A bayesian translational framework for knowledge propagation, discovery, and integration under specific contexts.

PubMed

Deng, Michelle; Zollanvari, Amin; Alterovitz, Gil

2012-01-01

The immense corpus of biomedical literature existing today poses challenges in information search and integration. Many links between pieces of knowledge occur or are significant only under certain contexts-rather than under the entire corpus. This study proposes using networks of ontology concepts, linked based on their co-occurrences in annotations of abstracts of biomedical literature and descriptions of experiments, to draw conclusions based on context-specific queries and to better integrate existing knowledge. In particular, a Bayesian network framework is constructed to allow for the linking of related terms from two biomedical ontologies under the queried context concept. Edges in such a Bayesian network allow associations between biomedical concepts to be quantified and inference to be made about the existence of some concepts given prior information about others. This approach could potentially be a powerful inferential tool for context-specific queries, applicable to ontologies in other fields as well.

A Bayesian Translational Framework for Knowledge Propagation, Discovery, and Integration Under Specific Contexts

PubMed Central

Deng, Michelle; Zollanvari, Amin; Alterovitz, Gil

2012-01-01

The immense corpus of biomedical literature existing today poses challenges in information search and integration. Many links between pieces of knowledge occur or are significant only under certain contexts—rather than under the entire corpus. This study proposes using networks of ontology concepts, linked based on their co-occurrences in annotations of abstracts of biomedical literature and descriptions of experiments, to draw conclusions based on context-specific queries and to better integrate existing knowledge. In particular, a Bayesian network framework is constructed to allow for the linking of related terms from two biomedical ontologies under the queried context concept. Edges in such a Bayesian network allow associations between biomedical concepts to be quantified and inference to be made about the existence of some concepts given prior information about others. This approach could potentially be a powerful inferential tool for context-specific queries, applicable to ontologies in other fields as well. PMID:22779044

Semantic annotation in biomedicine: the current landscape.

PubMed

Jovanović, Jelena; Bagheri, Ebrahim

2017-09-22

The abundance and unstructured nature of biomedical texts, be it clinical or research content, impose significant challenges for the effective and efficient use of information and knowledge stored in such texts. Annotation of biomedical documents with machine intelligible semantics facilitates advanced, semantics-based text management, curation, indexing, and search. This paper focuses on annotation of biomedical entity mentions with concepts from relevant biomedical knowledge bases such as UMLS. As a result, the meaning of those mentions is unambiguously and explicitly defined, and thus made readily available for automated processing. This process is widely known as semantic annotation, and the tools that perform it are known as semantic annotators.Over the last dozen years, the biomedical research community has invested significant efforts in the development of biomedical semantic annotation technology. Aiming to establish grounds for further developments in this area, we review a selected set of state of the art biomedical semantic annotators, focusing particularly on general purpose annotators, that is, semantic annotation tools that can be customized to work with texts from any area of biomedicine. We also examine potential directions for further improvements of today's annotators which could make them even more capable of meeting the needs of real-world applications. To motivate and encourage further developments in this area, along the suggested and/or related directions, we review existing and potential practical applications and benefits of semantic annotators.

Biomedical Applications of Carbon Nanotubes: A Critical Review.

PubMed

Sharma, Priyanka; Mehra, Neelesh Kumar; Jain, Keerti; Jain, N K

2016-08-01

The convergence of nano and biotechnology is enabling scientific and technical knowledge for improving human well being. Carbon nanotubes have become most fascinating material to be studied and unveil new avenues in the field of nanobiotechnology. The nanometer size and high aspect ratio of the CNTs are the two distinct features, which have contributed to diverse biomedical applications. They have captured the attention as nanoscale materials due to their nanometric structure and remarkable list of superlative and extravagant properties that encouraged their exploitation for promising applications. Significant progress has been made in order to overcome some of the major hurdles towards biomedical application of nanomaterials, especially on issues regarding the aqueous solubility/dispersion and safety of CNTs. Functionalized CNTs have been used in drug targeting, imaging, and in the efficient delivery of gene and nucleic acids. CNTs have also demonstrated great potential in diverse biomedical uses like drug targeting, imaging, cancer treatment, tissue regeneration, diagnostics, biosensing, genetic engineering and so forth. The present review highlights the possible potential of CNTs in diagnostics, imaging and targeted delivery of bioactives and also outlines the future opportunities for biomedical applications.

Chapter 1: Biomedical knowledge integration.

PubMed

Payne, Philip R O

2012-01-01

The modern biomedical research and healthcare delivery domains have seen an unparalleled increase in the rate of innovation and novel technologies over the past several decades. Catalyzed by paradigm-shifting public and private programs focusing upon the formation and delivery of genomic and personalized medicine, the need for high-throughput and integrative approaches to the collection, management, and analysis of heterogeneous data sets has become imperative. This need is particularly pressing in the translational bioinformatics domain, where many fundamental research questions require the integration of large scale, multi-dimensional clinical phenotype and bio-molecular data sets. Modern biomedical informatics theory and practice has demonstrated the distinct benefits associated with the use of knowledge-based systems in such contexts. A knowledge-based system can be defined as an intelligent agent that employs a computationally tractable knowledge base or repository in order to reason upon data in a targeted domain and reproduce expert performance relative to such reasoning operations. The ultimate goal of the design and use of such agents is to increase the reproducibility, scalability, and accessibility of complex reasoning tasks. Examples of the application of knowledge-based systems in biomedicine span a broad spectrum, from the execution of clinical decision support, to epidemiologic surveillance of public data sets for the purposes of detecting emerging infectious diseases, to the discovery of novel hypotheses in large-scale research data sets. In this chapter, we will review the basic theoretical frameworks that define core knowledge types and reasoning operations with particular emphasis on the applicability of such conceptual models within the biomedical domain, and then go on to introduce a number of prototypical data integration requirements and patterns relevant to the conduct of translational bioinformatics that can be addressed via the design and use of knowledge-based systems.

Addressing the translational dilemma: dynamic knowledge representation of inflammation using agent-based modeling.

PubMed

An, Gary; Christley, Scott

2012-01-01

Given the panoply of system-level diseases that result from disordered inflammation, such as sepsis, atherosclerosis, cancer, and autoimmune disorders, understanding and characterizing the inflammatory response is a key target of biomedical research. Untangling the complex behavioral configurations associated with a process as ubiquitous as inflammation represents a prototype of the translational dilemma: the ability to translate mechanistic knowledge into effective therapeutics. A critical failure point in the current research environment is a throughput bottleneck at the level of evaluating hypotheses of mechanistic causality; these hypotheses represent the key step toward the application of knowledge for therapy development and design. Addressing the translational dilemma will require utilizing the ever-increasing power of computers and computational modeling to increase the efficiency of the scientific method in the identification and evaluation of hypotheses of mechanistic causality. More specifically, development needs to focus on facilitating the ability of non-computer trained biomedical researchers to utilize and instantiate their knowledge in dynamic computational models. This is termed "dynamic knowledge representation." Agent-based modeling is an object-oriented, discrete-event, rule-based simulation method that is well suited for biomedical dynamic knowledge representation. Agent-based modeling has been used in the study of inflammation at multiple scales. The ability of agent-based modeling to encompass multiple scales of biological process as well as spatial considerations, coupled with an intuitive modeling paradigm, suggest that this modeling framework is well suited for addressing the translational dilemma. This review describes agent-based modeling, gives examples of its applications in the study of inflammation, and introduces a proposed general expansion of the use of modeling and simulation to augment the generation and evaluation of knowledge by the biomedical research community at large.

Chapter 1: Biomedical Knowledge Integration

PubMed Central

Payne, Philip R. O.

2012-01-01

The modern biomedical research and healthcare delivery domains have seen an unparalleled increase in the rate of innovation and novel technologies over the past several decades. Catalyzed by paradigm-shifting public and private programs focusing upon the formation and delivery of genomic and personalized medicine, the need for high-throughput and integrative approaches to the collection, management, and analysis of heterogeneous data sets has become imperative. This need is particularly pressing in the translational bioinformatics domain, where many fundamental research questions require the integration of large scale, multi-dimensional clinical phenotype and bio-molecular data sets. Modern biomedical informatics theory and practice has demonstrated the distinct benefits associated with the use of knowledge-based systems in such contexts. A knowledge-based system can be defined as an intelligent agent that employs a computationally tractable knowledge base or repository in order to reason upon data in a targeted domain and reproduce expert performance relative to such reasoning operations. The ultimate goal of the design and use of such agents is to increase the reproducibility, scalability, and accessibility of complex reasoning tasks. Examples of the application of knowledge-based systems in biomedicine span a broad spectrum, from the execution of clinical decision support, to epidemiologic surveillance of public data sets for the purposes of detecting emerging infectious diseases, to the discovery of novel hypotheses in large-scale research data sets. In this chapter, we will review the basic theoretical frameworks that define core knowledge types and reasoning operations with particular emphasis on the applicability of such conceptual models within the biomedical domain, and then go on to introduce a number of prototypical data integration requirements and patterns relevant to the conduct of translational bioinformatics that can be addressed via the design and use of knowledge-based systems. PMID:23300416

Knowledge acquisition, semantic text mining, and security risks in health and biomedical informatics

PubMed Central

Huang, Jingshan; Dou, Dejing; Dang, Jiangbo; Pardue, J Harold; Qin, Xiao; Huan, Jun; Gerthoffer, William T; Tan, Ming

2012-01-01

Computational techniques have been adopted in medical and biological systems for a long time. There is no doubt that the development and application of computational methods will render great help in better understanding biomedical and biological functions. Large amounts of datasets have been produced by biomedical and biological experiments and simulations. In order for researchers to gain knowledge from original data, nontrivial transformation is necessary, which is regarded as a critical link in the chain of knowledge acquisition, sharing, and reuse. Challenges that have been encountered include: how to efficiently and effectively represent human knowledge in formal computing models, how to take advantage of semantic text mining techniques rather than traditional syntactic text mining, and how to handle security issues during the knowledge sharing and reuse. This paper summarizes the state-of-the-art in these research directions. We aim to provide readers with an introduction of major computing themes to be applied to the medical and biological research. PMID:22371823

The Application of Integrated Knowledge-based Systems for the Biomedical Risk Assessment Intelligent Network (BRAIN)

NASA Technical Reports Server (NTRS)

Loftin, Karin C.; Ly, Bebe; Webster, Laurie; Verlander, James; Taylor, Gerald R.; Riley, Gary; Culbert, Chris; Holden, Tina; Rudisill, Marianne

1993-01-01

One of NASA's goals for long duration space flight is to maintain acceptable levels of crew health, safety, and performance. One way of meeting this goal is through the Biomedical Risk Assessment Intelligent Network (BRAIN), an integrated network of both human and computer elements. The BRAIN will function as an advisor to flight surgeons by assessing the risk of in-flight biomedical problems and recommending appropriate countermeasures. This paper describes the joint effort among various NASA elements to develop BRAIN and an Infectious Disease Risk Assessment (IDRA) prototype. The implementation of this effort addresses the technological aspects of the following: (1) knowledge acquisition; (2) integration of IDRA components; (3) use of expert systems to automate the biomedical prediction process; (4) development of a user-friendly interface; and (5) integration of the IDRA prototype and Exercise Countermeasures Intelligent System (ExerCISys). Because the C Language, CLIPS (the C Language Integrated Production System), and the X-Window System were portable and easily integrated, they were chosen as the tools for the initial IDRA prototype. The feasibility was tested by developing an IDRA prototype that predicts the individual risk of influenza. The application of knowledge-based systems to risk assessment is of great market value to the medical technology industry.

Pattern recognition and expert image analysis systems in biomedical image processing (Invited Paper)

NASA Astrophysics Data System (ADS)

Oosterlinck, A.; Suetens, P.; Wu, Q.; Baird, M.; F. M., C.

1987-09-01

This paper gives an overview of pattern recoanition techniques (P.R.) used in biomedical image processing and problems related to the different P.R. solutions. Also the use of knowledge based systems to overcome P.R. difficulties, is described. This is illustrated by a common example ofabiomedical image processing application.

Text Mining in Biomedical Domain with Emphasis on Document Clustering.

PubMed

Renganathan, Vinaitheerthan

2017-07-01

With the exponential increase in the number of articles published every year in the biomedical domain, there is a need to build automated systems to extract unknown information from the articles published. Text mining techniques enable the extraction of unknown knowledge from unstructured documents. This paper reviews text mining processes in detail and the software tools available to carry out text mining. It also reviews the roles and applications of text mining in the biomedical domain. Text mining processes, such as search and retrieval of documents, pre-processing of documents, natural language processing, methods for text clustering, and methods for text classification are described in detail. Text mining techniques can facilitate the mining of vast amounts of knowledge on a given topic from published biomedical research articles and draw meaningful conclusions that are not possible otherwise.

Concept recognition for extracting protein interaction relations from biomedical text

PubMed Central

Baumgartner, William A; Lu, Zhiyong; Johnson, Helen L; Caporaso, J Gregory; Paquette, Jesse; Lindemann, Anna; White, Elizabeth K; Medvedeva, Olga; Cohen, K Bretonnel; Hunter, Lawrence

2008-01-01

Background: Reliable information extraction applications have been a long sought goal of the biomedical text mining community, a goal that if reached would provide valuable tools to benchside biologists in their increasingly difficult task of assimilating the knowledge contained in the biomedical literature. We present an integrated approach to concept recognition in biomedical text. Concept recognition provides key information that has been largely missing from previous biomedical information extraction efforts, namely direct links to well defined knowledge resources that explicitly cement the concept's semantics. The BioCreative II tasks discussed in this special issue have provided a unique opportunity to demonstrate the effectiveness of concept recognition in the field of biomedical language processing. Results: Through the modular construction of a protein interaction relation extraction system, we present several use cases of concept recognition in biomedical text, and relate these use cases to potential uses by the benchside biologist. Conclusion: Current information extraction technologies are approaching performance standards at which concept recognition can begin to deliver high quality data to the benchside biologist. Our system is available as part of the BioCreative Meta-Server project and on the internet . PMID:18834500

Unsupervised Transfer Learning via Multi-Scale Convolutional Sparse Coding for Biomedical Applications

PubMed Central

Chang, Hang; Han, Ju; Zhong, Cheng; Snijders, Antoine M.; Mao, Jian-Hua

2017-01-01

The capabilities of (I) learning transferable knowledge across domains; and (II) fine-tuning the pre-learned base knowledge towards tasks with considerably smaller data scale are extremely important. Many of the existing transfer learning techniques are supervised approaches, among which deep learning has the demonstrated power of learning domain transferrable knowledge with large scale network trained on massive amounts of labeled data. However, in many biomedical tasks, both the data and the corresponding label can be very limited, where the unsupervised transfer learning capability is urgently needed. In this paper, we proposed a novel multi-scale convolutional sparse coding (MSCSC) method, that (I) automatically learns filter banks at different scales in a joint fashion with enforced scale-specificity of learned patterns; and (II) provides an unsupervised solution for learning transferable base knowledge and fine-tuning it towards target tasks. Extensive experimental evaluation of MSCSC demonstrates the effectiveness of the proposed MSCSC in both regular and transfer learning tasks in various biomedical domains. PMID:28129148

Text Mining in Biomedical Domain with Emphasis on Document Clustering

PubMed Central

2017-01-01

Objectives With the exponential increase in the number of articles published every year in the biomedical domain, there is a need to build automated systems to extract unknown information from the articles published. Text mining techniques enable the extraction of unknown knowledge from unstructured documents. Methods This paper reviews text mining processes in detail and the software tools available to carry out text mining. It also reviews the roles and applications of text mining in the biomedical domain. Results Text mining processes, such as search and retrieval of documents, pre-processing of documents, natural language processing, methods for text clustering, and methods for text classification are described in detail. Conclusions Text mining techniques can facilitate the mining of vast amounts of knowledge on a given topic from published biomedical research articles and draw meaningful conclusions that are not possible otherwise. PMID:28875048

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.

Silk Materials Functionalized via Genetic Engineering for Biomedical Applications.

PubMed

Deptuch, Tomasz; Dams-Kozlowska, Hanna

2017-12-12

The great mechanical properties, biocompatibility and biodegradability of silk-based materials make them applicable to the biomedical field. Genetic engineering enables the construction of synthetic equivalents of natural silks. Knowledge about the relationship between the structure and function of silk proteins enables the design of bioengineered silks that can serve as the foundation of new biomaterials. Furthermore, in order to better address the needs of modern biomedicine, genetic engineering can be used to obtain silk-based materials with new functionalities. Sequences encoding new peptides or domains can be added to the sequences encoding the silk proteins. The expression of one cDNA fragment indicates that each silk molecule is related to a functional fragment. This review summarizes the proposed genetic functionalization of silk-based materials that can be potentially useful for biomedical applications.

The SWAN biomedical discourse ontology.

PubMed

Ciccarese, Paolo; Wu, Elizabeth; Wong, Gwen; Ocana, Marco; Kinoshita, June; Ruttenberg, Alan; Clark, Tim

2008-10-01

Developing cures for highly complex diseases, such as neurodegenerative disorders, requires extensive interdisciplinary collaboration and exchange of biomedical information in context. Our ability to exchange such information across sub-specialties today is limited by the current scientific knowledge ecosystem's inability to properly contextualize and integrate data and discourse in machine-interpretable form. This inherently limits the productivity of research and the progress toward cures for devastating diseases such as Alzheimer's and Parkinson's. SWAN (Semantic Web Applications in Neuromedicine) is an interdisciplinary project to develop a practical, common, semantically structured, framework for biomedical discourse initially applied, but not limited, to significant problems in Alzheimer Disease (AD) research. The SWAN ontology has been developed in the context of building a series of applications for biomedical researchers, as well as in extensive discussions and collaborations with the larger bio-ontologies community. In this paper, we present and discuss the SWAN ontology of biomedical discourse. We ground its development theoretically, present its design approach, explain its main classes and their application, and show its relationship to other ongoing activities in biomedicine and bio-ontologies.

Structural Design and Physicochemical Foundations of Hydrogels for Biomedical Applications.

PubMed

Li, Qingyong; Ning, Zhengxiang; Ren, Jiaoyan; Liao, Wenzhen

2018-01-01

Biomedical research, known as medical research, is conducive to support and promote the development of knowledge in the field of medicine. Hydrogels have been extensively used in many biomedical fields due to their highly absorbent and flexible properties. The smart hydrogels, especially, can respond to a broad range of external stimuli such as temperature, pH value, light, electric and magnetic fields. With excellent biocompatibility, tunable rheology, mechanical properties, porosity, and hydrated molecular structure, hydrogels are considered as promising candidate for simulating local tissue microenvironment. In this review article, we mainly focused on the most recent development of engineering synthetic hydrogels; moreover, the classification, properties, especially the biomedical applications including tissue engineering and cell scaffolding, drug and gene delivery, immunotherapies and vaccines, are summarized and discussed. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

UMLS content views appropriate for NLP processing of the biomedical literature vs. clinical text.

PubMed

Demner-Fushman, Dina; Mork, James G; Shooshan, Sonya E; Aronson, Alan R

2010-08-01

Identification of medical terms in free text is a first step in such Natural Language Processing (NLP) tasks as automatic indexing of biomedical literature and extraction of patients' problem lists from the text of clinical notes. Many tools developed to perform these tasks use biomedical knowledge encoded in the Unified Medical Language System (UMLS) Metathesaurus. We continue our exploration of automatic approaches to creation of subsets (UMLS content views) which can support NLP processing of either the biomedical literature or clinical text. We found that suppression of highly ambiguous terms in the conservative AutoFilter content view can partially replace manual filtering for literature applications, and suppression of two character mappings in the same content view achieves 89.5% precision at 78.6% recall for clinical applications. Published by Elsevier Inc.

Organization and integration of biomedical knowledge with concept maps for key peroxisomal pathways.

PubMed

Willemsen, A M; Jansen, G A; Komen, J C; van Hooff, S; Waterham, H R; Brites, P M T; Wanders, R J A; van Kampen, A H C

2008-08-15

One important area of clinical genomics research involves the elucidation of molecular mechanisms underlying (complex) disorders which eventually may lead to new diagnostic or drug targets. To further advance this area of clinical genomics one of the main challenges is the acquisition and integration of data, information and expert knowledge for specific biomedical domains and diseases. Currently the required information is not very well organized but scattered over biological and biomedical databases, basic text books, scientific literature and experts' minds and may be highly specific, heterogeneous, complex and voluminous. We present a new framework to construct knowledge bases with concept maps for presentation of information and the web ontology language OWL for the representation of information. We demonstrate this framework through the construction of a peroxisomal knowledge base, which focuses on four key peroxisomal pathways and several related genetic disorders. All 155 concept maps in our knowledge base are linked to at least one other concept map, which allows the visualization of one big network of related pieces of information. The peroxisome knowledge base is available from www.bioinformaticslaboratory.nl (Support-->Web applications). Supplementary data is available from www.bioinformaticslaboratory.nl (Research-->Output--> Publications--> KB_SuppInfo)

k-neighborhood Decentralization: A Comprehensive Solution to Index the UMLS for Large Scale Knowledge Discovery

PubMed Central

Xiang, Yang; Lu, Kewei; James, Stephen L.; Borlawsky, Tara B.; Huang, Kun; Payne, Philip R.O.

2011-01-01

The Unified Medical Language System (UMLS) is the largest thesaurus in the biomedical informatics domain. Previous works have shown that knowledge constructs comprised of transitively-associated UMLS concepts are effective for discovering potentially novel biomedical hypotheses. However, the extremely large size of the UMLS becomes a major challenge for these applications. To address this problem, we designed a k-neighborhood Decentralization Labeling Scheme (kDLS) for the UMLS, and the corresponding method to effectively evaluate the kDLS indexing results. kDLS provides a comprehensive solution for indexing the UMLS for very efficient large scale knowledge discovery. We demonstrated that it is highly effective to use kDLS paths to prioritize disease-gene relations across the whole genome, with extremely high fold-enrichment values. To our knowledge, this is the first indexing scheme capable of supporting efficient large scale knowledge discovery on the UMLS as a whole. Our expectation is that kDLS will become a vital engine for retrieving information and generating hypotheses from the UMLS for future medical informatics applications. PMID:22154838

k-Neighborhood decentralization: a comprehensive solution to index the UMLS for large scale knowledge discovery.

PubMed

Xiang, Yang; Lu, Kewei; James, Stephen L; Borlawsky, Tara B; Huang, Kun; Payne, Philip R O

2012-04-01

The Unified Medical Language System (UMLS) is the largest thesaurus in the biomedical informatics domain. Previous works have shown that knowledge constructs comprised of transitively-associated UMLS concepts are effective for discovering potentially novel biomedical hypotheses. However, the extremely large size of the UMLS becomes a major challenge for these applications. To address this problem, we designed a k-neighborhood Decentralization Labeling Scheme (kDLS) for the UMLS, and the corresponding method to effectively evaluate the kDLS indexing results. kDLS provides a comprehensive solution for indexing the UMLS for very efficient large scale knowledge discovery. We demonstrated that it is highly effective to use kDLS paths to prioritize disease-gene relations across the whole genome, with extremely high fold-enrichment values. To our knowledge, this is the first indexing scheme capable of supporting efficient large scale knowledge discovery on the UMLS as a whole. Our expectation is that kDLS will become a vital engine for retrieving information and generating hypotheses from the UMLS for future medical informatics applications. Copyright © 2011 Elsevier Inc. All rights reserved.

Immediate detailed feedback to test-enhanced learning: an effective online educational tool.

PubMed

Wojcikowski, Ken; Kirk, Leslie

2013-11-01

Test-enhanced learning has gained popularity because it is an effective way to increase retention of knowledge; provided the student receives the correct answer soon after the test is taken. To determine whether detailed feedback provided to test-enhanced learning questions is an effective online educational tool for improving performance on complex biomedical information exams. A series of online multiple choice tests were developed to test knowledge of biomedical information that students were expected to know after each patient-case. Following submission of the student answers, one cohort (n = 52) received answers only while the following year, a second cohort (n = 51) received the answers with detailed feedback explaining why each answer was correct or incorrect. Students in both groups progressed through the series of online tests with little assessor intervention. Students receiving the answers along with the explanations within their feedback performed significantly better in the final biomedical information exam than those students receiving correct answers only. This pilot study found that the detailed feedback to test-enhanced learning questions is an important online learning tool. The increase in student performance in the complex biomedical information exam in this study suggests that detailed feedback should be investigated not only for increasing knowledge, but also be investigated for its effect on retention and application of knowledge.

Silk Materials Functionalized via Genetic Engineering for Biomedical Applications

PubMed Central

Deptuch, Tomasz

2017-01-01

The great mechanical properties, biocompatibility and biodegradability of silk-based materials make them applicable to the biomedical field. Genetic engineering enables the construction of synthetic equivalents of natural silks. Knowledge about the relationship between the structure and function of silk proteins enables the design of bioengineered silks that can serve as the foundation of new biomaterials. Furthermore, in order to better address the needs of modern biomedicine, genetic engineering can be used to obtain silk-based materials with new functionalities. Sequences encoding new peptides or domains can be added to the sequences encoding the silk proteins. The expression of one cDNA fragment indicates that each silk molecule is related to a functional fragment. This review summarizes the proposed genetic functionalization of silk-based materials that can be potentially useful for biomedical applications. PMID:29231863

Research Trend Visualization by MeSH Terms from PubMed.

PubMed

Yang, Heyoung; Lee, Hyuck Jai

2018-05-30

Motivation : PubMed is a primary source of biomedical information comprising search tool function and the biomedical literature from MEDLINE which is the US National Library of Medicine premier bibliographic database, life science journals and online books. Complimentary tools to PubMed have been developed to help the users search for literature and acquire knowledge. However, these tools are insufficient to overcome the difficulties of the users due to the proliferation of biomedical literature. A new method is needed for searching the knowledge in biomedical field. Methods : A new method is proposed in this study for visualizing the recent research trends based on the retrieved documents corresponding to a search query given by the user. The Medical Subject Headings (MeSH) are used as the primary analytical element. MeSH terms are extracted from the literature and the correlations between them are calculated. A MeSH network, called MeSH Net, is generated as the final result based on the Pathfinder Network algorithm. Results : A case study for the verification of proposed method was carried out on a research area defined by the search query (immunotherapy and cancer and "tumor microenvironment"). The MeSH Net generated by the method is in good agreement with the actual research activities in the research area (immunotherapy). Conclusion : A prototype application generating MeSH Net was developed. The application, which could be used as a "guide map for travelers", allows the users to quickly and easily acquire the knowledge of research trends. Combination of PubMed and MeSH Net is expected to be an effective complementary system for the researchers in biomedical field experiencing difficulties with search and information analysis.

Learning through projects in the training of biomedical engineers: an application experience

NASA Astrophysics Data System (ADS)

Gambi, José Antonio Li; Peme, Carmen

2011-09-01

Learning through Projects in the curriculum consists of both the identification and analysis of a problem, and the design of solution, execution and evaluation strategies, with teams of students. The project is conceived as the creation of a set of strategies articulated and developed during a certain amount of time to solve a problem contextualized in situations continually changing, where the constant evaluation provides feedback to make adjustments. In 2009, Learning through Projects was applied on the subject Hospital Facilities and three intervention projects were developed in health centers. This first stage is restricted to the analysis of the aspects that are considered to be basic to the professional training: a) Context knowledge: The future biomedical engineers must be familiarized with the complex health system where they will develop their profession; b) Team work: This is one of the essential skills in the training of students, since Biomedical Engineering connects the knowledge of sciences of life with the knowledge of exact sciences and technology; c) Regulations: The activities related to the profession require the implementation of regulations; therefore, to be aware of and to apply these regulations is a fundamental aspect to be analyzed in this stage; d) Project evaluation: It refers to the elaboration and studying of co-evaluation reports, which helps to find out if Learning through Projects contributes to the training. This new line of investigation has the purpose of discovering if the application of this learning strategy makes changes in the training of students in relation to their future professional career. The findings of this ongoing investigation will allow for the analysis of the possibility of extending its application. Key words: engineering, biomedical, learning, projects, strategies.

Data Analysis and Data Mining: Current Issues in Biomedical Informatics

PubMed Central

Bellazzi, Riccardo; Diomidous, Marianna; Sarkar, Indra Neil; Takabayashi, Katsuhiko; Ziegler, Andreas; McCray, Alexa T.

2011-01-01

Summary Background Medicine and biomedical sciences have become data-intensive fields, which, at the same time, enable the application of data-driven approaches and require sophisticated data analysis and data mining methods. Biomedical informatics provides a proper interdisciplinary context to integrate data and knowledge when processing available information, with the aim of giving effective decision-making support in clinics and translational research. Objectives To reflect on different perspectives related to the role of data analysis and data mining in biomedical informatics. Methods On the occasion of the 50th year of Methods of Information in Medicine a symposium was organized, that reflected on opportunities, challenges and priorities of organizing, representing and analysing data, information and knowledge in biomedicine and health care. The contributions of experts with a variety of backgrounds in the area of biomedical data analysis have been collected as one outcome of this symposium, in order to provide a broad, though coherent, overview of some of the most interesting aspects of the field. Results The paper presents sections on data accumulation and data-driven approaches in medical informatics, data and knowledge integration, statistical issues for the evaluation of data mining models, translational bioinformatics and bioinformatics aspects of genetic epidemiology. Conclusions Biomedical informatics represents a natural framework to properly and effectively apply data analysis and data mining methods in a decision-making context. In the future, it will be necessary to preserve the inclusive nature of the field and to foster an increasing sharing of data and methods between researchers. PMID:22146916

BioPortal: enhanced functionality via new Web services from the National Center for Biomedical Ontology to access and use ontologies in software applications.

PubMed

Whetzel, Patricia L; Noy, Natalya F; Shah, Nigam H; Alexander, Paul R; Nyulas, Csongor; Tudorache, Tania; Musen, Mark A

2011-07-01

The National Center for Biomedical Ontology (NCBO) is one of the National Centers for Biomedical Computing funded under the NIH Roadmap Initiative. Contributing to the national computing infrastructure, NCBO has developed BioPortal, a web portal that provides access to a library of biomedical ontologies and terminologies (http://bioportal.bioontology.org) via the NCBO Web services. BioPortal enables community participation in the evaluation and evolution of ontology content by providing features to add mappings between terms, to add comments linked to specific ontology terms and to provide ontology reviews. The NCBO Web services (http://www.bioontology.org/wiki/index.php/NCBO_REST_services) enable this functionality and provide a uniform mechanism to access ontologies from a variety of knowledge representation formats, such as Web Ontology Language (OWL) and Open Biological and Biomedical Ontologies (OBO) format. The Web services provide multi-layered access to the ontology content, from getting all terms in an ontology to retrieving metadata about a term. Users can easily incorporate the NCBO Web services into software applications to generate semantically aware applications and to facilitate structured data collection.

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/.

From bench to bedside and to health policies: ethics in translational research.

PubMed

Petrini, C

2011-01-01

Translation of biomedical research knowledge to effective clinical treatment is essential to the public good. The first level of translation ("from bench to bedside") corresponds to efficacy studies under controlled conditions with careful attention to internal validity (clinical research). The second level is the translation of results from clinical studies into everyday clinical practice and health decision making. The article summarises the ethical issues involved in the translation of biomedical research advances to clinical applications and to clinical practice. In particular, the article synthesizes theory from clinical ethics, operational design, and philosophy to examine the unique bioethical issues raised by the recent focus on translational research. In this framework safety of study participants and balancing of risk due to treatment with the potential benefits of the research are crucial: in clinical research there is a danger that the emphasis on advancements in scientific knowledge might prevail over the protection of the people who participate in research. These issues involve basic scientists, clinicians and bioethicists because of their application to comparative effectiveness research, clinical trials and evidence-based medicine, as well basic biomedical research.

Toxicity of inorganic nanomaterials in biomedical imaging.

PubMed

Li, Jinxia; Chang, Xueling; Chen, Xiaoxia; Gu, Zhanjun; Zhao, Feng; Chai, Zhifang; Zhao, Yuliang

2014-01-01

Inorganic nanoparticles have shown promising potentials as novel biomedical imaging agents with high sensitivity, high spatial and temporal resolution. To translate the laboratory innovations into clinical applications, their potential toxicities are highly concerned and have to be evaluated comprehensively both in vitro and in vivo before their clinical applications. In this review, we first summarized the in vivo and in vitro toxicities of the representative inorganic nanoparticles used in biomedical imagings. Then we further discuss the origin of nanotoxicity of inorganic nanomaterials, including ROS generation and oxidative stress, chemical instability, chemical composition, the surface modification, dissolution of nanoparticles to release excess free ions of metals, metal redox state, and left-over chemicals from synthesis, etc. We intend to provide the readers a better understanding of the toxicology aspects of inorganic nanomaterials and knowledge for achieving optimized designs of safer inorganic nanomaterials for clinical applications. Copyright © 2014 Elsevier Inc. All rights reserved.

Biomedical literature classification using encyclopedic knowledge: a Wikipedia-based bag-of-concepts approach.

PubMed

Mouriño García, Marcos Antonio; Pérez Rodríguez, Roberto; Anido Rifón, Luis E

2015-01-01

Automatic classification of text documents into a set of categories has a lot of applications. Among those applications, the automatic classification of biomedical literature stands out as an important application for automatic document classification strategies. Biomedical staff and researchers have to deal with a lot of literature in their daily activities, so it would be useful a system that allows for accessing to documents of interest in a simple and effective way; thus, it is necessary that these documents are sorted based on some criteria-that is to say, they have to be classified. Documents to classify are usually represented following the bag-of-words (BoW) paradigm. Features are words in the text-thus suffering from synonymy and polysemy-and their weights are just based on their frequency of occurrence. This paper presents an empirical study of the efficiency of a classifier that leverages encyclopedic background knowledge-concretely Wikipedia-in order to create bag-of-concepts (BoC) representations of documents, understanding concept as "unit of meaning", and thus tackling synonymy and polysemy. Besides, the weighting of concepts is based on their semantic relevance in the text. For the evaluation of the proposal, empirical experiments have been conducted with one of the commonly used corpora for evaluating classification and retrieval of biomedical information, OHSUMED, and also with a purpose-built corpus of MEDLINE biomedical abstracts, UVigoMED. Results obtained show that the Wikipedia-based bag-of-concepts representation outperforms the classical bag-of-words representation up to 157% in the single-label classification problem and up to 100% in the multi-label problem for OHSUMED corpus, and up to 122% in the single-label classification problem and up to 155% in the multi-label problem for UVigoMED corpus.

Recent progress in automatically extracting information from the pharmacogenomic literature

PubMed Central

Garten, Yael; Coulet, Adrien; Altman, Russ B

2011-01-01

The biomedical literature holds our understanding of pharmacogenomics, but it is dispersed across many journals. In order to integrate our knowledge, connect important facts across publications and generate new hypotheses we must organize and encode the contents of the literature. By creating databases of structured pharmocogenomic knowledge, we can make the value of the literature much greater than the sum of the individual reports. We can, for example, generate candidate gene lists or interpret surprising hits in genome-wide association studies. Text mining automatically adds structure to the unstructured knowledge embedded in millions of publications, and recent years have seen a surge in work on biomedical text mining, some specific to pharmacogenomics literature. These methods enable extraction of specific types of information and can also provide answers to general, systemic queries. In this article, we describe the main tasks of text mining in the context of pharmacogenomics, summarize recent applications and anticipate the next phase of text mining applications. PMID:21047206

A methodology for extending domain coverage in SemRep.

PubMed

Rosemblat, Graciela; Shin, Dongwook; Kilicoglu, Halil; Sneiderman, Charles; Rindflesch, Thomas C

2013-12-01

We describe a domain-independent methodology to extend SemRep coverage beyond the biomedical domain. SemRep, a natural language processing application originally designed for biomedical texts, uses the knowledge sources provided by the Unified Medical Language System (UMLS©). Ontological and terminological extensions to the system are needed in order to support other areas of knowledge. We extended SemRep's application by developing a semantic representation of a previously unsupported domain. This was achieved by adapting well-known ontology engineering phases and integrating them with the UMLS knowledge sources on which SemRep crucially depends. While the process to extend SemRep coverage has been successfully applied in earlier projects, this paper presents in detail the step-wise approach we followed and the mechanisms implemented. A case study in the field of medical informatics illustrates how the ontology engineering phases have been adapted for optimal integration with the UMLS. We provide qualitative and quantitative results, which indicate the validity and usefulness of our methodology. Published by Elsevier Inc.

Assessing the practice of biomedical ontology evaluation: Gaps and opportunities.

PubMed

Amith, Muhammad; He, Zhe; Bian, Jiang; Lossio-Ventura, Juan Antonio; Tao, Cui

2018-04-01

With the proliferation of heterogeneous health care data in the last three decades, biomedical ontologies and controlled biomedical terminologies play a more and more important role in knowledge representation and management, data integration, natural language processing, as well as decision support for health information systems and biomedical research. Biomedical ontologies and controlled terminologies are intended to assure interoperability. Nevertheless, the quality of biomedical ontologies has hindered their applicability and subsequent adoption in real-world applications. Ontology evaluation is an integral part of ontology development and maintenance. In the biomedicine domain, ontology evaluation is often conducted by third parties as a quality assurance (or auditing) effort that focuses on identifying modeling errors and inconsistencies. In this work, we first organized four categorical schemes of ontology evaluation methods in the existing literature to create an integrated taxonomy. Further, to understand the ontology evaluation practice in the biomedicine domain, we reviewed a sample of 200 ontologies from the National Center for Biomedical Ontology (NCBO) BioPortal-the largest repository for biomedical ontologies-and observed that only 15 of these ontologies have documented evaluation in their corresponding inception papers. We then surveyed the recent quality assurance approaches for biomedical ontologies and their use. We also mapped these quality assurance approaches to the ontology evaluation criteria. It is our anticipation that ontology evaluation and quality assurance approaches will be more widely adopted in the development life cycle of biomedical ontologies. Copyright © 2018 Elsevier Inc. All rights reserved.

The application of integrated knowledge-based systems for the Biomedical Risk Assessment Intelligent Network (BRAIN)

NASA Technical Reports Server (NTRS)

Loftin, Karin C.; Ly, Bebe; Webster, Laurie; Verlander, James; Taylor, Gerald R.; Riley, Gary; Culbert, Chris

1992-01-01

One of NASA's goals for long duration space flight is to maintain acceptable levels of crew health, safety, and performance. One way of meeting this goal is through BRAIN, an integrated network of both human and computer elements. BRAIN will function as an advisor to mission managers by assessing the risk of inflight biomedical problems and recommending appropriate countermeasures. Described here is a joint effort among various NASA elements to develop BRAIN and the Infectious Disease Risk Assessment (IDRA) prototype. The implementation of this effort addresses the technological aspects of knowledge acquisition, integration of IDRA components, the use of expert systems to automate the biomedical prediction process, development of a user friendly interface, and integration of IDRA and ExerCISys systems. Because C language, CLIPS and the X-Window System are portable and easily integrated, they were chosen ss the tools for the initial IDRA prototype.

Semantic similarity between ontologies at different scales

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

Zhang, Qingpeng; Haglin, David J.

In the past decade, existing and new knowledge and datasets has been encoded in different ontologies for semantic web and biomedical research. The size of ontologies is often very large in terms of number of concepts and relationships, which makes the analysis of ontologies and the represented knowledge graph computational and time consuming. As the ontologies of various semantic web and biomedical applications usually show explicit hierarchical structures, it is interesting to explore the trade-offs between ontological scales and preservation/precision of results when we analyze ontologies. This paper presents the first effort of examining the capability of this idea viamore » studying the relationship between scaling biomedical ontologies at different levels and the semantic similarity values. We evaluate the semantic similarity between three Gene Ontology slims (Plant, Yeast, and Candida, among which the latter two belong to the same kingdom—Fungi) using four popular measures commonly applied to biomedical ontologies (Resnik, Lin, Jiang-Conrath, and SimRel). The results of this study demonstrate that with proper selection of scaling levels and similarity measures, we can significantly reduce the size of ontologies without losing substantial detail. In particular, the performance of Jiang-Conrath and Lin are more reliable and stable than that of the other two in this experiment, as proven by (a) consistently showing that Yeast and Candida are more similar (as compared to Plant) at different scales, and (b) small deviations of the similarity values after excluding a majority of nodes from several lower scales. This study provides a deeper understanding of the application of semantic similarity to biomedical ontologies, and shed light on how to choose appropriate semantic similarity measures for biomedical engineering.« less

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.

Semantic transference for enriching multilingual biomedical knowledge resources.

PubMed

Pérez, María; Berlanga, Rafael

2015-12-01

Biomedical knowledge resources (KRs) are mainly expressed in English, and many applications using them suffer from the scarcity of knowledge in non-English languages. The goal of the present work is to take maximum profit from existing multilingual biomedical KRs lexicons to enrich their non-English counterparts. We propose to combine different automatic methods to generate pair-wise language alignments. More specifically, we use two well-known translation methods (GIZA++ and Moses), and we propose a new ad hoc method specially devised for multilingual KRs. Then, resulting alignments are used to transfer semantics between KRs across their languages. Transference quality is ensured by checking the semantic coherence of the generated alignments. Experiments have been carried out over the Spanish, French and German UMLS Metathesaurus counterparts. As a result, the enriched Spanish KR can grow up to 1,514,217 concepts (originally 286,659), the French KR up to 1,104,968 concepts (originally 83,119), and the German KR up to 1,136,020 concepts (originally 86,842). Copyright © 2015 Elsevier Inc. All rights reserved.

Revisit of Machine Learning Supported Biological and Biomedical Studies.

PubMed

Yu, Xiang-Tian; Wang, Lu; Zeng, Tao

2018-01-01

Generally, machine learning includes many in silico methods to transform the principles underlying natural phenomenon to human understanding information, which aim to save human labor, to assist human judge, and to create human knowledge. It should have wide application potential in biological and biomedical studies, especially in the era of big biological data. To look through the application of machine learning along with biological development, this review provides wide cases to introduce the selection of machine learning methods in different practice scenarios involved in the whole biological and biomedical study cycle and further discusses the machine learning strategies for analyzing omics data in some cutting-edge biological studies. Finally, the notes on new challenges for machine learning due to small-sample high-dimension are summarized from the key points of sample unbalance, white box, and causality.

Predicate Oriented Pattern Analysis for Biomedical Knowledge Discovery

PubMed Central

Shen, Feichen; Liu, Hongfang; Sohn, Sunghwan; Larson, David W.; Lee, Yugyung

2017-01-01

In the current biomedical data movement, numerous efforts have been made to convert and normalize a large number of traditional structured and unstructured data (e.g., EHRs, reports) to semi-structured data (e.g., RDF, OWL). With the increasing number of semi-structured data coming into the biomedical community, data integration and knowledge discovery from heterogeneous domains become important research problem. In the application level, detection of related concepts among medical ontologies is an important goal of life science research. It is more crucial to figure out how different concepts are related within a single ontology or across multiple ontologies by analysing predicates in different knowledge bases. However, the world today is one of information explosion, and it is extremely difficult for biomedical researchers to find existing or potential predicates to perform linking among cross domain concepts without any support from schema pattern analysis. Therefore, there is a need for a mechanism to do predicate oriented pattern analysis to partition heterogeneous ontologies into closer small topics and do query generation to discover cross domain knowledge from each topic. In this paper, we present such a model that predicates oriented pattern analysis based on their close relationship and generates a similarity matrix. Based on this similarity matrix, we apply an innovated unsupervised learning algorithm to partition large data sets into smaller and closer topics and generate meaningful queries to fully discover knowledge over a set of interlinked data sources. We have implemented a prototype system named BmQGen and evaluate the proposed model with colorectal surgical cohort from the Mayo Clinic. PMID:28983419

Rational engineering of physicochemical properties of nanomaterials for biomedical applications with nanotoxicological perspectives.

PubMed

Navya, P N; Daima, Hemant Kumar

2016-01-01

Innovative engineered nanomaterials are at the leading edge of rapidly emerging fields of nanobiotechnology and nanomedicine. Meticulous synthesis, unique physicochemical properties, manifestation of chemical or biological moieties on the surface of materials make engineered nanostructures suitable for a variety of biomedical applications. Besides, tailored nanomaterials exhibit entirely novel therapeutic applications with better functionality, sensitivity, efficiency and specificity due to their customized unique physicochemical and surface properties. Additionally, such designer made nanomaterials has potential to generate series of interactions with various biological entities including DNA, proteins, membranes, cells and organelles at nano-bio interface. These nano-bio interactions are driven by colloidal forces and predominantly depend on the dynamic physicochemical and surface properties of nanomaterials. Nevertheless, recent development and atomic scale tailoring of various physical, chemical and surface properties of nanomaterials is promising to dictate their interaction in anticipated manner with biological entities for biomedical applications. As a result, rationally designed nanomaterials are in extensive demand for bio-molecular detection and diagnostics, therapeutics, drug and gene delivery, fluorescent labelling, tissue engineering, biochemical sensing and other pharmaceuticals applications. However, toxicity and risk associated with engineered nanomaterials is rather unclear or not well understood; which is gaining considerable attention and the field of nanotoxicology is evolving promptly. Therefore, this review explores current knowledge of articulate engineering of nanomaterials for biomedical applications with special attention on potential toxicological perspectives.

Rational engineering of physicochemical properties of nanomaterials for biomedical applications with nanotoxicological perspectives

NASA Astrophysics Data System (ADS)

Navya, P. N.; Daima, Hemant Kumar

2016-02-01

Innovative engineered nanomaterials are at the leading edge of rapidly emerging fields of nanobiotechnology and nanomedicine. Meticulous synthesis, unique physicochemical properties, manifestation of chemical or biological moieties on the surface of materials make engineered nanostructures suitable for a variety of biomedical applications. Besides, tailored nanomaterials exhibit entirely novel therapeutic applications with better functionality, sensitivity, efficiency and specificity due to their customized unique physicochemical and surface properties. Additionally, such designer made nanomaterials has potential to generate series of interactions with various biological entities including DNA, proteins, membranes, cells and organelles at nano-bio interface. These nano-bio interactions are driven by colloidal forces and predominantly depend on the dynamic physicochemical and surface properties of nanomaterials. Nevertheless, recent development and atomic scale tailoring of various physical, chemical and surface properties of nanomaterials is promising to dictate their interaction in anticipated manner with biological entities for biomedical applications. As a result, rationally designed nanomaterials are in extensive demand for bio-molecular detection and diagnostics, therapeutics, drug and gene delivery, fluorescent labelling, tissue engineering, biochemical sensing and other pharmaceuticals applications. However, toxicity and risk associated with engineered nanomaterials is rather unclear or not well understood; which is gaining considerable attention and the field of nanotoxicology is evolving promptly. Therefore, this review explores current knowledge of articulate engineering of nanomaterials for biomedical applications with special attention on potential toxicological perspectives.

The Ontology for Biomedical Investigations.

PubMed

Bandrowski, Anita; Brinkman, Ryan; Brochhausen, Mathias; Brush, Matthew H; Bug, Bill; Chibucos, Marcus C; Clancy, Kevin; Courtot, Mélanie; Derom, Dirk; Dumontier, Michel; Fan, Liju; Fostel, Jennifer; Fragoso, Gilberto; Gibson, Frank; Gonzalez-Beltran, Alejandra; Haendel, Melissa A; He, Yongqun; Heiskanen, Mervi; Hernandez-Boussard, Tina; Jensen, Mark; Lin, Yu; Lister, Allyson L; Lord, Phillip; Malone, James; Manduchi, Elisabetta; McGee, Monnie; Morrison, Norman; Overton, James A; Parkinson, Helen; Peters, Bjoern; Rocca-Serra, Philippe; Ruttenberg, Alan; Sansone, Susanna-Assunta; Scheuermann, Richard H; Schober, Daniel; Smith, Barry; Soldatova, Larisa N; Stoeckert, Christian J; Taylor, Chris F; Torniai, Carlo; Turner, Jessica A; Vita, Randi; Whetzel, Patricia L; Zheng, Jie

2016-01-01

The Ontology for Biomedical Investigations (OBI) is an ontology that provides terms with precisely defined meanings to describe all aspects of how investigations in the biological and medical domains are conducted. OBI re-uses ontologies that provide a representation of biomedical knowledge from the Open Biological and Biomedical Ontologies (OBO) project and adds the ability to describe how this knowledge was derived. We here describe the state of OBI and several applications that are using it, such as adding semantic expressivity to existing databases, building data entry forms, and enabling interoperability between knowledge resources. OBI covers all phases of the investigation process, such as planning, execution and reporting. It represents information and material entities that participate in these processes, as well as roles and functions. Prior to OBI, it was not possible to use a single internally consistent resource that could be applied to multiple types of experiments for these applications. OBI has made this possible by creating terms for entities involved in biological and medical investigations and by importing parts of other biomedical ontologies such as GO, Chemical Entities of Biological Interest (ChEBI) and Phenotype Attribute and Trait Ontology (PATO) without altering their meaning. OBI is being used in a wide range of projects covering genomics, multi-omics, immunology, and catalogs of services. OBI has also spawned other ontologies (Information Artifact Ontology) and methods for importing parts of ontologies (Minimum information to reference an external ontology term (MIREOT)). The OBI project is an open cross-disciplinary collaborative effort, encompassing multiple research communities from around the globe. To date, OBI has created 2366 classes and 40 relations along with textual and formal definitions. The OBI Consortium maintains a web resource (http://obi-ontology.org) providing details on the people, policies, and issues being addressed in association with OBI. The current release of OBI is available at http://purl.obolibrary.org/obo/obi.owl.

The Ontology for Biomedical Investigations

PubMed Central

Bandrowski, Anita; Brinkman, Ryan; Brochhausen, Mathias; Brush, Matthew H.; Chibucos, Marcus C.; Clancy, Kevin; Courtot, Mélanie; Derom, Dirk; Dumontier, Michel; Fan, Liju; Fostel, Jennifer; Fragoso, Gilberto; Gibson, Frank; Gonzalez-Beltran, Alejandra; Haendel, Melissa A.; He, Yongqun; Heiskanen, Mervi; Hernandez-Boussard, Tina; Jensen, Mark; Lin, Yu; Lister, Allyson L.; Lord, Phillip; Malone, James; Manduchi, Elisabetta; McGee, Monnie; Morrison, Norman; Overton, James A.; Parkinson, Helen; Peters, Bjoern; Rocca-Serra, Philippe; Ruttenberg, Alan; Sansone, Susanna-Assunta; Scheuermann, Richard H.; Schober, Daniel; Smith, Barry; Soldatova, Larisa N.; Stoeckert, Christian J.; Taylor, Chris F.; Torniai, Carlo; Turner, Jessica A.; Vita, Randi; Whetzel, Patricia L.; Zheng, Jie

2016-01-01

The Ontology for Biomedical Investigations (OBI) is an ontology that provides terms with precisely defined meanings to describe all aspects of how investigations in the biological and medical domains are conducted. OBI re-uses ontologies that provide a representation of biomedical knowledge from the Open Biological and Biomedical Ontologies (OBO) project and adds the ability to describe how this knowledge was derived. We here describe the state of OBI and several applications that are using it, such as adding semantic expressivity to existing databases, building data entry forms, and enabling interoperability between knowledge resources. OBI covers all phases of the investigation process, such as planning, execution and reporting. It represents information and material entities that participate in these processes, as well as roles and functions. Prior to OBI, it was not possible to use a single internally consistent resource that could be applied to multiple types of experiments for these applications. OBI has made this possible by creating terms for entities involved in biological and medical investigations and by importing parts of other biomedical ontologies such as GO, Chemical Entities of Biological Interest (ChEBI) and Phenotype Attribute and Trait Ontology (PATO) without altering their meaning. OBI is being used in a wide range of projects covering genomics, multi-omics, immunology, and catalogs of services. OBI has also spawned other ontologies (Information Artifact Ontology) and methods for importing parts of ontologies (Minimum information to reference an external ontology term (MIREOT)). The OBI project is an open cross-disciplinary collaborative effort, encompassing multiple research communities from around the globe. To date, OBI has created 2366 classes and 40 relations along with textual and formal definitions. The OBI Consortium maintains a web resource (http://obi-ontology.org) providing details on the people, policies, and issues being addressed in association with OBI. The current release of OBI is available at http://purl.obolibrary.org/obo/obi.owl. PMID:27128319

An engineering paradigm in the biomedical sciences: Knowledge as epistemic tool.

PubMed

Boon, Mieke

2017-10-01

In order to deal with the complexity of biological systems and attempts to generate applicable results, current biomedical sciences are adopting concepts and methods from the engineering sciences. Philosophers of science have interpreted this as the emergence of an engineering paradigm, in particular in systems biology and synthetic biology. This article aims at the articulation of the supposed engineering paradigm by contrast with the physics paradigm that supported the rise of biochemistry and molecular biology. This articulation starts from Kuhn's notion of a disciplinary matrix, which indicates what constitutes a paradigm. It is argued that the core of the physics paradigm is its metaphysical and ontological presuppositions, whereas the core of the engineering paradigm is the epistemic aim of producing useful knowledge for solving problems external to the scientific practice. Therefore, the two paradigms involve distinct notions of knowledge. Whereas the physics paradigm entails a representational notion of knowledge, the engineering paradigm involves the notion of 'knowledge as epistemic tool'. Copyright © 2017 Elsevier Ltd. All rights reserved.

An infrastructure for ontology-based information systems in biomedicine: RICORDO case study.

PubMed

Wimalaratne, Sarala M; Grenon, Pierre; Hoehndorf, Robert; Gkoutos, Georgios V; de Bono, Bernard

2012-02-01

The article presents an infrastructure for supporting the semantic interoperability of biomedical resources based on the management (storing and inference-based querying) of their ontology-based annotations. This infrastructure consists of: (i) a repository to store and query ontology-based annotations; (ii) a knowledge base server with an inference engine to support the storage of and reasoning over ontologies used in the annotation of resources; (iii) a set of applications and services allowing interaction with the integrated repository and knowledge base. The infrastructure is being prototyped and developed and evaluated by the RICORDO project in support of the knowledge management of biomedical resources, including physiology and pharmacology models and associated clinical data. The RICORDO toolkit and its source code are freely available from http://ricordo.eu/relevant-resources. sarala@ebi.ac.uk.

MODELING MICROBUBBLE DYNAMICS IN BIOMEDICAL APPLICATIONS*

PubMed Central

CHAHINE, Georges L.; HSIAO, Chao-Tsung

2012-01-01

Controlling microbubble dynamics to produce desirable biomedical outcomes when and where necessary and avoid deleterious effects requires advanced knowledge, which can be achieved only through a combination of experimental and numerical/analytical techniques. The present communication presents a multi-physics approach to study the dynamics combining viscous- in-viscid effects, liquid and structure dynamics, and multi bubble interaction. While complex numerical tools are developed and used, the study aims at identifying the key parameters influencing the dynamics, which need to be included in simpler models. PMID:22833696

Bio-NCs--the marriage of ultrasmall metal nanoclusters with biomolecules.

PubMed

Goswami, Nirmal; Zheng, Kaiyuan; Xie, Jianping

2014-11-21

Ultrasmall metal nanoclusters (NCs) have attracted increasing attention due to their fascinating physicochemical properties. Today, functional metal NCs are finding growing acceptance in biomedical applications. To achieve a better performance in biomedical applications, metal NCs can be interfaced with biomolecules, such as proteins, peptides, and DNA, to form a new class of biomolecule-NC composites (or bio-NCs in short), which typically show synergistic or novel physicochemical and physiological properties. This feature article focuses on the recent studies emerging at the interface of metal NCs and biomolecules, where the interactions could impart unique physicochemical properties to the metal NCs, as well as mutually regulate biological functions of the bio-NCs. In this article, we first provide a broad overview of key concepts and developments in the novel biomolecule-directed synthesis of metal NCs. A special focus is placed on the key roles of biomolecules in metal NC synthesis. In the second part, we describe how the encapsulated metal NCs affect the structure and function of biomolecules. Followed by that, we discuss several unique synergistic effects observed in the bio-NCs, and illustrate them with examples highlighting their potential biomedical applications. Continued interdisciplinary efforts are required to build up in-depth knowledge about the interfacial chemistry and biology of bio-NCs, which could further pave their ways toward biomedical applications.

Bio-NCs - the marriage of ultrasmall metal nanoclusters with biomolecules

NASA Astrophysics Data System (ADS)

Goswami, Nirmal; Zheng, Kaiyuan; Xie, Jianping

2014-10-01

Ultrasmall metal nanoclusters (NCs) have attracted increasing attention due to their fascinating physicochemical properties. Today, functional metal NCs are finding growing acceptance in biomedical applications. To achieve a better performance in biomedical applications, metal NCs can be interfaced with biomolecules, such as proteins, peptides, and DNA, to form a new class of biomolecule-NC composites (or bio-NCs in short), which typically show synergistic or novel physicochemical and physiological properties. This feature article focuses on the recent studies emerging at the interface of metal NCs and biomolecules, where the interactions could impart unique physicochemical properties to the metal NCs, as well as mutually regulate biological functions of the bio-NCs. In this article, we first provide a broad overview of key concepts and developments in the novel biomolecule-directed synthesis of metal NCs. A special focus is placed on the key roles of biomolecules in metal NC synthesis. In the second part, we describe how the encapsulated metal NCs affect the structure and function of biomolecules. Followed by that, we discuss several unique synergistic effects observed in the bio-NCs, and illustrate them with examples highlighting their potential biomedical applications. Continued interdisciplinary efforts are required to build up in-depth knowledge about the interfacial chemistry and biology of bio-NCs, which could further pave their ways toward biomedical applications.

Investigating implicit knowledge in ontologies with application to the anatomical domain.

PubMed

Zhang, S; Bodenreider, O

2004-01-01

Knowledge in biomedical ontologies can be explicitly represented (often by means of semantic relations), but may also be implicit, i.e., embedded in the concept names and inferable from various combinations of semantic relations. This paper investigates implicit knowledge in two ontologies of anatomy: the Foundational Model of Anatomy and GALEN. The methods consist of extracting the knowledge explicitly represented, acquiring the implicit knowledge through augmentation and inference techniques, and identifying the origin of each semantic relation. The number of relations (12 million in FMA and 4.6 million in GALEN), broken down by source, is presented. Major findings include: each technique provides specific relations; and many relations can be generated by more than one technique. The application of these findings to ontology auditing, validation, and maintenance is discussed, as well as the application to ontology integration.

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

Adaptive Biomedical Innovation: Evolving Our Global System to Sustainably and Safely Bring New Medicines to Patients in Need

PubMed Central

Trusheim, M; Cobbs, E; Bala, M; Garner, S; Hartman, D; Isaacs, K; Lumpkin, M; Lim, R; Oye, K; Pezalla, E; Saltonstall, P; Selker, H

2016-01-01

The current system of biomedical innovation is unable to keep pace with scientific advancements. We propose to address this gap by reengineering innovation processes to accelerate reliable delivery of products that address unmet medical needs. Adaptive biomedical innovation (ABI) provides an integrative, strategic approach for process innovation. Although the term “ABI” is new, it encompasses fragmented “tools” that have been developed across the global pharmaceutical industry, and could accelerate the evolution of the system through more coordinated application. ABI involves bringing stakeholders together to set shared objectives, foster trust, structure decision‐making, and manage expectations through rapid‐cycle feedback loops that maximize product knowledge and reduce uncertainty in a continuous, adaptive, and sustainable learning healthcare system. Adaptive decision‐making, a core element of ABI, provides a framework for structuring decision‐making designed to manage two types of uncertainty – the maturity of scientific and clinical knowledge, and the behaviors of other critical stakeholders. PMID:27626610

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.

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.

Discovering and visualizing indirect associations between biomedical concepts

PubMed Central

Tsuruoka, Yoshimasa; Miwa, Makoto; Hamamoto, Kaisei; Tsujii, Jun'ichi; Ananiadou, Sophia

2011-01-01

Motivation: Discovering useful associations between biomedical concepts has been one of the main goals in biomedical text-mining, and understanding their biomedical contexts is crucial in the discovery process. Hence, we need a text-mining system that helps users explore various types of (possibly hidden) associations in an easy and comprehensible manner. Results: This article describes FACTA+, a real-time text-mining system for finding and visualizing indirect associations between biomedical concepts from MEDLINE abstracts. The system can be used as a text search engine like PubMed with additional features to help users discover and visualize indirect associations between important biomedical concepts such as genes, diseases and chemical compounds. FACTA+ inherits all functionality from its predecessor, FACTA, and extends it by incorporating three new features: (i) detecting biomolecular events in text using a machine learning model, (ii) discovering hidden associations using co-occurrence statistics between concepts, and (iii) visualizing associations to improve the interpretability of the output. To the best of our knowledge, FACTA+ is the first real-time web application that offers the functionality of finding concepts involving biomolecular events and visualizing indirect associations of concepts with both their categories and importance. Availability: FACTA+ is available as a web application at http://refine1-nactem.mc.man.ac.uk/facta/, and its visualizer is available at http://refine1-nactem.mc.man.ac.uk/facta-visualizer/. Contact: tsuruoka@jaist.ac.jp PMID:21685059

Accessing and integrating data and knowledge for biomedical research.

PubMed

Burgun, A; Bodenreider, O

2008-01-01

To review the issues that have arisen with the advent of translational research in terms of integration of data and knowledge, and survey current efforts to address these issues. Using examples form the biomedical literature, we identified new trends in biomedical research and their impact on bioinformatics. We analyzed the requirements for effective knowledge repositories and studied issues in the integration of biomedical knowledge. New diagnostic and therapeutic approaches based on gene expression patterns have brought about new issues in the statistical analysis of data, and new workflows are needed are needed to support translational research. Interoperable data repositories based on standard annotations, infrastructures and services are needed to support the pooling and meta-analysis of data, as well as their comparison to earlier experiments. High-quality, integrated ontologies and knowledge bases serve as a source of prior knowledge used in combination with traditional data mining techniques and contribute to the development of more effective data analysis strategies. As biomedical research evolves from traditional clinical and biological investigations towards omics sciences and translational research, specific needs have emerged, including integrating data collected in research studies with patient clinical data, linking omics knowledge with medical knowledge, modeling the molecular basis of diseases, and developing tools that support in-depth analysis of research data. As such, translational research illustrates the need to bridge the gap between bioinformatics and medical informatics, and opens new avenues for biomedical informatics research.

Explorative search of distributed bio-data to answer complex biomedical questions

PubMed Central

2014-01-01

Background The huge amount of biomedical-molecular data increasingly produced is providing scientists with potentially valuable information. Yet, such data quantity makes difficult to find and extract those data that are most reliable and most related to the biomedical questions to be answered, which are increasingly complex and often involve many different biomedical-molecular aspects. Such questions can be addressed only by comprehensively searching and exploring different types of data, which frequently are ordered and provided by different data sources. Search Computing has been proposed for the management and integration of ranked results from heterogeneous search services. Here, we present its novel application to the explorative search of distributed biomedical-molecular data and the integration of the search results to answer complex biomedical questions. Results A set of available bioinformatics search services has been modelled and registered in the Search Computing framework, and a Bioinformatics Search Computing application (Bio-SeCo) using such services has been created and made publicly available at http://www.bioinformatics.deib.polimi.it/bio-seco/seco/. It offers an integrated environment which eases search, exploration and ranking-aware combination of heterogeneous data provided by the available registered services, and supplies global results that can support answering complex multi-topic biomedical questions. Conclusions By using Bio-SeCo, scientists can explore the very large and very heterogeneous biomedical-molecular data available. They can easily make different explorative search attempts, inspect obtained results, select the most appropriate, expand or refine them and move forward and backward in the construction of a global complex biomedical query on multiple distributed sources that could eventually find the most relevant results. Thus, it provides an extremely useful automated support for exploratory integrated bio search, which is fundamental for Life Science data driven knowledge discovery. PMID:24564278

From biomedical-engineering research to clinical application and industrialization

NASA Astrophysics Data System (ADS)

Taguchi, Tetsushi; Aoyagi, Takao

2012-12-01

The rising costs and aging of the population due to a low birth rate negatively affect the healthcare system in Japan. In 2011, the Council for Science and Technology Policy released the 4th Japan's Science and Technology Basic Policy Report from 2011 to 2015. This report includes two major innovations, 'Life Innovation' and 'Green Innovation', to promote economic growth. Biomedical engineering research is part of 'Life Innovation' and its outcomes are required to maintain people's mental and physical health. It has already resulted in numerous biomedical products, and new ones should be developed using nanotechnology-based concepts. The combination of accumulated knowledge and experience, and 'nanoarchitechtonics' will result in novel, well-designed functional biomaterials. This focus issue contains three reviews and 19 original papers on various biomedical topics, including biomaterials, drug-delivery systems, tissue engineering and diagnostics. We hope that it demonstrates the importance of collaboration among scientists, engineers and clinicians, and will contribute to the further development of biomedical engineering.

What is biomedical informatics?

PubMed Central

Bernstam, Elmer V.; Smith, Jack W.; Johnson, Todd R.

2009-01-01

Biomedical informatics lacks a clear and theoretically grounded definition. Many proposed definitions focus on data, information, and knowledge, but do not provide an adequate definition of these terms. Leveraging insights from the philosophy of information, we define informatics as the science of information, where information is data plus meaning. Biomedical informatics is the science of information as applied to or studied in the context of biomedicine. Defining the object of study of informatics as data plus meaning clearly distinguishes the field from related fields, such as computer science, statistics and biomedicine, which have different objects of study. The emphasis on data plus meaning also suggests that biomedical informatics problems tend to be difficult when they deal with concepts that are hard to capture using formal, computational definitions. In other words, problems where meaning must be considered are more difficult than problems where manipulating data without regard for meaning is sufficient. Furthermore, the definition implies that informatics research, teaching, and service should focus on biomedical information as data plus meaning rather than only computer applications in biomedicine. PMID:19683067

Progress in Biomedical Knowledge Discovery: A 25-year Retrospective

PubMed Central

Sacchi, L.

2016-01-01

Summary Objectives We sought to explore, via a systematic review of the literature, the state of the art of knowledge discovery in biomedical databases as it existed in 1992, and then now, 25 years later, mainly focused on supervised learning. Methods We performed a rigorous systematic search of PubMed and latent Dirichlet allocation to identify themes in the literature and trends in the science of knowledge discovery in and between time periods and compare these trends. We restricted the result set using a bracket of five years previous, such that the 1992 result set was restricted to articles published between 1987 and 1992, and the 2015 set between 2011 and 2015. This was to reflect the current literature available at the time to researchers and others at the target dates of 1992 and 2015. The search term was framed as: Knowledge Discovery OR Data Mining OR Pattern Discovery OR Pattern Recognition, Automated. Results A total 538 and 18,172 documents were retrieved for 1992 and 2015, respectively. The number and type of data sources increased dramatically over the observation period, primarily due to the advent of electronic clinical systems. The period 1992-2015 saw the emergence of new areas of research in knowledge discovery, and the refinement and application of machine learning approaches that were nascent or unknown in 1992. Conclusions Over the 25 years of the observation period, we identified numerous developments that impacted the science of knowledge discovery, including the availability of new forms of data, new machine learning algorithms, and new application domains. Through a bibliometric analysis we examine the striking changes in the availability of highly heterogeneous data resources, the evolution of new algorithmic approaches to knowledge discovery, and we consider from legal, social, and political perspectives possible explanations of the growth of the field. Finally, we reflect on the achievements of the past 25 years to consider what the next 25 years will bring with regard to the availability of even more complex data and to the methods that could be, and are being now developed for the discovery of new knowledge in biomedical data. PMID:27488403

Progress in Biomedical Knowledge Discovery: A 25-year Retrospective.

PubMed

Sacchi, L; Holmes, J H

2016-08-02

We sought to explore, via a systematic review of the literature, the state of the art of knowledge discovery in biomedical databases as it existed in 1992, and then now, 25 years later, mainly focused on supervised learning. We performed a rigorous systematic search of PubMed and latent Dirichlet allocation to identify themes in the literature and trends in the science of knowledge discovery in and between time periods and compare these trends. We restricted the result set using a bracket of five years previous, such that the 1992 result set was restricted to articles published between 1987 and 1992, and the 2015 set between 2011 and 2015. This was to reflect the current literature available at the time to researchers and others at the target dates of 1992 and 2015. The search term was framed as: Knowledge Discovery OR Data Mining OR Pattern Discovery OR Pattern Recognition, Automated. A total 538 and 18,172 documents were retrieved for 1992 and 2015, respectively. The number and type of data sources increased dramatically over the observation period, primarily due to the advent of electronic clinical systems. The period 1992- 2015 saw the emergence of new areas of research in knowledge discovery, and the refinement and application of machine learning approaches that were nascent or unknown in 1992. Over the 25 years of the observation period, we identified numerous developments that impacted the science of knowledge discovery, including the availability of new forms of data, new machine learning algorithms, and new application domains. Through a bibliometric analysis we examine the striking changes in the availability of highly heterogeneous data resources, the evolution of new algorithmic approaches to knowledge discovery, and we consider from legal, social, and political perspectives possible explanations of the growth of the field. Finally, we reflect on the achievements of the past 25 years to consider what the next 25 years will bring with regard to the availability of even more complex data and to the methods that could be, and are being now developed for the discovery of new knowledge in biomedical data.

Pathophysiologic mechanisms of biomedical nanomaterials

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

Wang, Liming, E-mail: wangliming@ihep.ac.cn; Chen, Chunying, E-mail: chenchy@nanoctr.cn

Nanomaterials (NMs) have been widespread used in biomedical fields, daily consuming, and even food industry. It is crucial to understand the safety and biomedical efficacy of NMs. In this review, we summarized the recent progress about the physiological and pathological effects of NMs from several levels: protein-nano interface, NM-subcellular structures, and cell–cell interaction. We focused on the detailed information of nano-bio interaction, especially about protein adsorption, intracellular trafficking, biological barriers, and signaling pathways as well as the associated mechanism mediated by nanomaterials. We also introduced related analytical methods that are meaningful and helpful for biomedical effect studies in the future.more » We believe that knowledge about pathophysiologic effects of NMs is not only significant for rational design of medical NMs but also helps predict their safety and further improve their applications in the future. - Highlights: • Rapid protein adsorption onto nanomaterials that affects biomedical effects • Nanomaterials and their interaction with biological membrane, intracellular trafficking and specific cellular effects • Nanomaterials and their interaction with biological barriers • The signaling pathways mediated by nanomaterials and related biomedical effects • Novel techniques for studying translocation and biomedical effects of NMs.« less

Personalized biomedical devices & systems for healthcare applications

NASA Astrophysics Data System (ADS)

Chen, I.-Ming; Phee, Soo Jay; Luo, Zhiqiang; Lim, Chee Kian

2011-03-01

With the advancement in micro- and nanotechnology, electromechanical components and systems are getting smaller and smaller and gradually can be applied to the human as portable, mobile and even wearable devices. Healthcare industry have started to benefit from this technology trend by providing more and more miniature biomedical devices for personalized medical treatments in order to obtain better and more accurate outcome. This article introduces some recent development in non-intrusive and intrusive biomedical devices resulted from the advancement of niche miniature sensors and actuators, namely, wearable biomedical sensors, wearable haptic devices, and ingestible medical capsules. The development of these devices requires carful integration of knowledge and people from many different disciplines like medicine, electronics, mechanics, and design. Furthermore, designing affordable devices and systems to benefit all mankind is a great challenge ahead. The multi-disciplinary nature of the R&D effort in this area provides a new perspective for the future mechanical engineers.

Melanins and melanogenesis: from pigment cells to human health and technological applications.

PubMed

d'Ischia, Marco; Wakamatsu, Kazumasa; Cicoira, Fabio; Di Mauro, Eduardo; Garcia-Borron, Josè Carlos; Commo, Stephane; Galván, Ismael; Ghanem, Ghanem; Kenzo, Koike; Meredith, Paul; Pezzella, Alessandro; Santato, Clara; Sarna, Tadeusz; Simon, John D; Zecca, Luigi; Zucca, Fabio A; Napolitano, Alessandra; Ito, Shosuke

2015-09-01

During the past decade, melanins and melanogenesis have attracted growing interest for a broad range of biomedical and technological applications. The burst of polydopamine-based multifunctional coatings in materials science is just one example, and the list may be expanded to include melanin thin films for organic electronics and bioelectronics, drug delivery systems, functional nanoparticles and biointerfaces, sunscreens, environmental remediation devices. Despite considerable advances, applied research on melanins and melanogenesis is still far from being mature. A closer intersectoral interaction between research centers is essential to raise the interests and increase the awareness of the biomedical, biomaterials science and hi-tech sectors of the manifold opportunities offered by pigment cells and related metabolic pathways. Starting from a survey of biological roles and functions, the present review aims at providing an interdisciplinary perspective of melanin pigments and related pathway with a view to showing how it is possible to translate current knowledge about physical and chemical properties and control mechanisms into new bioinspired solutions for biomedical, dermocosmetic, and technological applications. © 2015 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

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

A bioinformatics knowledge discovery in text application for grid computing

PubMed Central

Castellano, Marcello; Mastronardi, Giuseppe; Bellotti, Roberto; Tarricone, Gianfranco

2009-01-01

Background A fundamental activity in biomedical research is Knowledge Discovery which has the ability to search through large amounts of biomedical information such as documents and data. High performance computational infrastructures, such as Grid technologies, are emerging as a possible infrastructure to tackle the intensive use of Information and Communication resources in life science. The goal of this work was to develop a software middleware solution in order to exploit the many knowledge discovery applications on scalable and distributed computing systems to achieve intensive use of ICT resources. Methods The development of a grid application for Knowledge Discovery in Text using a middleware solution based methodology is presented. The system must be able to: perform a user application model, process the jobs with the aim of creating many parallel jobs to distribute on the computational nodes. Finally, the system must be aware of the computational resources available, their status and must be able to monitor the execution of parallel jobs. These operative requirements lead to design a middleware to be specialized using user application modules. It included a graphical user interface in order to access to a node search system, a load balancing system and a transfer optimizer to reduce communication costs. Results A middleware solution prototype and the performance evaluation of it in terms of the speed-up factor is shown. It was written in JAVA on Globus Toolkit 4 to build the grid infrastructure based on GNU/Linux computer grid nodes. A test was carried out and the results are shown for the named entity recognition search of symptoms and pathologies. The search was applied to a collection of 5,000 scientific documents taken from PubMed. Conclusion In this paper we discuss the development of a grid application based on a middleware solution. It has been tested on a knowledge discovery in text process to extract new and useful information about symptoms and pathologies from a large collection of unstructured scientific documents. As an example a computation of Knowledge Discovery in Database was applied on the output produced by the KDT user module to extract new knowledge about symptom and pathology bio-entities. PMID:19534749

A bioinformatics knowledge discovery in text application for grid computing.

PubMed

Castellano, Marcello; Mastronardi, Giuseppe; Bellotti, Roberto; Tarricone, Gianfranco

2009-06-16

A fundamental activity in biomedical research is Knowledge Discovery which has the ability to search through large amounts of biomedical information such as documents and data. High performance computational infrastructures, such as Grid technologies, are emerging as a possible infrastructure to tackle the intensive use of Information and Communication resources in life science. The goal of this work was to develop a software middleware solution in order to exploit the many knowledge discovery applications on scalable and distributed computing systems to achieve intensive use of ICT resources. The development of a grid application for Knowledge Discovery in Text using a middleware solution based methodology is presented. The system must be able to: perform a user application model, process the jobs with the aim of creating many parallel jobs to distribute on the computational nodes. Finally, the system must be aware of the computational resources available, their status and must be able to monitor the execution of parallel jobs. These operative requirements lead to design a middleware to be specialized using user application modules. It included a graphical user interface in order to access to a node search system, a load balancing system and a transfer optimizer to reduce communication costs. A middleware solution prototype and the performance evaluation of it in terms of the speed-up factor is shown. It was written in JAVA on Globus Toolkit 4 to build the grid infrastructure based on GNU/Linux computer grid nodes. A test was carried out and the results are shown for the named entity recognition search of symptoms and pathologies. The search was applied to a collection of 5,000 scientific documents taken from PubMed. In this paper we discuss the development of a grid application based on a middleware solution. It has been tested on a knowledge discovery in text process to extract new and useful information about symptoms and pathologies from a large collection of unstructured scientific documents. As an example a computation of Knowledge Discovery in Database was applied on the output produced by the KDT user module to extract new knowledge about symptom and pathology bio-entities.

Accessing and Integrating Data and Knowledge for Biomedical Research

PubMed Central

Burgun, A.; Bodenreider, O.

2008-01-01

Summary Objectives To review the issues that have arisen with the advent of translational research in terms of integration of data and knowledge, and survey current efforts to address these issues. Methods Using examples form the biomedical literature, we identified new trends in biomedical research and their impact on bioinformatics. We analyzed the requirements for effective knowledge repositories and studied issues in the integration of biomedical knowledge. Results New diagnostic and therapeutic approaches based on gene expression patterns have brought about new issues in the statistical analysis of data, and new workflows are needed are needed to support translational research. Interoperable data repositories based on standard annotations, infrastructures and services are needed to support the pooling and meta-analysis of data, as well as their comparison to earlier experiments. High-quality, integrated ontologies and knowledge bases serve as a source of prior knowledge used in combination with traditional data mining techniques and contribute to the development of more effective data analysis strategies. Conclusion As biomedical research evolves from traditional clinical and biological investigations towards omics sciences and translational research, specific needs have emerged, including integrating data collected in research studies with patient clinical data, linking omics knowledge with medical knowledge, modeling the molecular basis of diseases, and developing tools that support in-depth analysis of research data. As such, translational research illustrates the need to bridge the gap between bioinformatics and medical informatics, and opens new avenues for biomedical informatics research. PMID:18660883

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.

A Day in the Professional Life of a Collaborative Biostatistician Deconstructed: Implications for Curriculum Design

ERIC Educational Resources Information Center

Samsa, Gregory P.

2018-01-01

Collaborative biostatistics is the creative application of statistical tools to biomedical problems. The relatively modest literature about the traits of effective collaborative biostatisticians focuses on four core competencies: (a) technical and analytical; (b) substance-matter knowledge; (c) communication; and (d) problem solving and problem…

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.

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.

Big Data Application in Biomedical Research and Health Care: A Literature Review.

PubMed

Luo, Jake; Wu, Min; Gopukumar, Deepika; Zhao, Yiqing

2016-01-01

Big data technologies are increasingly used for biomedical and health-care informatics research. Large amounts of biological and clinical data have been generated and collected at an unprecedented speed and scale. For example, the new generation of sequencing technologies enables the processing of billions of DNA sequence data per day, and the application of electronic health records (EHRs) is documenting large amounts of patient data. The cost of acquiring and analyzing biomedical data is expected to decrease dramatically with the help of technology upgrades, such as the emergence of new sequencing machines, the development of novel hardware and software for parallel computing, and the extensive expansion of EHRs. Big data applications present new opportunities to discover new knowledge and create novel methods to improve the quality of health care. The application of big data in health care is a fast-growing field, with many new discoveries and methodologies published in the last five years. In this paper, we review and discuss big data application in four major biomedical subdisciplines: (1) bioinformatics, (2) clinical informatics, (3) imaging informatics, and (4) public health informatics. Specifically, in bioinformatics, high-throughput experiments facilitate the research of new genome-wide association studies of diseases, and with clinical informatics, the clinical field benefits from the vast amount of collected patient data for making intelligent decisions. Imaging informatics is now more rapidly integrated with cloud platforms to share medical image data and workflows, and public health informatics leverages big data techniques for predicting and monitoring infectious disease outbreaks, such as Ebola. In this paper, we review the recent progress and breakthroughs of big data applications in these health-care domains and summarize the challenges, gaps, and opportunities to improve and advance big data applications in health care.

Big Data Application in Biomedical Research and Health Care: A Literature Review

PubMed Central

Luo, Jake; Wu, Min; Gopukumar, Deepika; Zhao, Yiqing

2016-01-01

Big data technologies are increasingly used for biomedical and health-care informatics research. Large amounts of biological and clinical data have been generated and collected at an unprecedented speed and scale. For example, the new generation of sequencing technologies enables the processing of billions of DNA sequence data per day, and the application of electronic health records (EHRs) is documenting large amounts of patient data. The cost of acquiring and analyzing biomedical data is expected to decrease dramatically with the help of technology upgrades, such as the emergence of new sequencing machines, the development of novel hardware and software for parallel computing, and the extensive expansion of EHRs. Big data applications present new opportunities to discover new knowledge and create novel methods to improve the quality of health care. The application of big data in health care is a fast-growing field, with many new discoveries and methodologies published in the last five years. In this paper, we review and discuss big data application in four major biomedical subdisciplines: (1) bioinformatics, (2) clinical informatics, (3) imaging informatics, and (4) public health informatics. Specifically, in bioinformatics, high-throughput experiments facilitate the research of new genome-wide association studies of diseases, and with clinical informatics, the clinical field benefits from the vast amount of collected patient data for making intelligent decisions. Imaging informatics is now more rapidly integrated with cloud platforms to share medical image data and workflows, and public health informatics leverages big data techniques for predicting and monitoring infectious disease outbreaks, such as Ebola. In this paper, we review the recent progress and breakthroughs of big data applications in these health-care domains and summarize the challenges, gaps, and opportunities to improve and advance big data applications in health care. PMID:26843812

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.

cluML: A markup language for clustering and cluster validity assessment of microarray data.

PubMed

Bolshakova, Nadia; Cunningham, Pádraig

2005-01-01

cluML is a new markup language for microarray data clustering and cluster validity assessment. The XML-based format has been designed to address some of the limitations observed in traditional formats, such as inability to store multiple clustering (including biclustering) and validation results within a dataset. cluML is an effective tool to support biomedical knowledge representation in gene expression data analysis. Although cluML was developed for DNA microarray analysis applications, it can be effectively used for the representation of clustering and for the validation of other biomedical and physical data that has no limitations.

Designing a mobile augmented reality tool for the locative visualisation of biomedical knowledge.

PubMed

Kilby, Jess; Gray, Kathleen; Elliott, Kristine; Waycott, Jenny; Sanchez, Fernando Martin; Dave, Bharat

2013-01-01

Mobile augmented reality (MAR) may offer new and engaging ways to support consumer participation in health. We report on design-based research into a MAR application for smartphones and tablets, intended to improve public engagement with biomedical research in a specific urban precinct. Following a review of technical capabilities and organizational and locative design considerations, we worked with staff of four research institutes to elicit their ideas about information and interaction functionalities of a shared MAR app. The results were promising, supporting the development of a prototype and initial field testing with these staff. Evidence from this project may point the way toward user-centred design of MAR services that will enable more widespread adoption of the technology in other healthcare and biomedical research contexts.

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.

A Diagram Editor for Efficient Biomedical Knowledge Capture and Integration

PubMed Central

Yu, Bohua; Jakupovic, Elvis; Wilson, Justin; Dai, Manhong; Xuan, Weijian; Mirel, Barbara; Athey, Brian; Watson, Stanley; Meng, Fan

2008-01-01

Understanding the molecular mechanisms underlying complex disorders requires the integration of data and knowledge from different sources including free text literature and various biomedical databases. To facilitate this process, we created the Biomedical Concept Diagram Editor (BCDE) to help researchers distill knowledge from data and literature and aid the process of hypothesis development. A key feature of BCDE is the ability to capture information with a simple drag-and-drop. This is a vast improvement over manual methods of knowledge and data recording and greatly increases the efficiency of the biomedical researcher. BCDE also provides a unique concept matching function to enforce consistent terminology, which enables conceptual relationships deposited by different researchers in the BCDE database to be mined and integrated for intelligible and useful results. We hope BCDE will promote the sharing and integration of knowledge from different researchers for effective hypothesis development. PMID:21347131

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.

Conceptual Knowledge Acquisition in Biomedicine: A Methodological Review

PubMed Central

Payne, Philip R.O.; Mendonça, Eneida A.; Johnson, Stephen B.; Starren, Justin B.

2007-01-01

The use of conceptual knowledge collections or structures within the biomedical domain is pervasive, spanning a variety of applications including controlled terminologies, semantic networks, ontologies, and database schemas. A number of theoretical constructs and practical methods or techniques support the development and evaluation of conceptual knowledge collections. This review will provide an overview of the current state of knowledge concerning conceptual knowledge acquisition, drawing from multiple contributing academic disciplines such as biomedicine, computer science, cognitive science, education, linguistics, semiotics, and psychology. In addition, multiple taxonomic approaches to the description and selection of conceptual knowledge acquisition and evaluation techniques will be proposed in order to partially address the apparent fragmentation of the current literature concerning this domain. PMID:17482521

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.

Text mining for traditional Chinese medical knowledge discovery: a survey.

PubMed

Zhou, Xuezhong; Peng, Yonghong; Liu, Baoyan

2010-08-01

Extracting meaningful information and knowledge from free text is the subject of considerable research interest in the machine learning and data mining fields. Text data mining (or text mining) has become one of the most active research sub-fields in data mining. Significant developments in the area of biomedical text mining during the past years have demonstrated its great promise for supporting scientists in developing novel hypotheses and new knowledge from the biomedical literature. Traditional Chinese medicine (TCM) provides a distinct methodology with which to view human life. It is one of the most complete and distinguished traditional medicines with a history of several thousand years of studying and practicing the diagnosis and treatment of human disease. It has been shown that the TCM knowledge obtained from clinical practice has become a significant complementary source of information for modern biomedical sciences. TCM literature obtained from the historical period and from modern clinical studies has recently been transformed into digital data in the form of relational databases or text documents, which provide an effective platform for information sharing and retrieval. This motivates and facilitates research and development into knowledge discovery approaches and to modernize TCM. In order to contribute to this still growing field, this paper presents (1) a comparative introduction to TCM and modern biomedicine, (2) a survey of the related information sources of TCM, (3) a review and discussion of the state of the art and the development of text mining techniques with applications to TCM, (4) a discussion of the research issues around TCM text mining and its future directions. Copyright 2010 Elsevier Inc. All rights reserved.

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.

Expanding the Basic Science Debate: The Role of Physics Knowledge in Interpreting Clinical Findings

ERIC Educational Resources Information Center

Goldszmidt, Mark; Minda, John Paul; Devantier, Sarah L.; Skye, Aimee L.; Woods, Nicole N.

2012-01-01

Current research suggests a role for biomedical knowledge in learning and retaining concepts related to medical diagnosis. However, learning may be influenced by other, non-biomedical knowledge. We explored this idea using an experimental design and examined the effects of causal knowledge on the learning, retention, and interpretation of medical…

[Biomedical publications in Spain on debate (II): the on-going 'revolutions' and their application to neurological journals].

PubMed

González de Dios, J; Sempere, A P; Aleixandre-Benavent, R

To debate about the application of on-going 'revolutions' in medical knowledge to Spanish neurological journals in the 21st century. This article reviews the current status of five revolutions in the field of health sciences, in general, and in neurological sciences, in particular: 1) the knowledge revolution: to translate the scientific investigation to the patient, with knowledge needs-driven research agenda with founder commissioning research to answer questions posed by clinicians, managers and patients, and systematic and critical appraisal reviews as the creator of quality improved knowledge; 2) the evidence based medicine revolution: the pyramid information of '4S', with systems (guidelines and computerized decision support systems), synopses (secondary journals), syntheses (systematic reviews and meta-analysis) and studies (original studies published in journals); 3) the web revolution: the possibility of dissemination of biomedical documentation by means of the Internet network are producing changes in the traditional way of conceiving scientific publication; the Internet represents a great advantage for investigation and also for clinical practice, since it permits free, universal access to databases and the interchange of texts, images and videos; 4) the open access revolution: to take full control over all operations related to the process of publish (to create, publish, communicate, distribute, reproduce and transform) with no need of any intermediaries, and to transform fundamental aspects concerning the circulation of knowledge, its use and availability; and 5) the librarian revolution: the project of a Virtual Health Library in Spain as a tool to access and disseminate scientific and technical knowledge on health through the Internet.

Incorporating domain knowledge in chemical and biomedical named entity recognition with word representations.

PubMed

Munkhdalai, Tsendsuren; Li, Meijing; Batsuren, Khuyagbaatar; Park, Hyeon Ah; Choi, Nak Hyeon; Ryu, Keun Ho

2015-01-01

Chemical and biomedical Named Entity Recognition (NER) is an essential prerequisite task before effective text mining can begin for biochemical-text data. Exploiting unlabeled text data to leverage system performance has been an active and challenging research topic in text mining due to the recent growth in the amount of biomedical literature. We present a semi-supervised learning method that efficiently exploits unlabeled data in order to incorporate domain knowledge into a named entity recognition model and to leverage system performance. The proposed method includes Natural Language Processing (NLP) tasks for text preprocessing, learning word representation features from a large amount of text data for feature extraction, and conditional random fields for token classification. Other than the free text in the domain, the proposed method does not rely on any lexicon nor any dictionary in order to keep the system applicable to other NER tasks in bio-text data. We extended BANNER, a biomedical NER system, with the proposed method. This yields an integrated system that can be applied to chemical and drug NER or biomedical NER. We call our branch of the BANNER system BANNER-CHEMDNER, which is scalable over millions of documents, processing about 530 documents per minute, is configurable via XML, and can be plugged into other systems by using the BANNER Unstructured Information Management Architecture (UIMA) interface. BANNER-CHEMDNER achieved an 85.68% and an 86.47% F-measure on the testing sets of CHEMDNER Chemical Entity Mention (CEM) and Chemical Document Indexing (CDI) subtasks, respectively, and achieved an 87.04% F-measure on the official testing set of the BioCreative II gene mention task, showing remarkable performance in both chemical and biomedical NER. BANNER-CHEMDNER system is available at: https://bitbucket.org/tsendeemts/banner-chemdner.

The Development of Clinical Reasoning Skills: A Major Objective of the Anatomy Course

ERIC Educational Resources Information Center

Elizondo-Omana, Rodrigo E.; Lopez, Santos Guzman

2008-01-01

Traditional medical school curricula have made a clear demarcation between the basic biomedical sciences and the clinical years. It is our view that a comprehensive medical education necessarily involves an increased correlation between basic science knowledge and its clinical applications. A basic anatomy course should have two main objectives:…

Effective Design of Educational Virtual Reality Applications for Medicine Using Knowledge-Engineering Techniques

ERIC Educational Resources Information Center

Górski, Filip; Bun, Pawel; Wichniarek, Radoslaw; Zawadzki, Przemyslaw; Hamrol, Adam

2017-01-01

Effective medical and biomedical engineering education is an important problem. Traditional methods are difficult and costly. That is why Virtual Reality is often used for that purpose. Educational medical VR is a well-developed IT field, with many available hardware and software solutions. Current solutions are prepared without methodological…

Defining the Field of Behavioral Medicine: A Collaborative Endeavor.

PubMed

Dekker, Joost; Stauder, Adrienne; Penedo, Frank J

2017-02-01

To respond to comments on our proposal for an update of the definition and scope of behavioral medicine. We identify common themes in the comments and provide a response. We discuss the relationship of behavioral medicine to other disciplines and fields, the scope of behavioral medicine, and issues related to the application of behavioral medicine. Based on the comments of our esteemed colleagues and our reflection on those comments, we now offer the following refined definition and scope of behavioral medicine. 'Behavioral medicine can be defined as the field characterized by the collaboration among multiple disciplines concerned with the development and integration of biomedical and behavioral knowledge relevant to health and disease, and the application of this knowledge to prevention, health promotion, diagnosis, treatment, rehabilitation, and care. The scope of behavioral medicine extends from bio-behavioral mechanisms (i.e. the interaction among biomedical, psychological, social, societal, cultural and environmental processes related to health and disease), to clinical diagnosis and intervention, and to public health'. We propose to use this refined definition and scope as the starting point for seeking further input from the ISBM member societies.

Awareness about biomedical waste management and knowledge of effective recycling of dental materials among dental students.

PubMed

Ranjan, Rajeev; Pathak, Ruchi; Singh, Dhirendra K; Jalaluddin, Md; Kore, Shobha A; Kore, Abhijeet R

2016-01-01

Biomedical waste management has become a concern with increasing number of dental practitioners in India. Being health care professionals, dentists should be aware regarding safe disposal of biomedical waste and recycling of dental materials to minimize biohazards to the environment. The aim of the present study was to assess awareness regarding biomedical waste management as well as knowledge of effective recycling and reuse of dental materials among dental students. This cross-sectional study was conducted among dental students belonging from all dental colleges of Bhubaneswar, Odisha (India) from February 2016 to April 2016. A total of 500 students (208 males and 292 females) participated in the study, which was conducted in two phases. A questionnaire was distributed to assess the awareness of biomedical waste management and knowledge of effective recycling of dental materials, and collected data was examined on a 5-point unipolar scale in percentages to assess the relative awareness regarding these two different categorizes. The Statistical Package for Social Sciences was used to analyzed collected data. Forty-four percent of the dental students were not at all aware about the management of biomedical waste, 22% were moderately aware, 21% slightly aware, 7% very aware, and 5% fell in extremely aware category. Similarly, a higher percentage of participants (61%) were completely unaware regarding recycling and reusing of biomedical waste. There is lack of sufficient knowledge among dental students regarding management of biomedical waste and recycling or reusing of dental materials. Considering its impact on the environment, biomedical waste management requires immediate academic assessment to increase the awareness during training courses.

Semantic biomedical resource discovery: a Natural Language Processing framework.

PubMed

Sfakianaki, Pepi; Koumakis, Lefteris; Sfakianakis, Stelios; Iatraki, Galatia; Zacharioudakis, Giorgos; Graf, Norbert; Marias, Kostas; Tsiknakis, Manolis

2015-09-30

A plethora of publicly available biomedical resources do currently exist and are constantly increasing at a fast rate. In parallel, specialized repositories are been developed, indexing numerous clinical and biomedical tools. The main drawback of such repositories is the difficulty in locating appropriate resources for a clinical or biomedical decision task, especially for non-Information Technology expert users. In parallel, although NLP research in the clinical domain has been active since the 1960s, progress in the development of NLP applications has been slow and lags behind progress in the general NLP domain. The aim of the present study is to investigate the use of semantics for biomedical resources annotation with domain specific ontologies and exploit Natural Language Processing methods in empowering the non-Information Technology expert users to efficiently search for biomedical resources using natural language. A Natural Language Processing engine which can "translate" free text into targeted queries, automatically transforming a clinical research question into a request description that contains only terms of ontologies, has been implemented. The implementation is based on information extraction techniques for text in natural language, guided by integrated ontologies. Furthermore, knowledge from robust text mining methods has been incorporated to map descriptions into suitable domain ontologies in order to ensure that the biomedical resources descriptions are domain oriented and enhance the accuracy of services discovery. The framework is freely available as a web application at ( http://calchas.ics.forth.gr/ ). For our experiments, a range of clinical questions were established based on descriptions of clinical trials from the ClinicalTrials.gov registry as well as recommendations from clinicians. Domain experts manually identified the available tools in a tools repository which are suitable for addressing the clinical questions at hand, either individually or as a set of tools forming a computational pipeline. The results were compared with those obtained from an automated discovery of candidate biomedical tools. For the evaluation of the results, precision and recall measurements were used. Our results indicate that the proposed framework has a high precision and low recall, implying that the system returns essentially more relevant results than irrelevant. There are adequate biomedical ontologies already available, sufficiency of existing NLP tools and quality of biomedical annotation systems for the implementation of a biomedical resources discovery framework, based on the semantic annotation of resources and the use on NLP techniques. The results of the present study demonstrate the clinical utility of the application of the proposed framework which aims to bridge the gap between clinical question in natural language and efficient dynamic biomedical resources discovery.

Disparities in HIV knowledge and attitudes toward biomedical interventions among the non-medical HIV workforce in the United States.

PubMed

Copeland, Raniyah M; Wilson, Phill; Betancourt, Gabriela; Garcia, David; Penner, Murray; Abravanel, Rebecca; Wong, Eric Y; Parisi, Lori D

2017-12-01

Non-medical, community-based workers play a critical role in supporting people living with (or at risk of acquiring) HIV along the care continuum. The biomedical nature of promising advances in HIV prevention, such as pre-exposure prophylaxis and treatment-as-prevention, requires frontline workers to be knowledgeable about HIV science and treatment. This study was developed to: measure knowledge of HIV science and treatment within the HIV non-medical workforce, evaluate workers' familiarity with and attitudes toward recent biomedical interventions, and identify factors that may affect HIV knowledge and attitudes. A 62-question, web-based survey was completed in English or Spanish between 2012 and 2014 by 3663 US-based employees, contractors, and volunteers working in AIDS service organizations, state/local health departments, and other community-based organizations in a non-medical capacity. Survey items captured the following: respondent demographics, HIV science and treatment knowledge, and familiarity with and attitudes toward biomedical interventions. An average of 61% of HIV knowledge questions were answered correctly. Higher knowledge scores were associated with higher education levels, work at organizations that serve people living with HIV/AIDS or who are at a high risk of acquiring HIV, and longer tenure in the field. Lower knowledge scores were associated with non-Hispanic Black or Black race/ethnicity and taking the survey in Spanish. Similarly, subgroup analyses showed that respondents who were non-Hispanic Black or Hispanic (versus non-Hispanic white), as well as those located in the South (versus other regions) scored significantly lower. These subpopulations were also less familiar with and had less positive attitudes toward newer biomedical prevention interventions. Respondents who took the survey in Spanish (versus English) had lower knowledge scores and higher familiarity with, but generally less positive attitudes toward, biomedical interventions. In summary, low knowledge scores suggest the need for additional capacity-building efforts and training for non-medical HIV workers, particularly those who provide services in the communities most affected by HIV.

Literature Mining for the Discovery of Hidden Connections between Drugs, Genes and Diseases

PubMed Central

Frijters, Raoul; van Vugt, Marianne; Smeets, Ruben; van Schaik, René; de Vlieg, Jacob; Alkema, Wynand

2010-01-01

The scientific literature represents a rich source for retrieval of knowledge on associations between biomedical concepts such as genes, diseases and cellular processes. A commonly used method to establish relationships between biomedical concepts from literature is co-occurrence. Apart from its use in knowledge retrieval, the co-occurrence method is also well-suited to discover new, hidden relationships between biomedical concepts following a simple ABC-principle, in which A and C have no direct relationship, but are connected via shared B-intermediates. In this paper we describe CoPub Discovery, a tool that mines the literature for new relationships between biomedical concepts. Statistical analysis using ROC curves showed that CoPub Discovery performed well over a wide range of settings and keyword thesauri. We subsequently used CoPub Discovery to search for new relationships between genes, drugs, pathways and diseases. Several of the newly found relationships were validated using independent literature sources. In addition, new predicted relationships between compounds and cell proliferation were validated and confirmed experimentally in an in vitro cell proliferation assay. The results show that CoPub Discovery is able to identify novel associations between genes, drugs, pathways and diseases that have a high probability of being biologically valid. This makes CoPub Discovery a useful tool to unravel the mechanisms behind disease, to find novel drug targets, or to find novel applications for existing drugs. PMID:20885778

Awareness of biomedical waste management among health care personnel in jaipur, India.

PubMed

Sharma, Alok; Sharma, Varsha; Sharma, Swati; Singh, Prabhat

2013-03-01

The study aimed to determine the following among the workforce of the Jaipur Dental College, India: their awareness regarding biomedical (BM) waste management policy and practices, their attitude towards biomedical waste management, and their awareness regarding needle-stick injury and its prevalence among different categories of health care providers. A cross-sectional study was conducted using a questionnaire with closed-ended questions. It was distributed to 144 dentists, nurses, laboratory technicians and Class IV employees (cleaners and maintenance personnel) at Jaipur Dental College. The questionnaire was used to assess their knowledge of biomedical medical waste disposal. The resulting answers were graded and the percentage of correct and incorrect answers for each question from all the participants was obtained. Of the 144 questionnaires, 140 were returned and the answers graded. The results showed that there was a poor level of knowledge and awareness of biomedical waste generation hazards, legislation and management among health care personnel. It was surprising that 36% of the nurses had an extremely poor knowledge of biomedical waste generation and legislation and just 15% of the Class IV employees had an excellent awareness of biomedical waste management practice. It can be concluded from the present study that there are poor levels of knowledge and awareness about BM waste generation hazards, legislation and management among health care personnel in Jaipur Dental College. Regular monitoring and training are required at all levels.

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.

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

Preparing for motherhood: authoritative knowledge and the undercurrents of shared experience in two childbirth education courses in Cagliari, Italy.

PubMed

Ketler, S K

2000-06-01

This article compares the social settings and teaching organization of two differently structured childbirth education courses in Cagliari, Italy, in order to understand how social processes and contexts work to negotiate authoritative knowledge. Although the explicit goal of both courses was to transmit biomedical knowledge, knowledge based in women's experience nonetheless dominated some course sessions. Thus, I examine the social processes and interactions that enabled women's experiential knowledge to dominate discussions and subsequently share in the authority of biomedical knowledge in some situations. Because few existing studies do so, this article also addresses a gap in our current understanding by exploring not only how experiential knowledge comes to share authority with biomedical knowledge, but also, why it is important that it does. Focusing on the efficacy of differently structured courses, this article informs the planning of future childbirth education courses in similar settings.

Awareness and Knowledge of the U.S. Public Health Service Syphilis Study at Tuskegee: Implications for Biomedical Research

PubMed Central

McCallum, Jan M.; Arekere, Dhananjaya M.; Green, B. Lee; Katz, Ralph V.; Rivers, Brian M.

2007-01-01

The purpose of this review was to collect and interpret the findings of all published qualitative or quantitative research that assessed African Americans’ 1) general awareness and/or specific knowledge of the U.S. Public Health Service (USPHS) Syphilis Study at Tuskegee, and 2) attitudes towards and/or willingness to participate in biomedical research. An exhaustive review of the literature produced eight articles that fit the aforementioned selection criteria. All articles that assessed both awareness and knowledge found that familiarity with the USPHS Syphilis Study at Tuskegee did not necessarily ensure accurate knowledge of it Four studies also found that awareness of the USPHS Syphilis Study at Tuskegee did not relate to willingness to participate in biomedical research. In addition to awareness and knowledge of the USPHS Syphilis Study at Tuskegee, published studies suggest that a broad, array of structural and sociocultural factors influence minorities’ willingness to participate in biomedical studies. PMID:17242526

Awareness and knowledge of the U.S. Public Health Service syphilis study at Tuskegee: implications for biomedical research.

PubMed

McCallum, Jan M; Arekere, Dhananjaya M; Green, B Lee; Katz, Ralph V; Rivers, Brian M

2006-11-01

The purpose of this review was to collect and interpret the findings of all published qualitative or quantitative research that assessed African Americans' 1) general awareness and/or specific knowledge of the U.S. Public Health Service (USPHS) Syphilis Study at Tuskegee, and 2) attitudes towards and/or willingness to participate in biomedical research. An exhaustive review of the literature produced eight articles that fit the aforementioned selection criteria. All articles that assessed both awareness and knowledge found that familiarity with the USPHS Syphilis Study at Tuskegee did not necessarily ensure accurate knowledge of it. Four studies also found that awareness of the USPHS Syphilis Study at Tuskegee did not relate to willingness to participate in biomedical research. In addition to awareness and knowledge of the USPHS Syphilis Study at Tuskegee, published studies suggest that a broad array of structural and sociocultural factors influence minorities' willingness to participate in biomedical studies.

Interoperability between biomedical ontologies through relation expansion, upper-level ontologies and automatic reasoning.

PubMed

Hoehndorf, Robert; Dumontier, Michel; Oellrich, Anika; Rebholz-Schuhmann, Dietrich; Schofield, Paul N; Gkoutos, Georgios V

2011-01-01

Researchers design ontologies as a means to accurately annotate and integrate experimental data across heterogeneous and disparate data- and knowledge bases. Formal ontologies make the semantics of terms and relations explicit such that automated reasoning can be used to verify the consistency of knowledge. However, many biomedical ontologies do not sufficiently formalize the semantics of their relations and are therefore limited with respect to automated reasoning for large scale data integration and knowledge discovery. We describe a method to improve automated reasoning over biomedical ontologies and identify several thousand contradictory class definitions. Our approach aligns terms in biomedical ontologies with foundational classes in a top-level ontology and formalizes composite relations as class expressions. We describe the semi-automated repair of contradictions and demonstrate expressive queries over interoperable ontologies. Our work forms an important cornerstone for data integration, automatic inference and knowledge discovery based on formal representations of knowledge. Our results and analysis software are available at http://bioonto.de/pmwiki.php/Main/ReasonableOntologies.

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

Micro-/nano-engineered cellular responses for soft tissue engineering and biomedical applications.

PubMed

Tay, Chor Yong; Irvine, Scott Alexander; Boey, Freddy Y C; Tan, Lay Poh; Venkatraman, Subbu

2011-05-23

The development of biomedical devices and reconstruction of functional ex vivo tissues often requires the need to fabricate biomimetic surfaces with features of sub-micrometer precision. This can be achieved with the advancements in micro-/nano-engineering techniques, allowing researchers to manipulate a plethora of cellular behaviors at the cell-biomaterial interface. Systematic studies conducted on these 2D engineered surfaces have unraveled numerous novel findings that can potentially be integrated as part of the design consideration for future 2D and 3D biomaterials and will no doubt greatly benefit tissue engineering. In this review, recent developments detailing the use of micro-/nano-engineering techniques to direct cellular orientation and function pertinent to soft tissue engineering will be highlighted. Particularly, this article aims to provide valuable insights into distinctive cell interactions and reactions to controlled surfaces, which can be exploited to understand the mechanisms of cell growth on micro-/nano-engineered interfaces, and to harness this knowledge to optimize the performance of 3D artificial soft tissue grafts and biomedical applications. Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Awareness about biomedical waste management and knowledge of effective recycling of dental materials among dental students

PubMed Central

Ranjan, Rajeev; Pathak, Ruchi; Singh, Dhirendra K.; Jalaluddin, Md.; Kore, Shobha A.; Kore, Abhijeet R.

2016-01-01

Aims and Objectives: Biomedical waste management has become a concern with increasing number of dental practitioners in India. Being health care professionals, dentists should be aware regarding safe disposal of biomedical waste and recycling of dental materials to minimize biohazards to the environment. The aim of the present study was to assess awareness regarding biomedical waste management as well as knowledge of effective recycling and reuse of dental materials among dental students. Materials and Methods: This cross-sectional study was conducted among dental students belonging from all dental colleges of Bhubaneswar, Odisha (India) from February 2016 to April 2016. A total of 500 students (208 males and 292 females) participated in the study, which was conducted in two phases. A questionnaire was distributed to assess the awareness of biomedical waste management and knowledge of effective recycling of dental materials, and collected data was examined on a 5-point unipolar scale in percentages to assess the relative awareness regarding these two different categorizes. The Statistical Package for Social Sciences was used to analyzed collected data. Results: Forty-four percent of the dental students were not at all aware about the management of biomedical waste, 22% were moderately aware, 21% slightly aware, 7% very aware, and 5% fell in extremely aware category. Similarly, a higher percentage of participants (61%) were completely unaware regarding recycling and reusing of biomedical waste. Conclusion: There is lack of sufficient knowledge among dental students regarding management of biomedical waste and recycling or reusing of dental materials. Considering its impact on the environment, biomedical waste management requires immediate academic assessment to increase the awareness during training courses. PMID:27891315

TU-F-BRD-01: Biomedical Informatics for Medical Physicists

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

Phillips, M; Kalet, I; McNutt, T

Biomedical informatics encompasses a very large domain of knowledge and applications. This broad and loosely defined field can make it difficult to navigate. Physicists often are called upon to provide informatics services and/or to take part in projects involving principles of the field. The purpose of the presentations in this symposium is to help medical physicists gain some knowledge about the breadth of the field and how, in the current clinical and research environment, they can participate and contribute. Three talks have been designed to give an overview from the perspective of physicists and to provide a more in-depth discussionmore » in two areas. One of the primary purposes, and the main subject of the first talk, is to help physicists achieve a perspective about the range of the topics and concepts that fall under the heading of 'informatics'. The approach is to de-mystify topics and jargon and to help physicists find resources in the field should they need them. The other talks explore two areas of biomedical informatics in more depth. The goal is to highlight two domains of intense current interest--databases and models--in enough depth into current approaches so that an adequate background for independent inquiry is achieved. These two areas will serve as good examples of how physicists, using informatics principles, can contribute to oncology practice and research. Learning Objectives: To understand how the principles of biomedical informatics are used by medical physicists. To put the relevant informatics concepts in perspective with regard to biomedicine in general. To use clinical database design as an example of biomedical informatics. To provide a solid background into the problems and issues of the design and use of data and databases in radiation oncology. To use modeling in the service of decision support systems as an example of modeling methods and data use. To provide a background into how uncertainty in our data and knowledge can be incorporated into modeling methods.« less

Queer challenges to evidence-based practice.

PubMed

Zeeman, Laetitia; Aranda, Kay; Grant, Alec

2014-06-01

This paper aims to queer evidence-based practice by troubling the concepts of evidence, knowledge and mental illness. The evidence-based narrative that emerged within biomedicine has dominated health care. The biomedical notion of 'evidence' has been critiqued extensively and is seen as exclusive and limiting, and even though the social constructionist paradigm attempts to challenge the authority of biomedicine to legitimate what constitutes acceptable evidence or knowledge for those experiencing mental illness, biomedical notions of evidence appear to remain relatively intact. Queer theory offers theoretical tools to disrupt biomedical norms and challenges biomedical normativity to indicate how marginalisation occurs when normative truths about mental health classify those who differ from the norm as 'ill' or 'disordered'. Queer theory's emphasis on normativity serves the political aim to subvert marginalisation and bring about radical social and material change. Reference will be made to mental health subjects within each discourse by indicating how the body acts as a vehicle for knowing. Deleuzian notions of the rhizome are used as metaphor to suggest a relational approach to knowledge that does away with either/or positions in either biomedical, or queer knowledge to arrive at a both/and position where the biomedical, constructionist and queer are interrelated and entangled in needing the other for their own evolution. However, queer does not ask for assimilation but celebrates difference by remaining outside to disrupt that which is easily overlooked, assumed to be natural or represented as the norm. The task of queer knowledge is to do justice to the lives lived in the name of evidence-based practice and demands that we consider the relations of power where knowledge is produced. This pursuit creates different knowledge spaces where we identify new intersections that allow for socially just understandings of knowing or evidence to emerge. © 2013 John Wiley & Sons Ltd.

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

PubMed

Honavar, Vasant

2015-01-01

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

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 literature classification using encyclopedic knowledge: a Wikipedia-based bag-of-concepts approach

PubMed Central

Pérez Rodríguez, Roberto; Anido Rifón, Luis E.

2015-01-01

Automatic classification of text documents into a set of categories has a lot of applications. Among those applications, the automatic classification of biomedical literature stands out as an important application for automatic document classification strategies. Biomedical staff and researchers have to deal with a lot of literature in their daily activities, so it would be useful a system that allows for accessing to documents of interest in a simple and effective way; thus, it is necessary that these documents are sorted based on some criteria—that is to say, they have to be classified. Documents to classify are usually represented following the bag-of-words (BoW) paradigm. Features are words in the text—thus suffering from synonymy and polysemy—and their weights are just based on their frequency of occurrence. This paper presents an empirical study of the efficiency of a classifier that leverages encyclopedic background knowledge—concretely Wikipedia—in order to create bag-of-concepts (BoC) representations of documents, understanding concept as “unit of meaning”, and thus tackling synonymy and polysemy. Besides, the weighting of concepts is based on their semantic relevance in the text. For the evaluation of the proposal, empirical experiments have been conducted with one of the commonly used corpora for evaluating classification and retrieval of biomedical information, OHSUMED, and also with a purpose-built corpus of MEDLINE biomedical abstracts, UVigoMED. Results obtained show that the Wikipedia-based bag-of-concepts representation outperforms the classical bag-of-words representation up to 157% in the single-label classification problem and up to 100% in the multi-label problem for OHSUMED corpus, and up to 122% in the single-label classification problem and up to 155% in the multi-label problem for UVigoMED corpus. PMID:26468436

Design and preliminary validation of a mobile application-based expert system to facilitate repair of medical equipment in resource-limited health settings.

PubMed

Wong, Alison L; Lacob, Kelly M; Wilson, Madeline G; Zwolski, Stacie M; Acharya, Soumyadipta

2018-01-01

One of the greatest barriers to safe surgery is the availability of functional biomedical equipment. Biomedical technicians play a major role in ensuring that equipment is functional. Following in-field observations and an online survey, a mobile application was developed to aid technicians in troubleshooting biomedical equipment. It was hypothesized that this application could be used to aid technicians in equipment repair, as modeled by repair of a pulse oximeter. To identify specific barriers to equipment repair and maintenance for biomedical technicians, an online survey was conducted to determine current practices and challenges. These findings were used to guide the development of a mobile application system that guides technicians through maintenance and repair tasks. A convenience sample of technicians in Ethiopia tested the application using a broken pulse oximeter task and following this completed usability and content validity surveys. Fifty-three technicians from 13 countries responded to the initial survey. The results of the survey showed that technicians find equipment manuals most useful, but these are not easily accessible. Many do not know how to or are uncomfortable reaching out to human resources. Thirty-three technicians completed the broken pulse oximeter task using the application. All were able to appropriately identify and repair the equipment, and post-task surveys of usability and content validity demonstrated highly positive scores (Agree to Strongly Agree) on both scales. This research demonstrates the need for improved access to resources for technicians and shows that a mobile application can be used to address a gap in the access to knowledge and resources in low- and middle-income countries. Further research will include prospective studies to determine the impact of an application on the availability of functional equipment in a hospital and the effect on the provision and safety of surgical care.

Dynamic knowledge representation using agent-based modeling: ontology instantiation and verification of conceptual models.

PubMed

An, Gary

2009-01-01

The sheer volume of biomedical research threatens to overwhelm the capacity of individuals to effectively process this information. Adding to this challenge is the multiscale nature of both biological systems and the research community as a whole. Given this volume and rate of generation of biomedical information, the research community must develop methods for robust representation of knowledge in order for individuals, and the community as a whole, to "know what they know." Despite increasing emphasis on "data-driven" research, the fact remains that researchers guide their research using intuitively constructed conceptual models derived from knowledge extracted from publications, knowledge that is generally qualitatively expressed using natural language. Agent-based modeling (ABM) is a computational modeling method that is suited to translating the knowledge expressed in biomedical texts into dynamic representations of the conceptual models generated by researchers. The hierarchical object-class orientation of ABM maps well to biomedical ontological structures, facilitating the translation of ontologies into instantiated models. Furthermore, ABM is suited to producing the nonintuitive behaviors that often "break" conceptual models. Verification in this context is focused at determining the plausibility of a particular conceptual model, and qualitative knowledge representation is often sufficient for this goal. Thus, utilized in this fashion, ABM can provide a powerful adjunct to other computational methods within the research process, as well as providing a metamodeling framework to enhance the evolution of biomedical ontologies.

Foundational biomedical informatics research in the clinical and translational science era: a call to action.

PubMed

Payne, Philip R O; Embi, Peter J; Niland, Joyce

2010-01-01

Advances in clinical and translational science, along with related national-scale policy and funding mechanisms, have provided significant opportunities for the advancement of applied clinical research informatics (CRI) and translational bioinformatics (TBI). Such efforts are primarily oriented to application and infrastructure development and are critical to the conduct of clinical and translational research. However, they often come at the expense of the foundational CRI and TBI research needed to grow these important biomedical informatics subdisciplines and ensure future innovations. In light of this challenge, it is critical that a number of steps be taken, including the conduct of targeted advocacy campaigns, the development of community-accepted research agendas, and the continued creation of forums for collaboration and knowledge exchange. Such efforts are needed to ensure that the biomedical informatics community is able to advance CRI and TBI science in the context of the modern clinical and translational science era.

AMIA Board white paper: definition of biomedical informatics and specification of core competencies for graduate education in the discipline

PubMed Central

Kulikowski, Casimir A; Shortliffe, Edward H; Currie, Leanne M; Elkin, Peter L; Hunter, Lawrence E; Johnson, Todd R; Kalet, Ira J; Lenert, Leslie A; Musen, Mark A; Ozbolt, Judy G; Smith, Jack W; Tarczy-Hornoch, Peter Z

2012-01-01

The AMIA biomedical informatics (BMI) core competencies have been designed to support and guide graduate education in BMI, the core scientific discipline underlying the breadth of the field's research, practice, and education. The core definition of BMI adopted by AMIA specifies that BMI is ‘the interdisciplinary field that studies and pursues the effective uses of biomedical data, information, and knowledge for scientific inquiry, problem solving and decision making, motivated by efforts to improve human health.’ Application areas range from bioinformatics to clinical and public health informatics and span the spectrum from the molecular to population levels of health and biomedicine. The shared core informatics competencies of BMI draw on the practical experience of many specific informatics sub-disciplines. The AMIA BMI analysis highlights the central shared set of competencies that should guide curriculum design and that graduate students should be expected to master. PMID:22683918

The effects of utility evaluations, biomedical knowledge and modernization on intention to exclusively use biomedical health facilities among rural households in Mozambique.

PubMed

Mukolo, Abraham; Cooil, Bruce; Victor, Bart

2015-08-01

In resource-limited settings, the choice between utilizing biomedical health services and/or traditional healers is critical to the success of the public health mission. In the literature, this choice has been predicted to be influenced by three major factors: knowledge about biomedical etiologies; cultural modernization; and rational choice. The current study investigated all three of these predicted determinants, applying data from a general household survey conducted in 2010 in Zambézia Province of Mozambique involving 1045 randomly sampled rural households. Overall, more respondents (N = 802) intended to continue to supplement their biomedical healthcare with traditional healer services in comparison with those intending to utilize biomedical care exclusively (N = 243). The findings strongly supported the predicted association between rational utility (measured as satisfaction with the quality of service and results from past care) with the future intention to continue to supplement or utilize biomedical care exclusively. Odds of moving away from supplementation increase by a factor of 2.5 if the respondent reported seeing their condition improve under government/private biomedical care. Odds of staying with supplementation increase by a factor 3.1 if the respondent was satisfied with traditional care and a factor of 16 if the condition had improved under traditional care. Modernization variables (education, income, religion, and Portuguese language skills) were relevant and provided a significant component of the best scientific model. Amount of biomedical knowledge was not a significant predictor of choice. There was a small effect on choice from knowing the limitations of biomedical care. The findings have implications for public healthcare promotion activities in areas where biomedical care is introduced as an alternative to traditional healing. Copyright © 2015 Elsevier Ltd. All rights reserved.

Architecture and Initial Development of a Knowledge-as-a-Service Activator for Computable Knowledge Objects for Health.

PubMed

Flynn, Allen J; Boisvert, Peter; Gittlen, Nate; Gross, Colin; Iott, Brad; Lagoze, Carl; Meng, George; Friedman, Charles P

2018-01-01

The Knowledge Grid (KGrid) is a research and development program toward infrastructure capable of greatly decreasing latency between the publication of new biomedical knowledge and its widespread uptake into practice. KGrid comprises digital knowledge objects, an online Library to store them, and an Activator that uses them to provide Knowledge-as-a-Service (KaaS). KGrid's Activator enables computable biomedical knowledge, held in knowledge objects, to be rapidly deployed at Internet-scale in cloud computing environments for improved health. Here we present the Activator, its system architecture and primary functions.

Biological interactions of carbon-based nanomaterials: From coronation to degradation.

PubMed

Bhattacharya, Kunal; Mukherjee, Sourav P; Gallud, Audrey; Burkert, Seth C; Bistarelli, Silvia; Bellucci, Stefano; Bottini, Massimo; Star, Alexander; Fadeel, Bengt

2016-02-01

Carbon-based nanomaterials including carbon nanotubes, graphene oxide, fullerenes and nanodiamonds are potential candidates for various applications in medicine such as drug delivery and imaging. However, the successful translation of nanomaterials for biomedical applications is predicated on a detailed understanding of the biological interactions of these materials. Indeed, the potential impact of the so-called bio-corona of proteins, lipids, and other biomolecules on the fate of nanomaterials in the body should not be ignored. Enzymatic degradation of carbon-based nanomaterials by immune-competent cells serves as a special case of bio-corona interactions with important implications for the medical use of such nanomaterials. In the present review, we highlight emerging biomedical applications of carbon-based nanomaterials. We also discuss recent studies on nanomaterial 'coronation' and how this impacts on biodistribution and targeting along with studies on the enzymatic degradation of carbon-based nanomaterials, and the role of surface modification of nanomaterials for these biological interactions. Advances in technology have produced many carbon-based nanomaterials. These are increasingly being investigated for the use in diagnostics and therapeutics. Nonetheless, there remains a knowledge gap in terms of the understanding of the biological interactions of these materials. In this paper, the authors provided a comprehensive review on the recent biomedical applications and the interactions of various carbon-based nanomaterials. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

Design, implementation and validation of a novel open framework for agile development of mobile health applications.

PubMed

Banos, Oresti; Villalonga, Claudia; Garcia, Rafael; Saez, Alejandro; Damas, Miguel; Holgado-Terriza, Juan A; Lee, Sungyong; Pomares, Hector; Rojas, Ignacio

2015-01-01

The delivery of healthcare services has experienced tremendous changes during the last years. Mobile health or mHealth is a key engine of advance in the forefront of this revolution. Although there exists a growing development of mobile health applications, there is a lack of tools specifically devised for their implementation. This work presents mHealthDroid, an open source Android implementation of a mHealth Framework designed to facilitate the rapid and easy development of mHealth and biomedical apps. The framework is particularly planned to leverage the potential of mobile devices such as smartphones or tablets, wearable sensors and portable biomedical systems. These devices are increasingly used for the monitoring and delivery of personal health care and wellbeing. The framework implements several functionalities to support resource and communication abstraction, biomedical data acquisition, health knowledge extraction, persistent data storage, adaptive visualization, system management and value-added services such as intelligent alerts, recommendations and guidelines. An exemplary application is also presented along this work to demonstrate the potential of mHealthDroid. This app is used to investigate on the analysis of human behavior, which is considered to be one of the most prominent areas in mHealth. An accurate activity recognition model is developed and successfully validated in both offline and online conditions.

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.

Blockchain distributed ledger technologies for biomedical and health care applications.

PubMed

Kuo, Tsung-Ting; Kim, Hyeon-Eui; Ohno-Machado, Lucila

2017-11-01

To introduce blockchain technologies, including their benefits, pitfalls, and the latest applications, to the biomedical and health care domains. Biomedical and health care informatics researchers who would like to learn about blockchain technologies and their applications in the biomedical/health care domains. The covered topics include: (1) introduction to the famous Bitcoin crypto-currency and the underlying blockchain technology; (2) features of blockchain; (3) review of alternative blockchain technologies; (4) emerging nonfinancial distributed ledger technologies and applications; (5) benefits of blockchain for biomedical/health care applications when compared to traditional distributed databases; (6) overview of the latest biomedical/health care applications of blockchain technologies; and (7) discussion of the potential challenges and proposed solutions of adopting blockchain technologies in biomedical/health care domains. © The Author 2017. Published by Oxford University Press on behalf of the American Medical Informatics Association.

Proposal for an Update of the Definition and Scope of Behavioral Medicine.

PubMed

Dekker, Joost; Stauder, Adrienne; Penedo, Frank J

2017-02-01

We aim to provide an update of the definition and scope of behavioral medicine in the Charter of ISBM, as the present version was developed more than 25 years ago. We identify issues which need clarification or updating. This leads us to propose an update of the definition and scope of behavioral medicine. Issues in need of clarification or updating include the scope of behavioral medicine (biobehavioral mechanisms, clinical diagnosis and intervention, and prevention and health promotion); research as an essential characteristic of all three areas of behavioral medicine; the application of behavioral medicine; the terminology of behavioral medicine as a multidisciplinary field; and the relationship and distinction between behavioral medicine, mental health, health psychology, and psychosomatic medicine. We propose the following updated definition and scope of behavioral medicine: "Behavioral medicine can be defined as the multidisciplinary field concerned with the development and integration of biomedical and behavioral knowledge relevant to health and disease, and the application of this knowledge to prevention, health promotion, diagnosis, treatment, rehabilitation, and care. The scope of behavioral medicine extends from biobehavioral mechanisms (i.e., the interaction of biomedical processes with psychological, social, societal, cultural, and environmental processes), to clinical diagnosis and intervention, and to public health."

Special Issue: 3D Printing for Biomedical Engineering.

PubMed

Chua, Chee Kai; Yeong, Wai Yee; An, Jia

2017-02-28

Three-dimensional (3D) printing has a long history of applications in biomedical engineering. The development and expansion of traditional biomedical applications are being advanced and enriched by new printing technologies. New biomedical applications such as bioprinting are highly attractive and trendy. This Special Issue aims to provide readers with a glimpse of the recent profile of 3D printing in biomedical research.

Knowledge of the Nigerian Code of Health Research Ethics Among Biomedical Researchers in Southern Nigeria.

PubMed

Ogunrin, Olubunmi A; Daniel, Folasade; Ansa, Victor

2016-12-01

Responsibility for protection of research participants from harm and exploitation rests on Research Ethics Committees and principal investigators. The Nigerian National Code of Health Research Ethics defines responsibilities of stakeholders in research so its knowledge among researchers will likely aid ethical conduct of research. The levels of awareness and knowledge of the Code among biomedical researchers in southern Nigerian research institutions was assessed. Four institutions were selected using a stratified random sampling technique. Research participants were selected by purposive sampling and completed a pre-tested structured questionnaire. A total of 102 biomedical researchers completed the questionnaires. Thirty percent of the participants were aware of the National Code though 64% had attended at least one training seminar in research ethics. Twenty-five percent had a fairly acceptable knowledge (scores 50%-74%) and 10% had excellent knowledge of the code (score ≥75%). Ninety-five percent expressed intentions to learn more about the National Code and agreed that it is highly relevant to the ethical conduct of research. Awareness and knowledge of the Code were found to be very limited among biomedical researchers in southern Nigeria. There is need to improve awareness and knowledge through ethics seminars and training. Use of existing Nigeria-specific online training resources is also encouraged.

Midwifery across the generations: a modernizing midwife in Guatemala.

PubMed

Cosminksy, S

2001-01-01

This article examines change and continuity in midwifery knowledge and practice by comparing a mother and daughter, both of whom are local midwives, or comadronas, on a Guatemalan plantation. The daughter apprenticed with the mother, who died in 1997. Like her mother, she received a government midwifery license after attending an official training course. I discuss the applicability of the concept of "postmodern midwifery" as I trace how both mother and daughter adapted to the pressures of medicalization and modernization. The daughter negotiates with biomedical personnel and copes with increasing government regulations, and she tends to accept biomedical authority more readily than did her mother. Unlike her mother, she sometimes uses this authority to enhance her own status. Nevertheless, her acceptance of the biomedical model is not complete, for she recognizes the practical constraints of poverty, under which both she and her clients live, and she also insists upon the superiority of such practices as massage. Furthermore, biomedicalization is countered by a process of sacralization, which, I suggest, enables midwives both to contest biomedical authority and to deliver meaningful care.

NASA Biomedical Informatics Capabilities and Needs

NASA Technical Reports Server (NTRS)

Johnson-Throop, Kathy A.

2009-01-01

To improve on-orbit clinical capabilities by developing and providing operational support for intelligent, robust, reliable, and secure, enterprise-wide and comprehensive health care and biomedical informatics systems with increasing levels of autonomy, for use on Earth, low Earth orbit & exploration class missions. Biomedical Informatics is an emerging discipline that has been defined as the study, invention, and implementation of structures and algorithms to improve communication, understanding and management of medical information. The end objective of biomedical informatics is the coalescing of data, knowledge, and the tools necessary to apply that data and knowledge in the decision-making process, at the time and place that a decision needs to be made.

Comparative analysis of knowledge representation and reasoning requirements across a range of life sciences textbooks.

PubMed

Chaudhri, Vinay K; Elenius, Daniel; Goldenkranz, Andrew; Gong, Allison; Martone, Maryann E; Webb, William; Yorke-Smith, Neil

2014-01-01

Using knowledge representation for biomedical projects is now commonplace. In previous work, we represented the knowledge found in a college-level biology textbook in a fashion useful for answering questions. We showed that embedding the knowledge representation and question-answering abilities in an electronic textbook helped to engage student interest and improve learning. A natural question that arises from this success, and this paper's primary focus, is whether a similar approach is applicable across a range of life science textbooks. To answer that question, we considered four different textbooks, ranging from a below-introductory college biology text to an advanced, graduate-level neuroscience textbook. For these textbooks, we investigated the following questions: (1) To what extent is knowledge shared between the different textbooks? (2) To what extent can the same upper ontology be used to represent the knowledge found in different textbooks? (3) To what extent can the questions of interest for a range of textbooks be answered by using the same reasoning mechanisms? Our existing modeling and reasoning methods apply especially well both to a textbook that is comparable in level to the text studied in our previous work (i.e., an introductory-level text) and to a textbook at a lower level, suggesting potential for a high degree of portability. Even for the overlapping knowledge found across the textbooks, the level of detail covered in each textbook was different, which requires that the representations must be customized for each textbook. We also found that for advanced textbooks, representing models and scientific reasoning processes was particularly important. With some additional work, our representation methodology would be applicable to a range of textbooks. The requirements for knowledge representation are common across textbooks, suggesting that a shared semantic infrastructure for the life sciences is feasible. Because our representation overlaps heavily with those already being used for biomedical ontologies, this work suggests a natural pathway to include such representations as part of the life sciences curriculum at different grade levels.

The placebo puzzle: examining the discordant space between biomedical science and illness/healing.

PubMed

Pohlman, Shawn; Cibulka, Nancy J; Palmer, Janice L; Lorenz, Rebecca A; SmithBattle, Lee

2013-03-01

The placebo response presents an enigma to biomedical science: how can 'inert' or 'sham' procedures reduce symptoms and produce physiological changes that are comparable to prescribed treatments? In this study, we examine this puzzle by explicating the discordant space between the prevailing biomedical paradigm, which focuses on a technical understanding of diagnosis and treatment, and a broader understanding of illness and healing as relational and embodied. Although biomedical achievements are impressive, the knowledge resulting from this paradigm is limited by its ontological and epistemological assumptions. When the body and world are objectified, illness meanings, therapeutic relationships, and healing practices are dismissed or distorted. In spite of a robust critique of the tenets of biomedicine for guiding practice, the biomedical paradigm retains a tenacious hold on evidence-based medicine and nursing, downplaying our clinical understanding of the sentient body, patients' life-worlds, and illness and healing. In reality, skilled nurses rely on multiple forms of knowledge in providing high-quality care to particular patients. Clinically wise nurses integrate their experience and knowledge of patients' priorities, fears, and illness trajectories along with biomedical findings to make astute judgments and promote health and healing. © 2012 Blackwell Publishing Ltd.

Relationship of biomedical science content acquisition performance to students' level of PBL group interaction: are students learning during PBL group?

PubMed

Romito, Laura M; Eckert, George J

2011-05-01

This study assessed biomedical science content acquisition from problem-based learning (PBL) and its relationship to students' level of group interaction. We hypothesized that learning in preparation for exams results primarily from individual study of post-case learning objectives and that outcomes would be unrelated to students' group involvement. During dental curricular years 1 and 2, student-generated biomedical learning issues (LIs) were identified from six randomly chosen PBL cases. Knowledge and application of case concepts were assessed with quizzes based on the identified LIs prior to dissemination of the learning objectives. Students and facilitators were surveyed on students' level of group involvement for the assessed LI topics. Year 1 students had significantly higher assessment scores (p=0.0001). For both student classes, means were significantly higher for the recall item (Q1) than for the application item (Q2). Q1 scores increased along with the student's reported role for Year 1 (p=0.04). However, there was no relationship between the student's reported role and Q1 for Year 2 (p=0.20). There was no relationship between the student's reported role and Q2 for Year 1 (p=0.09) or Year 2 (p=0.19). This suggests that students' level of group involvement on the biomedical learning issues did not significantly impact students' assessment performance.

[Biomedical waste management in five hospitals in Dakar, Senegal].

PubMed

Ndiaye, M; El Metghari, L; Soumah, M M; Sow, M L

2012-10-01

Biomedical waste is currently a real health and environmental concern. In this regard, a study was conducted in 5 hospitals in Dakar to review their management of biomedical waste and to formulate recommendations. This is a descriptive cross-sectional study conducted from 1 April to 31 July 2010 in five major hospitals of Dakar. A questionnaire administered to hospital managers, heads of departments, residents and heads of hospital hygiene departments as well as interviews conducted with healthcare personnel and operators of waste incinerators made it possible to assess mechanisms and knowledge on biomedical waste management. Content analysis of interviews, observations and a data sheet allowed processing the data thus gathered. Of the 150 questionnaires distributed, 98 responses were obtained representing a response rate of 65.3%. An interview was conducted with 75 employees directly involved in the management of biomedical waste and observations were made on biomedical waste management in 86 hospital services. Sharps as well as blood and liquid waste were found in all services except in pharmacies, pharmaceutical waste in 66 services, infectious waste in 49 services and anatomical waste in 11 services. Sorting of biomedical waste was ill-adapted in 53.5% (N = 46) of services and the use of the colour-coding system effective in 31.4% (N = 27) of services. Containers for the safe disposal of sharps were available in 82.5% (N = 71) of services and were effectively utilized in 51.1% (N = 44) of these services. In most services, an illadapted packaging was observed with the use of plastic bottles and bins for waste collection and overfilled containers. With the exception of Hôpital Principal, the main storage area was in open air, unsecured, with biomedical waste littered on the floor and often mixed with waste similar to household refuse. The transfer of biomedical waste to the main storage area was done using trolleys or carts in 67.4% (N = 58) of services and wheelbarrows in 33.7% (N = 29). Biomedical waste was disposed of in old incinerators or in artisanal ovens with a great deal of smoke emanating from these. Working conditions were deemed poor by 81.3% (N = 61) of employees interviewed and personal protection equipment was available in 45.3% (N = 39) of services. Knowledge about biomedical waste management was deemed satisfactory by 62.6% (N = 47) of interviewees and 80% (N = 60) were aware of the health risks related to biomedical waste. The poor management of biomedical waste is a reality in hospital facilities in Dakar. This can be addressed by increasing the awareness of managers for an effective application of the legislation, implementing realistic management programmes and providing the appropriate on-the-job training to staff members.

Special Issue: 3D Printing for Biomedical Engineering

PubMed Central

Chua, Chee Kai; Yeong, Wai Yee; An, Jia

2017-01-01

Three-dimensional (3D) printing has a long history of applications in biomedical engineering. The development and expansion of traditional biomedical applications are being advanced and enriched by new printing technologies. New biomedical applications such as bioprinting are highly attractive and trendy. This Special Issue aims to provide readers with a glimpse of the recent profile of 3D printing in biomedical research. PMID:28772604

Representation of Biomedical Expertise in Ontologies: a Case Study about Knowledge Acquisition on HTLV viruses and their clinical manifestations.

PubMed

Cardoso Coelho, Kátia; Barcellos Almeida, Maurício

2015-01-01

In this paper, we introduce a set of methodological steps for knowledge acquisition applied to the organization of biomedical information through ontologies. Those steps are tested in a real case involving Human T Cell Lymphotropic Virus (HTLV), which causes myriad infectious diseases. We hope to contribute to providing suitable knowledge representation of scientific domains.

The Role Biomedical Science Laboratories Can Play in Improving Science Knowledge and Promoting First-Year Nursing Academic Success

ERIC Educational Resources Information Center

Arneson, Pam

2011-01-01

The need for additional nursing and health care professionals is expected to increase dramatically over the next 20 years. With this in mind, students must have strong biomedical science knowledge to be competent in their field. Some studies have shown that participation in bioscience laboratories can enhance science knowledge. If this is true, an…

Cognitive and learning sciences in biomedical and health instructional design: A review with lessons for biomedical informatics education.

PubMed

Patel, Vimla L; Yoskowitz, Nicole A; Arocha, Jose F; Shortliffe, Edward H

2009-02-01

Theoretical and methodological advances in the cognitive and learning sciences can greatly inform curriculum and instruction in biomedicine and also educational programs in biomedical informatics. It does so by addressing issues such as the processes related to comprehension of medical information, clinical problem-solving and decision-making, and the role of technology. This paper reviews these theories and methods from the cognitive and learning sciences and their role in addressing current and future needs in designing curricula, largely using illustrative examples drawn from medical education. The lessons of this past work are also applicable, however, to biomedical and health professional curricula in general, and to biomedical informatics training, in particular. We summarize empirical studies conducted over two decades on the role of memory, knowledge organization and reasoning as well as studies of problem-solving and decision-making in medical areas that inform curricular design. The results of this research contribute to the design of more informed curricula based on empirical findings about how people learn and think, and more specifically, how expertise is developed. Similarly, the study of practice can also help to shape theories of human performance, technology-based learning, and scientific and professional collaboration that extend beyond the domain of medicine. Just as biomedical science has revolutionized health care practice, research in the cognitive and learning sciences provides a scientific foundation for education in biomedicine, the health professions, and biomedical informatics.

Biomedical discovery acceleration, with applications to craniofacial development.

PubMed

Leach, Sonia M; Tipney, Hannah; Feng, Weiguo; Baumgartner, William A; Kasliwal, Priyanka; Schuyler, Ronald P; Williams, Trevor; Spritz, Richard A; Hunter, Lawrence

2009-03-01

The profusion of high-throughput instruments and the explosion of new results in the scientific literature, particularly in molecular biomedicine, is both a blessing and a curse to the bench researcher. Even knowledgeable and experienced scientists can benefit from computational tools that help navigate this vast and rapidly evolving terrain. In this paper, we describe a novel computational approach to this challenge, a knowledge-based system that combines reading, reasoning, and reporting methods to facilitate analysis of experimental data. Reading methods extract information from external resources, either by parsing structured data or using biomedical language processing to extract information from unstructured data, and track knowledge provenance. Reasoning methods enrich the knowledge that results from reading by, for example, noting two genes that are annotated to the same ontology term or database entry. Reasoning is also used to combine all sources into a knowledge network that represents the integration of all sorts of relationships between a pair of genes, and to calculate a combined reliability score. Reporting methods combine the knowledge network with a congruent network constructed from experimental data and visualize the combined network in a tool that facilitates the knowledge-based analysis of that data. An implementation of this approach, called the Hanalyzer, is demonstrated on a large-scale gene expression array dataset relevant to craniofacial development. The use of the tool was critical in the creation of hypotheses regarding the roles of four genes never previously characterized as involved in craniofacial development; each of these hypotheses was validated by further experimental work.

DEApp: an interactive web interface for differential expression analysis of next generation sequence data.

PubMed

Li, Yan; Andrade, Jorge

2017-01-01

A growing trend in the biomedical community is the use of Next Generation Sequencing (NGS) technologies in genomics research. The complexity of downstream differential expression (DE) analysis is however still challenging, as it requires sufficient computer programing and command-line knowledge. Furthermore, researchers often need to evaluate and visualize interactively the effect of using differential statistical and error models, assess the impact of selecting different parameters and cutoffs, and finally explore the overlapping consensus of cross-validated results obtained with different methods. This represents a bottleneck that slows down or impedes the adoption of NGS technologies in many labs. We developed DEApp, an interactive and dynamic web application for differential expression analysis of count based NGS data. This application enables models selection, parameter tuning, cross validation and visualization of results in a user-friendly interface. DEApp enables labs with no access to full time bioinformaticians to exploit the advantages of NGS applications in biomedical research. This application is freely available at https://yanli.shinyapps.io/DEAppand https://gallery.shinyapps.io/DEApp.

Synergies and Distinctions between Computational Disciplines in Biomedical Research: Perspective from the Clinical and Translational Science Award Programs

PubMed Central

Bernstam, Elmer V.; Hersh, William R.; Johnson, Stephen B.; Chute, Christopher G.; Nguyen, Hien; Sim, Ida; Nahm, Meredith; Weiner, Mark; Miller, Perry; DiLaura, Robert P.; Overcash, Marc; Lehmann, Harold P.; Eichmann, David; Athey, Brian D.; Scheuermann, Richard H.; Anderson, Nick; Starren, Justin B.; Harris, Paul A.; Smith, Jack W.; Barbour, Ed; Silverstein, Jonathan C.; Krusch, David A.; Nagarajan, Rakesh; Becich, Michael J.

2010-01-01

Clinical and translational research increasingly requires computation. Projects may involve multiple computationally-oriented groups including information technology (IT) professionals, computer scientists and biomedical informaticians. However, many biomedical researchers are not aware of the distinctions among these complementary groups, leading to confusion, delays and sub-optimal results. Although written from the perspective of clinical and translational science award (CTSA) programs within academic medical centers, the paper addresses issues that extend beyond clinical and translational research. The authors describe the complementary but distinct roles of operational IT, research IT, computer science and biomedical informatics using a clinical data warehouse as a running example. In general, IT professionals focus on technology. The authors distinguish between two types of IT groups within academic medical centers: central or administrative IT (supporting the administrative computing needs of large organizations) and research IT (supporting the computing needs of researchers). Computer scientists focus on general issues of computation such as designing faster computers or more efficient algorithms, rather than specific applications. In contrast, informaticians are concerned with data, information and knowledge. Biomedical informaticians draw on a variety of tools, including but not limited to computers, to solve information problems in health care and biomedicine. The paper concludes with recommendations regarding administrative structures that can help to maximize the benefit of computation to biomedical research within academic health centers. PMID:19550198

Advances in nano-scaled biosensors for biomedical applications.

PubMed

Wang, Jianling; Chen, Guihua; Jiang, Hui; Li, Zhiyong; Wang, Xuemei

2013-08-21

Recently, a growing amount of attention has been focused on the utility of biosensors for biomedical applications. Combined with nanomaterials and nanostructures, nano-scaled biosensors are installed for biomedical applications, such as pathogenic bacteria monitoring, virus recognition, disease biomarker detection, among others. These nano-biosensors offer a number of advantages and in many respects are ideally suited to biomedical applications, which could be made as extremely flexible devices, allowing biomedical analysis with speediness, excellent selectivity and high sensitivity. This minireview discusses the literature published in the latest years on the advances in biomedical applications of nano-scaled biosensors for disease bio-marking and detection, especially in bio-imaging and the diagnosis of pathological cells and viruses, monitoring pathogenic bacteria, thus providing insight into the future prospects of biosensors in relevant clinical applications.

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.

Biomedical question answering using semantic relations.

PubMed

Hristovski, Dimitar; Dinevski, Dejan; Kastrin, Andrej; Rindflesch, Thomas C

2015-01-16

The proliferation of the scientific literature in the field of biomedicine makes it difficult to keep abreast of current knowledge, even for domain experts. While general Web search engines and specialized information retrieval (IR) systems have made important strides in recent decades, the problem of accurate knowledge extraction from the biomedical literature is far from solved. Classical IR systems usually return a list of documents that have to be read by the user to extract relevant information. This tedious and time-consuming work can be lessened with automatic Question Answering (QA) systems, which aim to provide users with direct and precise answers to their questions. In this work we propose a novel methodology for QA based on semantic relations extracted from the biomedical literature. We extracted semantic relations with the SemRep natural language processing system from 122,421,765 sentences, which came from 21,014,382 MEDLINE citations (i.e., the complete MEDLINE distribution up to the end of 2012). A total of 58,879,300 semantic relation instances were extracted and organized in a relational database. The QA process is implemented as a search in this database, which is accessed through a Web-based application, called SemBT (available at http://sembt.mf.uni-lj.si ). We conducted an extensive evaluation of the proposed methodology in order to estimate the accuracy of extracting a particular semantic relation from a particular sentence. Evaluation was performed by 80 domain experts. In total 7,510 semantic relation instances belonging to 2,675 distinct relations were evaluated 12,083 times. The instances were evaluated as correct 8,228 times (68%). In this work we propose an innovative methodology for biomedical QA. The system is implemented as a Web-based application that is able to provide precise answers to a wide range of questions. A typical question is answered within a few seconds. The tool has some extensions that make it especially useful for interpretation of DNA microarray results.

Understanding semantic mapping evolution by observing changes in biomedical ontologies.

PubMed

dos Reis, Julio Cesar; Pruski, Cédric; Da Silveira, Marcos; Reynaud-Delaître, Chantal

2014-02-01

Knowledge Organization Systems (KOSs) are extensively used in the biomedical domain to support information sharing between software applications. KOSs are proposed covering different, but overlapping subjects, and mappings indicate the semantic relation between concepts from two KOSs. Over time, KOSs change as do the mappings between them. This can result from a new discovery or a revision of existing knowledge which includes corrections of concepts or mappings. Indeed, changes affecting KOS entities may force the underline mappings to be updated in order to ensure their reliability over time. To tackle this open research problem, we study how mappings are affected by KOS evolution. This article presents a detailed descriptive analysis of the impact that changes in KOS have on mappings. As a case study, we use the official mappings established between SNOMED CT and ICD-9-CM from 2009 to 2011. Results highlight factors according to which KOS changes in varying degrees influence the evolution of mappings. Copyright © 2013 Elsevier Inc. All rights reserved.

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.

Core competencies for scientific editors of biomedical journals: consensus statement.

PubMed

Moher, David; Galipeau, James; Alam, Sabina; Barbour, Virginia; Bartolomeos, Kidist; Baskin, Patricia; Bell-Syer, Sally; Cobey, Kelly D; Chan, Leighton; Clark, Jocalyn; Deeks, Jonathan; Flanagin, Annette; Garner, Paul; Glenny, Anne-Marie; Groves, Trish; Gurusamy, Kurinchi; Habibzadeh, Farrokh; Jewell-Thomas, Stefanie; Kelsall, Diane; Lapeña, José Florencio; MacLehose, Harriet; Marusic, Ana; McKenzie, Joanne E; Shah, Jay; Shamseer, Larissa; Straus, Sharon; Tugwell, Peter; Wager, Elizabeth; Winker, Margaret; Zhaori, Getu

2017-09-11

Scientific editors are responsible for deciding which articles to publish in their journals. However, we have not found documentation of their required knowledge, skills, and characteristics, or the existence of any formal core competencies for this role. We describe the development of a minimum set of core competencies for scientific editors of biomedical journals. The 14 key core competencies are divided into three major areas, and each competency has a list of associated elements or descriptions of more specific knowledge, skills, and characteristics that contribute to its fulfillment. We believe that these core competencies are a baseline of the knowledge, skills, and characteristics needed to perform competently the duties of a scientific editor at a biomedical journal.

A Novel Multi-Class Ensemble Model for Classifying Imbalanced Biomedical Datasets

NASA Astrophysics Data System (ADS)

Bikku, Thulasi; Sambasiva Rao, N., Dr; Rao, Akepogu Ananda, Dr

2017-08-01

This paper mainly focuseson developing aHadoop based framework for feature selection and classification models to classify high dimensionality data in heterogeneous biomedical databases. Wide research has been performing in the fields of Machine learning, Big data and Data mining for identifying patterns. The main challenge is extracting useful features generated from diverse biological systems. The proposed model can be used for predicting diseases in various applications and identifying the features relevant to particular diseases. There is an exponential growth of biomedical repositories such as PubMed and Medline, an accurate predictive model is essential for knowledge discovery in Hadoop environment. Extracting key features from unstructured documents often lead to uncertain results due to outliers and missing values. In this paper, we proposed a two phase map-reduce framework with text preprocessor and classification model. In the first phase, mapper based preprocessing method was designed to eliminate irrelevant features, missing values and outliers from the biomedical data. In the second phase, a Map-Reduce based multi-class ensemble decision tree model was designed and implemented in the preprocessed mapper data to improve the true positive rate and computational time. The experimental results on the complex biomedical datasets show that the performance of our proposed Hadoop based multi-class ensemble model significantly outperforms state-of-the-art baselines.

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

2017-05-01

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 is an e-learning platform that empowers the biomedical community to develop, launch and share open training materials. It deploys hands-on software training toolboxes through virtualization technologies such as Amazon EC2 and Virtualbox. The BBDTC facilitates migration of courses across other course management platforms. The framework encourages knowledge sharing and content personalization through the playlist functionality that enables unique learning experiences and accelerates information dissemination to a wider community.

Camera systems in human motion analysis for biomedical applications

NASA Astrophysics Data System (ADS)

Chin, Lim Chee; Basah, Shafriza Nisha; Yaacob, Sazali; Juan, Yeap Ewe; Kadir, Aida Khairunnisaa Ab.

2015-05-01

Human Motion Analysis (HMA) system has been one of the major interests among researchers in the field of computer vision, artificial intelligence and biomedical engineering and sciences. This is due to its wide and promising biomedical applications, namely, bio-instrumentation for human computer interfacing and surveillance system for monitoring human behaviour as well as analysis of biomedical signal and image processing for diagnosis and rehabilitation applications. This paper provides an extensive review of the camera system of HMA, its taxonomy, including camera types, camera calibration and camera configuration. The review focused on evaluating the camera system consideration of the HMA system specifically for biomedical applications. This review is important as it provides guidelines and recommendation for researchers and practitioners in selecting a camera system of the HMA system for biomedical applications.

Biomedical physics in continuing medical education: an analysis of learning needs.

PubMed

Rotomskis, Ricardas; Karenauskaite, Violeta; Balzekiene, Aiste

2009-01-01

To examine the learning and practice needs of medical professionals in the field of continuing education of biomedical physics in Lithuania. The study was based on a questionnaire survey of 309 medical professionals throughout Lithuania, 3 focus group discussions, and 18 interviews with medical and physics experts. The study showed that medical professionals lack knowledge of physics: only 15.1% of the respondents admitted that they had enough knowledge in biomedical physics to understand the functioning of the medical devices that they used, and 7.5% of respondents indicated that they had enough knowledge to understand and adopt medical devices of the new generation. Physics knowledge was valued more highly by medical professionals with scientific degrees. As regards continuing medical education, it was revealed that personal motivation (88.7%) and responsibility for patients (44.3%) were the most important motives for upgrading competencies, whereas workload (65.4%) and financial limits (45.3%) were the main obstacles. The most popular teaching methods were those based on practical work (78.9%), and the least popular was project work (27.8%). The study revealed that biomedical physics knowledge was needed in both specializations and practical work, and the most important factor for determining its need was professional aspirations. Medical professionals' understanding of medical devices, especially those of the new generation, is essentially functional in nature. Professional upgrading courses contain only fragmented biomedical physics content, and new courses should be developed jointly by experts in physics and medicine to meet the specialized needs of medical professionals.

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.

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

Design, implementation and validation of a novel open framework for agile development of mobile health applications

PubMed Central

2015-01-01

The delivery of healthcare services has experienced tremendous changes during the last years. Mobile health or mHealth is a key engine of advance in the forefront of this revolution. Although there exists a growing development of mobile health applications, there is a lack of tools specifically devised for their implementation. This work presents mHealthDroid, an open source Android implementation of a mHealth Framework designed to facilitate the rapid and easy development of mHealth and biomedical apps. The framework is particularly planned to leverage the potential of mobile devices such as smartphones or tablets, wearable sensors and portable biomedical systems. These devices are increasingly used for the monitoring and delivery of personal health care and wellbeing. The framework implements several functionalities to support resource and communication abstraction, biomedical data acquisition, health knowledge extraction, persistent data storage, adaptive visualization, system management and value-added services such as intelligent alerts, recommendations and guidelines. An exemplary application is also presented along this work to demonstrate the potential of mHealthDroid. This app is used to investigate on the analysis of human behavior, which is considered to be one of the most prominent areas in mHealth. An accurate activity recognition model is developed and successfully validated in both offline and online conditions. PMID:26329639

The BioLexicon: a large-scale terminological resource for biomedical text mining

PubMed Central

2011-01-01

Background Due to the rapidly expanding body of biomedical literature, biologists require increasingly sophisticated and efficient systems to help them to search for relevant information. Such systems should account for the multiple written variants used to represent biomedical concepts, and allow the user to search for specific pieces of knowledge (or events) involving these concepts, e.g., protein-protein interactions. Such functionality requires access to detailed information about words used in the biomedical literature. Existing databases and ontologies often have a specific focus and are oriented towards human use. Consequently, biological knowledge is dispersed amongst many resources, which often do not attempt to account for the large and frequently changing set of variants that appear in the literature. Additionally, such resources typically do not provide information about how terms relate to each other in texts to describe events. Results This article provides an overview of the design, construction and evaluation of a large-scale lexical and conceptual resource for the biomedical domain, the BioLexicon. The resource can be exploited by text mining tools at several levels, e.g., part-of-speech tagging, recognition of biomedical entities, and the extraction of events in which they are involved. As such, the BioLexicon must account for real usage of words in biomedical texts. In particular, the BioLexicon gathers together different types of terms from several existing data resources into a single, unified repository, and augments them with new term variants automatically extracted from biomedical literature. Extraction of events is facilitated through the inclusion of biologically pertinent verbs (around which events are typically organized) together with information about typical patterns of grammatical and semantic behaviour, which are acquired from domain-specific texts. In order to foster interoperability, the BioLexicon is modelled using the Lexical Markup Framework, an ISO standard. Conclusions The BioLexicon contains over 2.2 M lexical entries and over 1.8 M terminological variants, as well as over 3.3 M semantic relations, including over 2 M synonymy relations. Its exploitation can benefit both application developers and users. We demonstrate some such benefits by describing integration of the resource into a number of different tools, and evaluating improvements in performance that this can bring. PMID:21992002

The BioLexicon: a large-scale terminological resource for biomedical text mining.

PubMed

Thompson, Paul; McNaught, John; Montemagni, Simonetta; Calzolari, Nicoletta; del Gratta, Riccardo; Lee, Vivian; Marchi, Simone; Monachini, Monica; Pezik, Piotr; Quochi, Valeria; Rupp, C J; Sasaki, Yutaka; Venturi, Giulia; Rebholz-Schuhmann, Dietrich; Ananiadou, Sophia

2011-10-12

Due to the rapidly expanding body of biomedical literature, biologists require increasingly sophisticated and efficient systems to help them to search for relevant information. Such systems should account for the multiple written variants used to represent biomedical concepts, and allow the user to search for specific pieces of knowledge (or events) involving these concepts, e.g., protein-protein interactions. Such functionality requires access to detailed information about words used in the biomedical literature. Existing databases and ontologies often have a specific focus and are oriented towards human use. Consequently, biological knowledge is dispersed amongst many resources, which often do not attempt to account for the large and frequently changing set of variants that appear in the literature. Additionally, such resources typically do not provide information about how terms relate to each other in texts to describe events. This article provides an overview of the design, construction and evaluation of a large-scale lexical and conceptual resource for the biomedical domain, the BioLexicon. The resource can be exploited by text mining tools at several levels, e.g., part-of-speech tagging, recognition of biomedical entities, and the extraction of events in which they are involved. As such, the BioLexicon must account for real usage of words in biomedical texts. In particular, the BioLexicon gathers together different types of terms from several existing data resources into a single, unified repository, and augments them with new term variants automatically extracted from biomedical literature. Extraction of events is facilitated through the inclusion of biologically pertinent verbs (around which events are typically organized) together with information about typical patterns of grammatical and semantic behaviour, which are acquired from domain-specific texts. In order to foster interoperability, the BioLexicon is modelled using the Lexical Markup Framework, an ISO standard. The BioLexicon contains over 2.2 M lexical entries and over 1.8 M terminological variants, as well as over 3.3 M semantic relations, including over 2 M synonymy relations. Its exploitation can benefit both application developers and users. We demonstrate some such benefits by describing integration of the resource into a number of different tools, and evaluating improvements in performance that this can bring.

Precarious projects: conversions of (biomedical) knowledge in an East African city.

PubMed

Prince, Ruth J

2014-01-01

This article explores the orientations of lay people in Kenya to science-specifically to biomedical knowledge about HIV--and their struggles to convert this knowledge into meaningful futures. In Kenya, the global response to the HIV-AIDS epidemic has resulted in a highly stratified landscape of intervention. Globally-funded treatment programs and clinical trials, focusing on HIV, channel transnational resources, expertise, and knowledge into specific sites--HIV clinics, NGOs, and research stations--inscribing these spaces as 'global' while leaving others decidedly 'local.' Rolled out in the form of 'projects,' these interventions offer resources and opportunities for a limited time only. Based on ethnographic fieldwork in the city of Kisumu, this article follows the circulation of biomedical knowledge through such projects and its conversion in ways beyond those imagined by policy-makers, as it meets the aspirations of city-dwellers and enters into local livelihoods. Mediated by nongovernmental organizations through workshops and certificates, this knowledge is both fragmentary and ephemeral. I explore the temporal and spatial implications of such knowledge for those who seek to attach themselves to it and shape their identities and futures in relation to it.

Synthesis and Characterization of Stimuli Responsive Block Copolymers, Self-Assembly Behavior and Applications

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

Determan, Michael Duane

The central theme of this thesis work is to develop new block copolymer materials for biomedical applications. While there are many reports of stimuli-responsive amphiphilic [19-21] and crosslinked hydrogel materials [22], the development of an in situ gel forming, pH responsive pentablock copolymer is a novel contribution to the field, Figure 1.1 is a sketch of an ABCBA pentablock copolymer. The A blocks are cationic tertiary amine methacrylates blocked to a central Pluronic F127 triblock copolymer. In addition to the prerequisite synthetic and macromolecular characterization of these new materials, the self-assembled supramolecular structures formed by the pentablock were experimentally evaluated.more » This synthesis and characterization process serves to elucidate the important structure property relationships of these novel materials, The pH and temperature responsive behavior of the pentablock copolymer were explored especially with consideration towards injectable drug delivery applications. Future synthesis work will focus on enhancing and tuning the cell specific targeting of DNA/pentablock copolymer polyplexes. The specific goals of this research are: (1) Develop a synthetic route for gel forming pentablock block copolymers with pH and temperature sensitive properties. Synthesis of these novel copolymers is accomplished with ATRP, yielding low polydispersity and control of the block copolymer architecture. Well defined macromolecular characteristics are required to tailor the phase behavior of these materials. (2) Characterize relationship between the size and shape of pentablock copolymer micelles and gel structure and the pH and temperature of the copolymer solutions with SAXS, SANS and CryoTEM. (3) Evaluate the temperature and pH induced phase separation and macroscopic self-assembly phenomenon of the pentablock copolymer. (4) Utilize the knowledge gained from first three goals to design and formulate drug delivery formulations based on the multi-responsive properties of the pentablock copolymer. Demonstrate potential biomedical applications of these materials with in vitro drug release studies from pentablock copolymer hydrogels. The intent of this work is to contribute to the knowledge necessary for further tailoring of these, and other functional block copolymer materials for biomedical applications.« less

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

Medicinal plants used by women in Mecca: urban, Muslim and gendered knowledge.

PubMed

Alqethami, Afnan; Hawkins, Julie A; Teixidor-Toneu, Irene

2017-11-17

This study explores medicinal plant knowledge and use among Muslim women in the city of Mecca, Saudi Arabia. Ethnobotanical research in the region has focused on rural populations and male herbal healers in cities, and based on these few studies, it is suggested that medicinal plant knowledge may be eroding. Here, we document lay, female knowledge of medicinal plants in an urban centre, interpreting findings in the light of the growing field of urban ethnobotany and gendered knowledge and in an Islamic context. Free-listing, structured and semi-structured interviews were used to document the extent of medicinal plant knowledge among 32 Meccan women. Vernacular names, modes of preparation and application, intended therapeutic use and emic toxicological remarks were recorded. Women were asked where they learnt about medicinal plants and if and when they preferred using medicinal plants over biomedical resources. Prior informed consent was always obtained. We compared the list of medicinal plants used by these Meccan women with medicinal plants previously documented in published literature. One hundred eighteen vernacular names were collected, corresponding to approximately 110 plants, including one algae. Of these, 95 were identified at the species level and 39 (41%) had not been previously cited in Saudi Arabian medicinal plant literature. Almost one half of the plants cited are food and flavouring plants. Meccan women interviewed learn about medicinal plants from their social network, mass media and written sources, and combine biomedical and medicinal plant health care. However, younger women more often prefer biomedical resources and learn from written sources and mass media. The fairly small number of interviews conducted in this study was sufficient to reveal the singular body of medicinal plant knowledge held by women in Mecca and applied to treat common ailments. Plant availability in local shops and markets and inclusion in religious texts seem to shape the botanical diversity used by the Meccan women interviewed, and the use of foods and spices medicinally could be a global feature of urban ethnobotany. Ethnobotanical knowledge among women in Islamic communities may be changing due to access to mass media and biomedicine. We recognise the lack of documentation of the diversity of medicinal plant knowledge in the Arabian Peninsula and an opportunity to better understand gendered urban and rural knowledge.

Design of Biomedical Robots for Phenotype Prediction Problems

PubMed Central

deAndrés-Galiana, Enrique J.; Sonis, Stephen T.

2016-01-01

Abstract Genomics has been used with varying degrees of success in the context of drug discovery and in defining mechanisms of action for diseases like cancer and neurodegenerative and rare diseases in the quest for orphan drugs. To improve its utility, accuracy, and cost-effectiveness optimization of analytical methods, especially those that translate to clinically relevant outcomes, is critical. Here we define a novel tool for genomic analysis termed a biomedical robot in order to improve phenotype prediction, identifying disease pathogenesis and significantly defining therapeutic targets. Biomedical robot analytics differ from historical methods in that they are based on melding feature selection methods and ensemble learning techniques. The biomedical robot mathematically exploits the structure of the uncertainty space of any classification problem conceived as an ill-posed optimization problem. Given a classifier, there exist different equivalent small-scale genetic signatures that provide similar predictive accuracies. We perform the sensitivity analysis to noise of the biomedical robot concept using synthetic microarrays perturbed by different kinds of noises in expression and class assignment. Finally, we show the application of this concept to the analysis of different diseases, inferring the pathways and the correlation networks. The final aim of a biomedical robot is to improve knowledge discovery and provide decision systems to optimize diagnosis, treatment, and prognosis. This analysis shows that the biomedical robots are robust against different kinds of noises and particularly to a wrong class assignment of the samples. Assessing the uncertainty that is inherent to any phenotype prediction problem is the right way to address this kind of problem. PMID:27347715

Design of Biomedical Robots for Phenotype Prediction Problems.

PubMed

deAndrés-Galiana, Enrique J; Fernández-Martínez, Juan Luis; Sonis, Stephen T

2016-08-01

Genomics has been used with varying degrees of success in the context of drug discovery and in defining mechanisms of action for diseases like cancer and neurodegenerative and rare diseases in the quest for orphan drugs. To improve its utility, accuracy, and cost-effectiveness optimization of analytical methods, especially those that translate to clinically relevant outcomes, is critical. Here we define a novel tool for genomic analysis termed a biomedical robot in order to improve phenotype prediction, identifying disease pathogenesis and significantly defining therapeutic targets. Biomedical robot analytics differ from historical methods in that they are based on melding feature selection methods and ensemble learning techniques. The biomedical robot mathematically exploits the structure of the uncertainty space of any classification problem conceived as an ill-posed optimization problem. Given a classifier, there exist different equivalent small-scale genetic signatures that provide similar predictive accuracies. We perform the sensitivity analysis to noise of the biomedical robot concept using synthetic microarrays perturbed by different kinds of noises in expression and class assignment. Finally, we show the application of this concept to the analysis of different diseases, inferring the pathways and the correlation networks. The final aim of a biomedical robot is to improve knowledge discovery and provide decision systems to optimize diagnosis, treatment, and prognosis. This analysis shows that the biomedical robots are robust against different kinds of noises and particularly to a wrong class assignment of the samples. Assessing the uncertainty that is inherent to any phenotype prediction problem is the right way to address this kind of problem.

Biomedical text mining and its applications in cancer research.

PubMed

Zhu, Fei; Patumcharoenpol, Preecha; Zhang, Cheng; Yang, Yang; Chan, Jonathan; Meechai, Asawin; Vongsangnak, Wanwipa; Shen, Bairong

2013-04-01

Cancer is a malignant disease that has caused millions of human deaths. Its study has a long history of well over 100years. There have been an enormous number of publications on cancer research. This integrated but unstructured biomedical text is of great value for cancer diagnostics, treatment, and prevention. The immense body and rapid growth of biomedical text on cancer has led to the appearance of a large number of text mining techniques aimed at extracting novel knowledge from scientific text. Biomedical text mining on cancer research is computationally automatic and high-throughput in nature. However, it is error-prone due to the complexity of natural language processing. In this review, we introduce the basic concepts underlying text mining and examine some frequently used algorithms, tools, and data sets, as well as assessing how much these algorithms have been utilized. We then discuss the current state-of-the-art text mining applications in cancer research and we also provide some resources for cancer text mining. With the development of systems biology, researchers tend to understand complex biomedical systems from a systems biology viewpoint. Thus, the full utilization of text mining to facilitate cancer systems biology research is fast becoming a major concern. To address this issue, we describe the general workflow of text mining in cancer systems biology and each phase of the workflow. We hope that this review can (i) provide a useful overview of the current work of this field; (ii) help researchers to choose text mining tools and datasets; and (iii) highlight how to apply text mining to assist cancer systems biology research. Copyright © 2012 Elsevier Inc. All rights reserved.

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.

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

Character-level neural network for biomedical named entity recognition.

PubMed

Gridach, Mourad

2017-06-01

Biomedical named entity recognition (BNER), which extracts important named entities such as genes and proteins, is a challenging task in automated systems that mine knowledge in biomedical texts. The previous state-of-the-art systems required large amounts of task-specific knowledge in the form of feature engineering, lexicons and data pre-processing to achieve high performance. In this paper, we introduce a novel neural network architecture that benefits from both word- and character-level representations automatically, by using a combination of bidirectional long short-term memory (LSTM) and conditional random field (CRF) eliminating the need for most feature engineering tasks. We evaluate our system on two datasets: JNLPBA corpus and the BioCreAtIvE II Gene Mention (GM) corpus. We obtained state-of-the-art performance by outperforming the previous systems. To the best of our knowledge, we are the first to investigate the combination of deep neural networks, CRF, word embeddings and character-level representation in recognizing biomedical named entities. Copyright © 2017 Elsevier Inc. All rights reserved.

Leveraging Wikipedia knowledge to classify multilingual biomedical documents.

PubMed

Antonio Mouriño García, Marcos; Pérez Rodríguez, Roberto; Anido Rifón, Luis

2018-05-02

This article presents a classifier that leverages Wikipedia knowledge to represent documents as vectors of concepts weights, and analyses its suitability for classifying biomedical documents written in any language when it is trained only with English documents. We propose the cross-language concept matching technique, which relies on Wikipedia interlanguage links to convert concept vectors between languages. The performance of the classifier is compared to a classifier based on machine translation, and two classifiers based on MetaMap. To perform the experiments, we created two multilingual corpus. The first one, Multi-Lingual UVigoMED (ML-UVigoMED) is composed of 23,647 Wikipedia documents about biomedical topics written in English, German, French, Spanish, Italian, Galician, Romanian, and Icelandic. The second one, English-French-Spanish-German UVigoMED (EFSG-UVigoMED) is composed of 19,210 biomedical abstract extracted from MEDLINE written in English, French, Spanish, and German. The performance of the approach proposed is superior to any of the state-of-the art classifier in the benchmark. We conclude that leveraging Wikipedia knowledge is of great advantage in tasks of multilingual classification of biomedical documents. Copyright © 2018 Elsevier B.V. All rights reserved.

Excluding the poor from accessing biomedical literature: a rights violation that impedes global health.

PubMed

Yamey, Gavin

2008-01-01

Most biomedical journals charge readers a hefty access toll to read the full text version of a published research article. These tolls bring enormous profits to the traditional corporate publishing industry, but they make it impossible for most people worldwide--particularly in low and middle income countries--to access the biomedical literature. Traditional publishers also insist on owning the copyright on these articles, making it illegal for readers to freely distribute and photocopy papers, translate them, or create derivative educational works. This article argues that excluding the poor from accessing and freely using the biomedical research literature is harming global public health. Health care workers, for example, are prevented from accessing the information they need to practice effective medicine, while policymakers are prevented from accessing the essential knowledge they require to build better health care systems. The author proposes that the biomedical literature should be considered a global public good, basing his arguments upon longstanding and recent international declarations that enshrine access to scientific and medical knowledge as a human right. He presents an emerging alternative publishing model, called open access, and argues that this model is a more socially responsive and equitable approach to knowledge dissemination.

Advances in Electronic-Nose Technologies Developed for Biomedical Applications

PubMed Central

Wilson, Alphus D.; Baietto, Manuela

2011-01-01

The research and development of new electronic-nose applications in the biomedical field has accelerated at a phenomenal rate over the past 25 years. Many innovative e-nose technologies have provided solutions and applications to a wide variety of complex biomedical and healthcare problems. The purposes of this review are to present a comprehensive analysis of past and recent biomedical research findings and developments of electronic-nose sensor technologies, and to identify current and future potential e-nose applications that will continue to advance the effectiveness and efficiency of biomedical treatments and healthcare services for many years. An abundance of electronic-nose applications has been developed for a variety of healthcare sectors including diagnostics, immunology, pathology, patient recovery, pharmacology, physical therapy, physiology, preventative medicine, remote healthcare, and wound and graft healing. Specific biomedical e-nose applications range from uses in biochemical testing, blood-compatibility evaluations, disease diagnoses, and drug delivery to monitoring of metabolic levels, organ dysfunctions, and patient conditions through telemedicine. This paper summarizes the major electronic-nose technologies developed for healthcare and biomedical applications since the late 1980s when electronic aroma detection technologies were first recognized to be potentially useful in providing effective solutions to problems in the healthcare industry. PMID:22346620

Biomedical Biopolymers, their Origin and Evolution in Biomedical Sciences: A Systematic Review

PubMed Central

Yadav, Harsh; Shah, Veena Gowri; Shah, Gaurav; Dhaka, Gaurav

2015-01-01

Biopolymers provide a plethora of applications in the pharmaceutical and medical applications. A material that can be used for biomedical applications like wound healing, drug delivery and tissue engineering should possess certain properties like biocompatibility, biodegradation to non-toxic products, low antigenicity, high bio-activity, processability to complicated shapes with appropriate porosity, ability to support cell growth and proliferation and appropriate mechanical properties, as well as maintaining mechanical strength. This paper reviews biodegradable biopolymers focusing on their potential in biomedical applications. Biopolymers most commonly used and most abundantly available have been described with focus on the properties relevant to biomedical importance. PMID:26501034

The Dental Solid Waste Management in Different Categories of Dental Laboratories in Abha City, Saudi Arabia

PubMed Central

Haralur, Satheesh B.; Al-Qahtani, Ali S.; Al-Qarni, Marie M.; Al-Homrany, Rami M.; Aboalkhair, Ayyob E.; Madalakote, Sujatha S.

2015-01-01

Aim: To study the awareness, attitude, practice and facilities among the different categories of dental laboratories in Abha city. Materials and Methods: A total of 80 dental technicians were surveyed in the study. The dental laboratories included in the study were teaching institute (Group I), Government Hospital (Group II), Private Dental Clinic (Group III) and Independent laboratory (Group IV). The pre-tested anonymous questionnaire was used to understand knowledge, attitude, facilities, practice and orientation regarding biomedical waste management. Results: The knowledge of biomedical waste categories, colour coding and segregation was better among Group I (55-65%) and Group II (65-75%). The lowest standard of waste disposal was practiced at Group IV (15-20%) and Group III (25-35%). The availability of disposal facilities was poor at Group IV. The continuous education on biomedical waste management lacked in all the Groups. Conclusion: The significant improvement in disposal facilities was required at Group III and Group IV laboratories. All dental technicians were in need of regular training of biomedical waste management. Clinical Significance: The dental laboratories are an integral part of dental practice. The dental laboratories are actively involved in the generation, handling and disposal of biomedical waste. Hence, it is important to assess the biomedical waste management knowledge, attitude, facilities and practice among different categories of dental laboratories. PMID:26962373

Knowledge-Based, Interactive, Custom Anatomical Scene Creation for Medical Education: The Biolucida System

PubMed Central

Warren, Wayne; Brinkley, James F.

2005-01-01

Few biomedical subjects of study are as resource-intensive to teach as gross anatomy. Medical education stands to benefit greatly from applications which deliver virtual representations of human anatomical structures. While many applications have been created to achieve this goal, their utility to the student is limited because of a lack of interactivity or customizability by expert authors. Here we describe the first version of the Biolucida system, which allows an expert anatomist author to create knowledge-based, customized, and fully interactive scenes and lessons for students of human macroscopic anatomy. Implemented in Java and VRML, Biolucida allows the sharing of these instructional 3D environments over the internet. The system simplifies the process of authoring immersive content while preserving its flexibility and expressivity. PMID:16779148

Knowledge-based, interactive, custom anatomical scene creation for medical education: the Biolucida system.

PubMed

Warren, Wayne; Brinkley, James F

2005-01-01

Few biomedical subjects of study are as resource-intensive to teach as gross anatomy. Medical education stands to benefit greatly from applications which deliver virtual representations of human anatomical structures. While many applications have been created to achieve this goal, their utility to the student is limited because of a lack of interactivity or customizability by expert authors. Here we describe the first version of the Biolucida system, which allows an expert anatomist author to create knowledge-based, customized, and fully interactive scenes and lessons for students of human macroscopic anatomy. Implemented in Java and VRML, Biolucida allows the sharing of these instructional 3D environments over the internet. The system simplifies the process of authoring immersive content while preserving its flexibility and expressivity.

Knowledge acquisition for medical diagnosis using collective intelligence.

PubMed

Hernández-Chan, G; Rodríguez-González, A; Alor-Hernández, G; Gómez-Berbís, J M; Mayer-Pujadas, M A; Posada-Gómez, R

2012-11-01

The wisdom of the crowds (WOC) is the process of taking into account the collective opinion of a group of individuals rather than a single expert to answer a question. Based on this assumption, the use of processes based on WOC techniques to collect new biomedical knowledge represents a challenging and cutting-edge trend on biomedical knowledge acquisition. The work presented in this paper shows a new schema to collect diagnosis information in Diagnosis Decision Support Systems (DDSS) based on collective intelligence and consensus methods.

Deep learning for healthcare: review, opportunities and challenges.

PubMed

Miotto, Riccardo; Wang, Fei; Wang, Shuang; Jiang, Xiaoqian; Dudley, Joel T

2017-05-06

Gaining knowledge and actionable insights from complex, high-dimensional and heterogeneous biomedical data remains a key challenge in transforming health care. Various types of data have been emerging in modern biomedical research, including electronic health records, imaging, -omics, sensor data and text, which are complex, heterogeneous, poorly annotated and generally unstructured. Traditional data mining and statistical learning approaches typically need to first perform feature engineering to obtain effective and more robust features from those data, and then build prediction or clustering models on top of them. There are lots of challenges on both steps in a scenario of complicated data and lacking of sufficient domain knowledge. The latest advances in deep learning technologies provide new effective paradigms to obtain end-to-end learning models from complex data. In this article, we review the recent literature on applying deep learning technologies to advance the health care domain. Based on the analyzed work, we suggest that deep learning approaches could be the vehicle for translating big biomedical data into improved human health. However, we also note limitations and needs for improved methods development and applications, especially in terms of ease-of-understanding for domain experts and citizen scientists. We discuss such challenges and suggest developing holistic and meaningful interpretable architectures to bridge deep learning models and human interpretability. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

A semantic-based method for extracting concept definitions from scientific publications: evaluation in the autism phenotype domain.

PubMed

Hassanpour, Saeed; O'Connor, Martin J; Das, Amar K

2013-08-12

A variety of informatics approaches have been developed that use information retrieval, NLP and text-mining techniques to identify biomedical concepts and relations within scientific publications or their sentences. These approaches have not typically addressed the challenge of extracting more complex knowledge such as biomedical definitions. In our efforts to facilitate knowledge acquisition of rule-based definitions of autism phenotypes, we have developed a novel semantic-based text-mining approach that can automatically identify such definitions within text. Using an existing knowledge base of 156 autism phenotype definitions and an annotated corpus of 26 source articles containing such definitions, we evaluated and compared the average rank of correctly identified rule definition or corresponding rule template using both our semantic-based approach and a standard term-based approach. We examined three separate scenarios: (1) the snippet of text contained a definition already in the knowledge base; (2) the snippet contained an alternative definition for a concept in the knowledge base; and (3) the snippet contained a definition not in the knowledge base. Our semantic-based approach had a higher average rank than the term-based approach for each of the three scenarios (scenario 1: 3.8 vs. 5.0; scenario 2: 2.8 vs. 4.9; and scenario 3: 4.5 vs. 6.2), with each comparison significant at the p-value of 0.05 using the Wilcoxon signed-rank test. Our work shows that leveraging existing domain knowledge in the information extraction of biomedical definitions significantly improves the correct identification of such knowledge within sentences. Our method can thus help researchers rapidly acquire knowledge about biomedical definitions that are specified and evolving within an ever-growing corpus of scientific publications.

Semantator: semantic annotator for converting biomedical text to linked data.

PubMed

Tao, Cui; Song, Dezhao; Sharma, Deepak; Chute, Christopher G

2013-10-01

More than 80% of biomedical data is embedded in plain text. The unstructured nature of these text-based documents makes it challenging to easily browse and query the data of interest in them. One approach to facilitate browsing and querying biomedical text is to convert the plain text to a linked web of data, i.e., converting data originally in free text to structured formats with defined meta-level semantics. In this paper, we introduce Semantator (Semantic Annotator), a semantic-web-based environment for annotating data of interest in biomedical documents, browsing and querying the annotated data, and interactively refining annotation results if needed. Through Semantator, information of interest can be either annotated manually or semi-automatically using plug-in information extraction tools. The annotated results will be stored in RDF and can be queried using the SPARQL query language. In addition, semantic reasoners can be directly applied to the annotated data for consistency checking and knowledge inference. Semantator has been released online and was used by the biomedical ontology community who provided positive feedbacks. Our evaluation results indicated that (1) Semantator can perform the annotation functionalities as designed; (2) Semantator can be adopted in real applications in clinical and transactional research; and (3) the annotated results using Semantator can be easily used in Semantic-web-based reasoning tools for further inference. Copyright © 2013 Elsevier Inc. All rights reserved.

Challenges facing academic research in commercializing event-detector implantable devices for an in-vivo biomedical subcutaneous device for biomedical analysis

NASA Astrophysics Data System (ADS)

Juanola-Feliu, E.; Colomer-Farrarons, J.; Miribel-Català, P.; Samitier, J.; Valls-Pasola, J.

2011-05-01

It is widely recognized that the welfare of the most advanced economies is at risk, and that the only way to tackle this situation is by controlling the knowledge economies and dealing with. To achieve this ambitious goal, we need to improve the performance of each dimension in the "knowledge triangle": education, research and innovation. Indeed, recent findings point to the importance of strategies of adding-value and marketing during R+D processes so as to bridge the gap between the laboratory and the market and so ensure the successful commercialization of new technology-based products. Moreover, in a global economy in which conventional manufacturing is dominated by developing economies, the future of industry in the most advanced economies must rely on its ability to innovate in those high-tech activities that can offer a differential added-value, rather than on improving existing technologies and products. It seems quite clear, therefore, that the combination of health (medicine) and nanotechnology in a new biomedical device is very capable of meeting these requisites. This work propose a generic CMOS Front-End Self-Powered In-Vivo Implantable Biomedical Device, based on a threeelectrode amperometric biosensor approach, capable of detecting threshold values for targeted concentrations of pathogens, ions, oxygen concentration, etc. Given the speed with which diabetes can spread, as diabetes is the fastest growing disease in the world, the nano-enabled implantable device for in-vivo biomedical analysis needs to be introduced into the global diabetes care devices market. In the case of glucose monitoring, the detection of a threshold decrease in the glucose level it is mandatory to avoid critic situations like the hypoglycemia. Although the case study reported in this paper is complex because it involves multiple organizations and sources of data, it contributes to extend experience to the best practices and models on nanotechnology applications and commercialization.

Precarious Projects: Conversions of (Biomedical) Knowledge in an East African City

PubMed Central

Prince, Ruth J.

2014-01-01

This article explores the orientations of lay people in Kenya to science—specifically to biomedical knowledge about HIV—and their struggles to convert this knowledge into meaningful futures. In Kenya, the global response to the HIV-AIDS epidemic has resulted in a highly stratified landscape of intervention. Globally-funded treatment programs and clinical trials, focusing on HIV, channel transnational resources, expertise, and knowledge into specific sites—HIV clinics, NGOs, and research stations—inscribing these spaces as ‘global’ while leaving others decidedly ‘local.’ Rolled out in the form of ‘projects,’ these interventions offer resources and opportunities for a limited time only. Based on ethnographic fieldwork in the city of Kisumu, this article follows the circulation of biomedical knowledge through such projects and its conversion in ways beyond those imagined by policy-makers, as it meets the aspirations of city-dwellers and enters into local livelihoods. Mediated by nongovernmental organizations through workshops and certificates, this knowledge is both fragmentary and ephemeral. I explore the temporal and spatial implications of such knowledge for those who seek to attach themselves to it and shape their identities and futures in relation to it. PMID:24383753

Diagnostic reasoning and underlying knowledge of students with preclinical patient contacts in PBL.

PubMed

Diemers, Agnes D; van de Wiel, Margje W J; Scherpbier, Albert J J A; Baarveld, Frank; Dolmans, Diana H J M

2015-12-01

Medical experts have access to elaborate and integrated knowledge networks consisting of biomedical and clinical knowledge. These coherent knowledge networks enable them to generate more accurate diagnoses in a shorter time. However, students' knowledge networks are less organised and students have difficulties linking theory and practice and transferring acquired knowledge. Therefore we wanted to explore the development and transfer of knowledge of third-year preclinical students on a problem-based learning (PBL) course with real patient contacts. Before and after a 10-week PBL course with real patients, third-year medical students were asked to think out loud while diagnosing four types of paper patient problems (two course cases and two transfer cases), and explain the underlying pathophysiological mechanisms of the patient features. Diagnostic accuracy and time needed to think through the cases were measured. The think-aloud protocols were transcribed verbatim and different types of knowledge were coded and quantitatively analysed. The written pathophysiological explanations were translated into networks of concepts. Both the concepts and the links between concepts in students' networks were compared to model networks. Over the course diagnostic accuracy increased, case-processing time decreased, and students used less biomedical and clinical knowledge during diagnostic reasoning. The quality of the pathophysiological explanations increased: the students used more concepts, especially more model concepts, and they used fewer wrong concepts and links. The findings differed across course and transfer cases. The effects were generally less strong for transfer cases. Students' improved diagnostic accuracy and the improved quality of their knowledge networks suggest that integration of biomedical and clinical knowledge took place during a 10-week course. The differences between course and transfer cases demonstrate that transfer is complex and time-consuming. We therefore suggest offering students many varied patient contacts with the same underlying pathophysiological mechanism and encouraging students to link biomedical and clinical knowledge. © 2015 John Wiley & Sons Ltd.

Understanding the Structure-Function Relationships of Dendrimers in Environmental and Biomedical Applications

NASA Astrophysics Data System (ADS)

Wang, Bo

We are living an era wherein nanoparticles (NPs) have been widely applied in our lives. Dendrimers are special polymeric NPs with unique physiochemical properties, which have been intensely explored for a variety of applications. Current studies on dendrimers are bottlenecked by insufficient understandings of their structure and dynamic behaviors from a molecular level. With primarily computational approaches supplemented by many other experimental technics, this dissertation aims to establish structure-function relationships of dendrimers in environmental and biomedical applications. More specifically, it thoroughly investigates the interactions between dendrimers and different biomolecules including carbon-based NPs, metal-based NPs, and proteins/peptides. Those results not only provide profound knowledge for evaluating the impacts of dendrimers on environmental and biological systems but also facilitate designing next-generation functional polymeric nanomaterials. The dissertation is organized as following. Chapter 1 provides an overview of current progresses on dendrimer studies, where methodology of Discrete Molecular Dynamics (DMD), my major research tool, is also introduced. Two directions of utilizing dendrimers will be discussed in following chapters. Chapter 2 will focus on environmental applications of dendrimers, where two back-to-back studies are presented. I will start from describing some interesting observations from experiments i.e. dendrimers dispersed model oil molecules. Then, I will reveal why surface chemistries of dendrimers lead to different remediation efficiencies by computational modelings. Finally, I will demonstrate different scenarios of dendrimer-small molecules association. Chapter 3 is centered on dendrimers in the biomedical applications including two subtopics. In the first topic, we will discuss dendrimers as surfactants that modulating the interactions between proteins and NPs. Some fundamental concepts regarding to NPs-Protein interactions such as NP-protein corona are also explained. In the following topic, I will look into amyloid protein aggregation mediated by dendrimers, which is of high expectations for combating amyloidogenic-related diseases. Chapter 4 concludes the whole dissertation. It also briefly introduces my ongoing projects and future research directions about dendrimers. This dissertation has presented a systematic study of dendrimers in environmental and biomedical applications which might provide valuable information for future dendrimer design thus benefit the nanobiotechnology.

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

Graph theory enables drug repurposing--how a mathematical model can drive the discovery of hidden mechanisms of action.

PubMed

Gramatica, Ruggero; Di Matteo, T; Giorgetti, Stefano; Barbiani, Massimo; Bevec, Dorian; Aste, Tomaso

2014-01-01

We introduce a methodology to efficiently exploit natural-language expressed biomedical knowledge for repurposing existing drugs towards diseases for which they were not initially intended. Leveraging on developments in Computational Linguistics and Graph Theory, a methodology is defined to build a graph representation of knowledge, which is automatically analysed to discover hidden relations between any drug and any disease: these relations are specific paths among the biomedical entities of the graph, representing possible Modes of Action for any given pharmacological compound. We propose a measure for the likeliness of these paths based on a stochastic process on the graph. This measure depends on the abundance of indirect paths between a peptide and a disease, rather than solely on the strength of the shortest path connecting them. We provide real-world examples, showing how the method successfully retrieves known pathophysiological Mode of Action and finds new ones by meaningfully selecting and aggregating contributions from known bio-molecular interactions. Applications of this methodology are presented, and prove the efficacy of the method for selecting drugs as treatment options for rare diseases.

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

Summary of the BioLINK SIG 2013 meeting at ISMB/ECCB 2013.

PubMed

Verspoor, Karin; Shatkay, Hagit; Hirschman, Lynette; Blaschke, Christian; Valencia, Alfonso

2015-01-15

The ISMB Special Interest Group on Linking Literature, Information and Knowledge for Biology (BioLINK) organized a one-day workshop at ISMB/ECCB 2013 in Berlin, Germany. The theme of the workshop was 'Roles for text mining in biomedical knowledge discovery and translational medicine'. This summary reviews the outcomes of the workshop. Meeting themes included concept annotation methods and applications, extraction of biological relationships and the use of text-mined data for biological data analysis. All articles are available at http://biolinksig.org/proceedings-online/. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

News of Biomedical Advances in HIV: Relationship to Treatment Optimism and Expected Risk Behavior in US MSM.

PubMed

Zimmerman, Rick S; Kirschbaum, Allison L

2018-02-01

HIV treatment optimism and the ways in which news of HIV biomedical advances in HIV is presented to the most at-risk communities interact in ways that affect risk behavior and the incidence of HIV. The goal of the current study was to understand the relationships among HIV treatment optimism, knowledge of HIV biomedical advances, and current and expected increased risk behavior as a result of reading hypothetical news stories of further advances. Most of an online-recruited sample of MSM were quite knowledgeable about current biomedical advances. After reading three hypothetical news stories, 15-24% of those not living with HIV and 26-52% of those living with HIV reported their condom use would decrease if the story they read were true. Results suggest the importance of more cautious reporting on HIV biomedical advances, and for targeting individuals with greater treatment optimism and those living with HIV via organizations where they are most likely to receive their information about HIV.

Functionalized carbon nanotubes: biomedical applications

PubMed Central

Vardharajula, Sandhya; Ali, Sk Z; Tiwari, Pooja M; Eroğlu, Erdal; Vig, Komal; Dennis, Vida A; Singh, Shree R

2012-01-01

Carbon nanotubes (CNTs) are emerging as novel nanomaterials for various biomedical applications. CNTs can be used to deliver a variety of therapeutic agents, including biomolecules, to the target disease sites. In addition, their unparalleled optical and electrical properties make them excellent candidates for bioimaging and other biomedical applications. However, the high cytotoxicity of CNTs limits their use in humans and many biological systems. The biocompatibility and low cytotoxicity of CNTs are attributed to size, dose, duration, testing systems, and surface functionalization. The functionalization of CNTs improves their solubility and biocompatibility and alters their cellular interaction pathways, resulting in much-reduced cytotoxic effects. Functionalized CNTs are promising novel materials for a variety of biomedical applications. These potential applications are particularly enhanced by their ability to penetrate biological membranes with relatively low cytotoxicity. This review is directed towards the overview of CNTs and their functionalization for biomedical applications with minimal cytotoxicity. PMID:23091380

Functionalized carbon nanotubes: biomedical applications.

PubMed

Vardharajula, Sandhya; Ali, Sk Z; Tiwari, Pooja M; Eroğlu, Erdal; Vig, Komal; Dennis, Vida A; Singh, Shree R

2012-01-01

Carbon nanotubes (CNTs) are emerging as novel nanomaterials for various biomedical applications. CNTs can be used to deliver a variety of therapeutic agents, including biomolecules, to the target disease sites. In addition, their unparalleled optical and electrical properties make them excellent candidates for bioimaging and other biomedical applications. However, the high cytotoxicity of CNTs limits their use in humans and many biological systems. The biocompatibility and low cytotoxicity of CNTs are attributed to size, dose, duration, testing systems, and surface functionalization. The functionalization of CNTs improves their solubility and biocompatibility and alters their cellular interaction pathways, resulting in much-reduced cytotoxic effects. Functionalized CNTs are promising novel materials for a variety of biomedical applications. These potential applications are particularly enhanced by their ability to penetrate biological membranes with relatively low cytotoxicity. This review is directed towards the overview of CNTs and their functionalization for biomedical applications with minimal cytotoxicity.

Knowledge representation and management: benefits and challenges of the semantic web for the fields of KRM and NLP.

PubMed

Rassinoux, A-M

2011-01-01

To summarize excellent current research in the field of knowledge representation and management (KRM). A synopsis of the articles selected for the IMIA Yearbook 2011 is provided and an attempt to highlight the current trends in the field is sketched. This last decade, with the extension of the text-based web towards a semantic-structured web, NLP techniques have experienced a renewed interest in knowledge extraction. This trend is corroborated through the five papers selected for the KRM section of the Yearbook 2011. They all depict outstanding studies that exploit NLP technologies whenever possible in order to accurately extract meaningful information from various biomedical textual sources. Bringing semantic structure to the meaningful content of textual web pages affords the user with cooperative sharing and intelligent finding of electronic data. As exemplified by the best paper selection, more and more advanced biomedical applications aim at exploiting the meaningful richness of free-text documents in order to generate semantic metadata and recently to learn and populate domain ontologies. These later are becoming a key piece as they allow portraying the semantics of the Semantic Web content. Maintaining their consistency with documents and semantic annotations that refer to them is a crucial challenge of the Semantic Web for the coming years.

Innovation strategy management survey of the Chilean biomedical industry. Assessment of windows of opportunities to reduce technological gaps.

PubMed

Bas, Tomas Gabriel; Oliu, Carolina Alejandra

2018-04-01

The convergence of different theories (ie, catch-up effect and windows of opportunities) allows for the interpretation of different "technological innovation gaps" in Chile's biomedical industry. It is common knowledge that Chile has always had an economy almost exclusively based on services, commodities, and mainly in the exploitation of natural resources with low value added. The literature confirms that countries that concentrate their economies on the knowledge, research, development, and commercialization of technology and innovation have a better and more stable growth rate in the medium and long run. The "Asian Tigers" are a good example of this. Analyzing the technological gaps that affect the Chilean biomedical industry, it is possible to find windows of opportunities to catch up. This could allow the country to take its knowledge, skills, and capabilities further, thus enabling Chile to not just depend on its unpredictable natural resources. For the first time, a quantitative diagnosis of the Chilean biomedical industry was made. This study considered the Chilean biomedical industry and its innovation and entrepreneurship environment, taking into account its productive capacities and its potential to make progress in technological innovation and, as a result, dramatically reducing technological gaps through windows of opportunities. Copyright © 2018 John Wiley & Sons, Ltd.

Science with radioactive beams: the alchemist's dream

NASA Astrophysics Data System (ADS)

Gelletly, W.

2001-05-01

Nuclear science is being transformed by a new capacity to create beams of radioactive nuclei. Until now all of our knowledge of nuclear physics and the applications which flow from it has been derived from studies of radioactive decay and nuclear reactions induced by beams of the 283 stable or long-lived nuclear species we can find on Earth. Here we describe first how beams of radioactive nuclei can be created. The present status of nuclear physics is then reviewed before potential applications to nuclear physics, nuclear astrophysics, materials science, bio-medical, and environmental studies are described.

Beyond decision making: class, community organizations, and the healthwork of people living with HIV/AIDS. Contributions from institutional ethnographic research.

PubMed

Mykhalovskiy, Eric

2008-01-01

The consolidation of antiretroviral therapy as the primary biomedical response to HIV infection in the global North has occasioned a growing interest in the health decision making of people living with HIV (PHAs). This interest is burdened by the weight of a behaviorist theoretical orientation that limits decision making to individual acts of rational choice. This article offers an alternative way to understand how PHAs come to take (or not take) biomedical treatments. Drawing on institutional ethnographic research conducted in Toronto, Canada, it explores how the "healthwork" of coming to take (or not take) treatments is organized by extended relations of biomedical knowledge. The article focuses on two aspects of the knowledge relations of coming to take pharmaceutical medications that transcend the conceptual and relational terrain of rational decision-making perspectives. First, it explores disjunctures between the everyday healthwork of poor, socially marginalized PHAs and the terms of biomedical decision making. Second, it investigates the knowledge-mediating activities of community-based organizations that help mitigate those disjunctures.

Synthesis and size classification of metal oxide nanoparticles for biomedical applications

NASA Astrophysics Data System (ADS)

Atsumi, Takashi; Jeyadevan, Balachandran; Sato, Yoshinori; Tamura, Kazuchika; Aiba, Setsuya; Tohji, Kazuyuki

2004-12-01

Magnetic nanoparticles are considered for biomedical applications, such as the medium in magnetic resonance imaging, hyperthermia, drug delivery, and for the purification or classification of DNA or virus. The performance of magnetic nanoparticles in biomedical application such as hyperthermia depends very much on the magnetic properties, size and size distribution. We briefly described the basic idea behind their use in drug delivery, magnetic separation and hyperthermia and discussed the prerequisite properties magnetic particles for biomedical applications. Finally reported the synthesis and classification scheme to prepare magnetite (Fe3O4) nanoparticles with narrow size distribution for magnetic fluid hyperthermia.

Ayurvedic college education, reifying biomedicine and the need for reflexivity.

PubMed

Bode, Maarten; Shankar, Prasan

2017-05-16

The paper analyses the experiences with government sanctioned Ayurvedic college education of 14 young Ayurvedic doctors working at the Integrative Health Centre in Bangalore, India. Unfamiliarity with Ayurvedic logic and Indian natural philosophies, lack of clinical training and the mixing-up of Ayurvedic and biomedical notions are their main complaints. The 14 young Ayurvedic doctors also missed a convincing perspective on how to integrate Ayurvedic logic, modern scientific knowledge and biomedical diagnostics. Ayurvedic state sanctioned education seems to be caught between Ayurveda's natural philosophy of health and the techno-science of biomedicine. The Ayurvedic doctors under scrutiny face the danger of becoming 'half-baked products' when they do not learn to reflect on the tension between Indian traditional knowledge and biomedical learning. The paper argues that the logic of modern science and biomedicine's claim to value-free knowledge captivates Ayurvedic education and research. This hinders Ayurveda's development as a vibrant alterity to biomedicine. What is needed is a critical social science perspective on the construction of medical knowledge and India's hierarchical medical landscape.

A Short Factography About IMIA and EFMI

PubMed Central

Hofdijk, Jacob; Weber, Patrick; Mantas, John; Mihalas, George; Masic, Izet

2014-01-01

International Medical Informatics Association (IMIA) and European Federation of Medical Informatics are scientific associations which represents Health/Medical informatics as scientific and profesional disciplines. Those associations have long tradition in spreading knowledge, experiences and strategies in organization, practical applications and education within Health, Medical and Biomedical informatics in approximately 60 countries the world. In this review we present basic facts about IMIA and EFMI.who celebrate this 50 years of their establishing as professional associations. PMID:24648623

Management and analysis of genomic functional and phenotypic controlled annotations to support biomedical investigation and practice.

PubMed

Masseroli, Marco

2007-07-01

The growing available genomic information provides new opportunities for novel research approaches and original biomedical applications that can provide effective data management and analysis support. In fact, integration and comprehensive evaluation of available controlled data can highlight information patterns leading to unveil new biomedical knowledge. Here, we describe Genome Function INtegrated Discover (GFINDer), a Web-accessible three-tier multidatabase system we developed to automatically enrich lists of user-classified genes with several functional and phenotypic controlled annotations, and to statistically evaluate them in order to identify annotation categories significantly over- or underrepresented in each considered gene class. Genomic controlled annotations from Gene Ontology (GO), KEGG, Pfam, InterPro, and Online Mendelian Inheritance in Man (OMIM) were integrated in GFINDer and several categorical tests were implemented for their analysis. A controlled vocabulary of inherited disorder phenotypes was obtained by normalizing and hierarchically structuring disease accompanying signs and symptoms from OMIM Clinical Synopsis sections. GFINDer modular architecture is well suited for further system expansion and for sustaining increasing workload. Testing results showed that GFINDer analyses can highlight gene functional and phenotypic characteristics and differences, demonstrating its value in supporting genomic biomedical approaches aiming at understanding the complex biomolecular mechanisms underlying patho-physiological phenotypes, and in helping the transfer of genomic results to medical practice.

Advances in electronic-nose technologies developed for biomedical applications

Treesearch

Dan Wilson; Manuela Baietto

2011-01-01

The research and development of new electronic-nose applications in the biomedical field has accelerated at a phenomenal rate over the past 25 years. Many innovative e-nose technologies have provided solutions and applications to a wide variety of complex biomedical and healthcare problems. The purposes of this review are to present a comprehensive analysis of past and...

Deep learning in bioinformatics.

PubMed

Min, Seonwoo; Lee, Byunghan; Yoon, Sungroh

2017-09-01

In the era of big data, transformation of biomedical big data into valuable knowledge has been one of the most important challenges in bioinformatics. Deep learning has advanced rapidly since the early 2000s and now demonstrates state-of-the-art performance in various fields. Accordingly, application of deep learning in bioinformatics to gain insight from data has been emphasized in both academia and industry. Here, we review deep learning in bioinformatics, presenting examples of current research. To provide a useful and comprehensive perspective, we categorize research both by the bioinformatics domain (i.e. omics, biomedical imaging, biomedical signal processing) and deep learning architecture (i.e. deep neural networks, convolutional neural networks, recurrent neural networks, emergent architectures) and present brief descriptions of each study. Additionally, we discuss theoretical and practical issues of deep learning in bioinformatics and suggest future research directions. We believe that this review will provide valuable insights and serve as a starting point for researchers to apply deep learning approaches in their bioinformatics studies. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Synthesis and Biomedical Applications of Poly((meth)acrylic acid) Brushes.

PubMed

Qu, Zhenyuan; Xu, Hong; Gu, Hongchen

2015-07-15

Poly((meth)acrylic acid) (P(M)AA) brushes possess a number of distinctive properties that are particularly attractive for biomedical applications. This minireview summarizes recent advances in the synthesis and biomedical applications of P(M)AA brushes and brushes containing P(M)AA segments. First, we review different surface-initiated polymerization (SIP) methods, with a focus on recent progress in the surface-initiated controlled/living radical polymerization (SI-CLRP) techniques used to generate P(M)AA brushes with a tailored structure. Next, we discuss biomolecule immobilization methods for P(M)AA brushes, including physical adsorption, covalent binding, and affinity interactions. Finally, typical biomedical applications of P(M)AA brushes are reviewed, and their performance is discussed based on their unique properties. We conclude that P(M)AA brushes are promising biomaterials, and more potential biomedical applications are expected to emerge with the further development of synthetic techniques and increased understanding of their interactions with biological systems.

Engineered magnetic core shell nanoprobes: Synthesis and applications to cancer imaging and therapeutics.

PubMed

Mandal, Samir; Chaudhuri, Keya

2016-02-26

Magnetic core shell nanoparticles are composed of a highly magnetic core material surrounded by a thin shell of desired drug, polymer or metal oxide. These magnetic core shell nanoparticles have a wide range of applications in biomedical research, more specifically in tissue imaging, drug delivery and therapeutics. The present review discusses the up-to-date knowledge on the various procedures for synthesis of magnetic core shell nanoparticles along with their applications in cancer imaging, drug delivery and hyperthermia or cancer therapeutics. Literature in this area shows that magnetic core shell nanoparticle-based imaging, drug targeting and therapy through hyperthermia can potentially be a powerful tool for the advanced diagnosis and treatment of various cancers.

"Exploring knowledge-user experiences in integrated knowledge translation: a biomedical investigation of the causes and consequences of food allergy".

PubMed

Dixon, Jenna; Elliott, Susan J; Clarke, Ann E

2016-01-01

Food allergy is a serious public health problem in Canada and other high-income countries, as it is potentially life threatening and severely impacts the quality of life for individuals and their families. Yet, many questions still remain as to its origins and determinants, and the best practices for treatment. Formed to tackle these very questions, the GET-FACTS research study centers on a novel concept in biomedical research: in order to make this science useful, knowledge creation must include meaningful interactions with knowledge-users. With this, knowledge-users are present at every stage of the research and are crucial, central and equal contributors. This study reflects on the early part of that journey from the perspective of the knowledge-users. We conducted interviews with all non-scientist members of the GET-FACTS steering committee, representing Canadian organizations that deal with patient advocacy and policy with regards to food allergy. Steering committee members had a clear sense that scientists and knowledge-users are equally responsible for putting knowledge into action and the importance of consulting and integrating knowledge-users throughout research. They also have high expectations for the GET-FACTS integrated process; that this model of doing science will create better scientists (e.g. improve communication skills) and make the scientific output more useful and relevant. Our work highlights both the unique contributions that knowledge-users can offer to knowledge creation as well as the challenges of trying to unify members from such different communities (policy/advocacy and biomedical science). There remains a real need to develop more touch points and opportunities for collaboration if true integration is to be achieved. Despite the obstacles, this model can help change the way knowledge is created in the biomedical world. ᅟ. Despite the burden of food allergic disease many questions remain as to its origins, determinants and best practices for treatment. Formed to tackle these very questions, the GET-FACTS (Genetics, Environment and Therapies: Food Allergy Clinical Tolerance Studies) research study centers around a novel concept in biomedical research: in order to make this science useful, knowledge creation must include meaningful interactions with knowledge-users, known as Integrated Knowledge Translation (IKT). In IKT, knowledge-users are present at every stage of the research and are crucial, central and equal contributors. This paper contributes to this exciting form of research by reflecting on the beginning of that journey from the perspective of the knowledge-users. Semi structured in-depth interviews were conducted in year 2 of the 5 year GET-FACTS project with all ( n  = 9) non-scientist members of the GET-FACTS steering committee, representing Canadian organizations that deal with patient advocacy and policy with regards to food allergy. Transcripts were coded and organized by themes developed both deductively and inductively. Steering committee members indicated a clear sense that scientists and knowledge-users are equally responsible for the translation of knowledge into action and the importance of consulting and integrating knowledge-users throughout research. Overall, these knowledge-users have very high expectations for the GET-FACTS IKT process; they feel that this model of doing science will create better scientists (e.g. improve communication skills) and make the resulting science more useful and relevant; indeed, they reported that this model of knowledge creation can be paradigm shifting. This study highlights both the unique contributions that knowledge-users can offer to knowledge creation as well as the challenges of trying to unify members from such different communities (policy/advocacy and biomedical science). While our steering committee has a strong conceptual grasp on IKT and vision for their contributions, execution is not without challenges. There remains a real need to develop more touch points and opportunities for collaboration if true integration is to be achieved. Despite the obstacles, the GET-FACTS IKT model represents a new approach to knowledge creation in Canadian biomedical research and can help foster a culture of openness to participant involvement.

New Challenges in Tribology: Wear Assessment Using 3D Optical Scanners

PubMed Central

Valigi, Maria Cristina; Logozzo, Silvia; Affatato, Saverio

2017-01-01

Wear is a significant mechanical and clinical problem. To acquire further knowledge on the tribological phenomena that involve freeform mechanical components or medical prostheses, wear tests are performed on biomedical and industrial materials in order to solve or reduce failures or malfunctions due to material loss. Scientific and technological advances in the field of optical scanning allow the application of innovative devices for wear measurements, leading to improvements that were unimaginable until a few years ago. It is therefore important to develop techniques, based on new instrumentations, for more accurate and reproducible measurements of wear. The aim of this work is to discuss the use of innovative 3D optical scanners and an experimental procedure to detect and evaluate wear, comparing this technique with other wear evaluation methods for industrial components and biomedical devices. PMID:28772905

New Challenges in Tribology: Wear Assessment Using 3D Optical Scanners.

PubMed

Valigi, Maria Cristina; Logozzo, Silvia; Affatato, Saverio

2017-05-18

Wear is a significant mechanical and clinical problem. To acquire further knowledge on the tribological phenomena that involve freeform mechanical components or medical prostheses, wear tests are performed on biomedical and industrial materials in order to solve or reduce failures or malfunctions due to material loss. Scientific and technological advances in the field of optical scanning allow the application of innovative devices for wear measurements, leading to improvements that were unimaginable until a few years ago. It is therefore important to develop techniques, based on new instrumentations, for more accurate and reproducible measurements of wear. The aim of this work is to discuss the use of innovative 3D optical scanners and an experimental procedure to detect and evaluate wear, comparing this technique with other wear evaluation methods for industrial components and biomedical devices.

45 CFR 46.301 - Applicability.

Code of Federal Regulations, 2012 CFR

2012-10-01

... Additional Protections Pertaining to Biomedical and Behavioral Research Involving Prisoners as Subjects § 46.301 Applicability. (a) The regulations in this subpart are applicable to all biomedical and behavioral...

45 CFR 46.301 - Applicability.

Code of Federal Regulations, 2011 CFR

2011-10-01

... Additional Protections Pertaining to Biomedical and Behavioral Research Involving Prisoners as Subjects § 46.301 Applicability. (a) The regulations in this subpart are applicable to all biomedical and behavioral...

45 CFR 46.301 - Applicability.

Code of Federal Regulations, 2014 CFR

2014-10-01

... Additional Protections Pertaining to Biomedical and Behavioral Research Involving Prisoners as Subjects § 46.301 Applicability. (a) The regulations in this subpart are applicable to all biomedical and behavioral...

45 CFR 46.301 - Applicability.

Code of Federal Regulations, 2013 CFR

2013-10-01

... Additional Protections Pertaining to Biomedical and Behavioral Research Involving Prisoners as Subjects § 46.301 Applicability. (a) The regulations in this subpart are applicable to all biomedical and behavioral...

AST commercial human space flight biomedical data collection

DOT National Transportation Integrated Search

2007-02-01

Recommendations are made for specific biomedical data, equipment, and a database that will increase the knowledge and understanding of how short duration, suborbital space flight missions with brief exposure to microgravity affects the human body. Th...

Assistance to NASA in biomedical areas of the technology utilization program

NASA Technical Reports Server (NTRS)

Culclasure, D. F.; Eckhardt, L.

1972-01-01

The applications of aerospace technology to biomedical research are reported. The medical institutions participating in the Biomedical Applications Program are listed along with the institutions currently utilizing the services of the Southwest Research Institute Biomedical Applications Team. Significant accomplishments during this period include: ultra-low bandpass amplifier for gastro-intestinal electric potentials; non-encumbering EEG electrode assembly suitable for long term sleep research; accurate cardiac telemetry system for active subjects; warning system for the deaf; tracking cane for the blind; and an improved control mechanism to expand the self-sufficiency of quadriplegics.

A common layer of interoperability for biomedical ontologies based on OWL EL.

PubMed

Hoehndorf, Robert; Dumontier, Michel; Oellrich, Anika; Wimalaratne, Sarala; Rebholz-Schuhmann, Dietrich; Schofield, Paul; Gkoutos, Georgios V

2011-04-01

Ontologies are essential in biomedical research due to their ability to semantically integrate content from different scientific databases and resources. Their application improves capabilities for querying and mining biological knowledge. An increasing number of ontologies is being developed for this purpose, and considerable effort is invested into formally defining them in order to represent their semantics explicitly. However, current biomedical ontologies do not facilitate data integration and interoperability yet, since reasoning over these ontologies is very complex and cannot be performed efficiently or is even impossible. We propose the use of less expressive subsets of ontology representation languages to enable efficient reasoning and achieve the goal of genuine interoperability between ontologies. We present and evaluate EL Vira, a framework that transforms OWL ontologies into the OWL EL subset, thereby enabling the use of tractable reasoning. We illustrate which OWL constructs and inferences are kept and lost following the conversion and demonstrate the performance gain of reasoning indicated by the significant reduction of processing time. We applied EL Vira to the open biomedical ontologies and provide a repository of ontologies resulting from this conversion. EL Vira creates a common layer of ontological interoperability that, for the first time, enables the creation of software solutions that can employ biomedical ontologies to perform inferences and answer complex queries to support scientific analyses. The EL Vira software is available from http://el-vira.googlecode.com and converted OBO ontologies and their mappings are available from http://bioonto.gen.cam.ac.uk/el-ont.

Recent development and biomedical applications of probabilistic Boolean networks

PubMed Central

2013-01-01

Probabilistic Boolean network (PBN) modelling is a semi-quantitative approach widely used for the study of the topology and dynamic aspects of biological systems. The combined use of rule-based representation and probability makes PBN appealing for large-scale modelling of biological networks where degrees of uncertainty need to be considered. A considerable expansion of our knowledge in the field of theoretical research on PBN can be observed over the past few years, with a focus on network inference, network intervention and control. With respect to areas of applications, PBN is mainly used for the study of gene regulatory networks though with an increasing emergence in signal transduction, metabolic, and also physiological networks. At the same time, a number of computational tools, facilitating the modelling and analysis of PBNs, are continuously developed. A concise yet comprehensive review of the state-of-the-art on PBN modelling is offered in this article, including a comparative discussion on PBN versus similar models with respect to concepts and biomedical applications. Due to their many advantages, we consider PBN to stand as a suitable modelling framework for the description and analysis of complex biological systems, ranging from molecular to physiological levels. PMID:23815817

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

Eating well with Canada's food guide? Authoritative knowledge about food and health among newcomer mothers.

PubMed

Anderson, L C; Mah, C L; Sellen, D W

2015-08-01

Current versions of Canada's Food Guide (CFG) aim to inform a culturally diverse population, but it is not known how intended audiences from different cultural and linguistic groups within Canada's diverse population understand and apply its messages. We analyzed data from qualitative interviews conducted with 32 newcomer mothers of children aged 1-5 years to explore how conceptions of food and health change with migration to Canada among Spanish-speaking Latin American and Tamil Speaking Sri Lankan newcomers and may influence the appropriateness and applicability of Canada's Food Guide (CFG) as a nutrition education tool. We applied Jordan's model of authoritative knowledge to identify different forms of newcomer maternal nutrition knowledge, how they influence child feeding practices, and shifts causing some forms of knowledge to be devalued in favor of others. Awareness of CFG differed between groups, with all Latin American and only half of Tamil participants familiar with it. Three distinct, overlapping ways of knowing about the relationship between food and health are identified within both groups of mothers: "natural" foods as healthy; influence of foods on illness susceptibility, and the nutritional components of food. CFG was found to be limited in its representations of recommended foods and its exclusive utilization of biomedical concepts of nutrition. Development of new, culturally competent versions of CFG that depict a variety of ethno-culturally meaningful diets and encompass both non-biomedical conceptualizations of food and health has the potential to enhance effective knowledge translation of CFG's key messages to an increasingly cosmopolitan Canadian population. Copyright © 2015 Elsevier Ltd. All rights reserved.

Southwest Research Institute assistance to NASA in biomedical areas of the technology utilization program

NASA Technical Reports Server (NTRS)

Culclasure, D. F.; Sigmon, J. L.; Carter, J. M.

1973-01-01

The activities are reported of the NASA Biomedical Applications Team at Southwest Research Institute between 25 August, 1972 and 15 November, 1973. The program background and methodology are discussed along with the technology applications, and biomedical community impacts.

A standard based approach for biomedical knowledge representation.

PubMed

Farkash, Ariel; Neuvirth, Hani; Goldschmidt, Yaara; Conti, Costanza; Rizzi, Federica; Bianchi, Stefano; Salvi, Erika; Cusi, Daniele; Shabo, Amnon

2011-01-01

The new generation of health information standards, where the syntax and semantics of the content is explicitly formalized, allows for interoperability in healthcare scenarios and analysis in clinical research settings. Studies involving clinical and genomic data include accumulating knowledge as relationships between genotypic and phenotypic information as well as associations within the genomic and clinical worlds. Some involve analysis results targeted at a specific disease; others are of a predictive nature specific to a patient and may be used by decision support applications. Representing knowledge is as important as representing data since data is more useful when coupled with relevant knowledge. Any further analysis and cross-research collaboration would benefit from persisting knowledge and data in a unified way. This paper describes a methodology used in Hypergenes, an EC FP7 project targeting Essential Hypertension, which captures data and knowledge using standards such as HL7 CDA and Clinical Genomics, aligned with the CEN EHR 13606 specification. We demonstrate the benefits of such an approach for clinical research as well as in healthcare oriented scenarios.

Biomedical applications engineering tasks

NASA Technical Reports Server (NTRS)

Laenger, C. J., Sr.

1976-01-01

The engineering tasks performed in response to needs articulated by clinicians are described. Initial contacts were made with these clinician-technology requestors by the Southwest Research Institute NASA Biomedical Applications Team. The basic purpose of the program was to effectively transfer aerospace technology into functional hardware to solve real biomedical problems.

Carbon Nanotubes in Biomedical Applications: Factors, Mechanisms, and Remedies of Toxicity.

PubMed

Alshehri, Reem; Ilyas, Asad Muhammad; Hasan, Anwarul; Arnaout, Adnan; Ahmed, Farid; Memic, Adnan

2016-09-22

Carbon nanotubes (CNTs) represent one of the most studied allotropes of carbon. The unique physicochemical properties of CNTs make them among prime candidates for numerous applications in biomedical fields including drug delivery, gene therapy, biosensors, and tissue engineering applications. However, toxicity of CNTs has been a major concern for their use in biomedical applications. In this review, we present an overview of carbon nanotubes in biomedical applications; we particularly focus on various factors and mechanisms affecting their toxicity. We have discussed various parameters including the size, length, agglomeration, and impurities of CNTs that may cause oxidative stress, which is often the main mechanism of CNTs' toxicity. Other toxic pathways are also examined, and possible ways to overcome these challenges have been discussed.

Few-Layered Black Phosphorus: From Fabrication and Customization to Biomedical Applications.

PubMed

Wang, Huaiyu; Yu, Xue-Feng

2018-02-01

As a new kind of 2D material, black phosphorus has gained increased attention in the past three years. Although few-layered black phosphorus nanosheets (BPs) degrade quickly under ambient conditions to phosphate anions, which greatly hampers their optical and electronic applications, this property also makes BPs highly biocompatible and biodegradable, and is regarded as an advantage for various biomedical applications. This Concept summarizes the state-of-art progresses of BPs, from fabrication and surface modification to biomedical applications. It is expected that BPs with such fascinating properties will encourage more scientists to engage in expanding its biomedical applications by tackling the scientific challenges involved in their development. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Enhancing biomedical text summarization using semantic relation extraction.

PubMed

Shang, Yue; Li, Yanpeng; Lin, Hongfei; Yang, Zhihao

2011-01-01

Automatic text summarization for a biomedical concept can help researchers to get the key points of a certain topic from large amount of biomedical literature efficiently. In this paper, we present a method for generating text summary for a given biomedical concept, e.g., H1N1 disease, from multiple documents based on semantic relation extraction. Our approach includes three stages: 1) We extract semantic relations in each sentence using the semantic knowledge representation tool SemRep. 2) We develop a relation-level retrieval method to select the relations most relevant to each query concept and visualize them in a graphic representation. 3) For relations in the relevant set, we extract informative sentences that can interpret them from the document collection to generate text summary using an information retrieval based method. Our major focus in this work is to investigate the contribution of semantic relation extraction to the task of biomedical text summarization. The experimental results on summarization for a set of diseases show that the introduction of semantic knowledge improves the performance and our results are better than the MEAD system, a well-known tool for text summarization.

Text mining and its potential applications in systems biology.

PubMed

Ananiadou, Sophia; Kell, Douglas B; Tsujii, Jun-ichi

2006-12-01

With biomedical literature increasing at a rate of several thousand papers per week, it is impossible to keep abreast of all developments; therefore, automated means to manage the information overload are required. Text mining techniques, which involve the processes of information retrieval, information extraction and data mining, provide a means of solving this. By adding meaning to text, these techniques produce a more structured analysis of textual knowledge than simple word searches, and can provide powerful tools for the production and analysis of systems biology models.

Strategic implementation plan

NASA Technical Reports Server (NTRS)

1989-01-01

The Life Science Division of the NASA Office of Space Science and Applications (OSSA) describes its plans for assuring the health, safety, and productivity of astronauts in space, and its plans for acquiring further fundamental scientific knowledge concerning space life sciences. This strategic implementation plan details OSSA's goals, objectives, and planned initiatives. The following areas of interest are identified: operational medicine; biomedical research; space biology; exobiology; biospheric research; controlled ecological life support; flight programs and advance technology development; the life sciences educational program; and earth benefits from space life sciences.

Twelfth International Symposium on Methodologies for Intelligent Systems (ISMIS󈧄) Held in Charlotte, North Carolina on October 11-14, 2000

DTIC Science & Technology

2000-10-14

without any knowledge of the problem area. Therefore, Darwinian-type evolutionary computation has found a very wide range of applications, including many ...the author examined many biomedical studies that included literature searches. The Science Citation Index (SCL) Abstracts of these studies...yield many records that are non-relevant to the main technical themes of the study. In summary, these types of simple limited queries can result in two

Students' self-explanations while solving unfamiliar cases: the role of biomedical knowledge.

PubMed

Chamberland, Martine; Mamede, Sílvia; St-Onge, Christina; Rivard, Marc-Antoine; Setrakian, Jean; Lévesque, Annie; Lanthier, Luc; Schmidt, Henk G; Rikers, Remy M J P

2013-11-01

General guidelines for teaching clinical reasoning have received much attention, despite a paucity of instructional approaches with demonstrated effectiveness. As suggested in a recent experimental study, self-explanation while solving clinical cases may be an effective strategy to foster reasoning in clinical clerks dealing with less familiar cases. However, the mechanisms that mediate this benefit have not been specifically investigated. The aim of this study was to explore the types of knowledge used by students when solving familiar and less familiar clinical cases with self-explanation. In a previous study, 36 third-year medical students diagnosed familiar and less familiar clinical cases either by engaging in self-explanation or not. Based on an analysis of previously collected data, the present study compared the content of self-explanation protocols generated by seven randomly selected students while solving four familiar and four less familiar cases. In total, 56 verbal protocols (28 familiar and 28 less familiar) were segmented and coded using the following categories: paraphrases, biomedical inferences, clinical inferences, monitoring statements and errors. Students provided more self-explanation segments from less familiar cases (M = 275.29) than from familiar cases (M = 248.71, p = 0.046). They provided significantly more paraphrases (p = 0.001) and made more errors (p = 0.008). A significant interaction was found between familiarity and the type of inferences (biomedical versus clinical, p = 0.016). When self-explaining less familiar cases, students provided significantly more biomedical inferences than familiar cases. Lack of familiarity with a case seems to stimulate medical students to engage in more extensive thinking during self-explanation. Less familiar cases seem to activate students' biomedical knowledge, which in turn helps them to create new links between biomedical and clinical knowledge, and eventually construct a more coherent mental representation of diseases. This may clarify the previously found positive effect that self-explanation has on the diagnosis of unfamiliar cases. © 2013 John Wiley & Sons Ltd.

Advancing translational research with the Semantic Web.

PubMed

Ruttenberg, Alan; Clark, Tim; Bug, William; Samwald, Matthias; Bodenreider, Olivier; Chen, Helen; Doherty, Donald; Forsberg, Kerstin; Gao, Yong; Kashyap, Vipul; Kinoshita, June; Luciano, Joanne; Marshall, M Scott; Ogbuji, Chimezie; Rees, Jonathan; Stephens, Susie; Wong, Gwendolyn T; Wu, Elizabeth; Zaccagnini, Davide; Hongsermeier, Tonya; Neumann, Eric; Herman, Ivan; Cheung, Kei-Hoi

2007-05-09

A fundamental goal of the U.S. National Institute of Health (NIH) "Roadmap" is to strengthen Translational Research, defined as the movement of discoveries in basic research to application at the clinical level. A significant barrier to translational research is the lack of uniformly structured data across related biomedical domains. The Semantic Web is an extension of the current Web that enables navigation and meaningful use of digital resources by automatic processes. It is based on common formats that support aggregation and integration of data drawn from diverse sources. A variety of technologies have been built on this foundation that, together, support identifying, representing, and reasoning across a wide range of biomedical data. The Semantic Web Health Care and Life Sciences Interest Group (HCLSIG), set up within the framework of the World Wide Web Consortium, was launched to explore the application of these technologies in a variety of areas. Subgroups focus on making biomedical data available in RDF, working with biomedical ontologies, prototyping clinical decision support systems, working on drug safety and efficacy communication, and supporting disease researchers navigating and annotating the large amount of potentially relevant literature. We present a scenario that shows the value of the information environment the Semantic Web can support for aiding neuroscience researchers. We then report on several projects by members of the HCLSIG, in the process illustrating the range of Semantic Web technologies that have applications in areas of biomedicine. Semantic Web technologies present both promise and challenges. Current tools and standards are already adequate to implement components of the bench-to-bedside vision. On the other hand, these technologies are young. Gaps in standards and implementations still exist and adoption is limited by typical problems with early technology, such as the need for a critical mass of practitioners and installed base, and growing pains as the technology is scaled up. Still, the potential of interoperable knowledge sources for biomedicine, at the scale of the World Wide Web, merits continued work.

Advancing translational research with the Semantic Web

PubMed Central

Ruttenberg, Alan; Clark, Tim; Bug, William; Samwald, Matthias; Bodenreider, Olivier; Chen, Helen; Doherty, Donald; Forsberg, Kerstin; Gao, Yong; Kashyap, Vipul; Kinoshita, June; Luciano, Joanne; Marshall, M Scott; Ogbuji, Chimezie; Rees, Jonathan; Stephens, Susie; Wong, Gwendolyn T; Wu, Elizabeth; Zaccagnini, Davide; Hongsermeier, Tonya; Neumann, Eric; Herman, Ivan; Cheung, Kei-Hoi

2007-01-01

Background A fundamental goal of the U.S. National Institute of Health (NIH) "Roadmap" is to strengthen Translational Research, defined as the movement of discoveries in basic research to application at the clinical level. A significant barrier to translational research is the lack of uniformly structured data across related biomedical domains. The Semantic Web is an extension of the current Web that enables navigation and meaningful use of digital resources by automatic processes. It is based on common formats that support aggregation and integration of data drawn from diverse sources. A variety of technologies have been built on this foundation that, together, support identifying, representing, and reasoning across a wide range of biomedical data. The Semantic Web Health Care and Life Sciences Interest Group (HCLSIG), set up within the framework of the World Wide Web Consortium, was launched to explore the application of these technologies in a variety of areas. Subgroups focus on making biomedical data available in RDF, working with biomedical ontologies, prototyping clinical decision support systems, working on drug safety and efficacy communication, and supporting disease researchers navigating and annotating the large amount of potentially relevant literature. Results We present a scenario that shows the value of the information environment the Semantic Web can support for aiding neuroscience researchers. We then report on several projects by members of the HCLSIG, in the process illustrating the range of Semantic Web technologies that have applications in areas of biomedicine. Conclusion Semantic Web technologies present both promise and challenges. Current tools and standards are already adequate to implement components of the bench-to-bedside vision. On the other hand, these technologies are young. Gaps in standards and implementations still exist and adoption is limited by typical problems with early technology, such as the need for a critical mass of practitioners and installed base, and growing pains as the technology is scaled up. Still, the potential of interoperable knowledge sources for biomedicine, at the scale of the World Wide Web, merits continued work. PMID:17493285

Towards an Obesity-Cancer Knowledge Base: Biomedical Entity Identification and Relation Detection

PubMed Central

Lossio-Ventura, Juan Antonio; Hogan, William; Modave, François; Hicks, Amanda; Hanna, Josh; Guo, Yi; He, Zhe; Bian, Jiang

2017-01-01

Obesity is associated with increased risks of various types of cancer, as well as a wide range of other chronic diseases. On the other hand, access to health information activates patient participation, and improve their health outcomes. However, existing online information on obesity and its relationship to cancer is heterogeneous ranging from pre-clinical models and case studies to mere hypothesis-based scientific arguments. A formal knowledge representation (i.e., a semantic knowledge base) would help better organizing and delivering quality health information related to obesity and cancer that consumers need. Nevertheless, current ontologies describing obesity, cancer and related entities are not designed to guide automatic knowledge base construction from heterogeneous information sources. Thus, in this paper, we present methods for named-entity recognition (NER) to extract biomedical entities from scholarly articles and for detecting if two biomedical entities are related, with the long term goal of building a obesity-cancer knowledge base. We leverage both linguistic and statistical approaches in the NER task, which supersedes the state-of-the-art results. Further, based on statistical features extracted from the sentences, our method for relation detection obtains an accuracy of 99.3% and a f-measure of 0.993. PMID:28503356

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.

Careers in biomedical engineering.

PubMed

Madrid, R E; Rotger, V I; Herrera, M C

2010-01-01

Although biomedical engineering was started in Argentina about 35 years ago, it has had a sustained growth for the last 25 years in human resources, with the emergence of new undergraduate and postgraduate careers, as well as in research, knowledge, technological development, and health care.

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.

Stimuli-responsive magnetic particles for biomedical applications.

PubMed

Medeiros, S F; Santos, A M; Fessi, H; Elaissari, A

2011-01-17

In recent years, magnetic nanoparticles have been studied due to their potential applications as magnetic carriers in biomedical area. These materials have been increasingly exploited as efficient delivery vectors, leading to opportunities of use as magnetic resonance imaging (MRI) agents, mediators of hyperthermia cancer treatment and in targeted therapies. Much attention has been also focused on "smart" polymers, which are able to respond to environmental changes, such as changes in the temperature and pH. In this context, this article reviews the state-of-the art in stimuli-responsive magnetic systems for biomedical applications. The paper describes different types of stimuli-sensitive systems, mainly temperature- and pH sensitive polymers, the combination of this characteristic with magnetic properties and, finally, it gives an account of their preparation methods. The article also discusses the main in vivo biomedical applications of such materials. A survey of the recent literature on various stimuli-responsive magnetic gels in biomedical applications is also included. Copyright © 2010 Elsevier B.V. All rights reserved.

Generating and Executing Complex Natural Language Queries across Linked Data.

PubMed

Hamon, Thierry; Mougin, Fleur; Grabar, Natalia

2015-01-01

With the recent and intensive research in the biomedical area, the knowledge accumulated is disseminated through various knowledge bases. Links between these knowledge bases are needed in order to use them jointly. Linked Data, SPARQL language, and interfaces in Natural Language question-answering provide interesting solutions for querying such knowledge bases. We propose a method for translating natural language questions in SPARQL queries. We use Natural Language Processing tools, semantic resources, and the RDF triples description. The method is designed on 50 questions over 3 biomedical knowledge bases, and evaluated on 27 questions. It achieves 0.78 F-measure on the test set. The method for translating natural language questions into SPARQL queries is implemented as Perl module available at http://search.cpan.org/ thhamon/RDF-NLP-SPARQLQuery.

DNA nanotechnology and its applications in biomedical research.

PubMed

Sun, Lifan; Yu, Lu; Shen, Wanqiu

2014-09-01

DNA nanotechnology, which uses DNA as a material to self-assemble designed nanostructures, including DNA 2D arrays, 3D nanostructures, DNA nanotubes and DNA nanomechanical devices, has showed great promise in biomedical applications. Various DNA nanostructures have been used for protein characterization, enzyme assembly, biosensing, drug delivery and biomimetic assemblies. In this review, we will present recent advances of DNA nanotechnology and its applications in biomedical research field.

Informatics and Technology in Resident Education.

PubMed

Niehaus, William

2017-05-01

Biomedical or clinical informatics is the transdisciplinary field that studies and develops effective uses of biomedical data, information technology innovations, and medical knowledge for scientific inquiry, problem solving, and decision making, with an emphasis on improving human health. Given the ongoing advances in information technology, the field of informatics is becoming important to clinical practice and to residency education. This article will discuss how informatics is specifically relevant to residency education and the different ways to incorporate informatics into residency education, and will highlight applications of current technology in the context of residency education. How informatics can optimize communication for residents, promote information technology use, refine documentation techniques, reduce medical errors, and improve clinical decision making will be reviewed. It is hoped that this article will increase faculty and trainees' knowledge of the field of informatics, awareness of available technology, and will assist practitioners to maximize their ability to provide quality care to their patients. This article will also introduce the idea of incorporating informatics specialists into residency programs to help practitioners deliver more evidenced-based care and to further improve their efficiency. Copyright © 2017 American Academy of Physical Medicine and Rehabilitation. Published by Elsevier Inc. All rights reserved.

Evaluating the effects of an integrated medical ethics curriculum on first-year students.

PubMed

Chin, Jacqueline J L; Voo, Teck Chuan; Karim, Syahirah Abdul; Chan, Yiong Huak; Campbell, Alastair V

2011-01-01

An integrated biomedical ethics track was implemented as part of the new medical undergraduate curriculum at the National University of Singapore Yong Loo Lin School of Medicine in academic year (AY) 2008/2009. This study analyses the effects of the new curriculum on fi rst-year students' knowledge, confidence and opinions in relation to the subject. In a cohort-based quasi-experimental study, we administered a pre-course and post-course questionnaire to a group of fi rst-year students in AY2008/2009 who underwent the new biomedical ethics curriculum. The same questionnaire was carried out with the fi rst-year cohort of AY2007/2008, who had received only ad hoc teaching in biomedical ethics. The questionnaire focused on the students' opinions on selected taught topics in biomedical ethics and law, and formal ethics education; their confidence in relation to specific clinical ethical competencies; and their knowledge of selected taught topics in the fi rst-year syllabus. The experimental cohort acquired more knowledge and confidence. They rated more positively formal ethics teaching and assessment as a requirement of medical education. Attitudes were found to have been 'professionalised' within the experimental group, with significantly greater receptiveness towards ethical codes of the profession and the regulatory role of the Singapore Medical Council. They were found to be more conservative with respect to legislative changes in healthcare. The pioneer biomedical ethics curriculum had significant effects on the ethical development of fi rst-year medical students. Longitudinal research through further phases of the integrated curriculum is needed to identify learning issues that affect the consolidation of knowledge, confidence and attitudes in medical ethics, law and professionalism.

The theory and design of piezoelectric/pyroelectric polymer film sensors for biomedical engineering applications.

PubMed

Brown, L F

1989-01-01

The unique properties of piezoelectric/pyroelectric polymers offer many new opportunities for biomedical engineering sensor applications. Since their discovery nearly 20 years ago, the polymer films have been used for many novel switching and sensor applications. Despite the prodigious exposure from many recent publications describing piezo film applications, methods of sensor fabrication and circuit interfacing still elude most engineers. This paper is presented as a tutorial guide to applying piezo polymers to biomedical engineering applications. A review of the fundamentals of piezoelectricity/pyroelectricity in piezo polymers is first presented. Their material properties are contrasted with piezoelectric ceramic materials. Some advantages and disadvantages of the films for biomedical sensors are discussed. Specific details on the fabrication of piezo film sensors are presented. Methods are described for forming, cutting, and mounting film sensors, and making lead connections. A brief discussion of equivalent circuit models for the design and simulation of piezoelectric/pyroelectric sensors is included, as well as common circuit interface techniques. Finally, several sources are recommended for further information on a variety of biomedical sensor applications.

geneCBR: a translational tool for multiple-microarray analysis and integrative information retrieval for aiding diagnosis in cancer research.

PubMed

Glez-Peña, Daniel; Díaz, Fernando; Hernández, Jesús M; Corchado, Juan M; Fdez-Riverola, Florentino

2009-06-18

Bioinformatics and medical informatics are two research fields that serve the needs of different but related communities. Both domains share the common goal of providing new algorithms, methods and technological solutions to biomedical research, and contributing to the treatment and cure of diseases. Although different microarray techniques have been successfully used to investigate useful information for cancer diagnosis at the gene expression level, the true integration of existing methods into day-to-day clinical practice is still a long way off. Within this context, case-based reasoning emerges as a suitable paradigm specially intended for the development of biomedical informatics applications and decision support systems, given the support and collaboration involved in such a translational development. With the goals of removing barriers against multi-disciplinary collaboration and facilitating the dissemination and transfer of knowledge to real practice, case-based reasoning systems have the potential to be applied to translational research mainly because their computational reasoning paradigm is similar to the way clinicians gather, analyze and process information in their own practice of clinical medicine. In addressing the issue of bridging the existing gap between biomedical researchers and clinicians who work in the domain of cancer diagnosis, prognosis and treatment, we have developed and made accessible a common interactive framework. Our geneCBR system implements a freely available software tool that allows the use of combined techniques that can be applied to gene selection, clustering, knowledge extraction and prediction for aiding diagnosis in cancer research. For biomedical researches, geneCBR expert mode offers a core workbench for designing and testing new techniques and experiments. For pathologists or oncologists, geneCBR diagnostic mode implements an effective and reliable system that can diagnose cancer subtypes based on the analysis of microarray data using a CBR architecture. For programmers, geneCBR programming mode includes an advanced edition module for run-time modification of previous coded techniques. geneCBR is a new translational tool that can effectively support the integrative work of programmers, biomedical researches and clinicians working together in a common framework. The code is freely available under the GPL license and can be obtained at http://www.genecbr.org.

Biomedical applications of aerospace technology

NASA Technical Reports Server (NTRS)

Castles, T. R.

1971-01-01

Aerospace technology transfer to biomedical research problems is discussed, including transfer innovations and potential applications. Statistical analysis of the transfer activities and impact is also presented.

Techniques of EMG signal analysis: detection, processing, classification and applications

PubMed Central

Hussain, M.S.; Mohd-Yasin, F.

2006-01-01

Electromyography (EMG) signals can be used for clinical/biomedical applications, Evolvable Hardware Chip (EHW) development, and modern human computer interaction. EMG signals acquired from muscles require advanced methods for detection, decomposition, processing, and classification. The purpose of this paper is to illustrate the various methodologies and algorithms for EMG signal analysis to provide efficient and effective ways of understanding the signal and its nature. We further point up some of the hardware implementations using EMG focusing on applications related to prosthetic hand control, grasp recognition, and human computer interaction. A comparison study is also given to show performance of various EMG signal analysis methods. This paper provides researchers a good understanding of EMG signal and its analysis procedures. This knowledge will help them develop more powerful, flexible, and efficient applications. PMID:16799694

Semantic Web meets Integrative Biology: a survey.

PubMed

Chen, Huajun; Yu, Tong; Chen, Jake Y

2013-01-01

Integrative Biology (IB) uses experimental or computational quantitative technologies to characterize biological systems at the molecular, cellular, tissue and population levels. IB typically involves the integration of the data, knowledge and capabilities across disciplinary boundaries in order to solve complex problems. We identify a series of bioinformatics problems posed by interdisciplinary integration: (i) data integration that interconnects structured data across related biomedical domains; (ii) ontology integration that brings jargons, terminologies and taxonomies from various disciplines into a unified network of ontologies; (iii) knowledge integration that integrates disparate knowledge elements from multiple sources; (iv) service integration that build applications out of services provided by different vendors. We argue that IB can benefit significantly from the integration solutions enabled by Semantic Web (SW) technologies. The SW enables scientists to share content beyond the boundaries of applications and websites, resulting into a web of data that is meaningful and understandable to any computers. In this review, we provide insight into how SW technologies can be used to build open, standardized and interoperable solutions for interdisciplinary integration on a global basis. We present a rich set of case studies in system biology, integrative neuroscience, bio-pharmaceutics and translational medicine, to highlight the technical features and benefits of SW applications in IB.

Pacific Northwest Laboratory annual report for 1987 to the DOE Office of Energy Research: Part 1, Biomedical Sciences

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

Park, J.F.

1988-02-01

This report summarizes progress on OHER biomedical and health-effects research conducted at Pacific Northwest Laboratory in FY 1987. The research develops the knowledge and scientific principles necessary to identify, understand, and anticipate the long-term health consequences of energy-related radiation and chemicals. Our continuing emphasis is to decrease the uncertainty of health-effects risk estimates from existing and/or developing energy-related technologies through an increased understanding of how radiation and chemicals cause health effects. The report is arranged to reflect PNL research relative to OHER programmatic structure. The first section, on human health effects, concerns statistical and epidemiological studies for assessing health risks.more » The next section, which contains reports of health-effects research in biological systems, includes research with radiation and chemicals. The last section is related to medical applications of nuclear technology.« less

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

PubMed

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

2016-05-01

External content sources such as MEDLINE(®), National Institutes of Health (NIH) grants and conference websites provide access to the latest breaking biomedical information, which can inform pharmaceutical and biotechnology company pipeline decisions. The value of the sites for industry, however, is limited by the use of the public internet, the limited synonyms, the rarity of batch searching capability and the disconnected nature of the sites. Fortunately, many sites now offer their content for download and we have developed an automated internal workflow that uses text mining and tailored ontologies for programmatic search and knowledge extraction. We believe such an efficient and secure approach provides a competitive advantage to companies needing access to the latest information for a range of use cases and complements manually curated commercial sources. Copyright © 2016. Published by Elsevier Ltd.

OpenDMAP: An open source, ontology-driven concept analysis engine, with applications to capturing knowledge regarding protein transport, protein interactions and cell-type-specific gene expression

PubMed Central

Hunter, Lawrence; Lu, Zhiyong; Firby, James; Baumgartner, William A; Johnson, Helen L; Ogren, Philip V; Cohen, K Bretonnel

2008-01-01

Background Information extraction (IE) efforts are widely acknowledged to be important in harnessing the rapid advance of biomedical knowledge, particularly in areas where important factual information is published in a diverse literature. Here we report on the design, implementation and several evaluations of OpenDMAP, an ontology-driven, integrated concept analysis system. It significantly advances the state of the art in information extraction by leveraging knowledge in ontological resources, integrating diverse text processing applications, and using an expanded pattern language that allows the mixing of syntactic and semantic elements and variable ordering. Results OpenDMAP information extraction systems were produced for extracting protein transport assertions (transport), protein-protein interaction assertions (interaction) and assertions that a gene is expressed in a cell type (expression). Evaluations were performed on each system, resulting in F-scores ranging from .26 – .72 (precision .39 – .85, recall .16 – .85). Additionally, each of these systems was run over all abstracts in MEDLINE, producing a total of 72,460 transport instances, 265,795 interaction instances and 176,153 expression instances. Conclusion OpenDMAP advances the performance standards for extracting protein-protein interaction predications from the full texts of biomedical research articles. Furthermore, this level of performance appears to generalize to other information extraction tasks, including extracting information about predicates of more than two arguments. The output of the information extraction system is always constructed from elements of an ontology, ensuring that the knowledge representation is grounded with respect to a carefully constructed model of reality. The results of these efforts can be used to increase the efficiency of manual curation efforts and to provide additional features in systems that integrate multiple sources for information extraction. The open source OpenDMAP code library is freely available at PMID:18237434

GRAM-CNN: a deep learning approach with local context for named entity recognition in biomedical text.

PubMed

Zhu, Qile; Li, Xiaolin; Conesa, Ana; Pereira, Cécile

2018-05-01

Best performing named entity recognition (NER) methods for biomedical literature are based on hand-crafted features or task-specific rules, which are costly to produce and difficult to generalize to other corpora. End-to-end neural networks achieve state-of-the-art performance without hand-crafted features and task-specific knowledge in non-biomedical NER tasks. However, in the biomedical domain, using the same architecture does not yield competitive performance compared with conventional machine learning models. We propose a novel end-to-end deep learning approach for biomedical NER tasks that leverages the local contexts based on n-gram character and word embeddings via Convolutional Neural Network (CNN). We call this approach GRAM-CNN. To automatically label a word, this method uses the local information around a word. Therefore, the GRAM-CNN method does not require any specific knowledge or feature engineering and can be theoretically applied to a wide range of existing NER problems. The GRAM-CNN approach was evaluated on three well-known biomedical datasets containing different BioNER entities. It obtained an F1-score of 87.26% on the Biocreative II dataset, 87.26% on the NCBI dataset and 72.57% on the JNLPBA dataset. Those results put GRAM-CNN in the lead of the biological NER methods. To the best of our knowledge, we are the first to apply CNN based structures to BioNER problems. The GRAM-CNN source code, datasets and pre-trained model are available online at: https://github.com/valdersoul/GRAM-CNN. andyli@ece.ufl.edu or aconesa@ufl.edu. Supplementary data are available at Bioinformatics online.

GRAM-CNN: a deep learning approach with local context for named entity recognition in biomedical text

PubMed Central

Zhu, Qile; Li, Xiaolin; Conesa, Ana; Pereira, Cécile

2018-01-01

Abstract Motivation Best performing named entity recognition (NER) methods for biomedical literature are based on hand-crafted features or task-specific rules, which are costly to produce and difficult to generalize to other corpora. End-to-end neural networks achieve state-of-the-art performance without hand-crafted features and task-specific knowledge in non-biomedical NER tasks. However, in the biomedical domain, using the same architecture does not yield competitive performance compared with conventional machine learning models. Results We propose a novel end-to-end deep learning approach for biomedical NER tasks that leverages the local contexts based on n-gram character and word embeddings via Convolutional Neural Network (CNN). We call this approach GRAM-CNN. To automatically label a word, this method uses the local information around a word. Therefore, the GRAM-CNN method does not require any specific knowledge or feature engineering and can be theoretically applied to a wide range of existing NER problems. The GRAM-CNN approach was evaluated on three well-known biomedical datasets containing different BioNER entities. It obtained an F1-score of 87.26% on the Biocreative II dataset, 87.26% on the NCBI dataset and 72.57% on the JNLPBA dataset. Those results put GRAM-CNN in the lead of the biological NER methods. To the best of our knowledge, we are the first to apply CNN based structures to BioNER problems. Availability and implementation The GRAM-CNN source code, datasets and pre-trained model are available online at: https://github.com/valdersoul/GRAM-CNN. Contact andyli@ece.ufl.edu or aconesa@ufl.edu Supplementary information Supplementary data are available at Bioinformatics online. PMID:29272325

Using CamiTK for rapid prototyping of interactive computer assisted medical intervention applications.

PubMed

Promayon, Emmanuel; Fouard, Céline; Bailet, Mathieu; Deram, Aurélien; Fiard, Gaëlle; Hungr, Nikolai; Luboz, Vincent; Payan, Yohan; Sarrazin, Johan; Saubat, Nicolas; Selmi, Sonia Yuki; Voros, Sandrine; Cinquin, Philippe; Troccaz, Jocelyne

2013-01-01

Computer Assisted Medical Intervention (CAMI hereafter) is a complex multi-disciplinary field. CAMI research requires the collaboration of experts in several fields as diverse as medicine, computer science, mathematics, instrumentation, signal processing, mechanics, modeling, automatics, optics, etc. CamiTK is a modular framework that helps researchers and clinicians to collaborate together in order to prototype CAMI applications by regrouping the knowledge and expertise from each discipline. It is an open-source, cross-platform generic and modular tool written in C++ which can handle medical images, surgical navigation, biomedicals simulations and robot control. This paper presents the Computer Assisted Medical Intervention ToolKit (CamiTK) and how it is used in various applications in our research team.

Preparation of Magnetic Carbon Nanotubes (Mag-CNTs) for Biomedical and Biotechnological Applications

PubMed Central

Masotti, Andrea; Caporali, Andrea

2013-01-01

Carbon nanotubes (CNTs) have been widely studied for their potential applications in many fields from nanotechnology to biomedicine. The preparation of magnetic CNTs (Mag-CNTs) opens new avenues in nanobiotechnology and biomedical applications as a consequence of their multiple properties embedded within the same moiety. Several preparation techniques have been developed during the last few years to obtain magnetic CNTs: grafting or filling nanotubes with magnetic ferrofluids or attachment of magnetic nanoparticles to CNTs or their polymeric coating. These strategies allow the generation of novel versatile systems that can be employed in many biotechnological or biomedical fields. Here, we review and discuss the most recent papers dealing with the preparation of magnetic CNTs and their application in biomedical and biotechnological fields. PMID:24351838

Preparation of magnetic carbon nanotubes (Mag-CNTs) for biomedical and biotechnological applications.

PubMed

Masotti, Andrea; Caporali, Andrea

2013-12-18

Carbon nanotubes (CNTs) have been widely studied for their potential applications in many fields from nanotechnology to biomedicine. The preparation of magnetic CNTs (Mag-CNTs) opens new avenues in nanobiotechnology and biomedical applications as a consequence of their multiple properties embedded within the same moiety. Several preparation techniques have been developed during the last few years to obtain magnetic CNTs: grafting or filling nanotubes with magnetic ferrofluids or attachment of magnetic nanoparticles to CNTs or their polymeric coating. These strategies allow the generation of novel versatile systems that can be employed in many biotechnological or biomedical fields. Here, we review and discuss the most recent papers dealing with the preparation of magnetic CNTs and their application in biomedical and biotechnological fields.

Healing and morality: a Javanese example.

PubMed

Woodward, M R

1985-01-01

Javanese traditional medicine is based on Sufi Muslim notions of personhood, knowledge and magical power. This world view motivates two conflicting modalities of medical practice: one based on the magic powers of curers (dukun), the others on the religiously validated powers of Sufi saints. The association of magical and bio-medical knowledge allows Javanese to interpret traditional and bio-medical cures as components of a unified health care system. Comparison of Javanese medical, religious and political systems suggests that the structural uniformity of cultural domains derives from the hierarchical organization of cultural knowledge and that the study of traditional medicine and medical pluralism can not be undertaken apart from that of world view.

Towards precision medicine; a new biomedical cosmology.

PubMed

Vegter, M W

2018-02-10

Precision Medicine has become a common label for data-intensive and patient-driven biomedical research. Its intended future is reflected in endeavours such as the Precision Medicine Initiative in the USA. This article addresses the question whether it is possible to discern a new 'medical cosmology' in Precision Medicine, a concept that was developed by Nicholas Jewson to describe comprehensive transformations involving various dimensions of biomedical knowledge and practice, such as vocabularies, the roles of patients and physicians and the conceptualisation of disease. Subsequently, I will elaborate my assessment of the features of Precision Medicine with the help of Michel Foucault, by exploring how precision medicine involves a transformation along three axes: the axis of biomedical knowledge, of biomedical power and of the patient as a self. Patients are encouraged to become the managers of their own health status, while the medical domain is reframed as a data-sharing community, characterised by changing power relationships between providers and patients, producers and consumers. While the emerging Precision Medicine cosmology may surpass existing knowledge frameworks; it obscures previous traditions and reduces research-subjects to mere data. This in turn, means that the individual is both subjected to the neoliberal demand to share personal information, and at the same time has acquired the positive 'right' to become a member of the data-sharing community. The subject has to constantly negotiate the meaning of his or her data, which can either enable self-expression, or function as a commanding Superego.

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.

The predictive validity of the BioMedical Admissions Test for pre-clinical examination performance.

PubMed

Emery, Joanne L; Bell, John F

2009-06-01

Some medical courses in the UK have many more applicants than places and almost all applicants have the highest possible previous and predicted examination grades. The BioMedical Admissions Test (BMAT) was designed to assist in the student selection process specifically for a number of 'traditional' medical courses with clear pre-clinical and clinical phases and a strong focus on science teaching in the early years. It is intended to supplement the information provided by examination results, interviews and personal statements. This paper reports on the predictive validity of the BMAT and its predecessor, the Medical and Veterinary Admissions Test. Results from the earliest 4 years of the test (2000-2003) were matched to the pre-clinical examination results of those accepted onto the medical course at the University of Cambridge. Correlation and logistic regression analyses were performed for each cohort. Section 2 of the test ('Scientific Knowledge') correlated more strongly with examination marks than did Section 1 ('Aptitude and Skills'). It also had a stronger relationship with the probability of achieving the highest examination class. The BMAT and its predecessor demonstrate predictive validity for the pre-clinical years of the medical course at the University of Cambridge. The test identifies important differences in skills and knowledge between candidates, not shown by their previous attainment, which predict their examination performance. It is thus a valid source of additional admissions information for medical courses with a strong scientific emphasis when previous attainment is very high.

Plasma in dentistry: a review of basic concepts and applications in dentistry.

PubMed

Kim, Jae-Hoon; Lee, Mi-Ae; Han, Geum-Jun; Cho, Byeong-Hoon

2014-01-01

Plasma-related technologies are essential in modern industries. Recently, plasma has attracted increased attention in the biomedical field. This paper provides a basic knowledge of plasma and a narrative review of plasma applications in dentistry. To review plasma applications in dentistry, an electronic search in PubMed, SCOPUS and Google scholar up to December 2012 was done. This was followed by extensive hand searching using reference lists from relevant articles. There have been attempts to apply plasma technology in various fields of dentistry including surface modifications of dental implants, adhesion, caries treatment, endodontic treatment and tooth bleaching. Although many studies were in early stages, the potential value of plasma for dental applications has been demonstrated. To enlarge the scope of plasma applications and put relevant research to practical use, interdisciplinary research with participation of dental professionals is required.

Nanoparticles for Biomedical Imaging

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

Nune, Satish K.; Gunda, Padmaja; Thallapally, Praveen K.

2009-11-01

Background: Synthetic nanoparticles are emerging as versatile tools in biomedical applications, particularly in the area of biomedical imaging. Nanoparticles 1 to 100 nm in diameter possess dimensions comparable to biological functional units. Diverse surface chemistries, unique magnetic properties, tunable absorption and emission properties, and recent advances in the synthesis and engineering of various nanoparticles suggest their potential as probes for early detection of diseases such as cancer. Surface functionalization has further expanded the potential of nanoparticles as probes for molecular imaging. Objective: To summarize emerging research of nanoparticles for biomedical imaging with increased selectivity and reduced non-specific uptake with increasedmore » spatial resolution containing stabilizers conjugated with targeting ligands. Methods: This review summarizes recent technological advances in the synthesis of various nanoparticle probes, and surveys methods to improve the targeting of nanoparticles for their applications in biomedical imaging. Conclusion: Structural design of nanomaterials for biomedical imaging continues to expand and diversify. Synthetic methods have aimed to control the size and surface characteristics of nanoparticles to control distribution, half-life and elimination. Although molecular imaging applications using nanoparticles are advancing into clinical applications, challenges such as storage stability and long-term toxicology should continue to be addressed. Keywords: nanoparticle synthesis, surface modification, targeting, molecular imaging, and biomedical imaging.« less

42 CFR 52c.1 - Applicability.

Code of Federal Regulations, 2012 CFR

2012-10-01

... PUBLIC HEALTH SERVICE, DEPARTMENT OF HEALTH AND HUMAN SERVICES GRANTS MINORITY BIOMEDICAL RESEARCH... Biomedical Research Support Program) awarded in accordance with section 301(a)(3) of the Public Health... investigators engaged in biomedical research, and to broaden the opportunities for participation in biomedical...

42 CFR 52c.1 - Applicability.

Code of Federal Regulations, 2010 CFR

2010-10-01

... PUBLIC HEALTH SERVICE, DEPARTMENT OF HEALTH AND HUMAN SERVICES GRANTS MINORITY BIOMEDICAL RESEARCH... Biomedical Research Support Program) awarded in accordance with section 301(a)(3) of the Public Health... investigators engaged in biomedical research, and to broaden the opportunities for participation in biomedical...

42 CFR 52c.1 - Applicability.

Code of Federal Regulations, 2011 CFR

2011-10-01

... PUBLIC HEALTH SERVICE, DEPARTMENT OF HEALTH AND HUMAN SERVICES GRANTS MINORITY BIOMEDICAL RESEARCH... Biomedical Research Support Program) awarded in accordance with section 301(a)(3) of the Public Health... investigators engaged in biomedical research, and to broaden the opportunities for participation in biomedical...

42 CFR 52c.1 - Applicability.

Code of Federal Regulations, 2013 CFR

2013-10-01

... PUBLIC HEALTH SERVICE, DEPARTMENT OF HEALTH AND HUMAN SERVICES GRANTS MINORITY BIOMEDICAL RESEARCH... Biomedical Research Support Program) awarded in accordance with section 301(a)(3) of the Public Health... investigators engaged in biomedical research, and to broaden the opportunities for participation in biomedical...

42 CFR 52c.1 - Applicability.

Code of Federal Regulations, 2014 CFR

2014-10-01

... PUBLIC HEALTH SERVICE, DEPARTMENT OF HEALTH AND HUMAN SERVICES GRANTS MINORITY BIOMEDICAL RESEARCH... Biomedical Research Support Program) awarded in accordance with section 301(a)(3) of the Public Health... investigators engaged in biomedical research, and to broaden the opportunities for participation in biomedical...

Characterizing semantic mappings adaptation via biomedical KOS evolution: a case study investigating SNOMED CT and ICD.

PubMed

Dos Reis, Julio Cesar; Pruski, Cédric; Da Silveira, Marcos; Reynaud-Delaître, Chantal

2013-01-01

Mappings established between Knowledge Organization Systems (KOS) increase semantic interoperability between biomedical information systems. However, biomedical knowledge is highly dynamic and changes affecting KOS entities can potentially invalidate part or the totality of existing mappings. Understanding how mappings evolve and what the impacts of KOS evolution on mappings are is therefore crucial for the definition of an automatic approach to maintain mappings valid and up-to-date over time. In this article, we study variations of a specific KOS complex change (split) for two biomedical KOS (SNOMED CT and ICD-9-CM) through a rigorous method of investigation for identifying and refining complex changes, and for selecting representative cases. We empirically analyze and explain their influence on the evolution of associated mappings. Results point out the importance of considering various dimensions of the information described in KOS, like the semantic structure of concepts, the set of relevant information used to define the mappings and the change operations interfering with this set of information.

Characterizing Semantic Mappings Adaptation via Biomedical KOS Evolution: A Case Study Investigating SNOMED CT and ICD

PubMed Central

Reis, Julio Cesar Dos; Pruski, Cédric; Da Silveira, Marcos; Reynaud-Delaître, Chantal

2013-01-01

Mappings established between Knowledge Organization Systems (KOS) increase semantic interoperability between biomedical information systems. However, biomedical knowledge is highly dynamic and changes affecting KOS entities can potentially invalidate part or the totality of existing mappings. Understanding how mappings evolve and what the impacts of KOS evolution on mappings are is therefore crucial for the definition of an automatic approach to maintain mappings valid and up-to-date over time. In this article, we study variations of a specific KOS complex change (split) for two biomedical KOS (SNOMED CT and ICD-9-CM) through a rigorous method of investigation for identifying and refining complex changes, and for selecting representative cases. We empirically analyze and explain their influence on the evolution of associated mappings. Results point out the importance of considering various dimensions of the information described in KOS, like the semantic structure of concepts, the set of relevant information used to define the mappings and the change operations interfering with this set of information. PMID:24551341

Magnetic nanoparticles as potential candidates for biomedical and biological applications.

PubMed

Zeinali Sehrig, Fatemeh; Majidi, Sima; Nikzamir, Nasrin; Nikzamir, Nasim; Nikzamir, Mohammad; Akbarzadeh, Abolfazl

2016-05-01

Magnetic iron oxide nanoparticles have become the main candidates for biomedical and biological applications, and the application of small iron oxide nanoparticles in in vitro diagnostics has been practiced for about half a century. Magnetic nanoparticles (MNPs), in combination with an external magnetic field and/or magnetizable grafts, allow the delivery of particles to the chosen target area, fix them at the local site while the medication is released, and act locally. In this review, we focus mostly on the potential use of MNPs for biomedical and biotechnological applications, and the improvements made in using these nanoparticles (NPs) in biological applications.

A scoping review of competencies for scientific editors of biomedical journals.

PubMed

Galipeau, James; Barbour, Virginia; Baskin, Patricia; Bell-Syer, Sally; Cobey, Kelly; Cumpston, Miranda; Deeks, Jon; Garner, Paul; MacLehose, Harriet; Shamseer, Larissa; Straus, Sharon; Tugwell, Peter; Wager, Elizabeth; Winker, Margaret; Moher, David

2016-02-02

Biomedical journals are the main route for disseminating the results of health-related research. Despite this, their editors operate largely without formal training or certification. To our knowledge, no body of literature systematically identifying core competencies for scientific editors of biomedical journals exists. Therefore, we aimed to conduct a scoping review to determine what is known on the competency requirements for scientific editors of biomedical journals. We searched the MEDLINE®, Cochrane Library, Embase®, CINAHL, PsycINFO, and ERIC databases (from inception to November 2014) and conducted a grey literature search for research and non-research articles with competency-related statements (i.e. competencies, knowledge, skills, behaviors, and tasks) pertaining to the role of scientific editors of peer-reviewed health-related journals. We also conducted an environmental scan, searched the results of a previous environmental scan, and searched the websites of existing networks, major biomedical journal publishers, and organizations that offer resources for editors. A total of 225 full-text publications were included, 25 of which were research articles. We extracted a total of 1,566 statements possibly related to core competencies for scientific editors of biomedical journals from these publications. We then collated overlapping or duplicate statements which produced a list of 203 unique statements. Finally, we grouped these statements into seven emergent themes: (1) dealing with authors, (2) dealing with peer reviewers, (3) journal publishing, (4) journal promotion, (5) editing, (6) ethics and integrity, and (7) qualities and characteristics of editors. To our knowledge, this scoping review is the first attempt to systematically identify possible competencies of editors. Limitations are that (1) we may not have captured all aspects of a biomedical editor's work in our searches, (2) removing redundant and overlapping items may have led to the elimination of some nuances between items, (3) restricting to certain databases, and only French and English publications, may have excluded relevant publications, and (4) some statements may not necessarily be competencies. This scoping review is the first step of a program to develop a minimum set of core competencies for scientific editors of biomedical journals which will be followed by a training needs assessment, a Delphi exercise, and a consensus meeting.

The Unified Medical Language System (UMLS): integrating biomedical terminology

PubMed Central

Bodenreider, Olivier

2004-01-01

The Unified Medical Language System (http://umlsks.nlm.nih.gov) is a repository of biomedical vocabularies developed by the US National Library of Medicine. The UMLS integrates over 2 million names for some 900 000 concepts from more than 60 families of biomedical vocabularies, as well as 12 million relations among these concepts. Vocabularies integrated in the UMLS Metathesaurus include the NCBI taxonomy, Gene Ontology, the Medical Subject Headings (MeSH), OMIM and the Digital Anatomist Symbolic Knowledge Base. UMLS concepts are not only inter-related, but may also be linked to external resources such as GenBank. In addition to data, the UMLS includes tools for customizing the Metathesaurus (MetamorphoSys), for generating lexical variants of concept names (lvg) and for extracting UMLS concepts from text (MetaMap). The UMLS knowledge sources are updated quarterly. All vocabularies are available at no fee for research purposes within an institution, but UMLS users are required to sign a license agreement. The UMLS knowledge sources are distributed on CD-ROM and by FTP. PMID:14681409

The National Institutes of Health's Big Data to Knowledge (BD2K) initiative: capitalizing on biomedical big data.

PubMed

Margolis, Ronald; Derr, Leslie; Dunn, Michelle; Huerta, Michael; Larkin, Jennie; Sheehan, Jerry; Guyer, Mark; Green, Eric D

2014-01-01

Biomedical research has and will continue to generate large amounts of data (termed 'big data') in many formats and at all levels. Consequently, there is an increasing need to better understand and mine the data to further knowledge and foster new discovery. The National Institutes of Health (NIH) has initiated a Big Data to Knowledge (BD2K) initiative to maximize the use of biomedical big data. BD2K seeks to better define how to extract value from the data, both for the individual investigator and the overall research community, create the analytic tools needed to enhance utility of the data, provide the next generation of trained personnel, and develop data science concepts and tools that can be made available to all stakeholders. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

The Unified Medical Language System (UMLS): integrating biomedical terminology.

PubMed

Bodenreider, Olivier

2004-01-01

The Unified Medical Language System (http://umlsks.nlm.nih.gov) is a repository of biomedical vocabularies developed by the US National Library of Medicine. The UMLS integrates over 2 million names for some 900,000 concepts from more than 60 families of biomedical vocabularies, as well as 12 million relations among these concepts. Vocabularies integrated in the UMLS Metathesaurus include the NCBI taxonomy, Gene Ontology, the Medical Subject Headings (MeSH), OMIM and the Digital Anatomist Symbolic Knowledge Base. UMLS concepts are not only inter-related, but may also be linked to external resources such as GenBank. In addition to data, the UMLS includes tools for customizing the Metathesaurus (MetamorphoSys), for generating lexical variants of concept names (lvg) and for extracting UMLS concepts from text (MetaMap). The UMLS knowledge sources are updated quarterly. All vocabularies are available at no fee for research purposes within an institution, but UMLS users are required to sign a license agreement. The UMLS knowledge sources are distributed on CD-ROM and by FTP.

The social origin of the illness experience--an outline of problems.

PubMed

Skrzypek, Michał

2014-01-01

The main research objective is a study of social influences on the processes of experiencing illness in the sociological meaning of the term 'illness experience' focusing attention on the subjective activity inspired by being ill, taking into account interpretive (meaning-making) activity. The goal of the analysis is to specify 'social actors' jointly creating the phenomena of 'illness' and 'being ill', taking into consideration the evolution of the position of medical sociology on this issue. BRIEF DESCRIPTION OF THE STATE OF KNOWLEDGE: The ways of experiencing illness in contemporary society, including processes of creating the meanings of the phenomena of 'illness' and 'being ill', are the outcome of not only the application of biomedical knowledge, but are also parallelly a sociocultural 'construct' in the sense that they are under the impact of social and cultural influences. In the sociology of illness experience it is pointed out that illness experience develops in connection with experiencing somatic discomfort, this process occurring in the context of influences of culture, society and socially accepted norms and values. These relationships are interpreted by the sociological, interactionist model which presents illness as a 'social construct'. Sociological studies on the social construction of 'illness' and 'being ill' construct a model of these phenomena, complementary to the biomedical model, conducive to the validation of the patient's perspective in the processes of medical treatment, and to the humanization of the naturalistically oriented, biomedical approach to illness, i.e. to adjust it more accurately to typically human needs manifesting themselves in the situation of being ill.

Biomedical applications of nano-titania in theranostics and photodynamic therapy.

PubMed

Rehman, F U; Zhao, C; Jiang, H; Wang, X

2016-01-01

Titanium dioxide (TiO2) is one of the most abundantly used nanomaterials for human life. It is used in sunscreen, photovoltaic devices, biomedical applications and as a food additive and environmental scavenger. Nano-TiO2 in biomedical applications is well documented. It is used in endoprosthetic implants and early theranostics of neoplastic and non-neoplastic maladies as a photodynamic therapeutic agent and as vehicles in nano-drug delivery systems. Herein, we focus on the recent advancements and applications of nano-TiO2 in bio-nanotechnology, nanomedicine and photodynamic therapy (PDT).

Alginate: properties and biomedical applications

PubMed Central

Lee, Kuen Yong; Mooney, David J.

2011-01-01

Alginate is a biomaterial that has found numerous applications in biomedical science and engineering due to its favorable properties, including biocompatibility and ease of gelation. Alginate hydrogels have been particularly attractive in wound healing, drug delivery, and tissue engineering applications to date, as these gels retain structural similarity to the extracellular matrices in tissues and can be manipulated to play several critical roles. This review will provide a comprehensive overview of general properties of alginate and its hydrogels, their biomedical applications, and suggest new perspectives for future studies with these polymers. PMID:22125349

Desiderata for ontologies to be used in semantic annotation of biomedical documents.

PubMed

Bada, Michael; Hunter, Lawrence

2011-02-01

A wealth of knowledge valuable to the translational research scientist is contained within the vast biomedical literature, but this knowledge is typically in the form of natural language. Sophisticated natural-language-processing systems are needed to translate text into unambiguous formal representations grounded in high-quality consensus ontologies, and these systems in turn rely on gold-standard corpora of annotated documents for training and testing. To this end, we are constructing the Colorado Richly Annotated Full-Text (CRAFT) Corpus, a collection of 97 full-text biomedical journal articles that are being manually annotated with the entire sets of terms from select vocabularies, predominantly from the Open Biomedical Ontologies (OBO) library. Our efforts in building this corpus has illuminated infelicities of these ontologies with respect to the semantic annotation of biomedical documents, and we propose desiderata whose implementation could substantially improve their utility in this task; these include the integration of overlapping terms across OBOs, the resolution of OBO-specific ambiguities, the integration of the BFO with the OBOs and the use of mid-level ontologies, the inclusion of noncanonical instances, and the expansion of relations and realizable entities. Copyright © 2010 Elsevier Inc. All rights reserved.

[Big data, medical language and biomedical terminology systems].

PubMed

Schulz, Stefan; López-García, Pablo

2015-08-01

A variety of rich terminology systems, such as thesauri, classifications, nomenclatures and ontologies support information and knowledge processing in health care and biomedical research. Nevertheless, human language, manifested as individually written texts, persists as the primary carrier of information, in the description of disease courses or treatment episodes in electronic medical records, and in the description of biomedical research in scientific publications. In the context of the discussion about big data in biomedicine, we hypothesize that the abstraction of the individuality of natural language utterances into structured and semantically normalized information facilitates the use of statistical data analytics to distil new knowledge out of textual data from biomedical research and clinical routine. Computerized human language technologies are constantly evolving and are increasingly ready to annotate narratives with codes from biomedical terminology. However, this depends heavily on linguistic and terminological resources. The creation and maintenance of such resources is labor-intensive. Nevertheless, it is sensible to assume that big data methods can be used to support this process. Examples include the learning of hierarchical relationships, the grouping of synonymous terms into concepts and the disambiguation of homonyms. Although clear evidence is still lacking, the combination of natural language technologies, semantic resources, and big data analytics is promising.

Enhancing Biomedical Text Summarization Using Semantic Relation Extraction

PubMed Central

Shang, Yue; Li, Yanpeng; Lin, Hongfei; Yang, Zhihao

2011-01-01

Automatic text summarization for a biomedical concept can help researchers to get the key points of a certain topic from large amount of biomedical literature efficiently. In this paper, we present a method for generating text summary for a given biomedical concept, e.g., H1N1 disease, from multiple documents based on semantic relation extraction. Our approach includes three stages: 1) We extract semantic relations in each sentence using the semantic knowledge representation tool SemRep. 2) We develop a relation-level retrieval method to select the relations most relevant to each query concept and visualize them in a graphic representation. 3) For relations in the relevant set, we extract informative sentences that can interpret them from the document collection to generate text summary using an information retrieval based method. Our major focus in this work is to investigate the contribution of semantic relation extraction to the task of biomedical text summarization. The experimental results on summarization for a set of diseases show that the introduction of semantic knowledge improves the performance and our results are better than the MEAD system, a well-known tool for text summarization. PMID:21887336

PATTERNS IN BIOMEDICAL DATA-HOW DO WE FIND THEM?

PubMed

Basile, Anna O; Verma, Anurag; Byrska-Bishop, Marta; Pendergrass, Sarah A; Darabos, Christian; Lester Kirchner, H

2017-01-01

Given the exponential growth of biomedical data, researchers are faced with numerous challenges in extracting and interpreting information from these large, high-dimensional, incomplete, and often noisy data. To facilitate addressing this growing concern, the "Patterns in Biomedical Data-How do we find them?" session of the 2017 Pacific Symposium on Biocomputing (PSB) is devoted to exploring pattern recognition using data-driven approaches for biomedical and precision medicine applications. The papers selected for this session focus on novel machine learning techniques as well as applications of established methods to heterogeneous data. We also feature manuscripts aimed at addressing the current challenges associated with the analysis of biomedical data.

Applicability Analysis of Validation Evidence for Biomedical Computational Models

DOE PAGES

Pathmanathan, Pras; Gray, Richard A.; Romero, Vicente J.; ...

2017-09-07

Computational modeling has the potential to revolutionize medicine the way it transformed engineering. However, despite decades of work, there has only been limited progress to successfully translate modeling research to patient care. One major difficulty which often occurs with biomedical computational models is an inability to perform validation in a setting that closely resembles how the model will be used. For example, for a biomedical model that makes in vivo clinically relevant predictions, direct validation of predictions may be impossible for ethical, technological, or financial reasons. Unavoidable limitations inherent to the validation process lead to challenges in evaluating the credibilitymore » of biomedical model predictions. Therefore, when evaluating biomedical models, it is critical to rigorously assess applicability, that is, the relevance of the computational model, and its validation evidence to the proposed context of use (COU). However, there are no well-established methods for assessing applicability. In this paper, we present a novel framework for performing applicability analysis and demonstrate its use with a medical device computational model. The framework provides a systematic, step-by-step method for breaking down the broad question of applicability into a series of focused questions, which may be addressed using supporting evidence and subject matter expertise. The framework can be used for model justification, model assessment, and validation planning. While motivated by biomedical models, it is relevant to a broad range of disciplines and underlying physics. Finally, the proposed applicability framework could help overcome some of the barriers inherent to validation of, and aid clinical implementation of, biomedical models.« less

Applicability Analysis of Validation Evidence for Biomedical Computational Models

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

Pathmanathan, Pras; Gray, Richard A.; Romero, Vicente J.

Computational modeling has the potential to revolutionize medicine the way it transformed engineering. However, despite decades of work, there has only been limited progress to successfully translate modeling research to patient care. One major difficulty which often occurs with biomedical computational models is an inability to perform validation in a setting that closely resembles how the model will be used. For example, for a biomedical model that makes in vivo clinically relevant predictions, direct validation of predictions may be impossible for ethical, technological, or financial reasons. Unavoidable limitations inherent to the validation process lead to challenges in evaluating the credibilitymore » of biomedical model predictions. Therefore, when evaluating biomedical models, it is critical to rigorously assess applicability, that is, the relevance of the computational model, and its validation evidence to the proposed context of use (COU). However, there are no well-established methods for assessing applicability. In this paper, we present a novel framework for performing applicability analysis and demonstrate its use with a medical device computational model. The framework provides a systematic, step-by-step method for breaking down the broad question of applicability into a series of focused questions, which may be addressed using supporting evidence and subject matter expertise. The framework can be used for model justification, model assessment, and validation planning. While motivated by biomedical models, it is relevant to a broad range of disciplines and underlying physics. Finally, the proposed applicability framework could help overcome some of the barriers inherent to validation of, and aid clinical implementation of, biomedical models.« less

International Conference on Bio-Medical Instrumentation and related Engineering and Physical Sciences (BIOMEP 2015)

NASA Astrophysics Data System (ADS)

2015-09-01

The International Conference on Bio-Medical Instrumentation and related Engineering and Physical Sciences (BIOMEP 2015) took place in the Technological Educational Institute (TEI) of Athens, Greece on June 18-20, 2015 and was organized by the Department of Biomedical Engineering. The scope of the conference was to provide a forum on the latest developments in Biomedical Instrumentation and related principles of Physical and Engineering sciences. Scientists and engineers from academic, industrial and health disciplines were invited to participate in the Conference and to contribute both in the promotion and dissemination of the scientific knowledge.

Biomedical Applications of Enzymes From Marine Actinobacteria.

PubMed

Kamala, K; Sivaperumal, P

Marine microbial enzyme technologies have progressed significantly in the last few decades for different applications. Among the various microorganisms, marine actinobacterial enzymes have significant active properties, which could allow them to be biocatalysts with tremendous bioactive metabolites. Moreover, marine actinobacteria have been considered as biofactories, since their enzymes fulfill biomedical and industrial needs. In this chapter, the marine actinobacteria and their enzymes' uses in biological activities and biomedical applications are described. © 2017 Elsevier Inc. All rights reserved.

A data analysis framework for biomedical big data: Application on mesoderm differentiation of human pluripotent stem cells

PubMed Central

Karlsson, Alexander; Riveiro, Maria; Améen, Caroline; Åkesson, Karolina; Andersson, Christian X.; Sartipy, Peter; Synnergren, Jane

2017-01-01

The development of high-throughput biomolecular technologies has resulted in generation of vast omics data at an unprecedented rate. This is transforming biomedical research into a big data discipline, where the main challenges relate to the analysis and interpretation of data into new biological knowledge. The aim of this study was to develop a framework for biomedical big data analytics, and apply it for analyzing transcriptomics time series data from early differentiation of human pluripotent stem cells towards the mesoderm and cardiac lineages. To this end, transcriptome profiling by microarray was performed on differentiating human pluripotent stem cells sampled at eleven consecutive days. The gene expression data was analyzed using the five-stage analysis framework proposed in this study, including data preparation, exploratory data analysis, confirmatory analysis, biological knowledge discovery, and visualization of the results. Clustering analysis revealed several distinct expression profiles during differentiation. Genes with an early transient response were strongly related to embryonic- and mesendoderm development, for example CER1 and NODAL. Pluripotency genes, such as NANOG and SOX2, exhibited substantial downregulation shortly after onset of differentiation. Rapid induction of genes related to metal ion response, cardiac tissue development, and muscle contraction were observed around day five and six. Several transcription factors were identified as potential regulators of these processes, e.g. POU1F1, TCF4 and TBP for muscle contraction genes. Pathway analysis revealed temporal activity of several signaling pathways, for example the inhibition of WNT signaling on day 2 and its reactivation on day 4. This study provides a comprehensive characterization of biological events and key regulators of the early differentiation of human pluripotent stem cells towards the mesoderm and cardiac lineages. The proposed analysis framework can be used to structure data analysis in future research, both in stem cell differentiation, and more generally, in biomedical big data analytics. PMID:28654683

A data analysis framework for biomedical big data: Application on mesoderm differentiation of human pluripotent stem cells.

PubMed

Ulfenborg, Benjamin; Karlsson, Alexander; Riveiro, Maria; Améen, Caroline; Åkesson, Karolina; Andersson, Christian X; Sartipy, Peter; Synnergren, Jane

2017-01-01

The development of high-throughput biomolecular technologies has resulted in generation of vast omics data at an unprecedented rate. This is transforming biomedical research into a big data discipline, where the main challenges relate to the analysis and interpretation of data into new biological knowledge. The aim of this study was to develop a framework for biomedical big data analytics, and apply it for analyzing transcriptomics time series data from early differentiation of human pluripotent stem cells towards the mesoderm and cardiac lineages. To this end, transcriptome profiling by microarray was performed on differentiating human pluripotent stem cells sampled at eleven consecutive days. The gene expression data was analyzed using the five-stage analysis framework proposed in this study, including data preparation, exploratory data analysis, confirmatory analysis, biological knowledge discovery, and visualization of the results. Clustering analysis revealed several distinct expression profiles during differentiation. Genes with an early transient response were strongly related to embryonic- and mesendoderm development, for example CER1 and NODAL. Pluripotency genes, such as NANOG and SOX2, exhibited substantial downregulation shortly after onset of differentiation. Rapid induction of genes related to metal ion response, cardiac tissue development, and muscle contraction were observed around day five and six. Several transcription factors were identified as potential regulators of these processes, e.g. POU1F1, TCF4 and TBP for muscle contraction genes. Pathway analysis revealed temporal activity of several signaling pathways, for example the inhibition of WNT signaling on day 2 and its reactivation on day 4. This study provides a comprehensive characterization of biological events and key regulators of the early differentiation of human pluripotent stem cells towards the mesoderm and cardiac lineages. The proposed analysis framework can be used to structure data analysis in future research, both in stem cell differentiation, and more generally, in biomedical big data analytics.

Extraction of relations between genes and diseases from text and large-scale data analysis: implications for translational research.

PubMed

Bravo, Àlex; Piñero, Janet; Queralt-Rosinach, Núria; Rautschka, Michael; Furlong, Laura I

2015-02-21

Current biomedical research needs to leverage and exploit the large amount of information reported in scientific publications. Automated text mining approaches, in particular those aimed at finding relationships between entities, are key for identification of actionable knowledge from free text repositories. We present the BeFree system aimed at identifying relationships between biomedical entities with a special focus on genes and their associated diseases. By exploiting morpho-syntactic information of the text, BeFree is able to identify gene-disease, drug-disease and drug-target associations with state-of-the-art performance. The application of BeFree to real-case scenarios shows its effectiveness in extracting information relevant for translational research. We show the value of the gene-disease associations extracted by BeFree through a number of analyses and integration with other data sources. BeFree succeeds in identifying genes associated to a major cause of morbidity worldwide, depression, which are not present in other public resources. Moreover, large-scale extraction and analysis of gene-disease associations, and integration with current biomedical knowledge, provided interesting insights on the kind of information that can be found in the literature, and raised challenges regarding data prioritization and curation. We found that only a small proportion of the gene-disease associations discovered by using BeFree is collected in expert-curated databases. Thus, there is a pressing need to find alternative strategies to manual curation, in order to review, prioritize and curate text-mining data and incorporate it into domain-specific databases. We present our strategy for data prioritization and discuss its implications for supporting biomedical research and applications. BeFree is a novel text mining system that performs competitively for the identification of gene-disease, drug-disease and drug-target associations. Our analyses show that mining only a small fraction of MEDLINE results in a large dataset of gene-disease associations, and only a small proportion of this dataset is actually recorded in curated resources (2%), raising several issues on data prioritization and curation. We propose that joint analysis of text mined data with data curated by experts appears as a suitable approach to both assess data quality and highlight novel and interesting information.

Big Data: Are Biomedical and Health Informatics Training Programs Ready?

PubMed Central

Hersh, W.; Ganesh, A. U. Jai

2014-01-01

Summary Objectives The growing volume and diversity of health and biomedical data indicate that the era of Big Data has arrived for healthcare. This has many implications for informatics, not only in terms of implementing and evaluating information systems, but also for the work and training of informatics researchers and professionals. This article addresses the question: What do biomedical and health informaticians working in analytics and Big Data need to know? Methods We hypothesize a set of skills that we hope will be discussed among academic and other informaticians. Results The set of skills includes: Programming - especially with data-oriented tools, such as SQL and statistical programming languages; Statistics - working knowledge to apply tools and techniques; Domain knowledge - depending on one’s area of work, bioscience or health care; and Communication - being able to understand needs of people and organizations, and articulate results back to them. Conclusions Biomedical and health informatics educational programs must introduce concepts of analytics, Big Data, and the underlying skills to use and apply them into their curricula. The development of new coursework should focus on those who will become experts, with training aiming to provide skills in “deep analytical talent” as well as those who need knowledge to support such individuals. PMID:25123740

Big Data: Are Biomedical and Health Informatics Training Programs Ready? Contribution of the IMIA Working Group for Health and Medical Informatics Education.

PubMed

Otero, P; Hersh, W; Jai Ganesh, A U

2014-08-15

The growing volume and diversity of health and biomedical data indicate that the era of Big Data has arrived for healthcare. This has many implications for informatics, not only in terms of implementing and evaluating information systems, but also for the work and training of informatics researchers and professionals. This article addresses the question: What do biomedical and health informaticians working in analytics and Big Data need to know? We hypothesize a set of skills that we hope will be discussed among academic and other informaticians. The set of skills includes: Programming - especially with data-oriented tools, such as SQL and statistical programming languages; Statistics - working knowledge to apply tools and techniques; Domain knowledge - depending on one's area of work, bioscience or health care; and Communication - being able to understand needs of people and organizations, and articulate results back to them. Biomedical and health informatics educational programs must introduce concepts of analytics, Big Data, and the underlying skills to use and apply them into their curricula. The development of new coursework should focus on those who will become experts, with training aiming to provide skills in "deep analytical talent" as well as those who need knowledge to support such individuals.

DyKOSMap: A framework for mapping adaptation between biomedical knowledge organization systems.

PubMed

Dos Reis, Julio Cesar; Pruski, Cédric; Da Silveira, Marcos; Reynaud-Delaître, Chantal

2015-06-01

Knowledge Organization Systems (KOS) and their associated mappings play a central role in several decision support systems. However, by virtue of knowledge evolution, KOS entities are modified over time, impacting mappings and potentially turning them invalid. This requires semi-automatic methods to maintain such semantic correspondences up-to-date at KOS evolution time. We define a complete and original framework based on formal heuristics that drives the adaptation of KOS mappings. Our approach takes into account the definition of established mappings, the evolution of KOS and the possible changes that can be applied to mappings. This study experimentally evaluates the proposed heuristics and the entire framework on realistic case studies borrowed from the biomedical domain, using official mappings between several biomedical KOSs. We demonstrate the overall performance of the approach over biomedical datasets of different characteristics and sizes. Our findings reveal the effectiveness in terms of precision, recall and F-measure of the suggested heuristics and methods defining the framework to adapt mappings affected by KOS evolution. The obtained results contribute and improve the quality of mappings over time. The proposed framework can adapt mappings largely automatically, facilitating thus the maintenance task. The implemented algorithms and tools support and minimize the work of users in charge of KOS mapping maintenance. Copyright © 2015 Elsevier Inc. All rights reserved.

Computational Modeling of Human Metabolism and Its Application to Systems Biomedicine.

PubMed

Aurich, Maike K; Thiele, Ines

2016-01-01

Modern high-throughput techniques offer immense opportunities to investigate whole-systems behavior, such as those underlying human diseases. However, the complexity of the data presents challenges in interpretation, and new avenues are needed to address the complexity of both diseases and data. Constraint-based modeling is one formalism applied in systems biology. It relies on a genome-scale reconstruction that captures extensive biochemical knowledge regarding an organism. The human genome-scale metabolic reconstruction is increasingly used to understand normal cellular and disease states because metabolism is an important factor in many human diseases. The application of human genome-scale reconstruction ranges from mere querying of the model as a knowledge base to studies that take advantage of the model's topology and, most notably, to functional predictions based on cell- and condition-specific metabolic models built based on omics data.An increasing number and diversity of biomedical questions are being addressed using constraint-based modeling and metabolic models. One of the most successful biomedical applications to date is cancer metabolism, but constraint-based modeling also holds great potential for inborn errors of metabolism or obesity. In addition, it offers great prospects for individualized approaches to diagnostics and the design of disease prevention and intervention strategies. Metabolic models support this endeavor by providing easy access to complex high-throughput datasets. Personalized metabolic models have been introduced. Finally, constraint-based modeling can be used to model whole-body metabolism, which will enable the elucidation of metabolic interactions between organs and disturbances of these interactions as either causes or consequence of metabolic diseases. This chapter introduces constraint-based modeling and describes some of its contributions to systems biomedicine.

Material Processing and Design of Biodegradable Metal Matrix Composites for Biomedical Applications.

PubMed

Yang, Jingxin; Guo, Jason L; Mikos, Antonios G; He, Chunyan; Cheng, Guang

2018-06-04

In recent years, biodegradable metallic materials have played an important role in biomedical applications. However, as typical for the metal materials, their structure, general properties, preparation technology and biocompatibility are hard to change. Furthermore, biodegradable metals are susceptible to excessive degradation and subsequent disruption of their mechanical integrity; this phenomenon limits the utility of these biomaterials. Therefore, the use of degradable metals, as the base material to prepare metal matrix composite materials, it is an excellent alternative to solve the problems above described. Biodegradable metals can thus be successfully combined with other materials to form biodegradable metallic matrix composites for biomedical applications and functions. The present article describes the processing methods currently available to design biodegradable metal matrix composites for biomedical applications and provides an overview of the current existing biodegradable metal systems. At the end, the manuscript presents and discusses the challenges and future research directions for development of biodegradable metallic matrix composites for biomedical purposes.

A robust data scaling algorithm to improve classification accuracies in biomedical data.

PubMed

Cao, Xi Hang; Stojkovic, Ivan; Obradovic, Zoran

2016-09-09

Machine learning models have been adapted in biomedical research and practice for knowledge discovery and decision support. While mainstream biomedical informatics research focuses on developing more accurate models, the importance of data preprocessing draws less attention. We propose the Generalized Logistic (GL) algorithm that scales data uniformly to an appropriate interval by learning a generalized logistic function to fit the empirical cumulative distribution function of the data. The GL algorithm is simple yet effective; it is intrinsically robust to outliers, so it is particularly suitable for diagnostic/classification models in clinical/medical applications where the number of samples is usually small; it scales the data in a nonlinear fashion, which leads to potential improvement in accuracy. To evaluate the effectiveness of the proposed algorithm, we conducted experiments on 16 binary classification tasks with different variable types and cover a wide range of applications. The resultant performance in terms of area under the receiver operation characteristic curve (AUROC) and percentage of correct classification showed that models learned using data scaled by the GL algorithm outperform the ones using data scaled by the Min-max and the Z-score algorithm, which are the most commonly used data scaling algorithms. The proposed GL algorithm is simple and effective. It is robust to outliers, so no additional denoising or outlier detection step is needed in data preprocessing. Empirical results also show models learned from data scaled by the GL algorithm have higher accuracy compared to the commonly used data scaling algorithms.

Photoreconfigurable polymers for biomedical applications: chemistry and macromolecular engineering.

PubMed

Zhu, Congcong; Ninh, Chi; Bettinger, Christopher J

2014-10-13

Stimuli-responsive polymers play an important role in many biomedical technologies. Light responsive polymers are particularly desirable because the parameters of irradiated light and diverse photoactive chemistries produce a large number of combinations between functional materials and associated stimuli. This Review summarizes recent advances in utilizing photoactive chemistries in macromolecules for prospective use in biomedical applications. Special focus is granted to selection criterion when choosing photofunctional groups. Synthetic strategies to incorporate these functionalities into polymers and networks with different topologies are also highlighted herein. Prospective applications of these materials are discussed including programmable matrices for controlled release, dynamic scaffolds for tissue engineering, and functional coatings for medical devices. The article concludes by summarizing the state of the art in photoresponsive polymers for biomedical applications including current challenges and future opportunities.

Chapter 16: text mining for translational bioinformatics.

PubMed

Cohen, K Bretonnel; Hunter, Lawrence E

2013-04-01

Text mining for translational bioinformatics is a new field with tremendous research potential. It is a subfield of biomedical natural language processing that concerns itself directly with the problem of relating basic biomedical research to clinical practice, and vice versa. Applications of text mining fall both into the category of T1 translational research-translating basic science results into new interventions-and T2 translational research, or translational research for public health. Potential use cases include better phenotyping of research subjects, and pharmacogenomic research. A variety of methods for evaluating text mining applications exist, including corpora, structured test suites, and post hoc judging. Two basic principles of linguistic structure are relevant for building text mining applications. One is that linguistic structure consists of multiple levels. The other is that every level of linguistic structure is characterized by ambiguity. There are two basic approaches to text mining: rule-based, also known as knowledge-based; and machine-learning-based, also known as statistical. Many systems are hybrids of the two approaches. Shared tasks have had a strong effect on the direction of the field. Like all translational bioinformatics software, text mining software for translational bioinformatics can be considered health-critical and should be subject to the strictest standards of quality assurance and software testing.

Calculating semantic relatedness for biomedical use in a knowledge-poor environment.

PubMed

Rybinski, Maciej; Aldana-Montes, José

2014-01-01

Computing semantic relatedness between textual labels representing biological and medical concepts is a crucial task in many automated knowledge extraction and processing applications relevant to the biomedical domain, specifically due to the huge amount of new findings being published each year. Most methods benefit from making use of highly specific resources, thus reducing their usability in many real world scenarios that differ from the original assumptions. In this paper we present a simple resource-efficient method for calculating semantic relatedness in a knowledge-poor environment. The method obtains results comparable to state-of-the-art methods, while being more generic and flexible. The solution being presented here was designed to use only a relatively generic and small document corpus and its statistics, without referring to a previously defined knowledge base, thus it does not assume a 'closed' problem. We propose a method in which computation for two input texts is based on the idea of comparing the vocabulary associated with the best-fit documents related to those texts. As keyterm extraction is a costly process, it is done in a preprocessing step on a 'per-document' basis in order to limit the on-line processing. The actual computations are executed in a compact vector space, limited by the most informative extraction results. The method has been evaluated on five direct benchmarks by calculating correlation coefficients w.r.t. average human answers. It also has been used on Gene - Disease and Disease- Disease data pairs to highlight its potential use as a data analysis tool. Apart from comparisons with reported results, some interesting features of the method have been studied, i.e. the relationship between result quality, efficiency and applicable trimming threshold for size reduction. Experimental evaluation shows that the presented method obtains results that are comparable with current state of the art methods, even surpassing them on a majority of the benchmarks. Additionally, a possible usage scenario for the method is showcased with a real-world data experiment. Our method improves flexibility of the existing methods without a notable loss of quality. It is a legitimate alternative to the costly construction of specialized knowledge-rich resources.

Development of thermal energy storage materials for biomedical applications.

PubMed

Shukla, A; Sharma, Atul; Shukla, Manjari; Chen, C R

2015-01-01

The phase change materials (PCMs) have been utilized widely for solar thermal energy storage (TES) devices. The quality of these materials to remain at a particular temperature during solid-liquid, liquid-solid phase transition can also be utilized for many biomedical applications as well and has been explored in recent past already. This study reports some novel PCMs developed by them, along with some existing PCMs, to be used for such biomedical applications. Interestingly, it was observed that the heating/cooling properties of these PCMs enhance the quality of a variety of biomedical applications with many advantages (non-electric, no risk of electric shock, easy to handle, easy to recharge thermally, long life, cheap and easily available, reusable) over existing applications. Results of the present study are quite interesting and exciting, opening a plethora of opportunities for more work on the subject, which require overlapping expertise of material scientists, biochemists and medical experts for broader social benefits.

Carbon Nanotubes Reinforced Composites for Biomedical Applications

PubMed Central

Wang, Wei; Zhu, Yuhe; Liao, Susan; Li, Jiajia

2014-01-01

This review paper reported carbon nanotubes reinforced composites for biomedical applications. Several studies have found enhancement in the mechanical properties of CNTs-based reinforced composites by the addition of CNTs. CNTs reinforced composites have been intensively investigated for many aspects of life, especially being made for biomedical applications. The review introduced fabrication of CNTs reinforced composites (CNTs reinforced metal matrix composites, CNTs reinforced polymer matrix composites, and CNTs reinforced ceramic matrix composites), their mechanical properties, cell experiments in vitro, and biocompatibility tests in vivo. PMID:24707488

Medical benefits from the NASA biomedical applications program

NASA Technical Reports Server (NTRS)

Sigmon, J. L.

1974-01-01

To achieve its goals the NASA Biomedical Applications Program performs four basic tasks: (1) identification of major medical problems which lend themselves to solution by relevant aerospace technology; (2) identification of relevant aerospace technology which can be applied to those problems; (3) application of that technology to demonstrate the feasibility as real solutions to the identified problems; and, (4) motivation of the industrial community to manufacture and market the identified solution to maximize the utilization of aerospace solutions to the biomedical community.

Polydopamine--a nature-inspired polymer coating for biomedical science.

PubMed

Lynge, Martin E; van der Westen, Rebecca; Postma, Almar; Städler, Brigitte

2011-12-01

Polymer coatings are of central importance for many biomedical applications. In the past few years, poly(dopamine) (PDA) has attracted considerable interest for various types of biomedical applications. This feature article outlines the basic chemistry and material science regarding PDA and discusses its successful application from coatings for interfacing with cells, to drug delivery and biosensing. Although many questions remain open, the primary aim of this feature article is to illustrate the advent of PDA on its way to become a popular polymer for bioengineering purposes.

Carbon nanotubes reinforced composites for biomedical applications.

PubMed

Wang, Wei; Zhu, Yuhe; Liao, Susan; Li, Jiajia

2014-01-01

This review paper reported carbon nanotubes reinforced composites for biomedical applications. Several studies have found enhancement in the mechanical properties of CNTs-based reinforced composites by the addition of CNTs. CNTs reinforced composites have been intensively investigated for many aspects of life, especially being made for biomedical applications. The review introduced fabrication of CNTs reinforced composites (CNTs reinforced metal matrix composites, CNTs reinforced polymer matrix composites, and CNTs reinforced ceramic matrix composites), their mechanical properties, cell experiments in vitro, and biocompatibility tests in vivo.

Designing Biomedical Informatics Infrastructure for Clinical and Translational Science

ERIC Educational Resources Information Center

La Paz Lillo, Ariel Isaac

2009-01-01

Clinical and Translational Science (CTS) rests largely on information flowing smoothly at multiple levels, in multiple directions, across multiple locations. Biomedical Informatics (BI) is seen as a backbone that helps to manage information flows for the translation of knowledge generated and stored in silos of basic science into bedside…

Frequency domain phase-shifted confocal microscopy (FDPCM) with array detection

NASA Astrophysics Data System (ADS)

Ge, Baoliang; Huang, Yujia; Fang, Yue; Kuang, Cuifang; Xiu, Peng; Liu, Xu

2017-09-01

We proposed a novel method to reconstruct images taken by array detected confocal microscopy without prior knowledge about its detector distribution. The proposed frequency domain phase-shifted confocal microscopy (FDPCM) shifts the image from each detection channel to its corresponding place by substituting the phase information in Fourier domain. Theoretical analysis shows that our method could approach the resolution nearly twofold of wide-field microscopy. Simulation and experiment results are also shown to verify the applicability and effectiveness of our method. Compared to Airyscan, our method holds the advantage of simplicity and convenience to be applied to array detectors with different structure, which makes FDPCM have great potential in the application of biomedical observation in the future.

Mixing formula for tissue-mimicking silicone phantoms in the near infrared

NASA Astrophysics Data System (ADS)

Böcklin, C.; Baumann, D.; Stuker, F.; Fröhlich, Jürg

2015-03-01

The knowledge of accurate optical parameters of materials is paramount in biomedical optics applications and numerical simulations of such systems. Phantom materials with variable but predefined parameters are needed to optimise these systems. An optimised integrating sphere measurement setup and reconstruction algorithm are presented in this work to determine the optical properties of silicone rubber based phantoms whose absorption and scattering properties are altered with TiO2 and carbon black particles. A mixing formula for all constituents is derived and allows to create phantoms with predefined optical properties.

Directed molecular evolution to design advanced red fluorescent proteins.

PubMed

Subach, Fedor V; Piatkevich, Kiryl D; Verkhusha, Vladislav V

2011-11-29

Fluorescent proteins have become indispensable imaging tools for biomedical research. Continuing progress in fluorescence imaging, however, requires probes with additional colors and properties optimized for emerging techniques. Here we summarize strategies for development of red-shifted fluorescent proteins. We discuss possibilities for knowledge-based rational design based on the photochemistry of fluorescent proteins and the position of the chromophore in protein structure. We consider advances in library design by mutagenesis, protein expression systems and instrumentation for high-throughput screening that should yield improved fluorescent proteins for advanced imaging applications.

Functionalized Gold Nanoparticles and Their Biomedical Applications

PubMed Central

Tiwari, Pooja M.; Vig, Komal; Dennis, Vida A.; Singh, Shree R.

2011-01-01

Metal nanoparticles are being extensively used in various biomedical applications due to their small size to volume ratio and extensive thermal stability. Gold nanoparticles (GNPs) are an obvious choice due to their amenability of synthesis and functionalization, less toxicity and ease of detection. The present review focuses on various methods of functionalization of GNPs and their applications in biomedical research. Functionalization facilitates targeted delivery of these nanoparticles to various cell types, bioimaging, gene delivery, drug delivery and other therapeutic and diagnostic applications. This review is an amalgamation of recent advances in the field of functionalization of gold nanoparticles and their potential applications in the field of medicine and biology. PMID:28348279

Recent development of antifouling polymers: structure, evaluation, and biomedical applications in nano/micro-structures.

PubMed

Liu, Lingyun; Li, Wenchen; Liu, Qingsheng

2014-01-01

Antifouling polymers have been proven to be vital to many biomedical applications such as medical implants, drug delivery, and biosensing. This review covers the major development of antifouling polymers in the last 2 decades, including the material chemistry, structural factors important to antifouling properties, and how to challenge or evaluate the antifouling performances. We then discuss the applications of antifouling polymers in nano/micro-biomedical applications in the form of nanoparticles, thin coatings for medical devices (e.g., artificial joint, catheter, wound dressing), and nano/microscale fibers. © 2014 Wiley Periodicals, Inc.

TRANSAUTOPHAGY: European network for multidisciplinary research and translation of autophagy knowledge.

PubMed

Casas, Caty; Codogno, Patrice; Pinti, Marcello; Batoko, Henri; Morán, María; Proikas-Cezanne, Tassula; Reggiori, Fulvio; Sirko, Agnieszka; Soengas, María S; Velasco, Guillermo; Lafont, Frank; Lane, Jon; Faure, Mathias; Cossarizza, Andrea

2016-01-01

A collaborative consortium, named "TRANSAUTOPHAGY," has been created among European research groups, comprising more than 150 scientists from 21 countries studying diverse branches of basic and translational autophagy. The consortium was approved in the framework of the Horizon 2020 Program in November 2015 as a COST Action of the European Union (COST means: CO-operation in Science and Technology), and will be sponsored for 4 years. TRANSAUTOPHAGY will form an interdisciplinary platform for basic and translational researchers, enterprises and stakeholders of diverse disciplines (including nanotechnology, bioinformatics, physics, chemistry, biology and various medical disciplines). TRANSAUTOPHAGY will establish 5 different thematic working groups, formulated to cooperate in research projects, share ideas, and results through workshops, meetings and short term exchanges of personnel (among other initiatives). TRANSAUTOPHAGY aims to generate breakthrough multidisciplinary knowledge about autophagy regulation, and to boost translation of this knowledge into biomedical and biotechnological applications.

TRANSAUTOPHAGY: European network for multidisciplinary research and translation of autophagy knowledge

PubMed Central

Casas, Caty; Codogno, Patrice; Pinti, Marcello; Batoko, Henri; Morán, María; Proikas-Cezanne, Tassula; Reggiori, Fulvio; Sirko, Agnieszka; Soengas, María S; Velasco, Guillermo; Lafont, Frank; Lane, Jon; Faure, Mathias; Cossarizza, Andrea

2016-01-01

abstract A collaborative consortium, named “TRANSAUTOPHAGY,” has been created among European research groups, comprising more than 150 scientists from 21 countries studying diverse branches of basic and translational autophagy. The consortium was approved in the framework of the Horizon 2020 Program in November 2015 as a COST Action of the European Union (COST means: CO-operation in Science and Technology), and will be sponsored for 4 years. TRANSAUTOPHAGY will form an interdisciplinary platform for basic and translational researchers, enterprises and stakeholders of diverse disciplines (including nanotechnology, bioinformatics, physics, chemistry, biology and various medical disciplines). TRANSAUTOPHAGY will establish 5 different thematic working groups, formulated to cooperate in research projects, share ideas, and results through workshops, meetings and short term exchanges of personnel (among other initiatives). TRANSAUTOPHAGY aims to generate breakthrough multidisciplinary knowledge about autophagy regulation, and to boost translation of this knowledge into biomedical and biotechnological applications. PMID:27046256

Carbon nanotubes: potential medical applications and safety concerns.

PubMed

Amenta, Valeria; Aschberger, Karin

2015-01-01

Carbon nanotubes (CNTs) have unique atomic structure, as well as outstanding thermal, mechanical, and electronic properties, making them extremely attractive materials for several different applications. Many research groups are focusing on biomedical applications of carbon-based nanomaterials, however the application of CNTs to the biomedical field is not developing as fast as in other areas. While CNTs-based products are already being used in textiles, polymer matrices to strengthen materials, sports articles, microelectronics, energy storage, etc., medicinal products and medical devices for in vivo application based on CNTs have not been commercialized yet. However, CNTs for biomedical application, i.e., CNTs conjugated to siRNA for cancer therapy, or CNTs for imaging of colorectal cancer and many other products may enter clinical trials in the next years. Concerns related to the toxicity of CNTs must be overcome in order to have these products commercialized in a near future. This article reviews emerging biomedical applications of CNTs, specifically for therapy. It also deals with challenges associated with possible medical applications of CNTs, such as their not fully understood toxicological profile in the human body. © 2014 Wiley Periodicals, Inc.

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

medplot: a web application for dynamic summary and analysis of longitudinal medical data based on R.

PubMed

Ahlin, Črt; Stupica, Daša; Strle, Franc; Lusa, Lara

2015-01-01

In biomedical studies the patients are often evaluated numerous times and a large number of variables are recorded at each time-point. Data entry and manipulation of longitudinal data can be performed using spreadsheet programs, which usually include some data plotting and analysis capabilities and are straightforward to use, but are not designed for the analyses of complex longitudinal data. Specialized statistical software offers more flexibility and capabilities, but first time users with biomedical background often find its use difficult. We developed medplot, an interactive web application that simplifies the exploration and analysis of longitudinal data. The application can be used to summarize, visualize and analyze data by researchers that are not familiar with statistical programs and whose knowledge of statistics is limited. The summary tools produce publication-ready tables and graphs. The analysis tools include features that are seldom available in spreadsheet software, such as correction for multiple testing, repeated measurement analyses and flexible non-linear modeling of the association of the numerical variables with the outcome. medplot is freely available and open source, it has an intuitive graphical user interface (GUI), it is accessible via the Internet and can be used within a web browser, without the need for installing and maintaining programs locally on the user's computer. This paper describes the application and gives detailed examples describing how to use the application on real data from a clinical study including patients with early Lyme borreliosis.

Current investigations into magnetic nanoparticles for biomedical applications.

PubMed

Li, Xiaoming; Wei, Jianrong; Aifantis, Katerina E; Fan, Yubo; Feng, Qingling; Cui, Fu-Zhai; Watari, Fumio

2016-05-01

It is generally recognized that nanoparticles possess unique physicochemical properties that are largely different from those of conventional materials, specifically the electromagnetic properties of magnetic nanoparticles (MNPs). These properties have attracted many researchers to launch investigations into their potential biomedical applications, which have been reviewed in this article. First, common types of MNPs were briefly introduced. Then, the biomedical applications of MNPs were reviewed in seven parts: magnetic resonance imaging (MRI), cancer therapy, the delivery of drugs and genes, bone and dental repair, tissue engineering, biosensors, and in other aspects, which indicated that MNPs possess great potentials for many kinds of biomedical applications due to their unique properties. Although lots of achievements have been obtained, there is still a lot of work to do. New synthesis techniques and methods are still needed to develop the MNPs with satisfactory biocompatibility. More effective methods need to be exploited to prepare MNPs-based composites with fine microstructures and high biomedical performances. Other promising research points include the development of more appropriate techniques of experiments both in vitro and in vivo to detect and analyze the biocompatibility and cytotoxicity of MNPs and understand the possible influencing mechanism of the two properties. More comprehensive investigations into the diagnostic and therapeutic applications of composites containing MNPs with "core-shell" structure and deeper understanding and further study into the properties of MNPs to reveal their new biomedical applications, are also described in the conclusion and perspectives part. © 2016 Wiley Periodicals, Inc.

A knowledge representation view on biomedical structure and function.

PubMed Central

Schulz, Stefan; Hahn, Udo

2002-01-01

In biomedical ontologies, structural and functional considerations are of outstanding importance, and concepts which belong to these two categories are highly interdependent. At the representational level both axes must be clearly kept separate in order to support disciplined ontology engineering. Furthermore, the biaxial organization of physical structure (both by a taxonomic and partonomic order) entails intricate patterns of inference. We here propose a layered encoding of taxonomic, partonomic and functional aspects of biomedical concepts using description logics. PMID:12463912

Book Review: Reiner Salzer and Heinz W. Siesler (Eds.): Infrared and Raman spectroscopic imaging, 2nd ed.

DOE PAGES

Moore, David Steven

2015-05-10

This second edition of "Infrared and Raman Spectroscopic Imaging" propels practitioners in that wide-ranging field, as well as other readers, to the current state of the art in a well-produced and full-color, completely revised and updated, volume. This new edition chronicles the expanded application of vibrational spectroscopic imaging from yesterday's time-consuming point-by-point buildup of a hyperspectral image cube, through the improvements afforded by the addition of focal plane arrays and line scan imaging, to methods applicable beyond the diffraction limit, instructs the reader on the improved instrumentation and image and data analysis methods, and expounds on their application to fundamentalmore » biomedical knowledge, food and agricultural surveys, materials science, process and quality control, and many others.« less

Whispering-Gallery Mode Resonators for Detecting Cancer

PubMed Central

Pongruengkiat, Weeratouch; Pechprasarn, Suejit

2017-01-01

Optical resonators are sensors well known for their high sensitivity and fast response time. These sensors have a wide range of applications, including in the biomedical fields, and cancer detection is one such promising application. Sensor diagnosis currently has many limitations, such as being expensive, highly invasive, and time-consuming. New developments are welcomed to overcome these limitations. Optical resonators have high sensitivity, which enable medical testing to detect disease in the early stage. Herein, we describe the principle of whispering-gallery mode and ring optical resonators. We also add to the knowledge of cancer biomarker diagnosis, where we discuss the application of optical resonators for specific biomarkers. Lastly, we discuss advancements in optical resonators for detecting cancer in terms of their ability to detect small amounts of cancer biomarkers. PMID:28902169

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.

Boosting production yield of biomedical peptides

NASA Technical Reports Server (NTRS)

Manatt, S. L.

1978-01-01

Nuclear magnetic resonance (NMR) technique is employed to monitor synthesis of biomedical peptides. Application of NMR technique may improve production yields of insulin, ACTH, and growth hormones, as well as other synthesized biomedical peptides.

Laser surface texturing of polymers for biomedical applications

NASA Astrophysics Data System (ADS)

Riveiro, Antonio; Maçon, Anthony L. B.; del Val, Jesus; Comesaña, Rafael; Pou, Juan

2018-02-01

Polymers are materials widely used in biomedical science because of their biocompatibility, and good mechanical properties (which, in some cases, are similar to those of human tissues); however, these materials are, in general, chemically and biologically inert. Surface characteristics, such as topography (at the macro-, micro, and nanoscale), surface chemistry, surface energy, charge or wettability are interrelated properties, and they cooperatively influence the biological performance of materials when used for biomedical applications. They regulate the biological response at the implant/tissue interface (e.g., influencing the cell adhesion, cell orientation, cell motility, etc.). Several surface processing techniques have been explored to modulate these properties for biomedical applications. Despite their potentials, these methods have limitations that prevent their applicability. In this regard, laser-based methods, in particular laser surface texturing (LST), can be an interesting alternative. Different works have showed the potentiality of this technique to control the surface properties of biomedical polymers and enhance their biological performance; however, more research is needed to obtain the desired biological response. This work provides a general overview of the basics and applications of LST for the surface modification of polymers currently used in the clinical practice (e.g. PEEK, UHMWPE, PP, etc.). The modification of roughness, wettability, and their impact on the biological response is addressed to offer new insights on the surface modification of biomedical polymers.

National Space Biomedical Research Institute

NASA Technical Reports Server (NTRS)

2003-01-01

In June 1996, NASA released a Cooperative Agreement Notice (CAN) inviting proposals to establish a National Space Biomedical Research Institute (9-CAN-96-01). This CAN stated that: The Mission of the Institute will be to lead a National effort for accomplishing the integrated, critical path, biomedical research necessary to support the long term human presence, development, and exploration of space and to enhance life on Earth by applying the resultant advances in human knowledge and technology acquired through living and working in space. The Institute will be the focal point of NASA sponsored space biomedical research. This statement has not been amended by NASA and remains the mission of the NSBRI.

Integrating Multiple On-line Knowledge Bases for Disease-Lab Test Relation Extraction.

PubMed

Zhang, Yaoyun; Soysal, Ergin; Moon, Sungrim; Wang, Jingqi; Tao, Cui; Xu, Hua

2015-01-01

A computable knowledge base containing relations between diseases and lab tests would be a great resource for many biomedical informatics applications. This paper describes our initial step towards establishing a comprehensive knowledge base of disease and lab tests relations utilizing three public on-line resources. LabTestsOnline, MedlinePlus and Wikipedia are integrated to create a freely available, computable disease-lab test knowledgebase. Disease and lab test concepts are identified using MetaMap and relations between diseases and lab tests are determined based on source-specific rules. Experimental results demonstrate a high precision for relation extraction, with Wikipedia achieving the highest precision of 87%. Combining the three sources reached a recall of 51.40%, when compared with a subset of disease-lab test relations extracted from a reference book. Moreover, we found additional disease-lab test relations from on-line resources, indicating they are complementary to existing reference books for building a comprehensive disease and lab test relation knowledge base.

The Value of Traditional Ecological Knowledge for the Environmental Health Sciences and Biomedical Research

PubMed Central

Herne, Mose; Castille, Dorothy

2017-01-01

Background: Traditional Ecological Knowledge (TEK) is a term, relatively new to Western science, that encompasses a subset of traditional knowledge maintained by Indigenous nations about the relationships between people and the natural environment. The term was first shared by tribal elders in the 1980s to help raise awareness of the importance of TEK. TEK has become a construct that Western scientists have increasingly considered for conducting culturally relevant research with Tribal nations. Objectives: The authors aim to position TEK in relation to other emerging schools of thought, that is, concepts such as the exposome, social determinants of health (SDoH), and citizen science, and to explore TEK’s relevance to environmental health research. This article provides examples of successful application of TEK principles in federally funded research when implemented with respect for the underlying cultural context and in partnership with Indigenous communities. Discussion: Rather than treating TEK as an adjunct or element to be quantified or incorporated into Western scientific studies, TEK can instead ground our understanding of the environmental, social, and biomedical determinants of health and improve our understanding of health and disease. This article provides historical and recent examples of how TEK has informed Western scientific research. Conclusions: This article provides recommendations for researchers and federal funders to ensure respect for the contributions of TEK to research and to ensure equity and self-determination for Tribal nations who participate in research. https://doi.org/10.1289/EHP858 PMID:28858824

Translational research: understanding the continuum from bench to bedside.

PubMed

Drolet, Brian C; Lorenzi, Nancy M

2011-01-01

The process of translating basic scientific discoveries to clinical applications, and ultimately to public health improvements, has emerged as an important, but difficult, objective in biomedical research. The process is best described as a "translation continuum" because various resources and actions are involved in this progression of knowledge, which advances discoveries from the bench to the bedside. The current model of this continuum focuses primarily on translational research, which is merely one component of the overall translation process. This approach is ineffective. A revised model to address the entire continuum would provide a methodology to identify and describe all translational activities (eg, implementation, adoption translational research, etc) as well their place within the continuum. This manuscript reviews and synthesizes the literature to provide an overview of the current terminology and model for translation. A modification of the existing model is proposed to create a framework called the Biomedical Research Translation Continuum, which defines the translation process and describes the progression of knowledge from laboratory to health gains. This framework clarifies translation for readers who have not followed the evolving and complicated models currently described. Authors and researchers may use the continuum to understand and describe their research better as well as the translational activities within a conceptual framework. Additionally, the framework may increase the advancement of knowledge by refining discussions of translation and allowing more precise identification of barriers to progress. Copyright © 2011 Mosby, Inc. All rights reserved.

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/ .

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.

Extracting semantically enriched events from biomedical literature

PubMed Central

2012-01-01

Background Research into event-based text mining from the biomedical literature has been growing in popularity to facilitate the development of advanced biomedical text mining systems. Such technology permits advanced search, which goes beyond document or sentence-based retrieval. However, existing event-based systems typically ignore additional information within the textual context of events that can determine, amongst other things, whether an event represents a fact, hypothesis, experimental result or analysis of results, whether it describes new or previously reported knowledge, and whether it is speculated or negated. We refer to such contextual information as meta-knowledge. The automatic recognition of such information can permit the training of systems allowing finer-grained searching of events according to the meta-knowledge that is associated with them. Results Based on a corpus of 1,000 MEDLINE abstracts, fully manually annotated with both events and associated meta-knowledge, we have constructed a machine learning-based system that automatically assigns meta-knowledge information to events. This system has been integrated into EventMine, a state-of-the-art event extraction system, in order to create a more advanced system (EventMine-MK) that not only extracts events from text automatically, but also assigns five different types of meta-knowledge to these events. The meta-knowledge assignment module of EventMine-MK performs with macro-averaged F-scores in the range of 57-87% on the BioNLP’09 Shared Task corpus. EventMine-MK has been evaluated on the BioNLP’09 Shared Task subtask of detecting negated and speculated events. Our results show that EventMine-MK can outperform other state-of-the-art systems that participated in this task. Conclusions We have constructed the first practical system that extracts both events and associated, detailed meta-knowledge information from biomedical literature. The automatically assigned meta-knowledge information can be used to refine search systems, in order to provide an extra search layer beyond entities and assertions, dealing with phenomena such as rhetorical intent, speculations, contradictions and negations. This finer grained search functionality can assist in several important tasks, e.g., database curation (by locating new experimental knowledge) and pathway enrichment (by providing information for inference). To allow easy integration into text mining systems, EventMine-MK is provided as a UIMA component that can be used in the interoperable text mining infrastructure, U-Compare. PMID:22621266

Extracting semantically enriched events from biomedical literature.

PubMed

Miwa, Makoto; Thompson, Paul; McNaught, John; Kell, Douglas B; Ananiadou, Sophia

2012-05-23

Research into event-based text mining from the biomedical literature has been growing in popularity to facilitate the development of advanced biomedical text mining systems. Such technology permits advanced search, which goes beyond document or sentence-based retrieval. However, existing event-based systems typically ignore additional information within the textual context of events that can determine, amongst other things, whether an event represents a fact, hypothesis, experimental result or analysis of results, whether it describes new or previously reported knowledge, and whether it is speculated or negated. We refer to such contextual information as meta-knowledge. The automatic recognition of such information can permit the training of systems allowing finer-grained searching of events according to the meta-knowledge that is associated with them. Based on a corpus of 1,000 MEDLINE abstracts, fully manually annotated with both events and associated meta-knowledge, we have constructed a machine learning-based system that automatically assigns meta-knowledge information to events. This system has been integrated into EventMine, a state-of-the-art event extraction system, in order to create a more advanced system (EventMine-MK) that not only extracts events from text automatically, but also assigns five different types of meta-knowledge to these events. The meta-knowledge assignment module of EventMine-MK performs with macro-averaged F-scores in the range of 57-87% on the BioNLP'09 Shared Task corpus. EventMine-MK has been evaluated on the BioNLP'09 Shared Task subtask of detecting negated and speculated events. Our results show that EventMine-MK can outperform other state-of-the-art systems that participated in this task. We have constructed the first practical system that extracts both events and associated, detailed meta-knowledge information from biomedical literature. The automatically assigned meta-knowledge information can be used to refine search systems, in order to provide an extra search layer beyond entities and assertions, dealing with phenomena such as rhetorical intent, speculations, contradictions and negations. This finer grained search functionality can assist in several important tasks, e.g., database curation (by locating new experimental knowledge) and pathway enrichment (by providing information for inference). To allow easy integration into text mining systems, EventMine-MK is provided as a UIMA component that can be used in the interoperable text mining infrastructure, U-Compare.

Knowledge and awareness regarding biomedical waste management in dental teaching institutions in India- A systematic review

PubMed Central

Kapoor, Daljit; Nirola, Ashutosh; Kapoor, Vinod

2014-01-01

Objectives: Proper handling, treatment and disposal of biomedical wastes are important elements in any health care setting. Not much attention has been paid to the management of Biomedical Waste (BMW) in recent years, in dental colleges and hospitals in India. The present systematic review was conducted to assess knowledge and awareness regarding BMW management among staff and students of dental teaching institutions in India. Material and Methods: A systematic review of relevant cross-sectional studies was conducted regarding BMW management in India in dental teaching institutions in India. Six studies were finally included in the present review after conducting both electronic and manual search like Pubmed, EMBASE etc. and after making necessary exclusions. Potential biases were addressed and relevant data was extracted by the concerned investigators. Results: Six studies were finally included in the review. Colour coding of wastes was not done by 67% of the subjects in one of the studies conducted in Haryana. Almost all the subjects agreed to the fact that exposure to hazardous health care waste can result in disease or infection in another study. According to another study reports, none of the respondents was able to list the legislative act regarding BMW when asked. Conclusions: The results of the present review showed that knowledge and awareness level of subjects was inadequate and there is considerable variation in practice and management regarding BMW. There is a great need for continuing education and training programmes to be conducted in dental teaching institutions in India. Key words:Biomedical waste, knowledge, awareness, dentists, institution. PMID:25593667

Knowledge and awareness regarding biomedical waste management in dental teaching institutions in India- A systematic review.

PubMed

Kapoor, Daljit; Nirola, Ashutosh; Kapoor, Vinod; Gambhir, Ramandeep-Singh

2014-10-01

Proper handling, treatment and disposal of biomedical wastes are important elements in any health care setting. Not much attention has been paid to the management of Biomedical Waste (BMW) in recent years, in dental colleges and hospitals in India. The present systematic review was conducted to assess knowledge and awareness regarding BMW management among staff and students of dental teaching institutions in India. A systematic review of relevant cross-sectional studies was conducted regarding BMW management in India in dental teaching institutions in India. Six studies were finally included in the present review after conducting both electronic and manual search like Pubmed, EMBASE etc. and after making necessary exclusions. Potential biases were addressed and relevant data was extracted by the concerned investigators. Six studies were finally included in the review. Colour coding of wastes was not done by 67% of the subjects in one of the studies conducted in Haryana. Almost all the subjects agreed to the fact that exposure to hazardous health care waste can result in disease or infection in another study. According to another study reports, none of the respondents was able to list the legislative act regarding BMW when asked. The results of the present review showed that knowledge and awareness level of subjects was inadequate and there is considerable variation in practice and management regarding BMW. There is a great need for continuing education and training programmes to be conducted in dental teaching institutions in India. Key words:Biomedical waste, knowledge, awareness, dentists, institution.

Foundations for Gerontological Education.

ERIC Educational Resources Information Center

Johnson, Harold R.; And Others

1980-01-01

Focuses on: (1) components of a basic core of knowledge essential for all people working in the field of aging; (2) knowledge essential for professions related to biomedical science, human services, social and physical environment; and (3) knowledge essential for clinical psychology, nursing, nutrition, and social work. (Author)

A special issue on reviews in biomedical applications of nanomaterials, tissue engineering, stem cells, bioimaging, and toxicity.

PubMed

Nalwa, Hari Singh

2014-10-01

This second special issue of the Journal of Biomedical Nanotechnology in a series contains another 30 state-of-the-art reviews focused on the biomedical applications of nanomaterials, biosensors, bone tissue engineering, MRI and bioimaging, single-cell detection, stem cells, endothelial progenitor cells, toxicity and biosafety of nanodrugs, nanoparticle-based new therapeutic approaches for cancer, hepatic and cardiovascular disease.

Optical Tecnology Developments in Biomedicine: History, Current and Future

PubMed Central

Nioka, Shoko; Chen, Yu

2011-01-01

Biomedical optics is a rapidly emerging field for medical imaging and diagnostics. This paper reviews several biomedical optical technologies that have been developed and translated for either clinical or pre-clinical applications. Specifically, we focus on the following technologies: 1) near-infrared spectroscopy and tomography, 2) optical coherence tomography, 3) fluorescence spectroscopy and imaging, and 4) optical molecular imaging. There representative biomedical applications are also discussed here. PMID:23905030

Outcome of a Workshop on Applications of Protein Models in Biomedical Research

PubMed Central

Schwede, Torsten; Sali, Andrej; Honig, Barry; Levitt, Michael; Berman, Helen M.; Jones, David; Brenner, Steven E.; Burley, Stephen K.; Das, Rhiju; Dokholyan, Nikolay V.; Dunbrack, Roland L.; Fidelis, Krzysztof; Fiser, Andras; Godzik, Adam; Huang, Yuanpeng Janet; Humblet, Christine; Jacobson, Matthew P.; Joachimiak, Andrzej; Krystek, Stanley R.; Kortemme, Tanja; Kryshtafovych, Andriy; Montelione, Gaetano T.; Moult, John; Murray, Diana; Sanchez, Roberto; Sosnick, Tobin R.; Standley, Daron M.; Stouch, Terry; Vajda, Sandor; Vasquez, Max; Westbrook, John D.; Wilson, Ian A.

2009-01-01

Summary We describe the proceedings and conclusions from a “Workshop on Applications of Protein Models in Biomedical Research” that was held at University of California at San Francisco on 11 and 12 July, 2008. At the workshop, international scientists involved with structure modeling explored (i) how models are currently used in biomedical research, (ii) what the requirements and challenges for different applications are, and (iii) how the interaction between the computational and experimental research communities could be strengthened to advance the field. PMID:19217386

A review of engineered zirconia surfaces in biomedical applications

PubMed Central

Yin, Ling; Nakanishi, Yoshitaka; Alao, Abdur-Rasheed; Song, Xiao-Fei; Abduo, Jaafar; Zhang, Yu

2017-01-01

Zirconia is widely used for load-bearing functional structures in medicine and dentistry. The quality of engineered zirconia surfaces determines not only the fracture and fatigue behaviour but also the low temperature degradation (ageing sensitivity), bacterial colonization and bonding strength of zirconia devices. This paper reviews the current manufacturing techniques for fabrication of zirconia surfaces in biomedical applications, particularly, in tooth and joint replacements, and influences of the zirconia surface quality on their functional behaviours. It discusses emerging manufacturing techniques and challenges for fabrication of zirconia surfaces in biomedical applications. PMID:29130030

Synthesis and Biomedical Applications of Copper Sulfide Nanoparticles: From Sensors to Theranostics

PubMed Central

Goel, Shreya; Chen, Feng; Cai, Weibo

2013-01-01

Copper sulfide (CuS) nanoparticles have attracted increasing attention from biomedical researchers across the globe, because of their intriguing properties which have been mainly explored for energy- and catalysis-related applications to date. This focused review article aims to summarize the recent progress made in the synthesis and biomedical applications of various CuS nanoparticles. After a brief introduction to CuS nanoparticles in the first section, we will provide a concise outline of the various synthetic routes to obtain different morphologies of CuS nanoparticles, which can influence their properties and potential applications. CuS nanoparticles have found broad applications in vitro, especially in the detection of biomolecules, chemicals, and pathogens which will be illustrated in detail. The in vivo uses of CuS nanoparticles have also been investigated in preclinical studies, including molecular imaging with various techniques, cancer therapy based on the photothermal properties of CuS, as well as drug delivery and theranostic applications. Research on CuS nanoparticles will continue to thrive over the next decade, and tremendous opportunities lie ahead for potential biomedical/clinical applications of CuS nanoparticles. PMID:24106015

Factors Influencing the Application of a Biopsychosocial Perspective in Clinical Judgement of Chronic Pain: Interactive Management with Medical Students.

PubMed

Dwyer, Christopher P; McKenna-Plumley, Phoebe E; Durand, Hannah; Gormley, Emer M; Slattery, Brian W; Harney, Owen M; MacNeela, Padraig; McGuire, Brian E

2017-09-01

Though there is wide support for the application of biopsychosocial perspectives in clinical judgement of chronic pain cases, such perspectives are often overlooked due to either inadequate training or attitudes favoring a biomedical approach. Recent research has indicated that despite such explanations, both established general practitioners (GP) and medical students account for some psychosocial factors when making clinical judgements regarding chronic pain cases, but report not being likely to apply these in real-world, clinical settings due to numerous factors, including available time with patients. Thus, it is evident that a greater understanding of clinical judgement-making processes and the factors that affect application of these processes is required, particularly regarding chronic pain. The aims of the current study were to investigate medical students' conceptualizations of the factors that influence application of a biopsychosocial approach to clinical judgement-making in cases of chronic pain using interactive management (IM), model the relationships among these factors, and make recommendations to chronic pain treatment policy in light of the findings. The current study used IM to identify and model factors that influence the application of a biopsychosocial approach to clinical judgement-making in cases of chronic pain, based on medical students' conceptualizations of these factors. Two university classrooms. IM is a systems thinking and action mapping strategy used to aid groups in developing outcomes regarding complex issues, through integrating contributions from individuals with diverse views, backgrounds, and perspectives. IM commonly utilizes the nominal group technique and interpretive structural modeling, which in this context were employed to help medical students identify, clarify, and model influences on the application of biopsychosocial perspectives in treating chronic pain patients. Results of IM group work revealed 7 core biopsychosocial approach application categories: GP attitudes, cost, GP knowledge, time, patient-doctor relationship, biomedical factors. and patient perception. GP attitudes was the most critical driver of all other competencies in the system, with cost and GP knowledge revealed as secondary drivers. Potential differences in level of prior biopsychosocial perspective knowledge across participants and a potentially small sample size (though consistent with past research and appropriate for an exploratory study of this nature - for purposes of achieving the depth and richness of the deliberation and qualitative insights revealed by participants using the IM methodology). Results from this study may be used to both recommend further research on the identified factors influencing application of biopsychosocial perspectives in treatment of chronic pain and support amendment to extant health care policy, particularly with respect to cost, GP attitudes, and knowledge. Though this research claims neither that the influences identified are the only influences on biopsychosocial application, nor the order of their importance, the research does contribute to an on-going effort to better understand the factors that influence doctors in their treatment of chronic pain.Key words: Chronic pain, biopsychosocial, medical education, clinical judgement, interactive management, pain management.

Biomedical applications of a real-time terahertz color scanner

PubMed Central

Schirmer, Markus; Fujio, Makoto; Minami, Masaaki; Miura, Jiro; Araki, Tsutomu; Yasui, Takeshi

2010-01-01

A real-time THz color scanner has the potential to further expand the application scope of THz spectral imaging based on its rapid image acquisition rate. We demonstrated three possible applications of a THz color scanner in the biomedical field: imaging of pharmaceutical tablets, human teeth, and human hair. The first application showed the scanner’s potential in total inspection for rapid quality control of pharmaceutical tablets moving on a conveyor belt. The second application demonstrated that the scanner can be used to identify a potential indicator for crystallinity of dental tissue. In the third application, the scanner was successfully used to visualize the drying process of wet hairs. These demonstrations indicated the high potential of the THz color scanner for practical applications in the biomedical field. PMID:21258472

A snapshot of translational research funded by the National Institutes of Health (NIH): A case study using behavioral and social science research awards and Clinical and Translational Science Awards funded publications.

PubMed

Han, Xueying; Williams, Sharon R; Zuckerman, Brian L

2018-01-01

The translation of biomedical research from basic knowledge to application has been a priority at the National Institute of Health (NIH) for many years. Tracking the progress of scientific research and knowledge through the translational process is difficult due to variation in the definition of translational research as well as the identification of benchmarks for the spread and application of biomedical research; quantitatively tracking this process is even more difficult. Using a simple and reproducible method to assess whether publications are translational, we examined NIH R01 behavioral and social science research (BSSR) awards funded between 2008 and 2014 to determine whether there are differences in the percent of translational research publications produced by basic and applied research awards. We also assessed the percent of translational research publications produced by the Clinical and Translational Science Awards (CTSA) program to evaluate whether targeted translational research awards result in increased translational research. We found that 3.9% of publications produced by basic research awards were translational; that the percent of translational research publications produced by applied research awards is approximately double that of basic research awards (7.4%); and that targeted translational research awards from the CTSA program produced the highest percentage of translational research publications (13.4%). In addition, we assessed differences in time to first publication, time to first citation, and publication quality by award type (basic vs. applied), and whether an award (or publication) is translational.

A snapshot of translational research funded by the National Institutes of Health (NIH): A case study using behavioral and social science research awards and Clinical and Translational Science Awards funded publications

PubMed Central

Williams, Sharon R.; Zuckerman, Brian L.

2018-01-01

The translation of biomedical research from basic knowledge to application has been a priority at the National Institute of Health (NIH) for many years. Tracking the progress of scientific research and knowledge through the translational process is difficult due to variation in the definition of translational research as well as the identification of benchmarks for the spread and application of biomedical research; quantitatively tracking this process is even more difficult. Using a simple and reproducible method to assess whether publications are translational, we examined NIH R01 behavioral and social science research (BSSR) awards funded between 2008 and 2014 to determine whether there are differences in the percent of translational research publications produced by basic and applied research awards. We also assessed the percent of translational research publications produced by the Clinical and Translational Science Awards (CTSA) program to evaluate whether targeted translational research awards result in increased translational research. We found that 3.9% of publications produced by basic research awards were translational; that the percent of translational research publications produced by applied research awards is approximately double that of basic research awards (7.4%); and that targeted translational research awards from the CTSA program produced the highest percentage of translational research publications (13.4%). In addition, we assessed differences in time to first publication, time to first citation, and publication quality by award type (basic vs. applied), and whether an award (or publication) is translational. PMID:29742129

Improving "lab-on-a-chip" techniques using biomedical nanotechnology: a review.

PubMed

Gorjikhah, Fatemeh; Davaran, Soodabeh; Salehi, Roya; Bakhtiari, Mohsen; Hasanzadeh, Arash; Panahi, Yunes; Emamverdy, Masumeh; Akbarzadeh, Abolfazl

2016-11-01

Nanotechnology and its applications in biomedical sciences principally in molecular nanodiagnostics are known as nanomolecular diagnostics, which provides new options for clinical nanodiagnostic techniques. Molecular nanodiagnostics are a critical role in the development of personalized medicine, which features point-of care performance of diagnostic procedure. This can to check patients at point-of-care facilities or in remote or resource-poor locations, therefore reducing checking time from days to minutes. In this review, applications of nanotechnology suited to biomedicine are discussed in two main class: biomedical applications for use inside (such as drugs, diagnostic techniques, prostheses, and implants) and outside the body (such as "lab-on-a-chip" techniques). A lab-on-a-chip (LOC) is a tool that incorporates numerous laboratory tasks onto a small device, usually only millimeters or centimeters in size. Finally, are discussed the applications of biomedical nanotechnology in improving "lab-on-a-chip" techniques.

Marine Polysaccharides from Algae with Potential Biomedical Applications

PubMed Central

de Jesus Raposo, Maria Filomena; de Morais, Alcina Maria Bernardo; de Morais, Rui Manuel Santos Costa

2015-01-01

There is a current tendency towards bioactive natural products with applications in various industries, such as pharmaceutical, biomedical, cosmetics and food. This has put some emphasis in research on marine organisms, including macroalgae and microalgae, among others. Polysaccharides with marine origin constitute one type of these biochemical compounds that have already proved to have several important properties, such as anticoagulant and/or antithrombotic, immunomodulatory ability, antitumor and cancer preventive, antilipidaemic and hypoglycaemic, antibiotics and anti-inflammatory and antioxidant, making them promising bioactive products and biomaterials with a wide range of applications. Their properties are mainly due to their structure and physicochemical characteristics, which depend on the organism they are produced by. In the biomedical field, the polysaccharides from algae can be used in controlled drug delivery, wound management, and regenerative medicine. This review will focus on the biomedical applications of marine polysaccharides from algae. PMID:25988519

pH-responsive poly(aspartic acid) hydrogel-coated magnetite nanoparticles for biomedical applications.

PubMed

Vega-Chacón, Jaime; Arbeláez, María Isabel Amaya; Jorge, Janaina Habib; Marques, Rodrigo Fernando C; Jafelicci, Miguel

2017-08-01

A novel multifunctional nanosystem formed by magnetite nanoparticles coated with pH-responsive poly(aspartic acid) hydrogel was developed. Magnetite nanoparticles (Fe 3 O 4 ) have been intensively investigated for biomedical applications due to their magnetic properties and dimensions similar to the biostructures. Poly(aspartic acid) is a water-soluble, biodegradable and biocompatible polymer, which features makes it a potential candidate for biomedical applications. The nanoparticles surface modification was carried out by crosslinking polysuccinimide on the magnetite nanoparticles surface and hydrolyzing the succinimide units in mild alkaline medium to obtain the magnetic poly(aspartic acid) hydrogel. The surface modification in each step was confirmed by DRIFTS, TEM and zeta potential measurements. The hydrodynamic diameter of the nanosystems decreases as the pH value decreases. The nanosystems showed high colloidal stability in water and no cytotoxicity was detected, which make these nanosystems suitable for biomedical applications. Copyright © 2017 Elsevier B.V. All rights reserved.

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

Commercialising genetically engineered animal biomedical products.

PubMed

Sullivan, Eddie J; Pommer, Jerry; Robl, James M

2008-01-01

Research over the past two decades has increased the quality and quantity of tools available to produce genetically engineered animals. The number of potentially viable biomedical products from genetically engineered animals is increasing. However, moving from cutting-edge research to development and commercialisation of a biomedical product that is useful and wanted by the public has significant challenges. Even early stage development of genetically engineered animal applications requires consideration of many steps, including quality assurance and quality control, risk management, gap analysis, founder animal establishment, cell banking, sourcing of animals and animal-derived material, animal facilities, product collection facilities and processing facilities. These steps are complicated and expensive. Biomedical applications of genetically engineered animals have had some recent successes and many applications are well into development. As researchers consider applications for their findings, having a realistic understanding of the steps involved in the development and commercialisation of a product, produced in genetically engineered animals, is useful in determining the risk of genetic modification to the animal nu. the potential public benefit of the application.

Opal web services for biomedical applications.

PubMed

Ren, Jingyuan; Williams, Nadya; Clementi, Luca; Krishnan, Sriram; Li, Wilfred W

2010-07-01

Biomedical applications have become increasingly complex, and they often require large-scale high-performance computing resources with a large number of processors and memory. The complexity of application deployment and the advances in cluster, grid and cloud computing require new modes of support for biomedical research. Scientific Software as a Service (sSaaS) enables scalable and transparent access to biomedical applications through simple standards-based Web interfaces. Towards this end, we built a production web server (http://ws.nbcr.net) in August 2007 to support the bioinformatics application called MEME. The server has grown since to include docking analysis with AutoDock and AutoDock Vina, electrostatic calculations using PDB2PQR and APBS, and off-target analysis using SMAP. All the applications on the servers are powered by Opal, a toolkit that allows users to wrap scientific applications easily as web services without any modification to the scientific codes, by writing simple XML configuration files. Opal allows both web forms-based access and programmatic access of all our applications. The Opal toolkit currently supports SOAP-based Web service access to a number of popular applications from the National Biomedical Computation Resource (NBCR) and affiliated collaborative and service projects. In addition, Opal's programmatic access capability allows our applications to be accessed through many workflow tools, including Vision, Kepler, Nimrod/K and VisTrails. From mid-August 2007 to the end of 2009, we have successfully executed 239,814 jobs. The number of successfully executed jobs more than doubled from 205 to 411 per day between 2008 and 2009. The Opal-enabled service model is useful for a wide range of applications. It provides for interoperation with other applications with Web Service interfaces, and allows application developers to focus on the scientific tool and workflow development. Web server availability: http://ws.nbcr.net.

Recent development and biomedical applications of self-healing hydrogels.

PubMed

Wang, Yinan; Adokoh, Christian K; Narain, Ravin

2018-01-01

Hydrogels are of special importance, owing to their high-water content and various applications in biomedical and bio-engineering research. Self-healing properties is a common phenomenon in living organisms. Their endowed property of being able to self-repair after physical/chemical/mechanical damage to fully or partially its original properties demonstrates their prospective therapeutic applications. Due to complicated preparation and selection of suitable materials, the application of many host-guest supramolecular polymeric hydrogels are so limited. Thus, the design and construction of self-repairing material are highly desirable for effectively increase in the lifetime of a functional material. However, recent advances in the field of materials science and bioengineering and nanotechnology have led to the design of biologically relevant self-healing hydrogels for therapeutic applications. This review focuses on the recent development of self-healing hydrogels for biomedical application. Areas covered: The strategies of making self-healing hydrogels and their healing mechanisms are discussed. The significance of self-healing hydrogel for biomedical application is also highlighted in areas such as 3D/4D printing, cell/drug delivery, as well as soft actuators. Expert opinion: Materials that have the ability to self-repair damage and regain the desired mechanical properties, have been found to be excellent candidate materials for a range of biomedical uses especially if their unique characteristics are similar to that of soft-tissues. Self-healing hydrogels have been synthesized and shown to exhibit similar characteristics as human tissues, however, significant improvement is required in the fabrication process from inexpensive and nontoxic/non-hazardous materials and techniques, and, in addition, further fine-tuning of the self-healing properties are needed for specific biomedical uses.

Photonic crystal fibres in biomedical investigations

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

Skibina, Yu S; Tuchin, Valerii V; Beloglazov, V I

2011-04-30

The state of the art in the field of design and study of photonic crystal fibres for biomedical applications is considered and some original results recently obtained by the authors are presented. Optical properties of the fibres that offer prospects of their wide application as biological sensors, 'labs-on-a-chip', and facilities of electromagnetic radiation control in a wide range of wavelengths aimed at designing novel biomedical instrumentation are considered (optical technologies in biophysics and medicine)

Teaching biomedical applications to secondary students.

PubMed

Openshaw, S; Fleisher, A; Ljunggren, C

1999-01-01

Certain aspects of biomedical engineering applications lend themselves well to experimentation that can be done by high school students. This paper describes two experiments done during a six-week summer internship program in which two high school students used electrodes, circuit boards, and computers to mimic a sophisticated heart monitor and also to control a robotic car. Our experience suggests that simple illustrations of complex instrumentation can be effective in introducing adolescents to the biomedical engineering field.

Predicting activities of daily living for cancer patients using an ontology-guided machine learning methodology.

PubMed

Min, Hua; Mobahi, Hedyeh; Irvin, Katherine; Avramovic, Sanja; Wojtusiak, Janusz

2017-09-16

Bio-ontologies are becoming increasingly important in knowledge representation and in the machine learning (ML) fields. This paper presents a ML approach that incorporates bio-ontologies and its application to the SEER-MHOS dataset to discover patterns of patient characteristics that impact the ability to perform activities of daily living (ADLs). Bio-ontologies are used to provide computable knowledge for ML methods to "understand" biomedical data. This retrospective study included 723 cancer patients from the SEER-MHOS dataset. Two ML methods were applied to create predictive models for ADL disabilities for the first year after a patient's cancer diagnosis. The first method is a standard rule learning algorithm; the second is that same algorithm additionally equipped with methods for reasoning with ontologies. The models showed that a patient's race, ethnicity, smoking preference, treatment plan and tumor characteristics including histology, staging, cancer site, and morphology were predictors for ADL performance levels one year after cancer diagnosis. The ontology-guided ML method was more accurate at predicting ADL performance levels (P < 0.1) than methods without ontologies. This study demonstrated that bio-ontologies can be harnessed to provide medical knowledge for ML algorithms. The presented method demonstrates that encoding specific types of hierarchical relationships to guide rule learning is possible, and can be extended to other types of semantic relationships present in biomedical ontologies. The ontology-guided ML method achieved better performance than the method without ontologies. The presented method can also be used to promote the effectiveness and efficiency of ML in healthcare, in which use of background knowledge and consistency with existing clinical expertise is critical.

Using classification models for the generation of disease-specific medications from biomedical literature and clinical data repository.

PubMed

Wang, Liqin; Haug, Peter J; Del Fiol, Guilherme

2017-05-01

Mining disease-specific associations from existing knowledge resources can be useful for building disease-specific ontologies and supporting knowledge-based applications. Many association mining techniques have been exploited. However, the challenge remains when those extracted associations contained much noise. It is unreliable to determine the relevance of the association by simply setting up arbitrary cut-off points on multiple scores of relevance; and it would be expensive to ask human experts to manually review a large number of associations. We propose that machine-learning-based classification can be used to separate the signal from the noise, and to provide a feasible approach to create and maintain disease-specific vocabularies. We initially focused on disease-medication associations for the purpose of simplicity. For a disease of interest, we extracted potentially treatment-related drug concepts from biomedical literature citations and from a local clinical data repository. Each concept was associated with multiple measures of relevance (i.e., features) such as frequency of occurrence. For the machine purpose of learning, we formed nine datasets for three diseases with each disease having two single-source datasets and one from the combination of previous two datasets. All the datasets were labeled using existing reference standards. Thereafter, we conducted two experiments: (1) to test if adding features from the clinical data repository would improve the performance of classification achieved using features from the biomedical literature only, and (2) to determine if classifier(s) trained with known medication-disease data sets would be generalizable to new disease(s). Simple logistic regression and LogitBoost were two classifiers identified as the preferred models separately for the biomedical-literature datasets and combined datasets. The performance of the classification using combined features provided significant improvement beyond that using biomedical-literature features alone (p-value<0.001). The performance of the classifier built from known diseases to predict associated concepts for new diseases showed no significant difference from the performance of the classifier built and tested using the new disease's dataset. It is feasible to use classification approaches to automatically predict the relevance of a concept to a disease of interest. It is useful to combine features from disparate sources for the task of classification. Classifiers built from known diseases were generalizable to new diseases. Copyright © 2017 Elsevier Inc. All rights reserved.

Synthesis, toxicity, biocompatibility, and biomedical applications of graphene and graphene-related materials.

PubMed

Gurunathan, Sangiliyandi; Kim, Jin-Hoi

2016-01-01

Graphene is a two-dimensional atomic crystal, and since its development it has been applied in many novel ways in both research and industry. Graphene possesses unique properties, and it has been used in many applications including sensors, batteries, fuel cells, supercapacitors, transistors, components of high-strength machinery, and display screens in mobile devices. In the past decade, the biomedical applications of graphene have attracted much interest. Graphene has been reported to have antibacterial, antiplatelet, and anticancer activities. Several salient features of graphene make it a potential candidate for biological and biomedical applications. The synthesis, toxicity, biocompatibility, and biomedical applications of graphene are fundamental issues that require thorough investigation in any kind of applications related to human welfare. Therefore, this review addresses the various methods available for the synthesis of graphene, with special reference to biological synthesis, and highlights the biological applications of graphene with a focus on cancer therapy, drug delivery, bio-imaging, and tissue engineering, together with a brief discussion of the challenges and future perspectives of graphene. We hope to provide a comprehensive review of the latest progress in research on graphene, from synthesis to applications.

Synthesis, toxicity, biocompatibility, and biomedical applications of graphene and graphene-related materials

PubMed Central

Gurunathan, Sangiliyandi; Kim, Jin-Hoi

2016-01-01

Graphene is a two-dimensional atomic crystal, and since its development it has been applied in many novel ways in both research and industry. Graphene possesses unique properties, and it has been used in many applications including sensors, batteries, fuel cells, supercapacitors, transistors, components of high-strength machinery, and display screens in mobile devices. In the past decade, the biomedical applications of graphene have attracted much interest. Graphene has been reported to have antibacterial, antiplatelet, and anticancer activities. Several salient features of graphene make it a potential candidate for biological and biomedical applications. The synthesis, toxicity, biocompatibility, and biomedical applications of graphene are fundamental issues that require thorough investigation in any kind of applications related to human welfare. Therefore, this review addresses the various methods available for the synthesis of graphene, with special reference to biological synthesis, and highlights the biological applications of graphene with a focus on cancer therapy, drug delivery, bio-imaging, and tissue engineering, together with a brief discussion of the challenges and future perspectives of graphene. We hope to provide a comprehensive review of the latest progress in research on graphene, from synthesis to applications. PMID:27226713

Relational Network for Knowledge Discovery through Heterogeneous Biomedical and Clinical Features

PubMed Central

Chen, Huaidong; Chen, Wei; Liu, Chenglin; Zhang, Le; Su, Jing; Zhou, Xiaobo

2016-01-01

Biomedical big data, as a whole, covers numerous features, while each dataset specifically delineates part of them. “Full feature spectrum” knowledge discovery across heterogeneous data sources remains a major challenge. We developed a method called bootstrapping for unified feature association measurement (BUFAM) for pairwise association analysis, and relational dependency network (RDN) modeling for global module detection on features across breast cancer cohorts. Discovered knowledge was cross-validated using data from Wake Forest Baptist Medical Center’s electronic medical records and annotated with BioCarta signaling signatures. The clinical potential of the discovered modules was exhibited by stratifying patients for drug responses. A series of discovered associations provided new insights into breast cancer, such as the effects of patient’s cultural background on preferences for surgical procedure. We also discovered two groups of highly associated features, the HER2 and the ER modules, each of which described how phenotypes were associated with molecular signatures, diagnostic features, and clinical decisions. The discovered “ER module”, which was dominated by cancer immunity, was used as an example for patient stratification and prediction of drug responses to tamoxifen and chemotherapy. BUFAM-derived RDN modeling demonstrated unique ability to discover clinically meaningful and actionable knowledge across highly heterogeneous biomedical big data sets. PMID:27427091

Relational Network for Knowledge Discovery through Heterogeneous Biomedical and Clinical Features

NASA Astrophysics Data System (ADS)

Chen, Huaidong; Chen, Wei; Liu, Chenglin; Zhang, Le; Su, Jing; Zhou, Xiaobo

2016-07-01

Biomedical big data, as a whole, covers numerous features, while each dataset specifically delineates part of them. “Full feature spectrum” knowledge discovery across heterogeneous data sources remains a major challenge. We developed a method called bootstrapping for unified feature association measurement (BUFAM) for pairwise association analysis, and relational dependency network (RDN) modeling for global module detection on features across breast cancer cohorts. Discovered knowledge was cross-validated using data from Wake Forest Baptist Medical Center’s electronic medical records and annotated with BioCarta signaling signatures. The clinical potential of the discovered modules was exhibited by stratifying patients for drug responses. A series of discovered associations provided new insights into breast cancer, such as the effects of patient’s cultural background on preferences for surgical procedure. We also discovered two groups of highly associated features, the HER2 and the ER modules, each of which described how phenotypes were associated with molecular signatures, diagnostic features, and clinical decisions. The discovered “ER module”, which was dominated by cancer immunity, was used as an example for patient stratification and prediction of drug responses to tamoxifen and chemotherapy. BUFAM-derived RDN modeling demonstrated unique ability to discover clinically meaningful and actionable knowledge across highly heterogeneous biomedical big data sets.

ABSTRACTION FOR DATA INTEGRATION: FUSING MAMMALIAN MOLECULAR, CELLULAR AND PHENOTYPE BIG DATASETS FOR BETTER KNOWLEDGE EXTRACTION

PubMed Central

Rouillard, Andrew D.; Wang, Zichen; Ma’ayan, Avi

2015-01-01

With advances in genomics, transcriptomics, metabolomics and proteomics, and more expansive electronic clinical record monitoring, as well as advances in computation, we have entered the Big Data era in biomedical research. Data gathering is growing rapidly while only a small fraction of this data is converted to useful knowledge or reused in future studies. To improve this, an important concept that is often overlooked is data abstraction. To fuse and reuse biomedical datasets from diverse resources, data abstraction is frequently required. Here we summarize some of the major Big Data biomedical research resources for genomics, proteomics and phenotype data, collected from mammalian cells, tissues and organisms. We then suggest simple data abstraction methods for fusing this diverse but related data. Finally, we demonstrate examples of the potential utility of such data integration efforts, while warning about the inherit biases that exist within such data. PMID:26101093

From Lemongrass to Ivermectin: Ethnomedical Management of Chagas Disease in Tropical Bolivia.

PubMed

Forsyth, Colin

2018-04-01

Chagas disease is a neglected tropical disease; the only viable drugs are outdated and produce frequent side effects, and the overwhelming majority of cases are undiagnosed and untreated. Globally, people encounter numerous impediments to accessing biomedical treatment for Chagas disease. However, little is known about how people with Chagas disease manage their health outside the biomedical system. In this article, I discuss knowledge of ethnomedical treatments among marginalized patients in an endemic area of Bolivia. I interviewed 68 patients, 63 (93 percent) of whom had positive diagnoses for Chagas disease. Participants free listed 66 ethnomedical remedies either for Chagas disease (n = 39) or its cardiac symptoms. Participants stressed the accessibility of ethnomedical remedies in contrast to the multiple barriers to accessing biomedical treatment. Far from eroding in the face of globalization and sociopolitical marginalization, ethnomedical knowledge in the study area is dynamic and flexible, communicated through various channels.

Biofuel cells for biomedical applications: colonizing the animal kingdom.

PubMed

Falk, Magnus; Narváez Villarrubia, Claudia W; Babanova, Sofia; Atanassov, Plamen; Shleev, Sergey

2013-07-22

Interdisciplinary research has combined the efforts of many scientists and engineers to gain an understanding of biotic and abiotic electrochemical processes, materials properties, biomedical, and engineering approaches for the development of alternative power-generating and/or energy-harvesting devices, aiming to solve health-related issues and to improve the quality of human life. This review intends to recapitulate the principles of biofuel cell development and the progress over the years, thanks to the contribution of cross-disciplinary researchers that have combined knowledge and innovative ideas to the field. The emergence of biofuel cells, as a response to the demand of electrical power devices that can operate under physiological conditions, are reviewed. Implantable biofuel cells operating inside living organisms have been envisioned for over fifty years, but few reports of implanted devices have existed up until very recently. The very first report of an implanted biofuel cell (implanted in a grape) was published only in 2003 by Adam Heller and his coworkers. This work was a result of earlier scientific efforts of this group to "wire" enzymes to the electrode surface. The last couple of years have, however, seen a multitude of biofuel cells being implanted and operating in different living organisms, including mammals. Herein, the evolution of the biofuel concept, the understanding and employment of catalyst and biocatalyst processes to mimic biological processes, are explored. These potentially green technology biodevices are designed to be applied for biomedical applications to power nano- and microelectronic devices, drug delivery systems, biosensors, and many more. Copyright © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Systems identification and application systems development for monitoring the physiological and health status of crewmen in space

NASA Technical Reports Server (NTRS)

Leonard, J. I.; Furukawa, S.; Vannordstrand, P. C.

1975-01-01

The use of automated, analytical techniques to aid medical support teams is suggested. Recommendations are presented for characterizing crew health in terms of: (1) wholebody function including physiological, psychological and performance factors; (2) a combination of critical performance indexes which consist of multiple factors of measurable parameters; (3) specific responses to low noise level stress tests; and (4) probabilities of future performance based on present and periodic examination of past performance. A concept is proposed for a computerized real time biomedical monitoring and health care system that would have the capability to integrate monitored data, detect off-nominal conditions based on current knowledge of spaceflight responses, predict future health status, and assist in diagnosis and alternative therapies. Mathematical models could play an important role in this approach, especially when operating in a real time mode. Recommendations are presented to update the present health monitoring systems in terms of recent advances in computer technology and biomedical monitoring systems.

Predicting protein function and other biomedical characteristics with heterogeneous ensembles

PubMed Central

Whalen, Sean; Pandey, Om Prakash

2015-01-01

Prediction problems in biomedical sciences, including protein function prediction (PFP), are generally quite difficult. This is due in part to incomplete knowledge of the cellular phenomenon of interest, the appropriateness and data quality of the variables and measurements used for prediction, as well as a lack of consensus regarding the ideal predictor for specific problems. In such scenarios, a powerful approach to improving prediction performance is to construct heterogeneous ensemble predictors that combine the output of diverse individual predictors that capture complementary aspects of the problems and/or datasets. In this paper, we demonstrate the potential of such heterogeneous ensembles, derived from stacking and ensemble selection methods, for addressing PFP and other similar biomedical prediction problems. Deeper analysis of these results shows that the superior predictive ability of these methods, especially stacking, can be attributed to their attention to the following aspects of the ensemble learning process: (i) better balance of diversity and performance, (ii) more effective calibration of outputs and (iii) more robust incorporation of additional base predictors. Finally, to make the effective application of heterogeneous ensembles to large complex datasets (big data) feasible, we present DataSink, a distributed ensemble learning framework, and demonstrate its sound scalability using the examined datasets. DataSink is publicly available from https://github.com/shwhalen/datasink. PMID:26342255

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

PubMed

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

2013-08-01

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

Addressing Health Disparities in the Undergraduate Curriculum: An Approach to Develop a Knowledgeable Biomedical Workforce

ERIC Educational Resources Information Center

Benabentos, Rocio; Ray, Payal; Kumar, Deepak

2014-01-01

Disparities in health and healthcare are a major concern in the United States and worldwide. Approaches to alleviate these disparities must be multifaceted and should include initiatives that touch upon the diverse areas that influence the healthcare system. Developing a strong biomedical workforce with an awareness of the issues concerning health…

Recontextualizing and Delivering the Biomedical Model as a Physical Education Curriculum

ERIC Educational Resources Information Center

Johns, David P.

2005-01-01

This paper examines the problem of delivering a body of knowledge based on biomedical research as a school physical education discourse. The paper attempts to deconstruct the ideology of healthism upon which the discourse is based in order to show how ascetic practices in school physical education are promoted as a way of combating the hedonistic…

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.

Hemispheric Activation Differences in Novice and Expert Clinicians during Clinical Decision Making

ERIC Educational Resources Information Center

Hruska, Pam; Hecker, Kent G.; Coderre, Sylvain; McLaughlin, Kevin; Cortese, Filomeno; Doig, Christopher; Beran, Tanya; Wright, Bruce; Krigolson, Olav

2016-01-01

Clinical decision making requires knowledge, experience and analytical/non-analytical types of decision processes. As clinicians progress from novice to expert, research indicates decision-making becomes less reliant on foundational biomedical knowledge and more on previous experience. In this study, we investigated how knowledge and experience…

Synthetic Xylosides: Probing the Glycosaminoglycan Biosynthetic Machinery for Biomedical Applications.

PubMed

Chua, Jie Shi; Kuberan, Balagurunathan

2017-11-21

Glycosaminoglycans (GAGs) are polysaccharides ubiquitously found on cell surfaces and in the extracellular matrix (ECM). They regulate numerous cellular signaling events involved in many developmental and pathophysiological processes. GAGs are composed of complex sequences of repeating disaccharide units, each of which can carry many different modifications. The tremendous structural variations account for their ability to bind many proteins and thus, for their numerous functions. Although the sequence of GAG biosynthetic events and the enzymes involved mostly were deduced a decade ago, the emergence of tissue or cell specific GAGs from a nontemplate driven process remains an enigma. Current knowledge favors the hypothesis that macromolecular assemblies of GAG biosynthetic enzymes termed "GAGOSOMEs" coordinate polymerization and fine structural modifications in the Golgi apparatus. Distinct GAG structures arise from the differential channeling of substrates through the Golgi apparatus to various GAGOSOMEs. As GAGs perform multiple regulatory roles, it is of great interest to develop molecular strategies to selectively interfere with GAG biosynthesis for therapeutic applications. In this Account, we assess our present knowledge on GAG biosynthesis, the manipulation of GAG biosynthesis using synthetic xylosides, and the unrealized potential of these xylosides in various biomedical applications. Synthetic xylosides are small molecules consisting of a xylose attached to an aglycone group, and they compete with endogenous proteins for precursors and biosynthetic enzymes to assemble GAGs. This competition reduces endogenous proteoglycan-bound GAGs while increasing xyloside-bound free GAGs, mostly chondroitin sulfate (CS) and less heparan sulfate (HS), resulting in a variety of biological consequences. To date, hundreds of xylosides have been published and the importance of the aglycone group in determining the structure of the primed GAG chains is well established. However, the structure-activity relationship has long been cryptic. Nonetheless, xylosides have been designed to increase HS priming, modified to inhibit endogenous GAG production without priming, and engineered to be more biologically relevant. Synthetic xylosides hold great promise in many biomedical applications and as therapeutics. They are small, orally bioavailable, easily excreted, and utilize the host cell biosynthetic machinery to assemble GAGs that are likely nonimmunogenic. Various xylosides have been shown, in different biological systems, to have anticoagulant effects, selectively kill tumor cells, abrogate angiogenic and metastatic pathways, promote angiogenesis and neuronal growth, and affect embryonic development. However, most of these studies utilized the commercially available one or two β-D-xylosides and focused on the impact of endogenous proteoglycan-bound GAG inhibition on biological activity. Nevertheless, the manipulation of cell behavior as a result of stabilizing growth factor signaling with xyloside-primed GAGs is also reckonable but underexplored. Recent advances in the use of molecular modeling and docking simulations to understand the structure-activity relationships of xylosides have opened up the possibility of a more rational aglycone design to achieve a desirable biological outcome through selective priming and inhibitory activities. We envision these advances will encourage more researchers to explore these fascinating xylosides, harness the GAG biosynthetic machinery for a wider range of biomedical applications, and accelerate the successful transition of xyloside-based therapeutics from bench to bedside.

Integration of an OWL-DL knowledge base with an EHR prototype and providing customized information.

PubMed

Jing, Xia; Kay, Stephen; Marley, Tom; Hardiker, Nicholas R

2014-09-01

When clinicians use electronic health record (EHR) systems, their ability to obtain general knowledge is often an important contribution to their ability to make more informed decisions. In this paper we describe a method by which an external, formal representation of clinical and molecular genetic knowledge can be integrated into an EHR such that customized knowledge can be delivered to clinicians in a context-appropriate manner.Web Ontology Language-Description Logic (OWL-DL) is a formal knowledge representation language that is widely used for creating, organizing and managing biomedical knowledge through the use of explicit definitions, consistent structure and a computer-processable format, particularly in biomedical fields. In this paper we describe: 1) integration of an OWL-DL knowledge base with a standards-based EHR prototype, 2) presentation of customized information from the knowledge base via the EHR interface, and 3) lessons learned via the process. The integration was achieved through a combination of manual and automatic methods. Our method has advantages for scaling up to and maintaining knowledge bases of any size, with the goal of assisting clinicians and other EHR users in making better informed health care decisions.

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: transforming textual information into useful knowledge.

PubMed

Rassinoux, A-M

2010-01-01

To summarize current outstanding research in the field of knowledge representation and management. Synopsis of the articles selected for the IMIA Yearbook 2010. Four interesting papers, dealing with structured knowledge, have been selected for the section knowledge representation and management. Combining the newest techniques in computational linguistics and natural language processing with the latest methods in statistical data analysis, machine learning and text mining has proved to be efficient for turning unstructured textual information into meaningful knowledge. Three of the four selected papers for the section knowledge representation and management corroborate this approach and depict various experiments conducted to .extract meaningful knowledge from unstructured free texts such as extracting cancer disease characteristics from pathology reports, or extracting protein-protein interactions from biomedical papers, as well as extracting knowledge for the support of hypothesis generation in molecular biology from the Medline literature. Finally, the last paper addresses the level of formally representing and structuring information within clinical terminologies in order to render such information easily available and shareable among the health informatics community. Delivering common powerful tools able to automatically extract meaningful information from the huge amount of electronically unstructured free texts is an essential step towards promoting sharing and reusability across applications, domains, and institutions thus contributing to building capacities worldwide.

Engineering ultrasmall water-soluble gold and silver nanoclusters for biomedical applications.

PubMed

Luo, Zhentao; Zheng, Kaiyuan; Xie, Jianping

2014-05-25

Gold and silver nanoclusters or Au/Ag NCs with core sizes smaller than 2 nm have been an attractive frontier of nanoparticle research because of their unique physicochemical properties such as well-defined molecular structure, discrete electronic transitions, quantized charging, and strong luminescence. As a result of these unique properties, ultrasmall size, and good biocompatibility, Au/Ag NCs have great potential for a variety of biomedical applications, such as bioimaging, biosensing, antimicrobial agents, and cancer therapy. In this feature article, we will first discuss some critical biological considerations, such as biocompatibility and renal clearance, of Au/Ag NCs that are applied for biomedical applications, leading to some design criteria for functional Au/Ag NCs in the biological settings. According to these biological considerations, we will then survey some efficient synthetic strategies for the preparation of protein- and peptide-protected Au/Ag NCs with an emphasis on our recent contributions in this fast-growing field. In the last part, we will highlight some potential biomedical applications of these protein- and peptide-protected Au/Ag NCs. It is believed that with continued efforts to understand the interactions of biomolecule-protected Au/Ag NCs with the biological systems, scientists can largely realize the great potential of Au/Ag NCs for biomedical applications, which could finally pave their way towards clinical use.

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.

The Obligation to Participate in Biomedical Research

PubMed Central

Schaefer, G. Owen; Emanuel, Ezekiel J.; Wertheimer, Alan

2009-01-01

The prevailing view is that participation in biomedical research is above and beyond the call of duty. While some commentators have offered reasons against this, we propose a novel public goods argument for an obligation to participate in biomedical research. Biomedical knowledge is a public good, available to any individual even if that individual does not contribute to it. Participation in research is a critical way to support that important public good. Consequently, we all have a duty to participate. The current social norm is that people participate only if they have a good reason to do so. The public goods argument implies that people should participate unless they have a good reason not to. Such a shift would be of great aid to the progress of biomedical research, eventually making our society significantly healthier and longer-lived. PMID:19567441

Investigating Public trust in Expert Knowledge: Narrative, Ethics, and Engagement.

PubMed

Camporesi, Silvia; Vaccarella, Maria; Davis, Mark

2017-03-01

"Public Trust in Expert Knowledge: Narrative, Ethics, and Engagement" examines the social, cultural, and ethical ramifications of changing public trust in the expert biomedical knowledge systems of emergent and complex global societies. This symposium was conceived as an interdisciplinary project, drawing on bioethics, the social sciences, and the medical humanities. We settled on public trust as a topic for our work together because its problematization cuts across our fields and substantive research interests. For us, trust is simultaneously a matter of ethics, social relations, and the cultural organization of meaning. We share a commitment to narrative inquiry across our fields of expertise in the bioethics of transformative health technologies, public communications on health threats, and narrative medicine. The contributions to this symposium have applied, in different ways and with different effects, this interdisciplinary mode of inquiry, supplying new reflections on public trust, expertise, and biomedical knowledge.

Lensless, ultra-wideband fiber optic rotary joint for biomedical applications.

PubMed

Kim, Wihan; Chen, Xi; Jo, Javier A; Applegate, Brian E

2016-05-01

The demands of optical fiber-based biomedical applications can, in many cases, outstrip the capabilities of lens-based commercially available fiber optic rotary joints. In some circumstances, it is necessary to use very broad spectral bandwidths (near UV to short-wave IR) and specialized optical fibers, such as double-clad fiber, and have the capacity to accommodate high rotational velocities. The broad spectrum, stretching down into the UV, presents two problems: (1) adequate chromatic correction in the lenses across the entire bandwidth and (2) strong UV absorption by the fluids used to lubricate the rotary joint. To accommodate these types of applications, we have developed an ultra-wideband lensless fiber optic rotary joint based on the principle that when two optical fibers are coaligned and placed in contact (or very close), the optical losses at the junction are very low. The advances demonstrated here enable excellent performance (<0.2  dB insertion loss), even down into the UV and spanning a wavelength range of at least 355-1360 nm with single-mode, multimode, and double-clad fibers. We also demonstrate excellent performance, ∼0.38  dB insertion loss, at rotational velocities up to 8800 rpm (146 Hz). To the best of our knowledge, this is the first demonstration of this type of rotary joint capable of such a wide bandwidth and high rotational velocities.

DADOS-Survey: an open-source application for CHERRIES-compliant Web surveys

PubMed Central

Shah, Anand; Jacobs, Danny O; Martins, Henrique; Harker, Matthew; Menezes, Andreia; McCready, Mariana; Pietrobon, Ricardo

2006-01-01

Background The Internet has been increasingly utilized in biomedical research. From online searching for literature to data sharing, the Internet has emerged as a primary means of research for many physicians and scientists. As a result, Web-based surveys have been employed as an alternative to traditional, paper-based surveys. We describe DADOS-Survey, an open-source Web-survey application developed at our institution that, to the best of our knowledge, is the first to be compliant with the Checklist for Reporting Results of Internet E-Surveys (CHERRIES). DADOS-Survey was designed with usability as a priority, allowing investigators to design and execute their own studies with minimal technical difficulties in doing so. Results To date, DADOS-Survey has been successfully implemented in five Institutional Review Board-approved studies conducted by various departments within our academic center. Each of these studies employed a Web-survey design as their primary methodology. Our initial experience indicates that DADOS-Survey has been used with relative ease by each of the investigators and survey recipients. This has been further demonstrated through formal and field usability testing, during which time suggestions for improvement were incorporated into the software design. Conclusion DADOS-Survey has the potential to have an important role in the future direction of Web-survey administration in biomedical research. This CHERRIES-compliant application is tailored to the emerging requirements of quality data collection in medicine. PMID:16978409

Silver metal nanoparticles study for biomedical and green house applications

NASA Astrophysics Data System (ADS)

Rauwel, E.; Simón-Gracia, L.; Guha, M.; Rauwel, P.; Kuunal, S.; Wragg, D.

2017-02-01

Metallic nanoparticles (MNP) with diameters ranging from 2 to 100nm have received extensive attention during the past decades due to their many potential applications. This paper presents a structural and cytotoxicity study of silver metal nanoparticles targeted towards biomedical applications. Spherical Ag MNPs of diameter from 20 to 50 nm have been synthesized. The encapsulation of Ag MNPs inside pH-sensitive polymersomes has been also studied for the development of biomedical applications. A cytotoxicity study of the Ag MNPs against primary prostatic cancer cell line (PPC-1) has demonstrated a high mortality rate for concentrations ranging from 100 to 200mg/L. The paper will discuss the potential for therapeutic treatments of these Ag MNPs.

The Digital Anatomist Distributed Framework and Its Applications to Knowledge-based Medical Imaging

PubMed Central

Brinkley, James F.; Rosse, Cornelius

1997-01-01

Abstract The domain of medical imaging is anatomy. Therefore, anatomic knowledge should be a rational basis for organizing and analyzing images. The goals of the Digital Anatomist Program at the University of Washington include the development of an anatomically based software framework for organizing, analyzing, visualizing and utilizing biomedical information. The framework is based on representations for both spatial and symbolic anatomic knowledge, and is being implemented in a distributed architecture in which multiple client programs on the Internet are used to update and access an expanding set of anatomical information resources. The development of this framework is driven by several practical applications, including symbolic anatomic reasoning, knowledge based image segmentation, anatomy information retrieval, and functional brain mapping. Since each of these areas involves many difficult image processing issues, our research strategy is an evolutionary one, in which applications are developed somewhat independently, and partial solutions are integrated in a piecemeal fashion, using the network as the substrate. This approach assumes that networks of interacting components can synergistically work together to solve problems larger than either could solve on its own. Each of the individual projects is described, along with evaluations that show that the individual components are solving the problems they were designed for, and are beginning to interact with each other in a synergistic manner. We argue that this synergy will increase, not only within our own group, but also among groups as the Internet matures, and that an anatomic knowledge base will be a useful means for fostering these interactions. PMID:9147337

Educational Intervention in a Medically Underserved Area.

PubMed

Atance, Joel; Mickalis, Morgan; Kincade, Brianna

2018-04-01

Medical students from rural and medically underserved areas (MUAs) are more likely than their peers to practice medicine in rural areas and MUAs. However, students from MUAs are also more likely to face socioeconomic barriers to a career in medicine. To determine whether a week-long summer enrichment experience (SEE) at Edward Via College of Osteopathic Medicine-Carolinas could successfully teach high school students from MUAs basic biomedical concepts and foster an interest in medicine and the health sciences. The SEE program is open to high school students in the Spartanburg, South Carolina, area. The program includes interactive lectures, laboratories, demonstrations on gross anatomy prosections, demonstrations on medical simulation models, tours of emergency vehicles, an introduction to osteopathic manipulative medicine, and student-led research projects. Participants were asked to complete a 15-question quiz that assessed their knowledge of basic biomedical concepts and a 10-question survey that assessed their attitudes toward careers in medicine and health sciences. Both the quiz and the survey were completed on both the first and final days of the program. The data were analyzed using paired t tests. Participant knowledge of basic biomedical concepts, as determined by the quiz scores, increased after completion of the program (9.1 average correct answers vs 12.6 average correct answers) (P<.001). Participant attitude toward medicine and the health sciences improved in 9 of the 10 items surveyed after completion of the program (P<.05). Participant knowledge of basic biomedical concepts and their knowledge of and interest in careers in the health sciences improved after completing the SEE program. These findings suggest that educational interventions for high school students could help to develop primary care physicians for rural areas and MUAs and that there is a role for osteopathic medical schools to nurture these students as early as possible.

Oxidative Stress and Mitochondrial Activation as the Main Mechanisms Underlying Graphene Toxicity against Human Cancer Cells

PubMed Central

2016-01-01

Due to the development of nanotechnology graphene and graphene-based nanomaterials have attracted the most attention owing to their unique physical, chemical, and mechanical properties. Graphene can be applied in many fields among which biomedical applications especially diagnostics, cancer therapy, and drug delivery have been arousing a lot of interest. Therefore it is essential to understand better the graphene-cell interactions, especially toxicity and underlying mechanisms for proper use and development. This review presents the recent knowledge concerning graphene cytotoxicity and influence on different cancer cell lines. PMID:26649139

Stem Cells and Aging.

PubMed

Koliakos, George

2017-02-01

The article is a presentation at the 4th Conference of ESAAM, which took place on October 30-31, 2015, in Athens, Greece. Its purpose was not to cover all aspects of cellular aging but to share with the audience of the Conference, in a 15-minute presentation, current knowledge about the rejuvenating and repairing somatic stem cells that are distinct from other stem cell types (such as embryonic or induced pluripotent stem cells), emphasize that our body in old age cannot take advantage of these rejuvenating cells, and provide some examples of novel experimental stem cell applications in the field of rejuvenation and antiaging biomedical research.

Bovine tuberculosis research: Immune mechanisms relevant to biomedical applications

USDA-ARS?s Scientific Manuscript database

Pioneer studies on infectious disease and immunology by Jenner, Pasteur, Koch, Von Behring, Nocard, Roux, and Ehrlich forged a path for the dual-purpose with dual benefit approach, clearly demonstrating the relevance of veterinary studies for biomedical applications. Tuberculosis (TB), primarily due...

New graduate students' baseline knowledge of the responsible conduct of research.

PubMed

Heitman, Elizabeth; Olsen, Cara H; Anestidou, Lida; Bulger, Ruth Ellen

2007-09-01

To assess (1) new biomedical science graduate students' baseline knowledge of core concepts and standards in responsible conduct of research (RCR), (2) differences in graduate students' baseline knowledge overall and across the Office of Research Integrity's nine core areas, and (3) demographic and educational factors in these differences. A 30-question, computer-scored multiple-choice test on core concepts and standards of RCR was developed following content analysis of 20 United States-published RCR texts, and combined with demographic questions on undergraduate experience with RCR developed from graduate student focus groups. Four hundred two new graduate students at three health science universities were recruited for Scantron and online testing before beginning RCR instruction. Two hundred fifty-one of 402 eligible trainees (62%) at three universities completed the test; scores ranged from 26.7% to 83.3%, with a mean of 59.5%. Only seven (3%) participants scored 80% or above. Students who received their undergraduate education outside the United States scored significantly lower (mean 52.0%) than those with U.S. bachelor's degrees (mean 60.5%, P < .001). Participants with prior graduate biomedical or health professions education scored marginally higher than new students, but both groups' mean scores were well below 80%. The mean score of 16 participants who reported previous graduate-level RCR instruction was 67.7%. Participants' specific knowledge varied, but overall scores were universally low. New graduate biomedical sciences students have inadequate and inconsistent knowledge of RCR, irrespective of their prior education or experience. Incoming trainees with previous graduate RCR education may also have gaps in core knowledge.

Knowledge and acceptability of alternative HIV prevention bio-medical products among MSM who bareback.

PubMed

Nodin, N; Carballo-Diéguez, A; Ventuneac, A M; Balan, I C; Remien, R

2008-01-01

Condom use is the best available strategy to prevent HIV infection during sexual intercourse. However, since many people choose not to use condoms in circumstances in which HIV risk exists, alternatives to condom use for HIV prevention are needed. Currently there are several alternative bio-medical HIV-prevention products in different stages of development: microbicides, vaccines, post-exposure prophylaxis (PEP) and pre-exposure prophylaxis (PrEP). Seventy-two men who have sex with men (MSM) who took part in a study on Internet use and intentional condomless anal intercourse were asked about these four products during a semi-structured interview. The questions explored knowledge and acceptability of all the products and willingness to participate in microbicide and vaccine trials. Qualitative analysis of the data suggests that these men had virtually no knowledge of PrEP, very limited knowledge of microbicides, some information about PEP and considerably more knowledge about vaccines. Reactions towards the products were generally positive except for PrEP, for which reactions were polarized as either enthusiastic or negative. With the exception of PrEP, many men expressed willingness to use the products in the future. Most men would be willing to participate in trials for microbicides and vaccines if given basic reassurances. Concerns over negative side effects and preoccupation with possible infection were some of the motives given for non-willingness to participate in a vaccine trial. These results should inform the development of future trials of biomedical prevention products.

Learning the Structure of Biomedical Relationships from Unstructured Text

PubMed Central

Percha, Bethany; Altman, Russ B.

2015-01-01

The published biomedical research literature encompasses most of our understanding of how drugs interact with gene products to produce physiological responses (phenotypes). Unfortunately, this information is distributed throughout the unstructured text of over 23 million articles. The creation of structured resources that catalog the relationships between drugs and genes would accelerate the translation of basic molecular knowledge into discoveries of genomic biomarkers for drug response and prediction of unexpected drug-drug interactions. Extracting these relationships from natural language sentences on such a large scale, however, requires text mining algorithms that can recognize when different-looking statements are expressing similar ideas. Here we describe a novel algorithm, Ensemble Biclustering for Classification (EBC), that learns the structure of biomedical relationships automatically from text, overcoming differences in word choice and sentence structure. We validate EBC's performance against manually-curated sets of (1) pharmacogenomic relationships from PharmGKB and (2) drug-target relationships from DrugBank, and use it to discover new drug-gene relationships for both knowledge bases. We then apply EBC to map the complete universe of drug-gene relationships based on their descriptions in Medline, revealing unexpected structure that challenges current notions about how these relationships are expressed in text. For instance, we learn that newer experimental findings are described in consistently different ways than established knowledge, and that seemingly pure classes of relationships can exhibit interesting chimeric structure. The EBC algorithm is flexible and adaptable to a wide range of problems in biomedical text mining. PMID:26219079

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.

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.

Perspective on nanoparticle technology for biomedical use

PubMed Central

Raliya, Ramesh; Chadha, Tandeep Singh; Hadad, Kelsey; Biswas, Pratim

2016-01-01

This review gives a short overview on the widespread use of nanostructured and nanocomposite materials for disease diagnostics, drug delivery, imaging and biomedical sensing applications. Nanoparticle interaction with a biological matrix/entity is greatly influenced by its morphology, crystal phase, surface chemistry, functionalization, physicochemical and electronic properties of the particle. Various nanoparticle synthesis routes, characteristization, and functionalization methodologies to be used for biomedical applications ranging from drug delivery to molecular probing of underlying mechanisms and concepts are described with several examples (150 references). PMID:26951098

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.

The legacy of the Tuskegee Syphilis Study: assessing its impact on willingness to participate in biomedical studies.

PubMed

Katz, Ralph V; Green, B Lee; Kressin, Nancy R; Kegeles, S Stephen; Wang, Min Qi; James, Sherman A; Russell, Stefanie L; Claudio, Cristina; McCallum, Jan M

2008-11-01

The phrase, 'legacy of the Tuskegee Syphilis Study', is sometimes used to denote the belief that Blacks are more reluctant than Whites to participate in biomedical research studies because of the infamous study of syphilis in men run by the U.S. Public Health Service from 1932-72. This paper is the first to attempt to assess directly the accuracy of this belief within a multi-city, multi-racial, large-scale, detailed random survey. We administered the Tuskegee Legacy Project (TLP) Questionnaire to 826 Blacks and non-Hispanic White adults in three U.S. cities. While Blacks had higher levels of general awareness of the Tuskegee Syphilis Study, there was no association between either awareness or detailed knowledge of the Tuskegee Syphilis Study and willingness to participate in biomedical research, either for Blacks or Whites observed in our survey. While this study refutes the notion that there is a direct connection between detailed knowledge of the Tuskegee Syphilis Study and willingness to participate in biomedical research, it does not assess the broader question of whether and how historical events influence people's willingness to participate in research. Future studies should explore this.

The Legacy of the Tuskegee Syphilis Study: Assessing its Impact on Willingness to Participate in Biomedical Studies

PubMed Central

Katz, Ralph V.; Green, B. Lee; Kressin, Nancy R.; Kegeles, S. Stephen; Wang, Min Qi; James, Sherman A.; Russell, Stefanie L.; Claudio, Cristina; McCallum, Jan M.

2009-01-01

The phrase, legacy of the Tuskegee Syphilis Study, is sometimes used to denote the belief that Blacks are more reluctant than Whites to participate in biomedical research studies because of the infamous study of syphilis in men run by the U.S. Public Health Service from 1932-72. This paper is the first to attempt to assess directly the accuracy of this belief within a multi-city, multi-racial, large-scale, detailed random survey. We administered the Tuskegee Legacy Project (TLP) Questionnaire to 826 Blacks and non-Hispanic White adults in three U.S. cities. While Blacks had higher levels of general awareness of the Tuskegee Syphilis Study, there was no association between either awareness or detailed knowledge of the Tuskegee Syphilis Study and willingness to participate in biomedical research, either for Blacks or Whites observed in our survey. While this study refutes the notion that there is a direct connection between detailed knowledge of the Tuskegee Syphilis Study and willingness to participate in biomedical research, it does not assess the broader question of whether and how historical events influence people's willingness to participate in research. Future studies should explore this. PMID:19029744

Novel Blend for Producing Porous Chitosan-Based Films Suitable for Biomedical Applications

PubMed Central

Nady, Norhan; Kandil, Sherif H.

2018-01-01

In this work, a chitosan–gelatin–ferulic acid blend was used in different ratios for preparing novel films that can be used in biomedical applications. Both acetic and formic acid were tested as solvents for the chitosan–gelatin–ferulic acid blend. Glycerol was tested as a plasticizer. The thickness, mechanical strength, static water contact angle and water uptake of the prepared films were determined. Also, the prepared films were characterized using different analysis techniques such as Fourier transform infrared spectroscopy (FT-IR) analysis, X-ray diffraction (XRD), thermal gravimetric analysis (TGA), differential scanning calorimetry (DSC) and scanning electron microscopy (SEM). Acetic acid produced continuous compact surfaces that are not recommended for testing in biomedical applications. The plasticized chitosan–gelatin–ferulic acid blend, using formic acid solvent, produced novel hexagonal porous films with a pore size of around 10–14 µm. This blend is recommended for preparing films (scaffolds) for testing in biomedical applications as it has the advantage of a decreased thickness. PMID:29301357

Modelling of Argon Cold Atmospheric Plasmas for Biomedical Applications

NASA Astrophysics Data System (ADS)

Atanasova, M.; Benova, E.; Degrez, G.; van der Mullen, J. A. M.

2018-02-01

Plasmas for biomedical applications are one of the newest fields of plasma utilization. Especially high is the interest toward plasma usage in medicine. Promising results are achieved in blood coagulation, wound healing, treatment of some forms of cancer, diabetic complications, etc. However, the investigations of the biomedical applications from biological and medical viewpoint are much more advanced than the studies on the dynamics of the plasma. In this work we aim to address some specific challenges in the field of plasma modelling, arising from biomedical applications - what are the plasma reactive species’ and electrical fields’ spatial distributions as well as their production mechanisms; what are the fluxes and energies of the various components of the plasma delivers to the treated surfaces; what is the gas flow pattern? The focus is on two devices, namely the capacitive coupled plasma jet and the microwave surface wave sustained discharge. The devices are representatives of the so called cold atmospheric plasmas (CAPs). These are discharges characterized by low gas temperature - less than 40°C at the point of application - and non-equilibrium chemistry.

The development of large-scale de-identified biomedical databases in the age of genomics-principles and challenges.

PubMed

Dankar, Fida K; Ptitsyn, Andrey; Dankar, Samar K

2018-04-10

Contemporary biomedical databases include a wide range of information types from various observational and instrumental sources. Among the most important features that unite biomedical databases across the field are high volume of information and high potential to cause damage through data corruption, loss of performance, and loss of patient privacy. Thus, issues of data governance and privacy protection are essential for the construction of data depositories for biomedical research and healthcare. In this paper, we discuss various challenges of data governance in the context of population genome projects. The various challenges along with best practices and current research efforts are discussed through the steps of data collection, storage, sharing, analysis, and knowledge dissemination.

Empirical expression for DC magnetization curve of immobilized magnetic nanoparticles for use in biomedical applications

NASA Astrophysics Data System (ADS)

Elrefai, Ahmed L.; Sasayama, Teruyoshi; Yoshida, Takashi; Enpuku, Keiji

2018-05-01

We studied the magnetization (M-H) curve of immobilized magnetic nanoparticles (MNPs) used for biomedical applications. First, we performed numerical simulation on the DC M-H curve over a wide range of MNPs parameters. Based on the simulation results, we obtained an empirical expression for DC M-H curve. The empirical expression was compared with the measured M-H curves of various MNP samples, and quantitative agreements were obtained between them. We can also estimate the basic parameters of MNP from the comparison. Therefore, the empirical expression is useful for analyzing the M-H curve of immobilized MNPs for specific biomedical applications.

Magnetic Characterization of Iron Oxide Nanoparticles for Biomedical Applications.

PubMed

Maldonado-Camargo, Lorena; Unni, Mythreyi; Rinaldi, Carlos

2017-01-01

Iron oxide nanoparticles are of interest in a wide range of biomedical applications due to their response to applied magnetic fields and their unique magnetic properties. Magnetization measurements in constant and time-varying magnetic field are often carried out to quantify key properties of iron oxide nanoparticles. This chapter describes the importance of thorough magnetic characterization of iron oxide nanoparticles intended for use in biomedical applications. A basic introduction to relevant magnetic properties of iron oxide nanoparticles is given, followed by protocols and conditions used for measurement of magnetic properties, along with examples of data obtained from each measurement, and methods of data analysis.

Recent advances in terahertz technology for biomedical applications.

PubMed

Sun, Qiushuo; He, Yuezhi; Liu, Kai; Fan, Shuting; Parrott, Edward P J; Pickwell-MacPherson, Emma

2017-06-01

Terahertz instrumentation has improved significantly in recent years such that THz imaging systems have become more affordable and easier to use. THz systems can now be operated by non-THz experts greatly facilitating research into many potential applications. Due to the non-ionising nature of THz light and its high sensitivity to soft tissues, there is an increasing interest in biomedical applications including both in vivo and ex vivo studies. Additionally, research continues into understanding the origin of contrast and how to interpret terahertz biomedical images. This short review highlights some of the recent work in these areas and suggests some future research directions.

Engineering artificial machines from designable DNA materials for biomedical applications.

PubMed

Qi, Hao; Huang, Guoyou; Han, Yulong; Zhang, Xiaohui; Li, Yuhui; Pingguan-Murphy, Belinda; Lu, Tian Jian; Xu, Feng; Wang, Lin

2015-06-01

Deoxyribonucleic acid (DNA) emerges as building bricks for the fabrication of nanostructure with complete artificial architecture and geometry. The amazing ability of DNA in building two- and three-dimensional structures raises the possibility of developing smart nanomachines with versatile controllability for various applications. Here, we overviewed the recent progresses in engineering DNA machines for specific bioengineering and biomedical applications.

Engineering Artificial Machines from Designable DNA Materials for Biomedical Applications

PubMed Central

Huang, Guoyou; Han, Yulong; Zhang, Xiaohui; Li, Yuhui; Pingguan-Murphy, Belinda; Lu, Tian Jian; Xu, Feng

2015-01-01

Deoxyribonucleic acid (DNA) emerges as building bricks for the fabrication of nanostructure with complete artificial architecture and geometry. The amazing ability of DNA in building two- and three-dimensional structures raises the possibility of developing smart nanomachines with versatile controllability for various applications. Here, we overviewed the recent progresses in engineering DNA machines for specific bioengineering and biomedical applications. PMID:25547514

Emerging applications of nanoparticles: Biomedical and environmental

NASA Astrophysics Data System (ADS)

Gulati, Shivani; Sachdeva, M.; Bhasin, K. K.

2018-05-01

Nanotechnology finds a wide range of applications from energy production to industrial fabrication processes to biomedical applications. Nanoparticles (NPs) can be engineered to possess unique compositions and functionalities to empower novel tools and techniques that have not existed previously in biomedical research. The unique size and shape dependent physicochemical properties along with their unique spectral and optical properties have prompted the development of a wide variety of potential applications in the field of diagnostics and medicines. In the plethora of scientific and technological fields, environmental safety is also a big concern. For this purpose, nanomaterials have been functionalized to cope up the existing pollution, improving manufacturing methods to reduce the generation of new pollution, and making alternative and more cost effective energy sources.

Chitosan nanocomposites based on distinct inorganic fillers for biomedical applications

PubMed Central

Moura, Duarte; Mano, João F.; Paiva, Maria C.; Alves, Natália M.

2016-01-01

Abstract Chitosan (CHI), a biocompatible and biodegradable polysaccharide with the ability to provide a non-protein matrix for tissue growth, is considered to be an ideal material in the biomedical field. However, the lack of good mechanical properties limits its applications. In order to overcome this drawback, CHI has been combined with different polymers and fillers, leading to a variety of chitosan-based nanocomposites. The extensive research on CHI nanocomposites as well as their main biomedical applications are reviewed in this paper. An overview of the different fillers and assembly techniques available to produce CHI nanocomposites is presented. Finally, the properties of such nanocomposites are discussed with particular focus on bone regeneration, drug delivery, wound healing and biosensing applications. PMID:27877909

A Biomedical Application of Activated Carbon Adsorption: An Experiment Using Acetaminophen and N-Acetylcysteine.

ERIC Educational Resources Information Center

Rybolt, Thomas R.; And Others

1988-01-01

Illustrates an interesting biomedical application of adsorption from solution and demonstrates some of the factors that influence the in vivo adsorption of drug molecules onto activated charcoal. Uses acetaminophen and N-acetylcysteine for the determination. Suggests several related experiments. (MVL)

Bodies for empire: biopolitics, reproduction, and sexual knowledge in late colonial Korea.

PubMed

Park, Jin-kyung

2014-08-01

This paper explores the history of the biomedical construction of women's bodies as social bodies in the formation of colonial modernity in Korea. To do so, I engage with Michel Foucault's concepts of governmentality and biopolitics and the postcolonial history of medicine that has critically revisited these Foucauldian notions. These offer critical insights into the modern calculation of population and the biomedical gaze on female bodies on the Korean Peninsula under Japan's colonial rule (1910-1945). Foucauldian reflections on governmentality and colonial medicine can also shed light on the role of biomedical physicians in the advancement of colonial biopolitics. Biomedical physicians-state and non-state employees This paper explores the history of the biomedical construction of women's bodies as social bodies in the formation of colonial modernity in Korea. To do so, I engage with Michel Foucault's concepts of governmentality and biopolitics and the postcolonial history of medicine that has critically revisited these Foucauldian notions. These offer critical insights into the modern calculation of population and the biomedical gaze on female bodies on the Korean Peninsula under Japan's colonial rule (1910-1945). Foucauldian reflections on governmentality and colonial medicine can also shed light on the role of biomedical physicians in the advancement of colonial biopolitics. Biomedical physicians-state and non-state employees and colonizers and colonized alike - served as key agents investigating, knowing, and managing, as well as proliferating a discourse about, women's bodies and reproduction during Japan's empire-building. In particular, this paper sheds light on the processes by which Korean women's bodies became the objects of intense scrutiny as part of an attempt to quantify, as well as maximize, the total population in late colonial Korea. In the aftermath of the establishment of the Manchurian puppet state in 1932, Japanese imperial and colonial states actively sought to mobilize Koreans as crucial human resources for the further penetration of Japan's imperial holdings into the Chinese continent. State and non-state medical doctors meticulously interrogated, recorded, and circulated knowledge about the sexual and conjugal practices and reproductive life of Korean women in the agricultural sector, for the purposes of measuring and increasing the size, health, and vitality of the colonial population. At the heart of such medical endeavors stood the Investigative Committee for Social Hygiene in Rural Korea and Japan-trained Korean medical students/physicians, including Chóe Ŭg-sŏk, who carried out a social hygiene study in the mid-1930s. Their study illuminates the ways in which Korean women's bodies entered the modern domain of scientific knowledge at the intersection of Japan's imperialism, colonial governmentality, and biomedicine. A critical case study of the Investigative Committee's study and Chóe can set the stage for clarifying the vestiges as well as the reformulation of knowledge, ideas, institutions, and activities of colonial biopolitics in the divided Koreas.

Carbon nanotubes from synthesis to in vivo biomedical applications.

PubMed

Sajid, Muhammad Imran; Jamshaid, Usama; Jamshaid, Talha; Zafar, Nadiah; Fessi, H; Elaissari, Abdelhamid

2016-03-30

Owing to their unique and interesting properties, extensive research round the globe has been carried out on carbon nanotubes and carbon nanotubes based systems to investigate their practical usefulness in biomedical applications. The results from these studies demonstrate a great promise in their use in targeted drug delivery systems, diagnostic techniques and in bio-analytical applications. Although, carbon nanotubes possess quite interesting properties, which make them potential candidates in the biomedical science, but they also have some inherent properties which arise great concern regarding their biosafety. In this comprehensive review, we have discussed different aspects of carbon nanotubes and carbon nanotube based systems related to biomedical applications. In the beginning, a short historical account of these tiny yet powerful particles is given followed by discussion regarding their types, properties, methods of synthesis, large scale production method, purification techniques and characterization aspects of carbon nanotubes. In the second part of the review, the functionalization of carbon nanotubes is reviewed in detail, which is not only important to make them biocompatible and stable in biological systems but also render them a great property of loading various biomolecules, diagnostic and therapeutic moieties resulting in diversified applications. In the final part of the review, emphasis is given on the pharmacokinetic aspects of carbon nanotubes including administration routes, absorption mechanisms, distribution and elimination of carbon nanotubes based systems. Lastly, a comprehensive account about the potential biomedical applications has been given followed by insights into the future. Copyright © 2016 Elsevier B.V. All rights reserved.

Calcium Orthophosphate-Containing Biocomposites and Hybrid Biomaterials for Biomedical Applications

PubMed Central

Dorozhkin, Sergey V.

2015-01-01

The state-of-the-art on calcium orthophosphate (CaPO4)-containing biocomposites and hybrid biomaterials suitable for biomedical applications is presented. Since these types of biomaterials offer many significant and exciting possibilities for hard tissue regeneration, this subject belongs to a rapidly expanding area of biomedical research. Through the successful combinations of the desired properties of matrix materials with those of fillers (in such systems, CaPO4 might play either role), innovative bone graft biomaterials can be designed. Various types of CaPO4-based biocomposites and hybrid biomaterials those are either already in use or being investigated for biomedical applications are extensively discussed. Many different formulations in terms of the material constituents, fabrication technologies, structural and bioactive properties, as well as both in vitro and in vivo characteristics have been already proposed. Among the others, the nano-structurally controlled biocomposites, those containing nanodimensional compounds, biomimetically fabricated formulations with collagen, chitin and/or gelatin, as well as various functionally graded structures seem to be the most promising candidates for clinical applications. The specific advantages of using CaPO4-based biocomposites and hybrid biomaterials in the selected applications are highlighted. As the way from a laboratory to a hospital is a long one and the prospective biomedical candidates have to meet many different necessities, the critical issues and scientific challenges that require further research and development are also examined. PMID:26262645

Evolving technologies drive the new roles of Biomedical Engineering.

PubMed

Frisch, P H; St Germain, J; Lui, W

2008-01-01

Rapidly changing technology coupled with the financial impact of organized health care, has required hospital Biomedical Engineering organizations to augment their traditional operational and business models to increase their role in developing enhanced clinical applications utilizing new and evolving technologies. The deployment of these technology based applications has required Biomedical Engineering organizations to re-organize to optimize the manner in which they provide and manage services. Memorial Sloan-Kettering Cancer Center has implemented a strategy to explore evolving technologies integrating them into enhanced clinical applications while optimally utilizing the expertise of the traditional Biomedical Engineering component (Clinical Engineering) to provide expanded support in technology / equipment management, device repair, preventive maintenance and integration with legacy clinical systems. Specifically, Biomedical Engineering is an integral component of the Medical Physics Department which provides comprehensive and integrated support to the Center in advanced physical, technical and engineering technology. This organizational structure emphasizes the integration and collaboration between a spectrum of technical expertise for clinical support and equipment management roles. The high cost of clinical equipment purchases coupled with the increasing cost of service has driven equipment management responsibilities to include significant business and financial aspects to provide a cost effective service model. This case study details the dynamics of these expanded roles, future initiatives and benefits for Biomedical Engineering and Memorial Sloan Kettering Cancer Center.

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.

A community of practice: librarians in a biomedical research network.

PubMed

De Jager-Loftus, Danielle P; Midyette, J David; Harvey, Barbara

2014-01-01

Providing library and reference services within a biomedical research community presents special challenges for librarians, especially those in historically lower-funded states. These challenges can include understanding needs, defining and communicating the library's role, building relationships, and developing and maintaining general and subject specific knowledge. This article describes a biomedical research network and the work of health sciences librarians at the lead intensive research institution with librarians from primarily undergraduate institutions and tribal colleges. Applying the concept of a community of practice to a collaborative effort suggests how librarians can work together to provide effective reference services to researchers in biomedicine.

Nanodimensional and Nanocrystalline Apatites and Other Calcium Orthophosphates in Biomedical Engineering, Biology and Medicine

PubMed Central

Dorozhkin, Sergey V.

2009-01-01

Recent developments in biomineralization have already demonstrated that nanosized particles play an important role in the formation of hard tissues of animals. Namely, the basic inorganic building blocks of bones and teeth of mammals are nanodimensional and nanocrystalline calcium orthophosphates (in the form of apatites) of a biological origin. In mammals, tens to hundreds nanocrystals of a biological apatite were found to be combined into self-assembled structures under the control of various bioorganic matrixes. In addition, the structures of both dental enamel and bones could be mimicked by an oriented aggregation of nanosized calcium orthophosphates, determined by the biomolecules. The application and prospective use of nanodimensional and nanocrystalline calcium orthophosphates for a clinical repair of damaged bones and teeth are also known. For example, a greater viability and a better proliferation of various types of cells were detected on smaller crystals of calcium orthophosphates. Thus, the nanodimensional and nanocrystalline forms of calcium orthophosphates have a great potential to revolutionize the field of hard tissue engineering starting from bone repair and augmentation to the controlled drug delivery devices. This paper reviews current state of knowledge and recent developments of this subject starting from the synthesis and characterization to biomedical and clinical applications. More to the point, this review provides possible directions of future research and development.

Bioinformatics and Medical Informatics: Collaborations on the Road to Genomic Medicine?

PubMed Central

Maojo, Victor; Kulikowski, Casimir A.

2003-01-01

In this report, the authors compare and contrast medical informatics (MI) and bioinformatics (BI) and provide a viewpoint on their complementarities and potential for collaboration in various subfields. The authors compare MI and BI along several dimensions, including: (1) historical development of the disciplines, (2) their scientific foundations, (3) data quality and analysis, (4) integration of knowledge and databases, (5) informatics tools to support practice, (6) informatics methods to support research (signal processing, imaging and vision, and computational modeling, (7) professional and patient continuing education, and (8) education and training. It is pointed out that, while the two disciplines differ in their histories, scientific foundations, and methodologic approaches to research in various areas, they nevertheless share methods and tools, which provides a basis for exchange of experience in their different applications. MI expertise in developing health care applications and the strength of BI in biological “discovery science” complement each other well. The new field of biomedical informatics (BMI) holds great promise for developing informatics methods that will be crucial in the development of genomic medicine. The future of BMI will be influenced strongly by whether significant advances in clinical practice and biomedical research come about from separate efforts in MI and BI, or from emerging, hybrid informatics subdisciplines at their interface. PMID:12925552

Reusable and Mediator-Free Cholesterol Biosensor Based on Cholesterol Oxidase Immobilized onto TGA-SAM Modified Smart Bio-Chips

PubMed Central

Rahman, Mohammed M.

2014-01-01

A reusable and mediator-free cholesterol biosensor based on cholesterol oxidase (ChOx) was fabricated based on self-assembled monolayer (SAM) of thioglycolic acid (TGA) (covalent enzyme immobilization by dropping method) using bio-chips. Cholesterol was detected with modified bio-chip (Gold/Thioglycolic-acid/Cholesterol-oxidase i.e., Au/TGA/ChOx) by reliable cyclic voltammetric (CV) technique at room conditions. The Au/TGA/ChOx modified bio-chip sensor demonstrates good linearity (1.0 nM to 1.0 mM; R = 0.9935), low-detection limit (∼0.42 nM, SNR∼3), and higher sensitivity (∼74.3 µAµM−1cm−2), lowest-small sample volume (50.0 μL), good stability, and reproducibility. To the best of our knowledge, this is the first statement with a very high sensitivity, low-detection limit, and low-sample volumes are required for cholesterol biosensor using Au/TGA/ChOx-chips assembly. The result of this facile approach was investigated for the biomedical applications for real samples at room conditions with significant assembly (Au/TGA/ChOx) towards the development of selected cholesterol biosensors, which can offer analytical access to a large group of enzymes for wide range of biomedical applications in health-care fields. PMID:24949733

War of Ontology Worlds: Mathematics, Computer Code, or Esperanto?

PubMed Central

Rzhetsky, Andrey; Evans, James A.

2011-01-01

The use of structured knowledge representations—ontologies and terminologies—has become standard in biomedicine. Definitions of ontologies vary widely, as do the values and philosophies that underlie them. In seeking to make these views explicit, we conducted and summarized interviews with a dozen leading ontologists. Their views clustered into three broad perspectives that we summarize as mathematics, computer code, and Esperanto. Ontology as mathematics puts the ultimate premium on rigor and logic, symmetry and consistency of representation across scientific subfields, and the inclusion of only established, non-contradictory knowledge. Ontology as computer code focuses on utility and cultivates diversity, fitting ontologies to their purpose. Like computer languages C++, Prolog, and HTML, the code perspective holds that diverse applications warrant custom designed ontologies. Ontology as Esperanto focuses on facilitating cross-disciplinary communication, knowledge cross-referencing, and computation across datasets from diverse communities. We show how these views align with classical divides in science and suggest how a synthesis of their concerns could strengthen the next generation of biomedical ontologies. PMID:21980276

Defaults, context, and knowledge: alternatives for OWL-indexed knowledge bases.

PubMed

Rector, A

2004-01-01

The new Web Ontology Language (OWL) and its Description Logic compatible sublanguage (OWL-DL) explicitly exclude defaults and exceptions, as do all logic based formalisms for ontologies. However, many biomedical applications appear to require default reasoning, at least if they are to be engineered in a maintainable way. Default reasoning has always been one of the great strengths of Frame systems such as Protégé. Resolving this conflict requires analysis of the different uses for defaults and exceptions. In some cases, alternatives can be provided within the OWL framework; in others, it appears that hybrid reasoning about a knowledge base of contingent facts built around the core ontology is necessary. Trade-offs include both human factors and the scaling of computational performance. The analysis presented here is based on the OpenGALEN experience with large scale ontologies using a formalism, GRAIL, which explicitly incorporates constructs for hybrid reasoning, numerous experiments with OWL, and initial work on combining OWL and Protégé.

War of ontology worlds: mathematics, computer code, or Esperanto?

PubMed

Rzhetsky, Andrey; Evans, James A

2011-09-01

The use of structured knowledge representations-ontologies and terminologies-has become standard in biomedicine. Definitions of ontologies vary widely, as do the values and philosophies that underlie them. In seeking to make these views explicit, we conducted and summarized interviews with a dozen leading ontologists. Their views clustered into three broad perspectives that we summarize as mathematics, computer code, and Esperanto. Ontology as mathematics puts the ultimate premium on rigor and logic, symmetry and consistency of representation across scientific subfields, and the inclusion of only established, non-contradictory knowledge. Ontology as computer code focuses on utility and cultivates diversity, fitting ontologies to their purpose. Like computer languages C++, Prolog, and HTML, the code perspective holds that diverse applications warrant custom designed ontologies. Ontology as Esperanto focuses on facilitating cross-disciplinary communication, knowledge cross-referencing, and computation across datasets from diverse communities. We show how these views align with classical divides in science and suggest how a synthesis of their concerns could strengthen the next generation of biomedical ontologies.

Cross-organism learning method to discover new gene functionalities.

PubMed

Domeniconi, Giacomo; Masseroli, Marco; Moro, Gianluca; Pinoli, Pietro

2016-04-01

Knowledge of gene and protein functions is paramount for the understanding of physiological and pathological biological processes, as well as in the development of new drugs and therapies. Analyses for biomedical knowledge discovery greatly benefit from the availability of gene and protein functional feature descriptions expressed through controlled terminologies and ontologies, i.e., of gene and protein biomedical controlled annotations. In the last years, several databases of such annotations have become available; yet, these valuable annotations are incomplete, include errors and only some of them represent highly reliable human curated information. Computational techniques able to reliably predict new gene or protein annotations with an associated likelihood value are thus paramount. Here, we propose a novel cross-organisms learning approach to reliably predict new functionalities for the genes of an organism based on the known controlled annotations of the genes of another, evolutionarily related and better studied, organism. We leverage a new representation of the annotation discovery problem and a random perturbation of the available controlled annotations to allow the application of supervised algorithms to predict with good accuracy unknown gene annotations. Taking advantage of the numerous gene annotations available for a well-studied organism, our cross-organisms learning method creates and trains better prediction models, which can then be applied to predict new gene annotations of a target organism. We tested and compared our method with the equivalent single organism approach on different gene annotation datasets of five evolutionarily related organisms (Homo sapiens, Mus musculus, Bos taurus, Gallus gallus and Dictyostelium discoideum). Results show both the usefulness of the perturbation method of available annotations for better prediction model training and a great improvement of the cross-organism models with respect to the single-organism ones, without influence of the evolutionary distance between the considered organisms. The generated ranked lists of reliably predicted annotations, which describe novel gene functionalities and have an associated likelihood value, are very valuable both to complement available annotations, for better coverage in biomedical knowledge discovery analyses, and to quicken the annotation curation process, by focusing it on the prioritized novel annotations predicted. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Formalizing nursing knowledge: from theories and models to ontologies.

PubMed

Peace, Jane; Brennan, Patricia Flatley

2009-01-01

Knowledge representation in nursing is poised to address the depth of nursing knowledge about the specific phenomena of importance to nursing. Nursing theories and models may provide a starting point for making this knowledge explicit in representations. We combined knowledge building methods from nursing and ontology design methods from biomedical informatics to create a nursing representation of family health history. Our experience provides an example of how knowledge representations may be created to facilitate electronic support for nursing practice and knowledge development.

78 FR 5469 - Announcement of Requirements and Registration for the 2013 NIBIB DEsign by Biomedical...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-01-25

... tools, tissue engineering, drug and gene delivery (c) Technology to Aid Underserved Populations and... and engineering and associated technologies and modalities with biomedical applications; and (3) to...: September 2013, Biomedical Engineering Society Conference (exact date to be announced at http://debut2013...

Modern technologies for retinal scanning and imaging: an introduction for the biomedical engineer

PubMed Central

2014-01-01

This review article is meant to help biomedical engineers and nonphysical scientists better understand the principles of, and the main trends in modern scanning and imaging modalities used in ophthalmology. It is intended to ease the communication between physicists, medical doctors and engineers, and hopefully encourage “classical” biomedical engineers to generate new ideas and to initiate projects in an area which has traditionally been dominated by optical physics. Most of the methods involved are applicable to other areas of biomedical optics and optoelectronics, such as microscopic imaging, spectroscopy, spectral imaging, opto-acoustic tomography, fluorescence imaging etc., all of which are with potential biomedical application. Although all described methods are novel and important, the emphasis of this review has been placed on three technologies introduced in the 1990’s and still undergoing vigorous development: Confocal Scanning Laser Ophthalmoscopy, Optical Coherence Tomography, and polarization-sensitive retinal scanning. PMID:24779618

Biomedical research applications of electromagnetically separated enriched stable isotopes

NASA Astrophysics Data System (ADS)

Lambrecht, R. M.

The current and projected annual requirements through 1985 for stable isotopes enriched by electromagnetic separation methods were reviewed for applications in various types of biomedical research: (1) medical radiosiotope production, labeled compounds, and potential radio-pharmaceuticals; (2) nutrition, food science, and pharmacology: (3) metallobiochemistry and environmental toxicology; (4) nuclear magnetic resonance, electron paramagnetic resonance, and moessbauer spectroscopy in biochemical, biophysical, and biomedical research; and (5) miscellaneous advances in radioactive and nonradioactive tracer technology. Radioisotopes available from commercial sources or routinely used in clinical nuclear medicine were excluded. Current requirements for enriched stable isotopes in biomedical research are not being satisfied. Severe shortages exist for Mg 26, Ca 43, Zn 70, Se 76, Se 77, Se 78, Pd 102, Cd 111, Cd 113, and Os 190. Many interesting and potentially important investigations in biomedical research require small quantities of specific elements at high isotopic enrichments.

The development and application of bioinformatics core competencies to improve bioinformatics training and education.

PubMed

Mulder, Nicola; Schwartz, Russell; Brazas, Michelle D; Brooksbank, Cath; Gaeta, Bruno; Morgan, Sarah L; Pauley, Mark A; Rosenwald, Anne; Rustici, Gabriella; Sierk, Michael; Warnow, Tandy; Welch, Lonnie

2018-02-01

Bioinformatics is recognized as part of the essential knowledge base of numerous career paths in biomedical research and healthcare. However, there is little agreement in the field over what that knowledge entails or how best to provide it. These disagreements are compounded by the wide range of populations in need of bioinformatics training, with divergent prior backgrounds and intended application areas. The Curriculum Task Force of the International Society of Computational Biology (ISCB) Education Committee has sought to provide a framework for training needs and curricula in terms of a set of bioinformatics core competencies that cut across many user personas and training programs. The initial competencies developed based on surveys of employers and training programs have since been refined through a multiyear process of community engagement. This report describes the current status of the competencies and presents a series of use cases illustrating how they are being applied in diverse training contexts. These use cases are intended to demonstrate how others can make use of the competencies and engage in the process of their continuing refinement and application. The report concludes with a consideration of remaining challenges and future plans.

The development and application of bioinformatics core competencies to improve bioinformatics training and education

PubMed Central

Brooksbank, Cath; Morgan, Sarah L.; Rosenwald, Anne; Warnow, Tandy; Welch, Lonnie

2018-01-01

Bioinformatics is recognized as part of the essential knowledge base of numerous career paths in biomedical research and healthcare. However, there is little agreement in the field over what that knowledge entails or how best to provide it. These disagreements are compounded by the wide range of populations in need of bioinformatics training, with divergent prior backgrounds and intended application areas. The Curriculum Task Force of the International Society of Computational Biology (ISCB) Education Committee has sought to provide a framework for training needs and curricula in terms of a set of bioinformatics core competencies that cut across many user personas and training programs. The initial competencies developed based on surveys of employers and training programs have since been refined through a multiyear process of community engagement. This report describes the current status of the competencies and presents a series of use cases illustrating how they are being applied in diverse training contexts. These use cases are intended to demonstrate how others can make use of the competencies and engage in the process of their continuing refinement and application. The report concludes with a consideration of remaining challenges and future plans. PMID:29390004

Synthesis and Ligand-Exchange Reactions of a Tri-Tungsten Cluster with Applications in Biomedical Imaging

ERIC Educational Resources Information Center

Noey, Elizabeth; Curtis, Jeff C.; Tam, Sylvia; Pham, David M.; Jones, Ella F.

2011-01-01

In this experiment students are exposed to concepts in inorganic synthesis and various spectroscopies as applied to a tri-tungsten cluster with applications in biomedical imaging. The tungsten-acetate cluster, Na[W[superscript 3](mu-O)[subscript 2](CH[superscript 3]COO)[superscript 9

Erratum: Synthesis of Cd-free InP/ZnS Quantum Dots Suitable for Biomedical Applications.

PubMed

2016-02-29

A correction was made to: Synthesis of Cd-free InP/ZnS Quantum Dots Suitable for Biomedical Applications. There was an error with an author's given name. The author's name was corrected to: Katye M. Fichter from: Kathryn M. Fichter.

Application of nanotechnology in biomedical sciences.

PubMed

Zhao, Wei; Cao, Hong; Wan, Cheng-Song; Zhang, Wen-Bing

2002-05-01

Nanotechnology, a new research field that holds enormous prospects in the 21th century, has by now gained wide application in biomedical sciences, and consequently gives rise to two new cross-disciplines, nanobiology and nanobiomedicine. The authors provide a brief summarization of the progress so far achieved in these two new disciplines.

Nanotube Production and Applications at Johnson Space Center

NASA Technical Reports Server (NTRS)

Nikolaev, Pavel; Files, Bradley; Arepalli, Sivaram; Scott, Carl; Holmes, William; Nicholson, Leonard S. (Technical Monitor)

2000-01-01

Promise of applications of carbon nanotubes has led to an intense effort at NASA/JSC, especially in the area of nanotube composites. Using the extraordinary mechanical strength of nanotubes, NASA hopes to design this revolutionary lightweight material for use in aerospace applications. Current research focuses on structural polymeric materials to attempt to lower the weight of spacecraft necessary for interplanetary missions. Other applications of nanotubes are also of interest for energy storage, gas storage, nanoelectronics, field emission, and biomedical applications. In pursuit of these goals, we have set up both laser and arc production processes for nanotubes. An in-depth diagnostic study of the plasma plume in front of the laser target has been studied to try to determine nanotube growth mechanisms. Complementary studies of characterization of nanotube product have added to knowledge of growth conditions. Results of our preliminary experiments in incorporating nanotubes into composites will be presented. Morphology and mechanical properties of the nanotubes composites will be discussed.

Review of spectral imaging technology in biomedical engineering: achievements and challenges.

PubMed

Li, Qingli; He, Xiaofu; Wang, Yiting; Liu, Hongying; Xu, Dongrong; Guo, Fangmin

2013-10-01

Spectral imaging is a technology that integrates conventional imaging and spectroscopy to get both spatial and spectral information from an object. Although this technology was originally developed for remote sensing, it has been extended to the biomedical engineering field as a powerful analytical tool for biological and biomedical research. This review introduces the basics of spectral imaging, imaging methods, current equipment, and recent advances in biomedical applications. The performance and analytical capabilities of spectral imaging systems for biological and biomedical imaging are discussed. In particular, the current achievements and limitations of this technology in biomedical engineering are presented. The benefits and development trends of biomedical spectral imaging are highlighted to provide the reader with an insight into the current technological advances and its potential for biomedical research.

Potential Applications of Nanocellulose-Containing Materials in the Biomedical Field

PubMed Central

Halib, Nadia; Perrone, Francesca; Dapas, Barbara; Farra, Rossella; Abrami, Michela; Chiarappa, Gianluca; Forte, Giancarlo; Zanconati, Fabrizio; Pozzato, Gabriele; Murena, Luigi; Fiotti, Nicola; Lapasin, Romano; Cansolino, Laura; Grassi, Gabriele

2017-01-01

Because of its high biocompatibility, bio-degradability, low-cost and easy availability, cellulose finds application in disparate areas of research. Here we focus our attention on the most recent and attractive potential applications of cellulose in the biomedical field. We first describe the chemical/structural composition of cellulose fibers, the cellulose sources/features and cellulose chemical modifications employed to improve its properties. We then move to the description of cellulose potential applications in biomedicine. In this field, cellulose is most considered in recent research in the form of nano-sized particle, i.e., nanofiber cellulose (NFC) or cellulose nanocrystal (CNC). NFC is obtained from cellulose via chemical and mechanical methods. CNC can be obtained from macroscopic or microscopic forms of cellulose following strong acid hydrolysis. NFC and CNC are used for several reasons including the mechanical properties, the extended surface area and the low toxicity. Here we present some potential applications of nano-sized cellulose in the fields of wound healing, bone-cartilage regeneration, dental application and different human diseases including cancer. To witness the close proximity of nano-sized cellulose to the practical biomedical use, examples of recent clinical trials are also reported. Altogether, the described examples strongly support the enormous application potential of nano-sized cellulose in the biomedical field. PMID:28825682

Potential of Electrospun Nanofibers for Biomedical and Dental Applications

PubMed Central

Zafar, Muhammad; Najeeb, Shariq; Khurshid, Zohaib; Vazirzadeh, Masoud; Zohaib, Sana; Najeeb, Bilal; Sefat, Farshid

2016-01-01

Electrospinning is a versatile technique that has gained popularity for various biomedical applications in recent years. Electrospinning is being used for fabricating nanofibers for various biomedical and dental applications such as tooth regeneration, wound healing and prevention of dental caries. Electrospun materials have the benefits of unique properties for instance, high surface area to volume ratio, enhanced cellular interactions, protein absorption to facilitate binding sites for cell receptors. Extensive research has been conducted to explore the potential of electrospun nanofibers for repair and regeneration of various dental and oral tissues including dental pulp, dentin, periodontal tissues, oral mucosa and skeletal tissues. However, there are a few limitations of electrospinning hindering the progress of these materials to practical or clinical applications. In terms of biomaterials aspects, the better understanding of controlled fabrication, properties and functioning of electrospun materials is required to overcome the limitations. More in vivo studies are definitely required to evaluate the biocompatibility of electrospun scaffolds. Furthermore, mechanical properties of such scaffolds should be enhanced so that they resist mechanical stresses during tissue regeneration applications. The objective of this article is to review the current progress of electrospun nanofibers for biomedical and dental applications. In addition, various aspects of electrospun materials in relation to potential dental applications have been discussed. PMID:28787871

Load-Bearing Biomedical Applications of Diamond-Like Carbon Coatings - Current Status

PubMed Central

Alakoski, Esa; Tiainen, Veli-Matti; Soininen, Antti; Konttinen, Yrjö T

2008-01-01

The current status of diamond-like carbon (DLC) coatings for biomedical applications is reviewed with emphasis on load-bearing coatings. Although diamond-like carbon coating materials have been studied for decades, no indisputably successful commercial biomedical applications for high load situations exist today. High internal stress, leading to insufficient adhesion of thick coatings, is the evident reason behind this delay of the break-through of DLC coatings for applications. Excellent adhesion of thick DLC coatings is of utmost importance for load-bearing applications. According to this review superior candidate material for articulating implants is thick and adherent DLC on both sliding surfaces. With the filtered pulsed arc discharge method, all the necessary requirements for the deposition of thick and adherent DLC are fulfilled, provided that the substrate material is selected properly. PMID:19478929

Translating Knowledge on Poverty to Humanize Care: Benefits and Synergies of Community Engagement with the Arts

ERIC Educational Resources Information Center

Lévesque, Martine Cécile; Dupéré, Sophie; Morin, Nathalie; Côté, Johanne; Roberge, Nancy; Laurin, Isabelle; Charbonneau, Anne; Loignon, Christine; Bedos, Christophe

2015-01-01

The knowledge translation movement in health has led to the production of vast amounts of knowledge tools aimed at broadening clinicians' evidence base and improving the quality and efficacy of their practices. However important, these tools, largely oriented towards biomedical and technological aspects of care, are of limited potential for…

Performing Drug Safety Research During Pregnancy and Lactation: Biomedical HIV Prevention Research as a Template.

PubMed

Beigi, Richard H; Noguchi, Lisa; Brown, Gina; Piper, Jeanna; Watts, D Heather

2016-07-01

Evidence-based guidance regarding use of nearly all pharmaceuticals by pregnant and lactating women is limited. Models for performing research may assist in filling these knowledge gaps. Internationally, reproductive age women are at high risk of human immunodeficiency virus (HIV) acquisition. Susceptibility to HIV infection may be increased during pregnancy, and risk of maternal-child transmission is increased with incident HIV infection during pregnancy and lactation. A multidisciplinary meeting of experts was convened at the United States National Institutes of Health to consider paradigms for drug research in pregnancy and lactation applicable to HIV prevention. This report summarizes the meeting proceedings and describes a framework for research on candidate HIV prevention agent use during pregnancy and lactation that may also have broader applications to other pharmaceutical products.

A Semantic Web Management Model for Integrative Biomedical Informatics

PubMed Central

Deus, Helena F.; Stanislaus, Romesh; Veiga, Diogo F.; Behrens, Carmen; Wistuba, Ignacio I.; Minna, John D.; Garner, Harold R.; Swisher, Stephen G.; Roth, Jack A.; Correa, Arlene M.; Broom, Bradley; Coombes, Kevin; Chang, Allen; Vogel, Lynn H.; Almeida, Jonas S.

2008-01-01

Background Data, data everywhere. The diversity and magnitude of the data generated in the Life Sciences defies automated articulation among complementary efforts. The additional need in this field for managing property and access permissions compounds the difficulty very significantly. This is particularly the case when the integration involves multiple domains and disciplines, even more so when it includes clinical and high throughput molecular data. Methodology/Principal Findings The emergence of Semantic Web technologies brings the promise of meaningful interoperation between data and analysis resources. In this report we identify a core model for biomedical Knowledge Engineering applications and demonstrate how this new technology can be used to weave a management model where multiple intertwined data structures can be hosted and managed by multiple authorities in a distributed management infrastructure. Specifically, the demonstration is performed by linking data sources associated with the Lung Cancer SPORE awarded to The University of Texas MDAnderson Cancer Center at Houston and the Southwestern Medical Center at Dallas. A software prototype, available with open source at www.s3db.org, was developed and its proposed design has been made publicly available as an open source instrument for shared, distributed data management. Conclusions/Significance The Semantic Web technologies have the potential to addresses the need for distributed and evolvable representations that are critical for systems Biology and translational biomedical research. As this technology is incorporated into application development we can expect that both general purpose productivity software and domain specific software installed on our personal computers will become increasingly integrated with the relevant remote resources. In this scenario, the acquisition of a new dataset should automatically trigger the delegation of its analysis. PMID:18698353

Semantics-driven modelling of user preferences for information retrieval in the biomedical domain.

PubMed

Gladun, Anatoly; Rogushina, Julia; Valencia-García, Rafael; Béjar, Rodrigo Martínez

2013-03-01

A large amount of biomedical and genomic data are currently available on the Internet. However, data are distributed into heterogeneous biological information sources, with little or even no organization. Semantic technologies provide a consistent and reliable basis with which to confront the challenges involved in the organization, manipulation and visualization of data and knowledge. One of the knowledge representation techniques used in semantic processing is the ontology, which is commonly defined as a formal and explicit specification of a shared conceptualization of a domain of interest. The work presented here introduces a set of interoperable algorithms that can use domain and ontological information to improve information-retrieval processes. This work presents an ontology-based information-retrieval system for the biomedical domain. This system, with which some experiments have been carried out that are described in this paper, is based on the use of domain ontologies for the creation and normalization of lightweight ontologies that represent user preferences in a determined domain in order to improve information-retrieval processes.

Reprint of "Abstraction for data integration: Fusing mammalian molecular, cellular and phenotype big datasets for better knowledge extraction".

PubMed

Rouillard, Andrew D; Wang, Zichen; Ma'ayan, Avi

2015-12-01

With advances in genomics, transcriptomics, metabolomics and proteomics, and more expansive electronic clinical record monitoring, as well as advances in computation, we have entered the Big Data era in biomedical research. Data gathering is growing rapidly while only a small fraction of this data is converted to useful knowledge or reused in future studies. To improve this, an important concept that is often overlooked is data abstraction. To fuse and reuse biomedical datasets from diverse resources, data abstraction is frequently required. Here we summarize some of the major Big Data biomedical research resources for genomics, proteomics and phenotype data, collected from mammalian cells, tissues and organisms. We then suggest simple data abstraction methods for fusing this diverse but related data. Finally, we demonstrate examples of the potential utility of such data integration efforts, while warning about the inherit biases that exist within such data. Copyright © 2015 Elsevier Ltd. All rights reserved.

Art and science of authorship for biomedical research publication.

PubMed

Harsoor, S S

2016-09-01

Completion of research is logically followed by process of submission of the outcomes for publication. The objective of this article is to sensitise the young potential authors to improve their skill of writing so that the acceptance rate of publication is improved without significant comments and efforts of the editors of the journal. The article is based on the available literature combined with the experience of the author himself as reviewer and editor of biomedical journals. The treatment patterns of clinicians are moving towards evidence-based medical practice. Hence, a clinically relevant research question based on the contemporary knowledge gap is studied using appropriate research methodology. The writers are informed about the criteria to be fulfilled to claim authorship. Finally, emphasis is laid on the essentials of good medical writing necessary for publication. The writing for submission to biomedical journal is both an art and science in itself. A scientifically well-conducted study along with a sound knowledge of the mechanics of writing will enable the novices to achieve better acceptance rate for publication.

"Women come here on their own when they need to": prenatal care, authoritative knowledge, and maternal health in Oaxaca.

PubMed

Sesia, P M

1996-06-01

Physiological and anatomical concepts about reproduction held by traditional midwives in Southern Oaxaca differ considerably from those of biomedicine. Government training courses for traditional midwives disregard these deep-seated differences, and also the underlying conceptual rationale of ethno-obstetrics. These courses constantly reinforce and actively promote the biomedical model of care. But rural midwives, despite these training courses, do not substantially change their obstetrical vision and ways. The strength of their own authoritative knowledge, fully shared by the women and men of their communities, allows them to continue their traditional style of care, despite pressures to conform to biomedical values, beliefs, and practices. Suggestions for a mutual accommodation of biomedical and midwifery approaches to prenatal care include training medical personnel in ethno-obstetric techniques and rationales, teaching midwives basic medical interventions, addressing in intervention programs all social actors participating in reproductive decision making, and adopting an interdisciplinary approach that includes nonmedical aspects of maternal care.

Policies to increase the social value of science and the scientist satisfaction. An exploratory survey among Harvard bioscientists.

PubMed Central

Ballabeni, Andrea; Boggio, Andrea; Hemenway, David

2014-01-01

Basic research in the biomedical field generates both knowledge that has a value per se regardless of its possible practical outcome and knowledge that has the potential to produce more practical benefits. Policies can increase the benefit potential to society of basic biomedical research by offering various kinds of incentives to basic researchers. In this paper we argue that soft incentives or “nudges” are particularly promising. However, to be well designed, these incentives must take into account the motivations, goals and views of the basic scientists. In the paper we present the results of an investigation that involved more than 300 scientists at Harvard Medical School and affiliated institutes. The results of this study suggest that some soft incentives could be valuable tools to increase the transformative value of fundamental investigations without affecting the spirit of the basic research and scientists’ work satisfaction. After discussing the findings, we discuss a few examples of nudges for basic researchers in the biomedical fields. PMID:24795807

Policies to increase the social value of science and the scientist satisfaction. An exploratory survey among Harvard bioscientists.

PubMed

Ballabeni, Andrea; Boggio, Andrea; Hemenway, David

2014-01-01

Basic research in the biomedical field generates both knowledge that has a value per se regardless of its possible practical outcome and knowledge that has the potential to produce more practical benefits. Policies can increase the benefit potential to society of basic biomedical research by offering various kinds of incentives to basic researchers. In this paper we argue that soft incentives or "nudges" are particularly promising. However, to be well designed, these incentives must take into account the motivations, goals and views of the basic scientists. In the paper we present the results of an investigation that involved more than 300 scientists at Harvard Medical School and affiliated institutes. The results of this study suggest that some soft incentives could be valuable tools to increase the transformative value of fundamental investigations without affecting the spirit of the basic research and scientists' work satisfaction. After discussing the findings, we discuss a few examples of nudges for basic researchers in the biomedical fields.

Deep Learning in Nuclear Medicine and Molecular Imaging: Current Perspectives and Future Directions.

PubMed

Choi, Hongyoon

2018-04-01

Recent advances in deep learning have impacted various scientific and industrial fields. Due to the rapid application of deep learning in biomedical data, molecular imaging has also started to adopt this technique. In this regard, it is expected that deep learning will potentially affect the roles of molecular imaging experts as well as clinical decision making. This review firstly offers a basic overview of deep learning particularly for image data analysis to give knowledge to nuclear medicine physicians and researchers. Because of the unique characteristics and distinctive aims of various types of molecular imaging, deep learning applications can be different from other fields. In this context, the review deals with current perspectives of deep learning in molecular imaging particularly in terms of development of biomarkers. Finally, future challenges of deep learning application for molecular imaging and future roles of experts in molecular imaging will be discussed.

Cellulose nanocrystals: synthesis, functional properties, and applications

PubMed Central

George, Johnsy; Sabapathi, SN

2015-01-01

Cellulose nanocrystals are unique nanomaterials derived from the most abundant and almost inexhaustible natural polymer, cellulose. These nanomaterials have received significant interest due to their mechanical, optical, chemical, and rheological properties. Cellulose nanocrystals primarily obtained from naturally occurring cellulose fibers are biodegradable and renewable in nature and hence they serve as a sustainable and environmentally friendly material for most applications. These nanocrystals are basically hydrophilic in nature; however, they can be surface functionalized to meet various challenging requirements, such as the development of high-performance nanocomposites, using hydrophobic polymer matrices. Considering the ever-increasing interdisciplinary research being carried out on cellulose nanocrystals, this review aims to collate the knowledge available about the sources, chemical structure, and physical and chemical isolation procedures, as well as describes the mechanical, optical, and rheological properties, of cellulose nanocrystals. Innovative applications in diverse fields such as biomedical engineering, material sciences, electronics, catalysis, etc, wherein these cellulose nanocrystals can be used, are highlighted. PMID:26604715

Effects of Atmospheric Pressure Plasmas on Isolated and Cellular DNA—A Review

PubMed Central

Arjunan, Krishna Priya; Sharma, Virender K.; Ptasinska, Sylwia

2015-01-01

Atmospheric Pressure Plasma (APP) is being used widely in a variety of biomedical applications. Extensive research in the field of plasma medicine has shown the induction of DNA damage by APP in a dose-dependent manner in both prokaryotic and eukaryotic systems. Recent evidence suggests that APP-induced DNA damage shows potential benefits in many applications, such as sterilization and cancer therapy. However, in several other applications, such as wound healing and dentistry, DNA damage can be detrimental. This review reports on the extensive investigations devoted to APP interactions with DNA, with an emphasis on the critical role of reactive species in plasma-induced damage to DNA. The review consists of three main sections dedicated to fundamental knowledge of the interactions of reactive oxygen species (ROS)/reactive nitrogen species (RNS) with DNA and its components, as well as the effects of APP on isolated and cellular DNA in prokaryotes and eukaryotes. PMID:25642755

Effects of atmospheric pressure plasmas on isolated and cellular DNA-a review.

PubMed

Arjunan, Krishna Priya; Sharma, Virender K; Ptasinska, Sylwia

2015-01-29

Atmospheric Pressure Plasma (APP) is being used widely in a variety of biomedical applications. Extensive research in the field of plasma medicine has shown the induction of DNA damage by APP in a dose-dependent manner in both prokaryotic and eukaryotic systems. Recent evidence suggests that APP-induced DNA damage shows potential benefits in many applications, such as sterilization and cancer therapy. However, in several other applications, such as wound healing and dentistry, DNA damage can be detrimental. This review reports on the extensive investigations devoted to APP interactions with DNA, with an emphasis on the critical role of reactive species in plasma-induced damage to DNA. The review consists of three main sections dedicated to fundamental knowledge of the interactions of reactive oxygen species (ROS)/reactive nitrogen species (RNS) with DNA and its components, as well as the effects of APP on isolated and cellular DNA in prokaryotes and eukaryotes.

Ultrasmall inorganic nanoparticles: State-of-the-art and perspectives for biomedical applications.

PubMed

Zarschler, Kristof; Rocks, Louise; Licciardello, Nadia; Boselli, Luca; Polo, Ester; Garcia, Karina Pombo; De Cola, Luisa; Stephan, Holger; Dawson, Kenneth A

2016-08-01

Ultrasmall nanoparticulate materials with core sizes in the 1-3nm range bridge the gap between single molecules and classical, larger-sized nanomaterials, not only in terms of spatial dimension, but also as regards physicochemical and pharmacokinetic properties. Due to these unique properties, ultrasmall nanoparticles appear to be promising materials for nanomedicinal applications. This review overviews the different synthetic methods of inorganic ultrasmall nanoparticles as well as their properties, characterization, surface modification and toxicity. We moreover summarize the current state of knowledge regarding pharmacokinetics, biodistribution and targeting of nanoscale materials. Aside from addressing the issue of biomolecular corona formation and elaborating on the interactions of ultrasmall nanoparticles with individual cells, we discuss the potential diagnostic, therapeutic and theranostic applications of ultrasmall nanoparticles in the emerging field of nanomedicine in the final part of this review. Copyright © 2016 Elsevier Inc. All rights reserved.

Advances in utilization of renewable substrates for biosurfactant production

PubMed Central

2011-01-01

Biosurfactants are amphiphilic molecules that have both hydrophilic and hydrophobic moieties which partition preferentially at the interfaces such as liquid/liquid, gas/liquid or solid/liquid interfaces. Such characteristics enable emulsifying, foaming, detergency and dispersing properties. Their low toxicity and environmental friendly nature and the wide range of potential industrial applications in bioremediation, health care, oil and food processing industries makes them a highly sought after group of chemical compounds. Interest in them has also been encouraged because of the potential advantages they offer over their synthetic counterparts in many fields spanning environmental, food, biomedical, petrochemical and other industrial applications. Their large scale production and application however are currently restricted by the high cost of production and by the limited understanding of their interactions with cells and with the abiotic environment. In this paper, we review the current knowledge and latest advances in the search for cost effective renewable agro industrial alternative substrates for their production. PMID:21906330

Relationship of resident characteristics, attitudes, prior training and clinical knowledge to communication skills performance.

PubMed

Laidlaw, Toni Suzuki; Kaufman, David M; MacLeod, Heather; van Zanten, Sander; Simpson, David; Wrixon, William

2006-01-01

A substantial body of literature demonstrates that communication skills in medicine can be taught and retained through teaching and practice. Considerable evidence also reveals that characteristics such as gender, age, language and attitudes affect communication skills performance. Our study examined the characteristics, attitudes and prior communication skills training of residents to determine the relationship of each to patient-doctor communication. The relationship between communication skills proficiency and clinical knowledge application (biomedical and ethical) was also examined through the use of doctor-developed clinical content checklists, as very little research has been conducted in this area. A total of 78 first- and second-year residents across all departments at Dalhousie Medical School participated in a videotaped 4-station objective structured clinical examination presenting a range of communication and clinical knowledge challenges. A variety of instruments were used to gather information and assess performance. Two expert raters evaluated the videotapes. Significant relationships were observed between resident characteristics, prior communication skills training, clinical knowledge and communication skills performance. Females, younger residents and residents with English as first language scored significantly higher, as did residents with prior communication skills training. A significant positive relationship was found between the clinical content checklist and communication performance. Gender was the only characteristic related significantly to attitudes. Gender, age, language and prior communication skills training are related to communication skills performance and have implications for resident education. The positive relationship between communication skills proficiency and clinical knowledge application is important and should be explored further.

Micro and nanotechnology for biological and biomedical applications.

PubMed

Lim, Chwee Teck; Han, Jongyoon; Guck, Jochen; Espinosa, Horacio

2010-10-01

This special issue contains some of the current state-of-the-art development and use of micro and nanotechnological tools, devices and techniques for both biological and biomedical research and applications. These include nanoparticles for bioimaging and biosensing, optical and biophotonic techniques for probing diseases at the nanoscale, micro and nano-fabricated tools for elucidating molecular mechanisms of mechanotransduction in cell and molecular biology and cell separation microdevices and techniques for isolating and enriching targeted cells for disease detection and diagnosis. Although some of these works are still at the research stage, there is no doubt that some of the important outcomes will eventually see actual biomedical applications in the not too distant future.

Engineering and Application of Zinc Finger Proteins and TALEs for Biomedical Research.

PubMed

Kim, Moon-Soo; Kini, Anu Ganesh

2017-08-01

Engineered DNA-binding domains provide a powerful technology for numerous biomedical studies due to their ability to recognize specific DNA sequences. Zinc fingers (ZF) are one of the most common DNA-binding domains and have been extensively studied for a variety of applications, such as gene regulation, genome engineering and diagnostics. Another novel DNA-binding domain known as a transcriptional activator-like effector (TALE) has been more recently discovered, which has a previously undescribed DNA-binding mode. Due to their modular architecture and flexibility, TALEs have been rapidly developed into artificial gene targeting reagents. Here, we describe the methods used to design these DNA-binding proteins and their key applications in biomedical research.

Engineering mechanical microenvironment of macrophage and its biomedical applications.

PubMed

Li, Jing; Li, Yuhui; Gao, Bin; Qin, Chuanguang; He, Yining; Xu, Feng; Yang, Hui; Lin, Min

2018-03-01

Macrophages are the most plastic cells in the hematopoietic system and can be widely found in almost all tissues. Recently studies have shown that mechanical cues (e.g., matrix stiffness and stress/strain) can significantly affect macrophage behaviors. Although existing reviews on the physical and mechanical cues that regulate the macrophage's phenotype are available, engineering mechanical microenvironment of macrophages in vitro as well as a comprehensive overview and prospects for their biomedical applications (e.g., tissue engineering and immunotherapy) has yet to be summarized. Thus, this review provides an overview on the existing methods for engineering mechanical microenvironment of macrophages in vitro and then a section on their biomedical applications and further perspectives are presented.

Microbubble Compositions, Properties and Biomedical Applications

PubMed Central

Sirsi, Shashank

2010-01-01

Over the last decade, there has been significant progress towards the development of microbubbles as theranostics for a wide variety of biomedical applications. The unique ability of microbubbles to respond to ultrasound makes them useful agents for contrast ultrasound imaging, molecular imaging, and targeted drug and gene delivery. The general composition of a microbubble is a gas core stabilized by a shell comprised of proteins, lipids or polymers. Each type of microbubble has its own unique advantages and can be tailored for specialized functions. In this review, different microbubbles compositions and physiochemical properties are discussed in the context of current progress towards developing novel constructs for biomedical applications, with specific emphasis on molecular imaging and targeted drug/gene delivery. PMID:20574549

Functional Electrospun Nanofibrous Scaffolds for Biomedical Applications

PubMed Central

Liang, Dehai; Hsiao, Benjamin S.; Chu, Benjamin

2009-01-01

Functional nanofibrous scaffolds produced by electrospinning have great potential in many biomedical applications, such as tissue engineering, wound dressing, enzyme immobilization and drug (gene) delivery. For a specific successful application, the chemical, physical and biological properties of electrospun scaffolds should be adjusted to match the environment by using a combination of multi-component compositions and fabrication techniques where electrospinning has often become a pivotal tool. The property of the nanofibrous scaffold can be further improved with innovative development in electrospinning processes, such as two-component electrospinning and in-situ mixing electrospinning. Post modifications of electrospun membranes also provide effective means to render the electrospun scaffolds with controlled anisotropy and porosity. In this review, we review the materials, techniques and post modification methods to functionalize electrospun nanofibrous scaffolds suitable for biomedical applications. PMID:17884240

Combinatorial nanodiamond in pharmaceutical and biomedical applications.

PubMed

Lim, Dae Gon; Prim, Racelly Ena; Kim, Ki Hyun; Kang, Eunah; Park, Kinam; Jeong, Seong Hoon

2016-11-30

One of the newly emerging carbon materials, nanodiamond (ND), has been exploited for use in traditional electric materials and this has extended into biomedical and pharmaceutical applications. Recently, NDs have attained significant interests as a multifunctional and combinational drug delivery system. ND studies have provided insights into granting new potentials with their wide ranging surface chemistry, complex formation with biopolymers, and combination with biomolecules. The studies that have proved ND inertness, biocompatibility, and low toxicity have made NDs much more feasible for use in real in vivo applications. This review gives an understanding of NDs in biomedical engineering and pharmaceuticals, focusing on the classified introduction of ND/drug complexes. In addition, the diverse potential applications that can be obtained with chemical modification are presented. Copyright © 2016 Elsevier B.V. All rights reserved.

Metal-containing and related polymers for biomedical applications.

PubMed

Yan, Yi; Zhang, Jiuyang; Ren, Lixia; Tang, Chuanbing

2016-10-07

A survey of the most recent progress in the biomedical applications of metal-containing polymers is given. Due to the unique optical, electrochemical, and magnetic properties, at least 30 different metal elements, most of them transition metals, are introduced into polymeric frameworks for interactions with biology-relevant substrates via various means. Inspired by the advance of metal-containing small molecular drugs and promoted by the great progress in polymer chemistry, metal-containing polymers have gained momentum during recent decades. According to their different applications, this review summarizes the following biomedical applications: (1) metal-containing polymers as drug delivery vehicles; (2) metal-containing polymeric drugs and biocides, including antimicrobial and antiviral agents, anticancer drugs, photodynamic therapy agents, radiotherapy agents and biocides; (3) metal-containing polymers as biosensors, and (4) metal-containing polymers in bioimaging.

Biomedical Impact in Implantable Devices-The Transcatheter Aortic Valve as an example

NASA Astrophysics Data System (ADS)

Anastasiou, Alexandros; Saatsakis, George

2015-09-01

Objective: To update of the scientific community about the biomedical engineering involvement in the implantable devices chain. Moreover the transcatheter Aortic Valve (TAV) replacement, in the field of cardiac surgery, will be analyzed as an example of contemporary implantable technology. Methods: A detailed literature review regarding biomedical engineers participating in the implantable medical product chain, starting from the design of the product till the final implantation technique. Results: The scientific role of biomedical engineers has clearly been established. Certain parts of the product chain are implemented almost exclusively by experienced biomedical engineers such as the transcatheter aortic valve device. The successful professional should have a multidisciplinary knowledge, including medicine, in order to pursue the challenges for such intuitive technology. This clearly indicates that biomedical engineers are among the most appropriate scientists to accomplish such tasks. Conclusions: The biomedical engineering involvement in medical implantable devices has been widely accepted by the scientific community, worldwide. Its important contribution, starting from the design and extended to the development, clinical trials, scientific support, education of other scientists (surgeons, cardiologists, technicians etc.), and even to sales, makes biomedical engineers a valuable player in the scientific arena. Notably, the sector of implantable devices is constantly raising, as emerging technologies continuously set up new targets.

Job Profiles of Biomedical Informatics Graduates. Results of a Graduate Survey.

PubMed

Ammenwerth, E; Hackl, W O

2015-01-01

Biomedical informatics programs exist in many countries. Some analyses of the skills needed and of recommendations for curricular content for such programs have been published. However, not much is known of the job profiles and job careers of their graduates. To analyse the job profiles and job careers of 175 graduates of the biomedical informatics bachelor and master program of the Tyrolean university UMIT. Survey of all biomedical informatics students who graduated from UMIT between 2001 and 2013. Information is available for 170 graduates. Eight percent of graduates are male. Of all bachelor graduates, 86% started a master program. Of all master graduates, 36% started a PhD. The job profiles are quite diverse: at the time of the survey, 35% of all master graduates worked in the health IT industry, 24% at research institutions, 9% in hospitals, 9% as medical doctors, 17% as informaticians outside the health care sector, and 6% in other areas. Overall, 68% of the graduates are working as biomedical informaticians. The results of the survey indicate a good job situation for the graduates. The job opportunities for biomedical informaticians who graduated with a bachelor or master degree from UMIT seem to be quite good. The majority of graduates are working as biomedical informaticians. A larger number of comparable surveys of graduates from other biomedical informatics programs would help to enhance our knowledge about careers in biomedical informatics.

National Space Biomedical Research Institute

NASA Technical Reports Server (NTRS)

1998-01-01

The National Space Biomedical Research Institute (NSBRI) sponsors and performs fundamental and applied space biomedical research with the mission of leading a world-class, national effort in integrated, critical path space biomedical research that supports NASA's Human Exploration and Development of Space (HEDS) Strategic Plan. It focuses on the enabling of long-term human presence in, development of, and exploration of space. This will be accomplished by: designing, implementing, and validating effective countermeasures to address the biological and environmental impediments to long-term human space flight; defining the molecular, cellular, organ-level, integrated responses and mechanistic relationships that ultimately determine these impediments, where such activity fosters the development of novel countermeasures; establishing biomedical support technologies to maximize human performance in space, reduce biomedical hazards to an acceptable level, and deliver quality medical care; transferring and disseminating the biomedical advances in knowledge and technology acquired through living and working in space to the benefit of mankind in space and on Earth, including the treatment of patients suffering from gravity- and radiation-related conditions on Earth; and ensuring open involvement of the scientific community, industry, and the public at large in the Institute's activities and fostering a robust collaboration with NASA, particularly through Johnson Space Center.

Chitosan: An Update on Potential Biomedical and Pharmaceutical Applications

PubMed Central

Cheung, Randy Chi Fai; Ng, Tzi Bun; Wong, Jack Ho; Chan, Wai Yee

2015-01-01

Chitosan is a natural polycationic linear polysaccharide derived from chitin. The low solubility of chitosan in neutral and alkaline solution limits its application. Nevertheless, chemical modification into composites or hydrogels brings to it new functional properties for different applications. Chitosans are recognized as versatile biomaterials because of their non-toxicity, low allergenicity, biocompatibility and biodegradability. This review presents the recent research, trends and prospects in chitosan. Some special pharmaceutical and biomedical applications are also highlighted. PMID:26287217

Digital fabrication of multi-material biomedical objects.

PubMed

Cheung, H H; Choi, S H

2009-12-01

This paper describes a multi-material virtual prototyping (MMVP) system for modelling and digital fabrication of discrete and functionally graded multi-material objects for biomedical applications. The MMVP system consists of a DMMVP module, an FGMVP module and a virtual reality (VR) simulation module. The DMMVP module is used to model discrete multi-material (DMM) objects, while the FGMVP module is for functionally graded multi-material (FGM) objects. The VR simulation module integrates these two modules to perform digital fabrication of multi-material objects, which can be subsequently visualized and analysed in a virtual environment to optimize MMLM processes for fabrication of product prototypes. Using the MMVP system, two biomedical objects, including a DMM human spine and an FGM intervertebral disc spacer are modelled and digitally fabricated for visualization and analysis in a VR environment. These studies show that the MMVP system is a practical tool for modelling, visualization, and subsequent fabrication of biomedical objects of discrete and functionally graded multi-materials for biomedical applications. The system may be adapted to control MMLM machines with appropriate hardware for physical fabrication of biomedical objects.

Inorganic nanolayers: structure, preparation, and biomedical applications.

PubMed

Saifullah, Bullo; Hussein, Mohd Zobir B

2015-01-01

Hydrotalcite-like compounds are two-dimensional inorganic nanolayers also known as clay minerals or anionic clays or layered double hydroxides/layered hydroxy salts, and have emerged as a single type of material with numerous biomedical applications, such as drug delivery, gene delivery, cosmetics, and biosensing. Inorganic nanolayers are promising materials due to their fascinating properties, such as ease of preparation, ability to intercalate different type of anions (inorganic, organic, biomolecules, and even genes), high thermal stability, delivery of intercalated anions in a sustained manner, high biocompatibility, and easy biodegradation. Inorganic nanolayers have been the focus for researchers over the last decade, resulting in widening application horizons, especially in the field of biomedical science. These nanolayers have been widely applied in drug and gene delivery. They have also been applied in biosensing technology, and most recently in bioimaging science. The suitability of inorganic nanolayers for application in drug delivery, gene delivery, biosensing technology, and bioimaging science makes them ideal materials to be applied for theranostic purposes. In this paper, we review the structure, methods of preparation, and latest advances made by inorganic nanolayers in such biomedical applications as drug delivery, gene delivery, biosensing, and bioimaging.

Inorganic nanolayers: structure, preparation, and biomedical applications

PubMed Central

Saifullah, Bullo; Hussein, Mohd Zobir B

2015-01-01

Hydrotalcite-like compounds are two-dimensional inorganic nanolayers also known as clay minerals or anionic clays or layered double hydroxides/layered hydroxy salts, and have emerged as a single type of material with numerous biomedical applications, such as drug delivery, gene delivery, cosmetics, and biosensing. Inorganic nanolayers are promising materials due to their fascinating properties, such as ease of preparation, ability to intercalate different type of anions (inorganic, organic, biomolecules, and even genes), high thermal stability, delivery of intercalated anions in a sustained manner, high biocompatibility, and easy biodegradation. Inorganic nanolayers have been the focus for researchers over the last decade, resulting in widening application horizons, especially in the field of biomedical science. These nanolayers have been widely applied in drug and gene delivery. They have also been applied in biosensing technology, and most recently in bioimaging science. The suitability of inorganic nanolayers for application in drug delivery, gene delivery, biosensing technology, and bioimaging science makes them ideal materials to be applied for theranostic purposes. In this paper, we review the structure, methods of preparation, and latest advances made by inorganic nanolayers in such biomedical applications as drug delivery, gene delivery, biosensing, and bioimaging. PMID:26366081

Informatics in radiology: radiology gamuts ontology: differential diagnosis for the Semantic Web.

PubMed

Budovec, Joseph J; Lam, Cesar A; Kahn, Charles E

2014-01-01

The Semantic Web is an effort to add semantics, or "meaning," to empower automated searching and processing of Web-based information. The overarching goal of the Semantic Web is to enable users to more easily find, share, and combine information. Critical to this vision are knowledge models called ontologies, which define a set of concepts and formalize the relations between them. Ontologies have been developed to manage and exploit the large and rapidly growing volume of information in biomedical domains. In diagnostic radiology, lists of differential diagnoses of imaging observations, called gamuts, provide an important source of knowledge. The Radiology Gamuts Ontology (RGO) is a formal knowledge model of differential diagnoses in radiology that includes 1674 differential diagnoses, 19,017 terms, and 52,976 links between terms. Its knowledge is used to provide an interactive, freely available online reference of radiology gamuts ( www.gamuts.net ). A Web service allows its content to be discovered and consumed by other information systems. The RGO integrates radiologic knowledge with other biomedical ontologies as part of the Semantic Web. © RSNA, 2014.

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.

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.

Biomedical Applications of Zinc Oxide Nanomaterials

PubMed Central

Zhang, Yin; Nayak, Tapas R.; Hong, Hao; Cai, Weibo

2013-01-01

Nanotechnology has witnessed tremendous advancement over the last several decades. Zinc oxide (ZnO), which can exhibit a wide variety of nanostructures, possesses unique semiconducting, optical, and piezoelectric properties hence has been investigated for a wide variety of applications. One of the most important features of ZnO nanomaterials is low toxicity and biodegradability. Zn2+ is an indispensable trace element for adults (~10 mg of Zn2+ per day is recommended) and it is involved in various aspects of metabolism. Chemically, the surface of ZnO is rich in -OH groups, which can be readily functionalized by various surface decorating molecules. In this review article, we summarized the current status of the use of ZnO nanomaterials for biomedical applications, such as biomedical imaging (which includes fluorescence, magnetic resonance, positron emission tomography, as well as dual-modality imaging), drug delivery, gene delivery, and biosensing of a wide array of molecules of interest. Research in biomedical applications of ZnO nanomaterials will continue to flourish over the next decade, and much research effort will be needed to develop biocompatible/biodegradable ZnO nanoplatforms for potential clinical translation. PMID:24206130

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

GPCR ontology: development and application of a G protein-coupled receptor pharmacology knowledge framework.

PubMed

Przydzial, Magdalena J; Bhhatarai, Barun; Koleti, Amar; Vempati, Uma; Schürer, Stephan C

2013-12-15

Novel tools need to be developed to help scientists analyze large amounts of available screening data with the goal to identify entry points for the development of novel chemical probes and drugs. As the largest class of drug targets, G protein-coupled receptors (GPCRs) remain of particular interest and are pursued by numerous academic and industrial research projects. We report the first GPCR ontology to facilitate integration and aggregation of GPCR-targeting drugs and demonstrate its application to classify and analyze a large subset of the PubChem database. The GPCR ontology, based on previously reported BioAssay Ontology, depicts available pharmacological, biochemical and physiological profiles of GPCRs and their ligands. The novelty of the GPCR ontology lies in the use of diverse experimental datasets linked by a model to formally define these concepts. Using a reasoning system, GPCR ontology offers potential for knowledge-based classification of individuals (such as small molecules) as a function of the data. The GPCR ontology is available at http://www.bioassayontology.org/bao_gpcr and the National Center for Biomedical Ontologies Web site.

42 CFR 52h.1 - Applicability.

Code of Federal Regulations, 2012 CFR

2012-10-01

... reference in this part to grants includes cooperative agreements) for biomedical and behavioral research; and (2) Biomedical and behavioral research and development contract project concepts and proposals for...

42 CFR 52h.1 - Applicability.

Code of Federal Regulations, 2011 CFR

2011-10-01

... reference in this part to grants includes cooperative agreements) for biomedical and behavioral research; and (2) Biomedical and behavioral research and development contract project concepts and proposals for...

42 CFR 52h.1 - Applicability.

Code of Federal Regulations, 2013 CFR

2013-10-01

... reference in this part to grants includes cooperative agreements) for biomedical and behavioral research; and (2) Biomedical and behavioral research and development contract project concepts and proposals for...

42 CFR 52h.1 - Applicability.

Code of Federal Regulations, 2014 CFR

2014-10-01

... reference in this part to grants includes cooperative agreements) for biomedical and behavioral research; and (2) Biomedical and behavioral research and development contract project concepts and proposals for...

Can Andean medicine coexist with biomedical healthcare? A comparison of two rural communities in Peru and Bolivia.

PubMed

Mathez-Stiefel, Sarah-Lan; Vandebroek, Ina; Rist, Stephan

2012-07-24

It is commonly assumed that indigenous medical systems remain strong in developing countries because biomedicine is physically inaccessible or financially not affordable. This paper compares the health-seeking behavior of households from rural Andean communities at a Peruvian and a Bolivian study site. The main research question was whether the increased presence of biomedicine led to a displacement of Andean indigenous medical practices or to coexistence of the two healing traditions. Open-ended interviews and free listing exercises were conducted between June 2006 and December 2008 with 18 households at each study site. Qualitative identification of households' therapeutic strategies and use of remedies was carried out by means of content analysis of interview transcriptions and inductive interference. Furthermore, a quantitative assessment of the incidence of culture-bound illnesses in local ethnobiological inventories was performed. Our findings indicate that the health-seeking behavior of the Andean households in this study is independent of the degree of availability of biomedical facilities in terms of quality of services provided, physical accessibility, and financial affordability, except for specific practices such as childbirth. Preference for natural remedies over pharmaceuticals coexists with biomedical healthcare that is both accessible and affordable. Furthermore, our results show that greater access to biomedicine does not lead to less prevalence of Andean indigenous medical knowledge, as represented by the levels of knowledge about culture-bound illnesses. The take-home lesson for health policy-makers from this study is that the main obstacle to use of biomedicine in resource-poor rural areas might not be infrastructural or economic alone. Rather, it may lie in lack of sufficient recognition by biomedical practitioners of the value and importance of indigenous medical systems. We propose that the implementation of health care in indigenous communities be designed as a process of joint development of complementary knowledge and practices from indigenous and biomedical health traditions.

Can Andean medicine coexist with biomedical healthcare? A comparison of two rural communities in Peru and Bolivia

PubMed Central

2012-01-01

Background It is commonly assumed that indigenous medical systems remain strong in developing countries because biomedicine is physically inaccessible or financially not affordable. This paper compares the health-seeking behavior of households from rural Andean communities at a Peruvian and a Bolivian study site. The main research question was whether the increased presence of biomedicine led to a displacement of Andean indigenous medical practices or to coexistence of the two healing traditions. Methodology Open-ended interviews and free listing exercises were conducted between June 2006 and December 2008 with 18 households at each study site. Qualitative identification of households’ therapeutic strategies and use of remedies was carried out by means of content analysis of interview transcriptions and inductive interference. Furthermore, a quantitative assessment of the incidence of culture-bound illnesses in local ethnobiological inventories was performed. Results Our findings indicate that the health-seeking behavior of the Andean households in this study is independent of the degree of availability of biomedical facilities in terms of quality of services provided, physical accessibility, and financial affordability, except for specific practices such as childbirth. Preference for natural remedies over pharmaceuticals coexists with biomedical healthcare that is both accessible and affordable. Furthermore, our results show that greater access to biomedicine does not lead to less prevalence of Andean indigenous medical knowledge, as represented by the levels of knowledge about culture-bound illnesses. Conclusions The take-home lesson for health policy-makers from this study is that the main obstacle to use of biomedicine in resource-poor rural areas might not be infrastructural or economic alone. Rather, it may lie in lack of sufficient recognition by biomedical practitioners of the value and importance of indigenous medical systems. We propose that the implementation of health care in indigenous communities be designed as a process of joint development of complementary knowledge and practices from indigenous and biomedical health traditions. PMID:22827917

Sensor Fusion and Smart Sensor in Sports and Biomedical Applications.

PubMed

Mendes, José Jair Alves; Vieira, Mário Elias Marinho; Pires, Marcelo Bissi; Stevan, Sergio Luiz

2016-09-23

The following work presents an overview of smart sensors and sensor fusion targeted at biomedical applications and sports areas. In this work, the integration of these areas is demonstrated, promoting a reflection about techniques and applications to collect, quantify and qualify some physical variables associated with the human body. These techniques are presented in various biomedical and sports applications, which cover areas related to diagnostics, rehabilitation, physical monitoring, and the development of performance in athletes, among others. Although some applications are described in only one of two fields of study (biomedicine and sports), it is very likely that the same application fits in both, with small peculiarities or adaptations. To illustrate the contemporaneity of applications, an analysis of specialized papers published in the last six years has been made. In this context, the main characteristic of this review is to present the largest quantity of relevant examples of sensor fusion and smart sensors focusing on their utilization and proposals, without deeply addressing one specific system or technique, to the detriment of the others.

Image cloning beyond diffraction based on coherent population trapping in a hot rubidium vapor.

PubMed

Ding, Dong-Sheng; Zhou, Zhi-Yuan; Shi, Bao-Sen

2014-01-15

Following recent theoretical predictions, we report on an experimental realization of image cloning beyond usual diffraction, through the coherent population trapping (CPT) effect in a hot rubidium vapor. In our experiment, an alphabet letter image was transferred from a coupling field to a probe field, based on the CPT effect. Furthermore, we demonstrate that the cloned probe field carrying the image is transmitted without the usual diffraction. To our best knowledge, this is the first experimental report about image cloning beyond diffraction. We believe this mechanism, based on CPT, has definite and important applications in image metrology, image processing, and biomedical imaging.

LAMDA at TREC CDS track 2015: Clinical Decision Support Track

DTIC Science & Technology

2015-11-20

outperforms all the other vector space models supported by Elasticsearch. MetaMap is the online tool that maps biomedical text to the Metathesaurus, and...cases. The medical knowledge consists of 700,000 biomedical documents supported by the PubMed Central [3] which is online digital database freely...Science Research Program through the National Research Foundation (NRF) of Korea funded by the Ministry of Science, ICT , and Future Planning (MSIP

Micro Electromechanical Systems (MEMS) Based Microfluidic Devices for Biomedical Applications

PubMed Central

Ashraf, Muhammad Waseem; Tayyaba, Shahzadi; Afzulpurkar, Nitin

2011-01-01

Micro Electromechanical Systems (MEMS) based microfluidic devices have gained popularity in biomedicine field over the last few years. In this paper, a comprehensive overview of microfluidic devices such as micropumps and microneedles has been presented for biomedical applications. The aim of this paper is to present the major features and issues related to micropumps and microneedles, e.g., working principles, actuation methods, fabrication techniques, construction, performance parameters, failure analysis, testing, safety issues, applications, commercialization issues and future prospects. Based on the actuation mechanisms, the micropumps are classified into two main types, i.e., mechanical and non-mechanical micropumps. Microneedles can be categorized according to their structure, fabrication process, material, overall shape, tip shape, size, array density and application. The presented literature review on micropumps and microneedles will provide comprehensive information for researchers working on design and development of microfluidic devices for biomedical applications. PMID:21747700

Recent advances in biomedical applications of accelerator mass spectrometry.

PubMed

Hah, Sang Soo; Henderson, Paul T; Turteltaub, Kenneth W

2009-06-17

The use of radioisotopes has a long history in biomedical science, and the technique of accelerator mass spectrometry (AMS), an extremely sensitive nuclear physics technique for detection of very low-abundant, stable and long-lived isotopes, has now revolutionized high-sensitivity isotope detection in biomedical research, because it allows the direct determination of the amount of isotope in a sample rather than measuring its decay, and thus the quantitative analysis of the fate of the radiolabeled probes under the given conditions. Since AMS was first used in the early 90's for the analysis of biological samples containing enriched 14C for toxicology and cancer research, the biomedical applications of AMS to date range from in vitro to in vivo studies, including the studies of 1) toxicant and drug metabolism, 2) neuroscience, 3) pharmacokinetics, and 4) nutrition and metabolism of endogenous molecules such as vitamins. In addition, a new drug development concept that relies on the ultrasensitivity of AMS, known as human microdosing, is being used to obtain early human metabolism information of candidate drugs. These various aspects of AMS are reviewed and a perspective on future applications of AMS to biomedical research is provided.

Recent advances in biomedical applications of accelerator mass spectrometry

PubMed Central

Hah, Sang Soo

2009-01-01

The use of radioisotopes has a long history in biomedical science, and the technique of accelerator mass spectrometry (AMS), an extremely sensitive nuclear physics technique for detection of very low-abundant, stable and long-lived isotopes, has now revolutionized high-sensitivity isotope detection in biomedical research, because it allows the direct determination of the amount of isotope in a sample rather than measuring its decay, and thus the quantitative analysis of the fate of the radiolabeled probes under the given conditions. Since AMS was first used in the early 90's for the analysis of biological samples containing enriched 14C for toxicology and cancer research, the biomedical applications of AMS to date range from in vitro to in vivo studies, including the studies of 1) toxicant and drug metabolism, 2) neuroscience, 3) pharmacokinetics, and 4) nutrition and metabolism of endogenous molecules such as vitamins. In addition, a new drug development concept that relies on the ultrasensitivity of AMS, known as human microdosing, is being used to obtain early human metabolism information of candidate drugs. These various aspects of AMS are reviewed and a perspective on future applications of AMS to biomedical research is provided. PMID:19534792

Biomedical technology transfer applications of NASA science and technology

NASA Technical Reports Server (NTRS)

1972-01-01

The identification and solution of research and clinical problems in cardiovascular medicine which were investigated by means of biomedical data transfer are reported. The following are sample areas that were focused upon by the Stanford University Biomedical Technology Transfer Team: electrodes for hemiplegia research; vectorcardiogram computer analysis; respiration and phonation electrodes; radiotelemetry of intracranial pressure; and audiotransformation of the electrocardiographic signal. It is concluded that this biomedical technology transfer is significantly aiding present research in cardiovascular medicine.

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.

Potential Theranostics Application of Bio-Synthesized Silver Nanoparticles (4-in-1 System)

PubMed Central

Mukherjee, Sudip; Chowdhury, Debabrata; Kotcherlakota, Rajesh; Patra, Sujata; B, Vinothkumar; Bhadra, Manika Pal; Sreedhar, Bojja; Patra, Chitta Ranjan

2014-01-01

In this report, we have designed a simple and efficient green chemistry approach for the synthesis of colloidal silver nanoparticles (b-AgNPs) that is formed by the reduction of silver nitrate (AgNO3) solution using Olax scandens leaf extract. The colloidal b-AgNPs, characterized by various physico-chemical techniques exhibit multifunctional biological activities (4-in-1 system). Firstly, bio-synthesized silver nanoparticles (b-AgNPs) shows enhanced antibacterial activity compared to chemically synthesize silver nanoparticles (c-AgNPs). Secondly, b-AgNPs show anti-cancer activities to different cancer cells (A549: human lung cancer cell lines, B16: mouse melanoma cell line & MCF7: human breast cancer cells) (anti-cancer). Thirdly, these nanoparticles are biocompatible to rat cardiomyoblast normal cell line (H9C2), human umbilical vein endothelial cells (HUVEC) and Chinese hamster ovary cells (CHO) which indicates the future application of b-AgNPs as drug delivery vehicle. Finally, the bio-synthesized AgNPs show bright red fluorescence inside the cells that could be utilized to detect the localization of drug molecules inside the cancer cells (a diagnostic approach). All results together demonstrate the multifunctional biological activities of bio-synthesized AgNPs (4-in-1 system) that could be applied as (i) anti-bacterial & (ii) anti-cancer agent, (iii) drug delivery vehicle, and (iv) imaging facilitator. To the best of our knowledge, there is not a single report of biosynthesized AgNPs that demonstrates the versatile applications (4-in-1 system) towards various biomedical applications. Additionally, a plausible mechanistic approach has been explored for the synthesis of b-AgNPs and its anti-bacterial as well as anti-cancer activity. We strongly believe that bio-synthesized AgNPs will open a new direction towards various biomedical applications in near future. PMID:24505239

Assessment of knowledge about biobanking among healthcare students and their willingness to donate biospecimens.

PubMed

Merdad, Leena; Aldakhil, Lama; Gadi, Rawan; Assidi, Mourad; Saddick, Salina Y; Abuzenadah, Adel; Vaught, Jim; Buhmeida, Abdelbaset; Al-Qahtani, Mohammed H

2017-05-02

Biobanks and biospecimen collections are becoming a primary means of delivering personalized diagnostics and tailoring individualized therapeutics. This shift towards precision medicine (PM) requires interactions among a variety of stakeholders, including the public, patients, healthcare providers, government, and donors. Very few studies have investigated the role of healthcare students in biobanking and biospecimen donations. The main aims of this study were (1) to evaluate the knowledge of senior healthcare students about biobanks and (2) to assess the students' willingness to donate biospecimens and the factors influencing their attitudes. A cross-sectional study was conducted among senior healthcare students at King Abdulaziz University (KAU), Saudi Arabia. The data were obtained using a self-administered questionnaire in English. In addition to the respondents' biographical data section, the questionnaire assessed the respondents' general knowledge about biobanking, the factors influencing their willingness to donate biospecimens to biobanks and their general attitudes towards biomedical research. A total of 597 senior healthcare students were included in the study. The general knowledge score was 3.2 (±1.6) out of 7. Only approximately 44% and 27% of students were aware of the terms "Human Genome Project" (HGP) and "biobank," respectively. The majority of the students (89%) were willing to donate biospecimens to biobanks. Multiple factors were significantly associated with their willingness to donate, including their perceived general health (p < 0.001), past experience with both tissue testing (p < 0.04) and tissue donation (p < 0.001), biobanking knowledge score (p < 0.001) and biomedical research attitude score (p < 0.001). The main reasons for students' willingness to donate were advancement of medical research and societal benefits, whereas misuse of biospecimens and confidentiality breaches were the main reasons for a reluctance to donate. Despite their strong willingness to donate biospecimens, students exhibited a notable lack of knowledge about biobanking and the HGP. To expedite the transition towards PM, it is highly recommended to enhance healthcare curricula by including more educational and awareness programmes to familiarize students with OMICs technologies in addition to the scope of research and clinical applications.

Audacious goals for health and biomedical informatics in the new millennium.

PubMed

Greenes, R A; Lorenzi, N M

1998-01-01

The 1998 Scientific Symposium of the American College of Medical Informatics (ACMI) was devoted to developing visions for the future of health care and biomedicine and a strategic agenda for health and biomedical informatics in support of those visions. This symposium focus was prompted by the many major changes currently underway in health care delivery, education, and research, as well as in our health and biomedical enterprises, and by the constantly increasing role of information technology in both shaping and enabling these changes. The three audacious goals developed for 2008 are a virtual health care databank, a national health care knowledge base, and a personal clinical health record.

The Development of Adaptive Expertise in Biotransport

ERIC Educational Resources Information Center

Martin, Taylor; Petrosino, Anthony J.; Rivale, Stephanie; Diller, Kenneth R.

2006-01-01

This chapter describes a model for continuous development of adaptive expertise, including growth along the dimensions of innovation and knowledge, examined in the context of a biotransport course in biomedical engineering. Students improved on both knowledge and innovation, moving along a continuum toward adaptive expertise. (Contains 5 figures.)

Luminescent nanodiamonds for biomedical applications.

PubMed

Say, Jana M; van Vreden, Caryn; Reilly, David J; Brown, Louise J; Rabeau, James R; King, Nicholas J C

2011-12-01

In recent years, nanodiamonds have emerged from primarily an industrial and mechanical applications base, to potentially underpinning sophisticated new technologies in biomedical and quantum science. Nanodiamonds are relatively inexpensive, biocompatible, easy to surface functionalise and optically stable. This combination of physical properties are ideally suited to biological applications, including intracellular labelling and tracking, extracellular drug delivery and adsorptive detection of bioactive molecules. Here we describe some of the methods and challenges for processing nanodiamond materials, detection schemes and some of the leading applications currently under investigation.

Specialized project in biophotonics

NASA Astrophysics Data System (ADS)

Garcia Martin, Agueda L.; Sastriques-Silva, Pedro O.; Martinez-Fundora, Julia N.; Augier Calderin, Angel G.; Lopez-Cepero, Xonia

2000-06-01

As science advances, it is more evident the necessity of a health interdisciplinary approach in Medicine. In the case of medical applications of light, the knowledge of the use of dispositives, equipment, diagnostic and treatment means, as well as the bases for the use of this update technologies is required. At the present moment, the outstanding work of specialized professionals of different profiles requires personnel with high professional formation in keeping with the latest trends in science and technology. The authors present here an Specialized Project in Biophotonics, with the aim of increasing the professional preparation of university graduates with an ample profile--physicists and engineers--who work in Biomedical Optics, thus contributing to the specialized formation of medic and paramedic personnel. The course is structured into six-subject-modules and into two phases. As to the basic professional formation, each one attending this course, will select between two variants of the Basic Formation Postgraduate Course: Anatomy and Physiology, Physical Bioenergetics, Clinic Bioenergetics; or Physics in Medicine, Optics and Applied Information Theory, depending on the student's professional profile. In the second phase, the General Formation Postgraduate Course: Biomedical Optics, Optical Bioenergetics and Laser in Medicine.

Genetically engineered pigs as models for human disease

PubMed Central

Perleberg, Carolin; Kind, Alexander

2018-01-01

ABSTRACT Genetically modified animals are vital for gaining a proper understanding of disease mechanisms. Mice have long been the mainstay of basic research into a wide variety of diseases but are not always the most suitable means of translating basic knowledge into clinical application. The shortcomings of rodent preclinical studies are widely recognised, and regulatory agencies around the world now require preclinical trial data from nonrodent species. Pigs are well suited to biomedical research, sharing many similarities with humans, including body size, anatomical features, physiology and pathophysiology, and they already play an important role in translational studies. This role is set to increase as advanced genetic techniques simplify the generation of pigs with precisely tailored modifications designed to replicate lesions responsible for human disease. This article provides an overview of the most promising and clinically relevant genetically modified porcine models of human disease for translational biomedical research, including cardiovascular diseases, cancers, diabetes mellitus, Alzheimer's disease, cystic fibrosis and Duchenne muscular dystrophy. We briefly summarise the technologies involved and consider the future impact of recent technical advances. PMID:29419487

An introduction to the Semantic Web for health sciences librarians.

PubMed

Robu, Ioana; Robu, Valentin; Thirion, Benoit

2006-04-01

The paper (1) introduces health sciences librarians to the main concepts and principles of the Semantic Web (SW) and (2) briefly reviews a number of projects on the handling of biomedical information that uses SW technology. The paper is structured into two main parts. "Semantic Web Technology" provides a high-level description, with examples, of the main standards and concepts: extensible markup language (XML), Resource Description Framework (RDF), RDF Schema (RDFS), ontologies, and their utility in information retrieval, concluding with mention of more advanced SW languages and their characteristics. "Semantic Web Applications and Research Projects in the Biomedical Field" is a brief review of the Unified Medical Language System (UMLS), Generalised Architecture for Languages, Encyclopedias and Nomenclatures in Medicine (GALEN), HealthCyberMap, LinkBase, and the thesaurus of the National Cancer Institute (NCI). The paper also mentions other benefits and by-products of the SW, citing projects related to them. Some of the problems facing the SW vision are presented, especially the ways in which the librarians' expertise in organizing knowledge and in structuring information may contribute to SW projects.

Reproducibility of results in preclinical studies: a perspective from the bone field.

PubMed

Manolagas, Stavros C; Kronenberg, Henry M

2014-10-01

The biomedical research enterprise-and the public support for it-is predicated on the belief that discoveries and the conclusions drawn from them can be trusted to build a body of knowledge which will be used to improve human health. As in all other areas of scientific inquiry, knowledge and understanding grow by layering new discoveries upon earlier ones. The process self-corrects and distills knowledge by discarding false ideas and unsubstantiated claims. Although self-correction is inexorable in the long-term, in recent years biomedical scientists and the public alike have become alarmed and deeply troubled by the fact that many published results cannot be reproduced. The chorus of concern reached a high pitch with a recent commentary from the NIH Director, Francis S. Collins, and Principal Deputy Director, Lawrence A. Tabak, and their announcement of specific plans to enhance reproducibility of preclinical research that relies on animal models. In this invited perspective, we highlight the magnitude of the problem across biomedical fields and address the relevance of these concerns to the field of bone and mineral metabolism. We also suggest how our specialty journals, our scientific organizations, and our community of bone and mineral researchers can help to overcome this troubling trend. © 2014 American Society for Bone and Mineral Research.

Comparison of pharmacy students' perceived and actual knowledge using the Pharmacy Curricular Outcomes Assessment.

PubMed

Naughton, Cynthia A; Friesner, Daniel L

2012-05-10

To determine whether a correlation exists between third-year PharmD students' perceived pharmacy knowledge and actual pharmacy knowledge as assessed by the Pharmacy Curricular Outcomes Assessment (PCOA). In 2010 and 2011, the PCOA was administered in a low-stakes environment to third-year pharmacy students at North Dakota State University College of Pharmacy, Nursing, and Allied Sciences (COPNAS). A survey instrument was also administered on which students self-assessed their perceived competencies in each of the core areas covered by the PCOA examination. The pharmacy students rated their competencies slightly higher than average. Performance on the PCOA was similar to but slightly higher than national averages. Correlations between each of the 4 content areas (basic biomedical sciences, pharmaceutical sciences, social/administrative sciences, and clinical sciences) mirrored those reported nationally by the National Association of Boards of Pharmacy (NABP). Student performance on the basic biomedical sciences portion of the PCOA was significantly correlated with students' perceived competencies in the biomedical sciences. No other correlations between actual and perceived competencies were significant. A lack of correlation exists between what students perceive they know and what they actually know in the areas of pharmaceutical science; social, behavioral, and administrative science; and clinical science. Therefore, additional standardized measures are needed to assess curricular effectiveness and provide comparisons among pharmacy programs.