Innovations in biomedical nanoengineering: nanowell array biosensor

NASA Astrophysics Data System (ADS)

Seo, YoungTae; Jeong, Sunil; Lee, JuKyung; Choi, Hak Soo; Kim, Jonghan; Lee, HeaYeon

2018-04-01

Nanostructured biosensors have pioneered biomedical engineering by providing highly sensitive analyses of biomolecules. The nanowell array (NWA)-based biosensing platform is particularly innovative, where the small size of NWs within the array permits extremely profound sensing of a small quantity of biomolecules. Undoubtedly, the NWA geometry of a gently-sloped vertical wall is critical for selective docking of specific proteins without capillary resistances, and nanoprocessing has contributed to the fabrication of NWA electrodes on gold substrate such as molding process, e-beam lithography, and krypton-fluoride (KrF) stepper semiconductor method. The Lee group at the Mara Nanotech has established this NW-based biosensing technology during the past two decades by engineering highly sensitive electrochemical sensors and providing a broad range of detection methods from large molecules (e.g., cells or proteins) to small molecules (e.g., DNA and RNA). Nanosized gold dots in the NWA enhance the detection of electrochemical biosensing to the range of zeptomoles in precision against the complementary target DNA molecules. In this review, we discuss recent innovations in biomedical nanoengineering with a specific focus on novel NWA-based biosensors. We also describe our continuous efforts in achieving a label-free detection without non-specific binding while maintaining the activity and stability of immobilized biomolecules. This research can lay the foundation of a new platform for biomedical nanoengineering systems.

Zinc Oxide Nanomaterials for Biomedical Fluorescence Detection

PubMed Central

Hahm, Jong-in

2014-01-01

One-dimensional zinc oxide nanomaterials have been recently developed into novel, extremely effective, optical signal-enhancing bioplatforms. Their usefulness has been demonstrated in various biomedical fluorescence assays. Fluorescence is extensively used in biology and medicine as a sensitive and noninvasive detection method for tracking and analyzing biological molecules. Achieving high sensitivity via improving signal-to-noise ratio is of paramount importance in fluorescence-based, trace-level detection. Recent advances in the development of optically superior one-dimensional materials have contributed to this important biomedical area of detection. This review article will discuss major research developments that have so far been made in this emerging and exciting topical field. The discussion will cover a broad range of subjects including synthesis of zinc oxide nanorods (ZnO NRs), various properties differentiating them as suitable optical biodetection platforms, their demonstrated applicability in DNA and protein detection, and the nanomaterial characteristics relevant for biomolecular fluorescence enhancement. This review will then summarize the current status of ZnO NR-based biodetection and further elaborate future utility of ZnO NR platforms for advanced biomedical assays, based on their proven advantages. Lastly, present challenges experienced in this topical area will be identified and focal subject areas for future research will be suggested as well. PMID:24730276

The BioIntelligence Framework: a new computational platform for biomedical knowledge computing.

PubMed

Farley, Toni; Kiefer, Jeff; Lee, Preston; Von Hoff, Daniel; Trent, Jeffrey M; Colbourn, Charles; Mousses, Spyro

2013-01-01

Breakthroughs in molecular profiling technologies are enabling a new data-intensive approach to biomedical research, with the potential to revolutionize how we study, manage, and treat complex diseases. The next great challenge for clinical applications of these innovations will be to create scalable computational solutions for intelligently linking complex biomedical patient data to clinically actionable knowledge. Traditional database management systems (DBMS) are not well suited to representing complex syntactic and semantic relationships in unstructured biomedical information, introducing barriers to realizing such solutions. We propose a scalable computational framework for addressing this need, which leverages a hypergraph-based data model and query language that may be better suited for representing complex multi-lateral, multi-scalar, and multi-dimensional relationships. We also discuss how this framework can be used to create rapid learning knowledge base systems to intelligently capture and relate complex patient data to biomedical knowledge in order to automate the recovery of clinically actionable information.

Recent Advances in Nanobiotechnology and High-Throughput Molecular Techniques for Systems Biomedicine

PubMed Central

Kim, Eung-Sam; Ahn, Eun Hyun; Chung, Euiheon; Kim, Deok-Ho

2013-01-01

Nanotechnology-based tools are beginning to emerge as promising platforms for quantitative high-throughput analysis of live cells and tissues. Despite unprecedented progress made over the last decade, a challenge still lies in integrating emerging nanotechnology-based tools into macroscopic biomedical apparatuses for practical purposes in biomedical sciences. In this review, we discuss the recent advances and limitations in the analysis and control of mechanical, biochemical, fluidic, and optical interactions in the interface areas of nanotechnology-based materials and living cells in both in vitro and in vivo settings. PMID:24258011

KaBOB: ontology-based semantic integration of biomedical databases.

PubMed

Livingston, Kevin M; Bada, Michael; Baumgartner, William A; Hunter, Lawrence E

2015-04-23

The ability to query many independent biological databases using a common ontology-based semantic model would facilitate deeper integration and more effective utilization of these diverse and rapidly growing resources. Despite ongoing work moving toward shared data formats and linked identifiers, significant problems persist in semantic data integration in order to establish shared identity and shared meaning across heterogeneous biomedical data sources. We present five processes for semantic data integration that, when applied collectively, solve seven key problems. These processes include making explicit the differences between biomedical concepts and database records, aggregating sets of identifiers denoting the same biomedical concepts across data sources, and using declaratively represented forward-chaining rules to take information that is variably represented in source databases and integrating it into a consistent biomedical representation. We demonstrate these processes and solutions by presenting KaBOB (the Knowledge Base Of Biomedicine), a knowledge base of semantically integrated data from 18 prominent biomedical databases using common representations grounded in Open Biomedical Ontologies. An instance of KaBOB with data about humans and seven major model organisms can be built using on the order of 500 million RDF triples. All source code for building KaBOB is available under an open-source license. KaBOB is an integrated knowledge base of biomedical data representationally based in prominent, actively maintained Open Biomedical Ontologies, thus enabling queries of the underlying data in terms of biomedical concepts (e.g., genes and gene products, interactions and processes) rather than features of source-specific data schemas or file formats. KaBOB resolves many of the issues that routinely plague biomedical researchers intending to work with data from multiple data sources and provides a platform for ongoing data integration and development and for formal reasoning over a wealth of integrated biomedical data.

Biomedical Big Data Training Collaborative (BBDTC): An effort to bridge the talent gap in biomedical science and research.

PubMed

Purawat, Shweta; Cowart, Charles; Amaro, Rommie E; Altintas, Ilkay

2016-06-01

The BBDTC (https://biobigdata.ucsd.edu) is a community-oriented platform to encourage high-quality knowledge dissemination with the aim of growing a well-informed biomedical big data community through collaborative efforts on training and education. The BBDTC collaborative is an e-learning platform that supports the biomedical community to access, develop and deploy open training materials. The BBDTC supports Big Data skill training for biomedical scientists at all levels, and from varied backgrounds. The natural hierarchy of courses allows them to be broken into and handled as modules . Modules can be reused in the context of multiple courses and reshuffled, producing a new and different, dynamic course called a playlist . Users may create playlists to suit their learning requirements and share it with individual users or the wider public. BBDTC leverages the maturity and design of the HUBzero content-management platform for delivering educational content. To facilitate the migration of existing content, the BBDTC supports importing and exporting course material from the edX platform. Migration tools will be extended in the future to support other platforms. Hands-on training software packages, i.e., toolboxes , are supported through Amazon EC2 and Virtualbox virtualization technologies, and they are available as: ( i ) downloadable lightweight Virtualbox Images providing a standardized software tool environment with software packages and test data on their personal machines, and ( ii ) remotely accessible Amazon EC2 Virtual Machines for accessing biomedical big data tools and scalable big data experiments. At the moment, the BBDTC site contains three open Biomedical big data training courses with lecture contents, videos and hands-on training utilizing VM toolboxes, covering diverse topics. The courses have enhanced the hands-on learning environment by providing structured content that users can use at their own pace. A four course biomedical big data series is planned for development in 2016.

Recent advances in nanobiotechnology and high-throughput molecular techniques for systems biomedicine.

PubMed

Kim, Eung-Sam; Ahn, Eun Hyun; Chung, Euiheon; Kim, Deok-Ho

2013-12-01

Nanotechnology-based tools are beginning to emerge as promising platforms for quantitative high-throughput analysis of live cells and tissues. Despite unprecedented progress made over the last decade, a challenge still lies in integrating emerging nanotechnology-based tools into macroscopic biomedical apparatuses for practical purposes in biomedical sciences. In this review, we discuss the recent advances and limitations in the analysis and control of mechanical, biochemical, fluidic, and optical interactions in the interface areas of nanotechnologybased materials and living cells in both in vitro and in vivo settings.

A theoretical-experimental methodology for assessing the sensitivity of biomedical spectral imaging platforms, assays, and analysis methods.

PubMed

Leavesley, Silas J; Sweat, Brenner; Abbott, Caitlyn; Favreau, Peter; Rich, Thomas C

2018-01-01

Spectral imaging technologies have been used for many years by the remote sensing community. More recently, these approaches have been applied to biomedical problems, where they have shown great promise. However, biomedical spectral imaging has been complicated by the high variance of biological data and the reduced ability to construct test scenarios with fixed ground truths. Hence, it has been difficult to objectively assess and compare biomedical spectral imaging assays and technologies. Here, we present a standardized methodology that allows assessment of the performance of biomedical spectral imaging equipment, assays, and analysis algorithms. This methodology incorporates real experimental data and a theoretical sensitivity analysis, preserving the variability present in biomedical image data. We demonstrate that this approach can be applied in several ways: to compare the effectiveness of spectral analysis algorithms, to compare the response of different imaging platforms, and to assess the level of target signature required to achieve a desired performance. Results indicate that it is possible to compare even very different hardware platforms using this methodology. Future applications could include a range of optimization tasks, such as maximizing detection sensitivity or acquisition speed, providing high utility for investigators ranging from design engineers to biomedical scientists. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

BioGraph: unsupervised biomedical knowledge discovery via automated hypothesis generation

PubMed Central

2011-01-01

We present BioGraph, a data integration and data mining platform for the exploration and discovery of biomedical information. The platform offers prioritizations of putative disease genes, supported by functional hypotheses. We show that BioGraph can retrospectively confirm recently discovered disease genes and identify potential susceptibility genes, outperforming existing technologies, without requiring prior domain knowledge. Additionally, BioGraph allows for generic biomedical applications beyond gene discovery. BioGraph is accessible at http://www.biograph.be. PMID:21696594

The BioIntelligence Framework: a new computational platform for biomedical knowledge computing

PubMed Central

Farley, Toni; Kiefer, Jeff; Lee, Preston; Von Hoff, Daniel; Trent, Jeffrey M; Colbourn, Charles

2013-01-01

Breakthroughs in molecular profiling technologies are enabling a new data-intensive approach to biomedical research, with the potential to revolutionize how we study, manage, and treat complex diseases. The next great challenge for clinical applications of these innovations will be to create scalable computational solutions for intelligently linking complex biomedical patient data to clinically actionable knowledge. Traditional database management systems (DBMS) are not well suited to representing complex syntactic and semantic relationships in unstructured biomedical information, introducing barriers to realizing such solutions. We propose a scalable computational framework for addressing this need, which leverages a hypergraph-based data model and query language that may be better suited for representing complex multi-lateral, multi-scalar, and multi-dimensional relationships. We also discuss how this framework can be used to create rapid learning knowledge base systems to intelligently capture and relate complex patient data to biomedical knowledge in order to automate the recovery of clinically actionable information. PMID:22859646

SATORI: a system for ontology-guided visual exploration of biomedical data repositories.

PubMed

Lekschas, Fritz; Gehlenborg, Nils

2018-04-01

The ever-increasing number of biomedical datasets provides tremendous opportunities for re-use but current data repositories provide limited means of exploration apart from text-based search. Ontological metadata annotations provide context by semantically relating datasets. Visualizing this rich network of relationships can improve the explorability of large data repositories and help researchers find datasets of interest. We developed SATORI-an integrative search and visual exploration interface for the exploration of biomedical data repositories. The design is informed by a requirements analysis through a series of semi-structured interviews. We evaluated the implementation of SATORI in a field study on a real-world data collection. SATORI enables researchers to seamlessly search, browse and semantically query data repositories via two visualizations that are highly interconnected with a powerful search interface. SATORI is an open-source web application, which is freely available at http://satori.refinery-platform.org and integrated into the Refinery Platform. nils@hms.harvard.edu. Supplementary data are available at Bioinformatics online.

A midas plugin to enable construction of reproducible web-based image processing pipelines

PubMed Central

Grauer, Michael; Reynolds, Patrick; Hoogstoel, Marion; Budin, Francois; Styner, Martin A.; Oguz, Ipek

2013-01-01

Image processing is an important quantitative technique for neuroscience researchers, but difficult for those who lack experience in the field. In this paper we present a web-based platform that allows an expert to create a brain image processing pipeline, enabling execution of that pipeline even by those biomedical researchers with limited image processing knowledge. These tools are implemented as a plugin for Midas, an open-source toolkit for creating web based scientific data storage and processing platforms. Using this plugin, an image processing expert can construct a pipeline, create a web-based User Interface, manage jobs, and visualize intermediate results. Pipelines are executed on a grid computing platform using BatchMake and HTCondor. This represents a new capability for biomedical researchers and offers an innovative platform for scientific collaboration. Current tools work well, but can be inaccessible for those lacking image processing expertise. Using this plugin, researchers in collaboration with image processing experts can create workflows with reasonable default settings and streamlined user interfaces, and data can be processed easily from a lab environment without the need for a powerful desktop computer. This platform allows simplified troubleshooting, centralized maintenance, and easy data sharing with collaborators. These capabilities enable reproducible science by sharing datasets and processing pipelines between collaborators. In this paper, we present a description of this innovative Midas plugin, along with results obtained from building and executing several ITK based image processing workflows for diffusion weighted MRI (DW MRI) of rodent brain images, as well as recommendations for building automated image processing pipelines. Although the particular image processing pipelines developed were focused on rodent brain MRI, the presented plugin can be used to support any executable or script-based pipeline. PMID:24416016

A midas plugin to enable construction of reproducible web-based image processing pipelines.

PubMed

Grauer, Michael; Reynolds, Patrick; Hoogstoel, Marion; Budin, Francois; Styner, Martin A; Oguz, Ipek

2013-01-01

Image processing is an important quantitative technique for neuroscience researchers, but difficult for those who lack experience in the field. In this paper we present a web-based platform that allows an expert to create a brain image processing pipeline, enabling execution of that pipeline even by those biomedical researchers with limited image processing knowledge. These tools are implemented as a plugin for Midas, an open-source toolkit for creating web based scientific data storage and processing platforms. Using this plugin, an image processing expert can construct a pipeline, create a web-based User Interface, manage jobs, and visualize intermediate results. Pipelines are executed on a grid computing platform using BatchMake and HTCondor. This represents a new capability for biomedical researchers and offers an innovative platform for scientific collaboration. Current tools work well, but can be inaccessible for those lacking image processing expertise. Using this plugin, researchers in collaboration with image processing experts can create workflows with reasonable default settings and streamlined user interfaces, and data can be processed easily from a lab environment without the need for a powerful desktop computer. This platform allows simplified troubleshooting, centralized maintenance, and easy data sharing with collaborators. These capabilities enable reproducible science by sharing datasets and processing pipelines between collaborators. In this paper, we present a description of this innovative Midas plugin, along with results obtained from building and executing several ITK based image processing workflows for diffusion weighted MRI (DW MRI) of rodent brain images, as well as recommendations for building automated image processing pipelines. Although the particular image processing pipelines developed were focused on rodent brain MRI, the presented plugin can be used to support any executable or script-based pipeline.

Design and Development of Micro-Power Generating Device for Biomedical Applications of Lab-on-a-Disc.

PubMed

Joseph, Karunan; Ibrahim, Fatimah; Cho, Jongman; Thio, Tzer Hwai Gilbert; Al-Faqheri, Wisam; Madou, Marc

2015-01-01

The development of micro-power generators for centrifugal microfluidic discs enhances the platform as a green point-of-care diagnostic system and eliminates the need for attaching external peripherals to the disc. In this work, we present micro-power generators that harvest energy from the disc's rotational movement to power biomedical applications on the disc. To implement these ideas, we developed two types of micro-power generators using piezoelectric films and an electromagnetic induction system. The piezoelectric-based generator takes advantage of the film's vibration during the disc's rotational motion, whereas the electromagnetic induction-based generator operates on the principle of current generation in stacks of coil exposed to varying magnetic flux. We have successfully demonstrated that at the spinning speed of 800 revolutions per minute (RPM) the piezoelectric film-based generator is able to produce up to 24 microwatts using 6 sets of films and the magnetic induction-based generator is capable of producing up to 125 milliwatts using 6 stacks of coil. As a proof of concept, a custom made localized heating system was constructed to test the capability of the magnetic induction-based generator. The heating system was able to achieve a temperature of 58.62 °C at 2200 RPM. This development of lab-on-a-disc micro power generators preserves the portability standards and enhances the future biomedical applications of centrifugal microfluidic platforms.

Tumor-on-a-chip platforms for assessing nanoparticle-based cancer therapy.

PubMed

Wang, Yimin; Cuzzucoli, Fabio; Escobar, Andres; Lu, Siming; Liang, Liguo; Wang, ShuQi

2018-08-17

Cancer has become the most prevalent cause of deaths, placing a huge economic and healthcare burden worldwide. Nanoparticles (NPs), as a key component of nanomedicine, provide alternative options for promoting the efficacy of cancer therapy. Current conventional cancer models have limitations in predicting the effects of various cancer treatments. To overcome these limitations, biomimetic and novel 'tumor-on-a-chip' platforms have emerged with other innovative biomedical engineering methods that enable the evaluation of NP-based cancer therapy. In this review, we first describe cancer models for evaluation of NP-based cancer therapy techniques, and then present the latest advances in 'tumor-on-a-chip' platforms that can potentially facilitate clinical translation of NP-based cancer therapies.

Generating Researcher Networks with Identified Persons on a Semantic Service Platform

NASA Astrophysics Data System (ADS)

Jung, Hanmin; Lee, Mikyoung; Kim, Pyung; Lee, Seungwoo

This paper describes a Semantic Web-based method to acquire researcher networks by means of identification scheme, ontology, and reasoning. Three steps are required to realize it; resolving co-references, finding experts, and generating researcher networks. We adopt OntoFrame as an underlying semantic service platform and apply reasoning to make direct relations between far-off classes in ontology schema. 453,124 Elsevier journal articles with metadata and full-text documents in information technology and biomedical domains have been loaded and served on the platform as a test set.

High-throughput screening approaches and combinatorial development of biomaterials using microfluidics.

PubMed

Barata, David; van Blitterswijk, Clemens; Habibovic, Pamela

2016-04-01

From the first microfluidic devices used for analysis of single metabolic by-products to highly complex multicompartmental co-culture organ-on-chip platforms, efforts of many multidisciplinary teams around the world have been invested in overcoming the limitations of conventional research methods in the biomedical field. Close spatial and temporal control over fluids and physical parameters, integration of sensors for direct read-out as well as the possibility to increase throughput of screening through parallelization, multiplexing and automation are some of the advantages of microfluidic over conventional, 2D tissue culture in vitro systems. Moreover, small volumes and relatively small cell numbers used in experimental set-ups involving microfluidics, can potentially decrease research cost. On the other hand, these small volumes and numbers of cells also mean that many of the conventional molecular biology or biochemistry assays cannot be directly applied to experiments that are performed in microfluidic platforms. Development of different types of assays and evidence that such assays are indeed a suitable alternative to conventional ones is a step that needs to be taken in order to have microfluidics-based platforms fully adopted in biomedical research. In this review, rather than providing a comprehensive overview of the literature on microfluidics, we aim to discuss developments in the field of microfluidics that can aid advancement of biomedical research, with emphasis on the field of biomaterials. Three important topics will be discussed, being: screening, in particular high-throughput and combinatorial screening; mimicking of natural microenvironment ranging from 3D hydrogel-based cellular niches to organ-on-chip devices; and production of biomaterials with closely controlled properties. While important technical aspects of various platforms will be discussed, the focus is mainly on their applications, including the state-of-the-art, future perspectives and challenges. Microfluidics, being a technology characterized by the engineered manipulation of fluids at the submillimeter scale, offers some interesting tools that can advance biomedical research and development. Screening platforms based on microfluidic technologies that allow high-throughput and combinatorial screening may lead to breakthrough discoveries not only in basic research but also relevant to clinical application. This is further strengthened by the fact that reliability of such screens may improve, since microfluidic systems allow close mimicking of physiological conditions. Finally, microfluidic systems are also very promising as micro factories of a new generation of natural or synthetic biomaterials and constructs, with finely controlled properties. Copyright © 2015 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.

Cloud-based bioinformatics workflow platform for large-scale next-generation sequencing analyses

PubMed Central

Liu, Bo; Madduri, Ravi K; Sotomayor, Borja; Chard, Kyle; Lacinski, Lukasz; Dave, Utpal J; Li, Jianqiang; Liu, Chunchen; Foster, Ian T

2014-01-01

Due to the upcoming data deluge of genome data, the need for storing and processing large-scale genome data, easy access to biomedical analyses tools, efficient data sharing and retrieval has presented significant challenges. The variability in data volume results in variable computing and storage requirements, therefore biomedical researchers are pursuing more reliable, dynamic and convenient methods for conducting sequencing analyses. This paper proposes a Cloud-based bioinformatics workflow platform for large-scale next-generation sequencing analyses, which enables reliable and highly scalable execution of sequencing analyses workflows in a fully automated manner. Our platform extends the existing Galaxy workflow system by adding data management capabilities for transferring large quantities of data efficiently and reliably (via Globus Transfer), domain-specific analyses tools preconfigured for immediate use by researchers (via user-specific tools integration), automatic deployment on Cloud for on-demand resource allocation and pay-as-you-go pricing (via Globus Provision), a Cloud provisioning tool for auto-scaling (via HTCondor scheduler), and the support for validating the correctness of workflows (via semantic verification tools). Two bioinformatics workflow use cases as well as performance evaluation are presented to validate the feasibility of the proposed approach. PMID:24462600

Cloud-based bioinformatics workflow platform for large-scale next-generation sequencing analyses.

PubMed

Liu, Bo; Madduri, Ravi K; Sotomayor, Borja; Chard, Kyle; Lacinski, Lukasz; Dave, Utpal J; Li, Jianqiang; Liu, Chunchen; Foster, Ian T

2014-06-01

Due to the upcoming data deluge of genome data, the need for storing and processing large-scale genome data, easy access to biomedical analyses tools, efficient data sharing and retrieval has presented significant challenges. The variability in data volume results in variable computing and storage requirements, therefore biomedical researchers are pursuing more reliable, dynamic and convenient methods for conducting sequencing analyses. This paper proposes a Cloud-based bioinformatics workflow platform for large-scale next-generation sequencing analyses, which enables reliable and highly scalable execution of sequencing analyses workflows in a fully automated manner. Our platform extends the existing Galaxy workflow system by adding data management capabilities for transferring large quantities of data efficiently and reliably (via Globus Transfer), domain-specific analyses tools preconfigured for immediate use by researchers (via user-specific tools integration), automatic deployment on Cloud for on-demand resource allocation and pay-as-you-go pricing (via Globus Provision), a Cloud provisioning tool for auto-scaling (via HTCondor scheduler), and the support for validating the correctness of workflows (via semantic verification tools). Two bioinformatics workflow use cases as well as performance evaluation are presented to validate the feasibility of the proposed approach. Copyright © 2014 Elsevier Inc. All rights reserved.

Design of sensor node platform for wireless biomedical sensor networks.

PubMed

Xijun, Chen; -H Meng, Max; Hongliang, Ren

2005-01-01

Design of low-cost, miniature, lightweight, ultra low-power, flexible sensor platform capable of customization and seamless integration into a wireless biomedical sensor network(WBSN) for health monitoring applications presents one of the most challenging tasks. In this paper, we propose a WBSN node platform featuring an ultra low-power microcontroller, an IEEE 802.15.4 compatible transceiver, and a flexible expansion connector. The proposed solution promises a cost-effective, flexible platform that allows easy customization, energy-efficient computation and communication. The development of a common platform for multiple physical sensors will increase reuse and alleviate costs of transition to a new generation of sensors. As a case study, we present an implementation of an ECG (Electrocardiogram) sensor.

Introducing meta-services for biomedical information extraction

PubMed Central

Leitner, Florian; Krallinger, Martin; Rodriguez-Penagos, Carlos; Hakenberg, Jörg; Plake, Conrad; Kuo, Cheng-Ju; Hsu, Chun-Nan; Tsai, Richard Tzong-Han; Hung, Hsi-Chuan; Lau, William W; Johnson, Calvin A; Sætre, Rune; Yoshida, Kazuhiro; Chen, Yan Hua; Kim, Sun; Shin, Soo-Yong; Zhang, Byoung-Tak; Baumgartner, William A; Hunter, Lawrence; Haddow, Barry; Matthews, Michael; Wang, Xinglong; Ruch, Patrick; Ehrler, Frédéric; Özgür, Arzucan; Erkan, Güneş; Radev, Dragomir R; Krauthammer, Michael; Luong, ThaiBinh; Hoffmann, Robert; Sander, Chris; Valencia, Alfonso

2008-01-01

We introduce the first meta-service for information extraction in molecular biology, the BioCreative MetaServer (BCMS; ). This prototype platform is a joint effort of 13 research groups and provides automatically generated annotations for PubMed/Medline abstracts. Annotation types cover gene names, gene IDs, species, and protein-protein interactions. The annotations are distributed by the meta-server in both human and machine readable formats (HTML/XML). This service is intended to be used by biomedical researchers and database annotators, and in biomedical language processing. The platform allows direct comparison, unified access, and result aggregation of the annotations. PMID:18834497

Design and Development of Micro-Power Generating Device for Biomedical Applications of Lab-on-a-Disc

PubMed Central

Joseph, Karunan; Ibrahim, Fatimah; Cho, Jongman; Thio, Tzer Hwai Gilbert; Al-Faqheri, Wisam; Madou, Marc

2015-01-01

The development of micro-power generators for centrifugal microfluidic discs enhances the platform as a green point-of-care diagnostic system and eliminates the need for attaching external peripherals to the disc. In this work, we present micro-power generators that harvest energy from the disc’s rotational movement to power biomedical applications on the disc. To implement these ideas, we developed two types of micro-power generators using piezoelectric films and an electromagnetic induction system. The piezoelectric-based generator takes advantage of the film’s vibration during the disc’s rotational motion, whereas the electromagnetic induction-based generator operates on the principle of current generation in stacks of coil exposed to varying magnetic flux. We have successfully demonstrated that at the spinning speed of 800 revolutions per minute (RPM) the piezoelectric film-based generator is able to produce up to 24 microwatts using 6 sets of films and the magnetic induction-based generator is capable of producing up to 125 milliwatts using 6 stacks of coil. As a proof of concept, a custom made localized heating system was constructed to test the capability of the magnetic induction-based generator. The heating system was able to achieve a temperature of 58.62°C at 2200 RPM. This development of lab-on-a-disc micro power generators preserves the portability standards and enhances the future biomedical applications of centrifugal microfluidic platforms. PMID:26422249

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.

The World Wide Web: a review of an emerging internet-based technology for the distribution of biomedical information.

PubMed Central

Lowe, H J; Lomax, E C; Polonkey, S E

1996-01-01

The Internet is rapidly evolving from a resource used primarily by the research community to a true global information network offering a wide range of databases and services. This evolution presents many opportunities for improved access to biomedical information, but Internet-based resources have often been difficult for the non-expert to develop and use. The World Wide Web (WWW) supports an inexpensive, easy-to-use, cross-platform, graphic interface to the Internet that may radically alter the way we retrieve and disseminate medical data. This paper summarizes the Internet and hypertext origins of the WWW, reviews WWW-specific technologies, and describes current and future applications of this technology in medicine and medical informatics. The paper also includes an appendix of useful biomedical WWW servers. PMID:8750386

Rembrandt: Helping Personalized Medicine Become a Reality Through Integrative Translational Research

PubMed Central

Madhavan, Subha; Zenklusen, Jean-Claude; Kotliarov, Yuri; Sahni, Himanso; Fine, Howard A.; Buetow, Kenneth

2009-01-01

Finding better therapies for the treatment of brain tumors is hampered by the lack of consistently obtained molecular data in a large sample set, and ability to integrate biomedical data from disparate sources enabling translation of therapies from bench to bedside. Hence, a critical factor in the advancement of biomedical research and clinical translation is the ease with which data can be integrated, redistributed and analyzed both within and across functional domains. Novel biomedical informatics infrastructure and tools are essential for developing individualized patient treatment based on the specific genomic signatures in each patient’s tumor. Here we present Rembrandt, Repository of Molecular BRAin Neoplasia DaTa, a cancer clinical genomics database and a web-based data mining and analysis platform aimed at facilitating discovery by connecting the dots between clinical information and genomic characterization data. To date, Rembrandt contains data generated through the Glioma Molecular Diagnostic Initiative from 874 glioma specimens comprising nearly 566 gene expression arrays, 834 copy number arrays and 13,472 clinical phenotype data points. Data can be queried and visualized for a selected gene across all data platforms or for multiple genes in a selected platform. Additionally, gene sets can be limited to clinically important annotations including secreted, kinase, membrane, and known gene-anomaly pairs to facilitate the discovery of novel biomarkers and therapeutic targets. We believe that REMBRANDT represents a prototype of how high throughput genomic and clinical data can be integrated in a way that will allow expeditious and efficient translation of laboratory discoveries to the clinic. PMID:19208739

qPortal: A platform for data-driven biomedical research.

PubMed

Mohr, Christopher; Friedrich, Andreas; Wojnar, David; Kenar, Erhan; Polatkan, Aydin Can; Codrea, Marius Cosmin; Czemmel, Stefan; Kohlbacher, Oliver; Nahnsen, Sven

2018-01-01

Modern biomedical research aims at drawing biological conclusions from large, highly complex biological datasets. It has become common practice to make extensive use of high-throughput technologies that produce big amounts of heterogeneous data. In addition to the ever-improving accuracy, methods are getting faster and cheaper, resulting in a steadily increasing need for scalable data management and easily accessible means of analysis. We present qPortal, a platform providing users with an intuitive way to manage and analyze quantitative biological data. The backend leverages a variety of concepts and technologies, such as relational databases, data stores, data models and means of data transfer, as well as front-end solutions to give users access to data management and easy-to-use analysis options. Users are empowered to conduct their experiments from the experimental design to the visualization of their results through the platform. Here, we illustrate the feature-rich portal by simulating a biomedical study based on publically available data. We demonstrate the software's strength in supporting the entire project life cycle. The software supports the project design and registration, empowers users to do all-digital project management and finally provides means to perform analysis. We compare our approach to Galaxy, one of the most widely used scientific workflow and analysis platforms in computational biology. Application of both systems to a small case study shows the differences between a data-driven approach (qPortal) and a workflow-driven approach (Galaxy). qPortal, a one-stop-shop solution for biomedical projects offers up-to-date analysis pipelines, quality control workflows, and visualization tools. Through intensive user interactions, appropriate data models have been developed. These models build the foundation of our biological data management system and provide possibilities to annotate data, query metadata for statistics and future re-analysis on high-performance computing systems via coupling of workflow management systems. Integration of project and data management as well as workflow resources in one place present clear advantages over existing solutions.

SPARK: A Framework for Multi-Scale Agent-Based Biomedical Modeling.

PubMed

Solovyev, Alexey; Mikheev, Maxim; Zhou, Leming; Dutta-Moscato, Joyeeta; Ziraldo, Cordelia; An, Gary; Vodovotz, Yoram; Mi, Qi

2010-01-01

Multi-scale modeling of complex biological systems remains a central challenge in the systems biology community. A method of dynamic knowledge representation known as agent-based modeling enables the study of higher level behavior emerging from discrete events performed by individual components. With the advancement of computer technology, agent-based modeling has emerged as an innovative technique to model the complexities of systems biology. In this work, the authors describe SPARK (Simple Platform for Agent-based Representation of Knowledge), a framework for agent-based modeling specifically designed for systems-level biomedical model development. SPARK is a stand-alone application written in Java. It provides a user-friendly interface, and a simple programming language for developing Agent-Based Models (ABMs). SPARK has the following features specialized for modeling biomedical systems: 1) continuous space that can simulate real physical space; 2) flexible agent size and shape that can represent the relative proportions of various cell types; 3) multiple spaces that can concurrently simulate and visualize multiple scales in biomedical models; 4) a convenient graphical user interface. Existing ABMs of diabetic foot ulcers and acute inflammation were implemented in SPARK. Models of identical complexity were run in both NetLogo and SPARK; the SPARK-based models ran two to three times faster.

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.

Enabling online studies of conceptual relationships between medical terms: developing an efficient web platform.

PubMed

Albin, Aaron; Ji, Xiaonan; Borlawsky, Tara B; Ye, Zhan; Lin, Simon; Payne, Philip Ro; Huang, Kun; Xiang, Yang

2014-10-07

The Unified Medical Language System (UMLS) contains many important ontologies in which terms are connected by semantic relations. For many studies on the relationships between biomedical concepts, the use of transitively associated information from ontologies and the UMLS has been shown to be effective. Although there are a few tools and methods available for extracting transitive relationships from the UMLS, they usually have major restrictions on the length of transitive relations or on the number of data sources. Our goal was to design an efficient online platform that enables efficient studies on the conceptual relationships between any medical terms. To overcome the restrictions of available methods and to facilitate studies on the conceptual relationships between medical terms, we developed a Web platform, onGrid, that supports efficient transitive queries and conceptual relationship studies using the UMLS. This framework uses the latest technique in converting natural language queries into UMLS concepts, performs efficient transitive queries, and visualizes the result paths. It also dynamically builds a relationship matrix for two sets of input biomedical terms. We are thus able to perform effective studies on conceptual relationships between medical terms based on their relationship matrix. The advantage of onGrid is that it can be applied to study any two sets of biomedical concept relations and the relations within one set of biomedical concepts. We use onGrid to study the disease-disease relationships in the Online Mendelian Inheritance in Man (OMIM). By crossvalidating our results with an external database, the Comparative Toxicogenomics Database (CTD), we demonstrated that onGrid is effective for the study of conceptual relationships between medical terms. onGrid is an efficient tool for querying the UMLS for transitive relations, studying the relationship between medical terms, and generating hypotheses.

Black Phosphorus and its Biomedical Applications

PubMed Central

Choi, Jane Ru; Yong, Kar Wey; Choi, Jean Yu; Nilghaz, Azadeh; Lin, Yang; Xu, Jie; Lu, Xiaonan

2018-01-01

Black phosphorus (BP), also known as phosphorene, has attracted recent scientific attention since its first successful exfoliation in 2014 owing to its unique structure and properties. In particular, its exceptional attributes, such as the excellent optical and mechanical properties, electrical conductivity and electron-transfer capacity, contribute to its increasing demand as an alternative to graphene-based materials in biomedical applications. Although the outlook of this material seems promising, its practical applications are still highly challenging. In this review article, we discuss the unique properties of BP, which make it a potential platform for biomedical applications compared to other 2D materials, including graphene, molybdenum disulphide (MoS2), tungsten diselenide (WSe2) and hexagonal boron nitride (h-BN). We then introduce various synthesis methods of BP and review its latest progress in biomedical applications, such as biosensing, drug delivery, photoacoustic imaging and cancer therapies (i.e., photothermal and photodynamic therapies). Lastly, the existing challenges and future perspective of BP in biomedical applications are briefly discussed. PMID:29463996

Magnetic microbubble: A biomedical platform co-constructed from magnetics and acoustics

NASA Astrophysics Data System (ADS)

Yang, Fang; Gu, Zhu-Xiao; Jin, Xin; Wang, Hao-Yao; Gu, Ning

2013-10-01

Generation of magnetic micrbubbles and their basic magnetic and acoustic mechanism are reviewed. The ultrasound (US) and magnetic resonance (MR) dual imaging, the controlled therapeutic delivery, as well as theranostic multifunctions are all introduced based on recent research results. Some on-going research is also discussed.

Current trends for customized biomedical software tools.

PubMed

Khan, Haseeb Ahmad

2017-01-01

In the past, biomedical scientists were solely dependent on expensive commercial software packages for various applications. However, the advent of user-friendly programming languages and open source platforms has revolutionized the development of simple and efficient customized software tools for solving specific biomedical problems. Many of these tools are designed and developed by biomedical scientists independently or with the support of computer experts and often made freely available for the benefit of scientific community. The current trends for customized biomedical software tools are highlighted in this short review.

Ionic Driven Embedment of Hyaluronic Acid Coated Liposomes in Polyelectrolyte Multilayer Films for Local Therapeutic Delivery

NASA Astrophysics Data System (ADS)

Hayward, Stephen L.; Francis, David M.; Sis, Matthew J.; Kidambi, Srivatsan

2015-10-01

The ability to control the spatial distribution and temporal release of a therapeutic remains a central challenge for biomedical research. Here, we report the development and optimization of a novel substrate mediated therapeutic delivery system comprising of hyaluronic acid covalently functionalized liposomes (HALNPs) embedded into polyelectrolyte multilayer (PEM) platform via ionic stabilization. The PEM platform was constructed from sequential deposition of Poly-L-Lysine (PLL) and Poly(Sodium styrene sulfonate) (SPS) “(PLL/SPS)4.5” followed by adsorption of anionic HALNPs. An adsorption affinity assay and saturation curve illustrated the preferential HALNP deposition density for precise therapeutic loading. (PLL/SPS)2.5 capping layer on top of the deposited HALNP monolayer further facilitated complete nanoparticle immobilization, cell adhesion, and provided nanoparticle confinement for controlled linear release profiles of the nanocarrier and encapsulated cargo. To our knowledge, this is the first study to demonstrate the successful embedment of a translatable lipid based nanocarrier into a substrate that allows for temporal and spatial release of both hydrophobic and hydrophilic drugs. Specifically, we have utilized our platform to deliver chemotherapeutic drug Doxorubicin from PEM confined HALNPs. Overall, we believe the development of our HALNP embedded PEM system is significant and will catalyze the usage of substrate mediated delivery platforms in biomedical applications.

Metadata based management and sharing of distributed biomedical data

PubMed Central

Vergara-Niedermayr, Cristobal; Liu, Peiya

2014-01-01

Biomedical research data sharing is becoming increasingly important for researchers to reuse experiments, pool expertise and validate approaches. However, there are many hurdles for data sharing, including the unwillingness to share, lack of flexible data model for providing context information, difficulty to share syntactically and semantically consistent data across distributed institutions, and high cost to provide tools to share the data. SciPort is a web-based collaborative biomedical data sharing platform to support data sharing across distributed organisations. SciPort provides a generic metadata model to flexibly customise and organise the data. To enable convenient data sharing, SciPort provides a central server based data sharing architecture with a one-click data sharing from a local server. To enable consistency, SciPort provides collaborative distributed schema management across distributed sites. To enable semantic consistency, SciPort provides semantic tagging through controlled vocabularies. SciPort is lightweight and can be easily deployed for building data sharing communities. PMID:24834105

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.

Cell and small animal models for phenotypic drug discovery.

PubMed

Szabo, Mihaly; Svensson Akusjärvi, Sara; Saxena, Ankur; Liu, Jianping; Chandrasekar, Gayathri; Kitambi, Satish S

2017-01-01

The phenotype-based drug discovery (PDD) approach is re-emerging as an alternative platform for drug discovery. This review provides an overview of the various model systems and technical advances in imaging and image analyses that strengthen the PDD platform. In PDD screens, compounds of therapeutic value are identified based on the phenotypic perturbations produced irrespective of target(s) or mechanism of action. In this article, examples of phenotypic changes that can be detected and quantified with relative ease in a cell-based setup are discussed. In addition, a higher order of PDD screening setup using small animal models is also explored. As PDD screens integrate physiology and multiple signaling mechanisms during the screening process, the identified hits have higher biomedical applicability. Taken together, this review highlights the advantages gained by adopting a PDD approach in drug discovery. Such a PDD platform can complement target-based systems that are currently in practice to accelerate drug discovery.

Harvest: an open platform for developing web-based biomedical data discovery and reporting applications.

PubMed

Pennington, Jeffrey W; Ruth, Byron; Italia, Michael J; Miller, Jeffrey; Wrazien, Stacey; Loutrel, Jennifer G; Crenshaw, E Bryan; White, Peter S

2014-01-01

Biomedical researchers share a common challenge of making complex data understandable and accessible as they seek inherent relationships between attributes in disparate data types. Data discovery in this context is limited by a lack of query systems that efficiently show relationships between individual variables, but without the need to navigate underlying data models. We have addressed this need by developing Harvest, an open-source framework of modular components, and using it for the rapid development and deployment of custom data discovery software applications. Harvest incorporates visualizations of highly dimensional data in a web-based interface that promotes rapid exploration and export of any type of biomedical information, without exposing researchers to underlying data models. We evaluated Harvest with two cases: clinical data from pediatric cardiology and demonstration data from the OpenMRS project. Harvest's architecture and public open-source code offer a set of rapid application development tools to build data discovery applications for domain-specific biomedical data repositories. All resources, including the OpenMRS demonstration, can be found at http://harvest.research.chop.edu.

Harvest: an open platform for developing web-based biomedical data discovery and reporting applications

PubMed Central

Pennington, Jeffrey W; Ruth, Byron; Italia, Michael J; Miller, Jeffrey; Wrazien, Stacey; Loutrel, Jennifer G; Crenshaw, E Bryan; White, Peter S

2014-01-01

Biomedical researchers share a common challenge of making complex data understandable and accessible as they seek inherent relationships between attributes in disparate data types. Data discovery in this context is limited by a lack of query systems that efficiently show relationships between individual variables, but without the need to navigate underlying data models. We have addressed this need by developing Harvest, an open-source framework of modular components, and using it for the rapid development and deployment of custom data discovery software applications. Harvest incorporates visualizations of highly dimensional data in a web-based interface that promotes rapid exploration and export of any type of biomedical information, without exposing researchers to underlying data models. We evaluated Harvest with two cases: clinical data from pediatric cardiology and demonstration data from the OpenMRS project. Harvest's architecture and public open-source code offer a set of rapid application development tools to build data discovery applications for domain-specific biomedical data repositories. All resources, including the OpenMRS demonstration, can be found at http://harvest.research.chop.edu PMID:24131510

Tackling the challenges of matching biomedical ontologies.

PubMed

Faria, Daniel; Pesquita, Catia; Mott, Isabela; Martins, Catarina; Couto, Francisco M; Cruz, Isabel F

2018-01-15

Biomedical ontologies pose several challenges to ontology matching due both to the complexity of the biomedical domain and to the characteristics of the ontologies themselves. The biomedical tracks in the Ontology Matching Evaluation Initiative (OAEI) have spurred the development of matching systems able to tackle these challenges, and benchmarked their general performance. In this study, we dissect the strategies employed by matching systems to tackle the challenges of matching biomedical ontologies and gauge the impact of the challenges themselves on matching performance, using the AgreementMakerLight (AML) system as the platform for this study. We demonstrate that the linear complexity of the hash-based searching strategy implemented by most state-of-the-art ontology matching systems is essential for matching large biomedical ontologies efficiently. We show that accounting for all lexical annotations (e.g., labels and synonyms) in biomedical ontologies leads to a substantial improvement in F-measure over using only the primary name, and that accounting for the reliability of different types of annotations generally also leads to a marked improvement. Finally, we show that cross-references are a reliable source of information and that, when using biomedical ontologies as background knowledge, it is generally more reliable to use them as mediators than to perform lexical expansion. We anticipate that translating traditional matching algorithms to the hash-based searching paradigm will be a critical direction for the future development of the field. Improving the evaluation carried out in the biomedical tracks of the OAEI will also be important, as without proper reference alignments there is only so much that can be ascertained about matching systems or strategies. Nevertheless, it is clear that, to tackle the various challenges posed by biomedical ontologies, ontology matching systems must be able to efficiently combine multiple strategies into a mature matching approach.

ReVeaLD: a user-driven domain-specific interactive search platform for biomedical research.

PubMed

Kamdar, Maulik R; Zeginis, Dimitris; Hasnain, Ali; Decker, Stefan; Deus, Helena F

2014-02-01

Bioinformatics research relies heavily on the ability to discover and correlate data from various sources. The specialization of life sciences over the past decade, coupled with an increasing number of biomedical datasets available through standardized interfaces, has created opportunities towards new methods in biomedical discovery. Despite the popularity of semantic web technologies in tackling the integrative bioinformatics challenge, there are many obstacles towards its usage by non-technical research audiences. In particular, the ability to fully exploit integrated information needs using improved interactive methods intuitive to the biomedical experts. In this report we present ReVeaLD (a Real-time Visual Explorer and Aggregator of Linked Data), a user-centered visual analytics platform devised to increase intuitive interaction with data from distributed sources. ReVeaLD facilitates query formulation using a domain-specific language (DSL) identified by biomedical experts and mapped to a self-updated catalogue of elements from external sources. ReVeaLD was implemented in a cancer research setting; queries included retrieving data from in silico experiments, protein modeling and gene expression. ReVeaLD was developed using Scalable Vector Graphics and JavaScript and a demo with explanatory video is available at http://www.srvgal78.deri.ie:8080/explorer. A set of user-defined graphic rules controls the display of information through media-rich user interfaces. Evaluation of ReVeaLD was carried out as a game: biomedical researchers were asked to assemble a set of 5 challenge questions and time and interactions with the platform were recorded. Preliminary results indicate that complex queries could be formulated under less than two minutes by unskilled researchers. The results also indicate that supporting the identification of the elements of a DSL significantly increased intuitiveness of the platform and usability of semantic web technologies by domain users. Copyright © 2013 The Authors. Published by Elsevier Inc. All rights reserved.

Biomedical Informatics on the Cloud: A Treasure Hunt for Advancing Cardiovascular Medicine.

PubMed

Ping, Peipei; Hermjakob, Henning; Polson, Jennifer S; Benos, Panagiotis V; Wang, Wei

2018-04-27

In the digital age of cardiovascular medicine, the rate of biomedical discovery can be greatly accelerated by the guidance and resources required to unearth potential collections of knowledge. A unified computational platform leverages metadata to not only provide direction but also empower researchers to mine a wealth of biomedical information and forge novel mechanistic insights. This review takes the opportunity to present an overview of the cloud-based computational environment, including the functional roles of metadata, the architecture schema of indexing and search, and the practical scenarios of machine learning-supported molecular signature extraction. By introducing several established resources and state-of-the-art workflows, we share with our readers a broadly defined informatics framework to phenotype cardiovascular health and disease. © 2018 American Heart Association, Inc.

Combining clinical and genomics queries using i2b2 – Three methods

PubMed Central

Murphy, Shawn N.; Avillach, Paul; Bellazzi, Riccardo; Phillips, Lori; Gabetta, Matteo; Eran, Alal; McDuffie, Michael T.; Kohane, Isaac S.

2017-01-01

We are fortunate to be living in an era of twin biomedical data surges: a burgeoning representation of human phenotypes in the medical records of our healthcare systems, and high-throughput sequencing making rapid technological advances. The difficulty representing genomic data and its annotations has almost by itself led to the recognition of a biomedical “Big Data” challenge, and the complexity of healthcare data only compounds the problem to the point that coherent representation of both systems on the same platform seems insuperably difficult. We investigated the capability for complex, integrative genomic and clinical queries to be supported in the Informatics for Integrating Biology and the Bedside (i2b2) translational software package. Three different data integration approaches were developed: The first is based on Sequence Ontology, the second is based on the tranSMART engine, and the third on CouchDB. These novel methods for representing and querying complex genomic and clinical data on the i2b2 platform are available today for advancing precision medicine. PMID:28388645

Wafer-scale integrated micro-supercapacitors on an ultrathin and highly flexible biomedical platform.

PubMed

Maeng, Jimin; Meng, Chuizhou; Irazoqui, Pedro P

2015-02-01

We present wafer-scale integrated micro-supercapacitors on an ultrathin and highly flexible parylene platform, as progress toward sustainably powering biomedical microsystems suitable for implantable and wearable applications. All-solid-state, low-profile (<30 μm), and high-density (up to ~500 μF/mm(2)) micro-supercapacitors are formed on an ultrathin (~20 μm) freestanding parylene film by a wafer-scale parylene packaging process in combination with a polyaniline (PANI) nanowire growth technique assisted by surface plasma treatment. These micro-supercapacitors are highly flexible and shown to be resilient toward flexural stress. Further, direct integration of micro-supercapacitors into a radio frequency (RF) rectifying circuit is achieved on a single parylene platform, yielding a complete RF energy harvesting microsystem. The system discharging rate is shown to improve by ~17 times in the presence of the integrated micro-supercapacitors. This result suggests that the integrated micro-supercapacitor technology described herein is a promising strategy for sustainably powering biomedical microsystems dedicated to implantable and wearable applications.

Integrated Circuit-Based Biofabrication with Common Biomaterials for Probing Cellular Biomechanics.

PubMed

Sung, Chun-Yen; Yang, Chung-Yao; Yeh, J Andrew; Cheng, Chao-Min

2016-02-01

Recent advances in bioengineering have enabled the development of biomedical tools with modifiable surface features (small-scale architecture) to mimic extracellular matrices and aid in the development of well-controlled platforms that allow for the application of mechanical stimulation for studying cellular biomechanics. An overview of recent developments in common biomaterials that can be manufactured using integrated circuit-based biofabrication is presented. Integrated circuit-based biofabrication possesses advantages including mass and diverse production capacities for fabricating in vitro biomedical devices. This review highlights the use of common biomaterials that have been most frequently used to study cellular biomechanics. In addition, the influence of various small-scale characteristics on common biomaterial surfaces for a range of different cell types is discussed. Copyright © 2015 Elsevier Ltd. All rights reserved.

A game-based platform for crowd-sourcing biomedical image diagnosis and standardized remote training and education of diagnosticians

NASA Astrophysics Data System (ADS)

Feng, Steve; Woo, Minjae; Chandramouli, Krithika; Ozcan, Aydogan

2015-03-01

Over the past decade, crowd-sourcing complex image analysis tasks to a human crowd has emerged as an alternative to energy-inefficient and difficult-to-implement computational approaches. Following this trend, we have developed a mathematical framework for statistically combining human crowd-sourcing of biomedical image analysis and diagnosis through games. Using a web-based smart game (BioGames), we demonstrated this platform's effectiveness for telediagnosis of malaria from microscopic images of individual red blood cells (RBCs). After public release in early 2012 (http://biogames.ee.ucla.edu), more than 3000 gamers (experts and non-experts) used this BioGames platform to diagnose over 2800 distinct RBC images, marking them as positive (infected) or negative (non-infected). Furthermore, we asked expert diagnosticians to tag the same set of cells with labels of positive, negative, or questionable (insufficient information for a reliable diagnosis) and statistically combined their decisions to generate a gold standard malaria image library. Our framework utilized minimally trained gamers' diagnoses to generate a set of statistical labels with an accuracy that is within 98% of our gold standard image library, demonstrating the "wisdom of the crowd". Using the same image library, we have recently launched a web-based malaria training and educational game allowing diagnosticians to compare their performance with their peers. After diagnosing a set of ~500 cells per game, diagnosticians can compare their quantified scores against a leaderboard and view their misdiagnosed cells. Using this platform, we aim to expand our gold standard library with new RBC images and provide a quantified digital tool for measuring and improving diagnostician training globally.

RMS: a platform for managing cross-disciplinary and multi-institutional research project collaboration.

PubMed

Luo, Jake; Apperson-Hansen, Carolyn; Pelfrey, Clara M; Zhang, Guo-Qiang

2014-11-30

Cross-institutional cross-disciplinary collaboration has become a trend as researchers move toward building more productive and innovative teams for scientific research. Research collaboration is significantly changing the organizational structure and strategies used in the clinical and translational science domain. However, due to the obstacles of diverse administrative structures, differences in area of expertise, and communication barriers, establishing and managing a cross-institutional research project is still a challenging task. We address these challenges by creating an integrated informatics platform to reduce the barriers to biomedical research collaboration. The Request Management System (RMS) is an informatics infrastructure designed to transform a patchwork of expertise and resources into an integrated support network. The RMS facilitates investigators' initiation of new collaborative projects and supports the management of the collaboration process. In RMS, experts and their knowledge areas are categorized and managed structurally to provide consistent service. A role-based collaborative workflow is tightly integrated with domain experts and services to streamline and monitor the life-cycle of a research project. The RMS has so far tracked over 1,500 investigators with over 4,800 tasks. The research network based on the data collected in RMS illustrated that the investigators' collaborative projects increased close to 3 times from 2009 to 2012. Our experience with RMS indicates that the platform reduces barriers for cross-institutional collaboration of biomedical research projects. Building a new generation of infrastructure to enhance cross-disciplinary and multi-institutional collaboration has become an important yet challenging task. In this paper, we share the experience of developing and utilizing a collaborative project management system. The results of this study demonstrate that a web-based integrated informatics platform can facilitate and increase research interactions among investigators.

Biomedical research in a Digital Health Framework

PubMed Central

2014-01-01

This article describes a Digital Health Framework (DHF), benefitting from the lessons learnt during the three-year life span of the FP7 Synergy-COPD project. The DHF aims to embrace the emerging requirements - data and tools - of applying systems medicine into healthcare with a three-tier strategy articulating formal healthcare, informal care and biomedical research. Accordingly, it has been constructed based on three key building blocks, namely, novel integrated care services with the support of information and communication technologies, a personal health folder (PHF) and a biomedical research environment (DHF-research). Details on the functional requirements and necessary components of the DHF-research are extensively presented. Finally, the specifics of the building blocks strategy for deployment of the DHF, as well as the steps toward adoption are analyzed. The proposed architectural solutions and implementation steps constitute a pivotal strategy to foster and enable 4P medicine (Predictive, Preventive, Personalized and Participatory) in practice and should provide a head start to any community and institution currently considering to implement a biomedical research platform. PMID:25472554

Collective intelligence for translational medicine: Crowdsourcing insights and innovation from an interdisciplinary biomedical research community.

PubMed

Budge, Eleanor Jane; Tsoti, Sandra Maria; Howgate, Daniel James; Sivakumar, Shivan; Jalali, Morteza

2015-01-01

Translational medicine bridges the gap between discoveries in biomedical science and their safe and effective clinical application. Despite the gross opportunity afforded by modern research for unparalleled advances in this field, the process of translation remains protracted. Efforts to expedite science translation have included the facilitation of interdisciplinary collaboration within both academic and clinical environments in order to generate integrated working platforms fuelling the sharing of knowledge, expertise, and tools to align biomedical research with clinical need. However, barriers to scientific translation remain, and further progress is urgently required. Collective intelligence and crowdsourcing applications offer the potential for global online networks, allowing connection and collaboration between a wide variety of fields. This would drive the alignment of biomedical science with biotechnology, clinical need, and patient experience, in order to deliver evidence-based innovation which can revolutionize medical care worldwide. Here we discuss the critical steps towards implementing collective intelligence in translational medicine using the experience of those in other fields of science and public health.

The Galaxy platform for accessible, reproducible and collaborative biomedical analyses: 2018 update.

PubMed

Afgan, Enis; Baker, Dannon; Batut, Bérénice; van den Beek, Marius; Bouvier, Dave; Cech, Martin; Chilton, John; Clements, Dave; Coraor, Nate; Grüning, Björn A; Guerler, Aysam; Hillman-Jackson, Jennifer; Hiltemann, Saskia; Jalili, Vahid; Rasche, Helena; Soranzo, Nicola; Goecks, Jeremy; Taylor, James; Nekrutenko, Anton; Blankenberg, Daniel

2018-05-22

Galaxy (homepage: https://galaxyproject.org, main public server: https://usegalaxy.org) is a web-based scientific analysis platform used by tens of thousands of scientists across the world to analyze large biomedical datasets such as those found in genomics, proteomics, metabolomics and imaging. Started in 2005, Galaxy continues to focus on three key challenges of data-driven biomedical science: making analyses accessible to all researchers, ensuring analyses are completely reproducible, and making it simple to communicate analyses so that they can be reused and extended. During the last two years, the Galaxy team and the open-source community around Galaxy have made substantial improvements to Galaxy's core framework, user interface, tools, and training materials. Framework and user interface improvements now enable Galaxy to be used for analyzing tens of thousands of datasets, and >5500 tools are now available from the Galaxy ToolShed. The Galaxy community has led an effort to create numerous high-quality tutorials focused on common types of genomic analyses. The Galaxy developer and user communities continue to grow and be integral to Galaxy's development. The number of Galaxy public servers, developers contributing to the Galaxy framework and its tools, and users of the main Galaxy server have all increased substantially.

Lensfree Computational Microscopy Tools and their Biomedical Applications

NASA Astrophysics Data System (ADS)

Sencan, Ikbal

Conventional microscopy has been a revolutionary tool for biomedical applications since its invention several centuries ago. Ability to non-destructively observe very fine details of biological objects in real time enabled to answer many important questions about their structures and functions. Unfortunately, most of these advance microscopes are complex, bulky, expensive, and/or hard to operate, so they could not reach beyond the walls of well-equipped laboratories. Recent improvements in optoelectronic components and computational methods allow creating imaging systems that better fulfill the specific needs of clinics or research related biomedical applications. In this respect, lensfree computational microscopy aims to replace bulky and expensive optical components with compact and cost-effective alternatives through the use of computation, which can be particularly useful for lab-on-a-chip platforms as well as imaging applications in low-resource settings. Several high-throughput on-chip platforms are built with this approach for applications including, but not limited to, cytometry, micro-array imaging, rare cell analysis, telemedicine, and water quality screening. The lack of optical complexity in these lensfree on-chip imaging platforms is compensated by using computational techniques. These computational methods are utilized for various purposes in coherent, incoherent and fluorescent on-chip imaging platforms e.g. improving the spatial resolution, to undo the light diffraction without using lenses, localization of objects in a large volume and retrieval of the phase or the color/spectral content of the objects. For instance, pixel super resolution approaches based on source shifting are used in lensfree imaging platforms to prevent under sampling, Bayer pattern, and aliasing artifacts. Another method, iterative phase retrieval, is utilized to compensate the lack of lenses by undoing the diffraction and removing the twin image noise of in-line holograms. This technique enables recovering the complex optical field from its intensity measurement(s) by using additional constraints in iterations, such as spatial boundaries and other known properties of objects. Another computational tool employed in lensfree imaging is compressive sensing (or decoding), which is a novel method taking advantage of the fact that natural signals/objects are mostly sparse or compressible in known bases. This inherent property of objects enables better signal recovery when the number of measurement is low, even below the Nyquist rate, and increases the additive noise immunity of the system.

CRISPR editing in biological and biomedical investigation.

PubMed

Huang, Jiaojiao; Wang, Yanfang; Zhao, Jianguo

2018-05-01

Recently, clustered regularly interspaced short palindromic repeats (CRISPR) based genomic editing technologies have armed researchers with powerful new tools to biological and biomedical investigations. To further improve and expand its functionality, natural, and engineered CRISPR associated nine proteins (Cas9s) have been investigated, various CRISPR delivery strategies have been tested and optimized, and multiple schemes have been developed to ensure precise mammalian genome editing. Benefiting from those in-depth understanding and further development of CRISPR, versatile CRISPR-based platforms for genome editing have been rapidly developed to advance investigations in biology and biomedicine. In biological research area, CRISPR has been widely adopted in both fundamental and applied research fields, such as accurate base editing, transcriptional regulation, and genome-wide screening. In biomedical research area, CRISPR has also shown its extensive applicability in the establishment of animal models for genetic disorders especially those large animals and non-human primates models, and gene therapy to combat virus infectious diseases, to correct monogenic disorders in vivo or in pluripotent cells. In this prospect article, after highlighting recent developments of CRISPR systems, we outline different applications and current limitations of CRISPR use in biological and biomedical investigation. Finally, we provide a perspective for future development and potential risks of this multifunctional technology. © 2017 Wiley Periodicals, Inc.

Cloud-Based Smart Health Monitoring System for Automatic Cardiovascular and Fall Risk Assessment in Hypertensive Patients.

PubMed

Melillo, P; Orrico, A; Scala, P; Crispino, F; Pecchia, L

2015-10-01

The aim of this paper is to describe the design and the preliminary validation of a platform developed to collect and automatically analyze biomedical signals for risk assessment of vascular events and falls in hypertensive patients. This m-health platform, based on cloud computing, was designed to be flexible, extensible, and transparent, and to provide proactive remote monitoring via data-mining functionalities. A retrospective study was conducted to train and test the platform. The developed system was able to predict a future vascular event within the next 12 months with an accuracy rate of 84 % and to identify fallers with an accuracy rate of 72 %. In an ongoing prospective trial, almost all the recruited patients accepted favorably the system with a limited rate of inadherences causing data losses (<20 %). The developed platform supported clinical decision by processing tele-monitored data and providing quick and accurate risk assessment of vascular events and falls.

Harvest: a web-based biomedical data discovery and reporting application development platform.

PubMed

Italia, Michael J; Pennington, Jeffrey W; Ruth, Byron; Wrazien, Stacey; Loutrel, Jennifer G; Crenshaw, E Bryan; Miller, Jeffrey; White, Peter S

2013-01-01

Biomedical researchers share a common challenge of making complex data understandable and accessible. This need is increasingly acute as investigators seek opportunities for discovery amidst an exponential growth in the volume and complexity of laboratory and clinical data. To address this need, we developed Harvest, an open source framework that provides a set of modular components to aid the rapid development and deployment of custom data discovery software applications. Harvest incorporates visual representations of multidimensional data types in an intuitive, web-based interface that promotes a real-time, iterative approach to exploring complex clinical and experimental data. The Harvest architecture capitalizes on standards-based, open source technologies to address multiple functional needs critical to a research and development environment, including domain-specific data modeling, abstraction of complex data models, and a customizable web client.

New Tools for New Research in Psychiatry: A Scalable and Customizable Platform to Empower Data Driven Smartphone Research.

PubMed

Torous, John; Kiang, Mathew V; Lorme, Jeanette; Onnela, Jukka-Pekka

2016-05-05

A longstanding barrier to progress in psychiatry, both in clinical settings and research trials, has been the persistent difficulty of accurately and reliably quantifying disease phenotypes. Mobile phone technology combined with data science has the potential to offer medicine a wealth of additional information on disease phenotypes, but the large majority of existing smartphone apps are not intended for use as biomedical research platforms and, as such, do not generate research-quality data. Our aim is not the creation of yet another app per se but rather the establishment of a platform to collect research-quality smartphone raw sensor and usage pattern data. Our ultimate goal is to develop statistical, mathematical, and computational methodology to enable us and others to extract biomedical and clinical insights from smartphone data. We report on the development and early testing of Beiwe, a research platform featuring a study portal, smartphone app, database, and data modeling and analysis tools designed and developed specifically for transparent, customizable, and reproducible biomedical research use, in particular for the study of psychiatric and neurological disorders. We also outline a proposed study using the platform for patients with schizophrenia. We demonstrate the passive data capabilities of the Beiwe platform and early results of its analytical capabilities. Smartphone sensors and phone usage patterns, when coupled with appropriate statistical learning tools, are able to capture various social and behavioral manifestations of illnesses, in naturalistic settings, as lived and experienced by patients. The ubiquity of smartphones makes this type of moment-by-moment quantification of disease phenotypes highly scalable and, when integrated within a transparent research platform, presents tremendous opportunities for research, discovery, and patient health.

New Tools for New Research in Psychiatry: A Scalable and Customizable Platform to Empower Data Driven Smartphone Research

PubMed Central

Torous, John; Kiang, Mathew V; Lorme, Jeanette

2016-01-01

Background A longstanding barrier to progress in psychiatry, both in clinical settings and research trials, has been the persistent difficulty of accurately and reliably quantifying disease phenotypes. Mobile phone technology combined with data science has the potential to offer medicine a wealth of additional information on disease phenotypes, but the large majority of existing smartphone apps are not intended for use as biomedical research platforms and, as such, do not generate research-quality data. Objective Our aim is not the creation of yet another app per se but rather the establishment of a platform to collect research-quality smartphone raw sensor and usage pattern data. Our ultimate goal is to develop statistical, mathematical, and computational methodology to enable us and others to extract biomedical and clinical insights from smartphone data. Methods We report on the development and early testing of Beiwe, a research platform featuring a study portal, smartphone app, database, and data modeling and analysis tools designed and developed specifically for transparent, customizable, and reproducible biomedical research use, in particular for the study of psychiatric and neurological disorders. We also outline a proposed study using the platform for patients with schizophrenia. Results We demonstrate the passive data capabilities of the Beiwe platform and early results of its analytical capabilities. Conclusions Smartphone sensors and phone usage patterns, when coupled with appropriate statistical learning tools, are able to capture various social and behavioral manifestations of illnesses, in naturalistic settings, as lived and experienced by patients. The ubiquity of smartphones makes this type of moment-by-moment quantification of disease phenotypes highly scalable and, when integrated within a transparent research platform, presents tremendous opportunities for research, discovery, and patient health. PMID:27150677

Building biomedical web communities using a semantically aware content management system.

PubMed

Das, Sudeshna; Girard, Lisa; Green, Tom; Weitzman, Louis; Lewis-Bowen, Alister; Clark, Tim

2009-03-01

Web-based biomedical communities are becoming an increasingly popular vehicle for sharing information amongst researchers and are fast gaining an online presence. However, information organization and exchange in such communities is usually unstructured, rendering interoperability between communities difficult. Furthermore, specialized software to create such communities at low cost-targeted at the specific common information requirements of biomedical researchers-has been largely lacking. At the same time, a growing number of biological knowledge bases and biomedical resources are being structured for the Semantic Web. Several groups are creating reference ontologies for the biomedical domain, actively publishing controlled vocabularies and making data available in Resource Description Framework (RDF) language. We have developed the Science Collaboration Framework (SCF) as a reusable platform for advanced structured online collaboration in biomedical research that leverages these ontologies and RDF resources. SCF supports structured 'Web 2.0' style community discourse amongst researchers, makes heterogeneous data resources available to the collaborating scientist, captures the semantics of the relationship among the resources and structures discourse around the resources. The first instance of the SCF framework is being used to create an open-access online community for stem cell research-StemBook (http://www.stembook.org). We believe that such a framework is required to achieve optimal productivity and leveraging of resources in interdisciplinary scientific research. We expect it to be particularly beneficial in highly interdisciplinary areas, such as neurodegenerative disease and neurorepair research, as well as having broad utility across the natural sciences.

The rolling evolution of biomedical science as an essential tool in modern clinical practice.

PubMed

Blann, Andrew

2016-01-01

The British Journal of Biomedical Science is committed to publishing high-quality original research that represents a clear advance in the practice of biomedical science, and reviews that summarise recent advances in the field of biomedical science. The overall aim of the Journal is to provide a platform for the dissemination of new and innovative information on the diagnosis and management of disease that is valuable to the practicing laboratory scientist. The Editorial that follows describes the Journal and provides a perspective of its aims and objectives.

Successful fabrication of a convex platform PMMA cell-counting slide using a high-precision perpendicular dual-spindle CNC machine tool

NASA Astrophysics Data System (ADS)

Chen, Shun-Tong; Chang, Chih-Hsien

2013-12-01

This study presents a novel approach to the fabrication of a biomedical-mold for producing convex platform PMMA (poly-methyl-meth-acrylate) slides for counting cells. These slides allow for the microscopic examination of urine sediment cells. Manufacturing of such slides incorporates three important procedures: (1) the development of a tabletop high-precision dual-spindle CNC (computerized numerical control) machine tool; (2) the formation of a boron-doped polycrystalline composite diamond (BD-PCD) wheel-tool on the machine tool developed in procedure (1); and (3) the cutting of a multi-groove-biomedical-mold array using the formed diamond wheel-tool in situ on the developed machine. The machine incorporates a hybrid working platform providing wheel-tool thinning using spark erosion to cut, polish, and deburr microgrooves on NAK80 steel directly. With consideration given for the electrical conductive properties of BD-PCD, the diamond wheel-tool is thinned to a thickness of 5 µm by rotary wire electrical discharge machining. The thinned wheel-tool can grind microgrooves 10 µm wide. An embedded design, which inserts a close fitting precision core into the biomedical-mold to create step-difference (concave inward) of 50 µm in height between the core and the mold, is also proposed and realized. The perpendicular dual-spindles and precision rotary stage are features that allow for biomedical-mold machining without the necessity of uploading and repositioning materials until all tasks are completed. A PMMA biomedical-slide with a plurality of juxtaposed counting chambers is formed and its usefulness verified.

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

Combining unique properties of dendrimers and magnetic nanoparticles towards cancer theranostics.

PubMed

Chandra, Sudeshna; Nigam, Saumya; Bahadur, Dhirendra

2014-01-01

Magnetic nanoparticles (MNPs) are a well explored class of nanomaterials, known for their high magnetization and biocompatibility thus finding their way in several biomedical applications viz., drug delivery, magnetic resonance imaging contrast agent, immunoassay, detoxification of biological fluids and cell separation, biosensing and hyperthermia. On other hand, dendrimers are a class of hyperbranched, mostly symmetrical polymers that originate from a central core with repetitive branching units, called monomers, thus forming a globular structure. Due to their structural properties and controlled size, dendrimers have emerged as an attractive material for biomedical applications particularly as carriers for therapeutic cargo. Of late, researchers have started attempting to combine the unique features of dendrimer chemistry with the versatile magnetic nanoparticles to provide a facile platform for enhanced therapeutics and biomedical applications. This review intends to present the advances made towards fabrication of dendrimer based magnetic nanoparticles with varied surface architecture and their contribution towards theranostics, particularly for cancer.

The Galaxy platform for accessible, reproducible and collaborative biomedical analyses: 2016 update

PubMed Central

Afgan, Enis; Baker, Dannon; van den Beek, Marius; Blankenberg, Daniel; Bouvier, Dave; Čech, Martin; Chilton, John; Clements, Dave; Coraor, Nate; Eberhard, Carl; Grüning, Björn; Guerler, Aysam; Hillman-Jackson, Jennifer; Von Kuster, Greg; Rasche, Eric; Soranzo, Nicola; Turaga, Nitesh; Taylor, James; Nekrutenko, Anton; Goecks, Jeremy

2016-01-01

High-throughput data production technologies, particularly ‘next-generation’ DNA sequencing, have ushered in widespread and disruptive changes to biomedical research. Making sense of the large datasets produced by these technologies requires sophisticated statistical and computational methods, as well as substantial computational power. This has led to an acute crisis in life sciences, as researchers without informatics training attempt to perform computation-dependent analyses. Since 2005, the Galaxy project has worked to address this problem by providing a framework that makes advanced computational tools usable by non experts. Galaxy seeks to make data-intensive research more accessible, transparent and reproducible by providing a Web-based environment in which users can perform computational analyses and have all of the details automatically tracked for later inspection, publication, or reuse. In this report we highlight recently added features enabling biomedical analyses on a large scale. PMID:27137889

Characteristics Desired in Clinical Data Warehouse for Biomedical Research

PubMed Central

Shin, Soo-Yong; Kim, Woo Sung

2014-01-01

Objectives Due to the unique characteristics of clinical data, clinical data warehouses (CDWs) have not been successful so far. Specifically, the use of CDWs for biomedical research has been relatively unsuccessful thus far. The characteristics necessary for the successful implementation and operation of a CDW for biomedical research have not clearly defined yet. Methods Three examples of CDWs were reviewed: a multipurpose CDW in a hospital, a CDW for independent multi-institutional research, and a CDW for research use in an institution. After reviewing the three CDW examples, we propose some key characteristics needed in a CDW for biomedical research. Results A CDW for research should include an honest broker system and an Institutional Review Board approval interface to comply with governmental regulations. It should also include a simple query interface, an anonymized data review tool, and a data extraction tool. Also, it should be a biomedical research platform for data repository use as well as data analysis. Conclusions The proposed characteristics desired in a CDW may have limited transfer value to organizations in other countries. However, these analysis results are still valid in Korea, and we have developed clinical research data warehouse based on these desiderata. PMID:24872909

Biomedical instruments versus toys:a preliminary comparison of force platforms and the nintendo wii balance board - biomed 2011.

PubMed

Pagnacco, Guido; Oggero, Elena; Wright, Cameron H G

2011-01-01

Biomedical sciences rely heavily on devices to acquire and analyze the physiological data needed to understand and model the biological processes of humans and animals. Therefore, the results of the investigations, clinical or academic, depend heavily on the instrumentation used. Unfortunately, all too often the users do not understand their instruments and end up compromising the results of their investigations by choosing an inadequate instrument or by not using it appropriately. One field where this is particularly apparent is posturography: the misconceptions about instruments are so widespread and deep that just recently there have been articles published in scientific journals suggesting the use of a “toy”, the Nintendo Wii Balance Board, instead of instrument grade force platform to acquire posturographic data. Characterizing the tools used for research becomes the first and probably the most important step in producing sound research and clinical results, and in the case of posturographic force platforms and the Nintendo Wii Balance Board a simple experimental setup can be used to find their characteristics. Furthermore, based on the preliminary results of this investigation, a mathematical formula can be used to predict the behavior of a posturographic tool, once its noise characteristics and “dead weight” response are known.

A game-based crowdsourcing platform for rapidly training middle and high school students to perform biomedical image analysis

NASA Astrophysics Data System (ADS)

Feng, Steve; Woo, Min-jae; Kim, Hannah; Kim, Eunso; Ki, Sojung; Shao, Lei; Ozcan, Aydogan

2016-03-01

We developed an easy-to-use and widely accessible crowd-sourcing tool for rapidly training humans to perform biomedical image diagnostic tasks and demonstrated this platform's ability on middle and high school students in South Korea to diagnose malaria infected red-blood-cells (RBCs) using Giemsa-stained thin blood smears imaged under light microscopes. We previously used the same platform (i.e., BioGames) to crowd-source diagnostics of individual RBC images, marking them as malaria positive (infected), negative (uninfected), or questionable (insufficient information for a reliable diagnosis). Using a custom-developed statistical framework, we combined the diagnoses from both expert diagnosticians and the minimally trained human crowd to generate a gold standard library of malaria-infection labels for RBCs. Using this library of labels, we developed a web-based training and educational toolset that provides a quantified score for diagnosticians/users to compare their performance against their peers and view misdiagnosed cells. We have since demonstrated the ability of this platform to quickly train humans without prior training to reach high diagnostic accuracy as compared to expert diagnosticians. Our initial trial group of 55 middle and high school students has collectively played more than 170 hours, each demonstrating significant improvements after only 3 hours of training games, with diagnostic scores that match expert diagnosticians'. Next, through a national-scale educational outreach program in South Korea we recruited >1660 students who demonstrated a similar performance level after 5 hours of training. We plan to further demonstrate this tool's effectiveness for other diagnostic tasks involving image labeling and aim to provide an easily-accessible and quickly adaptable framework for online training of new diagnosticians.

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

Miniaturizable Ion-Selective Arrays Based on Highly Stable Polymer Membranes for Biomedical Applications

PubMed Central

Mir, Mònica; Lugo, Roberto; Tahirbegi, Islam Bogachan; Samitier, Josep

2014-01-01

Poly(vinylchloride) (PVC) is the most common polymer matrix used in the fabrication of ion-selective electrodes (ISEs). However, the surfaces of PVC-based sensors have been reported to show membrane instability. In an attempt to overcome this limitation, here we developed two alternative methods for the preparation of highly stable and robust ion-selective sensors. These platforms are based on the selective electropolymerization of poly(3,4-ethylenedioxythiophene) (PEDOT), where the sulfur atoms contained in the polymer covalently interact with the gold electrode, also permitting controlled selective attachment on a miniaturized electrode in an array format. This platform sensor was improved with the crosslinking of the membrane compounds with poly(ethyleneglycol) diglycidyl ether (PEG), thus also increasing the biocompatibility of the sensor. The resulting ISE membranes showed faster signal stabilization of the sensor response compared with that of the PVC matrix and also better reproducibility and stability, thus making these platforms highly suitable candidates for the manufacture of robust implantable sensors. PMID:24999717

A Versatile Microarray Platform for Capturing Rare Cells

NASA Astrophysics Data System (ADS)

Brinkmann, Falko; Hirtz, Michael; Haller, Anna; Gorges, Tobias M.; Vellekoop, Michael J.; Riethdorf, Sabine; Müller, Volkmar; Pantel, Klaus; Fuchs, Harald

2015-10-01

Analyses of rare events occurring at extremely low frequencies in body fluids are still challenging. We established a versatile microarray-based platform able to capture single target cells from large background populations. As use case we chose the challenging application of detecting circulating tumor cells (CTCs) - about one cell in a billion normal blood cells. After incubation with an antibody cocktail, targeted cells are extracted on a microarray in a microfluidic chip. The accessibility of our platform allows for subsequent recovery of targets for further analysis. The microarray facilitates exclusion of false positive capture events by co-localization allowing for detection without fluorescent labelling. Analyzing blood samples from cancer patients with our platform reached and partly outreached gold standard performance, demonstrating feasibility for clinical application. Clinical researchers free choice of antibody cocktail without need for altered chip manufacturing or incubation protocol, allows virtual arbitrary targeting of capture species and therefore wide spread applications in biomedical sciences.

Degradable Magnetic Composites for Minimally Invasive Interventions: Device Fabrication, Targeted Drug Delivery, and Cytotoxicity Tests.

PubMed

Peters, Christian; Hoop, Marcus; Pané, Salvador; Nelson, Bradley J; Hierold, Christofer

2016-01-20

Superparamagnetic nanoparticles and a functional, degradable polymer matrix based on poly(ethylene glycol) are combined to enable fully degradable magnetic microdevices for minimally invasive biomedical applications. A bioinspired helical microrobot platform mimicking Escherichia coli bacteria is fabricated and actuated using weak rotating magnetic fields. Locomotion based on corkscrew propulsion, targeted drug delivery, and low-degradation-product cytotoxicity are demonstrated. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

An Ontology-Enabled Natural Language Processing Pipeline for Provenance Metadata Extraction from Biomedical Text (Short Paper).

PubMed

Valdez, Joshua; Rueschman, Michael; Kim, Matthew; Redline, Susan; Sahoo, Satya S

2016-10-01

Extraction of structured information from biomedical literature is a complex and challenging problem due to the complexity of biomedical domain and lack of appropriate natural language processing (NLP) techniques. High quality domain ontologies model both data and metadata information at a fine level of granularity, which can be effectively used to accurately extract structured information from biomedical text. Extraction of provenance metadata, which describes the history or source of information, from published articles is an important task to support scientific reproducibility. Reproducibility of results reported by previous research studies is a foundational component of scientific advancement. This is highlighted by the recent initiative by the US National Institutes of Health called "Principles of Rigor and Reproducibility". In this paper, we describe an effective approach to extract provenance metadata from published biomedical research literature using an ontology-enabled NLP platform as part of the Provenance for Clinical and Healthcare Research (ProvCaRe). The ProvCaRe-NLP tool extends the clinical Text Analysis and Knowledge Extraction System (cTAKES) platform using both provenance and biomedical domain ontologies. We demonstrate the effectiveness of ProvCaRe-NLP tool using a corpus of 20 peer-reviewed publications. The results of our evaluation demonstrate that the ProvCaRe-NLP tool has significantly higher recall in extracting provenance metadata as compared to existing NLP pipelines such as MetaMap.

Home telecare system using cable television plants--an experimental field trial.

PubMed

Lee, R G; Chen, H S; Lin, C C; Chang, K C; Chen, J H

2000-03-01

To solve the inconvenience of routine transportation of chronically ill and handicapped patients, this paper proposes a platform based on a hybrid fiber coaxial (HFC) network in Taiwan designed to make a home telecare system feasible. The aim of this home telecare system is to combine biomedical data, including three-channel electrocardiogram (ECG) and blood pressure (BP), video, and audio into a National Television Standard Committee (NTSC) channel for communication between the patient and healthcare provider. Digitized biomedical data and output from medical devices can be further modulated to a second audio program (SAP) subchannel which can be used for second-language audio in NTSC television signals. For long-distance transmission, we translate the digital biomedical data into the frequency domain using frequency shift key (FSK) technology and insert this signal into an SAP band. The whole system has been implemented and tested. The results obtained using this system clearly demonstrated that real-time video, audio, and biomedical data transmission are very clear with a carrier-to-noise ratio up to 43 dB.

Biomedical applications of nanodiamond (Review)

NASA Astrophysics Data System (ADS)

Turcheniuk, K.; Mochalin, Vadym N.

2017-06-01

The interest in nanodiamond applications in biology and medicine is on the rise over recent years. This is due to the unique combination of properties that nanodiamond provides. Small size (∼5 nm), low cost, scalable production, negligible toxicity, chemical inertness of diamond core and rich chemistry of nanodiamond surface, as well as bright and robust fluorescence resistant to photobleaching are the distinct parameters that render nanodiamond superior to any other nanomaterial when it comes to biomedical applications. The most exciting recent results have been related to the use of nanodiamonds for drug delivery and diagnostics—two components of a quickly growing area of biomedical research dubbed theranostics. However, nanodiamond offers much more in addition: it can be used to produce biodegradable bone surgery devices, tissue engineering scaffolds, kill drug resistant microbes, help us to fight viruses, and deliver genetic material into cell nucleus. All these exciting opportunities require an in-depth understanding of nanodiamond. This review covers the recent progress as well as general trends in biomedical applications of nanodiamond, and underlines the importance of purification, characterization, and rational modification of this nanomaterial when designing nanodiamond based theranostic platforms.

Real-Time Processing Library for Open-Source Hardware Biomedical Sensors

PubMed Central

Castro-García, Juan A.; Lebrato-Vázquez, Clara

2018-01-01

Applications involving data acquisition from sensors need samples at a preset frequency rate, the filtering out of noise and/or analysis of certain frequency components. We propose a novel software architecture based on open-software hardware platforms which allows programmers to create data streams from input channels and easily implement filters and frequency analysis objects. The performances of the different classes given in the size of memory allocated and execution time (number of clock cycles) were analyzed in the low-cost platform Arduino Genuino. In addition, 11 people took part in an experiment in which they had to implement several exercises and complete a usability test. Sampling rates under 250 Hz (typical for many biomedical applications) makes it feasible to implement filters, sliding windows and Fourier analysis, operating in real time. Participants rated software usability at 70.2 out of 100 and the ease of use when implementing several signal processing applications was rated at just over 4.4 out of 5. Participants showed their intention of using this software because it was percieved as useful and very easy to use. The performances of the library showed that it may be appropriate for implementing small biomedical real-time applications or for human movement monitoring, even in a simple open-source hardware device like Arduino Genuino. The general perception about this library is that it is easy to use and intuitive. PMID:29596394

Real-Time Processing Library for Open-Source Hardware Biomedical Sensors.

PubMed

Molina-Cantero, Alberto J; Castro-García, Juan A; Lebrato-Vázquez, Clara; Gómez-González, Isabel M; Merino-Monge, Manuel

2018-03-29

Applications involving data acquisition from sensors need samples at a preset frequency rate, the filtering out of noise and/or analysis of certain frequency components. We propose a novel software architecture based on open-software hardware platforms which allows programmers to create data streams from input channels and easily implement filters and frequency analysis objects. The performances of the different classes given in the size of memory allocated and execution time (number of clock cycles) were analyzed in the low-cost platform Arduino Genuino. In addition, 11 people took part in an experiment in which they had to implement several exercises and complete a usability test. Sampling rates under 250 Hz (typical for many biomedical applications) makes it feasible to implement filters, sliding windows and Fourier analysis, operating in real time. Participants rated software usability at 70.2 out of 100 and the ease of use when implementing several signal processing applications was rated at just over 4.4 out of 5. Participants showed their intention of using this software because it was percieved as useful and very easy to use. The performances of the library showed that it may be appropriate for implementing small biomedical real-time applications or for human movement monitoring, even in a simple open-source hardware device like Arduino Genuino. The general perception about this library is that it is easy to use and intuitive.

Development of an information platform for new grid users in the biomedical field.

PubMed

Skrowny, Daniela; Dickmann, Frank; Löhnhardt, Benjamin; Knoch, Tobias A; Sax, Ulrich

2010-01-01

Bringing new users into grids is a top priority for all grid initiatives and one of the most challenging tasks. Especially in life sciences it is essential to have a certain amount of users to establish a critical mass for a sustainable grid and give feedback back to the technological middleware layer. Based on the presumable lack of grid IT knowledge it is notably more arduous to satisfy user demands although here the requirements are especially demanding. Therefore, the development of an information- and learning platform could support the efforts of grid experts to guide new users. By providing a platform about grid technology and their feasibilities for users of the community of biomedicine potential, users could be supported using the high potential of their discipline.

NCBO Resource Index: Ontology-Based Search and Mining of Biomedical Resources

PubMed Central

Jonquet, Clement; LePendu, Paea; Falconer, Sean; Coulet, Adrien; Noy, Natalya F.; Musen, Mark A.; Shah, Nigam H.

2011-01-01

The volume of publicly available data in biomedicine is constantly increasing. However, these data are stored in different formats and on different platforms. Integrating these data will enable us to facilitate the pace of medical discoveries by providing scientists with a unified view of this diverse information. Under the auspices of the National Center for Biomedical Ontology (NCBO), we have developed the Resource Index—a growing, large-scale ontology-based index of more than twenty heterogeneous biomedical resources. The resources come from a variety of repositories maintained by organizations from around the world. We use a set of over 200 publicly available ontologies contributed by researchers in various domains to annotate the elements in these resources. We use the semantics that the ontologies encode, such as different properties of classes, the class hierarchies, and the mappings between ontologies, in order to improve the search experience for the Resource Index user. Our user interface enables scientists to search the multiple resources quickly and efficiently using domain terms, without even being aware that there is semantics “under the hood.” PMID:21918645

NCBO Resource Index: Ontology-Based Search and Mining of Biomedical Resources.

PubMed

Jonquet, Clement; Lependu, Paea; Falconer, Sean; Coulet, Adrien; Noy, Natalya F; Musen, Mark A; Shah, Nigam H

2011-09-01

The volume of publicly available data in biomedicine is constantly increasing. However, these data are stored in different formats and on different platforms. Integrating these data will enable us to facilitate the pace of medical discoveries by providing scientists with a unified view of this diverse information. Under the auspices of the National Center for Biomedical Ontology (NCBO), we have developed the Resource Index-a growing, large-scale ontology-based index of more than twenty heterogeneous biomedical resources. The resources come from a variety of repositories maintained by organizations from around the world. We use a set of over 200 publicly available ontologies contributed by researchers in various domains to annotate the elements in these resources. We use the semantics that the ontologies encode, such as different properties of classes, the class hierarchies, and the mappings between ontologies, in order to improve the search experience for the Resource Index user. Our user interface enables scientists to search the multiple resources quickly and efficiently using domain terms, without even being aware that there is semantics "under the hood."

Caffeine-catalyzed gels.

PubMed

DiCiccio, Angela M; Lee, Young-Ah Lucy; Glettig, Dean L; Walton, Elizabeth S E; de la Serna, Eva L; Montgomery, Veronica A; Grant, Tyler M; Langer, Robert; Traverso, Giovanni

2018-07-01

Covalently cross-linked gels are utilized in a broad range of biomedical applications though their synthesis often compromises easy implementation. Cross-linking reactions commonly utilize catalysts or conditions that can damage biologics and sensitive compounds, producing materials that require extensive post processing to achieve acceptable biocompatibility. As an alternative, we report a batch synthesis platform to produce covalently cross-linked materials appropriate for direct biomedical application enabled by green chemistry and commonly available food grade ingredients. Using caffeine, a mild base, to catalyze anhydrous carboxylate ring-opening of diglycidyl-ether functionalized monomers with citric acid as a tri-functional crosslinking agent we introduce a novel poly(ester-ether) gel synthesis platform. We demonstrate that biocompatible Caffeine Catalyzed Gels (CCGs) exhibit dynamic physical, chemical, and mechanical properties, which can be tailored in shape, surface texture, solvent response, cargo release, shear and tensile strength, among other potential attributes. The demonstrated versatility, low cost and facile synthesis of these CCGs renders them appropriate for a broad range of customized engineering applications including drug delivery constructs, tissue engineering scaffolds, and medical devices. Copyright © 2018 The Authors. Published by Elsevier Ltd.. All rights reserved.

Engineering of microscale three-dimensional pancreatic islet models in vitro and their biomedical applications.

PubMed

Gao, Bin; Wang, Lin; Han, Shuang; Pingguan-Murphy, Belinda; Zhang, Xiaohui; Xu, Feng

2016-08-01

Diabetes now is the most common chronic disease in the world inducing heavy burden for the people's health. Based on this, diabetes research such as islet function has become a hot topic in medical institutes of the world. Today, in medical institutes, the conventional experiment platform in vitro is monolayer cell culture. However, with the development of micro- and nano-technologies, several microengineering methods have been developed to fabricate three-dimensional (3D) islet models in vitro which can better mimic the islet of pancreases in vivo. These in vitro islet models have shown better cell function than monolayer cells, indicating their great potential as better experimental platforms to elucidate islet behaviors under both physiological and pathological conditions, such as the molecular mechanisms of diabetes and clinical islet transplantation. In this review, we present the state-of-the-art advances in the microengineering methods for fabricating microscale islet models in vitro. We hope this will help researchers to better understand the progress in the engineering 3D islet models and their biomedical applications such as drug screening and islet transplantation.

Microcarrier-based platforms for in vitro expansion and differentiation of human pluripotent stem cells in bioreactor culture systems.

PubMed

Badenes, Sara M; Fernandes, Tiago G; Rodrigues, Carlos A V; Diogo, Maria Margarida; Cabral, Joaquim M S

2016-09-20

Human pluripotent stem cells (hPSC) have attracted a great attention as an unlimited source of cells for cell therapies and other in vitro biomedical applications such as drug screening, toxicology assays and disease modeling. The implementation of scalable culture platforms for the large-scale production of hPSC and their derivatives is mandatory to fulfill the requirement of obtaining large numbers of cells for these applications. Microcarrier technology has been emerging as an effective approach for the large scale ex vivo hPSC expansion and differentiation. This review presents recent achievements in hPSC microcarrier-based culture systems and discusses the crucial aspects that influence the performance of these culture platforms. Recent progress includes addressing chemically-defined culture conditions for manufacturing of hPSC and their derivatives, with the development of xeno-free media and microcarrier coatings to meet good manufacturing practice (GMP) quality requirements. Finally, examples of integrated platforms including hPSC expansion and directed differentiation to specific lineages are also presented in this review. Copyright © 2016 Elsevier B.V. All rights reserved.

OntoGene web services for biomedical text mining.

PubMed

Rinaldi, Fabio; Clematide, Simon; Marques, Hernani; Ellendorff, Tilia; Romacker, Martin; Rodriguez-Esteban, Raul

2014-01-01

Text mining services are rapidly becoming a crucial component of various knowledge management pipelines, for example in the process of database curation, or for exploration and enrichment of biomedical data within the pharmaceutical industry. Traditional architectures, based on monolithic applications, do not offer sufficient flexibility for a wide range of use case scenarios, and therefore open architectures, as provided by web services, are attracting increased interest. We present an approach towards providing advanced text mining capabilities through web services, using a recently proposed standard for textual data interchange (BioC). The web services leverage a state-of-the-art platform for text mining (OntoGene) which has been tested in several community-organized evaluation challenges,with top ranked results in several of them.

Polydimethylsiloxane films doped with NdFeB powder: magnetic characterization and potential applications in biomedical engineering and microrobotics.

PubMed

Iacovacci, V; Lucarini, G; Innocenti, C; Comisso, N; Dario, P; Ricotti, L; Menciassi, A

2015-12-01

This work reports the fabrication, magnetic characterization and controlled navigation of film-shaped microrobots consisting of a polydimethylsiloxane-NdFeB powder composite material. The fabrication process relies on spin-coating deposition, powder orientation and permanent magnetization. Films with different powder concentrations (10 %, 30 %, 50 % and 70 % w/w) were fabricated and characterized in terms of magnetic properties and magnetic navigation performances (by exploiting an electromagnet-based platform). Standardized data are provided, thus enabling the exploitation of these composite materials in a wide range of applications, from MEMS/microrobot development to biomedical systems. Finally, the possibility to microfabricate free-standing polymeric structures and the biocompatibility of the proposed composite materials is demonstrated.

OntoGene web services for biomedical text mining

PubMed Central

2014-01-01

Text mining services are rapidly becoming a crucial component of various knowledge management pipelines, for example in the process of database curation, or for exploration and enrichment of biomedical data within the pharmaceutical industry. Traditional architectures, based on monolithic applications, do not offer sufficient flexibility for a wide range of use case scenarios, and therefore open architectures, as provided by web services, are attracting increased interest. We present an approach towards providing advanced text mining capabilities through web services, using a recently proposed standard for textual data interchange (BioC). The web services leverage a state-of-the-art platform for text mining (OntoGene) which has been tested in several community-organized evaluation challenges, with top ranked results in several of them. PMID:25472638

Graphene as multifunctional delivery platform in cancer therapy.

PubMed

Nejabat, Mojgan; Charbgoo, Fahimeh; Ramezani, Mohammad

2017-08-01

The biomedical applications of graphene-based nanomaterials including drug and gene delivery have grown rapidly in the past few years. This is due to its high surface area that results in high cargo loading capacity. It is demonstrated that graphene can improve drug efficacy without increasing the dose of the chemotherapeutic agent in cancer treatment. Considering these valuable benefits of graphene, this review focused on the newest advancements in drug and gene delivery systems using graphene and unveiling advantages and disadvantages of different graphene-based materials in introducing an effective cargo delivery system for cancer therapy. Different approaches for reducing cytotoxic impacts of graphene oxide and production of biocompatible delivery platform were also reviewed. © 2017 Wiley Periodicals, Inc. J Biomed Mater Res Part A: 105A: 2355-2367, 2017. © 2017 Wiley Periodicals, Inc.

Mining biomedical images towards valuable information retrieval in biomedical and life sciences

PubMed Central

Ahmed, Zeeshan; Zeeshan, Saman; Dandekar, Thomas

2016-01-01

Biomedical images are helpful sources for the scientists and practitioners in drawing significant hypotheses, exemplifying approaches and describing experimental results in published biomedical literature. In last decades, there has been an enormous increase in the amount of heterogeneous biomedical image production and publication, which results in a need for bioimaging platforms for feature extraction and analysis of text and content in biomedical images to take advantage in implementing effective information retrieval systems. In this review, we summarize technologies related to data mining of figures. We describe and compare the potential of different approaches in terms of their developmental aspects, used methodologies, produced results, achieved accuracies and limitations. Our comparative conclusions include current challenges for bioimaging software with selective image mining, embedded text extraction and processing of complex natural language queries. PMID:27538578

Silicon nanomaterials platform for bioimaging, biosensing, and cancer therapy.

PubMed

Peng, Fei; Su, Yuanyuan; Zhong, Yiling; Fan, Chunhai; Lee, Shuit-Tong; He, Yao

2014-02-18

Silicon nanomaterials are an important class of nanomaterials with great potential for technologies including energy, catalysis, and biotechnology, because of their many unique properties, including biocompatibility, abundance, and unique electronic, optical, and mechanical properties, among others. Silicon nanomaterials are known to have little or no toxicity due to favorable biocompatibility of silicon, which is an important precondition for biological and biomedical applications. In addition, huge surface-to-volume ratios of silicon nanomaterials are responsible for their unique optical, mechanical, or electronic properties, which offer exciting opportunities for design of high-performance silicon-based functional nanoprobes, nanosensors, and nanoagents for biological analysis and detection and disease treatment. Moreover, silicon is the second most abundant element (after oxygen) on earth, providing plentiful and inexpensive resources for large-scale and low-cost preparation of silicon nanomaterials for practical applications. Because of these attractive traits, and in parallel with a growing interest in their design and synthesis, silicon nanomaterials are extensively investigated for wide-ranging applications, including energy, catalysis, optoelectronics, and biology. Among them, bioapplications of silicon nanomaterials are of particular interest. In the past decade, scientists have made an extensive effort to construct a silicon nanomaterials platform for various biological and biomedical applications, such as biosensors, bioimaging, and cancer treatment, as new and powerful tools for disease diagnosis and therapy. Nonetheless, there are few review articles covering these important and promising achievements to promote the awareness of development of silicon nanobiotechnology. In this Account, we summarize recent representative works to highlight the recent developments of silicon functional nanomaterials for a new, powerful platform for biological and biomedical applications, including biosensor, bioimaging, and cancer therapy. First, we show that the interesting photoluminescence properties (e.g., strong fluorescence and robust photostability) and excellent biocompatibility of silicon nanoparticles (SiNPs) are superbly suitable for direct and long-term visualization of biological systems. The strongly fluorescent SiNPs are highly effective for bioimaging applications, especially for long-term cellular labeling, cancer cell detection, and tumor imaging in vitro and in vivo with high sensitivity. Next, we discuss the utilization of silicon nanomaterials to construct high-performance biosensors, such as silicon-based field-effect transistors (FET) and surface-enhanced Raman scattering (SERS) sensors, which hold great promise for ultrasensitive and selective detection of biological species (e.g., DNA and protein). Then, we introduce recent exciting research findings on the applications of silicon nanomaterials for cancer therapy with encouraging therapeutic outcomes. Lastly, we highlight the major challenges and promises in this field, and the prospect of a new nanobiotechnology platform based on silicon nanomaterials.

Microflow1, a sheathless fiber-optic flow cytometry biomedical platform: demonstration onboard the international space station.

PubMed

Dubeau-Laramée, Geneviève; Rivière, Christophe; Jean, Isabelle; Mermut, Ozzy; Cohen, Luchino Y

2014-04-01

A fiber-optic based flow cytometry platform was designed to build a portable and robust instrument for space applications. At the core of the Microflow1 is a unique fiber-optic flow cell fitted to a fluidic system and fiber coupled to the source and detection channels. A Microflow1 engineering unit was first tested and benchmarked against a commercial flow cytometer as a reference in a standard laboratory environment. Testing in parabolic flight campaigns was performed to establish Microflow1's performance in weightlessness, before operating the new platform on the International Space Station. Microflow1 had comparable performances to commercial systems, and operated remarkably and robustly in weightlessness (microgravity). Microflow1 supported immunophenotyping as well as microbead-based multiplexed cytokine assays in the space environment and independently of gravity levels. Results presented here provide evidence that this fiber-optic cytometer technology is inherently compatible with the space environment with negligible compromise to analytical performance. © 2013 International Society for Advancement of Cytometry.

Applications of Deep Learning in Biomedicine.

PubMed

Mamoshina, Polina; Vieira, Armando; Putin, Evgeny; Zhavoronkov, Alex

2016-05-02

Increases in throughput and installed base of biomedical research equipment led to a massive accumulation of -omics data known to be highly variable, high-dimensional, and sourced from multiple often incompatible data platforms. While this data may be useful for biomarker identification and drug discovery, the bulk of it remains underutilized. Deep neural networks (DNNs) are efficient algorithms based on the use of compositional layers of neurons, with advantages well matched to the challenges -omics data presents. While achieving state-of-the-art results and even surpassing human accuracy in many challenging tasks, the adoption of deep learning in biomedicine has been comparatively slow. Here, we discuss key features of deep learning that may give this approach an edge over other machine learning methods. We then consider limitations and review a number of applications of deep learning in biomedical studies demonstrating proof of concept and practical utility.

A Scientific Workflow Platform for Generic and Scalable Object Recognition on Medical Images

NASA Astrophysics Data System (ADS)

Möller, Manuel; Tuot, Christopher; Sintek, Michael

In the research project THESEUS MEDICO we aim at a system combining medical image information with semantic background knowledge from ontologies to give clinicians fully cross-modal access to biomedical image repositories. Therefore joint efforts have to be made in more than one dimension: Object detection processes have to be specified in which an abstraction is performed starting from low-level image features across landmark detection utilizing abstract domain knowledge up to high-level object recognition. We propose a system based on a client-server extension of the scientific workflow platform Kepler that assists the collaboration of medical experts and computer scientists during development and parameter learning.

Bio-Inspired Extreme Wetting Surfaces for Biomedical Applications

PubMed Central

Shin, Sera; Seo, Jungmok; Han, Heetak; Kang, Subin; Kim, Hyunchul; Lee, Taeyoon

2016-01-01

Biological creatures with unique surface wettability have long served as a source of inspiration for scientists and engineers. More specifically, materials exhibiting extreme wetting properties, such as superhydrophilic and superhydrophobic surfaces, have attracted considerable attention because of their potential use in various applications, such as self-cleaning fabrics, anti-fog windows, anti-corrosive coatings, drag-reduction systems, and efficient water transportation. In particular, the engineering of surface wettability by manipulating chemical properties and structure opens emerging biomedical applications ranging from high-throughput cell culture platforms to biomedical devices. This review describes design and fabrication methods for artificial extreme wetting surfaces. Next, we introduce some of the newer and emerging biomedical applications using extreme wetting surfaces. Current challenges and future prospects of the surfaces for potential biomedical applications are also addressed. PMID:28787916

Flow-through nanohole array based sensor implemented on analogue smartphone components

NASA Astrophysics Data System (ADS)

Gomez-Cruz, Juan; Nair, Srijit; Ascanio, Gabriel; Escobedo, Carlos

2017-08-01

Mobile communications have massively populated the consumer electronics market over the past few years and it is now ubiquitous, providing a timeless opportunity for the development of smartphone-based technologies as point-of-care (POC) diagnosis tools1 . The expectation for a fully integrated smartphone-based sensor that enables applications such as environmental monitoring, explosive detection and biomedical analysis has increased among the scientific community in the past few years2,3. The commercialization forecast for smartphone-based sensing technologies is very promising, but reliable, miniature and cost-effective sensing platforms that can adapt to portable electronics in still under development. In this work, we present an integrated sensing platform based on flow-through metallic nanohole arrays. The nanohole arrays are 260 nm in diameter and 520 nm in pitch, fabricated using Focused Ion Beam (FIB) lithography. A white LED resembling a smartphone flash LED serves as light source to excite surface plasmons and the signal is recorded via a Complementary Metal-Oxide-Semiconductor (CMOS) module. The sensing abilities of the integrated sensing platform is demonstrated for the detection of (i) changes in bulk refractive index (RI), (ii) real-time monitoring of surface modification by receptor-analyte system of streptavidin-biotin.

HaloTag Technology: A Versatile Platform for Biomedical Applications

PubMed Central

2015-01-01

Exploration of protein function and interaction is critical for discovering links among genomics, proteomics, and disease state; yet, the immense complexity of proteomics found in biological systems currently limits our investigational capacity. Although affinity and autofluorescent tags are widely employed for protein analysis, these methods have been met with limited success because they lack specificity and require multiple fusion tags and genetic constructs. As an alternative approach, the innovative HaloTag protein fusion platform allows protein function and interaction to be comprehensively analyzed using a single genetic construct with multiple capabilities. This is accomplished using a simplified process, in which a variable HaloTag ligand binds rapidly to the HaloTag protein (usually linked to the protein of interest) with high affinity and specificity. In this review, we examine all current applications of the HaloTag technology platform for biomedical applications, such as the study of protein isolation and purification, protein function, protein–protein and protein–DNA interactions, biological assays, in vitro cellular imaging, and in vivo molecular imaging. In addition, novel uses of the HaloTag platform are briefly discussed along with potential future applications. PMID:25974629

Mining biomedical images towards valuable information retrieval in biomedical and life sciences.

PubMed

Ahmed, Zeeshan; Zeeshan, Saman; Dandekar, Thomas

2016-01-01

Biomedical images are helpful sources for the scientists and practitioners in drawing significant hypotheses, exemplifying approaches and describing experimental results in published biomedical literature. In last decades, there has been an enormous increase in the amount of heterogeneous biomedical image production and publication, which results in a need for bioimaging platforms for feature extraction and analysis of text and content in biomedical images to take advantage in implementing effective information retrieval systems. In this review, we summarize technologies related to data mining of figures. We describe and compare the potential of different approaches in terms of their developmental aspects, used methodologies, produced results, achieved accuracies and limitations. Our comparative conclusions include current challenges for bioimaging software with selective image mining, embedded text extraction and processing of complex natural language queries. © The Author(s) 2016. Published by Oxford University Press.

Magnetic hydroxyapatite: a promising multifunctional platform for nanomedicine application

PubMed Central

Mondal, Sudip; Manivasagan, Panchanathan; Bharathiraja, Subramaniyan; Santha Moorthy, Madhappan; Kim, Hye Hyun; Seo, Hansu; Lee, Kang Dae; Oh, Junghwan

2017-01-01

In this review, specific attention is paid to the development of nanostructured magnetic hydroxyapatite (MHAp) and its potential application in controlled drug/gene delivery, tissue engineering, magnetic hyperthermia treatment, and the development of contrast agents for magnetic resonance imaging. Both magnetite and hydroxyapatite materials have excellent prospects in nanomedicine with multifunctional therapeutic approaches. To date, many research articles have focused on biomedical applications of nanomaterials because of which it is very difficult to focus on any particular type of nanomaterial. This study is possibly the first effort to emphasize on the comprehensive assessment of MHAp nanostructures for biomedical applications supported with very recent experimental studies. From basic concepts to the real-life applications, the relevant characteristics of magnetic biomaterials are patented which are briefly discussed. The potential therapeutic and diagnostic ability of MHAp-nanostructured materials make them an ideal platform for future nanomedicine. We hope that this advanced review will provide a better understanding of MHAp and its important features to utilize it as a promising material for multifunctional biomedical applications. PMID:29200851

Lynx web services for annotations and systems analysis of multi-gene disorders.

PubMed

Sulakhe, Dinanath; Taylor, Andrew; Balasubramanian, Sandhya; Feng, Bo; Xie, Bingqing; Börnigen, Daniela; Dave, Utpal J; Foster, Ian T; Gilliam, T Conrad; Maltsev, Natalia

2014-07-01

Lynx is a web-based integrated systems biology platform that supports annotation and analysis of experimental data and generation of weighted hypotheses on molecular mechanisms contributing to human phenotypes and disorders of interest. Lynx has integrated multiple classes of biomedical data (genomic, proteomic, pathways, phenotypic, toxicogenomic, contextual and others) from various public databases as well as manually curated data from our group and collaborators (LynxKB). Lynx provides tools for gene list enrichment analysis using multiple functional annotations and network-based gene prioritization. Lynx provides access to the integrated database and the analytical tools via REST based Web Services (http://lynx.ci.uchicago.edu/webservices.html). This comprises data retrieval services for specific functional annotations, services to search across the complete LynxKB (powered by Lucene), and services to access the analytical tools built within the Lynx platform. © The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research.

Integrated microfluidic platforms for investigating neuronal networks

NASA Astrophysics Data System (ADS)

Kim, Hyung Joon

This dissertation describes the development and application of integrated microfluidics-based assay platforms to study neuronal activities in the nervous system in-vitro. The assay platforms were fabricated using soft lithography and micro/nano fabrication including microfluidics, surface patterning, and nanomaterial synthesis. The use of integrated microfluidics-based assay platform allows culturing and manipulating many types of neuronal tissues in precisely controlled microenvironment. Furthermore, they provide organized multi-cellular in-vitro model, long-term monitoring with live cell imaging, and compatibility with molecular biology techniques and electrophysiology experiment. In this dissertation, the integrated microfluidics-based assay platforms are developed for investigation of neuronal activities such as local protein synthesis, impairment of axonal transport by chemical/physical variants, growth cone path finding under chemical/physical cues, and synaptic transmission in neuronal circuit. Chapter 1 describes the motivation, objectives, and scope for developing in-vitro platform to study various neuronal activities. Chapter 2 introduces microfluidic culture platform for biochemical assay with large-scale neuronal tissues that are utilized as model system in neuroscience research. Chapter 3 focuses on the investigation of impaired axonal transport by beta-Amyloid and oxidative stress. The platform allows to control neuronal processes and to quantify mitochondrial movement in various regions of axons away from applied drugs. Chapter 4 demonstrates the development of microfluidics-based growth cone turning assay to elucidate the mechanism underlying axon guidance under soluble factors and shear flow. Using this platform, the behaviors of growth cone of mammalian neurons are verified under the gradient of inhibitory molecules and also shear flow in well-controlled manner. In Chapter 5, I combine in-vitro multicellular model with microfabricated MEA (multielectrode array) or nanowire electrode array to study electrophysiology in neuronal network. Also, "diode-like" microgrooves to control the number of neuronal processes is embedded in this platform. Chapter 6 concludes with a possible future direction of this work. Interfacing micro/nanotechnology with primary neuron culture would open many doors in fundamental neuroscience research and also biomedical innovation.

Ion Channel ElectroPhysiology Ontology (ICEPO) - a case study of text mining assisted ontology development.

PubMed

Elayavilli, Ravikumar Komandur; Liu, Hongfang

2016-01-01

Computational modeling of biological cascades is of great interest to quantitative biologists. Biomedical text has been a rich source for quantitative information. Gathering quantitative parameters and values from biomedical text is one significant challenge in the early steps of computational modeling as it involves huge manual effort. While automatically extracting such quantitative information from bio-medical text may offer some relief, lack of ontological representation for a subdomain serves as impedance in normalizing textual extractions to a standard representation. This may render textual extractions less meaningful to the domain experts. In this work, we propose a rule-based approach to automatically extract relations involving quantitative data from biomedical text describing ion channel electrophysiology. We further translated the quantitative assertions extracted through text mining to a formal representation that may help in constructing ontology for ion channel events using a rule based approach. We have developed Ion Channel ElectroPhysiology Ontology (ICEPO) by integrating the information represented in closely related ontologies such as, Cell Physiology Ontology (CPO), and Cardiac Electro Physiology Ontology (CPEO) and the knowledge provided by domain experts. The rule-based system achieved an overall F-measure of 68.93% in extracting the quantitative data assertions system on an independently annotated blind data set. We further made an initial attempt in formalizing the quantitative data assertions extracted from the biomedical text into a formal representation that offers potential to facilitate the integration of text mining into ontological workflow, a novel aspect of this study. This work is a case study where we created a platform that provides formal interaction between ontology development and text mining. We have achieved partial success in extracting quantitative assertions from the biomedical text and formalizing them in ontological framework. The ICEPO ontology is available for download at http://openbionlp.org/mutd/supplementarydata/ICEPO/ICEPO.owl.

An active visual search interface for Medline.

PubMed

Xuan, Weijian; Dai, Manhong; Mirel, Barbara; Wilson, Justin; Athey, Brian; Watson, Stanley J; Meng, Fan

2007-01-01

Searching the Medline database is almost a daily necessity for many biomedical researchers. However, available Medline search solutions are mainly designed for the quick retrieval of a small set of most relevant documents. Because of this search model, they are not suitable for the large-scale exploration of literature and the underlying biomedical conceptual relationships, which are common tasks in the age of high throughput experimental data analysis and cross-discipline research. We try to develop a new Medline exploration approach by incorporating interactive visualization together with powerful grouping, summary, sorting and active external content retrieval functions. Our solution, PubViz, is based on the FLEX platform designed for interactive web applications and its prototype is publicly available at: http://brainarray.mbni.med.umich.edu/Brainarray/DataMining/PubViz.

Magnetic Nanoparticles for Cancer Diagnosis and Therapy

PubMed Central

Yigit, Mehmet V.; Moore, Anna

2013-01-01

Nanotechnology is evolving as a new field that has a potentially high research and clinical impact. Medicine, in particular, could benefit from nanotechnology, due to emerging applications for noninvasive imaging and therapy. One important nanotechnological platform that has shown promise includes the so-called iron oxide nanoparticles. With specific relevance to cancer therapy, iron oxide nanoparticle-based therapy represents an important alternative to conventional chemotherapy, radiation, or surgery. Iron oxide nanoparticles are usually composed of three main components: an iron core, a polymer coating, and functional moieties. The biodegradable iron core can be designed to be superparamagnetic. This is particularly important, if the nanoparticles are to be used as a contrast agent for noninvasive magnetic resonance imaging (MRI). Surrounding the iron core is generally a polymer coating, which not only serves as a protective layer but also is a very important component for transforming nanoparticles into biomedical nanotools for in vivo applications. Finally, different moieties attached to the coating serve as targeting macromolecules, therapeutics payloads, or additional imaging tags. Despite the development of several nanoparticles for biomedical applications, we believe that iron oxide nanoparticles are still the most promising platform that can transform nanotechnology into a conventional medical discipline. PMID:22274558

SCALEUS: Semantic Web Services Integration for Biomedical Applications.

PubMed

Sernadela, Pedro; González-Castro, Lorena; Oliveira, José Luís

2017-04-01

In recent years, we have witnessed an explosion of biological data resulting largely from the demands of life science research. The vast majority of these data are freely available via diverse bioinformatics platforms, including relational databases and conventional keyword search applications. This type of approach has achieved great results in the last few years, but proved to be unfeasible when information needs to be combined or shared among different and scattered sources. During recent years, many of these data distribution challenges have been solved with the adoption of semantic web. Despite the evident benefits of this technology, its adoption introduced new challenges related with the migration process, from existent systems to the semantic level. To facilitate this transition, we have developed Scaleus, a semantic web migration tool that can be deployed on top of traditional systems in order to bring knowledge, inference rules, and query federation to the existent data. Targeted at the biomedical domain, this web-based platform offers, in a single package, straightforward data integration and semantic web services that help developers and researchers in the creation process of new semantically enhanced information systems. SCALEUS is available as open source at http://bioinformatics-ua.github.io/scaleus/ .

Moving forward in plant food safety and security through NanoBioSensors: Adopt or adapt biomedical technologies?

PubMed

Sharma, Tarun K; Ramanathan, Rajesh; Rakwal, Randeep; Agrawal, Ganesh K; Bansal, Vipul

2015-05-01

Plant-based foods are integral part of our day-to-day diet. Increasing world population has put forth an ever increasing demand for plant-based foods, and food security remains a major concern. Similarly, biological, chemical, and physical threats to our food and increasing regulatory demands to control the presence of foreign species in food products have made food safety a growing issue. Nanotechnology has already established its roots in diverse disciplines. However, the food industry is yet to harness the full potential of the unique capabilities offered by this next-generation technology. While there might be safety concerns in regards to integration of nanoproducts with our food products, an aspect of nanotechnology that can make remarkable contribution to different elements of the food chain is the use of nanobiosensors and diagnostic platforms for monitoring food traceability, quality, safety, and nutritional value. This brings us to an important question that whether existing diagnostic platforms that have already been well developed for biomedical and clinical application are suitable for food industry or whether the demands of the food industry are altogether different that may not allow adoption/adaptation of the existing technology. This review is an effort to raise this important "uncomfortable" yet "timely" question. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

TRIAD: The Translational Research Informatics and Data Management Grid

PubMed Central

Payne, P.; Ervin, D.; Dhaval, R.; Borlawsky, T.; Lai, A.

2011-01-01

Objective Multi-disciplinary and multi-site biomedical research programs frequently require infrastructures capable of enabling the collection, management, analysis, and dissemination of heterogeneous, multi-dimensional, and distributed data and knowledge collections spanning organizational boundaries. We report on the design and initial deployment of an extensible biomedical informatics platform that is intended to address such requirements. Methods A common approach to distributed data, information, and knowledge management needs in the healthcare and life science settings is the deployment and use of a service-oriented architecture (SOA). Such SOA technologies provide for strongly-typed, semantically annotated, and stateful data and analytical services that can be combined into data and knowledge integration and analysis “pipelines.” Using this overall design pattern, we have implemented and evaluated an extensible SOA platform for clinical and translational science applications known as the Translational Research Informatics and Data-management grid (TRIAD). TRIAD is a derivative and extension of the caGrid middleware and has an emphasis on supporting agile “working interoperability” between data, information, and knowledge resources. Results Based upon initial verification and validation studies conducted in the context of a collection of driving clinical and translational research problems, we have been able to demonstrate that TRIAD achieves agile “working interoperability” between distributed data and knowledge sources. Conclusion Informed by our initial verification and validation studies, we believe TRIAD provides an example instance of a lightweight and readily adoptable approach to the use of SOA technologies in the clinical and translational research setting. Furthermore, our initial use cases illustrate the importance and efficacy of enabling “working interoperability” in heterogeneous biomedical environments. PMID:23616879

TRIAD: The Translational Research Informatics and Data Management Grid.

PubMed

Payne, P; Ervin, D; Dhaval, R; Borlawsky, T; Lai, A

2011-01-01

Multi-disciplinary and multi-site biomedical research programs frequently require infrastructures capable of enabling the collection, management, analysis, and dissemination of heterogeneous, multi-dimensional, and distributed data and knowledge collections spanning organizational boundaries. We report on the design and initial deployment of an extensible biomedical informatics platform that is intended to address such requirements. A common approach to distributed data, information, and knowledge management needs in the healthcare and life science settings is the deployment and use of a service-oriented architecture (SOA). Such SOA technologies provide for strongly-typed, semantically annotated, and stateful data and analytical services that can be combined into data and knowledge integration and analysis "pipelines." Using this overall design pattern, we have implemented and evaluated an extensible SOA platform for clinical and translational science applications known as the Translational Research Informatics and Data-management grid (TRIAD). TRIAD is a derivative and extension of the caGrid middleware and has an emphasis on supporting agile "working interoperability" between data, information, and knowledge resources. Based upon initial verification and validation studies conducted in the context of a collection of driving clinical and translational research problems, we have been able to demonstrate that TRIAD achieves agile "working interoperability" between distributed data and knowledge sources. Informed by our initial verification and validation studies, we believe TRIAD provides an example instance of a lightweight and readily adoptable approach to the use of SOA technologies in the clinical and translational research setting. Furthermore, our initial use cases illustrate the importance and efficacy of enabling "working interoperability" in heterogeneous biomedical environments.

Performance and scalability of Fourier domain optical coherence tomography acceleration using graphics processing units.

PubMed

Li, Jian; Bloch, Pavel; Xu, Jing; Sarunic, Marinko V; Shannon, Lesley

2011-05-01

Fourier domain optical coherence tomography (FD-OCT) provides faster line rates, better resolution, and higher sensitivity for noninvasive, in vivo biomedical imaging compared to traditional time domain OCT (TD-OCT). However, because the signal processing for FD-OCT is computationally intensive, real-time FD-OCT applications demand powerful computing platforms to deliver acceptable performance. Graphics processing units (GPUs) have been used as coprocessors to accelerate FD-OCT by leveraging their relatively simple programming model to exploit thread-level parallelism. Unfortunately, GPUs do not "share" memory with their host processors, requiring additional data transfers between the GPU and CPU. In this paper, we implement a complete FD-OCT accelerator on a consumer grade GPU/CPU platform. Our data acquisition system uses spectrometer-based detection and a dual-arm interferometer topology with numerical dispersion compensation for retinal imaging. We demonstrate that the maximum line rate is dictated by the memory transfer time and not the processing time due to the GPU platform's memory model. Finally, we discuss how the performance trends of GPU-based accelerators compare to the expected future requirements of FD-OCT data rates.

Microfluidic Organ/Body-on-a-Chip Devices at the Convergence of Biology and Microengineering.

PubMed

Perestrelo, Ana Rubina; Águas, Ana C P; Rainer, Alberto; Forte, Giancarlo

2015-12-10

Recent advances in biomedical technologies are mostly related to the convergence of biology with microengineering. For instance, microfluidic devices are now commonly found in most research centers, clinics and hospitals, contributing to more accurate studies and therapies as powerful tools for drug delivery, monitoring of specific analytes, and medical diagnostics. Most remarkably, integration of cellularized constructs within microengineered platforms has enabled the recapitulation of the physiological and pathological conditions of complex tissues and organs. The so-called "organ-on-a-chip" technology, which represents a new avenue in the field of advanced in vitro models, with the potential to revolutionize current approaches to drug screening and toxicology studies. This review aims to highlight recent advances of microfluidic-based devices towards a body-on-a-chip concept, exploring their technology and broad applications in the biomedical field.

Architecture for an advanced biomedical collaboration domain for the European paediatric cancer research community (ABCD-4-E).

PubMed

Nitzlnader, Michael; Falgenhauer, Markus; Gossy, Christian; Schreier, Günter

2015-01-01

Today, progress in biomedical research often depends on large, interdisciplinary research projects and tailored information and communication technology (ICT) support. In the context of the European Network for Cancer Research in Children and Adolescents (ENCCA) project the exchange of data between data source (Source Domain) and data consumer (Consumer Domain) systems in a distributed computing environment needs to be facilitated. This work presents the requirements and the corresponding solution architecture of the Advanced Biomedical Collaboration Domain for Europe (ABCD-4-E). The proposed concept utilises public as well as private cloud systems, the Integrating the Healthcare Enterprise (IHE) framework and web-based applications to provide the core capabilities in accordance with privacy and security needs. The utility of crucial parts of the concept was evaluated by prototypic implementation. A discussion of the design indicates that the requirements of ENCCA are fully met. A whole system demonstration is currently being prepared to verify that ABCD-4-E has the potential to evolve into a domain-bridging collaboration platform in the future.

BioTCM-SE: a semantic search engine for the information retrieval of modern biology and traditional Chinese medicine.

PubMed

Chen, Xi; Chen, Huajun; Bi, Xuan; Gu, Peiqin; Chen, Jiaoyan; Wu, Zhaohui

2014-01-01

Understanding the functional mechanisms of the complex biological system as a whole is drawing more and more attention in global health care management. Traditional Chinese Medicine (TCM), essentially different from Western Medicine (WM), is gaining increasing attention due to its emphasis on individual wellness and natural herbal medicine, which satisfies the goal of integrative medicine. However, with the explosive growth of biomedical data on the Web, biomedical researchers are now confronted with the problem of large-scale data analysis and data query. Besides that, biomedical data also has a wide coverage which usually comes from multiple heterogeneous data sources and has different taxonomies, making it hard to integrate and query the big biomedical data. Embedded with domain knowledge from different disciplines all regarding human biological systems, the heterogeneous data repositories are implicitly connected by human expert knowledge. Traditional search engines cannot provide accurate and comprehensive search results for the semantically associated knowledge since they only support keywords-based searches. In this paper, we present BioTCM-SE, a semantic search engine for the information retrieval of modern biology and TCM, which provides biologists with a comprehensive and accurate associated knowledge query platform to greatly facilitate the implicit knowledge discovery between WM and TCM.

BioTCM-SE: A Semantic Search Engine for the Information Retrieval of Modern Biology and Traditional Chinese Medicine

PubMed Central

Chen, Xi; Chen, Huajun; Bi, Xuan; Gu, Peiqin; Chen, Jiaoyan; Wu, Zhaohui

2014-01-01

Understanding the functional mechanisms of the complex biological system as a whole is drawing more and more attention in global health care management. Traditional Chinese Medicine (TCM), essentially different from Western Medicine (WM), is gaining increasing attention due to its emphasis on individual wellness and natural herbal medicine, which satisfies the goal of integrative medicine. However, with the explosive growth of biomedical data on the Web, biomedical researchers are now confronted with the problem of large-scale data analysis and data query. Besides that, biomedical data also has a wide coverage which usually comes from multiple heterogeneous data sources and has different taxonomies, making it hard to integrate and query the big biomedical data. Embedded with domain knowledge from different disciplines all regarding human biological systems, the heterogeneous data repositories are implicitly connected by human expert knowledge. Traditional search engines cannot provide accurate and comprehensive search results for the semantically associated knowledge since they only support keywords-based searches. In this paper, we present BioTCM-SE, a semantic search engine for the information retrieval of modern biology and TCM, which provides biologists with a comprehensive and accurate associated knowledge query platform to greatly facilitate the implicit knowledge discovery between WM and TCM. PMID:24772189

Extending XNAT Platform with an Incremental Semantic Framework

PubMed Central

Timón, Santiago; Rincón, Mariano; Martínez-Tomás, Rafael

2017-01-01

Informatics increases the yield from neuroscience due to improved data. Data sharing and accessibility enable joint efforts between different research groups, as well as replication studies, pivotal for progress in the field. Research data archiving solutions are evolving rapidly to address these necessities, however, distributed data integration is still difficult because of the need of explicit agreements for disparate data models. To address these problems, ontologies are widely used in biomedical research to obtain common vocabularies and logical descriptions, but its application may suffer from scalability issues, domain bias, and loss of low-level data access. With the aim of improving the application of semantic models in biobanking systems, an incremental semantic framework that takes advantage of the latest advances in biomedical ontologies and the XNAT platform is designed and implemented. We follow a layered architecture that allows the alignment of multi-domain biomedical ontologies to manage data at different levels of abstraction. To illustrate this approach, the development is integrated in the JPND (EU Joint Program for Neurodegenerative Disease) APGeM project, focused on finding early biomarkers for Alzheimer's and other dementia related diseases. PMID:28912709

Extending XNAT Platform with an Incremental Semantic Framework.

PubMed

Timón, Santiago; Rincón, Mariano; Martínez-Tomás, Rafael

2017-01-01

Informatics increases the yield from neuroscience due to improved data. Data sharing and accessibility enable joint efforts between different research groups, as well as replication studies, pivotal for progress in the field. Research data archiving solutions are evolving rapidly to address these necessities, however, distributed data integration is still difficult because of the need of explicit agreements for disparate data models. To address these problems, ontologies are widely used in biomedical research to obtain common vocabularies and logical descriptions, but its application may suffer from scalability issues, domain bias, and loss of low-level data access. With the aim of improving the application of semantic models in biobanking systems, an incremental semantic framework that takes advantage of the latest advances in biomedical ontologies and the XNAT platform is designed and implemented. We follow a layered architecture that allows the alignment of multi-domain biomedical ontologies to manage data at different levels of abstraction. To illustrate this approach, the development is integrated in the JPND (EU Joint Program for Neurodegenerative Disease) APGeM project, focused on finding early biomarkers for Alzheimer's and other dementia related diseases.

Smart article: application of intelligent platforms in next generation biomedical publications.

PubMed

Mohammadi, Babak; Saeedi, Marjan; Haghpanah, Vahid

2017-01-01

Production of scientific data has been accelerated exponentially though ease of access to the required knowledge is still challenging. Hence, the emergence of new frameworks to allow more efficient storage of information would be beneficial. Attaining intelligent platforms enable the smart article to serve as a forum for exchanging idea among experts of academic disciplines for a rapid and efficient scientific discourse.

Compressive hyperspectral time-resolved wide-field fluorescence lifetime imaging

NASA Astrophysics Data System (ADS)

Pian, Qi; Yao, Ruoyang; Sinsuebphon, Nattawut; Intes, Xavier

2017-07-01

Spectrally resolved fluorescence lifetime imaging and spatial multiplexing have offered information content and collection-efficiency boosts in microscopy, but efficient implementations for macroscopic applications are still lacking. An imaging platform based on time-resolved structured light and hyperspectral single-pixel detection has been developed to perform quantitative macroscopic fluorescence lifetime imaging (MFLI) over a large field of view (FOV) and multiple spectral bands simultaneously. The system makes use of three digital micromirror device (DMD)-based spatial light modulators (SLMs) to generate spatial optical bases and reconstruct N by N images over 16 spectral channels with a time-resolved capability (∼40 ps temporal resolution) using fewer than N2 optical measurements. We demonstrate the potential of this new imaging platform by quantitatively imaging near-infrared (NIR) Förster resonance energy transfer (FRET) both in vitro and in vivo. The technique is well suited for quantitative hyperspectral lifetime imaging with a high sensitivity and paves the way for many important biomedical applications.

A low power biomedical signal processor ASIC based on hardware software codesign.

PubMed

Nie, Z D; Wang, L; Chen, W G; Zhang, T; Zhang, Y T

2009-01-01

A low power biomedical digital signal processor ASIC based on hardware and software codesign methodology was presented in this paper. The codesign methodology was used to achieve higher system performance and design flexibility. The hardware implementation included a low power 32bit RISC CPU ARM7TDMI, a low power AHB-compatible bus, and a scalable digital co-processor that was optimized for low power Fast Fourier Transform (FFT) calculations. The co-processor could be scaled for 8-point, 16-point and 32-point FFTs, taking approximate 50, 100 and 150 clock circles, respectively. The complete design was intensively simulated using ARM DSM model and was emulated by ARM Versatile platform, before conducted to silicon. The multi-million-gate ASIC was fabricated using SMIC 0.18 microm mixed-signal CMOS 1P6M technology. The die area measures 5,000 microm x 2,350 microm. The power consumption was approximately 3.6 mW at 1.8 V power supply and 1 MHz clock rate. The power consumption for FFT calculations was less than 1.5 % comparing with the conventional embedded software-based solution.

Inductive power transmission to millimeter-sized biomedical implants using printed spiral coils.

PubMed

Ibrahim, Ahmed; Kiani, Mehdi

2016-08-01

The operation frequency (f) has been a key parameter in optimizing wireless power transmission links for biomedical implants with millimeter (mm) dimensions. This paper studies the feasibility of using printed spiral coils (PSCs) for powering mm-sized implants with high power transmission efficiency (PTE) at different fps. Compared to wire-wound coils (WWCs), using a PSC in the implant side allows batch fabrication on rigid or flexible substrates, which can also be used as a platform for integrating implant components. For powering an implant with 1 mm diameter, located 10 mm inside the tissue, the geometries of transmitter (Tx) and receiver (Rx) PSCs were optimized at different fPs of 50 MHz, 200 MHz, and 500 MHz using a commercial field solver (HFSS). In simulations, PSC- and WWC-based links achieved maximum PTE of 0.13% and 3.3%, and delivered power of 65.7 μW and 720 μW under specific absorption rate (SAR) constraints at the optimal fp of 50 MHz and 100 MHz, respectively, suggesting that the performance of the PSC-based link is significantly inferior to that of the WWC-based link.

A testing platform for durability studies of polymers and fiber-reinforced polymer composites under concurrent hygrothermo-mechanical stimuli.

PubMed

Gomez, Antonio; Pires, Robert; Yambao, Alyssa; La Saponara, Valeria

2014-12-11

The durability of polymers and fiber-reinforced polymer composites under service condition is a critical aspect to be addressed for their robust designs and condition-based maintenance. These materials are adopted in a wide range of engineering applications, from aircraft and ship structures, to bridges, wind turbine blades, biomaterials and biomedical implants. Polymers are viscoelastic materials, and their response may be highly nonlinear and thus make it challenging to predict and monitor their in-service performance. The laboratory-scale testing platform presented herein assists the investigation of the influence of concurrent mechanical loadings and environmental conditions on these materials. The platform was designed to be low-cost and user-friendly. Its chemically resistant materials make the platform adaptable to studies of chemical degradation due to in-service exposure to fluids. An example of experiment was conducted at RT on closed-cell polyurethane foam samples loaded with a weight corresponding to ~50% of their ultimate static and dry load. Results show that the testing apparatus is appropriate for these studies. Results also highlight the larger vulnerability of the polymer under concurrent loading, based on the higher mid-point displacements and lower residual failure loads. Recommendations are made for additional improvements to the testing apparatus.

A Testing Platform for Durability Studies of Polymers and Fiber-reinforced Polymer Composites under Concurrent Hygrothermo-mechanical Stimuli

PubMed Central

Gomez, Antonio; Pires, Robert; Yambao, Alyssa; La Saponara, Valeria

2014-01-01

The durability of polymers and fiber-reinforced polymer composites under service condition is a critical aspect to be addressed for their robust designs and condition-based maintenance. These materials are adopted in a wide range of engineering applications, from aircraft and ship structures, to bridges, wind turbine blades, biomaterials and biomedical implants. Polymers are viscoelastic materials, and their response may be highly nonlinear and thus make it challenging to predict and monitor their in-service performance. The laboratory-scale testing platform presented herein assists the investigation of the influence of concurrent mechanical loadings and environmental conditions on these materials. The platform was designed to be low-cost and user-friendly. Its chemically resistant materials make the platform adaptable to studies of chemical degradation due to in-service exposure to fluids. An example of experiment was conducted at RT on closed-cell polyurethane foam samples loaded with a weight corresponding to ~50% of their ultimate static and dry load. Results show that the testing apparatus is appropriate for these studies. Results also highlight the larger vulnerability of the polymer under concurrent loading, based on the higher mid-point displacements and lower residual failure loads. Recommendations are made for additional improvements to the testing apparatus. PMID:25548950

Semantic Web repositories for genomics data using the eXframe platform.

PubMed

Merrill, Emily; Corlosquet, Stéphane; Ciccarese, Paolo; Clark, Tim; Das, Sudeshna

2014-01-01

With the advent of inexpensive assay technologies, there has been an unprecedented growth in genomics data as well as the number of databases in which it is stored. In these databases, sample annotation using ontologies and controlled vocabularies is becoming more common. However, the annotation is rarely available as Linked Data, in a machine-readable format, or for standardized queries using SPARQL. This makes large-scale reuse, or integration with other knowledge bases very difficult. To address this challenge, we have developed the second generation of our eXframe platform, a reusable framework for creating online repositories of genomics experiments. This second generation model now publishes Semantic Web data. To accomplish this, we created an experiment model that covers provenance, citations, external links, assays, biomaterials used in the experiment, and the data collected during the process. The elements of our model are mapped to classes and properties from various established biomedical ontologies. Resource Description Framework (RDF) data is automatically produced using these mappings and indexed in an RDF store with a built-in Sparql Protocol and RDF Query Language (SPARQL) endpoint. Using the open-source eXframe software, institutions and laboratories can create Semantic Web repositories of their experiments, integrate it with heterogeneous resources and make it interoperable with the vast Semantic Web of biomedical knowledge.

Graphene-Based Optical Biosensors and Imaging

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

Tang, Zhiwen; He, Shijiang; Pei, Hao

2014-01-13

This chapter focuses on the design, fabrication and application of graphene based optical nanobiosensors. The emerging graphene based optical nanobiosensors demonstrated the promising bioassay and biomedical applications thanking to the unique optical features of graphene. According to the different applications, the graphene can be tailored to form either fluorescent emitter or efficient fluorescence quencher. The exceptional electronic feature of graphene makes it a powerful platform for fabricating the SPR and SERS biosensors. Today the graphene based optical biosensors have been constructed to detect various targets including ions, small biomolecules, DNA/RNA and proteins. This chapter reviews the recent progress in graphene-basedmore » optical biosensors and discusses the opportunities and challenges in this field.« less

Recent Advances in Laser-Ablative Synthesis of Bare Au and Si Nanoparticles and Assessment of Their Prospects for Tissue Engineering Applications.

PubMed

Al-Kattan, Ahmed; Nirwan, Viraj P; Popov, Anton; Ryabchikov, Yury V; Tselikov, Gleb; Sentis, Marc; Fahmi, Amir; Kabashin, Andrei V

2018-05-24

Driven by surface cleanness and unique physical, optical and chemical properties, bare (ligand-free) laser-synthesized nanoparticles (NPs) are now in the focus of interest as promising materials for the development of advanced biomedical platforms related to biosensing, bioimaging and therapeutic drug delivery. We recently achieved significant progress in the synthesis of bare gold (Au) and silicon (Si) NPs and their testing in biomedical tasks, including cancer imaging and therapy, biofuel cells, etc. We also showed that these nanomaterials can be excellent candidates for tissue engineering applications. This review is aimed at the description of our recent progress in laser synthesis of bare Si and Au NPs and their testing as functional modules (additives) in innovative scaffold platforms intended for tissue engineering tasks.

Lignin and silicate based hydrogels for biosensor applications

NASA Astrophysics Data System (ADS)

Burrs, S. L.; Jairam, S.; Vanegas, D. C.; Tong, Z.; McLamore, E. S.

2013-05-01

Advances in biocompatible materials and electrocatalytic nanomaterials have extended and enhanced the field of biosensors. Immobilization of biorecognition elements on nanomaterial platforms is an efficient technique for developing high fidelity biosensors. Single layer (i.e., Langmuir-Blodgett) protein films are efficient, but disadvantages of this approach include high cost, mass transfer limitations, and Vromer competition for surface binding sites. There is a need for simple, user friendly protein-nanomaterial sensing membranes that can be developed in laboratories or classrooms (i.e., outside of the clean room). In this research, we develop high fidelity nanomaterial platforms for developing electrochemical biosensors using sustainable biomaterials and user-friendly deposition techniques. Catalytic nanomaterial platforms are developed using a combination of self assembled monolayer chemistry and electrodeposition. High performance biomaterials (e.g., nanolignin) are recovered from paper pulp waste and combined with proteins and nanomaterials to form active sensor membranes. These methods are being used to develop electrochemical biosensors for studying physiological transport in biomedical, agricultural, and environmental applications.

Microfluidic Organ/Body-on-a-Chip Devices at the Convergence of Biology and Microengineering

PubMed Central

Perestrelo, Ana Rubina; Águas, Ana C. P.; Rainer, Alberto; Forte, Giancarlo

2015-01-01

Recent advances in biomedical technologies are mostly related to the convergence of biology with microengineering. For instance, microfluidic devices are now commonly found in most research centers, clinics and hospitals, contributing to more accurate studies and therapies as powerful tools for drug delivery, monitoring of specific analytes, and medical diagnostics. Most remarkably, integration of cellularized constructs within microengineered platforms has enabled the recapitulation of the physiological and pathological conditions of complex tissues and organs. The so-called “organ-on-a-chip” technology, which represents a new avenue in the field of advanced in vitro models, with the potential to revolutionize current approaches to drug screening and toxicology studies. This review aims to highlight recent advances of microfluidic-based devices towards a body-on-a-chip concept, exploring their technology and broad applications in the biomedical field. PMID:26690442

Requirements for data integration platforms in biomedical research networks: a reference model.

PubMed

Ganzinger, Matthias; Knaup, Petra

2015-01-01

Biomedical research networks need to integrate research data among their members and with external partners. To support such data sharing activities, an adequate information technology infrastructure is necessary. To facilitate the establishment of such an infrastructure, we developed a reference model for the requirements. The reference model consists of five reference goals and 15 reference requirements. Using the Unified Modeling Language, the goals and requirements are set into relation to each other. In addition, all goals and requirements are described textually in tables. This reference model can be used by research networks as a basis for a resource efficient acquisition of their project specific requirements. Furthermore, a concrete instance of the reference model is described for a research network on liver cancer. The reference model is transferred into a requirements model of the specific network. Based on this concrete requirements model, a service-oriented information technology architecture is derived and also described in this paper.

Qualification of Ti6Al4V ELI Alloy Produced by Laser Powder Bed Fusion for Biomedical Applications

NASA Astrophysics Data System (ADS)

Yadroitsev, I.; Krakhmalev, P.; Yadroitsava, I.; Du Plessis, A.

2018-03-01

Rectangular Ti6Al4V extralow interstitials (ELI) samples were manufactured by laser powder bed fusion (LPBF) in vertical and horizontal orientations relative to the build platform and subjected to various heat treatments. Detailed analyses of porosity, microstructure, residual stress, tensile properties, fatigue, and fracture surfaces were performed based on x-ray micro-computed tomography, scanning electron microscopy, and x-ray diffraction methods. The types of fracture and the tensile fracture mechanisms of the LPBF Ti6Al4V ELI alloy were also studied. Detailed analysis of the microstructure and the corresponding mechanical properties were compared against standard specifications for conventional Ti6Al4V alloy for use in surgical implant applications. Conclusions regarding the mechanical properties and heat treatment of LPBF Ti6Al4V ELI for biomedical applications are made.

Medicine 2.0: social networking, collaboration, participation, apomediation, and openness.

PubMed

Eysenbach, Gunther

2008-08-25

In a very significant development for eHealth, broad adoption of Web 2.0 technologies and approaches coincides with the more recent emergence of Personal Health Application Platforms and Personally Controlled Health Records such as Google Health, Microsoft HealthVault, and Dossia. "Medicine 2.0" applications, services and tools are defined as Web-based services for health care consumers, caregivers, patients, health professionals, and biomedical researchers, that use Web 2.0 technologies and/or semantic web and virtual reality approaches to enable and facilitate specifically 1) social networking, 2) participation, 3) apomediation, 4) openness and 5) collaboration, within and between these user groups. The Journal of Medical Internet Research (JMIR) publishes a Medicine 2.0 theme issue and sponsors a conference on "How Social Networking and Web 2.0 changes Health, Health Care, Medicine and Biomedical Research", to stimulate and encourage research in these five areas.

Medicine 2.0: Social Networking, Collaboration, Participation, Apomediation, and Openness

PubMed Central

2008-01-01

In a very significant development for eHealth, a broad adoption of Web 2.0 technologies and approaches coincides with the more recent emergence of Personal Health Application Platforms and Personally Controlled Health Records such as Google Health, Microsoft HealthVault, and Dossia. “Medicine 2.0” applications, services, and tools are defined as Web-based services for health care consumers, caregivers, patients, health professionals, and biomedical researchers, that use Web 2.0 technologies and/or semantic web and virtual reality approaches to enable and facilitate specifically 1) social networking, 2) participation, 3) apomediation, 4) openness, and 5) collaboration, within and between these user groups. The Journal of Medical Internet Research (JMIR) publishes a Medicine 2.0 theme issue and sponsors a conference on “How Social Networking and Web 2.0 changes Health, Health Care, Medicine, and Biomedical Research”, to stimulate and encourage research in these five areas. PMID:18725354

Cloud computing applications for biomedical science: A perspective.

PubMed

Navale, Vivek; Bourne, Philip E

2018-06-01

Biomedical research has become a digital data-intensive endeavor, relying on secure and scalable computing, storage, and network infrastructure, which has traditionally been purchased, supported, and maintained locally. For certain types of biomedical applications, cloud computing has emerged as an alternative to locally maintained traditional computing approaches. Cloud computing offers users pay-as-you-go access to services such as hardware infrastructure, platforms, and software for solving common biomedical computational problems. Cloud computing services offer secure on-demand storage and analysis and are differentiated from traditional high-performance computing by their rapid availability and scalability of services. As such, cloud services are engineered to address big data problems and enhance the likelihood of data and analytics sharing, reproducibility, and reuse. Here, we provide an introductory perspective on cloud computing to help the reader determine its value to their own research.

Cloud computing applications for biomedical science: A perspective

PubMed Central

2018-01-01

Biomedical research has become a digital data–intensive endeavor, relying on secure and scalable computing, storage, and network infrastructure, which has traditionally been purchased, supported, and maintained locally. For certain types of biomedical applications, cloud computing has emerged as an alternative to locally maintained traditional computing approaches. Cloud computing offers users pay-as-you-go access to services such as hardware infrastructure, platforms, and software for solving common biomedical computational problems. Cloud computing services offer secure on-demand storage and analysis and are differentiated from traditional high-performance computing by their rapid availability and scalability of services. As such, cloud services are engineered to address big data problems and enhance the likelihood of data and analytics sharing, reproducibility, and reuse. Here, we provide an introductory perspective on cloud computing to help the reader determine its value to their own research. PMID:29902176

Biofunctionalized 3-D Carbon Nano-Network Platform for Enhanced Fibroblast Cell Adhesion

NASA Astrophysics Data System (ADS)

Chowdhury, A. K. M. Rezaul Haque; Tavangar, Amirhossein; Tan, Bo; Venkatakrishnan, Krishnan

2017-03-01

Carbon nanomaterials have been investigated for various biomedical applications. In most cases, however, these nanomaterials must be functionalized biologically or chemically due to their biological inertness or possible cytotoxicity. Here, we report the development of a new carbon nanomaterial with a bioactive phase that significantly promotes cell adhesion. We synthesize the bioactive phase by introducing self-assembled nanotopography and altered nano-chemistry to graphite substrates using ultrafast laser. To the best of our knowledge, this is the first time that such a cytophilic bio-carbon is developed in a single step without requiring subsequent biological/chemical treatments. By controlling the nano-network concentration and chemistry, we develop platforms with different degrees of cell cytophilicity. We study quantitatively and qualitatively the cell response to nano-network platforms with NIH-3T3 fibroblasts. The findings from the in vitro study indicate that the platforms possess excellent biocompatibility and promote cell adhesion considerably. The study of the cell morphology shows a healthy attachment of cells with a well-spread shape, overextended actin filaments, and morphological symmetry, which is indicative of a high cellular interaction with the nano-network. The developed nanomaterial possesses great biocompatibility and considerably stimulates cell adhesion and subsequent cell proliferation, thus offering a promising path toward engineering various biomedical devices.

Boron dipyrromethene (BODIPY) functionalized carbon nano-onions for high resolution cellular imaging

NASA Astrophysics Data System (ADS)

Bartelmess, Juergen; de Luca, Elisa; Signorelli, Angelo; Baldrighi, Michele; Becce, Michele; Brescia, Rosaria; Nardone, Valentina; Parisini, Emilio; Echegoyen, Luis; Pompa, Pier Paolo; Giordani, Silvia

2014-10-01

Carbon nano-onions (CNOs) are an exciting class of carbon nanomaterials, which have recently demonstrated a facile cell-penetration capability. In the present work, highly fluorescent boron dipyrromethene (BODIPY) dyes were covalently attached to the surface of CNOs. The introduction of this new carbon nanomaterial-based imaging platform, made of CNOs and BODIPY fluorophores, allows for the exploration of synergetic effects between the two building blocks and for the elucidation of its performance in biological applications. The high fluorescence intensity exhibited by the functionalized CNOs translates into an excellent in vitro probe for the high resolution imaging of MCF-7 human breast cancer cells. It was also found that the CNOs, internalized by the cells by endocytosis, localized in the lysosomes and did not show any cytotoxic effects. The presented results highlight CNOs as excellent platforms for biological and biomedical studies due to their low toxicity, efficient cellular uptake and low fluorescence quenching of attached probes.Carbon nano-onions (CNOs) are an exciting class of carbon nanomaterials, which have recently demonstrated a facile cell-penetration capability. In the present work, highly fluorescent boron dipyrromethene (BODIPY) dyes were covalently attached to the surface of CNOs. The introduction of this new carbon nanomaterial-based imaging platform, made of CNOs and BODIPY fluorophores, allows for the exploration of synergetic effects between the two building blocks and for the elucidation of its performance in biological applications. The high fluorescence intensity exhibited by the functionalized CNOs translates into an excellent in vitro probe for the high resolution imaging of MCF-7 human breast cancer cells. It was also found that the CNOs, internalized by the cells by endocytosis, localized in the lysosomes and did not show any cytotoxic effects. The presented results highlight CNOs as excellent platforms for biological and biomedical studies due to their low toxicity, efficient cellular uptake and low fluorescence quenching of attached probes. Electronic supplementary information (ESI) available: Additional experimental and crystallographic data, additional confocal microscopy and HR-TEM images and illustrations, EELS, TGA, DLS and Z-potential results. Movie M1. See DOI: 10.1039/c4nr04533e

Integration of multisensor hybrid reasoners to support personal autonomy in the smart home.

PubMed

Valero, Miguel Ángel; Bravo, José; Chamizo, Juan Manuel García; López-de-Ipiña, Diego

2014-09-17

The deployment of the Ambient Intelligence (AmI) paradigm requires designing and integrating user-centered smart environments to assist people in their daily life activities. This research paper details an integration and validation of multiple heterogeneous sensors with hybrid reasoners that support decision making in order to monitor personal and environmental data at a smart home in a private way. The results innovate on knowledge-based platforms, distributed sensors, connected objects, accessibility and authentication methods to promote independent living for elderly people. TALISMAN+, the AmI framework deployed, integrates four subsystems in the smart home: (i) a mobile biomedical telemonitoring platform to provide elderly patients with continuous disease management; (ii) an integration middleware that allows context capture from heterogeneous sensors to program environment's reaction; (iii) a vision system for intelligent monitoring of daily activities in the home; and (iv) an ontologies-based integrated reasoning platform to trigger local actions and manage private information in the smart home. The framework was integrated in two real running environments, the UPM Accessible Digital Home and MetalTIC house, and successfully validated by five experts in home care, elderly people and personal autonomy.

Continuous inertial microparticle and blood cell separation in straight channels with local microstructures.

PubMed

Wu, Zhenlong; Chen, Yu; Wang, Moran; Chung, Aram J

2016-02-07

Fluid inertia which has conventionally been neglected in microfluidics has been gaining much attention for particle and cell manipulation because inertia-based methods inherently provide simple, passive, precise and high-throughput characteristics. Particularly, the inertial approach has been applied to blood separation for various biomedical research studies mainly using spiral microchannels. For higher throughput, parallelization is essential; however, it is difficult to realize using spiral channels because of their large two dimensional layouts. In this work, we present a novel inertial platform for continuous sheathless particle and blood cell separation in straight microchannels containing microstructures. Microstructures within straight channels exert secondary flows to manipulate particle positions similar to Dean flow in curved channels but with higher controllability. Through a balance between inertial lift force and microstructure-induced secondary flow, we deterministically position microspheres and cells based on their sizes to be separated downstream. Using our inertial platform, we successfully sorted microparticles and fractionized blood cells with high separation efficiencies, high purities and high throughputs. The inertial separation platform developed here can be operated to process diluted blood with a throughput of 10.8 mL min(-1)via radially arrayed single channels with one inlet and two rings of outlets.

Integration of Multisensor Hybrid Reasoners to Support Personal Autonomy in the Smart Home

PubMed Central

Valero, Miguel Ángel; Bravo, José; Chamizo, Juan Manuel García; López-de-Ipiña, Diego

2014-01-01

The deployment of the Ambient Intelligence (AmI) paradigm requires designing and integrating user-centered smart environments to assist people in their daily life activities. This research paper details an integration and validation of multiple heterogeneous sensors with hybrid reasoners that support decision making in order to monitor personal and environmental data at a smart home in a private way. The results innovate on knowledge-based platforms, distributed sensors, connected objects, accessibility and authentication methods to promote independent living for elderly people. TALISMAN+, the AmI framework deployed, integrates four subsystems in the smart home: (i) a mobile biomedical telemonitoring platform to provide elderly patients with continuous disease management; (ii) an integration middleware that allows context capture from heterogeneous sensors to program environment's reaction; (iii) a vision system for intelligent monitoring of daily activities in the home; and (iv) an ontologies-based integrated reasoning platform to trigger local actions and manage private information in the smart home. The framework was integrated in two real running environments, the UPM Accessible Digital Home and MetalTIC house, and successfully validated by five experts in home care, elderly people and personal autonomy. PMID:25232910

A web platform for the network analysis of high-throughput data in melanoma and its use to investigate mechanisms of resistance to anti-PD1 immunotherapy.

PubMed

Dreyer, Florian S; Cantone, Martina; Eberhardt, Martin; Jaitly, Tanushree; Walter, Lisa; Wittmann, Jürgen; Gupta, Shailendra K; Khan, Faiz M; Wolkenhauer, Olaf; Pützer, Brigitte M; Jäck, Hans-Martin; Heinzerling, Lucie; Vera, Julio

2018-06-01

Cellular phenotypes are established and controlled by complex and precisely orchestrated molecular networks. In cancer, mutations and dysregulations of multiple molecular factors perturb the regulation of these networks and lead to malignant transformation. High-throughput technologies are a valuable source of information to establish the complex molecular relationships behind the emergence of malignancy, but full exploitation of this massive amount of data requires bioinformatics tools that rely on network-based analyses. In this report we present the Virtual Melanoma Cell, an online tool developed to facilitate the mining and interpretation of high-throughput data on melanoma by biomedical researches. The platform is based on a comprehensive, manually generated and expert-validated regulatory map composed of signaling pathways important in malignant melanoma. The Virtual Melanoma Cell is a tool designed to accept, visualize and analyze user-generated datasets. It is available at: https://www.vcells.net/melanoma. To illustrate the utilization of the web platform and the regulatory map, we have analyzed a large publicly available dataset accounting for anti-PD1 immunotherapy treatment of malignant melanoma patients. Copyright © 2018 Elsevier B.V. All rights reserved.

CGI: Java Software for Mapping and Visualizing Data from Array-based Comparative Genomic Hybridization and Expression Profiling

PubMed Central

Gu, Joyce Xiuweu-Xu; Wei, Michael Yang; Rao, Pulivarthi H.; Lau, Ching C.; Behl, Sanjiv; Man, Tsz-Kwong

2007-01-01

With the increasing application of various genomic technologies in biomedical research, there is a need to integrate these data to correlate candidate genes/regions that are identified by different genomic platforms. Although there are tools that can analyze data from individual platforms, essential software for integration of genomic data is still lacking. Here, we present a novel Java-based program called CGI (Cytogenetics-Genomics Integrator) that matches the BAC clones from array-based comparative genomic hybridization (aCGH) to genes from RNA expression profiling datasets. The matching is computed via a fast, backend MySQL database containing UCSC Genome Browser annotations. This program also provides an easy-to-use graphical user interface for visualizing and summarizing the correlation of DNA copy number changes and RNA expression patterns from a set of experiments. In addition, CGI uses a Java applet to display the copy number values of a specific BAC clone in aCGH experiments side by side with the expression levels of genes that are mapped back to that BAC clone from the microarray experiments. The CGI program is built on top of extensible, reusable graphic components specifically designed for biologists. It is cross-platform compatible and the source code is freely available under the General Public License. PMID:19936083

CGI: Java software for mapping and visualizing data from array-based comparative genomic hybridization and expression profiling.

PubMed

Gu, Joyce Xiuweu-Xu; Wei, Michael Yang; Rao, Pulivarthi H; Lau, Ching C; Behl, Sanjiv; Man, Tsz-Kwong

2007-10-06

With the increasing application of various genomic technologies in biomedical research, there is a need to integrate these data to correlate candidate genes/regions that are identified by different genomic platforms. Although there are tools that can analyze data from individual platforms, essential software for integration of genomic data is still lacking. Here, we present a novel Java-based program called CGI (Cytogenetics-Genomics Integrator) that matches the BAC clones from array-based comparative genomic hybridization (aCGH) to genes from RNA expression profiling datasets. The matching is computed via a fast, backend MySQL database containing UCSC Genome Browser annotations. This program also provides an easy-to-use graphical user interface for visualizing and summarizing the correlation of DNA copy number changes and RNA expression patterns from a set of experiments. In addition, CGI uses a Java applet to display the copy number values of a specific BAC clone in aCGH experiments side by side with the expression levels of genes that are mapped back to that BAC clone from the microarray experiments. The CGI program is built on top of extensible, reusable graphic components specifically designed for biologists. It is cross-platform compatible and the source code is freely available under the General Public License.

BioMEMS –Advancing the Frontiers of Medicine

PubMed Central

James, Teena; Mannoor, Manu Sebastian; Ivanov, Dentcho V.

2008-01-01

Biological and medical application of micro-electro-mechanical-systems (MEMS) is currently seen as an area of high potential impact. Integration of biology and microtechnology has resulted in the development of a number of platforms for improving biomedical and pharmaceutical technologies. This review provides a general overview of the applications and the opportunities presented by MEMS in medicine by classifying these platforms according to their applications in the medical field. PMID:27873858

Generation and precise control of dynamic biochemical gradients for cellular assays

NASA Astrophysics Data System (ADS)

Saka, Yasushi; MacPherson, Murray; Giuraniuc, Claudiu V.

2017-03-01

Spatial gradients of diffusible signalling molecules play crucial roles in controlling diverse cellular behaviour such as cell differentiation, tissue patterning and chemotaxis. In this paper, we report the design and testing of a microfluidic device for diffusion-based gradient generation for cellular assays. A unique channel design of the device eliminates cross-flow between the source and sink channels, thereby stabilizing gradients by passive diffusion. The platform also enables quick and flexible control of chemical concentration that makes highly dynamic gradients in diffusion chambers. A model with the first approximation of diffusion and surface adsorption of molecules recapitulates the experimentally observed gradients. Budding yeast cells cultured in a gradient of a chemical inducer expressed a reporter fluorescence protein in a concentration-dependent manner. This microfluidic platform serves as a versatile prototype applicable to a broad range of biomedical investigations.

Molecular Optical Simulation Environment (MOSE): A Platform for the Simulation of Light Propagation in Turbid Media

PubMed Central

Ren, Shenghan; Chen, Xueli; Wang, Hailong; Qu, Xiaochao; Wang, Ge; Liang, Jimin; Tian, Jie

2013-01-01

The study of light propagation in turbid media has attracted extensive attention in the field of biomedical optical molecular imaging. In this paper, we present a software platform for the simulation of light propagation in turbid media named the “Molecular Optical Simulation Environment (MOSE)”. Based on the gold standard of the Monte Carlo method, MOSE simulates light propagation both in tissues with complicated structures and through free-space. In particular, MOSE synthesizes realistic data for bioluminescence tomography (BLT), fluorescence molecular tomography (FMT), and diffuse optical tomography (DOT). The user-friendly interface and powerful visualization tools facilitate data analysis and system evaluation. As a major measure for resource sharing and reproducible research, MOSE aims to provide freeware for research and educational institutions, which can be downloaded at http://www.mosetm.net. PMID:23577215

Freestanding, Fiber-Based, Wearable Temperature Sensor with Tunable Thermal Index for Healthcare Monitoring.

PubMed

Trung, Tran Quang; Le, Hoang Sinh; Dang, Thi My Linh; Ju, Sanghyun; Park, Sang Yoon; Lee, Nae-Eung

2018-06-01

Fiber-based sensors integrated on textiles or clothing systems are required for the next generation of wearable electronic platforms. Fiber-based physical sensors are developed, but the development of fiber-based temperature sensors is still limited. Herein, a new approach to develop wearable temperature sensors that use freestanding single reduction graphene oxide (rGO) fiber is proposed. A freestanding and wearable temperature-responsive rGO fiber with tunable thermal index is obtained using simple wet spinning and a controlled graphene oxide reduction time. The freestanding fiber-based temperature sensor shows high responsivity, fast response time (7 s), and good recovery time (20 s) to temperature. It also maintains its response under an applied mechanical deformation. The fiber device fabricated by means of a simple process is easily integrated into fabric such as socks or undershirts and can be worn by a person to monitor the temperature of the environment and skin temperature without interference during movement and various activities. These results demonstrate that the freestanding fiber-based temperature sensor has great potential for fiber-based wearable electronic platforms. It is also promising for applications in healthcare and biomedical monitoring. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Electrospinning: An enabling nanotechnology platform for drug delivery and regenerative medicine.

PubMed

Chen, Shixuan; Li, Ruiquan; Li, Xiaoran; Xie, Jingwei

2018-05-02

Electrospinning provides an enabling nanotechnology platform for generating a rich variety of novel structured materials in many biomedical applications including drug delivery, biosensing, tissue engineering, and regenerative medicine. In this review article, we begin with a thorough discussion on the method of producing 1D, 2D, and 3D electrospun nanofiber materials. In particular, we emphasize on how the 3D printing technology can contribute to the improvement of traditional electrospinning technology for the fabrication of 3D electrospun nanofiber materials as drug delivery devices/implants, scaffolds or living tissue constructs. We then highlight several notable examples of electrospun nanofiber materials in specific biomedical applications including cancer therapy, guiding cellular responses, engineering in vitro 3D tissue models, and tissue regeneration. Finally, we finish with conclusions and future perspectives of electrospun nanofiber materials for drug delivery and regenerative medicine. Copyright © 2018 Elsevier B.V. All rights reserved.

Evaluating the Impact of Conceptual Knowledge Engineering on the Design and Usability of a Clinical and Translational Science Collaboration Portal

PubMed Central

Payne, Philip R.O.; Borlawsky, Tara B.; Rice, Robert; Embi, Peter J.

2010-01-01

With the growing prevalence of large-scale, team science endeavors in the biomedical and life science domains, the impetus to implement platforms capable of supporting asynchronous interaction among multidisciplinary groups of collaborators has increased commensurately. However, there is a paucity of literature describing systematic approaches to identifying the information needs of targeted end-users for such platforms, and the translation of such requirements into practicable software component design criteria. In previous studies, we have reported upon the efficacy of employing conceptual knowledge engineering (CKE) techniques to systematically address both of the preceding challenges in the context of complex biomedical applications. In this manuscript we evaluate the impact of CKE approaches relative to the design of a clinical and translational science collaboration portal, and report upon the preliminary qualitative users satisfaction as reported for the resulting system. PMID:21347146

Crowdsourcing in biomedicine: challenges and opportunities

PubMed Central

Khare, Ritu; Good, Benjamin M.; Leaman, Robert; Su, Andrew I.

2016-01-01

The use of crowdsourcing to solve important but complex problems in biomedical and clinical sciences is growing and encompasses a wide variety of approaches. The crowd is diverse and includes online marketplace workers, health information seekers, science enthusiasts and domain experts. In this article, we review and highlight recent studies that use crowdsourcing to advance biomedicine. We classify these studies into two broad categories: (i) mining big data generated from a crowd (e.g. search logs) and (ii) active crowdsourcing via specific technical platforms, e.g. labor markets, wikis, scientific games and community challenges. Through describing each study in detail, we demonstrate the applicability of different methods in a variety of domains in biomedical research, including genomics, biocuration and clinical research. Furthermore, we discuss and highlight the strengths and limitations of different crowdsourcing platforms. Finally, we identify important emerging trends, opportunities and remaining challenges for future crowdsourcing research in biomedicine. PMID:25888696

Grating-Coupled Surface Plasmon Resonance (GC-SPR) Optimization for Phase-Interrogation Biosensing in a Microfluidic Chamber.

PubMed

Rossi, Stefano; Gazzola, Enrico; Capaldo, Pietro; Borile, Giulia; Romanato, Filippo

2018-05-18

Surface Plasmon Resonance (SPR)-based sensors have the advantage of being label-free, enzyme-free and real-time. However, their spreading in multidisciplinary research is still mostly limited to prism-coupled devices. Plasmonic gratings, combined with a simple and cost-effective instrumentation, have been poorly developed compared to prism-coupled system mainly due to their lower sensitivity. Here we describe the optimization and signal enhancement of a sensing platform based on phase-interrogation method, which entails the exploitation of a nanostructured sensor. This technique is particularly suitable for integration of the plasmonic sensor in a lab-on-a-chip platform and can be used in a microfluidic chamber to ease the sensing procedures and limit the injected volume. The careful optimization of most suitable experimental parameters by numerical simulations leads to a 30⁻50% enhancement of SPR response, opening new possibilities for applications in the biomedical research field while maintaining the ease and versatility of the configuration.

Grating-Coupled Surface Plasmon Resonance (GC-SPR) Optimization for Phase-Interrogation Biosensing in a Microfluidic Chamber

PubMed Central

Rossi, Stefano; Gazzola, Enrico; Capaldo, Pietro; Borile, Giulia; Romanato, Filippo

2018-01-01

Surface Plasmon Resonance (SPR)-based sensors have the advantage of being label-free, enzyme-free and real-time. However, their spreading in multidisciplinary research is still mostly limited to prism-coupled devices. Plasmonic gratings, combined with a simple and cost-effective instrumentation, have been poorly developed compared to prism-coupled system mainly due to their lower sensitivity. Here we describe the optimization and signal enhancement of a sensing platform based on phase-interrogation method, which entails the exploitation of a nanostructured sensor. This technique is particularly suitable for integration of the plasmonic sensor in a lab-on-a-chip platform and can be used in a microfluidic chamber to ease the sensing procedures and limit the injected volume. The careful optimization of most suitable experimental parameters by numerical simulations leads to a 30–50% enhancement of SPR response, opening new possibilities for applications in the biomedical research field while maintaining the ease and versatility of the configuration. PMID:29783711

Metal-organic frameworks as biosensors for luminescence-based detection and imaging

PubMed Central

Miller, Sophie E.; Teplensky, Michelle H.; Moghadam, Peyman Z.; Fairen-Jimenez, David

2016-01-01

Metal-organic frameworks (MOFs), formed by the self-assembly of metal centres or clusters and organic linkers, possess many key structural and chemical features that have enabled them to be used in sensing platforms for a variety of environmentally, chemically and biomedically relevant compounds. In particular, their high porosity, large surface area, tuneable chemical composition, high degree of crystallinity, and potential for post-synthetic modification for molecular recognition make MOFs promising candidates for biosensing applications. In this review, we separate our discussion of MOF biosensors into two categories: quantitative sensing, focusing specifically on luminescence-based sensors for the direct measurement of a specific analyte, and qualitative sensing, where we describe MOFs used for fluorescence microscopy and as magnetic resonance imaging contrast agents. We highlight several key publications in each of these areas, concluding that MOFs present an exciting, versatile new platform for biosensing applications and imaging, and we expect to see their usage grow as the field progresses. PMID:27499847

Nanodiamonds as a new horizon for pharmaceutical and biomedical applications.

PubMed

Chaudhary, Harsiddhi M; Duttagupta, Aindrilla S; Jadhav, Kisan R; Chilajwar, Sai V; Kadam, Vilasrao J

2015-01-01

A palpable need for the optimization of therapeutic agents, due to challenges tackled by them such as poor pharmacokinetics and chemoresistance, has steered the journey towards novel interdisciplinary scientific field for emergence of nanostructure materials as a carrier for targeted delivery of therapeutic agents. Amongst various nanostructures, nanodiamonds are rapidly rising as promising nanostructures that are suited especially for various biomedical and imaging applications. Advantage of being biocompatible and ease of surface functionalization for targeting purpose, besides safety which are vacant by nanodiamonds made them a striking nanotool compared to other nonmaterials which seldom offer advantages of both functionality as well as safety. This review outlines the summary of nanodiamonds, regarding their types, methods of preparation, and surface modification. It also portrays the potential applications of nanodiamond as targeted drug delivery of various bioactive agents. Based on photoluminescent and optical property, nanodiamonds are envisioned as an efficient bioimaging nanostructure. Nanodiamonds as a novel platform hold great promise for targeting cancer cells and in-vivo cell imaging. Based upon their inimitable properties and applications nanodiamonds propose an exciting future in field of therapeutics and thus possess vibrant opportunities.

Wireless plataforms for the monitoring of biomedical variables

NASA Astrophysics Data System (ADS)

Bianco, Román; Laprovitta, Agustín; Misa, Alberto; Toselli, Eduardo; Castagnola, Juan Luis

2007-11-01

The present paper aims to analyze and to compare two wireless platforms for the monitoring of biomedical variables. They must obtain the vital signals of the patients, transmit them through a radio frequency bond and centralize them for their process, storage and monitoring in real time. The implementation of this system permit us to obtain two important benefits; The patient will enjoy greater comfort during the internment, and the doctors will be able to know the state of the biomedical variables of each patient, in simultaneous form. In order to achieve the objective of this work, two communication systems for wireless transmissions data were developed and implemented. The CC1000 transceiver was used in the first system and the Bluetooth module was used in the other system.

Semantic Web repositories for genomics data using the eXframe platform

PubMed Central

2014-01-01

Background With the advent of inexpensive assay technologies, there has been an unprecedented growth in genomics data as well as the number of databases in which it is stored. In these databases, sample annotation using ontologies and controlled vocabularies is becoming more common. However, the annotation is rarely available as Linked Data, in a machine-readable format, or for standardized queries using SPARQL. This makes large-scale reuse, or integration with other knowledge bases very difficult. Methods To address this challenge, we have developed the second generation of our eXframe platform, a reusable framework for creating online repositories of genomics experiments. This second generation model now publishes Semantic Web data. To accomplish this, we created an experiment model that covers provenance, citations, external links, assays, biomaterials used in the experiment, and the data collected during the process. The elements of our model are mapped to classes and properties from various established biomedical ontologies. Resource Description Framework (RDF) data is automatically produced using these mappings and indexed in an RDF store with a built-in Sparql Protocol and RDF Query Language (SPARQL) endpoint. Conclusions Using the open-source eXframe software, institutions and laboratories can create Semantic Web repositories of their experiments, integrate it with heterogeneous resources and make it interoperable with the vast Semantic Web of biomedical knowledge. PMID:25093072

Microfluidic impact printer with interchangeable cartridges for versatile non-contact multiplexed micropatterning

PubMed Central

Ding, Yuzhe; Huang, Eric; Lam, Kit S.; Pan, Tingrui

2015-01-01

Biopatterning has been increasingly used for well-defined cellular microenvironment, patterned surface topology, and guided biological cues; however, it meets additional challenges on biocompatibility, temperature and chemical sensitivity and limited reagent volume. In this paper, we target at combining the desired features from the non-contact inkjet printing and the dot-matrix impact printing to establish a versatile multiplexed micropatterning platform, referred to as Microfluidic Impact Printer (MI-Printer), for emerging biomedical applications. Using this platform, we can achieve the distinct features of no cross-contamination, minute volume manipulation with minimal dead volume, high-throughput and biocompatible printing process, multiplexed patterning with automatic alignment, printing availability for complex medium (cell suspension or colloidal solutions), interchangeable/disposable microfluidic cartridge design with out-of-cleanroom microfabrication, simple printing system assembly and configuration, all highly desirable towards biological applications. Specifically, the printing resolution of the MI-printer platform has been experimentally characterized and theoretically analyzed. Printed droplets with 80µm in diameter have been repeatedly obtained. Furthermore, two unique features of MI-printer platform, multiplexed printing and self-alignment printing, have been successfully experimentally demonstrated (less than 10µm misalignment). In addition, combinatorial patterning and biological patterning, which utilizes the multiplexed and self-alignment printing nature of the MI-printer, have been devised to demonstrate the applicability of this robust printing technique for emerging biomedical applications. PMID:23525299

Gold Nanoparticles for Diagnostics: Advances towards Points of Care

PubMed Central

Cordeiro, Mílton; Ferreira Carlos, Fábio; Pedrosa, Pedro; Lopez, António; Baptista, Pedro Viana

2016-01-01

The remarkable physicochemical properties of gold nanoparticles (AuNPs) have prompted developments in the exploration of biomolecular interactions with AuNP-containing systems, in particular for biomedical applications in diagnostics. These systems show great promise in improving sensitivity, ease of operation and portability. Despite this endeavor, most platforms have yet to reach maturity and make their way into clinics or points of care (POC). Here, we present an overview of emerging and available molecular diagnostics using AuNPs for biomedical sensing that are currently being translated to the clinical setting. PMID:27879660

An Architecture for the Integration of Clinical Data from a PEHR in a Regional Research Platform.

PubMed

Schreiweis, Björn; Bronsch, Tobias; Stein, Katharina E; Nöst, Stefan; Aguduri, Lakshmi S; Brandner, Antje; Pensold, Peter; Weiss, Nicolas; Yüksekogul, Nilay; Bergh, Björn; Heinze, Oliver

2016-01-01

Making clinical information available for research is not only relevant for healthcare institutions, but also for regional EHRs, as cross-sectorial information can be made accessible. In the INFOPAT (INFOrmation technology for PATient-oriented health care in the Rhine-Neckar metropolitan region) project we are thus implementing both, a regional personal cross-enterprise electronic health record (PEHR) and a regional research platform (RRP) based on information from the PEHR. IHE profiles are implemented to achieve interoperability between healthcare institutions electronic medical records (EMR) and PEHR on the one hand, as well as PEHR and RRP on the other hand. The use case for the RRP is cross-sectorial quality assessment and improvement for colorectal cancer based on a quality indicator (QI) approach including patients' perspectives. For semantic interoperability the responses are transferred in the form of HL7 CDA L2 documents. The resulting architecture for a RRP shows that implementing a PEHR in combination with a RRP based on international communication standards is possible. Also IHE XDS can be used for integration of patient care and biomedical research infrastructures.

A Graphene-Based Biosensing Platform Based on Regulated Release of an Aptameric DNA Biosensor

PubMed Central

Mao, Yu; Chen, Yongli; Li, Song; Lin, Shuo; Jiang, Yuyang

2015-01-01

A novel biosensing platform was developed by integrating an aptamer-based DNA biosensor with graphene oxide (GO) for rapid and facile detection of adenosine triphosphate (ATP, as a model target). The DNA biosensor, which is locked by GO, is designed to contain two sensing modules that include recognition site for ATP and self-replication track that yields the nicking domain for Nt.BbvCI. By taking advantage of the different binding affinity of single-stranded DNA, double-stranded DNA and aptamer-target complex toward GO, the DNA biosensor could be efficiently released from GO in the presence of target with the help of a complementary DNA strand (CPDNA) that partially hybridizes to the DNA biosensor. Then, the polymerization/nicking enzyme synergetic isothermal amplification could be triggered, leading to the synthesis of massive DNA amplicons, thus achieving an enhanced sensitivity with a wide linear dynamic response range of four orders of magnitude and good selectivity. This biosensing strategy expands the applications of GO-DNA nanobiointerfaces in biological sensing, showing great potential in fundamental research and biomedical diagnosis. PMID:26569239

A Graphene-Based Biosensing Platform Based on Regulated Release of an Aptameric DNA Biosensor.

PubMed

Mao, Yu; Chen, Yongli; Li, Song; Lin, Shuo; Jiang, Yuyang

2015-11-09

A novel biosensing platform was developed by integrating an aptamer-based DNA biosensor with graphene oxide (GO) for rapid and facile detection of adenosine triphosphate (ATP, as a model target). The DNA biosensor, which is locked by GO, is designed to contain two sensing modules that include recognition site for ATP and self-replication track that yields the nicking domain for Nt.BbvCI. By taking advantage of the different binding affinity of single-stranded DNA, double-stranded DNA and aptamer-target complex toward GO, the DNA biosensor could be efficiently released from GO in the presence of target with the help of a complementary DNA strand (CPDNA) that partially hybridizes to the DNA biosensor. Then, the polymerization/nicking enzyme synergetic isothermal amplification could be triggered, leading to the synthesis of massive DNA amplicons, thus achieving an enhanced sensitivity with a wide linear dynamic response range of four orders of magnitude and good selectivity. This biosensing strategy expands the applications of GO-DNA nanobiointerfaces in biological sensing, showing great potential in fundamental research and biomedical diagnosis.

Document Exploration and Automatic Knowledge Extraction for Unstructured Biomedical Text

NASA Astrophysics Data System (ADS)

Chu, S.; Totaro, G.; Doshi, N.; Thapar, S.; Mattmann, C. A.; Ramirez, P.

2015-12-01

We describe our work on building a web-browser based document reader with built-in exploration tool and automatic concept extraction of medical entities for biomedical text. Vast amounts of biomedical information are offered in unstructured text form through scientific publications and R&D reports. Utilizing text mining can help us to mine information and extract relevant knowledge from a plethora of biomedical text. The ability to employ such technologies to aid researchers in coping with information overload is greatly desirable. In recent years, there has been an increased interest in automatic biomedical concept extraction [1, 2] and intelligent PDF reader tools with the ability to search on content and find related articles [3]. Such reader tools are typically desktop applications and are limited to specific platforms. Our goal is to provide researchers with a simple tool to aid them in finding, reading, and exploring documents. Thus, we propose a web-based document explorer, which we called Shangri-Docs, which combines a document reader with automatic concept extraction and highlighting of relevant terms. Shangri-Docsalso provides the ability to evaluate a wide variety of document formats (e.g. PDF, Words, PPT, text, etc.) and to exploit the linked nature of the Web and personal content by performing searches on content from public sites (e.g. Wikipedia, PubMed) and private cataloged databases simultaneously. Shangri-Docsutilizes Apache cTAKES (clinical Text Analysis and Knowledge Extraction System) [4] and Unified Medical Language System (UMLS) to automatically identify and highlight terms and concepts, such as specific symptoms, diseases, drugs, and anatomical sites, mentioned in the text. cTAKES was originally designed specially to extract information from clinical medical records. Our investigation leads us to extend the automatic knowledge extraction process of cTAKES for biomedical research domain by improving the ontology guided information extraction process. We will describe our experience and implementation of our system and share lessons learned from our development. We will also discuss ways in which this could be adapted to other science fields. [1] Funk et al., 2014. [2] Kang et al., 2014. [3] Utopia Documents, http://utopiadocs.com [4] Apache cTAKES, http://ctakes.apache.org

The BioMedical Evidence Graph (BMEG) | Informatics Technology for Cancer Research (ITCR)

Cancer.gov

The BMEG is a Cancer Data integration Platform that utilizes methods collected from DREAM challenges and applied to large datasets, such as the TCGA, and makes them avalible for analysis using a high performance graph database

Hybrid-modality high-resolution imaging: for diagnostic biomedical imaging and sensing for disease diagnosis

NASA Astrophysics Data System (ADS)

Murukeshan, Vadakke M.; Hoong Ta, Lim

2014-11-01

Medical diagnostics in the recent past has seen the challenging trend to come up with dual and multi-modality imaging for implementing better diagnostic procedures. The changes in tissues in the early disease stages are often subtle and can occur beneath the tissue surface. In most of these cases, conventional types of medical imaging using optics may not be able to detect these changes easily due to its penetration depth of the orders of 1 mm. Each imaging modality has its own advantages and limitations, and the use of a single modality is not suitable for every diagnostic applications. Therefore the need for multi or hybrid-modality imaging arises. Combining more than one imaging modalities overcomes the limitation of individual imaging method and integrates the respective advantages into a single setting. In this context, this paper will be focusing on the research and development of two multi-modality imaging platforms. The first platform combines ultrasound and photoacoustic imaging for diagnostic applications in the eye. The second platform consists of optical hyperspectral and photoacoustic imaging for diagnostic applications in the colon. Photoacoustic imaging is used as one of the modalities in both platforms as it can offer deeper penetration depth compared to optical imaging. The optical engineering and research challenges in developing the dual/multi-modality platforms will be discussed, followed by initial results validating the proposed scheme. The proposed schemes offer high spatial and spectral resolution imaging and sensing, and is expected to offer potential biomedical imaging solutions in the near future.

Engineering synthetic TALE and CRISPR/Cas9 transcription factors for regulating gene expression.

PubMed

Kabadi, Ami M; Gersbach, Charles A

2014-09-01

Engineered DNA-binding proteins that can be targeted to specific sites in the genome to manipulate gene expression have enabled many advances in biomedical research. This includes generating tools to study fundamental aspects of gene regulation and the development of a new class of gene therapies that alter the expression of endogenous genes. Designed transcription factors have entered clinical trials for the treatment of human diseases and others are in preclinical development. High-throughput and user-friendly platforms for designing synthetic DNA-binding proteins present innovative methods for deciphering cell biology and designing custom synthetic gene circuits. We review two platforms for designing synthetic transcription factors for manipulating gene expression: Transcription activator-like effectors (TALEs) and the RNA-guided clustered regularly interspaced short palindromic repeats (CRISPR)/Cas9 system. We present an overview of each technology and a guide for designing and assembling custom TALE- and CRISPR/Cas9-based transcription factors. We also discuss characteristics of each platform that are best suited for different applications. Copyright © 2014 Elsevier Inc. All rights reserved.

Diffusion phenomena of cells and biomolecules in microfluidic devices.

PubMed

Yildiz-Ozturk, Ece; Yesil-Celiktas, Ozlem

2015-09-01

Biomicrofluidics is an emerging field at the cross roads of microfluidics and life sciences which requires intensive research efforts in terms of introducing appropriate designs, production techniques, and analysis. The ultimate goal is to deliver innovative and cost-effective microfluidic devices to biotech, biomedical, and pharmaceutical industries. Therefore, creating an in-depth understanding of the transport phenomena of cells and biomolecules becomes vital and concurrently poses significant challenges. The present article outlines the recent advancements in diffusion phenomena of cells and biomolecules by highlighting transport principles from an engineering perspective, cell responses in microfluidic devices with emphases on diffusion- and flow-based microfluidic gradient platforms, macroscopic and microscopic approaches for investigating the diffusion phenomena of biomolecules, microfluidic platforms for the delivery of these molecules, as well as the state of the art in biological applications of mammalian cell responses and diffusion of biomolecules.

Diffusion phenomena of cells and biomolecules in microfluidic devices

PubMed Central

Yildiz-Ozturk, Ece; Yesil-Celiktas, Ozlem

2015-01-01

Biomicrofluidics is an emerging field at the cross roads of microfluidics and life sciences which requires intensive research efforts in terms of introducing appropriate designs, production techniques, and analysis. The ultimate goal is to deliver innovative and cost-effective microfluidic devices to biotech, biomedical, and pharmaceutical industries. Therefore, creating an in-depth understanding of the transport phenomena of cells and biomolecules becomes vital and concurrently poses significant challenges. The present article outlines the recent advancements in diffusion phenomena of cells and biomolecules by highlighting transport principles from an engineering perspective, cell responses in microfluidic devices with emphases on diffusion- and flow-based microfluidic gradient platforms, macroscopic and microscopic approaches for investigating the diffusion phenomena of biomolecules, microfluidic platforms for the delivery of these molecules, as well as the state of the art in biological applications of mammalian cell responses and diffusion of biomolecules. PMID:26180576

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

Coherent fiber supercontinuum for biophotonics

PubMed Central

Tu, Haohua; Boppart, Stephen A.

2013-01-01

Biophotonics and nonlinear fiber optics have traditionally been two independent fields. Since the discovery of fiber-based supercontinuum generation in 1999, biophotonics applications employing incoherent light have experienced a large impact from nonlinear fiber optics, primarily because of the access to a wide range of wavelengths and a uniform spatial profile afforded by fiber supercontinuum. However, biophotonics applications employing coherent light have not benefited from the most well-known techniques of supercontinuum generation for reasons such as poor coherence (or high noise), insufficient controllability, and inadequate portability. Fortunately, a few key techniques involving nonlinear fiber optics and femtosecond laser development have emerged to overcome these critical limitations. Despite their relative independence, these techniques are the focus of this review, because they can be integrated into a low-cost portable biophotonics source platform. This platform can be shared across many different areas of research in biophotonics, enabling new applications such as point-of-care coherent optical biomedical imaging. PMID:24358056

Chiral DOTA chelators as an improved platform for biomedical imaging and therapy applications.

PubMed

Dai, Lixiong; Jones, Chloe M; Chan, Wesley Ting Kwok; Pham, Tiffany A; Ling, Xiaoxi; Gale, Eric M; Rotile, Nicholas J; Tai, William Chi-Shing; Anderson, Carolyn J; Caravan, Peter; Law, Ga-Lai

2018-02-27

Despite established clinical utilisation, there is an increasing need for safer, more inert gadolinium-based contrast agents, and for chelators that react rapidly with radiometals. Here we report the syntheses of a series of chiral DOTA chelators and their corresponding metal complexes and reveal properties that transcend the parent DOTA compound. We incorporated symmetrical chiral substituents around the tetraaza ring, imparting enhanced rigidity to the DOTA cavity, enabling control over the range of stereoisomers of the lanthanide complexes. The Gd chiral DOTA complexes are shown to be orders of magnitude more inert to Gd release than [GdDOTA] - . These compounds also exhibit very-fast water exchange rates in an optimal range for high field imaging. Radiolabeling studies with (Cu-64/Lu-177) also demonstrate faster labelling properties. These chiral DOTA chelators are alternative general platforms for the development of stable, high relaxivity contrast agents, and for radiometal complexes used for imaging and/or therapy.

Status and Perspectives of Ion Track Electronics for Advanced Biosensing

NASA Astrophysics Data System (ADS)

Fink, D.; Muñoz, H. Gerardo; Alfonta, L.; Mandabi, Y.; Dias, J. F.; de Souza, C. T.; Bacakova, L. E.; Vacík, J.; Hnatowicz, V.; Kiv, A. E.; Fuks, D.; Papaleo, R. M.

New multifunctional ion irradiation-based three-dimensional electronic structures are developed for biotechnological applications, specifically for sensing of biomaterials, bacteria and mammalian cells. This is accomplished by combined micrometric surface and nanometric bulk microstructuring of insulators (specifically of polymer foils and SiO2/Si hybride structures) by adequate ion beams. Our main goal is the production of a cheap small universal generic working platform with multifunctional properties for biomedical analysis. Surface engineering of this platform enables cell bonding and its bulk engineering enables the extraction of cell secrets, for the sake of intercepting and analyzing the biomolecules used in cell communication. The exact knowledge of the spectrum of these cell-secreted signalling molecules should enable one to identify unambiguously the cell type. This knowledge will help developing strategies for preventive quorum sensing of bacteria, with the aim of fighting bacterial infections in an ecologically secure way.

Emotion-affected decision making in human simulation.

PubMed

Zhao, Y; Kang, J; Wright, D K

2006-01-01

Human modelling is an interdisciplinary research field. The topic, emotion-affected decision making, was originally a cognitive psychology issue, but is now recognized as an important research direction for both computer science and biomedical modelling. The main aim of this paper is to attempt to bridge the gap between psychology and bioengineering in emotion-affected decision making. The work is based on Ortony's theory of emotions and bounded rationality theory, and attempts to connect the emotion process with decision making. A computational emotion model is proposed, and the initial framework of this model in virtual human simulation within the platform of Virtools is presented.

Light-based theranostics using hybrid structures derived from biological and organic materials

NASA Astrophysics Data System (ADS)

Vankayala, Raviraj; Burns, Joshua M.; Mac, Jenny T.; Anvari, Bahman

2016-09-01

We have engineered hybrid nanostructures derived from erythrocytes, which can be doped with various near infrared (NIR) organic chromophores, including the FDA-approved indocyanine green (ICG). We refer to these vesicles as NIR erythrocyte-mimicking transducers (NETs), as they are capable of generating heat, reactive oxygen species (ROS) or emit fluorescence light. We present preliminary results that demonstrate the effectiveness of NETs for fluorescence imaging and photodynamic therapeutic destruction of breast cancer cells, upon photo-excitation using NIR light. These hybrid nanostructures present a promising platform with theranostic capability for future biomedical clinical applications.

Requirements for data integration platforms in biomedical research networks: a reference model

PubMed Central

Knaup, Petra

2015-01-01

Biomedical research networks need to integrate research data among their members and with external partners. To support such data sharing activities, an adequate information technology infrastructure is necessary. To facilitate the establishment of such an infrastructure, we developed a reference model for the requirements. The reference model consists of five reference goals and 15 reference requirements. Using the Unified Modeling Language, the goals and requirements are set into relation to each other. In addition, all goals and requirements are described textually in tables. This reference model can be used by research networks as a basis for a resource efficient acquisition of their project specific requirements. Furthermore, a concrete instance of the reference model is described for a research network on liver cancer. The reference model is transferred into a requirements model of the specific network. Based on this concrete requirements model, a service-oriented information technology architecture is derived and also described in this paper. PMID:25699205

Magnetic porous carbon nanocomposites derived from metal-organic frameworks as a sensing platform for DNA fluorescent detection.

PubMed

Tan, Hongliang; Tang, Gonge; Wang, Zhixiong; Li, Qian; Gao, Jie; Wu, Shimeng

2016-10-12

Metal-organic frameworks (MOFs) have emerged as very fascinating functional materials due to their tunable nature and diverse applications. In this work, we prepared a magnetic porous carbon (MPC) nanocomposite by employing iron-containing MOFs (MIL-88A) as precursors through a one-pot thermolysis method. It was found that the MPC can absorb selectively single-stranded DNA (ssDNA) probe to form MPC/ssDNA complex and subsequently quench the labelled fluorescent dye of the ssDNA probe, which is resulted from the synergetic effect of magnetic nanoparticles and carbon matrix. Upon the addition of complementary target DNA, however, the absorbed ssDNA probe could be released from MPC surface by forming double-stranded DNA with target DNA, and accompanied by the recovery of the fluorescence of ssDNA probe. Based on these findings, a sensing platform with low background signal for DNA fluorescent detection was developed. The proposed sensing platform exhibits high sensitivity with detection limit of 1 nM and excellent selectivity to specific target DNA, even single-base mismatched nucleotide can be distinguished. We envision that the presented study would provide a new perspective on the potential applications of MOF-derived nanocomposites in biomedical fields. Copyright © 2016 Elsevier B.V. All rights reserved.

Biomedical application of optical fibre sensors

NASA Astrophysics Data System (ADS)

Correia, R.; James, S.; Lee, S.-W.; Morgan, S. P.; Korposh, S.

2018-07-01

Optical fibre sensors (OFS), as a result of their unique properties such as small size, no interference with electromagnetic radiation, high sensitivity and the ability to design multiplexed or distributed sensing systems, have found applications ranging from structural health monitoring to biomedical and point of care instrumentation. While the former represents the main commercial application for OFS, there is body of literature concerning the deployment of this versatile sensing platform in healthcare. This paper reviews the different types of OFS and their most recent applications in healthcare. It aims to help clinicians to better understand OFS technology and also provides an overview of the challenges involved in the deployment of developed technology in healthcare. Examples of the application of OFS in healthcare are discussed with particular emphasis on recently (2015–2017) published works to avoid replicating recent review papers. The majority of the work on the development of biomedical OFS stops at the laboratory stage and, with a few exceptions, is not explored in healthcare settings. OFSs have yet to fulfil their great potential in healthcare and methods of increasing the adoption of medical devices based on optical fibres are discussed. It is important to consider these factors early in the device development process for successful translation of the developed sensors to healthcare practice.

AggNet: Deep Learning From Crowds for Mitosis Detection in Breast Cancer Histology Images.

PubMed

Albarqouni, Shadi; Baur, Christoph; Achilles, Felix; Belagiannis, Vasileios; Demirci, Stefanie; Navab, Nassir

2016-05-01

The lack of publicly available ground-truth data has been identified as the major challenge for transferring recent developments in deep learning to the biomedical imaging domain. Though crowdsourcing has enabled annotation of large scale databases for real world images, its application for biomedical purposes requires a deeper understanding and hence, more precise definition of the actual annotation task. The fact that expert tasks are being outsourced to non-expert users may lead to noisy annotations introducing disagreement between users. Despite being a valuable resource for learning annotation models from crowdsourcing, conventional machine-learning methods may have difficulties dealing with noisy annotations during training. In this manuscript, we present a new concept for learning from crowds that handle data aggregation directly as part of the learning process of the convolutional neural network (CNN) via additional crowdsourcing layer (AggNet). Besides, we present an experimental study on learning from crowds designed to answer the following questions. 1) Can deep CNN be trained with data collected from crowdsourcing? 2) How to adapt the CNN to train on multiple types of annotation datasets (ground truth and crowd-based)? 3) How does the choice of annotation and aggregation affect the accuracy? Our experimental setup involved Annot8, a self-implemented web-platform based on Crowdflower API realizing image annotation tasks for a publicly available biomedical image database. Our results give valuable insights into the functionality of deep CNN learning from crowd annotations and prove the necessity of data aggregation integration.

WebProtégé: a collaborative Web-based platform for editing biomedical ontologies.

PubMed

Horridge, Matthew; Tudorache, Tania; Nuylas, Csongor; Vendetti, Jennifer; Noy, Natalya F; Musen, Mark A

2014-08-15

WebProtégé is an open-source Web application for editing OWL 2 ontologies. It contains several features to aid collaboration, including support for the discussion of issues, change notification and revision-based change tracking. WebProtégé also features a simple user interface, which is geared towards editing the kinds of class descriptions and annotations that are prevalent throughout biomedical ontologies. Moreover, it is possible to configure the user interface using views that are optimized for editing Open Biomedical Ontology (OBO) class descriptions and metadata. Some of these views are shown in the Supplementary Material and can be seen in WebProtégé itself by configuring the project as an OBO project. WebProtégé is freely available for use on the Web at http://webprotege.stanford.edu. It is implemented in Java and JavaScript using the OWL API and the Google Web Toolkit. All major browsers are supported. For users who do not wish to host their ontologies on the Stanford servers, WebProtégé is available as a Web app that can be run locally using a Servlet container such as Tomcat. Binaries, source code and documentation are available under an open-source license at http://protegewiki.stanford.edu/wiki/WebProtege. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Superhydrophobic Materials for Biomedical Applications

PubMed Central

Colson, Yolonda L.; Grinstaff, Mark W.

2016-01-01

Superhydrophobic surfaces are actively studied across a wide range of applications and industries, and are now finding increased use in the biomedical arena as substrates to control protein adsorption, cellular interaction, and bacterial growth, as well as platforms for drug delivery devices and for diagnostic tools. The commonality in the design of these materials is to create a stable or metastable air state at the material surface, which lends itself to a number of unique properties. These activities are catalyzing the development of new materials, applications, and fabrication techniques, as well as collaborations across material science, chemistry, engineering, and medicine given the interdisciplinary nature of this work. The review begins with a discussion of superhydrophobicity, and then explores biomedical applications that are utilizing superhydrophobicity in depth including material selection characteristics, in vitro performance, and in vivo performance. General trends are offered for each application in addition to discussion of conflicting data in the literature, and the review concludes with the authors’ future perspectives on the utility of superhydrophobic surfaces for biomedical applications. PMID:27449946

Crossing the chasm: information technology to biomedical informatics.

PubMed

Fahy, Brenda G; Balke, C William; Umberger, Gloria H; Talbert, Jeffery; Canales, Denise Niles; Steltenkamp, Carol L; Conigliaro, Joseph

2011-06-01

Accelerating the translation of new scientific discoveries to improve human health and disease management is the overall goal of a series of initiatives integrated in the National Institutes of Health (NIH) "Roadmap for Medical Research." The Clinical and Translational Science Award (CTSA) program is, arguably, the most visible component of the NIH Roadmap providing resources to institutions to transform their clinical and translational research enterprises along the goals of the Roadmap. The CTSA program emphasizes biomedical informatics as a critical component for the accomplishment of the NIH's translational objectives. To be optimally effective, emerging biomedical informatics programs must link with the information technology platforms of the enterprise clinical operations within academic health centers.This report details one academic health center's transdisciplinary initiative to create an integrated academic discipline of biomedical informatics through the development of its infrastructure for clinical and translational science infrastructure and response to the CTSA mechanism. This approach required a detailed informatics strategy to accomplish these goals. This transdisciplinary initiative was the impetus for creation of a specialized biomedical informatics core, the Center for Biomedical Informatics (CBI). Development of the CBI codified the need to incorporate medical informatics including quality and safety informatics and enterprise clinical information systems within the CBI. This article describes the steps taken to develop the biomedical informatics infrastructure, its integration with clinical systems at one academic health center, successes achieved, and barriers encountered during these efforts.

Crowdsourcing in biomedicine: challenges and opportunities.

PubMed

Khare, Ritu; Good, Benjamin M; Leaman, Robert; Su, Andrew I; Lu, Zhiyong

2016-01-01

The use of crowdsourcing to solve important but complex problems in biomedical and clinical sciences is growing and encompasses a wide variety of approaches. The crowd is diverse and includes online marketplace workers, health information seekers, science enthusiasts and domain experts. In this article, we review and highlight recent studies that use crowdsourcing to advance biomedicine. We classify these studies into two broad categories: (i) mining big data generated from a crowd (e.g. search logs) and (ii) active crowdsourcing via specific technical platforms, e.g. labor markets, wikis, scientific games and community challenges. Through describing each study in detail, we demonstrate the applicability of different methods in a variety of domains in biomedical research, including genomics, biocuration and clinical research. Furthermore, we discuss and highlight the strengths and limitations of different crowdsourcing platforms. Finally, we identify important emerging trends, opportunities and remaining challenges for future crowdsourcing research in biomedicine. Published by Oxford University Press 2015. This work is written by US Government employees and is in the public domain in the US.

An organophosphonate strategy for functionalizing silicon photonic biosensors

PubMed Central

Shang, Jing; Cheng, Fang; Dubey, Manish; Kaplan, Justin M.; Rawal, Meghana; Jiang, Xi; Newburg, David S.; Sullivan, Philip A.; Andrade, Rodrigo B.; Ratner, Daniel M.

2012-01-01

Silicon photonic microring resonators have established their potential for label-free and low-cost biosensing applications. However, the long-term performance of this optical sensing platform requires robust surface modification and biofunctionalization. Herein, we demonstrate a conjugation strategy based on an organophosphonate surface coating and vinyl sulfone linker to biofunctionalize silicon resonators for biomolecular sensing. To validate this method, a series of glycans, including carbohydrates and glycoconjugates, were immobilized on divinyl sulfone (DVS)/organophosphonate-modified microrings and used to characterize carbohydrate-protein and norovirus particle interactions. This biofunctional platform was able to orthogonally detect multiple specific carbohydrate-protein interactions simultaneously. Additionally, the platform was capable of reproducible binding after multiple regenerations by high-salt, high-pH or low-pH solutions and after 1-month storage in ambient conditions. This remarkable stability and durability of the organophosphonate immobilization strategy will facilitate the application of silicon microring resonators in various sensing conditions, prolong their lifetime, and minimize the cost for storage and delivery; these characteristics are requisite for developing biosensors for point-of-care and distributed diagnostics and other biomedical applications. In addition, the platform demonstrated its ability to characterize carbohydrate-mediated host-virus interactions, providing a facile method for discovering new anti-viral agents to prevent infectious disease. PMID:22220731

Jupyter and Galaxy: Easing entry barriers into complex data analyses for biomedical researchers.

PubMed

Grüning, Björn A; Rasche, Eric; Rebolledo-Jaramillo, Boris; Eberhard, Carl; Houwaart, Torsten; Chilton, John; Coraor, Nate; Backofen, Rolf; Taylor, James; Nekrutenko, Anton

2017-05-01

What does it take to convert a heap of sequencing data into a publishable result? First, common tools are employed to reduce primary data (sequencing reads) to a form suitable for further analyses (i.e., the list of variable sites). The subsequent exploratory stage is much more ad hoc and requires the development of custom scripts and pipelines, making it problematic for biomedical researchers. Here, we describe a hybrid platform combining common analysis pathways with the ability to explore data interactively. It aims to fully encompass and simplify the "raw data-to-publication" pathway and make it reproducible.

Tissue cell assisted fabrication of tubular catalytic platinum microengines

NASA Astrophysics Data System (ADS)

Wang, Hong; Moo, James Guo Sheng; Pumera, Martin

2014-09-01

We report a facile platform for mass production of robust self-propelled tubular microengines. Tissue cells extracted from fruits of banana and apple, Musa acuminata and Malus domestica, are used as the support on which a thin platinum film is deposited by means of physical vapor deposition. Upon sonication of the cells/Pt-coated substrate in water, microscrolls of highly uniform sizes are spontaneously formed. Tubular microengines fabricated with the fruit cell assisted method exhibit a fast motion of ~100 bodylengths per s (~1 mm s-1). An extremely simple and affordable platform for mass production of the micromotors is crucial for the envisioned swarms of thousands and millions of autonomous micromotors performing biomedical and environmental remediation tasks.We report a facile platform for mass production of robust self-propelled tubular microengines. Tissue cells extracted from fruits of banana and apple, Musa acuminata and Malus domestica, are used as the support on which a thin platinum film is deposited by means of physical vapor deposition. Upon sonication of the cells/Pt-coated substrate in water, microscrolls of highly uniform sizes are spontaneously formed. Tubular microengines fabricated with the fruit cell assisted method exhibit a fast motion of ~100 bodylengths per s (~1 mm s-1). An extremely simple and affordable platform for mass production of the micromotors is crucial for the envisioned swarms of thousands and millions of autonomous micromotors performing biomedical and environmental remediation tasks. Electronic supplementary information (ESI) available: Related video. See DOI: 10.1039/c4nr03720k

Chitosan-hyaluronan based 3D co-culture platform for studying the crosstalk of lung cancer cells and mesenchymal stem cells.

PubMed

Han, Hao-Wei; Hsu, Shan-Hui

2016-09-15

The controversial roles of mesenchymal stem cells (MSCs) in lung cancer development are not yet resolved because of the lack of an extracellular environment that mimics the tumor microenvironment. Three-dimensional (3D) culture system is an emerging research tool for biomedical applications such as drug screening. In this study, MSCs and human non-small cell lung carcinoma cells (A549) were co-cultured on a thin biomaterial-based substratum (hyaluronan-grafted chitosan, CS-HA; ∼2μm), and they were self-organized into the 3D tumor co-spheroids with core-shell structure. The gene expression levels of tumorigenicity markers in cancer cells associated with cancer stemness, epithelial-mesenchymal transition (EMT) property, and cell mobility were up-regulated for more than twofold in the MSC-tumor co-spheroids, through the promoted expression of certain tumor enhancers and the direct cell-cell interaction. To verify the different extents of tumorigenicity, A549 cells or those co-cultured with MSCs were transplanted into zebrafish embryos for evaluation in vivo. The tumorigenicity obtained from the zebrafish xenotransplantation model was consistent with that observed in vitro. These evidences suggest that the CS-HA substrate-based 3D co-culture platform for cancer cells and MSCs may be a convenient tool for studying the cell-cell interaction in a tumor-like microenvironment and potentially for cancer drug testing. Mesenchymal stem cells (MSCs) have been found in several types of tumor tissues. However, the controversial roles of MSCs in cancer development are still unsolved. Chitosan and hyaluronan are commonly used materials in the biomedical field. In the current study, we co-cultured lung cancer cells and MSCs on the planar hyaluronan-grafted chitosan (CS-HA) hybrid substrates, and discovered that lung cancer cells and MSCs were rapidly self-assembled into 3D tumor spheroids with core-shell structure on the substrates after only two days in culture. Therefore, CS-HA based 3D co-culture platform can be applied to exploration of the relationship between cancer cells and MSCs and other cancer-related medical applications such as drug screening. Copyright © 2016 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.

Textpresso Central: a customizable platform for searching, text mining, viewing, and curating biomedical literature.

PubMed

Müller, H-M; Van Auken, K M; Li, Y; Sternberg, P W

2018-03-09

The biomedical literature continues to grow at a rapid pace, making the challenge of knowledge retrieval and extraction ever greater. Tools that provide a means to search and mine the full text of literature thus represent an important way by which the efficiency of these processes can be improved. We describe the next generation of the Textpresso information retrieval system, Textpresso Central (TPC). TPC builds on the strengths of the original system by expanding the full text corpus to include the PubMed Central Open Access Subset (PMC OA), as well as the WormBase C. elegans bibliography. In addition, TPC allows users to create a customized corpus by uploading and processing documents of their choosing. TPC is UIMA compliant, to facilitate compatibility with external processing modules, and takes advantage of Lucene indexing and search technology for efficient handling of millions of full text documents. Like Textpresso, TPC searches can be performed using keywords and/or categories (semantically related groups of terms), but to provide better context for interpreting and validating queries, search results may now be viewed as highlighted passages in the context of full text. To facilitate biocuration efforts, TPC also allows users to select text spans from the full text and annotate them, create customized curation forms for any data type, and send resulting annotations to external curation databases. As an example of such a curation form, we describe integration of TPC with the Noctua curation tool developed by the Gene Ontology (GO) Consortium. Textpresso Central is an online literature search and curation platform that enables biocurators and biomedical researchers to search and mine the full text of literature by integrating keyword and category searches with viewing search results in the context of the full text. It also allows users to create customized curation interfaces, use those interfaces to make annotations linked to supporting evidence statements, and then send those annotations to any database in the world. Textpresso Central URL: http://www.textpresso.org/tpc.

Portable semiconductor disk laser for in vivo tissue monitoring: a platform for the development of clinical applications

NASA Astrophysics Data System (ADS)

Aviles-Espinosa, Rodrigo; Filippidis, George; Hamilton, Craig; Malcolm, Graeme; Weingarten, Kurt J.; Südmeyer, Thomas; Barbarin, Yohan; Keller, Ursula; Artigas, David; Loza-Alvarez, Pablo

2011-07-01

Long term in vivo observations at large penetration depths and minimum sample disturbance are some of the key factors that have enabled the study of different cellular and tissue mechanisms. The continuous optimization of these aspects is the main driving force for the development of advanced microscopy techniques such as those based on nonlinear effects. Its wide implementation for general biomedical applications is however, limited as the currently used nonlinear microscopes are based on bulky, maintenance-intensive and expensive excitation sources such as Ti:sapphire ultrafast lasers. We present the suitability of a portable (140x240x70 mm) ultrafast semiconductor disk laser (SDL) source, to be used in nonlinear microscopy. The SDL is modelocked by a quantum-dot semiconductor saturable absorber mirror (SESAM). This enables the source to deliver an average output power of 287 mW with 1.5 ps pulses at 500 MHz, corresponding to a peak power of 0.4 kW. The laser center wavelength (965 nm) virtually matches the two-photon absorption cross-section of the widely used Green Fluorescent Protein (GFP). This property greatly relaxes the required peak powers, thus maximizing sample viability. This is demonstrated by presenting two-photon excited fluorescence images of GFP labeled neurons and second-harmonic generation images of pharyngeal muscles in living C. elegans nematodes. Our results also demonstrate that this compact laser is well suited for efficiently exciting different biological dyes. Importantly this non expensive, turn-key, compact laser system could be used as a platform to develop portable nonlinear bio-imaging devices, facilitating its widespread adoption in biomedical applications.

Smart Cancer Cell Targeting Imaging and Drug Delivery System by Systematically Engineering Periodic Mesoporous Organosilica Nanoparticles.

PubMed

Lu, Nan; Tian, Ying; Tian, Wei; Huang, Peng; Liu, Ying; Tang, Yuxia; Wang, Chunyan; Wang, Shouju; Su, Yunyan; Zhang, Yunlei; Pan, Jing; Teng, Zhaogang; Lu, Guangming

2016-02-10

The integration of diagnosis and therapy into one nanoplatform, known as theranostics, has attracted increasing attention in the biomedical areas. Herein, we first present a cancer cell targeting imaging and drug delivery system based on engineered thioether-bridged periodic mesoporous organosilica nanoparticles (PMOs). The PMOs are stably and selectively conjugated with near-infrared fluorescence (NIRF) dye Cyanine 5.5 (Cy5.5) and anti-Her2 affibody on the outer surfaces to endow them with excellent NIRF imaging and cancer targeting properties. Also, taking the advantage of the thioether-group-incorporated mesopores, the release of chemotherapy drug doxorubicin (DOX) loaded in the PMOs is responsive to the tumor-related molecule glutathione (GSH). The drug release percentage reaches 84.8% in 10 mM of GSH solution within 24 h, which is more than 2-fold higher than that without GSH. In addition, the drug release also exhibits pH-responsive, which reaches 53.6% at pH 5 and 31.7% at pH 7.4 within 24 h. Confocal laser scanning microscopy and flow cytometry analysis demonstrate that the PMOs-based theranostic platforms can efficiently target to and enter Her2 positive tumor cells. Thus, the smart imaging and drug delivery nanoplatforms induce high tumor cell growth inhibition. Meanwhile, the Cy5.5 conjugated PMOs perform great NIRF imaging ability, which could monitor the intracellular distribution, delivery and release of the chemotherapy drug. In addition, cell viability and histological assessments show the engineered PMOs have good biocompatibility, further encouraging the following biomedical applications. Over all, the systemically engineered PMOs can serve as a novel cancer cell targeting imaging and drug delivery platform with NIRF imaging, GSH and pH dual-responsive drug release, and high tumor cell targeting ability.

Observation Platform for Dynamic Biomedical and Biotechnology Experiments Using the International Space Station (ISS) Light Microscopy Module (LMM)

NASA Technical Reports Server (NTRS)

Kurk, Michael A. (Andy)

2015-01-01

Techshot, Inc., has developed an observation platform for the LMM on the ISS that will enable biomedical and biotechnology experiments. The LMM Dynamic Stage consists of an electronics module and the first two of a planned suite of experiment modules. Specimens and reagent solutions can be injected into a small, hollow microscope slide-the heart of the innovation-via a combination of small reservoirs, pumps, and valves. A life science experiment module allows investigators to load up to two different fluids for on-orbit, real-time image cytometry. Fluids can be changed to initiate a process, fix biological samples, or retrieve suspended cells. A colloid science experiment module conducts microparticle and nanoparticle tests for investigation of colloid self-assembly phenomena. This module includes a hollow glass slide and heating elements for the creation of a thermal gradient from one end of the slide to the other. The electronics module supports both experiment modules and contains a unique illuminator/condenser for bright and dark field and phase contrast illumination, power supplies for two piezoelectric pumps, and controller boards for pumps and valves. This observation platform safely contains internal fluids and will greatly accelerate the research and development (R&D) cycle of numerous experiments, products, and services aboard the ISS.

BIOMedical Search Engine Framework: Lightweight and customized implementation of domain-specific biomedical search engines.

PubMed

Jácome, Alberto G; Fdez-Riverola, Florentino; Lourenço, Anália

2016-07-01

Text mining and semantic analysis approaches can be applied to the construction of biomedical domain-specific search engines and provide an attractive alternative to create personalized and enhanced search experiences. Therefore, this work introduces the new open-source BIOMedical Search Engine Framework for the fast and lightweight development of domain-specific search engines. The rationale behind this framework is to incorporate core features typically available in search engine frameworks with flexible and extensible technologies to retrieve biomedical documents, annotate meaningful domain concepts, and develop highly customized Web search interfaces. The BIOMedical Search Engine Framework integrates taggers for major biomedical concepts, such as diseases, drugs, genes, proteins, compounds and organisms, and enables the use of domain-specific controlled vocabulary. Technologies from the Typesafe Reactive Platform, the AngularJS JavaScript framework and the Bootstrap HTML/CSS framework support the customization of the domain-oriented search application. Moreover, the RESTful API of the BIOMedical Search Engine Framework allows the integration of the search engine into existing systems or a complete web interface personalization. The construction of the Smart Drug Search is described as proof-of-concept of the BIOMedical Search Engine Framework. This public search engine catalogs scientific literature about antimicrobial resistance, microbial virulence and topics alike. The keyword-based queries of the users are transformed into concepts and search results are presented and ranked accordingly. The semantic graph view portraits all the concepts found in the results, and the researcher may look into the relevance of different concepts, the strength of direct relations, and non-trivial, indirect relations. The number of occurrences of the concept shows its importance to the query, and the frequency of concept co-occurrence is indicative of biological relations meaningful to that particular scope of research. Conversely, indirect concept associations, i.e. concepts related by other intermediary concepts, can be useful to integrate information from different studies and look into non-trivial relations. The BIOMedical Search Engine Framework supports the development of domain-specific search engines. The key strengths of the framework are modularity and extensibilityin terms of software design, the use of open-source consolidated Web technologies, and the ability to integrate any number of biomedical text mining tools and information resources. Currently, the Smart Drug Search keeps over 1,186,000 documents, containing more than 11,854,000 annotations for 77,200 different concepts. The Smart Drug Search is publicly accessible at http://sing.ei.uvigo.es/sds/. The BIOMedical Search Engine Framework is freely available for non-commercial use at https://github.com/agjacome/biomsef. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Deploying and sharing U-Compare workflows as web services.

PubMed

Kontonatsios, Georgios; Korkontzelos, Ioannis; Kolluru, Balakrishna; Thompson, Paul; Ananiadou, Sophia

2013-02-18

U-Compare is a text mining platform that allows the construction, evaluation and comparison of text mining workflows. U-Compare contains a large library of components that are tuned to the biomedical domain. Users can rapidly develop biomedical text mining workflows by mixing and matching U-Compare's components. Workflows developed using U-Compare can be exported and sent to other users who, in turn, can import and re-use them. However, the resulting workflows are standalone applications, i.e., software tools that run and are accessible only via a local machine, and that can only be run with the U-Compare platform. We address the above issues by extending U-Compare to convert standalone workflows into web services automatically, via a two-click process. The resulting web services can be registered on a central server and made publicly available. Alternatively, users can make web services available on their own servers, after installing the web application framework, which is part of the extension to U-Compare. We have performed a user-oriented evaluation of the proposed extension, by asking users who have tested the enhanced functionality of U-Compare to complete questionnaires that assess its functionality, reliability, usability, efficiency and maintainability. The results obtained reveal that the new functionality is well received by users. The web services produced by U-Compare are built on top of open standards, i.e., REST and SOAP protocols, and therefore, they are decoupled from the underlying platform. Exported workflows can be integrated with any application that supports these open standards. We demonstrate how the newly extended U-Compare enhances the cross-platform interoperability of workflows, by seamlessly importing a number of text mining workflow web services exported from U-Compare into Taverna, i.e., a generic scientific workflow construction platform.

Deploying and sharing U-Compare workflows as web services

PubMed Central

2013-01-01

Background U-Compare is a text mining platform that allows the construction, evaluation and comparison of text mining workflows. U-Compare contains a large library of components that are tuned to the biomedical domain. Users can rapidly develop biomedical text mining workflows by mixing and matching U-Compare’s components. Workflows developed using U-Compare can be exported and sent to other users who, in turn, can import and re-use them. However, the resulting workflows are standalone applications, i.e., software tools that run and are accessible only via a local machine, and that can only be run with the U-Compare platform. Results We address the above issues by extending U-Compare to convert standalone workflows into web services automatically, via a two-click process. The resulting web services can be registered on a central server and made publicly available. Alternatively, users can make web services available on their own servers, after installing the web application framework, which is part of the extension to U-Compare. We have performed a user-oriented evaluation of the proposed extension, by asking users who have tested the enhanced functionality of U-Compare to complete questionnaires that assess its functionality, reliability, usability, efficiency and maintainability. The results obtained reveal that the new functionality is well received by users. Conclusions The web services produced by U-Compare are built on top of open standards, i.e., REST and SOAP protocols, and therefore, they are decoupled from the underlying platform. Exported workflows can be integrated with any application that supports these open standards. We demonstrate how the newly extended U-Compare enhances the cross-platform interoperability of workflows, by seamlessly importing a number of text mining workflow web services exported from U-Compare into Taverna, i.e., a generic scientific workflow construction platform. PMID:23419017

Introducing Theranostics Journal - From the Editor-in-Chief

PubMed Central

Chen, Xiaoyuan (Shawn)

2011-01-01

Theranostics is a multidisciplinary journal that publishes innovative and original research papers reflecting the field of molecular imaging, molecular therapeutics, multifunctional nanoparticle platforms, image-guided therapy, and translational nanomedicine. A broad spectrum of biomedical research that can be applied to future theranostic applications is encouraged. PMID:21547150

Perspective: fostering biomedical literacy among America's youth: how medical simulation reshapes the strategy.

PubMed

Gordon, James A; Oriol, Nancy E

2008-05-01

Medicine is a uniquely powerful platform for teaching science and ethics, technology and humanity, life and death. Yet, society has historically limited medical education to a select few, and only after an advanced course of premedical studies. In an era when biomedical literacy is increasingly viewed as a national imperative, the authors hypothesized that advanced instruction in medicine could be intellectually transformative among a broad range of young people. Using high-fidelity patient simulators, a group of college and high school students was immersed in a weeklong course designed to replicate the practice of modern medicine. On the basis of the students' reported experiences, the authors feel that patient simulation can foster forceful interest in the life sciences at an early age. Such efforts could catalyze a significant expansion of interest in biomedical science among students nationwide.

The Perfect Neuroimaging-Genetics-Computation Storm: Collision of Petabytes of Data, Millions of Hardware Devices and Thousands of Software Tools

PubMed Central

Dinov, Ivo D.; Petrosyan, Petros; Liu, Zhizhong; Eggert, Paul; Zamanyan, Alen; Torri, Federica; Macciardi, Fabio; Hobel, Sam; Moon, Seok Woo; Sung, Young Hee; Jiang, Zhiguo; Labus, Jennifer; Kurth, Florian; Ashe-McNalley, Cody; Mayer, Emeran; Vespa, Paul M.; Van Horn, John D.; Toga, Arthur W.

2013-01-01

The volume, diversity and velocity of biomedical data are exponentially increasing providing petabytes of new neuroimaging and genetics data every year. At the same time, tens-of-thousands of computational algorithms are developed and reported in the literature along with thousands of software tools and services. Users demand intuitive, quick and platform-agnostic access to data, software tools, and infrastructure from millions of hardware devices. This explosion of information, scientific techniques, computational models, and technological advances leads to enormous challenges in data analysis, evidence-based biomedical inference and reproducibility of findings. The Pipeline workflow environment provides a crowd-based distributed solution for consistent management of these heterogeneous resources. The Pipeline allows multiple (local) clients and (remote) servers to connect, exchange protocols, control the execution, monitor the states of different tools or hardware, and share complete protocols as portable XML workflows. In this paper, we demonstrate several advanced computational neuroimaging and genetics case-studies, and end-to-end pipeline solutions. These are implemented as graphical workflow protocols in the context of analyzing imaging (sMRI, fMRI, DTI), phenotypic (demographic, clinical), and genetic (SNP) data. PMID:23975276

@Note: a workbench for biomedical text mining.

PubMed

Lourenço, Anália; Carreira, Rafael; Carneiro, Sónia; Maia, Paulo; Glez-Peña, Daniel; Fdez-Riverola, Florentino; Ferreira, Eugénio C; Rocha, Isabel; Rocha, Miguel

2009-08-01

Biomedical Text Mining (BioTM) is providing valuable approaches to the automated curation of scientific literature. However, most efforts have addressed the benchmarking of new algorithms rather than user operational needs. Bridging the gap between BioTM researchers and biologists' needs is crucial to solve real-world problems and promote further research. We present @Note, a platform for BioTM that aims at the effective translation of the advances between three distinct classes of users: biologists, text miners and software developers. Its main functional contributions are the ability to process abstracts and full-texts; an information retrieval module enabling PubMed search and journal crawling; a pre-processing module with PDF-to-text conversion, tokenisation and stopword removal; a semantic annotation schema; a lexicon-based annotator; a user-friendly annotation view that allows to correct annotations and a Text Mining Module supporting dataset preparation and algorithm evaluation. @Note improves the interoperability, modularity and flexibility when integrating in-home and open-source third-party components. Its component-based architecture allows the rapid development of new applications, emphasizing the principles of transparency and simplicity of use. Although it is still on-going, it has already allowed the development of applications that are currently being used.

ChemBank: a small-molecule screening and cheminformatics resource database.

PubMed

Seiler, Kathleen Petri; George, Gregory A; Happ, Mary Pat; Bodycombe, Nicole E; Carrinski, Hyman A; Norton, Stephanie; Brudz, Steve; Sullivan, John P; Muhlich, Jeremy; Serrano, Martin; Ferraiolo, Paul; Tolliday, Nicola J; Schreiber, Stuart L; Clemons, Paul A

2008-01-01

ChemBank (http://chembank.broad.harvard.edu/) is a public, web-based informatics environment developed through a collaboration between the Chemical Biology Program and Platform at the Broad Institute of Harvard and MIT. This knowledge environment includes freely available data derived from small molecules and small-molecule screens and resources for studying these data. ChemBank is unique among small-molecule databases in its dedication to the storage of raw screening data, its rigorous definition of screening experiments in terms of statistical hypothesis testing, and its metadata-based organization of screening experiments into projects involving collections of related assays. ChemBank stores an increasingly varied set of measurements derived from cells and other biological assay systems treated with small molecules. Analysis tools are available and are continuously being developed that allow the relationships between small molecules, cell measurements, and cell states to be studied. Currently, ChemBank stores information on hundreds of thousands of small molecules and hundreds of biomedically relevant assays that have been performed at the Broad Institute by collaborators from the worldwide research community. The goal of ChemBank is to provide life scientists unfettered access to biomedically relevant data and tools heretofore available primarily in the private sector.

A small animal time-resolved optical tomography platform using wide-field excitation

NASA Astrophysics Data System (ADS)

Venugopal, Vivek

Small animal imaging plays a critical role in present day biomedical research by filling an important gap in the translation of research from the bench to the bedside. Optical techniques constitute an emerging imaging modality which have tremendous potential in preclinical applications. Optical imaging methods are capable of non-invasive assessment of the functional and molecular characteristics of biological tissue. The three-dimensional optical imaging technique, referred to as diffuse optical tomography, provides an approach for the whole-body imaging of small animal models and can provide volumetric maps of tissue functional parameters (e.g. blood volume, oxygen saturation etc.) and/or provide 3D localization and quantification of fluorescence-based molecular markers in vivo. However, the complex mathematical reconstruction problem associated with optical tomography and the cumbersome instrumental designs limits its adoption as a high-throughput quantitative whole-body imaging modality in current biomedical research. The development of new optical imaging paradigms is thus necessary for a wide-acceptance of this new technology. In this thesis, the design, development, characterization and optimization of a small animal optical tomography system is discussed. Specifically, the platform combines a highly sensitive time-resolved imaging paradigm with multi-spectral excitation capability and CCD-based detection to provide a system capable of generating spatially, spectrally and temporally dense measurement datasets. The acquisition of such data sets however can take long and translate to often unrealistic acquisition times when using the classical point source based excitation scheme. The novel approach in the design of this platform is the adoption of a wide-field excitation scheme which employs extended excitation sources and in the process allows an estimated ten-fold reduction in the acquisition time. The work described herein details the design of the imaging platform employing DLP-based excitation and time-gated intensified CCD detection and the optimal system operation parameters are determined. The feasibility this imaging approach and accuracy of the system in reconstructing functional parameters and fluorescence markers based on lifetime contrast is established through phantom studies. As a part of the system characterization, the effect of noise in time-resolved optical tomography is investigated and propagation of system noise in optical reconstructions is established. Furthermore, data processing and measurement calibration techniques aimed at reducing the effect of noise in reconstructions are defined. The optimization of excitation pattern selection is established through a novel measurement-guided iterative pattern correction scheme. This technique referred to as Adaptive Full-Field Optical Tomography was shown to improve reconstruction performances in murine models by reducing the dynamic range in photon flux measurements on the surface. Lastly, the application of the unique attributes of this platform to a biologically relevant imaging application, referred to as Forster Resonance Energy Transfer is described. The tomographic imaging of FRET interaction in vivo on a whole-body scale is achieved using the wide-field imaging approach based on lifetime contrast. This technique represents the first demonstration of tomographic FRET imaging in small animals and has significant potential in the development of optical imaging techniques in varied applications ranging from drug discovery to in vivo study of protein-protein interaction.

A new paradigm for improved co-ordination and efficacy of European biomedical research: taking diabetes as a model.

PubMed

Halban, P A; Boulton, A J M; Smith, U

2013-03-01

Today, European biomedical and health-related research is insufficiently well funded and is fragmented, with no common vision, less-than-optimal sharing of resources, and inadequate support and training in clinical research. Improvements to the competitiveness of European biomedical research will depend on the creation of new infrastructures that must be dynamic and free of bureaucracy, involve all stakeholders and facilitate faster delivery of new discoveries from bench to bedside. Taking diabetes research as the model, a new paradigm for European biomedical research is presented, which offers improved co-ordination and common resources that will benefit both academic and industrial clinical research. This includes the creation of a European Council for Health Research, first proposed by the Alliance for Biomedical Research in Europe, which will bring together and consult with all health stakeholders to develop strategic and multidisciplinary research programmes addressing the full innovation cycle. A European Platform for Clinical Research in Diabetes is proposed by the Alliance for European Diabetes Research (EURADIA) in response to the special challenges and opportunities presented by research across the European region, with the need for common standards and shared expertise and data.

Gold nanoparticle-DNA aptamer composites as a universal carrier for in vivo delivery of biologically functional proteins.

PubMed

Ryou, Sang-Mi; Yeom, Ji-Hyun; Kang, Hyo Jung; Won, Miae; Kim, Jin-Sik; Lee, Boeun; Seong, Maeng-Je; Ha, Nam-Chul; Bae, Jeehyeon; Lee, Kangseok

2014-12-28

Although the delivery of biologically functional protein(s) into mammalian cells could be of tremendous value to biomedical research, the development of such technology has been hindered by the lack of a safe and effective delivery method. Here, we present a simple, efficient, and versatile gold nanoparticle-DNA aptamer conjugate (AuNP-Apt)-based system, with nanoblock-like properties, that allows any recombinant protein to be loaded without additional modifications and delivered into mammalian living systems. AuNP-Apt-based protein delivery system was able to deliver various proteins into variety of cell types in vitro without showing cytotoxicity. This AuNP-Apt system was also effective for the local and systemic targeted delivery of proteins in vivo. A local injection of the AuNP-Apt loaded with the apoptosis-inducing BIM protein efficiently inhibited the growth of xenograft tumors in mice. Furthermore, an intravenous injection of AuNP-Apt loaded with both epidermal growth factor (EGF) and BIM resulted in the targeted delivery of BIM into a xenograft tumor derived from EGF receptor-overexpressing cancer cells with no detectable systemic toxicity. Our findings show that this system can serve as an innovative platform for the development of protein-based biomedical applications. Copyright © 2014 Elsevier B.V. All rights reserved.

Distribution of immunodeficiency fact files with XML--from Web to WAP.

PubMed

Väliaho, Jouni; Riikonen, Pentti; Vihinen, Mauno

2005-06-26

Although biomedical information is growing rapidly, it is difficult to find and retrieve validated data especially for rare hereditary diseases. There is an increased need for services capable of integrating and validating information as well as proving it in a logically organized structure. A XML-based language enables creation of open source databases for storage, maintenance and delivery for different platforms. Here we present a new data model called fact file and an XML-based specification Inherited Disease Markup Language (IDML), that were developed to facilitate disease information integration, storage and exchange. The data model was applied to primary immunodeficiencies, but it can be used for any hereditary disease. Fact files integrate biomedical, genetic and clinical information related to hereditary diseases. IDML and fact files were used to build a comprehensive Web and WAP accessible knowledge base ImmunoDeficiency Resource (IDR) available at http://bioinf.uta.fi/idr/. A fact file is a user oriented user interface, which serves as a starting point to explore information on hereditary diseases. The IDML enables the seamless integration and presentation of genetic and disease information resources in the Internet. IDML can be used to build information services for all kinds of inherited diseases. The open source specification and related programs are available at http://bioinf.uta.fi/idml/.

Editorial policies and good practices in editing the journal 'International Medical Journal--Medicus'.

PubMed

Pollozhani, Aziz

2014-01-01

Ten years ago the Association of Albanian Physicians in Macedonia undertook the very brave step of publishing a scientific medical journal, Medicus, as a platform for publishing biomedical research papers. Medical journal MEDICUS is an international peer-review journal of biomedical science. The first issue was published in 2004, starting with publishing two issues per year. From 2013, the journal delivered three issues per year, namely in January, May and September. Editor-in-Chief of the journal is Prof. Dr. Aziz Pollozhani. This year marks the tenth anniversary since publication of the first issue of Medicus, a fact that makes us proud and happy. The journal has its own official website (www.imjm.mk), where papers can be submitted and published in electronic form. In addition, the journal also comes out in print form to be distributed mainly in the region. Taking into account the specific socio-cultural characteristics of the region, the journal attempts to promote research activities in the region, while seeking to serve as an educational tool to promote scientific work in such a setting. As a result, Medicus accepts manuscripts for publication in English, Albanian and Macedonian, with a mandatory abstract in English for all papers. The journal Medicus represents a solid platform of biomedical sciences that will serve to advance scientific research and promote professional achievements in medicine.

Ubiquitous Computing for Remote Cardiac Patient Monitoring: A Survey

PubMed Central

Kumar, Sunil; Kambhatla, Kashyap; Hu, Fei; Lifson, Mark; Xiao, Yang

2008-01-01

New wireless technologies, such as wireless LAN and sensor networks, for telecardiology purposes give new possibilities for monitoring vital parameters with wearable biomedical sensors, and give patients the freedom to be mobile and still be under continuous monitoring and thereby better quality of patient care. This paper will detail the architecture and quality-of-service (QoS) characteristics in integrated wireless telecardiology platforms. It will also discuss the current promising hardware/software platforms for wireless cardiac monitoring. The design methodology and challenges are provided for realistic implementation. PMID:18604301

Ubiquitous computing for remote cardiac patient monitoring: a survey.

PubMed

Kumar, Sunil; Kambhatla, Kashyap; Hu, Fei; Lifson, Mark; Xiao, Yang

2008-01-01

New wireless technologies, such as wireless LAN and sensor networks, for telecardiology purposes give new possibilities for monitoring vital parameters with wearable biomedical sensors, and give patients the freedom to be mobile and still be under continuous monitoring and thereby better quality of patient care. This paper will detail the architecture and quality-of-service (QoS) characteristics in integrated wireless telecardiology platforms. It will also discuss the current promising hardware/software platforms for wireless cardiac monitoring. The design methodology and challenges are provided for realistic implementation.

Architecture and Initial Development of a Digital Library Platform for Computable Knowledge Objects for Health.

PubMed

Flynn, Allen J; Bahulekar, Namita; Boisvert, Peter; Lagoze, Carl; Meng, George; Rampton, James; Friedman, Charles P

2017-01-01

Throughout the world, biomedical knowledge is routinely generated and shared through primary and secondary scientific publications. However, there is too much latency between publication of knowledge and its routine use in practice. To address this latency, what is actionable in scientific publications can be encoded to make it computable. We have created a purpose-built digital library platform to hold, manage, and share actionable, computable knowledge for health called the Knowledge Grid Library. Here we present it with its system architecture.

Tellurium-containing polymer micelles: competitive-ligand-regulated coordination responsive systems.

PubMed

Cao, Wei; Gu, Yuwei; Meineck, Myriam; Li, Tianyu; Xu, Huaping

2014-04-02

Nanomaterials capable of achieving tunable cargo release kinetics are of significance in a fundamental sense and various biological or medical applications. We report a competitive coordination system based on a novel tellurium-containing polymer and its ligand-regulated release manners. Tellurium was introduced to water-soluble polymers for the first time as drug delivery vehicles. The coordination chemistry between platinum and tellurium was designed to enable the load of platinum-based drugs. Through the competitive coordination of biomolecules, the drugs could be released in a controlled manner. Furthermore, the release kinetics could be modulated by the competitive ligands involved due to their different coordination ability. This tellurium-containing polymer may enrich the family of delivery systems and provide a new platform for future biomedical nanotechnologies.

Silicon nanostructures for cancer diagnosis and therapy.

PubMed

Peng, Fei; Cao, Zhaohui; Ji, Xiaoyuan; Chu, Binbin; Su, Yuanyuan; He, Yao

2015-01-01

The emergence of nanotechnology suggests new and exciting opportunities for early diagnosis and therapy of cancer. During the recent years, silicon-based nanomaterials featuring unique properties have received great attention, showing high promise for myriad biological and biomedical applications. In this review, we will particularly summarize latest representative achievements on the development of silicon nanostructures as a powerful platform for cancer early diagnosis and therapy. First, we introduce the silicon nanomaterial-based biosensors for detecting cancer markers (e.g., proteins, tumor-suppressor genes and telomerase activity, among others) with high sensitivity and selectivity under molecular level. Then, we summarize in vitro and in vivo applications of silicon nanostructures as efficient nanoagents for cancer therapy. Finally, we discuss the future perspective of silicon nanostructures for cancer diagnosis and therapy.

Fabrication of an electrochemical platform based on the self-assembly of graphene oxide-multiwall carbon nanotube nanocomposite and horseradish peroxidase: direct electrochemistry and electrocatalysis

NASA Astrophysics Data System (ADS)

Zhang, Qian; Yang, Shaojun; Zhang, Jing; Zhang, Ling; Kang, Pingli; Li, Jinghong; Xu, Jingwei; Zhou, Hua; Song, Xi-Ming

2011-12-01

A novel hybrid nanomaterial (GO-MWNTs) was explored based on the self-assembly of multiwall carbon nanotubes (MWNTs) and graphene oxide (GO). Compared with pristine MWNTs, such a nanocomposite could be well dispersed in aqueous solution and exhibit a negative charge. Driven by the electrostatic interaction, positively charged horseradish peroxidase (HRP) could then be immobilized onto GO-MWNTs at the surface of a glassy carbon (GC) electrode to form a HRP/GO-MWNT/GC electrode under mild conditions. TEM was used to characterize the morphology of the GO-MWNT nanocomposite. UV-vis and FTIR spectra suggested that HRP was immobilized onto the hybrid matrix without denaturation. Furthermore, the immobilized HRP showed enhanced direct electron transfer for the HRP-Fe(III)/Fe(II) redox center. Based on the direct electron transfer of the immobilized HRP, the HRP/GO-MWNT/GC electrode exhibited excellent electrocatalytic behavior to the reduction of H2O2 and NaNO2, respectively. Therefore, GO-MWNTs could provide a novel and efficient platform for the immobilization and biosensing of redox enzymes, and thus may find wide potential applications in the fabrication of biosensors, biomedical devices, and bioelectronics.

Facilities available for biomedical science research in the public universities in Lagos, Nigeria.

PubMed

John, T A

2010-03-01

Across the world, basic medical scientists and physician scientists work on common platforms in state-of-the-arts laboratories doing translational research that occasionally results in bedside application. Biotechnology industries capitalise on useful findings for colossal profit.1 In Nigeria and the rest of Africa, biomedical science has not thrived and the contribution of publications to global high impact journals is low.2 This work investigated facilities available for modern biomedical research in Lagos public universities to extract culprit factors. The two public universities in Lagos, Nigeria were investigated by a cross sectional questionnaire survey of the technical staff manning biomedical science departments. They were asked about availability of 47 modern biomedical science research laboratory components such as cold room and microscopes and six research administration components such as director of research and grants administration. For convenient basic laboratory components such as autoclaves and balances, 50% responses indicated "well maintained and always functional" whereas for less convenient complex, high maintenance, state-of-the-arts equipment 19% responses indicated "well maintained and always functional." Respondents indicated that components of modern biomedical science research administration were 44% of expectation. The survey reveal a deficit in state-of the-arts research equipment and also a deficit in high maintenance, expensive equipment indicating that biomedical science in the investigated environment lacks the momentum of global trends and also lacks buoyant funding. In addition, administration supporting biomedical science is below expectation and may also account for the low contributions of research articles to global high impact journals.

Microsystems and Nanoscience for Biomedical Applications: A View to the Future

ERIC Educational Resources Information Center

Pilarski, Linda M.; Mehta, Michael D.; Caulfield, Timothy; Kaler, Karan V. I. S.; Backhouse, Christopher J.

2004-01-01

At present there is an enormous discrepancy between our nanotechnological capabilities (particularly our nanobiotechnologies), our social wisdom, and consensus on how to apply them. To date, cost considerations have greatly constrained our application of nanotechnologies. However, novel advances in microsystem platform technologies are about to…

Synthetic Micro/Nanomachines and Their Applications: Towards 'Fantastic Voyage'

NASA Astrophysics Data System (ADS)

Gao, Wei

The 1966 movie Fantastic Voyage captured the world's imagination, portraying a tiny submarine navigating through the human bloodstream and treating life-threatening medical conditions. My PhD research focuses on the synthetic nano/microscale machines to realize the Fantastic Voyage vision. Various biomedical and environmental areas would benefit from the developments of efficient fuel-free and fuel-driven nano/microscale machines. The polymer-based catalytic tubular microengine is synthesized using a template based electrodeposition method. The oxygen bubble propelled microengine harvests the energy from chemical fuels (such as H2O2) and displays very efficient propulsion. It can serve as an ideal platform for diverse biomedical and environmental applications. For example, lectin modified polyaniline based microengines can be used for selective bacteria (E. Coli) isolation from food, clinical and environmental samples; poly(3-aminophenylboronic acid)/Ni/Pt microengine itself provides the 'built in' glucose recognition capability for 'on-the-fly' capture, transport and release of yeast cells. A series of micromotors which can be self-propelled in natural environments without additional chemical fuels are developed, holding great promise for in vivo biomedical applications: the polyaniline/zinc microrockets display effective autonomous motion in extreme acidic environments (such as human stomach); the Al-Ga/Ti based Janus micromotor can be propelled by the hydrogen bubbles generated from the rapid aluminum and water reaction; alkanethiols modified seawater-driven Mg Janus micromotors, which utilize macrogalvanic corrosion and chloride pitting corrosion processes, can be used for environmental oil remediation. Magnetically powered nanoswimmers have attracted considerable attention due to their great biocompatibility. A high-speed magnetically-propelled nanowire swimmer which mimics swimming microorganisms by exploiting the flexible nanowire as artificial flagella under rotating magnetic field is illustrated. New bioinspired microswimmers can also be prepared directly from isolated spiral vessels of plants, harnessing the intrinsic biological structures of nature. Potential applications of these cargo-towing nanoswimmers are demonstrated by the directed delivery of drug-loaded microparticles to HeLa cancer cells in biological media. With such innovations and developments, along with careful attention to key challenges and requirements, nano/microscale motors are expected to have tremendous impact on diverse biomedical and environmental applications, providing unlimited opportunities limited only by one's imagination.

Crossing the Chasm: Information Technology to Biomedical Informatics

PubMed Central

Fahy, Brenda G.; Balke, C. William; Umberger, Gloria H.; Talbert, Jeffery; Canales, Denise Niles; Steltenkamp, Carol L.; Conigliaro, Joseph

2011-01-01

Accelerating the translation of new scientific discoveries to improve human health and disease management is the overall goal of a series of initiatives integrated in the National Institutes of Health (NIH) “Roadmap for Medical Research.” The Clinical and Translational Research Award (CTSA) program is, arguably, the most visible component of the NIH Roadmap providing resources to institutions to transform their clinical and translational research enterprises along the goals of the Roadmap. The CTSA program emphasizes biomedical informatics as a critical component for the accomplishment of the NIH’s translational objectives. To be optimally effective, emerging biomedical informatics programs must link with the information technology (IT) platforms of the enterprise clinical operations within academic health centers. This report details one academic health center’s transdisciplinary initiative to create an integrated academic discipline of biomedical informatics through the development of its infrastructure for clinical and translational science infrastructure and response to the CTSA mechanism. This approach required a detailed informatics strategy to accomplish these goals. This transdisciplinary initiative was the impetus for creation of a specialized biomedical informatics core, the Center for Biomedical Informatics (CBI). Development of the CBI codified the need to incorporate medical informatics including quality and safety informatics and enterprise clinical information systems within the CBI. This paper describes the steps taken to develop the biomedical informatics infrastructure, its integration with clinical systems at one academic health center, successes achieved, and barriers encountered during these efforts. PMID:21383632

Multifunctional, inexpensive, and reusable nanoparticle-printed biochip for cell manipulation and diagnosis

PubMed Central

Esfandyarpour, Rahim; DiDonato, Matthew J.; Yang, Yuxin; Durmus, Naside Gozde; Harris, James S.; Davis, Ronald W.

2017-01-01

Isolation and characterization of rare cells and molecules from a heterogeneous population is of critical importance in diagnosis of common lethal diseases such as malaria, tuberculosis, HIV, and cancer. For the developing world, point-of-care (POC) diagnostics design must account for limited funds, modest public health infrastructure, and low power availability. To address these challenges, here we integrate microfluidics, electronics, and inkjet printing to build an ultra–low-cost, rapid, and miniaturized lab-on-a-chip (LOC) platform. This platform can perform label-free and rapid single-cell capture, efficient cellular manipulation, rare-cell isolation, selective analytical separation of biological species, sorting, concentration, positioning, enumeration, and characterization. The miniaturized format allows for small sample and reagent volumes. By keeping the electronics separate from microfluidic chips, the former can be reused and device lifetime is extended. Perhaps most notably, the device manufacturing is significantly less expensive, time-consuming, and complex than traditional LOC platforms, requiring only an inkjet printer rather than skilled personnel and clean-room facilities. Production only takes 20 min (vs. up to weeks) and $0.01—an unprecedented cost in clinical diagnostics. The platform works based on intrinsic physical characteristics of biomolecules (e.g., size and polarizability). We demonstrate biomedical applications and verify cell viability in our platform, whose multiplexing and integration of numerous steps and external analyses enhance its application in the clinic, including by nonspecialists. Through its massive cost reduction and usability we anticipate that our platform will enable greater access to diagnostic facilities in developed countries as well as POC diagnostics in resource-poor and developing countries. PMID:28167769

Java and its future in biomedical computing.

PubMed Central

Rodgers, R P

1996-01-01

Java, a new object-oriented computing language related to C++, is receiving considerable attention due to its use in creating network-sharable, platform-independent software modules (known as "applets") that can be used with the World Wide Web. The Web has rapidly become the most commonly used information-retrieval tool associated with the global computer network known as the Internet, and Java has the potential to further accelerate the Web's application to medical problems. Java's potentially wide acceptance due to its Web association and its own technical merits also suggests that it may become a popular language for non-Web-based, object-oriented computing. PMID:8880677

The Cell Collective: Toward an open and collaborative approach to systems biology

PubMed Central

2012-01-01

Background Despite decades of new discoveries in biomedical research, the overwhelming complexity of cells has been a significant barrier to a fundamental understanding of how cells work as a whole. As such, the holistic study of biochemical pathways requires computer modeling. Due to the complexity of cells, it is not feasible for one person or group to model the cell in its entirety. Results The Cell Collective is a platform that allows the world-wide scientific community to create these models collectively. Its interface enables users to build and use models without specifying any mathematical equations or computer code - addressing one of the major hurdles with computational research. In addition, this platform allows scientists to simulate and analyze the models in real-time on the web, including the ability to simulate loss/gain of function and test what-if scenarios in real time. Conclusions The Cell Collective is a web-based platform that enables laboratory scientists from across the globe to collaboratively build large-scale models of various biological processes, and simulate/analyze them in real time. In this manuscript, we show examples of its application to a large-scale model of signal transduction. PMID:22871178

The application of biomedical engineering techniques to the diagnosis and management of tropical diseases: a review.

PubMed

Ibrahim, Fatimah; Thio, Tzer Hwai Gilbert; Faisal, Tarig; Neuman, Michael

2015-03-23

This paper reviews a number of biomedical engineering approaches to help aid in the detection and treatment of tropical diseases such as dengue, malaria, cholera, schistosomiasis, lymphatic filariasis, ebola, leprosy, leishmaniasis, and American trypanosomiasis (Chagas). Many different forms of non-invasive approaches such as ultrasound, echocardiography and electrocardiography, bioelectrical impedance, optical detection, simplified and rapid serological tests such as lab-on-chip and micro-/nano-fluidic platforms and medical support systems such as artificial intelligence clinical support systems are discussed. The paper also reviewed the novel clinical diagnosis and management systems using artificial intelligence and bioelectrical impedance techniques for dengue clinical applications.

Three-dimensional Imaging and Scanning: Current and Future Applications for Pathology

PubMed Central

Farahani, Navid; Braun, Alex; Jutt, Dylan; Huffman, Todd; Reder, Nick; Liu, Zheng; Yagi, Yukako; Pantanowitz, Liron

2017-01-01

Imaging is vital for the assessment of physiologic and phenotypic details. In the past, biomedical imaging was heavily reliant on analog, low-throughput methods, which would produce two-dimensional images. However, newer, digital, and high-throughput three-dimensional (3D) imaging methods, which rely on computer vision and computer graphics, are transforming the way biomedical professionals practice. 3D imaging has been useful in diagnostic, prognostic, and therapeutic decision-making for the medical and biomedical professions. Herein, we summarize current imaging methods that enable optimal 3D histopathologic reconstruction: Scanning, 3D scanning, and whole slide imaging. Briefly mentioned are emerging platforms, which combine robotics, sectioning, and imaging in their pursuit to digitize and automate the entire microscopy workflow. Finally, both current and emerging 3D imaging methods are discussed in relation to current and future applications within the context of pathology. PMID:28966836

Utility and translatability of mathematical modeling, cell culture and small and large animal models in magnetic nanoparticle hyperthermia cancer treatment research

NASA Astrophysics Data System (ADS)

Hoopes, P. J.; Petryk, Alicia A.; Misra, Adwiteeya; Kastner, Elliot J.; Pearce, John A.; Ryan, Thomas P.

2015-03-01

For more than 50 years, hyperthermia-based cancer researchers have utilized mathematical models, cell culture studies and animal models to better understand, develop and validate potential new treatments. It has been, and remains, unclear how and to what degree these research techniques depend on, complement and, ultimately, translate accurately to a successful clinical treatment. In the past, when mathematical models have not proven accurate in a clinical treatment situation, the initiating quantitative scientists (engineers, mathematicians and physicists) have tended to believe the biomedical parameters provided to them were inaccurately determined or reported. In a similar manner, experienced biomedical scientists often tend to question the value of mathematical models and cell culture results since those data typically lack the level of biologic and medical variability and complexity that are essential to accurately study and predict complex diseases and subsequent treatments. Such quantitative and biomedical interdependence, variability, diversity and promise have never been greater than they are within magnetic nanoparticle hyperthermia cancer treatment. The use of hyperthermia to treat cancer is well studied and has utilized numerous delivery techniques, including microwaves, radio frequency, focused ultrasound, induction heating, infrared radiation, warmed perfusion liquids (combined with chemotherapy), and, recently, metallic nanoparticles (NP) activated by near infrared radiation (NIR) and alternating magnetic field (AMF) based platforms. The goal of this paper is to use proven concepts and current research to address the potential pathobiology, modeling and quantification of the effects of treatment as pertaining to the similarities and differences in energy delivered by known external delivery techniques and iron oxide nanoparticles.

Lessons Learned from Development of De-identification System for Biomedical Research in a Korean Tertiary Hospital.

PubMed

Shin, Soo-Yong; Lyu, Yongman; Shin, Yongdon; Choi, Hyo Joung; Park, Jihyun; Kim, Woo-Sung; Lee, Jae Ho

2013-06-01

The Korean government has enacted two laws, namely, the Personal Information Protection Act and the Bioethics and Safety Act to prevent the unauthorized use of medical information. To protect patients' privacy by complying with governmental regulations and improve the convenience of research, Asan Medical Center has been developing a de-identification system for biomedical research. We reviewed Korean regulations to define the scope of the de-identification methods and well-known previous biomedical research platforms to extract the functionalities of the systems. Based on these review results, we implemented necessary programs based on the Asan Medical Center Information System framework which was built using the Microsoft. NET Framework and C#. The developed de-identification system comprises three main components: a de-identification tool, a search tool, and a chart review tool. The de-identification tool can substitute a randomly assigned research ID for a hospital patient ID, remove the identifiers in the structured format, and mask them in the unstructured format, i.e., texts. This tool achieved 98.14% precision and 97.39% recall for 6,520 clinical notes. The search tool can find the number of patients which satisfies given search criteria. The chart review tool can provide de-identified patient's clinical data for review purposes. We found that a clinical data warehouse was essential for successful implementation of the de-identification system, and this system should be tightly linked to an electronic Institutional Review Board system for easy operation of honest brokers. Additionally, we found that a secure cloud environment could be adopted to protect patients' privacy more thoroughly.

CRISPR Editing in Biological and Biomedical Investigation.

PubMed

Ju, Xing-Da; Xu, Jing; Sun, Zhong Sheng

2018-01-01

The CRISPR (clustered regularly interspaced short palindromic repeat)-Cas (CRISPR-associated protein) system, a prokaryotic RNA-based adaptive immune system against viral infection, is emerging as a powerful genome editing tool in broad research areas. To further improve and expand its functionality, various CRISPR delivery strategies have been tested and optimized, and key CRISPR system components such as Cas protein have been engineered with different purposes. Benefiting from more in-depth understanding and further development of CRISPR, versatile CRISPR-based platforms for genome editing have been rapidly developed to advance investigations in biology and biomedicine. In biological research area, CRISPR has been widely adopted in both fundamental and applied research fields, such as genomic and epigenomic modification, genome-wide screening, cell and animal research, agriculture transforming, livestock breeding, food manufacture, industrial biotechnology, and gene drives in disease agents control. In biomedical research area, CRISPR has also shown its extensive applicability in the establishment of animal models for genetic disorders, generation of tissue donors, implementation of antimicrobial and antiviral studies, identification and assessment of new drugs, and even treatment for clinical diseases. However, there are still several problems to consider, and the biggest concerns are the off-target effects and ethical issues of this technology. In this prospect article, after highlighting recent development of CRISPR systems, we outline different applications and current limitations of CRISPR in biological and biomedical investigation. Finally, we provide a perspective on future development and potential risks of this multifunctional technology. J. Cell. Biochem. 119: 52-61, 2018. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Comparing the performance of biomedical clustering methods.

PubMed

Wiwie, Christian; Baumbach, Jan; Röttger, Richard

2015-11-01

Identifying groups of similar objects is a popular first step in biomedical data analysis, but it is error-prone and impossible to perform manually. Many computational methods have been developed to tackle this problem. Here we assessed 13 well-known methods using 24 data sets ranging from gene expression to protein domains. Performance was judged on the basis of 13 common cluster validity indices. We developed a clustering analysis platform, ClustEval (http://clusteval.mpi-inf.mpg.de), to promote streamlined evaluation, comparison and reproducibility of clustering results in the future. This allowed us to objectively evaluate the performance of all tools on all data sets with up to 1,000 different parameter sets each, resulting in a total of more than 4 million calculated cluster validity indices. We observed that there was no universal best performer, but on the basis of this wide-ranging comparison we were able to develop a short guideline for biomedical clustering tasks. ClustEval allows biomedical researchers to pick the appropriate tool for their data type and allows method developers to compare their tool to the state of the art.

Biomedical semantics in the Semantic Web

PubMed Central

2011-01-01

The Semantic Web offers an ideal platform for representing and linking biomedical information, which is a prerequisite for the development and application of analytical tools to address problems in data-intensive areas such as systems biology and translational medicine. As for any new paradigm, the adoption of the Semantic Web offers opportunities and poses questions and challenges to the life sciences scientific community: which technologies in the Semantic Web stack will be more beneficial for the life sciences? Is biomedical information too complex to benefit from simple interlinked representations? What are the implications of adopting a new paradigm for knowledge representation? What are the incentives for the adoption of the Semantic Web, and who are the facilitators? Is there going to be a Semantic Web revolution in the life sciences? We report here a few reflections on these questions, following discussions at the SWAT4LS (Semantic Web Applications and Tools for Life Sciences) workshop series, of which this Journal of Biomedical Semantics special issue presents selected papers from the 2009 edition, held in Amsterdam on November 20th. PMID:21388570

Biomedical semantics in the Semantic Web.

PubMed

Splendiani, Andrea; Burger, Albert; Paschke, Adrian; Romano, Paolo; Marshall, M Scott

2011-03-07

The Semantic Web offers an ideal platform for representing and linking biomedical information, which is a prerequisite for the development and application of analytical tools to address problems in data-intensive areas such as systems biology and translational medicine. As for any new paradigm, the adoption of the Semantic Web offers opportunities and poses questions and challenges to the life sciences scientific community: which technologies in the Semantic Web stack will be more beneficial for the life sciences? Is biomedical information too complex to benefit from simple interlinked representations? What are the implications of adopting a new paradigm for knowledge representation? What are the incentives for the adoption of the Semantic Web, and who are the facilitators? Is there going to be a Semantic Web revolution in the life sciences?We report here a few reflections on these questions, following discussions at the SWAT4LS (Semantic Web Applications and Tools for Life Sciences) workshop series, of which this Journal of Biomedical Semantics special issue presents selected papers from the 2009 edition, held in Amsterdam on November 20th.

Graphene Field Effect Transistors for Biomedical Applications: Current Status and Future Prospects.

PubMed

Forsyth, Rhiannan; Devadoss, Anitha; Guy, Owen J

2017-07-26

Since the discovery of the two-dimensional (2D) carbon material, graphene, just over a decade ago, the development of graphene-based field effect transistors (G-FETs) has become a widely researched area, particularly for use in point-of-care biomedical applications. G-FETs are particularly attractive as next generation bioelectronics due to their mass-scalability and low cost of the technology's manufacture. Furthermore, G-FETs offer the potential to complete label-free, rapid, and highly sensitive analysis coupled with a high sample throughput. These properties, coupled with the potential for integration into portable instrumentation, contribute to G-FETs' suitability for point-of-care diagnostics. This review focuses on elucidating the recent developments in the field of G-FET sensors that act on a bioaffinity basis, whereby a binding event between a bioreceptor and the target analyte is transduced into an electrical signal at the G-FET surface. Recognizing and quantifying these target analytes accurately and reliably is essential in diagnosing many diseases, therefore it is vital to design the G-FET with care. Taking into account some limitations of the sensor platform, such as Debye-Hükel screening and device surface area, is fundamental in developing improved bioelectronics for applications in the clinical setting. This review highlights some efforts undertaken in facing these limitations in order to bring G-FET development for biomedical applications forward.

COEUS: “semantic web in a box” for biomedical applications

PubMed Central

2012-01-01

Background As the “omics” revolution unfolds, the growth in data quantity and diversity is bringing about the need for pioneering bioinformatics software, capable of significantly improving the research workflow. To cope with these computer science demands, biomedical software engineers are adopting emerging semantic web technologies that better suit the life sciences domain. The latter’s complex relationships are easily mapped into semantic web graphs, enabling a superior understanding of collected knowledge. Despite increased awareness of semantic web technologies in bioinformatics, their use is still limited. Results COEUS is a new semantic web framework, aiming at a streamlined application development cycle and following a “semantic web in a box” approach. The framework provides a single package including advanced data integration and triplification tools, base ontologies, a web-oriented engine and a flexible exploration API. Resources can be integrated from heterogeneous sources, including CSV and XML files or SQL and SPARQL query results, and mapped directly to one or more ontologies. Advanced interoperability features include REST services, a SPARQL endpoint and LinkedData publication. These enable the creation of multiple applications for web, desktop or mobile environments, and empower a new knowledge federation layer. Conclusions The platform, targeted at biomedical application developers, provides a complete skeleton ready for rapid application deployment, enhancing the creation of new semantic information systems. COEUS is available as open source at http://bioinformatics.ua.pt/coeus/. PMID:23244467

COEUS: "semantic web in a box" for biomedical applications.

PubMed

Lopes, Pedro; Oliveira, José Luís

2012-12-17

As the "omics" revolution unfolds, the growth in data quantity and diversity is bringing about the need for pioneering bioinformatics software, capable of significantly improving the research workflow. To cope with these computer science demands, biomedical software engineers are adopting emerging semantic web technologies that better suit the life sciences domain. The latter's complex relationships are easily mapped into semantic web graphs, enabling a superior understanding of collected knowledge. Despite increased awareness of semantic web technologies in bioinformatics, their use is still limited. COEUS is a new semantic web framework, aiming at a streamlined application development cycle and following a "semantic web in a box" approach. The framework provides a single package including advanced data integration and triplification tools, base ontologies, a web-oriented engine and a flexible exploration API. Resources can be integrated from heterogeneous sources, including CSV and XML files or SQL and SPARQL query results, and mapped directly to one or more ontologies. Advanced interoperability features include REST services, a SPARQL endpoint and LinkedData publication. These enable the creation of multiple applications for web, desktop or mobile environments, and empower a new knowledge federation layer. The platform, targeted at biomedical application developers, provides a complete skeleton ready for rapid application deployment, enhancing the creation of new semantic information systems. COEUS is available as open source at http://bioinformatics.ua.pt/coeus/.

Distance-based microfluidic quantitative detection methods for point-of-care testing.

PubMed

Tian, Tian; Li, Jiuxing; Song, Yanling; Zhou, Leiji; Zhu, Zhi; Yang, Chaoyong James

2016-04-07

Equipment-free devices with quantitative readout are of great significance to point-of-care testing (POCT), which provides real-time readout to users and is especially important in low-resource settings. Among various equipment-free approaches, distance-based visual quantitative detection methods rely on reading the visual signal length for corresponding target concentrations, thus eliminating the need for sophisticated instruments. The distance-based methods are low-cost, user-friendly and can be integrated into portable analytical devices. Moreover, such methods enable quantitative detection of various targets by the naked eye. In this review, we first introduce the concept and history of distance-based visual quantitative detection methods. Then, we summarize the main methods for translation of molecular signals to distance-based readout and discuss different microfluidic platforms (glass, PDMS, paper and thread) in terms of applications in biomedical diagnostics, food safety monitoring, and environmental analysis. Finally, the potential and future perspectives are discussed.

The Perseus computational platform for comprehensive analysis of (prote)omics data.

PubMed

Tyanova, Stefka; Temu, Tikira; Sinitcyn, Pavel; Carlson, Arthur; Hein, Marco Y; Geiger, Tamar; Mann, Matthias; Cox, Jürgen

2016-09-01

A main bottleneck in proteomics is the downstream biological analysis of highly multivariate quantitative protein abundance data generated using mass-spectrometry-based analysis. We developed the Perseus software platform (http://www.perseus-framework.org) to support biological and biomedical researchers in interpreting protein quantification, interaction and post-translational modification data. Perseus contains a comprehensive portfolio of statistical tools for high-dimensional omics data analysis covering normalization, pattern recognition, time-series analysis, cross-omics comparisons and multiple-hypothesis testing. A machine learning module supports the classification and validation of patient groups for diagnosis and prognosis, and it also detects predictive protein signatures. Central to Perseus is a user-friendly, interactive workflow environment that provides complete documentation of computational methods used in a publication. All activities in Perseus are realized as plugins, and users can extend the software by programming their own, which can be shared through a plugin store. We anticipate that Perseus's arsenal of algorithms and its intuitive usability will empower interdisciplinary analysis of complex large data sets.

Nanodroplet processing platform for deep and quantitative proteome profiling of 10-100 mammalian cells.

PubMed

Zhu, Ying; Piehowski, Paul D; Zhao, Rui; Chen, Jing; Shen, Yufeng; Moore, Ronald J; Shukla, Anil K; Petyuk, Vladislav A; Campbell-Thompson, Martha; Mathews, Clayton E; Smith, Richard D; Qian, Wei-Jun; Kelly, Ryan T

2018-02-28

Nanoscale or single-cell technologies are critical for biomedical applications. However, current mass spectrometry (MS)-based proteomic approaches require samples comprising a minimum of thousands of cells to provide in-depth profiling. Here, we report the development of a nanoPOTS (nanodroplet processing in one pot for trace samples) platform for small cell population proteomics analysis. NanoPOTS enhances the efficiency and recovery of sample processing by downscaling processing volumes to <200 nL to minimize surface losses. When combined with ultrasensitive liquid chromatography-MS, nanoPOTS allows identification of ~1500 to ~3000 proteins from ~10 to ~140 cells, respectively. By incorporating the Match Between Runs algorithm of MaxQuant, >3000 proteins are consistently identified from as few as 10 cells. Furthermore, we demonstrate quantification of ~2400 proteins from single human pancreatic islet thin sections from type 1 diabetic and control donors, illustrating the application of nanoPOTS for spatially resolved proteome measurements from clinical tissues.

Nanodroplet processing platform for deep and quantitative proteome profiling of 10–100 mammalian cells

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

Zhu, Ying; Piehowski, Paul D.; Zhao, Rui

Nanoscale or single cell technologies are critical for biomedical applications. However, current mass spectrometry (MS)-based proteomic approaches require samples comprising a minimum of thousands of cells to provide in-depth profiling. Here, we report the development of a nanoPOTS (Nanodroplet Processing in One pot for Trace Samples) platform as a major advance in overall sensitivity. NanoPOTS dramatically enhances the efficiency and recovery of sample processing by downscaling processing volumes to <200 nL to minimize surface losses. When combined with ultrasensitive LC-MS, nanoPOTS allows identification of ~1500 to ~3,000 proteins from ~10 to ~140 cells, respectively. By incorporating the Match Between Runsmore » algorithm of MaxQuant, >3000 proteins were consistently identified from as few as 10 cells. Furthermore, we demonstrate robust quantification of ~2400 proteins from single human pancreatic islet thin sections from type 1 diabetic and control donors, illustrating the application of nanoPOTS for spatially resolved proteome measurements from clinical tissues.« less

Nanodroplet processing platform for deep and quantitative proteome profiling of 10–100 mammalian cells

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

Zhu, Ying; Piehowski, Paul D.; Zhao, Rui

Nanoscale or single-cell technologies are critical for biomedical applications. However, current mass spectrometry (MS)-based proteomic approaches require samples comprising a minimum of thousands of cells to provide in-depth profiling. Here in this paper, we report the development of a nanoPOTS (nanodroplet processing in one pot for trace samples) platform for small cell population proteomics analysis. NanoPOTS enhances the efficiency and recovery of sample processing by downscaling processing volumes to <200 nL to minimize surface losses. When combined with ultrasensitive liquid chromatography-MS, nanoPOTS allows identification of ~1500 to ~3000 proteins from ~10 to ~140 cells, respectively. By incorporating the Match Betweenmore » Runs algorithm of MaxQuant, >3000 proteins are consistently identified from as few as 10 cells. Furthermore, we demonstrate quantification of ~2400 proteins from single human pancreatic islet thin sections from type 1 diabetic and control donors, illustrating the application of nanoPOTS for spatially resolved proteome measurements from clinical tissues.« less

Biodegradable gold nanovesicles with an ultrastrong plasmonic coupling effect for photoacoustic imaging and photothermal therapy.

PubMed

Huang, Peng; Lin, Jing; Li, Wanwan; Rong, Pengfei; Wang, Zhe; Wang, Shouju; Wang, Xiaoping; Sun, Xiaolian; Aronova, Maria; Niu, Gang; Leapman, Richard D; Nie, Zhihong; Chen, Xiaoyuan

2013-12-23

The hierarchical assembly of gold nanoparticles (GNPs) allows the localized surface plasmon resonance peaks to be engineered to the near-infrared (NIR) region for enhanced photothermal therapy (PTT). Herein we report a novel theranostic platform based on biodegradable plasmonic gold nanovesicles for photoacoustic (PA) imaging and PTT. The disulfide bond at the terminus of a PEG-b-PCL block-copolymer graft enables dense packing of GNPs during the assembly process and induces ultrastrong plasmonic coupling between adjacent GNPs. The strong NIR absorption induced by plasmon coupling and very high photothermal conversion efficiency (η=37%) enable simultaneous thermal/PA imaging and enhanced PTT efficacy with improved clearance of the dissociated particles after the completion of PTT. The assembly of various nanocrystals with tailored optical, magnetic, and electronic properties into vesicle architectures opens new possibilities for the construction of multifunctional biodegradable platforms for biomedical applications. Copyright © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Nanodroplet processing platform for deep and quantitative proteome profiling of 10–100 mammalian cells

DOE PAGES

Zhu, Ying; Piehowski, Paul D.; Zhao, Rui; ...

2018-02-28

Nanoscale or single-cell technologies are critical for biomedical applications. However, current mass spectrometry (MS)-based proteomic approaches require samples comprising a minimum of thousands of cells to provide in-depth profiling. Here in this paper, we report the development of a nanoPOTS (nanodroplet processing in one pot for trace samples) platform for small cell population proteomics analysis. NanoPOTS enhances the efficiency and recovery of sample processing by downscaling processing volumes to <200 nL to minimize surface losses. When combined with ultrasensitive liquid chromatography-MS, nanoPOTS allows identification of ~1500 to ~3000 proteins from ~10 to ~140 cells, respectively. By incorporating the Match Betweenmore » Runs algorithm of MaxQuant, >3000 proteins are consistently identified from as few as 10 cells. Furthermore, we demonstrate quantification of ~2400 proteins from single human pancreatic islet thin sections from type 1 diabetic and control donors, illustrating the application of nanoPOTS for spatially resolved proteome measurements from clinical tissues.« less

A RNA nanotechnology platform for a simultaneous two-in-one siRNA delivery and its application in synergistic RNAi therapy

PubMed Central

Jang, Mihue; Han, Hee Dong; Ahn, Hyung Jun

2016-01-01

Incorporating multiple copies of two RNAi molecules into a single nanostructure in a precisely controlled manner can provide an efficient delivery tool to regulate multiple gene pathways in the relation of mutual dependence. Here, we show a RNA nanotechnology platform for a two-in-one RNAi delivery system to contain polymeric two RNAi molecules within the same RNA nanoparticles, without the aid of polyelectrolyte condensation reagents. As our RNA nanoparticles lead to the simultaneous silencing of two targeted mRNAs, of which biological functions are highly interdependent, combination therapy for multi-drug resistance cancer cells, which was studied as a specific application of our two-in-one RNAi delivery system, demonstrates the efficient synergistic effects for cancer therapy. Therefore, this RNA nanoparticles approach has an efficient tool for a simultaneous co-delivery of RNAi molecules in the RNAi-based biomedical applications, and our current studies present an efficient strategy to overcome multi-drug resistance caused by malfunction of genes in chemotherapy. PMID:27562435

Quantitative thermodynamic predication of interactions between nucleic acid and non-nucleic acid species using Microsoft excel.

PubMed

Zou, Jiaqi; Li, Na

2013-09-01

Proper design of nucleic acid sequences is crucial for many applications. We have previously established a thermodynamics-based quantitative model to help design aptamer-based nucleic acid probes by predicting equilibrium concentrations of all interacting species. To facilitate customization of this thermodynamic model for different applications, here we present a generic and easy-to-use platform to implement the algorithm of the model with Microsoft(®) Excel formulas and VBA (Visual Basic for Applications) macros. Two Excel spreadsheets have been developed: one for the applications involving only nucleic acid species, the other for the applications involving both nucleic acid and non-nucleic acid species. The spreadsheets take the nucleic acid sequences and the initial concentrations of all species as input, guide the user to retrieve the necessary thermodynamic constants, and finally calculate equilibrium concentrations for all species in various bound and unbound conformations. The validity of both spreadsheets has been verified by comparing the modeling results with the experimental results on nucleic acid sequences reported in the literature. This Excel-based platform described here will allow biomedical researchers to rationalize the sequence design of nucleic acid probes using the thermodynamics-based modeling even without relevant theoretical and computational skills. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

eClims: An Extensible and Dynamic Integration Framework for Biomedical Information Systems.

PubMed

Savonnet, Marinette; Leclercq, Eric; Naubourg, Pierre

2016-11-01

Biomedical information systems (BIS) require consideration of three types of variability: data variability induced by new high throughput technologies, schema or model variability induced by large scale studies or new fields of research, and knowledge variability resulting from new discoveries. Beyond data heterogeneity, managing variabilities in the context of BIS requires extensible and dynamic integration process. In this paper, we focus on data and schema variabilities and we propose an integration framework based on ontologies, master data, and semantic annotations. The framework addresses issues related to: 1) collaborative work through a dynamic integration process; 2) variability among studies using an annotation mechanism; and 3) quality control over data and semantic annotations. Our approach relies on two levels of knowledge: BIS-related knowledge is modeled using an application ontology coupled with UML models that allow controlling data completeness and consistency, and domain knowledge is described by a domain ontology, which ensures data coherence. A system build with the eClims framework has been implemented and evaluated in the context of a proteomic platform.

Gold Nanocages for Biomedical Applications**

PubMed Central

Skrabalak, Sara E.; Chen, Jingyi; Au, Leslie; Lu, Xianmao; Li, Xingde; Xia, Younan

2008-01-01

Nanostructured materials provide a promising platform for early cancer detection and treatment. Here we highlight recent advances in the synthesis and use of Au nanocages for such biomedical applications. Gold nanocages represent a novel class of nanostructures, which can be prepared via a remarkably simple route based on the galvanic replacement reaction between Ag nanocubes and HAuCl4. The Au nanocages have a tunable surface plasmon resonance peak that extends into the near-infrared, where the optical attenuation caused by blood and soft tissue is essentially negligible. They are also biocompatible and present a well-established surface for easy functionalization. We have tailored the scattering and absorption cross-sections of Au nanocages for use in optical coherence tomography and photothermal treatment, respectively. Our preliminary studies show greatly improved spectroscopic image contrast for tissue phantoms containing Au nanocages. Our most recent results also demonstrate the photothermal destruction of breast cancer cells in vitro by using immuno-targeted Au nanocages as an effective photo-thermal transducer. These experiments suggest that Au nanocages may be a new class of nanometer-sized agents for cancer diagnosis and therapy. PMID:18648528

Nanorobot Hardware Architecture for Medical Defense.

PubMed

Cavalcanti, Adriano; Shirinzadeh, Bijan; Zhang, Mingjun; Kretly, Luiz C

2008-05-06

This work presents a new approach with details on the integrated platform and hardware architecture for nanorobots application in epidemic control, which should enable real time in vivo prognosis of biohazard infection. The recent developments in the field of nanoelectronics, with transducers progressively shrinking down to smaller sizes through nanotechnology and carbon nanotubes, are expected to result in innovative biomedical instrumentation possibilities, with new therapies and efficient diagnosis methodologies. The use of integrated systems, smart biosensors, and programmable nanodevices are advancing nanoelectronics, enabling the progressive research and development of molecular machines. It should provide high precision pervasive biomedical monitoring with real time data transmission. The use of nanobioelectronics as embedded systems is the natural pathway towards manufacturing methodology to achieve nanorobot applications out of laboratories sooner as possible. To demonstrate the practical application of medical nanorobotics, a 3D simulation based on clinical data addresses how to integrate communication with nanorobots using RFID, mobile phones, and satellites, applied to long distance ubiquitous surveillance and health monitoring for troops in conflict zones. Therefore, the current model can also be used to prevent and save a population against the case of some targeted epidemic disease.

Single-cell trapping and selective treatment via co-flow within a microfluidic platform.

PubMed

Benavente-Babace, A; Gallego-Pérez, D; Hansford, D J; Arana, S; Pérez-Lorenzo, E; Mujika, M

2014-11-15

Lab on a chip (LOC) systems provide interesting and low-cost solutions for key studies and applications in the biomedical field. Along with microfluidics, these microdevices make single-cell manipulation possible with high spatial and temporal resolution. In this work we have designed, fabricated and characterized a versatile and inexpensive microfluidic platform for on-chip selective single-cell trapping and treatment using laminar co-flow. The combination of co-existing laminar flow manipulation and hydrodynamic single-cell trapping for selective treatment offers a cost-effective solution for studying the effect of novel drugs on single-cells. The operation of the whole system is experimentally simple, highly adaptable and requires no specific equipment. As a proof of concept, a cytotoxicity study of ethanol in isolated hepatocytes is presented. The developed microfluidic platform controlled by means of co-flow is an attractive and multipurpose solution for the study of new substances of high interest in cell biology research. In addition, this platform will pave the way for the study of cell behavior under dynamic and controllable fluidic conditions providing information at the individual cell level. Thus, this analysis device could also hold a great potential to easily use the trapped cells as sensing elements expanding its functionalities as a cell-based biosensor with single-cell resolution. Copyright © 2014 Elsevier B.V. All rights reserved.

Biomedical research platforms and their influence on article submissions and journal rankings: An update.

PubMed Central

Lippi, Giuseppe; Favaloro, Emmanuel J; Simundic, Ana-Maria

2012-01-01

After being indexed in 2006 in EMBASE/Excerpta Medica and Scopus, and later in Science Citation Index Expanded and Journal Citation Reports/Science Edition citation databases, Biochemia Medica launched a new web page and online manuscript submission system in 2010, and celebrated its first Impact Factor in the same year. Now, starting from the end of the 2011, the journal will also be indexed in PubMed/Medline, and this will contribute to increase the journal’s exposure and accessibility worldwide. This is an important breakthrough, which is expected to further increase the popularity of the journal, as well as the submission rate and citations. Although several tools are currently available as Web resources to retrieve scientific articles, whose functioning and basic criteria are thought to be rather similar, the functionality, coverage, notoriety and prominence may differ widely. The recent indexing of Biochemia Medica in PubMed/Medline has thereby given us the opportunity to provide a timely update on biomedical research platforms, their relationship with article submissions and journal rankings. PMID:22384515

Getting to zero the biomedical way in Africa: outcomes of deliberation at the 2013 Biomedical HIV Prevention Forum in Abuja, Nigeria

PubMed Central

2014-01-01

Background Over the last few decades, biomedical HIV prevention research had engaged multiple African stakeholders. There have however been few platforms to enable regional stakeholders to engage with one another. In partnership with the World AIDS Campaign International, the Institute of Public Health of Obafemi Awolowo University, and the National Agency for the Control of AIDS in Nigeria, the New HIV Vaccine and Microbicide Advocacy Society hosted a forum on biomedical HIV prevention research in Africa. Stakeholders’ present explored evidences related to biomedical HIV prevention research and development in Africa, and made recommendations to inform policy, guidelines and future research agenda. Discussion The BHPF hosted 342 participants. Topics discussed included the use of antiretrovirals for HIV prevention, considerations for biomedical HIV prevention among key populations; HIV vaccine development; HIV cure; community and civil society engagement; and ethical considerations in implementation of biomedical HIV prevention research. Participants identified challenges for implementation of proven efficacious interventions and discovery of other new prevention options for Africa. Concerns raised included limited funding by African governments, lack of cohesive advocacy and policy agenda for biomedical HIV prevention research and development by Africa, varied ethical practices, and limited support to communities’ capacity to actively engaged with clinical trial conducts. Participants recommended that the African Government implement the Abuja +12 declaration; the civil society build stronger partnerships with diverse stakeholders, and develop a coherent advocacy agenda that also enhances community research literacy; and researchers and sponsors of trials on the African continent establish a process for determining appropriate standards for trial conduct on the continent. Conclusion By highlighting key considerations for biomedical HIV prevention research and development in Africa, the forum has helped identify key advocacy issues that Civil Society can expend efforts on so as to strengthen support for future biomedical HIV prevention research on the continent. PMID:26636825

Getting to zero the biomedical way in Africa: outcomes of deliberation at the 2013 Biomedical HIV Prevention Forum in Abuja, Nigeria.

PubMed

Folayan, Morenike Oluwatoyin; Gottemoeller, Megan; Mburu, Rosemary; Brown, Brandon

2014-01-01

Over the last few decades, biomedical HIV prevention research had engaged multiple African stakeholders. There have however been few platforms to enable regional stakeholders to engage with one another. In partnership with the World AIDS Campaign International, the Institute of Public Health of Obafemi Awolowo University, and the National Agency for the Control of AIDS in Nigeria, the New HIV Vaccine and Microbicide Advocacy Society hosted a forum on biomedical HIV prevention research in Africa. Stakeholders' present explored evidences related to biomedical HIV prevention research and development in Africa, and made recommendations to inform policy, guidelines and future research agenda. The BHPF hosted 342 participants. Topics discussed included the use of antiretrovirals for HIV prevention, considerations for biomedical HIV prevention among key populations; HIV vaccine development; HIV cure; community and civil society engagement; and ethical considerations in implementation of biomedical HIV prevention research. Participants identified challenges for implementation of proven efficacious interventions and discovery of other new prevention options for Africa. Concerns raised included limited funding by African governments, lack of cohesive advocacy and policy agenda for biomedical HIV prevention research and development by Africa, varied ethical practices, and limited support to communities' capacity to actively engaged with clinical trial conducts. Participants recommended that the African Government implement the Abuja +12 declaration; the civil society build stronger partnerships with diverse stakeholders, and develop a coherent advocacy agenda that also enhances community research literacy; and researchers and sponsors of trials on the African continent establish a process for determining appropriate standards for trial conduct on the continent. By highlighting key considerations for biomedical HIV prevention research and development in Africa, the forum has helped identify key advocacy issues that Civil Society can expend efforts on so as to strengthen support for future biomedical HIV prevention research on the continent.

The Corn Smut ('Huitlacoche') as a New Platform for Oral Vaccines.

PubMed

Juárez-Montiel, Margarita; Romero-Maldonado, Andrea; Monreal-Escalante, Elizabeth; Becerra-Flora, Alicia; Korban, Schuyler S; Rosales-Mendoza, Sergio; Jiménez-Bremont, Juan Francisco

2015-01-01

The development of new alternative platforms for subunit vaccine production is a priority in the biomedical field. In this study, Ustilago maydis, the causal agent of common corn smut or 'huitlacoche'has been genetically engineered to assess expression and immunogenicity of the B subunit of the cholera toxin (CTB), a relevant immunomodulatory agent in vaccinology. An oligomeric CTB recombinant protein was expressed in corn smut galls at levels of up to 1.3 mg g-1 dry weight (0.8% of the total soluble protein). Mice orally immunized with 'huitlacoche'-derived CTB showed significant humoral responses that were well-correlated with protection against challenge with the cholera toxin (CT). These findings demonstrate the feasibility of using edible corn smut as a safe, effective, and low-cost platform for production and delivery of a subunit oral vaccine. The implications of this platform in the area of molecular pharming are discussed.

The Corn Smut (‘Huitlacoche’) as a New Platform for Oral Vaccines

PubMed Central

Juárez-Montiel, Margarita; Romero-Maldonado, Andrea; Monreal-Escalante, Elizabeth; Becerra-Flora, Alicia; Korban, Schuyler S.; Rosales-Mendoza, Sergio; Jiménez-Bremont, Juan Francisco

2015-01-01

The development of new alternative platforms for subunit vaccine production is a priority in the biomedical field. In this study, Ustilago maydis, the causal agent of common corn smut or ‘huitlacoche’has been genetically engineered to assess expression and immunogenicity of the B subunit of the cholera toxin (CTB), a relevant immunomodulatory agent in vaccinology. An oligomeric CTB recombinant protein was expressed in corn smut galls at levels of up to 1.3 mg g-1 dry weight (0.8% of the total soluble protein). Mice orally immunized with ‘huitlacoche’-derived CTB showed significant humoral responses that were well-correlated with protection against challenge with the cholera toxin (CT). These findings demonstrate the feasibility of using edible corn smut as a safe, effective, and low-cost platform for production and delivery of a subunit oral vaccine. The implications of this platform in the area of molecular pharming are discussed. PMID:26207365

Functional protein-based nanomaterial produced in microorganisms recognized as safe: A new platform for biotechnology.

PubMed

Cano-Garrido, Olivia; Sánchez-Chardi, Alejandro; Parés, Sílvia; Giró, Irene; Tatkiewicz, Witold I; Ferrer-Miralles, Neus; Ratera, Imma; Natalello, Antonino; Cubarsi, Rafael; Veciana, Jaume; Bach, Àlex; Villaverde, Antonio; Arís, Anna; Garcia-Fruitós, Elena

2016-10-01

Inclusion bodies (IBs) are protein-based nanoparticles formed in Escherichia coli through stereospecific aggregation processes during the overexpression of recombinant proteins. In the last years, it has been shown that IBs can be used as nanostructured biomaterials to stimulate mammalian cell attachment, proliferation, and differentiation. In addition, these nanoparticles have also been explored as natural delivery systems for protein replacement therapies. Although the production of these protein-based nanomaterials in E. coli is economically viable, important safety concerns related to the presence of endotoxins in the products derived from this microorganism need to be addressed. Lactic acid bacteria (LAB) are a group of food-grade microorganisms that have been classified as safe by biologically regulatory agencies. In this context, we have demonstrated herein, for the first time, the production of fully functional, IB-like protein nanoparticles in LAB. These nanoparticles have been fully characterized using a wide range of techniques, including field emission scanning electron microscopy (FESEM), transmission electron microscopy (TEM), dynamic light scattering (DLS), Fourier transform infrared (FTIR) spectroscopy, zymography, cytometry, confocal microscopy, and wettability and cell coverage measurements. Our results allow us to conclude that these materials share the main physico-chemical characteristics with IBs from E. coli and moreover are devoid of any harmful endotoxin contaminant. These findings reveal a new platform for the production of protein-based safe products with high pharmaceutical interest. The development of both natural and synthetic biomaterials for biomedical applications is a field in constant development. In this context, E. coli is a bacteria that has been widely studied for its ability to naturally produce functional biomaterials with broad biomedical uses. Despite being effective, products derived from this species contain membrane residues able to trigger a non-desired immunogenic responses. Accordingly, exploring alternative bacteria able to synthesize such biomaterials in a safe molecular environment is becoming a challenge. Thus, the present study describes a new type of functional protein-based nanomaterial free of toxic contaminants with a wide range of applications in both human and veterinary medicine. Copyright © 2016 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.

Nanogold as NEMS platform: past, present, and future

NASA Astrophysics Data System (ADS)

Cornejo-Monroy, Delfino; Acosta-Torres, Laura S.; Castaño, Victor M.

2012-06-01

Gold has been a biomedical material since ancient times. We shall review the historical uses of gold, in different forms as well as the properties of this metal, which make it very attractive for MEMS and NEMS applications. In particular, we will discuss the synthesis and physic-chemical characteristics of nano particles of gold, emphasizing the role of surface modification, which enables the nano gold to act as a true nano reactor or a nano platform to develop various functions at the nanoscale. Finally, we will describe the use of nano gold for drug targeting and disease detection.

Recent Advances in Extrusion-Based 3D Printing for Biomedical Applications.

PubMed

Placone, Jesse K; Engler, Adam J

2018-04-01

Additive manufacturing, or 3D printing, has become significantly more commonplace in tissue engineering over the past decade, as a variety of new printing materials have been developed. In extrusion-based printing, materials are used for applications that range from cell free printing to cell-laden bioinks that mimic natural tissues. Beyond single tissue applications, multi-material extrusion based printing has recently been developed to manufacture scaffolds that mimic tissue interfaces. Despite these advances, some material limitations prevent wider adoption of the extrusion-based 3D printers currently available. This progress report provides an overview of this commonly used printing strategy, as well as insight into how this technique can be improved. As such, it is hoped that the prospective report guides the inclusion of more rigorous material characterization prior to printing, thereby facilitating cross-platform utilization and reproducibility. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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

PubMed

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

2016-01-01

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

Intelligent biomedical clothing for personal health and disease management: state of the art and future vision.

PubMed

Lymberis, Andreas; Olsson, Silas

2003-01-01

Telemedicine has been introduced to overcome distance in order to get prompt access to medical knowledge and appropriate health care. More recently, work in telemedicine has aimed at developing solutions to support the management of chronic diseases such as diabetes, and lung and heart diseases, as well as to provide support for home care services. Telemedicine is also entering the fields of health promotion/prevention disease, life style management, and well-being. The evolution and broadening of telemedicine gives birth to a nomenclature that includes "e-health," "telehealth," and "telecare." The latest developments in microsystems and nanotechnologies as well as in information processing and communication technologies allow miniaturization and non-invasive smart monitoring of physiological and physical data. Ongoing cutting-edge multidisciplinary research in textile fibers, biomedical sensors, and wireless and mobile telecommunications integrated with telemedicine, aims at developing intelligent biomedical clothing (IBC) that could pave the way to support personalized management of health and diseases at the point of need and at any time. In this study, we aim to describe the current status of multidisciplinary research and development of IBC, based on bibliographic research and reports from seminars, workshops, conferences, and working groups. A further aim is to inform the developers, the decision makers, and users in the health and healthcare sector regarding future solutions to support personalized health care and disease management. Both the textile sector and healthcare sector are looking with great interest at the innovative products and applications that could result from the integration of microsystems, nanotechnologies, biomedical sensors, textiles, and mobile telecommunications. For health monitoring, disease prevention and management, rehabilitation, and sport medicine, IBC may offer, in the mid-term future, a unique, wearable non-obtrusive telemedicine platform for individualized services that is readily accessible and of good quality.

Legacy of Biomedical Research During the Space Shuttle Program

NASA Technical Reports Server (NTRS)

Hayes, Judith C.

2011-01-01

The Space Shuttle Program provided many opportunities to study the role of spaceflight on human life for over 30 years and represented the longest and largest US human spaceflight program. Outcomes of the research were understanding the effect of spaceflight on human physiology and performance, countermeasures, operational protocols, and hardware. The Shuttle flights were relatively short, < 16 days and routinely had 4 to 6 crewmembers for a total of 135 flights. Biomedical research was conducted on the Space Shuttle using various vehicle resources. Specially constructed pressurized laboratories called Spacelab and SPACEHAB housed many laboratory instruments to accomplish experiments in the Shuttle s large payload bay. In addition to these laboratory flights, nearly every mission had dedicated human life science research experiments conducted in the Shuttle middeck. Most Shuttle astronauts participated in some life sciences research experiments either as test subjects or test operators. While middeck experiments resulted in a low sample per mission compared to many Earth-based studies, this participation allowed investigators to have repetition of tests over the years on successive Shuttle flights. In addition, as a prelude to the International Space Station (ISS), NASA used the Space Shuttle as a platform for assessing future ISS hardware systems and procedures. The purpose of this panel is to provide an understanding of science integration activities required to implement Shuttle research, review biomedical research, characterize countermeasures developed for Shuttle and ISS as well as discuss lessons learned that may support commercial crew endeavors. Panel topics include research integration, cardiovascular physiology, neurosciences, skeletal muscle, and exercise physiology. Learning Objective: The panel provides an overview from the Space Shuttle Program regarding research integration, scientific results, lessons learned from biomedical research and countermeasure development.

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

Adhikari, Ananta R., E-mail: aa8381@gmail.com; Rusakova, Irene; Chu, Wei-Kan

Polymer-matrix nanocomposites based on Poly(lactic-co-glycolic) acid (PLGA) and Graphene platelets (GNPs) were studied. GNPs, nanomaterials with a 2D flat surface, were chosen with or without chemical modification in PLGA/GNP nanocomposites and their microstructure, thermal property, and their compatibility as scaffolds for cell growth were investigated. PLGA/GNP nanocomposites (0, 1, and 5 wt. % of GNPs) were prepared using a solution based technique. Transmission electron microscopy, X-ray diffraction, Differential scanning calorimeter, and Thermogravimetric analyzer were used to analyze morphology and thermal properties. This work demonstrated the role of GNPs flat surface to provide a favorable platform resulting in an enhanced PLGA crystallization. Functionalizedmore » GNPs suppress both the thermal stability and the crystallization of PLGA. Finally, to determine the potential usefulness of these scaffolds for biomedical applications, mammalian cells were cultured on various PLGA/GNP nanocomposites (0, 1, and 5 wt. % GNPs). 1 wt. % PLGA/GNP nanocomposites showed better biocompatibility for cell growth with/without graphenes functionalization compared to pure PLGA and 5 wt. % PLGA/GNP. The function of GNPs in PLGA/GNPs (1 wt. %) composites is to provide a stage for PLGA crystallization where cell growth is favored. These results provide strong evidence for a new class of materials that could be important for biomedical applications.« less

Partially reduced graphene oxide based FRET on fiber-optic interferometer for biochemical detection

NASA Astrophysics Data System (ADS)

Yao, B. C.; Wu, Y.; Yu, C. B.; He, J. R.; Rao, Y. J.; Gong, Y.; Fu, F.; Chen, Y. F.; Li, Y. R.

2016-03-01

Fluorescent resonance energy transfer (FRET) with naturally exceptional selectivity is a powerful technique and widely used in chemical and biomedical analysis. However, it is still challenging for conventional FRET to perform as a high sensitivity compact sensor. Here we propose a novel ‘FRET on Fiber’ concept, in which a partially reduced graphene oxide (prGO) film is deposited on a fiber-optic modal interferometer, acting as both the fluorescent quencher for the FRET and the sensitive cladding for optical phase measurement due to refractive index changes in biochemical detection. The target analytes induced fluorescence recovery with good selectivity and optical phase shift with high sensitivity are measured simultaneously. The functionalized prGO film coated on the fiber-optic interferometer shows high sensitivities for the detections of metal ion, dopamine and single-stranded DNA (ssDNA), with detection limits of 1.2 nM, 1.3 μM and 1 pM, respectively. Such a prGO based ‘FRET on fiber’ configuration, bridging the FRET and the fiber-optic sensing technology, may serve as a platform for the realization of series of integrated ‘FRET on Fiber’ sensors for on-line environmental, chemical, and biomedical detection, with excellent compactness, high sensitivity, good selectivity and fast response

Partially reduced graphene oxide based FRET on fiber-optic interferometer for biochemical detection

PubMed Central

Yao, B. C.; Wu, Y.; Yu, C. B.; He, J. R.; Rao, Y. J.; Gong, Y.; Fu, F.; Chen, Y. F.; Li, Y. R.

2016-01-01

Fluorescent resonance energy transfer (FRET) with naturally exceptional selectivity is a powerful technique and widely used in chemical and biomedical analysis. However, it is still challenging for conventional FRET to perform as a high sensitivity compact sensor. Here we propose a novel ‘FRET on Fiber’ concept, in which a partially reduced graphene oxide (prGO) film is deposited on a fiber-optic modal interferometer, acting as both the fluorescent quencher for the FRET and the sensitive cladding for optical phase measurement due to refractive index changes in biochemical detection. The target analytes induced fluorescence recovery with good selectivity and optical phase shift with high sensitivity are measured simultaneously. The functionalized prGO film coated on the fiber-optic interferometer shows high sensitivities for the detections of metal ion, dopamine and single-stranded DNA (ssDNA), with detection limits of 1.2 nM, 1.3 μM and 1 pM, respectively. Such a prGO based ‘FRET on fiber’ configuration, bridging the FRET and the fiber-optic sensing technology, may serve as a platform for the realization of series of integrated ‘FRET on Fiber’ sensors for on-line environmental, chemical, and biomedical detection, with excellent compactness, high sensitivity, good selectivity and fast response PMID:27010752

Smartphones for cell and biomolecular detection.

PubMed

Liu, Xiyuan; Lin, Tung-Yi; Lillehoj, Peter B

2014-11-01

Recent advances in biomedical science and technology have played a significant role in the development of new sensors and assays for cell and biomolecular detection. Generally, these efforts are aimed at reducing the complexity and costs associated with diagnostic testing so that it can be performed outside of a laboratory or hospital setting, requiring minimal equipment and user involvement. In particular, point-of-care (POC) testing offers immense potential for many important applications including medical diagnosis, environmental monitoring, food safety, and biosecurity. When coupled with smartphones, POC systems can offer portability, ease of use and enhanced functionality while maintaining performance. This review article focuses on recent advancements and developments in smartphone-based POC systems within the last 6 years with an emphasis on cell and biomolecular detection. These devices typically comprise multiple components, such as detectors, sample processors, disposable chips, batteries, and software, which are integrated with a commercial smartphone. One of the most important aspects of developing these systems is the integration of these components onto a compact and lightweight platform that requires minimal power. Researchers have demonstrated several promising approaches employing various detection schemes and device configurations, and it is expected that further developments in biosensors, battery technology and miniaturized electronics will enable smartphone-based POC technologies to become more mainstream tools in the scientific and biomedical communities.

The Application of Biomedical Engineering Techniques to the Diagnosis and Management of Tropical Diseases: A Review

PubMed Central

Ibrahim, Fatimah; Thio, Tzer Hwai Gilbert; Faisal, Tarig; Neuman, Michael

2015-01-01

This paper reviews a number of biomedical engineering approaches to help aid in the detection and treatment of tropical diseases such as dengue, malaria, cholera, schistosomiasis, lymphatic filariasis, ebola, leprosy, leishmaniasis, and American trypanosomiasis (Chagas). Many different forms of non-invasive approaches such as ultrasound, echocardiography and electrocardiography, bioelectrical impedance, optical detection, simplified and rapid serological tests such as lab-on-chip and micro-/nano-fluidic platforms and medical support systems such as artificial intelligence clinical support systems are discussed. The paper also reviewed the novel clinical diagnosis and management systems using artificial intelligence and bioelectrical impedance techniques for dengue clinical applications. PMID:25806872

InSilico DB genomic datasets hub: an efficient starting point for analyzing genome-wide studies in GenePattern, Integrative Genomics Viewer, and R/Bioconductor.

PubMed

Coletta, Alain; Molter, Colin; Duqué, Robin; Steenhoff, David; Taminau, Jonatan; de Schaetzen, Virginie; Meganck, Stijn; Lazar, Cosmin; Venet, David; Detours, Vincent; Nowé, Ann; Bersini, Hugues; Weiss Solís, David Y

2012-11-18

Genomics datasets are increasingly useful for gaining biomedical insights, with adoption in the clinic underway. However, multiple hurdles related to data management stand in the way of their efficient large-scale utilization. The solution proposed is a web-based data storage hub. Having clear focus, flexibility and adaptability, InSilico DB seamlessly connects genomics dataset repositories to state-of-the-art and free GUI and command-line data analysis tools. The InSilico DB platform is a powerful collaborative environment, with advanced capabilities for biocuration, dataset sharing, and dataset subsetting and combination. InSilico DB is available from https://insilicodb.org.

Surface Plasmon Resonance: A Versatile Technique for Biosensor Applications

PubMed Central

Nguyen, Hoang Hiep; Park, Jeho; Kang, Sebyung; Kim, Moonil

2015-01-01

Surface plasmon resonance (SPR) is a label-free detection method which has emerged during the last two decades as a suitable and reliable platform in clinical analysis for biomolecular interactions. The technique makes it possible to measure interactions in real-time with high sensitivity and without the need of labels. This review article discusses a wide range of applications in optical-based sensors using either surface plasmon resonance (SPR) or surface plasmon resonance imaging (SPRI). Here we summarize the principles, provide examples, and illustrate the utility of SPR and SPRI through example applications from the biomedical, proteomics, genomics and bioengineering fields. In addition, SPR signal amplification strategies and surface functionalization are covered in the review. PMID:25951336

Beyond editing: repurposing CRISPR-Cas9 for precision genome regulation and interrogation.

PubMed

Dominguez, Antonia A; Lim, Wendell A; Qi, Lei S

2016-01-01

The bacterial CRISPR-Cas9 system has emerged as a multifunctional platform for sequence-specific regulation of gene expression. This Review describes the development of technologies based on nuclease-deactivated Cas9, termed dCas9, for RNA-guided genomic transcription regulation, both by repression through CRISPR interference (CRISPRi) and by activation through CRISPR activation (CRISPRa). We highlight different uses in diverse organisms, including bacterial and eukaryotic cells, and summarize current applications of harnessing CRISPR-dCas9 for multiplexed, inducible gene regulation, genome-wide screens and cell fate engineering. We also provide a perspective on future developments of the technology and its applications in biomedical research and clinical studies.

Beyond editing: repurposing CRISPR–Cas9 for precision genome regulation and interrogation

PubMed Central

Dominguez, Antonia A.; Lim, Wendell A.; Qi, Lei S.

2016-01-01

The bacterial CRISPR–Cas9 system has emerged as a multifunctional platform for sequence-specific regulation of gene expression. This Review describes the development of technologies based on nuclease-deactivated Cas9, termed dCas9, for RNA-guided genomic transcription regulation, both by repression through CRISPR interference (CRISPRi) and by activation through CRISPR activation (CRISPRa). We highlight different uses in diverse organisms, including bacterial and eukaryotic cells, and summarize current applications of harnessing CRISPR–dCas9 for multiplexed, inducible gene regulation, genome-wide screens and cell fate engineering. We also provide a perspective on future developments of the technology and its applications in biomedical research and clinical studies. PMID:26670017

Gathering and Exploring Scientific Knowledge in Pharmacovigilance

PubMed Central

Lopes, Pedro; Nunes, Tiago; Campos, David; Furlong, Laura Ines; Bauer-Mehren, Anna; Sanz, Ferran; Carrascosa, Maria Carmen; Mestres, Jordi; Kors, Jan; Singh, Bharat; van Mulligen, Erik; Van der Lei, Johan; Diallo, Gayo; Avillach, Paul; Ahlberg, Ernst; Boyer, Scott; Diaz, Carlos; Oliveira, José Luís

2013-01-01

Pharmacovigilance plays a key role in the healthcare domain through the assessment, monitoring and discovery of interactions amongst drugs and their effects in the human organism. However, technological advances in this field have been slowing down over the last decade due to miscellaneous legal, ethical and methodological constraints. Pharmaceutical companies started to realize that collaborative and integrative approaches boost current drug research and development processes. Hence, new strategies are required to connect researchers, datasets, biomedical knowledge and analysis algorithms, allowing them to fully exploit the true value behind state-of-the-art pharmacovigilance efforts. This manuscript introduces a new platform directed towards pharmacovigilance knowledge providers. This system, based on a service-oriented architecture, adopts a plugin-based approach to solve fundamental pharmacovigilance software challenges. With the wealth of collected clinical and pharmaceutical data, it is now possible to connect knowledge providers’ analysis and exploration algorithms with real data. As a result, new strategies allow a faster identification of high-risk interactions between marketed drugs and adverse events, and enable the automated uncovering of scientific evidence behind them. With this architecture, the pharmacovigilance field has a new platform to coordinate large-scale drug evaluation efforts in a unique ecosystem, publicly available at http://bioinformatics.ua.pt/euadr/. PMID:24349421

A simple encoding method for Sigma-Delta ADC based biopotential acquisition systems.

PubMed

Guerrero, Federico N; Spinelli, Enrique M

2017-10-01

Sigma Delta analogue-to-digital converters allow acquiring the full dynamic range of biomedical signals at the electrodes, resulting in less complex hardware and increased measurement robustness. However, the increased data size per sample (typically 24 bits) demands the transmission of extremely large volumes of data across the isolation barrier, thus increasing power consumption on the patient side. This problem is accentuated when a large number of channels is used as in current 128-256 electrodes biopotential acquisition systems, that usually opt for an optic fibre link to the computer. An analogous problem occurs for simpler low-power acquisition platforms that transmit data through a wireless link to a computing platform. In this paper, a low-complexity encoding method is presented to decrease sample data size without losses, while preserving the full DC-coupled signal. The method achieved a 2.3 average compression ratio evaluated over an ECG and EMG signal bank acquired with equipment based on Sigma-Delta converters. It demands a very low processing load: a C language implementation is presented that resulted in an 110 clock cycles average execution on an 8-bit microcontroller.

Support for Taverna workflows in the VPH-Share cloud platform.

PubMed

Kasztelnik, Marek; Coto, Ernesto; Bubak, Marian; Malawski, Maciej; Nowakowski, Piotr; Arenas, Juan; Saglimbeni, Alfredo; Testi, Debora; Frangi, Alejandro F

2017-07-01

To address the increasing need for collaborative endeavours within the Virtual Physiological Human (VPH) community, the VPH-Share collaborative cloud platform allows researchers to expose and share sequences of complex biomedical processing tasks in the form of computational workflows. The Taverna Workflow System is a very popular tool for orchestrating complex biomedical & bioinformatics processing tasks in the VPH community. This paper describes the VPH-Share components that support the building and execution of Taverna workflows, and explains how they interact with other VPH-Share components to improve the capabilities of the VPH-Share platform. Taverna workflow support is delivered by the Atmosphere cloud management platform and the VPH-Share Taverna plugin. These components are explained in detail, along with the two main procedures that were developed to enable this seamless integration: workflow composition and execution. 1) Seamless integration of VPH-Share with other components and systems. 2) Extended range of different tools for workflows. 3) Successful integration of scientific workflows from other VPH projects. 4) Execution speed improvement for medical applications. The presented workflow integration provides VPH-Share users with a wide range of different possibilities to compose and execute workflows, such as desktop or online composition, online batch execution, multithreading, remote execution, etc. The specific advantages of each supported tool are presented, as are the roles of Atmosphere and the VPH-Share plugin within the VPH-Share project. The combination of the VPH-Share plugin and Atmosphere engenders the VPH-Share infrastructure with far more flexible, powerful and usable capabilities for the VPH-Share community. As both components can continue to evolve and improve independently, we acknowledge that further improvements are still to be developed and will be described. Copyright © 2017 Elsevier B.V. All rights reserved.

A mass spectrometry proteomics data management platform.

PubMed

Sharma, Vagisha; Eng, Jimmy K; Maccoss, Michael J; Riffle, Michael

2012-09-01

Mass spectrometry-based proteomics is increasingly being used in biomedical research. These experiments typically generate a large volume of highly complex data, and the volume and complexity are only increasing with time. There exist many software pipelines for analyzing these data (each typically with its own file formats), and as technology improves, these file formats change and new formats are developed. Files produced from these myriad software programs may accumulate on hard disks or tape drives over time, with older files being rendered progressively more obsolete and unusable with each successive technical advancement and data format change. Although initiatives exist to standardize the file formats used in proteomics, they do not address the core failings of a file-based data management system: (1) files are typically poorly annotated experimentally, (2) files are "organically" distributed across laboratory file systems in an ad hoc manner, (3) files formats become obsolete, and (4) searching the data and comparing and contrasting results across separate experiments is very inefficient (if possible at all). Here we present a relational database architecture and accompanying web application dubbed Mass Spectrometry Data Platform that is designed to address the failings of the file-based mass spectrometry data management approach. The database is designed such that the output of disparate software pipelines may be imported into a core set of unified tables, with these core tables being extended to support data generated by specific pipelines. Because the data are unified, they may be queried, viewed, and compared across multiple experiments using a common web interface. Mass Spectrometry Data Platform is open source and freely available at http://code.google.com/p/msdapl/.

Immunochromatographic diagnostic test analysis using Google Glass.

PubMed

Feng, Steve; Caire, Romain; Cortazar, Bingen; Turan, Mehmet; Wong, Andrew; Ozcan, Aydogan

2014-03-25

We demonstrate a Google Glass-based rapid diagnostic test (RDT) reader platform capable of qualitative and quantitative measurements of various lateral flow immunochromatographic assays and similar biomedical diagnostics tests. Using a custom-written Glass application and without any external hardware attachments, one or more RDTs labeled with Quick Response (QR) code identifiers are simultaneously imaged using the built-in camera of the Google Glass that is based on a hands-free and voice-controlled interface and digitally transmitted to a server for digital processing. The acquired JPEG images are automatically processed to locate all the RDTs and, for each RDT, to produce a quantitative diagnostic result, which is returned to the Google Glass (i.e., the user) and also stored on a central server along with the RDT image, QR code, and other related information (e.g., demographic data). The same server also provides a dynamic spatiotemporal map and real-time statistics for uploaded RDT results accessible through Internet browsers. We tested this Google Glass-based diagnostic platform using qualitative (i.e., yes/no) human immunodeficiency virus (HIV) and quantitative prostate-specific antigen (PSA) tests. For the quantitative RDTs, we measured activated tests at various concentrations ranging from 0 to 200 ng/mL for free and total PSA. This wearable RDT reader platform running on Google Glass combines a hands-free sensing and image capture interface with powerful servers running our custom image processing codes, and it can be quite useful for real-time spatiotemporal tracking of various diseases and personal medical conditions, providing a valuable tool for epidemiology and mobile health.

Immunochromatographic Diagnostic Test Analysis Using Google Glass

PubMed Central

2014-01-01

We demonstrate a Google Glass-based rapid diagnostic test (RDT) reader platform capable of qualitative and quantitative measurements of various lateral flow immunochromatographic assays and similar biomedical diagnostics tests. Using a custom-written Glass application and without any external hardware attachments, one or more RDTs labeled with Quick Response (QR) code identifiers are simultaneously imaged using the built-in camera of the Google Glass that is based on a hands-free and voice-controlled interface and digitally transmitted to a server for digital processing. The acquired JPEG images are automatically processed to locate all the RDTs and, for each RDT, to produce a quantitative diagnostic result, which is returned to the Google Glass (i.e., the user) and also stored on a central server along with the RDT image, QR code, and other related information (e.g., demographic data). The same server also provides a dynamic spatiotemporal map and real-time statistics for uploaded RDT results accessible through Internet browsers. We tested this Google Glass-based diagnostic platform using qualitative (i.e., yes/no) human immunodeficiency virus (HIV) and quantitative prostate-specific antigen (PSA) tests. For the quantitative RDTs, we measured activated tests at various concentrations ranging from 0 to 200 ng/mL for free and total PSA. This wearable RDT reader platform running on Google Glass combines a hands-free sensing and image capture interface with powerful servers running our custom image processing codes, and it can be quite useful for real-time spatiotemporal tracking of various diseases and personal medical conditions, providing a valuable tool for epidemiology and mobile health. PMID:24571349

Architecture for biomedical multimedia information delivery on the World Wide Web

NASA Astrophysics Data System (ADS)

Long, L. Rodney; Goh, Gin-Hua; Neve, Leif; Thoma, George R.

1997-10-01

Research engineers at the National Library of Medicine are building a prototype system for the delivery of multimedia biomedical information on the World Wide Web. This paper discuses the architecture and design considerations for the system, which will be used initially to make images and text from the third National Health and Nutrition Examination Survey (NHANES) publicly available. We categorized our analysis as follows: (1) fundamental software tools: we analyzed trade-offs among use of conventional HTML/CGI, X Window Broadway, and Java; (2) image delivery: we examined the use of unconventional TCP transmission methods; (3) database manager and database design: we discuss the capabilities and planned use of the Informix object-relational database manager and the planned schema for the HNANES database; (4) storage requirements for our Sun server; (5) user interface considerations; (6) the compatibility of the system with other standard research and analysis tools; (7) image display: we discuss considerations for consistent image display for end users. Finally, we discuss the scalability of the system in terms of incorporating larger or more databases of similar data, and the extendibility of the system for supporting content-based retrieval of biomedical images. The system prototype is called the Web-based Medical Information Retrieval System. An early version was built as a Java applet and tested on Unix, PC, and Macintosh platforms. This prototype used the MiniSQL database manager to do text queries on a small database of records of participants in the second NHANES survey. The full records and associated x-ray images were retrievable and displayable on a standard Web browser. A second version has now been built, also a Java applet, using the MySQL database manager.

Lessons Learned from Development of De-identification System for Biomedical Research in a Korean Tertiary Hospital

PubMed Central

Shin, Soo-Yong; Lyu, Yongman; Shin, Yongdon; Choi, Hyo Joung; Park, Jihyun; Kim, Woo-Sung

2013-01-01

Objectives The Korean government has enacted two laws, namely, the Personal Information Protection Act and the Bioethics and Safety Act to prevent the unauthorized use of medical information. To protect patients' privacy by complying with governmental regulations and improve the convenience of research, Asan Medical Center has been developing a de-identification system for biomedical research. Methods We reviewed Korean regulations to define the scope of the de-identification methods and well-known previous biomedical research platforms to extract the functionalities of the systems. Based on these review results, we implemented necessary programs based on the Asan Medical Center Information System framework which was built using the Microsoft. NET Framework and C#. Results The developed de-identification system comprises three main components: a de-identification tool, a search tool, and a chart review tool. The de-identification tool can substitute a randomly assigned research ID for a hospital patient ID, remove the identifiers in the structured format, and mask them in the unstructured format, i.e., texts. This tool achieved 98.14% precision and 97.39% recall for 6,520 clinical notes. The search tool can find the number of patients which satisfies given search criteria. The chart review tool can provide de-identified patient's clinical data for review purposes. Conclusions We found that a clinical data warehouse was essential for successful implementation of the de-identification system, and this system should be tightly linked to an electronic Institutional Review Board system for easy operation of honest brokers. Additionally, we found that a secure cloud environment could be adopted to protect patients' privacy more thoroughly. PMID:23882415

Datasets2Tools, repository and search engine for bioinformatics datasets, tools and canned analyses

PubMed Central

Torre, Denis; Krawczuk, Patrycja; Jagodnik, Kathleen M.; Lachmann, Alexander; Wang, Zichen; Wang, Lily; Kuleshov, Maxim V.; Ma’ayan, Avi

2018-01-01

Biomedical data repositories such as the Gene Expression Omnibus (GEO) enable the search and discovery of relevant biomedical digital data objects. Similarly, resources such as OMICtools, index bioinformatics tools that can extract knowledge from these digital data objects. However, systematic access to pre-generated ‘canned’ analyses applied by bioinformatics tools to biomedical digital data objects is currently not available. Datasets2Tools is a repository indexing 31,473 canned bioinformatics analyses applied to 6,431 datasets. The Datasets2Tools repository also contains the indexing of 4,901 published bioinformatics software tools, and all the analyzed datasets. Datasets2Tools enables users to rapidly find datasets, tools, and canned analyses through an intuitive web interface, a Google Chrome extension, and an API. Furthermore, Datasets2Tools provides a platform for contributing canned analyses, datasets, and tools, as well as evaluating these digital objects according to their compliance with the findable, accessible, interoperable, and reusable (FAIR) principles. By incorporating community engagement, Datasets2Tools promotes sharing of digital resources to stimulate the extraction of knowledge from biomedical research data. Datasets2Tools is freely available from: http://amp.pharm.mssm.edu/datasets2tools. PMID:29485625

Datasets2Tools, repository and search engine for bioinformatics datasets, tools and canned analyses.

PubMed

Torre, Denis; Krawczuk, Patrycja; Jagodnik, Kathleen M; Lachmann, Alexander; Wang, Zichen; Wang, Lily; Kuleshov, Maxim V; Ma'ayan, Avi

2018-02-27

Biomedical data repositories such as the Gene Expression Omnibus (GEO) enable the search and discovery of relevant biomedical digital data objects. Similarly, resources such as OMICtools, index bioinformatics tools that can extract knowledge from these digital data objects. However, systematic access to pre-generated 'canned' analyses applied by bioinformatics tools to biomedical digital data objects is currently not available. Datasets2Tools is a repository indexing 31,473 canned bioinformatics analyses applied to 6,431 datasets. The Datasets2Tools repository also contains the indexing of 4,901 published bioinformatics software tools, and all the analyzed datasets. Datasets2Tools enables users to rapidly find datasets, tools, and canned analyses through an intuitive web interface, a Google Chrome extension, and an API. Furthermore, Datasets2Tools provides a platform for contributing canned analyses, datasets, and tools, as well as evaluating these digital objects according to their compliance with the findable, accessible, interoperable, and reusable (FAIR) principles. By incorporating community engagement, Datasets2Tools promotes sharing of digital resources to stimulate the extraction of knowledge from biomedical research data. Datasets2Tools is freely available from: http://amp.pharm.mssm.edu/datasets2tools.

CNN-based ranking for biomedical entity normalization.

PubMed

Li, Haodi; Chen, Qingcai; Tang, Buzhou; Wang, Xiaolong; Xu, Hua; Wang, Baohua; Huang, Dong

2017-10-03

Most state-of-the-art biomedical entity normalization systems, such as rule-based systems, merely rely on morphological information of entity mentions, but rarely consider their semantic information. In this paper, we introduce a novel convolutional neural network (CNN) architecture that regards biomedical entity normalization as a ranking problem and benefits from semantic information of biomedical entities. The CNN-based ranking method first generates candidates using handcrafted rules, and then ranks the candidates according to their semantic information modeled by CNN as well as their morphological information. Experiments on two benchmark datasets for biomedical entity normalization show that our proposed CNN-based ranking method outperforms traditional rule-based method with state-of-the-art performance. We propose a CNN architecture that regards biomedical entity normalization as a ranking problem. Comparison results show that semantic information is beneficial to biomedical entity normalization and can be well combined with morphological information in our CNN architecture for further improvement.

Digital microfluidics for automated hanging drop cell spheroid culture.

PubMed

Aijian, Andrew P; Garrell, Robin L

2015-06-01

Cell spheroids are multicellular aggregates, grown in vitro, that mimic the three-dimensional morphology of physiological tissues. Although there are numerous benefits to using spheroids in cell-based assays, the adoption of spheroids in routine biomedical research has been limited, in part, by the tedious workflow associated with spheroid formation and analysis. Here we describe a digital microfluidic platform that has been developed to automate liquid-handling protocols for the formation, maintenance, and analysis of multicellular spheroids in hanging drop culture. We show that droplets of liquid can be added to and extracted from through-holes, or "wells," and fabricated in the bottom plate of a digital microfluidic device, enabling the formation and assaying of hanging drops. Using this digital microfluidic platform, spheroids of mouse mesenchymal stem cells were formed and maintained in situ for 72 h, exhibiting good viability (>90%) and size uniformity (% coefficient of variation <10% intraexperiment, <20% interexperiment). A proof-of-principle drug screen was performed on human colorectal adenocarcinoma spheroids to demonstrate the ability to recapitulate physiologically relevant phenomena such as insulin-induced drug resistance. With automatable and flexible liquid handling, and a wide range of in situ sample preparation and analysis capabilities, the digital microfluidic platform provides a viable tool for automating cell spheroid culture and analysis. © 2014 Society for Laboratory Automation and Screening.

Getting the most from microfluidic platforms for biomedical applications (Conference Presentation)

NASA Astrophysics Data System (ADS)

Shen, Amy

2016-03-01

Microfluidics has emerged in recent years as a versatile method of manipulating fluids at small length-scales, and in particular, for generating and manipulating micron size droplets with controllable size and functionality. For example, many research groups developed microfluidics devices for cell encapsulation, and synthesizing functionalized polymer microspheres and inorganic nanoparticles with precise control over their shapes and sizes. In this talk, I will showcase 2 microfluidic platforms to highlight their versatility and potential biomedical applications. (1) Droplet microfluidic platforms (a) A droplet microfluidics method to fabricate alginate microspheres while simultaneously immobilizing anti-Mycobacterium tuberculosis complex IgY and anti-Escherichia coli IgG antibodies primarily on the porous alginate carriers for specific binding and binding affinity tests. The binding affinity of antibodies is directly measured by fluorescence intensity of stained target bacteria on the microspheres. We demonstrate that the functionalized alginate microspheres yield specificity comparable with an enzyme-linked immunosorbent assay. We can easily modify the size and shape of alginate microspheres, and increase the concentration of functionalized alginate microspheres to further enhance binding kinetics and enable multiplexing. (b) A novel droplet microfluidics method to image oxygen in single islets (pancreatic cells) for glucose sensing. Individual islets and a fluorescent oxygen-sensitive dye were encased within a thin alginate polymer microcapsule for insulin secretion monitoring. The sensing system operated similarly from 2-48 hours following encapsulation, and viability and function of the islets were not significantly affected by the encapsulation process. This approach should be applicable to other cell types and dyes sensitive to other biologically important molecules. (2) A microfluidic chamber to perform uniform electric field stimulation in circular shaped culturewares A 3D computer-aided designed (CAD) polymeric insert is designed and retrofitted to circular shaped culturewares in an integrated microfluidic electrical stimulation platform to generate uniform EF with higher cell yields. In particular, NIH/3T3 mouse embryonic fibroblast cells are used to validate the performance of the 3D designed Poly(methyl methacrylate) (PMMA) inserts in a circular-shaped 6-well plate. The CAD based inserts can be easily scaled up to further increase effective stimulation area percentages, and also be implemented in commercially available culturewares for a wide variety of EF-related research such as EF-cell interaction and tissue regeneration studies.

Nanotechnology meets 3D in vitro models: tissue engineered tumors and cancer therapies.

PubMed

da Rocha, E L; Porto, L M; Rambo, C R

2014-01-01

Advances in nanotechnology are providing to medicine a new dimension. Multifunctional nanomaterials with diagnostics and treatment modalities integrated in one nanoparticle or in cooperative nanosystems are promoting new insights to cancer treatment and diagnosis. The recent convergence between tissue engineering and cancer is gradually moving towards the development of 3D disease models that more closely resemble in vivo characteristics of tumors. However, the current nanomaterials based therapies are accomplished mainly in 2D cell cultures or in complex in vivo models. The development of new platforms to evaluate nano-based therapies in parallel with possible toxic effects will allow the design of nanomaterials for biomedical applications prior to in vivo studies. Therefore, this review focuses on how 3D in vitro models can be applied to study tumor biology, nanotoxicology and to evaluate nanomaterial based therapies. © 2013.

Integrated culture platform based on a human platelet lysate supplement for the isolation and scalable manufacturing of umbilical cord matrix-derived mesenchymal stem/stromal cells.

PubMed

de Soure, António M; Fernandes-Platzgummer, Ana; Moreira, Francisco; Lilaia, Carla; Liu, Shi-Hwei; Ku, Chen-Peng; Huang, Yi-Feng; Milligan, William; Cabral, Joaquim M S; da Silva, Cláudia L

2017-05-01

Umbilical cord matrix (UCM)-derived mesenchymal stem/stromal cells (MSCs) are promising therapeutic candidates for regenerative medicine settings. UCM MSCs have advantages over adult cells as these can be obtained through a non-invasive harvesting procedure and display a higher proliferative capacity. However, the high cell doses required in the clinical setting make large-scale manufacturing of UCM MSCs mandatory. A commercially available human platelet lysate-based culture supplement (UltraGRO TM , AventaCell BioMedical) (5%(v/v)) was tested to effectively isolate UCM MSCs and to expand these cells under (1) static conditions, using planar culture systems and (2) stirred culture using plastic microcarriers in a spinner flask. The MSC-like cells were isolated from UCM explant cultures after 11 ± 2 days. After five passages in static culture, UCM MSCs retained their immunophenotype and multilineage differentiation potential. The UCM MSCs cultured under static conditions using UltraGRO TM -supplemented medium expanded more rapidly compared with UCM MSCs expanded using a previously established protocol. Importantly, UCM MSCs were successfully expanded under dynamic conditions on plastic microcarriers using UltraGRO TM -supplemented medium in spinner flasks. Upon an initial 54% cell adhesion to the beads, UCM MSCs expanded by >13-fold after 5-6 days, maintaining their immunophenotype and multilineage differentiation ability. The present paper reports the establishment of an easily scalable integrated culture platform based on a human platelet lysate supplement for the effective isolation and expansion of UCM MSCs in a xenogeneic-free microcarrier-based system. This platform represents an important advance in obtaining safer and clinically meaningful MSC numbers for clinical translation. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Simplified generation of biomedical 3D surface model data for embedding into 3D portable document format (PDF) files for publication and education.

PubMed

Newe, Axel; Ganslandt, Thomas

2013-01-01

The usefulness of the 3D Portable Document Format (PDF) for clinical, educational, and research purposes has recently been shown. However, the lack of a simple tool for converting biomedical data into the model data in the necessary Universal 3D (U3D) file format is a drawback for the broad acceptance of this new technology. A new module for the image processing and rapid prototyping framework MeVisLab does not only provide a platform-independent possibility to create surface meshes out of biomedical/DICOM and other data and to export them into U3D--it also lets the user add meta data to these meshes to predefine colors and names that can be processed by a PDF authoring software while generating 3D PDF files. Furthermore, the source code of the respective module is available and well documented so that it can easily be modified for own purposes.

An adaptable XML based approach for scientific data management and integration

NASA Astrophysics Data System (ADS)

Wang, Fusheng; Thiel, Florian; Furrer, Daniel; Vergara-Niedermayr, Cristobal; Qin, Chen; Hackenberg, Georg; Bourgue, Pierre-Emmanuel; Kaltschmidt, David; Wang, Mo

2008-03-01

Increased complexity of scientific research poses new challenges to scientific data management. Meanwhile, scientific collaboration is becoming increasing important, which relies on integrating and sharing data from distributed institutions. We develop SciPort, a Web-based platform on supporting scientific data management and integration based on a central server based distributed architecture, where researchers can easily collect, publish, and share their complex scientific data across multi-institutions. SciPort provides an XML based general approach to model complex scientific data by representing them as XML documents. The documents capture not only hierarchical structured data, but also images and raw data through references. In addition, SciPort provides an XML based hierarchical organization of the overall data space to make it convenient for quick browsing. To provide generalization, schemas and hierarchies are customizable with XML-based definitions, thus it is possible to quickly adapt the system to different applications. While each institution can manage documents on a Local SciPort Server independently, selected documents can be published to a Central Server to form a global view of shared data across all sites. By storing documents in a native XML database, SciPort provides high schema extensibility and supports comprehensive queries through XQuery. By providing a unified and effective means for data modeling, data access and customization with XML, SciPort provides a flexible and powerful platform for sharing scientific data for scientific research communities, and has been successfully used in both biomedical research and clinical trials.

An Adaptable XML Based Approach for Scientific Data Management and Integration.

PubMed

Wang, Fusheng; Thiel, Florian; Furrer, Daniel; Vergara-Niedermayr, Cristobal; Qin, Chen; Hackenberg, Georg; Bourgue, Pierre-Emmanuel; Kaltschmidt, David; Wang, Mo

2008-02-20

Increased complexity of scientific research poses new challenges to scientific data management. Meanwhile, scientific collaboration is becoming increasing important, which relies on integrating and sharing data from distributed institutions. We develop SciPort, a Web-based platform on supporting scientific data management and integration based on a central server based distributed architecture, where researchers can easily collect, publish, and share their complex scientific data across multi-institutions. SciPort provides an XML based general approach to model complex scientific data by representing them as XML documents. The documents capture not only hierarchical structured data, but also images and raw data through references. In addition, SciPort provides an XML based hierarchical organization of the overall data space to make it convenient for quick browsing. To provide generalization, schemas and hierarchies are customizable with XML-based definitions, thus it is possible to quickly adapt the system to different applications. While each institution can manage documents on a Local SciPort Server independently, selected documents can be published to a Central Server to form a global view of shared data across all sites. By storing documents in a native XML database, SciPort provides high schema extensibility and supports comprehensive queries through XQuery. By providing a unified and effective means for data modeling, data access and customization with XML, SciPort provides a flexible and powerful platform for sharing scientific data for scientific research communities, and has been successfully used in both biomedical research and clinical trials.

Optimizing biomedical science learning in a veterinary curriculum: a review.

PubMed

Warren, Amy L; Donnon, Tyrone

2013-01-01

As veterinary medical curricula evolve, the time dedicated to biomedical science teaching, as well as the role of biomedical science knowledge in veterinary education, has been scrutinized. Aside from being mandated by accrediting bodies, biomedical science knowledge plays an important role in developing clinical, diagnostic, and therapeutic reasoning skills in the application of clinical skills, in supporting evidence-based veterinary practice and life-long learning, and in advancing biomedical knowledge and comparative medicine. With an increasing volume and fast pace of change in biomedical knowledge, as well as increased demands on curricular time, there has been pressure to make biomedical science education efficient and relevant for veterinary medicine. This has lead to a shift in biomedical education from fact-based, teacher-centered and discipline-based teaching to applicable, student-centered, integrated teaching. This movement is supported by adult learning theories and is thought to enhance students' transference of biomedical science into their clinical practice. The importance of biomedical science in veterinary education and the theories of biomedical science learning will be discussed in this article. In addition, we will explore current advances in biomedical teaching methodologies that are aimed to maximize knowledge retention and application for clinical veterinary training and practice.

Fluorescent Imaging of Single Nanoparticles and Viruses on a Smart Phone

PubMed Central

Wei, Qingshan; Qi, Hangfei; Luo, Wei; Tseng, Derek; Ki, So Jung; Wan, Zhe; Göröcs, Zoltán; Bentolila, Laurent A.; Wu, Ting-Ting; Sun, Ren; Ozcan, Aydogan

2014-01-01

Optical imaging of nanoscale objects, whether it is based on scattering or fluorescence, is a challenging task due to reduced detection signal-to-noise ratio and contrast at subwavelength dimensions. Here, we report a field-portable fluorescence microscopy platform installed on a smart phone for imaging of individual nanoparticles as well as viruses using a lightweight and compact opto-mechanical attachment to the existing camera module of the cell phone. This hand-held fluorescent imaging device utilizes (i) a compact 450 nm laser diode that creates oblique excitation on the sample plane with an incidence angle of ~75°, (ii) a long-pass thin-film interference filter to reject the scattered excitation light, (iii) an external lens creating 2× optical magnification, and (iv) a translation stage for focus adjustment. We tested the imaging performance of this smart-phone-enabled microscopy platform by detecting isolated 100 nm fluorescent particles as well as individual human cytomegaloviruses that are fluorescently labeled. The size of each detected nano-object on the cell phone platform was validated using scanning electron microscopy images of the same samples. This field-portable fluorescence microscopy attachment to the cell phone, weighing only ~186 g, could be used for specific and sensitive imaging of subwavelength objects including various bacteria and viruses and, therefore, could provide a valuable platform for the practice of nanotechnology in field settings and for conducting viral load measurements and other biomedical tests even in remote and resource-limited environments. PMID:24016065

Photocatalysis-Based Nanoprobes Using Noble Metal-Semiconductor Heterostructure for Visible Light-Driven in Vivo Detection of Mercury.

PubMed

Zhi, Lihua; Zeng, Xiaofan; Wang, Hao; Hai, Jun; Yang, Xiangliang; Wang, Baodui; Zhu, Yanhong

2017-07-18

The development of sensitive and reliable methods to monitor the presence of mercuric ions in cells and organisms is of great importance to biological research and biomedical applications. In this work, we propose a strategy to construct a solar-driven nanoprobe using a 3D Au@MoS 2 heterostructure as a photocatalyst and rhodamine B (RB) as a fluorescent and color change reporter molecule for monitoring Hg 2+ in living cells and animals. The sensing mechanism is based on the photoinduced electron formation of gold amalgam in the 3D Au@MoS 2 heterostructure under visible light illumination. This formation is able to remarkably inhibit the photocatalytic activity of the heterostructure toward RB decomposition. As a result, "OFF-ON" fluorescence and color change are produced. Such characteristics enable this new sensing platform to sensitively and selectively detect Hg 2+ in water by fluorescence and colorimetric methods. The detection limits of the fluorescence assay and colorimetric assay are 0.22 and 0.038 nM for Hg 2+ , respectively; these values are well below the acceptable limits in drinking water standards (10 nM). For the first time, such photocatalysis-based sensing platform is successfully used to monitor Hg 2+ in live cells and mice. Our work therefore opens a promising photocatalysis-based analysis methodology for highly sensitive and selective in vivo Hg 2+ bioimaging studies.

Nanoparticles for biomedical imaging, therapy, and quantitative diagnostics

NASA Astrophysics Data System (ADS)

Yust, Brian G.

Nanoparticles and nanomaterials are known to exhibit extraordinary characteristics and have a wide range of application which utilizes their unique properties. In particular, nanoparticles have shown great promise towards advancing the state of biological and biomedical techniques such as in vivo and in vitro imaging modalities, biosensing, and disease detection and therapy. Nanocrystalline hosts: NaYF4, KYF4, KGdF4, NaMF3, and KMF3 (M=Mg, Ba, Mn, Fe, Co, Ni, Cr) doped with rare earth ions have been synthesized by thermolysis, solvothermal, and hydrothermal methods. The morphology and spectroscopic properties have been thoroughly characterized. These nanoparticles (NP) are particularly useful for biomedical purposes since both the exciting and emitting wavelengths are in the near-infrared, where most tissues do not strongly absorb or scatter light. In vivo and in vitro imaging was performed with a 980 nm excitation source. Finally, NPs were conjugated with zinc phthalocyanine, a photosensitizer with a large absorption coefficient in the red and NIR regions, to illustrate the efficacy of these NPs as a platform for dual-mode infrared-activated imaging and photodynamic platforms. In addition, nonlinear optical nanomaterials, such as BaTiO3 and Ag@BaTiO3, were also synthesized and characterized. The nonlinear optical properties were investigated, and it is demonstrated that these nanoparticles can produce phase conjugate waves when used in a counterpropagating four wave mixing setup. The third order susceptibility is quantified using the z-scan technique, and the toxicity of these nanoparticles is also explored.

Supercomputing with toys: harnessing the power of NVIDIA 8800GTX and playstation 3 for bioinformatics problem.

PubMed

Wilson, Justin; Dai, Manhong; Jakupovic, Elvis; Watson, Stanley; Meng, Fan

2007-01-01

Modern video cards and game consoles typically have much better performance to price ratios than that of general purpose CPUs. The parallel processing capabilities of game hardware are well-suited for high throughput biomedical data analysis. Our initial results suggest that game hardware is a cost-effective platform for some computationally demanding bioinformatics problems.

Semantically Interoperable XML Data

PubMed Central

Vergara-Niedermayr, Cristobal; Wang, Fusheng; Pan, Tony; Kurc, Tahsin; Saltz, Joel

2013-01-01

XML is ubiquitously used as an information exchange platform for web-based applications in healthcare, life sciences, and many other domains. Proliferating XML data are now managed through latest native XML database technologies. XML data sources conforming to common XML schemas could be shared and integrated with syntactic interoperability. Semantic interoperability can be achieved through semantic annotations of data models using common data elements linked to concepts from ontologies. In this paper, we present a framework and software system to support the development of semantic interoperable XML based data sources that can be shared through a Grid infrastructure. We also present our work on supporting semantic validated XML data through semantic annotations for XML Schema, semantic validation and semantic authoring of XML data. We demonstrate the use of the system for a biomedical database of medical image annotations and markups. PMID:25298789

Flash NanoPrecipitation (FNP) for bioengineering nanoparticles to enhance the bioavailability

NASA Astrophysics Data System (ADS)

Feng, Jie; Zhang, Yingyue; McManus, Simone; Prud'Homme, Robert

2017-11-01

Nanoparticles for the delivery of therapeutics have been one of the successful areas in biomedical nanotechnology. Nanoparticles improve bioavailability by 1) the higher surface-to-volume ratios, enhancing dissolution rates, and 2) trapping drug molecules in higher energy, amorphous states for a higher solubility. However, conventional direct precipitation to prepare nanoparticles has the issues of low loading and encapsulation efficiency. Here we demonstrate a kinetically controlled and rapid-precipitation process called Flash NanoPrecipitation (FNP), to offer a multi-phase mixing platform for bioengineering nanoparticles. With the designed geometry in the micro-mixer, we can generate nanoparticles with a narrow size distribution, while maintaining high loading and encapsulation efficiency. By controlling the time scales in FNP, we can tune the nanoparticle size and the robustness of the process. Remarkably, the dissolution rates of the nanoparticles are significantly improved compared with crystalline drug powders. Furthermore, we investigate how to recover the drug-loaded nanoparticles from the aqueous dispersions. Regarding the maintenance of the bioavailability, we discuss the advantages and disadvantages of each drying process. These results suggest that FNP offers a versatile and scalable nano-fabrication platform for biomedical engineering.

Experimental characterization and analysis of the BITalino platforms against a reference device.

PubMed

Batista, Diana; Silva, Hugo; Fred, Ana

2017-07-01

Low-cost hardware platforms for biomedical engineering are becoming increasingly available, which empower the research community in the development of new projects in a wide range of areas related with physiological data acquisition. Building upon previous work by our group, this work compares the quality of the data acquired by means of two different versions of the multimodal physiological computing platform BITalino, with a device that can be considered a reference. We acquired data from 5 sensors, namely Accelerometry (ACC), Electrocardiography (ECG), Electroencephalography (EEG), Electrodermal Activity (EDA) and Electromyography (EMG). Experimental evaluation shows that ACC, ECG and EDA data are highly correlated with the reference in what concerns the raw waveforms. When compared by means of their commonly used features, EEG and EMG data are also quite similar across the different devices.

Nanorobot Hardware Architecture for Medical Defense

PubMed Central

Cavalcanti, Adriano; Shirinzadeh, Bijan; Zhang, Mingjun; Kretly, Luiz C.

2008-01-01

This work presents a new approach with details on the integrated platform and hardware architecture for nanorobots application in epidemic control, which should enable real time in vivo prognosis of biohazard infection. The recent developments in the field of nanoelectronics, with transducers progressively shrinking down to smaller sizes through nanotechnology and carbon nanotubes, are expected to result in innovative biomedical instrumentation possibilities, with new therapies and efficient diagnosis methodologies. The use of integrated systems, smart biosensors, and programmable nanodevices are advancing nanoelectronics, enabling the progressive research and development of molecular machines. It should provide high precision pervasive biomedical monitoring with real time data transmission. The use of nanobioelectronics as embedded systems is the natural pathway towards manufacturing methodology to achieve nanorobot applications out of laboratories sooner as possible. To demonstrate the practical application of medical nanorobotics, a 3D simulation based on clinical data addresses how to integrate communication with nanorobots using RFID, mobile phones, and satellites, applied to long distance ubiquitous surveillance and health monitoring for troops in conflict zones. Therefore, the current model can also be used to prevent and save a population against the case of some targeted epidemic disease. PMID:27879858

A Cost-Effective Fluorescence Mini-Microscope with Adjustable Magnifications for Biomedical Applications

PubMed Central

Zhang, Yu Shrike; Ribas, João; Nadhman, Akhtar; Aleman, Julio; Selimović, Šeila; Lesher-Perez, Sasha Cai; Wang, Ting; Manoharan, Vijayan; Shin, Su-Ryon; Damilano, Alessia; Annabi, Nasim; Dokmeci, Mehmet Remzi; Takayama, Shuichi; Khademhosseini, Ali

2015-01-01

We have designed and fabricated a miniature microscope from off-the-shelf components and webcam, with built-in fluorescence capability for biomedical applications. The mini-microscope was able to detect both biochemical parameters such as cell/tissue viability (e.g. Live/Dead assay), and biophysical properties of the microenvironment such as oxygen levels in microfabricated tissues based on an oxygen-sensitive fluorescent dye. This mini-microscope has adjustable magnifications from 8-60X, achieves a resolution as high as <2 μm, and possesses a long working distance of 4.5 mm (at a magnification of 8X). The mini-microscope was able to chronologically monitor cell migration and analyze beating of microfluidic liver and cardiac bioreactors in real time, respectively. The mini-microscope system is cheap, and its modularity allows convenient integration with a wide variety of pre-existing platforms including but not limited to, cell culture plates, microfluidic devices, and organs-on-a-chip systems. Therefore, we envision its widespread applications in cell biology, tissue engineering, biosensing, microfluidics, and organs-on-chips, which can potentially replace conventional bench-top microscopy where long-term in situ and large-scale imaging/analysis is required. PMID:26282117

A cost-effective fluorescence mini-microscope for biomedical applications.

PubMed

Zhang, Yu Shrike; Ribas, João; Nadhman, Akhtar; Aleman, Julio; Selimović, Šeila; Lesher-Perez, Sasha Cai; Wang, Ting; Manoharan, Vijayan; Shin, Su-Ryon; Damilano, Alessia; Annabi, Nasim; Dokmeci, Mehmet Remzi; Takayama, Shuichi; Khademhosseini, Ali

2015-01-01

We have designed and fabricated a miniature microscope from off-the-shelf components and a webcam, with built-in fluorescence capability for biomedical applications. The mini-microscope was able to detect both biochemical parameters, such as cell/tissue viability (e.g. live/dead assay), and biophysical properties of the microenvironment such as oxygen levels in microfabricated tissues based on an oxygen-sensitive fluorescent dye. This mini-microscope has adjustable magnifications from 8-60×, achieves a resolution as high as <2 μm, and possesses a long working distance of 4.5 mm (at a magnification of 8×). The mini-microscope was able to chronologically monitor cell migration and analyze beating of microfluidic liver and cardiac bioreactors in real time, respectively. The mini-microscope system is cheap, and its modularity allows convenient integration with a wide variety of pre-existing platforms including, but not limited to, cell culture plates, microfluidic devices, and organs-on-a-chip systems. Therefore, we envision its widespread application in cell biology, tissue engineering, biosensing, microfluidics, and organs-on-chips, which can potentially replace conventional bench-top microscopy where long-term in situ and large-scale imaging/analysis is required.

Membrane mimetic surface functionalization of nanoparticles: Methods and applications

PubMed Central

Weingart, Jacob; Vabbilisetty, Pratima; Sun, Xue-Long

2013-01-01

Nanoparticles (NPs), due to their size-dependent physical and chemical properties, have shown remarkable potential for a wide range of applications over the past decades. Particularly, the biological compatibilities and functions of NPs have been extensively studied for expanding their potential in areas of biomedical application such as bioimaging, biosensing, and drug delivery. In doing so, surface functionalization of NPs by introducing synthetic ligands and/or natural biomolecules has become a critical component in regards to the overall performance of the NP system for its intended use. Among known examples of surface functionalization, the construction of an artificial cell membrane structure, based on phospholipids, has proven effective in enhancing biocompatibility and has become a viable alternative to more traditional modifications, such as direct polymer conjugation. Furthermore, certain bioactive molecules can be immobilized onto the surface of phospholipid platforms to generate displays more reminiscent of cellular surface components. Thus, NPs with membrane-mimetic displays have found use in a range of bioimaging, biosensing, and drug delivery applications. This review herein describes recent advances in the preparations and characterization of integrated functional NPs covered by artificial cell membrane structures and their use in various biomedical applications. PMID:23688632

Microfluidic Diatomite Analytical Devices for Illicit Drug Sensing with ppb-Level Sensitivity.

PubMed

Kong, Xianming; Chong, Xinyuan; Squire, Kenny; Wang, Alan X

2018-04-15

The escalating research interests in porous media microfluidics, such as microfluidic paper-based analytical devices, have fostered a new spectrum of biomedical devices for point-of-care (POC) diagnosis and biosensing. In this paper, we report microfluidic diatomite analytical devices (μDADs), which consist of highly porous photonic crystal biosilica channels, as an innovative lab-on-a-chip platform to detect illicit drugs. The μDADs in this work are fabricated by spin-coating and tape-stripping diatomaceous earth on regular glass slides with cross section of 400×30µm 2 . As the most unique feature, our μDADs can simultaneously perform on-chip chromatography to separate small molecules from complex biofluidic samples and acquire the surface-enhanced Raman scattering spectra of the target chemicals with high specificity. Owing to the ultra-small dimension of the diatomite microfluidic channels and the photonic crystal effect from the fossilized diatom frustules, we demonstrate unprecedented sensitivity down to part-per-billion (ppb) level when detecting pyrene (1ppb) from mixed sample with Raman dye and cocaine (10 ppb) from human plasma. This pioneering work proves the exclusive advantage of μDADs as emerging microfluidic devices for chemical and biomedical sensing, especially for POC drug screening.

Quality management and accreditation of research tissue banks: experience of the National Center for Tumor Diseases (NCT) Heidelberg.

PubMed

Herpel, Esther; Röcken, Christoph; Manke, Heike; Schirmacher, Peter; Flechtenmacher, Christa

2010-12-01

Tissue banks are key resource and technology platforms in biomedical research that address the molecular pathogenesis of diseases as well as disease prevention, diagnosis, and treatment. Due to the central role of tissue banks in standardized collection, storage, and distribution of human tissues and their derivatives, quality management and its external assessment is becoming increasingly relevant for the maintenance, acceptance, and funding of tissue banks. Little experience exists regarding formalized external evaluation of tissue banks, especially regarding certification and accreditation. Based on the accreditation of the National Center of Tumor Diseases (NCT) tissue bank in Heidelberg (Germany), criteria, requirements, processes, and implications were compiled and evaluated. Accreditation formally approved professional competence and performance of the tissue bank in all steps involved in tissue collection, storage, handling as well as macroscopic and histologic examination and final (exit) examination of the tissue and transfer supervised by board-certified competent histopathologists. Thereby, accreditation provides a comprehensive measure to evaluate and document the quality standard of tissue research banks and may play a significant role in the future assessment of tissue banks. Furthermore, accreditation may support harmonization and standardization of tissue banking for biomedical research purposes.

Biocompatible and biodegradable dual-drug release system based on silk hydrogel containing silk nanoparticles.

PubMed

Numata, Keiji; Yamazaki, Shoya; Naga, Naofumi

2012-05-14

We developed a facile and quick ethanol-based method for preparing silk nanoparticles and then fabricated a biodegradable and biocompatible dual-drug release system based on silk nanoparticles and the molecular networks of silk hydrogels. Model drugs incorporated in the silk nanoparticles and silk hydrogels showed fast and constant release, respectively, indicating successful dual-drug release from silk hydrogel containing silk nanoparticles. The release behaviors achieved by this dual-drug release system suggest to be regulated by physical properties (e.g., β-sheet contents and size of the silk nanoparticles and network size of the silk hydrogels), which is an important advantage for biomedical applications. The present silk-based system for dual-drug release also demonstrated no significant cytotoxicity against human mesenchymal stem cells (hMSCs), and thus, this silk-based dual-drug release system has potential as a versatile and useful new platform of polymeric materials for various types of dual delivery of bioactive molecules.

Cell-phone-based platform for biomedical device development and education applications.

PubMed

Smith, Zachary J; Chu, Kaiqin; Espenson, Alyssa R; Rahimzadeh, Mehdi; Gryshuk, Amy; Molinaro, Marco; Dwyre, Denis M; Lane, Stephen; Matthews, Dennis; Wachsmann-Hogiu, Sebastian

2011-03-02

In this paper we report the development of two attachments to a commercial cell phone that transform the phone's integrated lens and image sensor into a 350x microscope and visible-light spectrometer. The microscope is capable of transmission and polarized microscopy modes and is shown to have 1.5 micron resolution and a usable field-of-view of 150 x 50 with no image processing, and approximately 350 x 350 when post-processing is applied. The spectrometer has a 300 nm bandwidth with a limiting spectral resolution of close to 5 nm. We show applications of the devices to medically relevant problems. In the case of the microscope, we image both stained and unstained blood-smears showing the ability to acquire images of similar quality to commercial microscope platforms, thus allowing diagnosis of clinical pathologies. With the spectrometer we demonstrate acquisition of a white-light transmission spectrum through diffuse tissue as well as the acquisition of a fluorescence spectrum. We also envision the devices to have immediate relevance in the educational field.

Cell-Phone-Based Platform for Biomedical Device Development and Education Applications

PubMed Central

Smith, Zachary J.; Chu, Kaiqin; Espenson, Alyssa R.; Rahimzadeh, Mehdi; Gryshuk, Amy; Molinaro, Marco; Dwyre, Denis M.; Lane, Stephen; Matthews, Dennis; Wachsmann-Hogiu, Sebastian

2011-01-01

In this paper we report the development of two attachments to a commercial cell phone that transform the phone's integrated lens and image sensor into a 350× microscope and visible-light spectrometer. The microscope is capable of transmission and polarized microscopy modes and is shown to have 1.5 micron resolution and a usable field-of-view of 150×150 with no image processing, and approximately 350×350 when post-processing is applied. The spectrometer has a 300 nm bandwidth with a limiting spectral resolution of close to 5 nm. We show applications of the devices to medically relevant problems. In the case of the microscope, we image both stained and unstained blood-smears showing the ability to acquire images of similar quality to commercial microscope platforms, thus allowing diagnosis of clinical pathologies. With the spectrometer we demonstrate acquisition of a white-light transmission spectrum through diffuse tissue as well as the acquisition of a fluorescence spectrum. We also envision the devices to have immediate relevance in the educational field. PMID:21399693

Electronic platform for real-time multi-parametric analysis of cellular behavior post-exposure to single-walled carbon nanotubes

PubMed Central

Eldawud, Reem; Wagner, Alixandra; Dong, Chenbo; Rojansakul, Yon; Dinu, Cerasela Zoica

2016-01-01

Single-walled carbon nanotubes (SWCNTs) implementation in a variety of biomedical applications from bioimaging, to controlled drug delivery and cellular-directed alignment for muscle myofiber fabrication, has raised awareness of their potential toxicity. Nanotubes structural aspects which resemble asbestos, as well as their ability to induce cyto and genotoxicity upon interaction with biological systems by generating reactive oxygen species or inducing membrane damage, just to name a few, have led to focused efforts aimed to assess associated risks prior their user implementation. In this study, we employed a non-invasive and real-time electric cell impedance sensing (ECIS) platform to monitor behavior of lung epithelial cells upon exposure to a library of SWCNTs with user-defined physicochemical properties. Using the natural sensitivity of the cells, we evaluated SWCNT-induced cellular changes in relation to cell attachment, cell–cell interactions and cell viability respectively. Our methods have the potential to lead to the development of standardized assays for risk assessment of other nanomaterials as well as risk differentiation based on the nanomaterials surface chemistry, purity and agglomeration state. PMID:25913448

Plasmon-enhanced Raman detection of body-fluid components

NASA Astrophysics Data System (ADS)

Matteini, Paolo; Banchelli, Martina; De Angelis, Marella; D'Andrea, Cristiano; Pini, Roberto

2018-02-01

Plasmon-enhanced spectroscopies such as surface-enhanced Raman spectroscopy (SERS) concern the detection of enhanced optical responses of molecules in close proximity to plasmonic structures, which results in a strong increase in sensitivity. Recent advancements in nanofabrication methods have paved the way for a controlled design of tailor-made nanostructures with fine-tuning of their optical and surface properties. Among these, silver nanocubes (AgNCs) represent a convenient choice in SERS owing to intense electromagnetic fields localized at their extremities, which are further intensified in the gap regions between closely spaced nanoparticles. The integration of AgNCs assemblies within an optofluidic platform may confer potential for superior optical investigation due to a molecular enrichment on the plasmonic structures to collect an enhanced photonic response. We developed a novel sensing platform based on an optofluidic system involving assembled silver nanocubes of 50 nm in size for ultrasensitive SERS detection of biomolecules in wet conditions. The proposed system offers the perspective of advanced biochemical and biological characterizations of molecules as well as of effective detection of body fluid components and other molecules of biomedical interest in their own environment.

Graphene and graphene-like 2D materials for optical biosensing and bioimaging: a review

NASA Astrophysics Data System (ADS)

Zhu, Chengzhou; Du, Dan; Lin, Yuehe

2015-09-01

The increasing demands of bioassay and biomedical applications have significantly promoted the rational design and fabrication of a wide range of functional nanomaterials. Coupling these advanced nanomaterials with biomolecule recognition events leads to novel sensing and diagnostic platforms. Because of their unique structures and multifunctionalities, two-dimensional nanomaterials, such as graphene and graphene-like materials (e.g., graphitic carbon nitride, transition metal dichalcogenides, boron nitride, and transition metal oxides), have stimulated great interest in the field of optical biosensors and imaging because of their innovative mechanical, physicochemical and optical properties. Depending on the different applications, the graphene and graphene-like nanomaterials can be tailored to form either fluorescent emitters or efficient fluorescence quenchers, making them powerful platforms for fabricating a series of optical biosensors to sensitively detect various targets including ions, small biomolecules, DNA/RNA and proteins. This review highlights the recent progress in optical biosensors based on graphene and graphene-like 2D materials and their imaging applications. Finally, the opportunities and some critical challenges in this field are also addressed.

Lessons learned from a pilot implementation of the UMLS information sources map.

PubMed

Miller, P L; Frawley, S J; Wright, L; Roderer, N K; Powsner, S M

1995-01-01

To explore the software design issues involved in implementing an operational information sources map (ISM) knowledge base (KB) and system of navigational tools that can help medical users access network-based information sources relevant to a biomedical question. A pilot biomedical ISM KB and associated client-server software (ISM/Explorer) have been developed to help students, clinicians, researchers, and staff access network-based information sources, as part of the National Library of Medicine's (NLM) multi-institutional Unified Medical Language System (UMLS) project. The system allows the user to specify and constrain a search for a biomedical question of interest. The system then returns a list of sources matching the search. At this point the user may request 1) further information about a source, 2) that the list of sources be regrouped by different criteria to allow the user to get a better overall appreciation of the set of retrieved sources as a whole, or 3) automatic connection to a source. The pilot system operates in client-server mode and currently contains coded information for 121 sources. It is in routine use from approximately 40 workstations at the Yale School of Medicine. The lessons that have been learned are that: 1) it is important to make access to different versions of a source as seamless as possible, 2) achieving seamless, cross-platform access to heterogeneous sources is difficult, 3) significant differences exist between coding the subject content of an electronic information resource versus that of an article or a book, 4) customizing the ISM to multiple institutions entails significant complexities, and 5) there are many design trade-offs between specifying searches and viewing sets of retrieved sources that must be taken into consideration. An ISM KB and navigational tools have been constructed. In the process, much has been learned about the complexities of development and evaluation in this new environment, which are different from those for Gopher, wide area information servers (WAIS), World-Wide-Web (WWW), and MOSAIC resources.

Nanostructured sensors for biomedical applications--a current perspective.

PubMed

Krishnamoorthy, Sivashankar

2015-08-01

Nanostructured sensors have unique capabilities that can be tailored to advantage in advancing the diagnosis, monitoring and cure of several diseases and health conditions. This report aims at providing a current perspective on, (a) the emerging clinical needs that defines the challenges to be addressed by nanostructured sensors, with specific emphasis on early stage diagnosis, drug-diagnostic combinations, and predictive models to design therapy, (b) the emerging industry trends in in vitro diagnostics, mobile health care, high-throughput molecular and cell-based diagnostic platforms, and (c) recent instances of nanostructured biosensors, including promising sensing concepts that can be enhanced using nanostructures that carry high promise towards catering to the emerging clinical needs, as well as the market/industry trends. Copyright © 2014 Elsevier Ltd. All rights reserved.

NCBI BLAST+ integrated into Galaxy.

PubMed

Cock, Peter J A; Chilton, John M; Grüning, Björn; Johnson, James E; Soranzo, Nicola

2015-01-01

The NCBI BLAST suite has become ubiquitous in modern molecular biology and is used for small tasks such as checking capillary sequencing results of single PCR products, genome annotation or even larger scale pan-genome analyses. For early adopters of the Galaxy web-based biomedical data analysis platform, integrating BLAST into Galaxy was a natural step for sequence comparison workflows. The command line NCBI BLAST+ tool suite was wrapped for use within Galaxy. Appropriate datatypes were defined as needed. The integration of the BLAST+ tool suite into Galaxy has the goal of making common BLAST tasks easy and advanced tasks possible. This project is an informal international collaborative effort, and is deployed and used on Galaxy servers worldwide. Several examples of applications are described here.

Self-assembled peptide-based nanostructures: Smart nanomaterials toward targeted drug delivery.

PubMed

Habibi, Neda; Kamaly, Nazila; Memic, Adnan; Shafiee, Hadi

2016-02-01

Self-assembly of peptides can yield an array of well-defined nanostructures that are highly attractive nanomaterials for many biomedical applications such as drug delivery. Some of the advantages of self-assembled peptide nanostructures over other delivery platforms include their chemical diversity, biocompatibility, high loading capacity for both hydrophobic and hydrophilic drugs, and their ability to target molecular recognition sites. Furthermore, these self-assembled nanostructures could be designed with novel peptide motifs, making them stimuli-responsive and achieving triggered drug delivery at disease sites. The goal of this work is to present a comprehensive review of the most recent studies on self-assembled peptides with a focus on their "smart" activity for formation of targeted and responsive drug-delivery carriers.

Plasmonic improvement of microcavity biomedical sensor spectroscopic characteristics

NASA Astrophysics Data System (ADS)

Saetchnikov, Vladimir A.; Tcherniavskaia, Elina A.; Saetchnikov, Anton V.; Schweiger, Gustav; Ostendorf, Andreas; Ghadiri, Reza

2014-03-01

New opportunity to improve a sensetivity of a label-free biomolecule detection in sensing systems based on microcavity evanescent wave optical sensors has been recently found and is being under intensive development. Novel technique based on combination of optical resonance on microring structures with plasmon resonance. Recently developed tools based on neural network data processing can realize real-time identification of biological agents. So combining advantages of plasmon enhancing optical microcavity resonance with identification tools can give a new platform for ulta sensitive label-free biomedical sensor. Our developed technique used standard glass and polymer microspheres as sensetive elements. They are fixed in the solution flow by adhesive layer on the surface being in the field of evanescence wave. Sensitive layer have been treated by gold nanoparticel (GN) solution. Another technique used thin film gold layers deposited on the substrate below adhesive. The light from a tuneable diode laser is coupled into the microsphere through a prism and was sharply focussed on the single microsphere. Images were recorded by CMOS camera. Normalized by free spectral range resonance shift of whispering gallery mode (WGM) and a relative efficiency of their excitation were used as input data for biomolecule classification. Both biomolecules and NP injection was obtained caused WGM spectra modification. But after NP treatment spectral shift and intensity of WGM resonances in biomolecule solutions increased. WGM resonances in microspheres fixed on substrate with gold layer with optimized layer thickness in biomolecule solutions also had higher intensity and spectra modification then without gold layer.

In vitro cardiomyocyte-driven biogenerator based on aligned piezoelectric nanofibers

NASA Astrophysics Data System (ADS)

Liu, Xia; Zhao, Hui; Lu, Yingxian; Li, Song; Lin, Liwei; Du, Yanan; Wang, Xiaohong

2016-03-01

Capturing the body's mechanical energy from the heart, lungs, and diaphragm can probably meet the requirements for in vivo applications of implantable biomedical devices. In this work, we present a novel contractile cardiomyocyte (CM)-driven biogenerator based on piezoelectric nanofibers (NFs) uniaxially aligned on a PDMS thin film. Flexible nanostructures interact with the CMs, as a physical cue to guide the CMs to align in a specific way, and create mechanical interfaces of contractile CMs and piezoelectric NFs. As such, the cellular construct features specific alignment and synchronous contraction, which realizes the maximal resultant force to drive the NFs to bend periodically. Studies on contraction mapping show that neonatal rat CMs self-assemble into a functional bio-bot film with well-defined axes of force generation. Consequently, the biogenerator produces an average voltage of 200 mV and current of 45 nA at the cell concentration of 1.0 million per ml, offering a biocompatible and scalable platform for biological energy conversion.Capturing the body's mechanical energy from the heart, lungs, and diaphragm can probably meet the requirements for in vivo applications of implantable biomedical devices. In this work, we present a novel contractile cardiomyocyte (CM)-driven biogenerator based on piezoelectric nanofibers (NFs) uniaxially aligned on a PDMS thin film. Flexible nanostructures interact with the CMs, as a physical cue to guide the CMs to align in a specific way, and create mechanical interfaces of contractile CMs and piezoelectric NFs. As such, the cellular construct features specific alignment and synchronous contraction, which realizes the maximal resultant force to drive the NFs to bend periodically. Studies on contraction mapping show that neonatal rat CMs self-assemble into a functional bio-bot film with well-defined axes of force generation. Consequently, the biogenerator produces an average voltage of 200 mV and current of 45 nA at the cell concentration of 1.0 million per ml, offering a biocompatible and scalable platform for biological energy conversion. Electronic supplementary information (ESI) available: Includes the ESI methods and figures, and videos of cell contraction and biogenerator bending. See DOI: 10.1039/c5nr08430j

Magnesium oxide grafted carbon nanotubes based impedimetric genosensor for biomedical application.

PubMed

Patel, Manoj Kumar; Ali, Md Azahar; Srivastava, Saurabh; Agrawal, Ved Varun; Ansari, S G; Malhotra, Bansi D

2013-12-15

Nanostructured magnesium oxide (size<10nm) grafted carboxyl (COOH) functionalized multi-walled carbon nanotubes (nMgO-cMWCNTs) deposited electrophoretically onto indium tin oxide (ITO) coated glass electrode and have been utilized for Vibrio cholerae detection. Aminated 23 bases single stranded DNA (NH2-ssDNA) probe sequence (O1 gene) of V. cholerae has been covalently functionalized onto nMgO-cMWCNTs/ITO electrode surface using EDC-NHS chemistry. This DNA functionalized MgO grafted cMWCNTs electrode has been characterized using X-ray photoelectron spectroscopy (XPS), Fourier transform infrared spectroscopy (FT-IR), scanning electron microscopy (SEM), transmission electron microscopy (TEM) and electrochemical techniques. The results of XPS studies reveal that sufficient O-C=O groups present at the nMgO-cMWCNTs surface are utilized for DNA binding. The results of hybridization studies conducted with fragmented target DNA (ftDNA) of V. cholerae using electrochemical impedance spectroscopy (EIS) reveal sensitivity as 3.87 Ω ng(-1) cm(-2), detection limit of ~21.70 ng µL(-1) in the linear range of 100-500 ng µL(-1) and stability of about 120 days. The proposed DNA functionalized nMgO-cMWCNTs nanomatrix provides a novel impedimetric platform for the fabrication of a compact genosensor device for biomedical application. © 2013 Elsevier B.V. All rights reserved.

Applications of stereolithography for rapid prototyping of biologically compatible chip-based physiometers

NASA Astrophysics Data System (ADS)

Fuad, Nurul Mohd; Zhu, Feng; Kaslin, Jan; Wlodkowic, Donald

2016-12-01

Despite the growing demand and numerous applications for the biomedical community, the developments in millifluidic devices for small model organisms are limited compared to other fields of biomicrofluidics. The main reasons for this stagnanation are difficulties in prototyping of millimeter scale and high aspect ratio devices needed for large metazoan organisms. Standard photolithography is in this context a time consuming procedure not easily adapted for fabrication of molds with vertical dimensions above 1 mm. Moreover, photolithography is still largely unattainable to a gross majority of biomedical laboratories willing to pursue custom development of their own chip-based platforms due to costs and need for dedicated clean room facilities. In this work, we present application of high-definition additive manufacturing systems for fabrication of 3D printed moulds used in soft lithography. Combination of 3D printing with PDMS replica molding appears to be an alternative for millifluidic systems that yields rapid and cost effective prototyping pipeline. We investigated the important aspects on both 3D printed moulds and PDMS replicas such as geometric accuracies and surface topology. Our results demonstrated that SLA technologies could be applied for rapid and accurate fabrication of millifluidic devices for trapping of millimetre-sized specimens such as living zebrafish larvae. We applied the new manufacturing method in a proof-of-concept prototype device capable of trapping and immobilizing living zebrafish larvae for recording heart rate variation in cardio-toxicity experiments.

Life Sciences Research and Development Opportunities During Suborbital Space Flight

NASA Technical Reports Server (NTRS)

Davis, Jeffrey R.

2010-01-01

Suborbital space platforms provide a unique opportunity for Space Life Sciences in the next few years. The opportunities include: physiological characterization of the first few minutes of space flight; evaluation of a wide-variety of medical conditions during periods of hyper and hypo-gravity through physiological monitoring; and evaluation of new biomedical and environmental health technologies under hyper and hypo-gravity conditions

Reflections on "YouTestTube.com": An Online Video-Sharing Platform to Engage Students with Chemistry Laboratory Classes

ERIC Educational Resources Information Center

McClean, Stephen; McCartan, Kenneth G.; Meskin, Sheryl; Gorges, Beronia; Hagan, W. Paul

2016-01-01

This paper describes the construction and development of YouTestTube.com, a YouTube clone website to facilitate video-sharing, social networking, and reflections of chemistry laboratory classes for year one students within the School of Biomedical Sciences at Ulster University. The practice was first introduced in the 2008/09 academic year and has…

Engineering DNA scaffolds for delivery of anticancer therapeutics.

PubMed

Sun, Wujin; Gu, Zhen

2015-07-01

Engineering DNA nanostructures with programmability in size, shape and surface chemistry holds tremendous promise in biomedical applications. As an emerging platform for drug delivery, DNA nanostructures have been extensively studied for delivering anticancer therapeutics, including small-molecule drug, nucleic acids and proteins. In this mini-review, current advances in utilizing DNA scaffolds as drug carriers for cancer treatment were summarized and future challenges were also discussed.

A Mass Spectrometry Proteomics Data Management Platform*

PubMed Central

Sharma, Vagisha; Eng, Jimmy K.; MacCoss, Michael J.; Riffle, Michael

2012-01-01

Mass spectrometry-based proteomics is increasingly being used in biomedical research. These experiments typically generate a large volume of highly complex data, and the volume and complexity are only increasing with time. There exist many software pipelines for analyzing these data (each typically with its own file formats), and as technology improves, these file formats change and new formats are developed. Files produced from these myriad software programs may accumulate on hard disks or tape drives over time, with older files being rendered progressively more obsolete and unusable with each successive technical advancement and data format change. Although initiatives exist to standardize the file formats used in proteomics, they do not address the core failings of a file-based data management system: (1) files are typically poorly annotated experimentally, (2) files are “organically” distributed across laboratory file systems in an ad hoc manner, (3) files formats become obsolete, and (4) searching the data and comparing and contrasting results across separate experiments is very inefficient (if possible at all). Here we present a relational database architecture and accompanying web application dubbed Mass Spectrometry Data Platform that is designed to address the failings of the file-based mass spectrometry data management approach. The database is designed such that the output of disparate software pipelines may be imported into a core set of unified tables, with these core tables being extended to support data generated by specific pipelines. Because the data are unified, they may be queried, viewed, and compared across multiple experiments using a common web interface. Mass Spectrometry Data Platform is open source and freely available at http://code.google.com/p/msdapl/. PMID:22611296

NCBO Ontology Recommender 2.0: an enhanced approach for biomedical ontology recommendation.

PubMed

Martínez-Romero, Marcos; Jonquet, Clement; O'Connor, Martin J; Graybeal, John; Pazos, Alejandro; Musen, Mark A

2017-06-07

Ontologies and controlled terminologies have become increasingly important in biomedical research. Researchers use ontologies to annotate their data with ontology terms, enabling better data integration and interoperability across disparate datasets. However, the number, variety and complexity of current biomedical ontologies make it cumbersome for researchers to determine which ones to reuse for their specific needs. To overcome this problem, in 2010 the National Center for Biomedical Ontology (NCBO) released the Ontology Recommender, which is a service that receives a biomedical text corpus or a list of keywords and suggests ontologies appropriate for referencing the indicated terms. We developed a new version of the NCBO Ontology Recommender. Called Ontology Recommender 2.0, it uses a novel recommendation approach that evaluates the relevance of an ontology to biomedical text data according to four different criteria: (1) the extent to which the ontology covers the input data; (2) the acceptance of the ontology in the biomedical community; (3) the level of detail of the ontology classes that cover the input data; and (4) the specialization of the ontology to the domain of the input data. Our evaluation shows that the enhanced recommender provides higher quality suggestions than the original approach, providing better coverage of the input data, more detailed information about their concepts, increased specialization for the domain of the input data, and greater acceptance and use in the community. In addition, it provides users with more explanatory information, along with suggestions of not only individual ontologies but also groups of ontologies to use together. It also can be customized to fit the needs of different ontology recommendation scenarios. Ontology Recommender 2.0 suggests relevant ontologies for annotating biomedical text data. It combines the strengths of its predecessor with a range of adjustments and new features that improve its reliability and usefulness. Ontology Recommender 2.0 recommends over 500 biomedical ontologies from the NCBO BioPortal platform, where it is openly available (both via the user interface at http://bioportal.bioontology.org/recommender , and via a Web service API).

Hybrid Integrated Silicon Microfluidic Platform for Fluorescence Based Biodetection.

PubMed

Chandrasekaran, Arvind; Acharya, Ashwin; You, Jian Liang; Soo, Kim Young; Packirisamy, Muthukumaran; Stiharu, Ion; Darveau, André

2007-09-11

The desideratum to develop a fully integrated Lab-on-a-chip device capable ofrapid specimen detection for high throughput in-situ biomedical diagnoses and Point-of-Care testing applications has called for the integration of some of the novel technologiessuch as the microfluidics, microphotonics, immunoproteomics and Micro ElectroMechanical Systems (MEMS). In the present work, a silicon based microfluidic device hasbeen developed for carrying out fluorescence based immunoassay. By hybrid attachment ofthe microfluidic device with a Spectrometer-on-chip, the feasibility of synthesizing anintegrated Lab-on-a-chip type device for fluorescence based biosensing has beendemonstrated. Biodetection using the microfluidic device has been carried out usingantigen sheep IgG and Alexafluor-647 tagged antibody particles and the experimentalresults prove that silicon is a compatible material for the present application given thevarious advantages it offers such as cost-effectiveness, ease of bulk microfabrication,superior surface affinity to biomolecules, ease of disposability of the device etc., and is thussuitable for fabricating Lab-on-a-chip type devices.

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.

A hybrid model based on neural networks for biomedical relation extraction.

PubMed

Zhang, Yijia; Lin, Hongfei; Yang, Zhihao; Wang, Jian; Zhang, Shaowu; Sun, Yuanyuan; Yang, Liang

2018-05-01

Biomedical relation extraction can automatically extract high-quality biomedical relations from biomedical texts, which is a vital step for the mining of biomedical knowledge hidden in the literature. Recurrent neural networks (RNNs) and convolutional neural networks (CNNs) are two major neural network models for biomedical relation extraction. Neural network-based methods for biomedical relation extraction typically focus on the sentence sequence and employ RNNs or CNNs to learn the latent features from sentence sequences separately. However, RNNs and CNNs have their own advantages for biomedical relation extraction. Combining RNNs and CNNs may improve biomedical relation extraction. In this paper, we present a hybrid model for the extraction of biomedical relations that combines RNNs and CNNs. First, the shortest dependency path (SDP) is generated based on the dependency graph of the candidate sentence. To make full use of the SDP, we divide the SDP into a dependency word sequence and a relation sequence. Then, RNNs and CNNs are employed to automatically learn the features from the sentence sequence and the dependency sequences, respectively. Finally, the output features of the RNNs and CNNs are combined to detect and extract biomedical relations. We evaluate our hybrid model using five public (protein-protein interaction) PPI corpora and a (drug-drug interaction) DDI corpus. The experimental results suggest that the advantages of RNNs and CNNs in biomedical relation extraction are complementary. Combining RNNs and CNNs can effectively boost biomedical relation extraction performance. Copyright © 2018 Elsevier Inc. All rights reserved.

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.

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.

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.

Antioxidant Nanoplatforms for Dermal Delivery: Melatonin.

PubMed

Milan, Aroha Sanchez; Campmany, Ana Cristina Calpena; Naveros, Beatriz Clares

2017-01-01

Melatonin is emerging as a promising therapeutic agent, mainly due to its role as antioxidant. Substantial evidences show that melatonin is potentially effective in a variety of diseases as cancer, inflammation and neurodegenerative diseases. The excellent antioxidant capacity with pharmacokinetics characteristics and the emerging search for new pharmaceutical nanotechnology based systems, make it particularly attractive to elaborate nanoplatforms based on melatonin for biomedical or cosmetic dermal applications. Different nanosystems for dermal delivery have been investigated. This review focuses on nanocarrier production strategies, dermal melatonin application and delivery advances in vivo and in vitro. Equally, future perspectives of this assisted melatonin delivery have also been discussed. In the current review, we have revised relevant articles of the available literature using the major scientific databases. One hundred and thirteen papers were included in the review, the majority of which represent latest researches in nanosized platforms for the dermal delivery of melatonin including liposomes, ethosomes, niosomes, polymeric nanoparticles, solid lipid nanoparticles and cyclodextrins. Furthermore, relevant papers reporting in vitro and in vivo application studies of these nano-based melatonin platforms were also discussed. The use of nanoplatforms for the dermal melatonin delivery as antioxidant agent could improve the efficacy of conventional melatonin administration due to the preservation of the drug from premature oxidation and the enhancement of drug permeation through the skin providing greater exposure times. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Peptide and protein nanoparticle conjugates: versatile platforms for biomedical applications.

PubMed

Spicer, Christopher D; Jumeaux, Coline; Gupta, Bakul; Stevens, Molly M

2018-05-21

Peptide- and protein-nanoparticle conjugates have emerged as powerful tools for biomedical applications, enabling the treatment, diagnosis, and prevention of disease. In this review, we focus on the key roles played by peptides and proteins in improving, controlling, and defining the performance of nanotechnologies. Within this framework, we provide a comprehensive overview of the key sequences and structures utilised to provide biological and physical stability to nano-constructs, direct particles to their target and influence their cellular and tissue distribution, induce and control biological responses, and form polypeptide self-assembled nanoparticles. In doing so, we highlight the great advances made by the field, as well as the challenges still faced in achieving the clinical translation of peptide- and protein-functionalised nano-drug delivery vehicles, imaging species, and active therapeutics.

Emerging Human Fetuin A Assays for Biomedical Diagnostics.

PubMed

Vashist, Sandeep Kumar; Schneider, E Marion; Venkatesh, A G; Luong, John H T

2017-05-01

Human fetuin A (HFA) plays a prominent pathophysiological role in numerous diseases and pathophysiological conditions with considerable biomedical significance; one example is the formation of calciprotein particles in osteoporosis and impaired calcium metabolisms. With impressive advances in in vitro diagnostic assays during the last decade, ELISAs have become a workhorse in routine clinical diagnostics. Recent diagnostic formats involve high-sensitivity immunoassay procedures, surface plasmon resonance, rapid immunoassay chemistries, signal enhancement, and smartphone detection. The current trend is toward fully integrated lab-on-chip platforms with smartphone readouts, enabling health-care practitioners and even patients to monitor pathological changes in biomarker levels. This review provides a critical analysis of advances made in HFA assays along with the challenges and future prospects. Copyright © 2016 Elsevier Ltd. All rights reserved.

Biomedical technology in Franconia.

PubMed

Efferth, T

2000-01-01

Medical instrumentation and biotechnology business is developing rapidly in Franconia. The universities of Bayreuth, Erlangen-Nürnberg, and Würzburg hold upper ranks in biomedical extramural funding research. They have a high competence in biomedical research, medical instrumentation, and biotechnology. The association "BioMedTec Franken e.V" has been founded at the beginning of 1999 both to foster the information exchange between universities, industry and politics and to facilitate the establishment of biomedical companies by means of science parks. In the IGZ (Innovation and Foundation Center Nürnberg-Fürth-Erlangen) 4,500 square meters of space are currently shared by 19 novel companies. Since 1985 60 companies in the IGZ had a total turnover of about 74 Mio Euro. The TGZ (Technologie- und Gründerzentrum) in Würzburg provides space for 11 companies. For the specific needs of biomedical technology companies further science parks will be set up in the near future. A science park for medical instrumentation will be founded in Erlangen (IZMP, Innovations- und Gründerzentrum für Medizintechnik und Pharma in der Region Nürnberg, Fürch, Erlangen). Furthermore, a Biomedical Technology Center and a Research Center for Bicompatible Materials are to be founded in Würzburg and Bayreuth, respectively. Several communication platforms (Bayern Innovativ, FORWISS, FTT, KIM, N-TEC-VISIT, TBU, WETTI etc.) allow the transfer of local academic research activities to industrial utilization and open new co-operation possibilities. International pharmaceutical companies (Novartis, Nürnberg; Pharmacia Upjohn, Erlangen) are located in Franconia. Central Franconia represents a national focus for medical instrumentation. The Erlangen settlement of the Medical Engineering Section of Siemens employs 4,500 people including approximately 1,000 employees in the Siemens research center.

Progress and future opportunities in the development of vaccines against atherosclerosis.

PubMed

Govea-Alonso, Dania O; Beltrán-López, Josué; Salazar-González, Jorge A; Vargas-Morales, Juan; Rosales-Mendoza, Sergio

2017-04-01

Atherosclerosis represents a serious global health problem that demands new therapeutic and prophylactic interventions. Considering that atherosclerosis has autoimmune and inflammatory components, immunotherapy is a possible focus to treat this disease. Areas covered: Based on the analysis of the current biomedical literature, this review describes the status on the development of vaccines against atherosclerosis. Several targets have been identified including sequences of apolipoprotein B100 (ApoB100), cholesteryl ester transfer protein (CETP), heat shock proteins (HSP), extracellular matrix proteins, T cell receptor β chain variable region 31 (TRBV31), the major outer membrane protein (MOMP), and the outer membrane protein 5 (Pomp5) from Chlamydia pneumoniae. Humoral and cellular immunities to these targets have been associated with therapeutic effects in murine models and humans. The evaluation of some candidates in clinical trials is ongoing. Expert commentary: New research paths based on the use of next generation vaccine production platforms are envisioned.

Digitized molecular diagnostics: reading disk-based bioassays with standard computer drives.

PubMed

Li, Yunchao; Ou, Lily M L; Yu, Hua-Zhong

2008-11-01

We report herein a digital signal readout protocol for screening disk-based bioassays with standard optical drives of ordinary desktop/notebook computers. Three different types of biochemical recognition reactions (biotin-streptavidin binding, DNA hybridization, and protein-protein interaction) were performed directly on a compact disk in a line array format with the help of microfluidic channel plates. Being well-correlated with the optical darkness of the binding sites (after signal enhancement by gold nanoparticle-promoted autometallography), the reading error levels of prerecorded audio files can serve as a quantitative measure of biochemical interaction. This novel readout protocol is about 1 order of magnitude more sensitive than fluorescence labeling/scanning and has the capability of examining multiplex microassays on the same disk. Because no modification to either hardware or software is needed, it promises a platform technology for rapid, low-cost, and high-throughput point-of-care biomedical diagnostics.

Clarity™ digital PCR system: a novel platform for absolute quantification of nucleic acids.

PubMed

Low, Huiyu; Chan, Shun-Jie; Soo, Guo-Hao; Ling, Belinda; Tan, Eng-Lee

2017-03-01

In recent years, digital polymerase chain reaction (dPCR) has gained recognition in biomedical research as it provides a platform for precise and accurate quantification of nucleic acids without the need for a standard curve. However, this technology has not yet been widely adopted as compared to real-time quantitative PCR due to its more cumbersome workflow arising from the need to sub-divide a PCR sample into a large number of smaller partitions prior to thermal cycling to achieve zero or at least one copy of the target RNA/DNA per partition. A recently launched platform, the Clarity™ system from JN Medsys, simplifies dPCR workflow through the use of a novel chip-in-a-tube technology for sample partitioning. In this study, the performance of Clarity™ was evaluated through quantification of the single-copy human RNase P gene. The system demonstrated high precision and accuracy and also excellent linearity across a range of over 4 orders of magnitude for the absolute quantification of the target gene. Moreover, consistent DNA copy measurements were also attained using a panel of different probe- and dye-based master mixes, demonstrating the system's compatibility with commercial master mixes. The Clarity™ was then compared to the QX100™ droplet dPCR system from Bio-Rad using a set of DNA reference materials, and the copy number concentrations derived from both systems were found to be closely associated. Collectively, the results showed that Clarity™ is a reliable, robust and flexible platform for next-generation genetic analysis.

Superhydrophobic materials for biomedical applications.

PubMed

Falde, Eric J; Yohe, Stefan T; Colson, Yolonda L; Grinstaff, Mark W

2016-10-01

Superhydrophobic surfaces are actively studied across a wide range of applications and industries, and are now finding increased use in the biomedical arena as substrates to control protein adsorption, cellular interaction, and bacterial growth, as well as platforms for drug delivery devices and for diagnostic tools. The commonality in the design of these materials is to create a stable or metastable air layer at the material surface, which lends itself to a number of unique properties. These activities are catalyzing the development of new materials, applications, and fabrication techniques, as well as collaborations across material science, chemistry, engineering, and medicine given the interdisciplinary nature of this work. The review begins with a discussion of superhydrophobicity, and then explores biomedical applications that are utilizing superhydrophobicity in depth including material selection characteristics, in vitro performance, and in vivo performance. General trends are offered for each application in addition to discussion of conflicting data in the literature, and the review concludes with the authors' future perspectives on the utility of superhydrophobic biomaterials for medical applications. Copyright © 2016 Elsevier Ltd. All rights reserved.

Covalent Organic Frameworks: From Materials Design to Biomedical Application

PubMed Central

Zhao, Fuli; Liu, Huiming; Mathe, Salva D. R.; Dong, Anjie

2017-01-01

Covalent organic frameworks (COFs) are newly emerged crystalline porous polymers with well-defined skeletons and nanopores mainly consisted of light-weight elements (H, B, C, N and O) linked by dynamic covalent bonds. Compared with conventional materials, COFs possess some unique and attractive features, such as large surface area, pre-designable pore geometry, excellent crystallinity, inherent adaptability and high flexibility in structural and functional design, thus exhibiting great potential for various applications. Especially, their large surface area and tunable porosity and π conjugation with unique photoelectric properties will enable COFs to serve as a promising platform for drug delivery, bioimaging, biosensing and theranostic applications. In this review, we trace the evolution of COFs in terms of linkages and highlight the important issues on synthetic method, structural design, morphological control and functionalization. And then we summarize the recent advances of COFs in the biomedical and pharmaceutical sectors and conclude with a discussion of the challenges and opportunities of COFs for biomedical purposes. Although currently still at its infancy stage, COFs as an innovative source have paved a new way to meet future challenges in human healthcare and disease theranostic. PMID:29283423

Biomedical informatics: development of a comprehensive data warehouse for clinical and genomic breast cancer research.

PubMed

Hu, Hai; Brzeski, Henry; Hutchins, Joe; Ramaraj, Mohan; Qu, Long; Xiong, Richard; Kalathil, Surendran; Kato, Rand; Tenkillaya, Santhosh; Carney, Jerry; Redd, Rosann; Arkalgudvenkata, Sheshkumar; Shahzad, Kashif; Scott, Richard; Cheng, Hui; Meadow, Stephen; McMichael, John; Sheu, Shwu-Lin; Rosendale, David; Kvecher, Leonid; Ahern, Stephen; Yang, Song; Zhang, Yonghong; Jordan, Rick; Somiari, Stella B; Hooke, Jeffrey; Shriver, Craig D; Somiari, Richard I; Liebman, Michael N

2004-10-01

The Windber Research Institute is an integrated high-throughput research center employing clinical, genomic and proteomic platforms to produce terabyte levels of data. We use biomedical informatics technologies to integrate all of these operations. This report includes information on a multi-year, multi-phase hybrid data warehouse project currently under development in the Institute. The purpose of the warehouse is to host the terabyte-level of internal experimentally generated data as well as data from public sources. We have previously reported on the phase I development, which integrated limited internal data sources and selected public databases. Currently, we are completing phase II development, which integrates our internal automated data sources and develops visualization tools to query across these data types. This paper summarizes our clinical and experimental operations, the data warehouse development, and the challenges we have faced. In phase III we plan to federate additional manual internal and public data sources and then to develop and adapt more data analysis and mining tools. We expect that the final implementation of the data warehouse will greatly facilitate biomedical informatics research.

Biomedical applications of yeast- a patent view, part one: yeasts as workhorses for the production of therapeutics and vaccines.

PubMed

Roohvand, Farzin; Shokri, Mehdi; Abdollahpour-Alitappeh, Meghdad; Ehsani, Parastoo

2017-08-01

Yeasts, as Eukaryotes, offer unique features for ease of growth and genetic manipulation possibilities, making it an exceptional microbial host. Areas covered: This review provides general and patent-oriented insights into production of biopharmaceuticals by yeasts. Patents, wherever possible, were correlated to the original or review articles. The review describes applications of major GRAS (generally regarded as safe) yeasts for the production of therapeutic proteins and subunit vaccines; additionally, immunomodulatory properties of yeast cell wall components were reviewed for use of whole yeast cells as a new vaccine platform. The second part of the review will discuss yeast- humanization strategies and innovative applications. Expert opinion: Biomedical applications of yeasts were initiated by utilization of Saccharomyces cerevisiae, for production of leavened (fermented) products, and advanced to serve to produce biopharmaceuticals. Higher biomass production and expression/secretion yields, more similarity of glycosylation patterns to mammals and possibility of host-improvement strategies through application of synthetic biology might enhance selection of Pichia pastoris (instead of S. cerevisiae) as a host for production of biopharmaceutical in future. Immunomodulatory properties of yeast cell wall β-glucans and possibility of intracellular expression of heterologous pathogen/tumor antigens in yeast cells have expanded their application as a new platform, 'Whole Yeast Vaccines'.

Development and Evaluation of Thesauri-Based Bibliographic Biomedical Search Engine

ERIC Educational Resources Information Center

Alghoson, Abdullah

2017-01-01

Due to the large volume and exponential growth of biomedical documents (e.g., books, journal articles), it has become increasingly challenging for biomedical search engines to retrieve relevant documents based on users' search queries. Part of the challenge is the matching mechanism of free-text indexing that performs matching based on…

Miniaturization for Point-of-Care Analysis: Platform Technology for Almost Every Biomedical Assay.

PubMed

Schumacher, Soeren; Sartorius, Dorian; Ehrentreich-Förster, Eva; Bier, Frank F

2012-10-01

Platform technologies for the changing need of diagnostics are one of the main challenges in medical device technology. From one point-of-view the demand for new and more versatile diagnostic is increasing due to a deeper knowledge of biomarkers and their combination with diseases. From another point-of-view a decentralization of diagnostics will occur since decisions can be made faster resulting in higher success of therapy. Hence, new types of technologies have to be established which enables a multiparameter analysis at the point-of-care. Within this review-like article a system called Fraunhofer ivD-platform is introduced. It consists of a credit-card sized cartridge with integrated reagents, sensors and pumps and a read-out/processing unit. Within the cartridge the assay runs fully automated within 15-20 minutes. Due to the open design of the platform different analyses such as antibody, serological or DNA-assays can be performed. Specific examples of these three different assay types are given to show the broad applicability of the system.

The Alpha-Helix Concept: Innovative utilization of the Space Station Program. A report to the National Aeronautical and Space Administration requesting establishment of a Sensory Physiology Laboratory on the Space Station

NASA Technical Reports Server (NTRS)

Bandurski, R. S.; Singh, N.

1983-01-01

A major laboratory dedicated to biological-medical research is proposed for the Space Platform. The laboratory would focus on sensor physiology and biochemistry since sensory physiology represents the first impact of the new space environment on living organisms. Microgravity and the high radiation environment of space would be used to help solve the problems of prolonged sojourns in space but, more importantly, to help solve terrestrial problems of human health and agricultural productivity. The emphasis would be on experimental use of microorganisms and small plants and small animals to minimize the space and time required to use the Space Platform for maximum human betterment. The Alpha Helix Concept, that is, the use of the Space Platform to bring experimental biomedicine to a new and extreme frontier is introduced so as to better understand the worldly environment. Staffing and instrumenting the Space Platform biomedical laboratory in a manner patterned after successful terrestrial sensory physiology laboratories is also proposed.

The Alpha-Helix Concept: Innovative utilization of the Space Station Program. A report to the National Aeronautical and Space Administration requesting establishment of a Sensory Physiology Laboratory on the Space Station

NASA Astrophysics Data System (ADS)

Bandurski, R. S.; Singh, N.

1983-10-01

A major laboratory dedicated to biological-medical research is proposed for the Space Platform. The laboratory would focus on sensor physiology and biochemistry since sensory physiology represents the first impact of the new space environment on living organisms. Microgravity and the high radiation environment of space would be used to help solve the problems of prolonged sojourns in space but, more importantly, to help solve terrestrial problems of human health and agricultural productivity. The emphasis would be on experimental use of microorganisms and small plants and small animals to minimize the space and time required to use the Space Platform for maximum human betterment. The Alpha Helix Concept, that is, the use of the Space Platform to bring experimental biomedicine to a new and extreme frontier is introduced so as to better understand the worldly environment. Staffing and instrumenting the Space Platform biomedical laboratory in a manner patterned after successful terrestrial sensory physiology laboratories is also proposed.

Implementation of a platform dedicated to the biomedical analysis terminologies management

PubMed Central

Cormont, Sylvie; Vandenbussche, Pierre-Yves; Buemi, Antoine; Delahousse, Jean; Lepage, Eric; Charlet, Jean

2011-01-01

Background and objectives. Assistance Publique - Hôpitaux de Paris (AP-HP) is implementing a new laboratory management system (LMS) common to the 12 hospital groups. First step to this process was to acquire a biological analysis dictionary. This dictionary is interfaced with the international nomenclature LOINC, and has been developed in collaboration with experts from all biological disciplines. In this paper we describe in three steps (modeling, data migration and integration/verification) the implementation of a platform for publishing and maintaining the AP-HP laboratory data dictionary (AnaBio). Material and Methods. Due to data complexity and volume, setting up a platform dedicated to the terminology management was a key requirement. This is an enhancement tackling identified weaknesses of previous spreadsheet tool. Our core model allows interoperability regarding data exchange standards and dictionary evolution. Results. We completed our goals within one year. In addition, structuring data representation has lead to a significant data quality improvement (impacting more than 10% of data). The platform is active in the 21 hospitals of the institution spread into 165 laboratories. PMID:22195205

A knowledge-driven approach to biomedical document conceptualization.

PubMed

Zheng, Hai-Tao; Borchert, Charles; Jiang, Yong

2010-06-01

Biomedical document conceptualization is the process of clustering biomedical documents based on ontology-represented domain knowledge. The result of this process is the representation of the biomedical documents by a set of key concepts and their relationships. Most of clustering methods cluster documents based on invariant domain knowledge. The objective of this work is to develop an effective method to cluster biomedical documents based on various user-specified ontologies, so that users can exploit the concept structures of documents more effectively. We develop a flexible framework to allow users to specify the knowledge bases, in the form of ontologies. Based on the user-specified ontologies, we develop a key concept induction algorithm, which uses latent semantic analysis to identify key concepts and cluster documents. A corpus-related ontology generation algorithm is developed to generate the concept structures of documents. Based on two biomedical datasets, we evaluate the proposed method and five other clustering algorithms. The clustering results of the proposed method outperform the five other algorithms, in terms of key concept identification. With respect to the first biomedical dataset, our method has the F-measure values 0.7294 and 0.5294 based on the MeSH ontology and gene ontology (GO), respectively. With respect to the second biomedical dataset, our method has the F-measure values 0.6751 and 0.6746 based on the MeSH ontology and GO, respectively. Both results outperforms the five other algorithms in terms of F-measure. Based on the MeSH ontology and GO, the generated corpus-related ontologies show informative conceptual structures. The proposed method enables users to specify the domain knowledge to exploit the conceptual structures of biomedical document collections. In addition, the proposed method is able to extract the key concepts and cluster the documents with a relatively high precision. Copyright 2010 Elsevier B.V. All rights reserved.

Interactions Between Genetics, Lifestyle, and Environmental Factors for Healthcare.

PubMed

Lin, Yuxin; Chen, Jiajia; Shen, Bairong

2017-01-01

The occurrence and progression of diseases are strongly associated with a combination of genetic, lifestyle, and environmental factors. Understanding the interplay between genetic and nongenetic components provides deep insights into disease pathogenesis and promotes personalized strategies for people healthcare. Recently, the paradigm of systems medicine, which integrates biomedical data and knowledge at multidimensional levels, is considered to be an optimal way for disease management and clinical decision-making in the era of precision medicine. In this chapter, epigenetic-mediated genetics-lifestyle-environment interactions within specific diseases and different ethnic groups are systematically discussed, and data sources, computational models, and translational platforms for systems medicine research are sequentially presented. Moreover, feasible suggestions on precision healthcare and healthy longevity are kindly proposed based on the comprehensive review of current studies.

Micro- and nanodevices integrated with biomolecular probes

PubMed Central

Alapan, Yunus; Icoz, Kutay; Gurkan, Umut A.

2016-01-01

Understanding how biomolecules, proteins and cells interact with their surroundings and other biological entities has become the fundamental design criterion for most biomedical micro- and nanodevices. Advances in biology, medicine, and nanofabrication technologies complement each other and allow us to engineer new tools based on biomolecules utilized as probes. Engineered micro/nanosystems and biomolecules in nature have remarkably robust compatibility in terms of function, size, and physical properties. This article presents the state of the art in micro- and nanoscale devices designed and fabricated with biomolecular probes as their vital constituents. General design and fabrication concepts are presented and three major platform technologies are highlighted: microcantilevers, micro/nanopillars, and microfluidics. Overview of each technology, typical fabrication details, and application areas are presented by emphasizing significant achievements, current challenges, and future opportunities. PMID:26363089

Label-free electrical detection of pyrophosphate generated from DNA polymerase reactions on field-effect devices.

PubMed

Credo, Grace M; Su, Xing; Wu, Kai; Elibol, Oguz H; Liu, David J; Reddy, Bobby; Tsai, Ta-Wei; Dorvel, Brian R; Daniels, Jonathan S; Bashir, Rashid; Varma, Madoo

2012-03-21

We introduce a label-free approach for sensing polymerase reactions on deoxyribonucleic acid (DNA) using a chelator-modified silicon-on-insulator field-effect transistor (SOI-FET) that exhibits selective and reversible electrical response to pyrophosphate anions. The chemical modification of the sensor surface was designed to include rolling-circle amplification (RCA) DNA colonies for locally enhanced pyrophosphate (PPi) signal generation and sensors with immobilized chelators for capture and surface-sensitive detection of diffusible reaction by-products. While detecting arrays of enzymatic base incorporation reactions is typically accomplished using optical fluorescence or chemiluminescence techniques, our results suggest that it is possible to develop scalable and portable PPi-specific sensors and platforms for broad biomedical applications such as DNA sequencing and microbe detection using surface-sensitive electrical readout techniques.

Hypogravity Research and Educational Parabolic Flight Activities Conducted in Barcelona: a new Hub of Innovation in Europe

NASA Astrophysics Data System (ADS)

Perez-Poch, Antoni; González, Daniel Ventura; López, David

2016-12-01

We report on different research and educational activities related to parabolic flights conducted in Barcelona since 2008. We use a CAP10B single-engine aerobatic aircraft flying out of Sabadell Airport and operating in visual flight conditions providing up to 8 seconds of hypogravity for each parabola. Aside from biomedical experiments being conducted, different student teams have flown in parabolic flights in the framework of the international contest `Barcelona Zero-G Challenge', and have published their results in relevant symposiums and scientific journals. The platform can certainly be a good testbed for a proof-of-concept before accessing other microgravity platforms, and has proved to be excellent for motivational student campaigns.

Oracle Database 10g: a platform for BLAST search and Regular Expression pattern matching in life sciences.

PubMed

Stephens, Susie M; Chen, Jake Y; Davidson, Marcel G; Thomas, Shiby; Trute, Barry M

2005-01-01

As database management systems expand their array of analytical functionality, they become powerful research engines for biomedical data analysis and drug discovery. Databases can hold most of the data types commonly required in life sciences and consequently can be used as flexible platforms for the implementation of knowledgebases. Performing data analysis in the database simplifies data management by minimizing the movement of data from disks to memory, allowing pre-filtering and post-processing of datasets, and enabling data to remain in a secure, highly available environment. This article describes the Oracle Database 10g implementation of BLAST and Regular Expression Searches and provides case studies of their usage in bioinformatics. http://www.oracle.com/technology/software/index.html.

Ontology driven integration platform for clinical and translational research

PubMed Central

Mirhaji, Parsa; Zhu, Min; Vagnoni, Mattew; Bernstam, Elmer V; Zhang, Jiajie; Smith, Jack W

2009-01-01

Semantic Web technologies offer a promising framework for integration of disparate biomedical data. In this paper we present the semantic information integration platform under development at the Center for Clinical and Translational Sciences (CCTS) at the University of Texas Health Science Center at Houston (UTHSC-H) as part of our Clinical and Translational Science Award (CTSA) program. We utilize the Semantic Web technologies not only for integrating, repurposing and classification of multi-source clinical data, but also to construct a distributed environment for information sharing, and collaboration online. Service Oriented Architecture (SOA) is used to modularize and distribute reusable services in a dynamic and distributed environment. Components of the semantic solution and its overall architecture are described. PMID:19208190

Multifunctional Gold Nanostars for Molecular Imaging and Cancer Therapy

NASA Astrophysics Data System (ADS)

Liu, Yang; Yuan, Hsiangkuo; Fales, Andrew; Register, Janna; Vo-Dinh, Tuan

2015-08-01

Plasmonics-active gold nanoparticles offer excellent potential in molecular imaging and cancer therapy. Among them, gold nanostars (AuNS) exhibit cross-platform flexibility as multimodal contrast agents for macroscopic X-ray computer tomography (CT), magnetic resonance imaging (MRI), positron emission tomography (PET), as well as nanoprobes for photoacoustic tomography (PAT), two-photon photoluminescence (TPL) and surface-enhanced Raman spectroscopy (SERS). Their surfactant-free surface enables versatile functionalization to enhance cancer targeting, and allow triggered drug release. AuNS can also be used as an efficient platform for drug carrying, photothermal therapy, and photodynamic therapy. This review paper presents the latest progress regarding AuNS as a promising nanoplatform for cancer nanotheranostics. Future research directions with AuNS for biomedical applications will also be discussed.

Nano-assembly and Controlled Release Kinetics of Nanoelements from Nanoporous Templates

NASA Astrophysics Data System (ADS)

Gultepe, E.; Nagesha, D.; McNulty, J.; Sridhar, S.

2008-03-01

Nanotemplates and nanoparticles have potential for use in the area of nanomanufacturing and biomedical applications. We are using highly ordered nanoporous alumina as a template for drug delivery and to assemble nanoelements such as latex beads and single wall carbon nanotubes (SWNT) by the means of electrophoresis and/or dielectrophoresis. The results of 100% assembly of latex beads and controlled elution of drugs from nanoporous templates will be discussed. Vertically assembled SWNT and with the I-V characteristic as 3D interconnects, will also be presented. We have developed a variety of platforms incorporating superparamagnetic iron oxide nanoparticles for targeted delivery, magnetic hyperthermia and as a contrast agent for magnetic resonance imaging. The results of cell studies on these platforms will be discussed.

Smart polyhydroxyalkanoate nanobeads by protein based functionalization.

PubMed

Dinjaski, Nina; Prieto, M Auxiliadora

2015-05-01

The development of innovative medicines and personalized biomedical approaches calls for new generation easily tunable biomaterials that can be manufactured applying straightforward and low-priced technologies. Production of functionalized bacterial polyhydroxyalkanoate (PHA) nanobeads by harnessing their natural carbon-storage granule production system is a thrilling recent development. This branch of nanobiotechnology employs proteins intrinsically binding the PHA granules as tags to immobilize recombinant proteins of interest and design functional nanocarriers for wide range of applications. Additionally, the implementation of new methodological platforms regarding production of endotoxin free PHA nanobeads using Gram-positive bacteria opened new avenues for biomedical applications. This prompts serious considerations of possible exploitation of bacterial cell factories as alternatives to traditional chemical synthesis and sources of novel bioproducts that could dramatically expand possible applications of biopolymers. In the 21st century, we are coming into the age of personalized medicine. There is a growing use of biomaterials in the clinical setting. In this review article, the authors describe the use of natural polyhydroxyalkanoate (PHA) nanoparticulates, which are formed within bacterial cells and can be easily functionalized. The potential uses would include high-affinity bioseparation, enzyme immobilization, protein delivery, diagnostics etc. The challenges of this approach remain the possible toxicity from endotoxin and the high cost of production. Copyright © 2015 Elsevier Inc. All rights reserved.

Zebrafish and Medaka: new model organisms for modern biomedical research.

PubMed

Lin, Cheng-Yung; Chiang, Cheng-Yi; Tsai, Huai-Jen

2016-01-28

Although they are primitive vertebrates, zebrafish (Danio rerio) and medaka (Oryzias latipes) have surpassed other animals as the most used model organisms based on their many advantages. Studies on gene expression patterns, regulatory cis-elements identification, and gene functions can be facilitated by using zebrafish embryos via a number of techniques, including transgenesis, in vivo transient assay, overexpression by injection of mRNAs, knockdown by injection of morpholino oligonucleotides, knockout and gene editing by CRISPR/Cas9 system and mutagenesis. In addition, transgenic lines of model fish harboring a tissue-specific reporter have become a powerful tool for the study of biological sciences, since it is possible to visualize the dynamic expression of a specific gene in the transparent embryos. In particular, some transgenic fish lines and mutants display defective phenotypes similar to those of human diseases. Therefore, a wide variety of fish model not only sheds light on the molecular mechanisms underlying disease pathogenesis in vivo but also provides a living platform for high-throughput screening of drug candidates. Interestingly, transgenic model fish lines can also be applied as biosensors to detect environmental pollutants, and even as pet fish to display beautiful fluorescent colors. Therefore, transgenic model fish possess a broad spectrum of applications in modern biomedical research, as exampled in the following review.

Biotea: RDFizing PubMed Central in support for the paper as an interface to the Web of Data

PubMed Central

2013-01-01

Background The World Wide Web has become a dissemination platform for scientific and non-scientific publications. However, most of the information remains locked up in discrete documents that are not always interconnected or machine-readable. The connectivity tissue provided by RDF technology has not yet been widely used to support the generation of self-describing, machine-readable documents. Results In this paper, we present our approach to the generation of self-describing machine-readable scholarly documents. We understand the scientific document as an entry point and interface to the Web of Data. We have semantically processed the full-text, open-access subset of PubMed Central. Our RDF model and resulting dataset make extensive use of existing ontologies and semantic enrichment services. We expose our model, services, prototype, and datasets at http://biotea.idiginfo.org/ Conclusions The semantic processing of biomedical literature presented in this paper embeds documents within the Web of Data and facilitates the execution of concept-based queries against the entire digital library. Our approach delivers a flexible and adaptable set of tools for metadata enrichment and semantic processing of biomedical documents. Our model delivers a semantically rich and highly interconnected dataset with self-describing content so that software can make effective use of it. PMID:23734622

Recent advances in bulk metallic glasses for biomedical applications.

PubMed

Li, H F; Zheng, Y F

2016-05-01

With a continuously increasing aging population and the improvement of living standards, large demands of biomaterials are expected for a long time to come. Further development of novel biomaterials, that are much safer and of much higher quality, in terms of both biomedical and mechanical properties, are therefore of great interest for both the research scientists and clinical surgeons. Compared with the conventional crystalline metallic counterparts, bulk metallic glasses have unique amorphous structures, and thus exhibit higher strength, lower Young's modulus, improved wear resistance, good fatigue endurance, and excellent corrosion resistance. For this purpose, bulk metallic glasses (BMGs) have recently attracted much attention for biomedical applications. This review discusses and summarizes the recent developments and advances of bulk metallic glasses, including Ti-based, Zr-based, Fe-based, Mg-based, Zn-based, Ca-based and Sr-based alloying systems for biomedical applications. Future research directions will move towards overcoming the brittleness, increasing the glass forming ability (GFA) thus obtaining corresponding bulk metallic glasses with larger sizes, removing/reducing toxic elements, and surface modifications. Bulk metallic glasses (BMGs), also known as amorphous alloys or liquid metals, are relative newcomers in the field of biomaterials. They have gained increasing attention during the past decades, as they exhibit an excellent combination of properties and processing capabilities desired for versatile biomedical implant applications. The present work reviewed the recent developments and advances of biomedical BMGs, including Ti-based, Zr-based, Fe-based, Mg-based, Zn-based, Ca-based and Sr-based BMG alloying systems. Besides, the critical analysis and in-depth discussion on the current status, challenge and future development of biomedical BMGs are included. The possible solution to the BMG size limitation, the brittleness of BMGs has been proposed. Copyright © 2016 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.

Dispersed publication of editorial research.

PubMed

Rosenberg, Jacob; Pommergaard, Hans-Christian; Vinther, Siri; Burcharth, Jakob

2015-02-01

There seems to be no dedicated journals available for publication of editorial research in the biomedical sciences; that is research into editorial or publication process issues involving the scientific approach to writing, reviewing, editing and publishing. It is unknown where papers concerning these issues are typically published. We therefore set out to study the distribution of such papers in the biomedical literature. In this pilot study, we conducted a MEDLINE search for papers on editorial research published in the year 2012. We found 445 articles published in 311 journals with a median of one article per journal (range: 1-17). The publication of papers on editorial research seems to be dispersed. In order to increase the visibility of this research field, it may be reasonable to establish well-defined platforms such as dedicated journals or journal sections in which such research could preferably be published.

A multiple distributed representation method based on neural network for biomedical event extraction.

PubMed

Wang, Anran; Wang, Jian; Lin, Hongfei; Zhang, Jianhai; Yang, Zhihao; Xu, Kan

2017-12-20

Biomedical event extraction is one of the most frontier domains in biomedical research. The two main subtasks of biomedical event extraction are trigger identification and arguments detection which can both be considered as classification problems. However, traditional state-of-the-art methods are based on support vector machine (SVM) with massive manually designed one-hot represented features, which require enormous work but lack semantic relation among words. In this paper, we propose a multiple distributed representation method for biomedical event extraction. The method combines context consisting of dependency-based word embedding, and task-based features represented in a distributed way as the input of deep learning models to train deep learning models. Finally, we used softmax classifier to label the example candidates. The experimental results on Multi-Level Event Extraction (MLEE) corpus show higher F-scores of 77.97% in trigger identification and 58.31% in overall compared to the state-of-the-art SVM method. Our distributed representation method for biomedical event extraction avoids the problems of semantic gap and dimension disaster from traditional one-hot representation methods. The promising results demonstrate that our proposed method is effective for biomedical event extraction.

A flexible home monitoring platform for patients affected by chronic heart failure directly integrated with the remote Hospital Information System

NASA Astrophysics Data System (ADS)

Donati, Massimiliano; Bacchillone, Tony; Saponara, Sergio; Fanucci, Luca

2011-05-01

Today Chronic Heart Failure (CHF) represents one of leading cause of hospitalization among chronic disease, especially for elderly citizens, with a consequent considerable impact on patient quality of life, resources congestion and healthcare costs for the National Sanitary System. The current healthcare model is mostly in-hospital based and consists of periodic visits, but unfortunately it does not allow to promptly detect exacerbations resulting in a large number of rehospitalization. Recently physicians and administrators identify telemonitoring systems as a strategy able to provide effective and cost efficient healthcare services for CHF patients, ensuring early diagnosis and treatments in case of necessity. This work presents a complete and integrated ICT solution to improve the management of chronic heart failure through the remote monitoring of vital signs at patient home, able to connect in-hospital care of acute syndrome with out-of-hospital follow-up. The proposed platform represents the patient's interface, acting as link between biomedical sensors and the data collection point at the Hospital Information System (HIS) in order to handle in transparent way the reception, analysis and forwarding of the main physiological parameters.

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.

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

Two-color, 30 second microwave-accelerated Metal-Enhanced Fluorescence DNA assays: a new Rapid Catch and Signal (RCS) technology.

PubMed

Dragan, Anatoliy I; Golberg, Karina; Elbaz, Amit; Marks, Robert; Zhang, Yongxia; Geddes, Chris D

2011-03-07

For analyses of DNA fragment sequences in solution we introduce a 2-color DNA assay, utilizing a combination of the Metal-Enhanced Fluorescence (MEF) effect and microwave-accelerated DNA hybridization. The assay is based on a new "Catch and Signal" technology, i.e. the simultaneous specific recognition of two target DNA sequences in one well by complementary anchor-ssDNAs, attached to silver island films (SiFs). It is shown that fluorescent labels (Alexa 488 and Alexa 594), covalently attached to ssDNA fragments, play the role of biosensor recognition probes, demonstrating strong response upon DNA hybridization, locating fluorophores in close proximity to silver NPs, which is ideal for MEF. Subsequently the emission dramatically increases, while the excited state lifetime decreases. It is also shown that 30s microwave irradiation of wells, containing DNA molecules, considerably (~1000-fold) speeds up the highly selective hybridization of DNA fragments at ambient temperature. The 2-color "Catch and Signal" DNA assay platform can radically expedite quantitative analysis of genome DNA sequences, creating a simple and fast bio-medical platform for nucleic acid analysis. Copyright © 2010 Elsevier B.V. All rights reserved.

High-Throughput Nano-Biofilm Microarray for Antifungal Drug Discovery

DTIC Science & Technology

2013-06-25

High-Throughput Nano-Biofilm Microarray for Antifungal Drug Discovery Anand Srinivasan,a, c Kai P. Leung,d Jose L. Lopez-Ribot,b, c Anand K...Ramasubramaniana, c Departments of Biomedical Engineeringa and Biologyb and South Texas Center for Emerging Infectious Diseases, c The University of Texas at San...of the opportunistic fungal pathogen Candida albicans on a microarray platform. The mi- croarray consists of 1,200 individual cultures of 30 nl of C

Using a Search Engine-Based Mutually Reinforcing Approach to Assess the Semantic Relatedness of Biomedical Terms

PubMed Central

Hsu, Yi-Yu; Chen, Hung-Yu; Kao, Hung-Yu

2013-01-01

Background Determining the semantic relatedness of two biomedical terms is an important task for many text-mining applications in the biomedical field. Previous studies, such as those using ontology-based and corpus-based approaches, measured semantic relatedness by using information from the structure of biomedical literature, but these methods are limited by the small size of training resources. To increase the size of training datasets, the outputs of search engines have been used extensively to analyze the lexical patterns of biomedical terms. Methodology/Principal Findings In this work, we propose the Mutually Reinforcing Lexical Pattern Ranking (ReLPR) algorithm for learning and exploring the lexical patterns of synonym pairs in biomedical text. ReLPR employs lexical patterns and their pattern containers to assess the semantic relatedness of biomedical terms. By combining sentence structures and the linking activities between containers and lexical patterns, our algorithm can explore the correlation between two biomedical terms. Conclusions/Significance The average correlation coefficient of the ReLPR algorithm was 0.82 for various datasets. The results of the ReLPR algorithm were significantly superior to those of previous methods. PMID:24348899

A proteomics performance standard to support measurement quality in proteomics.

PubMed

Beasley-Green, Ashley; Bunk, David; Rudnick, Paul; Kilpatrick, Lisa; Phinney, Karen

2012-04-01

The emergence of MS-based proteomic platforms as a prominent technology utilized in biochemical and biomedical research has increased the need for high-quality MS measurements. To address this need, National Institute of Standards and Technology (NIST) reference material (RM) 8323 yeast protein extract is introduced as a proteomics quality control material for benchmarking the preanalytical and analytical performance of proteomics-based experimental workflows. RM 8323 yeast protein extract is based upon the well-characterized eukaryote Saccharomyces cerevisiae and can be utilized in the design and optimization of proteomics-based methodologies from sample preparation to data analysis. To demonstrate its utility as a proteomics quality control material, we coupled LC-MS/MS measurements of RM 8323 with the NIST MS Quality Control (MSQC) performance metrics to quantitatively assess the LC-MS/MS instrumentation parameters that influence measurement accuracy, repeatability, and reproducibility. Due to the complexity of the yeast proteome, we also demonstrate how NIST RM 8323, along with the NIST MSQC performance metrics, can be used in the evaluation and optimization of proteomics-based sample preparation methods. © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Supervised Learning Based Hypothesis Generation from Biomedical Literature.

PubMed

Sang, Shengtian; Yang, Zhihao; Li, Zongyao; Lin, Hongfei

2015-01-01

Nowadays, the amount of biomedical literatures is growing at an explosive speed, and there is much useful knowledge undiscovered in this literature. Researchers can form biomedical hypotheses through mining these works. In this paper, we propose a supervised learning based approach to generate hypotheses from biomedical literature. This approach splits the traditional processing of hypothesis generation with classic ABC model into AB model and BC model which are constructed with supervised learning method. Compared with the concept cooccurrence and grammar engineering-based approaches like SemRep, machine learning based models usually can achieve better performance in information extraction (IE) from texts. Then through combining the two models, the approach reconstructs the ABC model and generates biomedical hypotheses from literature. The experimental results on the three classic Swanson hypotheses show that our approach outperforms SemRep system.

NanoLuc: A Small Luciferase is Brightening up the Field of Bioluminescence

PubMed Central

Cai, Weibo

2016-01-01

The biomedical field has greatly benefited from the discovery of bioluminescent proteins. Currently, scientists employ bioluminescent systems for numerous biomedical applications, ranging from highly sensitive cellular assays to bioluminescence-based molecular imaging. Traditionally, these systems are based on Firefly and Renilla luciferases; however, the applicability of these enzymes is limited by their size, stability, and luminescence efficiency. NanoLuc (NLuc), a novel bioluminescence platform, offers several advantages over established systems, including enhanced stability, smaller size, and >150-fold increase in luminescence. In addition, the substrate for NLuc displays enhanced stability and lower background activity, opening up new possibilities in the field of bioluminescence imaging. The NLuc system is incredibly versatile and may be utilized for a wide array of applications. The increased sensitivity, high stability, and small size of the NLuc system have the potential to drastically change the field of reporter assays in the future. However, as with all such technology, NLuc has limitations (including a non-ideal emission for in vivo applications and its unique substrate) which may cause it to find restricted use in certain areas of molecular biology. As this unique technology continues to broaden, NLuc may have a significant impact in both preclinical and clinical fields, with potential roles in disease detection, molecular imaging, and therapeutic monitoring. This review will present the NLuc technology to the scientific community in a non-biased manner, allowing the audience to adopt their own views of this novel system. PMID:27045664

Curriculum Mapping with Academic Analytics in Medical and Healthcare Education.

PubMed

Komenda, Martin; Víta, Martin; Vaitsis, Christos; Schwarz, Daniel; Pokorná, Andrea; Zary, Nabil; Dušek, Ladislav

2015-01-01

No universal solution, based on an approved pedagogical approach, exists to parametrically describe, effectively manage, and clearly visualize a higher education institution's curriculum, including tools for unveiling relationships inside curricular datasets. We aim to solve the issue of medical curriculum mapping to improve understanding of the complex structure and content of medical education programs. Our effort is based on the long-term development and implementation of an original web-based platform, which supports an outcomes-based approach to medical and healthcare education and is suitable for repeated updates and adoption to curriculum innovations. We adopted data exploration and visualization approaches in the context of medical curriculum innovations in higher education institutions domain. We have developed a robust platform, covering detailed formal metadata specifications down to the level of learning units, interconnections, and learning outcomes, in accordance with Bloom's taxonomy and direct links to a particular biomedical nomenclature. Furthermore, we used selected modeling techniques and data mining methods to generate academic analytics reports from medical curriculum mapping datasets. We present a solution that allows users to effectively optimize a curriculum structure that is described with appropriate metadata, such as course attributes, learning units and outcomes, a standardized vocabulary nomenclature, and a tree structure of essential terms. We present a case study implementation that includes effective support for curriculum reengineering efforts of academics through a comprehensive overview of the General Medicine study program. Moreover, we introduce deep content analysis of a dataset that was captured with the use of the curriculum mapping platform; this may assist in detecting any potentially problematic areas, and hence it may help to construct a comprehensive overview for the subsequent global in-depth medical curriculum inspection. We have proposed, developed, and implemented an original framework for medical and healthcare curriculum innovations and harmonization, including: planning model, mapping model, and selected academic analytics extracted with the use of data mining.

Curriculum Mapping with Academic Analytics in Medical and Healthcare Education

PubMed Central

Komenda, Martin; Víta, Martin; Vaitsis, Christos; Schwarz, Daniel; Pokorná, Andrea; Zary, Nabil; Dušek, Ladislav

2015-01-01

Background No universal solution, based on an approved pedagogical approach, exists to parametrically describe, effectively manage, and clearly visualize a higher education institution’s curriculum, including tools for unveiling relationships inside curricular datasets. Objective We aim to solve the issue of medical curriculum mapping to improve understanding of the complex structure and content of medical education programs. Our effort is based on the long-term development and implementation of an original web-based platform, which supports an outcomes-based approach to medical and healthcare education and is suitable for repeated updates and adoption to curriculum innovations. Methods We adopted data exploration and visualization approaches in the context of medical curriculum innovations in higher education institutions domain. We have developed a robust platform, covering detailed formal metadata specifications down to the level of learning units, interconnections, and learning outcomes, in accordance with Bloom’s taxonomy and direct links to a particular biomedical nomenclature. Furthermore, we used selected modeling techniques and data mining methods to generate academic analytics reports from medical curriculum mapping datasets. Results We present a solution that allows users to effectively optimize a curriculum structure that is described with appropriate metadata, such as course attributes, learning units and outcomes, a standardized vocabulary nomenclature, and a tree structure of essential terms. We present a case study implementation that includes effective support for curriculum reengineering efforts of academics through a comprehensive overview of the General Medicine study program. Moreover, we introduce deep content analysis of a dataset that was captured with the use of the curriculum mapping platform; this may assist in detecting any potentially problematic areas, and hence it may help to construct a comprehensive overview for the subsequent global in-depth medical curriculum inspection. Conclusions We have proposed, developed, and implemented an original framework for medical and healthcare curriculum innovations and harmonization, including: planning model, mapping model, and selected academic analytics extracted with the use of data mining. PMID:26624281

A novel biomedical image indexing and retrieval system via deep preference learning.

PubMed

Pang, Shuchao; Orgun, Mehmet A; Yu, Zhezhou

2018-05-01

The traditional biomedical image retrieval methods as well as content-based image retrieval (CBIR) methods originally designed for non-biomedical images either only consider using pixel and low-level features to describe an image or use deep features to describe images but still leave a lot of room for improving both accuracy and efficiency. In this work, we propose a new approach, which exploits deep learning technology to extract the high-level and compact features from biomedical images. The deep feature extraction process leverages multiple hidden layers to capture substantial feature structures of high-resolution images and represent them at different levels of abstraction, leading to an improved performance for indexing and retrieval of biomedical images. We exploit the current popular and multi-layered deep neural networks, namely, stacked denoising autoencoders (SDAE) and convolutional neural networks (CNN) to represent the discriminative features of biomedical images by transferring the feature representations and parameters of pre-trained deep neural networks from another domain. Moreover, in order to index all the images for finding the similarly referenced images, we also introduce preference learning technology to train and learn a kind of a preference model for the query image, which can output the similarity ranking list of images from a biomedical image database. To the best of our knowledge, this paper introduces preference learning technology for the first time into biomedical image retrieval. We evaluate the performance of two powerful algorithms based on our proposed system and compare them with those of popular biomedical image indexing approaches and existing regular image retrieval methods with detailed experiments over several well-known public biomedical image databases. Based on different criteria for the evaluation of retrieval performance, experimental results demonstrate that our proposed algorithms outperform the state-of-the-art techniques in indexing biomedical images. We propose a novel and automated indexing system based on deep preference learning to characterize biomedical images for developing computer aided diagnosis (CAD) systems in healthcare. Our proposed system shows an outstanding indexing ability and high efficiency for biomedical image retrieval applications and it can be used to collect and annotate the high-resolution images in a biomedical database for further biomedical image research and applications. Copyright © 2018 Elsevier B.V. All rights reserved.

The National Center for Biomedical Ontology

PubMed Central

Noy, Natalya F; Shah, Nigam H; Whetzel, Patricia L; Chute, Christopher G; Story, Margaret-Anne; Smith, Barry

2011-01-01

The National Center for Biomedical Ontology is now in its seventh year. The goals of this National Center for Biomedical Computing are to: create and maintain a repository of biomedical ontologies and terminologies; build tools and web services to enable the use of ontologies and terminologies in clinical and translational research; educate their trainees and the scientific community broadly about biomedical ontology and ontology-based technology and best practices; and collaborate with a variety of groups who develop and use ontologies and terminologies in biomedicine. The centerpiece of the National Center for Biomedical Ontology is a web-based resource known as BioPortal. BioPortal makes available for research in computationally useful forms more than 270 of the world's biomedical ontologies and terminologies, and supports a wide range of web services that enable investigators to use the ontologies to annotate and retrieve data, to generate value sets and special-purpose lexicons, and to perform advanced analytics on a wide range of biomedical data. PMID:22081220

The biomedical disciplines and the structure of biomedical and clinical knowledge.

PubMed

Nederbragt, H

2000-11-01

The relation between biomedical knowledge and clinical knowledge is discussed by comparing their respective structures. The knowledge of a disease as a biological phenomenon is constructed by the interaction of facts and theories from the main biomedical disciplines: epidemiology, diagnostics, clinical trial, therapy development and pathogenesis. Although these facts and theories are based on probabilities and extrapolations, the interaction provides a reliable and coherent structure, comparable to a Kuhnian paradigma. In the structure of clinical knowledge, i.e. knowledge of the patient with the disease, not only biomedical knowledge contributes to the structure but also economic and social relations, ethics and personal experience. However, the interaction between each of the participating "knowledges" in clinical knowledge is not based on mutual dependency and accumulation of different arguments from each, as in biomedical knowledge, but on competition and partial exclusion. Therefore, the structure of biomedical knowledge is different from that of clinical knowledge. This difference is used as the basis for a discussion in which the place of technology, evidence-based medicine and the gap between scientific and clinical knowledge are evaluated.

Privacy preserving interactive record linkage (PPIRL).

PubMed

Kum, Hye-Chung; Krishnamurthy, Ashok; Machanavajjhala, Ashwin; Reiter, Michael K; Ahalt, Stanley

2014-01-01

Record linkage to integrate uncoordinated databases is critical in biomedical research using Big Data. Balancing privacy protection against the need for high quality record linkage requires a human-machine hybrid system to safely manage uncertainty in the ever changing streams of chaotic Big Data. In the computer science literature, private record linkage is the most published area. It investigates how to apply a known linkage function safely when linking two tables. However, in practice, the linkage function is rarely known. Thus, there are many data linkage centers whose main role is to be the trusted third party to determine the linkage function manually and link data for research via a master population list for a designated region. Recently, a more flexible computerized third-party linkage platform, Secure Decoupled Linkage (SDLink), has been proposed based on: (1) decoupling data via encryption, (2) obfuscation via chaffing (adding fake data) and universe manipulation; and (3) minimum information disclosure via recoding. We synthesize this literature to formalize a new framework for privacy preserving interactive record linkage (PPIRL) with tractable privacy and utility properties and then analyze the literature using this framework. Human-based third-party linkage centers for privacy preserving record linkage are the accepted norm internationally. We find that a computer-based third-party platform that can precisely control the information disclosed at the micro level and allow frequent human interaction during the linkage process, is an effective human-machine hybrid system that significantly improves on the linkage center model both in terms of privacy and utility.

A multimodal imaging platform with integrated simultaneous photoacoustic microscopy, optical coherence tomography, optical Doppler tomography and fluorescence microscopy

NASA Astrophysics Data System (ADS)

Dadkhah, Arash; Zhou, Jun; Yeasmin, Nusrat; Jiao, Shuliang

2018-02-01

Various optical imaging modalities with different optical contrast mechanisms have been developed over the past years. Although most of these imaging techniques are being used in many biomedical applications and researches, integration of these techniques will allow researchers to reach the full potential of these technologies. Nevertheless, combining different imaging techniques is always challenging due to the difference in optical and hardware requirements for different imaging systems. Here, we developed a multimodal optical imaging system with the capability of providing comprehensive structural, functional and molecular information of living tissue in micrometer scale. This imaging system integrates photoacoustic microscopy (PAM), optical coherence tomography (OCT), optical Doppler tomography (ODT) and fluorescence microscopy in one platform. Optical-resolution PAM (OR-PAM) provides absorption-based imaging of biological tissues. Spectral domain OCT is able to provide structural information based on the scattering property of biological sample with no need for exogenous contrast agents. In addition, ODT is a functional extension of OCT with the capability of measurement and visualization of blood flow based on the Doppler effect. Fluorescence microscopy allows to reveal molecular information of biological tissue using autofluoresce or exogenous fluorophores. In-vivo as well as ex-vivo imaging studies demonstrated the capability of our multimodal imaging system to provide comprehensive microscopic information on biological tissues. Integrating all the aforementioned imaging modalities for simultaneous multimodal imaging has promising potential for preclinical research and clinical practice in the near future.

5-Azacytidine delivered by mesoporous silica nanoparticles regulates the differentiation of P19 cells into cardiomyocytes

NASA Astrophysics Data System (ADS)

Cheng, Jin; Ding, Qian; Wang, Jia; Deng, Lin; Yang, Lu; Tao, Lei; Lei, Haihong; Lu, Shaoping

2016-01-01

Heart disease is one of the deadliest diseases causing mortality due to the limited regenerative capability of highly differentiated cardiomyocytes. Stem cell-based therapy in tissue engineering is one of the most exciting and rapidly growing areas and raises promising prospects for cardiac repair. In this study, we have synthesized FITC-mesoporous silica nanoparticles (FMSNs) based on a sol-gel method (known as Stöber's method) as a drug delivery platform to transport 5-azacytidine in P19 embryonic carcinoma stem cells. The surfactant CTAB is utilized as a liquid crystal template to self-aggregate into micelles, resulting in the synthesis of MSNs. Based on the cell viability assay, treatment with FMSNs + 5-azacytidine resulted in much more significant inhibition of the proliferation than 5-azacytidine alone. To study the mechanism, we have tested the differentiation genes and cardiac marker genes in P19 cells and found that these genes have been up-regulated in P19 embryonic carcinoma stem cells treated with FMSNs + 5-azacytidine + poly(allylamine hydrochloride) (PAH), with the changes of histone modifications on the regulatory region. In conclusion, with FMSNs as drug delivery platforms, 5-azacytidine can be more efficiently delivered into stem cells and can be used to monitor and track the transfection process in situ to clarify their effects on stem cell functions and the differentiation process, which can serve as a promising tool in tissue engineering and other biomedical fields.

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

New Interfacial Nanochemistry on Sensory Bioscaffold-Membranes of Nanobelts

NASA Astrophysics Data System (ADS)

Chen, Feng

Nanostructured bioscaffolds and biosensors are evolving as popular and powerful tools in life science and biotechnology, due to the possible control of their surface and structural properties at the nm-scale. Being seldom discussed in literature and long-underexploited in materials and biomedical sciences, development of nanofiber-based sensory bioscaffolds has great promises and grand challenges in finding an ideal platform for low-cost quantifications of biological and chemical species in real-time, label-free, and ultrasensitive fashion. In this study, titanate nanobelts were first of all synthesized, from hydrothermal reactions of a NaOH (or KOH solution) with TiO2 powder, to possess underexploited structure and surface vital to the rapid and label-free electrochemical detections of protein (cytochrome c) and neurotransmitter (dopamine). This work is based on a suite of new physical and chemical properties on the titanate nanobelt in water, including high surface area, zwitterionic surface, chemical- and photochemical-durability, cation-exchange and anion- and cation-sorption capacities, protein- and cell-compatibility, thermal-stability, and charge conductivity. The Fourier transform infrared (FTIR) was used for identifying any denaturing of the cytochrome c pre-immobilized on the titanate nanobelts. On that basis, the pheochromocytoma cells (PC-12 cell) were chosen to grow on the titanate nanobelts. These experiments prove that the sensory bioscaffolds of titanate nanobelt-membrane is a multiplex platform for developing new tools for energy, environmental and life sciences.

Development of a high resolution plantar pressure monitoring pad based on fiber Bragg grating (FBG) sensors.

PubMed

Suresh, R; Bhalla, S; Hao, J; Singh, C

2015-01-01

High importance is given to plantar pressure monitoring in the field of biomedical engineering for the diagnosis of posture related ailments associated with diseases such as diabetes and gonarthrosis. This paper presents the proof-of-concept development of a new high resolution plantar pressure monitoring pad based on fiber Bragg grating (FBG) sensors. In the proposed configuration, the FBG sensors are embedded within layers of carbon composite material (CCM) in turn conforming to an arc shape. A total of four such arc shaped sensors are instrumented in the pad at the locations of the forefoot and the hind foot. As a test of the pad, static plantar pressure is monitored on normal subjects under various posture conditions. The pad is evaluated both as a standalone platform as well as a pad inserted inside a standard shoe. An average pressure sensitivity of 1.2 pm/kPa and a resolution of approximately 0.8 kPa is obtained in this special configuration. The pad is found to be suitable in both configurations- stand-alone pad as well as an insert inside a standard shoe. The proposed set up offers a cost-effective high resolution and accurate plantar pressure measurement system suitable for clinical deployment. The novelty of the developed pressure pad lies in its ability to be used both as platform type as well as inserted in-sole type sensor system.

Towards rapid prototyped convective microfluidic DNA amplification platform

NASA Astrophysics Data System (ADS)

Ajit, Smrithi; Praveen, Hemanth Mithun; Puneeth, S. B.; Dave, Abhishek; Sesham, Bharat; Mohan, K. N.; Goel, Sanket

2017-02-01

Today, Polymerase Chain Reaction (PCR) based DNA amplification plays an indispensable role in the field of biomedical research. Its inherent ability to exponentially amplify sample DNA has proven useful for the identification of virulent pathogens like those causing Multiple Drug-Resistant Tuberculosis (MDR-TB). The intervention of Microfluidics technology has revolutionized the concept of PCR from being a laborious and time consuming process into one that is faster, easily portable and capable of being multifunctional. The Microfluidics based PCR outweighs its traditional counterpart in terms of flexibility of varying reaction rate, operation simplicity, need of a fraction of volume and capability of being integrated with other functional elements. The scope of the present work involves the development of a real-time continuous flow microfluidic device, fabricated by 3D printing-governed rapid prototyping method, eventually leading to an automated and robust platform to process multiple DNA samples for detection of MDRTB-associated mutations. The thermal gradient characteristic to the PCR process is produced using peltier units appropriate to the microfluidic environment fully monitored and controlled by a low cost controller driven by a Data Acquisition System. The process efficiency achieved in the microfluidic environment in terms of output per cycle is expected to be on par with the traditional PCR and capable of earning the additional advantages of being faster and minimizing the handling.

The effect of contact angles and capillary dimensions on the burst frequency of super hydrophilic and hydrophilic centrifugal microfluidic platforms, a CFD study.

PubMed

Kazemzadeh, Amin; Ganesan, Poo; Ibrahim, Fatimah; He, Shuisheng; Madou, Marc J

2013-01-01

This paper employs the volume of fluid (VOF) method to numerically investigate the effect of the width, height, and contact angles on burst frequencies of super hydrophilic and hydrophilic capillary valves in centrifugal microfluidic systems. Existing experimental results in the literature have been used to validate the implementation of the numerical method. The performance of capillary valves in the rectangular and the circular microfluidic structures on super hydrophilic centrifugal microfluidic platforms is studied. The numerical results are also compared with the existing theoretical models and the differences are discussed. Our experimental and computed results show a minimum burst frequency occurring at square capillaries and this result is useful for designing and developing more sophisticated networks of capillary valves. It also predicts that in super hydrophilic microfluidics, the fluid leaks consistently from the capillary valve at low pressures which can disrupt the biomedical procedures in centrifugal microfluidic platforms.

The Effect of Contact Angles and Capillary Dimensions on the Burst Frequency of Super Hydrophilic and Hydrophilic Centrifugal Microfluidic Platforms, a CFD Study

PubMed Central

Kazemzadeh, Amin; Ganesan, Poo; Ibrahim, Fatimah; He, Shuisheng; Madou, Marc J.

2013-01-01

This paper employs the volume of fluid (VOF) method to numerically investigate the effect of the width, height, and contact angles on burst frequencies of super hydrophilic and hydrophilic capillary valves in centrifugal microfluidic systems. Existing experimental results in the literature have been used to validate the implementation of the numerical method. The performance of capillary valves in the rectangular and the circular microfluidic structures on super hydrophilic centrifugal microfluidic platforms is studied. The numerical results are also compared with the existing theoretical models and the differences are discussed. Our experimental and computed results show a minimum burst frequency occurring at square capillaries and this result is useful for designing and developing more sophisticated networks of capillary valves. It also predicts that in super hydrophilic microfluidics, the fluid leaks consistently from the capillary valve at low pressures which can disrupt the biomedical procedures in centrifugal microfluidic platforms. PMID:24069169

CDAPubMed: a browser extension to retrieve EHR-based biomedical literature.

PubMed

Perez-Rey, David; Jimenez-Castellanos, Ana; Garcia-Remesal, Miguel; Crespo, Jose; Maojo, Victor

2012-04-05

Over the last few decades, the ever-increasing output of scientific publications has led to new challenges to keep up to date with the literature. In the biomedical area, this growth has introduced new requirements for professionals, e.g., physicians, who have to locate the exact papers that they need for their clinical and research work amongst a huge number of publications. Against this backdrop, novel information retrieval methods are even more necessary. While web search engines are widespread in many areas, facilitating access to all kinds of information, additional tools are required to automatically link information retrieved from these engines to specific biomedical applications. In the case of clinical environments, this also means considering aspects such as patient data security and confidentiality or structured contents, e.g., electronic health records (EHRs). In this scenario, we have developed a new tool to facilitate query building to retrieve scientific literature related to EHRs. We have developed CDAPubMed, an open-source web browser extension to integrate EHR features in biomedical literature retrieval approaches. Clinical users can use CDAPubMed to: (i) load patient clinical documents, i.e., EHRs based on the Health Level 7-Clinical Document Architecture Standard (HL7-CDA), (ii) identify relevant terms for scientific literature search in these documents, i.e., Medical Subject Headings (MeSH), automatically driven by the CDAPubMed configuration, which advanced users can optimize to adapt to each specific situation, and (iii) generate and launch literature search queries to a major search engine, i.e., PubMed, to retrieve citations related to the EHR under examination. CDAPubMed is a platform-independent tool designed to facilitate literature searching using keywords contained in specific EHRs. CDAPubMed is visually integrated, as an extension of a widespread web browser, within the standard PubMed interface. It has been tested on a public dataset of HL7-CDA documents, returning significantly fewer citations since queries are focused on characteristics identified within the EHR. For instance, compared with more than 200,000 citations retrieved by breast neoplasm, fewer than ten citations were retrieved when ten patient features were added using CDAPubMed. This is an open source tool that can be freely used for non-profit purposes and integrated with other existing systems.

CDAPubMed: a browser extension to retrieve EHR-based biomedical literature

PubMed Central

2012-01-01

Background Over the last few decades, the ever-increasing output of scientific publications has led to new challenges to keep up to date with the literature. In the biomedical area, this growth has introduced new requirements for professionals, e.g., physicians, who have to locate the exact papers that they need for their clinical and research work amongst a huge number of publications. Against this backdrop, novel information retrieval methods are even more necessary. While web search engines are widespread in many areas, facilitating access to all kinds of information, additional tools are required to automatically link information retrieved from these engines to specific biomedical applications. In the case of clinical environments, this also means considering aspects such as patient data security and confidentiality or structured contents, e.g., electronic health records (EHRs). In this scenario, we have developed a new tool to facilitate query building to retrieve scientific literature related to EHRs. Results We have developed CDAPubMed, an open-source web browser extension to integrate EHR features in biomedical literature retrieval approaches. Clinical users can use CDAPubMed to: (i) load patient clinical documents, i.e., EHRs based on the Health Level 7-Clinical Document Architecture Standard (HL7-CDA), (ii) identify relevant terms for scientific literature search in these documents, i.e., Medical Subject Headings (MeSH), automatically driven by the CDAPubMed configuration, which advanced users can optimize to adapt to each specific situation, and (iii) generate and launch literature search queries to a major search engine, i.e., PubMed, to retrieve citations related to the EHR under examination. Conclusions CDAPubMed is a platform-independent tool designed to facilitate literature searching using keywords contained in specific EHRs. CDAPubMed is visually integrated, as an extension of a widespread web browser, within the standard PubMed interface. It has been tested on a public dataset of HL7-CDA documents, returning significantly fewer citations since queries are focused on characteristics identified within the EHR. For instance, compared with more than 200,000 citations retrieved by breast neoplasm, fewer than ten citations were retrieved when ten patient features were added using CDAPubMed. This is an open source tool that can be freely used for non-profit purposes and integrated with other existing systems. PMID:22480327

Biomedical Engineering and Cognitive Science Secondary Science Curriculum Development: A Three Year Study

ERIC Educational Resources Information Center

Klein, Stacy S.; Sherwood, Robert D.

2005-01-01

This study reports on a multi-year effort to create and evaluate cognitive-based curricular materials for secondary school science classrooms. A team of secondary teachers, educational researchers, and academic biomedical engineers developed a series of curriculum units that are based in biomedical engineering for secondary level students in…

Mueller matrix polarimetry imaging for breast cancer analysis (Conference Presentation)

NASA Astrophysics Data System (ADS)

Gribble, Adam; Vitkin, Alex

2017-02-01

Polarized light has many applications in biomedical imaging. The interaction of a biological sample with polarized light reveals information about its biological composition, both structural and functional. The most comprehensive type of polarimetry analysis is to measure the Mueller matrix, a polarization transfer function that completely describes how a sample interacts with polarized light. However, determination of the Mueller matrix requires tissue analysis under many different states of polarized light; a time consuming and measurement intensive process. Here we address this limitation with a new rapid polarimetry system, and use this polarimetry platform to investigate a variety of tissue changes associated with breast cancer. We have recently developed a rapid polarimetry imaging platform based on four photoelastic modulators (PEMs). The PEMs generate fast polarization modulations that allow the complete sample Mueller matrix to be imaged over a large field of view, with no moving parts. This polarimetry system is then demonstrated to be sensitive to a variety of tissue changes that are relevant to breast cancer. Specifically, we show that changes in depolarization can reveal tumor margins, and can differentiate between viable and necrotic breast cancer metastasized to the lymph nodes. Furthermore, the polarimetric property of linear retardance (related to birefringence) is dependent on collagen organization in the extracellular matrix. These findings indicate that our polarimetry platform may have future applications in fields such as breast cancer diagnosis, improving the speed and efficacy of intraoperative pathology, and providing prognostic information that may be beneficial for guiding treatment.

Capillary electrophoresis interfaced with a mass spectrometer (CE-MS): technical considerations and applicability for biomarker studies in animals.

PubMed

Albalat, Amaya; Husi, Holger; Siwy, Justyna; Nally, Jarlath E; McLauglin, Mark; Eckersall, Peter D; Mullen, William

2014-02-01

Proteomics is a growing field that has the potential to be applied to many biology-related disciplines. However, the study of the proteome has proven to be very challenging due to its high level of complexity when compared to genome and transcriptome data. In order to analyse this level of complexity, high resolution separation of peptides/proteins are needed together with high resolution analysers. Currently, liquid chromatography and capillary electrophoresis (CE) are the two most widely used separation techniques that can be coupled on-line with a mass spectrometer (MS). In CE, proteins/ peptides are separated according to their size, charge and shape leading to high resolving power. Although further progress in the area of sensitivity, throughput and proteome coverage are expected, MS-based proteomics have developed to a level at which they are habitually applied to study a wide range of biological questions. The aim of this review is to present CE-MS as a proteomic analytical platform for biomarker research that could be used in farm animal and veterinary studies. This is a MS-analytical platform that has been widely used for biomarker research in the biomedical field but its application in animal proteomic studies is relatively novel. The review will focus on introducing the CE-MS platform and the primary considerations for its application to biomarker research. Furthermore, current applications but more importantly potential application in the field of farm animals and veterinary science will be presented and discussed.

76 FR 53690 - National Institute of Biomedical Imaging and Bioengineering; Notice of Closed Meeting

Federal Register 2010, 2011, 2012, 2013, 2014

2011-08-29

... Biomedical Imaging and Bioengineering; Notice of Closed Meeting Pursuant to section 10(d) of the Federal... Biomedical Imaging and Bioengineering Special Emphasis Panel, NIBIB 2012 R25 Team Based Education. Date... Person: Ruth Grossman, DDS, Scientific Review Officer, National Institute of Biomedical Imaging and...

Droplet Microarray Based on Patterned Superhydrophobic Surfaces Prevents Stem Cell Differentiation and Enables High-Throughput Stem Cell Screening.

PubMed

Tronser, Tina; Popova, Anna A; Jaggy, Mona; Bastmeyer, Martin; Levkin, Pavel A

2017-12-01

Over the past decades, stem cells have attracted growing interest in fundamental biological and biomedical research as well as in regenerative medicine, due to their unique ability to self-renew and differentiate into various cell types. Long-term maintenance of the self-renewal ability and inhibition of spontaneous differentiation, however, still remain challenging and are not fully understood. Uncontrolled spontaneous differentiation of stem cells makes high-throughput screening of stem cells also difficult. This further hinders investigation of the underlying mechanisms of stem cell differentiation and the factors that might affect it. In this work, a dual functionality of nanoporous superhydrophobic-hydrophilic micropatterns is demonstrated in their ability to inhibit differentiation of mouse embryonic stem cells (mESCs) and at the same time enable formation of arrays of microdroplets (droplet microarray) via the effect of discontinuous dewetting. Such combination makes high-throughput screening of undifferentiated mouse embryonic stem cells possible. The droplet microarray is used to investigate the development, differentiation, and maintenance of stemness of mESC, revealing the dependence of stem cell behavior on droplet volume in nano- and microliter scale. The inhibition of spontaneous differentiation of mESCs cultured on the droplet microarray for up to 72 h is observed. In addition, up to fourfold increased cell growth rate of mESCs cultured on our platform has been observed. The difference in the behavior of mESCs is attributed to the porosity and roughness of the polymer surface. This work demonstrates that the droplet microarray possesses the potential for the screening of mESCs under conditions of prolonged inhibition of stem cells' spontaneous differentiation. Such a platform can be useful for applications in the field of stem cell research, pharmacological testing of drug efficacy and toxicity, biomedical research as well as in the field of regenerative medicine and tissue engineering. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Development of simulation interfaces for evaluation task with the use of physiological data and virtual reality applied to a vehicle simulator

NASA Astrophysics Data System (ADS)

Miranda, Mateus R.; Costa, Henrik; Oliveira, Luiz; Bernardes, Thiago; Aguiar, Carla; Miosso, Cristiano; Oliveira, Alessandro B. S.; Diniz, Alberto C. G. C.; Domingues, Diana Maria G.

2015-03-01

This paper aims at describing an experimental platform used to evaluate the performance of individuals at training immersive physiological games. The platform proposed is embedded in an immersive environment in a CAVE of Virtual Reality and consists on a base frame with actuators with three degrees of freedom, sensor array interface and physiological sensors. Physiological data of breathing, galvanic skin resistance (GSR) and pressure on the hand of the user and a subjective questionnaire were collected during the experiments. The theoretical background used in a project focused on Software Engineering, Biomedical Engineering in the field of Ergonomics and Creative Technologies in order to presents this case study, related of an evaluation of a vehicular simulator located inside the CAVE. The analysis of the simulator uses physiological data of the drivers obtained in a period of rest and after the experience, with and without movements at the simulator. Also images from the screen are captured through time at the embedded experience and data collected through physiological data visualization (average frequency and RMS graphics). They are empowered by the subjective questionnaire as strong lived experience provided by the technological apparatus. The performed immersion experience inside the CAVE allows to replicate behaviors from physical spaces inside data space enhanced by physiological properties. In this context, the biocybrid condition is expanded beyond art and entertainment, as it is applied to automotive engineering and biomedical engineering. In fact, the kinesthetic sensations amplified by synesthesia replicates the sensation of displacement in the interior of an automobile, as well as the sensations of vibration and vertical movements typical of a vehicle, different speeds, collisions, etc. The contribution of this work is the possibility to tracing a stress analysis protocol for drivers while operating a vehicle getting affective behaviors coming from physiological data, mixed to embedded simulation in Mixed Reality.

Scaled Anatomical Model Creation of Biomedical Tomographic Imaging Data and Associated Labels for Subsequent Sub-surface Laser Engraving (SSLE) of Glass Crystals.

PubMed

Betts, Aislinn M; McGoldrick, Matthew T; Dethlefs, Christopher R; Piotrowicz, Justin; Van Avermaete, Tony; Maki, Jeff; Gerstler, Steve; Leevy, W M

2017-04-25

Biomedical imaging modalities like computed tomography (CT) and magnetic resonance (MR) provide excellent platforms for collecting three-dimensional data sets of patient or specimen anatomy in clinical or preclinical settings. However, the use of a virtual, on-screen display limits the ability of these tomographic images to fully convey the anatomical information embedded within. One solution is to interface a biomedical imaging data set with 3D printing technology to generate a physical replica. Here we detail a complementary method to visualize tomographic imaging data with a hand-held model: Sub Surface Laser Engraving (SSLE) of crystal glass. SSLE offers several unique benefits including: the facile ability to include anatomical labels, as well as a scale bar; streamlined multipart assembly of complex structures in one medium; high resolution in the X, Y, and Z planes; and semi-transparent shells for visualization of internal anatomical substructures. Here we demonstrate the process of SSLE with CT data sets derived from pre-clinical and clinical sources. This protocol will serve as a powerful and inexpensive new tool with which to visualize complex anatomical structures for scientists and students in a number of educational and research settings.

QCloud: A cloud-based quality control system for mass spectrometry-based proteomics laboratories

PubMed Central

Chiva, Cristina; Olivella, Roger; Borràs, Eva; Espadas, Guadalupe; Pastor, Olga; Solé, Amanda

2018-01-01

The increasing number of biomedical and translational applications in mass spectrometry-based proteomics poses new analytical challenges and raises the need for automated quality control systems. Despite previous efforts to set standard file formats, data processing workflows and key evaluation parameters for quality control, automated quality control systems are not yet widespread among proteomics laboratories, which limits the acquisition of high-quality results, inter-laboratory comparisons and the assessment of variability of instrumental platforms. Here we present QCloud, a cloud-based system to support proteomics laboratories in daily quality assessment using a user-friendly interface, easy setup, automated data processing and archiving, and unbiased instrument evaluation. QCloud supports the most common targeted and untargeted proteomics workflows, it accepts data formats from different vendors and it enables the annotation of acquired data and reporting incidences. A complete version of the QCloud system has successfully been developed and it is now open to the proteomics community (http://qcloud.crg.eu). QCloud system is an open source project, publicly available under a Creative Commons License Attribution-ShareAlike 4.0. PMID:29324744

Novel Advances in Shotgun Lipidomics for Biology and Medicine

PubMed Central

Wang, Miao; Wang, Chunyan; Han, Rowland H.; Han, Xianlin

2015-01-01

The field of lipidomics, as coined in 2003, has made profound advances and been rapidly expanded. The mass spectrometry-based strategies of this analytical methodology-oriented research discipline for lipid analysis are largely fallen into three categories: direct infusion-based shotgun lipidomics, liquid chromatography-mass spectrometry-based platforms, and matrix-assisted laser desorption/ionization mass spectrometry-based approaches (particularly in imagining lipid distribution in tissues or cells). This review focuses on shotgun lipidomics. After briefly introducing its fundamentals, the major materials of this article cover its recent advances. These include the novel methods of lipid extraction, novel shotgun lipidomics strategies for identification and quantification of previously hardly accessible lipid classes and molecular species including isomers, and novel tools for processing and interpretation of lipidomics data. Representative applications of advanced shotgun lipidomics for biological and biomedical research are also presented in this review. We believe that with these novel advances in shotgun lipidomics, this approach for lipid analysis should become more comprehensive and high throughput, thereby greatly accelerating the lipidomics field to substantiate the aberrant lipid metabolism, signaling, trafficking, and homeostasis under pathological conditions and their underpinning biochemical mechanisms. PMID:26703190

iMSRC: converting a standard automated microscope into an intelligent screening platform.

PubMed

Carro, Angel; Perez-Martinez, Manuel; Soriano, Joaquim; Pisano, David G; Megias, Diego

2015-05-27

Microscopy in the context of biomedical research is demanding new tools to automatically detect and capture objects of interest. The few extant packages addressing this need, however, have enjoyed limited uptake due to complexity of use and installation. To overcome these drawbacks, we developed iMSRC, which combines ease of use and installation with high flexibility and enables applications such as rare event detection and high-resolution tissue sample screening, saving time and resources.

CoMetaR: A Collaborative Metadata Repository for Biomedical Research Networks.

PubMed

Stöhr, Mark R; Helm, Gudrun; Majeed, Raphael W; Günther, Andreas

2017-01-01

The German Center for Lung Research (DZL) is a research network with the aim of researching respiratory diseases. To perform consortium-wide queries through one single interface, it requires a uniform conceptual structure. No single terminology covers all our concepts. To achieve a broadly accepted and complete ontology, we developed a platform for collaborative metadata management "CoMetaR". Anyone can browse and discuss the ontology while editing can be performed by authenticated users.

Nanoparticle-Protein Interaction: The Significance and Role of Protein Corona.

PubMed

Ahsan, Saad Mohammad; Rao, Chintalagiri Mohan; Ahmad, Md Faiz

2018-01-01

The physico-chemical properties of nanoparticles, as characterized under idealized laboratory conditions, have been suggested to differ significantly when studied under complex physiological environments. A major reason for this variation has been the adsorption of biomolecules (mainly proteins) on the nanoparticle surface, constituting the so-called "biomolecular corona". The formation of biomolecular corona on the nanoparticle surface has been reported to influence various nanoparticle properties viz. cellular targeting, cellular interaction, in vivo clearance, toxicity, etc. Understanding the interaction of nanoparticles with proteins upon administration in vivo thus becomes important for the development of effective nanotechnology-based platforms for biomedical applications. In this chapter, we describe the formation of protein corona on nanoparticles and the differences arising in its composition due to variations in nanoparticle properties. Also discussed is the influence of protein corona on various nanoparticle activities.

Micro- and nanodevices integrated with biomolecular probes.

PubMed

Alapan, Yunus; Icoz, Kutay; Gurkan, Umut A

2015-12-01

Understanding how biomolecules, proteins and cells interact with their surroundings and other biological entities has become the fundamental design criterion for most biomedical micro- and nanodevices. Advances in biology, medicine, and nanofabrication technologies complement each other and allow us to engineer new tools based on biomolecules utilized as probes. Engineered micro/nanosystems and biomolecules in nature have remarkably robust compatibility in terms of function, size, and physical properties. This article presents the state of the art in micro- and nanoscale devices designed and fabricated with biomolecular probes as their vital constituents. General design and fabrication concepts are presented and three major platform technologies are highlighted: microcantilevers, micro/nanopillars, and microfluidics. Overview of each technology, typical fabrication details, and application areas are presented by emphasizing significant achievements, current challenges, and future opportunities. Copyright © 2015 Elsevier Inc. All rights reserved.

Versatile Dual Photoresponsive System for Precise Control of Chemical Reactions.

PubMed

Xu, Can; Bing, Wei; Wang, Faming; Ren, Jinsong; Qu, Xiaogang

2017-08-22

A versatile method for photoregulation of chemical reactions was developed through a combination of near-infrared (NIR) and ultraviolet (UV) light sensitive materials. This regulatory effect was achieved through photoresponsive modulation of reaction temperature and pH values, two prominent factors influencing reaction kinetics. Photothermal nanomaterial graphene oxide (GO) and photobase reagent malachite green carbinol base (MGCB) were selected for temperature and pH regulation, respectively. Using nanocatalyst- and enzyme-mediated chemical reactions as model systems, we demonstrated the feasibility and high efficiency of this method. In addition, a photoresponsive, multifunctional "Band-aid"-like hydrogel platform was presented for programmable wound healing. Overall, this simple, efficient, and reversible system was found to be effective for controlling a wide variety of chemical reactions. Our work may provide a method for remote and sustainable control over chemical reactions for industrial and biomedical applications.

Guidance of neurite outgrowth on aligned electrospun polypyrrole/poly(styrene-beta-isobutylene-beta-styrene) fiber platforms.

PubMed

Liu, Xiao; Chen, Jun; Gilmore, Kerry J; Higgins, Michael J; Liu, Yong; Wallace, Gordon G

2010-09-15

The purpose of this work was to investigate the potential biomedical application of novel aligned electrospun polypyrrole (PPy)/poly(styrene-beta-isobutylene-beta-styrene) (SIBS) fibers. After successfully aligning the electroactive PPy/SIBS fibers based on our modified electrospinning method, we demonstrated that neurite outgrowth from PC12 cells could be highly orientated parallel to the aligned PPy/SIBS fibers. Physical interactions between the nerve cells and PPy/SIBS fibers through filopodia "sensing" were observed using atomic force microscopy. These observations indicate a role of contact guidance as a mechanism for the observed alignment. This work highlights the capacity for electroactive PPy/SIBS fibers to support and guide nerve cell differentiation through topographic cues, which is a highly desirable characteristic in medical implants for neurological applications. (c) 2010 Wiley Periodicals, Inc.

A Wireless Biomedical Signal Interface System-on-Chip for Body Sensor Networks.

PubMed

Lei Wang; Guang-Zhong Yang; Jin Huang; Jinyong Zhang; Li Yu; Zedong Nie; Cumming, D R S

2010-04-01

Recent years have seen the rapid development of biosensor technology, system-on-chip design, wireless technology. and ubiquitous computing. When assembled into an autonomous body sensor network (BSN), the technologies become powerful tools in well-being monitoring, medical diagnostics, and personal connectivity. In this paper, we describe the first demonstration of a fully customized mixed-signal silicon chip that has most of the attributes required for use in a wearable or implantable BSN. Our intellectual-property blocks include low-power analog sensor interface for temperature and pH, a data multiplexing and conversion module, a digital platform based around an 8-b microcontroller, data encoding for spread-spectrum wireless transmission, and a RF section requiring very few off-chip components. The chip has been fully evaluated and tested by connection to external sensors, and it satisfied typical system requirements.

Oracle Database 10g: a platform for BLAST search and Regular Expression pattern matching in life sciences

PubMed Central

Stephens, Susie M.; Chen, Jake Y.; Davidson, Marcel G.; Thomas, Shiby; Trute, Barry M.

2005-01-01

As database management systems expand their array of analytical functionality, they become powerful research engines for biomedical data analysis and drug discovery. Databases can hold most of the data types commonly required in life sciences and consequently can be used as flexible platforms for the implementation of knowledgebases. Performing data analysis in the database simplifies data management by minimizing the movement of data from disks to memory, allowing pre-filtering and post-processing of datasets, and enabling data to remain in a secure, highly available environment. This article describes the Oracle Database 10g implementation of BLAST and Regular Expression Searches and provides case studies of their usage in bioinformatics. http://www.oracle.com/technology/software/index.html PMID:15608287

The Emory Chemical Biology Discovery Center: leveraging academic innovation to advance novel targets through HTS and beyond.

PubMed

Johns, Margaret A; Meyerkord-Belton, Cheryl L; Du, Yuhong; Fu, Haian

2014-03-01

The Emory Chemical Biology Discovery Center (ECBDC) aims to accelerate high throughput biology and translation of biomedical research discoveries into therapeutic targets and future medicines by providing high throughput research platforms to scientific collaborators worldwide. ECBDC research is focused at the interface of chemistry and biology, seeking to fundamentally advance understanding of disease-related biology with its HTS/HCS platforms and chemical tools, ultimately supporting drug discovery. Established HTS/HCS capabilities, university setting, and expertise in diverse assay formats, including protein-protein interaction interrogation, have enabled the ECBDC to contribute to national chemical biology efforts, empower translational research, and serve as a training ground for young scientists. With these resources, the ECBDC is poised to leverage academic innovation to advance biology and therapeutic discovery.

Tunable green/red luminescence by infrared upconversion in biocompatible forsterite nanoparticles with high erbium doping uptake

NASA Astrophysics Data System (ADS)

Zampiva, Rúbia Young Sun; Acauan, Luiz Henrique; Venturini, Janio; Garcia, Jose Augusto Martins; da Silva, Diego Silverio; Han, Zhaohong; Kassab, Luciana Reyes Pires; Wetter, Niklaus Ursus; Agarwal, Anuradha; Alves, Annelise Kopp; Bergmann, Carlos Pérez

2018-02-01

Nanoparticles represent a promising platform for diagnostics and therapy of human diseases. For biomedical applications, these nanoparticles are usually coated with photosensitizers regularly activated in a spectral window of 530-700 nm. The emissions at 530 nm (green) and 660 nm (red) are of particular interest for imaging and photodynamic therapy, respectively. This work presents the Mg2SiO4:Er3+ system, produced by reverse strike co-precipitation, with up to 10% dopant and no secondary phase formation. These nanoparticles when excited at 985 nm show upconversion emission with peaks around 530 and 660 nm, although excitation at 808 nm leads to only a single emission peak at around 530 nm. The direct upconversion of this biomaterial without a co-dopant, and its tunability by the excitation source, renders Mg2SiO4:Er3+ nanoparticles a promising system for biomedical applications.

High-speed laser photoacoustic imaging system combined with a digital ultrasonic imaging platform

NASA Astrophysics Data System (ADS)

Zeng, Lvming; Liu, Guodong; Ji, Xuanrong; Ren, Zhong; Huang, Zhen

2009-07-01

As a new field of combined ultrasound/photoacoustic imaging in biomedical photonics research, we present and demonstrate a high-speed laser photoacoustic imaging system combined with digital ultrasound imaging platform. In the prototype system, a new B-mode digital ultrasonic imaging system is modified as the hardware platform with 384 vertical transducer elements. The centre resonance frequency of the piezoelectric transducer is 5.0 MHz with greater than 70% pulse-echo -6dB fractional bandwidth. The modular instrument of PCI-6541 is used as the hardware control centre of the testing system, which features 32 high-speed channels to build low-skew and multi-channel system. The digital photoacoustic data is transported into computer for subsequent reconstruction at 25 MHz clock frequency. Meantime, the software system for controlling and analyzing is correspondingly explored with LabVIEW language on virtual instrument platform. In the breast tissue experiment, the reconstructed image agrees well with the original sample, and the spatial resolution of the system can reach 0.2 mm with multi-element synthetic aperture focusing technique. Therefore, the system and method may have a significant value in improving early detecting level of cancer in the breast and other organs.

Synthesis of three-dimensional calcium carbonate nanofibrous structure from eggshell using femtosecond laser ablation

PubMed Central

2011-01-01

Background Natural biomaterials from bone-like minerals derived from avian eggshells have been considered as promising bone substitutes owing to their biodegradability, abundance, and lower price in comparison with synthetic biomaterials. However, cell adhesion to bulk biomaterials is poor and surface modifications are required to improve biomaterial-cell interaction. Three-dimensional (3D) nanostructures are preferred to act as growth support platforms for bone and stem cells. Although there have been several studies on generating nanoparticles from eggshells, no research has been reported on synthesizing 3D nanofibrous structures. Results In this study, we propose a novel technique to synthesize 3D calcium carbonate interwoven nanofibrous platforms from eggshells using high repetition femtosecond laser irradiation. The eggshell waste is value engineered to calcium carbonate nanofibrous layer in a single step under ambient conditions. Our striking results demonstrate that by controlling the laser pulse repetition, nanostructures with different nanofiber density can be achieved. This approach presents an important step towards synthesizing 3D interwoven nanofibrous platforms from natural biomaterials. Conclusion The synthesized 3D nanofibrous structures can promote biomaterial interfacial properties to improve cell-platform surface interaction and develop new functional biomaterials for a variety of biomedical applications. PMID:21251288

Novel Polysaccharide Based Polymers and Nanoparticles for Controlled Drug Delivery and Biomedical Imaging

NASA Astrophysics Data System (ADS)

Shalviri, Alireza

The use of polysaccharides as building blocks in the development of drugs and contrast agents delivery systems is rapidly growing. This can be attributed to the outstanding virtues of polysaccharides such as biocompatibility, biodegradability, upgradability, multiple reacting groups and low cost. The focus of this thesis was to develop and characterize novel starch based hydrogels and nanoparticles for delivery of drugs and imaging agents. To this end, two different systems were developed. The first system includes polymer and nanoparticles prepared by graft polymerization of polymethacrylic acid and polysorbate 80 onto starch. This starch based platform nanotechnology was developed using the design principles based on the pathophysiology of breast cancer, with applications in both medical imaging and breast cancer chemotherapy. The nanoparticles exhibited a high degree of doxorubicin loading as well as sustained pH dependent release of the drug. The drug loaded nanoparticles were significantly more effective against multidrug resistant human breast cancer cells compared to free doxorubicin. Systemic administration of the starch based nanoparticles co-loaded with doxorubicin and a near infrared fluorescent probe allowed for non-invasive real time monitoring of the nanoparticles biodistribution, tumor accumulation, and clearance. Systemic administration of the clinically relevant doses of the drug loaded particles to a mouse model of breast cancer significantly enhanced therapeutic efficacy while minimizing side effects compared to free doxorubicin. A novel, starch based magnetic resonance imaging (MRI) contrast agent with good in vitro and in vivo tolerability was formulated which exhibited superior signal enhancement in tumor and vasculature. The second system is a co-polymeric hydrogel of starch and xanthan gum with adjustable swelling and permeation properties. The hydrogels exhibited excellent film forming capability, and appeared to be particularly useful in controlled delivery applications of larger molecular size compounds. The starch based hydrogels, polymers and nanoparticles developed in this work have shown great potentials for controlled drug delivery and biomedical imaging applications.

A New Pivoting and Iterative Text Detection Algorithm for Biomedical Images

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

Xu, Songhua; Krauthammer, Prof. Michael

2010-01-01

There is interest to expand the reach of literature mining to include the analysis of biomedical images, which often contain a paper's key findings. Examples include recent studies that use Optical Character Recognition (OCR) to extract image text, which is used to boost biomedical image retrieval and classification. Such studies rely on the robust identification of text elements in biomedical images, which is a non-trivial task. In this work, we introduce a new text detection algorithm for biomedical images based on iterative projection histograms. We study the effectiveness of our algorithm by evaluating the performance on a set of manuallymore » labeled random biomedical images, and compare the performance against other state-of-the-art text detection algorithms. We demonstrate that our projection histogram-based text detection approach is well suited for text detection in biomedical images, and that the iterative application of the algorithm boosts performance to an F score of .60. We provide a C++ implementation of our algorithm freely available for academic use.« less

Knowledge Representation and Management: a Linked Data Perspective.

PubMed

Barros, M; Couto, F M

2016-11-10

Biomedical research is increasingly becoming a data-intensive science in several areas, where prodigious amounts of data is being generated that has to be stored, integrated, shared and analyzed. In an effort to improve the accessibility of data and knowledge, the Linked Data initiative proposed a well-defined set of recommendations for exposing, sharing and integrating data, information and knowledge, using semantic web technologies. The main goal of this paper is to identify the current status and future trends of knowledge representation and management in Life and Health Sciences, mostly with regard to linked data technologies. We selected three prominent linked data studies, namely Bio2RDF, Open PHACTS and EBI RDF platform, and selected 14 studies published after 2014 (inclusive) that cited any of the three studies. We manually analyzed these 14 papers in relation to how they use linked data techniques. The analyses show a tendency to use linked data techniques in Life and Health Sciences, and even if some studies do not follow all of the recommendations, many of them already represent and manage their knowledge using RDF and biomedical ontologies. These insights from RDF and biomedical ontologies are having a strong impact on how knowledge is generated from biomedical data, by making data elements increasingly connected and by providing a better description of their semantics. As health institutes become more data centric, we believe that the adoption of linked data techniques will continue to grow and be an effective solution to knowledge representation and management.

A data-driven modeling approach to stochastic computation for low-energy biomedical devices.

PubMed

Lee, Kyong Ho; Jang, Kuk Jin; Shoeb, Ali; Verma, Naveen

2011-01-01

Low-power devices that can detect clinically relevant correlations in physiologically-complex patient signals can enable systems capable of closed-loop response (e.g., controlled actuation of therapeutic stimulators, continuous recording of disease states, etc.). In ultra-low-power platforms, however, hardware error sources are becoming increasingly limiting. In this paper, we present how data-driven methods, which allow us to accurately model physiological signals, also allow us to effectively model and overcome prominent hardware error sources with nearly no additional overhead. Two applications, EEG-based seizure detection and ECG-based arrhythmia-beat classification, are synthesized to a logic-gate implementation, and two prominent error sources are introduced: (1) SRAM bit-cell errors and (2) logic-gate switching errors ('stuck-at' faults). Using patient data from the CHB-MIT and MIT-BIH databases, performance similar to error-free hardware is achieved even for very high fault rates (up to 0.5 for SRAMs and 7 × 10(-2) for logic) that cause computational bit error rates as high as 50%.

Smart Materials Meet Multifunctional Biomedical Devices: Current and Prospective Implications for Nanomedicine.

PubMed

Genchi, Giada Graziana; Marino, Attilio; Tapeinos, Christos; Ciofani, Gianni

2017-01-01

With the increasing advances in the fabrication and in monitoring approaches of nanotechnology devices, novel materials are being synthesized and tested for the interaction with biological environments. Among them, smart materials in particular provide versatile and dynamically tunable platforms for the investigation and manipulation of several biological activities with very low invasiveness in hardly accessible anatomical districts. In the following, we will briefly recall recent examples of nanotechnology-based materials that can be remotely activated and controlled through different sources of energy, such as electromagnetic fields or ultrasounds, for their relevance to both basic science investigations and translational nanomedicine. Moreover, we will introduce some examples of hybrid materials showing mutually beneficial components for the development of multifunctional devices, able to simultaneously perform duties like imaging, tissue targeting, drug delivery, and redox state control. Finally, we will highlight challenging perspectives for the development of theranostic agents (merging diagnostic and therapeutic functionalities), underlining open questions for these smart nanotechnology-based devices to be made readily available to the patients in need.

Mean of the typical decoding rates: a new translation efficiency index based on the analysis of ribosome profiling data.

PubMed

Dana, Alexandra; Tuller, Tamir

2014-12-01

Gene translation modeling and prediction is a fundamental problem that has numerous biomedical implementations. In this work we present a novel, user-friendly tool/index for calculating the mean of the typical decoding rates that enables predicting translation elongation efficiency of protein coding genes for different tissue types, developmental stages, and experimental conditions. The suggested translation efficiency index is based on the analysis of the organism's ribosome profiling data. This index could be used for example to predict changes in translation elongation efficiency of lowly expressed genes that usually have relatively low and/or biased ribosomal densities and protein levels measurements, or can be used for example for predicting translation efficiency of new genetically engineered genes. We demonstrate the usability of this index via the analysis of six organisms in different tissues and developmental stages. Distributable cross platform application and guideline are available for download at: http://www.cs.tau.ac.il/~tamirtul/MTDR/MTDR_Install.html. Copyright © 2015 Dana and Tuller.

Molecular Assembly of Polysaccharide-Based Microcapsules and Their Biomedical Applications.

PubMed

Feng, Xiyun; Du, Cuiling; Li, Junbai

2016-08-01

Advanced multifunctional microcapsules have revealed great potential in biomedical applications owing to their tunable size, shape, surface properties, and stimuli responsiveness. Polysaccharides are one of the most acceptable biomaterials for biomedical applications because of their outstanding virtues such as biocompatibility, biodegradability, and low toxicity. Many efforts have been devoted to investigating novel molecular design and efficient building blocks for polysaccharide-based microcapsules. In this Personal Account, we first summarize the common features of polysaccharides and the main principles of the design and fabrication of polysaccharide-based microcapsules, and further discuss their applications in biomedical areas and perspectives for future research. © 2016 The Chemical Society of Japan & Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Platinum(II)-Oligonucleotide Coordination Based Aptasensor for Simple and Selective Detection of Platinum Compounds.

PubMed

Cai, Sheng; Tian, Xueke; Sun, Lianli; Hu, Haihong; Zheng, Shirui; Jiang, Huidi; Yu, Lushan; Zeng, Su

2015-10-20

Wide use of platinum-based chemotherapeutic regimens for the treatment for carcinoma calls for a simple and selective detection of platinum compound in biological samples. On the basis of the platinum(II)-base pair coordination, a novel type of aptameric platform for platinum detection has been introduced. This chemiluminescence (CL) aptasensor consists of a designed streptavidin (SA) aptamer sequence in which several base pairs were replaced by G-G mismatches. Only in the presence of platinum, coordination occurs between the platinum and G-G base pairs as opposed to the hydrogen-bonded G-C base pairs, which leads to SA aptamer sequence activation, resulting in their binding to SA coated magnetic beads. These Pt-DNA coordination events were monitored by a simple and direct luminol-peroxide CL reaction through horseradish peroxidase (HRP) catalysis with a strong chemiluminescence emission. The validated ranges of quantification were 0.12-240 μM with a limit of detection of 60 nM and selectivity over other metal ions. This assay was also successfully used in urine sample determination. It will be a promising candidate for the detection of platinum in biomedical and environmental samples.

Multifunctional nanoparticle platforms for in vivo MRI enhancement and photodynamic therapy of a rat brain cancer

NASA Astrophysics Data System (ADS)

Kopelman, Raoul; Lee Koo, Yong-Eun; Philbert, Martin; Moffat, Bradford A.; Ramachandra Reddy, G.; McConville, Patrick; Hall, Daniel E.; Chenevert, Thomas L.; Bhojani, Mahaveer Swaroop; Buck, Sarah M.; Rehemtulla, Alnawaz; Ross, Brian D.

2005-05-01

A paradigm for brain cancer detection, treatment, and monitoring is established. Multifunctional biomedical nanoparticles (30-60 nm) containing photosensitizer externally deliver reactive oxygen species (ROS) to cancer cells while simultaneously enhancing magnetic resonance imaging (MRI) contrast providing real-time tumor kill measurement. Plasma residence time control and specific cell targeting are achieved. A 5 min treatment in rats halted and even reversed in vivo tumor growth after 3-4 days post-treatment.

iMSRC: converting a standard automated microscope into an intelligent screening platform

PubMed Central

Carro, Angel; Perez-Martinez, Manuel; Soriano, Joaquim; Pisano, David G.; Megias, Diego

2015-01-01

Microscopy in the context of biomedical research is demanding new tools to automatically detect and capture objects of interest. The few extant packages addressing this need, however, have enjoyed limited uptake due to complexity of use and installation. To overcome these drawbacks, we developed iMSRC, which combines ease of use and installation with high flexibility and enables applications such as rare event detection and high-resolution tissue sample screening, saving time and resources. PMID:26015081

Detecting Disease Biomarkers Using Nanocavities and Nanoparticle Composites

NASA Astrophysics Data System (ADS)

Forster, Robert J.; Mallon, Colm; Devadoss, Anitha; Keyes, Tia E.

2011-08-01

The convergence of electrochemistry, materials, photonics and biomedical science at the nanoscale opens up significant opportunities for developing advanced sensors. In this contribution, we present examples of our use of nanometer dimensioned electrodes, nanocavities and nanoparticle-metallopolymer composites to create high sensitivity detection platforms and materials for detecting proteins and nucleic acids. The application of these approaches in the diagnosis and prognosis of cancers such as neuroblastoma, as well as point-of-care detection of infectious disease, will be discussed.

Physiological Sensing Now Open to the World: New Resources Are Allowing Us to Learn, Experiment, and Create Imaginative Solutions for Biomedical Applications.

PubMed

da Silva, Hugo Placido

2018-01-01

With the advent of low-cost computing platforms, such as Arduino (http://www.arduino.cc) and Raspberry Pi (http://www.raspberrypi.org), it has become clear that lowering the cost barrier and shortening the learning curve, with the backing of a motivated community, would play a transformational role in the way people learn, experiment, and create imaginative solutions to outstanding problems that can benefit from embedded systems.

The center for causal discovery of biomedical knowledge from big data

PubMed Central

Bahar, Ivet; Becich, Michael J; Benos, Panayiotis V; Berg, Jeremy; Espino, Jeremy U; Glymour, Clark; Jacobson, Rebecca Crowley; Kienholz, Michelle; Lee, Adrian V; Lu, Xinghua; Scheines, Richard

2015-01-01

The Big Data to Knowledge (BD2K) Center for Causal Discovery is developing and disseminating an integrated set of open source tools that support causal modeling and discovery of biomedical knowledge from large and complex biomedical datasets. The Center integrates teams of biomedical and data scientists focused on the refinement of existing and the development of new constraint-based and Bayesian algorithms based on causal Bayesian networks, the optimization of software for efficient operation in a supercomputing environment, and the testing of algorithms and software developed using real data from 3 representative driving biomedical projects: cancer driver mutations, lung disease, and the functional connectome of the human brain. Associated training activities provide both biomedical and data scientists with the knowledge and skills needed to apply and extend these tools. Collaborative activities with the BD2K Consortium further advance causal discovery tools and integrate tools and resources developed by other centers. PMID:26138794

Open-source mobile digital platform for clinical trial data collection in low-resource settings.

PubMed

van Dam, Joris; Omondi Onyango, Kevin; Midamba, Brian; Groosman, Nele; Hooper, Norman; Spector, Jonathan; Pillai, Goonaseelan Colin; Ogutu, Bernhards

2017-02-01

Governments, universities and pan-African research networks are building durable infrastructure and capabilities for biomedical research in Africa. This offers the opportunity to adopt from the outset innovative approaches and technologies that would be challenging to retrofit into fully established research infrastructures such as those regularly found in high-income countries. In this context we piloted the use of a novel mobile digital health platform, designed specifically for low-resource environments, to support high-quality data collection in a clinical research study. Our primary aim was to assess the feasibility of a using a mobile digital platform for clinical trial data collection in a low-resource setting. Secondarily, we sought to explore the potential benefits of such an approach. The investigative site was a research institute in Nairobi, Kenya. We integrated an open-source platform for mobile data collection commonly used in the developing world with an open-source, standard platform for electronic data capture in clinical trials. The integration was developed using common data standards (Clinical Data Interchange Standards Consortium (CDISC) Operational Data Model), maximising the potential to extend the approach to other platforms. The system was deployed in a pharmacokinetic study involving healthy human volunteers. The electronic data collection platform successfully supported conduct of the study. Multidisciplinary users reported high levels of satisfaction with the mobile application and highlighted substantial advantages when compared with traditional paper record systems. The new system also demonstrated a potential for expediting data quality review. This pilot study demonstrated the feasibility of using a mobile digital platform for clinical research data collection in low-resource settings. Sustainable scientific capabilities and infrastructure are essential to attract and support clinical research studies. Since many research structures in Africa are being developed anew, stakeholders should consider implementing innovative technologies and approaches.

Translational physiology: from molecules to public health.

PubMed

Seals, Douglas R

2013-07-15

The term 'translational research' was coined 20 years ago and has become a guiding influence in biomedical research. It refers to a process by which the findings of basic research are extended to the clinical research setting (bench to bedside) and then to clinical practice and eventually health policy (bedside to community). It is a dynamic, multidisciplinary research approach. The concept of translational physiology applies the translational research model to the physiological sciences. It differs from the traditional areas of integrative and clinical physiology by its broad investigative scope of basic research to community health. Translational physiology offers exciting opportunities, but presently is under-developed and -utilized. A key challenge will be to expand physiological research by extending investigations to communities of patients and healthy (or at risk) individuals. This will allow bidirectional physiological investigation throughout the translational continuum: basic research observations can be studied up to the population level, and mechanisms can be assessed by 'reverse translation' in clinical research settings and preclinical models based on initial observations made in populations. Examples of translational physiology questions, experimental approaches, roadblocks and strategies for promotion are discussed. Translational physiology provides a novel framework for physiology programs and an investigational platform for physiologists to study function from molecular events to public health. It holds promise for enhancing the completeness and societal impact of our work, while further solidifying the critical role of physiology in the biomedical research enterprise.

Translational physiology: from molecules to public health

PubMed Central

Seals, Douglas R

2013-01-01

The term ‘translational research’ was coined 20 years ago and has become a guiding influence in biomedical research. It refers to a process by which the findings of basic research are extended to the clinical research setting (bench to bedside) and then to clinical practice and eventually health policy (bedside to community). It is a dynamic, multidisciplinary research approach. The concept of translational physiology applies the translational research model to the physiological sciences. It differs from the traditional areas of integrative and clinical physiology by its broad investigative scope of basic research to community health. Translational physiology offers exciting opportunities, but presently is under-developed and -utilized. A key challenge will be to expand physiological research by extending investigations to communities of patients and healthy (or at risk) individuals. This will allow bidirectional physiological investigation throughout the translational continuum: basic research observations can be studied up to the population level, and mechanisms can be assessed by ‘reverse translation’ in clinical research settings and preclinical models based on initial observations made in populations. Examples of translational physiology questions, experimental approaches, roadblocks and strategies for promotion are discussed. Translational physiology provides a novel framework for physiology programs and an investigational platform for physiologists to study function from molecular events to public health. It holds promise for enhancing the completeness and societal impact of our work, while further solidifying the critical role of physiology in the biomedical research enterprise. PMID:23732641

Considerations for Reporting Finite Element Analysis Studies in Biomechanics

PubMed Central

Erdemir, Ahmet; Guess, Trent M.; Halloran, Jason; Tadepalli, Srinivas C.; Morrison, Tina M.

2012-01-01

Simulation-based medicine and the development of complex computer models of biological structures is becoming ubiquitous for advancing biomedical engineering and clinical research. Finite element analysis (FEA) has been widely used in the last few decades to understand and predict biomechanical phenomena. Modeling and simulation approaches in biomechanics are highly interdisciplinary, involving novice and skilled developers in all areas of biomedical engineering and biology. While recent advances in model development and simulation platforms offer a wide range of tools to investigators, the decision making process during modeling and simulation has become more opaque. Hence, reliability of such models used for medical decision making and for driving multiscale analysis comes into question. Establishing guidelines for model development and dissemination is a daunting task, particularly with the complex and convoluted models used in FEA. Nonetheless, if better reporting can be established, researchers will have a better understanding of a model’s value and the potential for reusability through sharing will be bolstered. Thus, the goal of this document is to identify resources and considerate reporting parameters for FEA studies in biomechanics. These entail various levels of reporting parameters for model identification, model structure, simulation structure, verification, validation, and availability. While we recognize that it may not be possible to provide and detail all of the reporting considerations presented, it is possible to establish a level of confidence with selective use of these parameters. More detailed reporting, however, can establish an explicit outline of the decision-making process in simulation-based analysis for enhanced reproducibility, reusability, and sharing. PMID:22236526

Exploiting semantic patterns over biomedical knowledge graphs for predicting treatment and causative relations.

PubMed

Bakal, Gokhan; Talari, Preetham; Kakani, Elijah V; Kavuluru, Ramakanth

2018-06-01

Identifying new potential treatment options for medical conditions that cause human disease burden is a central task of biomedical research. Since all candidate drugs cannot be tested with animal and clinical trials, in vitro approaches are first attempted to identify promising candidates. Likewise, identifying different causal relations between biomedical entities is also critical to understand biomedical processes. Generally, natural language processing (NLP) and machine learning are used to predict specific relations between any given pair of entities using the distant supervision approach. To build high accuracy supervised predictive models to predict previously unknown treatment and causative relations between biomedical entities based only on semantic graph pattern features extracted from biomedical knowledge graphs. We used 7000 treats and 2918 causes hand-curated relations from the UMLS Metathesaurus to train and test our models. Our graph pattern features are extracted from simple paths connecting biomedical entities in the SemMedDB graph (based on the well-known SemMedDB database made available by the U.S. National Library of Medicine). Using these graph patterns connecting biomedical entities as features of logistic regression and decision tree models, we computed mean performance measures (precision, recall, F-score) over 100 distinct 80-20% train-test splits of the datasets. For all experiments, we used a positive:negative class imbalance of 1:10 in the test set to model relatively more realistic scenarios. Our models predict treats and causes relations with high F-scores of 99% and 90% respectively. Logistic regression model coefficients also help us identify highly discriminative patterns that have an intuitive interpretation. We are also able to predict some new plausible relations based on false positives that our models scored highly based on our collaborations with two physician co-authors. Finally, our decision tree models are able to retrieve over 50% of treatment relations from a recently created external dataset. We employed semantic graph patterns connecting pairs of candidate biomedical entities in a knowledge graph as features to predict treatment/causative relations between them. We provide what we believe is the first evidence in direct prediction of biomedical relations based on graph features. Our work complements lexical pattern based approaches in that the graph patterns can be used as additional features for weakly supervised relation prediction. Copyright © 2018 Elsevier Inc. All rights reserved.

The next generation of similarity measures that fully explore the semantics in biomedical ontologies.

PubMed

Couto, Francisco M; Pinto, H Sofia

2013-10-01

There is a prominent trend to augment and improve the formality of biomedical ontologies. For example, this is shown by the current effort on adding description logic axioms, such as disjointness. One of the key ontology applications that can take advantage of this effort is the conceptual (functional) similarity measurement. The presence of description logic axioms in biomedical ontologies make the current structural or extensional approaches weaker and further away from providing sound semantics-based similarity measures. Although beneficial in small ontologies, the exploration of description logic axioms by semantics-based similarity measures is computational expensive. This limitation is critical for biomedical ontologies that normally contain thousands of concepts. Thus in the process of gaining their rightful place, biomedical functional similarity measures have to take the journey of finding how this rich and powerful knowledge can be fully explored while keeping feasible computational costs. This manuscript aims at promoting and guiding the development of compelling tools that deliver what the biomedical community will require in a near future: a next-generation of biomedical similarity measures that efficiently and fully explore the semantics present in biomedical ontologies.

A Pilot Study of Biomedical Text Comprehension using an Attention-Based Deep Neural Reader: Design and Experimental Analysis

PubMed Central

Lee, Kyubum; Kim, Byounggun; Jeon, Minji; Kim, Jihye; Tan, Aik Choon

2018-01-01

Background With the development of artificial intelligence (AI) technology centered on deep-learning, the computer has evolved to a point where it can read a given text and answer a question based on the context of the text. Such a specific task is known as the task of machine comprehension. Existing machine comprehension tasks mostly use datasets of general texts, such as news articles or elementary school-level storybooks. However, no attempt has been made to determine whether an up-to-date deep learning-based machine comprehension model can also process scientific literature containing expert-level knowledge, especially in the biomedical domain. Objective This study aims to investigate whether a machine comprehension model can process biomedical articles as well as general texts. Since there is no dataset for the biomedical literature comprehension task, our work includes generating a large-scale question answering dataset using PubMed and manually evaluating the generated dataset. Methods We present an attention-based deep neural model tailored to the biomedical domain. To further enhance the performance of our model, we used a pretrained word vector and biomedical entity type embedding. We also developed an ensemble method of combining the results of several independent models to reduce the variance of the answers from the models. Results The experimental results showed that our proposed deep neural network model outperformed the baseline model by more than 7% on the new dataset. We also evaluated human performance on the new dataset. The human evaluation result showed that our deep neural model outperformed humans in comprehension by 22% on average. Conclusions In this work, we introduced a new task of machine comprehension in the biomedical domain using a deep neural model. Since there was no large-scale dataset for training deep neural models in the biomedical domain, we created the new cloze-style datasets Biomedical Knowledge Comprehension Title (BMKC_T) and Biomedical Knowledge Comprehension Last Sentence (BMKC_LS) (together referred to as BioMedical Knowledge Comprehension) using the PubMed corpus. The experimental results showed that the performance of our model is much higher than that of humans. We observed that our model performed consistently better regardless of the degree of difficulty of a text, whereas humans have difficulty when performing biomedical literature comprehension tasks that require expert level knowledge. PMID:29305341

Company Profile: Selventa, Inc.

PubMed

Fryburg, David A; Latino, Louis J; Tagliamonte, John; Kenney, Renee D; Song, Diane H; Levine, Arnold J; de Graaf, David

2012-08-01

Selventa, Inc. (MA, USA) is a biomarker discovery company that enables personalized healthcare. Originally founded as Genstruct, Inc., Selventa has undergone significant evolution from a technology-based service provider to an active partner in the development of diagnostic tests, functioning as a molecular dashboard of disease activity using a unique platform. As part of that evolution, approximately 2 years ago the company was rebranded as Selventa to reflect its new identity and mission. The contributions to biomedical research by Selventa are based on in silico, reverse-engineering methods to determine biological causality. That is, given a set of in vitro or in vivo biological observations, which biological mechanisms can explain the measured results? Facilitated by a large and carefully curated knowledge base, these in silico methods generated new insights into the mechanisms driving a disease. As Selventa's methods would enable biomarker discovery and be directly applicable to generating novel diagnostics, the scientists at Selventa have focused on the development of predictive biomarkers of response in autoimmune and oncologic diseases. Selventa is presently building a portfolio of independent, as well as partnered, biomarker projects with the intention to create diagnostic tests that predict response to therapy.

Energy Analysis of Decoders for Rakeness-Based Compressed Sensing of ECG Signals.

PubMed

Pareschi, Fabio; Mangia, Mauro; Bortolotti, Daniele; Bartolini, Andrea; Benini, Luca; Rovatti, Riccardo; Setti, Gianluca

2017-12-01

In recent years, compressed sensing (CS) has proved to be effective in lowering the power consumption of sensing nodes in biomedical signal processing devices. This is due to the fact the CS is capable of reducing the amount of data to be transmitted to ensure correct reconstruction of the acquired waveforms. Rakeness-based CS has been introduced to further reduce the amount of transmitted data by exploiting the uneven distribution to the sensed signal energy. Yet, so far no thorough analysis exists on the impact of its adoption on CS decoder performance. The latter point is of great importance, since body-area sensor network architectures may include intermediate gateway nodes that receive and reconstruct signals to provide local services before relaying data to a remote server. In this paper, we fill this gap by showing that rakeness-based design also improves reconstruction performance. We quantify these findings in the case of ECG signals and when a variety of reconstruction algorithms are used either in a low-power microcontroller or a heterogeneous mobile computing platform.

Carbon-Based Nanomaterials: Multi-Functional Materials for Biomedical Engineering

PubMed Central

Cha, Chaenyung; Shin, Su Ryon; Annabi, Nasim; Dokmeci, Mehmet R.; Khademhosseini, Ali

2013-01-01

Functional carbon-based nanomaterials (CBNs) have become important due to their unique combinations of chemical and physical properties (i.e., thermal and electrical conductivity, high mechanical strength, and optical properties), extensive research efforts are being made to utilize these materials for various industrial applications, such as high-strength materials and electronics. These advantageous properties of CBNs are also actively investigated in several areas of biomedical engineering. This Perspective highlights different types of carbon-based nanomaterials currently used in biomedical applications. PMID:23560817

Carbon-based nanomaterials: multifunctional materials for biomedical engineering.

PubMed

Cha, Chaenyung; Shin, Su Ryon; Annabi, Nasim; Dokmeci, Mehmet R; Khademhosseini, Ali

2013-04-23

Functional carbon-based nanomaterials (CBNs) have become important due to their unique combinations of chemical and physical properties (i.e., thermal and electrical conductivity, high mechanical strength, and optical properties), and extensive research efforts are being made to utilize these materials for various industrial applications, such as high-strength materials and electronics. These advantageous properties of CBNs are also actively investigated in several areas of biomedical engineering. This Perspective highlights different types of carbon-based nanomaterials currently used in biomedical applications.

A microchip fabricated with a vapor-diffusion self-assembled-monolayer method to transport droplets across superhydrophobic to hydrophilic surfaces.

PubMed

Lai, Yu-Hsuan; Yang, Jing-Tang; Shieh, Dar-Bin

2010-02-21

A wettability gradient to transport a droplet across superhydrophobic to hydrophilic surfaces is fabricated on combining a structure gradient and a self-assembled-monolayer (SAM) gradient. The combination of these two gradients is realized with a simple but versatile SAM technique, in which the textured silicon wafer strip is placed vertically in a bottle that contains a decyltrichlorosilane solution to form concurrently a saturated SAM below the liquid surface and a wettability gradient above. The platform fabricated in this way has a water-contact angle from 151.2 degrees to 39.7 degrees; the self-transport distance is hence increased significantly to about 9 mm. A theoretical model that approximates the shape of a moving drop to a spheroidal cap is developed to predict the self-transport behavior. Satisfactory agreement is shown for most regions except where the hysteresis effect is unmeasurable and an unsymmetrical deformation occurs. A double-directional gradient surface to alter the direction of movement of a droplet is also realized. The platforms we developed serve not only to transport a fluid over a long distance but also for a broad spectrum of biomedical applications such as protein adsorption, cell adhesion and DNA-based biosensors.

Generation of a new Gateway-compatible inducible lentiviral vector platform allowing easy derivation of co-transduced cells.

PubMed

De Groote, Philippe; Grootjans, Sasker; Lippens, Saskia; Eichperger, Chantal; Leurs, Kirsten; Kahr, Irene; Tanghe, Giel; Bruggeman, Inge; De Schamphelaire, Wouter; Urwyler, Corinne; Vandenabeele, Peter; Haustraete, Jurgen; Declercq, Wim

2016-01-01

In contrast to most common gene delivery techniques, lentiviral vectors allow targeting of almost any mammalian cell type, even non-dividing cells, and they stably integrate in the genome. Therefore, these vectors are a very powerful tool for biomedical research. Here we report the generation of a versatile new set of 22 lentiviral vectors with broad applicability in multiple research areas. In contrast to previous systems, our platform provides a choice between constitutive and/or conditional expression and six different C-terminal fusions. Furthermore, two compatible selection markers enable the easy derivation of stable cell lines co-expressing differently tagged transgenes in a constitutive or inducible manner. We show that all of the vector features are functional and that they contribute to transgene overexpression in proof-of-principle experiments.

Genomically Encoded Analog Memory with Precise In vivo DNA Writing in Living Cell Populations

PubMed Central

Farzadfard, Fahim; Lu, Timothy K.

2014-01-01

Cellular memory is crucial to many natural biological processes and for sophisticated synthetic-biology applications. Existing cellular memories rely on epigenetic switches or recombinases, which are limited in scalability and recording capacity. Here, we use the DNA of living cell populations as genomic ‘tape recorders’ for the analog and distributed recording of long-term event histories. We describe a platform for generating single-stranded DNA (ssDNA) in vivo in response to arbitrary transcriptional signals. When co-expressed with a recombinase, these intracellularly expressed ssDNAs target specific genomic DNA addresses, resulting in precise mutations that accumulate in cell populations as a function of the magnitude and duration of the inputs. This platform could enable long-term cellular recorders for environmental and biomedical applications, biological state machines, and enhanced genome engineering strategies. PMID:25395541

Privacy preserving interactive record linkage (PPIRL)

PubMed Central

Kum, Hye-Chung; Krishnamurthy, Ashok; Machanavajjhala, Ashwin; Reiter, Michael K; Ahalt, Stanley

2014-01-01

Objective Record linkage to integrate uncoordinated databases is critical in biomedical research using Big Data. Balancing privacy protection against the need for high quality record linkage requires a human–machine hybrid system to safely manage uncertainty in the ever changing streams of chaotic Big Data. Methods In the computer science literature, private record linkage is the most published area. It investigates how to apply a known linkage function safely when linking two tables. However, in practice, the linkage function is rarely known. Thus, there are many data linkage centers whose main role is to be the trusted third party to determine the linkage function manually and link data for research via a master population list for a designated region. Recently, a more flexible computerized third-party linkage platform, Secure Decoupled Linkage (SDLink), has been proposed based on: (1) decoupling data via encryption, (2) obfuscation via chaffing (adding fake data) and universe manipulation; and (3) minimum information disclosure via recoding. Results We synthesize this literature to formalize a new framework for privacy preserving interactive record linkage (PPIRL) with tractable privacy and utility properties and then analyze the literature using this framework. Conclusions Human-based third-party linkage centers for privacy preserving record linkage are the accepted norm internationally. We find that a computer-based third-party platform that can precisely control the information disclosed at the micro level and allow frequent human interaction during the linkage process, is an effective human–machine hybrid system that significantly improves on the linkage center model both in terms of privacy and utility. PMID:24201028

[A web-based biomedical image mosaicing system].

PubMed

Zhang, Meng; Yan, Zhuang-zhi; Pan, Zhi-jun; Shao, Shi-jie

2006-11-01

This paper describes a web service for biomedical image mosaicing. A web site based on CGI (Common Gateway Interface) is implemented. The system is based on Browser/Server model and is tested in www. Finally implementation examples and experiment results are provided.

A new pivoting and iterative text detection algorithm for biomedical images.

PubMed

Xu, Songhua; Krauthammer, Michael

2010-12-01

There is interest to expand the reach of literature mining to include the analysis of biomedical images, which often contain a paper's key findings. Examples include recent studies that use Optical Character Recognition (OCR) to extract image text, which is used to boost biomedical image retrieval and classification. Such studies rely on the robust identification of text elements in biomedical images, which is a non-trivial task. In this work, we introduce a new text detection algorithm for biomedical images based on iterative projection histograms. We study the effectiveness of our algorithm by evaluating the performance on a set of manually labeled random biomedical images, and compare the performance against other state-of-the-art text detection algorithms. We demonstrate that our projection histogram-based text detection approach is well suited for text detection in biomedical images, and that the iterative application of the algorithm boosts performance to an F score of .60. We provide a C++ implementation of our algorithm freely available for academic use. Copyright © 2010 Elsevier Inc. All rights reserved.

NIR‐Triggered Crystal Phase Transformation of NiTi‐Layered Double Hydroxides Films for Localized Chemothermal Tumor Therapy

PubMed Central

Wang, Donghui; Ge, Naijian; Yang, Tingting; Peng, Feng; Qiao, Yuqin; Li, Qianwen

2018-01-01

Abstract Construction of localized drug‐eluting systems with synergistic chemothermal tumor‐killing abilities is promising for biomedical implants directly contacting with tumor tissues. In this study, an intelligent and biocompatible drug‐loading platform, based on a gold nanorods‐modified butyrate‐inserted NiTi‐layered double hydroxides film (Au@LDH/B), is prepared on the surface of nitinol alloy. The prepared films function as drug‐loading “sponges,” which pump butyrate out under near‐infrared (NIR) irradiation and resorb drugs in water when the NIR laser is shut off. The stimuli‐responsive release of butyrate is verified to be related with the NIR‐triggered crystal phase transformation of Au@LDH/B. In vitro and in vivo studies reveal that the prepared films possess excellent biosafety and high efficiency in synergistic thermochemo tumor therapy, showing a promising application in the construction of localized stimuli‐responsive drug‐delivery systems. PMID:29721424

Home e-health system integration in the Smart Home through a common media server.

PubMed

Pau, I; Seoane, F; Lindecrantz, K; Valero, M A; Carracedo, J

2009-01-01

Home e-health systems and services are revealed as one of the most important challenges to promote Quality of Life related to Health in the Information Society. Leading companies have worked on e-health systems although the majority of them are addressed to hospital or primary care settings. The solution detailed in this paper offers a personal health system to be integrated with Smart Home services platform to support home based e-care. Thus, the home e-health system and architecture detailed in this research work is ready to supply a seamless personal care solution both from the biomedical data analysis, service provision, security guarantee and information management s point of view. The solution is ready to be integrated within the Accessible Digital Home, a living lab managed by Universidad Politécnica de Madrid for R&D activities.

Structure Elucidation of Unknown Metabolites in Metabolomics by Combined NMR and MS/MS Prediction

DOE PAGES

Boiteau, Rene M.; Hoyt, David W.; Nicora, Carrie D.; ...

2018-01-17

Here, we introduce a cheminformatics approach that combines highly selective and orthogonal structure elucidation parameters; accurate mass, MS/MS (MS 2), and NMR in a single analysis platform to accurately identify unknown metabolites in untargeted studies. The approach starts with an unknown LC-MS feature, and then combines the experimental MS/MS and NMR information of the unknown to effectively filter the false positive candidate structures based on their predicted MS/MS and NMR spectra. We demonstrate the approach on a model mixture and then we identify an uncatalogued secondary metabolite in Arabidopsis thaliana. The NMR/MS 2 approach is well suited for discovery ofmore » new metabolites in plant extracts, microbes, soils, dissolved organic matter, food extracts, biofuels, and biomedical samples, facilitating the identification of metabolites that are not present in experimental NMR and MS metabolomics databases.« less

"Clickable" Polymeric Nanofibers through Hydrophilic-Hydrophobic Balance: Fabrication of Robust Biomolecular Immobilization Platforms.

PubMed

Kalaoglu-Altan, Ozlem I; Sanyal, Rana; Sanyal, Amitav

2015-05-11

Fabrication of hydrophilic polymeric nanofibers that undergo facile and selective functionalization through metal catalyst-free Diels-Alder "click" reaction in aqueous environment is outlined. Electrospinning of copolymers containing an electron-rich furan moiety, hydrophobic methyl methacrylate units and hydrophilic poly(ethylene glycol)s as side chains provide specifically functionalizable yet antibiofouling fibers that remain stable in aqueous media due to appropriate hydrophobic hydrophilic balance. Efficient functionalization of these nanofibers is accomplished through the Diels-Alder reaction by exposing them to maleimide-containing molecules and ligands. Diels-Alder conjugation based functionalization is demonstrated through attachment of fluorescein-maleimide and a maleimide tethered biotin ligand. Biotinylated nanofibers were utilized to mediate immobilization of the protein streptavidin, as well as streptavidin coated quantum dots. Facile fabrication from readily available polymers and their effective functionalization under mild and reagent-free conditions in aqueous media make these "clickable" nanofibers attractive candidates as functionalizable scaffolds for various biomedical applications.

Structure Elucidation of Unknown Metabolites in Metabolomics by Combined NMR and MS/MS Prediction

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

Boiteau, Rene M.; Hoyt, David W.; Nicora, Carrie D.

Here, we introduce a cheminformatics approach that combines highly selective and orthogonal structure elucidation parameters; accurate mass, MS/MS (MS 2), and NMR in a single analysis platform to accurately identify unknown metabolites in untargeted studies. The approach starts with an unknown LC-MS feature, and then combines the experimental MS/MS and NMR information of the unknown to effectively filter the false positive candidate structures based on their predicted MS/MS and NMR spectra. We demonstrate the approach on a model mixture and then we identify an uncatalogued secondary metabolite in Arabidopsis thaliana. The NMR/MS 2 approach is well suited for discovery ofmore » new metabolites in plant extracts, microbes, soils, dissolved organic matter, food extracts, biofuels, and biomedical samples, facilitating the identification of metabolites that are not present in experimental NMR and MS metabolomics databases.« less

AND logic-like pH- and light-dual controlled drug delivery by surface modified mesoporous silica nanoparticles.

PubMed

Zhao, Junwei; He, Zhaoshuai; Li, Biao; Cheng, Tanyu; Liu, Guohua

2017-04-01

Recently, the controlled drug delivery system has become a potential platform for biomedical application. Herein, we developed a pH and light-dual controlled cargo release system exhibiting AND logic based on MCM-41 mesoporous silica nanoparticles, which was surface modified using β-cyclodextrin (β-CD) with imine bond and azobenzene derivative. The complex of β-CD and azobenzene derivative effectively blocked the cargo delivery in pH=7.0 phosphate buffered saline (PBS) solution without 365nm UV light irradiation. The cargo was fully released when both factors of acidic environment (pH=5.0 PBS) and 365nm UV light irradiation were satisfied, meanwhile only very little cargo was delivered if one factor was satisfied. The result also demonstrates that the opening/closing of the gate and the release of the cargo in small portions can be controlled. Copyright © 2016 Elsevier B.V. All rights reserved.

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.

Structure Elucidation of Unknown Metabolites in Metabolomics by Combined NMR and MS/MS Prediction

PubMed Central

Hoyt, David W.; Nicora, Carrie D.; Kinmonth-Schultz, Hannah A.; Ward, Joy K.

2018-01-01

We introduce a cheminformatics approach that combines highly selective and orthogonal structure elucidation parameters; accurate mass, MS/MS (MS2), and NMR into a single analysis platform to accurately identify unknown metabolites in untargeted studies. The approach starts with an unknown LC-MS feature, and then combines the experimental MS/MS and NMR information of the unknown to effectively filter out the false positive candidate structures based on their predicted MS/MS and NMR spectra. We demonstrate the approach on a model mixture, and then we identify an uncatalogued secondary metabolite in Arabidopsis thaliana. The NMR/MS2 approach is well suited to the discovery of new metabolites in plant extracts, microbes, soils, dissolved organic matter, food extracts, biofuels, and biomedical samples, facilitating the identification of metabolites that are not present in experimental NMR and MS metabolomics databases. PMID:29342073

A fluorescent graphitic carbon nitride nanosheet biosensor for highly sensitive, label-free detection of alkaline phosphatase.

PubMed

Xiang, Mei-Hao; Liu, Jin-Wen; Li, Na; Tang, Hao; Yu, Ru-Qin; Jiang, Jian-Hui

2016-02-28

Graphitic C3N4 (g-C3N4) nanosheets provide an attractive option for bioprobes and bioimaging applications. Utilizing highly fluorescent and water-dispersible ultrathin g-C3N4 nanosheets, a highly sensitive, selective and label-free biosensor has been developed for ALP detection for the first time. The developed approach utilizes a natural substrate of ALP in biological systems and thus affords very high catalytic efficiency. This novel biosensor is demonstrated to enable quantitative analysis of ALP in a wide range from 0.1 to 1000 U L(-1) with a low detection limit of 0.08 U L(-1), which is among the most sensitive assays for ALP. It is expected that the developed method may provide a low-cost, convenient, rapid and highly sensitive platform for ALP-based clinical diagnostics and biomedical applications.

Engineering Cell-Cell Signaling

PubMed Central

Milano, Daniel F.; Natividad, Robert J.; Asthagiri, Anand R.

2014-01-01

Juxtacrine cell-cell signaling mediated by the direct interaction of adjoining mammalian cells is arguably the mode of cell communication that is most recalcitrant to engineering. Overcoming this challenge is crucial for progress in biomedical applications, such as tissue engineering, regenerative medicine, immune system engineering and therapeutic design. Here, we describe the significant advances that have been made in developing synthetic platforms (materials and devices) and synthetic cells (cell surface engineering and synthetic gene circuits) to modulate juxtacrine cell-cell signaling. In addition, significant progress has been made in elucidating design rules and strategies to modulate juxtacrine signaling based on quantitative, engineering analysis of the mechanical and regulatory role of juxtacrine signals in the context of other cues and physical constraints in the microenvironment. These advances in engineering juxtacrine signaling lay a strong foundation for an integrative approach to utilizing synthetic cells, advanced ‘chassis’ and predictive modeling to engineer the form and function of living tissues. PMID:23856592

SEMCARE: Multilingual Semantic Search in Semi-Structured Clinical Data.

PubMed

López-García, Pablo; Kreuzthaler, Markus; Schulz, Stefan; Scherr, Daniel; Daumke, Philipp; Markó, Kornél; Kors, Jan A; van Mulligen, Erik M; Wang, Xinkai; Gonna, Hanney; Behr, Elijah; Honrado, Ángel

2016-01-01

The vast amount of clinical data in electronic health records constitutes a great potential for secondary use. However, most of this content consists of unstructured or semi-structured texts, which is difficult to process. Several challenges are still pending: medical language idiosyncrasies in different natural languages, and the large variety of medical terminology systems. In this paper we present SEMCARE, a European initiative designed to minimize these problems by providing a multi-lingual platform (English, German, and Dutch) that allows users to express complex queries and obtain relevant search results from clinical texts. SEMCARE is based on a selection of adapted biomedical terminologies, together with Apache UIMA and Apache Solr as open source state-of-the-art natural language pipeline and indexing technologies. SEMCARE has been deployed and is currently being tested at three medical institutions in the UK, Austria, and the Netherlands, showing promising results in a cardiology use case.

Orthogonal Luciferase-Luciferin Pairs for Bioluminescence Imaging.

PubMed

Jones, Krysten A; Porterfield, William B; Rathbun, Colin M; McCutcheon, David C; Paley, Miranda A; Prescher, Jennifer A

2017-02-15

Bioluminescence imaging with luciferase-luciferin pairs is widely used in biomedical research. Several luciferases have been identified in nature, and many have been adapted for tracking cells in whole animals. Unfortunately, the optimal luciferases for imaging in vivo utilize the same substrate and therefore cannot easily differentiate multiple cell types in a single subject. To develop a broader set of distinguishable probes, we crafted custom luciferins that can be selectively processed by engineered luciferases. Libraries of mutant enzymes were iteratively screened with sterically modified luciferins, and orthogonal enzyme-substrate "hits" were identified. These tools produced light when complementary enzyme-substrate partners interacted both in vitro and in cultured cell models. Based on their selectivity, these designer pairs will bolster multicomponent imaging and enable the direct interrogation of cell networks not currently possible with existing tools. Our screening platform is also general and will expedite the identification of more unique luciferases and luciferins, further expanding the bioluminescence toolkit.

Rapid automated classification of anesthetic depth levels using GPU based parallelization of neural networks.

PubMed

Peker, Musa; Şen, Baha; Gürüler, Hüseyin

2015-02-01

The effect of anesthesia on the patient is referred to as depth of anesthesia. Rapid classification of appropriate depth level of anesthesia is a matter of great importance in surgical operations. Similarly, accelerating classification algorithms is important for the rapid solution of problems in the field of biomedical signal processing. However numerous, time-consuming mathematical operations are required when training and testing stages of the classification algorithms, especially in neural networks. In this study, to accelerate the process, parallel programming and computing platform (Nvidia CUDA) facilitates dramatic increases in computing performance by harnessing the power of the graphics processing unit (GPU) was utilized. The system was employed to detect anesthetic depth level on related electroencephalogram (EEG) data set. This dataset is rather complex and large. Moreover, the achieving more anesthetic levels with rapid response is critical in anesthesia. The proposed parallelization method yielded high accurate classification results in a faster time.

The forthcoming era of precision medicine.

PubMed

Gamulin, Stjepan

2016-11-01

The aim of this essay is to present the definition and principles of personalized or precision medicine, the perspective and barriers to its development and clinical application. The implementation of precision medicine in health care requires the coordinated efforts of all health care stakeholders (the biomedical community, government, regulatory bodies, patients' groups). Particularly, translational research with the integration of genomic and comprehensive data from all levels of the organism ("big data"), development of bioinformatics platforms enabling network analysis of disease etiopathogenesis, development of a legislative framework for handling personal data, and new paradigms of medical education are necessary for successful application of the concept of precision medicine in health care. In the present and future era of precision medicine, the collaboration of all participants in health care is necessary for its realization, resulting in improvement of diagnosis, prevention and therapy, based on a holistic, individually tailored approach. Copyright © 2016 by Academy of Sciences and Arts of Bosnia and Herzegovina.

BIOSSES: a semantic sentence similarity estimation system for the biomedical domain.

PubMed

Sogancioglu, Gizem; Öztürk, Hakime; Özgür, Arzucan

2017-07-15

The amount of information available in textual format is rapidly increasing in the biomedical domain. Therefore, natural language processing (NLP) applications are becoming increasingly important to facilitate the retrieval and analysis of these data. Computing the semantic similarity between sentences is an important component in many NLP tasks including text retrieval and summarization. A number of approaches have been proposed for semantic sentence similarity estimation for generic English. However, our experiments showed that such approaches do not effectively cover biomedical knowledge and produce poor results for biomedical text. We propose several approaches for sentence-level semantic similarity computation in the biomedical domain, including string similarity measures and measures based on the distributed vector representations of sentences learned in an unsupervised manner from a large biomedical corpus. In addition, ontology-based approaches are presented that utilize general and domain-specific ontologies. Finally, a supervised regression based model is developed that effectively combines the different similarity computation metrics. A benchmark data set consisting of 100 sentence pairs from the biomedical literature is manually annotated by five human experts and used for evaluating the proposed methods. The experiments showed that the supervised semantic sentence similarity computation approach obtained the best performance (0.836 correlation with gold standard human annotations) and improved over the state-of-the-art domain-independent systems up to 42.6% in terms of the Pearson correlation metric. A web-based system for biomedical semantic sentence similarity computation, the source code, and the annotated benchmark data set are available at: http://tabilab.cmpe.boun.edu.tr/BIOSSES/ . gizemsogancioglu@gmail.com or arzucan.ozgur@boun.edu.tr. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com

A novel end-to-end classifier using domain transferred deep convolutional neural networks for biomedical images.

PubMed

Pang, Shuchao; Yu, Zhezhou; Orgun, Mehmet A

2017-03-01

Highly accurate classification of biomedical images is an essential task in the clinical diagnosis of numerous medical diseases identified from those images. Traditional image classification methods combined with hand-crafted image feature descriptors and various classifiers are not able to effectively improve the accuracy rate and meet the high requirements of classification of biomedical images. The same also holds true for artificial neural network models directly trained with limited biomedical images used as training data or directly used as a black box to extract the deep features based on another distant dataset. In this study, we propose a highly reliable and accurate end-to-end classifier for all kinds of biomedical images via deep learning and transfer learning. We first apply domain transferred deep convolutional neural network for building a deep model; and then develop an overall deep learning architecture based on the raw pixels of original biomedical images using supervised training. In our model, we do not need the manual design of the feature space, seek an effective feature vector classifier or segment specific detection object and image patches, which are the main technological difficulties in the adoption of traditional image classification methods. Moreover, we do not need to be concerned with whether there are large training sets of annotated biomedical images, affordable parallel computing resources featuring GPUs or long times to wait for training a perfect deep model, which are the main problems to train deep neural networks for biomedical image classification as observed in recent works. With the utilization of a simple data augmentation method and fast convergence speed, our algorithm can achieve the best accuracy rate and outstanding classification ability for biomedical images. We have evaluated our classifier on several well-known public biomedical datasets and compared it with several state-of-the-art approaches. We propose a robust automated end-to-end classifier for biomedical images based on a domain transferred deep convolutional neural network model that shows a highly reliable and accurate performance which has been confirmed on several public biomedical image datasets. Copyright © 2017 Elsevier Ireland Ltd. All rights reserved.

Exploration of Nanoparticle-Mediated Photothermal Effect of TMB-H2O2 Colorimetric System and Its Application in a Visual Quantitative Photothermal Immunoassay.

PubMed

Fu, Guanglei; Sanjay, Sharma T; Zhou, Wan; Brekken, Rolf A; Kirken, Robert A; Li, XiuJun

2018-05-01

The exploration of new physical and chemical properties of materials and their innovative application in different fields are of great importance to advance analytical chemistry, material science, and other important fields. Herein, we, for the first time, discovered the photothermal effect of an iron oxide nanoparticles (NPs)-mediated TMB (3,3',5,5'-tetramethylbenzidine)-H 2 O 2 colorimetric system, and applied it toward the development of a new NP-mediated photothermal immunoassay platform for visual quantitative biomolecule detection using a thermometer as the signal reader. Using a sandwich-type proof-of-concept immunoassay, we found that the charge transfer complex of the iron oxide NPs-mediated one-electron oxidation product of TMB (oxidized TMB) exhibited not only color changes, but also a strong near-infrared (NIR) laser-driven photothermal effect. Hence, oxidized TMB was explored as a new sensitive photothermal probe to convert the immunoassay signal into heat through the near-infrared laser-driven photothermal effect, enabling simple photothermal immunoassay using a thermometer. Based on the new iron oxide NPs-mediated TMB-H 2 O 2 photothermal immunoassay platform, prostate-specific antigen (PSA) as a model biomarker can be detected at a concentration as low as 1.0 ng·mL -1 in normal human serum. The discovered photothermal effect of the colorimetric system and the developed new photothermal immunoassay platform open up a new horizon for affordable detection of disease biomarkers and have great potential for other important material and biomedical applications of interest.

Scaled Anatomical Model Creation of Biomedical Tomographic Imaging Data and Associated Labels for Subsequent Sub-surface Laser Engraving (SSLE) of Glass Crystals

PubMed Central

Dethlefs, Christopher R.; Piotrowicz, Justin; Van Avermaete, Tony; Maki, Jeff; Gerstler, Steve; Leevy, W. M.

2017-01-01

Biomedical imaging modalities like computed tomography (CT) and magnetic resonance (MR) provide excellent platforms for collecting three-dimensional data sets of patient or specimen anatomy in clinical or preclinical settings. However, the use of a virtual, on-screen display limits the ability of these tomographic images to fully convey the anatomical information embedded within. One solution is to interface a biomedical imaging data set with 3D printing technology to generate a physical replica. Here we detail a complementary method to visualize tomographic imaging data with a hand-held model: Sub Surface Laser Engraving (SSLE) of crystal glass. SSLE offers several unique benefits including: the facile ability to include anatomical labels, as well as a scale bar; streamlined multipart assembly of complex structures in one medium; high resolution in the X, Y, and Z planes; and semi-transparent shells for visualization of internal anatomical substructures. Here we demonstrate the process of SSLE with CT data sets derived from pre-clinical and clinical sources. This protocol will serve as a powerful and inexpensive new tool with which to visualize complex anatomical structures for scientists and students in a number of educational and research settings. PMID:28518066

Biomedical Applications Of Aromatic Azo Compounds: From Chromophore To Pharmacophore.

PubMed

Ali, Yousaf; Hamid, Shafida Abd; Rashid, Umer

2018-05-23

Azo dyes are widely used in textile, fiber, cosmetic, leather, paint and printing industries. Besides their characteristic coloring function, biological properties of certain azo compounds including antibacterial, antiviral, antifungal and cytotoxic are also reported. Azo compounds can be used as drug carriers, either by acting as a 'cargo' that entrap therapeutic agents or by prodrug approach. The drug is released by internal or external stimuli in the region of interest, as observed in colon-targeted drug delivery. Besides drug-like and drug carrier properties, a number of azo dyes are used in cellular staining to visualize cellular components and metabolic processes. However, the biological significance of azo compounds, especially in cancer chemotherapy, is still in its infancy. This may be linked to early findings that declared azo compounds as one of the possible causes of cancer and mutagenesis. Currently, researchers are screening the aromatic azo compounds for their potential biomedical use, including cancer diagnosis and therapy. The medical applications of azo compounds, particularly in cancer research are discussed. The biomedical significance of cis-trans interchange and negative implications of azo compounds are also highlighted in brief. This review may provide the researchers a platform in the quest of more potent therapeutic agents of this class. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Polylactic acid (PLA) controlled delivery carriers for biomedical applications.

PubMed

Tyler, Betty; Gullotti, David; Mangraviti, Antonella; Utsuki, Tadanobu; Brem, Henry

2016-12-15

Polylactic acid (PLA) and its copolymers have a long history of safety in humans and an extensive range of applications. PLA is biocompatible, biodegradable by hydrolysis and enzymatic activity, has a large range of mechanical and physical properties that can be engineered appropriately to suit multiple applications, and has low immunogenicity. Formulations containing PLA have also been Food and Drug Administration (FDA)-approved for multiple applications making PLA suitable for expedited clinical translatability. These biomaterials can be fashioned into sutures, scaffolds, cell carriers, drug delivery systems, and a myriad of fabrications. PLA has been the focus of a multitude of preclinical and clinical testing. Three-dimensional printing has expanded the possibilities of biomedical engineering and has enabled the fabrication of a myriad of platforms for an extensive variety of applications. PLA has been widely used as temporary extracellular matrices in tissue engineering. At the other end of the spectrum, PLA's application as drug-loaded nanoparticle drug carriers, such as liposomes, polymeric nanoparticles, dendrimers, and micelles, can encapsulate otherwise toxic hydrophobic anti-tumor drugs and evade systemic toxicities. The clinical translation of these technologies from preclinical experimental settings is an ever-evolving field with incremental advancements. In this review, some of the biomedical applications of PLA and its copolymers are highlighted and briefly summarized. Copyright © 2016 Elsevier B.V. All rights reserved.

Modeling and Optimization of Class-E Amplifier at Subnominal Condition in a Wireless Power Transfer System for Biomedical Implants.

PubMed

Liu, Hao; Shao, Qi; Fang, Xuelin

2017-02-01

For the class-E amplifier in a wireless power transfer (WPT) system, the design parameters are always determined by the nominal model. However, this model neglects the conduction loss and voltage stress of MOSFET and cannot guarantee the highest efficiency in the WPT system for biomedical implants. To solve this problem, this paper proposes a novel circuit model of the subnominal class-E amplifier. On a WPT platform for capsule endoscope, the proposed model was validated to be effective and the relationship between the amplifier's design parameters and its characteristics was analyzed. At a given duty ratio, the design parameters with the highest efficiency and safe voltage stress are derived and the condition is called 'optimal subnominal condition.' The amplifier's efficiency can reach the highest of 99.3% at the 0.097 duty ratio. Furthermore, at the 0.5 duty ratio, the measured efficiency of the optimal subnominal condition can reach 90.8%, which is 15.2% higher than that of the nominal condition. Then, a WPT experiment with a receiving unit was carried out to validate the feasibility of the optimized amplifier. In general, the design parameters of class-E amplifier in a WPT system for biomedical implants can be determined with the proposed optimization method in this paper.

Supramolecular Biofunctional Materials

PubMed Central

Zhou, Jie; Li, Jie; Du, Xuewen; Xu, Bing

2017-01-01

This review discusses supramolecular biofunctional materials, a novel class of biomaterials formed by small molecules that are held together via noncovalent interactions. The complexity of biology and relevant biomedical problems not only inspire, but also demand effective molecular design for functional materials. Supramolecular biofunctional materials offer (almost) unlimited possibilities and opportunities to address challenging biomedical problems. Rational molecular design of supramolecular biofunctional materials exploit powerful and versatile noncovalent interactions, which offer many advantages, such as responsiveness, reversibility, tunability, biomimicry, modularity, predictability, and, most importantly, adaptiveness. In this review, besides elaborating on the merits of supramolecular biofunctional materials (mainly in the form of hydrogels and/or nanoscale assemblies) resulting from noncovalent interactions, we also discuss the advantages of small peptides as a prevalent molecular platform to generate a wide range of supramolecular biofunctional materials for the applications in drug delivery, tissue engineering, immunology, cancer therapy, fluorescent imaging, and stem cell regulation. This review aims to provide a brief synopsis of recent achievements at the intersection of supramolecular chemistry and biomedical science in hope of contributing to the multidisciplinary research on supramolecular biofunctional materials for a wide range of applications. We envision that supramolecular biofunctional materials will contribute to the development of new therapies that will ultimately lead to a paradigm shift for developing next generation biomaterials for medicine. PMID:28319779

Supramolecular biofunctional materials.

PubMed

Zhou, Jie; Li, Jie; Du, Xuewen; Xu, Bing

2017-06-01

This review discusses supramolecular biofunctional materials, a novel class of biomaterials formed by small molecules that are held together via noncovalent interactions. The complexity of biology and relevant biomedical problems not only inspire, but also demand effective molecular design for functional materials. Supramolecular biofunctional materials offer (almost) unlimited possibilities and opportunities to address challenging biomedical problems. Rational molecular design of supramolecular biofunctional materials exploit powerful and versatile noncovalent interactions, which offer many advantages, such as responsiveness, reversibility, tunability, biomimicry, modularity, predictability, and, most importantly, adaptiveness. In this review, besides elaborating on the merits of supramolecular biofunctional materials (mainly in the form of hydrogels and/or nanoscale assemblies) resulting from noncovalent interactions, we also discuss the advantages of small peptides as a prevalent molecular platform to generate a wide range of supramolecular biofunctional materials for the applications in drug delivery, tissue engineering, immunology, cancer therapy, fluorescent imaging, and stem cell regulation. This review aims to provide a brief synopsis of recent achievements at the intersection of supramolecular chemistry and biomedical science in hope of contributing to the multidisciplinary research on supramolecular biofunctional materials for a wide range of applications. We envision that supramolecular biofunctional materials will contribute to the development of new therapies that will ultimately lead to a paradigm shift for developing next generation biomaterials for medicine. Copyright © 2017 Elsevier Ltd. All rights reserved.

Text mining patents for biomedical knowledge.

PubMed

Rodriguez-Esteban, Raul; Bundschus, Markus

2016-06-01

Biomedical text mining of scientific knowledge bases, such as Medline, has received much attention in recent years. Given that text mining is able to automatically extract biomedical facts that revolve around entities such as genes, proteins, and drugs, from unstructured text sources, it is seen as a major enabler to foster biomedical research and drug discovery. In contrast to the biomedical literature, research into the mining of biomedical patents has not reached the same level of maturity. Here, we review existing work and highlight the associated technical challenges that emerge from automatically extracting facts from patents. We conclude by outlining potential future directions in this domain that could help drive biomedical research and drug discovery. Copyright © 2016 Elsevier Ltd. All rights reserved.

An automated microfluidic platform for C. elegans embryo arraying, phenotyping, and long-term live imaging

NASA Astrophysics Data System (ADS)

Cornaglia, Matteo; Mouchiroud, Laurent; Marette, Alexis; Narasimhan, Shreya; Lehnert, Thomas; Jovaisaite, Virginija; Auwerx, Johan; Gijs, Martin A. M.

2015-05-01

Studies of the real-time dynamics of embryonic development require a gentle embryo handling method, the possibility of long-term live imaging during the complete embryogenesis, as well as of parallelization providing a population’s statistics, while keeping single embryo resolution. We describe an automated approach that fully accomplishes these requirements for embryos of Caenorhabditis elegans, one of the most employed model organisms in biomedical research. We developed a microfluidic platform which makes use of pure passive hydrodynamics to run on-chip worm cultures, from which we obtain synchronized embryo populations, and to immobilize these embryos in incubator microarrays for long-term high-resolution optical imaging. We successfully employ our platform to investigate morphogenesis and mitochondrial biogenesis during the full embryonic development and elucidate the role of the mitochondrial unfolded protein response (UPRmt) within C. elegans embryogenesis. Our method can be generally used for protein expression and developmental studies at the embryonic level, but can also provide clues to understand the aging process and age-related diseases in particular.

Microfluidic Synthesis of Composite Cross-Gradient Materials for Investigating Cell–Biomaterial Interactions

PubMed Central

He, Jiankang; Du, Yanan; Guo, Yuqi; Hancock, Matthew J.; Wang, Ben; Shin, Hyeongho; Wu, Jinhui; Li, Dichen; Khademhosseini, Ali

2010-01-01

Combinatorial material synthesis is a powerful approach for creating composite material libraries for the high-throughput screening of cell–material interactions. Although current combinatorial screening platforms have been tremendously successful in identifying target (termed “hit”) materials from composite material libraries, new material synthesis approaches are needed to further optimize the concentrations and blending ratios of the component materials. Here we employed a microfluidic platform to rapidly synthesize composite materials containing cross-gradients of gelatin and chitosan for investigating cell–biomaterial interactions. The microfluidic synthesis of the cross-gradient was optimized experimentally and theoretically to produce quantitatively controllable variations in the concentrations and blending ratios of the two components. The anisotropic chemical compositions of the gelatin/chitosan cross-gradients were characterized by Fourier transform infrared spectrometry and X-ray photoelectron spectrometry. The three-dimensional (3D) porous gelatin/chitosan cross-gradient materials were shown to regulate the cellular morphology and proliferation of smooth muscle cells (SMCs) in a gradient-dependent manner. We envision that our microfluidic cross-gradient platform may accelerate the material development processes involved in a wide range of biomedical applications. PMID:20721897

New routes to the functionalization patterning and manufacture of graphene-based materials for biomedical applications.

PubMed

De Sanctis, A; Russo, S; Craciun, M F; Alexeev, A; Barnes, M D; Nagareddy, V K; Wright, C D

2018-06-06

Graphene-based materials are being widely explored for a range of biomedical applications, from targeted drug delivery to biosensing, bioimaging and use for antibacterial treatments, to name but a few. In many such applications, it is not graphene itself that is used as the active agent, but one of its chemically functionalized forms. The type of chemical species used for functionalization will play a key role in determining the utility of any graphene-based device in any particular biomedical application, because this determines to a large part its physical, chemical, electrical and optical interactions. However, other factors will also be important in determining the eventual uptake of graphene-based biomedical technologies, in particular the ease and cost of manufacture of proposed device and system designs. In this work, we describe three novel routes for the chemical functionalization of graphene using oxygen, iron chloride and fluorine. We also introduce novel in situ methods for controlling and patterning such functionalization on the micro- and nanoscales. Our approaches are readily transferable to large-scale manufacturing, potentially paving the way for the eventual cost-effective production of functionalized graphene-based materials, devices and systems for a range of important biomedical applications.

Quantum Dot Platform for Single-Cell Molecular Profiling

NASA Astrophysics Data System (ADS)

Zrazhevskiy, Pavel S.

In-depth understanding of the nature of cell physiology and ability to diagnose and control the progression of pathological processes heavily rely on untangling the complexity of intracellular molecular mechanisms and pathways. Therefore, comprehensive molecular profiling of individual cells within the context of their natural tissue or cell culture microenvironment is essential. In principle, this goal can be achieved by tagging each molecular target with a unique reporter probe and detecting its localization with high sensitivity at sub-cellular resolution, primarily via microscopy-based imaging. Yet, neither widely used conventional methods nor more advanced nanoparticle-based techniques have been able to address this task up to date. High multiplexing potential of fluorescent probes is heavily restrained by the inability to uniquely match probes with corresponding molecular targets. This issue is especially relevant for quantum dot probes---while simultaneous spectral imaging of up to 10 different probes is possible, only few can be used concurrently for staining with existing methods. To fully utilize multiplexing potential of quantum dots, it is necessary to design a new staining platform featuring unique assignment of each target to a corresponding quantum dot probe. This dissertation presents two complementary versatile approaches towards achieving comprehensive single-cell molecular profiling and describes engineering of quantum dot probes specifically tailored for each staining method. Analysis of expanded molecular profiles is achieved through augmenting parallel multiplexing capacity with performing several staining cycles on the same specimen in sequential manner. In contrast to other methods utilizing quantum dots or other nanoparticles, which often involve sophisticated probe synthesis, the platform technology presented here takes advantage of simple covalent bioconjugation and non-covalent self-assembly mechanisms for straightforward probe preparation and specimen labeling, requiring no advanced technical skills and being directly applicable for a wide range of molecular profiling studies. Utilization of quantum dot platform for single-cell molecular profiling promises to greatly benefit both biomedical research and clinical diagnostics by providing a tool for addressing phenotypic heterogeneity within large cell populations, opening access to studying low-abundance events often masked or completely erased by batch processing, and elucidating biomarker signatures of diseases critical for accurate diagnostics and targeted therapy.

Multi-field query expansion is effective for biomedical dataset retrieval.

PubMed

Bouadjenek, Mohamed Reda; Verspoor, Karin

2017-01-01

In the context of the bioCADDIE challenge addressing information retrieval of biomedical datasets, we propose a method for retrieval of biomedical data sets with heterogenous schemas through query reformulation. In particular, the method proposed transforms the initial query into a multi-field query that is then enriched with terms that are likely to occur in the relevant datasets. We compare and evaluate two query expansion strategies, one based on the Rocchio method and another based on a biomedical lexicon. We then perform a comprehensive comparative evaluation of our method on the bioCADDIE dataset collection for biomedical retrieval. We demonstrate the effectiveness of our multi-field query method compared to two baselines, with MAP improved from 0.2171 and 0.2669 to 0.2996. We also show the benefits of query expansion, where the Rocchio expanstion method improves the MAP for our two baselines from 0.2171 and 0.2669 to 0.335. We show that the Rocchio query expansion method slightly outperforms the one based on the biomedical lexicon as a source of terms, with an improvement of roughly 3% for MAP. However, the query expansion method based on the biomedical lexicon is much less resource intensive since it does not require computation of any relevance feedback set or any initial execution of the query. Hence, in term of trade-off between efficiency, execution time and retrieval accuracy, we argue that the query expansion method based on the biomedical lexicon offers the best performance for a prototype biomedical data search engine intended to be used at a large scale. In the official bioCADDIE challenge results, although our approach is ranked seventh in terms of the infNDCG evaluation metric, it ranks second in term of P@10 and NDCG. Hence, the method proposed here provides overall good retrieval performance in relation to the approaches of other competitors. Consequently, the observations made in this paper should benefit the development of a Data Discovery Index prototype or the improvement of the existing one. © The Author(s) 2017. Published by Oxford University Press.

Multi-field query expansion is effective for biomedical dataset retrieval

PubMed Central

2017-01-01

Abstract In the context of the bioCADDIE challenge addressing information retrieval of biomedical datasets, we propose a method for retrieval of biomedical data sets with heterogenous schemas through query reformulation. In particular, the method proposed transforms the initial query into a multi-field query that is then enriched with terms that are likely to occur in the relevant datasets. We compare and evaluate two query expansion strategies, one based on the Rocchio method and another based on a biomedical lexicon. We then perform a comprehensive comparative evaluation of our method on the bioCADDIE dataset collection for biomedical retrieval. We demonstrate the effectiveness of our multi-field query method compared to two baselines, with MAP improved from 0.2171 and 0.2669 to 0.2996. We also show the benefits of query expansion, where the Rocchio expanstion method improves the MAP for our two baselines from 0.2171 and 0.2669 to 0.335. We show that the Rocchio query expansion method slightly outperforms the one based on the biomedical lexicon as a source of terms, with an improvement of roughly 3% for MAP. However, the query expansion method based on the biomedical lexicon is much less resource intensive since it does not require computation of any relevance feedback set or any initial execution of the query. Hence, in term of trade-off between efficiency, execution time and retrieval accuracy, we argue that the query expansion method based on the biomedical lexicon offers the best performance for a prototype biomedical data search engine intended to be used at a large scale. In the official bioCADDIE challenge results, although our approach is ranked seventh in terms of the infNDCG evaluation metric, it ranks second in term of P@10 and NDCG. Hence, the method proposed here provides overall good retrieval performance in relation to the approaches of other competitors. Consequently, the observations made in this paper should benefit the development of a Data Discovery Index prototype or the improvement of the existing one. PMID:29220457

Shape-Memory Polymers for Biomedical Applications

NASA Astrophysics Data System (ADS)

Yakacki, Christopher M.; Gall, Ken

Shape-memory polymers (SMPs) are a class of mechanically functional "smart" materials that have generated substantial interest for biomedical applications. SMPs offer the ability to promote minimally invasive surgery, provide structural support, exert stabilizing forces, elute therapeutic agents, and biodegrade. This review focuses on several areas of biomedicine including vascular, orthopedic, and neuronal applications with respect to the progress and potential for SMPs to improve the standard of treatment in these areas. Fundamental studies on proposed biomedical SMP systems are discussed with regards to biodegradability, tailorability, sterilization, and biocompatibility. Lastly, a proposed research and development pathway for SMP-based biomedical devices is proposed based on trends in the recent literature.

Micro/Nanostructured Films and Adhesives for Biomedical Applications.

PubMed

Lee, Jungkyu K; Kang, Sung Min; Yang, Sung Ho; Cho, Woo Kyung

2015-12-01

The advanced technologies available for micro/nanofabrication have opened new avenues for interdisciplinary approaches to solve the unmet medical needs of regenerative medicine and biomedical devices. This review highlights the recent developments in micro/nanostructured adhesives and films for biomedical applications, including waterproof seals for wounds or surgery sites, drug delivery, sensing human body signals, and optical imaging of human tissues. We describe in detail the fabrication processes required to prepare the adhesives and films, such as tape-based adhesives, nanofilms, and flexible and stretchable film-based electronic devices. We also discuss their biomedical functions, performance in vitro and in vivo, and the future research needed to improve the current systems.

Knowledge Representation and Management: A Linked Data Perspective

PubMed Central

Barros, M.

2016-01-01

Summary Introduction Biomedical research is increasingly becoming a data-intensive science in several areas, where prodigious amounts of data is being generated that has to be stored, integrated, shared and analyzed. In an effort to improve the accessibility of data and knowledge, the Linked Data initiative proposed a well-defined set of recommendations for exposing, sharing and integrating data, information and knowledge, using semantic web technologies. Objective The main goal of this paper is to identify the current status and future trends of knowledge representation and management in Life and Health Sciences, mostly with regard to linked data technologies. Methods We selected three prominent linked data studies, namely Bio2RDF, Open PHACTS and EBI RDF platform, and selected 14 studies published after 2014 (inclusive) that cited any of the three studies. We manually analyzed these 14 papers in relation to how they use linked data techniques. Results The analyses show a tendency to use linked data techniques in Life and Health Sciences, and even if some studies do not follow all of the recommendations, many of them already represent and manage their knowledge using RDF and biomedical ontologies. Conclusion These insights from RDF and biomedical ontologies are having a strong impact on how knowledge is generated from biomedical data, by making data elements increasingly connected and by providing a better description of their semantics. As health institutes become more data centric, we believe that the adoption of linked data techniques will continue to grow and be an effective solution to knowledge representation and management. PMID:27830248

Building a biomedical tokenizer using the token lattice design pattern and the adapted Viterbi algorithm

PubMed Central

2011-01-01

Background Tokenization is an important component of language processing yet there is no widely accepted tokenization method for English texts, including biomedical texts. Other than rule based techniques, tokenization in the biomedical domain has been regarded as a classification task. Biomedical classifier-based tokenizers either split or join textual objects through classification to form tokens. The idiosyncratic nature of each biomedical tokenizer’s output complicates adoption and reuse. Furthermore, biomedical tokenizers generally lack guidance on how to apply an existing tokenizer to a new domain (subdomain). We identify and complete a novel tokenizer design pattern and suggest a systematic approach to tokenizer creation. We implement a tokenizer based on our design pattern that combines regular expressions and machine learning. Our machine learning approach differs from the previous split-join classification approaches. We evaluate our approach against three other tokenizers on the task of tokenizing biomedical text. Results Medpost and our adapted Viterbi tokenizer performed best with a 92.9% and 92.4% accuracy respectively. Conclusions Our evaluation of our design pattern and guidelines supports our claim that the design pattern and guidelines are a viable approach to tokenizer construction (producing tokenizers matching leading custom-built tokenizers in a particular domain). Our evaluation also demonstrates that ambiguous tokenizations can be disambiguated through POS tagging. In doing so, POS tag sequences and training data have a significant impact on proper text tokenization. PMID:21658288

G-DOC Plus - an integrative bioinformatics platform for precision medicine.

PubMed

Bhuvaneshwar, Krithika; Belouali, Anas; Singh, Varun; Johnson, Robert M; Song, Lei; Alaoui, Adil; Harris, Michael A; Clarke, Robert; Weiner, Louis M; Gusev, Yuriy; Madhavan, Subha

2016-04-30

G-DOC Plus is a data integration and bioinformatics platform that uses cloud computing and other advanced computational tools to handle a variety of biomedical BIG DATA including gene expression arrays, NGS and medical images so that they can be analyzed in the full context of other omics and clinical information. G-DOC Plus currently holds data from over 10,000 patients selected from private and public resources including Gene Expression Omnibus (GEO), The Cancer Genome Atlas (TCGA) and the recently added datasets from REpository for Molecular BRAin Neoplasia DaTa (REMBRANDT), caArray studies of lung and colon cancer, ImmPort and the 1000 genomes data sets. The system allows researchers to explore clinical-omic data one sample at a time, as a cohort of samples; or at the level of population, providing the user with a comprehensive view of the data. G-DOC Plus tools have been leveraged in cancer and non-cancer studies for hypothesis generation and validation; biomarker discovery and multi-omics analysis, to explore somatic mutations and cancer MRI images; as well as for training and graduate education in bioinformatics, data and computational sciences. Several of these use cases are described in this paper to demonstrate its multifaceted usability. G-DOC Plus can be used to support a variety of user groups in multiple domains to enable hypothesis generation for precision medicine research. The long-term vision of G-DOC Plus is to extend this translational bioinformatics platform to stay current with emerging omics technologies and analysis methods to continue supporting novel hypothesis generation, analysis and validation for integrative biomedical research. By integrating several aspects of the disease and exposing various data elements, such as outpatient lab workup, pathology, radiology, current treatments, molecular signatures and expected outcomes over a web interface, G-DOC Plus will continue to strengthen precision medicine research. G-DOC Plus is available at: https://gdoc.georgetown.edu .

Cluster-Based Query Expansion Using Language Modeling for Biomedical Literature Retrieval

ERIC Educational Resources Information Center

Xu, Xuheng

2011-01-01

The tremendously huge volume of biomedical literature, scientists' specific information needs, long terms of multiples words, and fundamental problems of synonym and polysemy have been challenging issues facing the biomedical information retrieval community researchers. Search engines have significantly improved the efficiency and effectiveness of…

A Pilot Study of Biomedical Text Comprehension using an Attention-Based Deep Neural Reader: Design and Experimental Analysis.

PubMed

Kim, Seongsoon; Park, Donghyeon; Choi, Yonghwa; Lee, Kyubum; Kim, Byounggun; Jeon, Minji; Kim, Jihye; Tan, Aik Choon; Kang, Jaewoo

2018-01-05

With the development of artificial intelligence (AI) technology centered on deep-learning, the computer has evolved to a point where it can read a given text and answer a question based on the context of the text. Such a specific task is known as the task of machine comprehension. Existing machine comprehension tasks mostly use datasets of general texts, such as news articles or elementary school-level storybooks. However, no attempt has been made to determine whether an up-to-date deep learning-based machine comprehension model can also process scientific literature containing expert-level knowledge, especially in the biomedical domain. This study aims to investigate whether a machine comprehension model can process biomedical articles as well as general texts. Since there is no dataset for the biomedical literature comprehension task, our work includes generating a large-scale question answering dataset using PubMed and manually evaluating the generated dataset. We present an attention-based deep neural model tailored to the biomedical domain. To further enhance the performance of our model, we used a pretrained word vector and biomedical entity type embedding. We also developed an ensemble method of combining the results of several independent models to reduce the variance of the answers from the models. The experimental results showed that our proposed deep neural network model outperformed the baseline model by more than 7% on the new dataset. We also evaluated human performance on the new dataset. The human evaluation result showed that our deep neural model outperformed humans in comprehension by 22% on average. In this work, we introduced a new task of machine comprehension in the biomedical domain using a deep neural model. Since there was no large-scale dataset for training deep neural models in the biomedical domain, we created the new cloze-style datasets Biomedical Knowledge Comprehension Title (BMKC_T) and Biomedical Knowledge Comprehension Last Sentence (BMKC_LS) (together referred to as BioMedical Knowledge Comprehension) using the PubMed corpus. The experimental results showed that the performance of our model is much higher than that of humans. We observed that our model performed consistently better regardless of the degree of difficulty of a text, whereas humans have difficulty when performing biomedical literature comprehension tasks that require expert level knowledge. ©Seongsoon Kim, Donghyeon Park, Yonghwa Choi, Kyubum Lee, Byounggun Kim, Minji Jeon, Jihye Kim, Aik Choon Tan, Jaewoo Kang. Originally published in JMIR Medical Informatics (http://medinform.jmir.org), 05.01.2018.

A passage retrieval method based on probabilistic information retrieval model and UMLS concepts in biomedical question answering.

PubMed

Sarrouti, Mourad; Ouatik El Alaoui, Said

2017-04-01

Passage retrieval, the identification of top-ranked passages that may contain the answer for a given biomedical question, is a crucial component for any biomedical question answering (QA) system. Passage retrieval in open-domain QA is a longstanding challenge widely studied over the last decades. However, it still requires further efforts in biomedical QA. In this paper, we present a new biomedical passage retrieval method based on Stanford CoreNLP sentence/passage length, probabilistic information retrieval (IR) model and UMLS concepts. In the proposed method, we first use our document retrieval system based on PubMed search engine and UMLS similarity to retrieve relevant documents to a given biomedical question. We then take the abstracts from the retrieved documents and use Stanford CoreNLP for sentence splitter to make a set of sentences, i.e., candidate passages. Using stemmed words and UMLS concepts as features for the BM25 model, we finally compute the similarity scores between the biomedical question and each of the candidate passages and keep the N top-ranked ones. Experimental evaluations performed on large standard datasets, provided by the BioASQ challenge, show that the proposed method achieves good performances compared with the current state-of-the-art methods. The proposed method significantly outperforms the current state-of-the-art methods by an average of 6.84% in terms of mean average precision (MAP). We have proposed an efficient passage retrieval method which can be used to retrieve relevant passages in biomedical QA systems with high mean average precision. Copyright © 2017 Elsevier Inc. All rights reserved.

Combining Open-domain and Biomedical Knowledge for Topic Recognition in Consumer Health Questions.

PubMed

Mrabet, Yassine; Kilicoglu, Halil; Roberts, Kirk; Demner-Fushman, Dina

2016-01-01

Determining the main topics in consumer health questions is a crucial step in their processing as it allows narrowing the search space to a specific semantic context. In this paper we propose a topic recognition approach based on biomedical and open-domain knowledge bases. In the first step of our method, we recognize named entities in consumer health questions using an unsupervised method that relies on a biomedical knowledge base, UMLS, and an open-domain knowledge base, DBpedia. In the next step, we cast topic recognition as a binary classification problem of deciding whether a named entity is the question topic or not. We evaluated our approach on a dataset from the National Library of Medicine (NLM), introduced in this paper, and another from the Genetic and Rare Disease Information Center (GARD). The combination of knowledge bases outperformed the results obtained by individual knowledge bases by up to 16.5% F1 and achieved state-of-the-art performance. Our results demonstrate that combining open-domain knowledge bases with biomedical knowledge bases can lead to a substantial improvement in understanding user-generated health content.

The Translational Medicine Ontology and Knowledge Base: driving personalized medicine by bridging the gap between bench and bedside

PubMed Central

2011-01-01

Background Translational medicine requires the integration of knowledge using heterogeneous data from health care to the life sciences. Here, we describe a collaborative effort to produce a prototype Translational Medicine Knowledge Base (TMKB) capable of answering questions relating to clinical practice and pharmaceutical drug discovery. Results We developed the Translational Medicine Ontology (TMO) as a unifying ontology to integrate chemical, genomic and proteomic data with disease, treatment, and electronic health records. We demonstrate the use of Semantic Web technologies in the integration of patient and biomedical data, and reveal how such a knowledge base can aid physicians in providing tailored patient care and facilitate the recruitment of patients into active clinical trials. Thus, patients, physicians and researchers may explore the knowledge base to better understand therapeutic options, efficacy, and mechanisms of action. Conclusions This work takes an important step in using Semantic Web technologies to facilitate integration of relevant, distributed, external sources and progress towards a computational platform to support personalized medicine. Availability TMO can be downloaded from http://code.google.com/p/translationalmedicineontology and TMKB can be accessed at http://tm.semanticscience.org/sparql. PMID:21624155

Multifunctional nanomaterials for advanced molecular imaging and cancer therapy

NASA Astrophysics Data System (ADS)

Subramaniam, Prasad

Nanotechnology offers tremendous potential for use in biomedical applications, including cancer and stem cell imaging, disease diagnosis and drug delivery. The development of nanosystems has aided in understanding the molecular mechanisms of many diseases and permitted the controlled nanoscale manipulation of biological phenomena. In recent years, many studies have focused on the use of several kinds of nanomaterials for cancer and stem cell imaging and also for the delivery of anticancer therapeutics to tumor cells. However, the proper diagnosis and treatment of aggressive tumors such as brain and breast cancer requires highly sensitive diagnostic agents, in addition to the ability to deliver multiple therapeutics using a single platform to the target cells. Addressing these challenges, novel multifunctional nanomaterial-based platforms that incorporate multiple therapeutic and diagnostic agents, with superior molecular imaging and targeting capabilities, has been presented in this work. The initial part of this work presents the development of novel nanomaterials with superior optical properties for efficiently delivering soluble cues such as small interfering RNA (siRNA) into brain cancer cells with minimal toxicity. Specifically, this section details the development of non-toxic quantums dots for the imaging and delivery of siRNA into brain cancer and mesenchymal stem cells, with the hope of using these quantum dots as multiplexed imaging and delivery vehicles. The use of these quantum dots could overcome the toxicity issues associated with the use of conventional quantum dots, enabled the imaging of brain cancer and stem cells with high efficiency and allowed for the delivery of siRNA to knockdown the target oncogene in brain cancer cells. The latter part of this thesis details the development of nanomaterial-based drug delivery platforms for the co-delivery of multiple anticancer drugs to brain tumor cells. In particular, this part of the thesis focuses on the synthesis and use of a biodegradable dendritic polypeptide-based nanocarrier for the delivery of multiple anticancer drugs and siRNA to brain tumor cells. The co-delivery of important anticancer agents using a single platform was shown to increase the efficacy of the drugs manyfold, ensuring the cancer cell-specific delivery and minimizing dose limiting toxicities of the individual drugs. This would be of immense importance when used in vivo.

A New Pivoting and Iterative Text Detection Algorithm for Biomedical Images

PubMed Central

Xu, Songhua; Krauthammer, Michael

2010-01-01

There is interest to expand the reach of literature mining to include the analysis of biomedical images, which often contain a paper’s key findings. Examples include recent studies that use Optical Character Recognition (OCR) to extract image text, which is used to boost biomedical image retrieval and classification. Such studies rely on the robust identification of text elements in biomedical images, which is a non-trivial task. In this work, we introduce a new text detection algorithm for biomedical images based on iterative projection histograms. We study the effectiveness of our algorithm by evaluating the performance on a set of manually labeled random biomedical images, and compare the performance against other state-of-the-art text detection algorithms. In this paper, we demonstrate that a projection histogram-based text detection approach is well suited for text detection in biomedical images, with a performance of F score of .60. The approach performs better than comparable approaches for text detection. Further, we show that the iterative application of the algorithm is boosting overall detection performance. A C++ implementation of our algorithm is freely available through email request for academic use. PMID:20887803

Self-Powered Multiparameter Health Sensor.

PubMed

Tobola, Andreas; Leutheuser, Heike; Pollak, Markus; Spies, Peter; Hofmann, Christian; Weigand, Christian; Eskofier, Bjoern M; Fischer, Georg

2018-01-01

Wearable health sensors are about to change our health system. While several technological improvements have been presented to enhance performance and energy-efficiency, battery runtime is still a critical concern for practical use of wearable biomedical sensor systems. The runtime limitation is directly related to the battery size, which is another concern regarding practicality and customer acceptance. We introduced ULPSEK-Ultra-Low-Power Sensor Evaluation Kit-for evaluation of biomedical sensors and monitoring applications (http://ulpsek.com). ULPSEK includes a multiparameter sensor measuring and processing electrocardiogram, respiration, motion, body temperature, and photoplethysmography. Instead of a battery, ULPSEK is powered using an efficient body heat harvester. The harvester produced 171 W on average, which was sufficient to power the sensor below 25 C ambient temperature. We present design issues regarding the power supply and the power distribution network of the ULPSEK sensor platform. Due to the security aspect of self-powered health sensors, we suggest a hybrid solution consisting of a battery charged by a harvester.

CRISPR-cas System as a Genome Engineering Platform: Applications in Biomedicine and Biotechnology.

PubMed

Hashemi, Atieh

2018-01-01

Genome editing mediated by Clustered Regularly Interspaced Palindromic Repeats (CRISPR) and its associated proteins (Cas) has recently been considered to be used as efficient, rapid and site-specific tool in the modification of endogenous genes in biomedically important cell types and whole organisms. It has become a predictable and precise method of choice for genome engineering by specifying a 20-nt targeting sequence within its guide RNA. Firstly, this review aims to describe the biology of CRISPR system. Next, the applications of CRISPR-Cas9 in various ways, such as efficient generation of a wide variety of biomedically important cellular models as well as those of animals, modifying epigenomes, conducting genome-wide screens, gene therapy, labelling specific genomic loci in living cells, metabolic engineering of yeast and bacteria and endogenous gene expression regulation by an altered version of this system were reviewed. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

ARX - A Comprehensive Tool for Anonymizing Biomedical Data

PubMed Central

Prasser, Fabian; Kohlmayer, Florian; Lautenschläger, Ronald; Kuhn, Klaus A.

2014-01-01

Collaboration and data sharing have become core elements of biomedical research. Especially when sensitive data from distributed sources are linked, privacy threats have to be considered. Statistical disclosure control allows the protection of sensitive data by introducing fuzziness. Reduction of data quality, however, needs to be balanced against gains in protection. Therefore, tools are needed which provide a good overview of the anonymization process to those responsible for data sharing. These tools require graphical interfaces and the use of intuitive and replicable methods. In addition, extensive testing, documentation and openness to reviews by the community are important. Existing publicly available software is limited in functionality, and often active support is lacking. We present ARX, an anonymization tool that i) implements a wide variety of privacy methods in a highly efficient manner, ii) provides an intuitive cross-platform graphical interface, iii) offers a programming interface for integration into other software systems, and iv) is well documented and actively supported. PMID:25954407

A Machine Learning-based Method for Question Type Classification in Biomedical Question Answering.

PubMed

Sarrouti, Mourad; Ouatik El Alaoui, Said

2017-05-18

Biomedical question type classification is one of the important components of an automatic biomedical question answering system. The performance of the latter depends directly on the performance of its biomedical question type classification system, which consists of assigning a category to each question in order to determine the appropriate answer extraction algorithm. This study aims to automatically classify biomedical questions into one of the four categories: (1) yes/no, (2) factoid, (3) list, and (4) summary. In this paper, we propose a biomedical question type classification method based on machine learning approaches to automatically assign a category to a biomedical question. First, we extract features from biomedical questions using the proposed handcrafted lexico-syntactic patterns. Then, we feed these features for machine-learning algorithms. Finally, the class label is predicted using the trained classifiers. Experimental evaluations performed on large standard annotated datasets of biomedical questions, provided by the BioASQ challenge, demonstrated that our method exhibits significant improved performance when compared to four baseline systems. The proposed method achieves a roughly 10-point increase over the best baseline in terms of accuracy. Moreover, the obtained results show that using handcrafted lexico-syntactic patterns as features' provider of support vector machine (SVM) lead to the highest accuracy of 89.40 %. The proposed method can automatically classify BioASQ questions into one of the four categories: yes/no, factoid, list, and summary. Furthermore, the results demonstrated that our method produced the best classification performance compared to four baseline systems.

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.

Small animal imaging platform for quantitative assessment of short-wave infrared-emitting contrast agents

NASA Astrophysics Data System (ADS)

Hu, Philip; Mingozzi, Marco; Higgins, Laura M.; Ganapathy, Vidya; Zevon, Margot; Riman, Richard E.; Roth, Charles M.; Moghe, Prabhas V.; Pierce, Mark C.

2015-03-01

We report the design, calibration, and testing of a pre-clinical small animal imaging platform for use with short-wave infrared (SWIR) emitting contrast agents. Unlike materials emitting at visible or near-infrared wavelengths, SWIR-emitting agents require detection systems with sensitivity in the 1-2 μm wavelength region, beyond the range of commercially available small animal imagers. We used a collimated 980 nm laser beam to excite rare-earth-doped NaYF4:Er,Yb nanocomposites, as an example of a SWIR emitting material under development for biomedical imaging applications. This beam was raster scanned across the animal, with fluorescence in the 1550 nm wavelength region detected by an InGaAs area camera. Background adjustment and intensity non-uniformity corrections were applied in software. The final SWIR fluorescence image was overlaid onto a standard white-light image for registration of contrast agent uptake with respect to anatomical features.

Importing statistical measures into Artemis enhances gene identification in the Leishmania genome project.

PubMed

Aggarwal, Gautam; Worthey, E A; McDonagh, Paul D; Myler, Peter J

2003-06-07

Seattle Biomedical Research Institute (SBRI) as part of the Leishmania Genome Network (LGN) is sequencing chromosomes of the trypanosomatid protozoan species Leishmania major. At SBRI, chromosomal sequence is annotated using a combination of trained and untrained non-consensus gene-prediction algorithms with ARTEMIS, an annotation platform with rich and user-friendly interfaces. Here we describe a methodology used to import results from three different protein-coding gene-prediction algorithms (GLIMMER, TESTCODE and GENESCAN) into the ARTEMIS sequence viewer and annotation tool. Comparison of these methods, along with the CODONUSAGE algorithm built into ARTEMIS, shows the importance of combining methods to more accurately annotate the L. major genomic sequence. An improvised and powerful tool for gene prediction has been developed by importing data from widely-used algorithms into an existing annotation platform. This approach is especially fruitful in the Leishmania genome project where there is large proportion of novel genes requiring manual annotation.

"Mobile Nurse" platform for ubiquitous medicine.

PubMed

Struzik, Z R; Yoshiuchi, K; Sone, M; Ishikawa, T; Kikuchi, H; Kumano, H; Watsuji, T; Natelson, B H; Yamamoto, Y

2007-01-01

We introduce "Mobile Nurse" (MN) - an emerging platform for the practice of ubiquitous medicine. By implementing in a dynamic setting of daily life the patient care traditionally provided by the clinical nurses on duty, MN aims at integral data collection and shortening the response time to the patient. MN is also capable of intelligent interaction with the patient and is able to learn from the patient's behavior and disease sign evaluation for improved personalized treatment. In this paper, we outline the most essential concepts around the hardware, software and methodological designs of MN. We provide an example of the implementation, and elaborate on the possible future impact on medical practice and biomedical science research. The main innovation of MN, setting it apart from current tele-medicine systems, is the ability to integrate the patient's signs and symptoms on site, providing medical professionals with powerful tools to elucidate disease mechanisms, to make proper diagnoses and to prescribe treatment.

Hyperpolarized Porous Silicon Nanoparticles: Potential Theragnostic Material for ²⁹Si Magnetic Resonance Imaging.

PubMed

Seo, Hyeonglim; Choi, Ikjang; Whiting, Nicholas; Hu, Jingzhe; Luu, Quy Son; Pudakalakatti, Shivanand; McCowan, Caitlin; Kim, Yaewon; Zacharias, Niki; Lee, Seunghyun; Bhattacharya, Pratip; Lee, Youngbok

2018-05-20

Porous silicon nanoparticles have recently garnered attention as potentially-promising biomedical platforms for drug delivery and medical diagnostics. Here, we demonstrate porous silicon nanoparticles as contrast agents for ²⁹Si magnetic resonance imaging. Size-controlled porous silicon nanoparticles were synthesized by magnesiothermic reduction of silica nanoparticles and were surface activated for further functionalization. Particles were hyperpolarized via dynamic nuclear polarization to enhance their ²⁹Si MR signals; the particles demonstrated long ²⁹Si spin-lattice relaxation (T₁) times (~ 25 mins), which suggests potential applicability for medical imaging. Furthermore, ²⁹Si hyperpolarization levels were sufficient to allow ²⁹Si MRI in phantoms. These results underscore the potential of porous silicon nanoparticles that, when combined with hyperpolarized magnetic resonance imaging, can be a powerful theragnostic deep tissue imaging platform to interrogate various biomolecular processes in vivo. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Synthetic biology. Genomically encoded analog memory with precise in vivo DNA writing in living cell populations.

PubMed

Farzadfard, Fahim; Lu, Timothy K

2014-11-14

Cellular memory is crucial to many natural biological processes and sophisticated synthetic biology applications. Existing cellular memories rely on epigenetic switches or recombinases, which are limited in scalability and recording capacity. In this work, we use the DNA of living cell populations as genomic "tape recorders" for the analog and distributed recording of long-term event histories. We describe a platform for generating single-stranded DNA (ssDNA) in vivo in response to arbitrary transcriptional signals. When coexpressed with a recombinase, these intracellularly expressed ssDNAs target specific genomic DNA addresses, resulting in precise mutations that accumulate in cell populations as a function of the magnitude and duration of the inputs. This platform could enable long-term cellular recorders for environmental and biomedical applications, biological state machines, and enhanced genome engineering strategies. Copyright © 2014, American Association for the Advancement of Science.

Engineering β-sheet peptide assemblies for biomedical applications.

PubMed

Yu, Zhiqiang; Cai, Zheng; Chen, Qiling; Liu, Menghua; Ye, Ling; Ren, Jiaoyan; Liao, Wenzhen; Liu, Shuwen

2016-03-01

Hydrogels have been widely studied in various biomedical applications, such as tissue engineering, cell culture, immunotherapy and vaccines, and drug delivery. Peptide-based nanofibers represent a promising new strategy for current drug delivery approaches and cell carriers for tissue engineering. This review focuses on the recent advances in the use of self-assembling engineered β-sheet peptide assemblies for biomedical applications. The applications of peptide nanofibers in biomedical fields, such as drug delivery, tissue engineering, immunotherapy, and vaccines, are highlighted. The current challenges and future perspectives for self-assembling peptide nanofibers in biomedical applications are discussed.

Telemedicine optoelectronic biomedical data processing system

NASA Astrophysics Data System (ADS)

Prosolovska, Vita V.

2010-08-01

The telemedicine optoelectronic biomedical data processing system is created to share medical information for the control of health rights and timely and rapid response to crisis. The system includes the main blocks: bioprocessor, analog-digital converter biomedical images, optoelectronic module for image processing, optoelectronic module for parallel recording and storage of biomedical imaging and matrix screen display of biomedical images. Rated temporal characteristics of the blocks defined by a particular triggering optoelectronic couple in analog-digital converters and time imaging for matrix screen. The element base for hardware implementation of the developed matrix screen is integrated optoelectronic couples produced by selective epitaxy.

Supporting inter-topic entity search for biomedical Linked Data based on heterogeneous relationships.

PubMed

Zong, Nansu; Lee, Sungin; Ahn, Jinhyun; Kim, Hong-Gee

2017-08-01

The keyword-based entity search restricts search space based on the preference of search. When given keywords and preferences are not related to the same biomedical topic, existing biomedical Linked Data search engines fail to deliver satisfactory results. This research aims to tackle this issue by supporting an inter-topic search-improving search with inputs, keywords and preferences, under different topics. This study developed an effective algorithm in which the relations between biomedical entities were used in tandem with a keyword-based entity search, Siren. The algorithm, PERank, which is an adaptation of Personalized PageRank (PPR), uses a pair of input: (1) search preferences, and (2) entities from a keyword-based entity search with a keyword query, to formalize the search results on-the-fly based on the index of the precomputed Individual Personalized PageRank Vectors (IPPVs). Our experiments were performed over ten linked life datasets for two query sets, one with keyword-preference topic correspondence (intra-topic search), and the other without (inter-topic search). The experiments showed that the proposed method achieved better search results, for example a 14% increase in precision for the inter-topic search than the baseline keyword-based search engine. The proposed method improved the keyword-based biomedical entity search by supporting the inter-topic search without affecting the intra-topic search based on the relations between different entities. Copyright © 2017 Elsevier Ltd. All rights reserved.

Use of controlled vocabularies to improve biomedical information retrieval tasks.

PubMed

Pasche, Emilie; Gobeill, Julien; Vishnyakova, Dina; Ruch, Patrick; Lovis, Christian

2013-01-01

The high heterogeneity of biomedical vocabulary is a major obstacle for information retrieval in large biomedical collections. Therefore, using biomedical controlled vocabularies is crucial for managing these contents. We investigate the impact of query expansion based on controlled vocabularies to improve the effectiveness of two search engines. Our strategy relies on the enrichment of users' queries with additional terms, directly derived from such vocabularies applied to infectious diseases and chemical patents. We observed that query expansion based on pathogen names resulted in improvements of the top-precision of our first search engine, while the normalization of diseases degraded the top-precision. The expansion of chemical entities, which was performed on the second search engine, positively affected the mean average precision. We have shown that query expansion of some types of biomedical entities has a great potential to improve search effectiveness; therefore a fine-tuning of query expansion strategies could help improving the performances of search engines.

A coherent graph-based semantic clustering and summarization approach for biomedical literature and a new summarization evaluation method.

PubMed

Yoo, Illhoi; Hu, Xiaohua; Song, Il-Yeol

2007-11-27

A huge amount of biomedical textual information has been produced and collected in MEDLINE for decades. In order to easily utilize biomedical information in the free text, document clustering and text summarization together are used as a solution for text information overload problem. In this paper, we introduce a coherent graph-based semantic clustering and summarization approach for biomedical literature. Our extensive experimental results show the approach shows 45% cluster quality improvement and 72% clustering reliability improvement, in terms of misclassification index, over Bisecting K-means as a leading document clustering approach. In addition, our approach provides concise but rich text summary in key concepts and sentences. Our coherent biomedical literature clustering and summarization approach that takes advantage of ontology-enriched graphical representations significantly improves the quality of document clusters and understandability of documents through summaries.

A coherent graph-based semantic clustering and summarization approach for biomedical literature and a new summarization evaluation method

PubMed Central

Yoo, Illhoi; Hu, Xiaohua; Song, Il-Yeol

2007-01-01

Background A huge amount of biomedical textual information has been produced and collected in MEDLINE for decades. In order to easily utilize biomedical information in the free text, document clustering and text summarization together are used as a solution for text information overload problem. In this paper, we introduce a coherent graph-based semantic clustering and summarization approach for biomedical literature. Results Our extensive experimental results show the approach shows 45% cluster quality improvement and 72% clustering reliability improvement, in terms of misclassification index, over Bisecting K-means as a leading document clustering approach. In addition, our approach provides concise but rich text summary in key concepts and sentences. Conclusion Our coherent biomedical literature clustering and summarization approach that takes advantage of ontology-enriched graphical representations significantly improves the quality of document clusters and understandability of documents through summaries. PMID:18047705

Accelerating translational research by clinically driven development of an informatics platform--a case study.

PubMed

Abugessaisa, Imad; Saevarsdottir, Saedis; Tsipras, Giorgos; Lindblad, Staffan; Sandin, Charlotta; Nikamo, Pernilla; Ståhle, Mona; Malmström, Vivianne; Klareskog, Lars; Tegnér, Jesper

2014-01-01

Translational medicine is becoming increasingly dependent upon data generated from health care, clinical research, and molecular investigations. This increasing rate of production and diversity in data has brought about several challenges, including the need to integrate fragmented databases, enable secondary use of patient clinical data from health care in clinical research, and to create information systems that clinicians and biomedical researchers can readily use. Our case study effectively integrates requirements from the clinical and biomedical researcher perspectives in a translational medicine setting. Our three principal achievements are (a) a design of a user-friendly web-based system for management and integration of clinical and molecular databases, while adhering to proper de-identification and security measures; (b) providing a real-world test of the system functionalities using clinical cohorts; and (c) system integration with a clinical decision support system to demonstrate system interoperability. We engaged two active clinical cohorts, 747 psoriasis patients and 2001 rheumatoid arthritis patients, to demonstrate efficient query possibilities across the data sources, enable cohort stratification, extract variation in antibody patterns, study biomarker predictors of treatment response in RA patients, and to explore metabolic profiles of psoriasis patients. Finally, we demonstrated system interoperability by enabling integration with an established clinical decision support system in health care. To assure the usefulness and usability of the system, we followed two approaches. First, we created a graphical user interface supporting all user interactions. Secondly we carried out a system performance evaluation study where we measured the average response time in seconds for active users, http errors, and kilobits per second received and sent. The maximum response time was found to be 0.12 seconds; no server or client errors of any kind were detected. In conclusion, the system can readily be used by clinicians and biomedical researchers in a translational medicine setting.

An exploration of the biomedical optics course construction of undergraduate biomedical engineering program in medical colleges

NASA Astrophysics Data System (ADS)

Guo, Shijun; Lyu, Jie; Zhang, Peiming

2017-08-01

In this paper, the teaching goals, teaching contents and teaching methods in biomedical optics course construction are discussed. From the dimension of teaching goals, students should master the principle of optical inspection on the human body, diagnosis and treatment of methodology and instruments, through the study of the theory and practice of this course, and can utilize biomedical optics methods to solve practical problems in the clinical medical engineering practice. From the dimension of teaching contents, based on the characteristics of biomedical engineering in medical colleges, the organic integration of engineering aspects, medical optical instruments, and biomedical aspects dispersed in human anatomy, human physiology, clinical medicine fundamental related to the biomedical optics is build. Noninvasive measurement of the human body composition and noninvasive optical imaging of the human body were taken as actual problems in biomedical optics fields. Typical medical applications such as eye optics and laser medicine were also integrated into the theory and practice teaching. From the dimension of teaching methods, referencing to organ-system based medical teaching mode, optical principle and instrument principle were taught by teachers from school of medical instruments, and the histological characteristics and clinical actual need in areas such as digestive diseases and urinary surgery were taught by teachers from school of basic medicine or clinical medicine of medical colleges. Furthermore, clinical application guidance would be provided by physician and surgeons in hospitals.

Cloud Based Metalearning System for Predictive Modeling of Biomedical Data

PubMed Central

Vukićević, Milan

2014-01-01

Rapid growth and storage of biomedical data enabled many opportunities for predictive modeling and improvement of healthcare processes. On the other side analysis of such large amounts of data is a difficult and computationally intensive task for most existing data mining algorithms. This problem is addressed by proposing a cloud based system that integrates metalearning framework for ranking and selection of best predictive algorithms for data at hand and open source big data technologies for analysis of biomedical data. PMID:24892101

SemaTyP: a knowledge graph based literature mining method for drug discovery.

PubMed

Sang, Shengtian; Yang, Zhihao; Wang, Lei; Liu, Xiaoxia; Lin, Hongfei; Wang, Jian

2018-05-30

Drug discovery is the process through which potential new medicines are identified. High-throughput screening and computer-aided drug discovery/design are the two main drug discovery methods for now, which have successfully discovered a series of drugs. However, development of new drugs is still an extremely time-consuming and expensive process. Biomedical literature contains important clues for the identification of potential treatments. It could support experts in biomedicine on their way towards new discoveries. Here, we propose a biomedical knowledge graph-based drug discovery method called SemaTyP, which discovers candidate drugs for diseases by mining published biomedical literature. We first construct a biomedical knowledge graph with the relations extracted from biomedical abstracts, then a logistic regression model is trained by learning the semantic types of paths of known drug therapies' existing in the biomedical knowledge graph, finally the learned model is used to discover drug therapies for new diseases. The experimental results show that our method could not only effectively discover new drug therapies for new diseases, but also could provide the potential mechanism of action of the candidate drugs. In this paper we propose a novel knowledge graph based literature mining method for drug discovery. It could be a supplementary method for current drug discovery methods.

A neural joint model for entity and relation extraction from biomedical text.

PubMed

Li, Fei; Zhang, Meishan; Fu, Guohong; Ji, Donghong

2017-03-31

Extracting biomedical entities and their relations from text has important applications on biomedical research. Previous work primarily utilized feature-based pipeline models to process this task. Many efforts need to be made on feature engineering when feature-based models are employed. Moreover, pipeline models may suffer error propagation and are not able to utilize the interactions between subtasks. Therefore, we propose a neural joint model to extract biomedical entities as well as their relations simultaneously, and it can alleviate the problems above. Our model was evaluated on two tasks, i.e., the task of extracting adverse drug events between drug and disease entities, and the task of extracting resident relations between bacteria and location entities. Compared with the state-of-the-art systems in these tasks, our model improved the F1 scores of the first task by 5.1% in entity recognition and 8.0% in relation extraction, and that of the second task by 9.2% in relation extraction. The proposed model achieves competitive performances with less work on feature engineering. We demonstrate that the model based on neural networks is effective for biomedical entity and relation extraction. In addition, parameter sharing is an alternative method for neural models to jointly process this task. Our work can facilitate the research on biomedical text mining.

The center for causal discovery of biomedical knowledge from big data.

PubMed

Cooper, Gregory F; Bahar, Ivet; Becich, Michael J; Benos, Panayiotis V; Berg, Jeremy; Espino, Jeremy U; Glymour, Clark; Jacobson, Rebecca Crowley; Kienholz, Michelle; Lee, Adrian V; Lu, Xinghua; Scheines, Richard

2015-11-01

The Big Data to Knowledge (BD2K) Center for Causal Discovery is developing and disseminating an integrated set of open source tools that support causal modeling and discovery of biomedical knowledge from large and complex biomedical datasets. The Center integrates teams of biomedical and data scientists focused on the refinement of existing and the development of new constraint-based and Bayesian algorithms based on causal Bayesian networks, the optimization of software for efficient operation in a supercomputing environment, and the testing of algorithms and software developed using real data from 3 representative driving biomedical projects: cancer driver mutations, lung disease, and the functional connectome of the human brain. Associated training activities provide both biomedical and data scientists with the knowledge and skills needed to apply and extend these tools. Collaborative activities with the BD2K Consortium further advance causal discovery tools and integrate tools and resources developed by other centers. © The Author 2015. Published by Oxford University Press on behalf of the American Medical Informatics Association.All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Semantic Similarity in Biomedical Ontologies

PubMed Central

Pesquita, Catia; Faria, Daniel; Falcão, André O.; Lord, Phillip; Couto, Francisco M.

2009-01-01

In recent years, ontologies have become a mainstream topic in biomedical research. When biological entities are described using a common schema, such as an ontology, they can be compared by means of their annotations. This type of comparison is called semantic similarity, since it assesses the degree of relatedness between two entities by the similarity in meaning of their annotations. The application of semantic similarity to biomedical ontologies is recent; nevertheless, several studies have been published in the last few years describing and evaluating diverse approaches. Semantic similarity has become a valuable tool for validating the results drawn from biomedical studies such as gene clustering, gene expression data analysis, prediction and validation of molecular interactions, and disease gene prioritization. We review semantic similarity measures applied to biomedical ontologies and propose their classification according to the strategies they employ: node-based versus edge-based and pairwise versus groupwise. We also present comparative assessment studies and discuss the implications of their results. We survey the existing implementations of semantic similarity measures, and we describe examples of applications to biomedical research. This will clarify how biomedical researchers can benefit from semantic similarity measures and help them choose the approach most suitable for their studies. Biomedical ontologies are evolving toward increased coverage, formality, and integration, and their use for annotation is increasingly becoming a focus of both effort by biomedical experts and application of automated annotation procedures to create corpora of higher quality and completeness than are currently available. Given that semantic similarity measures are directly dependent on these evolutions, we can expect to see them gaining more relevance and even becoming as essential as sequence similarity is today in biomedical research. PMID:19649320