Comparing Effects of Biologic Agents in Treating Patients with Rheumatoid Arthritis: A Multiple Treatment Comparison Regression Analysis

PubMed Central

Tvete, Ingunn Fride; Natvig, Bent; Gåsemyr, Jørund; Meland, Nils; Røine, Marianne; Klemp, Marianne

2015-01-01

Rheumatoid arthritis patients have been treated with disease modifying anti-rheumatic drugs (DMARDs) and the newer biologic drugs. We sought to compare and rank the biologics with respect to efficacy. We performed a literature search identifying 54 publications encompassing 9 biologics. We conducted a multiple treatment comparison regression analysis letting the number experiencing a 50% improvement on the ACR score be dependent upon dose level and disease duration for assessing the comparable relative effect between biologics and placebo or DMARD. The analysis embraced all treatment and comparator arms over all publications. Hence, all measured effects of any biologic agent contributed to the comparison of all biologic agents relative to each other either given alone or combined with DMARD. We found the drug effect to be dependent on dose level, but not on disease duration, and the impact of a high versus low dose level was the same for all drugs (higher doses indicated a higher frequency of ACR50 scores). The ranking of the drugs when given without DMARD was certolizumab (ranked highest), etanercept, tocilizumab/ abatacept and adalimumab. The ranking of the drugs when given with DMARD was certolizumab (ranked highest), tocilizumab, anakinra, rituximab, golimumab/ infliximab/ abatacept, adalimumab/ etanercept. Still, all drugs were effective. All biologic agents were effective compared to placebo, with certolizumab the most effective and adalimumab (without DMARD treatment) and adalimumab/ etanercept (combined with DMARD treatment) the least effective. The drugs were in general more effective, except for etanercept, when given together with DMARDs. PMID:26356639

A novel nano-immunoassay method for quantification of proteins from CD138-purified myeloma cells: biological and clinical utility

PubMed Central

Misiewicz-Krzeminska, Irena; Corchete, Luis Antonio; Rojas, Elizabeta A.; Martínez-López, Joaquín; García-Sanz, Ramón; Oriol, Albert; Bladé, Joan; Lahuerta, Juan-José; Miguel, Jesús San; Mateos, María-Victoria; Gutiérrez, Norma C.

2018-01-01

Protein analysis in bone marrow samples from patients with multiple myeloma has been limited by the low concentration of proteins obtained after CD138+ cell selection. A novel approach based on capillary nano-immunoassay could make it possible to quantify dozens of proteins from each myeloma sample in an automated manner. Here we present a method for the accurate and robust quantification of the expression of multiple proteins extracted from CD138-purified multiple myeloma samples frozen in RLT Plus buffer, which is commonly used for nucleic acid preservation and isolation. Additionally, the biological and clinical value of this analysis for a panel of 12 proteins essential to the pathogenesis of multiple myeloma was evaluated in 63 patients with newly diagnosed multiple myeloma. The analysis of the prognostic impact of CRBN/Cereblon and IKZF1/Ikaros mRNA/protein showed that only the protein levels were able to predict progression-free survival of patients; mRNA levels were not associated with prognosis. Interestingly, high levels of Cereblon and Ikaros proteins were associated with longer progression-free survival only in patients who received immunomodulatory drugs and not in those treated with other drugs. In conclusion, the capillary nano-immunoassay platform provides a novel opportunity for automated quantification of the expression of more than 20 proteins in CD138+ primary multiple myeloma samples. PMID:29545347

A novel nano-immunoassay method for quantification of proteins from CD138-purified myeloma cells: biological and clinical utility.

PubMed

Misiewicz-Krzeminska, Irena; Corchete, Luis Antonio; Rojas, Elizabeta A; Martínez-López, Joaquín; García-Sanz, Ramón; Oriol, Albert; Bladé, Joan; Lahuerta, Juan-José; Miguel, Jesús San; Mateos, María-Victoria; Gutiérrez, Norma C

2018-05-01

Protein analysis in bone marrow samples from patients with multiple myeloma has been limited by the low concentration of proteins obtained after CD138 + cell selection. A novel approach based on capillary nano-immunoassay could make it possible to quantify dozens of proteins from each myeloma sample in an automated manner. Here we present a method for the accurate and robust quantification of the expression of multiple proteins extracted from CD138-purified multiple myeloma samples frozen in RLT Plus buffer, which is commonly used for nucleic acid preservation and isolation. Additionally, the biological and clinical value of this analysis for a panel of 12 proteins essential to the pathogenesis of multiple myeloma was evaluated in 63 patients with newly diagnosed multiple myeloma. The analysis of the prognostic impact of CRBN /Cereblon and IKZF1 /Ikaros mRNA/protein showed that only the protein levels were able to predict progression-free survival of patients; mRNA levels were not associated with prognosis. Interestingly, high levels of Cereblon and Ikaros proteins were associated with longer progression-free survival only in patients who received immunomodulatory drugs and not in those treated with other drugs. In conclusion, the capillary nano-immunoassay platform provides a novel opportunity for automated quantification of the expression of more than 20 proteins in CD138 + primary multiple myeloma samples. Copyright © 2018 Ferrata Storti Foundation.

Synthetic biology: tools to design microbes for the production of chemicals and fuels.

PubMed

Seo, Sang Woo; Yang, Jina; Min, Byung Eun; Jang, Sungho; Lim, Jae Hyung; Lim, Hyun Gyu; Kim, Seong Cheol; Kim, Se Yeon; Jeong, Jun Hong; Jung, Gyoo Yeol

2013-11-01

The engineering of biological systems to achieve specific purposes requires design tools that function in a predictable and quantitative manner. Recent advances in the field of synthetic biology, particularly in the programmable control of gene expression at multiple levels of regulation, have increased our ability to efficiently design and optimize biological systems to perform designed tasks. Furthermore, implementation of these designs in biological systems highlights the potential of using these tools to build microbial cell factories for the production of chemicals and fuels. In this paper, we review current developments in the design of tools for controlling gene expression at transcriptional, post-transcriptional and post-translational levels, and consider potential applications of these tools. Copyright © 2013 Elsevier Inc. All rights reserved.

Mobility as an emergent property of biological organization: Insights from experimental evolution.

PubMed

Wallace, Ian J; Garland, Theodore

2016-05-06

Anthropologists accept that mobility is a critical dimension of human culture, one that links economy, technology, and social relations. Less often acknowledged is that mobility depends on complex and dynamic interactions between multiple levels of our biological organization, including anatomy, physiology, neurobiology, and genetics. Here, we describe a novel experimental approach to examining the biological foundations of mobility, using mice from a long-term artificial selection experiment for high levels of voluntary exercise on wheels. In this experiment, mice from selectively bred lines have evolved to run roughly three times as far per day as those from nonselected control lines. We consider three insights gleaned from this experiment as foundational principles for the study of mobility from the perspective of biological evolution. First, an evolutionary change in mobility will necessarily be associated with alterations in biological traits both directly and indirectly connected to mobility. Second, changing mobility will result in trade-offs and constraints among some of the affected traits. Third, multiple solutions exist to altering mobility, so that various combinations of adjustments to traits linked with mobility can achieve the same overall behavioral outcome. We suggest that anthropological knowledge of variation in human mobility might be improved by greater research attention to its biological dimensions. © 2016 Wiley Periodicals, Inc.

Development of the Central Dogma Concept Inventory (CDCI) Assessment Tool.

PubMed

Newman, Dina L; Snyder, Christopher W; Fisk, J Nick; Wright, L Kate

2016-01-01

Scientific teaching requires scientifically constructed, field-tested instruments to accurately evaluate student thinking and gauge teacher effectiveness. We have developed a 23-question, multiple select-format assessment of student understanding of the essential concepts of the central dogma of molecular biology that is appropriate for all levels of undergraduate biology. Questions for the Central Dogma Concept Inventory (CDCI) tool were developed and iteratively revised based on student language and review by experts. The ability of the CDCI to discriminate between levels of understanding of the central dogma is supported by field testing (N= 54), and large-scale beta testing (N= 1733). Performance on the assessment increased with experience in biology; scores covered a broad range and showed no ceiling effect, even with senior biology majors, and pre/posttesting of a single class focused on the central dogma showed significant improvement. The multiple-select format reduces the chances of correct answers by random guessing, allows students at different levels to exhibit the extent of their knowledge, and provides deeper insight into the complexity of student thinking on each theme. To date, the CDCI is the first tool dedicated to measuring student thinking about the central dogma of molecular biology, and version 5 is ready to use. © 2016 D. L. Newman et al. 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).

Gender Gaps in Achievement and Participation in Multiple Introductory Biology Classrooms

ERIC Educational Resources Information Center

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…

ANALYTICAL STRATEGIES FOR ASSESSING CUMULATIVE EFFECTS OF CHEMICAL AND NONCHEMICAL STRESSORS

EPA Science Inventory

The project will assess the relative impact of community-level and individual-level stressors – including multiple chemical, social and psychosocial stressors -- on biologic markers of health effects across neighborhoods and vulnerable populations in Texas City, Texas...

Parallel algorithms for large-scale biological sequence alignment on Xeon-Phi based clusters.

PubMed

Lan, Haidong; Chan, Yuandong; Xu, Kai; Schmidt, Bertil; Peng, Shaoliang; Liu, Weiguo

2016-07-19

Computing alignments between two or more sequences are common operations frequently performed in computational molecular biology. The continuing growth of biological sequence databases establishes the need for their efficient parallel implementation on modern accelerators. This paper presents new approaches to high performance biological sequence database scanning with the Smith-Waterman algorithm and the first stage of progressive multiple sequence alignment based on the ClustalW heuristic on a Xeon Phi-based compute cluster. Our approach uses a three-level parallelization scheme to take full advantage of the compute power available on this type of architecture; i.e. cluster-level data parallelism, thread-level coarse-grained parallelism, and vector-level fine-grained parallelism. Furthermore, we re-organize the sequence datasets and use Xeon Phi shuffle operations to improve I/O efficiency. Evaluations show that our method achieves a peak overall performance up to 220 GCUPS for scanning real protein sequence databanks on a single node consisting of two Intel E5-2620 CPUs and two Intel Xeon Phi 7110P cards. It also exhibits good scalability in terms of sequence length and size, and number of compute nodes for both database scanning and multiple sequence alignment. Furthermore, the achieved performance is highly competitive in comparison to optimized Xeon Phi and GPU implementations. Our implementation is available at https://github.com/turbo0628/LSDBS-mpi .

Stressing Escherichia coli to educate students about research: A CURE to investigate multiple levels of gene regulation.

PubMed

McDonough, Janet; Goudsouzian, Lara K; Papaj, Agllai; Maceli, Ashley R; Klepac-Ceraj, Vanja; Peterson, Celeste N

2017-09-01

Course-based undergraduate research experiences (CUREs) have been shown to increase student retention and learning in the biological sciences. Most CURES cover only one aspect of gene regulation, such as transcriptional control. Here we present a new inquiry-based lab that engages understanding of gene expression from multiple perspectives. Students carry out a forward genetic screen to identify regulators of the stationary phase master regulator RpoS in the model organism Escherichia coli and then use a series of reporter fusions to determine if the regulation is at the level of transcription or the post-transcription level. This easy-to-implement course has been run both as a 9-week long project and a condensed 5-6 week version in three different schools and types of courses. A majority of the genes found in the screen are novel, thus giving students the opportunity to contribute to original findings to the field. Assessments of this CURE show student gains in learning in many knowledge areas. In addition, attitudinal surveys suggest the students are enthusiastic about the screen and their learning about gene regulation. In summary, this lab would be an appropriate addition to an intermediate or advanced level Molecular Biology, Genetics, or Microbiology curriculum. © 2017 by The International Union of Biochemistry and Molecular Biology, 45(5):449-458, 2017. © 2017 The International Union of Biochemistry and Molecular Biology.

Genetic variation and biological activity of isolates of lymantria dispar multiple nucleopolyhedrovirus from north america, europe, and asia

USDA-ARS?s Scientific Manuscript database

Little is known about genetic variation of Lymantria dispar multiple nucleopolyhedrovirus (LdMNPV; Baculoviridae: Alphabaculovirus) at the nucleotide sequence level. To obtain a more comprehensive view of genetic diversity among isolates of LdMNPV, partial sequences of the lef-8 gene were generated...

A highly tunable system for the simultaneous expression of multiple enzymes in Saccharomyces cerevisiae.

PubMed

Ito, Yoichiro; Yamanishi, Mamoru; Ikeuchi, Akinori; Matsuyama, Takashi

2015-01-16

Control of the expression levels of multiple enzymes in transgenic yeasts is essential for the effective production of complex molecules through fermentation. Here, we propose a tunable strategy for the control of expression levels based on the design of terminator regions and other gene-expression control elements in Saccharomyces cerevisiae. Our genome-integrated system, which is capable of producing high expression levels over a wide dynamic range, will broadly enable metabolic engineering and synthetic biology. We demonstrated that the activities of multiple cellulases and the production of ethanol were doubled in a transgenic yeast constructed with our system compared with those achieved with a standard expression system.

Beyond the Cell: Using Multiscalar Topics to Bring Interdisciplinarity into Undergraduate Cellular Biology Courses

PubMed Central

Weber, Carolyn F.

2016-01-01

Western science has grown increasingly reductionistic and, in parallel, the undergraduate life sciences curriculum has become disciplinarily fragmented. While reductionistic approaches have led to landmark discoveries, many of the most exciting scientific advances in the late 20th century have occurred at disciplinary interfaces; work at these interfaces is necessary to manage the world’s looming problems, particularly those that are rooted in cellular-level processes but have ecosystem- and even global-scale ramifications (e.g., nonsustainable agriculture, emerging infectious diseases). Managing such problems requires comprehending whole scenarios and their emergent properties as sums of their multiple facets and complex interrelationships, which usually integrate several disciplines across multiple scales (e.g., time, organization, space). This essay discusses bringing interdisciplinarity into undergraduate cellular biology courses through the use of multiscalar topics. Discussing how cellular-level processes impact large-scale phenomena makes them relevant to everyday life and unites diverse disciplines (e.g., sociology, cell biology, physics) as facets of a single system or problem, emphasizing their connections to core concepts in biology. I provide specific examples of multiscalar topics and discuss preliminary evidence that using such topics may increase students’ understanding of the cell’s position within an ecosystem and how cellular biology interfaces with other disciplines. PMID:27146162

From 'omics to otoliths: responses of an estuarine fish to endocrine disrupting compounds across biological scales.

PubMed

Brander, Susanne M; Connon, Richard E; He, Guochun; Hobbs, James A; Smalling, Kelly L; Teh, Swee J; White, J Wilson; Werner, Inge; Denison, Michael S; Cherr, Gary N

2013-01-01

Endocrine disrupting chemicals (EDCs) cause physiological abnormalities and population decline in fishes. However, few studies have linked environmental EDC exposures with responses at multiple tiers of the biological hierarchy, including population-level effects. To this end, we undertook a four-tiered investigation in the impacted San Francisco Bay estuary with the Mississippi silverside (Menidia audens), a small pelagic fish. This approach demonstrated links between different EDC sources and fish responses at different levels of biological organization. First we determined that water from a study site primarily impacted by ranch run-off had only estrogenic activity in vitro, while water sampled from a site receiving a combination of urban, limited ranch run-off, and treated wastewater effluent had both estrogenic and androgenic activity. Secondly, at the molecular level we found that fish had higher mRNA levels for estrogen-responsive genes at the site where only estrogenic activity was detected but relatively lower expression levels where both estrogenic and androgenic EDCs were detected. Thirdly, at the organism level, males at the site exposed to both estrogens and androgens had significantly lower mean gonadal somatic indices, significantly higher incidence of severe testicular necrosis and altered somatic growth relative to the site where only estrogens were detected. Finally, at the population level, the sex ratio was significantly skewed towards males at the site with measured androgenic and estrogenic activity. Our results suggest that mixtures of androgenic and estrogenic EDCs have antagonistic and potentially additive effects depending on the biological scale being assessed, and that mixtures containing androgens and estrogens may produce unexpected effects. In summary, evaluating EDC response at multiple tiers is necessary to determine the source of disruption (lowest scale, i.e. cell line) and what the ecological impact will be (largest scale, i.e. sex ratio).

Stressing "Escherichia coli" to Educate Students about Research: A CURE to Investigate Multiple Levels of Gene Regulation

ERIC Educational Resources Information Center

McDonough, Janet; Goudsouzian, Lara K.; Papaj, Agllai; Maceli, Ashley R.; Klepac-Ceraj, Vanja; Peterson, Celeste N.

2017-01-01

Course-based undergraduate research experiences (CUREs) have been shown to increase student retention and learning in the biological sciences. Most CURES cover only one aspect of gene regulation, such as transcriptional control. Here we present a new inquiry-based lab that engages understanding of gene expression from multiple perspectives.…

CONTRIBUTIONS OF ESTUARINE HABITAT TYPES TO THE ECOLOGICAL INTEGRITY OF A SMALL COVE

EPA Science Inventory

The U.S. EPA, NHEERL, Atlantic Ecology Division, is investigating ecosystem-level approaches to evaluate ecological integrity at multiple scales. The ultimate goal of our project is to develop an ecosystem-level tool to examine impacts of nitrogen pollution on biological integrit...

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.

Hierarchical analysis of forest bird species-environment relationships in the Oregon Coast Range

Treesearch

Samuel A. Cushman; Kevin McGarigal

2004-01-01

Species in biological communities respond to environmental variation simultaneously across a range of organizational levels. Accordingly, it is important to quantify the effects of environmental factors at multiple levels on species distribution and abundance. Hierarchical methods that explicitly separate the independent and confounded influences of environmental...

Effects of imputation on correlation: implications for analysis of mass spectrometry data from multiple biological matrices.

PubMed

Taylor, Sandra L; Ruhaak, L Renee; Kelly, Karen; Weiss, Robert H; Kim, Kyoungmi

2017-03-01

With expanded access to, and decreased costs of, mass spectrometry, investigators are collecting and analyzing multiple biological matrices from the same subject such as serum, plasma, tissue and urine to enhance biomarker discoveries, understanding of disease processes and identification of therapeutic targets. Commonly, each biological matrix is analyzed separately, but multivariate methods such as MANOVAs that combine information from multiple biological matrices are potentially more powerful. However, mass spectrometric data typically contain large amounts of missing values, and imputation is often used to create complete data sets for analysis. The effects of imputation on multiple biological matrix analyses have not been studied. We investigated the effects of seven imputation methods (half minimum substitution, mean substitution, k-nearest neighbors, local least squares regression, Bayesian principal components analysis, singular value decomposition and random forest), on the within-subject correlation of compounds between biological matrices and its consequences on MANOVA results. Through analysis of three real omics data sets and simulation studies, we found the amount of missing data and imputation method to substantially change the between-matrix correlation structure. The magnitude of the correlations was generally reduced in imputed data sets, and this effect increased with the amount of missing data. Significant results from MANOVA testing also were substantially affected. In particular, the number of false positives increased with the level of missing data for all imputation methods. No one imputation method was universally the best, but the simple substitution methods (Half Minimum and Mean) consistently performed poorly. © The Author 2016. Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

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

PubMed

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

2012-01-01

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

The molecular biology capstone assessment: a concept assessment for upper-division molecular biology students.

PubMed

Couch, Brian A; Wood, William B; Knight, Jennifer K

2015-03-02

Measuring students' conceptual understandings has become increasingly important to biology faculty members involved in evaluating and improving departmental programs. We developed the Molecular Biology Capstone Assessment (MBCA) to gauge comprehension of fundamental concepts in molecular and cell biology and the ability to apply these concepts in novel scenarios. Targeted at graduating students, the MBCA consists of 18 multiple-true/false (T/F) questions. Each question consists of a narrative stem followed by four T/F statements, which allows a more detailed assessment of student understanding than the traditional multiple-choice format. Questions were iteratively developed with extensive faculty and student feedback, including validation through faculty reviews and response validation through student interviews. The final assessment was taken online by 504 students in upper-division courses at seven institutions. Data from this administration indicate that the MBCA has acceptable levels of internal reliability (α=0.80) and test-retest stability (r=0.93). Students achieved a wide range of scores with a 67% overall average. Performance results suggest that students have an incomplete understanding of many molecular biology concepts and continue to hold incorrect conceptions previously documented among introductory-level students. By pinpointing areas of conceptual difficulty, the MBCA can provide faculty members with guidance for improving undergraduate biology programs. © 2015 B. A. Couch et al. CBE—Life Sciences Education © 2015 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).

Multiscale modeling of mucosal immune responses

PubMed Central

2015-01-01

Computational modeling techniques are playing increasingly important roles in advancing a systems-level mechanistic understanding of biological processes. Computer simulations guide and underpin experimental and clinical efforts. This study presents ENteric Immune Simulator (ENISI), a multiscale modeling tool for modeling the mucosal immune responses. ENISI's modeling environment can simulate in silico experiments from molecular signaling pathways to tissue level events such as tissue lesion formation. ENISI's architecture integrates multiple modeling technologies including ABM (agent-based modeling), ODE (ordinary differential equations), SDE (stochastic modeling equations), and PDE (partial differential equations). This paper focuses on the implementation and developmental challenges of ENISI. A multiscale model of mucosal immune responses during colonic inflammation, including CD4+ T cell differentiation and tissue level cell-cell interactions was developed to illustrate the capabilities, power and scope of ENISI MSM. Background Computational techniques are becoming increasingly powerful and modeling tools for biological systems are of greater needs. Biological systems are inherently multiscale, from molecules to tissues and from nano-seconds to a lifespan of several years or decades. ENISI MSM integrates multiple modeling technologies to understand immunological processes from signaling pathways within cells to lesion formation at the tissue level. This paper examines and summarizes the technical details of ENISI, from its initial version to its latest cutting-edge implementation. Implementation Object-oriented programming approach is adopted to develop a suite of tools based on ENISI. Multiple modeling technologies are integrated to visualize tissues, cells as well as proteins; furthermore, performance matching between the scales is addressed. Conclusion We used ENISI MSM for developing predictive multiscale models of the mucosal immune system during gut inflammation. Our modeling predictions dissect the mechanisms by which effector CD4+ T cell responses contribute to tissue damage in the gut mucosa following immune dysregulation. PMID:26329787

Multiscale modeling of mucosal immune responses.

PubMed

Mei, Yongguo; Abedi, Vida; Carbo, Adria; Zhang, Xiaoying; Lu, Pinyi; Philipson, Casandra; Hontecillas, Raquel; Hoops, Stefan; Liles, Nathan; Bassaganya-Riera, Josep

2015-01-01

Computational techniques are becoming increasingly powerful and modeling tools for biological systems are of greater needs. Biological systems are inherently multiscale, from molecules to tissues and from nano-seconds to a lifespan of several years or decades. ENISI MSM integrates multiple modeling technologies to understand immunological processes from signaling pathways within cells to lesion formation at the tissue level. This paper examines and summarizes the technical details of ENISI, from its initial version to its latest cutting-edge implementation. Object-oriented programming approach is adopted to develop a suite of tools based on ENISI. Multiple modeling technologies are integrated to visualize tissues, cells as well as proteins; furthermore, performance matching between the scales is addressed. We used ENISI MSM for developing predictive multiscale models of the mucosal immune system during gut inflammation. Our modeling predictions dissect the mechanisms by which effector CD4+ T cell responses contribute to tissue damage in the gut mucosa following immune dysregulation.Computational modeling techniques are playing increasingly important roles in advancing a systems-level mechanistic understanding of biological processes. Computer simulations guide and underpin experimental and clinical efforts. This study presents ENteric Immune Simulator (ENISI), a multiscale modeling tool for modeling the mucosal immune responses. ENISI's modeling environment can simulate in silico experiments from molecular signaling pathways to tissue level events such as tissue lesion formation. ENISI's architecture integrates multiple modeling technologies including ABM (agent-based modeling), ODE (ordinary differential equations), SDE (stochastic modeling equations), and PDE (partial differential equations). This paper focuses on the implementation and developmental challenges of ENISI. A multiscale model of mucosal immune responses during colonic inflammation, including CD4+ T cell differentiation and tissue level cell-cell interactions was developed to illustrate the capabilities, power and scope of ENISI MSM.

Systems Epidemiology: What’s in a Name?

PubMed Central

Dammann, O.; Gray, P.; Gressens, P.; Wolkenhauer, O.; Leviton, A.

2014-01-01

Systems biology is an interdisciplinary effort to integrate molecular, cellular, tissue, organ, and organism levels of function into computational models that facilitate the identification of general principles. Systems medicine adds a disease focus. Systems epidemiology adds yet another level consisting of antecedents that might contribute to the disease process in populations. In etiologic and prevention research, systems-type thinking about multiple levels of causation will allow epidemiologists to identify contributors to disease at multiple levels as well as their interactions. In public health, systems epidemiology will contribute to the improvement of syndromic surveillance methods. We encourage the creation of computational simulation models that integrate information about disease etiology, pathogenetic data, and the expertise of investigators from different disciplines. PMID:25598870

Intimate partner violence: the role of the relationship between perpetrators and children who witness violence.

PubMed

Israel, Emily; Stover, Carla

2009-10-01

The issue of the father-child relationship has been greatly ignored in the domestic violence research literature. This study investigated whether intimate partner violence (IPV) perpetrated by biological fathers resulted in higher levels of posttraumatic stress symptoms and behavior problems than violence perpetrated by nonbiological fathers and whether children who witnessed violence perpetrated by multiple father figures had increased levels of posttraumatic stress disorder and behavioral symptoms. Eighty mothers who experienced domestic incidents completed the Child Behavior Checklist (CBCL) and the University of California at Los Angeles Posttraumatic Stress Disorder Reaction Index (PTSD-RI) for their children aged 2 to 18. Children with multiple violent father figures had significantly more symptoms on the CBCL than children in the other two research groups while controlling for maternal symptoms and trauma history. There were no significant differences between the biological and nonbiological father groups or among the three groups on the PTSD-RI.

The social neuroscience and the theory of integrative levels.

PubMed

Bello-Morales, Raquel; Delgado-García, José María

2015-01-01

The theory of integrative levels provides a general description of the evolution of matter through successive orders of complexity and integration. Along its development, material forms pass through different levels of organization, such as physical, chemical, biological or sociological. The appearance of novel structures and dynamics during this process of development of matter in complex systems has been called emergence. Social neuroscience (SN), an interdisciplinary field that aims to investigate the biological mechanisms that underlie social structures, processes, and behavior and the influences between social and biological levels of organization, has affirmed the necessity for including social context as an essential element to understand the human behavior. To do this, SN proposes a multilevel integrative approach by means of three principles: multiple determinism, nonadditive determinism and reciprocal determinism. These theoretical principles seem to share the basic tenets of the theory of integrative levels but, in this paper, we aim to reveal the differences among both doctrines. First, SN asserts that combination of neural and social variables can produce emergent phenomena that would not be predictable from a neuroscientific or social psychological analysis alone; SN also suggests that to achieve a complete understanding of social structures we should use an integrative analysis that encompasses levels of organization ranging from the genetic level to the social one; finally, SN establishes that there can be mutual influences between biological and social factors in determining behavior, accepting, therefore, a double influence, upward from biology to social level, and downward, from social level to biology. In contrast, following the theory of integrative levels, emergent phenomena are not produced by the combination of variables from two levels, but by the increment of complexity at one level. In addition, the social behavior and structures might be contemplated not as the result of mixing or summing social and biological influences, but as emergent phenomena that should be described with its own laws. Finally, following the integrative levels view, influences upward, from biology to social level, and downward, from social level to biology, might not be equivalent, since the bottom-up processes are emergent and the downward causation (DC) is not.

The social neuroscience and the theory of integrative levels

PubMed Central

Bello-Morales, Raquel; Delgado-García, José María

2015-01-01

The theory of integrative levels provides a general description of the evolution of matter through successive orders of complexity and integration. Along its development, material forms pass through different levels of organization, such as physical, chemical, biological or sociological. The appearance of novel structures and dynamics during this process of development of matter in complex systems has been called emergence. Social neuroscience (SN), an interdisciplinary field that aims to investigate the biological mechanisms that underlie social structures, processes, and behavior and the influences between social and biological levels of organization, has affirmed the necessity for including social context as an essential element to understand the human behavior. To do this, SN proposes a multilevel integrative approach by means of three principles: multiple determinism, nonadditive determinism and reciprocal determinism. These theoretical principles seem to share the basic tenets of the theory of integrative levels but, in this paper, we aim to reveal the differences among both doctrines. First, SN asserts that combination of neural and social variables can produce emergent phenomena that would not be predictable from a neuroscientific or social psychological analysis alone; SN also suggests that to achieve a complete understanding of social structures we should use an integrative analysis that encompasses levels of organization ranging from the genetic level to the social one; finally, SN establishes that there can be mutual influences between biological and social factors in determining behavior, accepting, therefore, a double influence, upward from biology to social level, and downward, from social level to biology. In contrast, following the theory of integrative levels, emergent phenomena are not produced by the combination of variables from two levels, but by the increment of complexity at one level. In addition, the social behavior and structures might be contemplated not as the result of mixing or summing social and biological influences, but as emergent phenomena that should be described with its own laws. Finally, following the integrative levels view, influences upward, from biology to social level, and downward, from social level to biology, might not be equivalent, since the bottom-up processes are emergent and the downward causation (DC) is not. PMID:26578909

Metastable coexistence of multiple genotypes in a constant environment with a single resource through fixed settings of a multiplication-survival trade-off.

PubMed

Maharjan, Ram; Ferenci, Thomas

2016-04-01

The biological complexity of trade-offs has been a major obstacle in understanding bacterial diversity and coexistence. Here we reduce the biological complexity by using isogenic Escherichia coli strains differing only in a multiplication-survival trade-off regulated by RpoS. The contribution of trade-off characteristics to fitness in different environments was determined. We then designed an environment with intermediate-stress levels that elicits an equivalent fitness. We found metastable coexistence of three strains in steady-state chemostats until mutations changed the relative fitness of competing strains. Our results help explain the rich intra- and inter-species diversity of bacteria through alternative settings of relatively few trade-offs. Copyright © 2015 Institut Pasteur. Published by Elsevier Masson SAS. All rights reserved.

Does sufficient evidence exist to support a causal association between vitamin D status and cardiovascular disease risk? An assessment using Hill's criteria for causality.

PubMed

Weyland, Patricia G; Grant, William B; Howie-Esquivel, Jill

2014-09-02

Serum 25-hydroxyvitamin D (25(OH)D) levels have been found to be inversely associated with both prevalent and incident cardiovascular disease (CVD) risk factors; dyslipidemia, hypertension and diabetes mellitus. This review looks for evidence of a causal association between low 25(OH)D levels and increased CVD risk. We evaluated journal articles in light of Hill's criteria for causality in a biological system. The results of our assessment are as follows. Strength of association: many randomized controlled trials (RCTs), prospective and cross-sectional studies found statistically significant inverse associations between 25(OH)D levels and CVD risk factors. Consistency of observed association: most studies found statistically significant inverse associations between 25(OH)D levels and CVD risk factors in various populations, locations and circumstances. Temporality of association: many RCTs and prospective studies found statistically significant inverse associations between 25(OH)D levels and CVD risk factors. Biological gradient (dose-response curve): most studies assessing 25(OH)D levels and CVD risk found an inverse association exhibiting a linear biological gradient. Plausibility of biology: several plausible cellular-level causative mechanisms and biological pathways may lead from a low 25(OH)D level to increased risk for CVD with mediators, such as dyslipidemia, hypertension and diabetes mellitus. Experimental evidence: some well-designed RCTs found increased CVD risk factors with decreasing 25(OH)D levels. Analogy: the association between serum 25(OH)D levels and CVD risk is analogous to that between 25(OH)D levels and the risk of overall cancer, periodontal disease, multiple sclerosis and breast cancer. all relevant Hill criteria for a causal association in a biological system are satisfied to indicate a low 25(OH)D level as a CVD risk factor.

Dissociative semantic breakdown in Alzheimer's disease: evidence from multiple category fluency test.

PubMed

Ting, Simon Kang Seng; Hameed, Shahul; Earnest, Arul; Tan, Eng-King

2013-07-01

Category-specific semantic dissociation particularly in terms of biological and non-biological dichotomy has been described in Alzheimer's disease (AD). We re-examine above finding by performing multiple superordinate category verbal fluency test in AD patients. We analyze the baseline neuropsychological assessment performance of food and animal fluency test of AD patients from a tertiary hospital that collected prospectively over 5 years period and correlation was calculated by Kappa test. The analysis is stratified according to literacy level (primary: 0-6 years education and secondary: >6 years education) and disease severity (MMSE score: mild 19-24, moderate 13-18 and severe <13). A total of 296 AD patients were analyzed and only fair to moderate agreement between food and animal category fluency test was found especially in the mild AD cases (primary: kappa 0.42; secondary: kappa 0.40). Kappa agreement level increases when disease progress especially in the secondary education group. Food category, which is a more relevant semantic knowledge to Singapore population, is generally more affected. Higher educated subjects appeared to have less semantic dissociation effect when disease progress. Despite less primed in daily life, biological category of semantic knowledge appears to be affected less during AD process in highly urbanized Singapore society. Brain appears to have special protective mechanism towards living things. However, education level seems have a modulation effect towards the biological protective mechanism. Copyright © 2012 Elsevier B.V. All rights reserved.

Clinical and biological features of multiple myeloma involving the gastrointestinal system.

PubMed

Talamo, Giampaolo; Cavallo, Federica; Zangari, Maurizio; Barlogie, Bart; Lee, Choon-Kee; Pineda-Roman, Mauricio; Kiwan, Elias; Krishna, Somashekar; Tricot, Guido

2006-07-01

We report 24 cases of multiple myeloma (MM) with involvement of the gastrointestinal (GI) system. We found a strong association with high A lactate dehydrogenase levels, plasmablastic morphology, and A unfavorable karyotype. GI involvement at the time of initial diagnosis was much rarer than later in the course of the disease. The A median survival after diagnosis of GI involvement was 7 months. Among 13 patients treated with stem cell transplantation, the response rate was 92%, and median progression-free survival was 4 months. We conclude that MM involving the GI system is associated with adverse biological features and with short-lasting remissions, even after A high-dose chemotherapy.

Special Speciation

ERIC Educational Resources Information Center

Countryman, Lyn L.; Maroo, Jill D.

2015-01-01

Considerable anecdotal evidence indicates that some of the most difficult concepts that both high school and undergraduate elementary-education students struggle with are those surrounding evolutionary principles, especially speciation. It's no wonder that entry-level biology students are confused, when biologists have multiple definitions of…

View from... Photonics Meets Biology Summer School: The bio-mission of diode lasers

NASA Astrophysics Data System (ADS)

Won, Rachel

2015-12-01

Diode lasers represent a viable alternative to light sources used in many biomedical applications. Their ongoing development will further increase their importance, offering not only multiple wavelength ranges, but also higher power levels.

Systems Biology Analysis of Heterocellular Signaling.

PubMed

Tape, Christopher J

2016-08-01

Tissues comprise multiple heterotypic cell types (e.g., epithelial, mesenchymal, and immune cells). Communication between heterotypic cell types is essential for biological cohesion and is frequently dysregulated in disease. Despite the importance of heterocellular communication, most systems biology techniques do not report cell-specific signaling data from mixtures of cells. As a result, our existing perspective of cellular behavior under-represents the influence of heterocellular signaling. Recent technical advances now permit the resolution of systems-level cell-specific signaling data. This review discusses how new physical, spatial, and isotopic resolving methods are facilitating unique systems biology studies of heterocellular communication. Copyright © 2016 Elsevier Ltd. All rights reserved.

Interest in biology. Part I: A multidimensional construct

NASA Astrophysics Data System (ADS)

Gardner, Paul L.; Tamir, Pinchas

Interest in a school subject (e.g., biology) is conceptualized in terms of three components: topics, activities, and motives, each of which has several dimensions. In this study, seven instruments were developed and administered to grade-10 biology students in Israel. Factor analysis provided support for the conceptualization which underlies the development of the instruments. Topic dimensions included biochemical processes, nonhuman organisms, human biology, personal hygiene, and practical applications; the activity dimensions were experiential learning, reception learning, writing/summarizing and group discussion; motives included environmental issues, moral issues, examination success, personal independence, problem solving, and four career dimensions (research, high-status professions, lower-status careers, woodsy-birdsy careers). In an analysis described in Part II of this paper, the students were classified into four groups on the basis of their grade-11 subject enrollment intentions: H (high-level biology), L (low-level biology), P (physical science), and N (no science). Zero-order and multiple correlations were found between interest and other variables and membership/nonmembership of the four groups. Students in Group H were characterized by higher achievement in year-10 biology, higher levels of enjoyment of biology, career orientations towards research or high-status biology-based professions, greater interest in various biology topics, especially reproduction/cell division/genetics, and a greater tendency to regard the Bagrut (grade-12) examination as interesting. Students in Group N displayed lower levels of interest in various topics (especially the microscope, plants, and reproduction), were less motivated to solve problems, had poorer grades in biology (and chemistry), were less likely to perceive biology as useful, were less likely to regard the Bagrut examination as fair, and were less likely to be interested in social modes of learning. There were few associations between interest variables and membership in Groups L or P.

Interactions among conifer terpenoids and bark beetles across multiple levels of scale: An attempt to understand links between population patterns and physiological processes

Treesearch

Kenneth F. Raffa; Briah H. Aukema; Nadir Erbilgin; Kier D. Klepzig; Kimberly F. Wallin

2005-01-01

A major challenge confronting ecologists involves scaling up and down across various levels of biological organization. The ability to conduct such scaling is important, because there is often a gap between the level at which information is most needed or best described versus the level at which it is most reliably generated or best explained. Many patterns are most...

Microtubule-Targeting Therapy for Prostate Cancer

DTIC Science & Technology

2007-02-01

that were done to achieve the above specific goals. 1. Biological effects of ribozyme -carrying adenoviruses that target stathmin mRNA in human...prostate cancer cells: A ribozyme is a small RNA molecule that acts stoichiometrically to cleave multiple target RNA molecules [1]. This unique ability...of a ribozyme to degrade multiple target RNA molecules is a more efficient approach for down regulating genes that are expressed at very high levels

System and process for pulsed multiple reaction monitoring

DOEpatents

Belov, Mikhail E

2013-05-17

A new pulsed multiple reaction monitoring process and system are disclosed that uses a pulsed ion injection mode for use in conjunction with triple-quadrupole instruments. The pulsed injection mode approach reduces background ion noise at the detector, increases amplitude of the ion signal, and includes a unity duty cycle that provides a significant sensitivity increase for reliable quantitation of proteins/peptides present at attomole levels in highly complex biological mixtures.

Biomarkers of selenium status

USDA-ARS?s Scientific Manuscript database

The essential trace element selenium (Se) has multiple biological activities, which depend on the level of Se intake. Relatively low Se intakes determine the expression of selenoenzymes in which it serves as an essential constituent. Higher intakes have been shown to have anti-tumorigenic potentia...

Instantiating the multiple levels of analysis perspective in a program of study on externalizing behavior

PubMed Central

Beauchaine, Theodore P.; Gatzke-Kopp, Lisa M.

2014-01-01

During the last quarter century, developmental psychopathology has become increasingly inclusive and now spans disciplines ranging from psychiatric genetics to primary prevention. As a result, developmental psychopathologists have extended traditional diathesis–stress and transactional models to include causal processes at and across all relevant levels of analysis. Such research is embodied in what is known as the multiple levels of analysis perspective. We describe how multiple levels of analysis research has informed our current thinking about antisocial and borderline personality development among trait impulsive and therefore vulnerable individuals. Our approach extends the multiple levels of analysis perspective beyond simple Biology × Environment interactions by evaluating impulsivity across physiological systems (genetic, autonomic, hormonal, neural), psychological constructs (social, affective, motivational), developmental epochs (preschool, middle childhood, adolescence, adulthood), sexes (male, female), and methods of inquiry (self-report, informant report, treatment outcome, cardiovascular, electrophysiological, neuroimaging). By conducting our research using any and all available methods across these levels of analysis, we have arrived at a developmental model of trait impulsivity that we believe confers a greater understanding of this highly heritable trait and captures at least some heterogeneity in key behavioral outcomes, including delinquency and suicide. PMID:22781868

A Multidisciplinary, Open Access Platform for Research on Biomolecules.

PubMed

Bähler, Jürg

2011-08-22

I am pleased to introduce Biomolecules, a new journal to report on all aspects of science that focuses on biologically derived substances, from small molecules to complex polymers. Some examples are lipids, carbohydrates, vitamins, hormones, amino acids, nucleotides, peptides, RNA and polysaccharides, but this list is far from exhaustive. Research on biomolecules encompasses multiple fascinating questions. How are biomolecules synthesized and modified? What are their structures and interactions with other biomolecules? How do biomolecules function in biological processes, at the level of organelles, cells, organs, organisms, or even ecosystems? How do biomolecules affect either the organism that produces them or other organisms of the same or different species? How are biomolecules shaped by evolution, and how in turn do they affect cellular phenotypes? What is the systems-level contribution of biomolecules to biological function? [...].

The importance of trace element speciation in biomedical science.

PubMed

Templeton, Douglas M

2003-04-01

According to IUPAC terminology, trace element speciation reflects differences in chemical composition at multiple levels from nuclear and electronic structure to macromolecular complexation. In the medical sciences, all levels of composition are important in various circumstances, and each can affect the bioavailability, distribution, physiological function, toxicity, diagnostic utility, and therapeutic potential of an element. Here we discuss, with specific examples, three biological principles in the intimate relation between speciation and biological behavior: i) the kinetics of interconversion of species determines distribution within the organism, ii) speciation governs transport across various biological barriers, and iii) speciation can limit potentially undesirable interactions between physiologically essential elements. We will also describe differences in the speciation of iron in states of iron overload, to illustrate how speciation analysis can provide insight into cellular processes in human disease.

Predicting Trophic Interactions and Habitat Utilization in the California Current Ecosystem

DTIC Science & Technology

2013-09-30

in the California Current Ecosystem Jerome Fiechter UC Santa Cruz Institute of Marine Sciences 1156 High Street Santa Cruz, CA 95064 phone... Ecosystem (CCLME), the long-term goal of our modeling approach is to better understand and characterize biological “hotspots” (i.e., the aggregation of...multiple marine organisms over multiple trophic levels) off the U.S. west coast and in other regions where similar fully-coupled ecosystem models may

Male Inmate Profiles and Their Biological Correlates

PubMed Central

Horn, Mathilde; Potvin, Stephane; Allaire, Jean-François; Côté, Gilles; Gobbi, Gabriella; Benkirane, Karim; Vachon, Jeanne; Dumais, Alexandre

2014-01-01

Objective: Borderline and antisocial personality disorders (PDs) share common clinical features (impulsivity, aggressiveness, substance use disorders [SUDs], and suicidal behaviours) that are greatly overrepresented in prison populations. These disorders have been associated biologically with testosterone and cortisol levels. However, the associations are ambiguous and the subject of controversy, perhaps because these heterogeneous disorders have been addressed as unitary constructs. A consideration of profiles of people, rather than of exclusive diagnoses, might yield clearer relationships. Methods: In our study, multiple correspondence analysis and cluster analysis were employed to identify subgroups among 545 newly convicted inmates. The groups were then compared in terms of clinical features and biological markers, including levels of cortisol, testosterone, estradiol, progesterone, and sulfoconjugated dehydroepiandrosterone (DHEA-S). Results: Four clusters with differing psychiatric, criminal, and biological profiles emerged. Clinically, one group had intermediate scores for each of the tested clinical features. Another group comprised people with little comorbidity. Two others displayed severe impulsivity, PD, and SUD. Biologically, cortisol levels were lowest in the last 2 groups and highest in the group with less comorbidity. In keeping with previous findings reported in the literature, testosterone was higher in a younger population with severe psychiatric symptoms. However, some apparently comparable behavioural outcomes were found to be related to distinct biological profiles. No differences were observed for estradiol, progesterone, or DHEA-S levels. Conclusions: The results not only confirm the importance of biological markers in the study of personality features but also demonstrate the need to consider the role of comorbidities and steroid coregulation. PMID:25161069

Mass Spectrometry: A Technique of Many Faces

PubMed Central

Olshina, Maya A.; Sharon, Michal

2016-01-01

Protein complexes form the critical foundation for a wide range of biological process, however understanding the intricate details of their activities is often challenging. In this review we describe how mass spectrometry plays a key role in the analysis of protein assemblies and the cellular pathways which they are involved in. Specifically, we discuss how the versatility of mass spectrometric approaches provides unprecedented information on multiple levels. We demonstrate this on the ubiquitin-proteasome proteolytic pathway, a process that is responsible for protein turnover. We follow the various steps of this degradation route and illustrate the different mass spectrometry workflows that were applied for elucidating molecular information. Overall, this review aims to stimulate the integrated use of multiple mass spectrometry approaches for analyzing complex biological systems. PMID:28100928

Risk assessment of pesticides and other stressors in bees: Principles, data gaps and perspectives from the European Food Safety Authority.

PubMed

Rortais, Agnès; Arnold, Gérard; Dorne, Jean-Lou; More, Simon J; Sperandio, Giorgio; Streissl, Franz; Szentes, Csaba; Verdonck, Frank

2017-06-01

Current approaches to risk assessment in bees do not take into account co-exposures from multiple stressors. The European Food Safety Authority (EFSA) is deploying resources and efforts to move towards a holistic risk assessment approach of multiple stressors in bees. This paper describes the general principles of pesticide risk assessment in bees, including recent developments at EFSA dealing with risk assessment of single and multiple pesticide residues and biological hazards. The EFSA Guidance Document on the risk assessment of plant protection products in bees highlights the need for the inclusion of an uncertainty analysis, other routes of exposures and multiple stressors such as chemical mixtures and biological agents. The EFSA risk assessment on the survival, spread and establishment of the small hive beetle, Aethina tumida, an invasive alien species, is provided with potential insights for other bee pests such as the Asian hornet, Vespa velutina. Furthermore, data gaps are identified at each step of the risk assessment, and recommendations are made for future research that could be supported under the framework of Horizon 2020. Finally, the recent work conducted at EFSA is presented, under the overarching MUST-B project ("EU efforts towards the development of a holistic approach for the risk assessment on MUltiple STressors in Bees") comprising a toolbox for harmonised data collection under field conditions and a mechanistic model to assess effects from pesticides and other stressors such as biological agents and beekeeping management practices, at the colony level and in a spatially complex landscape. Future perspectives at EFSA include the development of a data model to collate high quality data to calibrate and validate the model to be used as a regulatory tool. Finally, the evidence collected within the framework of MUST-B will support EFSA's activities on the development of a holistic approach to the risk assessment of multiple stressors in bees. In conclusion, EFSA calls for collaborative action at the EU level to establish a common and open access database to serve multiple purposes and different stakeholders. Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.

Biological classification with RNA-Seq data: Can alternatively spliced transcript expression enhance machine learning classifier?

PubMed

Johnson, Nathan T; Dhroso, Andi; Hughes, Katelyn J; Korkin, Dmitry

2018-06-25

The extent to which the genes are expressed in the cell can be simplistically defined as a function of one or more factors of the environment, lifestyle, and genetics. RNA sequencing (RNA-Seq) is becoming a prevalent approach to quantify gene expression, and is expected to gain better insights to a number of biological and biomedical questions, compared to the DNA microarrays. Most importantly, RNA-Seq allows to quantify expression at the gene and alternative splicing isoform levels. However, leveraging the RNA-Seq data requires development of new data mining and analytics methods. Supervised machine learning methods are commonly used approaches for biological data analysis, and have recently gained attention for their applications to the RNA-Seq data. In this work, we assess the utility of supervised learning methods trained on RNA-Seq data for a diverse range of biological classification tasks. We hypothesize that the isoform-level expression data is more informative for biological classification tasks than the gene-level expression data. Our large-scale assessment is done through utilizing multiple datasets, organisms, lab groups, and RNA-Seq analysis pipelines. Overall, we performed and assessed 61 biological classification problems that leverage three independent RNA-Seq datasets and include over 2,000 samples that come from multiple organisms, lab groups, and RNA-Seq analyses. These 61 problems include predictions of the tissue type, sex, or age of the sample, healthy or cancerous phenotypes and, the pathological tumor stage for the samples from the cancerous tissue. For each classification problem, the performance of three normalization techniques and six machine learning classifiers was explored. We find that for every single classification problem, the isoform-based classifiers outperform or are comparable with gene expression based methods. The top-performing supervised learning techniques reached a near perfect classification accuracy, demonstrating the utility of supervised learning for RNA-Seq based data analysis. Published by Cold Spring Harbor Laboratory Press for the RNA Society.

Combining multiple tools outperforms individual methods in gene set enrichment analyses.

PubMed

Alhamdoosh, Monther; Ng, Milica; Wilson, Nicholas J; Sheridan, Julie M; Huynh, Huy; Wilson, Michael J; Ritchie, Matthew E

2017-02-01

Gene set enrichment (GSE) analysis allows researchers to efficiently extract biological insight from long lists of differentially expressed genes by interrogating them at a systems level. In recent years, there has been a proliferation of GSE analysis methods and hence it has become increasingly difficult for researchers to select an optimal GSE tool based on their particular dataset. Moreover, the majority of GSE analysis methods do not allow researchers to simultaneously compare gene set level results between multiple experimental conditions. The ensemble of genes set enrichment analyses (EGSEA) is a method developed for RNA-sequencing data that combines results from twelve algorithms and calculates collective gene set scores to improve the biological relevance of the highest ranked gene sets. EGSEA's gene set database contains around 25 000 gene sets from sixteen collections. It has multiple visualization capabilities that allow researchers to view gene sets at various levels of granularity. EGSEA has been tested on simulated data and on a number of human and mouse datasets and, based on biologists' feedback, consistently outperforms the individual tools that have been combined. Our evaluation demonstrates the superiority of the ensemble approach for GSE analysis, and its utility to effectively and efficiently extrapolate biological functions and potential involvement in disease processes from lists of differentially regulated genes. EGSEA is available as an R package at http://www.bioconductor.org/packages/EGSEA/ . The gene sets collections are available in the R package EGSEAdata from http://www.bioconductor.org/packages/EGSEAdata/ . monther.alhamdoosh@csl.com.au mritchie@wehi.edu.au. Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press.

Structure-function relations in physiology education: Where's the mechanism?

PubMed

Lira, Matthew E; Gardner, Stephanie M

2017-06-01

Physiology demands systems thinking: reasoning within and between levels of biological organization and across different organ systems. Many physiological mechanisms explain how structures and their properties interact at one level of organization to produce emergent functions at a higher level of organization. Current physiology principles, such as structure-function relations, selectively neglect mechanisms by not mentioning this term explicitly. We explored how students characterized mechanisms and functions to shed light on how students make sense of these terms. Students characterized mechanisms as 1 ) processes that occur at levels of organization lower than that of functions; and 2 ) as detailed events with many steps involved. We also found that students produced more variability in how they characterized functions compared with mechanisms: students characterized functions in relation to multiple levels of organization and multiple definitions. We interpret these results as evidence that students see mechanisms as holding a more narrow definition than used in the biological sciences, and that students struggle to coordinate and distinguish mechanisms from functions due to cognitive processes germane to learning in many domains. We offer the instructional suggestion that we scaffold student learning by affording students opportunities to relate and also distinguish between these terms so central to understanding physiology. Copyright © 2017 the American Physiological Society.

Impaired global, and compensatory local, biological motion processing in people with high levels of autistic traits.

PubMed

van Boxtel, Jeroen J A; Lu, Hongjing

2013-01-01

People with Autism Spectrum Disorder (ASD) are hypothesized to have poor high-level processing but superior low-level processing, causing impaired social recognition, and a focus on non-social stimulus contingencies. Biological motion perception provides an ideal domain to investigate exactly how ASD modulates the interaction between low and high-level processing, because it involves multiple processing stages, and carries many important social cues. We investigated individual differences among typically developing observers in biological motion processing, and whether such individual differences associate with the number of autistic traits. In Experiment 1, we found that individuals with fewer autistic traits were automatically and involuntarily attracted to global biological motion information, whereas individuals with more autistic traits did not show this pre-attentional distraction. We employed an action adaptation paradigm in the second study to show that individuals with more autistic traits were able to compensate for deficits in global processing with an increased involvement in local processing. Our findings can be interpreted within a predictive coding framework, which characterizes the functional relationship between local and global processing stages, and explains how these stages contribute to the perceptual difficulties associated with ASD.

Impaired Global, and Compensatory Local, Biological Motion Processing in People with High Levels of Autistic Traits

PubMed Central

van Boxtel, Jeroen J. A.; Lu, Hongjing

2013-01-01

People with Autism Spectrum Disorder (ASD) are hypothesized to have poor high-level processing but superior low-level processing, causing impaired social recognition, and a focus on non-social stimulus contingencies. Biological motion perception provides an ideal domain to investigate exactly how ASD modulates the interaction between low and high-level processing, because it involves multiple processing stages, and carries many important social cues. We investigated individual differences among typically developing observers in biological motion processing, and whether such individual differences associate with the number of autistic traits. In Experiment 1, we found that individuals with fewer autistic traits were automatically and involuntarily attracted to global biological motion information, whereas individuals with more autistic traits did not show this pre-attentional distraction. We employed an action adaptation paradigm in the second study to show that individuals with more autistic traits were able to compensate for deficits in global processing with an increased involvement in local processing. Our findings can be interpreted within a predictive coding framework, which characterizes the functional relationship between local and global processing stages, and explains how these stages contribute to the perceptual difficulties associated with ASD. PMID:23630514

Next-generation mammalian genetics toward organism-level systems biology.

PubMed

Susaki, Etsuo A; Ukai, Hideki; Ueda, Hiroki R

2017-01-01

Organism-level systems biology in mammals aims to identify, analyze, control, and design molecular and cellular networks executing various biological functions in mammals. In particular, system-level identification and analysis of molecular and cellular networks can be accelerated by next-generation mammalian genetics. Mammalian genetics without crossing, where all production and phenotyping studies of genome-edited animals are completed within a single generation drastically reduce the time, space, and effort of conducting the systems research. Next-generation mammalian genetics is based on recent technological advancements in genome editing and developmental engineering. The process begins with introduction of double-strand breaks into genomic DNA by using site-specific endonucleases, which results in highly efficient genome editing in mammalian zygotes or embryonic stem cells. By using nuclease-mediated genome editing in zygotes, or ~100% embryonic stem cell-derived mouse technology, whole-body knock-out and knock-in mice can be produced within a single generation. These emerging technologies allow us to produce multiple knock-out or knock-in strains in high-throughput manner. In this review, we discuss the basic concepts and related technologies as well as current challenges and future opportunities for next-generation mammalian genetics in organism-level systems biology.

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.

Simulating Chemical-Induced Injury Using Virtual Hepatic Tissues

EPA Science Inventory

Chemical-induced liver injury involves a dynamic sequence of events that span multiple levels of biological organization. Current methods for testing the toxicity of a single chemical can cost millions of dollars, take up to two years and sacrifice thousands of animals. It is dif...

A Chemoenzymatic Histology Method for O-GlcNAc Detection.

PubMed

Aguilar, Aime Lopez; Hou, Xiaomeng; Wen, Liuqing; Wang, Peng G; Wu, Peng

2017-12-14

Modification of nuclear and cytoplasmic proteins by the addition or removal of O-GlcNAc dynamically impacts multiple biological processes. Here, we present the development of a chemoenzymatic histology method for the detection of O-GlcNAc in tissue specimens. We applied this method to screen murine organs, uncovering specific O-GlcNAc distribution patterns in different tissue structures. We then utilized our histology method for O-GlcNAc detection in human brain specimens from healthy donors and donors with Alzheimer's disease and found higher levels of O-GlcNAc in specimens from healthy donors. We also performed an analysis using a multiple cancer tissue array, uncovering different O-GlcNAc levels between healthy and cancerous tissues, as well as different O-GlcNAc cellular distributions within certain tissue specimens. This chemoenzymatic histology method therefore holds great potential for revealing the biology of O-GlcNAc in physiopathological processes. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Clinical and Biological Predictors of Plasma Levels of Soluble RAGE in Critically Ill Patients: Secondary Analysis of a Prospective Multicenter Observational Study.

PubMed

Pranal, Thibaut; Pereira, Bruno; Berthelin, Pauline; Roszyk, Laurence; Godet, Thomas; Chabanne, Russell; Eisenmann, Nathanael; Lautrette, Alexandre; Belville, Corinne; Blondonnet, Raiko; Cayot, Sophie; Gillart, Thierry; Skrzypczak, Yvan; Souweine, Bertrand; Bouvier, Damien; Blanchon, Loic; Sapin, Vincent; Constantin, Jean-Michel; Jabaudon, Matthieu

2018-01-01

Although soluble forms of the receptor for advanced glycation end products (RAGE) have been recently proposed as biomarkers in multiple acute or chronic diseases, few studies evaluated the influence of usual clinical and biological parameters, or of patient characteristics and comorbidities, on circulating levels of soluble RAGE in the intensive care unit (ICU) setting. To determine, among clinical and biological parameters that are usually recorded upon ICU admission, which variables, if any, could be associated with plasma levels of soluble RAGE. Data for this ancillary study were prospectively obtained from adult patients with at least one ARDS risk factor upon ICU admission enrolled in a large multicenter observational study. At ICU admission, plasma levels of total soluble RAGE (sRAGE) and endogenous secretory (es)RAGE were measured by duplicate ELISA and baseline patient characteristics, comorbidities, and usual clinical and biological indices were recorded. After univariate analyses, significant variables were used in multivariate, multidimensional analyses. 294 patients were included in this ancillary study, among whom 62% were admitted for medical reasons, including septic shock (11%), coma (11%), and pneumonia (6%). Although some variables were associated with plasma levels of RAGE soluble forms in univariate analysis, multidimensional analyses showed no significant association between admission parameters and baseline plasma sRAGE or esRAGE. We found no obvious association between circulating levels of soluble RAGE and clinical and biological indices that are usually recorded upon ICU admission. This trial is registered with NCT02070536.

Does Sufficient Evidence Exist to Support a Causal Association between Vitamin D Status and Cardiovascular Disease Risk? An Assessment Using Hill’s Criteria for Causality

PubMed Central

Weyland, Patricia G.; Grant, William B.; Howie-Esquivel, Jill

2014-01-01

Serum 25-hydroxyvitamin D (25(OH)D) levels have been found to be inversely associated with both prevalent and incident cardiovascular disease (CVD) risk factors; dyslipidemia, hypertension and diabetes mellitus. This review looks for evidence of a causal association between low 25(OH)D levels and increased CVD risk. We evaluated journal articles in light of Hill’s criteria for causality in a biological system. The results of our assessment are as follows. Strength of association: many randomized controlled trials (RCTs), prospective and cross-sectional studies found statistically significant inverse associations between 25(OH)D levels and CVD risk factors. Consistency of observed association: most studies found statistically significant inverse associations between 25(OH)D levels and CVD risk factors in various populations, locations and circumstances. Temporality of association: many RCTs and prospective studies found statistically significant inverse associations between 25(OH)D levels and CVD risk factors. Biological gradient (dose-response curve): most studies assessing 25(OH)D levels and CVD risk found an inverse association exhibiting a linear biological gradient. Plausibility of biology: several plausible cellular-level causative mechanisms and biological pathways may lead from a low 25(OH)D level to increased risk for CVD with mediators, such as dyslipidemia, hypertension and diabetes mellitus. Experimental evidence: some well-designed RCTs found increased CVD risk factors with decreasing 25(OH)D levels. Analogy: the association between serum 25(OH)D levels and CVD risk is analogous to that between 25(OH)D levels and the risk of overall cancer, periodontal disease, multiple sclerosis and breast cancer. Conclusion: all relevant Hill criteria for a causal association in a biological system are satisfied to indicate a low 25(OH)D level as a CVD risk factor. PMID:25184368

MCAM: multiple clustering analysis methodology for deriving hypotheses and insights from high-throughput proteomic datasets.

PubMed

Naegle, Kristen M; Welsch, Roy E; Yaffe, Michael B; White, Forest M; Lauffenburger, Douglas A

2011-07-01

Advances in proteomic technologies continue to substantially accelerate capability for generating experimental data on protein levels, states, and activities in biological samples. For example, studies on receptor tyrosine kinase signaling networks can now capture the phosphorylation state of hundreds to thousands of proteins across multiple conditions. However, little is known about the function of many of these protein modifications, or the enzymes responsible for modifying them. To address this challenge, we have developed an approach that enhances the power of clustering techniques to infer functional and regulatory meaning of protein states in cell signaling networks. We have created a new computational framework for applying clustering to biological data in order to overcome the typical dependence on specific a priori assumptions and expert knowledge concerning the technical aspects of clustering. Multiple clustering analysis methodology ('MCAM') employs an array of diverse data transformations, distance metrics, set sizes, and clustering algorithms, in a combinatorial fashion, to create a suite of clustering sets. These sets are then evaluated based on their ability to produce biological insights through statistical enrichment of metadata relating to knowledge concerning protein functions, kinase substrates, and sequence motifs. We applied MCAM to a set of dynamic phosphorylation measurements of the ERRB network to explore the relationships between algorithmic parameters and the biological meaning that could be inferred and report on interesting biological predictions. Further, we applied MCAM to multiple phosphoproteomic datasets for the ERBB network, which allowed us to compare independent and incomplete overlapping measurements of phosphorylation sites in the network. We report specific and global differences of the ERBB network stimulated with different ligands and with changes in HER2 expression. Overall, we offer MCAM as a broadly-applicable approach for analysis of proteomic data which may help increase the current understanding of molecular networks in a variety of biological problems. © 2011 Naegle et al.

Organization of excitable dynamics in hierarchical biological networks.

PubMed

Müller-Linow, Mark; Hilgetag, Claus C; Hütt, Marc-Thorsten

2008-09-26

This study investigates the contributions of network topology features to the dynamic behavior of hierarchically organized excitable networks. Representatives of different types of hierarchical networks as well as two biological neural networks are explored with a three-state model of node activation for systematically varying levels of random background network stimulation. The results demonstrate that two principal topological aspects of hierarchical networks, node centrality and network modularity, correlate with the network activity patterns at different levels of spontaneous network activation. The approach also shows that the dynamic behavior of the cerebral cortical systems network in the cat is dominated by the network's modular organization, while the activation behavior of the cellular neuronal network of Caenorhabditis elegans is strongly influenced by hub nodes. These findings indicate the interaction of multiple topological features and dynamic states in the function of complex biological networks.

A heritable symbiont and host-associated factors shape fungal endophyte communities across spatial scales

USDA-ARS?s Scientific Manuscript database

Microbial ecologists are intensely interested in the processes governing microbial community assembly, progress has been limited by a lack of studies that span multiple geographical scales and levels of biological organization. High throughput sequencing was used to characterize foliar fungal endoph...

A Systems Biology Approach to Iron Metabolism

PubMed Central

Chifman, J.; Laubenbacher, R.; Torti, S.V.

2015-01-01

Iron is critical to the survival of almost all living organisms. However, inappropriately low or high levels of iron are detrimental and contribute to a wide range of diseases. Recent advances in the study of iron metabolism have revealed multiple intricate pathways that are essential to the maintenance of iron homeostasis. Further, iron regulation involves processes at several scales, ranging from the subcellular to the organismal. This complexity makes a systems biology approach crucial, with its enabling technology of computational models based on a mathematical description of regulatory systems. Systems biology may represent a new strategy for understanding imbalances in iron metabolism and their underlying causes. PMID:25480643

Harnessing the Power of Integrated Mitochondrial Biology and Physiology: A Special Report on the NHLBI Mitochondria in Heart Diseases Initiative

PubMed Central

Ping, Peipei; Gustafsson, Åsa B.; Bers, Don M.; Blatter, Lothar; Cai, Hua; Jahangir, Arshad; Kelly, Daniel; Muoio, Deborah; O'Rourke, Brian; Rabinovitch, Peter; Trayanova, Natalia; Van Eyk, Jennifer; Weiss, James N.; Wong, Renee; Longacre, Lisa Schwartz

2015-01-01

Summary Mitochondrial biology is the sum of diverse phenomena from molecular profiles to physiological functions. A mechanistic understanding of mitochondria in disease development, and hence the future prospect of clinical translations, relies on a systems-level integration of expertise from multiple fields of investigation. Upon the successful completion of a recent National Institutes of Health, National Heart, Lung, and Blood Institute initiative on integrative mitochondrial biology in cardiovascular diseases, we reflect on the accomplishments made possible by this unique interdisciplinary collaboration effort and exciting new fronts on the study of these remarkable organelles. PMID:26185209

Harnessing the Power of Integrated Mitochondrial Biology and Physiology: A Special Report on the NHLBI Mitochondria in Heart Diseases Initiative.

PubMed

Ping, Peipei; Gustafsson, Åsa B; Bers, Don M; Blatter, Lothar A; Cai, Hua; Jahangir, Arshad; Kelly, Daniel; Muoio, Deborah; O'Rourke, Brian; Rabinovitch, Peter; Trayanova, Natalia; Van Eyk, Jennifer; Weiss, James N; Wong, Renee; Schwartz Longacre, Lisa

2015-07-17

Mitochondrial biology is the sum of diverse phenomena from molecular profiles to physiological functions. A mechanistic understanding of mitochondria in disease development, and hence the future prospect of clinical translations, relies on a systems-level integration of expertise from multiple fields of investigation. Upon the successful conclusion of a recent National Institutes of Health, National Heart, Lung, and Blood Institute initiative on integrative mitochondrial biology in cardiovascular diseases, we reflect on the accomplishments made possible by this unique interdisciplinary collaboration effort and exciting new fronts on the study of these remarkable organelles. © 2015 American Heart Association, Inc.

Distinguishing Signatures of Multipathway Conformational Transitions

NASA Astrophysics Data System (ADS)

Pierse, Christopher A.; Dudko, Olga K.

2017-02-01

The folding and binding of biomolecules into functional conformations are thought to be commonly mediated by multiple pathways rather than a unique route. Yet even in experiments where one can "see" individual conformational transitions, their stochastic nature generally precludes one from determining whether the transitions occurred through one or multiple pathways. We establish model-free, observable signatures in the response of macromolecules to force that unambiguously identify multiple pathways—even when the pathways themselves cannot be resolved. The unified analytical description reveals that, through multiple pathways, the response of molecules to external forces can be shaped in diverse ways, resulting in a rich design space for a tailored biological function already at the single-molecule level.

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

PubMed

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

2010-01-01

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

ePlant: Visualizing and Exploring Multiple Levels of Data for Hypothesis Generation in Plant Biology[OPEN

PubMed Central

Waese, Jamie; Fan, Jim; Yu, Hans; Fucile, Geoffrey; Shi, Ruian; Cumming, Matthew; Town, Chris; Stuerzlinger, Wolfgang

2017-01-01

A big challenge in current systems biology research arises when different types of data must be accessed from separate sources and visualized using separate tools. The high cognitive load required to navigate such a workflow is detrimental to hypothesis generation. Accordingly, there is a need for a robust research platform that incorporates all data and provides integrated search, analysis, and visualization features through a single portal. Here, we present ePlant (http://bar.utoronto.ca/eplant), a visual analytic tool for exploring multiple levels of Arabidopsis thaliana data through a zoomable user interface. ePlant connects to several publicly available web services to download genome, proteome, interactome, transcriptome, and 3D molecular structure data for one or more genes or gene products of interest. Data are displayed with a set of visualization tools that are presented using a conceptual hierarchy from big to small, and many of the tools combine information from more than one data type. We describe the development of ePlant in this article and present several examples illustrating its integrative features for hypothesis generation. We also describe the process of deploying ePlant as an “app” on Araport. Building on readily available web services, the code for ePlant is freely available for any other biological species research. PMID:28808136

SPECIATION OF ARSENIC IN BIOLOGICAL MATRICES BY AUTOMATED HG-AAS WITH MULTIPLE MICROFLAME QUARTZ TUBE ATOMIZER (MULTIATOMIZER)

EPA Science Inventory

Analyses of arsenic (As) species in body fluids and tissues of individuals chronically exposed to inorganic arsenic (iAs) provide essential information about the exposure level and pattern of iAs metabolism. This information facilitates the risk assessment of disorders associated...

NCI Scientists Get Deep Look at CRISPR Complex Through Deep Freeze | Poster

Cancer.gov

To get a closer look at one CRISPR complex, researchers from NCI’s Center for Cancer Research and their collaborators recently put it “on ice” with cryo-electron microscopy, creating highly detailed images that show its biological structures in multiple states at a molecular level.

Development of a QSAR Model for Thyroperoxidase Inhbition and Screening of 72,524 REACH substances - (Eurotox 2016)

EPA Science Inventory

hyroid hormones (THs) are involved in multiple biological processes and are critical modulators of fetal development. Even moderate changes in maternal or fetal TH levels can produce irreversible neurological deficits in children, such as lower IQ. The enzyme thyroperoxidase (TPO...

Multiple-level defoliation assessment with hyperspectral data: integration of continuum-removed absorptions and red edges

USDA-ARS?s Scientific Manuscript database

Hyperspectral data were collected from 40 canopies of saltcedar (Tamarix ramosissima), 10 healthy canopies and 30 canopies defoliated by an introduced biological control agent, the saltcedar leaf beetle (Diorhabda elongata). These data were assessed to detect categories of defoliation in response to...

A Personal Appraisal of the MIBiol Courses in Entomology and Plant Pathology at Wolverhampton Polytechnic, 1967-71

ERIC Educational Resources Information Center

Ayerst, G.; Gower, A. M.

1972-01-01

Article provides brief description of two microbiology courses at the college level which have multiple characteristics. Course I provides instruction based on papers in biology and in a special subject. Course II is devoted entirely to the special subject. (PS)

Small RNA biology is systems biology.

PubMed

Jost, Daniel; Nowojewski, Andrzej; Levine, Erel

2011-01-01

During the last decade small regulatory RNA (srRNA) emerged as central players in the regulation of gene expression in all kingdoms of life. Multiple pathways for srRNA biogenesis and diverse mechanisms of gene regulation may indicate that srRNA regulation evolved independently multiple times. However, small RNA pathways share numerous properties, including the ability of a single srRNA to regulate multiple targets. Some of the mechanisms of gene regulation by srRNAs have significant effect on the abundance of free srRNAs that are ready to interact with new targets. This results in indirect interactions among seemingly unrelated genes, as well as in a crosstalk between different srRNA pathways. Here we briefly review and compare the major srRNA pathways, and argue that the impact of srRNA is always at the system level. We demonstrate how a simple mathematical model can ease the discussion of governing principles. To demonstrate these points we review a few examples from bacteria and animals.

Evaluation of an index of biotic integrity approach used to assess biological condition in western U.S. streams and rivers at varying spatial scales

USGS Publications Warehouse

Meador, M.R.; Whittier, T.R.; Goldstein, R.M.; Hughes, R.M.; Peck, D.V.

2008-01-01

Consistent assessments of biological condition are needed across multiple ecoregions to provide a greater understanding of the spatial extent of environmental degradation. However, consistent assessments at large geographic scales are often hampered by lack of uniformity in data collection, analyses, and interpretation. The index of biotic integrity (IBI) has been widely used in eastern and central North America, where fish assemblages are complex and largely composed of native species, but IBI development has been hindered in the western United States because of relatively low fish species richness and greater relative abundance of alien fishes. Approaches to developing IBIs rarely provide a consistent means of assessing biological condition across multiple ecoregions. We conducted an evaluation of IBIs recently proposed for three ecoregions of the western United States using an independent data set covering a large geographic scale. We standardized the regional IBIs and developed biological condition criteria, assessed the responsiveness of IBIs to basin-level land uses, and assessed their precision and concordance with basin-scale IBIs. Standardized IBI scores from 318 sites in the western United States comprising mountain, plains, and xeric ecoregions were significantly related to combined urban and agricultural land uses. Standard deviations and coefficients of variation revealed relatively low variation in IBI scores based on multiple sampling reaches at sites. A relatively high degree of corroboration with independent, locally developed IBIs indicates that the regional IBIs are robust across large geographic scales, providing precise and accurate assessments of biological condition for western U.S. streams. ?? Copyright by the American Fisheries Society 2008.

Vitamin D deficiency in multiple sclerosis: Should testing and treatment be based on racial background?

PubMed

Avasarala, Jagannadha; Zachariah, Phenu

2015-11-15

Maintaining adequate levels of vitamin D may have a protective effect and lower the risk of multiple sclerosis (MS). For patients with MS, maintaining an adequate level of vitamin D level is probably associated with lessening of the frequency and severity of their symptoms. However, what remains unclear is whether if this is true across all racial/ethnic backgrounds. In African-Americans (AAs) this effect is not only absent but curiously enough, low levels of vitamin D do not matter since the bioavailability of this molecule in AA subjects is normal. It is this paradox that led to this brief report and we suggest more research and database construction based on race/ethnicity be done, as a first step to understand the biological mechanisms that confer or negate the effect of vitamin D levels in MS. Copyright © 2015 Elsevier B.V. All rights reserved.

Systems biology of human atherosclerosis.

PubMed

Shalhoub, Joseph; Sikkel, Markus B; Davies, Kerry J; Vorkas, Panagiotis A; Want, Elizabeth J; Davies, Alun H

2014-01-01

Systems biology describes a holistic and integrative approach to understand physiology and pathology. The "omic" disciplines include genomics, transcriptomics, proteomics, and metabolic profiling (metabonomics and metabolomics). By adopting a stance, which is opposing (yet complimentary) to conventional research techniques, systems biology offers an overview by assessing the "net" biological effect imposed by a disease or nondisease state. There are a number of different organizational levels to be understood, from DNA to protein, metabolites, cells, organs and organisms, even beyond this to an organism's context. Systems biology relies on the existence of "nodes" and "edges." Nodes are the constituent part of the system being studied (eg, proteins in the proteome), while the edges are the way these constituents interact. In future, it will be increasingly important to collaborate, collating data from multiple studies to improve data sets, making them freely available and undertaking integrative analyses.

Rising tides, cumulative impacts and cascading changes to estuarine ecosystem functions.

PubMed

O'Meara, Theresa A; Hillman, Jenny R; Thrush, Simon F

2017-08-31

In coastal ecosystems, climate change affects multiple environmental factors, yet most predictive models are based on simple cause-and-effect relationships. Multiple stressor scenarios are difficult to predict because they can create a ripple effect through networked ecosystem functions. Estuarine ecosystem function relies on an interconnected network of physical and biological processes. Estuarine habitats play critical roles in service provision and represent global hotspots for organic matter processing, nutrient cycling and primary production. Within these systems, we predicted functional changes in the impacts of land-based stressors, mediated by changing light climate and sediment permeability. Our in-situ field experiment manipulated sea level, nutrient supply, and mud content. We used these stressors to determine how interacting environmental stressors influence ecosystem function and compared results with data collected along elevation gradients to substitute space for time. We show non-linear, multi-stressor effects deconstruct networks governing ecosystem function. Sea level rise altered nutrient processing and impacted broader estuarine services ameliorating nutrient and sediment pollution. Our experiment demonstrates how the relationships between nutrient processing and biological/physical controls degrade with environmental stress. Our results emphasise the importance of moving beyond simple physically-forced relationships to assess consequences of climate change in the context of ecosystem interactions and multiple stressors.

Clinical and Biological Predictors of Plasma Levels of Soluble RAGE in Critically Ill Patients: Secondary Analysis of a Prospective Multicenter Observational Study

PubMed Central

Pranal, Thibaut; Pereira, Bruno; Berthelin, Pauline; Roszyk, Laurence; Chabanne, Russell; Eisenmann, Nathanael; Lautrette, Alexandre; Belville, Corinne; Blondonnet, Raiko; Gillart, Thierry; Skrzypczak, Yvan; Souweine, Bertrand; Bouvier, Damien; Constantin, Jean-Michel

2018-01-01

Rationale Although soluble forms of the receptor for advanced glycation end products (RAGE) have been recently proposed as biomarkers in multiple acute or chronic diseases, few studies evaluated the influence of usual clinical and biological parameters, or of patient characteristics and comorbidities, on circulating levels of soluble RAGE in the intensive care unit (ICU) setting. Objectives To determine, among clinical and biological parameters that are usually recorded upon ICU admission, which variables, if any, could be associated with plasma levels of soluble RAGE. Methods Data for this ancillary study were prospectively obtained from adult patients with at least one ARDS risk factor upon ICU admission enrolled in a large multicenter observational study. At ICU admission, plasma levels of total soluble RAGE (sRAGE) and endogenous secretory (es)RAGE were measured by duplicate ELISA and baseline patient characteristics, comorbidities, and usual clinical and biological indices were recorded. After univariate analyses, significant variables were used in multivariate, multidimensional analyses. Measurements and Main Results 294 patients were included in this ancillary study, among whom 62% were admitted for medical reasons, including septic shock (11%), coma (11%), and pneumonia (6%). Although some variables were associated with plasma levels of RAGE soluble forms in univariate analysis, multidimensional analyses showed no significant association between admission parameters and baseline plasma sRAGE or esRAGE. Conclusions We found no obvious association between circulating levels of soluble RAGE and clinical and biological indices that are usually recorded upon ICU admission. This trial is registered with NCT02070536. PMID:29861796

Augmenting Surgery via Multi-scale Modeling and Translational Systems Biology in the Era of Precision Medicine: A Multidisciplinary Perspective

PubMed Central

Kassab, Ghassan S.; An, Gary; Sander, Edward A.; Miga, Michael; Guccione, Julius M.; Ji, Songbai; Vodovotz, Yoram

2016-01-01

In this era of tremendous technological capabilities and increased focus on improving clinical outcomes, decreasing costs, and increasing precision, there is a need for a more quantitative approach to the field of surgery. Multiscale computational modeling has the potential to bridge the gap to the emerging paradigms of Precision Medicine and Translational Systems Biology, in which quantitative metrics and data guide patient care through improved stratification, diagnosis, and therapy. Achievements by multiple groups have demonstrated the potential for 1) multiscale computational modeling, at a biological level, of diseases treated with surgery and the surgical procedure process at the level of the individual and the population; along with 2) patient-specific, computationally-enabled surgical planning, delivery, and guidance and robotically-augmented manipulation. In this perspective article, we discuss these concepts, and cite emerging examples from the fields of trauma, wound healing, and cardiac surgery. PMID:27015816

Top-down models in biology: explanation and control of complex living systems above the molecular level.

PubMed

Pezzulo, Giovanni; Levin, Michael

2016-11-01

It is widely assumed in developmental biology and bioengineering that optimal understanding and control of complex living systems follows from models of molecular events. The success of reductionism has overshadowed attempts at top-down models and control policies in biological systems. However, other fields, including physics, engineering and neuroscience, have successfully used the explanations and models at higher levels of organization, including least-action principles in physics and control-theoretic models in computational neuroscience. Exploiting the dynamic regulation of pattern formation in embryogenesis and regeneration requires new approaches to understand how cells cooperate towards large-scale anatomical goal states. Here, we argue that top-down models of pattern homeostasis serve as proof of principle for extending the current paradigm beyond emergence and molecule-level rules. We define top-down control in a biological context, discuss the examples of how cognitive neuroscience and physics exploit these strategies, and illustrate areas in which they may offer significant advantages as complements to the mainstream paradigm. By targeting system controls at multiple levels of organization and demystifying goal-directed (cybernetic) processes, top-down strategies represent a roadmap for using the deep insights of other fields for transformative advances in regenerative medicine and systems bioengineering. © 2016 The Author(s).

Top-down models in biology: explanation and control of complex living systems above the molecular level

PubMed Central

2016-01-01

It is widely assumed in developmental biology and bioengineering that optimal understanding and control of complex living systems follows from models of molecular events. The success of reductionism has overshadowed attempts at top-down models and control policies in biological systems. However, other fields, including physics, engineering and neuroscience, have successfully used the explanations and models at higher levels of organization, including least-action principles in physics and control-theoretic models in computational neuroscience. Exploiting the dynamic regulation of pattern formation in embryogenesis and regeneration requires new approaches to understand how cells cooperate towards large-scale anatomical goal states. Here, we argue that top-down models of pattern homeostasis serve as proof of principle for extending the current paradigm beyond emergence and molecule-level rules. We define top-down control in a biological context, discuss the examples of how cognitive neuroscience and physics exploit these strategies, and illustrate areas in which they may offer significant advantages as complements to the mainstream paradigm. By targeting system controls at multiple levels of organization and demystifying goal-directed (cybernetic) processes, top-down strategies represent a roadmap for using the deep insights of other fields for transformative advances in regenerative medicine and systems bioengineering. PMID:27807271

Anti-inflammatory nutritional intervention in patients with relapsing-remitting and primary-progressive multiple sclerosis: A pilot study.

PubMed

Riccio, Paolo; Rossano, Rocco; Larocca, Marilena; Trotta, Vincenzo; Mennella, Ilario; Vitaglione, Paola; Ettorre, Michele; Graverini, Antonio; De Santis, Alessandro; Di Monte, Elisabetta; Coniglio, Maria Gabriella

2016-03-01

The aim of this work was to assess the influence of nutritional intervention on inflammatory status and wellness in people with multiple sclerosis. To this end, in a seven-month pilot study we investigated the effects of a calorie-restricted, semi-vegetarian diet and administration of vitamin D and other dietary supplements (fish oil, lipoic acid, omega-3 polyunsaturated fatty acids, resveratrol and multivitamin complex) in 33 patients with relapsing-remitting multiple sclerosis and 10 patients with primary-progressive multiple sclerosis. At 0/3/6 months, patients had neurological examination, filled questionnaires and underwent anthropometric measurements and biochemical analyses. Serum fatty acids and vitamin D levels were measured as markers of dietary compliance and nutritional efficacy of treatment, whereas serum gelatinase levels were analyzed as markers of inflammatory status. All patients had insufficient levels of vitamin D at baseline, but their values did not ameliorate following a weekly administration of 5000  IU, and rather decreased over time. Conversely, omega-3 polyunsaturated fatty acids increased already after three months, even under dietary restriction only. Co-treatment with interferon-beta in relapsing-remitting multiple sclerosis was irrelevant to vitamin D levels. After six months nutritional treatment, no significant changes in neurological signs were observed in any group. However, serum levels of the activated isoforms of gelatinase matrix metalloproteinase-9 decreased by 59% in primary-progressive multiple sclerosis and by 51% in relapsing-remitting multiple sclerosis patients under nutritional intervention, including dietary supplements. This study indicates that a healthy nutritional intervention is well accepted by people with multiple sclerosis and may ameliorate their physical and inflammatory status. © 2016 by the Society for Experimental Biology and Medicine.

Mass fractionation processes of transition metal isotopes

NASA Astrophysics Data System (ADS)

Zhu, X. K.; Guo, Y.; Williams, R. J. P.; O'Nions, R. K.; Matthews, A.; Belshaw, N. S.; Canters, G. W.; de Waal, E. C.; Weser, U.; Burgess, B. K.; Salvato, B.

2002-06-01

Recent advances in mass spectrometry make it possible to utilise isotope variations of transition metals to address some important issues in solar system and biological sciences. Realisation of the potential offered by these new isotope systems however requires an adequate understanding of the factors controlling their isotope fractionation. Here we show the results of a broadly based study on copper and iron isotope fractionation during various inorganic and biological processes. These results demonstrate that: (1) naturally occurring inorganic processes can fractionate Fe isotope to a detectable level even at temperature ˜1000°C, which challenges the previous view that Fe isotope variations in natural system are unique biosignatures; (2) multiple-step equilibrium processes at low temperatures may cause large mass fractionation of transition metal isotopes even when the fractionation per single step is small; (3) oxidation-reduction is an importation controlling factor of isotope fractionation of transition metal elements with multiple valences, which opens a wide range of applications of these new isotope systems, ranging from metal-silicate fractionation in the solar system to uptake pathways of these elements in biological systems; (4) organisms incorporate lighter isotopes of transition metals preferentially, and transition metal isotope fractionation occurs stepwise along their pathways within biological systems during their uptake.

Neuromorphic neural interfaces: from neurophysiological inspiration to biohybrid coupling with nervous systems

NASA Astrophysics Data System (ADS)

Broccard, Frédéric D.; Joshi, Siddharth; Wang, Jun; Cauwenberghs, Gert

2017-08-01

Objective. Computation in nervous systems operates with different computational primitives, and on different hardware, than traditional digital computation and is thus subjected to different constraints from its digital counterpart regarding the use of physical resources such as time, space and energy. In an effort to better understand neural computation on a physical medium with similar spatiotemporal and energetic constraints, the field of neuromorphic engineering aims to design and implement electronic systems that emulate in very large-scale integration (VLSI) hardware the organization and functions of neural systems at multiple levels of biological organization, from individual neurons up to large circuits and networks. Mixed analog/digital neuromorphic VLSI systems are compact, consume little power and operate in real time independently of the size and complexity of the model. Approach. This article highlights the current efforts to interface neuromorphic systems with neural systems at multiple levels of biological organization, from the synaptic to the system level, and discusses the prospects for future biohybrid systems with neuromorphic circuits of greater complexity. Main results. Single silicon neurons have been interfaced successfully with invertebrate and vertebrate neural networks. This approach allowed the investigation of neural properties that are inaccessible with traditional techniques while providing a realistic biological context not achievable with traditional numerical modeling methods. At the network level, populations of neurons are envisioned to communicate bidirectionally with neuromorphic processors of hundreds or thousands of silicon neurons. Recent work on brain-machine interfaces suggests that this is feasible with current neuromorphic technology. Significance. Biohybrid interfaces between biological neurons and VLSI neuromorphic systems of varying complexity have started to emerge in the literature. Primarily intended as a computational tool for investigating fundamental questions related to neural dynamics, the sophistication of current neuromorphic systems now allows direct interfaces with large neuronal networks and circuits, resulting in potentially interesting clinical applications for neuroengineering systems, neuroprosthetics and neurorehabilitation.

Mergeomics: a web server for identifying pathological pathways, networks, and key regulators via multidimensional data integration.

PubMed

Arneson, Douglas; Bhattacharya, Anindya; Shu, Le; Mäkinen, Ville-Petteri; Yang, Xia

2016-09-09

Human diseases are commonly the result of multidimensional changes at molecular, cellular, and systemic levels. Recent advances in genomic technologies have enabled an outpour of omics datasets that capture these changes. However, separate analyses of these various data only provide fragmented understanding and do not capture the holistic view of disease mechanisms. To meet the urgent needs for tools that effectively integrate multiple types of omics data to derive biological insights, we have developed Mergeomics, a computational pipeline that integrates multidimensional disease association data with functional genomics and molecular networks to retrieve biological pathways, gene networks, and central regulators critical for disease development. To make the Mergeomics pipeline available to a wider research community, we have implemented an online, user-friendly web server ( http://mergeomics. idre.ucla.edu/ ). The web server features a modular implementation of the Mergeomics pipeline with detailed tutorials. Additionally, it provides curated genomic resources including tissue-specific expression quantitative trait loci, ENCODE functional annotations, biological pathways, and molecular networks, and offers interactive visualization of analytical results. Multiple computational tools including Marker Dependency Filtering (MDF), Marker Set Enrichment Analysis (MSEA), Meta-MSEA, and Weighted Key Driver Analysis (wKDA) can be used separately or in flexible combinations. User-defined summary-level genomic association datasets (e.g., genetic, transcriptomic, epigenomic) related to a particular disease or phenotype can be uploaded and computed real-time to yield biologically interpretable results, which can be viewed online and downloaded for later use. Our Mergeomics web server offers researchers flexible and user-friendly tools to facilitate integration of multidimensional data into holistic views of disease mechanisms in the form of tissue-specific key regulators, biological pathways, and gene networks.

The 1993 Gordon Research Conference on Chronobiology

NASA Technical Reports Server (NTRS)

Schwartz, William J.

1993-01-01

The study of biological timekeeping is now at a particularly fertile stage, encompassing multiple levels of biological organization, recruiting a wide array of disciplines and methodologies and uniting a host of investigators. This report summarizes a research conference on Chronobiology. Some of the topics focused on transcriptional and translational mechanisms of circadian rhythmicity, with discussions of putative 'clock genes' in cyanobacteria, algae, fungi, fruitflies, and hamsters. Cellular analysis, with emphasis on photoreceptors in frogs, neurons in molluscs, and testis in moths was addressed. New methods for investigating the circadian clock in the suprachiasmatic nucleus were introduced.

Anatomy and Physiology of Multiscale Modeling and Simulation in Systems Medicine.

PubMed

Mizeranschi, Alexandru; Groen, Derek; Borgdorff, Joris; Hoekstra, Alfons G; Chopard, Bastien; Dubitzky, Werner

2016-01-01

Systems medicine is the application of systems biology concepts, methods, and tools to medical research and practice. It aims to integrate data and knowledge from different disciplines into biomedical models and simulations for the understanding, prevention, cure, and management of complex diseases. Complex diseases arise from the interactions among disease-influencing factors across multiple levels of biological organization from the environment to molecules. To tackle the enormous challenges posed by complex diseases, we need a modeling and simulation framework capable of capturing and integrating information originating from multiple spatiotemporal and organizational scales. Multiscale modeling and simulation in systems medicine is an emerging methodology and discipline that has already demonstrated its potential in becoming this framework. The aim of this chapter is to present some of the main concepts, requirements, and challenges of multiscale modeling and simulation in systems medicine.

Genetic studies of plasma analytes identify novel potential biomarkers for several complex traits

PubMed Central

Deming, Yuetiva; Xia, Jian; Cai, Yefei; Lord, Jenny; Del-Aguila, Jorge L.; Fernandez, Maria Victoria; Carrell, David; Black, Kathleen; Budde, John; Ma, ShengMei; Saef, Benjamin; Howells, Bill; Bertelsen, Sarah; Bailey, Matthew; Ridge, Perry G.; Hefti, Franz; Fillit, Howard; Zimmerman, Earl A.; Celmins, Dzintra; Brown, Alice D.; Carrillo, Maria; Fleisher, Adam; Reeder, Stephanie; Trncic, Nadira; Burke, Anna; Tariot, Pierre; Reiman, Eric M.; Chen, Kewei; Sabbagh, Marwan N.; Beiden, Christine M.; Jacobson, Sandra A.; Sirrel, Sherye A.; Doody, Rachelle S.; Villanueva-Meyer, Javier; Chowdhury, Munir; Rountree, Susan; Dang, Mimi; Kowall, Neil; Killiany, Ronald; Budson, Andrew E.; Norbash, Alexander; Johnson, Patricia Lynn; Green, Robert C.; Marshall, Gad; Johnson, Keith A.; Sperling, Reisa A.; Snyder, Peter; Salloway, Stephen; Malloy, Paul; Correia, Stephen; Bernick, Charles; Munic, Donna; Stern, Yaakov; Honig, Lawrence S.; Bell, Karen L.; Relkin, Norman; Chaing, Gloria; Ravdin, Lisa; Paul, Steven; Flashman, Laura A.; Seltzer, Marc; Hynes, Mary L.; Santulli, Robert B.; Bates, Vernice; Capote, Horacio; Rainka, Michelle; Friedl, Karl; Murali Doraiswamy, P.; Petrella, Jeffrey R.; Borges-Neto, Salvador; James, Olga; Wong, Terence; Coleman, Edward; Schwartz, Adam; Cellar, Janet S.; Levey, Allan L.; Lah, James J.; Behan, Kelly; Scott Turner, Raymond; Johnson, Kathleen; Reynolds, Brigid; Pearlson, Godfrey D.; Blank, Karen; Anderson, Karen; Obisesan, Thomas O.; Wolday, Saba; Allard, Joanne; Lerner, Alan; Ogrocki, Paula; Tatsuoka, Curtis; Fatica, Parianne; Farlow, Martin R.; Saykin, Andrew J.; Foroud, Tatiana M.; Shen, Li; Faber, Kelly; Kim, Sungeun; Nho, Kwangsik; Marie Hake, Ann; Matthews, Brandy R.; Brosch, Jared R.; Herring, Scott; Hunt, Cynthia; Albert, Marilyn; Onyike, Chiadi; D’Agostino, Daniel; Kielb, Stephanie; Graff-Radford, Neill R; Parfitt, Francine; Kendall, Tracy; Johnson, Heather; Petersen, Ronald; Jack, Clifford R.; Bernstein, Matthew; Borowski, Bret; Gunter, Jeff; Senjem, Matt; Vemuri, Prashanthi; Jones, David; Kantarci, Kejal; Ward, Chad; Mason, Sara S.; Albers, Colleen S.; Knopman, David; Johnson, Kris; Chertkow, Howard; Hosein, Chris; Mintzer, Jacob; Spicer, Kenneth; Bachman, David; Grossman, Hillel; Mitsis, Effie; Pomara, Nunzio; Hernando, Raymundo; Sarrael, Antero; Potter, William; Buckholtz, Neil; Hsiao, John; Kittur, Smita; Galvin, James E.; Cerbone, Brittany; Michel, Christina A.; Pogorelec, Dana M.; Rusinek, Henry; de Leon, Mony J; Glodzik, Lidia; De Santi, Susan; Johnson, Nancy; Chuang-Kuo; Kerwin, Diana; Bonakdarpour, Borna; Weintraub, Sandra; Grafman, Jordan; Lipowski, Kristine; Mesulam, Marek-Marsel; Scharre, Douglas W.; Kataki, Maria; Adeli, Anahita; Kaye, Jeffrey; Quinn, Joseph; Silbert, Lisa; Lind, Betty; Carter, Raina; Dolen, Sara; Borrie, Michael; Lee, T-Y; Bartha, Rob; Martinez, Walter; Villena, Teresa; Sadowsky, Carl; Khachaturian, Zaven; Ott, Brian R.; Querfurth, Henry; Tremont, Geoffrey; Frank, Richard; Fleischman, Debra; Arfanakis, Konstantinos; Shah, Raj C.; deToledo-Morrell, Leyla; Sorensen, Greg; Finger, Elizabeth; Pasternack, Stephen; Rachinsky, Irina; Drost, Dick; Rogers, John; Kertesz, Andrew; Furst, Ansgar J.; Chad, Stevan; Yesavage, Jerome; Taylor, Joy L.; Lane, Barton; Rosen, Allyson; Tinklenberg, Jared; Black, Sandra; Stefanovic, Bojana; Caldwell, Curtis; Robin Hsiung, Ging-Yuek; Mudge, Benita; Assaly, Michele; Fox, Nick; Schultz, Susan K.; Boles Ponto, Laura L.; Shim, Hyungsub; Ekstam Smith, Karen; Burns, Jeffrey M.; Swerdlow, Russell H.; Brooks, William M.; Marson, Daniel; Griffith, Randall; Clark, David; Geldmacher, David; Brockington, John; Roberson, Erik; Natelson Love, Marissa; DeCarli, Charles; Carmichael, Owen; Olichney, John; Maillard, Pauline; Fletcher, Evan; Nguyen, Dana; Preda, Andrian; Potkin, Steven; Mulnard, Ruth A.; Thai, Gaby; McAdams-Ortiz, Catherine; Landau, Susan; Jagust, William; Apostolova, Liana; Tingus, Kathleen; Woo, Ellen; Silverman, Daniel H.S.; Lu, Po H.; Bartzokis, George; Thompson, Paul; Donohue, Michael; Thomas, Ronald G.; Walter, Sarah; Gessert, Devon; Brewer, James; Vanderswag, Helen; Sather, Tamie; Jiminez, Gus; Balasubramanian, Archana B.; Mason, Jennifer; Sim, Iris; Aisen, Paul; Davis, Melissa; Morrison, Rosemary; Harvey, Danielle; Thal, Lean; Beckett, Laurel; Neylan, Thomas; Finley, Shannon; Weiner, Michael W.; Hayes, Jacqueline; Rosen, Howard J.; Miller, Bruce L.; Perry, David; Massoglia, Dino; Brawman-Mentzer, Olga; Schuff, Norbert; Smith, Charles D.; Hardy, Peter; Sinha, Partha; Oates, Elizabeth; Conrad, Gary; Koeppe, Robert A.; Lord, Joanne L.; Heidebrink, Judith L.; Arnold, Steven E.; Karlawish, Jason H.; Wolk, David; Clark, Christopher M.; Trojanowki, John Q.; Shaw, Leslie M.; Lee, Virginia; Korecka, Magdalena; Figurski, Michal; Toga, Arthur W.; Crawford, Karen; Neu, Scott; Schneider, Lon S.; Pawluczyk, Sonia; Beccera, Mauricio; Teodoro, Liberty; Spann, Bryan M.; Womack, Kyle; Mathews, Dana; Quiceno, Mary; Foster, Norm; Montine, Tom; Fruehling, J. Jay; Harding, Sandra; Johnson, Sterling; Asthana, Sanjay; Carlsson, Cynthia M.; Petrie, Eric C.; Peskind, Elaine; Li, Gail; Porsteinsson, Anton P.; Goldstein, Bonnie S.; Martin, Kim; Makino, Kelly M.; Ismail, M. Saleem; Brand, Connie; Smith, Amanda; Ashok Raj, Balebail; Fargher, Kristin; Kuller, Lew; Mathis, Chet; Ann Oakley, Mary; Lopez, Oscar L.; Simpson, Donna M.; Sink, Kaycee M.; Gordineer, Leslie; Williamson, Jeff D.; Garg, Pradeep; Watkins, Franklin; Cairns, Nigel J.; Raichle, Marc; Morris, John C.; Householder, Erin; Taylor-Reinwald, Lisa; Holtzman, David; Ances, Beau; Carroll, Maria; Creech, Mary L.; Franklin, Erin; Mintun, Mark A.; Schneider, Stacy; Oliver, Angela; Duara, Ranjan; Varon, Daniel; Greig, Maria T.; Roberts, Peggy; Varma, Pradeep; MacAvoy, Martha G.; Carson, Richard E.; van Dyck, Christopher H.; Davies, Peter; Holtzman, David; Morris, John C.; Bales, Kelly; Pickering, Eve H.; Lee, Jin-Moo; Heitsch, Laura; Kauwe, John; Goate, Alison; Piccio, Laura; Cruchaga, Carlos

2016-01-01

Genome-wide association studies of 146 plasma protein levels in 818 individuals revealed 56 genome-wide significant associations (28 novel) with 47 analytes. Loci associated with plasma levels of 39 proteins tested have been previously associated with various complex traits such as heart disease, inflammatory bowel disease, Type 2 diabetes, and multiple sclerosis. These data suggest that these plasma protein levels may constitute informative endophenotypes for these complex traits. We found three potential pleiotropic genes: ABO for plasma SELE and ACE levels, FUT2 for CA19-9 and CEA plasma levels, and APOE for ApoE and CRP levels. We also found multiple independent signals in loci associated with plasma levels of ApoH, CA19-9, FetuinA, IL6r, and LPa. Our study highlights the power of biological traits for genetic studies to identify genetic variants influencing clinically relevant traits, potential pleiotropic effects, and complex disease associations in the same locus.

Systems-Level Synthetic Biology for Advanced Biofuel Production

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

Ruffing, Anne; Jensen, Travis J.; Strickland, Lucas Marshall

2015-03-01

Cyanobacteria have been shown to be capable of producing a variety of advanced biofuels; however, product yields remain well below those necessary for large scale production. New genetic tools and high throughput metabolic engineering techniques are needed to optimize cyanobacterial metabolisms for enhanced biofuel production. Towards this goal, this project advances the development of a multiple promoter replacement technique for systems-level optimization of gene expression in a model cyanobacterial host: Synechococcus sp. PCC 7002. To realize this multiple-target approach, key capabilities were developed, including a high throughput detection method for advanced biofuels, enhanced transformation efficiency, and genetic tools for Synechococcusmore » sp. PCC 7002. Moreover, several additional obstacles were identified for realization of this multiple promoter replacement technique. The techniques and tools developed in this project will help to enable future efforts in the advancement of cyanobacterial biofuels.« less

Integration of bioinformatics into an undergraduate biology curriculum and the impact on development of mathematical skills.

PubMed

Wightman, Bruce; Hark, Amy T

2012-01-01

The development of fields such as bioinformatics and genomics has created new challenges and opportunities for undergraduate biology curricula. Students preparing for careers in science, technology, and medicine need more intensive study of bioinformatics and more sophisticated training in the mathematics on which this field is based. In this study, we deliberately integrated bioinformatics instruction at multiple course levels into an existing biology curriculum. Students in an introductory biology course, intermediate lab courses, and advanced project-oriented courses all participated in new course components designed to sequentially introduce bioinformatics skills and knowledge, as well as computational approaches that are common to many bioinformatics applications. In each course, bioinformatics learning was embedded in an existing disciplinary instructional sequence, as opposed to having a single course where all bioinformatics learning occurs. We designed direct and indirect assessment tools to follow student progress through the course sequence. Our data show significant gains in both student confidence and ability in bioinformatics during individual courses and as course level increases. Despite evidence of substantial student learning in both bioinformatics and mathematics, students were skeptical about the link between learning bioinformatics and learning mathematics. While our approach resulted in substantial learning gains, student "buy-in" and engagement might be better in longer project-based activities that demand application of skills to research problems. Nevertheless, in situations where a concentrated focus on project-oriented bioinformatics is not possible or desirable, our approach of integrating multiple smaller components into an existing curriculum provides an alternative. Copyright © 2012 Wiley Periodicals, Inc.

Directed area search using socio-biological vision algorithms and cognitive Bayesian reasoning

NASA Astrophysics Data System (ADS)

Medasani, S.; Owechko, Y.; Allen, D.; Lu, T. C.; Khosla, D.

2010-04-01

Volitional search systems that assist the analyst by searching for specific targets or objects such as vehicles, factories, airports, etc in wide area overhead imagery need to overcome multiple problems present in current manual and automatic approaches. These problems include finding targets hidden in terabytes of information, relatively few pixels on targets, long intervals between interesting regions, time consuming analysis requiring many analysts, no a priori representative examples or templates of interest, detecting multiple classes of objects, and the need for very high detection rates and very low false alarm rates. This paper describes a conceptual analyst-centric framework that utilizes existing technology modules to search and locate occurrences of targets of interest (e.g., buildings, mobile targets of military significance, factories, nuclear plants, etc.), from video imagery of large areas. Our framework takes simple queries from the analyst and finds the queried targets with relatively minimum interaction from the analyst. It uses a hybrid approach that combines biologically inspired bottom up attention, socio-biologically inspired object recognition for volitionally recognizing targets, and hierarchical Bayesian networks for modeling and representing the domain knowledge. This approach has the benefits of high accuracy, low false alarm rate and can handle both low-level visual information and high-level domain knowledge in a single framework. Such a system would be of immense help for search and rescue efforts, intelligence gathering, change detection systems, and other surveillance systems.

Simultaneous measurement of NAD metabolome in aged mice tissue using liquid chromatography tandem-mass spectrometry.

PubMed

Yaku, Keisuke; Okabe, Keisuke; Nakagawa, Takashi

2018-06-01

Nicotinamide adenine dinucleotide (NAD) is a major co-factor that mediates multiple biological processes including redox reaction and gene expression. Recently, NAD metabolism has received considerable attention because administration of NAD precursors exhibited beneficial effects against aging-related metabolic disorders in animals. Although numerous studies have reported that NAD levels decline with aging in multiple animal tissues, the pathway and kinetics of NAD metabolism in aged organs are not completely understood. To determine the NAD metabolism upon aging, we developed targeted metabolomics based on an LC/MS/MS system. Our method is simple and applicable to crude biological samples, including culture cells and animal tissues. Unlike a conventional enzymatic cycling assay, our approach can determine NAD and NADH (reduced form of NAD) by performing a single sample preparation. Further, we validated our method using biological samples and investigated the alteration of the NAD metabolome during aging. Consistent with previous reports, the NAD levels in the liver and skeletal muscle decreased with aging. Further, we detected a significant increase in nicotinamide mononucleotide and nicotinamide riboside in the kidney upon aging. The LC/MS/MS-based NAD metabolomics that we have developed is extensively applicable to biomedical studies, and the results will present innovative ideas for the aging studies, especially for that of NAD metabolism. Copyright © 2018 John Wiley & Sons, Ltd.

ePlant: Visualizing and Exploring Multiple Levels of Data for Hypothesis Generation in Plant Biology.

PubMed

Waese, Jamie; Fan, Jim; Pasha, Asher; Yu, Hans; Fucile, Geoffrey; Shi, Ruian; Cumming, Matthew; Kelley, Lawrence A; Sternberg, Michael J; Krishnakumar, Vivek; Ferlanti, Erik; Miller, Jason; Town, Chris; Stuerzlinger, Wolfgang; Provart, Nicholas J

2017-08-01

A big challenge in current systems biology research arises when different types of data must be accessed from separate sources and visualized using separate tools. The high cognitive load required to navigate such a workflow is detrimental to hypothesis generation. Accordingly, there is a need for a robust research platform that incorporates all data and provides integrated search, analysis, and visualization features through a single portal. Here, we present ePlant (http://bar.utoronto.ca/eplant), a visual analytic tool for exploring multiple levels of Arabidopsis thaliana data through a zoomable user interface. ePlant connects to several publicly available web services to download genome, proteome, interactome, transcriptome, and 3D molecular structure data for one or more genes or gene products of interest. Data are displayed with a set of visualization tools that are presented using a conceptual hierarchy from big to small, and many of the tools combine information from more than one data type. We describe the development of ePlant in this article and present several examples illustrating its integrative features for hypothesis generation. We also describe the process of deploying ePlant as an "app" on Araport. Building on readily available web services, the code for ePlant is freely available for any other biological species research. © 2017 American Society of Plant Biologists. All rights reserved.

An investigation of bacterial protein interactions as a primary research project in a sophomore-level molecular biology course.

PubMed

Cardinale, Jean A

2011-01-01

Longer term research activities that may be incorporated in undergraduate courses are a powerful tool for promoting student interest and learning, developing cognitive process skills, and allowing undergraduates to experience real research activities in which they may not otherwise have the opportunity to participate. The challenge to doing so in lower-level courses is that students may have not fully grasped the scientific concepts needed to undertake such research endeavors, and that they may be discouraged if activities are perceived to be too challenging. The paper describes how a bacterial protein:protein interaction detection system was adapted and incorporated into the laboratory component of a sophomore-level Molecular Cell Biology course. The project was designed to address multiple learning objectives connecting course content to the laboratory activities, as well as teach basic molecular biology laboratory skills and procedures in the context of a primary research activity. Pre- and posttesting and student surveys both suggest that the laboratory curriculum resulted in significant learning gains, as well as being well received and valued by the students.

Multi-scale Multi-mechanism Toughening of Hydrogels

NASA Astrophysics Data System (ADS)

Zhao, Xuanhe

Hydrogels are widely used as scaffolds for tissue engineering, vehicles for drug delivery, actuators for optics and fluidics, and model extracellular matrices for biological studies. The scope of hydrogel applications, however, is often severely limited by their mechanical properties. Inspired by the mechanics and hierarchical structures of tough biological tissues, we propose that a general principle for the design of tough hydrogels is to implement two mechanisms for dissipating mechanical energy and maintaining high elasticity in hydrogels. A particularly promising strategy for the design is to integrate multiple pairs of mechanisms across multiple length scales into a hydrogel. We develop a multiscale theoretical framework to quantitatively guide the design of tough hydrogels. On the network level, we have developed micro-physical models to characterize the evolution of polymer networks under deformation. On the continuum level, we have implemented constitutive laws formulated from the network-level models into a coupled cohesive-zone and Mullins-effect model to quantitatively predict crack propagation and fracture toughness of hydrogels. Guided by the design principle and quantitative model, we will demonstrate a set of new hydrogels, based on diverse types of polymers, yet can achieve extremely high toughness superior to their natural counterparts such as cartilages. The work was supported by NSF(No. CMMI- 1253495) and ONR (No. N00014-14-1-0528).

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

Life-history strategies constrain invertebrate community tolerance to multiple stressors: A case study in the Ebro basin.

PubMed

Mondy, Cédric P; Muñoz, Isabel; Dolédec, Sylvain

2016-12-01

Multiple stressors constitute a serious threat to aquatic ecosystems, particularly in the Mediterranean region where water scarcity is likely to interact with other anthropogenic stressors. Biological traits potentially allow the unravelling of the effects of multiple stressors. However, thus far, trait-based approaches have failed to fully deliver on their promise and still lack strong predictive power when multiple stressors are present. We aimed to quantify specific community tolerances against six anthropogenic stressors and investigate the responses of the underlying macroinvertebrate biological traits and their combinations. We built and calibrated boosted regression tree models to predict community tolerances using multiple biological traits with a priori hypotheses regarding their individual responses to specific stressors. We analysed the combinations of traits underlying community tolerance and the effect of trait association on this tolerance. Our results validated the following three hypotheses: (i) the community tolerance models efficiently and robustly related trait combinations to stressor intensities and, to a lesser extent, to stressors related to the presence of dams and insecticides; (ii) the effects of traits on community tolerance not only depended on trait identity but also on the trait associations emerging at the community level from the co-occurrence of different traits in species; and (iii) the community tolerances and the underlying trait combinations were specific to the different stressors. This study takes a further step towards predictive tools in community ecology that consider combinations and associations of traits as the basis of stressor tolerance. Additionally, the community tolerance concept has potential application to help stream managers in the decision process regarding management options. Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.

Future Directions in Vulnerability to Depression among Youth: Integrating Risk Factors and Processes across Multiple Levels of Analysis

PubMed Central

Hankin, Benjamin L.

2014-01-01

Depression is a developmental phenomenon. Considerable progress has been made in describing the syndrome, establishing its prevalence and features, providing clues as to its etiology, and developing evidence-based treatment and prevention options. Despite considerable headway in distinct lines of vulnerability research, there is an explanatory gap in the field ability to more comprehensively explain and predict who is likely to become depressed, when, and why. Still, despite clear success in predicting moderate variance for future depression, especially with empirically rigorous methods and designs, the heterogeneous and multi-determined nature of depression suggests that additional etiologies need to be included to advance knowledge on developmental pathways to depression. This paper advocates for a multiple levels of analysis approach to investigating vulnerability to depression across the lifespan and providing a more comprehensive understanding of its etiology. One example of a multiple levels of analysis model of vulnerabilities to depression is provided that integrates the most accessible, observable factors (e.g., cognitive and temperament risks), intermediate processes and endophenotypes (e.g., information processing biases, biological stress physiology, and neural activation and connectivity), and genetic influences (e.g., candidate genes and epigenetics). Evidence for each of these factors as well as their cross-level integration is provided. Methodological and conceptual considerations important for conducting integrative, multiple levels of depression vulnerability research are discussed. Finally, translational implications for how a multiple levels of analysis perspective may confer additional leverage to reduce the global burden of depression and improve care are considered. PMID:22900513

Evaluating anthropogenic risk of grassland and forest habitat degradation using land-cover data

Treesearch

Kurt Riitters; James Wickham; Timothy Wade

2009-01-01

The effects of landscape context on habitat quality are receiving increased attention in conservation biology. The objective of this research is to demonstrate a landscape-level approach to mapping and evaluating the anthropogenic risks of grassland and forest habitat degradation by examining habitat context as defined by intensive anthropogenic land uses at multiple...

Turning the Potential Liability of Large Enrollment Laboratory Science Courses into an Asset

ERIC Educational Resources Information Center

Johnson, Dan; Levy, Foster; Karsai, Istvan; Stroud, Kimberly

2006-01-01

Data sharing among multiple lab sections increases statistical power of data analyses and informs student-generated hypotheses. We describe how to collect, organize, and manage data to support replicate and rolling inquiry models, with three illustrative examples of activities from a population-level biology course for science majors. (Contains 1…

The impact of the invasive brown marmorated stink bug in North America and Europe: history, biology, ecology, and management

USDA-ARS?s Scientific Manuscript database

Brown marmorated stink bug (BMSB), Halyomorpha halys (Stål), is an invasive Pentatomidae introduced to the USA, Canada, and multiple European countries. In 2010, BMSB populations in the mid-Atlantic region USA reached outbreak levels, and subsequent feeding resulted in severe damage to tree fruit a...

Prospective Elementary Science Teachers' Understanding of Photosynthesis and Cellular Respiration in the Context of Multiple Biological Levels as Nested Systems

ERIC Educational Resources Information Center

Akçay, Süleyman

2017-01-01

In this study, Turkish prospective elementary science teachers' understanding of photosynthesis and cellular respiration has been analysed within the contexts of ecosystem knowledge, organism knowledge and interconnection knowledge (IK). In the analysis, concept maps developed by 74 prospective teachers were used. The study was carried out with…

SPECIATION ANALYSIS OF ARSENIC IN BIOLOGICAL MATRICES BY AUTOMATED HYDRIDE GENERATION-CRYOTRAPPING-ATOMIC ABSORPTION SPECTROMETRY WITH MULTIPLE MICROFLAME QUARTZ TUBE ATOMIZER (MULTIATOMIZER)

EPA Science Inventory

Abstract Analyses of arsenic (As) species in tissues and body fluids of individuals chronically exposed to inorganic arsenic (iAs) provide essential information about the exposure level and pattern of iAs metabolism. We have previously described an oxidation state-specifi...

Predictors of student success in entry-level science courses

NASA Astrophysics Data System (ADS)

Singh, Mamta K.

Although the educational evaluation process is useful and valuable and is supported by the Higher Education Act, a strong research base for program evaluation of college entry-level science courses is still lacking. Studies in science disciplines such as, biology, chemistry, and physics have addressed various affective and demographic factors and their relationships to student achievement. However, the literature contains little information that specifically addresses student biology content knowledge skills (basics and higher order thinking skills) and identifies factors that affect students' success in entry-level college science courses. These gate-keeping courses require detailed evaluation if the goal of an institution is to increase students' performance and success in these courses. These factors are, in fact, a stepping stone for increasing the number of graduates in Science, Technology, Engineering, and Mathematics (STEM) majors. The present study measured students' biology content knowledge and investigated students' performance and success in college biology, chemistry, and physics entry-level courses. Seven variables---gender, ethnicity, high school Grade Point Average (GPA), high school science, college major, school financial aid support, and work hours were used as independent variables and course final performance as a dichotomous dependent variable. The sample comprised voluntary student participants in entry-level science courses. The study attempted to explore eight research questions. Content knowledge assessments, demographic information analysis, multiple regression analysis, and binary logistic regression analysis were used to address research questions. The results suggested that high school GPA was a consistently good predictor of students' performance and success in entry-level science courses. Additionally, high school chemistry was a significant predictor variable for student success in entry-level biology and chemistry courses. Similarly, students' performance and success in entry-level physics courses were influenced by high school physics. Finally, the study developed student success equation with high school GAP and high school chemistry as good predictors of students' success in entry-level science courses.

Synthetic Biology Platform for Sensing and Integrating Endogenous Transcriptional Inputs in Mammalian Cells.

PubMed

Angelici, Bartolomeo; Mailand, Erik; Haefliger, Benjamin; Benenson, Yaakov

2016-08-30

One of the goals of synthetic biology is to develop programmable artificial gene networks that can transduce multiple endogenous molecular cues to precisely control cell behavior. Realizing this vision requires interfacing natural molecular inputs with synthetic components that generate functional molecular outputs. Interfacing synthetic circuits with endogenous mammalian transcription factors has been particularly difficult. Here, we describe a systematic approach that enables integration and transduction of multiple mammalian transcription factor inputs by a synthetic network. The approach is facilitated by a proportional amplifier sensor based on synergistic positive autoregulation. The circuits efficiently transduce endogenous transcription factor levels into RNAi, transcriptional transactivation, and site-specific recombination. They also enable AND logic between pairs of arbitrary transcription factors. The results establish a framework for developing synthetic gene networks that interface with cellular processes through transcriptional regulators. Copyright © 2016 The Author(s). Published by Elsevier Inc. All rights reserved.

Multiple network-constrained regressions expand insights into influenza vaccination responses.

PubMed

Avey, Stefan; Mohanty, Subhasis; Wilson, Jean; Zapata, Heidi; Joshi, Samit R; Siconolfi, Barbara; Tsang, Sui; Shaw, Albert C; Kleinstein, Steven H

2017-07-15

Systems immunology leverages recent technological advancements that enable broad profiling of the immune system to better understand the response to infection and vaccination, as well as the dysregulation that occurs in disease. An increasingly common approach to gain insights from these large-scale profiling experiments involves the application of statistical learning methods to predict disease states or the immune response to perturbations. However, the goal of many systems studies is not to maximize accuracy, but rather to gain biological insights. The predictors identified using current approaches can be biologically uninterpretable or present only one of many equally predictive models, leading to a narrow understanding of the underlying biology. Here we show that incorporating prior biological knowledge within a logistic modeling framework by using network-level constraints on transcriptional profiling data significantly improves interpretability. Moreover, incorporating different types of biological knowledge produces models that highlight distinct aspects of the underlying biology, while maintaining predictive accuracy. We propose a new framework, Logistic Multiple Network-constrained Regression (LogMiNeR), and apply it to understand the mechanisms underlying differential responses to influenza vaccination. Although standard logistic regression approaches were predictive, they were minimally interpretable. Incorporating prior knowledge using LogMiNeR led to models that were equally predictive yet highly interpretable. In this context, B cell-specific genes and mTOR signaling were associated with an effective vaccination response in young adults. Overall, our results demonstrate a new paradigm for analyzing high-dimensional immune profiling data in which multiple networks encoding prior knowledge are incorporated to improve model interpretability. The R source code described in this article is publicly available at https://bitbucket.org/kleinstein/logminer . steven.kleinstein@yale.edu or stefan.avey@yale.edu. Supplementary data are available at Bioinformatics online. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com

Impacts of Air Pollution and Climate Change on Forest Ecosystems — Emerging Research Needs

PubMed Central

Paoletti, Elena; Bytnerowicz, Andrzej; Andersen, Chris; Augustaitis, Algirdas; Ferretti, Marco; Grulke, Nancy; Günthardt-Goerg, Madeleine S.; Innes, John; Johnson, Dale; Karnosky, Dave; Luangjame, Jesada; Matyssek, Rainer; McNulty, Steven; Müller-Starck, Gerhard; Musselman, Robert; Percy, Kevin

2007-01-01

Outcomes from the 22nd meeting for Specialists in Air Pollution Effects on Forest Ecosystems “Forests under Anthropogenic Pressure Effects of Air Pollution, Climate Change and Urban Development”, September 1016, 2006, Riverside, CA, are summarized. Tropospheric or ground-level ozone (O3) is still the phytotoxic air pollutant of major interest. Challenging issues are how to make O3 standards or critical levels more biologically based and at the same time practical for wide use; quantification of plant detoxification processes in flux modeling; inclusion of multiple environmental stresses in critical load determinations; new concept development for nitrogen saturation; interactions between air pollution, climate, and forest pests; effects of forest fire on air quality; the capacity of forests to sequester carbon under changing climatic conditions and coexposure to elevated levels of air pollutants; enhanced linkage between molecular biology, biochemistry, physiology, and morphological traits. PMID:17450274

Biological intuition in alignment-free methods: response to Posada.

PubMed

Ragan, Mark A; Chan, Cheong Xin

2013-08-01

A recent editorial in Journal of Molecular Evolution highlights opportunities and challenges facing molecular evolution in the era of next-generation sequencing. Abundant sequence data should allow more-complex models to be fit at higher confidence, making phylogenetic inference more reliable and improving our understanding of evolution at the molecular level. However, concern that approaches based on multiple sequence alignment may be computationally infeasible for large datasets is driving the development of so-called alignment-free methods for sequence comparison and phylogenetic inference. The recent editorial characterized these approaches as model-free, not based on the concept of homology, and lacking in biological intuition. We argue here that alignment-free methods have not abandoned models or homology, and can be biologically intuitive.

Identification of predictive markers of cytarabine response in AML by integrative analysis of gene-expression profiles with multiple phenotypes

PubMed Central

Lamba, Jatinder K; Crews, Kristine R; Pounds, Stanley B; Cao, Xueyuan; Gandhi, Varsha; Plunkett, William; Razzouk, Bassem I; Lamba, Vishal; Baker, Sharyn D; Raimondi, Susana C; Campana, Dario; Pui, Ching-Hon; Downing, James R; Rubnitz, Jeffrey E; Ribeiro, Raul C

2011-01-01

Aim To identify gene-expression signatures predicting cytarabine response by an integrative analysis of multiple clinical and pharmacological end points in acute myeloid leukemia (AML) patients. Materials & methods We performed an integrated analysis to associate the gene expression of diagnostic bone marrow blasts from acute myeloid leukemia (AML) patients treated in the discovery set (AML97; n = 42) and in the independent validation set (AML02; n = 46) with multiple clinical and pharmacological end points. Based on prior biological knowledge, we defined a gene to show a therapeutically beneficial (detrimental) pattern of association of its expression positively (negatively) correlated with favorable phenotypes such as intracellular cytarabine 5´-triphosphate levels, morphological response and event-free survival, and negatively (positively) correlated with unfavorable end points such as post-cytarabine DNA synthesis levels, minimal residual disease and cytarabine LC50. Results We identified 240 probe sets predicting a therapeutically beneficial pattern and 97 predicting detrimental pattern (p ≤ 0.005) in the discovery set. Of these, 60 were confirmed in the independent validation set. The validated probe sets correspond to genes involved in PIK3/PTEN/AKT/mTOR signaling, G-protein-coupled receptor signaling and leukemogenesis. This suggests that targeting these pathways as potential pharmacogenomic and therapeutic candidates could be useful for improving treatment outcomes in AML. Conclusion This study illustrates the power of integrated data analysis of genomic data as well as multiple clinical and pharmacologic end points in the identification of genes and pathways of biological relevance. PMID:21449673

BiologicalNetworks 2.0 - an integrative view of genome biology data

PubMed Central

2010-01-01

Background A significant problem in the study of mechanisms of an organism's development is the elucidation of interrelated factors which are making an impact on the different levels of the organism, such as genes, biological molecules, cells, and cell systems. Numerous sources of heterogeneous data which exist for these subsystems are still not integrated sufficiently enough to give researchers a straightforward opportunity to analyze them together in the same frame of study. Systematic application of data integration methods is also hampered by a multitude of such factors as the orthogonal nature of the integrated data and naming problems. Results Here we report on a new version of BiologicalNetworks, a research environment for the integral visualization and analysis of heterogeneous biological data. BiologicalNetworks can be queried for properties of thousands of different types of biological entities (genes/proteins, promoters, COGs, pathways, binding sites, and other) and their relations (interactions, co-expression, co-citations, and other). The system includes the build-pathways infrastructure for molecular interactions/relations and module discovery in high-throughput experiments. Also implemented in BiologicalNetworks are the Integrated Genome Viewer and Comparative Genomics Browser applications, which allow for the search and analysis of gene regulatory regions and their conservation in multiple species in conjunction with molecular pathways/networks, experimental data and functional annotations. Conclusions The new release of BiologicalNetworks together with its back-end database introduces extensive functionality for a more efficient integrated multi-level analysis of microarray, sequence, regulatory, and other data. BiologicalNetworks is freely available at http://www.biologicalnetworks.org. PMID:21190573

Case studies of hydrogen sulphide occupational exposure incidents in the UK.

PubMed

Jones, Kate

2014-12-15

The UK Health and Safety Executive has investigated several incidents of workplace accidents involving hydrogen sulphide exposure in recent years. Biological monitoring has been used in some incidents to determine the cause of unconsciousness resulting from these incidents and as a supporting evidence in regulatory enforcement. This paper reports on three case incidents and discusses the use of biological monitoring in such cases. Biological monitoring has a role in identifying hydrogen sulphide exposure in incidents, whether these are occupational or in the wider environment. Sample type, time of collection and sample storage are important factors in the applicability of this technique. For non-fatal incidents, multiple urine samples are recommended at two or more time points between the incident and 15 h post-exposure. For routine occupational monitoring, post-shift samples should be adequate. Due to endogenous levels of urinary thiosulphate, it is likely that exposures in excess of 12 ppm for 30 min (or 360 ppm/min equivalent) would be detectable using biological monitoring. This is within the Acute Exposure Guideline Level 2 (the level of the chemical in air at or above which there may be irreversible or other serious long-lasting effects or impaired ability to escape) for hydrogen sulphide. Crown Copyright © 2014. Published by Elsevier Ireland Ltd. All rights reserved.

NASA Human Research Program Space Radiation Program Element

NASA Technical Reports Server (NTRS)

Chappell, Lori; Huff, Janice; Patel, Janapriya; Wang, Minli; Hu, Shaowwen; Kidane, Yared; Myung-Hee, Kim; Li, Yongfeng; Nounu, Hatem; Plante, Ianik;

Genome-Wide Detection and Analysis of Multifunctional Genes

PubMed Central

Pritykin, Yuri; Ghersi, Dario; Singh, Mona

2015-01-01

Many genes can play a role in multiple biological processes or molecular functions. Identifying multifunctional genes at the genome-wide level and studying their properties can shed light upon the complexity of molecular events that underpin cellular functioning, thereby leading to a better understanding of the functional landscape of the cell. However, to date, genome-wide analysis of multifunctional genes (and the proteins they encode) has been limited. Here we introduce a computational approach that uses known functional annotations to extract genes playing a role in at least two distinct biological processes. We leverage functional genomics data sets for three organisms—H. sapiens, D. melanogaster, and S. cerevisiae—and show that, as compared to other annotated genes, genes involved in multiple biological processes possess distinct physicochemical properties, are more broadly expressed, tend to be more central in protein interaction networks, tend to be more evolutionarily conserved, and are more likely to be essential. We also find that multifunctional genes are significantly more likely to be involved in human disorders. These same features also hold when multifunctionality is defined with respect to molecular functions instead of biological processes. Our analysis uncovers key features about multifunctional genes, and is a step towards a better genome-wide understanding of gene multifunctionality. PMID:26436655

Aerated biofilters with multiple-level air injection configurations to enhance biological treatment of methane emissions.

PubMed

Farrokhzadeh, Hasti; Hettiaratchi, J Patrick A; Jayasinghe, Poornima; Kumar, Sunil

2017-09-01

Aiming to improve conventional methane biofilter performance, a multiple-level aeration biofilter design is proposed. Laboratory flow-through column experiments were conducted to evaluate three actively-aerated methane biofilter configurations. Columns were aerated at one, two, and three levels of the bed depth, with air introduced at flow rates calculated from methane oxidation reaction stoichiometry. Inlet methane loading rates were increased in five stages between 6 and 18mL/min. The effects of methane feeding rate, levels of aeration, and residence time on methane oxidation rates were determined. Samples collected after completion of flow-through experiments were used to determine methane oxidation kinetic parameters, V max , K m , and methanotrophic community distribution across biofilter columns. Results obtained from mixed variances analysis and response surfaces, as well as methanotrophic activity data, suggested that, biofilter column with two aeration levels has the most even performance over time, maintaining 85.1% average oxidation efficiency over 95days of experiments. Copyright © 2017 Elsevier Ltd. All rights reserved.

Preventability of Cancer

PubMed Central

Colditz, Graham A.; Wei, Esther K.

2013-01-01

Whereas models of cancer disparities and variation in cancer burden within population groups now specify multiple levels of action from biologic processes to individual risk factors and social and physical contextual factors, approaches to estimating the preventable proportion of cancer use more traditional direct models often from single exposures to cancer at specific organ sites. These approaches are reviewed, and the strengths and limitations are presented. The need for additional multilevel data and approaches to estimation of preventability are identified. International or regional variation in cancer may offer the most integrated exposure assessment over the life course. For the four leading cancers, which account for 50% of incidence and mortality, biologic, social, and physical environments play differing roles in etiology and potential prevention. Better understanding of the interactions and contributions across these levels will help refine prevention strategies. PMID:22224878

Genetic tool development and systemic regulation in biosynthetic technology.

PubMed

Dai, Zhongxue; Zhang, Shangjie; Yang, Qiao; Zhang, Wenming; Qian, Xiujuan; Dong, Weiliang; Jiang, Min; Xin, Fengxue

2018-01-01

With the increased development in research, innovation, and policy interest in recent years, biosynthetic technology has developed rapidly, which combines engineering, electronics, computer science, mathematics, and other disciplines based on classical genetic engineering and metabolic engineering. It gives a wider perspective and a deeper level to perceive the nature of life via cell mechanism, regulatory networks, or biological evolution. Currently, synthetic biology has made great breakthrough in energy, chemical industry, and medicine industries, particularly in the programmable genetic control at multiple levels of regulation to perform designed goals. In this review, the most advanced and comprehensive developments achieved in biosynthetic technology were represented, including genetic engineering as well as synthetic genomics. In addition, the superiority together with the limitations of the current genome-editing tools were summarized.

Too much of a good thing? Cardiac vagal tone's nonlinear relationship with well-being.

PubMed

Kogan, Aleksandr; Gruber, June; Shallcross, Amanda J; Ford, Brett Q; Mauss, Iris B

2013-08-01

Parasympathetic regulation of heart rate through the vagus nerve--often measured as resting respiratory sinus arrhythmia or cardiac vagal tone (CVT)--is a key biological correlate of psychological well-being. However, recent theorizing has suggested that many biological and psychological processes can become maladaptive when they reach extreme levels. This raises the possibility that CVT might not have an unmitigated positive relationship with well-being. In line with this reasoning, across 231 adult participants (Mage = 40.02 years; 52% female), we found that CVT was quadratically related to multiple measures of well-being, including life satisfaction and depressive symptoms. Individuals with moderate CVT had higher well-being than those with low or high CVT. These results provide the first direct evidence of a nonlinear relationship between CVT and well-being, adding to a growing body of research that has suggested some biological processes may cease being adaptive when they reach extreme levels. PsycINFO Database Record (c) 2013 APA, all rights reserved.

The evolution of colony-level development in the Siphonophora (Cnidaria:Hydrozoa).

PubMed

Dunn, Casey W; Wagner, Günter P

2006-12-01

Evolutionary developmental biology has focused almost exclusively on multicellular organisms, but there are other relevant levels of biological organization that have remained largely neglected. Animal colonies are made up of multiple physiologically integrated and genetically identical units called zooids that are each homologous to solitary, free-living animals. Siphonophores, a group of pelagic hydrozoans (Cnidaria), have the most complex colony-level organization of all animals. Here the colony-level development of five siphonophore species, strategically sampled across the siphonophore phylogeny, is described from specimens collected using deep-sea submersibles and by self-contained underwater breathing apparatus diving. These species include three cystonects, Bathyphysa sibogae, Rhizophysa filiformis, and Rhizophysa eysenhardti, and two "physonects", Agalma elegans and Nanomia bijuga. These data, together with previous findings, are analyzed in a phylogenetic framework to reconstruct key features of the history of colony-level organization and development in the Siphonophora. It is shown that gonodendra and gastrozooids of the examined cystonects arise as independent buds directly on the stem, whereas probud subdivision (the origin of feeding, reproductive, and other zooids from a single bud) is a synapomorphy of the Codonophora. The origin of probud subdivision is associated with the origin of cormidia as integrated units of colony organization, and may have allowed for greater morphological and ecological diversification in the Codonophora relative to the Cystonectae. It is also found that symmetry is labile in siphonophores, with multiple gains and/or losses of directional asymmetry in the group. This descriptive work will enable future mechanistic and molecular studies of colony-level development in the siphonophores.

The Math–Biology Values Instrument: Development of a Tool to Measure Life Science Majors’ Task Values of Using Math in the Context of Biology

PubMed Central

Andrews, Sarah E.; Runyon, Christopher; Aikens, Melissa L.

2017-01-01

In response to calls to improve the quantitative training of undergraduate biology students, there have been increased efforts to better integrate math into biology curricula. One challenge of such efforts is negative student attitudes toward math, which are thought to be particularly prevalent among biology students. According to theory, students’ personal values toward using math in a biological context will influence their achievement and behavioral outcomes, but a validated instrument is needed to determine this empirically. We developed the Math–Biology Values Instrument (MBVI), an 11-item college-level self-­report instrument grounded in expectancy-value theory, to measure life science students’ interest in using math to understand biology, the perceived usefulness of math to their life science career, and the cost of using math in biology courses. We used a process that integrates multiple forms of validity evidence to show that scores from the MBVI can be used as a valid measure of a student’s value of math in the context of biology. The MBVI can be used by instructors and researchers to help identify instructional strategies that influence math–biology values and understand how math–biology values are related to students’ achievement and decisions to pursue more advanced quantitative-based courses. PMID:28747355

Parallel seed-based approach to multiple protein structure similarities detection

DOE PAGES

Chapuis, Guillaume; Le Boudic-Jamin, Mathilde; Andonov, Rumen; ...

2015-01-01

Finding similarities between protein structures is a crucial task in molecular biology. Most of the existing tools require proteins to be aligned in order-preserving way and only find single alignments even when multiple similar regions exist. We propose a new seed-based approach that discovers multiple pairs of similar regions. Its computational complexity is polynomial and it comes with a quality guarantee—the returned alignments have both root mean squared deviations (coordinate-based as well as internal-distances based) lower than a given threshold, if such exist. We do not require the alignments to be order preserving (i.e., we consider nonsequential alignments), which makesmore » our algorithm suitable for detecting similar domains when comparing multidomain proteins as well as to detect structural repetitions within a single protein. Because the search space for nonsequential alignments is much larger than for sequential ones, the computational burden is addressed by extensive use of parallel computing techniques: a coarse-grain level parallelism making use of available CPU cores for computation and a fine-grain level parallelism exploiting bit-level concurrency as well as vector instructions.« less

Quantitative Proteomics via High Resolution MS Quantification: Capabilities and Limitations

PubMed Central

Higgs, Richard E.; Butler, Jon P.; Han, Bomie; Knierman, Michael D.

2013-01-01

Recent improvements in the mass accuracy and resolution of mass spectrometers have led to renewed interest in label-free quantification using data from the primary mass spectrum (MS1) acquired from data-dependent proteomics experiments. The capacity for higher specificity quantification of peptides from samples enriched for proteins of biological interest offers distinct advantages for hypothesis generating experiments relative to immunoassay detection methods or prespecified peptide ions measured by multiple reaction monitoring (MRM) approaches. Here we describe an evaluation of different methods to post-process peptide level quantification information to support protein level inference. We characterize the methods by examining their ability to recover a known dilution of a standard protein in background matrices of varying complexity. Additionally, the MS1 quantification results are compared to a standard, targeted, MRM approach on the same samples under equivalent instrument conditions. We show the existence of multiple peptides with MS1 quantification sensitivity similar to the best MRM peptides for each of the background matrices studied. Based on these results we provide recommendations on preferred approaches to leveraging quantitative measurements of multiple peptides to improve protein level inference. PMID:23710359

A Partial Flip Classroom Exercise in a Large Introductory General Biology Course Increases Performance at Multiple Levels

ERIC Educational Resources Information Center

Lax, Neil; Morris, James; Kolber, Benedict J.

2017-01-01

Incorporation of active learning into large lecture classes is gaining popularity as a pedagogical method due to its known benefits in helping learning outcomes. A more recent active learning technique that has emerged is the flipped classroom. In this study, we investigated the effects of incorporating a "partial-flip" into an…

Embodying Markov blankets. Comment on "Answering Schrödinger's question: A free-energy formulation" by Maxwell James Désormeau Ramstead et al.

NASA Astrophysics Data System (ADS)

Pezzulo, Giovanni; Levin, Michael

2018-03-01

The free-energy principle (FEP) has been initially proposed as a theory of brain structure and function [1], but its scope is rapidly extending to explain biological phenomena at multiple levels of complexity, from simple life forms and their morphology [2] to complex societal and cultural dynamics [3].

Vegetation engineers marsh morphology through multiple competing stable states

NASA Astrophysics Data System (ADS)

Marani, Marco; Da Lio, Cristina; D'Alpaos, Andrea

2013-02-01

Marshes display impressive biogeomorphic features, such as zonation, a mosaic of extensive vegetation patches of rather uniform composition, exhibiting sharp transitions in the presence of extremely small topographic gradients. Although generally associated with the accretion processes necessary for marshes to keep up with relative sea level rise, competing environmental constraints, and ecologic controls, zonation is still poorly understood in terms of the underlying biogeomorphic mechanisms. Here we find, through observations and modeling interpretation, that zonation is the result of coupled geomorphological-biological dynamics and that it stems from the ability of vegetation to actively engineer the landscape by tuning soil elevation within preferential ranges of optimal adaptation. We find multiple peaks in the frequency distribution of observed topographic elevation and identify them as the signature of biologic controls on geomorphodynamics through competing stable states modulated by the interplay of inorganic and organic deposition. Interestingly, the stable biogeomorphic equilibria correspond to suboptimal rates of biomass production, a result coherent with recent observations. The emerging biogeomorphic structures may display varying degrees of robustness to changes in the rate of sea level rise and sediment availability, with implications for the overall resilience of marsh ecosystems to climatic changes.

Vegetation engineers marsh morphology through multiple competing stable states

PubMed Central

Marani, Marco; Da Lio, Cristina; D’Alpaos, Andrea

2013-01-01

Marshes display impressive biogeomorphic features, such as zonation, a mosaic of extensive vegetation patches of rather uniform composition, exhibiting sharp transitions in the presence of extremely small topographic gradients. Although generally associated with the accretion processes necessary for marshes to keep up with relative sea level rise, competing environmental constraints, and ecologic controls, zonation is still poorly understood in terms of the underlying biogeomorphic mechanisms. Here we find, through observations and modeling interpretation, that zonation is the result of coupled geomorphological–biological dynamics and that it stems from the ability of vegetation to actively engineer the landscape by tuning soil elevation within preferential ranges of optimal adaptation. We find multiple peaks in the frequency distribution of observed topographic elevation and identify them as the signature of biologic controls on geomorphodynamics through competing stable states modulated by the interplay of inorganic and organic deposition. Interestingly, the stable biogeomorphic equilibria correspond to suboptimal rates of biomass production, a result coherent with recent observations. The emerging biogeomorphic structures may display varying degrees of robustness to changes in the rate of sea level rise and sediment availability, with implications for the overall resilience of marsh ecosystems to climatic changes. PMID:23401529

Signaling mechanisms underlying the robustness and tunability of the plant immune network

PubMed Central

Kim, Yungil; Tsuda, Kenichi; Igarashi, Daisuke; Hillmer, Rachel A.; Sakakibara, Hitoshi; Myers, Chad L.; Katagiri, Fumiaki

2014-01-01

Summary How does robust and tunable behavior emerge in a complex biological network? We sought to understand this for the signaling network controlling pattern-triggered immunity (PTI) in Arabidopsis. A dynamic network model containing four major signaling sectors, the jasmonate, ethylene, PAD4, and salicylate sectors, which together explain up to 80% of the PTI level, was built using data for dynamic sector activities and PTI levels under exhaustive combinatorial sector perturbations. Our regularized multiple regression model had a high level of predictive power and captured known and unexpected signal flows in the network. The sole inhibitory sector in the model, the ethylene sector, was central to the network robustness via its inhibition of the jasmonate sector. The model's multiple input sites linked specific signal input patterns varying in strength and timing to different network response patterns, indicating a mechanism enabling tunability. PMID:24439900

Root Systems Biology: Integrative Modeling across Scales, from Gene Regulatory Networks to the Rhizosphere1

PubMed Central

Hill, Kristine; Porco, Silvana; Lobet, Guillaume; Zappala, Susan; Mooney, Sacha; Draye, Xavier; Bennett, Malcolm J.

2013-01-01

Genetic and genomic approaches in model organisms have advanced our understanding of root biology over the last decade. Recently, however, systems biology and modeling have emerged as important approaches, as our understanding of root regulatory pathways has become more complex and interpreting pathway outputs has become less intuitive. To relate root genotype to phenotype, we must move beyond the examination of interactions at the genetic network scale and employ multiscale modeling approaches to predict emergent properties at the tissue, organ, organism, and rhizosphere scales. Understanding the underlying biological mechanisms and the complex interplay between systems at these different scales requires an integrative approach. Here, we describe examples of such approaches and discuss the merits of developing models to span multiple scales, from network to population levels, and to address dynamic interactions between plants and their environment. PMID:24143806

Comparative study of classification algorithms for immunosignaturing data

PubMed Central

2012-01-01

Background High-throughput technologies such as DNA, RNA, protein, antibody and peptide microarrays are often used to examine differences across drug treatments, diseases, transgenic animals, and others. Typically one trains a classification system by gathering large amounts of probe-level data, selecting informative features, and classifies test samples using a small number of features. As new microarrays are invented, classification systems that worked well for other array types may not be ideal. Expression microarrays, arguably one of the most prevalent array types, have been used for years to help develop classification algorithms. Many biological assumptions are built into classifiers that were designed for these types of data. One of the more problematic is the assumption of independence, both at the probe level and again at the biological level. Probes for RNA transcripts are designed to bind single transcripts. At the biological level, many genes have dependencies across transcriptional pathways where co-regulation of transcriptional units may make many genes appear as being completely dependent. Thus, algorithms that perform well for gene expression data may not be suitable when other technologies with different binding characteristics exist. The immunosignaturing microarray is based on complex mixtures of antibodies binding to arrays of random sequence peptides. It relies on many-to-many binding of antibodies to the random sequence peptides. Each peptide can bind multiple antibodies and each antibody can bind multiple peptides. This technology has been shown to be highly reproducible and appears promising for diagnosing a variety of disease states. However, it is not clear what is the optimal classification algorithm for analyzing this new type of data. Results We characterized several classification algorithms to analyze immunosignaturing data. We selected several datasets that range from easy to difficult to classify, from simple monoclonal binding to complex binding patterns in asthma patients. We then classified the biological samples using 17 different classification algorithms. Using a wide variety of assessment criteria, we found ‘Naïve Bayes’ far more useful than other widely used methods due to its simplicity, robustness, speed and accuracy. Conclusions ‘Naïve Bayes’ algorithm appears to accommodate the complex patterns hidden within multilayered immunosignaturing microarray data due to its fundamental mathematical properties. PMID:22720696

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.

A comparative study of students' performance in preclinical physiology assessed by multiple choice and short essay questions.

PubMed

Oyebola, D D; Adewoye, O E; Iyaniwura, J O; Alada, A R; Fasanmade, A A; Raji, Y

2000-01-01

This study was designed to compare the performance of medical students in physiology when assessed by multiple choice questions (MCQs) and short essay questions (SEQs). The study also examined the influence of factors such as age, sex, O/level grades and JAMB scores on performance in the MCQs and SEQs. A structured questionnaire was administered to 264 medical students' four months before the Part I MBBS examination. Apart from personal data of each student, the questionnaire sought information on the JAMB scores and GCE O' Level grades of each student in English Language, Biology, Chemistry, Physics and Mathematics. The physiology syllabus was divided into five parts and the students were administered separate examinations (tests) on each part. Each test consisted of MCQs and SEQs. The performance in MCQs and SEQs were compared. Also, the effects of JAMB scores and GCE O/level grades on the performance in both the MCQs and SEQs were assessed. The results showed that the students performed better in all MCQ tests than in the SEQs. JAMB scores and O' level English Language grade had no significant effect on students' performance in MCQs and SEQs. However O' level grades in Biology, Chemistry, Physics and Mathematics had significant effects on performance in MCQs and SEQs. Inadequate knowledge of physiology and inability to present information in a logical sequence are believed to be major factors contributing to the poorer performance in the SEQs compared with MCQs. In view of the finding of significant association between performance in MCQs and SEQs and GCE O/level grades in science subjects and mathematics, it was recommended that both JAMB results and the GCE results in the four O/level subjects above may be considered when selecting candidates for admission into the medical schools.

Integrative Radiation Biology

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

Barcellos-Hoff, Mary Helen

We plan to study tissue-level mechanisms important to human breast radiation carcinogenesis. We propose that the cell biology of irradiated tissues reveals a coordinated multicellular damage response program in which individual cell contributions are primarily directed towards suppression of carcinogenesis and reestablishment of homeostasis. We identified transforming growth factor β1 (TGFβ) as a pivotal signal. Notably, we have discovered that TGFβ suppresses genomic instability by controlling the intrinsic DNA damage response and centrosome integrity. However, TGFβ also mediates disruption of microenvironment interactions, which drive epithelial to mesenchymal transition in irradiated human mammary epithelial cells. This apparent paradox of positive andmore » negative controls by TGFβ is the topic of the present proposal. First, we postulate that these phenotypes manifest differentially following fractionated or chronic exposures; second, that the interactions of multiple cell types in tissues modify the responses evident in this single cell type culture models. The goals are to: 1) study the effect of low dose rate and fractionated radiation exposure in combination with TGFβ on the irradiated phenotype and genomic instability of non-malignant human epithelial cells; and 2) determine whether stromal-epithelial interactions suppress the irradiated phenotype in cell culture and the humanized mammary mouse model. These data will be used to 3) develop a systems biology model that integrates radiation effects across multiple levels of tissue organization and time. Modeling multicellular radiation responses coordinated via extracellular signaling could have a significant impact on the extrapolation of human health risks from high dose to low dose/rate radiation exposure.« less

Metabolic pathways for the whole community.

PubMed

Hanson, Niels W; Konwar, Kishori M; Hawley, Alyse K; Altman, Tomer; Karp, Peter D; Hallam, Steven J

2014-07-22

A convergence of high-throughput sequencing and computational power is transforming biology into information science. Despite these technological advances, converting bits and bytes of sequence information into meaningful insights remains a challenging enterprise. Biological systems operate on multiple hierarchical levels from genomes to biomes. Holistic understanding of biological systems requires agile software tools that permit comparative analyses across multiple information levels (DNA, RNA, protein, and metabolites) to identify emergent properties, diagnose system states, or predict responses to environmental change. Here we adopt the MetaPathways annotation and analysis pipeline and Pathway Tools to construct environmental pathway/genome databases (ePGDBs) that describe microbial community metabolism using MetaCyc, a highly curated database of metabolic pathways and components covering all domains of life. We evaluate Pathway Tools' performance on three datasets with different complexity and coding potential, including simulated metagenomes, a symbiotic system, and the Hawaii Ocean Time-series. We define accuracy and sensitivity relationships between read length, coverage and pathway recovery and evaluate the impact of taxonomic pruning on ePGDB construction and interpretation. Resulting ePGDBs provide interactive metabolic maps, predict emergent metabolic pathways associated with biosynthesis and energy production and differentiate between genomic potential and phenotypic expression across defined environmental gradients. This multi-tiered analysis provides the user community with specific operating guidelines, performance metrics and prediction hazards for more reliable ePGDB construction and interpretation. Moreover, it demonstrates the power of Pathway Tools in predicting metabolic interactions in natural and engineered ecosystems.

Ex-vivo dynamic 3-D culture of human tissues in the RCCS™ bioreactor allows the study of Multiple Myeloma biology and response to therapy.

PubMed

Ferrarini, Marina; Steimberg, Nathalie; Ponzoni, Maurilio; Belloni, Daniela; Berenzi, Angiola; Girlanda, Stefania; Caligaris-Cappio, Federico; Mazzoleni, Giovanna; Ferrero, Elisabetta

2013-01-01

Three-dimensional (3-D) culture models are emerging as invaluable tools in tumor biology, since they reproduce tissue-specific structural features and cell-cell interactions more accurately than conventional 2-D cultures. Multiple Myeloma, which depends on myeloma cell-Bone Marrow microenvironment interactions for development and response to drugs, may particularly benefit from such an approach. An innovative 3-D dynamic culture model based on the use of the RCCS™ Bioreactor was developed to allow long-term culture of myeloma tissue explants. This model was first validated with normal and pathological explants, then applied to tissues from myeloma patients. In all cases, histological examination demonstrated maintenance of viable myeloma cells inside their native microenvironment, with an overall well preserved histo-architecture including bone lamellae and vessels. This system was then successfully applied to evaluate the cytotoxic effects exerted by the proteasome inhibitor Bortezomib not only on myeloma cells but also on angiogenic vessels. Moreover, as surrogate markers of specialized functions expressed by myeloma cells and microenvironment, β2 microglobulin, VEGF and Angiopoietin-2 levels, as well as Matrix Metalloproteases activity, were evaluated in supernatants from 3D cultures and their levels reflected the effects of Bortezomib treatment. Notably, determination of β2 microglobulin levels in supernatants from Bortezomib-treated samples and in patients'sera following Bortezomib-based therapies disclosed an overall concordance in the response to the drug ex vivo and in vivo. Our findings indicate, as a proof of principle, that 3-D, RCCS™ bioreactor-based culture of tissue explants can be exploited for studying myeloma biology and for a pre-clinical approach to patient-targeted therapy.

Ex-Vivo Dynamic 3-D Culture of Human Tissues in the RCCS™ Bioreactor Allows the Study of Multiple Myeloma Biology and Response to Therapy

PubMed Central

Ponzoni, Maurilio; Belloni, Daniela; Berenzi, Angiola; Girlanda, Stefania; Caligaris-Cappio, Federico; Mazzoleni, Giovanna; Ferrero, Elisabetta

2013-01-01

Three-dimensional (3-D) culture models are emerging as invaluable tools in tumor biology, since they reproduce tissue-specific structural features and cell-cell interactions more accurately than conventional 2-D cultures. Multiple Myeloma, which depends on myeloma cell-Bone Marrow microenvironment interactions for development and response to drugs, may particularly benefit from such an approach. An innovative 3-D dynamic culture model based on the use of the RCCS™ Bioreactor was developed to allow long-term culture of myeloma tissue explants. This model was first validated with normal and pathological explants, then applied to tissues from myeloma patients. In all cases, histological examination demonstrated maintenance of viable myeloma cells inside their native microenvironment, with an overall well preserved histo-architecture including bone lamellae and vessels. This system was then successfully applied to evaluate the cytotoxic effects exerted by the proteasome inhibitor Bortezomib not only on myeloma cells but also on angiogenic vessels. Moreover, as surrogate markers of specialized functions expressed by myeloma cells and microenvironment, β2 microglobulin, VEGF and Angiopoietin-2 levels, as well as Matrix Metalloproteases activity, were evaluated in supernatants from 3D cultures and their levels reflected the effects of Bortezomib treatment. Notably, determination of β2 microglobulin levels in supernatants from Bortezomib-treated samples and in patients'sera following Bortezomib-based therapies disclosed an overall concordance in the response to the drug ex vivo and in vivo. Our findings indicate, as a proof of principle, that 3-D, RCCS™ bioreactor-based culture of tissue explants can be exploited for studying myeloma biology and for a pre-clinical approach to patient-targeted therapy. PMID:23990965

A standard-enabled workflow for synthetic biology.

PubMed

Myers, Chris J; Beal, Jacob; Gorochowski, Thomas E; Kuwahara, Hiroyuki; Madsen, Curtis; McLaughlin, James Alastair; Mısırlı, Göksel; Nguyen, Tramy; Oberortner, Ernst; Samineni, Meher; Wipat, Anil; Zhang, Michael; Zundel, Zach

2017-06-15

A synthetic biology workflow is composed of data repositories that provide information about genetic parts, sequence-level design tools to compose these parts into circuits, visualization tools to depict these designs, genetic design tools to select parts to create systems, and modeling and simulation tools to evaluate alternative design choices. Data standards enable the ready exchange of information within such a workflow, allowing repositories and tools to be connected from a diversity of sources. The present paper describes one such workflow that utilizes, among others, the Synthetic Biology Open Language (SBOL) to describe genetic designs, the Systems Biology Markup Language to model these designs, and SBOL Visual to visualize these designs. We describe how a standard-enabled workflow can be used to produce types of design information, including multiple repositories and software tools exchanging information using a variety of data standards. Recently, the ACS Synthetic Biology journal has recommended the use of SBOL in their publications. © 2017 The Author(s); published by Portland Press Limited on behalf of the Biochemical Society.

Copper metallothioneins.

PubMed

Calvo, Jenifer; Jung, Hunmin; Meloni, Gabriele

2017-04-01

Metallothioneins (MTs) are a class of low molecular weight and cysteine-rich metal binding proteins present in all the branches of the tree of life. MTs efficiently bind with high affinity several essential and toxic divalent and monovalent transition metals by forming characteristic polynuclear metal-thiolate clusters within their structure. MTs fulfil multiple biological functions related to their metal binding properties, with essential roles in both Zn(II) and Cu(I) homeostasis as well as metal detoxification. Depending on the organism considered, the primary sequence, and the specific physiological and metabolic status, Cu(I)-bound MT isoforms have been isolated, and their chemistry and biology characterized. Besides the recognized role in the biochemistry of divalent metals, it is becoming evident that unique biological functions in selectively controlling copper levels, its reactivity as well as copper-mediated biochemical processes have evolved in some members of the MT superfamily. Selected examples are reviewed to highlight the peculiar chemical properties and biological functions of copper MTs. © 2016 IUBMB Life, 69(4):236-245, 2017. © 2017 International Union of Biochemistry and Molecular Biology.

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.

Microarray profiling analysis uncovers common molecular mechanisms of rubella virus, human cytomegalovirus, and herpes simplex virus type 2 infections in ECV304 cells.

PubMed

Mo, X; Xu, L; Yang, Q; Feng, H; Peng, J; Zhang, Y; Yuan, W; Wang, Y; Li, Y; Deng, Y; Wan, Y; Chen, Z; Li, F; Wu, X

2011-08-01

To study the common molecular mechanisms of various viruses infections that might result in congential cardiovascular diseases in perinatal period, changes in mRNA expression levels of ECV304 cells infected by rubella virus (RUBV), human cytomegalovirus (HCMV), and herpes simplex virus type 2 (HSV-2) were analyzed using a microarray system representing 18,716 human genes. 99 genes were found to exhibit differential expression (80 up-regulated and 19 down-regulated). Biological process analysis showed that 33 signaling pathways including 22 genes were relevant significantly to RV, HCMV and HSV-II infections. Of these 33 biological processes, 28 belong to one-gene biological processes and 5 belong to multiple-gene biological processes. Gene annotation indicated that the 5 multiple-gene biological processes including regulation of cell growth, collagen fibril organization, mRNA transport, cell adhesion and regulation of cell shape, and seven down- or up-regulated genes [CRIM1 (cysteine rich transmembrane BMP regulator 1), WISP2 (WNT1 inducible signaling pathway protein 2), COL12A1 (collagen, type XII, alpha 1), COL11A2 (collagen, type XI, alpha 2), CNTN5 (contactin 5), DDR1 (discoidin domain receptor tyrosine kinase 1), VEGF (vascular endothelial growth factor precursor)], are significantly correlated to RUBV, HCMV and HSV-2 infections in ECV304 cells. The results obtained in this study suggested the common molecular mechanisms of viruses infections that might result in congential cardiovascular diseases.

Thin film bioreactors in space

NASA Technical Reports Server (NTRS)

Hughes-Fulford, M.; Scheld, H. W.

1989-01-01

Studies from the Skylab, SL-3 and D-1 missions have demonstrated that biological organisms grown in microgravity have changes in basic cellular functions such as DNA, mRNA and protein synthesis, cytoskeleton synthesis, glucose utilization, and cellular differentiation. Since microgravity could affect prokaryotic and eukaryotic cells at a subcellular and molecular level, space offers an opportunity to learn more about basic biological systems with one inmportant variable removed. The thin film bioreactor will facilitate the handling of fluids in microgravity, under constant temperature and will allow multiple samples of cells to be grown with variable conditions. Studies on cell cultures grown in microgravity would make it possible to identify and quantify changes in basic biological function in microgravity which are needed to develop new applications of orbital research and future biotechnology.

Tetrahymena in the classroom.

PubMed

Smith, Joshua J; Wiley, Emily A; Cassidy-Hanley, Donna M

2012-01-01

Tetrahymena has been a useful model in basic research in part due to the fact it is easy to grow in culture and exhibits a range of complex processes, all within a single cell. For these same reasons Tetrahymena has shown enormous potential as a teaching tool for fundamental principles of biology at multiple science education levels that can be integrated into K-12 classrooms and undergraduate and graduate college laboratory courses. These Tetrahymena-based teaching modules are inquiry-based experiences that are also effective at teaching scientific concepts, retaining students in science, and exciting students about the scientific process. Two learning communities have been developed that utilize Tetrahymena-based teaching modules. Advancing Secondary Science Education with Tetrahymena (ASSET) and the Ciliate Genomics Consortium (CGC) have developed modules for K-12 students and college-level curriculums, respectively. These modules range from addressing topics in ecology, taxonomy, and environmental toxicity to more advanced concepts in biochemistry, proteomics, bioinformatics, cell biology, and molecular biology. An overview of the current modules and their learning outcomes are discussed, as are assessment, dissemination, and sustainability strategies for K-12 and college-level curriculum. Copyright © 2012 Elsevier Inc. All rights reserved.

GenoMetric Query Language: a novel approach to large-scale genomic data management.

PubMed

Masseroli, Marco; Pinoli, Pietro; Venco, Francesco; Kaitoua, Abdulrahman; Jalili, Vahid; Palluzzi, Fernando; Muller, Heiko; Ceri, Stefano

2015-06-15

Improvement of sequencing technologies and data processing pipelines is rapidly providing sequencing data, with associated high-level features, of many individual genomes in multiple biological and clinical conditions. They allow for data-driven genomic, transcriptomic and epigenomic characterizations, but require state-of-the-art 'big data' computing strategies, with abstraction levels beyond available tool capabilities. We propose a high-level, declarative GenoMetric Query Language (GMQL) and a toolkit for its use. GMQL operates downstream of raw data preprocessing pipelines and supports queries over thousands of heterogeneous datasets and samples; as such it is key to genomic 'big data' analysis. GMQL leverages a simple data model that provides both abstractions of genomic region data and associated experimental, biological and clinical metadata and interoperability between many data formats. Based on Hadoop framework and Apache Pig platform, GMQL ensures high scalability, expressivity, flexibility and simplicity of use, as demonstrated by several biological query examples on ENCODE and TCGA datasets. The GMQL toolkit is freely available for non-commercial use at http://www.bioinformatics.deib.polimi.it/GMQL/. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Joint Identification of Genetic Variants for Physical Activity in Korean Population

PubMed Central

Kim, Jayoun; Kim, Jaehee; Min, Haesook; Oh, Sohee; Kim, Yeonjung; Lee, Andy H.; Park, Taesung

2014-01-01

There has been limited research on genome-wide association with physical activity (PA). This study ascertained genetic associations between PA and 344,893 single nucleotide polymorphism (SNP) markers in 8842 Korean samples. PA data were obtained from a validated questionnaire that included information on PA intensity and duration. Metabolic equivalent of tasks were calculated to estimate the total daily PA level for each individual. In addition to single- and multiple-SNP association tests, a pathway enrichment analysis was performed to identify the biological significance of SNP markers. Although no significant SNP was found at genome-wide significance level via single-SNP association tests, 59 genetic variants mapped to 76 genes were identified via a multiple SNP approach using a bootstrap selection stability measure. Pathway analysis for these 59 variants showed that maturity onset diabetes of the young (MODY) was enriched. Joint identification of SNPs could enable the identification of multiple SNPs with good predictive power for PA and a pathway enriched for PA. PMID:25026172

Spatially extended hybrid methods: a review

PubMed Central

2018-01-01

Many biological and physical systems exhibit behaviour at multiple spatial, temporal or population scales. Multiscale processes provide challenges when they are to be simulated using numerical techniques. While coarser methods such as partial differential equations are typically fast to simulate, they lack the individual-level detail that may be required in regions of low concentration or small spatial scale. However, to simulate at such an individual level throughout a domain and in regions where concentrations are high can be computationally expensive. Spatially coupled hybrid methods provide a bridge, allowing for multiple representations of the same species in one spatial domain by partitioning space into distinct modelling subdomains. Over the past 20 years, such hybrid methods have risen to prominence, leading to what is now a very active research area across multiple disciplines including chemistry, physics and mathematics. There are three main motivations for undertaking this review. Firstly, we have collated a large number of spatially extended hybrid methods and presented them in a single coherent document, while comparing and contrasting them, so that anyone who requires a multiscale hybrid method will be able to find the most appropriate one for their need. Secondly, we have provided canonical examples with algorithms and accompanying code, serving to demonstrate how these types of methods work in practice. Finally, we have presented papers that employ these methods on real biological and physical problems, demonstrating their utility. We also consider some open research questions in the area of hybrid method development and the future directions for the field. PMID:29491179

Harnessing the apoptotic programs in cancer stem-like cells

PubMed Central

Wang, Ying-Hua; Scadden, David T

2015-01-01

Elimination of malignant cells is an unmet challenge for most human cancer types even with therapies targeting specific driver mutations. Therefore, a multi-pronged strategy to alter cancer cell biology on multiple levels is increasingly recognized as essential for cancer cure. One such aspect of cancer cell biology is the relative apoptosis resistance of tumor-initiating cells. Here, we provide an overview of the mechanisms affecting the apoptotic process in tumor cells emphasizing the differences in the tumor-initiating or stem-like cells of cancer. Further, we summarize efforts to exploit these differences to design therapies targeting that important cancer cell population. PMID:26253117

Out-of-School Experience Categories Influencing Interest in Science of Upper Primary Students by Gender and Locale: Exploration on an Indian Sample

ERIC Educational Resources Information Center

Gafoor, K. Abdul; Narayan, Smitha

2012-01-01

In view of student shift away from science at advanced levels, and gender and locale based divergence in interest in studying physics, chemistry and biology, this study explores experience categories that significantly contribute to interest in science on a sample of upper primary school students from Kerala, India. A series of multiple regression…

Predicting Trophic Interactions and Habitat Utilization in the California Current Ecosystem

DTIC Science & Technology

2015-09-30

spatial and temporal distribution of key marine organisms over multiple trophic levels, and (2) natural and anthropogenic variability in ecosystem...areas of climate modeling in upwelling regions (E. Curchitser), physical-biological modeling in the CCLME (J. Fiechter and C. Edwards), data...optimal growth conditions). By comparing interannual changes in fat depot against EOF modes for environmental variability (i.e., SST) and prey

Stairway to heaven: evaluating levels of biological organization correlated with the successful ascent of natural waterfalls in the Hawaiian stream goby Sicyopterus stimpsoni.

PubMed

Schoenfuss, Heiko L; Maie, Takashi; Moody, Kristine N; Lesteberg, Kelsey E; Blob, Richard W; Schoenfuss, Tonya C

2013-01-01

Selective pressures generated by locomotor challenges act at the level of the individual. However, phenotypic variation among individuals that might convey a selective advantage may occur across any of multiple levels of biological organization. In this study, we test for differences in external morphology, muscle mechanical advantage, muscle fiber type and protein expression among individuals of the waterfall climbing Hawaiian fish Sicyopterus stimpsoni collected from sequential pools increasing in elevation within a single freshwater stream. Despite predictions from previous laboratory studies of morphological selection, few directional morphometric changes in body shape were observed at successively higher elevations. Similarly, lever arm ratios associated with the main pelvic sucker, central to climbing ability in this species, did not differ between elevations. However, among climbing muscles, the adductor pelvicus complex (largely responsible for generating pelvic suction during climbing) contained a significantly greater red muscle fiber content at upstream sites. A proteomic analysis of the adductor pelvicus revealed two-fold increases in expression levels for two respiratory chain proteins (NADH:ubiquinone reductase and cytochrome b) that are essential for aerobic respiration among individuals from successively higher elevations. Assessed collectively, these evaluations reveal phenotypic differences at some, but not all levels of biological organization that are likely the result of selective pressures experienced during climbing.

Stairway to Heaven: Evaluating Levels of Biological Organization Correlated with the Successful Ascent of Natural Waterfalls in the Hawaiian Stream Goby Sicyopterus stimpsoni

PubMed Central

Schoenfuss, Heiko L.; Maie, Takashi; Moody, Kristine N.; Lesteberg, Kelsey E.; Blob, Richard W.; Schoenfuss, Tonya C.

2013-01-01

Selective pressures generated by locomotor challenges act at the level of the individual. However, phenotypic variation among individuals that might convey a selective advantage may occur across any of multiple levels of biological organization. In this study, we test for differences in external morphology, muscle mechanical advantage, muscle fiber type and protein expression among individuals of the waterfall climbing Hawaiian fish Sicyopterus stimpsoni collected from sequential pools increasing in elevation within a single freshwater stream. Despite predictions from previous laboratory studies of morphological selection, few directional morphometric changes in body shape were observed at successively higher elevations. Similarly, lever arm ratios associated with the main pelvic sucker, central to climbing ability in this species, did not differ between elevations. However, among climbing muscles, the adductor pelvicus complex (largely responsible for generating pelvic suction during climbing) contained a significantly greater red muscle fiber content at upstream sites. A proteomic analysis of the adductor pelvicus revealed two-fold increases in expression levels for two respiratory chain proteins (NADH:ubiquinone reductase and cytochrome b) that are essential for aerobic respiration among individuals from successively higher elevations. Assessed collectively, these evaluations reveal phenotypic differences at some, but not all levels of biological organization that are likely the result of selective pressures experienced during climbing. PMID:24386424

Changes in hormone and stress-inducing activities of municipal wastewater in a conventional activated sludge wastewater treatment plant.

PubMed

Wojnarowicz, Pola; Yang, Wenbo; Zhou, Hongde; Parker, Wayne J; Helbing, Caren C

2014-12-01

Conventional municipal wastewater treatment plants do not efficiently remove contaminants of emerging concern, and so are primary sources for contaminant release into the aquatic environment. Although these contaminants are present in effluents at ng-μg/L concentrations (i.e. microcontaminants), many compounds can act as endocrine disrupting compounds or stress-inducing agents at these levels. Chemical fate analyses indicate that additional levels of wastewater treatment reduce but do not always completely remove all microcontaminants. The removal of microcontaminants from wastewater does not necessarily correspond to a reduction in biological activity, as contaminant metabolites or byproducts may still be biologically active. To evaluate the efficacy of conventional municipal wastewater treatment plants to remove biological activity, we examined the performance of a full scale conventional activated sludge municipal wastewater treatment plant located in Guelph, Ontario, Canada. We assessed reductions in levels of conventional wastewater parameters and thyroid hormone disrupting and stress-inducing activities in wastewater at three phases along the treatment train using a C-fin assay. Wastewater treatment was effective at reducing total suspended solids, chemical and biochemical oxygen demand, and stress-inducing bioactivity. However, only minimal reduction was observed in thyroid hormone disrupting activities. The present study underscores the importance of examining multiple chemical and biological endpoints in evaluating and monitoring the effectiveness of wastewater treatment for removal of microcontaminants. Copyright © 2014 Elsevier Ltd. All rights reserved.

FALDO: a semantic standard for describing the location of nucleotide and protein feature annotation.

PubMed

Bolleman, Jerven T; Mungall, Christopher J; Strozzi, Francesco; Baran, Joachim; Dumontier, Michel; Bonnal, Raoul J P; Buels, Robert; Hoehndorf, Robert; Fujisawa, Takatomo; Katayama, Toshiaki; Cock, Peter J A

2016-06-13

Nucleotide and protein sequence feature annotations are essential to understand biology on the genomic, transcriptomic, and proteomic level. Using Semantic Web technologies to query biological annotations, there was no standard that described this potentially complex location information as subject-predicate-object triples. We have developed an ontology, the Feature Annotation Location Description Ontology (FALDO), to describe the positions of annotated features on linear and circular sequences. FALDO can be used to describe nucleotide features in sequence records, protein annotations, and glycan binding sites, among other features in coordinate systems of the aforementioned "omics" areas. Using the same data format to represent sequence positions that are independent of file formats allows us to integrate sequence data from multiple sources and data types. The genome browser JBrowse is used to demonstrate accessing multiple SPARQL endpoints to display genomic feature annotations, as well as protein annotations from UniProt mapped to genomic locations. Our ontology allows users to uniformly describe - and potentially merge - sequence annotations from multiple sources. Data sources using FALDO can prospectively be retrieved using federalised SPARQL queries against public SPARQL endpoints and/or local private triple stores.

FALDO: a semantic standard for describing the location of nucleotide and protein feature annotation

DOE PAGES

Bolleman, Jerven T.; Mungall, Christopher J.; Strozzi, Francesco; ...

2016-06-13

Nucleotide and protein sequence feature annotations are essential to understand biology on the genomic, transcriptomic, and proteomic level. Using Semantic Web technologies to query biological annotations, there was no standard that described this potentially complex location information as subject-predicate-object triples. In this paper, we have developed an ontology, the Feature Annotation Location Description Ontology (FALDO), to describe the positions of annotated features on linear and circular sequences. FALDO can be used to describe nucleotide features in sequence records, protein annotations, and glycan binding sites, among other features in coordinate systems of the aforementioned “omics” areas. Using the same data formatmore » to represent sequence positions that are independent of file formats allows us to integrate sequence data from multiple sources and data types. The genome browser JBrowse is used to demonstrate accessing multiple SPARQL endpoints to display genomic feature annotations, as well as protein annotations from UniProt mapped to genomic locations. Our ontology allows users to uniformly describe – and potentially merge – sequence annotations from multiple sources. Finally, data sources using FALDO can prospectively be retrieved using federalised SPARQL queries against public SPARQL endpoints and/or local private triple stores.« less

FALDO: a semantic standard for describing the location of nucleotide and protein feature annotation

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

Bolleman, Jerven T.; Mungall, Christopher J.; Strozzi, Francesco

Nucleotide and protein sequence feature annotations are essential to understand biology on the genomic, transcriptomic, and proteomic level. Using Semantic Web technologies to query biological annotations, there was no standard that described this potentially complex location information as subject-predicate-object triples. In this paper, we have developed an ontology, the Feature Annotation Location Description Ontology (FALDO), to describe the positions of annotated features on linear and circular sequences. FALDO can be used to describe nucleotide features in sequence records, protein annotations, and glycan binding sites, among other features in coordinate systems of the aforementioned “omics” areas. Using the same data formatmore » to represent sequence positions that are independent of file formats allows us to integrate sequence data from multiple sources and data types. The genome browser JBrowse is used to demonstrate accessing multiple SPARQL endpoints to display genomic feature annotations, as well as protein annotations from UniProt mapped to genomic locations. Our ontology allows users to uniformly describe – and potentially merge – sequence annotations from multiple sources. Finally, data sources using FALDO can prospectively be retrieved using federalised SPARQL queries against public SPARQL endpoints and/or local private triple stores.« less

Step by Step: Biology Undergraduates' Problem-Solving Procedures during Multiple-Choice Assessment

ERIC Educational Resources Information Center

Prevost, Luanna B.; Lemons, Paula P.

2016-01-01

This study uses the theoretical framework of domain-specific problem solving to explore the procedures students use to solve multiple-choice problems about biology concepts. We designed several multiple-choice problems and administered them on four exams. We trained students to produce written descriptions of how they solved the problem, and this…

Corticosterone regulates multiple colour traits in Lacerta [Zootoca] vivipara males.

PubMed

San-Jose, L M; Fitze, P S

2013-12-01

Ornamental colours usually evolve as honest signals of quality, which is supported by the fact that they frequently depend on individual condition. It has generally been suggested that some, but not all types of ornamental colours are condition dependent, indicating that different evolutionary mechanisms underlie the evolution of multiple types of ornamental colours even when these are exhibited by the same species. Stress hormones, which negatively affect condition, have been shown to affect colour traits based on different pigments and structures, suggesting that they mediate condition dependence of multiple ornament types both among and within individuals. However, studies investigating effects of stress hormones on different ornament types within individuals are lacking, and thus, evidence for this hypothesis is scant. Here, we investigated whether corticosterone mediates condition dependence of multiple ornaments by manipulating corticosterone levels and body condition (via food availability) using a two-factorial design and by assessing their effect on multiple colour traits in male common lizards. Corticosterone negatively affected ventral melanin- and carotenoid-based coloration, whereas food availability did not affect coloration, despite its significant effect on body condition. The corticosterone effect on melanin- and carotenoid-based coloration demonstrates the condition dependence of both ornaments. Moreover, corticosterone affected ventral coloration and had no effect on the nonsexually selected dorsal coloration, showing specific effects of corticosterone on ornamental ventral colours. This suggests that corticosterone simultaneously mediates condition dependence of multiple colour traits and that it therefore accounts for covariation among them, which may influence their evolution via correlational selection. © 2013 The Authors. Journal of Evolutionary Biology © 2013 European Society For Evolutionary Biology.

Joint Project Manager (JPM) Chemical Biological Individual and Collective Protection Industry Day

DTIC Science & Technology

2008-07-22

ANSWER: The SBA operates the Office of Women’s B i O hi Th OWBO t thus ness wners p. e promo es e growth of women owned businesses through programs...TIC prioritization focused on a h i i k t f h tcompre ens ve r s managemen o w a we do not know: Absolute global production levels Absolute global...Modeling (For operational analyses) 2. Breakthrough Levels 3 D t ti A h. e ec on pproac es Multiple species may be present 4. Chemical Class Analysis

Method and apparatus for determining nutrient stimulation of biological processes

DOEpatents

Colwell, F.S.; Geesey, G.G.; Gillis, R.J.; Lehman, R.M.

1997-11-11

A method and apparatus is described for determining the nutrients to stimulate microorganisms in a particular environment. A representative sample of microorganisms from a particular environment are contacted with multiple support means wherein each support means has intimately associated with the surface of the support means a different nutrient composition for said microorganisms in said sample. The multiple support means is allowed to remain in contact with the microorganisms in the sample for a time period sufficient to measure differences in microorganism effects for the multiple support means. Microorganism effects for the multiple support means are then measured and compared. The invention is particularly adaptable to being conducted in situ. The additional steps of regulating nutrients added to the particular environment of microorganisms can enhance the desired results. Biological systems particularly suitable for this invention are bioremediation, biologically enhanced oil recovery, biological leaching of metals, and agricultural bioprocesses. 5 figs.

Method and apparatus for determining nutrient stimulation of biological processes

DOEpatents

Colwell, Frederick S.; Geesey, Gill G.; Gillis, Richard J.; Lehman, R. Michael

1999-01-01

A method and apparatus for determining the nutrients to stimulate microorganisms in a particular environment. A representative sample of microorganisms from a particular environment are contacted with multiple support means wherein each support means has intimately associated with the surface of the support means a different nutrient composition for said microorganisms in said sample. The multiple support means is allowed to remain in contact with the microorganisms in the sample for a time period sufficient to measure difference in microorganism effects for the multiple support means. Microorganism effects for the multiple support means are then measured and compared. The invention is particularly adaptable to being conducted in situ. The additional steps of regulating nutrients added to the particular environment of microorganisms can enhance the desired results. Biological systems particularly suitable for this invention are bioremediation, biologically enhanced oil recovery, biological leaching of metals, and agricultural bioprocesses.

Method and apparatus for determining nutrient stimulation of biological processes

DOEpatents

Colwell, F.S.; Geesey, G.G.; Gillis, R.J.; Lehman, R.M.

1999-07-13

A method and apparatus are disclosed for determining the nutrients to stimulate microorganisms in a particular environment. A representative sample of microorganisms from a particular environment are contacted with multiple support means wherein each support means has intimately associated with the surface of the support means a different nutrient composition for microorganisms in the sample. The multiple support means is allowed to remain in contact with the microorganisms in the sample for a time period sufficient to measure difference in microorganism effects for the multiple support means. Microorganism effects for the multiple support means are then measured and compared. The invention is particularly adaptable to being conducted in situ. The additional steps of regulating nutrients added to the particular environment of microorganisms can enhance the desired results. Biological systems particularly suitable for this invention are bioremediation, biologically enhanced oil recovery, biological leaching of metals, and agricultural bioprocesses. 5 figs.

Method and apparatus for determining nutrient stimulation of biological processes

DOEpatents

Colwell, Frederick S.; Geesey, Gill G.; Gillis, Richard J.; Lehman, R. Michael

1997-01-01

A method and apparatus for determining the nutrients to stimulate microorganisms in a particular environment. A representative sample of microorganisms from a particular environment are contacted with multiple support means wherein each support means has intimately associated with the surface of the support means a different nutrient composition for said microorganisms in said sample. The multiple support means is allowed to remain in contact with the microorganisms in the sample for a time period sufficient to measure differences in microorganism effects for the multiple support means. Microorganism effects for the multiple support means are then measured and compared. The invention is particularly adaptable to being conducted in situ. The additional steps of regulating nutrients added to the particular environment of microorganisms can enhance the desired results. Biological systems particularly suitable for this invention are bioremediation, biologically enhanced oil recovery, biological leaching of metals, and agricultural bioprocesses.

Predicting in vivo effect levels for repeat-dose systemic toxicity using chemical, biological, kinetic and study covariates.

PubMed

Truong, Lisa; Ouedraogo, Gladys; Pham, LyLy; Clouzeau, Jacques; Loisel-Joubert, Sophie; Blanchet, Delphine; Noçairi, Hicham; Setzer, Woodrow; Judson, Richard; Grulke, Chris; Mansouri, Kamel; Martin, Matthew

2018-02-01

In an effort to address a major challenge in chemical safety assessment, alternative approaches for characterizing systemic effect levels, a predictive model was developed. Systemic effect levels were curated from ToxRefDB, HESS-DB and COSMOS-DB from numerous study types totaling 4379 in vivo studies for 1247 chemicals. Observed systemic effects in mammalian models are a complex function of chemical dynamics, kinetics, and inter- and intra-individual variability. To address this complex problem, systemic effect levels were modeled at the study-level by leveraging study covariates (e.g., study type, strain, administration route) in addition to multiple descriptor sets, including chemical (ToxPrint, PaDEL, and Physchem), biological (ToxCast), and kinetic descriptors. Using random forest modeling with cross-validation and external validation procedures, study-level covariates alone accounted for approximately 15% of the variance reducing the root mean squared error (RMSE) from 0.96 log 10 to 0.85 log 10  mg/kg/day, providing a baseline performance metric (lower expectation of model performance). A consensus model developed using a combination of study-level covariates, chemical, biological, and kinetic descriptors explained a total of 43% of the variance with an RMSE of 0.69 log 10  mg/kg/day. A benchmark model (upper expectation of model performance) was also developed with an RMSE of 0.5 log 10  mg/kg/day by incorporating study-level covariates and the mean effect level per chemical. To achieve a representative chemical-level prediction, the minimum study-level predicted and observed effect level per chemical were compared reducing the RMSE from 1.0 to 0.73 log 10  mg/kg/day, equivalent to 87% of predictions falling within an order-of-magnitude of the observed value. Although biological descriptors did not improve model performance, the final model was enriched for biological descriptors that indicated xenobiotic metabolism gene expression, oxidative stress, and cytotoxicity, demonstrating the importance of accounting for kinetics and non-specific bioactivity in predicting systemic effect levels. Herein, we generated an externally predictive model of systemic effect levels for use as a safety assessment tool and have generated forward predictions for over 30,000 chemicals.

Toward Scalable Fabrication of Hierarchical Silica Capsules with Integrated Micro-, Meso-, and Macropores.

PubMed

Zhou, Weizheng; Tong, Gangsheng; Wang, Dali; Zhu, Bangshang; Ren, Yu; Butler, Michael; Pelan, Eddie; Yan, Deyue; Zhu, Xinyuan; Stoyanov, Simeon D

2016-04-06

Hierarchical porous structures are ubiquitous in biological organisms and inorganic systems. Although such structures have been replicated, designed, and fabricated, they are often inferior to naturally occurring analogues. Apart from the complexity and multiple functionalities developed by the biological systems, the controllable and scalable production of hierarchically porous structures and building blocks remains a technological challenge. Herein, a facile and scalable approach is developed to fabricate hierarchical hollow spheres with integrated micro-, meso-, and macropores ranging from 1 nm to 100 μm (spanning five orders of magnitude). (Macro)molecules, micro-rods (which play a key role for the creation of robust capsules), and emulsion droplets have been successfully employed as multiple length scale templates, allowing the creation of hierarchical porous macrospheres. Thanks to their specific mechanical strength, these hierarchical porous spheres could be incorporated and assembled as higher level building blocks in various novel materials. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Biologically-controlled multiple equilibria of tidal landforms and the fate of the Venice lagoon

NASA Astrophysics Data System (ADS)

Marani, Marco; D'Alpaos, Andrea; Lanzoni, Stefano; Carniello, Luca; Rinaldo, Andrea

2007-06-01

Looking across a tidal landscape, can one foresee the signs of impending shifts among different geomorphological structures? This is a question of paramount importance considering the ecological, cultural and socio-economic relevance of tidal environments and their worldwide decline. In this Letter we argue affirmatively by introducing a model of the coupled tidal physical and biological processes. Multiple equilibria, and transitions among them, appear in the evolutionary dynamics of tidal landforms. Vegetation type, disturbances of the benthic biofilm, sediment availability and marine transgressions or regressions drive the bio-geomorphic evolution of the system. Our approach provides general quantitative routes to model the fate of tidal landforms, which we illustrate in the case of the Venice lagoon (Italy), for which a large body of empirical observations exists spanning at least five centuries. Such observations are reproduced by the model, which also predicts that salt marshes in the Venice lagoon may not survive climatic changes in the next century if IPCC's scenarios of high relative sea level rise occur.

The landscape context of cereal aphid–parasitoid interactions

PubMed Central

Thies, Carsten; Roschewitz, Indra; Tscharntke, Teja

2005-01-01

Analyses at multiple spatial scales may show how important ecosystem services such as biological control are determined by processes acting on the landscape scale. We examined cereal aphid–parasitoid interactions in wheat fields in agricultural landscapes differing in structural complexity (32–100% arable land). Complex landscapes were associated with increased aphid mortality resulting from parasitism, but also with higher aphid colonization, thereby counterbalancing possible biological control by parasitoids and lastly resulting in similar aphid densities across landscapes. Thus, undisturbed perennial habitats appeared to enhance both pests and natural enemies. Analyses at multiple spatial scales (landscape sectors of 0.5–6 km diameter) showed that correlations between parasitism and percentage of arable land were significant at scales of 0.5–2 km, whereas aphid densities responded to percentage of arable land at scales of 1–6 km diameter. Hence, the higher trophic level populations appeared to be determined by smaller landscape sectors owing to dispersal limitation, showing the ‘functional spatial scale’ for species-specific landscape management. PMID:15695212

AID-dependent activation of a MYC transgene induces multiple myeloma in a conditional mouse model of post-germinal center malignancies

PubMed Central

Chesi, Marta; Robbiani, Davide F.; Sebag, Michael; Chng, Wee Joo; Affer, Maurizio; Tiedemann, Rodger; Valdez, Riccardo; Palmer, Stephen E.; Haas, Stephanie S.; Stewart, A. Keith; Fonseca, Rafael; Kremer, Richard; Cattoretti, Giorgio; Bergsagel, P. Leif

2008-01-01

Summary By misdirecting the activity of Activation-Induced Deaminase (AID) to a conditional MYC transgene, we have achieved sporadic, AID-dependent MYC activation in germinal center B-cells of Vk*MYC mice. Whereas control C57BL/6 mice develop benign monoclonal gammopathy with age, all Vk*MYC mice progress to an indolent multiple myeloma associated with the biological and clinical features highly characteristic of the human disease. Furthermore, antigen-dependent myeloma could be induced by immunization with a T-dependent antigen. Consistent with these findings in mice, more frequent MYC rearrangements, elevated levels of MYC mRNA and MYC target genes distinguish human patients with multiple myeloma from individuals with monoclonal gammopathy, implicating a causal role for MYC in the progression of monoclonal gammopathy to multiple myeloma in man. PMID:18242516

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.

Particulate pollution -- a biological dilemma

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

Marrack, D.

Human epidemiological data from multiple studies on USA. and European populations have been reviewed extensively. The consensus supports a weak association between PM-10 particulate matter and cardio-pulmonary morbidity and mortality. It is consistent with factors in the particles comprising PM-10 causing the biological effects. PM-10 is treated as a precisely defined entity, which it is not! Ambient PM-10 particles have multiple sources, sizes 10m m, chemistry and surface area. The medical and biological effects are seen with the inhalation of a multi-media matrix of pollutants, often at elevated levels, a medical and biological problem. This paper addresses this biology, predominantlymore » determined by size and sources of PM reflecting particle chemistry and surface area, describing one mechanism by which inhaled fine particles provoke heart muscle dysfunction. Combustion-PM-2.5m m (C-PM-2.5) reach the alveoli with 70% + retention and are engulfed by pulmonary alveolar macrophages. These particles trigger chain reactions that lead to cardio-pulmonary morbidity. Their structure includes high absorptive capacity carbon, transition metal plaques, and silica components. PAH`s (Polyaromatic hydrocarbons) and other potentially toxic chemicals are extensively absorbed on them and are piggy-backed into macrophages without dilution by blood. PM-2.5`s trace amounts of soluble transition metal salts are important in the molecular and biological events leading to heart damage. Animal inhalation studies of C-PM-2.5 cause little cellular reaction in normal lungs. In lungs already irritated by other agents, C-PM-2.5 inhalation greatly aggravates the inflammatory response. The soluble transition-metals (Fe Salts) are the effector. The data are impressive and provides a robust scientific basis for more stringent regulations of ambient C-PM-2.5.« less

High levels of 15-oxygenated steroids in circulation of patients with multiple sclerosis: fact or fiction?

PubMed

Björkhem, I; Lövgren-Sandblom, A; Piehl, F; Khademi, M; Pettersson, H; Leoni, V; Olsson, T; Diczfalusy, U

2011-01-01

15-Oxygenated cholesterol species such as 5α-cholest-8(14)ene-3β,15α-diol (15HC) and 3β-hydroxy-5α-cholest-8(14)-en-15-one (15KC) are commercially available synthetic products unlikely to occur in biological systems. Surprisingly, Farez et al. recently reported that these two steroids occur in human circulation at levels considerably higher than those of any other endogenous oxysterol [Farez, M. et al. 2009. Toll-like receptor 2 and poly(ADP-ribose) polymerase 1 promote central nervous system neuroinflammation in progressive EAE. Nat. Immunol. 10: 958-964]. The levels were reported to be increased in patients with multiple sclerosis in a progressive phase and the authors suggested that this could be utilized diagnostically. Based on extensive in vitro experiments exposing cells to the same high levels of 15HC as found in vivo (1000 ng/ml) the authors concluded that 15HC may be an important pathogenetic factor in multiple sclerosis. Using combined gas chromatography-mass spectrometry we fail to detect significant plasma levels of 15HC either in healthy controls or in patients with multiple sclerosis (levels < 2 ng/ml). If 15KC is present in these plasma samples, the concentration of it must be <10 ng/ml. Our failure to detect significant levels of the above steroids could not be due to loss during hydrolysis and work-up because recovery of the added two oxysterols was close to 100%. Autoxidation of lipoprotein-bound cholesterol resulted in extensive conversion of cholesterol into 7-oxygenated but not 15-oxygenated sterols. We conclude that if present there are trace amounts only of the above 15-oxygenated steroids in human circulation and that the role of such oxysterols as pathogenetic factors and biomarkers must be reconsidered.

Autofluorescence of atmospheric bioaerosols - fluorescent biomolecules and potential interferences

NASA Astrophysics Data System (ADS)

Pöhlker, C.; Huffman, J. A.; Pöschl, U.

2012-01-01

Primary biological aerosol particles (PBAP) are an important subset of air particulate matter with a substantial contribution to the organic aerosol fraction and potentially strong effects on public health and climate. Recent progress has been made in PBAP quantification by utilizing real-time bioaerosol detectors based on the principle that specific organic molecules of biological origin such as proteins, coenzymes, cell wall compounds and pigments exhibit intrinsic fluorescence. The properties of many fluorophores have been well documented, but it is unclear which are most relevant for detection of atmospheric PBAP. The present study provides a systematic synthesis of literature data on potentially relevant biological fluorophores. We analyze and discuss their relative importance for the detection of fluorescent biological aerosol particles (FBAP) by online instrumentation for atmospheric measurements such as the ultraviolet aerodynamic particle sizer (UV-APS) or the wide issue bioaerosol sensor (WIBS). In addition, we provide new laboratory measurement data for selected compounds using bench-top fluorescence spectroscopy. Relevant biological materials were chosen for comparison with existing literature data and to fill in gaps of understanding. The excitation-emission matrices (EEM) exhibit pronounced peaks at excitation wavelengths of ~280 nm and ~360 nm, confirming the suitability of light sources used for online detection of FBAP. They also show, however, that valuable information is missed by instruments that do not record full emission spectra at multiple wavelengths of excitation, and co-occurrence of multiple fluorophores within a detected sample will likely confound detailed molecular analysis. Selected non-biological materials were also analyzed to assess their possible influence on FBAP detection and generally exhibit only low levels of background-corrected fluorescent emission. This study strengthens the hypothesis that ambient supermicron particle fluorescence in wavelength ranges used for most FBAP instruments is likely to be dominated by biological material and that such instrumentation is able to discriminate between FBAP and non-biological material in many situations. More detailed follow-up studies on single particle fluorescence are still required to reduce these uncertainties further, however.

Autofluorescence of atmospheric bioaerosols - fluorescent biomolecules and potential interferences

NASA Astrophysics Data System (ADS)

Pöhlker, C.; Huffman, J. A.; Pöschl, U.

2011-09-01

Primary biological aerosol particles (PBAP) are an important subset of air particulate matter with a substantial contribution to the organic aerosol fraction and potentially strong effects on public health and climate. Recent progress has been made in PBAP quantification by utilizing real-time bioaerosol detectors based on the principle that specific organic molecules of biological origin such as proteins, coenzymes, cell wall compounds and pigments exhibit intrinsic fluorescence. The properties of many fluorophores have been well documented, but it is unclear which are most relevant for detection of atmospheric PBAP. The present study provides a systematic synthesis of literature data on potentially relevant biological fluorophores. We analyze and discuss their relative importance for the detection of fluorescent biological aerosol particles (FBAP) by online instrumentation for atmospheric measurements such as the ultraviolet aerodynamic particle sizer (UV-APS) or the wide issue bioaerosol sensor (WIBS). In addition, we provide new laboratory measurement data for selected compounds using bench-top fluorescence spectroscopy. Relevant biological materials were chosen for comparison with existing literature data and to fill in gaps of understanding. The excitation-emission matrices (EEM) exhibit pronounced peaks at excitation wavelengths of ~280 nm and ~360 nm, confirming the suitability of light sources used for online detection of FBAP. They also show, however, that valuable information is missed by instruments that do not record full emission spectra at multiple wavelengths of excitation, and co-occurrence of multiple fluorophores within a detected sample will likely confound detailed molecular analysis. Selected non-biological materials were also analyzed to assess their possible influence on FBAP detection and generally exhibit only low levels of background-corrected fluorescent emission. This study strengthens the hypothesis that ambient supermicron particle fluorescence in wavelength ranges used for most FBAP instruments is likely to be dominated by biological material and that such instrumentation is able to discriminate between FBAP and non-biological material in many situations. More detailed follow-up studies on single particle fluorescence are still required to reduce these uncertainties further, however.

The implications of non-linear biological oscillations on human electrophysiology for electrohypersensitivity (EHS) and multiple chemical sensitivity (MCS).

PubMed

Sage, Cindy

2015-01-01

The 'informational content' of Earth's electromagnetic signaling is like a set of operating instructions for human life. These environmental cues are dynamic and involve exquisitely low inputs (intensities) of critical frequencies with which all life on Earth evolved. Circadian and other temporal biological rhythms depend on these fluctuating electromagnetic inputs to direct gene expression, cell communication and metabolism, neural development, brainwave activity, neural synchrony, a diversity of immune functions, sleep and wake cycles, behavior and cognition. Oscillation is also a universal phenomenon, and biological systems of the heart, brain and gut are dependent on the cooperative actions of cells that function according to principles of non-linear, coupled biological oscillations for their synchrony. They are dependent on exquisitely timed cues from the environment at vanishingly small levels. Altered 'informational content' of environmental cues can swamp natural electromagnetic cues and result in dysregulation of normal biological rhythms that direct growth, development, metabolism and repair mechanisms. Pulsed electromagnetic fields (PEMF) and radiofrequency radiation (RFR) can have the devastating biological effects of disrupting homeostasis and desynchronizing normal biological rhythms that maintain health. Non-linear, weak field biological oscillations govern body electrophysiology, organize cell and tissue functions and maintain organ systems. Artificial bioelectrical interference can give false information (disruptive signaling) sufficient to affect critical pacemaker cells (of the heart, gut and brain) and desynchronize functions of these important cells that orchestrate function and maintain health. Chronic physiological stress undermines homeostasis whether it is chemically induced or electromagnetically induced (or both exposures are simultaneous contributors). This can eventually break down adaptive biological responses critical to health maintenance; and resilience can be compromised. Electrohypersensitivity can be caused by successive assaults on human bioelectrochemical dynamics from exogenous electromagnetic fields (EMF) and RFR or a single acute exposure. Once sensitized, further exposures are widely reported to cause reactivity to lower and lower intensities of EMF/RFR, at which point thousand-fold lower levels can cause adverse health impacts to the electrosensitive person. Electrohypersensitivity (EHS) can be a precursor to, or linked with, multiple chemical sensitivity (MCS) based on reports of individuals who first develop one condition, then rapidly develop the other. Similarity of chemical biomarkers is seen in both conditions [histamines, markers of oxidative stress, auto-antibodies, heat shock protein (HSP), melatonin markers and leakage of the blood-brain barrier]. Low intensity pulsed microwave activation of voltage-gated calcium channels (VGCCs) is postulated as a mechanism of action for non-thermal health effects.

Examining the Effect of Multiple Writing Tasks on Year 10 Biology Students' Understandings of Cell and Molecular Biology Concepts

ERIC Educational Resources Information Center

Hand, Brian; Hohenshell, Liesl; Prain, Vaughan

2007-01-01

This paper reports on a study that examined the cumulative effects on students' learning of science, and perceptions of the role of writing in learning, when the students engaged in multiple writing tasks with planning strategy support. The study was conducted with Year 10 biology students who completed two consecutive units on Cells and Molecular…

The Multiple Futures of Racism--Beyond Color and Culture, toward a New Paradigm for Resolution in the Third Millennium.

ERIC Educational Resources Information Center

Rosado, Caleb

The paper asserts that racism is still one of the most pervasive social evils in the world. Part of the problem is that attempts to eliminate racism have focused on surface differences of race, color, and biological supremacy. Such attempts do not get to the root of the problem, the deep-level value and belief systems that undergird racism. This…

Network Analysis of Epidermal Growth Factor Signaling Using Integrated Genomic, Proteomic and Phosphorylation Data

PubMed Central

Waters, Katrina M.; Liu, Tao; Quesenberry, Ryan D.; Willse, Alan R.; Bandyopadhyay, Somnath; Kathmann, Loel E.; Weber, Thomas J.; Smith, Richard D.; Wiley, H. Steven; Thrall, Brian D.

2012-01-01

To understand how integration of multiple data types can help decipher cellular responses at the systems level, we analyzed the mitogenic response of human mammary epithelial cells to epidermal growth factor (EGF) using whole genome microarrays, mass spectrometry-based proteomics and large-scale western blots with over 1000 antibodies. A time course analysis revealed significant differences in the expression of 3172 genes and 596 proteins, including protein phosphorylation changes measured by western blot. Integration of these disparate data types showed that each contributed qualitatively different components to the observed cell response to EGF and that varying degrees of concordance in gene expression and protein abundance measurements could be linked to specific biological processes. Networks inferred from individual data types were relatively limited, whereas networks derived from the integrated data recapitulated the known major cellular responses to EGF and exhibited more highly connected signaling nodes than networks derived from any individual dataset. While cell cycle regulatory pathways were altered as anticipated, we found the most robust response to mitogenic concentrations of EGF was induction of matrix metalloprotease cascades, highlighting the importance of the EGFR system as a regulator of the extracellular environment. These results demonstrate the value of integrating multiple levels of biological information to more accurately reconstruct networks of cellular response. PMID:22479638

Dissecting DNA repair in adult high grade gliomas for patient stratification in the post-genomic era

PubMed Central

Perry, Christina; Agarwal, Devika; Abdel-Fatah, Tarek M.A.; Lourdusamy, Anbarasu; Grundy, Richard; Auer, Dorothee T.; Walker, David; Lakhani, Ravi; Scott, Ian S.; Chan, Stephen; Ball, Graham; Madhusudan, Srinivasan

2014-01-01

Deregulation of multiple DNA repair pathways may contribute to aggressive biology and therapy resistance in gliomas. We evaluated transcript levels of 157 genes involved in DNA repair in an adult glioblastoma Test set (n=191) and validated in ‘The Cancer Genome Atlas’ (TCGA) cohort (n=508). A DNA repair prognostic index model was generated. Artificial neural network analysis (ANN) was conducted to investigate global gene interactions. Protein expression by immunohistochemistry was conducted in 61 tumours. A fourteen DNA repair gene expression panel was associated with poor survival in Test and TCGA cohorts. A Cox multivariate model revealed APE1, NBN, PMS2, MGMT and PTEN as independently associated with poor prognosis. A DNA repair prognostic index incorporating APE1, NBN, PMS2, MGMT and PTEN stratified patients in to three prognostic sub-groups with worsening survival. APE1, NBN, PMS2, MGMT and PTEN also have predictive significance in patients who received chemotherapy and/or radiotherapy. ANN analysis of APE1, NBN, PMS2, MGMT and PTEN revealed interactions with genes involved in transcription, hypoxia and metabolic regulation. At the protein level, low APE1 and low PTEN remain associated with poor prognosis. In conclusion, multiple DNA repair pathways operate to influence biology and clinical outcomes in adult high grade gliomas. PMID:25026297

Integrative mental health care: from theory to practice, Part 2.

PubMed

Lake, James

2008-01-01

Integrative approaches will lead to more accurate and different understandings of mental illness. Beneficial responses to complementary and alternative therapies provide important clues about the phenomenal nature of the human body in space-time and disparate biological, informational, and energetic factors associated with normal and abnormal psychological functioning. The conceptual framework of contemporary Western psychiatry includes multiple theoretical viewpoints, and there is no single best explanatory model of mental illness. Future theories of mental illness causation will not depend exclusively on empirical verification of strictly biological processes but will take into account both classically described biological processes and non-classical models, including complexity theory, resulting in more complete explanations of the characteristics and causes of symptoms and mechanisms of action that result in beneficial responses to treatments. Part 1 of this article examined the limitations of the theory and contemporary clinical methods employed in Western psychiatry and discussed implications of emerging paradigms in physics and the biological sciences for the future of psychiatry. In part 2, a practical methodology, for planning integrative assessment and treatment strategies in mental health care is proposed. Using this methodology the integrative management of moderate and severe psychiatric symptoms is reviewed in detail. As the conceptual framework of Western medicine evolves toward an increasingly integrative perspective, novel understanding of complex relationships between biological, informational, and energetic processes associated with normal psychological functioning and mental illness will lead to more effective integrative assessment and treatment strategies addressing the causes or meanings of symptoms at multiple hierarchic levels of body-brain-mind.

Integrative mental health care: from theory to practice, part 1.

PubMed

Lake, James

2007-01-01

Integrative approaches will lead to more accurate and different understandings of mental illness. Beneficial responses to complementary and alternative therapies provide important clues about the phenomenal nature of the human body in space-time and disparate biological, informational, and energetic factors associated with normal and abnormal psychological functioning. The conceptual framework of contemporary Western psychiatry includes multiple theoretical viewpoints, and there is no single best explanatory model of mental illness. Future theories of mental illness causation will not depend exclusively on empirical verification of strictly biological processes but will take into account both classically described biological processes and non-classical models, including complexity theory, resulting in more complete explanations of the characteristics and causes of symptoms and mechanisms of action that result in beneficial responses to treatments. Part 1 of this article examines the limitations of the theory and contemporary clinical methods employed in Western psychiatry and discusses implications of emerging paradigms in physics and the biological sciences for the future of psychiatry. In part 2, a practical methodology for planning integrative assessment and treatment strategies in mental health care is proposed. Using this methodology the integrative management of moderate and severe psychiatric symptoms is reviewed in detail. As the conceptual framework of Western medicine evolves toward an increasingly integrative perspective, novel understandings of complex relationships between biological, informational, and energetic processes associated with normal psychological functioning and mental illness will lead to more effective integrative assessment and treatment strategies addressing the causes or meanings of symptoms at multiple hierarchic levels of body-brain-mind.

Environmental Radiation Effects: A Need to Question Old Paradigms

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

Hinton, T.G.; Bedford, J.; Ulsh, B.

2003-03-27

A historical perspective is given of the current paradigm that does not explicitly protect the environment from radiation, but instead, relies on the concept that if dose limits are set to protect humans then the environment is automatically protected as well. We summarize recent international questioning of this paradigm and briefly present three different frameworks for protecting biota that are being considered by the U.S. DOE, the Canadian government and the International Commission on Radiological Protection. We emphasize that an enhanced collaboration is required between what has traditionally been separated disciplines of radiation biology and radiation ecology if we aremore » going to properly address the current environmental radiation problems. We then summarize results generated from an EMSP grant that allowed us to develop a Low Dose Irradiation Facility that specifically addresses effects of low-level, chronic irradiation on multiple levels of biological organization.« less

Social Determinants of Population Health: A Systems Sciences Approach

PubMed Central

Fink, David S.; Keyes, Katherine M.; Cerdá, Magdalena

2016-01-01

Population distributions of health emerge from the complex interplay of health-related factors at multiple levels, from the biological to the societal level. Individuals are aggregated within social networks, affected by their locations, and influenced differently across time. From aggregations of individuals, group properties can emerge, including some exposures that are ubiquitous within populations but variant across populations. By combining a focus on social determinants of health with a conceptual framework for understanding how genetics, biology, behavior, psychology, society, and environment interact, a systems science approach can inform our understanding of the underlying causes of the unequal distribution of health across generations and populations, and can help us identify promising approaches to reduce such inequalities. In this paper, we discuss how systems science approaches have already made several substantive and methodological contributions to the study of population health from a social epidemiology perspective. PMID:27642548

Hologenomics: Systems-Level Host Biology.

PubMed

Theis, Kevin R

2018-01-01

The hologenome concept of evolution is a hypothesis explaining host evolution in the context of the host microbiomes. As a hypothesis, it needs to be evaluated, especially with respect to the extent of fidelity of transgenerational coassociation of host and microbial lineages and the relative fitness consequences of repeated associations within natural holobiont populations. Behavioral ecologists are in a prime position to test these predictions because they typically focus on animal phenotypes that are quantifiable, conduct studies over multiple generations within natural animal populations, and collect metadata on genetic relatedness and relative reproductive success within these populations. Regardless of the conclusion on the hologenome concept as an evolutionary hypothesis, a hologenomic perspective has applied value as a systems-level framework for host biology, including in medicine. Specifically, it emphasizes investigating the multivarious and dynamic interactions between patient genomes and the genomes of their diverse microbiota when attempting to elucidate etiologies of complex, noninfectious diseases.

The oncogenic transforming potential of the passage of single α particles through mammalian cell nuclei

PubMed Central

Miller, Richard C.; Randers-Pehrson, Gerhard; Geard, Charles R.; Hall, Eric J.; Brenner, David J.

1999-01-01

Domestic, low-level exposure to radon gas is considered a major environmental lung-cancer hazard involving DNA damage to bronchial cells by α particles from radon progeny. At domestic exposure levels, the relevant bronchial cells are very rarely traversed by more than one α particle, whereas at higher radon levels—at which epidemiological studies in uranium miners allow lung-cancer risks to be quantified with reasonable precision—these bronchial cells are frequently exposed to multiple α-particle traversals. Measuring the oncogenic transforming effects of exactly one α particle without the confounding effects of multiple traversals has hitherto been unfeasible, resulting in uncertainty in extrapolations of risk from high to domestic radon levels. A technique to assess the effects of single α particles uses a charged-particle microbeam, which irradiates individual cells or cell nuclei with predefined exact numbers of particles. Although previously too slow to assess the relevant small oncogenic risks, recent improvements in throughput now permit microbeam irradiation of large cell numbers, allowing the first oncogenic risk measurements for the traversal of exactly one α particle through a cell nucleus. Given positive controls to ensure that the dosimetry and biological controls were comparable, the measured oncogenicity from exactly one α particle was significantly lower than for a Poisson-distributed mean of one α particle, implying that cells traversed by multiple α particles contribute most of the risk. If this result applies generally, extrapolation from high-level radon risks (involving cellular traversal by multiple α particles) may overestimate low-level (involving only single α particles) radon risks. PMID:9874764

The Distributed Biological Observatory (DBO)-A Change Detection Array in the Pacific Arctic Sector

NASA Astrophysics Data System (ADS)

Grebmeier, J. M.; Moore, S. E.; Cooper, L. W.; Frey, K. E.; Pickart, R. S.

2011-12-01

The Pacific sector of the Arctic Ocean is experiencing major reductions in seasonal sea ice extent and increases in sea surface temperatures. One of the key uncertainties in this region is how the marine ecosystem will respond to seasonal shifts in the timing of spring sea ice retreat and/or delays in fall sea ice formation. Variations in upper ocean water hydrography, planktonic production, pelagic-benthic coupling and sediment carbon cycling are all influenced by sea ice and temperature changes. Climate changes are likely to result in shifts in species composition and abundance, northward range expansions, and changes in lower trophic level productivity that can directly cascade and affect the life cycles of higher trophic level organisms. Several regionally critical marine sites in the Pacific Arctic sector that have very high biomass and are focused foraging points for apex predators have been re-occupied during multiple international cruises. The data documenting the importance of these ecosystem "hotspots" provide a growing marine time-series from the northern Bering Sea to Barrow Canyon at the boundary of the Chukchi and Beaufort seas. Results from these studies show spatial changes in carbon production and export to the sediments as indicated by infaunal community composition and biomass, shifts in sediment grain size on a S-to-N latitudinal gradient, and range extensions for lower trophic levels and further northward migration of higher trophic organisms, such as gray whales. There is also direct evidence of negative impacts on ice dependent species, such as walrus and polar bears. To more systematically track the broad biological response to sea ice retreat and associated environmental change, an international consortium of scientists are developing a "Distributed Biological Observatory" (DBO) that includes selected biological measurements at multiple trophic levels. The DBO currently focuses on five regional biological "hotspot" locations along a latitudinal gradient. Hydrographic transects occupied from spring to fall in 2010 and 2011 at two pilot sites in the SE Chukchi Sea and Barrow Canyon provide repeat collections of water parameters over the seasons that are unavailable from single cruises. This sampling indicates freshening and warming as Pacific seawater transits northward over the spring to fall seasons, with impacts on both plankton and benthic prey bases for larger marine mammals and seabirds. The intent of the DBO is to serve as a change detection array for the identification and consistent monitoring of biophysical responses. This network of spatially explicit DBOs is being organized through the Pacific Arctic Group (PAG), a collaborative network endorsed by the International Arctic Science Committee. Our presentation will provide new information to evaluate the status and developing trends of the marine biological system as it responds to the rapid environmental change.

Biological embedding: evaluation and analysis of an emerging concept for nursing scholarship.

PubMed

Nist, Marliese Dion

2017-02-01

The purpose of this paper was to report the analysis of the concept of biological embedding. Research that incorporates a life course perspective is becoming increasingly prominent in the health sciences. Biological embedding is a central concept in life course theory and may be important for nursing theories to enhance our understanding of health states in individuals and populations. Before the concept of biological embedding can be used in nursing theory and research, an analysis of the concept is required to advance it towards full maturity. Concept analysis. PubMed, CINAHL and PsycINFO were searched for publications using the term 'biological embedding' or 'biological programming' and published through 2015. An evaluation of the concept was first conducted to determine the concept's level of maturity and was followed by a concept comparison, using the methods for concept evaluation and comparison described by Morse. A consistent definition of biological embedding - the process by which early life experience alters biological processes to affect adult health outcomes - was found throughout the literature. The concept has been used in several theories that describe the mechanisms through which biological embedding might occur and highlight its role in the development of health trajectories. Biological embedding is a partially mature concept, requiring concept comparison with an overlapping concept - biological programming - to more clearly establish the boundaries of biological embedding. Biological embedding has significant potential for theory development and application in multiple academic disciplines, including nursing. © 2016 John Wiley & Sons Ltd.

Turning tumor-promoting copper into an anti-cancer weapon via high-throughput chemistry.

PubMed

Wang, F; Jiao, P; Qi, M; Frezza, M; Dou, Q P; Yan, B

2010-01-01

Copper is an essential element for multiple biological processes. Its concentration is elevated to a very high level in cancer tissues for promoting cancer development through processes such as angiogenesis. Organic chelators of copper can passively reduce cellular copper and serve the role as inhibitors of angiogenesis. However, they can also actively attack cellular targets such as proteasome, which plays a critical role in cancer development and survival. The discovery of such molecules initially relied on a step by step synthesis followed by biological assays. Today high-throughput chemistry and high-throughput screening have significantly expedited the copper-binding molecules discovery to turn "cancer-promoting" copper into anti-cancer agents.

A System Biology Perspective on Environment-Host-Microbe Interactions.

PubMed

Chen, Lianmin; Garmaeva, Sanzhima; Zherankova, Alexandra; Fu, Jingyuan; Wijmenga, Cisca

2018-04-16

A vast, complex and dynamic consortium of microorganisms known as the gut microbiome colonizes the human gut. Over the past few decades we have developed an increased awareness of its important role in human health. In this review we discuss the role of the gut microbiome in complex diseases and the possible causal scenarios behind its interactions with the host genome and environmental factors. We then propose a new analysis framework that combines a systems biology approach, cross-kingdom integration of multiple levels of omics data, and innovative in vitro models to yield an integrated picture of human host-microbe interactions. This new framework will lay the foundation for the development of the next phase in personalized medicine.

Post-transcriptional Regulation of Genes Related to Biological Behaviors of Gastric Cancer by Long Noncoding RNAs and MicroRNAs

PubMed Central

Liu, Wenjing; Ma, Rui; Yuan, Yuan

2017-01-01

Noncoding RNAs play critical roles in regulating protein-coding genes and comprise two major classes: long noncoding RNAs (lncRNAs) and microRNAs (miRNAs). LncRNAs regulate gene expression at transcriptional, post-transcriptional, and epigenetic levels via multiple action modes. LncRNAs can also function as endogenous competitive RNAs for miRNAs and indirectly regulate gene expression post-transcriptionally. By binding to the 3'-untranslated regions (3'-UTR) of target genes, miRNAs post-transcriptionally regulate gene expression. Herein, we conducted a review of post-transcriptional regulation by lncRNAs and miRNAs of genes associated with biological behaviors of gastric cancer. PMID:29187891

Generalizing genetical genomics: getting added value from environmental perturbation.

PubMed

Li, Yang; Breitling, Rainer; Jansen, Ritsert C

2008-10-01

Genetical genomics is a useful approach for studying the effect of genetic perturbations on biological systems at the molecular level. However, molecular networks depend on the environmental conditions and, thus, a comprehensive understanding of biological systems requires studying them across multiple environments. We propose a generalization of genetical genomics, which combines genetic and sensibly chosen environmental perturbations, to study the plasticity of molecular networks. This strategy forms a crucial step toward understanding why individuals respond differently to drugs, toxins, pathogens, nutrients and other environmental influences. Here we outline a strategy for selecting and allocating individuals to particular treatments, and we discuss the promises and pitfalls of the generalized genetical genomics approach.

A pharma perspective on the systems medicine and pharmacology of inflammation.

PubMed

Lahoz-Beneytez, Julio; Schnizler, Katrin; Eissing, Thomas

2015-02-01

Biological systems are complex and comprehend multiple scales of organisation. Hence, holistic approaches are necessary to capture the behaviour of these entities from the molecular and cellular to the whole organism level. This also applies to the understanding and treatment of different diseases. Traditional systems biology has been successful in describing different biological phenomena at the cellular level, but it still lacks of a holistic description of the multi-scale interactions within the body. The importance of the physiological context is of particular interest in inflammation. Regulatory agencies have urged the scientific community to increase the translational power of bio-medical research and it has been recognised that modelling and simulation could be a path to follow. Interestingly, in pharma R&D, modelling and simulation has been employed since a long time ago. Systems pharmacology, and particularly physiologically based pharmacokinetic/pharmacodynamic models, serve as a suitable framework to integrate the available and emerging knowledge at different levels of the drug development process. Systems medicine and pharmacology of inflammation will potentially benefit from this framework in order to better understand inflammatory diseases and to help to transfer the vast knowledge on the molecular and cellular level into a more physiological context. Ultimately, this may lead to reliable predictions of clinical outcomes such as disease progression or treatment efficacy, contributing thereby to a better care of patients. Copyright © 2014 Elsevier Inc. All rights reserved.

Analysis of a dynamic model of guard cell signaling reveals the stability of signal propagation

NASA Astrophysics Data System (ADS)

Gan, Xiao; Albert, RéKa

Analyzing the long-term behaviors (attractors) of dynamic models of biological systems can provide valuable insight into biological phenotypes and their stability. We identified the long-term behaviors of a multi-level, 70-node discrete dynamic model of the stomatal opening process in plants. We reduce the model's huge state space by reducing unregulated nodes and simple mediator nodes, and by simplifying the regulatory functions of selected nodes while keeping the model consistent with experimental observations. We perform attractor analysis on the resulting 32-node reduced model by two methods: 1. converting it into a Boolean model, then applying two attractor-finding algorithms; 2. theoretical analysis of the regulatory functions. We conclude that all nodes except two in the reduced model have a single attractor; and only two nodes can admit oscillations. The multistability or oscillations do not affect the stomatal opening level in any situation. This conclusion applies to the original model as well in all the biologically meaningful cases. We further demonstrate the robustness of signal propagation by showing that a large percentage of single-node knockouts does not affect the stomatal opening level. Thus, we conclude that the complex structure of this signal transduction network provides multiple information propagation pathways while not allowing extensive multistability or oscillations, resulting in robust signal propagation. Our innovative combination of methods offers a promising way to analyze multi-level models.

False positives in Biolog EcoPlates™ and MT2 MicroPlates™ caused by calcium.

PubMed

Pierce, Melissa L; Ward, J Evan; Dobbs, Fred C

2014-02-01

Biolog MicroPlates(TM) (e.g. EcoPlate(TM), MT2 MicroPlate(TM), GN MicroPlate(TM)) are useful tools for characterizing microbial communities, providing community-level physiological profiles to terrestrial and aquatic ecologists. The more recently designed Biolog EcoPlates have been used frequently in aquatic ecology with success. This study, however, reveals one major problem when using EcoPlates to evaluate samples within an estuarine or seawater matrix. At concentrations greater than 100 parts per million, the cation calcium begins to interfere with the microplate chemistry, causing false positive readings. Experiments, in which multiple treatments of natural and artificial seawater were tested, as well as calcium-addition experiments, demonstrate that calcium inhibits complete dissolution of the minimal growth medium in wells. Future studies involving Biolog EcoPlates and MicroPlates should take this effect into account, and the dilution of samples is strongly recommended to diminish the "calcium effect." Copyright © 2013 Elsevier B.V. All rights reserved.

Strategies for efficient numerical implementation of hybrid multi-scale agent-based models to describe biological systems

PubMed Central

Cilfone, Nicholas A.; Kirschner, Denise E.; Linderman, Jennifer J.

2015-01-01

Biologically related processes operate across multiple spatiotemporal scales. For computational modeling methodologies to mimic this biological complexity, individual scale models must be linked in ways that allow for dynamic exchange of information across scales. A powerful methodology is to combine a discrete modeling approach, agent-based models (ABMs), with continuum models to form hybrid models. Hybrid multi-scale ABMs have been used to simulate emergent responses of biological systems. Here, we review two aspects of hybrid multi-scale ABMs: linking individual scale models and efficiently solving the resulting model. We discuss the computational choices associated with aspects of linking individual scale models while simultaneously maintaining model tractability. We demonstrate implementations of existing numerical methods in the context of hybrid multi-scale ABMs. Using an example model describing Mycobacterium tuberculosis infection, we show relative computational speeds of various combinations of numerical methods. Efficient linking and solution of hybrid multi-scale ABMs is key to model portability, modularity, and their use in understanding biological phenomena at a systems level. PMID:26366228

Elbow joint variability for different hand positions of the round off in gymnastics.

PubMed

Farana, Roman; Irwin, Gareth; Jandacka, Daniel; Uchytil, Jaroslav; Mullineaux, David R

2015-02-01

The aim of the present study was to conduct within-gymnast analyses of biological movement variability in impact forces, elbow joint kinematics and kinetics of expert gymnasts in the execution of the round-off with different hand positions. Six international level female gymnasts performed 10 trials of the round-off from a hurdle step to a back-handspring using two hand potions: parallel and T-shape. Two force plates were used to determine ground reaction forces. Eight infrared cameras were employed to collect the kinematic data automatically. Within gymnast variability was calculated using biological coefficient of variation (BCV) discretely for ground reaction force, kinematic and kinetic measures. Variability of the continuous data was quantified using coefficient of multiple correlations (CMC). Group BCV and CMC were calculated and T-test with effect size statistics determined differences between the variability of the two techniques examined in this study. The major observation was a higher level of biological variability in the elbow joint abduction angle and adduction moment of force in the T-shaped hand position. This finding may lead to a reduced repetitive abduction stress and thus protect the elbow joint from overload. Knowledge of the differences in biological variability can inform clinicians and practitioners with effective skill selection. Copyright © 2014 Elsevier B.V. All rights reserved.

Use of a virtual human performance laboratory to improve integration of mathematics and biology in sports science curricula in Sweden and the United States.

PubMed

Garza, D; Besier, T; Johnston, T; Rolston, B; Schorsch, A; Matheson, G; Annerstedt, C; Lindh, J; Rydmark, M

2007-01-01

New fields such as bioengineering are exploring the role of the physical sciences in traditional biological approaches to problems, with exciting results in device innovation, medicine, and research biology. The integration of mathematics, biomechanics, and material sciences into the undergraduate biology curriculum will better prepare students for these opportunities and enhance cooperation among faculty and students at the university level. We propose the study of sports science as the basis for introduction of this interdisciplinary program. This novel integrated approach will require a virtual human performance laboratory dual-hosted in Sweden and the United States. We have designed a course model that involves cooperative learning between students at Göteborg University and Stanford University, utilizes new technologies, encourages development of original research and will rely on frequent self-assessment and reflective learning. We will compare outcomes between this course and a more traditional didactic format as well as assess the effectiveness of multiple web-hosted virtual environments. We anticipate the grant will result in a network of original faculty and student research in exercise science and pedagogy as well as provide the opportunity for implementation of the model in more advance training levels and K-12 programs.

Gene- and pathway-based association tests for multiple traits with GWAS summary statistics.

PubMed

Kwak, Il-Youp; Pan, Wei

2017-01-01

To identify novel genetic variants associated with complex traits and to shed new insights on underlying biology, in addition to the most popular single SNP-single trait association analysis, it would be useful to explore multiple correlated (intermediate) traits at the gene- or pathway-level by mining existing single GWAS or meta-analyzed GWAS data. For this purpose, we present an adaptive gene-based test and a pathway-based test for association analysis of multiple traits with GWAS summary statistics. The proposed tests are adaptive at both the SNP- and trait-levels; that is, they account for possibly varying association patterns (e.g. signal sparsity levels) across SNPs and traits, thus maintaining high power across a wide range of situations. Furthermore, the proposed methods are general: they can be applied to mixed types of traits, and to Z-statistics or P-values as summary statistics obtained from either a single GWAS or a meta-analysis of multiple GWAS. Our numerical studies with simulated and real data demonstrated the promising performance of the proposed methods. The methods are implemented in R package aSPU, freely and publicly available at: https://cran.r-project.org/web/packages/aSPU/ CONTACT: weip@biostat.umn.eduSupplementary information: Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Quantitative Proteomics by Metabolic Labeling of Model Organisms*

PubMed Central

Gouw, Joost W.; Krijgsveld, Jeroen; Heck, Albert J. R.

2010-01-01

In the biological sciences, model organisms have been used for many decades and have enabled the gathering of a large proportion of our present day knowledge of basic biological processes and their derailments in disease. Although in many of these studies using model organisms, the focus has primarily been on genetics and genomics approaches, it is important that methods become available to extend this to the relevant protein level. Mass spectrometry-based proteomics is increasingly becoming the standard to comprehensively analyze proteomes. An important transition has been made recently by moving from charting static proteomes to monitoring their dynamics by simultaneously quantifying multiple proteins obtained from differently treated samples. Especially the labeling with stable isotopes has proved an effective means to accurately determine differential expression levels of proteins. Among these, metabolic incorporation of stable isotopes in vivo in whole organisms is one of the favored strategies. In this perspective, we will focus on methodologies to stable isotope label a variety of model organisms in vivo, ranging from relatively simple organisms such as bacteria and yeast to Caenorhabditis elegans, Drosophila, and Arabidopsis up to mammals such as rats and mice. We also summarize how this has opened up ways to investigate biological processes at the protein level in health and disease, revealing conservation and variation across the evolutionary tree of life. PMID:19955089

Emergent properties of interacting populations of spiking neurons.

PubMed

Cardanobile, Stefano; Rotter, Stefan

2011-01-01

Dynamic neuronal networks are a key paradigm of increasing importance in brain research, concerned with the functional analysis of biological neuronal networks and, at the same time, with the synthesis of artificial brain-like systems. In this context, neuronal network models serve as mathematical tools to understand the function of brains, but they might as well develop into future tools for enhancing certain functions of our nervous system. Here, we present and discuss our recent achievements in developing multiplicative point processes into a viable mathematical framework for spiking network modeling. The perspective is that the dynamic behavior of these neuronal networks is faithfully reflected by a set of non-linear rate equations, describing all interactions on the population level. These equations are similar in structure to Lotka-Volterra equations, well known by their use in modeling predator-prey relations in population biology, but abundant applications to economic theory have also been described. We present a number of biologically relevant examples for spiking network function, which can be studied with the help of the aforementioned correspondence between spike trains and specific systems of non-linear coupled ordinary differential equations. We claim that, enabled by the use of multiplicative point processes, we can make essential contributions to a more thorough understanding of the dynamical properties of interacting neuronal populations.

A crucial step toward realism: responses to climate change from an evolving metacommunity perspective.

PubMed

Urban, Mark C; De Meester, Luc; Vellend, Mark; Stoks, Robby; Vanoverbeke, Joost

2012-02-01

We need to understand joint ecological and evolutionary responses to climate change to predict future threats to biological diversity. The 'evolving metacommunity' framework emphasizes that interactions between ecological and evolutionary mechanisms at both local and regional scales will drive community dynamics during climate change. Theory suggests that ecological and evolutionary dynamics often interact to produce outcomes different from those predicted based on either mechanism alone. We highlight two of these dynamics: (i) species interactions prevent adaptation of nonresident species to new niches and (ii) resident species adapt to changing climates and thereby prevent colonization by nonresident species. The rate of environmental change, level of genetic variation, source-sink structure, and dispersal rates mediate between these potential outcomes. Future models should evaluate multiple species, species interactions other than competition, and multiple traits. Future experiments should manipulate factors such as genetic variation and dispersal to determine their joint effects on responses to climate change. Currently, we know much more about how climates will change across the globe than about how species will respond to these changes despite the profound effects these changes will have on global biological diversity. Integrating evolving metacommunity perspectives into climate change biology should produce more accurate predictions about future changes to species distributions and extinction threats.

Adverse Outcome Pathway (AOP) Network Development for ...

EPA Pesticide Factsheets

Adverse outcome pathways (AOPs) are descriptive biological sequences that start from a molecular initiating event (MIE) and end with an adverse health outcome. AOPs provide biological context for high throughput chemical testing and further prioritize environmental health risk research. According to the Organization for Economic Co-operation and Development guidelines, AOPs are pathways with one MIE anchored to an adverse outcome (AO) by key events (KEs) and key event relationships (KERs). However, this approach does not always capture the cumulative impacts of multiple MIEs on the AO. For example, hepatic lipid flux due to chemical-induced toxicity initiates from multiple ligand-activated receptors and signaling pathways that cascade across biology to converge upon a common fatty liver (FL, also known as steatosis) outcome. To capture this complexity, a top-down strategy was used to develop a FL AOP network (AOPnet). Literature was queried based on the terms steatosis, fatty liver, cirrhosis, and hepatocellular carcinoma. Search results were analyzed for physiological and pathophysiological organ level, cellular and molecular processes, as well as pathway intermediates, to identify potential KEs and MIEs that are key for hepatic lipid metabolism, maintenance, and dysregulation. The analysis identified four apical KE nodes (hepatic fatty acid uptake, de novo fatty acid and lipid synthesis, fatty acid oxidation, and lipid efflux) juxtaposed to the FL AO. The apic

A crucial step toward realism: responses to climate change from an evolving metacommunity perspective

PubMed Central

Urban, Mark C; De Meester, Luc; Vellend, Mark; Stoks, Robby; Vanoverbeke, Joost

2012-01-01

We need to understand joint ecological and evolutionary responses to climate change to predict future threats to biological diversity. The ‘evolving metacommunity’ framework emphasizes that interactions between ecological and evolutionary mechanisms at both local and regional scales will drive community dynamics during climate change. Theory suggests that ecological and evolutionary dynamics often interact to produce outcomes different from those predicted based on either mechanism alone. We highlight two of these dynamics: (i) species interactions prevent adaptation of nonresident species to new niches and (ii) resident species adapt to changing climates and thereby prevent colonization by nonresident species. The rate of environmental change, level of genetic variation, source-sink structure, and dispersal rates mediate between these potential outcomes. Future models should evaluate multiple species, species interactions other than competition, and multiple traits. Future experiments should manipulate factors such as genetic variation and dispersal to determine their joint effects on responses to climate change. Currently, we know much more about how climates will change across the globe than about how species will respond to these changes despite the profound effects these changes will have on global biological diversity. Integrating evolving metacommunity perspectives into climate change biology should produce more accurate predictions about future changes to species distributions and extinction threats. PMID:25568038

Emergent Properties of Interacting Populations of Spiking Neurons

PubMed Central

Cardanobile, Stefano; Rotter, Stefan

2011-01-01

Dynamic neuronal networks are a key paradigm of increasing importance in brain research, concerned with the functional analysis of biological neuronal networks and, at the same time, with the synthesis of artificial brain-like systems. In this context, neuronal network models serve as mathematical tools to understand the function of brains, but they might as well develop into future tools for enhancing certain functions of our nervous system. Here, we present and discuss our recent achievements in developing multiplicative point processes into a viable mathematical framework for spiking network modeling. The perspective is that the dynamic behavior of these neuronal networks is faithfully reflected by a set of non-linear rate equations, describing all interactions on the population level. These equations are similar in structure to Lotka-Volterra equations, well known by their use in modeling predator-prey relations in population biology, but abundant applications to economic theory have also been described. We present a number of biologically relevant examples for spiking network function, which can be studied with the help of the aforementioned correspondence between spike trains and specific systems of non-linear coupled ordinary differential equations. We claim that, enabled by the use of multiplicative point processes, we can make essential contributions to a more thorough understanding of the dynamical properties of interacting neuronal populations. PMID:22207844

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

Conceptual understandings of biology in pre-service science educators and undergraduate biology students at Colorado institutions of higher education

NASA Astrophysics Data System (ADS)

Smith, Trenton John

Pre-service secondary science individuals, future middle or high school instructors training to become teachers, along with both Honors and general first year undergraduate biology students were investigated to determine how they reason about and understand two core topics in Biology: matter and energy flow through biological systems and evolution by natural selection. Diagnostic Question Clusters were used to assess student understanding of the processes by which matter and energy flow through biological systems over spatial scales, from the atomic-molecular to ecosystem levels. Key concepts and identified misconceptions were examined over topics of evolution by natural selection using the multiple-choice Concept Inventory of Natural Selection (CINS) and open-response Assessing COntextual Reasoning about Natural Selection (ACORNS). Pre-service teachers used more scientifically based reasoning than the undergraduate students over the topics of matter and energy flow. The Honors students used more scientific and less improper informal reasoning than the general undergraduates over matter and energy flow. Honors students performed best on both the CINS and ACORNS items over natural selection, while the general undergraduates scored the lowest on the CINS, and the pre-service instructors scored lowest on the ACORNS. Overall, there remain a large proportion of students not consistently using scientific reasoning about these two important concepts, even in future secondary science teachers. My findings are similar to those of other published studies using the same assessments. In general, very few biology students at the college level use scientific reasoning that exhibits deep conceptual understanding. A reason for this could be that instructors fail to recognize deficiencies in student reasoning; they assume their students use principle-based reasoning. Another reason could be that principle-based reasoning is very difficult and our teaching approaches in college promote memorization of content rather than conceptual change. My findings are significant to the work and progression of concept inventories in biology education, as well as to the instructors of students at all levels of biology curriculum, and those of future science teachers.

A structured sparse regression method for estimating isoform expression level from multi-sample RNA-seq data.

PubMed

Zhang, L; Liu, X J

2016-06-03

With the rapid development of next-generation high-throughput sequencing technology, RNA-seq has become a standard and important technique for transcriptome analysis. For multi-sample RNA-seq data, the existing expression estimation methods usually deal with each single-RNA-seq sample, and ignore that the read distributions are consistent across multiple samples. In the current study, we propose a structured sparse regression method, SSRSeq, to estimate isoform expression using multi-sample RNA-seq data. SSRSeq uses a non-parameter model to capture the general tendency of non-uniformity read distribution for all genes across multiple samples. Additionally, our method adds a structured sparse regularization, which not only incorporates the sparse specificity between a gene and its corresponding isoform expression levels, but also reduces the effects of noisy reads, especially for lowly expressed genes and isoforms. Four real datasets were used to evaluate our method on isoform expression estimation. Compared with other popular methods, SSRSeq reduced the variance between multiple samples, and produced more accurate isoform expression estimations, and thus more meaningful biological interpretations.

Calcium as a signal integrator in developing epithelial tissues.

PubMed

Brodskiy, Pavel A; Zartman, Jeremiah J

2018-05-16

Decoding how tissue properties emerge across multiple spatial and temporal scales from the integration of local signals is a grand challenge in quantitative biology. For example, the collective behavior of epithelial cells is critical for shaping developing embryos. Understanding how epithelial cells interpret a diverse range of local signals to coordinate tissue-level processes requires a systems-level understanding of development. Integration of multiple signaling pathways that specify cell signaling information requires second messengers such as calcium ions. Increasingly, specific roles have been uncovered for calcium signaling throughout development. Calcium signaling regulates many processes including division, migration, death, and differentiation. However, the pleiotropic and ubiquitous nature of calcium signaling implies that many additional functions remain to be discovered. Here we review a selection of recent studies to highlight important insights into how multiple signals are transduced by calcium transients in developing epithelial tissues. Quantitative imaging and computational modeling have provided important insights into how calcium signaling integration occurs. Reverse-engineering the conserved features of signal integration mediated by calcium signaling will enable novel approaches in regenerative medicine and synthetic control of morphogenesis.

PageMan: an interactive ontology tool to generate, display, and annotate overview graphs for profiling experiments.

PubMed

Usadel, Björn; Nagel, Axel; Steinhauser, Dirk; Gibon, Yves; Bläsing, Oliver E; Redestig, Henning; Sreenivasulu, Nese; Krall, Leonard; Hannah, Matthew A; Poree, Fabien; Fernie, Alisdair R; Stitt, Mark

2006-12-18

Microarray technology has become a widely accepted and standardized tool in biology. The first microarray data analysis programs were developed to support pair-wise comparison. However, as microarray experiments have become more routine, large scale experiments have become more common, which investigate multiple time points or sets of mutants or transgenics. To extract biological information from such high-throughput expression data, it is necessary to develop efficient analytical platforms, which combine manually curated gene ontologies with efficient visualization and navigation tools. Currently, most tools focus on a few limited biological aspects, rather than offering a holistic, integrated analysis. Here we introduce PageMan, a multiplatform, user-friendly, and stand-alone software tool that annotates, investigates, and condenses high-throughput microarray data in the context of functional ontologies. It includes a GUI tool to transform different ontologies into a suitable format, enabling the user to compare and choose between different ontologies. It is equipped with several statistical modules for data analysis, including over-representation analysis and Wilcoxon statistical testing. Results are exported in a graphical format for direct use, or for further editing in graphics programs.PageMan provides a fast overview of single treatments, allows genome-level responses to be compared across several microarray experiments covering, for example, stress responses at multiple time points. This aids in searching for trait-specific changes in pathways using mutants or transgenics, analyzing development time-courses, and comparison between species. In a case study, we analyze the results of publicly available microarrays of multiple cold stress experiments using PageMan, and compare the results to a previously published meta-analysis.PageMan offers a complete user's guide, a web-based over-representation analysis as well as a tutorial, and is freely available at http://mapman.mpimp-golm.mpg.de/pageman/. PageMan allows multiple microarray experiments to be efficiently condensed into a single page graphical display. The flexible interface allows data to be quickly and easily visualized, facilitating comparisons within experiments and to published experiments, thus enabling researchers to gain a rapid overview of the biological responses in the experiments.

Toxins, Targets, and Triggers: An Overview of Toxin-Antitoxin Biology.

PubMed

Harms, Alexander; Brodersen, Ditlev Egeskov; Mitarai, Namiko; Gerdes, Kenn

2018-06-07

Bacterial toxin-antitoxin (TA) modules are abundant genetic elements that encode a toxin protein capable of inhibiting cell growth and an antitoxin that counteracts the toxin. The majority of toxins are enzymes that interfere with translation or DNA replication, but a wide variety of molecular activities and cellular targets have been described. Antitoxins are proteins or RNAs that often control their cognate toxins through direct interactions and, in conjunction with other signaling elements, through transcriptional and translational regulation of TA module expression. Three major biological functions of TA modules have been discovered, post-segregational killing ("plasmid addiction"), abortive infection (bacteriophage immunity through altruistic suicide), and persister formation (antibiotic tolerance through dormancy). In this review, we summarize the current state of the field and highlight how multiple levels of regulation shape the conditions of toxin activation to achieve the different biological functions of TA modules. Copyright © 2018 Elsevier Inc. All rights reserved.

Multiscale Cancer Modeling

PubMed Central

Macklin, Paul; Cristini, Vittorio

2013-01-01

Simulating cancer behavior across multiple biological scales in space and time, i.e., multiscale cancer modeling, is increasingly being recognized as a powerful tool to refine hypotheses, focus experiments, and enable more accurate predictions. A growing number of examples illustrate the value of this approach in providing quantitative insight on the initiation, progression, and treatment of cancer. In this review, we introduce the most recent and important multiscale cancer modeling works that have successfully established a mechanistic link between different biological scales. Biophysical, biochemical, and biomechanical factors are considered in these models. We also discuss innovative, cutting-edge modeling methods that are moving predictive multiscale cancer modeling toward clinical application. Furthermore, because the development of multiscale cancer models requires a new level of collaboration among scientists from a variety of fields such as biology, medicine, physics, mathematics, engineering, and computer science, an innovative Web-based infrastructure is needed to support this growing community. PMID:21529163

Shadows of complexity: what biological networks reveal about epistasis and pleiotropy

PubMed Central

Tyler, Anna L.; Asselbergs, Folkert W.; Williams, Scott M.; Moore, Jason H.

2011-01-01

Pleiotropy, in which one mutation causes multiple phenotypes, has traditionally been seen as a deviation from the conventional observation in which one gene affects one phenotype. Epistasis, or gene-gene interaction, has also been treated as an exception to the Mendelian one gene-one phenotype paradigm. This simplified perspective belies the pervasive complexity of biology and hinders progress toward a deeper understanding of biological systems. We assert that epistasis and pleiotropy are not isolated occurrences, but ubiquitous and inherent properties of biomolecular networks. These phenomena should not be treated as exceptions, but rather as fundamental components of genetic analyses. A systems level understanding of epistasis and pleiotropy is, therefore, critical to furthering our understanding of human genetics and its contribution to common human disease. Finally, graph theory offers an intuitive and powerful set of tools with which to study the network bases of these important genetic phenomena. PMID:19204994

Wavelength dependence of biological damage induced by UV radiation on bacteria.

PubMed

Santos, Ana L; Oliveira, Vanessa; Baptista, Inês; Henriques, Isabel; Gomes, Newton C M; Almeida, Adelaide; Correia, António; Cunha, Ângela

2013-01-01

The biological effects of UV radiation of different wavelengths (UVA, UVB and UVC) were assessed in nine bacterial isolates displaying different UV sensitivities. Biological effects (survival and activity) and molecular markers of oxidative stress [DNA strand breakage (DSB), generation of reactive oxygen species (ROS), oxidative damage to proteins and lipids, and the activity of antioxidant enzymes catalase and superoxide dismutase] were quantified and statistically analyzed in order to identify the major determinants of cell inactivation under the different spectral regions. Survival and activity followed a clear wavelength dependence, being highest under UVA and lowest under UVC. The generation of ROS, as well as protein and lipid oxidation, followed the same pattern. DNA damage (DSB) showed the inverse trend. Multiple stepwise regression analysis revealed that survival under UVA, UVB and UVC wavelengths was best explained by DSB, oxidative damage to lipids, and intracellular ROS levels, respectively.

Examining the nature of retrocausal effects in biology and psychology

NASA Astrophysics Data System (ADS)

Mossbridge, Julia

2017-05-01

Multiple laboratories have reported physiological and psychological changes associated with future events that are designed to be unpredictable by normal sensory means. Such phenomena seem to be examples of retrocausality at the macroscopic level. Here I will discuss the characteristics of seemingly retrocausal effects in biology and psychology, specifically examining a biological and a psychological form of precognition, predictive anticipatory activity (PAA) and implicit precognition. The aim of this examination is to offer an analysis of the constraints posed by the characteristics of macroscopic retrocausal effects. Such constraints are critical to assessing any physical theory that purports to explain these effects. Following a brief introduction to recent research on PAA and implicit precognition, I will describe what I believe we have learned so far about the nature of these effects, and conclude with a testable, yet embryonic, model of macroscopic retrocausal phenomena.

Soundscapes from a Tropical Eastern Pacific reef and a Caribbean Sea reef

NASA Astrophysics Data System (ADS)

Staaterman, E.; Rice, A. N.; Mann, D. A.; Paris, C. B.

2013-06-01

Underwater soundscapes vary due to the abiotic and biological components of the habitat. We quantitatively characterized the acoustic environments of two coral reef habitats, one in the Tropical Eastern Pacific (Panama) and one in the Caribbean (Florida Keys), over 2-day recording durations in July 2011. We examined the frequency distribution, temporal variability, and biological patterns of sound production and found clear differences. The Pacific reef exhibited clear biological patterns and high temporal variability, such as the onset of snapping shrimp noise at night, as well as a 400-Hz daytime band likely produced by damselfish. In contrast, the Caribbean reef had high sound levels in the lowest frequencies, but lacked clear temporal patterns. We suggest that acoustic measures are an important element to include in reef monitoring programs, as the acoustic environment plays an important role in the ecology of reef organisms at multiple life-history stages.

Lichen physiology and cell biology

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

Brown, D.H.

1985-01-01

This book presents information on topics relating to mineral element accumulation in bog lichens, nitrogen losses from diazotrophic lichens, influence of automobile exhaust and lead on the oxygen exchange of lichens, temporal variation in lichen element levels, and lead and uranium uptake by lichens. Other topics include the architecture of the concentric bodies in the mycobiont of Peltigera praetextata; multiple enzyme forms in lichens, photosynthesis, water relations multiple enzyme forms in lichens, photosynthesis, water relations and thallus structure of strictaceae lichens; and aspects of carbohydrate metabolism in lichens. The distribution of uranium and companion elements in lichen heath associated withmore » undisturbed uranium deposits in the Canadian Arctic is also discussed.« less

The β-Arrestins: Multifunctional Regulators of G Protein-coupled Receptors.

PubMed

Smith, Jeffrey S; Rajagopal, Sudarshan

2016-04-22

The β-arrestins (βarrs) are versatile, multifunctional adapter proteins that are best known for their ability to desensitize G protein-coupled receptors (GPCRs), but also regulate a diverse array of cellular functions. To signal in such a complex fashion, βarrs adopt multiple conformations and are regulated at multiple levels to differentially activate downstream pathways. Recent structural studies have demonstrated that βarrs have a conserved structure and activation mechanism, with plasticity of their structural fold, allowing them to adopt a wide array of conformations. Novel roles for βarrs continue to be identified, demonstrating the importance of these dynamic regulators of cellular signaling. © 2016 by The American Society for Biochemistry and Molecular Biology, Inc.

Materiomics: biological protein materials, from nano to macro.

PubMed

Cranford, Steven; Buehler, Markus J

2010-11-12

Materiomics is an emerging field of science that provides a basis for multiscale material system characterization, inspired in part by natural, for example, protein-based materials. Here we outline the scope and explain the motivation of the field of materiomics, as well as demonstrate the benefits of a materiomic approach in the understanding of biological and natural materials as well as in the design of de novo materials. We discuss recent studies that exemplify the impact of materiomics - discovering Nature's complexity through a materials science approach that merges concepts of material and structure throughout all scales and incorporates feedback loops that facilitate sensing and resulting structural changes at multiple scales. The development and application of materiomics is illustrated for the specific case of protein-based materials, which constitute the building blocks of a variety of biological systems such as tendon, bone, skin, spider silk, cells, and tissue, as well as natural composite material systems (a combination of protein-based and inorganic constituents) such as nacre and mollusk shells, and other natural multiscale systems such as cellulose-based plant and wood materials. An important trait of these materials is that they display distinctive hierarchical structures across multiple scales, where molecular details are exhibited in macroscale mechanical responses. Protein materials are intriguing examples of materials that balance multiple tasks, representing some of the most sustainable material solutions that integrate structure and function despite severe limitations in the quality and quantity of material building blocks. However, up until now, our attempts to analyze and replicate Nature's materials have been hindered by our lack of fundamental understanding of these materials' intricate hierarchical structures, scale-bridging mechanisms, and complex material components that bestow protein-based materials their unique properties. Recent advances in analytical tools and experimental methods allow a holistic view of such a hierarchical biological material system. The integration of these approaches and amalgamation of material properties at all scale levels to develop a complete description of a material system falls within the emerging field of materiomics. Materiomics is the result of the convergence of engineering and materials science with experimental and computational biology in the context of natural and synthetic materials. Through materiomics, fundamental advances in our understanding of structure-property-process relations of biological systems contribute to the mechanistic understanding of certain diseases and facilitate the development of novel biological, biologically inspired, and completely synthetic materials for applications in medicine (biomaterials), nanotechnology, and engineering.

Materiomics: biological protein materials, from nano to macro

PubMed Central

Cranford, Steven; Buehler, Markus J

2010-01-01

Materiomics is an emerging field of science that provides a basis for multiscale material system characterization, inspired in part by natural, for example, protein-based materials. Here we outline the scope and explain the motivation of the field of materiomics, as well as demonstrate the benefits of a materiomic approach in the understanding of biological and natural materials as well as in the design of de novo materials. We discuss recent studies that exemplify the impact of materiomics – discovering Nature’s complexity through a materials science approach that merges concepts of material and structure throughout all scales and incorporates feedback loops that facilitate sensing and resulting structural changes at multiple scales. The development and application of materiomics is illustrated for the specific case of protein-based materials, which constitute the building blocks of a variety of biological systems such as tendon, bone, skin, spider silk, cells, and tissue, as well as natural composite material systems (a combination of protein-based and inorganic constituents) such as nacre and mollusk shells, and other natural multiscale systems such as cellulose-based plant and wood materials. An important trait of these materials is that they display distinctive hierarchical structures across multiple scales, where molecular details are exhibited in macroscale mechanical responses. Protein materials are intriguing examples of materials that balance multiple tasks, representing some of the most sustainable material solutions that integrate structure and function despite severe limitations in the quality and quantity of material building blocks. However, up until now, our attempts to analyze and replicate Nature’s materials have been hindered by our lack of fundamental understanding of these materials’ intricate hierarchical structures, scale-bridging mechanisms, and complex material components that bestow protein-based materials their unique properties. Recent advances in analytical tools and experimental methods allow a holistic view of such a hierarchical biological material system. The integration of these approaches and amalgamation of material properties at all scale levels to develop a complete description of a material system falls within the emerging field of materiomics. Materiomics is the result of the convergence of engineering and materials science with experimental and computational biology in the context of natural and synthetic materials. Through materiomics, fundamental advances in our understanding of structure–property–process relations of biological systems contribute to the mechanistic understanding of certain diseases and facilitate the development of novel biological, biologically inspired, and completely synthetic materials for applications in medicine (biomaterials), nanotechnology, and engineering. PMID:24198478

Acquisition of Cooperative Small Unmanned Aerial Systems for Advancing Man Machine Interface Research

DTIC Science & Technology

2016-08-24

global sensor field of views (FOVs), mimicking biological systems such as an insect fly eye , but allowing multiple aperture configurations. Due to...synthetic, global sensor field of views (FOVs), mimicking biological systems such as an insect fly eye , but allowing multiple aperture configurations. Due to...such as an insect fly eye , but allowing multiple aperture configurations. Due to the desired nature of distributed networked aerial vehicles (for the

A Systems Biology Analysis Unfolds the Molecular Pathways and Networks of Two Proteobacteria in Spaceflight and Simulated Microgravity Conditions.

PubMed

Roy, Raktim; Shilpa, P Phani; Bagh, Sangram

2016-09-01

Bacteria are important organisms for space missions due to their increased pathogenesis in microgravity that poses risks to the health of astronauts and for projected synthetic biology applications at the space station. We understand little about the effect, at the molecular systems level, of microgravity on bacteria, despite their significant incidence. In this study, we proposed a systems biology pipeline and performed an analysis on published gene expression data sets from multiple seminal studies on Pseudomonas aeruginosa and Salmonella enterica serovar Typhimurium under spaceflight and simulated microgravity conditions. By applying gene set enrichment analysis on the global gene expression data, we directly identified a large number of new, statistically significant cellular and metabolic pathways involved in response to microgravity. Alteration of metabolic pathways in microgravity has rarely been reported before, whereas in this analysis metabolic pathways are prevalent. Several of those pathways were found to be common across studies and species, indicating a common cellular response in microgravity. We clustered genes based on their expression patterns using consensus non-negative matrix factorization. The genes from different mathematically stable clusters showed protein-protein association networks with distinct biological functions, suggesting the plausible functional or regulatory network motifs in response to microgravity. The newly identified pathways and networks showed connection with increased survival of pathogens within macrophages, virulence, and antibiotic resistance in microgravity. Our work establishes a systems biology pipeline and provides an integrated insight into the effect of microgravity at the molecular systems level. Systems biology-Microgravity-Pathways and networks-Bacteria. Astrobiology 16, 677-689.

Integrated Analysis of Pharmacologic, Clinical, and SNP Microarray Data using Projection onto the Most Interesting Statistical Evidence with Adaptive Permutation Testing

PubMed Central

Pounds, Stan; Cao, Xueyuan; Cheng, Cheng; Yang, Jun; Campana, Dario; Evans, William E.; Pui, Ching-Hon; Relling, Mary V.

2010-01-01

Powerful methods for integrated analysis of multiple biological data sets are needed to maximize interpretation capacity and acquire meaningful knowledge. We recently developed Projection Onto the Most Interesting Statistical Evidence (PROMISE). PROMISE is a statistical procedure that incorporates prior knowledge about the biological relationships among endpoint variables into an integrated analysis of microarray gene expression data with multiple biological and clinical endpoints. Here, PROMISE is adapted to the integrated analysis of pharmacologic, clinical, and genome-wide genotype data that incorporating knowledge about the biological relationships among pharmacologic and clinical response data. An efficient permutation-testing algorithm is introduced so that statistical calculations are computationally feasible in this higher-dimension setting. The new method is applied to a pediatric leukemia data set. The results clearly indicate that PROMISE is a powerful statistical tool for identifying genomic features that exhibit a biologically meaningful pattern of association with multiple endpoint variables. PMID:21516175

Toward a multiscale modeling framework for understanding serotonergic function

PubMed Central

Wong-Lin, KongFatt; Wang, Da-Hui; Moustafa, Ahmed A; Cohen, Jeremiah Y; Nakamura, Kae

2017-01-01

Despite its importance in regulating emotion and mental wellbeing, the complex structure and function of the serotonergic system present formidable challenges toward understanding its mechanisms. In this paper, we review studies investigating the interactions between serotonergic and related brain systems and their behavior at multiple scales, with a focus on biologically-based computational modeling. We first discuss serotonergic intracellular signaling and neuronal excitability, followed by neuronal circuit and systems levels. At each level of organization, we will discuss the experimental work accompanied by related computational modeling work. We then suggest that a multiscale modeling approach that integrates the various levels of neurobiological organization could potentially transform the way we understand the complex functions associated with serotonin. PMID:28417684

Rapidly progressing malignant insulinoma presented with multiple liver metastases: a case report.

PubMed

Erdogan, Askin; Askin, Erdogan; Kose, Fatih; Fatih, Kose; Akkaya, Hampar; Hampar, Akkaya; Bascil Tutuncu, Neslihan; Tutuncu, Neslihan Bascil; Ozyilkan, Ozgur; Ozgur, Ozyilkan

2010-12-01

A 51-year-old female was admitted to emergency unit with sudden loss of consciousness. Her blood glucose level from fingertip was 33 mg/dl, and insulin level was 55 (normal range, 4-17 IU). Abdominal ultrasonography revealed pancreatic mass with diffuse liver metastases. Biopsy of liver metastases showed differentiated neuroendocrine carcinoma. Diazoxide and chemotherapy stabilized her glucose level for more than 4 months. However, the disease showed progression, and death occurred 8 months later. In conclusion, this case may suggest that biologic behavior may differ from histological behavior in insulinoma and platin-based systemic chemotherapy may provide some benefit in patients those who had diazoxide- and octreotide-resistant tumors.

An integrative system biology approach to unravel potential drug candidates for multiple age related disorders.

PubMed

Srivastava, Isha; Khurana, Pooja; Yadav, Mohini; Hasija, Yasha

2017-12-01

Aging, though an inevitable part of life, is becoming a worldwide social and economic problem. Healthy aging is usually marked by low probability of age related disorders. Good therapeutic approaches are still in need to cure age related disorders. Occurrence of more than one ARD in an individual, expresses the need of discovery of such target proteins, which can affect multiple ARDs. Advanced scientific and medical research technologies throughout last three decades have arrived to the point where lots of key molecular determinants affect human disorders can be examined thoroughly. In this study, we designed and executed an approach to prioritize drugs that may target multiple age related disorders. Our methodology, focused on the analysis of biological pathways and protein protein interaction networks that may contribute to the pharmacology of age related disorders, included various steps such as retrieval and analysis of data, protein-protein interaction network analysis, and statistical and comparative analysis of topological coefficients, pathway, and functional enrichment analysis, and identification of drug-target proteins. We assume that the identified molecular determinants may be prioritized for further screening as novel drug targets to cure multiple ARDs. Based on the analysis, an online tool named as 'ARDnet' has been developed to construct and demonstrate ARD interactions at the level of PPI, ARDs and ARDs protein interaction, ARDs pathway interaction and drug-target interaction. The tool is freely made available at http://genomeinformatics.dtu.ac.in/ARDNet/Index.html. Copyright © 2017 Elsevier B.V. All rights reserved.

“Gestaltomics”: Systems Biology Schemes for the Study of Neuropsychiatric Diseases

PubMed Central

Gutierrez Najera, Nora A.; Resendis-Antonio, Osbaldo; Nicolini, Humberto

2017-01-01

The integration of different sources of biological information about what defines a behavioral phenotype is difficult to unify in an entity that reflects the arithmetic sum of its individual parts. In this sense, the challenge of Systems Biology for understanding the “psychiatric phenotype” is to provide an improved vision of the shape of the phenotype as it is visualized by “Gestalt” psychology, whose fundamental axiom is that the observed phenotype (behavior or mental disorder) will be the result of the integrative composition of every part. Therefore, we propose the term “Gestaltomics” as a term from Systems Biology to integrate data coming from different sources of information (such as the genome, transcriptome, proteome, epigenome, metabolome, phenome, and microbiome). In addition to this biological complexity, the mind is integrated through multiple brain functions that receive and process complex information through channels and perception networks (i.e., sight, ear, smell, memory, and attention) that in turn are programmed by genes and influenced by environmental processes (epigenetic). Today, the approach of medical research in human diseases is to isolate one disease for study; however, the presence of an additional disease (co-morbidity) or more than one disease (multimorbidity) adds complexity to the study of these conditions. This review will present the challenge of integrating psychiatric disorders at different levels of information (Gestaltomics). The implications of increasing the level of complexity, for example, studying the co-morbidity with another disease such as cancer, will also be discussed. PMID:28536537

A Systems Biology Analysis Unfolds the Molecular Pathways and Networks of Two Proteobacteria in Spaceflight and Simulated Microgravity Conditions

NASA Astrophysics Data System (ADS)

Roy, Raktim; Phani Shilpa, P.; Bagh, Sangram

2016-09-01

Bacteria are important organisms for space missions due to their increased pathogenesis in microgravity that poses risks to the health of astronauts and for projected synthetic biology applications at the space station. We understand little about the effect, at the molecular systems level, of microgravity on bacteria, despite their significant incidence. In this study, we proposed a systems biology pipeline and performed an analysis on published gene expression data sets from multiple seminal studies on Pseudomonas aeruginosa and Salmonella enterica serovar Typhimurium under spaceflight and simulated microgravity conditions. By applying gene set enrichment analysis on the global gene expression data, we directly identified a large number of new, statistically significant cellular and metabolic pathways involved in response to microgravity. Alteration of metabolic pathways in microgravity has rarely been reported before, whereas in this analysis metabolic pathways are prevalent. Several of those pathways were found to be common across studies and species, indicating a common cellular response in microgravity. We clustered genes based on their expression patterns using consensus non-negative matrix factorization. The genes from different mathematically stable clusters showed protein-protein association networks with distinct biological functions, suggesting the plausible functional or regulatory network motifs in response to microgravity. The newly identified pathways and networks showed connection with increased survival of pathogens within macrophages, virulence, and antibiotic resistance in microgravity. Our work establishes a systems biology pipeline and provides an integrated insight into the effect of microgravity at the molecular systems level.

Biological Embedding: Evaluation and Analysis of an Emerging Concept for Nursing Scholarship

PubMed Central

Nist, Marliese Dion

2016-01-01

Aim The purpose of this paper is to report the analysis of the concept of biological embedding. Background Research that incorporates a life course perspective is becoming increasingly prominent in the health sciences. Biological embedding is a central concept in life course theory and may be important for nursing theories to enhance our understanding of health states in individuals and populations. Before the concept of biological embedding can be used in nursing theory and research, an analysis of the concept is required to advance it toward full maturity. Design Concept analysis. Data Sources PubMed, CINAHL and PsycINFO were searched for publications using the term ‘biological embedding’ or ‘biological programming’ and published through 2015. Methods An evaluation of the concept was first conducted to determine the concept’s level of maturity and was followed by a concept comparison, using the methods for concept evaluation and comparison described by Morse. Results A consistent definition of biological embedding – the process by which early life experience alters biological processes to affect adult health outcomes – was found throughout the literature. The concept has been used in several theories that describe the mechanisms through which biological embedding might occur and highlight its role in the development of health trajectories. Biological embedding is a partially mature concept, requiring concept comparison with an overlapping concept – biological programming – to more clearly establish the boundaries of biological embedding. Conclusions Biological embedding has significant potential for theory development and application in multiple academic disciplines, including nursing. PMID:27682606

Network Stability Is a Balancing Act of Personality, Power, and Conflict Dynamics in Rhesus Macaque Societies

PubMed Central

McCowan, Brenda; Beisner, Brianne A.; Capitanio, John P.; Jackson, Megan E.; Cameron, Ashley N.; Seil, Shannon; Atwill, Edward R.; Fushing, Hsieh

2011-01-01

Stability in biological systems requires evolved mechanisms that promote robustness. Cohesive primate social groups represent one example of a stable biological system, which persist in spite of frequent conflict. Multiple sources of stability likely exist for any biological system and such robustness, or lack thereof, should be reflected and thus detectable in the group's network structure, and likely at multiple levels. Here we show how network structure and group stability are linked to the fundamental characteristics of the individual agents in groups and to the environmental and social contexts in which these individuals interact. Both internal factors (e.g., personality, sex) and external factors (e.g., rank dynamics, sex ratio) were considered from the level of the individual to that of the group to examine the effects of network structure on group stability in a nonhuman primate species. The results yielded three main findings. First, successful third-party intervention behavior is a mechanism of group stability in rhesus macaques in that successful interventions resulted in less wounding in social groups. Second, personality is the primary factor that determines which individuals perform the role of key intervener, via its effect on social power and dominance discrepancy. Finally, individuals with high social power are not only key interveners but also key players in grooming networks and receive reconciliations from a higher diversity of individuals. The results from this study provide sound evidence that individual and group characteristics such as personality and sex ratio influence network structures such as patterns of reconciliation, grooming and conflict intervention that are indicators of network robustness and consequent health and well-being in rhesus macaque societies. Utilizing this network approach has provided greater insight into how behavioral and social processes influence social stability in nonhuman primate groups. PMID:21857922

Network stability is a balancing act of personality, power, and conflict dynamics in rhesus macaque societies.

PubMed

McCowan, Brenda; Beisner, Brianne A; Capitanio, John P; Jackson, Megan E; Cameron, Ashley N; Seil, Shannon; Atwill, Edward R; Fushing, Hsieh

2011-01-01

Stability in biological systems requires evolved mechanisms that promote robustness. Cohesive primate social groups represent one example of a stable biological system, which persist in spite of frequent conflict. Multiple sources of stability likely exist for any biological system and such robustness, or lack thereof, should be reflected and thus detectable in the group's network structure, and likely at multiple levels. Here we show how network structure and group stability are linked to the fundamental characteristics of the individual agents in groups and to the environmental and social contexts in which these individuals interact. Both internal factors (e.g., personality, sex) and external factors (e.g., rank dynamics, sex ratio) were considered from the level of the individual to that of the group to examine the effects of network structure on group stability in a nonhuman primate species. The results yielded three main findings. First, successful third-party intervention behavior is a mechanism of group stability in rhesus macaques in that successful interventions resulted in less wounding in social groups. Second, personality is the primary factor that determines which individuals perform the role of key intervener, via its effect on social power and dominance discrepancy. Finally, individuals with high social power are not only key interveners but also key players in grooming networks and receive reconciliations from a higher diversity of individuals. The results from this study provide sound evidence that individual and group characteristics such as personality and sex ratio influence network structures such as patterns of reconciliation, grooming and conflict intervention that are indicators of network robustness and consequent health and well-being in rhesus macaque societies. Utilizing this network approach has provided greater insight into how behavioral and social processes influence social stability in nonhuman primate groups.

Accelerated Genome Engineering through Multiplexing

PubMed Central

Zhao, Huimin

2015-01-01

Throughout the biological sciences, the past fifteen years have seen a push towards the analysis and engineering of biological systems at the organism level. Given the complexity of even the simplest organisms, though, to elicit a phenotype of interest often requires genotypic manipulation of several loci. By traditional means, sequential editing of genomic targets requires a significant investment of time and labor, as the desired editing event typically occurs at a very low frequency against an overwhelming unedited background. In recent years, the development of a suite of new techniques has greatly increased editing efficiency, opening up the possibility for multiple editing events to occur in parallel. Termed as multiplexed genome engineering, this approach to genome editing has greatly expanded the scope of possible genome manipulations in diverse hosts, ranging from bacteria to human cells. The enabling technologies for multiplexed genome engineering include oligonucleotide-based and nuclease-based methodologies, and their application has led to the great breadth of successful examples described in this review. While many technical challenges remain, there also exists a multiplicity of opportunities in this rapidly expanding field. PMID:26394307

Genetic Differences Between Humans and Great Apes -- Implications for the Evolution of Humans

NASA Astrophysics Data System (ADS)

Varki, Ajit

2004-06-01

At the level of individual protein sequences, humans are 97-100% identical to the great apes, our closest evolutionary relatives. The evolution of humans (and of human intelligence) from a common ancestor with the chimpanzee and bonobo involved many steps, influenced by interactions amongst factors of genetic, developmental, ecological, microbial, climatic, behavioral, cultural and social origin. The genetic factors can be approached by direct comparisons of human and great ape genomes, genes and gene products, and by elucidating biochemical and biological consequences of any differences found. We have discovered multiple genetic and biochemical differences between humans and great apes, particularly with respect to a family of cell surface molecules called sialic acids, as well as in the metabolism of thyroid hormones. The hormone differences have potential consequences for human brain development. The differences in sialic acid biology have multiple implications for the human condition, ranging from susceptibility or resistance to microbial pathogens, effects on endogenous receptors in the immune system, and potential effects on placental signaling, expression of oncofetal antigens in cancers, consequences of dietary intake of animal foods, and development of the mammalian brain.

Denitrifying capabilities of Tetrasphaera and their contribution towards nitrous oxide production in enhanced biological phosphorus removal processes.

PubMed

Marques, Ricardo; Ribera-Guardia, Anna; Santos, Jorge; Carvalho, Gilda; Reis, Maria A M; Pijuan, Maite; Oehmen, Adrian

2018-06-15

Denitrifying enhanced biological phosphorus removal (EBPR) systems can be an efficient means of removing phosphate (P) and nitrate (NO 3 - ) with low carbon source and oxygen requirements. Tetrasphaera is one of the most abundant polyphosphate accumulating organisms present in EBPR systems, but their capacity to achieve denitrifying EBPR has not previously been determined. An enriched Tetrasphaera culture, comprising over 80% of the bacterial biovolume was obtained in this work. Despite the denitrification capacity of Tetrasphaera, this culture achieved only low levels of anoxic P-uptake. Batch tests with different combinations of NO 3 - , nitrite (NO 2 - ) and nitrous oxide (N 2 O) revealed lower N 2 O accumulation by Tetrasphaera as compared to Accumulibacter and Competibacter when multiple electron acceptors were added. Electron competition was observed during the addition of multiple nitrogen electron acceptors species, where P uptake appeared to be slightly favoured over glycogen production in these situations. This study increases our understanding of the role of Tetrasphaera-related organisms in denitrifying EBPR systems. Copyright © 2018 Elsevier Ltd. All rights reserved.

Effects of multiple levels of social organization on survival and abundance.

PubMed

Ward, Eric J; Semmens, Brice X; Holmes, Elizabeth E; Balcomb Iii, Ken C

2011-04-01

Identifying how social organization shapes individual behavior, survival, and fecundity of animals that live in groups can inform conservation efforts and improve forecasts of population abundance, even when the mechanism responsible for group-level differences is unknown. We constructed a hierarchical Bayesian model to quantify the relative variability in survival rates among different levels of social organization (matrilines and pods) of an endangered population of killer whales (Orcinus orca). Individual killer whales often participate in group activities such as prey sharing and cooperative hunting. The estimated age-specific survival probabilities and survivorship curves differed considerably among pods and to a lesser extent among matrilines (within pods). Across all pods, males had lower life expectancy than females. Differences in survival between pods may be caused by a combination of factors that vary across the population's range, including reduced prey availability, contaminants in prey, and human activity. Our modeling approach could be applied to demographic rates for other species and for parameters other than survival, including reproduction, prey selection, movement, and detection probabilities. Conservation Biology ©2010 Society for Conservation Biology. No claim to original US government works.

Problem-Centered Supplemental Instruction in Biology: Influence on Content Recall, Content Understanding, and Problem Solving Ability

NASA Astrophysics Data System (ADS)

Gardner, Joel; Belland, Brian R.

2017-08-01

To address the need for effective, efficient ways to apply active learning in undergraduate biology courses, in this paper, we propose a problem-centered approach that utilizes supplemental web-based instructional materials based on principles of active learning. We compared two supplementary web-based modules using active learning strategies: the first used Merrill's First Principles of Instruction as a framework for organizing multiple active learning strategies; the second used a traditional web-based approach. Results indicated that (a) the First Principles group gained significantly from pretest to posttest at the Remember level ( t(40) = -1.432, p = 0.08, ES = 0.4) and at the Problem Solving level ( U = 142.5, N1 = 21, N2 = 21, p = .02, ES = 0.7) and (b) the Traditional group gained significantly from pretest to posttest at the Remember level ( t(36) = 1.762, p = 0.043, ES = 0.6). Those in the First Principles group were significantly more likely than the traditional group to be confident in their ability to solve problems in the future (χ2 (2, N = 40) = 3.585, p = 0.09).

When should we expect early bursts of trait evolution in comparative data? Predictions from an evolutionary food web model.

PubMed

Ingram, T; Harmon, L J; Shurin, J B

2012-09-01

Conceptual models of adaptive radiation predict that competitive interactions among species will result in an early burst of speciation and trait evolution followed by a slowdown in diversification rates. Empirical studies often show early accumulation of lineages in phylogenetic trees, but usually fail to detect early bursts of phenotypic evolution. We use an evolutionary simulation model to assemble food webs through adaptive radiation, and examine patterns in the resulting phylogenetic trees and species' traits (body size and trophic position). We find that when foraging trade-offs result in food webs where all species occupy integer trophic levels, lineage diversity and trait disparity are concentrated early in the tree, consistent with the early burst model. In contrast, in food webs in which many omnivorous species feed at multiple trophic levels, high levels of turnover of species' identities and traits tend to eliminate the early burst signal. These results suggest testable predictions about how the niche structure of ecological communities may be reflected by macroevolutionary patterns. © 2012 The Authors. Journal of Evolutionary Biology © 2012 European Society For Evolutionary Biology.

Gene regulatory network inference using fused LASSO on multiple data sets

PubMed Central

Omranian, Nooshin; Eloundou-Mbebi, Jeanne M. O.; Mueller-Roeber, Bernd; Nikoloski, Zoran

2016-01-01

Devising computational methods to accurately reconstruct gene regulatory networks given gene expression data is key to systems biology applications. Here we propose a method for reconstructing gene regulatory networks by simultaneous consideration of data sets from different perturbation experiments and corresponding controls. The method imposes three biologically meaningful constraints: (1) expression levels of each gene should be explained by the expression levels of a small number of transcription factor coding genes, (2) networks inferred from different data sets should be similar with respect to the type and number of regulatory interactions, and (3) relationships between genes which exhibit similar differential behavior over the considered perturbations should be favored. We demonstrate that these constraints can be transformed in a fused LASSO formulation for the proposed method. The comparative analysis on transcriptomics time-series data from prokaryotic species, Escherichia coli and Mycobacterium tuberculosis, as well as a eukaryotic species, mouse, demonstrated that the proposed method has the advantages of the most recent approaches for regulatory network inference, while obtaining better performance and assigning higher scores to the true regulatory links. The study indicates that the combination of sparse regression techniques with other biologically meaningful constraints is a promising framework for gene regulatory network reconstructions. PMID:26864687

How to integrate biological research into society and exclude errors in biomedical publications? Progress in theoretical and systems biology releases pressure on experimental research.

PubMed

Volkov, Vadim

2014-01-01

This brief opinion proposes measures to increase efficiency and exclude errors in biomedical research under the existing dynamic situation. Rapid changes in biology began with the description of the three dimensional structure of DNA 60 years ago; today biology has progressed by interacting with computer science and nanoscience together with the introduction of robotic stations for the acquisition of large-scale arrays of data. These changes have had an increasing influence on the entire research and scientific community. Future advance demands short-term measures to ensure error-proof and efficient development. They can include the fast publishing of negative results, publishing detailed methodical papers and excluding a strict connection between career progression and publication activity, especially for younger researchers. Further development of theoretical and systems biology together with the use of multiple experimental methods for biological experiments could also be helpful in the context of years and decades. With regards to the links between science and society, it is reasonable to compare both these systems, to find and describe specific features for biology and to integrate it into the existing stream of social life and financial fluxes. It will increase the level of scientific research and have mutual positive effects for both biology and society. Several examples are given for further discussion.

Do Houseflies Think? Patterns of Induction and Biological Beliefs in Development.

ERIC Educational Resources Information Center

Gutheil, Grant; Vera, Alonzo; Keil, Frank C.

1998-01-01

Examined preschoolers' inductive inferences across biological and non-biological kinds. Found support for gradual-enrichment model of conceptual change. Four-year-olds had a limited, coherent, independent biological theory which may form the basis of mature understanding of biological kinds. Explored results in terms of multiple explanatory…

Demonstrating microbial co-occurrence pattern analyses within and between ecosystems

PubMed Central

Williams, Ryan J.; Howe, Adina; Hofmockel, Kirsten S.

2014-01-01

Co-occurrence patterns are used in ecology to explore interactions between organisms and environmental effects on coexistence within biological communities. Analysis of co-occurrence patterns among microbial communities has ranged from simple pairwise comparisons between all community members to direct hypothesis testing between focal species. However, co-occurrence patterns are rarely studied across multiple ecosystems or multiple scales of biological organization within the same study. Here we outline an approach to produce co-occurrence analyses that are focused at three different scales: co-occurrence patterns between ecosystems at the community scale, modules of co-occurring microorganisms within communities, and co-occurring pairs within modules that are nested within microbial communities. To demonstrate our co-occurrence analysis approach, we gathered publicly available 16S rRNA amplicon datasets to compare and contrast microbial co-occurrence at different taxonomic levels across different ecosystems. We found differences in community composition and co-occurrence that reflect environmental filtering at the community scale and consistent pairwise occurrences that may be used to infer ecological traits about poorly understood microbial taxa. However, we also found that conclusions derived from applying network statistics to microbial relationships can vary depending on the taxonomic level chosen and criteria used to build co-occurrence networks. We present our statistical analysis and code for public use in analysis of co-occurrence patterns across microbial communities. PMID:25101065

Biological and nonbiological complex drugs for multiple sclerosis in Latin America: regulations and risk management.

PubMed

Carrá, Adriana; Macías Islas, Miguel Angel; Tarulla, Adriana; Bichuetti, Denis Bernardi; Finkelsztejn, Alessandro; Fragoso, Yara Dadalti; Árcega-Revilla, Raul; Cárcamo Rodríguez, Claudia; Durán, Juan Carlos; Bonitto, Juan García; León, Rosalba; Oehninger Gatti, Carlos; Orozco, Geraldine; Vizcarra Escobar, Darwin

2015-06-01

Biological drugs and nonbiological complex drugs with expired patents are followed by biosimilars and follow-on drugs that are supposedly similar and comparable with the reference product in terms of quality, safety and efficacy. Unlike simple molecules that can be copied and reproduced, biosimilars and follow-on complex drugs are heterogeneous and need specific regulations from health and pharmacovigilance agencies. A panel of 14 Latin American experts on multiple sclerosis from nine different countries met to discuss the recommendations regarding biosimilars and follow-on complex drugs for treating multiple sclerosis. Specific measures relating to manufacturing, therapeutic equivalence assessment and pharmacovigilance reports need to be implemented before commercialization. Physical, chemical, biological and immunogenic characterizations of the new product need to be available before clinical trials start. The new product must maintain the same immunogenicity as the original. Automatic substitution of biological and complex drugs poses unacceptable risks to the patient.

Multifactorial causal model of brain (dis)organization and therapeutic intervention: Application to Alzheimer's disease.

PubMed

Iturria-Medina, Yasser; Carbonell, Félix M; Sotero, Roberto C; Chouinard-Decorte, Francois; Evans, Alan C

2017-05-15

Generative models focused on multifactorial causal mechanisms in brain disorders are scarce and generally based on limited data. Despite the biological importance of the multiple interacting processes, their effects remain poorly characterized from an integrative analytic perspective. Here, we propose a spatiotemporal multifactorial causal model (MCM) of brain (dis)organization and therapeutic intervention that accounts for local causal interactions, effects propagation via physical brain networks, cognitive alterations, and identification of optimum therapeutic interventions. In this article, we focus on describing the model and applying it at the population-based level for studying late onset Alzheimer's disease (LOAD). By interrelating six different neuroimaging modalities and cognitive measurements, this model accurately predicts spatiotemporal alterations in brain amyloid-β (Aβ) burden, glucose metabolism, vascular flow, resting state functional activity, structural properties, and cognitive integrity. The results suggest that a vascular dysregulation may be the most-likely initial pathologic event leading to LOAD. Nevertheless, they also suggest that LOAD it is not caused by a unique dominant biological factor (e.g. vascular or Aβ) but by the complex interplay among multiple relevant direct interactions. Furthermore, using theoretical control analysis of the identified population-based multifactorial causal network, we show the crucial advantage of using combinatorial over single-target treatments, explain why one-target Aβ based therapies might fail to improve clinical outcomes, and propose an efficiency ranking of possible LOAD interventions. Although still requiring further validation at the individual level, this work presents the first analytic framework for dynamic multifactorial brain (dis)organization that may explain both the pathologic evolution of progressive neurological disorders and operationalize the influence of multiple interventional strategies. Copyright © 2017 Elsevier Inc. All rights reserved.

Detecting concerted demographic response across community assemblages using hierarchical approximate Bayesian computation.

PubMed

Chan, Yvonne L; Schanzenbach, David; Hickerson, Michael J

2014-09-01

Methods that integrate population-level sampling from multiple taxa into a single community-level analysis are an essential addition to the comparative phylogeographic toolkit. Detecting how species within communities have demographically tracked each other in space and time is important for understanding the effects of future climate and landscape changes and the resulting acceleration of extinctions, biological invasions, and potential surges in adaptive evolution. Here, we present a statistical framework for such an analysis based on hierarchical approximate Bayesian computation (hABC) with the goal of detecting concerted demographic histories across an ecological assemblage. Our method combines population genetic data sets from multiple taxa into a single analysis to estimate: 1) the proportion of a community sample that demographically expanded in a temporally clustered pulse and 2) when the pulse occurred. To validate the accuracy and utility of this new approach, we use simulation cross-validation experiments and subsequently analyze an empirical data set of 32 avian populations from Australia that are hypothesized to have expanded from smaller refugia populations in the late Pleistocene. The method can accommodate data set heterogeneity such as variability in effective population size, mutation rates, and sample sizes across species and exploits the statistical strength from the simultaneous analysis of multiple species. This hABC framework used in a multitaxa demographic context can increase our understanding of the impact of historical climate change by determining what proportion of the community responded in concert or independently and can be used with a wide variety of comparative phylogeographic data sets as biota-wide DNA barcoding data sets accumulate. © The Author 2014. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.

A Novel Method to Verify Multilevel Computational Models of Biological Systems Using Multiscale Spatio-Temporal Meta Model Checking

PubMed Central

Gilbert, David

2016-01-01

Insights gained from multilevel computational models of biological systems can be translated into real-life applications only if the model correctness has been verified first. One of the most frequently employed in silico techniques for computational model verification is model checking. Traditional model checking approaches only consider the evolution of numeric values, such as concentrations, over time and are appropriate for computational models of small scale systems (e.g. intracellular networks). However for gaining a systems level understanding of how biological organisms function it is essential to consider more complex large scale biological systems (e.g. organs). Verifying computational models of such systems requires capturing both how numeric values and properties of (emergent) spatial structures (e.g. area of multicellular population) change over time and across multiple levels of organization, which are not considered by existing model checking approaches. To address this limitation we have developed a novel approximate probabilistic multiscale spatio-temporal meta model checking methodology for verifying multilevel computational models relative to specifications describing the desired/expected system behaviour. The methodology is generic and supports computational models encoded using various high-level modelling formalisms because it is defined relative to time series data and not the models used to generate it. In addition, the methodology can be automatically adapted to case study specific types of spatial structures and properties using the spatio-temporal meta model checking concept. To automate the computational model verification process we have implemented the model checking approach in the software tool Mule (http://mule.modelchecking.org). Its applicability is illustrated against four systems biology computational models previously published in the literature encoding the rat cardiovascular system dynamics, the uterine contractions of labour, the Xenopus laevis cell cycle and the acute inflammation of the gut and lung. Our methodology and software will enable computational biologists to efficiently develop reliable multilevel computational models of biological systems. PMID:27187178

A System-Level Pathway-Phenotype Association Analysis Using Synthetic Feature Random Forest

PubMed Central

Pan, Qinxin; Hu, Ting; Malley, James D.; Andrew, Angeline S.; Karagas, Margaret R.; Moore, Jason H.

2015-01-01

As the cost of genome-wide genotyping decreases, the number of genome-wide association studies (GWAS) has increased considerably. However, the transition from GWAS findings to the underlying biology of various phenotypes remains challenging. As a result, due to its system-level interpretability, pathway analysis has become a popular tool for gaining insights on the underlying biology from high-throughput genetic association data. In pathway analyses, gene sets representing particular biological processes are tested for significant associations with a given phenotype. Most existing pathway analysis approaches rely on single-marker statistics and assume that pathways are independent of each other. As biological systems are driven by complex biomolecular interactions, embracing the complex relationships between single-nucleotide polymorphisms (SNPs) and pathways needs to be addressed. To incorporate the complexity of gene-gene interactions and pathway-pathway relationships, we propose a system-level pathway analysis approach, synthetic feature random forest (SF-RF), which is designed to detect pathway-phenotype associations without making assumptions about the relationships among SNPs or pathways. In our approach, the genotypes of SNPs in a particular pathway are aggregated into a synthetic feature representing that pathway via Random Forest (RF). Multiple synthetic features are analyzed using RF simultaneously and the significance of a synthetic feature indicates the significance of the corresponding pathway. We further complement SF-RF with pathway-based Statistical Epistasis Network (SEN) analysis that evaluates interactions among pathways. By investigating the pathway SEN, we hope to gain additional insights into the genetic mechanisms contributing to the pathway-phenotype association. We apply SF-RF to a population-based genetic study of bladder cancer and further investigate the mechanisms that help explain the pathway-phenotype associations using SEN. The bladder cancer associated pathways we found are both consistent with existing biological knowledge and reveal novel and plausible hypotheses for future biological validations. PMID:24535726

A Novel Method to Verify Multilevel Computational Models of Biological Systems Using Multiscale Spatio-Temporal Meta Model Checking.

PubMed

Pârvu, Ovidiu; Gilbert, David

2016-01-01

Insights gained from multilevel computational models of biological systems can be translated into real-life applications only if the model correctness has been verified first. One of the most frequently employed in silico techniques for computational model verification is model checking. Traditional model checking approaches only consider the evolution of numeric values, such as concentrations, over time and are appropriate for computational models of small scale systems (e.g. intracellular networks). However for gaining a systems level understanding of how biological organisms function it is essential to consider more complex large scale biological systems (e.g. organs). Verifying computational models of such systems requires capturing both how numeric values and properties of (emergent) spatial structures (e.g. area of multicellular population) change over time and across multiple levels of organization, which are not considered by existing model checking approaches. To address this limitation we have developed a novel approximate probabilistic multiscale spatio-temporal meta model checking methodology for verifying multilevel computational models relative to specifications describing the desired/expected system behaviour. The methodology is generic and supports computational models encoded using various high-level modelling formalisms because it is defined relative to time series data and not the models used to generate it. In addition, the methodology can be automatically adapted to case study specific types of spatial structures and properties using the spatio-temporal meta model checking concept. To automate the computational model verification process we have implemented the model checking approach in the software tool Mule (http://mule.modelchecking.org). Its applicability is illustrated against four systems biology computational models previously published in the literature encoding the rat cardiovascular system dynamics, the uterine contractions of labour, the Xenopus laevis cell cycle and the acute inflammation of the gut and lung. Our methodology and software will enable computational biologists to efficiently develop reliable multilevel computational models of biological systems.

Assessing secondary science students' knowledge of molecule movement, concentration gradients, and equilibrium through multiple contexts

NASA Astrophysics Data System (ADS)

Raven, Sara

2015-09-01

Background: Studies have shown that students' knowledge of osmosis and diffusion and the concepts associated with these processes is often inaccurate. This is important to address, as these concepts not only provide the foundation for more advanced topics in biology and chemistry, but are also threaded throughout both state and national science standards. Purpose: In this study, designed to determine the completeness and accuracy of three specific students' knowledge of molecule movement, concentration gradients, and equilibrium, I sought to address the following question: Using multiple evaluative methods, how can students' knowledge of molecule movement, concentration gradients, and equilibrium be characterized? Sample: This study focuses on data gathered from three students - Emma, Henry, and Riley - all of whom were gifted/honors ninth-grade biology students at a suburban high school in the southeast United States. Design and Methods: Using various qualitative data analysis techniques, I analyzed multiple sources of data from the three students, including multiple-choice test results, written free-response answers, think-aloud interview responses, and student drawings. Results: Results of the analysis showed that students maintained misconceptions about molecule movement, concentration gradients, and equilibrium. The conceptual knowledge students demonstrated differed depending on the assessment method, with the most distinct differences appearing on the multiple-choice versus the free-response questions, and in verbal versus written formats. Conclusions: Multiple levels of assessment may be required to obtain an accurate picture of content knowledge, as free-response and illustrative tasks made it difficult for students to conceal any misconceptions. Using a variety of assessment methods within a section of the curriculum can arguably help to provide a deeper understanding of student knowledge and learning, as well as illuminate misconceptions that may have remained unknown if only one assessment method was used. Furthermore, beyond simply evaluating past learning, multiple assessment methods may aid in student comprehension of key concepts.

Ocean acidification in the coastal zone from an organism's perspective: multiple system parameters, frequency domains, and habitats.

PubMed

Waldbusser, George G; Salisbury, Joseph E

2014-01-01

Multiple natural and anthropogenic processes alter the carbonate chemistry of the coastal zone in ways that either exacerbate or mitigate ocean acidification effects. Freshwater inputs and multiple acid-base reactions change carbonate chemistry conditions, sometimes synergistically. The shallow nature of these systems results in strong benthic-pelagic coupling, and marine invertebrates at different life history stages rely on both benthic and pelagic habitats. Carbonate chemistry in coastal systems can be highly variable, responding to processes with temporal modes ranging from seconds to centuries. Identifying scales of variability relevant to levels of biological organization requires a fuller characterization of both the frequency and magnitude domains of processes contributing to or reducing acidification in pelagic and benthic habitats. We review the processes that contribute to coastal acidification with attention to timescales of variability and habitats relevant to marine bivalves.

Explanatory Models for Psychiatric Illness

PubMed Central

Kendler, Kenneth S.

2009-01-01

How can we best develop explanatory models for psychiatric disorders? Because causal factors have an impact on psychiatric illness both at micro levels and macro levels, both within and outside of the individual, and involving processes best understood from biological, psychological, and sociocultural perspectives, traditional models of science that strive for single broadly applicable explanatory laws are ill suited for our field. Such models are based on the incorrect assumption that psychiatric illnesses can be understood from a single perspective. A more appropriate scientific model for psychiatry emphasizes the understanding of mechanisms, an approach that fits naturally with a multicausal framework and provides a realistic paradigm for scientific progress, that is, understanding mechanisms through decomposition and reassembly. Simple subunits of complicated mechanisms can be usefully studied in isolation. Reassembling these constituent parts into a functioning whole, which is straightforward for simple additive mechanisms, will be far more challenging in psychiatry where causal networks contain multiple nonlinear interactions and causal loops. Our field has long struggled with the interrelationship between biological and psychological explanatory perspectives. Building from the seminal work of the neuronal modeler and philosopher David Marr, the author suggests that biology will implement but not replace psychology within our explanatory systems. The iterative process of interactions between biology and psychology needed to achieve this implementation will deepen our understanding of both classes of processes. PMID:18483135

Ten good reasons to consider biological processes in prevention and intervention research

PubMed Central

BEAUCHAINE, THEODORE P.; NEUHAUS, EMILY; BRENNER, SHARON L.; GATZKE-KOPP, LISA

2009-01-01

Most contemporary accounts of psychopathology acknowledge the importance of both biological and environmental influences on behavior. In developmental psychopathology, multiple etiological mechanisms for psychiatric disturbance are well recognized, including those operating at genetic, neurobiological, and environmental levels of analysis. However, neuroscientific principles are rarely considered in current approaches to prevention or intervention. In this article, we explain why a deeper understanding of the genetic and neural substrates of behavior is essential for the next generation of preventive interventions, and we outline 10 specific reasons why considering biological processes can improve treatment efficacy. Among these, we discuss (a) the role of biomarkers and endophenotypes in identifying those most in need of prevention; (b) implications for treatment of genetic and neural mechanisms of homotypic comorbidity, heterotypic comorbidity, and heterotypic continuity; (c) ways in which biological vulnerabilities moderate the effects of environmental experience; (d) situations in which Biology×Environment interactions account for more variance in key outcomes than main effects; and (e) sensitivity of neural systems, via epigenesis, programming, and neural plasticity, to environmental moderation across the life span. For each of the 10 reasons outlined we present an example from current literature and discuss critical implications for prevention. PMID:18606030

Biological control of invasive plant species: a reassessment for the Anthropocene.

PubMed

Seastedt, Timothy R

2015-01-01

The science of finding, testing and releasing herbivores and pathogens to control invasive plant species has achieved a level of maturity and success that argues for continued and expanded use of this program. The practice, however, remains unpopular with some conservationists, invasion biologists, and stakeholders. The ecological and economic benefits of controlling densities of problematic plant species using biological control agents can be quantified, but the risks and net benefits of biological control programs are often derived from social or cultural rather than scientific criteria. Management of invasive plants is a 'wicked problem', and local outcomes to wicked problems have both positive and negative consequences differentially affecting various groups of stakeholders. The program has inherent uncertainties; inserting species into communities that are experiencing directional or even transformational changes can produce multiple outcomes due to context-specific factors that are further confounded by environmental change drivers. Despite these uncertainties, biological control could play a larger role in mitigation and adaptation strategies used to maintain biological diversity as well as contribute to human well-being by protecting food and fiber resources. © 2014 The Author New Phytologist © 2014 New Phytologist Trust.

Ten good reasons to consider biological processes in prevention and intervention research.

PubMed

Beauchaine, Theodore P; Neuhaus, Emily; Brenner, Sharon L; Gatzke-Kopp, Lisa

2008-01-01

Most contemporary accounts of psychopathology acknowledge the importance of both biological and environmental influences on behavior. In developmental psychopathology, multiple etiological mechanisms for psychiatric disturbance are well recognized, including those operating at genetic, neurobiological, and environmental levels of analysis. However, neuroscientific principles are rarely considered in current approaches to prevention or intervention. In this article, we explain why a deeper understanding of the genetic and neural substrates of behavior is essential for the next generation of preventive interventions, and we outline 10 specific reasons why considering biological processes can improve treatment efficacy. Among these, we discuss (a) the role of biomarkers and endophenotypes in identifying those most in need of prevention; (b) implications for treatment of genetic and neural mechanisms of homotypic comorbidity, heterotypic comorbidity, and heterotypic continuity; (c) ways in which biological vulnerabilities moderate the effects of environmental experience; (d) situations in which Biology x Environment interactions account for more variance in key outcomes than main effects; and (e) sensitivity of neural systems, via epigenesis, programming, and neural plasticity, to environmental moderation across the life span. For each of the 10 reasons outlined we present an example from current literature and discuss critical implications for prevention.

Promoting Inquiry-Based Teaching in Laboratory Courses: Are We Meeting the Grade?

PubMed Central

Butler, Amy; Burke da Silva, Karen

2014-01-01

Over the past decade, repeated calls have been made to incorporate more active teaching and learning in undergraduate biology courses. The emphasis on inquiry-based teaching is especially important in laboratory courses, as these are the courses in which students are applying the process of science. To determine the current state of research on inquiry-based teaching in undergraduate biology laboratory courses, we reviewed the recent published literature on inquiry-based exercises. The majority of studies in our data set were in the subdisciplines of biochemistry, cell biology, developmental biology, genetics, and molecular biology. In addition, most exercises were guided inquiry, rather than open ended or research based. Almost 75% of the studies included assessment data, with two-thirds of these studies including multiple types of assessment data. However, few exercises were assessed in multiple courses or at multiple institutions. Furthermore, assessments were rarely based on published instruments. Although the results of the studies in our data set show a positive effect of inquiry-based teaching in biology laboratory courses on student learning gains, research that uses the same instrument across a range of courses and institutions is needed to determine whether these results can be generalized. PMID:25185228

Significance of the E3 ubiquitin protein UBR5 as an oncogene and a prognostic biomarker in colorectal cancer

PubMed Central

Xu, Xiaowen; Zhu, Yan; Guo, Aizhen; Shen, Xian; Cao, Fuao; Chang, Wenjun

2017-01-01

The E3 ubiquitin protein UBR5 has been implicated in the regulation of multiple biological functions and has recently emerged as a key regulator of the ubiquitin-proteasome system (UPS) in cancer. However, the clinical significance and biological function of UBR5 in colorectal cancer (CRC) are poorly understood. In this study, we compared the expression pattern of UBR5 between CRC and adjacent normal tissues and found that UBR5 expression was frequently elevated in CRC, possibly through chromosomal gains. Using three CRC patient cohorts, we found that patients with high UBR5 mRNA levels, UBR5 gene amplification, or high nuclear UBR5 protein levels had poor prognoses. Multivariate analysis showed that the alterations in UBR5 were independent predictors of CRC prognosis with the TNM stage as a confounding factor. Furthermore, knockdown of UBR5 prevented the proliferation, colony formation, migration, and invasion of CRC cells in cell culture models. An in vivo animal model further confirmed that UBR5 knockdown reduced the growth of CRC tumors. In conclusion, our study is the first to systematically investigate the clinical and biological significance of UBR5 and to conclude that an elevated UBR5 level plays an oncogenic role and may be a potential prognostic marker in CRC. PMID:29296225

Comparison of intracellular water content measurements by dark-field imaging and EELS in medium voltage TEM

NASA Astrophysics Data System (ADS)

Terryn, C.; Michel, J.; Kilian, L.; Bonhomme, P.; Balossier, G.

2000-09-01

Knowledge of the water content at the subcellular level is important to evaluate the intracellular concentration of either diffusible or non-diffusible elements in the physiological state measured by the electron microprobe methods. Water content variations in subcellular compartments are directly related to secretion phenomena and to transmembrane exchange processes, which could be attributed to pathophysiological states. In this paper we will describe in details and compare two local water measurement methods using analytical electron microscopy. The first one is based on darkfield imaging. It is applied on freeze-dried biological cryosections; it allows indirect measurement of the water content at the subcellular level from recorded maps of darkfield intensity. The second method uses electron energy loss spectroscopy. It is applied to hydrated biological cryosections. It is based on the differences that appear in the electron energy loss spectra of macromolecular assemblies and vitrified ice in the 0-30 eV range. By a multiple least squares (MLS) fit between an experimental energy loss spectrum and reference spectra of both frozen-hydrated ice and macromolecular assemblies we can deduce directly the local water concentration in biological cryosections at the subcellular level. These two methods are applied to two test specimens: human erythrocytes in plasma, and baker's yeast (Saccharomyses Cerevisiae) cryosections. We compare the water content measurements obtained by these two methods and discuss their advantages and drawbacks.

Cellular automata with object-oriented features for parallel molecular network modeling.

PubMed

Zhu, Hao; Wu, Yinghui; Huang, Sui; Sun, Yan; Dhar, Pawan

2005-06-01

Cellular automata are an important modeling paradigm for studying the dynamics of large, parallel systems composed of multiple, interacting components. However, to model biological systems, cellular automata need to be extended beyond the large-scale parallelism and intensive communication in order to capture two fundamental properties characteristic of complex biological systems: hierarchy and heterogeneity. This paper proposes extensions to a cellular automata language, Cellang, to meet this purpose. The extended language, with object-oriented features, can be used to describe the structure and activity of parallel molecular networks within cells. Capabilities of this new programming language include object structure to define molecular programs within a cell, floating-point data type and mathematical functions to perform quantitative computation, message passing capability to describe molecular interactions, as well as new operators, statements, and built-in functions. We discuss relevant programming issues of these features, including the object-oriented description of molecular interactions with molecule encapsulation, message passing, and the description of heterogeneity and anisotropy at the cell and molecule levels. By enabling the integration of modeling at the molecular level with system behavior at cell, tissue, organ, or even organism levels, the program will help improve our understanding of how complex and dynamic biological activities are generated and controlled by parallel functioning of molecular networks. Index Terms-Cellular automata, modeling, molecular network, object-oriented.

Rebooting Bioresilience: A Multi-OMICS Approach to Tackle Global Catastrophic Biological Risks and Next-Generation Biothreats.

PubMed

Kambouris, Manousos E; Manoussopoulos, Yiannis; Kantzanou, Maria; Velegraki, Aristea; Gaitanis, Georgios; Arabatzis, Michalis; Patrinos, George P

2018-01-01

Global Catastrophic Biological Risks (GCBRs) refer to biological events-natural, deliberate, and accidental-of a global and lasting impact. This challenges the life scientists to raise their game on two hitherto neglected innovation frontiers: a veritable "futures" thinking to "think the unthinkable," and "systems thinking" so as to see both the trees and the forest when it comes to GCBRs. This innovation analysis article outlines the promise of Omics systems science biotechnologies, for example, to deploy rapid fire diagnostics for health security crises at GCBR level, possibly involving neopathogens and/or incurring epidemics (e.g., severe acute respiratory syndrome [SARS] and Ebola) that collectively threaten the lives of global society and interdependent biological ecosystems. Moreover, Omics encourages thinking beyond immediacy and in long-term strategies for biopreparedness and response innovation when the timelines are aggressive and compressed in response to crises such as GCBRs, but also to non-global but surging, multiple threats occurring as successive, overlapping, or distinct events, rather than as distinct entities-a prospect enforcing a reboot in Bioresilience. We define Next-Generation Bioresilience as "a systems approach against natural, accidental and perpetrated GCBRs using Omics technologies, and a shift in mentality, whereby the systems approach is expanded to include multiple plausible futures and expose unchecked assumptions attendant to risks, beyond technological determinism." In sum, it is time to think about the realistic potential of Omics biotechnologies beyond clinical practice and precision medicine so as to harness the opportunities and address the uncertainties associated not only with GCBRs but also with other emerging Omics applications in health and society.

The Math-Biology Values Instrument: Development of a Tool to Measure Life Science Majors' Task Values of Using Math in the Context of Biology.

PubMed

Andrews, Sarah E; Runyon, Christopher; Aikens, Melissa L

2017-01-01

In response to calls to improve the quantitative training of undergraduate biology students, there have been increased efforts to better integrate math into biology curricula. One challenge of such efforts is negative student attitudes toward math, which are thought to be particularly prevalent among biology students. According to theory, students' personal values toward using math in a biological context will influence their achievement and behavioral outcomes, but a validated instrument is needed to determine this empirically. We developed the Math-Biology Values Instrument (MBVI), an 11-item college-level self--report instrument grounded in expectancy-value theory, to measure life science students' interest in using math to understand biology, the perceived usefulness of math to their life science career, and the cost of using math in biology courses. We used a process that integrates multiple forms of validity evidence to show that scores from the MBVI can be used as a valid measure of a student's value of math in the context of biology. The MBVI can be used by instructors and researchers to help identify instructional strategies that influence math-biology values and understand how math-biology values are related to students' achievement and decisions to pursue more advanced quantitative-based courses. © 2017 S. E. Andrews 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).

Occupational exposure to potentially infectious biological material in a dental teaching environment.

PubMed

Machado-Carvalhais, Helenaura P; Ramos-Jorge, Maria L; Auad, Sheyla M; Martins, Laura H P M; Paiva, Saul M; Pordeus, Isabela A

2008-10-01

The aims of this cross-sectional study were to determine the prevalence of occupational accidents with exposure to biological material among undergraduate students of dentistry and to estimate potential risk factors associated with exposure to blood. Data were collected through a self-administered questionnaire (86.4 percent return rate), which was completed by a sample of 286 undergraduate dental students (mean age 22.4 +/-2.4 years). The students were enrolled in the clinical component of the curriculum, which corresponds to the final six semesters of study. Descriptive, bivariate, simple logistic regression and multiple logistic regression (Forward Stepwise Procedure) analyses were performed. The level of statistical significance was set at 5 percent. Percutaneous and mucous exposures to potentially infectious biological material were reported by 102 individuals (35.6 percent); 26.8 percent reported the occurrence of multiple episodes of exposure. The logistic regression analyses revealed that the incomplete use of individual protection equipment (OR=3.7; 95 percent CI 1.5-9.3), disciplines where surgical procedures are carried out (OR=16.3; 95 percent CI 7.1-37.2), and handling sharp instruments (OR=4.4; 95 percent CI 2.1-9.1), more specifically, hollow-bore needles (OR=6.8; 95 percent CI 2.1-19.0), were independently associated with exposure to blood. Policies of reviewing the procedures during clinical practice are recommended in order to reduce occupational exposure.

Indirect Effects of Global Change: From Physiological and Behavioral Mechanisms to Ecological Consequences.

PubMed

Gunderson, Alex R; Tsukimura, Brian; Stillman, Jonathon H

2017-07-01

A major focus of current ecological research is to understand how global change makes species vulnerable to extirpation. To date, mechanistic ecophysiological analyses of global change vulnerability have focused primarily on the direct effects of changing abiotic conditions on whole-organism physiological traits, such as metabolic rate, locomotor performance, cardiac function, and critical thermal limits. However, species do not live in isolation within their physical environments, and direct effects of climate change are likely to be compounded by indirect effects that result from altered interactions with other species, such as competitors and predators. The Society for Integrative and Comparative Biology 2017 Symposium "Indirect Effects of Global Change: From Physiological and Behavioral Mechanisms to Ecological Consequences" was designed to synthesize multiple approaches to investigating the indirect effects of global change by bringing together researchers that study the indirect effects of global change from multiple perspectives across habitat, type of anthropogenic change, and level of biological organization. Our goal in bringing together researchers from different backgrounds was to foster cross-disciplinary insights into the mechanistic bases and higher-order ecological consequences of indirect effects of global change, and to promote collaboration among fields. © The Author 2017. Published by Oxford University Press on behalf of the Society for Integrative and Comparative Biology. All rights reserved. For permissions please email: journals.permissions@oup.com.

Introduction to bioinformatics.

PubMed

Can, Tolga

2014-01-01

Bioinformatics is an interdisciplinary field mainly involving molecular biology and genetics, computer science, mathematics, and statistics. Data intensive, large-scale biological problems are addressed from a computational point of view. The most common problems are modeling biological processes at the molecular level and making inferences from collected data. A bioinformatics solution usually involves the following steps: Collect statistics from biological data. Build a computational model. Solve a computational modeling problem. Test and evaluate a computational algorithm. This chapter gives a brief introduction to bioinformatics by first providing an introduction to biological terminology and then discussing some classical bioinformatics problems organized by the types of data sources. Sequence analysis is the analysis of DNA and protein sequences for clues regarding function and includes subproblems such as identification of homologs, multiple sequence alignment, searching sequence patterns, and evolutionary analyses. Protein structures are three-dimensional data and the associated problems are structure prediction (secondary and tertiary), analysis of protein structures for clues regarding function, and structural alignment. Gene expression data is usually represented as matrices and analysis of microarray data mostly involves statistics analysis, classification, and clustering approaches. Biological networks such as gene regulatory networks, metabolic pathways, and protein-protein interaction networks are usually modeled as graphs and graph theoretic approaches are used to solve associated problems such as construction and analysis of large-scale networks.

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

Parasites, proteomes and systems: has Descartes' clock run out of time?

PubMed

Wastling, J M; Armstrong, S D; Krishna, R; Xia, D

2012-08-01

Systems biology aims to integrate multiple biological data types such as genomics, transcriptomics and proteomics across different levels of structure and scale; it represents an emerging paradigm in the scientific process which challenges the reductionism that has dominated biomedical research for hundreds of years. Systems biology will nevertheless only be successful if the technologies on which it is based are able to deliver the required type and quality of data. In this review we discuss how well positioned is proteomics to deliver the data necessary to support meaningful systems modelling in parasite biology. We summarise the current state of identification proteomics in parasites, but argue that a new generation of quantitative proteomics data is now needed to underpin effective systems modelling. We discuss the challenges faced to acquire more complete knowledge of protein post-translational modifications, protein turnover and protein-protein interactions in parasites. Finally we highlight the central role of proteome-informatics in ensuring that proteomics data is readily accessible to the user-community and can be translated and integrated with other relevant data types.

A biochemical network can control formation of a synthetic material by sensing numerous specific stimuli

NASA Astrophysics Data System (ADS)

Hun Yeon, Ju; Chan, Karen Y. T.; Wong, Ting-Chia; Chan, Kelvin; Sutherland, Michael R.; Ismagilov, Rustem F.; Pryzdial, Edward L. G.; Kastrup, Christian J.

2015-05-01

Developing bio-compatible smart materials that assemble in response to environmental cues requires strategies that can discriminate multiple specific stimuli in a complex milieu. Synthetic materials have yet to achieve this level of sensitivity, which would emulate the highly evolved and tailored reaction networks of complex biological systems. Here we show that the output of a naturally occurring network can be replaced with a synthetic material. Exploiting the blood coagulation system as an exquisite biological sensor, the fibrin clot end-product was replaced with a synthetic material under the biological control of a precisely regulated cross-linking enzyme. The functions of the coagulation network remained intact when the material was incorporated. Clot-like polymerization was induced in indirect response to distinct small molecules, phospholipids, enzymes, cells, viruses, an inorganic solid, a polyphenol, a polysaccharide, and a membrane protein. This strategy demonstrates for the first time that an existing stimulus-responsive biological network can be used to control the formation of a synthetic material by diverse classes of physiological triggers.

Parasites, proteomes and systems: has Descartes’ clock run out of time?

PubMed Central

WASTLING, J. M.; ARMSTRONG, S. D.; KRISHNA, R.; XIA, D.

2012-01-01

SUMMARY Systems biology aims to integrate multiple biological data types such as genomics, transcriptomics and proteomics across different levels of structure and scale; it represents an emerging paradigm in the scientific process which challenges the reductionism that has dominated biomedical research for hundreds of years. Systems biology will nevertheless only be successful if the technologies on which it is based are able to deliver the required type and quality of data. In this review we discuss how well positioned is proteomics to deliver the data necessary to support meaningful systems modelling in parasite biology. We summarise the current state of identification proteomics in parasites, but argue that a new generation of quantitative proteomics data is now needed to underpin effective systems modelling. We discuss the challenges faced to acquire more complete knowledge of protein post-translational modifications, protein turnover and protein-protein interactions in parasites. Finally we highlight the central role of proteome-informatics in ensuring that proteomics data is readily accessible to the user-community and can be translated and integrated with other relevant data types. PMID:22828391

The Annotated Bibliography and Citation Behavior: Enhancing Student Scholarship in an Undergraduate Biology Course

PubMed Central

Rux, Erika M.; Flaspohler, John A.

2007-01-01

Contemporary undergraduates in the biological sciences have unprecedented access to scientific information. Although many of these students may be savvy technologists, studies from the field of library and information science consistently show that undergraduates often struggle to locate, evaluate, and use high-quality, reputable sources of information. This study demonstrates the efficacy and pedagogical value of a collaborative teaching approach designed to enhance information literacy competencies among undergraduate biology majors who must write a formal scientific research paper. We rely on the triangulation of assessment data to determine the effectiveness of a substantial research paper project completed by students enrolled in an upper-level biology course. After enhancing library-based instruction, adding an annotated bibliography requirement, and using multiple assessment techniques, we show fundamental improvements in students' library research abilities. Ultimately, these improvements make it possible for students to more independently and effectively complete this challenging science-based writing assignment. We document critical information literacy advances in several key areas: student source-type use, annotated bibliography enhancement, plagiarism reduction, as well as student and faculty/librarian satisfaction. PMID:18056306

Using multi-criteria analysis of simulation models to understand complex biological systems

Treesearch

Maureen C. Kennedy; E. David Ford

2011-01-01

Scientists frequently use computer-simulation models to help solve complex biological problems. Typically, such models are highly integrated, they produce multiple outputs, and standard methods of model analysis are ill suited for evaluating them. We show how multi-criteria optimization with Pareto optimality allows for model outputs to be compared to multiple system...

Practice Makes Pretty Good: Assessment of Primary Literature Reading Abilities across Multiple Large-Enrollment Biology Laboratory Courses

ERIC Educational Resources Information Center

Sato, Brian K.; Kadandale, Pavan; He, Wenliang; Murata, Paige M. N.; Latif, Yama; Warschauer, Mark

2014-01-01

Primary literature is essential for scientific communication and is commonly utilized in undergraduate biology education. Despite this, there is often little time spent "training" our students how to critically analyze a paper. To address this, we introduced a primary literature module in multiple upper-division laboratory courses. In…

Hepatic Proteomic Analysis Revealed Altered Metabolic Pathways in Insulin Resistant Akt1+/-/Akt2-/-Mice

PubMed Central

Pedersen, Brian A; Wang, Weiwen; Taylor, Jared F; Khattab, Omar S; Chen, Yu-Han; Edwards, Robert A; Yazdi, Puya G; Wang, Ping H

2015-01-01

Objective The aim of this study was to identify liver proteome changes in a mouse model of severe insulin resistance and markedly decreased leptin levels. Methods Two-dimensional differential gel electrophoresis was utilized to identify liver proteome changes in AKT1+/-/AKT2-/- mice. Proteins with altered levels were identified with tandem mass spectrometry. Ingenuity Pathway analysis was performed for the interpretation of the biological significance of the observed proteomic changes. Results 11 proteins were identified from 2 biological replicates to be differentially expressed by a ratio of at least 1.3 between age-matched insulin resistant (Akt1+/-/Akt2-/-) and wild type mice. Albumin and mitochondrial ornithine aminotransferase were detected from multiple spots, which suggest post-translational modifications. Enzymes of the urea cycle were common members of top regulated pathways. Conclusion Our results help to unveil the regulation of the liver proteome underlying altered metabolism in an animal model of severe insulin resistance. PMID:26455965

Deep Residual Network Predicts Cortical Representation and Organization of Visual Features for Rapid Categorization.

PubMed

Wen, Haiguang; Shi, Junxing; Chen, Wei; Liu, Zhongming

2018-02-28

The brain represents visual objects with topographic cortical patterns. To address how distributed visual representations enable object categorization, we established predictive encoding models based on a deep residual network, and trained them to predict cortical responses to natural movies. Using this predictive model, we mapped human cortical representations to 64,000 visual objects from 80 categories with high throughput and accuracy. Such representations covered both the ventral and dorsal pathways, reflected multiple levels of object features, and preserved semantic relationships between categories. In the entire visual cortex, object representations were organized into three clusters of categories: biological objects, non-biological objects, and background scenes. In a finer scale specific to each cluster, object representations revealed sub-clusters for further categorization. Such hierarchical clustering of category representations was mostly contributed by cortical representations of object features from middle to high levels. In summary, this study demonstrates a useful computational strategy to characterize the cortical organization and representations of visual features for rapid categorization.

Inspiring Integration in College Students Reading Multiple Biology Texts

ERIC Educational Resources Information Center

Firetto, Carla

2013-01-01

Introductory biology courses typically present topics on related biological systems across separate chapters and lectures. A complete foundational understanding requires that students understand how these biological systems are related. Unfortunately, spontaneous generation of these connections is rare for novice learners. These experiments focus…

Integrated Analyses of Cuticular Hydrocarbons, Chromosome and mtDNA in the Neotropical Social Wasp Mischocyttarus consimilis Zikán (Hymenoptera, Vespidae).

PubMed

Cunha, D A S; Menezes, R S T; Costa, M A; Lima, S M; Andrade, L H C; Antonialli, W F

2017-12-01

In the present work, we explored multiple data from different biological levels such as cuticular hydrocarbons, chromosomal features, and mtDNA sequences in the Neotropical social wasp Mischocyttarus consimilis (J.F. Zikán). Particularly, we explored the genetic and chemical differentiation level within and between populations of this insect. Our dataset revealed shallow intraspecific differentiation in M. consimilis. The similarity among the analyzed samples can probably be due to the geographical proximity where the colonies were sampled, and we argue that Paraná River did not contribute effectively as a historical barrier to this wasp.

Challenges and opportunities in social neuroscience

PubMed Central

Cacioppo, John T.; Decety, Jean

2010-01-01

Social species are so characterized because they form organizations that extend beyond the individual. The goal of social neuroscience is to investigate the biological mechanisms that underlie these social structures, processes, and behavior and the influences between social and neural structures and processes. Such an endeavor is challenging because it necessitates the integration of multiple levels. Mapping across systems and levels (from genome to social groups and cultures) requires interdisciplinary expertise, comparative studies, innovative methods, and integrative conceptual analysis. Examples of how social neuroscience is contributing to our understanding of the functions of the brain and nervous system are described, and societal implications of social neuroscience are considered. PMID:21251011

Dose critical in-vivo detection of anti-cancer drug levels in blood

DOEpatents

Miller, Holly H.; Hirschfeld, deceased, Tomas B.

1991-01-01

A method and apparatus are disclosed for the in vivo and in vitro detection and measurement of dose critical levels of DNA-binding anti-cancer drug levels in biological fluids. The apparatus comprises a laser based fiber optic sensor (optrode) which utilizes the secondary interactions between the drug and an intercalating fluorochrome bound to a probe DNA, which in turn is attached to the fiber tip at one end thereof. The other end of the optical fiber is attached to an illumination source, detector and recorder. The fluorescence intensity is measured as a function of the drug concentration and its binding constant to the probe DNA. Anticancer drugs which lend themselves to analysis by the use of the method and the optrode of the present invention include doxorubicin, daunorubicin, carminomycin, aclacinomycin, chlorambucil, cyclophosphamide, methotrexate, 5-uracil, arabinosyl cytosine, mitomycin, cis-platinum 11 diamine dichloride procarbazine, vinblastine vincristine and the like. The present method and device are suitable for the continuous monitoring of the levels of these and other anticancer drugs in biological fluids such as blood, serum, urine and the like. The optrode of the instant invention also enables the measurement of the levels of these drugs from a remote location and from multiple samples.

Unmasking molecular profiles of bladder cancer.

PubMed

Piao, Xuan-Mei; Byun, Young Joon; Kim, Wun-Jae; Kim, Jayoung

2018-03-01

Precision medicine is designed to tailor treatments for individual patients by factoring in each person's specific biology and mechanism of disease. This paradigm shifted from a "one size fits all" approach to "personalized and precision care" requires multiple layers of molecular profiling of biomarkers for accurate diagnosis and prediction of treatment responses. Intensive studies are also being performed to understand the complex and dynamic molecular profiles of bladder cancer. These efforts involve looking bladder cancer mechanism at the multiple levels of the genome, epigenome, transcriptome, proteome, lipidome, metabolome etc. The aim of this short review is to outline the current technologies being used to investigate molecular profiles and discuss biomarker candidates that have been investigated as possible diagnostic and prognostic indicators of bladder cancer.

Systemic lupus erythematosus diagnostics in the ‘omics’ era

PubMed Central

Arriens, Cristina; Mohan, Chandra

2014-01-01

Systemic lupus erythematosus is a complex autoimmune disease affecting multiple organ systems. Currently, diagnosis relies upon meeting at least four out of eleven criteria outlined by the ACR. The scientific community actively pursues discovery of novel diagnostics in the hope of better identifying susceptible individuals in early stages of disease. Comprehensive studies have been conducted at multiple biological levels including: DNA (or genomics), mRNA (or transcriptomics), protein (or proteomics) and metabolites (or metabolomics). The ‘omics’ platforms allow us to re-examine systemic lupus erythematosus at a greater degree of molecular resolution. More importantly, one is hopeful that these ‘omics’ platforms may yield newer biomarkers for systemic lupus erythematosus that can help clinicians track the disease course with greater sensitivity and specificity. PMID:24860621

Why infectious disease research needs community ecology

PubMed Central

Johnson, Pieter T. J.; de Roode, Jacobus C.; Fenton, Andy

2016-01-01

Infectious diseases often emerge from interactions among multiple species and across nested levels of biological organization. Threats as diverse as Ebola virus, human malaria, and bat white-nose syndrome illustrate the need for a mechanistic understanding of the ecological interactions underlying emerging infections. We describe how recent advances in community ecology can be adopted to address contemporary challenges in disease research. These analytical tools can identify the factors governing complex assemblages of multiple hosts, parasites, and vectors, and reveal how processes link across scales from individual hosts to regions. They can also determine the drivers of heterogeneities among individuals, species, and regions to aid targeting of control strategies. We provide examples where these principles have enhanced disease management and illustrate how they can be further extended. PMID:26339035

Genetic variations in the serotonergic system contribute to amygdala volume in humans.

PubMed

Li, Jin; Chen, Chunhui; Wu, Karen; Zhang, Mingxia; Zhu, Bi; Chen, Chuansheng; Moyzis, Robert K; Dong, Qi

2015-01-01

The amygdala plays a critical role in emotion processing and psychiatric disorders associated with emotion dysfunction. Accumulating evidence suggests that amygdala structure is modulated by serotonin-related genes. However, there is a gap between the small contributions of single loci (less than 1%) and the reported 63-65% heritability of amygdala structure. To understand the "missing heritability," we systematically explored the contribution of serotonin genes on amygdala structure at the gene set level. The present study of 417 healthy Chinese volunteers examined 129 representative polymorphisms in genes from multiple biological mechanisms in the regulation of serotonin neurotransmission. A system-level approach using multiple regression analyses identified that nine SNPs collectively accounted for approximately 8% of the variance in amygdala volume. Permutation analyses showed that the probability of obtaining these findings by chance was low (p = 0.043, permuted for 1000 times). Findings showed that serotonin genes contribute moderately to individual differences in amygdala volume in a healthy Chinese sample. These results indicate that the system-level approach can help us to understand the genetic basis of a complex trait such as amygdala structure.

Associations between five-factor model of the Positive and Negative Syndrome Scale and plasma levels of monoamine metabolite in patients with schizophrenia.

PubMed

Watanabe, Kenya; Miura, Itaru; Kanno-Nozaki, Keiko; Horikoshi, Sho; Mashiko, Hirobumi; Niwa, Shin-Ichi; Yabe, Hirooki

2015-12-15

The five-factor model of the Positive and Negative Syndrome Scale (PANSS) for schizophrenia symptoms is the most common multiple-factor model used in analyses; its use may improve evaluation of symptoms in schizophrenia patients. Plasma monoamine metabolite levels are possible indicators of clinical symptoms or response to antipsychotics in schizophrenia. We investigated the association between five-factor model components and plasma monoamine metabolites levels to explore the model's biological basis. Plasma levels of homovanillic acid (HVA), 3-methoxy-4-hydroxyphenylglycol (MHPG), and 5-hydroxyindoleacetic acid (5-HIAA) were measured using high-performance liquid chromatography in 65 Japanese patients with schizophrenia. Significant negative correlation between plasma 5-HIAA levels and the depression/anxiety component was found. Furthermore, significant positive correlation was found between plasma MHPG levels and the excitement component. Plasma HVA levels were not correlated with any five-factor model component. These results suggest that the five-factor model of the PANSS may have a biological basis, and may be useful for elucidating the psychopathology of schizophrenia. Assessment using the five-factor model may enable understanding of monoaminergic dysfunction, possibly allowing more appropriate medication selection. Further studies of a larger number of first-episode schizophrenia patients are needed to confirm and extend these results. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Embracing interactions in ocean acidification research: confronting multiple stressor scenarios and context dependence

PubMed Central

Kordas, Rebecca L.; Harley, Christopher D. G.

2017-01-01

Changes in the Earth's environment are now sufficiently complex that our ability to forecast the emergent ecological consequences of ocean acidification (OA) is limited. Such projections are challenging because the effects of OA may be enhanced, reduced or even reversed by other environmental stressors or interactions among species. Despite an increasing emphasis on multifactor and multispecies studies in global change biology, our ability to forecast outcomes at higher levels of organization remains low. Much of our failure lies in a poor mechanistic understanding of nonlinear responses, a lack of specificity regarding the levels of organization at which interactions can arise, and an incomplete appreciation for linkages across these levels. To move forward, we need to fully embrace interactions. Mechanistic studies on physiological processes and individual performance in response to OA must be complemented by work on population and community dynamics. We must also increase our understanding of how linkages and feedback among multiple environmental stressors and levels of organization can generate nonlinear responses to OA. This will not be a simple undertaking, but advances are of the utmost importance as we attempt to mitigate the effects of ongoing global change. PMID:28356409

Embracing interactions in ocean acidification research: confronting multiple stressor scenarios and context dependence.

PubMed

Kroeker, Kristy J; Kordas, Rebecca L; Harley, Christopher D G

2017-03-01

Changes in the Earth's environment are now sufficiently complex that our ability to forecast the emergent ecological consequences of ocean acidification (OA) is limited. Such projections are challenging because the effects of OA may be enhanced, reduced or even reversed by other environmental stressors or interactions among species. Despite an increasing emphasis on multifactor and multispecies studies in global change biology, our ability to forecast outcomes at higher levels of organization remains low. Much of our failure lies in a poor mechanistic understanding of nonlinear responses, a lack of specificity regarding the levels of organization at which interactions can arise, and an incomplete appreciation for linkages across these levels. To move forward, we need to fully embrace interactions. Mechanistic studies on physiological processes and individual performance in response to OA must be complemented by work on population and community dynamics. We must also increase our understanding of how linkages and feedback among multiple environmental stressors and levels of organization can generate nonlinear responses to OA. This will not be a simple undertaking, but advances are of the utmost importance as we attempt to mitigate the effects of ongoing global change. © 2017 The Authors.

Structured association analysis leads to insight into Saccharomyces cerevisiae gene regulation by finding multiple contributing eQTL hotspots associated with functional gene modules.

PubMed

Curtis, Ross E; Kim, Seyoung; Woolford, John L; Xu, Wenjie; Xing, Eric P

2013-03-21

Association analysis using genome-wide expression quantitative trait locus (eQTL) data investigates the effect that genetic variation has on cellular pathways and leads to the discovery of candidate regulators. Traditional analysis of eQTL data via pairwise statistical significance tests or linear regression does not leverage the availability of the structural information of the transcriptome, such as presence of gene networks that reveal correlation and potentially regulatory relationships among the study genes. We employ a new eQTL mapping algorithm, GFlasso, which we have previously developed for sparse structured regression, to reanalyze a genome-wide yeast dataset. GFlasso fully takes into account the dependencies among expression traits to suppress false positives and to enhance the signal/noise ratio. Thus, GFlasso leverages the gene-interaction network to discover the pleiotropic effects of genetic loci that perturb the expression level of multiple (rather than individual) genes, which enables us to gain more power in detecting previously neglected signals that are marginally weak but pleiotropically significant. While eQTL hotspots in yeast have been reported previously as genomic regions controlling multiple genes, our analysis reveals additional novel eQTL hotspots and, more interestingly, uncovers groups of multiple contributing eQTL hotspots that affect the expression level of functional gene modules. To our knowledge, our study is the first to report this type of gene regulation stemming from multiple eQTL hotspots. Additionally, we report the results from in-depth bioinformatics analysis for three groups of these eQTL hotspots: ribosome biogenesis, telomere silencing, and retrotransposon biology. We suggest candidate regulators for the functional gene modules that map to each group of hotspots. Not only do we find that many of these candidate regulators contain mutations in the promoter and coding regions of the genes, in the case of the Ribi group, we provide experimental evidence suggesting that the identified candidates do regulate the target genes predicted by GFlasso. Thus, this structured association analysis of a yeast eQTL dataset via GFlasso, coupled with extensive bioinformatics analysis, discovers a novel regulation pattern between multiple eQTL hotspots and functional gene modules. Furthermore, this analysis demonstrates the potential of GFlasso as a powerful computational tool for eQTL studies that exploit the rich structural information among expression traits due to correlation, regulation, or other forms of biological dependencies.

Modeling the interaction of biological cells with a solidifying interface

NASA Astrophysics Data System (ADS)

Chang, Anthony; Dantzig, Jonathan A.; Darr, Brian T.; Hubel, Allison

2007-10-01

In this article, we develop a modified level set method for modeling the interaction of particles with a solidifying interface. The dynamic computation of the van der Waals and drag forces between the particles and the solidification front leads to a problem of multiple length scales, which we resolve using adaptive grid techniques. We present a variety of example problems to demonstrate the accuracy and utility of the method. We also use the model to interpret experimental results obtained using directional solidification in a cryomicroscope.

Do Sophisticated Epistemic Beliefs Predict Meaningful Learning? Findings from a Structural Equation Model of Undergraduate Biology Learning

ERIC Educational Resources Information Center

Lee, Silvia Wen-Yu; Liang, Jyh-Chong; Tsai, Chin-Chung

2016-01-01

This study investigated the relationships among college students' epistemic beliefs in biology (EBB), conceptions of learning biology (COLB), and strategies of learning biology (SLB). EBB includes four dimensions, namely "multiple-source," "uncertainty," "development," and "justification." COLB is further…

Integrated pipeline for mass spectrometry-based discovery and confirmation of biomarkers demonstrated in a mouse model of breast cancer.

PubMed

Whiteaker, Jeffrey R; Zhang, Heidi; Zhao, Lei; Wang, Pei; Kelly-Spratt, Karen S; Ivey, Richard G; Piening, Brian D; Feng, Li-Chia; Kasarda, Erik; Gurley, Kay E; Eng, Jimmy K; Chodosh, Lewis A; Kemp, Christopher J; McIntosh, Martin W; Paulovich, Amanda G

2007-10-01

Despite their potential to impact diagnosis and treatment of cancer, few protein biomarkers are in clinical use. Biomarker discovery is plagued with difficulties ranging from technological (inability to globally interrogate proteomes) to biological (genetic and environmental differences among patients and their tumors). We urgently need paradigms for biomarker discovery. To minimize biological variation and facilitate testing of proteomic approaches, we employed a mouse model of breast cancer. Specifically, we performed LC-MS/MS of tumor and normal mammary tissue from a conditional HER2/Neu-driven mouse model of breast cancer, identifying 6758 peptides representing >700 proteins. We developed a novel statistical approach (SASPECT) for prioritizing proteins differentially represented in LC-MS/MS datasets and identified proteins over- or under-represented in tumors. Using a combination of antibody-based approaches and multiple reaction monitoring-mass spectrometry (MRM-MS), we confirmed the overproduction of multiple proteins at the tissue level, identified fibulin-2 as a plasma biomarker, and extensively characterized osteopontin as a plasma biomarker capable of early disease detection in the mouse. Our results show that a staged pipeline employing shotgun-based comparative proteomics for biomarker discovery and multiple reaction monitoring for confirmation of biomarker candidates is capable of finding novel tissue and plasma biomarkers in a mouse model of breast cancer. Furthermore, the approach can be extended to find biomarkers relevant to human disease.

Feature generation and representations for protein-protein interaction classification.

PubMed

Lan, Man; Tan, Chew Lim; Su, Jian

2009-10-01

Automatic detecting protein-protein interaction (PPI) relevant articles is a crucial step for large-scale biological database curation. The previous work adopted POS tagging, shallow parsing and sentence splitting techniques, but they achieved worse performance than the simple bag-of-words representation. In this paper, we generated and investigated multiple types of feature representations in order to further improve the performance of PPI text classification task. Besides the traditional domain-independent bag-of-words approach and the term weighting methods, we also explored other domain-dependent features, i.e. protein-protein interaction trigger keywords, protein named entities and the advanced ways of incorporating Natural Language Processing (NLP) output. The integration of these multiple features has been evaluated on the BioCreAtIvE II corpus. The experimental results showed that both the advanced way of using NLP output and the integration of bag-of-words and NLP output improved the performance of text classification. Specifically, in comparison with the best performance achieved in the BioCreAtIvE II IAS, the feature-level and classifier-level integration of multiple features improved the performance of classification 2.71% and 3.95%, respectively.

Incorporation of multiple cloud layers for ultraviolet radiation modeling studies

NASA Technical Reports Server (NTRS)

Charache, Darryl H.; Abreu, Vincent J.; Kuhn, William R.; Skinner, Wilbert R.

1994-01-01

Cloud data sets compiled from surface observations were used to develop an algorithm for incorporating multiple cloud layers into a multiple-scattering radiative transfer model. Aerosol extinction and ozone data sets were also incorporated to estimate the seasonally averaged ultraviolet (UV) flux reaching the surface of the Earth in the Detroit, Michigan, region for the years 1979-1991, corresponding to Total Ozone Mapping Spectrometer (TOMS) version 6 ozone observations. The calculated UV spectrum was convolved with an erythema action spectrum to estimate the effective biological exposure for erythema. Calculations show that decreasing the total column density of ozone by 1% leads to an increase in erythemal exposure by approximately 1.1-1.3%, in good agreement with previous studies. A comparison of the UV radiation budget at the surface between a single cloud layer method and a multiple cloud layer method presented here is discussed, along with limitations of each technique. With improved parameterization of cloud properties, and as knowledge of biological effects of UV exposure increase, inclusion of multiple cloud layers may be important in accurately determining the biologically effective UV budget at the surface of the Earth.

Upper Secondary Students' Understanding of the Use of Multiple Models in Biology Textbooks--The Importance of Conceptual Variation and Incommensurability

ERIC Educational Resources Information Center

Gericke, Niklas; Hagberg, Mariana; Jorde, Doris

2013-01-01

In this study we investigate students' ability to discern conceptual variation and the use of multiple models in genetics when reading content-specific excerpts from biology textbooks. Using the history and philosophy of science as our reference, we were able to develop a research instrument allowing students themselves to investigate the…

The function of multiple ejaculations in bitterling.

PubMed

Smith, C; Warren, M; Rouchet, R; Reichard, M

2014-09-01

In some taxa, males perform multiple ejaculations, which may function in sperm competition or in maintaining a baseline density of spermatozoa in the female reproductive tract to ensure fertilization, a process that has been termed 'topping up'. We investigated the function of multiple ejaculations in two species of bitterling, the European bitterling (Rhodeus amarus) and Chinese rose bitterling (Rhodeus ocellatus). Bitterling oviposit in living freshwater mussels, with fertilization taking place within the mussel gill cavity. Thus, although fertilization is external, the mussel is analogous to the female reproductive tract in an internally fertilizing species. We measured the frequency of ejaculations and mussel inspections by individual males of two bitterling species in 28 replicated mesocosms and examined focal male responses to rival ejaculations and the presence of females in spawning condition. We used a model of ejaculatory behaviour to simulate the temporal abundance of spermatozoa in mussels. Male R. amarus exhibited high rates of ejaculation and inspection of the siphons of mussels and increased their ejaculation rate in response to the presence of females in spawning condition. Rhodeus ocellatus showed lower overall rates of ejaculation, but significantly elevated ejaculation rate in response to rival ejaculations. The ejaculatory strategy of R. amarus is one that maintains a minimum level of spermatozoa in mussels, which is elevated when the probability of oviposition increases. In contrast, R. ocellatus engages more directly in sperm competition with rivals. We discuss these results in the context of the function of multiple ejaculations and male mating tactics. © 2014 The Authors. Journal of Evolutionary Biology © 2014 European Society For Evolutionary Biology.

Systems and precision medicine approaches to diabetes heterogeneity: a Big Data perspective.

PubMed

Capobianco, Enrico

2017-12-01

Big Data, and in particular Electronic Health Records, provide the medical community with a great opportunity to analyze multiple pathological conditions at an unprecedented depth for many complex diseases, including diabetes. How can we infer on diabetes from large heterogeneous datasets? A possible solution is provided by invoking next-generation computational methods and data analytics tools within systems medicine approaches. By deciphering the multi-faceted complexity of biological systems, the potential of emerging diagnostic tools and therapeutic functions can be ultimately revealed. In diabetes, a multidimensional approach to data analysis is needed to better understand the disease conditions, trajectories and the associated comorbidities. Elucidation of multidimensionality comes from the analysis of factors such as disease phenotypes, marker types, and biological motifs while seeking to make use of multiple levels of information including genetics, omics, clinical data, and environmental and lifestyle factors. Examining the synergy between multiple dimensions represents a challenge. In such regard, the role of Big Data fuels the rise of Precision Medicine by allowing an increasing number of descriptions to be captured from individuals. Thus, data curations and analyses should be designed to deliver highly accurate predicted risk profiles and treatment recommendations. It is important to establish linkages between systems and precision medicine in order to translate their principles into clinical practice. Equivalently, to realize their full potential, the involved multiple dimensions must be able to process information ensuring inter-exchange, reducing ambiguities and redundancies, and ultimately improving health care solutions by introducing clinical decision support systems focused on reclassified phenotypes (or digital biomarkers) and community-driven patient stratifications.

Pathogenesis-related proteins and peptides as promising tools for engineering plants with multiple stress tolerance.

PubMed

Ali, Sajad; Ganai, Bashir Ahmad; Kamili, Azra N; Bhat, Ajaz Ali; Mir, Zahoor Ahmad; Bhat, Javaid Akhter; Tyagi, Anshika; Islam, Sheikh Tajamul; Mushtaq, Muntazir; Yadav, Prashant; Rawat, Sandhya; Grover, Anita

Pathogenesis-related (PR) proteins and antimicrobial peptides (AMPs) are a group of diverse molecules that are induced by phytopathogens as well as defense related signaling molecules. They are the key components of plant innate immune system especially systemic acquired resistance (SAR), and are widely used as diagnostic molecular markers of defense signaling pathways. Although, PR proteins and peptides have been isolated much before but their biological function remains largely enigmatic despite the availability of new scientific tools. The earlier studies have demonstrated that PR genes provide enhanced resistance against both biotic and abiotic stresses, which make them one of the most promising candidates for developing multiple stress tolerant crop varieties. In this regard, plant genetic engineering technology is widely accepted as one of the most fascinating approach to develop the disease resistant transgenic crops using different antimicrobial genes like PR genes. Overexpression of PR genes (chitinase, glucanase, thaumatin, defensin and thionin) individually or in combination have greatly uplifted the level of defense response in plants against a wide range of pathogens. However, the detailed knowledge of signaling pathways that regulates the expression of these versatile proteins is critical for improving crop plants to multiple stresses, which is the future theme of plant stress biology. Hence, this review provides an overall overview on the PR proteins like their classification, role in multiple stresses (biotic and abiotic) as well as in various plant defense signaling cascades. We also highlight the success and snags of transgenic plants expressing PR proteins and peptides. Copyright © 2018 Elsevier GmbH. All rights reserved.

Network-based drug discovery by integrating systems biology and computational technologies

PubMed Central

Leung, Elaine L.; Cao, Zhi-Wei; Jiang, Zhi-Hong; Zhou, Hua

2013-01-01

Network-based intervention has been a trend of curing systemic diseases, but it relies on regimen optimization and valid multi-target actions of the drugs. The complex multi-component nature of medicinal herbs may serve as valuable resources for network-based multi-target drug discovery due to its potential treatment effects by synergy. Recently, robustness of multiple systems biology platforms shows powerful to uncover molecular mechanisms and connections between the drugs and their targeting dynamic network. However, optimization methods of drug combination are insufficient, owning to lacking of tighter integration across multiple ‘-omics’ databases. The newly developed algorithm- or network-based computational models can tightly integrate ‘-omics’ databases and optimize combinational regimens of drug development, which encourage using medicinal herbs to develop into new wave of network-based multi-target drugs. However, challenges on further integration across the databases of medicinal herbs with multiple system biology platforms for multi-target drug optimization remain to the uncertain reliability of individual data sets, width and depth and degree of standardization of herbal medicine. Standardization of the methodology and terminology of multiple system biology and herbal database would facilitate the integration. Enhance public accessible databases and the number of research using system biology platform on herbal medicine would be helpful. Further integration across various ‘-omics’ platforms and computational tools would accelerate development of network-based drug discovery and network medicine. PMID:22877768

Exogenous hydrogen sulfide exerts proliferation, anti-apoptosis, migration effects and accelerates cell cycle progression in multiple myeloma cells via activating the Akt pathway.

PubMed

Zheng, Dong; Chen, Ziang; Chen, Jingfu; Zhuang, Xiaomin; Feng, Jianqiang; Li, Juan

2016-10-01

Hydrogen sulfide (H2S), regarded as the third gaseous transmitter, mediates and induces various biological effects. The present study investigated the effects of H2S on multiple myeloma cell progression via amplifying the activation of Akt pathway in multiple myeloma cells. The level of H2S produced in multiple myeloma (MM) patients and healthy subjects was measured using enzyme-linked immunosorbent assay (ELISA). MM cells were treated with 500 µmol/l NaHS (a donor of H2S) for 24 h. The expression levels of phosphorylated-Akt (p-Akt), Bcl-2 and caspase-3 were measured by western blot assay. Cell viability was detected by Cell Counting Kit 8 (CCK-8). The cell cycle was analyzed by flow cytometry. Our results show that the concentration of H2S was higher in MM patients and that it increased in parallel with disease progression. Treating MM cells with 500 µmol/l NaHS for 24 h markedly increased the expression level of Bcl-2 and the activation of p-Akt, however, the expression level of caspase-3 was decreased, cell viability was increased, and cell cycle progression was accelerated in MM cells. NaHS also induced migration in MM cells in transwell migration assay. Furthermore, co-treatment of MM cells with 500 µmol/l NaHS and 50 µmol/l LY294002 for 24 h significantly overset these effects. In conclusion, our findings demonstrate that the Akt pathway contributes to NaHS-induced cell proliferation, migration and acceleration of cell cycle progression in MM cells.

Moving beyond a descriptive aquatic toxicology: the value of biological process and trait information.

PubMed

Segner, Helmut

2011-10-01

In order to improve the ability to link chemical exposure to toxicological and ecological effects, aquatic toxicology will have to move from observing what chemical concentrations induce adverse effects to more explanatory approaches, that are concepts which build on knowledge of biological processes and pathways leading from exposure to adverse effects, as well as on knowledge on stressor vulnerability as given by the genetic, physiological and ecological (e.g., life history) traits of biota. Developing aquatic toxicology in this direction faces a number of challenges, including (i) taking into account species differences in toxicant responses on the basis of the evolutionarily developed diversity of phenotypic vulnerability to environmental stressors, (ii) utilizing diversified biological response profiles to serve as biological read across for prioritizing chemicals, categorizing them according to modes of action, and for guiding targeted toxicity evaluation; (iii) prediction of ecological consequences of toxic exposure from knowledge of how biological processes and phenotypic traits lead to effect propagation across the levels of biological hierarchy; and (iv) the search for concepts to assess the cumulative impact of multiple stressors. An underlying theme in these challenges is that, in addition to the question of what the chemical does to the biological receptor, we should give increasing emphasis to the question how the biological receptor handles the chemicals, i.e., through which pathways the initial chemical-biological interaction extends to the adverse effects, how this extension is modulated by adaptive or compensatory processes as well as by phenotypic traits of the biological receptor. 2011 Elsevier B.V. All rights reserved.

Integrated multiscale biomaterials experiment and modelling: a perspective

PubMed Central

Buehler, Markus J.; Genin, Guy M.

2016-01-01

Advances in multiscale models and computational power have enabled a broad toolset to predict how molecules, cells, tissues and organs behave and develop. A key theme in biological systems is the emergence of macroscale behaviour from collective behaviours across a range of length and timescales, and a key element of these models is therefore hierarchical simulation. However, this predictive capacity has far outstripped our ability to validate predictions experimentally, particularly when multiple hierarchical levels are involved. The state of the art represents careful integration of multiscale experiment and modelling, and yields not only validation, but also insights into deformation and relaxation mechanisms across scales. We present here a sampling of key results that highlight both challenges and opportunities for integrated multiscale experiment and modelling in biological systems. PMID:28981126

Multiscale mechanobiology: computational models for integrating molecules to multicellular systems

PubMed Central

Mak, Michael; Kim, Taeyoon

2015-01-01

Mechanical signals exist throughout the biological landscape. Across all scales, these signals, in the form of force, stiffness, and deformations, are generated and processed, resulting in an active mechanobiological circuit that controls many fundamental aspects of life, from protein unfolding and cytoskeletal remodeling to collective cell motions. The multiple scales and complex feedback involved present a challenge for fully understanding the nature of this circuit, particularly in development and disease in which it has been implicated. Computational models that accurately predict and are based on experimental data enable a means to integrate basic principles and explore fine details of mechanosensing and mechanotransduction in and across all levels of biological systems. Here we review recent advances in these models along with supporting and emerging experimental findings. PMID:26019013

Use of Graph Database for the Integration of Heterogeneous Biological Data.

PubMed

Yoon, Byoung-Ha; Kim, Seon-Kyu; Kim, Seon-Young

2017-03-01

Understanding complex relationships among heterogeneous biological data is one of the fundamental goals in biology. In most cases, diverse biological data are stored in relational databases, such as MySQL and Oracle, which store data in multiple tables and then infer relationships by multiple-join statements. Recently, a new type of database, called the graph-based database, was developed to natively represent various kinds of complex relationships, and it is widely used among computer science communities and IT industries. Here, we demonstrate the feasibility of using a graph-based database for complex biological relationships by comparing the performance between MySQL and Neo4j, one of the most widely used graph databases. We collected various biological data (protein-protein interaction, drug-target, gene-disease, etc.) from several existing sources, removed duplicate and redundant data, and finally constructed a graph database containing 114,550 nodes and 82,674,321 relationships. When we tested the query execution performance of MySQL versus Neo4j, we found that Neo4j outperformed MySQL in all cases. While Neo4j exhibited a very fast response for various queries, MySQL exhibited latent or unfinished responses for complex queries with multiple-join statements. These results show that using graph-based databases, such as Neo4j, is an efficient way to store complex biological relationships. Moreover, querying a graph database in diverse ways has the potential to reveal novel relationships among heterogeneous biological data.

Use of Graph Database for the Integration of Heterogeneous Biological Data

PubMed Central

Yoon, Byoung-Ha; Kim, Seon-Kyu

2017-01-01

Understanding complex relationships among heterogeneous biological data is one of the fundamental goals in biology. In most cases, diverse biological data are stored in relational databases, such as MySQL and Oracle, which store data in multiple tables and then infer relationships by multiple-join statements. Recently, a new type of database, called the graph-based database, was developed to natively represent various kinds of complex relationships, and it is widely used among computer science communities and IT industries. Here, we demonstrate the feasibility of using a graph-based database for complex biological relationships by comparing the performance between MySQL and Neo4j, one of the most widely used graph databases. We collected various biological data (protein-protein interaction, drug-target, gene-disease, etc.) from several existing sources, removed duplicate and redundant data, and finally constructed a graph database containing 114,550 nodes and 82,674,321 relationships. When we tested the query execution performance of MySQL versus Neo4j, we found that Neo4j outperformed MySQL in all cases. While Neo4j exhibited a very fast response for various queries, MySQL exhibited latent or unfinished responses for complex queries with multiple-join statements. These results show that using graph-based databases, such as Neo4j, is an efficient way to store complex biological relationships. Moreover, querying a graph database in diverse ways has the potential to reveal novel relationships among heterogeneous biological data. PMID:28416946

Individual and Neighborhood Stressors, Air Pollution and Cardiovascular Disease.

PubMed

Hazlehurst, Marnie F; Nurius, Paula S; Hajat, Anjum

2018-03-08

Psychosocial and environmental stress exposures across the life course have been shown to be relevant in the development of cardiovascular disease (CVD). Assessing more than one stressor from different domains (e.g., individual and neighborhood) and across the life course moves us towards a more integrated picture of how stress affects health and well-being. Furthermore, these individual and neighborhood psychosocial stressors act on biologic pathways, including immune function and inflammatory response, which are also impacted by ubiquitous environmental exposures such as air pollution. The objective of this study is to evaluate the interaction between psychosocial stressors, at both the individual and neighborhood level, and air pollution on CVD. This study used data from the 2009-2011 Behavioral Risk Factor Surveillance System (BRFSS) from Washington State. Adverse childhood experiences (ACEs) measured at the individual level, and neighborhood deprivation index (NDI) measured at the zip code level, were the psychosocial stressors of interest. Exposures to three air pollutants-particulate matter (both PM 2.5 and PM 10 ) and nitrogen dioxide (NO₂)-were also calculated at the zip code level. Outcome measures included several self-reported CVD-related health conditions. Both multiplicative and additive interaction quantified using the relative excess risk due to interaction (RERI), were evaluated. This study included 32,151 participants in 502 unique zip codes. Multiplicative and positive additive interactions were observed between ACEs and PM 10 for diabetes, in models adjusted for NDI. The prevalence of diabetes was 1.58 (95% CI: 1.40, 1.79) times higher among those with both high ACEs and high PM 10 compared to those with low ACEs and low PM 10 ( p -value = 0.04 for interaction on the multiplicative scale). Interaction was also observed between neighborhood-level stressors (NDI) and air pollution (NO₂) for the stroke and diabetes outcomes on both multiplicative and additive scales. Modest interaction was observed between NDI and air pollution, supporting prior literature on the importance of neighborhood-level stressors in cardiovascular health and reinforcing the importance of NDI on air pollution health effects. ACEs may exert health effects through selection into disadvantaged neighborhoods and more work is needed to understand the accumulation of risk in multiple domains across the life course.

Water hyacinths for upgrading sewage lagoons to meet advanced wastewater treatment standards, part 2

NASA Technical Reports Server (NTRS)

Wolverton, B. C.; Mcdonald, R. C.

1976-01-01

Field tests using water hyacinths as biological filtration agents were conducted in the Mississippi gulf coast region. The plants were installed in one single cell and one multiple cell sewage lagoon systems. Water hyacinths demonstrated the ability to maintain BOD5 and total suspended solid (TSS) levels within the Environmental Protection Agency's prescribed limits of 30 mg/lBOD5 and 30 mg/l TSS. A multiple cell sewage lagoon system consisting of two aerated and one water hyacinth covered cell connected in series demonstrated the ability to maintain BOD5 and TSS levels below 30 mg/l year-round. A water hyacinth covered lagoon with a surface area of 0.28 hectare containing a total volume of 6.8 million liters demonstrated the capacity to treat 437,000 to 1,893,000 liters of sewage influent from 2.65 hectares of aerated lagoons daily and produce an effluent that met or exceeded standards year-round.

Challenges and Opportunities in Mining Neuroscience Data

PubMed Central

Akil, Huda; Martone, Maryann E.; Van Essen, David C.

2011-01-01

Understanding the brain requires a broad range of approaches and methods from the domains of biology, psychology, chemistry, physics, and mathematics. The fundamental challenge is to decipher the “neural choreography” associated with complex behaviors and functions, including thoughts, memories, actions, and emotions. This demands the acquisition and integration of vast amounts of data of many types, at multiple scales in time and in space. Here, we discuss the need for neuroinformatics approaches to accelerate progress, using several illustrative examples. The nascent field of ‘connectomics’ aims to comprehensively describe neuronal connectivity at either a macroscopic level (long-distance pathways for the entire brain) or a microscopic level (axons, dendrites, synapses in a small brain region). The Neuroscience Information Framework encompasses all of neuroscience and facilitates integration of existing knowledge and databases of many types. These examples illustrate the opportunities and challenges of data mining across multiple tiers of neuroscience information and underscore the need for cultural and infrastructure changes if neuroinformatics is to fulfill its potential to advance our understanding of the brain. PMID:21311009

The South Georgia and the South Sandwich Islands MPA: protecting a biodiverse oceanic island chain situated in the flow of the antarctic circumpolar current.

PubMed

Trathan, Philip N; Collins, Martin A; Grant, Susie M; Belchier, Mark; Barnes, David K A; Brown, Judith; Staniland, Iain J

2014-01-01

South Georgia and the South Sandwich Islands (SGSSI) are surrounded by oceans that are species-rich, have high levels of biodiversity, important endemism and which also support large aggregations of charismatic upper trophic level species. Spatial management around these islands is complex, particularly in the context of commercial fisheries that exploit some of these living resources. Furthermore, management is especially complicated as local productivity relies fundamentally upon biological production transported from outside the area. The MPA uses practical management boundaries, allowing access for the current legal fisheries for Patagonian toothfish, mackerel icefish and Antarctic krill. Management measures developed as part of the planning process designated the whole SGSSI Maritime Zone as an IUCN Category VI reserve, within which a number of IUCN Category I reserves were identified. Multiple-use zones and temporal closures were also designated. A key multiple-use principle was to identify whether the ecological impacts of a particular fishery threatened either the pelagic or benthic domain.

Designed multiple ligands in metabolic disease research: from concept to platform.

PubMed

Gattrell, W; Johnstone, C; Patel, S; Smith, C Sambrook; Scheel, A; Schindler, M

2013-08-01

Type 2 diabetes mellitus (T2DM) is a multifactorial disease, and drug monotherapy typically results in unsatisfactory treatment outcomes for patients. Even when used in combination, existing therapies lack efficacy in the long term. Designed multiple ligands (DMLs) are compounds developed to modulate multiple targets relevant to a disease. DMLs offer the potential to yield greater efficacy over monotherapies, either by modulating different biological pathways, or by boosting a single one. However, examples of DMLs progressing into clinical trials, or onto the market are rare; DML drug discovery is challenging, and perceived by some to be almost impossible. Nevertheless, with the judicious selection of biological targets, both from a biological and chemical perspective, it is possible to develop drug-like DMLs. Copyright © 2013 Elsevier Ltd. All rights reserved.

Non-redundant patent sequence databases with value-added annotations at two levels

PubMed Central

Li, Weizhong; McWilliam, Hamish; de la Torre, Ana Richart; Grodowski, Adam; Benediktovich, Irina; Goujon, Mickael; Nauche, Stephane; Lopez, Rodrigo

2010-01-01

The European Bioinformatics Institute (EMBL-EBI) provides public access to patent data, including abstracts, chemical compounds and sequences. Sequences can appear multiple times due to the filing of the same invention with multiple patent offices, or the use of the same sequence by different inventors in different contexts. Information relating to the source invention may be incomplete, and biological information available in patent documents elsewhere may not be reflected in the annotation of the sequence. Search and analysis of these data have become increasingly challenging for both the scientific and intellectual-property communities. Here, we report a collection of non-redundant patent sequence databases, which cover the EMBL-Bank nucleotides patent class and the patent protein databases and contain value-added annotations from patent documents. The databases were created at two levels by the use of sequence MD5 checksums. Sequences within a level-1 cluster are 100% identical over their whole length. Level-2 clusters were defined by sub-grouping level-1 clusters based on patent family information. Value-added annotations, such as publication number corrections, earliest publication dates and feature collations, significantly enhance the quality of the data, allowing for better tracking and cross-referencing. The databases are available format: http://www.ebi.ac.uk/patentdata/nr/. PMID:19884134

Non-redundant patent sequence databases with value-added annotations at two levels.

PubMed

Li, Weizhong; McWilliam, Hamish; de la Torre, Ana Richart; Grodowski, Adam; Benediktovich, Irina; Goujon, Mickael; Nauche, Stephane; Lopez, Rodrigo

2010-01-01

The European Bioinformatics Institute (EMBL-EBI) provides public access to patent data, including abstracts, chemical compounds and sequences. Sequences can appear multiple times due to the filing of the same invention with multiple patent offices, or the use of the same sequence by different inventors in different contexts. Information relating to the source invention may be incomplete, and biological information available in patent documents elsewhere may not be reflected in the annotation of the sequence. Search and analysis of these data have become increasingly challenging for both the scientific and intellectual-property communities. Here, we report a collection of non-redundant patent sequence databases, which cover the EMBL-Bank nucleotides patent class and the patent protein databases and contain value-added annotations from patent documents. The databases were created at two levels by the use of sequence MD5 checksums. Sequences within a level-1 cluster are 100% identical over their whole length. Level-2 clusters were defined by sub-grouping level-1 clusters based on patent family information. Value-added annotations, such as publication number corrections, earliest publication dates and feature collations, significantly enhance the quality of the data, allowing for better tracking and cross-referencing. The databases are available format: http://www.ebi.ac.uk/patentdata/nr/.

Imaging and the new biology: What's wrong with this picture?

NASA Astrophysics Data System (ADS)

Vannier, Michael W.

2004-05-01

The Human Genome has been defined, giving us one part of the equation that stems from the central dogma of molecular biology. Despite this awesome scientific achievement, the correspondence between genomics and imaging is weak, since we cannot predict an organism's phenotype from even perfect knowledge of its genetic complement. Biological knowledge comes in several forms, and the genome is perhaps the best known and most completely understood type. Imaging creates another form of biological information, providing the ability to study morphology, growth and development, metabolic processes, and diseases in vitro and in vivo at many levels of scale. The principal challenge in biomedical imaging for the future lies in the need to reconcile the data provided by one or multiple modalities with other forms of biological knowledge, most importantly the genome, proteome, physiome, and other "-ome's." To date, the imaging science community has not set a high priority on the unification of their results with genomics, proteomics, and physiological functions in most published work. Images are relatively isolated from other forms of biological data, impairing our ability to conceive and address many fundamental questions in research and clinical practice. This presentation will explain the challenge of biological knowledge integration in basic research and clinical applications from the standpoint of imaging and image processing. The impediments to progress, isolation of the imaging community, and mainstream of new and future biological science will be identified, so the critical and immediate need for change can be highlighted.

Optimal design of compact and connected nature reserves for multiple species.

PubMed

Wang, Yicheng; Önal, Hayri

2016-04-01

When designing a conservation reserve system for multiple species, spatial attributes of the reserves must be taken into account at species level. The existing optimal reserve design literature considers either one spatial attribute or when multiple attributes are considered the analysis is restricted only to one species. We built a linear integer programing model that incorporates compactness and connectivity of the landscape reserved for multiple species. The model identifies multiple reserves that each serve a subset of target species with a specified coverage probability threshold to ensure the species' long-term survival in the reserve, and each target species is covered (protected) with another probability threshold at the reserve system level. We modeled compactness by minimizing the total distance between selected sites and central sites, and we modeled connectivity of a selected site to its designated central site by selecting at least one of its adjacent sites that has a nearer distance to the central site. We considered structural distance and functional distances that incorporated site quality between sites. We tested the model using randomly generated data on 2 species, one ground species that required structural connectivity and the other an avian species that required functional connectivity. We applied the model to 10 bird species listed as endangered by the state of Illinois (U.S.A.). Spatial coherence and selection cost of the reserves differed substantially depending on the weights assigned to these 2 criteria. The model can be used to design a reserve system for multiple species, especially species whose habitats are far apart in which case multiple disjunct but compact and connected reserves are advantageous. The model can be modified to increase or decrease the distance between reserves to reduce or promote population connectivity. © 2015 Society for Conservation Biology.

Programmable chemical controllers made from DNA.

PubMed

Chen, Yuan-Jyue; Dalchau, Neil; Srinivas, Niranjan; Phillips, Andrew; Cardelli, Luca; Soloveichik, David; Seelig, Georg

2013-10-01

Biological organisms use complex molecular networks to navigate their environment and regulate their internal state. The development of synthetic systems with similar capabilities could lead to applications such as smart therapeutics or fabrication methods based on self-organization. To achieve this, molecular control circuits need to be engineered to perform integrated sensing, computation and actuation. Here we report a DNA-based technology for implementing the computational core of such controllers. We use the formalism of chemical reaction networks as a 'programming language' and our DNA architecture can, in principle, implement any behaviour that can be mathematically expressed as such. Unlike logic circuits, our formulation naturally allows complex signal processing of intrinsically analogue biological and chemical inputs. Controller components can be derived from biologically synthesized (plasmid) DNA, which reduces errors associated with chemically synthesized DNA. We implement several building-block reaction types and then combine them into a network that realizes, at the molecular level, an algorithm used in distributed control systems for achieving consensus between multiple agents.

Structure and formation of ant transportation networks

PubMed Central

Latty, Tanya; Ramsch, Kai; Ito, Kentaro; Nakagaki, Toshiyuki; Sumpter, David J. T.; Middendorf, Martin; Beekman, Madeleine

2011-01-01

Many biological systems use extensive networks for the transport of resources and information. Ants are no exception. How do biological systems achieve efficient transportation networks in the absence of centralized control and without global knowledge of the environment? Here, we address this question by studying the formation and properties of inter-nest transportation networks in the Argentine ant (Linepithema humile). We find that the formation of inter-nest networks depends on the number of ants involved in the construction process. When the number of ants is sufficient and networks do form, they tend to have short total length but a low level of robustness. These networks are topologically similar to either minimum spanning trees or Steiner networks. The process of network formation involves an initial construction of multiple links followed by a pruning process that reduces the number of trails. Our study thus illuminates the conditions under and the process by which minimal biological transport networks can be constructed. PMID:21288958

Decoding the Heart through Next Generation Sequencing Approaches.

PubMed

Pawlak, Michal; Niescierowicz, Katarzyna; Winata, Cecilia Lanny

2018-06-07

: Vertebrate organs develop through a complex process which involves interaction between multiple signaling pathways at the molecular, cell, and tissue levels. Heart development is an example of such complex process which, when disrupted, results in congenital heart disease (CHD). This complexity necessitates a holistic approach which allows the visualization of genome-wide interaction networks, as opposed to assessment of limited subsets of factors. Genomics offers a powerful solution to address the problem of biological complexity by enabling the observation of molecular processes at a genome-wide scale. The emergence of next generation sequencing (NGS) technology has facilitated the expansion of genomics, increasing its output capacity and applicability in various biological disciplines. The application of NGS in various aspects of heart biology has resulted in new discoveries, generating novel insights into this field of study. Here we review the contributions of NGS technology into the understanding of heart development and its disruption reflected in CHD and discuss how emerging NGS based methodologies can contribute to the further understanding of heart repair.

Programmable chemical controllers made from DNA

NASA Astrophysics Data System (ADS)

Chen, Yuan-Jyue; Dalchau, Neil; Srinivas, Niranjan; Phillips, Andrew; Cardelli, Luca; Soloveichik, David; Seelig, Georg

2013-10-01

Biological organisms use complex molecular networks to navigate their environment and regulate their internal state. The development of synthetic systems with similar capabilities could lead to applications such as smart therapeutics or fabrication methods based on self-organization. To achieve this, molecular control circuits need to be engineered to perform integrated sensing, computation and actuation. Here we report a DNA-based technology for implementing the computational core of such controllers. We use the formalism of chemical reaction networks as a 'programming language' and our DNA architecture can, in principle, implement any behaviour that can be mathematically expressed as such. Unlike logic circuits, our formulation naturally allows complex signal processing of intrinsically analogue biological and chemical inputs. Controller components can be derived from biologically synthesized (plasmid) DNA, which reduces errors associated with chemically synthesized DNA. We implement several building-block reaction types and then combine them into a network that realizes, at the molecular level, an algorithm used in distributed control systems for achieving consensus between multiple agents.

[Human reproduction and environmental risk factors].

PubMed

Petrelli, G; Mantovani, A; Menditto, A

1999-01-01

Environmental pollution is a great cause of concern, in particular, growing attention is being paid to the potential of many chemicals to affect the reproductive system in humans. The key role of prevention and control of reproductive hazards is recognized world-wide. Many chemicals have been shown to impair fertility and/or prenatal and perinatal development in experimental studies. However, a sufficient evidence of an effect on human reproduction is available for some compounds only. The use of biological markers may improve the assessment of exposure to chemicals, contribute to identify mechanisms of action and put into evidence early, reversible, biological effects. Valid biological markers are also needed in epidemiological studies: without reliable data on the level of current and past exposures it is difficult to establish a causal relationship between a pollutant and the occurrence of adverse health effects. A multidisciplinary approach to risk assessment is required. Priorities for interdisciplinary research on environmental chemicals and reproduction include the identification of susceptible population subgroups and risk assessment of exposure to multiple chemicals.

Universal nucleic acids sample preparation method for cells, spores and their mixture

DOEpatents

Bavykin, Sergei [Darien, IL

2011-01-18

The present invention relates to a method for extracting nucleic acids from biological samples. More specifically the invention relates to a universal method for extracting nucleic acids from unidentified biological samples. An advantage of the presently invented method is its ability to effectively and efficiently extract nucleic acids from a variety of different cell types including but not limited to prokaryotic or eukaryotic cells and/or recalcitrant organisms (i.e. spores). Unlike prior art methods which are focused on extracting nucleic acids from vegetative cell or spores, the present invention effectively extracts nucleic acids from spores, multiple cell types or mixtures thereof using a single method. Important that the invented method has demonstrated an ability to extract nucleic acids from spores and vegetative bacterial cells with similar levels effectiveness. The invented method employs a multi-step protocol which erodes the cell structure of the biological sample, isolates, labels, fragments nucleic acids and purifies labeled samples from the excess of dye.

Programmable chemical controllers made from DNA

PubMed Central

Chen, Yuan-Jyue; Dalchau, Neil; Srinivas, Niranjan; Phillips, Andrew; Cardelli, Luca; Soloveichik, David; Seelig, Georg

2014-01-01

Biological organisms use complex molecular networks to navigate their environment and regulate their internal state. The development of synthetic systems with similar capabilities could lead to applications such as smart therapeutics or fabrication methods based on self-organization. To achieve this, molecular control circuits need to be engineered to perform integrated sensing, computation and actuation. Here we report a DNA-based technology for implementing the computational core of such controllers. We use the formalism of chemical reaction networks as a 'programming language', and our DNA architecture can, in principle, implement any behaviour that can be mathematically expressed as such. Unlike logic circuits, our formulation naturally allows complex signal processing of intrinsically analogue biological and chemical inputs. Controller components can be derived from biologically synthesized (plasmid) DNA, which reduces errors associated with chemically synthesized DNA. We implement several building-block reaction types and then combine them into a network that realizes, at the molecular level, an algorithm used in distributed control systems for achieving consensus between multiple agents. PMID:24077029

Practicing safe cell culture: applied process designs for minimizing virus contamination risk.

PubMed

Kiss, Robert D

2011-01-01

CONFERENCE PROCEEDING Proceedings of the PDA/FDA Adventitious Viruses in Biologics: Detection and Mitigation Strategies Workshop in Bethesda, MD, USA; December 1-3, 2010 Guest Editors: Arifa Khan (Bethesda, MD), Patricia Hughes (Bethesda, MD) and Michael Wiebe (San Francisco, CA) Genentech responded to a virus contamination in its biologics manufacturing facility by developing and implementing a series of barriers specifically designed to prevent recurrence of this significant and impactful event. The barriers included steps to inactivate or remove potential virus particles from the many raw materials used in cell culture processing. Additionally, analytical testing barriers provided protection of the downstream processing areas should a culture contamination occur, and robust virus clearance capability provided further assurance of virus safety should a low level contamination go undetected. This conference proceeding will review Genentech's approach, and lessons learned, in minimizing virus contamination risk in cell culture processes through multiple layers of targeted barriers designed to deliver biologics products with high success rates.

Impact of the Invasive Brown Marmorated Stink Bug in North America and Europe: History, Biology, Ecology, and Management.

PubMed

Leskey, Tracy C; Nielsen, Anne L

2018-01-07

The brown marmorated stink bug (BMSB), Halyomorpha halys (Stål), is an invasive pentatomid introduced from Asia into the United States, Canada, multiple European countries, and Chile. In 2010, BMSB populations in the mid-Atlantic United States reached outbreak levels and subsequent feeding severely damaged tree fruit as well as other crops. Significant nuisance issues from adults overwintering inside homes were common. BMSB is a highly polyphagous species with a strong dispersal capacity and high reproductive output, potentially enabling its spread and success in invaded regions. A greater understanding of BMSB biology and ecology and its natural enemies, the identification of the male-produced aggregation pheromone, and the recognition that BMSB disperses into crops from adjacent wooded habitats have led to the development of behavior-based integrated pest management (IPM) tactics. Much is still unknown about BMSB, and continued long-term collaborative studies are necessary to refine crop-specific IPM programs and enhance biological control across invaded landscapes.

MS Sunshine Study: Sun Exposure But Not Vitamin D Is Associated with Multiple Sclerosis Risk in Blacks and Hispanics.

PubMed

Langer-Gould, Annette; Lucas, Robyn; Xiang, Anny H; Chen, Lie H; Wu, Jun; Gonzalez, Edlin; Haraszti, Samantha; Smith, Jessica B; Quach, Hong; Barcellos, Lisa F

2018-02-27

Multiple sclerosis (MS) incidence and serum 25-hydroxyvitamin D (25OHD) levels vary by race/ethnicity. We examined the consistency of beneficial effects of 25OHD and/or sun exposure for MS risk across multiple racial/ethnic groups. We recruited incident MS cases and controls (blacks 116 cases/131 controls; Hispanics 183/197; whites 247/267) from the membership of Kaiser Permanente Southern California into the MS Sunshine Study to simultaneously examine sun exposure and 25OHD, accounting for genetic ancestry and other factors. Higher lifetime ultraviolet radiation exposure (a rigorous measure of sun exposure) was associated with a lower risk of MS independent of serum 25OHD levels in blacks (adjusted OR = 0.53, 95% CI = 0.31-0.83; p = 0.007) and whites (OR = 0.68, 95% CI = 0.48-0.94; p = 0.020) with a similar magnitude of effect that did not reach statistical significance in Hispanics (OR = 0.66, 95% CI = 0.42-1.04; p = 0.071). Higher serum 25OHD levels were associated with a lower risk of MS only in whites. No association was found in Hispanics or blacks regardless of how 25OHD was modeled. Lifetime sun exposure appears to reduce the risk of MS regardless of race/ethnicity. In contrast, serum 25OHD levels are not associated with MS risk in blacks or Hispanics. Our findings challenge the biological plausibility of vitamin D deficiency as causal for MS and call into question the targeting of specific serum 25OHD levels to achieve health benefits, particularly in blacks and Hispanics.

PROMISE: a tool to identify genomic features with a specific biologically interesting pattern of associations with multiple endpoint variables.

PubMed

Pounds, Stan; Cheng, Cheng; Cao, Xueyuan; Crews, Kristine R; Plunkett, William; Gandhi, Varsha; Rubnitz, Jeffrey; Ribeiro, Raul C; Downing, James R; Lamba, Jatinder

2009-08-15

In some applications, prior biological knowledge can be used to define a specific pattern of association of multiple endpoint variables with a genomic variable that is biologically most interesting. However, to our knowledge, there is no statistical procedure designed to detect specific patterns of association with multiple endpoint variables. Projection onto the most interesting statistical evidence (PROMISE) is proposed as a general procedure to identify genomic variables that exhibit a specific biologically interesting pattern of association with multiple endpoint variables. Biological knowledge of the endpoint variables is used to define a vector that represents the biologically most interesting values for statistics that characterize the associations of the endpoint variables with a genomic variable. A test statistic is defined as the dot-product of the vector of the observed association statistics and the vector of the most interesting values of the association statistics. By definition, this test statistic is proportional to the length of the projection of the observed vector of correlations onto the vector of most interesting associations. Statistical significance is determined via permutation. In simulation studies and an example application, PROMISE shows greater statistical power to identify genes with the interesting pattern of associations than classical multivariate procedures, individual endpoint analyses or listing genes that have the pattern of interest and are significant in more than one individual endpoint analysis. Documented R routines are freely available from www.stjuderesearch.org/depts/biostats and will soon be available as a Bioconductor package from www.bioconductor.org.

Bottom-up synthetic biology: modular design for making artificial platelets

NASA Astrophysics Data System (ADS)

Majumder, Sagardip; Liu, Allen P.

2018-01-01

Engineering artificial cells to mimic one or multiple fundamental cell biological functions is an emerging area of synthetic biology. Reconstituting functional modules from biological components in vitro is a challenging yet an important essence of bottom-up synthetic biology. Here we describe the concept of building artificial platelets using bottom-up synthetic biology and the four functional modules that together could enable such an ambitious effort.

Micronuclei related to anti-B[a]PDE-DNA adduct in peripheral blood lymphocytes of heavily polycyclic aromatic hydrocarbon-exposed nonsmoking coke-oven workers and controls.

PubMed

Pavanello, Sofia; Kapka, Lucyna; Siwinska, Ewa; Mielzyñska, Danuta; Bolognesi, Claudia; Clonfero, Erminio

2008-10-01

Micronuclei (MN) frequency associated to biologically effective dose of polycyclic aromatic hydrocarbons [PAH; anti-benzo[a]pyrene diolepoxide (B[a]PDE)-DNA] within the same subjects' peripheral blood lymphocytes (PBL) was evaluated. Study subjects were nonsmoking male Polish coke-oven workers (n=49) and matched controls (n=45) verified for PAH exposure by urinary 1-pyrenol. We found that coke-oven workers, heavily exposed to PAHs (80% workers exceeded the urinary 1-pyrenol biological exposure index value), presented significantly higher MN frequency in PBLs than controls (P<0.01). Substantial difference was also found for adduct levels in PBLs (P<0.01). Increase in MN levels was significantly related to anti-B[a]PDE-DNA formation, key adduct of the ultimate carcinogenic metabolite of B[a]P (n=94; r=0.47; P<0.001). The dose-response relationship was improved when subjects with adduct levels above the 3rd tertile (>or=4.35 adducts/10(8) nucleotides) were excluded (n=61; r=0.69; P<0.001). Saturation of adduct/MN formation at high levels may disturb the underlying relationship. Linear multiple regression analysis, without subjects of 3rd tertile adduct level (n=61), revealed that adduct formation (t=4.61; P<0.001), but not 1-pyrenol, was the significant determinant in increasing MN. In conclusion, the increase in MN frequency is mainly related to the specific anti-B[a]PDE-DNA formation within PBLs of the same subject. Our results substantiate, with the use of an early indicator of biological effect as well, that workers are at higher cancer risk than controls.

Scaling in cognitive performance reflects multiplicative multifractal cascade dynamics

PubMed Central

Stephen, Damian G.; Anastas, Jason R.; Dixon, James A.

2012-01-01

Self-organized criticality purports to build multi-scaled structures out of local interactions. Evidence of scaling in various domains of biology may be more generally understood to reflect multiplicative interactions weaving together many disparate scales. The self-similarity of power-law scaling entails homogeneity: fluctuations distribute themselves similarly across many spatial and temporal scales. However, this apparent homogeneity can be misleading, especially as it spans more scales. Reducing biological processes to one power-law relationship neglects rich cascade dynamics. We review recent research into multifractality in executive-function cognitive tasks and propose that scaling reflects not criticality but instead interactions across multiple scales and among fluctuations of multiple sizes. PMID:22529819

Learning the Cell Structures with Three-Dimensional Models: Students' Achievement by Methods, Type of School and Questions' Cognitive Level

NASA Astrophysics Data System (ADS)

Lazarowitz, Reuven; Naim, Raphael

2013-08-01

The cell topic was taught to 9th-grade students in three modes of instruction: (a) students "hands-on," who constructed three-dimensional cell organelles and macromolecules during the learning process; (b) teacher demonstration of the three-dimensional model of the cell structures; and (c) teaching the cell topic with the regular learning material in an expository mode (which use one- or two-dimensional cell structures as are presented in charts, textbooks and microscopic slides). The sample included 669, 9th-grade students from 25 classes who were taught by 22 Biology teachers. Students were randomly assigned to the three modes of instruction, and two tests in content knowledge in Biology were used. Data were treated with multiple analyses of variance. The results indicate that entry behavior in Biology was equal for all the study groups and types of schools. The "hands-on" learning group who build three-dimensional models through the learning process achieved significantly higher on academic achievements and on the high and low cognitive questions' levels than the other two groups. The study indicates the advantages students may have being actively engaged in the learning process through the "hands-on" mode of instruction/learning.

Synthetic Peptide Arrays for Pathway-Level Protein Monitoring by Liquid Chromatography-Tandem Mass Spectrometry*

PubMed Central

Hewel, Johannes A.; Liu, Jian; Onishi, Kento; Fong, Vincent; Chandran, Shamanta; Olsen, Jonathan B.; Pogoutse, Oxana; Schutkowski, Mike; Wenschuh, Holger; Winkler, Dirk F. H.; Eckler, Larry; Zandstra, Peter W.; Emili, Andrew

2010-01-01

Effective methods to detect and quantify functionally linked regulatory proteins in complex biological samples are essential for investigating mammalian signaling pathways. Traditional immunoassays depend on proprietary reagents that are difficult to generate and multiplex, whereas global proteomic profiling can be tedious and can miss low abundance proteins. Here, we report a target-driven liquid chromatography-tandem mass spectrometry (LC-MS/MS) strategy for selectively examining the levels of multiple low abundance components of signaling pathways which are refractory to standard shotgun screening procedures and hence appear limited in current MS/MS repositories. Our stepwise approach consists of: (i) synthesizing microscale peptide arrays, including heavy isotope-labeled internal standards, for use as high quality references to (ii) build empirically validated high density LC-MS/MS detection assays with a retention time scheduling system that can be used to (iii) identify and quantify endogenous low abundance protein targets in complex biological mixtures with high accuracy by correlation to a spectral database using new software tools. The method offers a flexible, rapid, and cost-effective means for routine proteomic exploration of biological systems including “label-free” quantification, while minimizing spurious interferences. As proof-of-concept, we have examined the abundance of transcription factors and protein kinases mediating pluripotency and self-renewal in embryonic stem cell populations. PMID:20467045

PTEN: Multiple Functions in Human Malignant Tumors.

PubMed

Milella, Michele; Falcone, Italia; Conciatori, Fabiana; Cesta Incani, Ursula; Del Curatolo, Anais; Inzerilli, Nicola; Nuzzo, Carmen M A; Vaccaro, Vanja; Vari, Sabrina; Cognetti, Francesco; Ciuffreda, Ludovica

2015-01-01

PTEN is the most important negative regulator of the PI3K signaling pathway. In addition to its canonical, PI3K inhibition-dependent functions, PTEN can also function as a tumor suppressor in a PI3K-independent manner. Indeed, the PTEN network regulates a broad spectrum of biological functions, modulating the flow of information from membrane-bound growth factor receptors to nuclear transcription factors, occurring in concert with other tumor suppressors and oncogenic signaling pathways. PTEN acts through its lipid and protein phosphatase activity and other non-enzymatic mechanisms. Studies conducted over the past 10 years have expanded our understanding of the biological role of PTEN, showing that in addition to its ability to regulate proliferation and cell survival, it also plays an intriguing role in regulating genomic stability, cell migration, stem cell self-renewal, and tumor microenvironment. Changes in PTEN protein levels, location, and enzymatic activity through various molecular mechanisms can generate a continuum of functional PTEN levels in inherited syndromes, sporadic cancers, and other diseases. PTEN activity can indeed, be modulated by mutations, epigenetic silencing, transcriptional repression, aberrant protein localization, and post-translational modifications. This review will discuss our current understanding of the biological role of PTEN, how PTEN expression and activity are regulated, and the consequences of PTEN dysregulation in human malignant tumors.

PTEN: Multiple Functions in Human Malignant Tumors

PubMed Central

Milella, Michele; Falcone, Italia; Conciatori, Fabiana; Cesta Incani, Ursula; Del Curatolo, Anais; Inzerilli, Nicola; Nuzzo, Carmen M. A.; Vaccaro, Vanja; Vari, Sabrina; Cognetti, Francesco; Ciuffreda, Ludovica

2015-01-01

PTEN is the most important negative regulator of the PI3K signaling pathway. In addition to its canonical, PI3K inhibition-dependent functions, PTEN can also function as a tumor suppressor in a PI3K-independent manner. Indeed, the PTEN network regulates a broad spectrum of biological functions, modulating the flow of information from membrane-bound growth factor receptors to nuclear transcription factors, occurring in concert with other tumor suppressors and oncogenic signaling pathways. PTEN acts through its lipid and protein phosphatase activity and other non-enzymatic mechanisms. Studies conducted over the past 10 years have expanded our understanding of the biological role of PTEN, showing that in addition to its ability to regulate proliferation and cell survival, it also plays an intriguing role in regulating genomic stability, cell migration, stem cell self-renewal, and tumor microenvironment. Changes in PTEN protein levels, location, and enzymatic activity through various molecular mechanisms can generate a continuum of functional PTEN levels in inherited syndromes, sporadic cancers, and other diseases. PTEN activity can indeed, be modulated by mutations, epigenetic silencing, transcriptional repression, aberrant protein localization, and post-translational modifications. This review will discuss our current understanding of the biological role of PTEN, how PTEN expression and activity are regulated, and the consequences of PTEN dysregulation in human malignant tumors. PMID:25763354

Detecting gene subnetworks under selection in biological pathways.

PubMed

Gouy, Alexandre; Daub, Joséphine T; Excoffier, Laurent

2017-09-19

Advances in high throughput sequencing technologies have created a gap between data production and functional data analysis. Indeed, phenotypes result from interactions between numerous genes, but traditional methods treat loci independently, missing important knowledge brought by network-level emerging properties. Therefore, detecting selection acting on multiple genes affecting the evolution of complex traits remains challenging. In this context, gene network analysis provides a powerful framework to study the evolution of adaptive traits and facilitates the interpretation of genome-wide data. We developed a method to analyse gene networks that is suitable to evidence polygenic selection. The general idea is to search biological pathways for subnetworks of genes that directly interact with each other and that present unusual evolutionary features. Subnetwork search is a typical combinatorial optimization problem that we solve using a simulated annealing approach. We have applied our methodology to find signals of adaptation to high-altitude in human populations. We show that this adaptation has a clear polygenic basis and is influenced by many genetic components. Our approach, implemented in the R package signet, improves on gene-level classical tests for selection by identifying both new candidate genes and new biological processes involved in adaptation to altitude. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

Fundamental Flaws of Hormesis for Public Health Decisions

PubMed Central

Thayer, Kristina A.; Melnick, Ronald; Burns, Kathy; Davis, Devra; Huff, James

2005-01-01

Hormesis (defined operationally as low-dose stimulation, high-dose inhibition) is often used to promote the notion that while high-level exposures to toxic chemicals could be detrimental to human health, low-level exposures would be beneficial. Some proponents claim hormesis is an adaptive, generalizable phenomenon and argue that the default assumption for risk assessments should be that toxic chemicals induce stimulatory (i.e., “beneficial”) effects at low exposures. In many cases, nonmonotonic dose–response curves are called hormetic responses even in the absence of any mechanistic characterization of that response. Use of the term “hormesis,” with its associated descriptors, distracts from the broader and more important questions regarding the frequency and interpretation of nonmonotonic dose responses in biological systems. A better understanding of the biological basis and consequences of nonmonotonic dose–response curves is warranted for evaluating human health risks. The assumption that hormesis is generally adaptive is an oversimplification of complex biological processes. Even if certain low-dose effects were sometimes considered beneficial, this should not influence regulatory decisions to allow increased environmental exposures to toxic and carcinogenic agents, given factors such as interindividual differences in susceptibility and multiplicity in exposures. In this commentary we evaluate the hormesis hypothesis and potential adverse consequences of incorporating low-dose beneficial effects into public health decisions. PMID:16203233

A framework for predicting impacts on ecosystem services ...

EPA Pesticide Factsheets

Protection of ecosystem services is increasingly emphasized as a risk-assessment goal, but there are wide gaps between current ecological risk-assessment endpoints and potential effects on services provided by ecosystems. The authors present a framework that links common ecotoxicological endpoints to chemical impacts on populations and communities and the ecosystem services that they provide. This framework builds on considerable advances in mechanistic effects models designed to span multiple levels of biological organization and account for various types of biological interactions and feedbacks. For illustration, the authors introduce 2 case studies that employ well-developed and validated mechanistic effects models: the inSTREAM individual-based model for fish populations and the AQUATOX ecosystem model. They also show how dynamic energy budget theory can provide a common currency for interpreting organism-level toxicity. They suggest that a framework based on mechanistic models that predict impacts on ecosystem services resulting from chemical exposure, combined with economic valuation, can provide a useful approach for informing environmental management. The authors highlight the potential benefits of using this framework as well as the challenges that will need to be addressed in future work. The framework introduced here represents an ongoing initiative supported by the National Institute of Mathematical and Biological Synthesis (NIMBioS; http://www.nimbi

Synthesizing genetic sequential logic circuit with clock pulse generator.

PubMed

Chuang, Chia-Hua; Lin, Chun-Liang

2014-05-28

Rhythmic clock widely occurs in biological systems which controls several aspects of cell physiology. For the different cell types, it is supplied with various rhythmic frequencies. How to synthesize a specific clock signal is a preliminary but a necessary step to further development of a biological computer in the future. This paper presents a genetic sequential logic circuit with a clock pulse generator based on a synthesized genetic oscillator, which generates a consecutive clock signal whose frequency is an inverse integer multiple to that of the genetic oscillator. An analogous electronic waveform-shaping circuit is constructed by a series of genetic buffers to shape logic high/low levels of an oscillation input in a basic sinusoidal cycle and generate a pulse-width-modulated (PWM) output with various duty cycles. By controlling the threshold level of the genetic buffer, a genetic clock pulse signal with its frequency consistent to the genetic oscillator is synthesized. A synchronous genetic counter circuit based on the topology of the digital sequential logic circuit is triggered by the clock pulse to synthesize the clock signal with an inverse multiple frequency to the genetic oscillator. The function acts like a frequency divider in electronic circuits which plays a key role in the sequential logic circuit with specific operational frequency. A cascaded genetic logic circuit generating clock pulse signals is proposed. Based on analogous implement of digital sequential logic circuits, genetic sequential logic circuits can be constructed by the proposed approach to generate various clock signals from an oscillation signal.

Effects of acute dieldrin exposure on neurotransmitters and global gene transcription in largemouth bass (Micropterus salmoides) hypothalamus

PubMed Central

Martyniuk, Christopher J.; Feswick, April; Spade, Daniel J.; Kroll, Kevin J.; Barber, David S.; Denslow, Nancy D.

2010-01-01

Exposure to dieldrin induces neurotoxic effects in the vertebrate CNS and disrupts reproductive processes in teleost fish. Reproductive impairment observed in fish by dieldrin is likely the result of multiple effects along the hypothalamic-pituitary-gonadal axis but the molecular signaling cascades are not well characterized. To better elucidate the mode of action of dieldrin in the hypothalamus, this study measured neurotransmitter levels and examined the transcriptomic response in female largemouth bass (LMB) to an acute treatment of dieldrin. Male and female LMB were injected with either vehicle or 10 mg dieldrin/kg and sacrificed after seven days. There were no significant changes in dopamine or DOPAC concentrations in the neuroendocrine brain of males and females after treatment but GABA levels in females were moderately increased 20–30% in the hypothalamus and cerebellum. In the female hypothalamus, there were 227 transcripts (p<0.001) identified as being differentially regulated by dieldrin. Functional enrichment analysis revealed transcription, DNA repair, ubiquitin-proteasome pathway, and cell communication, as biological processes over-represented in the microarray analysis. Pathway analysis identified DNA damage, inflammation, regeneration, and Alzheimer’s disease as major cell processes and diseases affected by dieldrin. Using multiple bioinformatics approaches, this study demonstrates that the teleostean hypothalamus is a target for dieldrin-induced neurotoxicity and provides mechanistic evidence that dieldrin activates similar cell pathways and biological processes that are also associated with the etiology of human neurological disorders. PMID:20438755

Variation of DNA Methylome of Zebrafish Cells under Cold Pressure

PubMed Central

Xu, Qiongqiong; Luo, Juntao; Shi, Yingdi; Li, Xiaoxia; Yan, Xiaonan; Zhang, Junfang

2016-01-01

DNA methylation is an essential epigenetic mechanism involved in multiple biological processes. However, the relationship between DNA methylation and cold acclimation remains poorly understood. In this study, Methylated DNA Immunoprecipitation Sequencing (MeDIP-seq) was performed to reveal a genome-wide methylation profile of zebrafish (Danio rerio) embryonic fibroblast cells (ZF4) and its variation under cold pressure. MeDIP-seq assay was conducted with ZF4 cells cultured at appropriate temperature of 28°C and at low temperature of 18°C for 5 (short-term) and 30 (long-term) days, respectively. Our data showed that DNA methylation level of whole genome increased after a short-term cold exposure and decreased after a long-term cold exposure. It is interesting that metabolism of folate pathway is significantly hypomethylated after short-term cold exposure, which is consistent with the increased DNA methylation level. 21% of methylation peaks were significantly altered after cold treatment. About 8% of altered DNA methylation peaks are located in promoter regions, while the majority of them are located in non-coding regions. Methylation of genes involved in multiple cold responsive biological processes were significantly affected, such as anti-oxidant system, apoptosis, development, chromatin modifying and immune system suggesting that those processes are responsive to cold stress through regulation of DNA methylation. Our data indicate the involvement of DNA methylation in cellular response to cold pressure, and put a new insight into the genome-wide epigenetic regulation under cold pressure. PMID:27494266

Predicting Human Protein Subcellular Locations by the Ensemble of Multiple Predictors via Protein-Protein Interaction Network with Edge Clustering Coefficients

PubMed Central

Du, Pufeng; Wang, Lusheng

2014-01-01

One of the fundamental tasks in biology is to identify the functions of all proteins to reveal the primary machinery of a cell. Knowledge of the subcellular locations of proteins will provide key hints to reveal their functions and to understand the intricate pathways that regulate biological processes at the cellular level. Protein subcellular location prediction has been extensively studied in the past two decades. A lot of methods have been developed based on protein primary sequences as well as protein-protein interaction network. In this paper, we propose to use the protein-protein interaction network as an infrastructure to integrate existing sequence based predictors. When predicting the subcellular locations of a given protein, not only the protein itself, but also all its interacting partners were considered. Unlike existing methods, our method requires neither the comprehensive knowledge of the protein-protein interaction network nor the experimentally annotated subcellular locations of most proteins in the protein-protein interaction network. Besides, our method can be used as a framework to integrate multiple predictors. Our method achieved 56% on human proteome in absolute-true rate, which is higher than the state-of-the-art methods. PMID:24466278

HAPRAP: a haplotype-based iterative method for statistical fine mapping using GWAS summary statistics.

PubMed

Zheng, Jie; Rodriguez, Santiago; Laurin, Charles; Baird, Denis; Trela-Larsen, Lea; Erzurumluoglu, Mesut A; Zheng, Yi; White, Jon; Giambartolomei, Claudia; Zabaneh, Delilah; Morris, Richard; Kumari, Meena; Casas, Juan P; Hingorani, Aroon D; Evans, David M; Gaunt, Tom R; Day, Ian N M

2017-01-01

Fine mapping is a widely used approach for identifying the causal variant(s) at disease-associated loci. Standard methods (e.g. multiple regression) require individual level genotypes. Recent fine mapping methods using summary-level data require the pairwise correlation coefficients ([Formula: see text]) of the variants. However, haplotypes rather than pairwise [Formula: see text], are the true biological representation of linkage disequilibrium (LD) among multiple loci. In this article, we present an empirical iterative method, HAPlotype Regional Association analysis Program (HAPRAP), that enables fine mapping using summary statistics and haplotype information from an individual-level reference panel. Simulations with individual-level genotypes show that the results of HAPRAP and multiple regression are highly consistent. In simulation with summary-level data, we demonstrate that HAPRAP is less sensitive to poor LD estimates. In a parametric simulation using Genetic Investigation of ANthropometric Traits height data, HAPRAP performs well with a small training sample size (N < 2000) while other methods become suboptimal. Moreover, HAPRAP's performance is not affected substantially by single nucleotide polymorphisms (SNPs) with low minor allele frequencies. We applied the method to existing quantitative trait and binary outcome meta-analyses (human height, QTc interval and gallbladder disease); all previous reported association signals were replicated and two additional variants were independently associated with human height. Due to the growing availability of summary level data, the value of HAPRAP is likely to increase markedly for future analyses (e.g. functional prediction and identification of instruments for Mendelian randomization). The HAPRAP package and documentation are available at http://apps.biocompute.org.uk/haprap/ CONTACT: : jie.zheng@bristol.ac.uk or tom.gaunt@bristol.ac.ukSupplementary information: Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press.

Production of knock-in mice in a single generation from embryonic stem cells.

PubMed

Ukai, Hideki; Kiyonari, Hiroshi; Ueda, Hiroki R

2017-12-01

The system-level identification and analysis of molecular networks in mammals can be accelerated by 'next-generation' genetics, defined as genetics that does not require crossing of multiple generations of animals in order to achieve the desired genetic makeup. We have established a highly efficient procedure for producing knock-in (KI) mice within a single generation, by optimizing the genome-editing protocol for KI embryonic stem (ES) cells and the protocol for the generation of fully ES-cell-derived mice (ES mice). Using this protocol, the production of chimeric mice is eliminated, and, therefore, there is no requirement for the crossing of chimeric mice to produce mice that carry the KI gene in all cells of the body. Our procedure thus shortens the time required to produce KI ES mice from about a year to ∼3 months. Various kinds of KI ES mice can be produced with a minimized amount of work, facilitating the elucidation of organism-level phenomena using a systems biology approach. In this report, we describe the basic technologies and protocols for this procedure, and discuss the current challenges for next-generation mammalian genetics in organism-level systems biology studies.

Spatial congruence in language and species richness but not threat in the world's top linguistic hotspot.

PubMed

Turvey, Samuel T; Pettorelli, Nathalie

2014-12-07

Languages share key evolutionary properties with biological species, and global-level spatial congruence in richness and threat is documented between languages and several taxonomic groups. However, there is little understanding of the functional connection between diversification or extinction in languages and species, or the relationship between linguistic and species richness across different spatial scales. New Guinea is the world's most linguistically rich region and contains extremely high biological diversity. We demonstrate significant positive relationships between language and mammal richness in New Guinea across multiple spatial scales, revealing a likely functional relationship over scales at which infra-island diversification may occur. However, correlations are driven by spatial congruence between low levels of language and species richness. Regional biocultural richness may have showed closer congruence before New Guinea's linguistic landscape was altered by Holocene demographic events. In contrast to global studies, we demonstrate a significant negative correlation across New Guinea between areas with high levels of threatened languages and threatened mammals, indicating that landscape-scale threats differ between these groups. Spatial resource prioritization to conserve biodiversity may not benefit threatened languages, and conservation policy must adopt a multi-faceted approach to protect biocultural diversity as a whole.

Constraints imposed by pollinator behaviour on the ecology and evolution of plant mating systems.

PubMed

Devaux, C; Lepers, C; Porcher, E

2014-07-01

Most flowering plants rely on pollinators for their reproduction. Plant-pollinator interactions, although mutualistic, involve an inherent conflict of interest between both partners and may constrain plant mating systems at multiple levels: the immediate ecological plant selfing rates, their distribution in and contribution to pollination networks, and their evolution. Here, we review experimental evidence that pollinator behaviour influences plant selfing rates in pairs of interacting species, and that plants can modify pollinator behaviour through plastic and evolutionary changes in floral traits. We also examine how theoretical studies include pollinators, implicitly or explicitly, to investigate the role of their foraging behaviour in plant mating system evolution. In doing so, we call for more evolutionary models combining ecological and genetic factors, and additional experimental data, particularly to describe pollinator foraging behaviour. Finally, we show that recent developments in ecological network theory help clarify the impact of community-level interactions on plant selfing rates and their evolution and suggest new research avenues to expand the study of mating systems of animal-pollinated plant species to the level of the plant-pollinator networks. © 2014 The Authors. Journal of Evolutionary Biology © 2014 European Society For Evolutionary Biology.

Knowledge discovery and system biology in molecular medicine: an application on neurodegenerative diseases.

PubMed

Fattore, Matteo; Arrigo, Patrizio

2005-01-01

The possibility to study an organism in terms of system theory has been proposed in the past, but only the advancement of molecular biology techniques allow us to investigate the dynamical properties of a biological system in a more quantitative and rational way than before . These new techniques can gave only the basic level view of an organisms functionality. The comprehension of its dynamical behaviour depends on the possibility to perform a multiple level analysis. Functional genomics has stimulated the interest in the investigation the dynamical behaviour of an organism as a whole. These activities are commonly known as System Biology, and its interests ranges from molecules to organs. One of the more promising applications is the 'disease modeling'. The use of experimental models is a common procedure in pharmacological and clinical researches; today this approach is supported by 'in silico' predictive methods. This investigation can be improved by a combination of experimental and computational tools. The Machine Learning (ML) tools are able to process different heterogeneous data sources, taking into account this peculiarity, they could be fruitfully applied to support a multilevel data processing (molecular, cellular and morphological) that is the prerequisite for the formal model design; these techniques can allow us to extract the knowledge for mathematical model development. The aim of our work is the development and implementation of a system that combines ML and dynamical models simulations. The program is addressed to the virtual analysis of the pathways involved in neurodegenerative diseases. These pathologies are multifactorial diseases and the relevance of the different factors has not yet been well elucidated. This is a very complex task; in order to test the integrative approach our program has been limited to the analysis of the effects of a specific protein, the Cyclin dependent kinase 5 (CDK5) which relies on the induction of neuronal apoptosis. The system has a modular structure centred on a textual knowledge discovery approach. The text mining is the only way to enhance the capability to extract ,from multiple data sources, the information required for the dynamical simulator. The user may access the publically available modules through the following site: http://biocomp.ge.ismac.cnr.it.

Chemical-agnostic hazard prediction: statistical inference of in ...

EPA Pesticide Factsheets

Toxicity pathways have been defined as normal cellular pathways that, when sufficiently perturbed as a consequence of chemical exposure, lead to an adverse outcome. If an exposure alters one or more normal biological pathways to an extent that leads to an adverse toxicity outcome, a significant correlation must exist between the exposure, the extent of pathway alteration, and the degree of adverse outcome. Biological pathways are regulated at multiple levels, including transcriptional, post-transcriptional, post-translational, and targeted degradation, each of which can affect the levels and extents of modification of proteins involved in the pathways. Significant alterations of toxicity pathways resulting from changes in regulation at any of these levels therefore are likely to be detectable as alterations in the proteome. We hypothesize that significant correlations between exposures, adverse outcomes, and changes in the proteome have the potential to identify putative toxicity pathways, facilitating selection of candidate targets for high throughput screening, even in the absence of a priori knowledge of either the specific pathways involved or the specific agents inducing the pathway alterations. We explored this hypothesis in vitro in BEAS-2B human airway epithelial cells exposed to different concentrations of Ni2+, Cd2+, and Cr6+, alone and in defined mixtures. Levels and phosphorylation status of a variety of signaling pathway proteins and cytokines were

Phenotypic and genotypic identification of Aeromonas spp. isolated from a chlorinated intermittent water distribution system in Lebanon.

PubMed

Tokajian, Sima; Hashwa, Fuad

2004-06-01

Aeromonas spp. were detected in samples collected from both untreated groundwater and treated drinking water in Lebanon. Aeromonas spp. levels ranged between 2 and 1,100 colonies per 100 ml in the intake underground well and between 3 and 43 colonies per 100 ml in samples from the distribution system. Samples positive for Aeromonas spp. from the network had a free chlorine level ranging between 0 and 0.4 mg l(-1). Multiple antibiotic-resistance was common among the isolated aeromonads; all were resistant to amoxycillin while 92% showed resistance to cephalexin. Haemolysis on blood agar was detected in 52% of the isolates recovered from the distribution network and 81% of isolates from the untreated underground source. The Biolog microbial identification system assigned identities to all of the isolated presumptive aeromonads (at least at the genus level), which was not the case with the API 20NE strips. Differences at the species level were observed when results from the Biolog system were compared with identification based on the MicroSeq 500 16S rDNA sequence analysis. The presence of Aeromonas spp. in drinking water can be an important threat to public health, thus greater awareness of Aeromonas strains as potential enteropathogens is warranted.

Central nervous system remyelination in culture--a tool for multiple sclerosis research.

PubMed

Zhang, Hui; Jarjour, Andrew A; Boyd, Amanda; Williams, Anna

2011-07-01

Multiple sclerosis is a demyelinating disease of the central nervous system which only affects humans. This makes it difficult to study at a molecular level, and to develop and test potential therapies that may change the course of the disease. The development of therapies to promote remyelination in multiple sclerosis is a key research aim, to both aid restoration of electrical impulse conduction in nerves and provide neuroprotection, reducing disability in patients. Testing a remyelination therapy in the many and various in vivo models of multiple sclerosis is expensive in terms of time, animals and money. We report the development and characterisation of an ex vivo slice culture system using mouse brain and spinal cord, allowing investigation of myelination, demyelination and remyelination, which can be used as an initial reliable screen to select the most promising remyelination strategies. We have automated the quantification of myelin to provide a high content and moderately-high-throughput screen for testing therapies for remyelination both by endogenous and exogenous means and as an invaluable way of studying the biology of remyelination. Copyright © 2011 Elsevier Inc. All rights reserved.

Central nervous system remyelination in culture — A tool for multiple sclerosis research

PubMed Central

Zhang, Hui; Jarjour, Andrew A.; Boyd, Amanda; Williams, Anna

2011-01-01

Multiple sclerosis is a demyelinating disease of the central nervous system which only affects humans. This makes it difficult to study at a molecular level, and to develop and test potential therapies that may change the course of the disease. The development of therapies to promote remyelination in multiple sclerosis is a key research aim, to both aid restoration of electrical impulse conduction in nerves and provide neuroprotection, reducing disability in patients. Testing a remyelination therapy in the many and various in vivo models of multiple sclerosis is expensive in terms of time, animals and money. We report the development and characterisation of an ex vivo slice culture system using mouse brain and spinal cord, allowing investigation of myelination, demyelination and remyelination, which can be used as an initial reliable screen to select the most promising remyelination strategies. We have automated the quantification of myelin to provide a high content and moderately-high-throughput screen for testing therapies for remyelination both by endogenous and exogenous means and as an invaluable way of studying the biology of remyelination. PMID:21515259

Disentangling the multigenic and pleiotropic nature of molecular function

PubMed Central

2015-01-01

Background Biological processes at the molecular level are usually represented by molecular interaction networks. Function is organised and modularity identified based on network topology, however, this approach often fails to account for the dynamic and multifunctional nature of molecular components. For example, a molecule engaging in spatially or temporally independent functions may be inappropriately clustered into a single functional module. To capture biologically meaningful sets of interacting molecules, we use experimentally defined pathways as spatial/temporal units of molecular activity. Results We defined functional profiles of Saccharomyces cerevisiae based on a minimal set of Gene Ontology terms sufficient to represent each pathway's genes. The Gene Ontology terms were used to annotate 271 pathways, accounting for pathway multi-functionality and gene pleiotropy. Pathways were then arranged into a network, linked by shared functionality. Of the genes in our data set, 44% appeared in multiple pathways performing a diverse set of functions. Linking pathways by overlapping functionality revealed a modular network with energy metabolism forming a sparse centre, surrounded by several denser clusters comprised of regulatory and metabolic pathways. Signalling pathways formed a relatively discrete cluster connected to the centre of the network. Genetic interactions were enriched within the clusters of pathways by a factor of 5.5, confirming the organisation of our pathway network is biologically significant. Conclusions Our representation of molecular function according to pathway relationships enables analysis of gene/protein activity in the context of specific functional roles, as an alternative to typical molecule-centric graph-based methods. The pathway network demonstrates the cooperation of multiple pathways to perform biological processes and organises pathways into functionally related clusters with interdependent outcomes. PMID:26678917

International interlaboratory study comparing single organism 16S rRNA gene sequencing data: Beyond consensus sequence comparisons

PubMed Central

Olson, Nathan D.; Lund, Steven P.; Zook, Justin M.; Rojas-Cornejo, Fabiola; Beck, Brian; Foy, Carole; Huggett, Jim; Whale, Alexandra S.; Sui, Zhiwei; Baoutina, Anna; Dobeson, Michael; Partis, Lina; Morrow, Jayne B.

2015-01-01

This study presents the results from an interlaboratory sequencing study for which we developed a novel high-resolution method for comparing data from different sequencing platforms for a multi-copy, paralogous gene. The combination of PCR amplification and 16S ribosomal RNA gene (16S rRNA) sequencing has revolutionized bacteriology by enabling rapid identification, frequently without the need for culture. To assess variability between laboratories in sequencing 16S rRNA, six laboratories sequenced the gene encoding the 16S rRNA from Escherichia coli O157:H7 strain EDL933 and Listeria monocytogenes serovar 4b strain NCTC11994. Participants performed sequencing methods and protocols available in their laboratories: Sanger sequencing, Roche 454 pyrosequencing®, or Ion Torrent PGM®. The sequencing data were evaluated on three levels: (1) identity of biologically conserved position, (2) ratio of 16S rRNA gene copies featuring identified variants, and (3) the collection of variant combinations in a set of 16S rRNA gene copies. The same set of biologically conserved positions was identified for each sequencing method. Analytical methods using Bayesian and maximum likelihood statistics were developed to estimate variant copy ratios, which describe the ratio of nucleotides at each identified biologically variable position, as well as the likely set of variant combinations present in 16S rRNA gene copies. Our results indicate that estimated variant copy ratios at biologically variable positions were only reproducible for high throughput sequencing methods. Furthermore, the likely variant combination set was only reproducible with increased sequencing depth and longer read lengths. We also demonstrate novel methods for evaluating variable positions when comparing multi-copy gene sequence data from multiple laboratories generated using multiple sequencing technologies. PMID:27077030

Determinants of the rate of protein sequence evolution

PubMed Central

Zhang, Jianzhi; Yang, Jian-Rong

2015-01-01

The rate and mechanism of protein sequence evolution have been central questions in evolutionary biology since the 1960s. Although the rate of protein sequence evolution depends primarily on the level of functional constraint, exactly what constitutes functional constraint has remained unclear. The increasing availability of genomic data has allowed for much needed empirical examinations on the nature of functional constraint. These studies found that the evolutionary rate of a protein is predominantly influenced by its expression level rather than functional importance. A combination of theoretical and empirical analyses have identified multiple mechanisms behind these observations and demonstrated a prominent role that selection against errors in molecular and cellular processes plays in protein evolution. PMID:26055156

A Structural Perspective on Readout of Epigenetic Histone and DNA Methylation Marks

PubMed Central

Patel, Dinshaw J.

2016-01-01

SUMMARY This article outlines the protein modules that target methylated lysine histone marks and 5mC DNA marks, and the molecular principles underlying recognition. The article focuses on the structural basis underlying readout of isolated marks by single reader molecules, as well as multivalent readout of multiple marks by linked reader cassettes at the histone tail and nucleosome level. Additional topics addressed include the role of histone mimics, cross talk between histone marks, technological developments at the genome-wide level, advances using chemical biology approaches, the linkage between histone and DNA methylation, the role for regulatory lncRNAs, and the promise of chromatin-based therapeutic modalities. PMID:26931326

A Robust Unified Approach to Analyzing Methylation and Gene Expression Data

PubMed Central

Khalili, Abbas; Huang, Tim; Lin, Shili

2009-01-01

Microarray technology has made it possible to investigate expression levels, and more recently methylation signatures, of thousands of genes simultaneously, in a biological sample. Since more and more data from different biological systems or technological platforms are being generated at an incredible rate, there is an increasing need to develop statistical methods that are applicable to multiple data types and platforms. Motivated by such a need, a flexible finite mixture model that is applicable to methylation, gene expression, and potentially data from other biological systems, is proposed. Two major thrusts of this approach are to allow for a variable number of components in the mixture to capture non-biological variation and small biases, and to use a robust procedure for parameter estimation and probe classification. The method was applied to the analysis of methylation signatures of three breast cancer cell lines. It was also tested on three sets of expression microarray data to study its power and type I error rates. Comparison with a number of existing methods in the literature yielded very encouraging results; lower type I error rates and comparable/better power were achieved based on the limited study. Furthermore, the method also leads to more biologically interpretable results for the three breast cancer cell lines. PMID:20161265

Using dual classifications in the development of avian wetland indices of biological integrity for wetlands in West Virginia, USA.

PubMed

Veselka, Walter; Anderson, James T; Kordek, Walter S

2010-05-01

Considerable resources are being used to develop and implement bioassessment methods for wetlands to ensure that "biological integrity" is maintained under the United States Clean Water Act. Previous research has demonstrated that avian composition is susceptible to human impairments at multiple spatial scales. Using a site-specific disturbance gradient, we built avian wetland indices of biological integrity (AW-IBI) specific to two wetland classification schemes, one based on vegetative structure and the other based on the wetland's position in the landscape and sources of water. The resulting class-specific AW-IBI was comprised of one to four metrics that varied in their sensitivity to the disturbance gradient. Some of these metrics were specific to only one of the classification schemes, whereas others could discriminate varying levels of disturbance regardless of classification scheme. Overall, all of the derived biological indices specific to the vegetative structure-based classes of wetlands had a significant relation with the disturbance gradient; however, the biological index derived for floodplain wetlands exhibited a more consistent response to a local disturbance gradient. We suspect that the consistency of this response is due to the inherent nature of the connectivity of available habitat in floodplain wetlands.

Lipidomics by ultrahigh performance liquid chromatography-high resolution mass spectrometry and its application to complex biological samples.

PubMed

Triebl, Alexander; Trötzmüller, Martin; Hartler, Jürgen; Stojakovic, Tatjana; Köfeler, Harald C

2017-05-15

An improved approach for selective and sensitive identification and quantitation of lipid molecular species using reversed phase chromatography coupled to high resolution mass spectrometry was developed. The method is applicable to a wide variety of biological matrices using a simple liquid-liquid extraction procedure. Together, this approach combines multiple selectivity criteria: Reversed phase chromatography separates lipids according to their acyl chain length and degree of unsaturation and is capable of resolving positional isomers of lysophospholipids, as well as structural isomers of diacyl phospholipids and glycerolipids. Orbitrap mass spectrometry delivers the elemental composition of both positive and negative ions with high mass accuracy. Finally, automatically generated tandem mass spectra provide structural insight into numerous glycerolipids, phospholipids, and sphingolipids within a single run. Calibration showed linearity ranges of more than four orders of magnitude, good values for accuracy and precision at biologically relevant concentration levels, and limits of quantitation of a few femtomoles on column. Hundreds of lipid molecular species were detected and quantified in three different biological matrices, which cover well the wide variety and complexity of various model organisms in lipidomic research. Together with a software package, this method is a prime choice for global lipidomic analysis of even the most complex biological samples. Copyright © 2017 Elsevier B.V. All rights reserved.

Dupuytren's: a systems biology disease

PubMed Central

2011-01-01

Dupuytren's disease (DD) is an ill-defined fibroproliferative disorder of the palm of the hands leading to digital contracture. DD commonly occurs in individuals of northern European extraction. Cellular components and processes associated with DD pathogenesis include altered gene and protein expression of cytokines, growth factors, adhesion molecules, and extracellular matrix components. Histology has shown increased but varying levels of particular types of collagen, myofibroblasts and myoglobin proteins in DD tissue. Free radicals and localised ischaemia have been suggested to trigger the proliferation of DD tissue. Although the existing available biological information on DD may contain potentially valuable (though largely uninterpreted) information, the precise aetiology of DD remains unknown. Systems biology combines mechanistic modelling with quantitative experimentation in studies of networks and better understanding of the interaction of multiple components in disease processes. Adopting systems biology may be the ideal approach for future research in order to improve understanding of complex diseases of multifactorial origin. In this review, we propose that DD is a disease of several networks rather than of a single gene, and show that this accounts for the experimental observations obtained to date from a variety of sources. We outline how DD may be investigated more effectively by employing a systems biology approach that considers the disease network as a whole rather than focusing on any specific single molecule. PMID:21943049

Neurofilament light antibodies in serum reflect response to natalizumab treatment in multiple sclerosis.

PubMed

Amor, Sandra; van der Star, Baukje J; Bosca, Isabel; Raffel, Joel; Gnanapavan, Sharmilee; Watchorn, Jonathan; Kuhle, Jens; Giovannoni, Gavin; Baker, David; Malaspina, Andrea; Puentes, Fabiola

2014-09-01

Increased levels of antibodies to neurofilament light protein (NF-L) in biological fluids have been found to reflect neuroinflammatory responses and neurodegeneration in multiple sclerosis (MS). To evaluate whether levels of serum antibodies against NF-L correlate with clinical variants and treatment response in MS. The autoantibody reactivity to NF-L protein was tested in serum samples from patients with relapsing-remitting MS (RRMS) (n=22) and secondary progressive MS (SPMS) (n=26). Two other cohorts of RRMS patients under treatment with natalizumab were analysed cross-sectionally (n=16) and longitudinally (n=24). The follow-up samples were taken at 6, 12, 18 and 24 months after treatment, and the NF-L antibody levels were compared against baseline levels. NF-L antibodies were higher in MS clinical groups than healthy controls and in RRMS compared to SPMS patients (p<0.001). NF-L antibody levels were lower in natalizumab treated than in untreated patients (p<0.001). In the longitudinal series, NF-L antibody levels decreased over time and a significant difference was found following 24 months of treatment compared with baseline measurements (p=0.001). Drug efficacy in MS treatment indicates the potential use of monitoring the content of antibodies against the NF-L chain as a predictive biomarker of treatment response in MS. © The Author(s) 2014.

A hybrid approach of gene sets and single genes for the prediction of survival risks with gene expression data.

PubMed

Seok, Junhee; Davis, Ronald W; Xiao, Wenzhong

2015-01-01

Accumulated biological knowledge is often encoded as gene sets, collections of genes associated with similar biological functions or pathways. The use of gene sets in the analyses of high-throughput gene expression data has been intensively studied and applied in clinical research. However, the main interest remains in finding modules of biological knowledge, or corresponding gene sets, significantly associated with disease conditions. Risk prediction from censored survival times using gene sets hasn't been well studied. In this work, we propose a hybrid method that uses both single gene and gene set information together to predict patient survival risks from gene expression profiles. In the proposed method, gene sets provide context-level information that is poorly reflected by single genes. Complementarily, single genes help to supplement incomplete information of gene sets due to our imperfect biomedical knowledge. Through the tests over multiple data sets of cancer and trauma injury, the proposed method showed robust and improved performance compared with the conventional approaches with only single genes or gene sets solely. Additionally, we examined the prediction result in the trauma injury data, and showed that the modules of biological knowledge used in the prediction by the proposed method were highly interpretable in biology. A wide range of survival prediction problems in clinical genomics is expected to benefit from the use of biological knowledge.

A Hybrid Approach of Gene Sets and Single Genes for the Prediction of Survival Risks with Gene Expression Data

PubMed Central

Seok, Junhee; Davis, Ronald W.; Xiao, Wenzhong

2015-01-01

Accumulated biological knowledge is often encoded as gene sets, collections of genes associated with similar biological functions or pathways. The use of gene sets in the analyses of high-throughput gene expression data has been intensively studied and applied in clinical research. However, the main interest remains in finding modules of biological knowledge, or corresponding gene sets, significantly associated with disease conditions. Risk prediction from censored survival times using gene sets hasn’t been well studied. In this work, we propose a hybrid method that uses both single gene and gene set information together to predict patient survival risks from gene expression profiles. In the proposed method, gene sets provide context-level information that is poorly reflected by single genes. Complementarily, single genes help to supplement incomplete information of gene sets due to our imperfect biomedical knowledge. Through the tests over multiple data sets of cancer and trauma injury, the proposed method showed robust and improved performance compared with the conventional approaches with only single genes or gene sets solely. Additionally, we examined the prediction result in the trauma injury data, and showed that the modules of biological knowledge used in the prediction by the proposed method were highly interpretable in biology. A wide range of survival prediction problems in clinical genomics is expected to benefit from the use of biological knowledge. PMID:25933378

Predicting Scientific Understanding of Prospective Elementary Teachers: Role of Gender, Education Level, Courses in Science, and Attitudes Toward Science and Mathematics

NASA Astrophysics Data System (ADS)

Kumar, David D.; Morris, John D.

2005-12-01

A multiple regression analysis of the relationship between prospective teachers' scientific understanding and Gender, Education Level (High School, College), Courses in Science (Biology, Chemistry, Physics, Earth Science, Astronomy, and Agriculture), Attitude Towards Science, and Attitude Towards Mathematics is reported. Undergraduate elementary science students ( N = 176) in an urban doctoral-level university in the United States participated in this study. The results of this study showed Gender, completion of courses in High School Chemistry and Physics, College Chemistry and Physics, and Attitudes Toward Mathematics and Science significantly correlated with scientific understanding. Based on a regression model, Gender, and College Chemistry and Physics experiences added significant predictive accuracy to scientific understanding among prospective elementary teachers compared to the other variables.

Promoting inquiry-based teaching in laboratory courses: are we meeting the grade?

PubMed

Beck, Christopher; Butler, Amy; da Silva, Karen Burke

2014-01-01

Over the past decade, repeated calls have been made to incorporate more active teaching and learning in undergraduate biology courses. The emphasis on inquiry-based teaching is especially important in laboratory courses, as these are the courses in which students are applying the process of science. To determine the current state of research on inquiry-based teaching in undergraduate biology laboratory courses, we reviewed the recent published literature on inquiry-based exercises. The majority of studies in our data set were in the subdisciplines of biochemistry, cell biology, developmental biology, genetics, and molecular biology. In addition, most exercises were guided inquiry, rather than open ended or research based. Almost 75% of the studies included assessment data, with two-thirds of these studies including multiple types of assessment data. However, few exercises were assessed in multiple courses or at multiple institutions. Furthermore, assessments were rarely based on published instruments. Although the results of the studies in our data set show a positive effect of inquiry-based teaching in biology laboratory courses on student learning gains, research that uses the same instrument across a range of courses and institutions is needed to determine whether these results can be generalized. © 2014 C. Beck 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).

Adaption of Ulva pertusa to multiple-contamination of heavy metals and nutrients: Biological mechanism of outbreak of Ulva sp. green tide.

PubMed

Ge, Changzi; Yu, Xiru; Kan, Manman; Qu, Chunfeng

2017-12-15

The multiple-contamination of heavy metals and nutrients worsens increasingly and Ulva sp. green tide occurs almost simultaneously. To reveal the biological mechanism for outbreak of the green tide, Ulva pertusa was exposed to seven-day-multiple-contamination. The relation between pH variation (V pH ), Chl a content, ratio of (Chl a content)/(Chl b content) (R chla/chlb ), SOD activity of U. pertusa (A SOD ) and contamination concentration is [Formula: see text] (p<0.05), C chla =0.88 ±0.09 -0.01 ±0.00 ×C Cd (p<0.05), [Formula: see text] (p<0.05), and [Formula: see text] (p<0.05), respectively. C ammonia , C Cd and C Zn is concentration of ammonia, Cd 2+ and Zn 2+ , respectively. Comparing the contamination concentrations of seawaters where Ulva sp. green tide occurred and the contamination concentrations set in the present work, U. pertusa can adapt to multiple-contaminations in these waters. Thus, the adaption to multiple-contamination may be one biological mechanism for the outbreak of Ulva sp. green tide. Copyright © 2017 Elsevier Ltd. All rights reserved.

Detection of multiple perturbations in multi-omics biological networks.

PubMed

Griffin, Paula J; Zhang, Yuqing; Johnson, William Evan; Kolaczyk, Eric D

2018-05-17

Cellular mechanism-of-action is of fundamental concern in many biological studies. It is of particular interest for identifying the cause of disease and learning the way in which treatments act against disease. However, pinpointing such mechanisms is difficult, due to the fact that small perturbations to the cell can have wide-ranging downstream effects. Given a snapshot of cellular activity, it can be challenging to tell where a disturbance originated. The presence of an ever-greater variety of high-throughput biological data offers an opportunity to examine cellular behavior from multiple angles, but also presents the statistical challenge of how to effectively analyze data from multiple sources. In this setting, we propose a method for mechanism-of-action inference by extending network filtering to multi-attribute data. We first estimate a joint Gaussian graphical model across multiple data types using penalized regression and filter for network effects. We then apply a set of likelihood ratio tests to identify the most likely site of the original perturbation. In addition, we propose a conditional testing procedure to allow for detection of multiple perturbations. We demonstrate this methodology on paired gene expression and methylation data from The Cancer Genome Atlas (TCGA). © 2018, The International Biometric Society.

Psychosocial correlates of physical activity in school children aged 8-10 years.

PubMed

Seabra, Ana C; Seabra, André F; Mendonça, Denisa M; Brustad, Robert; Maia, José A; Fonseca, António M; Malina, Robert M

2013-10-01

Understanding correlates of physical activity (PA) among children in different populations may contribute to fostering active lifestyles. This study considered gender differences in relationships between biologic (body mass index, BMI), demographic (socioeconomic sport status, SES) and psychosocial correlates of PA and level of PA in Portuguese primary school children. 683 children, aged 8-10 years, from 20 different elementary schools in northern Portugal were surveyed. Weight status was classified using International Obesity Task Force (IOTF) criteria for the BMI. Family SES was estimated from school records. PA level and psychosocial correlates (attraction to PA, perceived physical competence and parental socialization) were obtained with interview and standardized questionnaires, respectively. Sex-specific hierarchical multiple regression analyses (SPSS 18.0) were conducted and included two blocks of predictor variables (biologic and demographic, and psychosocial). Level of PA was significantly higher in boys than girls. Enjoyment of participation in vigorous PA was positively associated with level of PA. Perceived acceptance by peers in games and sports and parental encouragement were positively and significantly related to PA in girls. Perceived physical competence was positively and significantly related to PA in boys. Weight status and SES were not associated with PA. Boys and girls differed in perceived attractiveness of PA and perceived physical competence, both of which influenced level of PA. Differences in perceptions may be important aspects of motivation for PA in school children.

Chemical biology 2012: from drug targets to biological systems and back.

PubMed

Socher, Elke; Grossmann, Tom N

2013-01-02

Multiple sites sharing a common target: This year's EMBO conference on chemical biology encouraged over 340 researchers to come to Heidelberg, Germany, and discuss the use of diverse chemical strategies and tools to investigate biological questions and better understand cellular processes. Copyright © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

PROMISE: a tool to identify genomic features with a specific biologically interesting pattern of associations with multiple endpoint variables

PubMed Central

Pounds, Stan; Cheng, Cheng; Cao, Xueyuan; Crews, Kristine R.; Plunkett, William; Gandhi, Varsha; Rubnitz, Jeffrey; Ribeiro, Raul C.; Downing, James R.; Lamba, Jatinder

2009-01-01

Motivation: In some applications, prior biological knowledge can be used to define a specific pattern of association of multiple endpoint variables with a genomic variable that is biologically most interesting. However, to our knowledge, there is no statistical procedure designed to detect specific patterns of association with multiple endpoint variables. Results: Projection onto the most interesting statistical evidence (PROMISE) is proposed as a general procedure to identify genomic variables that exhibit a specific biologically interesting pattern of association with multiple endpoint variables. Biological knowledge of the endpoint variables is used to define a vector that represents the biologically most interesting values for statistics that characterize the associations of the endpoint variables with a genomic variable. A test statistic is defined as the dot-product of the vector of the observed association statistics and the vector of the most interesting values of the association statistics. By definition, this test statistic is proportional to the length of the projection of the observed vector of correlations onto the vector of most interesting associations. Statistical significance is determined via permutation. In simulation studies and an example application, PROMISE shows greater statistical power to identify genes with the interesting pattern of associations than classical multivariate procedures, individual endpoint analyses or listing genes that have the pattern of interest and are significant in more than one individual endpoint analysis. Availability: Documented R routines are freely available from www.stjuderesearch.org/depts/biostats and will soon be available as a Bioconductor package from www.bioconductor.org. Contact: stanley.pounds@stjude.org Supplementary information: Supplementary data are available at Bioinformatics online. PMID:19528086

Differential expression of estrogen receptor α and β isoforms in multiple and solitary leiomyomas

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

Shao, Ruyue; Fang, Liaoqiong; Xing, Ruoxi

Uterine leiomyomas are benign myometrial neoplasms that function as one of the common indications for hysterectomy. Clinical and biological evidences indicate that uterine leiomyomas are estrogen-dependent. Estrogen stimulates cell proliferation through binding to the estrogen receptor (ER), of which both subtypes α and β are present in leiomyomas. Clinically, leiomyomas may be singular or multiple, where the first one is rarely recurring if removed and the latter associated to a relatively young age or genetic predisposition. These markedly different clinical phenotypes indicate that there may different mechanism causing a similar smooth muscle response. To investigate the relative expression of ERαmore » and ERβ in multiple and solitary uterine leiomyomas, we collected samples from 35 Chinese women (multiple leiomyomas n = 20, solitary leiomyoma n = 15) undergoing surgery to remove uterine leiomyomas. ELISA assay was performed to detect estrogen(E{sub 2}) concentration. Quantitative real-time PCR analysis was performed to detect ERα and ERβ mRNA expression. Western blot and immunohistochemical analysis were performed to detect ERα and ERβ protein expression. We found that ERα mRNA and protein levels of in multiple leiomyomas were significantly lower than those of solitary leiomyomas, whereas ERβ mRNA and protein levels in multiple leiomyomas were significantly higher than those in solitary leiomyomas, irrespectively of the menstrual cycle stage. In both multiple and solitary leiomyomas, ERα expression was higher than that of ERβ. E{sub 2} concentration in multiple and solitary leiomyomas correlated with that of ERα expression. ERα was present in nuclus and cytoplasma while estrogen receptor β localized only in nuclei in both multiple and solitary leiomyomas. Our findings suggest that the difference of ERα and ERβ expression between multiple and solitary leiomyomas may be responsible for the course of the disease subtypes. - Highlights: • In both multiple and solitary leiomyomas, ERα expression was higher than that of ERβ. • ERα was significantly lower, whereas ERβ was significantly higher in multiple leiomyomas than that in solitary leiomyomas. • The differential expression of ERα and ERβ may be responsible for the cause of the disease subtypes.« less

Detecting Biological Warfare Agents

PubMed Central

Song, Linan; Ahn, Soohyoun

2005-01-01

We developed a fiber-optic, microsphere-based, high-density array composed of 18 species-specific probe microsensors to identify biological warfare agents. We simultaneously identified multiple biological warfare agents in environmental samples by looking at specific probe responses after hybridization and response patterns of the multiplexed array. PMID:16318712

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.

Comparison of Co-Temporal Modeling Algorithms on Sparse Experimental Time Series Data Sets.

PubMed

Allen, Edward E; Norris, James L; John, David J; Thomas, Stan J; Turkett, William H; Fetrow, Jacquelyn S

2010-01-01

Multiple approaches for reverse-engineering biological networks from time-series data have been proposed in the computational biology literature. These approaches can be classified by their underlying mathematical algorithms, such as Bayesian or algebraic techniques, as well as by their time paradigm, which includes next-state and co-temporal modeling. The types of biological relationships, such as parent-child or siblings, discovered by these algorithms are quite varied. It is important to understand the strengths and weaknesses of the various algorithms and time paradigms on actual experimental data. We assess how well the co-temporal implementations of three algorithms, continuous Bayesian, discrete Bayesian, and computational algebraic, can 1) identify two types of entity relationships, parent and sibling, between biological entities, 2) deal with experimental sparse time course data, and 3) handle experimental noise seen in replicate data sets. These algorithms are evaluated, using the shuffle index metric, for how well the resulting models match literature models in terms of siblings and parent relationships. Results indicate that all three co-temporal algorithms perform well, at a statistically significant level, at finding sibling relationships, but perform relatively poorly in finding parent relationships.

Measurement Frontiers in Molecular Biology

NASA Astrophysics Data System (ADS)

Laderman, Stephen

2009-03-01

Developments of molecular measurements and manipulations have long enabled forefront research in evolution, genetics, biological development and its dysfunction, and the impact of external factors on the behavior of cells. Measurement remains at the heart of exciting and challenging basic and applied problems in molecular and cell biology. Methods to precisely determine the identity and abundance of particular molecules amongst a complex mixture of similar and dissimilar types require the successful design and integration of multiple steps involving biochemical manipulations, separations, physical probing, and data processing. Accordingly, today's most powerful methods for characterizing life at the molecular level depend on coordinated advances in applied physics, biochemistry, chemistry, computer science, and engineering. This is well illustrated by recent approaches to the measurement of DNA, RNA, proteins, and intact cells. Such successes underlie well founded visions of how molecular biology can further assist in answering compelling scientific questions and in enabling the development of remarkable advances in human health. These visions, in turn, are motivating the interdisciplinary creation of even more comprehensive measurements. As a further and closely related consequence, they are motivating innovations in the conceptual and practical approaches to organizing and visualizing large, complex sets of interrelated experimental results and distilling from those data compelling, informative conclusions.

Semantic Web meets Integrative Biology: a survey.

PubMed

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

2013-01-01

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

INfORM: Inference of NetwOrk Response Modules.

PubMed

Marwah, Veer Singh; Kinaret, Pia Anneli Sofia; Serra, Angela; Scala, Giovanni; Lauerma, Antti; Fortino, Vittorio; Greco, Dario

2018-06-15

Detecting and interpreting responsive modules from gene expression data by using network-based approaches is a common but laborious task. It often requires the application of several computational methods implemented in different software packages, forcing biologists to compile complex analytical pipelines. Here we introduce INfORM (Inference of NetwOrk Response Modules), an R shiny application that enables non-expert users to detect, evaluate and select gene modules with high statistical and biological significance. INfORM is a comprehensive tool for the identification of biologically meaningful response modules from consensus gene networks inferred by using multiple algorithms. It is accessible through an intuitive graphical user interface allowing for a level of abstraction from the computational steps. INfORM is freely available for academic use at https://github.com/Greco-Lab/INfORM. Supplementary data are available at Bioinformatics online.

Chronic Inflammation: Accelerator of Biological Aging.

PubMed

Fougère, Bertrand; Boulanger, Eric; Nourhashémi, Fati; Guyonnet, Sophie; Cesari, Matteo

2017-09-01

Biological aging is characterized by a chronic low-grade inflammation level. This chronic phenomenon has been named "inflamm-aging" and is a highly significant risk factor for morbidity and mortality in the older persons. The most common theories of inflamm-aging include redox stress, mitochondrial dysfunction, glycation, deregulation of the immune system, hormonal changes, epigenetic modifications, and dysfunction telomere attrition. Inflamm-aging plays a role in the initiation and progression of age-related diseases such as type II diabetes, Alzheimer's disease, cardiovascular disease, frailty, sarcopenia, osteoporosis, and cancer. This review will cover the identification of pathways that control age-related inflammation across multiple systems and its potential causal role in contributing to adverse health outcomes. © The Author 2016. Published by Oxford University Press on behalf of The Gerontological Society of America. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Genomic and Coexpression Analyses Predict Multiple Genes Involved in Triterpene Saponin Biosynthesis in Medicago truncatula[C][W

PubMed Central

Naoumkina, Marina A.; Modolo, Luzia V.; Huhman, David V.; Urbanczyk-Wochniak, Ewa; Tang, Yuhong; Sumner, Lloyd W.; Dixon, Richard A.

2010-01-01

Saponins, an important group of bioactive plant natural products, are glycosides of triterpenoid or steroidal aglycones (sapogenins). Saponins possess many biological activities, including conferring potential health benefits for humans. However, most of the steps specific for the biosynthesis of triterpene saponins remain uncharacterized at the molecular level. Here, we use comprehensive gene expression clustering analysis to identify candidate genes involved in the elaboration, hydroxylation, and glycosylation of the triterpene skeleton in the model legume Medicago truncatula. Four candidate uridine diphosphate glycosyltransferases were expressed in Escherichia coli, one of which (UGT73F3) showed specificity for multiple sapogenins and was confirmed to glucosylate hederagenin at the C28 position. Genetic loss-of-function studies in M. truncatula confirmed the in vivo function of UGT73F3 in saponin biosynthesis. This report provides a basis for future studies to define genetically the roles of multiple cytochromes P450 and glycosyltransferases in triterpene saponin biosynthesis in Medicago. PMID:20348429

The multiple life of nerve growth factor: tribute to rita levi-montalcini (1909-2012).

PubMed

Aloe, Luigi; Chaldakov, George N

2013-03-01

At the end of the 19(th) century, it was envisaged by Santiago Ramon y Cajal, but not, proven, that life at the neuronal level requires trophic support. The proof was obtained in the early 1950's by work initiated by Rita Levi-Montalcini (RLM) discovering the nerve growth factor (NGF). Today, NGF and its relatives, collectively designated neurotrophins, are well recognized as mediators of multiple biological phenomena in health and disease, ranging from the neurotrophic through immunotrophic and epitheliotrophic to metabotrophic effects. Consequently, NGF and other neurotrophins are implicated in the pathogenesis of a large spectrum of neuronal and non-neuronal diseases, from Alzheimer's and other neurodegenerative diseases to atherosclerosis and other cardiometabolic diseases. Recent studies demonstrated the therapeutic potentials of NGF in these diseases, including ocular and cutaneous diseases. Furthermore, NGF TrkA receptor antagonists emerged as novel drugs for pain, prostate and breast cancer, melanoma, and urinary bladder syndromes. Altogether, NGF's multiple potential in health and disease is briefly described here.

Morphomics: An integral part of systems biology of the human placenta.

PubMed

Mayhew, T M

2015-04-01

The placenta is a transient organ the functioning of which has health consequences far beyond the embryo/fetus. Understanding the biology of any system (organ, organism, single cell, etc) requires a comprehensive and inclusive approach which embraces all the biomedical disciplines and 'omic' technologies and then integrates information obtained from all of them. Among the latest 'omics' is morphomics. The terms morphome and morphomics have been applied incoherently in biology and biomedicine but, recently, they have been given clear and widescale definitions. Morphomics is placed in the context of other 'omics' and its pertinent technologies and tools for sampling and quantitation are reviewed. Emphasis is accorded to the importance of random sampling principles in systems biology and the value of combining 3D quantification with alternative imaging techniques to advance knowledge and understanding of the human placental morphome. By analogy to other 'omes', the morphome is the totality of morphological features within a system and morphomics is the systematic study of those structures. Information about structure is required at multiple levels of resolution in order to understand better the processes by which a given system alters with time, experimental treatment or environmental insult. Therefore, morphomics research includes all imaging techniques at all levels of achievable resolution from gross anatomy and medical imaging, via optical and electron microscopy, to molecular characterisation. Quantification is an important element of all 'omics' studies and, because biological systems exist and operate in 3-dimensional (3D) space, precise descriptions of form, content and spatial relationships require the quantification of structure in 3D. These considerations are relevant to future study contributions to the Human Placenta Project. Copyright © 2015 Elsevier Ltd. All rights reserved.

Integrative analysis of GWAS, eQTLs and meQTLs data suggests that multiple gene sets are associated with bone mineral density.

PubMed

Wang, W; Huang, S; Hou, W; Liu, Y; Fan, Q; He, A; Wen, Y; Hao, J; Guo, X; Zhang, F

2017-10-01

Several genome-wide association studies (GWAS) of bone mineral density (BMD) have successfully identified multiple susceptibility genes, yet isolated susceptibility genes are often difficult to interpret biologically. The aim of this study was to unravel the genetic background of BMD at pathway level, by integrating BMD GWAS data with genome-wide expression quantitative trait loci (eQTLs) and methylation quantitative trait loci (meQTLs) data METHOD: We employed the GWAS datasets of BMD from the Genetic Factors for Osteoporosis Consortium (GEFOS), analysing patients' BMD. The areas studied included 32 735 femoral necks, 28 498 lumbar spines, and 8143 forearms. Genome-wide eQTLs (containing 923 021 eQTLs) and meQTLs (containing 683 152 unique methylation sites with local meQTLs) data sets were collected from recently published studies. Gene scores were first calculated by summary data-based Mendelian randomisation (SMR) software and meQTL-aligned GWAS results. Gene set enrichment analysis (GSEA) was then applied to identify BMD-associated gene sets with a predefined significance level of 0.05. We identified multiple gene sets associated with BMD in one or more regions, including relevant known biological gene sets such as the Reactome Circadian Clock (GSEA p-value = 1.0 × 10 -4 for LS and 2.7 × 10 -2 for femoral necks BMD in eQTLs-based GSEA) and insulin-like growth factor receptor binding (GSEA p-value = 5.0 × 10 -4 for femoral necks and 2.6 × 10 -2 for lumbar spines BMD in meQTLs-based GSEA). Our results provided novel clues for subsequent functional analysis of bone metabolism, and illustrated the benefit of integrating eQTLs and meQTLs data into pathway association analysis for genetic studies of complex human diseases. Cite this article : W. Wang, S. Huang, W. Hou, Y. Liu, Q. Fan, A. He, Y. Wen, J. Hao, X. Guo, F. Zhang. Integrative analysis of GWAS, eQTLs and meQTLs data suggests that multiple gene sets are associated with bone mineral density. Bone Joint Res 2017;6:572-576. © 2017 Wang et al.

New evidence for therapies in stroke rehabilitation.

PubMed

Dobkin, Bruce H; Dorsch, Andrew

2013-06-01

Neurologic rehabilitation aims to reduce impairments and disabilities so that persons with serious stroke can return to participation in usual self-care and daily activities as independently as feasible. New strategies to enhance recovery draw from a growing understanding of how types of training, progressive task-related practice of skills, exercise for strengthening and fitness, neurostimulation, and drug and biological manipulations can induce adaptations at multiple levels of the nervous system. Recent clinical trials provide evidence for a range of new interventions to manage walking, reach and grasp, aphasia, visual field loss, and hemi-inattention.

Genetic variations in the serotonergic system contribute to amygdala volume in humans

PubMed Central

Li, Jin; Chen, Chunhui; Wu, Karen; Zhang, Mingxia; Zhu, Bi; Chen, Chuansheng; Moyzis, Robert K.; Dong, Qi

2015-01-01

The amygdala plays a critical role in emotion processing and psychiatric disorders associated with emotion dysfunction. Accumulating evidence suggests that amygdala structure is modulated by serotonin-related genes. However, there is a gap between the small contributions of single loci (less than 1%) and the reported 63–65% heritability of amygdala structure. To understand the “missing heritability,” we systematically explored the contribution of serotonin genes on amygdala structure at the gene set level. The present study of 417 healthy Chinese volunteers examined 129 representative polymorphisms in genes from multiple biological mechanisms in the regulation of serotonin neurotransmission. A system-level approach using multiple regression analyses identified that nine SNPs collectively accounted for approximately 8% of the variance in amygdala volume. Permutation analyses showed that the probability of obtaining these findings by chance was low (p = 0.043, permuted for 1000 times). Findings showed that serotonin genes contribute moderately to individual differences in amygdala volume in a healthy Chinese sample. These results indicate that the system-level approach can help us to understand the genetic basis of a complex trait such as amygdala structure. PMID:26500508

A multispecies framework for landscape conservation planning.

PubMed

Schwenk, W Scott; Donovan, Therese M

2011-10-01

Rapidly changing landscapes have spurred the need for quantitative methods for conservation assessment and planning that encompass large spatial extents. We devised and tested a multispecies framework for conservation planning to complement single-species assessments and ecosystem-level approaches. Our framework consisted of 4 elements: sampling to effectively estimate population parameters, measuring how human activity affects landscapes at multiple scales, analyzing the relation between landscape characteristics and individual species occurrences, and evaluating and comparing the responses of multiple species to landscape modification. We applied the approach to a community of terrestrial birds across 25,000 km(2) with a range of intensities of human development. Human modification of land cover, road density, and other elements of the landscape, measured at multiple spatial extents, had large effects on occupancy of the 67 species studied. Forest composition within 1 km of points had a strong effect on occupancy of many species and a range of negative, intermediate, and positive associations. Road density within 1 km of points, percent evergreen forest within 300 m, and distance from patch edge were also strongly associated with occupancy for many species. We used the occupancy results to group species into 11 guilds that shared patterns of association with landscape characteristics. Our multispecies approach to conservation planning allowed us to quantify the trade-offs of different scenarios of land-cover change in terms of species occupancy. Conservation Biology © 2011 Society for Conservation Biology. No claim to original US government works.

Genome-Level Longitudinal Expression of Signaling Pathways and Gene Networks in Pediatric Septic Shock

PubMed Central

Shanley, Thomas P; Cvijanovich, Natalie; Lin, Richard; Allen, Geoffrey L; Thomas, Neal J; Doctor, Allan; Kalyanaraman, Meena; Tofil, Nancy M; Penfil, Scott; Monaco, Marie; Odoms, Kelli; Barnes, Michael; Sakthivel, Bhuvaneswari; Aronow, Bruce J; Wong, Hector R

2007-01-01

We have conducted longitudinal studies focused on the expression profiles of signaling pathways and gene networks in children with septic shock. Genome-level expression profiles were generated from whole blood-derived RNA of children with septic shock (n = 30) corresponding to day one and day three of septic shock, respectively. Based on sequential statistical and expression filters, day one and day three of septic shock were characterized by differential regulation of 2,142 and 2,504 gene probes, respectively, relative to controls (n = 15). Venn analysis demonstrated 239 unique genes in the day one dataset, 598 unique genes in the day three dataset, and 1,906 genes common to both datasets. Functional analyses demonstrated time-dependent, differential regulation of genes involved in multiple signaling pathways and gene networks primarily related to immunity and inflammation. Notably, multiple and distinct gene networks involving T cell- and MHC antigen-related biology were persistently downregulated on both day one and day three. Further analyses demonstrated large scale, persistent downregulation of genes corresponding to functional annotations related to zinc homeostasis. These data represent the largest reported cohort of patients with septic shock subjected to longitudinal genome-level expression profiling. The data further advance our genome-level understanding of pediatric septic shock and support novel hypotheses. PMID:17932561

Multiple time-scales and the developmental dynamics of social systems

PubMed Central

Flack, Jessica C.

2012-01-01

To build a theory of social complexity, we need to understand how aggregate social properties arise from individual interaction rules. Here, I review a body of work on the developmental dynamics of pigtailed macaque social organization and conflict management that provides insight into the mechanistic causes of multi-scale social systems. In this model system coarse-grained, statistical representations of collective dynamics are more predictive of the future state of the system than the constantly in-flux behavioural patterns at the individual level. The data suggest that individuals can perceive and use these representations for strategical decision-making. As an interaction history accumulates the coarse-grained representations consolidate. This constrains individual behaviour and provides the foundations for new levels of organization. The time-scales on which these representations change impact whether the consolidating higher-levels can be modified by individuals and collectively. The time-scales appear to be a function of the ‘coarseness’ of the representations and the character of the collective dynamics over which they are averages. The data suggest that an advantage of multiple timescales is that they allow social systems to balance tradeoffs between predictability and adaptability. I briefly discuss the implications of these findings for cognition, social niche construction and the evolution of new levels of organization in biological systems. PMID:22641819

Multiple time-scales and the developmental dynamics of social systems.

PubMed

Flack, Jessica C

2012-07-05

To build a theory of social complexity, we need to understand how aggregate social properties arise from individual interaction rules. Here, I review a body of work on the developmental dynamics of pigtailed macaque social organization and conflict management that provides insight into the mechanistic causes of multi-scale social systems. In this model system coarse-grained, statistical representations of collective dynamics are more predictive of the future state of the system than the constantly in-flux behavioural patterns at the individual level. The data suggest that individuals can perceive and use these representations for strategical decision-making. As an interaction history accumulates the coarse-grained representations consolidate. This constrains individual behaviour and provides the foundations for new levels of organization. The time-scales on which these representations change impact whether the consolidating higher-levels can be modified by individuals and collectively. The time-scales appear to be a function of the 'coarseness' of the representations and the character of the collective dynamics over which they are averages. The data suggest that an advantage of multiple timescales is that they allow social systems to balance tradeoffs between predictability and adaptability. I briefly discuss the implications of these findings for cognition, social niche construction and the evolution of new levels of organization in biological systems.

Integrative Exploratory Analysis of Two or More Genomic Datasets.

PubMed

Meng, Chen; Culhane, Aedin

2016-01-01

Exploratory analysis is an essential step in the analysis of high throughput data. Multivariate approaches such as correspondence analysis (CA), principal component analysis, and multidimensional scaling are widely used in the exploratory analysis of single dataset. Modern biological studies often assay multiple types of biological molecules (e.g., mRNA, protein, phosphoproteins) on a same set of biological samples, thereby creating multiple different types of omics data or multiassay data. Integrative exploratory analysis of these multiple omics data is required to leverage the potential of multiple omics studies. In this chapter, we describe the application of co-inertia analysis (CIA; for analyzing two datasets) and multiple co-inertia analysis (MCIA; for three or more datasets) to address this problem. These methods are powerful yet simple multivariate approaches that represent samples using a lower number of variables, allowing a more easily identification of the correlated structure in and between multiple high dimensional datasets. Graphical representations can be employed to this purpose. In addition, the methods simultaneously project samples and variables (genes, proteins) onto the same lower dimensional space, so the most variant variables from each dataset can be selected and associated with samples, which can be further used to facilitate biological interpretation and pathway analysis. We applied CIA to explore the concordance between mRNA and protein expression in a panel of 60 tumor cell lines from the National Cancer Institute. In the same 60 cell lines, we used MCIA to perform a cross-platform comparison of mRNA gene expression profiles obtained on four different microarray platforms. Last, as an example of integrative analysis of multiassay or multi-omics data we analyzed transcriptomic, proteomic, and phosphoproteomic data from pluripotent (iPS) and embryonic stem (ES) cell lines.

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).

The functional cancer map: a systems-level synopsis of genetic deregulation in cancer.

PubMed

Krupp, Markus; Maass, Thorsten; Marquardt, Jens U; Staib, Frank; Bauer, Tobias; König, Rainer; Biesterfeld, Stefan; Galle, Peter R; Tresch, Achim; Teufel, Andreas

2011-06-30

Cancer cells are characterized by massive dysegulation of physiological cell functions with considerable disruption of transcriptional regulation. Genome-wide transcriptome profiling can be utilized for early detection and molecular classification of cancers. Accurate discrimination of functionally different tumor types may help to guide selection of targeted therapy in translational research. Concise grouping of tumor types in cancer maps according to their molecular profile may further be helpful for the development of new therapeutic modalities or open new avenues for already established therapies. Complete available human tumor data of the Stanford Microarray Database was downloaded and filtered for relevance, adequacy and reliability. A total of 649 tumor samples from more than 1400 experiments and 58 different tissues were analyzed. Next, a method to score deregulation of KEGG pathway maps in different tumor entities was established, which was then used to convert hundreds of gene expression profiles into corresponding tumor-specific pathway activity profiles. Based on the latter, we defined a measure for functional similarity between tumor entities, which yielded to phylogeny of tumors. We provide a comprehensive, easy-to-interpret functional cancer map that characterizes tumor types with respect to their biological and functional behavior. Consistently, multiple pathways commonly associated with tumor progression were revealed as common features in the majority of the tumors. However, several pathways previously not linked to carcinogenesis were identified in multiple cancers suggesting an essential role of these pathways in cancer biology. Among these pathways were 'ECM-receptor interaction', 'Complement and Coagulation cascades', and 'PPAR signaling pathway'. The functional cancer map provides a systematic view on molecular similarities across different cancers by comparing tumors on the level of pathway activity. This work resulted in identification of novel superimposed functional pathways potentially linked to cancer biology. Therefore, our work may serve as a starting point for rationalizing combination of tumor therapeutics as well as for expanding the application of well-established targeted tumor therapies.

Microbiome studies in the biological control of plant pathogens

USDA-ARS?s Scientific Manuscript database

Biological control of plant pathogens, although it has been a successful alternative that has allowed to select microorganisms for the generation of bioproducts and to understand multiple biological mechanisms, cannot be considered as a strategy defined only from the selection of a range of cultiva...

Detection of biomolecules in complex media using surface plasmon resonance sensors

NASA Astrophysics Data System (ADS)

Malone, Michael R.; Masson, Jean-Francois; Barhnart, Margaret; Beaudoin, Stephen; Booksh, Karl S.

2005-11-01

Detection of multiple biologically relevant molecules was accomplished at sub-ng/mL levels in highly fouling media using fiber- optic based surface plasmon resonance sensors. Myocardial infarction markers, myoglobin and cTnI, were quantified in full serum with limits of detection below 1 ng/mL. Biologically relevant levels are between 15-30 ng/mL and 1-5 ng/mL for myoglobin and cTnI respectively. Cytokines involved in chronic wound healing, Interleukin 1, Interleukin 6, and tumor necrosis factor α, were detected at around 1 ng/mL in cell culture media. Preliminary results in monitoring these cytokines in cell cultures expressing the cytokines were obtained. The protein diagnostic of spinal muscular atrophy, survival motor neuron protein, was quantified from cell lysate. To obtain such results in complex media, the sensor's stability to non-specific protein adsorption had to be optimized. A layer of the N-hydroxysuccinimide ester of 16-mercaptohexadecanoic acid is attached to the sensor. This layer optimizes the antibody attachment to the sensor while minimizing the non-specific signal from serum proteins.

Life away from the coverslip. Comment on "Extracting physics of life at the molecular level: A review of single-molecule data analyses" by W. Colomb and S.K. Sarkar

NASA Astrophysics Data System (ADS)

Shepherd, Douglas

2015-06-01

Understanding how a population acts based on the collective actions of individuals is a long-standing challenge across all scientific fields. Over the last twenty years, a revolution in the detection of individual fluorescent molecules has brought together scientists from multiple fields, particularly with respect to imaging applications in cellular and microbiology [1-3]. Recently, new techniques have paved the way for sub-diffraction limit imaging of biological regulation in fixed and live cells, generating a wealth of new data [4-9]. However, this explosion in our ability to generate information on biology at the single-molecule level has so far outpaced our ability to robustly analyze, test, and understand what these experiments are actually reporting [10-12]. Because there are many sources of noise in these experiments, ranging from instrumental to stochastic chemical reactions, it is important to understand each source of noise and how to utilize it. In this sense, there is information in all the fluctuations that occur in these experiments.

Role of socio-economic and reproductive factors in the risk of multiple sclerosis.

PubMed

Magyari, M

2015-01-01

The incidence of multiple sclerosis is increasing in Danish women. Their risk of developing multiple sclerosis has more than doubled in 25 years while it has remained virtually unchanged for men. The explanation for these epidemiological changes should be sought in the environment as they are too rapid to be explained by gene alterations. We investigated the effect of numerous biological social physical and chemical environmental exposures in different periods of life. These data were available from population-based registries and were used in a case-control approach. This study database included all multiple sclerosis cases (n = 1403) from the Danish MS Registry with clinical onset between 2000 and 2004 as well as 35,045 controls drawn by random from the Danish Civil Registration System and matched by sex year of birth and residential municipality at the reference year. Having newborn children reduced the risk of multiple sclerosis (MS) in women but not in men. Childbirths reduced the risk of MS by about 46% during the following 5 years. Even pregnancies terminated early had a protective effect on the risk of developing MS suggesting a temporary immunosuppression during pregnancy. Our data on social behaviour regarding educational level income and relationship stability did not indicate reverse causality. A greater likelihood to be exposed to common infections did not show any effect on the risk of MS neither in puberty nor in adulthood. Socio-economic status and lifestyle expressed in educational level and sanitary conditions in youth were not associated with the risk of MS. © 2015 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Toward applied behavior analysis of life aloft

NASA Technical Reports Server (NTRS)

Brady, J. V.

1990-01-01

This article deals with systems at multiple levels, at least from cell to organization. It also deals with learning, decision making, and other behavior at multiple levels. Technological development of a human behavioral ecosystem appropriate to space environments requires an analytic and synthetic orientation, explicitly experimental in nature, dictated by scientific and pragmatic considerations, and closely approximating procedures of established effectiveness in other areas of natural science. The conceptual basis of such an approach has its roots in environmentalism which has two main features: (1) knowledge comes from experience rather than from innate ideas, divine revelation, or other obscure sources; and (2) action is governed by consequences rather than by instinct, reason, will, beliefs, attitudes or even the currently fashionable cognitions. Without an experimentally derived data base founded upon such a functional analysis of human behavior, the overgenerality of "ecological systems" approaches render them incapable of ensuring the successful establishment of enduring space habitats. Without an experimentally derived function account of individual behavioral variability, a natural science of behavior cannot exist. And without a natural science of behavior, the social sciences will necessarily remain in their current status as disciplines of less than optimal precision or utility. Such a functional analysis of human performance should provide an operational account of behavior change in a manner similar to the way in which Darwin's approach to natural selection accounted for the evolution of phylogenetic lines (i.e., in descriptive, nonteleological terms). Similarly, as Darwin's account has subsequently been shown to be consonant with information obtained at the cellular level, so too should behavior principles ultimately prove to be in accord with an account of ontogenetic adaptation at a biochemical level. It would thus seem obvious that the most productive conceptual and methodological approaches to long-term research investments focused upon human behavior in space environments will require multidisciplinary inputs from such wide-ranging fields as molecular biology, environmental physiology, behavioral biology, architecture, sociology, and political science, among others.

Studying Soft-matter and Biological Systems over a Wide Length-scale from Nanometer and Micrometer Sizes at the Small-angle Neutron Diffractometer KWS-2

PubMed Central

Radulescu, Aurel; Szekely, Noemi Kinga; Appavou, Marie-Sousai; Pipich, Vitaliy; Kohnke, Thomas; Ossovyi, Vladimir; Staringer, Simon; Schneider, Gerald J.; Amann, Matthias; Zhang-Haagen, Bo; Brandl, Georg; Drochner, Matthias; Engels, Ralf; Hanslik, Romuald; Kemmerling, Günter

2016-01-01

The KWS-2 SANS diffractometer is dedicated to the investigation of soft matter and biophysical systems covering a wide length scale, from nm to µm. The instrument is optimized for the exploration of the wide momentum transfer Q range between 1x10-4 and 0.5 Å-1 by combining classical pinhole, focusing (with lenses), and time-of-flight (with chopper) methods, while simultaneously providing high-neutron intensities with an adjustable resolution. Because of its ability to adjust the intensity and the resolution within wide limits during the experiment, combined with the possibility to equip specific sample environments and ancillary devices, the KWS-2 shows a high versatility in addressing the broad range of structural and morphological studies in the field. Equilibrium structures can be studied in static measurements, while dynamic and kinetic processes can be investigated over time scales between minutes to tens of milliseconds with time-resolved approaches. Typical systems that are investigated with the KWS-2 cover the range from complex, hierarchical systems that exhibit multiple structural levels (e.g., gels, networks, or macro-aggregates) to small and poorly-scattering systems (e.g., single polymers or proteins in solution). The recent upgrade of the detection system, which enables the detection of count rates in the MHz range, opens new opportunities to study even very small biological morphologies in buffer solution with weak scattering signals close to the buffer scattering level at high Q. In this paper, we provide a protocol to investigate samples with characteristic size levels spanning a wide length scale and exhibiting ordering in the mesoscale structure using KWS-2. We present in detail how to use the multiple working modes that are offered by the instrument and the level of performance that is achieved. PMID:28060296

[A complexity analysis of Chinese herbal property theory: the multiple expressions of herbal property].

PubMed

Jin, Rui; Zhang, Bing

2012-12-01

Chinese herbal property is the highly summarized concept of herbal nature and pharmaceutical effect, which reflect the characteristics of herbal actions on human body. These herbal actions, also interpreted as presenting the information about pharmaceutical effect contained in herbal property on the biological carrier, are defined as herbal property expressions. However, the biological expression of herbal property is believed to possess complex features for the involved complexity of Chinese medicine and organism. Firstly, there are multiple factors which could influence the expression results of herbal property such as the growth environment, harvest season and preparing methods of medicinal herbs, and physique and syndrome of body. Secondly, there are multiple biological approaches and biochemical indicators for the expression of the same property. This paper elaborated these complexities for further understanding of herbal property. The individuality of herbs and expression factors should be well analyzed in the related studies.

Diversity in Pathways to Common Childhood Disruptive Behavior Disorders

PubMed Central

Martel, Michelle M.; Nikolas, Molly; Jernigan, Katherine; Friderici, Karen; Nigg, Joel T.

2014-01-01

Oppositional-Defiant Disorder (ODD) and Attention-Deficit/Hyperactivity Disorder (ADHD) are highly comorbid, a phenomenon thought to be due to shared etiological factors and mechanisms. Little work has attempted to chart multiple-level-of-analysis pathways (i.e., simultaneously including biological, environmental, and trait influences) to ODD and ADHD, the goal of the present investigation. 559 children/adolescents (325 boys) between the ages of 6 and 18 participated in a multi-stage, comprehensive diagnostic procedure. 148 were classified as ODD; 309 were classified as ADHD, based on parent, teacher, and clinician ratings. Children provided buccal or salivary samples of DNA, assayed for select markers in DRD4 and 5HTT. Parents completed the Alabama Parenting Questionnaire and the California Q-Sort. Children completed the Child Perception of Interparental Conflict Scale. Correlational associations consistent with multiple-level-of-analysis pathways to ODD and ADHD emerged. For ODD, children with the short allele of the 5HTT promoter polymorphism had higher neuroticism and ODD symptoms regardless of level of self-blame in relation to inter-parental conflict, whereas children without this allele had more ODD symptoms only in the context of more self-blame for inter-parental conflict. For ADHD (and ODD), children homozygous for the long allele of DRD4 120bp insertion polymorphism had lower conscientiousness when exposed to inconsistent parenting, whereas children without this genotype were more resilient to effects of inconsistent discipline on conscientiousness. Thus, ODD and ADHD appear to demonstrate somewhat distinct correlational associations between etiological factors and mechanisms consistent with pathway models using a multiple-level-of-analysis approach. PMID:22584505

[Overexpression of four fatty acid synthase genes elevated the efficiency of long-chain polyunsaturated fatty acids biosynthesis in mammalian cells].

PubMed

Zhu, Guiming; Saleh, Abdulmomen Ali Mohammed; Bahwal, Said Ahmed; Wang, Kunfu; Wang, Mingfu; Wang, Didi; Ge, Tangdong; Sun, Jie

2014-09-01

Three long-chain polyunsaturated fatty acids, docosahexaenoic acid (DHA, 22:6n-3), eicosapentaenoic acid (EPA, 20:5n-3) and arachidonic acid (ARA, 20:4n-6), are the most biologically active polyunsaturated fatty acids in the body. They are important in developing and maintaining the brain function, and in preventing and treating many diseases such as cardiovascular disease, inflammation and cancer. Although mammals can biosynthesize these long-chain polyunsaturated fatty acids, the efficiency is very low and dietary intake is needed to meet the requirement. In this study, a multiple-genes expression vector carrying mammalian A6/A5 fatty acid desaturases and multiple-genes expression vector carrying mammalian Δ6/Δ5 fatty acid desaturases and Δ6/Δ5 fatty acid elongases coding genes was used to transfect HEK293T cells, then the overexpression of the target genes was detected. GC-MS analysis shows that the biosynthesis efficiency and level of DHA, EPA and ARA were significantly increased in cells transfected with the multiple-genes expression vector. Particularly, DHA level in these cells was 2.5 times higher than in the control cells. This study indicates mammal possess a certain mechanism for suppression of high level of biosynthesis of long chain polyunsaturated fatty acids, and the overexpression of Δ6/Δ5 fatty acid desaturases and Δ6/Δ5 fatty acid elongases broke this suppression mechanism so that the level of DHA, EPA and ARA was significantly increased. This study also provides a basis for potential applications of this gene construct in transgenic animal to produce high level of these long-chain polyunsaturated fatty acid.

Rig-I regulates NF-κB activity through binding to Nf-κb1 3′-UTR mRNA

PubMed Central

Zhang, Hong-Xin; Liu, Zi-Xing; Sun, Yue-Ping; Lu, Shun-Yuan; Liu, Xue-Song; Huang, Qiu-Hua; Xie, Yin-Yin; Dang, Su-Ying; Zheng, Guang-Yong; Li, Yi-Xue; Kuang, Ying; Fei, Jian; Chen, Zhu; Wang, Zhu-Gang

2013-01-01

Retinoic acid inducible gene I (RIG-I) senses viral RNAs and triggers innate antiviral responses through induction of type I IFNs and inflammatory cytokines. However, whether RIG-I interacts with host cellular RNA remains undetermined. Here we report that Rig-I interacts with multiple cellular mRNAs, especially Nf-κb1. Rig-I is required for NF-κB activity via regulating Nf-κb1 expression at posttranscriptional levels. It interacts with the multiple binding sites within 3′-UTR of Nf-κb1 mRNA. Further analyses reveal that three distinct tandem motifs enriched in the 3′-UTR fragments can be recognized by Rig-I. The 3′-UTR binding with Rig-I plays a critical role in normal translation of Nf-κb1 by recruiting the ribosomal proteins [ribosomal protein L13 (Rpl13) and Rpl8] and rRNAs (18S and 28S). Down-regulation of Rig-I or Rpl13 significantly reduces Nf-κb1 and 3′-UTR–mediated luciferase expression levels. These findings indicate that Rig-I functions as a positive regulator for NF-κB signaling and is involved in multiple biological processes in addition to host antivirus immunity. PMID:23553835

Serum dehydroepiandrosterone (DHEA) and DHEA-sulfate (S) levels in medicated patients with major depressive disorder compared with controls.

PubMed

Kurita, Hirofumi; Maeshima, Hitoshi; Kida, Sayaka; Matsuzaka, Hisashi; Shimano, Takahisa; Nakano, Yoshiyuki; Baba, Hajime; Suzuki, Toshihito; Arai, Heii

2013-04-05

There is accumulating evidence regarding gender differences in clinical symptoms or response to antidepressants in patients with depression. However, less attention has been given to sex differences in the underlying biological mechanisms of depression. The adrenal androgens, dehydroepiandrosterone (DHEA) and its sulfate derivative (DHEA-S), play a critical role in controlling affect, mood, and anxiety. Changes in serum adrenal androgen levels have been reported in conditions pertaining to stress as well as in psychiatric disorders. The objective of the present study was to investigate differences in serum levels of adrenal androgens in male and female patients with major depressive disorder (MDD). Participants included 90 inpatients with MDD at the psychiatric ward of Juntendo University Koshigaya Hospital who were receiving antidepressants. Serum levels of DHEA and DHEA-S were assessed at the time of admission. Matched controls (based on sex and age) included 128 healthy individuals. First, data from male and female MDD patients and controls were compared. Second, correlations between serum hormone levels and scores on the Hamilton Rating Scale for Depression (HAM-D) of patients with MDD were assessed by gender. In addition, effects of various factors on adrenal androgens were analyzed using multiple regression analysis. Serum DHEA levels were significantly increased in both male and female MDD patients compared with controls. Serum levels of DHEA-S in male patients were significantly decreased compared with male controls, whereas no significant differences were seen in female patients and controls. No significant correlations among adrenal androgens were observed in male patients with MDD, whereas significant positive correlations were found in both male and female controls. No significant correlations were seen between adrenal androgens and HAM-D scores in male or female patients. Multiple regression analysis showed that both hormones were affected by the age at onset of depression. All subjects in the present study were on antidepressant medications. Elevated levels of serum DHEA may be associated with the biological pathophysiology of depression, as DHEA administration has been found to be effective for the treatment of depression. Findings of differential changes in DHEA-S levels in men compared with women may suggest distinct characteristics of these hormones between men and women with depression. However, DHEA/DHEA-S may be a poor indicator for evaluating severity of depression. Copyright © 2012 Elsevier B.V. All rights reserved.

Copper and ceruloplasmin dyshomeostasis in serum and cerebrospinal fluid of multiple sclerosis subjects.

PubMed

De Riccardis, L; Buccolieri, A; Muci, M; Pitotti, E; De Robertis, F; Trianni, G; Manno, D; Maffia, M

2018-05-01

Although many studies have been carried out in order to understand the implication of copper (Cu) in the pathogenesis of multiple sclerosis (MS), the exact role that this metal plays in the disease is not still clear. Because of the lack of information in this subject, the present study compared the serum and cerebrospinal (CSF) levels of copper in MS patients in respect to a control group, matched for age and sex, finding a significant increase of metal concentrations, in both biological fluids of MS subjects. To confirm the possible impairment of Cu metabolism, we analyzed ceruloplasmin (Cp) level and activity, seeing as this protein is an established peripheral marker in diseases associated with Cu imbalance. By comparing these two parameters between control and MS subjects, we found an increase of Cp levels, associated with a decrease in Cp activity, in the second group. By analysing these data, free copper levels were calculated, significantly increased in serum of MS subjects; the increase in free copper could be one of the predisposing factors responsible for the Cu altered levels in CSF of MS patients. At the same time, this alteration could be attributable to the inability to incorporate Cu by Cp, probably due to the high oxidative environment found in serum of MS patients. Overall, all these copper alterations may play a role in MS pathogenesis. Copyright © 2018 Elsevier B.V. All rights reserved.

A Diagnostic Assessment for Introductory Molecular and Cell Biology

ERIC Educational Resources Information Center

Shi, Jia; Wood, William B.; Martin, Jennifer M.; Guild, Nancy A.; Vicens, Quentin; Knight, Jennifer K.

2010-01-01

We have developed and validated a tool for assessing understanding of a selection of fundamental concepts and basic knowledge in undergraduate introductory molecular and cell biology, focusing on areas in which students often have misconceptions. This multiple-choice Introductory Molecular and Cell Biology Assessment (IMCA) instrument is designed…

Biological auctions with multiple rewards

PubMed Central

Reiter, Johannes G.; Kanodia, Ayush; Gupta, Raghav; Nowak, Martin A.; Chatterjee, Krishnendu

2015-01-01

The competition for resources among cells, individuals or species is a fundamental characteristic of evolution. Biological all-pay auctions have been used to model situations where multiple individuals compete for a single resource. However, in many situations multiple resources with various values exist and single reward auctions are not applicable. We generalize the model to multiple rewards and study the evolution of strategies. In biological all-pay auctions the bid of an individual corresponds to its strategy and is equivalent to its payment in the auction. The decreasingly ordered rewards are distributed according to the decreasingly ordered bids of the participating individuals. The reproductive success of an individual is proportional to its fitness given by the sum of the rewards won minus its payments. Hence, successful bidding strategies spread in the population. We find that the results for the multiple reward case are very different from the single reward case. While the mixed strategy equilibrium in the single reward case with more than two players consists of mostly low-bidding individuals, we show that the equilibrium can convert to many high-bidding individuals and a few low-bidding individuals in the multiple reward case. Some reward values lead to a specialization among the individuals where one subpopulation competes for the rewards and the other subpopulation largely avoids costly competitions. Whether the mixed strategy equilibrium is an evolutionarily stable strategy (ESS) depends on the specific values of the rewards. PMID:26180069

Beneficial metabolic effects of 2', 3', 5'-tri-acetyl-N6-(3-hydroxylaniline) adenosine in multiple biological matrices and intestinal flora of hyperlipidemic hamsters.

PubMed

Li, Tianqi; Sun, Shanshan; Zhang, Jinyue; Qu, Kai; Yang, Liu; Ma, Changlu; Jin, Xiangju; Zhu, Haibo; Wang, Yinghong

2018-06-21

ABSTRACT：Hyperlipidemia is one of the main causes of obesity, type 2 diabetes mellitus (T2DM) and atherosclerosis. The adenosine derivative, 2', 3', 5'-tri-acetyl-N6-(3-hydroxylaniline) adenosine (IMM-H007) is an effective lipid-lowering compound that has important implications for the development of lipid-lowering drugs. Metabolomic analysis based on 1H-NMR was used to monitor dynamic changes in diverse biological media including serum, liver, urine, and feces in response to high-fat diet (HFD) and IMM-H007 treatments. Ultra-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) and gas chromatography (GC) analyses were performed to quantify the bile acids and fatty acids in the liver and feces. Fecal microbiome profiling was performed using Illumina sequencing of the 16S ribosomal RNA (16S rRNA) gene. IMM-H007 improved the metabolism of carbohydrate, ketone bodies, fatty acids, amino acids and bile acids in hyperlipidemic hamsters. The correlation between metabolite changes was explored in different biological media. Significant changes in gut microbiota were observed in the HFD and IMM-H007 treatment groups. In the HFD group at the phylum level, we found high levels of the Firmicutes genus and low levels of Bacteroidetes. In contrast, the administration of IMM-H007 reversed the levels of Firmicutes and Bacteroidetes. This reversal suggested that IMM-H007 may have the ability to regulate the composition of the gut flora. We also analyzed the correlation between the gut flora and the metabolites. Our results indicate that IMM-H007 treatment improves the hyperlipidemic metabolism and the structure of the gut microbiota in hyperlipidemic hamsters.

Application of the Red-List Index at a national level for multiple species groups.

PubMed

Juslén, Aino; Hyvärinen, Esko; Virtanen, Laura K

2013-04-01

The International Union for Conservation of Nature (IUCN) Red List Index (RLI) is recognized as one of the key indicators of trends in the status of species. The red-list assessment done by Finnish authorities of species in Finland is taxonomically one of the most extensive national assessments. We used the Finnish Red Lists from 2000 and 2010 to calculate for the first time the national RLIs for 11 taxonomic groups at different trophic levels and with different life cycles. The red-list index is calculated on the basis of changes in red-list categories and indicates trends in the status of biological diversity of sets of species. The RLI value ranges from 0 to 1. The lower the value the faster the set of species is heading toward extinction. If the value is 1, all species in the set are least concern and if the value is 0, all species are (regionally) extinct. The overall RLI of Finnish species decreased. This means that, in Finland, these taxonomic groups were heading toward extinction faster in 2010 than in 2000. Of the analyzed groups of organisms, RLIs of 5 decreased and RLIs of 6 increased. At the national level, the RLIs and status trends varied markedly between species groups. Thus, we concluded that generalizations on the basis of RLIs of a few taxa only may yield a biased view of ongoing trends in the status of biological diversity at the species level. In addition, one overall RLI that includes many different species groups may also be misleading if variation in RLI among species groups is not considered and if RLI values are not presented separately for each group. © 2013 Society for Conservation Biology.

Allostatic load and biological anthropology.

PubMed

Edes, Ashley N; Crews, Douglas E

2017-01-01

Multiple stressors affect developing and adult organisms, thereby partly structuring their phenotypes. Determining how stressors influence health, well-being, and longevity in human and nonhuman primate populations are major foci within biological anthropology. Although much effort has been devoted to examining responses to multiple environmental and sociocultural stressors, no holistic metric to measure stress-related physiological dysfunction has been widely applied within biological anthropology. Researchers from disciplines outside anthropology are using allostatic load indices (ALIs) to estimate such dysregulation and examine life-long outcomes of stressor exposures, including morbidity and mortality. Following allostasis theory, allostatic load represents accumulated physiological and somatic damage secondary to stressors and senescent processes experienced over the lifespan. ALIs estimate this wear-and-tear using a composite of biomarkers representing neuroendocrine, cardiovascular, metabolic, and immune systems. Across samples, ALIs are associated significantly with multiple individual characteristics (e.g., age, sex, education, DNA variation) of interest within biological anthropology. They also predict future outcomes, including aspects of life history variation (e.g., survival, lifespan), mental and physical health, morbidity and mortality, and likely health disparities between groups, by stressor exposures, ethnicity, occupations, and degree of departure from local indigenous life ways and integration into external and commodified ones. ALIs also may be applied to similar stress-related research areas among nonhuman primates. Given the reports from multiple research endeavors, here we propose ALIs may be useful for assessing stressors, stress responses, and stress-related dysfunction, current and long-term cognitive function, health and well-being, and risk of early mortality across many research programs within biological anthropology. © 2017 American Association of Physical Anthropologists.

Journal entries facilitating preprofessional scientific literacy and mutualistic symbiotic relationships

NASA Astrophysics Data System (ADS)

Vander Vliet, Valerie J.

This study explored journal writing as an alternative assessment to promote the development of pre-professional scientific literacy and mutualistic symbiotic relationships between teaching and learning, instruction and assessment, and students and teachers. The larger context of this study is an action reaction project of the attempted transformation of a traditional first year undergraduate pre-professional biology class to sociocultural constructivist principles. The participants were commuter and residential, full and part-time students ranging in age from 18 to 27 and 18/21 were female. The backgrounds of the students varied considerably, ranging from low to upper middle income, including students of Black and Asian heritage. The setting was a medium-sized Midwestern university. The instructor has twenty years of experience teaching Biology at the college level. The data were analyzed using the constant comparative method and the development of grounded theory. The journal entries were analyzed as to their function and form in relationship to the development of multiple aspects of pre-professional scientific literacy. The perceptions of the students as to the significance of the use of journal entries were also determined through the analysis of their use of journal entries in their portfolios and statements in surveys and portfolios. The analysis revealed that journal entries promoted multiple aspects of pre-professional scientific literacy in both students and the instructor and facilitated the development of mutualistic symbiotic relationships between teaching and learning, instruction and assessment, and students and teachers. The function analysis revealed that the journal entries fulfilled the functions intended for the development of multiple aspects of pre-professional scientific literacy. The complexity of journal writing emerged from the form analysis, which revealed the multiple form elements inherent in journal entries. Students perceived journal entries to act as cognitive, affective, and social catalysts of pre-professional scientific literacy. This study has shown that journal entries facilitate the development of multiple aspects of scientific literacy and mutualistic symbiotic relationships between teaching and learning, instruction and assessment, and students and teachers.

Assembly of micro/nanomaterials into complex, three-dimensional architectures by compressive buckling

NASA Astrophysics Data System (ADS)

Xu, Sheng; Yan, Zheng; Jang, Kyung-In; Huang, Wen; Fu, Haoran; Kim, Jeonghyun; Wei, Zijun; Flavin, Matthew; McCracken, Joselle; Wang, Renhan; Badea, Adina; Liu, Yuhao; Xiao, Dongqing; Zhou, Guoyan; Lee, Jungwoo; Chung, Ha Uk; Cheng, Huanyu; Ren, Wen; Banks, Anthony; Li, Xiuling; Paik, Ungyu; Nuzzo, Ralph G.; Huang, Yonggang; Zhang, Yihui; Rogers, John A.

2015-01-01

Complex three-dimensional (3D) structures in biology (e.g., cytoskeletal webs, neural circuits, and vasculature networks) form naturally to provide essential functions in even the most basic forms of life. Compelling opportunities exist for analogous 3D architectures in human-made devices, but design options are constrained by existing capabilities in materials growth and assembly. We report routes to previously inaccessible classes of 3D constructs in advanced materials, including device-grade silicon. The schemes involve geometric transformation of 2D micro/nanostructures into extended 3D layouts by compressive buckling. Demonstrations include experimental and theoretical studies of more than 40 representative geometries, from single and multiple helices, toroids, and conical spirals to structures that resemble spherical baskets, cuboid cages, starbursts, flowers, scaffolds, fences, and frameworks, each with single- and/or multiple-level configurations.

Airplane detection based on fusion framework by combining saliency model with Deep Convolutional Neural Networks

NASA Astrophysics Data System (ADS)

Dou, Hao; Sun, Xiao; Li, Bin; Deng, Qianqian; Yang, Xubo; Liu, Di; Tian, Jinwen

2018-03-01

Aircraft detection from very high resolution remote sensing images, has gained more increasing interest in recent years due to the successful civil and military applications. However, several problems still exist: 1) how to extract the high-level features of aircraft; 2) locating objects within such a large image is difficult and time consuming; 3) A common problem of multiple resolutions of satellite images still exists. In this paper, inspirited by biological visual mechanism, the fusion detection framework is proposed, which fusing the top-down visual mechanism (deep CNN model) and bottom-up visual mechanism (GBVS) to detect aircraft. Besides, we use multi-scale training method for deep CNN model to solve the problem of multiple resolutions. Experimental results demonstrate that our method can achieve a better detection result than the other methods.

Systems-level mechanisms of action of Panax ginseng: a network pharmacological approach.

PubMed

Park, Sa-Yoon; Park, Ji-Hun; Kim, Hyo-Su; Lee, Choong-Yeol; Lee, Hae-Jeung; Kang, Ki Sung; Kim, Chang-Eop

2018-01-01

Panax ginseng has been used since ancient times based on the traditional Asian medicine theory and clinical experiences, and currently, is one of the most popular herbs in the world. To date, most of the studies concerning P. ginseng have focused on specific mechanisms of action of individual constituents. However, in spite of many studies on the molecular mechanisms of P. ginseng , it still remains unclear how multiple active ingredients of P. ginseng interact with multiple targets simultaneously, giving the multidimensional effects on various conditions and diseases. In order to decipher the systems-level mechanism of multiple ingredients of P. ginseng , a novel approach is needed beyond conventional reductive analysis. We aim to review the systems-level mechanism of P. ginseng by adopting novel analytical framework-network pharmacology. Here, we constructed a compound-target network of P. ginseng using experimentally validated and machine learning-based prediction results. The targets of the network were analyzed in terms of related biological process, pathways, and diseases. The majority of targets were found to be related with primary metabolic process, signal transduction, nitrogen compound metabolic process, blood circulation, immune system process, cell-cell signaling, biosynthetic process, and neurological system process. In pathway enrichment analysis of targets, mainly the terms related with neural activity showed significant enrichment and formed a cluster. Finally, relative degrees analysis for the target-disease association of P. ginseng revealed several categories of related diseases, including respiratory, psychiatric, and cardiovascular diseases.

Sleep and biological parameters in professional burnout: A psychophysiological characterization

PubMed Central

Sauvet, Fabien; Gomez-Merino, Danielle; Boucher, Thierry; Elbaz, Maxime; Delafosse, Jean Yves; Leger, Damien; Chennaoui, Mounir

2018-01-01

Professional burnout syndrome has been described in association with insomnia and metabolic, inflammatory and immune correlates. We investigated the interest of exploring biological parameters and sleep disturbances in relation to burnout symptoms among white-collar workers. Fifty-four participants with burnout were compared to 86 healthy control participants in terms of professional rank level, sleep, job strain (Karasek questionnaire), social support, anxiety and depression (HAD scale). Fasting concentrations of glycaemia, glycosylated hemoglobin (HbA1C), total-cholesterol, triglycerides, C-reactive protein (CRP), thyroid stimulating hormone (TSH), 25-hydroxyvitamin D (25[OH]D), and white blood cell (WBC) counts were assessed. Analysis of variance and a forward Stepwise Multiple Logistic Regression were made to identify predictive factors of burnout. Besides reporting more job strain (in particular job control p = 0.02), higher levels of anxiety (p<0.001), and sleep disorders related to insomnia (OR = 21.5, 95%CI = 8.8–52.3), participants with burnout presented higher levels of HbA1C, glycaemia, CRP, lower levels of 25(OH)D, higher number of leukocytes, neutrophils and monocytes (P<0.001 for all) and higher total-cholesterol (P = 0.01). In particular, when HbA1c is > 3.5%, the prevalence of burnout increases from 16.6% to 60.0% (OR = 4.3, 95%CI = 2.8–6.9). Strong significant positive correlation existed between HbA1C and the two dimensions (emotional exhaustion and depersonalization (r = 0.79 and r = 0.71, p<0.01)) of burnout. Models including job strain, job satisfaction, anxiety and insomnia did not predict burnout (p = 0.30 and p = 0.50). However, when HbA1C levels is included, the prediction of burnout became significant (P = 0.03). Our findings demonstrated the interest of sleep and biological parameters, in particular HbA1C levels, in the characterization of professional burnout. PMID:29385150

Sleep and biological parameters in professional burnout: A psychophysiological characterization.

PubMed

Metlaine, Arnaud; Sauvet, Fabien; Gomez-Merino, Danielle; Boucher, Thierry; Elbaz, Maxime; Delafosse, Jean Yves; Leger, Damien; Chennaoui, Mounir

2018-01-01

Professional burnout syndrome has been described in association with insomnia and metabolic, inflammatory and immune correlates. We investigated the interest of exploring biological parameters and sleep disturbances in relation to burnout symptoms among white-collar workers. Fifty-four participants with burnout were compared to 86 healthy control participants in terms of professional rank level, sleep, job strain (Karasek questionnaire), social support, anxiety and depression (HAD scale). Fasting concentrations of glycaemia, glycosylated hemoglobin (HbA1C), total-cholesterol, triglycerides, C-reactive protein (CRP), thyroid stimulating hormone (TSH), 25-hydroxyvitamin D (25[OH]D), and white blood cell (WBC) counts were assessed. Analysis of variance and a forward Stepwise Multiple Logistic Regression were made to identify predictive factors of burnout. Besides reporting more job strain (in particular job control p = 0.02), higher levels of anxiety (p<0.001), and sleep disorders related to insomnia (OR = 21.5, 95%CI = 8.8-52.3), participants with burnout presented higher levels of HbA1C, glycaemia, CRP, lower levels of 25(OH)D, higher number of leukocytes, neutrophils and monocytes (P<0.001 for all) and higher total-cholesterol (P = 0.01). In particular, when HbA1c is > 3.5%, the prevalence of burnout increases from 16.6% to 60.0% (OR = 4.3, 95%CI = 2.8-6.9). Strong significant positive correlation existed between HbA1C and the two dimensions (emotional exhaustion and depersonalization (r = 0.79 and r = 0.71, p<0.01)) of burnout. Models including job strain, job satisfaction, anxiety and insomnia did not predict burnout (p = 0.30 and p = 0.50). However, when HbA1C levels is included, the prediction of burnout became significant (P = 0.03). Our findings demonstrated the interest of sleep and biological parameters, in particular HbA1C levels, in the characterization of professional burnout.

Phosphotyrosine-based-phosphoproteomics scaled-down to biopsy level for analysis of individual tumor biology and treatment selection.

PubMed

Labots, Mariette; van der Mijn, Johannes C; Beekhof, Robin; Piersma, Sander R; de Goeij-de Haas, Richard R; Pham, Thang V; Knol, Jaco C; Dekker, Henk; van Grieken, Nicole C T; Verheul, Henk M W; Jiménez, Connie R

2017-06-06

Mass spectrometry-based phosphoproteomics of cancer cell and tissue lysates provides insight in aberrantly activated signaling pathways and potential drug targets. For improved understanding of individual patient's tumor biology and to allow selection of tyrosine kinase inhibitors in individual patients, phosphoproteomics of small clinical samples should be feasible and reproducible. We aimed to scale down a pTyr-phosphopeptide enrichment protocol to biopsy-level protein input and assess reproducibility and applicability to tumor needle biopsies. To this end, phosphopeptide immunoprecipitation using anti-phosphotyrosine beads was performed using 10, 5 and 1mg protein input from lysates of colorectal cancer (CRC) cell line HCT116. Multiple needle biopsies from 7 human CRC resection specimens were analyzed at the 1mg-level. The total number of phosphopeptides captured and detected by LC-MS/MS ranged from 681 at 10mg input to 471 at 1mg HCT116 protein. ID-reproducibility ranged from 60.5% at 10mg to 43.9% at 1mg. Per 1mg-level biopsy sample, >200 phosphopeptides were identified with 57% ID-reproducibility between paired tumor biopsies. Unsupervised analysis clustered biopsies from individual patients together and revealed known and potential therapeutic targets. This study demonstrates the feasibility of label-free pTyr-phosphoproteomics at the tumor biopsy level based on reproducible analyses using 1mg of protein input. The considerable number of identified phosphopeptides at this level is attributed to an effective down-scaled immuno-affinity protocol as well as to the application of ID propagation in the data processing and analysis steps. Unsupervised cluster analysis reveals patient-specific profiles. Together, these findings pave the way for clinical trials in which pTyr-phosphoproteomics will be performed on pre- and on-treatment biopsies. Such studies will improve our understanding of individual tumor biology and may enable future pTyr-phosphoproteomics-based personalized medicine. Copyright © 2017. Published by Elsevier B.V.

Single-molecule techniques in biophysics: a review of the progress in methods and applications.

PubMed

Miller, Helen; Zhou, Zhaokun; Shepherd, Jack; Wollman, Adam J M; Leake, Mark C

2018-02-01

Single-molecule biophysics has transformed our understanding of biology, but also of the physics of life. More exotic than simple soft matter, biomatter lives far from thermal equilibrium, covering multiple lengths from the nanoscale of single molecules to up to several orders of magnitude higher in cells, tissues and organisms. Biomolecules are often characterized by underlying instability: multiple metastable free energy states exist, separated by levels of just a few multiples of the thermal energy scale k B T, where k B is the Boltzmann constant and T absolute temperature, implying complex inter-conversion kinetics in the relatively hot, wet environment of active biological matter. A key benefit of single-molecule biophysics techniques is their ability to probe heterogeneity of free energy states across a molecular population, too challenging in general for conventional ensemble average approaches. Parallel developments in experimental and computational techniques have catalysed the birth of multiplexed, correlative techniques to tackle previously intractable biological questions. Experimentally, progress has been driven by improvements in sensitivity and speed of detectors, and the stability and efficiency of light sources, probes and microfluidics. We discuss the motivation and requirements for these recent experiments, including the underpinning mathematics. These methods are broadly divided into tools which detect molecules and those which manipulate them. For the former we discuss the progress of super-resolution microscopy, transformative for addressing many longstanding questions in the life sciences, and for the latter we include progress in 'force spectroscopy' techniques that mechanically perturb molecules. We also consider in silico progress of single-molecule computational physics, and how simulation and experimentation may be drawn together to give a more complete understanding. Increasingly, combinatorial techniques are now used, including correlative atomic force microscopy and fluorescence imaging, to probe questions closer to native physiological behaviour. We identify the trade-offs, limitations and applications of these techniques, and discuss exciting new directions.

Single-molecule techniques in biophysics: a review of the progress in methods and applications

NASA Astrophysics Data System (ADS)

Miller, Helen; Zhou, Zhaokun; Shepherd, Jack; Wollman, Adam J. M.; Leake, Mark C.

2018-02-01

Single-molecule biophysics has transformed our understanding of biology, but also of the physics of life. More exotic than simple soft matter, biomatter lives far from thermal equilibrium, covering multiple lengths from the nanoscale of single molecules to up to several orders of magnitude higher in cells, tissues and organisms. Biomolecules are often characterized by underlying instability: multiple metastable free energy states exist, separated by levels of just a few multiples of the thermal energy scale k B T, where k B is the Boltzmann constant and T absolute temperature, implying complex inter-conversion kinetics in the relatively hot, wet environment of active biological matter. A key benefit of single-molecule biophysics techniques is their ability to probe heterogeneity of free energy states across a molecular population, too challenging in general for conventional ensemble average approaches. Parallel developments in experimental and computational techniques have catalysed the birth of multiplexed, correlative techniques to tackle previously intractable biological questions. Experimentally, progress has been driven by improvements in sensitivity and speed of detectors, and the stability and efficiency of light sources, probes and microfluidics. We discuss the motivation and requirements for these recent experiments, including the underpinning mathematics. These methods are broadly divided into tools which detect molecules and those which manipulate them. For the former we discuss the progress of super-resolution microscopy, transformative for addressing many longstanding questions in the life sciences, and for the latter we include progress in ‘force spectroscopy’ techniques that mechanically perturb molecules. We also consider in silico progress of single-molecule computational physics, and how simulation and experimentation may be drawn together to give a more complete understanding. Increasingly, combinatorial techniques are now used, including correlative atomic force microscopy and fluorescence imaging, to probe questions closer to native physiological behaviour. We identify the trade-offs, limitations and applications of these techniques, and discuss exciting new directions.

Enhanced in Vivo Efficacy of a Type I Interferon Superagonist with Extended Plasma Half-life in a Mouse Model of Multiple Sclerosis*

PubMed Central

Harari, Daniel; Kuhn, Nadine; Abramovich, Renne; Sasson, Keren; Zozulya, Alla L.; Smith, Paul; Schlapschy, Martin; Aharoni, Rina; Köster, Mario; Eilam, Raya; Skerra, Arne; Schreiber, Gideon

2014-01-01

IFNβ is a common therapeutic option to treat multiple sclerosis. It is unique among the family of type I IFNs in that it binds to the interferon receptors with high affinity, conferring exceptional biological properties. We have previously reported the generation of an interferon superagonist (dubbed YNSα8) that is built on the backbone of a low affinity IFNα but modified to exhibit higher receptor affinity than even for IFNβ. Here, YNSα8 was fused with a 600-residue hydrophilic, unstructured N-terminal polypeptide chain comprising proline, alanine, and serine (PAS) to prolong its plasma half-life via “PASylation.” PAS-YNSα8 exhibited a 10-fold increased half-life in both pharmacodynamic and pharmacokinetic assays in a transgenic mouse model harboring the human receptors, notably without any detectable loss in biological potency or bioavailability. This long-lived superagonist conferred significantly improved protection from MOG35–55-induced experimental autoimmune encephalomyelitis compared with IFNβ, despite being injected with a 4-fold less frequency and at an overall 16-fold lower dosage. These data were corroborated by FACS measurements showing a decrease of CD11b+/CD45hi myeloid lineage cells detectable in the CNS, as well as a decrease in IBA+ cells in spinal cord sections determined by immunohistochemistry for PAS-YNSα8-treated animals. Importantly, PAS-YNSα8 did not induce antibodies upon repeated administration, and its biological efficacy remained unchanged after 21 days of treatment. A striking correlation between increased levels of CD274 (PD-L1) transcripts from spleen-derived CD4+ cells and improved clinical response to autoimmune encephalomyelitis was observed, indicating that, at least in this mouse model of multiple sclerosis, CD274 may serve as a biomarker to predict the effectiveness of IFN therapy to treat this complex disease. PMID:25193661

BAYESIAN LARGE-SCALE MULTIPLE REGRESSION WITH SUMMARY STATISTICS FROM GENOME-WIDE ASSOCIATION STUDIES1

PubMed Central

Zhu, Xiang; Stephens, Matthew

2017-01-01

Bayesian methods for large-scale multiple regression provide attractive approaches to the analysis of genome-wide association studies (GWAS). For example, they can estimate heritability of complex traits, allowing for both polygenic and sparse models; and by incorporating external genomic data into the priors, they can increase power and yield new biological insights. However, these methods require access to individual genotypes and phenotypes, which are often not easily available. Here we provide a framework for performing these analyses without individual-level data. Specifically, we introduce a “Regression with Summary Statistics” (RSS) likelihood, which relates the multiple regression coefficients to univariate regression results that are often easily available. The RSS likelihood requires estimates of correlations among covariates (SNPs), which also can be obtained from public databases. We perform Bayesian multiple regression analysis by combining the RSS likelihood with previously proposed prior distributions, sampling posteriors by Markov chain Monte Carlo. In a wide range of simulations RSS performs similarly to analyses using the individual data, both for estimating heritability and detecting associations. We apply RSS to a GWAS of human height that contains 253,288 individuals typed at 1.06 million SNPs, for which analyses of individual-level data are practically impossible. Estimates of heritability (52%) are consistent with, but more precise, than previous results using subsets of these data. We also identify many previously unreported loci that show evidence for association with height in our analyses. Software is available at https://github.com/stephenslab/rss. PMID:29399241

Accurate and fast multiple-testing correction in eQTL studies.

PubMed

Sul, Jae Hoon; Raj, Towfique; de Jong, Simone; de Bakker, Paul I W; Raychaudhuri, Soumya; Ophoff, Roel A; Stranger, Barbara E; Eskin, Eleazar; Han, Buhm

2015-06-04

In studies of expression quantitative trait loci (eQTLs), it is of increasing interest to identify eGenes, the genes whose expression levels are associated with variation at a particular genetic variant. Detecting eGenes is important for follow-up analyses and prioritization because genes are the main entities in biological processes. To detect eGenes, one typically focuses on the genetic variant with the minimum p value among all variants in cis with a gene and corrects for multiple testing to obtain a gene-level p value. For performing multiple-testing correction, a permutation test is widely used. Because of growing sample sizes of eQTL studies, however, the permutation test has become a computational bottleneck in eQTL studies. In this paper, we propose an efficient approach for correcting for multiple testing and assess eGene p values by utilizing a multivariate normal distribution. Our approach properly takes into account the linkage-disequilibrium structure among variants, and its time complexity is independent of sample size. By applying our small-sample correction techniques, our method achieves high accuracy in both small and large studies. We have shown that our method consistently produces extremely accurate p values (accuracy > 98%) for three human eQTL datasets with different sample sizes and SNP densities: the Genotype-Tissue Expression pilot dataset, the multi-region brain dataset, and the HapMap 3 dataset. Copyright © 2015 The American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.

Pollinator specialization: from the individual to the community.

PubMed

Brosi, Berry J

2016-06-01

1190 I. 1190 II. 1191 III. 1191 IV. 1193 V. 1193 1194 References 1194 SUMMARY: Most spermatophytes need conspecific pollen in order to produce seed. This need for specialization seems to conflict with the generalized nature of most plant-pollinator interactions. Specialization and generalization are dynamic - not fixed - and exist simultaneously in multiple states at different levels of biological hierarchy. Over the short term, specialization ensures conspecific pollen transfer, whereas over the long term, generalization improves system-level robustness. The balance between specialization and generalization at different scales is critical for different kinds of ecological functioning and is an important factor in plant speciation and the evolution of plant mating systems. Community context, including diversity and interaction network structure at different levels of aggregation, is a key driver of specialization dynamics. © 2016 The Authors. New Phytologist © 2016 New Phytologist Trust.

Metabolomics and neuroanatomical evaluation of post-mortem changes in the hippocampus.

PubMed

Gonzalez-Riano, Carolina; Tapia-González, Silvia; García, Antonia; Muñoz, Alberto; DeFelipe, Javier; Barbas, Coral

2017-08-01

Understanding the human brain is the ultimate goal in neuroscience, but this is extremely challenging in part due to the fact that brain tissue obtained from autopsy is practically the only source of normal brain tissue and also since changes at different levels of biological organization (genetic, molecular, biochemical, anatomical) occur after death due to multiple mechanisms. Here we used metabolomic and anatomical techniques to study the possible relationship between post-mortem time (PT)-induced changes that may occur at both the metabolomics and anatomical levels in the same brains. Our experiments have mainly focused on the hippocampus of the mouse. We found significant metabolomic changes at 2 h PT, whereas the integrity of neurons and glia, at the anatomical/ neurochemical level, was not significantly altered during the first 5 h PT for the majority of histological markers.

Exploring the Factors Related to Acceptance of Evolutionary Theory among Turkish Preservice Biology Teachers: Toward a More Informative Conceptual Ecology for Biological Evolution

ERIC Educational Resources Information Center

Deniz, Hasan; Donnelly, Lisa A.; Yilmaz, Irfan

2008-01-01

In this study, using multiple regression analysis, we aimed to explore the factors related to acceptance of evolutionary theory among preservice Turkish biology teachers using conceptual ecology for biological evolution as a theoretical lens. We aimed to determine the extent to which we can account for the variance in acceptance of evolutionary…

[THE OPTIMIZATION OF NUTRITION FUNCTION UNDER SYNDROME OF RESISTANCE TO INSULIN, DISORDER OF FATTY ACIDS' METABOLISM AND ABSORPTION OF GLUCOSE BY CELLS (A LECTURE)].

PubMed

Titov, V N

2016-01-01

The phylogenetic processes continue to proceed in Homo Sapiens. At the very early stages ofphylogenesis, the ancient Archaea that formed mitochondria under symbiotic interaction with later bacterial cells conjointly formed yet another system. In this system, there are no cells' absorption of glucose if it is possible to absorb fatty acids from intercellular medium in the form of unesterfied fatty acids or ketonic bodies--metabolites of fatty acids. This is caused by objectively existed conditions and subsequent availability of substrates at the stages ofphylogenesis: acetate, ketonic bodies, fatty acids and only later glucose. The phylogenetically late insulin used after billions years the same dependencies at formation of regulation ofmetabolism offatty acids and cells' absorption of glucose. In order that syndrome ofresistance ceased to exist as afoundation of metabolic pandemic Homo Sapiens has to understand the following. After successful function ofArchaea+bacterial cells and considered by biology action of insulin for the third time in phylogenesis and using biological function of intelligence the content ofphylogenetically earlier palmitic saturated fatty acid infood can't to exceed possibilities of phylogenetically late lipoproteins to transfer it in intercellular medium and blood and cells to absorb it. It is supposed that at early stages of phylogenesis biological function of intelligence is primarily formed to bring into line "unconformities" of regulation of metabolism against the background of seeming relative biological "perfection". These unconformities were subsequently and separately formed at the level of cells in paracrin regulated cenosises of cells and organs and at the level of organism. The prevention of resistance to insulin basically requires biological function of intelligence, principle of self-restraint, bringing into line multiple desires of Homo Sapiens with much less extensive biological possibilities. The "unconformities" of regulation of metabolism in vivo are etiological factors of all metabolic pandemics including atherosclerosis, metabolic arterial hypertension, obesity and metabolic syndrome Tertiannondatum.

Cryptosporidium as a testbed for single cell genome characterization of unicellular eukaryotes.

PubMed

Troell, Karin; Hallström, Björn; Divne, Anna-Maria; Alsmark, Cecilia; Arrighi, Romanico; Huss, Mikael; Beser, Jessica; Bertilsson, Stefan

2016-06-23

Infectious disease involving multiple genetically distinct populations of pathogens is frequently concurrent, but difficult to detect or describe with current routine methodology. Cryptosporidium sp. is a widespread gastrointestinal protozoan of global significance in both animals and humans. It cannot be easily maintained in culture and infections of multiple strains have been reported. To explore the potential use of single cell genomics methodology for revealing genome-level variation in clinical samples from Cryptosporidium-infected hosts, we sorted individual oocysts for subsequent genome amplification and full-genome sequencing. Cells were identified with fluorescent antibodies with an 80 % success rate for the entire single cell genomics workflow, demonstrating that the methodology can be applied directly to purified fecal samples. Ten amplified genomes from sorted single cells were selected for genome sequencing and compared both to the original population and a reference genome in order to evaluate the accuracy and performance of the method. Single cell genome coverage was on average 81 % even with a moderate sequencing effort and by combining the 10 single cell genomes, the full genome was accounted for. By a comparison to the original sample, biological variation could be distinguished and separated from noise introduced in the amplification. As a proof of principle, we have demonstrated the power of applying single cell genomics to dissect infectious disease caused by closely related parasite species or subtypes. The workflow can easily be expanded and adapted to target other protozoans, and potential applications include mapping genome-encoded traits, virulence, pathogenicity, host specificity and resistance at the level of cells as truly meaningful biological units.

Synthesizing genetic sequential logic circuit with clock pulse generator

PubMed Central

2014-01-01

Background Rhythmic clock widely occurs in biological systems which controls several aspects of cell physiology. For the different cell types, it is supplied with various rhythmic frequencies. How to synthesize a specific clock signal is a preliminary but a necessary step to further development of a biological computer in the future. Results This paper presents a genetic sequential logic circuit with a clock pulse generator based on a synthesized genetic oscillator, which generates a consecutive clock signal whose frequency is an inverse integer multiple to that of the genetic oscillator. An analogous electronic waveform-shaping circuit is constructed by a series of genetic buffers to shape logic high/low levels of an oscillation input in a basic sinusoidal cycle and generate a pulse-width-modulated (PWM) output with various duty cycles. By controlling the threshold level of the genetic buffer, a genetic clock pulse signal with its frequency consistent to the genetic oscillator is synthesized. A synchronous genetic counter circuit based on the topology of the digital sequential logic circuit is triggered by the clock pulse to synthesize the clock signal with an inverse multiple frequency to the genetic oscillator. The function acts like a frequency divider in electronic circuits which plays a key role in the sequential logic circuit with specific operational frequency. Conclusions A cascaded genetic logic circuit generating clock pulse signals is proposed. Based on analogous implement of digital sequential logic circuits, genetic sequential logic circuits can be constructed by the proposed approach to generate various clock signals from an oscillation signal. PMID:24884665

The molecular basis of jaundice: An old symptom revisited.

PubMed

Gazzin, Silvia; Masutti, Flora; Vitek, Libor; Tiribelli, Claudio

2017-08-01

Increased serum bilirubin level is a widely used diagnostic marker for hepatic illnesses. Nevertheless, mild elevation of unconjugated serum bilirubin (such as in Gilbert syndrome) has been recently demonstrated to correlate with low risk of chronic inflammatory and/or oxidative stress-mediated diseases. In accord, a low serum bilirubin level has emerged as an important predisposing factor or a biomarker of these pathologic conditions including cardiovascular, tumour, and possibly neurodegenerative diseases. Bilirubin possesses multiple biological actions with interaction in a complex network of enzymatic and signalling pathways. The fact that the liver is the main organ controlling the bioavailability of bilirubin emphasizes the central role of this organ in human health. © 2016 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

The biogeochemical heterogeneity of tropical forests.

PubMed

Townsend, Alan R; Asner, Gregory P; Cleveland, Cory C

2008-08-01

Tropical forests are renowned for their biological diversity, but also harbor variable combinations of soil age, chemistry and susceptibility to erosion or tectonic uplift. Here we contend that the combined effects of this biotic and abiotic diversity promote exceptional biogeochemical heterogeneity at multiple scales. At local levels, high plant diversity creates variation in chemical and structural traits that affect plant production, decomposition and nutrient cycling. At regional levels, myriad combinations of soil age, soil chemistry and landscape dynamics create variation and uncertainty in limiting nutrients that do not exist at higher latitudes. The effects of such heterogeneity are not well captured in large-scale estimates of tropical ecosystem function, but we suggest new developments in remote sensing can help bridge the gap.

Individual and Neighborhood Stressors, Air Pollution and Cardiovascular Disease

PubMed Central

Hazlehurst, Marnie F.; Nurius, Paula S.; Hajat, Anjum

2018-01-01

Psychosocial and environmental stress exposures across the life course have been shown to be relevant in the development of cardiovascular disease (CVD). Assessing more than one stressor from different domains (e.g., individual and neighborhood) and across the life course moves us towards a more integrated picture of how stress affects health and well-being. Furthermore, these individual and neighborhood psychosocial stressors act on biologic pathways, including immune function and inflammatory response, which are also impacted by ubiquitous environmental exposures such as air pollution. The objective of this study is to evaluate the interaction between psychosocial stressors, at both the individual and neighborhood level, and air pollution on CVD. This study used data from the 2009–2011 Behavioral Risk Factor Surveillance System (BRFSS) from Washington State. Adverse childhood experiences (ACEs) measured at the individual level, and neighborhood deprivation index (NDI) measured at the zip code level, were the psychosocial stressors of interest. Exposures to three air pollutants—particulate matter (both PM2.5 and PM10) and nitrogen dioxide (NO2)—were also calculated at the zip code level. Outcome measures included several self-reported CVD-related health conditions. Both multiplicative and additive interaction quantified using the relative excess risk due to interaction (RERI), were evaluated. This study included 32,151 participants in 502 unique zip codes. Multiplicative and positive additive interactions were observed between ACEs and PM10 for diabetes, in models adjusted for NDI. The prevalence of diabetes was 1.58 (95% CI: 1.40, 1.79) times higher among those with both high ACEs and high PM10 compared to those with low ACEs and low PM10 (p-value = 0.04 for interaction on the multiplicative scale). Interaction was also observed between neighborhood-level stressors (NDI) and air pollution (NO2) for the stroke and diabetes outcomes on both multiplicative and additive scales. Modest interaction was observed between NDI and air pollution, supporting prior literature on the importance of neighborhood-level stressors in cardiovascular health and reinforcing the importance of NDI on air pollution health effects. ACEs may exert health effects through selection into disadvantaged neighborhoods and more work is needed to understand the accumulation of risk in multiple domains across the life course. PMID:29518012

Diversity in skeletal architecture influences biological heterogeneity and Symbiodinium habitat in corals.

PubMed

Yost, Denise M; Wang, Li-Hsueh; Fan, Tung-Yung; Chen, Chii-Shiarng; Lee, Raymond W; Sogin, Emilia; Gates, Ruth D

2013-10-01

Scleractinian corals vary in response to rapid shifts in the marine environment and changes in reef community structure post-disturbance reveal a clear relationship between coral performance and morphology. With exceptions, massive corals are thought to be more tolerant and branching corals more vulnerable to changing environmental conditions, notably thermal stress. The typical responses of massive and branching coral taxa, respectively, are well documented; however, the biological and functional characteristics that underpin this variation are not well understood. We address this gap by comparing multiple biological attributes that are correlated with skeletal architecture in two perforate (having porous skeletal matrices with intercalating tissues) and two imperforate coral species (Montipora aequituberculata, Porites lobata, Pocillopora damicornis, and Seriatopora hystrix) representing three morphotypes. Our results reveal inherent biological heterogeneity among corals and the potential for perforate skeletons to create complex, three-dimensional internal habitats that impact the dynamics of the symbiosis. Patterns of tissue thickness are correlated with the concentration of symbionts within narrow regions of tissue in imperforate corals versus broad distribution throughout the larger tissue area in perforate corals. Attributes of the perforate and environmentally tolerant P. lobata were notable, with tissues ∼5 times thicker than in the sensitive, imperforate species P. damicornis and S. hystrix. Additionally, P. lobata had the lowest baseline levels of superoxide and Symbiodinium that provisioned high levels of energy. Given our observations, we hypothesize that the complexity of the visually obscured internal environment has an impact on host-symbiont dynamics and ultimately on survival, warranting further scientific investigation. Copyright © 2013 Elsevier GmbH. All rights reserved.

A distributed system for fast alignment of next-generation sequencing data.

PubMed

Srimani, Jaydeep K; Wu, Po-Yen; Phan, John H; Wang, May D

2010-12-01

We developed a scalable distributed computing system using the Berkeley Open Interface for Network Computing (BOINC) to align next-generation sequencing (NGS) data quickly and accurately. NGS technology is emerging as a promising platform for gene expression analysis due to its high sensitivity compared to traditional genomic microarray technology. However, despite the benefits, NGS datasets can be prohibitively large, requiring significant computing resources to obtain sequence alignment results. Moreover, as the data and alignment algorithms become more prevalent, it will become necessary to examine the effect of the multitude of alignment parameters on various NGS systems. We validate the distributed software system by (1) computing simple timing results to show the speed-up gained by using multiple computers, (2) optimizing alignment parameters using simulated NGS data, and (3) computing NGS expression levels for a single biological sample using optimal parameters and comparing these expression levels to that of a microarray sample. Results indicate that the distributed alignment system achieves approximately a linear speed-up and correctly distributes sequence data to and gathers alignment results from multiple compute clients.

Evaluation of Cross-Protocol Stability of a Fully Automated Brain Multi-Atlas Parcellation Tool.

PubMed

Liang, Zifei; He, Xiaohai; Ceritoglu, Can; Tang, Xiaoying; Li, Yue; Kutten, Kwame S; Oishi, Kenichi; Miller, Michael I; Mori, Susumu; Faria, Andreia V

2015-01-01

Brain parcellation tools based on multiple-atlas algorithms have recently emerged as a promising method with which to accurately define brain structures. When dealing with data from various sources, it is crucial that these tools are robust for many different imaging protocols. In this study, we tested the robustness of a multiple-atlas, likelihood fusion algorithm using Alzheimer's Disease Neuroimaging Initiative (ADNI) data with six different protocols, comprising three manufacturers and two magnetic field strengths. The entire brain was parceled into five different levels of granularity. In each level, which defines a set of brain structures, ranging from eight to 286 regions, we evaluated the variability of brain volumes related to the protocol, age, and diagnosis (healthy or Alzheimer's disease). Our results indicated that, with proper pre-processing steps, the impact of different protocols is minor compared to biological effects, such as age and pathology. A precise knowledge of the sources of data variation enables sufficient statistical power and ensures the reliability of an anatomical analysis when using this automated brain parcellation tool on datasets from various imaging protocols, such as clinical databases.

Diffusion of multiple species with excluded-volume effects.

PubMed

Bruna, Maria; Chapman, S Jonathan

2012-11-28

Stochastic models of diffusion with excluded-volume effects are used to model many biological and physical systems at a discrete level. The average properties of the population may be described by a continuum model based on partial differential equations. In this paper we consider multiple interacting subpopulations/species and study how the inter-species competition emerges at the population level. Each individual is described as a finite-size hard core interacting particle undergoing brownian motion. The link between the discrete stochastic equations of motion and the continuum model is considered systematically using the method of matched asymptotic expansions. The system for two species leads to a nonlinear cross-diffusion system for each subpopulation, which captures the enhancement of the effective diffusion rate due to excluded-volume interactions between particles of the same species, and the diminishment due to particles of the other species. This model can explain two alternative notions of the diffusion coefficient that are often confounded, namely collective diffusion and self-diffusion. Simulations of the discrete system show good agreement with the analytic results.

The differential view of genotype–phenotype relationships

PubMed Central

Orgogozo, Virginie; Morizot, Baptiste; Martin, Arnaud

2015-01-01

An integrative view of diversity and singularity in the living world requires a better understanding of the intricate link between genotypes and phenotypes. Here we re-emphasize the old standpoint that the genotype–phenotype (GP) relationship is best viewed as a connection between two differences, one at the genetic level and one at the phenotypic level. As of today, predominant thinking in biology research is that multiple genes interact with multiple environmental variables (such as abiotic factors, culture, or symbionts) to produce the phenotype. Often, the problem of linking genotypes and phenotypes is framed in terms of genotype and phenotype maps, and such graphical representations implicitly bring us away from the differential view of GP relationships. Here we show that the differential view of GP relationships is a useful explanatory framework in the context of pervasive pleiotropy, epistasis, and environmental effects. In such cases, it is relevant to view GP relationships as differences embedded into differences. Thinking in terms of differences clarifies the comparison between environmental and genetic effects on phenotypes and helps to further understand the connection between genotypes and phenotypes. PMID:26042146

Imaging free zinc levels in vivo - what can be learned?

PubMed

De Leon-Rodriguez, Luis; Lubag, Angelo Josue M; Sherry, A Dean

2012-12-01

Our ever-expanding knowledge about the role of zinc in biology includes its role in redox modulation, immune response, neurotransmission, reproduction, diabetes, cancer, and Alzheimers disease is galvanizing interest in detecting and monitoring the various forms of Zn(II) in biological systems. This paper reviews reported strategies for detecting and tracking of labile or "free" unchelated Zn(II) in tissues. While different bound structural forms of Zn(II) have been identified and studied in vitro by multiple techniques, very few molecular imaging methods have successfully tracked the ion in vivo. A number of MRI and optical strategies have now been reported for detection of free Zn(II) in cells and tissues but only a few have been applied successfully in vivo. A recent report of a MRI sensor for in vivo tracking of Zn(II) released from pancreatic β-cells during insulin secretion exemplifies the promise of rational design of new Zn(II) sensors for tracking this biologically important ion in vivo. Such studies promise to provide new insights into zinc trafficking in vivo and the critical role of this ion in many human diseases.

Programming biological models in Python using PySB.

PubMed

Lopez, Carlos F; Muhlich, Jeremy L; Bachman, John A; Sorger, Peter K

2013-01-01

Mathematical equations are fundamental to modeling biological networks, but as networks get large and revisions frequent, it becomes difficult to manage equations directly or to combine previously developed models. Multiple simultaneous efforts to create graphical standards, rule-based languages, and integrated software workbenches aim to simplify biological modeling but none fully meets the need for transparent, extensible, and reusable models. In this paper we describe PySB, an approach in which models are not only created using programs, they are programs. PySB draws on programmatic modeling concepts from little b and ProMot, the rule-based languages BioNetGen and Kappa and the growing library of Python numerical tools. Central to PySB is a library of macros encoding familiar biochemical actions such as binding, catalysis, and polymerization, making it possible to use a high-level, action-oriented vocabulary to construct detailed models. As Python programs, PySB models leverage tools and practices from the open-source software community, substantially advancing our ability to distribute and manage the work of testing biochemical hypotheses. We illustrate these ideas using new and previously published models of apoptosis.

Improving Conceptual Understanding and Representation Skills Through Excel-Based Modeling

NASA Astrophysics Data System (ADS)

Malone, Kathy L.; Schunn, Christian D.; Schuchardt, Anita M.

2018-02-01

The National Research Council framework for science education and the Next Generation Science Standards have developed a need for additional research and development of curricula that is both technologically model-based and includes engineering practices. This is especially the case for biology education. This paper describes a quasi-experimental design study to test the effectiveness of a model-based curriculum focused on the concepts of natural selection and population ecology that makes use of Excel modeling tools (Modeling Instruction in Biology with Excel, MBI-E). The curriculum revolves around the bio-engineering practice of controlling an invasive species. The study takes place in the Midwest within ten high schools teaching a regular-level introductory biology class. A post-test was designed that targeted a number of common misconceptions in both concept areas as well as representational usage. The results of a post-test demonstrate that the MBI-E students significantly outperformed the traditional classes in both natural selection and population ecology concepts, thus overcoming a number of misconceptions. In addition, implementing students made use of more multiple representations as well as demonstrating greater fascination for science.

Molecular Cooperativity Governs Diverse and Monoallelic Olfactory Receptor Expression

NASA Astrophysics Data System (ADS)

Xing, Jianhua; Tian, Xiaojun; Zhang, Hang; Sannerud, Jens

Multiple-objective optimization is common in biological systems. In the mammalian olfactory system, each sensory neuron stochastically expresses only one out of up to thousands of olfactory receptor (OR) gene alleles; at organism level the types of expressed ORs need to be maximized. The molecular mechanism of this Nobel-Prize winning puzzle remains unresolved after decades of extensive studies. Existing models focus only on monoallele activation, and cannot explain recent observations in mutants, especially the reduced global diversity of expressed ORs in G9a/GLP knockouts. In this work we integrated existing information on OR expression, and proposed an evolutionarily optimized three-layer regulation mechanism, which includes zonal segregation, epigenetic and enhancer competition coupled to a negative feedback loop. This model not only recapitulates monoallelic OR expression, but also elucidates how the olfactory system maximizes and maintains the diversity of OR expression. The model is validated by several experimental results, and particularly underscores cooperativity and synergy as a general design principle of multi-objective optimization in biology. The work is supported by the NIGMS/DMS Mathematical Biology program.

Programming biological models in Python using PySB

PubMed Central

Lopez, Carlos F; Muhlich, Jeremy L; Bachman, John A; Sorger, Peter K

2013-01-01

Mathematical equations are fundamental to modeling biological networks, but as networks get large and revisions frequent, it becomes difficult to manage equations directly or to combine previously developed models. Multiple simultaneous efforts to create graphical standards, rule-based languages, and integrated software workbenches aim to simplify biological modeling but none fully meets the need for transparent, extensible, and reusable models. In this paper we describe PySB, an approach in which models are not only created using programs, they are programs. PySB draws on programmatic modeling concepts from little b and ProMot, the rule-based languages BioNetGen and Kappa and the growing library of Python numerical tools. Central to PySB is a library of macros encoding familiar biochemical actions such as binding, catalysis, and polymerization, making it possible to use a high-level, action-oriented vocabulary to construct detailed models. As Python programs, PySB models leverage tools and practices from the open-source software community, substantially advancing our ability to distribute and manage the work of testing biochemical hypotheses. We illustrate these ideas using new and previously published models of apoptosis. PMID:23423320

Molecular Dimensions of Gastric Cancer: Translational and Clinical Perspectives.

PubMed

Choi, Yoon Young; Noh, Sung Hoon; Cheong, Jae-Ho

2016-01-01

Gastric cancer is a global health burden and has the highest incidence in East Asia. This disease is complex in nature because it arises from multiple interactions of genetic, local environmental, and host factors, resulting in biological heterogeneity. This genetic intricacy converges on molecular characteristics reflecting the pathophysiology, tumor biology, and clinical outcome. Therefore, understanding the molecular characteristics at a genomic level is pivotal to improving the clinical care of patients with gastric cancer. A recent landmark study, The Cancer Genome Atlas (TCGA) project, showed the molecular landscape of gastric cancer through a comprehensive molecular evaluation of 295 primary gastric cancers. The proposed molecular classification divided gastric cancer into four subtypes: Epstein-Barr virus-positive, microsatellite unstable, genomic stable, and chromosomal instability. This information will be taken into account in future clinical trials and will be translated into clinical therapeutic decisions. To fully realize the clinical benefit, many challenges must be overcome. Rapid growth of high-throughput biology and functional validation of molecular targets will further deepen our knowledge of molecular dimensions of this cancer, allowing for personalized precision medicine.

A flexible ontology for inference of emergent whole cell function from relationships between subcellular processes.

PubMed

Hansen, Jens; Meretzky, David; Woldesenbet, Simeneh; Stolovitzky, Gustavo; Iyengar, Ravi

2017-12-18

Whole cell responses arise from coordinated interactions between diverse human gene products functioning within various pathways underlying sub-cellular processes (SCP). Lower level SCPs interact to form higher level SCPs, often in a context specific manner to give rise to whole cell function. We sought to determine if capturing such relationships enables us to describe the emergence of whole cell functions from interacting SCPs. We developed the Molecular Biology of the Cell Ontology based on standard cell biology and biochemistry textbooks and review articles. Currently, our ontology contains 5,384 genes, 753 SCPs and 19,180 expertly curated gene-SCP associations. Our algorithm to populate the SCPs with genes enables extension of the ontology on demand and the adaption of the ontology to the continuously growing cell biological knowledge. Since whole cell responses most often arise from the coordinated activity of multiple SCPs, we developed a dynamic enrichment algorithm that flexibly predicts SCP-SCP relationships beyond the current taxonomy. This algorithm enables us to identify interactions between SCPs as a basis for higher order function in a context dependent manner, allowing us to provide a detailed description of how SCPs together can give rise to whole cell functions. We conclude that this ontology can, from omics data sets, enable the development of detailed SCP networks for predictive modeling of emergent whole cell functions.

Biologically-inspired approaches for self-organization, adaptation, and collaboration of heterogeneous autonomous systems

NASA Astrophysics Data System (ADS)

Steinberg, Marc

2011-06-01

This paper presents a selective survey of theoretical and experimental progress in the development of biologicallyinspired approaches for complex surveillance and reconnaissance problems with multiple, heterogeneous autonomous systems. The focus is on approaches that may address ISR problems that can quickly become mathematically intractable or otherwise impractical to implement using traditional optimization techniques as the size and complexity of the problem is increased. These problems require dealing with complex spatiotemporal objectives and constraints at a variety of levels from motion planning to task allocation. There is also a need to ensure solutions are reliable and robust to uncertainty and communications limitations. First, the paper will provide a short introduction to the current state of relevant biological research as relates to collective animal behavior. Second, the paper will describe research on largely decentralized, reactive, or swarm approaches that have been inspired by biological phenomena such as schools of fish, flocks of birds, ant colonies, and insect swarms. Next, the paper will discuss approaches towards more complex organizational and cooperative mechanisms in team and coalition behaviors in order to provide mission coverage of large, complex areas. Relevant team behavior may be derived from recent advances in understanding of the social and cooperative behaviors used for collaboration by tens of animals with higher-level cognitive abilities such as mammals and birds. Finally, the paper will briefly discuss challenges involved in user interaction with these types of systems.

Multiple-Swarm Ensembles: Improving the Predictive Power and Robustness of Predictive Models and Its Use in Computational Biology.

PubMed

Alves, Pedro; Liu, Shuang; Wang, Daifeng; Gerstein, Mark

2018-01-01

Machine learning is an integral part of computational biology, and has already shown its use in various applications, such as prognostic tests. In the last few years in the non-biological machine learning community, ensembling techniques have shown their power in data mining competitions such as the Netflix challenge; however, such methods have not found wide use in computational biology. In this work, we endeavor to show how ensembling techniques can be applied to practical problems, including problems in the field of bioinformatics, and how they often outperform other machine learning techniques in both predictive power and robustness. Furthermore, we develop a methodology of ensembling, Multi-Swarm Ensemble (MSWE) by using multiple particle swarm optimizations and demonstrate its ability to further enhance the performance of ensembles.

WholePathwayScope: a comprehensive pathway-based analysis tool for high-throughput data

PubMed Central

Yi, Ming; Horton, Jay D; Cohen, Jonathan C; Hobbs, Helen H; Stephens, Robert M

2006-01-01

Background Analysis of High Throughput (HTP) Data such as microarray and proteomics data has provided a powerful methodology to study patterns of gene regulation at genome scale. A major unresolved problem in the post-genomic era is to assemble the large amounts of data generated into a meaningful biological context. We have developed a comprehensive software tool, WholePathwayScope (WPS), for deriving biological insights from analysis of HTP data. Result WPS extracts gene lists with shared biological themes through color cue templates. WPS statistically evaluates global functional category enrichment of gene lists and pathway-level pattern enrichment of data. WPS incorporates well-known biological pathways from KEGG (Kyoto Encyclopedia of Genes and Genomes) and Biocarta, GO (Gene Ontology) terms as well as user-defined pathways or relevant gene clusters or groups, and explores gene-term relationships within the derived gene-term association networks (GTANs). WPS simultaneously compares multiple datasets within biological contexts either as pathways or as association networks. WPS also integrates Genetic Association Database and Partial MedGene Database for disease-association information. We have used this program to analyze and compare microarray and proteomics datasets derived from a variety of biological systems. Application examples demonstrated the capacity of WPS to significantly facilitate the analysis of HTP data for integrative discovery. Conclusion This tool represents a pathway-based platform for discovery integration to maximize analysis power. The tool is freely available at . PMID:16423281

Systems Bioinformatics: increasing precision of computational diagnostics and therapeutics through network-based approaches.

PubMed

Oulas, Anastasis; Minadakis, George; Zachariou, Margarita; Sokratous, Kleitos; Bourdakou, Marilena M; Spyrou, George M

2017-11-27

Systems Bioinformatics is a relatively new approach, which lies in the intersection of systems biology and classical bioinformatics. It focuses on integrating information across different levels using a bottom-up approach as in systems biology with a data-driven top-down approach as in bioinformatics. The advent of omics technologies has provided the stepping-stone for the emergence of Systems Bioinformatics. These technologies provide a spectrum of information ranging from genomics, transcriptomics and proteomics to epigenomics, pharmacogenomics, metagenomics and metabolomics. Systems Bioinformatics is the framework in which systems approaches are applied to such data, setting the level of resolution as well as the boundary of the system of interest and studying the emerging properties of the system as a whole rather than the sum of the properties derived from the system's individual components. A key approach in Systems Bioinformatics is the construction of multiple networks representing each level of the omics spectrum and their integration in a layered network that exchanges information within and between layers. Here, we provide evidence on how Systems Bioinformatics enhances computational therapeutics and diagnostics, hence paving the way to precision medicine. The aim of this review is to familiarize the reader with the emerging field of Systems Bioinformatics and to provide a comprehensive overview of its current state-of-the-art methods and technologies. Moreover, we provide examples of success stories and case studies that utilize such methods and tools to significantly advance research in the fields of systems biology and systems medicine. © The Author 2017. Published by Oxford University Press.

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.

Multiple-Strain Approach and Probabilistic Modeling of Consumer Habits in Quantitative Microbial Risk Assessment: A Quantitative Assessment of Exposure to Staphylococcal Enterotoxin A in Raw Milk.

PubMed

Crotta, Matteo; Rizzi, Rita; Varisco, Giorgio; Daminelli, Paolo; Cunico, Elena Cosciani; Luini, Mario; Graber, Hans Ulrich; Paterlini, Franco; Guitian, Javier

2016-03-01

Quantitative microbial risk assessment (QMRA) models are extensively applied to inform management of a broad range of food safety risks. Inevitably, QMRA modeling involves an element of simplification of the biological process of interest. Two features that are frequently simplified or disregarded are the pathogenicity of multiple strains of a single pathogen and consumer behavior at the household level. In this study, we developed a QMRA model with a multiple-strain approach and a consumer phase module (CPM) based on uncertainty distributions fitted from field data. We modeled exposure to staphylococcal enterotoxin A in raw milk in Lombardy; a specific enterotoxin production module was thus included. The model is adaptable and could be used to assess the risk related to other pathogens in raw milk as well as other staphylococcal enterotoxins. The multiplestrain approach, implemented as a multinomial process, allowed the inclusion of variability and uncertainty with regard to pathogenicity at the bacterial level. Data from 301 questionnaires submitted to raw milk consumers were used to obtain uncertainty distributions for the CPM. The distributions were modeled to be easily updatable with further data or evidence. The sources of uncertainty due to the multiple-strain approach and the CPM were identified, and their impact on the output was assessed by comparing specific scenarios to the baseline. When the distributions reflecting the uncertainty in consumer behavior were fixed to the 95th percentile, the risk of exposure increased up to 160 times. This reflects the importance of taking into consideration the diversity of consumers' habits at the household level and the impact that the lack of knowledge about variables in the CPM can have on the final QMRA estimates. The multiple-strain approach lends itself to use in other food matrices besides raw milk and allows the model to better capture the complexity of the real world and to be capable of geographical specificity.

Biotic interactions modify multiple-stressor effects on juvenile brown trout in an experimental stream food web.

PubMed

Bruder, Andreas; Salis, Romana K; Jones, Peter E; Matthaei, Christoph D

2017-09-01

Agricultural land use results in multiple stressors affecting stream ecosystems. Flow reduction due to water abstraction, elevated levels of nutrients and chemical contaminants are common agricultural stressors worldwide. Concurrently, stream ecosystems are also increasingly affected by climate change. Interactions among multiple co-occurring stressors result in biological responses that cannot be predicted from single-stressor effects (i.e. synergisms and antagonisms). At the ecosystem level, multiple-stressor effects can be further modified by biotic interactions (e.g. trophic interactions). We conducted a field experiment using 128 flow-through stream mesocosms to examine the individual and combined effects of water abstraction, nutrient enrichment and elevated levels of the nitrification inhibitor dicyandiamide (DCD) on survival, condition and gut content of juvenile brown trout and on benthic abundance of their invertebrate prey. Flow velocity reduction decreased fish survival (-12% compared to controls) and condition (-8% compared to initial condition), whereas effects of nutrient and DCD additions and interactions among these stressors were not significant. Negative effects of flow velocity reduction on fish survival and condition were consistent with effects on fish gut content (-25% compared to controls) and abundance of dominant invertebrate prey (-30% compared to controls), suggesting a negative metabolic balance driving fish mortality and condition decline, which was confirmed by structural equation modelling. Fish mortality under reduced flow velocity increased as maximal daily water temperatures approached the upper limit of their tolerance range, reflecting synergistic interactions between these stressors. Our study highlights the importance of indirect stressor effects such as those transferred through trophic interactions, which need to be considered when assessing and managing fish populations and stream food webs in multiple-stressor situations. However, in real streams, compensatory mechanisms and behavioural responses, as well as seasonal and spatial variation, may alter the intensity of stressor effects and the sensitivity of trout populations. © 2017 John Wiley & Sons Ltd.

Development of a Biological Science Quantitative Reasoning Exam (BioSQuaRE)

ERIC Educational Resources Information Center

Stanhope, Liz; Ziegler, Laura; Haque, Tabassum; Le, Laura; Vinces, Marcelo; Davis, Gregory K.; Zieffler, Andrew; Brodfuehrer, Peter; Preest, Marion; Belitsky, Jason M.; Umbanhowar, Charles, Jr.; Overvoorde, Paul J.

2017-01-01

Multiple reports highlight the increasingly quantitative nature of biological research and the need to innovate means to ensure that students acquire quantitative skills. We present a tool to support such innovation. The Biological Science Quantitative Reasoning Exam (BioSQuaRE) is an assessment instrument designed to measure the quantitative…

The Biomarker-Surrogacy Evaluation Schema: a review of the biomarker-surrogate literature and a proposal for a criterion-based, quantitative, multidimensional hierarchical levels of evidence schema for evaluating the status of biomarkers as surrogate endpoints.

PubMed

Lassere, Marissa N

2008-06-01

There are clear advantages to using biomarkers and surrogate endpoints, but concerns about clinical and statistical validity and systematic methods to evaluate these aspects hinder their efficient application. Section 2 is a systematic, historical review of the biomarker-surrogate endpoint literature with special reference to the nomenclature, the systems of classification and statistical methods developed for their evaluation. In Section 3 an explicit, criterion-based, quantitative, multidimensional hierarchical levels of evidence schema - Biomarker-Surrogacy Evaluation Schema - is proposed to evaluate and co-ordinate the multiple dimensions (biological, epidemiological, statistical, clinical trial and risk-benefit evidence) of the biomarker clinical endpoint relationships. The schema systematically evaluates and ranks the surrogacy status of biomarkers and surrogate endpoints using defined levels of evidence. The schema incorporates the three independent domains: Study Design, Target Outcome and Statistical Evaluation. Each domain has items ranked from zero to five. An additional category called Penalties incorporates additional considerations of biological plausibility, risk-benefit and generalizability. The total score (0-15) determines the level of evidence, with Level 1 the strongest and Level 5 the weakest. The term ;surrogate' is restricted to markers attaining Levels 1 or 2 only. Surrogacy status of markers can then be directly compared within and across different areas of medicine to guide individual, trial-based or drug-development decisions. This schema would facilitate communication between clinical, researcher, regulatory, industry and consumer participants necessary for evaluation of the biomarker-surrogate-clinical endpoint relationship in their different settings.

Are viruses alive? The replicator paradigm sheds decisive light on an old but misguided question

PubMed Central

Koonin, Eugene V.; Starokadomskyy, Petro

2016-01-01

The question whether or not “viruses are alive” has caused considerable debate over many years. Yet, the question is effectively without substance because the answer depends entirely on the definition of life or the state of “being alive” that is bound to be arbitrary. In contrast, the status of viruses among biological entities is readily defined within the replicator paradigm. All biological replicators form a continuum along the selfishness-cooperativity axis, from the completely selfish to fully cooperative forms. Within this range, typical, lytic viruses represent the selfish extreme whereas temperate viruses and various mobile elements occupy positions closer to the middle of the range. Selfish replicators not only belong to the biological realm but are intrinsic to any evolving system of replicators. No such system can evolve without the emergence of parasites, and moreover, parasites drive the evolution of biological complexity at multiple levels. The history of life is a story of parasite-host coevolution that includes both the incessant arms race and various forms of cooperation. All organisms are communities of interacting, coevolving replicators of different classes. A complete theory of replicator coevolution remains to be developed, but it appears likely that not only the differentiation between selfish and cooperative replicators but the emergence of the entire range of replication strategies, from selfish to cooperative, is intrinsic to biological evolution. PMID:26965225

Using stem cell biology to study and treat ophthalmologic and oculoplastic diseases

PubMed Central

Wu, Albert Y.; Daniel, Michael G.

2017-01-01

With the rapid growth of the stem cell biology field, the prospect of regenerative medicine across multiple tissue types comes closer to reality. Several groundbreaking steps paved the way for applying stem cell biology to the several subfields within ophthalmology and oculoplastic surgery. These steps include the use of stem cell transplants as well as studies of various ophthalmologic pathologies at the molecular level. The necessity of stem cell transplant is readily apparent, having already been used for several studies such as artificial lacrimal gland design and eyelid reconstruction. Investigating the stem cell biology behind oncological diseases of the eye has also developed recently, such as with the identification of specific markers to label cancer stem cells in orbital adenoid cystic carcinoma. The advent of induced pluripotent stem cells led to a burst of productivity in the field of regenerative medicine, making it possible to take a patient's own cells, reprogram them, and use them to either study patient-specific pathology in vitro or use them for eventual patient specific therapeutics. Patient-specific adipose-derived stem cells (ASCs) have been used for a variety of treatments, such as wound healing and burn therapies. As the fields of stem cell biology and regenerative medicine continue to progress, its use will become a mainstay of patient-specific cell therapies in the future. PMID:29018761

Biological activity of selenium: Revisited.

PubMed

Wrobel, Jagoda K; Power, Ronan; Toborek, Michal

2016-02-01

Selenium (Se) is an essential micronutrient that exerts multiple and complex effects on human health. Se is essential for human well-being largely due to its potent antioxidant, anti-inflammatory, and antiviral properties. The physiological functions of Se are carried out by selenoproteins, in which Se is specifically incorporated as the amino acid, selenocysteine. Importantly, both beneficial and toxic effects of Se have been reported suggesting that the mode of action of Se is strictly chemical form and concentration dependent. Additionally, there is a relatively narrow window between Se deficiency and toxicity and growing evidence suggests that Se health effects depend greatly on the baseline level of this micronutrient. Thus, Se supplementation is not an easy task and requires an individualized approach. It is essential that we continue to explore and better characterize Se containing compounds and mechanisms of action, which could be crucial for disease prevention and treatment. © 2015 International Union of Biochemistry and Molecular Biology.

Somatostatin signaling and the regulation of growth and metabolism in fish.

PubMed

Klein, Sarah E; Sheridan, Mark A

2008-05-14

The study of the somatostatins (SS) signaling system in fish has provided important information about the structure, function, and evolution of SSs and their receptors. The SS signaling system elicits widespread biological actions via multiple hormone variants, numerous receptor subtypes, and a variety of signal transduction pathways. SSs alter growth via both direct and indirect actions, including inhibiting growth hormone release at the pituitary, decreasing hepatic GH sensitivity, and lowering plasma IGF-I levels. Metabolism also is significantly influenced by SSs. SSs stimulate the breakdown of energy stores and influences digestion, food intake, nutrient absorption, and food conversion both directly and through the modulation of other hormonal systems. The study of fish, which display a diversity of habitat types and life history forms, reveals that the SS signaling system helps regulate energy partitioning and integrate metabolism with growth and other biological processes.

Daily variations in oligosaccharides of human milk determined by microfluidic chips and mass spectrometry.

PubMed

Niñonuevo, Milady R; Perkins, Patrick D; Francis, Jimi; Lamotte, Latasha M; LoCascio, Riccardo G; Freeman, Samara L; Mills, David A; German, J Bruce; Grimm, Rudolf; Lebrilla, Carlito B

2008-01-23

Human milk is a complex biological fluid that provides not only primary nourishment for infants but also protection against pathogens and influences their metabolic, immunologic, and even cognitive development. The presence of oligosaccharides in remarkable abundance in human milk has been associated to provide diverse biological functions including directing the development of an infant's intestinal microflora and immune system. Recent advances in analytical tools offer invaluable insights in understanding the specific functions and health benefits these biomolecules impart to infants. Oligosaccharides in human milk samples obtained from five different individual donors over the course of a 3 month lactation period were isolated and analyzed using HPLC-Chip/TOF-MS technology. The levels and compositions of oligosaccharides in human milk were investigated from five individual donors. Comparison of HPLC-Chip/TOF-MS oligosaccharides profiles revealed heterogeneity among multiple individuals with no significant variations at different stages of lactation within individual donors.

Evaluating scaling models in biology using hierarchical Bayesian approaches

PubMed Central

Price, Charles A; Ogle, Kiona; White, Ethan P; Weitz, Joshua S

2009-01-01

Theoretical models for allometric relationships between organismal form and function are typically tested by comparing a single predicted relationship with empirical data. Several prominent models, however, predict more than one allometric relationship, and comparisons among alternative models have not taken this into account. Here we evaluate several different scaling models of plant morphology within a hierarchical Bayesian framework that simultaneously fits multiple scaling relationships to three large allometric datasets. The scaling models include: inflexible universal models derived from biophysical assumptions (e.g. elastic similarity or fractal networks), a flexible variation of a fractal network model, and a highly flexible model constrained only by basic algebraic relationships. We demonstrate that variation in intraspecific allometric scaling exponents is inconsistent with the universal models, and that more flexible approaches that allow for biological variability at the species level outperform universal models, even when accounting for relative increases in model complexity. PMID:19453621

A novel and rapid method for obtaining high titre intact prion strains from mammalian brain.

PubMed

Wenborn, Adam; Terry, Cassandra; Gros, Nathalie; Joiner, Susan; D'Castro, Laura; Panico, Silvia; Sells, Jessica; Cronier, Sabrina; Linehan, Jacqueline M; Brandner, Sebastian; Saibil, Helen R; Collinge, John; Wadsworth, Jonathan D F

2015-05-07

Mammalian prions exist as multiple strains which produce characteristic and highly reproducible phenotypes in defined hosts. How this strain diversity is encoded by a protein-only agent remains one of the most interesting and challenging questions in biology with wide relevance to understanding other diseases involving the aggregation or polymerisation of misfolded host proteins. Progress in understanding mammalian prion strains has however been severely limited by the complexity and variability of the methods used for their isolation from infected tissue and no high resolution structures have yet been reported. Using high-throughput cell-based prion bioassay to re-examine prion purification from first principles we now report the isolation of prion strains to exceptional levels of purity from small quantities of infected brain and demonstrate faithful retention of biological and biochemical strain properties. The method's effectiveness and simplicity should facilitate its wide application and expedite structural studies of prions.

A novel and rapid method for obtaining high titre intact prion strains from mammalian brain

PubMed Central

Wenborn, Adam; Terry, Cassandra; Gros, Nathalie; Joiner, Susan; D’Castro, Laura; Panico, Silvia; Sells, Jessica; Cronier, Sabrina; Linehan, Jacqueline M.; Brandner, Sebastian; Saibil, Helen R.; Collinge, John; Wadsworth, Jonathan D. F.

2015-01-01

Mammalian prions exist as multiple strains which produce characteristic and highly reproducible phenotypes in defined hosts. How this strain diversity is encoded by a protein-only agent remains one of the most interesting and challenging questions in biology with wide relevance to understanding other diseases involving the aggregation or polymerisation of misfolded host proteins. Progress in understanding mammalian prion strains has however been severely limited by the complexity and variability of the methods used for their isolation from infected tissue and no high resolution structures have yet been reported. Using high-throughput cell-based prion bioassay to re-examine prion purification from first principles we now report the isolation of prion strains to exceptional levels of purity from small quantities of infected brain and demonstrate faithful retention of biological and biochemical strain properties. The method’s effectiveness and simplicity should facilitate its wide application and expedite structural studies of prions. PMID:25950908

Fathering and adolescents' psychological adjustment: the role of fathers' involvement, residence and biology status.

PubMed

Flouri, E

2008-03-01

Studies on fathering and child mental health are now increasingly looking for specificity in children's psychological adjustment, indicating whether the impact of fathering is diagnostically specific or non-specific. Data from 435 fathers of secondary school-aged children in Britain were used to explore the association between resident biological fathers', non-resident biological fathers' and stepfathers' involvement and children's total difficulties, prosocial behaviour, emotional symptoms, conduct problems, hyperactivity and peer problems (all measured with the Strengths and Difficulties Questionnaire) in adolescence. After controlling for child-, father- and family-related factors, fathers' involvement was negatively associated with children's total difficulties and hyperactivity, was positively associated with children's prosocial behaviour, and was unrelated with children's emotional symptoms, conduct problems and peer problems. There was no non-resident biological father effect. Compared with resident biological fathers, stepfathers reported more total difficulties, conduct problems and hyperactivity in their children even after adjusting for involvement. Whether this reflects stepfathers' low tolerance levels or biological fathers' complacency, as sociobiologists would argue, or whether this is due to pre-existing predispositions of children in families which separate and restructure, to the effects of these multiple family changes or to the high exposure of children in restructured families to parental risk factors, is, given the data available and the study design, unclear. However, this study showed that, compared with their peers in biological father families, adolescents in stepfather families are perceived to be at higher risk of behaviour problems, and that father involvement is related to specific aspects of child adjustment.

Phenotype classification of single cells using SRS microscopy, RNA sequencing, and microfluidics (Conference Presentation)

NASA Astrophysics Data System (ADS)

Streets, Aaron M.; Cao, Chen; Zhang, Xiannian; Huang, Yanyi

2016-03-01

Phenotype classification of single cells reveals biological variation that is masked in ensemble measurement. This heterogeneity is found in gene and protein expression as well as in cell morphology. Many techniques are available to probe phenotypic heterogeneity at the single cell level, for example quantitative imaging and single-cell RNA sequencing, but it is difficult to perform multiple assays on the same single cell. In order to directly track correlation between morphology and gene expression at the single cell level, we developed a microfluidic platform for quantitative coherent Raman imaging and immediate RNA sequencing (RNA-Seq) of single cells. With this device we actively sort and trap cells for analysis with stimulated Raman scattering microscopy (SRS). The cells are then processed in parallel pipelines for lysis, and preparation of cDNA for high-throughput transcriptome sequencing. SRS microscopy offers three-dimensional imaging with chemical specificity for quantitative analysis of protein and lipid distribution in single cells. Meanwhile, the microfluidic platform facilitates single-cell manipulation, minimizes contamination, and furthermore, provides improved RNA-Seq detection sensitivity and measurement precision, which is necessary for differentiating biological variability from technical noise. By combining coherent Raman microscopy with RNA sequencing, we can better understand the relationship between cellular morphology and gene expression at the single-cell level.

An integrative model of evolutionary covariance: a symposium on body shape in fishes.

PubMed

Walker, Jeffrey A

2010-12-01

A major direction of current and future biological research is to understand how multiple, interacting functional systems coordinate in producing a body that works. This understanding is complicated by the fact that organisms need to work well in multiple environments, with both predictable and unpredictable environmental perturbations. Furthermore, organismal design reflects a history of past environments and not a plan for future environments. How complex, interacting functional systems evolve, then, is a truly grand challenge. In accepting the challenge, an integrative model of evolutionary covariance is developed. The model combines quantitative genetics, functional morphology/physiology, and functional ecology. The model is used to convene scientists ranging from geneticists, to physiologists, to ecologists, to engineers to facilitate the emergence of body shape in fishes as a model system for understanding how complex, interacting functional systems develop and evolve. Body shape of fish is a complex morphology that (1) results from many developmental paths and (2) functions in many different behaviors. Understanding the coordination and evolution of the many paths from genes to body shape, body shape to function, and function to a working fish body in a dynamic environment is now possible given new technologies from genetics to engineering and new theoretical models that integrate the different levels of biological organization (from genes to ecology).

Generation of light-sheet at the end of multimode fibre (Conference Presentation)

NASA Astrophysics Data System (ADS)

Plöschner, Martin; Kollárová, Véra; Dostál, Zbyněk.; Nylk, Jonathan; Barton-Owen, Thomas; Ferrier, David E. K.; Chmelik, Radim; Dholakia, Kishan; Cizmár, TomáÅ.¡

2017-02-01

Light-sheet fluorescence microscopy is quickly becoming one of the cornerstone imaging techniques in biology as it provides rapid, three-dimensional sectioning of specimens at minimal levels of phototoxicity. It is very appealing to bring this unique combination of imaging properties into an endoscopic setting and be able to perform optical sectioning deep in tissues. Current endoscopic approaches for delivery of light-sheet illumination are based on single-mode optical fibre terminated by cylindrical gradient index lens. Such configuration generates a light-sheet plane that is axially fixed and a mechanical movement of either the sample or the endoscope is required to acquire three-dimensional information about the sample. Furthermore, the axial resolution of this technique is limited to 5um. The delivery of the light-sheet through the multimode fibre provides better axial resolution limited only by its numerical aperture, the light-sheet is scanned holographically without any mechanical movement, and multiple advanced light-sheet imaging modalities, such as Bessel and structured illumination Bessel beam, are intrinsically supported by the system due to the cylindrical symmetry of the fibre. We discuss the holographic techniques for generation of multiple light-sheet types and demonstrate the imaging on a sample of fluorescent beads fixed in agarose gel, as well as on a biological sample of Spirobranchus Lamarcki.

Irreparable complex DNA double-strand breaks induce chromosome breakage in organotypic three-dimensional human lung epithelial cell culture

PubMed Central

Asaithamby, Aroumougame; Hu, Burong; Delgado, Oliver; Ding, Liang-Hao; Story, Michael D.; Minna, John D.; Shay, Jerry W.; Chen, David J.

2011-01-01

DNA damage and consequent mutations initiate the multistep carcinogenic process. Differentiated cells have a reduced capacity to repair DNA lesions, but the biological impact of unrepaired DNA lesions in differentiated lung epithelial cells is unclear. Here, we used a novel organotypic human lung three-dimensional (3D) model to investigate the biological significance of unrepaired DNA lesions in differentiated lung epithelial cells. We showed, consistent with existing notions that the kinetics of loss of simple double-strand breaks (DSBs) were significantly reduced in organotypic 3D culture compared to kinetics of repair in two-dimensional (2D) culture. Strikingly, we found that, unlike simple DSBs, a majority of complex DNA lesions were irreparable in organotypic 3D culture. Levels of expression of multiple DNA damage repair pathway genes were significantly reduced in the organotypic 3D culture compared with those in 2D culture providing molecular evidence for the defective DNA damage repair in organotypic culture. Further, when differentiated cells with unrepaired DNA lesions re-entered the cell cycle, they manifested a spectrum of gross-chromosomal aberrations in mitosis. Our data suggest that downregulation of multiple DNA repair pathway genes in differentiated cells renders them vulnerable to DSBs, promoting genome instability that may lead to carcinogenesis. PMID:21421565

Multiscale Mechanics of Articular Cartilage: Potentials and Challenges of Coupling Musculoskeletal, Joint, and Microscale Computational Models

PubMed Central

Halloran, J. P.; Sibole, S.; van Donkelaar, C. C.; van Turnhout, M. C.; Oomens, C. W. J.; Weiss, J. A.; Guilak, F.; Erdemir, A.

2012-01-01

Articular cartilage experiences significant mechanical loads during daily activities. Healthy cartilage provides the capacity for load bearing and regulates the mechanobiological processes for tissue development, maintenance, and repair. Experimental studies at multiple scales have provided a fundamental understanding of macroscopic mechanical function, evaluation of the micromechanical environment of chondrocytes, and the foundations for mechanobiological response. In addition, computational models of cartilage have offered a concise description of experimental data at many spatial levels under healthy and diseased conditions, and have served to generate hypotheses for the mechanical and biological function. Further, modeling and simulation provides a platform for predictive risk assessment, management of dysfunction, as well as a means to relate multiple spatial scales. Simulation-based investigation of cartilage comes with many challenges including both the computational burden and often insufficient availability of data for model development and validation. This review outlines recent modeling and simulation approaches to understand cartilage function from a mechanical systems perspective, and illustrates pathways to associate mechanics with biological function. Computational representations at single scales are provided from the body down to the microstructure, along with attempts to explore multiscale mechanisms of load sharing that dictate the mechanical environment of the cartilage and chondrocytes. PMID:22648577

Development of a Biological Science Quantitative Reasoning Exam (BioSQuaRE)

PubMed Central

Stanhope, Liz; Ziegler, Laura; Haque, Tabassum; Le, Laura; Vinces, Marcelo; Davis, Gregory K.; Zieffler, Andrew; Brodfuehrer, Peter; Preest, Marion; M. Belitsky, Jason; Umbanhowar, Charles; Overvoorde, Paul J.

2017-01-01

Multiple reports highlight the increasingly quantitative nature of biological research and the need to innovate means to ensure that students acquire quantitative skills. We present a tool to support such innovation. The Biological Science Quantitative Reasoning Exam (BioSQuaRE) is an assessment instrument designed to measure the quantitative skills of undergraduate students within a biological context. The instrument was developed by an interdisciplinary team of educators and aligns with skills included in national reports such as BIO2010, Scientific Foundations for Future Physicians, and Vision and Change. Undergraduate biology educators also confirmed the importance of items included in the instrument. The current version of the BioSQuaRE was developed through an iterative process using data from students at 12 postsecondary institutions. A psychometric analysis of these data provides multiple lines of evidence for the validity of inferences made using the instrument. Our results suggest that the BioSQuaRE will prove useful to faculty and departments interested in helping students acquire the quantitative competencies they need to successfully pursue biology, and useful to biology students by communicating the importance of quantitative skills. We invite educators to use the BioSQuaRE at their own institutions. PMID:29196427

Deciphering the associations between gene expression and copy number alteration using a sparse double Laplacian shrinkage approach

PubMed Central

Shi, Xingjie; Zhao, Qing; Huang, Jian; Xie, Yang; Ma, Shuangge

2015-01-01

Motivation: Both gene expression levels (GEs) and copy number alterations (CNAs) have important biological implications. GEs are partly regulated by CNAs, and much effort has been devoted to understanding their relations. The regulation analysis is challenging with one gene expression possibly regulated by multiple CNAs and one CNA potentially regulating the expressions of multiple genes. The correlations among GEs and among CNAs make the analysis even more complicated. The existing methods have limitations and cannot comprehensively describe the regulation. Results: A sparse double Laplacian shrinkage method is developed. It jointly models the effects of multiple CNAs on multiple GEs. Penalization is adopted to achieve sparsity and identify the regulation relationships. Network adjacency is computed to describe the interconnections among GEs and among CNAs. Two Laplacian shrinkage penalties are imposed to accommodate the network adjacency measures. Simulation shows that the proposed method outperforms the competing alternatives with more accurate marker identification. The Cancer Genome Atlas data are analysed to further demonstrate advantages of the proposed method. Availability and implementation: R code is available at http://works.bepress.com/shuangge/49/ Contact: shuangge.ma@yale.edu Supplementary information: Supplementary data are available at Bioinformatics online. PMID:26342102

Fluorescent probes for the simultaneous detection of multiple analytes in biology.

PubMed

Kolanowski, Jacek L; Liu, Fei; New, Elizabeth J

2018-01-02

Many of the key questions facing cellular biology concern the location and concentration of chemical species, from signalling molecules to metabolites to exogenous toxins. Fluorescent sensors (probes) have revolutionised the understanding of biological systems through their exquisite sensitivity to specific analytes. Probe design has focussed on selective sensors for individual analytes, but many of the most pertinent biological questions are related to the interaction of more than one chemical species. While it is possible to simultaneously use multiple sensors for such applications, data interpretation will be confounded by the fact that sensors will have different uptake, localisation and metabolism profiles. An alternative solution is to instead use a single probe that responds to two analytes, termed a dual-responsive probe. Recent progress in this field has yielded exciting probes, some of which have demonstrated biological application. Here we review work that has been carried out to date, and suggest future research directions that will harness the considerable potential of dual-responsive fluorescent probes.

Versatile and on-demand biologics co-production in yeast.

PubMed

Cao, Jicong; Perez-Pinera, Pablo; Lowenhaupt, Ky; Wu, Ming-Ru; Purcell, Oliver; de la Fuente-Nunez, Cesar; Lu, Timothy K

2018-01-08

Current limitations to on-demand drug manufacturing can be addressed by technologies that streamline manufacturing processes. Combining the production of two or more drugs into a single batch could not only be useful for research, clinical studies, and urgent therapies but also effective when combination therapies are needed or where resources are scarce. Here we propose strategies to concurrently produce multiple biologics from yeast in single batches by multiplexing strain development, cell culture, separation, and purification. We demonstrate proof-of-concept for three biologics co-production strategies: (i) inducible expression of multiple biologics and control over the ratio between biologic drugs produced together; (ii) consolidated bioprocessing; and (iii) co-expression and co-purification of a mixture of two monoclonal antibodies. We then use these basic strategies to produce drug mixtures as well as to separate drugs. These strategies offer a diverse array of options for on-demand, flexible, low-cost, and decentralized biomanufacturing applications without the need for specialized equipment.

Strategies for Controlled Delivery of Biologics for Cartilage Repair

PubMed Central

Lam, Johnny; Lu, Steven; Kasper, F. Kurtis; Mikos, Antonios G.

2014-01-01

The delivery of biologics is an important component in the treatment of osteoarthritis and the functional restoration of articular cartilage. Numerous factors have been implicated in the cartilage repair process, but the uncontrolled delivery of these factors may not only reduce their full reparative potential and can also cause unwanted morphological effects. It is therefore imperative to consider the type of biologic to be delivered, the method of delivery, and the temporal as well as spatial presentation of the biologic to achieve the desired effect in cartilage repair. Additionally, the delivery of a single factor may not be sufficient in guiding neo-tissue formation, motivating recent research towards the delivery of multiple factors. This review will discuss the roles of various biologics involved in cartilage repair and the different methods of delivery for appropriate healing responses. A number of spatiotemporal strategies will then be emphasized for the controlled delivery of single and multiple bioactive factors in both in vitro and in vivo cartilage tissue engineering applications. PMID:24993610

Genetic variation influences glutamate concentrations in brains of patients with multiple sclerosis.

PubMed

Baranzini, Sergio E; Srinivasan, Radhika; Khankhanian, Pouya; Okuda, Darin T; Nelson, Sarah J; Matthews, Paul M; Hauser, Stephen L; Oksenberg, Jorge R; Pelletier, Daniel

2010-09-01

Glutamate is the main excitatory neurotransmitter in the mammalian brain. Appropriate transmission of nerve impulses through glutamatergic synapses is required throughout the brain and forms the basis of many processes including learning and memory. However, abnormally high levels of extracellular brain glutamate can lead to neuroaxonal cell death. We have previously reported elevated glutamate levels in the brains of patients suffering from multiple sclerosis. Here two complementary analyses to assess the extent of genomic control over glutamate levels were used. First, a genome-wide association analysis in 382 patients with multiple sclerosis using brain glutamate concentration as a quantitative trait was conducted. In a second approach, a protein interaction network was used to find associated genes within the same pathway. The top associated marker was rs794185 (P < 6.44 x 10(-7)), a non-coding single nucleotide polymorphism within the gene sulphatase modifying factor 1. Our pathway approach identified a module composed of 70 genes with high relevance to glutamate biology. Individuals carrying a higher number of associated alleles from genes in this module showed the highest levels of glutamate. These individuals also showed greater decreases in N-acetylaspartate and in brain volume over 1 year of follow-up. Patients were then stratified by the amount of annual brain volume loss and the same approach was performed in the 'high' (n = 250) and 'low' (n = 132) neurodegeneration groups. The association with rs794185 was highly significant in the group with high neurodegeneration. Further, results from the network-based pathway analysis remained largely unchanged even after stratification. Results from these analyses indicated that variance in the activity of neurochemical pathways implicated in neurodegeneration is explained, at least in part, by the inheritance of common genetic polymorphisms. Spectroscopy-based imaging provides a novel quantitative endophenotype for genetic association studies directed towards identifying new factors that contribute to the heterogeneity of clinical expression of multiple sclerosis.

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.

Social relationships and their biological correlates: Coronary Artery Risk Development in Young Adults (CARDIA) study.

PubMed

Seeman, Teresa E; Gruenewald, Tara L; Cohen, Sheldon; Williams, David R; Matthews, Karen A

2014-05-01

Analyses test the hypothesis that aspects of social relationships (quantity of ties, social support and social strain) are associated with differences in levels of biological risk across multiple major physiological regulatory systems and consequently overall multi-systems risk (i.e., allostatic load [AL]). Data are from the Coronary Artery Risk Development in Young Adults (CARDIA) study--a bi-ethnic, prospective, multi-center epidemiological study, initiated in 1985-1986 to track the development of cardiovascular risk in young adulthood (N=5115). At the year 15 follow-up when participants were between 32 and 45 years of age, additional social and biological data were collected; biological data used to assess AL were collected at the Oakland, CA and Chicago, IL sites (N=844). Social strains were most strongly and positively related to overall AL (Cohen's d=.79 for highest vs. lowest quartile), and to each of its component biological subsystems, independent of social ties and support as well as sociodemographics and health behaviors. Social ties and emotional support were also negatively related to AL (Cohen's d=.33 and d=.44 for lowest vs. highest quartiles of ties and support, respectively) though controls for social strains reduced these associations to non-significance. Social support and social strain were more strongly related to overall AL than to any of its component subscales while social ties were less strongly related to AL and to its component subscales. There was no evidence that effects differed by sex, age or ethnicity. Findings focus attention on the particularly strong relationship between social strains and profiles of biological risk and support the cumulative impact of social factors on biological risks, showing larger effects for cumulative AL than for any of the individual biological systems. Copyright © 2014 Elsevier Ltd. All rights reserved.

Identifying Martian Hydrothermal Sites: Geological Investigation Utilizing Multiple Datasets

NASA Technical Reports Server (NTRS)

Dohm, J. M.; Baker, V. R.; Anderson, R. C.; Scott, D. H.; Rice, J. W., Jr.; Hare, T. M.

2000-01-01

Comprehensive geological investigations of martian landscapes that may have been modified by magmatic-driven hydrothermal activity, utilizing multiple datasets, will yield prime target sites for future hydrological, mineralogical, and biological investigations.

Multi-scale chromatin state annotation using a hierarchical hidden Markov model

NASA Astrophysics Data System (ADS)

Marco, Eugenio; Meuleman, Wouter; Huang, Jialiang; Glass, Kimberly; Pinello, Luca; Wang, Jianrong; Kellis, Manolis; Yuan, Guo-Cheng

2017-04-01

Chromatin-state analysis is widely applied in the studies of development and diseases. However, existing methods operate at a single length scale, and therefore cannot distinguish large domains from isolated elements of the same type. To overcome this limitation, we present a hierarchical hidden Markov model, diHMM, to systematically annotate chromatin states at multiple length scales. We apply diHMM to analyse a public ChIP-seq data set. diHMM not only accurately captures nucleosome-level information, but identifies domain-level states that vary in nucleosome-level state composition, spatial distribution and functionality. The domain-level states recapitulate known patterns such as super-enhancers, bivalent promoters and Polycomb repressed regions, and identify additional patterns whose biological functions are not yet characterized. By integrating chromatin-state information with gene expression and Hi-C data, we identify context-dependent functions of nucleosome-level states. Thus, diHMM provides a powerful tool for investigating the role of higher-order chromatin structure in gene regulation.

Inhibition-Based Biomarkers for Autism Spectrum Disorder.

PubMed

Levin, April R; Nelson, Charles A

2015-07-01

Autism spectrum disorder (ASD) is a behaviorally defined and heterogeneous disorder. Biomarkers for ASD offer the opportunity to improve prediction, diagnosis, stratification by severity and subtype, monitoring over time and in response to interventions, and overall understanding of the underlying biology of this disorder. A variety of potential biomarkers, from the level of genes and proteins to network-level interactions, is currently being examined. Many of these biomarkers relate to inhibition, which is of particular interest because in many cases ASD is thought to be a disorder of imbalance between excitation and inhibition. Abnormalities in inhibition at the cellular level lead to emergent properties in networks of neurons. These properties take into account a more complete genetic and cellular background than findings at the level of individual genes or cells, and are able to be measured in live humans, offering additional potential as diagnostic biomarkers and predictors of behaviors. In this review we provide examples of how altered inhibition may inform the search for ASD biomarkers at multiple levels, from genes to cells to networks.

Into the field: naturalistic education and the future of conservation.

PubMed

Hayes, Mark A

2009-10-01

Some educational psychologists and researchers have argued that there are multiple ways of being intelligent. In the early 1980s, Howard Gardner presented a theory of multiple intelligences by proposing that humans can be described not by a single kind of intelligence, or intelligence quotient score, but rather by a variety of kinds of intelligence. This idea of considering multiple views of intelligence has helped educators look at intelligence from a less rigid, more expansive perspective. I considered how the relatively new concept of naturalistic intelligence, which is the cognitive potential to process information that is exhibited by expert naturalists, might influence the design of undergraduate biology curricula. Naturalistic intelligence can be fostered in undergraduate biology students by emphasizing the need for well-rounded scientific naturalists; developing curricula that involves students in outdoor inquiry-based projects; and helping students learn how to observe both the natural world and their own learning, skills that are essential to developing expert naturalistic knowledge. Professors, graduate students, and administrators can improve the naturalistic intelligence of undergraduate biology students by giving these students opportunities to be involved in outdoor research. Time spent outdoors alone and among people with expertise in natural history, ecology, and conservation biology will have important influences on the knowledge and skills biology undergraduates learn, the careers they pursue, and the contributions they make to conserving Earth's biodiversity.

Configuration of multiple human stressors and their impacts on fish assemblages in Alpine river basins of Austria.

PubMed

Schinegger, Rafaela; Pucher, Matthias; Aschauer, Christiane; Schmutz, Stefan

2018-03-01

This work addresses multiple human stressors and their impacts on fish assemblages of the Drava and Mura rivers in southern Austria. The impacts of single and multiple human stressors on riverine fish assemblages in these basins were disentangled, based on an extensive dataset. Stressor configuration, i.e. various metrics of multiple stressors belonging to stressor groups hydrology, morphology, connectivity and water quality were investigated for the first time at river basin scale in Austria. As biological response variables, the Fish Index Austria (FIA) and its related single as well as the WFD biological- and total state were investigated. Stressor-response analysis shows divergent results, but a general trend of decreasing ecological integrity with increasing number of stressors and maximum stressor is observed. Fish metrics based on age structure, fish region index and biological status responded best to single stressors and/or their combinations. The knowledge gained in this work provides a basis for advanced investigations in Alpine river basins and beyond, supports WFD implementation and helps prioritizing further actions towards multi-stressor restoration- and management. Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.

Statistical inference from multiple iTRAQ experiments without using common reference standards.

PubMed

Herbrich, Shelley M; Cole, Robert N; West, Keith P; Schulze, Kerry; Yager, James D; Groopman, John D; Christian, Parul; Wu, Lee; O'Meally, Robert N; May, Damon H; McIntosh, Martin W; Ruczinski, Ingo

2013-02-01

Isobaric tags for relative and absolute quantitation (iTRAQ) is a prominent mass spectrometry technology for protein identification and quantification that is capable of analyzing multiple samples in a single experiment. Frequently, iTRAQ experiments are carried out using an aliquot from a pool of all samples, or "masterpool", in one of the channels as a reference sample standard to estimate protein relative abundances in the biological samples and to combine abundance estimates from multiple experiments. In this manuscript, we show that using a masterpool is counterproductive. We obtain more precise estimates of protein relative abundance by using the available biological data instead of the masterpool and do not need to occupy a channel that could otherwise be used for another biological sample. In addition, we introduce a simple statistical method to associate proteomic data from multiple iTRAQ experiments with a numeric response and show that this approach is more powerful than the conventionally employed masterpool-based approach. We illustrate our methods using data from four replicate iTRAQ experiments on aliquots of the same pool of plasma samples and from a 406-sample project designed to identify plasma proteins that covary with nutrient concentrations in chronically undernourished children from South Asia.

Mammalian designer cells: Engineering principles and biomedical applications.

PubMed

Xie, Mingqi; Fussenegger, Martin

2015-07-01

Biotechnology is a widely interdisciplinary field focusing on the use of living cells or organisms to solve established problems in medicine, food production and agriculture. Synthetic biology, the science of engineering complex biological systems that do not exist in nature, continues to provide the biotechnology industry with tools, technologies and intellectual property leading to improved cellular performance. One key aspect of synthetic biology is the engineering of deliberately reprogrammed designer cells whose behavior can be controlled over time and space. This review discusses the most commonly used techniques to engineer mammalian designer cells; while control elements acting on the transcriptional and translational levels of target gene expression determine the kinetic and dynamic profiles, coupling them to a variety of extracellular stimuli permits their remote control with user-defined trigger signals. Designer mammalian cells with novel or improved biological functions not only directly improve the production efficiency during biopharmaceutical manufacturing but also open the door for cell-based treatment strategies in molecular and translational medicine. In the future, the rational combination of multiple sets of designer cells could permit the construction and regulation of higher-order systems with increased complexity, thereby enabling the molecular reprogramming of tissues, organisms or even populations with highest precision. Copyright © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Novel Transcriptional Activities of Vitamin E: Inhibition of Cholesterol Biosynthesis

PubMed Central

Valastyan, Scott; Thakur, Varsha; Johnson, Amy; Kumar, Karan; Manor, Danny

2008-01-01

Vitamin E is a dietary lipid that is essential for vertebrate health and fertility. The biological activity of vitamin E is thought to reflect its ability to quench oxygen- and carbon- based free radicals, and thus to protect the organism from oxidative damage. However, recent reports suggest that vitamin E may also display other biological activities. Here, to examine possible mechanisms that may underlie such non-classical activities of vitamin E, we investigated the possibility that it functions as a specific modulator of gene expression. We show that treatment of cultured hepatocytes with RRR-α-tocopherol alters the expression of multiple genes and that these effects are distinct from those elicited by another antioxidant. Genes modulated by vitamin E include those that encode key enzymes in the cholesterol biosynthetic pathway. Correspondingly, vitamin E caused a pronounced inhibition of de novo cholesterol biosynthesis. The transcriptional activities of vitamin E were mediated by attenuating the post-translational processing of the transcription factor SREBP-2 that, in turn, led to a decreased transcriptional activity of sterol responsive elements in the promoters of target genes. These observations indicate that vitamin E possesses novel transcriptional activities that affect fundamental biological processes. Cross talk between tocopherol levels and cholesterol status may be an important facet of the biological activities of vitamin E. PMID:18095660

Aging effects on DNA methylation modules in human brain and blood tissue

PubMed Central

2012-01-01

Background Several recent studies reported aging effects on DNA methylation levels of individual CpG dinucleotides. But it is not yet known whether aging-related consensus modules, in the form of clusters of correlated CpG markers, can be found that are present in multiple human tissues. Such a module could facilitate the understanding of aging effects on multiple tissues. Results We therefore employed weighted correlation network analysis of 2,442 Illumina DNA methylation arrays from brain and blood tissues, which enabled the identification of an age-related co-methylation module. Module preservation analysis confirmed that this module can also be found in diverse independent data sets. Biological evaluation showed that module membership is associated with Polycomb group target occupancy counts, CpG island status and autosomal chromosome location. Functional enrichment analysis revealed that the aging-related consensus module comprises genes that are involved in nervous system development, neuron differentiation and neurogenesis, and that it contains promoter CpGs of genes known to be down-regulated in early Alzheimer's disease. A comparison with a standard, non-module based meta-analysis revealed that selecting CpGs based on module membership leads to significantly increased gene ontology enrichment, thus demonstrating that studying aging effects via consensus network analysis enhances the biological insights gained. Conclusions Overall, our analysis revealed a robustly defined age-related co-methylation module that is present in multiple human tissues, including blood and brain. We conclude that blood is a promising surrogate for brain tissue when studying the effects of age on DNA methylation profiles. PMID:23034122

Combining fungal biopesticides and insecticide-treated bednets to enhance malaria control.

PubMed

Hancock, Penelope A

2009-10-01

In developing strategies to control malaria vectors, there is increased interest in biological methods that do not cause instant vector mortality, but have sublethal and lethal effects at different ages and stages in the mosquito life cycle. These techniques, particularly if integrated with other vector control interventions, may produce substantial reductions in malaria transmission due to the total effect of alterations to multiple life history parameters at relevant points in the life-cycle and transmission-cycle of the vector. To quantify this effect, an analytically tractable gonotrophic cycle model of mosquito-malaria interactions is developed that unites existing continuous and discrete feeding cycle approaches. As a case study, the combined use of fungal biopesticides and insecticide treated bednets (ITNs) is considered. Low values of the equilibrium EIR and human prevalence were obtained when fungal biopesticides and ITNs were combined, even for scenarios where each intervention acting alone had relatively little impact. The effect of the combined interventions on the equilibrium EIR was at least as strong as the multiplicative effect of both interventions. For scenarios representing difficult conditions for malaria control, due to high transmission intensity and widespread insecticide resistance, the effect of the combined interventions on the equilibrium EIR was greater than the multiplicative effect, as a result of synergistic interactions between the interventions. Fungal biopesticide application was found to be most effective when ITN coverage was high, producing significant reductions in equilibrium prevalence for low levels of biopesticide coverage. By incorporating biological mechanisms relevant to vectorial capacity, continuous-time vector population models can increase their applicability to integrated vector management.

Advancing Risk Assessment through the Application of Systems Toxicology

PubMed Central

Sauer, John Michael; Kleensang, André; Peitsch, Manuel C.; Hayes, A. Wallace

2016-01-01

Risk assessment is the process of quantifying the probability of a harmful effect to individuals or populations from human activities. Mechanistic approaches to risk assessment have been generally referred to as systems toxicology. Systems toxicology makes use of advanced analytical and computational tools to integrate classical toxicology and quantitative analysis of large networks of molecular and functional changes occurring across multiple levels of biological organization. Three presentations including two case studies involving both in vitro and in vivo approaches described the current state of systems toxicology and the potential for its future application in chemical risk assessment. PMID:26977253

Advances in assessment, diagnosis, and treatment of hyperthyroidism in children.

PubMed

Amer, Kim Siarkowski

2005-04-01

The thyroid gland is responsible for regulating multiple complex metabolic processes that affect most organs. Physical growth and cognitive development are dependent on proper levels of thyroid hormone. This article will review common challenges in the diagnosis of hyperthyroidism in children, the approaches to treatment, and the nursing interventions guided toward child and family responses to thyroid disease. A comparison of signs and symptoms of hypothyroidism and hyperthyroidism is also included. The nursing interventions addressed in the article integrate the biological, psychological, social, and environmental stresses and adaptations necessary to cope with hyperthyroid disease.

Molecular biological analysis in a patient with multiple lung adenocarcinomas.

PubMed

Wakayama, Tomoshige; Hirata, Hirokuni; Suka, Shunsuke; Sato, Kozo; Tatewaki, Masamitsu; Souma, Ryosuke; Satoh, Hideyuki; Tamura, Motohiko; Matsumura, Yuji; Imada, Hiroki; Sugiyama, Kumiya; Arima, Masafumi; Kurasawa, Kazuhiro; Fukuda, Takeshi; Fukushima, Yasutsugu

2018-05-01

The utility of molecular biological analysis in lung adenocarcinoma has been demonstrated. Herein we report a rare case presenting as multiple lung adenocarcinomas with four different EGFR gene mutations detected in three lung tumors. After opacification was detected by routine chest X-ray, the patient, a 64-year-old woman, underwent chest computed tomography which revealed a right lung segment S4 ground-glass nodule (GGN). Follow-up computed tomography revealed a 42 mm GGN nodule with a 26 mm nodule (S6) and a 20 mm GGN (S10). Histopathology of resected specimens from the right middle and lower lobes revealed all three nodules were adenocarcinomas. Four EGFR mutations were detected; no three tumors had the same mutations. Molecular biological analysis is a promising tool for the diagnosis of primary tumors in patients with multiple lung carcinomas of the same histotype, enabling appropriate treatment. © 2018 The Authors. Thoracic Cancer published by China Lung Oncology Group and John Wiley & Sons Australia, Ltd.

Removal of Multiple Contaminants: Biological Treatment

EPA Science Inventory

This presentation contains (1) background material on nitrate, perchlorate and ammonia contamination in the continental US; (2) scientific background on biological drinking water treatment; (3) results of bench-scale anaerobic and aerobic treatment studies; (4) results of pilot-s...

Hybrid coexpression link similarity graph clustering for mining biological modules from multiple gene expression datasets.

PubMed

Salem, Saeed; Ozcaglar, Cagri

2014-01-01

Advances in genomic technologies have enabled the accumulation of vast amount of genomic data, including gene expression data for multiple species under various biological and environmental conditions. Integration of these gene expression datasets is a promising strategy to alleviate the challenges of protein functional annotation and biological module discovery based on a single gene expression data, which suffers from spurious coexpression. We propose a joint mining algorithm that constructs a weighted hybrid similarity graph whose nodes are the coexpression links. The weight of an edge between two coexpression links in this hybrid graph is a linear combination of the topological similarities and co-appearance similarities of the corresponding two coexpression links. Clustering the weighted hybrid similarity graph yields recurrent coexpression link clusters (modules). Experimental results on Human gene expression datasets show that the reported modules are functionally homogeneous as evident by their enrichment with biological process GO terms and KEGG pathways.

New biological agents in the treatment of multiple sclerosis.

PubMed

Buc, M

2018-01-01

Multiple sclerosis (MS) is an inflammatory disease induced by autoimmune processes. Their understanding has resulted in an introduction of biological agents to its treatment. Interferon beta and glatiramer acetate have been in clinical practice for more than 20 years. Nowadays, novel biologics, which target molecules involved in immunopathological processes more specifically have entered the scene. They are represented by monoclonal antibodies binding to molecules VLA4 (natalizumab), CD20 (ocrelizumab), CD52 (alemtuzumab) or alpha subunit of IL-2 receptor (daclizumab) or by small molecules such as those modulating the receptors involved in regulation of lymphocyte migration (fingolimod, ozanimod) or in induction of lymphopenia by apoptosis (dimethyl fumarate, cladribine). In the article, we shortly describe their efficacies, adverse reactions and perspectives of a future development in MS biologics. A treatment of neuromyelitis optica by monoclonal antibodies (rituximab, aquaporumab) is given too (Tab. 1, Fig. 2, Ref. 71).

Development and Analysis of an Instrument to Assess Student Understanding of Foundational Concepts before Biochemistry Coursework

ERIC Educational Resources Information Center

Villafane, Sachel M.; Bailey, Cheryl P.; Loertscher, Jennifer; Minderhout, Vicky; Lewis, Jennifer E.

2011-01-01

Biochemistry is a challenging subject because student learning depends on the application of previously learned concepts from general chemistry and biology to new, biological contexts. This article describes the development of a multiple-choice instrument intended to measure five concepts from general chemistry and three from biology that are…

Infusion of Quantitative and Statistical Concepts into Biology Courses Does Not Improve Quantitative Literacy

ERIC Educational Resources Information Center

Beck, Christopher W.

2018-01-01

Multiple national reports have pushed for the integration of quantitative concepts into the context of disciplinary science courses. The aim of this study was to evaluate the quantitative and statistical literacy of biology students and explore learning gains when those skills were taught implicitly in the context of biology. I examined gains in…

Exploring Pedagogical Content Knowledge of Biology Graduate Teaching Assistants through Their Participation in Lesson Study

ERIC Educational Resources Information Center

Lampley, Sandra A.; Gardner, Grant E.; Barlow, Angela T.

2018-01-01

Graduate teaching assistants (GTAs) are responsible for teaching the majority of biology undergraduate laboratory sections, although many feel underprepared to do so. This study explored the impact of biology GTA participation in a professional development model known as lesson study. Using a case study methodology with multiple qualitative data…

Multiple year effects of a biological control agent (Diorhabda carinulata) on Tamarix (saltcedar) ecosystem exchanges of carbon dioxide and water

USDA-ARS?s Scientific Manuscript database

Biological control of Tamarix spp. (saltcedar) with Diorhabda carinulata (the northern tamarisk beetle) is currently underway in several western states U.S.A. through historical releases and the natural migration of this insect. Given the widespread dispersal of this biological control agent and its...

Closing the Loop: Involving Faculty in the Assessment of Scientific and Quantitative Reasoning Skills of Biology Majors

ERIC Educational Resources Information Center

Hurney, Carol A.; Brown, Justin; Griscom, Heather Peckham; Kancler, Erika; Wigtil, Clifton J.; Sundre, Donna

2011-01-01

The development of scientific and quantitative reasoning skills in undergraduates majoring in science, technology, engineering, and mathematics (STEM) is an objective of many courses and curricula. The Biology Department at James Madison University (JMU) assesses these essential skills in graduating biology majors by using a multiple-choice exam…

Generation of mammalian cells stably expressing multiple genes at predetermined levels.

PubMed

Liu, X; Constantinescu, S N; Sun, Y; Bogan, J S; Hirsch, D; Weinberg, R A; Lodish, H F

2000-04-10

Expression of cloned genes at desired levels in cultured mammalian cells is essential for studying protein function. Controlled levels of expression have been difficult to achieve, especially for cell lines with low transfection efficiency or when expression of multiple genes is required. An internal ribosomal entry site (IRES) has been incorporated into many types of expression vectors to allow simultaneous expression of two genes. However, there has been no systematic quantitative analysis of expression levels in individual cells of genes linked by an IRES, and thus the broad use of these vectors in functional analysis has been limited. We constructed a set of retroviral expression vectors containing an IRES followed by a quantitative selectable marker such as green fluorescent protein (GFP) or truncated cell surface proteins CD2 or CD4. The gene of interest is placed in a multiple cloning site 5' of the IRES sequence under the control of the retroviral long terminal repeat (LTR) promoter. These vectors exploit the approximately 100-fold differences in levels of expression of a retrovirus vector depending on its site of insertion in the host chromosome. We show that the level of expression of the gene downstream of the IRES and the expression level and functional activity of the gene cloned upstream of the IRES are highly correlated in stably infected target cells. This feature makes our vectors extremely useful for the rapid generation of stably transfected cell populations or clonal cell lines expressing specific amounts of a desired protein simply by fluorescent activated cell sorting (FACS) based on the level of expression of the gene downstream of the IRES. We show how these vectors can be used to generate cells expressing high levels of the erythropoietin receptor (EpoR) or a dominant negative Smad3 protein and to generate cells expressing two different cloned proteins, Ski and Smad4. Correlation of a biologic effect with the level of expression of the protein downstream of the IRES provides strong evidence for the function of the protein placed upstream of the IRES.

Evidence of cellular stress and caspase-3 resulting from a combined two-frequency signal in the cerebrum and cerebellum of Sprague-dawley rats

PubMed Central

López-Furelos, Alberto; Leiro-Vidal, José Manuel; Salas-Sánchez, Aarón Ángel; Ares-Pena, Francisco José; López-Martín, María Elena

2016-01-01

Multiple simultaneous exposures to electromagnetic signals induced adjustments in mammal nervous systems. In this study, we investigated the non-thermal SAR (Specific Absorption Rate) in the cerebral or cerebellar hemispheres of rats exposed in vivo to combined electromagnetic field (EMF) signals at 900 and 2450 MHz. Forty rats divided into four groups of 10 were individually exposed or not exposed to radiation in a GTEM chamber for one or two hours. After radiation, we used the Chemiluminescent Enzyme-Linked Immunosorbent Assay (ChELISA) technique to measure cellular stress levels, indicated by the presence of heat shock proteins (HSP) 90 and 70, as well as caspase-3-dependent pre-apoptotic activity in left and right cerebral and cerebellar hemispheres of Sprague Dawley rats. Twenty-four hours after exposure to combined or single radiation, significant differences were evident in HSP 90 and 70 but not in caspase 3 levels between the hemispheres of the cerebral cortex at high SAR levels. In the cerebellar hemispheres, groups exposed to a single radiofrequency (RF) and high SAR showed significant differences in HSP 90, 70 and caspase-3 levels compared to control animals. The absorbed energy and/or biological effects of combined signals were not additive, suggesting that multiple signals act on nervous tissue by a different mechanism. PMID:27589837

Climate change and freshwater ecosystems: impacts across multiple levels of organization

PubMed Central

Woodward, Guy; Perkins, Daniel M.; Brown, Lee E.

2010-01-01

Fresh waters are particularly vulnerable to climate change because (i) many species within these fragmented habitats have limited abilities to disperse as the environment changes; (ii) water temperature and availability are climate-dependent; and (iii) many systems are already exposed to numerous anthropogenic stressors. Most climate change studies to date have focused on individuals or species populations, rather than the higher levels of organization (i.e. communities, food webs, ecosystems). We propose that an understanding of the connections between these different levels, which are all ultimately based on individuals, can help to develop a more coherent theoretical framework based on metabolic scaling, foraging theory and ecological stoichiometry, to predict the ecological consequences of climate change. For instance, individual basal metabolic rate scales with body size (which also constrains food web structure and dynamics) and temperature (which determines many ecosystem processes and key aspects of foraging behaviour). In addition, increasing atmospheric CO2 is predicted to alter molar CNP ratios of detrital inputs, which could lead to profound shifts in the stoichiometry of elemental fluxes between consumers and resources at the base of the food web. The different components of climate change (e.g. temperature, hydrology and atmospheric composition) not only affect multiple levels of biological organization, but they may also interact with the many other stressors to which fresh waters are exposed, and future research needs to address these potentially important synergies. PMID:20513717

Adapting High-Throughput Screening Methods and Assays for Biocontainment Laboratories

PubMed Central

Tigabu, Bersabeh; White, E. Lucile; Bostwick, Robert; Tower, Nichole; Bukreyev, Alexander; Rockx, Barry; LeDuc, James W.; Noah, James W.

2015-01-01

Abstract High-throughput screening (HTS) has been integrated into the drug discovery process, and multiple assay formats have been widely used in many different disease areas but with limited focus on infectious agents. In recent years, there has been an increase in the number of HTS campaigns using infectious wild-type pathogens rather than surrogates or biochemical pathogen-derived targets. Concurrently, enhanced emerging pathogen surveillance and increased human mobility have resulted in an increase in the emergence and dissemination of infectious human pathogens with serious public health, economic, and social implications at global levels. Adapting the HTS drug discovery process to biocontainment laboratories to develop new drugs for these previously uncharacterized and highly pathogenic agents is now feasible, but HTS at higher biosafety levels (BSL) presents a number of unique challenges. HTS has been conducted with multiple bacterial and viral pathogens at both BSL-2 and BSL-3, and pilot screens have recently been extended to BSL-4 environments for both Nipah and Ebola viruses. These recent successful efforts demonstrate that HTS can be safely conducted at the highest levels of biological containment. This review outlines the specific issues that must be considered in the execution of an HTS drug discovery program for high-containment pathogens. We present an overview of the requirements for HTS in high-level biocontainment laboratories. PMID:25710545