Towards a Unified Approach to Information Integration - A review paper on data/information fusion

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

Whitney, Paul D.; Posse, Christian; Lei, Xingye C.

2005-10-14

Information or data fusion of data from different sources are ubiquitous in many applications, from epidemiology, medical, biological, political, and intelligence to military applications. Data fusion involves integration of spectral, imaging, text, and many other sensor data. For example, in epidemiology, information is often obtained based on many studies conducted by different researchers at different regions with different protocols. In the medical field, the diagnosis of a disease is often based on imaging (MRI, X-Ray, CT), clinical examination, and lab results. In the biological field, information is obtained based on studies conducted on many different species. In military field, informationmore » is obtained based on data from radar sensors, text messages, chemical biological sensor, acoustic sensor, optical warning and many other sources. Many methodologies are used in the data integration process, from classical, Bayesian, to evidence based expert systems. The implementation of the data integration ranges from pure software design to a mixture of software and hardware. In this review we summarize the methodologies and implementations of data fusion process, and illustrate in more detail the methodologies involved in three examples. We propose a unified multi-stage and multi-path mapping approach to the data fusion process, and point out future prospects and challenges.« less

Multidimensional Computerized Adaptive Testing for Indonesia Junior High School Biology

ERIC Educational Resources Information Center

Kuo, Bor-Chen; Daud, Muslem; Yang, Chih-Wei

2015-01-01

This paper describes a curriculum-based multidimensional computerized adaptive test that was developed for Indonesia junior high school Biology. In adherence to the Indonesian curriculum of different Biology dimensions, 300 items was constructed, and then tested to 2238 students. A multidimensional random coefficients multinomial logit model was…

Modeling formalisms in Systems Biology

PubMed Central

2011-01-01

Systems Biology has taken advantage of computational tools and high-throughput experimental data to model several biological processes. These include signaling, gene regulatory, and metabolic networks. However, most of these models are specific to each kind of network. Their interconnection demands a whole-cell modeling framework for a complete understanding of cellular systems. We describe the features required by an integrated framework for modeling, analyzing and simulating biological processes, and review several modeling formalisms that have been used in Systems Biology including Boolean networks, Bayesian networks, Petri nets, process algebras, constraint-based models, differential equations, rule-based models, interacting state machines, cellular automata, and agent-based models. We compare the features provided by different formalisms, and discuss recent approaches in the integration of these formalisms, as well as possible directions for the future. PMID:22141422

Two Project-Based Strategies in an Interdisciplinary Mathematical Modeling in Biology Course

ERIC Educational Resources Information Center

Ludwig, Patrice; Tongen, Anthony; Walton, Brian

2018-01-01

James Madison University faculty team-teach an interdisciplinary mathematical modeling course for mathematics and biology students. We have used two different project-based approaches to emphasize the mathematical concepts taught in class, while also exposing students to new areas of mathematics not formally covered in class. The first method…

Longer leukocyte telomere length in Costa Rica's Nicoyan Peninsula: A population-based study

PubMed Central

Rehkopf, David H; Dow, William H; Rosero-Bixby, Luis; Lin, Jue; Epel, Elissa S; Blackburn, Elizabeth H

2013-01-01

Studies in humans suggest that leukocyte telomere length may act as a marker of biological aging. We investigated whether individuals in the Nicoya region of Costa Rica, known for exceptional longevity, had longer telomere length than those in other parts of the country. After controlling for age, age squared, rurality, rainy season and gender, mean leukocyte telomere length in Nicoya was substantially longer (81 base pairs, p<0.05) than in other areas of Costa Rica, providing evidence of a biological pathway to which this notable longevity may be related. This relationship remains unchanged (79 base pairs, p<0.05) after statistically controlling for nineteen potential biological, dietary and social and demographic mediators. Thus the difference in mean leukocyte telomere length that characterizes this unique region does not appear to be explainable by traditional behavioral and biological risk factors. More detailed examination of mean leukocyte telomere length by age shows that the regional telomere length difference declines at older ages. PMID:23988653

The Generalizability of Students' Interests in Biology Across Gender, Country and Religion

NASA Astrophysics Data System (ADS)

Hagay, G.; Baram-Tsabari, A.; Ametller, J.; Cakmakci, G.; Lopes, B.; Moreira, A.; Pedrosa-de-Jesus, H.

2013-06-01

In order to bridge the existing gap between biology curricula and students' interests in biology, a strategy for identifying students' interest based on their questions and integrating them into the curriculum was developed. To characterize the level of generalizability of students' science interests over 600 high school students from Portugal, Turkey, England and Israel, who chose biology as an advanced subject, their interest level was ranked in 36 questions that were originally raised by Israeli students. Results indicate that students from four different countries show interest in similar science questions. The most intriguing questions were the ones that dealt with human health and new developments in reproduction and genetics. Religious affiliation had the strongest effect on students' interest level, followed by national affiliation and gender. The findings suggest that students' interest in one context is relevant to the development of interest-based learning materials in a different context. However, despite these similarities, cultural and sociological differences need to be taken into account.

Effects of biological sex on the pathophysiology of the heart

PubMed Central

Fazal, Loubina; Azibani, Feriel; Vodovar, Nicolas; Cohen Solal, Alain; Delcayre, Claude; Samuel, Jane-Lise

2014-01-01

Cardiovascular diseases are the leading causes of death in men and women in industrialized countries. While the effects of biological sex on cardiovascular pathophysiology have long been known, the sex-specific mechanisms mediating these processes have been further elucidated over recent years. This review aims at analysing the sex-based differences in cardiac structure and function in adult mammals, and the sex-based differences in the main molecular mechanisms involved in the response of the heart to pathological situations. It emerged from this review that the sex-based difference is a variable that should be dealt with, not only in basic science or clinical research, but also with regards to therapeutic approaches. PMID:23763376

Students Mental Representation of Biology Diagrams/Pictures Conventions Based on Formation of Causal Network

NASA Astrophysics Data System (ADS)

Sampurno, A. W.; Rahmat, A.; Diana, S.

2017-09-01

Diagrams/pictures conventions is one form of visual media that often used to assist students in understanding the biological concepts. The effectiveness of use diagrams/pictures in biology learning at school level has also been mostly reported. This study examines the ability of high school students in reading diagrams/pictures biological convention which is described by Mental Representation based on formation of causal networks. The study involved 30 students 11th grade MIA senior high school Banten Indonesia who are studying the excretory system. MR data obtained by Instrument worksheet, developed based on CNET-protocol, in which there are diagrams/drawings of nephron structure and urinary mechanism. Three patterns formed MR, namely Markov chain, feedback control with a single measurement, and repeated feedback control with multiple measurement. The third pattern is the most dominating pattern, differences in the pattern of MR reveal the difference in how and from which point the students begin to uncover important information contained in the diagram to establish a causal networks. Further analysis shows that a difference in the pattern of MR relate to how complex the students process the information contained in the diagrams/pictures.

Development of the biology card sorting task to measure conceptual expertise in biology.

PubMed

Smith, Julia I; Combs, Elijah D; Nagami, Paul H; Alto, Valerie M; Goh, Henry G; Gourdet, Muryam A A; Hough, Christina M; Nickell, Ashley E; Peer, Adrian G; Coley, John D; Tanner, Kimberly D

2013-01-01

There are widespread aspirations to focus undergraduate biology education on teaching students to think conceptually like biologists; however, there is a dearth of assessment tools designed to measure progress from novice to expert biological conceptual thinking. We present the development of a novel assessment tool, the Biology Card Sorting Task, designed to probe how individuals organize their conceptual knowledge of biology. While modeled on tasks from cognitive psychology, this task is unique in its design to test two hypothesized conceptual frameworks for the organization of biological knowledge: 1) a surface feature organization focused on organism type and 2) a deep feature organization focused on fundamental biological concepts. In this initial investigation of the Biology Card Sorting Task, each of six analytical measures showed statistically significant differences when used to compare the card sorting results of putative biological experts (biology faculty) and novices (non-biology major undergraduates). Consistently, biology faculty appeared to sort based on hypothesized deep features, while non-biology majors appeared to sort based on either surface features or nonhypothesized organizational frameworks. Results suggest that this novel task is robust in distinguishing populations of biology experts and biology novices and may be an adaptable tool for tracking emerging biology conceptual expertise.

Examination of the Regulatory Frameworks Applicable to Biologic Drugs (Including Stem Cells and Their Progeny) in Europe, the U.S., and Australia: Part I—A Method of Manual Documentary Analysis

PubMed Central

Savic, Snezana; Siegel, Evan; Atkinson, Kerry; Tasic, Ljiljana

2012-01-01

Recent development of a wide range of regulatory standards applicable to production and use of tissues, cells, and other biologics (or biologicals), as advanced therapies, indicates considerable interest in the regulation of these products. The objective of this study was to analyze and compare high-tier documents within the Australian, European, and U.S. biologic drug regulatory environments using qualitative methodology. Cohort 1 of the selected 18 high-tier regulatory documents from the European Medicines Agency (EMA), the U.S. Food and Drug Administration (FDA), and the Therapeutic Goods Administration (TGA) regulatory frameworks were subject to a manual documentary analysis. These documents were consistent with the legal requirements for manufacturing and use of biologic drugs in humans and fall into six different categories. Manual analysis included a terminology search. The occurrence, frequency, and interchangeable use of different terms and phrases were recorded in the manual documentary analysis. Despite obvious differences, manual documentary analysis revealed certain consistency in use of terminology across analyzed frameworks. Phrase search frequencies have shown less uniformity than the search of terms. Overall, the EMA framework's documents referred to “medicinal products” and “marketing authorization(s),” the FDA documents discussed “drug(s)” or “biologic(s),” and the TGA documents referred to “biological(s).” Although high-tier documents often use different terminology they share concepts and themes. Documents originating from the same source have more conjunction in their terminology although they belong to different frameworks (i.e., Good Clinical Practice requirements based on the Declaration of Helsinki, 1964). Automated (software-based) documentary analysis should be obtained for the conceptual and relational analysis. PMID:23283551

Automated radiofrequency-based US measurement of common carotid intima-media thickness in RA patients treated with synthetic vs synthetic and biologic DMARDs.

PubMed

Naredo, Esperanza; Möller, Ingrid; Corrales, Alfonso; Bong, David A; Cobo-Ibáñez, Tatiana; Corominas, Hector; Garcia-Vivar, Ma Luz; Macarrón, Pilar; Navio, Teresa; Richi, Patricia; Iagnocco, Annamaria; Garrido, Jesús; Martínez-Hernández, David

2013-02-01

To compare the carotid intima-media thickness (IMT) assessed with automated radiofrequency-based US in RA patients treated with synthetic vs synthetic and biologic DMARDs and controls. Ninety-four RA patients and 94 sex- and age-matched controls were prospectively recruited at seven centres. Cardiovascular (CV) risk factors and co-morbidities, RA characteristics and therapy were recorded. Common carotid artery (CCA)-IMT was assessed in RA patients and controls with automated radiofrequency-based US by the same investigator at each centre. Forty-five (47.9%) RA patients had been treated with synthetic DMARDs and 49 (52.1%) with synthetic and biologic DMARDs. There were no significant differences between the RA patients and controls in demographics, CV co-morbidities and CV disease. There were significantly more smokers among RA patients treated with synthetic and biologic DMARDs (P = 0.036). Disease duration and duration of CS and synthetic DMARD therapy was significantly longer in RA patients treated with synthetic and biologic DMARDs (P < 0.0005). The mean CCA-IMT was significantly greater in RA patients treated only with synthetic DMARDs than in controls [591.4 (98.6) vs 562.1 (85.8); P = 0.035] and in RA patients treated with synthetic and biologic DMARDs [591.4 (98.6) vs 558.8 (95.3); P = 0.040). There was no significant difference between the mean CCA-IMT in RA patients treated with synthetic and biologic DMARDs and controls (P = 0.997). Our results suggest that radiofrequency-based measurement of CCA-IMT can discriminate between RA patients treated with synthetic DMARDs vs RA patients treated with synthetic and biologic DMARDs.

Agent-Based Modeling in Molecular Systems Biology.

PubMed

Soheilypour, Mohammad; Mofrad, Mohammad R K

2018-07-01

Molecular systems orchestrating the biology of the cell typically involve a complex web of interactions among various components and span a vast range of spatial and temporal scales. Computational methods have advanced our understanding of the behavior of molecular systems by enabling us to test assumptions and hypotheses, explore the effect of different parameters on the outcome, and eventually guide experiments. While several different mathematical and computational methods are developed to study molecular systems at different spatiotemporal scales, there is still a need for methods that bridge the gap between spatially-detailed and computationally-efficient approaches. In this review, we summarize the capabilities of agent-based modeling (ABM) as an emerging molecular systems biology technique that provides researchers with a new tool in exploring the dynamics of molecular systems/pathways in health and disease. © 2018 WILEY Periodicals, Inc.

Biology and genetics of human head and body lice.

PubMed

Veracx, Aurélie; Raoult, Didier

2012-12-01

Head lice and body lice have distinct ecologies and differ slightly in morphology and biology, questioning their taxonomic status. Over the past 10 years many genetic studies have been undertaken. Controversial data suggest that not only body lice but also head lice can serve as vectors of Bartonella quintana, and a better understanding of louse epidemiology is crucial. Here, we review taxonomic studies based on biology and genetics, including genomic data on lice, lice endosymbionts, and louse-transmitted bacteria. We recommend that studies of human lice employ morphological and biological characteristics in conjunction with transcriptomic date because lice seem to differ mainly in gene expression (and not in gene content), leading to different phenotypes. Copyright © 2012 Elsevier Ltd. All rights reserved.

Measuring Biological Age via Metabonomics: The Metabolic Age Score.

PubMed

Hertel, Johannes; Friedrich, Nele; Wittfeld, Katharina; Pietzner, Maik; Budde, Kathrin; Van der Auwera, Sandra; Lohmann, Tobias; Teumer, Alexander; Völzke, Henry; Nauck, Matthias; Grabe, Hans Jörgen

2016-02-05

Chronological age is one of the most important risk factors for adverse clinical outcome. Still, two individuals at the same chronological age could have different biological aging states, leading to different individual risk profiles. Capturing this individual variance could constitute an even more powerful predictor enhancing prediction in age-related morbidity. Applying a nonlinear regression technique, we constructed a metabonomic measurement for biological age, the metabolic age score, based on urine data measured via (1)H NMR spectroscopy. We validated the score in two large independent population-based samples by revealing its significant associations with chronological age and age-related clinical phenotypes as well as its independent predictive value for survival over approximately 13 years of follow-up. Furthermore, the metabolic age score was prognostic for weight loss in a sample of individuals who underwent bariatric surgery. We conclude that the metabolic age score is an informative measurement of biological age with possible applications in personalized medicine.

Understanding the effects of different social data on selecting priority conservation areas.

PubMed

Karimi, Azadeh; Tulloch, Ayesha I T; Brown, Greg; Hockings, Marc

2017-12-01

Conservation success is contingent on assessing social and environmental factors so that cost-effective implementation of strategies and actions can be placed in a broad social-ecological context. Until now, the focus has been on how to include spatially explicit social data in conservation planning, whereas the value of different kinds of social data has received limited attention. In a regional systematic conservation planning case study in Australia, we examined the spatial concurrence of a range of spatially explicit social values and land-use preferences collected using a public participation geographic information system and biological data. We used Zonation to integrate the social data with the biological data in a series of spatial-prioritization scenarios to determine the effect of the different types of social data on spatial prioritization compared with biological data alone. The type of social data (i.e., conservation opportunities or constraints) significantly affected spatial prioritization outcomes. The integration of social values and land-use preferences under different scenarios was highly variable and generated spatial prioritizations 1.2-51% different from those based on biological data alone. The inclusion of conservation-compatible values and preferences added relatively few new areas to conservation priorities, whereas including noncompatible economic values and development preferences as costs significantly changed conservation priority areas (48.2% and 47.4%, respectively). Based on our results, a multifaceted conservation prioritization approach that combines spatially explicit social data with biological data can help conservation planners identify the type of social data to collect for more effective and feasible conservation actions. © 2017 Society for Conservation Biology.

Apparent discrimination in the provision of biologic therapy to patients with Crohn's disease according to ethnicity.

PubMed

Farrukh, A; Mayberry, J F

2015-05-01

The objective of the study was to investigate whether patients from a South Asian ethnic background who had Crohn's disease received equivalent access to therapy with biologics compared to patients with an English background. The study was retrospective and covered the period 2008 to 2012. It was based on a register of all patients with Crohn's disease in Leicestershire who are treated with biologics. The prevalence of Crohn's disease in Leicestershire amongst South Asian and English patients was known from earlier studies and from these data it was possible to make corrections to allow for the difference in frequency of the condition between the two communities. All adult patients who received biologics for treatment of Crohn's disease in Leicestershire between 2008 and 2012 were reviewed and their gender and ethnicity noted as well as whether they had received infliximab or adalumimab. The expected numbers of patients who should have received these therapies were calculated in two ways: One hundred and twenty six patients with Crohn's disease who received treatment with biologics were European and 13 South Asian. The patients' gender was also noted and 67 European patients (53%) were female as were six Asians (46%). Based on prevalence data, the expected distribution of the treatment would have been for 97 of the patients to have been European and 42 to have been South Asian. If 126 European patients warranted treatment, on this basis the expected number of South Asian patients in need of biologic therapy would have been 55. Based on the smaller predicted number of South Asian patients (42) the difference is significant at P < 0.0001 [Proportion difference=0.69 (95% confidence interval=0.539278-0.809576]. For the difference to be extinguished the number of English patients who should have received biologic therapy would have been as low as between 30 and 39 cases (based on the calculated proportion of 97 and the actual figure of 126 European patients respectively). Based on a population composition, rather than prevalence data, in which 24% of the Leicester community should have been of South Asian origin, 33 patients would have received biologics compared with 92 patients of English origin (66%). This is significantly different to the 13 patients who did receive treatment (z=-3.2, P < 0.001). Suggested reasons for these differences have included concerns about the animal origins of infliximab as well as difficulties associated with accessing the service, such as the provision of information in an appropriate language through appropriate media. For those who come from groups with significant social deprivation there is often a readiness to accept more limited clinical services. However, such differences themselves, are examples of discrimination in clinical practice. Copyright © 2015 The Royal Society for Public Health. Published by Elsevier Ltd. All rights reserved.

Use artificial neural network to align biological ontologies.

PubMed

Huang, Jingshan; Dang, Jiangbo; Huhns, Michael N; Zheng, W Jim

2008-09-16

Being formal, declarative knowledge representation models, ontologies help to address the problem of imprecise terminologies in biological and biomedical research. However, ontologies constructed under the auspices of the Open Biomedical Ontologies (OBO) group have exhibited a great deal of variety, because different parties can design ontologies according to their own conceptual views of the world. It is therefore becoming critical to align ontologies from different parties. During automated/semi-automated alignment across biological ontologies, different semantic aspects, i.e., concept name, concept properties, and concept relationships, contribute in different degrees to alignment results. Therefore, a vector of weights must be assigned to these semantic aspects. It is not trivial to determine what those weights should be, and current methodologies depend a lot on human heuristics. In this paper, we take an artificial neural network approach to learn and adjust these weights, and thereby support a new ontology alignment algorithm, customized for biological ontologies, with the purpose of avoiding some disadvantages in both rule-based and learning-based aligning algorithms. This approach has been evaluated by aligning two real-world biological ontologies, whose features include huge file size, very few instances, concept names in numerical strings, and others. The promising experiment results verify our proposed hypothesis, i.e., three weights for semantic aspects learned from a subset of concepts are representative of all concepts in the same ontology. Therefore, our method represents a large leap forward towards automating biological ontology alignment.

Learner-Centered Inquiry in Undergraduate Biology: Positive Relationships with Long-Term Student Achievement

PubMed Central

Ebert-May, Diane

2010-01-01

We determined short- and long-term correlates of a revised introductory biology curriculum on understanding of biology as a process of inquiry and learning of content. In the original curriculum students completed two traditional lecture-based introductory courses. In the revised curriculum students completed two new learner-centered, inquiry-based courses. The new courses differed significantly from those of the original curriculum through emphases on critical thinking, collaborative work, and/or inquiry-based activities. Assessments were administered to compare student understanding of the process of biological science and content knowledge in the two curricula. More seniors who completed the revised curriculum had high-level profiles on the Views About Science Survey for Biology compared with seniors who completed the original curriculum. Also as seniors, students who completed the revised curriculum scored higher on the standardized Biology Field Test. Our results showed that an intense inquiry-based learner-centered learning experience early in the biology curriculum was associated with long-term improvements in learning. We propose that students learned to learn science in the new courses which, in turn, influenced their learning in subsequent courses. Studies that determine causal effects of learner-centered inquiry-based approaches, rather than correlative relationships, are needed to test our proposed explanation. PMID:21123693

Effects of biological sex on the pathophysiology of the heart.

PubMed

Fazal, Loubina; Azibani, Feriel; Vodovar, Nicolas; Cohen Solal, Alain; Delcayre, Claude; Samuel, Jane-Lise

2014-02-01

Cardiovascular diseases are the leading causes of death in men and women in industrialized countries. While the effects of biological sex on cardiovascular pathophysiology have long been known, the sex-specific mechanisms mediating these processes have been further elucidated over recent years. This review aims at analysing the sex-based differences in cardiac structure and function in adult mammals, and the sex-based differences in the main molecular mechanisms involved in the response of the heart to pathological situations. It emerged from this review that the sex-based difference is a variable that should be dealt with, not only in basic science or clinical research, but also with regards to therapeutic approaches. © 2013 The British Pharmacological Society.

Multi-level and hybrid modelling approaches for systems biology.

PubMed

Bardini, R; Politano, G; Benso, A; Di Carlo, S

2017-01-01

During the last decades, high-throughput techniques allowed for the extraction of a huge amount of data from biological systems, unveiling more of their underling complexity. Biological systems encompass a wide range of space and time scales, functioning according to flexible hierarchies of mechanisms making an intertwined and dynamic interplay of regulations. This becomes particularly evident in processes such as ontogenesis, where regulative assets change according to process context and timing, making structural phenotype and architectural complexities emerge from a single cell, through local interactions. The information collected from biological systems are naturally organized according to the functional levels composing the system itself. In systems biology, biological information often comes from overlapping but different scientific domains, each one having its own way of representing phenomena under study. That is, the different parts of the system to be modelled may be described with different formalisms. For a model to have improved accuracy and capability for making a good knowledge base, it is good to comprise different system levels, suitably handling the relative formalisms. Models which are both multi-level and hybrid satisfy both these requirements, making a very useful tool in computational systems biology. This paper reviews some of the main contributions in this field.

Network analysis reveals stage-specific changes in zebrafish embryo development using time course whole transcriptome profiling and prior biological knowledge.

PubMed

Zhang, Yuji

2015-01-01

Molecular networks act as the backbone of molecular activities within cells, offering a unique opportunity to better understand the mechanism of diseases. While network data usually constitute only static network maps, integrating them with time course gene expression information can provide clues to the dynamic features of these networks and unravel the mechanistic driver genes characterizing cellular responses. Time course gene expression data allow us to broadly "watch" the dynamics of the system. However, one challenge in the analysis of such data is to establish and characterize the interplay among genes that are altered at different time points in the context of a biological process or functional category. Integrative analysis of these data sources will lead us a more complete understanding of how biological entities (e.g., genes and proteins) coordinately perform their biological functions in biological systems. In this paper, we introduced a novel network-based approach to extract functional knowledge from time-dependent biological processes at a system level using time course mRNA sequencing data in zebrafish embryo development. The proposed method was applied to investigate 1α, 25(OH)2D3-altered mechanisms in zebrafish embryo development. We applied the proposed method to a public zebrafish time course mRNA-Seq dataset, containing two different treatments along four time points. We constructed networks between gene ontology biological process categories, which were enriched in differential expressed genes between consecutive time points and different conditions. The temporal propagation of 1α, 25-Dihydroxyvitamin D3-altered transcriptional changes started from a few genes that were altered initially at earlier stage, to large groups of biological coherent genes at later stages. The most notable biological processes included neuronal and retinal development and generalized stress response. In addition, we also investigated the relationship among biological processes enriched in co-expressed genes under different conditions. The enriched biological processes include translation elongation, nucleosome assembly, and retina development. These network dynamics provide new insights into the impact of 1α, 25-Dihydroxyvitamin D3 treatment in bone and cartilage development. We developed a network-based approach to analyzing the DEGs at different time points by integrating molecular interactions and gene ontology information. These results demonstrate that the proposed approach can provide insight on the molecular mechanisms taking place in vertebrate embryo development upon treatment with 1α, 25(OH)2D3. Our approach enables the monitoring of biological processes that can serve as a basis for generating new testable hypotheses. Such network-based integration approach can be easily extended to any temporal- or condition-dependent genomic data analyses.

Agent-based modelling in synthetic biology.

PubMed

Gorochowski, Thomas E

2016-11-30

Biological systems exhibit complex behaviours that emerge at many different levels of organization. These span the regulation of gene expression within single cells to the use of quorum sensing to co-ordinate the action of entire bacterial colonies. Synthetic biology aims to make the engineering of biology easier, offering an opportunity to control natural systems and develop new synthetic systems with useful prescribed behaviours. However, in many cases, it is not understood how individual cells should be programmed to ensure the emergence of a required collective behaviour. Agent-based modelling aims to tackle this problem, offering a framework in which to simulate such systems and explore cellular design rules. In this article, I review the use of agent-based models in synthetic biology, outline the available computational tools, and provide details on recently engineered biological systems that are amenable to this approach. I further highlight the challenges facing this methodology and some of the potential future directions. © 2016 The Author(s).

Functional networks inference from rule-based machine learning models.

PubMed

Lazzarini, Nicola; Widera, Paweł; Williamson, Stuart; Heer, Rakesh; Krasnogor, Natalio; Bacardit, Jaume

2016-01-01

Functional networks play an important role in the analysis of biological processes and systems. The inference of these networks from high-throughput (-omics) data is an area of intense research. So far, the similarity-based inference paradigm (e.g. gene co-expression) has been the most popular approach. It assumes a functional relationship between genes which are expressed at similar levels across different samples. An alternative to this paradigm is the inference of relationships from the structure of machine learning models. These models are able to capture complex relationships between variables, that often are different/complementary to the similarity-based methods. We propose a protocol to infer functional networks from machine learning models, called FuNeL. It assumes, that genes used together within a rule-based machine learning model to classify the samples, might also be functionally related at a biological level. The protocol is first tested on synthetic datasets and then evaluated on a test suite of 8 real-world datasets related to human cancer. The networks inferred from the real-world data are compared against gene co-expression networks of equal size, generated with 3 different methods. The comparison is performed from two different points of view. We analyse the enriched biological terms in the set of network nodes and the relationships between known disease-associated genes in a context of the network topology. The comparison confirms both the biological relevance and the complementary character of the knowledge captured by the FuNeL networks in relation to similarity-based methods and demonstrates its potential to identify known disease associations as core elements of the network. Finally, using a prostate cancer dataset as a case study, we confirm that the biological knowledge captured by our method is relevant to the disease and consistent with the specialised literature and with an independent dataset not used in the inference process. The implementation of our network inference protocol is available at: http://ico2s.org/software/funel.html.

DaGO-Fun: tool for Gene Ontology-based functional analysis using term information content measures.

PubMed

Mazandu, Gaston K; Mulder, Nicola J

2013-09-25

The use of Gene Ontology (GO) data in protein analyses have largely contributed to the improved outcomes of these analyses. Several GO semantic similarity measures have been proposed in recent years and provide tools that allow the integration of biological knowledge embedded in the GO structure into different biological analyses. There is a need for a unified tool that provides the scientific community with the opportunity to explore these different GO similarity measure approaches and their biological applications. We have developed DaGO-Fun, an online tool available at http://web.cbio.uct.ac.za/ITGOM, which incorporates many different GO similarity measures for exploring, analyzing and comparing GO terms and proteins within the context of GO. It uses GO data and UniProt proteins with their GO annotations as provided by the Gene Ontology Annotation (GOA) project to precompute GO term information content (IC), enabling rapid response to user queries. The DaGO-Fun online tool presents the advantage of integrating all the relevant IC-based GO similarity measures, including topology- and annotation-based approaches to facilitate effective exploration of these measures, thus enabling users to choose the most relevant approach for their application. Furthermore, this tool includes several biological applications related to GO semantic similarity scores, including the retrieval of genes based on their GO annotations, the clustering of functionally related genes within a set, and term enrichment analysis.

Genetic and molecular bases of yield-associated traits: a translational biology approach between rice and wheat.

PubMed

Valluru, Ravi; Reynolds, Matthew P; Salse, Jerome

2014-07-01

Transferring the knowledge bases between related species may assist in enlarging the yield potential of crop plants. Being cereals, rice and wheat share a high level of gene conservation; however, they differ at metabolic levels as a part of the environmental adaptation resulting in different yield capacities. This review focuses on the current understanding of genetic and molecular regulation of yield-associated traits in both crop species, highlights the similarities and differences and presents the putative knowledge gaps. We focus on the traits associated with phenology, photosynthesis, and assimilate partitioning and lodging resistance; the most important drivers of yield potential. Currently, there are large knowledge gaps in the genetic and molecular control of such major biological processes that can be filled in a translational biology approach in transferring genomics and genetics informations between rice and wheat.

Development of the Biology Card Sorting Task to Measure Conceptual Expertise in Biology

PubMed Central

Smith, Julia I.; Combs, Elijah D.; Nagami, Paul H.; Alto, Valerie M.; Goh, Henry G.; Gourdet, Muryam A. A.; Hough, Christina M.; Nickell, Ashley E.; Peer, Adrian G.; Coley, John D.; Tanner, Kimberly D.

2013-01-01

There are widespread aspirations to focus undergraduate biology education on teaching students to think conceptually like biologists; however, there is a dearth of assessment tools designed to measure progress from novice to expert biological conceptual thinking. We present the development of a novel assessment tool, the Biology Card Sorting Task, designed to probe how individuals organize their conceptual knowledge of biology. While modeled on tasks from cognitive psychology, this task is unique in its design to test two hypothesized conceptual frameworks for the organization of biological knowledge: 1) a surface feature organization focused on organism type and 2) a deep feature organization focused on fundamental biological concepts. In this initial investigation of the Biology Card Sorting Task, each of six analytical measures showed statistically significant differences when used to compare the card sorting results of putative biological experts (biology faculty) and novices (non–biology major undergraduates). Consistently, biology faculty appeared to sort based on hypothesized deep features, while non–biology majors appeared to sort based on either surface features or nonhypothesized organizational frameworks. Results suggest that this novel task is robust in distinguishing populations of biology experts and biology novices and may be an adaptable tool for tracking emerging biology conceptual expertise. PMID:24297290

Biological hydrogels as selective diffusion barriers.

PubMed

Lieleg, Oliver; Ribbeck, Katharina

2011-09-01

The controlled exchange of molecules between organelles, cells, or organisms and their environment is crucial for life. Biological gels such as mucus, the extracellular matrix (ECM), and the biopolymer barrier within the nuclear pore are well suited to achieve such a selective exchange, allowing passage of particular molecules while rejecting many others. Although hydrogel-based filters are integral parts of biology, clear concepts of how their barrier function is controlled at a microscopic level are still missing. We summarize here our current understanding of how selective filtering is established by different biopolymer-based hydrogels. We ask if the modulation of microscopic particle transport in biological hydrogels is based on a generic filtering principle which employs biochemical/biophysical interactions with the filtered molecules rather than size-exclusion effects. Copyright © 2011 Elsevier Ltd. All rights reserved.

The Effects of 3D Computer Simulation on Biology Students' Achievement and Memory Retention

ERIC Educational Resources Information Center

Elangovan, Tavasuria; Ismail, Zurida

2014-01-01

A quasi experimental study was conducted for six weeks to determine the effectiveness of two different 3D computer simulation based teaching methods, that is, realistic simulation and non-realistic simulation on Form Four Biology students' achievement and memory retention in Perak, Malaysia. A sample of 136 Form Four Biology students in Perak,…

New approaches to estimation of peat deposits for production of biologically active compounds

NASA Astrophysics Data System (ADS)

Stepchenko, L. M.; Yurchenko, V. I.; Krasnik, V. G.; Syedykh, N. J.

2009-04-01

It is known, that biologically active preparations from peat increase animals productivity as well as resistance against stress-factors and have adaptogeneous, antioxidant, immunomodulative properties. Optymal choice of peat deposits for the production of biologically active preparations supposes the detailed comparative analysis of peat properties from different deposits. For this the cadastre of peat of Ukraine is developed in the humic substances laboratory named after prof. Khristeva L.A. (Dnipropetrovsk Agrarian University, Ukraine). It based on the research of its physical and chemical properties, toxicity and biological activity, and called Biocadastre. The Biocadastre is based on the set of parameters, including the descriptions of physical and chemical properties (active acidity, degree of decomposition, botanical composition etc.), toxicity estimation (by parabyotyc, infusorial, inhibitor and other tests), biological activity indexes (growth-promoting, antioxidative, adaptogeneous, immunomodulative antistress and other actions). The blocks of Biocadastre indexes are differentiated, taking into account their use for creation the preparations for vegetable, animals and microorganisms. The Biocadastre will allow to choose the peat deposits, most suitable for the production of different biologically active preparations, both wide directed and narrow spectrum of action, depending on application fields (medicine, agriculture, veterinary medicine, microbiological industry, balneology, cosmetology).

Practical Strategies for Collaboration across Discipline-Based Education Research and the Learning Sciences.

PubMed

Peffer, Melanie; Renken, Maggie

Rather than pursue questions related to learning in biology from separate camps, recent calls highlight the necessity of interdisciplinary research agendas. Interdisciplinary collaborations allow for a complicated and expanded approach to questions about learning within specific science domains, such as biology. Despite its benefits, interdisciplinary work inevitably involves challenges. Some such challenges originate from differences in theoretical and methodological approaches across lines of work. Thus, aims at developing successful interdisciplinary research programs raise important considerations regarding methodologies for studying biology learning, strategies for approaching collaborations, and training of early-career scientists. Our goal here is to describe two fields important to understanding learning in biology, discipline-based education research and the learning sciences. We discuss differences between each discipline's approach to biology education research and the benefits and challenges associated with incorporating these perspectives in a single research program. We then propose strategies for building productive interdisciplinary collaboration. © 2016 M. Peffer and M. Renken. CBE—Life Sciences Education © 2016 The American Society for Cell Biology. This article is distributed by The American Society for Cell Biology under license from the author(s). It is available to the public under an Attribution–Noncommercial–Share Alike 3.0 Unported Creative Commons License (http://creativecommons.org/licenses/by-nc-sa/3.0).

Racing of the biological pacemaker.

PubMed

Yu, Han-Gang

2009-01-01

Over the past decade, rapid progress in the molecular studies of cardiac ion channels and stem cells biology has led to efforts to create a biological pacemaker to supplement the widely-used electronic pacemaker. We will review the main concepts of cardiac pacemaker activities in different heart regions and the approaches to design a working biological pacemaker. We will focus on how to use the gene- and cell-based approaches to meet the requirements of a working biological pacemaker. Possible future development and precautions for creation of an effective biological pacemaker superior to the electronic counterpart are also discussed along with recent patents.

Revolution of Alzheimer Precision Neurology Passageway of Systems Biology and Neurophysiology.

PubMed

Hampel, Harald; Toschi, Nicola; Babiloni, Claudio; Baldacci, Filippo; Black, Keith L; Bokde, Arun L W; Bun, René S; Cacciola, Francesco; Cavedo, Enrica; Chiesa, Patrizia A; Colliot, Olivier; Coman, Cristina-Maria; Dubois, Bruno; Duggento, Andrea; Durrleman, Stanley; Ferretti, Maria-Teresa; George, Nathalie; Genthon, Remy; Habert, Marie-Odile; Herholz, Karl; Koronyo, Yosef; Koronyo-Hamaoui, Maya; Lamari, Foudil; Langevin, Todd; Lehéricy, Stéphane; Lorenceau, Jean; Neri, Christian; Nisticò, Robert; Nyasse-Messene, Francis; Ritchie, Craig; Rossi, Simone; Santarnecchi, Emiliano; Sporns, Olaf; Verdooner, Steven R; Vergallo, Andrea; Villain, Nicolas; Younesi, Erfan; Garaci, Francesco; Lista, Simone

2018-03-16

The Precision Neurology development process implements systems theory with system biology and neurophysiology in a parallel, bidirectional research path: a combined hypothesis-driven investigation of systems dysfunction within distinct molecular, cellular, and large-scale neural network systems in both animal models as well as through tests for the usefulness of these candidate dynamic systems biomarkers in different diseases and subgroups at different stages of pathophysiological progression. This translational research path is paralleled by an "omics"-based, hypothesis-free, exploratory research pathway, which will collect multimodal data from progressing asymptomatic, preclinical, and clinical neurodegenerative disease (ND) populations, within the wide continuous biological and clinical spectrum of ND, applying high-throughput and high-content technologies combined with powerful computational and statistical modeling tools, aimed at identifying novel dysfunctional systems and predictive marker signatures associated with ND. The goals are to identify common biological denominators or differentiating classifiers across the continuum of ND during detectable stages of pathophysiological progression, characterize systems-based intermediate endophenotypes, validate multi-modal novel diagnostic systems biomarkers, and advance clinical intervention trial designs by utilizing systems-based intermediate endophenotypes and candidate surrogate markers. Achieving these goals is key to the ultimate development of early and effective individualized treatment of ND, such as Alzheimer's disease. The Alzheimer Precision Medicine Initiative (APMI) and cohort program (APMI-CP), as well as the Paris based core of the Sorbonne University Clinical Research Group "Alzheimer Precision Medicine" (GRC-APM) were recently launched to facilitate the passageway from conventional clinical diagnostic and drug development toward breakthrough innovation based on the investigation of the comprehensive biological nature of aging individuals. The APMI movement is gaining momentum to systematically apply both systems neurophysiology and systems biology in exploratory translational neuroscience research on ND.

Revolution of Alzheimer Precision Neurology: Passageway of Systems Biology and Neurophysiology

PubMed Central

Hampel, Harald; Toschi, Nicola; Babiloni, Claudio; Baldacci, Filippo; Black, Keith L.; Bokde, Arun L.W.; Bun, René S.; Cacciola, Francesco; Cavedo, Enrica; Chiesa, Patrizia A.; Colliot, Olivier; Coman, Cristina-Maria; Dubois, Bruno; Duggento, Andrea; Durrleman, Stanley; Ferretti, Maria-Teresa; George, Nathalie; Genthon, Remy; Habert, Marie-Odile; Herholz, Karl; Koronyo, Yosef; Koronyo-Hamaoui, Maya; Lamari, Foudil; Langevin, Todd; Lehéricy, Stéphane; Lorenceau, Jean; Neri, Christian; Nisticò, Robert; Nyasse-Messene, Francis; Ritchie, Craig; Rossi, Simone; Santarnecchi, Emiliano; Sporns, Olaf; Verdooner, Steven R.; Vergallo, Andrea; Villain, Nicolas; Younesi, Erfan; Garaci, Francesco; Lista, Simone

2018-01-01

The Precision Neurology development process implements systems theory with system biology and neurophysiology in a parallel, bidirectional research path: a combined hypothesis-driven investigation of systems dysfunction within distinct molecular, cellular and large-scale neural network systems in both animal models as well as through tests for the usefulness of these candidate dynamic systems biomarkers in different diseases and subgroups at different stages of pathophysiological progression. This translational research path is paralleled by an “omics”-based, hypothesis-free, exploratory research pathway, which will collect multimodal data from progressing asymptomatic, preclinical and clinical neurodegenerative disease (ND) populations, within the wide continuous biological and clinical spectrum of ND, applying high-throughput and high-content technologies combined with powerful computational and statistical modeling tools, aimed at identifying novel dysfunctional systems and predictive marker signatures associated with ND. The goals are to identify common biological denominators or differentiating classifiers across the continuum of ND during detectable stages of pathophysiological progression, characterize systems-based intermediate endophenotypes, validate multi-modal novel diagnostic systems biomarkers, and advance clinical intervention trial designs by utilizing systems-based intermediate endophenotypes and candidate surrogate markers. Achieving these goals is key to the ultimate development of early and effective individualized treatment of ND, such as Alzheimer’s disease (AD). The Alzheimer Precision Medicine Initiative (APMI) and cohort program (APMI-CP), as well as the Paris based core of the Sorbonne University Clinical Research Group “Alzheimer Precision Medicine” (GRC-APM) were recently launched to facilitate the passageway from conventional clinical diagnostic and drug development towards breakthrough innovation based on the investigation of the comprehensive biological nature of aging individuals. The APMI movement is gaining momentum to systematically apply both systems neurophysiology and systems biology in exploratory translational neuroscience research on ND. PMID:29562524

Modular analysis of biological networks.

PubMed

Kaltenbach, Hans-Michael; Stelling, Jörg

2012-01-01

The analysis of complex biological networks has traditionally relied on decomposition into smaller, semi-autonomous units such as individual signaling pathways. With the increased scope of systems biology (models), rational approaches to modularization have become an important topic. With increasing acceptance of de facto modularity in biology, widely different definitions of what constitutes a module have sparked controversies. Here, we therefore review prominent classes of modular approaches based on formal network representations. Despite some promising research directions, several important theoretical challenges remain open on the way to formal, function-centered modular decompositions for dynamic biological networks.

How Many Kingdoms? Current Views of Biological Classification.

ERIC Educational Resources Information Center

Margulis, Lynn

1981-01-01

Argues for the acceptance and use of a five-kingdom classification system for biology comprised of monera, protoctista, fungi, animals, and plants. Justifies the new system based upon the difference between prokaryotes and eukaryotes. Outlines each kingdom and describes its members. (DC)

The Genetics of Sex Differences in Brain and Behavior

PubMed Central

Ngun, Tuck C; Ghahramani, Negar; Sánchez, Francisco J.; Bocklandt, Sven; Vilain, Eric

2010-01-01

Biological differences between men and women contribute to many sex-specific illnesses and disorders. Historically, it was argued that such differences were largely, if not exclusively, due to gonadal hormone secretions. However, emerging research has shown that some differences are mediated by mechanisms other than the action of these hormone secretions and in particular by products of genes located on the X and Y chromosomes, which we refer to as direct genetic effects. This paper reviews the evidence for direct genetic effects in behavioral and brain sex differences. We highlight the `four core genotypes' model and sex differences in the midbrain dopaminergic system, specifically focusing on the role of Sry. We also discuss novel research being done on unique populations including people attracted to the same sex and people with a cross-gender identity. As science continues to advance our understanding of biological sex differences, a new field is emerging that is aimed at better addressing the needs of both sexes: gender-based biology and medicine. Ultimately, the study of the biological basis for sex differences will improve healthcare for both men and women. PMID:20951723

Systematic Biological Filter Design with a Desired I/O Filtering Response Based on Promoter-RBS Libraries.

PubMed

Hsu, Chih-Yuan; Pan, Zhen-Ming; Hu, Rei-Hsing; Chang, Chih-Chun; Cheng, Hsiao-Chun; Lin, Che; Chen, Bor-Sen

2015-01-01

In this study, robust biological filters with an external control to match a desired input/output (I/O) filtering response are engineered based on the well-characterized promoter-RBS libraries and a cascade gene circuit topology. In the field of synthetic biology, the biological filter system serves as a powerful detector or sensor to sense different molecular signals and produces a specific output response only if the concentration of the input molecular signal is higher or lower than a specified threshold. The proposed systematic design method of robust biological filters is summarized into three steps. Firstly, several well-characterized promoter-RBS libraries are established for biological filter design by identifying and collecting the quantitative and qualitative characteristics of their promoter-RBS components via nonlinear parameter estimation method. Then, the topology of synthetic biological filter is decomposed into three cascade gene regulatory modules, and an appropriate promoter-RBS library is selected for each module to achieve the desired I/O specification of a biological filter. Finally, based on the proposed systematic method, a robust externally tunable biological filter is engineered by searching the promoter-RBS component libraries and a control inducer concentration library to achieve the optimal reference match for the specified I/O filtering response.

XML-based approaches for the integration of heterogeneous bio-molecular data.

PubMed

Mesiti, Marco; Jiménez-Ruiz, Ernesto; Sanz, Ismael; Berlanga-Llavori, Rafael; Perlasca, Paolo; Valentini, Giorgio; Manset, David

2009-10-15

The today's public database infrastructure spans a very large collection of heterogeneous biological data, opening new opportunities for molecular biology, bio-medical and bioinformatics research, but raising also new problems for their integration and computational processing. In this paper we survey the most interesting and novel approaches for the representation, integration and management of different kinds of biological data by exploiting XML and the related recommendations and approaches. Moreover, we present new and interesting cutting edge approaches for the appropriate management of heterogeneous biological data represented through XML. XML has succeeded in the integration of heterogeneous biomolecular information, and has established itself as the syntactic glue for biological data sources. Nevertheless, a large variety of XML-based data formats have been proposed, thus resulting in a difficult effective integration of bioinformatics data schemes. The adoption of a few semantic-rich standard formats is urgent to achieve a seamless integration of the current biological resources.

Formal reasoning about systems biology using theorem proving

PubMed Central

Hasan, Osman; Siddique, Umair; Tahar, Sofiène

2017-01-01

System biology provides the basis to understand the behavioral properties of complex biological organisms at different levels of abstraction. Traditionally, analysing systems biology based models of various diseases have been carried out by paper-and-pencil based proofs and simulations. However, these methods cannot provide an accurate analysis, which is a serious drawback for the safety-critical domain of human medicine. In order to overcome these limitations, we propose a framework to formally analyze biological networks and pathways. In particular, we formalize the notion of reaction kinetics in higher-order logic and formally verify some of the commonly used reaction based models of biological networks using the HOL Light theorem prover. Furthermore, we have ported our earlier formalization of Zsyntax, i.e., a deductive language for reasoning about biological networks and pathways, from HOL4 to the HOL Light theorem prover to make it compatible with the above-mentioned formalization of reaction kinetics. To illustrate the usefulness of the proposed framework, we present the formal analysis of three case studies, i.e., the pathway leading to TP53 Phosphorylation, the pathway leading to the death of cancer stem cells and the tumor growth based on cancer stem cells, which is used for the prognosis and future drug designs to treat cancer patients. PMID:28671950

Biosimilars: biologics that meet patients' needs and healthcare economics.

PubMed

McCamish, Mark; Yoon, William; McKay, James

2016-09-01

Biologics have revolutionized medical care, yet uniform access to these effective medicines remains difficult due to the increasing costs of healthcare. As patent exclusivity on the early biologics wanes, regulatory and legal systems are adapting to bring competition to the field in the form of biosimilars. Biosimilars are biologics that offer the same clinical benefit in one or more of the same indications as the reference biologic drug and bring competition to the biologics space. Legislation creating a pathway resulting in the first US approvals of biosimilars has been in place since 2010, but the regulatory methodology and science of evaluating the sameness of two biologics has been in use for decades. The demonstration of biosimilarity is based on the "totality of the evidence" concept, in which all structural, functional, nonclinical, and clinical data for a biosimilar product are evaluated to show high similarity to the reference product. Clinical trials for biosimilars, therefore, are designed to confirm similarity, or discover clinically relevant differences between the reference product and the biosimilar, should differences exist. It is hoped that competition from biosimilars will drive biologic innovation and increase patient access to biologics.

Nation-Based Occurrence and Endogenous Biological Reduction of Mycotoxins in Medicinal Herbs and Spices.

PubMed

Do, Kee Hun; An, Tae Jin; Oh, Sang-Keun; Moon, Yuseok

2015-10-14

Medicinal herbs have been increasingly used for therapeutic purposes against a diverse range of human diseases worldwide. Moreover, the health benefits of spices have been extensively recognized in recent studies. However, inevitable contaminants, including mycotoxins, in medicinal herbs and spices can cause serious problems for humans in spite of their health benefits. Along with the different nation-based occurrences of mycotoxins, the ultimate exposure and toxicities can be diversely influenced by the endogenous food components in different commodities of the medicinal herbs and spices. The phytochemicals in these food stuffs can influence mold growth, mycotoxin production and biological action of the mycotoxins in exposed crops, as well as in animal and human bodies. The present review focuses on the occurrence of mycotoxins in medicinal herbs and spices and the biological interaction between mold, mycotoxin and herbal components. These networks will provide insights into the methods of mycotoxin reduction and toxicological risk assessment of mycotoxin-contaminated medicinal food components in the environment and biological organisms.

Nation-Based Occurrence and Endogenous Biological Reduction of Mycotoxins in Medicinal Herbs and Spices

PubMed Central

Do, Kee Hun; An, Tae Jin; Oh, Sang-Keun; Moon, Yuseok

2015-01-01

Medicinal herbs have been increasingly used for therapeutic purposes against a diverse range of human diseases worldwide. Moreover, the health benefits of spices have been extensively recognized in recent studies. However, inevitable contaminants, including mycotoxins, in medicinal herbs and spices can cause serious problems for humans in spite of their health benefits. Along with the different nation-based occurrences of mycotoxins, the ultimate exposure and toxicities can be diversely influenced by the endogenous food components in different commodities of the medicinal herbs and spices. The phytochemicals in these food stuffs can influence mold growth, mycotoxin production and biological action of the mycotoxins in exposed crops, as well as in animal and human bodies. The present review focuses on the occurrence of mycotoxins in medicinal herbs and spices and the biological interaction between mold, mycotoxin and herbal components. These networks will provide insights into the methods of mycotoxin reduction and toxicological risk assessment of mycotoxin-contaminated medicinal food components in the environment and biological organisms. PMID:26473926

DaGO-Fun: tool for Gene Ontology-based functional analysis using term information content measures

PubMed Central

2013-01-01

Background The use of Gene Ontology (GO) data in protein analyses have largely contributed to the improved outcomes of these analyses. Several GO semantic similarity measures have been proposed in recent years and provide tools that allow the integration of biological knowledge embedded in the GO structure into different biological analyses. There is a need for a unified tool that provides the scientific community with the opportunity to explore these different GO similarity measure approaches and their biological applications. Results We have developed DaGO-Fun, an online tool available at http://web.cbio.uct.ac.za/ITGOM, which incorporates many different GO similarity measures for exploring, analyzing and comparing GO terms and proteins within the context of GO. It uses GO data and UniProt proteins with their GO annotations as provided by the Gene Ontology Annotation (GOA) project to precompute GO term information content (IC), enabling rapid response to user queries. Conclusions The DaGO-Fun online tool presents the advantage of integrating all the relevant IC-based GO similarity measures, including topology- and annotation-based approaches to facilitate effective exploration of these measures, thus enabling users to choose the most relevant approach for their application. Furthermore, this tool includes several biological applications related to GO semantic similarity scores, including the retrieval of genes based on their GO annotations, the clustering of functionally related genes within a set, and term enrichment analysis. PMID:24067102

A multimodal imaging platform with integrated simultaneous photoacoustic microscopy, optical coherence tomography, optical Doppler tomography and fluorescence microscopy

NASA Astrophysics Data System (ADS)

Dadkhah, Arash; Zhou, Jun; Yeasmin, Nusrat; Jiao, Shuliang

2018-02-01

Various optical imaging modalities with different optical contrast mechanisms have been developed over the past years. Although most of these imaging techniques are being used in many biomedical applications and researches, integration of these techniques will allow researchers to reach the full potential of these technologies. Nevertheless, combining different imaging techniques is always challenging due to the difference in optical and hardware requirements for different imaging systems. Here, we developed a multimodal optical imaging system with the capability of providing comprehensive structural, functional and molecular information of living tissue in micrometer scale. This imaging system integrates photoacoustic microscopy (PAM), optical coherence tomography (OCT), optical Doppler tomography (ODT) and fluorescence microscopy in one platform. Optical-resolution PAM (OR-PAM) provides absorption-based imaging of biological tissues. Spectral domain OCT is able to provide structural information based on the scattering property of biological sample with no need for exogenous contrast agents. In addition, ODT is a functional extension of OCT with the capability of measurement and visualization of blood flow based on the Doppler effect. Fluorescence microscopy allows to reveal molecular information of biological tissue using autofluoresce or exogenous fluorophores. In-vivo as well as ex-vivo imaging studies demonstrated the capability of our multimodal imaging system to provide comprehensive microscopic information on biological tissues. Integrating all the aforementioned imaging modalities for simultaneous multimodal imaging has promising potential for preclinical research and clinical practice in the near future.

Functional proteomic analysis revealed ground-base ion radiations cannot reflect biological effects of space radiations of rice

NASA Astrophysics Data System (ADS)

Wang, Wei; Sun, Yeqing; Zhao, Qian; Han, Lu

2016-07-01

Highly ionizing radiation (HZE) in space is considered as main factor causing biological effects. Radiobiological studies during space flights are unrepeatable due to the variable space radiation environment, ground-base ion radiations are usually performed to simulate of the space biological effect. Spaceflights present a low-dose rate (0.1˜~0.3mGy/day) radiation environment inside aerocrafts while ground-base ion radiations present a much higher dose rate (100˜~500mGy/min). Whether ground-base ion radiation can reflect effects of space radiation is worth of evaluation. In this research, we compared the functional proteomic profiles of rice plants between on-ground simulated HZE particle radiation and spaceflight treatments. Three independent ground-base seed ionizing radiation experiments with different cumulative doses (dose range: 2˜~20000mGy) and different liner energy transfer (LET) values (13.3˜~500keV/μμm) and two independent seed spaceflight experiments onboard Chinese 20th satellite and SZ-6 spacecraft were carried out. Alterations in the proteome were analyzed by two-dimensional difference gel electrophoresis (2-D DIGE) with MALDI-TOF/TOF mass spectrometry identifications. 45 and 59 proteins showed significant (p<0.05) and reproducible quantitative differences in ground-base ion radiation and spaceflight experiments respectively. The functions of ground-base radiation and spaceflight proteins were both involved in a wide range of biological processes. Gene Ontology enrichment analysis further revealed that ground-base radiation responsive proteins were mainly involved in removal of superoxide radicals, defense response to stimulus and photosynthesis, while spaceflight responsive proteins mainly participate in nucleoside metabolic process, protein folding and phosphorylation. The results implied that ground-base radiations cannot truly reflect effects of spaceflight radiations, ground-base radiation was a kind of indirect effect to rice causing oxidation and metabolism stresses, but space radiation was a kind of direct effect leading to macromolecule (DNA and protein) damage and signal pathway disorders. This functional proteomic analysis work might provide a new evaluation method for further on-ground simulated HZE radiation experiments.

Computing biological functions using BioΨ, a formal description of biological processes based on elementary bricks of actions

PubMed Central

Pérès, Sabine; Felicori, Liza; Rialle, Stéphanie; Jobard, Elodie; Molina, Franck

2010-01-01

Motivation: In the available databases, biological processes are described from molecular and cellular points of view, but these descriptions are represented with text annotations that make it difficult to handle them for computation. Consequently, there is an obvious need for formal descriptions of biological processes. Results: We present a formalism that uses the BioΨ concepts to model biological processes from molecular details to networks. This computational approach, based on elementary bricks of actions, allows us to calculate on biological functions (e.g. process comparison, mapping structure–function relationships, etc.). We illustrate its application with two examples: the functional comparison of proteases and the functional description of the glycolysis network. This computational approach is compatible with detailed biological knowledge and can be applied to different kinds of systems of simulation. Availability: www.sysdiag.cnrs.fr/publications/supplementary-materials/BioPsi_Manager/ Contact: sabine.peres@sysdiag.cnrs.fr; franck.molina@sysdiag.cnrs.fr Supplementary information: Supplementary data are available at Bioinformatics online. PMID:20448138

Metabolic cancer biology: structural-based analysis of cancer as a metabolic disease, new sights and opportunities for disease treatment.

PubMed

Masoudi-Nejad, Ali; Asgari, Yazdan

2015-02-01

The cancer cell metabolism or the Warburg effect discovery goes back to 1924 when, for the first time Otto Warburg observed, in contrast to the normal cells, cancer cells have different metabolism. With the initiation of high throughput technologies and computational systems biology, cancer cell metabolism renaissances and many attempts were performed to revise the Warburg effect. The development of experimental and analytical tools which generate high-throughput biological data including lots of information could lead to application of computational models in biological discovery and clinical medicine especially for cancer. Due to the recent availability of tissue-specific reconstructed models, new opportunities in studying metabolic alteration in various kinds of cancers open up. Structural approaches at genome-scale levels seem to be suitable for developing diagnostic and prognostic molecular signatures, as well as in identifying new drug targets. In this review, we have considered these recent advances in structural-based analysis of cancer as a metabolic disease view. Two different structural approaches have been described here: topological and constraint-based methods. The ultimate goal of this type of systems analysis is not only the discovery of novel drug targets but also the development of new systems-based therapy strategies. Copyright © 2014 Elsevier Ltd. All rights reserved.

A Test of Biological and Behavioral Explanations for Gender Differences in Telomere Length: The Multi-Ethnic Study of Atherosclerosis

PubMed Central

NEEDHAM, BELINDA L.; DIEZ ROUX, ANA V.; BIRD, CHLOE E.; BRADLEY, RYAN; FITZPATRICK, ANNETTE L.; JACOBS, DAVID R.; OUYANG, PAMELA; SEEMAN, TERESA E.; THURSTON, REBECCA C.; VAIDYA, DHANANJAY; WANG, STEVEN

2015-01-01

The purpose of this study was to examine biological and behavioral explanations for gender differences in leukocyte telomere length (LTL), a biomarker of cell aging that has been hypothesized to contribute to women’s greater longevity. Data are from a subsample (n = 851) of the Multi-Ethnic Study of Atherosclerosis, a population-based study of women and men aged 45 to 84. Mediation models were used to examine study hypotheses. We found that women had longer LTL than men, but the gender difference was smaller at older ages. Gender differences in smoking and processed meat consumption partially mediated gender differences in telomere length, whereas gender differences in estradiol, total testosterone, oxidative stress, and body mass index did not. Neither behavioral nor biological factors explained why the gender difference in LTL was smaller at older ages. Longitudinal studies are needed to assess gender differences in the rate of change in LTL over time; to identify the biological, behavioral, and psychosocial factors that contribute to these differences throughout the life course; and to determine whether gender differences in LTL explain the gender gap in longevity. PMID:25343364

A test of biological and behavioral explanations for gender differences in telomere length: the multi-ethnic study of atherosclerosis.

PubMed

Needham, Belinda L; Diez Roux, Ana V; Bird, Chloe E; Bradley, Ryan; Fitzpatrick, Annette L; Jacobs, David R; Ouyang, Pamela; Seeman, Teresa E; Thurston, Rebecca C; Vaidya, Dhananjay; Wang, Steven

2014-01-01

The purpose of this study was to examine biological and behavioral explanations for gender differences in leukocyte telomere length (LTL), a biomarker of cell aging that has been hypothesized to contribute to women's greater longevity. Data are from a subsample (n = 851) of the Multi-Ethnic Study of Atherosclerosis, a population-based study of women and men aged 45 to 84. Mediation models were used to examine study hypotheses. We found that women had longer LTL than men, but the gender difference was smaller at older ages. Gender differences in smoking and processed meat consumption partially mediated gender differences in telomere length, whereas gender differences in estradiol, total testosterone, oxidative stress, and body mass index did not. Neither behavioral nor biological factors explained why the gender difference in LTL was smaller at older ages. Longitudinal studies are needed to assess gender differences in the rate of change in LTL over time; to identify the biological, behavioral, and psychosocial factors that contribute to these differences throughout the life course; and to determine whether gender differences in LTL explain the gender gap in longevity.

Comparison of Student Achievement Using Didactic, Inquiry-Based, and the Combination of Two Approaches of Science Instruction

NASA Astrophysics Data System (ADS)

Foster, Hyacinth Carmen

Science educators and administrators support the idea that inquiry-based and didactic-based instructional strategies have varying effects on students' acquisition of science concepts. The research problem addressed whether incorporating the two approaches covered the learning requirements of all students in science classes, enabling them to meet state and national standards. The purpose of this quasiexperimental, posttest design research study was to determine if student learning and achievement in high school biology classes differed for each type of instructional method. Constructivism theory suggested that each learner creates knowledge over time because of the learners' interactions with the environment. The optimal teaching method, didactic (teacher-directed), inquiry-based, or a combination of two approaches instructional method, becomes essential if students are to discover ways to learn information. The research question examined which form of instruction had a significant effect on student achievement in biology. The data analysis consisted of single-factor, independent-measures analysis of variance (ANOVA) that tested the hypotheses of the research study. Locally, the results indicated greater and statistically significant differences in standardized laboratory scores for students who were taught using the combination of two approaches. Based on these results, biology instructors will gain new insights into ways of improving the instructional process. Social change may occur as the science curriculum leadership applies the combination of two instructional approaches to improve acquisition of science concepts by biology students.

The quest for a new modelling framework in mathematical biology. Comment on "On the interplay between mathematics and biology: Hallmarks towards a new systems biology" by N. Bellomo et al.

NASA Astrophysics Data System (ADS)

Eftimie, Raluca

2015-03-01

One of the main unsolved problems of modern physics is finding a "theory of everything" - a theory that can explain, with the help of mathematics, all physical aspects of the universe. While the laws of physics could explain some aspects of the biology of living systems (e.g., the phenomenological interpretation of movement of cells and animals), there are other aspects specific to biology that cannot be captured by physics models. For example, it is generally accepted that the evolution of a cell-based system is influenced by the activation state of cells (e.g., only activated and functional immune cells can fight diseases); on the other hand, the evolution of an animal-based system can be influenced by the psychological state (e.g., distress) of animals. Therefore, the last 10-20 years have seen also a quest for a "theory of everything"-approach extended to biology, with researchers trying to propose mathematical modelling frameworks that can explain various biological phenomena ranging from ecology to developmental biology and medicine [1,2,6]. The basic idea behind this approach can be found in a few reviews on ecology and cell biology [6,7,9-11], where researchers suggested that due to the parallel between the micro-scale dynamics and the emerging macro-scale phenomena in both cell biology and in ecology, many mathematical methods used for ecological processes could be adapted to cancer modelling [7,9] or to modelling in immunology [11]. However, this approach generally involved the use of different models to describe different biological aspects (e.g., models for cell and animal movement, models for competition between cells or animals, etc.).

PROPER: global protein interaction network alignment through percolation matching.

PubMed

Kazemi, Ehsan; Hassani, Hamed; Grossglauser, Matthias; Pezeshgi Modarres, Hassan

2016-12-12

The alignment of protein-protein interaction (PPI) networks enables us to uncover the relationships between different species, which leads to a deeper understanding of biological systems. Network alignment can be used to transfer biological knowledge between species. Although different PPI-network alignment algorithms were introduced during the last decade, developing an accurate and scalable algorithm that can find alignments with high biological and structural similarities among PPI networks is still challenging. In this paper, we introduce a new global network alignment algorithm for PPI networks called PROPER. Compared to other global network alignment methods, our algorithm shows higher accuracy and speed over real PPI datasets and synthetic networks. We show that the PROPER algorithm can detect large portions of conserved biological pathways between species. Also, using a simple parsimonious evolutionary model, we explain why PROPER performs well based on several different comparison criteria. We highlight that PROPER has high potential in further applications such as detecting biological pathways, finding protein complexes and PPI prediction. The PROPER algorithm is available at http://proper.epfl.ch .

Two years comparative studies on biological effects of environmental UV radiation

NASA Astrophysics Data System (ADS)

Grof, P.; Ronto, Gyorgyi; Gaspar, S.; Berces, A.; Szabo, Laszlo D.

1994-07-01

A method has been developed for determination of the biologically effective UV dose based on T7 phage as biosensor. In field experiments clockwork driven telescope has been used for determining doses from direct and global (direct plus diffuse) solar radiation. On fine summer days at mid-latitude this arrangement allowed the following comparisons: measured doses from direct and global radiation obtained at the same time and measuring site reflecting the biological importance of diffuse radiation; direct and global radiation obtained at the same time and measuring site reflecting the biological importance of diffuse radiation; direct and global doses obtained at the same time on different measuring sites (downtown, suburb, outside the town) reflecting the differences caused by air quality; direct and global doses obtained on the same measuring place, in summertime of two different years reflecting the importance of the long-term measurements for estimating the biological risk caused by increased UV-B radiation; measured data and model calculations.

Promoting new concepts of skincare via skinomics and systems biology-From traditional skincare and efficacy-based skincare to precision skincare.

PubMed

Jiang, Biao; Jia, Yan; He, Congfen

2018-05-11

Traditional skincare involves the subjective classification of skin into 4 categories (oily, dry, mixed, and neutral) prior to skin treatment. Following the development of noninvasive methods in skin and skin imaging technology, scientists have developed efficacy-based skincare products based on the physiological characteristics of skin under different conditions. Currently, the emergence of skinomics and systems biology has facilitated the development of precision skincare. In this article, the evolution of skincare based on the physiological states of the skin (from traditional skincare and efficacy-based skincare to precision skincare) is described. In doing so, we highlight skinomics and systems biology, with particular emphasis on the importance of skin lipidomics and microbiomes in precision skincare. The emerging trends of precision skincare are anticipated. © 2018 Wiley Periodicals, Inc.

Biological features of hepatitis B virus isolates from patients based on full-length genomic analysis.

PubMed

Wen, Yu-Mei; Wang, Yong-Xiang

2009-01-01

The mechanisms for HBV persistence and the pathogenesis of chronic HB have been shown mainly due to defects in host immune responses. However, HBV isolates with different biological features may also contribute to different clinical outcomes and epidemiological implications in viral hepatitis B (HB). This review presents interesting biological features of HBV isolates based on the structural and functional analysis of full-length HBV isolates from various patients. Among isolates from children after failure of HB vaccination, 129L mutant at the 'a' determinant was found with normal binding efficiency to anti-HBs, but with reduced immunogenicity, which could initiate persistent HBV infections. Isolates from fulminant hepatitis (FH) B patients were not all highly replicative, but differences in capacities of anti-HBs induction could be involved in the pathogenesis of FH. The high replicative competency of isolates from hepatocellular carcinoma (HCC) patients could result in enhanced immune-mediated cytopathic effects against HBV viral proteins, and increased transactivating activity by the X protein. The mechanism of a double-spliced variant in enhancing replication of the wild-type virus is presented. The importance of integrating structural and functional analysis to reveal biological features of HBV isolates in viral pathogenesis is discussed.

Therapeutic Strategies against Cyclin E1-Amplified Ovarian Cancers

DTIC Science & Technology

2017-10-01

Ph.D. CONTRACTING ORGANIZATION: The Wistar Institute of Anatomy & Biology Philadelphia, PA 19104 REPORT DATE: October 2017 TYPE OF REPORT: Annual...ORGANIZATION NAME(S) AND ADDRESS(ES) 8. PERFORMING ORGANIZATION REPORT NUMBER The Wistar Institute of Anatomy & Biology 3601 Spruce Street Philadelphia, PA...ovarian cancers that address different aspects of CCNE1 biology . In the first aim, based on our preliminary data, we hypothesize that HSP90

WE-D-BRE-07: Variance-Based Sensitivity Analysis to Quantify the Impact of Biological Uncertainties in Particle Therapy

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

Kamp, F.; Brueningk, S.C.; Wilkens, J.J.

Purpose: In particle therapy, treatment planning and evaluation are frequently based on biological models to estimate the relative biological effectiveness (RBE) or the equivalent dose in 2 Gy fractions (EQD2). In the context of the linear-quadratic model, these quantities depend on biological parameters (α, β) for ions as well as for the reference radiation and on the dose per fraction. The needed biological parameters as well as their dependency on ion species and ion energy typically are subject to large (relative) uncertainties of up to 20–40% or even more. Therefore it is necessary to estimate the resulting uncertainties in e.g.more » RBE or EQD2 caused by the uncertainties of the relevant input parameters. Methods: We use a variance-based sensitivity analysis (SA) approach, in which uncertainties in input parameters are modeled by random number distributions. The evaluated function is executed 10{sup 4} to 10{sup 6} times, each run with a different set of input parameters, randomly varied according to their assigned distribution. The sensitivity S is a variance-based ranking (from S = 0, no impact, to S = 1, only influential part) of the impact of input uncertainties. The SA approach is implemented for carbon ion treatment plans on 3D patient data, providing information about variations (and their origin) in RBE and EQD2. Results: The quantification enables 3D sensitivity maps, showing dependencies of RBE and EQD2 on different input uncertainties. The high number of runs allows displaying the interplay between different input uncertainties. The SA identifies input parameter combinations which result in extreme deviations of the result and the input parameter for which an uncertainty reduction is the most rewarding. Conclusion: The presented variance-based SA provides advantageous properties in terms of visualization and quantification of (biological) uncertainties and their impact. The method is very flexible, model independent, and enables a broad assessment of uncertainties. Supported by DFG grant WI 3745/1-1 and DFG cluster of excellence: Munich-Centre for Advanced Photonics.« less

Studies on the toxic effects of pentachlorophenol on the biological activity of anaerobic granular sludge.

PubMed

Liu, Xin-Wen; He, Ruo; Shen, Dong-Sheng

2008-09-01

In order to explore the pathway of the anaerobic biotreatment of the wastewater containing pentachlorophenol (PCP) and ensure the normal operation of Upflow Anaerobic Sludge Blanket (UASB) reactor, the anaerobic sludge under different acclimation conditions were selected to seed and start up UASB reactors. Anaerobic toxicity assays were employed to study the biological activity, the tolerance and the capacity to degrade PCP of different anaerobic granular sludge from UASB reactors. Results showed that the anaerobic granular sludge acclimated to chlorophenols (CPs) could degrade PCP more quickly (up to 9.50mg-PCP g(-1)TVS d(-1)). And the anaerobic granular sludge without acclimation to CPs had only a little activity of degrading PCP (less than 0.07 mg-PCP g(-1)TVS d(-1)). Different PCP concentrations (2, 4, 6, 8 mg L(-1)) had different inhibition effects on glucose utilization, volatile fatted acidity (VFA)-degrading and methanogens activity of PCP degradation anaerobic granular sludge, and the biological activity declined with the increase in PCP concentration. The methanogens activity suffered inhibition from PCP more easily. The different acclimation patterns of seeded sludge had distinctly different effects on biological activity of the degradation of PCP of anaerobic granular sludge from UASB reactors. The biological activity of the anaerobic granular sludge acclimated to PCP only was also inhibited. This inhibition was weak compared to that of anaerobic granular sludge acclimated to CPs, further, the activity could recover more quickly in this case. In the same reactor, the anaerobic granular sludge from the mid and base layers showed higher tolerance to PCP than that from super layer or if the sludge is unacclimated to CPs, and the corresponding recovery time of the biological activity in the mid and base layers were short. Acetate-utilizing methanogens and syntrophic propinate degraders were sensitive to PCP, compared to syntrophic butyrate degraders.

A multiple index integrating different levels of organization.

PubMed

Cortes, Rui; Hughes, Samantha; Coimbra, Ana; Monteiro, Sandra; Pereira, Vítor; Lopes, Marisa; Pereira, Sandra; Pinto, Ana; Sampaio, Ana; Santos, Cátia; Carrola, João; de Jesus, Joaquim; Varandas, Simone

2016-10-01

Many methods in freshwater biomonitoring tend to be restricted to a few levels of biological organization, limiting the potential spectrum of measurable of cause-effect responses to different anthropogenic impacts. We combined distinct organisational levels, covering biological biomarkers (histopathological and biochemical reactions in liver and fish gills), community based bioindicators (fish guilds, invertebrate metrics/traits and chironomid pupal exuviae) and ecosystem functional indicators (decomposition rates) to assess ecological status at designated Water Framework Directive monitoring sites, covering a gradient of human impact across several rivers in northern Portugal. We used Random Forest to rank the variables that contributed more significantly to successfully predict the different classes of ecological status and also to provide specific cut levels to discriminate each WFD class based on reference condition. A total of 59 Biological Quality Elements and functional indicators were determined using this procedure and subsequently applied to develop the integrated Multiple Ecological Level Index (MELI Index), a potentially powerful bioassessment tool. Copyright © 2016 Elsevier Inc. All rights reserved.

Room temperature preparation of fluorescent starch nanoparticles from starch-dopamine conjugates and their biological applications.

PubMed

Shi, Yingge; Xu, Dazhuang; Liu, Meiying; Fu, Lihua; Wan, Qing; Mao, Liucheng; Dai, Yanfeng; Wen, Yuanqing; Zhang, Xiaoyong; Wei, Yen

2018-01-01

Fluorescent organic nanoparticles (FONs) have been regarded as the promising candidates for biomedical applications owing to their well adjustment of chemical structure and optical properties and good biological properties. However, the preparation of FONs from the natural derived polymers has been rarely reported thus far. In current work, we reported a novel strategy for preparation of FONs based on the self-polymerization of starch-dopamine conjugates and polyethyleneimine in rather mild experimental conditions, including air atmosphere, aqueous solution, absent catalysts and at room temperature. The morphology, chemical structure and optical properties of the resultant starch-based FONs were investigated by different characterization techniques. Biological evaluation results demonstrated that these starch-based FONs possess good biocompatibility and fluorescent imaging performance. More importantly, the novel strategy might also be extended for the preparation of many other carbohydrate polymers based FONs with different structure and functions. Therefore, this work opens a new avenue for the preparation and biomedical applications of luminescent carbohydrate polymers. Copyright © 2017 Elsevier B.V. All rights reserved.

Methods for biological data integration: perspectives and challenges

PubMed Central

Gligorijević, Vladimir; Pržulj, Nataša

2015-01-01

Rapid technological advances have led to the production of different types of biological data and enabled construction of complex networks with various types of interactions between diverse biological entities. Standard network data analysis methods were shown to be limited in dealing with such heterogeneous networked data and consequently, new methods for integrative data analyses have been proposed. The integrative methods can collectively mine multiple types of biological data and produce more holistic, systems-level biological insights. We survey recent methods for collective mining (integration) of various types of networked biological data. We compare different state-of-the-art methods for data integration and highlight their advantages and disadvantages in addressing important biological problems. We identify the important computational challenges of these methods and provide a general guideline for which methods are suited for specific biological problems, or specific data types. Moreover, we propose that recent non-negative matrix factorization-based approaches may become the integration methodology of choice, as they are well suited and accurate in dealing with heterogeneous data and have many opportunities for further development. PMID:26490630

Promoting a structural view of biology for varied audiences: an overview of RCSB PDB resources and experiences.

PubMed

Dutta, Shuchismita; Zardecki, Christine; Goodsell, David S; Berman, Helen M

2010-10-01

The Research Collaboratory for Structural Bioinformatics Protein Data Bank (RCSB PDB) supports scientific research and education worldwide by providing an essential resource of information on biomolecular structures. In addition to serving as a deposition, data-processing and distribution center for PDB data, the RCSB PDB offers resources and online materials that different audiences can use to customize their structural biology instruction. These include resources for general audiences that present macromolecular structure in the context of a biological theme, method-based materials for researchers who take a more traditional approach to the presentation of structural science, and materials that mix theme-based and method-based approaches for educators and students. Through these efforts the RCSB PDB aims to enable optimal use of structural data by researchers, educators and students designing and understanding experiments in biology, chemistry and medicine, and by general users making informed decisions about their life and health.

Function-Based Algorithms for Biological Sequences

ERIC Educational Resources Information Center

Mohanty, Pragyan Sheela P.

2015-01-01

Two problems at two different abstraction levels of computational biology are studied. At the molecular level, efficient pattern matching algorithms in DNA sequences are presented. For gene order data, an efficient data structure is presented capable of storing all gene re-orderings in a systematic manner. A common characteristic of presented…

The Various Forms of Neuroplasticity: Biological Bases of Learning and Teaching

ERIC Educational Resources Information Center

Tovar-Moll, Fernanda; Lent, Roberto

2016-01-01

Education is a socially structured form of learning. It involves the brains of different players--students, teachers, family members, and others--in permanent interaction. The biological set of mechanisms by which these brains receive, encode, store, and retrieve mutually exchanged information is called "neuroplasticity". This is the…

Knowledge Driven Variable Selection (KDVS) – a new approach to enrichment analysis of gene signatures obtained from high–throughput data

PubMed Central

2013-01-01

Background High–throughput (HT) technologies provide huge amount of gene expression data that can be used to identify biomarkers useful in the clinical practice. The most frequently used approaches first select a set of genes (i.e. gene signature) able to characterize differences between two or more phenotypical conditions, and then provide a functional assessment of the selected genes with an a posteriori enrichment analysis, based on biological knowledge. However, this approach comes with some drawbacks. First, gene selection procedure often requires tunable parameters that affect the outcome, typically producing many false hits. Second, a posteriori enrichment analysis is based on mapping between biological concepts and gene expression measurements, which is hard to compute because of constant changes in biological knowledge and genome analysis. Third, such mapping is typically used in the assessment of the coverage of gene signature by biological concepts, that is either score–based or requires tunable parameters as well, limiting its power. Results We present Knowledge Driven Variable Selection (KDVS), a framework that uses a priori biological knowledge in HT data analysis. The expression data matrix is transformed, according to prior knowledge, into smaller matrices, easier to analyze and to interpret from both computational and biological viewpoints. Therefore KDVS, unlike most approaches, does not exclude a priori any function or process potentially relevant for the biological question under investigation. Differently from the standard approach where gene selection and functional assessment are applied independently, KDVS embeds these two steps into a unified statistical framework, decreasing the variability derived from the threshold–dependent selection, the mapping to the biological concepts, and the signature coverage. We present three case studies to assess the usefulness of the method. Conclusions We showed that KDVS not only enables the selection of known biological functionalities with accuracy, but also identification of new ones. An efficient implementation of KDVS was devised to obtain results in a fast and robust way. Computing time is drastically reduced by the effective use of distributed resources. Finally, integrated visualization techniques immediately increase the interpretability of results. Overall, KDVS approach can be considered as a viable alternative to enrichment–based approaches. PMID:23302187

FMM: a web server for metabolic pathway reconstruction and comparative analysis.

PubMed

Chou, Chih-Hung; Chang, Wen-Chi; Chiu, Chih-Min; Huang, Chih-Chang; Huang, Hsien-Da

2009-07-01

Synthetic Biology, a multidisciplinary field, is growing rapidly. Improving the understanding of biological systems through mimicry and producing bio-orthogonal systems with new functions are two complementary pursuits in this field. A web server called FMM (From Metabolite to Metabolite) was developed for this purpose. FMM can reconstruct metabolic pathways form one metabolite to another metabolite among different species, based mainly on the Kyoto Encyclopedia of Genes and Genomes (KEGG) database and other integrated biological databases. Novel presentation for connecting different KEGG maps is newly provided. Both local and global graphical views of the metabolic pathways are designed. FMM has many applications in Synthetic Biology and Metabolic Engineering. For example, the reconstruction of metabolic pathways to produce valuable metabolites or secondary metabolites in bacteria or yeast is a promising strategy for drug production. FMM provides a highly effective way to elucidate the genes from which species should be cloned into those microorganisms based on FMM pathway comparative analysis. Consequently, FMM is an effective tool for applications in synthetic biology to produce both drugs and biofuels. This novel and innovative resource is now freely available at http://FMM.mbc.nctu.edu.tw/.

The Analysis of Certain Differences in Motor Skills of Sedentary Male Children in the 9-14 Age Group Based on the Biological Maturity

ERIC Educational Resources Information Center

Bayraktar, Isik; Yaman, Nigar; Zorba, Erdal; Yaman, Metin; Günay, Mehmet

2016-01-01

The aim of this study consists of the analysis of certain differences in motor skills of male children who are sedentary and in the age group of 9-14, in relation to the biological maturity. 522 sedentary male children from various parts of Turkey participated in this study. Body height and body weight measurements were taken from the participants…

Participation in introductory biology laboratories: An integrated assessment based on surveys, behavioral observations, and qualitative interviews

NASA Astrophysics Data System (ADS)

Russell, Connie Adelle

Scope and method of study. The purpose of this study was to evaluate the effect of gender, major, and prior knowledge of and attitude toward biology on participation in introductory biology laboratories. Subjects for this study were 3,527 students enrolled in college-level introductory biology courses. During the study, three introductory courses were replaced with one mixed-majors course. The new course adopted a different pedagological approach from the previous courses in that an inquiry-based approach was used in lectures and laboratories. All subjects completed a survey that measured content knowledge using the NABT/NSTA High School Biology Examination Version 1990 and attitude using Russell and Hollander's Biology Attitude Scale. I used and discuss the merits of using ethological methods and data collection software, EthoScribeTM (Tima Scientific) to collect behavioral data from 145 students. I also evaluated participation using qualitative interviews of 30 students. I analyzed content knowledge and attitude data using ANOVA and Pearson correlation, and behavioral data using Contingency Table Analysis. I analyzed interviews following methods outlined by Rubin and Rubin. Findings. Course style and gender were the most useful variables in distinguishing differences among groups of students with regard to attitude, content knowledge, and participation in laboratories. Attitude toward biology and achievement measured by the surveys were found to be positively correlated; however, gender, major, class standing, course style and interactions between these variables also had effects on these variables. I found a positive association among attitude, achievement and participation in hands-on activities in laboratories. Differences in participation also were associated group type. In a traditional introductory biology course, females in single-gender groups, gender-equal, or groups in which females were the majority spent more time performing hands-on science-related activities than did females in groups in which they were the minority. Conversely, males in mixed-gender groups spent more time performing hands-on activities than did males in single-gender groups. Both sexes participated equally in laboratories taught in an inquiry-based style.

Introducing DNA concepts to Swiss high school students based on a Brazilian educational game.

PubMed

da S Cardona, Tânia; Spiegel, Carolina N; Alves, Gutemberg G; Ducommun, Jacques; Henriques-Pons, Andrea; Araújo-Jorge, Tania C

2007-11-01

Subjects such as techniques for genetic diagnosis, cloning, sequencing, and gene therapy are now part of our lives and raise important questions about ethics, future medical diagnosis, and such. Students from different countries observe this explosion of biotechnological applications regardless of their social, academic, or cultural backgrounds, although they are not usually familiar with their theoretical genetic bases. To introduce some molecular biology concepts for high school students, we developed a new problem for the Brazilian board game "Discovering the cell" ("Célula Adentro©" in Portuguese), a pedagogic tool based on inquiry-, cooperative-, and problem-based learning. This problem (Case) is based on the forensic DNA, which represents an interesting theme for students, as it recurrently appears on newspapers and television series. In this work, we tested this game with secondary students and teachers from Switzerland. Our results indicate that the game "Discovering the cell" is well accepted by both students and teachers and may represent a good pedagogical approach to help teaching complex themes in molecular biology, even with students from different socioeconomical, cultural, and academic backgrounds. Copyright © 2007 International Union of Biochemistry and Molecular Biology, Inc.

Overview of chemical imaging methods to address biological questions.

PubMed

da Cunha, Marcel Menezes Lyra; Trepout, Sylvain; Messaoudi, Cédric; Wu, Ting-Di; Ortega, Richard; Guerquin-Kern, Jean-Luc; Marco, Sergio

2016-05-01

Chemical imaging offers extensive possibilities for better understanding of biological systems by allowing the identification of chemical components at the tissue, cellular, and subcellular levels. In this review, we introduce modern methods for chemical imaging that can be applied to biological samples. This work is mainly addressed to the biological sciences community and includes the bases of different technologies, some examples of its application, as well as an introduction to approaches on combining multimodal data. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

Light microscopy applications in systems biology: opportunities and challenges

PubMed Central

2013-01-01

Biological systems present multiple scales of complexity, ranging from molecules to entire populations. Light microscopy is one of the least invasive techniques used to access information from various biological scales in living cells. The combination of molecular biology and imaging provides a bottom-up tool for direct insight into how molecular processes work on a cellular scale. However, imaging can also be used as a top-down approach to study the behavior of a system without detailed prior knowledge about its underlying molecular mechanisms. In this review, we highlight the recent developments on microscopy-based systems analyses and discuss the complementary opportunities and different challenges with high-content screening and high-throughput imaging. Furthermore, we provide a comprehensive overview of the available platforms that can be used for image analysis, which enable community-driven efforts in the development of image-based systems biology. PMID:23578051

Biological attachment devices: exploring nature's diversity for biomimetics.

PubMed

Gorb, Stanislav N

2008-05-13

Many species of animals and plants are supplied with diverse attachment devices, in which morphology depends on the species biology and the particular function in which the attachment device is involved. Many functional solutions have evolved independently in different lineages of animals and plants. Since the diversity of such biological structures is huge, there is a need for their classification. This paper, based on the original and literature data, proposes ordering of biological attachment systems according to several principles: (i) fundamental physical mechanism, according to which the system operates, (ii) biological function of the attachment device, and (iii) duration of the contact. Finally, we show a biomimetic potential of studies on biological attachment devices.

Coupling biology and oceanography in models.

PubMed

Fennel, W; Neumann, T

2001-08-01

The dynamics of marine ecosystems, i.e. the changes of observable chemical-biological quantities in space and time, are driven by biological and physical processes. Predictions of future developments of marine systems need a theoretical framework, i.e. models, solidly based on research and understanding of the different processes involved. The natural way to describe marine systems theoretically seems to be the embedding of chemical-biological models into circulation models. However, while circulation models are relatively advanced the quantitative theoretical description of chemical-biological processes lags behind. This paper discusses some of the approaches and problems in the development of consistent theories and indicates the beneficial potential of the coupling of marine biology and oceanography in models.

Factors Affecting Participation in Traditional and Inquiry-based Laboratories.

ERIC Educational Resources Information Center

Russell, Connie P.; French, Donald P.

2002-01-01

Reports on a study of participation, achievement, and attitude in cookbook and inquiry-based introductory biology laboratories through observations, interviews, and attitude/knowledge surveys. Participation differences between men and women disappeared in the inquiry-based laboratory. (Author/MM)

Standoff laser-induced fluorescence of suspensions from different bacterial strains

NASA Astrophysics Data System (ADS)

Duschek, Frank; Walter, Arne; Fellner, Lea; Grünewald, Karin; Pargmann, Carsten; Handke, Jürgen; Tomaso, Herbert

2016-10-01

Biological hazardous substances like certain fungi and bacteria represent a high risk for the broad public if fallen into wrong hands. Incidents based on bio agents are commonly considered to have incalculable and complex consequences for first responders and people. The impact of such an event can be minimized by a combination of different sensor technologies that have been developed to detect bio-threats and to gather information after an incident. Sensors for bio-agents can be grouped into two categories. Sampling devices collect material from locations supposed to be contaminated, and they are able to identify biological material with high sensitivity and selectivity. However, these point sensors need to be positioned correctly in advance of an attack, and moving sources of biological material cannot be tracked. A different approach is based on optical standoff detection. For biological samples laser induced florescence (LIF) has been proven to get real time data on location and type of hazards without being in contact with the suspicious substance. This work is based on a bio-detector developed at the DLR Lampoldshausen. The LIF detection has been designed for outdoor operation at standoff distances from 20 m up to more than 100 m. The detector acquires LIF spectral data for two different excitation wavelengths (280 and 355 nm) as well as time resolved information for the fluorescence decay which can be used to classify suspicious samples. While the classification device had been trained on uncritical samples (like amino acids, NADH, yeast, chemicals, oils), this work presents the progress to more relevant, living bacteria of different strains. The low risk and non-pathogenic bacteria Bacillus thuringensis, Bacillus atrophaeus, Bacillus subtilis, Brevibacillus brevis, Micrococcus luteus, Oligella urethralis, Paenibacillus polymyxa and Escherichia coli (K12) have been investigated with the above set-up at both excitation wavelengths

Design and analysis of large-scale biological rhythm studies: a comparison of algorithms for detecting periodic signals in biological data

PubMed Central

Deckard, Anastasia; Anafi, Ron C.; Hogenesch, John B.; Haase, Steven B.; Harer, John

2013-01-01

Motivation: To discover and study periodic processes in biological systems, we sought to identify periodic patterns in their gene expression data. We surveyed a large number of available methods for identifying periodicity in time series data and chose representatives of different mathematical perspectives that performed well on both synthetic data and biological data. Synthetic data were used to evaluate how each algorithm responds to different curve shapes, periods, phase shifts, noise levels and sampling rates. The biological datasets we tested represent a variety of periodic processes from different organisms, including the cell cycle and metabolic cycle in Saccharomyces cerevisiae, circadian rhythms in Mus musculus and the root clock in Arabidopsis thaliana. Results: From these results, we discovered that each algorithm had different strengths. Based on our findings, we make recommendations for selecting and applying these methods depending on the nature of the data and the periodic patterns of interest. Additionally, these results can also be used to inform the design of large-scale biological rhythm experiments so that the resulting data can be used with these algorithms to detect periodic signals more effectively. Contact: anastasia.deckard@duke.edu Supplementary information: Supplementary data are available at Bioinformatics online. PMID:24058056

Biological Networks for Cancer Candidate Biomarkers Discovery

PubMed Central

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

2016-01-01

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

Using Petri Net Tools to Study Properties and Dynamics of Biological Systems

PubMed Central

Peleg, Mor; Rubin, Daniel; Altman, Russ B.

2005-01-01

Petri Nets (PNs) and their extensions are promising methods for modeling and simulating biological systems. We surveyed PN formalisms and tools and compared them based on their mathematical capabilities as well as by their appropriateness to represent typical biological processes. We measured the ability of these tools to model specific features of biological systems and answer a set of biological questions that we defined. We found that different tools are required to provide all capabilities that we assessed. We created software to translate a generic PN model into most of the formalisms and tools discussed. We have also made available three models and suggest that a library of such models would catalyze progress in qualitative modeling via PNs. Development and wide adoption of common formats would enable researchers to share models and use different tools to analyze them without the need to convert to proprietary formats. PMID:15561791

[Illness caused by water-based paints?].

PubMed

Birkeland, G; Zahlsen, K; Aas, K

1994-08-20

Illness caused by the indoor environment is a challenging and complicated field to investigate. Emissions from paints may contribute to the problems. Several components of water-based paints evaporate for a long time after painting, and some of them may affect human biology. We describe one patient who has experienced symptoms caused by water-based paint. Different reaction mechanisms may be involved, and these are discussed. Components which may elicit biological effects are listed and discussed. Physicians should be aware of the possibility that a few patients may suffer from illness caused by emissions from modern paints.

Biomimetic cellular metals-using hierarchical structuring for energy absorption.

PubMed

Bührig-Polaczek, A; Fleck, C; Speck, T; Schüler, P; Fischer, S F; Caliaro, M; Thielen, M

2016-07-19

Fruit walls as well as nut and seed shells typically perform a multitude of functions. One of the biologically most important functions consists in the direct or indirect protection of the seeds from mechanical damage or other negative environmental influences. This qualifies such biological structures as role models for the development of new materials and components that protect commodities and/or persons from damage caused for example by impacts due to rough handling or crashes. We were able to show how the mechanical properties of metal foam based components can be improved by altering their structure on various hierarchical levels inspired by features and principles important for the impact and/or puncture resistance of the biological role models, rather than by tuning the properties of the bulk material. For this various investigation methods have been established which combine mechanical testing with different imaging methods, as well as with in situ and ex situ mechanical testing methods. Different structural hierarchies especially important for the mechanical deformation and failure behaviour of the biological role models, pomelo fruit (Citrus maxima) and Macadamia integrifolia, were identified. They were abstracted and transferred into corresponding structural principles and thus hierarchically structured bio-inspired metal foams have been designed. A production route for metal based bio-inspired structures by investment casting was successfully established. This allows the production of complex and reliable structures, by implementing and combining different hierarchical structural elements found in the biological concept generators, such as strut design and integration of fibres, as well as by minimising casting defects. To evaluate the structural effects, similar investigation methods and mechanical tests were applied to both the biological role models and the metallic foams. As a result an even deeper quantitative understanding of the form-structure-function relationship of the biological concept generators as well as the bio-inspired metal foams was achieved, on deeper hierarchical levels and overarching different levels.

Guidelines for Genome-Scale Analysis of Biological Rhythms.

PubMed

Hughes, Michael E; Abruzzi, Katherine C; Allada, Ravi; Anafi, Ron; Arpat, Alaaddin Bulak; Asher, Gad; Baldi, Pierre; de Bekker, Charissa; Bell-Pedersen, Deborah; Blau, Justin; Brown, Steve; Ceriani, M Fernanda; Chen, Zheng; Chiu, Joanna C; Cox, Juergen; Crowell, Alexander M; DeBruyne, Jason P; Dijk, Derk-Jan; DiTacchio, Luciano; Doyle, Francis J; Duffield, Giles E; Dunlap, Jay C; Eckel-Mahan, Kristin; Esser, Karyn A; FitzGerald, Garret A; Forger, Daniel B; Francey, Lauren J; Fu, Ying-Hui; Gachon, Frédéric; Gatfield, David; de Goede, Paul; Golden, Susan S; Green, Carla; Harer, John; Harmer, Stacey; Haspel, Jeff; Hastings, Michael H; Herzel, Hanspeter; Herzog, Erik D; Hoffmann, Christy; Hong, Christian; Hughey, Jacob J; Hurley, Jennifer M; de la Iglesia, Horacio O; Johnson, Carl; Kay, Steve A; Koike, Nobuya; Kornacker, Karl; Kramer, Achim; Lamia, Katja; Leise, Tanya; Lewis, Scott A; Li, Jiajia; Li, Xiaodong; Liu, Andrew C; Loros, Jennifer J; Martino, Tami A; Menet, Jerome S; Merrow, Martha; Millar, Andrew J; Mockler, Todd; Naef, Felix; Nagoshi, Emi; Nitabach, Michael N; Olmedo, Maria; Nusinow, Dmitri A; Ptáček, Louis J; Rand, David; Reddy, Akhilesh B; Robles, Maria S; Roenneberg, Till; Rosbash, Michael; Ruben, Marc D; Rund, Samuel S C; Sancar, Aziz; Sassone-Corsi, Paolo; Sehgal, Amita; Sherrill-Mix, Scott; Skene, Debra J; Storch, Kai-Florian; Takahashi, Joseph S; Ueda, Hiroki R; Wang, Han; Weitz, Charles; Westermark, Pål O; Wijnen, Herman; Xu, Ying; Wu, Gang; Yoo, Seung-Hee; Young, Michael; Zhang, Eric Erquan; Zielinski, Tomasz; Hogenesch, John B

2017-10-01

Genome biology approaches have made enormous contributions to our understanding of biological rhythms, particularly in identifying outputs of the clock, including RNAs, proteins, and metabolites, whose abundance oscillates throughout the day. These methods hold significant promise for future discovery, particularly when combined with computational modeling. However, genome-scale experiments are costly and laborious, yielding "big data" that are conceptually and statistically difficult to analyze. There is no obvious consensus regarding design or analysis. Here we discuss the relevant technical considerations to generate reproducible, statistically sound, and broadly useful genome-scale data. Rather than suggest a set of rigid rules, we aim to codify principles by which investigators, reviewers, and readers of the primary literature can evaluate the suitability of different experimental designs for measuring different aspects of biological rhythms. We introduce CircaInSilico, a web-based application for generating synthetic genome biology data to benchmark statistical methods for studying biological rhythms. Finally, we discuss several unmet analytical needs, including applications to clinical medicine, and suggest productive avenues to address them.

Guidelines for Genome-Scale Analysis of Biological Rhythms

PubMed Central

Hughes, Michael E.; Abruzzi, Katherine C.; Allada, Ravi; Anafi, Ron; Arpat, Alaaddin Bulak; Asher, Gad; Baldi, Pierre; de Bekker, Charissa; Bell-Pedersen, Deborah; Blau, Justin; Brown, Steve; Ceriani, M. Fernanda; Chen, Zheng; Chiu, Joanna C.; Cox, Juergen; Crowell, Alexander M.; DeBruyne, Jason P.; Dijk, Derk-Jan; DiTacchio, Luciano; Doyle, Francis J.; Duffield, Giles E.; Dunlap, Jay C.; Eckel-Mahan, Kristin; Esser, Karyn A.; FitzGerald, Garret A.; Forger, Daniel B.; Francey, Lauren J.; Fu, Ying-Hui; Gachon, Frédéric; Gatfield, David; de Goede, Paul; Golden, Susan S.; Green, Carla; Harer, John; Harmer, Stacey; Haspel, Jeff; Hastings, Michael H.; Herzel, Hanspeter; Herzog, Erik D.; Hoffmann, Christy; Hong, Christian; Hughey, Jacob J.; Hurley, Jennifer M.; de la Iglesia, Horacio O.; Johnson, Carl; Kay, Steve A.; Koike, Nobuya; Kornacker, Karl; Kramer, Achim; Lamia, Katja; Leise, Tanya; Lewis, Scott A.; Li, Jiajia; Li, Xiaodong; Liu, Andrew C.; Loros, Jennifer J.; Martino, Tami A.; Menet, Jerome S.; Merrow, Martha; Millar, Andrew J.; Mockler, Todd; Naef, Felix; Nagoshi, Emi; Nitabach, Michael N.; Olmedo, Maria; Nusinow, Dmitri A.; Ptáček, Louis J.; Rand, David; Reddy, Akhilesh B.; Robles, Maria S.; Roenneberg, Till; Rosbash, Michael; Ruben, Marc D.; Rund, Samuel S.C.; Sancar, Aziz; Sassone-Corsi, Paolo; Sehgal, Amita; Sherrill-Mix, Scott; Skene, Debra J.; Storch, Kai-Florian; Takahashi, Joseph S.; Ueda, Hiroki R.; Wang, Han; Weitz, Charles; Westermark, Pål O.; Wijnen, Herman; Xu, Ying; Wu, Gang; Yoo, Seung-Hee; Young, Michael; Zhang, Eric Erquan; Zielinski, Tomasz; Hogenesch, John B.

2017-01-01

Genome biology approaches have made enormous contributions to our understanding of biological rhythms, particularly in identifying outputs of the clock, including RNAs, proteins, and metabolites, whose abundance oscillates throughout the day. These methods hold significant promise for future discovery, particularly when combined with computational modeling. However, genome-scale experiments are costly and laborious, yielding “big data” that are conceptually and statistically difficult to analyze. There is no obvious consensus regarding design or analysis. Here we discuss the relevant technical considerations to generate reproducible, statistically sound, and broadly useful genome-scale data. Rather than suggest a set of rigid rules, we aim to codify principles by which investigators, reviewers, and readers of the primary literature can evaluate the suitability of different experimental designs for measuring different aspects of biological rhythms. We introduce CircaInSilico, a web-based application for generating synthetic genome biology data to benchmark statistical methods for studying biological rhythms. Finally, we discuss several unmet analytical needs, including applications to clinical medicine, and suggest productive avenues to address them. PMID:29098954

Head and facial anthropometry of mixed-race US Army male soldiers for military design and sizing: a pilot study.

PubMed

Yokota, Miyo

2005-05-01

In the United States, the biologically admixed population is increasing. Such demographic changes may affect the distribution of anthropometric characteristics, which are incorporated into the design of equipment and clothing for the US Army and other large organizations. The purpose of this study was to examine multivariate craniofacial anthropometric distributions between biologically admixed male populations and single racial groups of Black and White males. Multivariate statistical results suggested that nose breadth and lip length were different between Blacks and Whites. Such differences may be considered for adjustments to respirators and chemical-biological protective masks. However, based on this pilot study, multivariate anthropometric distributions of admixed individuals were within the distributions of single racial groups. Based on the sample reported, sizing and designing for the admixed groups are not necessary if anthropometric distributions of single racial groups comprising admixed groups are known.

Nonlinear dynamics based digital logic and circuits.

PubMed

Kia, Behnam; Lindner, John F; Ditto, William L

2015-01-01

We discuss the role and importance of dynamics in the brain and biological neural networks and argue that dynamics is one of the main missing elements in conventional Boolean logic and circuits. We summarize a simple dynamics based computing method, and categorize different techniques that we have introduced to realize logic, functionality, and programmability. We discuss the role and importance of coupled dynamics in networks of biological excitable cells, and then review our simple coupled dynamics based method for computing. In this paper, for the first time, we show how dynamics can be used and programmed to implement computation in any given base, including but not limited to base two.

Trait-Dependent Biogeography: (Re)Integrating Biology into Probabilistic Historical Biogeographical Models.

PubMed

Sukumaran, Jeet; Knowles, L Lacey

2018-06-01

The development of process-based probabilistic models for historical biogeography has transformed the field by grounding it in modern statistical hypothesis testing. However, most of these models abstract away biological differences, reducing species to interchangeable lineages. We present here the case for reintegration of biology into probabilistic historical biogeographical models, allowing a broader range of questions about biogeographical processes beyond ancestral range estimation or simple correlation between a trait and a distribution pattern, as well as allowing us to assess how inferences about ancestral ranges themselves might be impacted by differential biological traits. We show how new approaches to inference might cope with the computational challenges resulting from the increased complexity of these trait-based historical biogeographical models. Copyright © 2018 Elsevier Ltd. All rights reserved.

Hypoxia-based strategies for regenerative dentistry-Views from the different dental fields.

PubMed

Müller, Anna Sonja; Janjić, Klara; Lilaj, Bledar; Edelmayer, Michael; Agis, Hermann

2017-09-01

The understanding of the cell biological processes underlying development and regeneration of oral tissues leads to novel regenerative approaches. Over the past years, knowledge on key roles of the hypoxia-based response has become more profound. Based on these findings, novel regenerative approaches for dentistry are emerging, which target cellular oxygen sensors. These approaches include hypoxia pre-conditioning and pharmacologically simulated hypoxia. The increase in studies on hypoxia and hypoxia-based strategies in regenerative dentistry highlights the growing attention to hypoxia's role in regeneration and its underlying biology, as well as its application in a therapeutic setting. In this narrative review, we present the current knowledge on the role of hypoxia in oral tissues and review the proposed hypoxia-based approaches in different fields of dentistry, including endodontics, orthodontics, periodontics, and oral surgery. Copyright © 2017 Elsevier Ltd. All rights reserved.

Unified Deep Learning Architecture for Modeling Biology Sequence.

PubMed

Wu, Hongjie; Cao, Chengyuan; Xia, Xiaoyan; Lu, Qiang

2017-10-09

Prediction of the spatial structure or function of biological macromolecules based on their sequence remains an important challenge in bioinformatics. When modeling biological sequences using traditional sequencing models, characteristics, such as long-range interactions between basic units, the complicated and variable output of labeled structures, and the variable length of biological sequences, usually lead to different solutions on a case-by-case basis. This study proposed the use of bidirectional recurrent neural networks based on long short-term memory or a gated recurrent unit to capture long-range interactions by designing the optional reshape operator to adapt to the diversity of the output labels and implementing a training algorithm to support the training of sequence models capable of processing variable-length sequences. Additionally, the merge and pooling operators enhanced the ability to capture short-range interactions between basic units of biological sequences. The proposed deep-learning model and its training algorithm might be capable of solving currently known biological sequence-modeling problems through the use of a unified framework. We validated our model on one of the most difficult biological sequence-modeling problems currently known, with our results indicating the ability of the model to obtain predictions of protein residue interactions that exceeded the accuracy of current popular approaches by 10% based on multiple benchmarks.

Data Integration and Mining for Synthetic Biology Design.

PubMed

Mısırlı, Göksel; Hallinan, Jennifer; Pocock, Matthew; Lord, Phillip; McLaughlin, James Alastair; Sauro, Herbert; Wipat, Anil

2016-10-21

One aim of synthetic biologists is to create novel and predictable biological systems from simpler modular parts. This approach is currently hampered by a lack of well-defined and characterized parts and devices. However, there is a wealth of existing biological information, which can be used to identify and characterize biological parts, and their design constraints in the literature and numerous biological databases. However, this information is spread among these databases in many different formats. New computational approaches are required to make this information available in an integrated format that is more amenable to data mining. A tried and tested approach to this problem is to map disparate data sources into a single data set, with common syntax and semantics, to produce a data warehouse or knowledge base. Ontologies have been used extensively in the life sciences, providing this common syntax and semantics as a model for a given biological domain, in a fashion that is amenable to computational analysis and reasoning. Here, we present an ontology for applications in synthetic biology design, SyBiOnt, which facilitates the modeling of information about biological parts and their relationships. SyBiOnt was used to create the SyBiOntKB knowledge base, incorporating and building upon existing life sciences ontologies and standards. The reasoning capabilities of ontologies were then applied to automate the mining of biological parts from this knowledge base. We propose that this approach will be useful to speed up synthetic biology design and ultimately help facilitate the automation of the biological engineering life cycle.

Essential Oils from Thyme (Thymus vulgaris): Chemical Composition and Biological Effects in Mouse Model.

PubMed

Vetvicka, Vaclav; Vetvickova, Jana

2016-12-01

Thymus species are popular spices and contain volatile oils as main chemical constituents. Recently, plant-derived essential oils are gaining significant attention due to their significant biological activities. Seven different thymus-derived essential oils were compared in our study. First, we focused on their chemical composition, which was followed up by testing their effects on phagocytosis, cytokine production, chemotaxis, edema inhibition, and liver protection. We found limited biological activities among tested oils, with no correlation between composition and biological effects. Similarly, no oils were effective in every reaction. Based on our data, the tested biological use of these essential oils is questionable.

Ultrafast fluorescence spectroscopy of biologically relevant chromophores using type II difference frequency generation

NASA Astrophysics Data System (ADS)

Léonard, J.; Gelot, T.; Torgasin, K.; Haacke, S.

2011-01-01

A novel femtosecond fluorescence experiment based on type II difference frequency mixing is demonstrated. This approach is particularly interesting for near-UV emitting biological chromophores like amino acids and nucleotides, as the fluorescence is converted into the spectral range where CCD have their highest quantum efficiencies. The method is implemented with a 5-kHz amplified Ti:Sapphire laser system and first results obtained with 2,5-diphenyloxazole (PPO) in ethanol are reported.

Regular Biology Students Learn Like AP Students with SUN

ERIC Educational Resources Information Center

Batiza, Ann; Luo, Wen; Zhang, Bo; Gruhl, Mary; Nelson, David; Hoelzer, Mark; Ning, Ling; Roberts, Marisa; Knopp, Jonathan; Harrington, Tom; LaFlamme, Donna; Haasch, Mary Anne; Vogt, Gina; Goodsell, David; Marcey, David

2016-01-01

The SUN approach to biological energy transfer education is fundamentally different from past practices that trace chemical and energy inputs and outputs. The SUN approach uses a hydrogen fuel cell to convince learners that electrons can move from one substance to another based on differential attraction. With a hydrogen fuel cell, learners can…

A Systems' Biology Approach to Study MicroRNA-Mediated Gene Regulatory Networks

PubMed Central

Kunz, Manfred; Vera, Julio; Wolkenhauer, Olaf

2013-01-01

MicroRNAs (miRNAs) are potent effectors in gene regulatory networks where aberrant miRNA expression can contribute to human diseases such as cancer. For a better understanding of the regulatory role of miRNAs in coordinating gene expression, we here present a systems biology approach combining data-driven modeling and model-driven experiments. Such an approach is characterized by an iterative process, including biological data acquisition and integration, network construction, mathematical modeling and experimental validation. To demonstrate the application of this approach, we adopt it to investigate mechanisms of collective repression on p21 by multiple miRNAs. We first construct a p21 regulatory network based on data from the literature and further expand it using algorithms that predict molecular interactions. Based on the network structure, a detailed mechanistic model is established and its parameter values are determined using data. Finally, the calibrated model is used to study the effect of different miRNA expression profiles and cooperative target regulation on p21 expression levels in different biological contexts. PMID:24350286

Stigmatized Biologies: Examining the Cumulative Effects of Oral Health Disparities for Mexican American Farmworker Children

PubMed Central

Horton, Sarah; Barker, Judith C.

2012-01-01

Severe early childhood caries (ECC) can leave lasting effects on children’s physical development, including malformed oral arches and crooked permanent dentition. This article examines the way that ECC sets up Mexican American farm worker children in the United States for lasting dental problems and social stigma as young adults. We examine the role of dietary and environmental factors in contributing to what we call “stigmatized biologies,” and that of market-based dental public health insurance systems in cementing their enduring effects. We adapt Margaret Lock’s term, local biology, to illustrate the way that biology differs not only because of culture, diet, and environment but also because of disparities in insurance coverage. By showing the long-term effects of ECC and disparate dental treatment on farmworker adults, we show how the interaction of immigrant caregiving practices and underinsurance can have lasting social effects. An examination of the long-term effects of farm worker children’s ECC illustrates the ways that market-based health care systems can create embodied differences that in turn reproduce a system of social inequality. PMID:20550093

RNA-seq based transcriptomic map reveals new insights into mouse salivary gland development and maturation.

PubMed

Gluck, Christian; Min, Sangwon; Oyelakin, Akinsola; Smalley, Kirsten; Sinha, Satrajit; Romano, Rose-Anne

2016-11-16

Mouse models have served a valuable role in deciphering various facets of Salivary Gland (SG) biology, from normal developmental programs to diseased states. To facilitate such studies, gene expression profiling maps have been generated for various stages of SG organogenesis. However these prior studies fall short of capturing the transcriptional complexity due to the limited scope of gene-centric microarray-based technology. Compared to microarray, RNA-sequencing (RNA-seq) offers unbiased detection of novel transcripts, broader dynamic range and high specificity and sensitivity for detection of genes, transcripts, and differential gene expression. Although RNA-seq data, particularly under the auspices of the ENCODE project, have covered a large number of biological specimens, studies on the SG have been lacking. To better appreciate the wide spectrum of gene expression profiles, we isolated RNA from mouse submandibular salivary glands at different embryonic and adult stages. In parallel, we processed RNA-seq data for 24 organs and tissues obtained from the mouse ENCODE consortium and calculated the average gene expression values. To identify molecular players and pathways likely to be relevant for SG biology, we performed functional gene enrichment analysis, network construction and hierarchal clustering of the RNA-seq datasets obtained from different stages of SG development and maturation, and other mouse organs and tissues. Our bioinformatics-based data analysis not only reaffirmed known modulators of SG morphogenesis but revealed novel transcription factors and signaling pathways unique to mouse SG biology and function. Finally we demonstrated that the unique SG gene signature obtained from our mouse studies is also well conserved and can demarcate features of the human SG transcriptome that is different from other tissues. Our RNA-seq based Atlas has revealed a high-resolution cartographic view of the dynamic transcriptomic landscape of the mouse SG at various stages. These RNA-seq datasets will complement pre-existing microarray based datasets, including the Salivary Gland Molecular Anatomy Project by offering a broader systems-biology based perspective rather than the classical gene-centric view. Ultimately such resources will be valuable in providing a useful toolkit to better understand how the diverse cell population of the SG are organized and controlled during development and differentiation.

Use of tolerance values to diagnose water-quality stressors to aquatic biota in New England streams

USGS Publications Warehouse

Meador, M.R.; Carlisle, D.M.; Coles, J.F.

2008-01-01

Identification of stressors related to biological impairment is critical to biological assessments. We applied nationally derived tolerance indicator values for four water-quality variables to fish and benthic macroinvertebrate assemblages at 29 sites along an urban gradient in New England. Tolerance indicator values (TIVs), as biologically based predictors of water-quality variables, were determined for dissolved oxygen, nitrite plus nitrate (nitrate), total phosphorus, and water temperature for each site based on observed biological assemblages (TIVO), and for expected assemblages (TIVE). The quotient method, based on a ratio of the TIVs for observed and expected assemblages (tolerance units), was used to diagnose potential water-quality stressors. In addition, the ratio of measured water-quality values to water-quality criteria (water-quality units) was calculated for each water-quality variable to assess measured water-quality stressors. Results from a RIVPACS predictive model for benthic macroinvertebrates and Bray-Curtis dissimilarity for fish were used to classify sites into categories of good or impaired ecological condition. Significant differences were detected between good and impaired sites for all biological tolerance units (fish and benthic macroinvertebrate assemblages averaged) except for nitrate (P = 0.480), and for all water-quality units except for nitrate (P = 0.183). Diagnosis of water-quality stressors at selected sites was, in general, consistent with State-reported causes of impairment. Tolerance units for benthic macroinvertebrate and fish assemblages were significantly correlated for water temperature (P = 0.001, r = 0.63), dissolved oxygen (P = 0.001, r = 0.61), and total phosphorus (P = 0.001, r = 0.61), but not for nitrate (P = 0.059, r = -0.35). Differences between the two assemblages in site-specific diagnosis of water-quality stressors may be the result of differences in nitrate tolerance.

Synthetic biology and its alternatives. Descartes, Kant and the idea of engineering biological machines.

PubMed

Kogge, Werner; Richter, Michael

2013-06-01

The engineering-based approach of synthetic biology is characterized by an assumption that 'engineering by design' enables the construction of 'living machines'. These 'machines', as biological machines, are expected to display certain properties of life, such as adapting to changing environments and acting in a situated way. This paper proposes that a tension exists between the expectations placed on biological artefacts and the notion of producing such systems by means of engineering; this tension makes it seem implausible that biological systems, especially those with properties characteristic of living beings, can in fact be produced using the specific methods of engineering. We do not claim that engineering techniques have nothing to contribute to the biotechnological construction of biological artefacts. However, drawing on Descartes's and Kant's thinking on the relationship between the organism and the machine, we show that it is considerably more plausible to assume that distinctively biological artefacts emerge within a paradigm different from the paradigm of the Cartesian machine that underlies the engineering approach. We close by calling for increased attention to be paid to approaches within molecular biology and chemistry that rest on conceptions different from those of synthetic biology's engineering paradigm. Copyright © 2013 Elsevier Ltd. All rights reserved.

Life detection systems.

NASA Technical Reports Server (NTRS)

Mitz, M. A.

1972-01-01

Some promising newer approaches for detecting microorganisms are discussed, giving particular attention to the integration of different methods into a single instrument. Life detection methods may be divided into biological, chemical, and cytological methods. Biological methods are based on the biological properties of assimilation, metabolism, and growth. Devices for the detection of organic materials are considered, taking into account an instrument which volatilizes, separates, and analyzes a sample sequentially. Other instrumental systems described make use of a microscope and the cytochemical staining principle.

CytoCluster: A Cytoscape Plugin for Cluster Analysis and Visualization of Biological Networks.

PubMed

Li, Min; Li, Dongyan; Tang, Yu; Wu, Fangxiang; Wang, Jianxin

2017-08-31

Nowadays, cluster analysis of biological networks has become one of the most important approaches to identifying functional modules as well as predicting protein complexes and network biomarkers. Furthermore, the visualization of clustering results is crucial to display the structure of biological networks. Here we present CytoCluster, a cytoscape plugin integrating six clustering algorithms, HC-PIN (Hierarchical Clustering algorithm in Protein Interaction Networks), OH-PIN (identifying Overlapping and Hierarchical modules in Protein Interaction Networks), IPCA (Identifying Protein Complex Algorithm), ClusterONE (Clustering with Overlapping Neighborhood Expansion), DCU (Detecting Complexes based on Uncertain graph model), IPC-MCE (Identifying Protein Complexes based on Maximal Complex Extension), and BinGO (the Biological networks Gene Ontology) function. Users can select different clustering algorithms according to their requirements. The main function of these six clustering algorithms is to detect protein complexes or functional modules. In addition, BinGO is used to determine which Gene Ontology (GO) categories are statistically overrepresented in a set of genes or a subgraph of a biological network. CytoCluster can be easily expanded, so that more clustering algorithms and functions can be added to this plugin. Since it was created in July 2013, CytoCluster has been downloaded more than 9700 times in the Cytoscape App store and has already been applied to the analysis of different biological networks. CytoCluster is available from http://apps.cytoscape.org/apps/cytocluster.

CytoCluster: A Cytoscape Plugin for Cluster Analysis and Visualization of Biological Networks

PubMed Central

Li, Min; Li, Dongyan; Tang, Yu; Wang, Jianxin

2017-01-01

Nowadays, cluster analysis of biological networks has become one of the most important approaches to identifying functional modules as well as predicting protein complexes and network biomarkers. Furthermore, the visualization of clustering results is crucial to display the structure of biological networks. Here we present CytoCluster, a cytoscape plugin integrating six clustering algorithms, HC-PIN (Hierarchical Clustering algorithm in Protein Interaction Networks), OH-PIN (identifying Overlapping and Hierarchical modules in Protein Interaction Networks), IPCA (Identifying Protein Complex Algorithm), ClusterONE (Clustering with Overlapping Neighborhood Expansion), DCU (Detecting Complexes based on Uncertain graph model), IPC-MCE (Identifying Protein Complexes based on Maximal Complex Extension), and BinGO (the Biological networks Gene Ontology) function. Users can select different clustering algorithms according to their requirements. The main function of these six clustering algorithms is to detect protein complexes or functional modules. In addition, BinGO is used to determine which Gene Ontology (GO) categories are statistically overrepresented in a set of genes or a subgraph of a biological network. CytoCluster can be easily expanded, so that more clustering algorithms and functions can be added to this plugin. Since it was created in July 2013, CytoCluster has been downloaded more than 9700 times in the Cytoscape App store and has already been applied to the analysis of different biological networks. CytoCluster is available from http://apps.cytoscape.org/apps/cytocluster. PMID:28858211

Subcellular Carrier-Based Optical Ion-Selective Nanosensors

PubMed Central

Carregal-Romero, Susana; Montenegro, Jose-Maria; Parak, Wolfgang J.; Rivera_Gil, Pilar

2012-01-01

In this review, two carrier systems based on nanotechnology for real-time sensing of biologically relevant analytes (ions or other biological molecules) inside cells in a non-invasive way are discussed. One system is based on inorganic nanoparticles with an organic coating, whereas the second system is based on organic microcapsules. The sensor molecules presented within this work use an optical read-out. Due to the different physicochemical properties, both sensors show distinctive geometries that directly affect their internalization patterns. The nanoparticles carry the sensor molecule attached to their surfaces whereas the microcapsules encapsulate the sensor within their cavities. Their different size (nano and micro) enable each sensors to locate in different cellular regions. For example, the nanoparticles are mostly found in endolysosomal compartments but the microcapsules are rather found in phagolysosomal vesicles. Thus, allowing creating a tool of sensors that sense differently. Both sensor systems enable to measure ratiometrically however, only the microcapsules have the unique ability of multiplexing. At the end, an outlook on how more sophisticated sensors can be created by confining the nano-scaled sensors within the microcapsules will be given. PMID:22557969

Magnetic nanoparticles in different biological environments analyzed by magnetic particle spectroscopy

NASA Astrophysics Data System (ADS)

Löwa, Norbert; Seidel, Maria; Radon, Patricia; Wiekhorst, Frank

2017-04-01

Quantification of magnetic iron oxide nanoparticles (MNP) in biological systems like cells, tissue, or organs is of vital importance for development of novel biomedical applications, e.g. magnetofection, drug targeting or hyperthermia. Among others, the recently developed magnetic measurement technique magnetic particle spectroscopy (MPS) provides signals that are specific for MNP. MPS is based on the non-linear magnetic response of MNP exposed to a strong sinusoidal excitation field of up to 25 mT amplitude and 25 kHz frequency. So far, it has been proven a powerful tool for quantification of MNP in biological systems. In this study we investigated in detail the influence of typical biological media on the magnetic behavior of different MNP systems by MPS. The results reveal that amplitude and shape (ratio of harmonics) of the MPS spectra allow for perceptively monitoring changes in MNP magnetism caused by different physiological media. Additionally, the observed linear correlation between MPS amplitude and shape alterations can be used to reduce the quantification uncertainty for MNP suspended in a biological environment.

EUD-based biological optimization for carbon ion therapy

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

Brüningk, Sarah C., E-mail: sarah.brueningk@icr.ac.uk; Kamp, Florian; Wilkens, Jan J.

2015-11-15

Purpose: Treatment planning for carbon ion therapy requires an accurate modeling of the biological response of each tissue to estimate the clinical outcome of a treatment. The relative biological effectiveness (RBE) accounts for this biological response on a cellular level but does not refer to the actual impact on the organ as a whole. For photon therapy, the concept of equivalent uniform dose (EUD) represents a simple model to take the organ response into account, yet so far no formulation of EUD has been reported that is suitable to carbon ion therapy. The authors introduce the concept of an equivalentmore » uniform effect (EUE) that is directly applicable to both ion and photon therapies and exemplarily implemented it as a basis for biological treatment plan optimization for carbon ion therapy. Methods: In addition to a classical EUD concept, which calculates a generalized mean over the RBE-weighted dose distribution, the authors propose the EUE to simplify the optimization process of carbon ion therapy plans. The EUE is defined as the biologically equivalent uniform effect that yields the same probability of injury as the inhomogeneous effect distribution in an organ. Its mathematical formulation is based on the generalized mean effect using an effect-volume parameter to account for different organ architectures and is thus independent of a reference radiation. For both EUD concepts, quadratic and logistic objective functions are implemented into a research treatment planning system. A flexible implementation allows choosing for each structure between biological effect constraints per voxel and EUD constraints per structure. Exemplary treatment plans are calculated for a head-and-neck patient for multiple combinations of objective functions and optimization parameters. Results: Treatment plans optimized using an EUE-based objective function were comparable to those optimized with an RBE-weighted EUD-based approach. In agreement with previous results from photon therapy, the optimization by biological objective functions resulted in slightly superior treatment plans in terms of final EUD for the organs at risk (OARs) compared to voxel-based optimization approaches. This observation was made independent of the underlying objective function metric. An absolute gain in OAR sparing was observed for quadratic objective functions, whereas intersecting DVHs were found for logistic approaches. Even for considerable under- or overestimations of the used effect- or dose–volume parameters during the optimization, treatment plans were obtained that were of similar quality as the results of a voxel-based optimization. Conclusions: EUD-based optimization with either of the presented concepts can successfully be applied to treatment plan optimization. This makes EUE-based optimization for carbon ion therapy a useful tool to optimize more specifically in the sense of biological outcome while voxel-to-voxel variations of the biological effectiveness are still properly accounted for. This may be advantageous in terms of computational cost during treatment plan optimization but also enables a straight forward comparison of different fractionation schemes or treatment modalities.« less

A robust high resolution reversed-phase HPLC strategy to investigate various metabolic species in different biological models.

PubMed

D'Alessandro, Angelo; Gevi, Federica; Zolla, Lello

2011-04-01

Recent advancements in the field of omics sciences have paved the way for further expansion of metabolomics. Originally tied to NMR spectroscopy, metabolomic disciplines are constantly and growingly involving HPLC and mass spectrometry (MS)-based analytical strategies and, in this context, we hereby propose a robust and efficient extraction protocol for metabolites from four different biological sources which are subsequently analysed, identified and quantified through high resolution reversed-phase fast HPLC and mass spectrometry. To this end, we demonstrate the elevated intra- and inter-day technical reproducibility, ease of an MRM-based MS method, allowing simultaneous detection of up to 10 distinct features, and robustness of multiple metabolite detection and quantification in four different biological samples. This strategy might become routinely applicable to various samples/biological matrices, especially for low-availability ones. In parallel, we compare the present strategy for targeted detection of a representative metabolite, L-glutamic acid, with our previously-proposed chemical-derivatization through dansyl chloride. A direct comparison of the present method against spectrophotometric assays is proposed as well. An application of the proposed method is also introduced, using the SAOS-2 cell line, either induced or non-induced to express the TAp63 isoform of the p63 gene, as a model for determination of variations of glutamate concentrations.

A DNA-based pattern classifier with in vitro learning and associative recall for genomic characterization and biosensing without explicit sequence knowledge.

PubMed

Lee, Ju Seok; Chen, Junghuei; Deaton, Russell; Kim, Jin-Woo

2014-01-01

Genetic material extracted from in situ microbial communities has high promise as an indicator of biological system status. However, the challenge is to access genomic information from all organisms at the population or community scale to monitor the biosystem's state. Hence, there is a need for a better diagnostic tool that provides a holistic view of a biosystem's genomic status. Here, we introduce an in vitro methodology for genomic pattern classification of biological samples that taps large amounts of genetic information from all genes present and uses that information to detect changes in genomic patterns and classify them. We developed a biosensing protocol, termed Biological Memory, that has in vitro computational capabilities to "learn" and "store" genomic sequence information directly from genomic samples without knowledge of their explicit sequences, and that discovers differences in vitro between previously unknown inputs and learned memory molecules. The Memory protocol was designed and optimized based upon (1) common in vitro recombinant DNA operations using 20-base random probes, including polymerization, nuclease digestion, and magnetic bead separation, to capture a snapshot of the genomic state of a biological sample as a DNA memory and (2) the thermal stability of DNA duplexes between new input and the memory to detect similarities and differences. For efficient read out, a microarray was used as an output method. When the microarray-based Memory protocol was implemented to test its capability and sensitivity using genomic DNA from two model bacterial strains, i.e., Escherichia coli K12 and Bacillus subtilis, results indicate that the Memory protocol can "learn" input DNA, "recall" similar DNA, differentiate between dissimilar DNA, and detect relatively small concentration differences in samples. This study demonstrated not only the in vitro information processing capabilities of DNA, but also its promise as a genomic pattern classifier that could access information from all organisms in a biological system without explicit genomic information. The Memory protocol has high potential for many applications, including in situ biomonitoring of ecosystems, screening for diseases, biosensing of pathological features in water and food supplies, and non-biological information processing of memory devices, among many.

Biosensors and Bio-Bar Code Assays Based on Biofunctionalized Magnetic Microbeads

PubMed Central

Jaffrezic-Renault, Nicole; Martelet, Claude; Chevolot, Yann; Cloarec, Jean-Pierre

2007-01-01

This review paper reports the applications of magnetic microbeads in biosensors and bio-bar code assays. Affinity biosensors are presented through different types of transducing systems: electrochemical, piezo electric or magnetic ones, applied to immunodetection and genodetection. Enzymatic biosensors are based on biofunctionalization through magnetic microbeads of a transducer, more often amperometric, potentiometric or conductimetric. The bio-bar code assays relie on a sandwich structure based on specific biological interaction of a magnetic microbead and a nanoparticle with a defined biological molecule. The magnetic particle allows the separation of the reacted target molecules from unreacted ones. The nanoparticles aim at the amplification and the detection of the target molecule. The bio-bar code assays allow the detection at very low concentration of biological molecules, similar to PCR sensitivity.

Smooth quantile normalization.

PubMed

Hicks, Stephanie C; Okrah, Kwame; Paulson, Joseph N; Quackenbush, John; Irizarry, Rafael A; Bravo, Héctor Corrada

2018-04-01

Between-sample normalization is a critical step in genomic data analysis to remove systematic bias and unwanted technical variation in high-throughput data. Global normalization methods are based on the assumption that observed variability in global properties is due to technical reasons and are unrelated to the biology of interest. For example, some methods correct for differences in sequencing read counts by scaling features to have similar median values across samples, but these fail to reduce other forms of unwanted technical variation. Methods such as quantile normalization transform the statistical distributions across samples to be the same and assume global differences in the distribution are induced by only technical variation. However, it remains unclear how to proceed with normalization if these assumptions are violated, for example, if there are global differences in the statistical distributions between biological conditions or groups, and external information, such as negative or control features, is not available. Here, we introduce a generalization of quantile normalization, referred to as smooth quantile normalization (qsmooth), which is based on the assumption that the statistical distribution of each sample should be the same (or have the same distributional shape) within biological groups or conditions, but allowing that they may differ between groups. We illustrate the advantages of our method on several high-throughput datasets with global differences in distributions corresponding to different biological conditions. We also perform a Monte Carlo simulation study to illustrate the bias-variance tradeoff and root mean squared error of qsmooth compared to other global normalization methods. A software implementation is available from https://github.com/stephaniehicks/qsmooth.

Quantifying biological integrity by taxonomic completeness: its utility in regional and global assessments.

PubMed

Hawkins, Charles P

2006-08-01

Water resources managers and conservation biologists need reliable, quantitative, and directly comparable methods for assessing the biological integrity of the world's aquatic ecosystems. Large-scale assessments are constrained by the lack of consistency in the indicators used to assess biological integrity and our current inability to translate between indicators. In theory, assessments based on estimates of taxonomic completeness, i.e., the proportion of expected taxa that were observed (observed/expected, O/E) are directly comparable to one another and should therefore allow regionally and globally consistent summaries of the biological integrity of freshwater ecosystems. However, we know little about the true comparability of O/E assessments derived from different data sets or how well O/E assessments perform relative to other indicators in use. I compared the performance (precision, bias, and sensitivity to stressors) of O/E assessments based on five different data sets with the performance of the indicators previously applied to these data (three multimetric indices, a biotic index, and a hybrid method used by the state of Maine). Analyses were based on data collected from U.S. stream ecosystems in North Carolina, the Mid-Atlantic Highlands, Maine, and Ohio. O/E assessments resulted in very similar estimates of mean regional conditions compared with most other indicators once these indicators' values were standardized relative to reference-site means. However, other indicators tended to be biased estimators of O/E, a consequence of differences in their response to natural environmental gradients and sensitivity to stressors. These results imply that, in some cases, it may be possible to compare assessments derived from different indicators by standardizing their values (a statistical approach to data harmonization). In situations where it is difficult to standardize or otherwise harmonize two or more indicators, O/E values can easily be derived from existing raw sample data. With some caveats, O/E should provide more directly comparable assessments of biological integrity across regions than is possible by harmonizing values of a mix of indicators.

Biosimilars: pharmacovigilance and risk management.

PubMed

Zuñiga, Leyre; Calvo, Begoña

2010-07-01

Biosimilars cannot be authorized based on the same requirements that apply to generic medicines. Despite the fact that the biosimilar and reference drug can show similar efficacy, the biosimilar may exhibit different safety profile in terms of nature, seriousness or incidence of adverse reactions. However, the data from pre-authorization clinical studies normally are insufficient to identify all potential differences. Therefore, clinical safety of similar biological medicinal products must be monitored closely on an ongoing basis during the post-approval phase including continued risk-benefit assessment. The biosimilar applicant must provide the European Medicines Agency (EMEA) with a risk management plan (EU-RMP) and pharmacovigilance programme with its application, including a description of the potential safety issues associated with the similar biological medicinal product that may be a result of differences in the manufacturing process from the reference biologic. The most critical safety concern relating to biopharmaceuticals (including biosimilars) is immunogenicity. Risk management applies scientifically based methodologies to identify, assess, communicate and minimise risk throughout a drug's life cycle so as to establish and maintain a favourable benefit-risk profile in patients. The risk management plan for biosimilars should focus on heightens the pharmacovigilance measures, identify immunogenicity risk and implement special post-marketing surveillance. Although International Nonproprietary Names (INNs) served as a useful tool in worldwide pharmacovigilance, for biologicals they should not be relied upon as the only means of product identification. Biologicals should always be commercialized with a brand name or the INN plus the manufacturer's name. (c) 2010 John Wiley & Sons, Ltd.

Incorporating biologically based models into assessments of risk from chemical contaminants

NASA Technical Reports Server (NTRS)

Bull, R. J.; Conolly, R. B.; De Marini, D. M.; MacPhail, R. C.; Ohanian, E. V.; Swenberg, J. A.

1993-01-01

The general approach to assessment of risk from chemical contaminants in drinking water involves three steps: hazard identification, exposure assessment, and dose-response assessment. Traditionally, the risks to humans associated with different levels of a chemical have been derived from the toxic responses observed in animals. It is becoming increasingly clear, however, that further information is needed if risks to humans are to be assessed accurately. Biologically based models help clarify the dose-response relationship and reduce uncertainty.

OmicsNet: a web-based tool for creation and visual analysis of biological networks in 3D space.

PubMed

Zhou, Guangyan; Xia, Jianguo

2018-06-07

Biological networks play increasingly important roles in omics data integration and systems biology. Over the past decade, many excellent tools have been developed to support creation, analysis and visualization of biological networks. However, important limitations remain: most tools are standalone programs, the majority of them focus on protein-protein interaction (PPI) or metabolic networks, and visualizations often suffer from 'hairball' effects when networks become large. To help address these limitations, we developed OmicsNet - a novel web-based tool that allows users to easily create different types of molecular interaction networks and visually explore them in a three-dimensional (3D) space. Users can upload one or multiple lists of molecules of interest (genes/proteins, microRNAs, transcription factors or metabolites) to create and merge different types of biological networks. The 3D network visualization system was implemented using the powerful Web Graphics Library (WebGL) technology that works natively in most major browsers. OmicsNet supports force-directed layout, multi-layered perspective layout, as well as spherical layout to help visualize and navigate complex networks. A rich set of functions have been implemented to allow users to perform coloring, shading, topology analysis, and enrichment analysis. OmicsNet is freely available at http://www.omicsnet.ca.

Do two machine-learning based prognostic signatures for breast cancer capture the same biological processes?

PubMed

Drier, Yotam; Domany, Eytan

2011-03-14

The fact that there is very little if any overlap between the genes of different prognostic signatures for early-discovery breast cancer is well documented. The reasons for this apparent discrepancy have been explained by the limits of simple machine-learning identification and ranking techniques, and the biological relevance and meaning of the prognostic gene lists was questioned. Subsequently, proponents of the prognostic gene lists claimed that different lists do capture similar underlying biological processes and pathways. The present study places under scrutiny the validity of this claim, for two important gene lists that are at the focus of current large-scale validation efforts. We performed careful enrichment analysis, controlling the effects of multiple testing in a manner which takes into account the nested dependent structure of gene ontologies. In contradiction to several previous publications, we find that the only biological process or pathway for which statistically significant concordance can be claimed is cell proliferation, a process whose relevance and prognostic value was well known long before gene expression profiling. We found that the claims reported by others, of wider concordance between the biological processes captured by the two prognostic signatures studied, were found either to be lacking statistical rigor or were in fact based on addressing some other question.

Society and 'good woman': A critical review of gender difference in depression.

PubMed

Maji, Sucharita

2018-06-01

Worldwide, women are found to suffer from depression significantly more than men. This has puzzled the scientists since no biological explanation can completely resolve the matter. Extant empirical work has been conducted to solve the mystery of the issue. However, most of the research has pivoted their attention to biology. Therefore, based on the previous literature from the disciplines of medicine, psychology and sociology, the author aimed at looking and reviewing the matter critically. Specifically, the present critical review aims at conceptualising the psychological, social and cultural factors in the context of gender difference in depression. The work reveals that psychological variables such as women's unique attachment patterns, relational self-construal, as well as a macro-level issue like power dynamics based on gender, and the skewed division of labour play an important role in gender difference in depression. The work also suggests that focusing solely on biological underpinnings may result in losing the entire scenario; therefore, social and cultural issues that place women in a socially disadvantaged position are equally important.

A monolithic glass chip for active single-cell sorting based on mechanical phenotyping.

PubMed

Faigle, Christoph; Lautenschläger, Franziska; Whyte, Graeme; Homewood, Philip; Martín-Badosa, Estela; Guck, Jochen

2015-03-07

The mechanical properties of biological cells have long been considered as inherent markers of biological function and disease. However, the screening and active sorting of heterogeneous populations based on serial single-cell mechanical measurements has not been demonstrated. Here we present a novel monolithic glass chip for combined fluorescence detection and mechanical phenotyping using an optical stretcher. A new design and manufacturing process, involving the bonding of two asymmetrically etched glass plates, combines exact optical fiber alignment, low laser damage threshold and high imaging quality with the possibility of several microfluidic inlet and outlet channels. We show the utility of such a custom-built optical stretcher glass chip by measuring and sorting single cells in a heterogeneous population based on their different mechanical properties and verify sorting accuracy by simultaneous fluorescence detection. This offers new possibilities of exact characterization and sorting of small populations based on rheological properties for biological and biomedical applications.

Toward Clarifying the Meanings of "Gender" in Mathematics Education Research

ERIC Educational Resources Information Center

Damarin, Suzanne; Erchick, Diana B.

2010-01-01

The importance of clarity in definitions of gender is discussed and several conceptual models of gender are presented. Four of these models begin with biological sex differences but draw attention to other aspects of gender. Four models set biology aside and are based on social and cultural theories. Some of the advantages of the latter for…

Module-based multiscale simulation of angiogenesis in skeletal muscle

PubMed Central

2011-01-01

Background Mathematical modeling of angiogenesis has been gaining momentum as a means to shed new light on the biological complexity underlying blood vessel growth. A variety of computational models have been developed, each focusing on different aspects of the angiogenesis process and occurring at different biological scales, ranging from the molecular to the tissue levels. Integration of models at different scales is a challenging and currently unsolved problem. Results We present an object-oriented module-based computational integration strategy to build a multiscale model of angiogenesis that links currently available models. As an example case, we use this approach to integrate modules representing microvascular blood flow, oxygen transport, vascular endothelial growth factor transport and endothelial cell behavior (sensing, migration and proliferation). Modeling methodologies in these modules include algebraic equations, partial differential equations and agent-based models with complex logical rules. We apply this integrated model to simulate exercise-induced angiogenesis in skeletal muscle. The simulation results compare capillary growth patterns between different exercise conditions for a single bout of exercise. Results demonstrate how the computational infrastructure can effectively integrate multiple modules by coordinating their connectivity and data exchange. Model parameterization offers simulation flexibility and a platform for performing sensitivity analysis. Conclusions This systems biology strategy can be applied to larger scale integration of computational models of angiogenesis in skeletal muscle, or other complex processes in other tissues under physiological and pathological conditions. PMID:21463529

Promoting a structural view of biology for varied audiences: an overview of RCSB PDB resources and experiences

PubMed Central

Dutta, Shuchismita; Zardecki, Christine; Goodsell, David S.; Berman, Helen M.

2010-01-01

The Research Collaboratory for Structural Bioinformatics Protein Data Bank (RCSB PDB) supports scientific research and education worldwide by providing an essential resource of information on biomolecular structures. In addition to serving as a deposition, data-processing and distribution center for PDB data, the RCSB PDB offers resources and online materials that different audiences can use to customize their structural biology instruction. These include resources for general audiences that present macromolecular structure in the context of a biological theme, method-based materials for researchers who take a more traditional approach to the presentation of structural science, and materials that mix theme-based and method-based approaches for educators and students. Through these efforts the RCSB PDB aims to enable optimal use of structural data by researchers, educators and students designing and understanding experiments in biology, chemistry and medicine, and by general users making informed decisions about their life and health. PMID:20877496

Improvement of the titanium implant biological properties by coating with poly (ε-caprolactone)-based hybrid nanocomposites synthesized via sol-gel

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

Catauro, Michelina; Bollino, Flavia; Papale, Ferdinando

When bioactive coatings are applied to medical implants by means of sol-gel dip coating technique, the biological proprieties of the implant surface can be modified to match the properties of the surrounding tissues. In this study organo-inorganic nanocomposites materials were synthesized via sol-gel. They consisted of an inorganic zirconium-based and silica-based matrix, in which a biodegradable polymer (the poly-ε-caprolactone, PCL) was incorporated in different weight percentages. The synthesized materials, in sol phase, were used to dip-coat a substrate of commercially pure titanium grade 4 (CP Ti gr. 4) in order to improve its biological properties. A microstructural analysis of themore » obtained films was carried out by scanning electron microscopy (SEM) and attenuated total reflectance (ATR) Fourier transform infrared spectroscopy (FT-IR). Biological proprieties of the coated substrates were investigated by means of in vitro tests.« less

Measuring the Evolutionary Rewiring of Biological Networks

PubMed Central

Shou, Chong; Bhardwaj, Nitin; Lam, Hugo Y. K.; Yan, Koon-Kiu; Kim, Philip M.; Snyder, Michael; Gerstein, Mark B.

2011-01-01

We have accumulated a large amount of biological network data and expect even more to come. Soon, we anticipate being able to compare many different biological networks as we commonly do for molecular sequences. It has long been believed that many of these networks change, or “rewire”, at different rates. It is therefore important to develop a framework to quantify the differences between networks in a unified fashion. We developed such a formalism based on analogy to simple models of sequence evolution, and used it to conduct a systematic study of network rewiring on all the currently available biological networks. We found that, similar to sequences, biological networks show a decreased rate of change at large time divergences, because of saturation in potential substitutions. However, different types of biological networks consistently rewire at different rates. Using comparative genomics and proteomics data, we found a consistent ordering of the rewiring rates: transcription regulatory, phosphorylation regulatory, genetic interaction, miRNA regulatory, protein interaction, and metabolic pathway network, from fast to slow. This ordering was found in all comparisons we did of matched networks between organisms. To gain further intuition on network rewiring, we compared our observed rewirings with those obtained from simulation. We also investigated how readily our formalism could be mapped to other network contexts; in particular, we showed how it could be applied to analyze changes in a range of “commonplace” networks such as family trees, co-authorships and linux-kernel function dependencies. PMID:21253555

Natural products in modern life science.

PubMed

Bohlin, Lars; Göransson, Ulf; Alsmark, Cecilia; Wedén, Christina; Backlund, Anders

2010-06-01

With a realistic threat against biodiversity in rain forests and in the sea, a sustainable use of natural products is becoming more and more important. Basic research directed against different organisms in Nature could reveal unexpected insights into fundamental biological mechanisms but also new pharmaceutical or biotechnological possibilities of more immediate use. Many different strategies have been used prospecting the biodiversity of Earth in the search for novel structure-activity relationships, which has resulted in important discoveries in drug development. However, we believe that the development of multidisciplinary incentives will be necessary for a future successful exploration of Nature. With this aim, one way would be a modernization and renewal of a venerable proven interdisciplinary science, Pharmacognosy, which represents an integrated way of studying biological systems. This has been demonstrated based on an explanatory model where the different parts of the model are explained by our ongoing research. Anti-inflammatory natural products have been discovered based on ethnopharmacological observations, marine sponges in cold water have resulted in substances with ecological impact, combinatory strategy of ecology and chemistry has revealed new insights into the biodiversity of fungi, in depth studies of cyclic peptides (cyclotides) has created new possibilities for engineering of bioactive peptides, development of new strategies using phylogeny and chemography has resulted in new possibilities for navigating chemical and biological space, and using bioinformatic tools for understanding of lateral gene transfer could provide potential drug targets. A multidisciplinary subject like Pharmacognosy, one of several scientific disciplines bridging biology and chemistry with medicine, has a strategic position for studies of complex scientific questions based on observations in Nature. Furthermore, natural product research based on intriguing scientific questions in Nature can be of value to increase the attraction for young students in modern life science.

Metamaterial Absorber Based Multifunctional Sensor Application

NASA Astrophysics Data System (ADS)

Ozer, Z.; Mamedov, A. M.; Ozbay, E.

2017-02-01

In this study metamaterial based (MA) absorber sensor, integrated with an X-band waveguide, is numerically and experimentally suggested for important application including pressure, density sensing and marble type detecting applications based on rectangular split ring resonator, sensor layer and absorber layer that measures of changing in the dielectric constant and/or the thickness of a sensor layer. Changing of physical, chemical or biological parameters in the sensor layer can be detected by measuring the resonant frequency shifting of metamaterial absorber based sensor. Suggested MA based absorber sensor can be used for medical, biological, agricultural and chemical detecting applications in microwave frequency band. We compare the simulation and experimentally obtained results from the fabricated sample which are good agreement. Simulation results show that the proposed structure can detect the changing of the refractive indexes of different materials via special resonance frequencies, thus it could be said that the MA-based sensors have high sensitivity. Additionally due to the simple and tiny structures it could be adapted to other electronic devices in different sizes.

Dispensing Processes Impact Apparent Biological Activity as Determined by Computational and Statistical Analyses

PubMed Central

Ekins, Sean; Olechno, Joe; Williams, Antony J.

2013-01-01

Dispensing and dilution processes may profoundly influence estimates of biological activity of compounds. Published data show Ephrin type-B receptor 4 IC50 values obtained via tip-based serial dilution and dispensing versus acoustic dispensing with direct dilution differ by orders of magnitude with no correlation or ranking of datasets. We generated computational 3D pharmacophores based on data derived by both acoustic and tip-based transfer. The computed pharmacophores differ significantly depending upon dispensing and dilution methods. The acoustic dispensing-derived pharmacophore correctly identified active compounds in a subsequent test set where the tip-based method failed. Data from acoustic dispensing generates a pharmacophore containing two hydrophobic features, one hydrogen bond donor and one hydrogen bond acceptor. This is consistent with X-ray crystallography studies of ligand-protein interactions and automatically generated pharmacophores derived from this structural data. In contrast, the tip-based data suggest a pharmacophore with two hydrogen bond acceptors, one hydrogen bond donor and no hydrophobic features. This pharmacophore is inconsistent with the X-ray crystallographic studies and automatically generated pharmacophores. In short, traditional dispensing processes are another important source of error in high-throughput screening that impacts computational and statistical analyses. These findings have far-reaching implications in biological research. PMID:23658723

Influence of subject matter discipline and science content knowledge on National Board Certified science teachers' conceptions, enactment, and goals for inquiry

NASA Astrophysics Data System (ADS)

Breslyn, Wayne Gene

The present study investigated differences in the continuing development of National Board Certified Science Teachers' (NBCSTs) conceptions of inquiry across the disciplines of biology, chemistry, earth science, and physics. The central research question of the study was, "How does a NBCST's science discipline (biology, chemistry, earth science, or physics) influence their conceptions, enactment, and goals for inquiry-based teaching and learning?" A mixed methods approach was used that included an analysis of the National Board portfolio entry, Active Scientific Inquiry, for participants (n=48) achieving certification in the 2007 cohort. The portfolio entry provided detailed documentation of teachers' goals and enactment of an inquiry lesson taught in their classroom. Based on the results from portfolio analysis, participant interviews were conducted with science teachers (n=12) from the 2008 NBCST cohort who represented the science disciplines of biology, chemistry, earth science, and physics. The interviews provided a broader range of contexts to explore teachers' conceptions, enactment, and goals of inquiry. Other factors studied were disciplinary differences in NBCSTs' views of the nature of science, the relation between their science content knowledge and use of inquiry, and changes in their conceptions of inquiry as result of the NB certification process. Findings, based on a situated cognitive framework, suggested that differences exist between biology, chemistry, and earth science teachers' conceptions, enactment, and goals for inquiry. Further, individuals teaching in more than one discipline often held different conceptions of inquiry depending on the discipline in which they were teaching. Implications for the research community include being aware of disciplinary differences in studies on inquiry and exercising caution in generalizing findings across disciplines. In addition, teachers who teach in more than one discipline can highlight the contextual and culturally based nature of teachers' conceptions of inquiry. For the education community, disciplinary differences should be considered in the development of curriculum and professional development. An understanding of disciplinary trends can allow for more targeted and relevant representations of inquiry.

Psychological and biological responses to race-based social stress as pathways to disparities in educational outcomes.

PubMed

Levy, Dorainne J; Heissel, Jennifer A; Richeson, Jennifer A; Adam, Emma K

2016-09-01

We present the race-based disparities in stress and sleep in context model (RDSSC), which argues that racial/ethnic disparities in educational achievement and attainment are partially explained by the effects of race-based stressors, such as stereotype threat and perceived discrimination, on psychological and biological responses to stress, which, in turn, impact cognitive functioning and academic performance. Whereas the roles of psychological coping responses, such as devaluation and disidentification, have been theorized in previous work, the present model integrates the roles of biological stress responses, such as changes in stress hormones and sleep hours and quality, to this rich literature. We situate our model of the impact of race-based stress in the broader contexts of other stressors [e.g., stressors associated with socioeconomic status (SES)], developmental histories of stress, and individual and group differences in access to resources, opportunity and employment structures. Considering both psychological and biological responses to race-based stressors, in social contexts, will yield a more comprehensive understanding of the emergence of academic disparities between Whites and racial/ethnic minorities. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Genetic basis and fitness correlates of dynamic carotenoid-based ornamental coloration in male and female common kestrels Falco tinnunculus.

PubMed

Vergara, P; Fargallo, J A; Martínez-Padilla, J

2015-01-01

Knowledge of the genetic basis of sexual ornaments is essential to understand their evolution through sexual selection. Although carotenoid-based ornaments have been instrumental in the study of sexual selection, given the inability of animals to synthesize carotenoids de novo, they are generally assumed to be influenced solely by environmental variation. However, very few studies have directly estimated the role of genes and the environment in shaping variation in carotenoid-based traits. Using long-term individual-based data, we here explore the evolutionary potential of a dynamic, carotenoid-based ornament (namely skin coloration), in male and female common kestrels. We first estimate the amount of genetic variation underlying variation in hue, chroma and brightness. After correcting for sex differences, the chroma of the orange-yellow eye ring coloration was significantly heritable (h2±SE=0.40±0.17), whereas neither hue (h2=0) nor brightness (h2=0.02) was heritable. Second, we estimate the strength and shape of selection acting upon chromatic (hue and chroma) and achromatic (brightness) variation and show positive and negative directional selection on female but not male chroma and hue, respectively, whereas brightness was unrelated to fitness in both sexes. This suggests that different components of carotenoid-based signals traits may show different evolutionary dynamics. Overall, we show that carotenoid-based coloration is a complex and multifaceted trait. If we are to gain a better understanding of the processes responsible for the generation and maintenance of variation in carotenoid-based coloration, these complexities need to be taken into account. © 2014 European Society For Evolutionary Biology. Journal of Evolutionary Biology © 2014 European Society For Evolutionary Biology.

Functional diversity patterns of abyssal nematodes in the Eastern Mediterranean: A comparison between cold seeps and typical deep sea sediments

NASA Astrophysics Data System (ADS)

Kalogeropoulou, V.; Keklikoglou, K.; Lampadariou, N.

2015-04-01

Spatial patterns in deep sea nematode biological trait composition and functional diversity were investigated between chemosynthetic and typical deep sea ecosystems as well as between different microhabitats within the chemosynthetic ecosystems, in the Eastern Mediterranean. The chemosynthetic ecosystems chosen were two mud volcanoes, Napoli at 1950 m depth and Amsterdam at 2040 m depth which are cold seeps characterized by high chemosynthetic activity and spatial heterogeneity. Typical deep sea ecosystems consisted of fine-grained silt-clay sediments which were collected from three areas located in the south Ionian Sea at 2765 to 2840 m depth, the southern Cretan margin at 1089 to 1998 m depth and the Levantine Sea at 3055 to 3870 m depth. A range of biological traits (9 traits; 31 categories) related to buccal morphology, tail shape, body size, body shape, life history strategy, sediment position, cuticle morphology, amphid shape and presence of somatic setae were combined to identify patterns in the functional composition of nematode assemblages between the two habitats, the two mud volcanoes (macroscale) and between the microhabitats within the mud volcanoes (microscale). Data on trait correspondence was provided by biological information on species and genera. A total of 170 nematode species were allocated in 67 different trait combinations, i.e. functional groups, based on taxonomic, morphological and behavioral characteristics. The Biological Trait Analysis (BTA) revealed significant differences between the mud volcanoes and the typical deep sea sediments indicating the presence of different biological functions in ecologically very different environments. Moreover, chemosynthetic activity and habitat heterogeneity within mud volcanoes enhance the presence of different biological and ecological functions in nematode assemblages of different microhabitats. Functional diversity and species richness patterns varied significantly across the different environmental gradients prevailing in the study areas. Biological trait analysis, with the addition of newly introduced trait categories, and functional diversity outcomes provided greater explanatory power of ecosystem functioning than species richness and taxonomic diversity.

Optimal network alignment with graphlet degree vectors.

PubMed

Milenković, Tijana; Ng, Weng Leong; Hayes, Wayne; Przulj, Natasa

2010-06-30

Important biological information is encoded in the topology of biological networks. Comparative analyses of biological networks are proving to be valuable, as they can lead to transfer of knowledge between species and give deeper insights into biological function, disease, and evolution. We introduce a new method that uses the Hungarian algorithm to produce optimal global alignment between two networks using any cost function. We design a cost function based solely on network topology and use it in our network alignment. Our method can be applied to any two networks, not just biological ones, since it is based only on network topology. We use our new method to align protein-protein interaction networks of two eukaryotic species and demonstrate that our alignment exposes large and topologically complex regions of network similarity. At the same time, our alignment is biologically valid, since many of the aligned protein pairs perform the same biological function. From the alignment, we predict function of yet unannotated proteins, many of which we validate in the literature. Also, we apply our method to find topological similarities between metabolic networks of different species and build phylogenetic trees based on our network alignment score. The phylogenetic trees obtained in this way bear a striking resemblance to the ones obtained by sequence alignments. Our method detects topologically similar regions in large networks that are statistically significant. It does this independent of protein sequence or any other information external to network topology.

Interactive learning and action: realizing the promise of synthetic biology for global health.

PubMed

Betten, A Wieke; Roelofsen, Anneloes; Broerse, Jacqueline E W

2013-09-01

The emerging field of synthetic biology has the potential to improve global health. For example, synthetic biology could contribute to efforts at vaccine development in a context in which vaccines and immunization have been identified by the international community as being crucial to international development efforts and, in particular, the millennium development goals. However, past experience with innovations shows that realizing a technology's potential can be difficult and complex. To achieve better societal embedding of synthetic biology and to make sure it reaches its potential, science and technology development should be made more inclusive and interactive. Responsible research and innovation is based on the premise that a broad range of stakeholders with different views, needs and ideas should have a voice in the technological development and deployment process. The interactive learning and action (ILA) approach has been developed as a methodology to bring societal stakeholders into a science and technology development process. This paper proposes an ILA in five phases for an international effort, with national case studies, to develop socially robust applications of synthetic biology for global health, based on the example of vaccine development. The design is based on results of a recently initiated ILA project on synthetic biology; results from other interactive initiatives described in the literature; and examples of possible applications of synthetic biology for global health that are currently being developed.

Graph-based semi-supervised learning with genomic data integration using condition-responsive genes applied to phenotype classification.

PubMed

Doostparast Torshizi, Abolfazl; Petzold, Linda R

2018-01-01

Data integration methods that combine data from different molecular levels such as genome, epigenome, transcriptome, etc., have received a great deal of interest in the past few years. It has been demonstrated that the synergistic effects of different biological data types can boost learning capabilities and lead to a better understanding of the underlying interactions among molecular levels. In this paper we present a graph-based semi-supervised classification algorithm that incorporates latent biological knowledge in the form of biological pathways with gene expression and DNA methylation data. The process of graph construction from biological pathways is based on detecting condition-responsive genes, where 3 sets of genes are finally extracted: all condition responsive genes, high-frequency condition-responsive genes, and P-value-filtered genes. The proposed approach is applied to ovarian cancer data downloaded from the Human Genome Atlas. Extensive numerical experiments demonstrate superior performance of the proposed approach compared to other state-of-the-art algorithms, including the latest graph-based classification techniques. Simulation results demonstrate that integrating various data types enhances classification performance and leads to a better understanding of interrelations between diverse omics data types. The proposed approach outperforms many of the state-of-the-art data integration algorithms. © The Author 2017. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For Permissions, please email: journals.permissions@oup.com

The use and QA of biologically related models for treatment planning: short report of the TG-166 of the therapy physics committee of the AAPM.

PubMed

Allen Li, X; Alber, Markus; Deasy, Joseph O; Jackson, Andrew; Ken Jee, Kyung-Wook; Marks, Lawrence B; Martel, Mary K; Mayo, Charles; Moiseenko, Vitali; Nahum, Alan E; Niemierko, Andrzej; Semenenko, Vladimir A; Yorke, Ellen D

2012-03-01

Treatment planning tools that use biologically related models for plan optimization and/or evaluation are being introduced for clinical use. A variety of dose-response models and quantities along with a series of organ-specific model parameters are included in these tools. However, due to various limitations, such as the limitations of models and available model parameters, the incomplete understanding of dose responses, and the inadequate clinical data, the use of biologically based treatment planning system (BBTPS) represents a paradigm shift and can be potentially dangerous. There will be a steep learning curve for most planners. The purpose of this task group is to address some of these relevant issues before the use of BBTPS becomes widely spread. In this report, the authors (1) discuss strategies, limitations, conditions, and cautions for using biologically based models and parameters in clinical treatment planning; (2) demonstrate the practical use of the three most commonly used commercially available BBTPS and potential dosimetric differences between biologically model based and dose-volume based treatment plan optimization and evaluation; (3) identify the desirable features and future directions in developing BBTPS; and (4) provide general guidelines and methodology for the acceptance testing, commissioning, and routine quality assurance (QA) of BBTPS.

Why is infant mortality higher in boys than in girls? A new hypothesis based on preconception environment and evidence from a large sample of twins.

PubMed

Pongou, Roland

2013-04-01

Infant mortality is higher in boys than girls in most parts of the world. This has been explained by sex differences in genetic and biological makeup, with boys being biologically weaker and more susceptible to diseases and premature death. At the same time, recent studies have found that numerous preconception or prenatal environmental factors affect the probability of a baby being conceived male or female. I propose that these environmental factors also explain sex differences in mortality. I contribute a new methodology of distinguishing between child biology and preconception environment by comparing male-female differences in mortality across opposite-sex twins, same-sex twins, and all twins. Using a large sample of twins from sub-Saharan Africa, I find that both preconception environment and child biology increase the mortality of male infants, but the effect of biology is substantially smaller than the literature suggests. I also estimate the interacting effects of biology with some intrauterine and external environmental factors, including birth order within a twin pair, social status, and climate. I find that a twin is more likely to be male if he is the firstborn, born to an educated mother, or born in certain climatic conditions. Male firstborns are more likely to survive than female firstborns, but only during the neonatal period. Finally, mortality is not affected by the interactions between biology and climate or between biology and social status.

Pupil-segmentation-based adaptive optics for microscopy

NASA Astrophysics Data System (ADS)

Ji, Na; Milkie, Daniel E.; Betzig, Eric

2011-03-01

Inhomogeneous optical properties of biological samples make it difficult to obtain diffraction-limited resolution in depth. Correcting the sample-induced optical aberrations needs adaptive optics (AO). However, the direct wavefront-sensing approach commonly used in astronomy is not suitable for most biological samples due to their strong scattering of light. We developed an image-based AO approach that is insensitive to sample scattering. By comparing images of the sample taken with different segments of the pupil illuminated, local tilt in the wavefront is measured from image shift. The aberrated wavefront is then obtained either by measuring the local phase directly using interference or with phase reconstruction algorithms similar to those used in astronomical AO. We implemented this pupil-segmentation-based approach in a two-photon fluorescence microscope and demonstrated that diffraction-limited resolution can be recovered from nonbiological and biological samples.

Multi-agent-based bio-network for systems biology: protein-protein interaction network as an example.

PubMed

Ren, Li-Hong; Ding, Yong-Sheng; Shen, Yi-Zhen; Zhang, Xiang-Feng

2008-10-01

Recently, a collective effort from multiple research areas has been made to understand biological systems at the system level. This research requires the ability to simulate particular biological systems as cells, organs, organisms, and communities. In this paper, a novel bio-network simulation platform is proposed for system biology studies by combining agent approaches. We consider a biological system as a set of active computational components interacting with each other and with an external environment. Then, we propose a bio-network platform for simulating the behaviors of biological systems and modelling them in terms of bio-entities and society-entities. As a demonstration, we discuss how a protein-protein interaction (PPI) network can be seen as a society of autonomous interactive components. From interactions among small PPI networks, a large PPI network can emerge that has a remarkable ability to accomplish a complex function or task. We also simulate the evolution of the PPI networks by using the bio-operators of the bio-entities. Based on the proposed approach, various simulators with different functions can be embedded in the simulation platform, and further research can be done from design to development, including complexity validation of the biological system.

A comparison of discontinuation rates of tofacitinib and biologic disease-modifying anti-rheumatic drugs in rheumatoid arthritis: a systematic review and Bayesian network meta-analysis.

PubMed

Park, Sun-Kyeong; Lee, Min-Young; Jang, Eun-Jin; Kim, Hye-Lin; Ha, Dong-Mun; Lee, Eui-Kyung

2017-01-01

The purpose of this study was to compare the discontinuation rates of tofacitinib and biologics (tumour necrosis factor inhibitors (TNFi), abatacept, rituximab, and tocilizumab) in rheumatoid arthritis (RA) patients considering inadequate responses (IRs) to previous treatment(s). Randomised controlled trials of tofacitinib and biologics - reporting at least one total discontinuation, discontinuation due to lack of efficacy (LOE), and discontinuation due to adverse events (AEs) - were identified through systematic review. The analyses were conducted for patients with IRs to conventional synthetic disease-modifying anti-rheumatic drugs (cDMARDs) and for patients with biologics-IR, separately. Bayesian network meta-analysis was used to estimate rate ratio (RR) of a biologic relative to tofacitinib with 95% credible interval (CrI), and probability of RR being <1 (P[RR<1]). The analyses of 34 studies showed no significant differences in discontinuation rates between tofacitinib and biologics in the cDMARDs-IR group. In the biologics-IR group, however, TNFi (RR 0.17, 95% CrI 0.01-3.61, P[RR<1] 92.0%) and rituximab (RR 0.20, 95% CrI 0.01-2.91, P[RR<1] 92.3%) showed significantly lower total discontinuation rates than tofacitinib did. Despite the difference, discontinuation cases owing to LOE and AEs revealed that tofacitinib was comparable to the biologics. The comparability of discontinuation rate between tofacitinib and biologics was different based on previous treatments and discontinuation reasons: LOE, AEs, and total (due to other reasons). Therefore, those factors need to be considered to decide the optimal treatment strategy.

Laboratory based instruction in Pakistan: Comparative evaluation of three laboratory instruction methods in biological science at higher secondary school level

NASA Astrophysics Data System (ADS)

Cheema, Tabinda Shahid

This study of laboratory based instruction at higher secondary school level was an attempt to gain some insight into the effectiveness of three laboratory instruction methods: cooperative group instruction method, individualised instruction method and lecture demonstration method on biology achievement and retention. A Randomised subjects, Pre-test Post-test Comparative Methods Design was applied. Three groups of students from a year 11 class in Pakistan conducted experiments using the different laboratory instruction methods. Pre-tests, achievement tests after the experiments and retention tests one month later were administered. Results showed no significant difference between the groups on total achievement and retention, nor was there any significant difference on knowledge and comprehension test scores or skills performance. Future research investigating a similar problem is suggested.

Intensity calibration of a laser scanning confocal microscope based on concentrated dyes.

PubMed

Model, Michael A; Blank, James L

2006-10-01

To find water-soluble fluorescent dyes with absorption in various regions of the spectrum and investigate their utility as standards for laser scanning confocal microscopy. Several dyes were found to have characteristics required for fluorescence microscopy standards. The intensity of biological fluorescent specimens was measured against the emission of concentrated dyes. Results using different optics and different microscopes were compared. Slides based on concentrated dyes can be prepared in a highly reproducible manner and are stable under laser scanning. Normalized fluorescence of biological specimens remains consistent with different objective lenses and is tolerant to some mismatch in optical filters or imperfect pinhole alignment. Careful choice of scanning parameters is necessary to ensure linearity of intensity measurements. Concentrated dyes provide a robust and inexpensive intensity standard that can be used in basic research or clinical studies.

Evaluation of targeted and untargeted effects-based monitoring tools to assess impacts of contaminants of emerging concern on fish in the South Platte River, CO.

PubMed

Ekman, Drew R; Keteles, Kristen; Beihoffer, Jon; Cavallin, Jenna E; Dahlin, Kenneth; Davis, John M; Jastrow, Aaron; Lazorchak, James M; Mills, Marc A; Murphy, Mark; Nguyen, David; Vajda, Alan M; Villeneuve, Daniel L; Winkelman, Dana L; Collette, Timothy W

2018-08-01

Rivers in the arid Western United States face increasing influences from anthropogenic contaminants due to population growth, urbanization, and drought. To better understand and more effectively track the impacts of these contaminants, biologically-based monitoring tools are increasingly being used to complement routine chemical monitoring. This study was initiated to assess the ability of both targeted and untargeted biologically-based monitoring tools to discriminate impacts of two adjacent wastewater treatment plants (WWTPs) on Colorado's South Platte River. A cell-based estrogen assay (in vitro, targeted) determined that water samples collected downstream of the larger of the two WWTPs displayed considerable estrogenic activity in its two separate effluent streams. Hepatic vitellogenin mRNA expression (in vivo, targeted) and NMR-based metabolomic analyses (in vivo, untargeted) from caged male fathead minnows also suggested estrogenic activity downstream of the larger WWTP, but detected significant differences in responses from its two effluent streams. The metabolomic results suggested that these differences were associated with oxidative stress levels. Finally, partial least squares regression was used to explore linkages between the metabolomics responses and the chemical contaminants that were detected at the sites. This analysis, along with univariate statistical approaches, identified significant covariance between the biological endpoints and estrone concentrations, suggesting the importance of this contaminant and recommending increased focus on its presence in the environment. These results underscore the benefits of a combined targeted and untargeted biologically-based monitoring strategy when used alongside contaminant monitoring to more effectively assess ecological impacts of exposures to complex mixtures in surface waters. Published by Elsevier Ltd.

Understanding the sorption and biotransformation of organic micropollutants in innovative biological wastewater treatment technologies.

PubMed

Alvarino, T; Suarez, S; Lema, J; Omil, F

2018-02-15

New technologies for wastewater treatment have been developed in the last years based on the combination of biological reactors operating under different redox conditions. Their efficiency in the removal of organic micropollutants (OMPs) has not been clearly assessed yet. This review paper is focussed on understanding the sorption and biotransformation of a selected group of 17 OMPs, including pharmaceuticals, hormones and personal care products, during biological wastewater treatment processes. Apart from considering the role of "classical" operational parameters, new factors such as biomass conformation and particle size, upward velocity applied or the addition of adsorbents have been considered. It has been found that the OMP removal by sorption not only depends on their physico-chemical characteristics and other parameters, such as the biomass conformation and particle size, or some operational conditions also relevant. Membrane biological reactors (MBR), have shown to enhance sorption and biotransformation of some OMPs. The same applies to technologies bases on direct addition of activated carbon in bioreactors. The OMP biotransformation degree and pathway is mainly driven by the redox potential and the primary substrate activity. The combination of different redox potentials in hybrid reactor systems can significantly enhance the overall OMP removal efficiency. Sorption and biotransformation can be synergistically promoted in biological reactors by the addition of activated carbon. The deeper knowledge of the main parameters influencing OMP removal provided by this review will allow optimizing the biological processes in the future. Copyright © 2017 Elsevier B.V. All rights reserved.

Evaluation of Formative Computer-Based Assessment by Cell Biology Students with Differing Entry Qualifications and Ethnicity

ERIC Educational Resources Information Center

Bax, Christopher; Baggott, Glenn; Howey, Ellen; Pellet-Many, Carolyn; Rayne, Richard; Neonaki, Maria; Bax, Bridget E.; White, Christopher Branford

2006-01-01

This study was carried out to examine students' responses to the use of on-line assessments that included feedback. First year BSc students taking a Cell Biology module undertook such an assessment and were then asked to evaluate the test by completing an anonymous questionnaire. Answers were analysed in light of the respondents' ethnicity and…

The origin of neutron biological effectiveness as a function of energy.

PubMed

Baiocco, G; Barbieri, S; Babini, G; Morini, J; Alloni, D; Friedland, W; Kundrát, P; Schmitt, E; Puchalska, M; Sihver, L; Ottolenghi, A

2016-09-22

The understanding of the impact of radiation quality in early and late responses of biological targets to ionizing radiation exposure necessarily grounds on the results of mechanistic studies starting from physical interactions. This is particularly true when, already at the physical stage, the radiation field is mixed, as it is the case for neutron exposure. Neutron Relative Biological Effectiveness (RBE) is energy dependent, maximal for energies ~1 MeV, varying significantly among different experiments. The aim of this work is to shed light on neutron biological effectiveness as a function of field characteristics, with a comprehensive modeling approach: this brings together transport calculations of neutrons through matter (with the code PHITS) and the predictive power of the biophysical track structure code PARTRAC in terms of DNA damage evaluation. Two different energy dependent neutron RBE models are proposed: the first is phenomenological and based only on the characterization of linear energy transfer on a microscopic scale; the second is purely ab-initio and based on the induction of complex DNA damage. Results for the two models are compared and found in good qualitative agreement with current standards for radiation protection factors, which are agreed upon on the basis of RBE data.

The origin of neutron biological effectiveness as a function of energy

NASA Astrophysics Data System (ADS)

Baiocco, G.; Barbieri, S.; Babini, G.; Morini, J.; Alloni, D.; Friedland, W.; Kundrát, P.; Schmitt, E.; Puchalska, M.; Sihver, L.; Ottolenghi, A.

2016-09-01

The understanding of the impact of radiation quality in early and late responses of biological targets to ionizing radiation exposure necessarily grounds on the results of mechanistic studies starting from physical interactions. This is particularly true when, already at the physical stage, the radiation field is mixed, as it is the case for neutron exposure. Neutron Relative Biological Effectiveness (RBE) is energy dependent, maximal for energies ~1 MeV, varying significantly among different experiments. The aim of this work is to shed light on neutron biological effectiveness as a function of field characteristics, with a comprehensive modeling approach: this brings together transport calculations of neutrons through matter (with the code PHITS) and the predictive power of the biophysical track structure code PARTRAC in terms of DNA damage evaluation. Two different energy dependent neutron RBE models are proposed: the first is phenomenological and based only on the characterization of linear energy transfer on a microscopic scale; the second is purely ab-initio and based on the induction of complex DNA damage. Results for the two models are compared and found in good qualitative agreement with current standards for radiation protection factors, which are agreed upon on the basis of RBE data.

The origin of neutron biological effectiveness as a function of energy

PubMed Central

Baiocco, G.; Barbieri, S.; Babini, G.; Morini, J.; Alloni, D.; Friedland, W.; Kundrát, P.; Schmitt, E.; Puchalska, M.; Sihver, L.; Ottolenghi, A.

2016-01-01

The understanding of the impact of radiation quality in early and late responses of biological targets to ionizing radiation exposure necessarily grounds on the results of mechanistic studies starting from physical interactions. This is particularly true when, already at the physical stage, the radiation field is mixed, as it is the case for neutron exposure. Neutron Relative Biological Effectiveness (RBE) is energy dependent, maximal for energies ~1 MeV, varying significantly among different experiments. The aim of this work is to shed light on neutron biological effectiveness as a function of field characteristics, with a comprehensive modeling approach: this brings together transport calculations of neutrons through matter (with the code PHITS) and the predictive power of the biophysical track structure code PARTRAC in terms of DNA damage evaluation. Two different energy dependent neutron RBE models are proposed: the first is phenomenological and based only on the characterization of linear energy transfer on a microscopic scale; the second is purely ab-initio and based on the induction of complex DNA damage. Results for the two models are compared and found in good qualitative agreement with current standards for radiation protection factors, which are agreed upon on the basis of RBE data. PMID:27654349

Regional grey matter structure differences between transsexuals and healthy controls--a voxel based morphometry study.

PubMed

Simon, Lajos; Kozák, Lajos R; Simon, Viktória; Czobor, Pál; Unoka, Zsolt; Szabó, Ádám; Csukly, Gábor

2013-01-01

Gender identity disorder (GID) refers to transsexual individuals who feel that their assigned biological gender is incongruent with their gender identity and this cannot be explained by any physical intersex condition. There is growing scientific interest in the last decades in studying the neuroanatomy and brain functions of transsexual individuals to better understand both the neuroanatomical features of transsexualism and the background of gender identity. So far, results are inconclusive but in general, transsexualism has been associated with a distinct neuroanatomical pattern. Studies mainly focused on male to female (MTF) transsexuals and there is scarcity of data acquired on female to male (FTM) transsexuals. Thus, our aim was to analyze structural MRI data with voxel based morphometry (VBM) obtained from both FTM and MTF transsexuals (n = 17) and compare them to the data of 18 age matched healthy control subjects (both males and females). We found differences in the regional grey matter (GM) structure of transsexual compared with control subjects, independent from their biological gender, in the cerebellum, the left angular gyrus and in the left inferior parietal lobule. Additionally, our findings showed that in several brain areas, regarding their GM volume, transsexual subjects did not differ significantly from controls sharing their gender identity but were different from those sharing their biological gender (areas in the left and right precentral gyri, the left postcentral gyrus, the left posterior cingulate, precuneus and calcarinus, the right cuneus, the right fusiform, lingual, middle and inferior occipital, and inferior temporal gyri). These results support the notion that structural brain differences exist between transsexual and healthy control subjects and that majority of these structural differences are dependent on the biological gender.

Regional Grey Matter Structure Differences between Transsexuals and Healthy Controls—A Voxel Based Morphometry Study

PubMed Central

Simon, Lajos; Kozák, Lajos R.; Simon, Viktória; Czobor, Pál; Unoka, Zsolt; Szabó, Ádám; Csukly, Gábor

2013-01-01

Gender identity disorder (GID) refers to transsexual individuals who feel that their assigned biological gender is incongruent with their gender identity and this cannot be explained by any physical intersex condition. There is growing scientific interest in the last decades in studying the neuroanatomy and brain functions of transsexual individuals to better understand both the neuroanatomical features of transsexualism and the background of gender identity. So far, results are inconclusive but in general, transsexualism has been associated with a distinct neuroanatomical pattern. Studies mainly focused on male to female (MTF) transsexuals and there is scarcity of data acquired on female to male (FTM) transsexuals. Thus, our aim was to analyze structural MRI data with voxel based morphometry (VBM) obtained from both FTM and MTF transsexuals (n = 17) and compare them to the data of 18 age matched healthy control subjects (both males and females). We found differences in the regional grey matter (GM) structure of transsexual compared with control subjects, independent from their biological gender, in the cerebellum, the left angular gyrus and in the left inferior parietal lobule. Additionally, our findings showed that in several brain areas, regarding their GM volume, transsexual subjects did not differ significantly from controls sharing their gender identity but were different from those sharing their biological gender (areas in the left and right precentral gyri, the left postcentral gyrus, the left posterior cingulate, precuneus and calcarinus, the right cuneus, the right fusiform, lingual, middle and inferior occipital, and inferior temporal gyri). These results support the notion that structural brain differences exist between transsexual and healthy control subjects and that majority of these structural differences are dependent on the biological gender. PMID:24391851

Quantitative measures of healthy aging and biological age

PubMed Central

Kim, Sangkyu; Jazwinski, S. Michal

2015-01-01

Numerous genetic and non-genetic factors contribute to aging. To facilitate the study of these factors, various descriptors of biological aging, including ‘successful aging’ and ‘frailty’, have been put forth as integrative functional measures of aging. A separate but related quantitative approach is the ‘frailty index’, which has been operationalized and frequently used. Various frailty indices have been constructed. Although based on different numbers and types of health variables, frailty indices possess several common properties that make them useful across different studies. We have been using a frailty index termed FI34 based on 34 health variables. Like other frailty indices, FI34 increases non-linearly with advancing age and is a better indicator of biological aging than chronological age. FI34 has a substantial genetic basis. Using FI34, we found elevated levels of resting metabolic rate linked to declining health in nonagenarians. Using FI34 as a quantitative phenotype, we have also found a genomic region on chromosome 12 that is associated with healthy aging and longevity. PMID:26005669

Do US Black Women Experience Stress-Related Accelerated Biological Aging?

PubMed Central

Hicken, Margaret T.; Pearson, Jay A.; Seashols, Sarah J.; Brown, Kelly L.; Cruz, Tracey Dawson

2010-01-01

We hypothesize that black women experience accelerated biological aging in response to repeated or prolonged adaptation to subjective and objective stressors. Drawing on stress physiology and ethnographic, social science, and public health literature, we lay out the rationale for this hypothesis. We also perform a first population-based test of its plausibility, focusing on telomere length, a biomeasure of aging that may be shortened by stressors. Analyzing data from the Study of Women's Health Across the Nation (SWAN), we estimate that at ages 49–55, black women are 7.5 years biologically “older” than white women. Indicators of perceived stress and poverty account for 27% of this difference. Data limitations preclude assessing objective stressors and also result in imprecise estimates, limiting our ability to draw firm inferences. Further investigation of black-white differences in telomere length using large-population-based samples of broad age range and with detailed measures of environmental stressors is merited. PMID:20436780

Integrative Chemical-Biological Read-Across Approach for Chemical Hazard Classification

PubMed Central

Low, Yen; Sedykh, Alexander; Fourches, Denis; Golbraikh, Alexander; Whelan, Maurice; Rusyn, Ivan; Tropsha, Alexander

2013-01-01

Traditional read-across approaches typically rely on the chemical similarity principle to predict chemical toxicity; however, the accuracy of such predictions is often inadequate due to the underlying complex mechanisms of toxicity. Here we report on the development of a hazard classification and visualization method that draws upon both chemical structural similarity and comparisons of biological responses to chemicals measured in multiple short-term assays (”biological” similarity). The Chemical-Biological Read-Across (CBRA) approach infers each compound's toxicity from those of both chemical and biological analogs whose similarities are determined by the Tanimoto coefficient. Classification accuracy of CBRA was compared to that of classical RA and other methods using chemical descriptors alone, or in combination with biological data. Different types of adverse effects (hepatotoxicity, hepatocarcinogenicity, mutagenicity, and acute lethality) were classified using several biological data types (gene expression profiling and cytotoxicity screening). CBRA-based hazard classification exhibited consistently high external classification accuracy and applicability to diverse chemicals. Transparency of the CBRA approach is aided by the use of radial plots that show the relative contribution of analogous chemical and biological neighbors. Identification of both chemical and biological features that give rise to the high accuracy of CBRA-based toxicity prediction facilitates mechanistic interpretation of the models. PMID:23848138

Spectroscopy of Isolated Prebiotic Nucleobases

NASA Technical Reports Server (NTRS)

Svadlenak, Nathan; Callahan, Michael P.; Ligare, Marshall; Gulian, Lisa; Gengeliczki, Zsolt; Nachtigallova, Dana; Hobza, Pavel; deVries, Mattanjah

2011-01-01

We use multiphoton ionization and double resonance spectroscopy to study the excited state dynamics of biologically relevant molecules as well as prebiotic nucleobases, isolated in the gas phase. Molecules that are biologically relevant to life today tend to exhibit short excited state lifetimes compared to similar but non-biologically relevant analogs. The mechanism is internal conversion, which may help protect the biologically active molecules from UV damage. This process is governed by conical intersections that depend very strongly on molecular structure. Therefore we have studied purines and pyrimidines with systematic variations of structure, including substitutions, tautomeric forms, and cluster structures that represent different base pair binding motifs. These structural variations also include possible alternate base pairs that may shed light on prebiotic chemistry. With this in mind we have begun to probe the ultrafast dynamics of molecules that exhibit very short excited states and search for evidence of internal conversions.

SBML-PET: a Systems Biology Markup Language-based parameter estimation tool.

PubMed

Zi, Zhike; Klipp, Edda

2006-11-01

The estimation of model parameters from experimental data remains a bottleneck for a major breakthrough in systems biology. We present a Systems Biology Markup Language (SBML) based Parameter Estimation Tool (SBML-PET). The tool is designed to enable parameter estimation for biological models including signaling pathways, gene regulation networks and metabolic pathways. SBML-PET supports import and export of the models in the SBML format. It can estimate the parameters by fitting a variety of experimental data from different experimental conditions. SBML-PET has a unique feature of supporting event definition in the SMBL model. SBML models can also be simulated in SBML-PET. Stochastic Ranking Evolution Strategy (SRES) is incorporated in SBML-PET for parameter estimation jobs. A classic ODE Solver called ODEPACK is used to solve the Ordinary Differential Equation (ODE) system. http://sysbio.molgen.mpg.de/SBML-PET/. The website also contains detailed documentation for SBML-PET.

Of mice and women: a comparative tissue biology perspective of breast stem cells and differentiation.

PubMed

Dontu, Gabriela; Ince, Tan A

2015-06-01

Tissue based research requires a background in human and veterinary pathology, developmental biology, anatomy, as well as molecular and cellular biology. This type of comparative tissue biology (CTB) expertise is necessary to tackle some of the conceptual challenges in human breast stem cell research. It is our opinion that the scarcity of CTB expertise contributed to some erroneous interpretations in tissue based research, some of which are reviewed here in the context of breast stem cells. In this article we examine the dissimilarities between mouse and human mammary tissue and suggest how these may impact stem cell studies. In addition, we consider the differences between breast ducts vs. lobules and clarify how these affect the interpretation of results in stem cell research. Lastly, we introduce a new elaboration of normal epithelial cell types in human breast and discuss how this provides a clinically useful basis for breast cancer classification.

Sex and life expectancy.

PubMed

Seifarth, Joshua E; McGowan, Cheri L; Milne, Kevin J

2012-12-01

A sexual dimorphism in human life expectancy has existed in almost every country for as long as records have been kept. Although human life expectancy has increased each year, females still live longer, on average, than males. Undoubtedly, the reasons for the sex gap in life expectancy are multifaceted, and it has been discussed from both sociological and biological perspectives. However, even if biological factors make up only a small percentage of the determinants of the sex difference in this phenomenon, parity in average life expectancy should not be anticipated. The aim of this review is to highlight biological mechanisms that may underlie the sexual dimorphism in life expectancy. Using PubMed, ISI Web of Knowledge, and Google Scholar, as well as cited and citing reference histories of articles through August 2012, English-language articles were identified, read, and synthesized into categories that could account for biological sex differences in human life expectancy. The examination of biological mechanisms accounting for the female-based advantage in human life expectancy has been an active area of inquiry; however, it is still difficult to prove the relative importance of any 1 factor. Nonetheless, biological differences between the sexes do exist and include differences in genetic and physiological factors such as progressive skewing of X chromosome inactivation, telomere attrition, mitochondrial inheritance, hormonal and cellular responses to stress, immune function, and metabolic substrate handling among others. These factors may account for at least a part of the female advantage in human life expectancy. Despite noted gaps in sex equality, higher body fat percentages and lower physical activity levels globally at all ages, a sex-based gap in life expectancy exists in nearly every country for which data exist. There are several biological mechanisms that may contribute to explaining why females live longer than men on average, but the complexity of the human life experience makes research examining the contribution of any single factor for the female advantage difficult. However, this information may still prove important to the development of strategies for healthy aging in both sexes. Copyright © 2012 Elsevier HS Journals, Inc. All rights reserved.

Biological and psychological rhythms: an integrative approach to rhythm disturbances in autistic disorder.

PubMed

Botbol, Michel; Cabon, Philippe; Kermarrec, Solenn; Tordjman, Sylvie

2013-09-01

Biological rhythms are crucial phenomena that are perfect examples of the adaptation of organisms to their environment. A considerable amount of work has described different types of biological rhythms (from circadian to ultradian), individual differences in their patterns and the complexity of their regulation. In particular, the regulation and maturation of the sleep-wake cycle have been thoroughly studied. Its desynchronization, both endogenous and exogenous, is now well understood, as are its consequences for cognitive impairments and health problems. From a completely different perspective, psychoanalysts have shown a growing interest in the rhythms of psychic life. This interest extends beyond the original focus of psychoanalysis on dreams and the sleep-wake cycle, incorporating central theoretical and practical psychoanalytic issues related to the core functioning of the psychic life: the rhythmic structures of drive dynamics, intersubjective developmental processes and psychic containment functions. Psychopathological and biological approaches to the study of infantile autism reveal the importance of specific biological and psychological rhythmic disturbances in this disorder. Considering data and hypotheses from both perspectives, this paper proposes an integrative approach to the study of these rhythmic disturbances and offers an etiopathogenic hypothesis based on this integrative approach. Copyright © 2013 Elsevier Ltd. All rights reserved.

3D printing of tissue-simulating phantoms as a traceable standard for biomedical optical measurement

NASA Astrophysics Data System (ADS)

Dong, Erbao; Wang, Minjie; Shen, Shuwei; Han, Yilin; Wu, Qiang; Xu, Ronald

2016-01-01

Optical phantoms are commonly used to validate and calibrate biomedical optical devices in order to ensure accurate measurement of optical properties in biological tissue. However, commonly used optical phantoms are based on homogenous materials that reflect neither optical properties nor multi-layer heterogeneities of biological tissue. Using these phantoms for optical calibration may result in significant bias in biological measurement. We propose to characterize and fabricate tissue simulating phantoms that simulate not only the multi-layer heterogeneities but also optical properties of biological tissue. The tissue characterization module detects tissue structural and functional properties in vivo. The phantom printing module generates 3D tissue structures at different scales by layer-by-layer deposition of phantom materials with different optical properties. The ultimate goal is to fabricate multi-layer tissue simulating phantoms as a traceable standard for optimal calibration of biomedical optical spectral devices.

A technique for measuring oxygen saturation in biological tissues based on diffuse optical spectroscopy

NASA Astrophysics Data System (ADS)

Kleshnin, Mikhail; Orlova, Anna; Kirillin, Mikhail; Golubiatnikov, German; Turchin, Ilya

2017-07-01

A new approach to optical measuring blood oxygen saturation was developed and implemented. This technique is based on an original three-stage algorithm for reconstructing the relative concentration of biological chromophores (hemoglobin, water, lipids) from the measured spectra of diffusely scattered light at different distances from the probing radiation source. The numerical experiments and approbation of the proposed technique on a biological phantom have shown the high reconstruction accuracy and the possibility of correct calculation of hemoglobin oxygenation in the presence of additive noise and calibration errors. The obtained results of animal studies have agreed with the previously published results of other research groups and demonstrated the possibility to apply the developed technique to monitor oxygen saturation in tumor tissue.

Parasites as Biological Tags for Stock Discrimination of Beaked Redfish (Sebastes mentella): Parasite Infra-Communities vs. Limited Resolution of Cytochrome Markers

PubMed Central

Klapper, Regina; Kochmann, Judith; O’Hara, Robert B.; Karl, Horst; Kuhn, Thomas

2016-01-01

The use of parasites as biological tags for discrimination of fish stocks has become a commonly used approach in fisheries management. Metazoan parasite community analysis and anisakid nematode population genetics based on a mitochondrial cytochrome marker were applied in order to assess the usefulness of the two parasitological methods for stock discrimination of beaked redfish Sebastes mentella of three fishing grounds in the North East Atlantic. Multivariate, model-based approaches demonstrated that the metazoan parasite fauna of beaked redfish from East Greenland differed from Tampen, northern North Sea, and Bear Island, Barents Sea. A joint model (latent variable model) was used to estimate the effects of covariates on parasite species and identified four parasite species as main source of differences among fishing grounds; namely Chondracanthus nodosus, Anisakis simplex s.s., Hysterothylacium aduncum, and Bothriocephalus scorpii. Due to its high abundance and differences between fishing grounds, Anisakis simplex s.s. was considered as a major biological tag for host stock differentiation. Whilst the sole examination of Anisakis simplex s.s. on a population genetic level is only of limited use, anisakid nematodes (in particular, A. simplex s.s.) can serve as biological tags on a parasite community level. This study confirmed the use of multivariate analyses as a tool to evaluate parasite infra-communities and to identify parasite species that might serve as biological tags. The present study suggests that S. mentella in the northern North Sea and Barents Sea is not sub-structured. PMID:27104735

Home-Based vs. Laboratory-Based Practical Activities in the Learning of Human Physiology: The Perception of Students

ERIC Educational Resources Information Center

Neves, Ben-Hur S.; Altermann, Caroline; Gonçalves, Rithiele; Lara, Marcus Vinícius; Mello-Carpes, Pâmela B.

2017-01-01

Different tools have been used to facilitate the teaching and learning process in different areas of knowledge. Practical activities represent a form of teaching in which students not only listen to theoretical concepts but are also able to link theory and practice, and their importance in the biological sciences is notable. Sometimes, however,…

A neuromorphic circuit mimicking biological short-term memory.

PubMed

Barzegarjalali, Saeid; Parker, Alice C

2016-08-01

Research shows that the way we remember things for a few seconds is a different mechanism from the way we remember things for a longer time. Short-term memory is based on persistently firing neurons, whereas storing information for a longer time is based on strengthening the synapses or even forming new neural connections. Information about location and appearance of an object is segregated and processed by separate neurons. Furthermore neurons can continue firing using different mechanisms. Here, we have designed a biomimetic neuromorphic circuit that mimics short-term memory by firing neurons, using biological mechanisms to remember location and shape of an object. Our neuromorphic circuit has a hybrid architecture. Neurons are designed with CMOS 45nm technology and synapses are designed with carbon nanotubes (CNT).

FPGA implementation of a configurable neuromorphic CPG-based locomotion controller.

PubMed

Barron-Zambrano, Jose Hugo; Torres-Huitzil, Cesar

2013-09-01

Neuromorphic engineering is a discipline devoted to the design and development of computational hardware that mimics the characteristics and capabilities of neuro-biological systems. In recent years, neuromorphic hardware systems have been implemented using a hybrid approach incorporating digital hardware so as to provide flexibility and scalability at the cost of power efficiency and some biological realism. This paper proposes an FPGA-based neuromorphic-like embedded system on a chip to generate locomotion patterns of periodic rhythmic movements inspired by Central Pattern Generators (CPGs). The proposed implementation follows a top-down approach where modularity and hierarchy are two desirable features. The locomotion controller is based on CPG models to produce rhythmic locomotion patterns or gaits for legged robots such as quadrupeds and hexapods. The architecture is configurable and scalable for robots with either different morphologies or different degrees of freedom (DOFs). Experiments performed on a real robot are presented and discussed. The obtained results demonstrate that the CPG-based controller provides the necessary flexibility to generate different rhythmic patterns at run-time suitable for adaptable locomotion. Copyright © 2013 Elsevier Ltd. All rights reserved.

Population-based differences in treatment outcome following anticancer drug therapies.

PubMed

Ma, Brigette By; Hui, Edwin P; Mok, Tony Sk

2010-01-01

Population-based differences in toxicity and clinical outcome following treatment with anticancer drugs have an important effect on oncology practice and drug development. These differences arise from complex interactions between biological and environmental factors, which include genetic diversity affecting drug metabolism and the expression of drug targets, variations in tumour biology and host physiology, socioeconomic disparities, and regional preferences in treatment standards. Some well-known examples include the high prevalence of activating epidermal growth factor receptor (EGFR) mutations in pulmonary adenocarcinoma among northeast (China, Japan, Korea) and parts of southeast Asia (excluding India) non-smokers, which predict sensitivity to EGFR kinase inhibitors, and the sharp contrast between Japan and the west in the management and survival outcome of gastric cancer. This review is a critical overview of population-based differences in the four most prevalent cancers in the world: lung, breast, colorectal, and stomach cancer. Particular attention is given to the clinical relevance of such knowledge in terms of the individualisation of drug therapy and in the design of clinical trials. Copyright (c) 2010 Elsevier Ltd. All rights reserved.

Targeting oncogenic vulnerabilities in triple negative breast cancer: biological bases and ongoing clinical studies

PubMed Central

Ocana, Alberto; Pandiella, Atanasio

2017-01-01

Triple negative breast cancer (TNBC) is still an incurable disease despite the great scientific effort performed during the last years. The huge heterogeneity of this disease has motivated the evaluation of a great number of therapies against different molecular alterations. In this article, we review the biological bases of this entity and how the known molecular evidence supports the current preclinical and clinical development of new therapies. Special attention will be given to ongoing clinical studies and potential options for future drug combinations. PMID:28108739

A comprehensive company database analysis of biological assay variability.

PubMed

Kramer, Christian; Dahl, Göran; Tyrchan, Christian; Ulander, Johan

2016-08-01

Analysis of data from various compounds measured in diverse biological assays is a central part of drug discovery research projects. However, no systematic overview of the variability in biological assays has been published and judgments on assay quality and robustness of data are often based on personal belief and experience within the drug discovery community. To address this we performed a reproducibility analysis of all biological assays at AstraZeneca between 2005 and 2014. We found an average experimental uncertainty of less than a twofold difference and no technologies or assay types had higher variability than others. This work suggests that robust data can be obtained from the most commonly applied biological assays. Copyright © 2016. Published by Elsevier Ltd.

Physical Activity and Movement Proficiency: The Need for a Biocultural Approach.

PubMed

Malina, Robert M; Cumming, Sean P; Coelho E Silva, Manuel J

2016-05-01

"Gaps in Our Knowledge" are discussed in the context of the need to integrate biological and behavioral factors in a biocultural approach to physical activity and movement proficiency. Specific issues considered include outdoor play, organized and informal activity, biological maturation, tracking of activity, development of movement proficiency, and individual differences. Studies considered are largely based on youth in economically better-off, developed countries in the western culture context. There is a need to extend studies of physical activity and movement proficiency to different cultural contexts.

Biological sex affects the neurobiology of autism

PubMed Central

Lombardo, Michael V.; Suckling, John; Ruigrok, Amber N. V.; Chakrabarti, Bhismadev; Ecker, Christine; Deoni, Sean C. L.; Craig, Michael C.; Murphy, Declan G. M.; Bullmore, Edward T.; Baron-Cohen, Simon

2013-01-01

In autism, heterogeneity is the rule rather than the exception. One obvious source of heterogeneity is biological sex. Since autism was first recognized, males with autism have disproportionately skewed research. Females with autism have thus been relatively overlooked, and have generally been assumed to have the same underlying neurobiology as males with autism. Growing evidence, however, suggests that this is an oversimplification that risks obscuring the biological base of autism. This study seeks to answer two questions about how autism is modulated by biological sex at the level of the brain: (i) is the neuroanatomy of autism different in males and females? and (ii) does the neuroanatomy of autism fit predictions from the ‘extreme male brain’ theory of autism, in males and/or in females? Neuroanatomical features derived from voxel-based morphometry were compared in a sample of equal-sized high-functioning male and female adults with and without autism (n = 120, n = 30/group). The first question was investigated using a 2 × 2 factorial design, and by spatial overlap analyses of the neuroanatomy of autism in males and females. The second question was tested through spatial overlap analyses of specific patterns predicted by the extreme male brain theory. We found that the neuroanatomy of autism differed between adult males and females, evidenced by minimal spatial overlap (not different from that occurred under random condition) in both grey and white matter, and substantially large white matter regions showing significant sex × diagnosis interactions in the 2 × 2 factorial design. These suggest that autism manifests differently by biological sex. Furthermore, atypical brain areas in females with autism substantially and non-randomly (P < 0.001) overlapped with areas that were sexually dimorphic in neurotypical controls, in both grey and white matter, suggesting neural ‘masculinization’. This was not seen in males with autism. How differences in neuroanatomy relate to the similarities in cognition between males and females with autism remains to be understood. Future research should stratify by biological sex to reduce heterogeneity and to provide greater insight into the neurobiology of autism. PMID:23935125

Across the Great Divide: The Effects of Technology in Secondary Biology Classrooms

NASA Astrophysics Data System (ADS)

Worley, Johnny Howard, II

This study investigates the relationship between technology use and student achievement in public high school across North Carolina. The purpose of this study was to determine whether a digital divide (differences in technology utilization based on student demographics of race/ethnicity, gender, socioeconomic status, and municipality) exists among schools and whether those differences relate to student achievement in high school biology classrooms. The study uses North Carolina end-of-course (EOC) data for biology to analyze student demographic data and assessment results from the 2010-2011 school year from the North Carolina Department of Public Instruction. The data analyses use descriptive and factorial univariate statistics to determine the existence of digital divides and their effects on biology achievement. Analysis of these data described patterns of technology use to determine whether potential variances resulted in a digital divide. Specific technology uses were identified in the data and then their impact on biology achievement scores within various demographic groups was examined. Research findings revealed statistically significant variations of use within different population groups. Despite being statistically significant, the relevance of the association in the variations was minimal at best -- based on the effect scale established by Cohen (1988). Additional factorial univariate analyses were employed to determine potential relationships between technology use and student achievement. The data revealed that technology use did not influence the variation of student achievement scale scores as much as race/ethnicity and socioeconomic status. White students outperformed Hispanic students by an average of three scale score points and Black students by an average of six scale score points. Technology use alone averaged less than a one point difference in mean scale scores, and only when interacting with race, gender, and/or SES did the mean difference increase. However, this increase within the context of the biology scale score range was negligible. This study contributes to the existing body of research on the effects of technology use on student achievement and its influence within various student demographic groups and municipalities. The study also provides additional research information for effective technology utilization, implementation, and instruction in educational environments.

Biological sex affects the neurobiology of autism.

PubMed

Lai, Meng-Chuan; Lombardo, Michael V; Suckling, John; Ruigrok, Amber N V; Chakrabarti, Bhismadev; Ecker, Christine; Deoni, Sean C L; Craig, Michael C; Murphy, Declan G M; Bullmore, Edward T; Baron-Cohen, Simon

2013-09-01

In autism, heterogeneity is the rule rather than the exception. One obvious source of heterogeneity is biological sex. Since autism was first recognized, males with autism have disproportionately skewed research. Females with autism have thus been relatively overlooked, and have generally been assumed to have the same underlying neurobiology as males with autism. Growing evidence, however, suggests that this is an oversimplification that risks obscuring the biological base of autism. This study seeks to answer two questions about how autism is modulated by biological sex at the level of the brain: (i) is the neuroanatomy of autism different in males and females? and (ii) does the neuroanatomy of autism fit predictions from the 'extreme male brain' theory of autism, in males and/or in females? Neuroanatomical features derived from voxel-based morphometry were compared in a sample of equal-sized high-functioning male and female adults with and without autism (n = 120, n = 30/group). The first question was investigated using a 2 × 2 factorial design, and by spatial overlap analyses of the neuroanatomy of autism in males and females. The second question was tested through spatial overlap analyses of specific patterns predicted by the extreme male brain theory. We found that the neuroanatomy of autism differed between adult males and females, evidenced by minimal spatial overlap (not different from that occurred under random condition) in both grey and white matter, and substantially large white matter regions showing significant sex × diagnosis interactions in the 2 × 2 factorial design. These suggest that autism manifests differently by biological sex. Furthermore, atypical brain areas in females with autism substantially and non-randomly (P < 0.001) overlapped with areas that were sexually dimorphic in neurotypical controls, in both grey and white matter, suggesting neural 'masculinization'. This was not seen in males with autism. How differences in neuroanatomy relate to the similarities in cognition between males and females with autism remains to be understood. Future research should stratify by biological sex to reduce heterogeneity and to provide greater insight into the neurobiology of autism.

Illustrations of mathematical modeling in biology: epigenetics, meiosis, and an outlook.

PubMed

Richards, D; Berry, S; Howard, M

2012-01-01

In the past few years, mathematical modeling approaches in biology have begun to fulfill their promise by assisting in the dissection of complex biological systems. Here, we review two recent examples of predictive mathematical modeling in plant biology. The first involves the quantitative epigenetic silencing of the floral repressor gene FLC in Arabidopsis, mediated by a Polycomb-based system. The second involves the spatiotemporal dynamics of telomere bouquet formation in wheat-rye meiosis. Although both the biology and the modeling framework of the two systems are different, both exemplify how mathematical modeling can help to accelerate discovery of the underlying mechanisms in complex biological systems. In both cases, the models that developed were relatively minimal, including only essential features, but both nevertheless yielded fundamental insights. We also briefly review the current state of mathematical modeling in biology, difficulties inherent in its application, and its potential future development.

Patient characteristics influence the choice of biological drug in RA, and will make non-TNFi biologics appear more harmful than TNFi biologics.

PubMed

Frisell, Thomas; Baecklund, Eva; Bengtsson, Karin; Di Giuseppe, Daniela; Forsblad-d'Elia, Helena; Askling, Johan

2018-05-01

With the wide range of biological disease-modifying anti-rheumatic drugs (bDMARDs) available for treating rheumatoid arthritis (RA), and limited evidence to guide the choice for individual patients, we wished to evaluate whether patient characteristics influence the choice of bDMARD in clinical practice, and to quantify the extent to which this would bias direct comparisons of treatment outcome. Register-based study of all Swedish patients with RA initiating necrosis factor inhibitor (TNFi), rituximab, abatacept or tocilizumab in 2011-2015 as their first bDMARD (n=6481), or after switch from TNFi as first bDMARD (n=2829). Group differences in demographics, clinical characteristics and medical history were assessed in multivariable regression models. Predicted differences in safety and treatment outcomes were calculated as a function of patient characteristics, through regression modelling based on observed outcomes among patients with RA starting bDMARDs 2006-2010. Patients starting non-TNFi were older than those starting TNFi, had lower socioeconomic status, higher disease activity and higher burden of diseases including malignancy, serious infections and diabetes. Differences were most pronounced at first bDMARD initiation. These factors were linked to treatment outcome independent of therapy, yielding worse apparent safety and effectiveness for non-TNFi biologics, most extreme for rituximab. Standardising to the age/sex distribution of the TNFi group reduced differences considerably. There was significant channelling of older and less healthy patients with RA to non-TNFi bDMARDs, in particular as first bDMARD. Whether this channelling represents a maximised benefit/risk ratio is unclear. Unless differences in age, medical history and disease activity are accounted for, they will substantially confound non-randomised comparative studies of available bDMARDs' safety and effectiveness. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

SU-F-T-193: Evaluation of a GPU-Based Fast Monte Carlo Code for Proton Therapy Biological Optimization

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

Taleei, R; Qin, N; Jiang, S

2016-06-15

Purpose: Biological treatment plan optimization is of great interest for proton therapy. It requires extensive Monte Carlo (MC) simulations to compute physical dose and biological quantities. Recently, a gPMC package was developed for rapid MC dose calculations on a GPU platform. This work investigated its suitability for proton therapy biological optimization in terms of accuracy and efficiency. Methods: We performed simulations of a proton pencil beam with energies of 75, 150 and 225 MeV in a homogeneous water phantom using gPMC and FLUKA. Physical dose and energy spectra for each ion type on the central beam axis were scored. Relativemore » Biological Effectiveness (RBE) was calculated using repair-misrepair-fixation model. Microdosimetry calculations were performed using Monte Carlo Damage Simulation (MCDS). Results: Ranges computed by the two codes agreed within 1 mm. Physical dose difference was less than 2.5 % at the Bragg peak. RBE-weighted dose agreed within 5 % at the Bragg peak. Differences in microdosimetric quantities such as dose average lineal energy transfer and specific energy were < 10%. The simulation time per source particle with FLUKA was 0.0018 sec, while gPMC was ∼ 600 times faster. Conclusion: Physical dose computed by FLUKA and gPMC were in a good agreement. The RBE differences along the central axis were small, and RBE-weighted dose difference was found to be acceptable. The combined accuracy and efficiency makes gPMC suitable for proton therapy biological optimization.« less

Modularization of biochemical networks based on classification of Petri net t-invariants.

PubMed

Grafahrend-Belau, Eva; Schreiber, Falk; Heiner, Monika; Sackmann, Andrea; Junker, Björn H; Grunwald, Stefanie; Speer, Astrid; Winder, Katja; Koch, Ina

2008-02-08

Structural analysis of biochemical networks is a growing field in bioinformatics and systems biology. The availability of an increasing amount of biological data from molecular biological networks promises a deeper understanding but confronts researchers with the problem of combinatorial explosion. The amount of qualitative network data is growing much faster than the amount of quantitative data, such as enzyme kinetics. In many cases it is even impossible to measure quantitative data because of limitations of experimental methods, or for ethical reasons. Thus, a huge amount of qualitative data, such as interaction data, is available, but it was not sufficiently used for modeling purposes, until now. New approaches have been developed, but the complexity of data often limits the application of many of the methods. Biochemical Petri nets make it possible to explore static and dynamic qualitative system properties. One Petri net approach is model validation based on the computation of the system's invariant properties, focusing on t-invariants. T-invariants correspond to subnetworks, which describe the basic system behavior.With increasing system complexity, the basic behavior can only be expressed by a huge number of t-invariants. According to our validation criteria for biochemical Petri nets, the necessary verification of the biological meaning, by interpreting each subnetwork (t-invariant) manually, is not possible anymore. Thus, an automated, biologically meaningful classification would be helpful in analyzing t-invariants, and supporting the understanding of the basic behavior of the considered biological system. Here, we introduce a new approach to automatically classify t-invariants to cope with network complexity. We apply clustering techniques such as UPGMA, Complete Linkage, Single Linkage, and Neighbor Joining in combination with different distance measures to get biologically meaningful clusters (t-clusters), which can be interpreted as modules. To find the optimal number of t-clusters to consider for interpretation, the cluster validity measure, Silhouette Width, is applied. We considered two different case studies as examples: a small signal transduction pathway (pheromone response pathway in Saccharomyces cerevisiae) and a medium-sized gene regulatory network (gene regulation of Duchenne muscular dystrophy). We automatically classified the t-invariants into functionally distinct t-clusters, which could be interpreted biologically as functional modules in the network. We found differences in the suitability of the various distance measures as well as the clustering methods. In terms of a biologically meaningful classification of t-invariants, the best results are obtained using the Tanimoto distance measure. Considering clustering methods, the obtained results suggest that UPGMA and Complete Linkage are suitable for clustering t-invariants with respect to the biological interpretability. We propose a new approach for the biological classification of Petri net t-invariants based on cluster analysis. Due to the biologically meaningful data reduction and structuring of network processes, large sets of t-invariants can be evaluated, allowing for model validation of qualitative biochemical Petri nets. This approach can also be applied to elementary mode analysis.

Modularization of biochemical networks based on classification of Petri net t-invariants

PubMed Central

Grafahrend-Belau, Eva; Schreiber, Falk; Heiner, Monika; Sackmann, Andrea; Junker, Björn H; Grunwald, Stefanie; Speer, Astrid; Winder, Katja; Koch, Ina

2008-01-01

Background Structural analysis of biochemical networks is a growing field in bioinformatics and systems biology. The availability of an increasing amount of biological data from molecular biological networks promises a deeper understanding but confronts researchers with the problem of combinatorial explosion. The amount of qualitative network data is growing much faster than the amount of quantitative data, such as enzyme kinetics. In many cases it is even impossible to measure quantitative data because of limitations of experimental methods, or for ethical reasons. Thus, a huge amount of qualitative data, such as interaction data, is available, but it was not sufficiently used for modeling purposes, until now. New approaches have been developed, but the complexity of data often limits the application of many of the methods. Biochemical Petri nets make it possible to explore static and dynamic qualitative system properties. One Petri net approach is model validation based on the computation of the system's invariant properties, focusing on t-invariants. T-invariants correspond to subnetworks, which describe the basic system behavior. With increasing system complexity, the basic behavior can only be expressed by a huge number of t-invariants. According to our validation criteria for biochemical Petri nets, the necessary verification of the biological meaning, by interpreting each subnetwork (t-invariant) manually, is not possible anymore. Thus, an automated, biologically meaningful classification would be helpful in analyzing t-invariants, and supporting the understanding of the basic behavior of the considered biological system. Methods Here, we introduce a new approach to automatically classify t-invariants to cope with network complexity. We apply clustering techniques such as UPGMA, Complete Linkage, Single Linkage, and Neighbor Joining in combination with different distance measures to get biologically meaningful clusters (t-clusters), which can be interpreted as modules. To find the optimal number of t-clusters to consider for interpretation, the cluster validity measure, Silhouette Width, is applied. Results We considered two different case studies as examples: a small signal transduction pathway (pheromone response pathway in Saccharomyces cerevisiae) and a medium-sized gene regulatory network (gene regulation of Duchenne muscular dystrophy). We automatically classified the t-invariants into functionally distinct t-clusters, which could be interpreted biologically as functional modules in the network. We found differences in the suitability of the various distance measures as well as the clustering methods. In terms of a biologically meaningful classification of t-invariants, the best results are obtained using the Tanimoto distance measure. Considering clustering methods, the obtained results suggest that UPGMA and Complete Linkage are suitable for clustering t-invariants with respect to the biological interpretability. Conclusion We propose a new approach for the biological classification of Petri net t-invariants based on cluster analysis. Due to the biologically meaningful data reduction and structuring of network processes, large sets of t-invariants can be evaluated, allowing for model validation of qualitative biochemical Petri nets. This approach can also be applied to elementary mode analysis. PMID:18257938

Modeling languages for biochemical network simulation: reaction vs equation based approaches.

PubMed

Wiechert, Wolfgang; Noack, Stephan; Elsheikh, Atya

2010-01-01

Biochemical network modeling and simulation is an essential task in any systems biology project. The systems biology markup language (SBML) was established as a standardized model exchange language for mechanistic models. A specific strength of SBML is that numerous tools for formulating, processing, simulation and analysis of models are freely available. Interestingly, in the field of multidisciplinary simulation, the problem of model exchange between different simulation tools occurred much earlier. Several general modeling languages like Modelica have been developed in the 1990s. Modelica enables an equation based modular specification of arbitrary hierarchical differential algebraic equation models. Moreover, libraries for special application domains can be rapidly developed. This contribution compares the reaction based approach of SBML with the equation based approach of Modelica and explains the specific strengths of both tools. Several biological examples illustrating essential SBML and Modelica concepts are given. The chosen criteria for tool comparison are flexibility for constraint specification, different modeling flavors, hierarchical, modular and multidisciplinary modeling. Additionally, support for spatially distributed systems, event handling and network analysis features is discussed. As a major result it is shown that the choice of the modeling tool has a strong impact on the expressivity of the specified models but also strongly depends on the requirements of the application context.

Disease gene classification with metagraph representations.

PubMed

Kircali Ata, Sezin; Fang, Yuan; Wu, Min; Li, Xiao-Li; Xiao, Xiaokui

2017-12-01

Protein-protein interaction (PPI) networks play an important role in studying the functional roles of proteins, including their association with diseases. However, protein interaction networks are not sufficient without the support of additional biological knowledge for proteins such as their molecular functions and biological processes. To complement and enrich PPI networks, we propose to exploit biological properties of individual proteins. More specifically, we integrate keywords describing protein properties into the PPI network, and construct a novel PPI-Keywords (PPIK) network consisting of both proteins and keywords as two different types of nodes. As disease proteins tend to have a similar topological characteristics on the PPIK network, we further propose to represent proteins with metagraphs. Different from a traditional network motif or subgraph, a metagraph can capture a particular topological arrangement involving the interactions/associations between both proteins and keywords. Based on the novel metagraph representations for proteins, we further build classifiers for disease protein classification through supervised learning. Our experiments on three different PPI databases demonstrate that the proposed method consistently improves disease protein prediction across various classifiers, by 15.3% in AUC on average. It outperforms the baselines including the diffusion-based methods (e.g., RWR) and the module-based methods by 13.8-32.9% for overall disease protein prediction. For predicting breast cancer genes, it outperforms RWR, PRINCE and the module-based baselines by 6.6-14.2%. Finally, our predictions also turn out to have better correlations with literature findings from PubMed. Copyright © 2017 Elsevier Inc. All rights reserved.

Virtual screening applications: a study of ligand-based methods and different structure representations in four different scenarios.

PubMed

Hristozov, Dimitar P; Oprea, Tudor I; Gasteiger, Johann

2007-01-01

Four different ligand-based virtual screening scenarios are studied: (1) prioritizing compounds for subsequent high-throughput screening (HTS); (2) selecting a predefined (small) number of potentially active compounds from a large chemical database; (3) assessing the probability that a given structure will exhibit a given activity; (4) selecting the most active structure(s) for a biological assay. Each of the four scenarios is exemplified by performing retrospective ligand-based virtual screening for eight different biological targets using two large databases--MDDR and WOMBAT. A comparison between the chemical spaces covered by these two databases is presented. The performance of two techniques for ligand--based virtual screening--similarity search with subsequent data fusion (SSDF) and novelty detection with Self-Organizing Maps (ndSOM) is investigated. Three different structure representations--2,048-dimensional Daylight fingerprints, topological autocorrelation weighted by atomic physicochemical properties (sigma electronegativity, polarizability, partial charge, and identity) and radial distribution functions weighted by the same atomic physicochemical properties--are compared. Both methods were found applicable in scenario one. The similarity search was found to perform slightly better in scenario two while the SOM novelty detection is preferred in scenario three. No method/descriptor combination achieved significant success in scenario four.

Agent-based modeling: case study in cleavage furrow models.

PubMed

Mogilner, Alex; Manhart, Angelika

2016-11-07

The number of studies in cell biology in which quantitative models accompany experiments has been growing steadily. Roughly, mathematical and computational techniques of these models can be classified as "differential equation based" (DE) or "agent based" (AB). Recently AB models have started to outnumber DE models, but understanding of AB philosophy and methodology is much less widespread than familiarity with DE techniques. Here we use the history of modeling a fundamental biological problem-positioning of the cleavage furrow in dividing cells-to explain how and why DE and AB models are used. We discuss differences, advantages, and shortcomings of these two approaches. © 2016 Mogilner and Manhart. This article is distributed by The American Society for Cell Biology under license from the author(s). Two months after publication it is available to the public under an Attribution–Noncommercial–Share Alike 3.0 Unported Creative Commons License (http://creativecommons.org/licenses/by-nc-sa/3.0).

Testing Silica Fume-Based Concrete Composites under Chemical and Microbiological Sulfate Attacks

PubMed Central

Estokova, Adriana; Kovalcikova, Martina; Luptakova, Alena; Prascakova, Maria

2016-01-01

Current design practices based on descriptive approaches to concrete specification may not be appropriate for the management of aggressive environments. In this study, the durability of cement-based materials with and without the addition of silica fume, subjected to conditions that leach calcium and silicon, were investigated. Chemical corrosion was simulated by employing various H2SO4 and MgSO4 solutions, and biological corrosion was simulated using Acidithiobacillus sp. bacterial inoculation, leading to disrupted and damaged surfaces; the samples’ mass changes were studied following both chemical and biological attacks. Different leaching trends were observed via X-ray fluorescence when comparing chemical with biological leaching. Lower leaching rates were found for concrete samples fortified with silica fume than those without silica fume. X-ray diffraction and scanning electron microscopy confirmed a massive sulfate precipitate formation on the concrete surface due to bacterial exposure. PMID:28773452

Application of a Nanostructured Enzymatic Biosensor Based on Fullerene and Gold Nanoparticles to Polyphenol Detection.

PubMed

Tortolini, Cristina; Sanzò, Gabriella; Antiochia, Riccarda; Mazzei, Franco; Favero, Gabriele

2017-01-01

Electrochemical biosensors provide an attractive means of analyzing the content of a biological sample due to the direct conversion of a biological event to an electronic signal. The signal transduction and the general performance of electrochemical biosensors are often determined by the surface architectures that connect the sensing element to the biological sample at the nanometer scale. The most common surface modification techniques, the various electrochemical transduction mechanisms, and the choice of the recognition receptor molecules all influence the ultimate sensitivity of the sensor. We show herein a novel electrochemical biosensing platform based on the coupling of two different nanostructured materials (gold nanoparticles and fullerenols) displaying interesting electrochemical features. The use of these nanomaterials improved the electrochemical performance of the proposed biosensor.An application of the nanostructured enzyme-based biosensor has been developed for evaluating the detection of polyphenols either in buffer solution or in real wine samples.

Physiologically based pharmacokinetic (PBPK) modeling considering methylated trivalent arsenicals

EPA Science Inventory

PBPK modeling provides a quantitative biologically-based framework to integrate diverse types of information for application to risk analysis. For example, genetic polymorphisms in arsenic metabolizing enzymes (AS3MT) can lead to differences in target tissue dosimetry for key tri...

Modeling of contact theories for the manipulation of biological micro/nanoparticles in the form of circular crowned rollers based on the atomic force microscope

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

Korayem, M. H.; Khaksar, H.; Taheri, M.

2013-11-14

This article has dealt with the development and modeling of various contact theories for biological nanoparticles shaped as cylinders and circular crowned rollers for application in the manipulation of different biological micro/nanoparticles based on Atomic Force Microscope. First, the effective contact forces were simulated, and their impact on contact mechanics simulation was investigated. In the next step, the Hertz contact model was simulated and compared for gold and DNA nanoparticles with the three types of spherical, cylindrical, and circular crowned roller type contact geometries. Then by reducing the length of the cylindrical section in the circular crowned roller geometry, themore » geometry of the body was made to approach that of a sphere, and the results were compared for DNA nanoparticles. To anticipatory validate the developed theories, the results of the cylindrical and the circular crowned roller contacts were compared with the results of the existing spherical contact simulations. Following the development of these contact models for the manipulation of various biological micro/nanoparticles, the cylindrical and the circular crowned roller type contact theories were modeled based on the theories of Lundberg, Dowson, Nikpur, Heoprich, and Hertz for the manipulation of biological micro/nanoparticles. Then, for a more accurate validation, the results obtained from the simulations were compared with those obtained by the finite element method and with the experimental results available in previous articles. The previous research works on the simulation of nanomanipulation have mainly investigated the contact theories used in the manipulation of spherical micro/nanoparticles. However since in real biomanipulation situations, biological micro/nanoparticles of more complex shapes need to be displaced in biological environments, this article therefore has modeled and compared, for the first time, different contact theories for use in the biomanipulation of cylindrical and circular crowned roller shaped micro/nanoparticles. The results of models indicate that the contact model of Hertz achieves the largest amount of deformation for the DNA nanoparticle in cylindrical form and the contact model of Heoprich achieves the largest deformation for the circular crowned roller shaped DNA. Of course, this finding is not always true for the other nanoparticles; and considering the mechanical and environmental characteristics, different results can be obtained. Also, by comparing the deformations of different types of nanoparticles, it was determined that the platelet type nanoparticles display the highest degree of deformation in all the considered models, due to their particular mechanical characteristics.« less

Recent Progress in Optical Biosensors Based on Smartphone Platforms

PubMed Central

Geng, Zhaoxin; Zhang, Xiong; Fan, Zhiyuan; Lv, Xiaoqing; Su, Yue; Chen, Hongda

2017-01-01

With a rapid improvement of smartphone hardware and software, especially complementary metal oxide semiconductor (CMOS) cameras, many optical biosensors based on smartphone platforms have been presented, which have pushed the development of the point-of-care testing (POCT). Imaging-based and spectrometry-based detection techniques have been widely explored via different approaches. Combined with the smartphone, imaging-based and spectrometry-based methods are currently used to investigate a wide range of molecular properties in chemical and biological science for biosensing and diagnostics. Imaging techniques based on smartphone-based microscopes are utilized to capture microscale analysts, while spectrometry-based techniques are used to probe reactions or changes of molecules. Here, we critically review the most recent progress in imaging-based and spectrometry-based smartphone-integrated platforms that have been developed for chemical experiments and biological diagnosis. We focus on the analytical performance and the complexity for implementation of the platforms. PMID:29068375

Recent Progress in Optical Biosensors Based on Smartphone Platforms.

PubMed

Geng, Zhaoxin; Zhang, Xiong; Fan, Zhiyuan; Lv, Xiaoqing; Su, Yue; Chen, Hongda

2017-10-25

With a rapid improvement of smartphone hardware and software, especially complementary metal oxide semiconductor (CMOS) cameras, many optical biosensors based on smartphone platforms have been presented, which have pushed the development of the point-of-care testing (POCT). Imaging-based and spectrometry-based detection techniques have been widely explored via different approaches. Combined with the smartphone, imaging-based and spectrometry-based methods are currently used to investigate a wide range of molecular properties in chemical and biological science for biosensing and diagnostics. Imaging techniques based on smartphone-based microscopes are utilized to capture microscale analysts, while spectrometry-based techniques are used to probe reactions or changes of molecules. Here, we critically review the most recent progress in imaging-based and spectrometry-based smartphone-integrated platforms that have been developed for chemical experiments and biological diagnosis. We focus on the analytical performance and the complexity for implementation of the platforms.

Fast Biological Modeling for Voxel-based Heavy Ion Treatment Planning Using the Mechanistic Repair-Misrepair-Fixation Model and Nuclear Fragment Spectra

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

Kamp, Florian; Department of Radiation Oncology, Technische Universität München, Klinikum Rechts der Isar, München; Physik-Department, Technische Universität München, Garching

2015-11-01

Purpose: The physical and biological differences between heavy ions and photons have not been fully exploited and could improve treatment outcomes. In carbon ion therapy, treatment planning must account for physical properties, such as the absorbed dose and nuclear fragmentation, and for differences in the relative biological effectiveness (RBE) of ions compared with photons. We combined the mechanistic repair-misrepair-fixation (RMF) model with Monte Carlo-generated fragmentation spectra for biological optimization of carbon ion treatment plans. Methods and Materials: Relative changes in double-strand break yields and radiosensitivity parameters with particle type and energy were determined using the independently benchmarked Monte Carlo damagemore » simulation and the RMF model to estimate the RBE values for primary carbon ions and secondary fragments. Depth-dependent energy spectra were generated with the Monte Carlo code FLUKA for clinically relevant initial carbon ion energies. The predicted trends in RBE were compared with the published experimental data. Biological optimization for carbon ions was implemented in a 3-dimensional research treatment planning tool. Results: We compared the RBE and RBE-weighted dose (RWD) distributions of different carbon ion treatment scenarios with and without nuclear fragments. The inclusion of fragments in the simulations led to smaller RBE predictions. A validation of RMF against measured cell survival data reported in published studies showed reasonable agreement. We calculated and optimized the RWD distributions on patient data and compared the RMF predictions with those from other biological models. The RBE values in an astrocytoma tumor ranged from 2.2 to 4.9 (mean 2.8) for a RWD of 3 Gy(RBE) assuming (α/β){sub X} = 2 Gy. Conclusions: These studies provide new information to quantify and assess uncertainties in the clinically relevant RBE values for carbon ion therapy based on biophysical mechanisms. We present results from the first biological optimization of carbon ion radiation therapy beams on patient data using a combined RMF and Monte Carlo damage simulation modeling approach. The presented method is advantageous for fast biological optimization.« less

Fast Biological Modeling for Voxel-based Heavy Ion Treatment Planning Using the Mechanistic Repair-Misrepair-Fixation Model and Nuclear Fragment Spectra.

PubMed

Kamp, Florian; Cabal, Gonzalo; Mairani, Andrea; Parodi, Katia; Wilkens, Jan J; Carlson, David J

2015-11-01

The physical and biological differences between heavy ions and photons have not been fully exploited and could improve treatment outcomes. In carbon ion therapy, treatment planning must account for physical properties, such as the absorbed dose and nuclear fragmentation, and for differences in the relative biological effectiveness (RBE) of ions compared with photons. We combined the mechanistic repair-misrepair-fixation (RMF) model with Monte Carlo-generated fragmentation spectra for biological optimization of carbon ion treatment plans. Relative changes in double-strand break yields and radiosensitivity parameters with particle type and energy were determined using the independently benchmarked Monte Carlo damage simulation and the RMF model to estimate the RBE values for primary carbon ions and secondary fragments. Depth-dependent energy spectra were generated with the Monte Carlo code FLUKA for clinically relevant initial carbon ion energies. The predicted trends in RBE were compared with the published experimental data. Biological optimization for carbon ions was implemented in a 3-dimensional research treatment planning tool. We compared the RBE and RBE-weighted dose (RWD) distributions of different carbon ion treatment scenarios with and without nuclear fragments. The inclusion of fragments in the simulations led to smaller RBE predictions. A validation of RMF against measured cell survival data reported in published studies showed reasonable agreement. We calculated and optimized the RWD distributions on patient data and compared the RMF predictions with those from other biological models. The RBE values in an astrocytoma tumor ranged from 2.2 to 4.9 (mean 2.8) for a RWD of 3 Gy(RBE) assuming (α/β)X = 2 Gy. These studies provide new information to quantify and assess uncertainties in the clinically relevant RBE values for carbon ion therapy based on biophysical mechanisms. We present results from the first biological optimization of carbon ion radiation therapy beams on patient data using a combined RMF and Monte Carlo damage simulation modeling approach. The presented method is advantageous for fast biological optimization. Copyright © 2015 Elsevier Inc. All rights reserved.

Culture and social support: neural bases and biological impact.

PubMed

Sherman, David K; Kim, Heejung S; Taylor, Shelley E

2009-01-01

Social support is an effective means by which people cope with stressful events, and consequently, it beneficially affects health and well-being. Yet there are profound cultural differences in the effectiveness of different types of support and how people use their support networks. In this paper, we examine research on the impact of culture on social support, the neural underpinnings of social support, and how cultural differences in social support seeking are manifested biologically. We focus on cultural factors that may affect individuals' decisions to seek or not to seek social support and how culture moderates the impact of support seeking on biological and psychological health outcomes. We also examine recent research on the interaction between genes and culture in social support use. Discussion centers on the importance of developing an overarching framework of social support that integrates health psychology, cultural psychology, social neuroscience, and genetics.

ISOL@: an Italian SOLAnaceae genomics resource.

PubMed

Chiusano, Maria Luisa; D'Agostino, Nunzio; Traini, Alessandra; Licciardello, Concetta; Raimondo, Enrico; Aversano, Mario; Frusciante, Luigi; Monti, Luigi

2008-03-26

Present-day '-omics' technologies produce overwhelming amounts of data which include genome sequences, information on gene expression (transcripts and proteins) and on cell metabolic status. These data represent multiple aspects of a biological system and need to be investigated as a whole to shed light on the mechanisms which underpin the system functionality. The gathering and convergence of data generated by high-throughput technologies, the effective integration of different data-sources and the analysis of the information content based on comparative approaches are key methods for meaningful biological interpretations. In the frame of the International Solanaceae Genome Project, we propose here ISOLA, an Italian SOLAnaceae genomics resource. ISOLA (available at http://biosrv.cab.unina.it/isola) represents a trial platform and it is conceived as a multi-level computational environment.ISOLA currently consists of two main levels: the genome and the expression level. The cornerstone of the genome level is represented by the Solanum lycopersicum genome draft sequences generated by the International Tomato Genome Sequencing Consortium. Instead, the basic element of the expression level is the transcriptome information from different Solanaceae species, mainly in the form of species-specific comprehensive collections of Expressed Sequence Tags (ESTs). The cross-talk between the genome and the expression levels is based on data source sharing and on tools that enhance data quality, that extract information content from the levels' under parts and produce value-added biological knowledge. ISOLA is the result of a bioinformatics effort that addresses the challenges of the post-genomics era. It is designed to exploit '-omics' data based on effective integration to acquire biological knowledge and to approach a systems biology view. Beyond providing experimental biologists with a preliminary annotation of the tomato genome, this effort aims to produce a trial computational environment where different aspects and details are maintained as they are relevant for the analysis of the organization, the functionality and the evolution of the Solanaceae family.

Polarimetric imaging of biological tissues based on the indices of polarimetric purity.

PubMed

Van Eeckhout, Albert; Lizana, Angel; Garcia-Caurel, Enric; Gil, José J; Sansa, Adrià; Rodríguez, Carla; Estévez, Irene; González, Emilio; Escalera, Juan C; Moreno, Ignacio; Campos, Juan

2018-04-01

We highlight the interest of using the indices of polarimetric purity (IPPs) to the inspection of biological tissues. The IPPs were recently proposed in the literature and they result in a further synthetization of the depolarizing properties of samples. Compared with standard polarimetric images of biological samples, IPP-based images lead to larger image contrast of some biological structures and to a further physical interpretation of the depolarizing mechanisms inherent to the samples. In addition, unlike other methods, their calculation do not require advanced algebraic operations (as is the case of polar decompositions), and they result in 3 indicators of easy implementation. We also propose a pseudo-colored encoding of the IPP information that leads to an improved visualization of samples. This last technique opens the possibility of tailored adjustment of tissues contrast by using customized pseudo-colored images. The potential of the IPP approach is experimentally highlighted along the manuscript by studying 3 different ex-vivo samples. A significant image contrast enhancement is obtained by using the IPP-based methods, compared to standard polarimetric images. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Essential oils from wild populations of Algerian Lavandula stoechas L.: composition, chemical variability, and in vitro biological properties.

PubMed

Benabdelkader, Tarek; Zitouni, Abdelghani; Guitton, Yann; Jullien, Frédéric; Maitre, Dany; Casabianca, Hervé; Legendre, Laurent; Kameli, Abdelkrim

2011-05-01

In an effort to develop local productions of aromatic and medicinal plants, a comprehensive assessment of the composition and biological activities of the essential oils (EOs) extracted from the aerial flowering parts of wild growing Lavandula stoechas L. collected from eleven different locations in northern Algeria was performed. The oils were characterized by GC-FID and GC/MS analyses, and 121 compounds were identified, accounting for 69.88-91.2% of the total oil compositions. The eleven oils greatly differed in their compositions, since only 66 compounds were common to all oils. Major EO components were fenchone (2; 11.27-37.48%), camphor (3, 1.94-21.8%), 1,8-cineole (1; 0.16-8.71%), and viridiflorol (10; 2.89-7.38%). The assessed in vitro biological properties demonstrated that the DPPH-based radical-scavenging activities and the inhibition of the β-carotene/linoleic acid-based lipid oxidation differed by an eight-fold factor between the most and the least active oils and were linked to different sets of molecules in the different EOs. The eleven EOs exhibited good antimicrobial activities against most of the 16 tested strains of bacteria, filamentous fungi, and yeasts, with minimum inhibitory concentrations (MICs) ranging from 0.16 to 11.90 mg/ml. Copyright © 2011 Verlag Helvetica Chimica Acta AG, Zürich.

Developmental Gender Differences on the Naglieri Nonverbal Ability Test in a Nationally Normed Sample of 5-17 Year Olds

ERIC Educational Resources Information Center

Rojahn, Johannes; Naglieri, Jack A.

2006-01-01

Lynn [Lynn, R., 2002. Sex differences on the progressive matrices among 15-16 year olds: some data from South Africa. "Personality and Individual Differences 33," 669-673.] proposed that biologically based developmental sex differences produce different IQ trajectories across childhood and adolescence. To test this theory we analyzed the…

Comparative 3D QSAR study on β1-, β2-, and β3-adrenoceptor agonists

PubMed Central

Senthil Kumar, P.

2009-01-01

A quantitative structure–activity relationship study of tryptamine-based derivatives of β1-, β2-, and β3-adrenoceptor agonists was conducted using comparative molecular field analysis (CoMFA). Correlation coefficients (cross-validated r2) of 0.578, 0.595, and 0.558 were obtained for the three subtypes, respectively, in three different CoMFA models. All three CoMFA models have different steric and electrostatic contributions, implying different requirements inside the binding cavity. The CoMFA coefficient contour plots of the three models and comparisons among these plots provide clues regarding the main chemical features responsible for the biological activity variations and also result in predictions which correlate very well with the observed biological activity. Based on the analysis, a summary regeospecific description of the requirements for improving β-adrenoceptor subtype selectivity is given. PMID:21170122

A comparison of Massachusetts and Texas high school biology teachers' attitudes towards the teaching of evolution

NASA Astrophysics Data System (ADS)

Howarth, Richard T.

Darwin's theory of evolution by natural selection is considered to be the unifying theory for all life sciences (American Association for the Advancement of Science, AAAS, 1990; National Academy of Sciences, 1998; National Research Council, NRC, 1996; National Science Teachers Association, NSTA, 2010a) and as such, the biology topic has been established as a central learning standard by the National Science Education Science Standards (NSES, 2005). The purpose of this study was to compare how Massachusetts and Texas high school biology teachers' attitudes toward the teaching of evolution differ as compared to other biology topics. Texas and Massachusetts are two states that exemplify standards based education yet differ dramatically in their histories surrounding the topic of evolution. A survey was conducted among 217 Massachusetts and 139 Texas in-service high school biology teachers to help provide a sense of the phenomena surrounding biology teachers in respect to how their attitudes towards the teaching of evolution are shaped. Additionally, an open-ended question was asked to help contextualize the results of the survey between teachers of these two states. The findings in this study suggest that community appears to be a powerful persuasive message and socialization experience that shapes the development of attitudes towards evolution for some educators, especially when it is highly intertwined with religion. For biology teachers in the state of Texas, the synergistic result of this relationship has resulted in statistically significant differences in regards to attitudes towards evolution as compared to teachers in Massachusetts. These findings yield implications regarding scientific literacy, student learning, assessment, the quality of science instruction, curriculum, undergraduate biology programs, and the needs of biology teachers in terms of professional development.

Selecting islands and shoals for conservation based on biological and aesthetic criteria

USGS Publications Warehouse

Knutson, M.G.; Leopold, D.J.; Smardon, R.C.

1993-01-01

Consideration of biological quality has long been an important component of rating areas for conservation. Often these same areas are highly valued by people for aesthetic reasons, creating demands for housing and recreation that may conflict with protection plans for these habitats. Most methods of selecting land for conservation purposes use biological factors alone. For some land areas, analysis of aesthetic qualities is also important in describing the scenic value of undisturbed land. A method for prioritizing small islands and shoals based on both biological and visual quality factors is presented here. The study included 169 undeveloped islands and shoals a??0.8 ha in the Thousand Islands Region of the St. Lawrence River, New York. Criteria such as critical habitat for uncommon plant and animal species were considered together with visual quality and incorporated into a rating system that ranked the islands and shoals according to their priority for conservation management and protection from development. Biological factors were determined based on previous research and a field survey. Visual quality was determined by visual diagnostic criteria developed from public responses to photographs of a sample of islands. Variables such as elevation, soil depth, and type of plant community can be used to classify islands into different categories of visual quality but are unsuccessful in classifying islands into categories of overall biological quality.

Putting the Biological Species Concept to the Test: Using Mating Networks to Delimit Species

PubMed Central

Lagache, Lélia; Leger, Jean-Benoist; Daudin, Jean-Jacques; Petit, Rémy J.; Vacher, Corinne

2013-01-01

Although interfertility is the key criterion upon which Mayr’s biological species concept is based, it has never been applied directly to delimit species under natural conditions. Our study fills this gap. We used the interfertility criterion to delimit two closely related oak species in a forest stand by analyzing the network of natural mating events between individuals. The results reveal two groups of interfertile individuals connected by only few mating events. These two groups were largely congruent with those determined using other criteria (morphological similarity, genotypic similarity and individual relatedness). Our study, therefore, shows that the analysis of mating networks is an effective method to delimit species based on the interfertility criterion, provided that adequate network data can be assembled. Our study also shows that although species boundaries are highly congruent across methods of species delimitation, they are not exactly the same. Most of the differences stem from assignment of individuals to an intermediate category. The discrepancies between methods may reflect a biological reality. Indeed, the interfertility criterion is an environment-dependant criterion as species abundances typically affect rates of hybridization under natural conditions. Thus, the methods of species delimitation based on the interfertility criterion are expected to give results slightly different from those based on environment-independent criteria (such as the genotypic similarity criteria). However, whatever the criterion chosen, the challenge we face when delimiting species is to summarize continuous but non-uniform variations in biological diversity. The grade of membership model that we use in this study appears as an appropriate tool. PMID:23818990

Reliable classification of high explosive and chemical/biological artillery using acoustic sensors

NASA Astrophysics Data System (ADS)

Desai, Sachi V.; Hohil, Myron E.; Bass, Henry E.; Chambers, Jim

2005-05-01

Feature extraction methods based on the discrete wavelet transform and multiresolution analysis are used to develop a robust classification algorithm that reliably discriminates between conventional and simulated chemical/biological artillery rounds via acoustic signals produced during detonation utilizing a generic acoustic sensor. Based on the transient properties of the signature blast distinct characteristics arise within the different acoustic signatures because high explosive warheads emphasize concussive and shrapnel effects, while chemical/biological warheads are designed to disperse their contents over large areas, therefore employing a slower burning, less intense explosive to mix and spread their contents. The ensuing blast waves are readily characterized by variations in the corresponding peak pressure and rise time of the blast, differences in the ratio of positive pressure amplitude to the negative amplitude, and variations in the overall duration of the resulting waveform. Unique attributes can also be identified that depend upon the properties of the gun tube, projectile speed at the muzzle, and the explosive burn rates of the warhead. The algorithm enables robust classification of various airburst signatures using acoustics. It is capable of being integrated within an existing chemical/biological sensor, a stand-alone generic sensor, or a part of a disparate sensor suite. When emplaced in high-threat areas, this added capability would further provide field personal with advanced battlefield knowledge without the aide of so-called "sniffer" sensors that rely upon air particle information based on direct contact with possible contaminated air. In this work, the discrete wavelet transform is used to extract the predominant components of these characteristics from air burst signatures at ranges exceeding 2km while maintaining temporal sequence of the data to keep relevance to the transient differences of the airburst signatures. Highly reliable discrimination is achieved with a feedforward neural network classifier trained on a feature space derived from the distribution of wavelet coefficients and higher frequency details found within different levels of the multiresolution decomposition the neural network then is capable of classifying new airburst signatures as Chemical/Biological or High Explosive.

Diffusion Geometry Based Nonlinear Methods for Hyperspectral Change Detection

DTIC Science & Technology

2010-05-12

for matching biological spectra across a data base of hyperspectral pathology slides acquires with different instruments in different conditions, as...generalizing wavelets and similar scaling mechanisms. Plain Sight Systems, Inc. -7- Proprietary and Confidential To be specific, let the bi-Markov...remarkably well. Conventional nearest neighbor search , compared with a diffusion search. The data is a pathology slide ,each pixel is a digital

OWL reasoning framework over big biological knowledge network.

PubMed

Chen, Huajun; Chen, Xi; Gu, Peiqin; Wu, Zhaohui; Yu, Tong

2014-01-01

Recently, huge amounts of data are generated in the domain of biology. Embedded with domain knowledge from different disciplines, the isolated biological resources are implicitly connected. Thus it has shaped a big network of versatile biological knowledge. Faced with such massive, disparate, and interlinked biological data, providing an efficient way to model, integrate, and analyze the big biological network becomes a challenge. In this paper, we present a general OWL (web ontology language) reasoning framework to study the implicit relationships among biological entities. A comprehensive biological ontology across traditional Chinese medicine (TCM) and western medicine (WM) is used to create a conceptual model for the biological network. Then corresponding biological data is integrated into a biological knowledge network as the data model. Based on the conceptual model and data model, a scalable OWL reasoning method is utilized to infer the potential associations between biological entities from the biological network. In our experiment, we focus on the association discovery between TCM and WM. The derived associations are quite useful for biologists to promote the development of novel drugs and TCM modernization. The experimental results show that the system achieves high efficiency, accuracy, scalability, and effectivity.

OWL Reasoning Framework over Big Biological Knowledge Network

PubMed Central

Chen, Huajun; Chen, Xi; Gu, Peiqin; Wu, Zhaohui; Yu, Tong

2014-01-01

Recently, huge amounts of data are generated in the domain of biology. Embedded with domain knowledge from different disciplines, the isolated biological resources are implicitly connected. Thus it has shaped a big network of versatile biological knowledge. Faced with such massive, disparate, and interlinked biological data, providing an efficient way to model, integrate, and analyze the big biological network becomes a challenge. In this paper, we present a general OWL (web ontology language) reasoning framework to study the implicit relationships among biological entities. A comprehensive biological ontology across traditional Chinese medicine (TCM) and western medicine (WM) is used to create a conceptual model for the biological network. Then corresponding biological data is integrated into a biological knowledge network as the data model. Based on the conceptual model and data model, a scalable OWL reasoning method is utilized to infer the potential associations between biological entities from the biological network. In our experiment, we focus on the association discovery between TCM and WM. The derived associations are quite useful for biologists to promote the development of novel drugs and TCM modernization. The experimental results show that the system achieves high efficiency, accuracy, scalability, and effectivity. PMID:24877076

German National Proficiency Scales in Biology: Internal Structure, Relations to General Cognitive Abilities and Verbal Skills

PubMed Central

KÖLLER, OLAF

2016-01-01

ABSTRACT National and international large‐scale assessments (LSA) have a major impact on educational systems, which raises fundamental questions about the validity of the measures regarding their internal structure and their relations to relevant covariates. Given its importance, research on the validity of instruments specifically developed for LSA is still sparse, especially in science and its subdomains biology, chemistry, and physics. However, policy decisions for the improvement of educational quality based on LSA can only be helpful if valid information on students’ achievement levels is provided. In the present study, the nature of the measurement instruments based on the German Educational Standards in Biology is examined. On the basis of data from 3,165 students in Grade 10, we present dimensional analyses and report the relationship between different subdimensions of biology literacy and cognitive covariates such as general cognitive abilities and verbal skills. A theory‐driven two‐dimensional model fitted the data best. Content knowledge and scientific inquiry, two subdimensions of biology literacy, are highly correlated and show differential correlational patterns to the covariates. We argue that the underlying structure of biology should be incorporated into curricula, teacher training and future assessments. PMID:27818532

German National Proficiency Scales in Biology: Internal Structure, Relations to General Cognitive Abilities and Verbal Skills.

PubMed

Kampa, Nele; Köller, Olaf

2016-09-01

National and international large-scale assessments (LSA) have a major impact on educational systems, which raises fundamental questions about the validity of the measures regarding their internal structure and their relations to relevant covariates. Given its importance, research on the validity of instruments specifically developed for LSA is still sparse, especially in science and its subdomains biology, chemistry, and physics. However, policy decisions for the improvement of educational quality based on LSA can only be helpful if valid information on students' achievement levels is provided. In the present study, the nature of the measurement instruments based on the German Educational Standards in Biology is examined. On the basis of data from 3,165 students in Grade 10, we present dimensional analyses and report the relationship between different subdimensions of biology literacy and cognitive covariates such as general cognitive abilities and verbal skills. A theory-driven two-dimensional model fitted the data best. Content knowledge and scientific inquiry, two subdimensions of biology literacy, are highly correlated and show differential correlational patterns to the covariates. We argue that the underlying structure of biology should be incorporated into curricula, teacher training and future assessments.

Gender Gaps in Achievement and Participation in Multiple Introductory Biology Classrooms

PubMed Central

Brownell, Sara E.; Wenderoth, Mary Pat

2014-01-01

Although gender gaps have been a major concern in male-dominated science, technology, engineering, and mathematics disciplines such as physics and engineering, the numerical dominance of female students in biology has supported the assumption that gender disparities do not exist at the undergraduate level in life sciences. Using data from 23 large introductory biology classes for majors, we examine two measures of gender disparity in biology: academic achievement and participation in whole-class discussions. We found that females consistently underperform on exams compared with males with similar overall college grade point averages. In addition, although females on average represent 60% of the students in these courses, their voices make up less than 40% of those heard responding to instructor-posed questions to the class, one of the most common ways of engaging students in large lectures. Based on these data, we propose that, despite numerical dominance of females, gender disparities remain an issue in introductory biology classrooms. For student retention and achievement in biology to be truly merit based, we need to develop strategies to equalize the opportunities for students of different genders to practice the skills they need to excel. PMID:25185231

Sex-Based Differences in Physiology: What Should We Teach in the Medical Curriculum?

ERIC Educational Resources Information Center

Blair, Martha L.

2007-01-01

An abundance of recent research indicates that there are multiple differences between males and females both in normal physiology and in the pathophysiology of disease. The Refresher Course on Gender Differences in Physiology, sponsored by the American Physiological Society Education Committee at the 2006 Experimental Biology Meeting in San…

Dead Heroes: Surviving the Male Myth.

ERIC Educational Resources Information Center

O'Hara, Bruce

North American men die about 10 years younger than their female counterparts. This difference is not based on biological differences but on behavioral differences. Men are taught not to take care of themselves and to deaden themselves emotionally. Men are incurable romantics. They are addicted to the hero myth which is a wonderful inspiring,…

Investigating the Relationship between Instructors’ Use of Active-Learning Strategies and Students’ Conceptual Understanding and Affective Changes in Introductory Biology: A Comparison of Two Active-Learning Environments

PubMed Central

Cleveland, Lacy M.; Olimpo, Jeffrey T.; DeChenne-Peters, Sue Ellen

2017-01-01

In response to calls for reform in undergraduate biology education, we conducted research examining how varying active-learning strategies impacted students’ conceptual understanding, attitudes, and motivation in two sections of a large-lecture introductory cell and molecular biology course. Using a quasi-experimental design, we collected quantitative data to compare participants’ conceptual understanding, attitudes, and motivation in the biological sciences across two contexts that employed different active-learning strategies and that were facilitated by unique instructors. Students participated in either graphic organizer/worksheet activities or clicker-based case studies. After controlling for demographic and presemester affective differences, we found that students in both active-learning environments displayed similar and significant learning gains. In terms of attitudinal and motivational data, significant differences were observed for two attitudinal measures. Specifically, those students who had participated in graphic organizer/worksheet activities demonstrated more expert-like attitudes related to their enjoyment of biology and ability to make real-world connections. However, all motivational and most attitudinal data were not significantly different between the students in the two learning environments. These data reinforce the notion that active learning is associated with conceptual change and suggests that more research is needed to examine the differential effects of varying active-learning strategies on students’ attitudes and motivation in the domain. PMID:28389428

Neuroanatomical correlates of biological motion detection.

PubMed

Gilaie-Dotan, Sharon; Kanai, Ryota; Bahrami, Bahador; Rees, Geraint; Saygin, Ayse P

2013-02-01

Biological motion detection is both commonplace and important, but there is great inter-individual variability in this ability, the neural basis of which is currently unknown. Here we examined whether the behavioral variability in biological motion detection is reflected in brain anatomy. Perceptual thresholds for detection of biological motion and control conditions (non-biological object motion detection and motion coherence) were determined in a group of healthy human adults (n=31) together with structural magnetic resonance images of the brain. Voxel based morphometry analyzes revealed that gray matter volumes of left posterior superior temporal sulcus (pSTS) and left ventral premotor cortex (vPMC) significantly predicted individual differences in biological motion detection, but showed no significant relationship with performance on the control tasks. Our study reveals a neural basis associated with the inter-individual variability in biological motion detection, reliably linking the neuroanatomical structure of left pSTS and vPMC with biological motion detection performance. Copyright © 2012 Elsevier Ltd. All rights reserved.

Immunogenicity of biologic therapies: causes and consequences.

PubMed

Boehncke, Wolf-Henning; Brembilla, Nicolo Costantino

2018-04-25

Antibodies or fusion proteins termed biologics allow the targeted therapy of diseases. Many of these agents have proven superior efficacy and safety to conventional therapies, and subsequently revolutionized the management of numerous chronic diseases. Repetitive administration of these protein-based therapeutics to immunocompetent patients elicit immune responses in the form of Anti Drug Antibodies (ADAs), which in turn impact their pharmacological properties and may trigger adverse events. Areas covered: Structural characteristics determining the immunogenicity of biologics are reviewed along with strategies to minimize it. Next, the different types of treatment-emerging ADAs, their potential clinical implications, and assays to detect them are addressed. Emphasis is put on the review of data on the immunogenicity of different types of biologics across numerous indications. Finally, practical considerations are discussed on how to manage patients with issues around the immunogenicity of their biologic treatment. Expert commentary: Immunogenicity is a clinically relevant criterion when selecting a biologic. Besides intrinsic properties of the agent (namely its structure), its respective mode of action, dosing regimen, comedication, and the indication treated must be considered. ADA detection assays need to be standardized to improve comparability of available data and to allow clinical decision-making.

The impact of an introductory college-level biology class on biology self-efficacy and attitude towards science

NASA Astrophysics Data System (ADS)

Thomas, Megan Elizabeth

Self-efficacy theory was first introduced in a seminal article by Albert Bandura in 1977 entitled "Self-efficacy: Toward a unifying theory of behavioral change". Since its original introduction, self-efficacy has been a major focus of academic performance, anxiety, career development, and teacher retention research. Self-efficacy can be defined as the belief an individual possesses about their ability to perform a given task. Bandura proposed that self-efficacy should be measured at the highest level of specificity due to the fact that different people are efficacious in different areas. Interested in students' efficacy toward biology, Ebert-May, Baldwin, & Allred (1997) created and validated a survey to measure students' biology self-efficacy. Their survey was modeled after the guidelines for science literacy, and loaded to three sub-factors; methods of biology, generalization to other science courses, and application of the concepts. As self-efficacy theory has been related to effort expenditure and persistence (Bandura, 1977; 1997), one might think it would have some effect on students' attitudes toward the topic at hand. The current research investigated what changes in biology self-efficacy occurred after an introductory biology course with an inquiry based laboratory learning environment. In addition, changes in students' attitudes towards science were explored and how self-efficacy might affect them.

Behavior of nanoceria in biologically-relevant environments

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

Kumar, Amit; Das, Soumen; Munusamy, Prabhakaran

2014-09-08

Cerium oxide nanoparticles (CNPs) have gained a considerable attention in biological research due to their anti-oxidant like behaviour and regenerative nature. The current literature on CNPs reports many successful attempts on harnessing the beneficial therapeutic properties in biology. However studies have also shown toxicity effect with some types of CNPs. This review discusses issues associated with the behaviours of CNPs in biological systems and identifies key knowledge gaps. We explore how salient physicochemical properties (size, surface chemistry, surface stabilizers) contribute to the potential positive and negative aspects of nanoceria in biological systems. Based on variations of results reported in themore » literature, important issues need to be addressed. Are we really studying the same particles with slight variations in size and physicochemical properties or do the particles being examined have fundamentally different behaviours? Are the variations observed in the result of differences in the initial properties of the particles or the results of downstream effects that emerge as the particles are prepared for specific studies and they interact with biological or other environmental moieties? How should particles be appropriately prepared for relevant environmental/toxicology/safety studies? It is useful to recognize that nanoparticles encompass some of the same complexities and variability associated with biological components« less

Investigating the Relationship between Instructors' Use of Active-Learning Strategies and Students' Conceptual Understanding and Affective Changes in Introductory Biology: A Comparison of Two Active-Learning Environments.

PubMed

Cleveland, Lacy M; Olimpo, Jeffrey T; DeChenne-Peters, Sue Ellen

2017-01-01

In response to calls for reform in undergraduate biology education, we conducted research examining how varying active-learning strategies impacted students' conceptual understanding, attitudes, and motivation in two sections of a large-lecture introductory cell and molecular biology course. Using a quasi-experimental design, we collected quantitative data to compare participants' conceptual understanding, attitudes, and motivation in the biological sciences across two contexts that employed different active-learning strategies and that were facilitated by unique instructors. Students participated in either graphic organizer/worksheet activities or clicker-based case studies. After controlling for demographic and presemester affective differences, we found that students in both active-learning environments displayed similar and significant learning gains. In terms of attitudinal and motivational data, significant differences were observed for two attitudinal measures. Specifically, those students who had participated in graphic organizer/worksheet activities demonstrated more expert-like attitudes related to their enjoyment of biology and ability to make real-world connections. However, all motivational and most attitudinal data were not significantly different between the students in the two learning environments. These data reinforce the notion that active learning is associated with conceptual change and suggests that more research is needed to examine the differential effects of varying active-learning strategies on students' attitudes and motivation in the domain. © 2017 L. M. Cleveland et al. CBE—Life Sciences Education © 2017 The American Society for Cell Biology. This article is distributed by The American Society for Cell Biology under license from the author(s). It is available to the public under an Attribution–Noncommercial–Share Alike 3.0 Unported Creative Commons License (http://creativecommons.org/licenses/by-nc-sa/3.0).

Applying the Nernst equation to simulate redox potential variations for biological nitrification and denitrification processes.

PubMed

Chang, Cheng-Nan; Cheng, Hong-Bang; Chao, Allen C

2004-03-15

In this paper, various forms of Nernst equations have been developed based on the real stoichiometric relationship of biological nitrification and denitrification reactions. Instead of using the Nernst equation based on a one-to-one stoichiometric relation for the oxidizing and the reducing species, the basic Nernst equation is modified into slightly different forms. Each is suitable for simulating the redox potential (ORP) variation of a specific biological nitrification or denitrification process. Using the data published in the literature, the validity of these developed Nernst equations has been verified by close fits of the measured ORP data with the calculated ORP curve. The simulation results also indicate that if the biological process is simulated using an incorrect form of Nernst equation, the calculated ORP curve will not fit the measured data. Using these Nernst equations, the ORP value that corresponds to a predetermined degree of completion for the biochemical reaction can be calculated. Thus, these Nernst equations will enable a more efficient on-line control of the biological process.

Synthetic Biology for Specialty Chemicals.

PubMed

Markham, Kelly A; Alper, Hal S

2015-01-01

In this review, we address recent advances in the field of synthetic biology and describe how those tools have been applied to produce a wide variety of chemicals in microorganisms. Here we classify the expansion of the synthetic biology toolbox into three different categories based on their primary function in strain engineering-for design, for construction, and for optimization. Next, focusing on recent years, we look at how chemicals have been produced using these new synthetic biology tools. Advances in producing fuels are briefly described, followed by a more thorough treatment of commodity chemicals, specialty chemicals, pharmaceuticals, and nutraceuticals. Throughout this review, an emphasis is placed on how synthetic biology tools are applied to strain engineering. Finally, we discuss organism and host strain diversity and provide a future outlook in the field.

Chemical, biological, radiological and nuclear terrorism: an introduction for occupational physicians.

PubMed

Thornton, R; Court, B; Meara, J; Murray, V; Palmer, I; Scott, R; Wale, M; Wright, D

2004-03-01

Chemical, biological, radiological and nuclear terrorism poses considerable threat throughout the world. To provide occupational physicians with an understanding of this threat and its main forms and what action can be taken to counter this threat. Presenters at a conference on chemical, biological, radiological and nuclear terrorism were asked to contribute their evidence-based opinions in order to produce a review article. This paper presents a summary of the different forms of chemical, biological, radiological and nuclear terrorism and the effective counter-measures and also provides a review of current scientific literature. The threat of chemical, biological, radiological and nuclear terrorism is present throughout the world and is one that occupational physicians should be aware of, as well as the action that can be taken to counter it.

Synthetic biology in space: considering the broad societal and ethical implications

NASA Astrophysics Data System (ADS)

Race, Margaret S.; Moses, Jacob; McKay, Christopher; Venkateswaran, Kasthuri J.

2012-02-01

Although the field of synthetic biology is still in its infancy, there are expectations for great advances in the coming decades, both on Earth and potentially in space. Promising applications for long duration space missions include a variety of biologically engineered products and biologically aided processes and technologies, which will undoubtedly be scrutinized for risks and benefits in the broad context of ethical, legal and social realms. By comparing and contrasting features of Earth-based and space-applied synthetic biology, it is possible to identify the likely similarities and differences, and to identify possible challenges ahead for space applications that will require additional research, both in the short and long terms. Using an analytical framework associated with synthetic biology and new technologies on Earth, this paper analyses the kinds of issues and concerns ahead, and identifies those areas where space applications may require additional examination. In general, while Earth- and space-based synthetic biology share many commonalities, space applications have additional challenges such as those raised by space microbiology and environmental factors, legal complications, planetary protection, lack of decision-making infrastructure(s), long duration human missions, terraforming and the possible discovery of extraterrestrial (ET) life. For synthetic biology, the way forward offers many exciting opportunities, but is not without legitimate concerns - for life, environments and society, both on Earth and beyond.

Isobio software: biological dose distribution and biological dose volume histogram from physical dose conversion using linear-quadratic-linear model.

PubMed

Jaikuna, Tanwiwat; Khadsiri, Phatchareewan; Chawapun, Nisa; Saekho, Suwit; Tharavichitkul, Ekkasit

2017-02-01

To develop an in-house software program that is able to calculate and generate the biological dose distribution and biological dose volume histogram by physical dose conversion using the linear-quadratic-linear (LQL) model. The Isobio software was developed using MATLAB version 2014b to calculate and generate the biological dose distribution and biological dose volume histograms. The physical dose from each voxel in treatment planning was extracted through Computational Environment for Radiotherapy Research (CERR), and the accuracy was verified by the differentiation between the dose volume histogram from CERR and the treatment planning system. An equivalent dose in 2 Gy fraction (EQD 2 ) was calculated using biological effective dose (BED) based on the LQL model. The software calculation and the manual calculation were compared for EQD 2 verification with pair t -test statistical analysis using IBM SPSS Statistics version 22 (64-bit). Two and three-dimensional biological dose distribution and biological dose volume histogram were displayed correctly by the Isobio software. Different physical doses were found between CERR and treatment planning system (TPS) in Oncentra, with 3.33% in high-risk clinical target volume (HR-CTV) determined by D 90% , 0.56% in the bladder, 1.74% in the rectum when determined by D 2cc , and less than 1% in Pinnacle. The difference in the EQD 2 between the software calculation and the manual calculation was not significantly different with 0.00% at p -values 0.820, 0.095, and 0.593 for external beam radiation therapy (EBRT) and 0.240, 0.320, and 0.849 for brachytherapy (BT) in HR-CTV, bladder, and rectum, respectively. The Isobio software is a feasible tool to generate the biological dose distribution and biological dose volume histogram for treatment plan evaluation in both EBRT and BT.

svdPPCS: an effective singular value decomposition-based method for conserved and divergent co-expression gene module identification.

PubMed

Zhang, Wensheng; Edwards, Andrea; Fan, Wei; Zhu, Dongxiao; Zhang, Kun

2010-06-22

Comparative analysis of gene expression profiling of multiple biological categories, such as different species of organisms or different kinds of tissue, promises to enhance the fundamental understanding of the universality as well as the specialization of mechanisms and related biological themes. Grouping genes with a similar expression pattern or exhibiting co-expression together is a starting point in understanding and analyzing gene expression data. In recent literature, gene module level analysis is advocated in order to understand biological network design and system behaviors in disease and life processes; however, practical difficulties often lie in the implementation of existing methods. Using the singular value decomposition (SVD) technique, we developed a new computational tool, named svdPPCS (SVD-based Pattern Pairing and Chart Splitting), to identify conserved and divergent co-expression modules of two sets of microarray experiments. In the proposed methods, gene modules are identified by splitting the two-way chart coordinated with a pair of left singular vectors factorized from the gene expression matrices of the two biological categories. Importantly, the cutoffs are determined by a data-driven algorithm using the well-defined statistic, SVD-p. The implementation was illustrated on two time series microarray data sets generated from the samples of accessory gland (ACG) and malpighian tubule (MT) tissues of the line W118 of M. drosophila. Two conserved modules and six divergent modules, each of which has a unique characteristic profile across tissue kinds and aging processes, were identified. The number of genes contained in these models ranged from five to a few hundred. Three to over a hundred GO terms were over-represented in individual modules with FDR < 0.1. One divergent module suggested the tissue-specific relationship between the expressions of mitochondrion-related genes and the aging process. This finding, together with others, may be of biological significance. The validity of the proposed SVD-based method was further verified by a simulation study, as well as the comparisons with regression analysis and cubic spline regression analysis plus PAM based clustering. svdPPCS is a novel computational tool for the comparative analysis of transcriptional profiling. It especially fits the comparison of time series data of related organisms or different tissues of the same organism under equivalent or similar experimental conditions. The general scheme can be directly extended to the comparisons of multiple data sets. It also can be applied to the integration of data sets from different platforms and of different sources.

Integrating biological and social values when prioritizing places for biodiversity conservation.

PubMed

Whitehead, Amy L; Kujala, Heini; Ives, Christopher D; Gordon, Ascelin; Lentini, Pia E; Wintle, Brendan A; Nicholson, Emily; Raymond, Christopher M

2014-08-01

The consideration of information on social values in conjunction with biological data is critical for achieving both socially acceptable and scientifically defensible conservation planning outcomes. However, the influence of social values on spatial conservation priorities has received limited attention and is poorly understood. We present an approach that incorporates quantitative data on social values for conservation and social preferences for development into spatial conservation planning. We undertook a public participation GIS survey to spatially represent social values and development preferences and used species distribution models for 7 threatened fauna species to represent biological values. These spatially explicit data were simultaneously included in the conservation planning software Zonation to examine how conservation priorities changed with the inclusion of social data. Integrating spatially explicit information about social values and development preferences with biological data produced prioritizations that differed spatially from the solution based on only biological data. However, the integrated solutions protected a similar proportion of the species' distributions, indicating that Zonation effectively combined the biological and social data to produce socially feasible conservation solutions of approximately equivalent biological value. We were able to identify areas of the landscape where synergies and conflicts between different value sets are likely to occur. Identification of these synergies and conflicts will allow decision makers to target communication strategies to specific areas and ensure effective community engagement and positive conservation outcomes. © 2014 Society for Conservation Biology.

Toxicity assessment using different bioassays and microbial biosensors.

PubMed

Hassan, Sedky H A; Van Ginkel, Steven W; Hussein, Mohamed A M; Abskharon, Romany; Oh, Sang-Eun

2016-01-01

Toxicity assessment of water streams, wastewater, and contaminated sediments, is a very important part of environmental pollution monitoring. Evaluation of biological effects using a rapid, sensitive and cost effective method can indicate specific information on ecotoxicity assessment. Recently, different biological assays for toxicity assessment based on higher and lower organisms such as fish, invertebrates, plants and algal cells, and microbial bioassays have been used. This review focuses on microbial biosensors as an analytical device for environmental, food, and biomedical applications. Different techniques which are commonly used in microbial biosensing include amperometry, potentiometry, conductometry, voltammetry, microbial fuel cells, fluorescence, bioluminescence, and colorimetry. Examples of the use of different microbial biosensors in assessing a variety of environments are summarized. Copyright © 2016 Elsevier Ltd. All rights reserved.

World Federation of Societies of Biological Psychiatry (WFSBP) guidelines for biological treatment of schizophrenia - a short version for primary care.

PubMed

Hasan, Alkomiet; Falkai, Peter; Wobrock, Thomas; Lieberman, Jeffrey; Glenthøj, Birte; Gattaz, Wagner F; Thibaut, Florence; Möller, Hans-Jürgen

2017-06-01

Schizophrenia is a severe mental disorder and many patients are treated in primary care settings. Apart from the pharmacological management of disease-associated symptoms, the detection and treatment of side effects is of the utmost importance in clinical practice. The purpose of this publication is to offer relevant evidence-based recommendations for the biological treatment of schizophrenia in primary care. This publication is a short and practice-oriented summary of Parts I-III of the World Federation of Societies of Biological Psychiatry (WFSBP) Guidelines for Biological Treatment of Schizophrenia. The recommendations were developed by the authors and consented by a task force of international experts. Guideline recommendations are based on randomized-controlled trials and supplemented with non-randomized trials and meta-analyses where necessary. Antipsychotics of different chemical classes are the first-line pharmacological treatments for schizophrenia. Specific circumstances (e.g., suicidality, depression, substance dependence) may need additional treatment options. The pharmacological and non-pharmacological management of side effects is of crucial importance for the long-term treatment in all settings of the healthcare system. This summary of the three available evidence-based guidelines has the potential to support clinical decisions and can improve treatment of schizophrenia in primary care settings.

Gene network biological validity based on gene-gene interaction relevance.

PubMed

Gómez-Vela, Francisco; Díaz-Díaz, Norberto

2014-01-01

In recent years, gene networks have become one of the most useful tools for modeling biological processes. Many inference gene network algorithms have been developed as techniques for extracting knowledge from gene expression data. Ensuring the reliability of the inferred gene relationships is a crucial task in any study in order to prove that the algorithms used are precise. Usually, this validation process can be carried out using prior biological knowledge. The metabolic pathways stored in KEGG are one of the most widely used knowledgeable sources for analyzing relationships between genes. This paper introduces a new methodology, GeneNetVal, to assess the biological validity of gene networks based on the relevance of the gene-gene interactions stored in KEGG metabolic pathways. Hence, a complete KEGG pathway conversion into a gene association network and a new matching distance based on gene-gene interaction relevance are proposed. The performance of GeneNetVal was established with three different experiments. Firstly, our proposal is tested in a comparative ROC analysis. Secondly, a randomness study is presented to show the behavior of GeneNetVal when the noise is increased in the input network. Finally, the ability of GeneNetVal to detect biological functionality of the network is shown.

CRISPR editing in biological and biomedical investigation.

PubMed

Huang, Jiaojiao; Wang, Yanfang; Zhao, Jianguo

2018-05-01

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

Genes2WordCloud: a quick way to identify biological themes from gene lists and free text.

PubMed

Baroukh, Caroline; Jenkins, Sherry L; Dannenfelser, Ruth; Ma'ayan, Avi

2011-10-13

Word-clouds recently emerged on the web as a solution for quickly summarizing text by maximizing the display of most relevant terms about a specific topic in the minimum amount of space. As biologists are faced with the daunting amount of new research data commonly presented in textual formats, word-clouds can be used to summarize and represent biological and/or biomedical content for various applications. Genes2WordCloud is a web application that enables users to quickly identify biological themes from gene lists and research relevant text by constructing and displaying word-clouds. It provides users with several different options and ideas for the sources that can be used to generate a word-cloud. Different options for rendering and coloring the word-clouds give users the flexibility to quickly generate customized word-clouds of their choice. Genes2WordCloud is a word-cloud generator and a word-cloud viewer that is based on WordCram implemented using Java, Processing, AJAX, mySQL, and PHP. Text is fetched from several sources and then processed to extract the most relevant terms with their computed weights based on word frequencies. Genes2WordCloud is freely available for use online; it is open source software and is available for installation on any web-site along with supporting documentation at http://www.maayanlab.net/G2W. Genes2WordCloud provides a useful way to summarize and visualize large amounts of textual biological data or to find biological themes from several different sources. The open source availability of the software enables users to implement customized word-clouds on their own web-sites and desktop applications.

Genes2WordCloud: a quick way to identify biological themes from gene lists and free text

PubMed Central

2011-01-01

Background Word-clouds recently emerged on the web as a solution for quickly summarizing text by maximizing the display of most relevant terms about a specific topic in the minimum amount of space. As biologists are faced with the daunting amount of new research data commonly presented in textual formats, word-clouds can be used to summarize and represent biological and/or biomedical content for various applications. Results Genes2WordCloud is a web application that enables users to quickly identify biological themes from gene lists and research relevant text by constructing and displaying word-clouds. It provides users with several different options and ideas for the sources that can be used to generate a word-cloud. Different options for rendering and coloring the word-clouds give users the flexibility to quickly generate customized word-clouds of their choice. Methods Genes2WordCloud is a word-cloud generator and a word-cloud viewer that is based on WordCram implemented using Java, Processing, AJAX, mySQL, and PHP. Text is fetched from several sources and then processed to extract the most relevant terms with their computed weights based on word frequencies. Genes2WordCloud is freely available for use online; it is open source software and is available for installation on any web-site along with supporting documentation at http://www.maayanlab.net/G2W. Conclusions Genes2WordCloud provides a useful way to summarize and visualize large amounts of textual biological data or to find biological themes from several different sources. The open source availability of the software enables users to implement customized word-clouds on their own web-sites and desktop applications. PMID:21995939

Moving beyond the van Krevelen Diagram: A New Stoichiometric Approach for Compound Classification in Organisms

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

Rivas-Ubach, Albert; Liu, Yina; Bianchi, Thomas S.

van Krevelen diagrams (O:C vs H:C ratios of elemental formulas) have been widely used in studies to obtain an estimation of the main compound categories present in environmental samples. However, the limits defining a specific compound category based solely on O:C and H:C ratios of elemental formulas have never been accurately listed or proposed to classify metabolites in biological samples. Furthermore, while O:C vs. H:C ratios of elemental formulas can provide an overview of the compound categories, such classification is inefficient because of the large overlap among different compound categories along both axes. We propose a more accurate compound classificationmore » for biological samples analyzed by high-resolution mass spectrometry-based on an assessment of the C:H:O:N:P stoichiometric ratios of over 130,000 elemental formulas of compounds classified in 6 main categories: lipids, peptides, amino-sugars, carbohydrates, nucleotides and phytochemical compounds (oxy-aromatic compounds). Our multidimensional stoichiometric compound classification (MSCC) constraints showed a highly accurate categorization of elemental formulas to the main compound categories in biological samples with over 98% of accuracy representing a substantial improvement over any classification based on the classic van Krevelen diagram. This method represents a significant step forward in environmental research, especially ecological stoichiometry and eco-metabolomics studies, by providing a novel and robust tool to further our understanding the ecosystem structure and function through the chemical characterization of different biological samples.« less

A proposal to rationalize within-species plant virus nomenclature: benefits and implications of inaction.

PubMed

Jones, Roger A C; Kehoe, Monica A

2016-07-01

Current approaches used to name within-species, plant virus phylogenetic groups are often misleading and illogical. They involve names based on biological properties, sequence differences and geographical, country or place-association designations, or any combination of these. This type of nomenclature is becoming increasingly unsustainable as numbers of sequences of the same virus from new host species and different parts of the world increase. Moreover, this increase is accelerating as world trade and agriculture expand, and climate change progresses. Serious consequences for virus research and disease management might arise from incorrect assumptions made when current within-species phylogenetic group names incorrectly identify properties of group members. This could result in development of molecular tools that incorrectly target dangerous virus strains, potentially leading to unjustified impediments to international trade or failure to prevent such strains being introduced to countries, regions or continents formerly free of them. Dangerous strains might be missed or misdiagnosed by diagnostic laboratories and monitoring programs, and new cultivars with incorrect strain-specific resistances released. Incorrect deductions are possible during phylogenetic analysis of plant virus sequences and errors from strain misidentification during molecular and biological virus research activities. A nomenclature system for within-species plant virus phylogenetic group names is needed which avoids such problems. We suggest replacing all other naming approaches with Latinized numerals, restricting biologically based names only to biological strains and removing geographically based names altogether. Our recommendations have implications for biosecurity authorities, diagnostic laboratories, disease-management programs, plant breeders and researchers.

Do Teachers Make All Their Students Play the Same Learning Games? A Comparative Study of Learning Games in Biology and English as a Second Language

ERIC Educational Resources Information Center

Gruson, Brigitte; Marlot, Corinne

2016-01-01

This article, based upon the field of comparative didactics, seeks to contribute to the identification of generic and specific features in the teaching and learning process. More particularly, its aim was to examine, through the study of two different school subjects: biology and English as a second language, how "passive didactic…

Impact of calcium and TOC on biological acidification assessment in Norwegian rivers.

PubMed

Schneider, Susanne C

2011-02-15

Acidification continues to be a major impact in freshwaters of northern Europe, and the biotic response to chemical recovery from acidification is often not a straightforward process. The focus on biological recovery is relevant within the context of the EU Water Framework Directive, where a biological monitoring system is needed that detects differences in fauna and flora compared to undisturbed reference conditions. In order to verify true reference sites for biological analyses, expected river pH is modeled based on Ca and TOC, and 94% of variability in pH at reference sites is explained by Ca alone, while 98% is explained by a combination of Ca and TOC. Based on 59 samples from 28 reference sites, compared to 547 samples from 285 non-reference sites, the impact of calcium and total organic carbon (TOC) on benthic algae species composition, expressed as acidification index periphyton (AIP), is analyzed. Rivers with a high Ca concentration have a naturally higher AIP, and TOC affects reference AIP only at low Ca concentrations. Four biological river types are needed for assessment of river acidification in Norway based on benthic algae: very calcium-poor, humic rivers (Ca<1 mg/l and TOC>2 mg/l); very calcium-poor, clear rivers (Ca<1 mg/l and TOC<2 mg/l); calcium-poor rivers (Ca between 1 and 4 mg/l); moderately calcium rich rivers (Ca>4 mg/l). A biological assessment system for river acidification in Norway based on benthic algae is presented, following the demands of the Water Framework Directive. Copyright © 2010 Elsevier B.V. All rights reserved.

Zebrafish Whole-Adult-Organism Chemogenomics for Large-Scale Predictive and Discovery Chemical Biology

PubMed Central

Lam, Siew Hong; Mathavan, Sinnakarupan; Tong, Yan; Li, Haixia; Karuturi, R. Krishna Murthy; Wu, Yilian; Vega, Vinsensius B.; Liu, Edison T.; Gong, Zhiyuan

2008-01-01

The ability to perform large-scale, expression-based chemogenomics on whole adult organisms, as in invertebrate models (worm and fly), is highly desirable for a vertebrate model but its feasibility and potential has not been demonstrated. We performed expression-based chemogenomics on the whole adult organism of a vertebrate model, the zebrafish, and demonstrated its potential for large-scale predictive and discovery chemical biology. Focusing on two classes of compounds with wide implications to human health, polycyclic (halogenated) aromatic hydrocarbons [P(H)AHs] and estrogenic compounds (ECs), we generated robust prediction models that can discriminate compounds of the same class from those of different classes in two large independent experiments. The robust expression signatures led to the identification of biomarkers for potent aryl hydrocarbon receptor (AHR) and estrogen receptor (ER) agonists, respectively, and were validated in multiple targeted tissues. Knowledge-based data mining of human homologs of zebrafish genes revealed highly conserved chemical-induced biological responses/effects, health risks, and novel biological insights associated with AHR and ER that could be inferred to humans. Thus, our study presents an effective, high-throughput strategy of capturing molecular snapshots of chemical-induced biological states of a whole adult vertebrate that provides information on biomarkers of effects, deregulated signaling pathways, and possible affected biological functions, perturbed physiological systems, and increased health risks. These findings place zebrafish in a strategic position to bridge the wide gap between cell-based and rodent models in chemogenomics research and applications, especially in preclinical drug discovery and toxicology. PMID:18618001

Evidence-based support for the all-hazards approach to emergency preparedness

PubMed Central

2012-01-01

Background During the last decade there has been a need to respond and recover from various types of emergencies including mass casualty events (MCEs), mass toxicological/chemical events (MTEs), and biological events (pandemics and bio-terror agents). Effective emergency preparedness is more likely to be achieved if an all-hazards response plan is adopted. Objectives To investigate if there is a relationship among hospitals' preparedness for various emergency scenarios, and whether components of one emergency scenario correlate with preparedness for other emergency scenarios. Methods Emergency preparedness levels of all acute-care hospitals for MCEs, MTEs, and biological events were evaluated, utilizing a structured evaluation tool based on measurable parameters. Evaluations were made by professional experts in two phases: evaluation of standard operating procedures (SOPs) followed by a site visit. Relationships among total preparedness and different components' scores for various types of emergencies were analyzed. Results Significant relationships were found among preparedness for different emergencies. Standard Operating Procedures (SOPs) for biological events correlated with preparedness for all investigated emergency scenarios. Strong correlations were found between training and drills with preparedness for all investigated emergency scenarios. Conclusions Fundamental critical building blocks such as SOPs, training, and drill programs improve preparedness for different emergencies including MCEs, MTEs, and biological events, more than other building blocks, such as equipment or knowledge of personnel. SOPs are especially important in unfamiliar emergency scenarios. The findings support the adoption of an all-hazards approach to emergency preparedness. PMID:23098065

Elaboration and use of nickel planar macrocyclic complex-based sensors for the direct electrochemical measurement of nitric oxide in biological media.

PubMed

Bedioui, F; Trevin, S; Devynck, J; Lantoine, F; Brunet, A; Devynck, M A

1997-01-01

We describe here the electrochemical detection of nitric oxide, NO, in biological systems by using chemically modified ultramicro carbon electrodes. In the first part of the paper, the different steps involved in the electrochemical preparation and characterization of the nickel-based sensor are described. This is illustrated by the use of nickel(II) tetrasulfonated phthalocyanine complex. The second part of the paper describes two examples of the direct electrochemical measurement of NO production in human blood platelets and endothelial cells from umbilical cord vein.

Workflow based framework for life science informatics.

PubMed

Tiwari, Abhishek; Sekhar, Arvind K T

2007-10-01

Workflow technology is a generic mechanism to integrate diverse types of available resources (databases, servers, software applications and different services) which facilitate knowledge exchange within traditionally divergent fields such as molecular biology, clinical research, computational science, physics, chemistry and statistics. Researchers can easily incorporate and access diverse, distributed tools and data to develop their own research protocols for scientific analysis. Application of workflow technology has been reported in areas like drug discovery, genomics, large-scale gene expression analysis, proteomics, and system biology. In this article, we have discussed the existing workflow systems and the trends in applications of workflow based systems.

A systematic approach to infer biological relevance and biases of gene network structures.

PubMed

Antonov, Alexey V; Tetko, Igor V; Mewes, Hans W

2006-01-10

The development of high-throughput technologies has generated the need for bioinformatics approaches to assess the biological relevance of gene networks. Although several tools have been proposed for analysing the enrichment of functional categories in a set of genes, none of them is suitable for evaluating the biological relevance of the gene network. We propose a procedure and develop a web-based resource (BIOREL) to estimate the functional bias (biological relevance) of any given genetic network by integrating different sources of biological information. The weights of the edges in the network may be either binary or continuous. These essential features make our web tool unique among many similar services. BIOREL provides standardized estimations of the network biases extracted from independent data. By the analyses of real data we demonstrate that the potential application of BIOREL ranges from various benchmarking purposes to systematic analysis of the network biology.

Frontiers of optofluidics in synthetic biology.

PubMed

Tan, Cheemeng; Lo, Shih-Jie; LeDuc, Philip R; Cheng, Chao-Min

2012-10-07

The development of optofluidic-based technology has ushered in a new era of lab-on-a-chip functionality, including miniaturization of biomedical devices, enhanced sensitivity for molecular detection, and multiplexing of optical measurements. While having great potential, optofluidic devices have only begun to be exploited in many biotechnological applications. Here, we highlight the potential of integrating optofluidic devices with synthetic biological systems, which is a field focusing on creating novel cellular systems by engineering synthetic gene and protein networks. First, we review the development of synthetic biology at different length scales, ranging from single-molecule, single-cell, to cellular population. We emphasize light-sensitive synthetic biological systems that would be relevant for the integration with optofluidic devices. Next, we propose several areas for potential applications of optofluidics in synthetic biology. The integration of optofluidics and synthetic biology would have a broad impact on point-of-care diagnostics and biotechnology.

Fabrication and characterization of biotissue-mimicking phantoms in the THz frequency range

NASA Astrophysics Data System (ADS)

Liakhov, E.; Smolyanskaya, O.; Popov, A.; Odlyanitskiy, E.; Balbekin, N.; Khodzitsky, M.

2016-08-01

The study revealed the most promising candidates for phantoms mimicking different biological tissues in the terahertz frequency range. Closest to biological tissues in terms of the refractive index appeared to be gelatin-based gels; in terms of the absorption coefficient they were agar-based gels. Gelatin is more stable in time, but requires special storage conditions to limit water evaporation. The dense structure of the agar-based phantom allows its use without mold and risk of damage. However, agar is a nutrient medium for bacteria and its parameters degrade even when the phantom form and water content are retained. Use of liquid suspensions of lecithin and milk powder are found to be extremely limited.

Method and system for real-time analysis of biosensor data

DOEpatents

Greenbaum, Elias; Rodriguez, Jr., Miguel

2014-08-19

A method of biosensor-based detection of toxins includes the steps of providing a fluid to be analyzed having a plurality of photosynthetic organisms therein, wherein chemical, biological or radiological agents alter a nominal photosynthetic activity of the photosynthetic organisms. At a first time a measured photosynthetic activity curve is obtained from the photosynthetic organisms. The measured curve is automatically compared to a reference photosynthetic activity curve to determine differences therebetween. The presence of the chemical, biological or radiological agents, or precursors thereof, are then identified if present in the fluid using the differences.

A blueprint for the synthesis and characterisation of thin graphene oxide with controlled lateral dimensions for biomedicine

NASA Astrophysics Data System (ADS)

Filipe Rodrigues, Artur; Newman, Leon; Lozano, Neus; Mukherjee, Sourav P.; Fadeel, Bengt; Bussy, Cyrill; Kostarelos, Kostas

2018-07-01

Graphene-based materials (GBMs) have ignited a revolution in material science and technology, with electronic, optical and mechanical properties that are of relevant interest for a wide range of applications. To support the development of these enabling technologies, a global research effort has been invested to assess their hazard and biocompatibility. Different production methods have however generated a diverse collection of GBMs with different physicochemical properties, leading to a variety of biological outcomes that are still not fully understood. To better understand the biological interactions of GBMs with biological systems and allow the design of safer materials, a thorough physicochemical characterisation is therefore highly recommended. The aim of the present work was to produce a blueprint for the synthesis and characterisation of non-pyrogenic graphene oxide (GO) flakes with three different controlled lateral dimensions, which could be further used for either hazard assessment or biomedical proof-of-concept studies. A battery of techniques used to characterise the physicochemical properties of the GO samples included atomic force microscopy, transmission electron microscopy, Fourier-transformed infra-red spectroscopy, x-ray photoelectron spectroscopy and Raman spectroscopy. The combination of these different techniques confirmed that only the lateral dimension varied among the GO materials produced, without significant change in any other of their fundamental physicochemical properties, such as the thickness or surface chemistry. The proposed systematic approach in GO batch production for biology will hopefully contribute to a better understanding of the material properties that govern their interactions with biological systems and offer a blueprint towards standardisation of biologically relevant 2D materials.

Comparison of textbook passages, nonfiction trade book passages and fiction trade book passages as instructional tools for learning science

NASA Astrophysics Data System (ADS)

Kelly, Cynthia

This study examined the impact of different types of text on student achievement in elementary school science. Gender was also examined to see if the type of text passage read had any differential effect on boys' and girls' achievement. This study was a pretest/posttest/retention test design. Eighty-four fourth grade students from a public charter elementary school in South Florida were randomly assigned a passage from a physical science textbook, a physical science nonfiction trade book, a physical science fiction trade book, a biological science textbook or a biological science nonfiction trade book. Results in the physical science content area revealed that students in the textbook passage group had higher posttest and retention test results than students in the nonfiction and fiction trade book passage groups. There was no difference on the posttest results of students in the biological science textbook and nonfiction trade book passage groups. Students in the biological science textbook passage group had higher retention results than students in the biological science nonfiction passage group. Gender results in the physical science content area revealed that boys had a higher retention score than girls in the fiction trade book passage group. There were no gender achievement differences as a result of the text passage read in the biological science content area. It was concluded that no definitive answer as to the efficacy of textbooks versus trade books was possible based upon results of the study. Recommendations for future research include examining the effects of different types of texts in conjunction with other authentic teaching methods.

Difference or Disorder? Cultural Issues in Understanding Neurodevelopmental Disorders

ERIC Educational Resources Information Center

Norbury, Courtenay Frazier; Sparks, Alison

2013-01-01

Developmental disorders, such as autism spectrum disorder and specific language impairment, are biologically based disorders that currently rely on behaviorally defined criteria for diagnosis and treatment. Specific behaviors that are included in diagnostic frameworks and the point at which individual differences in behavior constitute abnormality…

The Physics of Open Ended Evolution

NASA Astrophysics Data System (ADS)

Adams, Alyssa M.

What makes living systems different than non-living ones? Unfortunately this question is impossible to answer, at least currently. Instead, we must face computationally tangible questions based on our current understanding of physics, computation, information, and biology. Yet we have few insights into how living systems might quantifiably differ from their non-living counterparts, as in a mathematical foundation to explain away our observations of biological evolution, emergence, innovation, and organization. The development of a theory of living systems, if at all possible, demands a mathematical understanding of how data generated by complex biological systems changes over time. In addition, this theory ought to be broad enough as to not be constrained to an Earth-based biochemistry. In this dissertation, the philosophy of studying living systems from the perspective of traditional physics is first explored as a motivating discussion for subsequent research. Traditionally, we have often thought of the physical world from a bottom-up approach: things happening on a smaller scale aggregate into things happening on a larger scale. In addition, the laws of physics are generally considered static over time. Research suggests that biological evolution may follow dynamic laws that (at least in part) change as a function of the state of the system. Of the three featured research projects, cellular automata (CA) are used as a model to study certain aspects of living systems in two of them. These aspects include self-reference, open-ended evolution, local physical universality, subjectivity, and information processing. Open-ended evolution and local physical universality are attributed to the vast amount of innovation observed throughout biological evolution. Biological systems may distinguish themselves in terms of information processing and storage, not outside the theory of computation. The final research project concretely explores real-world phenomenon by means of mapping dominance hierarchies in the evolution of video game strategies. Though the main question of how life differs from non-life remains unanswered, the mechanisms behind open-ended evolution and physical universality are revealed.

Features analysis for identification of date and party hubs in protein interaction network of Saccharomyces Cerevisiae.

PubMed

Mirzarezaee, Mitra; Araabi, Babak N; Sadeghi, Mehdi

2010-12-19

It has been understood that biological networks have modular organizations which are the sources of their observed complexity. Analysis of networks and motifs has shown that two types of hubs, party hubs and date hubs, are responsible for this complexity. Party hubs are local coordinators because of their high co-expressions with their partners, whereas date hubs display low co-expressions and are assumed as global connectors. However there is no mutual agreement on these concepts in related literature with different studies reporting their results on different data sets. We investigated whether there is a relation between the biological features of Saccharomyces Cerevisiae's proteins and their roles as non-hubs, intermediately connected, party hubs, and date hubs. We propose a classifier that separates these four classes. We extracted different biological characteristics including amino acid sequences, domain contents, repeated domains, functional categories, biological processes, cellular compartments, disordered regions, and position specific scoring matrix from various sources. Several classifiers are examined and the best feature-sets based on average correct classification rate and correlation coefficients of the results are selected. We show that fusion of five feature-sets including domains, Position Specific Scoring Matrix-400, cellular compartments level one, and composition pairs with two and one gaps provide the best discrimination with an average correct classification rate of 77%. We study a variety of known biological feature-sets of the proteins and show that there is a relation between domains, Position Specific Scoring Matrix-400, cellular compartments level one, composition pairs with two and one gaps of Saccharomyces Cerevisiae's proteins, and their roles in the protein interaction network as non-hubs, intermediately connected, party hubs and date hubs. This study also confirms the possibility of predicting non-hubs, party hubs and date hubs based on their biological features with acceptable accuracy. If such a hypothesis is correct for other species as well, similar methods can be applied to predict the roles of proteins in those species.

Optical sensor for heat conduction measurement in biological tissue

NASA Astrophysics Data System (ADS)

Gutierrez-Arroyo, A.; Sanchez-Perez, C.; Aleman-Garcia, N.

2013-06-01

This paper presents the design of a heat flux sensor using an optical fiber system to measure heat conduction in biological tissues. This optoelectronic device is based on the photothermal beam deflection of a laser beam travelling in an acrylic slab this deflection is measured with a fiber optic angle sensor. We measure heat conduction in biological samples with high repeatability and sensitivity enough to detect differences in tissues from three chicken organs. This technique could provide important information of vital organ function as well as the detect modifications due to degenerative diseases or physical damage caused by medications or therapies.

Molecular profiles to biology and pathways: a systems biology approach.

PubMed

Van Laere, Steven; Dirix, Luc; Vermeulen, Peter

2016-06-16

Interpreting molecular profiles in a biological context requires specialized analysis strategies. Initially, lists of relevant genes were screened to identify enriched concepts associated with pathways or specific molecular processes. However, the shortcoming of interpreting gene lists by using predefined sets of genes has resulted in the development of novel methods that heavily rely on network-based concepts. These algorithms have the advantage that they allow a more holistic view of the signaling properties of the condition under study as well as that they are suitable for integrating different data types like gene expression, gene mutation, and even histological parameters.

[Biological preparations with different mechanism of action for protecting potato against fungal diseases].

PubMed

Kulikov, S N; Alimova, F K; Zakharova, N G; Nemtsev, S V; Varlamov, V P

2006-01-01

Mycological analysis throughout the vegetation period of potato (Solanum tuberosum) made it possible to study in detail the structure of micromycete community, to determine typical dominant (frequency, more than 60%), typical common (frequency, 30 to 60%), typical rare (frequency, 10 to 30%), and casual (frequency, less than 10%) species and to estimate changes in the microorganism community caused by plant protection preparations with different mechanisms of action. It was shown that, as a result of occurrence of resistant forms, synthetic preparations against fungal pathogens of potato (such as TMTD, Ridomil gold MC, and Cupricol) were only slightly more effective than biological preparations (Trichodermin and AgroChit), with the former considerably changing the natural saprophytic mycological community. An increase in the soil pool of Trichoderma harzianum as a result of application of a biological preparation based on this antagonistic fungus correlated with its effectiveness against the soil pathogen Fusarium sp., which causes root rots. A chitosan-based elicitor preparation more effectively suppressed the development of early (Alternaria sp. and Macrosporium sp.) and late (Phytophthora sp.) blights of leaves and had a weaker effect on the soil microflora.

Fluidity models in ancient Greece and current practices of sex assignment

PubMed Central

Chen, Min-Jye; McCann-Crosby, Bonnie; Gunn, Sheila; Georgiadis, Paraskevi; Placencia, Frank; Mann, David; Axelrad, Marni; Karaviti, L.P; McCullough, Laurence B.

2018-01-01

Disorders of sexual differentiation such as androgen insensitivity and gonadal dysgenesis can involve an intrinsic fluidity at different levels, from the anatomical and biological to the social (gender) that must be considered in the context of social constraints. Sex assignment models based on George Engel’s biopsychosocial aspects model of biology accept fluidity of gender as a central concept and therefore help establish expectations within the uncertainty of sex assignment and anticipate potential changes. The biology underlying the fluidity inherent to these disorders should be presented to parents at diagnosis, an approach that the gender medicine field should embrace as good practice. Greek mythology provides many accepted archetypes of change, and the ancient Greek appreciation of metamorphosis can be used as context with these patients. Our goal is to inform expertise and optimal approaches, knowing that this fluidity may eventually necessitate sex reassignment. Physicians should provide sex assignment education based on different components of sexual differentiation, prepare parents for future hormone-triggered changes in their children, and establish a sex-assignment algorithm. PMID:28478088

Fluidity models in ancient Greece and current practices of sex assignment.

PubMed

Chen, Min-Jye; McCann-Crosby, Bonnie; Gunn, Sheila; Georgiadis, Paraskevi; Placencia, Frank; Mann, David; Axelrad, Marni; Karaviti, L P; McCullough, Laurence B

2017-06-01

Disorders of sexual differentiation such as androgen insensitivity and gonadal dysgenesis can involve an intrinsic fluidity at different levels, from the anatomical and biological to the social (gender) that must be considered in the context of social constraints. Sex assignment models based on George Engel's biopsychosocial aspects model of biology accept fluidity of gender as a central concept and therefore help establish expectations within the uncertainty of sex assignment and anticipate potential changes. The biology underlying the fluidity inherent to these disorders should be presented to parents at diagnosis, an approach that the gender medicine field should embrace as good practice. Greek mythology provides many accepted archetypes of change, and the ancient Greek appreciation of metamorphosis can be used as context with these patients. Our goal is to inform expertise and optimal approaches, knowing that this fluidity may eventually necessitate sex reassignment. Physicians should provide sex assignment education based on different components of sexual differentiation, prepare parents for future hormone-triggered changes in their children, and establish a sex-assignment algorithm. Copyright © 2017 Elsevier Inc. All rights reserved.

Transmission as a basic process in microbial biology. Lwoff Award Prize Lecture.

PubMed

Baquero, Fernando

2017-11-01

Transmission is a basic process in biology and evolution, as it communicates different biological entities within and across hierarchical levels (from genes to holobionts) both in time and space. Vertical descent, replication, is transmission of information across generations (in the time dimension), and horizontal descent is transmission of information across compartments (in the space dimension). Transmission is essentially a communication process that can be studied by analogy of the classic information theory, based on 'emitters', 'messages' and 'receivers'. The analogy can be easily extended to the triad 'emigration', 'migration' and 'immigration'. A number of causes (forces) determine the emission, and another set of causes (energies) assures the reception. The message in fact is essentially constituted by 'meaningful' biological entities. A DNA sequence, a cell and a population have a semiotic dimension, are 'signs' that are eventually recognized (decoded) and integrated by receiver biological entities. In cis-acting or unenclosed transmission, the emitters and receivers correspond to separated entities of the same hierarchical level; in trans-acting or embedded transmission, the information flows between different, but frequently nested, hierarchical levels. The result (as in introgressive events) is constantly producing innovation and feeding natural selection, influencing also the evolution of transmission processes. This review is based on the concepts presented at the André Lwoff Award Lecture in the FEMS Microbiology Congress in Maastricht in 2015. © FEMS 2017. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Access to biologicals in Crohn’s disease in ten European countries

PubMed Central

Péntek, Márta; Lakatos, Peter L; Oorsprong, Talitha; Gulácsi, László; Pavlova, Milena; Groot, Wim; Rencz, Fanni; Brodszky, Valentin; Baji, Petra; Crohn’s Disease Research Group

2017-01-01

AIM To analyze access (availability, affordability and acceptability) to biologicals for Crohn’s disease (CD) in ten European countries and to explore the associations between these dimensions, the uptake of biologicals and economic development. METHODS A questionnaire-based survey combined with desk research was carried out in May 2016. Gastroenterologists from the Czech Republic, France, Germany, Hungary, Latvia, Poland, Romania, Slovakia, Spain and Sweden were invited to participate and provide data on the availability of biologicals/biosimilars, reimbursement criteria, clinical practice and prices, and use of biologicals. An availability score was developed to evaluate the restrictiveness of eligibility and administrative criteria applied in the countries. Affordability was defined as the annual cost of treatment as a share of gross domestic product (GDP) per capita. Correlations with the uptake of biologicals, dimensions of access and GDP per capita were calculated. RESULTS At the time of the survey, infliximab and adalimumab were reimbursed in all ten countries, and vedolizumab was reimbursed in five countries (France, Germany, Latvia, Slovakia, Sweden). Reimbursement criteria were the least strict in Sweden and Germany, and the strictest in Hungary, Poland and Slovakia. Between countries, the annual cost of different biological treatments differed 1.6-3.3-fold. Treatments were the most affordable in Sweden (13%-37% of the GDP per capita) and the least affordable in the Central and Eastern European countries, especially in Hungary (87%-124%) and Romania (141%-277%). Biosimilars made treatments more affordable by driving down the annual costs. The number of patients with CD on biologicals per 100000 population was strongly correlated with GDP per capita (0.91), although substantial differences were found in the uptake among countries with similar economic development. Correlation between the number of patients with CD on biologicals per 100000 population and the availability and affordability was also strong (-0.75, -0.69 respectively). CONCLUSION Substantial inequalities in access to biologicals were largely associated with GDP. To explain differences in access among countries with similar development needs further research on acceptance. PMID:28974896

Identifying misclassification in youth self-reported smoking status: testing different consent processes of biological sample collection to capture misclassification.

PubMed

Dietz, Noella A; Arheart, Kristopher L; Lee, David J; Sly, David F; McClure, Laura A

2015-04-01

In Florida, since 1998, identical survey items have been used to measure youth smoking status for the CDC sponsored state school-based survey and the tobacco control program evaluation telephone survey. The two surveys should parallel one another to track tobacco use. Tobacco items collected in the two surveys closely paralleled one another until recently. Since 2008, data show dramatically divergent youth smoking estimates (e.g., relative differences as high as 50%), which cannot be explained by differences in survey and sampling design. As a first step in detecting misclassification of smoking status, we examined the feasibility of asking youth to self-report their smoking behavior and collect a biological sample, with the expectation that some youth will misreport their smoking status. Using a cross-sectional population level telephone survey, youth were randomly assigned to one of three groups to test mode effects of collecting biological data with self-reported survey data (n = 303). It showed two groups of youth (those who are not asked for a biological and those asked for a biological with an indirect explanation of its use) had similar response rates and self-reported smoking status, while the third group (biological request with a direct explanation of its use) had a substantially lower response rate and self-reported smoking status. The data show youth who are given an indirect explanation of how biological data are to be used were as likely to self-report their smoking status as youth who were not asked to provide a biological sample. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

A craniometric analysis of early modern Romania and Hungary: The roles of migration and conversion in shaping European Ottoman population history.

PubMed

Allen, Kathryn Grow; von Cramon-Taubadel, Noreen

2017-11-01

Debate persists regarding the biological makeup of European Ottoman communities settled during the expansion of the Ottoman Empire during the 16th and 17th centuries, and the roles of conversion and migration in shaping demography and population history. The aim of this study was to perform an assessment of the biological affinities of three European Ottoman series based on craniometric data. Craniometric data collected from three Ottoman series from Hungary and Romania were compared to European and Anatolian comparative series, selected to represent biological affinity representative of historically recorded migration and conversion influences. Sex-separated samples were analyzed using D 2 -matrices, along with principal coordinates and PERMANOVA analyses to investigate biological affinities. Discriminant function analysis was employed to assign Ottoman individuals to two potential classes: European or Anatolian. Affinity analyses show larger than expected biological differences between males and females within each of the Ottoman communities. Discriminant function analyses show that the majority of Ottoman individuals could be classified as either European or Anatolian with a high probability. Moreover, location within Europe proved influential, as the Ottomans from a location of more geopolitical importance (Budapest) diverged from more hinterland communities in terms of biological affinity patterns. The results suggest that male and female Ottomans may possess distinct population histories, with males and females divergent from each other in terms of their biological affinities. The Ottoman communities appear diverse in terms of constituting a mix of peoples from different biological backgrounds. The greater distances between sexes from the same community, and the differences between communities, may be evidence that the processes of migration and conversion impacted individual people and groups diversely. © 2017 Wiley Periodicals, Inc.

Chemometric analysis of Hymenoptera toxins and defensins: A model for predicting the biological activity of novel peptides from venoms and hemolymph.

PubMed

Saidemberg, Daniel M; Baptista-Saidemberg, Nicoli B; Palma, Mario S

2011-09-01

When searching for prospective novel peptides, it is difficult to determine the biological activity of a peptide based only on its sequence. The "trial and error" approach is generally laborious, expensive and time consuming due to the large number of different experimental setups required to cover a reasonable number of biological assays. To simulate a virtual model for Hymenoptera insects, 166 peptides were selected from the venoms and hemolymphs of wasps, bees and ants and applied to a mathematical model of multivariate analysis, with nine different chemometric components: GRAVY, aliphaticity index, number of disulfide bonds, total residues, net charge, pI value, Boman index, percentage of alpha helix, and flexibility prediction. Principal component analysis (PCA) with non-linear iterative projections by alternating least-squares (NIPALS) algorithm was performed, without including any information about the biological activity of the peptides. This analysis permitted the grouping of peptides in a way that strongly correlated to the biological function of the peptides. Six different groupings were observed, which seemed to correspond to the following groups: chemotactic peptides, mastoparans, tachykinins, kinins, antibiotic peptides, and a group of long peptides with one or two disulfide bonds and with biological activities that are not yet clearly defined. The partial overlap between the mastoparans group and the chemotactic peptides, tachykinins, kinins and antibiotic peptides in the PCA score plot may be used to explain the frequent reports in the literature about the multifunctionality of some of these peptides. The mathematical model used in the present investigation can be used to predict the biological activities of novel peptides in this system, and it may also be easily applied to other biological systems. Copyright © 2011 Elsevier Inc. All rights reserved.

European do-it-yourself (DIY) biology: beyond the hope, hype and horror.

PubMed

Seyfried, Günter; Pei, Lei; Schmidt, Markus

2014-06-01

The encounter of amateur science with synthetic biology has led to the formation of several amateur/do-it-yourself biology (DIYBio) groups worldwide. Although media outlets covered DIYBio events, most seemed only to highlight the hope, hype, and horror of what DIYBio would do in the future. Here, we analyze the European amateur biology movement to find out who they are, what they aim for and how they differ from US groups. We found that all groups are driven by a core leadership of (semi-)professional people who struggle with finding lab space and equipment. Regulations on genetic modification limit what groups can do. Differences between Europe and the US are found in the distinct regulatory environments and the European emphasis on bio-art. We conclude that DIYBio Europe has so far been a responsible and transparent citizen science movement with a solid user base that will continue to grow irrespective of media attention. © 2014 The Authors. Bioessays published by WILEY Periodicals, Inc.

European do-it-yourself (DIY) biology: Beyond the hope, hype and horror

PubMed Central

Seyfried, Günter; Pei, Lei; Schmidt, Markus

2014-01-01

The encounter of amateur science with synthetic biology has led to the formation of several amateur/do-it-yourself biology (DIYBio) groups worldwide. Although media outlets covered DIYBio events, most seemed only to highlight the hope, hype, and horror of what DIYBio would do in the future. Here, we analyze the European amateur biology movement to find out who they are, what they aim for and how they differ from US groups. We found that all groups are driven by a core leadership of (semi-)professional people who struggle with finding lab space and equipment. Regulations on genetic modification limit what groups can do. Differences between Europe and the US are found in the distinct regulatory environments and the European emphasis on bio-art. We conclude that DIYBio Europe has so far been a responsible and transparent citizen science movement with a solid user base that will continue to grow irrespective of media attention. PMID:24782329

Differentiation of closely related but biologically distinct cherry isolates of Prunus necrotic ringspot virus by polymerase chain reaction.

PubMed

Hammond, R W; Crosslin, J M; Pasini, R; Howell, W E; Mink, G I

1999-07-01

Prunus necrotic ringspot ilarvirus (PNRSV) exists as a number of biologically distinct variants which differ in host specificity, serology, and pathology. Previous nucleotide sequence alignment and phylogenetic analysis of cloned reverse transcription-polymerase chain reaction (RT-PCR) products of several biologically distinct sweet cherry isolates revealed correlations between symptom type and the nucleotide and amino acid sequences of the 3a (putative movement protein) and 3b (coat protein) open reading frames. Based upon this analysis, RT-PCR assays have been developed that can identify isolates displaying different symptoms and serotypes. The incorporation of primers in a multiplex PCR protocol permits rapid detection and discrimination among the strains. The results of PCR amplification using type-specific primers that amplify a portion of the coat protein gene demonstrate that the primer-selection procedure developed for PNRSV constitutes a reliable method of viral strain discrimination in cherry for disease control and will also be useful for examining biological diversity within the PNRSV virus group.

[Exposure to biological agents used in Polish enterprises: analysis of data derived from the National Register of Biological Agent].

PubMed

Kozajda, Anna; Szadkowska-Stańczyk, Irena

2011-01-01

The National Register of Biological Agents at Work and the National Information Centre for Biological Agents Present at Workplaces were established in the Nofer Institute of Occupational Medicine in 2005. The National Information Centre carries out consultation and education activities concerning occupational exposure and risk assessment, development and implementation of preventive programs and accurate registration of reliable information about the use of biological agents. Educational materials on biological exposure are published on the website. The National Register of Biological Agents (database) collects and periodically analyzes the information obtained from employers about the use of biological agents for research, diagnostic or industrial purposes. As of 10 December 2010 there were 240 notifications from companies, which use biological agents for the following purposes: research--69, industrial--30 and diagnostic--321. Near 75% of all notifications were obtained from different diagnostic laboratories (public and private). In total, 3226 workers, including 2967 (92%) women and 256 (8%) men were exposed to biological agents. In general, occupational exposure to 209 biological agents (186 of risk group 2 and 23 of risk group 3, of which 16 are additionally marked by 3**) were registered in the data base.

Synergistic Modification Induced Specific Recognition between Histone and TRIM24 via Fluctuation Correlation Network Analysis

NASA Astrophysics Data System (ADS)

Zhang, Jinmai; Luo, Huajie; Liu, Hao; Ye, Wei; Luo, Ray; Chen, Hai-Feng

2016-04-01

Histone modification plays a key role in gene regulation and gene expression. TRIM24 as a histone reader can recognize histone modification. However the specific recognition mechanism between TRIM24 and histone modification is unsolved. Here, systems biology method of dynamics correlation network based on molecular dynamics simulation was used to answer the question. Our network analysis shows that the dynamics correlation network of H3K23ac is distinctly different from that of wild type and other modifications. A hypothesis of “synergistic modification induced recognition” is then proposed to link histone modification and TRIM24 binding. These observations were further confirmed from community analysis of networks with mutation and network perturbation. Finally, a possible recognition pathway is also identified based on the shortest path search for H3K23ac. Significant difference of recognition pathway was found among different systems due to methylation and acetylation modifications. The analysis presented here and other studies show that the dynamic network-based analysis might be a useful general strategy to study the biology of protein post-translational modification and associated recognition.

Real-time Measurements of Biological Particles at Several Continental Sites using the WIBS-4A

NASA Astrophysics Data System (ADS)

McMeeking, G. R.; Kok, G. L.; Petters, M. D.; Wright, T.; Hader, J.; Mccubbin, I. B.; Hallar, A. G.; Twohy, C. H.; Toohey, D. W.; DeMott, P. J.; McCluskey, C.; Baumgardner, D.

2013-12-01

Biological particles (bacteria, fungi/fungal spores, viruses, algae and fragments of biological material) may play a significant role in modifying cloud properties by acting as ice nuclei and thus have an indirect effect on climate forcing. Little is known, however, regarding the abundance and distribution of biological particles and their importance to cloud microphysics in different environments. On-line, continuous measurement systems offer the potential to measure biological systems at high time resolution and sensitivity, providing greater insight into their distribution in the atmosphere, dispersal mechanisms and potential soures. The WIBS-4A (Wideband Integrated Bioaerosol Sensor) detects fluorescent biological material in real-time associated with individual particles. It measures five properties: a) optical size via light scattering, b) fluorescent emissions in the wavelength range 310-400 following excitation by 280 nm light, c) fluorescent emissions in the wavelength range 420-650 following excitation by 280 nm light, d) fluorescent emissions in the wavelength range 420-650 following excitation by 370 nm light, and e) particle asymmetry factor based on intensities of forward scattered light onto a 4-element detector. Together, these properties aid the classification of sampled particles that contain biofluorophores such as tryptophan or NAD(P)H, which can be found in biological particles. Here we present results from a series of laboratory, ground- and aircraft-based measurements of biological particles using the WIBS-4A. The studies include airborne measurements over the United States, ground-based measurements at a coastal site, an urban site in the southeast US and a high alpine site, and laboratory measurements of a variety of biological and non-biological particles. Our analysis focused on both the characterization of the instrument response as well as an evaluation of its suitability for performing ambient measurements and potential artifacts. We also present recommendations for field operation of the instrument, sample system design considerations, and data analysis approaches.

Controllability and observability of Boolean networks arising from biology

NASA Astrophysics Data System (ADS)

Li, Rui; Yang, Meng; Chu, Tianguang

2015-02-01

Boolean networks are currently receiving considerable attention as a computational scheme for system level analysis and modeling of biological systems. Studying control-related problems in Boolean networks may reveal new insights into the intrinsic control in complex biological systems and enable us to develop strategies for manipulating biological systems using exogenous inputs. This paper considers controllability and observability of Boolean biological networks. We propose a new approach, which draws from the rich theory of symbolic computation, to solve the problems. Consequently, simple necessary and sufficient conditions for reachability, controllability, and observability are obtained, and algorithmic tests for controllability and observability which are based on the Gröbner basis method are presented. As practical applications, we apply the proposed approach to several different biological systems, namely, the mammalian cell-cycle network, the T-cell activation network, the large granular lymphocyte survival signaling network, and the Drosophila segment polarity network, gaining novel insights into the control and/or monitoring of the specific biological systems.

[Application of microelectronics CAD tools to synthetic biology].

PubMed

Madec, Morgan; Haiech, Jacques; Rosati, Élise; Rezgui, Abir; Gendrault, Yves; Lallement, Christophe

2017-02-01

Synthetic biology is an emerging science that aims to create new biological functions that do not exist in nature, based on the knowledge acquired in life science over the last century. Since the beginning of this century, several projects in synthetic biology have emerged. The complexity of the developed artificial bio-functions is relatively low so that empirical design methods could be used for the design process. Nevertheless, with the increasing complexity of biological circuits, this is no longer the case and a large number of computer aided design softwares have been developed in the past few years. These tools include languages for the behavioral description and the mathematical modelling of biological systems, simulators at different levels of abstraction, libraries of biological devices and circuit design automation algorithms. All of these tools already exist in other fields of engineering sciences, particularly in microelectronics. This is the approach that is put forward in this paper. © 2017 médecine/sciences – Inserm.

Novel statistical framework to identify differentially expressed genes allowing transcriptomic background differences.

PubMed

Ling, Zhi-Qiang; Wang, Yi; Mukaisho, Kenichi; Hattori, Takanori; Tatsuta, Takeshi; Ge, Ming-Hua; Jin, Li; Mao, Wei-Min; Sugihara, Hiroyuki

2010-06-01

Tests of differentially expressed genes (DEGs) from microarray experiments are based on the null hypothesis that genes that are irrelevant to the phenotype/stimulus are expressed equally in the target and control samples. However, this strict hypothesis is not always true, as there can be several transcriptomic background differences between target and control samples, including different cell/tissue types, different cell cycle stages and different biological donors. These differences lead to increased false positives, which have little biological/medical significance. In this article, we propose a statistical framework to identify DEGs between target and control samples from expression microarray data allowing transcriptomic background differences between these samples by introducing a modified null hypothesis that the gene expression background difference is normally distributed. We use an iterative procedure to perform robust estimation of the null hypothesis and identify DEGs as outliers. We evaluated our method using our own triplicate microarray experiment, followed by validations with reverse transcription-polymerase chain reaction (RT-PCR) and on the MicroArray Quality Control dataset. The evaluations suggest that our technique (i) results in less false positive and false negative results, as measured by the degree of agreement with RT-PCR of the same samples, (ii) can be applied to different microarray platforms and results in better reproducibility as measured by the degree of DEG identification concordance both intra- and inter-platforms and (iii) can be applied efficiently with only a few microarray replicates. Based on these evaluations, we propose that this method not only identifies more reliable and biologically/medically significant DEG, but also reduces the power-cost tradeoff problem in the microarray field. Source code and binaries freely available for download at http://comonca.org.cn/fdca/resources/softwares/deg.zip.

Functional annotation of the vlinc class of non-coding RNAs using systems biology approach

PubMed Central

Laurent, Georges St.; Vyatkin, Yuri; Antonets, Denis; Ri, Maxim; Qi, Yao; Saik, Olga; Shtokalo, Dmitry; de Hoon, Michiel J.L.; Kawaji, Hideya; Itoh, Masayoshi; Lassmann, Timo; Arner, Erik; Forrest, Alistair R.R.; Nicolas, Estelle; McCaffrey, Timothy A.; Carninci, Piero; Hayashizaki, Yoshihide; Wahlestedt, Claes; Kapranov, Philipp

2016-01-01

Functionality of the non-coding transcripts encoded by the human genome is the coveted goal of the modern genomics research. While commonly relied on the classical methods of forward genetics, integration of different genomics datasets in a global Systems Biology fashion presents a more productive avenue of achieving this very complex aim. Here we report application of a Systems Biology-based approach to dissect functionality of a newly identified vast class of very long intergenic non-coding (vlinc) RNAs. Using highly quantitative FANTOM5 CAGE dataset, we show that these RNAs could be grouped into 1542 novel human genes based on analysis of insulators that we show here indeed function as genomic barrier elements. We show that vlincRNAs genes likely function in cis to activate nearby genes. This effect while most pronounced in closely spaced vlincRNA–gene pairs can be detected over relatively large genomic distances. Furthermore, we identified 101 vlincRNA genes likely involved in early embryogenesis based on patterns of their expression and regulation. We also found another 109 such genes potentially involved in cellular functions also happening at early stages of development such as proliferation, migration and apoptosis. Overall, we show that Systems Biology-based methods have great promise for functional annotation of non-coding RNAs. PMID:27001520

Enantioselective potential of polysaccharide-based chiral stationary phases in supercritical fluid chromatography.

PubMed

Kucerova, Gabriela; Kalikova, Kveta; Tesarova, Eva

2017-06-01

The enantioselective potential of two polysaccharide-based chiral stationary phases for analysis of chiral structurally diverse biologically active compounds was evaluated in supercritical fluid chromatography using a set of 52 analytes. The chiral selectors immobilized on 2.5 μm silica particles were tris-(3,5-dimethylphenylcarmabate) derivatives of cellulose or amylose. The influence of the polysaccharide backbone, different organic modifiers, and different mobile phase additives on retention and enantioseparation was monitored. Conditions for fast baseline enantioseparation were found for the majority of the compounds. The success rate of baseline and partial enantioseparation with cellulose-based chiral stationary phase was 51.9% and 15.4%, respectively. Using amylose-based chiral stationary phase we obtained 76.9% of baseline enantioseparations and 9.6% of partial enantioseparations of the tested compounds. The best results on cellulose-based chiral stationary phase were achieved particularly with propane-2-ol and a mixture of isopropylamine and trifluoroacetic acid as organic modifier and additive to CO 2 , respectively. Methanol and basic additive isopropylamine were preferred on amylose-based chiral stationary phase. The complementary enantioselectivity of the cellulose- and amylose-based chiral stationary phases allows separation of the majority of the tested structurally different compounds. Separation systems were found to be directly applicable for analyses of biologically active compounds of interest. © 2017 Wiley Periodicals, Inc.

Analyzing gene expression time-courses based on multi-resolution shape mixture model.

PubMed

Li, Ying; He, Ye; Zhang, Yu

2016-11-01

Biological processes actually are a dynamic molecular process over time. Time course gene expression experiments provide opportunities to explore patterns of gene expression change over a time and understand the dynamic behavior of gene expression, which is crucial for study on development and progression of biology and disease. Analysis of the gene expression time-course profiles has not been fully exploited so far. It is still a challenge problem. We propose a novel shape-based mixture model clustering method for gene expression time-course profiles to explore the significant gene groups. Based on multi-resolution fractal features and mixture clustering model, we proposed a multi-resolution shape mixture model algorithm. Multi-resolution fractal features is computed by wavelet decomposition, which explore patterns of change over time of gene expression at different resolution. Our proposed multi-resolution shape mixture model algorithm is a probabilistic framework which offers a more natural and robust way of clustering time-course gene expression. We assessed the performance of our proposed algorithm using yeast time-course gene expression profiles compared with several popular clustering methods for gene expression profiles. The grouped genes identified by different methods are evaluated by enrichment analysis of biological pathways and known protein-protein interactions from experiment evidence. The grouped genes identified by our proposed algorithm have more strong biological significance. A novel multi-resolution shape mixture model algorithm based on multi-resolution fractal features is proposed. Our proposed model provides a novel horizons and an alternative tool for visualization and analysis of time-course gene expression profiles. The R and Matlab program is available upon the request. Copyright © 2016 Elsevier Inc. All rights reserved.

Direct Electron Transfer of Enzymes in a Biologically Assembled Conductive Nanomesh Enzyme Platform.

PubMed

Lee, Seung-Woo; Lee, Ki-Young; Song, Yong-Won; Choi, Won Kook; Chang, Joonyeon; Yi, Hyunjung

2016-02-24

Nondestructive assembly of a nanostructured enzyme platform is developed in combination of the specific biomolecular attraction and electrostatic coupling for highly efficient direct electron transfer (DET) of enzymes with unprecedented applicability and versatility. The biologically assembled conductive nanomesh enzyme platform enables DET-based flexible integrated biosensors and DET of eight different enzyme with various catalytic activities. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Nanoparticle surface characterization and clustering through concentration-dependent surface adsorption modeling.

PubMed

Chen, Ran; Zhang, Yuntao; Sahneh, Faryad Darabi; Scoglio, Caterina M; Wohlleben, Wendel; Haase, Andrea; Monteiro-Riviere, Nancy A; Riviere, Jim E

2014-09-23

Quantitative characterization of nanoparticle interactions with their surrounding environment is vital for safe nanotechnological development and standardization. A recent quantitative measure, the biological surface adsorption index (BSAI), has demonstrated promising applications in nanomaterial surface characterization and biological/environmental prediction. This paper further advances the approach beyond the application of five descriptors in the original BSAI to address the concentration dependence of the descriptors, enabling better prediction of the adsorption profile and more accurate categorization of nanomaterials based on their surface properties. Statistical analysis on the obtained adsorption data was performed based on three different models: the original BSAI, a concentration-dependent polynomial model, and an infinite dilution model. These advancements in BSAI modeling showed a promising development in the application of quantitative predictive modeling in biological applications, nanomedicine, and environmental safety assessment of nanomaterials.

Transcriptomic basis for drought-resistance in Brassica napus L.

NASA Astrophysics Data System (ADS)

Wang, Pei; Yang, Cuiling; Chen, Hao; Song, Chunpeng; Zhang, Xiao; Wang, Daojie

2017-01-01

Based on transcriptomic data from four experimental settings with drought-resistant and drought-sensitive cultivars under drought and well-watered conditions, statistical analysis revealed three categories encompassing 169 highly differentially expressed genes (DEGs) in response to drought in Brassica napus L., including 37 drought-resistant cultivar-related genes, 35 drought-sensitive cultivar-related genes and 97 cultivar non-specific ones. We provide evidence that the identified DEGs were fairly uniformly distributed on different chromosomes and their expression patterns are variety specific. Except commonly enriched in response to various stimuli or stresses, different categories of DEGs show specific enrichment in certain biological processes or pathways, which indicated the possibility of functional differences among the three categories. Network analysis revealed relationships among the 169 DEGs, annotated biological processes and pathways. The 169 DEGs can be classified into different functional categories via preferred pathways or biological processes. Some pathways might simultaneously involve a large number of shared DEGs, and these pathways are likely to cross-talk and have overlapping biological functions. Several members of the identified DEGs fit to drought stress signal transduction pathway in Arabidopsis thaliana. Finally, quantitative real-time PCR validations confirmed the reproducibility of the RNA-seq data. These investigations are profitable for the improvement of crop varieties through transgenic engineering.

Biological Sex Differences in Depression: A Systematic Review.

PubMed

Labaka, Ainitze; Goñi-Balentziaga, Olatz; Lebeña, Andrea; Pérez-Tejada, Joana

2018-07-01

Depression is the leading cause of disability worldwide, and its prevalence is 2 times higher in women than in men. There is, however, a lack of data on sex-specific pathophysiology of this disorder. The purpose of this systematic review is to identify the biological sex differences found in major depressive disorder (MDD) in studies published in the last 10 years. We conducted a literature search using the Medline, PsycInfo, PubMed, and Web of Science databases, selecting English-language studies that included physiological measures compared by sex in addition to MDD. We identified 20 relevant studies, which consisted primarily of mixed methodology and samples. The reported physiological measures comprised a variety of serum biomarkers, gene mRNA expression, and brain activity. Findings suggest different biological patterns in those with MDD depending on sex. Specifically, women presented higher levels of inflammatory, neurotrophic, and serotonergic markers and a stronger correlation between levels of some inflammatory and neurotrophic factors and the severity of symptoms. This review provides information about possible different biological patterns for women and men with depressive disorder and may have important implications for treatment. Future research should include homogeneous samples; make comparisons based on sex, control sex hormone fluctuations and pharmacological treatment; and use consistent criteria for evaluating psychobiological changes in MDD.

Dietary antioxidant synergy in chemical and biological systems.

PubMed

Wang, Sunan; Zhu, Fan

2017-07-24

Antioxidant (AOX) synergies have been much reported in chemical ("test-tube" based assays focusing on pure chemicals), biological (tissue culture, animal and clinical models), and food systems during the past decade. Tentative synergies differ from each other due to the composition of AOX and the quantification methods. Regeneration mechanism responsible for synergy in chemical systems has been discussed. Solvent effects could contribute to the artifacts of synergy observed in the chemical models. Synergy in chemical models may hardly be relevant to biological systems that have been much less studied. Apparent discrepancies exist in understanding the molecular mechanisms in both chemical and biological systems. This review discusses diverse variables associated with AOX synergy and molecular scenarios for explanation. Future research to better utilize the synergy is suggested.

Genetic divergence and isolation by thermal environment in geothermal populations of an aquatic invertebrate.

PubMed

Johansson, M P; Quintela, M; Laurila, A

2016-09-01

Temperature is one of the most influential forces of natural selection impacting all biological levels. In the face of increasing global temperatures, studies over small geographic scales allowing investigations on the effects of gene flow are of great value for understanding thermal adaptation. Here, we investigated genetic population structure in the freshwater gastropod Radix balthica originating from contrasting thermal habitats in three areas of geothermal activity in Iceland. Snails from 32 sites were genotyped at 208 AFLP loci. Five AFLPs were identified as putatively under divergent selection in Lake Mývatn, a geothermal lake with an almost 20 °C difference in mean temperature across a distance of a few kilometres. In four of these loci, variation across all study populations was correlated with temperature. We found significant population structure in neutral markers both within and between the areas. Cluster analysis using neutral markers classified the sites mainly by geography, whereas analyses using markers under selection differentiated the sites based on temperature. Isolation by distance was stronger in the neutral than in the outlier loci. Pairwise differences based on outlier FST were significantly correlated with temperature at different spatial scales, even after correcting for geographic distance or neutral pairwise FST differences. In general, genetic variation decreased with increasing environmental temperature, possibly suggesting that natural selection had reduced the genetic diversity in the warm origin sites. Our results emphasize the influence of environmental temperature on the genetic structure of populations and suggest local thermal adaptation in these geothermal habitats. © 2016 European Society For Evolutionary Biology. Journal of Evolutionary Biology © 2016 European Society For Evolutionary Biology.

The influence of rearing order on personality development within two adoption cohorts.

PubMed

Beer, J M; Horn, J M

2000-08-01

There is an extensive literature on the relationship between birth order and psychological traits, but no previous study has investigated the influence of ordinal position on personality development within adoptive siblings. Such a design is important because it effectively separates the effects of biological birth order and rearing order. Here we report data from two adoption cohorts in which subjects were biological first-borns reared in various ordinal positions. Data were analyzed with reference to Sulloway's (1996) evolutionarily based sibling rivalry theory of birth order effects. Between- and within-family analyses indicated that rearing order's influence on personality was very weak. The only clear difference was for conscientiousness, on which first-reared siblings scored higher. We draw possible implications for Sulloway's theory and speculate upon an alternative, prenatal biological process that may produce birth order differences.

Recent findings and technological advances in phosphoproteomics for cells and tissues.

PubMed

von Stechow, Louise; Francavilla, Chiara; Olsen, Jesper V

2015-01-01

Site-specific phosphorylation is a fast and reversible covalent post-translational modification that is tightly regulated in cells. The cellular machinery of enzymes that write, erase and read these modifications (kinases, phosphatases and phospho-binding proteins) is frequently deregulated in different diseases, including cancer. Large-scale studies of phosphoproteins - termed phosphoproteomics - strongly rely on the use of high-performance mass spectrometric instrumentation. This powerful technology has been applied to study a great number of phosphorylation-based phenotypes. Nevertheless, many technical and biological challenges have to be overcome to identify biologically relevant phosphorylation sites in cells and tissues. This review describes different technological strategies to identify and quantify phosphorylation sites with high accuracy, without significant loss of analysis speed and reproducibility in tissues and cells. Moreover, computational tools for analysis, integration and biological interpretation of phosphorylation events are discussed.

Using Multiple Lenses to Examine the Development of Beginning Biology Teachers' Pedagogical Content Knowledge for Teaching Natural Selection Simulations

NASA Astrophysics Data System (ADS)

Sickel, Aaron J.; Friedrichsen, Patricia

2018-02-01

Pedagogical content knowledge (PCK) has become a useful construct to examine science teacher learning. Yet, researchers conceptualize PCK development in different ways. The purpose of this longitudinal study was to use three analytic lenses to understand the development of three beginning biology teachers' PCK for teaching natural selection simulations. We observed three early-career biology teachers as they taught natural selection in their respective school contexts over two consecutive years. Data consisted of six interviews with each participant. Using the PCK model developed by Magnusson et al. (1999), we examined topic-specific PCK development utilizing three different lenses: (1) expansion of knowledge within an individual knowledge base, (2) integration of knowledge across knowledge bases, and (3) knowledge that explicitly addressed core concepts of natural selection. We found commonalities across the participants, yet each lens was also useful to understand the influence of different factors (e.g., orientation, subject matter preparation, and the idiosyncratic nature of teacher knowledge) on PCK development. This multi-angle approach provides implications for considering the quality of beginning science teachers' knowledge and future research on PCK development. We conclude with an argument that explicitly communicating lenses used to understand PCK development will help the research community compare analytic approaches and better understand the nature of science teacher learning.

Yeast prions: structure, biology, and prion-handling systems.

PubMed

Wickner, Reed B; Shewmaker, Frank P; Bateman, David A; Edskes, Herman K; Gorkovskiy, Anton; Dayani, Yaron; Bezsonov, Evgeny E

2015-03-01

A prion is an infectious protein horizontally transmitting a disease or trait without a required nucleic acid. Yeast and fungal prions are nonchromosomal genes composed of protein, generally an altered form of a protein that catalyzes the same alteration of the protein. Yeast prions are thus transmitted both vertically (as genes composed of protein) and horizontally (as infectious proteins, or prions). Formation of amyloids (linear ordered β-sheet-rich protein aggregates with β-strands perpendicular to the long axis of the filament) underlies most yeast and fungal prions, and a single prion protein can have any of several distinct self-propagating amyloid forms with different biological properties (prion variants). Here we review the mechanism of faithful templating of protein conformation, the biological roles of these prions, and their interactions with cellular chaperones, the Btn2 and Cur1 aggregate-handling systems, and other cellular factors governing prion generation and propagation. Human amyloidoses include the PrP-based prion conditions and many other, more common amyloid-based diseases, several of which show prion-like features. Yeast prions increasingly are serving as models for the understanding and treatment of many mammalian amyloidoses. Patients with different clinical pictures of the same amyloidosis may be the equivalent of yeasts with different prion variants. Copyright © 2015, American Society for Microbiology. All Rights Reserved.

Students' Participation in an Interdisciplinary, Socioscientific Issues Based Undergraduate Human Biology Major and Their Understanding of Scientific Inquiry

NASA Astrophysics Data System (ADS)

Eastwood, Jennifer L.; Sadler, Troy D.; Sherwood, Robert D.; Schlegel, Whitney M.

2013-06-01

The purpose of this study was to examine whether Socioscientific Issues (SSI) based learning environments affect university students' epistemological understanding of scientific inquiry differently from traditional science educational contexts. We identify and compare conceptions of scientific inquiry of students participating in an interdisciplinary, SSI-focused undergraduate human biology major (SSI) and those participating in a traditional biology major (BIO). Forty-five SSI students and 50 BIO students completed an open-ended questionnaire examining their understanding of scientific inquiry. Eight general themes including approximately 60 subthemes emerged from questionnaire responses, and the numbers of students including each subtheme in their responses were statistically compared between groups. A subset of students participated in interviews, which were used to validate and triangulate questionnaire data and probe students' understanding of scientific inquiry in relation to their majors. We found that both groups provided very similar responses, differing significantly in only five subthemes. Results indicated that both groups held generally adequate understandings of inquiry, but also a number of misconceptions. Small differences between groups supported by both questionnaires and interviews suggest that the SSI context contributed to nuanced understandings, such as a more interdisciplinary and problem-centered conception of scientific inquiry. Implications for teaching and research are discussed.

Utilization of different anti-viral mechanisms by mammalian embryonic stem cells and differentiated cells.

PubMed

Guo, Yan-Lin

2017-01-01

Embryonic stem cells (ESCs) have received tremendous attention because of their potential applications in regenerative medicine. Over the past two decades, intensive research has not only led to the generation of various types of cells from ESCs that can be potentially used for the treatment of human diseases but also led to the formation of new concepts and breakthroughs that have significantly impacted our understanding of basic cell biology and developmental biology. Recent studies have revealed that ESCs and other types of pluripotent cells do not have a functional interferon (IFN)-based anti-viral mechanism, challenging the idea that the IFN system is developed as the central component of anti-viral innate immunity in all types of cells in vertebrates. This finding also provided important insight into a question that has been uncertain for a long time: whether or not the RNA interference (RNAi) anti-viral mechanism operates in mammalian cells. An emerging paradigm is that mammals may have adapted distinct anti-viral mechanisms at different stages of organismal development; the IFN-based system is mainly used by differentiated somatic cells, while the RNAi anti-viral mechanism may be used in ESCs. This paper discusses the molecular basis and biological implications for mammals to have different anti-viral mechanisms during development.

Yeast Prions: Structure, Biology, and Prion-Handling Systems

PubMed Central

Shewmaker, Frank P.; Bateman, David A.; Edskes, Herman K.; Gorkovskiy, Anton; Dayani, Yaron; Bezsonov, Evgeny E.

2015-01-01

SUMMARY A prion is an infectious protein horizontally transmitting a disease or trait without a required nucleic acid. Yeast and fungal prions are nonchromosomal genes composed of protein, generally an altered form of a protein that catalyzes the same alteration of the protein. Yeast prions are thus transmitted both vertically (as genes composed of protein) and horizontally (as infectious proteins, or prions). Formation of amyloids (linear ordered β-sheet-rich protein aggregates with β-strands perpendicular to the long axis of the filament) underlies most yeast and fungal prions, and a single prion protein can have any of several distinct self-propagating amyloid forms with different biological properties (prion variants). Here we review the mechanism of faithful templating of protein conformation, the biological roles of these prions, and their interactions with cellular chaperones, the Btn2 and Cur1 aggregate-handling systems, and other cellular factors governing prion generation and propagation. Human amyloidoses include the PrP-based prion conditions and many other, more common amyloid-based diseases, several of which show prion-like features. Yeast prions increasingly are serving as models for the understanding and treatment of many mammalian amyloidoses. Patients with different clinical pictures of the same amyloidosis may be the equivalent of yeasts with different prion variants. PMID:25631286

Knowledge-driven genomic interactions: an application in ovarian cancer.

PubMed

Kim, Dokyoon; Li, Ruowang; Dudek, Scott M; Frase, Alex T; Pendergrass, Sarah A; Ritchie, Marylyn D

2014-01-01

Effective cancer clinical outcome prediction for understanding of the mechanism of various types of cancer has been pursued using molecular-based data such as gene expression profiles, an approach that has promise for providing better diagnostics and supporting further therapies. However, clinical outcome prediction based on gene expression profiles varies between independent data sets. Further, single-gene expression outcome prediction is limited for cancer evaluation since genes do not act in isolation, but rather interact with other genes in complex signaling or regulatory networks. In addition, since pathways are more likely to co-operate together, it would be desirable to incorporate expert knowledge to combine pathways in a useful and informative manner. Thus, we propose a novel approach for identifying knowledge-driven genomic interactions and applying it to discover models associated with cancer clinical phenotypes using grammatical evolution neural networks (GENN). In order to demonstrate the utility of the proposed approach, an ovarian cancer data from the Cancer Genome Atlas (TCGA) was used for predicting clinical stage as a pilot project. We identified knowledge-driven genomic interactions associated with cancer stage from single knowledge bases such as sources of pathway-pathway interaction, but also knowledge-driven genomic interactions across different sets of knowledge bases such as pathway-protein family interactions by integrating different types of information. Notably, an integration model from different sources of biological knowledge achieved 78.82% balanced accuracy and outperformed the top models with gene expression or single knowledge-based data types alone. Furthermore, the results from the models are more interpretable because they are framed in the context of specific biological pathways or other expert knowledge. The success of the pilot study we have presented herein will allow us to pursue further identification of models predictive of clinical cancer survival and recurrence. Understanding the underlying tumorigenesis and progression in ovarian cancer through the global view of interactions within/between different biological knowledge sources has the potential for providing more effective screening strategies and therapeutic targets for many types of cancer.

Estimating the biological value of soft-bottom sediments with sediment profile imaging and grab sampling

NASA Astrophysics Data System (ADS)

Van Hoey, Gert; Birchenough, Silvana N. R.; Hostens, Kris

2014-02-01

Biological value estimation is based on a set of assessment questions and several thresholds to delineate areas of ecological importance (e.g. biodiversity). An existing framework, that was specifically designed to assess the ecosystem biodiversity, was expanded by adding new questions on the productivity, functionality and biogeochemical status of benthic habitats. The additional ecological and sedimentological information was collected by using sediment profile imagery (SPI) and grab sampling. Additionally, information on the performance and comparability of both techniques is provided in this study. The research idea was tested at a site near the harbor of Zeebrugge, an area under consideration as a new disposal site for dredged material from the harbor entrance. The sedimentology of the area can be adequately described based on the information from both SPI and Van Veen grab samples, but only the SPI revealed structural information on the physical habitat (layering, a-RPD). The latter information represented the current status of the benthic habitat, which was confirmed by the Van Veen grab samples. All information was summarized through the biological valuation framework, and provided clear evidence of the differences in biological value for the different sediment types within the area. We concluded that the installation of a new dredged material disposal site in this area was not in conflict with the benthic ecology. This area has a low biological value and the benthic system is adapted to changing conditions, which was signaled by the dominance of mobile, short living and opportunistic species. This study showed that suitable sedimentological and ecological information can be gathered by these traditional and complementary techniques, to estimate the biological value of an area in the light of marine spatial planning and environmental impact assessments.

Fuzzy Stochastic Petri Nets for Modeling Biological Systems with Uncertain Kinetic Parameters

PubMed Central

Liu, Fei; Heiner, Monika; Yang, Ming

2016-01-01

Stochastic Petri nets (SPNs) have been widely used to model randomness which is an inherent feature of biological systems. However, for many biological systems, some kinetic parameters may be uncertain due to incomplete, vague or missing kinetic data (often called fuzzy uncertainty), or naturally vary, e.g., between different individuals, experimental conditions, etc. (often called variability), which has prevented a wider application of SPNs that require accurate parameters. Considering the strength of fuzzy sets to deal with uncertain information, we apply a specific type of stochastic Petri nets, fuzzy stochastic Petri nets (FSPNs), to model and analyze biological systems with uncertain kinetic parameters. FSPNs combine SPNs and fuzzy sets, thereby taking into account both randomness and fuzziness of biological systems. For a biological system, SPNs model the randomness, while fuzzy sets model kinetic parameters with fuzzy uncertainty or variability by associating each parameter with a fuzzy number instead of a crisp real value. We introduce a simulation-based analysis method for FSPNs to explore the uncertainties of outputs resulting from the uncertainties associated with input parameters, which works equally well for bounded and unbounded models. We illustrate our approach using a yeast polarization model having an infinite state space, which shows the appropriateness of FSPNs in combination with simulation-based analysis for modeling and analyzing biological systems with uncertain information. PMID:26910830

The emerging genomics and systems biology research lead to systems genomics studies.

PubMed

Yang, Mary Qu; Yoshigoe, Kenji; Yang, William; Tong, Weida; Qin, Xiang; Dunker, A; Chen, Zhongxue; Arbania, Hamid R; Liu, Jun S; Niemierko, Andrzej; Yang, Jack Y

2014-01-01

Synergistically integrating multi-layer genomic data at systems level not only can lead to deeper insights into the molecular mechanisms related to disease initiation and progression, but also can guide pathway-based biomarker and drug target identification. With the advent of high-throughput next-generation sequencing technologies, sequencing both DNA and RNA has generated multi-layer genomic data that can provide DNA polymorphism, non-coding RNA, messenger RNA, gene expression, isoform and alternative splicing information. Systems biology on the other hand studies complex biological systems, particularly systematic study of complex molecular interactions within specific cells or organisms. Genomics and molecular systems biology can be merged into the study of genomic profiles and implicated biological functions at cellular or organism level. The prospectively emerging field can be referred to as systems genomics or genomic systems biology. The Mid-South Bioinformatics Centre (MBC) and Joint Bioinformatics Ph.D. Program of University of Arkansas at Little Rock and University of Arkansas for Medical Sciences are particularly interested in promoting education and research advancement in this prospectively emerging field. Based on past investigations and research outcomes, MBC is further utilizing differential gene and isoform/exon expression from RNA-seq and co-regulation from the ChiP-seq specific for different phenotypes in combination with protein-protein interactions, and protein-DNA interactions to construct high-level gene networks for an integrative genome-phoneme investigation at systems biology level.

Impact of heuristics in clustering large biological networks.

PubMed

Shafin, Md Kishwar; Kabir, Kazi Lutful; Ridwan, Iffatur; Anannya, Tasmiah Tamzid; Karim, Rashid Saadman; Hoque, Mohammad Mozammel; Rahman, M Sohel

2015-12-01

Traditional clustering algorithms often exhibit poor performance for large networks. On the contrary, greedy algorithms are found to be relatively efficient while uncovering functional modules from large biological networks. The quality of the clusters produced by these greedy techniques largely depends on the underlying heuristics employed. Different heuristics based on different attributes and properties perform differently in terms of the quality of the clusters produced. This motivates us to design new heuristics for clustering large networks. In this paper, we have proposed two new heuristics and analyzed the performance thereof after incorporating those with three different combinations in a recently celebrated greedy clustering algorithm named SPICi. We have extensively analyzed the effectiveness of these new variants. The results are found to be promising. Copyright © 2015 Elsevier Ltd. All rights reserved.

Enhancing endosomal escape for nanoparticle mediated siRNA delivery

NASA Astrophysics Data System (ADS)

Ma, Da

2014-05-01

Gene therapy with siRNA is a promising biotechnology to treat cancer and other diseases. To realize siRNA-based gene therapy, a safe and efficient delivery method is essential. Nanoparticle mediated siRNA delivery is of great importance to overcome biological barriers for systemic delivery in vivo. Based on recent discoveries, endosomal escape is a critical biological barrier to be overcome for siRNA delivery. This feature article focuses on endosomal escape strategies used for nanoparticle mediated siRNA delivery, including cationic polymers, pH sensitive polymers, calcium phosphate, and cell penetrating peptides. Work has been done to develop different endosomal escape strategies based on nanoparticle types, administration routes, and target organ/cell types. Also, enhancement of endosomal escape has been considered along with other aspects of siRNA delivery to ensure target specific accumulation, high cell uptake, and low toxicity. By enhancing endosomal escape and overcoming other biological barriers, great progress has been achieved in nanoparticle mediated siRNA delivery.

A pathway-based view of human diseases and disease relationships.

PubMed

Li, Yong; Agarwal, Pankaj

2009-01-01

It is increasingly evident that human diseases are not isolated from each other. Understanding how different diseases are related to each other based on the underlying biology could provide new insights into disease etiology, classification, and shared biological mechanisms. We have taken a computational approach to studying disease relationships through 1) systematic identification of disease associated genes by literature mining, 2) associating diseases to biological pathways where disease genes are enriched, and 3) linking diseases together based on shared pathways. We identified 4,195 candidate disease associated genes for 1028 diseases. On average, about 50% of disease associated genes of a disease are statistically mapped to pathways. We generated a disease network which consists of 591 diseases and 6,931 disease relationships. We examined properties of this network and provided examples of novel disease relationships which cannot be readily captured through simple literature search or gene overlap analysis. Our results could potentially provide insights into the design of novel, pathway-guided therapeutic interventions for diseases.

Teaching statistics in biology: using inquiry-based learning to strengthen understanding of statistical analysis in biology laboratory courses.

PubMed

Metz, Anneke M

2008-01-01

There is an increasing need for students in the biological sciences to build a strong foundation in quantitative approaches to data analyses. Although most science, engineering, and math field majors are required to take at least one statistics course, statistical analysis is poorly integrated into undergraduate biology course work, particularly at the lower-division level. Elements of statistics were incorporated into an introductory biology course, including a review of statistics concepts and opportunity for students to perform statistical analysis in a biological context. Learning gains were measured with an 11-item statistics learning survey instrument developed for the course. Students showed a statistically significant 25% (p < 0.005) increase in statistics knowledge after completing introductory biology. Students improved their scores on the survey after completing introductory biology, even if they had previously completed an introductory statistics course (9%, improvement p < 0.005). Students retested 1 yr after completing introductory biology showed no loss of their statistics knowledge as measured by this instrument, suggesting that the use of statistics in biology course work may aid long-term retention of statistics knowledge. No statistically significant differences in learning were detected between male and female students in the study.

Effects of Immunomodulators and Biologic Agents on Sexual Health in Patients With Inflammatory Bowel Disease.

PubMed

Kanar, Ozdemir; Berry, Andrew C; Nakshabendi, Rahman; Lee, Ann Joo; Aldridge, Petra; Myers, Travis; Eid, Emely

2017-01-01

Although much knowledge has been gained regarding the medical and surgical management of inflammatory bowel disease (IBD), a paucity of information is available on the psychosexual issues related to IBD. The aim of this study was to evaluate the sexual health of patients with IBD who were taking immunomodulators and/or biologic agents vs patients with IBD who were not on that medication regimen. All study participants completed a validated sexual health questionnaire, the Female Sexual Function Index or the International Index of Erectile Function, to assess their subjective perception of the effect of IBD on the different domains of sexual function during the prior 1-month time period. No statistically significant differences in any baseline demographic variables were found for either sex between the group taking immunomodulators/biologic agents and the nontreatment group. Among females and males, individual question responses, domain scores, and total scores showed no statistically significant differences between the 2 treatment groups. Our data suggest that the use of immunomodulators or biologic agents does not affect female or male sexual health. However, treatment of patients with IBD must be individualized based on the aggressive nature of the disease, treatment goals, and the tolerability of various medications.

Molecular commonality detection using an artificial enzyme membrane for in situ one-stop biosurveillance.

PubMed

Ikeno, Shinya; Asakawa, Hitoshi; Haruyama, Tetsuya

2007-08-01

Biodetection and biosensing have been developed based on the concept of sensitivity toward specific molecules. However, current demand may require more levelheaded or far-sighted methods, especially in the field of biological safety and security. In the fields of hygiene, public safety, and security including fighting bioterrorism, the detection of biological contaminants, e.g., microorganisms, spores, and viruses, is a constant challenge. However, there is as yet no sophisticated method of detecting such contaminants in situ without oversight. The authors focused their attention on diphosphoric acid anhydride, which is a structure common to all biological phosphoric substances. Interestingly, biological phosphoric substances are peculiar substances present in all living things and include many different substances, e.g., ATP, ADP, dNTP, pyrophosphate, and so forth, all of which have a diphosphoric acid anhydride structure. The authors took this common structure as the basis of their development of an artificial enzyme membrane with selectivity for the structure common to all biological phosphoric substances and studied the possibility of its application to in situ biosurveillance sensors. The artificial enzyme membrane-based amperometric biosensor developed by the authors can detect various biological phosphoric substances, because it has a comprehensive molecular selectivity for the structure of these biological phosphoric substances. This in situ detection method of the common diphosphoric acid anhydride structure brings a unique advantage to the fabrication of in situ biosurveillance sensors for monitoring biological contaminants, e.g., microorganism, spores, and viruses, without an oversight, even if they were transformed.

Comparative Network-Based Recovery Analysis and Proteomic Profiling of Neurological Changes in Valproic Acid-Treated Mice

PubMed Central

2013-01-01

Despite its prominence for characterization of complex mixtures, LC–MS/MS frequently fails to identify many proteins. Network-based analysis methods, based on protein–protein interaction networks (PPINs), biological pathways, and protein complexes, are useful for recovering non-detected proteins, thereby enhancing analytical resolution. However, network-based analysis methods do come in varied flavors for which the respective efficacies are largely unknown. We compare the recovery performance and functional insights from three distinct instances of PPIN-based approaches, viz., Proteomics Expansion Pipeline (PEP), Functional Class Scoring (FCS), and Maxlink, in a test scenario of valproic acid (VPA)-treated mice. We find that the most comprehensive functional insights, as well as best non-detected protein recovery performance, are derived from FCS utilizing real biological complexes. This outstrips other network-based methods such as Maxlink or Proteomics Expansion Pipeline (PEP). From FCS, we identified known biological complexes involved in epigenetic modifications, neuronal system development, and cytoskeletal rearrangements. This is congruent with the observed phenotype where adult mice showed an increase in dendritic branching to allow the rewiring of visual cortical circuitry and an improvement in their visual acuity when tested behaviorally. In addition, PEP also identified a novel complex, comprising YWHAB, NR1, NR2B, ACTB, and TJP1, which is functionally related to the observed phenotype. Although our results suggest different network analysis methods can produce different results, on the whole, the findings are mutually supportive. More critically, the non-overlapping information each provides can provide greater holistic understanding of complex phenotypes. PMID:23557376

Profiling of polar metabolites in biological extracts using diamond hydride-based aqueous normal phase chromatography.

PubMed

Callahan, Damien L; De Souza, David; Bacic, Antony; Roessner, Ute

2009-07-01

Highly polar metabolites, such as sugars and most amino acids are not retained by conventional RP LC columns. Without sufficient retention low concentration compounds are not detected due ion suppression and structural isomers are not resolved. In contrast, hydrophilic interaction chromatography (HILIC) and aqueous normal phase chromatography (ANP) retain compounds based on their hydrophilicity and therefore provides a means of separating highly polar compounds. Here, an ANP method based on the diamond hydride stationary phase is presented for profiling biological small molecules by LC. A rapid separation system based upon a fast gradient that delivers reproducible chromatography is presented. Approximately 1000 compounds were reproducibly detected in human urine samples and clear differences between these samples were identified. This chromatography was also applied to xylem fluid from soyabean (Glycine max) plants to which 400 compounds were detected. This method greatly increases the metabolite coverage over RP-only metabolite profiling in biological samples. We show that both forms of chromatography are necessary for untargeted comprehensive metabolite profiling and that the diamond hydride stationary phase provides a good option for polar metabolite analysis.

Ground-Based Facilities for Simulation of Microgravity: Organism-Specific Recommendations for Their Use, and Recommended Terminology

PubMed Central

Anken, Ralf; Boonstra, Johannes; Braun, Markus; Christianen, Peter C.M.; de Geest, Maarten; Hauslage, Jens; Hilbig, Reinhard; Hill, Richard J.A.; Lebert, Michael; Medina, F. Javier; Vagt, Nicole; Ullrich, Oliver

2013-01-01

Abstract Research in microgravity is indispensable to disclose the impact of gravity on biological processes and organisms. However, research in the near-Earth orbit is severely constrained by the limited number of flight opportunities. Ground-based simulators of microgravity are valuable tools for preparing spaceflight experiments, but they also facilitate stand-alone studies and thus provide additional and cost-efficient platforms for gravitational research. The various microgravity simulators that are frequently used by gravitational biologists are based on different physical principles. This comparative study gives an overview of the most frequently used microgravity simulators and demonstrates their individual capacities and limitations. The range of applicability of the various ground-based microgravity simulators for biological specimens was carefully evaluated by using organisms that have been studied extensively under the conditions of real microgravity in space. In addition, current heterogeneous terminology is discussed critically, and recommendations are given for appropriate selection of adequate simulators and consistent use of nomenclature. Key Words: 2-D clinostat—3-D clinostat—Gravity—Magnetic levitation—Random positioning machine—Simulated microgravity—Space biology. Astrobiology 13, 1–17. PMID:23252378

[Problems of world outlook and methodology of science integration in biological studies].

PubMed

Khododova, Iu D

1981-01-01

Problems of worldoutlook and methodology of the natural-science knowledge are considered basing on the analysis of tendencies in the development of the membrane theory of cell processes and the use of principles of biological membrane functioning when solving some scientific and applied problems pertaining to different branches of chemistry and biology. The notion scientific knowledge integration is defined as interpenetration of approaches, methods and ideas of different branches of knowledge and enrichment on this basis of their content resulting in knowledge augmentation in each field taken separately. These processes are accompanied by appearance of new branches of knowledge - sciences "on junction" and their subsequent differentiations. The analysis of some gnoseological situations shows that integration of sciences contributes to coordination and some agreement of thinking styles of different specialists, puts forward keen personality of a scientist demanding, in particular, his high professional mobility. Problems of scientific activity organization are considered, which involve social sciences into the integration processes. The role of philosophy in the integration processes is emphasized.

Using the mixed media according to internet-based on the instructional multimedia for developing students' learning achievements in biology course on foundational cell issue of secondary students at the 10th grade level in Rangsit University demonstration school

NASA Astrophysics Data System (ADS)

Kangloan, Pichet; Chayaburakul, Kanokporn; Santiboon, Toansakul

2018-01-01

The aims of this research study were 1) to develop students' learning achievements in biology course on foundational cell issue, 2) to examine students' satisfactions of their learning activities through the mixed media according to internet-based multi-instruction in biology on foundational cell issue at the 10th grade level were used in the first semester in the academic year 2014, which a sample size of 17 students in Rangsit University Demonstration School with cluster random sampling was selected. Students' learning administrations were instructed with the 3-instructional lesson plans according to the 5-Step Ladder Learning Management Plan (LLMP) namely; the maintaining lesson plan on the equilibrium of cell issue, a lesson plan for learning how to communicate between cell and cell division. Students' learning achievements were assessed with the 30-item Assessment of Learning Biology Test (ALBT), students' perceptions of their satisfactions were satisfied with the 20-item Questionnaire on Students Satisfaction (QSS), and students' learning activities were assessed with the Mixed Media Internet-Based Instruction (MMIBI) on foundational cell issue was designed. The results of this research study have found that: statistically significant of students' post-learning achievements were higher than their pre-learning outcomes and indicated that the differences were significant at the .05 level. Students' performances of their satisfaction to their perceptions toward biology class with the mixed media according to internet-based multi instruction in biology on foundational cell issue were the highest level and evidence of average mean score as 4.59.

Nanogranular SiO2 proton gated silicon layer transistor mimicking biological synapses

NASA Astrophysics Data System (ADS)

Liu, M. J.; Huang, G. S.; Feng, P.; Guo, Q. L.; Shao, F.; Tian, Z. A.; Li, G. J.; Wan, Q.; Mei, Y. F.

2016-06-01

Silicon on insulator (SOI)-based transistors gated by nanogranular SiO2 proton conducting electrolytes were fabricated to mimic synapse behaviors. This SOI-based device has both top proton gate and bottom buried oxide gate. Electrical transfer properties of top proton gate show hysteresis curves different from those of bottom gate, and therefore, excitatory post-synaptic current and paired pulse facilitation (PPF) behavior of biological synapses are mimicked. Moreover, we noticed that PPF index can be effectively tuned by the spike interval applied on the top proton gate. Synaptic behaviors and functions, like short-term memory, and its properties are also experimentally demonstrated in our device. Such SOI-based electronic synapses are promising for building neuromorphic systems.

Towards quantitative mass spectrometry-based metabolomics in microbial and mammalian systems.

PubMed

Kapoore, Rahul Vijay; Vaidyanathan, Seetharaman

2016-10-28

Metabolome analyses are a suite of analytical approaches that enable us to capture changes in the metabolome (small molecular weight components, typically less than 1500 Da) in biological systems. Mass spectrometry (MS) has been widely used for this purpose. The key challenge here is to be able to capture changes in a reproducible and reliant manner that is representative of the events that take place in vivo Typically, the analysis is carried out in vitro, by isolating the system and extracting the metabolome. MS-based approaches enable us to capture metabolomic changes with high sensitivity and resolution. When developing the technique for different biological systems, there are similarities in challenges and differences that are specific to the system under investigation. Here, we review some of the challenges in capturing quantitative changes in the metabolome with MS based approaches, primarily in microbial and mammalian systems.This article is part of the themed issue 'Quantitative mass spectrometry'. © 2016 The Author(s).

Toward Contactless Biology: Acoustophoretic DNA Transfection

NASA Astrophysics Data System (ADS)

Vasileiou, Thomas; Foresti, Daniele; Bayram, Adem; Poulikakos, Dimos; Ferrari, Aldo

2016-02-01

Acoustophoresis revolutionized the field of container-less manipulation of liquids and solids by enabling mixing procedures which avoid contamination and loss of reagents due to the contact with the support. While its applications to chemistry and engineering are straightforward, additional developments are needed to obtain reliable biological protocols in a contactless environment. Here, we provide a first, fundamental step towards biological reactions in air by demonstrating the acoustophoretic DNA transfection of mammalian cells. We developed an original acoustophoretic design capable of levitating, moving and mixing biological suspensions of living mammalians cells and of DNA plasmids. The precise and sequential delivery of the mixed solutions into tissue culture plates is actuated by a novel mechanism based on the controlled actuation of the acoustophoretic force. The viability of the contactless procedure is tested using a cellular model sensitive to small perturbation of neuronal differentiation pathways. Additionally, the efficiency of the transfection procedure is compared to standard, container-based methods for both single and double DNA transfection and for different cell types including adherent growing HeLa cancer cells, and low adhesion neuron-like PC12 cells. In all, this work provides a proof of principle which paves the way to the development of high-throughput acoustophoretic biological reactors.

Synthetic biology between challenges and risks: suggestions for a model of governance and a regulatory framework, based on fundamental rights.

PubMed

Colussi, Ilaria Anna

2013-01-01

This paper deals with the emerging synthetic biology, its challenges and risks, and tries to design a model for the governance and regulation of the field. The model is called of "prudent vigilance" (inspired by the report about synthetic biology, drafted by the U.S. Presidential Commission on Bioethics, 2010), and it entails (a) an ongoing and periodically revised process of assessment and management of all the risks and concerns, and (b) the adoption of policies - taken through "hard law" and "soft law" sources - that are based on the principle of proportionality (among benefits and risks), on a reasonable balancing between different interests and rights at stake, and are oriented by a constitutional frame, which is represented by the protection of fundamental human rights emerging in the field of synthetic biology (right to life, right to health, dignity, freedom of scientific research, right to environment). After the theoretical explanation of the model, its operability is "checked", by considering its application with reference to only one specific risk brought up by synthetic biology - biosecurity risk, i.e. the risk of bioterrorism.

Toward Contactless Biology: Acoustophoretic DNA Transfection.

PubMed

Vasileiou, Thomas; Foresti, Daniele; Bayram, Adem; Poulikakos, Dimos; Ferrari, Aldo

2016-02-01

Acoustophoresis revolutionized the field of container-less manipulation of liquids and solids by enabling mixing procedures which avoid contamination and loss of reagents due to the contact with the support. While its applications to chemistry and engineering are straightforward, additional developments are needed to obtain reliable biological protocols in a contactless environment. Here, we provide a first, fundamental step towards biological reactions in air by demonstrating the acoustophoretic DNA transfection of mammalian cells. We developed an original acoustophoretic design capable of levitating, moving and mixing biological suspensions of living mammalians cells and of DNA plasmids. The precise and sequential delivery of the mixed solutions into tissue culture plates is actuated by a novel mechanism based on the controlled actuation of the acoustophoretic force. The viability of the contactless procedure is tested using a cellular model sensitive to small perturbation of neuronal differentiation pathways. Additionally, the efficiency of the transfection procedure is compared to standard, container-based methods for both single and double DNA transfection and for different cell types including adherent growing HeLa cancer cells, and low adhesion neuron-like PC12 cells. In all, this work provides a proof of principle which paves the way to the development of high-throughput acoustophoretic biological reactors.

Toward Contactless Biology: Acoustophoretic DNA Transfection

PubMed Central

Vasileiou, Thomas; Foresti, Daniele; Bayram, Adem; Poulikakos, Dimos; Ferrari, Aldo

2016-01-01

Acoustophoresis revolutionized the field of container-less manipulation of liquids and solids by enabling mixing procedures which avoid contamination and loss of reagents due to the contact with the support. While its applications to chemistry and engineering are straightforward, additional developments are needed to obtain reliable biological protocols in a contactless environment. Here, we provide a first, fundamental step towards biological reactions in air by demonstrating the acoustophoretic DNA transfection of mammalian cells. We developed an original acoustophoretic design capable of levitating, moving and mixing biological suspensions of living mammalians cells and of DNA plasmids. The precise and sequential delivery of the mixed solutions into tissue culture plates is actuated by a novel mechanism based on the controlled actuation of the acoustophoretic force. The viability of the contactless procedure is tested using a cellular model sensitive to small perturbation of neuronal differentiation pathways. Additionally, the efficiency of the transfection procedure is compared to standard, container-based methods for both single and double DNA transfection and for different cell types including adherent growing HeLa cancer cells, and low adhesion neuron-like PC12 cells. In all, this work provides a proof of principle which paves the way to the development of high-throughput acoustophoretic biological reactors. PMID:26828312

Comparative Proteomic Profiling and Biomarker Identification of Traditional Chinese Medicine-Based HIV/AIDS Syndromes.

PubMed

Wen, Li; Liu, Ye-Fang; Jiang, Cen; Zeng, Shao-Qian; Su, Yue; Wu, Wen-Jun; Liu, Xi-Yang; Wang, Jian; Liu, Ying; Su, Chen; Li, Bai-Xue; Feng, Quan-Sheng

2018-03-08

Given the challenges in exploring lifelong therapy with little side effect for human immunodeficiency virus infection and acquired immune deficiency syndrome (HIV/AIDS) cases, there is increasing interest in developing traditional Chinese medicine (TCM) treatments based on specific TCM syndrome. However, there are few objective and biological evidences for classification and diagnosis of HIV/AIDS TCM syndromes to date. In this study, iTRAQ-2DLC-MS/MS coupled with bioinformatics were firstly employed for comparative proteomic profiling of top popular TCM syndromes of HIV/AIDS: accumulation of heat-toxicity (AHT) and Yang deficiency of spleen and kidney (YDSK). It was found that for the two TCM syndromes, the identified differential expressed proteins (DEPs) as well as their biological function distributions and participation in signaling pathways were significantly different, providing biological evidence for the classification of HIV/AIDS TCM syndromes. Furthermore, the TCM syndrome-specific DEPs were confirmed as biomarkers based on western blot analyses, including FN1, GPX3, KRT10 for AHT and RBP4, ApoE, KNG1 for YDSK. These biomarkers also biologically linked with the specific TCM syndrome closely. Thus the clinical and biological basis for differentiation and diagnosis of HIV/AIDs TCM syndromes were provided for the first time, providing more opportunities for stable exertion and better application of TCM efficacy and superiority in HIV/AIDS treatment.

Recent advances in stable isotope labeling based techniques for proteome relative quantification.

PubMed

Zhou, Yuan; Shan, Yichu; Zhang, Lihua; Zhang, Yukui

2014-10-24

The large scale relative quantification of all proteins expressed in biological samples under different states is of great importance for discovering proteins with important biological functions, as well as screening disease related biomarkers and drug targets. Therefore, the accurate quantification of proteins at proteome level has become one of the key issues in protein science. Herein, the recent advances in stable isotope labeling based techniques for proteome relative quantification were reviewed, from the aspects of metabolic labeling, chemical labeling and enzyme-catalyzed labeling. Furthermore, the future research direction in this field was prospected. Copyright © 2014 Elsevier B.V. All rights reserved.

Nanoelectronic programmable synapses based on phase change materials for brain-inspired computing.

PubMed

Kuzum, Duygu; Jeyasingh, Rakesh G D; Lee, Byoungil; Wong, H-S Philip

2012-05-09

Brain-inspired computing is an emerging field, which aims to extend the capabilities of information technology beyond digital logic. A compact nanoscale device, emulating biological synapses, is needed as the building block for brain-like computational systems. Here, we report a new nanoscale electronic synapse based on technologically mature phase change materials employed in optical data storage and nonvolatile memory applications. We utilize continuous resistance transitions in phase change materials to mimic the analog nature of biological synapses, enabling the implementation of a synaptic learning rule. We demonstrate different forms of spike-timing-dependent plasticity using the same nanoscale synapse with picojoule level energy consumption.

Biological and chemical sensors based on graphene materials.

PubMed

Liu, Yuxin; Dong, Xiaochen; Chen, Peng

2012-03-21

Owing to their extraordinary electrical, chemical, optical, mechanical and structural properties, graphene and its derivatives have stimulated exploding interests in their sensor applications ever since the first isolation of free-standing graphene sheets in year 2004. This article critically and comprehensively reviews the emerging graphene-based electrochemical sensors, electronic sensors, optical sensors, and nanopore sensors for biological or chemical detection. We emphasize on the underlying detection (or signal transduction) mechanisms, the unique roles and advantages of the used graphene materials. Properties and preparations of different graphene materials, their functionalizations are also comparatively discussed in view of sensor development. Finally, the perspective and current challenges of graphene sensors are outlined (312 references).

The Viking biology results

NASA Technical Reports Server (NTRS)

Klein, Harold P.

1989-01-01

A brief review of the purposes and the results from the Viking Biology experiments is presented, in the expectation that the lessons learned from this mission will be useful in planning future approaches to the biological exploration of Mars. Since so little was then known about potential micro-environments on Mars, three different experiments were included in the Viking mission, each one based on different assumptions about what Martian organisms might be like. In addition to the Viking Biology Instrument (VBI), important corollary information was obtained from the Viking lander imaging system and from the molecular analysis experiments that were conducted using the gas chromatograph-mass spectrometer (GCMS) instrument. No biological objects were noted by the lander imaging instrument. The GCMS did not detect any organic compounds. A description of the tests conducted by the Gas Exchange Experiment, the Labeled Release experiment, and the Pyrolytic Release experiment is given. Results are discussed. Taken as a whole, the Viking data yielded no unequivocal evidence for a Martian biota at either landing site. The results also revealed the presence of one or more reactive oxidants in the surface material and these need to be further characterized, as does the range of micro-environments, before embarking upon future searches for extant life on Mars.

Is the whole the sum of its parts? Agent-based modelling of wastewater treatment systems.

PubMed

Schuler, A J; Majed, N; Bucci, V; Hellweger, F L; Tu, Y; Gu, A Z

2011-01-01

Agent-based models (ABMS) simulate individual units within a system, such as the bacteria in a biological wastewater treatment system. This paper outlines past, current and potential future applications of ABMs to wastewater treatment. ABMs track heterogeneities within microbial populations, and this has been demonstrated to yield different predictions of bulk behaviors than the conventional, "lumped" approaches for enhanced biological phosphorus removal (EBPR) completely mixed reactors systems. Current work included the application of the ABM approach to bacterial adaptation/evolution, using the model system of individual EBPR bacteria that are allowed to evolve a kinetic parameter (maximum glycogen storage) in a competitive environment. The ABM approach was successfully implemented to a simple anaerobic-aerobic system and it was found the differing initial states converged to the same optimal solution under uncertain hydraulic residence times associated with completely mixed hydraulics. In another study, an ABM was developed and applied to simulate the heterogeneity in intracellular polymer storage compounds, including polyphosphate (PP), in functional microbial populations in enhanced biological phosphorus removal (EBPR) process. The simulation results were compared to the experimental measurements of single-cell abundance of PP in polyphosphate accumulating organisms (PAOs), performed using Raman microscopy. The model-predicted heterogeneity was generally consistent with observations, and it was used to investigate the relative contribution of external (different life histories) and internal (biological) mechanisms leading to heterogeneity. In the future, ABMs could be combined with computational fluid dynamics (CFD) models to understand incomplete mixing, more intracellular states and mechanisms can be incorporated, and additional experimental verification is needed.

Developments in purification methods for obtaining and evaluation of collagen derived endogenous angioinhibitors

PubMed Central

Gunda, Venugopal; Verma, Raj K.; Pawar, Smita C.; Sudhakar, Yakkanti A.

2013-01-01

Collagen constitutes one of the vital components of the basement membrane scaffolds. Non-collagenous domains (NC1) derived from collagens exhibit potent anti-angiogenic properties, thus attaining significance in regulation of angiogenesis promoted diseases. Individual NC1 domains essential for anti-angiogenic evaluations are generally obtained through purification of individual non-collagenous domains, which have undergone steady developments for enhancing the yields, purpose of biological evaluations and solubility based on the nature of different NC1 domains. This review focuses on the method developments in obtaining biologically active NC1 domains and for specific evaluations in different scenarios. PMID:24215863

Simulation-based model checking approach to cell fate specification during Caenorhabditis elegans vulval development by hybrid functional Petri net with extension.

PubMed

Li, Chen; Nagasaki, Masao; Ueno, Kazuko; Miyano, Satoru

2009-04-27

Model checking approaches were applied to biological pathway validations around 2003. Recently, Fisher et al. have proved the importance of model checking approach by inferring new regulation of signaling crosstalk in C. elegans and confirming the regulation with biological experiments. They took a discrete and state-based approach to explore all possible states of the system underlying vulval precursor cell (VPC) fate specification for desired properties. However, since both discrete and continuous features appear to be an indispensable part of biological processes, it is more appropriate to use quantitative models to capture the dynamics of biological systems. Our key motivation of this paper is to establish a quantitative methodology to model and analyze in silico models incorporating the use of model checking approach. A novel method of modeling and simulating biological systems with the use of model checking approach is proposed based on hybrid functional Petri net with extension (HFPNe) as the framework dealing with both discrete and continuous events. Firstly, we construct a quantitative VPC fate model with 1761 components by using HFPNe. Secondly, we employ two major biological fate determination rules - Rule I and Rule II - to VPC fate model. We then conduct 10,000 simulations for each of 48 sets of different genotypes, investigate variations of cell fate patterns under each genotype, and validate the two rules by comparing three simulation targets consisting of fate patterns obtained from in silico and in vivo experiments. In particular, an evaluation was successfully done by using our VPC fate model to investigate one target derived from biological experiments involving hybrid lineage observations. However, the understandings of hybrid lineages are hard to make on a discrete model because the hybrid lineage occurs when the system comes close to certain thresholds as discussed by Sternberg and Horvitz in 1986. Our simulation results suggest that: Rule I that cannot be applied with qualitative based model checking, is more reasonable than Rule II owing to the high coverage of predicted fate patterns (except for the genotype of lin-15ko; lin-12ko double mutants). More insights are also suggested. The quantitative simulation-based model checking approach is a useful means to provide us valuable biological insights and better understandings of biological systems and observation data that may be hard to capture with the qualitative one.

Students' Participation in an Interdisciplinary, Socioscientific Issues Based Undergraduate Human Biology Major and Their Understanding of Scientific Inquiry

ERIC Educational Resources Information Center

Eastwood, Jennifer L.; Sadler, Troy D.; Sherwood, Robert D.; Schlegel, Whitney M.

2013-01-01

The purpose of this study was to examine whether Socioscientific Issues (SSI) based learning environments affect university students' epistemological understanding of scientific inquiry differently from traditional science educational contexts. We identify and compare conceptions of scientific inquiry of students participating in an…

Detecting duplicate biological entities using Shortest Path Edit Distance.

PubMed

Rudniy, Alex; Song, Min; Geller, James

2010-01-01

Duplicate entity detection in biological data is an important research task. In this paper, we propose a novel and context-sensitive Shortest Path Edit Distance (SPED) extending and supplementing our previous work on Markov Random Field-based Edit Distance (MRFED). SPED transforms the edit distance computational problem to the calculation of the shortest path among two selected vertices of a graph. We produce several modifications of SPED by applying Levenshtein, arithmetic mean, histogram difference and TFIDF techniques to solve subtasks. We compare SPED performance to other well-known distance algorithms for biological entity matching. The experimental results show that SPED produces competitive outcomes.

From Presentation to Programming: Doing Something Different, Not the Same Thing Differently.

ERIC Educational Resources Information Center

Galas, Cathleen

1998-01-01

Discusses the use of multimedia software and the need to apply constructivist theories so students become more involved with the software, progressing from simply watching presentations to creating simulations. A project-based learning environment that uses MicroWorlds software is described that focuses on marine biology and oceanography. (LRW)

Effects of Irrigating Tree Seedlings with a Nutrient Solution

Treesearch

R. P. Belanger; C. B. Briscoe

1963-01-01

Subsurface irrigation with nutrient solution was found to be biologically feasible under the conditions tested. Growth of seedlings was satisfactory, but not unusually good. On the bases of total height growth, and growth in fresh weight, the various fertilizers tested produced statistically different results. The species tested, members of three different families and...

The Role of Student Major in Grade Perception in Chemistry Courses

ERIC Educational Resources Information Center

Karatjas, Andrew; Webb, Jeffrey

2017-01-01

The Kruger-Dunning effect was studied as it related to performance in chemistry courses based on student differences in academic background. Student major was chosen as the classification to look at the effect of students with different interests/specializations. Chemistry majors tended to predict lower performance than biology majors, while…

The role of different sampling methods in improving biological activity prediction using deep belief network.

PubMed

Ghasemi, Fahimeh; Fassihi, Afshin; Pérez-Sánchez, Horacio; Mehri Dehnavi, Alireza

2017-02-05

Thousands of molecules and descriptors are available for a medicinal chemist thanks to the technological advancements in different branches of chemistry. This fact as well as the correlation between them has raised new problems in quantitative structure activity relationship studies. Proper parameter initialization in statistical modeling has merged as another challenge in recent years. Random selection of parameters leads to poor performance of deep neural network (DNN). In this research, deep belief network (DBN) was applied to initialize DNNs. DBN is composed of some stacks of restricted Boltzmann machine, an energy-based method that requires computing log likelihood gradient for all samples. Three different sampling approaches were suggested to solve this gradient. In this respect, the impact of DBN was applied based on the different sampling approaches mentioned above to initialize the DNN architecture in predicting biological activity of all fifteen Kaggle targets that contain more than 70k molecules. The same as other fields of processing research, the outputs of these models demonstrated significant superiority to that of DNN with random parameters. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Biological parameters used in setting captive-breeding quotas for Indonesia's breeding facilities.

PubMed

Janssen, Jordi; Chng, Serene C L

2018-02-01

The commercial captive breeding of wildlife is often seen as a potential conservation tool to relieve pressure on wild populations, but laundering of wild-sourced specimens as captive bred can seriously undermine conservation efforts and provide a false sense of sustainability. Indonesia is at the center of such controversy; therefore, we examined Indonesia's captive-breeding production plan (CBPP) for 2016. We compared the biological parameters used in the CBPP with parameters in the literature and with parameters suggested by experts on each species and identified shortcomings of the CBPP. Production quotas for 99 out of 129 species were based on inaccurate or unrealistic biological parameters and production quotas deviated more than 10% from what parameters in the literature allow for. For 38 species, the quota exceeded the number of animals that can be bred based on the biological parameters (range 100-540%) calculated with equations in the CBPP. We calculated a lower reproductive output for 88 species based on published biological parameters compared with the parameters used in the CBPP. The equations used in the production plan did not appear to account for other factors (e.g., different survival rate for juveniles compared to adult animals) involved in breeding the proposed large numbers of specimens. We recommend the CBPP be adjusted so that realistic published biological parameters are applied and captive-breeding quotas are not allocated to species if their captive breeding is unlikely to be successful or no breeding stock is available. The shortcomings in the current CBPP create loopholes that mean mammals, reptiles, and amphibians from Indonesia declared captive bred may have been sourced from the wild. © 2017 Society for Conservation Biology.

Organophosphorus Insecticide Pharmacokinetics

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

Timchalk, Charles

2010-01-01

This chapter highlights a number of current and future applications of pharmacokinetics to assess organophosphate (OP) insecticide dosimetry, biological response and risk in humans exposed to these agents. Organophosphates represent a large family of pesticides where insecticidal as well as toxicological mode of action is associated with their ability to target and inhibit acetylcholinesterase (AChE). Pharmacokinetics entails the quantitative integration of physiological and metabolic processes associated with the absorption, distribution, metabolism and excretion (ADME) of drugs and xenobiotics. Pharmacokinetic studies provide important data on the amount of toxicant delivered to a target site as well as species-, age-, gender-specific andmore » dose-dependent differences in biological response. These studies have been conducted with organophosphorus insecticides in multiple species, at various dose levels, and across different routes of exposure to understand their in vivo pharmacokinetics and how they contribute to the observed toxicological response. To access human exposure to organophosphorus insecticides, human pharmacokinetic studies have been conducted and used to develop biological monitoring strategies based on the quantitation of key metabolites in biological fluids. Pharmacokinetic studies with these insecticides are also useful to facilitate extrapolation of dosimetry and biological response from animals to humans and for the assessment of human health risk. In this regard, physiologically based pharmacokinetic and pharmacodynamic (PBPK/PD) models are being utilized to assess risk and understand the toxicological implications of known or suspected exposures to various insecticides. In this chapter a number of examples are presented that illustrate the utility and limitation of pharmacokinetic studies to address human health concerns associated with organophosphorus insecticides.« less

Brown Spider (Loxosceles genus) Venom Toxins: Tools for Biological Purposes

PubMed Central

Chaim, Olga Meiri; Trevisan-Silva, Dilza; Chaves-Moreira, Daniele; Wille, Ana Carolina M.; Ferrer, Valéria Pereira; Matsubara, Fernando Hitomi; Mangili, Oldemir Carlos; da Silveira, Rafael Bertoni; Gremski, Luiza Helena; Gremski, Waldemiro; Senff-Ribeiro, Andrea; Veiga, Silvio Sanches

2011-01-01

Venomous animals use their venoms as tools for defense or predation. These venoms are complex mixtures, mainly enriched of proteic toxins or peptides with several, and different, biological activities. In general, spider venom is rich in biologically active molecules that are useful in experimental protocols for pharmacology, biochemistry, cell biology and immunology, as well as putative tools for biotechnology and industries. Spider venoms have recently garnered much attention from several research groups worldwide. Brown spider (Loxosceles genus) venom is enriched in low molecular mass proteins (5–40 kDa). Although their venom is produced in minute volumes (a few microliters), and contain only tens of micrograms of protein, the use of techniques based on molecular biology and proteomic analysis has afforded rational projects in the area and permitted the discovery and identification of a great number of novel toxins. The brown spider phospholipase-D family is undoubtedly the most investigated and characterized, although other important toxins, such as low molecular mass insecticidal peptides, metalloproteases and hyaluronidases have also been identified and featured in literature. The molecular pathways of the action of these toxins have been reported and brought new insights in the field of biotechnology. Herein, we shall see how recent reports describing discoveries in the area of brown spider venom have expanded biotechnological uses of molecules identified in these venoms, with special emphasis on the construction of a cDNA library for venom glands, transcriptome analysis, proteomic projects, recombinant expression of different proteic toxins, and finally structural descriptions based on crystallography of toxins. PMID:22069711

Mosaic, self-similarity logic, and biological attraction principles: three explanatory instruments in biology.

PubMed

Agnati, Luigi F; Baluska, Frantisek; Barlow, Peter W; Guidolin, Diego

2009-11-01

From a structural standpoint, living organisms are organized like a nest of Russian matryoshka dolls, in which structures are buried within one another. From a temporal point of view, this type of organization is the result of a history comprised of a set of time backcloths which have accompanied the passage of living matter from its origins up to the present day. The aim of the present paper is to indicate a possible course of this 'passage through time, and suggest how today's complexity has been reached by living organisms. This investigation will employ three conceptual tools, namely the Mosaic, Self-Similarity Logic, and the Biological Attraction principles. Self-Similarity Logic indicates the self-consistency by which elements of a living system interact, irrespective of the spatiotemporal level under consideration. The term Mosaic indicates how, from the same set of elements assembled according to different patterns, it is possible to arrive at completely different constructions: hence, each system becomes endowed with different emergent properties. The Biological Attraction principle states that there is an inherent drive for association and merging of compatible elements at all levels of biological complexity. By analogy with the gravitation law in physics, biological attraction is based on the evidence that each living organism creates an attractive field around itself. This field acts as a sphere of influence that actively attracts similar fields of other biological systems, thereby modifying salient features of the interacting organisms. Three specific organizational levels of living matter, namely the molecular, cellular, and supracellular levels, have been considered in order to analyse and illustrate the interpretative as well as the predictive roles of each of these three explanatory principles.

Analysis of classical Fourier, SPL and DPL heat transfer model in biological tissues in presence of metabolic and external heat source

NASA Astrophysics Data System (ADS)

Kumar, Dinesh; Singh, Surjan; Rai, K. N.

2016-06-01

In this paper, the temperature distribution in a finite biological tissue in presence of metabolic and external heat source when the surface subjected to different type of boundary conditions is studied. Classical Fourier, single-phase-lag (SPL) and dual-phase-lag (DPL) models were developed for bio-heat transfer in biological tissues. The analytical solution obtained for all the three models using Laplace transform technique and results are compared. The effect of the variability of different parameters such as relaxation time, metabolic heat source, spatial heat source, different type boundary conditions on temperature distribution in different type of the tissues like muscle, tumor, fat, dermis and subcutaneous based on three models are analyzed and discussed in detail. The result obtained in three models is compared with experimental observation of Stolwijk and Hardy (Pflug Arch 291:129-162, 1966). It has been observe that the DPL bio-heat transfer model provides better result in comparison of other two models. The value of metabolic and spatial heat source in boundary condition of first, second and third kind for different type of thermal therapies are evaluated.

From biology to mathematical models and back: teaching modeling to biology students, and biology to math and engineering students.

PubMed

Chiel, Hillel J; McManus, Jeffrey M; Shaw, Kendrick M

2010-01-01

We describe the development of a course to teach modeling and mathematical analysis skills to students of biology and to teach biology to students with strong backgrounds in mathematics, physics, or engineering. The two groups of students have different ways of learning material and often have strong negative feelings toward the area of knowledge that they find difficult. To give students a sense of mastery in each area, several complementary approaches are used in the course: 1) a "live" textbook that allows students to explore models and mathematical processes interactively; 2) benchmark problems providing key skills on which students make continuous progress; 3) assignment of students to teams of two throughout the semester; 4) regular one-on-one interactions with instructors throughout the semester; and 5) a term project in which students reconstruct, analyze, extend, and then write in detail about a recently published biological model. Based on student evaluations and comments, an attitude survey, and the quality of the students' term papers, the course has significantly increased the ability and willingness of biology students to use mathematical concepts and modeling tools to understand biological systems, and it has significantly enhanced engineering students' appreciation of biology.

Sexual orientation modulates endocrine stress reactivity.

PubMed

Juster, Robert-Paul; Hatzenbuehler, Mark L; Mendrek, Adrianna; Pfaus, James G; Smith, Nathan Grant; Johnson, Philip Jai; Lefebvre-Louis, Jean-Philippe; Raymond, Catherine; Marin, Marie-France; Sindi, Shireen; Lupien, Sonia J; Pruessner, Jens C

2015-04-01

Biological sex differences and sociocultural gender diversity influence endocrine stress reactivity. Although numerous studies have shown that men typically activate stronger stress responses than women when exposed to laboratory-based psychosocial stressors, it is unclear whether sexual orientation further modulates stress reactivity. Given that lesbian, gay, and bisexual (LGB) individuals frequently report heightened distress secondary to stigma-related stressors, we investigated whether cortisol stress reactivity differs between LGB individuals and heterosexual individuals in response to a well-validated psychosocial stressor. The study population comprised 87 healthy adults (mean age, 25 years) who were grouped according to their biological sex and their gendered sexual orientation: lesbian/bisexual women (n = 20), heterosexual women (n = 21), gay/bisexual men (n = 26), and heterosexual men (n = 20). Investigators collected 10 salivary cortisol samples throughout a 2-hour afternoon visit involving exposure to the Trier Social Stress Test modified to maximize between-sex differences. Relative to heterosexual women, lesbian/bisexual women showed higher cortisol stress reactivity 40 min after exposure to the stressor. In contrast, gay/bisexual men displayed lower overall cortisol concentrations throughout testing compared with heterosexual men. Main findings were significant while adjusting for sex hormones (estradiol-to-progesterone ratio in women and testosterone in men), age, self-esteem, and disclosure status (whether LGB participants had completed their "coming out"). Our results provide novel evidence for gender-based modulation of cortisol stress reactivity based on sexual orientation that goes beyond well-established between-sex differences. This study raises several important avenues for future research related to the physiologic functioning of LGB populations and gender diversity more broadly. Copyright © 2015 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.

Can current analytical quality performance of UK clinical laboratories support evidence-based guidelines for diabetes and ischaemic heart disease?--A pilot study and a proposal.

PubMed

Jassam, Nuthar; Yundt-Pacheco, John; Jansen, Rob; Thomas, Annette; Barth, Julian H

2013-08-01

The implementation of national and international guidelines is beginning to standardise clinical practice. However, since many guidelines have decision limits based on laboratory tests, there is an urgent need to ensure that different laboratories obtain the same analytical result on any sample. A scientifically-based quality control process will be a pre-requisite to provide this level of analytical performance which will support evidence-based guidelines and movement of patients across boundaries while maintaining standardised outcomes. We discuss the finding of a pilot study performed to assess UK clinical laboratories readiness to work to a higher grade quality specifications such as biological variation-based quality specifications. Internal quality control (IQC) data for HbA1c, glucose, creatinine, cholesterol and high density lipoprotein (HDL)-cholesterol were collected from UK laboratories participating in the Bio-Rad Unity QC programme. The median of the coefficient of variation (CV%) of the participating laboratories was evaluated against the CV% based on biological variation. Except creatinine, the other four analytes had a variable degree of compliance with the biological variation-based quality specifications. More than 75% of the laboratories met the biological variation-based quality specifications for glucose, cholesterol and HDL-cholesterol. Slightly over 50% of the laboratories met the analytical goal for HBA1c. Only one analyte (cholesterol) had a performance achieving the higher quality specifications consistent with 5σ. Our data from IQC do not consistently demonstrate that the results from clinical laboratories meet evidence-based quality specifications. Therefore, we propose that a graded scale of quality specifications may be needed at this stage.

[The safety of biologics : a risk-benefit assessment of treating rheumatoid arthritis with biologics based on registry data on mortality].

PubMed

Sander, O

2010-11-01

The aim of this study is a risk-benefit assessment of treating rheumatoid arthritis with biologics based on registry data on mortality.UK, Sweden and Spain have published evaluable data on mortality. A parallel control group was conducted in the UK. Sweden and Spain used an historical cohort for comparison.Central registries supported British and Swedish research by sending details on all deaths. The variety of possible confounders prevents direct comparisons of the registers and safe predictions for individual patients.The death rate in TNF-inhibitor-treated patients is higher than in the general population but lower than in the control groups with RA. Thus comorbidities are not balanced, the weighted mortality rate scaled down the difference between exposed patients and controls. When TNF-inhibitors are given for the usual indication, mortality is reduced compared to conventional therapy.

Uncertainty result of biotic index in analysing the water quality of Cikapundung river catchment area, Bandung

NASA Astrophysics Data System (ADS)

Surtikanti, Hertien Koosbandiah

2017-05-01

The Biotic Index was developed in Western Countries in response to the need in water quality evaluation. This method analysis is based on the classification of aquatic macrobenthos as a bioindicator for clean and polluted water. The aim of this study is to compare the analysis of Cikapundung river using 6 different Biotic Indexes. BI Shannon-Weiner, Belgian Biological Index (BBI), Family Biotic Index (FBI), Biological Monitoring Working Party (BMWP), Biological Monitoring Working Party-Average Score Per Taxon (BMWP-ASPT), and A Scoring System for Macroinvertebrate in Australian River (A SIGNAL). Those analysis are compared with Physical Water Index (CPI) which is developed in Indonesia. The result shows that a decreasing water quality is detected upstream to downstream of Cikapundung River. However, based on the CPI analysis result, the BMWP-ASPT biotic index analysis is more comprehensive than other BI in explaining Cikapundung water quality.

A simple method of fabricating mask-free microfluidic devices for biological analysis

PubMed Central

Yi, Xin; Kodzius, Rimantas; Gong, Xiuqing; Xiao, Kang; Wen, Weijia

2010-01-01

We report a simple, low-cost, rapid, and mask-free method to fabricate two-dimensional (2D) and three-dimensional (3D) microfluidic chip for biological analysis researches. In this fabrication process, a laser system is used to cut through paper to form intricate patterns and differently configured channels for specific purposes. Bonded with cyanoacrylate-based resin, the prepared paper sheet is sandwiched between glass slides (hydrophilic) or polymer-based plates (hydrophobic) to obtain a multilayer structure. In order to examine the chip’s biocompatibility and applicability, protein concentration was measured while DNA capillary electrophoresis was carried out, and both of them show positive results. With the utilization of direct laser cutting and one-step gas-sacrificing techniques, the whole fabrication processes for complicated 2D and 3D microfluidic devices are shorten into several minutes which make it a good alternative of poly(dimethylsiloxane) microfluidic chips used in biological analysis researches. PMID:20890452

Green Synthesis of Metallic Nanoparticles via Biological Entities

PubMed Central

Shah, Monaliben; Fawcett, Derek; Sharma, Shashi; Tripathy, Suraj Kumar; Poinern, Gérrard Eddy Jai

2015-01-01

Nanotechnology is the creation, manipulation and use of materials at the nanometre size scale (1 to 100 nm). At this size scale there are significant differences in many material properties that are normally not seen in the same materials at larger scales. Although nanoscale materials can be produced using a variety of traditional physical and chemical processes, it is now possible to biologically synthesize materials via environment-friendly green chemistry based techniques. In recent years, the convergence between nanotechnology and biology has created the new field of nanobiotechnology that incorporates the use of biological entities such as actinomycetes algae, bacteria, fungi, viruses, yeasts, and plants in a number of biochemical and biophysical processes. The biological synthesis via nanobiotechnology processes have a significant potential to boost nanoparticles production without the use of harsh, toxic, and expensive chemicals commonly used in conventional physical and chemical processes. The aim of this review is to provide an overview of recent trends in synthesizing nanoparticles via biological entities and their potential applications. PMID:28793638

Time-resolved photoacoustic measurement for evaluation of viscoelastic properties of biological tissues

NASA Astrophysics Data System (ADS)

Zhao, Yue; Chen, Conggui; Liu, Hongwei; Yang, Sihua; Xing, Da

2016-11-01

In this letter, we proposed a method for viscoelastic characterization of biological tissues based on time-resolved photoacoustic measurement. The theoretical and experimental study was performed on the influence of viscoelasticity effects on photoacoustic generation. Taking the time delay between the photoacoustic signal and the exciting laser, the viscoelasticity distribution of biological tissues can be mapped. To validate our method, gelatin phantoms with different densities were measured. We also applied this method in discrimination between fat and liver to confirm the usefulness of the viscoelastic evaluation. Furthermore, pilot experiments were performed on atherosclerosis artery from an apolipoprotein E-knockout mouse to show the viscoelastic characterization of atherosclerotic plaque. Our results demonstrate that this technique has the potential for visualizing the biomechanical properties and lesions of biological tissues.

Materials Manufactured from 3D Printed Synthetic Biology Arrays

NASA Technical Reports Server (NTRS)

Gentry, Diana; Micks, Ashley

2013-01-01

Many complex, biologically-derived materials have extremely useful properties (think wood or silk), but are unsuitable for space-related applications due to production, manufacturing, or processing limitations. Large-scale ecosystem-based production, such as raising and harvesting trees for wood, is impractical in a self-contained habitat such as a space station or potential Mars colony. Manufacturing requirements, such as the specialized equipment needed to harvest and process cotton, add too much upmass for current launch technology. Cells in nature are already highly specialized for making complex biological materials on a micro scale. We envision combining these strengths with the recently emergent technologies of synthetic biology and 3D printing to create 3D-structured arrays of cells that are bioengineered to secrete different materials in a specified three-dimensional pattern.

Does a prosocial-selfish distinction help explain the biological affects? Comment on Buck (1999).

PubMed

Gray, Jeremy R

2002-10-01

R. Buck (1999) argued that a conceptual distinction between prosocial and selfish motivation is necessary to understand the biological affects (consciously experienced feelings and desires having an innate neurochemical basis). However, at a biological level of analysis, a prosocial-selfish distinction is doubtful empirically and conceptually. For this reason, Buck's proposed typology of biological affects is unclear. Moreover, a prosocial-selfish distinction is not necessary to explain hemispheric differences in brain activity associated with affect. In contrast, an approach-withdrawal distinction explains some data uniquely well, although numerous exceptions imply that simple models are inadequate. To extend hemispheric models of experienced emotion, a prosocial-selfish distinction is unlikely to be explanatory, whereas an alternative account based on a distinction between verbal and nonverbal working memory may be useful.

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

Hartmann, Anja, E-mail: hartmann@ipk-gatersleben.de; Schreiber, Falk; Martin-Luther-University Halle-Wittenberg, Halle

The characterization of biological systems with respect to their behavior and functionality based on versatile biochemical interactions is a major challenge. To understand these complex mechanisms at systems level modeling approaches are investigated. Different modeling formalisms allow metabolic models to be analyzed depending on the question to be solved, the biochemical knowledge and the availability of experimental data. Here, we describe a method for an integrative analysis of the structure and dynamics represented by qualitative and quantitative metabolic models. Using various formalisms, the metabolic model is analyzed from different perspectives. Determined structural and dynamic properties are visualized in the contextmore » of the metabolic model. Interaction techniques allow the exploration and visual analysis thereby leading to a broader understanding of the behavior and functionality of the underlying biological system. The System Biology Metabolic Model Framework (SBM{sup 2} – Framework) implements the developed method and, as an example, is applied for the integrative analysis of the crop plant potato.« less

An FD-LC-MS/MS Proteomic Strategy for Revealing Cellular Protein Networks: A Conditional Superoxide Dismutase 1 Knockout Cells

PubMed Central

Ichibangase, Tomoko; Sugawara, Yasuhiro; Yamabe, Akio; Koshiyama, Akiyo; Yoshimura, Akari; Enomoto, Takemi; Imai, Kazuhiro

2012-01-01

Systems biology aims to understand biological phenomena in terms of complex biological and molecular interactions, and thus proteomics plays an important role in elucidating protein networks. However, many proteomic methods have suffered from their high variability, resulting in only showing altered protein names. Here, we propose a strategy for elucidating cellular protein networks based on an FD-LC-MS/MS proteomic method. The strategy permits reproducible relative quantitation of differences in protein levels between different cell populations and allows for integration of the data with those obtained through other methods. We demonstrate the validity of the approach through a comparison of differential protein expression in normal and conditional superoxide dismutase 1 gene knockout cells and believe that beginning with an FD-LC-MS/MS proteomic approach will enable researchers to elucidate protein networks more easily and comprehensively. PMID:23029042

CHOmine: an integrated data warehouse for CHO systems biology and modeling

PubMed Central

Hanscho, Michael; Ruckerbauer, David E.; Zanghellini, Jürgen; Borth, Nicole

2017-01-01

Abstract The last decade has seen a surge in published genome-scale information for Chinese hamster ovary (CHO) cells, which are the main production vehicles for therapeutic proteins. While a single access point is available at www.CHOgenome.org, the primary data is distributed over several databases at different institutions. Currently research is frequently hampered by a plethora of gene names and IDs that vary between published draft genomes and databases making systems biology analyses cumbersome and elaborate. Here we present CHOmine, an integrative data warehouse connecting data from various databases and links to other ones. Furthermore, we introduce CHOmodel, a web based resource that provides access to recently published CHO cell line specific metabolic reconstructions. Both resources allow to query CHO relevant data, find interconnections between different types of data and thus provides a simple, standardized entry point to the world of CHO systems biology. Database URL: http://www.chogenome.org PMID:28605771

Constitutive expression of tdTomato protein as a cytotoxicity and proliferation marker for space radiation biology

NASA Astrophysics Data System (ADS)

Chishti, Arif A.; Hellweg, Christine E.; Berger, Thomas; Baumstark-Khan, Christa; Feles, Sebastian; Kätzel, Thorben; Reitz, Günther

2015-01-01

The radiation risk assessment for long-term space missions requires knowledge on the biological effectiveness of different space radiation components, e.g. heavy ions, on the interaction of radiation and other space environmental factors such as microgravity, and on the physical and biological dose distribution in the human body. Space experiments and ground-based experiments at heavy ion accelerators require fast and reliable test systems with an easy readout for different endpoints. In order to determine the effect of different radiation qualities on cellular proliferation and the biological depth dose distribution after heavy ion exposure, a stable human cell line expressing a novel fluorescent protein was established and characterized. tdTomato, a red fluorescent protein of the new generation with fast maturation and high fluorescence intensity, was selected as reporter of cell proliferation. Human embryonic kidney (HEK/293) cells were stably transfected with a plasmid encoding tdTomato under the control of the constitutively active cytomegalovirus (CMV) promoter (ptdTomato-N1). The stably transfected cell line was named HEK-ptdTomato-N1 8. This cytotoxicity biosensor was tested by ionizing radiation (X-rays and accelerated heavy ions) exposure. As biological endpoints, the proliferation kinetics and the cell density reached 100 h after irradiation reflected by constitutive expression of the tdTomato were investigated. Both were reduced dose-dependently after radiation exposure. Finally, the cell line was used for biological weighting of heavy ions of different linear energy transfer (LET) as space-relevant radiation quality. The relative biological effectiveness of accelerated heavy ions in reducing cellular proliferation peaked at an LET of 91 keV/μm. The results of this study demonstrate that the HEK-ptdTomato-N1 reporter cell line can be used as a fast and reliable biosensor system for detection of cytotoxic damage caused by ionizing radiation.

Research of detection depth for graphene-based optical sensor

NASA Astrophysics Data System (ADS)

Yang, Yong; Sun, Jialve; Liu, Lu; Zhu, Siwei; Yuan, Xiaocong

2018-03-01

Graphene-based optical sensors have been developed for research into the biological intercellular refractive index (RI) because they offer greater detection depths than those provided by the surface plasmon resonance technique. In this Letter, we propose an experimental approach for measurement of the detection depth in a graphene-based optical sensor system that uses transparent polydimethylsiloxane layers with different thicknesses. The experimental results show that detection depths of 2.5 μm and 3 μm can be achieved at wavelengths of 532 nm and 633 nm, respectively. These results prove that graphene-based optical sensors can realize long-range RI detection and are thus promising for use as tools in the biological cell detection field. Additionally, we analyze the factors that influence the detection depth and provide a feasible approach for detection depth control based on adjustment of the wavelength and the angle of incidence. We believe that this approach will be useful in RI tomography applications.

A Feedfordward Adaptive Controller to Reduce the Imaging Time of Large-Sized Biological Samples with a SPM-Based Multiprobe Station

PubMed Central

Otero, Jorge; Guerrero, Hector; Gonzalez, Laura; Puig-Vidal, Manel

2012-01-01

The time required to image large samples is an important limiting factor in SPM-based systems. In multiprobe setups, especially when working with biological samples, this drawback can make impossible to conduct certain experiments. In this work, we present a feedfordward controller based on bang-bang and adaptive controls. The controls are based in the difference between the maximum speeds that can be used for imaging depending on the flatness of the sample zone. Topographic images of Escherichia coli bacteria samples were acquired using the implemented controllers. Results show that to go faster in the flat zones, rather than using a constant scanning speed for the whole image, speeds up the imaging process of large samples by up to a 4× factor. PMID:22368491

ADAM: analysis of discrete models of biological systems using computer algebra.

PubMed

Hinkelmann, Franziska; Brandon, Madison; Guang, Bonny; McNeill, Rustin; Blekherman, Grigoriy; Veliz-Cuba, Alan; Laubenbacher, Reinhard

2011-07-20

Many biological systems are modeled qualitatively with discrete models, such as probabilistic Boolean networks, logical models, Petri nets, and agent-based models, to gain a better understanding of them. The computational complexity to analyze the complete dynamics of these models grows exponentially in the number of variables, which impedes working with complex models. There exist software tools to analyze discrete models, but they either lack the algorithmic functionality to analyze complex models deterministically or they are inaccessible to many users as they require understanding the underlying algorithm and implementation, do not have a graphical user interface, or are hard to install. Efficient analysis methods that are accessible to modelers and easy to use are needed. We propose a method for efficiently identifying attractors and introduce the web-based tool Analysis of Dynamic Algebraic Models (ADAM), which provides this and other analysis methods for discrete models. ADAM converts several discrete model types automatically into polynomial dynamical systems and analyzes their dynamics using tools from computer algebra. Specifically, we propose a method to identify attractors of a discrete model that is equivalent to solving a system of polynomial equations, a long-studied problem in computer algebra. Based on extensive experimentation with both discrete models arising in systems biology and randomly generated networks, we found that the algebraic algorithms presented in this manuscript are fast for systems with the structure maintained by most biological systems, namely sparseness and robustness. For a large set of published complex discrete models, ADAM identified the attractors in less than one second. Discrete modeling techniques are a useful tool for analyzing complex biological systems and there is a need in the biological community for accessible efficient analysis tools. ADAM provides analysis methods based on mathematical algorithms as a web-based tool for several different input formats, and it makes analysis of complex models accessible to a larger community, as it is platform independent as a web-service and does not require understanding of the underlying mathematics.

The effect of nanobioceramic reinforcement on mechanical and biological properties of Co-base alloy/hydroxyapatite nanocomposite.

PubMed

Bahrami, M; Fathi, M H; Ahmadian, M

2015-03-01

The goal of the present research was to fabricate, characterize, and evaluate mechanical and biological properties of Co-base alloy composites with different amounts of hydroxyapatite (HA) nanopowder reinforcement. The powder of Co-Cr-Mo alloy was mixed with different amounts of HA by ball milling and it was then cold pressed and sintered. X-ray diffraction (XRD) and scanning electron microscopy (SEM) techniques were used. Microhardness measurement and compressive tests were also carried out. Bioactivity behavior was evaluated in simulated body fluid (SBF). A significant decrease in modulus elasticity and an increase in microhardness of the sintered composites were observed. Apatite formation on the surface of the composites showed that it could successfully convert bioinert Co-Cr-Mo alloy to bioactive type by adding 10, 15, and 20wt.% HA which have lower modulus elasticity and higher microhardness. Copyright © 2014 Elsevier B.V. All rights reserved.

The potential of standards-based agriculture biology as an alternative to traditional biology in California

NASA Astrophysics Data System (ADS)

Sellu, George Sahr

Over the past five decades, several waves of educational reform have influenced K-12 science course offerings and classroom instruction in public education. The effectiveness of educational policies has been increasingly measured by standardized tests. The focus on test scores, content standards, and performance standards (which is a product of recent educational policies) has influenced course offerings and the depth and breadth of curriculum coverage (Linn, 2000). For the better part of the last hundred years, vocational education and traditional education have followed two separate tracks in terms of objectives, policies, and values (Hillison, 1996). Educational reform policies have had varying influences on school programs. For example, elective courses such as Career Technical Education (CTE) courses---which are not considered core academic courses---have been negatively influenced by current educational reform. In the past three decades, there has been gradual movement toward merging vocational and traditional education. It has been difficult for policies from both sides to merge because of differences in objectives for both tracks. Traditional courses have been guided by federal policies, such as No Child Left Behind (NCLB) and Common Core State Standards (CCSS) while the Carl D. Perkins Act (Perkins Act) has shaped CTE courses. It appears that several of the requirements of the Perkins Act meet expectations of traditional education policies. However, there is no direct metric for measuring the contribution of CTE courses toward increased achievement in science as measured by standardized tests. As such, CTE courses will continue to lose resources in order to support courses that prepare students for standardized tests. In order to address some of these challenges over the last three decades, agriculture educators have developed integrated science courses as a means for increasing science achievement scores for agriculture education students in K-12 public schools. Thoron & Meyer (2011) suggested that research into the contribution of integrated science courses toward higher test scores yielded mixed results. This finding may have been due in part to the fact that integrated science courses only incorporate select topics into agriculture education courses. In California, however, agriculture educators have developed standards-based courses such as Agriculture Biology (AgBio) that cover the same content standards as core traditional courses such as traditional biology. Students in both AgBio and traditional biology take the same standardized biology test. This is the first time there has been an opportunity for a fair comparison and a uniform metric for an agriscience course such as AgBio to be directly compared to traditional biology. This study will examine whether there are differences between AgBio and traditional biology with regard to standardized test scores in biology. Furthermore, the study examines differences in perception between teachers and students regarding teaching and learning activities associated with higher achievement in science. The findings of the study could provide a basis for presenting AgBio as a potential alternative to traditional biology. The findings of this study suggest that there are no differences between AgBio and traditional biology students with regard to standardized biology test scores. Additionally, the findings indicate that co-curricular activities in AgBio could contribute higher student achievement in biology. However, further research is required to identify specific activities in AgBio that contribute to higher achievement in science.

Forward Modeling of Atmospheric Carbon Dioxide in GEOS-5: Uncertainties Related to Surface Fluxes and Sub-Grid Transport

NASA Technical Reports Server (NTRS)

Pawson, Steven; Ott, Lesley E.; Zhu, Zhengxin; Bowman, Kevin; Brix, Holger; Collatz, G. James; Dutkiewicz, Stephanie; Fisher, Joshua B.; Gregg, Watson W.; Hill, Chris;

Testing and Validation of Computational Methods for Mass Spectrometry.

PubMed

Gatto, Laurent; Hansen, Kasper D; Hoopmann, Michael R; Hermjakob, Henning; Kohlbacher, Oliver; Beyer, Andreas

2016-03-04

High-throughput methods based on mass spectrometry (proteomics, metabolomics, lipidomics, etc.) produce a wealth of data that cannot be analyzed without computational methods. The impact of the choice of method on the overall result of a biological study is often underappreciated, but different methods can result in very different biological findings. It is thus essential to evaluate and compare the correctness and relative performance of computational methods. The volume of the data as well as the complexity of the algorithms render unbiased comparisons challenging. This paper discusses some problems and challenges in testing and validation of computational methods. We discuss the different types of data (simulated and experimental validation data) as well as different metrics to compare methods. We also introduce a new public repository for mass spectrometric reference data sets ( http://compms.org/RefData ) that contains a collection of publicly available data sets for performance evaluation for a wide range of different methods.

Methods for improving simulations of biological systems: systemic computation and fractal proteins

PubMed Central

Bentley, Peter J.

2009-01-01

Modelling and simulation are becoming essential for new fields such as synthetic biology. Perhaps the most important aspect of modelling is to follow a clear design methodology that will help to highlight unwanted deficiencies. The use of tools designed to aid the modelling process can be of benefit in many situations. In this paper, the modelling approach called systemic computation (SC) is introduced. SC is an interaction-based language, which enables individual-based expression and modelling of biological systems, and the interactions between them. SC permits a precise description of a hypothetical mechanism to be written using an intuitive graph-based or a calculus-based notation. The same description can then be directly run as a simulation, merging the hypothetical mechanism and the simulation into the same entity. However, even when using well-designed modelling tools to produce good models, the best model is not always the most accurate one. Frequently, computational constraints or lack of data make it infeasible to model an aspect of biology. Simplification may provide one way forward, but with inevitable consequences of decreased accuracy. Instead of attempting to replace an element with a simpler approximation, it is sometimes possible to substitute the element with a different but functionally similar component. In the second part of this paper, this modelling approach is described and its advantages are summarized using an exemplar: the fractal protein model. Finally, the paper ends with a discussion of good biological modelling practice by presenting lessons learned from the use of SC and the fractal protein model. PMID:19324681

TrypsNetDB: An integrated framework for the functional characterization of trypanosomatid proteins

PubMed Central

Gazestani, Vahid H.; Yip, Chun Wai; Nikpour, Najmeh; Berghuis, Natasha

2017-01-01

Trypanosomatid parasites cause serious infections in humans and production losses in livestock. Due to the high divergence from other eukaryotes, such as humans and model organisms, the functional roles of many trypanosomatid proteins cannot be predicted by homology-based methods, rendering a significant portion of their proteins as uncharacterized. Recent technological advances have led to the availability of multiple systematic and genome-wide datasets on trypanosomatid parasites that are informative regarding the biological role(s) of their proteins. Here, we report TrypsNetDB (http://trypsNetDB.org), a web-based resource for the functional annotation of 16 different species/strains of trypanosomatid parasites. The database not only visualizes the network context of the queried protein(s) in an intuitive way but also examines the response of the represented network in more than 50 different biological contexts and its enrichment for various biological terms and pathways, protein sequence signatures, and potential RNA regulatory elements. The interactome core of the database, as of Jan 23, 2017, contains 101,187 interactions among 13,395 trypanosomatid proteins inferred from 97 genome-wide and focused studies on the interactome of these organisms. PMID:28158179

Phospho-silicate and silicate layers modified by hydroxyapatite particles

NASA Astrophysics Data System (ADS)

Rokita, M.; Brożek, A.; Handke, M.

2005-06-01

Common used metal materials do not ensure good connection between an implant and biological neighbourhood. Covering implants by thin silicate or phosphate layers enable to improve biological properties of implants and create conditions for producing the non-concrete bonding between the implant and tissue. The project includes preparing silicate sols of different concentrations and proper (powder) fraction of synthetic as well as natural ox hydroxyapatite, depositing the sol mixed with hydroxyapatite onto the base material (metal, ceramic carbon) and heat treatment. Our work includes also preparation of phospho-silicate layers deposited onto different base materials using sol-gel method. Deposited sols were prepared regarding composition, concentration and layer heat treatment conditions. The prepared layers are examined to determine their phase composition (XRD, IR spectroscopy methods), density and continuity (scanning microscopy with EDX methods). Biological activity of layers was evaluated by means of estimation of their corrosive resistance in synthetic body fluids ('in vitro' method) and of bone cells growth on the layers surface. Introducing hydroxyapatite to the layer sol should improve connection between tissue and implant as well as limit the disadvantageous, corrosive influence of implant material (metal) on the tissue.

Identifying novel glioma associated pathways based on systems biology level meta-analysis.

PubMed

Hu, Yangfan; Li, Jinquan; Yan, Wenying; Chen, Jiajia; Li, Yin; Hu, Guang; Shen, Bairong

2013-01-01

With recent advances in microarray technology, including genomics, proteomics, and metabolomics, it brings a great challenge for integrating this "-omics" data to analysis complex disease. Glioma is an extremely aggressive and lethal form of brain tumor, and thus the study of the molecule mechanism underlying glioma remains very important. To date, most studies focus on detecting the differentially expressed genes in glioma. However, the meta-analysis for pathway analysis based on multiple microarray datasets has not been systematically pursued. In this study, we therefore developed a systems biology based approach by integrating three types of omics data to identify common pathways in glioma. Firstly, the meta-analysis has been performed to study the overlapping of signatures at different levels based on the microarray gene expression data of glioma. Among these gene expression datasets, 12 pathways were found in GeneGO database that shared by four stages. Then, microRNA expression profiles and ChIP-seq data were integrated for the further pathway enrichment analysis. As a result, we suggest 5 of these pathways could be served as putative pathways in glioma. Among them, the pathway of TGF-beta-dependent induction of EMT via SMAD is of particular importance. Our results demonstrate that the meta-analysis based on systems biology level provide a more useful approach to study the molecule mechanism of complex disease. The integration of different types of omics data, including gene expression microarrays, microRNA and ChIP-seq data, suggest some common pathways correlated with glioma. These findings will offer useful potential candidates for targeted therapeutic intervention of glioma.

Classification of Complete Proteomes of Different Organisms and Protein Sets Based on Their Protein Distributions in Terms of Some Key Attributes of Proteins

PubMed Central

Ma, Yue; Tuskan, Gerald A.

2018-01-01

The existence of complete genome sequences makes it important to develop different approaches for classification of large-scale data sets and to make extraction of biological insights easier. Here, we propose an approach for classification of complete proteomes/protein sets based on protein distributions on some basic attributes. We demonstrate the usefulness of this approach by determining protein distributions in terms of two attributes: protein lengths and protein intrinsic disorder contents (ID). The protein distributions based on L and ID are surveyed for representative proteome organisms and protein sets from the three domains of life. The two-dimensional maps (designated as fingerprints here) from the protein distribution densities in the LD space defined by ln(L) and ID are then constructed. The fingerprints for different organisms and protein sets are found to be distinct with each other, and they can therefore be used for comparative studies. As a test case, phylogenetic trees have been constructed based on the protein distribution densities in the fingerprints of proteomes of organisms without performing any protein sequence comparison and alignments. The phylogenetic trees generated are biologically meaningful, demonstrating that the protein distributions in the LD space may serve as unique phylogenetic signals of the organisms at the proteome level. PMID:29686995

Construction of an ortholog database using the semantic web technology for integrative analysis of genomic data.

PubMed

Chiba, Hirokazu; Nishide, Hiroyo; Uchiyama, Ikuo

2015-01-01

Recently, various types of biological data, including genomic sequences, have been rapidly accumulating. To discover biological knowledge from such growing heterogeneous data, a flexible framework for data integration is necessary. Ortholog information is a central resource for interlinking corresponding genes among different organisms, and the Semantic Web provides a key technology for the flexible integration of heterogeneous data. We have constructed an ortholog database using the Semantic Web technology, aiming at the integration of numerous genomic data and various types of biological information. To formalize the structure of the ortholog information in the Semantic Web, we have constructed the Ortholog Ontology (OrthO). While the OrthO is a compact ontology for general use, it is designed to be extended to the description of database-specific concepts. On the basis of OrthO, we described the ortholog information from our Microbial Genome Database for Comparative Analysis (MBGD) in the form of Resource Description Framework (RDF) and made it available through the SPARQL endpoint, which accepts arbitrary queries specified by users. In this framework based on the OrthO, the biological data of different organisms can be integrated using the ortholog information as a hub. Besides, the ortholog information from different data sources can be compared with each other using the OrthO as a shared ontology. Here we show some examples demonstrating that the ortholog information described in RDF can be used to link various biological data such as taxonomy information and Gene Ontology. Thus, the ortholog database using the Semantic Web technology can contribute to biological knowledge discovery through integrative data analysis.

Plasma pharmacy - physical plasma in pharmaceutical applications.

PubMed

von Woedtke, Th; Haertel, B; Weltmann, K-D; Lindequist, U

2013-07-01

During the last years the use of physical plasma for medical applications has grown rapidly. A multitude of findings about plasma-cell and plasma-tissue interactions and its possible use in therapy have been provided. One of the key findings of plasma medical basic research is that several biological effects do not result from direct plasma-cell or plasma-tissue interaction but are mediated by liquids. Above all, it was demonstrated that simple liquids like water or physiological saline, are antimicrobially active after treatment by atmospheric pressure plasma and that these effects are attributable to the generation of different low-molecular reactive species. Besides, it could be shown that plasma treatment leads to the stimulation of specific aspects of cell metabolism and to a transient and reversible increase of diffusion properties of biological barriers. All these results gave rise to think about another new and innovative field of medical plasma application. In contrast to plasma medicine, which means the direct use of plasmas on or in the living organism for direct therapeutic purposes, this field - as a specific field of medical plasma application - is called plasma pharmacy. Based on the present state of knowledge, most promising application fields of plasma pharmacy might be: plasma-based generation of biologically active liquids; plasma-based preparation, optimization, or stabilization of - mainly liquid - pharmaceutical preparations; support of drug transport across biological barriers; plasma-based stimulation of biotechnological processes.

Functional annotation of the vlinc class of non-coding RNAs using systems biology approach.

PubMed

St Laurent, Georges; Vyatkin, Yuri; Antonets, Denis; Ri, Maxim; Qi, Yao; Saik, Olga; Shtokalo, Dmitry; de Hoon, Michiel J L; Kawaji, Hideya; Itoh, Masayoshi; Lassmann, Timo; Arner, Erik; Forrest, Alistair R R; Nicolas, Estelle; McCaffrey, Timothy A; Carninci, Piero; Hayashizaki, Yoshihide; Wahlestedt, Claes; Kapranov, Philipp

2016-04-20

Functionality of the non-coding transcripts encoded by the human genome is the coveted goal of the modern genomics research. While commonly relied on the classical methods of forward genetics, integration of different genomics datasets in a global Systems Biology fashion presents a more productive avenue of achieving this very complex aim. Here we report application of a Systems Biology-based approach to dissect functionality of a newly identified vast class of very long intergenic non-coding (vlinc) RNAs. Using highly quantitative FANTOM5 CAGE dataset, we show that these RNAs could be grouped into 1542 novel human genes based on analysis of insulators that we show here indeed function as genomic barrier elements. We show that vlinc RNAs genes likely function in cisto activate nearby genes. This effect while most pronounced in closely spaced vlinc RNA-gene pairs can be detected over relatively large genomic distances. Furthermore, we identified 101 vlinc RNA genes likely involved in early embryogenesis based on patterns of their expression and regulation. We also found another 109 such genes potentially involved in cellular functions also happening at early stages of development such as proliferation, migration and apoptosis. Overall, we show that Systems Biology-based methods have great promise for functional annotation of non-coding RNAs. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

Structure-Based Design and Synthesis of Harmine Derivatives with Different Selectivity Profiles in Kinase versus Monoamine Oxidase Inhibition.

PubMed

Bálint, Balázs; Wéber, Csaba; Cruzalegui, Francisco; Burbridge, Mike; Kotschy, Andras

2017-06-21

Dual-specificity tyrosine-phosphorylation-regulated kinase 1A (DYRK1A) is an emerging biological target with implications in diverse therapeutic areas such as neurological disorders (Down syndrome, in particular), metabolism, and oncology. Harmine, a natural product that selectively inhibits DYRK1A amongst kinases, could serve as a tool compound to better understand the biological processes that arise from DYRK1A inhibition. On the other hand, harmine is also a potent inhibitor of monoamine oxidase A (MAO-A). Using structure-based design, we synthesized a collection of harmine analogues with tunable selectivity toward these two enzymes. Modifications at the 7-position typically decreased affinity for DYRK1A, whereas substitution at the 9-position had a similar effect on MAO-A inhibition but DYRK1A inhibition was maintained. The resulting collection of compounds can help to understand the biological role of DYRK1A and also to assess the interference in the biological effect originating in MAO-A inhibition. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

How accelerated biological aging can affect solar reflective polymeric based building materials

NASA Astrophysics Data System (ADS)

Ferrari, C.; Santunione, G.; Libbra, A.; Muscio, A.; Sgarbi, E.

2017-11-01

Among the main issues concerning building materials, in particular outdoor ones, one can identify the colonization by microorganisms referred to as biological aggression. This can affect not only the aesthetical aspect but also the thermal performance of solar reflective materials. In order to improve the reliability of tests aimed to assess the resistance to biological aggression and contextually reduce the test duration, an accelerated test method has been developed. It is based on a lab reproducible setup where specific and controlled environmental and boundary conditions are imposed to accelerate as much as possible biological growth on building materials. Due to their widespread use, polymeric materials have been selected for the present analysis, in the aim of reaching an advanced bio-aged level in a relatively short time (8 weeks or less) and at the same time comparatively evaluate different materials under a given set of ageing conditions. Surface properties before, during and after ageing have been investigated by surface, microstructural and chemical analyses, as well as by examination of time progressive images to assess bacterial and algal growth rate.

Photo-Responsive Graphene and Carbon Nanotubes to Control and Tackle Biological Systems.

PubMed

Cardano, Francesca; Frasconi, Marco; Giordani, Silvia

2018-01-01

Photo-responsive multifunctional nanomaterials are receiving considerable attention for biological applications because of their unique properties. The functionalization of the surface of carbon nanotubes (CNTs) and graphene, among other carbon based nanomaterials, with molecular switches that exhibit reversible transformations between two or more isomers in response to different kind of external stimuli, such as electromagnetic radiation, temperature and pH, has allowed the control of the optical and electrical properties of the nanomaterial. Light-controlled molecular switches, such as azobenzene and spiropyran, have attracted a lot of attention for nanomaterial's functionalization because of the remote modulation of their physicochemical properties using light stimulus. The enhanced properties of the hybrid materials obtained from the coupling of carbon based nanomaterials with light-responsive switches has enabled the fabrication of smart devices for various biological applications, including drug delivery, bioimaging and nanobiosensors. In this review, we highlight the properties of photo-responsive carbon nanomaterials obtained by the conjugation of CNTs and graphene with azobenzenes and spiropyrans molecules to investigate biological systems, devising possible future directions in the field.

Using a biology-based model (DEBtox) to analyze bioassays in ecotoxicology: opportunities and recommendations.

PubMed

Péry, Alexandre R R; Flammarion, Patrick; Vollat, Bernard; Bedaux, Jacques J M; Kooijman, Sebastiaan A L M; Garric, Jeanne

2002-02-01

The conventional analysis of bioassays does not account for biological significance. However, mathematical models do exist that are realistic from a biological point of view and describe toxicokinetics and effects on test organisms of chemical compounds. Here we studied a biology-based model (DEBtox) that provides an estimate of a no-effect concentration, and we demonstrated the ability of such a model to adapt to different situations. We showed that the basic model can be extended to deal with problems usually faced during bioassays like time-varying concentrations or unsuitable choices of initial concentrations. To reach this goal, we report experimental data from Daphnia magna exposed to zinc. These data also showed the potential benefit of the model in understanding the influence of food on toxicity. We finally make some recommendations about the choice of initial concentrations, and we propose a test with a depuration period to check the relevance and the predictive capacity of the DEBtox model. In our experiments, the model performed well and proved its usefulness as a tool in risk assessment.

Photo-Responsive Graphene and Carbon Nanotubes to Control and Tackle Biological Systems

PubMed Central

Cardano, Francesca; Frasconi, Marco; Giordani, Silvia

2018-01-01

Photo-responsive multifunctional nanomaterials are receiving considerable attention for biological applications because of their unique properties. The functionalization of the surface of carbon nanotubes (CNTs) and graphene, among other carbon based nanomaterials, with molecular switches that exhibit reversible transformations between two or more isomers in response to different kind of external stimuli, such as electromagnetic radiation, temperature and pH, has allowed the control of the optical and electrical properties of the nanomaterial. Light-controlled molecular switches, such as azobenzene and spiropyran, have attracted a lot of attention for nanomaterial's functionalization because of the remote modulation of their physicochemical properties using light stimulus. The enhanced properties of the hybrid materials obtained from the coupling of carbon based nanomaterials with light-responsive switches has enabled the fabrication of smart devices for various biological applications, including drug delivery, bioimaging and nanobiosensors. In this review, we highlight the properties of photo-responsive carbon nanomaterials obtained by the conjugation of CNTs and graphene with azobenzenes and spiropyrans molecules to investigate biological systems, devising possible future directions in the field. PMID:29707534

Photo-Responsive Graphene and Carbon Nanotubes to Control and Tackle Biological Systems

NASA Astrophysics Data System (ADS)

Cardano, Francesca; Frasconi, Marco; Giordani, Silvia

2018-04-01

Photo-responsive multifunctional nanomaterials are receiving considerable attention for biological applications because of their unique properties. The functionalization of the surface of carbon nanotubes (CNTs) and graphene, among other carbon based nanomaterials, with molecular switches that exhibit reversible transformations between two or more isomers in response to different kind of external stimuli, such as electromagnetic radiation, temperature and pH, has allowed the control of the optical and electrical properties of the nanomaterial. Light-controlled molecular switches, such as azobenzene and spiropyran, have attracted a lot of attention for nanomaterial’s functionalization because of the remote modulation of their physicochemical properties using light stimulus. The enhanced properties of the hybrid materials obtained from the coupling of carbon based nanomaterials with light-responsive switches has enabled the fabrication of smart devices for various biological applications, including drug delivery, bioimaging and nanobiosensors. In this review, we highlight the properties of photo-responsive carbon nanomaterials obtained by the conjugation of CNTs and graphene with azobenzenes and spiropyrans molecules to investigate biological systems, devising possible future directions in the field.

Dynamic biological exposure indexes for n-hexane and 2,5-hexanedione, suggested by a physiologically based pharmacokinetic model

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

Perbellini, L.; Mozzo, P.; Olivato, D.

Biological exposure index (BEI) of n-hexane was studied for accuracy using a physiologically based pharmacokinetic (PB-PK) model. The kinetics of n-hexane in alveolar air, blood, urine, and other tissues were simulated for different values of alveolar ventilations and also for constant and variable exposures. The kinetics of 2,5-hexanedione, the toxic n-hexane metabolite, were also simulated. The ranges of n-hexane concentrations in biological media and the urinary concentrations of 2,5-hexanedione are discussed in connection with a mean n-hexane exposure of 180 mg/m3 (50 ppm) (threshold limit value (TLV) suggested by American Conference of Governmental Industrial Hygienists (ACGIH) for 1988-89). The experimentalmore » and field data as well as those predicted by simulation with the PB-PK model were comparable. The physiological-pharmacokinetic simulations are used to propose the dynamic BEIs of n-hexane and 2,5-hexanedione. The use of simulation with PB-PK models enables a better understanding of the limits, advantages, and issues associated with biological monitoring of exposures to industrial solvents.« less

Organizing Community-Based Data Standards: Lessons from Developing a Successful Open Standard in Systems Biology

NASA Astrophysics Data System (ADS)

Hucka, M.

2015-09-01

In common with many fields, including astronomy, a vast number of software tools for computational modeling and simulation are available today in systems biology. This wealth of resources is a boon to researchers, but it also presents interoperability problems. Despite working with different software tools, researchers want to disseminate their work widely as well as reuse and extend the models of other researchers. This situation led in the year 2000 to an effort to create a tool-independent, machine-readable file format for representing models: SBML, the Systems Biology Markup Language. SBML has since become the de facto standard for its purpose. Its success and general approach has inspired and influenced other community-oriented standardization efforts in systems biology. Open standards are essential for the progress of science in all fields, but it is often difficult for academic researchers to organize successful community-based standards. I draw on personal experiences from the development of SBML and summarize some of the lessons learned, in the hope that this may be useful to other groups seeking to develop open standards in a community-oriented fashion.

Differences in carbon source usage by dental plaque in children with and without early childhood caries

PubMed Central

Zhao, Yan; Zhong, Wen-Jie; Xun, Zhe; Zhang, Qian; Song, Ye-Qing; Liu, Yun-Song; Chen, Feng

2017-01-01

Early childhood caries (ECC) is a considerable pediatric and public health problem worldwide. Preceding studies have focused primarily on bacterial diversity at the taxonomic level. Although these studies have provided significant information regarding the connection between dental caries and oral microbiomes, further comprehension of this microbial community’s ecological relevance is limited. This study identified the carbon source metabolic differences in dental plaque between children with and without ECC. We compared the microbial community functional diversity in 18 caries-free subjects with 18 severe ECC patients based on sole carbon source usage using a Biolog assay. The anaerobic microbial community in the ECC patients displayed greater metabolic activity than that of the control group. Specific carbon source metabolism differed significantly between the two groups. Subjects from the two groups were well distinguished by cluster and principal component analyses based on discriminative carbon sources. Our results implied that the microbial functional diversity between the ECC patients and healthy subjects differed significantly. In addition, the Biolog assay furthered our understanding of oral microbiomes as a composite of functional abilities, thus enabling us to identify the ecologically relevant functional differences among oral microbial communities.

Developmental Origins of Biological Explanations: The case of infants' internal property bias.

PubMed

Taborda-Osorio, Hernando; Cheries, Erik W

2017-10-01

People's explanations about the biological world are heavily biased toward internal, non-obvious properties. Adults and children as young as 5 years of age find internal properties more causally central than external features for explaining general biological processes and category membership. In this paper, we describe how this 'internal property bias' may be grounded in two different developmental precursors observed in studies with infants: (1) an early understanding of biological agency that is apparent in infants' reasoning about animals, and (2) the acquisition of kind-based representations that distinguish between essential and accidental properties, spanning from animals to artifacts. We argue that these precursors may support the progressive construction of the notion of biological kinds and explanations during childhood. Shortly after their first year of life, infants seem to represent the internal properties of animates as more central and identity-determining that external properties. Over time, this skeletal notion of biological kinds is integrated into diverse explanations about kind membership and biological processes, with an increasingly better understanding of the causal role of internal properties.

Unexpected Levels of Biological Activity during the Polar Night Offer New Perspectives on a Warming Arctic.

PubMed

Berge, Jørgen; Daase, Malin; Renaud, Paul E; Ambrose, William G; Darnis, Gerald; Last, Kim S; Leu, Eva; Cohen, Jonathan H; Johnsen, Geir; Moline, Mark A; Cottier, Finlo; Varpe, Øystein; Shunatova, Natalia; Bałazy, Piotr; Morata, Nathalie; Massabuau, Jean-Charles; Falk-Petersen, Stig; Kosobokova, Ksenia; Hoppe, Clara J M; Węsławski, Jan Marcin; Kukliński, Piotr; Legeżyńska, Joanna; Nikishina, Daria; Cusa, Marine; Kędra, Monika; Włodarska-Kowalczuk, Maria; Vogedes, Daniel; Camus, Lionel; Tran, Damien; Michaud, Emma; Gabrielsen, Tove M; Granovitch, Andrei; Gonchar, Anya; Krapp, Rupert; Callesen, Trine A

2015-10-05

The current understanding of Arctic ecosystems is deeply rooted in the classical view of a bottom-up controlled system with strong physical forcing and seasonality in primary-production regimes. Consequently, the Arctic polar night is commonly disregarded as a time of year when biological activities are reduced to a minimum due to a reduced food supply. Here, based upon a multidisciplinary ecosystem-scale study from the polar night at 79°N, we present an entirely different view. Instead of an ecosystem that has entered a resting state, we document a system with high activity levels and biological interactions across most trophic levels. In some habitats, biological diversity and presence of juvenile stages were elevated in winter months compared to the more productive and sunlit periods. Ultimately, our results suggest a different perspective regarding ecosystem function that will be of importance for future environmental management and decision making, especially at a time when Arctic regions are experiencing accelerated environmental change [1]. Copyright © 2015 Elsevier Ltd. All rights reserved.

Supporting read-across using biological data.

PubMed

Zhu, Hao; Bouhifd, Mounir; Donley, Elizabeth; Egnash, Laura; Kleinstreuer, Nicole; Kroese, E Dinant; Liu, Zhichao; Luechtefeld, Thomas; Palmer, Jessica; Pamies, David; Shen, Jie; Strauss, Volker; Wu, Shengde; Hartung, Thomas

2016-01-01

Read-across, i.e. filling toxicological data gaps by relating to similar chemicals, for which test data are available, is usually done based on chemical similarity. Besides structure and physico-chemical properties, however, biological similarity based on biological data adds extra strength to this process. In the context of developing Good Read-Across Practice guidance, a number of case studies were evaluated to demonstrate the use of biological data to enrich read-across. In the simplest case, chemically similar substances also show similar test results in relevant in vitro assays. This is a well-established method for the read-across of e.g. genotoxicity assays. Larger datasets of biological and toxicological properties of hundreds and thousands of substances become increasingly available enabling big data approaches in read-across studies. Several case studies using various big data sources are described in this paper. An example is given for the US EPA's ToxCast dataset allowing read-across for high quality uterotrophic assays for estrogenic endocrine disruption. Similarly, an example for REACH registration data enhancing read-across for acute toxicity studies is given. A different approach is taken using omics data to establish biological similarity: Examples are given for stem cell models in vitro and short-term repeated dose studies in rats in vivo to support read-across and category formation. These preliminary biological data-driven read-across studies highlight the road to the new generation of read-across approaches that can be applied in chemical safety assessment.

Introducing Mammalian Cell Culture and Cell Viability Techniques in the Undergraduate Biology Laboratory.

PubMed

Bowey-Dellinger, Kristen; Dixon, Luke; Ackerman, Kristin; Vigueira, Cynthia; Suh, Yewseok K; Lyda, Todd; Sapp, Kelli; Grider, Michael; Crater, Dinene; Russell, Travis; Elias, Michael; Coffield, V McNeil; Segarra, Verónica A

2017-01-01

Undergraduate students learn about mammalian cell culture applications in introductory biology courses. However, laboratory modules are rarely designed to provide hands-on experience with mammalian cells or teach cell culture techniques, such as trypsinization and cell counting. Students are more likely to learn about cell culture using bacteria or yeast, as they are typically easier to grow, culture, and manipulate given the equipment, tools, and environment of most undergraduate biology laboratories. In contrast, the utilization of mammalian cells requires a dedicated biological safety cabinet and rigorous antiseptic techniques. For this reason, we have devised a laboratory module and method herein that familiarizes students with common cell culture procedures, without the use of a sterile hood or large cell culture facility. Students design and perform a time-efficient inquiry-based cell viability experiment using HeLa cells and tools that are readily available in an undergraduate biology laboratory. Students will become familiar with common techniques such as trypsinizing cells, cell counting with a hemocytometer, performing serial dilutions, and determining cell viability using trypan blue dye. Additionally, students will work with graphing software to analyze their data and think critically about the mechanism of death on a cellular level. Two different adaptations of this inquiry-based lab are presented-one for non-biology majors and one for biology majors. Overall, these laboratories aim to expose students to mammalian cell culture and basic techniques and help them to conceptualize their application in scientific research.

Introducing Mammalian Cell Culture and Cell Viability Techniques in the Undergraduate Biology Laboratory †

PubMed Central

Bowey-Dellinger, Kristen; Dixon, Luke; Ackerman, Kristin; Vigueira, Cynthia; Suh, Yewseok K.; Lyda, Todd; Sapp, Kelli; Grider, Michael; Crater, Dinene; Russell, Travis; Elias, Michael; Coffield, V. McNeil; Segarra, Verónica A.

2017-01-01

Undergraduate students learn about mammalian cell culture applications in introductory biology courses. However, laboratory modules are rarely designed to provide hands-on experience with mammalian cells or teach cell culture techniques, such as trypsinization and cell counting. Students are more likely to learn about cell culture using bacteria or yeast, as they are typically easier to grow, culture, and manipulate given the equipment, tools, and environment of most undergraduate biology laboratories. In contrast, the utilization of mammalian cells requires a dedicated biological safety cabinet and rigorous antiseptic techniques. For this reason, we have devised a laboratory module and method herein that familiarizes students with common cell culture procedures, without the use of a sterile hood or large cell culture facility. Students design and perform a time-efficient inquiry-based cell viability experiment using HeLa cells and tools that are readily available in an undergraduate biology laboratory. Students will become familiar with common techniques such as trypsinizing cells, cell counting with a hemocytometer, performing serial dilutions, and determining cell viability using trypan blue dye. Additionally, students will work with graphing software to analyze their data and think critically about the mechanism of death on a cellular level. Two different adaptations of this inquiry-based lab are presented—one for non-biology majors and one for biology majors. Overall, these laboratories aim to expose students to mammalian cell culture and basic techniques and help them to conceptualize their application in scientific research. PMID:28861134

Gender gaps in achievement and participation in multiple introductory biology classrooms.

PubMed

Eddy, Sarah L; Brownell, Sara E; Wenderoth, Mary Pat

2014-01-01

Although gender gaps have been a major concern in male-dominated science, technology, engineering, and mathematics disciplines such as physics and engineering, the numerical dominance of female students in biology has supported the assumption that gender disparities do not exist at the undergraduate level in life sciences. Using data from 23 large introductory biology classes for majors, we examine two measures of gender disparity in biology: academic achievement and participation in whole-class discussions. We found that females consistently underperform on exams compared with males with similar overall college grade point averages. In addition, although females on average represent 60% of the students in these courses, their voices make up less than 40% of those heard responding to instructor-posed questions to the class, one of the most common ways of engaging students in large lectures. Based on these data, we propose that, despite numerical dominance of females, gender disparities remain an issue in introductory biology classrooms. For student retention and achievement in biology to be truly merit based, we need to develop strategies to equalize the opportunities for students of different genders to practice the skills they need to excel. © 2014 S. L. Eddy et al. CBE—Life Sciences Education © 2014 The American Society for Cell Biology. This article is distributed by The American Society for Cell Biology under license from the author(s). It is available to the public under an Attribution–Noncommercial–Share Alike 3.0 Unported Creative Commons License (http://creativecommons.org/licenses/by-nc-sa/3.0).

Why proteomics is not the new genomics and the future of mass spectrometry in cell biology.

PubMed

Sidoli, Simone; Kulej, Katarzyna; Garcia, Benjamin A

2017-01-02

Mass spectrometry (MS) is an essential part of the cell biologist's proteomics toolkit, allowing analyses at molecular and system-wide scales. However, proteomics still lag behind genomics in popularity and ease of use. We discuss key differences between MS-based -omics and other booming -omics technologies and highlight what we view as the future of MS and its role in our increasingly deep understanding of cell biology. © 2017 Sidoli et al.

Surface Enhanced Raman Scattering (SERS)-Based Next Generation Commercially Available Substrate: Physical Characterization and Biological Application

DTIC Science & Technology

2011-09-01

the spore and the active areas on the Klarite surface. For these experiments an aliquot of the common bacillus spore B. coagulans was drop...suspension B. coagulans (ATCC SUS-CG) was purchased from Raven Biologicals and used at a log 4 or 6 population per 0.1 mL of solution. For experiments...Klarite substrates were evaluated with the spore sample B. coagulans . In these experiments different substrates and the changes in overall band

Molecular Diversity by Olefin Cross-Metathesis on Solid Support. Generation of Libraries of Biologically Promising β-Lactam Derivatives.

PubMed

Méndez, Luciana; Poeylaut-Palena, Andrés A; Mata, Ernesto G

2018-05-16

The application of the reagent-based diversification strategy for generation of libraries of biologically promising β-lactam derivatives is described. Key features are the versatility of the linker used and the cross-metathesis functionalization at the cleavage step. From an immobilized primary library, diversity was expanded by applying different cleavage conditions, leading to a series of cholesterol absorption inhibitor analogues together with interesting hybrid compounds through incorporation of a chalcone moiety.

Silicon nanoparticles: applications in cell biology and medicine

PubMed Central

O’Farrell, Norah; Houlton, Andrew; Horrocks, Benjamin R

2006-01-01

In this review, we describe the synthesis, physical properties, surface functionalization, and biological applications of silicon nanoparticles (also known as quantum dots). We compare them against current technologies, such as fluorescent organic dyes and heavy metal chalcogenide-based quantum dots. In particular, we examine the many different methods that can be used to both create and modify these nanoparticles and the advantages they may have over current technologies that have stimulated research into designing silicon nanoparticles for in vitro and in vivo applications. PMID:17722279

Construction of Biologically Functional Bacterial Plasmids In Vitro

PubMed Central

Cohen, Stanley N.; Chang, Annie C. Y.; Boyer, Herbert W.; Helling, Robert B.

1973-01-01

The construction of new plasmid DNA species by in vitro joining of restriction endonuclease-generated fragments of separate plasmids is described. Newly constructed plasmids that are inserted into Escherichia coli by transformation are shown to be biologically functional replicons that possess genetic properties and nucleotide base sequences from both of the parent DNA molecules. Functional plasmids can be obtained by reassociation of endonuclease-generated fragments of larger replicons, as well as by joining of plasmid DNA molecules of entirely different origins. Images PMID:4594039

Developing an online programme in computational biology.

PubMed

Vincent, Heather M; Page, Christopher

2013-11-01

Much has been written about the need for continuing education and training to enable life scientists and computer scientists to manage and exploit the different types of biological data now becoming available. Here we describe the development of an online programme that combines short training courses, so that those who require an educational programme can progress to complete a formal qualification. Although this flexible approach fits the needs of course participants, it does not fit easily within the organizational structures of a campus-based university.

Enzymatic control of biological deposits in papermaking.

PubMed

Hatcher, H J

1984-01-01

Deposit control in the pulp and paper industry has traditionally been accomplished by the use of toxic biocides. A method has been found whereby biological deposits can be controlled by the use of an enzyme-based product. Numerous field studies have been conducted successfully and photographs prepared illustrating the process. The dynamics of deposit formation and problems associated with such formations have been the subject of considerable study. Development and control of deposit problems under different paper mill conditions using the chemical-biochemical approach will be discussed.

Unity and disunity in evolutionary sciences: process-based analogies open common research avenues for biology and linguistics.

PubMed

List, Johann-Mattis; Pathmanathan, Jananan Sylvestre; Lopez, Philippe; Bapteste, Eric

2016-08-20

For a long time biologists and linguists have been noticing surprising similarities between the evolution of life forms and languages. Most of the proposed analogies have been rejected. Some, however, have persisted, and some even turned out to be fruitful, inspiring the transfer of methods and models between biology and linguistics up to today. Most proposed analogies were based on a comparison of the research objects rather than the processes that shaped their evolution. Focusing on process-based analogies, however, has the advantage of minimizing the risk of overstating similarities, while at the same time reflecting the common strategy to use processes to explain the evolution of complexity in both fields. We compared important evolutionary processes in biology and linguistics and identified processes specific to only one of the two disciplines as well as processes which seem to be analogous, potentially reflecting core evolutionary processes. These new process-based analogies support novel methodological transfer, expanding the application range of biological methods to the field of historical linguistics. We illustrate this by showing (i) how methods dealing with incomplete lineage sorting offer an introgression-free framework to analyze highly mosaic word distributions across languages; (ii) how sequence similarity networks can be used to identify composite and borrowed words across different languages; (iii) how research on partial homology can inspire new methods and models in both fields; and (iv) how constructive neutral evolution provides an original framework for analyzing convergent evolution in languages resulting from common descent (Sapir's drift). Apart from new analogies between evolutionary processes, we also identified processes which are specific to either biology or linguistics. This shows that general evolution cannot be studied from within one discipline alone. In order to get a full picture of evolution, biologists and linguists need to complement their studies, trying to identify cross-disciplinary and discipline-specific evolutionary processes. The fact that we found many process-based analogies favoring transfer from biology to linguistics further shows that certain biological methods and models have a broader scope than previously recognized. This opens fruitful paths for collaboration between the two disciplines. This article was reviewed by W. Ford Doolittle and Eugene V. Koonin.

Cardiac Muscle-cell Based Actuator and Self-stabilizing Biorobot - PART 1.

PubMed

Holley, Merrel T; Nagarajan, Neerajha; Danielson, Christian; Zorlutuna, Pinar; Park, Kidong

2017-07-11

Biological machines often referred to as biorobots, are living cell- or tissue-based devices that are powered solely by the contractile activity of living components. Due to their inherent advantages, biorobots are gaining interest as alternatives to traditional fully artificial robots. Various studies have focused on harnessing the power of biological actuators, but only recently studies have quantitatively characterized the performance of biorobots and studied their geometry to enhance functionality and efficiency. Here, we demonstrate the development of a self-stabilizing swimming biorobot that can maintain its pitch, depth, and roll without external intervention. The design and fabrication of the PDMS scaffold for the biological actuator and biorobot followed by the functionalization with fibronectin is described in this first part. In the second part of this two-part article, we detail the incorporation of cardiomyocytes and characterize the biological actuator and biorobot function. Both incorporate a base and tail (cantilever) which produce fin-based propulsion. The tail is constructed with soft lithography techniques using PDMS and laser engraving. After incorporating the tail with the device base, it is functionalized with a cell adhesive protein and seeded confluently with cardiomyocytes. The base of the biological actuator consists of a solid PDMS block with a central glass bead (acts as a weight). The base of the biorobot consists of two composite PDMS materials, Ni-PDMS and microballoon-PDMS (MB-PDMS). The nickel powder (in Ni-PDMS) allows magnetic control of the biorobot during cells seeding and stability during locomotion. Microballoons (in MB-PDMS) decrease the density of MB-PDMS, and enable the biorobot to float and swim steadily. The use of these two materials with different mass densities, enabled precise control over the weight distribution to ensure a positive restoration force at any angle of the biorobot. This technique produces a magnetically controlled self-stabilizing swimming biorobot.

Economic benefits of optimizing anchor therapy for rheumatoid arthritis.

PubMed

Fautrel, Bruno

2012-06-01

The total cost of RA is substantial, particularly in patients with high levels of disability. There are considerable differences in cost between countries, driven in part by differences in the use of biologic therapies. Economic evaluations are needed to assess the extra cost of using these treatments and the benefits obtained, to ensure appropriate allocation of limited health care resources. The BeSt trial, evaluating four treatment strategies, found comparable medium-term efficacy but substantially higher costs with early biologic therapy. A systematic review of such cost-effectiveness analyses concluded that biologic therapy should be used after therapy has failed with less costly alternatives such as synthetic DMARDs and glucocorticoids. Optimizing such relatively low-cost therapy to improve outcomes may delay the need for biologic therapy, thereby saving costs. A simple model has confirmed the value of this approach. The addition of modified-release prednisone 5 mg/day to existing synthetic DMARD therapy in patients with active disease resulted in improvement in DAS-28 to below the threshold level for initiation of reimbursed biologic therapy in 28-34% of patients. On a conservative estimate (i.e. assuming no further benefits beyond the 12 weeks of the study and a 12-week wait-and-see approach to starting biologic therapy), cost savings amounted to nearly € 400 per patient. While treatment decisions should never be based only on cost considerations, prolonging disease control by optimizing the use of non-biologic treatments may bring benefits to patients and also economic benefits by delaying the need for biologic treatments.

Teaching Statistics in Biology: Using Inquiry-based Learning to Strengthen Understanding of Statistical Analysis in Biology Laboratory Courses

PubMed Central

2008-01-01

There is an increasing need for students in the biological sciences to build a strong foundation in quantitative approaches to data analyses. Although most science, engineering, and math field majors are required to take at least one statistics course, statistical analysis is poorly integrated into undergraduate biology course work, particularly at the lower-division level. Elements of statistics were incorporated into an introductory biology course, including a review of statistics concepts and opportunity for students to perform statistical analysis in a biological context. Learning gains were measured with an 11-item statistics learning survey instrument developed for the course. Students showed a statistically significant 25% (p < 0.005) increase in statistics knowledge after completing introductory biology. Students improved their scores on the survey after completing introductory biology, even if they had previously completed an introductory statistics course (9%, improvement p < 0.005). Students retested 1 yr after completing introductory biology showed no loss of their statistics knowledge as measured by this instrument, suggesting that the use of statistics in biology course work may aid long-term retention of statistics knowledge. No statistically significant differences in learning were detected between male and female students in the study. PMID:18765754

Characterizing gene sets using discriminative random walks with restart on heterogeneous biological networks.

PubMed

Blatti, Charles; Sinha, Saurabh

2016-07-15

Analysis of co-expressed gene sets typically involves testing for enrichment of different annotations or 'properties' such as biological processes, pathways, transcription factor binding sites, etc., one property at a time. This common approach ignores any known relationships among the properties or the genes themselves. It is believed that known biological relationships among genes and their many properties may be exploited to more accurately reveal commonalities of a gene set. Previous work has sought to achieve this by building biological networks that combine multiple types of gene-gene or gene-property relationships, and performing network analysis to identify other genes and properties most relevant to a given gene set. Most existing network-based approaches for recognizing genes or annotations relevant to a given gene set collapse information about different properties to simplify (homogenize) the networks. We present a network-based method for ranking genes or properties related to a given gene set. Such related genes or properties are identified from among the nodes of a large, heterogeneous network of biological information. Our method involves a random walk with restarts, performed on an initial network with multiple node and edge types that preserve more of the original, specific property information than current methods that operate on homogeneous networks. In this first stage of our algorithm, we find the properties that are the most relevant to the given gene set and extract a subnetwork of the original network, comprising only these relevant properties. We then re-rank genes by their similarity to the given gene set, based on a second random walk with restarts, performed on the above subnetwork. We demonstrate the effectiveness of this algorithm for ranking genes related to Drosophila embryonic development and aggressive responses in the brains of social animals. DRaWR was implemented as an R package available at veda.cs.illinois.edu/DRaWR. blatti@illinois.edu Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press.

Concepts of Mental Disorders in Trainee Clinical Psychologists.

PubMed

Read, R; Moberly, N J; Salter, D; Broome, M R

2017-03-01

The models of mental disorders held by all mental health professionals are implicit in their attitudes and inform all aspects of theory and practice. The present study aims to explore the attitudes of trainee clinical psychologists towards mental disorders by building on a study conducted by Harland et al. () with psychiatrists. In so doing, the present study contributes to an evidence base that can inform the development of clinical training programs and multidisciplinary working. The Maudsley Attitude Questionnaire was administered in an online survey of trainee clinical psychologists (n = 289). Analyses of variance revealed main effects of model, and of diagnostic category, and a significant interaction effect between model and diagnostic category. Principal component analysis revealed a biological-psychosocial continuum and cognitive/behavioural and psychodynamic/spiritual dimensions. Comparisons with Harland et al.'s () psychiatrists revealed large differences, particularly in biological and social constructionist model endorsement. Results suggest that the attitudes of psychologists and psychiatrists continue to sit at opposite ends of a biological-psychosocial continuum. However, an area of consensus regarding psychotherapeutic models was indicated. Training courses can be reassured that strong opinions tended to reflect the evidence base. Future research with similarly large representative samples from different disciplines would allow findings of the current study to be better contextualized. Copyright © 2016 John Wiley & Sons, Ltd. The models of mental disorders held by clinical psychologists are implicit in their attitudes and inform all aspects of theory and practice. We found that trainee clinical psychologists continue to favour psychosocial over biological understandings of mental disorders, giving the cognitive, behavioural and psychodynamic models equal value overall, and stronger attitudes were supported by the evidence base. We found that trainee clinical psychologists organized their attitudes around a biological-psychosocial continuum and cognitive/behavioural and psychodynamic/spiritual dimensions. These findings may be useful for those involved in developing clinical training programs and multidisciplinary working because they provide an insight into the attitudes of emerging clinical psychologists. Copyright © 2016 John Wiley & Sons, Ltd.

Hemodynamic Evaluation of a Biological and Mechanical Aortic Valve Prosthesis Using Patient-Specific MRI-Based CFD.

PubMed

Hellmeier, Florian; Nordmeyer, Sarah; Yevtushenko, Pavlo; Bruening, Jan; Berger, Felix; Kuehne, Titus; Goubergrits, Leonid; Kelm, Marcus

2018-01-01

Modeling different treatment options before a procedure is performed is a promising approach for surgical decision making and patient care in heart valve disease. This study investigated the hemodynamic impact of different prostheses through patient-specific MRI-based CFD simulations. Ten time-resolved MRI data sets with and without velocity encoding were obtained to reconstruct the aorta and set hemodynamic boundary conditions for simulations. Aortic hemodynamics after virtual valve replacement with a biological and mechanical valve prosthesis were investigated. Wall shear stress (WSS), secondary flow degree (SFD), transvalvular pressure drop (TPD), turbulent kinetic energy (TKE), and normalized flow displacement (NFD) were evaluated to characterize valve-induced hemodynamics. The biological prostheses induced significantly higher WSS (medians: 9.3 vs. 8.6 Pa, P = 0.027) and SFD (means: 0.78 vs. 0.49, P = 0.002) in the ascending aorta, TPD (medians: 11.4 vs. 2.7 mm Hg, P = 0.002), TKE (means: 400 vs. 283 cm 2 /s 2 , P = 0.037), and NFD (means: 0.0994 vs. 0.0607, P = 0.020) than the mechanical prostheses. The differences between the prosthesis types showed great inter-patient variability, however. Given this variability, a patient-specific evaluation is warranted. In conclusion, MRI-based CFD offers an opportunity to assess the interactions between prosthesis and patient-specific boundary conditions, which may help in optimizing surgical decision making and providing additional guidance to clinicians. © 2017 International Center for Artificial Organs and Transplantation and Wiley Periodicals, Inc.

Predicting the biological condition of streams: Use of geospatial indicators of natural and anthropogenic characteristics of watersheds

USGS Publications Warehouse

Carlisle, D.M.; Falcone, J.; Meador, M.R.

2009-01-01

We developed and evaluated empirical models to predict biological condition of wadeable streams in a large portion of the eastern USA, with the ultimate goal of prediction for unsampled basins. Previous work had classified (i.e., altered vs. unaltered) the biological condition of 920 streams based on a biological assessment of macroinvertebrate assemblages. Predictor variables were limited to widely available geospatial data, which included land cover, topography, climate, soils, societal infrastructure, and potential hydrologic modification. We compared the accuracy of predictions of biological condition class based on models with continuous and binary responses. We also evaluated the relative importance of specific groups and individual predictor variables, as well as the relationships between the most important predictors and biological condition. Prediction accuracy and the relative importance of predictor variables were different for two subregions for which models were created. Predictive accuracy in the highlands region improved by including predictors that represented both natural and human activities. Riparian land cover and road-stream intersections were the most important predictors. In contrast, predictive accuracy in the lowlands region was best for models limited to predictors representing natural factors, including basin topography and soil properties. Partial dependence plots revealed complex and nonlinear relationships between specific predictors and the probability of biological alteration. We demonstrate a potential application of the model by predicting biological condition in 552 unsampled basins across an ecoregion in southeastern Wisconsin (USA). Estimates of the likelihood of biological condition of unsampled streams could be a valuable tool for screening large numbers of basins to focus targeted monitoring of potentially unaltered or altered stream segments. ?? Springer Science+Business Media B.V. 2008.

Identification of biological traits associated with differences in residual energy intake among lactating Holstein cows.

PubMed

Fischer, A; Delagarde, R; Faverdin, P

2018-05-01

Residual feed intake, which is usually used to estimate individual variation of feed efficiency, requires frequent and accurate measurements of individual feed intake to be carried out. Developing a breeding scheme based on residual feed intake in dairy cows is therefore complicated, especially because feed intake is not measurable for a large population. Another solution could be to focus on biological determinants of feed efficiency, which could potentially be directly and broadband measurable on farm. Several phenotypes have been identified in literature as being associated with differences in feed efficiency. The present study therefore aims to identify which biological mechanisms are associated with residual energy intake (REI) differences among dairy cows. Several candidate phenotypes were recorded frequently and simultaneously throughout the first 238 d in milk for 60 Holstein cows fed on a constant diet based on maize silage. A multiple linear regression of the 238 d in milk average of net energy intake was fitted on the 238 d in milk averages for milk energy output, metabolic body weight, the sum over the 238 d in milk of both, body condition score loss and gain, and the residuals were defined as REI. A partial least square regression was fitted over all biological traits to explain REI variability. Linear multiple regression explained 93.6% of net energy intake phenotypic variation, with 65.5% associated with lactation requirement, 23.2% with maintenance, and 4.9% with body reserves change; the 6.4% residuals represented REI. Overall, measured biological traits contributed to 58.9% of REI phenotypic variability, which were mainly explained by activity (26.5%) and feeding behavior (21.3%). However, apparent confounding was observed between behavior, activity, digestibility, and rumen-temperature variables. Drawing a conclusion on biological traits that explain feed efficiency differences among dairy cows was not possible due to this apparent confounding between the measured variables. Further investigation is needed to validate these results and to characterize the causal relationship of feed efficiency with feeding behavior, digestibility, body reserves change, activity, and rumen temperature. The Authors. Published by FASS Inc. and Elsevier Inc. on behalf of the American Dairy Science Association®. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/3.0/).

Mechanisms of Sex Differences in Fear and Posttraumatic Stress Disorder.

PubMed

Ramikie, Teniel Sonya; Ressler, Kerry J

2018-05-15

Following sexual maturity, females disproportionately have higher rates of posttraumatic stress disorder (PTSD) and experience greater symptom severity and chronicity as compared with males. This observation has led many to examine sex differences in PTSD risk factors. Though relatively few, these studies reveal that the root causes of PTSD sex differences are complex, and partly represent interactions between sex-specific nonbiological and biological risk factors, which differentially shape PTSD vulnerability. Moreover, these studies suggest that sex-specific PTSD vulnerability is partly regulated by sex differences in fear systems. Fear, which represents a highly conserved adaptive response to threatening environmental stimuli, becomes pathological in trauma- and stress-based psychiatric syndromes, such as PTSD. Over the last 30 years, considerable progress has been made in understanding normal and pathological molecular and behavioral fear processes in humans and animal models. Thus, fear mechanisms represent a tractable PTSD biomarker in the study of sex differences in fear. In this review, we discuss studies that examine nonbiological and biological sex differences that contribute to normal and pathological fear behaviors in humans and animal models. This, we hope, will shed greater light on the potential mechanisms that contribute to increased PTSD vulnerability in females. Copyright © 2017 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.

A hybrid biology course: Implications of merging Internet-enhanced and campus-based instructional modes

NASA Astrophysics Data System (ADS)

Clark, Sharron Ann

This is possibly the first study of a hybrid online biology course where WebCT internet-enhanced modes of instruction replaced conventional face-to-face (F2F) lecture materials, merging with collaborative inquiry-based on-campus laboratory instructional modes. Although not a true experiment, the design of this study included three independent cohorts, a pretest and three posttests, as described by Gay and Airasian (2000). This study reported differences in age, gender, number of prior online courses and pretest scores. Over time, persistence, achievement and computer self-efficacy differed in one hybrid online section (N = 31) and two F2F cohorts (N = 29 and 30). One F2F cohort used written test materials and the other used intranet-delivered materials to examine possible differences in groups using electronic assessment modes. In this study, community college students self-selecting into online hybrid and traditional versions of the same biology course did not have the same number of prior online courses, achievement or persistence rates as those self-selecting into F2F sections of the same course with the same laboratories and instructor. This study includes twenty pretest items selected from Instructor's Manual and Test Item File to Accompany: Inquiry into Life, 9th Edition (Schrock, 2000). This study produced 63 tables, 13 figures and 173 references.

Scoring clustering solutions by their biological relevance.

PubMed

Gat-Viks, I; Sharan, R; Shamir, R

2003-12-12

A central step in the analysis of gene expression data is the identification of groups of genes that exhibit similar expression patterns. Clustering gene expression data into homogeneous groups was shown to be instrumental in functional annotation, tissue classification, regulatory motif identification, and other applications. Although there is a rich literature on clustering algorithms for gene expression analysis, very few works addressed the systematic comparison and evaluation of clustering results. Typically, different clustering algorithms yield different clustering solutions on the same data, and there is no agreed upon guideline for choosing among them. We developed a novel statistically based method for assessing a clustering solution according to prior biological knowledge. Our method can be used to compare different clustering solutions or to optimize the parameters of a clustering algorithm. The method is based on projecting vectors of biological attributes of the clustered elements onto the real line, such that the ratio of between-groups and within-group variance estimators is maximized. The projected data are then scored using a non-parametric analysis of variance test, and the score's confidence is evaluated. We validate our approach using simulated data and show that our scoring method outperforms several extant methods, including the separation to homogeneity ratio and the silhouette measure. We apply our method to evaluate results of several clustering methods on yeast cell-cycle gene expression data. The software is available from the authors upon request.

Novel Bioinformatics-Based Approach for Proteomic Biomarkers Prediction of Calpain-2 & Caspase-3 Protease Fragmentation: Application to βII-Spectrin Protein

NASA Astrophysics Data System (ADS)

El-Assaad, Atlal; Dawy, Zaher; Nemer, Georges; Kobeissy, Firas

2017-01-01

The crucial biological role of proteases has been visible with the development of degradomics discipline involved in the determination of the proteases/substrates resulting in breakdown-products (BDPs) that can be utilized as putative biomarkers associated with different biological-clinical significance. In the field of cancer biology, matrix metalloproteinases (MMPs) have shown to result in MMPs-generated protein BDPs that are indicative of malignant growth in cancer, while in the field of neural injury, calpain-2 and caspase-3 proteases generate BDPs fragments that are indicative of different neural cell death mechanisms in different injury scenarios. Advanced proteomic techniques have shown a remarkable progress in identifying these BDPs experimentally. In this work, we present a bioinformatics-based prediction method that identifies protease-associated BDPs with high precision and efficiency. The method utilizes state-of-the-art sequence matching and alignment algorithms. It starts by locating consensus sequence occurrences and their variants in any set of protein substrates, generating all fragments resulting from cleavage. The complexity exists in space O(mn) as well as in O(Nmn) time, where N, m, and n are the number of protein sequences, length of the consensus sequence, and length per protein sequence, respectively. Finally, the proposed methodology is validated against βII-spectrin protein, a brain injury validated biomarker.

Arrays of nucleic acid probes on biological chips

DOEpatents

Chee, Mark; Cronin, Maureen T.; Fodor, Stephen P. A.; Huang, Xiaohua X.; Hubbell, Earl A.; Lipshutz, Robert J.; Lobban, Peter E.; Morris, MacDonald S.; Sheldon, Edward L.

1998-11-17

DNA chips containing arrays of oligonucleotide probes can be used to determine whether a target nucleic acid has a nucleotide sequence identical to or different from a specific reference sequence. The array of probes comprises probes exactly complementary to the reference sequence, as well as probes that differ by one or more bases from the exactly complementary probes.

Disciplinary reporting affects the interpretation of climate change impacts in global oceans.

PubMed

Hauser, Donna D W; Tobin, Elizabeth D; Feifel, Kirsten M; Shah, Vega; Pietri, Diana M

2016-01-01

Climate change is affecting marine ecosystems, but different investigative approaches in physical, chemical, and biological disciplines may influence interpretations of climate-driven changes in the ocean. Here, we review the ocean change literature from 2007 to 2012 based on 461 of the most highly cited studies in physical and chemical oceanography and three biological subdisciplines. Using highly cited studies, we focus on research that has shaped recent discourse on climate-driven ocean change. Our review identified significant differences in spatial and temporal scales of investigation among disciplines. Physical/chemical studies had a median duration of 29 years (n = 150) and covered the greatest study areas (median 1.41 × 10(7) km(2) , n = 148). Few biological studies were conducted over similar spatial and temporal scales (median 8 years, n = 215; median 302 km(2) , n = 196), suggesting a more limited ability to separate climate-related responses from natural variability. We linked physical/chemical and biological disciplines by tracking studies examining biological responses to changing ocean conditions. Of the 545 biological responses recorded, a single physical or chemical stressor was usually implicated as the cause (59%), with temperature as the most common primary stressor (44%). The most frequently studied biological responses were changes in physiology (31%) and population abundance (30%). Differences in disciplinary studies, as identified in this review, can ultimately influence how researchers interpret climate-related impacts in marine systems. We identified research gaps and the need for more discourse in (1) the Indian and other Southern Hemisphere ocean basins; (2) research themes such as archaea, bacteria, viruses, mangroves, turtles, and ocean acidification; (3) physical and chemical stressors such as dissolved oxygen, salinity, and upwelling; and (4) adaptive responses of marine organisms to climate-driven ocean change. Our findings reveal that highly cited biological studies are rarely conducted on scales that match those of physical and chemical studies. Rather, we suggest a need for measuring responses at biologically relevant scales. © 2015 The Authors. Global Change Biology Published by John Wiley & Sons Ltd.

Assessment of soil biological quality index (QBS-ar) in different crop rotation systems in paddy soils

NASA Astrophysics Data System (ADS)

Nadimi-Goki, Mandana; Bini, Claudio; haefele, Stephan

2013-04-01

New methods, based on soil microarthropods for soil quality evaluation have been proposed by some Authors. Soil microarthropods demonstrated to respond sensitively to land management practices and to be correlated with beneficial soil functions. QBS Index (QBS-ar) is calculated on the basis of microarthropod groups present in a soil sample. Each biological form found in the sample receives a score from 1 to 20 (eco-morphological index, EMI), according to its adaptation to soil environment. The objective of this study was to evaluate the effect of various rotation systems and sampling periods on soil biological quality index, in paddy soils. For the purpose of this study surface soil samples (0-15 cm depth) were collected from different rotation systems (rice-rice-rice, soya-rice-rice, fallow-rice and pea-soya-rice) with three replications, and four sampling times in April (after field preparation), June (after seedling), August (after tillering stage) and October (after rice harvesting). The study area is located in paddy soils of Verona area, Northern Italy. Soil microarthropods from a total of 48 samples were extracted and classified according to the Biological Quality of Soil Index (QBS-ar) method. In addition soil moisture, Cumulative Soil Respiration and pH were measured in each site. More diversity of microarthropod groups was found in June and August sampling times. T-test results between different rotations did not show significant differences while the mean difference between rotation and different sampling times is statistically different. The highest QBS-ar value was found in the fallow-rice rotation in the forth soil sampling time. Similar value was found in soya-rice-rice rotation. Result of linear regression analysis indicated that there is significant correlation between QBS-ar values and Cumulative Soil Respiration. Keywords: soil biological quality index (QBS-ar), Crop Rotation System, paddy soils, Italy

Investigating How German Biology Teachers Use Three-Dimensional Physical Models in Classroom Instruction: a Video Study

NASA Astrophysics Data System (ADS)

Werner, Sonja; Förtsch, Christian; Boone, William; von Kotzebue, Lena; Neuhaus, Birgit J.

2017-07-01

To obtain a general understanding of science, model use as part of National Education Standards is important for instruction. Model use can be characterized by three aspects: (1) the characteristics of the model, (2) the integration of the model into instruction, and (3) the use of models to foster scientific reasoning. However, there were no empirical results describing the implementation of National Education Standards in science instruction concerning the use of models. Therefore, the present study investigated the implementation of different aspects of model use in German biology instruction. Two biology lessons on the topic neurobiology in grade nine of 32 biology teachers were videotaped (N = 64 videos). These lessons were analysed using an event-based coding manual according to three aspects of model described above. Rasch analysis of the coded categories was conducted and showed reliable measurement. In the first analysis, we identified 68 lessons where a total of 112 different models were used. The in-depth analysis showed that special aspects of an elaborate model use according to several categories of scientific reasoning were rarely implemented in biology instruction. A critical reflection of the used model (N = 25 models; 22.3%) and models to demonstrate scientific reasoning (N = 26 models; 23.2%) were seldom observed. Our findings suggest that pre-service biology teacher education and professional development initiatives in Germany have to focus on both aspects.

Biologically active ligands for yersinia outer protein H (YopH): feature based pharmacophore screening, docking and molecular dynamics studies.

PubMed

Tamilvanan, Thangaraju; Hopper, Waheeta

2014-01-01

Yersinia pestis, a Gram negative bacillus, spreads via lymphatic to lymph nodes and to all organs through the bloodstream, causing plague. Yersinia outer protein H (YopH) is one of the important effector proteins, which paralyzes lymphocytes and macrophages by dephosphorylating critical tyrosine kinases and signal transduction molecules. The purpose of the study is to generate a three-dimensional (3D) pharmacophore model by using diverse sets of YopH inhibitors, which would be useful for designing of potential antitoxin. In this study, we have selected 60 biologically active inhibitors of YopH to perform Ligand based pharmacophore study to elucidate the important structural features responsible for biological activity. Pharmacophore model demonstrated the importance of two acceptors, one hydrophobic and two aromatic features toward the biological activity. Based on these features, different databases were screened to identify novel compounds and these ligands were subjected for docking, ADME properties and Binding energy prediction. Post docking validation was performed using molecular dynamics simulation for selected ligands to calculate the Root Mean Square Deviation (RMSD) and Root Mean Square Fluctuation (RMSF). The ligands, ASN03270114, Mol_252138, Mol_31073 and ZINC04237078 may act as inhibitors against YopH of Y. pestis.

Human Leukocyte Antigen (HLA) Genotype as a Contributor to Racial/Ethnic Differences in Breast Cancer: A Population-Based Molecular Epidemiologic Study

DTIC Science & Technology

2006-05-01

Ohsawa M, Kawano K, Wu DM, et al. Epstein - Barr virus in gastric carcinoma in Suzhou, China and Osaka, Japan: association with clinico-pathologic...HLA) component of the immune system differ across racial/ethnic groups, HLA may be a biologically based risk factor for breast cancer and explain...while A-01, B-07, and B-45 decreased risk. Some associations were modified by disease stage at diagnosis, ER status of tumors, and breast cancer

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

Experimental strategies to assess the biological ramifications of multiple drivers of global ocean change-A review.

PubMed

Boyd, Philip W; Collins, Sinead; Dupont, Sam; Fabricius, Katharina; Gattuso, Jean-Pierre; Havenhand, Jonathan; Hutchins, David A; Riebesell, Ulf; Rintoul, Max S; Vichi, Marcello; Biswas, Haimanti; Ciotti, Aurea; Gao, Kunshan; Gehlen, Marion; Hurd, Catriona L; Kurihara, Haruko; McGraw, Christina M; Navarro, Jorge M; Nilsson, Göran E; Passow, Uta; Pörtner, Hans-Otto

2018-06-01

Marine life is controlled by multiple physical and chemical drivers and by diverse ecological processes. Many of these oceanic properties are being altered by climate change and other anthropogenic pressures. Hence, identifying the influences of multifaceted ocean change, from local to global scales, is a complex task. To guide policy-making and make projections of the future of the marine biosphere, it is essential to understand biological responses at physiological, evolutionary and ecological levels. Here, we contrast and compare different approaches to multiple driver experiments that aim to elucidate biological responses to a complex matrix of ocean global change. We present the benefits and the challenges of each approach with a focus on marine research, and guidelines to navigate through these different categories to help identify strategies that might best address research questions in fundamental physiology, experimental evolutionary biology and community ecology. Our review reveals that the field of multiple driver research is being pulled in complementary directions: the need for reductionist approaches to obtain process-oriented, mechanistic understanding and a requirement to quantify responses to projected future scenarios of ocean change. We conclude the review with recommendations on how best to align different experimental approaches to contribute fundamental information needed for science-based policy formulation. © 2018 John Wiley & Sons Ltd.

Wearable System for Acquisition and Monitoring of Biological Signals

NASA Astrophysics Data System (ADS)

Piccinini, D. J.; Andino, N. B.; Ponce, S. D.; Roberti, MA; López, y. N.

2016-04-01

This paper presents a modular, wearable system for acquisition and wireless transmission of biological signals. Configurable slaves for different signals (such as ECG, EMG, inertial sensors, and temperature) based in the ADS1294 Medical Analog Front End are connected to a Master, based in the CC3200 microcontroller, both from Texas Instruments. The slaves are configurable according to the specific application, providing versatility to the wearable system. The battery consumption is reduced, through a couple of Li-ion batteries and the circuit has also a battery charger. A custom made box was designed and fabricated in a 3D printer, preserving the requirements of low cost, low weight and safety recommendations.

Biological evaluation of silver nanoparticles incorporated into chitosan-based membranes.

PubMed

Shao, Jinlong; Yu, Na; Kolwijck, Eva; Wang, Bing; Tan, Ke Wei; Jansen, John A; Walboomers, X Frank; Yang, Fang

2017-11-01

To evaluate the antibacterial potential and biological performance of silver nanoparticles in chitosan-based membranes. Electrospun chitosan/poly(ethylene oxide) membranes with different amounts of silver nanoparticles were evaluated for antibacterial properties and cytotoxicity in vitro and for tissue response in a rabbit subcutaneous model. The nanoparticles displayed dose-dependent antibacterial properties against Porphyromonas gingivalis and Fusobacterium nucleatum, without showing noticeable cytotoxicity. The membranes with silver nanoparticles evoked a similar inflammatory response compared with the membranes without silver nanoparticles. The antibacterial effect, combined with the findings on cyto- and biocompatibility warrants further investigation to the usefulness of chitosan/poly(ethylene oxide) membranes with silver nanoparticles, for clinical applications like guided tissue regeneration.

The analytical change in plasma creatinine that constitutes a biologic/physiologic change.

PubMed

Toffaletti, John G; Hammett-Stabler, Catherine A; Gearhart, Margaret; Roy Choudhury, Kingshuk; Handel, Elizabeth A

2016-08-01

Accurate and precise measurements of creatinine are necessary to evaluate changes in kidney function related to a decreased glomerular filtration rate (GFR). When serial measurements of creatinine are monitored in an individual, it is useful to know what magnitude of an analytical change in creatinine indicates a true physiologic/biologic change in plasma creatinine that might warrant clinical intervention. We compared results between three different methods for creatinine using large chemistry analyzers, two based on alkaline picrate (AP1 and AP2), and one based on dry-slide enzymatic conversion (ENZ). On each of three different segments or days of the study spaced 1-2months apart, we selected 10 different plasma samples having creatinine concentrations ranging from about 0.5mg/dL to 4.5mg/dL (44 to 400μmol/L). Each sample was analyzed in triplicate on each of two same-model analyzers at each institution, then from this data we determined the precision of each model of analyzer. The within-instrument precision of each analyzer was evaluated from the differences between the triplicate results on each sample by each analyzer (mean and SD of the differences). The between-instrument precision was evaluated as the differences between results on the same sample (1, 2, 3, etc.) analyzed on different analyzers of the same model (A and B). This between-analyzer precision data was used to determine both the range and mean±2SD of the differences that could be used to indicate that greater changes in creatinine concentrations would represent a biologic change. The within-instrument precision was best for the ENZ method in comparison to the two alkaline picrate rate methods. The between-instrument precision of the 90 consecutive measurements (30 samples×triplicate analyses) between the same-model analyzers were (mean and SD of differences in mg/dL): -0.018 and 0.029 (ENZ); 0.016 and 0.11 (AP1), and -0.058 and 0.071 (AP2). While all three of the creatinine methods studied had good precision, the ENZ method had the best precision, such that a change of 0.07mg/dL (6μmol/L) in serial creatinine concentrations up to 1.5mg/dL on a patient could indicate a biologic change had occurred. For the alkaline picrate methods, a measured change of creatinine of 0.23mg/dL for AP1 or 0.11mg/dL for AP2 would indicate that a physiologic change in serum/plasma creatinine has occurred. While a definite biologic change may simply represent daily variations, detecting a biologic change in creatinine more rapidly could impact the ability of creatinine to detect early and clinically significant changes in renal function. Copyright © 2016 Elsevier B.V. All rights reserved.

Bacteriophage vehicles for phage display: biology, mechanism, and application.

PubMed

Ebrahimizadeh, Walead; Rajabibazl, Masoumeh

2014-08-01

The phage display technique is a powerful tool for selection of various biological agents. This technique allows construction of large libraries from the antibody repertoire of different hosts and provides a fast and high-throughput selection method. Specific antibodies can be isolated based on distinctive characteristics from a library consisting of millions of members. These features made phage display technology preferred method for antibody selection and engineering. There are several phage display methods available and each has its unique merits and application. Selection of appropriate display technique requires basic knowledge of available methods and their mechanism. In this review, we describe different phage display techniques, available bacteriophage vehicles, and their mechanism.

Biologically inspired emotion recognition from speech

NASA Astrophysics Data System (ADS)

Caponetti, Laura; Buscicchio, Cosimo Alessandro; Castellano, Giovanna

2011-12-01

Emotion recognition has become a fundamental task in human-computer interaction systems. In this article, we propose an emotion recognition approach based on biologically inspired methods. Specifically, emotion classification is performed using a long short-term memory (LSTM) recurrent neural network which is able to recognize long-range dependencies between successive temporal patterns. We propose to represent data using features derived from two different models: mel-frequency cepstral coefficients (MFCC) and the Lyon cochlear model. In the experimental phase, results obtained from the LSTM network and the two different feature sets are compared, showing that features derived from the Lyon cochlear model give better recognition results in comparison with those obtained with the traditional MFCC representation.

Topological study of nanomaterials using surface-enhanced ellipsometric contrast microscopy (SEEC)

NASA Astrophysics Data System (ADS)

Muckenhirn, Sylvain

2016-03-01

Innovations in nanotechnology are empowering scientists to deepen their understanding of physical, chemical and biological mechanisms. Powerful and precise characterization systems are essential to meet researchers' requirements. SEEC (Surface Enhanced Ellipsometric Contrast) microscopy is an innovative advanced optical technique based on ellipsometric and interference fringes of Fizeau principles. This technique offers live and label-free topographic imaging of organic, inorganic and biological samples with high Z resolution (down to 0.1nm thickness), and enhanced X-Y detection limit (down to 1.5nm width). This technique has been successfully applied to the study of nanometric films and structures, biological layers, and nano-objects. We applied SEEC technology to different applications explored below.

Constructing phylogenetic trees using interacting pathways.

PubMed

Wan, Peng; Che, Dongsheng

2013-01-01

Phylogenetic trees are used to represent evolutionary relationships among biological species or organisms. The construction of phylogenetic trees is based on the similarities or differences of their physical or genetic features. Traditional approaches of constructing phylogenetic trees mainly focus on physical features. The recent advancement of high-throughput technologies has led to accumulation of huge amounts of biological data, which in turn changed the way of biological studies in various aspects. In this paper, we report our approach of building phylogenetic trees using the information of interacting pathways. We have applied hierarchical clustering on two domains of organisms-eukaryotes and prokaryotes. Our preliminary results have shown the effectiveness of using the interacting pathways in revealing evolutionary relationships.

Ionization of biomolecular targets by ion impact: input data for radiobiological applications

NASA Astrophysics Data System (ADS)

de Vera, Pablo; Abril, Isabel; Garcia-Molina, Rafael; Solov'yov, Andrey V.

2013-06-01

In this work we review and further develop a semiempirical model recently proposed for the ion impact ionization of complex biological media. The model is based on the dielectric formalism, and makes use of a semiempirical parametrization of the optical energy-loss function of bioorganic compounds, allowing the calculation of single and total ionization cross sections and related quantities for condensed biological targets, such as liquid water, DNA and its components, proteins, lipids, carbohydrates or cell constituents. The model shows a very good agreement with experimental data for water, adenine and uracil, and allows the comparison of the ionization efficiency of different biological targets, and also the average kinetic energy of the ejected secondary electrons.

Network Approach to Disease Diagnosis

NASA Astrophysics Data System (ADS)

Sharma, Amitabh; Bashan, Amir; Barabasi, Alber-Laszlo

2014-03-01

Human diseases could be viewed as perturbations of the underlying biological system. A thorough understanding of the topological and dynamical properties of the biological system is crucial to explain the mechanisms of many complex diseases. Recently network-based approaches have provided a framework for integrating multi-dimensional biological data that results in a better understanding of the pathophysiological state of complex diseases. Here we provide a network-based framework to improve the diagnosis of complex diseases. This framework is based on the integration of transcriptomics and the interactome. We analyze the overlap between the differentially expressed (DE) genes and disease genes (DGs) based on their locations in the molecular interaction network (''interactome''). Disease genes and their protein products tend to be much more highly connected than random, hence defining a disease sub-graph (called disease module) in the interactome. DE genes, even though different from the known set of DGs, may be significantly associated with the disease when considering their closeness to the disease module in the interactome. This new network approach holds the promise to improve the diagnosis of patients who cannot be diagnosed using conventional tools. Support was provided by HL066289 and HL105339 grants from the U.S. National Institutes of Health.

Concurrent estimates of carbon export reveal physical biases in ΔO2/Ar-based net community production estimates in the Southern California Bight

NASA Astrophysics Data System (ADS)

Haskell, William Z.; Fleming, John C.

2018-07-01

Net community production (NCP) represents the amount of biologically-produced organic carbon that is available to be exported out of the surface ocean and is typically estimated using measurements of the O2/Ar ratio in the surface mixed layer under the assumption of negligible vertical transport. However, physical processes can significantly bias NCP estimates based on this in-situ tracer. It is actively debated whether discrepancies between O2/Ar-based NCP and carbon export estimates are due to differences in the location of biological production and export, or the result of physical biases. In this study, we calculate export production across the euphotic depth during two months of upwelling in Southern California in 2014, based on an estimate of the consumption rate of dissolved organic carbon (DOC) and the dissolved: total organic carbon consumption ratio below the euphotic depth. This estimate equals the concurrent O2/Ar-based NCP estimates over the same period that are corrected for physical biases, but is significantly different than NCP estimated without a correction for vertical transport. This comparison demonstrates that concurrent physical transport estimates would significantly improve O2/Ar-based estimates of NCP, particularly in settings with vertical advection. Potential approaches to mitigate this bias are discussed.

The development of Army relevant peptide-based surface enhanced Raman scattering (SERS) sensors for biological threat detection

NASA Astrophysics Data System (ADS)

Farrell, Mikella E.; Strobbia, Pietro; Sarkes, Deborah A.; Stratis-Cullum, Dimitra N.; Cullum, Brian M.; Pellegrino, Paul M.

2016-05-01

The utility of peptide-based molecular sensing for the development of novel biosensors has resulted in a significant increase in their development and usage for sensing targets like chemical, biological, energetic and toxic materials. Using peptides as a molecular recognition element is particularly advantageous because there are several mature peptide synthesis protocols that already exist, peptide structures can be tailored, selected and manipulated to be highly discerning towards desired targets, peptides can be modified to be very stable in a host of environments and stable under many different conditions, and through the development of bifunctionalized peptides can be synthesized to also bind onto desired sensing platforms (various metal materials, glass, etc.). Two examples of the several Army relevant biological targets for peptide-based sensing platforms include Ricin and Abrin. Ricin and Abrin are alarming threats because both can be weaponized and there is no antidote for exposure. Combining the sensitivity of SERS with the selectivity of a bifunctional peptide allows for the emergence of dynamic hazard sensor for Army application.

Cancer systems biology in the genome sequencing era: part 1, dissecting and modeling of tumor clones and their networks.

PubMed

Wang, Edwin; Zou, Jinfeng; Zaman, Naif; Beitel, Lenore K; Trifiro, Mark; Paliouras, Miltiadis

2013-08-01

Recent tumor genome sequencing confirmed that one tumor often consists of multiple cell subpopulations (clones) which bear different, but related, genetic profiles such as mutation and copy number variation profiles. Thus far, one tumor has been viewed as a whole entity in cancer functional studies. With the advances of genome sequencing and computational analysis, we are able to quantify and computationally dissect clones from tumors, and then conduct clone-based analysis. Emerging technologies such as single-cell genome sequencing and RNA-Seq could profile tumor clones. Thus, we should reconsider how to conduct cancer systems biology studies in the genome sequencing era. We will outline new directions for conducting cancer systems biology by considering that genome sequencing technology can be used for dissecting, quantifying and genetically characterizing clones from tumors. Topics discussed in Part 1 of this review include computationally quantifying of tumor subpopulations; clone-based network modeling, cancer hallmark-based networks and their high-order rewiring principles and the principles of cell survival networks of fast-growing clones. Crown Copyright © 2013. Published by Elsevier Ltd. All rights reserved.

SLEPR: A Sample-Level Enrichment-Based Pathway Ranking Method — Seeking Biological Themes through Pathway-Level Consistency

PubMed Central

Yi, Ming; Stephens, Robert M.

2008-01-01

Analysis of microarray and other high throughput data often involves identification of genes consistently up or down-regulated across samples as the first step in extraction of biological meaning. This gene-level paradigm can be limited as a result of valid sample fluctuations and biological complexities. In this report, we describe a novel method, SLEPR, which eliminates this limitation by relying on pathway-level consistencies. Our method first selects the sample-level differentiated genes from each individual sample, capturing genes missed by other analysis methods, ascertains the enrichment levels of associated pathways from each of those lists, and then ranks annotated pathways based on the consistency of enrichment levels of individual samples from both sample classes. As a proof of concept, we have used this method to analyze three public microarray datasets with a direct comparison with the GSEA method, one of the most popular pathway-level analysis methods in the field. We found that our method was able to reproduce the earlier observations with significant improvements in depth of coverage for validated or expected biological themes, but also produced additional insights that make biological sense. This new method extends existing analyses approaches and facilitates integration of different types of HTP data. PMID:18818771

Eugene--a domain specific language for specifying and constraining synthetic biological parts, devices, and systems.

PubMed

Bilitchenko, Lesia; Liu, Adam; Cheung, Sherine; Weeding, Emma; Xia, Bing; Leguia, Mariana; Anderson, J Christopher; Densmore, Douglas

2011-04-29

Synthetic biological systems are currently created by an ad-hoc, iterative process of specification, design, and assembly. These systems would greatly benefit from a more formalized and rigorous specification of the desired system components as well as constraints on their composition. Therefore, the creation of robust and efficient design flows and tools is imperative. We present a human readable language (Eugene) that allows for the specification of synthetic biological designs based on biological parts, as well as provides a very expressive constraint system to drive the automatic creation of composite Parts (Devices) from a collection of individual Parts. We illustrate Eugene's capabilities in three different areas: Device specification, design space exploration, and assembly and simulation integration. These results highlight Eugene's ability to create combinatorial design spaces and prune these spaces for simulation or physical assembly. Eugene creates functional designs quickly and cost-effectively. Eugene is intended for forward engineering of DNA-based devices, and through its data types and execution semantics, reflects the desired abstraction hierarchy in synthetic biology. Eugene provides a powerful constraint system which can be used to drive the creation of new devices at runtime. It accomplishes all of this while being part of a larger tool chain which includes support for design, simulation, and physical device assembly.

Efficiently Photocontrollable or not? Biological Activity of Photoisomerizable Diarylethenes.

PubMed

Komarov, Igor V; Afonin, Sergii; Babii, Oleg; Schober, Tim; Ulrich, Anne S

2018-04-06

Diarylethene derivatives, whose biological activity can be reversibly changed by irradiation with light of different wavelengths, have shown promise as scientific tools and as candidates for photocontrollable drugs. However, examples demonstrating efficient photocontrol of their biological activity are still relatively rare. This concept article discusses the possible reasons for this situation and presents a critical analysis of existing data and hypotheses in this field, in order to extract the design principles enabling the construction of efficient photocontrollable diarylethene-based molecules. Papers addressing biologically relevant interactions between diarylethenes and biomolecules are analyzed; however, in most published cases, the efficiency of photocontrol in living systems remains to be demonstrated. We hope that this article will encourage further discussion of design principles, primarily among pharmacologists and synthetic and medicinal chemists. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

The short-lived African turquoise killifish: an emerging experimental model for ageing

PubMed Central

Kim, Yumi; Nam, Hong Gil; Valenzano, Dario Riccardo

2016-01-01

ABSTRACT Human ageing is a fundamental biological process that leads to functional decay, increased risk for various diseases and, ultimately, death. Some of the basic biological mechanisms underlying human ageing are shared with other organisms; thus, animal models have been invaluable in providing key mechanistic and molecular insights into the common bases of biological ageing. In this Review, we briefly summarise the major applications of the most commonly used model organisms adopted in ageing research and highlight their relevance in understanding human ageing. We compare the strengths and limitations of different model organisms and discuss in detail an emerging ageing model, the short-lived African turquoise killifish. We review the recent progress made in using the turquoise killifish to study the biology of ageing and discuss potential future applications of this promising animal model. PMID:26839399

Application of in Vitro Biotransformation Data and ...

EPA Pesticide Factsheets

The adverse biological effects of toxic substances are dependent upon the exposure concentration and the duration of exposure. Pharmacokinetic models can quantitatively relate the external concentration of a toxicant in the environment to the internal dose of the toxicant in the target tissues of an exposed organism. The exposure concentration of a toxic substance is usually not the same as the concentration of the active form of the toxicant that reaches the target tissues following absorption, distribution, and biotransformation of the parent toxicant. Biotransformation modulates the biological activity of chemicals through bioactivation and detoxication pathways. Many toxicants require biotransformation to exert their adverse biological effects. Considerable species differences in biotransformation and other pharmacokinetic processes can make extrapolation of toxicity data from laboratory animals to humans problematic. Additionally, interindividual differences in biotransformation among human populations with diverse genetics and lifestyles can lead to considerable variability in the bioactivation of toxic chemicals. Compartmental pharmacokinetic models of animals and humans are needed to understand the quantitative relationships between chemical exposure and target tissue dose as well as animal to human differences and interindividual differences in human populations. The data-based compartmental pharmacokinetic models widely used in clinical pharmacology ha

Grandparenting and adolescent adjustment in two-parent biological, lone-parent, and step-families.

PubMed

Attar-Schwartz, Shalhevet; Tan, Jo-Pei; Buchanan, Ann; Flouri, Eirini; Griggs, Julia

2009-02-01

There is limited research on the links between grandparenting and adolescents' well-being, especially from the perspective of the adolescents. The study examined whether grandparent involvement varied in two-parent biological, lone-parent, and step-families and whether this had a different contribution to the emotional and behavioral adjustment of adolescents across different family structures. The study is based on a sample of 1,515 secondary school students (ages 11-16 years) from England and Wales who completed a structured questionnaire. Findings of hierarchical regression analyses showed that among the whole sample, greater grandparent involvement was associated with fewer emotional problems (p < .01) and with more prosocial behavior (p < .001). In addition, while there were no differences in the level of grandparent involvement across the different family structures, grandparent involvement was more strongly associated with reduced adjustment difficulties among adolescents from lone-parent and step-families than those from two-parent biological families. A possible implication is that the positive role of grandparent involvement in lone-parent and step- families should be more emphasized in family psychology. (PsycINFO Database Record (c) 2009 APA, all rights reserved).

Variation in reaction norms: Statistical considerations and biological interpretation.

PubMed

Morrissey, Michael B; Liefting, Maartje

2016-09-01

Analysis of reaction norms, the functions by which the phenotype produced by a given genotype depends on the environment, is critical to studying many aspects of phenotypic evolution. Different techniques are available for quantifying different aspects of reaction norm variation. We examine what biological inferences can be drawn from some of the more readily applicable analyses for studying reaction norms. We adopt a strongly biologically motivated view, but draw on statistical theory to highlight strengths and drawbacks of different techniques. In particular, consideration of some formal statistical theory leads to revision of some recently, and forcefully, advocated opinions on reaction norm analysis. We clarify what simple analysis of the slope between mean phenotype in two environments can tell us about reaction norms, explore the conditions under which polynomial regression can provide robust inferences about reaction norm shape, and explore how different existing approaches may be used to draw inferences about variation in reaction norm shape. We show how mixed model-based approaches can provide more robust inferences than more commonly used multistep statistical approaches, and derive new metrics of the relative importance of variation in reaction norm intercepts, slopes, and curvatures. © 2016 The Author(s). Evolution © 2016 The Society for the Study of Evolution.

Nanomaterial-based electrochemical sensors for arsenic - A review.

PubMed

Kempahanumakkagari, Sureshkumar; Deep, Akash; Kim, Ki-Hyun; Kumar Kailasa, Suresh; Yoon, Hye-On

2017-09-15

The existence of arsenic in the environment poses severe global health threats. Considering its toxicity, the sensing of arsenic is extremely important. Due to the complexity of environmental and biological samples, many of the available detection methods for arsenic have serious limitations on selectivity and sensitivity. To improve sensitivity and selectivity and to circumvent interferences, different electrode systems have been developed based on surface modification with nanomaterials including carbonaceous nanomaterials, metallic nanoparticles (MNPs), metal nanotubes (MNTs), and even enzymes. Despite the progress made in electrochemical sensing of arsenic, some issues still need to be addressed to realize cost effective, portable, and flow-injection type sensor systems. The present review provides an in-depth evaluation of the nanoparticle-modified electrode (NME) based methods for the electrochemical sensing of arsenic. NME based sensing systems are projected to become an important option for monitoring hazardous pollutants in both environmental and biological media. Copyright © 2017 Elsevier B.V. All rights reserved.

Protein purification by aminosquarylium cyanine dye-affinity chromatography.

PubMed

Silva, M S; Graça, V C; Reis, L V; Santos, P F; Almeida, P; Queiroz, J A; Sousa, F

2013-12-01

The most selective purification method for proteins and other biomolecules is affinity chromatography. This method is based on the unique biological-based specificity of the biomolecule-ligand interaction and commonly uses biological ligands. However, these ligands may present some drawbacks, mainly because of their cost and lability. Dye-affinity chromatography overcomes the limitations of biological ligands and is widely used owing to the low cost of synthetic dyes and to their resistance to biological and chemical degradation. In this work, immobilized aminosquarylium cyanine dyes are used in order to exploit affinity interactions with standard proteins such as lysozyme, α-chymotrypsin and trypsin. These studies evaluate the affinity interactions occurring between the immobilized ligand and the different proteins, as a reflection of the sum of several molecular interactions, namely ionic, hydrophobic and van der Waals, spread throughout the structure, in a defined spatial manner. The results show the possibility of using an aminosquarylium cyanine dye bearing a N-hexyl pendant chain, with a ligand density of 1.8 × 10(-2) mmol of dye/g of chromatographic support, to isolate lysozyme, α-chymotrypsin and trypsin from a mixture. The application of a decreasing ammonium sulfate gradient resulted in the recovery of lysozyme in the flowthrough. On the other hand, α-chymotrypsin and trypsin were retained, involving different interactions with the ligand. In conclusion, this study demonstrates the potential applicability of ligands such as aminosquarylium cyanine dyes for the separation and purification of proteins by affinity chromatography. Copyright © 2013 John Wiley & Sons, Ltd.

Multi-tissue DNA methylation age predictor in mouse.

PubMed

Stubbs, Thomas M; Bonder, Marc Jan; Stark, Anne-Katrien; Krueger, Felix; von Meyenn, Ferdinand; Stegle, Oliver; Reik, Wolf

2017-04-11

DNA methylation changes at a discrete set of sites in the human genome are predictive of chronological and biological age. However, it is not known whether these changes are causative or a consequence of an underlying ageing process. It has also not been shown whether this epigenetic clock is unique to humans or conserved in the more experimentally tractable mouse. We have generated a comprehensive set of genome-scale base-resolution methylation maps from multiple mouse tissues spanning a wide range of ages. Many CpG sites show significant tissue-independent correlations with age which allowed us to develop a multi-tissue predictor of age in the mouse. Our model, which estimates age based on DNA methylation at 329 unique CpG sites, has a median absolute error of 3.33 weeks and has similar properties to the recently described human epigenetic clock. Using publicly available datasets, we find that the mouse clock is accurate enough to measure effects on biological age, including in the context of interventions. While females and males show no significant differences in predicted DNA methylation age, ovariectomy results in significant age acceleration in females. Furthermore, we identify significant differences in age-acceleration dependent on the lipid content of the diet. Here we identify and characterise an epigenetic predictor of age in mice, the mouse epigenetic clock. This clock will be instrumental for understanding the biology of ageing and will allow modulation of its ticking rate and resetting the clock in vivo to study the impact on biological age.

From Biology to Mathematical Models and Back: Teaching Modeling to Biology Students, and Biology to Math and Engineering Students

PubMed Central

McManus, Jeffrey M.; Shaw, Kendrick M.

2010-01-01

We describe the development of a course to teach modeling and mathematical analysis skills to students of biology and to teach biology to students with strong backgrounds in mathematics, physics, or engineering. The two groups of students have different ways of learning material and often have strong negative feelings toward the area of knowledge that they find difficult. To give students a sense of mastery in each area, several complementary approaches are used in the course: 1) a “live” textbook that allows students to explore models and mathematical processes interactively; 2) benchmark problems providing key skills on which students make continuous progress; 3) assignment of students to teams of two throughout the semester; 4) regular one-on-one interactions with instructors throughout the semester; and 5) a term project in which students reconstruct, analyze, extend, and then write in detail about a recently published biological model. Based on student evaluations and comments, an attitude survey, and the quality of the students' term papers, the course has significantly increased the ability and willingness of biology students to use mathematical concepts and modeling tools to understand biological systems, and it has significantly enhanced engineering students' appreciation of biology. PMID:20810957

A sense of life: computational and experimental investigations with models of biochemical and evolutionary processes.

PubMed

Mishra, Bud; Daruwala, Raoul-Sam; Zhou, Yi; Ugel, Nadia; Policriti, Alberto; Antoniotti, Marco; Paxia, Salvatore; Rejali, Marc; Rudra, Archisman; Cherepinsky, Vera; Silver, Naomi; Casey, William; Piazza, Carla; Simeoni, Marta; Barbano, Paolo; Spivak, Marina; Feng, Jiawu; Gill, Ofer; Venkatesh, Mysore; Cheng, Fang; Sun, Bing; Ioniata, Iuliana; Anantharaman, Thomas; Hubbard, E Jane Albert; Pnueli, Amir; Harel, David; Chandru, Vijay; Hariharan, Ramesh; Wigler, Michael; Park, Frank; Lin, Shih-Chieh; Lazebnik, Yuri; Winkler, Franz; Cantor, Charles R; Carbone, Alessandra; Gromov, Mikhael

2003-01-01

We collaborate in a research program aimed at creating a rigorous framework, experimental infrastructure, and computational environment for understanding, experimenting with, manipulating, and modifying a diverse set of fundamental biological processes at multiple scales and spatio-temporal modes. The novelty of our research is based on an approach that (i) requires coevolution of experimental science and theoretical techniques and (ii) exploits a certain universality in biology guided by a parsimonious model of evolutionary mechanisms operating at the genomic level and manifesting at the proteomic, transcriptomic, phylogenic, and other higher levels. Our current program in "systems biology" endeavors to marry large-scale biological experiments with the tools to ponder and reason about large, complex, and subtle natural systems. To achieve this ambitious goal, ideas and concepts are combined from many different fields: biological experimentation, applied mathematical modeling, computational reasoning schemes, and large-scale numerical and symbolic simulations. From a biological viewpoint, the basic issues are many: (i) understanding common and shared structural motifs among biological processes; (ii) modeling biological noise due to interactions among a small number of key molecules or loss of synchrony; (iii) explaining the robustness of these systems in spite of such noise; and (iv) cataloging multistatic behavior and adaptation exhibited by many biological processes.

Comparing Biology Grades Based on Instructional Delivery and Instructor at a Community College: Face-to-Face Course Versus Online Course

NASA Astrophysics Data System (ADS)

Rosenzweig, Amanda H.

Through distance learning, the community college system has been able to serve more students by providing educational opportunities to students who would otherwise be unable to attend college. The community college of focus in the study increased its online enrollments and online course offerings due to the growth of overall enrollment. The need and purpose of the study is to address if there is a difference in students' grades between face-to-face and online biology related courses and if there are differences in grades between face-to-face and online biology courses taught by different instructors and the same instructor. The study also addresses if online course delivery is a viable method to educate students in biology-related fields. The study spanned 14 semesters between spring 2006 and summer 2011. Data were collected for 6,619 students. For each student, demographic information, cumulative grade point average, ACT, and data on course performance were gathered. Student data were gathered from General Biology I, Microbiology of Human Pathogens, Human Anatomy and Physiology I, and Human Anatomy and Physiology II courses. Univariate analysis of variance, linear regression, and descriptive analysis were used to analyze the data and determine which variables significantly impacted grade achievement for face-to-face and online students in biology classes. The findings from the study showed that course type, face-to-face or online, was significant for Microbiology of Human Pathogens and Human Anatomy and Physiology I, both upper level courses. Teachers were significant for General Biology I, a lower level course, Human Anatomy and Physiology I, and Human Anatomy and Physiology II. However, in every class, there were teachers who had significant differences within their courses between their face-to-face and online courses. This study will allow information to be concluded about the relationship between the students' final grades and class type, face-to-face or online, and instructor. Administrators, faculty and students can use this information to understand what needs to be done to successfully teach and enroll in biology courses, face-to-face or online. biology courses, online courses, face-to-face courses, class type, teacher influence, grades, CGPA, community college

Indices of polarimetric purity for biological tissues inspection

NASA Astrophysics Data System (ADS)

Van Eeckhout, Albert; Lizana, Angel; Garcia-Caurel, Enric; Gil, José J.; Sansa, Adrià; Rodríguez, Carla; Estévez, Irene; González, Emilio; Escalera, Juan C.; Moreno, Ignacio; Campos, Juan

2018-02-01

We highlight the interest of using the Indices of Polarimetric Purity (IPPs) for the biological tissue inspection. These are three polarimetric metrics focused on the study of the depolarizing behaviour of the sample. The IPPs have been recently proposed in the literature and provide different and synthetized information than the commonly used depolarizing indices, as depolarization index (PΔ) or depolarization power (Δ). Compared with the standard polarimetric images of biological samples, IPPs enhance the contrast between different tissues of the sample and show differences between similar tissues which are not observed using the other standard techniques. Moreover, they present further physical information related to the depolarization mechanisms inherent to different tissues. In addition, the algorithm does not require advanced calculations (as in the case of polar decompositions), being the indices of polarimetric purity fast and easy to implement. We also propose a pseudo-coloured image method which encodes the sample information as a function of the different indices weights. These images allow us to customize the visualization of samples and to highlight certain of their constitutive structures. The interest and potential of the IPP approach are experimentally illustrated throughout the manuscript by comparing polarimetric images of different ex-vivo samples obtained with standard polarimetric methods with those obtained from the IPPs analysis. Enhanced contrast and retrieval of new information are experimentally obtained from the different IPP based images.

Epigenome overlap measure (EPOM) for comparing tissue/cell types based on chromatin states.

PubMed

Li, Wei Vivian; Razaee, Zahra S; Li, Jingyi Jessica

2016-01-11

The dynamics of epigenomic marks in their relevant chromatin states regulate distinct gene expression patterns, biological functions and phenotypic variations in biological processes. The availability of high-throughput epigenomic data generated by next-generation sequencing technologies allows a data-driven approach to evaluate the similarities and differences of diverse tissue and cell types in terms of epigenomic features. While ChromImpute has allowed for the imputation of large-scale epigenomic information to yield more robust data to capture meaningful relationships between biological samples, widely used methods such as hierarchical clustering and correlation analysis cannot adequately utilize epigenomic data to accurately reveal the distinction and grouping of different tissue and cell types. We utilize a three-step testing procedure-ANOVA, t test and overlap test to identify tissue/cell-type- associated enhancers and promoters and to calculate a newly defined Epigenomic Overlap Measure (EPOM). EPOM results in a clear correspondence map of biological samples from different tissue and cell types through comparison of epigenomic marks evaluated in their relevant chromatin states. Correspondence maps by EPOM show strong capability in distinguishing and grouping different tissue and cell types and reveal biologically meaningful similarities between Heart and Muscle, Blood & T-cell and HSC & B-cell, Brain and Neurosphere, etc. The gene ontology enrichment analysis both supports and explains the discoveries made by EPOM and suggests that the associated enhancers and promoters demonstrate distinguishable functions across tissue and cell types. Moreover, the tissue/cell-type-associated enhancers and promoters show enrichment in the disease-related SNPs that are also associated with the corresponding tissue or cell types. This agreement suggests the potential of identifying causal genetic variants relevant to cell-type-specific diseases from our identified associated enhancers and promoters. The proposed EPOM measure demonstrates superior capability in grouping and finding a clear correspondence map of biological samples from different tissue and cell types. The identified associated enhancers and promoters provide a comprehensive catalog to study distinct biological processes and disease variants in different tissue and cell types. Our results also find that the associated promoters exhibit more cell-type-specific functions than the associated enhancers do, suggesting that the non-associated promoters have more housekeeping functions than the non-associated enhancers.

Robust and automated three-dimensional segmentation of densely packed cell nuclei in different biological specimens with Lines-of-Sight decomposition.

PubMed

Mathew, B; Schmitz, A; Muñoz-Descalzo, S; Ansari, N; Pampaloni, F; Stelzer, E H K; Fischer, S C

2015-06-08

Due to the large amount of data produced by advanced microscopy, automated image analysis is crucial in modern biology. Most applications require reliable cell nuclei segmentation. However, in many biological specimens cell nuclei are densely packed and appear to touch one another in the images. Therefore, a major difficulty of three-dimensional cell nuclei segmentation is the decomposition of cell nuclei that apparently touch each other. Current methods are highly adapted to a certain biological specimen or a specific microscope. They do not ensure similarly accurate segmentation performance, i.e. their robustness for different datasets is not guaranteed. Hence, these methods require elaborate adjustments to each dataset. We present an advanced three-dimensional cell nuclei segmentation algorithm that is accurate and robust. Our approach combines local adaptive pre-processing with decomposition based on Lines-of-Sight (LoS) to separate apparently touching cell nuclei into approximately convex parts. We demonstrate the superior performance of our algorithm using data from different specimens recorded with different microscopes. The three-dimensional images were recorded with confocal and light sheet-based fluorescence microscopes. The specimens are an early mouse embryo and two different cellular spheroids. We compared the segmentation accuracy of our algorithm with ground truth data for the test images and results from state-of-the-art methods. The analysis shows that our method is accurate throughout all test datasets (mean F-measure: 91%) whereas the other methods each failed for at least one dataset (F-measure≤69%). Furthermore, nuclei volume measurements are improved for LoS decomposition. The state-of-the-art methods required laborious adjustments of parameter values to achieve these results. Our LoS algorithm did not require parameter value adjustments. The accurate performance was achieved with one fixed set of parameter values. We developed a novel and fully automated three-dimensional cell nuclei segmentation method incorporating LoS decomposition. LoS are easily accessible features that ensure correct splitting of apparently touching cell nuclei independent of their shape, size or intensity. Our method showed superior performance compared to state-of-the-art methods, performing accurately for a variety of test images. Hence, our LoS approach can be readily applied to quantitative evaluation in drug testing, developmental and cell biology.

Luminol-Based Chemiluminescent Signals: Clinical and Non-clinical Application and Future Uses

PubMed Central

Khan, Parvez; Idrees, Danish; Moxley, Michael A.; Corbett, John A.; Ahmad, Faizan; von Figura, Guido; Sly, William S.; Waheed, Abdul

2015-01-01

Chemiluminescence (CL) is an important method for quantification and analysis of various macromolecules. A wide range of CL agents such as luminol, hydrogen peroxide, fluorescein, dioxetanes and derivatives of oxalate, and acridinium dyes are used according to their biological specificity and utility. This review describes the application of luminol chemiluminescence (LCL) in forensic, biomedical, and clinical sciences. LCL is a very useful detection method due to its selectivity, simplicity, low cost, and high sensitivity. LCL has a dynamic range of applications, including quantification and detection of macro and micromolecules such as proteins, carbohydrates, DNA, and RNA. Luminol-based methods are used in environmental monitoring as biosensors, in the pharmaceutical industry for cellular localization and as biological tracers, and in reporter gene-based assays and several other immunoassays. Here, we also provide information about different compounds that may enhance or inhibit the LCL along with the effect of pH and concentration on LCL. This review covers most of the significant information related to the applications of luminol in different fields. PMID:24752935

Partial Least Squares Based Gene Expression Analysis in EBV- Positive and EBV-Negative Posttransplant Lymphoproliferative Disorders.

PubMed

Wu, Sa; Zhang, Xin; Li, Zhi-Ming; Shi, Yan-Xia; Huang, Jia-Jia; Xia, Yi; Yang, Hang; Jiang, Wen-Qi

2013-01-01

Post-transplant lymphoproliferative disorder (PTLD) is a common complication of therapeutic immunosuppression after organ transplantation. Gene expression profile facilitates the identification of biological difference between Epstein-Barr virus (EBV) positive and negative PTLDs. Previous studies mainly implemented variance/regression analysis without considering unaccounted array specific factors. The aim of this study is to investigate the gene expression difference between EBV positive and negative PTLDs through partial least squares (PLS) based analysis. With a microarray data set from the Gene Expression Omnibus database, we performed PLS based analysis. We acquired 1188 differentially expressed genes. Pathway and Gene Ontology enrichment analysis identified significantly over-representation of dysregulated genes in immune response and cancer related biological processes. Network analysis identified three hub genes with degrees higher than 15, including CREBBP, ATXN1, and PML. Proteins encoded by CREBBP and PML have been reported to be interact with EBV before. Our findings shed light on expression distinction of EBV positive and negative PTLDs with the hope to offer theoretical support for future therapeutic study.

Examining the Use of Web-Based Tests for Testing Academic Vocabulary in EAP Instruction

ERIC Educational Resources Information Center

Dashtestani, Reza

2015-01-01

Interest in Web-based and computer-assisted language testing is growing in the field of English for academic purposes (EAP). In this study, four groups of undergraduate EAP students (n = 120), each group consisted of 30 students, were randomly selected from four different disciplines, i.e. biology, political sciences, psychology, and law. The four…

Kernel-PCA data integration with enhanced interpretability

PubMed Central

2014-01-01

Background Nowadays, combining the different sources of information to improve the biological knowledge available is a challenge in bioinformatics. One of the most powerful methods for integrating heterogeneous data types are kernel-based methods. Kernel-based data integration approaches consist of two basic steps: firstly the right kernel is chosen for each data set; secondly the kernels from the different data sources are combined to give a complete representation of the available data for a given statistical task. Results We analyze the integration of data from several sources of information using kernel PCA, from the point of view of reducing dimensionality. Moreover, we improve the interpretability of kernel PCA by adding to the plot the representation of the input variables that belong to any dataset. In particular, for each input variable or linear combination of input variables, we can represent the direction of maximum growth locally, which allows us to identify those samples with higher/lower values of the variables analyzed. Conclusions The integration of different datasets and the simultaneous representation of samples and variables together give us a better understanding of biological knowledge. PMID:25032747

The BEL information extraction workflow (BELIEF): evaluation in the BioCreative V BEL and IAT track

PubMed Central

Madan, Sumit; Hodapp, Sven; Senger, Philipp; Ansari, Sam; Szostak, Justyna; Hoeng, Julia; Peitsch, Manuel; Fluck, Juliane

2016-01-01

Network-based approaches have become extremely important in systems biology to achieve a better understanding of biological mechanisms. For network representation, the Biological Expression Language (BEL) is well designed to collate findings from the scientific literature into biological network models. To facilitate encoding and biocuration of such findings in BEL, a BEL Information Extraction Workflow (BELIEF) was developed. BELIEF provides a web-based curation interface, the BELIEF Dashboard, that incorporates text mining techniques to support the biocurator in the generation of BEL networks. The underlying UIMA-based text mining pipeline (BELIEF Pipeline) uses several named entity recognition processes and relationship extraction methods to detect concepts and BEL relationships in literature. The BELIEF Dashboard allows easy curation of the automatically generated BEL statements and their context annotations. Resulting BEL statements and their context annotations can be syntactically and semantically verified to ensure consistency in the BEL network. In summary, the workflow supports experts in different stages of systems biology network building. Based on the BioCreative V BEL track evaluation, we show that the BELIEF Pipeline automatically extracts relationships with an F-score of 36.4% and fully correct statements can be obtained with an F-score of 30.8%. Participation in the BioCreative V Interactive task (IAT) track with BELIEF revealed a systems usability scale (SUS) of 67. Considering the complexity of the task for new users—learning BEL, working with a completely new interface, and performing complex curation—a score so close to the overall SUS average highlights the usability of BELIEF. Database URL: BELIEF is available at http://www.scaiview.com/belief/ PMID:27694210

The BEL information extraction workflow (BELIEF): evaluation in the BioCreative V BEL and IAT track.

PubMed

Madan, Sumit; Hodapp, Sven; Senger, Philipp; Ansari, Sam; Szostak, Justyna; Hoeng, Julia; Peitsch, Manuel; Fluck, Juliane

2016-01-01

Network-based approaches have become extremely important in systems biology to achieve a better understanding of biological mechanisms. For network representation, the Biological Expression Language (BEL) is well designed to collate findings from the scientific literature into biological network models. To facilitate encoding and biocuration of such findings in BEL, a BEL Information Extraction Workflow (BELIEF) was developed. BELIEF provides a web-based curation interface, the BELIEF Dashboard, that incorporates text mining techniques to support the biocurator in the generation of BEL networks. The underlying UIMA-based text mining pipeline (BELIEF Pipeline) uses several named entity recognition processes and relationship extraction methods to detect concepts and BEL relationships in literature. The BELIEF Dashboard allows easy curation of the automatically generated BEL statements and their context annotations. Resulting BEL statements and their context annotations can be syntactically and semantically verified to ensure consistency in the BEL network. In summary, the workflow supports experts in different stages of systems biology network building. Based on the BioCreative V BEL track evaluation, we show that the BELIEF Pipeline automatically extracts relationships with an F-score of 36.4% and fully correct statements can be obtained with an F-score of 30.8%. Participation in the BioCreative V Interactive task (IAT) track with BELIEF revealed a systems usability scale (SUS) of 67. Considering the complexity of the task for new users-learning BEL, working with a completely new interface, and performing complex curation-a score so close to the overall SUS average highlights the usability of BELIEF.Database URL: BELIEF is available at http://www.scaiview.com/belief/. © The Author(s) 2016. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Implementation of protocolized tight control and biological dose optimization in daily clinical practice: results of a pilot study.

PubMed

Lesuis, N; Verhoef, L M; Nieboer, L M; Bruyn, G A; Baudoin, P; van Vollenhoven, R F; Hulscher, Mejl; van den Hoogen, Fhj; den Broeder, A A

2017-03-01

To assess the effects of education, guideline development, and individualized treatment advice on rheumatologist adherence to tight control-based treatment and biological dose optimization in rheumatoid arthritis (RA), psoriatic arthritis (PsA), and spondyloarthropathy (SpA) patients. This pilot study, among two rheumatologists and two specialized nurses in a general hospital, combined education, feedback, local guideline development, and individualized treatment advice. Outcomes (baseline and 1 year post-intervention) were the percentage of patients with a Disease Activity Score in 28 joints (DAS28) or Bath Ankylosing Spondylitis Disease Activity Index (BASDAI) measured during the visit, mean DAS28/BASDAI, and the percentage of patients using a reduced biological dose. DAS28 outcomes only applied to RA and PsA patients, BASDAI outcomes only applied to SpA patients whereas outcomes on biological dose applied to all patients. A total of 232 patients (67% RA, 15% PsA, 18% SpA; 58% female, mean age 56 ± 15 years) were included in the study. The percentage of DAS28 and BASDAI measurements performed increased after the intervention [DAS28 15-51%, odds ratio (OR) 3.3, 95% confidence interval (CI) 2.1-5.5; BASDAI 23-50%, OR 2.2, 95% CI 1.0-5.5], with mean DAS28 and BASDAI scores remaining similar (DAS28: mean difference 0.1, 95% CI -0.3 to 0.5; BASDAI: mean difference 0.03, 95% CI -1.8 to 1.9). Use of a reduced biological dose increased from 10% to 61% (OR 3.9, 95% CI 2.4-6.5). A multicomponent intervention strategy aimed at rheumatologists can lead to improved adherence to tight control-based treatment and a reduction in the use of biologicals in RA, SpA, and PsA patients.

Mosaic, Self-Similarity Logic, and Biological Attraction principles

PubMed Central

Baluška, František; Barlow, Peter W; Guidolin, Diego

2009-01-01

From a structural standpoint, living organisms are organized like a nest of Russian matryoshka dolls, in which structures are buried within one another. From a temporal point of view, this type of organization is the result of a history comprised of a set of time backcloths which have accompanied the passage of living matter from its origins up to the present day. The aim of the present paper is to indicate a possible course of this ‘passage through time, and suggest how today’s complexity has been reached by living organisms. This investigation will employ three conceptual tools, namely the Mosaic, Self-Similarity Logic, and the Biological Attraction principles. Self-Similarity Logic indicates the self-consistency by which elements of a living system interact, irrespective of the spatiotemporal level under consideration. The term Mosaic indicates how, from the same set of elements assembled according to different patterns, it is possible to arrive at completely different constructions: hence, each system becomes endowed with different emergent properties. The Biological Attraction principle states that there is an inherent drive for association and merging of compatible elements at all levels of biological complexity. By analogy with the gravitation law in physics, biological attraction is based on the evidence that each living organism creates an attractive field around itself. This field acts as a sphere of influence that actively attracts similar fields of other biological systems, thereby modifying salient features of the interacting organisms. Three specific organizational levels of living matter, namely the molecular, cellular, and supracellular levels, have been considered in order to analyse and illustrate the interpretative as well as the predictive roles of each of these three explanatory principles. PMID:20195461

Using student motivation to design groups in a non-majors biology course for team-based collaborative learning: Impacts on knowledge, views, attitudes, and perceptions

NASA Astrophysics Data System (ADS)

Walters, Kristi L.

The importance of student motivation and its connection to other learning variables (i.e., attitudes, knowledge, persistence, attendance) is well established. Collaborative work at the undergraduate level has been recognized as a valuable tool in large courses. However, motivation and collaborative group work have rarely been combined. This project utilized student motivation to learn biology to place non-major biology undergraduates in collaborative learning groups at East Carolina University, a mid-sized southeastern American university, to determine the effects of this construct on student learning. A pre-test measuring motivation to learn biology, attitudes toward biology, perceptions of biology and biologists, views of science, and content knowledge was administered. A similar post-test followed as part of the final exam. Two sections of the same introductory biology course (n = 312) were used and students were divided into homogeneous and heterogeneous groups (based on their motivation score). The heterogeneous groups (n = 32) consisted of a mixture of different motivation levels, while the homogeneous groups (n = 32) were organized into teams with similar motivation scores using tiers of high-, middle-, and low-level participants. Data analysis determined mixed perceptions of biology and biologists. These include the perceptions biology was less intriguing, less relevant, less practical, less ethical, and less understandable. Biologists were perceived as being neat and slightly intelligent, but not very altruistic, humane, ethical, logical, honest, or moral. Content knowledge scores more than doubled from pre- to post-test. Half of the items measuring views of science were not statistically significantly different from pre- to post-test. Many of the factors for attitudes toward biology became more agreeable from pre- to post-test. Correlations between motivation scores, participation levels, attendance rates, and final course grades were examined at both the individual and group level. Motivation had low correlations with the other variables. Changes in group membership (i.e., attrition) were evaluated at the group level and showed the highest rates with the heterogeneous groups and the lowest with the homogeneous middle groups. Group gender ratios were examined, but showed no correlation with final course grade. Linear regression was utilized to identify any variables that might be useful in predicting the final course grade of each student. Only participation, attendance, and final exam grade were predictive, but as they were components of the final course grade, they were not useful for the model. Differences between the groups were also examined to determine if the group type was predictive of final course grade, but no significant difference was found. Results of the study are discussed in the context of the literature on student motivation to learn science. Implications of the study are discussed through the lens of the Millennial generation's perspectives on teaching and learning. Millennials often consider an education to be a commodity and may expect results with less effort. Millennials may be expressing a pseudo-intrinsic motivation in order to impress peers and instructors, while they may actually be more extrinsically motivated to succeed

The Role of Multiple Neuromodulators in Reinforcement Learning That Is Based on Competition between Eligibility Traces.

PubMed

Huertas, Marco A; Schwettmann, Sarah E; Shouval, Harel Z

2016-01-01

The ability to maximize reward and avoid punishment is essential for animal survival. Reinforcement learning (RL) refers to the algorithms used by biological or artificial systems to learn how to maximize reward or avoid negative outcomes based on past experiences. While RL is also important in machine learning, the types of mechanistic constraints encountered by biological machinery might be different than those for artificial systems. Two major problems encountered by RL are how to relate a stimulus with a reinforcing signal that is delayed in time (temporal credit assignment), and how to stop learning once the target behaviors are attained (stopping rule). To address the first problem synaptic eligibility traces were introduced, bridging the temporal gap between a stimulus and its reward. Although, these were mere theoretical constructs, recent experiments have provided evidence of their existence. These experiments also reveal that the presence of specific neuromodulators converts the traces into changes in synaptic efficacy. A mechanistic implementation of the stopping rule usually assumes the inhibition of the reward nucleus; however, recent experimental results have shown that learning terminates at the appropriate network state even in setups where the reward nucleus cannot be inhibited. In an effort to describe a learning rule that solves the temporal credit assignment problem and implements a biologically plausible stopping rule, we proposed a model based on two separate synaptic eligibility traces, one for long-term potentiation (LTP) and one for long-term depression (LTD), each obeying different dynamics and having different effective magnitudes. The model has been shown to successfully generate stable learning in recurrent networks. Although, the model assumes the presence of a single neuromodulator, evidence indicates that there are different neuromodulators for expressing the different traces. What could be the role of different neuromodulators for expressing the LTP and LTD traces? Here we expand on our previous model to include several neuromodulators, and illustrate through various examples how different these contribute to learning reward-timing within a wide set of training paradigms and propose further roles that multiple neuromodulators can play in encoding additional information of the rewarding signal.

Identification of nanoparticles and nanosystems in biological matrices with scanning probe microscopy.

PubMed

Angeloni, Livia; Reggente, Melania; Passeri, Daniele; Natali, Marco; Rossi, Marco

2018-04-17

Identification of nanoparticles and nanosystems into cells and biological matrices is a hot research topic in nanobiotechnologies. Because of their capability to map physical properties (mechanical, electric, magnetic, chemical, or optical), several scanning probe microscopy based techniques have been proposed for the subsurface detection of nanomaterials in biological systems. In particular, atomic force microscopy (AFM) can be used to reveal stiff nanoparticles in cells and other soft biomaterials by probing the sample mechanical properties through the acquisition of local indentation curves or through the combination of ultrasound-based methods, like contact resonance AFM (CR-AFM) or scanning near field ultrasound holography. Magnetic force microscopy can detect magnetic nanoparticles and other magnetic (bio)materials in nonmagnetic biological samples, while electric force microscopy, conductive AFM, and Kelvin probe force microscopy can reveal buried nanomaterials on the basis of the differences between their electric properties and those of the surrounding matrices. Finally, scanning near field optical microscopy and tip-enhanced Raman spectroscopy can visualize buried nanostructures on the basis of their optical and chemical properties. Despite at a still early stage, these methods are promising for detection of nanomaterials in biological systems as they could be truly noninvasive, would not require destructive and time-consuming specific sample preparation, could be performed in vitro, on alive samples and in water or physiological environment, and by continuously imaging the same sample could be used to dynamically monitor the diffusion paths and interaction mechanisms of nanomaterials into cells and biological systems. This article is categorized under: Diagnostic Tools > In Vivo Nanodiagnostics and Imaging Nanotechnology Approaches to Biology > Nanoscale Systems in Biology. © 2018 Wiley Periodicals, Inc.

mRNA translation and protein synthesis: an analysis of different modelling methodologies and a new PBN based approach

PubMed Central

2014-01-01

Background mRNA translation involves simultaneous movement of multiple ribosomes on the mRNA and is also subject to regulatory mechanisms at different stages. Translation can be described by various codon-based models, including ODE, TASEP, and Petri net models. Although such models have been extensively used, the overlap and differences between these models and the implications of the assumptions of each model has not been systematically elucidated. The selection of the most appropriate modelling framework, and the most appropriate way to develop coarse-grained/fine-grained models in different contexts is not clear. Results We systematically analyze and compare how different modelling methodologies can be used to describe translation. We define various statistically equivalent codon-based simulation algorithms and analyze the importance of the update rule in determining the steady state, an aspect often neglected. Then a novel probabilistic Boolean network (PBN) model is proposed for modelling translation, which enjoys an exact numerical solution. This solution matches those of numerical simulation from other methods and acts as a complementary tool to analytical approximations and simulations. The advantages and limitations of various codon-based models are compared, and illustrated by examples with real biological complexities such as slow codons, premature termination and feedback regulation. Our studies reveal that while different models gives broadly similiar trends in many cases, important differences also arise and can be clearly seen, in the dependence of the translation rate on different parameters. Furthermore, the update rule affects the steady state solution. Conclusions The codon-based models are based on different levels of abstraction. Our analysis suggests that a multiple model approach to understanding translation allows one to ascertain which aspects of the conclusions are robust with respect to the choice of modelling methodology, and when (and why) important differences may arise. This approach also allows for an optimal use of analysis tools, which is especially important when additional complexities or regulatory mechanisms are included. This approach can provide a robust platform for dissecting translation, and results in an improved predictive framework for applications in systems and synthetic biology. PMID:24576337

CUFID-query: accurate network querying through random walk based network flow estimation.

PubMed

Jeong, Hyundoo; Qian, Xiaoning; Yoon, Byung-Jun

2017-12-28

Functional modules in biological networks consist of numerous biomolecules and their complicated interactions. Recent studies have shown that biomolecules in a functional module tend to have similar interaction patterns and that such modules are often conserved across biological networks of different species. As a result, such conserved functional modules can be identified through comparative analysis of biological networks. In this work, we propose a novel network querying algorithm based on the CUFID (Comparative network analysis Using the steady-state network Flow to IDentify orthologous proteins) framework combined with an efficient seed-and-extension approach. The proposed algorithm, CUFID-query, can accurately detect conserved functional modules as small subnetworks in the target network that are expected to perform similar functions to the given query functional module. The CUFID framework was recently developed for probabilistic pairwise global comparison of biological networks, and it has been applied to pairwise global network alignment, where the framework was shown to yield accurate network alignment results. In the proposed CUFID-query algorithm, we adopt the CUFID framework and extend it for local network alignment, specifically to solve network querying problems. First, in the seed selection phase, the proposed method utilizes the CUFID framework to compare the query and the target networks and to predict the probabilistic node-to-node correspondence between the networks. Next, the algorithm selects and greedily extends the seed in the target network by iteratively adding nodes that have frequent interactions with other nodes in the seed network, in a way that the conductance of the extended network is maximally reduced. Finally, CUFID-query removes irrelevant nodes from the querying results based on the personalized PageRank vector for the induced network that includes the fully extended network and its neighboring nodes. Through extensive performance evaluation based on biological networks with known functional modules, we show that CUFID-query outperforms the existing state-of-the-art algorithms in terms of prediction accuracy and biological significance of the predictions.

Invited review liquid crystal models of biological materials and silk spinning.

PubMed

Rey, Alejandro D; Herrera-Valencia, Edtson E

2012-06-01

A review of thermodynamic, materials science, and rheological liquid crystal models is presented and applied to a wide range of biological liquid crystals, including helicoidal plywoods, biopolymer solutions, and in vivo liquid crystals. The distinguishing characteristics of liquid crystals (self-assembly, packing, defects, functionalities, processability) are discussed in relation to biological materials and the strong correspondence between different synthetic and biological materials is established. Biological polymer processing based on liquid crystalline precursors includes viscoelastic flow to form and shape fibers. Viscoelastic models for nematic and chiral nematics are reviewed and discussed in terms of key parameters that facilitate understanding and quantitative information from optical textures and rheometers. It is shown that viscoelastic modeling the silk spinning process using liquid crystal theories sheds light on textural transitions in the duct of spiders and silk worms as well as on tactoidal drops and interfacial structures. The range and consistency of the predictions demonstrates that the use of mesoscopic liquid crystal models is another tool to develop the science and biomimetic applications of mesogenic biological soft matter. Copyright © 2011 Wiley Periodicals, Inc.

Computational protein design-the next generation tool to expand synthetic biology applications.

PubMed

Gainza-Cirauqui, Pablo; Correia, Bruno Emanuel

2018-05-02

One powerful approach to engineer synthetic biology pathways is the assembly of proteins sourced from one or more natural organisms. However, synthetic pathways often require custom functions or biophysical properties not displayed by natural proteins, limitations that could be overcome through modern protein engineering techniques. Structure-based computational protein design is a powerful tool to engineer new functional capabilities in proteins, and it is beginning to have a profound impact in synthetic biology. Here, we review efforts to increase the capabilities of synthetic biology using computational protein design. We focus primarily on computationally designed proteins not only validated in vitro, but also shown to modulate different activities in living cells. Efforts made to validate computational designs in cells can illustrate both the challenges and opportunities in the intersection of protein design and synthetic biology. We also highlight protein design approaches, which although not validated as conveyors of new cellular function in situ, may have rapid and innovative applications in synthetic biology. We foresee that in the near-future, computational protein design will vastly expand the functional capabilities of synthetic cells. Copyright © 2018. Published by Elsevier Ltd.

Interactive and coordinated visualization approaches for biological data analysis.

PubMed

Cruz, António; Arrais, Joel P; Machado, Penousal

2018-03-26

The field of computational biology has become largely dependent on data visualization tools to analyze the increasing quantities of data gathered through the use of new and growing technologies. Aside from the volume, which often results in large amounts of noise and complex relationships with no clear structure, the visualization of biological data sets is hindered by their heterogeneity, as data are obtained from different sources and contain a wide variety of attributes, including spatial and temporal information. This requires visualization approaches that are able to not only represent various data structures simultaneously but also provide exploratory methods that allow the identification of meaningful relationships that would not be perceptible through data analysis algorithms alone. In this article, we present a survey of visualization approaches applied to the analysis of biological data. We focus on graph-based visualizations and tools that use coordinated multiple views to represent high-dimensional multivariate data, in particular time series gene expression, protein-protein interaction networks and biological pathways. We then discuss how these methods can be used to help solve the current challenges surrounding the visualization of complex biological data sets.

Enhancing Scientific Communication Through an Undergraduate Biology and Journalism Partnership.

PubMed

Schwingel, Johanna M

2018-01-01

Scientific terminology presents an obstacle to effective communication with nonscientific audiences. To overcome this obstacle, biology majors in a general microbiology elective completed a project involving two different audiences: a scientific audience of their peers and a general, nonscientific audience. First, students presented an overview of a primary research paper and the significance of its findings to a general, nonscientific audience in an elevator-type talk. This was followed by a peer interview with a student in a journalism course, in which the biology students needed to comprehend the article to effectively communicate it to the journalism students, and the journalism students needed to ask questions about an unfamiliar, technical topic. Next, the biology students wrote a summary of their article for a scientific audience. Finally, the students presented a figure from the article to their peers in a scientific, Bio-Minute format. The biology-journalism partnership allowed biology students to develop their ability to communicate scientific information and journalism students their ability to ask appropriate questions and establish a base of knowledge from which to write.

Graphics processing units in bioinformatics, computational biology and systems biology.

PubMed

Nobile, Marco S; Cazzaniga, Paolo; Tangherloni, Andrea; Besozzi, Daniela

2017-09-01

Several studies in Bioinformatics, Computational Biology and Systems Biology rely on the definition of physico-chemical or mathematical models of biological systems at different scales and levels of complexity, ranging from the interaction of atoms in single molecules up to genome-wide interaction networks. Traditional computational methods and software tools developed in these research fields share a common trait: they can be computationally demanding on Central Processing Units (CPUs), therefore limiting their applicability in many circumstances. To overcome this issue, general-purpose Graphics Processing Units (GPUs) are gaining an increasing attention by the scientific community, as they can considerably reduce the running time required by standard CPU-based software, and allow more intensive investigations of biological systems. In this review, we present a collection of GPU tools recently developed to perform computational analyses in life science disciplines, emphasizing the advantages and the drawbacks in the use of these parallel architectures. The complete list of GPU-powered tools here reviewed is available at http://bit.ly/gputools. © The Author 2016. Published by Oxford University Press.

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

PubMed

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

2018-04-10

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

Community-Reviewed Biological Network Models for Toxicology and Drug Discovery Applications

PubMed Central

Namasivayam, Aishwarya Alex; Morales, Alejandro Ferreiro; Lacave, Ángela María Fajardo; Tallam, Aravind; Simovic, Borislav; Alfaro, David Garrido; Bobbili, Dheeraj Reddy; Martin, Florian; Androsova, Ganna; Shvydchenko, Irina; Park, Jennifer; Calvo, Jorge Val; Hoeng, Julia; Peitsch, Manuel C.; Racero, Manuel González Vélez; Biryukov, Maria; Talikka, Marja; Pérez, Modesto Berraquero; Rohatgi, Neha; Díaz-Díaz, Noberto; Mandarapu, Rajesh; Ruiz, Rubén Amián; Davidyan, Sergey; Narayanasamy, Shaman; Boué, Stéphanie; Guryanova, Svetlana; Arbas, Susana Martínez; Menon, Swapna; Xiang, Yang

2016-01-01

Biological network models offer a framework for understanding disease by describing the relationships between the mechanisms involved in the regulation of biological processes. Crowdsourcing can efficiently gather feedback from a wide audience with varying expertise. In the Network Verification Challenge, scientists verified and enhanced a set of 46 biological networks relevant to lung and chronic obstructive pulmonary disease. The networks were built using Biological Expression Language and contain detailed information for each node and edge, including supporting evidence from the literature. Network scoring of public transcriptomics data inferred perturbation of a subset of mechanisms and networks that matched the measured outcomes. These results, based on a computable network approach, can be used to identify novel mechanisms activated in disease, quantitatively compare different treatments and time points, and allow for assessment of data with low signal. These networks are periodically verified by the crowd to maintain an up-to-date suite of networks for toxicology and drug discovery applications. PMID:27429547

Biological contributions to addictions in adolescents and adults: prevention, treatment, and policy implications.

PubMed

Potenza, Marc N

2013-02-01

Despite significant advances in our understanding of the biological bases of addictions, these disorders continue to represent a huge public health burden that is associated with substantial personal suffering. Efforts to target addictions require consideration of how the improved biological understanding of addictions may lead to improved prevention, treatment, and policy initiatives. In this article, we provide a narrative review of current biological models for addictions with a goal of placing existing data and theories within a translational and developmental framework targeting the advancement of prevention, treatment, and policy strategies. Data regarding individual differences, intermediary phenotypes, and main and interactive influences of genetic and environmental contributions in the setting of developmental trajectories that may be influenced by addictive drugs or behavior indicate complex underpinnings of addictions. Consideration and further elucidation of the biological etiologies of addictions hold significant potential for making important gains and reducing the public health impact of addictions. Copyright © 2013 Society for Adolescent Health and Medicine. Published by Elsevier Inc. All rights reserved.

Biological Contributions to Addictions in Adolescents and Adults: Prevention, Treatment and Policy Implications

PubMed Central

Potenza, Marc N.

2012-01-01

Purpose Despite significant advances in our understanding of the biological bases of addictions, these disorders continue to represent a huge public health burden that is associated with substantial personal suffering. Efforts to target addictions require consideration of how the improved biological understanding of addictions may lead to improved prevention, treatment and policy initiatives. Method In this article, we provide a narrative review of current biological models for addictions with a goal of placing existing data and theories within a translational and developmental framework targeting the advancement of prevention, treatment and policy strategies. Results Data regarding individual differences, intermediary phenotypes, and main and interactive influences of genetic and environmental contributions in the setting of developmental trajectories that may be influenced by addictive drugs or behavior indicate complex underpinnings of addictions. Conclusions Consideration and further elucidation of the biological etiologies of addictions hold significant potential for making important gains and reducing the public health impact of addictions. PMID:23332567

Comparative systems biology between human and animal models based on next-generation sequencing methods.

PubMed

Zhao, Yu-Qi; Li, Gong-Hua; Huang, Jing-Fei

2013-04-01

Animal models provide myriad benefits to both experimental and clinical research. Unfortunately, in many situations, they fall short of expected results or provide contradictory results. In part, this can be the result of traditional molecular biological approaches that are relatively inefficient in elucidating underlying molecular mechanism. To improve the efficacy of animal models, a technological breakthrough is required. The growing availability and application of the high-throughput methods make systematic comparisons between human and animal models easier to perform. In the present study, we introduce the concept of the comparative systems biology, which we define as "comparisons of biological systems in different states or species used to achieve an integrated understanding of life forms with all their characteristic complexity of interactions at multiple levels". Furthermore, we discuss the applications of RNA-seq and ChIP-seq technologies to comparative systems biology between human and animal models and assess the potential applications for this approach in the future studies.

Alignment-free protein interaction network comparison

PubMed Central

Ali, Waqar; Rito, Tiago; Reinert, Gesine; Sun, Fengzhu; Deane, Charlotte M.

2014-01-01

Motivation: Biological network comparison software largely relies on the concept of alignment where close matches between the nodes of two or more networks are sought. These node matches are based on sequence similarity and/or interaction patterns. However, because of the incomplete and error-prone datasets currently available, such methods have had limited success. Moreover, the results of network alignment are in general not amenable for distance-based evolutionary analysis of sets of networks. In this article, we describe Netdis, a topology-based distance measure between networks, which offers the possibility of network phylogeny reconstruction. Results: We first demonstrate that Netdis is able to correctly separate different random graph model types independent of network size and density. The biological applicability of the method is then shown by its ability to build the correct phylogenetic tree of species based solely on the topology of current protein interaction networks. Our results provide new evidence that the topology of protein interaction networks contains information about evolutionary processes, despite the lack of conservation of individual interactions. As Netdis is applicable to all networks because of its speed and simplicity, we apply it to a large collection of biological and non-biological networks where it clusters diverse networks by type. Availability and implementation: The source code of the program is freely available at http://www.stats.ox.ac.uk/research/proteins/resources. Contact: w.ali@stats.ox.ac.uk Supplementary information: Supplementary data are available at Bioinformatics online. PMID:25161230

Attractiveness of facial averageness and symmetry in non-western cultures: in search of biologically based standards of beauty.

PubMed

Rhodes, G; Yoshikawa, S; Clark, A; Lee, K; McKay, R; Akamatsu, S

2001-01-01

Averageness and symmetry are attractive in Western faces and are good candidates for biologically based standards of beauty. A hallmark of such standards is that they are shared across cultures. We examined whether facial averageness and symmetry are attractive in non-Western cultures. Increasing the averageness of individual faces, by warping those faces towards an averaged composite of the same race and sex, increased the attractiveness of both Chinese (experiment 1) and Japanese (experiment 2) faces, for Chinese and Japanese participants, respectively. Decreasing averageness by moving the faces away from an average shape decreased attractiveness. We also manipulated the symmetry of Japanese faces by blending each original face with its mirror image to create perfectly symmetric versions. Japanese raters preferred the perfectly symmetric versions to the original faces (experiment 2). These findings show that preferences for facial averageness and symmetry are not restricted to Western cultures, consistent with the view that they are biologically based. Interestingly, it made little difference whether averageness was manipulated by using own-race or other-race averaged composites and there was no preference for own-race averaged composites over other-race or mixed-race composites (experiment 1). We discuss the implications of these results for understanding what makes average faces attractive. We also discuss some limitations of our studies, and consider other lines of converging evidence that may help determine whether preferences for average and symmetric faces are biologically based.

Impact of Substratum Surface on Microbial Community Structure and Treatment Performance in Biological Aerated Filters

PubMed Central

Kim, Lavane; Pagaling, Eulyn; Zuo, Yi Y.

2014-01-01

The impact of substratum surface property change on biofilm community structure was investigated using laboratory biological aerated filter (BAF) reactors and molecular microbial community analysis. Two substratum surfaces that differed in surface properties were created via surface coating and used to develop biofilms in test (modified surface) and control (original surface) BAF reactors. Microbial community analysis by 16S rRNA gene-based PCR-denaturing gradient gel electrophoresis (DGGE) showed that the surface property change consistently resulted in distinct profiles of microbial populations during replicate reactor start-ups. Pyrosequencing of the bar-coded 16S rRNA gene amplicons surveyed more than 90% of the microbial diversity in the microbial communities and identified 72 unique bacterial species within 19 bacterial orders. Among the 19 orders of bacteria detected, Burkholderiales and Rhodocyclales of the Betaproteobacteria class were numerically dominant and accounted for 90.5 to 97.4% of the sequence reads, and their relative abundances in the test and control BAF reactors were different in consistent patterns during the two reactor start-ups. Three of the five dominant bacterial species also showed consistent relative abundance changes between the test and control BAF reactors. The different biofilm microbial communities led to different treatment efficiencies, with consistently higher total organic carbon (TOC) removal in the test reactor than in the control reactor. Further understanding of how surface properties affect biofilm microbial communities and functional performance would enable the rational design of new generations of substrata for the improvement of biofilm-based biological treatment processes. PMID:24141134

Dendritic Cells in the Context of Human Tumors: Biology and Experimental Tools.

PubMed

Volovitz, Ilan; Melzer, Susanne; Amar, Sarah; Bocsi, József; Bloch, Merav; Efroni, Sol; Ram, Zvi; Tárnok, Attila

2016-01-01

Dendritic cells (DC) are the most potent and versatile antigen-presenting cells (APC) in the immune system. DC have an exceptional ability to comprehend the immune context of a captured antigen based on molecular signals identified from its vicinity. The analyzed information is then conveyed to other immune effector cells. Such capability enables DC to play a pivotal role in mediating either an immunogenic response or immune tolerance towards an acquired antigen. This review summarizes current knowledge on DC in the context of human tumors. It covers the basics of human DC biology, elaborating on the different markers, morphology and function of the different subsets of human DC. Human blood-borne DC are comprised of at least three subsets consisting of one plasmacytoid DC (pDC) and two to three myeloid DC (mDC) subsets. Some tissues have unique DC. Each subset has a different phenotype and function and may induce pro-tumoral or anti-tumoral effects. The review also discusses two methods fundamental to the research of DC on the single-cell level: multicolor flow cytometry (FCM) and image-based cytometry (IC). These methods, along with new genomics and proteomics tools, can provide high-resolution information on specific DC subsets and on immune and tumor cells with which they interact. The different layers of collected biological data may then be integrated using Immune-Cytomics modeling approaches. Such novel integrated approaches may help unravel the complex network of cellular interactions that DC carry out within tumors, and may help harness this complex immunological information into the development of more effective treatments for cancer.

Economic Burden and Treatment Patterns of Cycling between Conventional Synthetic Disease-modifying Antirheumatic Drugs Among Biologic-treated Patients with Rheumatoid Arthritis.

PubMed

Betts, Keith A; Griffith, Jenny; Ganguli, Arijit; Li, Nanxin; Douglas, Kevin; Wu, Eric Q

2016-05-01

To assess the economic outcomes and treatment patterns among patients with rheumatoid arthritis (RA) who used 1, 2, or 3 or more conventional synthetic disease-modifying antirheumatic drugs (DMARDs) before receiving a biologic therapy. Adult patients with ≥2 RA diagnoses (International Classification of Diseases, Ninth Revision, Clinical Modification [ICD-9-CM] codes 714.xx) on different dates, ≥1 claim for a conventional synthetic DMARD, and ≥1 claim for a biologic DMARD were identified from a large commercial claims database. The initiation date of the first biologic DMARD was defined as the index date. Based on the number of distinct conventional synthetic DMARDs initiated between the first RA diagnosis and the index date, patients were classified into 3 cohorts: those who used 1, 2, or 3 or more conventional synthetic DMARDs. Baseline characteristics were measured 6 months preindex date and compared between the 3 cohorts. All-cause health care costs (in 2014 US$) were compared during the follow-up period (12 months postbiologic initiation) using multivariable gamma models adjusting for baseline characteristics. Time to discontinuation of the index biologic DMARD and time to switching to a new DMARD were compared using multivariable Cox proportional hazards models. The 1, 2, and 3 or more conventional synthetic DMARD cohorts included 6215; 3227; and 976 patients, respectively. At baseline, patients in the 3 or more conventional synthetic DMARD cohort had the least severe RA, as indicated by the lowest claims-based index for RA severity score (1 vs 2 vs 3 or more = 6.1 vs 5.9 vs 5.8). During the study period, there was a significant association between number of conventional synthetic DMARDs and higher all-cause total health care costs (adjusted mean difference, 1 vs 2: $772; P < 0.001; 2 vs 3 or more: $2390; P < 0.001). The all-cause medical and pharmacy costs were also significantly higher with the increasing number of conventional synthetic DMARDs. Patients who cycled more conventional synthetic DMARDs were also more likely to switch treatment after biologic initiation (1 vs 2: adjusted hazard ratio = 0.89; P = 0.005; 2 vs 3 or more: adjusted hazard ratio = 0.89; P = 0.087). There were no differences in index biologic discontinuation between the 3 cohorts. Patients with RA who cycled more conventional synthetic DMARDs had increased economic burden in the 12 months following biologic initiation and were more likely to switch therapy. These results highlight the importance of timely switching to biologic DMARDs for the treatment of RA. Copyright © 2016 Elsevier HS Journals, Inc. All rights reserved.

Systems Biology, Neuroimaging, Neuropsychology, Neuroconnectivity and Traumatic Brain Injury

PubMed Central

Bigler, Erin D.

2016-01-01

The patient who sustains a traumatic brain injury (TBI) typically undergoes neuroimaging studies, usually in the form of computed tomography (CT) and magnetic resonance imaging (MRI). In most cases the neuroimaging findings are clinically assessed with descriptive statements that provide qualitative information about the presence/absence of visually identifiable abnormalities; though little if any of the potential information in a scan is analyzed in any quantitative manner, except in research settings. Fortunately, major advances have been made, especially during the last decade, in regards to image quantification techniques, especially those that involve automated image analysis methods. This review argues that a systems biology approach to understanding quantitative neuroimaging findings in TBI provides an appropriate framework for better utilizing the information derived from quantitative neuroimaging and its relation with neuropsychological outcome. Different image analysis methods are reviewed in an attempt to integrate quantitative neuroimaging methods with neuropsychological outcome measures and to illustrate how different neuroimaging techniques tap different aspects of TBI-related neuropathology. Likewise, how different neuropathologies may relate to neuropsychological outcome is explored by examining how damage influences brain connectivity and neural networks. Emphasis is placed on the dynamic changes that occur following TBI and how best to capture those pathologies via different neuroimaging methods. However, traditional clinical neuropsychological techniques are not well suited for interpretation based on contemporary and advanced neuroimaging methods and network analyses. Significant improvements need to be made in the cognitive and behavioral assessment of the brain injured individual to better interface with advances in neuroimaging-based network analyses. By viewing both neuroimaging and neuropsychological processes within a systems biology perspective could represent a significant advancement for the field. PMID:27555810

The impact of a prospective survey-based workplace intervention program on employee health, biologic stress markers, and organizational productivity.

PubMed

Anderzén, Ingrid; Arnetz, Bengt B

2005-07-01

To study whether knowledge about psychosocial work indicators and a structured method to implement changes based on such knowledge comprise an effective management tool for enhancing organizational as well as employee health and well-being. White- collar employees representing 22 different work units were assessed before and after a 1-year intervention program. Subjective ratings on health and work environment, biologic markers, absenteeism, and productivity were measured. Significant improvements in performance feedback, participatory management, employeeship, skills development, efficiency, leadership, employee well-being, and work-related exhaustion were identified. The restorative hormone testosterone increased during the intervention and changes correlated with increased overall organizational well-being. Absenteeism decreased and productivity improved. Fact-based psychosocial workplace interventions are suggested to be an important process for enhancing employee well-being as well as organizational performance.

Vertically integrated photonic multichip module architecture for vision applications

NASA Astrophysics Data System (ADS)

Tanguay, Armand R., Jr.; Jenkins, B. Keith; von der Malsburg, Christoph; Mel, Bartlett; Holt, Gary; O'Brien, John D.; Biederman, Irving; Madhukar, Anupam; Nasiatka, Patrick; Huang, Yunsong

2000-05-01

The development of a truly smart camera, with inherent capability for low latency semi-autonomous object recognition, tracking, and optimal image capture, has remained an elusive goal notwithstanding tremendous advances in the processing power afforded by VLSI technologies. These features are essential for a number of emerging multimedia- based applications, including enhanced augmented reality systems. Recent advances in understanding of the mechanisms of biological vision systems, together with similar advances in hybrid electronic/photonic packaging technology, offer the possibility of artificial biologically-inspired vision systems with significantly different, yet complementary, strengths and weaknesses. We describe herein several system implementation architectures based on spatial and temporal integration techniques within a multilayered structure, as well as the corresponding hardware implementation of these architectures based on the hybrid vertical integration of multiple silicon VLSI vision chips by means of dense 3D photonic interconnections.

Physicochemical and biological characterization of SB2, a biosimilar of Remicade® (infliximab)

PubMed Central

Hong, Juyong; Lee, Yuhwa; Lee, Changsoo; Eo, Suhyeon; Kim, Soyeon; Park, Seungkyu; Seo, Donghyuck; Lee, Youngji; Yeon, Soojeong; Bou-Assaf, George; Sosic, Zoran; Zhang, Wei

2017-01-01

ABSTRACT A biosimilar is a biological medicinal product that contains a version of the active substance of an already authorized original biological medicinal product. Biosimilarity to the reference product (RP) in terms of quality characteristics, such as physicochemical and biological properties, safety, and efficacy, based on a comprehensive comparability exercise needs to be established. SB2 (Flixabi® and Renflexis®) is a biosimilar to Remicade® (infliximab). The development of SB2 was performed in accordance with relevant guidelines of the International Conference on Harmonisation, the European Medicines Agency, and the United States Food and Drug Administration. To determine whether critical quality attributes meet quality standards, an extensive characterization test was performed with more than 80 lots of EU- and US-sourced RP. The physicochemical characterization study results revealed that SB2 was similar to the RP. Although a few differences in physicochemical attributes were observed, the evidence from the related literature, structure-activity relationship studies, and comparative biological assays showed that these differences were unlikely to be clinically meaningful. The biological characterization results showed that SB2 was similar to the RP in terms of tumor necrosis factor–α (TNF-α) binding and TNF-α neutralization activities as a main mode of action. SB2 was also similar in Fc-related biological activities including antibody-dependent cell-mediated cytotoxicity, complement-dependent cytotoxicity, neonatal Fc receptor binding, C1q binding, and Fc gamma receptor binding activities. These analytical findings support that SB2 is similar to the RP and also provide confidence of biosimilarity in terms of clinical safety and efficacy. PMID:28005456

Atypical biological motion kinematics are represented by complementary lower-level and top-down processes during imitation learning.

PubMed

Hayes, Spencer J; Dutoy, Chris A; Elliott, Digby; Gowen, Emma; Bennett, Simon J

2016-01-01

Learning a novel movement requires a new set of kinematics to be represented by the sensorimotor system. This is often accomplished through imitation learning where lower-level sensorimotor processes are suggested to represent the biological motion kinematics associated with an observed movement. Top-down factors have the potential to influence this process based on the social context, attention and salience, and the goal of the movement. In order to further examine the potential interaction between lower-level and top-down processes in imitation learning, the aim of this study was to systematically control the mediating effects during an imitation of biological motion protocol. In this protocol, we used non-human agent models that displayed different novel atypical biological motion kinematics, as well as a control model that displayed constant velocity. Importantly the three models had the same movement amplitude and movement time. Also, the motion kinematics were displayed in the presence, or absence, of end-state-targets. Kinematic analyses showed atypical biological motion kinematics were imitated, and that this performance was different from the constant velocity control condition. Although the imitation of atypical biological motion kinematics was not modulated by the end-state-targets, movement time was more accurate in the absence, compared to the presence, of an end-state-target. The fact that end-state targets modulated movement time accuracy, but not biological motion kinematics, indicates imitation learning involves top-down attentional, and lower-level sensorimotor systems, which operate as complementary processes mediated by the environmental context. Copyright © 2015 Elsevier B.V. All rights reserved.

Assessing the biological impact of exposure to environmental surface waters with cell-based lipidomics

EPA Science Inventory

Environmental surface waters often contain a variety of chemical contaminants from different sources including wastewater treatment plants, concentrated animal feeding operations, agricultural runoff and other human-related activities. Exposure to these contaminants may pose a th...

Temperament and Learning Disability

ERIC Educational Resources Information Center

Teglasi, Hedwig; Cohn, Andrea; Meshbesher, Nicole

2004-01-01

The link between learning problems and social-emotional difficulties is well documented and both are associated with temperamental risk factors. Whereas temperament refers to individual differences in biologically based dispositions for responding to and engaging with one's surroundings, developmental outcomes are the products of experiences as…

SynBioSS designer: a web-based tool for the automated generation of kinetic models for synthetic biological constructs

PubMed Central

Weeding, Emma; Houle, Jason

2010-01-01

Modeling tools can play an important role in synthetic biology the same way modeling helps in other engineering disciplines: simulations can quickly probe mechanisms and provide a clear picture of how different components influence the behavior of the whole. We present a brief review of available tools and present SynBioSS Designer. The Synthetic Biology Software Suite (SynBioSS) is used for the generation, storing, retrieval and quantitative simulation of synthetic biological networks. SynBioSS consists of three distinct components: the Desktop Simulator, the Wiki, and the Designer. SynBioSS Designer takes as input molecular parts involved in gene expression and regulation (e.g. promoters, transcription factors, ribosome binding sites, etc.), and automatically generates complete networks of reactions that represent transcription, translation, regulation, induction and degradation of those parts. Effectively, Designer uses DNA sequences as input and generates networks of biomolecular reactions as output. In this paper we describe how Designer uses universal principles of molecular biology to generate models of any arbitrary synthetic biological system. These models are useful as they explain biological phenotypic complexity in mechanistic terms. In turn, such mechanistic explanations can assist in designing synthetic biological systems. We also discuss, giving practical guidance to users, how Designer interfaces with the Registry of Standard Biological Parts, the de facto compendium of parts used in synthetic biology applications. PMID:20639523

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

Lee, Li -Chen; Lu, Jie; Weck, Marcus

In shell cross-linked micelles (SCMs) containing acid sites in the shell and base sites in the core are prepared from amphiphilic poly(2-oxazoline) triblock copolymers. These materials are utilized as two-chamber nanoreactors for a prototypical acid-base bifunctional tandem deacetalization-nitroaldol reaction. Furthermore, the acid and base sites are localized in different regions of the micelle, allowing the two steps in the reaction sequence to largely proceed in separate compartments, akin to the compartmentalization that occurs in biological systems.

Surface Sampling of Spores in Dry-Deposition Aerosols▿

PubMed Central

Edmonds, Jason M.; Collett, Patricia J.; Valdes, Erica R.; Skowronski, Evan W.; Pellar, Gregory J.; Emanuel, Peter A.

2009-01-01

The ability to reliably and reproducibly sample surfaces contaminated with a biological agent is a critical step in measuring the extent of contamination and determining if decontamination steps have been successful. The recovery operations following the 2001 attacks with Bacillus anthracis spores were complicated by the fact that no standard sample collection format or decontamination procedures were established. Recovery efficiencies traditionally have been calculated based upon biological agents which were applied to test surfaces in a liquid format and then allowed to dry prior to sampling tests, which may not be best suited for a real-world event with aerosolized biological agents. In order to ascertain if differences existed between air-dried liquid deposition and biological spores which were allowed to settle on a surface in a dried format, a study was undertaken to determine if differences existed in surface sampling recovery efficiencies for four representative surfaces. Studies were then undertaken to compare sampling efficiencies between liquid spore deposition and aerosolized spores which were allowed to gradually settle under gravity on four different test coupon types. Tests with both types of deposition compared efficiencies of four unique swabbing materials applied to four surfaces with various surface properties. Our studies demonstrate that recovery of liquid-deposited spores differs significantly from recovery of dry aerosol-deposited spores in most instances. Whether the recovery of liquid-deposited spores is overexaggerated or underrepresented with respect to that of aerosol-deposited spores depends upon the surface material being tested. PMID:18997021

Classification of Complete Proteomes of Different Organisms and Protein Sets Based on Their Protein Distributions in Terms of Some Key Attributes of Proteins

DOE PAGES

Guo, Hao-Bo; Ma, Yue; Tuskan, Gerald A.; ...

2018-01-01

The existence of complete genome sequences makes it important to develop different approaches for classification of large-scale data sets and to make extraction of biological insights easier. Here, we propose an approach for classification of complete proteomes/protein sets based on protein distributions on some basic attributes. We demonstrate the usefulness of this approach by determining protein distributions in terms of two attributes: protein lengths and protein intrinsic disorder contents (ID). The protein distributions based on L and ID are surveyed for representative proteome organisms and protein sets from the three domains of life. The two-dimensional maps (designated as fingerprints here)more » from the protein distribution densities in the LD space defined by ln( L ) and ID are then constructed. The fingerprints for different organisms and protein sets are found to be distinct with each other, and they can therefore be used for comparative studies. As a test case, phylogenetic trees have been constructed based on the protein distribution densities in the fingerprints of proteomes of organisms without performing any protein sequence comparison and alignments. The phylogenetic trees generated are biologically meaningful, demonstrating that the protein distributions in the LD space may serve as unique phylogenetic signals of the organisms at the proteome level.« less

Comparison of two screening bioassays, based on the frog sciatic nerve and yeast cells, for the assessment of herbicide toxicity.

PubMed

Papaefthimiou, Chrisovalantis; Cabral, Maria de Guadalupe; Mixailidou, Christina; Viegas, Cristina A; Sá-Correia, Isabel; Theophilidis, George

2004-05-01

Two different test systems, one based on the isolated sciatic nerve of an amphibian and the other on a microbial eukaryote, were used for the assessment of herbicide toxicity. More specifically, we determined the deleterious effects of increasing concentrations of herbicides of different chemical classes (phenoxyacetic acids, triazines, and acetamides), and of 2,4-dichlorophenol (2,4-DCP), a degradation product of the herbicide 2,4-dichlorophenoxyacetic acid (2,4-D), on electrophysiological parameters and the vitality of the axons of the isolated sciatic nerve of the frog (Rana ridibunda) and on the growth curve of the yeast Saccharomyces cerevisiae based on microtiter plate susceptibility assays. The no-observed-effect-concentration (NOEC), defined as the maximum concentration of the tested compound that has no effect on these biological parameters, was estimated. In spite of the different methodological approaches and biological systems compared, the NOEC values were identical and correlated with the lipophilicity of the tested compounds. The relative toxicity established here, 2,4-DCP > alachlor, metolachlor > metribuzin > 2,4-D, 2-methyl-4-chlorophenoxyacetic acid (MCPA), correlates with the toxicity indexes reported in the literature for freshwater organisms. Based on these results, we suggest that the relatively simple, rapid, and low-cost test systems examined here may be of interest as alternative or complementary tests for toxicological assessment of herbicides.

Classification of Complete Proteomes of Different Organisms and Protein Sets Based on Their Protein Distributions in Terms of Some Key Attributes of Proteins

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

Guo, Hao-Bo; Ma, Yue; Tuskan, Gerald A.

The existence of complete genome sequences makes it important to develop different approaches for classification of large-scale data sets and to make extraction of biological insights easier. Here, we propose an approach for classification of complete proteomes/protein sets based on protein distributions on some basic attributes. We demonstrate the usefulness of this approach by determining protein distributions in terms of two attributes: protein lengths and protein intrinsic disorder contents (ID). The protein distributions based on L and ID are surveyed for representative proteome organisms and protein sets from the three domains of life. The two-dimensional maps (designated as fingerprints here)more » from the protein distribution densities in the LD space defined by ln( L ) and ID are then constructed. The fingerprints for different organisms and protein sets are found to be distinct with each other, and they can therefore be used for comparative studies. As a test case, phylogenetic trees have been constructed based on the protein distribution densities in the fingerprints of proteomes of organisms without performing any protein sequence comparison and alignments. The phylogenetic trees generated are biologically meaningful, demonstrating that the protein distributions in the LD space may serve as unique phylogenetic signals of the organisms at the proteome level.« less

Design control considerations for biologic-device combination products.

PubMed

Anderson, Dave; Liu, Roger; Anand Subramony, J; Cammack, Jon

2017-03-01

Combination products are therapeutic and diagnostic medical products that combine drugs, devices, and/or biological products with one another. Historically, biologics development involved identifying efficacious doses administered to patients intravenously or perhaps by a syringe. Until fairly recently, there has been limited focus on developing an accompanying medical device, such as a prefilled syringe or auto-injector, to enable easy and more efficient delivery. For the last several years, and looking forward, where there may be little to distinguish biologics medicines with relatively similar efficacy profiles, the biotechnology market is beginning to differentiate products by patient-focused, biologic-device based combination products. As innovative as biologic-device combination products are, they can pose considerable development, regulatory, and commercialization challenges due to unique physicochemical properties and special clinical considerations (e.g., dosing volumes, frequency, co-medications, etc.) of the biologic medicine. A biologic-device combination product is a marriage between two partners with "cultural differences," so to speak. There are clear differences in the development, review, and commercialization processes of the biologic and the device. When these two cultures come together in a combination product, developers and reviewers must find ways to address the design controls and risk management processes of both the biologic and device, and knit them into a single entity with supporting product approval documentation. Moreover, digital medicine and connected health trends are pushing the boundaries of combination product development and regulations even further. Despite an admirable cooperation between industry and FDA in recent years, unique product configurations and design features have resulted in review challenges. These challenges have prompted agency reviewers to modernize consultation processes, while at the same time, promoting development of innovative, safe and effective combination products. It remains the manufacturer's responsibility to comply with the relevant requirements and regulations, and develop good business practices that clearly describe how these practices comply with FDA's final rule (21 CFR Part 4) and aligns with the company's already established quality system. Copyright © 2017 Elsevier B.V. All rights reserved.

Meta-analysis of pathway enrichment: combining independent and dependent omics data sets.

PubMed

Kaever, Alexander; Landesfeind, Manuel; Feussner, Kirstin; Morgenstern, Burkhard; Feussner, Ivo; Meinicke, Peter

2014-01-01

A major challenge in current systems biology is the combination and integrative analysis of large data sets obtained from different high-throughput omics platforms, such as mass spectrometry based Metabolomics and Proteomics or DNA microarray or RNA-seq-based Transcriptomics. Especially in the case of non-targeted Metabolomics experiments, where it is often impossible to unambiguously map ion features from mass spectrometry analysis to metabolites, the integration of more reliable omics technologies is highly desirable. A popular method for the knowledge-based interpretation of single data sets is the (Gene) Set Enrichment Analysis. In order to combine the results from different analyses, we introduce a methodical framework for the meta-analysis of p-values obtained from Pathway Enrichment Analysis (Set Enrichment Analysis based on pathways) of multiple dependent or independent data sets from different omics platforms. For dependent data sets, e.g. obtained from the same biological samples, the framework utilizes a covariance estimation procedure based on the nonsignificant pathways in single data set enrichment analysis. The framework is evaluated and applied in the joint analysis of Metabolomics mass spectrometry and Transcriptomics DNA microarray data in the context of plant wounding. In extensive studies of simulated data set dependence, the introduced correlation could be fully reconstructed by means of the covariance estimation based on pathway enrichment. By restricting the range of p-values of pathways considered in the estimation, the overestimation of correlation, which is introduced by the significant pathways, could be reduced. When applying the proposed methods to the real data sets, the meta-analysis was shown not only to be a powerful tool to investigate the correlation between different data sets and summarize the results of multiple analyses but also to distinguish experiment-specific key pathways.

Biographer: web-based editing and rendering of SBGN compliant biochemical networks.

PubMed

Krause, Falko; Schulz, Marvin; Ripkens, Ben; Flöttmann, Max; Krantz, Marcus; Klipp, Edda; Handorf, Thomas

2013-06-01

The rapid accumulation of knowledge in the field of Systems Biology during the past years requires advanced, but simple-to-use, methods for the visualization of information in a structured and easily comprehensible manner. We have developed biographer, a web-based renderer and editor for reaction networks, which can be integrated as a library into tools dealing with network-related information. Our software enables visualizations based on the emerging standard Systems Biology Graphical Notation. It is able to import networks encoded in various formats such as SBML, SBGN-ML and jSBGN, a custom lightweight exchange format. The core package is implemented in HTML5, CSS and JavaScript and can be used within any kind of web-based project. It features interactive graph-editing tools and automatic graph layout algorithms. In addition, we provide a standalone graph editor and a web server, which contains enhanced features like web services for the import and export of models and visualizations in different formats. The biographer tool can be used at and downloaded from the web page http://biographer.biologie.hu-berlin.de/. The different software packages, including a server-independent version as well as a web server for Windows and Linux based systems, are available at http://code.google.com/p/biographer/ under the open-source license LGPL

Systems and methods of detecting force and stress using tetrapod nanocrystal

DOEpatents

Choi, Charina L.; Koski, Kristie J.; Sivasankar, Sanjeevi; Alivisatos, A. Paul

2013-08-20

Systems and methods of detecting force on the nanoscale including methods for detecting force using a tetrapod nanocrystal by exposing the tetrapod nanocrystal to light, which produces a luminescent response by the tetrapod nanocrystal. The method continues with detecting a difference in the luminescent response by the tetrapod nanocrystal relative to a base luminescent response that indicates a force between a first and second medium or stresses or strains experienced within a material. Such systems and methods find use with biological systems to measure forces in biological events or interactions.

Effectiveness of Biologic Factors in Shoulder Disorders

PubMed Central

Giotis, Dimitrios; Aryaei, Ashkan; Vasilakakos, Theofanis; Paschos, Nikolaos K.

2017-01-01

Background: Shoulder pathology can cause significant pain, discomfort, and loss of function that all interfere with activities of daily living and may lead to poor quality of life. Primary osteoarthritis and rotator cuff diseases with its sequalae are the main culprits. Management of shoulder disorders using biological factors gained an increasing interest over the last years. This interest reveals the need of effective treatments for shoulder degenerative disorders, and highlights the importance of a comprehensive and detailed understanding of the rapidly increasing knowledge in the field. Methods: This study will describe most of the available biology-based strategies that have been recently developed, focusing on their effectiveness in animal and clinical studies. Results: Data from in vitro work will also be briefly presented; in order to further elucidate newly acquired knowledge regarding mechanisms of tissue degeneration and repair that would probably drive translational work in the next decade. The role of platelet rich-plasma, growth factors, stem cells and other alternative treatments will be described in an evidence-based approach, in an attempt to provide guidelines for their clinical application. Finally, certain challenges that biologic treatments face today will be described as an initiative for future strategies. Conclusion: The application of different growth factors and mesenchymal stem cells appears as promising approaches for enhancing biologic repair. However, data from clinical studies are still limited, and future studies need to improve understanding of the repair process in cellular and molecular level and evaluate the effectiveness of biologic factors in the management of shoulder disorders. PMID:28400884

t4 report1

PubMed Central

Zhu, Hao; Bouhifd, Mounir; Kleinstreuer, Nicole; Kroese, E. Dinant; Liu, Zhichao; Luechtefeld, Thomas; Pamies, David; Shen, Jie; Strauss, Volker; Wu, Shengde; Hartung, Thomas

2016-01-01

Summary Read-across, i.e. filling toxicological data gaps by relating to similar chemicals, for which test data are available, is usually done based on chemical similarity. Besides structure and physico-chemical properties, however, biological similarity based on biological data adds extra strength to this process. In the context of developing Good Read-Across Practice guidance, a number of case studies were evaluated to demonstrate the use of biological data to enrich read-across. In the simplest case, chemically similar substances also show similar test results in relevant in vitro assays. This is a well-established method for the read-across of e.g. genotoxicity assays. Larger datasets of biological and toxicological properties of hundreds and thousands of substances become increasingly available enabling big data approaches in read-across studies. Several case studies using various big data sources are described in this paper. An example is given for the US EPA’s ToxCast dataset allowing read-across for high quality uterotrophic assays for estrogenic endocrine disruption. Similarly, an example for REACH registration data enhancing read-across for acute toxicity studies is given. A different approach is taken using omics data to establish biological similarity: Examples are given for stem cell models in vitro and short-term repeated dose studies in rats in vivo to support read-across and category formation. These preliminary biological data-driven read-across studies highlight the road to the new generation of read-across approaches that can be applied in chemical safety assessment. PMID:26863516

Infrared microspectroscopy of live cells in microfluidic devices (MD-IRMS): toward a powerful label-free cell-based assay.

PubMed

Vaccari, L; Birarda, G; Businaro, L; Pacor, S; Grenci, G

2012-06-05

Until nowadays most infrared microspectroscopy (IRMS) experiments on biological specimens (i.e., tissues or cells) have been routinely carried out on fixed or dried samples in order to circumvent water absorption problems. In this paper, we demonstrate the possibility to widen the range of in-vitro IRMS experiments to vibrational analysis of live cellular samples, thanks to the development of novel biocompatible IR-visible transparent microfluidic devices (MD). In order to highlight the biological relevance of IRMS in MD (MD-IRMS), we performed a systematic exploration of the biochemical alterations induced by different fixation protocols, ethanol 70% and formaldehyde solution 4%, as well as air-drying on U937 leukemic monocytes by comparing their IR vibrational features with the live U937 counterpart. Both fixation and air-drying procedures affected lipid composition and order as well as protein structure at a different extent while they both induced structural alterations in nucleic acids. Therefore, only IRMS of live cells can provide reliable information on both DNA and RNA structure and on their cellular dynamic. In summary, we show that MD-IRMS of live cells is feasible, reliable, and biologically relevant to be recognized as a label-free cell-based assay.

Using Cluster Analysis to Compartmentalize a Large Managed Wetland Based on Physical, Biological, and Climatic Geospatial Attributes.

PubMed

Hahus, Ian; Migliaccio, Kati; Douglas-Mankin, Kyle; Klarenberg, Geraldine; Muñoz-Carpena, Rafael

2018-04-27

Hierarchical and partitional cluster analyses were used to compartmentalize Water Conservation Area 1, a managed wetland within the Arthur R. Marshall Loxahatchee National Wildlife Refuge in southeast Florida, USA, based on physical, biological, and climatic geospatial attributes. Single, complete, average, and Ward's linkages were tested during the hierarchical cluster analyses, with average linkage providing the best results. In general, the partitional method, partitioning around medoids, found clusters that were more evenly sized and more spatially aggregated than those resulting from the hierarchical analyses. However, hierarchical analysis appeared to be better suited to identify outlier regions that were significantly different from other areas. The clusters identified by geospatial attributes were similar to clusters developed for the interior marsh in a separate study using water quality attributes, suggesting that similar factors have influenced variations in both the set of physical, biological, and climatic attributes selected in this study and water quality parameters. However, geospatial data allowed further subdivision of several interior marsh clusters identified from the water quality data, potentially indicating zones with important differences in function. Identification of these zones can be useful to managers and modelers by informing the distribution of monitoring equipment and personnel as well as delineating regions that may respond similarly to future changes in management or climate.

Design of a transdermal delivery system for aspirin as an antithrombotic drug.

PubMed

Ammar, H O; Ghorab, M; El-Nahhas, S A; Kamel, R

2006-12-11

Aspirin has become the gold standard to which newer antiplatelet drugs are compared for reducing risks of cardiovascular diseases, while keeping low cost. Oral aspirin has a repertoire of gastrointestinal side effects even at low doses and requires high frequent dosing because it undergoes extensive presystemic metabolism. Transdermal delivery offers an alternative route that bypasses the gut and may be more convenient and safer for aspirin delivery especially during long-term use. This study comprised formulation of aspirin in different topical bases. Release studies revealed that hydrocarbon gel allowed highest drug release. In vitro permeation studies revealed high drug permeation from hydrocarbon gel. Several chemical penetration enhancers were monitored for augmenting the permeation from this base. Combination of propylene glycol and alcohol showed maximum enhancing effect and, hence, was selected for biological investigation. The biological performance of the selected formulation was assessed by measuring the inhibition of platelet aggregation relevant to different dosage regimens aiming to minimize both drug dose and frequency of application. The results demonstrated the feasibility of successfully influencing platelet function and revealed that the drug therapeutic efficacy in transdermal delivery system is dose independent. Biological performance was re-assessed after storage and the results revealed stability and persistent therapeutic efficacy.

ProtocolNavigator: emulation-based software for the design, documentation and reproduction biological experiments.

PubMed

Khan, Imtiaz A; Fraser, Adam; Bray, Mark-Anthony; Smith, Paul J; White, Nick S; Carpenter, Anne E; Errington, Rachel J

2014-12-01

Experimental reproducibility is fundamental to the progress of science. Irreproducible research decreases the efficiency of basic biological research and drug discovery and impedes experimental data reuse. A major contributing factor to irreproducibility is difficulty in interpreting complex experimental methodologies and designs from written text and in assessing variations among different experiments. Current bioinformatics initiatives either are focused on computational research reproducibility (i.e. data analysis) or laboratory information management systems. Here, we present a software tool, ProtocolNavigator, which addresses the largely overlooked challenges of interpretation and assessment. It provides a biologist-friendly open-source emulation-based tool for designing, documenting and reproducing biological experiments. ProtocolNavigator was implemented in Python 2.7, using the wx module to build the graphical user interface. It is a platform-independent software and freely available from http://protocolnavigator.org/index.html under the GPL v2 license. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Terminal-instar larval systematics and biology of west European species of Ormyridae associated with insect galls (Hymenoptera, Chalcidoidea)

PubMed Central

Gómez, Jose F.; Nieves, María Hernández; Gayubo, Severiano F.; Nieves-Aldrey, Jose Luis

2017-01-01

Abstract A systematic study of the genus Ormyrus (Chalcidoidea, Ormyridae) was conducted based on the morphology and biology of the terminal-instar larvae of ten west European species that are parasitoids of gall wasps and gallflies of the families Cynipidae, Eurytomidae and Tephritidae. The first detailed descriptions are provided of the terminal-instar larvae of these ten species using SEM images to illustrate diagnostic characters with systematic values. A key is provided for the identification of ormyrid larvae associated with galls in Europe, which is based particularly on characters of the head, mouthparts and mandibles. Although only limited informative variation in body shape was found, the setation of the head provided several characters of potential taxonomic value. The larval biology of the ten ormyrid species inhabiting different galls is also summarised. Although Ormyrus larvae are usually solitary idiobiont ectoparasitoids of the host larva of various gall-inhabiting insects, evidence of secondary phytophagy was observed in some species. PMID:28144185

Some biologically active oxovanadium(IV) complexes of triazole derived Schiff bases: their synthesis, characterization and biological properties.

PubMed

Chohan, Zahid H; Sumrra, Sajjad H

2010-10-01

A series of biologically active oxovanadium(IV) complexes of triazole derived Schiff bases L(1)-L(5) have been synthesized and characterized by their physical, analytical, and spectral data. The synthesized ligands potentially act as bidentate, in which the oxygen of furfural and nitrogen of azomethine coordinate with the oxovanadium atom to give a stoichiometry of vanadyl complexes 1:2 (M:L) in a square-pyramidal geometry. In vitro antibacterial and antifungal activities on different species of pathogenic bacteria (E. coli, S. flexneri, P. aeruginosa, S. typhi, S. aureus, and B. subtilis) and fungi (T. longifusus, C. albicans, A. flavus, M. canis, F. solani, and C. glabrata) have been studied. All compounds showed moderate to significant antibacterial activity against one or more bacterial strains and good antifungal activity against most of the fungal strains. The brine shrimp bioassay was also carried out to check the cytotoxicity of coordinated and uncoordinated synthesized compounds.

A systems approach to physiologic evolution: From micelles to consciousness.

PubMed

Torday, John S; Miller, William B

2018-01-01

A systems approach to evolutionary biology offers the promise of an improved understanding of the fundamental principles of life through the effective integration of many biologic disciplines. It is presented that any critical integrative approach to evolutionary development involves a paradigmatic shift in perspective, more than just the engagement of a large number of disciplines. Critical to this differing viewpoint is the recognition that all biological processes originate from the unicellular state and remain permanently anchored to that phase throughout evolutionary development despite their macroscopic appearances. Multicellular eukaryotic development can, therefore, be viewed as a series of connected responses to epiphenomena that proceeds from that base in continuous iterative maintenance of collective cellular homeostatic equipoise juxtaposed against an ever-changing and challenging environment. By following this trajectory of multicellular eukaryotic evolution from within unicellular First Principles of Physiology forward, the mechanistic nature of complex physiology can be identified through a step-wise analysis of a continuous arc of vertebrate evolution based upon serial exaptations. © 2017 Wiley Periodicals, Inc.

Fast gene ontology based clustering for microarray experiments.

PubMed

Ovaska, Kristian; Laakso, Marko; Hautaniemi, Sampsa

2008-11-21

Analysis of a microarray experiment often results in a list of hundreds of disease-associated genes. In order to suggest common biological processes and functions for these genes, Gene Ontology annotations with statistical testing are widely used. However, these analyses can produce a very large number of significantly altered biological processes. Thus, it is often challenging to interpret GO results and identify novel testable biological hypotheses. We present fast software for advanced gene annotation using semantic similarity for Gene Ontology terms combined with clustering and heat map visualisation. The methodology allows rapid identification of genes sharing the same Gene Ontology cluster. Our R based semantic similarity open-source package has a speed advantage of over 2000-fold compared to existing implementations. From the resulting hierarchical clustering dendrogram genes sharing a GO term can be identified, and their differences in the gene expression patterns can be seen from the heat map. These methods facilitate advanced annotation of genes resulting from data analysis.

Molecular engineering of two-photon fluorescent probes for bioimaging applications

NASA Astrophysics Data System (ADS)

Liu, Hong-Wen; Liu, Yongchao; Wang, Peng; Zhang, Xiao-Bing

2017-03-01

During the past two decades, two-photon microscopy (TPM), which utilizes two near-infrared photons as the excitation source, has emerged as a novel, attractive imaging tool for biological research. Compared with one-photon microscopy, TPM offers several advantages, such as lowering background fluorescence in living cells and tissues, reducing photodamage to biosamples, and a photobleaching phenomenon, offering better 3D spatial localization, and increasing penetration depth. Small-molecule-based two-photon fluorescent probes have been well developed for the detection and imaging of various analytes in biological systems. In this review, we will give a general introduction of molecular engineering of two-photon fluorescent probes based on different fluorescence response mechanisms for bioimaging applications during the past decade. Inspired by the desired advantages of small-molecule two-photon fluorescent probes in biological imaging applications, we expect that more attention will be devoted to the development of new two-photon fluorophores and applications of TPM in areas of bioanalysis and disease diagnosis.

Cost-Benefit Analysis for Biological Control Programs That Targeted Insect Pests of Eucalypts in Urban Landscapes of California.

PubMed

Paine, T D; Millar, J G; Hanks, L M; Gould, J; Wang, Q; Daane, K; Dahlsten, D L; Mcpherson, E G

2015-12-01

As well as being planted for wind breaks, landscape trees, and fuel wood, eucalypts are also widely used as urban street trees in California. They now are besieged by exotic insect herbivores of four different feeding guilds. The objective of the current analysis was to determine the return on investment from biological control programs that have targeted these pests. Independent estimates of the total number of eucalypt street trees in California ranged from a high of 476,527 trees (based on tree inventories from 135 California cities) to a low of 190,666 trees (based on 49 tree inventories). Based on a survey of 3,512 trees, the estimated mean value of an individual eucalypt was US$5,978. Thus, the total value of eucalypt street trees in California ranged from more than US$1.0 billion to more than US$2.8 billion. Biological control programs that targeted pests of eucalypts in California have cost US$2,663,097 in extramural grants and University of California salaries. Consequently, the return derived from protecting the value of this resource through the biological control efforts, per dollar expended, ranged from US$1,070 for the high estimated number of trees to US$428 for the lower estimate. The analyses demonstrate both the tremendous value of urban street trees, and the benefits that stem from successful biological control programs aimed at preserving these trees. Economic analyses such as this, which demonstrate the substantial rates of return from successful biological control of invasive pests, may play a key role in developing both grass-roots and governmental support for future urban biological control efforts. © The Authors 2015. Published by Oxford University Press on behalf of Entomological Society of America. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Full Monte Carlo-Based Biologic Treatment Plan Optimization System for Intensity Modulated Carbon Ion Therapy on Graphics Processing Unit.

PubMed

Qin, Nan; Shen, Chenyang; Tsai, Min-Yu; Pinto, Marco; Tian, Zhen; Dedes, Georgios; Pompos, Arnold; Jiang, Steve B; Parodi, Katia; Jia, Xun

2018-01-01

One of the major benefits of carbon ion therapy is enhanced biological effectiveness at the Bragg peak region. For intensity modulated carbon ion therapy (IMCT), it is desirable to use Monte Carlo (MC) methods to compute the properties of each pencil beam spot for treatment planning, because of their accuracy in modeling physics processes and estimating biological effects. We previously developed goCMC, a graphics processing unit (GPU)-oriented MC engine for carbon ion therapy. The purpose of the present study was to build a biological treatment plan optimization system using goCMC. The repair-misrepair-fixation model was implemented to compute the spatial distribution of linear-quadratic model parameters for each spot. A treatment plan optimization module was developed to minimize the difference between the prescribed and actual biological effect. We used a gradient-based algorithm to solve the optimization problem. The system was embedded in the Varian Eclipse treatment planning system under a client-server architecture to achieve a user-friendly planning environment. We tested the system with a 1-dimensional homogeneous water case and 3 3-dimensional patient cases. Our system generated treatment plans with biological spread-out Bragg peaks covering the targeted regions and sparing critical structures. Using 4 NVidia GTX 1080 GPUs, the total computation time, including spot simulation, optimization, and final dose calculation, was 0.6 hour for the prostate case (8282 spots), 0.2 hour for the pancreas case (3795 spots), and 0.3 hour for the brain case (6724 spots). The computation time was dominated by MC spot simulation. We built a biological treatment plan optimization system for IMCT that performs simulations using a fast MC engine, goCMC. To the best of our knowledge, this is the first time that full MC-based IMCT inverse planning has been achieved in a clinically viable time frame. Copyright © 2017 Elsevier Inc. All rights reserved.

HAlign-II: efficient ultra-large multiple sequence alignment and phylogenetic tree reconstruction with distributed and parallel computing.

PubMed

Wan, Shixiang; Zou, Quan

2017-01-01

Multiple sequence alignment (MSA) plays a key role in biological sequence analyses, especially in phylogenetic tree construction. Extreme increase in next-generation sequencing results in shortage of efficient ultra-large biological sequence alignment approaches for coping with different sequence types. Distributed and parallel computing represents a crucial technique for accelerating ultra-large (e.g. files more than 1 GB) sequence analyses. Based on HAlign and Spark distributed computing system, we implement a highly cost-efficient and time-efficient HAlign-II tool to address ultra-large multiple biological sequence alignment and phylogenetic tree construction. The experiments in the DNA and protein large scale data sets, which are more than 1GB files, showed that HAlign II could save time and space. It outperformed the current software tools. HAlign-II can efficiently carry out MSA and construct phylogenetic trees with ultra-large numbers of biological sequences. HAlign-II shows extremely high memory efficiency and scales well with increases in computing resource. THAlign-II provides a user-friendly web server based on our distributed computing infrastructure. HAlign-II with open-source codes and datasets was established at http://lab.malab.cn/soft/halign.

Repetition rate dependency of low-density plasma effects during femtosecond-laser-based surgery of biological tissue

NASA Astrophysics Data System (ADS)

Kuetemeyer, K.; Baumgart, J.; Lubatschowski, H.; Heisterkamp, A.

2009-11-01

Femtosecond laser based nanosurgery of biological tissue is usually done in two different regimes. Depending on the application, low kHz repetition rates above the optical breakdown threshold or high MHz repetition rates in the low-density plasma regime are used. In contrast to the well understood optical breakdown, mechanisms leading to dissection below this threshold are not well known due to the complexity of chemical effects with high numbers of interacting molecules. Furthermore, the laser repetition rate may influence their efficiency. In this paper, we present our study on low-density plasma effects in biological tissue depending on repetition rate by static exposure of porcine corneal stroma to femtosecond pulses. We observed a continuous increase of the laser-induced damage with decreasing repetition rate over two orders of magnitude at constant numbers of applied laser pulses or constant laser pulse energies. Therefore, low repetition rates in the kHz regime are advantageous to minimize the total delivered energy to biological tissue during femtosecond laser irradiation. However, due to frequent excessive damage in this regime directly above the threshold, MHz repetition rates are preferable to create nanometer-sized cuts in the low-density plasma regime.

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

PubMed

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

2016-04-05

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

Influence of Different ECM-Like Hydrogels on Neurite Outgrowth Induced by Adipose Tissue-Derived Stem Cells

PubMed Central

Oliveira, E.; Assunção-Silva, R. C.; Teixeira, F. G.

2017-01-01

Mesenchymal stem cells (MSCs) have been proposed for spinal cord injury (SCI) applications due to their capacity to secrete growth factors and vesicles—secretome—that impacts important phenomena in SCI regeneration. To improve MSC survival into SCI sites, hydrogels have been used as transplantation vehicles. Herein, we hypothesized if different hydrogels could interact differently with adipose tissue-derived MSCs (ASCs). The efficacy of three natural hydrogels, gellan gum (functionalized with a fibronectin peptide), collagen, and a hydrogel rich in laminin epitopes (NVR-gel) in promoting neuritogenesis (alone and cocultured with ASCs), was evaluated in the present study. Their impact on ASC survival, metabolic activity, and gene expression was also evaluated. Our results indicated that all hydrogels supported ASC survival and viability, being this more evident for the functionalized GG hydrogels. Moreover, the presence of different ECM-derived biological cues within the hydrogels appears to differently affect the mRNA levels of growth factors involved in neuronal survival, differentiation, and axonal outgrowth. All the hydrogel-based systems supported axonal growth mediated by ASCs, but this effect was more robust in functionalized GG. The data herein presented highlights the importance of biological cues within hydrogel-based biomaterials as possible modulators of ASC secretome and its effects for SCI applications. PMID:29333166

Monkey-based research on human disease: the implications of genetic differences.

PubMed

Bailey, Jarrod

2014-11-01

Assertions that the use of monkeys to investigate human diseases is valid scientifically are frequently based on a reported 90-93% genetic similarity between the species. Critical analyses of the relevance of monkey studies to human biology, however, indicate that this genetic similarity does not result in sufficient physiological similarity for monkeys to constitute good models for research, and that monkey data do not translate well to progress in clinical practice for humans. Salient examples include the failure of new drugs in clinical trials, the highly different infectivity and pathology of SIV/HIV, and poor extrapolation of research on Alzheimer's disease, Parkinson's disease and stroke. The major molecular differences underlying these inter-species phenotypic disparities have been revealed by comparative genomics and molecular biology - there are key differences in all aspects of gene expression and protein function, from chromosome and chromatin structure to post-translational modification. The collective effects of these differences are striking, extensive and widespread, and they show that the superficial similarity between human and monkey genetic sequences is of little benefit for biomedical research. The extrapolation of biomedical data from monkeys to humans is therefore highly unreliable, and the use of monkeys must be considered of questionable value, particularly given the breadth and potential of alternative methods of enquiry that are currently available to scientists. 2014 FRAME.

Fast wavefront optimization for focusing through biological tissue (Conference Presentation)

NASA Astrophysics Data System (ADS)

Blochet, Baptiste; Bourdieu, Laurent; Gigan, Sylvain

2017-02-01

The propagation of light in biological tissues is rapidly dominated by multiple scattering: ballistic light is exponentially attenuated, which limits the penetration depth of conventional microscopy techniques. For coherent light, the recombination of the different scattered paths creates a complex interference: speckle. Recently, different wavefront shaping techniques have been developed to coherently manipulate the speckle. It opens the possibility to focus light through complex media and ultimately to image in them, provided however that the medium can be considered as stationary. We have studied the possibility to focus in and through time-varying biological tissues. Their intrinsic temporal dynamics creates a fast decorrelation of the speckle pattern. Therefore, focusing through biological tissues requires fast wavefront shaping devices, sensors and algorithms. We have investigated the use of a MEMS-based spatial light modulator (SLM) and a fast photodetector, combined with FPGA electronics to implement a closed-loop optimization. Our optimization process is just limited by the temporal dynamics of the SLM (200µs) and the computation time (45µs), thus corresponding to a rate of 4 kHz. To our knowledge, it's the fastest closed loop optimization using phase modulators. We have studied the focusing through colloidal solutions of TiO2 particles in glycerol, allowing tunable temporal stability, and scattering properties similar to biological tissues. We have shown that our set-up fulfills the required characteristics (speed, enhancement) to focus through biological tissues. We are currently investigating the focusing through acute rat brain slices and the memory effect in dynamic scattering media.

Contrasting ENSO types with novel satellite derived ocean phytoplankton biomass

NASA Astrophysics Data System (ADS)

Sharma, P.; Singh, A. M.; Marinov, I.; Kostadinov, T. S.

2016-12-01

Observed variations in community structure and biogeochemical processes in the tropics and the North Atlantic have been linked, in the first order, to the El Niño Southern Oscillation phenomenon (e.g., Bates, 2001; Karl et al., 2001; Di Lorenzo et al., 2010; Di Lorenzo et al., 2013). Current significant technical advances have allowed for the retrieval of biological data from the optical properties of the water via satellite ocean color remote sensing, providing an opportunity for quantifying the relationships between biological and climate indices. Studies have focused in-depth on contrasting flavors of the ENSO types with various physical (e.g., Singh et al. 2011; Turk et al. 2011) and biological (e.g., Radenac et al. 2012) indices. Here, we analyze the impact of different ENSO types on biology via analysis of recently-derived backscattering-based biomass separated into size-groups (Kostadinov et al. 2010, 2016) over the 17-year (1997-2013). We further contrast the responses of biomass with those of chlorophyll (Chl) and particulate inorganic carbon (PIC). We analyze the complex spatial differences in both physical (SST, mixed layer depth, winds) and biological (Chl, total and size-partitioned biomass) variability across the Pacific warm pool and equatorial tongue via simple EOF, combined regression-EOF and Agglomerative Hierarchical Clustering (AHC) analysis. The interannual variability in the physical and biological fields show clear signatures of the Niño cold-tongue (NCT) and Niño warm pool (NWP). Possible mechanisms responsible for these signatures are discussed.

Acid–base bifunctional shell cross-linked micelle nanoreactor for one-pot tandem reaction

DOE PAGES

Lee, Li -Chen; Lu, Jie; Weck, Marcus; ...

2015-12-29

In shell cross-linked micelles (SCMs) containing acid sites in the shell and base sites in the core are prepared from amphiphilic poly(2-oxazoline) triblock copolymers. These materials are utilized as two-chamber nanoreactors for a prototypical acid-base bifunctional tandem deacetalization-nitroaldol reaction. Furthermore, the acid and base sites are localized in different regions of the micelle, allowing the two steps in the reaction sequence to largely proceed in separate compartments, akin to the compartmentalization that occurs in biological systems.

Inference on periodicity of circadian time series.

PubMed

Costa, Maria J; Finkenstädt, Bärbel; Roche, Véronique; Lévi, Francis; Gould, Peter D; Foreman, Julia; Halliday, Karen; Hall, Anthony; Rand, David A

2013-09-01

Estimation of the period length of time-course data from cyclical biological processes, such as those driven by the circadian pacemaker, is crucial for inferring the properties of the biological clock found in many living organisms. We propose a methodology for period estimation based on spectrum resampling (SR) techniques. Simulation studies show that SR is superior and more robust to non-sinusoidal and noisy cycles than a currently used routine based on Fourier approximations. In addition, a simple fit to the oscillations using linear least squares is available, together with a non-parametric test for detecting changes in period length which allows for period estimates with different variances, as frequently encountered in practice. The proposed methods are motivated by and applied to various data examples from chronobiology.

CHOmine: an integrated data warehouse for CHO systems biology and modeling.

PubMed

Gerstl, Matthias P; Hanscho, Michael; Ruckerbauer, David E; Zanghellini, Jürgen; Borth, Nicole

2017-01-01

The last decade has seen a surge in published genome-scale information for Chinese hamster ovary (CHO) cells, which are the main production vehicles for therapeutic proteins. While a single access point is available at www.CHOgenome.org, the primary data is distributed over several databases at different institutions. Currently research is frequently hampered by a plethora of gene names and IDs that vary between published draft genomes and databases making systems biology analyses cumbersome and elaborate. Here we present CHOmine, an integrative data warehouse connecting data from various databases and links to other ones. Furthermore, we introduce CHOmodel, a web based resource that provides access to recently published CHO cell line specific metabolic reconstructions. Both resources allow to query CHO relevant data, find interconnections between different types of data and thus provides a simple, standardized entry point to the world of CHO systems biology. http://www.chogenome.org. © The Author(s) 2017. Published by Oxford University Press.

A novel biological 'twin-father' temporal paradox of General Relativity in a Gödel universe - Where reproductive biology meets theoretical physics.

PubMed

Ashrafian, Hutan

2018-03-01

Several temporal paradoxes exist in physics. These include General Relativity's grandfather and ontological paradoxes and Special Relativity's Langevin-Einstein twin-paradox. General relativity paradoxes can exist due to a Gödel universe that follows Gödel's closed timelike curves solution to Einstein's field equations. A novel biological temporal paradox of General Relativity is proposed based on reproductive biology's phenomenon of heteropaternal fecundation. Herein, dizygotic twins from two different fathers are the result of concomitant fertilization during one menstrual cycle. In this case an Oedipus-like individual exposed to a Gödel closed timelike curve would sire a child during his maternal fertilization cycle. As a consequence of heteropaternal superfecundation, he would father his own dizygotic twin and would therefore generate a new class of autofraternal superfecundation, and by doing so creating a 'twin-father' temporal paradox. Copyright © 2017 Elsevier Ltd. All rights reserved.