherbino, Jonathan

2017-01-01

Background  Team-based learning (TBL) is an instructional method that is being increasingly incorporated in health professions education, although use in graduate medical education (GME) has been more limited. Objective  To curate and describe themes that emerged from a virtual journal club discussion about TBL in GME, held across multiple digital platforms, while also evaluating the use of social media in online academic discussions. Methods  The Journal of Graduate Medical Education (JGME) and the Academic Life in Emergency Medicine blog facilitated a weeklong, open-access, virtual journal club on the 2015 JGME article “Use of Team-Based Learning Pedagogy for Internal Medicine Ambulatory Resident Teaching.” Using 4 stimulus questions (hosted on a blog as a starting framework), we facilitated discussions via the blog, Twitter, and Google Hangouts on Air platforms. We evaluated 2-week web analytics and performed a thematic analysis of the discussion. Results  The virtual journal club reached a large international audience as exemplified by the blog page garnering 685 page views from 241 cities in 42 countries. Our thematic analysis identified 4 domains relevant to TBL in GME: (1) the benefits and barriers to TBL; (2) the design of teams; (3) the role of assessment and peer evaluation; and (4) crowdsourced TBL resources. Conclusions  The virtual journal club provided a novel forum across multiple social media platforms, engaging authors, content experts, and the health professions education community in a discussion about the importance, impediments to implementation, available resources, and logistics of adopting TBL in GME. PMID:28261403

Real-Time Continuous Identification of Greenhouse Plant Pathogens Based on Recyclable Microfluidic Bioassay System.

PubMed

Qu, Xiangmeng; Li, Min; Zhang, Hongbo; Lin, Chenglie; Wang, Fei; Xiao, Mingshu; Zhou, Yi; Shi, Jiye; Aldalbahi, Ali; Pei, Hao; Chen, Hong; Li, Li

2017-09-20

The development of a real-time continuous analytical platform for the pathogen detection is of great scientific importance for achieving better disease control and prevention. In this work, we report a rapid and recyclable microfluidic bioassay system constructed from oligonucleotide arrays for selective and sensitive continuous identification of DNA targets of fungal pathogens. We employ the thermal denaturation method to effectively regenerate the oligonucleotide arrays for multiple sample detection, which could considerably reduce the screening effort and costs. The combination of thermal denaturation and laser-induced fluorescence detection technique enables real-time continuous identification of multiple samples (<10 min per sample). As a proof of concept, we have demonstrated that two DNA targets of fungal pathogens (Botrytis cinerea and Didymella bryoniae) can be sequentially analyzed using our rapid microfluidic bioassay system, which provides a new paradigm in the design of microfluidic bioassay system and will be valuable for chemical and biomedical analysis.

Optofluidic platforms based on surface-enhanced Raman scattering.

PubMed

Lim, Chaesung; Hong, Jongin; Chung, Bong Geun; deMello, Andrew J; Choo, Jaebum

2010-05-01

We report recent progress in the development of surface-enhanced Raman scattering (SERS)-based optofluidic platforms for the fast and sensitive detection of chemical and biological analytes. In the current context, a SERS-based optofluidic platform is defined as an integrated analytical device composed of a microfluidic element and a sensitive Raman spectrometer. Optofluidic devices for SERS detection normally involve nanocolloid-based microfluidic systems or metal nanostructure-embedded microfluidic systems. In the current review, recent advances in both approaches are surveyed and assessed. Additionally, integrated real-time sensing systems that combine portable Raman spectrometers with microfluidic devices are also reviewed. Such real-time sensing systems have significant utility in environmental monitoring, forensic science and homeland defense applications.

Gas chromatography fractionation platform featuring parallel flame-ionization detection and continuous high-resolution analyte collection in 384-well plates.

PubMed

Jonker, Willem; Clarijs, Bas; de Witte, Susannah L; van Velzen, Martin; de Koning, Sjaak; Schaap, Jaap; Somsen, Govert W; Kool, Jeroen

2016-09-02

Gas chromatography (GC) is a superior separation technique for many compounds. However, fractionation of a GC eluate for analyte isolation and/or post-column off-line analysis is not straightforward, and existing platforms are limited in the number of fractions that can be collected. Moreover, aerosol formation may cause serious analyte losses. Previously, our group has developed a platform that resolved these limitations of GC fractionation by post-column infusion of a trap solvent prior to continuous small-volume fraction collection in a 96-wells plate (Pieke et al., 2013 [17]). Still, this GC fractionation set-up lacked a chemical detector for the on-line recording of chromatograms, and the introduction of trap solvent resulted in extensive peak broadening for late-eluting compounds. This paper reports advancements to the fractionation platform allowing flame ionization detection (FID) parallel to high-resolution collection of a full GC chromatograms in up to 384 nanofractions of 7s each. To this end, a post-column split was incorporated which directs part of the eluate towards FID. Furthermore, a solvent heating device was developed for stable delivery of preheated/vaporized trap solvent, which significantly reduced band broadening by post-column infusion. In order to achieve optimal analyte trapping, several solvents were tested at different flow rates. The repeatability of the optimized GC fraction collection process was assessed demonstrating the possibility of up-concentration of isolated analytes by repetitive analyses of the same sample. The feasibility of the improved GC fractionation platform for bioactivity screening of toxic compounds was studied by the analysis of a mixture of test pesticides, which after fractionation were subjected to a post-column acetylcholinesterase (AChE) assay. Fractions showing AChE inhibition could be unambiguously correlated with peaks from the parallel-recorded FID chromatogram. Copyright © 2016 Elsevier B.V. All rights reserved.

A Novel Platform for Evaluating the Environmental Impacts on Bacterial Cellulose Production.

PubMed

Basu, Anindya; Vadanan, Sundaravadanam Vishnu; Lim, Sierin

2018-04-10

Bacterial cellulose (BC) is a biocompatible material with versatile applications. However, its large-scale production is challenged by the limited biological knowledge of the bacteria. The advent of synthetic biology has lead the way to the development of BC producing microbes as a novel chassis. Hence, investigation on optimal growth conditions for BC production and understanding of the fundamental biological processes are imperative. In this study, we report a novel analytical platform that can be used for studying the biology and optimizing growth conditions of cellulose producing bacteria. The platform is based on surface growth pattern of the organism and allows us to confirm that cellulose fibrils produced by the bacteria play a pivotal role towards their chemotaxis. The platform efficiently determines the impacts of different growth conditions on cellulose production and is translatable to static culture conditions. The analytical platform provides a means for fundamental biological studies of bacteria chemotaxis as well as systematic approach towards rational design and development of scalable bioprocessing strategies for industrial production of bacterial cellulose.

Cross-platform learning: on the nature of children's learning from multiple media platforms.

PubMed

Fisch, Shalom M

2013-01-01

It is increasingly common for an educational media project to span several media platforms (e.g., TV, Web, hands-on materials), assuming that the benefits of learning from multiple media extend beyond those gained from one medium alone. Yet research typically has investigated learning from a single medium in isolation. This paper reviews several recent studies to explore cross-platform learning (i.e., learning from combined use of multiple media platforms) and how such learning compares to learning from one medium. The paper discusses unique benefits of cross-platform learning, a theoretical mechanism to explain how these benefits might arise, and questions for future research in this emerging field. Copyright © 2013 Wiley Periodicals, Inc., A Wiley Company.

SAW-Based Phononic Crystal Microfluidic Sensor—Microscale Realization of Velocimetry Approaches for Integrated Analytical Platform Applications

PubMed Central

Lucklum, Ralf; Zubtsov, Mikhail; Schmidt, Marc-Peter; Mukhin, Nikolay V.; Hirsch, Soeren

2017-01-01

The current work demonstrates a novel surface acoustic wave (SAW) based phononic crystal sensor approach that allows the integration of a velocimetry-based sensor concept into single chip integrated solutions, such as Lab-on-a-Chip devices. The introduced sensor platform merges advantages of ultrasonic velocimetry analytic systems and a microacoustic sensor approach. It is based on the analysis of structural resonances in a periodic composite arrangement of microfluidic channels confined within a liquid analyte. Completed theoretical and experimental investigations show the ability to utilize periodic structure localized modes for the detection of volumetric properties of liquids and prove the efficacy of the proposed sensor concept. PMID:28946609

SAW-Based Phononic Crystal Microfluidic Sensor-Microscale Realization of Velocimetry Approaches for Integrated Analytical Platform Applications.

PubMed

Oseev, Aleksandr; Lucklum, Ralf; Zubtsov, Mikhail; Schmidt, Marc-Peter; Mukhin, Nikolay V; Hirsch, Soeren

2017-09-23

The current work demonstrates a novel surface acoustic wave (SAW) based phononic crystal sensor approach that allows the integration of a velocimetry-based sensor concept into single chip integrated solutions, such as Lab-on-a-Chip devices. The introduced sensor platform merges advantages of ultrasonic velocimetry analytic systems and a microacoustic sensor approach. It is based on the analysis of structural resonances in a periodic composite arrangement of microfluidic channels confined within a liquid analyte. Completed theoretical and experimental investigations show the ability to utilize periodic structure localized modes for the detection of volumetric properties of liquids and prove the efficacy of the proposed sensor concept.

Validation of a multiplex electrochemiluminescent immunoassay platform in human and mouse samples

PubMed Central

Bastarache, J.A.; Koyama, T.; Wickersham, N.E; Ware, L.B.

2014-01-01

Despite the widespread use of multiplex immunoassays, there are very few scientific reports that test the accuracy and reliability of a platform prior to publication of experimental data. Our laboratory has previously demonstrated the need for new assay platform validation prior to use of biologic samples from large studies in order to optimize sample handling and assay performance. In this study, our goal was to test the accuracy and reproducibility of an electrochemiluminescent multiplex immunoassay platform (Meso Scale Discovery, MSD®) and compare this platform to validated, singleplex immunoassays (R&D Systems®) using actual study subject (human plasma and mouse bronchoalveolar lavage fluid (BALF) and plasma) samples. We found that the MSD platform performed well on intra- and inter-assay comparisons, spike and recovery and cross-platform comparisons. The mean intra-assay CV% and range for MSD was 3.49 (0.0-10.4) for IL-6 and 2.04 (0.1-7.9) for IL-8. The correlation between values for identical samples measured on both MSD and R&D was R=0.97 for both analytes. The mouse MSD assay had a broader range of CV% with means ranging from 9.5-28.5 depending on the analyte. The range of mean CV% was similar for single plex ELISAs at 4.3-23.7 depending on the analyte. Regardless of species or sample type, CV% was more variable at lower protein concentrations. In conclusion, we validated a multiplex electrochemiluminscent assay system and found that it has superior test characteristics in human plasma compared to mouse BALF and plasma. Both human and MSD assays compared favorably to well-validated singleplex ELISA's PMID:24768796

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

DOE Office of Scientific and Technical Information (OSTI.GOV)

Xie, Hongzhi; Mukundan, Harshini; Martinez, Jennifer S

2009-01-01

The quantitative, simultaneous detection of multiple biomarkers with high sensitivity and specificity is critical for biomedical diagnostics, drug discovery and biomarker characterization [Wilson 2006, Tok 2006, Straub 2005, Joos 2002, Jani 2000]. Detection systems relying on optical signal transduction are, in general, advantageous because they are fast, portable, inexpensive, sensitive, and have the potential for multiplex detection of analytes of interest. However, conventional immunoassays for the detection of biomarkers, such as the Enzyme Linked Immunosorbant Assays (ELISAs) are semi-quantitative, time consuming and insensitive. ELISA assays are also limited by high non-specific binding, especially when used with complex biological samples suchmore » as serum and urine (REF). Organic fluorophores that are commonly used in such applications lack photostability and possess a narrow Stoke's shift that makes simultaneous detection of multiple fluorophores with a single excitation source difficult, thereby restricting their use in multiplex assays. The above limitations with traditional assay platforms have resulted in the increased use of nanotechnology-based tools and techniques in the fields of medical imaging [ref], targeted drug delivery [Caruthers 2007, Liu 2007], and sensing [ref]. One such area of increasing interest is the use of semiconductor quantum dots (QDs) for biomedical research and diagnostics [Gao and Cui 2004, Voura 2004, Michalet 2005, Chan 2002, Jaiswal 2004, Gao 2005, Medintz 2005, So 2006 2006, Wu 2003]. Compared to organic dyes, QDs provide several advantages for use in immunoassay platforms, including broad absorption bands with high extinction coefficients, narrow and symmetric emission bands with high quantum yields, high photostablility, and a large Stokes shift [Michalet 2005, Gu 2002]. These features prompted the use of QDs as probes in biodetection [Michalet 2005, Medintz 2005]. For example, Jaiswal et al. reported long term multiple color imaging of live cells using QD-bioconjugates [Jaiswal 2003]. Gao [Gao 2004] and So [So 2006] have used QDs as probes for in-vivo cancer targeting and imaging. Medintz et al. reported self-assembled QD-based biosensors for detection of analytes based on energy transfer [Medintz 2003]. Others have developed an approach for multiplex optical encoding of biomolecules using QDs [Han 2001]. Immunoassays have also benefited from the advantages of QDs. Recently, dihydrolipoic acid (DHLA) capped-QDs have been attached to antibodies and used as fluorescence reporters in plate-based multiplex immunoassays [Goodman 2004]. However, DHLA-QDs are associated with low quantum efficiency and are unstable at neutral pH. These problems limit the application of this technology to the sensitive detection of biomolecules, especially in complex biological samples. Thus, the development of a rapid, sensitive, quantitative, and specific multiplex platform for the detection of biomarkers in difficult samples remains an elusive target. The goal stated above has applications in many fields including medical diagnostics, biological research, and threat reduction. The current decade alone has seen the development of a need to rapidly and accurately detect potential biological warfare agents. For example, current methods for the detection of anthrax are grossly inadequate for a variety of reasons including long incubation time (5 days from time of exposure to onset of symptoms) and non-specific ('flu-like') symptoms. When five employees of the United State Senate were exposed to B. anthracis in the mail (2001), only one patient had a confirmed diagnosis before death. Since then, sandwich immunoassays using both colorimetric and fluorescence detectors have been developed for key components of the anthrax lethal toxin, namely protective antigen (PA), lethal factor (LF), and the edema factor [Mourez 2001]. While these platforms were successful in assays against anthrax toxins, the sensitivity was poor. Furthermore, no single platform exists for the simultaneous and quantitative detection of multiple components of the B. anthracis toxin. Addressing multiple biomarkers at the same time will increase confidence in a positive result, and may lead to application in the simultaneous detection of anthrax and other biowarfare agents.« less

Fundamental Biological Research on the International Space Station

NASA Technical Reports Server (NTRS)

Souza, K. A.; Yost, Bruce; Fletcher, L.; Dalton, Bonnie P. (Technical Monitor)

2000-01-01

The fundamental Biology Program of NASA's Life Sciences Division is chartered with enabling and sponsoring research on the International Space Station (ISS) in order to understand the effects of the space flight environment, particularly microgravity, on living systems. To accomplish this goal, NASA Ames Research Center (ARC) has been tasked with managing the development of a number of biological habitats, along with their support systems infrastructure. This integrated suite of habitats and support systems is being designed to support research requirements identified by the scientific community. As such, it will support investigations using cells and tissues, avian eggs, insects, plants, aquatic organisms and rodents. Studies following organisms through complete life cycles and over multiple generations will eventually be possible. As an adjunct to the development of these basic habitats, specific analytical and monitoring technologies are being targeted for maturation to complete the research cycle by transferring existing or emerging analytical techniques, sensors, and processes from the laboratory bench to the ISS research platform.

Computer-operated analytical platform for the determination of nutrients in hydroponic systems.

PubMed

Rius-Ruiz, F Xavier; Andrade, Francisco J; Riu, Jordi; Rius, F Xavier

2014-03-15

Hydroponics is a water, energy, space, and cost efficient system for growing plants in constrained spaces or land exhausted areas. Precise control of hydroponic nutrients is essential for growing healthy plants and producing high yields. In this article we report for the first time on a new computer-operated analytical platform which can be readily used for the determination of essential nutrients in hydroponic growing systems. The liquid-handling system uses inexpensive components (i.e., peristaltic pump and solenoid valves), which are discretely computer-operated to automatically condition, calibrate and clean a multi-probe of solid-contact ion-selective electrodes (ISEs). These ISEs, which are based on carbon nanotubes, offer high portability, robustness and easy maintenance and storage. With this new computer-operated analytical platform we performed automatic measurements of K(+), Ca(2+), NO3(-) and Cl(-) during tomato plants growth in order to assure optimal nutritional uptake and tomato production. Copyright © 2013 Elsevier Ltd. All rights reserved.

Customisation of the exome data analysis pipeline using a combinatorial approach.

PubMed

Pattnaik, Swetansu; Vaidyanathan, Srividya; Pooja, Durgad G; Deepak, Sa; Panda, Binay

2012-01-01

The advent of next generation sequencing (NGS) technologies have revolutionised the way biologists produce, analyse and interpret data. Although NGS platforms provide a cost-effective way to discover genome-wide variants from a single experiment, variants discovered by NGS need follow up validation due to the high error rates associated with various sequencing chemistries. Recently, whole exome sequencing has been proposed as an affordable option compared to whole genome runs but it still requires follow up validation of all the novel exomic variants. Customarily, a consensus approach is used to overcome the systematic errors inherent to the sequencing technology, alignment and post alignment variant detection algorithms. However, the aforementioned approach warrants the use of multiple sequencing chemistry, multiple alignment tools, multiple variant callers which may not be viable in terms of time and money for individual investigators with limited informatics know-how. Biologists often lack the requisite training to deal with the huge amount of data produced by NGS runs and face difficulty in choosing from the list of freely available analytical tools for NGS data analysis. Hence, there is a need to customise the NGS data analysis pipeline to preferentially retain true variants by minimising the incidence of false positives and make the choice of right analytical tools easier. To this end, we have sampled different freely available tools used at the alignment and post alignment stage suggesting the use of the most suitable combination determined by a simple framework of pre-existing metrics to create significant datasets.

Conducting On-orbit Gene Expression Analysis on ISS: WetLab-2

NASA Technical Reports Server (NTRS)

Parra, Macarena; Almeida, Eduardo; Boone, Travis; Jung, Jimmy; Lera, Matthew P.; Ricco, Antonio; Souza, Kenneth; Wu, Diana; Richey, C. Scott

2013-01-01

WetLab-2 will enable expanded genomic research on orbit by developing tools that support in situ sample collection, processing, and analysis on ISS. This capability will reduce the time-to-results for investigators and define new pathways for discovery on the ISS National Lab. The primary objective is to develop a research platform on ISS that will facilitate real-time quantitative gene expression analysis of biological samples collected on orbit. WetLab-2 will be capable of processing multiple sample types ranging from microbial cultures to animal tissues dissected on orbit. WetLab-2 will significantly expand the analytical capabilities onboard ISS and enhance science return from ISS.

Novel predictive models for metabolic syndrome risk: a "big data" analytic approach.

PubMed

Steinberg, Gregory B; Church, Bruce W; McCall, Carol J; Scott, Adam B; Kalis, Brian P

2014-06-01

We applied a proprietary "big data" analytic platform--Reverse Engineering and Forward Simulation (REFS)--to dimensions of metabolic syndrome extracted from a large data set compiled from Aetna's databases for 1 large national customer. Our goals were to accurately predict subsequent risk of metabolic syndrome and its various factors on both a population and individual level. The study data set included demographic, medical claim, pharmacy claim, laboratory test, and biometric screening results for 36,944 individuals. The platform reverse-engineered functional models of systems from diverse and large data sources and provided a simulation framework for insight generation. The platform interrogated data sets from the results of 2 Comprehensive Metabolic Syndrome Screenings (CMSSs) as well as complete coverage records; complete data from medical claims, pharmacy claims, and lab results for 2010 and 2011; and responses to health risk assessment questions. The platform predicted subsequent risk of metabolic syndrome, both overall and by risk factor, on population and individual levels, with ROC/AUC varying from 0.80 to 0.88. We demonstrated that improving waist circumference and blood glucose yielded the largest benefits on subsequent risk and medical costs. We also showed that adherence to prescribed medications and, particularly, adherence to routine scheduled outpatient doctor visits, reduced subsequent risk. The platform generated individualized insights using available heterogeneous data within 3 months. The accuracy and short speed to insight with this type of analytic platform allowed Aetna to develop targeted cost-effective care management programs for individuals with or at risk for metabolic syndrome.

The Human Urine Metabolome

PubMed Central

Bouatra, Souhaila; Aziat, Farid; Mandal, Rupasri; Guo, An Chi; Wilson, Michael R.; Knox, Craig; Bjorndahl, Trent C.; Krishnamurthy, Ramanarayan; Saleem, Fozia; Liu, Philip; Dame, Zerihun T.; Poelzer, Jenna; Huynh, Jessica; Yallou, Faizath S.; Psychogios, Nick; Dong, Edison; Bogumil, Ralf; Roehring, Cornelia; Wishart, David S.

2013-01-01

Urine has long been a “favored” biofluid among metabolomics researchers. It is sterile, easy-to-obtain in large volumes, largely free from interfering proteins or lipids and chemically complex. However, this chemical complexity has also made urine a particularly difficult substrate to fully understand. As a biological waste material, urine typically contains metabolic breakdown products from a wide range of foods, drinks, drugs, environmental contaminants, endogenous waste metabolites and bacterial by-products. Many of these compounds are poorly characterized and poorly understood. In an effort to improve our understanding of this biofluid we have undertaken a comprehensive, quantitative, metabolome-wide characterization of human urine. This involved both computer-aided literature mining and comprehensive, quantitative experimental assessment/validation. The experimental portion employed NMR spectroscopy, gas chromatography mass spectrometry (GC-MS), direct flow injection mass spectrometry (DFI/LC-MS/MS), inductively coupled plasma mass spectrometry (ICP-MS) and high performance liquid chromatography (HPLC) experiments performed on multiple human urine samples. This multi-platform metabolomic analysis allowed us to identify 445 and quantify 378 unique urine metabolites or metabolite species. The different analytical platforms were able to identify (quantify) a total of: 209 (209) by NMR, 179 (85) by GC-MS, 127 (127) by DFI/LC-MS/MS, 40 (40) by ICP-MS and 10 (10) by HPLC. Our use of multiple metabolomics platforms and technologies allowed us to identify several previously unknown urine metabolites and to substantially enhance the level of metabolome coverage. It also allowed us to critically assess the relative strengths and weaknesses of different platforms or technologies. The literature review led to the identification and annotation of another 2206 urinary compounds and was used to help guide the subsequent experimental studies. An online database containing the complete set of 2651 confirmed human urine metabolite species, their structures (3079 in total), concentrations, related literature references and links to their known disease associations are freely available at http://www.urinemetabolome.ca. PMID:24023812

Open chemistry: RESTful web APIs, JSON, NWChem and the modern web application.

PubMed

Hanwell, Marcus D; de Jong, Wibe A; Harris, Christopher J

2017-10-30

An end-to-end platform for chemical science research has been developed that integrates data from computational and experimental approaches through a modern web-based interface. The platform offers an interactive visualization and analytics environment that functions well on mobile, laptop and desktop devices. It offers pragmatic solutions to ensure that large and complex data sets are more accessible. Existing desktop applications/frameworks were extended to integrate with high-performance computing resources, and offer command-line tools to automate interaction-connecting distributed teams to this software platform on their own terms. The platform was developed openly, and all source code hosted on the GitHub platform with automated deployment possible using Ansible coupled with standard Ubuntu-based machine images deployed to cloud machines. The platform is designed to enable teams to reap the benefits of the connected web-going beyond what conventional search and analytics platforms offer in this area. It also has the goal of offering federated instances, that can be customized to the sites/research performed. Data gets stored using JSON, extending upon previous approaches using XML, building structures that support computational chemistry calculations. These structures were developed to make it easy to process data across different languages, and send data to a JavaScript-based web client.

MEASUREMENTS OF NON-METHANE VOLATILE ORGANIC COMPOUNDS IN THE LOWER TROPOSPHERE FROM TETHERED BALLOON AND KITE SAMPLING PLATFORMS BY INTERNAL STANDARD CALIBRATION USING AMBIENT CFC REFERENCE COMPOUNDS

EPA Science Inventory

A new analytical approach for the sampling and analysis of volatile organic compounds (VOCs) from sampling platforms used in the vertical profiling of the lower troposphere, such as kites, balloons, and remotely piloted vehicles will be developed. These sampling platforms a...

A Unified Analysis of Structured Sonar-terrain Data using Bayesian Functional Mixed Models.

PubMed

Zhu, Hongxiao; Caspers, Philip; Morris, Jeffrey S; Wu, Xiaowei; Müller, Rolf

2018-01-01

Sonar emits pulses of sound and uses the reflected echoes to gain information about target objects. It offers a low cost, complementary sensing modality for small robotic platforms. While existing analytical approaches often assume independence across echoes, real sonar data can have more complicated structures due to device setup or experimental design. In this paper, we consider sonar echo data collected from multiple terrain substrates with a dual-channel sonar head. Our goals are to identify the differential sonar responses to terrains and study the effectiveness of this dual-channel design in discriminating targets. We describe a unified analytical framework that achieves these goals rigorously, simultaneously, and automatically. The analysis was done by treating the echo envelope signals as functional responses and the terrain/channel information as covariates in a functional regression setting. We adopt functional mixed models that facilitate the estimation of terrain and channel effects while capturing the complex hierarchical structure in data. This unified analytical framework incorporates both Gaussian models and robust models. We fit the models using a full Bayesian approach, which enables us to perform multiple inferential tasks under the same modeling framework, including selecting models, estimating the effects of interest, identifying significant local regions, discriminating terrain types, and describing the discriminatory power of local regions. Our analysis of the sonar-terrain data identifies time regions that reflect differential sonar responses to terrains. The discriminant analysis suggests that a multi- or dual-channel design achieves target identification performance comparable with or better than a single-channel design.

A Unified Analysis of Structured Sonar-terrain Data using Bayesian Functional Mixed Models

PubMed Central

Zhu, Hongxiao; Caspers, Philip; Morris, Jeffrey S.; Wu, Xiaowei; Müller, Rolf

2017-01-01

Sonar emits pulses of sound and uses the reflected echoes to gain information about target objects. It offers a low cost, complementary sensing modality for small robotic platforms. While existing analytical approaches often assume independence across echoes, real sonar data can have more complicated structures due to device setup or experimental design. In this paper, we consider sonar echo data collected from multiple terrain substrates with a dual-channel sonar head. Our goals are to identify the differential sonar responses to terrains and study the effectiveness of this dual-channel design in discriminating targets. We describe a unified analytical framework that achieves these goals rigorously, simultaneously, and automatically. The analysis was done by treating the echo envelope signals as functional responses and the terrain/channel information as covariates in a functional regression setting. We adopt functional mixed models that facilitate the estimation of terrain and channel effects while capturing the complex hierarchical structure in data. This unified analytical framework incorporates both Gaussian models and robust models. We fit the models using a full Bayesian approach, which enables us to perform multiple inferential tasks under the same modeling framework, including selecting models, estimating the effects of interest, identifying significant local regions, discriminating terrain types, and describing the discriminatory power of local regions. Our analysis of the sonar-terrain data identifies time regions that reflect differential sonar responses to terrains. The discriminant analysis suggests that a multi- or dual-channel design achieves target identification performance comparable with or better than a single-channel design. PMID:29749977

Evaluating the Use of Commercial West Nile Virus Antigens as Positive Controls in the Rapid Analyte Measurement Platform West Nile Virus Assay.

PubMed

Burkhalter, Kristen L; Savage, Harry M

2015-12-01

We evaluated the utility of 2 types of commercially available antigens as positive controls in the Rapid Analyte Measurement Platform (RAMP®) West Nile virus (WNV) assay. Purified recombinant WNV envelope antigens and whole killed virus antigens produced positive RAMP results and either type would be useful as a positive control. Killed virus antigens provide operational and economic advantages and we recommend their use over purified recombinant antigens. We also offer practical applications for RAMP positive controls and recommendations for preparing them.

Enhancing battery efficiency for pervasive health-monitoring systems based on electronic textiles.

PubMed

Zheng, Nenggan; Wu, Zhaohui; Lin, Man; Yang, Laurence Tianruo

2010-03-01

Electronic textiles are regarded as one of the most important computation platforms for future computer-assisted health-monitoring applications. In these novel systems, multiple batteries are used in order to prolong their operational lifetime, which is a significant metric for system usability. However, due to the nonlinear features of batteries, computing systems with multiple batteries cannot achieve the same battery efficiency as those powered by a monolithic battery of equal capacity. In this paper, we propose an algorithm aiming to maximize battery efficiency globally for the computer-assisted health-care systems with multiple batteries. Based on an accurate analytical battery model, the concept of weighted battery fatigue degree is introduced and the novel battery-scheduling algorithm called predicted weighted fatigue degree least first (PWFDLF) is developed. Besides, we also discuss our attempts during search PWFDLF: a weighted round-robin (WRR) and a greedy algorithm achieving highest local battery efficiency, which reduces to the sequential discharging policy. Evaluation results show that a considerable improvement in battery efficiency can be obtained by PWFDLF under various battery configurations and current profiles compared to conventional sequential and WRR discharging policies.

The dynamics and control of large flexible space structures, 3. Part A: Shape and orientation control of a platform in orbit using point actuators

NASA Technical Reports Server (NTRS)

Bainum, P. M.; Reddy, A. S. S. R.; Krishna, R.; James, P. K.

1980-01-01

The dynamics, attitude, and shape control of a large thin flexible square platform in orbit are studied. Attitude and shape control are assumed to result from actuators placed perpendicular to the main surface and one edge and their effect on the rigid body and elastic modes is modelled to first order. The equations of motion are linearized about three different nominal orientations: (1) the platform following the local vertical with its major surface perpendicular to the orbital plane; (2) the platform following the local horizontal with its major surface normal to the local vertical; and (3) the platform following the local vertical with its major surface perpendicular to the orbit normal. The stability of the uncontrolled system is investigated analytically. Once controllability is established for a set of actuator locations, control law development is based on decoupling, pole placement, and linear optimal control theory. Frequencies and elastic modal shape functions are obtained using a finite element computer algorithm, two different approximate analytical methods, and the results of the three methods compared.

Next-generation confirmatory disease diagnostics

NASA Astrophysics Data System (ADS)

Lin, Robert; Gerver, Rachel; Karns, Kelly; Apori, Akwasi A.; Denisin, Aleksandra K.; Herr, Amy E.

2014-06-01

Microfluidic tools are advancing capabilities in screening diagnostics for use in near-patient settings. Here, we review three case studies to illustrate the flexibility and analytical power offered by microanalytical tools. We first overview a near-patient tool for detection of protein markers found in cerebrospinal fluid (CSF), as a means to identify the presence of cerebrospinal fluid in nasal mucous - an indication that CSF is leaking into the nasal cavity. Microfluidic design allowed integration of several up-stream preparatory steps and rapid, specific completion of the human CSF protein assay. Second, we overview a tear fluid based assay for lactoferrin, a protein produced in the lacrimal gland, then secreted into tear fluid. Tear Lf is a putative biomarker for primary SS. A critical contribution of this and related work being measurement of Lf, even in light of well-known and significant matrix interactions and losses during the tear fluid collection and preparation. Lastly, we review a microfluidic barcode platform that enables rapid measurement of multiple infectious disease biomarkers in human sera. The assay presents a new approach to multiplexed biomarker detection, yet in a simple straight microchannel - thus providing a streamlined, simplified microanalytical platform, as is relevant to robust operation in diagnostic settings. We view microfluidic design and analytical chemistry as the basis for emerging, sophisticated assays that will advance not just screening diagnostic technology, but confirmatory assays, sample preparation and handling, and thus introduction and utilization of new biomarkers and assay formats.

Interactive 3D geodesign tool for multidisciplinary wind turbine planning.

PubMed

Rafiee, Azarakhsh; Van der Male, Pim; Dias, Eduardo; Scholten, Henk

2018-01-01

Wind turbine site planning is a multidisciplinary task comprising of several stakeholder groups from different domains and with different priorities. An information system capable of integrating the knowledge on the multiple aspects of a wind turbine plays a crucial role on providing a common picture to the involved groups. In this study, we have developed an interactive and intuitive 3D system (Falcon) for planning wind turbine locations. This system supports iterative design loops (wind turbine configurations), based on the emerging field of geodesign. The integration of GIS, game engine and the analytical models has resulted in an interactive platform with real-time feedback on the multiple wind turbine aspects which performs efficiently for different use cases and different environmental settings. The implementation of tiling techniques and open standard web services support flexible and on-the-fly loading and querying of different (massive) geospatial elements from different resources. This boosts data accessibility and interoperability that are of high importance in a multidisciplinary process. The incorporation of the analytical models in Falcon makes this system independent from external tools for different environmental impacts estimations and results in a unified platform for performing different environmental analysis in every stage of the scenario design. Game engine techniques, such as collision detection, are applied in Falcon for the real-time implementation of different environmental models (e.g. noise and visibility). The interactivity and real-time performance of Falcon in any location in the whole country assist the stakeholders in the seamless exploration of various scenarios and their resulting environmental effects and provides a scope for an interwoven discussion process. The flexible architecture of the system enables the effortless application of Falcon in other countries, conditional to input data availability. The embedded open web standards in Falcon results in a smooth integration of different input data which are increasingly available online and through standardized access mechanisms. Copyright © 2017 Elsevier Ltd. All rights reserved.

Predicting Droplet Formation on Centrifugal Microfluidic Platforms

NASA Astrophysics Data System (ADS)

Moebius, Jacob Alfred

Centrifugal microfluidics is a widely known research tool for biological sample and water quality analysis. Currently, the standard equipment used for such diagnostic applications include slow, bulky machines controlled by multiple operators. These machines can be condensed into a smaller, faster benchtop sample-to-answer system. Sample processing is an important step taken to extract, isolate, and convert biological factors, such as nucleic acids or proteins, from a raw sample to an analyzable solution. Volume definition is one such step. The focus of this thesis is the development of a model predicting monodispersed droplet formation and the application of droplets as a technique for volume definition. First, a background of droplet microfluidic platforms is presented, along with current biological analysis technologies and the advantages of integrating such technologies onto microfluidic platforms. Second, background and theories of centrifugal microfluidics is given, followed by theories relevant to droplet emulsions. Third, fabrication techniques for centrifugal microfluidic designs are discussed. Finally, the development of a model for predicting droplet formation on the centrifugal microfluidic platform are presented for the rest of the thesis. Predicting droplet formation analytically based on the volumetric flow rates of the continuous and dispersed phases, the ratios of these two flow rates, and the interfacial tension between the continuous and dispersed phases presented many challenges, which will be discussed in this work. Experimental validation was completed using continuous phase solutions of different interfacial tensions. To conclude, prospective applications are discussed with expected challenges.

PubFocus: semantic MEDLINE/PubMed citations analytics through integration of controlled biomedical dictionaries and ranking algorithm

PubMed Central

Plikus, Maksim V; Zhang, Zina; Chuong, Cheng-Ming

2006-01-01

Background Understanding research activity within any given biomedical field is important. Search outputs generated by MEDLINE/PubMed are not well classified and require lengthy manual citation analysis. Automation of citation analytics can be very useful and timesaving for both novices and experts. Results PubFocus web server automates analysis of MEDLINE/PubMed search queries by enriching them with two widely used human factor-based bibliometric indicators of publication quality: journal impact factor and volume of forward references. In addition to providing basic volumetric statistics, PubFocus also prioritizes citations and evaluates authors' impact on the field of search. PubFocus also analyses presence and occurrence of biomedical key terms within citations by utilizing controlled vocabularies. Conclusion We have developed citations' prioritisation algorithm based on journal impact factor, forward referencing volume, referencing dynamics, and author's contribution level. It can be applied either to the primary set of PubMed search results or to the subsets of these results identified through key terms from controlled biomedical vocabularies and ontologies. NCI (National Cancer Institute) thesaurus and MGD (Mouse Genome Database) mammalian gene orthology have been implemented for key terms analytics. PubFocus provides a scalable platform for the integration of multiple available ontology databases. PubFocus analytics can be adapted for input sources of biomedical citations other than PubMed. PMID:17014720

Recent Advances in Paper-Based Sensors

PubMed Central

Liana, Devi D.; Raguse, Burkhard; Gooding, J. Justin; Chow, Edith

2012-01-01

Paper-based sensors are a new alternative technology for fabricating simple, low-cost, portable and disposable analytical devices for many application areas including clinical diagnosis, food quality control and environmental monitoring. The unique properties of paper which allow passive liquid transport and compatibility with chemicals/biochemicals are the main advantages of using paper as a sensing platform. Depending on the main goal to be achieved in paper-based sensors, the fabrication methods and the analysis techniques can be tuned to fulfill the needs of the end-user. Current paper-based sensors are focused on microfluidic delivery of solution to the detection site whereas more advanced designs involve complex 3-D geometries based on the same microfluidic principles. Although paper-based sensors are very promising, they still suffer from certain limitations such as accuracy and sensitivity. However, it is anticipated that in the future, with advances in fabrication and analytical techniques, that there will be more new and innovative developments in paper-based sensors. These sensors could better meet the current objectives of a viable low-cost and portable device in addition to offering high sensitivity and selectivity, and multiple analyte discrimination. This paper is a review of recent advances in paper-based sensors and covers the following topics: existing fabrication techniques, analytical methods and application areas. Finally, the present challenges and future outlooks are discussed. PMID:23112667

Comprehensive two-dimensional gas chromatography and food sensory properties: potential and challenges.

PubMed

Cordero, Chiara; Kiefl, Johannes; Schieberle, Peter; Reichenbach, Stephen E; Bicchi, Carlo

2015-01-01

Modern omics disciplines dealing with food flavor focus the analytical efforts on the elucidation of sensory-active compounds, including all possible stimuli of multimodal perception (aroma, taste, texture, etc.) by means of a comprehensive, integrated treatment of sample constituents, such as physicochemical properties, concentration in the matrix, and sensory properties (odor/taste quality, perception threshold). Such analyses require detailed profiling of known bioactive components as well as advanced fingerprinting techniques to catalog sample constituents comprehensively, quantitatively, and comparably across samples. Multidimensional analytical platforms support comprehensive investigations required for flavor analysis by combining information on analytes' identities, physicochemical behaviors (volatility, polarity, partition coefficient, and solubility), concentration, and odor quality. Unlike other omics, flavor metabolomics and sensomics include the final output of the biological phenomenon (i.e., sensory perceptions) as an additional analytical dimension, which is specifically and exclusively triggered by the chemicals analyzed. However, advanced omics platforms, which are multidimensional by definition, pose challenging issues not only in terms of coupling with detection systems and sample preparation, but also in terms of data elaboration and processing. The large number of variables collected during each analytical run provides a high level of information, but requires appropriate strategies to exploit fully this potential. This review focuses on advances in comprehensive two-dimensional gas chromatography and analytical platforms combining two-dimensional gas chromatography with olfactometry, chemometrics, and quantitative assays for food sensory analysis to assess the quality of a given product. We review instrumental advances and couplings, automation in sample preparation, data elaboration, and a selection of applications.

PADF RF localization experiments with multi-agent caged-MAV platforms

NASA Astrophysics Data System (ADS)

Barber, Christopher; Gates, Miguel; Selmic, Rastko; Al-Issa, Huthaifa; Ordonez, Raul; Mitra, Atindra

2011-06-01

This paper provides a summary of preliminary RF direction finding results generated within an AFOSR funded testbed facility recently developed at Louisiana Tech University. This facility, denoted as the Louisiana Tech University Micro- Aerial Vehicle/Wireless Sensor Network (MAVSeN) Laboratory, has recently acquired a number of state-of-the-art MAV platforms that enable us to analyze, design, and test some of our recent results in the area of multiplatform position-adaptive direction finding (PADF) [1] [2] for localization of RF emitters in challenging embedded multipath environments. Discussions within the segmented sections of this paper include a description of the MAVSeN Laboratory and the preliminary results from the implementation of mobile platforms with the PADF algorithm. This novel approach to multi-platform RF direction finding is based on the investigation of iterative path-loss based (i.e. path loss exponent) metrics estimates that are measured across multiple platforms in order to develop a control law that robotically/intelligently positionally adapt (i.e. self-adjust) the location of each distributed/cooperative platform. The body of this paper provides a summary of our recent results on PADF and includes a discussion on state-of-the-art Sensor Mote Technologies as applied towards the development of sensor-integrated caged-MAV platform for PADF applications. Also, a discussion of recent experimental results that incorporate sample approaches to real-time singleplatform data pruning is included as part of a discussion on potential approaches to refining a basic PADF technique in order to integrate and perform distributed self-sensitivity and self-consistency analysis as part of a PADF technique with distributed robotic/intelligent features. These techniques are extracted in analytical form from a parallel study denoted as "PADF RF Localization Criteria for Multi-Model Scattering Environments". The focus here is on developing and reporting specific approaches to self-sensitivity and self-consistency within this experimental PADF framework via the exploitation of specific single-agent caged-MAV trajectories that are unique to this experiment set.

Microfluidic-Based Platform for Universal Sample Preparation and Biological Assays Automation for Life-Sciences Research and Remote Medical Applications

NASA Astrophysics Data System (ADS)

Brassard, D.; Clime, L.; Daoud, J.; Geissler, M.; Malic, L.; Charlebois, D.; Buckley, N.; Veres, T.

2018-02-01

An innovative centrifugal microfluidic universal platform for remote bio-analytical assays automation required in life-sciences research and medical applications, including purification and analysis from body fluids of cellular and circulating markers.

SmartR: an open-source platform for interactive visual analytics for translational research data

PubMed Central

Herzinger, Sascha; Gu, Wei; Satagopam, Venkata; Eifes, Serge; Rege, Kavita; Barbosa-Silva, Adriano; Schneider, Reinhard

2017-01-01

Abstract Summary: In translational research, efficient knowledge exchange between the different fields of expertise is crucial. An open platform that is capable of storing a multitude of data types such as clinical, pre-clinical or OMICS data combined with strong visual analytical capabilities will significantly accelerate the scientific progress by making data more accessible and hypothesis generation easier. The open data warehouse tranSMART is capable of storing a variety of data types and has a growing user community including both academic institutions and pharmaceutical companies. tranSMART, however, currently lacks interactive and dynamic visual analytics and does not permit any post-processing interaction or exploration. For this reason, we developed SmartR, a plugin for tranSMART, that equips the platform not only with several dynamic visual analytical workflows, but also provides its own framework for the addition of new custom workflows. Modern web technologies such as D3.js or AngularJS were used to build a set of standard visualizations that were heavily improved with dynamic elements. Availability and Implementation: The source code is licensed under the Apache 2.0 License and is freely available on GitHub: https://github.com/transmart/SmartR. Contact: reinhard.schneider@uni.lu Supplementary information: Supplementary data are available at Bioinformatics online. PMID:28334291

SmartR: an open-source platform for interactive visual analytics for translational research data.

PubMed

Herzinger, Sascha; Gu, Wei; Satagopam, Venkata; Eifes, Serge; Rege, Kavita; Barbosa-Silva, Adriano; Schneider, Reinhard

2017-07-15

In translational research, efficient knowledge exchange between the different fields of expertise is crucial. An open platform that is capable of storing a multitude of data types such as clinical, pre-clinical or OMICS data combined with strong visual analytical capabilities will significantly accelerate the scientific progress by making data more accessible and hypothesis generation easier. The open data warehouse tranSMART is capable of storing a variety of data types and has a growing user community including both academic institutions and pharmaceutical companies. tranSMART, however, currently lacks interactive and dynamic visual analytics and does not permit any post-processing interaction or exploration. For this reason, we developed SmartR , a plugin for tranSMART, that equips the platform not only with several dynamic visual analytical workflows, but also provides its own framework for the addition of new custom workflows. Modern web technologies such as D3.js or AngularJS were used to build a set of standard visualizations that were heavily improved with dynamic elements. The source code is licensed under the Apache 2.0 License and is freely available on GitHub: https://github.com/transmart/SmartR . reinhard.schneider@uni.lu. Supplementary data are available at Bioinformatics online. © The Author(s) 2017. Published by Oxford University Press.

Teachable, high-content analytics for live-cell, phase contrast movies.

PubMed

Alworth, Samuel V; Watanabe, Hirotada; Lee, James S J

2010-09-01

CL-Quant is a new solution platform for broad, high-content, live-cell image analysis. Powered by novel machine learning technologies and teach-by-example interfaces, CL-Quant provides a platform for the rapid development and application of scalable, high-performance, and fully automated analytics for a broad range of live-cell microscopy imaging applications, including label-free phase contrast imaging. The authors used CL-Quant to teach off-the-shelf universal analytics, called standard recipes, for cell proliferation, wound healing, cell counting, and cell motility assays using phase contrast movies collected on the BioStation CT and BioStation IM platforms. Similar to application modules, standard recipes are intended to work robustly across a wide range of imaging conditions without requiring customization by the end user. The authors validated the performance of the standard recipes by comparing their performance with truth created manually, or by custom analytics optimized for each individual movie (and therefore yielding the best possible result for the image), and validated by independent review. The validation data show that the standard recipes' performance is comparable with the validated truth with low variation. The data validate that the CL-Quant standard recipes can provide robust results without customization for live-cell assays in broad cell types and laboratory settings.

Alkaloids Profiling of Fumaria capreolata by Analytical Platforms Based on the Hyphenation of Gas Chromatography and Liquid Chromatography with Quadrupole-Time-of-Flight Mass Spectrometry.

PubMed

Contreras, María Del Mar; Bribi, Noureddine; Gómez-Caravaca, Ana María; Gálvez, Julio; Segura-Carretero, Antonio

2017-01-01

Two analytical platforms, gas chromatography (GC) coupled to quadrupole-time-of-flight (QTOF) mass spectrometry (MS) and reversed-phase ultrahigh performance liquid chromatography (UHPLC) coupled to diode array (DAD) and QTOF detection, were applied in order to study the alkaloid profile of Fumaria capreolata . The use of these mass analyzers enabled tentatively identifying the alkaloids by matching their accurate mass signals and suggested molecular formulae with those previously reported in libraries and databases. Moreover, the proposed structures were corroborated by studying their fragmentation pattern obtained by both platforms. In this way, 8 and 26 isoquinoline alkaloids were characterized using GC-QTOF-MS and RP-UHPLC-DAD-QTOF-MS, respectively, and they belonged to the following subclasses: protoberberine, protopine, aporphine, benzophenanthridine, spirobenzylisoquinoline, morphinandienone, and benzylisoquinoline. Moreover, the latter analytical method was selected to determine at 280 nm the concentration of protopine (9.6 ± 0.7 mg/g), a potential active compound of the extract. In conclusion, although GC-MS has been commonly used for the analysis of this type of phytochemicals, RP-UHPLC-DAD-QTOF-MS provided essential complementary information. This analytical method can be applied for the quality control of phytopharmaceuticals containing Fumaria extracts currently found in the market.

Alkaloids Profiling of Fumaria capreolata by Analytical Platforms Based on the Hyphenation of Gas Chromatography and Liquid Chromatography with Quadrupole-Time-of-Flight Mass Spectrometry

PubMed Central

Bribi, Noureddine; Gómez-Caravaca, Ana María

2017-01-01

Two analytical platforms, gas chromatography (GC) coupled to quadrupole-time-of-flight (QTOF) mass spectrometry (MS) and reversed-phase ultrahigh performance liquid chromatography (UHPLC) coupled to diode array (DAD) and QTOF detection, were applied in order to study the alkaloid profile of Fumaria capreolata. The use of these mass analyzers enabled tentatively identifying the alkaloids by matching their accurate mass signals and suggested molecular formulae with those previously reported in libraries and databases. Moreover, the proposed structures were corroborated by studying their fragmentation pattern obtained by both platforms. In this way, 8 and 26 isoquinoline alkaloids were characterized using GC-QTOF-MS and RP-UHPLC-DAD-QTOF-MS, respectively, and they belonged to the following subclasses: protoberberine, protopine, aporphine, benzophenanthridine, spirobenzylisoquinoline, morphinandienone, and benzylisoquinoline. Moreover, the latter analytical method was selected to determine at 280 nm the concentration of protopine (9.6 ± 0.7 mg/g), a potential active compound of the extract. In conclusion, although GC-MS has been commonly used for the analysis of this type of phytochemicals, RP-UHPLC-DAD-QTOF-MS provided essential complementary information. This analytical method can be applied for the quality control of phytopharmaceuticals containing Fumaria extracts currently found in the market. PMID:29348751

Real-Time Detection and Tracking of Multiple People in Laser Scan Frames

NASA Astrophysics Data System (ADS)

Cui, J.; Song, X.; Zhao, H.; Zha, H.; Shibasaki, R.

This chapter presents an approach to detect and track multiple people ro bustly in real time using laser scan frames. The detection and tracking of people in real time is a problem that arises in a variety of different contexts. Examples in clude intelligent surveillance for security purposes, scene analysis for service robot, and crowd behavior analysis for human behavior study. Over the last several years, an increasing number of laser-based people-tracking systems have been developed in both mobile robotics platforms and fixed platforms using one or multiple laser scanners. It has been proved that processing on laser scanner data makes the tracker much faster and more robust than a vision-only based one in complex situations. In this chapter, we present a novel robust tracker to detect and track multiple people in a crowded and open area in real time. First, raw data are obtained that measures two legs for each people at a height of 16 cm from horizontal ground with multiple registered laser scanners. A stable feature is extracted using accumulated distribu tion of successive laser frames. In this way, the noise that generates split and merged measurements is smoothed well, and the pattern of rhythmic swinging legs is uti lized to extract each leg. Second, a probabilistic tracking model is presented, and then a sequential inference process using a Bayesian rule is described. A sequential inference process is difficult to compute analytically, so two strategies are presented to simplify the computation. In the case of independent tracking, the Kalman fil ter is used with a more efficient measurement likelihood model based on a region coherency property. Finally, to deal with trajectory fragments we present a concise approach to fuse just a little visual information from synchronized video camera to laser data. Evaluation with real data shows that the proposed method is robust and effective. It achieves a significant improvement compared with existing laser-based trackers.

Dynamic and label-free high-throughput detection of biomolecular interactions based on phase-shift interferometry

NASA Astrophysics Data System (ADS)

Li, Qiang; Huang, Guoliang; Gan, Wupeng; Chen, Shengyi

2009-08-01

Biomolecular interactions can be detected by many established technologies such as fluorescence imaging, surface plasmon resonance (SPR)[1-4], interferometry and radioactive labeling of the analyte. In this study, we have designed and constructed a label-free, real-time sensing platform and its operating imaging instrument that detects interactions using optical phase differences from the accumulation of biological material on solid substrates. This system allows us to monitor biomolecular interactions in real time and quantify concentration changes during micro-mixing processes by measuring the changes of the optical path length (OPD). This simple interferometric technology monitors the optical phase difference resulting from accumulated biomolecular mass. A label-free protein chip that forms a 4×4 probe array was designed and fabricated using a commercial microarray robot spotter on solid substrates. Two positive control probe lines of BSA (Bovine Serum Albumin) and two experimental human IgG and goat IgG was used. The binding of multiple protein targets was performed and continuously detected by using this label-free and real-time sensing platform.

The Human Serum Metabolome

PubMed Central

Psychogios, Nikolaos; Hau, David D.; Peng, Jun; Guo, An Chi; Mandal, Rupasri; Bouatra, Souhaila; Sinelnikov, Igor; Krishnamurthy, Ramanarayan; Eisner, Roman; Gautam, Bijaya; Young, Nelson; Xia, Jianguo; Knox, Craig; Dong, Edison; Huang, Paul; Hollander, Zsuzsanna; Pedersen, Theresa L.; Smith, Steven R.; Bamforth, Fiona; Greiner, Russ; McManus, Bruce; Newman, John W.; Goodfriend, Theodore; Wishart, David S.

2011-01-01

Continuing improvements in analytical technology along with an increased interest in performing comprehensive, quantitative metabolic profiling, is leading to increased interest pressures within the metabolomics community to develop centralized metabolite reference resources for certain clinically important biofluids, such as cerebrospinal fluid, urine and blood. As part of an ongoing effort to systematically characterize the human metabolome through the Human Metabolome Project, we have undertaken the task of characterizing the human serum metabolome. In doing so, we have combined targeted and non-targeted NMR, GC-MS and LC-MS methods with computer-aided literature mining to identify and quantify a comprehensive, if not absolutely complete, set of metabolites commonly detected and quantified (with today's technology) in the human serum metabolome. Our use of multiple metabolomics platforms and technologies allowed us to substantially enhance the level of metabolome coverage while critically assessing the relative strengths and weaknesses of these platforms or technologies. Tables containing the complete set of 4229 confirmed and highly probable human serum compounds, their concentrations, related literature references and links to their known disease associations are freely available at http://www.serummetabolome.ca. PMID:21359215

Cross-Platform Learning: On the Nature of Children's Learning from Multiple Media Platforms

ERIC Educational Resources Information Center

Fisch, Shalom M.

2013-01-01

It is increasingly common for an educational media project to span several media platforms (e.g., TV, Web, hands-on materials), assuming that the benefits of learning from multiple media extend beyond those gained from one medium alone. Yet research typically has investigated learning from a single medium in isolation. This paper reviews several…

A new basaltic glass microanalytical reference material for multiple techniques

USGS Publications Warehouse

Wilson, Steve; Koenig, Alan; Lowers, Heather

2012-01-01

The U.S. Geological Survey (USGS) has been producing reference materials since the 1950s. Over 50 materials have been developed to cover bulk rock, sediment, and soils for the geological community. These materials are used globally in geochemistry, environmental, and analytical laboratories that perform bulk chemistry and/or microanalysis for instrument calibration and quality assurance testing. To answer the growing demand for higher spatial resolution and sensitivity, there is a need to create a new generation of microanalytical reference materials suitable for a variety of techniques, such as scanning electron microscopy/X-ray spectrometry (SEM/EDS), electron probe microanalysis (EPMA), laser ablation inductively coupled mass spectrometry (LA-ICP-MS), and secondary ion mass spectrometry (SIMS). As such, the microanalytical reference material (MRM) needs to be stable under the beam, be homogeneous at scales of better than 10–25 micrometers for the major to ultra-trace element level, and contain all of the analytes (elements or isotopes) of interest. Previous development of basaltic glasses intended for LA-ICP-MS has resulted in a synthetic basaltic matrix series of glasses (USGS GS-series) and a natural basalt series of glasses (BCR-1G, BHVO-2G, and NKT-1G). These materials have been useful for the LA-ICP-MS community but were not originally intended for use by the electron or ion beam community. A material developed from start to finish with intended use in multiple microanalytical instruments would be useful for inter-laboratory and inter-instrument platform comparisons. This article summarizes the experiments undertaken to produce a basalt glass reference material suitable for distribution as a multiple-technique round robin material. The goal of the analytical work presented here is to demonstrate that the elemental homogeneity of the new glass is acceptable for its use as a reference material. Because the round robin exercise is still underway, only nominal compositional ranges for each element are given in the article.

Iodine-Containing Mass-Defect-Tuned Dendrimers for Use as Internal Mass Spectrometry Calibrants

NASA Astrophysics Data System (ADS)

Giesen, Joseph A.; Diament, Benjamin J.; Grayson, Scott M.

2018-03-01

Calibrants based on synthetic dendrimers have been recently proposed as a versatile alternative to peptides and proteins for both MALDI and ESI mass spectrometry calibration. Because of their modular synthetic platform, dendrimer calibrants are particularly amenable to tailoring for specific applications. Utilizing this versatility, a set of dendrimers has been designed as an internal calibrant with a tailored mass defect to differentiate them from the majority of natural peptide analytes. This was achieved by incorporating a tris-iodinated aromatic core as an initiator for the dendrimer synthesis, thereby affording multiple calibration points ( m/z range 600-2300) with an optimized mass-defect offset relative to all peptides composed of the 20 most common proteinogenic amino acids. [Figure not available: see fulltext.

PARAMO: A Parallel Predictive Modeling Platform for Healthcare Analytic Research using Electronic Health Records

PubMed Central

Ng, Kenney; Ghoting, Amol; Steinhubl, Steven R.; Stewart, Walter F.; Malin, Bradley; Sun, Jimeng

2014-01-01

Objective Healthcare analytics research increasingly involves the construction of predictive models for disease targets across varying patient cohorts using electronic health records (EHRs). To facilitate this process, it is critical to support a pipeline of tasks: 1) cohort construction, 2) feature construction, 3) cross-validation, 4) feature selection, and 5) classification. To develop an appropriate model, it is necessary to compare and refine models derived from a diversity of cohorts, patient-specific features, and statistical frameworks. The goal of this work is to develop and evaluate a predictive modeling platform that can be used to simplify and expedite this process for health data. Methods To support this goal, we developed a PARAllel predictive MOdeling (PARAMO) platform which 1) constructs a dependency graph of tasks from specifications of predictive modeling pipelines, 2) schedules the tasks in a topological ordering of the graph, and 3) executes those tasks in parallel. We implemented this platform using Map-Reduce to enable independent tasks to run in parallel in a cluster computing environment. Different task scheduling preferences are also supported. Results We assess the performance of PARAMO on various workloads using three datasets derived from the EHR systems in place at Geisinger Health System and Vanderbilt University Medical Center and an anonymous longitudinal claims database. We demonstrate significant gains in computational efficiency against a standard approach. In particular, PARAMO can build 800 different models on a 300,000 patient data set in 3 hours in parallel compared to 9 days if running sequentially. Conclusion This work demonstrates that an efficient parallel predictive modeling platform can be developed for EHR data. This platform can facilitate large-scale modeling endeavors and speed-up the research workflow and reuse of health information. This platform is only a first step and provides the foundation for our ultimate goal of building analytic pipelines that are specialized for health data researchers. PMID:24370496

PARAMO: a PARAllel predictive MOdeling platform for healthcare analytic research using electronic health records.

PubMed

Ng, Kenney; Ghoting, Amol; Steinhubl, Steven R; Stewart, Walter F; Malin, Bradley; Sun, Jimeng

2014-04-01

Healthcare analytics research increasingly involves the construction of predictive models for disease targets across varying patient cohorts using electronic health records (EHRs). To facilitate this process, it is critical to support a pipeline of tasks: (1) cohort construction, (2) feature construction, (3) cross-validation, (4) feature selection, and (5) classification. To develop an appropriate model, it is necessary to compare and refine models derived from a diversity of cohorts, patient-specific features, and statistical frameworks. The goal of this work is to develop and evaluate a predictive modeling platform that can be used to simplify and expedite this process for health data. To support this goal, we developed a PARAllel predictive MOdeling (PARAMO) platform which (1) constructs a dependency graph of tasks from specifications of predictive modeling pipelines, (2) schedules the tasks in a topological ordering of the graph, and (3) executes those tasks in parallel. We implemented this platform using Map-Reduce to enable independent tasks to run in parallel in a cluster computing environment. Different task scheduling preferences are also supported. We assess the performance of PARAMO on various workloads using three datasets derived from the EHR systems in place at Geisinger Health System and Vanderbilt University Medical Center and an anonymous longitudinal claims database. We demonstrate significant gains in computational efficiency against a standard approach. In particular, PARAMO can build 800 different models on a 300,000 patient data set in 3h in parallel compared to 9days if running sequentially. This work demonstrates that an efficient parallel predictive modeling platform can be developed for EHR data. This platform can facilitate large-scale modeling endeavors and speed-up the research workflow and reuse of health information. This platform is only a first step and provides the foundation for our ultimate goal of building analytic pipelines that are specialized for health data researchers. Copyright © 2013 Elsevier Inc. All rights reserved.

Open chemistry: RESTful web APIs, JSON, NWChem and the modern web application

DOE PAGES

Hanwell, Marcus D.; de Jong, Wibe A.; Harris, Christopher J.

2017-10-30

An end-to-end platform for chemical science research has been developed that integrates data from computational and experimental approaches through a modern web-based interface. The platform offers an interactive visualization and analytics environment that functions well on mobile, laptop and desktop devices. It offers pragmatic solutions to ensure that large and complex data sets are more accessible. Existing desktop applications/frameworks were extended to integrate with high-performance computing resources, and offer command-line tools to automate interaction - connecting distributed teams to this software platform on their own terms. The platform was developed openly, and all source code hosted on the GitHub platformmore » with automated deployment possible using Ansible coupled with standard Ubuntu-based machine images deployed to cloud machines. The platform is designed to enable teams to reap the benefits of the connected web - going beyond what conventional search and analytics platforms offer in this area. It also has the goal of offering federated instances, that can be customized to the sites/research performed. Data gets stored using JSON, extending upon previous approaches using XML, building structures that support computational chemistry calculations. These structures were developed to make it easy to process data across different languages, and send data to a JavaScript-based web client.« less

Open chemistry: RESTful web APIs, JSON, NWChem and the modern web application

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hanwell, Marcus D.; de Jong, Wibe A.; Harris, Christopher J.

An end-to-end platform for chemical science research has been developed that integrates data from computational and experimental approaches through a modern web-based interface. The platform offers an interactive visualization and analytics environment that functions well on mobile, laptop and desktop devices. It offers pragmatic solutions to ensure that large and complex data sets are more accessible. Existing desktop applications/frameworks were extended to integrate with high-performance computing resources, and offer command-line tools to automate interaction - connecting distributed teams to this software platform on their own terms. The platform was developed openly, and all source code hosted on the GitHub platformmore » with automated deployment possible using Ansible coupled with standard Ubuntu-based machine images deployed to cloud machines. The platform is designed to enable teams to reap the benefits of the connected web - going beyond what conventional search and analytics platforms offer in this area. It also has the goal of offering federated instances, that can be customized to the sites/research performed. Data gets stored using JSON, extending upon previous approaches using XML, building structures that support computational chemistry calculations. These structures were developed to make it easy to process data across different languages, and send data to a JavaScript-based web client.« less

High performance multichannel photonic biochip sensors for future point of care diagnostics: an overview on two EU-sponsored projects

NASA Astrophysics Data System (ADS)

Giannone, Domenico; Kazmierczak, Andrzej; Dortu, Fabian; Vivien, Laurent; Sohlström, Hans

2010-04-01

We present here research work on two optical biosensors which have been developed within two separate European projects (6th and 7th EU Framework Programmes). The biosensors are based on the idea of a disposable biochip, integrating photonics and microfluidics, optically interrogated by a multichannel interrogation platform. The objective is to develop versatile tools, suitable for performing screening tests at Point of Care or for example, at schools or in the field. The two projects explore different options in terms of optical design and different materials. While SABIO used Si3N4/SiO2 ring resonators structures, P3SENS aims at the use of photonic crystal devices based on polymers, potentially a much more economical option. We discuss both approaches to show how they enable high sensitivity and multiple channel detection. The medium term objective is to develop a new detection system that has low cost and is portable but at the same time offering high sensitivity, selectivity and multiparametric detection from a sample containing various components (e.g. blood, serum, saliva, etc.). Most biological sensing devices already present on the market suffer from limitations in multichannel operation capability (either the detection of multiple analytes indicating a given pathology or the simultaneous detection of multiple pathologies). In other words, the number of different analytes that can be detected on a single chip is very limited. This limitation is a main issue addressed by the two projects. The excessive cost per test of conventional bio sensing devices is a second issue that is addressed.

Universal electronics for miniature and automated chemical assays.

PubMed

Urban, Pawel L

2015-02-21

This minireview discusses universal electronic modules (generic programmable units) and their use by analytical chemists to construct inexpensive, miniature or automated devices. Recently, open-source platforms have gained considerable popularity among tech-savvy chemists because their implementation often does not require expert knowledge and investment of funds. Thus, chemistry students and researchers can easily start implementing them after a few hours of reading tutorials and trial-and-error. Single-board microcontrollers and micro-computers such as Arduino, Teensy, Raspberry Pi or BeagleBone enable collecting experimental data with high precision as well as efficient control of electric potentials and actuation of mechanical systems. They are readily programmed using high-level languages, such as C, C++, JavaScript or Python. They can also be coupled with mobile consumer electronics, including smartphones as well as teleinformatic networks. More demanding analytical tasks require fast signal processing. Field-programmable gate arrays enable efficient and inexpensive prototyping of high-performance analytical platforms, thus becoming increasingly popular among analytical chemists. This minireview discusses the advantages and drawbacks of universal electronic modules, considering their application in prototyping and manufacture of intelligent analytical instrumentation.

Design challenges in nanoparticle-based platforms: Implications for targeted drug delivery systems

NASA Astrophysics Data System (ADS)

Mullen, Douglas Gurnett

Characterization and control of heterogeneous distributions of nanoparticle-ligand components are major design challenges for nanoparticle-based platforms. This dissertation begins with an examination of poly(amidoamine) (PAMAM) dendrimer-based targeted delivery platform. A folic acid targeted modular platform was developed to target human epithelial cancer cells. Although active targeting was observed in vitro, active targeting was not found in vivo using a mouse tumor model. A major flaw of this platform design was that it did not provide for characterization or control of the component distribution. Motivated by the problems experienced with the modular design, the actual composition of nanoparticle-ligand distributions were examined using a model dendrimer-ligand system. High Pressure Liquid Chromatography (HPLC) resolved the distribution of components in samples with mean ligand/dendrimer ratios ranging from 0.4 to 13. A peak fitting analysis enabled the quantification of the component distribution. Quantified distributions were found to be significantly more heterogeneous than commonly expected and standard analytical parameters, namely the mean ligand/nanoparticle ratio, failed to adequately represent the component heterogeneity. The distribution of components was also found to be sensitive to particle modifications that preceded the ligand conjugation. With the knowledge gained from this detailed distribution analysis, a new platform design was developed to provide a system with dramatically improved control over the number of components and with improved batch reproducibility. Using semi-preparative HPLC, individual dendrimer-ligand components were isolated. The isolated dendrimer with precise numbers of ligands were characterized by NMR and analytical HPLC. In total, nine different dendrimer-ligand components were obtained with degrees of purity ≥80%. This system has the potential to serve as a platform to which a precise number of functional molecules can be attached and has the potential to dramatically improve platform efficacy. An additional investigation of reproducibility challenges for current dendrimer-based platform designs is also described. The mass transport quality during the partial acetylation reaction of the dendrimer was found to have a major impact on subsequent dendrimer-ligand distributions that cannot be detected by standard analytical techniques. Consequently, this reaction should be eliminated from the platform design. Finally, optimized protocols for purification and characterization of PAMAM dendrimer were detailed.

NASA Operation IceBridge Flies Into the Classroom!

NASA Astrophysics Data System (ADS)

Kane, M.

2017-12-01

Field research opportunities for educators is leveraged as an invaluable tool to increase public engagement in climate research and the geosciences. We investigate the influence of educator's authentic fieldwork by highlighting the post-field impacts of a PolarTREC Teacher who participated in two campaigns, including NASA Operation IceBridge campaign over Antarctica in 2016. NASA's Operation IceBridge has hosted PolarTREC teachers since 2012, welcoming five teachers aboard multiple flights over the Arctic and one over Antarctica. The continuity of teacher inclusion in Operation IceBridge campaigns has facilitated a platform for collaborative curriculum development and revision, integration of National Snow and Ice Data Center (NSIDC) data into multiple classrooms, and given us a means whereby students can interact with science team members. I present impacts to my teaching and classrooms as I grapple with "Big Data" to allow students to work directly with lidar and radar data, I examine public outreach impacts through analytics from virtual networking tools including social media, NASA's Mission Tools Suite for Education, and field blog interactions.

Advanced biological and chemical discovery (ABCD): centralizing discovery knowledge in an inherently decentralized world.

PubMed

Agrafiotis, Dimitris K; Alex, Simson; Dai, Heng; Derkinderen, An; Farnum, Michael; Gates, Peter; Izrailev, Sergei; Jaeger, Edward P; Konstant, Paul; Leung, Albert; Lobanov, Victor S; Marichal, Patrick; Martin, Douglas; Rassokhin, Dmitrii N; Shemanarev, Maxim; Skalkin, Andrew; Stong, John; Tabruyn, Tom; Vermeiren, Marleen; Wan, Jackson; Xu, Xiang Yang; Yao, Xiang

2007-01-01

We present ABCD, an integrated drug discovery informatics platform developed at Johnson & Johnson Pharmaceutical Research & Development, L.L.C. ABCD is an attempt to bridge multiple continents, data systems, and cultures using modern information technology and to provide scientists with tools that allow them to analyze multifactorial SAR and make informed, data-driven decisions. The system consists of three major components: (1) a data warehouse, which combines data from multiple chemical and pharmacological transactional databases, designed for supreme query performance; (2) a state-of-the-art application suite, which facilitates data upload, retrieval, mining, and reporting, and (3) a workspace, which facilitates collaboration and data sharing by allowing users to share queries, templates, results, and reports across project teams, campuses, and other organizational units. Chemical intelligence, performance, and analytical sophistication lie at the heart of the new system, which was developed entirely in-house. ABCD is used routinely by more than 1000 scientists around the world and is rapidly expanding into other functional areas within the J&J organization.

Comparative analytical evaluation of the respiratory TaqMan Array Card with real-time PCR and commercial multi-pathogen assays.

PubMed

Harvey, John J; Chester, Stephanie; Burke, Stephen A; Ansbro, Marisela; Aden, Tricia; Gose, Remedios; Sciulli, Rebecca; Bai, Jing; DesJardin, Lucy; Benfer, Jeffrey L; Hall, Joshua; Smole, Sandra; Doan, Kimberly; Popowich, Michael D; St George, Kirsten; Quinlan, Tammy; Halse, Tanya A; Li, Zhen; Pérez-Osorio, Ailyn C; Glover, William A; Russell, Denny; Reisdorf, Erik; Whyte, Thomas; Whitaker, Brett; Hatcher, Cynthia; Srinivasan, Velusamy; Tatti, Kathleen; Tondella, Maria Lucia; Wang, Xin; Winchell, Jonas M; Mayer, Leonard W; Jernigan, Daniel; Mawle, Alison C

2016-02-01

In this study, a multicenter evaluation of the Life Technologies TaqMan(®) Array Card (TAC) with 21 custom viral and bacterial respiratory assays was performed on the Applied Biosystems ViiA™ 7 Real-Time PCR System. The goal of the study was to demonstrate the analytical performance of this platform when compared to identical individual pathogen specific laboratory developed tests (LDTs) designed at the Centers for Disease Control and Prevention (CDC), equivalent LDTs provided by state public health laboratories, or to three different commercial multi-respiratory panels. CDC and Association of Public Health Laboratories (APHL) LDTs had similar analytical sensitivities for viral pathogens, while several of the bacterial pathogen APHL LDTs demonstrated sensitivities one log higher than the corresponding CDC LDT. When compared to CDC LDTs, TAC assays were generally one to two logs less sensitive depending on the site performing the analysis. Finally, TAC assays were generally more sensitive than their counterparts in three different commercial multi-respiratory panels. TAC technology allows users to spot customized assays and design TAC layout, simplify assay setup, conserve specimen, dramatically reduce contamination potential, and as demonstrated in this study, analyze multiple samples in parallel with good reproducibility between instruments and operators. Copyright © 2015 Elsevier B.V. All rights reserved.

On Establishing Big Data Wave Breakwaters with Analytics (Invited)

NASA Astrophysics Data System (ADS)

Riedel, M.

2013-12-01

The Research Data Alliance Big Data Analytics (RDA-BDA) Interest Group seeks to develop community based recommendations on feasible data analytics approaches to address scientific community needs of utilizing large quantities of data. RDA-BDA seeks to analyze different scientific domain applications and their potential use of various big data analytics techniques. A systematic classification of feasible combinations of analysis algorithms, analytical tools, data and resource characteristics and scientific queries will be covered in these recommendations. These combinations are complex since a wide variety of different data analysis algorithms exist (e.g. specific algorithms using GPUs of analyzing brain images) that need to work together with multiple analytical tools reaching from simple (iterative) map-reduce methods (e.g. with Apache Hadoop or Twister) to sophisticated higher level frameworks that leverage machine learning algorithms (e.g. Apache Mahout). These computational analysis techniques are often augmented with visual analytics techniques (e.g. computational steering on large-scale high performance computing platforms) to put the human judgement into the analysis loop or new approaches with databases that are designed to support new forms of unstructured or semi-structured data as opposed to the rather tradtional structural databases (e.g. relational databases). More recently, data analysis and underpinned analytics frameworks also have to consider energy footprints of underlying resources. To sum up, the aim of this talk is to provide pieces of information to understand big data analytics in the context of science and engineering using the aforementioned classification as the lighthouse and as the frame of reference for a systematic approach. This talk will provide insights about big data analytics methods in context of science within varios communities and offers different views of how approaches of correlation and causality offer complementary methods to advance in science and engineering today. The RDA Big Data Analytics Group seeks to understand what approaches are not only technically feasible, but also scientifically feasible. The lighthouse Goal of the RDA Big Data Analytics Group is a classification of clever combinations of various Technologies and scientific applications in order to provide clear recommendations to the scientific community what approaches are technicalla and scientifically feasible.

The Earth Data Analytic Services (EDAS) Framework

NASA Astrophysics Data System (ADS)

Maxwell, T. P.; Duffy, D.

2017-12-01

Faced with unprecedented growth in earth data volume and demand, NASA has developed the Earth Data Analytic Services (EDAS) framework, a high performance big data analytics framework built on Apache Spark. This framework enables scientists to execute data processing workflows combining common analysis operations close to the massive data stores at NASA. The data is accessed in standard (NetCDF, HDF, etc.) formats in a POSIX file system and processed using vetted earth data analysis tools (ESMF, CDAT, NCO, etc.). EDAS utilizes a dynamic caching architecture, a custom distributed array framework, and a streaming parallel in-memory workflow for efficiently processing huge datasets within limited memory spaces with interactive response times. EDAS services are accessed via a WPS API being developed in collaboration with the ESGF Compute Working Team to support server-side analytics for ESGF. The API can be accessed using direct web service calls, a Python script, a Unix-like shell client, or a JavaScript-based web application. New analytic operations can be developed in Python, Java, or Scala (with support for other languages planned). Client packages in Python, Java/Scala, or JavaScript contain everything needed to build and submit EDAS requests. The EDAS architecture brings together the tools, data storage, and high-performance computing required for timely analysis of large-scale data sets, where the data resides, to ultimately produce societal benefits. It is is currently deployed at NASA in support of the Collaborative REAnalysis Technical Environment (CREATE) project, which centralizes numerous global reanalysis datasets onto a single advanced data analytics platform. This service enables decision makers to compare multiple reanalysis datasets and investigate trends, variability, and anomalies in earth system dynamics around the globe.

PlanetSense: A Real-time Streaming and Spatio-temporal Analytics Platform for Gathering Geo-spatial Intelligence from Open Source Data

DOE Office of Scientific and Technical Information (OSTI.GOV)

Thakur, Gautam S; Bhaduri, Budhendra L; Piburn, Jesse O

Geospatial intelligence has traditionally relied on the use of archived and unvarying data for planning and exploration purposes. In consequence, the tools and methods that are architected to provide insight and generate projections only rely on such datasets. Albeit, if this approach has proven effective in several cases, such as land use identification and route mapping, it has severely restricted the ability of researchers to inculcate current information in their work. This approach is inadequate in scenarios requiring real-time information to act and to adjust in ever changing dynamic environments, such as evacuation and rescue missions. In this work, wemore » propose PlanetSense, a platform for geospatial intelligence that is built to harness the existing power of archived data and add to that, the dynamics of real-time streams, seamlessly integrated with sophisticated data mining algorithms and analytics tools for generating operational intelligence on the fly. The platform has four main components i) GeoData Cloud a data architecture for storing and managing disparate datasets; ii) Mechanism to harvest real-time streaming data; iii) Data analytics framework; iv) Presentation and visualization through web interface and RESTful services. Using two case studies, we underpin the necessity of our platform in modeling ambient population and building occupancy at scale.« less

Simultaneous determination of CRP and D-dimer in human blood plasma samples with White Light Reflectance Spectroscopy.

PubMed

Koukouvinos, Georgios; Petrou, Panagiota; Misiakos, Konstantinos; Drygiannakis, Dimitris; Raptis, Ioannis; Stefanitsis, Gerasimos; Martini, Spyridoula; Nikita, Dimitra; Goustouridis, Dimitrios; Moser, Isabella; Jobst, Gerhard; Kakabakos, Sotirios

2016-10-15

A dual-analyte assay for the simultaneous determination of C-reactive protein (CRP) and D-dimer in human blood plasma based on a white light interference spectroscopy sensing platform is presented. Measurement is accomplished in real-time by scanning the sensing surface, on which distinct antibody areas have been created, with a reflection probe used both for illumination of the surface and collection of the reflected interference spectrum. The composition of the transducer, the sensing surface chemical activation and biofunctionalization procedures were optimized with respect to signal magnitude and repeatability. The assay format involved direct detection of CRP whereas for D-dimer a two-site immunoassay employing a biotinylated reporter antibody and reaction with streptavidin was selected. The assays were sensitive with detection limits of 25ng/mL for both analytes, precise with intra- and inter-assay CV values ranging from 3.6% to 7.7%, and from 4.8% to 9.5%, respectively, for both assays, and accurate with recovery values ranging from 88.5% to 108% for both analytes. Moreover, the values determined for the two analytes in 35 human plasma samples were in excellent agreement with those received for the same samples by standard diagnostic laboratory instrumentation employing commercial kits. The excellent agreement of the results supported the validity of the proposed system for clinical application for the detection of multiple analytes since it was demonstrated that up to seven antibody areas can be created on the sensing surface and successfully interrogated with the developed optical set-up. Copyright © 2015. Published by Elsevier B.V.

Liquid chromatography-mass spectrometry platform for both small neurotransmitters and neuropeptides in blood, with automatic and robust solid phase extraction

NASA Astrophysics Data System (ADS)

Johnsen, Elin; Leknes, Siri; Wilson, Steven Ray; Lundanes, Elsa

2015-03-01

Neurons communicate via chemical signals called neurotransmitters (NTs). The numerous identified NTs can have very different physiochemical properties (solubility, charge, size etc.), so quantification of the various NT classes traditionally requires several analytical platforms/methodologies. We here report that a diverse range of NTs, e.g. peptides oxytocin and vasopressin, monoamines adrenaline and serotonin, and amino acid GABA, can be simultaneously identified/measured in small samples, using an analytical platform based on liquid chromatography and high-resolution mass spectrometry (LC-MS). The automated platform is cost-efficient as manual sample preparation steps and one-time-use equipment are kept to a minimum. Zwitter-ionic HILIC stationary phases were used for both on-line solid phase extraction (SPE) and liquid chromatography (capillary format, cLC). This approach enabled compounds from all NT classes to elute in small volumes producing sharp and symmetric signals, and allowing precise quantifications of small samples, demonstrated with whole blood (100 microliters per sample). An additional robustness-enhancing feature is automatic filtration/filter back-flushing (AFFL), allowing hundreds of samples to be analyzed without any parts needing replacement. The platform can be installed by simple modification of a conventional LC-MS system.

A differential mobility spectrometry/mass spectrometry platform for the rapid detection and quantitation of DNA adduct dG-ABP.

PubMed

Kafle, Amol; Klaene, Joshua; Hall, Adam B; Glick, James; Coy, Stephen L; Vouros, Paul

2013-07-15

There is continued interest in exploring new analytical technologies for the detection and quantitation of DNA adducts, biomarkers which provide direct evidence of exposure and genetic damage in cells. With the goal of reducing clean-up steps and improving sample throughput, a Differential Mobility Spectrometry/Mass Spectrometry (DMS/MS) platform has been introduced for adduct analysis. A DMS/MS platform has been utilized for the analysis of dG-ABP, the deoxyguanosine adduct of the bladder carcinogen 4-aminobiphenyl (4-ABP). After optimization of the DMS parameters, each sample was analyzed in just 30 s following a simple protein precipitation step of the digested DNA. A detection limit of one modification in 10^6 nucleosides has been achieved using only 2 µg of DNA. A brief comparison (quantitative and qualitative) with liquid chromatography/mass spectrometry is also presented highlighting the advantages of using the DMS/MS method as a high-throughput platform. The data presented demonstrate the successful application of a DMS/MS/MS platform for the rapid quantitation of DNA adducts using, as a model analyte, the deoxyguanosine adduct of the bladder carcinogen 4-aminobiphenyl. Copyright © 2013 John Wiley & Sons, Ltd.

A versatile phenotyping system and analytics platform reveals diverse temporal responses to water availability in Setaria

USDA-ARS?s Scientific Manuscript database

With rapid advances in DNA sequencing, phenotyping has become the rate-limiting step in using large-scale genomic data to understand and improve agricultural crops. Here, the Bellwether Phenotyping platform for controlled-environment plant growth and automated, multimodal phenotyping is described. T...

The development of a biomimetic acoustic direction finding system for use on multiple platforms

NASA Astrophysics Data System (ADS)

Deligeorges, Socrates; Anderson, David; Browning, Cassandra A.; Cohen, Howard; Freedman, David; Gore, Tyler; Karl, Christian; Kelsall, Sarah; Mountain, David; Nourzad, Marianne; Pu, Yirong; Sandifer, Matt; Xue, Shuwan; Ziph-Schatzberg, Leah; Hubbard, Allyn

2008-04-01

This paper describes the flow of scientific and technological achievements beginning with a stationary "small, smart, biomimetic acoustic processor" designed for DARPA that led to a program aimed at acoustic characterization and direction finding for multiple, mobile platforms. ARL support and collaboration has allowed us to adapt the core technology to multiple platforms including a Packbot robotic platform, a soldier worn platform, as well as a vehicle platform. Each of these has varying size and power requirements, but miniaturization is an important component of the program for creating practical systems which we address further in companion papers. We have configured the system to detect and localize gunfire and tested system performance with live fire from numerous weapons such as the AK47, the Dragunov, and the AR15. The ARL-sponsored work has led to connections with Natick Labs and the Future Force Warrior program, and in addition, the work has many and obvious applications to homeland defense, police, and civilian needs.

New approaches in GMO detection.

PubMed

Querci, Maddalena; Van den Bulcke, Marc; Zel, Jana; Van den Eede, Guy; Broll, Hermann

2010-03-01

The steady rate of development and diffusion of genetically modified plants and their increasing diversification of characteristics, genes and genetic control elements poses a challenge in analysis of genetically modified organisms (GMOs). It is expected that in the near future the picture will be even more complex. Traditional approaches, mostly based on the sequential detection of one target at a time, or on a limited multiplexing, allowing only a few targets to be analysed at once, no longer meet the testing requirements. Along with new analytical technologies, new approaches for the detection of GMOs authorized for commercial purposes in various countries have been developed that rely on (1) a smart and accurate strategy for target selection, (2) the use of high-throughput systems or platforms for the detection of multiple targets and (3) algorithms that allow the conversion of analytical results into an indication of the presence of individual GMOs potentially present in an unknown sample. This paper reviews the latest progress made in GMO analysis, taking examples from the most recently developed strategies and tools, and addresses some of the critical aspects related to these approaches.

Targeted proteomics coming of age - SRM, PRM and DIA performance evaluated from a core facility perspective.

PubMed

Kockmann, Tobias; Trachsel, Christian; Panse, Christian; Wahlander, Asa; Selevsek, Nathalie; Grossmann, Jonas; Wolski, Witold E; Schlapbach, Ralph

2016-08-01

Quantitative mass spectrometry is a rapidly evolving methodology applied in a large number of omics-type research projects. During the past years, new designs of mass spectrometers have been developed and launched as commercial systems while in parallel new data acquisition schemes and data analysis paradigms have been introduced. Core facilities provide access to such technologies, but also actively support the researchers in finding and applying the best-suited analytical approach. In order to implement a solid fundament for this decision making process, core facilities need to constantly compare and benchmark the various approaches. In this article we compare the quantitative accuracy and precision of current state of the art targeted proteomics approaches single reaction monitoring (SRM), parallel reaction monitoring (PRM) and data independent acquisition (DIA) across multiple liquid chromatography mass spectrometry (LC-MS) platforms, using a readily available commercial standard sample. All workflows are able to reproducibly generate accurate quantitative data. However, SRM and PRM workflows show higher accuracy and precision compared to DIA approaches, especially when analyzing low concentrated analytes. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Multiple emulsions as effective platforms for controlled anti-cancer drug delivery.

PubMed

Dluska, Ewa; Markowska-Radomska, Agnieszka; Metera, Agata; Tudek, Barbara; Kosicki, Konrad

2017-09-01

Developing pH-responsive multiple emulsion platforms for effective glioblastoma multiforme therapy with reduced toxicity, a drug release study and modeling. Cancer cell line: U87 MG, multiple emulsions with pH-responsive biopolymer and encapsulated doxorubicin (DOX); preparation of multiple emulsions in a Couette-Taylor flow biocontactor, in vitro release study of DOX (fluorescence intensity analysis), in vitro cytotoxicity study (alamarBlue cell viability assay) and numerical simulation of DOX release rates. The multiple emulsions offered a high DOX encapsulation efficiency (97.4 ± 1%) and pH modulated release rates of a drug. Multiple emulsions with a low concentration of DOX (0.02 μM) exhibited broadly advanced cell (U87 MG) cytotoxicity than free DOX solution used at the same concentration. Emulsion platforms could be explored for potential delivery of chemotherapeutics in glioblastoma multiforme therapy.

Centrifugal microfluidic platform for ultrasensitive detection of botulinum toxin

DOE PAGES

Koh, Chung -Yan; Schaff, Ulrich Y.; Sandstone Diagnostics, Livermore, CA; ...

2014-12-18

In this study, we present an innovative centrifugal microfluidic immunoassay platform (SpinDx) to address the urgent biodefense and public health need for ultrasensitive point-of-care/incident detection of botulinum toxin. The simple, sample-to-answer centrifugal microfluidic immunoassay approach is based on binding of toxins to antibody-laden capture particles followed by sedimentation of the particles through a density-media in a microfluidic disk and quantification by laser-induced fluorescence. A blind, head-to-head comparison study of SpinDx versus the gold-standard mouse bioassay demonstrates 100-fold improvement in sensitivity (limit of detection = 0.09 pg/mL), while achieving total sample-to-answer time of <30 min with 2-μL required volume of themore » unprocessed sample. We further demonstrate quantification of botulinum toxin in both exogeneous (human blood and serum spiked with toxins) and endogeneous (serum from mice intoxicated via oral, intranasal, and intravenous routes) samples. SpinDx can analyze, without any sample preparation, multiple sample types including whole blood, serum, and food. It is readily expandable to additional analytes as the assay reagents (i.e., the capture beads and detection antibodies) are disconnected from the disk architecture and the reader, facilitating rapid development of new assays. SpinDx can also serve as a general-purpose immunoassay platform applicable to diagnosis of other conditions and diseases.« less

Common aero vehicle autonomous reentry trajectory optimization satisfying waypoint and no-fly zone constraints

NASA Astrophysics Data System (ADS)

Jorris, Timothy R.

2007-12-01

To support the Air Force's Global Reach concept, a Common Aero Vehicle is being designed to support the Global Strike mission. "Waypoints" are specified for reconnaissance or multiple payload deployments and "no-fly zones" are specified for geopolitical restrictions or threat avoidance. Due to time critical targets and multiple scenario analysis, an autonomous solution is preferred over a time-intensive, manually iterative one. Thus, a real-time or near real-time autonomous trajectory optimization technique is presented to minimize the flight time, satisfy terminal and intermediate constraints, and remain within the specified vehicle heating and control limitations. This research uses the Hypersonic Cruise Vehicle (HCV) as a simplified two-dimensional platform to compare multiple solution techniques. The solution techniques include a unique geometric approach developed herein, a derived analytical dynamic optimization technique, and a rapidly emerging collocation numerical approach. This up-and-coming numerical technique is a direct solution method involving discretization then dualization, with pseudospectral methods and nonlinear programming used to converge to the optimal solution. This numerical approach is applied to the Common Aero Vehicle (CAV) as the test platform for the full three-dimensional reentry trajectory optimization problem. The culmination of this research is the verification of the optimality of this proposed numerical technique, as shown for both the two-dimensional and three-dimensional models. Additionally, user implementation strategies are presented to improve accuracy and enhance solution convergence. Thus, the contributions of this research are the geometric approach, the user implementation strategies, and the determination and verification of a numerical solution technique for the optimal reentry trajectory problem that minimizes time to target while satisfying vehicle dynamics and control limitation, and heating, waypoint, and no-fly zone constraints.

Graphene-Plasmonic Hybrid Platform for Label-Free SERS Biomedical Detection

NASA Astrophysics Data System (ADS)

Wang, Pu

Surface Enhanced Raman Scattering (SERS) has attracted explosive interest for the wealth of vibrational information it provides with minimal invasive effects to target analyte. Nanotechnology, especially in the form of noble metal nanoparticles exhibit unique electromagnetic and chemical characteristics that are explored to realize ultra-sensitive SERS detection in chemical and biological analysis. Graphene, atom-thick carbon monolayer, exhibits superior chemical stability and bio-compatibility. A combination of SERS-active metal nanostructures and graphene will create various synergies in SERS. The main objective of this research was to exploit the applications of the graphene-Au tip hybrid platform in SERS. The hybrid platform consists of a periodic Au nano-pyramid substrate to provide reproducible plasmonic enhancement, and the superimposed monolayer graphene sheet, serving as "built-in" Raman marker. Extensive theoretical and experimental studies were conducted to determine the potentials of the hybrid platform as SERS substrate. Results from both Finite-Domain Time-Domain (FDTD) numerical simulation and Raman scattering of graphene suggested that the hybrid platform boosted a high density of hotspots yielding 1000 times SERS enhancement of graphene bands. Ultra-high sensitivity of the hybrid platform was demonstrated by bio-molecules including dye, protein and neurotransmitters. Dopamine and serotonin can be detected and distinguished at 10-9 M concentration in the presence of human body fluid. Single molecule detection was obtained using a bi-analyte technique. Graphene supported a vibration mode dependent SERS chemical enhancement of ˜10 to the analyte. Quantitative evaluation of hotspots was presented using spatially resolved Raman mapping of graphene SERS enhancement. Graphene plays a crucial role in quantifying SERS hotspots and paves the path for defining SERS EF that could be universally applied to various SERS systems. A reproducible and statistically reliable SERS quantification approach using the hybrid platform was proposed. The SERS mapping based approach not only leverages the ultra-sensitivity but also minimizes the spot-to-spot variations. Feasibility of biomedical diagnosis with the hybrid platform was exploited by colon cancer cell sensing and time-dependent SERS of amyloid beta protein monomer. The capabilities of the platform are demonstrated by colon cancer cell detection in simulated body fluid background with cell concentration down to 50 cells /mL. Sensitivity of 95% was evidenced by Principle Components Analysis (PCA). Besides, a noticeable evolution profile of the Abeta SERS peaks was observed and attributed to the Abeta configurational change. Taken together, the results suggested the graphene-plasmonic hybrid platform can potentially deliver a biomedical detection and diagnostic imaging platform with superior sensitivity and resolution.

Platform for efficient switching between multiple devices in the intensive care unit.

PubMed

De Backere, F; Vanhove, T; Dejonghe, E; Feys, M; Herinckx, T; Vankelecom, J; Decruyenaere, J; De Turck, F

2015-01-01

This article is part of the Focus Theme of METHODS of Information in Medicine on "Managing Interoperability and Complexity in Health Systems". Handheld computers, such as tablets and smartphones, are becoming more and more accessible in the clinical care setting and in Intensive Care Units (ICUs). By making the most useful and appropriate data available on multiple devices and facilitate the switching between those devices, staff members can efficiently integrate them in their workflow, allowing for faster and more accurate decisions. This paper addresses the design of a platform for the efficient switching between multiple devices in the ICU. The key functionalities of the platform are the integration of the platform into the workflow of the medical staff and providing tailored and dynamic information at the point of care. The platform is designed based on a 3-tier architecture with a focus on extensibility, scalability and an optimal user experience. After identification to a device using Near Field Communication (NFC), the appropriate medical information will be shown on the selected device. The visualization of the data is adapted to the type of the device. A web-centric approach was used to enable extensibility and portability. A prototype of the platform was thoroughly evaluated. The scalability, performance and user experience were evaluated. Performance tests show that the response time of the system scales linearly with the amount of data. Measurements with up to 20 devices have shown no performance loss due to the concurrent use of multiple devices. The platform provides a scalable and responsive solution to enable the efficient switching between multiple devices. Due to the web-centric approach new devices can easily be integrated. The performance and scalability of the platform have been evaluated and it was shown that the response time and scalability of the platform was within an acceptable range.

Teaching individuals with intellectual disability to email across multiple device platforms.

PubMed

Cihak, David F; McMahon, Donald; Smith, Cate C; Wright, Rachel; Gibbons, Melinda M

2014-11-20

The purpose of this study was to examine the use of email by people with intellectual disability across multiple technological devices or platforms. Four individuals with intellectual disability participated in this study. Participants were taught how to access and send an email on a Windows desktop computer, laptop, and an iPad tablet device. Results indicated a functional relation. All participants acquired and generalized sending and receiving an email from multiple platforms. Conclusions are discussed about the importance of empowering people with intellectual disability by providing multiple means of expression, including the ability to communicate effectively using a variety of devices. Copyright © 2014 Elsevier Ltd. All rights reserved.

The Climate Data Analytic Services (CDAS) Framework.

NASA Astrophysics Data System (ADS)

Maxwell, T. P.; Duffy, D.

2016-12-01

Faced with unprecedented growth in climate data volume and demand, NASA has developed the Climate Data Analytic Services (CDAS) framework. This framework enables scientists to execute data processing workflows combining common analysis operations in a high performance environment close to the massive data stores at NASA. The data is accessed in standard (NetCDF, HDF, etc.) formats in a POSIX file system and processed using vetted climate data analysis tools (ESMF, CDAT, NCO, etc.). A dynamic caching architecture enables interactive response times. CDAS utilizes Apache Spark for parallelization and a custom array framework for processing huge datasets within limited memory spaces. CDAS services are accessed via a WPS API being developed in collaboration with the ESGF Compute Working Team to support server-side analytics for ESGF. The API can be accessed using either direct web service calls, a python script, a unix-like shell client, or a javascript-based web application. Client packages in python, scala, or javascript contain everything needed to make CDAS requests. The CDAS architecture brings together the tools, data storage, and high-performance computing required for timely analysis of large-scale data sets, where the data resides, to ultimately produce societal benefits. It is is currently deployed at NASA in support of the Collaborative REAnalysis Technical Environment (CREATE) project, which centralizes numerous global reanalysis datasets onto a single advanced data analytics platform. This service permits decision makers to investigate climate changes around the globe, inspect model trends and variability, and compare multiple reanalysis datasets.

ELISA-type assays of trace biomarkers using microfluidic methods.

PubMed

Dong, Jinhua; Ueda, Hiroshi

2017-09-01

Recently, great progress has been achieved for analytical technologies for biological substances. Traditionally, detection methods for analytes mainly rely on large instrumental analyses. These methods require costly equipment, skilled operators and long measurement time despite their generally low sensitivity. In contrast, immunoassays are becoming more and more popular for it is powerful, inexpensive, and convenient nature. Immunoassay has a range of applications, because it employs antibody, a protein produced by plasma cells in the acquired immune system to identify and neutralize diverse pathogens and other exogenous substances. However, the sensitivity of conventional immunoassays so far is limited by their reaction principles and detection methods. The microfluidics technology is the one that manipulates small volumes of fluid and flow, which has the potential to miniaturize many laboratory procedures. Immunoassays on microfluidic devices have been studied extensively and have gained significant attention owing to intrinsic advantages offered by the assay platforms. The techniques have allowed the miniaturization of conventional immunoassay and bring the advantages such as small volumes of samples and reagents as well as the decrease of contamination, which results in the decline of false-positive results. Ultimately, the combination of immunoassays with microfluidics affords a promising platform for multiple, sensitive, and automatic point-of-care diagnostics. Recent achievements on microfluidic devices and immunoassay detection systems including digital assay employing single molecule will be introduced in detail and the strategies for faster and more sensitive configurations in microfluidic immunosensors will be highlighted. WIREs Nanomed Nanobiotechnol 2017, 9:e1457. doi: 10.1002/wnan.1457 For further resources related to this article, please visit the WIREs website. © 2017 Wiley Periodicals, Inc.

Market implementation of the MVA platform for pre-pandemic and pandemic influenza vaccines: A quantitative key opinion leader analysis

PubMed Central

Ramezanpour, Bahar; Pronker, Esther S.; Kreijtz, Joost H.C.M.; Osterhaus, Albert D.M.E.; Claassen, E.

2015-01-01

A quantitative method is presented to rank strengths, weaknesses, opportunities, and threats (SWOT) of modified vaccinia virus Ankara (MVA) as a platform for pre-pandemic and pandemic influenza vaccines. Analytic hierarchy process (AHP) was applied to achieve pairwise comparisons among SWOT factors in order to prioritize them. Key opinion leaders (KOLs) in the influenza vaccine field were interviewed to collect a unique dataset to evaluate the market potential of this platform. The purpose of this study, to evaluate commercial potential of the MVA platform for the development of novel generation pandemic influenza vaccines, is accomplished by using a SWOT and AHP combined analytic method. Application of the SWOT–AHP model indicates that its strengths are considered more important by KOLs than its weaknesses, opportunities, and threats. Particularly, the inherent immunogenicity capability of MVA without the requirement of an adjuvant is the most important factor to increase commercial attractiveness of this platform. Concerns regarding vector vaccines and anti-vector immunity are considered its most important weakness, which might lower public health value of this platform. Furthermore, evaluation of the results of this study emphasizes equally important role that threats and opportunities of this platform play. This study further highlights unmet needs in the influenza vaccine market, which could be addressed by the implementation of the MVA platform. Broad use of MVA in clinical trials shows great promise for this vector as vaccine platform for pre-pandemic and pandemic influenza and threats by other respiratory viruses. Moreover, from the results of the clinical trials seem that MVA is particularly attractive for development of vaccines against pathogens for which no, or only insufficiently effective vaccines, are available. PMID:26048779

Market implementation of the MVA platform for pre-pandemic and pandemic influenza vaccines: A quantitative key opinion leader analysis.

PubMed

Ramezanpour, Bahar; Pronker, Esther S; Kreijtz, Joost H C M; Osterhaus, Albert D M E; Claassen, E

2015-08-20

A quantitative method is presented to rank strengths, weaknesses, opportunities, and threats (SWOT) of modified vaccinia virus Ankara (MVA) as a platform for pre-pandemic and pandemic influenza vaccines. Analytic hierarchy process (AHP) was applied to achieve pairwise comparisons among SWOT factors in order to prioritize them. Key opinion leaders (KOLs) in the influenza vaccine field were interviewed to collect a unique dataset to evaluate the market potential of this platform. The purpose of this study, to evaluate commercial potential of the MVA platform for the development of novel generation pandemic influenza vaccines, is accomplished by using a SWOT and AHP combined analytic method. Application of the SWOT-AHP model indicates that its strengths are considered more important by KOLs than its weaknesses, opportunities, and threats. Particularly, the inherent immunogenicity capability of MVA without the requirement of an adjuvant is the most important factor to increase commercial attractiveness of this platform. Concerns regarding vector vaccines and anti-vector immunity are considered its most important weakness, which might lower public health value of this platform. Furthermore, evaluation of the results of this study emphasizes equally important role that threats and opportunities of this platform play. This study further highlights unmet needs in the influenza vaccine market, which could be addressed by the implementation of the MVA platform. Broad use of MVA in clinical trials shows great promise for this vector as vaccine platform for pre-pandemic and pandemic influenza and threats by other respiratory viruses. Moreover, from the results of the clinical trials seem that MVA is particularly attractive for development of vaccines against pathogens for which no, or only insufficiently effective vaccines, are available. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

A DUAL PLATFORM FOR SELECTIVE ANALYTE ENRICHMENT AND IONIZATION IN MASS SPECTROMETRY USING APTAMER-CONJUGATED GRAPHENE OXIDE

PubMed Central

Gulbakan, Basri; Yasun, Emir; Shukoor, M. Ibrahim; Zhu, Zhi; You, Mingxu; Tan, Xiaohong; Sanchez, Hernan; Powell, David H.; Dai, Hongjie; Tan, Weihong

2010-01-01

This study demonstrates the use of aptamer-conjugated graphene oxide as an affinity extraction and detection platform for analytes from complex biological media. We have shown that cocaine and adenosine can be selectively enriched from plasma samples and that direct mass spectrometric readout can be obtained without a matrix and with greatly improved signal-to-noise ratios. The aptamer conjugated graphene oxide has clear advantages in target enrichment and in generating highly efficient ionization of target molecules for mass spectrometry. These results demonstrate the utility of the approach for analysis of small molecules in real biological samples. PMID:21090719

A fluorescent immunoassay for the determination of procalcitonin and C-reactive protein

NASA Astrophysics Data System (ADS)

Baldini, F.; Bolzoni, L.; Giannetti, A.; Porro, G.; Senesi, F.; Trono, C.

2009-05-01

The discrimination of viral and bacterial sepsis is an important issue in intensive care patients. For this purpose, the simultaneous measurements of different analytes such as C-reactive protein (CRP), procalcitonin (PCT), myeloperoxidase, interleukines and neopterin, are necessary. A novel optical platform was designed and realised for the implementation of fluorescence-based immunoassays. The core of the optical platform is a plastic biochip, formed by a series of microchannels each of them devoted to the determination of a single analyte. Sandwich assays for CRP and PCT spiked in serum were performed in order to demonstrate the reliability of a multi-array device.

OLED-based biosensing platform with ZnO nanoparticles for enzyme immobilization

NASA Astrophysics Data System (ADS)

Cai, Yuankun; Shinar, Ruth; Shinar, Joseph

2009-08-01

Organic light-emitting diode (OLED)-based sensing platforms are attractive for photoluminescence (PL)-based monitoring of a variety of analytes. Among the promising OLED attributes for sensing applications is the thin and flexible size and design of the OLED pixel array that is used for PL excitation. To generate a compact, fielddeployable sensor, other major sensor components, such as the sensing probe and the photodetector, in addition to the thin excitation source, should be compact. To this end, the OLED-based sensing platform was tested with composite thin biosensing films, where oxidase enzymes were immobilized on ZnO nanoparticles, rather than dissolved in solution, to generate a more compact device. The analytes tested, glucose, cholesterol, and lactate, were monitored by following their oxidation reactions in the presence of oxygen and their respective oxidase enzymes. During such reactions, oxygen is consumed and its residual concentration, which is determined by the initial concentration of the above-mentioned analytes, is monitored. The sensors utilized the oxygen-sensitive dye Pt octaethylporphyrin, embedded in polystyrene. The enzymes were sandwiched between two thin ZnO layers, an approach that was found to improve the stability of the sensing probes.

Enhanced Quality Factor Label-free Biosensing with Micro-Cantilevers Integrated into Microfluidic Systems.

PubMed

Kartanas, Tadas; Ostanin, Victor; Challa, Pavan Kumar; Daly, Ronan; Charmet, Jerome; Knowles, Tuomas P J

2017-11-21

Microelectromechanical systems (MEMS) have enabled the development of a new generation of sensor platforms. Acoustic sensor operation in liquid, the native environment of biomolecules, causes, however, significant degradation of sensing performance due to viscous drag and relies on the availability of capture molecules to bind analytes of interest to the sensor surface. Here, we describe a strategy to interface MEMS sensors with microfluidic platforms through an aerosol spray. Our sensing platform comprises a microfluidic spray nozzle and a microcantilever array operated in dynamic mode within a closed loop oscillator. A solution containing the analyte is sprayed uniformly through picoliter droplets onto the microcantilever surface; the micrometer-scale drops evaporate rapidly and leave the solutes behind, adding to the mass of the cantilever. This sensing scheme results in a 50-fold increase in the quality factor compared to operation in liquid, yet allows the analytes to be introduced into the sensing system from a solution phase. It achieves a 370 femtogram limit of detection, and we demonstrate quantitative label-free analysis of inorganic salts and model proteins. These results demonstrate that the standard resolution limits of cantilever sensing in dynamic mode can be overcome with the integration of spray microfluidics with MEMS.

New technology for early detection of health threats

NASA Astrophysics Data System (ADS)

Southern, Šárka O.; Lilienthal, Gerald W.

2008-04-01

Governmental agencies charged with protecting the health of the population and agriculture have several main strategic objectives including the detection of harmful agents, the identification of vulnerable biological targets, the prediction of health outcomes and the development of countermeasures. New technologies are urgently needed in several critical areas of bio-chemical defense: economical and minimally invasive biosensors for field use in humans and other species important for agriculture and infrastructure, universal analytical platforms for broad-based, early warnings of threats and technologies guiding the development of countermeasures. A new technology called Stress Response Profiling (SRP) was recently developed by the Gaia Medical Institute. SRP provides a universal analytical platform for monitoring health status based on measurements of physiological stress. The platform is implemented through handheld devices that can be used for noninvasive detection of early-stage health problems. This paper summarizes SRP features, advantages and potential benefits for critical areas of homeland defense.

Mass spectrometry-based biomarker discovery: toward a global proteome index of individuality.

PubMed

Hawkridge, Adam M; Muddiman, David C

2009-01-01

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

Retention in porous layer pillar array planar separation platforms

DOE PAGES

Lincoln, Danielle R.; Lavrik, Nickolay V.; Kravchenko, Ivan I.; ...

2016-08-11

Here, this work presents the retention capabilities and surface area enhancement of highly ordered, high-aspect-ratio, open-platform, two-dimensional (2D) pillar arrays when coated with a thin layer of porous silicon oxide (PSO). Photolithographically prepared pillar arrays were coated with 50–250 nm of PSO via plasma-enhanced chemical vapor deposition and then functionalized with either octadecyltrichlorosilane or n-butyldimethylchlorosilane. Theoretical calculations indicate that a 50 nm layer of PSO increases the surface area of a pillar nearly 120-fold. Retention capabilities were tested by observing capillary-action-driven development under various conditions, as well as by running one-dimensional separations on varying thicknesses of PSO. Increasing the thicknessmore » of PSO on an array clearly resulted in greater retention of the analyte(s) in question in both experiments. In culmination, a two-dimensional separation of fluorescently derivatized amines was performed to further demonstrate the capabilities of these fabricated platforms.« less

Nanoparticle functionalised small-core suspended-core fibre - a novel platform for efficient sensing.

PubMed

Doherty, Brenda; Csáki, Andrea; Thiele, Matthias; Zeisberger, Matthias; Schwuchow, Anka; Kobelke, Jens; Fritzsche, Wolfgang; Schmidt, Markus A

2017-02-01

Detecting small quantities of specific target molecules is of major importance within bioanalytics for efficient disease diagnostics. One promising sensing approach relies on combining plasmonically-active waveguides with microfluidics yielding an easy-to-use sensing platform. Here we introduce suspended-core fibres containing immobilised plasmonic nanoparticles surrounding the guiding core as a concept for an entirely integrated optofluidic platform for efficient refractive index sensing. Due to the extremely small optical core and the large adjacent microfluidic channels, over two orders of magnitude of nanoparticle coverage densities have been accessed with millimetre-long sample lengths showing refractive index sensitivities of 170 nm/RIU for aqueous analytes where the fibre interior is functionalised by gold nanospheres. Our concept represents a fully integrated optofluidic sensing system demanding small sample volumes and allowing for real-time analyte monitoring, both of which are highly relevant within invasive bioanalytics, particularly within molecular disease diagnostics and environmental science.

AMP: A platform for managing and mining data in the treatment of Autism Spectrum Disorder.

PubMed

Linstead, Erik; Burns, Ryan; Duy Nguyen; Tyler, David

2016-08-01

We introduce AMP (Autism Management Platform), an integrated health care information system for capturing, analyzing, and managing data associated with the diagnosis and treatment of Autism Spectrum Disorder in children. AMP's mobile application simplifies the means by which parents, guardians, and clinicians can collect and share multimedia data with one another, facilitating communication and reducing data redundancy, while simplifying retrieval. Additionally, AMP provides an intelligent web interface and analytics platform which allow physicians and specialists to aggregate and mine patient data in real-time, as well as give relevant feedback to automatically learn data filtering preferences over time. Together AMP's mobile app, web client, and analytics engine implement a rich set of features that streamline the data collection and analysis process in the context of a secure and easy-to-use system so that data may be more effectively leveraged to guide treatment.

OpenHealth Platform for Interactive Contextualization of Population Health Open Data.

PubMed

Almeida, Jonas S; Hajagos, Janos; Crnosija, Ivan; Kurc, Tahsin; Saltz, Mary; Saltz, Joel

The financial incentives for data science applications leading to improved health outcomes, such as DSRIP (bit.ly/dsrip), are well-aligned with the broad adoption of Open Data by State and Federal agencies. This creates entirely novel opportunities for analytical applications that make exclusive use of the pervasive Web Computing platform. The framework described here explores this new avenue to contextualize Health data in a manner that relies exclusively on the native JavaScript interpreter and data processing resources of the ubiquitous Web Browser. The OpenHealth platform is made publicly available, and is publicly hosted with version control and open source, at https://github.com/mathbiol/openHealth. The different data/analytics workflow architectures explored are accompanied with live applications ranging from DSRIP, such as Hospital Inpatient Prevention Quality Indicators at http://bit.ly/pqiSuffolk, to The Cancer Genome Atlas (TCGA) as illustrated by http://bit.ly/tcgascopeGBM.

Retention in porous layer pillar array planar separation platforms

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lincoln, Danielle R.; Lavrik, Nickolay V.; Kravchenko, Ivan I.

Here, this work presents the retention capabilities and surface area enhancement of highly ordered, high-aspect-ratio, open-platform, two-dimensional (2D) pillar arrays when coated with a thin layer of porous silicon oxide (PSO). Photolithographically prepared pillar arrays were coated with 50–250 nm of PSO via plasma-enhanced chemical vapor deposition and then functionalized with either octadecyltrichlorosilane or n-butyldimethylchlorosilane. Theoretical calculations indicate that a 50 nm layer of PSO increases the surface area of a pillar nearly 120-fold. Retention capabilities were tested by observing capillary-action-driven development under various conditions, as well as by running one-dimensional separations on varying thicknesses of PSO. Increasing the thicknessmore » of PSO on an array clearly resulted in greater retention of the analyte(s) in question in both experiments. In culmination, a two-dimensional separation of fluorescently derivatized amines was performed to further demonstrate the capabilities of these fabricated platforms.« less

Sandplay therapy with couples within the framework of analytical psychology.

PubMed

Albert, Susan Carol

2015-02-01

Sandplay therapy with couples is discussed within an analytical framework. Guidelines are proposed as a means of developing this relatively new area within sandplay therapy, and as a platform to open a wider discussion to bring together sandplay therapy and couple therapy. Examples of sand trays created during couple therapy are also presented to illustrate the transformations during the therapeutic process. © 2015, The Society of Analytical Psychology.

Evaluation of Direct Infusion-Multiple Reaction Monitoring Mass Spectrometry for Quantification of Heat Shock Proteins

PubMed Central

Xiang, Yun; Koomen, John M.

2012-01-01

Protein quantification with liquid chromatography-multiple reaction monitoring mass spectrometry (LC-MRM) has emerged as a powerful platform for assessing panels of biomarkers. In this study, direct infusion, using automated, chip-based nanoelectrospray ionization, coupled with MRM (DI-MRM) is used for protein quantification. Removal of the LC separation step increases the importance of evaluating the ratios between the transitions. Therefore, the effects of solvent composition, analyte concentration, spray voltage, and quadrupole resolution settings on fragmentation patterns have been studied using peptide and protein standards. After DI-MRM quantification was evaluated for standards, quantitative assays for the expression of heat shock proteins (HSPs) were translated from LC-MRM to DI-MRM for implementation in cell line models of multiple myeloma. Requirements for DI-MRM assay development are described. Then, the two methods are compared; criteria for effective DI-MRM analysis are reported based on the analysis of HSP expression in digests of whole cell lysates. The increased throughput of DI-MRM analysis is useful for rapid analysis of large batches of similar samples, such as time course measurements of cellular responses to therapy. PMID:22293045

Comprehensive Molecular Characterization of Muscle-Invasive Bladder Cancer.

PubMed

Robertson, A Gordon; Kim, Jaegil; Al-Ahmadie, Hikmat; Bellmunt, Joaquim; Guo, Guangwu; Cherniack, Andrew D; Hinoue, Toshinori; Laird, Peter W; Hoadley, Katherine A; Akbani, Rehan; Castro, Mauro A A; Gibb, Ewan A; Kanchi, Rupa S; Gordenin, Dmitry A; Shukla, Sachet A; Sanchez-Vega, Francisco; Hansel, Donna E; Czerniak, Bogdan A; Reuter, Victor E; Su, Xiaoping; de Sa Carvalho, Benilton; Chagas, Vinicius S; Mungall, Karen L; Sadeghi, Sara; Pedamallu, Chandra Sekhar; Lu, Yiling; Klimczak, Leszek J; Zhang, Jiexin; Choo, Caleb; Ojesina, Akinyemi I; Bullman, Susan; Leraas, Kristen M; Lichtenberg, Tara M; Wu, Catherine J; Schultz, Nicholaus; Getz, Gad; Meyerson, Matthew; Mills, Gordon B; McConkey, David J; Weinstein, John N; Kwiatkowski, David J; Lerner, Seth P

2017-10-19

We report a comprehensive analysis of 412 muscle-invasive bladder cancers characterized by multiple TCGA analytical platforms. Fifty-eight genes were significantly mutated, and the overall mutational load was associated with APOBEC-signature mutagenesis. Clustering by mutation signature identified a high-mutation subset with 75% 5-year survival. mRNA expression clustering refined prior clustering analyses and identified a poor-survival "neuronal" subtype in which the majority of tumors lacked small cell or neuroendocrine histology. Clustering by mRNA, long non-coding RNA (lncRNA), and miRNA expression converged to identify subsets with differential epithelial-mesenchymal transition status, carcinoma in situ scores, histologic features, and survival. Our analyses identified 5 expression subtypes that may stratify response to different treatments. Copyright © 2017 Elsevier Inc. All rights reserved.

Application of Soft Computing in Coherent Communications Phase Synchronization

NASA Technical Reports Server (NTRS)

Drake, Jeffrey T.; Prasad, Nadipuram R.

2000-01-01

The use of soft computing techniques in coherent communications phase synchronization provides an alternative to analytical or hard computing methods. This paper discusses a novel use of Adaptive Neuro-Fuzzy Inference Systems (ANFIS) for phase synchronization in coherent communications systems utilizing Multiple Phase Shift Keying (MPSK) modulation. A brief overview of the M-PSK digital communications bandpass modulation technique is presented and it's requisite need for phase synchronization is discussed. We briefly describe the hybrid platform developed by Jang that incorporates fuzzy/neural structures namely the, Adaptive Neuro-Fuzzy Interference Systems (ANFIS). We then discuss application of ANFIS to phase estimation for M-PSK. The modeling of both explicit, and implicit phase estimation schemes for M-PSK symbols with unknown structure are discussed. Performance results from simulation of the above scheme is presented.

A coordinated set of ecosystem research platforms open to international research in ecotoxicology, AnaEE-France.

PubMed

Mougin, Christian; Azam, Didier; Caquet, Thierry; Cheviron, Nathalie; Dequiedt, Samuel; Le Galliard, Jean-François; Guillaume, Olivier; Houot, Sabine; Lacroix, Gérard; Lafolie, François; Maron, Pierre-Alain; Michniewicz, Radika; Pichot, Christian; Ranjard, Lionel; Roy, Jacques; Zeller, Bernd; Clobert, Jean; Chanzy, André

2015-10-01

The infrastructure for Analysis and Experimentation on Ecosystems (AnaEE-France) is an integrated network of the major French experimental, analytical, and modeling platforms dedicated to the biological study of continental ecosystems (aquatic and terrestrial). This infrastructure aims at understanding and predicting ecosystem dynamics under global change. AnaEE-France comprises complementary nodes offering access to the best experimental facilities and associated biological resources and data: Ecotrons, seminatural experimental platforms to manipulate terrestrial and aquatic ecosystems, in natura sites equipped for large-scale and long-term experiments. AnaEE-France also provides shared instruments and analytical platforms dedicated to environmental (micro) biology. Finally, AnaEE-France provides users with data bases and modeling tools designed to represent ecosystem dynamics and to go further in coupling ecological, agronomical, and evolutionary approaches. In particular, AnaEE-France offers adequate services to tackle the new challenges of research in ecotoxicology, positioning its various types of platforms in an ecologically advanced ecotoxicology approach. AnaEE-France is a leading international infrastructure, and it is pioneering the construction of AnaEE (Europe) infrastructure in the field of ecosystem research. AnaEE-France infrastructure is already open to the international community of scientists in the field of continental ecotoxicology.

Clinical validation of the 50 gene AmpliSeq Cancer Panel V2 for use on a next generation sequencing platform using formalin fixed, paraffin embedded and fine needle aspiration tumour specimens.

PubMed

Rathi, Vivek; Wright, Gavin; Constantin, Diana; Chang, Siok; Pham, Huong; Jones, Kerryn; Palios, Atha; Mclachlan, Sue-Anne; Conron, Matthew; McKelvie, Penny; Williams, Richard

2017-01-01

The advent of massively parallel sequencing has caused a paradigm shift in the ways cancer is treated, as personalised therapy becomes a reality. More and more laboratories are looking to introduce next generation sequencing (NGS) as a tool for mutational analysis, as this technology has many advantages compared to conventional platforms like Sanger sequencing. In Australia all massively parallel sequencing platforms are still considered in-house in vitro diagnostic tools by the National Association of Testing Authorities (NATA) and a comprehensive analytical validation of all assays, and not just mere verification, is a strict requirement before accreditation can be granted for clinical testing on these platforms. Analytical validation of assays on NGS platforms can prove to be extremely challenging for pathology laboratories. Although there are many affordable and easily accessible NGS instruments available, there are no standardised guidelines as yet for clinical validation of NGS assays. We present an accreditation development procedure that was both comprehensive and applicable in a setting of hospital laboratory for NGS services. This approach may also be applied to other NGS applications in service laboratories. Copyright © 2016 Royal College of Pathologists of Australasia. Published by Elsevier B.V. All rights reserved.

Development of Analytical Plug-ins for ENSITE: Version 1.0

DTIC Science & Technology

2017-11-01

ENSITE’s core-software platform builds upon leading geospatial platforms already in use by the Army and is designed to offer an easy-to-use, customized ...use by the Army and is designed to offer an easy-to-use, customized set of workflows for CB planners. Within this platform are added software compo...public good . Find out more at www.erdc.usace.army.mil. To search for other technical reports published by ERDC, visit the ERDC online library at

Automated platform for designing multiple robot work cells

NASA Astrophysics Data System (ADS)

Osman, N. S.; Rahman, M. A. A.; Rahman, A. A. Abdul; Kamsani, S. H.; Bali Mohamad, B. M.; Mohamad, E.; Zaini, Z. A.; Rahman, M. F. Ab; Mohamad Hatta, M. N. H.

2017-06-01

Designing the multiple robot work cells is very knowledge-intensive, intricate, and time-consuming process. This paper elaborates the development process of a computer-aided design program for generating the multiple robot work cells which offer a user-friendly interface. The primary purpose of this work is to provide a fast and easy platform for less cost and human involvement with minimum trial and errors adjustments. The automated platform is constructed based on the variant-shaped configuration concept with its mathematical model. A robot work cell layout, system components, and construction procedure of the automated platform are discussed in this paper where integration of these items will be able to automatically provide the optimum robot work cell design according to the information set by the user. This system is implemented on top of CATIA V5 software and utilises its Part Design, Assembly Design, and Macro tool. The current outcomes of this work provide a basis for future investigation in developing a flexible configuration system for the multiple robot work cells.

The Analytic Information Warehouse (AIW): a Platform for Analytics using Electronic Health Record Data

PubMed Central

Post, Andrew R.; Kurc, Tahsin; Cholleti, Sharath; Gao, Jingjing; Lin, Xia; Bornstein, William; Cantrell, Dedra; Levine, David; Hohmann, Sam; Saltz, Joel H.

2013-01-01

Objective To create an analytics platform for specifying and detecting clinical phenotypes and other derived variables in electronic health record (EHR) data for quality improvement investigations. Materials and Methods We have developed an architecture for an Analytic Information Warehouse (AIW). It supports transforming data represented in different physical schemas into a common data model, specifying derived variables in terms of the common model to enable their reuse, computing derived variables while enforcing invariants and ensuring correctness and consistency of data transformations, long-term curation of derived data, and export of derived data into standard analysis tools. It includes software that implements these features and a computing environment that enables secure high-performance access to and processing of large datasets extracted from EHRs. Results We have implemented and deployed the architecture in production locally. The software is available as open source. We have used it as part of hospital operations in a project to reduce rates of hospital readmission within 30 days. The project examined the association of over 100 derived variables representing disease and co-morbidity phenotypes with readmissions in five years of data from our institution’s clinical data warehouse and the UHC Clinical Database (CDB). The CDB contains administrative data from over 200 hospitals that are in academic medical centers or affiliated with such centers. Discussion and Conclusion A widely available platform for managing and detecting phenotypes in EHR data could accelerate the use of such data in quality improvement and comparative effectiveness studies. PMID:23402960

An Interactive Platform to Visualize Data-Driven Clinical Pathways for the Management of Multiple Chronic Conditions.

PubMed

Zhang, Yiye; Padman, Rema

2017-01-01

Patients with multiple chronic conditions (MCC) pose an increasingly complex health management challenge worldwide, particularly due to the significant gap in our understanding of how to provide coordinated care. Drawing on our prior research on learning data-driven clinical pathways from actual practice data, this paper describes a prototype, interactive platform for visualizing the pathways of MCC to support shared decision making. Created using Python web framework, JavaScript library and our clinical pathway learning algorithm, the visualization platform allows clinicians and patients to learn the dominant patterns of co-progression of multiple clinical events from their own data, and interactively explore and interpret the pathways. We demonstrate functionalities of the platform using a cluster of 36 patients, identified from a dataset of 1,084 patients, who are diagnosed with at least chronic kidney disease, hypertension, and diabetes. Future evaluation studies will explore the use of this platform to better understand and manage MCC.

Evaluation of analytical performance of a new high-sensitivity immunoassay for cardiac troponin I.

PubMed

Masotti, Silvia; Prontera, Concetta; Musetti, Veronica; Storti, Simona; Ndreu, Rudina; Zucchelli, Gian Carlo; Passino, Claudio; Clerico, Aldo

2018-02-23

The study aim was to evaluate and compare the analytical performance of the new chemiluminescent immunoassay for cardiac troponin I (cTnI), called Access hs-TnI using DxI platform, with those of Access AccuTnI+3 method, and high-sensitivity (hs) cTnI method for ARCHITECT platform. The limits of blank (LoB), detection (LoD) and quantitation (LoQ) at 10% and 20% CV were evaluated according to international standardized protocols. For the evaluation of analytical performance and comparison of cTnI results, both heparinized plasma samples, collected from healthy subjects and patients with cardiac diseases, and quality control samples distributed in external quality assessment programs were used. LoB, LoD and LoQ at 20% and 10% CV values of the Access hs-cTnI method were 0.6, 1.3, 2.1 and 5.3 ng/L, respectively. Access hs-cTnI method showed analytical performance significantly better than that of Access AccuTnI+3 method and similar results to those of hs ARCHITECT cTnI method. Moreover, the cTnI concentrations measured with Access hs-cTnI method showed close linear regressions with both Access AccuTnI+3 and ARCHITECT hs-cTnI methods, although there were systematic differences between these methods. There was no difference between cTnI values measured by Access hs-cTnI in heparinized plasma and serum samples, whereas there was a significant difference between cTnI values, respectively measured in EDTA and heparin plasma samples. Access hs-cTnI has analytical sensitivity parameters significantly improved compared to Access AccuTnI+3 method and is similar to those of the high-sensitivity method using ARCHITECT platform.

Design and Calibration of a Flowfield Survey Rake for Inlet Flight Research

NASA Technical Reports Server (NTRS)

Flynn, Darin C.; Ratnayake, Nalin A.; Frederick, Michael

2009-01-01

The Propulsion Flight Test Fixture at the NASA Dryden Flight Research Center is a unique test platform available for use on NASA's F-15B aircraft, tail number 836, as a modular host for a variety of aerodynamics and propulsion research. For future flight data from this platform to be valid, more information must be gathered concerning the quality of the airflow underneath the body of the F-15B at various flight conditions, especially supersonic conditions. The flow angularity and Mach number must be known at multiple locations on any test article interface plane for measurement data at these locations to be valid. To determine this prerequisite information, flight data will be gathered in the Rake Airflow Gauge Experiment using a custom-designed flowfield rake to probe the airflow underneath the F-15B at the desired flight conditions. This paper addresses the design considerations of the rake and probe assembly, including the loads and stress analysis using analytical methods, computational fluid dynamics, and finite element analysis. It also details the flow calibration procedure, including the completed wind-tunnel test and posttest data reduction, calibration verification, and preparation for flight-testing.

Optimized acoustic biochip integrated with microfluidics for biomarkers detection in molecular diagnostics.

PubMed

Papadakis, G; Friedt, J M; Eck, M; Rabus, D; Jobst, G; Gizeli, E

2017-09-01

The development of integrated platforms incorporating an acoustic device as the detection element requires addressing simultaneously several challenges of technological and scientific nature. The present work was focused on the design of a microfluidic module, which, combined with a dual or array type Love wave acoustic chip could be applied to biomedical applications and molecular diagnostics. Based on a systematic study we optimized the mechanics of the flow cell attachment and the sealing material so that fluidic interfacing/encapsulation would impose minimal losses to the acoustic wave. We have also investigated combinations of operating frequencies with waveguide materials and thicknesses for maximum sensitivity during the detection of protein and DNA biomarkers. Within our investigations neutravidin was used as a model protein biomarker and unpurified PCR amplified Salmonella DNA as the model genetic target. Our results clearly indicate the need for experimental verification of the optimum engineering and analytical parameters, in order to develop commercially viable systems for integrated analysis. The good reproducibility of the signal together with the ability of the array biochip to detect multiple samples hold promise for the future use of the integrated system in a Lab-on-a-Chip platform for application to molecular diagnostics.

Developing a Multiplexed Quantitative Cross-Linking Mass Spectrometry Platform for Comparative Structural Analysis of Protein Complexes.

PubMed

Yu, Clinton; Huszagh, Alexander; Viner, Rosa; Novitsky, Eric J; Rychnovsky, Scott D; Huang, Lan

2016-10-18

Cross-linking mass spectrometry (XL-MS) represents a recently popularized hybrid methodology for defining protein-protein interactions (PPIs) and analyzing structures of large protein assemblies. In particular, XL-MS strategies have been demonstrated to be effective in elucidating molecular details of PPIs at the peptide resolution, providing a complementary set of structural data that can be utilized to refine existing complex structures or direct de novo modeling of unknown protein structures. To study structural and interaction dynamics of protein complexes, quantitative cross-linking mass spectrometry (QXL-MS) strategies based on isotope-labeled cross-linkers have been developed. Although successful, these approaches are mostly limited to pairwise comparisons. In order to establish a robust workflow enabling comparative analysis of multiple cross-linked samples simultaneously, we have developed a multiplexed QXL-MS strategy, namely, QMIX (Quantitation of Multiplexed, Isobaric-labeled cross (X)-linked peptides) by integrating MS-cleavable cross-linkers with isobaric labeling reagents. This study has established a new analytical platform for quantitative analysis of cross-linked peptides, which can be directly applied for multiplexed comparisons of the conformational dynamics of protein complexes and PPIs at the proteome scale in future studies.

A Semantic Big Data Platform for Integrating Heterogeneous Wearable Data in Healthcare.

PubMed

Mezghani, Emna; Exposito, Ernesto; Drira, Khalil; Da Silveira, Marcos; Pruski, Cédric

2015-12-01

Advances supported by emerging wearable technologies in healthcare promise patients a provision of high quality of care. Wearable computing systems represent one of the most thrust areas used to transform traditional healthcare systems into active systems able to continuously monitor and control the patients' health in order to manage their care at an early stage. However, their proliferation creates challenges related to data management and integration. The diversity and variety of wearable data related to healthcare, their huge volume and their distribution make data processing and analytics more difficult. In this paper, we propose a generic semantic big data architecture based on the "Knowledge as a Service" approach to cope with heterogeneity and scalability challenges. Our main contribution focuses on enriching the NIST Big Data model with semantics in order to smartly understand the collected data, and generate more accurate and valuable information by correlating scattered medical data stemming from multiple wearable devices or/and from other distributed data sources. We have implemented and evaluated a Wearable KaaS platform to smartly manage heterogeneous data coming from wearable devices in order to assist the physicians in supervising the patient health evolution and keep the patient up-to-date about his/her status.

Microfluidic-integrated biosensors: prospects for point-of-care diagnostics.

PubMed

Kumar, Suveen; Kumar, Saurabh; Ali, Md Azahar; Anand, Pinki; Agrawal, Ved Varun; John, Renu; Maji, Sagar; Malhotra, Bansi D

2013-11-01

There is a growing demand to integrate biosensors with microfluidics to provide miniaturized platforms with many favorable properties, such as reduced sample volume, decreased processing time, low cost analysis and low reagent consumption. These microfluidics-integrated biosensors would also have numerous advantages such as laminar flow, minimal handling of hazardous materials, multiple sample detection in parallel, portability and versatility in design. Microfluidics involves the science and technology of manipulation of fluids at the micro- to nano-liter level. It is predicted that combining biosensors with microfluidic chips will yield enhanced analytical capability, and widen the possibilities for applications in clinical diagnostics. The recent developments in microfluidics have helped researchers working in industries and educational institutes to adopt some of these platforms for point-of-care (POC) diagnostics. This review focuses on the latest advancements in the fields of microfluidic biosensing technologies, and on the challenges and possible solutions for translation of this technology for POC diagnostic applications. We also discuss the fabrication techniques required for developing microfluidic-integrated biosensors, recently reported biomarkers, and the prospects of POC diagnostics in the medical industry. Copyright © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Using Presentation Software to Flip an Undergraduate Analytical Chemistry Course

ERIC Educational Resources Information Center

Fitzgerald, Neil; Li, Luisa

2015-01-01

An undergraduate analytical chemistry course has been adapted to a flipped course format. Course content was provided by video clips, text, graphics, audio, and simple animations organized as concept maps using the cloud-based presentation platform, Prezi. The advantages of using Prezi to present course content in a flipped course format are…

VAP/VAT: video analytics platform and test bed for testing and deploying video analytics

NASA Astrophysics Data System (ADS)

Gorodnichy, Dmitry O.; Dubrofsky, Elan

2010-04-01

Deploying Video Analytics in operational environments is extremely challenging. This paper presents a methodological approach developed by the Video Surveillance and Biometrics Section (VSB) of the Science and Engineering Directorate (S&E) of the Canada Border Services Agency (CBSA) to resolve these problems. A three-phase approach to enable VA deployment within an operational agency is presented and the Video Analytics Platform and Testbed (VAP/VAT) developed by the VSB section is introduced. In addition to allowing the integration of third party and in-house built VA codes into an existing video surveillance infrastructure, VAP/VAT also allows the agency to conduct an unbiased performance evaluation of the cameras and VA software available on the market. VAP/VAT consists of two components: EventCapture, which serves to Automatically detect a "Visual Event", and EventBrowser, which serves to Display & Peruse of "Visual Details" captured at the "Visual Event". To deal with Open architecture as well as with Closed architecture cameras, two video-feed capture mechanisms have been developed within the EventCapture component: IPCamCapture and ScreenCapture.

An Overview on the Importance of Combining Complementary Analytical Platforms in Metabolomic Research.

PubMed

Gonzalez-Dominguez, Alvaro; Duran-Guerrero, Enrique; Fernandez-Recamales, Angeles; Lechuga-Sancho, Alfonso Maria; Sayago, Ana; Schwarz, Monica; Segundo, Carmen; Gonzalez-Dominguez, Raul

2017-01-01

The analytical bias introduced by most of the commonly used techniques in metabolomics considerably hinders the simultaneous detection of all metabolites present in complex biological samples. In order to solve this limitation, the combination of complementary approaches is emerging in recent years as the most suitable strategy in order to maximize metabolite coverage. This review article presents a general overview of the most important analytical techniques usually employed in metabolomics: nuclear magnetic resonance, mass spectrometry and hybrid approaches. Furthermore, we emphasize the potential of integrating various tools in the form of metabolomic multi-platforms in order to get a deeper metabolome characterization, for which a revision of the existing literature in this field is provided. This review is not intended to be exhaustive but, rather, to give a practical and concise guide to readers not familiar with analytical chemistry on the considerations to account for the proper selection of the technique to be used in a metabolomic experiment in biomedical research. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Application of next generation sequencing toward sensitive detection of enteric viruses isolated from celery samples as an example of produce.

PubMed

Yang, Zhihui; Mammel, Mark; Papafragkou, Efstathia; Hida, Kaoru; Elkins, Christopher A; Kulka, Michael

2017-11-16

Next generation sequencing (NGS) holds promise as a single application for both detection and sequence identification of foodborne viruses; however, technical challenges remain due to anticipated low quantities of virus in contaminated food. In this study, with a focus on data analysis using several bioinformatics tools, we applied NGS toward amplification-independent detection and identification of norovirus at low copy (<10 3 copies) or within multiple strains from produce. Celery samples were inoculated with human norovirus (stool suspension) either as a single norovirus strain, a mixture of strains (GII.4 and GII.6), or a mixture of different species (hepatitis A virus and norovirus). Viral RNA isolation and recovery was confirmed by RT-qPCR, and optimized for library generation and sequencing without amplification using the Illumina MiSeq platform. Extracts containing either a single virus or a two-virus mixture were analyzed using two different analytic approaches to achieve virus detection and identification. First an overall assessment of viral genome coverage for samples varying in copy numbers (1.1×10 3 to 1.7×10 7 ) and genomic content (single or multiple strains in various ratios) was completed by reference-guided mapping. Not unexpectedly, this targeted approach to identification was successful in correctly mapping reads, thus identifying each virus contained in the inoculums even at low copy (estimated at 12 copies). For the second (metagenomic) approach, samples were treated as "unknowns" for data analyses using (i) a sequence-based alignment with a local database, (ii) an "in-house" k-mer tool, (iii) a commercially available metagenomics bioinformatic analysis platform cosmosID, and (iv) an open-source program Kraken. Of the four metagenomics tools applied in this study, only the local database alignment and in-house k-mer tool were successful in detecting norovirus (as well as HAV) at low copy (down to <10 3 copies) and within a mixture of virus strains or species. The results of this investigation provide support for continued investigation into the development and integration of these analytical tools for identification and detection of foodborne viruses. Published by Elsevier B.V.

NASA Space Biology Plant Research for 2010-2020

NASA Technical Reports Server (NTRS)

Levine, H. G.; Tomko, D. L.; Porterfield, D. M.

2012-01-01

The U.S. National Research Council (NRC) recently published "Recapturing a Future for Space Exploration: Life and Physical Sciences Research for a New Era" (http://www.nap.edu/catalog.php?record id=13048), and NASA completed a Space Biology Science Plan to develop a strategy for implementing its recommendations ( http://www.nasa.gov/exploration/library/esmd documents.html). The most important recommendations of the NRC report on plant biology in space were that NASA should: (1) investigate the roles of microbial-plant systems in long-term bioregenerative life support systems, and (2) establish a robust spaceflight program of research analyzing plant growth and physiological responses to the multiple stimuli encountered in spaceflight environments. These efforts should take advantage of recently emerged analytical technologies (genomics, transcriptomics, proteomics, metabolomics) and apply modern cellular and molecular approaches in the development of a vigorous flight-based and ground-based research program. This talk will describe NASA's strategy and plans for implementing these NRC Plant Space Biology recommendations. New research capabilities for Plant Biology, optimized by providing state-of-the-art automated technology and analytical techniques to maximize scientific return, will be described. Flight experiments will use the most appropriate platform to achieve science results (e.g., ISS, free flyers, sub-orbital flights) and NASA will work closely with its international partners and other U.S. agencies to achieve its objectives. One of NASA's highest priorities in Space Biology is the development research capabilities for use on the International Space Station and other flight platforms for studying multiple generations of large plants. NASA will issue recurring NASA Research Announcements (NRAs) that include a rapid turn-around model to more fully engage the biology community in designing experiments to respond to the NRC recommendations. In doing so, NASA's Space Biology research will optimize ISS research utilization, develop and demonstrate technology and hardware that will enable new science, and contribute to the base of fundamental knowledge that will facilitate development of new tools for human space exploration and Earth applications. By taking these steps, NASA will energize the Space Biology user community and advance our knowledge of the effect of the space flight environment on living systems.

Embedded-Based Graphics Processing Unit Cluster Platform for Multiple Sequence Alignments

PubMed Central

Wei, Jyh-Da; Cheng, Hui-Jun; Lin, Chun-Yuan; Ye, Jin; Yeh, Kuan-Yu

2017-01-01

High-end graphics processing units (GPUs), such as NVIDIA Tesla/Fermi/Kepler series cards with thousands of cores per chip, are widely applied to high-performance computing fields in a decade. These desktop GPU cards should be installed in personal computers/servers with desktop CPUs, and the cost and power consumption of constructing a GPU cluster platform are very high. In recent years, NVIDIA releases an embedded board, called Jetson Tegra K1 (TK1), which contains 4 ARM Cortex-A15 CPUs and 192 Compute Unified Device Architecture cores (belong to Kepler GPUs). Jetson Tegra K1 has several advantages, such as the low cost, low power consumption, and high applicability, and it has been applied into several specific applications. In our previous work, a bioinformatics platform with a single TK1 (STK platform) was constructed, and this previous work is also used to prove that the Web and mobile services can be implemented in the STK platform with a good cost-performance ratio by comparing a STK platform with the desktop CPU and GPU. In this work, an embedded-based GPU cluster platform will be constructed with multiple TK1s (MTK platform). Complex system installation and setup are necessary procedures at first. Then, 2 job assignment modes are designed for the MTK platform to provide services for users. Finally, ClustalW v2.0.11 and ClustalWtk will be ported to the MTK platform. The experimental results showed that the speedup ratios achieved 5.5 and 4.8 times for ClustalW v2.0.11 and ClustalWtk, respectively, by comparing 6 TK1s with a single TK1. The MTK platform is proven to be useful for multiple sequence alignments. PMID:28835734

Embedded-Based Graphics Processing Unit Cluster Platform for Multiple Sequence Alignments.

PubMed

Wei, Jyh-Da; Cheng, Hui-Jun; Lin, Chun-Yuan; Ye, Jin; Yeh, Kuan-Yu

2017-01-01

High-end graphics processing units (GPUs), such as NVIDIA Tesla/Fermi/Kepler series cards with thousands of cores per chip, are widely applied to high-performance computing fields in a decade. These desktop GPU cards should be installed in personal computers/servers with desktop CPUs, and the cost and power consumption of constructing a GPU cluster platform are very high. In recent years, NVIDIA releases an embedded board, called Jetson Tegra K1 (TK1), which contains 4 ARM Cortex-A15 CPUs and 192 Compute Unified Device Architecture cores (belong to Kepler GPUs). Jetson Tegra K1 has several advantages, such as the low cost, low power consumption, and high applicability, and it has been applied into several specific applications. In our previous work, a bioinformatics platform with a single TK1 (STK platform) was constructed, and this previous work is also used to prove that the Web and mobile services can be implemented in the STK platform with a good cost-performance ratio by comparing a STK platform with the desktop CPU and GPU. In this work, an embedded-based GPU cluster platform will be constructed with multiple TK1s (MTK platform). Complex system installation and setup are necessary procedures at first. Then, 2 job assignment modes are designed for the MTK platform to provide services for users. Finally, ClustalW v2.0.11 and ClustalWtk will be ported to the MTK platform. The experimental results showed that the speedup ratios achieved 5.5 and 4.8 times for ClustalW v2.0.11 and ClustalWtk, respectively, by comparing 6 TK1s with a single TK1. The MTK platform is proven to be useful for multiple sequence alignments.

Application of DNA Machineries for the Barcode Patterned Detection of Genes or Proteins.

PubMed

Zhou, Zhixin; Luo, Guofeng; Wulf, Verena; Willner, Itamar

2018-06-05

The study introduces an analytical platform for the detection of genes or aptamer-ligand complexes by nucleic acid barcode patterns generated by DNA machineries. The DNA machineries consist of nucleic acid scaffolds that include specific recognition sites for the different genes or aptamer-ligand analytes. The binding of the analytes to the scaffolds initiate, in the presence of the nucleotide mixture, a cyclic polymerization/nicking machinery that yields displaced strands of variable lengths. The electrophoretic separation of the resulting strands provides barcode patterns for the specific detection of the different analytes. Mixtures of DNA machineries that yield, upon sensing of different genes (or aptamer ligands), one-, two-, or three-band barcode patterns are described. The combination of nucleic acid scaffolds acting, in the presence of polymerase/nicking enzyme and nucleotide mixture, as DNA machineries, that generate multiband barcode patterns provide an analytical platform for the detection of an individual gene out of many possible genes. The diversity of genes (or other analytes) that can be analyzed by the DNA machineries and the barcode patterned imaging is given by the Pascal's triangle. As a proof-of-concept, the detection of one of six genes, that is, TP53, Werner syndrome, Tay-Sachs normal gene, BRCA1, Tay-Sachs mutant gene, and cystic fibrosis disorder gene by six two-band barcode patterns is demonstrated. The advantages and limitations of the detection of analytes by polymerase/nicking DNA machineries that yield barcode patterns as imaging readout signals are discussed.

Design of e-Science platform for biomedical imaging research cross multiple academic institutions and hospitals

NASA Astrophysics Data System (ADS)

Zhang, Jianguo; Zhang, Kai; Yang, Yuanyuan; Ling, Tonghui; Wang, Tusheng; Wang, Mingqing; Hu, Haibo; Xu, Xuemin

2012-02-01

More and more image informatics researchers and engineers are considering to re-construct imaging and informatics infrastructure or to build new framework to enable multiple disciplines of medical researchers, clinical physicians and biomedical engineers working together in a secured, efficient, and transparent cooperative environment. In this presentation, we show an outline and our preliminary design work of building an e-Science platform for biomedical imaging and informatics research and application in Shanghai. We will present our consideration and strategy on designing this platform, and preliminary results. We also will discuss some challenges and solutions in building this platform.

Using a digital marketing platform for the promotion of an internet based health encyclopedia in saudi arabia.

PubMed

Al Ateeq, Asma; Al Moamary, Eman; Daghestani, Tahani; Al Muallem, Yahya; Al Dogether, Majed; Alsughayr, Abdulrahman; Altuwaijri, Majid; Househ, Mowafa

2015-01-01

The objective of this paper is to investigate the experiences of using a digital marketing platform to promote the use of an internet based health encyclopedia in Saudi Arabia. Key informant interviews, meeting documentation, and Google Analytics were the data collection sources used in the study. Findings show that using a digital marketing platform led to a significant increase in the number of visitors to the health encyclopedia. The results demonstrate that digital marketing platforms are effective tools to be used for promoting internet based health education interventions. Future work will examine long-term educational impacts and costs in using digital marketing platforms to promote online healthcare sites in Saudi Arabia.

Wireless implantable electronic platform for chronic fluorescent-based biosensors.

PubMed

Valdastri, Pietro; Susilo, Ekawahyu; Förster, Thilo; Strohhöfer, Christof; Menciassi, Arianna; Dario, Paolo

2011-06-01

The development of a long-term wireless implantable biosensor based on fluorescence intensity measurement poses a number of technical challenges, ranging from biocompatibility to sensor stability over time. One of these challenges is the design of a power efficient and miniaturized electronics, enabling the biosensor to move from bench testing to long term validation, up to its final application in human beings. In this spirit, we present a wireless programmable electronic platform for implantable chronic monitoring of fluorescent-based autonomous biosensors. This system is able to achieve extremely low power operation with bidirectional telemetry, based on the IEEE802.15.4-2003 protocol, thus enabling over three-year battery lifetime and wireless networking of multiple sensors. During the performance of single fluorescent-based sensor measurements, the circuit drives a laser diode, for sensor excitation, and acquires the amplified signals from four different photodetectors. In vitro functionality was preliminarily tested for both glucose and calcium monitoring, simply by changing the analyte-binding protein of the biosensor. Electronics performance was assessed in terms of timing, power consumption, tissue exposure to electromagnetic fields, and in vivo wireless connectivity. The final goal of the presented platform is to be integrated in a complete system for blood glucose level monitoring that may be implanted for at least one year under the skin of diabetic patients. Results reported in this paper may be applied to a wide variety of biosensors based on fluorescence intensity measurement.

Facilitating Multiple Intelligences through Multimodal Learning Analytics

ERIC Educational Resources Information Center

Perveen, Ayesha

2018-01-01

This paper develops a theoretical framework for employing learning analytics in online education to trace multiple learning variations of online students by considering their potential of being multiple intelligences based on Howard Gardner's 1983 theory of multiple intelligences. The study first emphasizes the need to facilitate students as…

Autonomous Magnetic Microrobots by Navigating Gates for Multiple Biomolecules Delivery.

PubMed

Hu, Xinghao; Lim, Byeonghwa; Torati, Sri Ramulu; Ding, Junjia; Novosad, Valentine; Im, Mi-Young; Reddy, Venu; Kim, Kunwoo; Jung, Eunjoo; Shawl, Asif Iqbal; Kim, Eunjoo; Kim, CheolGi

2018-05-08

The precise delivery of biofunctionalized matters is of great interest from the fundamental and applied viewpoints. In spite of significant progress achieved during the last decade, a parallel and automated isolation and manipulation of rare analyte, and their simultaneous on-chip separation and trapping, still remain challenging. Here, a universal micromagnet junction for self-navigating gates of microrobotic particles to deliver the biomolecules to specific sites using a remote magnetic field is described. In the proposed concept, the nonmagnetic gap between the lithographically defined donor and acceptor micromagnets creates a crucial energy barrier to restrict particle gating. It is shown that by carefully designing the geometry of the junctions, it becomes possible to deliver multiple protein-functionalized carriers in high resolution, as well as MCF-7 and THP-1 cells from the mixture, with high fidelity and trap them in individual apartments. Integration of such junctions with magnetophoretic circuitry elements could lead to novel platforms without retrieving for the synchronous digital manipulation of particles/biomolecules in microfluidic multiplex arrays for next-generation biochips. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Programmable Bio-Nano-Chip Systems for Serum CA125 Quantification: Towards Ovarian Cancer Diagnostics at the Point-of-Care

PubMed Central

Raamanathan, Archana; Simmons, Glennon W.; Christodoulides, Nicolaos; Floriano, Pierre N.; Furmaga, Wieslaw B.; Redding, Spencer W.; Lu, Karen H.; Bast, Robert C.; McDevitt, John T.

2013-01-01

Point-of-care (POC) implementation of early detection and screening methodologies for ovarian cancer may enable improved survival rates through early intervention. Current laboratory-confined immunoanalyzers have long turnaround times and are often incompatible with multiplexing and POC implementation. Rapid, sensitive and multiplexable POC diagnostic platforms compatible with promising early detection approaches for ovarian cancer are needed. To this end, we report the adaptation of the programmable bio-nano-chip (p-BNC), an integrated, microfluidic, modular (Programmable) platform for CA125 serum quantitation, a biomarker prominently implicated in multi-modal and multi-marker screening approaches. In the p-BNC, CA125 from diseased sera (Bio) is sequestered and assessed with a fluorescence-based sandwich immunoassay, completed in the nano-nets (Nano) of sensitized agarose microbeads localized in individually addressable wells (Chip), housed in a microfluidic module, capable of integrating multiple sample, reagent and biowaste processing and handling steps. Antibody pairs that bind to distinct epitopes on CA125 were screened. To permit efficient biomarker sequestration in a 3-D microfluidic environment, the p-BNC operating variables (incubation times, flow rates and reagent concentrations) were tuned to deliver optimal analytical performance under 45 minutes. With short analysis times, competitive analytical performance (Inter- and intra-assay precision of 1.2% and 1.9% and LODs of 1.0 U/mL) was achieved on this mini-sensor ensemble. Further validation with sera of ovarian cancer patients (n=20) demonstrated excellent correlation (R2 = 0.97) with gold-standard ELISA. Building on the integration capabilities of novel microfluidic systems programmed for ovarian cancer, the rapid, precise and sensitive miniaturized p-BNC system shows strong promise for ovarian cancer diagnostics. PMID:22490510

Programmable bio-nano-chip systems for serum CA125 quantification: toward ovarian cancer diagnostics at the point-of-care.

PubMed

Raamanathan, Archana; Simmons, Glennon W; Christodoulides, Nicolaos; Floriano, Pierre N; Furmaga, Wieslaw B; Redding, Spencer W; Lu, Karen H; Bast, Robert C; McDevitt, John T

2012-05-01

Point-of-care (POC) implementation of early detection and screening methodologies for ovarian cancer may enable improved survival rates through early intervention. Current laboratory-confined immunoanalyzers have long turnaround times and are often incompatible with multiplexing and POC implementation. Rapid, sensitive, and multiplexable POC diagnostic platforms compatible with promising early detection approaches for ovarian cancer are needed. To this end, we report the adaptation of the programmable bio-nano-chip (p-BNC), an integrated, microfluidic, and modular (programmable) platform for CA125 serum quantitation, a biomarker prominently implicated in multimodal and multimarker screening approaches. In the p-BNCs, CA125 from diseased sera (Bio) is sequestered and assessed with a fluorescence-based sandwich immunoassay, completed in the nano-nets (Nano) of sensitized agarose microbeads localized in individually addressable wells (Chip), housed in a microfluidic module, capable of integrating multiple sample, reagent and biowaste processing, and handling steps. Antibody pairs that bind to distinct epitopes on CA125 were screened. To permit efficient biomarker sequestration in a three-dimensional microfluidic environment, the p-BNC operating variables (incubation times, flow rates, and reagent concentrations) were tuned to deliver optimal analytical performance under 45 minutes. With short analysis times, competitive analytical performance (inter- and intra-assay precision of 1.2% and 1.9% and limit of detection of 1.0 U/mL) was achieved on this minisensor ensemble. Furthermore, validation with sera of patients with ovarian cancer (n = 20) showed excellent correlation (R(2) = 0.97) with gold-standard ELISA. Building on the integration capabilities of novel microfluidic systems programmed for ovarian cancer, the rapid, precise, and sensitive miniaturized p-BNC system shows strong promise for ovarian cancer diagnostics.

Solving the problem of comparing whole bacterial genomes across different sequencing platforms.

PubMed

Kaas, Rolf S; Leekitcharoenphon, Pimlapas; Aarestrup, Frank M; Lund, Ole

2014-01-01

Whole genome sequencing (WGS) shows great potential for real-time monitoring and identification of infectious disease outbreaks. However, rapid and reliable comparison of data generated in multiple laboratories and using multiple technologies is essential. So far studies have focused on using one technology because each technology has a systematic bias making integration of data generated from different platforms difficult. We developed two different procedures for identifying variable sites and inferring phylogenies in WGS data across multiple platforms. The methods were evaluated on three bacterial data sets and sequenced on three different platforms (Illumina, 454, Ion Torrent). We show that the methods are able to overcome the systematic biases caused by the sequencers and infer the expected phylogenies. It is concluded that the cause of the success of these new procedures is due to a validation of all informative sites that are included in the analysis. The procedures are available as web tools.

e-Science platform for translational biomedical imaging research: running, statistics, and analysis

NASA Astrophysics Data System (ADS)

Wang, Tusheng; Yang, Yuanyuan; Zhang, Kai; Wang, Mingqing; Zhao, Jun; Xu, Lisa; Zhang, Jianguo

2015-03-01

In order to enable multiple disciplines of medical researchers, clinical physicians and biomedical engineers working together in a secured, efficient, and transparent cooperative environment, we had designed an e-Science platform for biomedical imaging research and application cross multiple academic institutions and hospitals in Shanghai and presented this work in SPIE Medical Imaging conference held in San Diego in 2012. In past the two-years, we implemented a biomedical image chain including communication, storage, cooperation and computing based on this e-Science platform. In this presentation, we presented the operating status of this system in supporting biomedical imaging research, analyzed and discussed results of this system in supporting multi-disciplines collaboration cross-multiple institutions.

iSeq: Web-Based RNA-seq Data Analysis and Visualization.

PubMed

Zhang, Chao; Fan, Caoqi; Gan, Jingbo; Zhu, Ping; Kong, Lei; Li, Cheng

2018-01-01

Transcriptome sequencing (RNA-seq) is becoming a standard experimental methodology for genome-wide characterization and quantification of transcripts at single base-pair resolution. However, downstream analysis of massive amount of sequencing data can be prohibitively technical for wet-lab researchers. A functionally integrated and user-friendly platform is required to meet this demand. Here, we present iSeq, an R-based Web server, for RNA-seq data analysis and visualization. iSeq is a streamlined Web-based R application under the Shiny framework, featuring a simple user interface and multiple data analysis modules. Users without programming and statistical skills can analyze their RNA-seq data and construct publication-level graphs through a standardized yet customizable analytical pipeline. iSeq is accessible via Web browsers on any operating system at http://iseq.cbi.pku.edu.cn .

Mass spectrometric directed system for the continuous-flow synthesis and purification of diphenhydramine.

PubMed

Loren, Bradley P; Wleklinski, Michael; Koswara, Andy; Yammine, Kathryn; Hu, Yanyang; Nagy, Zoltan K; Thompson, David H; Cooks, R Graham

2017-06-01

A highly integrated approach to the development of a process for the continuous synthesis and purification of diphenhydramine is reported. Mass spectrometry (MS) is utilized throughout the system for on-line reaction monitoring, off-line yield quantitation, and as a reaction screening module that exploits reaction acceleration in charged microdroplets for high throughput route screening. This effort has enabled the discovery and optimization of multiple routes to diphenhydramine in glass microreactors using MS as a process analytical tool (PAT). The ability to rapidly screen conditions in charged microdroplets was used to guide optimization of the process in a microfluidic reactor. A quantitative MS method was developed and used to measure the reaction kinetics. Integration of the continuous-flow reactor/on-line MS methodology with a miniaturized crystallization platform for continuous reaction monitoring and controlled crystallization of diphenhydramine was also achieved. Our findings suggest a robust approach for the continuous manufacture of pharmaceutical drug products, exemplified in the particular case of diphenhydramine, and optimized for efficiency and crystal size, and guided by real-time analytics to produce the agent in a form that is readily adapted to continuous synthesis.

Controlled positioning of analytes and cells on a plasmonic platform for glycan sensing using surface enhanced Raman spectroscopy.

PubMed

Tabatabaei, Mohammadali; Wallace, Gregory Q; Caetano, Fabiana A; Gillies, Elizabeth R; Ferguson, Stephen S G; Lagugné-Labarthet, François

2016-01-01

The rise of molecular plasmonics and its application to ultrasensitive spectroscopic measurements has been enabled by the rational design and fabrication of a variety of metallic nanostructures. Advanced nano and microfabrication methods are key to the development of such structures, allowing one to tailor optical fields at the sub-wavelength scale, thereby optimizing excitation conditions for ultrasensitive detection. In this work, the control of both analyte and cell positioning on a plasmonic platform is enabled using nanofabrication methods involving patterning of fluorocarbon (FC) polymer (C 4 F 8 ) thin films on a plasmonic platform fabricated by nanosphere lithography (NSL). This provides the possibility to probe biomolecules of interest in the vicinity of cells using plasmon-mediated surface enhanced spectroscopies. In this context, we demonstrate the surface enhanced biosensing of glycan expression in different cell lines by surface enhanced Raman spectroscopy (SERS) on these plasmonic platforms functionalized with 4-mercaptophenylboronic acid (4-MPBA) as the Raman reporter. These cell lines include human embryonic kidney (HEK 293), C2C12 mouse myoblasts, and HeLa (Henrietta Lacks) cervical cancer cells. A distinct glycan expression is observed for cancer cells compared to other cell lines by confocal SERS mapping. This suggests the potential application of these versatile SERS platforms for differentiating cancerous from non-cancerous cells.

LIBS-LIF-Raman: a new tool for the future E-RIHS

NASA Astrophysics Data System (ADS)

Detalle, Vincent; Bai, Xueshi; Bourguignon, Elsa; Menu, Michel; Pallot-Frossard, Isabelle

2017-07-01

France is one of the countries involved in the future E-RIHS - European Research Infrastructure for Heritage Science. The research infrastructure dedicated to the study of materials of cultural and natural heritage will provide transnational access to state-of-the-art technologies (synchrotron, ion beams, lasers, portable methods, etc.) and scientific archives. E-RIHS addresses the experimental problems of knowledge and conservation of heritage materials (collections of art and natural museums, monuments, archaeological sites, archives, libraries, etc.). The cultural artefacts are characterized by complementary methods at multi-scales. The variety and the hybrid are specific of these artefacts and induce complex problems that are not expected in traditional Natural Science: paints, ceramics and glasses, metals, palaeontological specimens, lithic materials, graphic documents, etc. E-RIHS develops in that purpose transnational access to distributed platforms in many European countries. Five complementary accesses are in this way available: FIXLAB (access to fixed platforms for synchrotron, neutrons, ion beams, lasers, etc.), MOLAB (access to mobile examination and analytical methods to study the works in situ), ARCHLAB (access to scientific archives kept in the cultural institutions), DIGILAB (access to a digital infrastructure for the processing of quantitative data, implementing a policy on (re)use of data, choice of data formats, etc.) and finally EXPERTLAB (panels of experts for the implementation of collaborative and multidisciplinary projects for the study, the analysis and the conservation of heritage works).Thus E-RIHS is specifically involved in complex studies for the development of advanced high-resolution analytical and imaging tools. The privileged field of intervention of the infrastructure is that of the study of large corpora, collections and architectural ensembles. Based on previous I3 European program, and especially IPERION-CH program that support the creation of new mobile instrumentation, the French institutions are involved in the development of LIBS/LIF/RAMAN portable instrumentation. After a presentation of the challenge and the multiple advantages in building the European Infrastructure and of the French E-RIHS hub, the major interests of associating the three lasers based on analytical methods for a more global and precise characterization of the heritage objects taking into account their precious characters and their specific constraints. Lastly some preliminary results will be presented in order to give a first idea of the power of this analytical tool.

Multiple Theoretical Lenses as an Analytical Strategy in Researching Group Discussions

ERIC Educational Resources Information Center

Berge, Maria; Ingerman, Åke

2017-01-01

Background: In science education today, there is an emerging focus on what is happening in situ, making use of an array of analytical traditions. Common practice is to use one specific analytical framing within a research project, but there are projects that make use of multiple analytical framings to further the understanding of the same data,…

Multiple Intelligences: The Most Effective Platform for Global 21st Century Educational and Instructional Methodologies

ERIC Educational Resources Information Center

McFarlane, Donovan A.

2011-01-01

This paper examines the theory of Multiple Intelligences (MI) as the most viable and effective platform for 21st century educational and instructional methodologies based on the understanding of the value of diversity in today's classrooms and educational institutions, the unique qualities and characteristics of individual learners, the…

A multicolor panel of TALE-KRAB based transcriptional repressor vectors enabling knockdown of multiple gene targets

PubMed Central

Zhang, Zhonghui; Wu, Elise; Qian, Zhijian; Wu, Wen-Shu

2014-01-01

Stable and efficient knockdown of multiple gene targets is highly desirable for dissection of molecular pathways. Because it allows sequence-specific DNA binding, transcription activator-like effector (TALE) offers a new genetic perturbation technique that allows for gene-specific repression. Here, we constructed a multicolor lentiviral TALE-Kruppel-associated box (KRAB) expression vector platform that enables knockdown of multiple gene targets. This platform is fully compatible with the Golden Gate TALEN and TAL Effector Kit 2.0, a widely used and efficient method for TALE assembly. We showed that this multicolor TALE-KRAB vector system when combined together with bone marrow transplantation could quickly knock down c-kit and PU.1 genes in hematopoietic stem and progenitor cells of recipient mice. Furthermore, our data demonstrated that this platform simultaneously knocked down both c-Kit and PU.1 genes in the same primary cell populations. Together, our results suggest that this multicolor TALE-KRAB vector platform is a promising and versatile tool for knockdown of multiple gene targets and could greatly facilitate dissection of molecular pathways. PMID:25475013

A multicolor panel of TALE-KRAB based transcriptional repressor vectors enabling knockdown of multiple gene targets.

PubMed

Zhang, Zhonghui; Wu, Elise; Qian, Zhijian; Wu, Wen-Shu

2014-12-05

Stable and efficient knockdown of multiple gene targets is highly desirable for dissection of molecular pathways. Because it allows sequence-specific DNA binding, transcription activator-like effector (TALE) offers a new genetic perturbation technique that allows for gene-specific repression. Here, we constructed a multicolor lentiviral TALE-Kruppel-associated box (KRAB) expression vector platform that enables knockdown of multiple gene targets. This platform is fully compatible with the Golden Gate TALEN and TAL Effector Kit 2.0, a widely used and efficient method for TALE assembly. We showed that this multicolor TALE-KRAB vector system when combined together with bone marrow transplantation could quickly knock down c-kit and PU.1 genes in hematopoietic stem and progenitor cells of recipient mice. Furthermore, our data demonstrated that this platform simultaneously knocked down both c-Kit and PU.1 genes in the same primary cell populations. Together, our results suggest that this multicolor TALE-KRAB vector platform is a promising and versatile tool for knockdown of multiple gene targets and could greatly facilitate dissection of molecular pathways.

General Mission Analysis Tool (GMAT) Acceptance Test Plan [Draft

NASA Technical Reports Server (NTRS)

Dove, Edwin; Hughes, Steve

2007-01-01

The information presented in this Acceptance Test Plan document shows the current status of the General Mission Analysis Tool (GMAT). GMAT is a software system developed by NASA Goddard Space Flight Center (GSFC) in collaboration with the private sector. The GMAT development team continuously performs acceptance tests in order to verify that the software continues to operate properly after updates are made. The GMAT Development team consists of NASA/GSFC Code 583 software developers, NASA/GSFC Code 595 analysts, and contractors of varying professions. GMAT was developed to provide a development approach that maintains involvement from the private sector and academia, encourages collaborative funding from multiple government agencies and the private sector, and promotes the transfer of technology from government funded research to the private sector. GMAT contains many capabilities, such as integrated formation flying modeling and MATLAB compatibility. The propagation capabilities in GMAT allow for fully coupled dynamics modeling of multiple spacecraft, in any flight regime. Other capabilities in GMAT inclucle: user definable coordinate systems, 3-D graphics in any coordinate system GMAT can calculate, 2-D plots, branch commands, solvers, optimizers, GMAT functions, planetary ephemeris sources including DE405, DE200, SLP and analytic models, script events, impulsive and finite maneuver models, and many more. GMAT runs on Windows, Mac, and Linux platforms. Both the Graphical User Interface (GUI) and the GMAT engine were built and tested on all of the mentioned platforms. GMAT was designed for intuitive use from both the GUI and with an importable script language similar to that of MATLAB.

An intelligent monitoring and management system for cross-enterprise biomedical data sharing platform

NASA Astrophysics Data System (ADS)

Wang, Tusheng; Yang, Yuanyuan; Zhang, Jianguo

2013-03-01

In order to enable multiple disciplines of medical researchers, clinical physicians and biomedical engineers working together in a secured, efficient, and transparent cooperative environment, we had designed an e-Science platform for biomedical imaging research and application cross multiple academic institutions and hospitals in Shanghai by using grid-based or cloud-based distributed architecture and presented this work in SPIE Medical Imaging conference held in San Diego in 2012. However, when the platform integrates more and more nodes over different networks, the first challenge is that how to monitor and maintain all the hosts and services operating cross multiple academic institutions and hospitals in the e-Science platform, such as DICOM and Web based image communication services, messaging services and XDS ITI transaction services. In this presentation, we presented a system design and implementation of intelligent monitoring and management which can collect system resource status of every node in real time, alert when node or service failure occurs, and can finally improve the robustness, reliability and service continuity of this e-Science platform.

Bioanalytical qualification of clinical biomarker assays in plasma using a novel multi-analyte Simple Plex™ platform.

PubMed

Gupta, Vinita; Davancaze, Teresa; Good, Jeremy; Kalia, Navdeep; Anderson, Michael; Wallin, Jeffrey J; Brady, Ann; Song, An; Xu, Wenfeng

2016-12-01

Immune-checkpoint inhibitors are presumed to break down the tolerogenic state of immune cells by activating T-lymphocytes that release cytokines and enhance effector cell function for elimination of tumors. Measurement of cytokines is being pursued for better understanding of the mechanism of action of immune-checkpoint inhibitors, as well as to identify potential predictive biomarkers. In this study, we show bioanalytical qualification of cytokine assays in plasma on a novel multi-analyte immunoassay platform, Simple Plex ™ . The qualified assays exhibited excellent sensitivity as evidenced by measurement of all samples within the quantifiable range. The accuracy and precision were 80-120% and 10%, respectively. The qualified assays will be useful in assessing mechanism of action cancer immunotherapies.

LipidQC: Method Validation Tool for Visual Comparison to SRM 1950 Using NIST Interlaboratory Comparison Exercise Lipid Consensus Mean Estimate Values.

PubMed

Ulmer, Candice Z; Ragland, Jared M; Koelmel, Jeremy P; Heckert, Alan; Jones, Christina M; Garrett, Timothy J; Yost, Richard A; Bowden, John A

2017-12-19

As advances in analytical separation techniques, mass spectrometry instrumentation, and data processing platforms continue to spur growth in the lipidomics field, more structurally unique lipid species are detected and annotated. The lipidomics community is in need of benchmark reference values to assess the validity of various lipidomics workflows in providing accurate quantitative measurements across the diverse lipidome. LipidQC addresses the harmonization challenge in lipid quantitation by providing a semiautomated process, independent of analytical platform, for visual comparison of experimental results of National Institute of Standards and Technology Standard Reference Material (SRM) 1950, "Metabolites in Frozen Human Plasma", against benchmark consensus mean concentrations derived from the NIST Lipidomics Interlaboratory Comparison Exercise.

A wireless modular multi-modal multi-node patch platform for robust biosignal monitoring.

PubMed

Pantelopoulos, Alexandros; Saldivar, Enrique; Roham, Masoud

2011-01-01

In this paper a wireless modular, multi-modal, multi-node patch platform is described. The platform comprises low-cost semi-disposable patch design aiming at unobtrusive ambulatory monitoring of multiple physiological parameters. Owing to its modular design it can be interfaced with various low-power RF communication and data storage technologies, while the data fusion of multi-modal and multi-node features facilitates measurement of several biosignals from multiple on-body locations for robust feature extraction. Preliminary results of the patch platform are presented which illustrate the capability to extract respiration rate from three different independent metrics, which combined together can give a more robust estimate of the actual respiratory rate.

Pharmacokinetics-on-a-Chip Using Label-Free SERS Technique for Programmable Dual-Drug Analysis.

PubMed

Fei, Jiayuan; Wu, Lei; Zhang, Yizhi; Zong, Shenfei; Wang, Zhuyuan; Cui, Yiping

2017-06-23

Synergistic effects of dual or multiple drugs have attracted great attention in medical fields, especially in cancer therapies. We provide a programmable microfluidic platform for pharmacokinetic detection of multiple drugs in multiple cells. The well-designed microfluidic platform includes two 2 × 3 microarrays of cell chambers, two gradient generators, and several pneumatic valves. Through the combined use of valves and gradient generators, each chamber can be controlled to infuse different kinds of living cells and drugs with specific concentrations as needed. In our experiments, 6-mercaptopurine (6MP) and methimazole (MMI) were chosen as two drug models and their pharmacokinetic parameters in different living cells were monitored through intracellular SERS spectra, which reflected the molecular structure of these drugs. The dynamic change of SERS fingerprints from 6MP and MMI molecules were recorded during drug metabolism in living cells. The results indicated that both 6MP and MMI molecules were diffused into the cells within 4 min and excreted out after 36 h. Moreover, the intracellular distribution of these drugs was monitored through SERS mapping. Thus, our microfluidic platform simultaneously accomplishes the functions to monitor pharmacokinetic action, distribution, and fingerprint of multiple drugs in multiple cells. Owing to its real-time, rapid-speed, high-precision, and programmable capability of multiple-drug and multicell analysis, such a microfluidic platform has great potential in drug design and development.

P³DB 3.0: From plant phosphorylation sites to protein networks.

PubMed

Yao, Qiuming; Ge, Huangyi; Wu, Shangquan; Zhang, Ning; Chen, Wei; Xu, Chunhui; Gao, Jianjiong; Thelen, Jay J; Xu, Dong

2014-01-01

In the past few years, the Plant Protein Phosphorylation Database (P(3)DB, http://p3db.org) has become one of the most significant in vivo data resources for studying plant phosphoproteomics. We have substantially updated P(3)DB with respect to format, new datasets and analytic tools. In the P(3)DB 3.0, there are altogether 47 923 phosphosites in 16 477 phosphoproteins curated across nine plant organisms from 32 studies, which have met our multiple quality standards for acquisition of in vivo phosphorylation site data. Centralized by these phosphorylation data, multiple related data and annotations are provided, including protein-protein interaction (PPI), gene ontology, protein tertiary structures, orthologous sequences, kinase/phosphatase classification and Kinase Client Assay (KiC Assay) data--all of which provides context for the phosphorylation event. In addition, P(3)DB 3.0 incorporates multiple network viewers for the above features, such as PPI network, kinase-substrate network, phosphatase-substrate network, and domain co-occurrence network to help study phosphorylation from a systems point of view. Furthermore, the new P(3)DB reflects a community-based design through which users can share datasets and automate data depository processes for publication purposes. Each of these new features supports the goal of making P(3)DB a comprehensive, systematic and interactive platform for phosphoproteomics research.

moocRP: Enabling Open Learning Analytics with an Open Source Platform for Data Distribution, Analysis, and Visualization

ERIC Educational Resources Information Center

Pardos, Zachary A.; Whyte, Anthony; Kao, Kevin

2016-01-01

In this paper, we address issues of transparency, modularity, and privacy with the introduction of an open source, web-based data repository and analysis tool tailored to the Massive Open Online Course community. The tool integrates data request/authorization and distribution workflow features as well as provides a simple analytics module upload…

Simultaneous multielement atomic absorption spectrometry with graphite furnace atomization

NASA Astrophysics Data System (ADS)

Harnly, James M.; Miller-Ihli, Nancy J.; O'Haver, Thomas C.

The extended analytical range capability of a simultaneous multielement atomic absorption continuum source spectrometer (SIMAAC) was tested for furnace atomization with respect to the signal measurement mode (peak height and area), the atomization mode (from the wall or from a platform), and the temperature program mode (stepped or ramped atomization). These parameters were evaluated with respect to the shapes of the analytical curves, the detection limits, carry-over contamination and accuracy. Peak area measurements gave more linear calibration curves. Methods for slowing the atomization step heating rate, the use of a ramped temperature program or a platform, produced similar calibration curves and longer linear ranges than atomization with a stepped temperature program. Peak height detection limits were best using stepped atomization from the wall. Peak area detection limits for all atomization modes were similar. Carry-over contamination was worse for peak area than peak height, worse for ramped atomization than stepped atomization, and worse for atomization from a platform than from the wall. Accurate determinations (100 ± 12% for Ca, Cu, Fe, Mn, and Zn in National Bureau of Standards' Standard Reference Materials Bovine Liver 1577 and Rice Flour 1568 were obtained using peak area measurements with ramped atomization from the wall and stepped atomization from a platform. Only stepped atomization from a platform gave accurate recoveries for K. Accurate recoveries, 100 ± 10%, with precisions ranging from 1 to 36 % (standard deviation), were obtained for the determination of Al, Co, Cr, Fe, Mn, Mo, Ni. Pb, V and Zn in Acidified Waters (NBS SRM 1643 and 1643a) using stepped atomization from a platform.

Feasibility of Floating Platform Systems for Wind Turbines: Preprint

DOE Office of Scientific and Technical Information (OSTI.GOV)

Musial, W.; Butterfield, S.; Boone, A.

This paper provides a general technical description of several types of floating platforms for wind turbines. Platform topologies are classified into multiple- or single-turbine floaters and by mooring method. Platforms using catenary mooring systems are contrasted to vertical mooring systems and the advantages and disadvantages are discussed. Specific anchor types are described in detail. A rough cost comparison is performed for two different platform architectures using a generic 5-MW wind turbine. One platform is a Dutch study of a tri-floater platform using a catenary mooring system, and the other is a mono-column tension-leg platform developed at the National Renewable Energymore » Laboratory. Cost estimates showed that single unit production cost is $7.1 M for the Dutch tri-floater, and $6.5 M for the NREL TLP concept. However, value engineering, multiple unit series production, and platform/turbine system optimization can lower the unit platform costs to $4.26 M and $2.88 M, respectively, with significant potential to reduce cost further with system optimization. These foundation costs are within the range necessary to bring the cost of energy down to the DOE target range of $0.05/kWh for large-scale deployment of offshore floating wind turbines.« less

The OrbitOutlook Data Archive

NASA Astrophysics Data System (ADS)

Czajkowski, M.; Shilliday, A.; LoFaso, N.; Dipon, A.; Van Brackle, D.

2016-09-01

In this paper, we describe and depict the Defense Advanced Research Projects Agency (DARPA)'s OrbitOutlook Data Archive (OODA) architecture. OODA is the infrastructure that DARPA's OrbitOutlook program has developed to integrate diverse data from various academic, commercial, government, and amateur space situational awareness (SSA) telescopes. At the heart of the OODA system is its world model - a distributed data store built to quickly query big data quantities of information spread out across multiple processing nodes and data centers. The world model applies a multi-index approach where each index is a distinct view on the data. This allows for analysts and analytics (algorithms) to access information through queries with a variety of terms that may be of interest to them. Our indices include: a structured global-graph view of knowledge, a keyword search of data content, an object-characteristic range search, and a geospatial-temporal orientation of spatially located data. In addition, the world model applies a federated approach by connecting to existing databases and integrating them into one single interface as a "one-stop shopping place" to access SSA information. In addition to the world model, OODA provides a processing platform for various analysts to explore and analytics to execute upon this data. Analytic algorithms can use OODA to take raw data and build information from it. They can store these products back into the world model, allowing analysts to gain situational awareness with this information. Analysts in turn would help decision makers use this knowledge to address a wide range of SSA problems. OODA is designed to make it easy for software developers who build graphical user interfaces (GUIs) and algorithms to quickly get started with working with this data. This is done through a multi-language software development kit that includes multiple application program interfaces (APIs) and a data model with SSA concepts and terms such as: space observation, observable, measurable, metadata, track, space object, catalog, expectation, and maneuver.

Considerations for multiple hypothesis correlation on tactical platforms

NASA Astrophysics Data System (ADS)

Thomas, Alan M.; Turpen, James E.

2013-05-01

Tactical platforms benefit greatly from the fusion of tracks from multiple sources in terms of increased situation awareness. As a necessary precursor to this track fusion, track-to-track association, or correlation, must first be performed. The related measurement-to-track fusion problem has been well studied with multiple hypothesis tracking and multiple frame assignment methods showing the most success. The track-to-track problem differs from this one in that measurements themselves are not available but rather track state update reports from the measuring sensors. Multiple hypothesis, multiple frame correlation systems have previously been considered; however, their practical implementation under the constraints imposed by tactical platforms is daunting. The situation is further exacerbated by the inconvenient nature of reports from legacy sensor systems on bandwidth- limited communications networks. In this paper, consideration is given to the special difficulties encountered when attempting the correlation of tracks from legacy sensors on tactical aircraft. Those difficulties include the following: covariance information from reporting sensors is frequently absent or incomplete; system latencies can create temporal uncertainty in data; and computational processing is severely limited by hardware and architecture. Moreover, consideration is given to practical solutions for dealing with these problems in a multiple hypothesis correlator.

Calponin-Like Chd64 Is Partly Disordered

PubMed Central

Jakób, Michał; Szpotkowski, Kamil; Wojtas, Magdalena; Rymarczyk, Grzegorz; Ożyhar, Andrzej

2014-01-01

20-hydroxyecdysone (20E) and juvenile hormone (JH) signaling pathways interact to regulate insect development. Recently, two proteins, a calponin-like Chd64 and immunophilin FKBP39 have been found to play a pivotal role in the cross-talk between 20E and JH, although the molecular basis of interaction remains unknown. The aim of this work was to identify the structural features that would provide understanding of the role of Chd64 in multiple and dynamic complex that cross-links the signaling pathways. Here, we demonstrate the results of in silico and in vitro analyses of the structural organization of Chd64 from Drosophila melanogaster and its homologue from Tribolium castaneum. Computational analysis predicted the existence of disordered regions on the termini of both proteins, while the central region appeared to be globular, probably corresponding to the calponin homology (CH) domain. In vitro analyses of the hydrodynamic properties of the proteins from analytical size-exclusion chromatography and analytical ultracentrifugation revealed that DmChd64 and TcChd64 had an asymmetrical, elongated shape, which was further confirmed by small angle X-ray scattering (SAXS). The Kratky plot indicated disorderness in both Chd64 proteins, which could possibly be on the protein termini and which would give rise to specific hydrodynamic properties. Disordered tails are often involved in diverse interactions. Therefore, it is highly possible that there are intrinsically disordered regions (IDRs) on both termini of the Chd64 proteins that serve as platforms for multiple interaction with various partners and constitute the foundation for their regulatory function. PMID:24805353

High-flux ionic diodes, ionic transistors and ionic amplifiers based on external ion concentration polarization by an ion exchange membrane: a new scalable ionic circuit platform.

PubMed

Sun, Gongchen; Senapati, Satyajyoti; Chang, Hsueh-Chia

2016-04-07

A microfluidic ion exchange membrane hybrid chip is fabricated using polymer-based, lithography-free methods to achieve ionic diode, transistor and amplifier functionalities with the same four-terminal design. The high ionic flux (>100 μA) feature of the chip can enable a scalable integrated ionic circuit platform for micro-total-analytical systems.

Titanium Dioxide Nanoparticles (TiO₂) Quenching Based Aptasensing Platform: Application to Ochratoxin A Detection.

PubMed

Sharma, Atul; Hayat, Akhtar; Mishra, Rupesh K; Catanante, Gaëlle; Bhand, Sunil; Marty, Jean Louis

2015-09-22

We demonstrate for the first time, the development of titanium dioxide nanoparticles (TiO₂) quenching based aptasensing platform for detection of target molecules. TiO₂ quench the fluorescence of FAM-labeled aptamer (fluorescein labeled aptamer) upon the non-covalent adsorption of fluorescent labeled aptamer on TiO₂ surface. When OTA interacts with the aptamer, it induced aptamer G-quadruplex complex formation, weakens the interaction between FAM-labeled aptamer and TiO₂, resulting in fluorescence recovery. As a proof of concept, an assay was employed for detection of Ochratoxin A (OTA). At optimized experimental condition, the obtained limit of detection (LOD) was 1.5 nM with a good linearity in the range 1.5 nM to 1.0 µM for OTA. The obtained results showed the high selectivity of assay towards OTA without interference to structurally similar analogue Ochratoxin B (OTB). The developed aptamer assay was evaluated for detection of OTA in beer sample and recoveries were recorded in the range from 94.30%-99.20%. Analytical figures of the merits of the developed aptasensing platform confirmed its applicability to real samples analysis. However, this is a generic aptasensing platform and can be extended for detection of other toxins or target analyte.

An architecture for genomics analysis in a clinical setting using Galaxy and Docker

PubMed Central

Digan, W; Countouris, H; Barritault, M; Baudoin, D; Laurent-Puig, P; Blons, H; Burgun, A

2017-01-01

Abstract Next-generation sequencing is used on a daily basis to perform molecular analysis to determine subtypes of disease (e.g., in cancer) and to assist in the selection of the optimal treatment. Clinical bioinformatics handles the manipulation of the data generated by the sequencer, from the generation to the analysis and interpretation. Reproducibility and traceability are crucial issues in a clinical setting. We have designed an approach based on Docker container technology and Galaxy, the popular bioinformatics analysis support open-source software. Our solution simplifies the deployment of a small-size analytical platform and simplifies the process for the clinician. From the technical point of view, the tools embedded in the platform are isolated and versioned through Docker images. Along the Galaxy platform, we also introduce the AnalysisManager, a solution that allows single-click analysis for biologists and leverages standardized bioinformatics application programming interfaces. We added a Shiny/R interactive environment to ease the visualization of the outputs. The platform relies on containers and ensures the data traceability by recording analytical actions and by associating inputs and outputs of the tools to EDAM ontology through ReGaTe. The source code is freely available on Github at https://github.com/CARPEM/GalaxyDocker. PMID:29048555

Real-time imaging of microparticles and living cells with CMOS nanocapacitor arrays

NASA Astrophysics Data System (ADS)

Laborde, C.; Pittino, F.; Verhoeven, H. A.; Lemay, S. G.; Selmi, L.; Jongsma, M. A.; Widdershoven, F. P.

2015-09-01

Platforms that offer massively parallel, label-free biosensing can, in principle, be created by combining all-electrical detection with low-cost integrated circuits. Examples include field-effect transistor arrays, which are used for mapping neuronal signals and sequencing DNA. Despite these successes, however, bioelectronics has so far failed to deliver a broadly applicable biosensing platform. This is due, in part, to the fact that d.c. or low-frequency signals cannot be used to probe beyond the electrical double layer formed by screening salt ions, which means that under physiological conditions the sensing of a target analyte located even a short distance from the sensor (∼1 nm) is severely hampered. Here, we show that high-frequency impedance spectroscopy can be used to detect and image microparticles and living cells under physiological salt conditions. Our assay employs a large-scale, high-density array of nanoelectrodes integrated with CMOS electronics on a single chip and the sensor response depends on the electrical properties of the analyte, allowing impedance-based fingerprinting. With our platform, we image the dynamic attachment and micromotion of BEAS, THP1 and MCF7 cancer cell lines in real time at submicrometre resolution in growth medium, demonstrating the potential of the platform for label/tracer-free high-throughput screening of anti-tumour drug candidates.

An architecture for genomics analysis in a clinical setting using Galaxy and Docker.

PubMed

Digan, W; Countouris, H; Barritault, M; Baudoin, D; Laurent-Puig, P; Blons, H; Burgun, A; Rance, B

2017-11-01

Next-generation sequencing is used on a daily basis to perform molecular analysis to determine subtypes of disease (e.g., in cancer) and to assist in the selection of the optimal treatment. Clinical bioinformatics handles the manipulation of the data generated by the sequencer, from the generation to the analysis and interpretation. Reproducibility and traceability are crucial issues in a clinical setting. We have designed an approach based on Docker container technology and Galaxy, the popular bioinformatics analysis support open-source software. Our solution simplifies the deployment of a small-size analytical platform and simplifies the process for the clinician. From the technical point of view, the tools embedded in the platform are isolated and versioned through Docker images. Along the Galaxy platform, we also introduce the AnalysisManager, a solution that allows single-click analysis for biologists and leverages standardized bioinformatics application programming interfaces. We added a Shiny/R interactive environment to ease the visualization of the outputs. The platform relies on containers and ensures the data traceability by recording analytical actions and by associating inputs and outputs of the tools to EDAM ontology through ReGaTe. The source code is freely available on Github at https://github.com/CARPEM/GalaxyDocker. © The Author 2017. Published by Oxford University Press.

A comparative analysis of high-throughput platforms for validation of a circulating microRNA signature in diabetic retinopathy.

PubMed

Farr, Ryan J; Januszewski, Andrzej S; Joglekar, Mugdha V; Liang, Helena; McAulley, Annie K; Hewitt, Alex W; Thomas, Helen E; Loudovaris, Tom; Kay, Thomas W H; Jenkins, Alicia; Hardikar, Anandwardhan A

2015-06-02

MicroRNAs are now increasingly recognized as biomarkers of disease progression. Several quantitative real-time PCR (qPCR) platforms have been developed to determine the relative levels of microRNAs in biological fluids. We systematically compared the detection of cellular and circulating microRNA using a standard 96-well platform, a high-content microfluidics platform and two ultra-high content platforms. We used extensive analytical tools to compute inter- and intra-run variability and concordance measured using fidelity scoring, coefficient of variation and cluster analysis. We carried out unprejudiced next generation sequencing to identify a microRNA signature for Diabetic Retinopathy (DR) and systematically assessed the validation of this signature on clinical samples using each of the above four qPCR platforms. The results indicate that sensitivity to measure low copy number microRNAs is inversely related to qPCR reaction volume and that the choice of platform for microRNA biomarker validation should be made based on the abundance of miRNAs of interest.

Microfabricated capillary electrophoresis chip and method for simultaneously detecting multiple redox labels

DOEpatents

Mathies, Richard A.; Singhal, Pankaj; Xie, Jin; Glazer, Alexander N.

2002-01-01

This invention relates to a microfabricated capillary electrophoresis chip for detecting multiple redox-active labels simultaneously using a matrix coding scheme and to a method of selectively labeling analytes for simultaneous electrochemical detection of multiple label-analyte conjugates after electrophoretic or chromatographic separation.

Ultramicroelectrode Array Based Sensors: A Promising Analytical Tool for Environmental Monitoring

PubMed Central

Orozco, Jahir; Fernández-Sánchez, César; Jiménez-Jorquera, Cecilia

2010-01-01

The particular analytical performance of ultramicroelectrode arrays (UMEAs) has attracted a high interest by the research community and has led to the development of a variety of electroanalytical applications. UMEA-based approaches have demonstrated to be powerful, simple, rapid and cost-effective analytical tools for environmental analysis compared to available conventional electrodes and standardised analytical techniques. An overview of the fabrication processes of UMEAs, their characterization and applications carried out by the Spanish scientific community is presented. A brief explanation of theoretical aspects that highlight their electrochemical behavior is also given. Finally, the applications of this transducer platform in the environmental field are discussed. PMID:22315551

X-Graphs: Language and Algorithms for Heterogeneous Graph Streams

DTIC Science & Technology

2017-09-01

INTRODUCTION 1 3 METHODS , ASUMPTIONS, AND PROCEDURES 2 Software Abstractions for Graph Analytic Applications 2 High performance Platforms for Graph Processing...data is stored in a distributed file system. 3 METHODS , ASUMPTIONS, AND PROCEDURES Software Abstractions for Graph Analytic Applications To...implementations of novel methods for networks analysis: several methods for detection of overlapping communities, personalized PageRank, node embeddings into a d

A Single Electrochemical Probe Used for Analysis of Multiple Nucleic Acid Sequences

PubMed Central

Mills, Dawn M.; Calvo-Marzal, Percy; Pinzon, Jeffer M.; Armas, Stephanie; Kolpashchikov, Dmitry M.; Chumbimuni-Torres, Karin Y.

2017-01-01

Electrochemical hybridization sensors have been explored extensively for analysis of specific nucleic acids. However, commercialization of the platform is hindered by the need for attachment of separate oligonucleotide probes complementary to a RNA or DNA target to an electrode’s surface. Here we demonstrate that a single probe can be used to analyze several nucleic acid targets with high selectivity and low cost. The universal electrochemical four-way junction (4J)-forming (UE4J) sensor consists of a universal DNA stem-loop (USL) probe attached to the electrode’s surface and two adaptor strands (m and f) which hybridize to the USL probe and the analyte to form a 4J associate. The m adaptor strand was conjugated with a methylene blue redox marker for signal ON sensing and monitored using square wave voltammetry. We demonstrated that a single sensor can be used for detection of several different DNA/RNA sequences and can be regenerated in 30 seconds by a simple water rinse. The UE4J sensor enables a high selectivity by recognition of a single base substitution, even at room temperature. The UE4J sensor opens a venue for a re-useable universal platform that can be adopted at low cost for the analysis of DNA or RNA targets. PMID:29371782

Stewardship and management challenges within a cloud-based open data ecosystem (Invited Paper 211863)

NASA Astrophysics Data System (ADS)

Kearns, E. J.

2017-12-01

NOAA's Big Data Project is conducting an experiment in the collaborative distribution of open government data to non-governmental cloud-based systems. Through Cooperative Research and Development Agreements signed in 2015 between NOAA and Amazon Web Services, Google Cloud Platform, IBM, Microsoft Azure, and the Open Commons Consortium, NOAA is distributing open government data to a wide community of potential users. There are a number of significant advantages related to the use of open data on commercial cloud platforms, but through this experiment NOAA is also discovering significant challenges for those stewarding and maintaining NOAA's data resources in support of users in the wider open data ecosystem. Among the challenges that will be discussed are: the need to provide effective interpretation of the data content to enable their use by data scientists from other expert communities; effective maintenance of Collaborators' open data stores through coordinated publication of new data and new versions of older data; the provenance and verification of open data as authentic NOAA-sourced data across multiple management boundaries and analytical tools; and keeping pace with the accelerating expectations of users with regard to improved quality control, data latency, availability, and discoverability. Suggested strategies to address these challenges will also be described.

FilmArray, an Automated Nested Multiplex PCR System for Multi-Pathogen Detection: Development and Application to Respiratory Tract Infection

PubMed Central

Poritz, Mark A.; Blaschke, Anne J.; Byington, Carrie L.; Meyers, Lindsay; Nilsson, Kody; Jones, David E.; Thatcher, Stephanie A.; Robbins, Thomas; Lingenfelter, Beth; Amiott, Elizabeth; Herbener, Amy; Daly, Judy; Dobrowolski, Steven F.; Teng, David H. -F.; Ririe, Kirk M.

2011-01-01

The ideal clinical diagnostic system should deliver rapid, sensitive, specific and reproducible results while minimizing the requirements for specialized laboratory facilities and skilled technicians. We describe an integrated diagnostic platform, the “FilmArray”, which fully automates the detection and identification of multiple organisms from a single sample in about one hour. An unprocessed biologic/clinical sample is subjected to nucleic acid purification, reverse transcription, a high-order nested multiplex polymerase chain reaction and amplicon melt curve analysis. Biochemical reactions are enclosed in a disposable pouch, minimizing the PCR contamination risk. FilmArray has the potential to detect greater than 100 different nucleic acid targets at one time. These features make the system well-suited for molecular detection of infectious agents. Validation of the FilmArray technology was achieved through development of a panel of assays capable of identifying 21 common viral and bacterial respiratory pathogens. Initial testing of the system using both cultured organisms and clinical nasal aspirates obtained from children demonstrated an analytical and clinical sensitivity and specificity comparable to existing diagnostic platforms. We demonstrate that automated identification of pathogens from their corresponding target amplicon(s) can be accomplished by analysis of the DNA melting curve of the amplicon. PMID:22039434

Big Data Analytics in Medicine and Healthcare.

PubMed

Ristevski, Blagoj; Chen, Ming

2018-05-10

This paper surveys big data with highlighting the big data analytics in medicine and healthcare. Big data characteristics: value, volume, velocity, variety, veracity and variability are described. Big data analytics in medicine and healthcare covers integration and analysis of large amount of complex heterogeneous data such as various - omics data (genomics, epigenomics, transcriptomics, proteomics, metabolomics, interactomics, pharmacogenomics, diseasomics), biomedical data and electronic health records data. We underline the challenging issues about big data privacy and security. Regarding big data characteristics, some directions of using suitable and promising open-source distributed data processing software platform are given.

Matrix Effect Compensation in Small-Molecule Profiling for an LC-TOF Platform Using Multicomponent Postcolumn Infusion.

PubMed

González, Oskar; van Vliet, Michael; Damen, Carola W N; van der Kloet, Frans M; Vreeken, Rob J; Hankemeier, Thomas

2015-06-16

The possible presence of matrix effect is one of the main concerns in liquid chromatography-mass spectrometry (LC-MS)-driven bioanalysis due to its impact on the reliability of the obtained quantitative results. Here we propose an approach to correct for the matrix effect in LC-MS with electrospray ionization using postcolumn infusion of eight internal standards (PCI-IS). We applied this approach to a generic ultraperformance liquid chromatography-time-of-flight (UHPLC-TOF) platform developed for small-molecule profiling with a main focus on drugs. Different urine samples were spiked with 19 drugs with different physicochemical properties and analyzed in order to study matrix effect (in absolute and relative terms). Furthermore, calibration curves for each analyte were constructed and quality control samples at different concentration levels were analyzed to check the applicability of this approach in quantitative analysis. The matrix effect profiles of the PCI-ISs were different: this confirms that the matrix effect is compound-dependent, and therefore the most suitable PCI-IS has to be chosen for each analyte. Chromatograms were reconstructed using analyte and PCI-IS responses, which were used to develop an optimized method which compensates for variation in ionization efficiency. The approach presented here improved the results in terms of matrix effect dramatically. Furthermore, calibration curves of higher quality are obtained, dynamic range is enhanced, and accuracy and precision of QC samples is increased. The use of PCI-ISs is a very promising step toward an analytical platform free of matrix effect, which can make LC-MS analysis even more successful, adding a higher reliability in quantification to its intrinsic high sensitivity and selectivity.

An automated ranking platform for machine learning regression models for meat spoilage prediction using multi-spectral imaging and metabolic profiling.

PubMed

Estelles-Lopez, Lucia; Ropodi, Athina; Pavlidis, Dimitris; Fotopoulou, Jenny; Gkousari, Christina; Peyrodie, Audrey; Panagou, Efstathios; Nychas, George-John; Mohareb, Fady

2017-09-01

Over the past decade, analytical approaches based on vibrational spectroscopy, hyperspectral/multispectral imagining and biomimetic sensors started gaining popularity as rapid and efficient methods for assessing food quality, safety and authentication; as a sensible alternative to the expensive and time-consuming conventional microbiological techniques. Due to the multi-dimensional nature of the data generated from such analyses, the output needs to be coupled with a suitable statistical approach or machine-learning algorithms before the results can be interpreted. Choosing the optimum pattern recognition or machine learning approach for a given analytical platform is often challenging and involves a comparative analysis between various algorithms in order to achieve the best possible prediction accuracy. In this work, "MeatReg", a web-based application is presented, able to automate the procedure of identifying the best machine learning method for comparing data from several analytical techniques, to predict the counts of microorganisms responsible of meat spoilage regardless of the packaging system applied. In particularly up to 7 regression methods were applied and these are ordinary least squares regression, stepwise linear regression, partial least square regression, principal component regression, support vector regression, random forest and k-nearest neighbours. MeatReg" was tested with minced beef samples stored under aerobic and modified atmosphere packaging and analysed with electronic nose, HPLC, FT-IR, GC-MS and Multispectral imaging instrument. Population of total viable count, lactic acid bacteria, pseudomonads, Enterobacteriaceae and B. thermosphacta, were predicted. As a result, recommendations of which analytical platforms are suitable to predict each type of bacteria and which machine learning methods to use in each case were obtained. The developed system is accessible via the link: www.sorfml.com. Copyright © 2017 Elsevier Ltd. All rights reserved.

OpenChrom: a cross-platform open source software for the mass spectrometric analysis of chromatographic data.

PubMed

Wenig, Philip; Odermatt, Juergen

2010-07-30

Today, data evaluation has become a bottleneck in chromatographic science. Analytical instruments equipped with automated samplers yield large amounts of measurement data, which needs to be verified and analyzed. Since nearly every GC/MS instrument vendor offers its own data format and software tools, the consequences are problems with data exchange and a lack of comparability between the analytical results. To challenge this situation a number of either commercial or non-profit software applications have been developed. These applications provide functionalities to import and analyze several data formats but have shortcomings in terms of the transparency of the implemented analytical algorithms and/or are restricted to a specific computer platform. This work describes a native approach to handle chromatographic data files. The approach can be extended in its functionality such as facilities to detect baselines, to detect, integrate and identify peaks and to compare mass spectra, as well as the ability to internationalize the application. Additionally, filters can be applied on the chromatographic data to enhance its quality, for example to remove background and noise. Extended operations like do, undo and redo are supported. OpenChrom is a software application to edit and analyze mass spectrometric chromatographic data. It is extensible in many different ways, depending on the demands of the users or the analytical procedures and algorithms. It offers a customizable graphical user interface. The software is independent of the operating system, due to the fact that the Rich Client Platform is written in Java. OpenChrom is released under the Eclipse Public License 1.0 (EPL). There are no license constraints regarding extensions. They can be published using open source as well as proprietary licenses. OpenChrom is available free of charge at http://www.openchrom.net.

AIE-doped poly(ionic liquid) photonic spheres: a single sphere-based customizable sensing platform for the discrimination of multi-analytes† †Electronic supplementary information (ESI) available: Synthesis and characterization of the AIE luminogen, experimental details, response profiles and results of the multivariate analysis. See DOI: 10.1039/c7sc02409f Click here for additional data file.

PubMed Central

Zhang, Wanlin; Gao, Ning; Cui, Jiecheng; Wang, Chen; Wang, Shiqiang; Zhang, Guanxin; Dong, Xiaobiao

2017-01-01

By simultaneously exploiting the unique properties of ionic liquids and aggregation-induced emission (AIE) luminogens, as well as photonic structures, a novel customizable sensing system for multi-analytes was developed based on a single AIE-doped poly(ionic liquid) photonic sphere. It was found that due to the extraordinary multiple intermolecular interactions involved in the ionic liquid units, one single sphere could differentially interact with broader classes of analytes, thus generating response patterns with remarkable diversity. Moreover, the optical properties of both the AIE luminogen and photonic structure integrated in the poly(ionic liquid) sphere provide multidimensional signal channels for transducing the involved recognition process in a complementary manner and the acquisition of abundant and sufficient sensing information could be easily achieved on only one sphere sensor element. More importantly, the sensing performance of our poly(ionic liquid) photonic sphere is designable and customizable through a simple ion-exchange reaction and target-oriented multi-analyte sensing can be conveniently realized using a selective receptor species, such as counterions, showing great flexibility and extendibility. The power of our single sphere-based customizable sensing system was exemplified by the successful on-demand detection and discrimination of four multi-analyte challenge systems: all 20 natural amino acids, nine important phosphate derivatives, ten metal ions and three pairs of enantiomers. To further demonstrate the potential of our spheres for real-life application, 20 amino acids in human urine and their 26 unprecedented complex mixtures were also discriminated between by the single sphere-based array. PMID:28989662

The Use of Meta-Analytic Statistical Significance Testing

ERIC Educational Resources Information Center

Polanin, Joshua R.; Pigott, Terri D.

2015-01-01

Meta-analysis multiplicity, the concept of conducting multiple tests of statistical significance within one review, is an underdeveloped literature. We address this issue by considering how Type I errors can impact meta-analytic results, suggest how statistical power may be affected through the use of multiplicity corrections, and propose how…

Dynamic Covalent Chemistry within Biphenyl Scaffolds: Reversible Covalent Bonding, Control of Selectivity, and Chirality Sensing with a Single System.

PubMed

Ni, Cailing; Zha, Daijun; Ye, Hebo; Hai, Yu; Zhou, Yuntao; Anslyn, Eric V; You, Lei

2018-01-26

Axial chirality is a prevalent and important phenomenon in chemistry. Herein we report a combination of dynamic covalent chemistry and axial chirality for the development of a versatile platform for the binding and chirality sensing of multiple classes of mononucleophiles. An equilibrium between an open aldehyde and its cyclic hemiaminal within biphenyl derivatives enabled the dynamic incorporation of a broad range of alcohols, thiols, primary amines, and secondary amines with high efficiency. Selectivity toward different classes of nucleophiles was also achieved by regulating the distinct reactivity of the system with external stimuli. Through induced helicity as a result of central-to-axial chirality transfer, the handedness and ee values of chiral monoalcohol and monoamine analytes were reported by circular dichroism. The strategies introduced herein should find application in many contexts, including assembly, sensing, and labeling. © 2018 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Automated phenotyping of permanent crops

NASA Astrophysics Data System (ADS)

McPeek, K. Thomas; Steddom, Karl; Zamudio, Joseph; Pant, Paras; Mullenbach, Tyler

2017-05-01

AGERpoint is defining a new technology space for the growers' industry by introducing novel applications for sensor technology and data analysis to growers of permanent crops. Serving data to a state-of-the-art analytics engine from a cutting edge sensor platform, a new paradigm in precision agriculture is being developed that allows growers to understand the unique needs of each tree, bush or vine in their operation. Autonomous aerial and terrestrial vehicles equipped with multiple varieties of remote sensing technologies give AGERpoint the ability to measure key morphological and spectral features of permanent crops. This work demonstrates how such phenotypic measurements combined with machine learning algorithms can be used to determine the variety of crops (e.g., almond and pecan trees). This phenotypic and varietal information represents the first step in enabling growers with the ability to tailor their management practices to individual plants and maximize their economic productivity.

Comparison of Quantitative Mass Spectrometry Platforms for Monitoring Kinase ATP Probe Uptake in Lung Cancer.

PubMed

Hoffman, Melissa A; Fang, Bin; Haura, Eric B; Rix, Uwe; Koomen, John M

2018-01-05

Recent developments in instrumentation and bioinformatics have led to new quantitative mass spectrometry platforms including LC-MS/MS with data-independent acquisition (DIA) and targeted analysis using parallel reaction monitoring mass spectrometry (LC-PRM), which provide alternatives to well-established methods, such as LC-MS/MS with data-dependent acquisition (DDA) and targeted analysis using multiple reaction monitoring mass spectrometry (LC-MRM). These tools have been used to identify signaling perturbations in lung cancers and other malignancies, supporting the development of effective kinase inhibitors and, more recently, providing insights into therapeutic resistance mechanisms and drug repurposing opportunities. However, detection of kinases in biological matrices can be challenging; therefore, activity-based protein profiling enrichment of ATP-utilizing proteins was selected as a test case for exploring the limits of detection of low-abundance analytes in complex biological samples. To examine the impact of different MS acquisition platforms, quantification of kinase ATP uptake following kinase inhibitor treatment was analyzed by four different methods: LC-MS/MS with DDA and DIA, LC-MRM, and LC-PRM. For discovery data sets, DIA increased the number of identified kinases by 21% and reduced missingness when compared with DDA. In this context, MRM and PRM were most effective at identifying global kinome responses to inhibitor treatment, highlighting the value of a priori target identification and manual evaluation of quantitative proteomics data sets. We compare results for a selected set of desthiobiotinylated peptides from PRM, MRM, and DIA and identify considerations for selecting a quantification method and postprocessing steps that should be used for each data acquisition strategy.

Comparison of single cell sequencing data between two whole genome amplification methods on two sequencing platforms.

PubMed

Chen, DaYang; Zhen, HeFu; Qiu, Yong; Liu, Ping; Zeng, Peng; Xia, Jun; Shi, QianYu; Xie, Lin; Zhu, Zhu; Gao, Ya; Huang, GuoDong; Wang, Jian; Yang, HuanMing; Chen, Fang

2018-03-21

Research based on a strategy of single-cell low-coverage whole genome sequencing (SLWGS) has enabled better reproducibility and accuracy for detection of copy number variations (CNVs). The whole genome amplification (WGA) method and sequencing platform are critical factors for successful SLWGS (<0.1 × coverage). In this study, we compared single cell and multiple cells sequencing data produced by the HiSeq2000 and Ion Proton platforms using two WGA kits and then comprehensively evaluated the GC-bias, reproducibility, uniformity and CNV detection among different experimental combinations. Our analysis demonstrated that the PicoPLEX WGA Kit resulted in higher reproducibility, lower sequencing error frequency but more GC-bias than the GenomePlex Single Cell WGA Kit (WGA4 kit) independent of the cell number on the HiSeq2000 platform. While on the Ion Proton platform, the WGA4 kit (both single cell and multiple cells) had higher uniformity and less GC-bias but lower reproducibility than those of the PicoPLEX WGA Kit. Moreover, on these two sequencing platforms, depending on cell number, the performance of the two WGA kits was different for both sensitivity and specificity on CNV detection. The results can help researchers who plan to use SLWGS on single or multiple cells to select appropriate experimental conditions for their applications.

Integration of Ion Mobility MSE after Fully Automated, Online, High-Resolution Liquid Extraction Surface Analysis Micro-Liquid Chromatography

PubMed Central

2017-01-01

Direct analysis by mass spectrometry (imaging) has become increasingly deployed in preclinical and clinical research due to its rapid and accurate readouts. However, when it comes to biomarker discovery or histopathological diagnostics, more sensitive and in-depth profiling from localized areas is required. We developed a comprehensive, fully automated online platform for high-resolution liquid extraction surface analysis (HR-LESA) followed by micro–liquid chromatography (LC) separation and a data-independent acquisition strategy for untargeted and low abundant analyte identification directly from tissue sections. Applied to tissue sections of rat pituitary, the platform demonstrated improved spatial resolution, allowing sample areas as small as 400 μm to be studied, a major advantage over conventional LESA. The platform integrates an online buffer exchange and washing step for removal of salts and other endogenous contamination that originates from local tissue extraction. Our carry over–free platform showed high reproducibility, with an interextraction variability below 30%. Another strength of the platform is the additional selectivity provided by a postsampling gas-phase ion mobility separation. This allowed distinguishing coeluted isobaric compounds without requiring additional separation time. Furthermore, we identified untargeted and low-abundance analytes, including neuropeptides deriving from the pro-opiomelanocortin precursor protein and localized a specific area of the pituitary gland (i.e., adenohypophysis) known to secrete neuropeptides and other small metabolites related to development, growth, and metabolism. This platform can thus be applied for the in-depth study of small samples of complex tissues with histologic features of ∼400 μm or more, including potential neuropeptide markers involved in many diseases such as neurodegenerative diseases, obesity, bulimia, and anorexia nervosa. PMID:28945354

Optofluidic devices for biomolecule sensing and multiplexing

NASA Astrophysics Data System (ADS)

Ozcelik, Damla

Optofluidics which integrates photonics and microfluidics, has led to highly compact, sensitive and adaptable biomedical sensors. Optofluidic biosensors based on liquid-core anti-resonant reflecting optical waveguides (LC-ARROWs), have proven to be a highly sensitive, portable, and reconfigurable platform for fluorescence spectroscopy and detection of single biomolecules such as proteins, nucleic acids, and virus particles. However, continued improvements in sensitivity remain a major goal as we approach the ultimate limit of detecting individual bio-particles labeled by single or few fluorophores. Additionally, the ability to simultaneously detect and identify multiple biological particles or biomarkers is one of the key requirements for molecular diagnostic tests. The compactness and adaptability of these platforms can further be advanced by introducing tunability, integrating off-chip components, designing reconfigurable and customizable devices, which makes these platforms very good candidates for many different applications. The goal of this thesis was to introduce new elements in these LC-ARROW optofluidics platforms that provide major enhancements in their functionality, making them more sensitive, compact, customizable and multiplexed. First, a novel integrated tunable spectral filter that achieves effective elimination of background noise on the ARROW platform was demonstrated. A unique dual liquid-core design enabled the independent multi-wavelength tuning of the spectral filter by adjusting the refractive index and chemical properties of the liquid. In order to enhance the detection sensitivity of the platform, Y-splitter waveguides were integrated to create multiple excitation spots for each target molecule. A powerful signal processing algorithm was used to analyze the data to improve the signal-to-noise ratio (SNR) of the collected data. Next, the design, optimization and characterization of the Y-splitter waveguides are presented; and single influenza virus detection with an improved SNR was demonstrated using this platform. Finally, multiplexing capacity is introduced to the ARROW detection platform by integrating multi-mode interference (MMI) waveguides. MMI waveguides create wavelength dependent multiple excitation spots at the excitation region, allowing the spectral multiplexed detection of multiple different target molecules based on the excitation pattern, without the need for additional spectral filters. Successful spectral multiplexed detection of three different types of influenza viruses is achieved by using separate wavelengths and combination of wavelengths. This multiplexing capacity is further enhanced by taking advantage of the spatial properties of the MMI pattern, designing triple liquid-core waveguides that intersect the MMI waveguide in different locations. Furthermore, the spectral and spatial multiplexing capacities are combined in these triple liquid-core MMI platforms, allowing these devices to distinguish multiple different targets and samples simultaneously.

Assessment of Matrix Multiplication Learning with a Rule-Based Analytical Model--"A Bayesian Network Representation"

ERIC Educational Resources Information Center

Zhang, Zhidong

2016-01-01

This study explored an alternative assessment procedure to examine learning trajectories of matrix multiplication. It took rule-based analytical and cognitive task analysis methods specifically to break down operation rules for a given matrix multiplication. Based on the analysis results, a hierarchical Bayesian network, an assessment model,…

Mass Spectrometry Strategies for Clinical Metabolomics and Lipidomics in Psychiatry, Neurology, and Neuro-Oncology

PubMed Central

Wood, Paul L

2014-01-01

Metabolomics research has the potential to provide biomarkers for the detection of disease, for subtyping complex disease populations, for monitoring disease progression and therapy, and for defining new molecular targets for therapeutic intervention. These potentials are far from being realized because of a number of technical, conceptual, financial, and bioinformatics issues. Mass spectrometry provides analytical platforms that address the technical barriers to success in metabolomics research; however, the limited commercial availability of analytical and stable isotope standards has created a bottleneck for the absolute quantitation of a number of metabolites. Conceptual and financial factors contribute to the generation of statistically under-powered clinical studies, whereas bioinformatics issues result in the publication of a large number of unidentified metabolites. The path forward in this field involves targeted metabolomics analyses of large control and patient populations to define both the normal range of a defined metabolite and the potential heterogeneity (eg, bimodal) in complex patient populations. This approach requires that metabolomics research groups, in addition to developing a number of analytical platforms, build sufficient chemistry resources to supply the analytical standards required for absolute metabolite quantitation. Examples of metabolomics evaluations of sulfur amino-acid metabolism in psychiatry, neurology, and neuro-oncology and of lipidomics in neurology will be reviewed. PMID:23842599

A simple analytical platform based on thin-layer chromatography coupled with paper-based analytical device for determination of total capsaicinoids in chilli samples.

PubMed

Dawan, Phanphruk; Satarpai, Thiphol; Tuchinda, Patoomratana; Shiowatana, Juwadee; Siripinyanond, Atitaya

2017-01-01

A new analytical platform based on the use of thin-layer chromatography (TLC) coupled with paper-based analytical device (PAD) was developed for the determination of total capsaicinoids in chilli samples. This newly developed TLC-PAD is simple and low-cost without any requirement of special instrument or skillful person. The analysis consisted of two steps, i.e., extraction of capsaicinoids from chilli samples by using ethanol as solvent and separation of capsaicinoids by thin-layer chromatography (TLC) and elution of capsaicinoids from the TLC plate with in situ colorimetric detection of capsaicinoids on the PAD. For colorimetric detection, Folin-Ciocalteu reagent was used to detect phenolic functional group of capsaicinoids yielding the blue color. The blue color on the PAD was imaged by a scanner followed by evaluation of its grayscale intensity value by ImageJ program. This newly developed TLC-PAD method provided a linear range from 50 to 1000mgL -1 capsaicinoids with the limit of detection as low as 50mgL -1 capsaicinoids. The proposed method was applied to determine capsaicinoids in dried chilli and seasoning powder samples and the results were in good agreement with those obtained by HPLC method. Copyright © 2016 Elsevier B.V. All rights reserved.

Mass spectrometry strategies for clinical metabolomics and lipidomics in psychiatry, neurology, and neuro-oncology.

PubMed

Wood, Paul L

2014-01-01

Metabolomics research has the potential to provide biomarkers for the detection of disease, for subtyping complex disease populations, for monitoring disease progression and therapy, and for defining new molecular targets for therapeutic intervention. These potentials are far from being realized because of a number of technical, conceptual, financial, and bioinformatics issues. Mass spectrometry provides analytical platforms that address the technical barriers to success in metabolomics research; however, the limited commercial availability of analytical and stable isotope standards has created a bottleneck for the absolute quantitation of a number of metabolites. Conceptual and financial factors contribute to the generation of statistically under-powered clinical studies, whereas bioinformatics issues result in the publication of a large number of unidentified metabolites. The path forward in this field involves targeted metabolomics analyses of large control and patient populations to define both the normal range of a defined metabolite and the potential heterogeneity (eg, bimodal) in complex patient populations. This approach requires that metabolomics research groups, in addition to developing a number of analytical platforms, build sufficient chemistry resources to supply the analytical standards required for absolute metabolite quantitation. Examples of metabolomics evaluations of sulfur amino-acid metabolism in psychiatry, neurology, and neuro-oncology and of lipidomics in neurology will be reviewed.

Zero Energy Districts

DOE Office of Scientific and Technical Information (OSTI.GOV)

Polly, Benjamin J

This presentation shows how NREL is approaching Zero Energy Districts, including key opportunities, design strategies, and master planning concepts. The presentation also covers URBANopt, an advanced analytical platform for district that is being developed by NREL.

Total analysis systems with Thermochromic Etching Discs technology.

PubMed

Avella-Oliver, Miquel; Morais, Sergi; Carrascosa, Javier; Puchades, Rosa; Maquieira, Ángel

2014-12-16

A new analytical system based on Thermochromic Etching Discs (TED) technology is presented. TED comprises a number of attractive features such as track independency, selective irradiation, a high power laser, and the capability to create useful assay platforms. The analytical versatility of this tool opens up a wide range of possibilities to design new compact disc-based total analysis systems applicable in chemistry and life sciences. In this paper, TED analytical implementation is described and discussed, and their analytical potential is supported by several applications. Microarray immunoassay, immunofiltration assay, solution measurement, and cell culture approaches are herein addressed in order to demonstrate the practical capacity of this system. The analytical usefulness of TED technology is herein demonstrated, describing how to exploit this tool for developing truly integrated analytical systems that provide solutions within the point of care framework.

Towards a Web-Enabled Geovisualization and Analytics Platform for the Energy and Water Nexus

NASA Astrophysics Data System (ADS)

Sanyal, J.; Chandola, V.; Sorokine, A.; Allen, M.; Berres, A.; Pang, H.; Karthik, R.; Nugent, P.; McManamay, R.; Stewart, R.; Bhaduri, B. L.

2017-12-01

Interactive data analytics are playing an increasingly vital role in the generation of new, critical insights regarding the complex dynamics of the energy/water nexus (EWN) and its interactions with climate variability and change. Integration of impacts, adaptation, and vulnerability (IAV) science with emerging, and increasingly critical, data science capabilities offers a promising potential to meet the needs of the EWN community. To enable the exploration of pertinent research questions, a web-based geospatial visualization platform is being built that integrates a data analysis toolbox with advanced data fusion and data visualization capabilities to create a knowledge discovery framework for the EWN. The system, when fully built out, will offer several geospatial visualization capabilities including statistical visual analytics, clustering, principal-component analysis, dynamic time warping, support uncertainty visualization and the exploration of data provenance, as well as support machine learning discoveries to render diverse types of geospatial data and facilitate interactive analysis. Key components in the system architecture includes NASA's WebWorldWind, the Globus toolkit, postgresql, as well as other custom built software modules.

Graphene Quantum Dots-based Photoluminescent Sensor: A Multifunctional Composite for Pesticide Detection.

PubMed

Zor, Erhan; Morales-Narváez, Eden; Zamora-Gálvez, Alejandro; Bingol, Haluk; Ersoz, Mustafa; Merkoçi, Arben

2015-09-16

Due to their size and difficulty to obtain, cost/effective biological or synthetic receptors (e.g., antibodies or aptamers, respectively), organic toxic compounds (e.g., less than 1 kDa) are generally challenging to detect using simple platforms such as biosensors. This study reports on the synthesis and characterization of a novel multifunctional composite material, magnetic silica beads/graphene quantum dots/molecularly imprinted polypyrrole (mSGP). mSGP is engineered to specifically and effectively capture and signal small molecules due to the synergy among chemical, magnetic, and optical properties combined with molecular imprinting of tributyltin (291 Da), a hazardous compound, selected as a model analyte. Magnetic and selective properties of the mSGP composite can be exploited to capture and preconcentrate the analyte onto its surface, and its photoluminescent graphene quantum dots, which are quenched upon analyte recognition, are used to interrogate the presence of the contaminant. This multifunctional material enables a rapid, simple and sensitive platform for small molecule detection, even in complex mediums such as seawater, without any sample treatment.

Direct Profiling the Post-Translational Modification Codes of a Single Protein Immobilized on a Surface Using Cu-free Click Chemistry.

PubMed

Kim, Kyung Lock; Park, Kyeng Min; Murray, James; Kim, Kimoon; Ryu, Sung Ho

2018-05-23

Combinatorial post-translational modifications (PTMs), which can serve as dynamic "molecular barcodes", have been proposed to regulate distinct protein functions. However, studies of combinatorial PTMs on single protein molecules have been hindered by a lack of suitable analytical methods. Here, we describe erasable single-molecule blotting (eSiMBlot) for combinatorial PTM profiling. This assay is performed in a highly multiplexed manner and leverages the benefits of covalent protein immobilization, cyclic probing with different antibodies, and single molecule fluorescence imaging. Especially, facile and efficient covalent immobilization on a surface using Cu-free click chemistry permits multiple rounds (>10) of antibody erasing/reprobing without loss of antigenicity. Moreover, cumulative detection of coregistered multiple data sets for immobilized single-epitope molecules, such as HA peptide, can be used to increase the antibody detection rate. Finally, eSiMBlot enables direct visualization and quantitative profiling of combinatorial PTM codes at the single-molecule level, as we demonstrate by revealing the novel phospho-codes of ligand-induced epidermal growth factor receptor. Thus, eSiMBlot provides an unprecedentedly simple, rapid, and versatile platform for analyzing the vast number of combinatorial PTMs in biological pathways.

Direct Profiling the Post-Translational Modification Codes of a Single Protein Immobilized on a Surface Using Cu-free Click Chemistry

PubMed Central

2018-01-01

Combinatorial post-translational modifications (PTMs), which can serve as dynamic “molecular barcodes”, have been proposed to regulate distinct protein functions. However, studies of combinatorial PTMs on single protein molecules have been hindered by a lack of suitable analytical methods. Here, we describe erasable single-molecule blotting (eSiMBlot) for combinatorial PTM profiling. This assay is performed in a highly multiplexed manner and leverages the benefits of covalent protein immobilization, cyclic probing with different antibodies, and single molecule fluorescence imaging. Especially, facile and efficient covalent immobilization on a surface using Cu-free click chemistry permits multiple rounds (>10) of antibody erasing/reprobing without loss of antigenicity. Moreover, cumulative detection of coregistered multiple data sets for immobilized single-epitope molecules, such as HA peptide, can be used to increase the antibody detection rate. Finally, eSiMBlot enables direct visualization and quantitative profiling of combinatorial PTM codes at the single-molecule level, as we demonstrate by revealing the novel phospho-codes of ligand-induced epidermal growth factor receptor. Thus, eSiMBlot provides an unprecedentedly simple, rapid, and versatile platform for analyzing the vast number of combinatorial PTMs in biological pathways.

Geovisual analytics to enhance spatial scan statistic interpretation: an analysis of U.S. cervical cancer mortality

PubMed Central

Chen, Jin; Roth, Robert E; Naito, Adam T; Lengerich, Eugene J; MacEachren, Alan M

2008-01-01

Background Kulldorff's spatial scan statistic and its software implementation – SaTScan – are widely used for detecting and evaluating geographic clusters. However, two issues make using the method and interpreting its results non-trivial: (1) the method lacks cartographic support for understanding the clusters in geographic context and (2) results from the method are sensitive to parameter choices related to cluster scaling (abbreviated as scaling parameters), but the system provides no direct support for making these choices. We employ both established and novel geovisual analytics methods to address these issues and to enhance the interpretation of SaTScan results. We demonstrate our geovisual analytics approach in a case study analysis of cervical cancer mortality in the U.S. Results We address the first issue by providing an interactive visual interface to support the interpretation of SaTScan results. Our research to address the second issue prompted a broader discussion about the sensitivity of SaTScan results to parameter choices. Sensitivity has two components: (1) the method can identify clusters that, while being statistically significant, have heterogeneous contents comprised of both high-risk and low-risk locations and (2) the method can identify clusters that are unstable in location and size as the spatial scan scaling parameter is varied. To investigate cluster result stability, we conducted multiple SaTScan runs with systematically selected parameters. The results, when scanning a large spatial dataset (e.g., U.S. data aggregated by county), demonstrate that no single spatial scan scaling value is known to be optimal to identify clusters that exist at different scales; instead, multiple scans that vary the parameters are necessary. We introduce a novel method of measuring and visualizing reliability that facilitates identification of homogeneous clusters that are stable across analysis scales. Finally, we propose a logical approach to proceed through the analysis of SaTScan results. Conclusion The geovisual analytics approach described in this manuscript facilitates the interpretation of spatial cluster detection methods by providing cartographic representation of SaTScan results and by providing visualization methods and tools that support selection of SaTScan parameters. Our methods distinguish between heterogeneous and homogeneous clusters and assess the stability of clusters across analytic scales. Method We analyzed the cervical cancer mortality data for the United States aggregated by county between 2000 and 2004. We ran SaTScan on the dataset fifty times with different parameter choices. Our geovisual analytics approach couples SaTScan with our visual analytic platform, allowing users to interactively explore and compare SaTScan results produced by different parameter choices. The Standardized Mortality Ratio and reliability scores are visualized for all the counties to identify stable, homogeneous clusters. We evaluated our analysis result by comparing it to that produced by other independent techniques including the Empirical Bayes Smoothing and Kafadar spatial smoother methods. The geovisual analytics approach introduced here is developed and implemented in our Java-based Visual Inquiry Toolkit. PMID:18992163

Geovisual analytics to enhance spatial scan statistic interpretation: an analysis of U.S. cervical cancer mortality.

PubMed

Chen, Jin; Roth, Robert E; Naito, Adam T; Lengerich, Eugene J; Maceachren, Alan M

2008-11-07

Kulldorff's spatial scan statistic and its software implementation - SaTScan - are widely used for detecting and evaluating geographic clusters. However, two issues make using the method and interpreting its results non-trivial: (1) the method lacks cartographic support for understanding the clusters in geographic context and (2) results from the method are sensitive to parameter choices related to cluster scaling (abbreviated as scaling parameters), but the system provides no direct support for making these choices. We employ both established and novel geovisual analytics methods to address these issues and to enhance the interpretation of SaTScan results. We demonstrate our geovisual analytics approach in a case study analysis of cervical cancer mortality in the U.S. We address the first issue by providing an interactive visual interface to support the interpretation of SaTScan results. Our research to address the second issue prompted a broader discussion about the sensitivity of SaTScan results to parameter choices. Sensitivity has two components: (1) the method can identify clusters that, while being statistically significant, have heterogeneous contents comprised of both high-risk and low-risk locations and (2) the method can identify clusters that are unstable in location and size as the spatial scan scaling parameter is varied. To investigate cluster result stability, we conducted multiple SaTScan runs with systematically selected parameters. The results, when scanning a large spatial dataset (e.g., U.S. data aggregated by county), demonstrate that no single spatial scan scaling value is known to be optimal to identify clusters that exist at different scales; instead, multiple scans that vary the parameters are necessary. We introduce a novel method of measuring and visualizing reliability that facilitates identification of homogeneous clusters that are stable across analysis scales. Finally, we propose a logical approach to proceed through the analysis of SaTScan results. The geovisual analytics approach described in this manuscript facilitates the interpretation of spatial cluster detection methods by providing cartographic representation of SaTScan results and by providing visualization methods and tools that support selection of SaTScan parameters. Our methods distinguish between heterogeneous and homogeneous clusters and assess the stability of clusters across analytic scales. We analyzed the cervical cancer mortality data for the United States aggregated by county between 2000 and 2004. We ran SaTScan on the dataset fifty times with different parameter choices. Our geovisual analytics approach couples SaTScan with our visual analytic platform, allowing users to interactively explore and compare SaTScan results produced by different parameter choices. The Standardized Mortality Ratio and reliability scores are visualized for all the counties to identify stable, homogeneous clusters. We evaluated our analysis result by comparing it to that produced by other independent techniques including the Empirical Bayes Smoothing and Kafadar spatial smoother methods. The geovisual analytics approach introduced here is developed and implemented in our Java-based Visual Inquiry Toolkit.

Whole-body concentrations of elements in three fish species from offshore oil platforms and natural areas in the Southern California Bight, USA

USGS Publications Warehouse

Love, Milton S.; Saiki, Michael K.; May, Thomas W.; Yee, Julie L.

2013-01-01

elements. Forty-two elements were excluded from statistical comparisons as they (1) consisted of major cations that were unlikely to accumulate to potentially toxic concentrations; (2) were not detected by the analytical procedures; or (3) were detected at concentrations too low to yield reliable quantitative measurements. The remaining 21 elements consisted of aluminum, arsenic, barium, cadmium, chromium, cobalt, copper, gallium, iron, lead, lithium, manganese, mercury, nickel, rubidium, selenium, strontium, tin, titanium, vanadium, and zinc. Statistical comparisons of these elements indicated that none consistently exhibited higher concentrations at oil platforms than at natural areas. However, the concentrations of copper, selenium, titanium, and vanadium in Pacific sanddab were unusual because small individuals exhibited either no differences between oil platforms and natural areas or significantly lower concentrations at oil platforms than at natural areas, whereas large individuals exhibited significantly higher concentrations at oil platforms than at natural areas.

Strategies for comparing gene expression profiles from different microarray platforms: application to a case-control experiment.

PubMed

Severgnini, Marco; Bicciato, Silvio; Mangano, Eleonora; Scarlatti, Francesca; Mezzelani, Alessandra; Mattioli, Michela; Ghidoni, Riccardo; Peano, Clelia; Bonnal, Raoul; Viti, Federica; Milanesi, Luciano; De Bellis, Gianluca; Battaglia, Cristina

2006-06-01

Meta-analysis of microarray data is increasingly important, considering both the availability of multiple platforms using disparate technologies and the accumulation in public repositories of data sets from different laboratories. We addressed the issue of comparing gene expression profiles from two microarray platforms by devising a standardized investigative strategy. We tested this procedure by studying MDA-MB-231 cells, which undergo apoptosis on treatment with resveratrol. Gene expression profiles were obtained using high-density, short-oligonucleotide, single-color microarray platforms: GeneChip (Affymetrix) and CodeLink (Amersham). Interplatform analyses were carried out on 8414 common transcripts represented on both platforms, as identified by LocusLink ID, representing 70.8% and 88.6% of annotated GeneChip and CodeLink features, respectively. We identified 105 differentially expressed genes (DEGs) on CodeLink and 42 DEGs on GeneChip. Among them, only 9 DEGs were commonly identified by both platforms. Multiple analyses (BLAST alignment of probes with target sequences, gene ontology, literature mining, and quantitative real-time PCR) permitted us to investigate the factors contributing to the generation of platform-dependent results in single-color microarray experiments. An effective approach to cross-platform comparison involves microarrays of similar technologies, samples prepared by identical methods, and a standardized battery of bioinformatic and statistical analyses.

Population-based pediatric reference intervals for general clinical chemistry analytes on the Abbott Architect ci8200 instrument.

PubMed

Ridefelt, Peter; Aldrimer, Mattias; Rödöö, Per-Olof; Niklasson, Frank; Jansson, Leif; Gustafsson, Jan; Hellberg, Dan

2012-02-29

Reference intervals are crucial decision-making tools aiding clinicians in differentiating between healthy and diseased populations. However, for children such values often are lacking or incomplete. Blood samples were obtained from 692 healthy children, aged 6 months to 18 years, recruited in daycare centers and schools. Twelve common general clinical chemistry analytes were measured on the Abbott Architect ci8200 platform; sodium, potassium, chloride, calcium, albumin-adjusted calcium, phosphate, magnesium, creatinine (Jaffe and enzymatic), cystatin C, urea and uric acid. Age- and gender specific pediatric reference intervals were defined by calculating the 2.5th and 97.5th percentiles. The data generated is primarily applicable to a Caucasian population when using the Abbott Architect platform, but could be used by any laboratory if validated for the local patient population.

Framework for Deploying a Virtualized Computing Environment for Collaborative and Secure Data Analytics

PubMed Central

Meyer, Adrian; Green, Laura; Faulk, Ciearro; Galla, Stephen; Meyer, Anne-Marie

2016-01-01

Introduction: Large amounts of health data generated by a wide range of health care applications across a variety of systems have the potential to offer valuable insight into populations and health care systems, but robust and secure computing and analytic systems are required to leverage this information. Framework: We discuss our experiences deploying a Secure Data Analysis Platform (SeDAP), and provide a framework to plan, build and deploy a virtual desktop infrastructure (VDI) to enable innovation, collaboration and operate within academic funding structures. It outlines 6 core components: Security, Ease of Access, Performance, Cost, Tools, and Training. Conclusion: A platform like SeDAP is not simply successful through technical excellence and performance. It’s adoption is dependent on a collaborative environment where researchers and users plan and evaluate the requirements of all aspects. PMID:27683665

Versatile electrophoresis-based self-test platform.

PubMed

Guijt, Rosanne M

2015-03-01

Lab on a Chip technology offers the possibility to extract chemical information from a complex sample in a simple, automated way without the need for a laboratory setting. In the health care sector, this chemical information could be used as a diagnostic tool for example to inform dosing. In this issue, the research underpinning a family of electrophoresis-based point-of-care devices for self-testing of ionic analytes in various sample matrices is described [Electrophoresis 2015, 36, 712-721.]. Hardware, software, and methodological chances made to improve the overall analytical performance in terms of accuracy, precision, detection limit, and reliability are discussed. In addition to the main focus of lithium monitoring, new applications including the use of the platform for veterinary purposes, sodium, and for creatinine measurements are included. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

A universal and label-free impedimetric biosensing platform for discrimination of single nucleotide substitutions in long nucleic acid strands.

PubMed

Mills, Dawn M; Martin, Christopher P; Armas, Stephanie M; Calvo-Marzal, Percy; Kolpashchikov, Dmitry M; Chumbimuni-Torres, Karin Y

2018-06-30

We report a label-free universal biosensing platform for highly selective detection of long nucleic acid strands. The sensor consists of an electrode-immobilized universal stem-loop (USL) probe and two adaptor strands that form a 4J structure in the presence of a specific DNA/RNA analyte. The sensor was characterized by electrochemical impedance spectroscopy (EIS) using K 3 [Fe(CN) 6 ]/K 4 [Fe(CN) 6 ] redox couple in solution. An increase in charge transfer resistance (R CT ) was observed upon 4J structure formation, the value of which depends on the analyte length. Cyclic voltammetry (CV) was used to further characterize the sensor and monitor the electrochemical reaction in conjunction with thickness measurements of the mixed DNA monolayer obtained using spectroscopic ellipsometry. In addition, the electron transfer was calculated at the electrode/electrolyte interface using a rotating disk electrode. Limits of detection in the femtomolar range were achieved for nucleic acid targets of different lengths (22 nt, 60 nt, 200 nt). The sensor produced only a background signal in the presence of single base mismatched analytes, even in hundred times excess in concentration. This label-free and highly selective biosensing platform is versatile and can be used for universal detection of nucleic acids of varied lengths which could revolutionize point of care diagnostics for applications such as bacterial or cancer screening. Copyright © 2018 Elsevier B.V. All rights reserved.

Twitter 101 and beyond: introduction to social media platforms available to practicing hematologist/oncologists.

PubMed

Thompson, Michael A; Ahlstrom, Jenny; Dizon, Don S; Gad, Yash; Matthews, Greg; Luks, Howard J; Schorr, Andrew

2017-10-01

Social media utilizes specific media platforms to allow increased interactivity between participants. These platforms serve diverse groups and purposes including participation from patients, family caregivers, research scientists, physicians, and pharmaceutical companies. Utilization of these information outlets has increased with integration at conferences and between conferences with the use of hashtags and "chats". In the realm of the "e-Patient" it is key to not underestimate your audience. Highly technical information is just as useful as a basic post. With growing use, social media analytics help track the volume and impact of content. Additionally, platforms are leveraging each other for uses, including Twitter, blogs, web radio, and recorded video and images. We explore information on social media resources and applications from varying perspectives. While these platforms will evolve over time, or disappear with new platforms taking their place, it is apparent they are now a part of the everyday experience of oncology communication. Copyright © 2017 Elsevier Inc. All rights reserved.

Exploring the Dynamics of Cell Processes through Simulations of Fluorescence Microscopy Experiments

PubMed Central

Angiolini, Juan; Plachta, Nicolas; Mocskos, Esteban; Levi, Valeria

2015-01-01

Fluorescence correlation spectroscopy (FCS) methods are powerful tools for unveiling the dynamical organization of cells. For simple cases, such as molecules passively moving in a homogeneous media, FCS analysis yields analytical functions that can be fitted to the experimental data to recover the phenomenological rate parameters. Unfortunately, many dynamical processes in cells do not follow these simple models, and in many instances it is not possible to obtain an analytical function through a theoretical analysis of a more complex model. In such cases, experimental analysis can be combined with Monte Carlo simulations to aid in interpretation of the data. In response to this need, we developed a method called FERNET (Fluorescence Emission Recipes and Numerical routines Toolkit) based on Monte Carlo simulations and the MCell-Blender platform, which was designed to treat the reaction-diffusion problem under realistic scenarios. This method enables us to set complex geometries of the simulation space, distribute molecules among different compartments, and define interspecies reactions with selected kinetic constants, diffusion coefficients, and species brightness. We apply this method to simulate single- and multiple-point FCS, photon-counting histogram analysis, raster image correlation spectroscopy, and two-color fluorescence cross-correlation spectroscopy. We believe that this new program could be very useful for predicting and understanding the output of fluorescence microscopy experiments. PMID:26039162

An integrative computational approach for prioritization of genomic variants

DOE PAGES

Dubchak, Inna; Balasubramanian, Sandhya; Wang, Sheng; ...

2014-12-15

An essential step in the discovery of molecular mechanisms contributing to disease phenotypes and efficient experimental planning is the development of weighted hypotheses that estimate the functional effects of sequence variants discovered by high-throughput genomics. With the increasing specialization of the bioinformatics resources, creating analytical workflows that seamlessly integrate data and bioinformatics tools developed by multiple groups becomes inevitable. Here we present a case study of a use of the distributed analytical environment integrating four complementary specialized resources, namely the Lynx platform, VISTA RViewer, the Developmental Brain Disorders Database (DBDB), and the RaptorX server, for the identification of high-confidence candidatemore » genes contributing to pathogenesis of spina bifida. The analysis resulted in prediction and validation of deleterious mutations in the SLC19A placental transporter in mothers of the affected children that causes narrowing of the outlet channel and therefore leads to the reduced folate permeation rate. The described approach also enabled correct identification of several genes, previously shown to contribute to pathogenesis of spina bifida, and suggestion of additional genes for experimental validations. This study demonstrates that the seamless integration of bioinformatics resources enables fast and efficient prioritization and characterization of genomic factors and molecular networks contributing to the phenotypes of interest.« less

Quantitative fingerprinting by headspace--two-dimensional comprehensive gas chromatography-mass spectrometry of solid matrices: some challenging aspects of the exhaustive assessment of food volatiles.

PubMed

Nicolotti, Luca; Cordero, Chiara; Cagliero, Cecilia; Liberto, Erica; Sgorbini, Barbara; Rubiolo, Patrizia; Bicchi, Carlo

2013-10-10

The study proposes an investigation strategy that simultaneously provides detailed profiling and quantitative fingerprinting of food volatiles, through a "comprehensive" analytical platform that includes sample preparation by Headspace Solid Phase Microextraction (HS-SPME), separation by two-dimensional comprehensive gas chromatography coupled with mass spectrometry detection (GC×GC-MS) and data processing using advanced fingerprinting approaches. Experiments were carried out on roasted hazelnuts and on Gianduja pastes (sugar, vegetable oil, hazelnuts, cocoa, nonfat dried milk, vanilla flavorings) and demonstrated that the information potential of each analysis can better be exploited if suitable quantitation methods are applied. Quantitation approaches through Multiple Headspace Extraction and Standard Addition were compared in terms of performance parameters (linearity, precision, accuracy, Limit of Detection and Limit of Quantitation) under headspace linearity conditions. The results on 19 key analytes, potent odorants, and technological markers, and more than 300 fingerprint components, were used for further processing to obtain information concerning the effect of the matrix on volatile release, and to produce an informative chemical blueprint for use in sensomics and flavoromics. The importance of quantitation approaches in headspace analysis of solid matrices of complex composition, and the advantages of MHE, are also critically discussed. Copyright © 2013 Elsevier B.V. All rights reserved.

Comparison of aerial imagery from manned and unmanned aircraft platforms for monitoring cotton growth

USDA-ARS?s Scientific Manuscript database

Unmanned aircraft systems (UAS) have emerged as a low-cost and versatile remote sensing platform in recent years, but little work has been done on comparing imagery from manned and unmanned platforms for crop assessment. The objective of this study was to compare imagery taken from multiple cameras ...

Genomics Portals: integrative web-platform for mining genomics data.

PubMed

Shinde, Kaustubh; Phatak, Mukta; Johannes, Freudenberg M; Chen, Jing; Li, Qian; Vineet, Joshi K; Hu, Zhen; Ghosh, Krishnendu; Meller, Jaroslaw; Medvedovic, Mario

2010-01-13

A large amount of experimental data generated by modern high-throughput technologies is available through various public repositories. Our knowledge about molecular interaction networks, functional biological pathways and transcriptional regulatory modules is rapidly expanding, and is being organized in lists of functionally related genes. Jointly, these two sources of information hold a tremendous potential for gaining new insights into functioning of living systems. Genomics Portals platform integrates access to an extensive knowledge base and a large database of human, mouse, and rat genomics data with basic analytical visualization tools. It provides the context for analyzing and interpreting new experimental data and the tool for effective mining of a large number of publicly available genomics datasets stored in the back-end databases. The uniqueness of this platform lies in the volume and the diversity of genomics data that can be accessed and analyzed (gene expression, ChIP-chip, ChIP-seq, epigenomics, computationally predicted binding sites, etc), and the integration with an extensive knowledge base that can be used in such analysis. The integrated access to primary genomics data, functional knowledge and analytical tools makes Genomics Portals platform a unique tool for interpreting results of new genomics experiments and for mining the vast amount of data stored in the Genomics Portals backend databases. Genomics Portals can be accessed and used freely at http://GenomicsPortals.org.

Genomics Portals: integrative web-platform for mining genomics data

PubMed Central

2010-01-01

Background A large amount of experimental data generated by modern high-throughput technologies is available through various public repositories. Our knowledge about molecular interaction networks, functional biological pathways and transcriptional regulatory modules is rapidly expanding, and is being organized in lists of functionally related genes. Jointly, these two sources of information hold a tremendous potential for gaining new insights into functioning of living systems. Results Genomics Portals platform integrates access to an extensive knowledge base and a large database of human, mouse, and rat genomics data with basic analytical visualization tools. It provides the context for analyzing and interpreting new experimental data and the tool for effective mining of a large number of publicly available genomics datasets stored in the back-end databases. The uniqueness of this platform lies in the volume and the diversity of genomics data that can be accessed and analyzed (gene expression, ChIP-chip, ChIP-seq, epigenomics, computationally predicted binding sites, etc), and the integration with an extensive knowledge base that can be used in such analysis. Conclusion The integrated access to primary genomics data, functional knowledge and analytical tools makes Genomics Portals platform a unique tool for interpreting results of new genomics experiments and for mining the vast amount of data stored in the Genomics Portals backend databases. Genomics Portals can be accessed and used freely at http://GenomicsPortals.org. PMID:20070909

Using a patterned grating structure to create lipid bilayer platforms insensitive to air bubbles.

PubMed

Han, Chung-Ta; Chao, Ling

2015-01-07

Supported lipid bilayers (SLBs) have been used for various biosensing applications. The bilayer structure enables embedded lipid membrane species to maintain their native orientation, and the two-dimensional fluidity is crucial for numerous biomolecular interactions to occur. The platform integrated with a microfluidic device for reagent transport and exchange has great potential to be applied with surface analytical tools. However, SLBs can easily be destroyed by air bubbles during assay reagent transport and exchange. Here, we created a patterned obstacle grating structured surface in a microfluidic channel to protect SLBs from being destroyed by air bubbles. Unlike all of the previous approaches using chemical modification or adding protection layers to strengthen lipid bilayers, the uniqueness of this approach is that it uses the patterned obstacles to physically trap water above the bilayers to prevent the air-water interface from directly coming into contact with and peeling the bilayers. We showed that our platform with certain grating geometry criteria can provide promising protection to SLBs from air bubbles. The required obstacle distance was found to decrease when we increased the air-bubble movement speed. In addition, the interaction assay results from streptavidin and biotinylated lipids in the confined SLBs suggested that receptors at the SLBs retained the interaction ability after air-bubble treatment. The results showed that the developed SLB platform can preserve both high membrane fluidity and high accessibility to the outside environment, which have never been simultaneously achieved before. Incorporating the built platforms with some surface analytical tools could open the bottleneck of building highly robust in vitro cell-membrane-related bioassays.

Wave drift damping acting on multiple circular cylinders (model tests)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kinoshita, Takeshi; Sunahara, Shunji; Bao, W.

1995-12-31

The wave drift damping for the slow drift motion of a four-column platform is experimentally investigated. The estimation of damping force of the slow drift motion of moored floating structures in ocean waves, is one of the most important topics. Bao et al. calculated an interaction of multiple circular cylinders based on the potential flow theory, and showed that the wave drift damping is significantly influenced by the interaction between cylinders. This calculation method assumes that the slow drift motion is approximately replaced by steady current, that is, structures on slow drift motion are supposed to be equivalent to onesmore » in both regular waves and slow current. To validate semi-analytical solutions of Bao et al., experiments were carried out. At first, added resistance due to waves acting on a structure composed of multiple (four) vertical circular cylinders fixed to a slowly moving carriage, was measured in regular waves. Next, the added resistance of the structure moored by linear spring to the slowly moving carriage were measured in regular waves. Furthermore, to validate the assumption that the slow drift motion is replaced by steady current, free decay tests in still water and in regular waves were compared with the simulation of the slow drift motion using the wave drift damping coefficient obtained by the added resistance tests.« less

Single-Cell Detection of Secreted Aβ and sAPPα from Human IPSC-Derived Neurons and Astrocytes.

PubMed

Liao, Mei-Chen; Muratore, Christina R; Gierahn, Todd M; Sullivan, Sarah E; Srikanth, Priya; De Jager, Philip L; Love, J Christopher; Young-Pearse, Tracy L

2016-02-03

Secreted factors play a central role in normal and pathological processes in every tissue in the body. The brain is composed of a highly complex milieu of different cell types and few methods exist that can identify which individual cells in a complex mixture are secreting specific analytes. By identifying which cells are responsible, we can better understand neural physiology and pathophysiology, more readily identify the underlying pathways responsible for analyte production, and ultimately use this information to guide the development of novel therapeutic strategies that target the cell types of relevance. We present here a method for detecting analytes secreted from single human induced pluripotent stem cell (iPSC)-derived neural cells and have applied the method to measure amyloid β (Aβ) and soluble amyloid precursor protein-alpha (sAPPα), analytes central to Alzheimer's disease pathogenesis. Through these studies, we have uncovered the dynamic range of secretion profiles of these analytes from single iPSC-derived neuronal and glial cells and have molecularly characterized subpopulations of these cells through immunostaining and gene expression analyses. In examining Aβ and sAPPα secretion from single cells, we were able to identify previously unappreciated complexities in the biology of APP cleavage that could not otherwise have been found by studying averaged responses over pools of cells. This technique can be readily adapted to the detection of other analytes secreted by neural cells, which would have the potential to open new perspectives into human CNS development and dysfunction. We have established a technology that, for the first time, detects secreted analytes from single human neurons and astrocytes. We examine secretion of the Alzheimer's disease-relevant factors amyloid β (Aβ) and soluble amyloid precursor protein-alpha (sAPPα) and present novel findings that could not have been observed without a single-cell analytical platform. First, we identify a previously unappreciated subpopulation that secretes high levels of Aβ in the absence of detectable sAPPα. Further, we show that multiple cell types secrete high levels of Aβ and sAPPα, but cells expressing GABAergic neuronal markers are overrepresented. Finally, we show that astrocytes are competent to secrete high levels of Aβ and therefore may be a significant contributor to Aβ accumulation in the brain. Copyright © 2016 the authors 0270-6474/16/361730-17$15.00/0.

Drowned carbonate platforms in the Huon Gulf, Papua New Guinea

NASA Astrophysics Data System (ADS)

Webster, Jody M.; Wallace, Laura; Silver, Eli; Applegate, Bruce; Potts, Donald; Braga, Juan Carlos; Riker-Coleman, Kristin; Gallup, Christina

2004-11-01

The western Huon Gulf, Papua New Guinea, is an actively subsiding foreland basin dominated by drowned carbonate platforms. We investigated these platforms using new high-resolution multibeam, side-scan sonar and seismic data, combined with submersible observations and previously published radiometric and sedimentary facies data. The data reveal 14 distinct drowned carbonate platforms and numerous pinnacles/banks that increase in age (˜20-450 kyr) and depth (0.1-2.5 km) NE toward the Ramu-Markham Trench. Superimposed on this overall downward flexing of the platforms toward the trench is a systematic tilting of the deep platforms 15 m/km toward the NW and the shallow platforms 2 m/km toward the SE. This may reflect the encroaching thrust load from the NW (Finisterre Range) and spatial variations in the flexural rigidity of the underlying basement. The drowned platforms form a complex system of promontories and reentrants, with abundant pinnacles and banks preserved at similar depths seaward of the main platforms. This configuration closely mimics the present-day Huon coastline and its seaward islands fringed by modern coral reefs. The platforms retain structural, morphologic, and sedimentary facies evidence of primary platform growth, drowning, and subsequent backstepping, despite some lateral erosion of the platform margins (<100 m slope defacement) by mass wasting. Both platforms and pinnacles are composite features containing multiple terrace levels and notches, corresponding to multiple phases of growth, emergence, and drowning in response to rapid climatic and sea level changes during the evolution of each structure. On the basis of all observational and numerical modeling data, we propose a chronology for the initiation, growth, and drowning of the 14 platforms. Over shorter timescales (≤100 kyr) the rate and amplitude of eustatic sea level changes are critical in controlling initiation, growth, drowning or subaerial exposure, subsequent reinitiation, and final drowning of the platforms. However, continued tectonic subsidence and basement substrate morphology influence the overall backstepping geometry and subsequent tilting of the platforms over longer timescales (≥100-500 kyr).

Controlling multiple security robots in a warehouse environment

NASA Technical Reports Server (NTRS)

Everett, H. R.; Gilbreath, G. A.; Heath-Pastore, T. A.; Laird, R. T.

1994-01-01

The Naval Command Control and Ocean Surveillance Center (NCCOSC) has developed an architecture to provide coordinated control of multiple autonomous vehicles from a single host console. The multiple robot host architecture (MRHA) is a distributed multiprocessing system that can be expanded to accommodate as many as 32 robots. The initial application will employ eight Cybermotion K2A Navmaster robots configured as remote security platforms in support of the Mobile Detection Assessment and Response System (MDARS) Program. This paper discusses developmental testing of the MRHA in an operational warehouse environment, with two actual and four simulated robotic platforms.

Human-Robot Teaming for Hydrologic Data Gathering at Multiple Scales

NASA Astrophysics Data System (ADS)

Peschel, J.; Young, S. N.

2017-12-01

The use of personal robot-assistive technology by researchers and practitioners for hydrologic data gathering has grown in recent years as barriers to platform capability, cost, and human-robot interaction have been overcome. One consequence to this growth is a broad availability of unmanned platforms that might or might not be suitable for a specific hydrologic investigation. Through multiple field studies, a set of recommendations has been developed to help guide novice through experienced users in choosing the appropriate unmanned platforms for a given application. This talk will present a series of hydrologic data sets gathered using a human-robot teaming approach that has leveraged unmanned aerial, ground, and surface vehicles over multiple scales. The field case studies discussed will be connected to the best practices, also provided in the presentation. This talk will be of interest to geoscience researchers and practitioners, in general, as well as those working in fields related to emerging technologies.

a Web-Based Interactive Platform for Co-Clustering Spatio-Temporal Data

NASA Astrophysics Data System (ADS)

Wu, X.; Poorthuis, A.; Zurita-Milla, R.; Kraak, M.-J.

2017-09-01

Since current studies on clustering analysis mainly focus on exploring spatial or temporal patterns separately, a co-clustering algorithm is utilized in this study to enable the concurrent analysis of spatio-temporal patterns. To allow users to adopt and adapt the algorithm for their own analysis, it is integrated within the server side of an interactive web-based platform. The client side of the platform, running within any modern browser, is a graphical user interface (GUI) with multiple linked visualizations that facilitates the understanding, exploration and interpretation of the raw dataset and co-clustering results. Users can also upload their own datasets and adjust clustering parameters within the platform. To illustrate the use of this platform, an annual temperature dataset from 28 weather stations over 20 years in the Netherlands is used. After the dataset is loaded, it is visualized in a set of linked visualizations: a geographical map, a timeline and a heatmap. This aids the user in understanding the nature of their dataset and the appropriate selection of co-clustering parameters. Once the dataset is processed by the co-clustering algorithm, the results are visualized in the small multiples, a heatmap and a timeline to provide various views for better understanding and also further interpretation. Since the visualization and analysis are integrated in a seamless platform, the user can explore different sets of co-clustering parameters and instantly view the results in order to do iterative, exploratory data analysis. As such, this interactive web-based platform allows users to analyze spatio-temporal data using the co-clustering method and also helps the understanding of the results using multiple linked visualizations.

DNApod: DNA polymorphism annotation database from next-generation sequence read archives.

PubMed

Mochizuki, Takako; Tanizawa, Yasuhiro; Fujisawa, Takatomo; Ohta, Tazro; Nikoh, Naruo; Shimizu, Tokurou; Toyoda, Atsushi; Fujiyama, Asao; Kurata, Nori; Nagasaki, Hideki; Kaminuma, Eli; Nakamura, Yasukazu

2017-01-01

With the rapid advances in next-generation sequencing (NGS), datasets for DNA polymorphisms among various species and strains have been produced, stored, and distributed. However, reliability varies among these datasets because the experimental and analytical conditions used differ among assays. Furthermore, such datasets have been frequently distributed from the websites of individual sequencing projects. It is desirable to integrate DNA polymorphism data into one database featuring uniform quality control that is distributed from a single platform at a single place. DNA polymorphism annotation database (DNApod; http://tga.nig.ac.jp/dnapod/) is an integrated database that stores genome-wide DNA polymorphism datasets acquired under uniform analytical conditions, and this includes uniformity in the quality of the raw data, the reference genome version, and evaluation algorithms. DNApod genotypic data are re-analyzed whole-genome shotgun datasets extracted from sequence read archives, and DNApod distributes genome-wide DNA polymorphism datasets and known-gene annotations for each DNA polymorphism. This new database was developed for storing genome-wide DNA polymorphism datasets of plants, with crops being the first priority. Here, we describe our analyzed data for 679, 404, and 66 strains of rice, maize, and sorghum, respectively. The analytical methods are available as a DNApod workflow in an NGS annotation system of the DNA Data Bank of Japan and a virtual machine image. Furthermore, DNApod provides tables of links of identifiers between DNApod genotypic data and public phenotypic data. To advance the sharing of organism knowledge, DNApod offers basic and ubiquitous functions for multiple alignment and phylogenetic tree construction by using orthologous gene information.

DNApod: DNA polymorphism annotation database from next-generation sequence read archives

PubMed Central

Mochizuki, Takako; Tanizawa, Yasuhiro; Fujisawa, Takatomo; Ohta, Tazro; Nikoh, Naruo; Shimizu, Tokurou; Toyoda, Atsushi; Fujiyama, Asao; Kurata, Nori; Nagasaki, Hideki; Kaminuma, Eli; Nakamura, Yasukazu

2017-01-01

With the rapid advances in next-generation sequencing (NGS), datasets for DNA polymorphisms among various species and strains have been produced, stored, and distributed. However, reliability varies among these datasets because the experimental and analytical conditions used differ among assays. Furthermore, such datasets have been frequently distributed from the websites of individual sequencing projects. It is desirable to integrate DNA polymorphism data into one database featuring uniform quality control that is distributed from a single platform at a single place. DNA polymorphism annotation database (DNApod; http://tga.nig.ac.jp/dnapod/) is an integrated database that stores genome-wide DNA polymorphism datasets acquired under uniform analytical conditions, and this includes uniformity in the quality of the raw data, the reference genome version, and evaluation algorithms. DNApod genotypic data are re-analyzed whole-genome shotgun datasets extracted from sequence read archives, and DNApod distributes genome-wide DNA polymorphism datasets and known-gene annotations for each DNA polymorphism. This new database was developed for storing genome-wide DNA polymorphism datasets of plants, with crops being the first priority. Here, we describe our analyzed data for 679, 404, and 66 strains of rice, maize, and sorghum, respectively. The analytical methods are available as a DNApod workflow in an NGS annotation system of the DNA Data Bank of Japan and a virtual machine image. Furthermore, DNApod provides tables of links of identifiers between DNApod genotypic data and public phenotypic data. To advance the sharing of organism knowledge, DNApod offers basic and ubiquitous functions for multiple alignment and phylogenetic tree construction by using orthologous gene information. PMID:28234924

Multivariate optical element platform for compressed detection of fluorescence markers

NASA Astrophysics Data System (ADS)

Priore, Ryan J.; Swanstrom, Joseph A.

2014-05-01

The success of a commercial fluorescent diagnostic assay is dependent on the selection of a fluorescent biomarker; due to the broad nature of fluorescence biomarker emission profiles, only a small number of fluorescence biomarkers may be discriminated from each other as a function of excitation source. Multivariate Optical Elements (MOEs) are thin-film devices that encode a broad band, spectroscopic pattern allowing a simple broadband detector to generate a highly sensitive and specific detection for a target analyte. MOEs have historically been matched 1:1 to a discrete analyte or class prediction; however, MOE filter sets are capable of sensing projections of the original sparse spectroscopic space enabling a small set of MOEs to discriminate a multitude of target analytes. This optical regression can offer real-time measurements with relatively high signal-to-noise ratios that realize the advantages of multiplexed detection and pattern recognition in a simple optical instrument. The specificity advantage of MOE-based sensors allows fluorescent biomarkers that were once incapable of discrimination from one another via optical band pass filters to be employed in a common assay panel. A simplified MOE-based sensor may ultimately reduce the requirement for highly trained operators as well as move certain life science applications like disease prognostication from the laboratory to the point of care. This presentation will summarize the design and fabrication of compressed detection MOE filter sets for detecting multiple fluorescent biomarkers simultaneously with strong spectroscopic interference as well as comparing the detection performance of the MOE sensor with traditional optical band pass filter methodologies.

A sensitive gold nanoparticles sensing platform based on resonance energy transfer for chemiluminescence light on detection of biomolecules.

PubMed

Qin, Guoxing; Zhao, Shulin; Huang, Yong; Jiang, Jing; Liu, Yi-Ming

2013-08-15

In this article, we report a gold nanoparticles (AuNPs) sensing platform based on chemiluminescence resonance energy transfer (CRET) for light on detection of biomolecules. In designing such a CRET-based biosensing platform, the aptamer was first covalently labeled with a chemiluminescent reagent, N-(4-aminobutyl)-N-ethylisoluminol (ABEI). The ABEI labeled aptamer was then hybridized with AuNPs functionalized ssDNA which was complementary to the aptamer, obtaining the aptasensor. The CRET between ABEI and AuNPs in the aptasensor led to the CL quenching of ABEI. In the presence of a target analyte, it formed a complex with aptamer, and released ABEI-aptamer from AuNPs surface that resulted in CL recovery of ABEI. To test this design, a thrombin (used as a model analyte) aptasensor was prepared and evaluated. The results indicate that the proposed approach is simple and provided a linear range of 50-550 pM for thrombin detection with a detection limit of 15 pM. This new methodology can be easily extended to assay other biomolecules by simply changing the recognition sequence with the substrate aptamer. Copyright © 2013 Elsevier B.V. All rights reserved.

Global Simulation of Bioenergy Crop Productivity: Analytical Framework and Case Study for Switchgrass

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kang, Shujiang; Kline, Keith L; Nair, S. Surendran

A global energy crop productivity model that provides geospatially explicit quantitative details on biomass potential and factors affecting sustainability would be useful, but does not exist now. This study describes a modeling platform capable of meeting many challenges associated with global-scale agro-ecosystem modeling. We designed an analytical framework for bioenergy crops consisting of six major components: (i) standardized natural resources datasets, (ii) global field-trial data and crop management practices, (iii) simulation units and management scenarios, (iv) model calibration and validation, (v) high-performance computing (HPC) simulation, and (vi) simulation output processing and analysis. The HPC-Environmental Policy Integrated Climate (HPC-EPIC) model simulatedmore » a perennial bioenergy crop, switchgrass (Panicum virgatum L.), estimating feedstock production potentials and effects across the globe. This modeling platform can assess soil C sequestration, net greenhouse gas (GHG) emissions, nonpoint source pollution (e.g., nutrient and pesticide loss), and energy exchange with the atmosphere. It can be expanded to include additional bioenergy crops (e.g., miscanthus, energy cane, and agave) and food crops under different management scenarios. The platform and switchgrass field-trial dataset are available to support global analysis of biomass feedstock production potential and corresponding metrics of sustainability.« less

Innovative Visualization Techniques applied to a Flood Scenario

NASA Astrophysics Data System (ADS)

Falcão, António; Ho, Quan; Lopes, Pedro; Malamud, Bruce D.; Ribeiro, Rita; Jern, Mikael

2013-04-01

The large and ever-increasing amounts of multi-dimensional, time-varying and geospatial digital information from multiple sources represent a major challenge for today's analysts. We present a set of visualization techniques that can be used for the interactive analysis of geo-referenced and time sampled data sets, providing an integrated mechanism and that aids the user to collaboratively explore, present and communicate visually complex and dynamic data. Here we present these concepts in the context of a 4 hour flood scenario from Lisbon in 2010, with data that includes measures of water column (flood height) every 10 minutes at a 4.5 m x 4.5 m resolution, topography, building damage, building information, and online base maps. Techniques we use include web-based linked views, multiple charts, map layers and storytelling. We explain two of these in more detail that are not currently in common use for visualization of data: storytelling and web-based linked views. Visual storytelling is a method for providing a guided but interactive process of visualizing data, allowing more engaging data exploration through interactive web-enabled visualizations. Within storytelling, a snapshot mechanism helps the author of a story to highlight data views of particular interest and subsequently share or guide others within the data analysis process. This allows a particular person to select relevant attributes for a snapshot, such as highlighted regions for comparisons, time step, class values for colour legend, etc. and provide a snapshot of the current application state, which can then be provided as a hyperlink and recreated by someone else. Since data can be embedded within this snapshot, it is possible to interactively visualize and manipulate it. The second technique, web-based linked views, includes multiple windows which interactively respond to the user selections, so that when selecting an object and changing it one window, it will automatically update in all the other windows. These concepts can be part of a collaborative platform, where multiple people share and work together on the data, via online access, which also allows its remote usage from a mobile platform. Storytelling augments analysis and decision-making capabilities allowing to assimilate complex situations and reach informed decisions, in addition to helping the public visualize information. In our visualization scenario, developed in the context of the VA-4D project for the European Space Agency (see http://www.ca3-uninova.org/project_va4d), we make use of the GAV (GeoAnalytics Visualization) framework, a web-oriented visual analytics application based on multiple interactive views. The final visualization that we produce includes multiple interactive views, including a dynamic multi-layer map surrounded by other visualizations such as bar charts, time graphs and scatter plots. The map provides flood and building information, on top of a base city map (street maps and/or satellite imagery provided by online map services such as Google Maps, Bing Maps etc.). Damage over time for selected buildings, damage for all buildings at a chosen time period, correlation between damage and water depth can be analysed in the other views. This interactive web-based visualization that incorporates the ideas of storytelling, web-based linked views, and other visualization techniques, for a 4 hour flood event in Lisbon in 2010, can be found online at http://www.ncomva.se/flash/projects/esa/flooding/.

Analytical Performance of Four Polymerase Chain Reaction (PCR) and Real Time PCR (qPCR) Assays for the Detection of Six Leishmania Species DNA in Colombia

PubMed Central

León, Cielo M.; Muñoz, Marina; Hernández, Carolina; Ayala, Martha S.; Flórez, Carolina; Teherán, Aníbal; Cubides, Juan R.; Ramírez, Juan D.

2017-01-01

Leishmaniasis comprises a spectrum of parasitic diseases caused by protozoans of the genus Leishmania. Molecular tools have been widely employed for the detection of Leishmania due to its high sensitivity and specificity. However, the analytical performance of molecular platforms as PCR and real time PCR (qPCR) including a wide variety of molecular markers has never been evaluated. Herein, the aim was to evaluate the analytical performance of 4 PCR-based assays (designed on four different targets) and applied on conventional and real-time PCR platforms. We evaluated the analytical performance of conventional PCR and real time PCR, determining exclusivity and inclusivity, Anticipated Reportable Range (ARR), limit of detection (LoD) and accuracy using primers directed to kDNA, HSP70, 18S and ITS-1 targets. We observed that the kDNA was the most sensitive but does not meet the criterion of exclusivity. The HSP70 presented a higher LoD in conventional PCR and qPCR in comparison with the other markers (1 × 101 and 1 × 10-1 equivalent parasites/mL respectively) and had a higher coefficient of variation in qPCR. No statistically significant differences were found between the days of the test with the four molecular markers. The present study revealed that the 18S marker presented the best performance in terms of analytical sensitivity and specificity for the qPCR in the species tested (species circulating in Colombia). Therefore, we recommend to explore the analytical and diagnostic performance in future studies using a broader number of species across America. PMID:29046670

Analytical Performance of Four Polymerase Chain Reaction (PCR) and Real Time PCR (qPCR) Assays for the Detection of Six Leishmania Species DNA in Colombia.

PubMed

León, Cielo M; Muñoz, Marina; Hernández, Carolina; Ayala, Martha S; Flórez, Carolina; Teherán, Aníbal; Cubides, Juan R; Ramírez, Juan D

2017-01-01

Leishmaniasis comprises a spectrum of parasitic diseases caused by protozoans of the genus Leishmania . Molecular tools have been widely employed for the detection of Leishmania due to its high sensitivity and specificity. However, the analytical performance of molecular platforms as PCR and real time PCR (qPCR) including a wide variety of molecular markers has never been evaluated. Herein, the aim was to evaluate the analytical performance of 4 PCR-based assays (designed on four different targets) and applied on conventional and real-time PCR platforms. We evaluated the analytical performance of conventional PCR and real time PCR, determining exclusivity and inclusivity, Anticipated Reportable Range (ARR), limit of detection (LoD) and accuracy using primers directed to kDNA, HSP70, 18S and ITS-1 targets. We observed that the kDNA was the most sensitive but does not meet the criterion of exclusivity. The HSP70 presented a higher LoD in conventional PCR and qPCR in comparison with the other markers (1 × 10 1 and 1 × 10 -1 equivalent parasites/mL respectively) and had a higher coefficient of variation in qPCR. No statistically significant differences were found between the days of the test with the four molecular markers. The present study revealed that the 18S marker presented the best performance in terms of analytical sensitivity and specificity for the qPCR in the species tested (species circulating in Colombia). Therefore, we recommend to explore the analytical and diagnostic performance in future studies using a broader number of species across America.

Treatment patterns in disease-modifying therapy for patients with multiple sclerosis in the United States.

PubMed

Bonafede, Machaon M; Johnson, Barbara H; Wenten, Madé; Watson, Crystal

2013-10-01

Patients with multiple sclerosis (MS) whose disease activity is inadequately controlled with a platform therapy (interferon beta or glatiramer acetate [GA]) may switch to another platform therapy or escalate therapy to natalizumab or fingolimod, which were approved in the US in 2006 and 2010, respectively. The objective of this study was to describe treatment patterns in patients with multiple sclerosis (MS) in the United States who were followed for 2 years after initiating a disease-modifying therapy (DMT). A retrospective observational cohort study was conducted to examine treatment patterns of initial DMT use (on initial therapy for 2 years with and without gaps of ≥ 60 days, medication switching, and discontinuation) among patients with MS who initiated a platform therapy (interferon-β or glatiramer acetate) or natalizumab between January 1, 2007, and September 30, 2009; the first DMT claim was the index. Eligible patients were identified in the MarketScan Commercial and Medicare Supplemental databases based on continuous enrollment for 6 months before (preindex period) and 24 months after their index date, with a diagnosis of MS and no claim for a previous DMT in the 6-month preindex period. Demographics at index and clinical characteristics during the preindex period were also analyzed. A total of 6181 MS patients were included, with 5735 (92.8%) starting on platform therapy. Natalizumab initiators were more likely to stay on index therapy (32.3% vs 16.9%, P < 0.001) and have fewer treatment gaps of ≥ 60 days (44.8% vs 55.3%, P < 0.001) compared with platform initiators. In addition, natalizumab initiators were less likely to switch treatment (13.9% vs 19.1%, P = 0.007) and took longer to switch (400.9 days vs 330.7 days, P < 0.001) compared with platform initiators. Nearly 79% of platform initiators who switched went to another platform therapy. Approximately two thirds of patients who switched to a third DMT (n = 130) switched to another platform therapy. A total of 9% of natalizumab and platform initiators discontinued DMT within the 2 years. Most MS patients initiating DMT started on platform therapy. Natalizumab initiators tended to stay on index therapy, have fewer treatment gaps, and switch less than platform initiators in the 2 years after treatment initiation. Switching between platform therapies is common despite evidence that MS patients on platform therapy may benefit from switching to natalizumab. © 2013 Elsevier HS Journals, Inc. All rights reserved.

Surface-enhanced chiroptical spectroscopy with superchiral surface waves.

PubMed

Pellegrini, Giovanni; Finazzi, Marco; Celebrano, Michele; Duò, Lamberto; Biagioni, Paolo

2018-07-01

We study the chiroptical properties of one-dimensional photonic crystals supporting superchiral surface waves by introducing a simple formalism based on the Fresnel reflection matrix. We show that the proposed framework provides useful insights on the behavior of all the relevant chiroptical quantities, allowing for a deeper understanding of surface-enhanced chiral sensing platforms based on one-dimensional photonic crystals. Finally, we analyze and discuss the limitations of such platforms as the surface concentration of the target chiral analytes is gradually increased. © 2018 Wiley Periodicals, Inc.

The evolving potential of companion diagnostics.

PubMed

Khoury, Joseph D

2016-01-01

The scope of companion diagnostics in cancer has undergone significant shifts in the past few years, with increased development of targeted therapies and novel testing platforms. This has provided new opportunities to effect unprecedented paradigm shifts in the application of personalized medicine principles for patients with cancer. These shifts involve assay platforms, analytes, regulations, and therapeutic approaches. As opportunities involving each of these facets of companion diagnostics expand, close collaborations between key stakeholders should be enhanced to ensure optimal performance characteristics and patient outcomes.

A collaborative visual analytics suite for protein folding research.

PubMed

Harvey, William; Park, In-Hee; Rübel, Oliver; Pascucci, Valerio; Bremer, Peer-Timo; Li, Chenglong; Wang, Yusu

2014-09-01

Molecular dynamics (MD) simulation is a crucial tool for understanding principles behind important biochemical processes such as protein folding and molecular interaction. With the rapidly increasing power of modern computers, large-scale MD simulation experiments can be performed regularly, generating huge amounts of MD data. An important question is how to analyze and interpret such massive and complex data. One of the (many) challenges involved in analyzing MD simulation data computationally is the high-dimensionality of such data. Given a massive collection of molecular conformations, researchers typically need to rely on their expertise and prior domain knowledge in order to retrieve certain conformations of interest. It is not easy to make and test hypotheses as the data set as a whole is somewhat "invisible" due to its high dimensionality. In other words, it is hard to directly access and examine individual conformations from a sea of molecular structures, and to further explore the entire data set. There is also no easy and convenient way to obtain a global view of the data or its various modalities of biochemical information. To this end, we present an interactive, collaborative visual analytics tool for exploring massive, high-dimensional molecular dynamics simulation data sets. The most important utility of our tool is to provide a platform where researchers can easily and effectively navigate through the otherwise "invisible" simulation data sets, exploring and examining molecular conformations both as a whole and at individual levels. The visualization is based on the concept of a topological landscape, which is a 2D terrain metaphor preserving certain topological and geometric properties of the high dimensional protein energy landscape. In addition to facilitating easy exploration of conformations, this 2D terrain metaphor also provides a platform where researchers can visualize and analyze various properties (such as contact density) overlayed on the top of the 2D terrain. Finally, the software provides a collaborative environment where multiple researchers can assemble observations and biochemical events into storyboards and share them in real time over the Internet via a client-server architecture. The software is written in Scala and runs on the cross-platform Java Virtual Machine. Binaries and source code are available at http://www.aylasoftware.org and have been released under the GNU General Public License. Copyright © 2014 Elsevier Inc. All rights reserved.

categoryCompare, an analytical tool based on feature annotations

PubMed Central

Flight, Robert M.; Harrison, Benjamin J.; Mohammad, Fahim; Bunge, Mary B.; Moon, Lawrence D. F.; Petruska, Jeffrey C.; Rouchka, Eric C.

2014-01-01

Assessment of high-throughput—omics data initially focuses on relative or raw levels of a particular feature, such as an expression value for a transcript, protein, or metabolite. At a second level, analyses of annotations including known or predicted functions and associations of each individual feature, attempt to distill biological context. Most currently available comparative- and meta-analyses methods are dependent on the availability of identical features across data sets, and concentrate on determining features that are differentially expressed across experiments, some of which may be considered “biomarkers.” The heterogeneity of measurement platforms and inherent variability of biological systems confounds the search for robust biomarkers indicative of a particular condition. In many instances, however, multiple data sets show involvement of common biological processes or signaling pathways, even though individual features are not commonly measured or differentially expressed between them. We developed a methodology, categoryCompare, for cross-platform and cross-sample comparison of high-throughput data at the annotation level. We assessed the utility of the approach using hypothetical data, as well as determining similarities and differences in the set of processes in two instances: (1) denervated skin vs. denervated muscle, and (2) colon from Crohn's disease vs. colon from ulcerative colitis (UC). The hypothetical data showed that in many cases comparing annotations gave superior results to comparing only at the gene level. Improved analytical results depended as well on the number of genes included in the annotation term, the amount of noise in relation to the number of genes expressing in unenriched annotation categories, and the specific method in which samples are combined. In the skin vs. muscle denervation comparison, the tissues demonstrated markedly different responses. The Crohn's vs. UC comparison showed gross similarities in inflammatory response in the two diseases, with particular processes specific to each disease. PMID:24808906

Improved Sensitivity of Spectroscopic Quantification of Stable Isotope Content Using Capillary Absorption Spectroscopy

NASA Astrophysics Data System (ADS)

Moran, J.; Wilcox Freeburg, E.; Kriesel, J.; Linley, T. J.; Kelly, J.; Coleman, M. L.; Christensen, L. E.; Vance, S.

2016-12-01

Spectroscopy-based platforms have recently risen to the forefront for making stable isotope measurements of methane, carbon dioxide, water, or other analytes. These spectroscopy systems can be relatively straightforward to operate (versus a mass spectrometry platform), largely relieve the analyst of mass interference artifacts, and many can be used in the field. Despite these significant advantages, however, existing spectroscopy techniques suffer from a lack of measurement sensitivity that can ultimately limit select applications including spatially resolved and compound-specific measurements. Here we present a capillary absorption spectroscopy (CAS) system that is designed to mitigate sensitivity issues in spectroscopy-based stable isotope evaluation. The system uses mid-wave infrared excitation generated from a continuous wave quantum cascade laser. Importantly, the sample `chamber' is a flexible capillary with a total volume of less than one cc. Proprietary coatings on the internal surface of the fiber improve optical performance, guiding the light to a detector and facilitating high levels of interaction between the laser beam and gaseous analytes. We present data demonstrating that a tapered hollow fiber cell, with an internal diameter that broadens toward the detector, reduces optical feedback to further improve measurement sensitivity. Sensitivity of current hollow fiber / CAS systems enable measurements of only 10's of picomoles CO2 while theoretical improvements should enable measurements of as little as 10's of femtomoles. Continued optimization of sample introduction and improvements to optical feedback are being explored. Software is being designed to provide rapid integration of data and generation of processed isotope measurements using a graphical user interface. Taken together, the sensitivity improvements of the CAS system under development could, when coupled to a laser ablation sampling device, enable up to 2 µm spatial resolution (roughly the size of a eukaryotic cell or multiple prokaryotic cells) or provide a basis for compounds specific stable isotope analysis of trace biomarkers. The small size and low weight of the system holds future potential for field and / or remote deployment.

Real-time analysis for intensive care: development and deployment of the artemis analytic system.

PubMed

Blount, Marion; Ebling, Maria R; Eklund, J Mikael; James, Andrew G; McGregor, Carolyn; Percival, Nathan; Smith, Kathleen P; Sow, Daby

2010-01-01

The lives of many thousands of children born premature or ill at term around the world have been saved by those who work within neonatal intensive care units (NICUs). Modern-day neonatologists, together with nursing staff and other specialists within this domain, enjoy modern technologies for activities such as financial transactions, online purchasing, music, and video on demand. Yet, when they move into their workspace, in many cases, they are supported by nearly the same technology they used 20 years ago. Medical devices provide visual displays of vital signs through physiological streams such as electrocardiogram (ECG), heart rate, blood oxygen saturation (SpO(2)), and respiratory rate. Electronic health record initiatives around the world provide an environment for the electronic management of medical records, but they fail to support the high-frequency interpretation of streaming physiological data. We have taken a collaborative research approach to address this need to provide a flexible platform for the real-time online analysis of patients' data streams to detect medically significant conditions that precede the onset of medical complications. The platform supports automated or clinician-driven knowledge discovery to discover new relationships between physiological data stream events and latent medical conditions as well as to refine existing analytics. Patients benefit from the system because earlier detection of signs of the medical conditions may lead to earlier intervention that may potentially lead to improved patient outcomes and reduced length of stays. The clinician benefits from a decision support tool that provides insight into multiple streams of data that are too voluminous to assess with traditional methods. The remainder of this article summarizes the strengths of our research collaboration and the resulting environment known as Artemis, which is currently being piloted within the NICU of The Hospital for Sick Children (SickKids) in Toronto, Ontario, Canada. Although the discussion in this article focuses on a NICU, the technologies can be applied to any intensive care environment.

Use of multiple colorimetric indicators for paper-based microfluidic devices.

PubMed

Dungchai, Wijitar; Chailapakul, Orawon; Henry, Charles S

2010-08-03

We report here the use of multiple indicators for a single analyte for paper-based microfluidic devices (microPAD) in an effort to improve the ability to visually discriminate between analyte concentrations. In existing microPADs, a single dye system is used for the measurement of a single analyte. In our approach, devices are designed to simultaneously quantify analytes using multiple indicators for each analyte improving the accuracy of the assay. The use of multiple indicators for a single analyte allows for different indicator colors to be generated at different analyte concentration ranges as well as increasing the ability to better visually discriminate colors. The principle of our devices is based on the oxidation of indicators by hydrogen peroxide produced by oxidase enzymes specific for each analyte. Each indicator reacts at different peroxide concentrations and therefore analyte concentrations, giving an extended range of operation. To demonstrate the utility of our approach, the mixture of 4-aminoantipyrine and 3,5-dichloro-2-hydroxy-benzenesulfonic acid, o-dianisidine dihydrochloride, potassium iodide, acid black, and acid yellow were chosen as the indicators for simultaneous semi-quantitative measurement of glucose, lactate, and uric acid on a microPAD. Our approach was successfully applied to quantify glucose (0.5-20 mM), lactate (1-25 mM), and uric acid (0.1-7 mM) in clinically relevant ranges. The determination of glucose, lactate, and uric acid in control serum and urine samples was also performed to demonstrate the applicability of this device for biological sample analysis. Finally results for the multi-indicator and single indicator system were compared using untrained readers to demonstrate the improvements in accuracy achieved with the new system. 2010 Elsevier B.V. All rights reserved.

Microchannel gel electrophoretic separation systems and methods for preparing and using

DOEpatents

Herr, Amy E; Singh, Anup K; Throckmorton, Daniel J

2015-02-24

A micro-analytical platform for performing electrophoresis-based immunoassays was developed by integrating photopolymerized cross-linked polyacrylamide gels within a microfluidic device. The microfluidic immunoassays are performed by gel electrophoretic separation and quantifying analyte concentration based upon conventional polyacrylamide gel electrophoresis (PAGE). To retain biological activity of proteins and maintain intact immune complexes, native PAGE conditions were employed. Both direct (non-competitive) and competitive immunoassay formats are demonstrated in microchips for detecting toxins and biomarkers (cytokines, c-reactive protein) in bodily fluids (serum, saliva, oral fluids). Further, a description of gradient gels fabrication is included, in an effort to describe methods we have developed for further optimization of on-chip PAGE immunoassays. The described chip-based PAGE immunoassay method enables immunoassays that are fast (minutes) and require very small amounts of sample (less than a few microliters). Use of microfabricated chips as a platform enables integration, parallel assays, automation and development of portable devices.

Carbon Nanomaterial Based Biosensors for Non-Invasive Detection of Cancer and Disease Biomarkers for Clinical Diagnosis

PubMed Central

Tung, Thanh Tran

2017-01-01

The early diagnosis of diseases, e.g., Parkinson’s and Alzheimer’s disease, diabetes, and various types of cancer, and monitoring the response of patients to the therapy plays a critical role in clinical treatment; therefore, there is an intensive research for the determination of many clinical analytes. In order to achieve point-of-care sensing in clinical practice, sensitive, selective, cost-effective, simple, reliable, and rapid analytical methods are required. Biosensors have become essential tools in biomarker sensing, in which electrode material and architecture play critical roles in achieving sensitive and stable detection. Carbon nanomaterials in the form of particle/dots, tube/wires, and sheets have recently become indispensable elements of biosensor platforms due to their excellent mechanical, electronic, and optical properties. This review summarizes developments in this lucrative field by presenting major biosensor types and variability of sensor platforms in biomedical applications. PMID:28825646

Evaluation of a reconfigurable portable instrument for copper determination based on luminescent carbon dots.

PubMed

Salinas-Castillo, Alfonso; Morales, Diego P; Lapresta-Fernández, Alejandro; Ariza-Avidad, María; Castillo, Encarnación; Martínez-Olmos, Antonio; Palma, Alberto J; Capitan-Vallvey, Luis Fermin

2016-04-01

A portable reconfigurable platform for copper (Cu(II)) determination based on luminescent carbon dot (Cdots) quenching is described. The electronic setup consists of a light-emitting diode (LED) as the carbon dot optical exciter and a photodiode as a light-to-current converter integrated in the same instrument. Moreover, the overall analog conditioning is simply performed with one integrated solution, a field-programmable analog array (FPAA), which makes it possible to reconfigure the filter and gain stages in real time. This feature provides adaptability to use the platform as an analytical probe for carbon dots coming from different batches with some variations in luminescence characteristics. The calibration functions obtained that fit a modified Stern-Volmer equation were obtained using luminescence signals from Cdots quenching by Cu(II). The analytical applicability of the reconfigurable portable instrument for Cu(II) using Cdots has been successfully demonstrated in tap water analysis.

Microchannel gel electrophoretic separation systems and methods for preparing and using

DOEpatents

Herr, Amy; Singh, Anup K; Throckmorton, Daniel J

2013-09-03

A micro-analytical platform for performing electrophoresis-based immunoassays was developed by integrating photopolymerized cross-linked polyacrylamide gels within a microfluidic device. The microfluidic immunoassays are performed by gel electrophoretic separation and quantifying analyte concentration based upon conventional polyacrylamide gel electrophoresis (PAGE). To retain biological activity of proteins and maintain intact immune complexes, native PAGE conditions were employed. Both direct (non-competitive) and competitive immunoassay formats are demonstrated in microchips for detecting toxins and biomarkers (cytokines, c-reactive protein) in bodily fluids (serum, saliva, oral fluids). Further, a description of gradient gels fabrication is included, in an effort to describe methods we have developed for further optimization of on-chip PAGE immunoassays. The described chip-based PAGE immunoassay method enables immunoassays that are fast (minutes) and require very small amounts of sample (less than a few microliters). Use of microfabricated chips as a platform enables integration, parallel assays, automation and development of portable devices.

Matrix Factorizations at Scale: a Comparison of Scientific Data Analytics in Spark and C+MPI Using Three Case Studies

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gittens, Alex; Devarakonda, Aditya; Racah, Evan

We explore the trade-offs of performing linear algebra using Apache Spark, compared to traditional C and MPI implementations on HPC platforms. Spark is designed for data analytics on cluster computing platforms with access to local disks and is optimized for data-parallel tasks. We examine three widely-used and important matrix factorizations: NMF (for physical plausibility), PCA (for its ubiquity) and CX (for data interpretability). We apply these methods to 1.6TB particle physics, 2.2TB and 16TB climate modeling and 1.1TB bioimaging data. The data matrices are tall-and-skinny which enable the algorithms to map conveniently into Spark’s data parallel model. We perform scalingmore » experiments on up to 1600 Cray XC40 nodes, describe the sources of slowdowns, and provide tuning guidance to obtain high performance.« less

User testing and performance evaluation of the Electronic Quality Improvement Platform for Plans and Pharmacies.

PubMed

Pringle, Janice L; Kearney, Shannon M; Grasso, Kim; Boyer, Annette D; Conklin, Mark H; Szymanski, Keith A

2015-01-01

To user-test and evaluate a performance information management platform that makes standardized, benchmarked medication use quality data available to both health plans and community pharmacy organizations. Multiple health/drug plans and multiple chain and independent pharmacies across the United States. During the first phase of the study, user experience was measured via user satisfaction surveys and interviews with key personnel (pharmacists, pharmacy leaders, and health plan leadership). Improvements were subsequently made to the platform based on these findings. During the second phase of the study, the platform was implemented in a greater number of pharmacies and by a greater number of payers. User experience was then reevaluated to gather information for further improvements. The surveys and interviews revealed that users found the Web-based platform easy to use and beneficial in terms of understanding and comparing performance metrics. Primary concerns included lack of access to real-time data and patient-specific data. Many users also expressed uncertainty as to how they could use the information and data provided by the platform. The study findings indicate that while information management platforms can be used effectively in both pharmacy and health plan settings, future development is needed to ensure that the provided data can be transferred to pharmacy best practices and improved quality care.

Evaluation of a new eLearning platform for distance teaching of microsurgery.

PubMed

Messaoudi, T; Bodin, F; Hidalgo Diaz, J J; Ichihara, S; Fikry, T; Lacreuse, I; Liverneaux, P; Facca, S

2015-06-01

Online learning (or eLearning) is in constant evolution in medicine. An analytical survey of the websites of eight academic societies and medical schools was carried out. These sites were evaluated against parameters that define the quality of an eLearning website, as well as the shareable content object reference model (SCORM) technical standards. All studied platforms were maintained by a webmaster and regularly updated. Only two platforms had teleconference opportunities, five had courses in PDF format, and four allowed online testing. Based on SCORM standards, only four platforms allowed direct access without a password. The content of all platforms was adaptable, interoperable and reusable. But their sustainability was difficult to assess. In parallel, we developed the first eLearning platform to be used as part of a university diploma in microsurgery in France. The platform was evaluated by students enrolled this diploma program. A satisfaction survey and platform evaluation showed that students were generally satisfied and had used the platform for microsurgery education, especially the seven students living abroad. ELearning for microsurgery allows the content to be continuously updated, makes for fewer classroom visits, provides easy remote access, and especially better training time management and cost savings in terms of travel and accommodations. Copyright © 2015 Elsevier Masson SAS. All rights reserved.

Employing socially driven techniques for framing, contextualization, and collaboration in complex analytical threads

NASA Astrophysics Data System (ADS)

Wollocko, Arthur; Danczyk, Jennifer; Farry, Michael; Jenkins, Michael; Voshell, Martin

2015-05-01

The proliferation of sensor technologies continues to impact Intelligence Analysis (IA) work domains. Historical procurement focus on sensor platform development and acquisition has resulted in increasingly advanced collection systems; however, such systems often demonstrate classic data overload conditions by placing increased burdens on already overtaxed human operators and analysts. Support technologies and improved interfaces have begun to emerge to ease that burden, but these often focus on single modalities or sensor platforms rather than underlying operator and analyst support needs, resulting in systems that do not adequately leverage their natural human attentional competencies, unique skills, and training. One particular reason why emerging support tools often fail is due to the gap between military applications and their functions, and the functions and capabilities afforded by cutting edge technology employed daily by modern knowledge workers who are increasingly "digitally native." With the entry of Generation Y into these workplaces, "net generation" analysts, who are familiar with socially driven platforms that excel at giving users insight into large data sets while keeping cognitive burdens at a minimum, are creating opportunities for enhanced workflows. By using these ubiquitous platforms, net generation analysts have trained skills in discovering new information socially, tracking trends among affinity groups, and disseminating information. However, these functions are currently under-supported by existing tools. In this paper, we describe how socially driven techniques can be contextualized to frame complex analytical threads throughout the IA process. This paper focuses specifically on collaborative support technology development efforts for a team of operators and analysts. Our work focuses on under-supported functions in current working environments, and identifies opportunities to improve a team's ability to discover new information and disseminate insightful analytic findings. We describe our Cognitive Systems Engineering approach to developing a novel collaborative enterprise IA system that combines modern collaboration tools with familiar contemporary social technologies. Our current findings detail specific cognitive and collaborative work support functions that defined the design requirements for a prototype analyst collaborative support environment.

A Systematic Approach for Obtaining Performance on Matrix-Like Operations

NASA Astrophysics Data System (ADS)

Veras, Richard Michael

Scientific Computation provides a critical role in the scientific process because it allows us ask complex queries and test predictions that would otherwise be unfeasible to perform experimentally. Because of its power, Scientific Computing has helped drive advances in many fields ranging from Engineering and Physics to Biology and Sociology to Economics and Drug Development and even to Machine Learning and Artificial Intelligence. Common among these domains is the desire for timely computational results, thus a considerable amount of human expert effort is spent towards obtaining performance for these scientific codes. However, this is no easy task because each of these domains present their own unique set of challenges to software developers, such as domain specific operations, structurally complex data and ever-growing datasets. Compounding these problems are the myriads of constantly changing, complex and unique hardware platforms that an expert must target. Unfortunately, an expert is typically forced to reproduce their effort across multiple problem domains and hardware platforms. In this thesis, we demonstrate the automatic generation of expert level high-performance scientific codes for Dense Linear Algebra (DLA), Structured Mesh (Stencil), Sparse Linear Algebra and Graph Analytic. In particular, this thesis seeks to address the issue of obtaining performance on many complex platforms for a certain class of matrix-like operations that span across many scientific, engineering and social fields. We do this by automating a method used for obtaining high performance in DLA and extending it to structured, sparse and scale-free domains. We argue that it is through the use of the underlying structure found in the data from these domains that enables this process. Thus, obtaining performance for most operations does not occur in isolation of the data being operated on, but instead depends significantly on the structure of the data.

Micro-nano-bio acoustic system for the detection of foodborne pathogens in real samples.

PubMed

Papadakis, George; Murasova, Pavla; Hamiot, Audrey; Tsougeni, Katerina; Kaprou, Georgia; Eck, Michael; Rabus, David; Bilkova, Zuzana; Dupuy, Bruno; Jobst, Gerhard; Tserepi, Angeliki; Gogolides, Evangelos; Gizeli, Electra

2018-07-15

The fast and efficient detection of foodborne pathogens is a societal priority, given the large number of food-poisoning outbreaks, and a scientific and technological challenge, given the need to detect as little as 1 viable cell in 25 gr of food. Here, we present the first approach that achieves the above goal, thanks to the use of a micro/nano-technology and the detection capability of acoustic wave sensors. Starting from 1 Salmonella cell in 25 ml of milk, we employ immuno-magnetic beads to capture cells after only 3 h of pre-enrichment and subsequently demonstrate efficient DNA amplification using the Loop Mediated Isothermal Amplification method (LAMP) and acoustic detection in an integrated platform, within an additional ½ h. The demonstrated 4 h sample-to-analysis time comes as a huge improvement to the current need of few days to obtain the same result. In addition, the work presents the first reported Lab-on-Chip platform that comprises an acoustic device as the sensing element, exhibiting impressive analytical features, namely, an acoustic limit of detection of 2 cells/μl or 3 aM of the DNA target and ability to detect in a label-free manner dsDNA amplicons in impure samples. The use of food samples together with the incorporation of the necessary pre-enrichment step and ability for multiple analysis with an internal control, make the proposed methodology highly relevant to real-world applications. Moreover, the work suggests that acoustic wave devices can be used as an attractive alternative to electrochemical sensors in integrated platforms for applications in food safety and the point-of-care diagnostics. Copyright © 2018. Published by Elsevier B.V.

Sheathless Size-Based Acoustic Particle Separation

PubMed Central

Guldiken, Rasim; Jo, Myeong Chan; Gallant, Nathan D.; Demirci, Utkan; Zhe, Jiang

2012-01-01

Particle separation is of great interest in many biological and biomedical applications. Flow-based methods have been used to sort particles and cells. However, the main challenge with flow based particle separation systems is the need for a sheath flow for successful operation. Existence of the sheath liquid dilutes the analyte, necessitates precise flow control between sample and sheath flow, requires a complicated design to create sheath flow and separation efficiency depends on the sheath liquid composition. In this paper, we present a microfluidic platform for sheathless particle separation using standing surface acoustic waves. In this platform, particles are first lined up at the center of the channel without introducing any external sheath flow. The particles are then entered into the second stage where particles are driven towards the off-center pressure nodes for size based separation. The larger particles are exposed to more lateral displacement in the channel due to the acoustic force differences. Consequently, different-size particles are separated into multiple collection outlets. The prominent feature of the present microfluidic platform is that the device does not require the use of the sheath flow for positioning and aligning of particles. Instead, the sheathless flow focusing and separation are integrated within a single microfluidic device and accomplished simultaneously. In this paper, we demonstrated two different particle size-resolution separations; (1) 3 μm and 10 μm and (2) 3 μm and 5 μm. Also, the effects of the input power, the flow rate, and particle concentration on the separation efficiency were investigated. These technologies have potential to impact broadly various areas including the essential microfluidic components for lab-on-a-chip system and integrated biological and biomedical applications. PMID:22368502

Multicenter validation of cancer gene panel-based next-generation sequencing for translational research and molecular diagnostics.

PubMed

Hirsch, B; Endris, V; Lassmann, S; Weichert, W; Pfarr, N; Schirmacher, P; Kovaleva, V; Werner, M; Bonzheim, I; Fend, F; Sperveslage, J; Kaulich, K; Zacher, A; Reifenberger, G; Köhrer, K; Stepanow, S; Lerke, S; Mayr, T; Aust, D E; Baretton, G; Weidner, S; Jung, A; Kirchner, T; Hansmann, M L; Burbat, L; von der Wall, E; Dietel, M; Hummel, M

2018-04-01

The simultaneous detection of multiple somatic mutations in the context of molecular diagnostics of cancer is frequently performed by means of amplicon-based targeted next-generation sequencing (NGS). However, only few studies are available comparing multicenter testing of different NGS platforms and gene panels. Therefore, seven partner sites of the German Cancer Consortium (DKTK) performed a multicenter interlaboratory trial for targeted NGS using the same formalin-fixed, paraffin-embedded (FFPE) specimen of molecularly pre-characterized tumors (n = 15; each n = 5 cases of Breast, Lung, and Colon carcinoma) and a colorectal cancer cell line DNA dilution series. Detailed information regarding pre-characterized mutations was not disclosed to the partners. Commercially available and custom-designed cancer gene panels were used for library preparation and subsequent sequencing on several devices of two NGS different platforms. For every case, centrally extracted DNA and FFPE tissue sections for local processing were delivered to each partner site to be sequenced with the commercial gene panel and local bioinformatics. For cancer-specific panel-based sequencing, only centrally extracted DNA was analyzed at seven sequencing sites. Subsequently, local data were compiled and bioinformatics was performed centrally. We were able to demonstrate that all pre-characterized mutations were re-identified correctly, irrespective of NGS platform or gene panel used. However, locally processed FFPE tissue sections disclosed that the DNA extraction method can affect the detection of mutations with a trend in favor of magnetic bead-based DNA extraction methods. In conclusion, targeted NGS is a very robust method for simultaneous detection of various mutations in FFPE tissue specimens if certain pre-analytical conditions are carefully considered.

Structural performance of space station trusses with missing members

NASA Technical Reports Server (NTRS)

Dorsey, J. T.

1986-01-01

Structural performance of orthogonal tetrahedral and Warren-type full truss beams and platforms are compared. In addition, degradation of truss structural performance is determined for beams, platforms and a space station when individual struts are removed from the trusses. The truss beam, space station, and truss platform analytical models used in the studies are described. Stiffness degradation of the trusses due to single strut failures is determined using flexible body vibration modes. Ease of strut replacement is assessed by removing a strut and examining the truss deflection at the resulting gap due to applied forces. Finally, the reduction in truss beam strength due to a missing longeron is determined for a space station transverse boom model.

Metabolomics Characterization of U.S. and Japanese F-15 and C-130 Flight Line Crews Exposed to Jet Fuel Volatile Organic Compounds and Aerosols

DTIC Science & Technology

2014-09-30

resulted in the identification of metabolite patterns indicative of flight line exposure when compared to non -flight line control subjects...virtually non -invasive sample collection, minimal sample processing, robust and stable analytical platform, with excellent analytical and biological...identification of metabolite patterns indicative of flight line exposure when compared to non -flight line control subjects. Regardless of fuel (JP-4 or

Infrared Microspectroscopy: A Multiple-Screening Platform for Investigating Single-Cell Biochemical Perturbations upon Prion Infection

PubMed Central

2011-01-01

Prion diseases are a group of fatal neurodegenerative disorders characterized by the accumulation of prions in the central nervous system. The pathogenic prion (PrPSc) possesses the capability to convert the host-encoded cellular isoform of the prion protein, PrPC, into nascent PrPSc. The present work aims at providing novel insight into cellular response upon prion infection evidenced by synchrotron radiation infrared microspectroscopy (SR-IRMS). This non-invasive, label-free analytical technique was employed to investigate the biochemical perturbations undergone by prion infected mouse hypothalamic GT1-1 cells at the cellular and subcellular level. A decrement in total cellular protein content upon prion infection was identified by infrared (IR) whole-cell spectra and validated by bicinchoninic acid assay and single-cell volume analysis by atomic force microscopy (AFM). Hierarchical cluster analysis (HCA) of IR data discriminated between infected and uninfected cells and allowed to deduce an increment of lysosomal bodies within the cytoplasm of infected GT1-1 cells, a hypothesis further confirmed by SR-IRMS at subcellular spatial resolution and fluorescent microscopy. The purpose of this work, therefore, consists of proposing IRMS as a powerful multiscreening platform, drawing on the synergy with conventional biological assays and microscopy techniques in order to increase the accuracy of investigations performed at the single-cell level. PMID:22778865

Microfluidic Devices for Chemical and Biochemical Analysis in Microgravity

NASA Technical Reports Server (NTRS)

Roman, Gregory T.; Culbertson, Christopher T.; Meyer, Amanda; Ramsey, J. Michael; Gonda, Steven R.

2004-01-01

One often touted benefit of "Lab-on-a-Chip" devices is their potential for use in remote environments. The ultimate remote environment is outer space, and NASA has multiple needs in the area of analytical sensing capability in such an environment. In particular, we are interested in integrating microfluidic devices with NASA bioreactor systems. In such an integrated system, the microfluidic device will serve as a biosensor and be used for both feedback control and for detecting various bioproducts produced by cells cultured in the NASA bioreactors. As a first step in demonstrating the ability of microfluidic devices to operate under the extreme environmental conditions found in outer space, we constructed a portable, battery operated platform for testing under reduced gravity conditions on a NASA KC-135 reduced gravity research aircraft, (AKA "the vomit comet"). The test platform consisted of a microchip, two 0-8kV high voltage power supplies, a high voltage switch, a solid-state diode-pumped green laser, a channel photomultiplier, and an inertial mass measurement unit, all under the control of a laptop computer and powered by 10 D-cell alkaline batteries. Over the course of 4 KC-135 flights, 1817 fast electrophoretic separations of 4 amino acids and/or proteins were performed in a variety of gravitational environments including zero-G, Martian-G, lunar-G, and 2-G. Results from these experiments will be presented and discussed.

Infrared microspectroscopy: a multiple-screening platform for investigating single-cell biochemical perturbations upon prion infection.

PubMed

Didonna, Alessandro; Vaccari, Lisa; Bek, Alpan; Legname, Giuseppe

2011-03-16

Prion diseases are a group of fatal neurodegenerative disorders characterized by the accumulation of prions in the central nervous system. The pathogenic prion (PrP(Sc)) possesses the capability to convert the host-encoded cellular isoform of the prion protein, PrP(C), into nascent PrP(Sc). The present work aims at providing novel insight into cellular response upon prion infection evidenced by synchrotron radiation infrared microspectroscopy (SR-IRMS). This non-invasive, label-free analytical technique was employed to investigate the biochemical perturbations undergone by prion infected mouse hypothalamic GT1-1 cells at the cellular and subcellular level. A decrement in total cellular protein content upon prion infection was identified by infrared (IR) whole-cell spectra and validated by bicinchoninic acid assay and single-cell volume analysis by atomic force microscopy (AFM). Hierarchical cluster analysis (HCA) of IR data discriminated between infected and uninfected cells and allowed to deduce an increment of lysosomal bodies within the cytoplasm of infected GT1-1 cells, a hypothesis further confirmed by SR-IRMS at subcellular spatial resolution and fluorescent microscopy. The purpose of this work, therefore, consists of proposing IRMS as a powerful multiscreening platform, drawing on the synergy with conventional biological assays and microscopy techniques in order to increase the accuracy of investigations performed at the single-cell level.

Network-based drug discovery by integrating systems biology and computational technologies

PubMed Central

Leung, Elaine L.; Cao, Zhi-Wei; Jiang, Zhi-Hong; Zhou, Hua

2013-01-01

Network-based intervention has been a trend of curing systemic diseases, but it relies on regimen optimization and valid multi-target actions of the drugs. The complex multi-component nature of medicinal herbs may serve as valuable resources for network-based multi-target drug discovery due to its potential treatment effects by synergy. Recently, robustness of multiple systems biology platforms shows powerful to uncover molecular mechanisms and connections between the drugs and their targeting dynamic network. However, optimization methods of drug combination are insufficient, owning to lacking of tighter integration across multiple ‘-omics’ databases. The newly developed algorithm- or network-based computational models can tightly integrate ‘-omics’ databases and optimize combinational regimens of drug development, which encourage using medicinal herbs to develop into new wave of network-based multi-target drugs. However, challenges on further integration across the databases of medicinal herbs with multiple system biology platforms for multi-target drug optimization remain to the uncertain reliability of individual data sets, width and depth and degree of standardization of herbal medicine. Standardization of the methodology and terminology of multiple system biology and herbal database would facilitate the integration. Enhance public accessible databases and the number of research using system biology platform on herbal medicine would be helpful. Further integration across various ‘-omics’ platforms and computational tools would accelerate development of network-based drug discovery and network medicine. PMID:22877768

System and method for detecting components of a mixture including tooth elements for alignment

DOEpatents

Sommer, Gregory Jon; Schaff, Ulrich Y.

2016-11-22

Examples are described including assay platforms having tooth elements. An impinging element may sequentially engage tooth elements on the assay platform to sequentially align corresponding detection regions with a detection unit. In this manner, multiple measurements may be made of detection regions on the assay platform without necessarily requiring the starting and stopping of a motor.

Interlaboratory comparability, bias, and precision for four laboratories measuring constituents in precipitation, November 1982-August 1983

USGS Publications Warehouse

Brooks, M.H.; Schroder, L.J.; Malo, B.A.

1985-01-01

Four laboratories were evaluated in their analysis of identical natural and simulated precipitation water samples. Interlaboratory comparability was evaluated using analysis of variance coupled with Duncan 's multiple range test, and linear-regression models describing the relations between individual laboratory analytical results for natural precipitation samples. Results of the statistical analyses indicate that certain pairs of laboratories produce different results when analyzing identical samples. Analyte bias for each laboratory was examined using analysis of variance coupled with Duncan 's multiple range test on data produced by the laboratories from the analysis of identical simulated precipitation samples. Bias for a given analyte produced by a single laboratory has been indicated when the laboratory mean for that analyte is shown to be significantly different from the mean for the most-probable analyte concentrations in the simulated precipitation samples. Ion-chromatographic methods for the determination of chloride, nitrate, and sulfate have been compared with the colorimetric methods that were also in use during the study period. Comparisons were made using analysis of variance coupled with Duncan 's multiple range test for means produced by the two methods. Analyte precision for each laboratory has been estimated by calculating a pooled variance for each analyte. Analyte estimated precisions have been compared using F-tests and differences in analyte precisions for laboratory pairs have been reported. (USGS)

Single-Cell-Based Platform for Copy Number Variation Profiling through Digital Counting of Amplified Genomic DNA Fragments.

PubMed

Li, Chunmei; Yu, Zhilong; Fu, Yusi; Pang, Yuhong; Huang, Yanyi

2017-04-26

We develop a novel single-cell-based platform through digital counting of amplified genomic DNA fragments, named multifraction amplification (mfA), to detect the copy number variations (CNVs) in a single cell. Amplification is required to acquire genomic information from a single cell, while introducing unavoidable bias. Unlike prevalent methods that directly infer CNV profiles from the pattern of sequencing depth, our mfA platform denatures and separates the DNA molecules from a single cell into multiple fractions of a reaction mix before amplification. By examining the sequencing result of each fraction for a specific fragment and applying a segment-merge maximum likelihood algorithm to the calculation of copy number, we digitize the sequencing-depth-based CNV identification and thus provide a method that is less sensitive to the amplification bias. In this paper, we demonstrate a mfA platform through multiple displacement amplification (MDA) chemistry. When performing the mfA platform, the noise of MDA is reduced; therefore, the resolution of single-cell CNV identification can be improved to 100 kb. We can also determine the genomic region free of allelic drop-out with mfA platform, which is impossible for conventional single-cell amplification methods.

Permeation absorption sampler with multiple detection

DOEpatents

Zaromb, Solomon

1990-01-01

A system for detecting analytes in air or aqueous systems includes a permeation absorption preconcentrator sampler for the analytes and analyte detectors. The preconcentrator has an inner fluid-permeable container into which a charge of analyte-sorbing liquid is intermittently injected, and a fluid-impermeable outer container. The sample is passed through the outer container and around the inner container for trapping and preconcentrating the analyte in the sorbing liquid. The analyte can be detected photometrically by injecting with the sorbing material a reagent which reacts with the analyte to produce a characteristic color or fluorescence which is detected by illuminating the contents of the inner container with a light source and measuring the absorbed or emitted light, or by producing a characteristic chemiluminescence which can be detected by a suitable light sensor. The analyte can also be detected amperometrically. Multiple inner containers may be provided into which a plurality of sorbing liquids are respectively introduced for simultaneously detecting different analytes. Baffles may be provided in the outer container. A calibration technique is disclosed.

Polystyrene Core-Silica Shell Particles with Defined Nanoarchitectures as a Versatile Platform for Suspension Array Technology.

PubMed

Sarma, Dominik; Gawlitza, Kornelia; Rurack, Knut

2016-04-19

The need for rapid and high-throughput screening in analytical laboratories has led to significant growth in interest in suspension array technologies (SATs), especially with regard to cytometric assays targeting a low to medium number of analytes. Such SAT or bead-based assays rely on spherical objects that constitute the analytical platform. Usually, functionalized polymer or silica (SiO2) microbeads are used which each have distinct advantages and drawbacks. In this paper, we present a straightforward synthetic route to highly monodisperse SiO2-coated polystyrene core-shell (CS) beads for SAT with controllable architectures from smooth to raspberry- and multilayer-like shells by varying the molecular weight of poly(vinylpyrrolidone) (PVP), which was used as the stabilizer of the cores. The combination of both organic polymer core and a structurally controlled inorganic SiO2 shell in one hybrid particle holds great promises for flexible next-generation design of the spherical platform. The particles were characterized by electron microscopy (SEM, T-SEM, and TEM), thermogravimetry, flow cytometry, and nitrogen adsorption/desorption, offering comprehensive information on the composition, size, structure, and surface area. All particles show ideal cytometric detection patterns and facile handling due to the hybrid structure. The beads are endowed with straightforward modification possibilities through the defined SiO2 shells. We successfully implemented the particles in fluorometric SAT model assays, illustrating the benefits of tailored surface area which is readily available for small-molecule anchoring. Very promising assay performance was shown for DNA hybridization assays with quantification limits down to 8 fmol.

Analytical approach to determine vertical dynamics of a semi-trailer truck from the point of view of goods protection

NASA Astrophysics Data System (ADS)

Pidl, Renáta

2018-01-01

The overwhelming majority of intercontinental long-haul transportations of goods are usually carried out on road by semi-trailer trucks. Vibration has a major effect regarding the safety of the transport, the load and the transported goods. This paper deals with the logistics goals from the point of view of vibration and summarizes the methods to predict or measure the vibration load in order to design a proper system. From these methods, the focus of this paper is on the computer simulation of the vibration. An analytical method is presented to calculate the vertical dynamics of a semi-trailer truck containing general viscous damping and exposed to harmonic base excitation. For the purpose of a better understanding, the method will be presented through a simplified four degrees-of-freedom (DOF) half-vehicle model, which neglects the stiffness and damping of the tires, thus the four degrees-of-freedom are the vertical and angular displacements of the truck and the trailer. From the vertical and angular accelerations of the trailer, the vertical acceleration of each point of the platform of the trailer can easily be determined, from which the forces acting on the transported goods are given. As a result of this paper the response of the full platform-load-packaging system to any kind of vehicle, any kind of load and any kind of road condition can be analyzed. The peak acceleration of any point on the platform can be determined by the presented analytical method.

Concepts for a geostationary-like polar mission

NASA Astrophysics Data System (ADS)

Macdonald, Malcolm; Anderson, Pamela; Carrea, Laura; Dobke, Benjamin; Embury, Owen; Merchant, Chris; Bensi, Paolo

2014-10-01

An evidence-led scientific case for development of a space-based polar remote sensing platform at geostationary-like (GEO-like) altitudes is developed through methods including a data user survey. Whilst a GEO platform provides a nearstatic perspective, multiple platforms are required to provide circumferential coverage. Systems for achieving GEO-like polar observation likewise require multiple platforms however the perspective is non-stationery. A key choice is between designs that provide complete polar view from a single platform at any given instant, and designs where this is obtained by compositing partial views from multiple sensors. Users foresee an increased challenge in extracting geophysical information from composite images and consider the use of non-composited images advantageous. Users also find the placement of apogee over the pole to be preferable to the alternative scenarios. Thus, a clear majority of data users find the "Taranis" orbit concept to be better than a critical inclination orbit, due to the improved perspective offered. The geophysical products that would benefit from a GEO-like polar platform are mainly estimated from radiances in the visible/near infrared and thermal parts of the electromagnetic spectrum, which is consistent with currently proven technologies from GEO. Based on the survey results, needs analysis, and current technology proven from GEO, scientific and observation requirements are developed along with two instrument concepts with eight and four channels, based on Flexible Combined Imager heritage. It is found that an operational system could, mostly likely, be deployed from an Ariane 5 ES to a 16-hour orbit, while a proof-of-concept system could be deployed from a Soyuz launch to the same orbit.

Microfluidics Integrated Biosensors: A Leading Technology towards Lab-on-a-Chip and Sensing Applications

PubMed Central

Luka, George; Ahmadi, Ali; Najjaran, Homayoun; Alocilja, Evangelyn; DeRosa, Maria; Wolthers, Kirsten; Malki, Ahmed; Aziz, Hassan; Althani, Asmaa; Hoorfar, Mina

2015-01-01

A biosensor can be defined as a compact analytical device or unit incorporating a biological or biologically derived sensitive recognition element immobilized on a physicochemical transducer to measure one or more analytes. Microfluidic systems, on the other hand, provide throughput processing, enhance transport for controlling the flow conditions, increase the mixing rate of different reagents, reduce sample and reagents volume (down to nanoliter), increase sensitivity of detection, and utilize the same platform for both sample preparation and detection. In view of these advantages, the integration of microfluidic and biosensor technologies provides the ability to merge chemical and biological components into a single platform and offers new opportunities for future biosensing applications including portability, disposability, real-time detection, unprecedented accuracies, and simultaneous analysis of different analytes in a single device. This review aims at representing advances and achievements in the field of microfluidic-based biosensing. The review also presents examples extracted from the literature to demonstrate the advantages of merging microfluidic and biosensing technologies and illustrate the versatility that such integration promises in the future biosensing for emerging areas of biological engineering, biomedical studies, point-of-care diagnostics, environmental monitoring, and precision agriculture. PMID:26633409

Method development and qualification of capillary zone electrophoresis for investigation of therapeutic monoclonal antibody quality.

PubMed

Suba, Dávid; Urbányi, Zoltán; Salgó, András

2016-10-01

Capillary electrophoresis techniques are widely used in the analytical biotechnology. Different electrophoretic techniques are very adequate tools to monitor size-and charge heterogenities of protein drugs. Method descriptions and development studies of capillary zone electrophoresis (CZE) have been described in literature. Most of them are performed based on the classical one-factor-at-time (OFAT) approach. In this study a very simple method development approach is described for capillary zone electrophoresis: a "two-phase-four-step" approach is introduced which allows a rapid, iterative method development process and can be a good platform for CZE method. In every step the current analytical target profile and an appropriate control strategy were established to monitor the current stage of development. A very good platform was established to investigate intact and digested protein samples. Commercially available monoclonal antibody was chosen as model protein for the method development study. The CZE method was qualificated after the development process and the results were presented. The analytical system stability was represented by the calculated RSD% value of area percentage and migration time of the selected peaks (<0.8% and <5%) during the intermediate precision investigation. Copyright © 2016 Elsevier B.V. All rights reserved.

Big Data Analytics in Chemical Engineering.

PubMed

Chiang, Leo; Lu, Bo; Castillo, Ivan

2017-06-07

Big data analytics is the journey to turn data into insights for more informed business and operational decisions. As the chemical engineering community is collecting more data (volume) from different sources (variety), this journey becomes more challenging in terms of using the right data and the right tools (analytics) to make the right decisions in real time (velocity). This article highlights recent big data advancements in five industries, including chemicals, energy, semiconductors, pharmaceuticals, and food, and then discusses technical, platform, and culture challenges. To reach the next milestone in multiplying successes to the enterprise level, government, academia, and industry need to collaboratively focus on workforce development and innovation.

Control system design for the large space systems technology reference platform

NASA Technical Reports Server (NTRS)

Edmunds, R. S.

1982-01-01

Structural models and classical frequency domain control system designs were developed for the large space systems technology (LSST) reference platform which consists of a central bus structure, solar panels, and platform arms on which a variety of experiments may be mounted. It is shown that operation of multiple independently articulated payloads on a single platform presents major problems when subarc second pointing stability is required. Experiment compatibility will be an important operational consideration for systems of this type.

Multi-analyte profiling of inflammatory mediators in COPD sputum--the effects of processing.

PubMed

Pedersen, Frauke; Holz, Olaf; Lauer, Gereon; Quintini, Gianluca; Kiwull-Schöne, Heidrun; Kirsten, Anne-Marie; Magnussen, Helgo; Rabe, Klaus F; Goldmann, Torsten; Watz, Henrik

2015-02-01

Prior to using a new multi-analyte platform for the detection of markers in sputum it is advisable to assess whether sputum processing, especially mucus homogenization by dithiothreitol (DTT), affects the analysis. In this study we tested a novel Human Inflammation Multi Analyte Profiling® Kit (v1.0 Luminex platform; xMAP®). Induced sputum samples of 20 patients with stable COPD (mean FEV1, 59.2% pred.) were processed in parallel using standard processing (with DTT) and a more time consuming sputum dispersion method with phosphate buffered saline (PBS) only. A panel of 47 markers was analyzed in these sputum supernatants by the xMAP®. Twenty-five of 47 analytes have been detected in COPD sputum. Interestingly, 7 markers have been detected in sputum processed with DTT only, or significantly higher levels were observed following DTT treatment (VDBP, α-2-Macroglobulin, haptoglobin, α-1-antitrypsin, VCAM-1, and fibrinogen). However, standard DTT-processing resulted in lower detectable concentrations of ferritin, TIMP-1, MCP-1, MIP-1β, ICAM-1, and complement C3. The correlation between processing methods for the different markers indicates that DTT processing does not introduce a bias by affecting individual sputum samples differently. In conclusion, our data demonstrates that the Luminex-based xMAP® panel can be used for multi-analyte profiling of COPD sputum using the routinely applied method of sputum processing with DTT. However, researchers need to be aware that the absolute concentration of selected inflammatory markers can be affected by DTT. Copyright © 2014 Elsevier Ltd. All rights reserved.

Development of analytic intermodal freight networks for use within a GIS

DOT National Transportation Integrated Search

1997-05-01

The paper discusses the practical issues involved in constructing intermodal freight networks that can be used within GIS platforms to support inter-regional freight routing and subsequent (for example, commodity flow) analysis. The procedures descri...

Heating rates in furnace atomic absorption using the L'vov platform

USGS Publications Warehouse

Koirtyohann, S.R.; Giddings, R.C.; Taylor, Howard E.

1984-01-01

Heating rate profiles for the furnace tube wall, the furnace atmosphere, and a L'vov platform were established for a range of conditions in a cyclically heated graphite atomizer. The tube wall profile was made by direct observation with a recording optical pyrometer. The sodium line reversal method was used to establish the heating rate of the furnace atmosphere, and appearance temperatures for a series metals of differing volatility was used to establish platform profiles. The tube wall heating rate was nearly linear at 2240??C s- until the desired temperature was reached after which the temperature remained constant. The furnace atmosphere reached a given temperature 0.2-0.4 s later than the tube wall through most of the atomize cycle. The platform lagged the tube wall 0.5-0.8 s. Under typical operating conditions the furnace atmosphere was 100-200??C cooler than the tube wall and at nearly constant temperature when the analyte vaporized from the platform. The L'vov platform causes the cyclically heated commercial furnace to approximate the behavior of a constant temperature furnace during atomization. ?? 1984.

CISP: Simulation Platform for Collective Instabilities in the BRing of HIAF project

NASA Astrophysics Data System (ADS)

Liu, J.; Yang, J. C.; Xia, J. W.; Yin, D. Y.; Shen, G. D.; Li, P.; Zhao, H.; Ruan, S.; Wu, B.

2018-02-01

To simulate collective instabilities during the complicated beam manipulation in the BRing (Booster Ring) of HIAF (High Intensity heavy-ion Accelerator Facility) or other high intensity accelerators, a code, named CISP (Simulation Platform for Collective Instabilities), is designed and constructed in China's IMP (Institute of Modern Physics). The CISP is a scalable multi-macroparticle simulation platform that can perform longitudinal and transverse tracking when chromaticity, space charge effect, nonlinear magnets and wakes are included. And due to its well object-oriented design, the CISP is also a basic platform used to develop many other applications (like feedback). Several simulations, completed by the CISP in this paper, agree with analytical results very well, which shows that the CISP is fully functional now and it is a powerful platform for the further collective instability research in the BRing or other accelerators. In the future, the CISP can also be extended easily into a physics control system for HIAF or other facilities.

Nanopaper as an Optical Sensing Platform.

PubMed

Morales-Narváez, Eden; Golmohammadi, Hamed; Naghdi, Tina; Yousefi, Hossein; Kostiv, Uliana; Horák, Daniel; Pourreza, Nahid; Merkoçi, Arben

2015-07-28

Bacterial cellulose nanopaper (BC) is a multifunctional material known for numerous desirable properties: sustainability, biocompatibility, biodegradability, optical transparency, thermal properties, flexibility, high mechanical strength, hydrophilicity, high porosity, broad chemical-modification capabilities and high surface area. Herein, we report various nanopaper-based optical sensing platforms and describe how they can be tuned, using nanomaterials, to exhibit plasmonic or photoluminescent properties that can be exploited for sensing applications. We also describe several nanopaper configurations, including cuvettes, plates and spots that we printed or punched on BC. The platforms include a colorimetric-based sensor based on nanopaper containing embedded silver and gold nanoparticles; a photoluminescent-based sensor, comprising CdSe@ZnS quantum dots conjugated to nanopaper; and a potential up-conversion sensing platform constructed from nanopaper functionalized with NaYF4:Yb(3+)@Er(3+)&SiO2 nanoparticles. We have explored modulation of the plasmonic or photoluminescent properties of these platforms using various model biologically relevant analytes. Moreover, we prove that BC is and advantageous preconcentration platform that facilitates the analysis of small volumes of optically active materials (∼4 μL). We are confident that these platforms will pave the way to optical (bio)sensors or theranostic devices that are simple, transparent, flexible, disposable, lightweight, miniaturized and perhaps wearable.

An open source web interface for linking models to infrastructure system databases

NASA Astrophysics Data System (ADS)

Knox, S.; Mohamed, K.; Harou, J. J.; Rheinheimer, D. E.; Medellin-Azuara, J.; Meier, P.; Tilmant, A.; Rosenberg, D. E.

2016-12-01

Models of networked engineered resource systems such as water or energy systems are often built collaboratively with developers from different domains working at different locations. These models can be linked to large scale real world databases, and they are constantly being improved and extended. As the development and application of these models becomes more sophisticated, and the computing power required for simulations and/or optimisations increases, so has the need for online services and tools which enable the efficient development and deployment of these models. Hydra Platform is an open source, web-based data management system, which allows modellers of network-based models to remotely store network topology and associated data in a generalised manner, allowing it to serve multiple disciplines. Hydra Platform uses a web API using JSON to allow external programs (referred to as `Apps') to interact with its stored networks and perform actions such as importing data, running models, or exporting the networks to different formats. Hydra Platform supports multiple users accessing the same network and has a suite of functions for managing users and data. We present ongoing development in Hydra Platform, the Hydra Web User Interface, through which users can collaboratively manage network data and models in a web browser. The web interface allows multiple users to graphically access, edit and share their networks, run apps and view results. Through apps, which are located on the server, the web interface can give users access to external data sources and models without the need to install or configure any software. This also ensures model results can be reproduced by removing platform or version dependence. Managing data and deploying models via the web interface provides a way for multiple modellers to collaboratively manage data, deploy and monitor model runs and analyse results.

Specification Patent Management for Web Application Platform Ecosystem

NASA Astrophysics Data System (ADS)

Fukami, Yoshiaki; Isshiki, Masao; Takeda, Hideaki; Ohmukai, Ikki; Kokuryo, Jiro

Diversified usage of web applications has encouraged disintegration of web platform into management of identification and applications. Users make use of various kinds of data linked to their identity with multiple applications on certain social web platforms such as Facebook or MySpace. There has emerged competition among web application platforms. Platformers can design relationship with developers by controlling patent of their own specification and adopt open technologies developed external organizations. Platformers choose a way to open according to feature of the specification and their position. Patent management of specification come to be a key success factor to build competitive web application platforms. Each way to attract external developers such as standardization, open source has not discussed and analyzed all together.

The Clinical Relevance of Force Platform Measures in Multiple Sclerosis: A Review

PubMed Central

Prosperini, Luca; Pozzilli, Carlo

2013-01-01

Balance impairment and falls are frequent in patients with multiple sclerosis (PwMS), and they may occur even at the earliest stage of the disease and in minimally impaired patients. The introduction of computer-based force platform measures (i.e., static and dynamic posturography) has provided an objective and sensitive tool to document both deficits and improvements in balance. By using more challenging test conditions, force platform measures can also reveal subtle balance disorders undetectable by common clinical scales. Furthermore, posturographic techniques may also allow to reliably identify PwMS who are at risk of accidental falls. Although force platform measures offer several theoretical advantages, only few studies extensively investigated their role in better managing PwMS. Standardised procedures, as well as clinical relevance of changes detected by static or dynamic posturography, are still lacking. In this review, we summarized studies which investigated balance deficit by means of force platform measures, focusing on their ability in detecting patients at high risk of falls and in estimating rehabilitation-induced changes, highlighting the pros and the cons with respect to clinical scales. PMID:23766910

Screening Mammalian Cells on a Hydrogel: Functionalized Small Molecule Microarray.

PubMed

Zhu, Biwei; Jiang, Bo; Na, Zhenkun; Yao, Shao Q

2017-01-01

Mammalian cell-based microarray technology has gained wide attention, for its plethora of promising applications. The platform is able to provide simultaneous information on multiple parameters for a given target, or even multiple target proteins, in a complex biological system. Here we describe the preparation of mammalian cell-based microarrays using selectively captured of human prostate cancer cells (PC-3). This platform was then used in controlled drug release and measuring the associated drug effects on these cancer cells.

Registration and Fusion of Multiple Source Remotely Sensed Image Data

NASA Technical Reports Server (NTRS)

LeMoigne, Jacqueline

2004-01-01

Earth and Space Science often involve the comparison, fusion, and integration of multiple types of remotely sensed data at various temporal, radiometric, and spatial resolutions. Results of this integration may be utilized for global change analysis, global coverage of an area at multiple resolutions, map updating or validation of new instruments, as well as integration of data provided by multiple instruments carried on multiple platforms, e.g. in spacecraft constellations or fleets of planetary rovers. Our focus is on developing methods to perform fast, accurate and automatic image registration and fusion. General methods for automatic image registration are being reviewed and evaluated. Various choices for feature extraction, feature matching and similarity measurements are being compared, including wavelet-based algorithms, mutual information and statistically robust techniques. Our work also involves studies related to image fusion and investigates dimension reduction and co-kriging for application-dependent fusion. All methods are being tested using several multi-sensor datasets, acquired at EOS Core Sites, and including multiple sensors such as IKONOS, Landsat-7/ETM+, EO1/ALI and Hyperion, MODIS, and SeaWIFS instruments. Issues related to the coregistration of data from the same platform (i.e., AIRS and MODIS from Aqua) or from several platforms of the A-train (i.e., MLS, HIRDLS, OMI from Aura with AIRS and MODIS from Terra and Aqua) will also be considered.

Contemporary engagement with social media amongst hernia surgery specialists.

PubMed

Lui, D H; McDonald, J J; de Beaux, A; Tulloh, B; Brady, R R W

2017-08-01

Healthcare professional engagement is increasing. This study aims to identify levels of adoption and engagement of several social media platforms by a large international cohort of hernia surgery specialists. Hernia specialists attending the 38th International Congress of the European Hernia Society were identified. A manual search was then performed on Twitter, ResearchGate, and LinkedIn to identify those who had named accounts. Where accounts were identified, data on markers of utilisation were assessed. 759 surgeons (88.5% male) from 57 countries were identified. 334 surgeons (44%) engaged with a social media platform. 39 (5.1%) had Twitter accounts, 189 (24.9%) had ResearchGate accounts and 265 (34.9%) had LinkedIn accounts. 137 surgeons (18.1%) had accounts on 2 or more social media platforms. There was no gender association with social media account ownership (p > 0.05). Engagement in one social media platform was associated with increased engagement and utilisation on other platforms; LinkedIn users were more likely to have Twitter accounts (p < 0.001) and ResearchGate profiles (p < 0.001). Surgeons on all three SM platforms were more likely to have high markers of engagement across all SM platforms (multiple outcomes, p < 0.05). Geographical variation was noted with UK and South American Surgeons being more likely to be present on Twitter than their counterparts (p = 0.031). The level of engagement with social media amongst Hernia surgeons is similar to other surgical specialities. Geographical variation in SM engagement is seen. Engagement with one SM platform is associated with presence on multiple platforms.

Nonlinear Analyte Concentration Gradients for One-Step Kinetic Analysis Employing Optical Microring Resonators

PubMed Central

Marty, Michael T.; Kuhnline Sloan, Courtney D.; Bailey, Ryan C.; Sligar, Stephen G.

2012-01-01

Conventional methods to probe the binding kinetics of macromolecules at biosensor surfaces employ a stepwise titration of analyte concentrations and measure the association and dissociation to the immobilized ligand at each concentration level. It has previously been shown that kinetic rates can be measured in a single step by monitoring binding as the analyte concentration increases over time in a linear gradient. We report here the application of nonlinear analyte concentration gradients for determining kinetic rates and equilibrium binding affinities in a single experiment. A versatile nonlinear gradient maker is presented, which is easily applied to microfluidic systems. Simulations validate that accurate kinetic rates can be extracted for a wide range of association and dissociation rates, gradient slopes and curvatures, and with models for mass transport. The nonlinear analyte gradient method is demonstrated with a silicon photonic microring resonator platform to measure prostate specific antigen-antibody binding kinetics. PMID:22686186

Nonlinear analyte concentration gradients for one-step kinetic analysis employing optical microring resonators.

PubMed

Marty, Michael T; Sloan, Courtney D Kuhnline; Bailey, Ryan C; Sligar, Stephen G

2012-07-03

Conventional methods to probe the binding kinetics of macromolecules at biosensor surfaces employ a stepwise titration of analyte concentrations and measure the association and dissociation to the immobilized ligand at each concentration level. It has previously been shown that kinetic rates can be measured in a single step by monitoring binding as the analyte concentration increases over time in a linear gradient. We report here the application of nonlinear analyte concentration gradients for determining kinetic rates and equilibrium binding affinities in a single experiment. A versatile nonlinear gradient maker is presented, which is easily applied to microfluidic systems. Simulations validate that accurate kinetic rates can be extracted for a wide range of association and dissociation rates, gradient slopes, and curvatures, and with models for mass transport. The nonlinear analyte gradient method is demonstrated with a silicon photonic microring resonator platform to measure prostate specific antigen-antibody binding kinetics.

Metabolomics and Diabetes: Analytical and Computational Approaches

PubMed Central

Sas, Kelli M.; Karnovsky, Alla; Michailidis, George

2015-01-01

Diabetes is characterized by altered metabolism of key molecules and regulatory pathways. The phenotypic expression of diabetes and associated complications encompasses complex interactions between genetic, environmental, and tissue-specific factors that require an integrated understanding of perturbations in the network of genes, proteins, and metabolites. Metabolomics attempts to systematically identify and quantitate small molecule metabolites from biological systems. The recent rapid development of a variety of analytical platforms based on mass spectrometry and nuclear magnetic resonance have enabled identification of complex metabolic phenotypes. Continued development of bioinformatics and analytical strategies has facilitated the discovery of causal links in understanding the pathophysiology of diabetes and its complications. Here, we summarize the metabolomics workflow, including analytical, statistical, and computational tools, highlight recent applications of metabolomics in diabetes research, and discuss the challenges in the field. PMID:25713200

Are Higher Education Institutions Prepared for Learning Analytics?

ERIC Educational Resources Information Center

Ifenthaler, Dirk

2017-01-01

Higher education institutions and involved stakeholders can derive multiple benefits from learning analytics by using different data analytics strategies to produce summative, real-time, and predictive insights and recommendations. However, are institutions and academic as well as administrative staff prepared for learning analytics? A learning…

Recent Progress in Optical Biosensors Based on Smartphone Platforms

PubMed Central

Geng, Zhaoxin; Zhang, Xiong; Fan, Zhiyuan; Lv, Xiaoqing; Su, Yue; Chen, Hongda

2017-01-01

With a rapid improvement of smartphone hardware and software, especially complementary metal oxide semiconductor (CMOS) cameras, many optical biosensors based on smartphone platforms have been presented, which have pushed the development of the point-of-care testing (POCT). Imaging-based and spectrometry-based detection techniques have been widely explored via different approaches. Combined with the smartphone, imaging-based and spectrometry-based methods are currently used to investigate a wide range of molecular properties in chemical and biological science for biosensing and diagnostics. Imaging techniques based on smartphone-based microscopes are utilized to capture microscale analysts, while spectrometry-based techniques are used to probe reactions or changes of molecules. Here, we critically review the most recent progress in imaging-based and spectrometry-based smartphone-integrated platforms that have been developed for chemical experiments and biological diagnosis. We focus on the analytical performance and the complexity for implementation of the platforms. PMID:29068375

Pro-ana versus Pro-recovery: A Content Analytic Comparison of Social Media Users' Communication about Eating Disorders on Twitter and Tumblr.

PubMed

Branley, Dawn B; Covey, Judith

2017-01-01

Objectives: To compare how people communicate about eating disorders on two popular social media platforms - Twitter and Tumblr. Materials and Methods: Thematic analysis was conducted to characterize the types of communications posted, and a content analysis was undertaken of between-platform differences. Results: Three types of content (pro-ana, anti-ana, and pro-recovery) were posted on each platform. Overall, across both platforms, extreme pro-ana posts were in the minority compared to anti-ana and pro-recovery. Pro-ana posts (including 'thinspiration') were more common on Twitter than Tumblr, whereas anti-ana and pro-recovery posts were more common on Tumblr. Conclusion: The findings have implications for future research and health care relating to the treatment and prevention of eating disorders. Developers of future interventions targeting negative pro-ana content should remain aware of the need to avoid any detrimental impact on positive online support.

Recent Progress in Optical Biosensors Based on Smartphone Platforms.

PubMed

Geng, Zhaoxin; Zhang, Xiong; Fan, Zhiyuan; Lv, Xiaoqing; Su, Yue; Chen, Hongda

2017-10-25

With a rapid improvement of smartphone hardware and software, especially complementary metal oxide semiconductor (CMOS) cameras, many optical biosensors based on smartphone platforms have been presented, which have pushed the development of the point-of-care testing (POCT). Imaging-based and spectrometry-based detection techniques have been widely explored via different approaches. Combined with the smartphone, imaging-based and spectrometry-based methods are currently used to investigate a wide range of molecular properties in chemical and biological science for biosensing and diagnostics. Imaging techniques based on smartphone-based microscopes are utilized to capture microscale analysts, while spectrometry-based techniques are used to probe reactions or changes of molecules. Here, we critically review the most recent progress in imaging-based and spectrometry-based smartphone-integrated platforms that have been developed for chemical experiments and biological diagnosis. We focus on the analytical performance and the complexity for implementation of the platforms.

Micropillar arrays as a high-throughput screening platform for therapeutics in multiple sclerosis.

PubMed

Mei, Feng; Fancy, Stephen P J; Shen, Yun-An A; Niu, Jianqin; Zhao, Chao; Presley, Bryan; Miao, Edna; Lee, Seonok; Mayoral, Sonia R; Redmond, Stephanie A; Etxeberria, Ainhoa; Xiao, Lan; Franklin, Robin J M; Green, Ari; Hauser, Stephen L; Chan, Jonah R

2014-08-01

Functional screening for compounds that promote remyelination represents a major hurdle in the development of rational therapeutics for multiple sclerosis. Screening for remyelination is problematic, as myelination requires the presence of axons. Standard methods do not resolve cell-autonomous effects and are not suited for high-throughput formats. Here we describe a binary indicant for myelination using micropillar arrays (BIMA). Engineered with conical dimensions, micropillars permit resolution of the extent and length of membrane wrapping from a single two-dimensional image. Confocal imaging acquired from the base to the tip of the pillars allows for detection of concentric wrapping observed as 'rings' of myelin. The platform is formatted in 96-well plates, amenable to semiautomated random acquisition and automated detection and quantification. Upon screening 1,000 bioactive molecules, we identified a cluster of antimuscarinic compounds that enhance oligodendrocyte differentiation and remyelination. Our findings demonstrate a new high-throughput screening platform for potential regenerative therapeutics in multiple sclerosis.

Anomalous acoustic dispersion in architected microlattice metamaterials

NASA Astrophysics Data System (ADS)

KröDel, Sebastian; Palermo, Antonio; Daraio, Chiara

The ability to control dispersion in acoustic metamaterials is crucial to realize acoustic filtering and rectification devices as well as perfect imaging using negative refractive index materials. Architected microlattice metamaterials immersed in fluid constitute a versatile platform for achieving such control. We investigate architected microlattice materials able to exploit locally resonant modes of their fundamental building blocks that couple with propagating acoustic waves. Using analytical, numerical and experimental methods we find that such lattice materials show a hybrid dispersion behavior governed by Biot's theory for long wavelengths and multiple scattering theory when wave frequency is close to the resonances of the building block. We identify the relevant geometric parameters to alter and control the group and phase velocities in this class of acoustic metamaterials. Furthermore, we fabricate small-scale acoustic metamaterial samples using high precision SLA additive manufacturing and test the resulting materials experimentally using a customized ultrasonic setup. This work paves the way for new acoustic devices based on microlattice metamaterials.

Practical Applications of Digital Pathology.

PubMed

Saeed-Vafa, Daryoush; Magliocco, Anthony M

2015-04-01

Virtual microscopy and advances in machine learning have paved the way for the ever-expanding field of digital pathology. Multiple image-based computing environments capable of performing automated quantitative and morphological analyses are the foundation on which digital pathology is built. The applications for digital pathology in the clinical setting are numerous and are explored along with the digital software environments themselves, as well as the different analytical modalities specific to digital pathology. Prospective studies, case-control analyses, meta-analyses, and detailed descriptions of software environments were explored that pertained to digital pathology and its use in the clinical setting. Many different software environments have advanced platforms capable of improving digital pathology and potentially influencing clinical decisions. The potential of digital pathology is vast, particularly with the introduction of numerous software environments available for use. With all the digital pathology tools available as well as those in development, the field will continue to advance, particularly in the era of personalized medicine, providing health care professionals with more precise prognostic information as well as helping them guide treatment decisions.

Conversion of multiple analyte cation types to a single analyte anion type via ion/ion charge inversion.

PubMed

Hassell, Kerry M; LeBlanc, Yves; McLuckey, Scott A

2009-11-01

Charge inversion ion/ion reactions can convert several cation types associated with a single analyte molecule to a single anion type for subsequent mass analysis. Specifically, analyte ions present with one of a variety of cationizing agents, such as an excess proton, excess sodium ion, or excess potassium ion, can all be converted to the deprotonated molecule, provided that a stable anion can be generated for the analyte. Multiply deprotonated species that are capable of exchanging a proton for a metal ion serve as the reagent anions for the reaction. This process is demonstrated here for warfarin and for a glutathione conjugate. Examples for several other glutathione conjugates are provided as supplementary material to demonstrate the generality of the reaction. In the case of glutathione conjugates, multiple metal ions can be associated with the singly-charged analyte due to the presence of two carboxylate groups. The charge inversion reaction involves the removal of the excess cationizing agent, as well as any metal ions associated with anionic groups to yield a singly deprotonated analyte molecule. The ability to convert multiple cation types to a single anion type is analytically desirable in cases in which the analyte signal is distributed among several cation types, as is common in the electrospray ionization of solutions with relatively high salt contents. For analyte species that undergo efficient charge inversion, such as glutathione conjugates, there is the additional potential advantage for significantly improved signal-to-noise ratios when species that give rise to 'chemical noise' in the positive ion spectrum do not undergo efficient charge inversion.

Mass spectrometric directed system for the continuous-flow synthesis and purification of diphenhydramine† †Electronic supplementary information (ESI) available: NMR spectra of selected product, mass spectra of selected products, crystallization information, and experimental procedures are supplied. See DOI: 10.1039/c7sc00905d Click here for additional data file.

PubMed Central

Loren, Bradley P.; Wleklinski, Michael; Koswara, Andy; Yammine, Kathryn; Hu, Yanyang

2017-01-01

A highly integrated approach to the development of a process for the continuous synthesis and purification of diphenhydramine is reported. Mass spectrometry (MS) is utilized throughout the system for on-line reaction monitoring, off-line yield quantitation, and as a reaction screening module that exploits reaction acceleration in charged microdroplets for high throughput route screening. This effort has enabled the discovery and optimization of multiple routes to diphenhydramine in glass microreactors using MS as a process analytical tool (PAT). The ability to rapidly screen conditions in charged microdroplets was used to guide optimization of the process in a microfluidic reactor. A quantitative MS method was developed and used to measure the reaction kinetics. Integration of the continuous-flow reactor/on-line MS methodology with a miniaturized crystallization platform for continuous reaction monitoring and controlled crystallization of diphenhydramine was also achieved. Our findings suggest a robust approach for the continuous manufacture of pharmaceutical drug products, exemplified in the particular case of diphenhydramine, and optimized for efficiency and crystal size, and guided by real-time analytics to produce the agent in a form that is readily adapted to continuous synthesis. PMID:28979759

A fluorescence-based centrifugal microfluidic system for parallel detection of multiple allergens

NASA Astrophysics Data System (ADS)

Chen, Q. L.; Ho, H. P.; Cheung, K. L.; Kong, S. K.; Suen, Y. K.; Kwan, Y. W.; Li, W. J.; Wong, C. K.

2010-02-01

This paper reports a robust polymer based centrifugal microfluidic analysis system that can provide parallel detection of multiple allergens in vitro. Many commercial food products (milk, bean, pollen, etc.) may introduce allergy to people. A low-cost device for rapid detection of allergens is highly desirable. With this as the objective, we have studied the feasibility of using a rotating disk device incorporating centrifugal microfluidics for performing actuationfree and multi-analyte detection of different allergen species with minimum sample usage and fast response time. Degranulation in basophils or mast cells is an indicator to demonstrate allergic reaction. In this connection, we used acridine orange (AO) to demonstrate degranulation in KU812 human basophils. It was found that the AO was released from granules when cells were stimulated by ionomycin, thus signifying the release of histamine which accounts for allergy symptoms [1-2]. Within this rotating optical platform, major microfluidic components including sample reservoirs, reaction chambers, microchannel and flow-control compartments are integrated into a single bio-compatible polydimethylsiloxane (PDMS) substrate. The flow sequence and reaction time can be controlled precisely. Sequentially through varying the spinning speed, the disk may perform a variety of steps on sample loading, reaction and detection. Our work demonstrates the feasibility of using centrifugation as a possible immunoassay system in the future.

ePlant: Visualizing and Exploring Multiple Levels of Data for Hypothesis Generation in Plant Biology[OPEN

PubMed Central

Waese, Jamie; Fan, Jim; Yu, Hans; Fucile, Geoffrey; Shi, Ruian; Cumming, Matthew; Town, Chris; Stuerzlinger, Wolfgang

2017-01-01

A big challenge in current systems biology research arises when different types of data must be accessed from separate sources and visualized using separate tools. The high cognitive load required to navigate such a workflow is detrimental to hypothesis generation. Accordingly, there is a need for a robust research platform that incorporates all data and provides integrated search, analysis, and visualization features through a single portal. Here, we present ePlant (http://bar.utoronto.ca/eplant), a visual analytic tool for exploring multiple levels of Arabidopsis thaliana data through a zoomable user interface. ePlant connects to several publicly available web services to download genome, proteome, interactome, transcriptome, and 3D molecular structure data for one or more genes or gene products of interest. Data are displayed with a set of visualization tools that are presented using a conceptual hierarchy from big to small, and many of the tools combine information from more than one data type. We describe the development of ePlant in this article and present several examples illustrating its integrative features for hypothesis generation. We also describe the process of deploying ePlant as an “app” on Araport. Building on readily available web services, the code for ePlant is freely available for any other biological species research. PMID:28808136

PACOM: A Versatile Tool for Integrating, Filtering, Visualizing, and Comparing Multiple Large Mass Spectrometry Proteomics Data Sets.

PubMed

Martínez-Bartolomé, Salvador; Medina-Aunon, J Alberto; López-García, Miguel Ángel; González-Tejedo, Carmen; Prieto, Gorka; Navajas, Rosana; Salazar-Donate, Emilio; Fernández-Costa, Carolina; Yates, John R; Albar, Juan Pablo

2018-04-06

Mass-spectrometry-based proteomics has evolved into a high-throughput technology in which numerous large-scale data sets are generated from diverse analytical platforms. Furthermore, several scientific journals and funding agencies have emphasized the storage of proteomics data in public repositories to facilitate its evaluation, inspection, and reanalysis. (1) As a consequence, public proteomics data repositories are growing rapidly. However, tools are needed to integrate multiple proteomics data sets to compare different experimental features or to perform quality control analysis. Here, we present a new Java stand-alone tool, Proteomics Assay COMparator (PACOM), that is able to import, combine, and simultaneously compare numerous proteomics experiments to check the integrity of the proteomic data as well as verify data quality. With PACOM, the user can detect source of errors that may have been introduced in any step of a proteomics workflow and that influence the final results. Data sets can be easily compared and integrated, and data quality and reproducibility can be visually assessed through a rich set of graphical representations of proteomics data features as well as a wide variety of data filters. Its flexibility and easy-to-use interface make PACOM a unique tool for daily use in a proteomics laboratory. PACOM is available at https://github.com/smdb21/pacom .

Phytozome Comparative Plant Genomics Portal

DOE Office of Scientific and Technical Information (OSTI.GOV)

Goodstein, David; Batra, Sajeev; Carlson, Joseph

2014-09-09

The Dept. of Energy Joint Genome Institute is a genomics user facility supporting DOE mission science in the areas of Bioenergy, Carbon Cycling, and Biogeochemistry. The Plant Program at the JGI applies genomic, analytical, computational and informatics platforms and methods to: 1. Understand and accelerate the improvement (domestication) of bioenergy crops 2. Characterize and moderate plant response to climate change 3. Use comparative genomics to identify constrained elements and infer gene function 4. Build high quality genomic resource platforms of JGI Plant Flagship genomes for functional and experimental work 5. Expand functional genomic resources for Plant Flagship genomes

Experimental design and multiple response optimization. Using the desirability function in analytical methods development.

PubMed

Candioti, Luciana Vera; De Zan, María M; Cámara, María S; Goicoechea, Héctor C

2014-06-01

A review about the application of response surface methodology (RSM) when several responses have to be simultaneously optimized in the field of analytical methods development is presented. Several critical issues like response transformation, multiple response optimization and modeling with least squares and artificial neural networks are discussed. Most recent analytical applications are presented in the context of analytLaboratorio de Control de Calidad de Medicamentos (LCCM), Facultad de Bioquímica y Ciencias Biológicas, Universidad Nacional del Litoral, C.C. 242, S3000ZAA Santa Fe, ArgentinaLaboratorio de Control de Calidad de Medicamentos (LCCM), Facultad de Bioquímica y Ciencias Biológicas, Universidad Nacional del Litoral, C.C. 242, S3000ZAA Santa Fe, Argentinaical methods development, especially in multiple response optimization procedures using the desirability function. Copyright © 2014 Elsevier B.V. All rights reserved.

Opening Health Data: What Do Researchers Want? Early Experiences With New York's Open Health Data Platform.

PubMed

Martin, Erika G; Helbig, Natalie; Birkhead, Guthrie S

2015-01-01

Governments are rapidly developing open data platforms to improve transparency and make information more accessible. New York is a leader, with currently the only state platform devoted to health. Although these platforms could build public health departments' capabilities to serve more researchers, agencies have little guidance on releasing meaningful and usable data. Structured focus groups with researchers and practitioners collected stakeholder feedback on potential uses of open health data and New York's open data strategy. Researchers and practitioners attended a 1-day November 2013 workshop on New York State's open health data resources. After learning about the state's open data platform and vision for open health data, participants were organized into 7 focus groups to discuss the essential elements of open data sets, practical challenges to obtaining and using health data, and potential uses of open data. Participants included 33 quantitative health researchers from State University of New York campuses and private partners and 10 practitioners from the New York State Department of Health. There was low awareness of open data, with 67% of researchers reporting never using open data portals prior to the workshop. Participants were interested in data sets that were geocoded, longitudinal, or aggregated to small area granularity and capabilities to link multiple data sets. Multiple environmental conditions and barriers hinder their capacity to use health data for research. Although open data platforms cannot address all barriers, they provide multiple opportunities for public health research and practice, and participants were overall positive about the state's efforts to release open data. Open data are not ideal for some researchers because they do not contain individually identifiable data, indicating a need for tiered data release strategies. However, they do provide important new opportunities to facilitate research and foster collaborations among agencies, researchers, and practitioners.

Proactive Time-Rearrangement Scheme for Multi-Radio Collocated Platform

NASA Astrophysics Data System (ADS)

Kim, Chul; Shin, Sang-Heon; Park, Sang Kyu

We present a simple proactive time rearrangement scheme (PATRA) that reduces the interferences from multi-radio devices equipped in one platform and guarantees user-conceived QoS. Simulation results show that the interference among multiple radios in one platform causes severe performance degradation and cannot guarantee the user requested QoS. However, the PATRA can dramatically improve not only the userconceived QoS but also the overall network throughput.

Anisotropic transport of normal metal-barrier-normal metal junctions in monolayer phosphorene.

PubMed

De Sarkar, Sangita; Agarwal, Amit; Sengupta, K

2017-07-19

We study transport properties of a phosphorene monolayer in the presence of single and multiple potential barriers of height U 0 and width d, using both continuum and microscopic lattice models, and show that the nature of electron transport along its armchair edge (x direction) is qualitatively different from its counterpart in both conventional two-dimensional electron gas with Schrödinger-like quasiparticles and graphene or surfaces of topological insulators hosting massless Dirac quasiparticles. We show that the transport, mediated by massive Dirac electrons, allows one to achieve collimated quasiparticle motion along x and thus makes monolayer phosphorene an ideal experimental platform for studying Klein paradox in the context of gapped Dirac materials. We study the dependence of the tunneling conductance [Formula: see text] as a function of d and U 0 , and demonstrate that for a given applied voltage V its behavior changes from oscillatory to decaying function of d for a range of U 0 with finite non-zero upper and lower bounds, and provide analytical expression for these bounds within which G decays with d. We contrast such behavior of G with that of massless Dirac electrons in graphene and also with that along the zigzag edge (y direction) in phosphorene where the quasiparticles obey an effective Schrödinger equation at low energy. We also study transport through multiple barriers along x and demonstrate that these properties hold for transport through multiple barriers as well. Finally, we suggest concrete experiments which may verify our theoretical predictions.

Integration and Visualization of Translational Medicine Data for Better Understanding of Human Diseases

PubMed Central

Satagopam, Venkata; Gu, Wei; Eifes, Serge; Gawron, Piotr; Ostaszewski, Marek; Gebel, Stephan; Barbosa-Silva, Adriano; Balling, Rudi; Schneider, Reinhard

2016-01-01

Abstract Translational medicine is a domain turning results of basic life science research into new tools and methods in a clinical environment, for example, as new diagnostics or therapies. Nowadays, the process of translation is supported by large amounts of heterogeneous data ranging from medical data to a whole range of -omics data. It is not only a great opportunity but also a great challenge, as translational medicine big data is difficult to integrate and analyze, and requires the involvement of biomedical experts for the data processing. We show here that visualization and interoperable workflows, combining multiple complex steps, can address at least parts of the challenge. In this article, we present an integrated workflow for exploring, analysis, and interpretation of translational medicine data in the context of human health. Three Web services—tranSMART, a Galaxy Server, and a MINERVA platform—are combined into one big data pipeline. Native visualization capabilities enable the biomedical experts to get a comprehensive overview and control over separate steps of the workflow. The capabilities of tranSMART enable a flexible filtering of multidimensional integrated data sets to create subsets suitable for downstream processing. A Galaxy Server offers visually aided construction of analytical pipelines, with the use of existing or custom components. A MINERVA platform supports the exploration of health and disease-related mechanisms in a contextualized analytical visualization system. We demonstrate the utility of our workflow by illustrating its subsequent steps using an existing data set, for which we propose a filtering scheme, an analytical pipeline, and a corresponding visualization of analytical results. The workflow is available as a sandbox environment, where readers can work with the described setup themselves. Overall, our work shows how visualization and interfacing of big data processing services facilitate exploration, analysis, and interpretation of translational medicine data. PMID:27441714

SMA-MAP: a plasma protein panel for spinal muscular atrophy.

PubMed

Kobayashi, Dione T; Shi, Jing; Stephen, Laurie; Ballard, Karri L; Dewey, Ruth; Mapes, James; Chung, Brett; McCarthy, Kathleen; Swoboda, Kathryn J; Crawford, Thomas O; Li, Rebecca; Plasterer, Thomas; Joyce, Cynthia; Chung, Wendy K; Kaufmann, Petra; Darras, Basil T; Finkel, Richard S; Sproule, Douglas M; Martens, William B; McDermott, Michael P; De Vivo, Darryl C; Walker, Michael G; Chen, Karen S

2013-01-01

Spinal Muscular Atrophy (SMA) presents challenges in (i) monitoring disease activity and predicting progression, (ii) designing trials that allow rapid assessment of candidate therapies, and (iii) understanding molecular causes and consequences of the disease. Validated biomarkers of SMA motor and non-motor function would offer utility in addressing these challenges. Our objectives were (i) to discover additional markers from the Biomarkers for SMA (BforSMA) study using an immunoassay platform, and (ii) to validate the putative biomarkers in an independent cohort of SMA patients collected from a multi-site natural history study (NHS). BforSMA study plasma samples (N = 129) were analyzed by immunoassay to identify new analytes correlating to SMA motor function. These immunoassays included the strongest candidate biomarkers identified previously by chromatography. We selected 35 biomarkers to validate in an independent cohort SMA type 1, 2, and 3 samples (N = 158) from an SMA NHS. The putative biomarkers were tested for association to multiple motor scales and to pulmonary function, neurophysiology, strength, and quality of life measures. We implemented a Tobit model to predict SMA motor function scores. 12 of the 35 putative SMA biomarkers were significantly associated (p<0.05) with motor function, with a 13(th) analyte being nearly significant. Several other analytes associated with non-motor SMA outcome measures. From these 35 biomarkers, 27 analytes were selected for inclusion in a commercial panel (SMA-MAP) for association with motor and other functional measures. Discovery and validation using independent cohorts yielded a set of SMA biomarkers significantly associated with motor function and other measures of SMA disease activity. A commercial SMA-MAP biomarker panel was generated for further testing in other SMA collections and interventional trials. Future work includes evaluating the panel in other neuromuscular diseases, for pharmacodynamic responsiveness to experimental SMA therapies, and for predicting functional changes over time in SMA patients.

ANALYTICAL SOLUTIONS OF THE ATMOSPHERIC DIFFUSION EQUATION WITH MULTIPLE SOURCES AND HEIGHT-DEPENDENT WIND SPEED AND EDDY DIFFUSIVITIES. (R825689C072)

EPA Science Inventory

Abstract

Three-dimensional analytical solutions of the atmospheric diffusion equation with multiple sources and height-dependent wind speed and eddy diffusivities are derived in a systematic fashion. For homogeneous Neumann (total reflection), Dirichlet (total adsorpti...

ANALYTICAL SOLUTIONS OF THE ATMOSPHERIC DIFFUSION EQUATION WITH MULTIPLE SOURCES AND HEIGHT-DEPENDENT WIND SPEED AND EDDY DIFFUSIVITIES. (R825689C048)

EPA Science Inventory

Abstract

Three-dimensional analytical solutions of the atmospheric diffusion equation with multiple sources and height-dependent wind speed and eddy diffusivities are derived in a systematic fashion. For homogeneous Neumann (total reflection), Dirichlet (total adsorpti...

Using Distributed Data over HBase in Big Data Analytics Platform for Clinical Services

PubMed Central

Zamani, Hamid

2017-01-01

Big data analytics (BDA) is important to reduce healthcare costs. However, there are many challenges of data aggregation, maintenance, integration, translation, analysis, and security/privacy. The study objective to establish an interactive BDA platform with simulated patient data using open-source software technologies was achieved by construction of a platform framework with Hadoop Distributed File System (HDFS) using HBase (key-value NoSQL database). Distributed data structures were generated from benchmarked hospital-specific metadata of nine billion patient records. At optimized iteration, HDFS ingestion of HFiles to HBase store files revealed sustained availability over hundreds of iterations; however, to complete MapReduce to HBase required a week (for 10 TB) and a month for three billion (30 TB) indexed patient records, respectively. Found inconsistencies of MapReduce limited the capacity to generate and replicate data efficiently. Apache Spark and Drill showed high performance with high usability for technical support but poor usability for clinical services. Hospital system based on patient-centric data was challenging in using HBase, whereby not all data profiles were fully integrated with the complex patient-to-hospital relationships. However, we recommend using HBase to achieve secured patient data while querying entire hospital volumes in a simplified clinical event model across clinical services. PMID:29375652

Using Distributed Data over HBase in Big Data Analytics Platform for Clinical Services.

PubMed

Chrimes, Dillon; Zamani, Hamid

2017-01-01

Big data analytics (BDA) is important to reduce healthcare costs. However, there are many challenges of data aggregation, maintenance, integration, translation, analysis, and security/privacy. The study objective to establish an interactive BDA platform with simulated patient data using open-source software technologies was achieved by construction of a platform framework with Hadoop Distributed File System (HDFS) using HBase (key-value NoSQL database). Distributed data structures were generated from benchmarked hospital-specific metadata of nine billion patient records. At optimized iteration, HDFS ingestion of HFiles to HBase store files revealed sustained availability over hundreds of iterations; however, to complete MapReduce to HBase required a week (for 10 TB) and a month for three billion (30 TB) indexed patient records, respectively. Found inconsistencies of MapReduce limited the capacity to generate and replicate data efficiently. Apache Spark and Drill showed high performance with high usability for technical support but poor usability for clinical services. Hospital system based on patient-centric data was challenging in using HBase, whereby not all data profiles were fully integrated with the complex patient-to-hospital relationships. However, we recommend using HBase to achieve secured patient data while querying entire hospital volumes in a simplified clinical event model across clinical services.

Analytical investigation of the dynamics of tethered constellations in earth orbit

NASA Technical Reports Server (NTRS)

Lorenzini, Enrico C.; Gullahorn, Gordon E.; Estes, Robert D.

1988-01-01

This Quarterly Report on Tethering in Earth Orbit deals with three topics: (1) Investigation of the propagation of longitudinal and transverse waves along the upper tether. Specifically, the upper tether is modeled as three massive platforms connected by two perfectly elastic continua (tether segments). The tether attachment point to the station is assumed to vibrate both longitudinally and transversely at a given frequency. Longitudinal and transverse waves propagate along the tethers affecting the acceleration levels at the elevator and at the upper platform. The displacement and acceleration frequency-response functions at the elevator and at the upper platform are computed for both longitudinal and transverse waves. An analysis to optimize the damping time of the longitudinal dampers is also carried out in order to select optimal parameters. The analytical evaluation of the performance of tuned vs. detuned longitudinal dampers is also part of this analysis. (2) The use of the Shuttle primary Reaction Control System (RCS) thrusters for blowing away a recoiling broken tether is discussed. A microcomputer system was set up to support this operation. (3) Most of the effort in the tether plasma physics study was devoted to software development. A particle simulation code has been integrated into the Macintosh II computer system and will be utilized for studying the physics of hollow cathodes.

Multiple wavelength silicon photonic 200 mm R+D platform for 25Gb/s and above applications

NASA Astrophysics Data System (ADS)

Szelag, B.; Blampey, B.; Ferrotti, T.; Reboud, V.; Hassan, K.; Malhouitre, S.; Grand, G.; Fowler, D.; Brision, S.; Bria, T.; Rabillé, G.; Brianceau, P.; Hartmann, J. M.; Hugues, V.; Myko, A.; Elleboode, F.; Gays, F.; Fédéli, J. M.; Kopp, C.

2016-05-01

A silicon photonics platform that uses a CMOS foundry line is described. Fabrication process is following a modular integration scheme which leads to a flexible platform, allowing different device combinations. A complete device library is demonstrated for 1310 nm applications with state of the art performances. A PDK which includes specific photonic features and which is compatible with commercial EDA tools has been developed allowing an MPW shuttle service. Finally platform evolutions such as device offer extension to 1550 nm or new process modules introduction are presented.

On the multiple zeros of a real analytic function with applications to the averaging theory of differential equations

NASA Astrophysics Data System (ADS)

García, Isaac A.; Llibre, Jaume; Maza, Susanna

2018-06-01

In this work we consider real analytic functions , where , Ω is a bounded open subset of , is an interval containing the origin, are parameters, and ε is a small parameter. We study the branching of the zero-set of at multiple points when the parameter ε varies. We apply the obtained results to improve the classical averaging theory for computing T-periodic solutions of λ-families of analytic T-periodic ordinary differential equations defined on , using the displacement functions defined by these equations. We call the coefficients in the Taylor expansion of in powers of ε the averaged functions. The main contribution consists in analyzing the role that have the multiple zeros of the first non-zero averaged function. The outcome is that these multiple zeros can be of two different classes depending on whether the zeros belong or not to the analytic set defined by the real variety associated to the ideal generated by the averaged functions in the Noetheriang ring of all the real analytic functions at . We bound the maximum number of branches of isolated zeros that can bifurcate from each multiple zero z 0. Sometimes these bounds depend on the cardinalities of minimal bases of the former ideal. Several examples illustrate our results and they are compared with the classical theory, branching theory and also under the light of singularity theory of smooth maps. The examples range from polynomial vector fields to Abel differential equations and perturbed linear centers.

Analytical technologies for influenza virus-like particle candidate vaccines: challenges and emerging approaches

PubMed Central

2013-01-01

Influenza virus-like particle vaccines are one of the most promising ways to respond to the threat of future influenza pandemics. VLPs are composed of viral antigens but lack nucleic acids making them non-infectious which limit the risk of recombination with wild-type strains. By taking advantage of the advancements in cell culture technologies, the process from strain identification to manufacturing has the potential to be completed rapidly and easily at large scales. After closely reviewing the current research done on influenza VLPs, it is evident that the development of quantification methods has been consistently overlooked. VLP quantification at all stages of the production process has been left to rely on current influenza quantification methods (i.e. Hemagglutination assay (HA), Single Radial Immunodiffusion assay (SRID), NA enzymatic activity assays, Western blot, Electron Microscopy). These are analytical methods developed decades ago for influenza virions and final bulk influenza vaccines. Although these methods are time-consuming and cumbersome they have been sufficient for the characterization of final purified material. Nevertheless, these analytical methods are impractical for in-line process monitoring because VLP concentration in crude samples generally falls out of the range of detection for these methods. This consequently impedes the development of robust influenza-VLP production and purification processes. Thus, development of functional process analytical techniques, applicable at every stage during production, that are compatible with different production platforms is in great need to assess, optimize and exploit the full potential of novel manufacturing platforms. PMID:23642219

Mechanical and Electronic Approaches to Improve the Sensitivity of Microcantilever Sensors

PubMed Central

Mutyala, Madhu Santosh Ku; Bandhanadham, Deepika; Pan, Liu; Pendyala, Vijaya Rohini; Ji, Hai-Feng

2010-01-01

Advances in the field of Micro Electro Mechanical Systems (MEMS) and their uses now offer unique opportunities in the design of ultrasensitive analytical tools. The analytical community continues to search for cost-effective, reliable, and even portable analytical techniques that can give reliable and fast response results for a variety of chemicals and biomolecules. Microcantilevers (MCLs) have emerged as a unique platform for label-free biosensor or bioassay. Several electronic designs, including piezoresistive, piezoelectric, and capacitive approaches, have been applied to measure the bending or frequency change of the MCLs upon exposure to chemicals. This review summarizes mechanical, fabrication, and electronics approaches to increase the sensitivity of microcantilever (MCL) sensors. PMID:20975987

Blended Learning: An Evolving Praxis

ERIC Educational Resources Information Center

Fogal, Gary G.; Graham, Floyd H., III.; Lavigne, Anthony G.

2014-01-01

TED (Technology Entertainment Design), a collection of regularly updated talks, offers a web-based platform that is easily accessible. This platform affords language learners across multiple proficiency levels an opportunity to develop autonomy and critical thinking skills alongside their second language (L2) development. With an international…

Simulation Platform: a cloud-based online simulation environment.

PubMed

Yamazaki, Tadashi; Ikeno, Hidetoshi; Okumura, Yoshihiro; Satoh, Shunji; Kamiyama, Yoshimi; Hirata, Yutaka; Inagaki, Keiichiro; Ishihara, Akito; Kannon, Takayuki; Usui, Shiro

2011-09-01

For multi-scale and multi-modal neural modeling, it is needed to handle multiple neural models described at different levels seamlessly. Database technology will become more important for these studies, specifically for downloading and handling the neural models seamlessly and effortlessly. To date, conventional neuroinformatics databases have solely been designed to archive model files, but the databases should provide a chance for users to validate the models before downloading them. In this paper, we report our on-going project to develop a cloud-based web service for online simulation called "Simulation Platform". Simulation Platform is a cloud of virtual machines running GNU/Linux. On a virtual machine, various software including developer tools such as compilers and libraries, popular neural simulators such as GENESIS, NEURON and NEST, and scientific software such as Gnuplot, R and Octave, are pre-installed. When a user posts a request, a virtual machine is assigned to the user, and the simulation starts on that machine. The user remotely accesses to the machine through a web browser and carries out the simulation, without the need to install any software but a web browser on the user's own computer. Therefore, Simulation Platform is expected to eliminate impediments to handle multiple neural models that require multiple software. Copyright © 2011 Elsevier Ltd. All rights reserved.

Reprint of: Simulation Platform: a cloud-based online simulation environment.

PubMed

Yamazaki, Tadashi; Ikeno, Hidetoshi; Okumura, Yoshihiro; Satoh, Shunji; Kamiyama, Yoshimi; Hirata, Yutaka; Inagaki, Keiichiro; Ishihara, Akito; Kannon, Takayuki; Usui, Shiro

2011-11-01

For multi-scale and multi-modal neural modeling, it is needed to handle multiple neural models described at different levels seamlessly. Database technology will become more important for these studies, specifically for downloading and handling the neural models seamlessly and effortlessly. To date, conventional neuroinformatics databases have solely been designed to archive model files, but the databases should provide a chance for users to validate the models before downloading them. In this paper, we report our on-going project to develop a cloud-based web service for online simulation called "Simulation Platform". Simulation Platform is a cloud of virtual machines running GNU/Linux. On a virtual machine, various software including developer tools such as compilers and libraries, popular neural simulators such as GENESIS, NEURON and NEST, and scientific software such as Gnuplot, R and Octave, are pre-installed. When a user posts a request, a virtual machine is assigned to the user, and the simulation starts on that machine. The user remotely accesses to the machine through a web browser and carries out the simulation, without the need to install any software but a web browser on the user's own computer. Therefore, Simulation Platform is expected to eliminate impediments to handle multiple neural models that require multiple software. Copyright © 2011 Elsevier Ltd. All rights reserved.

Reconfigurable microfluidic hanging drop network for multi-tissue interaction and analysis.

PubMed

Frey, Olivier; Misun, Patrick M; Fluri, David A; Hengstler, Jan G; Hierlemann, Andreas

2014-06-30

Integration of multiple three-dimensional microtissues into microfluidic networks enables new insights in how different organs or tissues of an organism interact. Here, we present a platform that extends the hanging-drop technology, used for multi-cellular spheroid formation, to multifunctional complex microfluidic networks. Engineered as completely open, 'hanging' microfluidic system at the bottom of a substrate, the platform features high flexibility in microtissue arrangements and interconnections, while fabrication is simple and operation robust. Multiple spheroids of different cell types are formed in parallel on the same platform; the different tissues are then connected in physiological order for multi-tissue experiments through reconfiguration of the fluidic network. Liquid flow is precisely controlled through the hanging drops, which enable nutrient supply, substance dosage and inter-organ metabolic communication. The possibility to perform parallelized microtissue formation on the same chip that is subsequently used for complex multi-tissue experiments renders the developed platform a promising technology for 'body-on-a-chip'-related research.

Database and Analytical Tool Development for the Management of Data Derived from US DOE (NETL) Funded Fine Particulate (PM2.5) Research

DOE Office of Scientific and Technical Information (OSTI.GOV)

Robinson Khosah

2007-07-31

Advanced Technology Systems, Inc. (ATS) was contracted by the U. S. Department of Energy's National Energy Technology Laboratory (DOE-NETL) to develop a state-of-the-art, scalable and robust web-accessible database application to manage the extensive data sets resulting from the DOE-NETL-sponsored ambient air monitoring programs in the upper Ohio River valley region. The data management system was designed to include a web-based user interface that will allow easy access to the data by the scientific community, policy- and decision-makers, and other interested stakeholders, while providing detailed information on sampling, analytical and quality control parameters. In addition, the system will provide graphical analyticalmore » tools for displaying, analyzing and interpreting the air quality data. The system will also provide multiple report generation capabilities and easy-to-understand visualization formats that can be utilized by the media and public outreach/educational institutions. The project was conducted in two phases. Phase One included the following tasks: (1) data inventory/benchmarking, including the establishment of an external stakeholder group; (2) development of a data management system; (3) population of the database; (4) development of a web-based data retrieval system, and (5) establishment of an internal quality assurance/quality control system on data management. Phase Two involved the development of a platform for on-line data analysis. Phase Two included the following tasks: (1) development of a sponsor and stakeholder/user website with extensive online analytical tools; (2) development of a public website; (3) incorporation of an extensive online help system into each website; and (4) incorporation of a graphical representation (mapping) system into each website. The project is now technically completed.« less

Polysialylated N-Glycans Identified in Human Serum Through Combined Developments in Sample Preparation, Separations and Electrospray ionization-mass spectrometry

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kronewitter, Scott R.; Marginean, Ioan; Cox, Jonathan T.

The N-glycan diversity of human serum glycoproteins, i.e. the human blood serum N-glycome, is complex due to the range of glycan structures potentially synthesizable by human glycosylation enzymes. The reported glycome, however, is limited by methods of sample preparation, available analytical platforms, e.g., based upon electrospray ionization-mass spectrometry (ESI-MS), and software tools for data analysis. In this report, several improvements have been implemented in sample preparation and analysis to extend ESI-MS glycan characterization and to provide an improved view of glycan diversity. Sample preparation improvements include acidified, microwave-accelerated, PNGase F N-glycan release, and sodium borohydride reduction were optimized to improvemore » quantitative yields and conserve the number of glycoforms detected. Two-stage desalting (during solid phase extraction and on the analytical column) increased the sensitivity by reducing analyte signal division between multiple reducing-end-forms or cation adducts. On-line separations were improved by using extended length graphitized carbon columns and adding TFA as an acid modifier to a formic acid/reversed phase gradient which provides additional resolving power and significantly improved desorption of both large and heavily sialylated glycans. To improve MS sensitivity and provide gentler ionization conditions at the source-MS interface, subambient pressure ionization with nanoelectrospray (SPIN) has been utilized. When method improvements are combined together with the Glycomics Quintavariate Informed Quantification (GlyQ-IQ) recently described1 these technologies demonstrate the ability to significantly extend glycan detection sensitivity and provide expanded glycan coverage. We demonstrate application of these advances in the context of the human serum glycome, and for which our initial observations include detection of a new class of heavily sialylated N-glycans, including polysialylated N-glycans.« less

Preliminary Validation of Direct Detection of Foot-And-Mouth Disease Virus within Clinical Samples Using Reverse Transcription Loop-Mediated Isothermal Amplification Coupled with a Simple Lateral Flow Device for Detection

PubMed Central

Waters, Ryan A.; Fowler, Veronica L.; Armson, Bryony; Nelson, Noel; Gloster, John; Paton, David J.; King, Donald P.

2014-01-01

Rapid, field-based diagnostic assays are desirable tools for the control of foot-and-mouth disease (FMD). Current approaches involve either; 1) Detection of FMD virus (FMDV) with immuochromatographic antigen lateral flow devices (LFD), which have relatively low analytical sensitivity, or 2) portable RT-qPCR that has high analytical sensitivity but is expensive. Loop-mediated isothermal amplification (LAMP) may provide a platform upon which to develop field based assays without these drawbacks. The objective of this study was to modify an FMDV-specific reverse transcription–LAMP (RT-LAMP) assay to enable detection of dual-labelled LAMP products with an LFD, and to evaluate simple sample processing protocols without nucleic acid extraction. The limit of detection of this assay was demonstrated to be equivalent to that of a laboratory based real-time RT-qPCR assay and to have a 10,000 fold higher analytical sensitivity than the FMDV-specific antigen LFD currently used in the field. Importantly, this study demonstrated that FMDV RNA could be detected from epithelial suspensions without the need for prior RNA extraction, utilising a rudimentary heat source for amplification. Once optimised, this RT-LAMP-LFD protocol was able to detect multiple serotypes from field epithelial samples, in addition to detecting FMDV in the air surrounding infected cattle, pigs and sheep, including pre-clinical detection. This study describes the development and evaluation of an assay format, which may be used as a future basis for rapid and low cost detection of FMDV. In addition it provides providing “proof of concept” for the future use of LAMP assays to tackle other challenging diagnostic scenarios encompassing veterinary and human health. PMID:25165973

Space assembly fixtures and aids

NASA Technical Reports Server (NTRS)

Bloom, K. A.; Lillenas, A. N.

1980-01-01

Concepts and requirements for assembly fixtures and aids necessary for the assembly and maintenance of spare platforms were studied. Emphasis was placed on erectable and deployable type structures with the shuttle orbiter as the assembly base. Both single and multiple orbiter flight cases for the platform assembly were considered. Applicable space platform assembly studies were reviewed to provide a data base for establishing the assembly fixture and aids design requirements, assembly constraints, and the development of representative design concepts. Conclusions indicated that fixture requirements will vary with platform size. Larger platforms will require translation relative to the orbiter RMS working volume. The installation of platform payloads and subsystems (e.g., utility distribution) must also be considered in the specification of assembly fixtures and aids.

Geostationary platform systems concepts definition study. Volume 1: Executive summary

NASA Technical Reports Server (NTRS)

1980-01-01

The results of a geostationary platform concept analysis are summarized. Mission and payloads definition, concept selection, the requirements of an experimental platform, supporting research and technology, and the Space Transportation System interface requirements are addressed. It is concluded that platforms represent a logical extension of current trends toward larger, more complex, multifrequency satellites. Geostationary platforms offer significant cost savings compared to individual satellites, with the majority of these economies being realized with single Shuttle launched platforms. Further cost savings can be realized, however, by having larger platforms. Platforms accommodating communications equipment that operates at multiple frequencies and which provide larger scale frequency reuse through the use of large aperture multibeam antennas and onboard switching maximize the useful capacity of the orbital arc and frequency spectrum. Projections of market demand indicate that such conservation measures are clearly essential if orderly growth is to be provided for. In addition, it is pointed out that a NASA experimental platform is required to demonstrate the technologies necessary for operational geostationary platforms of the 1990's.

Electron Injections: A Study of Electron Acceleration by Multiple Dipolarizing Flux Bundles Using an Analytical Model

NASA Astrophysics Data System (ADS)

Gabrielse, C.; Angelopoulos, V.; Artemyev, A.; Runov, A.; Harris, C.

2016-12-01

We study energetic electron injections using an analytical model that self-consistently describes electric and magnetic field perturbations of transient, localized dipolarizing flux bundles (DFBs). Previous studies using THEMIS, Van Allen Probes, and the Magnetospheric Multiscale Mission have shown that injections can occur on short (minutes) or long (10s of minutes) timescales. These studies suggest that the short timescale injections correspond to a single DFB, whereas long timescale injections are likely caused by an aggregate of multiple DFBs, each incrementally heating the particle population. We therefore model the effects of multiple DFBs on the electron population using multi-spacecraft observations of the fields and particle fluxes to constrain the model parameters. The analytical model is the first of its kind to model multiple dipolarization fronts in order to better understand the transport and acceleration process throughout the plasma sheet. It can reproduce most injection signatures at multiple locations simultaneously, reaffirming earlier findings that multiple earthward-traveling DFBs can both transport and accelerate electrons to suprathermal energies, and can thus be considered the injections' primary driver.

Thiolene and SIFEL-based Microfluidic Platforms for Liquid-Liquid Extraction

PubMed Central

Goyal, Sachit; Desai, Amit V.; Lewis, Robert W.; Ranganathan, David R.; Li, Hairong; Zeng, Dexing; Reichert, David E.; Kenis, Paul J.A.

2014-01-01

Microfluidic platforms provide several advantages for liquid-liquid extraction (LLE) processes over conventional methods, for example with respect to lower consumption of solvents and enhanced extraction efficiencies due to the inherent shorter diffusional distances. Here, we report the development of polymer-based parallel-flow microfluidic platforms for LLE. To date, parallel-flow microfluidic platforms have predominantly been made out of silicon or glass due to their compatibility with most organic solvents used for LLE. Fabrication of silicon and glass-based LLE platforms typically requires extensive use of photolithography, plasma or laser-based etching, high temperature (anodic) bonding, and/or wet etching with KOH or HF solutions. In contrast, polymeric microfluidic platforms can be fabricated using less involved processes, typically photolithography in combination with replica molding, hot embossing, and/or bonding at much lower temperatures. Here we report the fabrication and testing of microfluidic LLE platforms comprised of thiolene or a perfluoropolyether-based material, SIFEL, where the choice of materials was mainly guided by the need for solvent compatibility and fabrication amenability. Suitable designs for polymer-based LLE platforms that maximize extraction efficiencies within the constraints of the fabrication methods and feasible operational conditions were obtained using analytical modeling. To optimize the performance of the polymer-based LLE platforms, we systematically studied the effect of surface functionalization and of microstructures on the stability of the liquid-liquid interface and on the ability to separate the phases. As demonstrative examples, we report (i) a thiolene-based platform to determine the lipophilicity of caffeine, and (ii) a SIFEL-based platform to extract radioactive copper from an acidic aqueous solution. PMID:25246730

An Integrated Framework for Effective and Efficient Communication with Families in the Adult Intensive Care Unit.

PubMed

Seaman, Jennifer B; Arnold, Robert M; Scheunemann, Leslie P; White, Douglas B

2017-06-01

The increased focus on patient and family-centered care in adult intensive care units (ICUs) has generated multiple platforms for clinician-family communication beyond traditional interdisciplinary family meetings (family meetings)-including family-centered rounds, bedside or telephone updates, and electronic family portals. Some clinicians and administrators are now using these platforms instead of conducting family meetings. For example, some institutions are moving toward using family-centered rounds as the main platform for clinician-family communication, and some physicians rely on brief daily updates to the family at the bedside or by phone, in lieu of family meetings. We argue that although each of these platforms is useful in some circumstances, there remains an important role for family meetings. We outline five goals of clinician-family communication-establishing trust, providing emotional support, conveying clinical information, understanding the patient as a person, and facilitating careful decision making-and we examine the extent to which various communication platforms are likely to achieve the goals. We argue that because no single platform can achieve all communication goals, an integrated strategy is needed. We present a model that integrates multiple communication platforms to effectively and efficiently support families across the arc of an ICU stay. Our framework employs bedside/telephone conversations and family-centered rounds throughout the admission to address high informational needs, along with well-timed family meetings that attend to families' emotions as well as patients' values and goals. This flexible model uses various communication platforms to achieve consistent, efficient communication throughout the ICU stay.

An Integrated Framework for Effective and Efficient Communication with Families in the Adult Intensive Care Unit

PubMed Central

Arnold, Robert M.; Scheunemann, Leslie P.; White, Douglas B.

2017-01-01

The increased focus on patient and family-centered care in adult intensive care units (ICUs) has generated multiple platforms for clinician–family communication beyond traditional interdisciplinary family meetings (family meetings)—including family-centered rounds, bedside or telephone updates, and electronic family portals. Some clinicians and administrators are now using these platforms instead of conducting family meetings. For example, some institutions are moving toward using family-centered rounds as the main platform for clinician–family communication, and some physicians rely on brief daily updates to the family at the bedside or by phone, in lieu of family meetings. We argue that although each of these platforms is useful in some circumstances, there remains an important role for family meetings. We outline five goals of clinician–family communication—establishing trust, providing emotional support, conveying clinical information, understanding the patient as a person, and facilitating careful decision making—and we examine the extent to which various communication platforms are likely to achieve the goals. We argue that because no single platform can achieve all communication goals, an integrated strategy is needed. We present a model that integrates multiple communication platforms to effectively and efficiently support families across the arc of an ICU stay. Our framework employs bedside/telephone conversations and family-centered rounds throughout the admission to address high informational needs, along with well-timed family meetings that attend to families’ emotions as well as patients’ values and goals. This flexible model uses various communication platforms to achieve consistent, efficient communication throughout the ICU stay. PMID:28282227

Incomplete Intelligence: Is the Information Sharing Environment an Effective Platform?

DTIC Science & Technology

2012-09-01

Initiative NYFD New York Fire Department NYPD New York Police Department OLAP On Line Analytics Processing OSINT Open Source Intelligence...Intelligence ( OSINT ), from public websites, media sources, and other unclassified events and reports. Although some of these sources do not have a direct

Droplet-based biosensing for lab-on-a-chip, open microfluidics platforms

USDA-ARS?s Scientific Manuscript database

Low cost, portable sensors can transform health care by bringing easily available diagnostic devices to low and middle income population, particularly in developing countries. Sample preparation, analyte handling and labeling are primary cost concerns for traditional lab-based diagnostic systems. La...

Infiltrated photonic crystal cavity as a highly sensitive platform for glucose concentration detection

NASA Astrophysics Data System (ADS)

Arafa, Safia; Bouchemat, Mohamed; Bouchemat, Touraya; Benmerkhi, Ahlem; Hocini, Abdesselam

2017-02-01

A Bio-sensing platform based on an infiltrated photonic crystal ring shaped holes cavity-coupled waveguide system is proposed for glucose concentration detection. Considering silicon-on-insulator (SOI) technology, it has been demonstrated that the ring shaped holes configuration provides an excellent optical confinement within the cavity region, which further enhances the light-matter interactions at the precise location of the analyte medium. Thus, the sensitivity and the quality factor (Q) can be significantly improved. The transmission characteristics of light in the biosensor under different refractive indices that correspond to the change in the analyte glucose concentration are analyzed by performing finite-difference time-domain (FDTD) simulations. Accordingly, an improved sensitivity of 462 nm/RIU and a Q factor as high as 1.11х105 have been achieved, resulting in a detection limit of 3.03х10-6 RIU. Such combination of attributes makes the designed structure a promising element for performing label-free biosensing in medical diagnosis and environmental monitoring.

NMR and MS Methods for Metabolomics.

PubMed

Amberg, Alexander; Riefke, Björn; Schlotterbeck, Götz; Ross, Alfred; Senn, Hans; Dieterle, Frank; Keck, Matthias

2017-01-01

Metabolomics, also often referred as "metabolic profiling," is the systematic profiling of metabolites in biofluids or tissues of organisms and their temporal changes. In the last decade, metabolomics has become more and more popular in drug development, molecular medicine, and other biotechnology fields, since it profiles directly the phenotype and changes thereof in contrast to other "-omics" technologies. The increasing popularity of metabolomics has been possible only due to the enormous development in the technology and bioinformatics fields. In particular, the analytical technologies supporting metabolomics, i.e., NMR, UPLC-MS, and GC-MS, have evolved into sensitive and highly reproducible platforms allowing the determination of hundreds of metabolites in parallel. This chapter describes the best practices of metabolomics as seen today. All important steps of metabolic profiling in drug development and molecular medicine are described in great detail, starting from sample preparation to determining the measurement details of all analytical platforms, and finally to discussing the corresponding specific steps of data analysis.

NMR and MS methods for metabonomics.

PubMed

Dieterle, Frank; Riefke, Björn; Schlotterbeck, Götz; Ross, Alfred; Senn, Hans; Amberg, Alexander

2011-01-01

Metabonomics, also often referred to as "metabolomics" or "metabolic profiling," is the systematic profiling of metabolites in bio-fluids or tissues of organisms and their temporal changes. In the last decade, metabonomics has become increasingly popular in drug development, molecular medicine, and other biotechnology fields, since it profiles directly the phenotype and changes thereof in contrast to other "-omics" technologies. The increasing popularity of metabonomics has been possible only due to the enormous development in the technology and bioinformatics fields. In particular, the analytical technologies supporting metabonomics, i.e., NMR, LC-MS, UPLC-MS, and GC-MS have evolved into sensitive and highly reproducible platforms allowing the determination of hundreds of metabolites in parallel. This chapter describes the best practices of metabonomics as seen today. All important steps of metabolic profiling in drug development and molecular medicine are described in great detail, starting from sample preparation, to determining the measurement details of all analytical platforms, and finally, to discussing the corresponding specific steps of data analysis.

VASA: Interactive Computational Steering of Large Asynchronous Simulation Pipelines for Societal Infrastructure.

PubMed

Ko, Sungahn; Zhao, Jieqiong; Xia, Jing; Afzal, Shehzad; Wang, Xiaoyu; Abram, Greg; Elmqvist, Niklas; Kne, Len; Van Riper, David; Gaither, Kelly; Kennedy, Shaun; Tolone, William; Ribarsky, William; Ebert, David S

2014-12-01

We present VASA, a visual analytics platform consisting of a desktop application, a component model, and a suite of distributed simulation components for modeling the impact of societal threats such as weather, food contamination, and traffic on critical infrastructure such as supply chains, road networks, and power grids. Each component encapsulates a high-fidelity simulation model that together form an asynchronous simulation pipeline: a system of systems of individual simulations with a common data and parameter exchange format. At the heart of VASA is the Workbench, a visual analytics application providing three distinct features: (1) low-fidelity approximations of the distributed simulation components using local simulation proxies to enable analysts to interactively configure a simulation run; (2) computational steering mechanisms to manage the execution of individual simulation components; and (3) spatiotemporal and interactive methods to explore the combined results of a simulation run. We showcase the utility of the platform using examples involving supply chains during a hurricane as well as food contamination in a fast food restaurant chain.

An Analytic Model for the Success Rate of a Robotic Actuator System in Hitting Random Targets.

PubMed

Bradley, Stuart

2015-11-20

Autonomous robotic systems are increasingly being used in a wide range of applications such as precision agriculture, medicine, and the military. These systems have common features which often includes an action by an "actuator" interacting with a target. While simulations and measurements exist for the success rate of hitting targets by some systems, there is a dearth of analytic models which can give insight into, and guidance on optimization, of new robotic systems. The present paper develops a simple model for estimation of the success rate for hitting random targets from a moving platform. The model has two main dimensionless parameters: the ratio of actuator spacing to target diameter; and the ratio of platform distance moved (between actuator "firings") to the target diameter. It is found that regions of parameter space having specified high success are described by simple equations, providing guidance on design. The role of a "cost function" is introduced which, when minimized, provides optimization of design, operating, and risk mitigation costs.

Decision Support Model for Introduction of Gamification Solution Using AHP

PubMed Central

2014-01-01

Gamification means the use of various elements of game design in nongame contexts including workplace collaboration, marketing, education, military, and medical services. Gamification is effective for both improving workplace productivity and motivating employees. However, introduction of gamification is not easy because the planning and implementation processes of gamification are very complicated and it needs interdisciplinary knowledge such as information systems, organization behavior, and human psychology. Providing a systematic decision making method for gamification process is the purpose of this paper. This paper suggests the decision criteria for selection of gamification platform to support a systematic decision making process for managements. The criteria are derived from previous works on gamification, introduction of information systems, and analytic hierarchy process. The weights of decision criteria are calculated through a survey by the professionals on game, information systems, and business administration. The analytic hierarchy process is used to derive the weights. The decision criteria and weights provided in this paper could support the managements to make a systematic decision for selection of gamification platform. PMID:24892075

Decision support model for introduction of gamification solution using AHP.

PubMed

Kim, Sangkyun

2014-01-01

Gamification means the use of various elements of game design in nongame contexts including workplace collaboration, marketing, education, military, and medical services. Gamification is effective for both improving workplace productivity and motivating employees. However, introduction of gamification is not easy because the planning and implementation processes of gamification are very complicated and it needs interdisciplinary knowledge such as information systems, organization behavior, and human psychology. Providing a systematic decision making method for gamification process is the purpose of this paper. This paper suggests the decision criteria for selection of gamification platform to support a systematic decision making process for managements. The criteria are derived from previous works on gamification, introduction of information systems, and analytic hierarchy process. The weights of decision criteria are calculated through a survey by the professionals on game, information systems, and business administration. The analytic hierarchy process is used to derive the weights. The decision criteria and weights provided in this paper could support the managements to make a systematic decision for selection of gamification platform.

Platform construction and extraction mechanism study of magnetic mixed hemimicelles solid-phase extraction

NASA Astrophysics Data System (ADS)

Xiao, Deli; Zhang, Chan; He, Jia; Zeng, Rong; Chen, Rong; He, Hua

2016-12-01

Simple, accurate and high-throughput pretreatment method would facilitate large-scale studies of trace analysis in complex samples. Magnetic mixed hemimicelles solid-phase extraction has the power to become a key pretreatment method in biological, environmental and clinical research. However, lacking of experimental predictability and unsharpness of extraction mechanism limit the development of this promising method. Herein, this work tries to establish theoretical-based experimental designs for extraction of trace analytes from complex samples using magnetic mixed hemimicelles solid-phase extraction. We selected three categories and six sub-types of compounds for systematic comparative study of extraction mechanism, and comprehensively illustrated the roles of different force (hydrophobic interaction, π-π stacking interactions, hydrogen-bonding interaction, electrostatic interaction) for the first time. What’s more, the application guidelines for supporting materials, surfactants and sample matrix were also summarized. The extraction mechanism and platform established in the study render its future promising for foreseeable and efficient pretreatment under theoretical based experimental design for trace analytes from environmental, biological and clinical samples.

An Enhanced Platform to Analyse Low-Affinity Amyloid β Protein by Integration of Electrical Detection and Preconcentrator.

PubMed

Yoo, Yong Kyoung; Yoon, Dae Sung; Kim, Gangeun; Kim, Jinsik; Han, Sung Il; Lee, Junwoo; Chae, Myung-Sic; Lee, Sang-Myung; Lee, Kyu Hyoung; Hwang, Kyo Seon; Lee, Jeong Hoon

2017-10-30

Sensitivity and limit of detection (LOD) enhancement are essential criteria for the development of ultrasensitive molecular sensors. Although various sensor types have been investigated to enhance sensitivity and LOD, analyte detection and its quantification are still challenging, particularly for protein-protein interactions with low association constants. To solve this problem, here, we used ion concentration polarization (ICP)-based preconcentration to increase the local concentration of analytes in a microfluidic platform for LOD improvement. This was the first demonstration of a microfluidic device with an integrated ICP preconcentrator and interdigitated microelectrode (IME) sensor to detect small changes in surface binding between antigens and antibodies. We detected the amyloid beta (Aβ) protein, an Alzheimer's disease marker, with low binding affinity to its antibodies by adopting ICP preconcentration phenomena. We demonstrated that a combination of ICP preconcentrator and IME sensor increased the LOD by 13.8-fold to femtomolar level (8.15 fM), which corresponds to a significant advance for clinical applications.

Electrokinetic Sample Preconcentration and Hydrodynamic Sample Injection for Microchip Electrophoresis Using a Pneumatic Microvalve

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cong, Yongzheng; Katipamula, Shanta; Geng, Tao

2016-02-01

A microfluidic platform was developed to perform online electrokinetic sample preconcentration and rapid hydrodynamic sample injection for electrophoresis using a single microvalve. The PDMS microchip consists of a separation channel, a side channel for sample introduction, and a control channel which is used as a pneumatic microvalve aligned at the intersection of the two flow channels. The closed microvalve, created by multilayer soft lithography, can serve as a preconcentrator under an applied electric potential, enabling current to pass through while blocking bulk flow. Once analytes are concentrated, the valve is briefly opened and the stacked sample is pressure injected intomore » the separation channel for electrophoretic separation. Fluorescently labeled peptides were enriched by a factor of ~450 in 230 s. The performance of the platform was validated by the online preconcentration, injection and electrophoretic separation of fluorescently labeled peptides. This method enables both rapid analyte concentration and controlled injection volume for high sensitivity, high resolution capillary electrophoresis.« less

Group specific internal standard technology (GSIST) for simultaneous identification and quantification of small molecules

DOEpatents

Adamec, Jiri; Yang, Wen-Chu; Regnier, Fred E

2014-01-14

Reagents and methods are provided that permit simultaneous analysis of multiple diverse small molecule analytes present in a complex mixture. Samples are labeled with chemically identical but isotopically distince forms of the labeling reagent, and analyzed using mass spectrometry. A single reagent simultaneously derivatizes multiple small molecule analytes having different reactive functional groups.

Detection of trace explosives on relevant substrates using a mobile platform for photothermal infrared imaging spectroscopy (PT-IRIS)

NASA Astrophysics Data System (ADS)

Kendziora, Christopher A.; Furstenberg, Robert; Papantonakis, Michael; Nguyen, Viet; Byers, Jeff; McGill, R. Andrew

2015-05-01

This manuscript describes the results of recent tests regarding standoff detection of trace explosives on relevant substrates using a mobile platform. We are developing a technology for detection based on photo-thermal infrared (IR) imaging spectroscopy (PT-IRIS). This approach leverages one or more microfabricated IR quantum cascade lasers, tuned to strong absorption bands in the analytes and directed to illuminate an area on a surface of interest. An IR focal plane array is used to image the surface thermal emission upon laser illumination. The PT-IRIS signal is processed as a hyperspectral image cube comprised of spatial, spectral and temporal dimensions as vectors within a detection algorithm. Increased sensitivity to explosives and selectivity between different analyte types is achieved by narrow bandpass IR filters in the collection path. We have previously demonstrated the technique at several meters of stand-off distance indoors and in field tests, while operating the lasers below the infrared eye-safe intensity limit (100 mW/cm2). Sensitivity to explosive traces as small as a single 10 μm diameter particle (~1 ng) has been demonstrated. Analytes tested here include RDX, TNT, ammonium nitrate and sucrose. The substrates tested in this current work include metal, plastics, glass and painted car panels.

Chromatographic analysis of Polygalae Radix by online hyphenating pressurized liquid extraction

NASA Astrophysics Data System (ADS)

Song, Yuelin; Song, Qingqing; Li, Jun; Shi, Shepo; Guo, Liping; Zhao, Yunfang; Jiang, Yong; Tu, Pengfei

2016-06-01

Practicing “green analytical chemistry” is of great importance when profiling the chemical composition of complex matrices. Herein, a novel hybrid analytical platform was developed for direct chemical analysis of complex matrices by online hyphenating pressurized warm water extraction followed by turbulent flow chromatography coupled with high performance liquid chromatography-tandem mass spectrometry (PWWE-TFC-LC-MS/MS). Two parallel hollow guard columns acted as extraction vessels connected to a long narrow polyether ether ketone tube, while warm water served as extraction solvent and was delivered at a flow rate of 2.5 mL/min to generate considerable back pressure at either vessel. A column oven heated both the solvent and crude materials. A TFC column, which is advantageous for the comprehensive trapping of small molecular substances from fluids under turbulent flow conditions, was employed to transfer analytes from the PWWE module to LC-MS/MS. Two electronic valves alternated each vessel between extraction and elution phases. As a proof-of-concept, a famous herbal medicine for the treatment of neurodegenerative disorders, namely Polygalae Radix, was selected for the qualitative and quantitative analyses. The results suggest that the hybrid platform is advantageous in terms of decreasing time, material, and solvent consumption and in its automation, versatility, and environmental friendliness.

Mass Spectrometry Based Lipidomics: An Overview of Technological Platforms

PubMed Central

Köfeler, Harald C.; Fauland, Alexander; Rechberger, Gerald N.; Trötzmüller, Martin

2012-01-01

One decade after the genomic and the proteomic life science revolution, new ‘omics’ fields are emerging. The metabolome encompasses the entity of small molecules—Most often end products of a catalytic process regulated by genes and proteins—with the lipidome being its fat soluble subdivision. Within recent years, lipids are more and more regarded not only as energy storage compounds but also as interactive players in various cellular regulation cycles and thus attain rising interest in the bio-medical community. The field of lipidomics is, on one hand, fuelled by analytical technology advances, particularly mass spectrometry and chromatography, but on the other hand new biological questions also drive analytical technology developments. Compared to fairly standardized genomic or proteomic high-throughput protocols, the high degree of molecular heterogeneity adds a special analytical challenge to lipidomic analysis. In this review, we will take a closer look at various mass spectrometric platforms for lipidomic analysis. We will focus on the advantages and limitations of various experimental setups like ‘shotgun lipidomics’, liquid chromatography—Mass spectrometry (LC-MS) and matrix assisted laser desorption ionization-time of flight (MALDI-TOF) based approaches. We will also examine available software packages for data analysis, which nowadays is in fact the rate limiting step for most ‘omics’ workflows. PMID:24957366

Mass spectrometry based lipidomics: an overview of technological platforms.

PubMed

Köfeler, Harald C; Fauland, Alexander; Rechberger, Gerald N; Trötzmüller, Martin

2012-01-05

One decade after the genomic and the proteomic life science revolution, new 'omics' fields are emerging. The metabolome encompasses the entity of small molecules-Most often end products of a catalytic process regulated by genes and proteins-with the lipidome being its fat soluble subdivision. Within recent years, lipids are more and more regarded not only as energy storage compounds but also as interactive players in various cellular regulation cycles and thus attain rising interest in the bio-medical community. The field of lipidomics is, on one hand, fuelled by analytical technology advances, particularly mass spectrometry and chromatography, but on the other hand new biological questions also drive analytical technology developments. Compared to fairly standardized genomic or proteomic high-throughput protocols, the high degree of molecular heterogeneity adds a special analytical challenge to lipidomic analysis. In this review, we will take a closer look at various mass spectrometric platforms for lipidomic analysis. We will focus on the advantages and limitations of various experimental setups like 'shotgun lipidomics', liquid chromatography-Mass spectrometry (LC-MS) and matrix assisted laser desorption ionization-time of flight (MALDI-TOF) based approaches. We will also examine available software packages for data analysis, which nowadays is in fact the rate limiting step for most 'omics' workflows.

Forensic electrochemistry: the electroanalytical sensing of synthetic cathinone-derivatives and their accompanying adulterants in "legal high" products.

PubMed

Smith, Jamie P; Metters, Jonathan P; Irving, Craig; Sutcliffe, Oliver B; Banks, Craig E

2014-01-21

The production and abuse of new psychoactive substances, known as "legal highs" which mimic traditional drugs of abuse is becoming a global epidemic. Traditional analytical methodologies exist which can provide confirmatory analysis but there is a requirement for an on-the-spot analytical screening tool that could be used to determine whether a substance, or sample matrix contains such legal, or formally "legal highs". In this paper the electrochemical sensing of (±)-methcathinone and related compounds at a range of commercially available electrode substrates is explored. We demonstrate for the first time that this class of "legal highs" are electrochemically active providing a novel sensing protocol based upon their electrochemical oxidation. Screen-printed graphite sensing platforms are favoured due to their proven ability to be mass-produced providing large numbers of reliable and reproducible electrode sensing platforms that preclude the requirement of surface pre-treatment such as mechanical polishing as is the case in the use of solid/re-usable electrode substrates. Additionally they hold potential to be used on-site potentially being the basis of an on-site legal high screening device. Consequently the electroanalytical sensing of (±)-methcathinone (3a), (±)-4′-methylmethcathinone [3b, 4-MMC, (±)-mephedrone] and (±)-4′-methyl-N-ethylcathinone (3c, 4-MEC) is explored using screen-printed sensing platforms with the effect of pH explored upon the analytical response with their analytical efficiency evaluated towards the target legal highs. Interesting at pH values below 6 the voltammetric response quantitatively changes from that of an electrochemically irreversible response to that of a quasi-reversible signature which can be used analytically. It is demonstrated for the first time that the electroanalytical sensing of (±)-methcathinone (3a), (±)-mephedrone (3b) and 4-MEC (3c) are possible with accessible linear ranges found to correspond to 16–200 μg mL(−1) for 3a (at pH 12) and 16–350 μg mL(−1) for both 3b and 3c in pH 2, with limits of detection (3σ) found to correspond to 44.5, 39.8 and 84.2 μg mL(−1) respectively. Additionally adulterants that are commonly incorporated into cathinone legal highs are electrochemically explored at both pH 2 and 12.

Simulation of cooperating robot manipulators on a mobile platform

NASA Technical Reports Server (NTRS)

Murphy, Stephen H.; Wen, John Ting-Yung; Saridis, George N.

1991-01-01

The dynamic equations of motion are presented for two or more cooperating manipulators on a freely moving mobile platform. The system of cooperating robot manipulators forms a closed kinematic chain where the force of interaction must be included in the formulation of robot and platform dynamics. The formulation includes the full dynamic interactions from arms to platform and arm tip to arm tip, and the possible translation and rotation of the platform. The equations of motion are shown to be identical in structure to the fixed-platform cooperative manipulator dynamics. The number of DOFs of the system is sufficiently large to make recursive dynamic calculation methods potentially more efficient than closed-form solutions. A complete simulation with two 6-DOF manipulators of a free-floating platform is presented along a with a multiple-arm controller to position the common load.

Design of smart composite platforms for adaptive trust vector control and adaptive laser telescope for satellite applications

NASA Astrophysics Data System (ADS)

Ghasemi-Nejhad, Mehrdad N.

2013-04-01

This paper presents design of smart composite platforms for adaptive trust vector control (TVC) and adaptive laser telescope for satellite applications. To eliminate disturbances, the proposed adaptive TVC and telescope systems will be mounted on two analogous smart composite platform with simultaneous precision positioning (pointing) and vibration suppression (stabilizing), SPPVS, with micro-radian pointing resolution, and then mounted on a satellite in two different locations. The adaptive TVC system provides SPPVS with large tip-tilt to potentially eliminate the gimbals systems. The smart composite telescope will be mounted on a smart composite platform with SPPVS and then mounted on a satellite. The laser communication is intended for the Geosynchronous orbit. The high degree of directionality increases the security of the laser communication signal (as opposed to a diffused RF signal), but also requires sophisticated subsystems for transmission and acquisition. The shorter wavelength of the optical spectrum increases the data transmission rates, but laser systems require large amounts of power, which increases the mass and complexity of the supporting systems. In addition, the laser communication on the Geosynchronous orbit requires an accurate platform with SPPVS capabilities. Therefore, this work also addresses the design of an active composite platform to be used to simultaneously point and stabilize an intersatellite laser communication telescope with micro-radian pointing resolution. The telescope is a Cassegrain receiver that employs two mirrors, one convex (primary) and the other concave (secondary). The distance, as well as the horizontal and axial alignment of the mirrors, must be precisely maintained or else the optical properties of the system will be severely degraded. The alignment will also have to be maintained during thruster firings, which will require vibration suppression capabilities of the system as well. The innovative platform has been designed to have tip-tilt pointing and simultaneous multi-degree-of-freedom vibration isolation capability for pointing stabilization. Analytical approaches have been employed for determining the loads in the components as well as optimizing the design of the system. The different critical components such as telescope tube struts, flexure joints, and the secondary mirror mount have been designed and analyzed using finite element technique. The Simultaneous Precision Positioning and Vibration Suppression (SPPVS) smart composites platforms for the adaptive TVC and adaptive composite telescope are analogous (e.g., see work by Ghasemi-Nejhad and co-workers [1, 2]), where innovative concepts and control strategies are introduced, and experimental verifications of simultaneous thrust vector control and vibration isolation of satellites were performed. The smart composite platforms function as an active structural interface between the main thruster of a satellite and the satellite structure for the adaptive TVC application and as an active structural interface between the main smart composite telescope and the satellite structure for the adaptive laser communication application. The cascaded multiple feedback loops compensate the hysteresis (for piezoelectric stacks inside the three linear actuators that individually have simultaneous precision positioning and vibration suppression), dead-zone, back-lash, and friction nonlinearities very well, and provide precision and quick smart platform control and satisfactory thrust vector control capability. In addition, for example for the adaptive TVC, the experimental results show that the smart composite platform satisfactorily provided precision and fast smart platform control as well as the satisfactory thrust vector control capability. The vibration controller isolated 97% of the vibration energy due to the thruster firing.

Spatial Data Infrastructures (SDIs): Improving the Scientific Environmental Data Management and Visualization with ArcGIS Platform

NASA Astrophysics Data System (ADS)

Shrestha, S. R.; Hogeweg, M.; Rose, B.; Turner, A.

2017-12-01

The requirement for quality, authoritatively sourced data can often be challenging when working with scientific data. In addition, the lack of standard mechanism to discover, access, and use such data can be cumbersome. This results in slow research, poor dissemination and missed opportunities for research to positively impact policy and knowledge. There is widespread recognition that authoritative datasets are maintained by multiple organizations following various standards, and addressing these challenges will involve multiple stakeholders as well. The bottom line is that organizations need a mechanism to efficiently create, share, catalog, and discover data, and the ability to apply these to create an authoritative information products and applications is powerful and provides value. In real-world applications, individual organizations develop, modify, finalize, and support foundational data for distributed users across the system and thus require an efficient method of data management. For this, the SDI (Spatial Data Infrastructure) framework can be applied for GIS users to facilitate efficient and powerful decision making based on strong visualization and analytics. Working with research institutions, governments, and organizations across the world, we have developed a Hub framework for data and analysis sharing that is driven by outcome-centric goals which apply common methodologies and standards. SDI are an operational capability that should be equitably accessible to policy-makers, analysts, departments and public communities. These SDI need to align with operational workflows and support social communications and collaboration. The Hub framework integrates data across agencies, projects and organizations to support interoperability and drive coordination. We will present and share how Esri has been supporting the development of local, state, and national SDIs for many years and show some use cases for applications of planetary SDI. We will also share what makes an SDI successful, how organizations have used the ArcGIS platform to quickly stand up key SDI products and applications, and describe some typical SDI scenarios.

Online Nanoflow Multidimensional Fractionation for High Efficiency Phosphopeptide Analysis*

PubMed Central

Ficarro, Scott B.; Zhang, Yi; Carrasco-Alfonso, Marlene J.; Garg, Brijesh; Adelmant, Guillaume; Webber, James T.; Luckey, C. John; Marto, Jarrod A.

2011-01-01

Despite intense, continued interest in global analyses of signaling cascades through mass spectrometry-based studies, the large-scale, systematic production of phosphoproteomics data has been hampered in-part by inefficient fractionation strategies subsequent to phosphopeptide enrichment. Here we explore two novel multidimensional fractionation strategies for analysis of phosphopeptides. In the first technique we utilize aliphatic ion pairing agents to improve retention of phosphopeptides at high pH in the first dimension of a two-dimensional RP-RP. The second approach is based on the addition of strong anion exchange as the second dimension in a three-dimensional reversed phase (RP)-strong anion exchange (SAX)-RP configuration. Both techniques provide for automated, online data acquisition, with the 3-D platform providing the highest performance both in terms of separation peak capacity and the number of unique phosphopeptide sequences identified per μg of cell lysate consumed. Our integrated RP-SAX-RP platform provides several analytical figures of merit, including: (1) orthogonal separation mechanisms in each dimension; (2) high separation peak capacity (3) efficient retention of singly- and multiply-phosphorylated peptides; (4) compatibility with automated, online LC-MS analysis. We demonstrate the reproducibility of RP-SAX-RP and apply it to the analysis of phosphopeptides derived from multiple biological contexts, including an in vitro model of acute myeloid leukemia in addition to primary polyclonal CD8+ T-cells activated in vivo through bacterial infection and then purified from a single mouse. PMID:21788404

Are CD-ROM LANs a Thing of the Past?

ERIC Educational Resources Information Center

Mehta, Apurva

1996-01-01

Remote access to full-text and CD-ROM databases using the Internet has advantages over a CD-ROM local area network. Topics include speed, document delivery, multiple platforms, technical support, licensing, copyright, and access to graphics. Considerations of duplication of information, platform compatibility, print versus digital media, back…

Evaluating the enhancement and improvement of China's technology and financial services platform innovation strategy.

PubMed

Wu, Ching-Sung; Hu, Kuang-Hua; Chen, Fu-Hsiang

2016-01-01

The development of high-tech industry has been prosperous around the world in past decades, while technology and finance have already become the most significant issues in the information era. While high-tech firms are a major force behind a country's economic development, it requires a lot of money for the development process, as well as the financing difficulties for its potential problems, thus, how to evaluate and establish appropriate technology and financial services platforms innovation strategy has become one of the most critical and difficult issues. Moreover, how the chosen intertwined financial environment can be optimized in order that high-tech firms financing problems can be decided has seldom been addressed. Thus, this research aims to establish a technology and financial services platform innovation strategy improvement model, as based on the hybrid MADM model, which addresses the main causal factors and amended priorities in order to strengthen ongoing planning. A DEMATEL technique, as based on Analytic Network Process, as well as modified VIKOR, will be proposed for selecting and re-configuring the aspired technology and financial services platform. An empirical study, as based on China's technology and financial services platform innovation strategy, will be provided for verifying the effectiveness of this proposed methodology. Based on expert interviews, technology and financial services platforms innovation strategy improvement should be made in the following order: credit guarantee platform ( C )_credit rating platform ( B )_investment and finance platform ( A ).

ATHLETE as a Mobile ISRU and Regolith Construction Platform

NASA Technical Reports Server (NTRS)

Howe, A. Scott; Wilcox, Brian; Barmatz, Martin; Voecks, Gerald

2016-01-01

The All-Terrain Hex-Limbed Extra-Terrestrial Explorer (ATHLETE) robotic mobility platform can provide precision positioning and mobility for site preparation and regolith construction needs. ATHLETE is a multi-use platform designed to use swap-out tools and implements that can be applied to any number of tasks that need precision limb manipulation or mobility. Major capabilities include off-loading habitats, transporting surface assets, robotically assembling outposts from multiple mission manifests, and supporting science and technology objectives. This paper describes conceptual approaches for supporting NASA regolith construction research, such as additive construction, modular brick and panel factory, and mobile ISRU platform.

A Platform-Independent Plugin for Navigating Online Radiology Cases.

PubMed

Balkman, Jason D; Awan, Omer A

2016-06-01

Software methods that enable navigation of radiology cases on various digital platforms differ between handheld devices and desktop computers. This has resulted in poor compatibility of online radiology teaching files across mobile smartphones, tablets, and desktop computers. A standardized, platform-independent, or "agnostic" approach for presenting online radiology content was produced in this work by leveraging modern hypertext markup language (HTML) and JavaScript web software technology. We describe the design and evaluation of this software, demonstrate its use across multiple viewing platforms, and make it publicly available as a model for future development efforts.

Comprehensive performance comparison of high-resolution array platforms for genome-wide Copy Number Variation (CNV) analysis in humans.

PubMed

Haraksingh, Rajini R; Abyzov, Alexej; Urban, Alexander Eckehart

2017-04-24

High-resolution microarray technology is routinely used in basic research and clinical practice to efficiently detect copy number variants (CNVs) across the entire human genome. A new generation of arrays combining high probe densities with optimized designs will comprise essential tools for genome analysis in the coming years. We systematically compared the genome-wide CNV detection power of all 17 available array designs from the Affymetrix, Agilent, and Illumina platforms by hybridizing the well-characterized genome of 1000 Genomes Project subject NA12878 to all arrays, and performing data analysis using both manufacturer-recommended and platform-independent software. We benchmarked the resulting CNV call sets from each array using a gold standard set of CNVs for this genome derived from 1000 Genomes Project whole genome sequencing data. The arrays tested comprise both SNP and aCGH platforms with varying designs and contain between ~0.5 to ~4.6 million probes. Across the arrays CNV detection varied widely in number of CNV calls (4-489), CNV size range (~40 bp to ~8 Mbp), and percentage of non-validated CNVs (0-86%). We discovered strikingly strong effects of specific array design principles on performance. For example, some SNP array designs with the largest numbers of probes and extensive exonic coverage produced a considerable number of CNV calls that could not be validated, compared to designs with probe numbers that are sometimes an order of magnitude smaller. This effect was only partially ameliorated using different analysis software and optimizing data analysis parameters. High-resolution microarrays will continue to be used as reliable, cost- and time-efficient tools for CNV analysis. However, different applications tolerate different limitations in CNV detection. Our study quantified how these arrays differ in total number and size range of detected CNVs as well as sensitivity, and determined how each array balances these attributes. This analysis will inform appropriate array selection for future CNV studies, and allow better assessment of the CNV-analytical power of both published and ongoing array-based genomics studies. Furthermore, our findings emphasize the importance of concurrent use of multiple analysis algorithms and independent experimental validation in array-based CNV detection studies.

A high-throughput platform for low-volume high-temperature/pressure sealed vessel solvent extractions.

PubMed

Damm, Markus; Kappe, C Oliver

2011-11-30

A high-throughput platform for performing parallel solvent extractions in sealed HPLC/GC vials inside a microwave reactor is described. The system consist of a strongly microwave-absorbing silicon carbide plate with 20 cylindrical wells of appropriate dimensions to be fitted with standard HPLC/GC autosampler vials serving as extraction vessels. Due to the possibility of heating up to four heating platforms simultaneously (80 vials), efficient parallel analytical-scale solvent extractions can be performed using volumes of 0.5-1.5 mL at a maximum temperature/pressure limit of 200°C/20 bar. Since the extraction and subsequent analysis by either gas chromatography or liquid chromatography coupled with mass detection (GC-MS or LC-MS) is performed directly from the autosampler vial, errors caused by sample transfer can be minimized. The platform was evaluated for the extraction and quantification of caffeine from commercial coffee powders assessing different solvent types, extraction temperatures and times. For example, 141±11 μg caffeine (5 mg coffee powder) were extracted during a single extraction cycle using methanol as extraction solvent, whereas only 90±11 were obtained performing the extraction in methylene chloride, applying the same reaction conditions (90°C, 10 min). In multiple extraction experiments a total of ~150 μg caffeine was extracted from 5 mg commercial coffee powder. In addition to the quantitative caffeine determination, a comparative qualitative analysis of the liquid phase coffee extracts and the headspace volatiles was performed, placing special emphasis on headspace analysis using solid-phase microextraction (SPME) techniques. The miniaturized parallel extraction technique introduced herein allows solvent extractions to be performed at significantly expanded temperature/pressure limits and shortened extraction times, using standard HPLC autosampler vials as reaction vessels. Remarkable differences regarding peak pattern and main peaks were observed when low-temperature extraction (60°C) and high-temperature extraction (160°C) are compared prior to headspace-SPME-GC-MS performed in the same HPLC/GC vials. Copyright © 2011 Elsevier B.V. All rights reserved.

Use of Tethered Enzymes as a Platform Technology for Rapid Analyte Detection

PubMed Central

Cohen, Roy; Lata, James P.; Lee, Yurim; Hernández, Jean C. Cruz; Nishimura, Nozomi; Schaffer, Chris B.; Mukai, Chinatsu; Nelson, Jacquelyn L.; Brangman, Sharon A.; Agrawal, Yash; Travis, Alexander J.

2015-01-01

Background Rapid diagnosis for time-sensitive illnesses such as stroke, cardiac arrest, and septic shock is essential for successful treatment. Much attention has therefore focused on new strategies for rapid and objective diagnosis, such as Point-of-Care Tests (PoCT) for blood biomarkers. Here we use a biomimicry-based approach to demonstrate a new diagnostic platform, based on enzymes tethered to nanoparticles (NPs). As proof of principle, we use oriented immobilization of pyruvate kinase (PK) and luciferase (Luc) on silica NPs to achieve rapid and sensitive detection of neuron-specific enolase (NSE), a clinically relevant biomarker for multiple diseases ranging from acute brain injuries to lung cancer. We hypothesize that an approach capitalizing on the speed and catalytic nature of enzymatic reactions would enable fast and sensitive biomarker detection, suitable for PoCT devices. Methods and findings We performed in-vitro, animal model, and human subject studies. First, the efficiency of coupled enzyme activities when tethered to NPs versus when in solution was tested, demonstrating a highly sensitive and rapid detection of physiological and pathological concentrations of NSE. Next, in rat stroke models the enzyme-based assay was able in minutes to show a statistically significant increase in NSE levels in samples taken 1 hour before and 0, 1, 3 and 6 hours after occlusion of the distal middle cerebral artery. Finally, using the tethered enzyme assay for detection of NSE in samples from 20 geriatric human patients, we show that our data match well (r = 0.815) with the current gold standard for biomarker detection, ELISA—with a major difference being that we achieve detection in 10 minutes as opposed to the several hours required for traditional ELISA. Conclusions Oriented enzyme immobilization conferred more efficient coupled activity, and thus higher assay sensitivity, than non-tethered enzymes. Together, our findings provide proof of concept for using oriented immobilization of active enzymes on NPs as the basis for a highly rapid and sensitive biomarker detection platform. This addresses a key challenge in developing a PoCT platform for time sensitive and difficult to diagnose pathologies. PMID:26605916

Phase sensitive spectral domain interferometry for label free biomolecular interaction analysis and biosensing applications

NASA Astrophysics Data System (ADS)

Chirvi, Sajal

Biomolecular interaction analysis (BIA) plays vital role in wide variety of fields, which include biomedical research, pharmaceutical industry, medical diagnostics, and biotechnology industry. Study and quantification of interactions between natural biomolecules (proteins, enzymes, DNA) and artificially synthesized molecules (drugs) is routinely done using various labeled and label-free BIA techniques. Labeled BIA (Chemiluminescence, Fluorescence, Radioactive) techniques suffer from steric hindrance of labels on interaction site, difficulty of attaching labels to molecules, higher cost and time of assay development. Label free techniques with real time detection capabilities have demonstrated advantages over traditional labeled techniques. The gold standard for label free BIA is surface Plasmon resonance (SPR) that detects and quantifies the changes in refractive index of the ligand-analyte complex molecule with high sensitivity. Although SPR is a highly sensitive BIA technique, it requires custom-made sensor chips and is not well suited for highly multiplexed BIA required in high throughput applications. Moreover implementation of SPR on various biosensing platforms is limited. In this research work spectral domain phase sensitive interferometry (SD-PSI) has been developed for label-free BIA and biosensing applications to address limitations of SPR and other label free techniques. One distinct advantage of SD-PSI compared to other label-free techniques is that it does not require use of custom fabricated biosensor substrates. Laboratory grade, off-the-shelf glass or plastic substrates of suitable thickness with proper surface functionalization are used as biosensor chips. SD-PSI is tested on four separate BIA and biosensing platforms, which include multi-well plate, flow cell, fiber probe with integrated optics and fiber tip biosensor. Sensitivity of 33 ng/ml for anti-IgG is achieved using multi-well platform. Principle of coherence multiplexing for multi-channel label-free biosensing applications is introduced. Simultaneous interrogation of multiple biosensors is achievable with a single spectral domain phase sensitive interferometer by coding the individual sensograms in coherence-multiplexed channels. Experimental results demonstrating multiplexed quantitative biomolecular interaction analysis of antibodies binding to antigen coated functionalized biosensor chip surfaces on different platforms are presented.

THE BERKELEY DATA ANALYSIS SYSTEM (BDAS): AN OPEN SOURCE PLATFORM FOR BIG DATA ANALYTICS

DTIC Science & Technology

2017-09-01

Evan Sparks, Oliver Zahn, Michael J. Franklin, David A. Patterson, Saul Perlmutter. Scientific Computing Meets Big Data Technology: An Astronomy ...Processing Astronomy Imagery Using Big Data Technology. IEEE Transaction on Big Data, 2016. Approved for Public Release; Distribution Unlimited. 22 [93

An ultra low energy biomedical signal processing system operating at near-threshold.

PubMed

Hulzink, J; Konijnenburg, M; Ashouei, M; Breeschoten, A; Berset, T; Huisken, J; Stuyt, J; de Groot, H; Barat, F; David, J; Van Ginderdeuren, J

2011-12-01

This paper presents a voltage-scalable digital signal processing system designed for the use in a wireless sensor node (WSN) for ambulatory monitoring of biomedical signals. To fulfill the requirements of ambulatory monitoring, power consumption, which directly translates to the WSN battery lifetime and size, must be kept as low as possible. The proposed processing platform is an event-driven system with resources to run applications with different degrees of complexity in an energy-aware way. The architecture uses effective system partitioning to enable duty cycling, single instruction multiple data (SIMD) instructions, power gating, voltage scaling, multiple clock domains, multiple voltage domains, and extensive clock gating. It provides an alternative processing platform where the power and performance can be scaled to adapt to the application need. A case study on a continuous wavelet transform (CWT)-based heart-beat detection shows that the platform not only preserves the sensitivity and positive predictivity of the algorithm but also achieves the lowest energy/sample for ElectroCardioGram (ECG) heart-beat detection publicly reported today.

The Effect of Multiple Intelligences Theory-Based Education on Academic Achievement: A Meta-Analytic Review

ERIC Educational Resources Information Center

Bas, Gökhan

2016-01-01

The main purpose of this study is to determine the effect of multiple intelligences theory (MIT)-based education on students' academic achievement. In this research, the meta-analytic method was adopted to determine this effect, and studies related to this subject carried out in Turkey were compiled. The effect sizes of the studies included in the…

Time-resolved SERS for characterizing extracellular vesicles

NASA Astrophysics Data System (ADS)

Rojalin, Tatu; Saari, Heikki; Somersalo, Petter; Laitinen, Saara; Turunen, Mikko; Viitala, Tapani; Wachsmann-Hogiu, Sebastian; Smith, Zachary J.; Yliperttula, Marjo

2017-02-01

The aim of this work is to develop a platform for characterizing extracellular vesicles (EV) by using gold-polymer nanopillar SERS arrays simultaneously circumventing the photoluminescence-related disadvantages of Raman with a time-resolved approach. EVs are rich of biochemical information reporting of, for example, diseased state of the biological system. Currently, straightforward, label-free and fast EV characterization methods with low sample consumption are warranted. In this study, SERS spectra of red blood cell and platelet derived EVs were successfully measured and their biochemical contents analyzed using multivariate data analysis techniques. The developed platform could be conveniently used for EV analytics in general.

On the dynamical stability of the space 'monorail'

NASA Astrophysics Data System (ADS)

Bergamaschi, S.; Manni, D.

The dynamical stability of 'monorail' tethered-satellite/elevator configurations being studied for the Space Station is investigated analytically, treating the end platforms and elevator as point masses, neglecting tether elasticity, and taking the Coriolis force and the complex gravitational field into account in analyzing the orbital-plane motion of the system. A mathematical model is constructed; the equations of motion are derived; and results obtained by numerical integration for platform masses 100,000 and 10,000 kg, elevator mass 5000 kg, and a 10-km-long 6-mm-diameter 4070-kg-mass tether are presented in graphs and briefly characterized.

In situ nuclear magnetic resonance microimaging of live biofilms in a microchannel

DOE Office of Scientific and Technical Information (OSTI.GOV)

Renslow, R. S.; Marshall, M. J.; Tucker, A. E.

Nuclear magnetic resonance (NMR) microimaging and spectroscopy was used to interrogate fluids of biological importance (e.g., water, buffer, medium solution) and live biofilms in a microchannel compatible for analyses at ambient pressure and under vacuum. Studies using buffer, growth medium, and actively growing Shewanella oneidensis biofilms were used to demonstrate in situ NMR microimaging measurement capabilities including velocity mapping, diffusion coefficient mapping, relaxometry, localized spectroscopy, and 2D and 3D imaging within a microchannel suitable for different analytical platforms. This technique is promising for diverse applications of correlative imaging using a portable microfluidic platform.

Lab-on-a-Chip Device for Rapid Measurement of Vitamin D Levels.

PubMed

Peter, Harald; Bistolas, Nikitas; Schumacher, Soeren; Laurisch, Cecilia; Guest, Paul C; Höller, Ulrich; Bier, Frank F

2018-01-01

Lab-on-a-chip assays allow rapid analysis of one or more molecular analytes on an automated user-friendly platform. Here we describe a fully automated assay and readout for measurement of vitamin D levels in less than 15 min using the Fraunhofer in vitro diagnostics platform. Vitamin D (25-hydroxyvitamin D 3 [25(OH)D 3 ]) dilution series in buffer were successfully tested down to 2 ng/mL. This could be applied in the future as an inexpensive point-of-care analysis for patients suffering from a variety of conditions marked by vitamin D deficiencies.

Analytical validation of soluble fms-like tyrosine and placental growth factor assays on B·R·A·H·M·S KRYPTOR Compact Plus automated immunoassay platform.

PubMed

Chan, Siaw Li; Rana, Sarosh; Chinthala, Sireesha; Salahuddin, Saira; Yeo, Kiang-Teck J

2018-01-01

Preeclampsia is one of the leading hypertensive disorders of pregnancy. Angiogenic biomarkers such as anti-angiogenic factor soluble fms-like tyrosine kinase 1 (sFlt1) and pro-angiogenic factor placental growth factor (PlGF) are involved in the pathophysiology of preeclampsia. The aim of this study is to validate the analytical performance of sFlt1 and PlGF on the B·R·A·H·M·S KRYPTOR Compact Plus (ThermoFisher Scientific). We examined K 2 -EDTA plasma samples from 50 patients on B·R·A·H·M·S KRYPTOR Compact Plus, an automated immunoassay platform. QC materials were used to assess intra- and inter-precision of the assay. Lower limit of quantitation and interference studies were determined using pooled patient plasma. The sFlt1 and PlGF assays demonstrated an analytical measuring range of 90-69,000 pg/mL and 11-7000 pg/mL, respectively (r 2  > 0.99). Lower limit of quantitation (20% CV) was interpolated to be 35 pg/mL for sFlt1 and 10 pg/mL for PlGF. Total precision for both assay displayed CVs of <10%. Interference studies showed that both assays were not significantly affected by hemolysis up to an H-index of 1100 for sFlt1 and 300 for PlGF; L- and I-index of 800 and 80 respectively for both assays. The Passing-Bablok regression analysis for sFlt1/PlGF yielded an equation of y = 1.05x + 0.02, and the Bland Altman analysis showed an average bias of 0.84. Plasma levels of sFlt1 and PlGF measured on the B·R·A·H·M·S KRYPTOR Compact Plus platform demonstrate excellent analytical performance and are acceptable as clinical grade assays. Copyright © 2018 International Society for the Study of Hypertension in Pregnancy. Published by Elsevier B.V. All rights reserved.

Performance Models for the Spike Banded Linear System Solver

DOE PAGES

Manguoglu, Murat; Saied, Faisal; Sameh, Ahmed; ...

2011-01-01

With availability of large-scale parallel platforms comprised of tens-of-thousands of processors and beyond, there is significant impetus for the development of scalable parallel sparse linear system solvers and preconditioners. An integral part of this design process is the development of performance models capable of predicting performance and providing accurate cost models for the solvers and preconditioners. There has been some work in the past on characterizing performance of the iterative solvers themselves. In this paper, we investigate the problem of characterizing performance and scalability of banded preconditioners. Recent work has demonstrated the superior convergence properties and robustness of banded preconditioners,more » compared to state-of-the-art ILU family of preconditioners as well as algebraic multigrid preconditioners. Furthermore, when used in conjunction with efficient banded solvers, banded preconditioners are capable of significantly faster time-to-solution. Our banded solver, the Truncated Spike algorithm is specifically designed for parallel performance and tolerance to deep memory hierarchies. Its regular structure is also highly amenable to accurate performance characterization. Using these characteristics, we derive the following results in this paper: (i) we develop parallel formulations of the Truncated Spike solver, (ii) we develop a highly accurate pseudo-analytical parallel performance model for our solver, (iii) we show excellent predication capabilities of our model – based on which we argue the high scalability of our solver. Our pseudo-analytical performance model is based on analytical performance characterization of each phase of our solver. These analytical models are then parameterized using actual runtime information on target platforms. An important consequence of our performance models is that they reveal underlying performance bottlenecks in both serial and parallel formulations. All of our results are validated on diverse heterogeneous multiclusters – platforms for which performance prediction is particularly challenging. Finally, we provide predict the scalability of the Spike algorithm using up to 65,536 cores with our model. In this paper we extend the results presented in the Ninth International Symposium on Parallel and Distributed Computing.« less

We Canwatch It For You Wholesale

NASA Astrophysics Data System (ADS)

Lipton, Alan J.

This chapter provides an introduction to video analytics—a branch of computer vision technology that deals with automatic detection of activities and events in surveillance video feeds. Initial applications focused on the security and surveillance space, but as the technology improves it is rapidly finding a home in many other application areas. This chapter looks at some of those spaces, the requirements they impose on video analytics systems, and provides an example architecture and set of technology components to meet those requirements. This exemplary system is put through its paces to see how it stacks up in an embedded environment. Finally, we explore the future of video analytics and examine some of the market requirements that are driving breakthroughs in both video analytics and processor platform technology alike.

Hierarchical zwitterionic modification of a SERS substrate enables real-time drug monitoring in blood plasma

NASA Astrophysics Data System (ADS)

Sun, Fang; Hung, Hsiang-Chieh; Sinclair, Andrew; Zhang, Peng; Bai, Tao; Galvan, Daniel David; Jain, Priyesh; Li, Bowen; Jiang, Shaoyi; Yu, Qiuming

2016-11-01

Surface-enhanced Raman spectroscopy (SERS) is an ultrasensitive analytical technique with molecular specificity, making it an ideal candidate for therapeutic drug monitoring (TDM). However, in critical diagnostic media including blood, nonspecific protein adsorption coupled with weak surface affinities and small Raman activities of many analytes hinder the TDM application of SERS. Here we report a hierarchical surface modification strategy, first by coating a gold surface with a self-assembled monolayer (SAM) designed to attract or probe for analytes and then by grafting a non-fouling zwitterionic polymer brush layer to effectively repel protein fouling. We demonstrate how this modification can enable TDM applications by quantitatively and dynamically measuring the concentrations of several analytes--including an anticancer drug (doxorubicin), several TDM-requiring antidepressant and anti-seizure drugs, fructose and blood pH--in undiluted plasma. This hierarchical surface chemistry is widely applicable to many analytes and provides a generalized platform for SERS-based biosensing in complex real-world media.

Analytical close-form solutions to the elastic fields of solids with dislocations and surface stress

NASA Astrophysics Data System (ADS)

Ye, Wei; Paliwal, Bhasker; Ougazzaden, Abdallah; Cherkaoui, Mohammed

2013-07-01

The concept of eigenstrain is adopted to derive a general analytical framework to solve the elastic field for 3D anisotropic solids with general defects by considering the surface stress. The formulation shows the elastic constants and geometrical features of the surface play an important role in determining the elastic fields of the solid. As an application, the analytical close-form solutions to the stress fields of an infinite isotropic circular nanowire are obtained. The stress fields are compared with the classical solutions and those of complex variable method. The stress fields from this work demonstrate the impact from the surface stress when the size of the nanowire shrinks but becomes negligible in macroscopic scale. Compared with the power series solutions of complex variable method, the analytical solutions in this work provide a better platform and they are more flexible in various applications. More importantly, the proposed analytical framework profoundly improves the studies of general 3D anisotropic materials with surface effects.

EGFR mutation detection in ctDNA from NSCLC patient plasma: A cross-platform comparison of leading technologies to support the clinical development of AZD9291.

PubMed

Thress, Kenneth S; Brant, Roz; Carr, T Hedley; Dearden, Simon; Jenkins, Suzanne; Brown, Helen; Hammett, Tracey; Cantarini, Mireille; Barrett, J Carl

2015-12-01

To assess the ability of different technology platforms to detect epidermal growth factor receptor (EGFR) mutations, including T790M, from circulating tumor DNA (ctDNA) in advanced non-small cell lung cancer (NSCLC) patients. A comparison of multiple platforms for detecting EGFR mutations in plasma ctDNA was undertaken. Plasma samples were collected from patients entering the ongoing AURA trial (NCT01802632), investigating the safety, tolerability, and efficacy of AZD9291 in patients with EGFR-sensitizing mutation-positive NSCLC. Plasma was collected prior to AZD9291 dosing but following clinical progression on a previous EGFR-tyrosine kinase inhibitor (TKI). Extracted ctDNA was analyzed using two non-digital platforms (cobas(®) EGFR Mutation Test and therascreen™ EGFR amplification refractory mutation system assay) and two digital platforms (Droplet Digital™ PCR and BEAMing digital PCR [dPCR]). Preliminary assessment (38 samples) was conducted using all four platforms. For EGFR-TKI-sensitizing mutations, high sensitivity (78-100%) and specificity (93-100%) were observed using tissue as a non-reference standard. For the T790M mutation, the digital platforms outperformed the non-digital platforms. Subsequent assessment using 72 additional baseline plasma samples was conducted using the cobas(®) EGFR Mutation Test and BEAMing dPCR. The two platforms demonstrated high sensitivity (82-87%) and specificity (97%) for EGFR-sensitizing mutations. For the T790M mutation, the sensitivity and specificity were 73% and 67%, respectively, with the cobas(®) EGFR Mutation Test, and 81% and 58%, respectively, with BEAMing dPCR. Concordance between the platforms was >90%, showing that multiple platforms are capable of sensitive and specific detection of EGFR-TKI-sensitizing mutations from NSCLC patient plasma. The cobas(®) EGFR Mutation Test and BEAMing dPCR demonstrate a high sensitivity for T790M mutation detection. Genomic heterogeneity of T790M-mediated resistance may explain the reduced specificity observed with plasma-based detection of T790M mutations versus tissue. These data support the use of both platforms in the AZD9291 clinical development program. Copyright © 2015 The Authors. Published by Elsevier Ireland Ltd.. All rights reserved.

Design of a New Ultracompact Resonant Plasmonic Multi-Analyte Label-Free Biosensing Platform

PubMed Central

De Palo, Maripina; Ciminelli, Caterina

2017-01-01

In this paper, we report on the design of a bio-multisensing platform for the selective label-free detection of protein biomarkers, carried out through a 3D numerical algorithm. The platform includes a number of biosensors, each of them is based on a plasmonic nanocavity, consisting of a periodic metal structure to be deposited on a silicon oxide substrate. Light is strongly confined in a region with extremely small size (=1.57 μm2), to enhance the light-matter interaction. A surface sensitivity Ss = 1.8 nm/nm has been calculated together with a detection limit of 128 pg/mm2. Such performance, together with the extremely small footprint, allow the integration of several devices on a single chip to realize extremely compact lab-on-chip microsystems. In addition, each sensing element of the platform has a good chemical stability that is guaranteed by the selection of gold for its fabrication. PMID:28783075

Pro-ana versus Pro-recovery: A Content Analytic Comparison of Social Media Users’ Communication about Eating Disorders on Twitter and Tumblr

PubMed Central

Branley, Dawn B.; Covey, Judith

2017-01-01

Objectives: To compare how people communicate about eating disorders on two popular social media platforms – Twitter and Tumblr. Materials and Methods: Thematic analysis was conducted to characterize the types of communications posted, and a content analysis was undertaken of between-platform differences. Results: Three types of content (pro-ana, anti-ana, and pro-recovery) were posted on each platform. Overall, across both platforms, extreme pro-ana posts were in the minority compared to anti-ana and pro-recovery. Pro-ana posts (including ‘thinspiration’) were more common on Twitter than Tumblr, whereas anti-ana and pro-recovery posts were more common on Tumblr. Conclusion: The findings have implications for future research and health care relating to the treatment and prevention of eating disorders. Developers of future interventions targeting negative pro-ana content should remain aware of the need to avoid any detrimental impact on positive online support. PMID:28848472

A versatile quantitation platform based on platinum nanoparticles incorporated volumetric bar-chart chip for highly sensitive assays.

PubMed

Wang, Yuzhen; Zhu, Guixian; Qi, Wenjin; Li, Ying; Song, Yujun

2016-11-15

Platinum nanoparticles incorporated volumetric bar-chart chip (PtNPs-V-Chip) is able to be used for point-of-care tests by providing quantitative and visualized readout without any assistance from instruments, data processing, or graphic plotting. To improve the sensitivity of PtNPs-V-Chip, hybridization chain reaction was employed in this quantitation platform for highly sensitive assays that can detect as low as 16 pM Ebola Virus DNA, 0.01ng/mL carcinoembryonic antigen (CEA), and the 10 HER2-expressing cancer cells. Based on this amplified strategy, a 100-fold decrease of detection limit was achieved for DNA by improving the number of platinum nanoparticle catalyst for the captured analyte. This quantitation platform can also distinguish single base mismatch of DNA hybridization and observe the concentration threshold of CEA. The new strategy lays the foundation for this quantitation platform to be applied in forensic analysis, biothreat detection, clinical diagnostics and drug screening. Copyright © 2016 Elsevier B.V. All rights reserved.

A web-based platform to support an evidence-based mental health intervention: lessons from the CBITS web site.

PubMed

Vona, Pamela; Wilmoth, Pete; Jaycox, Lisa H; McMillen, Janey S; Kataoka, Sheryl H; Wong, Marleen; DeRosier, Melissa E; Langley, Audra K; Kaufman, Joshua; Tang, Lingqi; Stein, Bradley D

2014-11-01

To explore the role of Web-based platforms in behavioral health, the study examined usage of a Web site for supporting training and implementation of an evidence-based intervention. Using data from an online registration survey and Google Analytics, the investigators examined user characteristics and Web site utilization. Site engagement was substantial across user groups. Visit duration differed by registrants' characteristics. Less experienced clinicians spent more time on the Web site. The training section accounted for most page views across user groups. Individuals previously trained in the Cognitive-Behavioral Intervention for Trauma in Schools intervention viewed more implementation assistance and online community pages than did other user groups. Web-based platforms have the potential to support training and implementation of evidence-based interventions for clinicians of varying levels of experience and may facilitate more rapid dissemination. Web-based platforms may be promising for trauma-related interventions, because training and implementation support should be readily available after a traumatic event.

URBANopt Advanced Analytics Platform | Buildings | NREL

Science.gov Websites

-use districts, different buildings may peak in energy consumption at different times. In certain cases applications. Districts, Neighborhoods, and Campuses For districts with different building types and mixed-use buildings? How does energy consumption vary depending on different building efficiency scenarios (e.g

78 FR 45565 - Notice Pursuant to the National Cooperative Research and Production Act of 1993 -- tranSMART...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-07-29

... activities are to enable effective sharing, integration, standardization, and analysis of heterogeneous data from collaborative translational research by mobilizing the tranSMART open- source and open-data...: (a) Establish and sustain tranSMART as the preferred data sharing and analytics platform for...

Improving Student Performance Using Nudge Analytics

ERIC Educational Resources Information Center

Feild, Jacqueline

2015-01-01

Providing students with continuous and personalized feedback on their performance is an important part of encouraging self regulated learning. As part of our higher education platform, we built a set of data visualizations to provide feedback to students on their assignment performance. These visualizations give students information about how they…

Optimizing the Usability of Mobile Phones for Individuals Who Are Deaf

ERIC Educational Resources Information Center

Liu, Chien-Hsiou; Chiu, Hsiao-Ping; Hsieh, Ching-Lin; Li, Rong-Kwer

2010-01-01

Mobile phones are employed as an assistive platform to improve the living quality of individuals who are deaf. However, deaf individuals experience difficulties using existing functions on mobile phones. This study identifies the functions that are inadequate and insufficient for deaf individuals using existing mobile phones. Analytical results…

RunJumpCode: An Educational Game for Educating Programming

ERIC Educational Resources Information Center

Hinds, Matthew; Baghaei, Nilufar; Ragon, Pedrito; Lambert, Jonathon; Rajakaruna, Tharindu; Houghton, Travers; Dacey, Simon

2017-01-01

Programming promotes critical thinking, problem solving and analytic skills through creating solutions that can solve everyday problems. However, learning programming can be a daunting experience for a lot of students. "RunJumpCode" is an educational 2D platformer video game, designed and developed in Unity, to teach players the…

An Interoperable Electronic Medical Record-Based Platform for Personalized Predictive Analytics

ERIC Educational Resources Information Center

Abedtash, Hamed

2017-01-01

Precision medicine refers to the delivering of customized treatment to patients based on their individual characteristics, and aims to reduce adverse events, improve diagnostic methods, and enhance the efficacy of therapies. Among efforts to achieve the goals of precision medicine, researchers have used observational data for developing predictive…

Brewing as a Comprehensive Learning Platform in Chemical Engineering

ERIC Educational Resources Information Center

Nielsen, Rudi P.; Sørensen, Jens L.; Simonsen, Morten E.; Madsen, Henrik T.; Muff, Jens; Strandgaard, Morten; Søgaard, Erik G.

2016-01-01

Chemical engineering is mostly taught using traditional classroom teaching and laboratory experiments when possible. Being a wide discipline encompassing topics such as analytical chemistry, process design, and microbiology, it may be argued that brewing of beer has many relations to chemical engineering topic-wise. This work illustrates how…

Learning Analytics Platform, towards an Open Scalable Streaming Solution for Education

ERIC Educational Resources Information Center

Lewkow, Nicholas; Zimmerman, Neil; Riedesel, Mark; Essa, Alfred

2015-01-01

Next generation digital learning environments require delivering "just-in-time feedback" to learners and those who support them. Unlike traditional business intelligence environments, streaming data requires resilient infrastructure that can move data at scale from heterogeneous data sources, process the data quickly for use across…

High-speed multiple sequence alignment on a reconfigurable platform.

PubMed

Oliver, Tim; Schmidt, Bertil; Maskell, Douglas; Nathan, Darran; Clemens, Ralf

2006-01-01

Progressive alignment is a widely used approach to compute multiple sequence alignments (MSAs). However, aligning several hundred sequences by popular progressive alignment tools requires hours on sequential computers. Due to the rapid growth of sequence databases biologists have to compute MSAs in a far shorter time. In this paper we present a new approach to MSA on reconfigurable hardware platforms to gain high performance at low cost. We have constructed a linear systolic array to perform pairwise sequence distance computations using dynamic programming. This results in an implementation with significant runtime savings on a standard FPGA.

Research in Evaluation Methods for Data Fusion-Capable Tactical Platforms and Distributed Multi-platform Systems in Electronic Warfare and Information-Warfare Related Missions

DTIC Science & Technology

2009-02-01

They support their launches until both outside reds are killed or until second shots are needed. In the baseline scenario shown, US2 achieves 2 kills ...red 5/6 kills . The SUT gate multiplication factor was 5 and 15. The PE gate multiplication factors of 3 and 5, PE designs for Vogel and Hungarian... ploughed in various sections of this land by splitting it into sub plots came to be known as the subplot factor. Such a design is used only when there

Web-based Visual Analytics for Extreme Scale Climate Science

DOE Office of Scientific and Technical Information (OSTI.GOV)

Steed, Chad A; Evans, Katherine J; Harney, John F

In this paper, we introduce a Web-based visual analytics framework for democratizing advanced visualization and analysis capabilities pertinent to large-scale earth system simulations. We address significant limitations of present climate data analysis tools such as tightly coupled dependencies, ineffi- cient data movements, complex user interfaces, and static visualizations. Our Web-based visual analytics framework removes critical barriers to the widespread accessibility and adoption of advanced scientific techniques. Using distributed connections to back-end diagnostics, we minimize data movements and leverage HPC platforms. We also mitigate system dependency issues by employing a RESTful interface. Our framework embraces the visual analytics paradigm via newmore » visual navigation techniques for hierarchical parameter spaces, multi-scale representations, and interactive spatio-temporal data mining methods that retain details. Although generalizable to other science domains, the current work focuses on improving exploratory analysis of large-scale Community Land Model (CLM) and Community Atmosphere Model (CAM) simulations.« less

Achieving Cost Reduction Through Data Analytics.

PubMed

Rocchio, Betty Jo

2016-10-01

The reimbursement structure of the US health care system is shifting from a volume-based system to a value-based system. Adopting a comprehensive data analytics platform has become important to health care facilities, in part to navigate this shift. Hospitals generate plenty of data, but actionable analytics are necessary to help personnel interpret and apply data to improve practice. Perioperative services is an important revenue-generating department for hospitals, and each perioperative service line requires a tailored approach to be successful in managing outcomes and controlling costs. Perioperative leaders need to prepare to use data analytics to reduce variation in supplies, labor, and overhead. Mercy, based in Chesterfield, Missouri, adopted a perioperative dashboard that helped perioperative leaders collaborate with surgeons and perioperative staff members to organize and analyze health care data, which ultimately resulted in significant cost savings. Copyright © 2016 AORN, Inc. Published by Elsevier Inc. All rights reserved.

The science of visual analysis at extreme scale

NASA Astrophysics Data System (ADS)

Nowell, Lucy T.

2011-01-01

Driven by market forces and spanning the full spectrum of computational devices, computer architectures are changing in ways that present tremendous opportunities and challenges for data analysis and visual analytic technologies. Leadership-class high performance computing system will have as many as a million cores by 2020 and support 10 billion-way concurrency, while laptop computers are expected to have as many as 1,000 cores by 2015. At the same time, data of all types are increasing exponentially and automated analytic methods are essential for all disciplines. Many existing analytic technologies do not scale to make full use of current platforms and fewer still are likely to scale to the systems that will be operational by the end of this decade. Furthermore, on the new architectures and for data at extreme scales, validating the accuracy and effectiveness of analytic methods, including visual analysis, will be increasingly important.