Analysis of undergraduate students' conceptual models of a complex biological system across a diverse body of learners

NASA Astrophysics Data System (ADS)

Dirnbeck, Matthew R.

Biological systems pose a challenge both for learners and teachers because they are complex systems mediated by feedback loops; networks of cause-effect relationships; and non-linear, hierarchical, and emergent properties. Teachers and scientists routinely use models to communicate ideas about complex systems. Model-based pedagogies engage students in model construction as a means of practicing higher-order reasoning skills. One such modeling paradigm describes systems in terms of their structures, behaviors, and functions (SBF). The SBF framework is a simple modeling language that has been used to teach about complex biological systems. Here, we used student-generated SBF models to assess students' causal reasoning in the context of a novel biological problem on an exam. We compared students' performance on the modeling problem, their performance on a set of knowledge/comprehension questions, and their performance on a set of scientific reasoning questions. We found that students who performed well on knowledge and understanding questions also constructed more networked, higher quality models. Previous studies have shown that learners' mental maps increase in complexity with increased expertise. We wanted to investigate if biology students with varying levels of training in biology showed a similar pattern when constructing system models. In a pilot study, we administered the same modeling problem to two additional groups of students: 1) an animal physiology course for students pursuing a major in biology (n=37) and 2) an exercise physiology course for non-majors (n=27). We found that there was no significant difference in model organization across the three student populations, but there was a significant difference in the ability to represent function between the three populations. Between the three groups the non-majors had the lowest function scores, the introductory majors had the middle function scores, and the upper division majors had the highest function scores.

Analyzing Change in Students' Gene-to-Evolution Models in College-Level Introductory Biology

ERIC Educational Resources Information Center

Dauer, Joseph T.; Momsen, Jennifer L.; Speth, Elena Bray; Makohon-Moore, Sasha C.; Long, Tammy M.

2013-01-01

Research in contemporary biology has become increasingly complex and organized around understanding biological processes in the context of systems. To better reflect the ways of thinking required for learning about systems, we developed and implemented a pedagogical approach using box-and-arrow models (similar to concept maps) as a foundational…

Absorption spectroscopic studies of Np(IV) complexes

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

Reed, D. T.

2004-01-01

The complexation of neptunium (IV) with selected inorganic and organic ligands was studied as part of an investigation to establish key subsurface interactions between neptunium and biological systems. The prevalence of reducing environments in most subsurface migation scenarios, which are in many cases induced by biological activity, has increased the role and importance of Np(IV) as a key subsurface neptunium oxidation state. The biodegradation of larger organics that often coexist with actinides in the subsurface leads to the formation of many organic acids as transient products that, by complexation, play a key role in defining the fate and speciation ofmore » neptunium in biologically active systems. These often compete with inorganic complexes e.g. hydrolysis and phosphate. Herein we report the results of a series of complexation studies based on new band formation of the characteristic 960 nm band for Np(IV). Formation constants for Np(IV) complexes with phosphate, hydrolysis, succinate, acetohydroxamic acid, and acetate were determined. These results show the 960 nm absorption band to be very amenable to these types of complexation studies.« less

Screening the efficient biological prospects of triazole allied mixed ligand metal complexes

NASA Astrophysics Data System (ADS)

Utthra, Ponnukalai Ponya; Kumaravel, Ganesan; Raman, Natarajan

2017-12-01

Triazole appended mixed ligand complexes (1-8) of the general formula [ML (bpy/phen)2]Cl2, where M = Cu(II), Co(II), Ni(II) and Zn(II), L = triazole appended Schiff base (E)sbnd N-(4-nitrobenzylidene)-1H-1,2,4-triazol-3-amine and bpy/phen = 2,2‧-bipyridine/1,10-phenanthroline, have been synthesized. The design and synthesis of this elaborate ligand has been performed with the aim of increasing stability and conjugation of 1,2,4 triazole, whose Schiff base derivatives are known as biologically active compounds thereby exploring their DNA binding affinity and other biological applications. The compounds have been comprehensively characterized by elemental analysis, spectroscopic methods (IR, UV-Vis, EPR, 1H and 13C NMR spectroscopy), ESI mass spectrometry and magnetic susceptibility measurements. The complexes were found to exhibit octahedral geometry. The complexes 1-8 were subjected to DNA binding techniques evaluated using UV-Vis absorption, CV, CD, Fluorescence spectroscopy and hydrodynamic measurements. Complex 5 showed a Kb value of 3.9 × 105 M-1. The DNA damaging efficacy for the complexes was observed to be high compared to the ligand. The antimicrobial screening of the compounds against bacterial and fungal strains indicates that the complexes possess excellent antimicrobial activity than the ligand. The overall biological activity of the complexes with phen as a co-ligand possessed superior potential than the ligand.

[Physico-chemical features of dinitrosyl iron complexes with natural thiol-containing ligands underlying biological activities of these complexes].

PubMed

Vanin, A F; Borodulin, R R; Kubrina, L N; Mikoian, V D; Burbaev, D Sh

2013-01-01

Current notions and new experimental data of the authors on physico-chemical features of dinitrosyl iron complexes with natural thiol-containing ligands (glutathione or cysteine), underlying the ability of the complexes to act as NO molecule and nitrosonium ion donors, are considered. This ability determines various biological activities of dinitrosyl iron complexes--inducing long-lasting vasodilation and thereby long-lasting hypotension in human and animals, inhibiting pellet aggregation, increasing red blood cell elasticity, thereby stimulating microcirculation, and reducing necrotic zone in animals with myocardial infarction. Moreover, dinitrosyl iron complexes are capable of accelerating skin wound healing, improving the function of penile cavernous tissue, blocking apoptosis development in cell cultures. When decomposed dinitrosyl iron complexes can exert cytotoxic effect that can be used for curing infectious and carcinogenic pathologies.

Computational complexity of algorithms for sequence comparison, short-read assembly and genome alignment.

PubMed

Baichoo, Shakuntala; Ouzounis, Christos A

A multitude of algorithms for sequence comparison, short-read assembly and whole-genome alignment have been developed in the general context of molecular biology, to support technology development for high-throughput sequencing, numerous applications in genome biology and fundamental research on comparative genomics. The computational complexity of these algorithms has been previously reported in original research papers, yet this often neglected property has not been reviewed previously in a systematic manner and for a wider audience. We provide a review of space and time complexity of key sequence analysis algorithms and highlight their properties in a comprehensive manner, in order to identify potential opportunities for further research in algorithm or data structure optimization. The complexity aspect is poised to become pivotal as we will be facing challenges related to the continuous increase of genomic data on unprecedented scales and complexity in the foreseeable future, when robust biological simulation at the cell level and above becomes a reality. Copyright © 2017 Elsevier B.V. All rights reserved.

Anion-exchange high-performance liquid chromatography of water-soluble chromium (VI) and chromium (III) complexes in biological materials.

PubMed

Suzuki, Y

1987-04-10

A high-performance anion-exchange liquid chromatograph coupled to visible-range (370 nm) and UV (280 nm) detectors and an atomic-absorption spectrometer allowed the rapid determination of CrVI and/or complexes of CrIII in rat plasma, erythrocyte lysate and liver supernatant treated with CrVI or CrIII in vitro. CrVI in the eluates was determined using both the visible-range detector and atomic-absorption spectrometer (AAS). The detection limits of CrVI in standard solutions using these methods were 2 and 5 ng (signal-to-noise ratio = 2), respectively. Separations of the biological components and of CrIII complexes were monitored by UV and AAS analyses, respectively. Time-related decreases of CrVI accompanied by increases in CrIII complexes were observed, indicating the reduction of CrVI by some of the biological components. The reduction rates were considerably higher in the liver supernatant and erythrocyte lysate than in the plasma. These results indicate that the anion-exchange high-performance liquid chromatographic system is useful for simultaneous determination of CrVI and CrIII complexes in biological materials.

Use of Biological and Non-biological Surrogates for Evaluating Cryptosporidium Removal by Filtration

EPA Science Inventory

Water treatment plants are currently facing increasing challenges in monitoring Cryptosporidium in source and treated water because of complex analytical techniques and associated health risks. Surrogates may be easier to analyze than Cryptosporidium, but they must also be reliab...

[Application of microelectronics CAD tools to synthetic biology].

PubMed

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

2017-02-01

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

COMPLEX MIXTURES OF CHEMICAL CARCINOGENS: PRINCIPLES OF ACTION AND HUMAN CANCER

EPA Science Inventory

There is strong epidemiological evidence supported by experimental animal data that complex environmental mixtures pose a risk to human health producing increases in cancer incidence. Understanding the chemical and biological properties of these mixtures leads to a clearer unde...

The diverse and expanding role of mass spectrometry in structural and molecular biology.

PubMed

Lössl, Philip; van de Waterbeemd, Michiel; Heck, Albert Jr

2016-12-15

The emergence of proteomics has led to major technological advances in mass spectrometry (MS). These advancements not only benefitted MS-based high-throughput proteomics but also increased the impact of mass spectrometry on the field of structural and molecular biology. Here, we review how state-of-the-art MS methods, including native MS, top-down protein sequencing, cross-linking-MS, and hydrogen-deuterium exchange-MS, nowadays enable the characterization of biomolecular structures, functions, and interactions. In particular, we focus on the role of mass spectrometry in integrated structural and molecular biology investigations of biological macromolecular complexes and cellular machineries, highlighting work on CRISPR-Cas systems and eukaryotic transcription complexes. © 2016 The Authors. Published under the terms of the CC BY NC ND 4.0 license.

Systems Proteomics for Translational Network Medicine

PubMed Central

Arrell, D. Kent; Terzic, Andre

2012-01-01

Universal principles underlying network science, and their ever-increasing applications in biomedicine, underscore the unprecedented capacity of systems biology based strategies to synthesize and resolve massive high throughput generated datasets. Enabling previously unattainable comprehension of biological complexity, systems approaches have accelerated progress in elucidating disease prediction, progression, and outcome. Applied to the spectrum of states spanning health and disease, network proteomics establishes a collation, integration, and prioritization algorithm to guide mapping and decoding of proteome landscapes from large-scale raw data. Providing unparalleled deconvolution of protein lists into global interactomes, integrative systems proteomics enables objective, multi-modal interpretation at molecular, pathway, and network scales, merging individual molecular components, their plurality of interactions, and functional contributions for systems comprehension. As such, network systems approaches are increasingly exploited for objective interpretation of cardiovascular proteomics studies. Here, we highlight network systems proteomic analysis pipelines for integration and biological interpretation through protein cartography, ontological categorization, pathway and functional enrichment and complex network analysis. PMID:22896016

The evolution of colour pattern complexity: selection for conspicuousness favours contrasting within-body colour combinations in lizards.

PubMed

Pérez I de Lanuza, G; Font, E

2016-05-01

Many animals display complex colour patterns that comprise several adjacent, often contrasting colour patches. Combining patches of complementary colours increases the overall conspicuousness of the complex pattern, enhancing signal detection. Therefore, selection for conspicuousness may act not only on the design of single colour patches, but also on their combination. Contrasting long- and short-wavelength colour patches are located on the ventral and lateral surfaces of many lacertid lizards. As the combination of long- and short-wavelength-based colours generates local chromatic contrast, we hypothesized that selection may favour the co-occurrence of lateral and ventral contrasting patches, resulting in complex colour patterns that maximize the overall conspicuousness of the signal. To test this hypothesis, we performed a comparative phylogenetic study using a categorical colour classification based on spectral data and descriptive information on lacertid coloration collected from the literature. Our results demonstrate that conspicuous ventral (long-wavelength-based) and lateral (short-wavelength-based) colour patches co-occur throughout the lacertid phylogeny more often than expected by chance, especially in the subfamily Lacertini. These results suggest that selection promotes the evolution of the complex pattern rather than the acquisition of a single conspicuous colour patch, possibly due to the increased conspicuousness caused by the combination of colours with contrasting spectral properties. © 2016 European Society For Evolutionary Biology. Journal of Evolutionary Biology © 2016 European Society For Evolutionary Biology.

Enhanced bioavailability of polyaromatic hydrocarbons in the form of mucin complexes.

PubMed

Drug, Eyal; Landesman-Milo, Dalit; Belgorodsky, Bogdan; Ermakov, Natalia; Frenkel-Pinter, Moran; Fadeev, Ludmila; Peer, Dan; Gozin, Michael

2011-03-21

Increasing exposure of biological systems to large amounts of polycyclic aromatic hydrocarbons is of great public concern. Organisms have an array of biological defense mechanisms, and it is believed that mucosal gel (which covers the respiratory system, the gastrointestinal tract, etc.) provides an effective chemical shield against a range of toxic materials. However, in this work, we demonstrate, for the first time, that, upon complexation of polyaromatic hydrocarbons with mucins, enhanced bioavailability and, therefore, toxicity are obtained. This work was aimed to demonstrate how complexation of various highly hydrophobic polycyclic aromatic hydrocarbons with representative mucin glycoprotein could lead to the formation of previously undescribed materials, which exhibit increased toxicity versus pristine polycyclic aromatic hydrocarbons. In the present work, we show that a representative mucin glycoprotein, bovine submaxillary mucin, has impressive and unprecedented capabilities of binding and solubilizing water-insoluble materials in physiological solution. The complexes formed between the mucin and a series of polycyclic aromatic hydrocarbons were comprehensively characterized, and their toxicity was evaluated by both in vivo and in vitro assays. In addition, the bioavailability and membrane-penetration capabilities were tested using an internalization assay. Our results provide, for the first time, evidence of an unknown route by which hydrophobic materials may achieve higher bioavailability, penetrating some of the biological defense systems, in the form of water-soluble complexes with mucosal proteins.

Effect of biological pretreatments in enhancing corn straw biogas production.

PubMed

Zhong, Weizhang; Zhang, Zhongzhi; Luo, Yijing; Sun, Shanshan; Qiao, Wei; Xiao, Meng

2011-12-01

A biological pretreatment with new complex microbial agents was used to pretreat corn straw at ambient temperature (about 20°C) to improve its biodegradability and anaerobic biogas production. A complex microbial agent dose of 0.01% (w/w) and pretreatment time of 15 days were appropriate for biological pretreatment. These treatment conditions resulted in 33.07% more total biogas yield, 75.57% more methane yield, and 34.6% shorter technical digestion time compared with the untreated sample. Analyses of chemical compositions showed 5.81-25.10% reductions in total lignin, cellulose, and hemicellulose contents, and 27.19-80.71% increases in hot-water extractives; these changes contributed to the enhancement of biogas production. Biological pretreatment could be an effective method for improving biodegradability and enhancing the highly efficient biological conversion of corn straw into bioenergy. Copyright © 2011 Elsevier Ltd. All rights reserved.

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.

Linear motif-mediated interactions have contributed to the evolution of modularity in complex protein interaction networks.

PubMed

Kim, Inhae; Lee, Heetak; Han, Seong Kyu; Kim, Sanguk

2014-10-01

The modular architecture of protein-protein interaction (PPI) networks is evident in diverse species with a wide range of complexity. However, the molecular components that lead to the evolution of modularity in PPI networks have not been clearly identified. Here, we show that weak domain-linear motif interactions (DLIs) are more likely to connect different biological modules than strong domain-domain interactions (DDIs). This molecular division of labor is essential for the evolution of modularity in the complex PPI networks of diverse eukaryotic species. In particular, DLIs may compensate for the reduction in module boundaries that originate from increased connections between different modules in complex PPI networks. In addition, we show that the identification of biological modules can be greatly improved by including molecular characteristics of protein interactions. Our findings suggest that transient interactions have played a unique role in shaping the architecture and modularity of biological networks over the course of evolution.

Nanomaterial-microbe cross-talk: physicochemical principles and (patho)biological consequences.

PubMed

Westmeier, D; Hahlbrock, A; Reinhardt, C; Fröhlich-Nowoisky, J; Wessler, S; Vallet, C; Pöschl, U; Knauer, S K; Stauber, R H

2018-05-17

The applications of nanoparticles (NPs) are increasing exponentially in consumer products, biotechnology and biomedicine, and humans, as well as the environment, are increasingly being exposed to NPs. Analogously, various (pathogenic) microorganisms are present at all the major exposure and entry sites for NPs in the human body as well as in environmental habitats. However, the field has just started to explore the complex interplay between NPs and microbes and the (patho)biological consequences. Based on recent insights, herein, we critically reviewed the available knowledge about the interaction of NPs with microbes and the analytical investigations including the latest intravital imaging tools. We have commented on how the NPs' characteristics influence complex formation with microorganisms, presented the underlying physicochemical forces, and provided examples of how this knowledge can be used to rationally control the NP-microbe interaction. We concluded by discussing the role of the biomolecule corona in NP-microbe crosstalk and speculated the impact of NP-microbe complex formation on the (patho)biological outcome and fate of microbial pathogens. The presented insights will not only support the field in engineering NPs with improved anti-microbial activity but also stimulate research on the biomedical and toxicological relevance of nanomaterial-microbiome complex formation for the anthropocene in general.

Tracking down the links between charged particles and biological response: A UK perspective

NASA Astrophysics Data System (ADS)

Hill, Mark A.

2013-07-01

The UK has a long history of radiobiology research into charged particles, with interest likely to expand in the coming years following the recent government announcement of £250 million to build two proton beam therapy facilities in the UK. A brief overview of research and facilities past and present with respect to radiation protection and oncology along with biological consequences and underlying mechanisms will be presented and discussed. Increased knowledge of the mechanisms underpinning the radiation action on biological systems is important in understanding, not only the risks associated with exposure, but also in optimising radiotherapy treatment of cancer. Ionizing radiation is always in the form of structure tracks which are a unique characteristic of ionizing radiation alone producing damage grossly different and far more biologically effective than endogenous damage. The track structure is the prime determinant of biological response to DNA, with charged particles of increasing LET leading to an increase in the frequency and complexity of clustered DNA damage. High-LET particles will also produce non-homogeneous dose distribution through a cell nucleus resulting in correlated DNA breaks along the path of the particle and an increase in the probability of complex chromosomal rearrangements. However it is now well established that there is variety of phenomena that do not conform to the conventional paradigm of targeted radiobiology, but there is insufficient evidence to assess the implications of these non-targeted effects for radiotherapy or relevance to risk for human health.

Synthesis and biological evaluation of new imidazolium and piperazinium salts of pyropheophorbide-a for photodynamic cancer therapy.

PubMed

Sengee, Gerelt-Ireedui; Badraa, Narangerel; Shim, Young K

2008-08-01

We have designed imidazolium and piperazinium salts of pyropheophorbide-a in order to develop effective photosensitizers which have good solubility in polar and non polar media and to reveal the possible influences of the piperazine and imidazole moieties on the biological activities of pyropheophorbide-a. The phototoxicity of those pyropheophorbide-a salts against A549 cells was studied in vitro and compared with that of pyropheophorbide-a. The result showed that complexing piperazine and imidazole into pyropheophorbide-a decreases its dark toxicity without greatly decreasing phototoxicity and, enhances its phototoxicity without greatly increasing dark toxicity, respectively. This work not only describes novel amphiphilic salt complexes of pyropheophobide-a which retain the biological activities of the parent compound pyropheophorbide-a and could be effective candidate for PDT, but also reveals the possibility of developing effective photosensitizers by complexing imidazole and piperazine into other hydrophobic photosensitizers.

Synthesis and Biological Evaluation of New Imidazolium and Piperazinium Salts of Pyropheophorbide-a for Photodynamic Cancer Therapy

PubMed Central

Sengee, Gerelt-Ireedui; Badraa, Narangerel; Shim, Young Key

2008-01-01

We have designed imidazolium and piperazinium salts of pyropheophorbide-a in order to develop effective photosensitizers which have good solubility in polar and non polar media and to reveal the possible influences of the piperazine and imidazole moieties on the biological activities of pyropheophorbide-a. The phototoxicity of those pyropheophorbide-a salts against A549 cells was studied in vitro and compared with that of pyropheophorbide-a. The result showed that complexing piperazine and imidazole into pyropheophorbide-a decreases its dark toxicity without greatly decreasing phototoxicity and, enhances its phototoxicity without greatly increasing dark toxicity, respectively. This work not only describes novel amphiphilic salt complexes of pyropheophobide-a which retain the biological activities of the parent compound pyropheophorbide-a and could be effective candidate for PDT, but also reveals the possibility of developing effective photosensitizers by complexing imidazole and piperazine into other hydrophobic photosensitizers. PMID:19325811

Leveraging advances in biology to design biomaterials

NASA Astrophysics Data System (ADS)

Darnell, Max; Mooney, David J.

2017-12-01

Biomaterials have dramatically increased in functionality and complexity, allowing unprecedented control over the cells that interact with them. From these engineering advances arises the prospect of improved biomaterial-based therapies, yet practical constraints favour simplicity. Tools from the biology community are enabling high-resolution and high-throughput bioassays that, if incorporated into a biomaterial design framework, could help achieve unprecedented functionality while minimizing the complexity of designs by identifying the most important material parameters and biological outputs. However, to avoid data explosions and to effectively match the information content of an assay with the goal of the experiment, material screens and bioassays must be arranged in specific ways. By borrowing methods to design experiments and workflows from the bioprocess engineering community, we outline a framework for the incorporation of next-generation bioassays into biomaterials design to effectively optimize function while minimizing complexity. This framework can inspire biomaterials designs that maximize functionality and translatability.

Is Self-organization a Rational Expectation?

NASA Astrophysics Data System (ADS)

Luediger, Heinz

Over decades and under varying names the study of biology-inspired algorithms applied to non-living systems has been the subject of a small and somewhat exotic research community. Only the recent coincidence of a growing inability to master the design, development and operation of increasingly intertwined systems and processes, and an accelerated trend towards a naïve if not romanticizing view of nature in the sciences, has led to the adoption of biology-inspired algorithmic research by a wider range of sciences. Adaptive systems, as we apparently observe in nature, are meanwhile viewed as a promising way out of the complexity trap and, propelled by a long list of ‘self’ catchwords, complexity research has become an influential stream in the science community. This paper presents four provocative theses that cast doubt on the strategic potential of complexity research and the viability of large scale deployment of biology-inspired algorithms in an expectation driven world.

Pharmaceutical, biological, and clinical properties of botulinum neurotoxin type A products.

PubMed

Frevert, Jürgen

2015-03-01

Botulinum neurotoxin injections are a valuable treatment modality for many therapeutic indications and have revolutionized the field of aesthetic medicine so that they are the leading cosmetic procedure performed worldwide. Studies show that onabotulinumtoxinA, abobotulinumtoxinA, and incobotulinumtoxinA are comparable in terms of clinical efficacy. Differences between the products relate to the botulinum neurotoxin complexes, specific biological potency, and their immunogenicity. Protein complex size and molecular weight have no effect on biological activity, stability, distribution, or side effect profile. Complexing proteins and inactive toxin (toxoid) content increase the risk of neutralizing antibody formation, which can cause secondary treatment failure, particularly in chronic disorders that require frequent injections and long-term treatment. These attributes could lead to differences in therapeutic outcomes, and, given the widespread aesthetic use of these three neurotoxin products, physicians should be aware of how they differ to ensure their safe and effective use.

URDME: a modular framework for stochastic simulation of reaction-transport processes in complex geometries.

PubMed

Drawert, Brian; Engblom, Stefan; Hellander, Andreas

2012-06-22

Experiments in silico using stochastic reaction-diffusion models have emerged as an important tool in molecular systems biology. Designing computational software for such applications poses several challenges. Firstly, realistic lattice-based modeling for biological applications requires a consistent way of handling complex geometries, including curved inner- and outer boundaries. Secondly, spatiotemporal stochastic simulations are computationally expensive due to the fast time scales of individual reaction- and diffusion events when compared to the biological phenomena of actual interest. We therefore argue that simulation software needs to be both computationally efficient, employing sophisticated algorithms, yet in the same time flexible in order to meet present and future needs of increasingly complex biological modeling. We have developed URDME, a flexible software framework for general stochastic reaction-transport modeling and simulation. URDME uses Unstructured triangular and tetrahedral meshes to resolve general geometries, and relies on the Reaction-Diffusion Master Equation formalism to model the processes under study. An interface to a mature geometry and mesh handling external software (Comsol Multiphysics) provides for a stable and interactive environment for model construction. The core simulation routines are logically separated from the model building interface and written in a low-level language for computational efficiency. The connection to the geometry handling software is realized via a Matlab interface which facilitates script computing, data management, and post-processing. For practitioners, the software therefore behaves much as an interactive Matlab toolbox. At the same time, it is possible to modify and extend URDME with newly developed simulation routines. Since the overall design effectively hides the complexity of managing the geometry and meshes, this means that newly developed methods may be tested in a realistic setting already at an early stage of development. In this paper we demonstrate, in a series of examples with high relevance to the molecular systems biology community, that the proposed software framework is a useful tool for both practitioners and developers of spatial stochastic simulation algorithms. Through the combined efforts of algorithm development and improved modeling accuracy, increasingly complex biological models become feasible to study through computational methods. URDME is freely available at http://www.urdme.org.

Systems genetics approaches to understand complex traits

PubMed Central

Civelek, Mete; Lusis, Aldons J.

2014-01-01

Systems genetics is an approach to understand the flow of biological information that underlies complex traits. It uses a range of experimental and statistical methods to quantitate and integrate intermediate phenotypes, such as transcript, protein or metabolite levels, in populations that vary for traits of interest. Systems genetics studies have provided the first global view of the molecular architecture of complex traits and are useful for the identification of genes, pathways and networks that underlie common human diseases. Given the urgent need to understand how the thousands of loci that have been identified in genome-wide association studies contribute to disease susceptibility, systems genetics is likely to become an increasingly important approach to understanding both biology and disease. PMID:24296534

Regulation of drug-metabolizing enzymes in infectious and inflammatory disease: implications for biologics-small molecule drug interactions.

PubMed

Mallick, Pankajini; Taneja, Guncha; Moorthy, Bhagavatula; Ghose, Romi

2017-06-01

Drug-metabolizing enzymes (DMEs) are primarily down-regulated during infectious and inflammatory diseases, leading to disruption in the metabolism of small molecule drugs (smds), which are increasingly being prescribed therapeutically in combination with biologics for a number of chronic diseases. The biologics may exert pro- or anti-inflammatory effect, which may in turn affect the expression/activity of DMEs. Thus, patients with infectious/inflammatory diseases undergoing biologic/smd treatment can have complex changes in DMEs due to combined effects of the disease and treatment. Areas covered: We will discuss clinical biologics-SMD interaction and regulation of DMEs during infection and inflammatory diseases. Mechanistic studies will be discussed and consequences on biologic-small molecule combination therapy on disease outcome due to changes in drug metabolism will be highlighted. Expert opinion: The involvement of immunomodulatory mediators in biologic-SMDs is well known. Regulatory guidelines recommend appropriate in vitro or in vivo assessments for possible interactions. The role of cytokines in biologic-SMDs has been documented. However, the mechanisms of drug-drug interactions is much more complex, and is probably multi-factorial. Studies aimed at understanding the mechanism by which biologics effect the DMEs during inflammation/infection are clinically important.

ENVIRONMENTAL EFFECTS OF A GOLF COMPLEX ON COASTAL WETLANDS IN THE GULF OF MEXICO

EPA Science Inventory

The increasing density of golf courses represents a potential source of contamination to nearby coastal wetlands and other near-shore areas. The chemical and biological magnitude of the problem is almost unknown. To provide perspective on this issue, the effects of golf complex r...

Integrating multiple lines of evidence to assess biological hazards of complex mixtures: A case study in the Maumee River

EPA Science Inventory

Product Description:Due to technological improvements, increasing numbers of chemical contaminants are being detected in surface waters nation-wide, including the Great Lakes. Methods are needed to understand what impact these complex mixtures of contaminants can have on aquatic ...

Light-energy conversion in engineered microorganisms.

PubMed

Johnson, Ethan T; Schmidt-Dannert, Claudia

2008-12-01

Increasing interest in renewable resources by the energy and chemical industries has spurred new technologies both to capture solar energy and to develop biologically derived chemical feedstocks and fuels. Advances in molecular biology and metabolic engineering have provided new insights and techniques for increasing biomass and biohydrogen production, and recent efforts in synthetic biology have demonstrated that complex regulatory and metabolic networks can be designed and engineered in microorganisms. Here, we explore how light-driven processes may be incorporated into nonphotosynthetic microbes to boost metabolic capacity for the production of industrial and fine chemicals. Progress towards the introduction of light-driven proton pumping or anoxygenic photosynthesis into Escherichia coli to increase the efficiency of metabolically-engineered biosynthetic pathways is highlighted.

Darwinian evolution in the light of genomics

PubMed Central

Koonin, Eugene V.

2009-01-01

Comparative genomics and systems biology offer unprecedented opportunities for testing central tenets of evolutionary biology formulated by Darwin in the Origin of Species in 1859 and expanded in the Modern Synthesis 100 years later. Evolutionary-genomic studies show that natural selection is only one of the forces that shape genome evolution and is not quantitatively dominant, whereas non-adaptive processes are much more prominent than previously suspected. Major contributions of horizontal gene transfer and diverse selfish genetic elements to genome evolution undermine the Tree of Life concept. An adequate depiction of evolution requires the more complex concept of a network or ‘forest’ of life. There is no consistent tendency of evolution towards increased genomic complexity, and when complexity increases, this appears to be a non-adaptive consequence of evolution under weak purifying selection rather than an adaptation. Several universals of genome evolution were discovered including the invariant distributions of evolutionary rates among orthologous genes from diverse genomes and of paralogous gene family sizes, and the negative correlation between gene expression level and sequence evolution rate. Simple, non-adaptive models of evolution explain some of these universals, suggesting that a new synthesis of evolutionary biology might become feasible in a not so remote future. PMID:19213802

Current trends in pharmacy benefit designs: a threat to disease management in chronic complex diseases.

PubMed

Owens, Gary; Emons, Matthew F; Christian-Herman, Jennifer; Lawless, Grant

2007-04-01

With a focus on those patients who are candidates for treatment with biologic agents, we review the impact that current pharmacy benefit trends have on patients with chronic complex diseases and how they affect opportunities for disease management in this unique patient population. Dramatic increases in health care costs have led to a variety of strategies to manage cost. Many of these strategies either limit access to care or increase the patient's responsibility for choosing and paying for care, especially for medications. These strategies have a disproportionate impact on patients with chronic complex diseases, particularly those who require the use of biologic medications. A fundamental prerequisite of disease management has been coverage of disease-modifying therapies. If current pharmacy benefit trends continue, unintended consequences will likely occur including lost opportunities for disease management. Current pharmacy benefit trends could adversely impact disease management, particularly for patients requiring the use of biologic agents. Health plans should consider innovative benefit designs that reflect an appropriate level of cost sharing across all key stake-holders, ensuring appropriate access to needed therapies. Additional research is needed to clarify the value of newer approaches to therapies or benefit design changes.

Consistent visualizations of changing knowledge

PubMed Central

Tipney, Hannah J.; Schuyler, Ronald P.; Hunter, Lawrence

2009-01-01

Networks are increasingly used in biology to represent complex data in uncomplicated symbolic form. However, as biological knowledge is continually evolving, so must those networks representing this knowledge. Capturing and presenting this type of knowledge change over time is particularly challenging due to the intimate manner in which researchers customize those networks they come into contact with. The effective visualization of this knowledge is important as it creates insight into complex systems and stimulates hypothesis generation and biological discovery. Here we highlight how the retention of user customizations, and the collection and visualization of knowledge associated provenance supports effective and productive network exploration. We also present an extension of the Hanalyzer system, ReOrient, which supports network exploration and analysis in the presence of knowledge change. PMID:21347184

Statistical Techniques Complement UML When Developing Domain Models of Complex Dynamical Biosystems.

PubMed

Williams, Richard A; Timmis, Jon; Qwarnstrom, Eva E

2016-01-01

Computational modelling and simulation is increasingly being used to complement traditional wet-lab techniques when investigating the mechanistic behaviours of complex biological systems. In order to ensure computational models are fit for purpose, it is essential that the abstracted view of biology captured in the computational model, is clearly and unambiguously defined within a conceptual model of the biological domain (a domain model), that acts to accurately represent the biological system and to document the functional requirements for the resultant computational model. We present a domain model of the IL-1 stimulated NF-κB signalling pathway, which unambiguously defines the spatial, temporal and stochastic requirements for our future computational model. Through the development of this model, we observe that, in isolation, UML is not sufficient for the purpose of creating a domain model, and that a number of descriptive and multivariate statistical techniques provide complementary perspectives, in particular when modelling the heterogeneity of dynamics at the single-cell level. We believe this approach of using UML to define the structure and interactions within a complex system, along with statistics to define the stochastic and dynamic nature of complex systems, is crucial for ensuring that conceptual models of complex dynamical biosystems, which are developed using UML, are fit for purpose, and unambiguously define the functional requirements for the resultant computational model.

Statistical Techniques Complement UML When Developing Domain Models of Complex Dynamical Biosystems

PubMed Central

Timmis, Jon; Qwarnstrom, Eva E.

2016-01-01

Computational modelling and simulation is increasingly being used to complement traditional wet-lab techniques when investigating the mechanistic behaviours of complex biological systems. In order to ensure computational models are fit for purpose, it is essential that the abstracted view of biology captured in the computational model, is clearly and unambiguously defined within a conceptual model of the biological domain (a domain model), that acts to accurately represent the biological system and to document the functional requirements for the resultant computational model. We present a domain model of the IL-1 stimulated NF-κB signalling pathway, which unambiguously defines the spatial, temporal and stochastic requirements for our future computational model. Through the development of this model, we observe that, in isolation, UML is not sufficient for the purpose of creating a domain model, and that a number of descriptive and multivariate statistical techniques provide complementary perspectives, in particular when modelling the heterogeneity of dynamics at the single-cell level. We believe this approach of using UML to define the structure and interactions within a complex system, along with statistics to define the stochastic and dynamic nature of complex systems, is crucial for ensuring that conceptual models of complex dynamical biosystems, which are developed using UML, are fit for purpose, and unambiguously define the functional requirements for the resultant computational model. PMID:27571414

Integrating ecological risk assessments across levels of organization using the Franklin-Noss model of biodiversity

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

Brugger, K.E.; Tiebout, H.M. III

1994-12-31

Wildlife toxicologists pioneered methodologies for assessing ecological risk to nontarget species. Historically, ecological risk assessments (ERAS) focused on a limited array of species and were based on a relatively few population-level endpoints (mortality, reproduction). Currently, risk assessment models are becoming increasingly complex that factor in multi-species interactions (across trophic levels) and utilize an increasingly diverse number of ecologically significant endpoints. This trend suggests the increasing importance of safeguarding not only populations of individual species, but also the overall integrity of the larger biotic systems that support them. In this sense, ERAs are in alignment with Conservation Biology, an applied sciencemore » of ecological knowledge used to conserve biodiversity. A theoretical conservation biology model could be incorporated in ERAs to quantify impacts to biodiversity (structure, function or composition across levels of biological organization). The authors suggest that the Franklin-Noss model for evaluating biodiversity, with its nested, hierarchical approach, may provide a suitable paradigm for assessing and integrating the ecological risk that chemical contaminants pose to biological systems from the simplest levels (genotypes, individual organisms) to the most complex levels of organization (communities and ecosystems). The Franklin-Noss model can accommodate the existing ecotoxicological database and, perhaps more importantly, indicate new areas in which critical endpoints should be identified and investigated.« less

Characterising the Development of the Understanding of Human Body Systems in High-School Biology Students--A Longitudinal Study

ERIC Educational Resources Information Center

Snapir, Zohar; Eberbach, Catherine; Ben-Zvi-Assaraf, Orit; Hmelo-Silver, Cindy; Tripto, Jaklin

2017-01-01

Science education today has become increasingly focused on research into complex natural, social and technological systems. In this study, we examined the development of high-school biology students' systems understanding of the human body, in a three-year longitudinal study. The development of the students' system understanding was evaluated…

Intuitive biological thought: Developmental changes and effects of biology education in late adolescence.

PubMed

Coley, John D; Arenson, Melanie; Xu, Yian; Tanner, Kimberly D

2017-02-01

A large body of cognitive research has shown that people intuitively and effortlessly reason about the biological world in complex and systematic ways. We addressed two questions about the nature of intuitive biological reasoning: How does intuitive biological thinking change during adolescence and early adulthood? How does increasing biology education influence intuitive biological thinking? To do so, we developed a battery of measures to systematically test three components of intuitive biological thought: anthropocentric thinking, teleological thinking and essentialist thinking, and tested 8th graders and university students (both biology majors, and non-biology majors). Results reveal clear evidence of persistent intuitive reasoning among all populations studied, consistent but surprisingly small differences between 8th graders and college students on measures of intuitive biological thought, and consistent but again surprisingly small influence of increasing biology education on intuitive biological reasoning. Results speak to the persistence of intuitive reasoning, the importance of taking intuitive knowledge into account in science classrooms, and the necessity of interdisciplinary research to advance biology education. Further studies are necessary to investigate how cultural context and continued acquisition of expertise impact intuitive biology thinking. Copyright © 2016 Elsevier Inc. All rights reserved.

Noise and poise: Enhancement of postural complexity in the elderly with a stochastic-resonance based therapy

NASA Astrophysics Data System (ADS)

Costa, M.; Priplata, A. A.; Lipsitz, L. A.; Wu, Z.; Huang, N. E.; Goldberger, A. L.; Peng, C.-K.

2007-03-01

Pathologic states are associated with a loss of dynamical complexity. Therefore, therapeutic interventions that increase physiologic complexity may enhance health status. Using multiscale entropy analysis, we show that the postural sway dynamics of healthy young and healthy elderly subjects are more complex than that of elderly subjects with a history of falls. Application of subsensory noise to the feet has been demonstrated to improve postural stability in the elderly. We next show that this therapy significantly increases the multiscale complexity of sway fluctuations in healthy elderly subjects. Quantification of changes in dynamical complexity of biologic variability may be the basis of a new approach to assessing risk and to predicting the efficacy of clinical interventions, including noise-based therapies.

Biological Agents

EPA Pesticide Factsheets

These chemicals or organisms increase the rate at which microorganisms break down complex compounds into simpler products (biodegredation). Two bioremediation technologies currently being used for oil spill cleanups are fertilization and seeding.

Interdisciplinary education - a predator-prey model for developing a skill set in mathematics, biology and technology

NASA Astrophysics Data System (ADS)

van der Hoff, Quay

2017-08-01

The science of biology has been transforming dramatically and so the need for a stronger mathematical background for biology students has increased. Biological students reaching the senior or post-graduate level often come to realize that their mathematical background is insufficient. Similarly, students in a mathematics programme, interested in biological phenomena, find it difficult to master the complex systems encountered in biology. In short, the biologists do not have enough mathematics and the mathematicians are not being taught enough biology. The need for interdisciplinary curricula that includes disciplines such as biology, physical science, and mathematics is widely recognized, but has not been widely implemented. In this paper, it is suggested that students develop a skill set of ecology, mathematics and technology to encourage working across disciplinary boundaries. To illustrate such a skill set, a predator-prey model that contains self-limiting factors for both predator and prey is suggested. The general idea of dynamics, is introduced and students are encouraged to discover the applicability of this approach to more complex biological systems. The level of mathematics and technology required is not advanced; therefore, it is ideal for inclusion in a senior-level or introductory graduate-level course for students interested in mathematical biology.

Compressed learning and its applications to subcellular localization.

PubMed

Zheng, Zhong-Long; Guo, Li; Jia, Jiong; Xie, Chen-Mao; Zeng, Wen-Cai; Yang, Jie

2011-09-01

One of the main challenges faced by biological applications is to predict protein subcellular localization in automatic fashion accurately. To achieve this in these applications, a wide variety of machine learning methods have been proposed in recent years. Most of them focus on finding the optimal classification scheme and less of them take the simplifying the complexity of biological systems into account. Traditionally, such bio-data are analyzed by first performing a feature selection before classification. Motivated by CS (Compressed Sensing) theory, we propose the methodology which performs compressed learning with a sparseness criterion such that feature selection and dimension reduction are merged into one analysis. The proposed methodology decreases the complexity of biological system, while increases protein subcellular localization accuracy. Experimental results are quite encouraging, indicating that the aforementioned sparse methods are quite promising in dealing with complicated biological problems, such as predicting the subcellular localization of Gram-negative bacterial proteins.

Ecological community integration increases with added trophic complexity

USGS Publications Warehouse

Wright, Christopher K.

2008-01-01

The existence of functional biological organization at the level of multi-species communities has long been contested in ecology and evolutionary biology. I found that adding a trophic level to simulated ecological communities enhanced their ability to compete at the community level, increasing the likelihood of one community forcing all or most species in a second community to extinction. Community-level identity emerged within systems of interacting ecological networks, while competitive ability at the community level was enhanced by intense within-community selection pressure. These results suggest a reassessment of the nature of biological organization above the level of species, indicating that the drive toward biological integration, so prominent throughout the history of life, might extend to multi-species communities.

Six Classroom Exercises to Teach Natural Selection to Undergraduate Biology Students

PubMed Central

Kalinowski, Steven T.; Leonard, Mary J.; Andrews, Tessa M.; Litt, Andrea R.

2013-01-01

Students in introductory biology courses frequently have misconceptions regarding natural selection. In this paper, we describe six activities that biology instructors can use to teach undergraduate students in introductory biology courses how natural selection causes evolution. These activities begin with a lesson introducing students to natural selection and also include discussions on sexual selection, molecular evolution, evolution of complex traits, and the evolution of behavior. The set of six topics gives students the opportunity to see how natural selection operates in a variety of contexts. Pre- and postinstruction testing showed students’ understanding of natural selection increased substantially after completing this series of learning activities. Testing throughout this unit showed steadily increasing student understanding, and surveys indicated students enjoyed the activities. PMID:24006396

Complex and unexpected dynamics in simple genetic regulatory networks

NASA Astrophysics Data System (ADS)

Borg, Yanika; Ullner, Ekkehard; Alagha, Afnan; Alsaedi, Ahmed; Nesbeth, Darren; Zaikin, Alexey

2014-03-01

One aim of synthetic biology is to construct increasingly complex genetic networks from interconnected simpler ones to address challenges in medicine and biotechnology. However, as systems increase in size and complexity, emergent properties lead to unexpected and complex dynamics due to nonlinear and nonequilibrium properties from component interactions. We focus on four different studies of biological systems which exhibit complex and unexpected dynamics. Using simple synthetic genetic networks, small and large populations of phase-coupled quorum sensing repressilators, Goodwin oscillators, and bistable switches, we review how coupled and stochastic components can result in clustering, chaos, noise-induced coherence and speed-dependent decision making. A system of repressilators exhibits oscillations, limit cycles, steady states or chaos depending on the nature and strength of the coupling mechanism. In large repressilator networks, rich dynamics can also be exhibited, such as clustering and chaos. In populations of Goodwin oscillators, noise can induce coherent oscillations. In bistable systems, the speed with which incoming external signals reach steady state can bias the network towards particular attractors. These studies showcase the range of dynamical behavior that simple synthetic genetic networks can exhibit. In addition, they demonstrate the ability of mathematical modeling to analyze nonlinearity and inhomogeneity within these systems.

Different Evolutionary Paths to Complexity for Small and Large Populations of Digital Organisms

PubMed Central

2016-01-01

A major aim of evolutionary biology is to explain the respective roles of adaptive versus non-adaptive changes in the evolution of complexity. While selection is certainly responsible for the spread and maintenance of complex phenotypes, this does not automatically imply that strong selection enhances the chance for the emergence of novel traits, that is, the origination of complexity. Population size is one parameter that alters the relative importance of adaptive and non-adaptive processes: as population size decreases, selection weakens and genetic drift grows in importance. Because of this relationship, many theories invoke a role for population size in the evolution of complexity. Such theories are difficult to test empirically because of the time required for the evolution of complexity in biological populations. Here, we used digital experimental evolution to test whether large or small asexual populations tend to evolve greater complexity. We find that both small and large—but not intermediate-sized—populations are favored to evolve larger genomes, which provides the opportunity for subsequent increases in phenotypic complexity. However, small and large populations followed different evolutionary paths towards these novel traits. Small populations evolved larger genomes by fixing slightly deleterious insertions, while large populations fixed rare beneficial insertions that increased genome size. These results demonstrate that genetic drift can lead to the evolution of complexity in small populations and that purifying selection is not powerful enough to prevent the evolution of complexity in large populations. PMID:27923053

Complex between triple helix of collagen and double helix of DNA in aqueous solution.

PubMed

Mrevlishvili, George M; Svintradze, David V

2005-06-01

We demonstrate in this paper that one example of a biologically important and molecular self-assembling complex system is a collagen-DNA ordered aggregate which spontaneously forms in aqueous solutions. Interaction between the collagen and the DNA leads to destruction of the hydration shell of the triple helix and stabilization of the double helix structure. From a molecular biology point of view this nano-scale self-assembling superstructure could increase the stability of DNA against the nucleases during collagen diseases and the growth of collagen fibrills in the presence of DNA.

Automated and miniaturized detection of biological threats with a centrifugal microfluidic system

NASA Astrophysics Data System (ADS)

Mark, D.; van Oordt, T.; Strohmeier, O.; Roth, G.; Drexler, J.; Eberhard, M.; Niedrig, M.; Patel, P.; Zgaga-Griesz, A.; Bessler, W.; Weidmann, M.; Hufert, F.; Zengerle, R.; von Stetten, F.

2012-06-01

The world's growing mobility, mass tourism, and the threat of terrorism increase the risk of the fast spread of infectious microorganisms and toxins. Today's procedures for pathogen detection involve complex stationary devices, and are often too time consuming for a rapid and effective response. Therefore a robust and mobile diagnostic system is required. We present a microstructured LabDisk which performs complex biochemical analyses together with a mobile centrifugal microfluidic device which processes the LabDisk. This portable system will allow fully automated and rapid detection of biological threats at the point-of-need.

Environmental Influence on the Evolution of Morphological Complexity in Machines

PubMed Central

Auerbach, Joshua E.; Bongard, Josh C.

2014-01-01

Whether, when, how, and why increased complexity evolves in biological populations is a longstanding open question. In this work we combine a recently developed method for evolving virtual organisms with an information-theoretic metric of morphological complexity in order to investigate how the complexity of morphologies, which are evolved for locomotion, varies across different environments. We first demonstrate that selection for locomotion results in the evolution of organisms with morphologies that increase in complexity over evolutionary time beyond what would be expected due to random chance. This provides evidence that the increase in complexity observed is a result of a driven rather than a passive trend. In subsequent experiments we demonstrate that morphologies having greater complexity evolve in complex environments, when compared to a simple environment when a cost of complexity is imposed. This suggests that in some niches, evolution may act to complexify the body plans of organisms while in other niches selection favors simpler body plans. PMID:24391483

Interactive and coordinated visualization approaches for biological data analysis.

PubMed

Cruz, António; Arrais, Joel P; Machado, Penousal

2018-03-26

The field of computational biology has become largely dependent on data visualization tools to analyze the increasing quantities of data gathered through the use of new and growing technologies. Aside from the volume, which often results in large amounts of noise and complex relationships with no clear structure, the visualization of biological data sets is hindered by their heterogeneity, as data are obtained from different sources and contain a wide variety of attributes, including spatial and temporal information. This requires visualization approaches that are able to not only represent various data structures simultaneously but also provide exploratory methods that allow the identification of meaningful relationships that would not be perceptible through data analysis algorithms alone. In this article, we present a survey of visualization approaches applied to the analysis of biological data. We focus on graph-based visualizations and tools that use coordinated multiple views to represent high-dimensional multivariate data, in particular time series gene expression, protein-protein interaction networks and biological pathways. We then discuss how these methods can be used to help solve the current challenges surrounding the visualization of complex biological data sets.

Conceptual Foundations of Systems Biology Explaining Complex Cardiac Diseases.

PubMed

Louridas, George E; Lourida, Katerina G

2017-02-21

Systems biology is an important concept that connects molecular biology and genomics with computing science, mathematics and engineering. An endeavor is made in this paper to associate basic conceptual ideas of systems biology with clinical medicine. Complex cardiac diseases are clinical phenotypes generated by integration of genetic, molecular and environmental factors. Basic concepts of systems biology like network construction, modular thinking, biological constraints (downward biological direction) and emergence (upward biological direction) could be applied to clinical medicine. Especially, in the field of cardiology, these concepts can be used to explain complex clinical cardiac phenotypes like chronic heart failure and coronary artery disease. Cardiac diseases are biological complex entities which like other biological phenomena can be explained by a systems biology approach. The above powerful biological tools of systems biology can explain robustness growth and stability during disease process from modulation to phenotype. The purpose of the present review paper is to implement systems biology strategy and incorporate some conceptual issues raised by this approach into the clinical field of complex cardiac diseases. Cardiac disease process and progression can be addressed by the holistic realistic approach of systems biology in order to define in better terms earlier diagnosis and more effective therapy.

[Study of the interrelations of ethmozine, cordarone and phenycaberan with heparin].

PubMed

Tolstopiatov, B I

1981-01-01

Cordarone, etmozin and phenycaberan form complexes with heparin. Etmozin and phenycaberan form complexes insoluble in an aqueous medium and exhibit a pronounced antiheparin action in in-vitro experiments. Cordarone and heparin form a complex which is soluble in an aqueous medium. This complex potentiates the biological activity of the anticoagulant. In experiments on rabbits cordarone and phenycaberan increase plasma tolerance to heparin followed by its lowering as compared with controls in experiments with phenycaberan. Etmozin decreases plasma tolerance to heparin.

Vibrational spectroscopy for imaging single microbial cells in complex biological samples

DOE PAGES

Harrison, Jesse P.; Berry, David

2017-04-13

Here, vibrational spectroscopy is increasingly used for the rapid and non-destructive imaging of environmental and medical samples. Both Raman and Fourier-transform infrared (FT-IR) imaging have been applied to obtain detailed information on the chemical composition of biological materials, ranging from single microbial cells to tissues. Due to its compatibility with methods such as stable isotope labeling for the monitoring of cellular activities, vibrational spectroscopy also holds considerable power as a tool in microbial ecology. Chemical imaging of undisturbed biological systems (such as live cells in their native habitats) presents unique challenges due to the physical and chemical complexity of themore » samples, potential for spectral interference, and frequent need for real-time measurements. This Mini Review provides a critical synthesis of recent applications of Raman and FT-IR spectroscopy for characterizing complex biological samples, with a focus on developments in single-cell imaging. We also discuss how new spectroscopic methods could be used to overcome current limitations of singlecell analyses. Given the inherent complementarity of Raman and FT-IR spectroscopic methods, we discuss how combining these approaches could enable us to obtain new insights into biological activities either in situ or under conditions that simulate selected properties of the natural environment.« less

Vibrational spectroscopy for imaging single microbial cells in complex biological samples

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

Harrison, Jesse P.; Berry, David

Here, vibrational spectroscopy is increasingly used for the rapid and non-destructive imaging of environmental and medical samples. Both Raman and Fourier-transform infrared (FT-IR) imaging have been applied to obtain detailed information on the chemical composition of biological materials, ranging from single microbial cells to tissues. Due to its compatibility with methods such as stable isotope labeling for the monitoring of cellular activities, vibrational spectroscopy also holds considerable power as a tool in microbial ecology. Chemical imaging of undisturbed biological systems (such as live cells in their native habitats) presents unique challenges due to the physical and chemical complexity of themore » samples, potential for spectral interference, and frequent need for real-time measurements. This Mini Review provides a critical synthesis of recent applications of Raman and FT-IR spectroscopy for characterizing complex biological samples, with a focus on developments in single-cell imaging. We also discuss how new spectroscopic methods could be used to overcome current limitations of singlecell analyses. Given the inherent complementarity of Raman and FT-IR spectroscopic methods, we discuss how combining these approaches could enable us to obtain new insights into biological activities either in situ or under conditions that simulate selected properties of the natural environment.« less

“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

APG: an Active Protein-Gene network model to quantify regulatory signals in complex biological systems.

PubMed

Wang, Jiguang; Sun, Yidan; Zheng, Si; Zhang, Xiang-Sun; Zhou, Huarong; Chen, Luonan

2013-01-01

Synergistic interactions among transcription factors (TFs) and their cofactors collectively determine gene expression in complex biological systems. In this work, we develop a novel graphical model, called Active Protein-Gene (APG) network model, to quantify regulatory signals of transcription in complex biomolecular networks through integrating both TF upstream-regulation and downstream-regulation high-throughput data. Firstly, we theoretically and computationally demonstrate the effectiveness of APG by comparing with the traditional strategy based only on TF downstream-regulation information. We then apply this model to study spontaneous type 2 diabetic Goto-Kakizaki (GK) and Wistar control rats. Our biological experiments validate the theoretical results. In particular, SP1 is found to be a hidden TF with changed regulatory activity, and the loss of SP1 activity contributes to the increased glucose production during diabetes development. APG model provides theoretical basis to quantitatively elucidate transcriptional regulation by modelling TF combinatorial interactions and exploiting multilevel high-throughput information.

APG: an Active Protein-Gene Network Model to Quantify Regulatory Signals in Complex Biological Systems

PubMed Central

Wang, Jiguang; Sun, Yidan; Zheng, Si; Zhang, Xiang-Sun; Zhou, Huarong; Chen, Luonan

2013-01-01

Synergistic interactions among transcription factors (TFs) and their cofactors collectively determine gene expression in complex biological systems. In this work, we develop a novel graphical model, called Active Protein-Gene (APG) network model, to quantify regulatory signals of transcription in complex biomolecular networks through integrating both TF upstream-regulation and downstream-regulation high-throughput data. Firstly, we theoretically and computationally demonstrate the effectiveness of APG by comparing with the traditional strategy based only on TF downstream-regulation information. We then apply this model to study spontaneous type 2 diabetic Goto-Kakizaki (GK) and Wistar control rats. Our biological experiments validate the theoretical results. In particular, SP1 is found to be a hidden TF with changed regulatory activity, and the loss of SP1 activity contributes to the increased glucose production during diabetes development. APG model provides theoretical basis to quantitatively elucidate transcriptional regulation by modelling TF combinatorial interactions and exploiting multilevel high-throughput information. PMID:23346354

Methods of Model Reduction for Large-Scale Biological Systems: A Survey of Current Methods and Trends.

PubMed

Snowden, Thomas J; van der Graaf, Piet H; Tindall, Marcus J

2017-07-01

Complex models of biochemical reaction systems have become increasingly common in the systems biology literature. The complexity of such models can present a number of obstacles for their practical use, often making problems difficult to intuit or computationally intractable. Methods of model reduction can be employed to alleviate the issue of complexity by seeking to eliminate those portions of a reaction network that have little or no effect upon the outcomes of interest, hence yielding simplified systems that retain an accurate predictive capacity. This review paper seeks to provide a brief overview of a range of such methods and their application in the context of biochemical reaction network models. To achieve this, we provide a brief mathematical account of the main methods including timescale exploitation approaches, reduction via sensitivity analysis, optimisation methods, lumping, and singular value decomposition-based approaches. Methods are reviewed in the context of large-scale systems biology type models, and future areas of research are briefly discussed.

The Diamond Light Source and the challenges ahead for structural biology: some informal remarks.

PubMed

Ramakrishnan, V

2015-03-06

The remarkable advances in structural biology in the past three decades have led to the determination of increasingly complex structures that lie at the heart of many important biological processes. Many of these advances have been made possible by the use of X-ray crystallography using synchrotron radiation. In this short article, some of the challenges and prospects that lie ahead will be summarized. © 2015 The Author(s) Published by the Royal Society. All rights reserved.

Protein Complex Production from the Drug Discovery Standpoint.

PubMed

Moarefi, Ismail

2016-01-01

Small molecule drug discovery critically depends on the availability of meaningful in vitro assays to guide medicinal chemistry programs that are aimed at optimizing drug potency and selectivity. As it becomes increasingly evident, most disease relevant drug targets do not act as a single protein. In the body, they are instead generally found in complex with protein cofactors that are highly relevant for their correct function and regulation. This review highlights selected examples of the increasing trend to use biologically relevant protein complexes for rational drug discovery to reduce costly late phase attritions due to lack of efficacy or toxicity.

Tumour necrosis factor-α/etanercept complexes in serum predict long-term efficacy of etanercept treatment in seronegative rheumatoid arthritis.

PubMed

Berthold, E; Månsson, B; Gullstrand, B; Geborek, P; Saxne, T; Bengtsson, A A; Kahn, R

2018-01-01

To study whether serum levels of tumour necrosis factor-α (TNF-α), free or bound to etanercept, in biological-naïve adults with rheumatoid arthritis (RA) could predict the long-term efficacy of etanercept, measured as drug survival. We identified 145 biological-naïve patients with RA starting treatment with etanercept at the Department of Rheumatology, Skåne University Hospital (1999-2008), of whom 16 had seronegative and 129 seropositive RA. TNF-α in serum was quantified using enzyme-linked immunosorbent assay in samples from the onset of treatment and at 6 week follow-up. Drug survival time was used to evaluate the long-term efficacy of etanercept. Levels of TNF-α were significantly increased at follow-up compared to at the start. At the 6 week follow-up, circulating TNF-α mainly comprised TNF-α in complex with etanercept. Longer drug survival time correlated with increased TNF-α at 6 week follow-up in the patients with seronegative RA, but not in the seropositive patients. We demonstrated that levels of circulating TNF-α increased in almost all individuals after initiation of treatment with etanercept and that this increase mainly comprised TNF-α in complex with etanercept. More importantly, this increase may predict drug survival in adults with seronegative, but not seropositive, RA and suggests that measuring TNF-α/etanercept complexes in serum may be relevant in patients with seronegative RA.

Use of biological priors enhances understanding of genetic architecture and genomic prediction of complex traits within and between dairy cattle breeds.

PubMed

Fang, Lingzhao; Sahana, Goutam; Ma, Peipei; Su, Guosheng; Yu, Ying; Zhang, Shengli; Lund, Mogens Sandø; Sørensen, Peter

2017-08-10

A better understanding of the genetic architecture underlying complex traits (e.g., the distribution of causal variants and their effects) may aid in the genomic prediction. Here, we hypothesized that the genomic variants of complex traits might be enriched in a subset of genomic regions defined by genes grouped on the basis of "Gene Ontology" (GO), and that incorporating this independent biological information into genomic prediction models might improve their predictive ability. Four complex traits (i.e., milk, fat and protein yields, and mastitis) together with imputed sequence variants in Holstein (HOL) and Jersey (JER) cattle were analysed. We first carried out a post-GWAS analysis in a HOL training population to assess the degree of enrichment of the association signals in the gene regions defined by each GO term. We then extended the genomic best linear unbiased prediction model (GBLUP) to a genomic feature BLUP (GFBLUP) model, including an additional genomic effect quantifying the joint effect of a group of variants located in a genomic feature. The GBLUP model using a single random effect assumes that all genomic variants contribute to the genomic relationship equally, whereas GFBLUP attributes different weights to the individual genomic relationships in the prediction equation based on the estimated genomic parameters. Our results demonstrate that the immune-relevant GO terms were more associated with mastitis than milk production, and several biologically meaningful GO terms improved the prediction accuracy with GFBLUP for the four traits, as compared with GBLUP. The improvement of the genomic prediction between breeds (the average increase across the four traits was 0.161) was more apparent than that it was within the HOL (the average increase across the four traits was 0.020). Our genomic feature modelling approaches provide a framework to simultaneously explore the genetic architecture and genomic prediction of complex traits by taking advantage of independent biological knowledge.

A brief introduction to mixed effects modelling and multi-model inference in ecology

PubMed Central

Donaldson, Lynda; Correa-Cano, Maria Eugenia; Goodwin, Cecily E.D.

2018-01-01

The use of linear mixed effects models (LMMs) is increasingly common in the analysis of biological data. Whilst LMMs offer a flexible approach to modelling a broad range of data types, ecological data are often complex and require complex model structures, and the fitting and interpretation of such models is not always straightforward. The ability to achieve robust biological inference requires that practitioners know how and when to apply these tools. Here, we provide a general overview of current methods for the application of LMMs to biological data, and highlight the typical pitfalls that can be encountered in the statistical modelling process. We tackle several issues regarding methods of model selection, with particular reference to the use of information theory and multi-model inference in ecology. We offer practical solutions and direct the reader to key references that provide further technical detail for those seeking a deeper understanding. This overview should serve as a widely accessible code of best practice for applying LMMs to complex biological problems and model structures, and in doing so improve the robustness of conclusions drawn from studies investigating ecological and evolutionary questions. PMID:29844961

A brief introduction to mixed effects modelling and multi-model inference in ecology.

PubMed

Harrison, Xavier A; Donaldson, Lynda; Correa-Cano, Maria Eugenia; Evans, Julian; Fisher, David N; Goodwin, Cecily E D; Robinson, Beth S; Hodgson, David J; Inger, Richard

2018-01-01

The use of linear mixed effects models (LMMs) is increasingly common in the analysis of biological data. Whilst LMMs offer a flexible approach to modelling a broad range of data types, ecological data are often complex and require complex model structures, and the fitting and interpretation of such models is not always straightforward. The ability to achieve robust biological inference requires that practitioners know how and when to apply these tools. Here, we provide a general overview of current methods for the application of LMMs to biological data, and highlight the typical pitfalls that can be encountered in the statistical modelling process. We tackle several issues regarding methods of model selection, with particular reference to the use of information theory and multi-model inference in ecology. We offer practical solutions and direct the reader to key references that provide further technical detail for those seeking a deeper understanding. This overview should serve as a widely accessible code of best practice for applying LMMs to complex biological problems and model structures, and in doing so improve the robustness of conclusions drawn from studies investigating ecological and evolutionary questions.

The Effectiveness of an Online Curriculum on High School Students' Understanding of Biological Evolution

NASA Astrophysics Data System (ADS)

Marsteller, Robert B.; Bodzin, Alec M.

2015-12-01

An online curriculum about biological evolution was designed to promote increased student content knowledge and evidentiary reasoning. A feasibility study was conducted with 77 rural high school biology students who learned with the online biological evolution unit. Data sources included the Biological Evolution Assessment Measure (BEAM), an analysis of discussion forum posts, and a post-implementation perceptions and attitudes questionnaire. BEAM posttest scores were significantly higher than the pretest scores. However, the findings revealed that the students required additional support to develop evidentiary reasoning. Many students perceived that the Web-based curriculum would have been enhanced by increased immediate interaction and feedback. Students required greater scaffolding to support complex, process-oriented tasks. Implications for designing Web-based science instruction with curriculum materials to support students' acquisition of content knowledge and science process skills in a Web-based setting are discussed.

Pharmacological Role of Anions (Sulphate, Nitrate, Oxalate and Acetate) on the Antibacterial Activity of Cobalt(II), Copper(II) and Nickel(II) Complexes With Nicotinoylhydrazine-Derived ONO, NNO and SNO Ligands

PubMed Central

Rauf, Abdur

1996-01-01

Mixed ligands biologically active complexes of cobalt(II), copper(II) and nickel(II) with nicotinoylhydrazine-derived ONO, NNO and SNO donor schiff-base ligands having the same metal ion but different anions such as sulphate, nitrate, oxalate and acetate have been synthesised and characterised on the basis of their physical, analytical and spectral data. In order to evaluate the role of anions on their bioability, these ligands and their synthesised metal complexes with various anions have been screened against bacterial species such as Escherichia coli, Pseudomonas aeruginosa and Staphylococcus aureus and the title studies have proved a definative role of anions in increasing the biological activity PMID:18472896

Utility of QR codes in biological collections

PubMed Central

Diazgranados, Mauricio; Funk, Vicki A.

2013-01-01

Abstract The popularity of QR codes for encoding information such as URIs has increased exponentially in step with the technological advances and availability of smartphones, digital tablets, and other electronic devices. We propose using QR codes on specimens in biological collections to facilitate linking vouchers’ electronic information with their associated collections. QR codes can efficiently provide such links for connecting collections, photographs, maps, ecosystem notes, citations, and even GenBank sequences. QR codes have numerous advantages over barcodes, including their small size, superior security mechanisms, increased complexity and quantity of information, and low implementation cost. The scope of this paper is to initiate an academic discussion about using QR codes on specimens in biological collections. PMID:24198709

Utility of QR codes in biological collections.

PubMed

Diazgranados, Mauricio; Funk, Vicki A

2013-01-01

The popularity of QR codes for encoding information such as URIs has increased exponentially in step with the technological advances and availability of smartphones, digital tablets, and other electronic devices. We propose using QR codes on specimens in biological collections to facilitate linking vouchers' electronic information with their associated collections. QR codes can efficiently provide such links for connecting collections, photographs, maps, ecosystem notes, citations, and even GenBank sequences. QR codes have numerous advantages over barcodes, including their small size, superior security mechanisms, increased complexity and quantity of information, and low implementation cost. The scope of this paper is to initiate an academic discussion about using QR codes on specimens in biological collections.

Artificial cell mimics as simplified models for the study of cell biology.

PubMed

Salehi-Reyhani, Ali; Ces, Oscar; Elani, Yuval

2017-07-01

Living cells are hugely complex chemical systems composed of a milieu of distinct chemical species (including DNA, proteins, lipids, and metabolites) interconnected with one another through a vast web of interactions: this complexity renders the study of cell biology in a quantitative and systematic manner a difficult task. There has been an increasing drive towards the utilization of artificial cells as cell mimics to alleviate this, a development that has been aided by recent advances in artificial cell construction. Cell mimics are simplified cell-like structures, composed from the bottom-up with precisely defined and tunable compositions. They allow specific facets of cell biology to be studied in isolation, in a simplified environment where control of variables can be achieved without interference from a living and responsive cell. This mini-review outlines the core principles of this approach and surveys recent key investigations that use cell mimics to address a wide range of biological questions. It will also place the field in the context of emerging trends, discuss the associated limitations, and outline future directions of the field. Impact statement Recent years have seen an increasing drive to construct cell mimics and use them as simplified experimental models to replicate and understand biological phenomena in a well-defined and controlled system. By summarizing the advances in this burgeoning field, and using case studies as a basis for discussion on the limitations and future directions of this approach, it is hoped that this minireview will spur others in the experimental biology community to use artificial cells as simplified models with which to probe biological systems.

78 FR 58311 - Complex Issues in Developing Drug and Biological Products for Rare Diseases; Public Workshop...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-09-23

...] Complex Issues in Developing Drug and Biological Products for Rare Diseases; Public Workshop; Request for... Issues in Developing Drug and Biological Products for Rare Diseases.'' The purpose of the public workshop is twofold: To discuss complex issues in clinical trials for developing drug and biological products...

Application of Biologically Based Lumping To Investigate the Toxicokinetic Interactions of a Complex Gasoline Mixture.

PubMed

Jasper, Micah N; Martin, Sheppard A; Oshiro, Wendy M; Ford, Jermaine; Bushnell, Philip J; El-Masri, Hisham

2016-03-15

People are often exposed to complex mixtures of environmental chemicals such as gasoline, tobacco smoke, water contaminants, or food additives. We developed an approach that applies chemical lumping methods to complex mixtures, in this case gasoline, based on biologically relevant parameters used in physiologically based pharmacokinetic (PBPK) modeling. Inhalation exposures were performed with rats to evaluate the performance of our PBPK model and chemical lumping method. There were 109 chemicals identified and quantified in the vapor in the chamber. The time-course toxicokinetic profiles of 10 target chemicals were also determined from blood samples collected during and following the in vivo experiments. A general PBPK model was used to compare the experimental data to the simulated values of blood concentration for 10 target chemicals with various numbers of lumps, iteratively increasing from 0 to 99. Large reductions in simulation error were gained by incorporating enzymatic chemical interactions, in comparison to simulating the individual chemicals separately. The error was further reduced by lumping the 99 nontarget chemicals. The same biologically based lumping approach can be used to simplify any complex mixture with tens, hundreds, or thousands of constituents.

Sender–receiver systems and applying information theory for quantitative synthetic biology

PubMed Central

Barcena Menendez, Diego; Senthivel, Vivek Raj; Isalan, Mark

2015-01-01

Sender–receiver (S–R) systems abound in biology, with communication systems sending information in various forms. Information theory provides a quantitative basis for analysing these processes and is being applied to study natural genetic, enzymatic and neural networks. Recent advances in synthetic biology are providing us with a wealth of artificial S–R systems, giving us quantitative control over networks with a finite number of well-characterised components. Combining the two approaches can help to predict how to maximise signalling robustness, and will allow us to make increasingly complex biological computers. Ultimately, pushing the boundaries of synthetic biology will require moving beyond engineering the flow of information and towards building more sophisticated circuits that interpret biological meaning. PMID:25282688

Advancing secondary metabolite biosynthesis in yeast with synthetic biology tools.

PubMed

Siddiqui, Michael S; Thodey, Kate; Trenchard, Isis; Smolke, Christina D

2012-03-01

Secondary metabolites are an important source of high-value chemicals, many of which exhibit important pharmacological properties. These valuable natural products are often difficult to synthesize chemically and are commonly isolated through inefficient extractions from natural biological sources. As such, they are increasingly targeted for production by biosynthesis from engineered microorganisms. The budding yeast species Saccharomyces cerevisiae has proven to be a powerful microorganism for heterologous expression of biosynthetic pathways. S. cerevisiae's usefulness as a host organism is owed in large part to the wealth of knowledge accumulated over more than a century of intense scientific study. Yet many challenges are currently faced in engineering yeast strains for the biosynthesis of complex secondary metabolite production. However, synthetic biology is advancing the development of new tools for constructing, controlling, and optimizing complex metabolic pathways in yeast. Here, we review how the coupling between yeast biology and synthetic biology is advancing the use of S. cerevisiae as a microbial host for the construction of secondary metabolic pathways. © 2011 Federation of European Microbiological Societies. Published by Blackwell Publishing Ltd. All rights reserved.

Plant Systems Biology at the Single-Cell Level.

PubMed

Libault, Marc; Pingault, Lise; Zogli, Prince; Schiefelbein, John

2017-11-01

Our understanding of plant biology is increasingly being built upon studies using 'omics and system biology approaches performed at the level of the entire plant, organ, or tissue. Although these approaches open new avenues to better understand plant biology, they suffer from the cellular complexity of the analyzed sample. Recent methodological advances now allow plant scientists to overcome this limitation and enable biological analyses of single-cells or single-cell-types. Coupled with the development of bioinformatics and functional genomics resources, these studies provide opportunities for high-resolution systems analyses of plant phenomena. In this review, we describe the recent advances, current challenges, and future directions in exploring the biology of single-cells and single-cell-types to enhance our understanding of plant biology as a system. Copyright © 2017 Elsevier Ltd. All rights reserved.

Knowledge-making distinctions in synthetic biology.

PubMed

O'Malley, Maureen A; Powell, Alexander; Davies, Jonathan F; Calvert, Jane

2008-01-01

Synthetic biology is an increasingly high-profile area of research that can be understood as encompassing three broad approaches towards the synthesis of living systems: DNA-based device construction, genome-driven cell engineering and protocell creation. Each approach is characterized by different aims, methods and constructs, in addition to a range of positions on intellectual property and regulatory regimes. We identify subtle but important differences between the schools in relation to their treatments of genetic determinism, cellular context and complexity. These distinctions tie into two broader issues that define synthetic biology: the relationships between biology and engineering, and between synthesis and analysis. These themes also illuminate synthetic biology's connections to genetic and other forms of biological engineering, as well as to systems biology. We suggest that all these knowledge-making distinctions in synthetic biology raise fundamental questions about the nature of biological investigation and its relationship to the construction of biological components and systems. (c) 2007 Wiley Periodicals, Inc.

Syntheses, Characterization, Resolution, and Biological Studies of Coordination Compounds of Aspartic Acid and Glycine

PubMed Central

Akinkunmi, Ezekiel; Ojo, Isaac; Adebajo, Clement; Isabirye, David

2017-01-01

Enantiomerically enriched coordination compounds of aspartic acid and racemic mixtures of coordination compounds of glycine metal-ligand ratio 1 : 3 were synthesized and characterized using infrared and UV-Vis spectrophotometric techniques and magnetic susceptibility measurements. Five of the complexes were resolved using (+)-cis-dichlorobis(ethylenediamine)cobalt(III) chloride, (+)-bis(glycinato)(1,10-phenanthroline)cobalt(III) chloride, and (+)-tris(1,10-phenanthroline)nickel(II) chloride as resolving agents. The antimicrobial and cytotoxic activities of these complexes were then determined. The results obtained indicated that aspartic acid and glycine coordinated in a bidentate fashion. The enantiomeric purity of the compounds was in the range of 22.10–32.10%, with (+)-cis-dichlorobis(ethylenediamine)cobalt(III) complex as the more efficient resolving agent. The resolved complexes exhibited better activity in some cases compared to the parent complexes for both biological activities. It was therefore inferred that although the increase in the lipophilicity of the complexes may assist in the permeability of the complexes through the cell membrane of the pathogens, the enantiomeric purity of the complexes is also of importance in their activity as antimicrobial and cytotoxic agents. PMID:28293149

Portable Raman instrument for rapid biological agent detection and identification

NASA Astrophysics Data System (ADS)

Lesaicherre, Marie L.; Paxon, Tracy L.; Mondello, Frank J.; Burrell, Michael C.; Linsebigler, Amy

2009-05-01

The rapid and sensitive identification of biological species is a critical need for the 1st responder and military communities. Raman spectroscopy is a powerful tool for substance identification that has gained popularity with the respective communities due to the increasing availability of portable Raman spectrometers. Attempts to use Raman spectroscopy for the direct identification of biological pathogens has been hindered by the complexity of the generated Raman spectrum. We report here the use of a sandwich immunoassay containing antibody modified magnetic beads to capture and concentrate target analytes in solution and Surface Enhanced Raman Spectroscopy (SERS) tags conjugated with these same antibodies for specific detection. Using this approach, the biological complexity of a microorganism can be translated into chemical simplicity and Raman can be used for the identification of biological pathogens. The developed assay has a low limit of detection due to the SERS effect, robust to commonly found white powders interferants, and stable at room temperature over extended period of time. This assay is being implemented into a user-friendly interface to be used in conjunction with the GE Homeland Protection StreetLab MobileTM Raman instrument for rapid, field deployable chemical and biological identification.

Thermo-Responsive Complexes of c-Myc Antisense Oligonucleotide with Block Copolymer of Poly(OEGMA) and Quaternized Poly(4-Vinylpyridine).

PubMed

Topuzogullari, Murat; Elalmis, Yeliz Basaran; Isoglu, Sevil Dincer

2017-04-01

Solution behavior of thermo-responsive polymers and their complexes with biological macromolecules may be affected by environmental conditions, such as the concentration of macromolecular components, pH, ion concentration, etc. Therefore, a thermo-responsive polymer and its complexes should be characterized in detail to observe their responses against possible environments under physiological conditions before biological applications. To briefly indicate this important issue, thermo-responsive block copolymer of quaternized poly(4-vinylpyridine) and poly(oligoethyleneglycol methyl ether methacrylate) as a potential nonviral vector has been synthesized. Polyelectrolyte complexes of this copolymer with the antisense oligonucleotide of c-Myc oncogene are also thermo-responsive but, have lower LCST (lower critical solution temperature) values compared to individual copolymer. LCST values of complexes decrease with molar ratio of macromolecular components and presence of salt. Dilution of solutions also affects solution behavior of complexes and causes a significant decrease in size and an increase in LCST, which indicates possible effects of severe dilutions in the blood stream. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

The Enigma of Tripeptidyl-Peptidase II: Dual Roles in Housekeeping and Stress

PubMed Central

Preta, Giulio; de Klark, Rainier; Gavioli, Riccardo; Glas, Rickard

2010-01-01

The tripeptidyl-peptidase II complex consists of repeated 138 kDa subunits, assembled into two twisted strands that form a high molecular weight complex (>5 MDa). TPPII, like many other cytosolic peptidases, plays a role in the ubiquitin-proteasome pathway downstream of the proteasome as well as in the production and destruction of MHC class I antigens and degradation of neuropeptides. Tripeptidyl-peptidase II activity is increased in cells with an increased demand for protein degradation, but whether degradation of cytosolic peptides is the only cell biological role for TPPII has remained unclear. Recent data indicated that TPPII translocates into the nucleus to control DNA damage responses in malignant cells, supporting that cytosolic “housekeeping peptidases” may have additional roles in cell biology, besides their contribution to protein turnover. Overall, TPPII has an emerging importance in several cancer-related fields, such as metabolism, cell death control, and control of genome integrity; roles that are not understood in detail. The present paper reviews the cell biology of TPPII and discusses distinct roles for TPPII in the nucleus and cytosol. PMID:20847939

Molecular Mechanics and Dynamics Characterization of an "in silico" Mutated Protein: A Stand-Alone Lab Module or Support Activity for "in vivo" and "in vitro" Analyses of Targeted Proteins

ERIC Educational Resources Information Center

Chiang, Harry; Robinson, Lucy C.; Brame, Cynthia J.; Messina, Troy C.

2013-01-01

Over the past 20 years, the biological sciences have increasingly incorporated chemistry, physics, computer science, and mathematics to aid in the development and use of mathematical models. Such combined approaches have been used to address problems from protein structure-function relationships to the workings of complex biological systems.…

Diagnostic nanoparticle targeting of the EGF-receptor in complex biological conditions using single-domain antibodies.

PubMed

Zarschler, K; Prapainop, K; Mahon, E; Rocks, L; Bramini, M; Kelly, P M; Stephan, H; Dawson, K A

2014-06-07

For effective localization of functionalized nanoparticles at diseased tissues such as solid tumours or metastases through biorecognition, appropriate targeting vectors directed against selected tumour biomarkers are a key prerequisite. The diversity of such vector molecules ranges from proteins, including antibodies and fragments thereof, through aptamers and glycans to short peptides and small molecules. Here, we analyse the specific nanoparticle targeting capabilities of two previously suggested peptides (D4 and GE11) and a small camelid single-domain antibody (sdAb), representing potential recognition agents for the epidermal growth factor receptor (EGFR). We investigate specificity by way of receptor RNA silencing techniques and look at increasing complexity in vitro by introducing increasing concentrations of human or bovine serum. Peptides D4 and GE11 proved problematic to employ and conjugation resulted in non-receptor specific uptake into cells. Our results show that sdAb-functionalized particles can effectively target the EGFR, even in more complex bovine and human serum conditions where targeting specificity is largely conserved for increasing serum concentration. In human serum however, an inhibition of overall nanoparticle uptake is observed with increasing protein concentration. For highly affine targeting ligands such as sdAbs, targeting a receptor such as EGFR with low serum competitor abundance, receptor recognition function can still be partially realised in complex conditions. Here, we stress the value of evaluating the targeting efficiency of nanoparticle constructs in realistic biological milieu, prior to more extensive in vivo studies.

Bayesian uncertainty analysis for complex systems biology models: emulation, global parameter searches and evaluation of gene functions.

PubMed

Vernon, Ian; Liu, Junli; Goldstein, Michael; Rowe, James; Topping, Jen; Lindsey, Keith

2018-01-02

Many mathematical models have now been employed across every area of systems biology. These models increasingly involve large numbers of unknown parameters, have complex structure which can result in substantial evaluation time relative to the needs of the analysis, and need to be compared to observed data of various forms. The correct analysis of such models usually requires a global parameter search, over a high dimensional parameter space, that incorporates and respects the most important sources of uncertainty. This can be an extremely difficult task, but it is essential for any meaningful inference or prediction to be made about any biological system. It hence represents a fundamental challenge for the whole of systems biology. Bayesian statistical methodology for the uncertainty analysis of complex models is introduced, which is designed to address the high dimensional global parameter search problem. Bayesian emulators that mimic the systems biology model but which are extremely fast to evaluate are embeded within an iterative history match: an efficient method to search high dimensional spaces within a more formal statistical setting, while incorporating major sources of uncertainty. The approach is demonstrated via application to a model of hormonal crosstalk in Arabidopsis root development, which has 32 rate parameters, for which we identify the sets of rate parameter values that lead to acceptable matches between model output and observed trend data. The multiple insights into the model's structure that this analysis provides are discussed. The methodology is applied to a second related model, and the biological consequences of the resulting comparison, including the evaluation of gene functions, are described. Bayesian uncertainty analysis for complex models using both emulators and history matching is shown to be a powerful technique that can greatly aid the study of a large class of systems biology models. It both provides insight into model behaviour and identifies the sets of rate parameters of interest.

Node fingerprinting: an efficient heuristic for aligning biological networks.

PubMed

Radu, Alex; Charleston, Michael

2014-10-01

With the continuing increase in availability of biological data and improvements to biological models, biological network analysis has become a promising area of research. An emerging technique for the analysis of biological networks is through network alignment. Network alignment has been used to calculate genetic distance, similarities between regulatory structures, and the effect of external forces on gene expression, and to depict conditional activity of expression modules in cancer. Network alignment is algorithmically complex, and therefore we must rely on heuristics, ideally as efficient and accurate as possible. The majority of current techniques for network alignment rely on precomputed information, such as with protein sequence alignment, or on tunable network alignment parameters, which may introduce an increased computational overhead. Our presented algorithm, which we call Node Fingerprinting (NF), is appropriate for performing global pairwise network alignment without precomputation or tuning, can be fully parallelized, and is able to quickly compute an accurate alignment between two biological networks. It has performed as well as or better than existing algorithms on biological and simulated data, and with fewer computational resources. The algorithmic validation performed demonstrates the low computational resource requirements of NF.

UML as a cell and biochemistry modeling language.

PubMed

Webb, Ken; White, Tony

2005-06-01

The systems biology community is building increasingly complex models and simulations of cells and other biological entities, and are beginning to look at alternatives to traditional representations such as those provided by ordinary differential equations (ODE). The lessons learned over the years by the software development community in designing and building increasingly complex telecommunication and other commercial real-time reactive systems, can be advantageously applied to the problems of modeling in the biology domain. Making use of the object-oriented (OO) paradigm, the unified modeling language (UML) and Real-Time Object-Oriented Modeling (ROOM) visual formalisms, and the Rational Rose RealTime (RRT) visual modeling tool, we describe a multi-step process we have used to construct top-down models of cells and cell aggregates. The simple example model described in this paper includes membranes with lipid bilayers, multiple compartments including a variable number of mitochondria, substrate molecules, enzymes with reaction rules, and metabolic pathways. We demonstrate the relevance of abstraction, reuse, objects, classes, component and inheritance hierarchies, multiplicity, visual modeling, and other current software development best practices. We show how it is possible to start with a direct diagrammatic representation of a biological structure such as a cell, using terminology familiar to biologists, and by following a process of gradually adding more and more detail, arrive at a system with structure and behavior of arbitrary complexity that can run and be observed on a computer. We discuss our CellAK (Cell Assembly Kit) approach in terms of features found in SBML, CellML, E-CELL, Gepasi, Jarnac, StochSim, Virtual Cell, and membrane computing systems.

Managing bioengineering complexity with AI techniques.

PubMed

Beal, Jacob; Adler, Aaron; Yaman, Fusun

2016-10-01

Our capabilities for systematic design and engineering of biological systems are rapidly increasing. Effectively engineering such systems, however, requires the synthesis of a rapidly expanding and changing complex body of knowledge, protocols, and methodologies. Many of the problems in managing this complexity, however, appear susceptible to being addressed by artificial intelligence (AI) techniques, i.e., methods enabling computers to represent, acquire, and employ knowledge. Such methods can be employed to automate physical and informational "routine" work and thus better allow humans to focus their attention on the deeper scientific and engineering issues. This paper examines the potential impact of AI on the engineering of biological organisms through the lens of a typical organism engineering workflow. We identify a number of key opportunities for significant impact, as well as challenges that must be overcome. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Molecular species delimitation methods recover most song-delimited cicada species in the European Cicadetta montana complex.

PubMed

Wade, E J; Hertach, T; Gogala, M; Trilar, T; Simon, C

2015-12-01

Molecular species delimitation is increasingly being used to discover and illuminate species level diversity, and a number of methods have been developed. Here, we compare the ability of two molecular species delimitation methods to recover song-delimited species in the Cicadetta montana cryptic species complex throughout Europe. Recent bioacoustics studies of male calling songs (premating reproductive barriers) have revealed cryptic species diversity in this complex. Maximum likelihood and Bayesian phylogenetic analyses were used to analyse the mitochondrial genes COI and COII and the nuclear genes EF1α and period for thirteen European Cicadetta species as well as the closely related monotypic genus Euboeana. Two molecular species delimitation methods, general mixed Yule-coalescent (GMYC) and Bayesian phylogenetics and phylogeography, identified the majority of song-delimited species and were largely congruent with each other. None of the molecular delimitation methods were able to fully recover a recent radiation of four Greek species. © 2015 European Society For Evolutionary Biology. Journal of Evolutionary Biology © 2015 European Society For Evolutionary Biology.

CHEMICAL PROCESSES AND MODELING IN ECOSYSTEMS

EPA Science Inventory

Trends in regulatory strategies require EPA to understand better chemical behavior in natural and impacted ecosystems and in biological systems to carry out the increasingly complex array of exposure and risk assessments needed to develop scientifically defensible regulations (GP...

Clinical features and pathophysiology of Complex Regional Pain Syndrome – current state of the art

PubMed Central

Marinus, Johan; Moseley, G. Lorimer; Birklein, Frank; Baron, Ralf; Maihöfner, Christian; Kingery, Wade S.; van Hilten, Jacobus J.

2017-01-01

That a minor injury can trigger a complex regional pain syndrome (CRPS) - multiple system dysfunction, severe and often chronic pain and disability - has fascinated scientists and perplexed clinicians for decades. However, substantial advances across several medical disciplines have recently increased our understanding of CRPS. Compelling evidence implicates biological pathways that underlie aberrant inflammation, vasomotor dysfunction, and maladaptive neuroplasticity in the clinical features of CRPS. Collectively, the evidence points to CRPS being a multifactorial disorder that is associated with an aberrant host response to tissue injury. Varying susceptibility to perturbed regulation of any of the underlying biological pathways probably accounts for the clinical heterogeneity of CRPS. PMID:21683929

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.

A Novel Framework for the Comparative Analysis of Biological Networks

PubMed Central

Pache, Roland A.; Aloy, Patrick

2012-01-01

Genome sequencing projects provide nearly complete lists of the individual components present in an organism, but reveal little about how they work together. Follow-up initiatives have deciphered thousands of dynamic and context-dependent interrelationships between gene products that need to be analyzed with novel bioinformatics approaches able to capture their complex emerging properties. Here, we present a novel framework for the alignment and comparative analysis of biological networks of arbitrary topology. Our strategy includes the prediction of likely conserved interactions, based on evolutionary distances, to counter the high number of missing interactions in the current interactome networks, and a fast assessment of the statistical significance of individual alignment solutions, which vastly increases its performance with respect to existing tools. Finally, we illustrate the biological significance of the results through the identification of novel complex components and potential cases of cross-talk between pathways and alternative signaling routes. PMID:22363585

Decoding the complex genetic causes of heart diseases using systems biology.

PubMed

Djordjevic, Djordje; Deshpande, Vinita; Szczesnik, Tomasz; Yang, Andrian; Humphreys, David T; Giannoulatou, Eleni; Ho, Joshua W K

2015-03-01

The pace of disease gene discovery is still much slower than expected, even with the use of cost-effective DNA sequencing and genotyping technologies. It is increasingly clear that many inherited heart diseases have a more complex polygenic aetiology than previously thought. Understanding the role of gene-gene interactions, epigenetics, and non-coding regulatory regions is becoming increasingly critical in predicting the functional consequences of genetic mutations identified by genome-wide association studies and whole-genome or exome sequencing. A systems biology approach is now being widely employed to systematically discover genes that are involved in heart diseases in humans or relevant animal models through bioinformatics. The overarching premise is that the integration of high-quality causal gene regulatory networks (GRNs), genomics, epigenomics, transcriptomics and other genome-wide data will greatly accelerate the discovery of the complex genetic causes of congenital and complex heart diseases. This review summarises state-of-the-art genomic and bioinformatics techniques that are used in accelerating the pace of disease gene discovery in heart diseases. Accompanying this review, we provide an interactive web-resource for systems biology analysis of mammalian heart development and diseases, CardiacCode ( http://CardiacCode.victorchang.edu.au/ ). CardiacCode features a dataset of over 700 pieces of manually curated genetic or molecular perturbation data, which enables the inference of a cardiac-specific GRN of 280 regulatory relationships between 33 regulator genes and 129 target genes. We believe this growing resource will fill an urgent unmet need to fully realise the true potential of predictive and personalised genomic medicine in tackling human heart disease.

Discovering protein complexes in protein interaction networks via exploring the weak ties effect

PubMed Central

2012-01-01

Background Studying protein complexes is very important in biological processes since it helps reveal the structure-functionality relationships in biological networks and much attention has been paid to accurately predict protein complexes from the increasing amount of protein-protein interaction (PPI) data. Most of the available algorithms are based on the assumption that dense subgraphs correspond to complexes, failing to take into account the inherence organization within protein complex and the roles of edges. Thus, there is a critical need to investigate the possibility of discovering protein complexes using the topological information hidden in edges. Results To provide an investigation of the roles of edges in PPI networks, we show that the edges connecting less similar vertices in topology are more significant in maintaining the global connectivity, indicating the weak ties phenomenon in PPI networks. We further demonstrate that there is a negative relation between the weak tie strength and the topological similarity. By using the bridges, a reliable virtual network is constructed, in which each maximal clique corresponds to the core of a complex. By this notion, the detection of the protein complexes is transformed into a classic all-clique problem. A novel core-attachment based method is developed, which detects the cores and attachments, respectively. A comprehensive comparison among the existing algorithms and our algorithm has been made by comparing the predicted complexes against benchmark complexes. Conclusions We proved that the weak tie effect exists in the PPI network and demonstrated that the density is insufficient to characterize the topological structure of protein complexes. Furthermore, the experimental results on the yeast PPI network show that the proposed method outperforms the state-of-the-art algorithms. The analysis of detected modules by the present algorithm suggests that most of these modules have well biological significance in context of complexes, suggesting that the roles of edges are critical in discovering protein complexes. PMID:23046740

On Crowd-verification of Biological Networks

PubMed Central

Ansari, Sam; Binder, Jean; Boue, Stephanie; Di Fabio, Anselmo; Hayes, William; Hoeng, Julia; Iskandar, Anita; Kleiman, Robin; Norel, Raquel; O’Neel, Bruce; Peitsch, Manuel C.; Poussin, Carine; Pratt, Dexter; Rhrissorrakrai, Kahn; Schlage, Walter K.; Stolovitzky, Gustavo; Talikka, Marja

2013-01-01

Biological networks with a structured syntax are a powerful way of representing biological information generated from high density data; however, they can become unwieldy to manage as their size and complexity increase. This article presents a crowd-verification approach for the visualization and expansion of biological networks. Web-based graphical interfaces allow visualization of causal and correlative biological relationships represented using Biological Expression Language (BEL). Crowdsourcing principles enable participants to communally annotate these relationships based on literature evidences. Gamification principles are incorporated to further engage domain experts throughout biology to gather robust peer-reviewed information from which relationships can be identified and verified. The resulting network models will represent the current status of biological knowledge within the defined boundaries, here processes related to human lung disease. These models are amenable to computational analysis. For some period following conclusion of the challenge, the published models will remain available for continuous use and expansion by the scientific community. PMID:24151423

Mapping complex traits as a dynamic system

PubMed Central

Sun, Lidan; Wu, Rongling

2017-01-01

Despite increasing emphasis on the genetic study of quantitative traits, we are still far from being able to chart a clear picture of their genetic architecture, given an inherent complexity involved in trait formation. A competing theory for studying such complex traits has emerged by viewing their phenotypic formation as a “system” in which a high-dimensional group of interconnected components act and interact across different levels of biological organization from molecules through cells to whole organisms. This system is initiated by a machinery of DNA sequences that regulate a cascade of biochemical pathways to synthesize endophenotypes and further assemble these endophenotypes toward the end-point phenotype in virtue of various developmental changes. This review focuses on a conceptual framework for genetic mapping of complex traits by which to delineate the underlying components, interactions and mechanisms that govern the system according to biological principles and understand how these components function synergistically under the control of quantitative trait loci (QTLs) to comprise a unified whole. This framework is built by a system of differential equations that quantifies how alterations of different components lead to the global change of trait development and function, and provides a quantitative and testable platform for assessing the multiscale interplay between QTLs and development. The method will enable geneticists to shed light on the genetic complexity of any biological system and predict, alter or engineer its physiological and pathological states. PMID:25772476

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.

Parameterization and Sensitivity Analysis of a Complex Simulation Model for Mosquito Population Dynamics, Dengue Transmission, and Their Control

PubMed Central

Ellis, Alicia M.; Garcia, Andres J.; Focks, Dana A.; Morrison, Amy C.; Scott, Thomas W.

2011-01-01

Models can be useful tools for understanding the dynamics and control of mosquito-borne disease. More detailed models may be more realistic and better suited for understanding local disease dynamics; however, evaluating model suitability, accuracy, and performance becomes increasingly difficult with greater model complexity. Sensitivity analysis is a technique that permits exploration of complex models by evaluating the sensitivity of the model to changes in parameters. Here, we present results of sensitivity analyses of two interrelated complex simulation models of mosquito population dynamics and dengue transmission. We found that dengue transmission may be influenced most by survival in each life stage of the mosquito, mosquito biting behavior, and duration of the infectious period in humans. The importance of these biological processes for vector-borne disease models and the overwhelming lack of knowledge about them make acquisition of relevant field data on these biological processes a top research priority. PMID:21813844

The dynamics of food chains under climate change and nutrient enrichment.

PubMed

Binzer, Amrei; Guill, Christian; Brose, Ulrich; Rall, Björn C

2012-11-05

Warming has profound effects on biological rates such as metabolism, growth, feeding and death of organisms, eventually affecting their ability to survive. Using a nonlinear bioenergetic population-dynamic model that accounts for temperature and body-mass dependencies of biological rates, we analysed the individual and interactive effects of increasing temperature and nutrient enrichment on the dynamics of a three-species food chain. At low temperatures, warming counteracts the destabilizing effects of enrichment by both bottom-up (via the carrying capacity) and top-down (via biological rates) mechanisms. Together with increasing consumer body masses, warming increases the system tolerance to fertilization. Simultaneously, warming increases the risk of starvation for large species in low-fertility systems. This effect can be counteracted by increased fertilization. In combination, therefore, two main drivers of global change and biodiversity loss can have positive and negative effects on food chain stability. Our model incorporates the most recent empirical data and may thus be used as the basis for more complex forecasting models incorporating food-web structure.

Towards physical principles of biological evolution

NASA Astrophysics Data System (ADS)

Katsnelson, Mikhail I.; Wolf, Yuri I.; Koonin, Eugene V.

2018-03-01

Biological systems reach organizational complexity that far exceeds the complexity of any known inanimate objects. Biological entities undoubtedly obey the laws of quantum physics and statistical mechanics. However, is modern physics sufficient to adequately describe, model and explain the evolution of biological complexity? Detailed parallels have been drawn between statistical thermodynamics and the population-genetic theory of biological evolution. Based on these parallels, we outline new perspectives on biological innovation and major transitions in evolution, and introduce a biological equivalent of thermodynamic potential that reflects the innovation propensity of an evolving population. Deep analogies have been suggested to also exist between the properties of biological entities and processes, and those of frustrated states in physics, such as glasses. Such systems are characterized by frustration whereby local state with minimal free energy conflict with the global minimum, resulting in ‘emergent phenomena’. We extend such analogies by examining frustration-type phenomena, such as conflicts between different levels of selection, in biological evolution. These frustration effects appear to drive the evolution of biological complexity. We further address evolution in multidimensional fitness landscapes from the point of view of percolation theory and suggest that percolation at level above the critical threshold dictates the tree-like evolution of complex organisms. Taken together, these multiple connections between fundamental processes in physics and biology imply that construction of a meaningful physical theory of biological evolution might not be a futile effort. However, it is unrealistic to expect that such a theory can be created in one scoop; if it ever comes to being, this can only happen through integration of multiple physical models of evolutionary processes. Furthermore, the existing framework of theoretical physics is unlikely to suffice for adequate modeling of the biological level of complexity, and new developments within physics itself are likely to be required.

A modified Wright-Fisher model that incorporates Ne: A variant of the standard model with increased biological realism and reduced computational complexity.

PubMed

Zhao, Lei; Gossmann, Toni I; Waxman, David

2016-03-21

The Wright-Fisher model is an important model in evolutionary biology and population genetics. It has been applied in numerous analyses of finite populations with discrete generations. It is recognised that real populations can behave, in some key aspects, as though their size that is not the census size, N, but rather a smaller size, namely the effective population size, Ne. However, in the Wright-Fisher model, there is no distinction between the effective and census population sizes. Equivalently, we can say that in this model, Ne coincides with N. The Wright-Fisher model therefore lacks an important aspect of biological realism. Here, we present a method that allows Ne to be directly incorporated into the Wright-Fisher model. The modified model involves matrices whose size is determined by Ne. Thus apart from increased biological realism, the modified model also has reduced computational complexity, particularly so when Ne⪡N. For complex problems, it may be hard or impossible to numerically analyse the most commonly-used approximation of the Wright-Fisher model that incorporates Ne, namely the diffusion approximation. An alternative approach is simulation. However, the simulations need to be sufficiently detailed that they yield an effective size that is different to the census size. Simulations may also be time consuming and have attendant statistical errors. The method presented in this work may then be the only alternative to simulations, when Ne differs from N. We illustrate the straightforward application of the method to some problems involving allele fixation and the determination of the equilibrium site frequency spectrum. We then apply the method to the problem of fixation when three alleles are segregating in a population. This latter problem is significantly more complex than a two allele problem and since the diffusion equation cannot be numerically solved, the only other way Ne can be incorporated into the analysis is by simulation. We have achieved good accuracy in all cases considered. In summary, the present work extends the realism and tractability of an important model of evolutionary biology and population genetics. Copyright © 2016 Elsevier Ltd. All rights reserved.

PyBioMed: a python library for various molecular representations of chemicals, proteins and DNAs and their interactions.

PubMed

Dong, Jie; Yao, Zhi-Jiang; Zhang, Lin; Luo, Feijun; Lin, Qinlu; Lu, Ai-Ping; Chen, Alex F; Cao, Dong-Sheng

2018-03-20

With the increasing development of biotechnology and informatics technology, publicly available data in chemistry and biology are undergoing explosive growth. Such wealthy information in these data needs to be extracted and transformed to useful knowledge by various data mining methods. Considering the amazing rate at which data are accumulated in chemistry and biology fields, new tools that process and interpret large and complex interaction data are increasingly important. So far, there are no suitable toolkits that can effectively link the chemical and biological space in view of molecular representation. To further explore these complex data, an integrated toolkit for various molecular representation is urgently needed which could be easily integrated with data mining algorithms to start a full data analysis pipeline. Herein, the python library PyBioMed is presented, which comprises functionalities for online download for various molecular objects by providing different IDs, the pretreatment of molecular structures, the computation of various molecular descriptors for chemicals, proteins, DNAs and their interactions. PyBioMed is a feature-rich and highly customized python library used for the characterization of various complex chemical and biological molecules and interaction samples. The current version of PyBioMed could calculate 775 chemical descriptors and 19 kinds of chemical fingerprints, 9920 protein descriptors based on protein sequences, more than 6000 DNA descriptors from nucleotide sequences, and interaction descriptors from pairwise samples using three different combining strategies. Several examples and five real-life applications were provided to clearly guide the users how to use PyBioMed as an integral part of data analysis projects. By using PyBioMed, users are able to start a full pipelining from getting molecular data, pretreating molecules, molecular representation to constructing machine learning models conveniently. PyBioMed provides various user-friendly and highly customized APIs to calculate various features of biological molecules and complex interaction samples conveniently, which aims at building integrated analysis pipelines from data acquisition, data checking, and descriptor calculation to modeling. PyBioMed is freely available at http://projects.scbdd.com/pybiomed.html .

Implementing Genome-Driven Oncology

PubMed Central

Hyman, David M.; Taylor, Barry S.; Baselga, José

2017-01-01

Early successes in identifying and targeting individual oncogenic drivers, together with the increasing feasibility of sequencing tumor genomes, have brought forth the promise of genome-driven oncology care. As we expand the breadth and depth of genomic analyses, the biological and clinical complexity of its implementation will be unparalleled. Challenges include target credentialing and validation, implementing drug combinations, clinical trial designs, targeting tumor heterogeneity, and deploying technologies beyond DNA sequencing, among others. We review how contemporary approaches are tackling these challenges and will ultimately serve as an engine for biological discovery and increase our insight into cancer and its treatment. PMID:28187282

Editorial overview: Omics

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

Barran, Perdita; Baker, Erin

The great complexity of biological systems and their environment poses similarly vast challenges for accurate analytical evaluations of their identity, structure and quantity. Post genomic science, has predicted much regarding the static populations of biological systems, but a further challenge for analysis is to test the accuracy of these predictions, as well as provide a better representation of the transient nature of the molecules of life. Accurate measurements of biological systems have wide applications for biological, forensic, biotechnological and healthcare fields. Therefore, the holy grail is to find a technique which can identify and quantify biological molecules with high throughput,more » sensitivity and robustness, as well evaluate molecular structure(s) in order to understand how the specific molecules interact and function. While wrapping all of these characteristics into one platform may sound difficult, ion mobility spectrometry (IMS) is addressing all of these challenges. Over the last decade, the number of analytical studies utilizing IMS for the evaluation of complex biological and environmental samples has greatly increased. In most cases IMS is coupled with mass spectrometry (IM-MS), but even alone IMS provides the unique capability of rapidly assessing a molecule’s structure, which can be extremely difficult with other techniques. The robustness of the IMS measurement is bourne out by its widespread use in security, environmental and military applications. The multidimensional IM-MS measurements however have been proven to be ever more powerful, as applied to complex mixtures as they enable the evaluation of both the structure and mass of every molecular component in a sample during a single measurement, without the need for continual reference calibration.« less

SeqCompress: an algorithm for biological sequence compression.

PubMed

Sardaraz, Muhammad; Tahir, Muhammad; Ikram, Ataul Aziz; Bajwa, Hassan

2014-10-01

The growth of Next Generation Sequencing technologies presents significant research challenges, specifically to design bioinformatics tools that handle massive amount of data efficiently. Biological sequence data storage cost has become a noticeable proportion of total cost in the generation and analysis. Particularly increase in DNA sequencing rate is significantly outstripping the rate of increase in disk storage capacity, which may go beyond the limit of storage capacity. It is essential to develop algorithms that handle large data sets via better memory management. This article presents a DNA sequence compression algorithm SeqCompress that copes with the space complexity of biological sequences. The algorithm is based on lossless data compression and uses statistical model as well as arithmetic coding to compress DNA sequences. The proposed algorithm is compared with recent specialized compression tools for biological sequences. Experimental results show that proposed algorithm has better compression gain as compared to other existing algorithms. Copyright © 2014 Elsevier Inc. All rights reserved.

Mercury reduction and complexation by natural organic matter in anoxic environments.

PubMed

Gu, Baohua; Bian, Yongrong; Miller, Carrie L; Dong, Wenming; Jiang, Xin; Liang, Liyuan

2011-01-25

Mercuric Hg(II) species form complexes with natural dissolved organic matter (DOM) such as humic acid (HA), and this binding is known to affect the chemical and biological transformation and cycling of mercury in aquatic environments. Dissolved elemental mercury, Hg(0), is also widely observed in sediments and water. However, reactions between Hg(0) and DOM have rarely been studied in anoxic environments. Here, under anoxic dark conditions we show strong interactions between reduced HA and Hg(0) through thiolate ligand-induced oxidative complexation with an estimated binding capacity of ~3.5 μmol Hg/g HA and a partitioning coefficient >10(6) mL/g. We further demonstrate that Hg(II) can be effectively reduced to Hg(0) in the presence of as little as 0.2 mg/L reduced HA, whereas production of Hg(0) is inhibited by complexation as HA concentration increases. This dual role played by DOM in the reduction and complexation of mercury is likely widespread in anoxic sediments and water and can be expected to significantly influence the mercury species transformations and biological uptake that leads to the formation of toxic methylmercury.

Evidence for a hyperglycaemia-dependent decrease of antithrombin III-thrombin complex formation in humans.

PubMed

Ceriello, A; Giugliano, D; Quatraro, A; Marchi, E; Barbanti, M; Lefèbvre, P

1990-03-01

In the presence of increased levels of fibrinopeptide A, decreased antithrombin III biological activity, and thrombin-antithrombin III complex levels are seen in diabetic patients. Induced-hyperglycaemia in diabetic and normal subjects decreased antithrombin III activity and thrombin-antithrombin III levels, and increased fibrinopeptide A plasma levels, while antithrombin III concentration did not change; heparin was shown to reduced these phenomena. In diabetic patients, euglycaemia induced by insulin infusion restored antithrombin III activity, thrombin-antithrombin III complex and fibrinopeptide A concentrations; heparin administration had the same effects. These data stress the role of a hyperglycaemia-dependent decrease of antithrombin III activity in precipitating thrombin hyperactivity in diabetes mellitus.

Biological consequences of nanoscale energy deposition near irradiated heavy atom nanoparticles

PubMed Central

McMahon, Stephen J.; Hyland, Wendy B.; Muir, Mark F.; Coulter, Jonathan A.; Jain, Suneil; Butterworth, Karl T.; Schettino, Giuseppe; Dickson, Glenn R.; Hounsell, Alan R.; O'Sullivan, Joe M.; Prise, Kevin M.; Hirst, David G.; Currell, Fred J.

2011-01-01

Gold nanoparticles (GNPs) are being proposed as contrast agents to enhance X-ray imaging and radiotherapy, seeking to take advantage of the increased X-ray absorption of gold compared to soft tissue. However, there is a great discrepancy between physically predicted increases in X-ray energy deposition and experimentally observed increases in cell killing. In this work, we present the first calculations which take into account the structure of energy deposition in the nanoscale vicinity of GNPs and relate this to biological outcomes, and show for the first time good agreement with experimentally observed cell killing by the combination of X-rays and GNPs. These results are not only relevant to radiotherapy, but also have implications for applications of heavy atom nanoparticles in biological settings or where human exposure is possible because the localised energy deposition high-lighted by these results may cause complex DNA damage, leading to mutation and carcinogenesis. PMID:22355537

Physical and biological mechanisms of nanosecond- and microsecond-pulsed FE-DBD plasma interaction with biological objects

NASA Astrophysics Data System (ADS)

Dobrynin, Danil

2013-09-01

Mechanisms of plasma interaction with living tissues and cells can be quite complex, owing to the complexity of both the plasma and the tissue. Thus, unification of all the mechanisms under one umbrella might not be possible. Here, analysis of interaction of floating electrode dielectric barrier discharge (FE-DBD) with living tissues and cells is presented and biological and physical mechanisms are discussed. In physical mechanisms, charged species are identified as the major contributors to the desired effect and a mechanism of this interaction is proposed. Biological mechanisms are also addressed and a hypothesis of plasma selectivity and its effects is offered. Spatially uniform nanosecond and sub-nanosecond short-pulsed dielectric barrier discharge plasmas are gaining popularity in biological and medical applications due to their increased uniformity, lower plasma temperature, lower surface power density, and higher concentration of the active species produced. In this presentation we will compare microsecond pulsed plasmas with nanosecond driven systems and their applications in biology and medicine with specific focus on wound healing and tissue regeneration. Transition from negative to positive streamer will be discussed with proposed hypothesis of uniformity mechanisms of positive streamer and the reduced dependence on morphology and surface chemistry of the second electrode (human body) being treated. Uniform plasma offers a more uniform delivery of active species to the tissue/surface being treated thus leading to better control over the biological results.

The dynamical analysis of modified two-compartment neuron model and FPGA implementation

NASA Astrophysics Data System (ADS)

Lin, Qianjin; Wang, Jiang; Yang, Shuangming; Yi, Guosheng; Deng, Bin; Wei, Xile; Yu, Haitao

2017-10-01

The complexity of neural models is increasing with the investigation of larger biological neural network, more various ionic channels and more detailed morphologies, and the implementation of biological neural network is a task with huge computational complexity and power consumption. This paper presents an efficient digital design using piecewise linearization on field programmable gate array (FPGA), to succinctly implement the reduced two-compartment model which retains essential features of more complicated models. The design proposes an approximate neuron model which is composed of a set of piecewise linear equations, and it can reproduce different dynamical behaviors to depict the mechanisms of a single neuron model. The consistency of hardware implementation is verified in terms of dynamical behaviors and bifurcation analysis, and the simulation results including varied ion channel characteristics coincide with the biological neuron model with a high accuracy. Hardware synthesis on FPGA demonstrates that the proposed model has reliable performance and lower hardware resource compared with the original two-compartment model. These investigations are conducive to scalability of biological neural network in reconfigurable large-scale neuromorphic system.

End-Directedness and Context in Nonliving Dissipative Systems

NASA Astrophysics Data System (ADS)

Dixon, James A.; Kay, Bruce A.; Davis, Tehran J.; Kondepudi, Dilip

Biological organisms are distinguished from non-living systems, in part, by their ability to choose and strive towards particular ends. This end-directed behavior is seen across all five biological kingdoms, from single-celled organisms to the most advanced primates. The ubiquitous nature of end-directedness, across such a wide variety of biological entities, suggests that a deeper principle may be at work. We propose that end-directedness, rather than being a special ability of living systems, is actually a fundamental property of a larger class of physical systems, called dissipative structures, which are formed and maintained by the flow of energy and matter. Our work shows that dissipative structures "behave so as to persist", seeking states that increase their rate of entropy production, and thus facilitate their own persistence. In addition, we suggest that biological entities create their exquisite sensitivity to context by interweaving this fundamental end-directedness with the contextual and physical constraints of their environments. The result is a repertoire of complex behavior. We provide an example of such complex behavior emerging from contextual and physical constraints coupled with end-directedness.

Climate change and occupational allergies: an overview on biological pollution, exposure and prevention.

PubMed

D'Ovidio, Maria Concetta; Annesi-Maesano, Isabella; D'Amato, Gennaro; Cecchi, Lorenzo

2016-01-01

Climate change, air pollution, temperature increase and other environmental variables are modifying air quality, contributing to the increase of prevalence of allergic respiratory diseases. Allergies are complex diseases characterized by multilevel interactions between individual susceptibility, response to immune modulation and environmental exposures to physical, chemical and biological agents. Occupational allergies introduce a further complexity to these relationships by adding occupational exposure to both the indoor and outdoor ones in the living environment. The aim of this paper is to overview climate-related allergy affecting environmental and occupational health, as literature data are scanty in this regard, and to suggest a management model of this risk based on a multidisciplinary approach, taking the case of biological pollution, with details on exposure and prevention. The management of climate-related occupational allergy should take into account preventive health strategies, environmental, public and occupational interventions, as well as to develop, implement, evaluate, and improve guidelines and standards protecting workers health under changing climatic conditions; new tools and strategies based on local conditions will have to be developed. Experimental studies and acquisition of environmental and personal data have to be matched to derive useful information for the scope of occupational health and safety.

Using HexSim to simulate complex species, landscape, and stressor interactions

EPA Science Inventory

Background / Question / Methods The use of simulation models in conservation biology, landscape ecology, and other disciplines is increasing. Models are essential tools for researchers who, for example, need to forecast future conditions, weigh competing recovery and mitigation...

Different design of enzyme-triggered CO-releasing molecules (ET-CORMs) reveals quantitative differences in biological activities in terms of toxicity and inflammation.

PubMed

Stamellou, E; Storz, D; Botov, S; Ntasis, E; Wedel, J; Sollazzo, S; Krämer, B K; van Son, W; Seelen, M; Schmalz, H G; Schmidt, A; Hafner, M; Yard, B A

2014-01-01

Acyloxydiene-Fe(CO)3 complexes can act as enzyme-triggered CO-releasing molecules (ET-CORMs). Their biological activity strongly depends on the mother compound from which they are derived, i.e. cyclohexenone or cyclohexanedione, and on the position of the ester functionality they harbour. The present study addresses if the latter characteristic affects CO release, if cytotoxicity of ET-CORMs is mediated through iron release or inhibition of cell respiration and to what extent cyclohexenone and cyclohexanedione derived ET-CORMs differ in their ability to counteract TNF-α mediated inflammation. Irrespective of the formulation (DMSO or cyclodextrin), toxicity in HUVEC was significantly higher for ET-CORMs bearing the ester functionality at the outer (rac-4), as compared to the inner (rac-1) position of the cyclohexenone moiety. This was paralleled by an increased CO release from the former ET-CORM. Toxicity was not mediated via iron as EC50 values for rac-4 were significantly lower than for FeCl2 or FeCl3 and were not influenced by iron chelation. ATP depletion preceded toxicity suggesting impaired cell respiration as putative cause for cell death. In long-term HUVEC cultures inhibition of VCAM-1 expression by rac-1 waned in time, while for the cyclohexanedione derived rac-8 inhibition seems to increase. NFκB was inhibited by both rac-1 and rac-8 independent of IκBα degradation. Both ET-CORMs activated Nrf-2 and consequently induced the expression of HO-1. This study further provides a rational framework for designing acyloxydiene-Fe(CO)3 complexes as ET-CORMs with differential CO release and biological activities. We also provide a better understanding of how these complexes affect cell-biology in mechanistic terms.

When physics is not "just physics": complexity science invites new measurement frames for exploring the physics of cognitive and biological development.

PubMed

Kelty-Stephen, Damian; Dixon, James A

2012-01-01

The neurobiological sciences have struggled to resolve the physical foundations for biological and cognitive phenomena with a suspicion that biological and cognitive systems, capable of exhibiting and contributing to structure within themselves and through their contexts, are fundamentally distinct or autonomous from purely physical systems. Complexity science offers new physics-based approaches to explaining biological and cognitive phenomena. In response to controversy over whether complexity science might seek to "explain away" biology and cognition as "just physics," we propose that complexity science serves as an application of recent advances in physics to phenomena in biology and cognition without reducing or undermining the integrity of the phenomena to be explained. We highlight that physics is, like the neurobiological sciences, an evolving field and that the threat of reduction is overstated. We propose that distinctions between biological and cognitive systems from physical systems are pretheoretical and thus optional. We review our own work applying insights from post-classical physics regarding turbulence and fractal fluctuations to the problems of developing cognitive structure. Far from hoping to reduce biology and cognition to "nothing but" physics, we present our view that complexity science offers new explanatory frameworks for considering physical foundations of biological and cognitive phenomena.

Multilayer network modeling of integrated biological systems. Comment on "Network science of biological systems at different scales: A review" by Gosak et al.

NASA Astrophysics Data System (ADS)

De Domenico, Manlio

2018-03-01

Biological systems, from a cell to the human brain, are inherently complex. A powerful representation of such systems, described by an intricate web of relationships across multiple scales, is provided by complex networks. Recently, several studies are highlighting how simple networks - obtained by aggregating or neglecting temporal or categorical description of biological data - are not able to account for the richness of information characterizing biological systems. More complex models, namely multilayer networks, are needed to account for interdependencies, often varying across time, of biological interacting units within a cell, a tissue or parts of an organism.

Functional complexity and ecosystem stability: an experimental approach

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

Van Voris, P.; O'Neill, R.V.; Shugart, H.H.

1978-01-01

The complexity-stability hypothesis was experimentally tested using intact terrestrial microcosms. Functional complexity was defined as the number and significance of component interactions (i.e., population interactions, physical-chemical reactions, biological turnover rates) influenced by nonlinearities, feedbacks, and time delays. It was postulated that functional complexity could be nondestructively measured through analysis of a signal generated from the system. Power spectral analysis of hourly CO/sub 2/ efflux, from eleven old-field microcosms, was analyzed for the number of low frequency peaks and used to rank the functional complexity of each system. Ranking of ecosystem stability was based on the capacity of the system tomore » retain essential nutrients and was measured by net loss of Ca after the system was stressed. Rank correlation supported the hypothesis that increasing ecosystem functional complexity leads to increasing ecosystem stability. The results indicated that complex functional dynamics can serve to stabilize the system. The results also demonstrated that microcosms are useful tools for system-level investigations.« less

Logic-Based Models for the Analysis of Cell Signaling Networks†

PubMed Central

2010-01-01

Computational models are increasingly used to analyze the operation of complex biochemical networks, including those involved in cell signaling networks. Here we review recent advances in applying logic-based modeling to mammalian cell biology. Logic-based models represent biomolecular networks in a simple and intuitive manner without describing the detailed biochemistry of each interaction. A brief description of several logic-based modeling methods is followed by six case studies that demonstrate biological questions recently addressed using logic-based models and point to potential advances in model formalisms and training procedures that promise to enhance the utility of logic-based methods for studying the relationship between environmental inputs and phenotypic or signaling state outputs of complex signaling networks. PMID:20225868

Online Interactive Teaching Modules Enhance Quantitative Proficiency of Introductory Biology Students

PubMed Central

Nelson, Kären C.; Marbach-Ad, Gili; Keller, Michael; Fagan, William F.

2010-01-01

There is widespread agreement within the scientific and education communities that undergraduate biology curricula fall short in providing students with the quantitative and interdisciplinary problem-solving skills they need to obtain a deep understanding of biological phenomena and be prepared fully to contribute to future scientific inquiry. MathBench Biology Modules were designed to address these needs through a series of interactive, Web-based modules that can be used to supplement existing course content across the biological sciences curriculum. The effect of the modules was assessed in an introductory biology course at the University of Maryland. Over the course of the semester, students showed significant increases in quantitative skills that were independent of previous math course work. Students also showed increased comfort with solving quantitative problems, whether or not they ultimately arrived at the correct answer. A survey of spring 2009 graduates indicated that those who had experienced MathBench in their course work had a greater appreciation for the role of mathematics in modern biology than those who had not used MathBench. MathBench modules allow students from diverse educational backgrounds to hone their quantitative skills, preparing them for more complex mathematical approaches in upper-division courses. PMID:20810959

Online interactive teaching modules enhance quantitative proficiency of introductory biology students.

PubMed

Thompson, Katerina V; Nelson, Kären C; Marbach-Ad, Gili; Keller, Michael; Fagan, William F

2010-01-01

There is widespread agreement within the scientific and education communities that undergraduate biology curricula fall short in providing students with the quantitative and interdisciplinary problem-solving skills they need to obtain a deep understanding of biological phenomena and be prepared fully to contribute to future scientific inquiry. MathBench Biology Modules were designed to address these needs through a series of interactive, Web-based modules that can be used to supplement existing course content across the biological sciences curriculum. The effect of the modules was assessed in an introductory biology course at the University of Maryland. Over the course of the semester, students showed significant increases in quantitative skills that were independent of previous math course work. Students also showed increased comfort with solving quantitative problems, whether or not they ultimately arrived at the correct answer. A survey of spring 2009 graduates indicated that those who had experienced MathBench in their course work had a greater appreciation for the role of mathematics in modern biology than those who had not used MathBench. MathBench modules allow students from diverse educational backgrounds to hone their quantitative skills, preparing them for more complex mathematical approaches in upper-division courses.

Biologically-Inspired Concepts for Self-Management of Complexity

NASA Technical Reports Server (NTRS)

Sterritt, Roy; Hinchey, G.

2006-01-01

Inherent complexity in large-scale applications may be impossible to eliminate or even ameliorate despite a number of promising advances. In such cases, the complexity must be tolerated and managed. Such management may be beyond the abilities of humans, or require such overhead as to make management by humans unrealistic. A number of initiatives inspired by concepts in biology have arisen for self-management of complex systems. We present some ideas and techniques we have been experimenting with, inspired by lesser-known concepts in biology that show promise in protecting complex systems and represent a step towards self-management of complexity.

Proteomics and Systems Biology: Current and Future Applications in the Nutritional Sciences1

PubMed Central

Moore, J. Bernadette; Weeks, Mark E.

2011-01-01

In the last decade, advances in genomics, proteomics, and metabolomics have yielded large-scale datasets that have driven an interest in global analyses, with the objective of understanding biological systems as a whole. Systems biology integrates computational modeling and experimental biology to predict and characterize the dynamic properties of biological systems, which are viewed as complex signaling networks. Whereas the systems analysis of disease-perturbed networks holds promise for identification of drug targets for therapy, equally the identified critical network nodes may be targeted through nutritional intervention in either a preventative or therapeutic fashion. As such, in the context of the nutritional sciences, it is envisioned that systems analysis of normal and nutrient-perturbed signaling networks in combination with knowledge of underlying genetic polymorphisms will lead to a future in which the health of individuals will be improved through predictive and preventative nutrition. Although high-throughput transcriptomic microarray data were initially most readily available and amenable to systems analysis, recent technological and methodological advances in MS have contributed to a linear increase in proteomic investigations. It is now commonplace for combined proteomic technologies to generate complex, multi-faceted datasets, and these will be the keystone of future systems biology research. This review will define systems biology, outline current proteomic methodologies, highlight successful applications of proteomics in nutrition research, and discuss the challenges for future applications of systems biology approaches in the nutritional sciences. PMID:22332076

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

PubMed Central

2013-01-01

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

The Importance of Normalization on Large and Heterogeneous Microarray Datasets

EPA Science Inventory

DNA microarray technology is a powerful functional genomics tool increasingly used for investigating global gene expression in environmental studies. Microarrays can also be used in identifying biological networks, as they give insight on the complex gene-to-gene interactions, ne...

The biological effect of asbestos exposure is dependent on ...

EPA Pesticide Factsheets

Abstract Functional groups on the surface of fibrous silicates can complex iron. We tested the postulate that 1) asbestos complexes and sequesters host cell iron resulting in a disruption of metal homeostasis and 2) this loss of essential metal results in an oxidative stress and biological effect in respiratory epithelial cells. Exposure of BEAS-2B cells to 50 μg/mL chrysotile resulted in diminished concentrations of mitochondrial iron. Pre-incubation of these cells with 200 μM ferric ammonium citrate (FAC) prevented significant mitochondrial iron loss following the same exposure. The host response to chrysotile included increased expression of the importer divalent metal transporter-1 (DMT1) supporting a functional iron deficiency. Incubation of BEAS-2B cells with both 200 μM FAC and 50 μg/mL chrysotile was associated with a greater cell accumulation of iron relative to either iron or chrysotile alone reflecting increased import to correct metal deficiency immediately following fiber exposure. Cellular oxidant generation was elevated after chrysotile exposure and this signal was diminished by co-incubation with 200 μM FAC. Similarly, exposure of BEAS-2B cells to 50 µg/mL chrysotile was associated with release of the pro-inflammatory mediators interleukin (IL)-6 and IL-8 and these changes were diminished by co-incubation with 200 μM FAC. We conclude that 1) the biological response following exposure to chrysotile is associated with complexation an

Capillary zone electrophoresis for analysis of phytochelatins and other thiol peptides in complex biological samples derivatized with monobromobimane.

PubMed

Perez-Rama, Mónica; Torres Vaamonde, Enrique; Abalde Alonso, Julio

2005-02-01

A new method to improve the analysis of phytochelatins and their precursors (cysteine, gamma-Glu-Cys, and glutathione) derivatized with monobromobimane (mBrB) in complex biological samples by capillary zone electrophoresis is described. The effects of the background electrolyte pH, concentration, and different organic additives (acetonitrile, methanol, and trifluoroethanol) on the separation were studied to achieve optimum resolution and number of theoretical plates of the analyzed compounds in the electropherograms. Optimum separation of the thiol peptides was obtained with 150 mM phosphate buffer at pH 1.60. Separation efficiency was improved when 2.5% v/v methanol was added to the background electrolyte. The electrophoretic conditions were 13 kV and capillary dimensions with 30 cm length from the inlet to the detector (38 cm total length) and 50 microm inner diameter. The injection was by pressure at 50 mbar for 17 s. Under these conditions, the separation between desglycyl-peptides and phytochelatins was also achieved. We also describe the optimum conditions for the derivatization of biological samples with mBrB to increase electrophoretic sensitivity and number of theoretical plates. The improved method was shown to be simple, reproducible, selective, and accurate in measuring thiol peptides in complex biological samples, the detection limit being 2.5 microM glutathione at a wavelength of 390 nm.

Pydna: a simulation and documentation tool for DNA assembly strategies using python.

PubMed

Pereira, Filipa; Azevedo, Flávio; Carvalho, Ângela; Ribeiro, Gabriela F; Budde, Mark W; Johansson, Björn

2015-05-02

Recent advances in synthetic biology have provided tools to efficiently construct complex DNA molecules which are an important part of many molecular biology and biotechnology projects. The planning of such constructs has traditionally been done manually using a DNA sequence editor which becomes error-prone as scale and complexity of the construction increase. A human-readable formal description of cloning and assembly strategies, which also allows for automatic computer simulation and verification, would therefore be a valuable tool. We have developed pydna, an extensible, free and open source Python library for simulating basic molecular biology DNA unit operations such as restriction digestion, ligation, PCR, primer design, Gibson assembly and homologous recombination. A cloning strategy expressed as a pydna script provides a description that is complete, unambiguous and stable. Execution of the script automatically yields the sequence of the final molecule(s) and that of any intermediate constructs. Pydna has been designed to be understandable for biologists with limited programming skills by providing interfaces that are semantically similar to the description of molecular biology unit operations found in literature. Pydna simplifies both the planning and sharing of cloning strategies and is especially useful for complex or combinatorial DNA molecule construction. An important difference compared to existing tools with similar goals is the use of Python instead of a specifically constructed language, providing a simulation environment that is more flexible and extensible by the user.

Application of Nanoparticle Technology to Reduce the Anti-Microbial Resistance through β-Lactam Antibiotic-Polymer Inclusion Nano-Complex.

PubMed

Salamanca, Constain H; Yarce, Cristhian J; Roman, Yony; Davalos, Andrés F; Rivera, Gustavo R

2018-02-10

Biocompatible polymeric materials with potential to form functional structures in association with different therapeutic molecules have a high potential for biological, medical and pharmaceutical applications. Therefore, the capability of the inclusion of nano-Complex formed between the sodium salt of poly(maleic acid- alt -octadecene) and a β-lactam drug (ampicillin trihydrate) to avoid the chemical and enzymatic degradation and enhance the biological activity were evaluated. PAM-18Na was produced and characterized, as reported previously. The formation of polymeric hydrophobic aggregates in aqueous solution was determined, using pyrene as a fluorescent probe. Furthermore, the formation of polymer-drug nano-complexes was characterized by Differential Scanning Calorimetry-DSC, viscometric, ultrafiltration/centrifugation assays, zeta potential and size measurements were determined by dynamic light scattering-DLS. The PAM-18Na capacity to avoid the chemical degradation was studied through stress stability tests. The enzymatic degradation was evaluated from a pure β-lactamase, while the biological degradation was determined by different β-lactamase producing Staphylococcus aureus strains. When ampicillin was associated with PAM-18Na, the half-life time in acidic conditions increased, whereas both the enzymatic degradation and the minimum inhibitory concentration decreased to a 90 and 75%, respectively. These results suggest a promissory capability of this polymer to protect the β-lactam drugs against chemical, enzymatic and biological degradation.

Application of Nanoparticle Technology to Reduce the Anti-Microbial Resistance through β-Lactam Antibiotic-Polymer Inclusion Nano-Complex

PubMed Central

Yarce, Cristhian J.; Roman, Yony; Davalos, Andrés F.; Rivera, Gustavo R.

2018-01-01

Biocompatible polymeric materials with potential to form functional structures in association with different therapeutic molecules have a high potential for biological, medical and pharmaceutical applications. Therefore, the capability of the inclusion of nano-Complex formed between the sodium salt of poly(maleic acid-alt-octadecene) and a β-lactam drug (ampicillin trihydrate) to avoid the chemical and enzymatic degradation and enhance the biological activity were evaluated. PAM-18Na was produced and characterized, as reported previously. The formation of polymeric hydrophobic aggregates in aqueous solution was determined, using pyrene as a fluorescent probe. Furthermore, the formation of polymer-drug nano-complexes was characterized by Differential Scanning Calorimetry-DSC, viscometric, ultrafiltration/centrifugation assays, zeta potential and size measurements were determined by dynamic light scattering-DLS. The PAM-18Na capacity to avoid the chemical degradation was studied through stress stability tests. The enzymatic degradation was evaluated from a pure β-lactamase, while the biological degradation was determined by different β-lactamase producing Staphylococcus aureus strains. When ampicillin was associated with PAM-18Na, the half-life time in acidic conditions increased, whereas both the enzymatic degradation and the minimum inhibitory concentration decreased to a 90 and 75%, respectively. These results suggest a promissory capability of this polymer to protect the β-lactam drugs against chemical, enzymatic and biological degradation. PMID:29439391

Model annotation for synthetic biology: automating model to nucleotide sequence conversion

PubMed Central

Misirli, Goksel; Hallinan, Jennifer S.; Yu, Tommy; Lawson, James R.; Wimalaratne, Sarala M.; Cooling, Michael T.; Wipat, Anil

2011-01-01

Motivation: The need for the automated computational design of genetic circuits is becoming increasingly apparent with the advent of ever more complex and ambitious synthetic biology projects. Currently, most circuits are designed through the assembly of models of individual parts such as promoters, ribosome binding sites and coding sequences. These low level models are combined to produce a dynamic model of a larger device that exhibits a desired behaviour. The larger model then acts as a blueprint for physical implementation at the DNA level. However, the conversion of models of complex genetic circuits into DNA sequences is a non-trivial undertaking due to the complexity of mapping the model parts to their physical manifestation. Automating this process is further hampered by the lack of computationally tractable information in most models. Results: We describe a method for automatically generating DNA sequences from dynamic models implemented in CellML and Systems Biology Markup Language (SBML). We also identify the metadata needed to annotate models to facilitate automated conversion, and propose and demonstrate a method for the markup of these models using RDF. Our algorithm has been implemented in a software tool called MoSeC. Availability: The software is available from the authors' web site http://research.ncl.ac.uk/synthetic_biology/downloads.html. Contact: anil.wipat@ncl.ac.uk Supplementary information: Supplementary data are available at Bioinformatics online. PMID:21296753

Fighting Cancer with Mathematics and Viruses.

PubMed

Santiago, Daniel N; Heidbuechel, Johannes P W; Kandell, Wendy M; Walker, Rachel; Djeu, Julie; Engeland, Christine E; Abate-Daga, Daniel; Enderling, Heiko

2017-08-23

After decades of research, oncolytic virotherapy has recently advanced to clinical application, and currently a multitude of novel agents and combination treatments are being evaluated for cancer therapy. Oncolytic agents preferentially replicate in tumor cells, inducing tumor cell lysis and complex antitumor effects, such as innate and adaptive immune responses and the destruction of tumor vasculature. With the availability of different vector platforms and the potential of both genetic engineering and combination regimens to enhance particular aspects of safety and efficacy, the identification of optimal treatments for patient subpopulations or even individual patients becomes a top priority. Mathematical modeling can provide support in this arena by making use of experimental and clinical data to generate hypotheses about the mechanisms underlying complex biology and, ultimately, predict optimal treatment protocols. Increasingly complex models can be applied to account for therapeutically relevant parameters such as components of the immune system. In this review, we describe current developments in oncolytic virotherapy and mathematical modeling to discuss the benefit of integrating different modeling approaches into biological and clinical experimentation. Conclusively, we propose a mutual combination of these research fields to increase the value of the preclinical development and the therapeutic efficacy of the resulting treatments.

Visualizing protein interactions and dynamics: evolving a visual language for molecular animation.

PubMed

Jenkinson, Jodie; McGill, Gaël

2012-01-01

Undergraduate biology education provides students with a number of learning challenges. Subject areas that are particularly difficult to understand include protein conformational change and stability, diffusion and random molecular motion, and molecular crowding. In this study, we examined the relative effectiveness of three-dimensional visualization techniques for learning about protein conformation and molecular motion in association with a ligand-receptor binding event. Increasingly complex versions of the same binding event were depicted in each of four animated treatments. Students (n = 131) were recruited from the undergraduate biology program at University of Toronto, Mississauga. Visualization media were developed in the Center for Molecular and Cellular Dynamics at Harvard Medical School. Stem cell factor ligand and cKit receptor tyrosine kinase were used as a classical example of a ligand-induced receptor dimerization and activation event. Each group completed a pretest, viewed one of four variants of the animation, and completed a posttest and, at 2 wk following the assessment, a delayed posttest. Overall, the most complex animation was the most effective at fostering students' understanding of the events depicted. These results suggest that, in select learning contexts, increasingly complex representations may be more desirable for conveying the dynamic nature of cell binding events.

Fighting Cancer with Mathematics and Viruses

PubMed Central

Santiago, Daniel N.; Heidbuechel, Johannes P. W.; Kandell, Wendy M.; Walker, Rachel; Djeu, Julie; Abate-Daga, Daniel; Enderling, Heiko

2017-01-01

After decades of research, oncolytic virotherapy has recently advanced to clinical application, and currently a multitude of novel agents and combination treatments are being evaluated for cancer therapy. Oncolytic agents preferentially replicate in tumor cells, inducing tumor cell lysis and complex antitumor effects, such as innate and adaptive immune responses and the destruction of tumor vasculature. With the availability of different vector platforms and the potential of both genetic engineering and combination regimens to enhance particular aspects of safety and efficacy, the identification of optimal treatments for patient subpopulations or even individual patients becomes a top priority. Mathematical modeling can provide support in this arena by making use of experimental and clinical data to generate hypotheses about the mechanisms underlying complex biology and, ultimately, predict optimal treatment protocols. Increasingly complex models can be applied to account for therapeutically relevant parameters such as components of the immune system. In this review, we describe current developments in oncolytic virotherapy and mathematical modeling to discuss the benefit of integrating different modeling approaches into biological and clinical experimentation. Conclusively, we propose a mutual combination of these research fields to increase the value of the preclinical development and the therapeutic efficacy of the resulting treatments. PMID:28832539

Direct determination and speciation of mercury compounds in environmental and biological samples by carbon bed atomic absorption spectroscopy

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

Skelly, E.M.

A method was developed for the direct determination of mercury in water and biological samples using a unique carbon bed atomizer for atomic absorption spectroscopy. The method avoided sources of error such as loss of volatile mercury during sample digestion and contamination of samples through added reagents by eliminating sample pretreatment steps. The design of the atomizer allowed use of the 184.9 nm mercury resonance line in the vacuum ultraviolet region, which increased sensitivity over the commonly used spin-forbidden 253.7 nm line. The carbon bed atomizer method was applied to a study of mercury concentrations in water, hair, sweat, urine,more » blood, breath and saliva samples from a non-occupationally exposed population. Data were collected on the average concentration, the range and distribution of mercury in the samples. Data were also collected illustrating individual variations in mercury concentrations with time. Concentrations of mercury found were significantly higher than values reported in the literature for a ''normal'' population. This is attributed to the increased accuracy gained by eliminating pretreatment steps and increasing atomization efficiency. Absorption traces were obtained for various solutions of pure and complexed mercury compounds. Absorption traces of biological fluids were also obtained. Differences were observed in the absorption-temperatures traces of various compounds. The utility of this technique for studying complexation was demonstrated.« less

The fusion of biology, computer science, and engineering: towards efficient and successful synthetic biology.

PubMed

Linshiz, Gregory; Goldberg, Alex; Konry, Tania; Hillson, Nathan J

2012-01-01

Synthetic biology is a nascent field that emerged in earnest only around the turn of the millennium. It aims to engineer new biological systems and impart new biological functionality, often through genetic modifications. The design and construction of new biological systems is a complex, multistep process, requiring multidisciplinary collaborative efforts from "fusion" scientists who have formal training in computer science or engineering, as well as hands-on biological expertise. The public has high expectations for synthetic biology and eagerly anticipates the development of solutions to the major challenges facing humanity. This article discusses laboratory practices and the conduct of research in synthetic biology. It argues that the fusion science approach, which integrates biology with computer science and engineering best practices, including standardization, process optimization, computer-aided design and laboratory automation, miniaturization, and systematic management, will increase the predictability and reproducibility of experiments and lead to breakthroughs in the construction of new biological systems. The article also discusses several successful fusion projects, including the development of software tools for DNA construction design automation, recursive DNA construction, and the development of integrated microfluidics systems.

Red alder-conifer stands in Alaska: An example of mixed species management to enhance structural and biological complexity

Treesearch

Robert Deal; Ewa Orlikowska; David D’Amore; Paul Hennon

2017-01-01

There is worldwide interest in managing forests to improve biodiversity, enhance ecosystem services and assure long-term sustainability of forest resources. An increasingly important goal of forest management is to increase stand diversity and improve wildlife and aquatic habitat. Well-planned silvicultural systems containing a mixture of broadleaf-conifer species have...

DNA damage and repair after high LET radiation

NASA Astrophysics Data System (ADS)

O'Neill, Peter; Cucinotta, Francis; Anderson, Jennifer

Predictions from biophysical models of interactions of radiation tracks with cellular DNA indicate that clustered DNA damage sites, defined as two or more lesions formed within one or two helical turns of the DNA by passage of a single radiation track, are formed in mammalian cells. These complex DNA damage sites are regarded as a signature of ionizing radiation exposure particularly as the likelihood of clustered damage sites arising endogenously is low. For instance, it was predicted from biophysical modelling that 30-40% of low LET-induced double strand breaks (DSB), a form of clustered damage, are complex with the yield increasing to >90% for high LET radiation, consistent with the reduced reparability of DSB with increasing ionization density of the radiation. The question arises whether the increased biological effects such as mutagenesis, carcinogenesis and lethality is in part related to DNA damage complexity and/or spatial distribution of the damage sites, which may lead to small DNA fragments. With particle radiation it is also important to consider not only delta-rays which may cause clustered damaged sites and may be highly mutagenic but the non-random spatial distribution of DSB which may lead to deletions. In this overview I will concentrate on the molecular aspects of the variation of the complexity of DNA damage on radiation quality and the challenges this complexity presents the DNA damage repair pathways. I will draw on data from micro-irradiations which indicate that the repair of DSBs by non-homologous end joining is highly regulated with pathway choice and kinetics of repair dependent on the chemical complexity of the DSB. In summary the aim is to emphasis the link between the spatial distribution of energy deposition events related to the track, the molecular products formed and the consequence of damage complexity contributing to biological effects and to present some of the outstanding molecular challenges with particle radiation.

Quantitative biological surface science: challenges and recent advances.

PubMed

Höök, Fredrik; Kasemo, Bengt; Grunze, Michael; Zauscher, Stefan

2008-12-23

Biological surface science is a broad, interdisciplinary subfield of surface science, where properties and processes at biological and synthetic surfaces and interfaces are investigated, and where biofunctional surfaces are fabricated. The need to study and to understand biological surfaces and interfaces in liquid environments provides sizable challenges as well as fascinating opportunities. Here, we report on recent progress in biological surface science that was described within the program assembled by the Biomaterial Interface Division of the Science and Technology of Materials, Interfaces and Processes (www.avs.org) during their 55th International Symposium and Exhibition held in Boston, October 19-24, 2008. The selected examples show that the rapid progress in nanoscience and nanotechnology, hand-in-hand with theory and simulation, provides increasingly sophisticated methods and tools to unravel the mechanisms and details of complex processes at biological surfaces and in-depth understanding of biomolecular surface interactions.

CHEMICAL CONTAMINATION AND TOXICITY ASSOCIATED WITH A COASTAL GOLF COURSE COMPLEX

EPA Science Inventory

The increasing density of golf courses represents a potential source of contamination to nearby coastal areas, the chemical and biological magnitude of which is almost unknown. The objective of this study was to compare the concentrations of contaminants and toxicities of sedime...

SEDIMENT CHEMICAL CONTAMINATION AND TOXICITY ASSOCIATED WITH A COASTAL GOLF COURSE COMPLEX.

EPA Science Inventory

The increasing density of golf courses represents a potential source of sediment contamination to nearby coastal areas, the chemical and biological magnitude of which is almost unknown. The objective of this study was to determine the concentrations of contaminants and toxicities...

Designer cell signal processing circuits for biotechnology

PubMed Central

Bradley, Robert W.; Wang, Baojun

2015-01-01

Microorganisms are able to respond effectively to diverse signals from their environment and internal metabolism owing to their inherent sophisticated information processing capacity. A central aim of synthetic biology is to control and reprogramme the signal processing pathways within living cells so as to realise repurposed, beneficial applications ranging from disease diagnosis and environmental sensing to chemical bioproduction. To date most examples of synthetic biological signal processing have been built based on digital information flow, though analogue computing is being developed to cope with more complex operations and larger sets of variables. Great progress has been made in expanding the categories of characterised biological components that can be used for cellular signal manipulation, thereby allowing synthetic biologists to more rationally programme increasingly complex behaviours into living cells. Here we present a current overview of the components and strategies that exist for designer cell signal processing and decision making, discuss how these have been implemented in prototype systems for therapeutic, environmental, and industrial biotechnological applications, and examine emerging challenges in this promising field. PMID:25579192

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

Medyantseva, E.P.; Budnikov, G.K.; Balakaeva, T.A.

The interest in the analytical chemistry of ruthenium and its compounds has recently been increasing. Ruthenium compounds can be used an antitumor agents and in the treatment of tuberculosis and fungal infections. It has been suggested that there is a specific relationship between the reduction potentials of the compounds and their biological activity. Of greatest interest among the biologically active compounds are the compounds with nitrogen-containing heterocycles. In order to obtain information on the degree of oxidation of the central atom in the complexes and to select the optimum conditions for the determination of the mono- and bi-nuclear complexes ofmore » ruthenium compounds with biologically active ligands such as imidazole (Im), histidine (His), benzimidazole (BIm) and its methyl derivative [1,2(CH{sub 3}){sub 2} - BIm], benzohyroxamic acid (Bha), and 1-phenyl-2-methylamino-1-propanol or ephedrine (Eph) in the present work, the authors studied their electrochemical behavior at dropping mercury (dme) and a platinum electrodes. 6 refs., 1 fig., 2 tabs.« less

KRAS Mouse Models

PubMed Central

O’Hagan, Rónán C.; Heyer, Joerg

2011-01-01

KRAS is a potent oncogene and is mutated in about 30% of all human cancers. However, the biological context of KRAS-dependent oncogenesis is poorly understood. Genetically engineered mouse models of cancer provide invaluable tools to study the oncogenic process, and insights from KRAS-driven models have significantly increased our understanding of the genetic, cellular, and tissue contexts in which KRAS is competent for oncogenesis. Moreover, variation among tumors arising in mouse models can provide insight into the mechanisms underlying response or resistance to therapy in KRAS-dependent cancers. Hence, it is essential that models of KRAS-driven cancers accurately reflect the genetics of human tumors and recapitulate the complex tumor-stromal intercommunication that is manifest in human cancers. Here, we highlight the progress made in modeling KRAS-dependent cancers and the impact that these models have had on our understanding of cancer biology. In particular, the development of models that recapitulate the complex biology of human cancers enables translational insights into mechanisms of therapeutic intervention in KRAS-dependent cancers. PMID:21779503

Mercury reduction and complexation by natural organic matter in anoxic environments

PubMed Central

Gu, Baohua; Bian, Yongrong; Miller, Carrie L.; Dong, Wenming; Jiang, Xin; Liang, Liyuan

2011-01-01

Mercuric Hg(II) species form complexes with natural dissolved organic matter (DOM) such as humic acid (HA), and this binding is known to affect the chemical and biological transformation and cycling of mercury in aquatic environments. Dissolved elemental mercury, Hg(0), is also widely observed in sediments and water. However, reactions between Hg(0) and DOM have rarely been studied in anoxic environments. Here, under anoxic dark conditions we show strong interactions between reduced HA and Hg(0) through thiolate ligand-induced oxidative complexation with an estimated binding capacity of ~3.5 μmol Hg/g HA and a partitioning coefficient >106 mL/g. We further demonstrate that Hg(II) can be effectively reduced to Hg(0) in the presence of as little as 0.2 mg/L reduced HA, whereas production of Hg(0) is inhibited by complexation as HA concentration increases. This dual role played by DOM in the reduction and complexation of mercury is likely widespread in anoxic sediments and water and can be expected to significantly influence the mercury species transformations and biological uptake that leads to the formation of toxic methylmercury. PMID:21220311

Synthesis, characterization and toxicity studies of pyridinecarboxaldehydes and L-tryptophan derived Schiff bases and corresponding copper (II) complexes.

PubMed

Malakyan, Margarita; Babayan, Nelly; Grigoryan, Ruzanna; Sarkisyan, Natalya; Tonoyan, Vahan; Tadevosyan, Davit; Matosyan, Vladimir; Aroutiounian, Rouben; Arakelyan, Arsen

2016-01-01

Schiff bases and their metal-complexes are versatile compounds exhibiting a broad range of biological activities and thus actively used in the drug development process. The aim of the present study was the synthesis and characterization of new Schiff bases and their copper (II) complexes, derived from L-tryptophan and isomeric (2-; 3-; 4-) pyridinecarboxaldehydes, as well as the assessment of their toxicity in vitro . The optimal conditions of the Schiff base synthesis resulting in up to 75-85% yield of target products were identified. The structure-activity relationship analysis indicated that the location of the carboxaldehyde group at 2-, 3- or 4-position with regard to nitrogen of the pyridine ring in aldehyde component of the L-tryptophan derivative Schiff bases and corresponding copper complexes essentially change the biological activity of the compounds. The carboxaldehyde group at 2- and 4-positions leads to the higher cytotoxic activity, than that of at 3-position, and the presence of the copper in the complexes increases the cytotoxicity. Based on toxicity classification data, the compounds with non-toxic profile were identified, which can be used as new entities in the drug development process using Schiff base scaffold.

Synthesis, characterization and biological evaluation of a novel "3 + 1" mixed ligand 99mTc complex having an aliphatic thiol as coligand.

PubMed

Rey, A; Papadopoulos, M; Leon, E; Mallo, L; Pirmettis, Y; Manta, E; Raptopoulou, C; Chiotellis, E; Leon, A

2001-03-01

A novel "3 + 1" mixed ligand 99mTc complex with N,N-bis(2-mercaptoethyl)-N'N'-diethyl-ethilenediamine as ligand and 1-octanethiol as coligand was prepared and evaluated as potential brain radiopharmaceutical. Preparation at tracer level was accomplished by substitution, using 99mTc-glucoheptonate as precursor and a coligand/ligand ratio of 5. Under these conditions the labeling yield was over 80% and a major product with radiochemical purity >80% was isolated by HPLC methods and used for biological evaluation. Chemical characterization at carrier level was developed using the corresponding rhenium and 99gTc complexes. Results were consistent with the expected "3 + 1" structure and X-ray diffraction study demonstrated that the complex adopted a distorted trigonal bipyramidal geometry. All sulphur atoms underwent ionization leading to the formation of a neutral compound. Biodistribution in mice demonstrated early brain uptake, fast blood clearance and excretion through hepatobiliary system. Although brain/blood ratio increased significantly with time, this novel 99mTc complex did not exhibit ideal properties as brain perfusion radiopharmaceutical since brain uptake was too low.

Synthesis, characterization and toxicity studies of pyridinecarboxaldehydes and L-tryptophan derived Schiff bases and corresponding copper (II) complexes

PubMed Central

Malakyan, Margarita; Babayan, Nelly; Grigoryan, Ruzanna; Sarkisyan, Natalya; Tonoyan, Vahan; Tadevosyan, Davit; Matosyan, Vladimir; Aroutiounian, Rouben; Arakelyan, Arsen

2016-01-01

Schiff bases and their metal-complexes are versatile compounds exhibiting a broad range of biological activities and thus actively used in the drug development process. The aim of the present study was the synthesis and characterization of new Schiff bases and their copper (II) complexes, derived from L-tryptophan and isomeric (2-; 3-; 4-) pyridinecarboxaldehydes, as well as the assessment of their toxicity in vitro. The optimal conditions of the Schiff base synthesis resulting in up to 75-85% yield of target products were identified. The structure-activity relationship analysis indicated that the location of the carboxaldehyde group at 2-, 3- or 4-position with regard to nitrogen of the pyridine ring in aldehyde component of the L-tryptophan derivative Schiff bases and corresponding copper complexes essentially change the biological activity of the compounds. The carboxaldehyde group at 2- and 4-positions leads to the higher cytotoxic activity, than that of at 3-position, and the presence of the copper in the complexes increases the cytotoxicity. Based on toxicity classification data, the compounds with non-toxic profile were identified, which can be used as new entities in the drug development process using Schiff base scaffold. PMID:28344771

E-Index for Differentiating Complex Dynamic Traits

PubMed Central

Qi, Jiandong; Sun, Jianfeng; Wang, Jianxin

2016-01-01

While it is a daunting challenge in current biology to understand how the underlying network of genes regulates complex dynamic traits, functional mapping, a tool for mapping quantitative trait loci (QTLs) and single nucleotide polymorphisms (SNPs), has been applied in a variety of cases to tackle this challenge. Though useful and powerful, functional mapping performs well only when one or more model parameters are clearly responsible for the developmental trajectory, typically being a logistic curve. Moreover, it does not work when the curves are more complex than that, especially when they are not monotonic. To overcome this inadaptability, we therefore propose a mathematical-biological concept and measurement, E-index (earliness-index), which cumulatively measures the earliness degree to which a variable (or a dynamic trait) increases or decreases its value. Theoretical proofs and simulation studies show that E-index is more general than functional mapping and can be applied to any complex dynamic traits, including those with logistic curves and those with nonmonotonic curves. Meanwhile, E-index vector is proposed as well to capture more subtle differences of developmental patterns. PMID:27064292

Improved delivery through biological membranes. XXXL: Solubilization and stabilization of an estradiol chemical delivery system by modified beta-cyclodextrins.

PubMed

Brewster, M E; Estes, K S; Loftsson, T; Perchalski, R; Derendorf, H; Mullersman, G; Bodor, N

1988-11-01

A dihydropyridine in equilibrium pyridinium salt chemical delivery system (CDS) for estradiol (E2CDS) was complexed with various modified beta-cyclodextrins including hydroxyethyl-beta-cyclodextrin (HECD), hydroxypropyl-beta-cyclodextrin (HPCD), and heptakis(2,6-di-O-methyl)-beta-cyclodextrin (DMCD). Complex formation with all of these cyclodextrins resulted in dramatic increases in the water solubility of E2CDS. Studies on the complex of E2CDS and HPCD (E2CDS-CD) indicated that the encapsulated estrogen was approximately four times more stable than the unmanipulated CDS, producing an estimated half-life of degradation of 4 years compared with 1.2 years for the uncomplexed drug at room temperature. The complexation of E2CDS and HPCD also stabilized the dihydronicotinate in solutions containing potassium ferricyanide. This formulation was shown to be equivalent to E2CDS in dimethyl sulfoxide in delivering the oxidized, estradiol precursor (E2Q+) to the brain, and also produced similar biological responses; these included decreased luteinizing hormone (LH) secretion and a decrease in the rate of weight gain in castrated female rats.

[New materia medica project: synthetic biology based bioactive metabolites research in medicinal plant].

PubMed

Wang, Yong

2017-03-25

In the last decade, synthetic biology research has been gradually transited from monocellular parts or devices toward more complex multicellular systems. The emerging plant synthetic biology is regarded as the "next chapter" of synthetic biology. The complex and diverse plant metabolism as the entry point, plant synthetic biology research not only helps us understand how real life is working, but also facilitates us to learn how to design and construct more complex artificial life. Bioactive compounds innovation and large-scale production are expected to be breakthrough with the redesigned plant metabolism as well. In this review, we discuss the research progress in plant synthetic biology and propose the new materia medica project to lift the level of traditional Chinese herbal medicine research.

Growing trend of CE at the omics level: the frontier of systems biology.

PubMed

Oh, Eulsik; Hasan, Md Nabiul; Jamshed, Muhammad; Park, Soo Hyun; Hong, Hye-Min; Song, Eun Joo; Yoo, Young Sook

2010-01-01

In a novel attempt to comprehend the complexity of life, systems biology has recently emerged as a state-of-the-art approach for biological research in contrast to the reductionist approaches that have been used in molecular cell biology since the 1950s. Because a massive amount of information is required in many systems biology studies of life processes, we have increasingly come to depend on techniques that provide high-throughput omics data. CE and CE coupled to MS have served as powerful analytical tools for providing qualitative and quantitative omics data. Recent systems biology studies have focused strongly on the diagnosis and treatment of diseases. The increasing number of clinical research papers on drug discovery and disease therapies reflects this growing interest among scientists. Since such clinical research reflects one of the ultimate purposes of bioscience, these trends will be sustained for a long time. Thus, this review mainly focuses on the application of CE and CE-MS in diagnosis as well as on the latest CE methods developed. Furthermore, we outline the new challenges that arose in 2008 and later in elucidating the system-level functions of the bioconstituents of living organisms.

Endogenous synchronous fluorescence spectroscopy (SFS) of basal cell carcinoma-initial study

NASA Astrophysics Data System (ADS)

Borisova, E.; Zhelyazkova, Al.; Keremedchiev, M.; Penkov, N.; Semyachkina-Glushkovskaya, O.; Avramov, L.

2016-01-01

The human skin is a complex, multilayered and inhomogeneous organ with spatially varying optical properties. Analysis of cutaneous fluorescence spectra could be a very complicated task; therefore researchers apply complex mathematical tools for data evaluation, or try to find some specific approaches, that would simplify the spectral analysis. Synchronous fluorescence spectroscopy (SFS) allows improving the spectral resolution, which could be useful for the biological tissue fluorescence characterization and could increase the tumour detection diagnostic accuracy.

SWI/SNF Chromatin-remodeling Factors: Multiscale Analyses and Diverse Functions*

PubMed Central

Euskirchen, Ghia; Auerbach, Raymond K.; Snyder, Michael

2012-01-01

Chromatin-remodeling enzymes play essential roles in many biological processes, including gene expression, DNA replication and repair, and cell division. Although one such complex, SWI/SNF, has been extensively studied, new discoveries are still being made. Here, we review SWI/SNF biochemistry; highlight recent genomic and proteomic advances; and address the role of SWI/SNF in human diseases, including cancer and viral infections. These studies have greatly increased our understanding of complex nuclear processes. PMID:22952240

Reasoning from non-stationarity

NASA Astrophysics Data System (ADS)

Struzik, Zbigniew R.; van Wijngaarden, Willem J.; Castelo, Robert

2002-11-01

Complex real-world (biological) systems often exhibit intrinsically non-stationary behaviour of their temporal characteristics. We discuss local measures of scaling which can capture and reveal changes in a system's behaviour. Such measures offer increased insight into a system's behaviour and are superior to global, spectral characteristics like the multifractal spectrum. They are, however, often inadequate for fully understanding and modelling the phenomenon. We illustrate an attempt to capture complex model characteristics by analysing (multiple order) correlations in a high dimensional space of parameters of the (biological) system being studied. Both temporal information, among others local scaling information, and external descriptors/parameters, possibly influencing the system's state, are used to span the search space investigated for the presence of a (sub-)optimal model. As an example, we use fetal heartbeat monitored during labour.

Engineering of routes to heparin and related polysaccharides.

PubMed

Bhaskar, Ujjwal; Sterner, Eric; Hickey, Anne Marie; Onishi, Akihiro; Zhang, Fuming; Dordick, Jonathan S; Linhardt, Robert J

2012-01-01

Anticoagulant heparin has been shown to possess important biological functions that vary according to its fine structure. Variability within heparin's structure occurs owing to its biosynthesis and animal tissue-based recovery and adds another dimension to its complex polymeric structure. The structural variations in chain length and sulfation patterns mediate its interaction with many heparin-binding proteins, thereby eliciting complex biological responses. The advent of novel chemical and enzymatic approaches for polysaccharide synthesis coupled with high throughput combinatorial approaches for drug discovery have facilitated an increased effort to understand heparin's structure-activity relationships. An improved understanding would offer potential for new therapeutic development through the engineering of polysaccharides. Such a bioengineering approach requires the amalgamation of several different disciplines, including carbohydrate synthesis, applied enzymology, metabolic engineering, and process biochemistry.

What does systems biology mean for drug development?

PubMed

Schrattenholz, André; Soskić, Vukić

2008-01-01

The complexity and flexibility of cellular architectures is increasingly recognized by impressive progress on the side of molecular analytics, i.e. proteomics, genomics and metabolomics. One of the messages from systems biology is that the number of molecular species in cellular networks is orders of magnitude bigger than anticipated by genomic analysis, in particular by fast posttranslational modifications of proteins. The requirements to manage external signals, integrate spatiotemporal signal transduction inside an organism and at the same time optimizing networks of biochemical and chemical reactions result in chemically extremely fine tuned molecular entities. Chemical side reactions of enzymatic activity, like e.g. random oxidative damage of proteins by free radicals during aging constantly introduce epigenetic alterations of protein targets. These events gradually and on an individual stochastic scale, keep modifying activities of these targets, and their affinities and selectivities towards biological and pharmacological ligands. One further message is that many of the key reactions in living systems are essentially based on interactions of low affinities and even low selectivities. This principle is responsible for the enormous flexibility and redundancy of cellular circuitries. So, in complex disorders like cancer or neurodegenerative diseases, which are rooted in relatively subtle and multimodal dysfunction of important physiologic pathways, drug discovery programs based on the concept of high affinity/high specificity compounds ("one-target, one-disease"), which still dominate the pharmaceutical industry increasingly turn out to be unsuccessful. Despite improvements in rational drug design and high throughput screening methods, the number of novel, single-target drugs fell much behind expectations during the past decade and the treatment of "complex diseases" remains a most pressing medical need. Currently a change of paradigm can be observed with regard to a new focus on agents that modulate multiple targets simultaneously. Targeting cellular function as a system rather than on the level of the single protein molecule significantly increases the size of the drugable proteome and is expected to introduce novel classes of multi-target drugs with fewer adverse effects and toxicity. Multiple target approaches have recently been used to design medications against atherosclerosis, cancer, depression, psychosis and neurodegenerative diseases. A focussed approach towards "systemic" drugs will certainly require the development of novel computational and mathematical concepts for appropriate modelling of complex data and extraction of "screenable" information from biological systems essentially ruled by deterministic chaotic processes on a background of individual stochasticity.

Deciphering deterioration mechanisms of complex diseases based on the construction of dynamic networks and systems analysis

NASA Astrophysics Data System (ADS)

Li, Yuanyuan; Jin, Suoqin; Lei, Lei; Pan, Zishu; Zou, Xiufen

2015-03-01

The early diagnosis and investigation of the pathogenic mechanisms of complex diseases are the most challenging problems in the fields of biology and medicine. Network-based systems biology is an important technique for the study of complex diseases. The present study constructed dynamic protein-protein interaction (PPI) networks to identify dynamical network biomarkers (DNBs) and analyze the underlying mechanisms of complex diseases from a systems level. We developed a model-based framework for the construction of a series of time-sequenced networks by integrating high-throughput gene expression data into PPI data. By combining the dynamic networks and molecular modules, we identified significant DNBs for four complex diseases, including influenza caused by either H3N2 or H1N1, acute lung injury and type 2 diabetes mellitus, which can serve as warning signals for disease deterioration. Function and pathway analyses revealed that the identified DNBs were significantly enriched during key events in early disease development. Correlation and information flow analyses revealed that DNBs effectively discriminated between different disease processes and that dysfunctional regulation and disproportional information flow may contribute to the increased disease severity. This study provides a general paradigm for revealing the deterioration mechanisms of complex diseases and offers new insights into their early diagnoses.

Motivating Tomorrow's Biologists

ERIC Educational Resources Information Center

Musante, Susan

2012-01-01

The story of biology is far more complex and fascinating than straightforward facts or neatly labeled diagrams of structures and systems. Although exams can motivate students, the key to using these extrinsic motivators to increase student understanding lies in the way the assessments are designed and what they measure. Those involved in…

Luminescent Rhenium(I) and Iridium(III) Polypyridine Complexes as Biological Probes, Imaging Reagents, and Photocytotoxic Agents.

PubMed

Lo, Kenneth Kam-Wing

2015-12-15

Although the interactions of transition metal complexes with biological molecules have been extensively studied, the use of luminescent transition metal complexes as intracellular sensors and bioimaging reagents has not been a focus of research until recently. The main advantages of luminescent transition metal complexes are their high photostability, long-lived phosphorescence that allows time-resolved detection, and large Stokes shifts that can minimize the possible self-quenching effect. Also, by the use of transition metal complexes, the degree of cellular uptake can be readily determined using inductively coupled plasma mass spectrometry. For more than a decade, we have been interested in the development of luminescent transition metal complexes as covalent labels and noncovalent probes for biological molecules. We argue that many transition metal polypyridine complexes display triplet charge transfer ((3)CT) emission that is highly sensitive to the local environment of the complexes. Hence, the biological labeling and binding interactions can be readily reflected by changes in the photophysical properties of the complexes. In this laboratory, we have modified luminescent tricarbonylrhenium(I) and bis-cyclometalated iridium(III) polypyridine complexes of general formula [Re(bpy-R(1))(CO)3(py-R(2))](+) and [Ir(ppy-R(3))2(bpy-R(4))](+), respectively, with reactive functional groups and used them to label the amine and sulfhydryl groups of biomolecules such as oligonucleotides, amino acids, peptides, and proteins. Additionally, using a range of biological substrates such as biotin, estradiol, and indole, we have designed luminescent rhenium(I) and iridium(III) polypyridine complexes as noncovalent probes for biological receptors. The interesting results generated from these studies have prompted us to investigate the possible applications of luminescent transition metal complexes in intracellular systems. Thus, in the past few years, we have developed an interest in the cytotoxic activity, cellular uptake, and bioimaging applications of these complexes. Additionally, we and other research groups have demonstrated that many transition metal complexes have facile cellular uptake and organelle-localization properties and that their cytotoxic activity can be readily controlled. For example, complexes that can target the nucleus, nucleolus, mitochondria, lysosomes, endoplasmic reticulum, and Golgi apparatus have been identified. We anticipate that this selective localization property can be utilized in the development of intracellular sensors and bioimaging reagents. Thus, we have functionalized luminescent rhenium(I) and iridium(III) polypyridine complexes with various pendants, including molecule-binding moieties, sugar molecules, bioorthogonal functional groups, and polymeric chains such as poly(ethylene glycol) and polyethylenimine, and examined their potentials as biological reagents. This Account describes our design of luminescent rhenium(I) and iridium(III) polypyridine complexes and explains how they can serve as a new generation of biological reagents for diagnostic and therapeutic applications.

Image processing for cryogenic transmission electron microscopy of symmetry-mismatched complexes.

PubMed

Huiskonen, Juha T

2018-02-08

Cryogenic transmission electron microscopy (cryo-TEM) is a high-resolution biological imaging method, whereby biological samples, such as purified proteins, macromolecular complexes, viral particles, organelles and cells, are embedded in vitreous ice preserving their native structures. Due to sensitivity of biological materials to the electron beam of the microscope, only relatively low electron doses can be applied during imaging. As a result, the signal arising from the structure of interest is overpowered by noise in the images. To increase the signal-to-noise ratio, different image processing-based strategies that aim at coherent averaging of signal have been devised. In such strategies, images are generally assumed to arise from multiple identical copies of the structure. Prior to averaging, the images must be grouped according to the view of the structure they represent and images representing the same view must be simultaneously aligned relatively to each other. For computational reconstruction of the three-dimensional structure, images must contain different views of the original structure. Structures with multiple symmetry-related substructures are advantageous in averaging approaches because each image provides multiple views of the substructures. However, the symmetry assumption may be valid for only parts of the structure, leading to incoherent averaging of the other parts. Several image processing approaches have been adapted to tackle symmetry-mismatched substructures with increasing success. Such structures are ubiquitous in nature and further computational method development is needed to understanding their biological functions. ©2018 The Author(s).

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

Siegel, S.

An increased level of mathematical sophistication will be needed in the future to be able to handle the spectrum of information as it comes from a broad array of biological systems and other sources. Classification will be an increasingly complex and difficult issue. Several projects that are discussed are being developed by the US Department of Health and Human Services (DHHS), including a directory of risk assessment projects and a directory of exposure information resources.

Characterising the development of the understanding of human body systems in high-school biology students - a longitudinal study

NASA Astrophysics Data System (ADS)

Snapir, Zohar; Eberbach, Catherine; Ben-Zvi-Assaraf, Orit; Hmelo-Silver, Cindy; Tripto, Jaklin

2017-10-01

Science education today has become increasingly focused on research into complex natural, social and technological systems. In this study, we examined the development of high-school biology students' systems understanding of the human body, in a three-year longitudinal study. The development of the students' system understanding was evaluated using the Components Mechanisms Phenomena (CMP) framework for conceptual representation. We coded and analysed the repertory grid personal constructs of 67 high-school biology students at 4 points throughout the study. Our data analysis builds on the assumption that systems understanding entails a perception of all the system categories, including structures within the system (its Components), specific processes and interactions at the macro and micro levels (Mechanisms), and the Phenomena that present the macro scale of processes and patterns within a system. Our findings suggest that as the learning process progressed, the systems understanding of our students became more advanced, moving forward within each of the major CMP categories. Moreover, there was an increase in the mechanism complexity presented by the students, manifested by more students describing mechanisms at the molecular level. Thus, the 'mechanism' category and the micro level are critical components that enable students to understand system-level phenomena such as homeostasis.

RNA and RNP as Building Blocks for Nanotechnology and Synthetic Biology.

PubMed

Ohno, Hirohisa; Saito, Hirohide

2016-01-01

Recent technologies that aimed to elucidate cellular function have revealed essential roles for RNA molecules in living systems. Our knowledge concerning functional and structural information of naturally occurring RNA and RNA-protein (RNP) complexes is increasing rapidly. RNA and RNP interaction motifs are structural units that function as building blocks to constitute variety of complex structures. RNA-central synthetic biology and nanotechnology are constructive approaches that employ the accumulated information and build synthetic RNA (RNP)-based circuits and nanostructures. Here, we describe how to design and construct synthetic RNA (RNP)-based devices and structures at the nanometer-scale for biological and future therapeutic applications. RNA/RNP nanostructures can also be utilized as the molecular scaffold to control the localization or interactions of target molecule(s). Moreover, RNA motifs recognized by RNA-binding proteins can be applied to make protein-responsive translational "switches" that can turn gene expression "on" or "off" depending on the intracellular environment. This "synthetic RNA and RNP world" will expand tools for nanotechnology and synthetic biology. In addition, these reconstructive approaches would lead to a greater understanding of building principle in naturally occurring RNA/RNP molecules and systems. Copyright © 2016 Elsevier Inc. All rights reserved.

Biocharts: a visual formalism for complex biological systems

PubMed Central

Kugler, Hillel; Larjo, Antti; Harel, David

2010-01-01

We address one of the central issues in devising languages, methods and tools for the modelling and analysis of complex biological systems, that of linking high-level (e.g. intercellular) information with lower-level (e.g. intracellular) information. Adequate ways of dealing with this issue are crucial for understanding biological networks and pathways, which typically contain huge amounts of data that continue to grow as our knowledge and understanding of a system increases. Trying to comprehend such data using the standard methods currently in use is often virtually impossible. We propose a two-tier compound visual language, which we call Biocharts, that is geared towards building fully executable models of biological systems. One of the main goals of our approach is to enable biologists to actively participate in the computational modelling effort, in a natural way. The high-level part of our language is a version of statecharts, which have been shown to be extremely successful in software and systems engineering. The statecharts can be combined with any appropriately well-defined language (preferably a diagrammatic one) for specifying the low-level dynamics of the pathways and networks. We illustrate the language and our general modelling approach using the well-studied process of bacterial chemotaxis. PMID:20022895

A Unifying Review of Bioassay-Guided Fractionation, Effect-Directed Analysis and Related Techniques

PubMed Central

Weller, Michael G.

2012-01-01

The success of modern methods in analytical chemistry sometimes obscures the problem that the ever increasing amount of analytical data does not necessarily give more insight of practical relevance. As alternative approaches, toxicity- and bioactivity-based assays can deliver valuable information about biological effects of complex materials in humans, other species or even ecosystems. However, the observed effects often cannot be clearly assigned to specific chemical compounds. In these cases, the establishment of an unambiguous cause-effect relationship is not possible. Effect-directed analysis tries to interconnect instrumental analytical techniques with a biological/biochemical entity, which identifies or isolates substances of biological relevance. Successful application has been demonstrated in many fields, either as proof-of-principle studies or even for complex samples. This review discusses the different approaches, advantages and limitations and finally shows some practical examples. The broad emergence of effect-directed analytical concepts might lead to a true paradigm shift in analytical chemistry, away from ever growing lists of chemical compounds. The connection of biological effects with the identification and quantification of molecular entities leads to relevant answers to many real life questions. PMID:23012539

A New Biology for the 21st Century; Ensuring the United States Leads the Coming Biology Revolution. Final committee report

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

None None

2012-05-10

In July, 2008, the National Institutes of Health (NIH), National Science Foundation (NSF), and Department of Energy (DOE) asked the National Research Council’s Board on Life Sciences to convene a committee to examine the current state of biological research in the United States and recommend how best to capitalize on recent technological and scientific advances that have allowed biologists to integrate biological research findings, collect and interpret vastly increased amounts of data, and predict the behavior of complex biological systems. From September 2008 through July of 2009, a committee of 16 experts from the fields of biology, engineering and computationalmore » science undertook to delineate those scientific and technological advances and come to a consensus on how the U.S. might best capitalize on them. This report, authored by the Committee on a New Biology for the 21st Century, describes the committee’s work and conclusions.« less

Recent opportunities for an increasing role for physical explanations in biology.

PubMed

Morange, Michel

2011-06-01

Relations between physics and biology have been always difficult. One reason is that physical approaches to the phenomena of life have frequently been conceived by their authors as alternatives to biological explanations. My argument is that molecular descriptions and explanations have been pushed so far that they have reached their limits: these limits constitute a favourable niche in which physical explanations can develop. I will focus on the field of molecular and cell biology and give many examples of these recent physical studies made possible by the precision of molecular observations. The nature of these niches is probably diverse. I consider that it is too early to have a global view of the interactions between biological and physical explanations, and to organize them into different categories. Such interactions are not new within the life sciences: the history of biology reveals a complex, permanently moving landscape of interactions between biological and physical explanations. Copyright © 2010 Elsevier Ltd. All rights reserved.

Fast and Accurate Circuit Design Automation through Hierarchical Model Switching.

PubMed

Huynh, Linh; Tagkopoulos, Ilias

2015-08-21

In computer-aided biological design, the trifecta of characterized part libraries, accurate models and optimal design parameters is crucial for producing reliable designs. As the number of parts and model complexity increase, however, it becomes exponentially more difficult for any optimization method to search the solution space, hence creating a trade-off that hampers efficient design. To address this issue, we present a hierarchical computer-aided design architecture that uses a two-step approach for biological design. First, a simple model of low computational complexity is used to predict circuit behavior and assess candidate circuit branches through branch-and-bound methods. Then, a complex, nonlinear circuit model is used for a fine-grained search of the reduced solution space, thus achieving more accurate results. Evaluation with a benchmark of 11 circuits and a library of 102 experimental designs with known characterization parameters demonstrates a speed-up of 3 orders of magnitude when compared to other design methods that provide optimality guarantees.

Antibody profiling sensitivity through increased reporter antibody layering

DOEpatents

Apel, William A.; Thompson, Vicki S.

2013-02-26

A method for analyzing a biological sample by antibody profiling for identifying forensic samples or for detecting the presence of an analyte. In an embodiment of the invention, the analyte is a drug, such as marijuana, Cocaine (crystalline tropane alkaloid), methamphetamine, methyltestosterone, or mesterolone. The method comprises attaching antigens to a surface of a solid support in a preselected pattern to form an array wherein locations of the antigens are known; contacting the array with the biological sample such that a portion of antibodies in the sample reacts with and binds to the antigens in the array to form immune complexes; washing away antibodies that do form immune complexes; and detecting the immune complexes, to form an antibody profile. Forensic samples are identified by comparing a sample from an unknown source with a sample from a known source. Further, an assay, such as a test for illegal drug use, can be coupled to a test for identity such that the results of the assay can be positively correlated to the subject's identity.

Antibody profiling sensitivity through increased reporter antibody layering

DOEpatents

Apel, William A.; Thompson, Vicki S.

2017-03-28

A method for analyzing a biological sample by antibody profiling for identifying forensic samples or for detecting the presence of an analyte. In an embodiment of the invention, the analyte is a drug, such as marijuana, Cocaine (crystalline tropane alkaloid), methamphetamine, methyltestosterone, or mesterolone. The method comprises attaching antigens to a surface of a solid support in a preselected pattern to form an array wherein locations of the antigens are known; contacting the array with the biological sample such that a portion of antibodies in the sample reacts with and binds to the antigens in the array to form immune complexes; washing away antibodies that do form immune complexes; and detecting the immune complexes, to form an antibody profile. Forensic samples are identified by comparing a sample from an unknown source with a sample from a known source. Further, an assay, such as a test for illegal drug use, can be coupled to a test for identity such that the results of the assay can be positively correlated to the subject's identity.

Atomic switch networks as complex adaptive systems

NASA Astrophysics Data System (ADS)

Scharnhorst, Kelsey S.; Carbajal, Juan P.; Aguilera, Renato C.; Sandouk, Eric J.; Aono, Masakazu; Stieg, Adam Z.; Gimzewski, James K.

2018-03-01

Complexity is an increasingly crucial aspect of societal, environmental and biological phenomena. Using a dense unorganized network of synthetic synapses it is shown that a complex adaptive system can be physically created on a microchip built especially for complex problems. These neuro-inspired atomic switch networks (ASNs) are a dynamic system with inherent and distributed memory, recurrent pathways, and up to a billion interacting elements. We demonstrate key parameters describing self-organized behavior such as non-linearity, power law dynamics, and multistate switching regimes. Device dynamics are then investigated using a feedback loop which provides control over current and voltage power-law behavior. Wide ranging prospective applications include understanding and eventually predicting future events that display complex emergent behavior in the critical regime.

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

PubMed

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

2008-02-08

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

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

PubMed Central

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

2008-01-01

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

Interacting complex systems: Theory and application to real-world situations

NASA Astrophysics Data System (ADS)

Piccinini, Nicola

The interest in complex systems has increased exponentially during the past years because it was found helpful in addressing many of today's challenges. The study of the brain, biology, earthquakes, markets and social sciences are only a few examples of the fields that have benefited from the investigation of complex systems. Internet, the increased mobility of people and the raising energy demand are among the factors that brought in contact complex systems that were isolated till a few years ago. A theory for the interaction between complex systems is becoming more and more urgent to help mankind in this transition. The present work builds upon the most recent results in this field by solving a theoretical problem that prevented previous work to be applied to important complex systems, like the brain. It also shows preliminary laboratory results of perturbation of in vitro neural networks that were done to test the theory. Finally, it gives a preview of the studies that are being done to create a theory that is even closer to the interaction between real complex systems.

Aortic Valve Stenosis Increases Helical Flow and Flow Complexity: A Study of Intra-Operative Cardiac Vector Flow Imaging.

PubMed

Hansen, Kristoffer Lindskov; Møller-Sørensen, Hasse; Kjaergaard, Jesper; Jensen, Maiken Brit; Jensen, Jørgen Arendt; Nielsen, Michael Bachmann

2017-08-01

Aortic valve stenosis alters blood flow in the ascending aorta. Using intra-operative vector flow imaging on the ascending aorta, secondary helical flow during peak systole and diastole, as well as flow complexity of primary flow during systole, were investigated in patients with normal, stenotic and replaced aortic valves. Peak systolic helical flow, diastolic helical flow and flow complexity during systole differed between the groups (p < 0.0001), and correlated to peak systolic velocity (R = 0.94, 0.87 and 0.88, respectively). The study indicates that aortic valve stenosis increases helical flow and flow complexity, which are measurable with vector flow imaging. For assessment of aortic stenosis and optimization of valve surgery, vector flow imaging may be useful. Copyright © 2017 World Federation for Ultrasound in Medicine & Biology. Published by Elsevier Inc. All rights reserved.

Light-activated protein inhibition through photoinduced electron transfer of a ruthenium(II)–cobalt(III) bimetallic complex

DOE PAGES

Holbrook, Robert J.; Weinberg, David J.; Peterson, Mark D.; ...

2015-02-11

In this paper, we describe a mechanism of light activation that initiates protein inhibitory action of a biologically inert Co(III) Schiff base (Co(III)-sb) complex. Photoinduced electron transfer (PET) occurs from a Ru(II) bipyridal complex to a covalently attached Co(III) complex and is gated by conformational changes that occur in tens of nanoseconds. Reduction of the Co(III)-sb by PET initiates displacement of the inert axial imidazole ligands, promoting coordination to active site histidines of α-thrombin. Upon exposure to 455 nm light, the rate of ligand exchange with 4-methylimidazole, a histidine mimic, increases by approximately 5-fold, as observed by NMR spectroscopy. Similarly,more » the rate of α-thrombin inhibition increases over 5-fold upon irradiation. Finally, these results convey a strategy for light activation of inorganic therapeutic agents through PET utilizing redox-active metal centers.« less

Antiproliferative and apoptosis-inducing activity of an oxidovanadium(IV) complex with the flavonoid silibinin against osteosarcoma cells.

PubMed

Leon, I E; Porro, V; Di Virgilio, A L; Naso, L G; Williams, P A M; Bollati-Fogolín, M; Etcheverry, S B

2014-01-01

Flavonoids are a large family of polyphenolic compounds synthesized by plants. They display interesting biological effects mainly related to their antioxidant properties. On the other hand, vanadium compounds also exhibit different biological and pharmacological effects in cell culture and in animal models. Since coordination of ligands to metals can improve or change the pharmacological properties, we report herein, for the first time, a detailed study of the mechanisms of action of an oxidovanadium(IV) complex with the flavonoid silibinin, Na2[VO(silibinin)2]·6H2O (VOsil), in a model of the human osteosarcoma derived cell line MG-63. The complex inhibited the viability of osteosarcoma cells in a dose-dependent manner with a greater potency than that of silibinin and oxidovanadium(IV) (p < 0.01), demonstrating the benefit of complexation. Cytotoxicity and genotoxicity studies also showed a concentration effect for VOsil. The increase in the levels of reactive oxygen species and the decrease of the ratio of the amount of reduced glutathione to the amount of oxidized glutathione were involved in the deleterious effects of the complex. Besides, the complex caused cell cycle arrest and activated caspase 3, triggering apoptosis as determined by flow cytometry. As a whole, these results show the main mechanisms of the deleterious effects of VOsil in the osteosarcoma cell line, demonstrating that this complex is a promising compound for cancer treatments.

Describing the complexity of systems: multivariable "set complexity" and the information basis of systems biology.

PubMed

Galas, David J; Sakhanenko, Nikita A; Skupin, Alexander; Ignac, Tomasz

2014-02-01

Context dependence is central to the description of complexity. Keying on the pairwise definition of "set complexity," we use an information theory approach to formulate general measures of systems complexity. We examine the properties of multivariable dependency starting with the concept of interaction information. We then present a new measure for unbiased detection of multivariable dependency, "differential interaction information." This quantity for two variables reduces to the pairwise "set complexity" previously proposed as a context-dependent measure of information in biological systems. We generalize it here to an arbitrary number of variables. Critical limiting properties of the "differential interaction information" are key to the generalization. This measure extends previous ideas about biological information and provides a more sophisticated basis for the study of complexity. The properties of "differential interaction information" also suggest new approaches to data analysis. Given a data set of system measurements, differential interaction information can provide a measure of collective dependence, which can be represented in hypergraphs describing complex system interaction patterns. We investigate this kind of analysis using simulated data sets. The conjoining of a generalized set complexity measure, multivariable dependency analysis, and hypergraphs is our central result. While our focus is on complex biological systems, our results are applicable to any complex system.

Gaseous VOCs rapidly modify particulate matter and its biological effects - Part 2: Complex urban VOCs and model PM

NASA Astrophysics Data System (ADS)

Ebersviller, S.; Lichtveld, K.; Sexton, K. G.; Zavala, J.; Lin, Y.-H.; Jaspers, I.; Jeffries, H. E.

2012-03-01

This is the second study in a three-part study designed to demonstrate dynamic entanglements among gaseous organic compounds (VOCs), particulate matter (PM), and their subsequent potential biological effects. We study these entanglements in increasingly complex VOC and PM mixtures in urban-like conditions in a large outdoor chamber, both in the dark and in sunlight. To the traditional chemical and physical characterizations of gas and PM, we added new measurements of gas-only- and PM-only-biological effects, using cultured human lung cells as model living receptors. These biological effects are assessed here as increases in cellular damage or expressed irritation (i.e., cellular toxic effects) from cells exposed to chamber air relative to cells exposed to clean air. Our exposure systems permit side-by-side, gas-only- and PM-only-exposures from the same air stream containing both gases and PM in equilibria, i.e., there are no extractive operations prior to cell exposure for either gases or PM. In Part 1 (Ebersviller et al., 2012a), we demonstrated the existence of PM "effect modification" (NAS, 2004) for the case of a single gas-phase toxicant and an inherently non-toxic PM (mineral oil aerosol, MOA). That is, in the presence of the single gas-phase toxicant in the dark, the initially non-toxic PM became toxic to lung cells in the PM-only-biological exposure system. In this Part 2 study, we used sunlit-reactive systems to create a large variety of gas-phase toxicants from a complex mixture of oxides of nitrogen and 54 VOCs representative of those measured in US city air. In these mostly day-long experiments, we have designated the period in the dark just after injection (but before sunrise) as the "Fresh" condition and the period in the dark after sunset as the "Aged" condition. These two conditions were used to expose cells and to collect chemical characterization samples. We used the same inherently non-toxic PM from the Part 1 study as the target PM for "effect modification". Fortunately, in the absence of "seed particles", the complex highly-reactive VOC system used does not create any secondary aerosol in situ. All PM present in these tests were, therefore, introduced by injection of MOA to serve as PM-to-be-modified by the gaseous environment. PM addition was only done during dark periods, either before or after the daylight period. The purpose of this design is to test if a non-toxic PM becomes toxic in initially unreacted ("Fresh"), or in reacted ("Aged") complex VOC conditions. To have a complete design, we also tested the effects of clean air and the same VOC conditions, but without introducing any PM. Thus, there were six exposure treatment conditions that were evaluated with the side-by-side, gas-only- and PM-only-effects exposure systems; five separate chamber experiments were performed: two with clean air and three with the complex VOC/NOx mixture. For all of these experiments and exposures, chemical composition data and matching biological effects results for two end-points were compared. Chemical measurements demonstrate the temporal evolution of oxidized species, with a corresponding increase in toxicity observed from exposed cells. The largest increase in gas-phase toxicity was observed in the two "Aged" VOC exposures. The largest increase in particle-phase toxicity was observed in the "Aged" VOC exposure with the addition of PM after sunset. These results are a clear demonstration that the findings from Part 1 can be extended to the complex urban oxidized environment. This further demonstrates that the atmosphere itself cannot be ignored as a source of toxic species when establishing the risks associated with exposure to PM. Because gases and PM are transported and deposited differently within the atmosphere and lungs, these results have significant consequences. In the next (and final) part of the study, testing is further applied to systems with real diesel exhaust, including primary PM from a vehicle operated with different types of diesel fuel.

Gaseous VOCs rapidly modify particulate matter and its biological effects - Part 2: Complex urban VOCs and model PM

NASA Astrophysics Data System (ADS)

Ebersviller, S.; Lichtveld, K.; Sexton, K. G.; Zavala, J.; Lin, Y.-H.; Jaspers, I.; Jeffries, H. E.

2012-12-01

This is the second study in a three-part study designed to demonstrate dynamic entanglements among gaseous organic compounds (VOCs), particulate matter (PM), and their subsequent potential biological effects. We study these entanglements in increasingly complex VOC and PM mixtures in urban-like conditions in a large outdoor chamber, both in the dark and in sunlight. To the traditional chemical and physical characterizations of gas and PM, we added new measurements of gas-only- and PM-only-biological effects, using cultured human lung cells as model living receptors. These biological effects are assessed here as increases in cellular damage or expressed irritation (i.e., cellular toxic effects) from cells exposed to chamber air relative to cells exposed to clean air. Our exposure systems permit side-by-side, gas-only- and PM-only-exposures from the same air stream containing both gases and PM in equilibria, i.e., there are no extractive operations prior to cell exposure for either gases or PM. In Part 1 (Ebersviller et al., 2012a), we demonstrated the existence of PM "effect modification" (NAS, 2004) for the case of a single gas-phase toxicant and an inherently non-toxic PM (mineral oil aerosol, MOA). That is, in the presence of the single gas-phase toxicant in the dark, the initially non-toxic PM became toxic to lung cells in the PM-only-biological exposure system. In this Part 2 study, we used sunlit-reactive systems to create a large variety of gas-phase toxicants from a complex mixture of oxides of nitrogen and 54 VOCs representative of those measured in US city air. In these mostly day-long experiments, we have designated the period in the dark just after injection (but before sunrise) as the "Fresh" condition and the period in the dark after sunset as the "Aged" condition. These two conditions were used to expose cells and to collect chemical characterization samples. We used the same inherently non-toxic PM from the Part 1 study as the target PM for "effect modification". Fortunately, in the absence of "seed particles", the complex highly-reactive VOC system used does not create any secondary aerosol in situ. All PM present in these tests were, therefore, introduced by injection of MOA to serve as PM-to-be-modified by the gaseous environment. PM addition was only done during dark periods, either before or after the daylight period. The purpose of this design is to test if a non-toxic PM becomes toxic in initially unreacted ("Fresh"), or in reacted ("Aged") complex VOC conditions. To have a complete design, we also tested the effects of clean air and the same VOC conditions, but without introducing any PM. Thus, there were six exposure treatment conditions that were evaluated with the side-by-side, gas-only- and PM-only-effects exposure systems; five separate chamber experiments were performed: two with clean air and three with the complex VOC/NOx mixture. For all of these experiments and exposures, chemical composition data and matching biological effects results for two end-points were compared. Chemical measurements demonstrate the temporal evolution of oxidized species, with a corresponding increase in toxicity observed from exposed cells. The largest increase in gas-phase toxicity was observed in the two "Aged" VOC exposures. The largest increase in particle-phase toxicity was observed in the "Aged" VOC exposure with the addition of PM after sunset. These results are a clear demonstration that the findings from Part 1 can be extended to the complex urban oxidized environment. This further demonstrates that the atmosphere itself cannot be ignored as a source of toxic species when establishing the risks associated with exposure to PM. Because gases and PM are transported and deposited differently within the atmosphere and lungs, these results have significant consequences. In the next (and final) part of the study, testing is further applied to systems with real diesel exhaust, including primary PM from a vehicle operated with different types of diesel fuel.

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

PubMed

Sukumaran, Jeet; Knowles, L Lacey

2018-06-01

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

Biology and genetic engineering of fruit maturation for enhanced quality and shelf-life.

PubMed

Matas, Antonio J; Gapper, Nigel E; Chung, Mi-Young; Giovannoni, James J; Rose, Jocelyn K C

2009-04-01

Commercial regulation of ripening is currently achieved through early harvest, by controlling the postharvest storage atmosphere and genetic selection for slow or late ripening varieties. Although these approaches are often effective, they are not universally applicable and often result in acceptable, but poor quality, products. With increased understanding of the molecular biology underlying ripening and the advent of genetic engineering technologies, researchers have pursued new strategies to address problems in fruit shelf-life and quality. These have been guided by recent insights into mechanisms by which ethylene and a complex network of transcription factors regulate ripening, and by an increased appreciation of factors that contribute to shelf-life, such as the fruit cuticle.

Tree physiology research in a changing world.

PubMed

Kaufmann, Merrill R.; Linder, Sune

1996-01-01

Changes in issues and advances in methodology have contributed to substantial progress in tree physiology research during the last several decades. Current research focuses on process interactions in complex systems and the integration of processes across multiple spatial and temporal scales. An increasingly important challenge for future research is assuring sustainability of production systems and forested ecosystems in the face of increased demands for natural resources and human disturbance of forests. Meeting this challenge requires significant shifts in research approach, including the study of limitations of productivity that may accompany achievement of system sustainability, and a focus on the biological capabilities of complex land bases altered by human activity.

A Biosocial Developmental Model of Borderline Personality: Elaborating and Extending Linehan's Theory

ERIC Educational Resources Information Center

Crowell, Sheila E.; Beauchaine, Theodore P.; Linehan, Marsha M.

2009-01-01

Over the past several decades, research has focused increasingly on developmental precursors to psychological disorders that were previously assumed to emerge only in adulthood. This change in focus follows from the recognition that complex transactions between biological vulnerabilities and psychosocial risk factors shape emotional and behavioral…

Affinity purification and mass spectrometry: an attractive choice to investigate protein-protein interactions in plant immunity

USDA-ARS?s Scientific Manuscript database

Affinity purification of protein complexes from biological tissues, followed by liquid chromatography- tandem mass spectrometry (AP-MS/MS), has ballooned in recent years due to sizeable increases in nucleic acid sequence data essential for interpreting mass spectra, improvements in affinity purifica...

Autism: A Review of Biological Bases, Assessment, and Intervention

ERIC Educational Resources Information Center

Volker, Martin A.; Lopata, Christopher

2008-01-01

The number of children classified with autism in US schools has risen sharply over the past decade. School psychologists are being called upon with increasing frequency to assist in the identification, assessment, and treatment of these children. The diagnostic complexities and heterogeneity of the disorder make dealing effectively with this…

Thermodynamical Arguments against Evolution

ERIC Educational Resources Information Center

Rosenhouse, Jason

2017-01-01

The argument that the second law of thermodynamics contradicts the theory of evolution has recently been revived by anti-evolutionists. In its basic form, the argument asserts that whereas evolution implies that there has been an increase in biological complexity over time, the second law, a fundamental principle of physics, shows this to be…

Ambient Air Pollution and Increases in Blood Pressure: Role for biological constituents of particulate matter

EPA Science Inventory

Particulate matter (PM) is a complex mixture of extremely small particles and liquid droplets made up of a number of components including elemental carbon, organic chemicals, metals, acids (such as nitrates and sulfates), and soil and dust particles. Epidemiological studies con...

Undergraduate Students' Development of Social, Cultural, and Human Capital in a Networked Research Experience

ERIC Educational Resources Information Center

Thompson, Jennifer Jo; Conaway, Evan; Dolan, Erin L.

2016-01-01

Recent calls for reform in undergraduate biology education have emphasized integrating research experiences into the learning experiences of all undergraduates. Contemporary science research increasingly demands collaboration across disciplines and institutions to investigate complex research questions, providing new contexts and models for…

Systems Biology Approaches to the Study of Biological Networks Underlying Alzheimer's Disease: Role of miRNAs.

PubMed

Roth, Wera; Hecker, David; Fava, Eugenio

2016-01-01

MicroRNAs (miRNAs) are emerging as significant regulators of mRNA complexity in the human central nervous system (CNS) thereby controlling distinct gene expression profiles in a spatio-temporal manner during development, neuronal plasticity, aging and (age-related) neurodegeneration, including Alzheimer's disease (AD). Increasing effort is expended towards dissecting and deciphering the molecular and genetic mechanisms of neurobiological and pathological functions of these brain-enriched miRNAs. Along these lines, recent data pinpoint distinct miRNAs and miRNA networks being linked to APP splicing, processing and Aβ pathology (Lukiw et al., Front Genet 3:327, 2013), and furthermore, to the regulation of tau and its cellular subnetworks (Lau et al., EMBO Mol Med 5:1613, 2013), altogether underlying the onset and propagation of Alzheimer's disease. MicroRNA profiling studies in Alzheimer's disease suffer from poor consensus which is an acknowledged concern in the field, and constitutes one of the current technical challenges. Hence, a strong demand for experimental and computational systems biology approaches arises, to incorporate and integrate distinct levels of information and scientific knowledge into a complex system of miRNA networks in the context of the transcriptome, proteome and metabolome in a given cellular environment. Here, we will discuss the state-of-the-art technologies and computational approaches on hand that may lead to a deeper understanding of the complex biological networks underlying the pathogenesis of Alzheimer's disease.

Complex Systems

PubMed Central

Goldberger, Ary L.

2006-01-01

Physiologic systems in health and disease display an extraordinary range of temporal behaviors and structural patterns that defy understanding based on linear constructs, reductionist strategies, and classical homeostasis. Application of concepts and computational tools derived from the contemporary study of complex systems, including nonlinear dynamics, fractals and “chaos theory,” is having an increasing impact on biology and medicine. This presentation provides a brief overview of an emerging area of biomedical research, including recent applications to cardiopulmonary medicine and chronic obstructive lung disease. PMID:16921107

Multiscale agent-based cancer modeling.

PubMed

Zhang, Le; Wang, Zhihui; Sagotsky, Jonathan A; Deisboeck, Thomas S

2009-04-01

Agent-based modeling (ABM) is an in silico technique that is being used in a variety of research areas such as in social sciences, economics and increasingly in biomedicine as an interdisciplinary tool to study the dynamics of complex systems. Here, we describe its applicability to integrative tumor biology research by introducing a multi-scale tumor modeling platform that understands brain cancer as a complex dynamic biosystem. We summarize significant findings of this work, and discuss both challenges and future directions for ABM in the field of cancer research.

Application of Biologically-Based Lumping To Investigate the ...

EPA Pesticide Factsheets

People are often exposed to complex mixtures of environmental chemicals such as gasoline, tobacco smoke, water contaminants, or food additives. However, investigators have often considered complex mixtures as one lumped entity. Valuable information can be obtained from these experiments, though this simplification provides little insight into the impact of a mixture's chemical composition on toxicologically-relevant metabolic interactions that may occur among its constituents. We developed an approach that applies chemical lumping methods to complex mixtures, in this case gasoline, based on biologically relevant parameters used in physiologically-based pharmacokinetic (PBPK) modeling. Inhalation exposures were performed with rats to evaluate performance of our PBPK model. There were 109 chemicals identified and quantified in the vapor in the chamber. The time-course kinetic profiles of 10 target chemicals were also determined from blood samples collected during and following the in vivo experiments. A general PBPK model was used to compare the experimental data to the simulated values of blood concentration for the 10 target chemicals with various numbers of lumps, iteratively increasing from 0 to 99. Large reductions in simulation error were gained by incorporating enzymatic chemical interactions, in comparison to simulating the individual chemicals separately. The error was further reduced by lumping the 99 non-target chemicals. Application of this biologic

Development and Effectiveness of an Educational Card Game as Supplementary Material in Understanding Selected Topics in Biology

PubMed Central

Gutierrez, Arnel F.

2014-01-01

The complex concepts and vocabulary of biology classes discourage many students. In this study, a pretest–posttest model was used to test the effectiveness of an educational card game in reinforcing biological concepts in comparison with traditional teaching methods. The subjects of this study were two biology classes at Bulacan State University–Sarmiento Campus. Both classes received conventional instruction; however, the experimental group's instruction was supplemented with the card game, while the control group's instruction was reinforced with traditional exercises and assignments. The score increases from pretest to posttest showed that both methods effectively reinforced biological concepts, but a t test showed that the card game is more effective than traditional teaching methods. Additionally, students from the experimental group evaluated the card game using five criteria: goals, design, organization, playability, and usefulness. The students rated the material very satisfactory. PMID:24591506

Development and effectiveness of an educational card game as supplementary material in understanding selected topics in biology.

PubMed

Gutierrez, Arnel F

2014-01-01

The complex concepts and vocabulary of biology classes discourage many students. In this study, a pretest-posttest model was used to test the effectiveness of an educational card game in reinforcing biological concepts in comparison with traditional teaching methods. The subjects of this study were two biology classes at Bulacan State University-Sarmiento Campus. Both classes received conventional instruction; however, the experimental group's instruction was supplemented with the card game, while the control group's instruction was reinforced with traditional exercises and assignments. The score increases from pretest to posttest showed that both methods effectively reinforced biological concepts, but a t test showed that the card game is more effective than traditional teaching methods. Additionally, students from the experimental group evaluated the card game using five criteria: goals, design, organization, playability, and usefulness. The students rated the material very satisfactory.

Electrical Chips for Biological Point-of-Care Detection.

PubMed

Reddy, Bobby; Salm, Eric; Bashir, Rashid

2016-07-11

As the future of health care diagnostics moves toward more portable and personalized techniques, there is immense potential to harness the power of electrical signals for biological sensing and diagnostic applications at the point of care. Electrical biochips can be used to both manipulate and sense biological entities, as they can have several inherent advantages, including on-chip sample preparation, label-free detection, reduced cost and complexity, decreased sample volumes, increased portability, and large-scale multiplexing. The advantages of fully integrated electrical biochip platforms are particularly attractive for point-of-care systems. This review summarizes these electrical lab-on-a-chip technologies and highlights opportunities to accelerate the transition from academic publications to commercial success.

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.

Fast neuromimetic object recognition using FPGA outperforms GPU implementations.

PubMed

Orchard, Garrick; Martin, Jacob G; Vogelstein, R Jacob; Etienne-Cummings, Ralph

2013-08-01

Recognition of objects in still images has traditionally been regarded as a difficult computational problem. Although modern automated methods for visual object recognition have achieved steadily increasing recognition accuracy, even the most advanced computational vision approaches are unable to obtain performance equal to that of humans. This has led to the creation of many biologically inspired models of visual object recognition, among them the hierarchical model and X (HMAX) model. HMAX is traditionally known to achieve high accuracy in visual object recognition tasks at the expense of significant computational complexity. Increasing complexity, in turn, increases computation time, reducing the number of images that can be processed per unit time. In this paper we describe how the computationally intensive and biologically inspired HMAX model for visual object recognition can be modified for implementation on a commercial field-programmable aate Array, specifically the Xilinx Virtex 6 ML605 evaluation board with XC6VLX240T FPGA. We show that with minor modifications to the traditional HMAX model we can perform recognition on images of size 128 × 128 pixels at a rate of 190 images per second with a less than 1% loss in recognition accuracy in both binary and multiclass visual object recognition tasks.

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

Visualizing Protein Interactions and Dynamics: Evolving a Visual Language for Molecular Animation

PubMed Central

Jenkinson, Jodie; McGill, Gaël

2012-01-01

Undergraduate biology education provides students with a number of learning challenges. Subject areas that are particularly difficult to understand include protein conformational change and stability, diffusion and random molecular motion, and molecular crowding. In this study, we examined the relative effectiveness of three-dimensional visualization techniques for learning about protein conformation and molecular motion in association with a ligand–receptor binding event. Increasingly complex versions of the same binding event were depicted in each of four animated treatments. Students (n = 131) were recruited from the undergraduate biology program at University of Toronto, Mississauga. Visualization media were developed in the Center for Molecular and Cellular Dynamics at Harvard Medical School. Stem cell factor ligand and cKit receptor tyrosine kinase were used as a classical example of a ligand-induced receptor dimerization and activation event. Each group completed a pretest, viewed one of four variants of the animation, and completed a posttest and, at 2 wk following the assessment, a delayed posttest. Overall, the most complex animation was the most effective at fostering students' understanding of the events depicted. These results suggest that, in select learning contexts, increasingly complex representations may be more desirable for conveying the dynamic nature of cell binding events. PMID:22383622

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

PubMed

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

2017-08-31

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

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

PubMed Central

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

2017-01-01

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

Mammals of the Braulio Carrillo- La Selva Complex, Costa Rica

USGS Publications Warehouse

Timm, Robert M.; Wilson, Don E.; Clauson, Barbara L.; LaVal, Richard K.; Vaughan, Christopher S.

1989-01-01

Costa Rica's La Selva-Braulio Carrillo complex encompasses a 60-km protected corridor of Caribbean rain and cloud forest extending from 30 m at the La Selva Biological Station to 2,906 m at the top of Volcán Barva. The 52,000-ha complex covers four life zones and two transitional zones, including tropical wet forest, tropical wet forest cool-transition, tropical premontane wet-transition rain forest, tropical premontane rain forest, lower montane rain forest, and montane rain forest. Located in the northeastern part of the country, the area is representative of Central American Caribbean slope forests that extend from Mexico to Panama. The extensive elevational gradient of the complex provides protected habitat for a variety of altitudinal migrants. With support from the National Geographic Society and Rice Foundation, the Organization for Tropical Studies organized a biological survey of the complex in early 1986. The mammal team worked at six sites along the elevational transect established by the expedition: 300 m, 700 m, 1,000 m, 1,500 m, 2,050 m, and 2,600 m. We supplemented our collecting records with unpublished records made available by colleagues, records in the published literature, and specimens in museum collections. In addition, observations recorded by a variety of observers at the La Selva Biological Station are summarized. The mammal fauna of the complex comprises 142 species including 79 bats, 23 rodents, 15 carnivores, 7 marsupials, 6 edentates, 4 artiodactyls, 3 primates, 2 rabbits, 2 shrews, and 1 perissodactyl. At least 10 additional species are likely to occur there. The only species of mammal likely to have been extirpated from the area is the giant anteater. Recognizing the importance of the area to wildlife and to mankind in general, the government of Costa Rica added 13,500 ha to the complex on 13 April 1986. This area, previously known as the “Zona Protectora,” provided the mid-elevational link between the lowlands of the La Selva Biological Station and the montane forests of Braulio Carrillo National Park. Unfortunately, destruction of the rain forests surrounding the complex will soon render it an isolated island of protected forest. Thus, the area will become increasingly valuable as a refuge for many species with home ranges that require extensive tracts of undisturbed habitat.

Environmental and biological context modulates the physiological stress response of bats to human disturbance.

PubMed

Phelps, Kendra L; Kingston, Tigga

2018-06-01

Environmental and biological context play significant roles in modulating physiological stress responses of individuals in wildlife populations yet are often overlooked when evaluating consequences of human disturbance on individual health and fitness. Furthermore, most studies gauge individual stress responses based on a single physiological biomarker, typically circulating glucocorticoid concentrations, which limits interpretation of the complex, multifaceted responses of individuals to stressors. We selected four physiological biomarkers to capture short-term and prolonged stress responses in a widespread cave-roosting bat, Hipposideros diadema, across multiple gradients of human disturbance in and around caves in the Philippines. We used conditional inference trees and random forest analysis to determine the role of environmental quality (cave complexity, available roosting area), assemblage composition (intra- and interspecific associations and species richness), and intrinsic characteristics of individuals (sex and reproductive status) in modulating responses to disturbance. Direct cave disturbance (hunting pressure and human visitation) was the primary driver of neutrophil-to-lymphocyte ratios, with lower ratios associated with increased disturbance, while context-specific factors were more important in explaining total leukocyte count, body condition, and ectoparasite load. Moreover, conditional inference trees revealed complex interactions among human disturbance and modulating factors. Cave complexity often ameliorated individual responses to human disturbance, whereas conspecific abundance often compounded responses. Our study demonstrates the importance of an integrated approach that incorporates environmental and biological context when identifying drivers of physiological responses, and that assesses responses to gradients of direct and indirect disturbance using multiple complementary biomarkers.

Chemistry meets biology in colitis-associated carcinogenesis

PubMed Central

Mangerich, Aswin; Dedon, Peter C.; Fox, James G.; Tannenbaum, Steven R.; Wogan, Gerald N.

2015-01-01

The intestine comprises an exceptional venue for a dynamic and complex interplay of numerous chemical and biological processes. Here, multiple chemical and biological systems, including the intestinal tissue itself, its associated immune system, the gut microbiota, xenobiotics, and metabolites meet and interact to form a sophisticated and tightly regulated state of tissue homoeostasis. Disturbance of this homeostasis can cause inflammatory bowel disease (IBD) – a chronic disease of multifactorial etiology that is strongly associated with increased risk for cancer development. This review addresses recent developments in research into chemical and biological mechanisms underlying the etiology of inflammation-induced colon cancer. Beginning with a general overview of reactive chemical species generated during colonic inflammation, the mechanistic interplay between chemical and biological mediators of inflammation, the role of genetic toxicology and microbial pathogenesis in disease development are discussed. When possible, we systematically compare evidence from studies utilizing human IBD patients with experimental investigations in mice. The comparison reveals that many strong pathological and mechanistic correlates exist between mouse models of colitis-associated cancer, and the clinically relevant situation in humans. We also summarize several emerging issues in the field, such as the carcinogenic potential of novel inflammation-related DNA adducts and genotoxic microbial factors, the systemic dimension of inflammation-induced genotoxicity, and the complex role of genome maintenance mechanisms during these processes. Taken together, current evidence points to the induction of genetic and epigenetic alterations by chemical and biological inflammatory stimuli ultimately leading to cancer formation. PMID:23926919

Investigating cholesterol metabolism and ageing using a systems biology approach.

PubMed

Morgan, A E; Mooney, K M; Wilkinson, S J; Pickles, N A; Mc Auley, M T

2017-08-01

CVD accounted for 27 % of all deaths in the UK in 2014, and was responsible for 1·7 million hospital admissions in 2013/2014. This condition becomes increasingly prevalent with age, affecting 34·1 and 29·8 % of males and females over 75 years of age respectively in 2011. The dysregulation of cholesterol metabolism with age, often observed as a rise in LDL-cholesterol, has been associated with the pathogenesis of CVD. To compound this problem, it is estimated by 2050, 22 % of the world's population will be over 60 years of age, in culmination with a growing resistance and intolerance to pre-existing cholesterol regulating drugs such as statins. Therefore, it is apparent research into additional therapies for hypercholesterolaemia and CVD prevention is a growing necessity. However, it is also imperative to recognise this complex biological system cannot be studied using a reductionist approach; rather its biological uniqueness necessitates a more integrated methodology, such as that offered by systems biology. In this review, we firstly discuss cholesterol metabolism and how it is affected by diet and the ageing process. Next, we describe therapeutic strategies for hypercholesterolaemia, and finally how the systems biology paradigm can be utilised to investigate how ageing interacts with complex systems such as cholesterol metabolism. We conclude by emphasising the need for nutritionists to work in parallel with the systems biology community, to develop novel approaches to studying cholesterol metabolism and its interaction with ageing.

Synthetic Genomics and Synthetic Biology Applications Between Hopes and Concerns

PubMed Central

König, Harald; Frank, Daniel; Heil, Reinhard; Coenen, Christopher

2013-01-01

New organisms and biological systems designed to satisfy human needs are among the aims of synthetic genomics and synthetic biology. Synthetic biology seeks to model and construct biological components, functions and organisms that do not exist in nature or to redesign existing biological systems to perform new functions. Synthetic genomics, on the other hand, encompasses technologies for the generation of chemically-synthesized whole genomes or larger parts of genomes, allowing to simultaneously engineer a myriad of changes to the genetic material of organisms. Engineering complex functions or new organisms in synthetic biology are thus progressively becoming dependent on and converging with synthetic genomics. While applications from both areas have been predicted to offer great benefits by making possible new drugs, renewable chemicals or clean energy, they have also given rise to concerns about new safety, environmental and socio-economic risks – stirring an increasingly polarizing debate. Here we intend to provide an overview on recent progress in biomedical and biotechnological applications of synthetic genomics and synthetic biology as well as on arguments and evidence related to their possible benefits, risks and governance implications. PMID:23997647

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.

Structure and Dynamics of Type III Secretion Effector Protein ExoU As determined by SDSL-EPR Spectroscopy in Conjunction with De Novo Protein Folding

PubMed Central

2017-01-01

ExoU is a 74 kDa cytotoxin that undergoes substantial conformational changes as part of its function, that is, it has multiple thermodynamically stable conformations that interchange depending on its environment. Such flexible proteins pose unique challenges to structural biology: (1) not only is it often difficult to determine structures by X-ray crystallography for all biologically relevant conformations because of the flat energy landscape (2) but also experimental conditions can easily perturb the biologically relevant conformation. The first challenge can be overcome by applying orthogonal structural biology techniques that are capable of observing alternative, biologically relevant conformations. The second challenge can be addressed by determining the structure in the same biological state with two independent techniques under different experimental conditions. If both techniques converge to the same structural model, the confidence that an unperturbed biologically relevant conformation is observed increases. To this end, we determine the structure of the C-terminal domain of the effector protein, ExoU, from data obtained by electron paramagnetic resonance spectroscopy in conjunction with site-directed spin labeling and in silico de novo structure determination. Our protocol encompasses a multimodule approach, consisting of low-resolution topology sampling, clustering, and high-resolution refinement. The resulting model was compared with an ExoU model in complex with its chaperone SpcU obtained previously by X-ray crystallography. The two models converged to a minimal RMSD100 of 3.2 Å, providing evidence that the unbound structure of ExoU matches the fold observed in complex with SpcU. PMID:28691114

The Upgrade Programme for the Structural Biology beamlines at the European Synchrotron Radiation Facility - High throughput sample evaluation and automation

NASA Astrophysics Data System (ADS)

Theveneau, P.; Baker, R.; Barrett, R.; Beteva, A.; Bowler, M. W.; Carpentier, P.; Caserotto, H.; de Sanctis, D.; Dobias, F.; Flot, D.; Guijarro, M.; Giraud, T.; Lentini, M.; Leonard, G. A.; Mattenet, M.; McCarthy, A. A.; McSweeney, S. M.; Morawe, C.; Nanao, M.; Nurizzo, D.; Ohlsson, S.; Pernot, P.; Popov, A. N.; Round, A.; Royant, A.; Schmid, W.; Snigirev, A.; Surr, J.; Mueller-Dieckmann, C.

2013-03-01

Automation and advances in technology are the key elements in addressing the steadily increasing complexity of Macromolecular Crystallography (MX) experiments. Much of this complexity is due to the inter-and intra-crystal heterogeneity in diffraction quality often observed for crystals of multi-component macromolecular assemblies or membrane proteins. Such heterogeneity makes high-throughput sample evaluation an important and necessary tool for increasing the chances of a successful structure determination. The introduction at the ESRF of automatic sample changers in 2005 dramatically increased the number of samples that were tested for diffraction quality. This "first generation" of automation, coupled with advances in software aimed at optimising data collection strategies in MX, resulted in a three-fold increase in the number of crystal structures elucidated per year using data collected at the ESRF. In addition, sample evaluation can be further complemented using small angle scattering experiments on the newly constructed bioSAXS facility on BM29 and the micro-spectroscopy facility (ID29S). The construction of a second generation of automated facilities on the MASSIF (Massively Automated Sample Screening Integrated Facility) beam lines will build on these advances and should provide a paradigm shift in how MX experiments are carried out which will benefit the entire Structural Biology community.

Biologically inspired robotic inspectors: the engineering reality and future outlook (Keynote address)

NASA Astrophysics Data System (ADS)

Bar-Cohen, Yoseph

2005-04-01

Human errors have long been recognized as a major factor in the reliability of nondestructive evaluation results. To minimize such errors, there is an increasing reliance on automatic inspection tools that allow faster and consistent tests. Crawlers and various manipulation devices are commonly used to perform variety of inspection procedures that include C-scan with contour following capability to rapidly inspect complex structures. The emergence of robots has been the result of the need to deal with parts that are too complex to handle by a simple automatic system. Economical factors are continuing to hamper the wide use of robotics for inspection applications however technology advances are increasingly changing this paradigm. Autonomous robots, which may look like human, can potentially address the need to inspect structures with configuration that are not predetermined. The operation of such robots that mimic biology may take place at harsh or hazardous environments that are too dangerous for human presence. Biomimetic technologies such as artificial intelligence, artificial muscles, artificial vision and numerous others are increasingly becoming common engineering tools. Inspired by science fiction, making biomimetic robots is increasingly becoming an engineering reality and in this paper the state-of-the-art will be reviewed and the outlook for the future will be discussed.

A systems biology model of the regulatory network in Populus leaves reveals interacting regulators and conserved regulation

PubMed Central

2011-01-01

Background Green plant leaves have always fascinated biologists as hosts for photosynthesis and providers of basic energy to many food webs. Today, comprehensive databases of gene expression data enable us to apply increasingly more advanced computational methods for reverse-engineering the regulatory network of leaves, and to begin to understand the gene interactions underlying complex emergent properties related to stress-response and development. These new systems biology methods are now also being applied to organisms such as Populus, a woody perennial tree, in order to understand the specific characteristics of these species. Results We present a systems biology model of the regulatory network of Populus leaves. The network is reverse-engineered from promoter information and expression profiles of leaf-specific genes measured over a large set of conditions related to stress and developmental. The network model incorporates interactions between regulators, such as synergistic and competitive relationships, by evaluating increasingly more complex regulatory mechanisms, and is therefore able to identify new regulators of leaf development not found by traditional genomics methods based on pair-wise expression similarity. The approach is shown to explain available gene function information and to provide robust prediction of expression levels in new data. We also use the predictive capability of the model to identify condition-specific regulation as well as conserved regulation between Populus and Arabidopsis. Conclusions We outline a computationally inferred model of the regulatory network of Populus leaves, and show how treating genes as interacting, rather than individual, entities identifies new regulators compared to traditional genomics analysis. Although systems biology models should be used with care considering the complexity of regulatory programs and the limitations of current genomics data, methods describing interactions can provide hypotheses about the underlying cause of emergent properties and are needed if we are to identify target genes other than those constituting the "low hanging fruit" of genomic analysis. PMID:21232107

PerSubs: A Graph-Based Algorithm for the Identification of Perturbed Subpathways Caused by Complex Diseases.

PubMed

Vrahatis, Aristidis G; Rapti, Angeliki; Sioutas, Spyros; Tsakalidis, Athanasios

2017-01-01

In the era of Systems Biology and growing flow of omics experimental data from high throughput techniques, experimentalists are in need of more precise pathway-based tools to unravel the inherent complexity of diseases and biological processes. Subpathway-based approaches are the emerging generation of pathway-based analysis elucidating the biological mechanisms under the perspective of local topologies onto a complex pathway network. Towards this orientation, we developed PerSub, a graph-based algorithm which detects subpathways perturbed by a complex disease. The perturbations are imprinted through differentially expressed and co-expressed subpathways as recorded by RNA-seq experiments. Our novel algorithm is applied on data obtained from a real experimental study and the identified subpathways provide biological evidence for the brain aging.

Vanadium(IV/V) complexes of Triapine and related thiosemicarbazones: Synthesis, solution equilibrium and bioactivity.

PubMed

Kowol, Christian R; Nagy, Nóra V; Jakusch, Tamás; Roller, Alexander; Heffeter, Petra; Keppler, Bernhard K; Enyedy, Éva A

2015-11-01

The stoichiometry and thermodynamic stability of vanadium(IV/V) complexes of Triapine and two related α(N)-heterocyclic thiosemicarbazones (TSCs) with potential antitumor activity have been determined by pH-potentiometry, EPR and (51)V NMR spectroscopy in 30% (w/w) dimethyl sulfoxide/water solvent mixtures. In all cases, mono-ligand complexes in different protonation states were identified. Dimethylation of the terminal amino group resulted in the formation of vanadium(IV/V) complexes with considerably higher stability. Three of the most stable complexes were also synthesized in solid state and comprehensively characterized. The biological evaluation of the synthesized vanadium complexes in comparison to the metal-free ligands in different human cancer cell lines revealed only minimal influence of the metal ion. Thus, in addition the coordination ability of salicylaldehyde thiosemicarbazone (STSC) to vanadium(IV/V) ions was investigated. The exchange of the pyridine nitrogen of the α(N)-heterocyclic TSCs to a phenolate oxygen in STSC significantly increased the stability of the complexes in solution. Finally, this also resulted in increased cytotoxicity activity of a vanadium(V) complex of STSC compared to the metal-free ligand. Copyright © 2015 Elsevier Inc. All rights reserved.

How do biological systems discriminate among physically similar ions?

PubMed

Diamond, J M

1975-10-01

This paper reviews the history of understanding how biological systems can discriminate so strikingly among physically similar ions, especially alkali cations. Appreciation of qualitative regularities ("permitted sequences") and quantitative regularities ("selectivity isotherms") in ion selectivity grew first from studies of ion exchangers and glass electrodes, then of biological systems such as enzymes and cell membranes, and most recently of lipid bilayers doped with model pores and carriers. Discrimination of ions depends on both electrostatic and steric forces. "Black-box" studies on intact biological membranes have in some cases yielded molecular clues to the structure of the actual biological pores and carriers. Major current problems involve the extraction of these molecules; how to do it, what to do when it is achieved, and how (and if) it is relevant to the central problems of membrane function. Further advances are expected soon from studies of rate barriers within membranes, of voltage-dependent ("excitable") conducting channels, and of increasingly complex model systems and biological membranes.

Detection and characterization of gene-gene and gene-environment interactions in common human diseases and complex clinical endpoints

EPA Science Inventory

Biological organisms are complex systems that dynamically integrate inputs from a multitude of physiological and environmental factors. Therefore, in addressing questions concerning the etiology of complex health outcomes, it is essential that the systemic nature of biology be ta...

Using Simple Manipulatives to Improve Student Comprehension of a Complex Biological Process: Protein Synthesis

ERIC Educational Resources Information Center

Guzman, Karen; Bartlett, John

2012-01-01

Biological systems and living processes involve a complex interplay of biochemicals and macromolecular structures that can be challenging for undergraduate students to comprehend and, thus, misconceptions abound. Protein synthesis, or translation, is an example of a biological process for which students often hold many misconceptions. This article…

Theory for the Emergence of Modularity in Complex Systems

NASA Astrophysics Data System (ADS)

Deem, Michael; Park, Jeong-Man

2013-03-01

Biological systems are modular, and this modularity evolves over time and in different environments. A number of observations have been made of increased modularity in biological systems under increased environmental pressure. We here develop a theory for the dynamics of modularity in these systems. We find a principle of least action for the evolved modularity at long times. In addition, we find a fluctuation dissipation relation for the rate of change of modularity at short times. We discuss a number of biological and social systems that can be understood with this framework. The modularity of the protein-protein interaction network increases when yeast are exposed to heat shock, and the modularity of the protein-protein networks in both yeast and E. coli appears to have increased over evolutionary time. Food webs in low-energy, stressful environments are more modular than those in plentiful environments, arid ecologies are more modular during droughts, and foraging of sea otters is more modular when food is limiting. The modularity of social networks changes over time: stock brokers instant messaging networks are more modular under stressful market conditions, criminal networks are more modular under increased police pressure, and world trade network modularity has decreased

7th Annual Systems Biology Symposium: Systems Biology and Engineering

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

Galitski, Timothy P.

2008-04-01

Systems biology recognizes the complex multi-scale organization of biological systems, from molecules to ecosystems. The International Symposium on Systems Biology has been hosted by the Institute for Systems Biology in Seattle, Washington, since 2002. The annual two-day event gathers the most influential researchers transforming biology into an integrative discipline investingating complex systems. Engineering and application of new technology is a central element of systems biology. Genome-scale, or very small-scale, biological questions drive the enigneering of new technologies, which enable new modes of experimentation and computational analysis, leading to new biological insights and questions. Concepts and analytical methods in engineering aremore » now finding direct applications in biology. Therefore, the 2008 Symposium, funded in partnership with the Department of Energy, featured global leaders in "Systems Biology and Engineering."« less

Post-traumatic stress disorder.

PubMed

Yehuda, Rachel; Hoge, Charles W; McFarlane, Alexander C; Vermetten, Eric; Lanius, Ruth A; Nievergelt, Caroline M; Hobfoll, Stevan E; Koenen, Karestan C; Neylan, Thomas C; Hyman, Steven E

2015-10-08

Post-traumatic stress disorder (PTSD) occurs in 5-10% of the population and is twice as common in women as in men. Although trauma exposure is the precipitating event for PTSD to develop, biological and psychosocial risk factors are increasingly viewed as predictors of symptom onset, severity and chronicity. PTSD affects multiple biological systems, such as brain circuitry and neurochemistry, and cellular, immune, endocrine and metabolic function. Treatment approaches involve a combination of medications and psychotherapy, with psychotherapy overall showing greatest efficacy. Studies of PTSD pathophysiology initially focused on the psychophysiology and neurobiology of stress responses, and the acquisition and the extinction of fear memories. However, increasing emphasis is being placed on identifying factors that explain individual differences in responses to trauma and promotion of resilience, such as genetic and social factors, brain developmental processes, cumulative biological and psychological effects of early childhood and other stressful lifetime events. The field of PTSD is currently challenged by fluctuations in diagnostic criteria, which have implications for epidemiological, biological, genetic and treatment studies. However, the advent of new biological methodologies offers the possibility of large-scale approaches to heterogeneous and genetically complex brain disorders, and provides optimism that individualized approaches to diagnosis and treatment will be discovered.

Fractal morphometry of cell complexity.

PubMed

Losa, Gabriele A

2002-01-01

Irregularity and self-similarity under scale changes are the main attributes of the morphological complexity of both normal and abnormal cells and tissues. In other words, the shape of a self-similar object does not change when the scale of measurement changes, because each part of it looks similar to the original object. However, the size and geometrical parameters of an irregular object do differ when it is examined at increasing resolution, which reveals more details. Significant progress has been made over the past three decades in understanding how irregular shapes and structures in the physical and biological sciences can be analysed. Dominant influences have been the discovery of a new practical geometry of Nature, now known as fractal geometry, and the continuous improvements in computation capabilities. Unlike conventional Euclidean geometry, which was developed to describe regular and ideal geometrical shapes which are practically unknown in nature, fractal geometry can be used to measure the fractal dimension, contour length, surface area and other dimension parameters of almost all irregular and complex biological tissues. We have used selected examples to illustrate the application of the fractal principle to measuring irregular and complex membrane ultrastructures of cells at specific functional and pathological stage.

Complexity reduction of biochemical rate expressions.

PubMed

Schmidt, Henning; Madsen, Mads F; Danø, Sune; Cedersund, Gunnar

2008-03-15

The current trend in dynamical modelling of biochemical systems is to construct more and more mechanistically detailed and thus complex models. The complexity is reflected in the number of dynamic state variables and parameters, as well as in the complexity of the kinetic rate expressions. However, a greater level of complexity, or level of detail, does not necessarily imply better models, or a better understanding of the underlying processes. Data often does not contain enough information to discriminate between different model hypotheses, and such overparameterization makes it hard to establish the validity of the various parts of the model. Consequently, there is an increasing demand for model reduction methods. We present a new reduction method that reduces complex rational rate expressions, such as those often used to describe enzymatic reactions. The method is a novel term-based identifiability analysis, which is easy to use and allows for user-specified reductions of individual rate expressions in complete models. The method is one of the first methods to meet the classical engineering objective of improved parameter identifiability without losing the systems biology demand of preserved biochemical interpretation. The method has been implemented in the Systems Biology Toolbox 2 for MATLAB, which is freely available from http://www.sbtoolbox2.org. The Supplementary Material contains scripts that show how to use it by applying the method to the example models, discussed in this article.

Synthetic biology strategies toward heterologous phytochemical production.

PubMed

Kotopka, Benjamin J; Li, Yanran; Smolke, Christina D

2018-06-13

Covering: 2006 to 2018Phytochemicals are important sources for the discovery and development of agricultural and pharmaceutical compounds, such as pesticides and medicines. However, these compounds are typically present in low abundance in nature, and the biosynthetic pathways for most phytochemicals are not fully elucidated. Heterologous production of phytochemicals in plant, bacterial, and yeast hosts has been pursued as a potential approach to address sourcing issues associated with many valuable phytochemicals, and more recently has been utilized as a tool to aid in the elucidation of plant biosynthetic pathways. Due to the structural complexity of certain phytochemicals and the associated biosynthetic pathways, reconstitution of plant pathways in heterologous hosts can encounter numerous challenges. Synthetic biology approaches have been developed to address these challenges in areas such as precise control over heterologous gene expression, improving functional expression of heterologous enzymes, and modifying central metabolism to increase the supply of precursor compounds into the pathway. These strategies have been applied to advance plant pathway reconstitution and phytochemical production in a wide variety of heterologous hosts. Here, we review synthetic biology strategies that have been recently applied to advance complex phytochemical production in heterologous hosts.

Passive film growth on titanium alloys: physicochemical and biologic considerations.

PubMed

Eliades, T

1997-01-01

The role of reactive oxygen derivatives (hydroxy peroxide, hydroxyl radical, and singlet oxygen) on the precipitation of inorganic and organic complexes onto the surface of titanium implant alloys is discussed in this review. In addition, the effect of possible implication of several biologic entities surrounding the implant on the implant-tissue interface constituents is described. Evidence from relevant studies suggests that local microenvironmental byproducts and factors associated with the inflammatory response resulting from the implant-induced tissue insult may enhance the expressivity of the inherent, clinically important property of titanium to form oxides. Growth of titanium oxide may be explained through several processes derived from biologic, thermodynamic, and electrochemical approaches. The models proposed to interpret this phenomenon are often contradictory, demonstrating inward or outward from the bulk material passive film growth, with increasing or self-limiting levels of oxide formation as a function of time. However, in vivo observations are consistent with aging-induced thickening of the complexes precipitated on the implant material surface. This review attempts to clarify several critical issues pertaining to passive film formation and kinetics on titanium-alloy surfaces.

Stepping into the omics era: Opportunities and challenges for biomaterials science and engineering.

PubMed

Groen, Nathalie; Guvendiren, Murat; Rabitz, Herschel; Welsh, William J; Kohn, Joachim; de Boer, Jan

2016-04-01

The research paradigm in biomaterials science and engineering is evolving from using low-throughput and iterative experimental designs towards high-throughput experimental designs for materials optimization and the evaluation of materials properties. Computational science plays an important role in this transition. With the emergence of the omics approach in the biomaterials field, referred to as materiomics, high-throughput approaches hold the promise of tackling the complexity of materials and understanding correlations between material properties and their effects on complex biological systems. The intrinsic complexity of biological systems is an important factor that is often oversimplified when characterizing biological responses to materials and establishing property-activity relationships. Indeed, in vitro tests designed to predict in vivo performance of a given biomaterial are largely lacking as we are not able to capture the biological complexity of whole tissues in an in vitro model. In this opinion paper, we explain how we reached our opinion that converging genomics and materiomics into a new field would enable a significant acceleration of the development of new and improved medical devices. The use of computational modeling to correlate high-throughput gene expression profiling with high throughput combinatorial material design strategies would add power to the analysis of biological effects induced by material properties. We believe that this extra layer of complexity on top of high-throughput material experimentation is necessary to tackle the biological complexity and further advance the biomaterials field. In this opinion paper, we postulate that converging genomics and materiomics into a new field would enable a significant acceleration of the development of new and improved medical devices. The use of computational modeling to correlate high-throughput gene expression profiling with high throughput combinatorial material design strategies would add power to the analysis of biological effects induced by material properties. We believe that this extra layer of complexity on top of high-throughput material experimentation is necessary to tackle the biological complexity and further advance the biomaterials field. Copyright © 2016. Published by Elsevier Ltd.

Annual Research Review: Developmental Considerations of Gene by Environment Interactions

ERIC Educational Resources Information Center

Lenroot, Rhoshel K.; Giedd, Jay N.

2011-01-01

Biological development is driven by a complex dance between nurture and nature, determined not only by the specific features of the interacting genetic and environmental influences but also by the timing of their rendezvous. The initiation of large-scale longitudinal studies, ever-expanding knowledge of genetics, and increasing availability of…

Achieving Masculinity: A Review of the Literature on Male Gender Identity Development.

ERIC Educational Resources Information Center

Puls, Daniel W.

Distinctions between males and females arise as a result of a complex developmental process involving biological, psychological, and sociological forces. Much research on male gender identity development has spurred from the increased interest in the etiology of homosexuality over the last two decades. Political, religious, and moral issues often…

Catalyzing sustainability: Cornell University's field practicum in conservation and sustainable development

Treesearch

John Schelhas

2000-01-01

Human society is increasingly facing a variety of complex, intertwined environmental conservation and rural development issues. For example, national park objectives have expanded from the conservation of biological diversity to also include contributing to the livelihood and development needs of local people. Human settlements in fragile uplands create conflicts...

Using a Coupled Modelling System to Examine the Impacts of Increased Corn Production on Groundwater Quality and Human Health

EPA Science Inventory

Attributing nitrogen (N) in the environment to emissions from agricultural management practices is difficult because of the complex and inter-related chemical and biological reactions associated with N and its cascading effects across land, air and water. Such analyses are critic...

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

The HADDOCK2.2 Web Server: User-Friendly Integrative Modeling of Biomolecular Complexes.

PubMed

van Zundert, G C P; Rodrigues, J P G L M; Trellet, M; Schmitz, C; Kastritis, P L; Karaca, E; Melquiond, A S J; van Dijk, M; de Vries, S J; Bonvin, A M J J

2016-02-22

The prediction of the quaternary structure of biomolecular macromolecules is of paramount importance for fundamental understanding of cellular processes and drug design. In the era of integrative structural biology, one way of increasing the accuracy of modeling methods used to predict the structure of biomolecular complexes is to include as much experimental or predictive information as possible in the process. This has been at the core of our information-driven docking approach HADDOCK. We present here the updated version 2.2 of the HADDOCK portal, which offers new features such as support for mixed molecule types, additional experimental restraints and improved protocols, all of this in a user-friendly interface. With well over 6000 registered users and 108,000 jobs served, an increasing fraction of which on grid resources, we hope that this timely upgrade will help the community to solve important biological questions and further advance the field. The HADDOCK2.2 Web server is freely accessible to non-profit users at http://haddock.science.uu.nl/services/HADDOCK2.2. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

Carbon cycling at the tipping point: Does ecosystem structure predict resistance to disturbance?

NASA Astrophysics Data System (ADS)

Gough, C. M.; Bond-Lamberty, B. P.; Stuart-Haentjens, E.; Atkins, J.; Haber, L.; Fahey, R. T.

2017-12-01

Ecosystems worldwide are subjected to disturbances that reshape their physical and biological structure and modify biogeochemical processes, including carbon storage and cycling rates. Disturbances, including those from insect pests, pathogens, and extreme weather, span a continuum of severity and, accordingly, may have different effects on carbon cycling processes. Some ecosystems resist biogeochemical changes following disturbance, until a critical threshold of severity is exceeded. The ecosystem properties underlying such functional resistance, and signifying when a tipping point will occur, however, are almost entirely unknown. Here, we present observational and experimental results from forests in the Great Lakes region, showing ecosystem structure is closely coupled with carbon cycling responses to disturbance, with shifts in structure predicting thresholds of and, in some cases, increases in carbon storage. We find, among forests in the region, that carbon storage regularly exhibits a non-linear threshold response to increasing disturbance levels, but the severity at which a threshold is reached varies among disturbed forests. More biologically and structurally complex forest ecosystems sometimes exhibit greater functional resistance than simpler forests, and consequently may have a higher disturbance severity threshold. Counter to model predictions but consistent with some theoretical frameworks, empirical data show moderate levels of disturbance may increase ecosystem complexity to a point, thereby increasing rates of carbon storage. Disturbances that increase complexity therefore may stimulate carbon storage, while severe disturbances at or beyond thresholds may simplify structure, leading to carbon storage declines. We conclude that ecosystem structural attributes are closely coupled with biogeochemical thresholds across disturbance severity gradients, suggesting that improved predictions of disturbance-related changes in the carbon cycle require better representation of ecosystem structure in models.

Yeast synthetic biology for high-value metabolites.

PubMed

Dai, Zhubo; Liu, Yi; Guo, Juan; Huang, Luqi; Zhang, Xueli

2015-02-01

Traditionally, high-value metabolites have been produced through direct extraction from natural biological sources which are inefficient, given the low abundance of these compounds. On the other hand, these high-value metabolites are usually difficult to be synthesized chemically, due to their complex structures. In the last few years, the discovery of genes involved in the synthetic pathways of these metabolites, combined with advances in synthetic biology tools, has allowed the construction of increasing numbers of yeast cell factories for production of these metabolites from renewable biomass. This review summarizes recent advances in synthetic biology in terms of the use of yeasts as microbial hosts for the identification of the pathways involved in the synthesis, as well as for the production of high-value metabolites. © FEMS 2015. All rights reserved. For permissions, please e-mail: journals.permission@oup.com.

Expanding Biosensing Abilities through Computer-Aided Design of Metabolic Pathways.

PubMed

Libis, Vincent; Delépine, Baudoin; Faulon, Jean-Loup

2016-10-21

Detection of chemical signals is critical for cells in nature as well as in synthetic biology, where they serve as inputs for designer circuits. Important progress has been made in the design of signal processing circuits triggering complex biological behaviors, but the range of small molecules recognized by sensors as inputs is limited. The ability to detect new molecules will increase the number of synthetic biology applications, but direct engineering of tailor-made sensors takes time. Here we describe a way to immediately expand the range of biologically detectable molecules by systematically designing metabolic pathways that transform nondetectable molecules into molecules for which sensors already exist. We leveraged computer-aided design to predict such sensing-enabling metabolic pathways, and we built several new whole-cell biosensors for molecules such as cocaine, parathion, hippuric acid, and nitroglycerin.

Evolutionary game theory for physical and biological scientists. II. Population dynamics equations can be associated with interpretations

PubMed Central

Liao, David; Tlsty, Thea D.

2014-01-01

The use of mathematical equations to analyse population dynamics measurements is being increasingly applied to elucidate complex dynamic processes in biological systems, including cancer. Purely ‘empirical’ equations may provide sufficient accuracy to support predictions and therapy design. Nevertheless, interpretation of fitting equations in terms of physical and biological propositions can provide additional insights that can be used both to refine models that prove inconsistent with data and to understand the scope of applicability of models that validate. The purpose of this tutorial is to assist readers in mathematically associating interpretations with equations and to provide guidance in choosing interpretations and experimental systems to investigate based on currently available biological knowledge, techniques in mathematical and computational analysis and methods for in vitro and in vivo experiments. PMID:25097752

Circulating complexes between tumour necrosis factor-alpha and etanercept predict long-term efficacy of etanercept in juvenile idiopathic arthritis.

PubMed

Kahn, Robin; Berthold, Elisabet; Gullstrand, Birgitta; Schmidt, Tobias; Kahn, Fredrik; Geborek, Pierre; Saxne, Tore; Bengtsson, Anders A; Månsson, Bengt

2016-04-01

The relationship between tumour necrosis factor-alpha (TNF-α) and drug survival had not been studied in juvenile idiopathic arthritis (JIA), and there were no laboratory tests to predict the long-term efficacy of biological drugs for JIA. We studied whether serum levels of TNF-α, free or bound to etanercept, could predict long-term efficacy of etanercept in children with JIA. We included 41 biologic-naïve patients with JIA who started treatment with etanercept at Skåne University Hospital between 1999 and 2010. Serum taken at the start of treatment and at the six-week follow-up were analysed for TNF-α and the long-term efficacy of etanercept was assessed using the drug survival time. Levels of TNF-α increased significantly at the six-week follow-up, and this was almost exclusively comprised of TNF-α in complex with etanercept. The increase in TNF-α showed a dose-dependent correlation to long-term drug survival (p < 0.01). Increasing levels of circulating TNF-α at treatment initiation predicted long-term efficacy of etanercept in children with JIA, which may have been due to different pathophysiological mechanisms of inflammation. Our result may provide a helpful clinical tool, as high levels of circulating TNF-α/etanercept complexes could be used as a marker for the long-term efficacy of etanercept. ©2015 The Authors. Acta Paediatrica published by John Wiley & Sons Ltd on behalf of Foundation Acta Paediatrica.

Intrinsic dimensionality predicts the saliency of natural dynamic scenes.

PubMed

Vig, Eleonora; Dorr, Michael; Martinetz, Thomas; Barth, Erhardt

2012-06-01

Since visual attention-based computer vision applications have gained popularity, ever more complex, biologically inspired models seem to be needed to predict salient locations (or interest points) in naturalistic scenes. In this paper, we explore how far one can go in predicting eye movements by using only basic signal processing, such as image representations derived from efficient coding principles, and machine learning. To this end, we gradually increase the complexity of a model from simple single-scale saliency maps computed on grayscale videos to spatiotemporal multiscale and multispectral representations. Using a large collection of eye movements on high-resolution videos, supervised learning techniques fine-tune the free parameters whose addition is inevitable with increasing complexity. The proposed model, although very simple, demonstrates significant improvement in predicting salient locations in naturalistic videos over four selected baseline models and two distinct data labeling scenarios.

Modeling the assembly order of multimeric heteroprotein complexes

PubMed Central

Esquivel-Rodriguez, Juan; Terashi, Genki; Christoffer, Charles; Shin, Woong-Hee

2018-01-01

Protein-protein interactions are the cornerstone of numerous biological processes. Although an increasing number of protein complex structures have been determined using experimental methods, relatively fewer studies have been performed to determine the assembly order of complexes. In addition to the insights into the molecular mechanisms of biological function provided by the structure of a complex, knowing the assembly order is important for understanding the process of complex formation. Assembly order is also practically useful for constructing subcomplexes as a step toward solving the entire complex experimentally, designing artificial protein complexes, and developing drugs that interrupt a critical step in the complex assembly. There are several experimental methods for determining the assembly order of complexes; however, these techniques are resource-intensive. Here, we present a computational method that predicts the assembly order of protein complexes by building the complex structure. The method, named Path-LzerD, uses a multimeric protein docking algorithm that assembles a protein complex structure from individual subunit structures and predicts assembly order by observing the simulated assembly process of the complex. Benchmarked on a dataset of complexes with experimental evidence of assembly order, Path-LZerD was successful in predicting the assembly pathway for the majority of the cases. Moreover, when compared with a simple approach that infers the assembly path from the buried surface area of subunits in the native complex, Path-LZerD has the strong advantage that it can be used for cases where the complex structure is not known. The path prediction accuracy decreased when starting from unbound monomers, particularly for larger complexes of five or more subunits, for which only a part of the assembly path was correctly identified. As the first method of its kind, Path-LZerD opens a new area of computational protein structure modeling and will be an indispensable approach for studying protein complexes. PMID:29329283

Modeling the assembly order of multimeric heteroprotein complexes.

PubMed

Peterson, Lenna X; Togawa, Yoichiro; Esquivel-Rodriguez, Juan; Terashi, Genki; Christoffer, Charles; Roy, Amitava; Shin, Woong-Hee; Kihara, Daisuke

2018-01-01

Protein-protein interactions are the cornerstone of numerous biological processes. Although an increasing number of protein complex structures have been determined using experimental methods, relatively fewer studies have been performed to determine the assembly order of complexes. In addition to the insights into the molecular mechanisms of biological function provided by the structure of a complex, knowing the assembly order is important for understanding the process of complex formation. Assembly order is also practically useful for constructing subcomplexes as a step toward solving the entire complex experimentally, designing artificial protein complexes, and developing drugs that interrupt a critical step in the complex assembly. There are several experimental methods for determining the assembly order of complexes; however, these techniques are resource-intensive. Here, we present a computational method that predicts the assembly order of protein complexes by building the complex structure. The method, named Path-LzerD, uses a multimeric protein docking algorithm that assembles a protein complex structure from individual subunit structures and predicts assembly order by observing the simulated assembly process of the complex. Benchmarked on a dataset of complexes with experimental evidence of assembly order, Path-LZerD was successful in predicting the assembly pathway for the majority of the cases. Moreover, when compared with a simple approach that infers the assembly path from the buried surface area of subunits in the native complex, Path-LZerD has the strong advantage that it can be used for cases where the complex structure is not known. The path prediction accuracy decreased when starting from unbound monomers, particularly for larger complexes of five or more subunits, for which only a part of the assembly path was correctly identified. As the first method of its kind, Path-LZerD opens a new area of computational protein structure modeling and will be an indispensable approach for studying protein complexes.

Final Report, 2011-2014. Forecasting Carbon Storage as Eastern Forests Age. Joining Experimental and Modeling Approaches at the UMBS AmeriFlux Site

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

Curtis, Peter; Bohrer, Gil; Gough, Christopher

2015-03-12

At the University of Michigan Biological Station (UMBS) AmeriFlux sites (US-UMB and US-UMd), long-term C cycling measurements and a novel ecosystem-scale experiment are revealing physical, biological, and ecological mechanisms driving long-term trajectories of C cycling, providing new data for improving modeling forecasts of C storage in eastern forests. Our findings provide support for previously untested hypotheses that stand-level structural and biological properties constrain long-term trajectories of C storage, and that remotely sensed canopy structural parameters can substantially improve model forecasts of forest C storage. Through the Forest Accelerated Succession ExperimenT (FASET), we are directly testing the hypothesis that forest Cmore » storage will increase due to increasing structural and biological complexity of the emerging tree communities. Support from this project, 2011-2014, enabled us to incorporate novel physical and ecological mechanisms into ecological, meteorological, and hydrological models to improve forecasts of future forest C storage in response to disturbance, succession, and current and long-term climate variation« less

Mathematical and Computational Modeling in Complex Biological Systems

PubMed Central

Li, Wenyang; Zhu, Xiaoliang

2017-01-01

The biological process and molecular functions involved in the cancer progression remain difficult to understand for biologists and clinical doctors. Recent developments in high-throughput technologies urge the systems biology to achieve more precise models for complex diseases. Computational and mathematical models are gradually being used to help us understand the omics data produced by high-throughput experimental techniques. The use of computational models in systems biology allows us to explore the pathogenesis of complex diseases, improve our understanding of the latent molecular mechanisms, and promote treatment strategy optimization and new drug discovery. Currently, it is urgent to bridge the gap between the developments of high-throughput technologies and systemic modeling of the biological process in cancer research. In this review, we firstly studied several typical mathematical modeling approaches of biological systems in different scales and deeply analyzed their characteristics, advantages, applications, and limitations. Next, three potential research directions in systems modeling were summarized. To conclude, this review provides an update of important solutions using computational modeling approaches in systems biology. PMID:28386558

Mathematical and Computational Modeling in Complex Biological Systems.

PubMed

Ji, Zhiwei; Yan, Ke; Li, Wenyang; Hu, Haigen; Zhu, Xiaoliang

2017-01-01

The biological process and molecular functions involved in the cancer progression remain difficult to understand for biologists and clinical doctors. Recent developments in high-throughput technologies urge the systems biology to achieve more precise models for complex diseases. Computational and mathematical models are gradually being used to help us understand the omics data produced by high-throughput experimental techniques. The use of computational models in systems biology allows us to explore the pathogenesis of complex diseases, improve our understanding of the latent molecular mechanisms, and promote treatment strategy optimization and new drug discovery. Currently, it is urgent to bridge the gap between the developments of high-throughput technologies and systemic modeling of the biological process in cancer research. In this review, we firstly studied several typical mathematical modeling approaches of biological systems in different scales and deeply analyzed their characteristics, advantages, applications, and limitations. Next, three potential research directions in systems modeling were summarized. To conclude, this review provides an update of important solutions using computational modeling approaches in systems biology.

Investigating the effect of gallium curcumin and gallium diacetylcurcumin complexes on the structure, function and oxidative stability of the peroxidase enzyme and their anticancer and antibacterial activities.

PubMed

Jahangoshaei, Parisa; Hassani, Leila; Mohammadi, Fakhrossadat; Hamidi, Akram; Mohammadi, Khosro

2015-10-01

Curcumin has a wide spectrum of biological and pharmacological activities including anti-inflammatory, antioxidant, antiproliferative, antimicrobial and anticancer activities. Complexation of curcumin with metals has gained attention in recent years for improvement of its stability. In this study, the effect of gallium curcumin and gallium diacetylcurcumin on the structure, function and oxidative stability of horseradish peroxidase (HRP) enzyme were evaluated by spectroscopic techniques. In addition to the enzymatic investigation, the cytotoxic effect of the complexes was assessed on bladder, MCF-7 breast cancer and LNCaP prostate carcinoma cell lines by MTT assay. Furthermore, antibacterial activity of the complexes against S. aureus and E. coli was explored by dilution test method. The results showed that the complexes improve activity of HRP and also increase its tolerance against the oxidative condition. After addition of the complexes, affinity of HRP for hydrogen peroxide substrate decreases, while the affinity increases for phenol substrate. Circular dichroism, intrinsic and synchronous fluorescence spectra showed that the enzyme structure around the catalytic heme group becomes less compact and also the distance between the heme group and tryptophan residues increases due to binding of the complexes to HRP. On the whole, it can be concluded that the change in the enzyme structure upon binding to the gallium curcumin and gallium diacetylcurcumin complexes results in an increase in the antioxidant efficiency and activity of the peroxidise enzyme. The result of anticancer and antibacterial activities suggested that the complexes exhibit the potential for cancer treatment, but they have no significant antibacterial activity.

Microwave gallium-68 radiochemistry for kinetically stable bis(thiosemicarbazone) complexes: structural investigations and cellular uptake under hypoxia.

PubMed

Alam, Israt S; Arrowsmith, Rory L; Cortezon-Tamarit, Fernando; Twyman, Frazer; Kociok-Köhn, Gabriele; Botchway, Stanley W; Dilworth, Jonathan R; Carroll, Laurence; Aboagye, Eric O; Pascu, Sofia I

2016-01-07

We report the microwave synthesis of several bis(thiosemicarbazones) and the rapid gallium-68 incorporation to give the corresponding metal complexes. These proved kinetically stable under 'cold' and 'hot' biological assays and were investigated using laser scanning confocal microscopy, flow cytometry and radioactive cell retention studies under normoxia and hypoxia. (68)Ga complex retention was found to be 34% higher in hypoxic cells than in normoxic cells over 30 min, further increasing to 53% at 120 min. Our data suggests that this class of gallium complexes show hypoxia selectivity suitable for imaging in living cells and in vivo tests by microPET in nude athymic mice showed that they are excreted within 1 h of their administration.

A multi-target caffeine derived rhodium(i) N-heterocyclic carbene complex: evaluation of the mechanism of action.

PubMed

Zhang, Jing-Jing; Muenzner, Julienne K; Abu El Maaty, Mohamed A; Karge, Bianka; Schobert, Rainer; Wölfl, Stefan; Ott, Ingo

2016-08-16

A rhodium(i) and a ruthenium(ii) complex with a caffeine derived N-heterocyclic carbene (NHC) ligand were biologically investigated as organometallic conjugates consisting of a metal center and a naturally occurring moiety. While the ruthenium(ii) complex was largely inactive, the rhodium(i) NHC complex displayed selective cytotoxicity and significant anti-metastatic and in vivo anti-vascular activities and acted as both a mammalian and an E. coli thioredoxin reductase inhibitor. In HCT-116 cells it increased the reactive oxygen species level, leading to DNA damage, and it induced cell cycle arrest, decreased the mitochondrial membrane potential, and triggered apoptosis. This rhodium(i) NHC derivative thus represents a multi-target compound with promising anti-cancer potential.

Comparison of biological activities of human antithrombins with high-mannose or complex-type nonfucosylated N-linked oligosaccharides

PubMed Central

Yamada, Tsuyoshi; Kanda, Yutaka; Takayama, Makoto; Hashimoto, Akitoshi; Sugihara, Tsutomu; Satoh-Kubota, Ai; Suzuki-Takanami, Eri; Yano, Keiichi; Iida, Shigeru; Satoh, Mitsuo

2016-01-01

The structure of the N-linked oligosaccharides attached to antithrombin (AT) has been shown to affect its anticoagulant activity and pharmacokinetics. Human AT has biantennary complex-type oligosaccharides with the unique feature of lacking a core fucose, which affects its biological activities by changing its heparin-binding affinity. In human plasma, AT circulates as a mixture of the α-form bearing four oligosaccharides and the β-form lacking an oligosaccharide at Asn135. However, it remains unclear how the immature high-mannose-type oligosaccharides produced by mammalian cells affect biological activities of AT. Here, we succeeded in directly comparing the activities between the high-mannose and complex types. Interestingly, although there were no substantial differences in thrombin inhibitory activity, the high-mannose type showed higher heparin-binding affinity. The anticoagulant activities were increased by heparin and correlated with the heparin-binding affinity, resulting in the strongest anticoagulant activity being displayed in the β-form with the high-mannose type. In pharmacokinetic profiling, the high-mannose type showed a much shorter plasma half-life than the complex type. The β-form was found to have a prolonged plasma half-life compared with the α-form for the high-mannose type; conversely, the α-form showed a longer half-life than the β-form for the complex-type. The present study highlights that AT physiological activities are strictly controlled not only by a core fucose at the reducing end but also by the high-mannose-type structures at the nonreducing end. The β-form with the immature high-mannose type appears to function as a more potent anticoagulant than the AT typically found in human plasma, once it emerges in the blood. PMID:26747427

Comparison of biological activities of human antithrombins with high-mannose or complex-type nonfucosylated N-linked oligosaccharides.

PubMed

Yamada, Tsuyoshi; Kanda, Yutaka; Takayama, Makoto; Hashimoto, Akitoshi; Sugihara, Tsutomu; Satoh-Kubota, Ai; Suzuki-Takanami, Eri; Yano, Keiichi; Iida, Shigeru; Satoh, Mitsuo

2016-05-01

The structure of the N-linked oligosaccharides attached to antithrombin (AT) has been shown to affect its anticoagulant activity and pharmacokinetics. Human AT has biantennary complex-type oligosaccharides with the unique feature of lacking a core fucose, which affects its biological activities by changing its heparin-binding affinity. In human plasma, AT circulates as a mixture of the α-form bearing four oligosaccharides and the β-form lacking an oligosaccharide at Asn135. However, it remains unclear how the immature high-mannose-type oligosaccharides produced by mammalian cells affect biological activities of AT. Here, we succeeded in directly comparing the activities between the high-mannose and complex types. Interestingly, although there were no substantial differences in thrombin inhibitory activity, the high-mannose type showed higher heparin-binding affinity. The anticoagulant activities were increased by heparin and correlated with the heparin-binding affinity, resulting in the strongest anticoagulant activity being displayed in the β-form with the high-mannose type. In pharmacokinetic profiling, the high-mannose type showed a much shorter plasma half-life than the complex type. The β-form was found to have a prolonged plasma half-life compared with the α-form for the high-mannose type; conversely, the α-form showed a longer half-life than the β-form for the complex-type. The present study highlights that AT physiological activities are strictly controlled not only by a core fucose at the reducing end but also by the high-mannose-type structures at the nonreducing end. The β-form with the immature high-mannose type appears to function as a more potent anticoagulant than the AT typically found in human plasma, once it emerges in the blood. © The Author 2016. Published by Oxford University Press.

Stepping into the omics era: Opportunities and challenges for biomaterials science and engineering☆

PubMed Central

Rabitz, Herschel; Welsh, William J.; Kohn, Joachim; de Boer, Jan

2016-01-01

The research paradigm in biomaterials science and engineering is evolving from using low-throughput and iterative experimental designs towards high-throughput experimental designs for materials optimization and the evaluation of materials properties. Computational science plays an important role in this transition. With the emergence of the omics approach in the biomaterials field, referred to as materiomics, high-throughput approaches hold the promise of tackling the complexity of materials and understanding correlations between material properties and their effects on complex biological systems. The intrinsic complexity of biological systems is an important factor that is often oversimplified when characterizing biological responses to materials and establishing property-activity relationships. Indeed, in vitro tests designed to predict in vivo performance of a given biomaterial are largely lacking as we are not able to capture the biological complexity of whole tissues in an in vitro model. In this opinion paper, we explain how we reached our opinion that converging genomics and materiomics into a new field would enable a significant acceleration of the development of new and improved medical devices. The use of computational modeling to correlate high-throughput gene expression profiling with high throughput combinatorial material design strategies would add power to the analysis of biological effects induced by material properties. We believe that this extra layer of complexity on top of high-throughput material experimentation is necessary to tackle the biological complexity and further advance the biomaterials field. PMID:26876875

Myeloid-derived suppressor cells in the tumor microenvironment: expect the unexpected.

PubMed

Marvel, Douglas; Gabrilovich, Dmitry I

2015-09-01

Our understanding of the role of myeloid-derived suppressor cells (MDSCs) in cancer is becoming increasingly complex. In addition to their eponymous role in suppressing immune responses, they directly support tumor growth, differentiation, and metastasis in a number of ways that are only now beginning to be appreciated. It is because of this increasingly complex role that these cells may become an important factor in the treatment of human cancer. In this Review, we discuss the most pertinent and controversial issues of MDSC biology and their role in promoting cancer progression and highlight how these cells may be used in the clinic, both as prognostic factors and as therapeutic targets.

Formal modeling and analysis of ER-α associated Biological Regulatory Network in breast cancer.

PubMed

Khalid, Samra; Hanif, Rumeza; Tareen, Samar H K; Siddiqa, Amnah; Bibi, Zurah; Ahmad, Jamil

2016-01-01

Breast cancer (BC) is one of the leading cause of death among females worldwide. The increasing incidence of BC is due to various genetic and environmental changes which lead to the disruption of cellular signaling network(s). It is a complex disease in which several interlinking signaling cascades play a crucial role in establishing a complex regulatory network. The logical modeling approach of René Thomas has been applied to analyze the behavior of estrogen receptor-alpha (ER- α ) associated Biological Regulatory Network (BRN) for a small part of complex events that leads to BC metastasis. A discrete model was constructed using the kinetic logic formalism and its set of logical parameters were obtained using the model checking technique implemented in the SMBioNet software which is consistent with biological observations. The discrete model was further enriched with continuous dynamics by converting it into an equivalent Petri Net (PN) to analyze the logical parameters of the involved entities. In-silico based discrete and continuous modeling of ER- α associated signaling network involved in BC provides information about behaviors and gene-gene interaction in detail. The dynamics of discrete model revealed, imperative behaviors represented as cyclic paths and trajectories leading to pathogenic states such as metastasis. Results suggest that the increased expressions of receptors ER- α , IGF-1R and EGFR slow down the activity of tumor suppressor genes (TSGs) such as BRCA1, p53 and Mdm2 which can lead to metastasis. Therefore, IGF-1R and EGFR are considered as important inhibitory targets to control the metastasis in BC. The in-silico approaches allow us to increase our understanding of the functional properties of living organisms. It opens new avenues of investigations of multiple inhibitory targets (ER- α , IGF-1R and EGFR) for wet lab experiments as well as provided valuable insights in the treatment of cancers such as BC.

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.

Near Infrared Dyes as Lifetime Solvatochromic Probes for Micropolarity Measurements of Biological Systems

PubMed Central

Berezin, Mikhail Y.; Lee, Hyeran; Akers, Walter; Achilefu, Samuel

2007-01-01

The polarity of biological mediums controls a host of physiological processes such as digestion, signaling, transportation, metabolism, and excretion. With the recent widespread use of near-infrared (NIR) fluorescent dyes for biological imaging of cells and living organisms, reporting medium polarity with these dyes would provide invaluable functional information in addition to conventional optical imaging parameters. Here, we report a new approach to determine polarities of macro- and microsystems for in vitro and potential in vivo applications using NIR polymethine molecular probes. Unlike the poor solvatochromic response of NIR dyes in solvents with diverse polarity, their fluorescence lifetimes are highly sensitive, increasing by a factor of up to 8 on moving from polar to nonpolar mediums. We also established a correlation between fluorescence lifetime and solvent orientation polarizability and developed a lifetime polarity index for determining the polarity of complex systems, including micelles and albumin binding sites. Because of the importance of medium polarity in molecular, cellular, and biochemical processes and the significance of reduced autofluorescence and deep tissue penetration of light in the NIR region, the findings reported herein represent an important advance toward using NIR molecular probes to measure the polarity of complex biological systems in vitro and in vivo. PMID:17573433

SABRE: a bio-inspired fault-tolerant electronic architecture.

PubMed

Bremner, P; Liu, Y; Samie, M; Dragffy, G; Pipe, A G; Tempesti, G; Timmis, J; Tyrrell, A M

2013-03-01

As electronic devices become increasingly complex, ensuring their reliable, fault-free operation is becoming correspondingly more challenging. It can be observed that, in spite of their complexity, biological systems are highly reliable and fault tolerant. Hence, we are motivated to take inspiration for biological systems in the design of electronic ones. In SABRE (self-healing cellular architectures for biologically inspired highly reliable electronic systems), we have designed a bio-inspired fault-tolerant hierarchical architecture for this purpose. As in biology, the foundation for the whole system is cellular in nature, with each cell able to detect faults in its operation and trigger intra-cellular or extra-cellular repair as required. At the next level in the hierarchy, arrays of cells are configured and controlled as function units in a transport triggered architecture (TTA), which is able to perform partial-dynamic reconfiguration to rectify problems that cannot be solved at the cellular level. Each TTA is, in turn, part of a larger multi-processor system which employs coarser grain reconfiguration to tolerate faults that cause a processor to fail. In this paper, we describe the details of operation of each layer of the SABRE hierarchy, and how these layers interact to provide a high systemic level of fault tolerance.

Interactions of platinum metals and their complexes in biological systems.

PubMed Central

LeRoy, A F

1975-01-01

Platinum-metal oxidation catalysts are to be introduced in exhaust systems of many 1975 model-year automobiles in the U.S. to meet Clean Air Act standards. Small quantities of finely divided catalyst have been found issuing from prototype systems; platinum and palladium compounds may be found also. Although platinum exhibits a remarkable resistance to oxidation and chemical attack, it reacts chemically under some conditions producing coordination complex compounds. Palladium reacts more readily than platinum. Some platinum-metal complexes interact with biological systems as bacteriostatic, bacteriocidal, viricidal, and immunosuppressive agents. Workers chronically exposed to platinum complexes often develop asthma-like respiratory distress and skin reactions called platinosis. Platinum complexes used alone and in combination therapy with other drugs have recently emerged as effective agents in cancer chemotherapy. Understanding toxic and favorable interactions of metal species with living organisms requires basic information on quantities and chemical characteristics of complexes at trace concentrations in biological materials. Some basic chemical kinetic and thermodynamic data are presented to characterize the chemical behavior of the complex cis-[Pt(NH3)2Cl2] used therapeutically. A brief discussion of platinum at manogram levels in biological tissue is discussed. PMID:50943

Functional characterization of EZH2β reveals the increased complexity of EZH2 isoforms involved in the regulation of mammalian gene expression

PubMed Central

2013-01-01

Background Histone methyltransferase enhancer of zeste homologue 2 (EZH2) forms an obligate repressive complex with suppressor of zeste 12 and embryonic ectoderm development, which is thought, along with EZH1, to be primarily responsible for mediating Polycomb-dependent gene silencing. Polycomb-mediated repression influences gene expression across the entire gamut of biological processes, including development, differentiation and cellular proliferation. Deregulation of EZH2 expression is implicated in numerous complex human diseases. To date, most EZH2-mediated function has been primarily ascribed to a single protein product of the EZH2 locus. Results We report that the EZH2 locus undergoes alternative splicing to yield at least two structurally and functionally distinct EZH2 methyltransferases. The longest protein encoded by this locus is the conventional enzyme, which we refer to as EZH2α, whereas EZH2β, characterized here, represents a novel isoform. We find that EZH2β localizes to the cell nucleus, complexes with embryonic ectoderm development and suppressor of zeste 12, trimethylates histone 3 at lysine 27, and mediates silencing of target promoters. At the cell biological level, we find that increased EZH2β induces cell proliferation, demonstrating that this protein is functional in the regulation of processes previously attributed to EZH2α. Biochemically, through the use of genome-wide expression profiling, we demonstrate that EZH2β governs a pattern of gene repression that is often ontologically redundant from that of EZH2α, but also divergent for a wide variety of specific target genes. Conclusions Combined, these results demonstrate that an expanded repertoire of EZH2 writers can modulate histone code instruction during histone 3 lysine 27-mediated gene silencing. These data support the notion that the regulation of EZH2-mediated gene silencing is more complex than previously anticipated and should guide the design and interpretation of future studies aimed at understanding the biochemical and biological roles of this important family of epigenomic regulators. PMID:23448518

Just working with the cellular machine: A high school game for teaching molecular biology.

PubMed

Cardoso, Fernanda Serpa; Dumpel, Renata; da Silva, Luisa B Gomes; Rodrigues, Carlos R; Santos, Dilvani O; Cabral, Lucio Mendes; Castro, Helena C

2008-03-01

Molecular biology is a difficult comprehension subject due to its high complexity, thus requiring new teaching approaches. Herein, we developed an interdisciplinary board game involving the human immune system response against a bacterial infection for teaching molecular biology at high school. Initially, we created a database with several questions and a game story that invites the students for helping the human immunological system to produce antibodies (IgG) and fight back a pathogenic bacterium second-time invasion. The game involves answering questions completing the game board in which the antibodies "are synthesized" through the molecular biology process. At the end, a problem-based learning approach is used, and a last question is raised about proteins. Biology teachers and high school students evaluated the game and considered it an easy and interesting tool for teaching the theme. An increase of about 5-30% in answering molecular biology questions revealed that the game improves learning and induced a more engaged and proactive learning profile in the high school students. Copyright © 2008 International Union of Biochemistry and Molecular Biology, Inc.

Towards Engineering Biological Systems in a Broader Context.

PubMed

Venturelli, Ophelia S; Egbert, Robert G; Arkin, Adam P

2016-02-27

Significant advances have been made in synthetic biology to program information processing capabilities in cells. While these designs can function predictably in controlled laboratory environments, the reliability of these devices in complex, temporally changing environments has not yet been characterized. As human society faces global challenges in agriculture, human health and energy, synthetic biology should develop predictive design principles for biological systems operating in complex environments. Natural biological systems have evolved mechanisms to overcome innumerable and diverse environmental challenges. Evolutionary design rules should be extracted and adapted to engineer stable and predictable ecological function. We highlight examples of natural biological responses spanning the cellular, population and microbial community levels that show promise in synthetic biology contexts. We argue that synthetic circuits embedded in host organisms or designed ecologies informed by suitable measurement of biotic and abiotic environmental parameters could be used as engineering substrates to achieve target functions in complex environments. Successful implementation of these methods will broaden the context in which synthetic biological systems can be applied to solve important problems. Copyright © 2015 Elsevier Ltd. All rights reserved.

Evolution of complex life cycles in trophically transmitted helminths. I. Host incorporation and trophic ascent.

PubMed

Parker, G A; Ball, M A; Chubb, J C

2015-02-01

Links between parasites and food webs are evolutionarily ancient but dynamic: life history theory provides insights into helminth complex life cycle origins. Most adult helminths benefit by sexual reproduction in vertebrates, often high up food chains, but direct infection is commonly constrained by a trophic vacuum between free-living propagules and definitive hosts. Intermediate hosts fill this vacuum, facilitating transmission to definitive hosts. The central question concerns why sexual reproduction, and sometimes even larval growth, is suppressed in intermediate hosts, favouring growth arrest at larval maturity in intermediate hosts and reproductive suppression until transmission to definitive hosts? Increased longevity and higher growth in definitive hosts can generate selection for larger parasite body size and higher fecundity at sexual maturity. Life cycle length is increased by two evolutionary mechanisms, upward and downward incorporation, allowing simple (one-host) cycles to become complex (multihost). In downward incorporation, an intermediate host is added below the definitive host: models suggest that downward incorporation probably evolves only after ecological or evolutionary perturbations create a trophic vacuum. In upward incorporation, a new definitive host is added above the original definitive host, which subsequently becomes an intermediate host, again maintained by the trophic vacuum: theory suggests that this is plausible even under constant ecological/evolutionary conditions. The final cycle is similar irrespective of its origin (upward or downward). Insights about host incorporation are best gained by linking comparative phylogenetic analyses (describing evolutionary history) with evolutionary models (examining selective forces). Ascent of host trophic levels and evolution of optimal host taxa ranges are discussed. © 2015 European Society For Evolutionary Biology. Journal of Evolutionary Biology © 2015 European Society For Evolutionary Biology.

Omega-3 fatty acids: new insights into the pharmacology and biology of docosahexaenoic acid, docosapentaenoic acid, and eicosapentaenoic acid.

PubMed

Davidson, Michael H

2013-12-01

Fish oil contains a complex mixture of omega-3 fatty acids, which are predominantly eicosapentaenoic acid (EPA), docosapentaenoic acid, and docosahexaenoic acid (DHA). Each of these omega-3 fatty acids has distinct biological effects that may have variable clinical effects. In addition, plasma levels of omega-3 fatty acids are affected not only by dietary intake, but also by the polymorphisms of coding genes fatty acid desaturase 1-3 for the desaturase enzymes that convert short-chain polyunsaturated fatty acids to long-chain polyunsaturated fatty acids. The clinical significance of this new understanding regarding the complexity of omega-3 fatty acid biology is the purpose of this review. FADS polymorphisms that result in either lower levels of long-chain omega-3 fatty acids or higher levels of long-chain omega-6 polyunsaturated fatty acids, such as arachidonic acid, are associated with dyslipidemia and other cardiovascular risk factors. EPA and DHA have differences in their effects on lipoprotein metabolism, in which EPA, with a more potent peroxisome proliferator-activated receptor-alpha effect, decreases hepatic lipogenesis, whereas DHA not only enhances VLDL lipolysis, resulting in greater conversion to LDL, but also increases HDL cholesterol and larger, more buoyant LDL particles. Overall, these results emphasize that blood concentrations of individual long-chain polyunsaturated fatty acids, which reflect both dietary intake and metabolic influences, may have independent, but also complementary- biological effects and reinforce the need to potentially provide a complex mixture of omega-3 fatty acids to maximize cardiovascular risk reduction.

Network biology: Describing biological systems by complex networks. Comment on "Network science of biological systems at different scales: A review" by M. Gosak et al.

NASA Astrophysics Data System (ADS)

Jalili, Mahdi

2018-03-01

I enjoyed reading Gosak et al. review on analysing biological systems from network science perspective [1]. Network science, first started within Physics community, is now a mature multidisciplinary field of science with many applications ranging from Ecology to biology, medicine, social sciences, engineering and computer science. Gosak et al. discussed how biological systems can be modelled and described by complex network theory which is an important application of network science. Although there has been considerable progress in network biology over the past two decades, this is just the beginning and network science has a great deal to offer to biology and medical sciences.

How Community Has Shaped the Protein Data Bank

PubMed Central

Berman, Helen M.; Kleywegt, Gerard J.; Nakamura, Haruki; Markley, John L.

2015-01-01

Following several years of community discussion, the Protein Data Bank (PDB) was established in 1971 as a public repository for the coordinates of three-dimensional models of biological macromolecules. Since then, the number, size, and complexity of structural models have continued to grow, reflecting the productivity of structural biology. Managed by the Worldwide PDB organization, the PDB has been able to meet increasing demands for the quantity of structural information and of quality. In addition to providing unrestricted access to structural information, the PDB also works to promote data standards and to raise the profile of structural biology with broader audiences. In this perspective, we describe the history of PDB and the many ways in which the community continues to shape the archive. PMID:24010707

Synthesis, structural elucidation, biological, antioxidant and nuclease activities of some 5-Fluorouracil-amino acid mixed ligand complexes

NASA Astrophysics Data System (ADS)

Shobana, Sutha; Subramaniam, Perumal; Mitu, Liviu; Dharmaraja, Jeyaprakash; Arvind Narayan, Sundaram

2015-01-01

Some biologically active mixed ligand complexes (1-9) have been synthesized from 5-Fluorouracil (5-FU; A) and amino acids (B) such as glycine (gly), L-alanine (ala) and L-valine (val) with Ni(II), Cu(II) and Zn(II) ions. The synthesized mixed ligand complexes (1-9) were characterized by various physico-chemical, spectral, thermal and morphological studies. 5-Fluorouracil and its mixed ligand complexes have been tested for their in vitro biological activities against some pathogenic bacterial and fungal species by the agar well diffusion method. The in vitro antioxidant activities of 5-Fluorouracil and its complexes have also been investigated by using the DPPH assay method. The results demonstrate that Cu(II) mixed ligand complexes (4-6) exhibit potent biological as well as antioxidant activities compared to 5-Fluorouracil and Ni(II) (1-3) and Zn(II) (7-9) mixed ligand complexes. Further, the cleaving activities of CT DNA under aerobic conditions show moderate activity with the synthesized Cu(II) and Ni(II) mixed ligand complexes (1-6) while no activity is seen with Zn(II) complexes (7-9). Binding studies of CT DNA with these complexes show a decrease in intensity of the charge transfer band to the extent of 5-15% along with a minor red shift. The free energy change values (Δ‡G) calculated from intrinsic binding constants indicate that the interaction between mixed ligand complex and DNA is spontaneous.

Structure and Bonding in Heme-Nitrosyl Complexes and Implications for Biology

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

Lehnert, Nicolai; Scheidt, W. Robert; Wolf, Matthew W.

This review summarizes our current understanding of the geometric and electronic structures of ferrous and ferric heme–nitrosyls, which are of key importance for the biological functions and transformations of NO. In-depth correlations are made between these properties and the reactivities of these species. Here, a focus is put on the discoveries that have been made in the last 10 years, but previous findings are also included as necessary. Besides this, ferrous heme–nitroxyl complexes are also considered, which have become of increasing interest recently due to their roles as intermediates in NO and multiheme nitrite reductases, and because of the potentialmore » role of HNO as a signaling molecule in mammals. In recent years, computational methods have received more attention as a means of investigating enzyme reaction mechanisms, and some important findings from these theoretical studies are also highlighted in this chapter.« less

Impact of reclamation treatment on the biological activity of soils of the solonetz complex in Western Siberia

NASA Astrophysics Data System (ADS)

Berezin, L. V.; Khamova, O. F.; Paderina, E. V.; Gindemit, A. M.

2014-11-01

The abundance and activity of the soil microflora were studied in a field experiment with the use of green manure crops to assess the impact of reclamation measures on the biological activity of soils of the solonetz complex. The number of microorganisms in the plow soil horizon increased in the background of the green fallows as compared to the black ones. Coefficients of mineralization, immobilization, and transformation of organic compounds were calculated for different variants of the soil treatment. The value of the mineralization coefficient indicates the intense decomposition of the green manure that entered the soil. In the first year, peas were actively decomposed, while oats, in the second year (aftereffect). The activity of the soil enzymes (invertase, urease, and catalase) was determined. A close relationship between the catalase activity and the intensity of the microbiological processes in the soils was revealed.

TASI: A software tool for spatial-temporal quantification of tumor spheroid dynamics.

PubMed

Hou, Yue; Konen, Jessica; Brat, Daniel J; Marcus, Adam I; Cooper, Lee A D

2018-05-08

Spheroid cultures derived from explanted cancer specimens are an increasingly utilized resource for studying complex biological processes like tumor cell invasion and metastasis, representing an important bridge between the simplicity and practicality of 2-dimensional monolayer cultures and the complexity and realism of in vivo animal models. Temporal imaging of spheroids can capture the dynamics of cell behaviors and microenvironments, and when combined with quantitative image analysis methods, enables deep interrogation of biological mechanisms. This paper presents a comprehensive open-source software framework for Temporal Analysis of Spheroid Imaging (TASI) that allows investigators to objectively characterize spheroid growth and invasion dynamics. TASI performs spatiotemporal segmentation of spheroid cultures, extraction of features describing spheroid morpho-phenotypes, mathematical modeling of spheroid dynamics, and statistical comparisons of experimental conditions. We demonstrate the utility of this tool in an analysis of non-small cell lung cancer spheroids that exhibit variability in metastatic and proliferative behaviors.

The receptive field is dead. Long live the receptive field?

PubMed Central

Fairhall, Adrienne

2014-01-01

Advances in experimental techniques, including behavioral paradigms using rich stimuli under closed loop conditions and the interfacing of neural systems with external inputs and outputs, reveal complex dynamics in the neural code and require a revisiting of standard concepts of representation. High-throughput recording and imaging methods along with the ability to observe and control neuronal subpopulations allow increasingly detailed access to the neural circuitry that subserves these representations and the computations they support. How do we harness theory to build biologically grounded models of complex neural function? PMID:24618227

Spectral characterization, cyclic voltammetry, morphology, biological activities and DNA cleaving studies of amino acid Schiff base metal(II) complexes

NASA Astrophysics Data System (ADS)

Neelakantan, M. A.; Rusalraj, F.; Dharmaraja, J.; Johnsonraja, S.; Jeyakumar, T.; Sankaranarayana Pillai, M.

2008-12-01

Metal complexes are synthesized with Schiff bases derived from o-phthalaldehyde (opa) and amino acids viz., glycine (gly) L-alanine (ala), L-phenylalanine (pal). Metal ions coordinate in a tetradentate or hexadentate manner with these N 2O 2 donor ligands, which are characterized by elemental analysis, molar conductance, magnetic moments, IR, electronic, 1H NMR and EPR spectral studies. The elemental analysis suggests the stoichiometry to be 1:1 (metal:ligand). Based on EPR studies, spin-Hamiltonian and bonding parameters have been calculated. The g-values calculated for copper complexes at 300 K and in frozen DMSO (77 K) indicate the presence of the unpaired electron in the d orbital. The evaluated metal-ligand bonding parameters showed strong in-plane σ- and π-bonding. X-ray diffraction (XRD) and scanning electron micrography (SEM) analysis provide the crystalline nature and the morphology of the metal complexes. The cyclic voltammograms of the Cu(II)/Mn(II)/VO(II) complexes investigated in DMSO solution exhibit metal centered electroactivity in the potential range -1.5 to +1.5 V. The electrochemical data obtained for Cu(II) complexes explains the change of structural arrangement of the ligand around Cu(II) ions. The biological activity of the complexes has been tested on eight bacteria and three fungi. Cu(II) and Ni(II) complexes show an increased activity in comparison to the controls. The metal complexes of opapal Schiff base were evaluated for their DNA cleaving activities with calf-thymus DNA (CT DNA) under aerobic conditions. Cu(II) and VO(II) complexes show more pronounced activity in presence of the oxidant.

Physicochemical and in vitro biological evaluations of furazolidone-based β-cyclodextrin complexes in Leishmania amazonensis.

PubMed

Carvalho, Suzana Gonçalves; Siqueira, Larissa Ataíde; Zanini, Marcos Santos; Dos Santos Matos, Ana Paula; Quaresma, Carla Holandino; da Silva, Luisa Mota; de Andrade, Sérgio Faloni; Severi, Juliana Aparecida; Villanova, Janaina Cecília Oliveira

2018-06-15

Recently, there have been numerous cases of leishmaniasis reported in different Brazilian states. The use of furazolidone (FZD) to treat leishmaniasis has been previously described; however, the drug is associated with adverse effects such as anorexia, weight loss, incoordination, and fatigue in dogs. Thus, in the present study, we prepared and evaluated inclusion complexes between FZD and β-cyclodextrin (β-CD) to guarantee increased drug solubility and reduce the toxicity associated with high doses. The FZD:β-CD complexes were prepared by two different techniques (kneading and lyophilization) prior to incorporation in an oral pharmaceutical dosage form. Formation of the complexes was confirmed using appropriate physicochemical methods. Antileishmanial activity against L. amazonensis was tested in vitro via a microplate assay using resazurin dye and cytotoxicity was determined using the fibroblast L929 lineage. Solubility studies showed the formation of complexes with complexation efficiencies lower than 100%. Physicochemical analysis revealed that FZD was inserted into the β-CD cavity after complexation by both methods. Biological in vitro evaluations demonstrated that free FZD and the FZD:β-CD complexes presented significant leishmanicidal activity against L. amazonensis with IC 50 values of 6.16 μg/mL and 1.83 μg/mL for the complexes prepared by kneading and lyophilization, respectively. The data showed that these complexes reduced the survival of promastigotes and presented no toxicity for tested cells. Our results indicate that the new compounds could be a cost-effective alternative for use in the pharmacotherapy of leishmaniasis in dogs infected with L. amazonensis. Copyright © 2018 Elsevier Ltd. All rights reserved.

Introduction to biological complexity as a missing link in drug discovery.

PubMed

Gintant, Gary A; George, Christopher H

2018-06-06

Despite a burgeoning knowledge of the intricacies and mechanisms responsible for human disease, technological advances in medicinal chemistry, and more efficient assays used for drug screening, it remains difficult to discover novel and effective pharmacologic therapies. Areas covered: By reference to the primary literature and concepts emerging from academic and industrial drug screening landscapes, the authors propose that this disconnect arises from the inability to scale and integrate responses from simpler model systems to outcomes from more complex and human-based biological systems. Expert opinion: Further collaborative efforts combining target-based and phenotypic-based screening along with systems-based pharmacology and informatics will be necessary to harness the technological breakthroughs of today to derive the novel drug candidates of tomorrow. New questions must be asked of enabling technologies-while recognizing inherent limitations-in a way that moves drug development forward. Attempts to integrate mechanistic and observational information acquired across multiple scales frequently expose the gap between our knowledge and our understanding as the level of complexity increases. We hope that the thoughts and actionable items highlighted will help to inform the directed evolution of the drug discovery process.

Protocols and characterization data for 2D, 3D, and slice-based tumor models from the PREDECT project.

PubMed

de Hoogt, Ronald; Estrada, Marta F; Vidic, Suzana; Davies, Emma J; Osswald, Annika; Barbier, Michael; Santo, Vítor E; Gjerde, Kjersti; van Zoggel, Hanneke J A A; Blom, Sami; Dong, Meng; Närhi, Katja; Boghaert, Erwin; Brito, Catarina; Chong, Yolanda; Sommergruber, Wolfgang; van der Kuip, Heiko; van Weerden, Wytske M; Verschuren, Emmy W; Hickman, John; Graeser, Ralph

2017-11-21

Two-dimensional (2D) culture of cancer cells in vitro does not recapitulate the three-dimensional (3D) architecture, heterogeneity and complexity of human tumors. More representative models are required that better reflect key aspects of tumor biology. These are essential studies of cancer biology and immunology as well as for target validation and drug discovery. The Innovative Medicines Initiative (IMI) consortium PREDECT (www.predect.eu) characterized in vitro models of three solid tumor types with the goal to capture elements of tumor complexity and heterogeneity. 2D culture and 3D mono- and stromal co-cultures of increasing complexity, and precision-cut tumor slice models were established. Robust protocols for the generation of these platforms are described. Tissue microarrays were prepared from all the models, permitting immunohistochemical analysis of individual cells, capturing heterogeneity. 3D cultures were also characterized using image analysis. Detailed step-by-step protocols, exemplary datasets from the 2D, 3D, and slice models, and refined analytical methods were established and are presented.

Protocols and characterization data for 2D, 3D, and slice-based tumor models from the PREDECT project

PubMed Central

de Hoogt, Ronald; Estrada, Marta F.; Vidic, Suzana; Davies, Emma J.; Osswald, Annika; Barbier, Michael; Santo, Vítor E.; Gjerde, Kjersti; van Zoggel, Hanneke J. A. A.; Blom, Sami; Dong, Meng; Närhi, Katja; Boghaert, Erwin; Brito, Catarina; Chong, Yolanda; Sommergruber, Wolfgang; van der Kuip, Heiko; van Weerden, Wytske M.; Verschuren, Emmy W.; Hickman, John; Graeser, Ralph

2017-01-01

Two-dimensional (2D) culture of cancer cells in vitro does not recapitulate the three-dimensional (3D) architecture, heterogeneity and complexity of human tumors. More representative models are required that better reflect key aspects of tumor biology. These are essential studies of cancer biology and immunology as well as for target validation and drug discovery. The Innovative Medicines Initiative (IMI) consortium PREDECT (www.predect.eu) characterized in vitro models of three solid tumor types with the goal to capture elements of tumor complexity and heterogeneity. 2D culture and 3D mono- and stromal co-cultures of increasing complexity, and precision-cut tumor slice models were established. Robust protocols for the generation of these platforms are described. Tissue microarrays were prepared from all the models, permitting immunohistochemical analysis of individual cells, capturing heterogeneity. 3D cultures were also characterized using image analysis. Detailed step-by-step protocols, exemplary datasets from the 2D, 3D, and slice models, and refined analytical methods were established and are presented. PMID:29160867

Antibody profiling sensitivity through increased reporter antibody layering

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

Apel, William A.; Thompson, Vicki S

A method for analyzing a biological sample by antibody profiling for identifying forensic samples or for detecting the presence of an analyte. In an embodiment of the invention, the analyte is a drug, such as marijuana, Cocaine (crystalline tropane alkaloid), methamphetamine, methyltestosterone, or mesterolone. The method comprises attaching antigens to a surface of a solid support in a preselected pattern to form an array wherein locations of the antigens are known; contacting the array with the biological sample such that a portion of antibodies in the sample reacts with and binds to the antigens in the array to form immunemore » complexes; washing away antibodies that do form immune complexes; and detecting the immune complexes, to form an antibody profile. Forensic samples are identified by comparing a sample from an unknown source with a sample from a known source. Further, an assay, such as a test for illegal drug use, can be coupled to a test for identity such that the results of the assay can be positively correlated to the subject's identity.« less

How can we improve problem solving in undergraduate biology? Applying lessons from 30 years of physics education research.

PubMed

Hoskinson, A-M; Caballero, M D; Knight, J K

2013-06-01

If students are to successfully grapple with authentic, complex biological problems as scientists and citizens, they need practice solving such problems during their undergraduate years. Physics education researchers have investigated student problem solving for the past three decades. Although physics and biology problems differ in structure and content, the instructional purposes align closely: explaining patterns and processes in the natural world and making predictions about physical and biological systems. In this paper, we discuss how research-supported approaches developed by physics education researchers can be adopted by biologists to enhance student problem-solving skills. First, we compare the problems that biology students are typically asked to solve with authentic, complex problems. We then describe the development of research-validated physics curricula emphasizing process skills in problem solving. We show that solving authentic, complex biology problems requires many of the same skills that practicing physicists and biologists use in representing problems, seeking relationships, making predictions, and verifying or checking solutions. We assert that acquiring these skills can help biology students become competent problem solvers. Finally, we propose how biology scholars can apply lessons from physics education in their classrooms and inspire new studies in biology education research.

Biological design in science classrooms

PubMed Central

Scott, Eugenie C.; Matzke, Nicholas J.

2007-01-01

Although evolutionary biology is replete with explanations for complex biological structures, scientists concerned about evolution education have been forced to confront “intelligent design” (ID), which rejects a natural origin for biological complexity. The content of ID is a subset of the claims made by the older “creation science” movement. Both creationist views contend that highly complex biological adaptations and even organisms categorically cannot result from natural causes but require a supernatural creative agent. Historically, ID arose from efforts to produce a form of creationism that would be less vulnerable to legal challenges and that would not overtly rely upon biblical literalism. Scientists do not use ID to explain nature, but because it has support from outside the scientific community, ID is nonetheless contributing substantially to a long-standing assault on the integrity of science education. PMID:17494747

Electron and Ion Reactions in Molecular Solids: from astrochemistry to radiobiology

NASA Astrophysics Data System (ADS)

Huels, Michael A.

2001-05-01

Wherever ionizing radiation interacts with matter, it initiates reaction cascades involving ions, radicals, and ballistic secondary electrons; these reactions occur on fs time-scales, and may lead to substantial physical and chemical modifications of a medium. Here I present measurements of 0-80 eV electron and ion reactions in condensed films ranging from simple to complex, and astrophysical to biological in nature. Targets contain either: small molecules, hydrocarbons of increasing complexity (incl. bases, sugars, single/double stranded DNA), molecules on rare gas matrices, or mixed cryogenic films resembling astrophysical or planetary surface ices containing O2, H2O, methane, and aromatic hydrocarbons. The basic electron or ion reaction mechanisms and pathways are found to be fundamentally universal, but are modulated by the physical and chemical nature of the medium; depending on the latter, a reaction cascade may lead to different end-points, e.g. a decrease in molecular complexity via molecular fragmentations, or increases in complexity via secondary ion collision induced synthesis of larger molecules in hydrocarbon rich surface ices.

Modelling protein functional domains in signal transduction using Maude

NASA Technical Reports Server (NTRS)

Sriram, M. G.

2003-01-01

Modelling of protein-protein interactions in signal transduction is receiving increased attention in computational biology. This paper describes recent research in the application of Maude, a symbolic language founded on rewriting logic, to the modelling of functional domains within signalling proteins. Protein functional domains (PFDs) are a critical focus of modern signal transduction research. In general, Maude models can simulate biological signalling networks and produce specific testable hypotheses at various levels of abstraction. Developing symbolic models of signalling proteins containing functional domains is important because of the potential to generate analyses of complex signalling networks based on structure-function relationships.

Deconstructing the core dynamics from a complex time-lagged regulatory biological circuit.

PubMed

Eriksson, O; Brinne, B; Zhou, Y; Björkegren, J; Tegnér, J

2009-03-01

Complex regulatory dynamics is ubiquitous in molecular networks composed of genes and proteins. Recent progress in computational biology and its application to molecular data generate a growing number of complex networks. Yet, it has been difficult to understand the governing principles of these networks beyond graphical analysis or extensive numerical simulations. Here the authors exploit several simplifying biological circumstances which thereby enable to directly detect the underlying dynamical regularities driving periodic oscillations in a dynamical nonlinear computational model of a protein-protein network. System analysis is performed using the cell cycle, a mathematically well-described complex regulatory circuit driven by external signals. By introducing an explicit time delay and using a 'tearing-and-zooming' approach the authors reduce the system to a piecewise linear system with two variables that capture the dynamics of this complex network. A key step in the analysis is the identification of functional subsystems by identifying the relations between state-variables within the model. These functional subsystems are referred to as dynamical modules operating as sensitive switches in the original complex model. By using reduced mathematical representations of the subsystems the authors derive explicit conditions on how the cell cycle dynamics depends on system parameters, and can, for the first time, analyse and prove global conditions for system stability. The approach which includes utilising biological simplifying conditions, identification of dynamical modules and mathematical reduction of the model complexity may be applicable to other well-characterised biological regulatory circuits. [Includes supplementary material].

Comprehensive inventory of protein complexes in the Protein Data Bank from consistent classification of interfaces.

PubMed

Bordner, Andrew J; Gorin, Andrey A

2008-05-12

Protein-protein interactions are ubiquitous and essential for all cellular processes. High-resolution X-ray crystallographic structures of protein complexes can reveal the details of their function and provide a basis for many computational and experimental approaches. Differentiation between biological and non-biological contacts and reconstruction of the intact complex is a challenging computational problem. A successful solution can provide additional insights into the fundamental principles of biological recognition and reduce errors in many algorithms and databases utilizing interaction information extracted from the Protein Data Bank (PDB). We have developed a method for identifying protein complexes in the PDB X-ray structures by a four step procedure: (1) comprehensively collecting all protein-protein interfaces; (2) clustering similar protein-protein interfaces together; (3) estimating the probability that each cluster is relevant based on a diverse set of properties; and (4) combining these scores for each PDB entry in order to predict the complex structure. The resulting clusters of biologically relevant interfaces provide a reliable catalog of evolutionary conserved protein-protein interactions. These interfaces, as well as the predicted protein complexes, are available from the Protein Interface Server (PInS) website (see Availability and requirements section). Our method demonstrates an almost two-fold reduction of the annotation error rate as evaluated on a large benchmark set of complexes validated from the literature. We also estimate relative contributions of each interface property to the accurate discrimination of biologically relevant interfaces and discuss possible directions for further improving the prediction method.

From the Director: The Joy of Science, the Courage of Research

MedlinePlus

... Dr. Zerhouni , one that combines an appreciation of biological complexity with the fearless search for scientific knowledge. ... techniques for greater understanding of the complexity of biological systems. The one thing that has driven my ...

Cross-Linking and Mass Spectrometry Methodologies to Facilitate Structural Biology: Finding a Path through the Maze

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

Merkley, Eric D.; Cort, John R.; Adkins, Joshua N.

2013-09-01

Multiprotein complexes, rather than individual proteins, make up a large part of the biological macromolecular machinery of a cell. Understanding the structure and organization of these complexes is critical to understanding cellular function. Chemical cross-linking coupled with mass spectrometry is emerging as a complementary technique to traditional structural biology methods and can provide low-resolution structural information for a multitude of purposes, such as distance constraints in computational modeling of protein complexes. In this review, we discuss the experimental considerations for successful application of chemical cross-linking-mass spectrometry in biological studies and highlight three examples of such studies from the recent literature.more » These examples (as well as many others) illustrate the utility of a chemical cross-linking-mass spectrometry approach in facilitating structural analysis of large and challenging complexes.« less

Colloquium paper: bioenergetics, the origins of complexity, and the ascent of man.

PubMed

Wallace, Douglas C

2010-05-11

Complex structures are generated and maintained through energy flux. Structures embody information, and biological information is stored in nucleic acids. The progressive increase in biological complexity over geologic time is thus the consequence of the information-generating power of energy flow plus the information-accumulating capacity of DNA, winnowed by natural selection. Consequently, the most important component of the biological environment is energy flow: the availability of calories and their use for growth, survival, and reproduction. Animals can exploit and adapt to available energy resources at three levels. They can evolve different anatomical forms through nuclear DNA (nDNA) mutations permitting exploitation of alternative energy reservoirs, resulting in new species. They can evolve modified bioenergetic physiologies within a species, primarily through the high mutation rate of mitochondrial DNA (mtDNA)-encoded bioenergetic genes, permitting adjustment to regional energetic environments. They can alter the epigenomic regulation of the thousands of dispersed bioenergetic genes via mitochondrially generated high-energy intermediates permitting individual accommodation to short-term environmental energetic fluctuations. Because medicine pertains to a single species, Homo sapiens, functional human variation often involves sequence changes in bioenergetic genes, most commonly mtDNA mutations, plus changes in the expression of bioenergetic genes mediated by the epigenome. Consequently, common nDNA polymorphisms in anatomical genes may represent only a fraction of the genetic variation associated with the common "complex" diseases, and the ascent of man has been the product of 3.5 billion years of information generation by energy flow, accumulated and preserved in DNA and edited by natural selection.

Multiple Replica Repulsion Technique for Efficient Conformational Sampling of Biological Systems

PubMed Central

Malevanets, Anatoly; Wodak, Shoshana J.

2011-01-01

Here, we propose a technique for sampling complex molecular systems with many degrees of freedom. The technique, termed “multiple replica repulsion” (MRR), does not suffer from poor scaling with the number of degrees of freedom associated with common replica exchange procedures and does not require sampling at high temperatures. The algorithm involves creation of multiple copies (replicas) of the system, which interact with one another through a repulsive potential that can be applied to the system as a whole or to portions of it. The proposed scheme prevents oversampling of the most populated states and provides accurate descriptions of conformational perturbations typically associated with sampling ground-state energy wells. The performance of MRR is illustrated for three systems of increasing complexity. A two-dimensional toy potential surface is used to probe the sampling efficiency as a function of key parameters of the procedure. MRR simulations of the Met-enkephalin pentapeptide, and the 76-residue protein ubiquitin, performed in presence of explicit water molecules and totaling 32 ns each, investigate the ability of MRR to characterize the conformational landscape of the peptide, and the protein native basin, respectively. Results obtained for the enkephalin peptide reflect more closely the extensive conformational flexibility of this peptide than previously reported simulations. Those obtained for ubiquitin show that conformational ensembles sampled by MRR largely encompass structural fluctuations relevant to biological recognition, which occur on the microsecond timescale, or are observed in crystal structures of ubiquitin complexes with other proteins. MRR thus emerges as a very promising simple and versatile technique for modeling the structural plasticity of complex biological systems. PMID:21843487

Rhodium complexes as therapeutic agents.

PubMed

Ma, Dik-Lung; Wang, Modi; Mao, Zhifeng; Yang, Chao; Ng, Chan-Tat; Leung, Chung-Hang

2016-02-21

The landscape of inorganic medicinal chemistry has been dominated by the investigation of platinum, and to a lesser extent ruthenium, complexes over the past few decades. Recently, complexes based on other metal centers such as rhodium have attracted attention due to their tunable chemical and biological properties as well as distinct mechanisms of action. This perspective highlights recent examples of rhodium complexes that show diverse biological activities against various targets, including enzymes and protein-protein interactions.

Physicochemical and biological properties of oxovanadium(IV), cobalt(II) and nickel(II) complexes with oxydiacetate anions.

PubMed

Wyrzykowski, Dariusz; Kloska, Anna; Pranczk, Joanna; Szczepańska, Aneta; Tesmar, Aleksandra; Jacewicz, Dagmara; Pilarski, Bogusław; Chmurzyński, Lech

2015-03-01

The potentiometric and conductometric titration methods have been used to characterize the stability of series of VO(IV)-, Co(II)- and Ni(II)-oxydiacetato complexes in DMSO-water solutions containing 0-50 % (v/v) DMSO. The influence of DMSO as a co-solvent on the stability of the complexes as well as the oxydiacetic acid was evaluated. Furthermore, the reactivity of the complexes towards superoxide free radicals was assessed by employing the nitro blue tetrazolium (NBT) assay. The biological properties of the complexes were investigated in relation to their cytoprotective activity against the oxidative damage generated exogenously by using hydrogen peroxide in the Human Dermal Fibroblasts adult (HDFa) cell line as well as to their antimicrobial activity against the bacteria (Bacillus subtilis, Escherichia coli, Enterococcus faecalis, Pseudomonas aeruginosa, Staphylococcus aureus, Staphylococcus epidermidis). The relationship between physicochemical and biological properties of the complexes was discussed.

Innate immune response to a bovine mastitis pathogen profiled in milk and blood monocytes using a systems biology approach

USDA-ARS?s Scientific Manuscript database

Bovine mastitis is an inflammatory condition of the mammary gland which leads to reduced milk yield and increased milk somatic cell counts (SCC) resulting in an estimated annual cost to the dairy industry worldwide of ~ 2 billion euros. Mastitis has a complex etiology, with pathogenic, host and envi...

Fundamental Physics Program and the NASA Mission

NASA Technical Reports Server (NTRS)

Trinh, Eugene

2003-01-01

The accomplishments of Physics, the increasing power of its instruments, and its expanding reach into other sciences have generated an unprecedented set of scientific opportunities. The committee has identified six such Grand Challenges listed below in no particular order: Developing quantum technologies. Creating new materials. Understanding complex systems. Unifying the forces of Nature. Exploring the universe Applying Physics to Biology.

Cognitive Flexibility and Undergraduate Physiology Students: Increasing Advanced Knowledge Acquisition within an Ill-Structured Domain

ERIC Educational Resources Information Center

Rhodes, Ashley E.; Rozell, Timothy G.

2017-01-01

Cognitive flexibility is defined as the ability to assimilate previously learned information and concepts to generate novel solutions to new problems. This skill is crucial for success within ill-structured domains such as biology, physiology, and medicine, where many concepts are simultaneously required for understanding a complex problem, yet…

Dynamic-landscape metapopulation models predict complex response of wildlife populations to climate and landscape change

Treesearch

Thomas W. Bonnot; Frank R. Thompson; Joshua J. Millspaugh

2017-01-01

The increasing need to predict how climate change will impact wildlife species has exposed limitations in how well current approaches model important biological processes at scales at which those processes interact with climate. We used a comprehensive approach that combined recent advances in landscape and population modeling into dynamic-landscape metapopulation...

Student Teachers' Pedagogical Content Knowledge for Teaching Systems Thinking: Effects of Different Interventions

ERIC Educational Resources Information Center

Rosenkränzer, Frank; Hörsch, Christian; Schuler, Stephan; Riess, Werner

2017-01-01

Systems' thinking has become increasingly relevant not only in education for sustainable development but also in everyday life. Even if teachers know the dynamics and complexity of living systems in biology and geography, they might not be able to effectively explain it to students. Teachers need an understanding of systems and their behaviour…

New cohort growth and survival in variable retention harvests of a pine ecosystem in Minnesota, USA

Treesearch

Rebecca A. Montgomery; Brian J. Palik; Suzanne B. Boyden; Peter B. Reich

2013-01-01

There is significant interest in silvicultural systems such as variable retention harvesting (VRH) that emulate natural disturbance and increase structural complexity, spatial heterogeneity, and biological diversity in managed forests. However, the consequences of variable retention harvesting for new cohort growth and survival are not well characterized in many forest...

Using synthetic biology to make cells tomorrow's test tubes.

PubMed

Garcia, Hernan G; Brewster, Robert C; Phillips, Rob

2016-04-18

The main tenet of physical biology is that biological phenomena can be subject to the same quantitative and predictive understanding that physics has afforded in the context of inanimate matter. However, the inherent complexity of many of these biological processes often leads to the derivation of complex theoretical descriptions containing a plethora of unknown parameters. Such complex descriptions pose a conceptual challenge to the establishment of a solid basis for predictive biology. In this article, we present various exciting examples of how synthetic biology can be used to simplify biological systems and distill these phenomena down to their essential features as a means to enable their theoretical description. Here, synthetic biology goes beyond previous efforts to engineer nature and becomes a tool to bend nature to understand it. We discuss various recent and classic experiments featuring applications of this synthetic approach to the elucidation of problems ranging from bacteriophage infection, to transcriptional regulation in bacteria and in developing embryos, to evolution. In all of these examples, synthetic biology provides the opportunity to turn cells into the equivalent of a test tube, where biological phenomena can be reconstituted and our theoretical understanding put to test with the same ease that these same phenomena can be studied in the in vitro setting.

Multi-Dimensional Scaling based grouping of known complexes and intelligent protein complex detection.

PubMed

Rehman, Zia Ur; Idris, Adnan; Khan, Asifullah

2018-06-01

Protein-Protein Interactions (PPI) play a vital role in cellular processes and are formed because of thousands of interactions among proteins. Advancements in proteomics technologies have resulted in huge PPI datasets that need to be systematically analyzed. Protein complexes are the locally dense regions in PPI networks, which extend important role in metabolic pathways and gene regulation. In this work, a novel two-phase protein complex detection and grouping mechanism is proposed. In the first phase, topological and biological features are extracted for each complex, and prediction performance is investigated using Bagging based Ensemble classifier (PCD-BEns). Performance evaluation through cross validation shows improvement in comparison to CDIP, MCode, CFinder and PLSMC methods Second phase employs Multi-Dimensional Scaling (MDS) for the grouping of known complexes by exploring inter complex relations. It is experimentally observed that the combination of topological and biological features in the proposed approach has greatly enhanced prediction performance for protein complex detection, which may help to understand various biological processes, whereas application of MDS based exploration may assist in grouping potentially similar complexes. Copyright © 2018 Elsevier Ltd. All rights reserved.

Evolving a lingua franca and associated software infrastructure for computational systems biology: the Systems Biology Markup Language (SBML) project.

PubMed

Hucka, M; Finney, A; Bornstein, B J; Keating, S M; Shapiro, B E; Matthews, J; Kovitz, B L; Schilstra, M J; Funahashi, A; Doyle, J C; Kitano, H

2004-06-01

Biologists are increasingly recognising that computational modelling is crucial for making sense of the vast quantities of complex experimental data that are now being collected. The systems biology field needs agreed-upon information standards if models are to be shared, evaluated and developed cooperatively. Over the last four years, our team has been developing the Systems Biology Markup Language (SBML) in collaboration with an international community of modellers and software developers. SBML has become a de facto standard format for representing formal, quantitative and qualitative models at the level of biochemical reactions and regulatory networks. In this article, we summarise the current and upcoming versions of SBML and our efforts at developing software infrastructure for supporting and broadening its use. We also provide a brief overview of the many SBML-compatible software tools available today.

Active Interaction Mapping as a tool to elucidate hierarchical functions of biological processes.

PubMed

Farré, Jean-Claude; Kramer, Michael; Ideker, Trey; Subramani, Suresh

2017-07-03

Increasingly, various 'omics data are contributing significantly to our understanding of novel biological processes, but it has not been possible to iteratively elucidate hierarchical functions in complex phenomena. We describe a general systems biology approach called Active Interaction Mapping (AI-MAP), which elucidates the hierarchy of functions for any biological process. Existing and new 'omics data sets can be iteratively added to create and improve hierarchical models which enhance our understanding of particular biological processes. The best datatypes to further improve an AI-MAP model are predicted computationally. We applied this approach to our understanding of general and selective autophagy, which are conserved in most eukaryotes, setting the stage for the broader application to other cellular processes of interest. In the particular application to autophagy-related processes, we uncovered and validated new autophagy and autophagy-related processes, expanded known autophagy processes with new components, integrated known non-autophagic processes with autophagy and predict other unexplored connections.

Determining absolute protein numbers by quantitative fluorescence microscopy.

PubMed

Verdaasdonk, Jolien Suzanne; Lawrimore, Josh; Bloom, Kerry

2014-01-01

Biological questions are increasingly being addressed using a wide range of quantitative analytical tools to examine protein complex composition. Knowledge of the absolute number of proteins present provides insights into organization, function, and maintenance and is used in mathematical modeling of complex cellular dynamics. In this chapter, we outline and describe three microscopy-based methods for determining absolute protein numbers--fluorescence correlation spectroscopy, stepwise photobleaching, and ratiometric comparison of fluorescence intensity to known standards. In addition, we discuss the various fluorescently labeled proteins that have been used as standards for both stepwise photobleaching and ratiometric comparison analysis. A detailed procedure for determining absolute protein number by ratiometric comparison is outlined in the second half of this chapter. Counting proteins by quantitative microscopy is a relatively simple yet very powerful analytical tool that will increase our understanding of protein complex composition. © 2014 Elsevier Inc. All rights reserved.

Spectral studies, thermal investigation and biological activity of some metal complexes derived from (E)-N‧-(1-(4-aminophenyl)ethylidene)morpholine-4-carbothiohydrazide

NASA Astrophysics Data System (ADS)

El-Samanody, El-Sayed A.; Polis, Magdy W.; Emara, Esam M.

2017-09-01

A new series of biologically active Co(II), Ni(II), Cu(II), Zn(II) and Cd(II) complexes derived from the novel thiosemicarbazone ligand; (E)-N‧-(1-(4-aminophenyl)ethylidene)morpholine-4-carbothiohydrazide (HL) were synthesized. The mode of bonding of the ligand and the geometrical structures of its metal complexes were achieved by different analytical and spectral methods. The ligand coordinated with metal ions in a neutral bidentate fashion through the thione sulfur and azomethine nitrogen atoms. All metal complexes adopted octahedral geometry, except Cu(II) complexes (3, 6, 7) which have a square planar structure. The general thermal decomposition pathways of the ligand along with its metal complexes were explained. The thermal stability of the complexes is controlled by the number of outer and inner sphere water molecules, ionic radii and the steric hindrance. The activation thermodynamic parameters; (activation energy (E*), enthalpy of activation (ΔH*), entropy of activation (ΔS*) and Gibbs free energy (ΔG*)) along with order of reaction (n) were estimated from DTG curves. The ESR spectra of Cu(II) complexes indicated that (dx2-y2)1 is the ground state with covalence character of metal-ligand bonds. The molluscicidal and biochemical effects of the ligand and its Ni(II); Cu(II) complexes (2; 3, 5, 7) along with their combinations with metaldehyde were screened in vitro on the mucous gland of Eobania vermiculata. The tested compounds exhibited a significant toxicity against the tested animals and have almost the same toxic effect of metaldehyde which increases the mucous secretion of the snails and leads to death.

Self-assembly of polyelectrolyte surfactant complexes using large scale MD simulation

NASA Astrophysics Data System (ADS)

Goswami, Monojoy; Sumpter, Bobby

2014-03-01

Polyelectrolytes (PE) and surfactants are known to form interesting structures with varied properties in aqueous solutions. The morphological details of the PE-surfactant complexes depend on a combination of polymer backbone, electrostatic interactions and hydrophobic interactions. We study the self-assembly of cationic PE and anionic surfactants complexes in dilute condition. The importance of such complexes of PE with oppositely charged surfactants can be found in biological systems, such as immobilization of enzymes in polyelectrolyte complexes or nonspecific association of DNA with protein. Many useful properties of PE surfactant complexes come from the highly ordered structures of surfactant self-assembly inside the PE aggregate which has applications in industry. We do large scale molecular dynamics simulation using LAMMPS to understand the structure and dynamics of PE-surfactant systems. Our investigation shows highly ordered pearl-necklace structures that have been observed experimentally in biological systems. We investigate many different properties of PE-surfactant complexation for different parameter ranges that are useful for pharmaceutical, engineering and biological applications.

The emergence of mind and brain: an evolutionary, computational, and philosophical approach.

PubMed

Mainzer, Klaus

2008-01-01

Modern philosophy of mind cannot be understood without recent developments in computer science, artificial intelligence (AI), robotics, neuroscience, biology, linguistics, and psychology. Classical philosophy of formal languages as well as symbolic AI assume that all kinds of knowledge must explicitly be represented by formal or programming languages. This assumption is limited by recent insights into the biology of evolution and developmental psychology of the human organism. Most of our knowledge is implicit and unconscious. It is not formally represented, but embodied knowledge, which is learnt by doing and understood by bodily interacting with changing environments. That is true not only for low-level skills, but even for high-level domains of categorization, language, and abstract thinking. The embodied mind is considered an emergent capacity of the brain as a self-organizing complex system. Actually, self-organization has been a successful strategy of evolution to handle the increasing complexity of the world. Genetic programs are not sufficient and cannot prepare the organism for all kinds of complex situations in the future. Self-organization and emergence are fundamental concepts in the theory of complex dynamical systems. They are also applied in organic computing as a recent research field of computer science. Therefore, cognitive science, AI, and robotics try to model the embodied mind in an artificial evolution. The paper analyzes these approaches in the interdisciplinary framework of complex dynamical systems and discusses their philosophical impact.

Complexity: the organizing principle at the interface of biological (dis)order.

PubMed

Bhat, Ramray; Pally, Dharma

2017-07-01

The term complexity means several things to biologists.When qualifying morphological phenotype, on the one hand, it is used to signify the sheer complicatedness of living systems, especially as a result of the multicomponent aspect of biological form. On the other hand, it has been used to represent the intricate nature of the connections between constituents that make up form: a more process-based explanation. In the context of evolutionary arguments, complexity has been defined, in a quantifiable fashion, as the amount of information, an informatic template such as a sequence of nucleotides or amino acids stores about its environment. In this perspective, we begin with a brief review of the history of complexity theory. We then introduce a developmental and an evolutionary understanding of what it means for biological systems to be complex.We propose that the complexity of living systems can be understood through two interdependent structural properties: multiscalarity of interconstituent mechanisms and excitability of the biological materials. The answer to whether a system becomes more or less complex over time depends on the potential for its constituents to interact in novel ways and combinations to give rise to new structures and functions, as well as on the evolution of excitable properties that would facilitate the exploration of interconstituent organization in the context of their microenvironments and macroenvironments.

Allometric scaling enhances stability in complex food webs.

PubMed

Brose, Ulrich; Williams, Richard J; Martinez, Neo D

2006-11-01

Classic local stability theory predicts that complex ecological networks are unstable and are unlikely to persist despite empiricists' abundant documentation of such complexity in nature. This contradiction has puzzled biologists for decades. While some have explored how stability may be achieved in small modules of a few interacting species, rigorous demonstrations of how large complex and ecologically realistic networks dynamically persist remain scarce and inadequately understood. Here, we help fill this void by combining structural models of complex food webs with nonlinear bioenergetic models of population dynamics parameterized by biological rates that are allometrically scaled to populations' average body masses. Increasing predator-prey body mass ratios increase population persistence up to a saturation level that is reached by invertebrate and ectotherm vertebrate predators when being 10 or 100 times larger than their prey respectively. These values are corroborated by empirical predator-prey body mass ratios from a global data base. Moreover, negative effects of diversity (i.e. species richness) on stability (i.e. population persistence) become neutral or positive relationships at these empirical ratios. These results demonstrate that the predator-prey body mass ratios found in nature may be key to enabling persistence of populations in complex food webs and stabilizing the diversity of natural ecosystems.

Multiscale Systems Analysis of Root Growth and Development: Modeling Beyond the Network and Cellular Scales

PubMed Central

Band, Leah R.; Fozard, John A.; Godin, Christophe; Jensen, Oliver E.; Pridmore, Tony; Bennett, Malcolm J.; King, John R.

2012-01-01

Over recent decades, we have gained detailed knowledge of many processes involved in root growth and development. However, with this knowledge come increasing complexity and an increasing need for mechanistic modeling to understand how those individual processes interact. One major challenge is in relating genotypes to phenotypes, requiring us to move beyond the network and cellular scales, to use multiscale modeling to predict emergent dynamics at the tissue and organ levels. In this review, we highlight recent developments in multiscale modeling, illustrating how these are generating new mechanistic insights into the regulation of root growth and development. We consider how these models are motivating new biological data analysis and explore directions for future research. This modeling progress will be crucial as we move from a qualitative to an increasingly quantitative understanding of root biology, generating predictive tools that accelerate the development of improved crop varieties. PMID:23110897

A basis for a visual language for describing, archiving and analyzing functional models of complex biological systems

PubMed Central

Cook, Daniel L; Farley, Joel F; Tapscott, Stephen J

2001-01-01

Background: We propose that a computerized, internet-based graphical description language for systems biology will be essential for describing, archiving and analyzing complex problems of biological function in health and disease. Results: We outline here a conceptual basis for designing such a language and describe BioD, a prototype language that we have used to explore the utility and feasibility of this approach to functional biology. Using example models, we demonstrate that a rather limited lexicon of icons and arrows suffices to describe complex cell-biological systems as discrete models that can be posted and linked on the internet. Conclusions: Given available computer and internet technology, BioD may be implemented as an extensible, multidisciplinary language that can be used to archive functional systems knowledge and be extended to support both qualitative and quantitative functional analysis. PMID:11305940

Virtual Transgenics: Using a Molecular Biology Simulation to Impact Student Academic Achievement and Attitudes

NASA Astrophysics Data System (ADS)

Shegog, Ross; Lazarus, Melanie M.; Murray, Nancy G.; Diamond, Pamela M.; Sessions, Nathalie; Zsigmond, Eva

2012-10-01

The transgenic mouse model is useful for studying the causes and potential cures for human genetic diseases. Exposing high school biology students to laboratory experience in developing transgenic animal models is logistically prohibitive. Computer-based simulation, however, offers this potential in addition to advantages of fidelity and reach. This study describes and evaluates a computer-based simulation to train advanced placement high school science students in laboratory protocols, a transgenic mouse model was produced. A simulation module on preparing a gene construct in the molecular biology lab was evaluated using a randomized clinical control design with advanced placement high school biology students in Mercedes, Texas ( n = 44). Pre-post tests assessed procedural and declarative knowledge, time on task, attitudes toward computers for learning and towards science careers. Students who used the simulation increased their procedural and declarative knowledge regarding molecular biology compared to those in the control condition (both p < 0.005). Significant increases continued to occur with additional use of the simulation ( p < 0.001). Students in the treatment group became more positive toward using computers for learning ( p < 0.001). The simulation did not significantly affect attitudes toward science in general. Computer simulation of complex transgenic protocols have potential to provide a "virtual" laboratory experience as an adjunct to conventional educational approaches.

Genetic Pedagogical Content Knowledge (PCK) Ability Profile of Prospective Biology Teacher

NASA Astrophysics Data System (ADS)

Purwianingsih, W.; Muthmainnah, E.; Hidayat, T.

2017-02-01

Genetics is one of the topics or subject matter in biology that are considered difficult. Student difficulties of understanding genetics, can be caused by lack of understanding this concept and the way of teachers teach. Pedagogical Content Knowledge (PCK) is a way to understand the complex relationships between teaching and content taught through the use of specific teaching approaches. The aims of study was to analyze genetic PCK ability profile of prospective biology teacher.13 student of sixth semester Biology education department who learned Kapita Selekta Biologi SMA course, participated in this study. PCK development was measured by CoRes (Content Representation). Before students fill CoRes, students are tested mastery genetic concepts through a multiple-choice test with three tier-test. Data was obtained from the prior CoRes and its revisions, as well as the mastery concept in pre and post test. Results showed that pre-test of genetic mastery concepts average on 55.4% (low category) and beginning of the writing CoRes, student get 43.2% (Pra PCK). After students get lecture and simulating learning, the post-test increased to 63.8% (sufficient category) and PCK revision is also increase 58.1% (growing PCK). It can be concluded that mastery of subject matter could affects the ability of genetic PCK.

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

Life Support System Technologies for NASA Exploration Missions

NASA Technical Reports Server (NTRS)

Ewert, Michael K.

2007-01-01

The Lunar Mars Life Support Test series successfully demonstrated integration and operation of advanced technologies for closed-loop life support systems, including physicochemical and biological subsystems. Increased closure was obtained when targeted technologies, such as brine dewatering subsystems, were added to further process life support system byproducts to recover resources. Physicochemical and biological systems can be integrated satisfactorily to achieve desired levels of closure. Imbalances between system components, such as differences in metabolic quotients between human crews and plants, must be addressed. Each subsystem or component that is added to increase closure will likely have added costs, ranging from initial launch mass, power, thermal, crew time, byproducts, etc., that must be factored into break even analysis. Achieving life support system closure while maintaining control of total mass and system complexity will be a challenge.

Graphics processing units in bioinformatics, computational biology and systems biology.

PubMed

Nobile, Marco S; Cazzaniga, Paolo; Tangherloni, Andrea; Besozzi, Daniela

2017-09-01

Several studies in Bioinformatics, Computational Biology and Systems Biology rely on the definition of physico-chemical or mathematical models of biological systems at different scales and levels of complexity, ranging from the interaction of atoms in single molecules up to genome-wide interaction networks. Traditional computational methods and software tools developed in these research fields share a common trait: they can be computationally demanding on Central Processing Units (CPUs), therefore limiting their applicability in many circumstances. To overcome this issue, general-purpose Graphics Processing Units (GPUs) are gaining an increasing attention by the scientific community, as they can considerably reduce the running time required by standard CPU-based software, and allow more intensive investigations of biological systems. In this review, we present a collection of GPU tools recently developed to perform computational analyses in life science disciplines, emphasizing the advantages and the drawbacks in the use of these parallel architectures. The complete list of GPU-powered tools here reviewed is available at http://bit.ly/gputools. © The Author 2016. Published by Oxford University Press.

Optimizing Nutrient Uptake in Biological Transport Networks

NASA Astrophysics Data System (ADS)

Ronellenfitsch, Henrik; Katifori, Eleni

2013-03-01

Many biological systems employ complex networks of vascular tubes to facilitate transport of solute nutrients, examples include the vascular system of plants (phloem), some fungi, and the slime-mold Physarum. It is believed that such networks are optimized through evolution for carrying out their designated task. We propose a set of hydrodynamic governing equations for solute transport in a complex network, and obtain the optimal network architecture for various classes of optimizing functionals. We finally discuss the topological properties and statistical mechanics of the resulting complex networks, and examine correspondence of the obtained networks to those found in actual biological systems.

LEMS: a language for expressing complex biological models in concise and hierarchical form and its use in underpinning NeuroML 2.

PubMed

Cannon, Robert C; Gleeson, Padraig; Crook, Sharon; Ganapathy, Gautham; Marin, Boris; Piasini, Eugenio; Silver, R Angus

2014-01-01

Computational models are increasingly important for studying complex neurophysiological systems. As scientific tools, it is essential that such models can be reproduced and critically evaluated by a range of scientists. However, published models are currently implemented using a diverse set of modeling approaches, simulation tools, and computer languages making them inaccessible and difficult to reproduce. Models also typically contain concepts that are tightly linked to domain-specific simulators, or depend on knowledge that is described exclusively in text-based documentation. To address these issues we have developed a compact, hierarchical, XML-based language called LEMS (Low Entropy Model Specification), that can define the structure and dynamics of a wide range of biological models in a fully machine readable format. We describe how LEMS underpins the latest version of NeuroML and show that this framework can define models of ion channels, synapses, neurons and networks. Unit handling, often a source of error when reusing models, is built into the core of the language by specifying physical quantities in models in terms of the base dimensions. We show how LEMS, together with the open source Java and Python based libraries we have developed, facilitates the generation of scripts for multiple neuronal simulators and provides a route for simulator free code generation. We establish that LEMS can be used to define models from systems biology and map them to neuroscience-domain specific simulators, enabling models to be shared between these traditionally separate disciplines. LEMS and NeuroML 2 provide a new, comprehensive framework for defining computational models of neuronal and other biological systems in a machine readable format, making them more reproducible and increasing the transparency and accessibility of their underlying structure and properties.

LEMS: a language for expressing complex biological models in concise and hierarchical form and its use in underpinning NeuroML 2

PubMed Central

Cannon, Robert C.; Gleeson, Padraig; Crook, Sharon; Ganapathy, Gautham; Marin, Boris; Piasini, Eugenio; Silver, R. Angus

2014-01-01

Computational models are increasingly important for studying complex neurophysiological systems. As scientific tools, it is essential that such models can be reproduced and critically evaluated by a range of scientists. However, published models are currently implemented using a diverse set of modeling approaches, simulation tools, and computer languages making them inaccessible and difficult to reproduce. Models also typically contain concepts that are tightly linked to domain-specific simulators, or depend on knowledge that is described exclusively in text-based documentation. To address these issues we have developed a compact, hierarchical, XML-based language called LEMS (Low Entropy Model Specification), that can define the structure and dynamics of a wide range of biological models in a fully machine readable format. We describe how LEMS underpins the latest version of NeuroML and show that this framework can define models of ion channels, synapses, neurons and networks. Unit handling, often a source of error when reusing models, is built into the core of the language by specifying physical quantities in models in terms of the base dimensions. We show how LEMS, together with the open source Java and Python based libraries we have developed, facilitates the generation of scripts for multiple neuronal simulators and provides a route for simulator free code generation. We establish that LEMS can be used to define models from systems biology and map them to neuroscience-domain specific simulators, enabling models to be shared between these traditionally separate disciplines. LEMS and NeuroML 2 provide a new, comprehensive framework for defining computational models of neuronal and other biological systems in a machine readable format, making them more reproducible and increasing the transparency and accessibility of their underlying structure and properties. PMID:25309419

Proteomics-Based Analysis of Protein Complexes in Pluripotent Stem Cells and Cancer Biology.

PubMed

Sudhir, Putty-Reddy; Chen, Chung-Hsuan

2016-03-22

A protein complex consists of two or more proteins that are linked together through protein-protein interactions. The proteins show stable/transient and direct/indirect interactions within the protein complex or between the protein complexes. Protein complexes are involved in regulation of most of the cellular processes and molecular functions. The delineation of protein complexes is important to expand our knowledge on proteins functional roles in physiological and pathological conditions. The genetic yeast-2-hybrid method has been extensively used to characterize protein-protein interactions. Alternatively, a biochemical-based affinity purification coupled with mass spectrometry (AP-MS) approach has been widely used to characterize the protein complexes. In the AP-MS method, a protein complex of a target protein of interest is purified using a specific antibody or an affinity tag (e.g., DYKDDDDK peptide (FLAG) and polyhistidine (His)) and is subsequently analyzed by means of MS. Tandem affinity purification, a two-step purification system, coupled with MS has been widely used mainly to reduce the contaminants. We review here a general principle for AP-MS-based characterization of protein complexes and we explore several protein complexes identified in pluripotent stem cell biology and cancer biology as examples.

Proteomics-Based Analysis of Protein Complexes in Pluripotent Stem Cells and Cancer Biology

PubMed Central

Sudhir, Putty-Reddy; Chen, Chung-Hsuan

2016-01-01

A protein complex consists of two or more proteins that are linked together through protein–protein interactions. The proteins show stable/transient and direct/indirect interactions within the protein complex or between the protein complexes. Protein complexes are involved in regulation of most of the cellular processes and molecular functions. The delineation of protein complexes is important to expand our knowledge on proteins functional roles in physiological and pathological conditions. The genetic yeast-2-hybrid method has been extensively used to characterize protein-protein interactions. Alternatively, a biochemical-based affinity purification coupled with mass spectrometry (AP-MS) approach has been widely used to characterize the protein complexes. In the AP-MS method, a protein complex of a target protein of interest is purified using a specific antibody or an affinity tag (e.g., DYKDDDDK peptide (FLAG) and polyhistidine (His)) and is subsequently analyzed by means of MS. Tandem affinity purification, a two-step purification system, coupled with MS has been widely used mainly to reduce the contaminants. We review here a general principle for AP-MS-based characterization of protein complexes and we explore several protein complexes identified in pluripotent stem cell biology and cancer biology as examples. PMID:27011181

Schiff bases in medicinal chemistry: a patent review (2010-2015).

PubMed

Hameed, Abdul; Al-Rashida, Mariya; Uroos, Maliha; Abid Ali, Syed; Khan, Khalid Mohammed

2017-01-01

Schiff bases are synthetically accessible and structurally diverse compounds, typically obtained by facile condensation between an aldehyde, or a ketone with primary amines. Schiff bases contain an azomethine (-C = N-) linkage that stitches together two or more biologically active aromatic/heterocyclic scaffolds to form various molecular hybrids with interesting biological properties. Schiff bases are versatile metal complexing agents and have been known to coordinate all metals to form stable metal complexes with vast therapeutic applications. Areas covered: This review aims to provide a comprehensive overview of the various patented therapeutic applications of Schiff bases and their metal complexes from 2010 to 2015. Expert opinion: Schiff bases are a popular class of compounds with interesting biological properties. Schiff bases are also versatile metal complexing ligands and have been used to coordinate almost all d-block metals as well as lanthanides. Therapeutically, Schiff bases and their metal complexes have been reported to exhibit a wide range of biological activities such as antibacterial including antimycobacterial, antifungal, antiviral, antimalarial, antiinflammatory, antioxidant, pesticidal, cytotoxic, enzyme inhibitory, and anticancer including DNA damage.

Thinking on building the network cardiovasology of Chinese medicine.

PubMed

Yu, Gui; Wang, Jie

2012-11-01

With advances in complex network theory, the thinking and methods regarding complex systems have changed revolutionarily. Network biology and network pharmacology were built by applying network-based approaches in biomedical research. The cardiovascular system may be regarded as a complex network, and cardiovascular diseases may be taken as the damage of structure and function of the cardiovascular network. Although Chinese medicine (CM) is effective in treating cardiovascular diseases, its mechanisms are still unclear. With the guidance of complex network theory, network biology and network pharmacology, network-based approaches could be used in the study of CM in preventing and treating cardiovascular diseases. A new discipline-network cardiovasology of CM was, therefore, developed. In this paper, complex network theory, network biology and network pharmacology were introduced and the connotation of "disease-syndrome-formula-herb" was illustrated from the network angle. Network biology could be used to analyze cardiovascular diseases and syndromes and network pharmacology could be used to analyze CM formulas and herbs. The "network-network"-based approaches could provide a new view for elucidating the mechanisms of CM treatment.

oGNM: online computation of structural dynamics using the Gaussian Network Model

PubMed Central

Yang, Lee-Wei; Rader, A. J.; Liu, Xiong; Jursa, Cristopher Jon; Chen, Shann Ching; Karimi, Hassan A.; Bahar, Ivet

2006-01-01

An assessment of the equilibrium dynamics of biomolecular systems, and in particular their most cooperative fluctuations accessible under native state conditions, is a first step towards understanding molecular mechanisms relevant to biological function. We present a web-based system, oGNM that enables users to calculate online the shape and dispersion of normal modes of motion for proteins, oligonucleotides and their complexes, or associated biological units, using the Gaussian Network Model (GNM). Computations with the new engine are 5–6 orders of magnitude faster than those using conventional normal mode analyses. Two cases studies illustrate the utility of oGNM. The first shows that the thermal fluctuations predicted for 1250 non-homologous proteins correlate well with X-ray crystallographic data over a broad range [7.3–15 Å] of inter-residue interaction cutoff distances and the correlations improve with increasing observation temperatures. The second study, focused on 64 oligonucleotides and oligonucleotide–protein complexes, shows that good agreement with experiments is achieved by representing each nucleotide by three GNM nodes (as opposed to one-node-per-residue in proteins) along with uniform interaction ranges for all components of the complexes. These results open the way to a rapid assessment of the dynamics of DNA/RNA-containing complexes. The server can be accessed at . PMID:16845002

How Can We Improve Problem Solving in Undergraduate Biology? Applying Lessons from 30 Years of Physics Education Research

PubMed Central

Hoskinson, A.-M.; Caballero, M. D.; Knight, J. K.

2013-01-01

If students are to successfully grapple with authentic, complex biological problems as scientists and citizens, they need practice solving such problems during their undergraduate years. Physics education researchers have investigated student problem solving for the past three decades. Although physics and biology problems differ in structure and content, the instructional purposes align closely: explaining patterns and processes in the natural world and making predictions about physical and biological systems. In this paper, we discuss how research-supported approaches developed by physics education researchers can be adopted by biologists to enhance student problem-solving skills. First, we compare the problems that biology students are typically asked to solve with authentic, complex problems. We then describe the development of research-validated physics curricula emphasizing process skills in problem solving. We show that solving authentic, complex biology problems requires many of the same skills that practicing physicists and biologists use in representing problems, seeking relationships, making predictions, and verifying or checking solutions. We assert that acquiring these skills can help biology students become competent problem solvers. Finally, we propose how biology scholars can apply lessons from physics education in their classrooms and inspire new studies in biology education research. PMID:23737623

Stochastic simulation of multiscale complex systems with PISKaS: A rule-based approach.

PubMed

Perez-Acle, Tomas; Fuenzalida, Ignacio; Martin, Alberto J M; Santibañez, Rodrigo; Avaria, Rodrigo; Bernardin, Alejandro; Bustos, Alvaro M; Garrido, Daniel; Dushoff, Jonathan; Liu, James H

2018-03-29

Computational simulation is a widely employed methodology to study the dynamic behavior of complex systems. Although common approaches are based either on ordinary differential equations or stochastic differential equations, these techniques make several assumptions which, when it comes to biological processes, could often lead to unrealistic models. Among others, model approaches based on differential equations entangle kinetics and causality, failing when complexity increases, separating knowledge from models, and assuming that the average behavior of the population encompasses any individual deviation. To overcome these limitations, simulations based on the Stochastic Simulation Algorithm (SSA) appear as a suitable approach to model complex biological systems. In this work, we review three different models executed in PISKaS: a rule-based framework to produce multiscale stochastic simulations of complex systems. These models span multiple time and spatial scales ranging from gene regulation up to Game Theory. In the first example, we describe a model of the core regulatory network of gene expression in Escherichia coli highlighting the continuous model improvement capacities of PISKaS. The second example describes a hypothetical outbreak of the Ebola virus occurring in a compartmentalized environment resembling cities and highways. Finally, in the last example, we illustrate a stochastic model for the prisoner's dilemma; a common approach from social sciences describing complex interactions involving trust within human populations. As whole, these models demonstrate the capabilities of PISKaS providing fertile scenarios where to explore the dynamics of complex systems. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

Innovation in academic chemical screening: filling the gaps in chemical biology.

PubMed

Hasson, Samuel A; Inglese, James

2013-06-01

Academic screening centers across the world have endeavored to discover small molecules that can modulate biological systems. To increase the reach of functional-genomic and chemical screening programs, universities, research institutes, and governments have followed their industrial counterparts in adopting high-throughput paradigms. As academic screening efforts have steadily grown in scope and complexity, so have the ideas of what is possible with the union of technology and biology. This review addresses the recent conceptual and technological innovation that has been propelling academic screening into its own unique niche. In particular, high-content and whole-organism screening are changing how academics search for novel bioactive compounds. Importantly, we recognize examples of successful chemical probe development that have punctuated the changing technology landscape. Published by Elsevier Ltd.

How community has shaped the Protein Data Bank.

PubMed

Berman, Helen M; Kleywegt, Gerard J; Nakamura, Haruki; Markley, John L

2013-09-03

Following several years of community discussion, the Protein Data Bank (PDB) was established in 1971 as a public repository for the coordinates of three-dimensional models of biological macromolecules. Since then, the number, size, and complexity of structural models have continued to grow, reflecting the productivity of structural biology. Managed by the Worldwide PDB organization, the PDB has been able to meet increasing demands for the quantity of structural information and of quality. In addition to providing unrestricted access to structural information, the PDB also works to promote data standards and to raise the profile of structural biology with broader audiences. In this perspective, we describe the history of PDB and the many ways in which the community continues to shape the archive. Copyright © 2013 Elsevier Ltd. All rights reserved.

Review on Physicochemical, Chemical, and Biological Processes for Pharmaceutical Wastewater

NASA Astrophysics Data System (ADS)

Li, Zhenchen; Yang, Ping

2018-02-01

Due to the needs of human life and health, pharmaceutical industry has made great progress in recent years, but it has also brought about severe environmental problems. The presence of pharmaceuticals in natural waters which might pose potential harm to the ecosystems and humans raised increasing concern worldwide. Pharmaceuticals cannot be effectively removed by conventional wastewater treatment plants (WWTPs) owing to the complex composition, high concentration of organic contaminants, high salinity and biological toxicity of pharmaceutical wastewater. Therefore, the development of efficient methods is needed to improve the removal effect of pharmaceuticals. This review provides an overview on three types of treatment technologies including physicochemical, chemical and biological processes and their advantages and disadvantages respectively. In addition, the future perspectives of pharmaceutical wastewater treatment are given.

BIOSPIDA: A Relational Database Translator for NCBI.

PubMed

Hagen, Matthew S; Lee, Eva K

2010-11-13

As the volume and availability of biological databases continue widespread growth, it has become increasingly difficult for research scientists to identify all relevant information for biological entities of interest. Details of nucleotide sequences, gene expression, molecular interactions, and three-dimensional structures are maintained across many different databases. To retrieve all necessary information requires an integrated system that can query multiple databases with minimized overhead. This paper introduces a universal parser and relational schema translator that can be utilized for all NCBI databases in Abstract Syntax Notation (ASN.1). The data models for OMIM, Entrez-Gene, Pubmed, MMDB and GenBank have been successfully converted into relational databases and all are easily linkable helping to answer complex biological questions. These tools facilitate research scientists to locally integrate databases from NCBI without significant workload or development time.

The multi-replication protein A (RPA) system--a new perspective.

PubMed

Sakaguchi, Kengo; Ishibashi, Toyotaka; Uchiyama, Yukinobu; Iwabata, Kazuki

2009-02-01

Replication protein A (RPA) complex has been shown, using both in vivo and in vitro approaches, to be required for most aspects of eukaryotic DNA metabolism: replication, repair, telomere maintenance and homologous recombination. Here, we review recent data concerning the function and biological importance of the multi-RPA complex. There are distinct complexes of RPA found in the biological kingdoms, although for a long time only one type of RPA complex was believed to be present in eukaryotes. Each complex probably serves a different role. In higher plants, three distinct large and medium subunits are present, but only one species of the smallest subunit. Each of these protein subunits forms stable complexes with their respective partners. They are paralogs as complex. Humans possess two paralogs and one analog of RPA. The multi-RPA system can be regarded as universal in eukaryotes. Among eukaryotic kingdoms, paralogs, orthologs, analogs and heterologs of many DNA synthesis-related factors, including RPA, are ubiquitous. Convergent evolution seems to be ubiquitous in these processes. Using recent findings, we review the composition and biological functions of RPA complexes.

Developments in the Tools and Methodologies of Synthetic Biology

PubMed Central

Kelwick, Richard; MacDonald, James T.; Webb, Alexander J.; Freemont, Paul

2014-01-01

Synthetic biology is principally concerned with the rational design and engineering of biologically based parts, devices, or systems. However, biological systems are generally complex and unpredictable, and are therefore, intrinsically difficult to engineer. In order to address these fundamental challenges, synthetic biology is aiming to unify a “body of knowledge” from several foundational scientific fields, within the context of a set of engineering principles. This shift in perspective is enabling synthetic biologists to address complexity, such that robust biological systems can be designed, assembled, and tested as part of a biological design cycle. The design cycle takes a forward-design approach in which a biological system is specified, modeled, analyzed, assembled, and its functionality tested. At each stage of the design cycle, an expanding repertoire of tools is being developed. In this review, we highlight several of these tools in terms of their applications and benefits to the synthetic biology community. PMID:25505788

Integrated Information Increases with Fitness in the Evolution of Animats

PubMed Central

Edlund, Jeffrey A.; Chaumont, Nicolas; Hintze, Arend; Koch, Christof; Tononi, Giulio; Adami, Christoph

2011-01-01

One of the hallmarks of biological organisms is their ability to integrate disparate information sources to optimize their behavior in complex environments. How this capability can be quantified and related to the functional complexity of an organism remains a challenging problem, in particular since organismal functional complexity is not well-defined. We present here several candidate measures that quantify information and integration, and study their dependence on fitness as an artificial agent (“animat”) evolves over thousands of generations to solve a navigation task in a simple, simulated environment. We compare the ability of these measures to predict high fitness with more conventional information-theoretic processing measures. As the animat adapts by increasing its “fit” to the world, information integration and processing increase commensurately along the evolutionary line of descent. We suggest that the correlation of fitness with information integration and with processing measures implies that high fitness requires both information processing as well as integration, but that information integration may be a better measure when the task requires memory. A correlation of measures of information integration (but also information processing) and fitness strongly suggests that these measures reflect the functional complexity of the animat, and that such measures can be used to quantify functional complexity even in the absence of fitness data. PMID:22028639

Towards a global initiative for fibrosis treatment (GIFT)

PubMed Central

Agusti, Alvar; Crestani, Bruno; Schwartz, David A.; Chambers, Rachel C.; Maher, Toby M.; Faner, Rosa; Mora, Ana Lucia; Rojas, Mauricio; Antoniou, Katerina M.; Sellares, Jacobo

2017-01-01

Idiopathic pulmonary fibrosis (IPF) is a progressive lung disease characterised by increased scarring of lung tissue. Despite the recent introduction of novel drugs that slow disease progression, IPF remains a deadly disease, and the benefits of these new drugs differ markedly between patients. Human diseases arise due to alterations in an almost limitless network of interconnected genes, proteins, metabolites, cells and tissues, in direct relationship with a continuously changing macro- or microenvironment. Systems biology is a novel research strategy that seeks to understand the structure and behaviour of the so-called “emergent properties” of complex systems, such as those involved in disease pathogenesis, which are most often overlooked when just one element of disease pathogenesis is observed in isolation. This article summarises the debate that took place during a European Respiratory Society research seminar in Barcelona, Spain on December 15–16, 2016, which focused on how systems biology could generate new data by integrating the different IPF pathogenic levels of complexity. The main conclusion of the seminar was to create a global initiative to improve IPF outcomes by integrating cutting-edge international research that leverages systems biology to develop a precision medicine approach to tackle this devastating disease. PMID:29214157

Synthetic biology: programming cells for biomedical applications.

PubMed

Hörner, Maximilian; Reischmann, Nadine; Weber, Wilfried

2012-01-01

The emerging field of synthetic biology is a novel biological discipline at the interface between traditional biology, chemistry, and engineering sciences. Synthetic biology aims at the rational design of complex synthetic biological devices and systems with desired properties by combining compatible, modular biological parts in a systematic manner. While the first engineered systems were mainly proof-of-principle studies to demonstrate the power of the modular engineering approach of synthetic biology, subsequent systems focus on applications in the health, environmental, and energy sectors. This review describes recent approaches for biomedical applications that were developed along the synthetic biology design hierarchy, at the level of individual parts, of devices, and of complex multicellular systems. It describes how synthetic biological parts can be used for the synthesis of drug-delivery tools, how synthetic biological devices can facilitate the discovery of novel drugs, and how multicellular synthetic ecosystems can give insight into population dynamics of parasites and hosts. These examples demonstrate how this new discipline could contribute to novel solutions in the biopharmaceutical industry.

Using Stereoscopy to Teach Complex Biological Concepts

ERIC Educational Resources Information Center

Ferdig, Richard; Blank, James; Kratcoski, Annette; Clements, Robert

2015-01-01

Used effectively, stereoscopic three-dimensional (3D) technologies can engage students with complex disciplinary content as they are presented with informative representations of abstract concepts. In addition, preliminary evidence suggests that stereoscopy may enhance learning and retention in some educational settings. Biological concepts…

New insights from monogenic diabetes for “common” type 2 diabetes

PubMed Central

Tallapragada, Divya Sri Priyanka; Bhaskar, Seema; Chandak, Giriraj R.

2015-01-01

Boundaries between monogenic and complex genetic diseases are becoming increasingly blurred, as a result of better understanding of phenotypes and their genetic determinants. This had a large impact on the way complex disease genetics is now being investigated. Starting with conventional approaches like familial linkage, positional cloning and candidate genes strategies, the scope of complex disease genetics has grown exponentially with scientific and technological advances in recent times. Despite identification of multiple loci harboring common and rare variants associated with complex diseases, interpreting and evaluating their functional role has proven to be difficult. Information from monogenic diseases, especially related to the intermediate traits associated with complex diseases comes handy. The significant overlap between traits and phenotypes of monogenic diseases with related complex diseases provides a platform to understand the disease biology better. In this review, we would discuss about one such complex disease, type 2 diabetes, which shares marked similarity of intermediate traits with different forms of monogenic diabetes. PMID:26300908

Synthesis, spectroscopic characterization and in vitro cytotoxicities of new organometallic palladium complexes with biologically active β-diketones; Biological evaluation probing of the interaction mechanism with DNA/Protein and molecular docking

NASA Astrophysics Data System (ADS)

Karami, Kazem; Rafiee, Mina; Lighvan, Zohreh Mehri; Zakariazadeh, Mostafa; Faal, Ali Yeganeh; Esmaeili, Seyed-Alireza; Momtazi-Borojeni, Amir Abbas

2018-02-01

[Pd{(C,N)sbnd C6H4CH (CH3)NH}(CUR)] (3) and [Pd2{(C,N)sbnd C6H4CH(CH3)NH2}2(μ-N3CS2)] (4) [cur = 1,7-bis(4-hydroxy-3-methoxyphenyl)-1,6-heptadiene-3,5-dion] novel organometallic complexes with biologically active ligands have been prepared and characterized via elemental analysis, multinuclear spectroscopic techniques (1H, and 13C NMR and IR) and their biological activities, including antitumoral activity and DNA-protein interactions have been investigated. Fluorescence spectroscopy used to study the interaction of the complexes with BSA have shown the affinity of the complexes for these proteins with relatively high binding constant values and the changed secondary structure of BSA in the presence of the complexes. In the meantime, spectroscopy and competitive titration have been applied to investigate the interaction of complexes with Warfarin and Ibuprofen site markers for sites I and II, respectively, with BSA. The results have suggested that the locations of complexes 3 and 4 are sites II and I, respectively. UV-Vis spectroscopy, emission titration and helix melting methods have been used to study the interaction of these complexes with CT-DNA, indicating that complexes are bound to CT-DNA by intercalation binding mode. In addition, good cytotoxic activity against MCF-7 (human breast cancer) and JURKAT (human leukemia) cell line has been shown by both complexes whereas low cytotoxicity was exerted on normal peripheral blood mononuclear cells.

Challenges and Rewards on the Road to Translational Systems Biology in Acute Illness: Four Case Reports from Interdisciplinary Teams

PubMed Central

An, Gary; Hunt, C. Anthony; Clermont, Gilles; Neugebauer, Edmund; Vodovotz, Yoram

2007-01-01

Introduction Translational systems biology approaches can be distinguished from mainstream systems biology in that their goal is to drive novel therapies and streamline clinical trials in critical illness. One systems biology approach, dynamic mathematical modeling (DMM), is increasingly used in dealing with the complexity of the inflammatory response and organ dysfunction. The use of DMM often requires a broadening of research methods and a multidisciplinary team approach that includes bioscientists, mathematicians, engineers, and computer scientists. However, the development of these groups must overcome domain-specific barriers to communication and understanding. Methods We present four case studies of successful translational, interdisciplinary systems biology efforts, which differ by organizational level from an individual to an entire research community. Results Case 1 is a single investigator involved in DMM of the acute inflammatory response at Cook County Hospital, in which extensive translational progress was made using agent-based models of inflammation and organ damage. Case 2 is a community-level effort from the University of Witten-Herdecke in Cologne, whose efforts have led to the formation of the Society for Complexity in Acute Illness. Case 3 is an institution-based group, the Biosystems Group at the University of California, San Francisco, whose work has included a focus on a common lexicon for DMM. Case 4 is an institution-based, trans-disciplinary research group (the Center for Inflammation and Regenerative Modeling at the University of Pittsburgh, whose modeling work has led to internal education efforts, grant support, and commercialization. Conclusion A transdisciplinary approach, which involves team interaction in an iterative fashion to address ambiguity and is supported by educational initiatives, is likely to be necessary for DMM in acute illness. Community-wide organizations such as the Society of Complexity in Acute Illness (SCAI) must strive to facilitate the implementation of DMM in sepsis/trauma research into the research community as a whole. PMID:17548029

Informing Biological Design by Integration of Systems and Synthetic Biology

PubMed Central

Smolke, Christina D.; Silver, Pamela A.

2011-01-01

Synthetic biology aims to make the engineering of biology faster and more predictable. In contrast, systems biology focuses on the interaction of myriad components and how these give rise to the dynamic and complex behavior of biological systems. Here, we examine the synergies between these two fields. PMID:21414477

Biomimetic carriers mimicking leukocyte plasma membrane to increase tumor vasculature permeability

NASA Astrophysics Data System (ADS)

Palomba, R.; Parodi, A.; Evangelopoulos, M.; Acciardo, S.; Corbo, C.; De Rosa, E.; Yazdi, I. K.; Scaria, S.; Molinaro, R.; Furman, N. E. Toledano; You, J.; Ferrari, M.; Salvatore, F.; Tasciotti, E.

2016-10-01

Recent advances in the field of nanomedicine have demonstrated that biomimicry can further improve targeting properties of current nanotechnologies while simultaneously enable carriers with a biological identity to better interact with the biological environment. Immune cells for example employ membrane proteins to target inflamed vasculature, locally increase vascular permeability, and extravasate across inflamed endothelium. Inspired by the physiology of immune cells, we recently developed a procedure to transfer leukocyte membranes onto nanoporous silicon particles (NPS), yielding Leukolike Vectors (LLV). LLV are composed of a surface coating containing multiple receptors that are critical in the cross-talk with the endothelium, mediating cellular accumulation in the tumor microenvironment while decreasing vascular barrier function. We previously demonstrated that lymphocyte function-associated antigen (LFA-1) transferred onto LLV was able to trigger the clustering of intercellular adhesion molecule 1 (ICAM-1) on endothelial cells. Herein, we provide a more comprehensive analysis of the working mechanism of LLV in vitro in activating this pathway and in vivo in enhancing vascular permeability. Our results suggest the biological activity of the leukocyte membrane can be retained upon transplant onto NPS and is critical in providing the particles with complex biological functions towards tumor vasculature.

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

PubMed

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

2016-04-05

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

Pattern Discovery in Biomolecular Data – Tools, Techniques, and Applications | Center for Cancer Research

Cancer.gov

Finding patterns in biomolecular data, particularly in DNA and RNA, is at the center of modern biological research. These data are complex and growing rapidly, so the search for patterns requires increasingly sophisticated computer methods. This book provides a summary of principal techniques. Each chapter describes techniques that are drawn from many fields, including graph

Mary, Mary Quite Contrary How Does Your Garden Grow? Creating the Creative School Garden

ERIC Educational Resources Information Center

Egan, Padraig

2017-01-01

Plants and the outdoors may be something of a mystery to a generation of children who are reportedly spending more and more time indoors; this has the potential to inhibit real understanding of many complex biological processes. Taking children outdoors introduces them to a world from which they are becoming increasingly distant. However, a…

Viruses and mobile elements as drivers of evolutionary transitions

PubMed Central

2016-01-01

The history of life is punctuated by evolutionary transitions which engender emergence of new levels of biological organization that involves selection acting at increasingly complex ensembles of biological entities. Major evolutionary transitions include the origin of prokaryotic and then eukaryotic cells, multicellular organisms and eusocial animals. All or nearly all cellular life forms are hosts to diverse selfish genetic elements with various levels of autonomy including plasmids, transposons and viruses. I present evidence that, at least up to and including the origin of multicellularity, evolutionary transitions are driven by the coevolution of hosts with these genetic parasites along with sharing of ‘public goods’. Selfish elements drive evolutionary transitions at two distinct levels. First, mathematical modelling of evolutionary processes, such as evolution of primitive replicator populations or unicellular organisms, indicates that only increasing organizational complexity, e.g. emergence of multicellular aggregates, can prevent the collapse of the host–parasite system under the pressure of parasites. Second, comparative genomic analysis reveals numerous cases of recruitment of genes with essential functions in cellular life forms, including those that enable evolutionary transitions. This article is part of the themed issue ‘The major synthetic evolutionary transitions’. PMID:27431520

Viruses and mobile elements as drivers of evolutionary transitions.

PubMed

Koonin, Eugene V

2016-08-19

The history of life is punctuated by evolutionary transitions which engender emergence of new levels of biological organization that involves selection acting at increasingly complex ensembles of biological entities. Major evolutionary transitions include the origin of prokaryotic and then eukaryotic cells, multicellular organisms and eusocial animals. All or nearly all cellular life forms are hosts to diverse selfish genetic elements with various levels of autonomy including plasmids, transposons and viruses. I present evidence that, at least up to and including the origin of multicellularity, evolutionary transitions are driven by the coevolution of hosts with these genetic parasites along with sharing of 'public goods'. Selfish elements drive evolutionary transitions at two distinct levels. First, mathematical modelling of evolutionary processes, such as evolution of primitive replicator populations or unicellular organisms, indicates that only increasing organizational complexity, e.g. emergence of multicellular aggregates, can prevent the collapse of the host-parasite system under the pressure of parasites. Second, comparative genomic analysis reveals numerous cases of recruitment of genes with essential functions in cellular life forms, including those that enable evolutionary transitions.This article is part of the themed issue 'The major synthetic evolutionary transitions'. © 2016 The Authors.

Bioinspired peony-like beta-Ni(OH)2 nanostructures with enhanced electrochemical activity and superhydrophobicity.

PubMed

Cao, Huaqiang; Zheng, He; Liu, Kaiyu; Warner, Jamie H

2010-02-01

Constructing complex nanostructures has become increasingly important in the development of hydrogen storage, self-cleaning materials, and the formation of chiral branched nanowires. Several approaches have been developed to generate complex nanostructures, which have led to novel applications. Combining biology and nanotechnology through the utilization of biomolecules to chemically template the growth of complex nanostructures during synthesis has aroused great interest. Herein, we use a biomolecule-assisted hydrothermal method to synthesize beta-phase Ni(OH)(2) peony-like complex nanostructures with second-order structure nanoplate structure. The novel beta-Ni(OH)(2) nanostructures exhibit high-power Ni/MH battery performance, close to the theoretical capacity of Ni(OH)(2), as well as controlled wetting behavior. We demonstrate that this bioinspired route to generate a complex nanostructure has applications in environmental protection and green secondary cells. This approach opens up opportunities for the synthesis and potential applications of new kinds of nanostructures.

Energy deposition processes in biological tissue: nonthermal biohazards seem unlikely in the ultra-high frequency range.

PubMed

Pickard, W F; Moros, E G

2001-02-01

The prospects of ultra high frequency (UHF, 300--3000 MHz) irradiation producing a nonthermal bioeffect are considered theoretically and found to be small. First, a general formula is derived within the framework of macroscopic electrodynamics for the specific absorption rate of microwaves in a biological tissue; this involves the complex Poynting vector, the mass density of the medium, the angular frequency of the electromagnetic field, and the three complex electromagnetic constitutive parameters of the medium. In the frequency ranges used for cellular telephony and personal communication systems, this model predicts that the chief physical loss mechanism will be ionic conduction, with increasingly important contributions from dielectric relaxation as the frequency rises. However, even in a magnetite unit cell within a magnetosome the deposition rate should not exceed 1/10 k(B)T per second. This supports previous arguments for the improbability of biological effects at UHF frequencies unless a mechanism can be found for accumulating energy over time and space and focussing it. Second, three possible nonthermal accumulation mechanisms are then considered and shown to be unlikely: (i) multiphoton absorption processes; (ii) direct electric field effects on ions; (iii) cooperative effects and/or coherent excitations. Finally, it is concluded that the rate of energy deposition from a typical field and within a typical tissue is so small as to make unlikely any significant nonthermal biological effect. Copyright 2001 Wiley-Liss, Inc.

Bringing the ocean into the laboratory to probe the chemical complexity of sea spray aerosol

PubMed Central

Prather, Kimberly A.; Bertram, Timothy H.; Grassian, Vicki H.; Deane, Grant B.; Stokes, M. Dale; DeMott, Paul J.; Aluwihare, Lihini I.; Palenik, Brian P.; Azam, Farooq; Seinfeld, John H.; Moffet, Ryan C.; Molina, Mario J.; Cappa, Christopher D.; Geiger, Franz M.; Roberts, Gregory C.; Russell, Lynn M.; Ault, Andrew P.; Baltrusaitis, Jonas; Collins, Douglas B.; Corrigan, Craig E.; Cuadra-Rodriguez, Luis A.; Ebben, Carlena J.; Forestieri, Sara D.; Guasco, Timothy L.; Hersey, Scott P.; Kim, Michelle J.; Lambert, William F.; Modini, Robin L.; Mui, Wilton; Pedler, Byron E.; Ruppel, Matthew J.; Ryder, Olivia S.; Schoepp, Nathan G.; Sullivan, Ryan C.; Zhao, Defeng

2013-01-01

The production, size, and chemical composition of sea spray aerosol (SSA) particles strongly depend on seawater chemistry, which is controlled by physical, chemical, and biological processes. Despite decades of studies in marine environments, a direct relationship has yet to be established between ocean biology and the physicochemical properties of SSA. The ability to establish such relationships is hindered by the fact that SSA measurements are typically dominated by overwhelming background aerosol concentrations even in remote marine environments. Herein, we describe a newly developed approach for reproducing the chemical complexity of SSA in a laboratory setting, comprising a unique ocean-atmosphere facility equipped with actual breaking waves. A mesocosm experiment was performed in natural seawater, using controlled phytoplankton and heterotrophic bacteria concentrations, which showed SSA size and chemical mixing state are acutely sensitive to the aerosol production mechanism, as well as to the type of biological species present. The largest reduction in the hygroscopicity of SSA occurred as heterotrophic bacteria concentrations increased, whereas phytoplankton and chlorophyll-a concentrations decreased, directly corresponding to a change in mixing state in the smallest (60–180 nm) size range. Using this newly developed approach to generate realistic SSA, systematic studies can now be performed to advance our fundamental understanding of the impact of ocean biology on SSA chemical mixing state, heterogeneous reactivity, and the resulting climate-relevant properties. PMID:23620519

The evolution of the Krebs cycle: A promising subject for meaningful learning of biochemistry.

PubMed

da Costa, Caetano; Galembeck, Eduardo

2016-05-06

Evolution has been recognized as a key concept for biologists. To enhance comprehension and motivate biology undergraduates for the contents of central energetic metabolism, we addressed the Krebs cycle structure and functions in an evolutionary view. To this end, we created a study guide that contextualizes the emergence of the cyclic pathway, in light of the prokaryotic influence since the early anaerobic condition of the Earth to increase oxygen in the atmosphere. The study guide is composed of three interrelated sections: (1) a problem, designed to arouse curiosity, inform and motivate students, (2) a text about life evolution, including early microorganisms and the emergence of the Krebs cycle, and (3) questions for debate. The activity consisted on individual reading and peer discussion based on this written material, under the guidance of the instructors. The questions were designed to foster debate in an ever-increasing level of complexity and to strengthen the main contextual aspects leading to emergence, evolving, and permanency of a complex metabolic pathway. Based on classroom observation, analysis of student's written responses, and individual interviews, we noticed they were engaged and motivated by the task, especially during group discussion. The whole experience suggests that the study guide was a stimulus to broaden the comprehension of the Krebs cycle, reinforcing the evolutionary approach as an important subject for learning purposes. © 2016 by The International Union of Biochemistry and Molecular Biology, 44:288-296, 2016. © 2016 The International Union of Biochemistry and Molecular Biology.

Photo-damage protective effect of two facial products, containing a unique complex of Dead Sea minerals and Himalayan actives.

PubMed

Wineman, Eitan; Portugal-Cohen, Meital; Soroka, Yoram; Cohen, Dror; Schlippe, Gerrit; Voss, Werner; Brenner, Sarah; Milner, Yoram; Hai, Noam; Ma'or, Zeevi

2012-09-01

Skin appearance is badly affected when exposed to solar UV rays, which encourage physiological and structural cutaneous alterations that eventually lead to skin photo-damage. To test the capability of two facial preparations, extreme day cream (EXD) and extreme night treatment (EXN), containing a unique complex of Dead Sea water and three Himalayan extracts, to antagonize biological effects induced by photo-damage. Pieces of organ cultures of human skin were used as a model to assess the biological effects of UVB irradiation and the protective effect of topical application of two Extreme preparations. Skin pieces were analyzed for mitochondrial activity by MTT assay, for apoptosis by caspase 3 assay, and for cytokine secretion by solid phase ELISA. Human subjects were tested to evaluate the effect of Extreme preparations on skin wrinkle depth using PRIMOS and skin hydration by a corneometer. UVB irradiation induced cell apoptosis in the epidermis of skin organ cultures and increased their pro-inflammatory cytokine, tumor necrosis α (TNFα) secretion. Topical applications of both preparations significantly attenuated all these effects. Furthermore, in human subjects, a reduction in wrinkle depth and an elevation in the intense skin moisture were observed. The observations clearly show that EXD and EXN preparations have protective anti-apoptotic and anti-inflammatory properties that can attenuate biological effects of skin photo-damage. Topical application of the preparations improves skin appearance by reducing its wrinkles depth and increasing its moisturizing impact. © 2012 Wiley Periodicals, Inc.

Effects of aerobic and anaerobic biological processes on leaching of heavy metals from soil amended with sewage sludge compost.

PubMed

Fang, Wen; Wei, Yonghong; Liu, Jianguo; Kosson, David S; van der Sloot, Hans A; Zhang, Peng

2016-12-01

The risk from leaching of heavy metals is a major factor hindering land application of sewage sludge compost (SSC). Understanding the change in heavy metal leaching resulting from soil biological processes provides important information for assessing long-term behavior of heavy metals in the compost amended soil. In this paper, 180days aerobic incubation and 240days anaerobic incubation were conducted to investigate the effects of the aerobic and anaerobic biological processes on heavy metal leaching from soil amended with SSC, combined with chemical speciation modeling. Results showed that leaching concentrations of heavy metals at natural pH were similar before and after biological process. However, the major processes controlling heavy metals were influenced by the decrease of DOC with organic matter mineralization during biological processes. Mineralization of organic matter lowered the contribution of DOC-complexation to Ni and Zn leaching. Besides, the reducing condition produced by biological processes, particularly by the anaerobic biological process, resulted in the loss of sorption sites for As on Fe hydroxide, which increased the potential risk of As release at alkaline pH. Copyright © 2016 Elsevier Ltd. All rights reserved.

Complex adaptive systems: concept analysis.

PubMed

Holden, Lela M

2005-12-01

The aim of this paper is to explicate the concept of complex adaptive systems through an analysis that provides a description, antecedents, consequences, and a model case from the nursing and health care literature. Life is more than atoms and molecules--it is patterns of organization. Complexity science is the latest generation of systems thinking that investigates patterns and has emerged from the exploration of the subatomic world and quantum physics. A key component of complexity science is the concept of complex adaptive systems, and active research is found in many disciplines--from biology to economics to health care. However, the research and literature related to these appealing topics have generated confusion. A thorough explication of complex adaptive systems is needed. A modified application of the methods recommended by Walker and Avant for concept analysis was used. A complex adaptive system is a collection of individual agents with freedom to act in ways that are not always totally predictable and whose actions are interconnected. Examples include a colony of termites, the financial market, and a surgical team. It is often referred to as chaos theory, but the two are not the same. Chaos theory is actually a subset of complexity science. Complexity science offers a powerful new approach--beyond merely looking at clinical processes and the skills of healthcare professionals. The use of complex adaptive systems as a framework is increasing for a wide range of scientific applications, including nursing and healthcare management research. When nursing and other healthcare managers focus on increasing connections, diversity, and interactions they increase information flow and promote creative adaptation referred to as self-organization. Complexity science builds on the rich tradition in nursing that views patients and nursing care from a systems perspective.

Gaseous VOCs rapidly modify particulate matter and its biological effects – Part 1: Simple VOCs and model PM

PubMed Central

Ebersviller, S.; Lichtveld, K.; Sexton, K. G.; Zavala, J.; Lin, Y-H.; Jaspers, I.; Jeffries, H. E.

2013-01-01

This is the first of a three-part study designed to demonstrate dynamic entanglements among gaseous organic compounds (VOC), particulate matter (PM), and their subsequent potential biological effects. We study these entanglements in increasingly complex VOC and PM mixtures in urban-like conditions in a large outdoor chamber. To the traditional chemical and physical characterizations of gas and PM, we added new measurements of gas-only- and PM-only-biological effects, using cultured human lung cells as model indicators. These biological effects are assessed here as increases in cellular damage or expressed irritation (i.e., cellular toxic effects) from cells exposed to chamber air relative to cells exposed to clean air. The exposure systems permit gas-only- or PM-only-exposures from the same air stream containing both gases and PM in equilibria, i.e., there are no extractive operations prior to cell exposure. Our simple experiments in this part of the study were designed to eliminate many competing atmospheric processes to reduce ambiguity in our results. Simple volatile and semi-volatile organic gases that have inherent cellular toxic properties were tested individually for biological effect in the dark (at constant humidity). Airborne mixtures were then created with each compound and PM that has no inherent cellular toxic properties for another cellular exposure. Acrolein and p-tolualdehyde were used as model VOCs and mineral oil aerosol (MOA) was selected as a surrogate for organic-containing PM. MOA is appropriately complex in composition to represent ambient PM, and it exhibits no inherent cellular toxic effects and thus did not contribute any biological detrimental effects on its own. Chemical measurements, combined with the responses of our biological exposures, clearly demonstrate that gas-phase pollutants can modify the composition of PM (and its resulting detrimental effects on lung cells) – even if the gas-phase pollutants are not considered likely to partition to the condensed phase: the VOC-modified-PM showed significantly more damage and inflammation to lung cells than did the original PM. Because gases and PM are transported and deposited differently within the atmosphere and the lungs, these results have significant consequences. For example, current US policies for research and regulation of PM do not recognize this “effect modification” phenomena (NAS, 2004). These results present an unambiguous demonstration that – even in these simple mixtures – physical and thermal interactions alone can cause a modification of the distribution of species among the phases of airborne pollution mixtures and can result in a non-toxic phase becoming toxic due to atmospheric thermal processes only. Subsequent work extends the simple results reported here to systems with photochemical transformations of complex urban mixtures and to systems with diesel exhaust produced by different fuels. PMID:23457430

Nonproliferation Test and Evaluation Complex - NPTEC

ScienceCinema

None

2018-01-16

The Nonproliferation Test and Evaluation Complex, or NPTEC, is the world's largest facility for open air testing of hazardous toxic materials and biological simulants. NPTEC is used for testing, experimentation, and training for technologies that require the release of toxic chemicals or biological simulants into the environment.

Entropy for the Complexity of Physiological Signal Dynamics.

PubMed

Zhang, Xiaohua Douglas

2017-01-01

Recently, the rapid development of large data storage technologies, mobile network technology, and portable medical devices makes it possible to measure, record, store, and track analysis of biological dynamics. Portable noninvasive medical devices are crucial to capture individual characteristics of biological dynamics. The wearable noninvasive medical devices and the analysis/management of related digital medical data will revolutionize the management and treatment of diseases, subsequently resulting in the establishment of a new healthcare system. One of the key features that can be extracted from the data obtained by wearable noninvasive medical device is the complexity of physiological signals, which can be represented by entropy of biological dynamics contained in the physiological signals measured by these continuous monitoring medical devices. Thus, in this chapter I present the major concepts of entropy that are commonly used to measure the complexity of biological dynamics. The concepts include Shannon entropy, Kolmogorov entropy, Renyi entropy, approximate entropy, sample entropy, and multiscale entropy. I also demonstrate an example of using entropy for the complexity of glucose dynamics.

Charge-transfer interaction of drug quinidine with quinol, picric acid and DDQ: Spectroscopic characterization and biological activity studies towards understanding the drug-receptor mechanism.

PubMed

Eldaroti, Hala H; Gadir, Suad A; Refat, Moamen S; Adam, Abdel Majid A

2014-04-01

Investigation of charge-transfer (CT) complexes of drugs has been recognized as an important phenomenon in understanding of the drug-receptor binding mechanism. Structural, thermal, morphological and biological behavior of CT complexes formed between drug quinidine (Qui) as a donor and quinol (QL), picric acid (PA) or dichlorodicyanobenzoquinone (DDQ) as acceptors were reported. The newly synthesized CT complexes have been spectroscopically characterized via elemental analysis; infrared (IR), Raman, 1 H NMR and electronic absorption spectroscopy; powder X-ray diffraction (PXRD); thermogravimetric (TG) analysis and scanning electron microscopy (SEM). It was found that the obtained complexes are nanoscale, semi-crystalline particles, thermally stable and spontaneous. The molecular composition of the obtained complexes was determined using spectrophotometric titration method and was found to be 1:1 ratios (donor:acceptor). Finally, the biological activities of the obtained CT complexes were tested for their antibacterial activities. The results obtained herein are satisfactory for estimation of drug Qui in the pharmaceutical form.

[Biological role of fetuin A and its potential importance for prediction of cardiovascular risk in patients with type 2 diabetes mellitus].

PubMed

Horshuns'ka, M Iu; Karachentsev, Iu I; Kravchun, N O; Ĭensen, É; Leshchenko, Zh A; Hladkykh, O I; Krasova, N S; Tyzhnenko, T V; Opaleĭko, Iu A; Poltorak, V V

2013-01-01

The authors' data and those from literature concerning biological role of fetuin A glycoprotein have been generalized in the article. A direct correlation has been established between fetuin A and some adipokines involved in the formation of insulin resistance and atherogenesis (progranulin, omentin-1), and osteoprotegerin (the novel cardiovascular risk factor) as well as an increase of circulating levels of fetuin A in patients with type 2 diabetes mellitus with high cardiovascular risk metabolic pattern but without manifestations of macrovascular complications. This substantiates the involvement of fetuin A in the complex of biomarkers of subclinical atherosclerosis.

High-throughput screening for bioactive components from traditional Chinese medicine.

PubMed

Zhu, Yanhui; Zhang, Zhiyun; Zhang, Meng; Mais, Dale E; Wang, Ming-Wei

2010-12-01

Throughout the centuries, traditional Chinese medicine has been a rich resource in the development of new drugs. Modern drug discovery, which relies increasingly on automated high throughput screening and quick hit-to-lead development, however, is confronted with the challenges of the chemical complexity associated with natural products. New technologies for biological screening as well as library building are in great demand in order to meet the requirements. Here we review the developments in these techniques under the perspective of their applicability in natural product drug discovery. Methods in library building, component characterizing, biological evaluation, and other screening methods including NMR and X-ray diffraction are discussed.

Ecological Limits to Terrestrial Carbon Dioxide Removal Strategies

NASA Astrophysics Data System (ADS)

Smith, L. J.; Torn, M. S.; Jones, A. D.

2011-12-01

Carbon dioxide removal from the atmosphere through terrestrial carbon sequestration and bioenergy (biological CDR) is a proposed climate change mitigation strategy. Biological CDR increases the carbon storage capacity of soils and biomass through changes in land cover and use, including reforestation, afforestation, conversion of land to agriculture for biofuels, conversion of degraded land to grassland, and alternative management practices such as conservation tillage. While biological CDR may play a valuable role in future climate change mitigation, many of its proponents fail to account for the full range of biological, biophysical, hydrologic, and economic complexities associated with proposed land use changes. In this analysis, we identify and discuss a set of ecological limits and impacts associated with terrestrial CDR. The capacity of biofuels, soils, and other living biomass to sequester carbon may be constrained by nutrient and water availability, soil dynamics, and local climate effects, all of which can change spatially and temporally in unpredictable ways. Even if CDR is effective at sequestering CO2, its associated land use and land cover changes may negatively impact ecological resources by compromising water quality and availability, degrading soils, reducing biodiversity, displacing agriculture, and altering local climate through albedo and evapotranspiration changes. Measures taken to overcome ecological limitations, such as fertilizer addition and irrigation, may exacerbate these impacts even further. The ecological considerations and quantitative analyses that we present highlight uncertainties introduced by ecological complexity, disagreements between models, perverse economic incentives, and changing environmental factors. We do not reject CDR as a potentially valuable strategy for climate change mitigation; ecosystem protection, restoration, and improved management practices could enhance soil fertility and protect biodiversity while reducing increases in atmospheric CO2. Rather, we emphasize the importance of evaluating the full set of biological, physical, economic, and political realities that accompany land-use changes and manipulations to the carbon cycle. While the immediate goal of biological CDR is to reduce atmospheric CO2 concentrations, its ultimate goal in mitigating climate change is to reduce the threats to ecosystems and society. Sequestering carbon at the cost of ecosystem health would not be a sensible approach.

Pharmaceutical applications of cyclodextrins: effects on drug permeation through biological membranes.

PubMed

Loftsson, Thorsteinn; Brewster, Marcus E

2011-09-01

Cyclodextrins are useful solubilizing excipients that have gained currency in the formulator's armamentarium based on their ability to temporarily camouflage undesirable physicochemical properties. In this context cyclodextrins can increase oral bioavailability, stabilize compounds to chemical and enzymatic degradation and can affect permeability through biological membranes under certain circumstances. This latter property is examined herein as a function of the published literature as well as work completed in our laboratories.   Cyclodextrins can increase the uptake of drugs through biological barriers if the limiting barrier component is the unstirred water layer (UWL) that exists between the membrane and bulk water. This means that cyclodextrins are most useful when they interact with lipophiles in systems where such an UWL is present and contributes significantly to the barrier properties of the membrane. Furthermore, these principles are used to direct the optimal formulation of drugs in cyclodextrins. A second related critical success factor in the formulation of cyclodextrin-based drug product is an understanding of the kinetics and thermodynamics of complexation and the need to optimize the cyclodextrin amount and drug-to-cyclodextrin ratios. Drug formulations, especially those targeting compartments associated with limited dissolution (i.e. the eye, subcutaneous space, etc.), should be carefully designed such that the thermodynamic activity of the drug in the formulation is optimal meaning that there is sufficient cyclodextrin to solubilize the drug but not more than that. Increasing the cyclodextrin concentration decreases the formulation 'push' and may reduce the bioavailability of the system. A mechanism-based understanding of cyclodextrin complexation is essential for the appropriate formulation of contemporary drug candidates. © 2011 The Authors. JPP © 2011 Royal Pharmaceutical Society.

An efficient grid layout algorithm for biological networks utilizing various biological attributes

PubMed Central

Kojima, Kaname; Nagasaki, Masao; Jeong, Euna; Kato, Mitsuru; Miyano, Satoru

2007-01-01

Background Clearly visualized biopathways provide a great help in understanding biological systems. However, manual drawing of large-scale biopathways is time consuming. We proposed a grid layout algorithm that can handle gene-regulatory networks and signal transduction pathways by considering edge-edge crossing, node-edge crossing, distance measure between nodes, and subcellular localization information from Gene Ontology. Consequently, the layout algorithm succeeded in drastically reducing these crossings in the apoptosis model. However, for larger-scale networks, we encountered three problems: (i) the initial layout is often very far from any local optimum because nodes are initially placed at random, (ii) from a biological viewpoint, human layouts still exceed automatic layouts in understanding because except subcellular localization, it does not fully utilize biological information of pathways, and (iii) it employs a local search strategy in which the neighborhood is obtained by moving one node at each step, and automatic layouts suggest that simultaneous movements of multiple nodes are necessary for better layouts, while such extension may face worsening the time complexity. Results We propose a new grid layout algorithm. To address problem (i), we devised a new force-directed algorithm whose output is suitable as the initial layout. For (ii), we considered that an appropriate alignment of nodes having the same biological attribute is one of the most important factors of the comprehension, and we defined a new score function that gives an advantage to such configurations. For solving problem (iii), we developed a search strategy that considers swapping nodes as well as moving a node, while keeping the order of the time complexity. Though a naïve implementation increases by one order, the time complexity, we solved this difficulty by devising a method that caches differences between scores of a layout and its possible updates. Conclusion Layouts of the new grid layout algorithm are compared with that of the previous algorithm and human layout in an endothelial cell model, three times as large as the apoptosis model. The total cost of the result from the new grid layout algorithm is similar to that of the human layout. In addition, its convergence time is drastically reduced (40% reduction). PMID:17338825

Industrial systems biology and its impact on synthetic biology of yeast cell factories.

PubMed

Fletcher, Eugene; Krivoruchko, Anastasia; Nielsen, Jens

2016-06-01

Engineering industrial cell factories to effectively yield a desired product while dealing with industrially relevant stresses is usually the most challenging step in the development of industrial production of chemicals using microbial fermentation processes. Using synthetic biology tools, microbial cell factories such as Saccharomyces cerevisiae can be engineered to express synthetic pathways for the production of fuels, biopharmaceuticals, fragrances, and food flavors. However, directing fluxes through these synthetic pathways towards the desired product can be demanding due to complex regulation or poor gene expression. Systems biology, which applies computational tools and mathematical modeling to understand complex biological networks, can be used to guide synthetic biology design. Here, we present our perspective on how systems biology can impact synthetic biology towards the goal of developing improved yeast cell factories. Biotechnol. Bioeng. 2016;113: 1164-1170. © 2015 Wiley Periodicals, Inc. © 2015 Wiley Periodicals, Inc.

Omics/systems biology and cancer cachexia.

PubMed

Gallagher, Iain J; Jacobi, Carsten; Tardif, Nicolas; Rooyackers, Olav; Fearon, Kenneth

2016-06-01

Cancer cachexia is a complex syndrome generated by interaction between the host and tumour cells with a background of treatment effects and toxicity. The complexity of the physiological pathways likely involved in cancer cachexia necessitates a holistic view of the relevant biology. Emergent properties are characteristic of complex systems with the result that the end result is more than the sum of its parts. Recognition of the importance of emergent properties in biology led to the concept of systems biology wherein a holistic approach is taken to the biology at hand. Systems biology approaches will therefore play an important role in work to uncover key mechanisms with therapeutic potential in cancer cachexia. The 'omics' technologies provide a global view of biological systems. Genomics, transcriptomics, proteomics, lipidomics and metabolomics approaches all have application in the study of cancer cachexia to generate systems level models of the behaviour of this syndrome. The current work reviews recent applications of these technologies to muscle atrophy in general and cancer cachexia in particular with a view to progress towards integration of these approaches to better understand the pathology and potential treatment pathways in cancer cachexia. Copyright © 2016. Published by Elsevier Ltd.

Studying the dynamics of interbeat interval time series of healthy and congestive heart failure subjects using scale based symbolic entropy analysis

PubMed Central

Awan, Imtiaz; Aziz, Wajid; Habib, Nazneen; Alowibdi, Jalal S.; Saeed, Sharjil; Nadeem, Malik Sajjad Ahmed; Shah, Syed Ahsin Ali

2018-01-01

Considerable interest has been devoted for developing a deeper understanding of the dynamics of healthy biological systems and how these dynamics are affected due to aging and disease. Entropy based complexity measures have widely been used for quantifying the dynamics of physical and biological systems. These techniques have provided valuable information leading to a fuller understanding of the dynamics of these systems and underlying stimuli that are responsible for anomalous behavior. The single scale based traditional entropy measures yielded contradictory results about the dynamics of real world time series data of healthy and pathological subjects. Recently the multiscale entropy (MSE) algorithm was introduced for precise description of the complexity of biological signals, which was used in numerous fields since its inception. The original MSE quantified the complexity of coarse-grained time series using sample entropy. The original MSE may be unreliable for short signals because the length of the coarse-grained time series decreases with increasing scaling factor τ, however, MSE works well for long signals. To overcome the drawback of original MSE, various variants of this method have been proposed for evaluating complexity efficiently. In this study, we have proposed multiscale normalized corrected Shannon entropy (MNCSE), in which instead of using sample entropy, symbolic entropy measure NCSE has been used as an entropy estimate. The results of the study are compared with traditional MSE. The effectiveness of the proposed approach is demonstrated using noise signals as well as interbeat interval signals from healthy and pathological subjects. The preliminary results of the study indicate that MNCSE values are more stable and reliable than original MSE values. The results show that MNCSE based features lead to higher classification accuracies in comparison with the MSE based features. PMID:29771977

An analysis of species boundaries and biogeographic patterns in a cryptic species complex: the rotifer--Brachionus plicatilis.

PubMed

Suatoni, Elizabeth; Vicario, Saverio; Rice, Sean; Snell, Terry; Caccone, Adalgisa

2006-10-01

Since the advent of molecular phylogenetics, there is increasing evidence that many small aquatic and marine invertebrates--once believed to be single, cosmopolitan species--are in fact cryptic species complexes. Although the application of the biological species concept is central to the identification of species boundaries in these cryptic complexes, tests of reproductive isolation do not frequently accompany phylogenetic studies. Because different species concepts generally identify different boundaries in cryptic complexes, studies that apply multiple species concepts are needed to gain a more detailed understanding of patterns of diversification in these taxa. Here we explore different methods of empirically delimiting species boundaries in the salt water rotifer Brachionus plicatilis by comparing reproductive data (i.e., the traditional biological species concept) to phylogenetic data (the genealogical species concept). Based on a high degree of molecular sequence divergence and largely concordant genetic patterns in COI and ITS1, the genealogical species hypothesis indicates the existence of at least 14 species--the highest estimate for the group thus far. A test of the genealogical species concept with biological crosses shows a fairly high level of concordance, depending on the degree of reproductive success used to draw boundaries. The convergence of species concepts in this group suggests that many of the species within the group may be old. Although the diversity of the group is higher than previously understood, geographic distributions remain broad. Efficient passive dispersal has resulted in global distributions for many species with some evidence of isolation by distance over large geographic scales. These patterns concur with expectations that micro-meiofauna (0.1-1mm) have biogeographies intermediate to microbial organisms and large vertebrates. Sympatry of genetically distant strains is common.

Direct Deposition of Gas Phase Generated Aerosol Gold Nanoparticles into Biological Fluids - Corona Formation and Particle Size Shifts

PubMed Central

Svensson, Christian R.; Messing, Maria E.; Lundqvist, Martin; Schollin, Alexander; Deppert, Knut; Pagels, Joakim H.; Rissler, Jenny; Cedervall, Tommy

2013-01-01

An ongoing discussion whether traditional toxicological methods are sufficient to evaluate the risks associated with nanoparticle inhalation has led to the emergence of Air-Liquid interface toxicology. As a step in this process, this study explores the evolution of particle characteristics as they move from the airborne state into physiological solution. Airborne gold nanoparticles (AuNP) are generated using an evaporation-condensation technique. Spherical and agglomerate AuNPs are deposited into physiological solutions of increasing biological complexity. The AuNP size is characterized in air as mobility diameter and in liquid as hydrodynamic diameter. AuNP:Protein aggregation in physiological solutions is determined using dynamic light scattering, particle tracking analysis, and UV absorption spectroscopy. AuNPs deposited into homocysteine buffer form large gold-aggregates. Spherical AuNPs deposited in solutions of albumin were trapped at the Air-Liquid interface but was readily suspended in the solutions with a size close to that of the airborne particles, indicating that AuNP:Protein complex formation is promoted. Deposition into serum and lung fluid resulted in larger complexes, reflecting the formation of a more complex protein corona. UV absorption spectroscopy indicated no further aggregation of the AuNPs after deposition in solution. The corona of the deposited AuNPs shows differences compared to AuNPs generated in suspension. Deposition of AuNPs from the aerosol phase into biological fluids offers a method to study the protein corona formed, upon inhalation and deposition in the lungs in a more realistic way compared to particle liquid suspensions. This is important since the protein corona together with key particle properties (e.g. size, shape and surface reactivity) to a large extent may determine the nanoparticle effects and possible translocation to other organs. PMID:24086363

Studying the dynamics of interbeat interval time series of healthy and congestive heart failure subjects using scale based symbolic entropy analysis.

PubMed

Awan, Imtiaz; Aziz, Wajid; Shah, Imran Hussain; Habib, Nazneen; Alowibdi, Jalal S; Saeed, Sharjil; Nadeem, Malik Sajjad Ahmed; Shah, Syed Ahsin Ali

2018-01-01

Considerable interest has been devoted for developing a deeper understanding of the dynamics of healthy biological systems and how these dynamics are affected due to aging and disease. Entropy based complexity measures have widely been used for quantifying the dynamics of physical and biological systems. These techniques have provided valuable information leading to a fuller understanding of the dynamics of these systems and underlying stimuli that are responsible for anomalous behavior. The single scale based traditional entropy measures yielded contradictory results about the dynamics of real world time series data of healthy and pathological subjects. Recently the multiscale entropy (MSE) algorithm was introduced for precise description of the complexity of biological signals, which was used in numerous fields since its inception. The original MSE quantified the complexity of coarse-grained time series using sample entropy. The original MSE may be unreliable for short signals because the length of the coarse-grained time series decreases with increasing scaling factor τ, however, MSE works well for long signals. To overcome the drawback of original MSE, various variants of this method have been proposed for evaluating complexity efficiently. In this study, we have proposed multiscale normalized corrected Shannon entropy (MNCSE), in which instead of using sample entropy, symbolic entropy measure NCSE has been used as an entropy estimate. The results of the study are compared with traditional MSE. The effectiveness of the proposed approach is demonstrated using noise signals as well as interbeat interval signals from healthy and pathological subjects. The preliminary results of the study indicate that MNCSE values are more stable and reliable than original MSE values. The results show that MNCSE based features lead to higher classification accuracies in comparison with the MSE based features.

Electrospun poly(ε-caprolactone) matrices containing silver sulfadiazine complexed with β-cyclodextrin as a new pharmaceutical dosage form to wound healing: preliminary physicochemical and biological evaluation.

PubMed

Souza, Sarah Oliveira Lamas; Cotrim, Monique Alvarenga Pinto; Oréfice, Rodrigo Lambert; Carvalho, Suzana Gonçalves; Dutra, Jessyca Aparecida Paes; de Paula Careta, Francisco; Resende, Juliana Alves; Villanova, Janaina Cecília Oliveira

2018-05-10

Cooperation between researchers in the areas of medical, pharmaceutical and materials science has facilitated the development of pharmaceutical dosage forms that elicit therapeutic effects and protective action with a single product. In addition to optimizing pharmacologic action, such dosage forms provide greater patient comfort and increase success and treatment compliance. In the present work, we prepared semipermeable bioactive electrospun fibers for use as wound dressings containing silver sulfadiazine complexed with β-cyclodextrin in a poly(Ɛ-caprolactone) nanofiber matrix aiming to reduce the direct contact between silver and skin and to modulate the drug release. Wound dressings were prepared by electrospinning, and were subjected to ATR-FT-IR and TG/DTG assays to evaluate drug stability. The hydrophilicity of the fibrous nanostructure in water and PBS buffer was studied by goniometry. Electrospun fibers permeability and swelling capacity were assessed, and a dissolution test was performed. In vitro biological tests were realized to investigate the biological compatibility and antimicrobial activity. We obtained flexible matrices that were each approximately 1.0 g in weight. The electrospun fibers were shown to be semipermeable, with water vapor transmission and swelling indexes compatible with the proposed objective. The hydrophilicity was moderate. Matrices containing pure drug modulated drug release adequately during 24 h but presented a high hemolytic index. Complexation promoted a decrease in the hemolytic index and in the drug release but did not negatively impact antimicrobial activity. The drug was released predominantly by diffusion. These results indicate that electrospun PCL matrices containing β-cyclodextrin/silver sulfadiazine inclusion complexes are a promising pharmaceutical dosage form for wound healing.

Simulating complex intracellular processes using object-oriented computational modelling.

PubMed

Johnson, Colin G; Goldman, Jacki P; Gullick, William J

2004-11-01

The aim of this paper is to give an overview of computer modelling and simulation in cellular biology, in particular as applied to complex biochemical processes within the cell. This is illustrated by the use of the techniques of object-oriented modelling, where the computer is used to construct abstractions of objects in the domain being modelled, and these objects then interact within the computer to simulate the system and allow emergent properties to be observed. The paper also discusses the role of computer simulation in understanding complexity in biological systems, and the kinds of information which can be obtained about biology via simulation.

Chemistry and biological activity of platinum amidine complexes.

PubMed

Michelin, Rino A; Sgarbossa, Paolo; Sbovata, Silvia Mazzega; Gandin, Valentina; Marzano, Cristina; Bertani, Roberta

2011-07-04

Platinum amidine complexes represent a new class of potential antitumor drugs that contain the imino moiety HN=C(sp(2)) bonded to the platinum center. They can be related to the iminoether derivatives, which were recently shown to be the first Pt(II) compounds with a trans configuration endowed with anticancer activity. The chemical and biological properties of platinum amidine complexes, and more generally of platinum imino derivatives, can be rationally modified through suitable synthetic procedures with the aim of improving their cytotoxicity and antitumor activity. The addition of protic nucleophiles to nitriles coordinated to platinum in various oxidation states can offer a wide variety of complexes with chemical, structural, and physical properties specifically tuned for a more efficacious biological response. Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Modeling biology with HDL languages: a first step toward a genetic design automation tool inspired from microelectronics.

PubMed

Gendrault, Yves; Madec, Morgan; Lallement, Christophe; Haiech, Jacques

2014-04-01

Nowadays, synthetic biology is a hot research topic. Each day, progresses are made to improve the complexity of artificial biological functions in order to tend to complex biodevices and biosystems. Up to now, these systems are handmade by bioengineers, which require strong technical skills and leads to nonreusable development. Besides, scientific fields that share the same design approach, such as microelectronics, have already overcome several issues and designers succeed in building extremely complex systems with many evolved functions. On the other hand, in systems engineering and more specifically in microelectronics, the development of the domain has been promoted by both the improvement of technological processes and electronic design automation tools. The work presented in this paper paves the way for the adaptation of microelectronics design tools to synthetic biology. Considering the similarities and differences between the synthetic biology and microelectronics, the milestones of this adaptation are described. The first one concerns the modeling of biological mechanisms. To do so, a new formalism is proposed, based on an extension of the generalized Kirchhoff laws to biology. This way, a description of all biological mechanisms can be made with languages widely used in microelectronics. Our approach is therefore successfully validated on specific examples drawn from the literature.

Biological roles of glycans

PubMed Central

Varki, Ajit

2017-01-01

Abstract Simple and complex carbohydrates (glycans) have long been known to play major metabolic, structural and physical roles in biological systems. Targeted microbial binding to host glycans has also been studied for decades. But such biological roles can only explain some of the remarkable complexity and organismal diversity of glycans in nature. Reviewing the subject about two decades ago, one could find very few clear-cut instances of glycan-recognition-specific biological roles of glycans that were of intrinsic value to the organism expressing them. In striking contrast there is now a profusion of examples, such that this updated review cannot be comprehensive. Instead, a historical overview is presented, broad principles outlined and a few examples cited, representing diverse types of roles, mediated by various glycan classes, in different evolutionary lineages. What remains unchanged is the fact that while all theories regarding biological roles of glycans are supported by compelling evidence, exceptions to each can be found. In retrospect, this is not surprising. Complex and diverse glycans appear to be ubiquitous to all cells in nature, and essential to all life forms. Thus, >3 billion years of evolution consistently generated organisms that use these molecules for many key biological roles, even while sometimes coopting them for minor functions. In this respect, glycans are no different from other major macromolecular building blocks of life (nucleic acids, proteins and lipids), simply more rapidly evolving and complex. It is time for the diverse functional roles of glycans to be fully incorporated into the mainstream of biological sciences. PMID:27558841

Profiling Bioactivity of the ToxCast Chemical Library Using BioMAP Primary Human Cell Systems

EPA Science Inventory

The complexity of human biology has made prediction of health effects as a consequence of exposure to environmental chemicals especially challenging. Complex cell systems, such as the Biologically Multiplexed Activity Profiling (BioMAP) primary, human, cell-based disease models, ...

High-Molecular-Weight Proanthocyanidins in Foods: Overcoming Analytical Challenges in Pursuit of Novel Dietary Bioactive Components.

PubMed

Neilson, Andrew P; O'Keefe, Sean F; Bolling, Bradley W

2016-01-01

Proanthocyanidins (PACs) are an abundant but complex class of polyphenols found in foods and botanicals. PACs are polymeric flavanols with a variety of linkages and subunits. Connectivity and degree of polymerization (DP) determine PAC bioavailability and bioactivity. Current quantitative and qualitative methods may ignore a large percentage of dietary PACs. Subsequent correlations between intake and activity are hindered by a lack of understanding of the true PAC complexity in many foods. Additionally, estimates of dietary intakes are likely inaccurate, as nutrient databank values are largely based on standards from cocoa (monomers to decamers) and blueberries (mean DP of 36). Improved analytical methodologies are needed to increase our understanding of the biological roles of these complex compounds.

Ask not what physics can do for biology--ask what biology can do for physics.

PubMed

Frauenfelder, Hans

2014-10-08

Stan Ulam, the famous mathematician, said once to Hans Frauenfelder: 'Ask not what Physics can do for biology, ask what biology can do for physics'. The interaction between biologists and physicists is a two-way street. Biology reveals the secrets of complex systems, physics provides the physical tools and the theoretical concepts to understand the complexity. The perspective gives a personal view of the path to some of the physical concepts that are relevant for biology and physics (Frauenfelder et al 1999 Rev. Mod. Phys. 71 S419-S442). Schrödinger's book (Schrödinger 1944 What is Life? (Cambridge: Cambridge University Press)), loved by physicists and hated by eminent biologists (Dronamraju 1999 Genetics 153 1071-6), still shows how a great physicist looked at biology well before the first protein structure was known.

Aluminum-induced entropy in biological systems: implications for neurological disease.

PubMed

Shaw, Christopher A; Seneff, Stephanie; Kette, Stephen D; Tomljenovic, Lucija; Oller, John W; Davidson, Robert M

2014-01-01

Over the last 200 years, mining, smelting, and refining of aluminum (Al) in various forms have increasingly exposed living species to this naturally abundant metal. Because of its prevalence in the earth's crust, prior to its recent uses it was regarded as inert and therefore harmless. However, Al is invariably toxic to living systems and has no known beneficial role in any biological systems. Humans are increasingly exposed to Al from food, water, medicinals, vaccines, and cosmetics, as well as from industrial occupational exposure. Al disrupts biological self-ordering, energy transduction, and signaling systems, thus increasing biosemiotic entropy. Beginning with the biophysics of water, disruption progresses through the macromolecules that are crucial to living processes (DNAs, RNAs, proteoglycans, and proteins). It injures cells, circuits, and subsystems and can cause catastrophic failures ending in death. Al forms toxic complexes with other elements, such as fluorine, and interacts negatively with mercury, lead, and glyphosate. Al negatively impacts the central nervous system in all species that have been studied, including humans. Because of the global impacts of Al on water dynamics and biosemiotic systems, CNS disorders in humans are sensitive indicators of the Al toxicants to which we are being exposed.

Aluminum-Induced Entropy in Biological Systems: Implications for Neurological Disease

PubMed Central

Shaw, Christopher A.; Seneff, Stephanie; Kette, Stephen D.; Tomljenovic, Lucija; Oller, John W.; Davidson, Robert M.

2014-01-01

Over the last 200 years, mining, smelting, and refining of aluminum (Al) in various forms have increasingly exposed living species to this naturally abundant metal. Because of its prevalence in the earth's crust, prior to its recent uses it was regarded as inert and therefore harmless. However, Al is invariably toxic to living systems and has no known beneficial role in any biological systems. Humans are increasingly exposed to Al from food, water, medicinals, vaccines, and cosmetics, as well as from industrial occupational exposure. Al disrupts biological self-ordering, energy transduction, and signaling systems, thus increasing biosemiotic entropy. Beginning with the biophysics of water, disruption progresses through the macromolecules that are crucial to living processes (DNAs, RNAs, proteoglycans, and proteins). It injures cells, circuits, and subsystems and can cause catastrophic failures ending in death. Al forms toxic complexes with other elements, such as fluorine, and interacts negatively with mercury, lead, and glyphosate. Al negatively impacts the central nervous system in all species that have been studied, including humans. Because of the global impacts of Al on water dynamics and biosemiotic systems, CNS disorders in humans are sensitive indicators of the Al toxicants to which we are being exposed. PMID:25349607

Ways of incorporating photographic images in learning and assessing high school biology: A study of visual perception and visual cognition

NASA Astrophysics Data System (ADS)

Nixon, Brenda Chaumont

This study evaluated the cognitive benefits and costs of incorporating biology-textbook and student-generated photographic images into the learning and assessment processes within a 10th grade biology classroom. The study implemented Wandersee's (2000) 20-Q Model of Image-Based Biology Test-Item Design (20-Q Model) to explore the use of photographic images to assess students' understanding of complex biological processes. A thorough review of the students' textbook using ScaleMaster R with PC Interface was also conducted. The photographs, diagrams, and other representations found in the textbook were measured to determine the percentage of each graphic depicted in the book and comparisons were made to the text. The theoretical framework that guided the research included Human Constructivist tenets espoused by Mintzes, Wandersee and Novak (2000). Physiological and cognitive factors of images and image-based learning as described by Robin (1992), Solso (1997) and Wandersee (2000) were examined. Qualitative case study design presented by Yin (1994), Denzin and Lincoln (1994) was applied and data were collected through interviews, observations, student activities, student and school artifacts and Scale Master IIRTM measurements. The results of the study indicate that although 24% of the high school biology textbook is devoted to photographic images which contribute significantly to textbook cost, the teacher and students paid little attention to photographic images other than as aesthetic elements for creating biological ambiance, wasting valuable opportunities for learning. The analysis of the photographs corroborated findings published by the Association American Association for the Advancement of Science that indicated "While most of the books are lavishly illustrated, these representations are rarely helpful, because they are too abstract, needlessly complicated, or inadequately explained" (Roseman, 2000, p. 2). The findings also indicate that applying the 20-Q Model to photographs in biology textbooks can (a) effectively assess students' understanding of complex biological concepts, (b) offer alternative assessment strategies that complement individual learning styles, (c) identify misconceptions, and (d) encourage students to practice metacognition. In addition, once students have learned how to interpret textbook images, application of that knowledge through self-generated biologically relevant digital or print images provides opportunities for increased conceptual understanding.

Heuristic Identification of Biological Architectures for Simulating Complex Hierarchical Genetic Interactions

PubMed Central

Moore, Jason H; Amos, Ryan; Kiralis, Jeff; Andrews, Peter C

2015-01-01

Simulation plays an essential role in the development of new computational and statistical methods for the genetic analysis of complex traits. Most simulations start with a statistical model using methods such as linear or logistic regression that specify the relationship between genotype and phenotype. This is appealing due to its simplicity and because these statistical methods are commonly used in genetic analysis. It is our working hypothesis that simulations need to move beyond simple statistical models to more realistically represent the biological complexity of genetic architecture. The goal of the present study was to develop a prototype genotype–phenotype simulation method and software that are capable of simulating complex genetic effects within the context of a hierarchical biology-based framework. Specifically, our goal is to simulate multilocus epistasis or gene–gene interaction where the genetic variants are organized within the framework of one or more genes, their regulatory regions and other regulatory loci. We introduce here the Heuristic Identification of Biological Architectures for simulating Complex Hierarchical Interactions (HIBACHI) method and prototype software for simulating data in this manner. This approach combines a biological hierarchy, a flexible mathematical framework, a liability threshold model for defining disease endpoints, and a heuristic search strategy for identifying high-order epistatic models of disease susceptibility. We provide several simulation examples using genetic models exhibiting independent main effects and three-way epistatic effects. PMID:25395175

Siderocalin-mediated recognition, sensitization, and cellular uptake of actinides.

PubMed

Allred, Benjamin E; Rupert, Peter B; Gauny, Stacey S; An, Dahlia D; Ralston, Corie Y; Sturzbecher-Hoehne, Manuel; Strong, Roland K; Abergel, Rebecca J

2015-08-18

Synthetic radionuclides, such as the transuranic actinides plutonium, americium, and curium, present severe health threats as contaminants, and understanding the scope of the biochemical interactions involved in actinide transport is instrumental in managing human contamination. Here we show that siderocalin, a mammalian siderophore-binding protein from the lipocalin family, specifically binds lanthanide and actinide complexes through molecular recognition of the ligands chelating the metal ions. Using crystallography, we structurally characterized the resulting siderocalin-transuranic actinide complexes, providing unprecedented insights into the biological coordination of heavy radioelements. In controlled in vitro assays, we found that intracellular plutonium uptake can occur through siderocalin-mediated endocytosis. We also demonstrated that siderocalin can act as a synergistic antenna to sensitize the luminescence of trivalent lanthanide and actinide ions in ternary protein-ligand complexes, dramatically increasing the brightness and efficiency of intramolecular energy transfer processes that give rise to metal luminescence. Our results identify siderocalin as a potential player in the biological trafficking of f elements, but through a secondary ligand-based metal sequestration mechanism. Beyond elucidating contamination pathways, this work is a starting point for the design of two-stage biomimetic platforms for photoluminescence, separation, and transport applications.

Getting a Grip on Complexes

PubMed Central

Nie, Yan; Viola, Cristina; Bieniossek, Christoph; Trowitzsch, Simon; Vijay-achandran, Lakshmi Sumitra; Chaillet, Maxime; Garzoni, Frederic; Berger, Imre

2009-01-01

We are witnessing tremendous advances in our understanding of the organization of life. Complete genomes are being deciphered with ever increasing speed and accuracy, thereby setting the stage for addressing the entire gene product repertoire of cells, towards understanding whole biological systems. Advances in bioinformatics and mass spectrometric techniques have revealed the multitude of interactions present in the proteome. Multiprotein complexes are emerging as a paramount cornerstone of biological activity, as many proteins appear to participate, stably or transiently, in large multisubunit assemblies. Analysis of the architecture of these assemblies and their manifold interactions is imperative for understanding their function at the molecular level. Structural genomics efforts have fostered the development of many technologies towards achieving the throughput required for studying system-wide single proteins and small interaction motifs at high resolution. The present shift in focus towards large multiprotein complexes, in particular in eukaryotes, now calls for a likewise concerted effort to develop and provide new technologies that are urgently required to produce in quality and quantity the plethora of multiprotein assemblies that form the complexome, and to routinely study their structure and function at the molecular level. Current efforts towards this objective are summarized and reviewed in this contribution. PMID:20514218

Synthesis, Characterization, and Biological Activity Studies of Copper(II) Mixed Compound with Histamine and Nalidixic Acid

PubMed Central

Bivián-Castro, Egla Yareth; López, Mercedes G.; Pedraza-Reyes, Mario; Bernès, Sylvain; Mendoza-Díaz, Guillermo

2009-01-01

A mixed copper complex with deprotonated nalidixic acid (nal) and histamine (hsm) was synthesized and characterized by FTIR, UV-Vis, elemental analysis, and conductivity. The crystal structure of [Cu(hsm)(nal)H2O]Cl·3H2O (chn) showed a pentacoordinated cooper(II) in a square pyramidal geometry surrounded by two N atoms from hsm, two O atoms from the quinolone, and one apical water oxygen. Alteration of bacterial DNA structure and/or associated functions in vivo by [Cu(hsm)(nal)H2O]Cl·3H2O was demonstrated by the induction of a recA-lacZ fusion integrated at the amyE locus of a recombinant Bacillus subtilis strain. Results from circular dichroism and denaturation of calf thymus DNA (CT-DNA) suggested that increased amounts of copper complex were able to stabilize the double helix of DNA in vitro mainly by formation of hydrogen bonds between chn and the sugars of DNA minor groove. In vivo and in vitro biological activities of the chn complex were compared with the chemical nuclease [Cu(phen)(nal)H2O]NO3 · 3H2O (cpn) where phen is phenanthroline. PMID:19557138

Siderocalin-mediated recognition, sensitization, and cellular uptake of actinides

PubMed Central

Allred, Benjamin E.; Rupert, Peter B.; Gauny, Stacey S.; An, Dahlia D.; Ralston, Corie Y.; Sturzbecher-Hoehne, Manuel; Strong, Roland K.; Abergel, Rebecca J.

2015-01-01

Synthetic radionuclides, such as the transuranic actinides plutonium, americium, and curium, present severe health threats as contaminants, and understanding the scope of the biochemical interactions involved in actinide transport is instrumental in managing human contamination. Here we show that siderocalin, a mammalian siderophore-binding protein from the lipocalin family, specifically binds lanthanide and actinide complexes through molecular recognition of the ligands chelating the metal ions. Using crystallography, we structurally characterized the resulting siderocalin–transuranic actinide complexes, providing unprecedented insights into the biological coordination of heavy radioelements. In controlled in vitro assays, we found that intracellular plutonium uptake can occur through siderocalin-mediated endocytosis. We also demonstrated that siderocalin can act as a synergistic antenna to sensitize the luminescence of trivalent lanthanide and actinide ions in ternary protein–ligand complexes, dramatically increasing the brightness and efficiency of intramolecular energy transfer processes that give rise to metal luminescence. Our results identify siderocalin as a potential player in the biological trafficking of f elements, but through a secondary ligand-based metal sequestration mechanism. Beyond elucidating contamination pathways, this work is a starting point for the design of two-stage biomimetic platforms for photoluminescence, separation, and transport applications. PMID:26240330

Inference, simulation, modeling, and analysis of complex networks, with special emphasis on complex networks in systems biology

NASA Astrophysics Data System (ADS)

Christensen, Claire Petra

Across diverse fields ranging from physics to biology, sociology, and economics, the technological advances of the past decade have engendered an unprecedented explosion of data on highly complex systems with thousands, if not millions of interacting components. These systems exist at many scales of size and complexity, and it is becoming ever-more apparent that they are, in fact, universal, arising in every field of study. Moreover, they share fundamental properties---chief among these, that the individual interactions of their constituent parts may be well-understood, but the characteristic behaviour produced by the confluence of these interactions---by these complex networks---is unpredictable; in a nutshell, the whole is more than the sum of its parts. There is, perhaps, no better illustration of this concept than the discoveries being made regarding complex networks in the biological sciences. In particular, though the sequencing of the human genome in 2003 was a remarkable feat, scientists understand that the "cellular-level blueprints" for the human being are cellular-level parts lists, but they say nothing (explicitly) about cellular-level processes. The challenge of modern molecular biology is to understand these processes in terms of the networks of parts---in terms of the interactions among proteins, enzymes, genes, and metabolites---as it is these processes that ultimately differentiate animate from inanimate, giving rise to life! It is the goal of systems biology---an umbrella field encapsulating everything from molecular biology to epidemiology in social systems---to understand processes in terms of fundamental networks of core biological parts, be they proteins or people. By virtue of the fact that there are literally countless complex systems, not to mention tools and techniques used to infer, simulate, analyze, and model these systems, it is impossible to give a truly comprehensive account of the history and study of complex systems. The author's own publications have contributed network inference, simulation, modeling, and analysis methods to the much larger body of work in systems biology, and indeed, in network science. The aim of this thesis is therefore twofold: to present this original work in the historical context of network science, but also to provide sufficient review and reference regarding complex systems (with an emphasis on complex networks in systems biology) and tools and techniques for their inference, simulation, analysis, and modeling, such that the reader will be comfortable in seeking out further information on the subject. The review-like Chapters 1, 2, and 4 are intended to convey the co-evolution of network science and the slow but noticeable breakdown of boundaries between disciplines in academia as research and comparison of diverse systems has brought to light the shared properties of these systems. It is the author's hope that theses chapters impart some sense of the remarkable and rapid progress in complex systems research that has led to this unprecedented academic synergy. Chapters 3 and 5 detail the author's original work in the context of complex systems research. Chapter 3 presents the methods and results of a two-stage modeling process that generates candidate gene-regulatory networks of the bacterium B.subtilis from experimentally obtained, yet mathematically underdetermined microchip array data. These networks are then analyzed from a graph theoretical perspective, and their biological viability is critiqued by comparing the networks' graph theoretical properties to those of other biological systems. The results of topological perturbation analyses revealing commonalities in behavior at multiple levels of complexity are also presented, and are shown to be an invaluable means by which to ascertain the level of complexity to which the network inference process is robust to noise. Chapter 5 outlines a learning algorithm for the development of a realistic, evolving social network (a city) into which a disease is introduced. The results of simulations in populations spanning two orders of magnitude are compared to prevaccine era measles data for England and Wales and demonstrate that the simulations are able to capture the quantitative and qualitative features of epidemics in populations as small as 10,000 people. The work presented in Chapter 5 validates the utility of network simulation in concurrently probing contact network dynamics and disease dynamics.

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.

Technetium-99m and rhenium-188 complexes with one and two pendant bisphosphonate groups for imaging arterial calcification.

PubMed

Bordoloi, Jayanta Kumar; Berry, David; Khan, Irfan Ullah; Sunassee, Kavitha; de Rosales, Rafael Torres Martin; Shanahan, Catherine; Blower, Philip J

2015-03-21

The first (99m)Tc and (188)Re complexes containing two pendant bisphosphonate groups have been synthesised, based on the mononuclear M(v) nitride core with two dithiocarbamate ligands each with a pendant bisphosphonate. The structural identity of the (99)Tc and stable rhenium analogues as uncharged, mononuclear nitridobis(dithiocarbamate) complexes was determined by electrospray mass spectrometry. The (99m)Tc complex showed greater affinity for synthetic and biological hydroxyapatite, and greater stability in biological media, than the well-known but poorly-characterised and inhomogeneous bone imaging agent (99m)Tc-MDP. It gave excellent SPECT images of both bone calcification (mice and rats) and vascular calcification (rat model), but the improved stability and the availability of two pendant bisphosphonate groups conferred no dramatic advantage in imaging over the conventional (99m)Tc-MDP agent in which the bisphosphonate group is bound directly to Tc. The (188)Re complex also showed preferential uptake in bone. These tracers and the biological model of vascular calcification offer the opportunity to study the biological interpretation and clinical potential of radionuclide imaging of vascular calcification and to deliver radionuclide therapy to bone metastases.

Global identifiability of linear compartmental models--a computer algebra algorithm.

PubMed

Audoly, S; D'Angiò, L; Saccomani, M P; Cobelli, C

1998-01-01

A priori global identifiability deals with the uniqueness of the solution for the unknown parameters of a model and is, thus, a prerequisite for parameter estimation of biological dynamic models. Global identifiability is however difficult to test, since it requires solving a system of algebraic nonlinear equations which increases both in nonlinearity degree and number of terms and unknowns with increasing model order. In this paper, a computer algebra tool, GLOBI (GLOBal Identifiability) is presented, which combines the topological transfer function method with the Buchberger algorithm, to test global identifiability of linear compartmental models. GLOBI allows for the automatic testing of a priori global identifiability of general structure compartmental models from general multi input-multi output experiments. Examples of usage of GLOBI to analyze a priori global identifiability of some complex biological compartmental models are provided.

Quantitative computational models of molecular self-assembly in systems biology

PubMed Central

Thomas, Marcus; Schwartz, Russell

2017-01-01

Molecular self-assembly is the dominant form of chemical reaction in living systems, yet efforts at systems biology modeling are only beginning to appreciate the need for and challenges to accurate quantitative modeling of self-assembly. Self-assembly reactions are essential to nearly every important process in cell and molecular biology and handling them is thus a necessary step in building comprehensive models of complex cellular systems. They present exceptional challenges, however, to standard methods for simulating complex systems. While the general systems biology world is just beginning to deal with these challenges, there is an extensive literature dealing with them for more specialized self-assembly modeling. This review will examine the challenges of self-assembly modeling, nascent efforts to deal with these challenges in the systems modeling community, and some of the solutions offered in prior work on self-assembly specifically. The review concludes with some consideration of the likely role of self-assembly in the future of complex biological system models more generally. PMID:28535149

Quantitative computational models of molecular self-assembly in systems biology.

PubMed

Thomas, Marcus; Schwartz, Russell

2017-05-23

Molecular self-assembly is the dominant form of chemical reaction in living systems, yet efforts at systems biology modeling are only beginning to appreciate the need for and challenges to accurate quantitative modeling of self-assembly. Self-assembly reactions are essential to nearly every important process in cell and molecular biology and handling them is thus a necessary step in building comprehensive models of complex cellular systems. They present exceptional challenges, however, to standard methods for simulating complex systems. While the general systems biology world is just beginning to deal with these challenges, there is an extensive literature dealing with them for more specialized self-assembly modeling. This review will examine the challenges of self-assembly modeling, nascent efforts to deal with these challenges in the systems modeling community, and some of the solutions offered in prior work on self-assembly specifically. The review concludes with some consideration of the likely role of self-assembly in the future of complex biological system models more generally.

A probabilistic framework for identifying biosignatures using Pathway Complexity

NASA Astrophysics Data System (ADS)

Marshall, Stuart M.; Murray, Alastair R. G.; Cronin, Leroy

2017-11-01

One thing that discriminates living things from inanimate matter is their ability to generate similarly complex or non-random structures in a large abundance. From DNA sequences to folded protein structures, living cells, microbial communities and multicellular structures, the material configurations in biology can easily be distinguished from non-living material assemblies. Many complex artefacts, from ordinary bioproducts to human tools, though they are not living things, are ultimately produced by biological processes-whether those processes occur at the scale of cells or societies, they are the consequences of living systems. While these objects are not living, they cannot randomly form, as they are the product of a biological organism and hence are either technological or cultural biosignatures. A generalized approach that aims to evaluate complex objects as possible biosignatures could be useful to explore the cosmos for new life forms. However, it is not obvious how it might be possible to create such a self-contained approach. This would require us to prove rigorously that a given artefact is too complex to have formed by chance. In this paper, we present a new type of complexity measure, which we call `Pathway Complexity', that allows us not only to threshold the abiotic-biotic divide, but also to demonstrate a probabilistic approach based on object abundance and complexity which can be used to unambiguously assign complex objects as biosignatures. We hope that this approach will not only open up the search for biosignatures beyond the Earth, but also allow us to explore the Earth for new types of biology, and to determine when a complex chemical system discovered in the laboratory could be considered alive. This article is part of the themed issue 'Reconceptualizing the origins of life'.

Bioengineering strategies to generate artificial protein complexes.

PubMed

Kim, Heejae; Siu, Ka-Hei; Raeeszadeh-Sarmazdeh, Maryam; Sun, Qing; Chen, Qi; Chen, Wilfred

2015-08-01

For many applications, increasing synergy between distinct proteins through organization is important for the specificity, regulation, and overall reaction efficiency. Although there are many examples of protein complexes in nature, a generalized method to create these complexes remains elusive. Many conventional techniques such as random chemical conjugation, physical adsorption onto surfaces, and encapsulation within matrices are imprecise approaches and can lead to deactivation of protein native functionalities. More "bio-friendly" approaches such as genetically fused proteins and biological scaffolds often can result in low yields and low complex stability. Alternatively, site-specific protein conjugation or ligation can generate artificial protein complexes that preserve the native functionalities of protein domains and maintain stability through covalent bonds. In this review, we describe three distinct methods to synthesize artificial protein complexes (genetic incorPoration of unnatural amino acids to introduce bio-orthogonal azide and alkyne groups to proteins, split-intein based expressed protein ligation, and sortase mediated ligation) and highlight interesting applications for each technique. © 2015 Wiley Periodicals, Inc.

Synthetic biology approaches in cancer immunotherapy, genetic network engineering, and genome editing.

PubMed

Chakravarti, Deboki; Cho, Jang Hwan; Weinberg, Benjamin H; Wong, Nicole M; Wong, Wilson W

2016-04-18

Investigations into cells and their contents have provided evolving insight into the emergence of complex biological behaviors. Capitalizing on this knowledge, synthetic biology seeks to manipulate the cellular machinery towards novel purposes, extending discoveries from basic science to new applications. While these developments have demonstrated the potential of building with biological parts, the complexity of cells can pose numerous challenges. In this review, we will highlight the broad and vital role that the synthetic biology approach has played in applying fundamental biological discoveries in receptors, genetic circuits, and genome-editing systems towards translation in the fields of immunotherapy, biosensors, disease models and gene therapy. These examples are evidence of the strength of synthetic approaches, while also illustrating considerations that must be addressed when developing systems around living cells.

The Chemical and Biological Effects of cis-Dichlorodiammineplatinum (II), an Antitumor Agent, on DNA

PubMed Central

Munchausen, Linda L.

1974-01-01

cis-Dichlorodiammineplatinum (II) binds irreversibly to the bases in DNA; the amount of platinum complex bound can be determined from changes in the ultraviolet absorption spectrum. As the ratio of platinum to phosphate is increased, an increasing inactivation of bacterial transforming DNA is observed. At a ratio that corresponds to spectrometric saturation, transforming activity is inactivated >105-fold. The trans isomer of the platinum complex, which is not effective against tumors, induces a similar inactivation of transforming DNA but with half the efficiency, indicating a different mode of binding. The sensitivity to inactivation by cis isomer varies slightly with the genetic marker assayed but is not dependent on the excision repair system. Uptake of DNA by competent cells is unaffected by bound platinum complex; however, integration of platinum-bound transforming DNA into the host genome decreases as the mole fraction of platinum increases. This loss of integration parallels the decreased transforming activity of the DNA. Although the drug induces interstrand crosslinks in DNA in vitro, these crosslinks are relatively rare events and cannot account for the observed inactivation. PMID:4548188

Integrative, Dynamic Structural Biology at Atomic Resolution—It’s About Time

PubMed Central

van den Bedem, Henry; Fraser, James S.

2015-01-01

Biomolecules adopt a dynamic ensemble of conformations, each with the potential to interact with binding partners or perform the chemical reactions required for a multitude of cellular functions. Recent advances in X-ray crystallography, Nuclear Magnetic Resonance (NMR) spectroscopy, and other techniques are helping us realize the dream of seeing—in atomic detail—how different parts of biomolecules exchange between functional sub-states using concerted motions. Integrative structural biology has advanced our understanding of the formation of large macromolecular complexes and how their components interact in assemblies by leveraging data from many low-resolution methods. Here, we review the growing opportunities for integrative, dynamic structural biology at the atomic scale, contending there is increasing synergistic potential between X-ray crystallography, NMR, and computer simulations to reveal a structural basis for protein conformational dynamics at high resolution. PMID:25825836

A Review of Biologic Therapies Targeting IL-23 and IL-17 for Use in Moderate-to-Severe Plaque Psoriasis.

PubMed

Campa, Molly; Mansouri, Bobbak; Warren, Richard; Menter, Alan

2016-03-01

The development of several highly effective biologic drugs in the past decade has revolutionized the treatment of moderate-to-severe plaque psoriasis. With increased understanding of the immunopathogenesis of psoriasis, the emphasis has turned toward more specific targets for psoriasis drugs. Although the complex immunological pathway of psoriasis is not yet completely understood, current models emphasize the significant importance of interleukin (IL)-23 and IL-17. Several biologic drugs targeting these cytokines are now in various stages of drug development. Drugs targeting IL-23 include BI-655066, briakinumab, guselkumab, tildrakizumab, and ustekinumab. Drugs targeting IL-17 include brodalumab, ixekizumab, and secukinumab. While many of these have shown safety and good efficacy in clinical trials of moderate-to-severe plaque psoriasis, long-term safety is still to be established.

[Cooperations between biology laboratories of the establishments of healthcare].

PubMed

Burnat, Pascal; Payen, Catherine; Mérens, Audrey; Ceppa, Franck; Renard, Christophe

2013-01-01

In France, the cooperations between biological laboratories of the healthcare establishments increased after those realized in the private laboratories. The biologists are confronted with various hypotheses of organization. They are often complex because they may preserve the quality of the care and their continuity while realizing financial economies. These economies are mostly based on the global reduction in the staff and in the equipments by mutualising the biological tests with varying degrees. We describe the various elements to be taken into account (staff, activities, budget, quality, transport, materials) and propose many scenarios of cooperations, from a unique central shape to the transfer of very specialized tests, with their advantages and their inconveniences. The management of human aspects in these cooperations is determining to facilitate their success as well as a reliable preliminary inventory of fixtures.

BIOSPIDA: A Relational Database Translator for NCBI

PubMed Central

Hagen, Matthew S.; Lee, Eva K.

2010-01-01

As the volume and availability of biological databases continue widespread growth, it has become increasingly difficult for research scientists to identify all relevant information for biological entities of interest. Details of nucleotide sequences, gene expression, molecular interactions, and three-dimensional structures are maintained across many different databases. To retrieve all necessary information requires an integrated system that can query multiple databases with minimized overhead. This paper introduces a universal parser and relational schema translator that can be utilized for all NCBI databases in Abstract Syntax Notation (ASN.1). The data models for OMIM, Entrez-Gene, Pubmed, MMDB and GenBank have been successfully converted into relational databases and all are easily linkable helping to answer complex biological questions. These tools facilitate research scientists to locally integrate databases from NCBI without significant workload or development time. PMID:21347013

Effect of ubiquinone Q(10) and antioxidant vitamins on free radical oxidation of phospholipids in biological membranes of rat liver.

PubMed

Tikhaze, A K; Konovalova, G G; Lankin, V Z; Kaminnyi, A I; Kaminnaja, V I; Ruuge, E K; Kukharchuk, V V

2005-08-01

We studied the effects of 30-day peroral treatment with beta-carotene, a complex of antioxidant vitamins (vitamins C and E and provitamin A) and selenium, and solubilized ubiquinone Q(10) on the antioxidant potential in rat liver (ascorbate-dependent free radical oxidation of unsaturated membrane phospholipids). beta-Carotene irrespective of the administration route increased antioxidant potential of the liver by 2-3.5 times. The complex of antioxidant vitamins and selenium increased this parameter by more than 15 times. Antiradical activity in rat liver was extremely high after administration of solubilized ubiquinone Q(10) (increase by more than by 36 times). It can be expected that reduced ubiquinone Q(10) in vivo should produce a more pronounced protective effect due to activity of the system for bioregeneration of this natural antioxidant.

Stochastic Simulation Service: Bridging the Gap between the Computational Expert and the Biologist

PubMed Central

Banerjee, Debjani; Bellesia, Giovanni; Daigle, Bernie J.; Douglas, Geoffrey; Gu, Mengyuan; Gupta, Anand; Hellander, Stefan; Horuk, Chris; Nath, Dibyendu; Takkar, Aviral; Lötstedt, Per; Petzold, Linda R.

2016-01-01

We present StochSS: Stochastic Simulation as a Service, an integrated development environment for modeling and simulation of both deterministic and discrete stochastic biochemical systems in up to three dimensions. An easy to use graphical user interface enables researchers to quickly develop and simulate a biological model on a desktop or laptop, which can then be expanded to incorporate increasing levels of complexity. StochSS features state-of-the-art simulation engines. As the demand for computational power increases, StochSS can seamlessly scale computing resources in the cloud. In addition, StochSS can be deployed as a multi-user software environment where collaborators share computational resources and exchange models via a public model repository. We demonstrate the capabilities and ease of use of StochSS with an example of model development and simulation at increasing levels of complexity. PMID:27930676

Stochastic Simulation Service: Bridging the Gap between the Computational Expert and the Biologist

DOE PAGES

Drawert, Brian; Hellander, Andreas; Bales, Ben; ...

2016-12-08

We present StochSS: Stochastic Simulation as a Service, an integrated development environment for modeling and simulation of both deterministic and discrete stochastic biochemical systems in up to three dimensions. An easy to use graphical user interface enables researchers to quickly develop and simulate a biological model on a desktop or laptop, which can then be expanded to incorporate increasing levels of complexity. StochSS features state-of-the-art simulation engines. As the demand for computational power increases, StochSS can seamlessly scale computing resources in the cloud. In addition, StochSS can be deployed as a multi-user software environment where collaborators share computational resources andmore » exchange models via a public model repository. We also demonstrate the capabilities and ease of use of StochSS with an example of model development and simulation at increasing levels of complexity.« less

Revisiting Paine’s 1966 sea star removal experiment, the most-cited empirical article in the American Naturalist

USGS Publications Warehouse

Lafferty, Kevin D.; Suchanek, Tom

2016-01-01

“Food Web Complexity and Species Diversity” (Paine 1966) is the most-cited empirical article published in the American Naturalist. In short, Paine removed predatory sea stars (Pisaster ochraceus) from the rocky intertidal and watched the key prey species, mussels (Mytilus californianus), crowd out seven subordinate primary space-holding species. However, because these mussels are a foundational species, they provide three-dimensional habitat for over 300 associated species inhabiting the mussel beds; thus, removing sea stars significantly increases community-wide diversity. In any case, most ecologists cite Paine (1966) to support a statement that predators increase diversity by interfering with competition. Although detractors remained skeptical of top-down effects and keystone concepts, the paradigm that predation increases diversity spread. By 1991, “Food Web Complexity and Species Diversity” was considered a classic ecological paper, and after 50 years it continues to influence ecological theory and conservation biology.

Metals and lipid oxidation. Contemporary issues.

PubMed

Schaich, K M

1992-03-01

Lipid oxidation is now recognized to be a critically important reaction in physiological and toxicological processes as well as in food products. This provides compelling reasons to understand what causes lipid oxidation in order to be able to prevent or control the reactions. Redox-active metals are major factors catalyzing lipid oxidation in biological systems. Classical mechanisms of direct electron transfer to double bonds by higher valence metals and of reduction of hydroperoxides by lower valence metals do not always account for patterns of metal catalysis of lipid oxidation in multiphasic or compartmentalized biological systems. To explain why oxidation kinetics, mechanisms, and products in molecular environments which are both chemically and physically complex often do not follow classical patterns predicted by model system studies, increased consideration must be given to five contemporary issues regarding metal catalysis of lipid oxidation: hypervalent non-heme iron or iron-oxygen complexes, heme catalysis mechanism(s), compartmentalization of reactions and lipid phase reactions of metals, effects of metals on product mixes, and factors affecting the mode of metal catalytic action.

Minireview: Epigenetics of Obesity and Diabetes in Humans

PubMed Central

Slomko, Howard; Heo, Hye J.

2012-01-01

Understanding the determinants of human health and disease is overwhelmingly complex, particularly for common, late-onset, chronic disorders, such as obesity and diabetes. Elucidating the genetic and environmental factors that influence susceptibility to disruptions in energy homeostasis and metabolic regulation remain a challenge, and progress will entail the integration of multiple assessments of temporally dynamic environmental exposures in the context of each individual's genotype. To meet this challenge, researchers are increasingly exploring the epigenome, which is the malleable interface of gene-environment interactions. Epigenetic variation, whether innate or induced, contributes to variation in gene expression, the range of potential individual responses to internal and external cues, and risk for metabolic disease. Ultimately, advancement in our understanding of chronic disease susceptibility in humans will depend on refinement of exposure assessment tools and systems biology approaches to interpretation. In this review, we present recent progress in epigenetics of human obesity and diabetes, existing challenges, and the potential for new approaches to unravel the complex biology of metabolic dysregulation. PMID:22253427

Emergent explosive synchronization in adaptive complex networks

NASA Astrophysics Data System (ADS)

Avalos-Gaytán, Vanesa; Almendral, Juan A.; Leyva, I.; Battiston, F.; Nicosia, V.; Latora, V.; Boccaletti, S.

2018-04-01

Adaptation plays a fundamental role in shaping the structure of a complex network and improving its functional fitting. Even when increasing the level of synchronization in a biological system is considered as the main driving force for adaptation, there is evidence of negative effects induced by excessive synchronization. This indicates that coherence alone cannot be enough to explain all the structural features observed in many real-world networks. In this work, we propose an adaptive network model where the dynamical evolution of the node states toward synchronization is coupled with an evolution of the link weights based on an anti-Hebbian adaptive rule, which accounts for the presence of inhibitory effects in the system. We found that the emergent networks spontaneously develop the structural conditions to sustain explosive synchronization. Our results can enlighten the shaping mechanisms at the heart of the structural and dynamical organization of some relevant biological systems, namely, brain networks, for which the emergence of explosive synchronization has been observed.

Virtual immunology: software for teaching basic immunology.

PubMed

Berçot, Filipe Faria; Fidalgo-Neto, Antônio Augusto; Lopes, Renato Matos; Faggioni, Thais; Alves, Luiz Anastácio

2013-01-01

As immunology continues to evolve, many educational methods have found difficulty in conveying the degree of complexity inherent in its basic principles. Today, the teaching-learning process in such areas has been improved with tools such as educational software. This article introduces "Virtual Immunology," a software program available free of charge in Portuguese and English, which can be used by teachers and students in physiology, immunology, and cellular biology classes. We discuss the development of the initial two modules: "Organs and Lymphoid Tissues" and "Inflammation" and the use of interactive activities to provide microscopic and macroscopic understanding in immunology. Students, both graduate and undergraduate, were questioned along with university level professors about the quality of the software and intuitiveness of use, facility of navigation, and aesthetic organization using a Likert scale. An overwhelmingly satisfactory result was obtained with both students and immunology teachers. Programs such as "Virtual Immunology" are offering more interactive, multimedia approaches to complex scientific principles that increase student motivation, interest, and comprehension. © 2013 by The International Union of Biochemistry and Molecular Biology.

Emergent explosive synchronization in adaptive complex networks.

PubMed

Avalos-Gaytán, Vanesa; Almendral, Juan A; Leyva, I; Battiston, F; Nicosia, V; Latora, V; Boccaletti, S

2018-04-01

Adaptation plays a fundamental role in shaping the structure of a complex network and improving its functional fitting. Even when increasing the level of synchronization in a biological system is considered as the main driving force for adaptation, there is evidence of negative effects induced by excessive synchronization. This indicates that coherence alone cannot be enough to explain all the structural features observed in many real-world networks. In this work, we propose an adaptive network model where the dynamical evolution of the node states toward synchronization is coupled with an evolution of the link weights based on an anti-Hebbian adaptive rule, which accounts for the presence of inhibitory effects in the system. We found that the emergent networks spontaneously develop the structural conditions to sustain explosive synchronization. Our results can enlighten the shaping mechanisms at the heart of the structural and dynamical organization of some relevant biological systems, namely, brain networks, for which the emergence of explosive synchronization has been observed.

Clustering Single-Cell Expression Data Using Random Forest Graphs.

PubMed

Pouyan, Maziyar Baran; Nourani, Mehrdad

2017-07-01

Complex tissues such as brain and bone marrow are made up of multiple cell types. As the study of biological tissue structure progresses, the role of cell-type-specific research becomes increasingly important. Novel sequencing technology such as single-cell cytometry provides researchers access to valuable biological data. Applying machine-learning techniques to these high-throughput datasets provides deep insights into the cellular landscape of the tissue where those cells are a part of. In this paper, we propose the use of random-forest-based single-cell profiling, a new machine-learning-based technique, to profile different cell types of intricate tissues using single-cell cytometry data. Our technique utilizes random forests to capture cell marker dependences and model the cellular populations using the cell network concept. This cellular network helps us discover what cell types are in the tissue. Our experimental results on public-domain datasets indicate promising performance and accuracy of our technique in extracting cell populations of complex tissues.

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

Minireview: Epigenetics of obesity and diabetes in humans.

PubMed

Slomko, Howard; Heo, Hye J; Einstein, Francine H

2012-03-01

Understanding the determinants of human health and disease is overwhelmingly complex, particularly for common, late-onset, chronic disorders, such as obesity and diabetes. Elucidating the genetic and environmental factors that influence susceptibility to disruptions in energy homeostasis and metabolic regulation remain a challenge, and progress will entail the integration of multiple assessments of temporally dynamic environmental exposures in the context of each individual's genotype. To meet this challenge, researchers are increasingly exploring the epigenome, which is the malleable interface of gene-environment interactions. Epigenetic variation, whether innate or induced, contributes to variation in gene expression, the range of potential individual responses to internal and external cues, and risk for metabolic disease. Ultimately, advancement in our understanding of chronic disease susceptibility in humans will depend on refinement of exposure assessment tools and systems biology approaches to interpretation. In this review, we present recent progress in epigenetics of human obesity and diabetes, existing challenges, and the potential for new approaches to unravel the complex biology of metabolic dysregulation.

Concept Maps for Improved Science Reasoning and Writing: Complexity Isn't Everything.

PubMed

Dowd, Jason E; Duncan, Tanya; Reynolds, Julie A

2015-01-01

A pervasive notion in the literature is that complex concept maps reflect greater knowledge and/or more expert-like thinking than less complex concept maps. We show that concept maps used to structure scientific writing and clarify scientific reasoning do not adhere to this notion. In an undergraduate course for thesis writers, students use concept maps instead of traditional outlines to define the boundaries and scope of their research and to construct an argument for the significance of their research. Students generate maps at the beginning of the semester, revise after peer review, and revise once more at the end of the semester. Although some students revised their maps to make them more complex, a significant proportion of students simplified their maps. We found no correlation between increased complexity and improved scientific reasoning and writing skills, suggesting that sometimes students simplify their understanding as they develop more expert-like thinking. These results suggest that concept maps, when used as an intervention, can meet the varying needs of a diverse population of student writers. © 2015 J. E. Dowd 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).

Complex mixtures, complex responses: Assessing pharmaceutical mixtures using field and laboratory approaches

USGS Publications Warehouse

Schoenfuss, Heiko L.; Furlong, Edward T.; Phillips, Patrick J.; Scott, Tia-Marie; Kolpin, Dana W.; Cetkovic-Cvrlje, Marina; Lesteberg, Kelsey E.; Rearick, Daniel C.

2016-01-01

Pharmaceuticals are present in low concentrations (<100 ng/L) in most municipal wastewater effluents but may be elevated locally because of factors such as input from pharmaceutical formulation facilities. Using existing concentration data, the authors assessed pharmaceuticals in laboratory exposures of fathead minnows (Pimephales promelas) and added environmental complexity through effluent exposures. In the laboratory, larval and mature minnows were exposed to a simple opioid mixture (hydrocodone, methadone, and oxycodone), an opioid agonist (tramadol), a muscle relaxant (methocarbamol), a simple antidepressant mixture (fluoxetine, paroxetine, venlafaxine), a sleep aid (temazepam), or a complex mixture of all compounds. Larval minnow response to effluent exposure was not consistent. The 2010 exposures resulted in shorter exposed minnow larvae, whereas the larvae exposed in 2012 exhibited altered escape behavior. Mature minnows exhibited altered hepatosomatic indices, with the strongest effects in females and in mixture exposures. In addition, laboratory-exposed, mature male minnows exposed to all pharmaceuticals (except the selective serotonin reuptake inhibitor mixture) defended nest sites less rigorously than fish in the control group. Tramadol or antidepressant mixture exposure resulted in increased splenic T lymphocytes. Only male minnows exposed to whole effluent responded with increased plasma vitellogenin concentrations. Female minnows exposed to pharmaceuticals (except the opioid mixture) had larger livers, likely as a compensatory result of greater prominence of vacuoles in liver hepatocytes. The observed alteration of apical endpoints central to sustaining fish populations confirms that effluents containing waste streams from pharmaceutical formulation facilities can adversely impact fish populations but that the effects may not be temporally consistent. The present study highlights the importance of including diverse biological endpoints spanning levels of biological organization and life stages when assessing contaminant interactions.

Analysis of Prebiotic Oligosaccharides

NASA Astrophysics Data System (ADS)

Sanz, M. L.; Ruiz-Matute, A. I.; Corzo, N.; Martínez-Castro, I.

Carbohydrates and more specifically prebiotics, are complex mixtures of isomers with different degrees of polymerization (DP), monosaccharide units and/or glycosidic linkages. Many efforts are focused on the search for new products and the determination of their biological activity. However, the study of their chemical structure is fundamental to both acquire a basic knowledge of the carbohydrate and to increase the understanding of the mechanisms for their metabolic effect.

Collaborative modelling: the future of computational neuroscience?

PubMed

Davison, Andrew P

2012-01-01

Given the complexity of biological neural circuits and of their component cells and synapses, building and simulating robust, well-validated, detailed models increasingly surpasses the resources of an individual researcher or small research group. In this article, I will briefly review possible solutions to this problem, argue for open, collaborative modelling as the optimal solution for advancing neuroscience knowledge, and identify potential bottlenecks and possible solutions.

Tumors Induce Complex DNA Damage in Distant Proliferative Tissues in Vivo | Center for Cancer Research

Cancer.gov

In radiation biology, a bystander effect occurs when cells not directly exposed to ionizing radiation show increased genomic instability and impaired viability due to the release of signaling molecules by the irradiated cells in their vicinity. Christophe Redon, Ph.D., and colleagues in CCR’s Laboratory of Molecular Pharmacology, decided to ask whether a tumor itself could

Informing biological design by integration of systems and synthetic biology.

PubMed

Smolke, Christina D; Silver, Pamela A

2011-03-18

Synthetic biology aims to make the engineering of biology faster and more predictable. In contrast, systems biology focuses on the interaction of myriad components and how these give rise to the dynamic and complex behavior of biological systems. Here, we examine the synergies between these two fields. Copyright © 2011 Elsevier Inc. All rights reserved.

The trajectory of life. Decreasing physiological network complexity through changing fractal patterns

PubMed Central

Sturmberg, Joachim P.; Bennett, Jeanette M.; Picard, Martin; Seely, Andrew J. E.

2015-01-01

In this position paper, we submit a synthesis of theoretical models based on physiology, non-equilibrium thermodynamics, and non-linear time-series analysis. Based on an understanding of the human organism as a system of interconnected complex adaptive systems, we seek to examine the relationship between health, complexity, variability, and entropy production, as it might be useful to help understand aging, and improve care for patients. We observe the trajectory of life is characterized by the growth, plateauing and subsequent loss of adaptive function of organ systems, associated with loss of functioning and coordination of systems. Understanding development and aging requires the examination of interdependence among these organ systems. Increasing evidence suggests network interconnectedness and complexity can be captured/measured/associated with the degree and complexity of healthy biologic rhythm variability (e.g., heart and respiratory rate variability). We review physiological mechanisms linking the omics, arousal/stress systems, immune function, and mitochondrial bioenergetics; highlighting their interdependence in normal physiological function and aging. We argue that aging, known to be characterized by a loss of variability, is manifested at multiple scales, within functional units at the small scale, and reflected by diagnostic features at the larger scale. While still controversial and under investigation, it appears conceivable that the integrity of whole body complexity may be, at least partially, reflected in the degree and variability of intrinsic biologic rhythms, which we believe are related to overall system complexity that may be a defining feature of health and it's loss through aging. Harnessing this information for the development of therapeutic and preventative strategies may hold an opportunity to significantly improve the health of our patients across the trajectory of life. PMID:26082722

Mammalian Synthetic Biology: Engineering Biological Systems.

PubMed

Black, Joshua B; Perez-Pinera, Pablo; Gersbach, Charles A

2017-06-21

The programming of new functions into mammalian cells has tremendous application in research and medicine. Continued improvements in the capacity to sequence and synthesize DNA have rapidly increased our understanding of mechanisms of gene function and regulation on a genome-wide scale and have expanded the set of genetic components available for programming cell biology. The invention of new research tools, including targetable DNA-binding systems such as CRISPR/Cas9 and sensor-actuator devices that can recognize and respond to diverse chemical, mechanical, and optical inputs, has enabled precise control of complex cellular behaviors at unprecedented spatial and temporal resolution. These tools have been critical for the expansion of synthetic biology techniques from prokaryotic and lower eukaryotic hosts to mammalian systems. Recent progress in the development of genome and epigenome editing tools and in the engineering of designer cells with programmable genetic circuits is expanding approaches to prevent, diagnose, and treat disease and to establish personalized theranostic strategies for next-generation medicines. This review summarizes the development of these enabling technologies and their application to transforming mammalian synthetic biology into a distinct field in research and medicine.

High fat, high sucrose diet causes cardiac mitochondrial dysfunction due in part to oxidative post-translational modification of mitochondrial complex II.

PubMed

Sverdlov, Aaron L; Elezaby, Aly; Behring, Jessica B; Bachschmid, Markus M; Luptak, Ivan; Tu, Vivian H; Siwik, Deborah A; Miller, Edward J; Liesa, Marc; Shirihai, Orian S; Pimentel, David R; Cohen, Richard A; Colucci, Wilson S

2015-01-01

Diet-induced obesity leads to metabolic heart disease (MHD) characterized by increased oxidative stress that may cause oxidative post-translational modifications (OPTM) of cardiac mitochondrial proteins. The functional consequences of OPTM of cardiac mitochondrial proteins in MHD are unknown. Our objective was to determine whether cardiac mitochondrial dysfunction in MHD due to diet-induced obesity is associated with cysteine OPTM. Male C57BL/6J mice were fed either a high-fat, high-sucrose (HFHS) or control diet for 8months. Cardiac mitochondria from HFHS-fed mice (vs. control diet) had an increased rate of H2O2 production, a decreased GSH/GSSG ratio, a decreased rate of complex II substrate-driven ATP synthesis and decreased complex II activity. Complex II substrate-driven ATP synthesis and complex II activity were partially restored ex-vivo by reducing conditions. A biotin switch assay showed that HFHS feeding increased cysteine OPTM in complex II subunits A (SDHA) and B (SDHB). Using iodo-TMT multiplex tags we found that HFHS feeding is associated with reversible oxidation of cysteines 89 and 231 in SDHA, and 100, 103 and 115 in SDHB. MHD due to consumption of a HFHS "Western" diet causes increased H2O2 production and oxidative stress in cardiac mitochondria associated with decreased ATP synthesis and decreased complex II activity. Impaired complex II activity and ATP production are associated with reversible cysteine OPTM of complex II. Possible sites of reversible cysteine OPTM in SDHA and SDHB were identified by iodo-TMT tag labeling. Mitochondrial ROS may contribute to the pathophysiology of MHD by impairing the function of complex II. This article is part of a Special Issue entitled "Mitochondria: From Basic Mitochondrial Biology to Cardiovascular Disease". Copyright © 2014 Elsevier Ltd. All rights reserved.

Corrections to chance fluctuations: quantum mind in biological evolution?

PubMed

Damiani, Giuseppe

2009-01-01

According to neo-Darwinian theory, biological evolution is produced by natural selection of random hereditary variations. This assumption stems from the idea of a mechanical and deterministic world based on the laws of classic physics. However, the increased knowledge of relationships between metabolism, epigenetic systems, and editing of nucleic acids suggests the existence of self-organized processes of adaptive evolution in response to environmental stresses. Living organisms are open thermodynamic systems which use entropic decay of external source of electromagnetic energy to increase their internal dynamic order and to generate new genetic and epigenetic information with a high degree of coherency and teleonomic creativity. Sensing, information processing, and decision making of biological systems might be mainly quantum phenomena. Amplification of microscopic quantum events using the long-range correlation of fractal structures, at the borderline between deterministic order and unpredictable chaos, may be used to direct a reproducible transition of the biological systems towards a defined macroscopic state. The discoveries of many natural genetic engineering systems, the ability to choose the most effective solutions, and the emergence of complex forms of consciousness at different levels confirm the importance of mind-action directed processes in biological evolution, as suggested by Alfred Russel Wallace. Although the main Darwinian principles will remain a crucial component of our understanding of evolution, a radical rethinking of the conceptual structure of the neo-Darwinian theory is needed.

Biophysical response of dryland soils to rainfall: implications for wind erosion

NASA Astrophysics Data System (ADS)

Bullard, J. E.; Strong, C. L.; Aubault, H.

2016-12-01

Dryland soils can be highly susceptible to wind erosion due to low vegetation cover. The formation of physical and biological soil crusts between vascular plants can exert some control on the soil surface erodibility. The development of these crusts is highly dependent on rainfall which causes sediment compaction and aggregate breakdown, and triggers photosynthetic activity and an increase soil organic matter within biological soil crusts. Using controlled field experiments, this study tests how biological soil crusts in different dryland geomorphic settings respond to various rainfall amounts (0, 5 or 10 mm) and how this in turn affects the resistance of soils to wind erosion. Results show that 10 mm of rainfall triggers more intense photosynthetic activity (high fluorescence) and a greater increase in extracellular polysaccharide content in biological crusts than 5 mm of rainfall but that the duration of photosynthetic activity is comparable for both quantities of rain. These biological responses have little impact on surface resistance, but results show that soils are more susceptible to wind erosion after rainfall events than in their initial dry state. This unexpected result could be explained by the detachment of surface sediments by raindrop impact and overland flow. The study highlights the complexity of soil erodibility at small scale which is driven by rain, wind and crust, and a necessity to understand how the spatial heterogeneity of crust and their ecophysiology alters small scale processes.

[An increase in efficiency of adaptations and a weakening of organism protective reactions in the process of biological evolution].

PubMed

Ivanov, K P

2014-01-01

The main direction of evolution of living organisms is development of the central nervous system and sense organ, an increase of energy exchange development of homoiothermia, development of the more and more complex forms of behavior, an increase in energy expenditure in connection with an increase of the organism activity, and development of adaptation to the habitat. Such fundamental processes were subjected and have been subjected to numerous studies and discussions. However, in different animals there exist different species peculiarities of evolution of physiological functions, from which finally formed are fundamental evolutionary processes. We studied some of these specific processes by dividing them into two categories. The first category is "Increase of efficiency of adaptation" in development of biological evolution. By this term we mean development of amazing by perfection specific physiological mechanisms of adaptive character. The second category is "Weakening of protective organism reactions". By this we understand disturbance of protective mechanisms of the organism immune system, discoordination of movement of leukocytes along microvessels, the absence of efficient collateral circulation in brain and in heart, etc.

The New Toxicology of Sophisticated Materials: Nanotoxicology and Beyond

PubMed Central

Maynard, Andrew D.; Warheit, David B.; Philbert, Martin A.

2011-01-01

It has long been recognized that the physical form of materials can mediate their toxicity—the health impacts of asbestiform materials, industrial aerosols, and ambient particulate matter are prime examples. Yet over the past 20 years, toxicology research has suggested complex and previously unrecognized associations between material physicochemistry at the nanoscale and biological interactions. With the rapid rise of the field of nanotechnology and the design and production of increasingly complex nanoscale materials, it has become ever more important to understand how the physical form and chemical composition of these materials interact synergistically to determine toxicity. As a result, a new field of research has emerged—nanotoxicology. Research within this field is highlighting the importance of material physicochemical properties in how dose is understood, how materials are characterized in a manner that enables quantitative data interpretation and comparison, and how materials move within, interact with, and are transformed by biological systems. Yet many of the substances that are the focus of current nanotoxicology studies are relatively simple materials that are at the vanguard of a new era of complex materials. Over the next 50 years, there will be a need to understand the toxicology of increasingly sophisticated materials that exhibit novel, dynamic and multifaceted functionality. If the toxicology community is to meet the challenge of ensuring the safe use of this new generation of substances, it will need to move beyond “nano” toxicology and toward a new toxicology of sophisticated materials. Here, we present a brief overview of the current state of the science on the toxicology of nanoscale materials and focus on three emerging toxicology-based challenges presented by sophisticated materials that will become increasingly important over the next 50 years: identifying relevant materials for study, physicochemical characterization, and biointeractions. PMID:21177774

Studies on Some Biologically Cobalt(II), Copper(II) and Zinc(II) Complexes With ONO, NNO and SNO Donor Pyrazinoylhydrazine-Derived Ligands

PubMed Central

Praveen, Marapaka; Sherazi, Syed K. A.

1998-01-01

Biologically active complexes of Co(II), Ni(II), Cu(II) and Zn(II) with novel ONO, NNO and SNO donor pyrazinoylhydrazine-derived compounds have been prepared and characterized on the basis of analytical data and various physicochemical studies. Distorted octahedral structures for all the complexes have been proposed. The synthesized ligands and their complexes have been screened for their antibacterial activity against bacterial species Escherichia coli, Pseudomonas aeruginosa, Staphylococcus aureus and Klebsiella pneumonae. The activity data show the metal complexes to be more active than the parent free ligands against one or more bacterial species. PMID:18475857

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

PubMed

Richards, D; Berry, S; Howard, M

2012-01-01

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

Hyaluronan Hybrid Cooperative Complexes as a Novel Frontier for Cellular Bioprocesses Re-Activation

PubMed Central

Stellavato, Antonietta; Corsuto, Luisana; D’Agostino, Antonella; La Gatta, Annalisa; Diana, Paola; Bernini, Patrizia; De Rosa, Mario

2016-01-01

Hyaluronic Acid (HA)-based dermal formulations have rapidly gained a large consensus in aesthetic medicine and dermatology. HA, highly expressed in the Extracellular Matrix (ECM), acts as an activator of biological cascades, stimulating cell migration and proliferation, and operating as a regulator of the skin immune surveillance, through specific interactions with its receptors. HA may be used in topical formulations, as dermal inducer, for wound healing. Moreover, intradermal HA formulations (injectable HA) provide an attractive tool to counteract skin aging (e.g., facial wrinkles, dryness, and loss of elasticity) and restore normal dermal functions, through simple and minimally invasive procedures. Biological activity of a commercially available hyaluronic acid, Profhilo®, based on NAHYCO™ technology, was compared to H-HA or L-HA alone. The formation of hybrid cooperative complexes was confirmed by the sudden drop in η0 values in the rheological measurements. Besides, hybrid cooperative complexes proved stable to hyaluronidase (BTH) digestion. Using in vitro assays, based on keratinocytes, fibroblasts cells and on the Phenion® Full Thickness Skin Model 3D, hybrid cooperative complexes were compared to H-HA, widely used in biorevitalization procedures, and to L-HA, recently proposed as the most active fraction modulating the inflammatory response. Quantitative real-time PCR analyses were accomplished for the transcript quantification of collagens and elastin. Finally immunofluorescence staining permitted to evaluate the complete biosynthesis of all the molecules investigated. An increase in the expression levels of type I and type III collagen in fibroblasts and type IV and VII collagen in keratinocytes were found with the hybrid cooperative complexes, compared to untreated cells (CTR) and to the H-HA and L-HA treatments. The increase in elastin expression found in both cellular model and in the Phenion® Full Thickness Skin Model 3D also at longer time (up to 7 days), supports the clinically observed improvement of skin elasticity. The biomarkers analyzed suggest an increase of tissue remodeling in the presence of Profhilo®, probably due to the long lasting release and the concurrent action of the two HA components. PMID:27723763

Characterizing Strain Variation in Engineered E. coli Using a Multi-Omics-Based Workflow

DOE PAGES

Brunk, Elizabeth; George, Kevin W.; Alonso-Gutierrez, Jorge; ...

2016-05-19

Understanding the complex interactions that occur between heterologous and native biochemical pathways represents a major challenge in metabolic engineering and synthetic biology. We present a workflow that integrates metabolomics, proteomics, and genome-scale models of Escherichia coli metabolism to study the effects of introducing a heterologous pathway into a microbial host. This workflow incorporates complementary approaches from computational systems biology, metabolic engineering, and synthetic biology; provides molecular insight into how the host organism microenvironment changes due to pathway engineering; and demonstrates how biological mechanisms underlying strain variation can be exploited as an engineering strategy to increase product yield. As a proofmore » of concept, we present the analysis of eight engineered strains producing three biofuels: isopentenol, limonene, and bisabolene. Application of this workflow identified the roles of candidate genes, pathways, and biochemical reactions in observed experimental phenomena and facilitated the construction of a mutant strain with improved productivity. The contributed workflow is available as an open-source tool in the form of iPython notebooks.« less

How to build a course in mathematical-biological modeling: content and processes for knowledge and skill.

PubMed

Hoskinson, Anne-Marie

2010-01-01

Biological problems in the twenty-first century are complex and require mathematical insight, often resulting in mathematical models of biological systems. Building mathematical-biological models requires cooperation among biologists and mathematicians, and mastery of building models. A new course in mathematical modeling presented the opportunity to build both content and process learning of mathematical models, the modeling process, and the cooperative process. There was little guidance from the literature on how to build such a course. Here, I describe the iterative process of developing such a course, beginning with objectives and choosing content and process competencies to fulfill the objectives. I include some inductive heuristics for instructors seeking guidance in planning and developing their own courses, and I illustrate with a description of one instructional model cycle. Students completing this class reported gains in learning of modeling content, the modeling process, and cooperative skills. Student content and process mastery increased, as assessed on several objective-driven metrics in many types of assessments.

Landauer in the Age of Synthetic Biology: Energy Consumption and Information Processing in Biochemical Networks

NASA Astrophysics Data System (ADS)

Mehta, Pankaj; Lang, Alex H.; Schwab, David J.

2016-03-01

A central goal of synthetic biology is to design sophisticated synthetic cellular circuits that can perform complex computations and information processing tasks in response to specific inputs. The tremendous advances in our ability to understand and manipulate cellular information processing networks raises several fundamental physics questions: How do the molecular components of cellular circuits exploit energy consumption to improve information processing? Can one utilize ideas from thermodynamics to improve the design of synthetic cellular circuits and modules? Here, we summarize recent theoretical work addressing these questions. Energy consumption in cellular circuits serves five basic purposes: (1) increasing specificity, (2) manipulating dynamics, (3) reducing variability, (4) amplifying signal, and (5) erasing memory. We demonstrate these ideas using several simple examples and discuss the implications of these theoretical ideas for the emerging field of synthetic biology. We conclude by discussing how it may be possible to overcome these limitations using "post-translational" synthetic biology that exploits reversible protein modification.

How to Build a Course in Mathematical–Biological Modeling: Content and Processes for Knowledge and Skill

PubMed Central

2010-01-01

Biological problems in the twenty-first century are complex and require mathematical insight, often resulting in mathematical models of biological systems. Building mathematical–biological models requires cooperation among biologists and mathematicians, and mastery of building models. A new course in mathematical modeling presented the opportunity to build both content and process learning of mathematical models, the modeling process, and the cooperative process. There was little guidance from the literature on how to build such a course. Here, I describe the iterative process of developing such a course, beginning with objectives and choosing content and process competencies to fulfill the objectives. I include some inductive heuristics for instructors seeking guidance in planning and developing their own courses, and I illustrate with a description of one instructional model cycle. Students completing this class reported gains in learning of modeling content, the modeling process, and cooperative skills. Student content and process mastery increased, as assessed on several objective-driven metrics in many types of assessments. PMID:20810966

Joining Forces: Integrating Proteomics and Cross-linking with the Mass Spectrometry of Intact Complexes*

PubMed Central

Stengel, Florian; Aebersold, Ruedi; Robinson, Carol V.

2012-01-01

Protein assemblies are critical for cellular function and understanding their physical organization is the key aim of structural biology. However, applying conventional structural biology approaches is challenging for transient, dynamic, or polydisperse assemblies. There is therefore a growing demand for hybrid technologies that are able to complement classical structural biology methods and thereby broaden our arsenal for the study of these important complexes. Exciting new developments in the field of mass spectrometry and proteomics have added a new dimension to the study of protein-protein interactions and protein complex architecture. In this review, we focus on how complementary mass spectrometry-based techniques can greatly facilitate structural understanding of protein assemblies. PMID:22180098

Quantum chemical investigation of levofloxacin-boron complexes: A computational approach

NASA Astrophysics Data System (ADS)

Sayin, Koray; Karakaş, Duran

2018-04-01

Quantum chemical calculations are performed over some boron complexes with levofloxacin. Boron complex with fluorine atoms are optimized at three different methods (HF, B3LYP and M062X) with 6-31 + G(d) basis set. The best level is determined as M062X/6-31 + G(d) by comparison of experimental and calculated results of complex (1). The other complexes are optimized by using the best level. Structural properties, IR and NMR spectrum are examined in detail. Biological activities of mentioned complexes are investigated by some quantum chemical descriptors and molecular docking analyses. As a result, biological activities of complex (2) and (4) are close to each other and higher than those of other complexes. Additionally, NLO properties of mentioned complexes are investigated by some quantum chemical parameters. It is found that complex (3) is the best candidate for NLO applications.

Measuring the Evolution of Ontology Complexity: The Gene Ontology Case Study

PubMed Central

Dameron, Olivier; Bettembourg, Charles; Le Meur, Nolwenn

2013-01-01

Ontologies support automatic sharing, combination and analysis of life sciences data. They undergo regular curation and enrichment. We studied the impact of an ontology evolution on its structural complexity. As a case study we used the sixty monthly releases between January 2008 and December 2012 of the Gene Ontology and its three independent branches, i.e. biological processes (BP), cellular components (CC) and molecular functions (MF). For each case, we measured complexity by computing metrics related to the size, the nodes connectivity and the hierarchical structure. The number of classes and relations increased monotonously for each branch, with different growth rates. BP and CC had similar connectivity, superior to that of MF. Connectivity increased monotonously for BP, decreased for CC and remained stable for MF, with a marked increase for the three branches in November and December 2012. Hierarchy-related measures showed that CC and MF had similar proportions of leaves, average depths and average heights. BP had a lower proportion of leaves, and a higher average depth and average height. For BP and MF, the late 2012 increase of connectivity resulted in an increase of the average depth and average height and a decrease of the proportion of leaves, indicating that a major enrichment effort of the intermediate-level hierarchy occurred. The variation of the number of classes and relations in an ontology does not provide enough information about the evolution of its complexity. However, connectivity and hierarchy-related metrics revealed different patterns of values as well as of evolution for the three branches of the Gene Ontology. CC was similar to BP in terms of connectivity, and similar to MF in terms of hierarchy. Overall, BP complexity increased, CC was refined with the addition of leaves providing a finer level of annotations but decreasing slightly its complexity, and MF complexity remained stable. PMID:24146805

Local and landscape drivers of predation services in urban gardens.

PubMed

Philpott, Stacy M; Bichier, Peter

2017-04-01

In agroecosystems, local and landscape features, as well as natural enemy abundance and richness, are significant predictors of predation services that may result in biological control of pests. Despite the increasing importance of urban gardening for provisioning of food to urban populations, most urban gardeners suffer from high pest problems, and have little knowledge about how to manage their plots to increase biological control services. We examined the influence of local, garden scale (i.e., herbaceous and arboreal vegetation abundance and diversity, ground cover) and landscape (i.e., landscape diversity and surrounding land use types) characteristics on predation services provided by naturally occurring predators in 19 urban gardens in the California central coast. We introduced sentinel pests (moth eggs and larvae and pea aphids) onto greenhouse-raised plants taken to gardens and assigned to open or bagged (predator exclosure) treatments. We found high predation rates with between 40% and 90% of prey items removed in open treatments. Predation services varied with local and landscape factors, but significant predictors differed by prey species. Predation of eggs and aphids increased with vegetation complexity in gardens, but larvae predation declined with vegetation complexity. Smaller gardens experienced higher predation services, likely due to increases in predator abundance in smaller gardens. Several ground cover features influenced predation services. In contrast to patterns in rural agricultural landscapes, predation on aphids declined with increases in landscape diversity. In sum, we report the relationships between several local management factors, as well as landscape surroundings, and implications for garden management. © 2017 by the Ecological Society of America.

Update of KDBI: Kinetic Data of Bio-molecular Interaction database

PubMed Central

Kumar, Pankaj; Han, B. C.; Shi, Z.; Jia, J.; Wang, Y. P.; Zhang, Y. T.; Liang, L.; Liu, Q. F.; Ji, Z. L.; Chen, Y. Z.

2009-01-01

Knowledge of the kinetics of biomolecular interactions is important for facilitating the study of cellular processes and underlying molecular events, and is essential for quantitative study and simulation of biological systems. Kinetic Data of Bio-molecular Interaction database (KDBI) has been developed to provide information about experimentally determined kinetic data of protein–protein, protein–nucleic acid, protein–ligand, nucleic acid–ligand binding or reaction events described in the literature. To accommodate increasing demand for studying and simulating biological systems, numerous improvements and updates have been made to KDBI, including new ways to access data by pathway and molecule names, data file in System Biology Markup Language format, more efficient search engine, access to published parameter sets of simulation models of 63 pathways, and 2.3-fold increase of data (19 263 entries of 10 532 distinctive biomolecular binding and 11 954 interaction events, involving 2635 proteins/protein complexes, 847 nucleic acids, 1603 small molecules and 45 multi-step processes). KDBI is publically available at http://bidd.nus.edu.sg/group/kdbi/kdbi.asp. PMID:18971255

Applications of artificial neural networks in medical science.

PubMed

Patel, Jigneshkumar L; Goyal, Ramesh K

2007-09-01

Computer technology has been advanced tremendously and the interest has been increased for the potential use of 'Artificial Intelligence (AI)' in medicine and biological research. One of the most interesting and extensively studied branches of AI is the 'Artificial Neural Networks (ANNs)'. Basically, ANNs are the mathematical algorithms, generated by computers. ANNs learn from standard data and capture the knowledge contained in the data. Trained ANNs approach the functionality of small biological neural cluster in a very fundamental manner. They are the digitized model of biological brain and can detect complex nonlinear relationships between dependent as well as independent variables in a data where human brain may fail to detect. Nowadays, ANNs are widely used for medical applications in various disciplines of medicine especially in cardiology. ANNs have been extensively applied in diagnosis, electronic signal analysis, medical image analysis and radiology. ANNs have been used by many authors for modeling in medicine and clinical research. Applications of ANNs are increasing in pharmacoepidemiology and medical data mining. In this paper, authors have summarized various applications of ANNs in medical science.

Sweetening ruthenium and osmium: organometallic arene complexes containing aspartame.

PubMed

Gray, Jennifer C; Habtemariam, Abraha; Winnig, Marcel; Meyerhof, Wolfgang; Sadler, Peter J

2008-09-01

The novel organometallic sandwich complexes [(eta(6)-p-cymene)Ru(eta(6)-aspartame)](OTf)(2) (1) (OTf = trifluoromethanesulfonate) and [(eta(6)-p-cymene)Os(eta(6)-aspartame)](OTf)(2) (2) incorporating the artificial sweetener aspartame have been synthesised and characterised. A number of properties of aspartame were found to be altered on binding to either metal. The pK(a) values of both the carboxyl and the amino groups of aspartame are lowered by between 0.35 and 0.57 pH units, causing partial deprotonation of the amino group at pH 7.4 (physiological pH). The rate of degradation of aspartame to 3,6-dioxo-5-phenylmethylpiperazine acetic acid (diketopiperazine) increased over threefold from 0.12 to 0.36 h(-1) for 1, and to 0.43 h(-1) for 2. Furthermore, the reduction potential of the ligand shifted from -1.133 to -0.619 V for 2. For the ruthenium complex 1 the process occurred in two steps, the first (at -0.38 V) within a biologically accessible range. This facilitates reactions with biological reductants such as ascorbate. Binding to and activation of the sweet taste receptor was not observed for these metal complexes up to concentrations of 1 mM. The factors which affect the ability of metal-bound aspartame to interact with the receptor site are discussed.

Overcoming heterologous protein interdependency to optimize P450-mediated Taxol precursor synthesis in Escherichia coli

PubMed Central

Biggs, Bradley Walters; Lim, Chin Giaw; Sagliani, Kristen; Shankar, Smriti; Stephanopoulos, Gregory; Ajikumar, Parayil Kumaran

2016-01-01

Recent advances in metabolic engineering have demonstrated the potential to exploit biological chemistry for the synthesis of complex molecules. Much of the progress to date has leveraged increasingly precise genetic tools to control the transcription and translation of enzymes for superior biosynthetic pathway performance. However, applying these approaches and principles to the synthesis of more complex natural products will require a new set of tools for enabling various classes of metabolic chemistries (i.e., cyclization, oxygenation, glycosylation, and halogenation) in vivo. Of these diverse chemistries, oxygenation is one of the most challenging and pivotal for the synthesis of complex natural products. Here, using Taxol as a model system, we use nature’s favored oxygenase, the cytochrome P450, to perform high-level oxygenation chemistry in Escherichia coli. An unexpected coupling of P450 expression and the expression of upstream pathway enzymes was discovered and identified as a key obstacle for functional oxidative chemistry. By optimizing P450 expression, reductase partner interactions, and N-terminal modifications, we achieved the highest reported titer of oxygenated taxanes (∼570 ± 45 mg/L) in E. coli. Altogether, this study establishes E. coli as a tractable host for P450 chemistry, highlights the potential magnitude of protein interdependency in the context of synthetic biology and metabolic engineering, and points to a promising future for the microbial synthesis of complex chemical entities. PMID:26951651

Overcoming heterologous protein interdependency to optimize P450-mediated Taxol precursor synthesis in Escherichia coli.

PubMed

Biggs, Bradley Walters; Lim, Chin Giaw; Sagliani, Kristen; Shankar, Smriti; Stephanopoulos, Gregory; De Mey, Marjan; Ajikumar, Parayil Kumaran

2016-03-22

Recent advances in metabolic engineering have demonstrated the potential to exploit biological chemistry for the synthesis of complex molecules. Much of the progress to date has leveraged increasingly precise genetic tools to control the transcription and translation of enzymes for superior biosynthetic pathway performance. However, applying these approaches and principles to the synthesis of more complex natural products will require a new set of tools for enabling various classes of metabolic chemistries (i.e., cyclization, oxygenation, glycosylation, and halogenation) in vivo. Of these diverse chemistries, oxygenation is one of the most challenging and pivotal for the synthesis of complex natural products. Here, using Taxol as a model system, we use nature's favored oxygenase, the cytochrome P450, to perform high-level oxygenation chemistry in Escherichia coli. An unexpected coupling of P450 expression and the expression of upstream pathway enzymes was discovered and identified as a key obstacle for functional oxidative chemistry. By optimizing P450 expression, reductase partner interactions, and N-terminal modifications, we achieved the highest reported titer of oxygenated taxanes (∼570 ± 45 mg/L) in E. coli. Altogether, this study establishes E. coli as a tractable host for P450 chemistry, highlights the potential magnitude of protein interdependency in the context of synthetic biology and metabolic engineering, and points to a promising future for the microbial synthesis of complex chemical entities.

Characterization of the influence of external stimulus on protein-nucleic acid complex through multiscale computations

NASA Astrophysics Data System (ADS)

Gosai, Agnivo

The concomitant detection, monitoring and analysis of biomolecules have assumed utmost importance in the field of medical diagnostics as well as in different spheres of biotechnology research such as drug development, environmental hazard detection and biodefense. There is an increased demand for the modulation of the biological response for such detection / sensing schemes which will be facilitated by the sensitive and controllable transmission of external stimuli. Electrostatic actuation for the controlled release/capture of biomolecules through conformational transformations of bioreceptors provides an efficient and feasible mechanism to modulate biological response. In addition, electrostatic actuation mechanism has the advantage of allowing massively parallel schemes and measurement capabilities that could ultimately be essential for biomedical applications. Experiments have previously demonstrated the unbinding of thrombin from its aptamer in presence of small positive electrode potential whereas the complex remained associated in presence of small negative potentials / zero potential. However, the nanoscale physics/chemistry involved in this process is not clearly understood. In this thesis a combination of continuum mechanics based modeling and a variety of atomistic simulation techniques have been utilized to corroborate the aforementioned experimental observations. It is found that the computational approach can satisfactorily predict the dynamics of the electrically excited aptamer-thrombin complex as well as provide an analytical model to characterize the forced binding of the complex.

Characterizing local biological hotspots in the Gulf of Maine using remote sensing data

NASA Astrophysics Data System (ADS)

Ribera, Marta M.

Researchers increasingly advocate the use of ecosystem-based management (EBM) for managing complex marine ecosystems. This approach requires managers to focus on processes and cross-scale interactions, rather than individual components. However, they often lack appropriate tools and data sources to pursue this change in management approach. One method that has been proposed to understand the ecological complexity inherent in marine ecosystems is the study of biological hotspots. Biological hotspots are locations where organisms from different trophic levels aggregate to feed on abundant supplies, and they are considered a first step toward understanding the processes driving spatial and temporal heterogeneity in marine systems. Biological hotspots are supported by phytoplankton aggregations, which are characterized by high spatial and temporal variability. As a result, methods developed to locate biological hotspots in relatively stable terrestrial systems are not well suited for more dynamic marine ecosystems. The main objective of this thesis is thus to identify and characterize local-scale biological hotspots in the western side of the Gulf of Maine. The first chapter describes a new methodological framework with the steps needed to locate these types of hotspots in marine ecosystems using remote sensing datasets. Then, in the second chapter these hotspots are characterized using a novel metric that uses time series information and spatial statistics to account for both the temporal variability and spatial structure of these marine aggregations. This metric redefines biological hotspots as areas with a high probability of exhibiting positive anomalies of productivity compared to the expected regional seasonal pattern. Finally, the third chapter compares the resulting biological hotspots to fishery-dependent abundance indices of surface and benthic predators to determine the effect of the location and magnitude of phytoplankton aggregations on the rest of the ecosystem. Analyses indicate that the spatial scale and magnitude of biological hotspots in the Gulf of Maine depend on the location and time of the year. Results also show that these hotspots change over time in response to both short-term oceanographic processes and long-term climatic cycles. Finally, the new metric presented here facilitates the spatial comparison between different trophic levels, thus allowing interdisciplinary ecosystem-wide studies.

Complex networks for data-driven medicine: the case of Class III dentoskeletal disharmony

NASA Astrophysics Data System (ADS)

Scala, A.; Auconi, P.; Scazzocchio, M.; Caldarelli, G.; McNamara, JA; Franchi, L.

2014-11-01

In the last decade, the availability of innovative algorithms derived from complexity theory has inspired the development of highly detailed models in various fields, including physics, biology, ecology, economy, and medicine. Due to the availability of novel and ever more sophisticated diagnostic procedures, all biomedical disciplines face the problem of using the increasing amount of information concerning each patient to improve diagnosis and prevention. In particular, in the discipline of orthodontics the current diagnostic approach based on clinical and radiographic data is problematic due to the complexity of craniofacial features and to the numerous interacting co-dependent skeletal and dentoalveolar components. In this study, we demonstrate the capability of computational methods such as network analysis and module detection to extract organizing principles in 70 patients with excessive mandibular skeletal protrusion with underbite, a condition known in orthodontics as Class III malocclusion. Our results could possibly constitute a template framework for organising the increasing amount of medical data available for patients’ diagnosis.

Narrative persuasion, causality, complex integration, and support for obesity policy.

PubMed

Niederdeppe, Jeff; Shapiro, Michael A; Kim, Hye Kyung; Bartolo, Danielle; Porticella, Norman

2014-01-01

Narrative messages have the potential to convey causal attribution information about complex social issues. This study examined attributions about obesity, an issue characterized by interrelated biological, behavioral, and environmental causes. Participants were randomly assigned to read one of three narratives emphasizing societal causes and solutions for obesity or an unrelated story that served as the control condition. The three narratives varied in the extent to which the character in the story acknowledged personal responsibility (high, moderate, and none) for controlling her weight. Stories that featured no acknowledgment and moderate acknowledgment of personal responsibility, while emphasizing environmental causes and solutions, were successful at increasing societal cause attributions about obesity and, among conservatives, increasing support for obesity-related policies relative to the control group. The extent to which respondents were able to make connections between individual and environmental causes of obesity (complex integration) mediated the relationship between the moderate acknowledgment condition and societal cause attributions. We conclude with a discussion of the implications of this work for narrative persuasion theory and health communication campaigns.

I-DIRT, a general method for distinguishing between specific and nonspecific protein interactions.

PubMed

Tackett, Alan J; DeGrasse, Jeffrey A; Sekedat, Matthew D; Oeffinger, Marlene; Rout, Michael P; Chait, Brian T

2005-01-01

Isolation of protein complexes via affinity-tagged proteins provides a powerful tool for studying biological systems, but the technique is often compromised by co-enrichment of nonspecifically interacting proteins. We describe a new technique (I-DIRT) that distinguishes contaminants from bona fide interactors in immunopurifications, overcoming this most challenging problem in defining protein complexes. I-DIRT will be of broad value for studying protein complexes in biological systems that can be metabolically labeled.

Systems Biology Graphical Notation: Entity Relationship language Level 1 Version 2.

PubMed

Sorokin, Anatoly; Le Novère, Nicolas; Luna, Augustin; Czauderna, Tobias; Demir, Emek; Haw, Robin; Mi, Huaiyu; Moodie, Stuart; Schreiber, Falk; Villéger, Alice

2015-09-04

The Systems Biological Graphical Notation (SBGN) is an international community effort for standardized graphical representations of biological pathways and networks. The goal of SBGN is to provide unambiguous pathway and network maps for readers with different scientific backgrounds as well as to support efficient and accurate exchange of biological knowledge between different research communities, industry, and other players in systems biology. Three SBGN languages, Process Description (PD), Entity Relationship (ER) and Activity Flow (AF), allow for the representation of different aspects of biological and biochemical systems at different levels of detail. The SBGN Entity Relationship language (ER) represents biological entities and their interactions and relationships within a network. SBGN ER focuses on all potential relationships between entities without considering temporal aspects. The nodes (elements) describe biological entities, such as proteins and complexes. The edges (connections) provide descriptions of interactions and relationships (or influences), e.g., complex formation, stimulation and inhibition. Among all three languages of SBGN, ER is the closest to protein interaction networks in biological literature and textbooks, but its well-defined semantics offer a superior precision in expressing biological knowledge.

Systems biology approaches and tools for analysis of interactomes and multi-target drugs.

PubMed

Schrattenholz, André; Groebe, Karlfried; Soskic, Vukic

2010-01-01

Systems biology is essentially a proteomic and epigenetic exercise because the relatively condensed information of genomes unfolds on the level of proteins. The flexibility of cellular architectures is not only mediated by a dazzling number of proteinaceous species but moreover by the kinetics of their molecular changes: The time scales of posttranslational modifications range from milliseconds to years. The genetic framework of an organism only provides the blue print of protein embodiments which are constantly shaped by external input. Indeed, posttranslational modifications of proteins represent the scope and velocity of these inputs and fulfil the requirements of integration of external spatiotemporal signal transduction inside an organism. The optimization of biochemical networks for this type of information processing and storage results in chemically extremely fine tuned molecular entities. The huge dynamic range of concentrations, the chemical diversity and the necessity of synchronisation of complex protein expression patterns pose the major challenge of systemic analysis of biological models. One further message is that many of the key reactions in living systems are essentially based on interactions of moderate affinities and moderate selectivities. This principle is responsible for the enormous flexibility and redundancy of cellular circuitries. In complex disorders such as cancer or neurodegenerative diseases, which initially appear to be rooted in relatively subtle dysfunctions of multimodal physiologic pathways, drug discovery programs based on the concept of high affinity/high specificity compounds ("one-target, one-disease"), which has been dominating the pharmaceutical industry for a long time, increasingly turn out to be unsuccessful. Despite improvements in rational drug design and high throughput screening methods, the number of novel, single-target drugs fell much behind expectations during the past decade, and the treatment of "complex diseases" remains a most pressing medical need. Currently, a change of paradigm can be observed with regard to a new interest in agents that modulate multiple targets simultaneously, essentially "dirty drugs." Targeting cellular function as a system rather than on the level of the single target, significantly increases the size of the drugable proteome and is expected to introduce novel classes of multi-target drugs with fewer adverse effects and toxicity. Multiple target approaches have recently been used to design medications against atherosclerosis, cancer, depression, psychosis and neurodegenerative diseases. A focussed approach towards "systemic" drugs will certainly require the development of novel computational and mathematical concepts for appropriate modelling of complex data. But the key is the extraction of relevant molecular information from biological systems by implementing rigid statistical procedures to differential proteomic analytics.

Complex posttraumatic stress disorder: The need to consolidate a distinct clinical syndrome or to reevaluate features of psychiatric disorders following interpersonal trauma?

PubMed

Giourou, Evangelia; Skokou, Maria; Andrew, Stuart P; Alexopoulou, Konstantina; Gourzis, Philippos; Jelastopulu, Eleni

2018-03-22

Complex posttraumatic stress disorder (Complex PTSD) has been recently proposed as a distinct clinical entity in the WHO International Classification of Diseases, 11 th version, due to be published, two decades after its first initiation. It is described as an enhanced version of the current definition of PTSD, with clinical features of PTSD plus three additional clusters of symptoms namely emotional dysregulation, negative self-cognitions and interpersonal hardship, thus resembling the clinical features commonly encountered in borderline personality disorder (BPD). Complex PTSD is related to complex trauma which is defined by its threatening and entrapping context, generally interpersonal in nature. In this manuscript, we review the current findings related to traumatic events predisposing the above-mentioned disorders as well as the biological correlates surrounding them, along with their clinical features. Furthermore, we suggest that besides the present distinct clinical diagnoses (PTSD; Complex PTSD; BPD), there is a cluster of these comorbid disorders, that follow a continuum of trauma and biological severity on a spectrum of common or similar clinical features and should be treated as such. More studies are needed to confirm or reject this hypothesis, particularly in clinical terms and how they correlate to clinical entities' biological background, endorsing a shift from the phenomenologically only classification of psychiatric disorders towards a more biologically validated classification.

Quantitative Interpretation of Multifrequency Multimode EPR Spectra of Metal Containing Proteins, Enzymes, and Biomimetic Complexes.

PubMed

Petasis, Doros T; Hendrich, Michael P

2015-01-01

Electron paramagnetic resonance (EPR) spectroscopy has long been a primary method for characterization of paramagnetic centers in materials and biological complexes. Transition metals in biological complexes have valence d-orbitals that largely define the chemistry of the metal centers. EPR spectra are distinctive for metal type, oxidation state, protein environment, substrates, and inhibitors. The study of many metal centers in proteins, enzymes, and biomimetic complexes has led to the development of a systematic methodology for quantitative interpretation of EPR spectra from a wide array of metal containing complexes. The methodology is now contained in the computer program SpinCount. SpinCount allows simulation of EPR spectra from any sample containing multiple species composed of one or two metals in any spin state. The simulations are quantitative, thus allowing determination of all species concentrations in a sample directly from spectra. This chapter will focus on applications to transition metals in biological systems using EPR spectra from multiple microwave frequencies and modes. © 2015 Elsevier Inc. All rights reserved.

From Synthesis to Biological Impact of Pd (II) Complexes: Synthesis, Characterization, and Antimicrobial and Scavenging Activity

PubMed Central

Sharma, Nitin Kumar; Ameta, Rakesh Kumar; Singh, Man

2016-01-01

The Pd (II) complexes with a series of halosubstituted benzylamine ligands (BLs) have been synthesized and characterized with different spectroscopic technique such as FTIR, UV/Vis, LCMS, 1H, and 13C NMR. Their molecular sustainability in different solvents such as DMSO, DMSO : H2O, and DMSO : PBS at physiological condition (pH 7.2) was determined by UV/Vis spectrophotometer. The in vitro antibacterial and antifungal activities of the complexes were investigated against Gram-positive and Gram-negative microbes and two different fungi indicated their significant biological potential. Additionally, their antioxidant activity has been analyzed with DPPH• free radical through spectrophotometric method and the result inferred them as an antioxidant. The stronger antibacterial and antioxidant activities of the synthesized complexes suggested them as a stronger antimicrobial agent. Our study advances the biological importance of palladium (II) amine complexes in the field of antimicrobial and antioxidant activities. PMID:27119023

Practising Conservation Biology in a Virtual Rainforest World

ERIC Educational Resources Information Center

Schedlbauer, Jessica L.; Nadolny, Larysa; Woolfrey, Joan

2016-01-01

The interdisciplinary science of conservation biology provides undergraduate biology students with the opportunity to connect the biological sciences with disciplines including economics, social science and philosophy to address challenging conservation issues. Because of its complexity, students do not often have the opportunity to practise…

Measurement of complex permittivities of biological materials and human skin in vivo in the frequency band

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

Ghodgaonkar, D.K.

1987-01-01

A new method, namely, modified infinite sample method, has been developed which is particularly suitable for millimeter-wave dielectric measurements of biological materials. In this method, an impedance transformer is used which reduces the reflectivity of the biological sample. Because of the effect of introducing impendance transformer, the measured reflection coefficients are more sensitive to the complex permittivities of biological samples. For accurate measurement of reflection coefficients, two automated measurment systems were developed which cover the frequencies range of 26.5-60 GHz. An uncertainty analysis was performed to get an estimate of the errors in the measured complex permittivities. The dielectric propertiesmore » were measured for 10% saline solution, whole human blood, 200 mg/ml bovine serum albumin (BSA) solution and suspension of Saccharomyces cerevisiae cells. The Maxwell-Fricke equation, which is derived from dielectric mixture theory, was used for determination bound water in BSA solution. The results of all biological samples were interpreted by fitting Debye relaxation and Cole-Cole model. It is observed that the dielectric data for the biological materials can be explained on the basis of Debye relaxation of water molecule.« less

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

PubMed

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

2011-07-20

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

The genome editing toolbox: a spectrum of approaches for targeted modification.

PubMed

Cheng, Joseph K; Alper, Hal S

2014-12-01

The increase in quality, quantity, and complexity of recombinant products heavily drives the need to predictably engineer model and complex (mammalian) cell systems. However, until recently, limited tools offered the ability to precisely manipulate their genomes, thus impeding the full potential of rational cell line development processes. Targeted genome editing can combine the advances in synthetic and systems biology with current cellular hosts to further push productivity and expand the product repertoire. This review highlights recent advances in targeted genome editing techniques, discussing some of their capabilities and limitations and their potential to aid advances in pharmaceutical biotechnology. Copyright © 2014 Elsevier Ltd. All rights reserved.

Fishing anti(lymph)angiogenic drugs with zebrafish.

PubMed

García-Caballero, Melissa; Quesada, Ana R; Medina, Miguel A; Marí-Beffa, Manuel

2018-02-01

Zebrafish, an amenable small teleost fish with a complex mammal-like circulatory system, is being increasingly used for drug screening and toxicity studies. It combines the biological complexity of in vivo models with a higher-throughput screening capability compared with other available animal models. Externally growing, transparent embryos, displaying well-defined blood and lymphatic vessels, allow the inexpensive, rapid, and automatable evaluation of drug candidates that are able to inhibit neovascularisation. Here, we briefly review zebrafish as a model for the screening of anti(lymph)angiogenic drugs, with emphasis on the advantages and limitations of the different zebrafish-based in vivo assays. Copyright © 2017 Elsevier Ltd. All rights reserved.

NUCLEAR FACTOR-Y: still complex after all these years?

PubMed

Myers, Zachary A; Holt, Ben F

2018-06-11

The NUCLEAR FACTOR-Y (NF-Y) families of transcription factors are important regulators of plant development and physiology. Though NF-Y regulatory roles have recently been suggested for numerous aspects of plant biology, their roles in flowering time, early seedling development, stress responses, hormone signaling, and nodulation are the best characterized. The past few years have also seen significant advances in our understanding of the mechanistic function of the NF-Y, and as such, increasingly complex and interesting questions are now more approachable. This review will primarily focus on these developmental, physiological, and mechanistic roles of the NF-Y in recent research. Copyright © 2018 Elsevier Ltd. All rights reserved.

Arsenic distribution and valence state variation studied by fast hierarchical length-scale morphological, compositional, and speciation imaging at the Nanoscopium, Synchrotron Soleil

NASA Astrophysics Data System (ADS)

Somogyi, Andrea; Medjoubi, Kadda; Sancho-Tomas, Maria; Visscher, P. T.; Baranton, Gil; Philippot, Pascal

2017-09-01

The understanding of real complex geological, environmental and geo-biological processes depends increasingly on in-depth non-invasive study of chemical composition and morphology. In this paper we used scanning hard X-ray nanoprobe techniques in order to study the elemental composition, morphology and As speciation in complex highly heterogeneous geological samples. Multivariate statistical analytical techniques, such as principal component analysis and clustering were used for data interpretation. These measurements revealed the quantitative and valance state inhomogeneity of As and its relation to the total compositional and morphological variation of the sample at sub-μm scales.

Recent advances in the chemistry of Rh carbenoids: multicomponent reactions of diazocarbonyl compounds

NASA Astrophysics Data System (ADS)

Medvedev, J. J.; Nikolaev, V. A.

2015-07-01

Multicomponent reactions of diazo compounds catalyzed by RhII complexes become a powerful tool for organic synthesis. They enable three- or four-step processes to be carried out as one-pot procedures (actually as one step) with high stereoselectivity to give complex organic molecules, including biologically active compounds. This review addresses recent results in the chemistry of Rh-catalyzed multicomponent reactions of diazocarbonyl compounds with the intermediate formation of N-, O- and C=O-ylides. The diastereo- and enantioselectivity of these reactions and the possibility of using various co-catalysts to increase the efficiency of the processes under consideration are discussed. The bibliography includes 120 references.

Complexation of sesquiterpene lactones with cyclodextrins: synthesis and effects on their activities on parasitic weeds.

PubMed

Cala, Antonio; Molinillo, José M G; Fernández-Aparicio, Mónica; Ayuso, Jesús; Álvarez, José A; Rubiales, Diego; Macías, Francisco A

2017-08-09

Allelochemicals are safer, more selective and more active alternatives than synthetic agrochemicals for weed control. However, the low solubility of these compounds in aqueous media limits their use as agrochemicals. Herein, we propose the application of α-, β- and γ-cyclodextrins to improve the physicochemical properties and biological activities of three sesquiterpene lactones: dehydrocostuslactone, costunolide and (-)-α-santonin. Complexation was achieved by kneading and coprecipitation methods. Aqueous solubility was increased in the range 100-4600% and the solubility-phase diagrams suggested that complex formation had been successful. The results of the PM3 semiempirical calculations were consistent with the experimental results. The activities on etiolated wheat coleoptiles, Standard Target Species and parasitic weeds were improved. Cyclodextrins preserved or enhanced the activity of the three sesquiterpene lactones. Free cyclodextrins did not show significant activity and therefore the enhancement in activity was due to complexation. These results are promising for applications in agrochemical design.

COBRApy: COnstraints-Based Reconstruction and Analysis for Python.

PubMed

Ebrahim, Ali; Lerman, Joshua A; Palsson, Bernhard O; Hyduke, Daniel R

2013-08-08

COnstraint-Based Reconstruction and Analysis (COBRA) methods are widely used for genome-scale modeling of metabolic networks in both prokaryotes and eukaryotes. Due to the successes with metabolism, there is an increasing effort to apply COBRA methods to reconstruct and analyze integrated models of cellular processes. The COBRA Toolbox for MATLAB is a leading software package for genome-scale analysis of metabolism; however, it was not designed to elegantly capture the complexity inherent in integrated biological networks and lacks an integration framework for the multiomics data used in systems biology. The openCOBRA Project is a community effort to promote constraints-based research through the distribution of freely available software. Here, we describe COBRA for Python (COBRApy), a Python package that provides support for basic COBRA methods. COBRApy is designed in an object-oriented fashion that facilitates the representation of the complex biological processes of metabolism and gene expression. COBRApy does not require MATLAB to function; however, it includes an interface to the COBRA Toolbox for MATLAB to facilitate use of legacy codes. For improved performance, COBRApy includes parallel processing support for computationally intensive processes. COBRApy is an object-oriented framework designed to meet the computational challenges associated with the next generation of stoichiometric constraint-based models and high-density omics data sets. http://opencobra.sourceforge.net/

Physico-chemical and Biological Evaluation of Flavonols: Fisetin, Quercetin and Kaempferol Alone and Incorporated in beta Cyclodextrins.

PubMed

Corina, Danciu; Bojin, Florina; Ambrus, Rita; Muntean, Delia; Soica, Codruta; Paunescu, Virgil; Cristea, Mirabela; Pinzaru, Iulia; Dehelean, Cristina

2017-01-01

Fisetin,quercetin and kaempferol are among the important representatives of flavonols, biological active phytocomounds, with low water solubility. To evaluate the antimicrobial effect, respectively the antiproliferative and pro apoptotic activity on the B164A5 murine melanoma cell line of pure flavonols and their beta cyclodextrins complexes. Incorporation of fisetin, quercetin and kaempferol in beta cyclodextrins was proved by scanning electron microscopy (SEM), differencial scanning calorimetry (DSC) and X-ray powder diffraction (XRPD). Pure compounds and their complexes were tested for antiproliferative (MTT) and pro-apoptotic activity (Annexin V-PI) on the B164A5 murine melanoma cell line and for the antimicrobial properties (Disk Diffusion Method) on the selected strains. The phytocompounds presented in a different manner in vitro chemopreventive activity against B164A5 murine melanoma cell line and weak antimicrobial effect. The three flavonols: fisetin, quercetin and kaempferol were successfully incorporated in beta-cyclodextrin (BCD) and hydroxylpropyl-beta-cyclodextrin (HPBCD). Incorporation in beta cyclodextrins had a mix effect on the biological activity conducing to decrease, increase or consistent effect compared to pure phytocompound, depending on the screened process and on the chosen combination. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Scale relativity theory and integrative systems biology: 1. Founding principles and scale laws.

PubMed

Auffray, Charles; Nottale, Laurent

2008-05-01

In these two companion papers, we provide an overview and a brief history of the multiple roots, current developments and recent advances of integrative systems biology and identify multiscale integration as its grand challenge. Then we introduce the fundamental principles and the successive steps that have been followed in the construction of the scale relativity theory, and discuss how scale laws of increasing complexity can be used to model and understand the behaviour of complex biological systems. In scale relativity theory, the geometry of space is considered to be continuous but non-differentiable, therefore fractal (i.e., explicitly scale-dependent). One writes the equations of motion in such a space as geodesics equations, under the constraint of the principle of relativity of all scales in nature. To this purpose, covariant derivatives are constructed that implement the various effects of the non-differentiable and fractal geometry. In this first review paper, the scale laws that describe the new dependence on resolutions of physical quantities are obtained as solutions of differential equations acting in the scale space. This leads to several possible levels of description for these laws, from the simplest scale invariant laws to generalized laws with variable fractal dimensions. Initial applications of these laws to the study of species evolution, embryogenesis and cell confinement are discussed.

Development of hydrogels for regenerative engineering.

PubMed

Guan, Xiaofei; Avci-Adali, Meltem; Alarçin, Emine; Cheng, Hao; Kashaf, Sara Saheb; Li, Yuxiao; Chawla, Aditya; Jang, Hae Lin; Khademhosseini, Ali

2017-05-01

The aim of regenerative engineering is to restore complex tissues and biological systems through convergence in the fields of advanced biomaterials, stem cell science, and developmental biology. Hydrogels are one of the most attractive biomaterials for regenerative engineering, since they can be engineered into tissue mimetic 3D scaffolds to support cell growth due to their similarity to native extracellular matrix. Advanced nano- and micro-technologies have dramatically increased the ability to control properties and functionalities of hydrogel materials by facilitating biomimetic fabrication of more sophisticated compositions and architectures, thus extending our understanding of cell-matrix interactions at the nanoscale. With this perspective, this review discusses the most commonly used hydrogel materials and their fabrication strategies for regenerative engineering. We highlight the physical, chemical, and functional modulation of hydrogels to design and engineer biomimetic tissues based on recent achievements in nano- and micro-technologies. In addition, current hydrogel-based regenerative engineering strategies for treating multiple tissues, such as musculoskeletal, nervous and cardiac tissue, are also covered in this review. The interaction of multiple disciplines including materials science, cell biology, and chemistry, will further play an important role in the design of functional hydrogels for the regeneration of complex tissues. Copyright © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Indirect electroreduction as pretreatment to enhance biodegradability of metronidazole.

PubMed

Saidi, I; Soutrel, I; Floner, D; Fourcade, F; Bellakhal, N; Amrane, A; Geneste, F

2014-08-15

The removal of metronidazole, a biorecalcitrant antibiotic, by coupling an electrochemical reduction with a biological treatment was examined. Electroreduction was performed in a home-made flow cell at -1.2V/SCE on graphite felt. After only one pass through the cell, analysis of the electrolyzed solution showed a total degradation of metronidazole. The biodegradability estimated from the BOD5/COD ratio increased from 0.07 to 0.2, namely below the value usually considered as the limit of biodegradability (0.4). In order to improve these results, indirect electrolysis of metronidazole was performed with a titanium complex known to reduce selectively nitro compounds into amine. The catalytic activity of the titanium complex towards electroreduction of metronidazole was shown by cyclic voltammetry analyses. Indirect electrolysis led to an improvement of the biodegradability from 0.07 to 0.42. To confirm the interest of indirect electroreduction to improve the electrochemical pretreatment, biological treatment was then carried out on activated sludge after direct and indirect electrolyses; different parameters were followed during the culture such as pH, TOC and metronidazole concentration. Both electrochemical processes led to a more efficient biodegradation of metronidazole compared with the single biological treatment, leading to an overall mineralization yield for the coupling process of 85%. Copyright © 2014 Elsevier B.V. All rights reserved.

The physical and biological basis of quantitative parameters derived from diffusion MRI

PubMed Central

2012-01-01

Diffusion magnetic resonance imaging is a quantitative imaging technique that measures the underlying molecular diffusion of protons. Diffusion-weighted imaging (DWI) quantifies the apparent diffusion coefficient (ADC) which was first used to detect early ischemic stroke. However this does not take account of the directional dependence of diffusion seen in biological systems (anisotropy). Diffusion tensor imaging (DTI) provides a mathematical model of diffusion anisotropy and is widely used. Parameters, including fractional anisotropy (FA), mean diffusivity (MD), parallel and perpendicular diffusivity can be derived to provide sensitive, but non-specific, measures of altered tissue structure. They are typically assessed in clinical studies by voxel-based or region-of-interest based analyses. The increasing recognition of the limitations of the diffusion tensor model has led to more complex multi-compartment models such as CHARMED, AxCaliber or NODDI being developed to estimate microstructural parameters including axonal diameter, axonal density and fiber orientations. However these are not yet in routine clinical use due to lengthy acquisition times. In this review, I discuss how molecular diffusion may be measured using diffusion MRI, the biological and physical bases for the parameters derived from DWI and DTI, how these are used in clinical studies and the prospect of more complex tissue models providing helpful micro-structural information. PMID:23289085

Effect of Simvastatin, Coenzyme Q10, Resveratrol, Acetylcysteine and Acetylcarnitine on Mitochondrial Respiration.

PubMed

Fišar, Z; Hroudová, J; Singh, N; Kopřivová, A; Macečková, D

2016-01-01

Some therapeutic and/or adverse effects of drugs may be related to their effects on mitochondrial function. The effects of simvastatin, resveratrol, coenzyme Q10, acetylcysteine, and acetylcarnitine on Complex I-, Complex II-, or Complex IV-linked respiratory rate were determined in isolated brain mitochondria. The protective effects of these biologically active compounds on the calcium-induced decrease of the respiratory rate were also studied. We observed a significant inhibitory effect of simvastatin on mitochondrial respiration (IC50 = 24.0 μM for Complex I-linked respiration, IC50 = 31.3 μM for Complex II-linked respiration, and IC50 = 42.9 μM for Complex IV-linked respiration); the inhibitory effect of resveratrol was found at very high concentrations (IC50 = 162 μM for Complex I-linked respiration, IC50 = 564 μM for Complex II-linked respiration, and IC50 = 1454 μM for Complex IV-linked respiration). Concentrations required for effective simvastatin- or resveratrol-induced inhibition of mitochondrial respiration were found much higher than concentrations achieved under standard dosing of these drugs. Acetylcysteine and acetylcarnitine did not affect the oxygen consumption rate of mitochondria. Coenzyme Q10 induced an increase of Complex I-linked respiration. The increase of free calcium ions induced partial inhibition of the Complex I+II-linked mitochondrial respiration, and all tested drugs counteracted this inhibition. None of the tested drugs showed mitochondrial toxicity (characterized by respiratory rate inhibition) at drug concentrations achieved at therapeutic drug intake. Resveratrol, simvastatin, and acetylcarnitine had the greatest neuroprotective potential (characterized by protective effects against calcium-induced reduction of the respiratory rate).

Cellular changes in microgravity and the design of space radiation experiments

NASA Technical Reports Server (NTRS)

Morrison, D. R.

1994-01-01

Cell metabolism, secretion and cell-cell interactions can be altered during space flight. Early radiobiology experiments have demonstrated synergistic effects of radiation and microgravity as indicated by increased mutagenesis, increased chromosome aberrations, inhibited development, and retarded growth. Microgravity-induced changes in immune cell functions include reduced blastogenesis and cell-mediated, delayed-type hypersensitivity responses, increased cytokine secretions, but inhibited cytotoxic effects an macrophage differentiation. These effects are important because of the high radiosensitivity of immune cells. It is difficult to compare ground studies with space radiation biology experiments because of the complexity of the space radiation environment, types of radiation damage and repair mechanisms. Altered intracellular functions and molecular mechanisms must be considered in the design and interpretation of space radiation experiments. Critical steps in radiocarcinogenesis could be affected. New cell systems and hardware are needed to determine the biological effectiveness of the low dose rate, isotropic, multispectral space radiation and the potential usefulness of radioprotectants during space flight.

Convergent integration of animal model and human studies of bipolar disorder (manic-depressive illness).

PubMed

Le-Niculescu, Helen; Patel, Sagar D; Niculescu, Alexander B

2010-10-01

Animal models and human studies of bipolar disorder and other psychiatric disorders are becoming increasingly integrated, prompted by recent successes. Particularly for genomics, the convergence and integration of data across species, experimental modalities and technical platforms is providing a fit-to-disease way of extracting reproducible and biologically important signal, in sharp contrast to the fit-to-cohort effect, disappointing findings to date, and limited reproducibility of human genetic analyses alone. Such work in psychiatry can provide an example of how to address other genetically complex disorders, and in turn will benefit by incorporating concepts from other areas, such as cancer biology and diabetes. Copyright © 2010. Published by Elsevier Ltd.

Advances in downstream processing of biologics - Spectroscopy: An emerging process analytical technology.

PubMed

Rüdt, Matthias; Briskot, Till; Hubbuch, Jürgen

2017-03-24

Process analytical technologies (PAT) for the manufacturing of biologics have drawn increased interest in the last decade. Besides being encouraged by the Food and Drug Administration's (FDA's) PAT initiative, PAT promises to improve process understanding, reduce overall production costs and help to implement continuous manufacturing. This article focuses on spectroscopic tools for PAT in downstream processing (DSP). Recent advances and future perspectives will be reviewed. In order to exploit the full potential of gathered data, chemometric tools are widely used for the evaluation of complex spectroscopic information. Thus, an introduction into the field will be given. Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.

BIOINFORMATICS IN THE K-8 CLASSROOM: DESIGNING INNOVATIVE ACTIVITIES FOR TEACHER IMPLEMENTATION

PubMed Central

Shuster, Michele; Claussen, Kira; Locke, Melly; Glazewski, Krista

2016-01-01

At the intersection of biology and computer science is the growing field of bioinformatics—the analysis of complex datasets of biological relevance. Despite the increasing importance of bioinformatics and associated practical applications, these are not standard topics in elementary and middle school classrooms. We report on a pilot project and its evolution to support implementation of bioinformatics-based activities in elementary and middle school classrooms. Specifically, we ultimately designed a multi-day summer teacher professional development workshop, in which teachers design innovative classroom activities. By focusing on teachers, our design leverages enhanced teacher knowledge and confidence to integrate innovative instructional materials into K-8 classrooms and contributes to capacity building in STEM instruction. PMID:27429860

Automatic Compilation from High-Level Biologically-Oriented Programming Language to Genetic Regulatory Networks

PubMed Central

Beal, Jacob; Lu, Ting; Weiss, Ron

2011-01-01

Background The field of synthetic biology promises to revolutionize our ability to engineer biological systems, providing important benefits for a variety of applications. Recent advances in DNA synthesis and automated DNA assembly technologies suggest that it is now possible to construct synthetic systems of significant complexity. However, while a variety of novel genetic devices and small engineered gene networks have been successfully demonstrated, the regulatory complexity of synthetic systems that have been reported recently has somewhat plateaued due to a variety of factors, including the complexity of biology itself and the lag in our ability to design and optimize sophisticated biological circuitry. Methodology/Principal Findings To address the gap between DNA synthesis and circuit design capabilities, we present a platform that enables synthetic biologists to express desired behavior using a convenient high-level biologically-oriented programming language, Proto. The high level specification is compiled, using a regulatory motif based mechanism, to a gene network, optimized, and then converted to a computational simulation for numerical verification. Through several example programs we illustrate the automated process of biological system design with our platform, and show that our compiler optimizations can yield significant reductions in the number of genes () and latency of the optimized engineered gene networks. Conclusions/Significance Our platform provides a convenient and accessible tool for the automated design of sophisticated synthetic biological systems, bridging an important gap between DNA synthesis and circuit design capabilities. Our platform is user-friendly and features biologically relevant compiler optimizations, providing an important foundation for the development of sophisticated biological systems. PMID:21850228

Automatic compilation from high-level biologically-oriented programming language to genetic regulatory networks.

PubMed

Beal, Jacob; Lu, Ting; Weiss, Ron

2011-01-01

The field of synthetic biology promises to revolutionize our ability to engineer biological systems, providing important benefits for a variety of applications. Recent advances in DNA synthesis and automated DNA assembly technologies suggest that it is now possible to construct synthetic systems of significant complexity. However, while a variety of novel genetic devices and small engineered gene networks have been successfully demonstrated, the regulatory complexity of synthetic systems that have been reported recently has somewhat plateaued due to a variety of factors, including the complexity of biology itself and the lag in our ability to design and optimize sophisticated biological circuitry. To address the gap between DNA synthesis and circuit design capabilities, we present a platform that enables synthetic biologists to express desired behavior using a convenient high-level biologically-oriented programming language, Proto. The high level specification is compiled, using a regulatory motif based mechanism, to a gene network, optimized, and then converted to a computational simulation for numerical verification. Through several example programs we illustrate the automated process of biological system design with our platform, and show that our compiler optimizations can yield significant reductions in the number of genes (~ 50%) and latency of the optimized engineered gene networks. Our platform provides a convenient and accessible tool for the automated design of sophisticated synthetic biological systems, bridging an important gap between DNA synthesis and circuit design capabilities. Our platform is user-friendly and features biologically relevant compiler optimizations, providing an important foundation for the development of sophisticated biological systems.

Mössbauer effect study of iron(III) inidazolidine nitroxyl-free radical ligand complex

NASA Astrophysics Data System (ADS)

Mulaba, A.; Kiremire, E.; Pollak, H.; Boeyens, J.

1999-09-01

A new complex, [Fe(acac)L2], bearing inidazolidine nitroxyl-free radical ligand (L-) was recently synthesised for biological studies. It proved to be biologically active against African sleeping sickness, plasmodium falciparum (malaria), leishmaniasis and chaga disease causative agents. Three ESR well resolved peaks indicated the presence of a free (unpaired) and chemically active electron in the complex. The structural complex ferric iron was found at the centre of two electric gradient whose the biggest is suggested to be initiated by the unpaired charge. No distinction between different cis isomers could be made.

CORUM: the comprehensive resource of mammalian protein complexes

PubMed Central

Ruepp, Andreas; Brauner, Barbara; Dunger-Kaltenbach, Irmtraud; Frishman, Goar; Montrone, Corinna; Stransky, Michael; Waegele, Brigitte; Schmidt, Thorsten; Doudieu, Octave Noubibou; Stümpflen, Volker; Mewes, H. Werner

2008-01-01

Protein complexes are key molecular entities that integrate multiple gene products to perform cellular functions. The CORUM (http://mips.gsf.de/genre/proj/corum/index.html) database is a collection of experimentally verified mammalian protein complexes. Information is manually derived by critical reading of the scientific literature from expert annotators. Information about protein complexes includes protein complex names, subunits, literature references as well as the function of the complexes. For functional annotation, we use the FunCat catalogue that enables to organize the protein complex space into biologically meaningful subsets. The database contains more than 1750 protein complexes that are built from 2400 different genes, thus representing 12% of the protein-coding genes in human. A web-based system is available to query, view and download the data. CORUM provides a comprehensive dataset of protein complexes for discoveries in systems biology, analyses of protein networks and protein complex-associated diseases. Comparable to the MIPS reference dataset of protein complexes from yeast, CORUM intends to serve as a reference for mammalian protein complexes. PMID:17965090

Heparin functionalization increases retention of TGF-β2 and GDF5 on biphasic silk fibroin scaffolds for tendon/ligament-to-bone tissue engineering.

PubMed

Font Tellado, Sònia; Chiera, Silvia; Bonani, Walter; Poh, Patrina S P; Migliaresi, Claudio; Motta, Antonella; Balmayor, Elizabeth R; van Griensven, Martijn

2018-05-01

The tendon/ligament-to-bone transition (enthesis) is a highly specialized interphase tissue with structural gradients of extracellular matrix composition, collagen molecule alignment and mineralization. These structural features are essential for enthesis function, but are often not regenerated after injury. Tissue engineering is a promising strategy for enthesis repair. Engineering of complex tissue interphases such as the enthesis is likely to require a combination of biophysical, biological and chemical cues to achieve functional tissue regeneration. In this study, we cultured human primary adipose-derived mesenchymal stem cells (AdMCs) on biphasic silk fibroin scaffolds with integrated anisotropic (tendon/ligament-like) and isotropic (bone/cartilage like) pore alignment. We functionalized those scaffolds with heparin and explored their ability to deliver transforming growth factor β2 (TGF-β2) and growth/differentiation factor 5 (GDF5). Heparin functionalization increased the amount of TGF-β2 and GDF5 remaining attached to the scaffold matrix and resulted in biological effects at low growth factor doses. We analyzed the combined impact of pore alignment and growth factors on AdMSCs. TGF-β2 and pore anisotropy synergistically increased the expression of tendon/ligament markers and collagen I protein content. In addition, the combined delivery of TGF-β2 and GDF5 enhanced the expression of cartilage markers and collagen II protein content on substrates with isotropic porosity, whereas enthesis markers were enhanced in areas of mixed anisotropic/isotropic porosity. Altogether, the data obtained in this study improves current understanding on the combined effects of biological and structural cues on stem cell fate and presents a promising strategy for tendon/ligament-to-bone regeneration. Regeneration of the tendon/ligament-to-bone interphase (enthesis) is of significance in the repair of ruptured tendons/ligaments to bone to improve implant integration and clinical outcome. This study proposes a novel approach for enthesis regeneration based on a biomimetic and integrated tendon/ligament-to-bone construct, stem cells and heparin-based delivery of growth factors. We show that heparin can keep growth factors local and biologically active at low doses, which is critical to avoid supraphysiological doses and associated side effects. In addition, we identify synergistic effects of biological (growth factors) and structural (pore alignment) cues on stem cells. These results improve current understanding on the combined impact of biological and structural cues on the multi-lineage differentiation capacity of stem cells for regenerating complex tissue interphases. Copyright © 2018 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.

Short-term bioassay of complex organic mixtures. Part II. Mutagenicity testing

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

Epler, J.L.; Clark, B.R.; Ho, C.

1978-01-01

The feasibility of using short-term mutagenicity assays to predict the potential biohazard of various crude and complex test materials has been examined in a coupled chemical and biological approach. The principal focus of the research has involved the preliminary chemical characterizatiion and preparation for bioassay, followed by testing in the Salmonella histidine reversion assay system. The mutagenicity tests are intended to act as predictors of profound long-range health effects such as mutagenesis and/or carcinogenesis; act as a mechanism to rapidly isolate and identify a hazardous agent in a complex mixture; and function as a measure of biological activity correlating baselinemore » data with changes in process conditions. Since complex mixtures can be fractionated and approached in these short-term assays, information reflecting on the actual compounds responsible for the biological effect may be accumulated.« less

Aerobic metabolism underlies complexity and capacity

PubMed Central

Koch, Lauren G; Britton, Steven L

2008-01-01

The evolution of biological complexity beyond single-celled organisms was linked temporally with the development of an oxygen atmosphere. Functionally, this linkage can be attributed to oxygen ranking high in both abundance and electronegativity amongst the stable elements of the universe. That is, reduction of oxygen provides for close to the largest possible transfer of energy for each electron transfer reaction. This suggests the general hypothesis that the steep thermodynamic gradient of an oxygen environment was permissive for the development of multicellular complexity. A corollary of this hypothesis is that aerobic metabolism underwrites complex biological function mechanistically at all levels of organization. The strong contemporary functional association of aerobic metabolism with both physical capacity and health is presumably a product of the integral role of oxygen in our evolutionary history. Here we provide arguments from thermodynamics, evolution, metabolic network analysis, clinical observations and animal models that are in accord with the centrality of oxygen in biology. PMID:17947307

[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.

MEAT SCIENCE AND MUSCLE BIOLOGY SYMPOSIUM--role of satellite cells in anabolic steroid-induced muscle growth in feedlot steers.

PubMed

Dayton, W R; White, M E

2014-01-01

Both androgenic and estrogenic steroids are widely used as growth promoters in feedlot steers because they significantly enhance feed efficiency, rate of gain, and muscle growth. However, despite their widespread use relatively little is known about the biological mechanism by which androgenic and estrogenic steroids enhance rate and efficiency of muscle growth in cattle. Treatment of feedlot steers with a combined estradiol (E2) and trenbolone acetate (TBA) implant results in an increased number of muscle satellite cells, increased expression of IGF-1 mRNA in muscle tissue, and increased levels of circulating IGF-1. Similarly, treatment of bovine satellite cell (BSC) cultures with either TBA or E2 results in increased expression of IGF-1 mRNA, increased rates of proliferation and protein synthesis, and decreased rates of protein degradation. Effects of E2 on BSC are mediated at least in part through the classical E2 receptor, estrogen receptor-α (ESR1), the IGF-1 receptor (IGFR1), and the G protein-coupled estrogen receptor-1 (GPER-1), formerly known as G protein-coupled receptor-30 (GPR30). The effects of TBA appear to be primarily mediated through the androgen receptor. Based on current research results, it is becoming clear that anabolic steroid-enhanced bovine muscle growth involves a complex interaction of numerous pathways and receptors. Consequently, additional in vivo and in vitro studies are necessary to understand the mechanisms involved in this complex process. The fundamental information generated by this research will help in developing future, safe, and effective strategies to increase rate and efficiency of muscle growth in beef cattle.

Coastal habitat and biological community response to dam removal on the Elwha River

USGS Publications Warehouse

Foley, Melissa M.; Warrick, Jonathan A.; Ritchie, Andrew C.; Stevens, Andrew; Shafroth, Patrick B.; Duda, Jeff; Beirne, Matthew M.; Paradis, Rebecca; Gelfenbaum, Guy R.; McCoy, Randall; Cubley, Erin S.

2017-01-01

Habitat diversity and heterogeneity play a fundamental role in structuring ecological communities. Dam emplacement and removal can fundamentally alter habitat characteristics, which in turn can affect associated biological communities. Beginning in the early 1900s, the Elwha and Glines Canyon dams in Washington, USA, withheld an estimated 30 million tonnes of sediment from river, coastal, and nearshore habitats. During the staged removal of these dams—the largest dam removal project in history—over 14 million tonnes of sediment were released from the former reservoirs. Our interdisciplinary study in coastal habitats—the first of its kind—shows how the physical changes to the river delta and estuary habitats during dam removal were linked to responses in biological communities. Sediment released during dam removal resulted in over a meter of sedimentation in the estuary and over 400 m of expansion of the river mouth delta landform. These changes increased the amount of supratidal and intertidal habitat, but also reduced the influx of seawater into the pre-removal estuary complex. The effects of these geomorphic and hydrologic changes cascaded to biological systems, reducing the abundance of macroinvertebrates and fish in the estuary and shifting community composition from brackish to freshwater-dominated species. Vegetation did not significantly change on the delta, but pioneer vegetation increased during dam removal, coinciding with the addition of newly available habitat. Understanding how coastal habitats respond to large-scale human stressors—and in some cases the removal of those stressors—is increasingly important as human uses and restoration activities increase in these habitats.

Biomass recalcitrance: a multi-scale, multi-factor, and conversion-specific property.

PubMed

McCann, Maureen C; Carpita, Nicholas C

2015-07-01

Recalcitrance of plant biomass to enzymatic hydrolysis for biofuel production is thought to be a property conferred by lignin or lignin-carbohydrate complexes. However, chemical catalytic and thermochemical conversion pathways, either alone or in combination with biochemical and fermentative pathways, now provide avenues to utilize lignin and to expand the product range beyond ethanol or butanol. To capture all of the carbon in renewable biomass, both lignin-derived aromatics and polysaccharide-derived sugars need to be transformed by catalysts to liquid hydrocarbons and high-value co-products. We offer a new definition of recalcitrance as those features of biomass which disproportionately increase energy requirements in conversion processes, increase the cost and complexity of operations in the biorefinery, and/or reduce the recovery of biomass carbon into desired products. The application of novel processing technologies applied to biomass reveal new determinants of recalcitrance that comprise a broad range of molecular, nanoscale, and macroscale factors. Sampling natural genetic diversity within a species, transgenic approaches, and synthetic biology approaches are all strategies that can be used to select biomass for reduced recalcitrance in various pretreatments and conversion pathways. © The Author 2015. Published by Oxford University Press on behalf of the Society for Experimental Biology. All rights reserved. For permissions, please email: journals.permissions@oup.com.

Dynamic Self-Stiffening in Liquid Crystal Elastomers

PubMed Central

Agrawal, Aditya; Chipara, Alin C.; Shamoo, Yousif; Patra, Prabir K.; Carey, Brent J.; Ajayan, Pulickel M.; Chapman, Walter G.

2013-01-01

Biological tissues have the remarkable ability to remodel and repair in response to disease, injury, and mechanical stresses. Synthetic materials lack the complexity of biological tissues, and man-made materials which respond to external stresses through a permanent increase in stiffness are uncommon. Here, we report that polydomain nematic liquid crystal elastomers increase in stiffness by up to 90% when subjected to a low-amplitude (5%), repetitive (dynamic) compression. Elastomer stiffening is influenced by liquid crystal content, the presence of a nematic liquid crystal phase and the use of a dynamic as opposed to static deformation. Through rheological and X-ray diffraction measurements, stiffening can be attributed to a nematic director which rotates in response to dynamic compression. Stiffening under dynamic compression has not been previously observed in liquid crystal elastomers and may be useful for the development of self-healing materials or for the development of biocompatible, adaptive materials for tissue replacement. PMID:23612280

Use of dispersion modelling for Environmental Impact Assessment of biological air pollution from composting: Progress, problems and prospects.

PubMed

Douglas, P; Hayes, E T; Williams, W B; Tyrrel, S F; Kinnersley, R P; Walsh, K; O'Driscoll, M; Longhurst, P J; Pollard, S J T; Drew, G H

2017-12-01

With the increase in composting asa sustainable waste management option, biological air pollution (bioaerosols) from composting facilities have become a cause of increasing concern due to their potential health impacts. Estimating community exposure to bioaerosols is problematic due to limitations in current monitoring methods. Atmospheric dispersion modelling can be used to estimate exposure concentrations, however several issues arise from the lack of appropriate bioaerosol data to use as inputs into models, and the complexity of the emission sources at composting facilities. This paper analyses current progress in using dispersion models for bioaerosols, examines the remaining problems and provides recommendations for future prospects in this area. A key finding is the urgent need for guidance for model users to ensure consistent bioaerosol modelling practices. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

On the use of ultracentrifugal devices for routine sample preparation in biomolecular magic-angle-spinning NMR

PubMed Central

Mandal, Abhishek; Boatz, Jennifer C.; Wheeler, Travis; van der Wel, Patrick C. A.

2017-01-01

A number of recent advances in the field of magic-angle-spinning (MAS) solid-state NMR have enabled its application to a range of biological systems of ever increasing complexity. To retain biological relevance, these samples are increasingly studied in a hydrated state. At the same time, experimental feasibility requires the sample preparation process to attain a high sample concentration within the final MAS rotor. We discuss these considerations, and how they have led to a number of different approaches to MAS NMR sample preparation. We describe our experience of how custom-made (or commercially available) ultracentrifugal devices can facilitate a simple, fast and reliable sample preparation process. A number of groups have since adopted such tools, in some cases to prepare samples for sedimentation-style MAS NMR experiments. Here we argue for a more widespread adoption of their use for routine MAS NMR sample preparation. PMID:28229262

Ocean acidification disrupts induced defences in the intertidal gastropod Littorina littorea.

PubMed

Bibby, Ruth; Cleall-Harding, Polly; Rundle, Simon; Widdicombe, Steve; Spicer, John

2007-12-22

Carbon dioxide-induced ocean acidification is predicted to have major implications for marine life, but the research focus to date has been on direct effects. We demonstrate that acidified seawater can have indirect biological effects by disrupting the capability of organisms to express induced defences, hence, increasing their vulnerability to predation. The intertidal gastropod Littorina littorea produced thicker shells in the presence of predation (crab) cues but this response was disrupted at low seawater pH. This response was accompanied by a marked depression in metabolic rate (hypometabolism) under the joint stress of high predation risk and reduced pH. However, snails in this treatment apparently compensated for a lack of morphological defence, by increasing their avoidance behaviour, which, in turn, could affect their interactions with other organisms. Together, these findings suggest that biological effects from ocean acidification may be complex and extend beyond simple direct effects.

Chromatin immunoprecipitation with fixed animal tissues and preparation for high-throughput sequencing.

PubMed

Cotney, Justin L; Noonan, James P

2015-02-02

Chromatin immunoprecipitation coupled with high-throughput sequencing (ChIP-Seq) is a powerful method used to identify genome-wide binding patterns of transcription factors and distribution of various histone modifications associated with different chromatin states. In most published studies, ChIP-Seq has been performed on cultured cells grown under controlled conditions, allowing generation of large amounts of material in a homogeneous biological state. Although such studies have provided great insight into the dynamic landscapes of animal genomes, they do not allow the examination of transcription factor binding and chromatin states in adult tissues, developing embryonic structures, or tumors. Such knowledge is critical to understanding the information required to create and maintain a complex biological tissue and to identify noncoding regions of the genome directly involved in tissues affected by complex diseases such as autism. Studying these tissue types with ChIP-Seq can be challenging due to the limited availability of tissues and the lack of complex biological states able to be achieved in culture. These inherent differences require alterations of standard cross-linking and chromatin extraction typically used in cell culture. Here we describe a general approach for using small amounts of animal tissue to perform ChIP-Seq directed at histone modifications and transcription factors. Tissue is homogenized before treatment with formaldehyde to ensure proper cross-linking, and a two-step nuclear isolation is performed to increase extraction of soluble chromatin. Small amounts of soluble chromatin are then used for immunoprecipitation (IP) and prepared for multiplexed high-throughput sequencing. © 2015 Cold Spring Harbor Laboratory Press.

The importance of extracellular speciation and corrosion of copper nanoparticles on lung cell membrane integrity.

PubMed

Hedberg, Jonas; Karlsson, Hanna L; Hedberg, Yolanda; Blomberg, Eva; Odnevall Wallinder, Inger

2016-05-01

Copper nanoparticles (Cu NPs) are increasingly used in various biologically relevant applications and products, e.g., due to their antimicrobial and catalytic properties. This inevitably demands for an improved understanding on their interactions and potential toxic effects on humans. The aim of this study was to investigate the corrosion of copper nanoparticles in various biological media and to elucidate the speciation of released copper in solution. Furthermore, reactive oxygen species (ROS) generation and lung cell (A549 type II) membrane damage induced by Cu NPs in the various media were studied. The used biological media of different complexity are of relevance for nanotoxicological studies: Dulbecco's modified eagle medium (DMEM), DMEM(+) (includes fetal bovine serum), phosphate buffered saline (PBS), and PBS+histidine. The results show that both copper release and corrosion are enhanced in DMEM(+), DMEM, and PBS+histidine compared with PBS alone. Speciation results show that essentially no free copper ions are present in the released fraction of Cu NPs in neither DMEM(+), DMEM nor histidine, while labile Cu complexes form in PBS. The Cu NPs were substantially more membrane reactive in PBS compared to the other media and the NPs caused larger effects compared to the same mass of Cu ions. Similarly, the Cu NPs caused much more ROS generation compared to the released fraction only. Taken together, the results suggest that membrane damage and ROS formation are stronger induced by Cu NPs and by free or labile Cu ions/complexes compared with Cu bound to biomolecules. Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.

On the Edge of Mathematics and Biology Integration: Improving Quantitative Skills in Undergraduate Biology Education

ERIC Educational Resources Information Center

Feser, Jason; Vasaly, Helen; Herrera, Jose

2013-01-01

In this paper, the authors describe how two institutions are helping their undergraduate biology students build quantitative competencies. Incorporation of quantitative skills and reasoning in biology are framed through a discussion of two cases that both concern introductory biology courses, but differ in the complexity of the mathematics and the…

MIMO: an efficient tool for molecular interaction maps overlap

PubMed Central

2013-01-01

Background Molecular pathways represent an ensemble of interactions occurring among molecules within the cell and between cells. The identification of similarities between molecular pathways across organisms and functions has a critical role in understanding complex biological processes. For the inference of such novel information, the comparison of molecular pathways requires to account for imperfect matches (flexibility) and to efficiently handle complex network topologies. To date, these characteristics are only partially available in tools designed to compare molecular interaction maps. Results Our approach MIMO (Molecular Interaction Maps Overlap) addresses the first problem by allowing the introduction of gaps and mismatches between query and template pathways and permits -when necessary- supervised queries incorporating a priori biological information. It then addresses the second issue by relying directly on the rich graph topology described in the Systems Biology Markup Language (SBML) standard, and uses multidigraphs to efficiently handle multiple queries on biological graph databases. The algorithm has been here successfully used to highlight the contact point between various human pathways in the Reactome database. Conclusions MIMO offers a flexible and efficient graph-matching tool for comparing complex biological pathways. PMID:23672344

Phase-Contrast versus Off-Axis Illumination: Is a More Complex Microscope Always More Powerful?

ERIC Educational Resources Information Center

Hostounsky, Zdenek; Pelc, Radek

2007-01-01

In this article, a practical demonstration suitable for any biology college classroom is presented. With the examples of a complex biological specimen (slug's radula) and a simple reference specimen (electron microscopical grid imprint in gelatin), both of which can be easily prepared, the capabilities of two imaging modes commonly used in optical…